In this paper, we introduce a specialized, fully automated experimental arrangement designed for assessing the effectiveness of augmented and virtual reality technologies in healthcare setting and explore its design principles focusing on depth sensor characterization. The main goal of this project is to establish a robust benchtop platform for the quantitative evaluation of extended reality technologies in a controlled environment, emphasizing the practical assessment of augmented reality head-mounted devices. We outline a design concept and considerations for an experimental configuration aimed at creating a realistic testing environment. This apparatus comprises an observation platform mounted on a three-degree-of-freedom motorized system and a test phantom stage. Focusing on real-case scenarios, we utilized a range of sensors, including readily available range-sensing cameras and commercial augmented reality headsets, such as the Intel RealSense L515 LiDAR camera, mounted on the motion control system. The setup enabled automated data collection and facilitates controlled assessments and validation of various facets of augmented reality technologies, including object, hand, and head tracking, as well as static and dynamic image registration. This paper describes the system architecture, the process of automated data collection, and presents several evaluation studies conducted with this setup, providing insights into the quality and temporal noise associated with static or moving objects or observers in augmented reality applications.

The purpose of the study is to establish compliance of the design of the modernized car with the requirements for safe operation. An option has been proposed for upgrading a passenger wagon to a Mobile Diagnostic Complex for transporting a combined vehicle equipped with appropriate flaw detection equipment intended for rail diagnostics. The authors have established the most optimal option for locating the diagnostic vehicle on board the Mobile Diagnostic Complex (MDC) wagon, taking into account the additional load from the vehicle. To achieve this goal, the article developed a three-dimensional model of the supporting structure of the wagon body, proposed a methodology and presented the results of a study of the stress-strain state of the wagon body, taking into account the additional weight of the wagon. The article develops a methodology for studying the natural frequencies of vibrations of the wagon body and develops a three-dimensional model of the wagon for calculating dynamic indicators in the Universal Mechanism software package. Taking into account the previously carried out strength calculations, as well as in order to maintain the factory life cycle indicators of the supporting structure of the wagon body, it is recommended to use the model in the first version.

The design complexity of the new generation of civil aero-engines results in higher demands on engines’ components, higher component temperature, higher heat generation, and, finally, critical thermal management issues. This paper will propose a methodological approach to create physics-based models for heat loads developed by sources as well as a systematic sensitivity analysis to identify the effects of design parameters on the thermal behaviour of civil aero-engines. The ranges and levels of heat loads generated by heat sources (e.g., accessory gearbox, bearing, pumps, etc.) and heat absorption capacity of heat sinks (e.g., engine fuel, oil, and air) are discussed systematically. The practical research challenges for thermal management system design and development for the new and next generation of turbofan engines will then be addressed through a sensitivity analysis of the heat load values as well as the heat sinks flow rates. The potential solutions for thermal performance enhancements of propulsion systems will be proposed and discussed accordingly.

The process involved in preparing driving simulator tests is a labor intensive one, and the nature of this complexity depends on the sophistication of the tests to be carried out, as well as the number of participants. Which has an impact on the duration of the research itself. The very solution of using driving simulators is a research tool that has been in use for many years and with great success. They are used in a very wide range of areas of human functioning. They replicate in a very realistic way the conditions that can occur in the external environment, offer the possibility of repetition of particular conditions and insight into certain behaviors that could be very difficult to initiate in real life. This article also describes the dis- ease of using simulators to conduct research activities, along with the workflow from assumptions to finalizing the research. An algorithm is also presented for the study of individual participants, with examples for separate research scenarios concerning driver behavior in the vicinity of pedestrian crossings.

Cars are a highly inefficient mode of urban transport with significant negative impacts. Electric vehicles make it possible to eliminate direct CO2 emissions (though the total over a vehicle’s entire life cycle greatly offsets the advantages) but leave unchanged – or even aggravate – all the other negative effects on the quality of urban environments. Three visions for urban transport were presented: automobility, multimodality and accessibility. The first dominates North American cities, the second European one. The anomalies of these two visions have been examined. The automobility cities cannot manage the congestion and the attempts are self- defeating. The anomalies of multimodality city are related to the public space consumption for mobility and the impossibility to plan spatial proximity. The sustainable vision, that resolve the anomalies, is represented by the accessibility city in the Triple Access System (TAS) version which, however, still has a long way to go to be accepted and implemented.

In this study, we investigate the growth of EV ownership among Swedish households. Through detailed socio-economic data and the Swedish vehicle register, we are able compare characteristics of households that bought an EV in 2016 with those that became EV owners in 2020. We are thus able to describe and analyse the transition from the early EV owners to the early majority. Unlike many prior studies in the field, which are based on surveys or interviews, this study relies on registry data, thereby encompassing all car owners in Sweden. In this study, we have also scrutinized the significance of ownership mode by distinguishing between households that have chosen to purchase a car and those that have chosen to lease one. The results show that the demand for EVs has reached new consumer groups, e.g. both younger and older car buyers, and that the option to lease a car privately has broadened the market for new cars in general, and for EV’s in particular.

Electrical contacts are important circuit components with diverse industrial applications, and their failure can lead to multiple unwanted effects. Hence, the behavior of electrical contacts is a widely studied topic in scientific literature based on various approaches, tools, and techniques. The present study proposes a numerical modeling and simulation approach based on the Holm contact theory to study the dependence between the electric potential and the temperature within an electrical contact. Structured in 5 sections, the research was conducted using COMSOL Multiphysics software and its solid-state mechanics, electric current, and heat transfer modules in order to highlight contact behavior from mechanical, electrical and thermal points of view: the von Mises stress, contact force, the electric field amplitude, the variation of the electrical potential along the current path, the temperature gradient, and dependence of temperature along the contact elements edges were obtained by simulation and graphically represented. The results are in line with the expectations and with past research that was studied in the literature review.

To improve efficacy and safety of sunscreen emulsions, UV‐filter skin permeation could be kept as low as possible by reducing UV‐filter content or changing emulsion composition. In this work, different lipid phase ratio (12, 14 and 16% w/w) were assessed for their ability to affect the technological and sensory properties of O/W emulsions in which bemotrizinol (BMTZ), a broad spectrum sunscreen agent, was incorporated free or loaded into nanostructured lipid nanocarriers (NLC) to reduce its release from the vehicle and, hence, its skin permeation. The following technological properties were evaluated in vitro by suitable methodologies: spreadability, viscosity, pH, occlusion factor, BMTZ release, sun protection factor (SPF). Sensory attributes were assessed by trained panelists in three different phases: before/during pick‐up, rub‐in, after application. Raising the lipid phase ratio led to an increase of viscosity and to a corresponding drop of spreadability while the incorporation of BMTZ‐loaded NLC determined a decrease of occlusion factor and an increase of SPF. No BMTZ release was observed from all emulsions. Sensory attributes were mainly affected by lipid phase ratio. These results suggest that lipid phase ratio and BMTZ incorporation into NLC could contribute to determine technological and sensory properties of O/W emulsions.

In order to achieve the elimination of the negative impacts of transport on road safety, the European Union is taking various measures resulting from its commitment to improve road safety. One of the instruments for achieving the objectives set is social legislation for the work of drivers in road freight and passenger transport. In line with the objective of improving the quality of working conditions for road transport drivers and road safety, the European Union applies Regulation (EC) No 561/2006 on the harmonisation of certain social legislation relating to road transport, which lays down rules on driving times, breaks and rest periods for drivers operating in road freight and passenger transport. The main objective of the paper is to assess the impact of social legislation on road transport safety by means of real research and to identify the factors influencing the violation of the legislation depending on the type of transports carried out in domestic or international road freight transport.

In Yaoundé, Cameroon, excessive and inappropriate speeding remains a major public health concern. Part of the problem are the unsafe speed limits, lack of evidence, and effective evaluation of speeding safety performance indicators (SSPIs), and the absence of speed management, hindering the city's ability to mitigate the risks associated with speeding. This study aimed to address this knowledge gap by assessing SSPIs using a well-defined methodology and suggesting speed management strategies. Data on speed, traffic volumes and road attributes were collected from a random selection of 16 representative road sections in Yaoundé. Seven SSPIs were calculated, and weights were assigned to evaluate city-level SSPIs. The findings showed that 66.8% of drivers drive within the speed limit, generally operating at speeds of 54 km/h with a speed variation of 26 km/h. Based on the speed analysis, evidence-based strategies are proposed, and implementing these strategies could potentially reduce fatalities and serious injuries by 16% to 84% across study locations, as indicated by Elvik's model. These findings have significant policy implications for reducing speeding in Yaoundé, and the methodological approach can be replicated in other urban settings. Future research should extend SSPI evaluation to the national level and test the effectiveness of the recommended strategies.

CD44 is a type I transmembrane glycoprotein, which is associated with poor prognosis in various solid tumors. Since CD44 plays critical roles in tumor development by regulating cell adhesion, survival, proliferation, and stemness, it has been considered a target for tumor therapy. Anti-CD44 monoclonal antibodies (mAbs) have been developed and applied to antibody-drug conjugates and chimeric antigen receptor-T cell therapy. We previously developed anti‐pan-CD44 mAbs, C₄₄Mab-5 and C₄₄Mab-46, which can recognize both CD44 standard (CD44s) and variant isoforms. In the present study, a defucosylated mouse IgG_2a version of the anti-pan-CD44 mAbs (5-mG_2a-f and C₄₄Mab-46-mG_2a-f) was generated to evaluate the antitumor activities against CD44-positive cells. Both 5-mG_2a-f and C₄₄Mab-46-mG_2a-f recognized CD44s-overexpressed CHO-K1 (CHO/CD44s) cells and esophageal tumor cell line (KYSE770) in flow cytometry. Furthermore, both 5-mG_2a-f and C₄₄Mab-46-mG_2a-f could activate effector cells in the presence of CHO/CD44s cells and exhibited the complement‐dependent cytotoxicity against both CHO/CD44s and KYSE770 cells. Furthermore, the administration of 5-mG_2a-f and C₄₄Mab-46-mG_2a-f significantly suppressed CHO/CD44s and KYSE770 xenograft tumor development compared with the control defucosylated mouse IgG_2a. These results indicate that 5-mG_2a-f and C₄₄Mab-46-mG_2a-f could exert antitumor activities against CD44-positive cancers and could be a promising therapeutic regimen for tumors.

One of the G protein-coupled receptors, C-C chemokine receptor 5 (CCR5), is an important regulator for the activation of T and B lymphocytes, dendritic cells, natural killer cells, and macrophages. Upon binding to the ligands, CCR5 activates downstream signaling, which plays critical roles in the innate and adaptive immune response through the promotion of lymphocyte migration and the secretion of pro-inflammatory cytokines. Anti-CCR5 monoclonal antibodies (mAbs) have been developed and evaluated in clinical trials for tumors and inflammatory diseases. In this study, we developed novel mAbs for mouse CCR5 (mCCR5) using the N-terminal peptide immunization. Among the established anti-mCCR5 mAbs, C₅Mab-4 (rat IgG_2a, kappa) and C₅Mab-8 (rat IgG₁, kappa), recognized mCCR5-overexpressed Chinese hamster ovary-K1 (CHO/mCCR5) and an endogenously mCCR5-expressing cell line (L1210) by flow cytometry. The dissociation constant (K_D) values of C₅Mab-4 and C₅Mab-8 for CHO/mCCR5 were determined as 3.5 × 10⁻⁸ M and 7.3 × 10⁻⁹ M, respectively. Furthermore, both C₅Mab-4 and C₅Mab-8 could detect mCCR5 by western blotting. These results indicated that C₅Mab-4 and C₅Mab-8 are useful for detecting mCCR5 by flow cytometry and western blotting and provide a possibility to obtain the proof of concept in preclinical studies.

C-C motif chemokine receptor-8 (CCR8) belongs to class A of G protein-coupled receptors (GPCRs). CCR8 interacts with the specific chemokine ligand CCL1/I-309 in humans, which is produced by various cells, including tumor-associated macrophages and regulatory T cells (Treg). CCR8 is highly expressed on Treg and T-helper 2 (T_H2) cells recruited to the inflammation site and is implicated in allergy, asthma, and cancer progression. The CCR8⁺Treg has been suggested to be an important regulator in the immunosuppressive tumor microenvironment (TME); therefore, it has been desired to develop sensitive monoclonal antibodies (mAbs) for CCR8. This study developed a specific mAb for human CCR8 (hCCR8), which is useful for flow cytometry by employing the Cell-Based Immunization and Screening (CBIS) method. The established anti-hCCR8 mAb, C₈Mab-21, (mouse IgM, kappa) reacted with hCCR8-overexpressed Chinese hamster ovary-K1 (CHO/hCCR8) cells, TALL-1 (acute T lymphoblastic leukemia), CCRF-HSB2 (human T-lymphoblastic leukemia), and natural killer cells, which express endogenous hCCR8 by flow cytometry. Furthermore, C₈Mab-21 demonstrated a moderate binding affinity for CHO/hCCR8 and TALL-1 with a dissociation constant of 6.5×10^-8 M and 2.0×10^-8 M, respectively. C₈Mab-21, which was established by the CBIS method, could be a useful tool for analyzing the hCCR8-related biological response using flow cytometry.

Warming of the climate system is unequivocal, and many of the observed changes are unprecedented over five decades to millennia. Globally the atmosphere and ocean is increasingly getting warmer, the amount of ice on the earth is decreasing over the oceans, and the sea level has risen. According to Intergovernmental Panel on Climate Change, the total increasing temperature globally averaged combined land and surface between the average of the 1850-1900 period and the 2003 to 2012 period is 0.78 °C (0.72 to 0.85). But should we prepare for such the relatively small change? The importance is not the mean of the warming but the considerable likelihood of climate change that could trigger extreme natural hazards. The impact and the risk of climate change associated with railway infrastructure have not been fully addressed in the literature due to the difference in local environmental parameters. On the other hand, the current railway network in Malaysia, over the last decade, has been significantly affected by severe weather conditions such as rainfall, lightning, wind and very high temperatures. Our research findings point out the extremes that can lead to asset system failure, degraded operation and ultimately, delays to train services. During the period of flood, the embankment of the track can be swept away and bridge can be demolished, while during drought, the embankment of the track can suffer from soil desiccation and embankment deterioration, high temperature increases the risk of track buckling and high winds can result in vegetation or foreign object incursion on to the infrastructure as well as additional quasi-static burden exerted. This review is of significant importance for planning and design of the newly proposed high speed rail link between Malaysia and Singapore.

The aim of the article is to verify differences in the perception of selected factors of sustainability among small and medium-sized enterprises (SMEs) in Central Europe. The subjects of analysis are factors such as corporate social responsibility (CSR), business risk sources (market, financial, personnel, and operational), reputation and social media, national support, social changes, and crisis events in business. The questionnaire was completed by 1,090 SMEs from the business environments of Visegrad Group countries. Statistical hypotheses were verified using Z-scores for two population properties. The most negatively perceived factors among owners and managers in the SME segment are national support and legislative changes. The most positively perceived factor is reputation and social media. The country of doing business is a significant factor. The perception of crisis events in business is most negative among Czech SMEs. More than 80% of Hungarian SMEs perceive their companies as sustainable. In comparison with Slovak and Polish SMEs, Hungarian perceptions are more positive in the context of sustainability. The country of doing business is the strongest factor in evaluating CSR indicators. The positive perception of CSR in Czech SMEs (43.9%) is lower than in other countries.

Gas and power networks are tightly coupled and interact with each other due to physically interconnected facilities. In an integrated gas and power network, a contingency observed in one system may cause iterative cascading failures, resulting in network wide disruptions. Therefore, understanding the impacts of the interactions in both systems is crucial for governments, system operators, regulators and operational planners, particularly, to ensure security of supply for the overall energy system. Although simulation has been widely used in the assessment of gas systems as well as power systems, there is a significant gap in simulation models that are able to address the coupling of both systems. In this paper, a simulation framework that models and simulates the gas and power network in an integrated manner is proposed. The framework consist of a transient model for the gas system and a steady state model for the power system based on AC-Optimal Power Flow. The gas and power system model are coupled through an interface which uses the coupling equations to establish the data exchange and coordination between the individual models. The bidirectional interlink between both systems considered in this studies are the fuel gas offtake of gas fired power plants for power generation and the power supply to LNG terminals and electric drivers installed in gas compressor stations and underground gas storage facilities. The simulation framework is implemented into an innovative simulation tool named SAInt (Scenario Analysis Interface for Energy Systems) and the capabilities of the tool are demonstrated by performing a contingency analysis for a real world example. Results indicate how a disruption triggered in one system propagates to the other system and affects the operation of critical facilities. In addition, the studies show the importance of using transient gas models for security of supply studies instead of successions of steady state models, where the time evolution of the line pack is not captured correctly.

This study aimed to evaluate the safety and tolerability of STP1, a combination of ibudilast and bumetanide, tailored for the treatment of a specific subgroup of patients with Autism Spectrum Disorder (ASD), namely ASD Phenotype 1 (ASD-Phen1). We conducted a randomized, double-blind, placebo-controlled, parallel-group phase 1b study with two 14-day treatment phases (registered at clinicaltrials.gov as NCT04644003). Nine ASD-Phen1 patients were administered STP1, while three received a placebo. We assessed safety and tolerability, along with electrophysiological markers, such as EEG, Auditory Habituation, and Auditory Chirp Synchronization, to better understand STP1's mechanism of action. Additionally, we used several clinical scales to measure treatment outcomes. The results showed that STP1 was safe and well-tolerated, with electrophysiological markers indicating a significant and dose-related reduction of gamma power in the whole brain and in brain areas associated with executive function and memory. Treatment with STP1 also increased alpha 2 power in frontal and occipital regions and improved habituation and neural synchronization to auditory chirps. Although numerical improvements were observed in several clinical scales, they did not reach statistical significance. Overall, this study suggests that STP1 is safe and well-tolerated in ASD-Phen1 patients and shows indirect target engagement in ASD brain regions of interest.

Still, the most common in vitro model for absorption, distribution, metabolism and excretion (ADME) purposes is the Caco-2 cell line. However, clear differences in gene- and protein expression towards the small intestine and an at best fair prediction accuracy of intestinal drug absorption restrict the usefulness as model for intestinal epithelial cells. To overcome these limitations, we evaluated a panel of low-passaged patient-derived colorectal cancer cell lines of the HROC collection concerning similarities to small intestinal epithelial cells and their potential to predict intestinal drug absorption. After initial screen of a larger panel, ten cell lines with confluent outgrowth and long-lasting barrier forming potential were further characterized in close detail. Tight junctional complexes and microvilli structures were detected in all lines, differentiated epithelial cells were abundant in 7/10. All lines expressed multiple transporter molecules, with expression levels in three lines being close to those of small intestinal epithelial cells. Compared to the Caco-2 model, three HROC lines demonstrated both higher similarity to jejunal epithelial tissue cells and higher regulatory potential of relevant drug transporters. In sum, these lines would be better suited human small intestinal epithelium models for basic and translational research; especially for ADME studies.

The 5-hydroxymethylfurfural (HMF) is a six-carbon heterocyclic organic compound with two substituents an aldehyde group and an alcohol group. It is formed from saccharides as a result of two reactions: the Maillard reaction and the caramelization of saccharides. It has both a negative and a positive effect on the human body, which makes it, even more, an attractive research object. The objective of the study was to determine HMF content in honey samples available on the Polish market using three varied methods and compare the results obtained. The methodology used included: two spectrophotometric methods (by White and Winkler) and the HMF determination method based on the LC-MS/MS technique developed uniquely for this study. The determined HMF content in all tested honey samples did not exceed the applicable standard. All results are within the scope of the European Council Directive 2001/110/EC of 20 December 2001, i.e. they do not exceed HMF content in honey, which is 40 mg/kg.

Tyrosine kinase fibroblast growth factor receptor (FGFR), which is aberrant in various cancer types, is a promising target for cancer therapy. Here we reported the design, synthesis, and biological evaluation of a new series of 6-(2,6-dichloro-3,5-dimethoxyphenyl)-4-substituted-1H-indazoles derivatives as potent FGFR inhibitors. Compound 10a was first identified as a potent FGFR1 inhibitor, with good enzymatic inhibition. Further structure-based optimization revealed that compound 13a is the most potent FGFR1 inhibitor in this series with the enzyme inhibitory activity about 30.2 nM of IC50 value.

Polyelectrolyte-drug complexes are interesting alternatives to improve unfavourable drugs properties. Vancomycin (VAN) is an antimicrobial used in the treatment of methicillin-resistant Staphylococcus aureus pulmonary infections in patients with cystic fibrosis. It is generally administered intravenously with high incidence of adverse side effects, which could be reduced by intrapulmonary administration. Currently, there are no commercially available inhalable formulations containing VAN. Thus, the present work focuses on the preparation and characterization of an ionic complex between hyaluronic acid (HA) and VAN with potential use as inhalable formulations. Particulate-solid HA-VAN25 complex by spray drying from an aqueous dispersion was obtained. FTIR spectroscopy and thermal analysis confirmed the ionic interaction between HA and VAN, while an amorphous diffraction pattern by X-ray was observed. The powder density, geometric size and morphology showed a suitable aerosolization and aerodynamic performance of the powder, indicating the capability of reaching the deep lung. An in vitro extended-release profile of VAN from the complex was obtained, exceeding 24 hours. Microbiological assays against methicillin-resistant and -sensitive reference strains of Staphylococcus aureus, showed that VAN preserves its antibacterial efficacy. In conclusion, HA-VAN25 exhibited interesting properties for the development of inhalable formulations with potential efficacy and safety advantages over conventional treatment.

Firefighters Protective Clothing consist of several layers of different properties and functions. The layers create barriers against dangerous outer factor. However, they are also barriers to transport of sweat produced by human organism. It causes that very often sweat in the form of vapor is not transferred effectively from the human organism through the FPC to environment. This leads to sweat condensation on the skin of the FPC user causing his discomfort. In order to ensure as good as possible physiological comfort of firefighter while firefighting and other rescue actions it is necessary to take into consideration the transport of condensed sweat in the multilayer textile set creating the FPC. In the presented work four variants of multilayer textile sets for the FPC have been tested in the aspect of liquid moisture transport. Measurement was performed by means of the Moisture Management Tester (MMT290) – innovative instrument manufactured by the SDL Atlas. Obtained results showed that the transfer of sweat in liquid form occurs only in the inner, next to skin layer of the multilayer sets for the FPC.

To develop peptide drugs targeting integrin receptors, synthetic peptide ligands endowed with well-defined selective binding motifs are necessary. The snake venom KTS-containing disintegrins, that selectively block collagen α1β1 integrin, were used as lead compounds for the synthesis and structure-activity relationship of a series of linear peptides containing the KTS-pharmacophore and alternating natural amino acids and 3-aminobenzoic acid (MABA). To ensure a better stiffness and metabolic stability, one, two and three MABA residues, were introduced around the KTS pharmacophore motif. Molecular dynamics simulations have determined that the solution conformation of MABA peptide 4 is more compact, underwent larger conformational changes until convergence, and spent most of the time in a single cluster. The peptides’ binding affinity has been characterized by enzyme linked immunosorbent assay in which the most potent peptide 4 inhibited with IC50 of 324±8 µM and 550±45 µM the binding of GST-α1-A domain to collagen IV fragment CB3, and the cell adhesion to collagen IV using α1-overexpressor cells, respectively. Docking studies and MM-GBSA calculations confirmed that peptide 4 binds a smaller region of the integrin near the collagen- binding site and penetrated deeper into the binding site near Trp1. Peptide 4, inhibited tube formation by endothelial cell migration in the Matrigel angiogenesis in vitro assay. Peptide 4 was acutely tolerated by mice, showed stability in human serum, decreased tumor volume and angiogenesis, and significantly increased the survival of mice injected with B16 melanoma cells. These findings propose that MABA-peptide 4 can further serve as an α1β1-integrin antagonist lead compound for further drug-optimization in angiogenesis and cancer therapy.

Nanoparticles have been used as a novel drug delivery system. Drug-incorporated nanoparticles for local delivery might optimize the efficacy and minimize the side effects of drugs. The efficacy and safety of intratracheal administration of prostacyclin analog (beraprost)-incorporated nanoparticles and imatinib, a PDGF-receptor tyrosine kinase inhibitor, -incorporated nanoparticles in Sugen-hypoxia-normoxia or monocrotaline rat models of PAH and in human PAH-pulmonary arterial smooth muscle cells have been reported. The use of inhaled drug-incorporated nanoparticles might be a novel approach for treatment of PAH.

Walking School Buses (WSBs) provide a safe alternative to being driven to school. Children benefit from the contribution the exercise provides towards their daily exercise target, it gives children practical experience with respect to road safety and helps to relieve traffic congestion around the entrance to their school. Walking routes are designed largely based in road safety considerations, catchment need and the availability of parent support. However, little attention is given to the air pollution exposure experienced by children during their journey to school, despite the commuting microenvironment being an important contributor to a child’s daily air pollution exposure. This study aims to quantify the air pollution exposure experienced by children walking to school and those being driven by car. A school was chosen in Bradford, UK. Three adult participants carried out the journey to and from school each carrying a P-Trak ultrafine particle (UFP) count monitor. One participant travelled the journey to school by car while the other two walked, each on opposite sides of the road for the majority of the journey. Data collection was carried out over a period of two weeks, for a total of five journeys to school in the morning and five on the way home at the end of the school day. Results of the study suggest that car commuters experience lower levels of air pollution dose due to lower exposures and reduced commute times. The largest reductions in exposure for pedestrians can be achieved by avoiding close proximity to traffic queuing up to intersections, and, where possible, walking on the side of the road opposite the traffic, especially during the morning commuting period. Major intersections should also be avoided as they were associated with peak exposures. Steps to ensure that the phasing of lights is optimized to minimize pedestrian waiting time would also help reduce exposures. If possible, busy roads should be avoided altogether. By the careful design of WSB routes, taking into account air pollution, children will be able to experience the benefits that walking to school brings while minimizing their air pollution exposure during their commute to and from school.

Cancer, characterized by abnormal cell proliferation driven by genetic mutations, remains a significant health challenge. Tailoring effective therapies depends on factors like tumor location, grade, and stage, alongside patient condition. Leveraging Nano-carrier encapsulated drugs offers a promising avenue, as they accumulate preferentially at tumor sites, enhancing therapeutic efficacy while mitigating side effects. Polymeric Nano-carriers, with their customizable properties, further optimize drug delivery efficiency and specificity. Incorporating active targeting ligands such as antibodies, carbohydrates, peptides, folates, and aptamers-onto polymeric nanoparticle surfaces through techniques like functionalization, adsorption, and conjugation plays a pivotal role in directing therapeutic agents to tumor cells. Consequently, polymeric nanoparticles emerge as the carrier of choice for delivering drugs to various tumor types, including breast, colon, lung, prostate, liver, and spleen tumors.

Knowing professionals’ attitudes is the basis for the development of skills for dealing with drug dependence. These attitudes may affect patients’ clinical safety and the cost-benefit ratio of the interventions. The goal of this study was to assess emergency and mental health nurses’ attitudes and perceptions towards alcoholics. A multicenter prospective descriptive study was conducted in six hospitals with 167 emergency and mental health nurses. Nurses classified alcoholics as sick individuals, although there was a tendency to feel comfortable working with them. Results indicated that these professionals had a rejecting attitude towards moderate alcohol consumption. We found a significant association between the attitude of the nurse and gender, with the degree of rejection towards the alcoholic being higher in men than in women and with less punitive attitudes in professionals from 0 to 11 years of professional experience.

Functional genomics, a multidisciplinary subject, investigates the functions of genes and their products in biological systems to better understand diseases and find new drugs. Drug repurposing is an economically efficient approach that entails discovering novel therapeutic applications for already-available medications. Genomics enables the identification of illness and therapeutic molecular characteristics and interactions, which in turn facilitates the process of drug repurposing. Techniques like gene expression profiling and Mendelian randomization are helpful in identifying possible medication candidates. Progress in computer science allows for the investigation and modelling of gene expression networks that involve large amounts of data. The integration of data from DNA, RNA, and protein activities has resemblance to pharmacogenomics, which is of utmost importance in the development of cancer drugs. Functional genomics in drug discovery, particularly for cancer, is still not thoroughly investigated, despite the existence of a significant amount of literature on the subject. Next-generation sequencing and proteomics present highly intriguing opportunities. Publicly available databases and mining techniques facilitate the development of cancer treatments based on functional genomics. Expanding the study and application of functional genomics has great promise to advance the process of discovering and repurposing drugs, especially in the field of oncology.

Chitosan (CS) nanoparticles are under investigation for a wide range of applications in nanomedicine. The structural, molecular and physicochemical properties of chitosan nanoparticles have a direct bearing on their efficacy in drug conjugation and delivery, gene delivery, and tissue engineering. Herein we report on the structural, morphological and molecular properties of chitosan nanoparticles synthesized using the ionic gelation method with the intended purpose of being used for drug delivery. The chitosan nanoparticles (CS-NPs) were prepared in the 0.25 to 1.0% w/v concentration range, whereas separate samples of the 1.0% w/v CS-NPs were also functionalized with polyethylene oxide (PEO) alone and with a diblock copolymer of PEO and polypropylene glycol (PPG). The average size of the CS-NPs was determined from TEM imaging to be in the range of 11.3 to 14.8 nm. The XRD and TEM analyses show that the CS-NPs have semi-crystalline structure with the degree of crystallinity depending upon the nature of synthesis. Our results show that functionalizing the 1.0% w/v CS-NPs with PEO increases the degree of crystallinity whereas functionalizing with the diblock copolymer PEO - PPG results in a significant increase in their degree crystallinity. The CS/TPP concentration (CS:TPP fixed at 1:1 ratio) had no apparent effect on the degree of crystallinity of the CS-NPs. The results from the FTIR analysis confirm incorporation of TPP with CS in the CS-NPs. Additionally, FTIR analysis shows an enhancement of hydrogen bonding that is consistent with the increase in the degree of crystallinity of the CS-NPs.

Several bio-actors are involved in the occurrence of leishmaniasis, which is made too complex for prevention and control options. Currently, all forms of leishmaniasis are being treated with chemical drugs, which have limitations and adverse effects on patients. Searching the bioactive molecules from plant sources allows the development of a novel drug. The essential oil and solvent extract of the roots of E. kebericho showed antileishmanial activity. But looking for biological activities of the isolated active ingredient from tubers of E. kebericho was scant. Thus, the isolation of the leishmanicidal compound from the roots of E. kebericho through a bioassay-guided technique was an aim of this work. Dehydrocostus lactone showed doubled potent than the standard drug miltefosine on leishmanicidal activities against L. major and L. tropica. Besides, the broad-spectrum biological activities of dehydrocostus lactone could be a potential drug candidate for co-infected patients caused by an association of leishmania and another pathogen.

Molecularly imprinted polymers (MIPs) were synthesized and applied for the selective extraction of oblongifolin C (OC) from fruit extracts of Garcinia yunnanensis Hu. A series of experiments and computational approaches were employed to improve the efficiency of screening for optimal MIP systems in the study. The molar ratio (1:4) was chosen at last based on the comparison of the binding energy of the complexes between the template (OC) and functional monomers using density functional theory (DFT) at the RI-PBE-D3-gCP/def2-TZVP level of theory. The binding characterization and the molecular recognition mechanism of MIPs were further explained using the molecular modeling method and NMR and IR spectra data. The reusability of this approach was demonstrated in over 20 batch rebinding experiments. 140.5 mg of OC (>95% purity) was obtained from the 5 g extracts with 2 g of MIPs with the best binding properties through gradient elution program from 35% to 70% methanol-water solution. At the same time, another structural analog, 46.5 mg of guttiferone K (GK) (>88% purity), was also obtained by the gradient elution procedure. Our results showed that the structural analogs could be separated from the crude extracts by the molecularly imprinted solid-phase extraction (MISPE) using a gradient elution procedure for the first time.

Batch and transport experiments were used to investigate the remediation of a loamy sand soil contaminated with Cr(VI) using zero valent iron nanoparticles (nZVI) stabilized by the carboxy methyl cellulose (CMC-nZVI). The effect of pH, ionic strength (IS), and flow rate on the removal efficiency of Cr(VI) were investigated under equilibrium (uniform transport) and non-equilibrium (Two-site sorption) transport using the Hydrus-1D model. The overall removal efficiency ranged from 70 to over 90% based on the chemical characteristics of the CMC-nZVI suspension and the transport conditions. The concentration and pH of the CMC-nZVI suspension had the most significant effect on the removal efficiency and transport of Cr(VI) in the soil. The average removal efficiency of Cr(VI) was increased from 24.1 to 75.5% when the concentration of CMC-nZVI nanoparticles was increased from 10 to 250 mg L-1, mainly because of the increased total surface area at larger particle concentration. Batch experiments showed that removal efficiency of Cr(VI) was much larger under acidic conditions. The average removal efficiency of Cr(VI) reached 90.1 and 60.5 % at pH 5 and 7, respectively. The Two-site sorption model described quite well (r2 = 0.96-0.98) the transport of Cr(VI) in soil as compared to the uniform transport model (r2 = 0.81-0.98). The average retardation of Cr(VI) was 3.51 and 1.61 at pH 5 and 7, respectively, indicating earlier arrival for the breakthrough curves and shorter time to reach maximum relative concentration at lower pH. The Hydrus-1D model has proven to be an efficient tool for assessing the removal of Cr(VI) pollutants, offering innovative, cost-effective, and environmentally friendly remediation methodologies.

The regulation of cell death is a fundamental issue in cell biology and continues to be intensely investigated worldwide. The significance of research in this field persists because understanding the determinants of cell lifespan directly impacts the maintenance of multicellular organism homeostasis and, consequently, is crucial for addressing biomedical challenges associated with various diseases. It is recognized that the initiation of cell death can be prompted by both specific signals (such as cytokines or hormones) and nonspecific stimuli, including radiation, temperature increase, or oxidants. When these factors affect a cell, numerous signaling pathways are triggered in the cell, leading to neutralization of the effects of their negative effects or, in case of irreparable damage, to cell elimination. This removal of damaged cells occurs through apoptosis or programmed cell death, a highly regulated process. Numerous signaling molecules participate in orchestrating the apoptotic process, many of which also govern other essential functions within the organism. Physiological factors capable of triggering the apoptotic program in cells include nitric oxide (NO), which serves as one of the key signaling molecules regulating the functions of the cardiovascular, nervous, and immune systems of the organism. The unique chemical nature of NO, along with its numerous intracellular targets and physiologically active redox forms, raises questions about the specific mechanisms through which NO exerts its damaging effects on cells. Utilizing pharmacological preparations- such as sources (donors) of exogenous nitric oxide- represents an approach to investigating the initiation and execution of the apoptotic program in sensitive target cells. Furthermore, this approach holds promise as a direction for discovering new selective drugs.

Structural health monitoring has been studied by a number of researchers as well as various industries to keep up with the increasing demand for preventive maintenance routines. This work presents a novel method for reconstruct prompt, informed strain/stress responses at the hot spots of the structures based on strain measurements at remote locations. The structural responses measured from usage monitoring system at available locations are decomposed into modal responses using empirical mode decomposition. Transformation equations based on finite element modeling are derived to extrapolate the modal responses from the measured locations to critical locations where direct sensor measurements are not available. Then, two numerical examples (a two-span beam and a 19956-degree of freedom simplified airfoil) are used to demonstrate the overall reconstruction method. Finally, the present work investigates the effectiveness and accuracy of the method through a set of experiments conducted on an aluminium alloy cantilever beam commonly used in air vehicle and spacecraft. The experiments collect the vibration strain signals of the beam via optical fiber sensors. Reconstruction results are compared with theoretical solutions and a detailed error analysis is also provided.

Lead optimization in drug discovery is a crucial phase where initial hits are refined into compounds with improved pharmacological properties. While traditional methods rely on manual experimentation and modifications, AI-driven techniques have revolutionized this process by leveraging big data and predictive modeling. This review explores how AI-driven approaches accelerate lead optimization, showcasing examples like deep neural networks and reinforcement learning. Integration of multi-omic data and experimental validation further enhances AI-driven strategies. The future lies in refining these AI methods, democratizing tools, and interdisciplinary collaboration to streamline drug discovery and address medical needs efficiently.

Public restrooms are often a hub of microbial contamination, and the examination of bacterial contamination in these facilities can serve as an important indicator of the transmission of infectious diseases. This study was conducted to determine the prevalence of bacterial contamination in public restrooms based on the economic class of the building. Samples were collected from various spots in 32 restrooms found in 10 shopping malls, classifying them into two categories: upper-end restrooms and lower-end restrooms. The findings showed that the level of contamination was higher in the lower-end restrooms, with the seat being the most contaminated area. The most dominant Gram-positive bacteria were coagulase-negative staphylococci species, making up 86% of the identified Gram-positive isolates. The most dominant Gram-negative bacteria identified were Klebsiella pneumoniae and Pseudomonas aeruginosa. The antibiotic sensitivity test results revealed the presence of multi-drug resistant bacteria among the Gram-positive and negative isolates, including Staphylococcus haemolyticus, Staphylococcus kloosi, Acinetobacter baumanii, and Pseudomonas aeruginosa. In conclusion, the study underscores the significance of monitoring bacterial contamination in public restrooms and the need for measures to reduce the spread of infectious diseases. Further research is crucial to gain a complete understanding of the bacterial contamination in public restrooms and their resistance patterns, to ensure the safety and health of the public. The implementation of improved cleaning practices and hands-free designs in restrooms can help reduce the risk of cross-contamination and prevent the spread of diseases.

Transportation systems through the ages have seen drastic evolutions in terms of transportation methods, speed of transport, infrastructure, technology, connectivity, influence on the environment, and accessibility. The massive transformation seen in the transportation sector has been fueled by the industrial revolutions which have continued expansion and progress into the fourth industrial revolution. However, the methodologies of data collection and processing used by the many drivers of this progress differ. The significance of standardized data and its mode of collection cannot be overstated as it has a major impact on the process outcomes. In order to achieve a better understanding of the impact of this, this study methodically reviewed the literature on the subject of the data collection and processing mechanism of 4IR technologies in the context of the transport industry with an emphasis on the areas of accomplishment of several studies and drawing attention to their limitations. Although the industry has advanced significantly as a result of the adoption and application of various research studies in this field, considerable focus needs to be placed in the areas of standardized data collection and computational approaches, which will ultimately assist in achieving various benefits in the transportation industry.

In this paper we derive a unified perspective for Optimal Transport (OT) theory and Mean Field Control (MFC) theory to analyse the learning process for Neural Networks algorithms in a high-dimensional framework. We consider Mean Field Neural Networks in the context of MFC theory, specifically the mean field formulation of OT theory that allows the development of highly efficient algorithms while providing a powerful tool in the context of explainable Artificial Intelligence.

In the dynamic landscape of drug discovery, Computer-rAided Drug Design (CADD) emerges as a transformative force, bridging the realms of biology and technology. This paper overviews CADD's historical evolution, categorization into structure-based and ligand-based approaches, and its crucial role in rationalizing and expediting drug discovery. As CADD advances, incorporating diverse biological data and ensuring data privacy become paramount. Challenges persist, demanding the optimization of algorithms and robust ethical frameworks. Integrating Machine Learning and Artificial Intelligence amplifies CADD's predictive capabilities, yet ethical considerations and scalability challenges linger. Collaborative efforts and global initiatives, exemplified by platforms like Open Source Malaria, underscore the democratization of drug discovery. The convergence of CADD with personalized medicine offers tailored therapeutic solutions, though ethical dilemmas and accessibility concerns must be navigated. Emerging technologies like quantum computing, immersive technologies, and green chemistry promise to redefine the future of CADD. The trajectory of CADD, marked by rapid advancements, anticipates challenges in ensuring accuracy, addressing biases in AI, and incorporating sustainability metrics. The paper concludes by highlighting the need for proactive measures in navigating the ethical, technological, and educational frontiers of CADD to shape a healthier, brighter future in drug discovery.

Infection with human immunodeficiency virus (HIV) and induced acquired immune deficiency syndrome (AIDS) represent one of the greatest health burdens worldwide. The complex pathophysiological pathways that link highly active antiretroviral therapy (HAART) and HIV infection per se with dyslipidemia make the management of lipid disorders and the subsequent increase in cardiovascular risk essential for the treatment of people living with HIV (PLHIV). Amongst the HAART regimens, darunavir and atazanavir in terms of protease inhibitors, tenofovir disoproxil fumarate, nevirapine or rilpivirine in terms of nucleoside reverse transcriptase inhibitors and non-nucleoside reverse transcriptase inhibitors respectively, and especially integrase inhibitors, have demonstrated the most favorable lipid profile emerging as sustainable options in HAART substitution. To this day, statins remain the cornerstone pharmacotherapy for dyslipidemia in PLHIV, although important drug-drug interactions with different HAART agents should be taken into account upon treatment initiation. For those intolerant or not meeting therapeutic goals, the addition of ezetimibe, PCSK9, bempedoic acid, fibrates or fish oils should also be considered. This review summarizes the current literature on the multifactorial etiology and intricate pathophysiology of hyperlipidemia in PLHIV, with an emphasis on the role of different HAART agents, while also providing valuable insights into potential switching strategies and therapeutic options.

Despite available global efforts and funding, Tuberculosis (TB) continues to affect a considerable number of patients worldwide. Policy makers and stakeholders set clear goals to reduce TB incidence and mortality, but the emergence of multidrug-resistant TB (MDR-TB) and extensively drug-resistant TB (XDR-TB) complicate the reach of these goals. Drug-resistance TB needs to be diagnosed rapidly and accurately to effectively treat patients, prevent the transmission of MDR-TB, minimise mortality, reduce treatment costs and avoid unnecessary hospitalisations. In this narrative review, we provide a comprehensive overview of laboratory methods for detecting drug resistance in MTB, focusing on phenotypic, molecular and other drug susceptibility testing (DST) techniques. We found a large variety of methods used, with the BACTEC MGIT 960 being the most common phenotypic DST and the Xpert MTB/RIF being the most common molecular DST. We emphasise the importance of integrating phenotypic and molecular DST to address issues like resistance to new drugs, heteroresistance, mixed infections and low-level resistance mutations. Notably, most of the analysed studies adhered to the outdated definition of XDR-TB and did not consider the pre-XDR definition, thus posing challenges in aligning diagnostic methods with the current landscape of TB resistance.

Efficient fixed crane position analysis is critical in precast buildings construction to maximize lifting efficiency for precast elements. The primary objective is to minimize the travel distances of fixed cranes, thereby enhancing operational efficiency and cost control. This involves strategically reducing the distances between the transport truck parking, where elements are stored, the fixed crane, and the construction installation point. Despite its significance, existing studies often overlook the dynamic movement efficiency of transport trucks, particularly when dealing with multiple transport trucks and various models of fixed cranes, rendering the opti-mization of this scenario a challenging NP-hard problem susceptible to combinatorial explosion. This study presents a novel mathematical model leveraging the Genetic Algorithm (GA). The model aims to solve optimal model and position of fixed cranes, along with identifying ideal positions for transport truck parking. The study's methodology is validated and demonstrated through a project case study. Comparative analyses between the proposed model and the original planning underscore a noteworthy 6% reduction in both duration and costs when lifting elements directly from transport trucks, as opposed to establishing an on-site stock yard. Furthermore, the developed GA exhibits a substantial improvement in final solutions, achieving a remarkable 30% reduction in both operational duration and costs. This research contributes valuable insights into fixed crane position analysis of precast building construction, providing foundation for enhanced operational efficiency and cost-effectiveness in the industry.

High-throughput screening technologies continues to produce large amounts of multiomics data from different populations and cell types for various diseases, such as cancer. However, analysis of such data encounters difficulties due to cancer heterogeneity, further exacerbated by human biological complexity and genomic variability. There is a need to redefine the drug discovery development pipeline, bringing an Artificial Intelligence (AI)-powered informational view that integrates relevant biological information and explores new ways to develop effective anticancer approaches. Here, we show SynPred, an interdisciplinary approach that leverages specifically designed ensembles of AI-algorithms, links omics and biophysical traits to predict synergistic anticancer drug synergy. SynPred exhibits state-of-the-art performance metrics: accuracy – 0.85, precision – 0.77, recall – 0.75, AUROC – 0.82, and F1-score - 0.76 in an independent test set. Moreover, data interpretability was achieved by deploying the most current and robust feature importance approaches. A simple web-based application available online at http://www.moreiralab.com/resources/synpred/ was constructed to predict synergistic anticancer drug combinations requiring only the upload of the two drug SMILES to be tested, allowing easy access by non-expert researchers.

This study explores the complexities involved in the extraction and purification of catechins, prominent bioactive compounds found in plant extracts and tea. It addresses challenges arising from the intricate molecular structure of catechins and their inherent variability across botanical sources. Despite these obstacles, catechins present significant potential, particularly in healthcare. Their potent antioxidant properties have been extensively investigated and associated with numerous health benefits, positioning them as promising therapeutic agents for combating chronic diseases. Furthermore, catechins have diverse applications across various industries, including food and beverage, cosmetics, agriculture, and materials science. This abstract emphasizes the importance of continued research and innovation in catechin extraction and utilization, which hold promise for advancing human health and technological progress across multiple domains.

This article delves into the intersection of generative AI and digital twins within drug discovery, exploring their synergistic potential to revolutionize pharmaceutical research and development. Through various instances and examples, we illuminate how generative AI algorithms, capable of simulating vast chemical spaces and predicting molecular properties, are increasingly integrated with digital twins of biological systems to expedite drug discovery. By harnessing the power of computational models and machine learning, researchers can design novel compounds tailored to specific targets, optimize drug candidates, and simulate their behavior within virtual biological environments. This paradigm shift offers unprecedented opportunities for accelerating drug development, reducing costs, and, ultimately, improving patient outcomes. As we navigate this rapidly evolving landscape, collaboration between interdisciplinary teams and continued innovation will be paramount in realizing the promise of generative AI and digital twins in advancing drug discovery.

In the dynamic interplay between people and their physical environments, the Global South stands as a mosaic undergoing a multitude of transformative influences in architecture and urbanism where examining social sustainability becomes imperative. While prevailing attention remains on environmental and economic sustainability, this study addresses a persistent gap in the urban literature by focusing on the dynamic and manifold nature of social sustainability. Positioning itself within the context of sustainable development, the study links the pursuit of social aspects of sustainability with selected unique urban contexts from the Global South. Five cases that include Alexandria (Egypt), Tripoli (Libya), Basra (Iraq), Lilongwe (Malawi), and Accra (Ghana) are discussed through multi-layered investigations that involve attitude surveys, interviews, focus groups, participatory systematic observations, and behavioral mapping, engaging directly with inhabitants and stakeholders. Uncovering people-place narratives in the identified contexts, the cases are developed into five knowledge typologies that serve as practical tools for planning and design decision-making, policy formulation, and academic discourse. Discussions are conceived to demonstrate the transformative role people-place narratives play in fostering a more sustainable and equitable urban future. Conclusions are drawn to offer practical insights for stakeholders involved in various capacities in shaping the urban landscape of the Global South.

Management of chronic inflammation and wounds has always been a key issue in the pharmaceutical and healthcare sector. Curcumin (CCM) is an active ingredient extracted from turmeric rhizomes that has antioxidant, anti-inflammatory, and antibacterial activities, thus showing significant effectiveness toward wound healing. However, its shortcomings such as poor water solubility, poor chemical stability and fast metabolic rate limit its bioavailability and long-term use. In this context, hydrogels appear to be a versatile matrix for carrying and stabilizing drugs due to the biomimetic structure, soft porous microarchitecture, and pleasant biomechanical properties. The drug loading/releasing efficiencies can also be controlled by use of highly crystalline and porous metal organic frameworks (MOFs). Here, a flexible hydrogel composed of sodium alginate (SA) matrix and CCM-loaded MOFs was constructed for long-term drug release and antibacterial activity. The morphology and physicochemical properties of composite hydrogels were analyzed by scanning electron microscopy (SEM), Fourier transform infrared spectroscopy (FT-IR), X-ray diffraction (XRD), ultraviolet visible spectroscopy (UV-Vis), Raman spectroscopy and mechanical property tests. The results showed that the composite hydrogel was highly twistable and bendable to mechanically comply with human skin. The as-prepared hydrogel could capture efficient CCM for slow drug release as well as effective killing of bacteria. Therefore, such composite hydrogel is expected to provide a new management system for chronic wound dressings.

The eutrophication of open water bodies, especially in coastal water area, has received intensive public focuses in recent years. Biological treatment of organic pollutants in industrial and domestic wastewater requires microbial flora to participate. The environmental impact of these microbes, particularly in regard to the spread of antibiotic resistance genes and pathogenicity in coastal water, remains largely unknown. We initiate studies to examine antibiotic resistance genes (ARGs) in microbial flora and study the mode of antibiotic spread in the coastal waters of Bohai Bay, North China by using high performance liquid chromatography-mass spectrum analysis and quantitative polymerase chain reaction. The metabolic features of bacteria related to the presence of ARGs in the coastal area showed the enrichment of Pseudomonadale species with triple resistance properties (ampicillin, kanamycin and gentamycin) at the estuary site locating adjacent to a coastal sewage treatment plant where both type I and type II polyketide synthase genes and b-lactam type antibiotics are detected. Pseudomonadale order is phylogenetically belonged to Proteobacteria Phylum, Gamma-proteobacteria Class and contains Pseudomonadaceae family and Pseudomonas genus. QPCR analysis suggests that the percent occupation of Pseudomonadale species to total Proteobacteria in the examined stations is close to several sampling stations close to sewage treatment plants, where consistent release of organic wastes occurred.

Does cell clustering influence intrinsic and acquired multi-drug resistance (MDR) differently? To address this question, we studied cultured monolayers (representing individual cells) and cultured spheroids (representing clusters) formed by drug-naïve (intrinsic MDR) and drug-exposed (acquired MDR) lines of ovarian cancer A2780 cells by cytometry of reaction rate constant (CRRC). MDR efflux was characterized by accurate and robust “cell number vs. MDR efflux rate constant (kMDR)” histograms. Both drug-naïve and drug-exposed monolayer cells presented unimodal histograms; the histogram of drug-exposed cells was shifted towards higher kMDR value suggesting greater MDR activity. Spheroids of drug-naïve cells presented a bimodal histogram indicating the presence of two subpopulations with different MDR activity. In contrast, spheroids of drug-exposed cells presented a unimodal histogram qualitatively similar to that of the monolayers of drug-exposed cells but with a moderate shift towards greater MDR activity. The observed greater effect of cell clustering on intrinsic than on acquired MDR can help guide the development of new therapeutic strategies targeting clusters of circulating tumor cells.

Background and Objectives: Knee osteoarthritis (KOA) is a degenerative disease that is targeting continuously people of different ages, but especially the elderly population, the number of which tends to increase continuously at the global level. Apart from age, excess weight can influence the evolution of the disease, with obesity being associated with a weak inflammation stage, and an imbalance between pro-inflammatory and anti-inflammatory cytokines. The present work aimed to identify specific biomarkers alike ACRP-30, IL-10, TNF-α, and IL-6 in synovial fluid and correlate them with patients’ clinical data. Materials and Methods: 24 subjects with KOA and over 50 years of age are involved in the present study. All patients performed a supine X-ray at the target knee. Ultrasound was performed using an ESAOTE MyLab Omega (ESAOTE Spa, Italy) ultrasound device and a 6-19 MHz linear array transducer. Results: The obtained results highlighted a significant correlation between age and adiponectin level (p=0.0451, r=-0.412). Also, the IL-10 values are lower in cases where the intensity of the pain is more pronounced (p=0.0405, r=-0.421). In addition, analyzing the data by gender, it was observed that in the case of males, stiffness is more related to age (p=0.0079, r=0.7993), compared to women (p=0.0203, r=0.6223). In the case of women, the progression of the disease tends to increase more intensively total WOMAC score’s values (p=0.00031, r=0.8342), compared with men (p=0.0289, r=7013). Regarding interleukins and BMI, significant correlations were observed only in the case of men. Conclusions: A significant correlation between age and adiponectin, and adiponectin and IL-6, suggests that advanced age may contribute to adiponectin reduction. Comparing men with women, it was observed that men's age is more related to rigidity, and IL-6 and IL-10 are directly correlated to BMI and women seem to be more sensitive to pain and stiffness.

The purpose of the present study was to investigate anti-staphylococcal activity of liposomal daptomycin, against four biofilm-producing S. aureus and S. epidermidis clinical strains, three of which are methicillin resistant. Neutral and negatively charged Daptomycin-loaded liposomes were prepared by three methods thin film hydration (TFH), DRV and microfluidic mixing (MM), and characterized for drug encapsulation (EE%), size distribution, zeta-potential, vesicle stability, drug release and drug integrity. Interestingly, whilst drug loading in THF and DRV nanosized (by extrusion) vesicles was around 30-35, very low loading (~4%) was possible in MM vesicles, requiring further explanatory investigations. Liposomal encapsulation protected daptomycin from degradation and preserve its bioactivity. Quantitative microtiter plate (crystal violet, CV), methylthiazoltetrazolium (MTT), and growth curve (GC) assays evaluated antimicrobial activity of neutral and negative charge daptomycin-liposomes towards planktonic bacteria and biofilms. Neutral liposomes exhibited dramatically enhanced inhibition of bacteria growth (compared to free drug) for all species studied, while negative charged liposomes were totally inactive. Biofilm prevention and treatment studies revealed high antibiofilm activity of liposomal daptomycin. Neutral liposomes were more active for prevention and negative charge ones for treating established biofilms. Planktonic bacteria as well as matured biofilms of low daptomycin susceptible MRSE and MRSA strains were almost completely eradicated by liposomal-daptomycin indicating the need for their further exploration as antimicrobial therapeutics.

Artificial intelligence AI or machine learning has proven to be a potential activity in the health and biomedical sciences. Previous research it has found that AI can learn new data and transform it into the useful knowledge. In the field of pharmacology, the aim is to design more efficient and novel vaccines using this method which are also cost effective. The underlying fact is to predict the molecular mechanism and structure for increased likelihood of developing new drugs. Clinical, electronic and high resolution imaging datasets can be used as inputs to aid the drug development niche. Moreover, the use of comprehensive target activity has been performed for repurposing a drug molecule by extending target profiles of drugs which also include off targets with therapeutic potential providing a new indication.

Tuberculosis (TB) remains a global health threat, necessitating innovative strategies for control and prevention. This comprehensive review explores the Mycobacterium tuberculosis Lysine Exporter (LysE) gene, unveiling its multifaceted roles and potential uses in controlling and preventing tuberculosis (TB). As a pivotal player in eliminating excess L-lysine and L-arginine, LysE contributes to the survival and virulence of M. tuberculosis. This review synthesizes findings from different electronic databases and includes 13 studies focused on the LysE of M. tuberculosis. The research unveils that LysE can be a potential drug target, a diagnostic marker for TB, and a promising candidate for vaccine development. The absence of LysE in the widely used BCG vaccine underscores its uniqueness and positions it as a novel area for TB prevention. In conclusion, this review underscores the significance of LysE in TB pathogenesis and its potential as a drug target, diagnostic marker, and vaccine candidate. The multifaceted nature of LysE positions it at the forefront of innovative approaches to combat TB, calling for sustained research efforts to harness its full potential in the global fight against this infectious disease.

Alzheimer's disease (AD) remains a significant challenge in the field of neurodegenerative disor-ders, even nearly a century after its discovery, due to the elusive nature of its causes. The develop-ment of drugs that target multiple aspects of the disease has emerged as a promising strategy to address the complexities of AD and related conditions. The immune system's role, particularly in AD, has gained considerable interest, with nanobodies representing a new frontier in biomedical research. Advances in targeting antibodies against amyloid-β (Aβ) and using messenger RNA for genetic translation have revolutionized the production of antibodies and drug development, open-ing new possibilities for treatment. Despite these advancements, conventional treatments for AD, such as Cognex, Exelon, Razadyne, and Aricept, often have limited long-term effectiveness, under-scoring the need for innovative solutions. This necessity has led to the incorporating of advanced technologies like artificial intelligence and machine learning into the drug discovery process for neurodegenerative diseases. These technologies help identify therapeutic targets and optimize lead compounds, offering a more effective approach to addressing the challenges of AD and similar conditions.

We report the electrical characterization and the field emission properties of CVD-grown MoS₂ bilayers deposited on SiO₂/Si substrate. Current-voltage characteristics are measured in the back-gate transistor configuration, with Ti contacts patterned by electron beam lithography. We confirm the n-type character of as-grown MoS₂ and we report normally-on field effect transistors. Local characterization of field emission is performed inside a scanning electron microscope chamber with piezo-controlled tungsten tips working as the anode and the cathode. We demonstrate that an electric field of ~200 V/μm is able to extract current from the flat part of MoS₂ bilayers, which therefore can be conveniently exploited for field emission applications even in low field-enhancement configurations. We show that a Fowler-Nordheim model, modified to account for electron confinement in 2D materials, fully describes the emission process.

Inhibitors of the factor FXI represent a new class of anticoagulant agents that are facing the clinical approval for the treatment of acute coronary syndrome (ACS), venous thromboembolism (VTE), and stroke prevention of atrial fibrillation (AF). These new inhibitors include chemical small molecules (asundexian and milvexian), monoclonal antibodies (abelacimab, osocimab, and xisomab), and antisense oligonucleotides (IONIS-FXIRX and fesomersen), and thus with very peculiar and different pharmacokinetic and pharmacodynamic properties. Besides their clinical efficacy and safety, based on their pharmacological heterogeneity, the use of these drugs in patients with comorbidities may undergo to drug-drug interactions (DDI) with other concomitant therapies. Although only few clinical evidence are available, it is possible to predict clinical relevant DDI by taking into consideration their pharmacokinetic properties, such as the CYP450-dependent metabolism, the interaction with drug transporters and/or the route of elimination. These characteristics may be useful to differentiate their use with the direct oral anticoagulant (DOAC) anti -FXa (rivaroxaban, apixaban, edoxaban) and thrombin (dabigatran), whose pharmacokinetics are strongly dependent from P-gp inhibitors/inducers. In the present review, we summarize the current clinical evidence on DDI of new anti FXI with CYP450/P-gp inhibitors and inducers and indicate potential differences with DOAC anti FXa.

Transketolase (TKT) is an essential thiamine diphosphate (ThDP)-dependent enzyme of the non-oxidative branch of pentose phosphate pathway, with the glucose-6P flux through the pathway regulated in various medically important conditions. Here, we characterize the brain TKT regulation by acylation in rats with perturbed thiamine-dependent metabolism, known to occur in neurodegenerative diseases. The perturbations are modelled by administration of oxythiamine inhibiting ThDP-dependent enzymes in vivo, or by reduced thiamine availability in the presence of metformin and amprolium, inhibiting intracellular thiamine transporters. Compared to control rats, chronic administration of oxythiamine does not significantly change the modification level of the two detected TKT acetylation sites (K6 and K102), but doubles malonylation of TKT K499, concomitantly decreasing 1.7-fold the level of demalonylase sirtuin 5. The inhibitors of thiamine transporters do not change average levels of TKT acylation or sirtuin 5. TKT structures indicate that the acylated residues are distant from the active sites. The acylations-perturbed electrostatic interactions may be involved in conformational shifts and/or formation of TKT complexes with other proteins or nucleic acids. Acetylation of K102 may affect the active site entrance/exit and subunit interactions. Correlation analysis reveals that the action of oxythiamine is characterized by significant negative correlations of K499 malonylation or K6 acetylation with TKT activity, not observed upon the action of the inhibitors of thiamine transport. However, the transport inhibitors induce significant negative correlations between the TKT activity and K102 acetylation or TKT expression, absent in the oxythiamine group. Thus, perturbations in the ThDP-dependent catalysis or thiamine transport manifest in the insult-specific patterns of the brain TKT malonylation and acetylations.

Today, transit control systems go beyond simple controllers located at the intersections of our streets, involving large companies in the field, which with the implementation and use of sophisticated equipment encompass endless new and advanced technologies that manage to give control to the massive automotive park, thus ensuring fluidity and road safety. Many of these systems are used in the big world capitals, which is why the model used in Santiago, Chile is a system applied and brought directly by the SIEMENS Company of England (specifically the system used in the City of London). It is capable of transmitting the different control signals in a similar and digital way from the different interconnected devices in and out of the road infrastructure.

Polysaccharides such as alginate and gellan gum are biocompatible and easily accessible biopolymers with excellent properties to produce microparticles as drug delivery systems. However, the production methods often fail in reproducibility, compromising the translational potential of such systems. In this work, microparticles made from gellan gum and alginate were optimized using the coaxial air flow method, and an inexpensive and reproducible production method. A Design of Experiments was used to identify the main parameters that affect the microparticle’s production and optimization, focusing on the diameter and dispersibility. Airflow was the most significant factor for both parameters. Pump flow affected the diameter, whilst the gellan gum/alginate ratio affected dispersibility. After optimization, microparticle swelling, drug entrapment and release profile were analyzed at two pH, 7.4 and 6.5. Using methylene blue as a model drug, higher encapsulation and swelling indexes were obtained at pH 7.4, whilst a more pronounced release occurred at pH 6.5. The microparticle release profiles were studied by resorting to well-known models, showing a Fickian type release. The developed microparticles show promising results as drug-delivery vehicles for biomedical applications.

Leishmaniasis is a tropical disease caused by a protozoan parasite Leishmania that is transmitted via infected female sandflies. At present, leishmaniasis treatment mainly counts on chemotherapy. The currently available drugs against leishmaniasis are costly, toxic, with multiple side effects, and limitations in the administration route. The rapid emergence of drug resistance has severely reduced the potency of anti-leishmanial drugs. As a result, there is a pressing need for the development of novel anti-leishmanial drugs with high potency, low cost, acceptable toxicity, and good pharmacokinetics features. Due to the availability of preclinical data, drug repurposing is a valuable approach for speeding up the development of effective antileishmanial through pointing to new drug targets in less time having low costs and risk. Metabolic pathways of this parasite play a crucial role in the growth and proliferation of Leishmania species during the various stages of their life cycle. Based on available genomics/proteomics information, known pathways-based (sterol biosynthetic pathway, purine salvage pathway, glycolysis, GPI biosynthesis, hypusine, polyamine biosynthesis) Leishmania-specific proteins could be targeted with known drugs that were used in other diseases, resulting in finding new promising anti-leishmanial therapeutics. The present review discusses various metabolic pathways of the Leishmania parasite and some drug candidates targeting these pathways effectively that could be potent drugs against leishmaniasis in the future.

Novel Coronavirus (2019-nCOV) causes inflammatory response with worsening symptoms. Classification of potential anti-viral and anti-inflammatory drugs in managing the symptoms of the COVID-19 and reducing morbidity is important. The objective of this study is to identify a group of drugs, best suited for COVID-19 treatment based on recent developments in clinical trials, FDA drug evaluation, directions and developments and from drug therapies globally. Online literature search was done on Medline, PubMed and google scholar databases for studies on various treatments and drug therapies for COVID-19 and relevant studies were identified and the identified drugs are described in detail as per their Pharmacological, pharmaceutical properties of the drugs, mechanism of action, current COVID-19 drug therapy, contraindications and drug-drug interactions Certain drugs can inhibit action against viral infection and protect lungs from severe inflammatory response. This article summarizes several drugs like Hydroxychloroquine, Chloroquine, Remdesivir, Favipiravir, Lopinavir, Ritonavir, Dexamethasone, Ivermectin, Baricitinib, Casirivimab / imdevimab, Bamlanivimab along with auxiliary treatment like convalescent plasma transfusion. Remdesivir is first drug approved by FDA. Hydroxychloroquine, dexamethasone and remdesivir are showing results against COVID-19 but it is important to test the efficacy and safety of such drugs though some drugs have shown remarkable results.

Background: Circulating rare cells participate in breast cancer evolution as systemic components of the disease and thus, are a source of theranostic information. Exploration of cancer-associated rare cells is in its infancy. We determined the validity of a rare-cell detection platform and demonstrated the usefulness of a certain rare cell subset as a novel approach to characterize the breast cancer system. Methods: Linearity of the Rarmax® platform was established using a spike-in approach. The platform includes red blood cell lysis, leukocyte depletion and high-resolution fluorescence image recording. Rare cell analysis was conducted on 28 samples (before and after surgery) from 14 patients with breast cancer, 20 healthy volunteers and 9 non-cancer control volunteers. In-depth identification of rare cells, including circulating tumor cells, endothelial-like cells, erythroblasts and inflammation-associated cells, was performed using a phenotype and morphology-based classification system. Results: The platform performed linearly over a range of 5-950 spiked cells, with an average recovery of 84.6%. Circulating epithelial and endothelial-like cell subsets have been demonstrated to be associated with or independent of cancer with tumor presence. Furthermore, certain cell patterns may be associated with treatment-related adverse effects. The sensitivity in detecting tumor-presence and cancer-associated abnormality before surgery was 50% and 85.7%, respectively and the specificity was 100% and 96.6%, respectively. Conclusion: The present study supports the idea of a cancer-associated rare cell abnormality to represent tumor entities as well as systemic cancer. The latter is independent of the apparent clinical cancer.

This publication aims to create 4K UHD video sequences with a specific focus on smart cities and transport. The created database will be accessible to all experts in the field and can be further used for research purposes. All reference video sequences will be transcoded into different quality settings. The resolution, compression standard, and bitrate will be changed. The work will aim to find out the best combination of video parameters from the measured values. Thanks to the overall evaluation, we will ensure for each single video sequence the quality with the best experience for the providers that will offer the service. The database will also be available with its objective and subjective ratings, with dynamicity information characterized by spatial and temporal information. After, It will be possible to compare the results of the subjective evaluation of a selected sample of our respondents with the work of other researchers who can evaluate with a different sample of evaluators.

We study the deterministic dynamics of N point particles moving at constant speed in a 2D table made of two polygonal urns connected by an active rectangular channel, which applies a feedback-control on the particles, inverting the horizontal component of their velocities, when their number in the channel exceeds a fixed threshold. Such a bounce--back mechanism is non-dissipative: it preserves volumes in phase space. An additional passive channel closes the billiard table forming a circuit in which a stationary current may flow. Under specific constraints on the geometry and on the initial conditions, the large N limit allows nonequilibrium phase transitions between homogeneous and inhomogeneous phases. The role of ergodicity in making a probabilistic theory applicable is discussed both for rational and irrational urns. The theoretical predictions are compared with the numerical simulation results. Connections with the dynamics of feedback-controlled biological systems are highlighted.

Following a recent proof of Shannon's entropy power inequality (EPI), a comprehensive framework for deriving various EPIs for the Rényi entropy is presented that uses transport arguments from normal densities and a change of variable by rotation. Simple arguments are given to recover the previously known Rényi EPIs and derive new ones, by unifying a multiplicative form with constant c and a modification with exponent α of previous works. In particular, for log-concave densities, we obtain a simple transportation proof of a sharp varentropy bound.

In the smart city, information and communications technologies (ICTs) are proposed as solutions to urban challenges, including sustainability concerns. While sustainability commonly refers to economic and environmental dimensions, the concept also contains a social component. Our study asked how smartphone applications (apps) address social sustainability challenges in urban transport, if at all. We focused on transport disadvantages experienced due to low income, physical disability, and language barriers. A review of 60 apps showed that transport apps respond to these equity and inclusion issues in two ways: (a) by employing universal design in general-use apps; including cost-conscious features; and providing language options (b) by specifically developing smartphone apps for persons with disabilities. The article discusses the study by positioning it in the literature of smart cities as well as socially sustainable transport.

Overactive bladder (OAB) is characterized by urinary urgency and increased urinary frequency, and can impact quality of life significantly. Tamsulosin and mirabegron combination therapy has been studied as a safe and effective treatment option for patients with OAB. This study evaluated the effects of combining these two drugs on their pharmacokinetics and safety profiles in healthy Korean males. In this open-label, fixed-sequence, 3-period, drug-drug interaction phase 1 study, a total of 36 male participants were administered multiple doses of tamsulosin alone (0.2 mg once daily), mirabegron alone (50 mg once daily), and a combination of both drugs. The results showed that the combination of tamsulosin and mirabegron increased tamsulosin exposure in the plasma by approximately 40%. In contrast, the maximum plasma concentration of mirabegron reduced by approximately 17%, when administered along with tamsulosin. No clinically significant changes in safety profiles, vital signs, or clinical laboratory test results were observed in this study. In conclusion, there were no clinically relevant drug-drug interactions between tamsulosin and mirabegron in terms of pharmacokinetics, safety, and tolerability, suggesting that their combination therapy could be a promising treatment option for patients with OAB.

Drugs-drugs interactions(DDI) are entities composed of different chemical substructures (functional groups). In existing methods that predict drug–drug interactions based on the usage of substructures, each node is considered the center of a substructure, and adjacent nodes eventually become centers of similar substructures, resulting in redundancy. Furthermore, the significant differ- ences in structure and properties among compounds can lead to unrelated pairings, making it difficult to integrate information. This heterogeneity negatively affects the prediction results. To address these issues, we propose a drug–drug interaction prediction method based on substructure signature learning (DDI-SSL). This method extracts useful information from local subgraphs surrounding drugs and effectively utilizes substructures to assist in predicting drug side effects. Additionally, a deep clustering algorithm is used to aggregate similar substructures, allowing any individual subgraph to be reconstructed using this set of global signatures. Furthermore, we developed a layer-independent collaborative attention mechanism to model the mutual influence between drugs, generating signal strength scores for each class of drugs to mitigate noise caused by heterogeneity. Finally, we evaluated DDI-SSL on a comprehensive dataset and demonstrated improved performance in DDI prediction compared to state-of-the-art methods.

Flavonoids are a biochemically diverse group of specialized metabolites in plants that are derived from phenylalanine. While the biosynthesis of the flavonoid aglycone is highly conserved across species and well characterized, numerous species-specific decoration steps and their relevance remained largely unexplored. The flavonoid biosynthesis takes place at the cytosolic site of the endoplasmatic reticulum (ER), but accumulation of various flavonoids was observed in the central vacuole. A universal explanation for the subcellular transport of flavonoids has eluded researchers for decades. Current knowledge suggests that a glutathione S-transferase-like protein (ligandin) protects anthocyanins and potentially proanthocyanidin precursors during the transport to the central vacuole. ABCC transporters and to a lower extend MATE transporters sequester anthocyanins into the vacuole. Glycosides of specific proanthocyanidin precursors are sequestered through MATE transporters. A P-ATPase in the tonoplast and potentially other proteins generate the proton gradient that is required for the MATE-mediated antiport. Vesicle-mediated transport of flavonoids from the ER to the vacuole is considered as an alternative or additional route.

The link between ICTs, freight transport, and CO₂ emissions has not received much explicit examination by researchers, despite freight transportation being an egregious contributor to environmental degradation. This paper investigates how ICTs can affect environmental quality when interacting with freight transport activities in 43 countries over the period 2002-2014, using carbon emissions as a proxy for environmental damages. ICTs are measured in terms of internet, telephone, and mobile phone technologies. Using GMM methodology, the results show that ICTs contribute to dampening environmental degradation when interacting with freight transport activities. Specifically, a 10% increase in the interaction between ICTs and freight transportation will decrease carbon emissions by between 1.27% and 3.02%. The results further suggest that fixed and smartphone technologies are the main contributors to reducing emissions when adopted in some specific transport sectors (i.e. road, rail, and inland), while the internet is the most efficient technology when interacting with air transport activity. In addition, the interaction between ICTs and multimodality accelerates environmental quality. The policy implications of these findings are discussed.

Microbe-plant interactions are linked with the core microbiota, and both the plant and the microbial partners depend on one other to thrive in nature. However, why and how the below-ground core microbiota become established aboveground is poorly understood. We tracked the movement of a probiotic Streptomyces endophyte throughout a managed strawberry ecosystem. Probiotics in the rhizosphere and anthosphere were genetically identical, yet these niches were segregated in space and time. The probiotic in the rhizosphere moved upward via the vascular bundle, relocated to aboveground plant parts, and protected against Botrytis cinerea. It also moved from flowers to roots, and among flowers via pollinators that were protected against pollinator pathogens. Our results reveal a solid evidence in tripartite interaction with Streptomyces exploiting plant and pollinator partners.

We report the electronic, magnetic and transport properties of a prototypical antiferromagnetic (AFM) spintronic device. We chose Cr as the active layer because it is the only room-temperature AFM elemental metal. We sandwiched Cr between two non-magnetic metals (Pt or Au) with large spin-orbit coupling. We also inserted a buffer layer of insulating MgO to mimic the structure and finite resistivity of a real device. We found that, while spin-orbit has a negligible effect on the current flowing through the device, the MgO layer plays a crucial role. Its effect is to decouple the Cr magnetic moment from Pt (or Au) and to develop an overall spin magnetization. We have also calculated the spin-polarized ballistic conductance of the device within the Büttiker-Landauer framework, and we have found that for small applied bias our Pt/Cr/MgO/Pt device presents a spin polarization of the current amounting to ~25%.

With the realization of the Grand Canal's full water supply and the strong pursuit of green and low-carbon transportation in contemporary society, the value of the Grand Canal's water transport has been further affirmed, and its coordinated development with other transportation modes has become inevitable and important. This paper analyzes and combs through the characteristics, development status and existing problems of Grand Canal water transport and other transport modes in depth, and takes Jiangsu as an example. A collaboration model of Grand Canal water transport and other transport modes was built and their collaboration degree has been calculated. It is believed that the coordinated development of Grand Canal water transport and other transport modes can be greatly promoted via four aspects: optimizing the construction and governance of Grand Canal water transport, building an integrated management platform of transport modes, improving the integrated transport network structure, and promoting the deep integration of integrated shipping and tourism.

Numerous study reports on chitosan hydrogels in different forms such as films, porous structures, nanoparticles, and microspheres for biomedical applications, however, this study concentrates on their modifications with different crosslinking agents and observing their effects on drug loading and releasing capacities. Linear chitosan along with crosslinked by two major cross-linkers, i.e., genipin and disulfide have been used to formulate three different hydrogel systems. The cross-linking process is heavily impacted by the temperature and the pH conditions. Three different drugs, i.e., thymoquinone, gefitinib, and erlotinib are loaded in phosphate buffer solutions and infused with three different hydrogel systems, thus, a total of nine combinations are studied and analyzed for drug loading and releasing capabilities with Ultraviolet–visible (UV-Vis) spectroscopy. This study finds thymoquinone shows the lowest loading efficacy compared to two other drugs in all three systems. Gefitinib shows stable loading and releasing regardless of crosslinking systems and genipin crosslinked system shows stable loading and releasing with all three drug molecules. These experimental results agree well with the findings of our previously published results conducted with molecular dynamics simulations.

Drug delivery through Liposomes has shown tremendous potential in terms of the therapeutic application of nanoparticles. There are several drug-loaded liposomal formulations approved for clinical use that help mitigate harmful effects of life-threatening diseases. Developments in the field of liposomal formulations and drug delivery have made it possible for clinicians and researchers to find therapeutic solutions for complicated medical conditions. A key aspect in the development of drug-loaded liposomes is a careful review of optimization techniques to improve the overall formulation stability and efficacy. Optimization studies help in improving/modulating the various properties of drug-loaded liposomes and are vital for the development of this class of delivery systems. A comprehensive overview of the various process variables and factors involved in the optimization of drug-loaded liposomes is presented in this review. The influence of different independent variables on drug release and loading properties with the application of a statistical experimental design is also explained in this article.

The study aimed to identify clinical pharmacology patterns of prescribed and taken medications in older cardiovascular patients using electronic health records (EHRs) (n = 704) (2019–2022). Medscape Drug Interaction Checker was used to identify pairwise drug-drug interactions (DDIs). Prevalence rates of DDIs were 73.5% and 68.5% among taken and prescribed drugs, respectively. However, total number of DDIs was significantly higher among prescribed medications compared with the list of taken drugs (p < 0.05). Serious DDIs comprised 16% and 7% of all DDIs among prescribed and taken medications, correspondingly (p < 0.05). Median DDI numbers between prescribed versus taken medications were Me = 2, IQR 0-7 and Me = 3, IQR 0-7 per record, respectively. Prevalence of polypharmacy was significantly higher among prescribed medications compared with taken medications (p < 0.05). Women were taking significantly more drugs and had higher rates of polypharmacy and DDIs (p < 0.05). No sex-related differences were observed in the list of prescribed medications. ICD code U07.1 (COVID-19, virus identified) was associated with the highest median DDI number per record. Further research is warranted to improve EHR structure, patient engagement in reporting adverse drug reactions, and genetic profiling of patients to avoid potentially serious DDIs.

Accurately predicting drug-drug interactions (DDIs) is crucial for preventing adverse drug events in clinical settings. However, existing methodologies often rely on complex models built from diverse data sources, posing challenges in computational drug discovery. To address the need for precise computational methods in predicting unknown DDIs, this study introduces a novel Deep Neural Network (DNN)-based approach. By leveraging a wide range of drug-related information, including substructure, targets, side effects, pathways, and indications, our method calculates multiple drug similarities. These similarities are then synthesized using a nonlinear fusion method to extract high-level features. Subsequently, a tailored neural network is deployed for interaction prediction. Comparative evaluation against three prominent machine learning classifiers—Extreme Gradient Boosting (XGBoost), Adaptive Gradient Boosting (AdaBoost), and Light Gradient-Boosting Machine (LGBM)—using three benchmark datasets demonstrates the superior performance of DNN. It achieves outstanding accuracy, precision, recall, and F1-score metrics, all reaching 94.6% in cross-validation. Additionally, case studies involving numerous drug pairs confirm the reliability of DNN in accurately predicting unknown DDIs. These findings underscore DNN as a potent and reliable method for DDI prediction, with promising implications for drug discovery and healthcare applications.

The regulatory approvals of tumor agnostic therapies have led to reevaluation of the drug development process. Conventional models of drug development are histology-based. On the other hand, tumor agnostic drug development of a new drug (or combination) focuses on targeting a common genomic biomarker in multiple cancers, regardless of histology. Basket-like clinical trials with multiple cohorts allow clinicians to evaluate pan-cancer efficacy and toxicity. There are currently 8 tumor agnostic approvals granted by the Food and Drug Administration (FDA). This includes two immune checkpoint inhibitors, and 5 targeted therapy agents. Pembrolizumab is an anti-PD-1 antibody that was the first FDA approved tumor agnostic treatment for unresectable or metastatic microsatellite instability-high (MSI-H) or deficient mismatch repair (dMMR) solid tumors in 2017. It was later approved for tumor mutational burden-high (TMB-H) solid tumors, although the TMB cut-off used is still debated. Subsequently, in 2021, another anti-PD-1 antibody, Dostarlimab was also approved for dMMR solid tumors in the refractory setting. Patients with fusion-positive cancers are typically difficult to treat due to their rare prevalence and distribution. Gene rearrangements or fusions are present in a variety of tumors. neurotrophic tyrosine kinase (NTRK) fusions are present in a range of pediatric and adult solid tumors in varying frequency. Larotrectinib and entrectinib were approved for neurotrophic tyrosine kinase (NTRK) fusion-positive cancers. Similarly, selpercatinib was approved for Rearranged During Transfection (RET) fusion-positive solid tumors. FDA approved the first combination therapy of dabrafenib, a B-Raf Proto-Oncogene Serine/Threonine Kinase (BRAF) inhibitor, plus trametinib, a mitogen-activated protein kinase (MEK) inhibitor for patients 6 months or older with unresectable or metastatic tumors (except colorectal cancer) carrying BRAFV600E mutation. The most recent FDA tumor agnostic approval is of fam-trastuzumab deruxtecan-nxki (T-Dxd) for HER2-positive solid tumors. It is important to identify and expeditiously develop drugs that have the potential to provide clinical benefit across tumor types.

Neurodegenerative diseases are universally marked by the accumulation of misfolded protein. Neurons respond to these proteostatic disturbances by sequestering, and thus inactivating, toxic misfolded proteins into a perinuclear organelle called the aggresome. The aggresome can be subsequently degraded in bulk by autophagy, a process termed aggrephagy. The formation of protein aggregates has historically been considered a spontaneous and unregulated process, but emerging research has instead discovered a diverse cohort of regulatory proteins that mediate protein aggregation. Chaperones are the first proteins to respond to misfolded proteins, and do so by recognizing the aberrant exposure of hydrophobic domains. When chaperones are unable to correctly refold proteins, their substrates are transferred to ubiquitin ligating machinery to catalyze polyubiquitination. Although ubiquitin chains typically direct proteins towards proteasomes, severe proteotoxic stress can overwhelm, or even directly inhibit, proteasomes. As an alternative to proteasomal degradation, misfolded proteins are redirected towards the mitotic organizing center (MTOC) and, following retrograde transport by dynein, are packaged and sequestered within an intermediate filament (IF) cage to form the aggresome. The biogenesis of the aggresome is thus a highly regulated event, and a better understanding of the mechanisms facilitating this process will provide critical insight into neurodegenerative disease.

Background: Glioblastoma is the deadliest, yet most common, brain tumor in adults, with poor survival and response to aggressive therapy. Therapeutic failure results from a number of causes inherent to these tumors. Imaging, computational, and drug delivery approaches can aid in the quest to access and kill each tumor cell in patients. One factor, interstitial fluid flow, is a driving force therapeutic delivery. However, convective and diffusive transport mechanisms are un-der-studied. In this study, we examine the application of a novel image analysis method to meas-ure fluid flow and diffusion in glioblastoma patients with MRI and compare to patient outcomes. Methods: Building on a prior imaging methodology tested and validated in vitro, in silico and in preclinical models of disease, here we apply our analysis method to archival patient data from the Ivy GAP dataset. Results: We characterize interstitial fluid flow and diffusion patterns in patients. We find strong correlations between flow rates measured within tumors and in the surrounding parenchymal space, where we hypothesized that velocities would be higher. Looking at overall magnitudes, there is significant correlation with both age and survival in this patient cohort. Additionally, we find that tumor size nor resection significantly alter the velocity magnitude. Last, we map the flow pathways in patient tumors and find variability in degree of directionality that we hypothesize in future studies may lead to information concerning treatment, invasive spread, and progression. Conclusions: Analysis of standard DCE-MRI in patients with glioblastoma offers more infor-mation regarding transport within and around tumor, can be measured post-resection and mag-nitudes correlate with patient prognosis.

This paper shows the development of a numerical analysis model, which enables the calculation of the cargo transport capacity of a vehicle that circulates through a vacuum tube at high speed, whose effectiveness in transport is analyzed. The simulated transportation system is based on vehicles moving in vacuum tubes at high speed, a concept commonly known as Hyperloop, but assuming the vehicles for cargo containers. For the specific vehicle proposed, which does not include a compressor and levitates on magnets, the system formed by the vehicle and the vacuum tube has been conceptually developed, establishing the corresponding mathematical relationships that define its behavior. To properly model the performance of this transport system, it has been necessary to establish the relationships between the design variables and the associated constraints, such as the Kantrowitz limit, aerodynamics, transport, energy consumption, etc. Once the model was built and validated, it was used to analyze the effects of the variation of the number of containers, the operating speed and the tube length, considering the total and specific consumption of energy. Once the most efficient configuration was found regarding energy consumption and transport effectiveness, the complete system was calculated. The results obtained constitute a first approximation for the pre-design of this transport system and the built model allows different alternatives to be compared according to the design variables.

This paper describes the development of a two-dimensional water quality model that solves hydrodynamic equations tied to transport equations with reactions mechanisms inherent in the processes. This enable us to perform an accurate assessment of the pollution in a coastal ecosystem. The model was developed with data drawn from the ecosystem found in Mexico's southeast state of Tabasco. The coastal ecosystem consists of the interaction of El Yucateco lagoon with the Chicozapote and Tonalá rivers, that connect the lagoon with the Gulf of Mexico. We present the results of pollutants transport simulation in the coastal ecosystem, focusing on toxic parameters for two hydrodynamic scenarios: wet and dry seasons. As it of interest in the zone, we study the transport of four metals: Cadmium, Chromium, Nickel and Lead. In order to address our objectives we solved numerically a self-posed mathematical problem,which is based on the measured data. The performed simulations show to characterise metal transport within the acceptable range of accuracy and in accordance with the measured data. The performed simulations show to characterise metals transport with an acceptable accuracy, agreeing well with measured data in total concentrations in four control points along the water body. Although for the accurate implementation of the hydrodynamic-based water quality model herein presented, boundary (geometry, tides, wind, etc.) and initial (concentrations measurements) conditions are required, it poses as an excellent option when the distribution of solutes with high accuracy is required, easing environmental, economic and social management of coastal ecosystems.

Background Praziquantel is the commonly used conventional treatment recommended for schistosomiasis in the mainstream healthcare system. Although Praziquantel may be free in healthcare facilities, many individuals may resort to the use of traditional medicine. This study aimed to assess perceptions of participants on the availability of Praziquantel and to ascertain whether individuals infected with schistosomiasis used concurrently African traditional medicines with this treatment. Methods A cross–sectional descriptive study, using face-to-face interviews, was conducted from January to April 2023 among healthcare workers (HCWs) and patients. A review of medical chart records of patients was further carried out to triangulate the information from interviews. Ddescriptive statistics including frequency and percentage were used; categorical data were represented as tables. Chi-squared tests were performed for the association between continuous variables. A p value ≤ 0.05 was estimated as statistically significant. Results Most of HCWs (114/124; 91.9%) reported that Praziquantel was available in healthcare facilities. Majority of HCWs (76/124; 61.3%) did not know whether patients seen by them used concurrently traditional medicine and Praziquantel for schistosomiasis. There was no significant relationship between the availability of Praziquantel and the concurrent use of TM by patients for schistosomiasis (X2 = 3.042, p = 0.551). Patients seen by THPs (8/20, 40%) did not use Praziquantel for schistosomiasis. Those patients (8/15, 53.3%) who crossed from TM to the mainstream healthcare system did not disclose their use of TM to HCWs. Their main reason was that concurrent use of TM and Praziquantel could destroy organs or make Praziquantel not to work properly. None of the medical chart records analysed documented the concurrent use of TM and Praziquantel. Conclusion Most of HCWs were not aware of the concurrent use of TM and Praziquantel by patients for the treatment of schistosomiasis. Patients seen by THPs relied solely on TM for schistosomiasis. Although patients indicated crossing from TM to the mainstream healthcare system, there was no evidence of documented use of TM in medical chart records of patients. Further studies are needed to contribute to the knowledge of medicinal plants used by THPs for schistosomiasis.

The primary purpose of this study was to determine the prevalence of drug-drug interaction (DDI) and duplicate therapy in chronic patients in a completely random study population engaged in digital health apps. In this cross-sectional study, polypharmacy checks for 100 completely anonymous patients were analyzed for the occurrence of DDIs and duplicate therapy. Logistic regression models were used to identify factors associated with DDIs and duplicate therapy. DDIs and duplicate therapy prevalence were 34% and 33%, respectively. Chi-Square test discovered a significant association between the DDIs and duplicate therapy variables. Logistic regression models showed a strong association between the number of medications taken and higher odds of DDIs occurring in our population only. In conclusion, our study shows that polypharmacy is a determining factor for the occurrence of unwanted DDIs, and the prevalence of duplicate therapy and DDIs is around 33%, increasing an issue regarding patient safety and its burden to the healthcare system.

Astaxanthin (ATX) is a carotenoid nutraceutical with a poor bioavailability due to its high lipophilicity. We tested a new tailored nano-droplet capable of solubilizing ATX in an oil-in-water micro-environment (LDS-ATX, manufactured by Lyotropic Delivery Systems (LDS)), for its capacity to improve ATX pharmacokinetic profile and anti-oxidant efficacy. We used liquid chromatography tandem mass spectrometry (LC-MS/MS) to compare the pharmacokinetic profile of ATX and LDS-ATX and protein carbonylation and lipid peroxidation assays to compare their basal and lipopolysaccharide (LPS)-induced oxidative damage. Our results show that only LPS-induced oxidative damage was corrected by ATX and LDS-ATX. While in the liver and muscle LDS-ATX was more efficacious than ATX in attenuating oxidative damage to both proteins and lipids, only oxidative damage to lipids was preferably corrected by LDS-ATX in the brain. These results strongly suggest improvement of ATX bioavailability and efficacy by the LDS-ATX nano-formulation.

Transmembrane transport of small organic and inorganic molecules is one of the cornerstones of cellular metabolism. Among transmembrane transporters, solute carrier (SLC) proteins form the largest, albeit very diverse, superfamily with over 400 members. It has been early on recognized that xenobiotics can directly interact with SLCs and that this interaction can fundamentally determine their efficacy, including bioavailability and intertissue distribution. Apart from the well-established prodrug strategy, the chemical ligation of transporter substrates to nanoparticles of various chemical composition has recently been used as a means to enhance their targeting or absorption. In this review, we summarize efforts in drug design exploiting interactions with specific SLC transporters to optimize their therapeutic effects. Furthermore, we describe current and future challenges as well as new directions for the advanced development of therapeutics that target SLC transporters.

Abstract: The study used whole-genome sequencing (WGS) and bioinformatics analysis for the genomic characterization of 60 isolates of Listeria monocytogenes isolated from cattle farms, cattle abattoirs, and retail outlets in Gauteng province, South Africa. The isolates' sequence types (STs), clonal complexes (CCs), and lineages were determined using in silico multilocus sequence typing (MLST). We used BLAST-based analyses to identify virulence and antimicrobial genes, plasmids, proviruses, and the CRISPR-Cas system. The study investigated any association of the detected genes to the origin in the beef production chain of the L. monocytogenes isolates. Overall, in 60 isolates of Listeria monocytogenes, there were 7 STs, 6 CCs, 44 putative virulence factors, 2 resistance genes, 1 plasmid with AMR genes and 3 with conjugative genes, 1 CRISPR gene, and all 60 isolates were positive for proviruses. Among the 7 STs detected, ST204 (46.7%) and ST2 (21.7%) were the most prominent, with ST frequency varying significantly (p&lt;0.001). The predominant CC detected were CC2 (21.7%) and CC204 (46.7%) in lineages I and II, respectively. Of the 44 virulence factors detected, 26 (across Listeria Pathogenicity Islands, LIPIs) were present in all the isolates. The difference in the detection frequency varied significantly (P&lt;0.001). The two AMR genes (fosX and vga(G)) detected were present in all 60 (100%) isolates of L. monocytogenes. The only plasmid, NF033156, was present in 3 (5%) isolates. A CRISPR-Cas system was detected in 6 (10%), and all the isolates carried proviruses. Significant differences were detected in the frequencies of STs and virulence factors regarding the source and sample type of the L. monocytogenes isolates. The presence of both fosX and vga(G) genes in all the isolates from the three industries (cattle farms, abattoirs, and retail outlets) can potentially cause therapeutic implications. Our study, which characterized L. monocytogenes recovered from the three levels in the beef production chain in the country, provides the first evidence of the distribution of the pathogen with potential food safety and therapeutic implications.

Pituitary adenylate cyclase-activating polypeptide receptor 1 (PAC1-R) has a higher affinity for pituitary adenylate cyclase- activating polypeptide (PACAP) than for vasoactive intestinal peptide (VIP). PACAP exerts its neuroprotective effects through PAC1-R. PAC1-R has become a target for drug development, and we targeted PAC1-R to screen small positive allosteric modulator 1 (SPAM1). SPAM1 has a neuroprotective effects, and in the D-galactose (D-gal) mouse model, SPAM1 improved the structure of the hippocampal dentate gyrus and restored the number of neurons. Compared with D-gal model mice, SPAM1 treatment upregulated the expression of Sirtuin 6 (SIRT6) and Lamin B1, and downregulated the expression of YinYang 1 (YY1) and p16. Consistent with this, the same results were obtained in senescent RGC-5 cells. Meanwhile, SPAM1 was also found to up-regulate SIRT6 and down-regulate YY1 expression in normal RGC-5 cells. Then, we further explored the mechanism of SPAM1 neuroprotection by whole transcriptome sequencing and proteomic analysis, and found that SPAM is involved in the longevity regulating pathway, and confirmed the up-regulation of neurofilament light polypeptide and neurofilament medium polypeptide by western blot, thus laying a pharmacological foundation for SPAM1 as a therapeutic agent for neurodegenerative diseases. polypeptide and neurofilament medium polypeptide. Thus, it lays a pharmacological foundation for SPAM1 as a therapeutic drug for neurodegenerative diseases.

Drug-induced pruritus triggers a desire to scratch, thereby diminishing one’s quality of life. Certain instances of this phenomenon follow complex mechanisms of action that diverge from histamine-mediated pathways, known contributors to pruritus. However, investigations into the relationship between drugs and pruritus are limited. In this study, data mining techniques were employed to comprehensively analyze the characteristics of drugs linked to pruritus, using the FDA Adverse Event Reporting System(FAERS) Data maintained in the United States. Reports linked to pruritus demonstrated noteworthy differences in gender, age, and weight when compared with non-pruritus cases. Among the leading candidates for drugs prompting pruritus were ophthalmic drugs, systemic antibacterials, contrast media, dermatological antifungals, and dermatological preparations. Principal component analysis showed that the second principal component served as an indicator for distinguishing between onsets at mucous membranes or the skin surface. Additionally, the third principal component functioned as an indicator for categorizing administration methods as either invasive or noninvasive. Furthermore, a hierarchical cluster analysis conducted on these obtained principal components revealed the potential for classifying drugs based on the site of pruritus onset and the method of drug administration. These findings contribute to the development of targeted prevention and treatment strategies for avoiding pruritus in clinical practice.

The fitting and modeling of skewed, complex, symmetric, and asymmetric datasets is an exciting research topic in many fields of applied sciences, notably lifetime, medical, and financial sciences. The Heavy tailed Nadarajah Haghighi model is introduced by compounding the heavy tailed family and Nadarajah Haghighi distribution in this paper. The so obtained model has three parameters accounting for the scale and shape of the distribution. The proposed distribution's fundamental characteristics such as probability density, cumulative distribution, hazard rate, and survival functions are provided, and several key statistical properties are established, and several entropy information measures are proposed. The estimation of model parameter is performed via the ML procedure. Further, different simulation experiments are conducted to demonstrate the performance of proposed estimator’s using some measure, like the average estimate, the average bias, and associated mean square error. Finally, we are applied our proposed model to analyze three different real datasets. In our illustration, we are compared the practicality of the recommended model with several well-known competing models.

Background: The SARS-CoV-2 virus is a new highly pathogen virus that can suppress cell immune response (Poly ADPR process, and interferon releasing in infected cell) by viral macrodomain and create fatal pneumonia. Cytokine storm phenomenon which can create consequence of SARS COV-2 by increase of the performance of human TRPM2, is a dangerous condition for human and its body organ such as kidney, heart, and liver. it seems like prevention of beginning of these events is necessary. Material and methods: in this study drug and drug like database was used for inhibition of the viral macrodomain and human TRPM2 that can initiate of the viral cell cycle infection and human cytokine storm respectively. Ligand base drug designed, pharmacophore modeling, docking and molecular dynamic simulation was performed Results: among up to billion compounds, 20 compounds were screened by infinisee program. Then 7 compounds were selected by pharmacophore modeling. between 7 compounds, 5 compound was removed because of high similarity to ADPR and possibility of toxic effect for human RNA and DNA polymerase. One compound was losartan and selected for docking and molecular dynamic simulation. Conclusion: losartan earned a proper dock score and binding affinity to create the complexes with TRPM2 and macrodomain. Molecular dynamic simulation has shown losartan had an adequate binding free energy for human trpm2 and viral macrodomain. The inhibitory effect of losartan on these protein has shown and it could interfere in several points (PARP, PARG- macrodomain and TRPM2) and decreases oxidative stress, apoptosis, cytokine storm in COVID-19.

Ketamine as an old - new drug has variety of clinical implications. In the last 30 years, ketamine has become popular for acute use in humans. Ketamine at standard doses is principally utilized for the induction and maintenance in surgical procedures. Beside its use in anesthesia and analgesia, recently studies had shown that ketamine find the place in the treatment of asthma, epilepsy, depression, bipolar affective disorders, alcohol and heroin addiction. Its mechanism of action is complex, but it mostly acts as a noncompetitive antagonist at the N-methyl-D-aspartate (NMDA) receptor. Ketamine is generally considered relatively secure and does not result in serious adverse effects when used at low doses and for short periods- Also, ketamine is known as a powerful psychostimulant. During the past decade, ketamine has been one of the commonly abused drug.

Sex differences are essential factors in disease etiology and manifestation in many diseases such as cardiovascular disease, cancer, and neurodegeneration (1). The biological influence of sex differences (including genomic, epigenetic, hormonal, immunological, and metabolic differences between males and females) and the lack of biomedical studies considering sex differences in their study design has led to several policies. For example, the National Institute of Health’s (NIH) sex as a biological variable (SABV) and Sex and Gender Equity in Research (SAGER)) policies to motivate researchers to consider sex differences (2). However, drug repurposing, a promising alternative to traditional drug discovery by identifying novel uses for FDA-approved drugs, lacks sex-aware methods that can improve the identification of drugs that have sex-specific responses (1,3–5). Sex-aware drug repurposing methods either select drug candidates that are more efficacious in one sex or deprioritize drug candidates based on if they are predicted to cause a sex-bias adverse event (SBAE), unintended therapeutic effects that are more likely to occur in one sex. Computational drug repurposing methods are encouraging approaches to develop for sex-aware drug repurposing because they can prioritize sex-specific drug candidates or SBAEs at lower cost and time than traditional drug discovery. Sex-aware methods currently exist for clinical, genomic, and transcriptomic information (3,6,7). They have not expanded to other data types, such as DNA variation, which has been beneficial in other drug repurposing methods that do not consider sex (8). Additionally, some sex-aware methods suffer from poorer performance because a disproportionate number of male and female samples are available to train computational methods (3). However, there is development potential for several different categories (i.e., data mining, ligand binding predictions, molecular associations, and networks). Low-dimensional representations of molecular association and network approaches are also especially promising candidates for future sex-aware drug repurposing methodologies because they reduce the multiple hypothesis testing burden and capture sex-specific variation better than the other methods (9,10). Here we review how sex influences drug response, the current state of drug repurposing including with respect to sex-bias drug response, and how model organism study design choices influence drug repurposing validation.

Drug abuse is a major issue worldwide. Methylphenidate (MPH) and alprazolam (ALZ) are commonly prescribed drugs for the treatment of ADHD and anxiety disorders, respectively. The limited studies suggest that abusers primarily use benzodiazepines to counteract adverse effects associated with methylphenidate usage. The main aim of this study was to investigate the interaction of drugs with DNA using spectroscopic methods. Female Wistar rats were administered with MPH (10, 20, 40 mg/kg) and ALZ (5, 10, 20 mg/kg) alone and in combination for a period of 28 days. The FT-IR and UV results reveal some spectral changes in a dose-dependent manner, which indicates interactions of drugs with DNA. Thus, the changes in spectral peaks provide some insight into the mechanism of the interaction of drugs with DNA.

Legumes are important sources of nitrogen and, therefore, the nitrogen fixing ability of the legume-rhizobia symbiosis has great potential to improve crop yields or reduce nitrogen fertilizer use. Unfortunately, legumes face serious and increasing threats of both biotic and abiotic stresses among which Fe-deficiency has been increased from past years. Fe nutrient deficiency limits pulse production and nitrogen fixation by specifically affecting any one of the four phases of legume-rhizobium symbiosis. Although Fe in soil is often present in adequate quantities, it is mainly present in insoluble Fe-(III) precipitates, limiting its uptake and utilization. The present review has focused on the iron nutrition and deficiency and probable uptake, transport and metabolism in legumes.

Anthropogenic activities such as the damming of rivers have resulted in the formation of depositional systems for sediments that are naturally transported along river channels all over the world. The steady accumulation of sediments has profound effects on how reservoirs function. As the reservoir ages, the impact of sedimentation becomes more pronounced. In an alluvial channel, the dynamics of sediment movement, scour, and deposition are exceedingly complicated. The quantitative and qualitative management of river engineering heavily relies on sediment motion. One of the key concerns affecting reservoir storage capacity is reservoir sedimentation. Understanding the form and behavior of the river or reservoir is necessary for a scientific approach to sedimentation. An overview of reservoir sedimentation processes, and models of reservoir and shallow water bodies is provided in this article. More research in the developing fields is advised for continuing studies on reservoir sedimentation due to climate change effects

In Acropora, the complex canals in a coral colony connect all polyps into a holistic network to collaborate in performing biological processes. There are various types of canals, including calice, axial canals, and other internal canals, with structures that are dynamically altered during different coral growth states due to internal calcium transport. However, few studies have considered the regulation of calcium transport in Acropora. In this study, we investigated the morphological changes of the axial canal in six Acropora muricata samples by high resolution micro-computed tomography, observing the patterns of the axial canal during the processes of new branch formation and truncated branch rebuilding. We visualized the formation of a new branch from a calice and deposition of the iconic hexactin skeletons in the axial canal. Furthermore, the diameter and volume changes of the axial canal in truncated branches during rebuilding processes were calculated, revealing that the volume ratio of calcareous deposits in the axial canal exhibit significant increases within the first three weeks, returning to levels in the initial state in the following week. This work indicates that the axial canal can transport calcium to form hexactin skeletons in a new branch and rebuild the tip of a truncated branch. The calcium transport along canal network regulates various growth processes, including budding, branching, skeleton forming, and self-rebuilding of an Acropora colony. Understanding the changes in canal function under normal and extreme conditions will provide theoretical guidance for restoration and protection of coral reefs.

Microplastics (MPs) are small pieces of plastics. They are ubiquitous in the environment and can enter the freshwater environment from surface run-off and wastewater effluent (treated and untreated), industrial effluent, degraded plastic waste, and atmospheric deposition. They are not usually destroyed but convert into one phase to another. They are a source of air pollution, occurring in dust and airborne fibrous particles. Mostly MPs are non-biodegradable while some MPs are biodegradable, which can be decomposed in the presence of ultraviolet (UV) light or by the action of microorganisms. Popular methods: chemical, spectroscopic, and thermo-analytical are available for the determination of the chemical composition and size of plastic particles. This chapter discusses the uses, health hazards, sources, and transport of MPs particles.

The concept of sustainability and sustainable development, especially systemic sustainable development, still raises controversy in literature. The article makes an attempt to re-examine these concepts from a systems perspective, seeking foundations and applications in the selected sector. It is becoming increasingly clear that sustainability and sustainable development are aimed at integrated economic, social, cultural, political, and ecological factors [1[,[2] (pp.641-642). This causes that the constructive approach to the issue is required, taking into account all the actors, areas and dimensions involved in the pursuit of systemic sustainable development. As a result, both local and global dimensions and the way they interact must be explored in a multi-faceted manner in order to offer a perspective more useful than other analytical approaches, because the systems view is a way of thinking in terms of connectedness, relationships, and context [3]. The article aims to review selected publications and studies so as to form the general idea of systemic sustainable development and define the systemic development of sustainable transport, including in particular the perspective of the actors of the sector, transport providers (passenger, urban) and transport development program, implemented both by local governments and on the European scale. An attempt was made to identify elements of the systemic sustainable development model, setting it in the reality of the following subcategories: “Society”, “Economy” and “Environment” in sectoral terms. It is supposed that, systemic sustainable development is a conglomerate of public administration entities, companies operating in the sector, individual and corporate customers, acting in certain conditions for economic, social and environmental well-being, and a number of their initiatives of major or minor significance, grouped in six sub-areas, undertaken to achieve systemic value in the examined sector, with a positive or negative business/economic, social and environmental impact.

The world is moving to the next phase of the energy transition with high penetrations of renewable energy. Flexible and scalable redox flow battery (RFB) technology is expected to play an important role in ensuring electricity network security and reliability. Continuous performance improvements will further enhance their value by reducing parasitic losses and maximizing available energy conversion over broader operating conditions. Concentration overpotentials from poor internal reactant distribution at high and low states of charge (SOC) limit power densities and are thus an important area of investigation. However, efforts to address these coupled electrochemical phenomena can compromise mechanical performance. Modelling and simulation of cell design innovations have shown it is possible to reduce losses from pump energy while increasing the availability of active species where required. The combination of wedge-shaped cells with static mixers investigated in this paper can reduce pressure drop and improve energy efficiency. Toroidal vanadium redox flow battery (VRB/VRFB) designs incorporating this innovation are presented for further development to improve community engagement with the technology.