Recent studies have emphasized the influence of resettlement factors on the mental health of refugees resettling in developed countries. However, little research has addressed gender differences in the nature and influence of resettlement stressors and sources of resilience. We address this gap in knowledge by investigating how gender moderates and mediates the influence of several sources of distress and resilience among 259 Afghan refugees residing in northern California. Gender moderated the effects of four factors on levels of distress. Intimate and extended family ties have little correlation with men’s distress levels, but are strongly associated with lower distress for women. English ability is positively associated with lower distress for women, but not men. In terms of gender ideology, traditionally oriented women and egalitarian men have lower levels of distress. And experiencing greater dissonant acculturation increases distress for men, but not women. The influence of gender interaction terms is substantial and patterns may reflect difficulty adapting to a different gender order. Future studies of similar populations should investigate gender differences in sources of distress and resilience, and efforts to assist new arrivals might inform them of changes in gender roles they may experience, and facilitate opportunities to renegotiate gender roles.

Mineral nutrition is essential for plant growth and interaction of plants with biotic and abiotic stresses. Mango twig-tip dieback (MTTD) is a new type of mango decline, but its impact on the trees’ mineral nutrition is unknown. This study was conducted to determine the effect of MTTD infection on the nutrient status, balance, and resorption efficiency (RE) of mango. Leaf nutrient concentrations and deviation from the optimum percentage (DOP) indices of ‘Kensington Pride’ (KP) mango trees with low (LD) and high (HD) levels of MTTD infections were analyzed to compare the foliar nutrition status and nutrient balance between the LD and HD trees. Moreover, the nutrient resorption efficiency of MTTD-infected dried leaves (RE_D) was compared with the resorption efficiency of healthy (RE_S) leaves of KP mangoes. The concentrations of the total Ca, Mg, Cu, Fe, Mn, and Zn were lower in the HD trees than in the LD trees. But the total K content was higher in the HD trees, and its DOP index was sufficient, while the total K concentration was low and deficient level in LD trees. Moreover, DOP indices for total Ca, Mn, and Zn were less deficient in LD trees than in HD trees, and overall nutrient imbalances were exacerbated in HD trees. RE_D was significantly lower than RE_S for the total N, P, S, Cu, Fe, and Zn but significantly higher than RE_S for K. The study underscores the significant influence of MTTD on the mineral nutrition of KP mangoes, revealing distinct nutrient variations between trees with low and high MTTD infection levels. These findings have important implications for mango crop management, emphasizing the need for targeted nutrient interventions to address imbalances induced by MTTD and enhance the overall health and resistance of mango trees against MTTD infection.

Volatile organic compounds (VOCs) released from plants have been correlated with disease-status. Analysis of VOCs using GC-MS is time-consuming, laboratory-based, and requires specialist training. Electronic nose devices (E-nose) provide a portable alternative. Three different E-nose devices were compared to assess how accurately they could detect Mango Twig Tip Dieback and Panama disease in banana. The devices were initially trained on known volatiles, then pure cultures of Pantoea sp., Staphylococcus sp., and Fusarium odoratissimum, and finally, on infected and healthy mango leaves and field-collected, infected banana pseudo-stems. The experiments were repeated three times with six replicates for each host-pathogen pair. The variation between healthy and infected host materials was evaluated by principal component and linear discriminant analysis, cross-validation and chemometric data analysis. GC-MS analysis was conducted contemporaneously and identified an 80% similarity between healthy and infected plant material. The portable C 320 was 100% successful in discriminating known volatiles but had a low capability in differentiating healthy and infected plant substrates. The advanced devices (PEN 3 / MSEM 160) successfully detected healthy and diseased samples with a high variance. The results suggest that E-nose devices are more sensitive and accurate in detecting changes of VOCs between healthy and infected plants compared to headspace GC-MS.

This study investigates the effect of perceived discrimination on the mental health of Afghan refugees, and secondly, tests the distress moderating effects of pre-migration traumatic experiences and post-resettlement adjustment factors. In a cross-sectional design, 259 Afghans completed surveys assessing perceived discrimination and a number of other factors using scales developed through inductive techniques. Multivariate analyses consisted of a series of hierarchical regressions testing the effect of perceived discrimination on distress, followed by a sequential analysis of moderator variables. Perceived discrimination was significantly associated with higher distress, and this relationship was stronger among those with a strong intra-ethnic identity, high civic engagement, and high pre-resettlement traumatic experiences. Discrimination is a significant source of stress for Afghan refugees, which may exacerbate stresses associated with other post-migration stressors. Future research is needed to tailor interventions that can help mitigate the stress associated with discrimination among this highly vulnerable group.

Yaba monkey tumor virus (YMTV) and Tanapox virus (TPV) are members of the Yatapoxvirus genus and can infect humans and other primates. Despite the threat posed by yatapoxviruses, the factors determining their host range are poorly understood. In this study, we analyzed the ability of YMTV and TPV orthologs of vaccinia virus K3 (called 012 in YMTV and TPV), which share 75% amino acid identity with one another, to inhibit PKR from 15 different primate species. We first used a luciferase-based reporter, and found that YMTV and TPV K3 orthologs inhibited PKR in a species-specific manner and showed distinct PKR inhibition profiles. TPV 012 inhibited PKR from 11 primates, including human, substantially better than YMTV 012. In contrast, both K3 orthologs inhibited the other four primate PKRs comparably well. Using YMTV 012 and TPV 012 hybrids, we mapped the region responsible for the differential PKR inhibition to the C- terminus of the K3 orthologs. Next, we generated chimeric vaccinia virus strains to investigate whether TPV K3 and YMTV K3 orthologs could rescue replication of a vaccinia virus strain that lacks PKR inhibitors K3L and E3L. Virus replication in primate-derived cells generally correlated with the patterns observed in the luciferase-based assay. Together, these observations demonstrate that yatapoxvirus K3 orthologs have distinct PKR inhibition profiles and inhibit PKR in a species-specific manner, which may contribute to the differential susceptibility of primate species to yatapoxvirus infections.

Objective: To employ Latent Class Analysis (LCA) to investigate dietary intake patterns among Sudanese children aged 0 to 2 years and to examine the association of these patterns with sociodemographic factors. Methods: This study leveraged the Sudan Multiple Indicator Cluster Survey (MICS) 2014 data to uncover dietary intake patterns among 7,362 children using latent class analysis (LCA). We investigated class memberships concerning demographic and socioeconomic factors. The model's adequacy was determined using several fit indices, including BIC, AIC, entropy, CAIC, and SABIC, providing a holistic evaluation of the model's accuracy in capturing dietary behaviors. Results: Three latent classes were identified: Class 1 (55%) with an average nutrition composition, Class 2 (28%) with limited nutrition composition, and Class 3 (17%) with good nutrition composition. Significant associations were found between latent class membership and sociodemographic factors, particularly mother's education level and household wealth. The three-class solution provided the best balance between model fit and class distinction. Conclusions: The LCA revealed distinct dietary intake patterns and underscored the influence of sociodemographic factors on child nutrition. The findings suggest that targeted nutritional interventions should be developed according to the specific needs of different latent classes. The study also highlights the utility of LCA as a robust statistical and machine learning tool in public health research, capable of informing tailored interventions and policies for improving child nutrition. Implications: The study emphasizes the importance of maternal education and socio-economic status in shaping dietary behaviors of children in Sudan. It implies the need for policies that address educational disparities, food security, and economic development as part of comprehensive nutritional interventions.

Lake sediment records are of great importance for understanding the evolution of watershed environments. Various studies have been carried out to constrain the depositional ages of lake sediments and examine their physical, chemical, and biological characteristics, aiming to construct historical vegetation, environment and climate patterns in Chinese lake watersheds. In this study, we obtained relevant literature on lake sediment records by searching the key word 'age-depth' from the databases – Web of Science and China National Knowledge Infrastructure (CNKI, the largest Chinese academic database). We analyzed the literature based on its type (published in a Chinese/English journal or as a Master’s/PhD thesis), period of publication, journal (if published in a journal), key authors, study area, dating scale, and main aims. The results suggest that the lakes in the plateau regions are the most popular research topic typically covering 100–200 years (short-term) and 500–30,000 years (long-term). The literature focuses on a wide range of topics, from past environmental evolution in the watershed to lake ecology, and provides a solid foundation for better understanding regional climate change and the preservation of lake environments and ecosystems. In the future, resulting data from environmental reconstruction with lake sediments will be needed to integrate with emerging information processing technologies (e.g., artificial intelligence and meta-analysis), to disentangle the complex interplay between Earth surface processes and global climate change; furthermore, strengthening interdisciplinary collaboration will deepen our comprehension of man-land relationship and promote the sustainable management of lake ecosystems in the context of global climate change.

Cardiovascular disease (CVD) and obesity are prevalent public health concerns with grave implications for morbidity and mortality, necessitating tailored interventions. This research explores the utility of fuzzy c-means clustering paired with principal component analysis (PCA) in detecting at-risk groups and personalizing health strategies for these conditions. Fuzzy c-means clustering allows for the dynamic classification of individuals into groups based on unique risk factors and intervention outcomes, while PCA aids in distilling complex data sets to uncover underlying patterns. The conjoined use of these methods has shown promise in identifying diverse risk profiles and in forecasting intervention success rates. The study acknowledges limitations, including possible biases stemming from data set composition and analytical parameter selection. Future research aims to refine these tools for clinical application. The results support implementing fuzzy c-means clustering and PCA for delineating specific target populations for health interventions, emphasizing careful use of these analytical approaches. Subsequent studies should focus on correlating these techniques with concrete clinical results to enhance public health measures.

Changes in hydrology from aridification in the U.S. Southwest have led to tension at the urban-rural divide about conservation and land management strategy. Strain on multi-generational agricultural livelihoods and a nearly 150-year-old Colorado River water adjudication system presents an opportunity for multidisciplinary solutions and symbiotic partnerships. In this study, producers in a small San Juan River headwater community in southwestern Colorado participated in a convergence research study developed collaboratively with community partners, prioritizing local objectives and policy needs. Acknowledging the historic and sometimes perceived role of academic institutions as representing urban interests, our goal was to highlight how research could support rural governance and identify rural interests. Respondents identified water availability and climate changes as the factor that most negatively affects operations. Respondents had interest in nature-based agroforestry methods like windbreak trees and drought-resistant crop species. Community members identified cost as the leading perceived barrier to implementing nature-based agricultural solutions, with over half of respondents indicating that programs to subsidize or eliminate cost would improve willingness to try nature-based methods. Analyses identified that satisfaction with community resources was positively correlated with scale of production, satisfaction with irrigation equipment, and familiarity with water rights. Further, our results outline barriers to perceptions about nature-based solutions on rural landscapes. We hope to contribute this model for wider applications in other regions to uncover place-based solutions to resource challenges and contribute to addressing stress at the urban-rural divide.

Diablo winds are dry and gusty north-northeasterly downslope windstorms that affect the Northern California. On the evening of October 8, 2017, Diablo winds contributed to the ignitions and rapid spread of the “Northern California Firestorm”, including the Tubbs Fire, which burned 2,800 homes in Santa Rosa, resulted in 22 fatalities and $1.2B USD in damages. We analyzed 18 years of data from a network of surface meteorological stations and show that Diablo winds tend to occur overnight through early morning in Fall, Winter and Spring. Conditions similar to Diablo winds occur commonly in the Sierra Nevada Mountains in addition to the area North of the San Francisco Bay Area including the Northern Coastal Ranges. Diablo winds are characterized by high wind speeds and low relative humidity, but they tend to neither be warmer than climatology nor do they have a higher gust factor, or ratio of wind gusts to mean wind speeds, than climatology.

Alzheimer’s disease (AD) and the therapies of AD with anti-amyloid1-42 (Aβ) monoclonal antibodies are associated with the vascular complications of brain edema, hemorrhage, and cerebral amyloid angiopathy (CAA) termed amyloid-related imaging abnormalities (ARIAs). The neuropathology of normal and AD brains demonstrates that monocyte/macrophages (MMs) are critical in successful brain clearance in healthy brain by up-loading, transporting, and degrading Aβ but fail degradation and clearance in AD patients by releasing Aβ into vessels at the blood-brain barrier, causing vasculitis and ARIAs. The naturally-formed epoxides (EpFAs) of polyunsaturated fatty acids (PUFA’s), including arachidonic, docosahexaenoic, and eicosapentaenoic fatty acids, may repair degradation of Aβ by regulating Aβ-degrading enzymes, inflammatory cytokines, and unfolded protein response (UPR) to endoplasmic reticulum stress in a homeostatic fashion. EpFAs are, however, degraded by the soluble epoxide hydrolase enzyme (sEH) but are protected by the sEH inhibitor (sEHI) TPPU. In the cultures of AD patients’ macrophages, TPPU with the epoxide EEQ, and the cGAS/STING inhibitor H-151 increased uptake of Aβ at 2 hours and degradation of Aβ at 24 hours. In conclusion, the soluble epoxide hydrolase inhibitor TPPU with omega-3 fatty acids and the cGAS/STING inhibitor H-151 increase Aβ uptake and degradation in macrophages of AD patients, and potentially enhancing Aβ clearance in the AD brain.

In this study, the causal-effect between carbon dioxide emissions and forestry production and trade was investigated in Ghana by employing a data spanning from 1961 to 2014 by using the VECM and ARDL model. Evidence of the long-run equilibrium relationship in the VECM shows that, a 1% increase in veneer sheet production reduces carbon dioxide emissions by 1.47% in the long-run. There was evidence of a bidirectional causality between carbon dioxide emissions and veneer sheet production, carbon dioxide emissions and wood charcoal production, and a unidirectional causality running from carbon dioxide emissions to wood fuel production and plywood production to carbon dioxide emissions. Evidence from the long-run equilibrium relationship in the ARDL model shows that; a 1% increase in plywood production will increase carbon dioxide emissions by 0.17% in the long-run, a 1% increase in sawnwood production will increase carbon dioxide emissions by 0.17% in the long-run, a 1% increase in wood charcoal production will increase carbon dioxide emissions by 0.36% in the long-run and a 1% increase in wood fuel production will increase carbon dioxide emissions by 0.37% in the long-run.

In this study, an attempt was made to investigate the Kenya case of multivariate causality of carbon dioxide emissions by employing a time series data spanning from 1961-2011 using the ARDL method of cointegration analysis. The long-run elasticities show that, a 1% increase in financial development increases carbon dioxide emissions by 0.28%, a 1% increase in GDP per capita increases carbon dioxide emissions by 1.32% and a 1% increase in urbanization decreases carbon dioxide emissions by 1.14%. There was a unidirectional causality running from financial development, food production index, GDP per capita, industrialization and urbanization to carbon dioxide emissions. The innovation accounting shows that 20% of future shocks in carbon dioxide emissions are due to fluctuations in financial development, 9% of future shocks in financial development are due to fluctuations urbanization and 22% of future shocks in food production index are due to fluctuations in carbon dioxide emissions.

Abstract: Endoglin (ENG) is a causative gene of type 1 hereditary hemorrhagic telangiectasia (HHT1). HHT1 patients have arteriovenous malformations (AVMs) in multiple organs, including the brain. In mice, Eng deletion induced by R26RCreER or SM22aCre leads to AVM development in the brain and other organs. We have reported that the severity of brain AVM in mice with activin receptor-like kinase 1 (Alk1, an HHT2 causative gene) mutation is correlated with the number of Alk1 negative endothelial cells (ECs). We hypothesized that increase of Eng negative ECs will enhance AVM severity. To increase EC Eng deletion, we used a codon improved cre (icre), which is more potent in recombination of floxed alleles than the wild type (WT) cre. R26RCreER;Eng^f/f mice that have Rosa promoter driving and tamoxifen (TM) inducible WT cre expression globally and PdgfbiCreER;Eng^f/f that have Pdgfb promoter driving and TM inducible icre expression in ECs were treated with 3 intra-peritoneal injections of TM (2.5 mg/25g of body weight) to delete Eng globally or in the ECs. AAV-VEGF was stereotactically injected into the brain to induce brain focal angiogenesis and brain AVM. We found that iCre caused more Eng deletion in the brain indicated by lower level of Eng proteins (p<0.001) and fewer Eng positive ECs (p=0.01) than mice with WT cre. Mice with iCre mediated Eng deletion have more abnormal vessels (p=0.02), CD68⁺ macrophages (p=0.002), and hemorrhage (p=0.04), and less vascular pericyte and smooth muscle coverage than mice with WT cre. In addition, arteriovenous shunts were detected in the intestines of icre mice, a phenotype that have not been detected in WT cre mice before. RNAseq analysis showed that 8 out of the 10 top upregulated pathways identified by Gene Ontology (GO) analysis are related to the inflammation. Therefore, increase of Eng deletion in ECs exacerbates AVM severity, which is associated with enhanced inflammation. Strategies that can reduce Eng negative ECs could be used to develop new therapies to reduce AVM severity for HHT1 patients.

Arbuscular mycorrhizal fungi (AMF) and rhizobium play a significant role in plant symbiosis. However, their influence on the soil microbiome associated with plant growth and soil health is not well defined in the Northern Great Plains. This study investigated the effect of microbial inoculants as seed treatment on plant yield, nutrient uptake, potential microbial functions, and rhizosphere soil microbial communities using high-throughput sequencing of 16S and ITS rRNA genes. The experiment was conducted under two contrasting dryland conditions with four treatments: control, single inoculation with AMF or Rhizobium, and dual inoculations of AMF and Rhizobium (AMF+Rhizobium). Our findings revealed that microbial inoculation efficacy was site-specific. In a non-P nutrient limiting condition, AMF+Rhizobium exhibited a synergistic effect on grain yield in Sidney, Montana (MT), dryland field site (DFS) 2. While AMF conferred plant resilience but marginal yield in low soil organic matter and acidic soil conditions in Froid, MT (DFS 1). Noteworthy, variation in microbial community structure and composition indicates site-specific response to AMF and AMF+Rhizobium microbial inoculants. Overall, site-specific factors had a greater influence on plant nutrient uptake, microbial community dynamics and functional potential. It underscores the need for tailored management strategies that consider site-specific characteristics to optimize benefits from microbial inoculation.

This review is focused on the current status of quantitative MR (qMR) of skeletal muscle. The first section covers the techniques of qMR in muscle with the focus on each quantitative parameter, the corresponding imaging sequence, discussion of the relation of the measured parameter to underlying physiology/ pathophysiology, the image processing and analysis approaches, and studies on normal subjects. We cover the more established parametric mapping from T1 weighted imaging for morphometrics including image segmentation, proton density fat fraction, T2 mapping, diffusion tensor imaging to emerging qMR features such as magnetization transfer including ultralow TE imaging for macromolecular fraction, and strain mapping. The second section is a summary of current clinical applications of qMR of muscle; the intent is to demonstrate the utility qMR in different disease states of the muscle rather than a complete comprehensive survey.

Abstract Introduction: Long COVID (LC) affects multiple systems and has a significant health impact on patients and society. Therefore, long COVID services should address patients’ needs through a holistic assessment and monitoring of patients’ symptoms. Aim: The aim was to understand which of the symptoms were most and least likely to improve, after our rehabilitation intervention so that the rehabilitation measures in the clinic could be modified to meet patients’ needs. At the same time, we wanted to assess the feasibility of using C19-YRS ELAROS application in monitoring of LC symptoms during and after the rehabilitation clinic attendance. Methodology: In this study, a total of 50 patients who have attended long COVID rehabilitation clinic in Salford, UK; were assessed by using digitalised C19-YRS ELAROS application. A total of 100 eligible initial and final post rehabilitation assessments were analysed. Conclusion: Pain and anxiety symptoms were the two most likely symptoms to improve after intervention at LC rehabilitation clinic, whereas swallowing difficulty is least likely to improve. Issues with caring for family/ social life (symptoms affecting social role) are likely to worsen even after treatment. It is feasible to monitor and track Long COVID symptoms utilising the digitalised version of C19-YRS via the ELAROS App. This also allows the tracking of symptoms overtime.

Reconstructing the Tree of Life remains a central goal in biology. Early methods, relying on small numbers of morphological or genetic characters, often yielded conflicting evolutionary histories, undermining confidence in the results. Investigations based on phylogenomics, which use hundreds to thousands of loci for phylogenetic inquiry, have provided a clearer picture of life's history, but certain branches remain problematic. To resolve difficult nodes on the Tree of Life, two recent studies tested the utility of synteny, the conserved collinearity of orthologous genetic loci in two or more organisms, for phylogenetics. Synteny exhibits compelling phylogenomic potential while also raising new challenges. We identify and discuss specific opportunities and challenges that bear on the value of synteny data and other rare genomic changes for phylogenomic studies. Synteny-based analyses of highly contiguous genome assemblies mark a new chapter in the phylogenomic era and the quest to reconstruct the Tree of Life.

Hereditary Hemorrhagic Telangiectasia (HHT), also known as Osler-Weber-Rendu syndrome, is a rare and inherited vascular disorder, characterized by the development of arteriovenous malformations (AVMs) in various organs and telangiectasia (small AVM) in the mucocutaneous. The majority of HHT patients have haploinsufficiency of genes involved in the transforming growth factor-beta (TGFβ) signaling pathway, including endoglin (ENG), activin receptor-like kinase 1 (ALK1, also known as ACVRL1), or SMAD4. Active angiogenesis is also required for telangiectasia and AVM development. Anti-angiogenic strategies have been tested in patients and animal models extensively. However, the exact mechanisms for telangiectasia and AVM development remain unclear. In this review, we discuss recent advances in identifying disease mechanisms, and potential therapeutic targets.

An analogy between magneto-fluid dynamics (MFD/MHD) and geostrophic flow in a rotating frame of reference including the existence of electromagnetic columns identical to Taylor-Proudman columns is identified and demonstrated theoretically. The latter occurs in the limit of large values of a dimensionless group representing the magnetic field number. Such conditions are shown to be easily satisfied in reality. Consequently, the electromagnetic fluid flow subject to these conditions is two dimensional and the streamlines are being shown to be identical to the pressure lines in complete analogy to rotating geostrophic flows. An experimental setup is suggested to confirm the theoretical results experimentally.

Background and Objectives: Cancer as the second leading cause of death in the United States poses a huge healthcare burden. Barriers to access to advanced therapies influence the outcome of cancer treatment. In this study, we examined whether insurance types affect the quality of cancer clinical care regarding access to an important monoclonal antibody, ramucirumab. Materials and Methods: Data for 13,340 cancer patients with Purchased or Medicaid insurance from the All of Us Database were collected for this study. The Chi-square test of proportions was employed to determine the significance of patient cohort characteristics and ramucirumab usage between Purchased and Medicaid insurance groups. The independent t-test was utilized to assess the influences of other determinants on insurance types. Results: Cancer patients who are African American, with lower socioeconomic status, or with lower educational attainment are more likely to be insured by Medicaid. Analysis of survey questions demonstrated the relationship between income and education level with insurance type as Medicaid cancer patients were less likely to receive primary care and specialist physician access and more likely to request lower cost medications. In addition, those with Medicaid insurance were identified to have poorer access to expensive therapeutics like ramucirumab compared to those with Purchased insurance.  Conclusions: The inequities of the US healthcare system are observed for cancer patient care; access to physicians and therapeutics are highly varied and dependent on insurance types. Socioeconomic status determines insurance type, which unfortunately generates a significant impact on cancer treatment and disease outcome.

In the last two decades, the application of composite structures in many industrial sectors has been made progressively. For the current major scientific and technological challenge, the energy transition with sustainable and eco-friendly initiatives, the polymer matrix laminated composites have been revealed as an excellent alternative for the renewable energy sector. In this context, the knowledge about mechanical behavior of multiphase materials is required. Then, researches related to macro, mesomechanical and multiscale approaches are very important to improve accuracy of the models to predict effective mechanical properties and to develop a better understanding about complex phenomena such as progressive damage, creep and fatigue. Due to theses needs, this research is a synthesis of fundamentals and advanced topics concerning to global modeling of laminated composite structures, layerwise analyzes and micro-macromechanical models, in which mainly fiber, matrix, interface and damage characteristics are studied and used in the macroscale approach. At the end of this study, some final remarks and a trend analysis are proposed based on literature consulted, in other words, expectations for the future works are made by the authors.

Familial pancreatic cancer (FPC) represents a significant yet underexplored area in pancreatic cancer research. Basic research efforts are notably limited, and when present, they are predominantly centered on BRCA1 and BRCA2 mutations due to the scarcity of other genetic variants associated with FPC, leading to a limited understanding of the broader genetic landscape of FPC. This review examines the current state of FPC research, focusing on the molecular mechanisms driving pancreatic ductal adenocarcinoma (PDAC) progression. It highlights the role of homologous recombination (HR) and its therapeutic exploitation via synthetic lethality with PARP inhibitors in BRCA1/2-deficient tumors. The review discusses various pre-clinical models of FPC, including conventional two-dimensional (2D) cell lines, patient-derived organoids (PDOs), patient-derived xenografts (PDXs), and genetically engineered mouse models (GEMMs) as well as new advancements in FPC research.

The objective of this study was to carry out the extraction and characterization of chitin and chitosan from the exoskeletons of the Farfantepenaeus californiensis species of shrimp, as well as its application in the formulation of polymeric films plasticized with glycerol used in the process of food packaging. The characterization of the extracted polymer was made by Fourier transform infrared spectroscopy (FTIR), Scanning electron microscopy (SEM), and physicochemical analysis of chitin and chitosan, resulting in a theoretical performance of 29.33% and 16.46%, respectively. In terms of quality, it was determined that the extracted chitosan had a molecular weight of 1.10 x105 g/mol and a deacetylation degree of 80.23%, which classifies it as a low-molecular weight chitosan, suitable for food packaging. It was shown that the extracted chitosan is fit for the production of the films by using the casting method, presenting a tension resistance of 1 MPa. The Antibacterial analysis was carried out using Staphylococcus aureus (S. aureus) and Escherichia coli (E. coli), bacterial models commonly found in food. The results showed an effective inhibition capability of the polymeric materials. Overall, the results for both chitosan and the films indicate a high potential for application in the food packaging sector.

Background: Surveys conducted in different regions of the world showed that the prevalence rates of health risk behaviors (HRBs) in university students are sometimes higher than those found in non-university populations. This study aims to identify the prevalence rates and demographic and academic environment correlates associated with HRBs among Brazilian university students. Methods: In a cross-sectional epidemiological study, a random sample of 5,310 university students answered an online questionnaire with demographic (sex, age, skin color, marital status, and paid work) and academic setting information (housing type, size of campus, year and shift of study), as well as items clustered in four HRB domains: personal safety and violence, sexual behavior and contraception, addictive substance use, and eating habits, physical activity, and sleep. The data were analyzed statistically using bivariate analysis and hierarchical multiple regression. Results: The highest prevalence rates occurred in HRBs clustered in the domain of eating habits, physical activity, and sleep (> 60%), while HRBs for personal security and violence were less prevalent (

Spray penetration into citrus canopies is critical for adequate coverage and deposition to ensure effective pest control. However, mismatch of air assistance to target canopy characteristics can lead to unintended spray loss through over penetration. To evaluate the effect of air assistance on on-target deposition, two sprayers (surrogates for airflow rates) were used to apply a fluorescent tracer dye solution @ target concentration of 300 ppm to 16 medium foliage density tree blocks in a commercial mandarin orchard. The complete factorial experiment in three replications comprised two ground speeds (1.6 and 4.8 km/h), two disc-core nozzles (TeeJet® D3-25 and D6-45), and either one or two nozzle rows to obtain a wide range of application rates (496 to 9,719 L/ha). Dye deposition significantly decreased with canopy depth (p=&lt;0.001) by nearly 7 times across the 3.4-m-wide canopies but was not significant over 1.2 to 2.2 m sampling height (p=0.867). Deposition obtained with the low airflow rate sprayer was significantly greater (p=&lt;0.001) than that obtained with the high airflow rate sprayer over the dose range likely due to too much air pushing out spray droplets. This study underscores the importance of matching the air assistance of orchard sprayers to the target canopy.

One mechanism by which fructose could exert deleterious effect in metabolism and inflammation is via its potency vis-à-vis de Maillard reaction. We employed simulated stomach and duodenum digestion of ovalbumin to test the hypothesis that indeed AGEs are formed by fructose during simulated digestion of an ubiquitous food protein with intrinsic allergenic potential and under model physiological conditions. Methods: OVA was subjected to simulated gastric and intestinal digestion using standard models, in presence of fructose or glucose (0-100 mM). Peptide fractions were analyzed by fluorescence spectroscopy and intensity at Excitation: λ370 nm, Emission: λ 440nm. Results: AGE adducts form between fructose and OVA which can be found in peptide fractions (< 5 kDa) at times (30 min) and concentration ranges (10 mM) plausibly found in the intestines, whereas no reaction occurs with glucose. The reaction is inhibited by chlorogenic acid at concentrations compatible with those found in the gut. The reaction is inhibited by AG, a specific antiglycation agent. Conclusion: Our proof of principle study shows that fructose-AGE formation on an ubiquitous allergenic protein indeed occurs in one hour and thereby may pave the way for the study of yet another mechanism by which the excess fructose in our Western diets is contributing to disease: intestinal AGE formation, absorption and RAGE engagement.

The recent mountain pine beetle outbreaks have caused widespread mortality among lodgepole pine trees in western North America, resulting in a reduced population of surviving trees. While previous studies have focused on the cascading impacts of these outbreaks on the physiology and growth of the surviving trees, there remains a need for a comprehensive study into the interactions among various physiological traits and the growth in post-outbreak stands. Specifically, the relationship between chemical (primarily terpenes) and anatomical (mainly resin ducts) defences, as well as the allocation of non-structural carbohydrates (NSCs) to support these defence modalities, is poorly understood. To address these gaps, we conducted a field survey of surviving lodgepole pine trees in post-mountain pine beetle outbreak stands in western Canada. Our retrospective analysis targeted to determine correlations between the post-outbreak concentrations of monoterpenes, diterpenes, and NSCs in the phloem, and the historical resin duct characteristics and growth traits before and after the outbreak. We detected strong correlations between post-outbreak concentrations of monoterpenes and historical resin duct characteristics, suggesting a possible link between these two defence modalities. Additionally, we found a positive relationship between NSCs and the total concentrations of monoterpenes and diterpenes, suggesting that NSCs likely influence the production of these terpenes in lodgepole pine. Furthermore, historical tree growth patterns showed strong positive correlations with many individual monoterpenes and diterpenes. Interestingly, while surviving trees had enhanced anatomical defences after the outbreak, their growth patterns did not vary before and after the outbreak conditions. The complexity of these relationships emphasizes the dynamics of post-outbreak stand dynamics and resource allocation in lodgepole pine forests, highlighting the need for further research. These findings contribute to a broader understanding of conifer defenses and their coordinated responses to forest insect outbreaks, with implications for forest management and conservation strategies.

In this study, the impact of energy, agriculture, macroeconomic and human-induced indicators on environmental pollution from 1971 to 2011 is investigated using the statistically inspired modification of partial least squares (SIMPLS) regression model. There was evidence of a linear relationship between energy, agriculture, macroeconomic and human-induced indicators and carbon dioxide emissions. Evidence from the SIMPLS regression shows that a 1% increase in crop production index will reduce carbon dioxide emissions by 0.71%. Economic growth increased by 1% will reduce carbon dioxide emissions by 0.46%, thus supports the environmental Kuznets curve hypothesis that an increase in a country’s economic growth leads to a reduction in environmental pollution. An increase in electricity production from hydroelectric sources by 1% will reduce carbon dioxide emissions by 0.30%, thus increasing renewable energy sources in Ghana’s energy portfolio will help mitigate carbon dioxide emissions. Increasing Enteric Emissions by 1% will increase carbon dioxide emissions by 4.22% and a 1% increase in the Nitrogen content of Manure Management will increase carbon dioxide emissions by 6.69%. The SIMPLS regression forecasting exhibited a 5% MAPE from the prediction of carbon dioxide emissions.

The population’s mobility in urban areas is a necessary variable in the modeling of risk scenarios caused by atmospheric contamination. The inclusion of this concept makes static models more dynamic while considering people within a city to be an entity with complex mobility processes. We propose a conceptual and methodological tool to make the representation of the social, economic and territorial components, as well as the patterns in the population´s mobility to delimitate risk areas for human health by exposure of contaminants. In the volatile organic compounds (VOC), benzene, ethylbenzene, toluene and xylene (BTEX) are amongst the most dominant substances in fugitive vapor emissions in gas stations (GS). In urban areas, the exposure to BTEX by residential proximity and proximity to other facilities, which cause intra-urban agglomeration, can impact and affect human health. This model seeks to facilitate the focalization, identification and prioritization of risk areas by BTEX environmental contamination. This article goes beyond de conceptual framework. It suggests methodological and instrumental aspects to be applied in other cities. The government agencies must consider these results when establishing rules, permissions and procedures to reduce environmental pollution for managing the risk in a complex urban environment.

Phosphorus (P) and iron (Fe) deficiency are major limiting factors for plant productivity worldwide. White lupin (Lupinus albus L.) has become a model plant for understanding plant adaptations to P and Fe deficiency, because of its ability to form cluster roots, bottle-brush-like root structures that play an important role in the uptake of P and Fe from soil. However, little is known about the signaling pathways involved in sensing and responding to P and Fe deficiency. Sucrose, sent in increased concentrations from the shoot to the root, has been identified as a long-distance signal of both P and Fe deficiency. To unravel responses to sucrose as signal, we performed Oxford Nanopore cDNA sequencing of white lupin roots treated with sucrose for 10 min, 15 min, and 20 min, compared to untreated controls. We identified a set of 17 genes, including two bHLH transcription factors, that were up-regulated at all three time points of sucrose treatment. GO (gene ontology) analysis revealed enrichment of auxin- and gibberellin-responses as early as 10 min after sucrose addition, and the emerging of ethanol-responses at 20 min of sucrose treatment, indicating a sequential involvement of these hormones in plant responses to sucrose.

This study investigates the impact of AI regulations and adoption on labor markets and employment in the USA. In order to achieve the study's objective, a robust econometric approach was employed using Principal Components Analysis (PCA) to address multicollinearity among the variables. The regression analysis incorporated principal components representing overall AI adoption and education (PC1), AI innovation and academic output (PC2), economic growth (PC3), and unemployment and AI strategies (PC4). The analysis utilized heteroskedasticity-robust standard errors to ensure reliable coefficient estimates and tested for stationarity to confirm the stability of the time series data. Data were collected from 2010 to 2022, encompassing key AI-related and economic indicators. The results reveal that higher AI adoption and education levels initially lead to job displacement, negatively impacting labor market metrics. Similarly, AI innovation and economic growth driven by AI do not immediately translate into job creation, reflecting transitional challenges. However, the strategic implementation of AI significantly mitigates these adverse effects and enhances employment conditions. The study finds that comprehensive AI strategies, robust regulatory frameworks, and effective workforce retraining and upskilling programs are essential for supporting labor market stability and promoting employment growth. Based on the findings, the study recommended that there is the need to develop and implement comprehensive AI strategies that include robust regulatory frameworks to support workforce transitions. Policies should focus on retraining and upskilling programs to help displaced workers adapt to new AI-driven roles.

Antibody-drug conjugates (ADCs), a groundbreaking advancement in cancer therapy, synergistically combine the precision of monoclonal antibodies with the potent destruction capabilities of cytotoxic drugs, signifying a new era in the targeted oncological treatments. This comprehensive paper delves into the evolving field of antibody-drug conjugates (ADCs) and their pivotal role in cancer therapy. We have conducted an in-depth exploration of the structural components of ADCs, including target antigens, monoclonal antibodies, chemical linkers, and cytotoxic payloads, each playing a crucial role in determining the efficacy and safety profile of these novel therapies. A detailed market analysis reveals the leading pharmaceutical companies shaping the ADC landscape, reflecting the growing interest and potential in this therapeutic approach. We further dissect the engineering intricacies of ADCs, focusing on their ability to target specific cancer cell antigens while minimizing off-target effects, thus offering a more focused treatment with reduced systemic side effects compared to traditional chemotherapy. This approach holds promise in a heightened therapeutic index and decreased toxicity. The mechanisms and effector functions of ADCs are explored, highlight- ing their multifaceted strategy in combating cancer. We include a comprehensive look at how ADCs operate from initial blood circulation to the induction of apoptosis in cancer cells. We also review several key ADCs currently in use or under investigation, offering insights into their unique mechanisms of action, pharmacokinetics, and clinical implications. The discussion extends to drug creation modalities, focusing on innovative conjugation techniques that enhance ADC homogeneity and therapeutic efficacy. In conclusion, the paper underscores the transformative potential of ADCs in the realm of cancer treatment, marking a shift towards more precise and targeted therapeutic approaches. By offering a thorough analysis of ADC technology, this paper sheds light on the prospects of these groundbreaking therapies in the ongoing fight against cancer.

The continuing mutability of the SARS-CoV-2 virus can result in failures of diagnostic assays. To address this, we describe a generalizable bioinformatics-to-biology pipeline developed for calibration and quality assurance of inactivated SARS-COV-2 variant panels provided to Radical Acceleration of Diagnostics programs (RADx)-radical program awardees. Heuristic genetic analysis based on variant-defining mutations demonstrated the lowest genetic variance in the Nucleocapsid protein (Np)- C-terminal domain (CTD) across all SARS-COV-2 variants. We then employed the Shannon entropy method on (Np) sequences collected from the major variants, verifying the CTD with lower entropy (less prone to mutations) than other Np regions. Polyclonal and monoclonal antibodies were raised against this target CTD antigen and used to develop an Enzyme-linked immunoassay (ELISA) test for SARS-CoV-2. Blinded Viral Quality Assurance (VQA) panels comprising of UV-inactivated SARS CoV-2 variants (XBB.1.5, BF.7, BA.1, B.1.617.2, and WA1) and distractor respiratory viruses (CoV 229E, CoV OC43, RSV A2, RSV B, IAV H1N1, and IBV) were assembled by the RADx-rad Diagnostics core and tested using the ELISA described here. The assay tested positive for all variants with high sensitivity (Limit of Detection: 1.72-8.78 ng/mL) and negative for the distractor virus panel. Epitope mapping for the monoclonal antibodies identified a twenty amino acid antigenic peptide on the Np-CTD that an in-silico program also predicted for the highest antigenicity. This work provides a template for a bioinformatics pipeline to select genetic regions with a low propensity for mutation (low Shannon entropy) to develop robust ‘pan-variant’ antigen-based assays for viruses prone to high mutational rates.

Pulmonary hypertension (PH) is a severe and chronic disease characterized by increased pulmonary vascular resistance and remodeling often precipitating right-sided heart dysfunction and death. Although the condition is progressive and incurable, current therapies for the disease focus on multiple different drugs and general supportive therapies to manage symptoms and prolong survival, ranging from medications more specific to pulmonary arterial hypertension (PAH) to exercise training. Moreover, there are multiple studies exploring novel experimental drugs and therapies including unique neurostimulation, to help better manage the disease. Here we provide a narrative review focusing on current PH treatments that target multiple underlying biochemical mechanisms, including but not limited to imbalances in vasoconstrictor-vasodilator and autonomic nervous system function, inflammation, and bone morphogenic protein (BMP) signaling. We also focus on the potential of novel therapies for managing PH, focusing on multiple types of neu-rostimulation including acupuncture. Lastly, we also touch upon the disease’s different subgroups, clinical presentations and prognosis, diagnostics, demographics, and cost.

This paper aims to explore the potential application of Extreme Learning Machines (ELM) in stock price prediction and optimise the ELM model by combining the Crown Porcupine Optimisation Algorithm and the Adaptive Bandwidth Kernel Function Density Estimation Algorithm. Specifically, the model's root mean square error (RMSE) on the test set is 0.018, which shows its good prediction accuracy. Meanwhile, the correlation coefficient R reaches 0.968, proving the model's effectiveness in predicting stock prices. In addition, the coefficient of determination R² of the training set and test set are 0.987 and 0.954, respectively, which are not much different, indicating that the model has good generalisation ability and is not prone to overfitting. This is crucial for practical application, as it implies that the model fits the existing data well and makes accurate predictions for future data. In terms of other evaluation metrics such as Mean Absolute Error (MAE), Root Mean Square Error (RMSE) and Mean Absolute Percentage Error (MAPE), the performance is excellent in both the training and test sets. Together, these results indicate that after optimising the ELM by introducing the crown porcupine optimisation algorithm and the adaptive bandwidth kernel function density estimation algorithm, the model can effectively capture the changing stock price pattern, thus achieving efficient and accurate stock price prediction. In summary, this study not only demonstrates the great potential of ELM in stock price prediction but also highlights the importance of improving the model performance through advanced algorithm optimisation, which provides a new way of thinking and methodology for financial market analysis. This strongly supports investors' decision-making and lays the foundation for related research.

The detection, characterization, and monitoring of SARS-CoV-2 recombinant variants is a challenge to public health authorities worldwide. Recombinant variants, composed of two or more SARS-CoV-2 lineages, often have unknown impacts on transmission, immune escape, and virulence in the early stages of emergence. We examined 4,213 SARS-CoV-2 recombinant SARS-CoV-2 genomes collected between 2020 and 2022 from California to describe regional and statewide trends in prevalence. Many of these recombinant genomes, such as those belonging to the XZ lineage, or novel recombinant lineages, likely originated within the state of California. We discuss the challenges and limitations surrounding Pango lineage assignments, the use of publicly available sequence data, and adequate sample sizes for epidemiologic analyses. Although these challenges will continue as SARS-CoV-2 sequencing volumes decrease globally, this study enhances our understanding of SARS-CoV-2 recombinant genomes to date while providing a foundation for future insights into emerging recombinant lineages.

This is the second paper in a series introducing a deterministic quantum mechanics theory that is shown to be consistent with the current mainstream statistical quantum theory as well as with classical physics. The first paper in this series demonstrated how causality, physical reality, and determinism are restored and concerns that were raised by results from the current mainstream statistical quantum theory were explained in simple form. The meaning of particle-wave duality and complementarity, the possibility of a particle, like the electron, to cross through the nucleus as it does when the angular momentum of the electron is zero, the possibility of a point-size particle to have an “intrinsic spin”, the possibility of “quantum jumps” as the electron transitions instantaneously from one stable orbital to another and does that at irregular time intervals, the natural collapse of the wave function as part of the solution, as well as consistency with the phenomenon of entanglement were some of the results that emerged from the proposed deterministic quantum mechanics theory. While the first paper presented overwhelming evidence of the latter, the present paper is the first to produce actual solutions that are consistent with current mainstream quantum theory as well as with classical physics. Analytical solutions are presented via a linear stability method. The Bohr-Schrödinger energy levels leading to the experimentally confirmed spectral lines, as well as the fine structure constant emerge directly from the solution of the equations governing the proposed deterministic quantum mechanics. Recommended follow-up solutions as well as generalizations are being presented at the end of the paper.

This author is not a philosopher nor historian of science, but an engineering thermodynamicist. In that regard and in addition to various philosophical “why & how” treatises and existing historical analyses, the physical and logical “what it is” reflections, as successive Key Points, where a key reasoning infers the next one, along with novel contributions and original generalizations, are presented. We need to keep in mind that in Sadi Carnot’s time (early 1800s) the steam engines were inefficient (below 5%, so the heat in and out were comparable within experimental uncertainty), the conservation of caloric flourished (might be a fortunate misconception), and many critical thermal-concepts, including the conservation of energy (The First Law) were not even established. If Clausius and Kelvin were "fathers of thermodynamics" then Sadi Carnot was the "grandfather" [Kostic, 2023 July 24], or better yet, Sadi Carnot was the "Forefather of Thermodynamics-to-become" [Kostic, 2023 October 29].

Epilepsy is a common neurological condition, typically diagnosed using Electroencephalogram (EEG). Large scale EEG datasets have recently been made publicly available, allowing the use of advanced Machine Learning (ML) algorithms to analyze EEG patterns associated with epilepsy. While most existing studies focus on identifying seizures in the EEG, few have tried to identify preictal EEG segments. Identifying preictal EEG segments are not only useful in developing early warning systems but also helps inform the course of treatment for the patient. In this study, we propose to represent EEG segments as images, instead of time-series data, and identify preictal EEG segments using a preexisting ML algorithm (YOLOv8) designed for image processing. Multiplexed images (containing the original EEG signal represented on a 2D grid, kurtosis, and spectral entropy) achieve the best accuracy of 95.75% on the dataset while images just containing the EEG signal result in an accuracy of 91.25%. Using only spectrograms, generated from the original EEG signal, results in an accuracy of 90.15%.

In genetic conflicts, driver and killer elements achieve biased survival, replication, or transmission over sensitive and targeted elements through a wide range of molecular mechanisms, including mimicry. Driving mechanisms manifest at all organismal levels, from the biased propagation of individual genes, as demonstrated by transposable elements, to the biased transmission of genomes, as illustrated by viruses, to the biased transmission of cell lineages, as in cancer. Targeted genomes are vulnerable to molecular mimicry through the conserved motifs they use for their own signaling and regulation. Mimicking these motifs enables a selfish element to control core target processes, and can occur at the sequence, structure, or functional level. Molecular mimicry was first appreciated as an important phenomenon more than twenty years ago. Modern genomics technologies, databases, and machine learning approaches offer tremendous potential to study the distribution of molecular mimicry across genetic conflicts in nature. Here, we explore the theoretical expectations for molecular mimicry between conflicting genomes, the trends in molecular mimicry mechanisms across known genetic conflicts, and outline how new examples can be gleaned from population genomic datasets. We discuss how mimics involving short sequence-based motifs or gene duplications can evolve convergently from new mutations. Whereas, processes that involve divergent domains or fully-folded structures occur among genomes by horizontal gene transfer. These trends are largely based on a small number of organisms and should be reevaluated in a general, phylogenetically independent framework. Currently, publicly available databases can be mined for genotypes driving non-mendelian inheritance patterns, epistatic interactions, and convergent protein structures. A subset of these conflicting elements may be molecular mimics. We propose approaches for detecting genetic conflict and molecular mimicry from these datasets.

Photoreceptor degeneration is a major cause of untreatable blindness worldwide and has recently been targeted by emerging technologies, including cell- and gene-based therapies. Cell types of neural lineage have shown promise for replacing either photoreceptors or retinal pigment epithelial cells following delivery to the subretinal space, while cells of bone marrow lineage have been tested for retinal trophic effects following delivery to the vitreous cavity. Here we explore an alternate approach in which cells from the immature neural retinal are delivered to the vitreous cavity with the goal of providing trophic support for degenerating photoreceptors. Rat and human retinal progenitor cells were transplanted to the vitreous of rats with a well-studied photoreceptor dystrophy, resulting in substantial anatomical preservation and functional rescue of vision. This work provides scientific proof-of-principle for a novel therapeutic approach to photoreceptor degeneration that is currently being evaluated in clinical trials.

Primary open-angle glaucoma (POAG) is a progressive optic neuropathy with a complex, multifactorial aetiology. Raised intraocular pressure (IOP) is the most important clinically modifiable risk factor for POAG. All current pharmacological agents target aqueous hu-mour dynamics to lower IOP. Newer therapeutic agents are required as some patients with POAG show a limited therapeutic response or develop ocular and systemic side ef-fects to topical medication. Elevated IOP in POAG results from cellular and molecular changes in the trabecular meshwork driven by increased levels of transforming growth factor β (TGFβ) in the anterior segment of the eye. Understanding how TGF affects both the structural and functional changes in the outflow pathway and IOP is required to de-velop new glaucoma therapies that target the molecular pathology in the trabecular meshwork. In this study we evaluated the effects of TGF-1 and -2 treatment on miRNA expression in cultured human primary trabecular meshwork cells. Our findings are pre-sented in terms of specific miRNAs (miRNA-centric), but given miRNAs work in net-works to control cellular pathways and processes, a pathway-centric view of miRNA ac-tion is also reported. Evaluating TGF-responsive miRNA expression in trabecular meshwork cells will further our understanding of the important pathways and changes involved in the pathogenesis of glaucoma and could lead to the development of miRNAs as new therapeutic modalities in glaucoma.

Parental refusal of childhood vaccines is a growing public health concern. Numerous reasons exist for this refusal, including religious, personal, and philosophical beliefs, and safety concerns. However, parental refusal of childhood vaccines is not simply an individualized problem for the family; this impacts herd immunity and affects the entire community. To improve vaccination rates among the pediatric population, understanding the thought process and decision-making behind parental opposition and refusal of vaccinations is essential. Using a survey developed to assess attitudes towards recommended childhood vaccines and the COVID-19 vaccine, this study examined the correlation between vaccine literacy and hesitancy among parents and legal guardians of elementary school-aged children in the Midwest. Responses were analyzed using Chi-squared tests on “R” software. Significant negative correlations were found between COVID-19 hesitancy and vaccine literacy, and resistance towards all vaccines and vaccine literacy. No significant negative correlations were found between hesitancy towards all vaccines and vaccine literacy, or hesitancy and literacy among different income and education brackets. Our results suggest that vaccine education may lessen vaccine hesitancy among parents and may be an essential factor in improving vaccination rates among the pediatric population.

Background: Coronavirus disease 2019 (COVID-19) caused several cardiovascular complications, including acute myocardial infarction(AMI) in infected patients. Our study aims to understand the overall trends of AMI among COVID-19 patients during the first two years of the pandemic and the disparities and outcomes between the first and second years. Methods: Our retrospective analysis via the 2020 and 2021 National Inpatient Sample(NIS) for hospitalizations between April 2020 and December 2021 analyzed adults with a primary diagnosis of COVID-19 who experienced events of AMI. We compared month-to-month events of AMI and mortality of AMI patients with COVID-19, patient characteristics, and outcomes between the 2020 and 2021 AMI samples. Results: There were 2,541,992 COVID-19 patients, with 3.55% experiencing AMI. The highest rate of AMI was in December 2021 (4.35%). No statistical differences in trends of AMI mortality were noted over the 21 months. AMI cases in 2021 had higher odds of undergoing PCI (aOR 1.627, p

The early 2-factor (E2F) family of transcription factors, including E2F1-8, plays a critical role in apoptosis, metabolism, proliferation, and angiogenesis within glioblastoma (GBM). However, the specific functions of E2F transcription factors (E2Fs) and their impact on the malignancy of Bevacizumab (BVZ)-responsive GBM subtypes remain unclear. This study used data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) to explore the impact of eight E2F family members on the clinical characteristics of BVZ-responsive GBM subtypes and possible mechanisms of recurrence after BVZ treatment.To predict the possibility of GBM patient survival and progression, we classified and comparedthe expression of E2Fs according to BVZ-responsive subtypes and employed a machine learning method-TreeBagger, one random forest algorithm. Multiple bioinformatics analyses have shown that the significant increased E2F8 post BVZ treatment may enhance the function of angiogenesis and stem cell proliferation, indicating one of the mechanisms of GBM recurrence after treatment. In addition, BVZ treatment in unresponsive GBM patients may potentially worsen disease progression. Our findings suggest that E2F family members play important roles in GBM malignancy and BVZ treatment response, highlighting their potential as prognostic biomarkers and therapeutic targets and recommending precise BVZ treatment for GBM patients.

The main sources of intrinsic noise in excitable cells at the microcircuit and network levels are the stochastic characteristics of ion channel gating and activation of the synaptic conductance. Studies using in vivo, in vitro, and in silico methods to examine the effects of synaptic background activity were not adequately investigated in non-neuronal excitatory cells, where neurotransmitter-based innervation also occurs. We created a mathematical model to replicate the background synaptic noise dynamics in a non-neuronal cell. We utilized the stochastic Ornstein-Uhlenbeck process to represent excitatory synaptic conductance, which was incorporated into a whole-cell model to produce spontaneous and evoked cellular electrical activities. The single-cell model includes many biophysically detailed ion channels represented by a set of ordinary differential equations in Hodgkin-Huxley and Markov formalisms. This paradigm effectively induced irregular spontaneous depolarizations (SDs) and spontaneous action potential (sAP) resembling in vitro-like electrical activity in the cells. The input resistance decreased by multiple factors, and the spontaneous action potential firing rate elevated. The potential to reach the action potential threshold is altered. Background synaptic activity can alter the input/output characteristics of non-neuronal excitatory cells. Suppressing these baseline activities would facilitate the discovery of new pharmaceutical targets for different clinical diseases.

In the most cases, invasive ductal carcinoma (IDC) of the breast is identifiable when they present with classic infiltrative growth pattern. However, subset of IDC can occur in a very sneaky way, significantly mimicking the appearance of ductal carcinoma in situ (DCIS). In this condition, it’s much easier to miss the invasive component without pulling ancillary staining when morphologic findings are extremely compatible with DCIS, especially the diagnosis of DCIS was made on the previous biopsy. Here, we reported a 55 year-old female who was noted to have microcalcification at the 11:00 o’clock of the right posterior breast on routine mammographic examination in 09/2023. Biopsy of the calcification area in 10/2023 reported high grade DCIS (ER+ PR-). Histologic examination of subsequent mastectomy specimen showed two separate DCIS-looking areas (Figure 1A-D and Figure 2). Immunohistochemical (IHC) staining showed that myoepithelial markers, smooth muscle myosin heavy chain (SMMHC), p63, CK5/6 and S100, were retained at the periphery of all the expanded acini in one area (Figure 1E-H). Unexpectedly and surprisingly, myoepithelial markers were completely lost at the periphery of part of the DCIS-looking acini in another area (Figure 3A-H), immunohistochemically compatible with the diagnosis of invasive ductal carcinoma admixed with DCIS. Knowing that invasive ductal carcinoma of the breast can present as DCIS-looking morphology, especially given the condition that the diagnosis of DCIS was rendered on the previous biopsy, will enhance awareness of pathologists to recognize DCIS-looking invasive ductal carcinoma. In turn, this will prevent misdiagnosis and under-treatment of patients with invasive ductal carcinoma of the breast.

Background and Objectives: Medulloblastoma is the most common malignant brain tumor in children. In recent decades, the therapeutic landscape has undergone significant changes, with stereotactic radiosurgery (SRS) emerging as a promising treatment for recurrent cases. Our study provides a comprehensive analysis of the long-term efficacy and safety of SRS in recurrent medulloblastomas across both pediatric and adult patients at a single institution. Methods: We retrospectively reviewed the clinical and radiological records of patients who underwent CyberKnife SRS for recurrent cranial medulloblastomas at our institution between 1998 and 2023. Follow-up data were available for 15 medulloblastomas in 10 patients. The cohort comprised 8 pediatric patients (ages 3-18) and 2 adult patients (ages 19-75). Median age at the time of SRS was 13 years, median tumor volume accounted for 1.9 cc, median biologically equivalent dose (BED) was 126 Gy, and single-fraction equivalent dose (SFED) was 18 Gy. The SRS was administered at 75% of the median isodose line. Results: Following a median follow-up of 39 months (range: 6-78), 53.3% of the medulloblastomas progressed, 13.3% regressed, and 33.3% remained stable. The 3-year local tumor control (LTC) rate for all medulloblastomas was 65%, with lower rates observed in the adult cohort (50%) and higher rates in pediatric patients (67%). The 3-year overall survival (OS) rate was 70%, with significantly higher rates in pediatric patients (75%) compared to adult patients (50%). The 3-year progression-free survival (PFS) rate was 58.3%, with higher rates in pediatric patients (60%) compared to adult patients (50%). Two pediatric patients developed radiation-induced edema, while two adult patients experienced radiation necrosis at the latest follow-up, with both adult patients passing away. Conclusion: Our study provides a complex perspective on the efficacy and safety of CyberKnife SRS in treating recurrent cranial medulloblastomas across pediatric and adult populations. The rarity of adverse radiation events (ARE) underscores the safety profile of SRS, reinforcing its role in enhancing treatment outcomes. The intricacies of symptomatic outcomes, intertwined with factors such as age, tumor location, and prior surgeries, emphasize the need for personalized treatment approaches. Our findings underscore the imperative for ongoing research and the development of more refined treatment strategies for recurrent medulloblastomas. Given the observed disparities in treatment outcomes, a more meticulous tailoring of treatment approaches becomes crucial.

HIV early detection (CD4 counts ≥350 cells/μL) is correlated with higher life expectancy among people living with HIV (PLHIV). Several factors including physical, cultural, structural, and financial barriers have contributed to HIV late detection. This is the first-of-its-kind study on the regional differences in early detection of HIV within Tajikistan and any country in the Central Asia region. Utilizing Tajikistan Ministry of Health's national HIV data (N=10,700) spanning 2010 to 2023, we developed median regression models with median CD4 cell count as the outcome and as predictors: time (years), region, age, gender, and area (urban/rural status). Individuals younger than 19 years old are more likely to be detected early for HIV, whereas those older than 39 years are more prone to late detection. Given their active engagement in age-related and sexual activities, those older than 39 years face a higher risk of HIV transmission to others if diagnosed late. Therefore, they require further attention and targeted interventions. Females are detected earlier compared to their male counterparts, regardless of region of residence. Rural populations are detected earlier in most years compared to their urban counterparts. The COVID-19 pandemic accelerated HIV early detection in 2021 but most regions have returned to near pre-pandemic levels of detection in 2022 and 2023. These fluctuations in early detection may signify a shift in attention and resource allocation, potentially affecting efforts to address access gaps during the initial year of the COVID-19 pandemic. There are significant health inequities among different demographic and geographic groups which warrant further attention.

Coccidioidomycosis (Valley Fever) is a disease caused by inhalation of Coccidioides spp. This neglected tropical disease of the Americas has substantial public health impact despite its geographic restriction to desert areas of the southwestern U.S., Mexico, Central and South America. The incidence of this infection in California and Arizona has been increasing over the past fifteen years. The burden of disease in outside the U.S. remains poorly understood. Several large cities are within the endemic region in the U.S. Coccidioidomycosis accounts for 25,000 hospital admissions per year in California. While most cases of coccidioidomycosis resolve spontaneously, up to 40% are severe enough to require anti-fungal treatment, and a significant number disseminate beyond the lungs. Disseminated infection, especially involving the meninges, is fatal without appropriate treatment. Infection with Coccidioides spp. is protective against a second infection, so vaccination seems biologically plausible. This review of efforts to develop a vaccine against coccidioidomycosis focuses on vaccine approaches and the difficulties in identifying protein antigen/adjuvant combinations that protect in experimental mouse models. Although the quest for a vaccine has not yet resulted in a clinically useful product, scientific efforts of vaccine development pave the way for future success.

Average of 41,900 patients are diagnosed annually with staphylococcus bacterial infection in California, 24,089 patients have Methicillin-resistant Staphylococcus Aureus (MRSA) and 17,810 patients have Methicillin-Sensitive Staphylococcus (MSSA). This paper demonstrates that there is a difference in mortality rate due to staphylococcus infection between males and females (P-value<0.05, CI 95%). Male patient diagnosed with S. aureus has 1.3 chance of mortality incidence than female patient. In addition, MRSA infection rate is 1.4 times MSSA infection (P-value<0.05, CI 95%), but the gap of infection is decreasing; however, mortality of both infections combined are more than threefold greater compared to three decades ago.

With the rapid development of new energy vehicles and the digital electronics industry, the demand for lithium has surged, necessitating advanced lithium extraction technologies. Electrochemical methods, noted for their high selectivity and efficiency in extracting target ions from liquid sources in an environmentally friendly manner, have become increasingly vital. These methods are versatile, applicable in scenarios such as lithium extraction from saline lakes, mother liquor separation, and lithium enrichment. They include electrochemical deintercalation, electrochemical ion pumps, and electrodialysis, each offering unique benefits and challenges depending on the application context. This review provides a detailed exploration of the research progress in lithium extraction using electrochemical methods and discusses future prospects for these technologies, emphasizing their potential to meet the growing demand for lithium.

Measuring cell confluence in high-throughput screening of pharmaceutics, cell culture monitoring, cancer research, and industrial applications requires quantitative and standardizable measures to minimize subjective observations and increase throughput1-12 . Over the past half-century, non-invasive specialized programs have been created to quantitatively assess cell confluence, and some software tools exist to meet these needs1,4,5,6,7,8,9 . However, many of these tools are expensive, computationally-demanding, or inaccessible to non-experts1,6. With the assistance of generative artificial intelligence, we have developed the Confluence Analysis Program (CAP), a modern tool designed to be precise, interactive, and user-friendly. CAP is written entirely in Python and runs in any command-line interface (CLI), including Terminal (OS) and Command Prompt (Windows). In addition to fetching all necessary external libraries automatically and prompting drag-and-drop image retrieval, CAP features live visual comparison of cell mass identification to the original image assay. Our results demonstrate robust performance of CAP on fluorescent micrographs of varying confluences ranging from low to high. CAP is provided as a free resource, accessible in the Supplementary Materials.

Preterm birth accounts for about 10% of births worldwide. Studying risk factors for perinatal brain damage is essential, as findings suggest that almost 20% of disabilities are linked to risks in the early stages of development. This research aimed to study longitudinal changes in intelligence from 6 to 8 years of age in a sample of 39 preterm children with a history of risk of brain damage and a control group of 35 children born at term. The Wechsler Intelligence Scale (WISC-IV) was used for cognitive measurement. The results showed that the preterm group obtained significantly lower scores than the control group. The working memory indicator significantly affected the interaction between age and prematurity. We consider that it is crucial to expand the knowledge we have about the neurocognitive development of premature infants both in specific cognitive domains and in age ranges so that the information obtained helps to predict the probability of presenting cognitive alterations from early stages and, therefore, to implement intervention strategies and programs based on scientific evidence and complemented in their design by clinical experience, empirical and theoretical knowledge of the different professionals involved in infant cognitive intervention.

In this study, the olive pomace was considered because of its importance in the environment. So, this study carried out to estimate the total nitrogen content and the fatty acids profile of olive pomace. The olive pomace samples were collected from Irbid, Jarash, Ajloun and Mafraq during the harvesting season 2014 to study the biochemical characteristics of fatty acid composition and the total nitrogen (TN) content. The total nitrogen content was determined by standard Kjeldahl method and the fatty acid profile was detected by gas chromatography (GC). The results show that the total nitrogen content ranged from (0.39 ± 0.0) to (0.62 ± 0.02) with statistically significant difference suggesting that the composition of matrices and their percentage may be responsible for composition of amendments. The calculated total protein percentage ranged between (2.43 ± 0.00) to (3.87 ± 0.17). Also, 13 different fatty acids were quantitatively profiled and quantitated. Oleic acid (C 18:1) was found to be the highest percentage of all other fatty acids and ranged between (59.03%) and (63.81%), moreover the C 18:1/C 18:2 (oil quality) was calculated and C.V% showed variation meaning that nutritional implication could affect the oxidative stability of oils. In conclusion, OP by-product could give a sustainable and alternative-cheap source for fertilizers, pharmaceutical industries, cosmetics and other industries.

Relationships of the three bryophyte lineages (liverworts, mosses, and hornworts) to vascular plants is a pivotal question in the study of origin and evolution of land plants. In recent decades, this question has been subject to intense phylogenetic analyses using morphological characters, multigene DNA sequences, and genome structural characters. A tentative consensus reached ten years ago suggested that bryophytes are a paraphyletic group, with liverworts being sister to all other land plants and hornworts being sister to vascular plants. However, several more recent nuclear phylogenomic studies have concluded that bryophytes represent a monophyletic group that is sister to vascular plants. A discussion is presented here on strengths and weaknesses of different types of characters (morphological traits, nucleotide sequences, and genome structural arrangements), and their suitability for resolving deep phylogenetic relationships. Moreover, several criteria for credible phylogenetic reconstruction are proposed. Strong statistical support for reconstructed relationships should be derived from high quality, independent characters selected for suitability to the particular question being addressed. The relationships inferred in a study should be congruent with those from as many other lines of phylogenetic evidence as possible. Any incongruities should be explicable by well-understood biological mechanisms. It is concluded that the relationships of the three bryophyte lineages to vascular plants should currently be viewed as unresolved. This is a difficult phylogenetic problem; the land plants underwent a rapid radiation a long time ago. Yet, further exploration of analytical methods and careful choice of characters should lead to eventual elucidation of diversification patterns among early land plants.

Aim: The aim of this study was to investigate if tests used to assess core stability could be used to determine success in physiological tests applied to assess dynamic balance and agility for a young active population. Methods: Pearson's r correlation coefficient was used to assess the relationship between the core stability tests and the dynamic balance and agility tests. Evaluation of the tests was established using Cronbach's coefficient of variance as part of intra-rater reliability tests. An analysis of 18 active college aged students was conducted (males: n= 13, females: n= 5). The mean ± SD age for males was 19.2 years ± 3.22 years and for females was 19.4 years ± 1.14 years. Conclusion: The results indicate that there is no significant relationship between tests that assess core stability and tests conducted to assess dynamic balance in active young adults. With the exception of the abdominal flexion test, no significant relationship exists between the remaining core stability tests and agility T-Test. Core stability is not a determinant of balance and agility.

This study explores an optimal strategy for muscle force estimation by integrating simplified cost functions with detailed muscle models, demonstrating significant advantages over traditional complex methods. Using elbow flexion as a case study, we characterize the interplay between muscle models and cost functions, showing that accurate muscle force estimations can be achieved effectively without electromyography (EMG) data while also substantially reducing computational demands. Validated against established bio-mechanical data, our models confirm their accuracy in predicting muscle behavior. This approach has profound implications for enhancing rehabilitation protocols and athletic training, providing a more accessible and adaptable tool for muscle force analysis. It broadens the applicability of muscle force estimation in clinical and sports settings and paves the way for future innovations in bio-mechanical research.

Tadpole shrimp (Triops longicaudatus) has become a major pest for California rice farmers. Currently, management relies solely on the insecticide lambda-cyhalothrin. However, resistance to this pyrethroid was confirmed in 2016, thus identifying an effective and practical biological control method for TPS is a priority. Field trials were conducted from 2017 to 2018 to: (1) evaluate the efficacy of the predatory fish Gambusia affinis and the predatory beetles, Laccophilus maculosus (Say) and Tropisternus lateralis (Fabricius), in controlling TPS, (2) test the efficacy of several inoculation rates of Gambusia affinis at controlling TPS and (3) to explore early indicators of TPS activity and damage as monitoring tools. Both Gambusia affinis and the predatory beetle treatments were not significantly different from the commercial standard (lambda-cyhalothrin). Both four and five Gambusia per 1 m2 controlled TPS as well as lambda-cyhalothrin, and we observed that Gambusia affinis was able to reproduce in the field. Water turbidity was significantly correlated with TPS counts (R = 0.85, N = 20, P &lt; 0.0001 (2017); R = 0.58, N = 30, P = 0.0007 (2018)). The number of dislodged seedlings was less reliably correlated with TPS count; in 2017 correlations were significant (R = 0.84, N = 20, P &lt; 0.0001), however, in 2018 correlations were not significant (R = 0.18, N = 30, P = 0.35). With further refinement water turbidity could play a valuable role in monitoring TPS populations.

This paper presents an analysis of the power flow within the Northern Interconnected Grid of Cameroon. The Newton-Raphson method has been performed, known for its accuracy, under MATLAB software, to model and solve complex power flow equations. This study simulates a series of outage scenarios to evaluate the responsive-ness of the grid. The results obtained underline the crucial importance of reactive power management and highlight the urgent need to consolidate the grid infrastructure of North Cameroon. To increase grid resilience and stability, the paper recommends the strategic integration of renewables and the development of interconnections with other power grids. These measures are presented as viable solutions to meet cur-rent and future energy distribution challenges, ensuring a reliable and sustainable power supply for Cameroon.

A number of regolith-hosted REE occurrences have recently been discovered in the Esperance region in southern Western Australia. This paper summarizes major characteristics of the REE mineralization and discusses contributing factors and potential controls. The main aim is to explain why there is a lack of highly sought-after ion-adsorption clay type REE deposits across the region despite the presence of the regolith-hosted REE mineralization on a regional scale. Local mineralization mostly occurs as continuous flat-lying enrichment “blankets” within the residual regolith developed over Archaean–Proterozoic granite gneisses and granitoids with elevated REE content. The enriched horizon is commonly located in the lower saprolite and saprock and is accompanied by an overlying REE-depleted zone. This distribution pattern, together with the data on HREE fractionation and the presence of the supergene REE minerals, indicate chemogenic type enrichment formed by supergene REE mobilization into groundwater, downward transport and accumulation in the lower part of the weathering profile. Residual REE accumulation processes due to bulk rock volume and mass reduction during weathering also contribute to mineralization. It is proposed that climate and groundwater chemistry are the critical controls on the distribution of REEs in the weathering profile and on their speciation in the enrichment zone. Cenozoic aridification of climate in southwest Australia heavily overprinted pre-existing REE distributions in the weathering profile. Acidic (pH &lt;4), highly saline groundwaters intensely leached away any relatively weakly bound, adsorbed or colloidal REE forms, moving them downward. Dissolved RREs precipitated as secondary phosphates in neutral to alkaline environment at lower Eh near the base of the weathering profile forming the supergene enrichment zone. Low denudation rates, characteristic of areas of low relief under the arid climate, are favorable for the preservation of the existing weathering profiles with REE mineralization.

Although Eulerian approaches are standard in computational acoustics, they are less effective for certain classes of problems like bubble acoustics and combustion noise. A different approach for solving acoustic problems is to compute with individual particles following particle motion. In this paper, a Lagrangian approach to model sound propagation in moving fluid is presented and implemented numerically, using three meshfree methods to solve the Lagrangian acoustic perturbation equations (LAPE) in the time domain. The LAPE split the fluid dynamic equations into a set of hydrodynamic equations for the motion of fluid particles and perturbation equations for the acoustic quantities corresponding to each fluid particle. Then, three meshfree methods, the smoothed particle hydrodynamics (SPH) method, the corrective smoothed particle (CSP) method, and the generalized finite difference (GFD) method, are introduced to solve the LAPE and the linearized LAPE (LLAPE). The SPH and CSP methods are widely used meshfree methods, while the GFD method based on the Taylor series expansion can be easily extended to higher orders. Applications to modeling sound propagation in steady or unsteady fluids in motion are outlined, treating a number of different cases in one and two space dimensions. A comparison of the LAPE and the LLAPE using the three meshfree methods is also presented. The Lagrangian approach shows good agreement with exact solutions. The comparison indicates that the CSP and GFD method exhibit convergence in cases with different background flow. The GFD method is more accurate, while the CSP method can handle higher Courant numbers.

This paper focuses on the paradigm that explains the link between energy transitions and financial transformations. In particular, it attempts to shed some light on the following question: How did the transition from wood to coal affect financial development in late 18^th and early 19^th century Britain? The results demonstrate that the energy transition in Britain during the 1^st Industrial Revolution constituted an important moment in the country's financial development and can be used as an example of how an energy innovation can foster the financial development of particular countries or regions.

Prostate cancer is the second leading cause of death in males in America, with advanced prostate cancers exhibiting a 5-year survival rate of only 32%. Castration-resistance is often developed during the course of treatment, though its influences require further understanding. This study explores the human microbiome for its implications in castration-resistance and metastasis in prostate cancer. RNA sequencing data was downloaded for bone and soft tissue biopsies of patients with metastatic castration-resistant prostate cancer. These sequences were mapped to bacterial sequences to yield species-level abundance approximations. Numerous species were found to correlate to the expression of known markers of castration-resistance, including AR, PI3K, and AKT. Castration-resistance-associated signaling pathways were also enriched with these species, including PI3K-AKT signaling and endocrine resistance. For their implications in cancer aggression and metastasis, cancer stem cell markers were further explored for relation to these species. EGFR and SLC3A2 were widely downregulated with greater abundance of most species. Our results suggest that the microbiome is heavily associated with castration-resistance and stemness in prostate cancer. By considering the microbiome’s importance in these factors, we may better understand the highly aggressive and highly invasive nature of prostate cancer, allowing for needed improvement in the treatment of this disease.

Elevated blood glucose levels, known as glycemia, play a significant role in sudden cardiac arrest, often resulting in sudden cardiac death, particularly among those with diabetes. Understanding the internal mechanisms has been a challenge for healthcare professionals, leading many research groups to investigate the relationship between blood glucose levels and cardiac electrical activity. Our hypothesis suggests that glucose-sensing biophysics mechanisms in cardiac tissue could clarify this connection. To explore this, we adapted a single-compartment, computational model of the human atrial node's action potential. We incorporated glucose-sensing mechanisms with voltage-gated sodium ion channels using ordinary differential equations. Parameters for the model were based on existing experimental studies to mimic the impact of glucose levels on atrial node action potential firing. Simulations using voltage clamp and current clamp techniques showed that elevated glucose levels decreased sodium ion channel currents, leading to a reduction in the sinoatrial node action potential frequency. In summary, our mathematical model provides a cellular-level understanding of how high glucose levels can lead to bradycardia and sudden cardiac death.

Using insights from cybernetics and an information-based understanding of biological systems, a precise, scientifically inspired, definition of free-will is offered and the essential requirements for an agent to possess it in principle are set out. These are: a) there must be a self to self-determine; b) there must be a non-zero probability of more than one option being enacted; c) there must be an internal means of choosing among options (which is not merely random, since randomness is not a choice). For (a) to be fulfilled, the agent of self-determination must be organisationally closed (a `Kantian whole'). For (c) to be fulfilled: d) options must be generated from an internal model of the self which can calculate future states contingent on possible responses; e) choosing among these options requires their evaluation using an internally generated goal defined on an objective function representing the overall `master function' of the agent and f) for `deep free-will', at least two nested levels of choice and goal (d-e) must be enacted by the agent. The agent must also be able to enact its choice in physical reality. The only systems known to meet all these criteria are living organisms, not just humans, but a wide range of organisms. The main impediment to free-will in present-day artificial robots, is their lack of being a Kantian whole. Consciousness does not seem to be a requirement and the minimum complexity for a free-will system may be quite low and include relatively simple life-forms that are at least able to learn.

Information theoretic quantities such as entropy, entropy rate, information gain, and relative entropy are often used to understand the performance of intelligent agents in learning applications. Mean squared error has not played a role in these analyses, primarily because it is not felt to be a viable performance indicator in these scenarios. We build on a new quantity, the log ratio of entropy powers, to establish that minimum mean squared error (MMSE) estimation, prediction, and smoothing are directly connected to Mutual Information Gain or Loss in an agent learning system modeled by a Markov chain for many probability distributions of interest. Expressions for mutual information gain or loss are developed for MMSE estimation, prediction, and smoothing and an example for fixed lag smoothing is presented.

This study aimed at testing the effectiveness of novel combinations of chemical and physical methods to control Prosopis juliflora, an invasive weed in the Moshi and Simanjiro districts of Nothern Tan-zania. Six different treatments including manual uprooting, glyphosate, bark chop with chemical application, two separate chemical mixtures and control were tested in a total of 32 plots, which represented two land use types (grazing land and farmland) found in the two districts. Each plot covered 20m×30m plot area. Two response variables (stem count and tree volume) were recorded to compare weed population density before and after treatment six months later. An analysis of the untreated control plots, showed that the inherent growth potential of P. juliflora was higher in Moshi than in Simanjiro district. The number of stems increased during the experiment for all six treatments showing that the P. juliflora population had not yet reached the local carrying capacity. For the manual control treatment, the increase was reduced compared to the untreated control. For all other treatments, the increase in stem count was on par with that in the untreated control or even higher. Thus, we conclude that only manual uprooting had a controlling effect but not to the extent that it eradicated P. juliflora. Thus, it is for P. juliflora as for weed control in general: weed control must be an ongoing effort.

Manuka honey (MH) exhibits potential antitumor activity in preclinical models of a number of human cancers. Treatment in vitro with MH at concentrations ranging from 0.3-5.0% (w/v) led to significant dose-dependent inhibition of proliferation of human breast cancer MCF-7 cells, but anti-proliferative effects of MH were less pronounced in triple-negative MDA-MB-231 breast cancer cells. Effects of MH were also tested on non-malignant human mammary epithelial cells (HMEC) at 2.5% w/v, and it was found that MH reduced proliferation of MCF-7 cells but not that of HMEC. Notably, the antitumor activity of MH was in the range of that exerted by treatment of MCF-7 cells with the antiestrogen tamoxifen. Further, MH treatment stimulated apoptosis of MCF-7 cells in vitro, with most cells exhibiting acute and significant levels of apoptosis that correlated with PARP activation. Additionally, effects of MH induced activation of AMPK and inhibition of AKT/mTOR downstream signaling. Treatment of MCF7 cells with increased concentrations of MH induced AMPK phosphorylation in a dose dependent manner that was accompanied by inhibition of phosphorylation of AKT and mTOR downstream effector protein S6. In addition, MH reduced phosphorylated STAT3 levels in vitro which may correlate with MH and AMPK-mediated anti-inflammatory properties. Further, in vivo, MH administered alone significantly inhibited the growth of established MCF-7 tumors in nude mice by 84%, resulting in an observable reduction in tumor volume. Our findings highlight the need for further research into the use of natural compounds, such as MH, for antitumor efficacy and potential chemoprevention and investigation of molecular pathways underlying these actions.

Balandra, one of the most popular beaches in La Paz, Baja California Sur, was declared a flora and fauna protection area in 2012 and, in 2021, was declared the best beach in Mexico. More recently, it was included among the ten most beautiful beaches in the world. Currently, this beach faces overcrowding. Formulating effective management policies depends, to a certain extent, on the knowledge of their recreational value and visitor characteristics. Recreational value allows us to know the benefits of the tradeoffs among the ecosystem services and society and exhibit the value of possible damages to marine ecosystems. Like the one caused in 2022 by the fire of a tourist boat inside Balandra. Using the individual travel cost method and applying 159 questionnaires to site visitors, four models were estimated to calculate the individual willingness to pay for accessing Balandra, which ranges between 3.86 and 10.38 US$/day/visitor. Recreational economic value (REV) for Balandra was estimated using two essential criteria. One, total of visitors registered in 2021. Two, daily maximum carrying capacity. We also calculated the REV as a proxy of the welfare loss derived from the site's closure. Finally, possible environmental and economic policy instruments that could be implemented are discussed.

This article examines the impact of climate change on the hydrometeorological state of some lakes and reservoirs in the Akmola and North Kazakhstan regions. Time series with values of various climate parameters for the period 1986-2023 are used for the climate analysis; the reliability of the results was assessed using the Fisher criteria. Hydrometric indicators were studied using the ArcGIG program. Using GIS to spatially analyze water climate data, 8-channel satellite images from 1995 to 2023 were used. During the study, it was found that the area of the main lakes has undergone changes.

A surprising insight from the advent of genomic sequencing was that many genes are deeply conserved during evolution. With a particular focus on genes that interact with light in animals, I explore the metaphor of genetic toolkits, which can be operationalized as lists of genes involved in a trait of interest. A fascinating observation is that genes of a toolkit are often used again and again during convergent evolution, sometimes across vast phylogenetic distances. Such a pattern in the evolution of toolkits requires three different stages: origin, maintenance, and redeployment of the genes. The functional origins of toolkit genes might often be rooted in interactions with external environments. The origins of light interacting genes in particular may be tied to ancient responses to photo-oxidative stress, inspiring questions about the extent to which the evolution of other toolkits were also impacted by stress. Maintenance of genetic toolkits over long evolutionary timescales requires gene multifunctionality to prevent gene loss when a trait of interest is absent. Finally, the deployment of toolkit genes in convergently evolved traits like eyes sometimes involves the repeated use of similar, ancient genes but other times involves different genes specific to each convergent origin. How often a particular gene family is used time and again for the same function may depend on how many possible biological solutions are available. When few solutions exist and are maintained, evolution is constrained to use the same genes over and over. However, when many different solutions are possible, the innovative possibilities of evolution are often on display. Therefore, a focus on genetic toolkits highlights the combination of legacy plus innovation that drives the evolution of biological diversity.

Current trends in systemic risk literature provide new insights into multi-hazard risks that interact and compound with built environments, creating more significant impacts on socio-economic and human systems. Recurrent natural hazards and extreme weather events are more likely to compound and cascade into more impactful events, especially in vulnerable societies. In small-island communities (SICS), including large archipelagos and Small Island Developing States (SIDS), the long-term impact of multi-, compounding-, and cascading-hazards (MCC hazards) can result in persistent vulnerability and residual risks. This is due to delayed responses, limited resources, poverty, fewer evacuation options, and inadequate markets and infrastructure. Using Ternate, a densely populated small volcanic island in North Maluku, Indonesia, as a case study, this paper assesses the impacts of seven types of natural hazards: flash floods, landslides, extreme weather, extreme waves and abrasion, earthquakes, tsunamis, and volcanic eruptions. The research focuses on the multi-hazard impact on population, land use, and infrastructure exposures in 60 villages in Ternate. The findings highlight population density, land use, and infrastructure exposure to multi-hazard risks, providing valuable information on potential losses in future hazard events.

The North China Plain is among the regions most afflicted by ground fissure disasters in China. Recent urbanization has accelerated ground fissure activity in the three counties of the northern North China Plain, posing significant threats to both the natural environment and socioeconomic sustainability. Despite the increased attention, a lack of comprehensive understanding persists due to delayed recognition and limited research. This study conducted field visits and geological surveys across 43 villages and 80 sites to elucidate the spatial distribution patterns of ground fissures in the aforementioned counties. By integrating these findings with regional geological data, we formulated a causative model to explain ground fissure formation. Our analysis reveals a concentration of ground fissures near the Niuxi and Rongxi faults, with the former exhibiting the most extensive distribution. The primary manifestations of ground fissures include linear cracks and patch-shaped collapse pits, predominantly oriented in east-west and north-south directions, indicating tensile failure with minimal vertical displacement. Various factors contribute to ground fissure development, including fault activity, ancient river channel distribution, bedrock undulations, rainfall, and ground settlement. Fault activity establishes a concealed fracture system in shallow geotechnical layers, laying the groundwork for ground fissure formation. Additionally, the distribution of ancient river channels and bedrock undulations modifies regional stress fields, further facilitating ground fissure emergence. Rainfall and differential ground settlement serve as triggering mechanisms, exposing ground fissures at the surface. This research offers novel insights into the causative mechanisms of ground fissures in the northern North China Plain, providing valuable scientific evidence for mitigating ground fissure disasters during the urbanization process in the region.

MicroRNAs, short non-protein coding RNAs, are overexpressed in GCTs. Circulating levels of germ cell tumor (GCT)- associated miRNAs, such as miR-371a-3p, can be utilized as efficient and cost-effective alternatives in diagnosing and managing patients presenting with GCTs. This quality of miRNAs has demonstrated favorable performance characteristics as a reliable blood-based biomarker with high diagnostic accuracy compared to current serum tumor markers (STMs) including α-fetoprotein (AFP), beta human chorionic gonadotropin (β-hCG), and lactate dehydrogenase (LDH). The conventional STMs exhibit limited specificity and sensitivity. Potential clinical implications of miRNAs include impact on de-escalating or intensifying treatment, detecting recurrence at earlier stages, and lessening the necessity of cross-sectional imaging or invasive tissue biopsy for non-teratomatous GCTs. Here we also highlight the outstanding issues that must be addressed prior to clinical implementation. Standards for measuring circulating miRNAs and determining ideal cutoff values are essential for integration into current clinical guidelines.

California and most other coastlines around the world are being impacted by both long-term sea-level rise and short-term extreme events. Because of California’s long and intensively developed coastline, it is an important area for evaluating responses to these challenges. The predominant historic approach to coastal erosion in California and globally has been the construction of hard coastal armoring such as seawalls and rock revetments. The concept of living shorelines – defined as using natural elements like plants, sand or rocks to stabilize the coastline – has been widely proposed as a soft or green response to coastal erosion and flooding. These approaches have very limited application in high-energy environments, however, such as California’s 1,100-mile-long outer coast and are not realistic solutions for protection from wave attack at high tides or long-term sea-level rise. Each of the state’s coastal communities need to identify their most vulnerable areas, develop adaptation plans, and plan eventual relocation strategies in response to an accelerating sea-level rise.

Animals are distinguished by their complex developmental programs, in which transcription factors play essential roles in coordinating the regulation of the genome. Thus, it has been hypothesized that animal origins involved the evolution of increasingly complex transcriptional regulatory mechanisms that permit greater spatiotemporal control over gene expression. Here, we revisit this hypothesis in light of new genomic and functional data from diverse phylogenetically-relevant taxa, including early branching animals (sponges, ctenophores) and close relatives of animals (choanoflagellates, filastereans, ichthyosporeans). We argue that many of the mechanisms posited to explain animal transcriptional complexity, such as large increases in transcription factor numbers, new transcription factor families, and distal enhancers, did not factor significantly into animal origins. Instead, we propose that the re-purposing of pre-existing transcriptional regulatory modules through cis-regulatory evolution and gene duplication events, combined with new protein-protein interactions among TFs, may have been fundamental to the transcriptional regulatory architecture of the first animals.

Diabetic foot ulcers (DFUs) significantly affect the lives of patients and increase the risk of hospital stay and amputation. We suggest a remote-monitoring platform for better DFU care. This system uses digital health metrics (scaled from 0 to 10, where higher scores indicate a greater risk of slow healing) to provide a comprehensive overview through a visual interface. The platform features smart offloading devices that capture behavioral metrics such as offloading adherence, daily steps, and cadence. Coupled with remotely measurable frailty and phenotypic metrics, it offers an in-depth patient profile. Additional demographic data, wound characteristics, and clinical parameters, such as cognitive function, were integrated, contributing to a comprehensive risk factor profile. We evaluated the feasibility of this platform with 124 DFU patients over 12 weeks; 39% experienced unfavorable outcomes such as dropout, adverse events, or non-healing. Digital biomarkers were benchmarked (0-10), categorized into low, medium, and high risk for unfavorable outcomes, and visually represented using color-coded radar plots. The initial results of case reports illustrate the value of this holistic visualization to pinpoint the underlying risk factors for unfavorable outcomes, including a high number of steps, poor adherence, and cognitive impairment. Although future studies are needed to validate the effectiveness of this visualization in personalizing care and improving wound outcomes, early results in identifying risk factors for unfavorable outcomes are promising.

This study evaluates the effectiveness of Darknet53 and VGG16 pretrained models to develop a hybrid ensemble model named HybridPlantNet23 deep learning model for effective plant disease classification, using the publicly available dataset ‘A Dataset of Leaf Images’ from Mendeley webpage. The preprocessing of the dataset involved resizing the images to the respective requirements of the pretrained models to develop a combined datastore which served as the input. All experiments were conducted using MATLAB R2023b deep network designer interface. Model performances were evaluated based on the conventional accuracy, precision, recall, and F1-score. VGG16 achieved the highest accuracy (97.25%), precision (96.30%), recall (96.96%), and F1-score (96.55%), outperforming both Darknet53 and the ensemble HybridPlantNet23 model. Despite the advanced architecture of the ensemble model, its performance (accuracy: 95.37%, precision: 93.56%, recall: 94.20%, F1-score: 93.74%) was not significantly superior, thus highlighting scientific reasons behind this development. Recommendations for future works were provided accordingly.

The quiet-time solar wind electrons feature non-thermal characteristics when viewed from the perspective of their velocity distribution functions. They typically have an appearance of being composed of a denser thermal “core” population plus a tenuous energetic “halo” population. At first, such a feature was empirically fitted with the Kappa velocity space distribution function, but ever since the ground-breaking work by Tsallis, the space physics community has embraced the potential implication of the Kappa distribution as reflecting the non-extensive nature of the space plasma. From the viewpoint of microscopic plasma theory, the formation of non-thermal electron velocity distribution function can be interpreted in terms of the plasma being in a state of turbulent quasi equilibrium. Such a finding brings forth the possible existence of a profound inter-relationship between the non-extensive statistical state and the turbulent quasi-equilibrium state. The present paper further develops the idea of solar wind electrons being in the turbulent equilibrium, but unlike the previous model, which involves the electrostatic turbulence near the plasma oscillation frequency (i.e., Langmuir turbulence), the present paper considers the impact of transverse electromagnetic turbulence, particularly, the turbulence in the whistler-mode frequency range. It is found that the coupling of spontaneously-emitted thermal fluctuations and the background turbulence leads to the formation of non-thermal electron velocity distribution function of the type observed in the solar wind during quiet times. This demonstrates that the whistler-range turbulence represents an alternative mechanism for producing the Kappa-like non-thermal distribution, especially close to the Sun and in the near-Earth space environment.

One of the most concerning global environmental issues is the pollution of agricultural soils by heavy metals (HMs), especially cadmium (Cd), which not only affects human health by taking Cd-containing foods but also impacts the quality of rice. The soil's nitrification and denitrification processes, coupled with the release of volatile organic compounds by plants, raise substantial concerns. The understanding of three aspects of paddy soil under conditions of heavy-metal pollution and water management is currently limited. In this review, we summarized recent literature related to the deleterious effects of Cd on both soil processes related to the N cycle and rice quality, particularly aroma, in different water management practices. Under both continuous flooding (CF) and alternate wetting and drying (AWD) conditions, cadmium (Cd) has been observed to reduce both nitrification and denitrification processes. The adverse effects are more pronounced in continuous flooding (CF) compared to alternate wetting and drying (AWD). Similarly, the alteration in rice aroma is more significant in AWD than in CF. The precise modulation of volatile organic compounds (VOCs) by Cd, remains unclear based on the available literature. Nevertheless, HM accumulation is higher in AWD conditions compared to CF, leading to a detrimental impact on volatile organic compounds (VOCs). The literature concluded that AWD practices should be avoided in Cd contaminated fields to decrease accumulation and maintain the quality of rice. In the future, rhizospheric engineering and plant biotechnology can be used to decrease the transport of HMs from the soil to the plant’s edible parts.

In this paper, four probability functions are compared with the purpose of establishing a methodology to improve the accuracy of the estimated wind energy in a desert city in northwestern Mexico. For the statistical modeling, 3 time series of wind speed data were used, corresponding to the years 2017, 2018, and 2019, recorded with a sonic anemometer at a sampling frequency of 10 Hz. From these, the analysis is performed with different stationarity periods (5, 30, 60, and 600 seconds). The estimation of the parameters characterizing the probability density functions was performed using different methods; the statistical models were evaluated by the coefficient of determination and the Nash-Sutcliffe efficiency coefficient, while their accuracy by the measured quadratic error, the mean square error, the mean absolute error, and the mean absolute percentage error. It was found that Weibull with the energy pattern factor method and Gamma using the method of moments were the probability density functions that best describe the statistical behavior of the wind speed and, therefore, better estimate the energy generated, so it is concluded that the proposed methodology will allow having greater confidence, both in the estimation of the wind speed and in the small wind energy available for its use.

Dirac's Large Number Hypothesis (LNH), proposed in 1937, has captivated the scientific community with its exploration of profound correlations between cosmic and atomic scales. This hypothesis delves into the intricate interplay between the infinitesimally small and the vastly large, offering potential insights into the fundamental nature of the universe. As we continue to uncover the mysteries of the cosmos, the LNH oscillates on the precipice of scientific acceptance—neither fully validated nor entirely dismissed. In this review paper, we embark on a comprehensive journey through Dirac's LNH, shedding light on its theoretical underpinnings, its implications for universe models, and its resonance with the Anthropic Principle. We delve into the possibilities of variable gravitational constants and continuous mass creation, inviting further exploration into the intricacies of our cosmic symphony. By embracing the ongoing quest for understanding, we endeavor to unravel the profound harmonies that connect the infinitesimal with the infinite, contributing to the symphony of knowledge in theoretical physics and cosmology.

Climate change is challenging the agricultural sector worldwide. The pressure exerted by the altered thermal conditions drives the zonal shift for various cultivations. This study presents the multiyear analysis of the Growing Degree Days (GDD) index over the Northern Mediterranean Basin (NMB), focused on the high-value vine cultivation derived from the E-OBS dataset. To handle this extensive environmental dataset, R-language scripts and packages were applied, along with the capabilities of the GIS software. The investigated time period spans from 1969 to 2018, and the performed analysis indicates a broad shift/expansion in areas of GDD exceeding 2000 heat units. The extracted results specify the viticultural areas where the GDD index surpasses the suitable values for vine cultivation, owing to the increase of the thermal stress risk. In addition to mapping areas with GDD ≥ 2000, spatial calculations of the surface of areas meeting this criterion per country in the study area were made. In the northern parts of the NMB, the rise of the GDD index values indicates the establishment of vine plantations in the future.

HER2/neu positive breast tumors predict a high mortality and comprise 25-30% of breast cancer. We have shown that Flavokawain A (FKA) preferentially reduces the viabilities of HER2 overexpressing breast cancer cell lines (i.e. SKBR3 and MCF7/HER2) versus those with less HER2 expression (i.e. MCF7 and MDA-MB-468). FKA at cytotoxic concentrations to breast cancer cell lines also has minimal effect on the growth of non-malignant breast epithelial MCF10 cells. FKA induces G2M arrest in cell cycle progression of HER2 overexpressing breast cancer cell lines through inhibition of Cdc2 and Cdc25C phosphorylation and down-regulation of Myt1 and Wee1expression leading to increased Cdc2 kinase activities. In addition, FKA induces apoptosis in SKBR3 cells by increasing the protein expression of Bim and BAX and decreasing expression of Bcl₂, Bcl_x/L , XIAP and survivin. FKA also down-regulates the protein expression of HER-2 and inhibits AKT phosphorylation. Herceptin plus FKA treatment leads to enhanced growth inhibitory effect on HER-2 overexpressing breast cancer cell lines through down-regulation of Myt1, Wee1, Skp2, Survivin and XIAP. Our results suggest the promise of FKA as a novel apoptosis inducer and G2 checkpoint abrogating agent in combination with Herceptin for treatment of HER2 overexpressing breast cancer.

As urban areas expand and populations grow, environmental challenges such as the urban heat island effect, air pollution, and light pollution intensify. The urban heat island effect exacerbates extreme heat conditions, leading to prolonged periods of unhealthy and hazardous environments for both humans and other species. This study investigates the thermal environment associated with the urban heat island effect, focusing on the role of trees in mitigating this issue. Using ENVI-met simulations, the study examines various factors influencing tree cooling effectiveness, including seasonal variations, building shading, transpiration rates, tree placement, and spacing. A new tree-planting strategy is developed based on these findings, aiming to enhance thermal comfort. The study compares the thermal environment of sidewalks under the new tree-planting scheme with the existing arrangement across different months. Results indicate that the new scheme reduces UTCI temperatures by 2.2°C on the hottest day, 0.97°C on the coldest day, and 1.52°C annually in the study area of Los Angeles, demonstrating that the cooling benefits of trees in hot weather outweigh the potential drawbacks in cold weather, highlighting its potential to mitigate the urban heat island effect.

The study investigated the application of Wastewater-Based Epidemiology (WBE) as a tool for monitoring SARS-CoV-2 prevalence in a city in Northern Italy from October 2021 to May 2023. Starting from a widely applied deterministic model, this study proposed a variation to take into account population characteristics and virus biodegradation in the sewer network. The model calculated virus loads and corresponding COVID-19 cases over time in different areas of the city and was validated with healthcare data while considering viral mutations, vaccinations, and testing variability. The correlation between the predicted and reported cases was high across the three waves that occurred in the considered period, demonstrating the model’s capacity to predict relevant fluctuations in the number of cases. Population characteristics did not substantially influence the predicted and reported infection rates. Conversely, biodegradation significantly reduced the virus load reaching the wastewater treatment plant, resulting in a 30% reduction in the total virus load produced in the study area. This approach can be applied for comparing virus load values across cities with varying population demographics and sewer network structures, enhancing the comparability of WBE data for effective surveillance and intervention strategies.

The role of natural factors mainly solar eleven-year cycle variability, and volcanic eruptions on two major modes of climate variability the North Atlantic Oscillation (NAO) and El Niño Southern Oscillation (ENSO) are studied for around last 150 years period. The NAO is the primary factor to regulate Central England Temperature (CET) during winter throughout the period, though NAO is impacted differently by other factors in various time periods. Solar variability indicates a strong positive influence on NAO during 1978-1997, though suggests opposite in earlier period. Solar NAO lag relationship is also shown sensitive to the chosen times of reference and thus points towards the previously proposed mechanism/ relationship related to the sun and NAO. The ENSO is influenced strongly by solar variability and volcanic eruptions in certain periods. This study observes a strong negative association between the sun and ENSO before the 1950s, which is even opposite during the second half of 20th century. The period 1978-1997, when two strong eruptions coincided with active years of strong solar cycles, the ENSO, and volcano suggested a stronger association, and we discussed the important role played by ENSO. That period showed warming in central tropical Pacific while cooling in the North Atlantic with reference to the later period (1999-2017) and also from chosen earlier period. Here we show that the mean atmospheric state is important for understanding the connection between solar variability, the NAO and ENSO and associated mechanism. It presents a critical analysis to improve knowledge about major modes of variability and their role in climate. We also discussed the importance of detecting the robust signal of natural variability, mainly the sun.

The purpose of this paper is to provide empirical evidence to water policy-makers and the evaluation of the application of economic instruments such as price and other factors affecting demand, they contribute to improved decision-making around water management in the Biosphere Reserve El Vizcaino, Mexico. It was estimated a dynamic function with average price specification and other price perception specification. The findings show that consumers react to average price perceived and not the marginal price; long-run price elasticity is higher than short-run and both elasticities are inelastic. Elasticities inelastic with rising prices generate high incomes to improve water planning, supply quality and expand service coverage. The results suggest that the level of knowledge of users on the price is key to take into account restructuring rates in a scenario where the consumer has asymmetric information and themselves achieve goals of economic efficiency, social equity and environmental sustainability.

Enhanced electrical activity in detrusor smooth muscle (DSM) cells is a key factor in detrusor overactivity which causes overactive bladder pathological disorders. Transient receptor potential melastatin-4 (TRPM4) channels, calcium-activated cation channels, play a role in regulating DSM electrical activities. These channels likely contribute to depolarizing the DSM cell membrane, leading to bladder overactivity. Our research focuses on understanding TRPM4 channel function in mouse DSM cells using computational modeling. We aimed to create a detailed computational model of the TRPM4 channel based on existing electrophysiological data. We employed a modified Hodgkin-Huxley model with an incorporated TRP-like current to simulate action potential firing in response to current and synaptic stimulus inputs. Validation against experimental data showed close agreement with our simulations. Our model is the first to analyze the TRPM4 channel's role in DSM electrical activity, potentially revealing insights into bladder overactivity. In conclusion, TRPM4 channels are pivotal in regulating human DSM function and TRPM4 channel inhibitors could be promising targets for treating overactive bladder.

The rapid evolution of drug resistance is one of the greatest health issues of the 21st century. There is an alarming situation to find new therapeutic strategies or candidate drugs to tackle ongoing multi-drug resistance development. The marine environment is one of the prime natural ecosystems on Earth, the majority of which is still unexplored, especially when it comes to the microbes. A wide variety of bioactive compounds have been obtained from a varied range of marine organisms, however, marine bacteria-produced bacteriocins are still undermined. Owing to the distinct environmental stresses that marine bacterial communities encounter, their bioactive compounds frequently undergo distinct adaptations that confer on them a variety of shapes and functions, setting them apart from their terrestrial counterparts. The ribosomally-synthesized and posttranslationally modified peptides (RiPPs), bacteriocins are of special interest because of their variety in structure and diverse potential biological activities. Additionally, the gut microbiome of marine creatures are largely unexplored source of new bacteriocins with promising activities. There is a huge possibility of novel bacteriocins from marine bacterial communities that might come out as efficient candidates to fight against antibiotic resistance, especially in light of the growing pressure from antibiotic-resistant diseases and industrial desire for innovative treatments. The present review summarizes known bacteriocins from marine bacteria, evolutionary aspects, challenges, and huge possibilities of unexplored bacteriocins from marine bacterial communities.

Oxidative stress, characterized by an imbalance between the production of reactive oxygen species (ROS) and the body's antioxidant defenses, significantly affects cellular function and viability. It plays a pivotal role in modulating action potentials (APs), essential for properly functioning excitable cells such as neurons, smooth muscles, pancreatic beta cells, and myocytes. The interaction between oxidative stress and AP dynamics is crucial for understanding the pathophysiology of various conditions, including neurodegenerative diseases, cardiac arrhythmias, and ischemia-reperfusion injuries. This review explores how oxidative stress influences APs, focusing on alterations in ion channel functionality, signaling pathways, and membrane properties. By integrating current research, we aim to elucidate how oxidative stress contributes to disease progression and discuss potential therapeutic interventions targeting this interaction.

This article studies electrostatic fields and potentials in the presence of conductors and point charges under the framework of solving Laplace’s equation with specifi ed boundary conditions. The results demonstrate that many problems posed and solved in elementary electrostatics through various heuristics such as the method of images, can be more rigorously treated under the solution framework of Laplace’s equation.

The unified Mittag-Leffler (ML) function is important factor in formulation of compact form of fractional integrals. In this paper estimations of integral operators, with the unified ML function as kernel are given. The Hadamard inequality in the form of fractional integrals is proved by considering refinement of convexities. These estimations provide various inequalities as refinements of recently published results.

Within the European Union (EU), new plant varieties, to be included at the Common catalog of a member state, has to be registered at the national list, after plant variety testing processes to establish whether the candidate variety is distinguishable, uniform and stable (DUS) and meets the requirement of the cultivation or use value requirement (VCU). Technical development, climate change and changing consumer needs, including the detection of GMOs, necessitate the innovation of plant variety testing methods. Within the EU-funded "InnoVar" project, it has been sent out questionnaires to several countries, which were aimed at analyzing strengths, weaknesses, opportunities and threats (SWOT) of the current methods and with their help it is possible to have look for a new direction, opportunity and strategy, which can incorporate together with the innovation results into the development of the new methods. Our study confirmed that the SWOT analysis could be used to achieve the set goals; according to the answers to the questionnaires, it became necessary to introduce new characters (e.g. cold tolerance) and new test methods (molecular markers, precision techniques, organic farming) into the variety testing procedures. The development of high-yielding, disease and/or pest-resistant plant varieties with good adaptability and the accurate evaluation of genotypes play a crucial role in ensuring that farmers can access high-performing plant varieties and contribute to sustainable food production.

External hoof characteristics, balance, and conformation have been extensively studied in horses; however, mules remain understudied in these aspects. This study evaluated the size, shape, and symmetry of untrimmed and unshod forelimb hooves, compared the symmetry between forelimb hooves and stratified external forelimb hoof measurements based on the body condition score of mules raised in the foothill plains of northern Thailand. The forelimb hooves of 38 mules were photographed and 33 parameters, including angular and linear measurements, were analyzed. Despite the absence of shoeing and trimming, these mules exhibited optimal left-right forelimb hoof symmetry, with no significant (p < 0.05) differences in: outer wall length and inner wall length (OWL - IWL); sole length and sole width (SLS - SW); dorsal hoof wall length and heel length (DHWL - HL); and frog length and frog width (FL - FW). However, significant (p < 0.05) differences were observed within each body condition score group for forelimb hoof measurements for DHWL, IWL, heel separation (HS), heel bulb distance (HBD), SW, FW, and FL. These findings provide valuable insights into mule welfare and management, contributing to understanding of the interplay between overall health and hoof conformation in the study area.

The study aims at evaluating the demand of forest bathing in the Northern Italy’s regions underlining the willingness to pay and the potential tourists’ habits and flows on attending alpine contexts. Through the submission of a questionnaire, the sample’s answers have been analyzed employing a stratified sampling methodology considering three different macro areas (Northwest regions, Northeast regions, and Friuli Venezia Giulia region). After analyzing the sample attitudes, the research approached the estimation section by calculating the flow as the number of potential forest bathing hikes per year and the willingness to pay trough the Contingent Valuation Method. The main results indicate that Forest Bathing activity in Northern Italy have a considerable monetary value and it is generally compared with positive feelings, particularly concerning well-being, and fascination factors.

The proliferation of wearable technology enables the generation of vast amounts of sensor data, offering significant opportunities for advancements in health monitoring, activity recognition, and personalized medicine. However, the complexity and volume of this data present substantial challenges in data modeling and analysis, which have been tamed with approaches spanning time series modeling to deep learning techniques. The latest frontier in this domain is the adoption of Large Language Models (LLMs), such as GPT-4 and Llama, for data analysis, modeling, understanding, and generation of human behavior through the lens of wearable sensor data. This survey explores current trends and challenges in applying LLMs for sensor-based human activity recognition and behavior modeling. We discuss the nature of wearable sensors data, the capabilities and limitations of LLMs to model them and their integration with traditional machine learning techniques. We also identify key challenges, including data quality, computational requirements, interpretability, and privacy concerns. By examining case studies and successful applications, we highlight the potential of LLMs in enhancing the analysis and interpretation of wearable sensors data. Finally, we propose future directions for research, emphasizing the need for improved preprocessing techniques, more efficient and scalable models, and interdisciplinary collaboration. This survey aims to provide a comprehensive overview of the intersection between wearable sensors data and LLMs, offering insights into the current state and future prospects of this emerging field.

Accurate fire severity mapping is essential for understanding the impacts of wildfires on vegetation dynamics in arid savannas. The frequent wildfires in these biomes often cause topkill, where vegetation experiences above-ground combustion, but the below-ground root structures survive, allowing for subsequent regrowth post-burn. Investigating post-fire regrowth is crucial for maintaining ecological balance, elucidating fire regimes, and enhancing the knowledge base of land managers regarding vegetation response. This study examined the relationship between bush fire severity and post-burn coppicing/regeneration events of woody vegetation in the Kalahari Desert of Botswana. Utilizing UAV-derived RGB imagery combined with a Random Forest (RF) classification algorithm, we aimed to enhance the precision of burn severity mapping at a fine spatial resolution. Our research focused on a 1 km2 plot within the Modisa Wildlife Reserve, extensively burnt by the Kgalagadi Transfrontier Fire of 2021. The UAV imagery, captured at various intervals post-burn, provided detailed orthomosaics and canopy height models, facilitating precise land cover classification and burn severity assessment. The RF model achieved an overall accuracy of 79.5% and effectively identified key burn severity indicators, including green vegetation, charred grass, and ash deposits. Our analysis revealed a &gt;50% probability of woody vegetation regrowth in high severity burn areas six months post-burn, highlighting the resilience of these ecosystems. This study demonstrates the efficacy of low-cost UAV photogrammetry for fine scale burn severity assessment and provides valuable insights into post-fire vegetation recovery, thereby aiding land management and conservation efforts in savannas.