Hydrophobic Microenvironment Modulation of Ru Nanoparticles in Metal-Organic Frameworks for Enhanced Electrocatalytic N2 Reduction.

The modulation of the chemical microenvironment surrounding metal nanoparticles (NPs) is an effective means to enhance the selectivity and activity of catalytic reactions. Herein, a post-synthetic modification strategy is developed to modulate the hydrophobic microenvironment of Ru nanoparticles encapsulated in a metal-organic framework (MOF), MIP-206, namely Ru@MIP-Fx (where x represents perfluoroalkyl chain lengths of 3, 5, 7, 11, and 15), in order to systematically explore the effect of the hydrophobic microenvironment on the electrocatalytic activity. The increase of perfluoroalkyl chain length can gradually enhance the hydrophobicity of the catalyst, which effectively suppresses the competitive hydrogen evolution reaction (HER). Moreover, the electrocatalytic production rate of ammonia and the corresponding Faraday efficiency display a volcano-like pattern with increasing hydrophobicity, with Ru@MIP-F7 showing the highest activity. Theoretical calculations and experiments jointly show that modification of perfluoroalkyl chains of different lengths on MIP-206 modulates the electronic state of Ru nanoparticles and reduces the rate-determining step for the formation of the key intermediate of N2H2 *, leading to superior electrocatalytic performance.

Therapeutic potential of boswellic acids: an update patent review (2016-2023).

INTRODUCTION: Boswellic acids (BAs) are a group of pentacyclic triterpenoids of the ursane and oleanane type. They have shown very interesting biological properties that have led to the development of a number of synthesis protocols. Both natural BAs and their synthetic derivatives may be useful in the treatment of a variety of cancers, viral infections and inflammatory diseases. AREAS COVERED: This review covers patents relating to the therapeutic activities of natural BAs and their synthetic derivatives. The latest patented studies of boswellic acids (are summarized by using the keywords 'boswellic acid,' in SciFinder, PubMed, and Google Patents and databases in the year from 2016 to 2023. EXPERT OPINION: Boswellic acids have shown potent antiviral, anticancer and anti-inflammatory potential. Few BAs analogues have been prepared by modification at the C24-CO2H functional groups. In particular, the C-24 amide and amino analogues have shown enhanced anticancer effects compared to the parent AKBA. In addition, BAs have the ability to form conjugates with other antiviral, anti-inflammatory and anticancer drugs that synergistically enhance their biological efficacy. In addition, this conjugation strategy will increase the solubility and bioavailability of BAs, which is one of the most important issues in the development of BAs.

Phase 1/2 AAV5-hRKp.RPGR (Botaretigene Sparoparvovec) Gene Therapy: Safety and Efficacy in RPGR-associated X-linked Retinitis Pigmentosa.

PURPOSE: To assess the safety and efficacy of AAV5-hRKp.RPGR in participants with retinitis pigmentosa GTPase regulator (RPGR)-associated X-linked retinitis pigmentosa (XLRP). DESIGN: Open-label, phase 1/2 dose escalation/expansion study (NCT03252847). METHODS: Males (≥5 years old) with XLRP-RPGR were evaluated. In the dose escalation phase, subretinal AAV5-hRKp.RPGR (low: 1.0×1011 vg/ml; intermediate: 2.0×1011 vg/ml; high: 4.0×1011 vg/ml) was administered to the poorer-seeing eye (n = 10). Dose confirmation (intermediate dose) was carried out in 3 pediatric participants. In the dose expansion phase, 36 participants were randomized 1:1:1 to immediate (low or intermediate dose) or deferred (control) treatment. The primary outcome was safety. Secondary efficacy outcomes included static perimetry, microperimetry, vision-guided mobility, best corrected visual acuity, and contrast sensitivity. Safety and efficacy outcomes were assessed for 52 weeks for immediate treatment participants and 26 weeks for control participants. RESULTS: AAV5-hRKp.RPGR was safe and well tolerated, with no reported dose-limiting events. Most adverse events (AEs) were transient and related to the surgical procedure, resolving without intervention. Two serious AEs were reported with immediate treatment (retinal detachment, uveitis). A third serious AE (increased intraocular pressure) was reported outside the reporting period. All ocular inflammation-related AEs responded to corticosteroids. Treatment with AAV5-hRKp.RPGR resulted in improvements in retinal sensitivity and functional vision compared with the deferred group at Week 26; similar trends were observed at Week 52. CONCLUSIONS: AAV5-hRKp.RPGR demonstrated an anticipated and manageable AE profile through 52 weeks. Safety and efficacy findings support investigation in a phase 3 trial.

Sero-epidemiology of bluetongue in ruminants raised on private holdings in North-Western Pakistan.

This study investigated the sero-epidemiology of bluetongue in ruminants in North-Western Pakistan. A total of 3,173 serum samples were collected from small (n = 1,651) and large (n = 1,522) ruminants being reared by farmers in 14 districts. Antibodies to bluetongue virus (BTV) were detected using competitive ELISA. The overall prevalence of BTV antibodies was 65%. A significant association (P < 0.05) between the prevalence of BTV antibodies and the risk factors including sex, species, age, area, husbandry practices and breed was shown by univariate analysis. In multivariate analysis, the seroprevalence was 6.5 (95% CL = 3.7-11.4), 5.9 (95% CL = 3.8-9.4) and 2.4 (95% CL = 1.5-3.7) times higher in buffaloes, cattle and goats than sheep, respectively. The seroprevalence was 1.4 (95% CL = 1.1-1.7) times higher in local breeds than in cross/exotic breeds. The seroprevalence was 1.6 (95% CL = 1.1 to 2.3) times higher in sedentary animals than in nomadic animals. The seroprevalence was significantly associated with age. Further work is required to determine the BTV serotypes prevalent in the study area for effective control of the disease.

Impact of diet and physical activity on reproductive profile: A comparison of middle-aged and elderly men.

Age is a known determinant of reproductive health and fertility in both genders. The present work aims to assess the reproductive hormone profile of a middle-aged and elderly man. For this descriptive cross-sectional study, healthy male subjects (n=77) were recruited from the valley. Any individual suffering from any acute or chronic diseases and on drugs was ruled out from the study. Group A consisted of 40 elderly men between 60-70 years of age, and Group B comprised 37 men between 35-46 years of age. Blood samples were taken to estimate the reproductive hormone profile. Level of oxidant and antioxidant: Malondialdehyde and Glutathione. The demographic variables, which included retrospective and prospective questions, helped to assess the physical activity and diet intake behaviour of all inducted individuals. The analysis of the reproductive profile of both groups was similar and within the normal range of standards. However, the median level of LH was higher in group A than in group B: 6.7 mIU/ml versus 3.4 mIU/ml, respectively, and p<0.003. Both groups showed predominantly involvement in physical activity, >90%. The correlation of biochemical variables gives an insight into the fact that the Mediterranean diet and physical activity help to maintain a normal BMI. These implicate the normal secretion of various hormones, leading to intact spermatogenesis. We can safely deduce from this study that physically active lifestyles and a healthy diet are crucial factors in maintaining an endocrine profile.

L'âge est un déterminant connu de la santé reproductive et de la fécondité chez les deux sexes. Le présent travail vise à évaluer le profil hormonal de la reproduction d'un homme d'âge moyen et âgé. Pour cette étude transversale descriptive, des sujets masculins en bonne santé (n = 77) ont été recrutés dans la vallée. Toute personne souffrant de maladies aiguës ou chroniques et prenant des médicaments a été exclue de l'étude. Le groupe A était composé de 40 hommes âgés de 60 à 70 ans et le groupe B de 37 hommes âgés de 35 à 46 ans. Des échantillons de sang ont été prélevés pour estimer le profil des hormones reproductives. Niveau d'oxydant et d'antioxydant : Malondialdéhyde et Glutathion. Les variables démographiques, qui comprenaient des questions rétrospectives et prospectives, ont permis d'évaluer l'activité physique et le comportement alimentaire de tous les individus intronisés. L'analyse du profil reproducteur des deux groupes était similaire et se situait dans la fourchette normale des normes. Cependant, le taux médian de LH était plus élevé dans le groupe A que dans le groupe B : respectivement 6,7 mUI/ml versus 3,4 mUI/ml et p<0,003. Les deux groupes présentaient une participation prédominante à l'activité physique, > 90 %. La corrélation des variables biochimiques donne un aperçu du fait que le régime méditerranéen et l'activité physique contribuent à maintenir un IMC normal. Celles-ci impliquent la sécrétion normale de diverses hormones, conduisant à une spermatogenèse intacte. Nous pouvons déduire de cette étude qu'un mode de vie physiquement actif et une alimentation saine sont des facteurs cruciaux pour maintenir un profil endocrinien.

Self correction fractional least mean square algorithm for application in digital beamforming.

Fractional order algorithms demonstrate superior efficacy in signal processing while retaining the same level of implementation simplicity as traditional algorithms. The self-adjusting dual-stage fractional order least mean square algorithm, denoted as LFLMS, is developed to expedite convergence, improve precision, and incurring only a slight increase in computational complexity. The initial segment employs the least mean square (LMS), succeeded by the fractional LMS (FLMS) approach in the subsequent stage. The latter multiplies the LMS output, with a replica of the steering vector (R) of the intended signal. Mathematical convergence analysis and the mathematical derivation of the proposed approach are provided. Its weight adjustment integrates the conventional integer ordered gradient with a fractional-ordered. Its effectiveness is gauged through the minimization of mean square error (MSE), and thorough comparisons with alternative methods are conducted across various parameters in simulations. Simulation results underscore the superior performance of LFLMS. Notably, the convergence rate of LFLMS surpasses that of LMS by 59%, accompanied by a 49% improvement in MSE relative to LMS. So it is concluded that the LFLMS approach is a suitable choice for next generation wireless networks, including Internet of Things, 6G, radars and satellite communication.

Undiagnosed vertebral fragility fractures in patients with distal radius fragility fractures: an opportunity for prevention of morbimortality in osteoporotic patients in developing countries.

Our study investigates vertebral fractures in individuals with distal radius fractures. Among 512 patients, 41.21% had vertebral fractures, predominantly in the lumbar spine. These findings highlight the importance of screening for vertebral fractures in this population, informing early intervention strategies to mitigate risks associated with osteoporosis. PURPOSE: This study's main goal was to look into the frequency, location, kind, and severity of asymptomatic vertebral fragility fractures (VFF) in people who had fractures of the fragility of the distal radius. Although VFF is frequently misdiagnosed, it is linked to higher mortality, morbidity, and hip fracture risk. The study also attempted to investigate the relationship between VFF and certain demographic and lifestyle factors, as well as FRAX data, in this patient population. METHODS: Between January, 2021, and January, 2022, individuals with low-energy distal radial fractures who presented to the emergency room of tertiary care hospital of Karachi, Pakistan, were the subject of a cross-sectional study and were 45 years of age or older except those who fitted the exclusion criteria (n = 208). The thoracic and/or lumbar spine was imaged using radiology, and information on demographics, way of life, and FRAX (Fracture Risk Assessment Tool) was gathered. Using the Genant semiquantitative approach, an impartial and blinded orthopaedist identified VF in the images and determined their severity. SPSS version 20 was used to analyse the data. RESULTS: Two hundred eleven (41.21%) of them were found to have radiographic VFF and only 12 (2.34%) of the 512 patients who were tested were getting osteoporotic therapy. The thoracic spine (32.7%), followed by the lumbar spine (43.12%), was the area most frequently afflicted. In 24.17% of the patients, multiple fractures of the thoracolumbar spine were found. The wedge form (54.5%), followed by biconcave (30.81%) and crush (14.7%), was the most prevalent VFF type. The majority of detected VFF were rated as having a 25-40% height loss (64.9%) then severe (> 40%) fractures (35.1%), according to the Genant grading method. Notably, there were no variations in smoking, drinking, BMI, or FRAX score between patients with and without VFF that were statistically significant. CONCLUSION: Based on our study's findings, it is clear that osteoporotic vertebral fragility fractures occur in almost half of individuals with distal radius fractures. The lumbar spine is notably the most affected region, predominantly with wedge fractures. Given the high prevalence of asymptomatic vertebral fragility fractures (VFF), proactive measures are necessary to mitigate associated risks. Prioritising comprehensive fall risk assessments for these patients and interventions to enhance bone mineral density and strength are crucial. Early identification of asymptomatic VFF enables timely intervention, optimising patient care and minimising the risk of complications in this vulnerable population.

Achieving zero emission targets: The influence of green bonds on clean energy investment and environmental quality.

The effectiveness of green finance in driving clean energy and environmental sustainability in the current era is receiving attention. Therefore, this study proposes an empirical framework highlighting the effects of green bonds (GB) on clean energy investment (CEI), clean energy investment efficiency (CEE) and environmental sustainability of 29 green bond issuing countries between 2014 and 2022. Using system and difference GMM approaches, this study finds that (i) green bond issuance drives clean energy investment. (ii) Green bonds sufficiently enhance the selected countries' environmental quality. These results supplement the promotion of green bonds in increasing the transfer of funds towards renewable energy projects by reducing reliance on fossil fuels. (iii) Using Driscoll & Kraay, Fully Modified-OLS, and changing the dependent variable, this study further supported the idea that green bonds effectively promote the CEE and environmental sustainability of the chosen countries. (iv) Similarly, this study conducted income heterogeneity, showing that green bonds improve high- and middle-income countries' CEI and environmental quality. (v) Finally, the results indicate that resource consumption escalates CO2 emissions by declining the CEI. Technological innovations increase CEI, whereas they do not mitigate CO2 emissions directly, hinting at the requirement for a comprehensive approach. Therefore, inclusive policies on green bond frameworks, robust incentives, and rigorous environmental criteria should be implemented to attract investment in clean energy development and ensure the environmental sustainability of the selected countries.

Optimizing Electrodeposition of Polyaniline on Various Woven Steel Mesh Sizes for Enhanced Supercapacitor Performance.

The development of efficient supercapacitors hinges on the innovation of superior electrodes, which are pivotal in augmenting their energy storage capabilities. Supercapacitors, recognized for their high-power density and extended cycle life, play a crucial role as sustainable solutions in addressing energy storage challenges. A fundamental aspect of supercapacitor functionality involves the electrode material, which works in concert with other key components such as the current collector, separator, and electrolyte. This study focuses on evaluating the impact of the current collector material on the performance of symmetric supercapacitors. We investigated the electropolymerization of polyaniline on woven steel mesh current collectors of varying mesh sizes, ranging from 20 to 200 mesh per inch, using assorted deposition conditions. The electrochemically modified woven steel meshes were utilized to construct symmetric supercapacitors. The electrochemical performance of the assembled supercapacitors, configured in a two-electrode system, was investigated using a variety of electrochemical techniques to better understand the kinetics of electrolyte ion migration. Notably, the 20-mesh size, characterized by the fewest pores per inch, demonstrated superior performance with an optimum capacitance of 4730 mF/cm2, an energy density of 317.8 µWh/cm2, and a power density of 400 µW/cm2 at a current density of 1 mA/cm2.

RLAD: A Reliable Hippo-guided Multi-task Model for Alzheimer's Disease Diagnosis.

Early diagnosis of Alzheimer's disease (AD) is crucial for its prevention, and hippocampal atrophy is a significant lesion for early diagnosis. The current DL-based AD diagnosis methods only focus on either AD classification or hippocampus segmentation independently, neglecting the correlation between the two tasks and lacking pathological interpretability. To address this issue, we propose a Reliable Hippo-guided Learning model for Alzheimer's Disease diagnosis (RLAD), which employs multi-task learning for AD classification as a main task supplemented by hippocampus segmentation. More specifically, our model consists of 1) a hybrid shared features encoder that encodes local and global information in MRI to enhance the model's ability to learn discriminative features; 2) Task Specific Decoders to accomplish AD classification and hippocampus segmentation; and 3) Task Coordination module to correlate the two tasks and guide the classification task to focus on the hippocampus area. Our proposed RLAD model is evaluated on MRI scans of 1631 subjects from three independent datasets, including ADNI-1, ADNI-2, and HarP. Our extensive experimental results demonstrate that the proposed model significantly improves the performance of AD classification and hippocampus segmentation with strong generalization capabilities. Our implementation and model are available at https://github.com/LeoLjl/Explainable-Alzheimer-s-Disease-Diagnosis.

Facilitated transport of ferrihydrite with phosphate under saturated flow conditions.

With increasing phosphate (P) entering the environment during agricultural application, the subsurface flow of particular P has been recently discussed as a vital P transport pathway. Iron (oxyhydr)oxide colloid-facilitated P transport is critical for iron and P biogeochemical processes in the subsurface. This study investigated the ferrihydrite colloid-facilitated P transport through adsorption and column experiments under different P concentrations and three pH conditions. Increased P loading on ferrihydrite colloids decreased the transport of ferrihydrite colloids (< 8.0%) under acid conditions through pore straining and irreversible attachment. Under neutral and alkaline conditions, ferrihydrite colloids exhibited more negative surfaces and smaller diameters with increasing P, which further enhanced ferrihydrite colloid transport (maximum to 95.6%). Ferrihydrite colloid-facilitated P transport was limited under acid conditions, and it was 10% - 57% enhancement under neutral and alkaline conditions with increasing P adsorption. Under neutral conditions, ferrihydrite colloid-facilitated P transport was strongest (maximum to 68.84%) because of its stronger ferrihydrite colloid transport than under acid conditions and larger P adsorption capacity than under alkaline conditions. Our findings indicate that the facilitated transport of ferrihydrite colloids in the presence of P may be appreciable in iron and phosphate-rich soil and subsurface systems, which is essential for evaluating the fate of iron and iron-facilitated P and potential environmental risks of P transport in the subsurface.

Solitonic solutions and stability analysis of Benjamin Bona Mahony Burger equation using two versatile techniques.

This study aims to explore the precise resolution of the nonlinear Benjamin Bona Mahony Burgers (BBMB) equation, which finds application in a variety of nonlinear scientific disciplines including fluid dynamics, shock generation, wave transmission, and soliton theory. Within this paper, we employ two versatile methodologies, specifically the extended exp ( - Ψ ( χ ) ) expansion technique and the novel Kudryashov method, to identify the exact soliton solutions of the nonlinear BBMB equation. The solutions we discovered involve trigonometric functions, hyperbolic functions, and rational functions. The uniqueness of this research lies in uncovering the bright soliton, kink wave solution, and periodic wave solution, and conducting stability analysis. Furthermore, the solutions' graphical characteristics were explored through the utilization of the mathematical software Maple 2022 ( https://maplesoft.com/downloads/selectplatform.aspx?hash=61ab59890f2313b2241fde3423fd975e ). The system's physical interpretation is defined through various types of graphs, including contour graphs, 3D-surface graphs, and line graphs, which use appropriate parameter values. These recommended techniques hold significant importance and are applicable in diverse nonlinear evolutionary equations found in the field of nonlinear sciences for illustrating nonlinear physical models.

Isothermal and kinetic screening of methyl red and methyl orange dyes adsorption from water by Delonix regia biochar-sulfur oxide (DRB-SO).

In this study, Delonix regia seed pods (DRSPs) as a locally available material were refluxed in 90% H2SO4 to yield a novel D. regia seed pods biochar-sulfur oxide (DRB-SO). FTIR, BET, BJH, SEM, EDX, XRD, DSC and TGA were applied to investigate the characterizations of the prepared DRB-SO. Various adsorption parameters like pH effect, dye concentration effect, adsorbent dose, reaction time isotherm and kinetic study were carried out to explain the process of adsorption of methyl orange (MO) and methyl red (MR) onto DRB-SO. Langmuir's adsorption model perfectly explained the adsorption process onto the surface of DRB-SO as a monolayer. The maximum adsorption efficiency of DRB-SO was (98%) and (99.6%) for MO and MR respectively which attained after 150 min with an adsorbent dose of 0.75 g/L. The pseudo-second-order kinetic model best explained the process of adsorption of MO and MR dyes by DRB-SO. The highest observed adsorption amount was as high as 144.9 mg/g for MO dye and 285.7 mg/g for MR dye, comparable with other reported materials based on activated carbon materials. All of the outcomes signposted a prodigious perspective of the fabricated biochar composite material in wastewater treatment. Using the regenerating DRB-SO through an acid-base regeneration process, six cycles of adsorption/desorption were examined. Over the course of the cycles, there was a minor decrease in the adsorption and desorption processes. Also, it was revealed what the most plausible mechanism was for DRB-SO to absorb the ions of the MO and MR dyes.

Novel acyl hydrazide derivatives of polyhydroquinoline as potent anti-diabetic and anti-glycating agents: Synthesis, in vitro α-amylase, α-glucosidase inhibition and anti-glycating activity with molecular docking insights.

In this study, eleven novel acyl hydrazides derivative of polyhydroquinoline were synthesized, characterized and screened for their in vitro anti-diabetic and anti-glycating activities. Seven compounds 2a, 2d, 2i, 2 h, 2j, 2f, and 2 g exhibited notable α-amylase inhibitory activity having IC50 values from 3.51 ± 2.13 to 11.92 ± 2.30 µM. Similarly, six compounds 2d, 2f, 2 h, 2i, 2j, and 2 g displayed potent α-glucosidase inhibitory activity compared to the standard acarbose. Moreover, eight derivatives 2d, 2 g, 2f, 2j, 2a, 2i, 2 g, and 2e showed excellent anti-glycating activity with IC50 values from 6.91 ± 2.66 to 15.80 ± 1.87 µM when compared them with the standard rutin (IC50 = 22.5 ± 0.90 µM). Molecular docking was carried out to predict the binding modes of all the compounds with α-amylase and α-glucosidase. The docking analysis revealed that most of the compounds established strong interactions with α-amylase and α-glucosidase. All compounds fitted well into the binding pockets of α-amylase and α-glucosidase. Among all compounds 2a and 2f were most potent based on docking score -8.2515 and -7.3949 against α-amylase and α-glucosidase respectively. These results hold promise for the development of novel candidates targeted at controlling postprandial glucose levels in individuals with diabetes.

SPE-UHPLC-ESI-MS/MS Analysis of Cocaine and Its Metabolites in Conventional and Alternative Biological Specimens: Application to Real Samples.

An increase in cocaine abuse has been observed globally since the past decade. Cocaine is among the commonly abused stimulants used for recreational purposes. In this study, the SPE-UHPLC-MS/MS method was developed and validated to be applied on real specimens of 20 chronic cocaine abusers to quantify cocaine/metabolites in conventional as well as alternative biological matrices. Cocaine was extracted from biological specimens using solid-phase extraction followed by liquid chromatography tandem mass spectrometry analysis. Chromatographic separation was achieved on a Poroshell120EC-18 column (2.1 mm × 50 mm, 2.7 µm particle size) using water-acetonitrile in 0.1% formic acid as a mobile phase in gradient elution mode. The flow rate of the mobile phase was 0.5 mL/min with a gradient varying the percentage of acetonitrile linearity ranging 15-95% in 6.0 min acquisition time, and the injection volume was set at 5 µL. Positive electrospray ionization with multireaction ion monitoring mode using two ion transitions for cocaine/metabolites and one for cocaine-d3 was employed. The quantification method demonstrated good linear ranges of 0.025-250 ng/mL in blood, urine, and oral fluid (ng/mg for hair and nail) with a ≥0.991% determination coefficient. The detection limit and lower quantification limit were 0.005 and 0.025 ng/mL in all matrices, respectively. The mean extraction recovery and ionization suppression ranged from 89.3 to 99.8% and -4.6 to -14.4% in the studied matrices. Within-run and between-days precisions were 1.8-7.2% and 1.9-6.1%, respectively. This study will not only help in quantifying cocaine/metabolites in alternative specimens (hair, nail, and oral fluid) but also guide clinical and forensic toxicologists in interpretation of exhumation cases. Furthermore, multiple specimens' analyses can be of significance in estimating the time/manner of drug exposure, in confirming the results of laboratories in cases of doubtful clinical histories, or in aiding medico-legal investigations.

A review on cultivating effective learning: synthesizing educational theories and virtual reality for enhanced educational experiences.

Immersive technology, especially virtual reality (VR), transforms education. It offers immersive and interactive learning experiences. This study presents a systematic review focusing on VR's integration with educational theories in higher education. The review evaluates the literature on VR applications combined with pedagogical frameworks. It aims to identify effective strategies for enhancing educational experiences through VR. The process involved analyzing studies about VR and educational theories, focusing on methodologies, outcomes, and effectiveness. Findings show that VR improves learning outcomes when aligned with theories such as constructivism, experiential learning, and collaborative learning. These integrations offer personalized, immersive, and interactive learning experiences. The study highlights the importance of incorporating educational principles into VR application development. It suggests a promising direction for future research and implementation in education. This approach aims to maximize VR's pedagogical value, enhancing learning outcomes across educational settings.

The UK Soft Drinks Industry Levy and childhood hospital admissions for asthma in England.

Sugar sweetened beverage consumption has been suggested as a risk factor for childhood asthma symptoms. We examined whether the UK Soft Drinks Industry Levy (SDIL), announced in March 2016 and implemented in April 2018, was associated with changes in National Health Service hospital admission rates for asthma in children, 22 months post-implementation of SDIL. We conducted interrupted time series analyses (2012-2020) to measure changes in monthly incidence rates of hospital admissions. Sub-analysis was by age-group (5-9,10-14,15-18 years) and neighbourhood deprivation quintiles. Changes were relative to counterfactual scenarios where the SDIL wasn't announced, or implemented. Overall, incidence rates reduced by 20.9% (95%CI: 29.6-12.2). Reductions were similar across age-groups and deprivation quintiles. These findings give support to the idea that implementation of a UK tax intended to reduce childhood obesity may have contributed to a significant unexpected and additional public health benefit in the form of reduced hospital admissions for childhood asthma.

Characterisation of the Cinnamomumparthenoxylon (Jack) Meisn (Lauraceae) transcriptome using Illumina paired-end sequencing and EST-SSR markers development for population genetics.

Cinnamomumparthenoxylon is an endemic and endangered species with significant economic and ecological value in Vietnam. A better understanding of the genetic architecture of the species will be useful when planning management and conservation. We aimed to characterize the transcriptome of C.parthenoxylon, develop novel molecular markers, and assess the genetic variability of the species. First, transcriptome sequencing of five trees (C.parthenoxylon) based on root, leaf, and stem tissues was performed for functional annotation analysis and development of novel molecular markers. The transcriptomes of C.parthenoxylon were analyzed via an Illumina HiSeqTM 4000 sequencing system. A total of 27,363,199 bases were generated for C.parthenoxylon. De novo assembly indicated that a total of 160,435 unigenes were generated (average length = 548.954 bp). The 51,691 unigenes were compared against different databases, i.e. COG, GO, KEGG, KOG, Pfam, Swiss-Prot, and NR for functional annotation. Furthermore, a total of 12,849 EST-SSRs were identified. Of the 134 primer pairs, 54 were randomly selected for testing, with 15 successfully amplified across nine populations of C.parthenoxylon. We uncovered medium levels of genetic diversity (PIC = 0.52, Na = 3.29, Ne = 2.18, P = 94.07%, Ho = 0.56 and He = 0.47) within the studied populations. The molecular variance was 10% among populations and low genetic differentiation (Fst = 0.06) indicated low gene flow (Nm = 2.16). A reduction in the population size of C.parthenoxylon was detected using BOTTLENECK (VP population). The structure analysis suggested two optimal genetic clusters related to gene flow among the populations. Analysis of molecular variance (AMOVA) revealed higher genetic variation within populations (90%) than among populations (10%). The UPGMA approach and DAPC divided the nine populations into three main clusters. Our findings revealed a significant fraction of the transcriptome sequences and these newlydeveloped novel EST-SSR markers are a very efficient tool for germplasm evaluation, genetic diversity and molecular marker-assisted selection in C.parthenoxylon. This study provides comprehensive genetic resources for the breeding and conservation of different varieties of C.parthenoxylon.

The recent advances in the approach of artificial intelligence (AI) towards drug discovery.

Artificial intelligence (AI) has recently emerged as a unique developmental influence that is playing an important role in the development of medicine. The AI medium is showing the potential in unprecedented advancements in truth and efficiency. The intersection of AI has the potential to revolutionize drug discovery. However, AI also has limitations and experts should be aware of these data access and ethical issues. The use of AI techniques for drug discovery applications has increased considerably over the past few years, including combinatorial QSAR and QSPR, virtual screening, and denovo drug design. The purpose of this survey is to give a general overview of drug discovery based on artificial intelligence, and associated applications. We also highlighted the gaps present in the traditional method for drug designing. In addition, potential strategies and approaches to overcome current challenges are discussed to address the constraints of AI within this field. We hope that this survey plays a comprehensive role in understanding the potential of AI in drug discovery.

Systematic Analysis of Biological Processes Reveals Gene Co-expression Modules Driving Pathway Dysregulation in Alzheimer's Disease.

Alzheimer's disease (AD) manifests as a complex systems pathology with intricate interplay among various genes and biological processes. Traditional differential gene expression (DEG) analysis, while commonly employed to characterize AD-driven perturbations, does not sufficiently capture the full spectrum of underlying biological processes. Utilizing single-nucleus RNA-sequencing data from postmortem brain samples across key regions-middle temporal gyrus, superior frontal gyrus, and entorhinal cortex-we provide a comprehensive systematic analysis of disrupted processes in AD. We go beyond the DEG-centric analysis by integrating pathway activity analysis with weighted gene co-expression patterns to comprehensively map gene interconnectivity, identifying region- and cell-type-specific drivers of biological processes associated with AD. Our analysis reveals profound modular heterogeneity in neurons and glia as well as extensive AD-related functional disruptions. Co-expression networks highlighted the extended involvement of astrocytes and microglia in biological processes beyond neuroinflammation, such as calcium homeostasis, glutamate regulation, lipid metabolism, vesicle-mediated transport, and TOR signaling. We find limited representation of DEGs within dysregulated pathways across neurons and glial cells, suggesting that differential gene expression alone may not adequately represent the disease complexity. Further dissection of inferred gene modules revealed distinct dynamics of hub DEGs in neurons versus glia, suggesting that DEGs exert more impact on neurons compared to glial cells in driving modular dysregulations underlying perturbed biological processes. Interestingly, we observe an overall downregulation of astrocyte and microglia modules across all brain regions in AD, indicating a prevailing trend of functional repression in glial cells across these regions. Notable genes from the CALM and HSP90 families emerged as hub genes across neuronal modules in all brain regions, suggesting conserved roles as drivers of synaptic dysfunction in AD. Our findings demonstrate the importance of an integrated, systems-oriented approach combining pathway and network analysis to comprehensively understand the cell-type-specific roles of genes in AD-related biological processes.