Background/Purpose: Over the last two decades, malaria has remained a major worldwide public health concern, especially in the developing countries leading to high morbidity and mortality among children. Nigeria is the world most burdened malaria endemic nation, contributing more than a quarter of global malaria cases. This study determined the prevalence of malaria among children 6-59 months in Nigeria, and the effects of individual and contextual factors. Methods: The study utilized data from 2018 Nigeria Demographic and Health Survey (NDHS) involving a weighted sample size of 10,185 children who were tested for malaria using rapid diagnostic test (RDT). Given the hierarchical structure of the data set, such that children at level-1 are nested in community at level-2, and nested in states and Federal Capital Territory (FCT) at level-3, multilevel mixed effect logistic regression models were used for the analysis. Results: The proportion of children 6-59 months of age in Nigeria that had malaria fever positive as assessed by RDTs was 35.5% (3,418/10185), (CI: 33.9-37.1). Kebbi State had the highest proportion of children 6-59 months who were malaria positive, 77.6%, (CI: 70.2-83.5), followed by Katsina State, 55.5%, (CI: 47.7-63.1). The Federal Capital Territory (FCT), Abuja had the proportion of 29.6%, (CI: 21.6-39.0), malaria positive children of 6-59 months of age. Children between the age of 48 and 59 months were 2.68 times more likely to have malaria fever than children 6-11 months of age (AOR=2.68, 95% CI: 2.03-3.54). Also, children from the rural area (AOR= 2.12, 95% CI: 1.75-2.57), were more likely to suffer from malaria infection compare with children from urban area. Conclusion: The study identified some individual and contextual predictors of malaria among children in Nigeria. These factors are areas that need to be considered for policy designs and implementations toward control and total elimination of malaria-related morbidity and mortality among children in Nigeria.

Background/Purpose: In recent times, Sub-Sahara Africa (SSA) had been rated by the World Health Organization, (WHO), as the most malaria endemic region in the world. Evidence synthesis of the risk factors associated with malaria among children aged under-five in SSA is urgently needed. This would help to inform decisions that policy makers and executors in the region need to make for the effective distribution of scare palliative resources to curb the spread of the illness. This scoping review is aimed to identify studies that have used multivariate classical regression analysis to determine risk factors associated with malaria among children under-five years old in SSA. Methods/Design: The search terms followed PICOTS, (Population, Intervention, Comparator, Outcome, Timing, Setting), and were used in searching through the following databases: PubMed, MEDLINE, Web of Science, Cumulative Index of Nursing and Allied Health Literature (CINAHL), Scopus, and MeasureDHS. The databases were searched for published articles from January 1990 to December 2020. Results: Among the 1154 studies identified, only thirteen (13) studies met the study’s inclusion/exclusion criteria. Narrative syntheses were performed on the selected papers to synchronise the various risk factors identified. Factors ranging from child-related, (age, birth order and use of bed net), parental/household-related, (maternal age and education status, household wealth index) and community-related variables, (community wealth status, free bed net distribution), were some of the identified significant risk factors. Conclusion: It is timely to have a synthesis of risk factors that influence the malaria status of children under-five in SSA. The outcome of the review will increase the knowledge of the epidemiology of morbidity that will form the basis for designing efficient and cost-effective distribution of palliatives and controls of malaria in SSA.

Background/Purpose: Multimorbidity of malaria, anaemia, and malnutrition (MAMM) is a condition in which an individual cohabits with two or more of these health outcomes and is becoming an emergent public health concern in sub-Saharan African countries. The independent associations of a child’s demographic variables and socioeconomic disparities with a child’s health outcomes have been established in literature. However, the effects of the intersection of these factors on MAMM, while accounting for other covariates have not been studied. Therefore, this study aimed to determine how children’s sex, age and socioeconomic status interact to explain the variations in MAMM among children aged 6-59 months in Nigeria. Methods: Data from the 2018 Nigeria Demographic and Health Survey and the 2018 National Human Development Report (NHDR) were used. The study includes weighted samples of 10,184 children aged 6-59 months in Nigeria. A three-level multilevel mixed effect ordinal logistic regression model such that individual characteristics at level 1 are nested in communities at level 2 and nested in states at level 3 was used. Subsequently, predictive probability charts and average adjusted probability tables were used to interpret the intersectional effects. Five models were created in this scenario. Model 1 is the interaction between the child's sex and wealth status; model 2, child's sex and age; model 3 is between child's age and wealth status; model 4 has the three 2-way interactions of child's sex, age, and household wealth status, and model 5 includes model 4 and the 3-way interactions between a child's sex, age, and wealth quintiles. Results: The prevalence of children with ‘none of the three diseases’ outcomes was 17.3% (1767/10,184), while, 34.4% (3499/10,184) had ‘only one of the diseases’, and 48.3% (4,918/10,184) cohabit with ‘two or more’ of MAMM. However, in the multivariate analyses, model 3 was the best fit compared with other models, so, that the two-way interaction effects of a child's age and wealth status are significant predictors in the model. Children aged 36-47 months living in the poorest households have the probability of 0.11, 0.18, and 0.32 of contracting MAMM above the probability of children of the same age and live in the middle, more prosperous and richest households, respectively, while all other covariates are held constant. Thus, the variation in MAMM over a child's age differs depending on the household wealth quintile. In other words, as the children grow older, variations in MAMM become more evident between the rich and the poor household. Conclusion: Therefore, it is recommended that policies that are geared toward economic redistribution will help bridged the disparities observed in multiple diseases among children aged 6-59 months in Nigeria

Background: Colorectal cancer (CRC) patients experienced multiple chemotoxicity affecting treatment compliance, survival, and quality of life (QOL). Prior research shows clinician-reported chemotoxicity (i.e., grading scales or diagnostic codes) predicts rehospitalization and cancer survival. However, a comprehensive synthesis of clinician-reported chemotoxicity is still lacking. Objectives: We conducted a systematic review and meta-analysis to determine the chemotoxicity's prevalence and risk factors in CRC. Methods: A systematic search from 2009 to 2024 yielded 30 studies for review, with 25 included in the meta-analysis. Results: Pooled prevalences of overall, non-hematological, and hematological moderate-to-severe toxicities were 45.7%, 39.2%, and 25.3%, respectively. The most common clinician-reported chemotoxicities were gastrointestinal (GI) toxicity (22.9%) and neuropathy or neutropenia (17.9%). Significant risk factors at baseline were malnutritional status, frailty, impaired immune or hepato-renal functions, short telomere lengths, low gut lactobacillus levels, age, female sex, aggressive chemotherapy, and low QOL. Age was associated with neutropenia (β: -1.44) and GI toxicity (β:1.85) (Ps 65 y.o.) had higher prevalences of overall (OR: 1.14) and GI (OR: 1.65) toxicities, but a lower prevalence of neutropenia (OR: 0.65) than younger adults (Ps

Space-borne Synthetic Aperture Radar (SAR) Interferometry (InSAR) is now a key geophysical tool for surface deformation studies. The European Commission’s Sentinel-1 Constellation began acquiring data systematically in late 2014. The data, which are free and open access, have global coverage at moderate resolution with a 6 or 12-day revisit, enabling researchers to investigate large-scale surface deformation systematically through time. However, full exploitation of the potential of Sentinel-1 requires specific processing approaches as well as the efficient use of modern computing and data storage facilities. Here we present LiCSAR, an operational system built for large-scale interferometric processing of Sentinel-1 data. LiCSAR is designed to automatically produce geocoded wrapped and unwrapped interferograms and coherence estimates, for large regions, at 0.001° resolution (WGS-84 system). The products are continuously updated in a frequency depending on prioritised regions (monthly, weekly or live update strategy). The products are open and freely accessible and downloadable through an online portal. We describe the algorithms, processing, and storage solutions implemented in LiCSAR, and show several case studies that use LiCSAR products to measure tectonic and volcanic deformation. We aim to accelerate the uptake of InSAR data by researchers as well as non-expert users by mass producing interferograms and derived products.

In this paper, we propose an imagined speech-based brain wave pattern recognition using deep learning. Multiple features were extracted concurrently from eight-channel Electroencephalography (EEG) signals. To obtain classifiable EEG data with fewer number of sensors, we placed the EEG sensors on carefully selected spots on the scalp. To decrease the dimensions and complexity of the EEG dataset and to avoid overfitting during the deep learning algorithm, we utilized the wavelet scattering transformation. A low-cost 8-channel EEG headset was used with MATLAB 2023a to acquire the EEG data. The Long-Short Term Memory Recurrent Neural Network (LSTM-RNN) was used to decode the identified EEG signals into four audio commands: Up, Down, Left, and Right. Wavelet scattering transformation was applied to extract the most stable features by passing the EEG dataset through a series of filtration processes. Filtration has been implemented for each individual command in the EEG datasets. The proposed imagined speech-based brain wave pattern recognition approach achieved a 92.50% overall classification accuracy. This accuracy is promising for designing a trustworthy imagined speech-based Brain-Computer Interface (BCI) future real-time systems. For better evaluation of the classification performance, other metrics were considered, and we obtained 92.74%, 92.50% and 92.62% for precision, recall, and F1-score, respectively.

Despite ample warning and significant lead time, global society has not acted sufficiently to combat climate change, and global carbon dioxide emissions are now about 60% higher today than in 1990 [1]. This paper uses marine fisheries as an analog model to compare with the many similar management issues faced with global climate change. Both marine fisheries and global climate change are complex systems that have similar properties that make management very difficult. A simple fishery prototype model is used to educate citizens about similar issues of dynamic complexity found in climate change models. We highlight how our slow reaction time to global climate change can be thought of as a mismatch between our cognitive abilities and the nature of global collective problems. Understanding the history and system structure of marine fisheries can provide insight into managing global climate change. We suggest ways to improve communication between science and citizens for updating mental models and changing climate policy.

Background. Metronidazole treats obligate anaerobic bacterial and protozoal infections, with an elimination half-life of around eight hours. The long elimination half-life, the favorable ratio of steady-state serum levels to minimum inhibitory concentration, and the presence of active metabolites lead to consideration of metronidazole use at 12-hour dosage intervals. This systematic review aimed to compare the clinical outcomes of twice-daily and thrice-daily metronidazole dosing. Methods. We used the Preferred Reporting Items for Systematic Reviews and Meta-Analyses checklist. PubMed, Scopus, Science Direct, the Cochrane Database of Systematic Reviews, and the Cochrane Central Register of Controlled Trials to systematically identify all relevant studies published up to June 16, 2023. Results. The final analysis included two published retrospective cohort studies; a single site (n = 200) and a multisite study (n = 85) of ‘good’ quality, as measured by the Newcastle-Ottawa scale. The reported baseline characteristics of the 8-hour and 12-hour dosing groups were comparable, and neither study identified significant differences in primary and secondary clinical outcomes. Meta-analysis of the need to escalate antibiotic therapy also showed no statistically significant differences using the Mantel-Haenszel fixed-effect method (95% CI: 47.6% lower to 6.4 times higher risk, p = 0.342) and inverse-variance method (RR: 1.87, 95% CI: 0.52-6.65, p = 0.336). Conclusions. Dosing metronidazole every 12 hours is as effective as every 8-hour dosing for anaerobic infections. Healthcare systems may consider the adoption of every 12-hour metronidazole dosing with continued evaluation of patient outcomes.

Background and Objectives: Clinical trials are a critical step in the development of new medicines and medical devices, testing the efficacy and safety of new treatment regimens. However, if the results of clinical trials are not made public, the evidence base on interventions is incomplete and possibly distorted, which lead to suboptimal treatment choices and negatively affect public health. This study analyses and contrasts the laws and regulations governing clinical trial registration and reporting in China and the United States. Methods: We used desk research to compile, assess and compare current laws, regulations, compliance patterns, and enforcement mechanisms and actions in China and the United States (U.S.). Policy documents were downloaded from Chinese and U.S. government websites. A spreadsheet analysis was utilized for direct comparison. Results: Both China and the U.S. have laws and regulations governing clinical trial registration and reporting. Chinese legislation covers a broader range of trials. In the U.S. trial results must be disclosed to both the national regulator and the public, while Chinese law mandates disclosure to the regulator alone. Cross-country comparisons of regulatory compliance by trial sponsors are impossible due to the opacity of the Chinese data platform. Neither country effectively ensures that all clinical trial results are made public as required by the Declaration of Helsinki and recommended by the WHO. Interpretation: While neither country is perfect, both may be able to learn from each other. There is a major gap in the literature regarding the extent of non-publication of clinical trial results by sponsors operating in China.

Field observations of external wounds associated with two common tree injection methods compared open (plug-less) and sealed (plug) systems in green ash (Fraxinus pennsylvanica Marshall) trees . A wound from any cause within 1.37 meters above the ground was common with 28.8% of all trees. The open system had statistically fewer (p<0.001) trees with at least one wound (11.6% of trees) than the sealed system (47.4% of trees). The open system had fewer (P<0.001) wounds (0.17, 0.04 SE) per tree and a smaller (P<0.001) total wound area (25.5 cm2, 8.7 SE) per tree, compared to the sealed system wounds (1.14, 0.13 SE) per tree and the total wound area (99.7 cm2, 16.2 SE) per tree. The incidence of a tree with a wound(s) within 1.37 m above the ground was 7.2 times more likely with trees treated though the sealed system. Wounds in the sealed system were observed to appear to have a high rate of improper application of plugs, which was associated in 77% of the cases to explain the wounds. Implications of study results are further provided to best protect ash trees, while at the same time reducing the incidence external wounding on ash trees.

Abstract: Peptide pools composed of short amino acid sequences have proven to be versatile tools in various research areas and clinical applications. They are powerful tools for epitope mapping, immunotherapy, and vaccine development. Their importance lies in their ability to map complex protein structures, enabling a comprehensive understanding of immune responses and facilitating the identification of potential therapeutic agents. The application of peptide pools also extends to the field of personalized medicine, offering tailored solutions for diseases such as cancer and infectious diseases. Peptide pools are complex mixtures of immunostimulatory antigens primarily intended for T-cell stimulation. They are commercially available in many different compositions and variants. However, unlike other reagents that consist of only one or a few compounds, peptide pools are highly complex products with limited stability. This makes their quality control a major challenge. Quantitative peptide analysis usually requires sophisticated methods, in most cases isotope-labeled standards and reference materials. None of these are routinely available for these products. Synthesis and purification of all labeled peptides might be required. Usually, this approach would be prohibitively laborious and expensive. Therefore, an approach is needed to provide a practical and feasible method for quality control of peptide pools. With insufficient quality control, the use of such products could lead to incorrect experimental results, which would worsen the well-known reproducibility crisis in the biomedical sciences. Here we propose the use of ultra-high performance liquid chromatography (UHPLC) with two detectors, a standard UV detector (at 214 nm) for quantitative analysis and a high-resolution mass spectrometer (HRMS) for identity confirmation. To be cost-efficient and fast, quantification and identification are performed in one chromatographic run. An optimized protocol is shown, and different peak integration methods are compared and discussed. This work was performed using a peptide pool known as CEF, which consists of 32 peptides derived from cytomegalovirus (CMV), Epstein-Barr virus (EBV) and influenza virus, ranging from 8 to 12 amino acids in length.

There is increasing demand from stakeholders for tools to support outcome-based approaches in environmental management. For such tools to be useful, understanding user requirements is key. In Scotland, UK, stakeholders were engaged in the development of an Environmental Decision Support System (EDSS) to support the management of land and freshwater resources for multiple policy outcomes. A structured participatory engagement process was employed to determine stakeholder requirements, establish development principles to fulfil these requirements and road-test prototypes. The EDSS specification that emerged from this bottom-up process was spatially-explicit, free at the point of use, and touch and mobile device compatible. This application, which is under development, does not closely resemble most existing published EDSS. We suggest that there is a mismatch between the way scientists typically conceptualise EDSS and the kinds of applications that are likely to be useful to decision-makers on the ground. Interactive mobile and web-based geospatial information services have become ubiquitous in our daily lives, but their importance is not reflected in current literature on EDSS. The current focus in environmental management on adaptive, stakeholder-centred strategies based on outcomes offers an opportunity to make better use of these new technologies to aid decision-making processes.

Approximately 240 million people are chronically infected with hepatitis B virus (HBV), despite four decades of an effective HBV vaccine. During chronic infection, HBV forms two distinct templates responsible for viral gene transcription: (1) episomal covalently closed circular (ccc)DNA and (2) host-genome integrated viral templates. Multiple ubiquitous and liver-specific transcription factors are recruited onto these templates and modulate viral gene transcription. This review details the latest developments in antivirals that inhibit HBV gene transcription, and their impact on the stability of viral transcripts. Notably, nuclear receptor agonists exhibit potent inhibition of viral gene transcription from cccDNA, small molecule inhibitors repress HBV X protein-mediated transcription from cccDNA and small interfering RNAs and single-stranded oligonucleotides result in transcript degradation from both cccDNA and integrant templates. These antivirals mediate their effects by reducing viral transcripts abundance, eventually leading to loss of surface antigen expression, and can potentially be added to the arsenal of drugs with demonstrable anti-HBV activity. Thus, these candidates deserve special attention for future repurposing or further development as anti-HBV therapeutics.

The dorsal column nuclei complex (DCN-complex) includes the dorsal column nuclei (DCN, referring to the gracile and cuneate nuclei collectively), external cuneate, X, and Z nuclei, and the median accessory nucleus. The DCN are organised by both somatotopy and modality, and have a diverse range of afferent inputs and projection targets. The functional organisation and connectivity of the DCN implicate them in a variety of sensorimotor functions, beyond their commonly accepted role in processing and transmitting somatosensory information to the thalamus, yet this is largely underappreciated in the literature. To consolidate insights into their sensorimotor functions, this review examines the morphology, organisation, and connectivity of the DCN and their associated nuclei. First, we briefly discuss the receptors, afferent fibres, and pathways involved in conveying tactile and proprioceptive information to the DCN. Next, we review the modality and somatotopic arrangements of the remaining constituents of the DCN-complex. Finally, we examine and discuss the functional implications of the myriad of DCN-complex projection targets throughout the diencephalon, midbrain, and hindbrain, in addition to their modulatory inputs from the cortex. The organisation and connectivity of the DCN-complex suggest that these nuclei should be considered a complex integration and distribution hub for sensorimotor information.

Chronological age represents the greatest risk factor for many life-threatening diseases including neurodegeneration, cancer and cardiovascular disease; ageing also increases susceptibility to infectious disease. Current therapies that effectively tackle individual diseases may have little impact on the overall healthspan of older individuals, who would still be vulnerable to other age-related pathologies. However, recent progress in ageing research has highlighted the accumulation of senescent cells with chronological age as a probable underlying cause of pathological ageing. Cellular senescence is an essentially irreversible proliferation arrest mechanism that has important roles in development, wound healing and preventing cancer, but it may limit tissue function and cause widespread inflammation with age. The serine/threonine kinase mTOR is a regulatory nexus heavily implicated in both ageing and senescence. Excitingly, a growing body of research has highlighted rapamycin and other mTOR inhibitors as promising treatments for a broad spectrum of age-related pathologies, including neurodegeneration, cancer, immunosenescence, osteoporosis, rheumatoid arthritis, age-related blindness, diabetic nephropathy, muscular dystrophy, and cardiovascular disease. In this review, we assess the use of mTOR inhibitors to treat age-related pathologies, discuss possible molecular mechanisms of action where evidence is available, and consider strategies to minimize undesirable side effects. We also emphasize the urgent need for reliable, non-invasive biomarkers of senescence and biological ageing to better monitor the efficacy of any healthy ageing therapy.

Charcot-Marie-Tooth (CMT) syndrome is the most common progressive human motor and sensory peripheral neuropathy. CMT type 1E is a demyelinating neuropathy affecting Schwann cells due to pmp22 mutations, modelized by Trembler-J mice. Curcumin, a natural polyphenol com-pound obtained from turmeric (Curcuma longa), exhibits dose- and time-varying antitumor, antioxidant and neuroprotective properties, however, the neurotherapeutic actions of curcumin still remain elusive. Here, we propose curcumin as a possible natural treatment capable of enhancing cellular detoxification mechanisms, resulting in an improvement of the neurodegenerative Trembler-J phenotype. Using a refined method for obtaining enriched Schwann cell cultures, we evaluated the neurotherapeutic action of low dose curcumin treatment on the PMP22 expression, and on the chaperones (HSF1 and Hsp27) and autophagy/mTOR (HDAC6 and ribosomes) pathways in Trembler-J and wild-type genotypes. In wild-type Schwann cells, the action of cur-cumin resulted in strong stimulation of the chaperone and macroautophagy pathway, whereas the modulation of ribophagy showed a mild effect. However, despite the promising neuroprotective effects for the treatment of neurological diseases, we report (demonstrate?) that the action of cur-cumin in Trembler-J Schwann cells could be impaired due to the irreversible impact of ethanol used as a common curcumin vehicle necessary for administration. These results contribute to expand our still limited understanding of PMP22 biology in neurobiology, and expose the intrinsic lability of the neurodegenerative Trembler-J genotype. Furthermore, they unravel interesting physiological mechanisms of cellular resilience relevant for to the pharmacological treatment of the neurodegenerative Tremble J phenotype with curcumin and ethanol. We conclude that the analysis of the effects of the vehicle itself is an essential and in-escapable step to comprehensibly assess the own effects and full potential of curcumin treatment for therapeutic purposes.

We know that the classical Mittag-Leffler function play an important role as solution of fractional order differential and integral equations. We introduce the j-generalized p - k Mittag-Leffler function. We evaluate the second order differential recurrence relation and four different integral representations and introduce a homogeneous linear differential equation whose one of the solution is the j-generalized p-k Mittag-Leffler function. Also we evaluate the certain relations that exist between j-generalized p - k Mittag-Leffler function and Riemann-Liouville fractional integrals and derivatives. We evaluate Mellin-Barnes integral representation of j-generalized p-k Mittag-Le er Function. The relationship of j-generalized p-k Mittag-Leffler Function with Fox H-Function and Wright hypergeometric function is also establish. we obtained its Euler transform, Laplace Transform and Mellin transform. Finally we derive some particular cases.

The French-Swiss Professor in inductive philosophy Richard Avenarius (1843-1896), the father of empirio-criticism together with Ernst Mach, is one of the most underrated and misunderstood philosophers ever. It mostly depends upon his terminology, which displays an insurmountable difficulty. However, influenced by the most innovative proposals of his times of transition between the idealistic/rationalist legacies and the new Materialism/scientific interpretation of reality – i.e, by cultural evolutionism, linguistics, biomechanics, entropy/energy and, above all, by the newborn experimental psychology-, he produced a complete system of philosophy and innovative methods of investigation of the laws of knowledge. Hints (chunk, scrap, fragments) of his original ideas can be found not only in philosophers of mind after him - such as Gestalt, phenomenalism, behaviourism, functionalism and cybernetics, autopoiesis, dynamical systems theory, embedded/embodied mind, free-energy principle of the brain – but also in recent neuroscientific theories – nervous transduction, electric spikes, cracking of neural code, multisensory integration -. Our aim is to provide the first chronological English summary of his masterpiece, the “Kritik”, to give the possibility to the (almost) totally unaware English speakers to appreciate such a neglected and innovative thinker.

Responses to water stress were measured for sugar maple (Acer saccharum subsp. saccharum Marshall) sources from Oklahoma (Caddo sugar maple), Missouri, Tennessee, Ontario and a black maple (Acer saccharum subsp. nigrum F. Michx.) source from Iowa. Seedling sources were selected for differences in temperature and precipitation of their geographic origins. Seedlings were preconditioned through moist (watered daily) or dry (watered every 4-7 days) cycles and then exposed to prolonged water stress. Dry preconditioned sugar maple seedlings from Oklahoma, Missouri, and Tennessee, sources from warmer and/or drier climates with greater relative evapotranspiration potentials, declined less rapidly in net photosynthesis, stomatal conductance, and water use efficiency (WUE) as water stress increased than dry preconditioned seedlings from Ontario and Iowa having origins in cooler, moister climates. Under imposed water stress the Ontario and Iowa sourced seedlings increased their root to shoot ratios and decreased their specific leaf area, mechanisms for drought avoidance. However, no corresponding changes in these values occurred for Oklahoma, Missouri, and Tennessee sources. Results from this study suggest greater tolerance of water stress in the Oklahoma, Missouri and Tennessee ecotypes from the western and southern range of sugar maple resulted primarily with WUE rather than other water stress coping mechanisms.

In this research paper, design and development of pyramidal horn antenna for J-band application is reported. It is particularly designed for 17 dB gain and half beam width about 25 degrees at 6.93 GHz. Horn aperture, horn axial length and distance from the throat of the antenna to aperture are the main design constraints which are calculated and used for the antenna design and simulation. Beam width in E-plane and H-plane horn is calculated and it is 19.18 dB and 22.86 dB respectively. The reported antenna design shows good performance for J-band in radiometry, satellite, and radar applications.

Urban lakes, especially those of natural origin, provide ecosystem services, recreation being one of the most important and highly valued by the city dwellers. Fulfilling the needs of city residents to relax and have contact with nature has become a priority in urbanized areas and has been proved to positively affect people’s health and well-being. The recreational potential of water bodies was identified to be most important aspect of ecosystem services to the residents of the neighboring areas. An assessment of recreational ecosystem services (RES) provisioning to society based on the real time spent by the citizens and housing values in the rural-urban gradient revealed that the economic benefits of lakes differ in urbanized, suburban and rural landscapes. The growth of cities has led to an increased population density in the surroundings of ecologically valuable areas, resulting in higher pressure from visitors seeking recreational areas. Along with urbanization, the impoverishment of ecosystem functions takes place, limiting their capability to provide ecosystem services. In this work provisioning of recreational ecosystem services of 28 floodplain lakes located along the urban-rural gradient of the Warsaw agglomeration was assessed. The relationship between the ecological value of the water bodies, measured using naturalness indices, and the recreational ecosystem services they can provide was assessed. The results showed that the floodplain lakes located along the urban-rural gradient are of a great importance to the citizens due to their recreational potential. The provisioning of recreational ecosystem services is poorly connected with the ecological characteristics of the floodplain lakes. Only hemeroby, was significantly correlated with provisioning, and there was no relationship with factors such as naturalness of vegetation or water quality, demonstrating that public preference was not generally influenced by high ecological quality. These data should be available to potential buyers and be integrated in spatial planning management plans in order to shape future housing policy.

The distribution of tiny sensors over a specific area was first proposed in the late 1990s as a concept known as Smart Dust. Several efforts focused primarily on computing and networking capabilities but quickly ran into problems related to power supply, cost, data transmission, and environmental pollution. To overcome these limitations, we propose using paper-based (confetti-like) chemosensors that exploit the inherent selectivity of chemical reagents, such as colorimetric indicators. In this work, cheap and biodegradable passive sensors made from cellulose could successfully indicate the presence of hazardous chemicals, e.g., strong acids, by a significant color change. A conventional color digital camera attached to a drone could easily detect this from a safe distance. The collected data was processed to define the hazardous area. Our work presents a combination of the smart dust concept, chemosensing, paper-based sensor technology, and low-cost drones for flexible, sensitive, economical, and rapid detection of hazardous chemicals in high-risk scenarios.

The affinity constant, also known as the equilibrium constant, binding constant, equilibrium association constant, or the reciprocal value, the equilibrium dissociation constant (K_d), can be considered as one of the most important characteristics for any antibody-antigen pair. Many methods based on different technologies have been proposed and used to determine this value. However, since a very large number of publications and commercial datasheets do not include this information, significant obstacles in performing such measurements seem to exist. In other cases where such data are reported, the results have often proved to be unreliable. This situation may indicate that most of the technologies available today require a high level of expertise that does not seem to be available in many laboratories. In this paper, we present a simple approach based on standard immunoassay technology that is easy and quick to perform. It relies on the effect that the molar IC₅₀ approaches the K_d value in the case of infinitely small concentrations of the reagent concentrations. A two-dimensional dilution of the reagents leads to an asymptotic convergence to K_d. The approach has some similarity to the well-known checkerboard titration used for the optimization of immunoassays. A well-known antibody against the FLAG peptide, clone M2, was used as a model system and the results were compared with other methods. This approach could be used in any case where a competitive assay is available or can be developed. The determination of an affinity constant should belong to the crucial parameters in any quality control of antibody-related products and assays and should be mandatory in papers using immunochemical protocols.

Chronic pain is a serious health concern and potentially debilitating condition, leading to anxiety, depression, reduced productivity and functionality, and poor quality of life. This condition can be even more detrimental and incapacitating in the pediatric patient population. In low and middle income countries (LMICs), pain services are inadequate or unavailable, leaving most of the world's pediatric population with chronic pain untreated. Many of these children in LMICs are suffering without treatment, and often die in pain. Awareness and advocacy for this population must be prioritized. We reviewed the available literature on the chronic pediatric pain burden in LMICs, barriers to treatments, and current efforts to treat these patients.

Polybrominated diphenyl ethers (PBDE) are a group of flame retardants used in a variety of artificial materials. Despite phasing out in most industrial countries, they persist in the environment and human tissues due to their persistence, lipophilicity, and bioaccumulation. Populational and experimental studies demonstrate male reproductive toxicity of PBDEs including increased incidence of genital malformations (hypospadias and cryptorchidism), altered weight of testes and other reproductive tissues, altered testes histology and transcriptome, decreased sperm production and sperm quality, altered epigenetic regulation of developmental genes in spermatozoa and altered secretion of reproductive hormones. A broad range of mechanistic hypotheses of PBDE reproductive toxicity has been suggested. Among these hypotheses, oxidative stress, disruption of estrogenic signaling, and mitochondria disruption are affected by PBDE concentrations much higher, than concentrations found in human tissues, making them unlikely links between exposures and adverse reproductive outcomes in the general population. Robust evidence suggests that at environmentally relevant doses, PBDEs and their metabolites may affect male reproductive health via mechanisms including AR antagonism and the disruption of a complex network of metabolic signaling.

The formation and propagation of cracks occurs through irreversible dislocation movements at notches, material defects and grain boundaries. Since this process is partly thermally controlled, the resistance to dislocation movements at low temperatures increases. This slows both fatigue initiation and fatigue crack propagation. From recent experimental data, it can be seen that fatigue crack growth is accelerated below the fatigue transition temperature (FTT) that correlates with the ductile-brittle transition temperature (DBTT) found by well-known fracture mechanics tests, i.e., Charpy impact, fracture toughness, and CTOD. Hence, this study investigates the relation between FTT and DBTT in S500 high-strength steel base material and welded joints at low temperatures using fatigue crack growth, fracture toughness tests as well as scanning electron microscopy. From the tests, an almost constant decrease in fatigue crack propagation rate is determined with decreasing test temperature even below the DBTT.

Epichloë species form bioprotective endophytic symbioses with many cool-season grasses, including agriculturally important forage grasses. Despite its importance, relatively little is known about the molecular details of the interaction and the regulatory genes involved. VelA is a key global regulator in fungal secondary metabolism and development. In previous studies, we showed the requirement of velA for E. festucae to form a mutualistic interaction with Lolium perenne. We showed that VelA regulates the expression of genes encoding proteins involved in membrane transport, fungal cell wall biosynthesis, host cell wall degradation and secondary metabolism, along with several small-secreted proteins in Epichloë festucae. Here, by a comparative transcriptomics analysis on perennial ryegrass seedlings and mature plants, which are endophyte free or infected with wild type (mutualistic interaction) or mutant ∆velA E. festucae (antagonistic or incompatible interaction), regulatory effects of the endophytic interaction on perennial ryegrass development was studied. We show that ∆velA mutant associations influence the expression of genes involved in primary metabolism, secondary metabolism and response to biotic and abiotic stresses compared to wild type associations, providing an insight into processes defining mutualistic versus antagonistic interactions.

Alloy 800H stands as one of the few code qualified materials for fabricating in core and out of core components operating in high temperature reactors (HTRs). Welding is a common practice for assembling these components, however, the election of a suitable filler material is essential to enhance the high-temperature creep resistance of Alloy 800H weldments in high temperature applications. In this study, Inconel 625 and Haynes 230 filler material were used to weld the Alloy 800H plates employing the Gas Tungsten Arc Welding (GTAW) technique. The high temperature tensile, creep rupture property, microstructural stability and evolution of the weldments after high temperature exposure were investigated and compared with Alloy 800H. The results showed that the both weldments exhibited enhanced tensile and creep behavior at 760 oC. The creep rupture time of the weldments with Inconel 625 filler and Haynes 230 filler materials was about two and three time longer than that of Alloy 800H base metal when tested at 80 MPa and 760 oC, respectively. Carbides (MC and M23C6) were commonly observed in the microstructure of both the weld and base metals in the two weldments after high temperature creep tests. However, the Inconel 625 filler weldment displayed detrimental δ and Laves phase in the fusion zone and these precipitates could be potential sites for initiating cracks following prolonged high temperature exposure. The study showed that the weldment with Haynes 230 exhibited better phase stability and creep rupture property than the one with Inconel 625 filler material, suggesting its potential as a candidate filler material for Alloy 800H for further investigation. The finding also emphasizes the critical consideration of microstructural evolutions and phase stability in evaluating high temperature materials and their weldments in high temperature reactor applications.

In recent years, many libraries and archives have started digitizing their collections thus making maps by Indigenous peoples more easily available for scholars to study. While a number of these maps were discussed by G. Malcolm Lewis in the History of Cartography series (volume 2, book 3, Chapter 4: 1984), more have since been found and disseminated. These maps are critical in understanding the historic and current land tenure of Indigenous groups. Further, Indigenous claims to land can be seen in their connections via toponymy. European concepts of territory and political boundaries did not coincide with First Nation/American Indian views resulting in the mistaken view that Natives did not have formal concepts of their territories. Further, Tribes/First Nations with cross-border territory have special jurisdictional problems. This paper will illustrate how many Native residents were very spatially cognizant of their own lands, as well as neighboring nations’ lands, overlaps between groups, hunting territories, populations, and trade networks. Currently, the Sinixt First Nation provides a perfect example of how an Aboriginal people are inputting and using a GIS representation of their territory with proper toponymy and use areas.

The ability to self-direct a research program determines graduate degree completion. Yet, research on incompletion of graduate physics programs assume students’ present level of self-direction adequate and neglects to recognize a lack of self-directed learning as key. One theoretical mathematical physicist focused on changing this challenge of physics graduate education by promoting self-directed learning through the type research flow that has been found to bring the greatest satisfaction to researchers with respect to their insights. This he provided through his space, time, open mindedness and theoretical contributions with his students and in collaboration with his colleagues. A self-directed learner himself, David J. Rowe developed methods of mentoring for encouraging physics graduate students to recognize symmetry as valuable in identifying solutions to problems quickly—helping these students take the lead in finding insightful resolutions to complex, multidimensional, mathematical physics uncertainties. How Rowe set about supporting self-directed learning in his graduate physics education interactions will be examined with the use of narrative research to interpret the texts and conversations with the author he made available. His techniques will be presented and recommendations made regarding how Rowe’s work in this regard can be modeled to improve self-direction in STEM graduate education.

Brain-Computer Interface (BCI) systems can assist physically challenged people to interact with their surroundings and improve the quality of their lives. Decoding human thoughts is a powerful technique that can assist paralyzed people who have lost their speech production ability. Speaking is a combined process involving synchronizing the brain and the oral articulators. This paper proposed a high-accuracy brain wave pattern recognition based on inner speech using a novel feature extraction method. Only eight EEG electrodes were used in this study, and they were set on selected spots on the scalp. Support Vector Machine (SVM) was employed to decode the recorded EEG dataset into four internally spoken words which are: Up, Down, Left, and Right. The proposed approach achieved overall classification accuracy that ranges between 96.20% to 97.5%. In addition, more performance evaluation metrics were estimated to test the reliability of classifying the EEG-based inner speech data, and we obtained 97.61%, 97.50%, and 97.73% for F1-score, recall, and precision respectively. Furthermore, the Area Under Curve of the Receiver Operating Characteristic (AUC-ROC) proved the strength of the proposed approach for classifying the specified inner speech commands by achieving a macro-average amount of 99.32%. The inner speech classification method using electroencephalography proposed in this work can clinically help improve communication for patients with problems including speech disorder, mutism, cognitive development, executive function, and psychopathology.

The purpose of this work was to evaluate the suitability of recent US Food and Drug Administration (US-FDA) approved and marketed oral liquid, powder, or granule products for children in North America, to identify the next group of Active Pharmaceutical Ingredients (APIs) that have high potential for development as commercially available FDA-approved finished liquid dosage forms , and to propose lists of compounded nonsterile preparations (CNSPs) that should developed as commercially available FDA-approved finished liquid dosage forms as well as those that pharmacists should continue to compound extemporaneously. Through this identification and categorization process, the pharmaceutical industry, government, and the professions are encouraged to continue to work together to improve the likelihood that patients will receive high quality standardized extemporaneous CNSPs and US-FDA-approved products.

The effect of high temperature (HT) stress on nicotine biosynthesis in Nicotiana attenuata was examined. Nicotine content was measured in mature leaves, young sink leaves and in roots from well-watered plants grown at 25 °C as controls and from plants exposed to 38 °C and 43 °C temperatures applied for 24, 48, 72 and 96-hr duration. At 38 °C, all leaf nicotine levels were significantly less than control plants for up to 72-hr exposure but rose sharply thereafter to levels significantly greater than controls with 96-hr exposure. In contrast, plants exposed to 43 °C never exhibited a reduction in leaf nicotine content and showed a significant increase in content with just 48-hr exposure. When radioactive 11CO2 was administered to plants, HT stress significantly reduced fixation. Furthermore, radiocarbon flux analysis revealed that ‘new’ C partitioning (as 11C) into the [11C]-amino acid pool was significantly reduced with HT stress as were yields of [11C]-aspartic acid, an important amino acid in nicotine biosynthesis, and its beta-amido counterpart [11C]-asparagine significantly reduced. In contrast, [12C]-aspartic acid levels appeared unaffected at 38 °C but were significantly elevated at 43 °C relative to controls. Additionally, [12C]-asparagine levels were significantly elevated at both stress temperatures. Finally, leaf total soluble protein (TSP) was reduced 39% with long exposures to both stress temperatures. However, Ribulose-1,5-bisphosphate carboxylase/oxygenase (Rubisco) which was 41% TSP appeared unaffected by HT stress. Altogether, these results support the theory that plant proteins other than Rubisco degrade at elevated temperatures freeing up essential amino acids supporting the nicotine biosynthetic machinery, and while feedback might downregulate de novo amino acid synthesis from ‘new’ C resources, more than likely plant C/N rebalancing caused by HT reductions in C input restricted N uptake, which in turn, limited this process.

As urban development increases in density, the space to grow urban trees becomes more constrained. In heavily developed areas, small stature trees can be planted to reduce both above- and below-ground conflicts with infrastructure elements. However, even these species have their limits when placed in extremely confining conditions. In this study, we build on past work to determine the minimum planting widths of small stature urban trees. We found that species, stem diameter, and the height at which stem diameter measurements occurred were all strong predictors of trunk flare diameter (adjusted R² of 0.843). Additionally, we modelled the relationship between planting space and the presence or absence of hardscape conflicts – using the predictions derived from this effort to project the potential cost savings in two United States cities. Study results provide a guideline to create sufficient space for urban trees and minimize infrastructure damage and associated cost savings.

Matter grows and self-assembles to produce complex structures such as virus capsids, carbon fullerenes, proteins, glasses, etc. Due to its complexity, performing pen-and-paper calculations to explain and describe such assemblies is cumbersome. Many years ago, Richard Kerner presented a pen-and-paper path integral approach to understand self-organized matter. Although successfully addressed many important problems including the yield of fullerene formation, the glass transition temperature of doped chalcogenide glasses, the fraction of boroxol rings in B2O3 glasses, the first theoretical explanation for the empirical recipe of window and Pyrex glass and the understanding of virus capsid self-assembly, still is not the primary choice when tackling similar problems. The reason lies in the fact that it diverges from mainstream approaches based on the energy landscape paradigm and non-equilibrium thermodynamics. In this context, a critical review is presented, demonstrating that the Richard Kerner method is, in fact, a clever way to identify relevant configurations. Its equations are simplified, common physical sense versions to those found in the energy landscape kinetic equations. Subsequently, the utilization of equilibrium Boltzmann factors in the transition Markov chain probabilities is analyzed within the context of local two-level energy landscape models kinetics. This analysis demonstrates that their use remains valid when the local energy barrier between reaction coordinate states is small compared to the thermal energy. This finding places the Richard Kerner model on par with other more sophisticated methods and, hopefully, will promote its adoption as an initial and useful choice for describing the self-agglomeration of matter.

Polymethyl methacrylate (PMMA) polymer is widely used in various fields today. In order to thoroughly reveal the structural impact performance of PMMA materials, this paper is based on the comprehensive Johnson-Cook constitutive model and damage failure model, and accurately confirm the J-C constitutive and damage failure model parameters of PMMA through material test data, The dynamic process of steel bullet impacting PMMA plate structure is analyzed by finite element software ABAQUS. The calculation results show that the numerical simulation results in this paper are in good agreement with the experimental test data. Therefore, the feasibility and accuracy of the impact analysis of PMMA structures based on J-C constitutive and damage failure models in this paper are studied. Finally, based on the J-C constitutive model and damage failure model, the variation of the residual velocity of the bullet with the PMMA plate thickness is analyzed in depth, that is, the results show that the residual velocity of the bullet has a certain linear relationship with the plate thickness.

Is it possible to develop a meaningful measure for the complexity of a simulation model? Algorithmic information theory provides concepts that have been applied in other areas of research for the practical measurement of object complexity. This article offers an overview of complexity from a variety of perspectives and provides a body of knowledge with respect to the complexity of simulation models. Key terms of model detail, resolution, and scope are defined. An important concept from algorithmic information theory, Kolmogorov complexity, and an application of this concept, normalized compression distance, are used to indicate the possibility of measuring changes in model detail. Additional research in this area can advance the modeling and simulation body of knowledge toward the practical application of measuring simulation model complexity. Examples show that KC and NCD measurements of simulation models can detect changes in scope and detail.

Background and Objectives: Acculturation is associated with excessive weight gain among immigrants to the U.S. Whether dietary factors mediate this association is unclear. This study aimed to examine whether overall diet quality or specific component(s) of diet quality mediate the association between acculturation and Body Mass Index (BMI) among Mexican American (MA) men and women. Material and Methods: This is a secondary data analysis using dietary intake data from 24-hour dietary recalls, measured height and weight, and self-reported acculturation from the National Health and Nutrition Examination Survey (NHANES) cycles 1999-2000 to 2011-2012. A total of 6848 MA adults (≥20 yrs) with reliable dietary recall status and body measures were included in the study. Path analyses was performed in Mplus with complex survey design effects adjusted. Results: HEI components of whole grains and sodium were found to play meditating roles in the acculturation-BMI association, and their effects on BMI were opposing [indirect effect were -0.01 (SE 0.00) and 0.02 (0.01), respectively]. In gender-specific analysis, sodium [0.01 (0.00)] was a significant mediator only in MA men; whereas, whole grains [-0.01 (0.00)] was a significant mediator only in MA women. Conclusions: HEI components of whole grains and sodium appeared to be significant dietary mediators in the acculturation-BMI association. Understanding the variations of dietary components and their relationship with acculturation as well as BMI is useful for developing dietary interventions and obesity reduction.

Entheseal spinal inflammation and new bone formation with progressive ankylosis may occur in ankylosing spondylitis (AS) and psoriatic arthritis (PsA). This study evaluated whether JAK inhibition with tofacitinib modulated the key disease associated cytokines, TNF and IL-17A and whether tofacitinib also modulated bone marrow stromal cell-derived mesenchymal stem cells (MSCs) function including osteogenesis, since post inflammation new bone formation occurs in these conditions. Methods: Conventional entheseal derived αβ CD4+ and CD8+ T-cells were in-vestigated following anti-CD3/CD28 bead stimulation to determine IL-17A and TNF levels in Tofacitinib treated (1000nM) peri-entheseal bone (PEB) and peripheral blood mononuclear cells (PBMC) following ELISA. Bone marrow stromal cell-derived mesenchymal stem cells (MSCs) colony forming unit (CFU-F) and multilineage potential was evaluated using tofacitinib (dosag-es ranging between 100, 500, 1000 and 10000nM). Results: Induced IL-17A and TNF cytokine production from both entheseal CD4+ T-cells and CD8+ T-cells were effectively inhibited by to-facitinib. Tofacitinib treatment did not impact on CFU-F potential or in vitro chondro- and oste-ogenesis. However, tofacitinib stimulation increased MSC adipogenic potential with greater Oil Red O stained area. Conclusion: Inducible IL-17A and TNF production by healthy human enthe-seal CD4+ and CD8+ T-cells was robustly inhibited in vitro by tofacitinib. However, tofacitinib did not impact on MSC osteogenesis but stimulated in vitro MSC adipogenesis, the rele-vance of which needs further evaluation given the adipocytes are associated with new bone formation in SpA.

This study reports the synthesis and characterization of novel per-fluorinated organic polymers with azo- and azomethine-based linkers using nucleophilic aromatic substitution. The polymers reveal variations in the fluorine content via the incorporation of decafluorobiphenyl and hexafluorobenzene linkers, which enhanced their hydrophobic nature. The rich fluorine polymers were slightly soluble in THF and have shown molecular weights between 4886 to 11948 g/mol. All polymers exhibit thermal stability in the range of 350-500°C, with varying thermal stability depending on the fluorine and nitrogen content. Conjugation of the polymers was confirmed through changes in the UV-Vis spectra, with a hypsochromic shift observed in all cases, more pronounced in azo-based fluorinated chains due to H-bonding on the nitrogen sites, chain conformations, and planarity. The optical band gap (Eg) of the polymers was determined from the UV-Vis data, with the Eg values of the azo-based fluorinated polymers being 1 eV higher than those of their corresponding linkers. The cross-linking formation was characterized by porosity measurements, with the azo-based polymer exhibiting the highest surface area of 770 m²/g with a pore volume of 0.35 cm³/g, while the open-chain azomethine-based polymer exhibited the lowest surface area of 285 m²/g with a pore volume of 0.0872 cm³/g. Porous structures with varied hydrophobicities were investigated as adsorbents for separating water-benzene and water-phenol mixtures and selectively binding methane/carbon dioxide gases from the air. The most hydrophobic polymers containing the decafluorbiphenyl linker were suitable for benzene separation, while the best methane uptake values were 6.14 and 3.46 mg/g for DAB-Z-1O and DAB-A-1O, respectively. DAB-Z-1h, with the highest surface area and rich in nitrogen sites, exhibited the highest CO₂ uptake at 298 K (17.25).

The transverse momentum distribution of J/ψ mesons produced in pp collisions at the center-of-mass energy 5 TeV, 7 TeV，and 13 TeV is described by the modified Hagedorn function which is based on the Tsallis function and Hagedorn function. The calculated results by the modified Hagedorn function are in accord with experimental data measured by the LHCb Collaboration at LHC. The related parameters are obtained and analyzed.

Considered one of the finest first-generation Nigerian writers, John Pepper Clark-Bekederemo, who passed away on 13th October, 2020, had been categorised as a Eurocentric writer. This work assesses the authenticity or otherwise of this critics’ perception of Clark by critiquing his America, their America. By analysing this autobiography vis-à-vis the notion of self and other which is a theoretical concern in contemporary travel writing, it was established, among other things, that every culture has its dark sides which it must not feel too proud to change as time and situation demand; that Clark vehemently rejects the Americans’ claim of sophistication and superiority of their culture over African culture. The paper concludes that contemporary travel writing should be a rightful site for negotiating cultural, political and diplomatic compromises between the Self and the Other since the gulf may be difficult to close altogether.

Angiogenesis is a critical physiological response to ischemia but becomes pathological when dysregulated and driven excessively by inflammation. We recently identified a novel angiogenic role for tripartite-motif-containing protein 2 (TRIM2) whereby lentiviral shRNA-mediated TRIM2 knockdown impaired endothelial angiogenic functions in vitro. This study sought to determine whether these effects could be translated in vivo and to determine the molecular mechanisms involved. CRISPR/Cas9-generated Trim2–/– mice that underwent a periarterial collar model of inflammation-induced angiogenesis exhibited significantly less adventitial macrophage infiltration relative to wildtype (WT) littermates, concomitant with decreased mRNA expression of macrophage marker Cd68 and reduced adventitial proliferating neovessels. Mechanistically, TRIM2 knockdown in endothelial cells in vitro attenuated inflammation-driven induction of critical angiogenic mediators, including nuclear HIF-1α, and curbed the phosphorylation of downstream effector eNOS. Conversely, in a hindlimb ischemia model of hypoxia-mediated angiogenesis, there were no differences in blood flow reperfusion to the ischemic hindlimbs of Trim2–/– and WT mice despite a decrease in proliferating neovessels and arterioles. TRIM2 knockdown in vitro attenuated hypoxia-driven induction of nuclear HIF-1α but had no further downstream effects on other angiogenic proteins. Our study has implications for understanding the role of TRIM2 in the regulation of angiogenesis in both pathophysiological contexts.

The aim of this document is to provide practical guidance on the choice of target difference used in the sample size calculation of a randomised controlled trial (RCT). Guidance is provided with a definitive trial, one that seeks to provide a useful answer, in mind and not those of a more exploratory nature. The term “target difference” is taken throughout to refer to the difference that is used in the sample size calculation (the one that the study formally “targets”). Please see the glossary for definitions and clarification with regards other relevant concepts. In order to address the specification of the target difference, it is appropriate, and to some degree necessary, to touch on related statistical aspects of conducting a sample size calculation. Generally the discussion of other aspects and more technical details is kept to a minimum, with more technical aspects covered in the appendices and referencing of relevant sources provided for further reading.The main body of this guidance assumes a standard RCT design is used; formally, this can be described as a two-arm parallel-group superiority trial. Most RCTs test for superiority of the interventions, that is, whether or not one of the interventions is superior to the other (See Box 1 for a formal definition of superiority, and of the two most common alternative approaches). Some common alternative trial designs are considered in Appendix 3. Additionally, it is assumed in the main body of the text that the conventional (Neyman-Pearson) approach to the sample size calculation of an RCT is being used. Other approaches (Bayesian, precision and value of information) are briefly considered in Appendix 2 with reference to the specification of the target difference.

Work-related thoughts in off-job time have been studied extensively in occupational health psychology and related fields. We provide a focused review of research on overcommitment – a component within the effort-reward imbalance model – and aim to connect this line of research to the most commonly studied aspects of work-related rumination. Drawing on this integrative review, we analyze survey data on ten facets of work-related rumination, namely (1) overcommitment, (2) psychological detachment, (3) affective rumination, (4) problem-solving pondering, (5) positive work reflection, (6) negative work reflection, (7) distraction, (8) cognitive irritation, (9) emotional irritation, and (10) inability to recover. First, we leverage exploratory factor analysis to self-report survey data from 357 employees to calibrate overcommitment items and to position overcommitment within the nomological net of work-related rumination constructs. Second, we leverage confirmatory factor analysis to self-report survey data from 388 employees to provide a more specific test of uniqueness vs. overlap among these constructs. Third, we apply relative weight analysis to quantify the unique criterion-related validity of each work-related rumination facet regarding (1) physical fatigue, (2) cognitive fatigue, (3) emotional fatigue, (4) burnout, (5) psychosomatic complaints, and (6) satisfaction with life. Our results suggest that several measures of work-related rumination (e.g., overcommitment and cognitive irritation) can be used interchangeably. Emotional irritation and affective rumination emerge as the strongest unique predictors of fatigue, burnout, psychosomatic complaints, and satisfaction with life. Our study assists researchers in making informed decisions on selecting scales for their research and paves the way for integrating research on effort-reward imbalance and work-related rumination.

In this note, I analyze the data generated by M. Fodje's (2013) simulation programs "epr-simple" and "epr-clocked". They were written in Python and published on Github. Inspection of the program descriptions shows that they make use of the detection-loophole and the coincidence-loophole respectively. I evaluate them with appropriate modified Bell-CHSH type inequalities: the Larsson detection-loophole adjusted CHSH, and the Larsson-Gill coincidence-loophole adjusted CHSH (NB: its correctness is conjecture, we do not have proof). The experimental efficiencies turn out to be approximately eta = 81% (close to optimal) and gamma = 55% (far from optimal). The observed values of CHSH are, as they should be, within the appropriately adjusted bounds. Fodjes' detection-loophole model turns out to be very, very close to Pearle's famous 1970 model, so the efficiency is close to optimal. The model has the same defect as Pearle's: the joint detection rates exhibit signaling. Fodje's coincidence-loophole model is actually a clever modification of his detection-loophole model. Because of this, however, it cannot lead to optimal efficiency.

This article reevaluates the Woesean concept of crossing a ‘Darwinian threshold’ from pre-genomic communality, as prevailing in an ancestral ‘progenote’ state, to vertically stable lineages of autonomous and self-similar cells. This transition from collective trunk-line evolution to Darwinian speciation is dependent on the generation of modular organismal genomes. The same general principle should be valid at subcellular levels, allowing the emergence of semi-autonomous genomic agents, such as viruses and plasmid-carrying endogenous vesicles with organelle-like properties. As compartmentalized agents of endogenous nature could start with smaller genomes than those required for fully autonomous cells, it is conjectured that stable subcellular lineages emerged earlier than their cellular counterparts. Referring to the recent ‘pre-endosymbiont hypothesis’, it is proposed that free-living bacteria (the first ‘prokaryote’ cells) arose by ‘lineage escape’ from plasmid-bearing organelle-like compartments, evolving inside the internally complexifying ‘paracells’ of the progenote community. The double-membrane envelopes of diderm bacteria may have resulted from cell-biological processes facilitating cellular lineage escape. The later emergence of archaeal cells (resembling bacteria in ‘prokaryote’ appearance with unichromosomal genomes) and eukaryotic organisms (with compartmented cells and multichromosal genomes) can also be interpreted in terms of this modified progenote hypothesis. Conceivably, the multichromosomal genomes of eukaryotes were bundled in endogenous nuclear compartments to organize a ‘nuclear-cytoplasmic lineage’, which became vertically stable by perfecting mitosis/meiosis-like divisions and yet retained some intra-species population confluence by sexual division-fusion cycles.

Although domestic cats are susceptible to infection with SARS-CoV-2, the role of the virus in causing feline disease is less well defined. We conducted a large-scale study to identify SARS-CoV-2 infections in UK pet cats, using active and passive surveillance. Remnant feline respiratory swab samples, submitted for other pathogen testing between May 2021 and February 2023, were screened using RT-qPCR. In addition, we appealed to veterinarians for swab samples from cats suspected of having clinical SARS-CoV-2 infections. Bespoke testing for SARS-CoV-2 neutralising antibodies was also performed, on request, in suspected cases. One RT-qPCR-positive cat was identified from the active surveillance (1/549, 0.18 %), during the Delta wave (1/175, 0.57 %). Passive surveillance detected one cat infected with the Alpha variant, and two of ten cats tested RT-qPCR-positive during the Delta wave. No cats tested RT-qPCR-positive after the emergence of Omicron BA.1 and its descendants although 374 were tested by active and eleven by passive surveillance. We describe four cases of SARS-CoV-2 infection in pet cats, identified by RT-qPCR and/or serology, that presented with a range of clinical signs, as well as their SARS-CoV-2 genome sequences. Our results demonstrate that, although uncommon, clinical infections in cats can and do occur.

Lichen Amyloidosis (LA) is a type of cutaneous amyloidosis characterized by brownish hyperkeratotic and itchy papules on the lower leg, back, forearm or thigh. It is associated with itching and Atopic Dermatitis (AD) according to an etiopathogenetic mechanism that has not yet been fully elucidated. Currently, available therapies for this condition include oral antihistamines, laser, cyclosporine, topical corticosteroids and phototherapy, but in light of the overlap with AD, Dupilumab may also be indicated. We report the case of a female, 52 years old, suffering from AD and LA for about 27 years. She had lesions attributable to both diseases on the trunk and lower limbs associated with severe itching and had proved resistant to cyclosporine therapy. It was decided to opt for Dupilumab with induction of 2 fl of 300 mg and maintenance with 1 fl every other week. The therapy proved effective, returning a total resolution of both diseases one year after the beginning of the treatment. Dupilumab demonstrated efficacy and safety in LA related to AD and led to clinical and quality of life improvement in this patient. Therefore, Dupilumab should be considered when treating LA. Further studies should be conducted focusing on the efficacy of the drug on LA (whether or not related to AD), changes in skin lesions after discontinuation, and the safety of long-term application.

Developmental hazard evaluation is an important part of assessing chemical risks during pregnancy. Toxicological outcomes from prenatal testing in pregnant animals result from complex chemical-biological interactions, and while New Approach Methods (NAMs) based on in vitro bioactivity profiles of human cells offer promising alternatives to animal testing, most of these assays lack cellular positional information, physical constraints, and regional organization of the intact embryo. Here, we engineered a fully computable model of the embryonic disc in the compucell3d.org modeling environment to simulate epithelial-mesenchymal transition of epiblast cells and self-organization of mesodermal domains (chordamesoderm, paraxial, lateral plate, posterior/extraembryonic). Cell fate in the model is determined by an autonomous homeobox (HOX) clock driven by morphogenetic signals (e.g., FGF, WNT, ATRA, CDX). Executing the model renders a quantitative cell-level computation of mesodermal subpopulations and consequences of perturbation based on known embryogeny. For example, synthetic perturbation of the control network rendered altered phenotypes (cybermorphs) mirroring experimental mouse embryology, with 50% reductions in FGF4, FGF8 and BMP4 signaling resulting in 86%, 98% and 59% reductions, respectively in the posterior mesodermal population, while ATRA exposure also resulted in a 78% decrease in this population. This model enables integration of in vitro chemical bioactivity data for specific molecular targets with known embryology to test mechanistic veracity and quantitative prediction of altered development.

This paper seeks to model the crack propagation in of AAs (aluminum-alloys) 2524-T3 and 7050-T7452 subjected to fatigue loading at low temperature. Fatigue crack growth tests were performed on AAs 2524-T3 and 7050-T7452 subjected to constant-amplitude and actual random-spectra loading histories at room temperature of about 25 °C and at cryogenic temperature of -70 °C, respectively, to determine their crack growth properties and residual lives. The interaction mechanisms between cryogenic temperature and the fatigue load were deduced on the basis of the results of fractographic analysis. Temperature-dependent residual lives under actual random-spectrum load history were modeled based on a modified accumulation damage rule by accounting for the load interaction. Good correlation was achieved between the predictions and actual experiments, demonstrating the practical and effective use of the proposed method.

The pregnane X receptor (PXR) is the main nuclear receptor regulating the expression of xenobiotic metabolizing enzymes and is highly expressed in the liver and intestine. Recent studies have highlighted its additional role in lipid homeostasis, however, the mechanisms of these regulations are not fully elucidated. We investigated the transcriptomic signature of PXR activation in the liver of adult wild-type vs Pxr-/- C57Bl6/J male mice treated with the rodent specific ligand pregnenolone 16α-carbonitrile (PCN). PXR activation increased liver triglyceride accumulation and significantly regulated the expression of 1215 genes mostly xenobiotic metabolizing enzymes. Among the down-regulated genes, we identified a strong peroxisome proliferator-activated receptor α (PPARα) signature. Comparison of this signature with a list of fasting-induced PPARα target genes confirmed that PXR activation decreased the expression of more than 25 PPARα target genes, among which the hepatokine fibroblast growth factor 21 (Fgf21). PXR activation abolished plasmatic levels of FGF21. We provide a comprehensive signature of PXR activation in the liver and identify new PXR target genes that might be involved in the steatogenic effect of PXR. Moreover, we show that PXR activation down-regulates hepatic PPARα activity and FGF21 circulation, which could participate in the pleiotropic role of PXR in energy homeostasis.

Information on the nutritive value and in vitro fermentation characteristics of native shrubs in New Zealand is scant. This is despite their potential as alternatives to exotic trees and shrubs for sup-plementary fodder, and mitigation of greenhouse gas and soil erosion on hill country sheep and beef farms. The objectives of this study were to measure the in vitro fermentation gas production, predict parameters of in vitro fermentation kinetics and to estimate in vitro fermentation of volatile fatty acids (VFA), microbial biomass (MBM) and greenhouse gases of four native shrubs (Coprosma robusta, Griselinia littoralis, Hoheria populnea and Pittosporum crassifolium) and an exotic fodder tree species, Salix schwerinii. Total in vitro gas production was higher (p<0.05) for natives than S. schwerinii. Prediction using the single pool model resulted in biologically incorrect negative in vitro total gas production from the immediately soluble fraction of the native shrubs. However, the dual pool model better predicted in vitro total gas production and was in alignment with measured in vitro fermentation end products. In vitro VFA and greenhouse gas production from fermentation of leaf and stem material were higher (p<0.05), and MBM lower (p<0.05), for native shrubs com-pared to S. schwerinii. The lower in vitro total gas production, VFA and greenhouse gases produc-tion, and higher MBM of S. schwerinii may be explained by the presence of condensed tannins (CT), although this was not measured and requires further study. In conclusion, results from this study suggests that when consumed by ruminant livestock, the browsable native shrubs can provide adequate energy and microbial protein, and that greenhouse gas production from these species is within ranges reported for typical New Zealand pastures.

Does the choice of proxy for stock market development matter? This paper suggests that the growth effect of stock market development is sensitive to the choice of proxy and using alternative financial development indicators have practically no influence on the results. We found that using either the stock market capitalization to GDP ratio or the stock market returns; have a positive and significant effect on growth. However, we cannot make same conclusion when one uses either the ratio of total value of trades on the major stock exchanges to GDP or stock market turnover ratio to proxy for stock market development as the coefficient on these variables were found to be statistically insignificant. The indexes extracted from principal component analysis confirm the sensitivity of the effect to the choice of proxy. This finding suggest that stock market development is a conceptual terms, thus, representing it with single indicators make it impossible to identify which stock market development indicators have a significant positive growth effects.

To show that underlying Schmitt's account of fascist politics lies a Gnostic-like metaphysical dualism separating the realms of value and power. Contrary to the normative political tradition of the West, which defends an ethical politics, Schmitt - jurist and theorist of the Nazis - aligns himself with Machiavelli and Hobbes to defend realpolitik: where sovereignty is ultimately a function of the Dictator's will alone. This paper shows the contradiction within such a position, which criticizes values in politics but by its advocacy, and its defense of the Dictator's willing, relies on valuation, choice, and hence the ethical.

Background: Positive person-centered attributes of inpatient rehabilitation need to be identified from the patient perspective to be further developed and sustained. Purpose: To identify which attributes patients openly evoke as being great care experiences, using an open appreciative inquiry during the inpatient rehabilitation stay. Methods: Qualitative secondary analysis of appreciative patient comments during a bedside patient experience rounding, facilitated by a neutral party. Two independent analysts employed an inductive, summative form of content analysis. Results: Among 150 patients rounded, 122 provided categorizable appreciative accounts. Over two thirds of the patients (67.2%) focused on “staff attributes” in their great-experience accounts. Those attributes were mostly interpersonal such as being “attentive & caring - beyond clinical duty” and being “encouraging (but not too hard) & reassuring”. These interpersonal staff attributes were reported with words showing deep levels of personal significance or patient appreciation. Beyond staff attributes, the perceived quality of the “patient care” (31.1%) and opportunities for “leisure and social activities” (9.0%) were also frequently evoked. Amenities like food or costumer service were the least evoked, rarely so as an exclusive attribute (0.8% for each). Conclusions: The human(e) factor, especially the interpersonal qualities of staff, emerged as greatly appreciated from the patient experience perspective during inpatient rehabilitation. These experiences help identify which person-centered attributes of care might be further developed and sustained.

Autism spectrum disorder (ASD) is characterized by diverse patterns of social interaction, communication, and behavior. This study explores the application of clustering and stochastic migration models to visualize and understand the social and neural connectivity patterns associated with autism. The clustering model, with its strong internal connections and limited external connections, mirrors the tight-knit social groups and communication barriers often observed in individuals with autism. In contrast, the stochastic model, characterized by more dispersed connections and greater adaptability, represents the variability and flexibility seen in social interactions across typical individuals. By comparing these models, we can gain deeper insights into the unique challenges and strengths of individuals with autism, highlighting the importance of personalized interventions. Additionally, these models provide a visual framework for understanding the differences in brain connectivity patterns observed in autism, with implications for both behavioral and neural correlates. This study underscores the value of computational models in advancing our understanding of autism and guiding effective support strategies.

The environment is seldom optimal for plant growth and changes in abiotic and biotic signals, including temperature, water availability, radiation and pests, induce plant responses to optimise survival. The New Zealand native plant species and close relative to Arabidopsis thaliana, Pachycladon cheesemanii grows under environmental conditions that are unsustainable for many plant species. Here we compare the responses of both plant species to different stressors (low temperature, salt and UV-B radiation) to help understand how P. cheesemanii can grow in such harsh environments. The stress transcriptomes were then determined and comparative transcriptome and network analyses discovered similar and unique responses within species between different stresses, and between the two plant species. A number of widely studied plant stress processes were highly conserved in A. thaliana and P. cheesemanii. However, in response to cold stress, Gene Ontology terms related to glycosinolate metabolism were only enriched in P. cheesemanii. Salt stress was associated with alteration of the cuticle and proline biosynthesis in A. thaliana and P. cheesemanii, respectively. Anthocyanin production may be a strategy to cope with UV-B radiation stress in P. cheesemanii only. These results allowed us to construct broad stress response pathways in A. thaliana and P. cheesemanii and identify possible novel plant strategies that help mitigate environmental stress.

There is scientific consensus that organismal aging did not evolve by natural selection (NS) because it lacks individual benefit. Nonetheless it exists, leading to much speculation about its origins, and when the diminishing force of selection begins. Both concepts are based upon two misconceptions; that aging occurs in and of itself and is caused by the declining strength of NS during the reproductive lifespan. Although lacking individual benefit, aging evolved by NS as a tradeoff of survival for reproduction. Based upon regulatory dynamics that participate in this tradeoff, aging begins once reproductive success has been achieved through offspring nurturing. Thereafter, the strength of NS wanes to exponentially accelerate aging, leading to death. Assumptions of the theory are that: (1) a life-long, “holistic” regulatory mechanism whose genic expression is modified epigenetically, originates in ontogenesis; (2) the regulatory mechanism of the last developmental stage becomes redundantly expressed during “morphostasis”, a non-aging, life interval of peak vitality to ensure completion of reproduction through nurturing, and (3) thereafter, loss of regulatory redundancy causes aging which reduces the strength of natural selection and allows accumulation of randomly occurring somatic damage.

Glioblastoma is a highly aggressive brain tumor characterized by rapid growth, extensive infiltration, and poor prognosis. Understanding the complex interplay of biological processes driving glioblastoma progression is crucial for developing effective therapeutic strategies. In this study, we present a comprehensive mathematical model that incorporates key aspects of glioblastoma growth and dissemination, including tumor cell diffusion, angiogenesis, nutrient availability, molecular signaling pathways, and blood-brain barrier (BBB) interactions. The model is based on a system of coupled partial differential equations (PDEs) and ordinary differential equations (ODEs) that capture the spatiotemporal dynamics of tumor cell density, nutrient concentration, signaling molecule concentrations, and BBB integrity. We employ numerical simulation techniques, such as the finite difference method and the Runge-Kutta method, to solve the model equations and visualize the evolution of tumor growth and its associated biological processes. The model parameters are estimated using experimental data from the literature, and the model is validated against clinical observations. Furthermore, we perform a comprehensive sensitivity analysis to identify the key parameters that significantly influence tumor growth, diffusion, and dissemination. The sensitivity analysis reveals the relative importance of each parameter in driving glioblastoma progression and highlights potential targets for therapeutic interventions. Our computational framework provides a powerful tool for understanding the complex dynamics of glioblastoma growth and offers valuable insights into the underlying biological mechanisms. The model can be used to test hypotheses, predict tumor response to various treatment strategies, and guide the design of targeted therapies. The findings from this study contribute to the ongoing efforts in developing personalized treatment approaches for glioblastoma patients and improving their clinical outcomes.

Introduction: The association of gene variants for interleukin 6(IL-6) (rs1800796), interleukin 10 (IL-10) (rs1800896) and tumor necrosis factorα (TNFα (rs1800629) with the occurrence of spontaneous preterm birth (PTB) was investigated to determine whether these genetic variants are a risk factor. Materials and methods: 199 blood samples from pregnant women who had given birth prematurely and 200 control blood samples were analyzed to determine single nucleotide polymor-phisms (SNPs) of genes for IL-6 (rs1800796), IL-10 (rs1800896) and TNFα (rs1800629). The control samples were samples from pregnant women with term delivery. Isolation of DNA was per-formed on mini-spin columns according to the manufacturer's protocol. The quality and purity of the isolated DNA were tested using a Qubit 3 fluorometer. Genotyping was performed with an ABI PRISM 7500 SDS using TaqMan SNP genotyping assays. The genotypes obtained were an-alyzed using the 7500 Software v2.3 package. Results: Carriers of the A/A genotype for the rs1800629 of the TNFα gene have 4.81 times greater chance of late-onset PTB compared to carriers of the G/G and A/G genotypes in the recessive inheritance model. The presence of the G/G genotype in the recessive inheritance model compared with the G/A and A/A genotypes for the rs1800896 of the IL-10 gene represents a potentially protective factor, with mothers in the term-birth group having an almost 2-fold lower odds of PTB in general and an almost 10-fold lower odds of early PTB. On the other hand, carriers of the A/G genotype of rs1800896 have a 1.54-fold higher chance of preterm birth in general and a 1.6-fold higher chance of late preterm birth in the super dominant inheritance model compared to the A/A and G/G genotypes in the group of mothers with PTB. In this study, no association was found between PTB and rs1800796 of the IL-6 gene. Conclusion: rs1800629 in mothers was associated with PTB. rs1800896 shows a potentially protective effect for the occurrence of PTB in this study. No association was found between PTB and rs1800796.

Satellite-based remote sensing technologies are utilized extensively to investigate urban thermal environments under rapid urban expansion. Current MODIS data is, however, unable to adequately represent the spatially detailed information because of its relatively coarser spatial resolution, while Landsat data can’t explore temporally the refined analysis due to the low temporal resolution. In order to resolve this situation, we used MODIS and Landsat data to generate “Landsat-like” data by using the flexible spatiotemporal data fusion method (FSDAF), and then studied spatiotemporal variation of land surface temperature (LST) and its driving factors. The results showed that 1) The estimated “Landsat-like” data have high precision; 2) By comparing 2013 and 2016 datasets, LST increases ranging from 1.8°C to 4°C were measurable in areas where the impervious surface area (ISA) increased, while LST decreases ranging from -3.52°C to -0.70°C were detected in areas where ISA decreased; 3) LST has a strongly negative relationship with the Normalized Difference Vegetation Index (NDVI), and a strongly positive relationship with Normalized Difference Built Index (NDBI) in summer; and 4) LST is well correlated with Building density (BD), in a complex conic mode, and LST may increase by 0.460°C to 0.786°C when BD increases by 0.1. Our findings can provide information useful for mitigating undesirable thermal conditions and for long-term urban thermal environmental management.

Eating and drinking difficulties are common in dementia, but little is known about the experiences of ethnic minority groups managing these difficulties at home. We undertook qualitative semi-structured interviews, exploring the meaning of food, the impact of dementia on eating and drinking and carers’ experiences of support. Interviews were audio-recorded and transcribed verbatim. We interviewed 17 carers and people with dementia from ethnic minority backgrounds, using reflexive thematic analysis to analyse data. Food/drink had strong links to identity, culture and emotions. Providing culturally familiar foods, celebrating traditional festivals and supporting previous food-related roles promoted reminiscence, which encouraged people with dementia to eat and drink, as did social interactions. However, these strategies sometimes led to distress in those with more advanced dementia. Food choices were also influenced by carer strain, generational differences and the impact of health conditions. Despite a strong sense of duty to care for relatives at home, there was low awareness of community support services. Carers expressed a need for culturally tailored support for managing dementia-related eating and drinking difficulties at home. Healthcare professionals must provide contextually relevant advice to carers, being mindful of how cultural backgrounds can affect dietary choices.

Myelination, the process of forming a myelin sheath around nerve fibers, is critical not only during early development but also throughout adulthood. This article explores the multifaceted impacts of myelination on the adult brain, highlighting its importance in cognitive functions, neurological health, and overall brain efficiency. In adults, efficient myelination enhances information processing speed, supports memory consolidation, and contributes to cognitive reserve, potentially delaying the onset of neurodegenerative diseases. Myelination ensures synchronized neural activity and energy-efficient brain function, playing a key role in complex cognitive tasks and coordination. Despite a slower rate of plasticity compared to early development, the adult brain retains the ability to adapt and learn, with myelination facilitating these processes. This article also draws parallels between myelination in the brain and learning curves in deep learning Perceptrons, emphasizing how reduced stimulation and experience can significantly slow down cognitive and learning processes. Additionally, the clinical implications of myelination are discussed, including its role in multiple sclerosis and age-related cognitive decline, along with strategies to maintain and enhance myelin health through lifestyle choices and emerging pharmacological interventions. Understanding the ongoing significance of myelination in the adult brain, and its comparison to artificial neural networks, is crucial for developing interventions to support cognitive health and mitigate neurological disorders.

This study presents two interconnected mathematical models: one describing the stability and bifurcation dynamics of ecological biomes, and another simulating the progressive deformation and structural failure of a toroidal object. Both models explore topological changes in complex systems, bridging concepts from ecology, materials science, and mathematical physics. The first part introduces a dynamic model of ecological biomes, incorporating seasonal oscillations and external pressures. We define equations for topology updates, seasonal effects, and pressure impacts, culminating in a bifurcation condition that represents a critical shift in the biome's equilibrium state. This model provides insights into the resilience and tipping points of ecological systems under varying environmental stresses.The second part extends these concepts to a three-dimensional toroidal structure. We present parametric equations describing the torus geometry and develop a time-dependent deformation model that includes both stochastic and deterministic elements. A novel twisting deformation component enhances the realism of the structural changes. We define a critical threshold for maximum displacement, beyond which the torus undergoes structural failure, analogous to the bifurcation point in the biome model. Both models are implemented computationally, providing visual representations of the systems' evolution over time. The biome model illustrates the path to and consequences of bifurcation, while the torus simulation depicts the stages of deformation leading to structural break. This work contributes to the understanding of topological changes and critical transitions in both ecological and physical systems. By presenting these models in parallel, we highlight the universal nature of stability, bifurcation, and failure across different domains. The methodologies presented here have potential applications in ecology, materials science, structural engineering, and theoretical physics, offering a framework for studying the limits of system integrity under stress.

This small article examines the pivotal roles of redundant and degenerate neural networks in the brain across three critical dimensions: evolutionary development, early childhood neural formation, and their implications in neurological diseases. Redundant networks, characterized by parallel neural pathways with similar functions, provide a foundation for cognitive resilience, ensuring continuity of brain functions despite damage or developmental anomalies. Degenerate networks, comprising structurally varied but functionally equivalent pathways, contribute to cognitive flexibility and adaptability, essential for innovative problem-solving and learning. From an evolutionary perspective, these networks have been instrumental in the brain's adaptation to diverse environmental challenges, facilitating cognitive maximization and the development of complex behaviors. The genetic underpinnings and environmental influences that shaped these networks are explored, highlighting their contribution to the evolutionary success of the human species. In the realm of early childhood development, the formation and reinforcement of these networks are crucial. The brain's plasticity during this period leads to the establishment of robust redundant networks and versatile degenerate networks, shaped significantly by environmental stimuli and learning experiences. This developmental phase lays the groundwork for cognitive abilities and resilience to neurological challenges later in life. Furthermore, the paper delves into the implications of these networks in the context of brain diseases. The disruption of the equilibrium between redundancy and degeneracy is linked to various neurological conditions, including Alzheimer's disease, Parkinson's disease, multiple sclerosis, stroke and Huntington's disease. Understanding the roles and balances of these networks offers insights into the pathophysiology of these diseases and potential therapeutic approaches. This review underscores the significance of redundant and degenerate neural networks in the evolutionary context, their critical formation during early childhood, and their profound impact on brain health and disease. It highlights the need for further research into these networks to enhance our understanding of brain function and to develop targeted interventions for neurological disorders.

This study aims to refine our understanding of evolutionary processes, particularly as they apply to complex organisms, using an innovative graph-based simulation approach. We model the topological evolution of simple (5-node ring graph) and complex (20-node dense random graph) organisms over 10 generations, applying different mutation rates to reflect biological realities. Our results provide intriguing insights into the potentially different evolutionary dynamics at play in simple versus complex organisms. While simple organisms demonstrate high topological flexibility and rapid adaptability, aligning with classical evolutionary models, complex organisms exhibit a surprising degree of structural stability. This stability persists even under mutation rates that would typically drive significant changes in simpler systems. The simulation highlights an important consideration: the intricate, interdependent networks characteristic of complex organisms may create a form of evolutionary buffering. This buffering could modulate the impact of random mutations and natural selection – processes that are cornerstones of evolutionary theory. Our findings suggest that the high degree of complexity in advanced life forms may necessitate a more nuanced view of how evolutionary processes operate across different levels of biological organization. Furthermore, the emergence of new structural motifs in simple organisms, contrasted with the relative conservation in complex topologies, indicates that evolutionary mechanisms may manifest differently across the spectrum of biological complexity. This observation invites a more detailed exploration of how evolutionary principles apply to diverse life forms.These results contribute to the ongoing refinement of evolutionary theory, especially in its application to complex organisms. They suggest that additional mechanisms, such as constrained mutations, epigenetic changes, or higher-order organizational principles, may play significant roles alongside random mutations and natural selection in the evolution of complex life forms.

A facilitative transport system exists on the blood brain barrier (BBB) that has been tacitly assumed to be a path for glutamate entry to brain. But glutamate is a non-essential amino acid whose brain content is much greater than plasma, and studies in vivo show that glutamate does not enter brain in material quantities except in those small regions with fenestrated capillaries (circumventricular organs). The situation became understandable when luminal (blood facing) and abluminal (brain facing) membranes were isolated and studied separately. Facilitative transport of glutamate and glutamine exist only on the luminal membranes whereas Na+-dependent transport systems for glutamate, glutamine and some other amino acids are present only on the abluminal membrane. The Na+-dependent cotransporters of the abluminal membrane are in a position to actively transport amino acids from the extracellular fluid (ECF) into the endothelial cells of the BBB. These powerful secondary active transporters couple the energy of the Na+-gradient to move glutamate and glutamine into the ECF whereupon glutamate can exit to blood on the luminal facilitative glutamate transporter. Glutamine may also exit brain on a separate facilitative transport system that exists on the luminal membranes or glutamine can be hydrolyzed to glutamate within the BBB thereby releasing ammonia that is freely diffusible. The γ-glutamyl participate cycle participates indirectly by producing oxoproline (pyroglutamate) that stimulates almost all secondary active transporters yet discovered in the abluminal membranes of the BBB.

This article explores the intricate dynamics of complexity and emergence through the lens of a graphical model representing hippocampal functions. Utilizing a series of overlapping curves that intersect at varying degrees and frequencies, we create a visual metaphor for the sophisticated processes to store information observed in the hippocampus. This model not only depicts the spatial and frequency-related interactions of these curves but also illustrates the emergent patterns that arise from these interactions. These patterns exemplify the principles of complexity and emergence, where the collective behavior of simple elements results in intricate and unexpected outcomes. This graphical representation serves as a bridge between the abstract mathematical concepts of complexity theory and the tangible biological processes observed in neuroscience. By drawing parallels to the hippocampus, known for its role in memory formation and spatial navigation, the article sheds light on how complex systems, such as neural networks, exhibit properties that are more than just the sum of their parts. The model thus offers a unique perspective on understanding complex systems, not only in neuroscience but in broader scientific inquiries where complexity and emergent phenomena are pivotal.

Multiple Sclerosis (MS) is a chronic autoimmune disorder characterized by the demyelination of neural fibers in the central nervous system. Understanding the impact of demyelination on neural network efficiency is crucial for elucidating the pathophysiological mechanisms underlying MS. This study aims to model the effects of demyelination on neural network efficiency, specifically focusing on how increased resistance and path lengths due to demyelination correlate with the clinical symptoms of MS. We employed a graph-theoretical approach to simulate neural networks, introducing varying degrees of demyelination. The demyelination was represented by increasing the resistance (weights) of selected edges within the network, affecting both random and clustered distributions of network connections. The primary metric analyzed was the average shortest path length, indicative of network efficiency. The models demonstrated a significant increase in the average shortest path length in demyelinated networks compared to intact ones. Specifically, networks with clustered demyelination exhibited localized inefficiencies, correlating with the focal nature of MS lesions. The increase in path length was associated with reduced signal transmission efficiency, providing insights into a range of MS symptoms including motor and sensory impairments, cognitive dysfunction, visual disturbances, and fatigue. The graph-theoretical model of neural network demyelination offers a novel perspective on how structural changes in the brain's connectivity due to MS can lead to diverse clinical manifestations. While the model simplifies the complexity of neural networks, it underscores the potential of computational approaches in understanding and predicting the course of neurological disorders like MS.

This study explores the intriguing phenomenon of action potentials reverberating and propagating in high-resistance tissues, such as gliosis, leading to the emergence of short circuits within the brain. Gliosis, characterized by increased tissue resistance, presents a unique environment for electrical signals. My research investigates the possible mechanisms behind these reverberations and their role in the creation of self-empowering short circuits that can potentially affect the entire brain's functionality. Understanding these processes may have significant implications for the treatment and management of neurological disorders associated with gliosis and abnormal electrical activity in the brain.

This project aims to simulate and analyze population dynamics in evolutionary systems, using stochastic differential equations and probabilistic rules for crossbreeding and benefits. The study employs advanced computational techniques to model the evolution of populations over an extended period. Specifically, we explore a scenario with ten distinct groups, each starting with an equal population and evolving under defined genetic and cooperative behaviors. The simulation spans 1000 years, incorporating individual lifespans, stochastic updates, and probabilistic interactions. To ensure robustness and reliability, the study includes detailed statistical analysis, encompassing descriptive statistics, confidence intervals, and ANOVA tests. We further visualize the temporal behavior of populations and subpopulations, providing insights into the evolutionary dynamics and stability of the system. The results demonstrate the effectiveness of balanced cooperation and genetic diversity in maintaining stable population distributions. The project showcases the integration of mathematical modeling, statistical analysis, and computational simulations, contributing valuable insights into evolutionary biology and complex systems. It highlights the importance of interdisciplinary approaches in understanding and predicting population behaviors, with implications for both theoretical research and practical applications in fields such as ecology, genetics, probability and social sciences.

Psychiatric disorders, characterized by complex and fluctuating patterns of thoughts, emotions, and behaviors, can be effectively modeled and visualized using mathematical wave equations. This study explores the representation of three major psychiatric conditions— Psychosis, Bipolar Disorder and Obsessive Compulsive Disorder (OCD)—through the application of differential equations, damping factors, and noise perturbations. Psychosis is modeled using Lissajous figures with high-frequency components, damping, and noise, symbolizing the irregular and erratic thought patterns characteristic of this condition. The inclusion of random perturbations and varying frequencies illustrates the chaotic and unpredictable nature of psychotic episodes, while damping effects reflect the temporary reductions in symptom intensity. For bipolar disorder, a system of partial differential equations simulates the cyclical nature of manic and depressive episodes. The model captures high-energy manic phases with periodic disturbances and the subsequent transition to lower-energy depressive states through damping effects. This representation highlights the oscillatory behavior and recurring episodes inherent to bipolar disorder. OCD is represented with Circumferential Complex Equations in Mult directions. The resulting graphical representations provide intuitive visual insights into the dynamics of these psychiatric disorders. By leveraging wave equations and mathematical modeling, this approach offers a novel perspective on understanding and analyzing the complex behaviors associated with OCD, bipolar disorder and psychosis. This method not only aids in the conceptualization of psychiatric phenomena but also underscores the potential of mathematical tools in the study of mental health conditions.

Attention-Deficit/Hyperactivity Disorder (ADHD) exhibits a notable prevalence across diverse populations, with estimates ranging from 4% to 6%. This wide range prompts an investigation into the evolutionary and genetic underpinnings of ADHD, especially considering the markedly different environments faced by ancestral human populations compared to today's structured societies. This study examines the potential adaptive advantages of ADHD-associated traits in hunter-gatherer contexts, where hyperactivity, impulsivity, and novelty-seeking behaviors may have conferred survival benefits. We employ the principles of population genetics, including Hardy-Weinberg equilibrium, selection coefficients, and genetic drift, to model the dynamics of ADHD allele frequencies over time. Additionally, we discuss balancing selection as a mechanism for maintaining genetic diversity and how gene-environment interactions (GxE) contribute to the expression of ADHD in contemporary settings. Our analysis suggests that traits associated with ADHD, while potentially maladaptive in modern structured environments, could have been preserved through evolutionary processes due to their adaptive value in ancestral contexts. Understanding these dynamics provides a comprehensive view of ADHD's prevalence and highlights the significance of genetic and environmental interplay in shaping human behavior.

Quantum-dot cellular automata (QCA) is an emerging transistor-less field-coupled nanocomputing (FCN) approach to ultra-scale ‘nanochip’ integration. In QCA, to represent digital circuitry, electrostatic repulsion between electrons and the mechanism of electron tunnelling in quantum dots are used. QCA technology can surpass conventional complementary metal-oxide semiconductor (CMOS) technology in terms of clock speed, reduced occupied chip area, and energy efficiency. To develop QCA circuits, irreversible majority gates are typically used as the primary components. Recently, some studies have introduced reversible design techniques, using reversible majority gates as the main building block, to develop ultra-energy efficient QCA circuits. However, this approach resulted in time delays, an increase in the number of QCA cells used, and an increase in the chip area occupied. This work introduces a novel hybrid design strategy employing QCA irreversible, reversible, and partially reversible gates to establish an optimal balance between power consumption, delay time, and occupied area. The hybrid technique allows the designer to have more control over the circuit characteristics to meet different system needs. A combination of reversible, irreversible, and innovative partially reversible majority gates is used in the proposed hybrid design method. We have evaluated the hybrid design method by examining the half-adder circuit as a case study. We have developed four hybrid QCA half-adder circuits, each of which simultaneously incorporates various types of majority gates. The QCADesigner-E 2.2 simulation tool was used to simulate the performance and energy efficiency of the half-adders. This tool provides numerical results for the circuit input/output response and heat dissipation at the physical level, within a microscopic quantum mechanical model.

This study presents a novel approach to understanding evolutionary dynamics through topological analysis of genotypic structures. We model the genome of a simple organism as a topological torus undergoing mutations at a constant rate of 1% per generation. Employing persistent homology and other topological data analysis techniques, we investigate how these mutations influence the overall topology of the genomic structure over time. Our simulations reveal that specific critical mutations lead to significant changes in the homotopic and homologic properties of the torus. We interpret these topological shifts as potential markers for the formation of new subspecies. By identifying the precise points of topological "breaks" within the toroidal genomic representation, our model provides a quantitative framework for observing the incremental transformations that underpin major evolutionary developments. The results offer new insights into the thresholds of speciation and adaptation, demonstrating how gradual genetic changes can accumulate to produce qualitative shifts in organismal traits. This approach bridges the gap between microscopic genetic mutations and macroscopic evolutionary outcomes, potentially revolutionizing our understanding of evolutionary processes. Our findings have implications for various fields, including theoretical biology, genetic engineering, and conservation biology. The model provides a novel perspective on genetic resilience and adaptability, offering a foundation for future research on the relationship between genomic topology and evolutionary trajectories. It also emphasizes the innovative nature of the research and its potential impact on multiple fields of study.

This study presents a computational simulation to explore the distinctive patterns of neural connectivity in Autism Spectrum Disorder (ASD), focusing on the concepts of spatial and topological proximities. ASD is characterized by unique cognitive and behavioral profiles, often attributed to atypical neural development and connectivity. Our simulation employs a two-pronged approach: first, by modeling spatial proximity through the generation of clustered 3D node positions, we mimic the observed over-connectivity in localized brain regions in ASD. Second, we construct a topological network to represent the complex interplay of under-connectivity and over-connectivity in functional brain networks, a hallmark of ASD's neural landscape. The spatial model demonstrates pronounced clustering, reflecting the structural brain differences and atypical growth patterns reported in neuroimaging studies of individuals with ASD. In contrast, the topological model reveals a network with a mix of sparse and dense connections, simulating the diverse and often contradictory findings of functional connectivity in ASD, such as reduced long-range connections and increased local connections. Our simulation provides a visual and conceptual framework for understanding the altered neural connectivity in ASD. It underscores the importance of considering both physical (spatial) and functional (topological) aspects of brain connectivity to grasp the full extent of neurodevelopmental deviations in ASD. This approach not only aids in elucidating the neural underpinnings of ASD's core symptoms but also offers a foundation for developing targeted interventions. Future research, integrating more complex and individual-specific data, could further refine this model, enhancing our understanding of ASD's neural dynamics and contributing to personalized therapeutic strategies.

The establishment of a well characterized non-human primate model of Zika virus (ZIKV) infection is critical for the development of medical interventions. In this study, challenging Indian rhesus macaques (IRMs) with ZIKV strains of the Asian lineage resulted in dose dependent peak viral loads between days 2 and 5 post infection; and a robust immune response which protected the animals from homologous and heterologous re-challenge. In contrast, viremia in IRMs challenged with an African lineage strain was below the assays lower limit of quantitation and the immune response was insufficient to protect from re-challenge. These results corroborate previous observations but are contrary to reports using other African strains obviating the need for additional studies to elucidate the variables contributing to the disparities. Nonetheless, the utility of an Asian lineage ZIKV IRM model for countermeasures development was verified by vaccinating animals with a formalin inactivated reference vaccine and demonstrating sterilizing immunity against a subsequent subcutaneous challenge.

Comparative analysis of mortality rates between public and private healthcare systems remains a critical yet complex area of study. This article synthesizes findings from extensive academic literature and empirical studies to examine the relationship between healthcare system type and patient outcomes across various countries. By focusing on mortality rates as a key indicator, we elucidate the nuanced impacts of public versus private healthcare delivery. Our analysis reveals the multifaceted challenges inherent in both systems and their implications for patient survival. We conclude by identifying crucial gaps in current research and proposing policy recommendations to optimize healthcare outcomes in diverse global contexts.This revised abstract:Starts with a strong opening statement that immediately captures the topic's importance. Clarifies the article's methodology (synthesizing existing literature and studies).Specifies the focus on mortality rates as the primary outcome measure.Hints at the complexity of the findings, avoiding oversimplification.Ends with a clear statement about the article's contributions to both research and policy.

DNA double-strand breaks (DSBs) trigger the Ataxia telangiectasia mutated (ATM)-dependent DNA damage response (DDR), which consists of histone H2AX, MDC1, RNF168, 53BP1, PTIP, RIF1, Rev7, and Shieldin. Early stages of B and T lymphocyte development are dependent on recombination activating gene (RAG)-induced DSBs that form the basis for further V(D)J recombination. Non-homologous end joining (NHEJ) pathway factors recognize, process, and ligate DSBs. Based on numerous loss-of-function studies, DDR factors were thought to be dispensable for the V(D)J recombination. In particular, mice lacking Mediator of DNA Damage Checkpoint Protein 1(MDC1) possessed nearly wild-type levels of mature B and T lymphocytes in the spleen, thymus, and bone marrow. NHEJ factor XRCC4-like factor (XLF)/Cernunnos is functionally redundant with ATM, histone H2AX, and p53-binding protein 1 (53BP1) during the lymphocyte development in mice. Here, we genetically inactivated MDC1, XLF, or both MDC1 and XLF in murine vAbl pro-B cell lines and, using chromosomally integrated substrates, demonstrated that MDC1 stimulates the V(D)J recombination in cells lacking XLF. Moreover, combined inactivation of MDC1 and XLF in mice resulted in synthetic lethality. Together, these findings suggest that MDC1 and XLF are functionally redundant during the mouse development, in general, and the V(D)J recombination, in particular.

Attention-Deficit/Hyperactivity Disorder (ADHD) is traditionally conceptualized within a framework emphasizing deficits in attention regulation and executive function. However, emerging evidence from the fields of predictive coding and active inference offers a novel lens through which to understand ADHD not merely as a disorder of attention but as a distinctive mode of neurodevelopmental variation. This article synthesizes current research and theoretical models to propose a redefined understanding of ADHD. By integrating insights from Ryan Smith, Paul B. Badcock, and Karl J. Friston (2020), we explore the premise that individuals with ADHD exhibit unique differences in how their brains generate and update predictions about the environment, leading to the characteristic behavioral patterns observed in ADHD. We argue that ADHD involves a divergence in the brain's predictive models and its ability to minimize prediction error, impacting sensory processing, attention allocation, and motor control. This perspective illuminates the adaptive aspects of ADHD, suggesting that what are often labeled as deficits could also reflect an adaptive fit to certain environmental contexts, underscoring the role of neurodiversity in human evolution. Furthermore, we discuss the implications of this reconceptualization for clinical practice, including diagnosis, treatment, and support for individuals with ADHD, emphasizing approaches that align with their unique neurocognitive profiles. This article calls for a shift in the narrative surrounding ADHD, advocating for a model that appreciates the complexity and adaptiveness of neurodevelopmental diversity.

Computational neuroscience has undergone a significant transformation in recent years, driven by the exponential growth of neural data and advancements in data science and machine learning. While traditional theoretical models remain valuable, there is a growing emphasis on integrating data-driven approaches to develop more accurate, biologically plausible, and predictive models of neural function. This shift has led to a new equilibrium in the field, where data-driven model development, machine learning techniques, and hybrid approaches that combine data and theory are increasingly prevalent. In this article, we discuss the evolving landscape of computational neuroscience, highlighting the importance of data-driven methods and the emergence of a more integrative approach that leverages both data and theory to unlock the mysteries of the brain. We also explore the implications of this shift for future research and clinical applications, emphasizing the potential for data-driven computational neuroscience to revolutionize our understanding of neural function and pave the way for new treatments for neurological disorders.

The complex dynamics of the neocortex, the outermost layer of the brain, have been a subject of intense research in neuroscience. Recent studies have suggested that magnetic fields generated by neuronal activity may play a significant role in neocortical dynamics. This paper presents a simplified mathematical model that explores the hypothesized interactions between magnetic dynamos, nondissipative systems, Hamiltonian equations, and the Lorenz force in the context of neocortical dynamics. The proposed model is based on a set of coupled Hamiltonian equations inspired by the Lorenz system, a well-known chaotic dynamical system. The generalized coordinates in the model represent the magnetic field components, while the generalized momenta are related to the electric field components or other relevant quantities. The Hamiltonian equations describe the conservative dynamics of the system, and the coupling terms in the equations are interpreted as representing the interactions between the magnetic and electric field components, analogous to the Lorenz force in electromagnetism. The model is implemented using Python, and the Hamiltonian equations are numerically solved using the odeint function from the scipy.integrate module. The resulting dynamics of the magnetic field components are visualized using matplotlib. While the model is highly simplified and does not capture the full complexity of neocortical dynamics, it serves as a starting point for investigating the potential role of magnetic dynamos and Lorenz force interactions in the brain. The paper discusses the limitations of the current model and highlights the need for further refinements, such as incorporating more realistic biological constraints, considering energy dissipation and compensation mechanisms, and validating the model against experimental data. Future work should focus on developing a more comprehensive and biologically plausible model that integrates the latest findings from neuroscience, physics, and computational modeling. By presenting this simplified Hamiltonian model, the paper aims to stimulate further research and discussion on the potential significance of magnetic dynamos and Lorenz force interactions in neocortical dynamics. The model provides a framework for exploring these hypothesized mechanisms and may guide future experimental and theoretical investigations in this emerging field of neuroscience

This paper presents data supporting the IC Regimen for potentiating the effectiveness of lorlatinib in treating ALK positive cancers, and specifically non-small cell lung cancer. Lorlatinib is an effective treatment for ALK driven non-small cell lung cancer and other ALK driven cancers. Lorlatinib inhibits ALK kinase and achieves good brain tissue levels, a common site for metastases in lung cancers. However, resistance to lorlatinib usually supervenes and the cancer awakens and starts growing again, resistant to lorlatinib. This paper analyses data indicating that adding two common generic drugs, itraconazole and cilostazol, to lorlatinib treatment may delay resistance development. Itraconazole is marketed worldwide as a generic antifungal drug that also inhibits Hedgehog signaling, CYP3A4, and the p-gp efflux pump. Cilostazol is a generic anti-thrombosis, phosphodiesterase 3 inhibiting drug that carries minimal bleeding risk. Cilostazol may enhance lorlatinib by deprivation of trophic growth factors supplied by platelets. Itraconazole may enhance lorlatinib effectiveness by reducing or stopping a Hedgehog centered amplifying feedback loop with ALK kinase. The combination of metastatic non-small cell lung cancer being a low-survival disease and the general safety itraconazole plus cilostazol augmentation, make a clinical trial of this trio worthwhile.

The intricate architecture of dendritic arborization is fundamental to the formation and functionality of neural networks, serving as the primary site for synaptic integration and signal propagation. This study presents a pioneering computational model that simulates dendritic growth dynamics, employing exponential and logarithmic scaling over an extended developmental period of 720 days. This model offers a valuable tool for investigating the implications of diverse dendritic growth patterns on neural development, synaptic connectivity, and ultimately, cognitive functions. The computational framework incorporates biologically plausible parameters, allowing for the systematic exploration of dendritic branching patterns and their potential impact on neuronal information processing. By simulating exponential and logarithmic growth scales, the model captures the inherent complexity and diversity of dendritic morphologies observed in various neuronal populations across different brain regions. The findings from this study hold significant implications for our understanding of neural circuit assembly, synaptic integration, and the potential functional consequences of aberrant dendritic growth patterns observed in neurodevelopmental disorders. Furthermore, the model's ability to simulate extended developmental trajectories over a prolonged period of 720 days offers insights into the dynamic interplay between dendritic growth and synaptic pruning, which is crucial for the refinement and optimization of neural networks.

Tumid Lupus Erythematosus has been the subject of heated debate as to its correct nosographic classification. In particular, its definition has changed over time, depending on the different studies performed. In this review we address the initial definition of TLE, the changes that have taken place in the understanding and placement within the classification of Lupus Erythematosus (LE), and focus on clinical, histopathological, immunophenotypical and differential diagnosis aspects.

Autism spectrum disorder (ASD) is a common condition with lifelong implications and a strong hereditary component suggesting genetic underpinnings. The last decade has seen dramatic improvements in DNA sequencing and related bioinformatics and databases. We analyzed the raw DNA sequencing files on the Variantyx® bioinformatics platform for the last 50 ASD patients evaluated with trio whole genome sequencing (trio-WGS). “Qualified” variants were defined as coding, rare, and evolutionarily conserved. Primary Diagnostic Variants (PDV) additionally were in genes directly linked to ASD and matched clinical correlation. A PDV was identified in 34/50 (68%) of cases, including 25 (50%) cases with heterozygous de novo and 10 (20%) with inherited variants. De novo variants in genes directly associated with ASD were far more likely to be Qualifying than non-Qualifying versus a control group of genes not associated with ASD (P = 0.0002, odds ratio 29), validating that most are indeed disease related. Only 14/34 (41%) of PDV cases had the variant listed on the laboratory report, and reanalysis increased diagnostic yield from 28% to 68%. Variants that we assigned as PDVs yet not on the report were predominately de novo in genes not yet reported as ASD associated. Many subjects both with and without a PDV had inherited Qualifying variants in known ASD-associated genes, suggesting polygenic inheritance. Thirty-three subjects (66%) had treatment recommendation(s) based on DNA analyses. Our results demonstrate high yield of trio-WGS for revealing molecular diagnoses in ASD that is greatly enhanced by re-analyzing DNA sequencing files. In contrast to previous reports, de novo variants dominate the findings, mostly representing novel conditions. This has implications to the cause and rising prevalence of autism.

Accelerated degradation of collagen membranes (CMs) in diabetic rats is associated with increased infiltration of macrophages and blood vessels. Since pre-implantation immersion of CMs in cross-linked high molecular weight hyaluronic acid (CLHA) delays membrane degradation, we evaluated its effect on the number of macrophages and endothelial cells (ECs) within the CM. Diabetes was induced with streptozotocin in 16 rats, while 16 healthy rats served as control. CM discs were labeled with biotin, soaked in CLHA or PBS and implanted under the scalp. Fourteen days later, CMs were embedded in paraffin and the number of macrophages and ECs within the CMs was determined using antibodies against CD68 and Transglutaminase II, respectively. Diabetes increased the number of macrophages and ECs within the CMs (∼2.5-fold and 4-fold, respectively). Immersion of CMs in CLHA statistically significantly reduced the number of macrophages (p<0.0001) in diabetic rats, but not that of ECs. In the healthy group, CLHA had no significant effect on the number of either cells. Higher residual collagen area and membrane thickness in CLHA-treated CMs in diabetic animals were significantly correlated with reduced number of macrophages but not ECs. Immersion of CM in CLHA inhibits macrophage infiltration and reduces CM degradation in diabetic animals.

In the global carbon cycle, atmospheric carbon emissions, both ‘natural’ and anthropogenic, are balanced by carbon uptake (i.e. sequestration) that mostly occurs via photosynthesis, plus a much smaller proportion via geological processes. Since the formation of the Earth about 4.54 billion years ago the ratio between emitted and sequestered carbon has varied considerably with atmospheric CO₂ levels ranging from 100,000 ppm to a mere 100 ppm. Over this time, a huge amount of carbon has been sequestered due to photosynthesis and essentially removed from the cycle, being buried as fossil deposits of coal, oil and gas. Relatively low atmospheric CO₂ levels were the norm for the past 10 million years, and during the past million years they averaged about 220 ppm. More recently, the Holocene epoch, starting ~11,700 years ago, has been a period of unusual climatic stability with relatively warm, moist conditions and low atmospheric CO₂ levels of between 260 and 280 ppm. During the Holocene, stable conditions facilitated a social revolution with domestication of crops and livestock leading to urbanisation and development of complex technologies. As part of the latter process, immense quantities of sequestered fossil carbon have recently been used as energy sources, resulting in a particularly rapid increase in CO₂ emissions after 1950 CE to the current value of 424 ppm, with further rises to >800 ppm predicted by 2100. This is already perturbing the previously stable Holocene climate and threatening future food production and social stability. Today, the global carbon cycle has been shifted such that carbon sequestration is no longer keeping up with recent anthropogenic emissions. In order to address this imbalance it is important to understand the roles of high-capacity carbon sequestration systems, such as natural forests and tropical croplands, and to devise strategies to facilitate net CO₂ uptake.

J/ψ, a charmonium bound state made of a charm and an anti-charm quark, has been discovered in the 1970s and confirmed the quark model. Because the mass of charms quarks is significantly above the Quantum Chromodynamics (QCD) scale ΛQCD, charmonia are considered as excellent probes to test perturbative Quantum Chromodynamics (pQCD) calculations. Over the past decades, they have been studied extensively at different high energy colliders. However, their production mechanisms, which involves multiple scales, are still not very well understood. Recently, in high multiplicity p+p collisions at RHIC and at the LHC, a significant enhancement of J/ψ production yield has been observed, which suggests a strong contribution from the Multi-Parton Interaction (MPI). This is different from the traditional pQCD picture where charm quark pairs are produced from a single hard scattering between partons in p+p collisions. In this work, we will report the J/ψ normalized production yield as a function of normalized charged particle multiplicity over a board range of rapidity and event multiplicity in the J/ψ→μ+μ− channel with PHENIX Run 15 p+p data at \sqrt{s}=200 GeV. The results are compared with PYTHIA 8 simulations with the MPI option on and off. Finally, the outlooks of J/ψ in p+Au and Au+p collisions along with Color Glass Condensate (CGC) predictions and of multiplicity dependent ψ(2S)/J/ψ ratio in p+p data will be briefly discussed.

The Flack Parameter is now almost universally reported for all chiral materials characterized by X-ray crystallography. It’s elegantly simplicity was an inspired development by Flack, and although the original algorithm for its computation has been strengthened by other workers, it remains an essential outcome for any crystallographic structure determination. As with any one-parameter metric, it needs to be interpreted in the context of its standard uncertainty.

Simulated crime scene investigation is an essential component of forensic science education, but its implementation poses challenges relating to cost, accessibility and breadth of experience. Virtual reality (VR) is an emerging technology which offers exciting prospects for teaching and learning, especially for imparting practical skills. We document here a multidisciplinary experimental study in which a bespoke VR crime scene app was designed and implemented, after which it was tested by both undergraduate student and staff/postgraduate student cohorts. Through both qualitative and quantitative analyses, we demonstrate that VR applications support learning of practical crime scene processing skills. VR-based practical sessions have the potential to add value to forensic science courses through offering cost-effective practical experience and the ability to work in isolation, in a variety of different scenarios. Both user groups reported high levels of satisfaction with the process and reports of adverse effects (motion sickness) were minimal. With reference to user feedback, we proceed to evaluate the scalability and development challenges associated with large-scale implementation of VR as an adjunct to forensic science education.

Driven by the growing interest of the scientific community and the proliferation of research in this field, cranial implants have seen significant advancements in recent years regarding design techniques, structural optimisation, appropriate material selection and fixation system method. Custom implants not only enhance aesthetics and functionality but are also crucial for achieving proper biological integration and optimal blood irrigation, critical aspects in bone regeneration and tissue health. This research aims to optimize the properties of implants designed from triply periodic minimal surface structures. The gyroid architecture is employed for its balance between mechanical and biological properties. Experimental samples were designed varying three parameters of the surface model: cell size, isovalue and shape factor. Computational simulation tools were used for determining the relationship between those parameters and the response variables: the surface area, permeability, porosity and Young modulus. These tools include computer aided design, finite element method and computational fluid dynamics. With the simulated values, the corresponding regression models were fitted. Using the NSGA-II, a multi-objective optimisation was carried out, finding the Pareto set which includes surface area and permeability as targets, and fulfil the constraints related with the porosity and Young modulus. From these non-dominated solutions, the most convenient for a given application was chosen, and an optimal implant was designed, from a patient computed tomography scan. An implant prototype was additively manufactured for validating the proposed approach.

Cardiovascular diseases (CVDs) are the leading cause of death in the globally. Morbidity and disability related to non-fatal events are increasing exponentially. There are several symptoms that may arise after invasive therapeutic approaches such as coronary artery bypass graft (CABG), including chronic pain in anatomical areas connected to the mediastinum; these pains can be found not only initially after surgery, but also years later. We present a case where non-specific neck pain (NNP), in a patient undergoing CABG five years earlier, was approached with an osteopathic technique, working the pericardial area. To the knowledge of the Authors, it is the first case report where osteopathy is associated with a gentle treatment on the pericardial area to resolve a NNP.

The allosteric SERCA (Sarcoplasmic/Endoplasmic Reticulum Ca2+-ATPase) activator CDN1163 has been recently added to the group of pharmacological tools for probing SERCA function. We chose to investigate the effects of the compound on T lymphocyte Ca2+ stores, using the well-described Jurkat T lymphocyte as a reliable cell system for Ca2+ signaling pathways. Our study identified the lowest concentrations of the SERCA inhibitors thapsigargin (TG) and 2,5-di-(tert butyl)-1,4-benzohydroquinone (tBHQ) capable of releasing Ca2+, permitting the differentiation of the TG-sensitive SERCA 2b Ca2+ store from the tBHQ-sensitive SERCA 3 Ca2+ store. We proceeded to test the effects of CDN1163 on Ca2+ stores, examining specific actions on the SERCA 2b and SERCA 3 Ca2+ pools using our low dose SERCA blocker regimen. In contrast to previous work, we find CDN1163 exerts complex time-sensitive and SERCA isoform-specific actions on Ca2+ stores. Surprisingly, short-term exposure (0-30 minutes) to CDN1163 perturbs T cell Ca2+ stores by suppressing Ca2+ uptake with diminished Ca2+ release from the SERCA 2b-controlled store. Concomitantly, we find evidence for a SERCA-activating effect of CDN1163 on the SERCA 3 regulated store, given the observation of increased Ca2+ release inducible by low dose tBHQ. Intriguingly, longer-term (&gt;12 hours) CDN1163 exposure reversed this pattern, with increased Ca2+ release from SERCA 2b-regulated pools, yet decreased Ca2+ release responses from tBHQ-sensitive SERCA 3 pool. Our results reveal differential effects of CDN1163 on Ca2+ stores regulated by distinct SERCA isoforms, prompting the need for careful interpretation of the compound’s effects, particularly in cells expressing multiple SERCA isoforms.

At 2.3 megabases in length, the dystrophin gene is enormous: transcription of a single mRNA requires approximately 16 hours. Principally expressed in skeletal muscle, the dystrophin protein product protects the muscle sarcolemma against contraction-induced injury, and dystrophin deficiency results in the fatal muscle-wasting disease, Duchenne muscular dystrophy. This gene is thus of key clinical interest, and therapeutic strategies aimed at eliciting dystrophin restoration require quantitative analysis of its expression. Approaches for quantifying dystrophin at the protein level are well established, however study at the mRNA level warrants closer scrutiny: measured expression values differ in a sequence-dependent fashion, with significant consequences for data interpretation. In this manuscript we discuss these nuances of expression and present evidence to support a transcriptional model whereby the long transcription time is coupled to a short mature mRNA half-life, with dystrophin transcripts being predominantly nascent as consequence. We explore the effects of such a model on cellular transcriptional dynamics, and then discuss key implications for the study of dystrophin gene expression, focussing both on conventional (qPCR) and next-gen (RNAseq) approaches.

In our investigation of the time evolution of energy states Einstein’s interpretation from more than a century ago is found to have greater internal consistency than that of non-relativistic quantum mechanics. We choose to align more closely with his methods by abandoning the non-relativistic Hamiltonian method, which has been the standard for nearly a century, in favor of a relativistically correct Lagrangian method. Integral equations of motion for the absorption and emission of radiation are derived that underlie and anticipate the differentially motivated Schrödinger equation. This new interpretation applies to a large volume of experimental evidence of both classical and quantum mechanical origin. Among the examples discussed in support are Planck’s law describing black body radiation, matrix mechanics, the function of the simplest quantum mechanical system an electron cyclotron, chaos theory, and evolutionary biology.

Detailed evaluation is provided for the likelihood statistics intrinsic to interlocking Sequential Bayes analysis, which allows estimation of evidential support for dendrograms charting the macroevolution of taxa. It involves complexity functions, such as fractal evolution, to generate well-supported evolutionary trees. Required are data on trait changes from ancestral species to descendant species, which is facilitated by reduction of large genera to monothetic groups (one ancestral species each), most conveniently named as separate genera. Assigning each species one Shannon informational bit per new trait, then adding the traits as sequential Bayesian analysis (each posterior probability used as the prior for the next iteration of Bayes Formula), then interpretation with an odds chart, provides a posterior probability that the ancestor-descendant order is correct, that is, entirely follows evolutionary theory involving adaptation and rarity of total trait reversals. The key fact is that the most recently acquired traits of the ancestral species are selectively inviolate and passed on without change to each descendant species. The details of sequential Bayesian analysis were clarified by calculation of likelihood ratios and Bayes factors that compare optimal models with the next most likely model. Such analysis demonstrated that the optimum arrangement of ancestor and descendant species leads to high support values for fitting evolutionary theory, comparable to statistical support levels reported for molecular evolutionary trees. The fact that phylogenetic analysis does not offer an ancestor-descendant model in is found to be conducive of precision at the expense of accuracy, and leads to wrong ancestor-free models with likelihoods explaining data at high credible levels. The number of advanced traits in the outgroup as a Bayesian prior greatly enhances posterior probability. The method is simple, free of special computer analysis, and well-suited to standard taxonomic practice.

Differences between the quantum mechanical and relativistic concepts of time observed in GPS satellites are accounted for by applying the equivalence principle to the transitioning electron of an atomic clock. This allows a differential equation of motion to be derived for the electron in the Minkowski space between electron shells. By applying Hamilton’s principle we transform the differential equation into a relativistically correct integral equation of motion, the time integral of a Lagrangian. This newly derived equation accounts for the abstract mathematics of the more familiar non-relativistic model by means of a physical interpretation. Abstract rotations in Hilbert space are replaced by real rotations of particle field geometries in Minkowki space that describe the electron transition and emission of a photon. Because the properties of energy are universal the same integral equations are able to be used to describe the time evolution of galaxies despite vast differences in lifetime. The comparison of gravitational and electromagnetic energy exchanges by means of radial and transverse fields leads to an alternative to the standard model that is based on a field model. It explains the observed properties of galaxies as a superposition of neutrinos localized within the horizon of a black hole with spins aligned. The particle properties of free neutrinos are accounted by means of a classical field geometry; specifically, a spin that is oriented in space with rotational inertia due to energy. A test of the standard model is proposed based on differing views for flavor oscillation.

During glioblastoma treatment, the pharmaceutical monoclonal antibody to VEGF, bevacizumab, has improved quality of life and delayed progression for several months but has not, or only marginally prolonged overall survival. In 2017 several dramatic research papers appeared that are crucial to our understanding of glioblastoma vis a vis the mode of action of bevacizumab. As a consequence of these papers, a new, potentially more effective, treatment protocol can be built around bevacizumab. This is the ADZT Regimen where four old drugs are added to bevacizumab. These four are apremilast, marketed to treat psoriasis, dapsone, marketed to treat Hansen’s disease, zonisamide, marketed to treat seizures, and telmisartan, marketed to treat hypertension. The ancillary attributes of each of these drugs has been shown to augment bevacizumab. This paper will detail the research data supporting that contention.