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Navigated repetitive transcranial magnetic stimulation for post-stroke recovery: A systematic review and meta-analysis of randomized controlled trials.

Repetitive transcranial magnetic stimulation (rTMS) is a subcategory of non-invasive brain stimulation (NIBS), used to modulate brain plasticity and improve post-stroke recovery. Neuronavigation is used to improve the accuracy of stimulation with the aim of achieving a superior clinical outcome than with conventional targeting. The objective of this review is to evaluate the efficacy of navigated rTMS in subacute and chronic stroke patients in comparison to sham stimulation. We conducted a systematic-review and meta-analysis of randomized controlled trials (RCTs) identified from Pubmed, Scopus and Cochrane CENTRAL. Trials employing neuronavigated rTMS were included of these five types; high and low frequency rTMS, intermittent and continuous theta-burst stimulation (TBS) and Hebbian-type stimulation. 13 RCTs were included after a screening of 1900 studies. 606 patients receiving either active (n = 360) or sham stimulation (n = 246) were assessed. The pooled standardized mean difference (SMD) favored rTMS over sham SMD = 0.4 (95 %CI: 0.11-0.69), with moderate heterogeneity I2 = 55 %. Among stimulation modalities, continuous TBS showed the largest pooled effect. rTMS was also associated with significant improvements in disability-related outcomes, SMD = 0.61 (95 % CI 0.14-1.08). Navigated rTMS is associated with modest but significant improvements in motor and disability outcomes in subacute and chronic stroke. Large comparative trials are required to clarify the potential added value over conventional targeting approaches.

Humans

Metagenome-scale modeling to assess microbiome metabolic complementarity for precision microbiota transplantation therapies.

Fecal microbiota transplantation (FMT) holds therapeutic promise beyond recurrent Clostridioides difficile infection, but clinical outcomes remain unpredictable and donor-selection strategies remain limited, in part because the role of donor‒recipient metabolic interactions in shaping the post-FMT community remains poorly understood. Here, we leverage metagenome-scale metabolic modeling to quantify metabolic niche complementarity between donor and recipient microbiomes and predict post-FMT community composition. Using MICOM-derived metabolic models, we show that donor genomes whose metabolic flux profiles are more dissimilar from the recipient community colonize at significantly higher rates in a murine FMT model. In a human IBS trial, the same metric predicted post-FMT community composition via leave-one-out cross-validation and captured known disease-associated alterations in short-chain fatty acid, sulfur, and gas metabolism. We then performed 2,548 in silico FMT simulations between IBS-D/M patients and donors from the OpenBiome biobank to evaluate personalized donor screening, identifying super-donors characterized by high taxonomic diversity, broad metabolic niche coverage, and community interaction networks dominated by cross-feeding rather than competition. Together, these results support metabolic niche complementarity as a potential determinant of post-FMT community composition and provide a mechanistic basis for evaluating donor-recipient metabolic compatibility. This framework offers a scalable approach for generating testable hypotheses for personalized donor selection.

Fecal Microbiota Transplantation

An automated geometric modeling framework in GATE for the design and optimization of high-sensitivity converging-beam SPECT collimators.

Objective.The trade-off between detection sensitivity and spatial resolution is a fundamental challenge in designing organ-dedicated Single-photon emission computed tomography (SPECT) collimators. While converging-hole geometries offer a solution, their optimization is often hindered by the lack of flexible computational tools capable of modeling large-scale, non-parallel hole arrays. This study aims to develop an automated geometric modeling framework to facilitate the design and evaluation of complex converging- and diverging-hole collimators within standard Monte Carlo environments.Approach.We developed a specialized modeling framework by implementing custom C++ classes and a vector-based alignment algorithm within GATE. This platform enables automated, orientation-consistent construction of large-scale converging arrays not natively supported by standard implementations. A high-sensitivity pure cone-beam collimator (CBC) was designed using this framework. The evaluation used hot-rod, disc, and Jaszczak phantoms for physical characterization, while XCAT and dedicated brain models were employed for clinical tasks, including cardiac, brain perfusion, and DaTscan SPECT simulations.Main results.The CBC achieved a nearly fourfold sensitivity increase compared to a conventional low-energy high-resolution parallel-hole collimator at a 20 cm radius of rotation, while maintaining comparable spatial resolution. Despite a 52.3% field of view reduction, the CBC yielded a 2.2-fold noise reduction (CV: 11.7% vs 25.9%) and mitigated partial volume effects via geometric magnification. XCAT and brain phantom simulations confirmed enhanced anatomical definition and contrast recovery in cardiac, perfusion, and DaTscan tasks.Significance.This work provides an efficient computational tool for rapid design space exploration of advanced collimator geometries. The results demonstrate that the proposed CBC design offers a significant sensitivity advantage, making it highly suitable for high-performance, small-volume clinical applications such as brain and cardiac molecular imaging.

Tomography, Emission-Computed, Single-Photon

Discovery and characterization of multifunctional bioactive peptides from Alaska Pollock (Gadus chalcogrammus) milt: hybrid in silico, in vitro, and proteomic approaches.

The growing demand for multifunctional bioactive peptides has sparked interest in underutilized marine by-products as sustainable bioresources. This study explored Alaska Pollock (Gadus chalcogrammus) milt protein as a novel source of peptides with anti-inflammatory, anti-hypertensive, and anti-diabetic effects. Protein composition was analyzed via LC-MS, followed by in silico digestion and bioactivity prediction. Molecular docking identified peptides targeting DPP-IV, α-glucosidase, ACE, GLP-1 receptor, COX-2, MuRF1, and the 20S proteasome. Among the candidates, a promising peptide (CLPPH) was synthesized and validated in vitro, demonstrating inhibitory effects on nitric oxide production, DPP-IV, ACE, and α-glucosidase. These results highlight CLPPH's potential as a multifunctional bioactive peptide and support the valorization of Alaska Pollock milt as a sustainable source for functional foods and nutraceutical applications.

Animals

Effectiveness of psychosocial and lifestyle interventions in promoting behaviour change and improving cognitive outcomes in older people with memory concerns: A systematic review.

BACKGROUND: Older adults with mild cognitive impairment or subjective cognitive decline have a greater dementia risk, particularly those from minority ethnic and socioeconomically disadvantaged backgrounds. Psychosocial and lifestyle interventions targeting modifiable risk factors offer hope for reducing risk, yet behavioural mechanisms remain unclear. This systematic review examines these mechanisms and associated outcomes. METHOD: We searched PubMed, Embase (Ovid), PsycINFO (Ovid), Web of Science, and Scopus for randomised control trials testing interventions that aimed to improve lifestyle and cognition in older adults with memory concerns. We explored behavioural mechanisms using the COM-B model and synthesised intervention effectiveness, overall and within underserved groups. We prioritised lower risk of bias studies. RESULTS: 26 studies described 23 randomised controlled trials (14 multidomain, 9 single domain interventions). Certainty of evidence that behaviour change was associated with cognition was low. Moderate-certainty evidence indicated that interventions providing a socially supportive environment and combining nutritional education and counselling for 6 + months improved diet. Physical activity improved primarily in interventions incorporating education, structured training, and enablement strategies (e.g., tailored programmes, providing tools). Interventions simultaneously targeting capability, opportunity and motivation showed greater overall effectiveness. Few studies recorded ethnicity (13%) or sociodemographic status (9%), and none explored their impact. CONCLUSIONS: Non-pharmacological interventions can help this population improve their lifestyles if they feel capable, equipped and motivated, highlighting the value of careful design and implementation. There is scarce evidence on how these interventions work for underserved populations. Future research should explore this to inform tailored interventions and develop equitable dementia prevention strategies.

Humans

Family-Wise Error Rate Control in Clinical Trials With Overlapping Populations.

We consider clinical trials with multiple, overlapping patient populations that test multiple treatment policies specifically tailored to these populations. Such designs may lead to multiplicity issues, as false statements will affect several populations. For type I error control, often the family-wise error rate (FWER) is controlled, which is the probability to reject at least one true null hypothesis. If the joint distribution of the test statistics is known, the FWER level can be exhausted by determining critical values or adjusted-levels. The adjustment is typically done under the common ANOVA assumptions. However, the performed tests are then only valid under the rather strong assumption of homogeneous null effects, that is, when the null hypothesis applies to all subpopulations and their intersections. We show that under cancelling null effects, when heterogeneous effects cancel out in some or all subpopulations, this procedure does not provide FWER control. We also suggest different alternatives and compare them in terms of FWER control and their power.

Humans

Modelling the effects of biological intervention in a dynamical gene network.

Cellular response to environmental and internal signals can be modeled by dynamical gene regulatory networks (GRN). In the literature, three main classes of gene network models can be distinguished: (1) non-quantitative (or data-based) models which do not describe the probability distribution of gene expressions; (2) quantitative models which fully describe the probability distribution of all genes co-expression; and (3) mechanistic models which allow for a causal interpretation of gene interactions. We propose two rigorous frameworks to model gene alteration in a dynamical GRN, depending on whether the network model is quantitative or mechanistic. We explain how these models can be used for design of experiment, or, if additional alteration data are available, for validation purposes or to improve the parameter estimation of the original model. We apply these methods to the Gaussian graphical model, which is quantitative but non-mechanistic, and to mechanistic models of Bayesian networks and penalized linear regression.

Gene Regulatory Networks

Space to grieve and grow: A systematic review of psychosocial interventions for people newly diagnosed with multiple sclerosis.

OBJECTIVE: This systematic review synthesized evidence from intervention studies published over the past 25 years that aimed to improve coping and psychosocial well-being among individuals early in the multiple sclerosis (MS) disease course. The goal was to evaluate intervention characteristics, theoretical foundations, and psychosocial outcomes, and to identify gaps for future research. METHODS: Following PRISMA guidelines, a comprehensive search was conducted across PubMed, CINAHL, PsycINFO, and Web of Science (2000-2025). Eligible studies included quantitative or mixed-methods interventions that addressed coping or psychosocial well-being among adults newly diagnosed with MS. Data extraction and quality assessment were completed independently by multiple reviewers using the Joanna Briggs Institute Critical Appraisal Tools. RESULTS: Seven studies (n = 345) met inclusion criteria, representing cognitive-behavioral therapy, mindfulness, acceptance-based, and nurse- or peer-delivered interventions. The interval between diagnosis and intervention enrollment ranged from 14 days to >4 years, suggesting different phases of adjustment. All interventions produced significant short-term improvements in at least one psychosocial domain (e.g., anxiety, depression, stress, coping, or illness acceptance). However, sustained effects beyond 6-12 months were inconsistent. Common mechanisms across interventions included enhancing self-efficacy, stress management, and adaptive coping. CONCLUSIONS: The available evidence suggests that brief psychosocial interventions for adults in the early years after MS diagnosis are feasible and may provide short-term benefits for selected psychosocial outcomes. However, the evidence base remains limited, heterogeneous, and preliminary. Future studies should more clearly define diagnosis timing, use adequately powered designs and longer follow-up, and examine mechanisms of change.

Humans

Penalized Cumulative Probability Model for a Continuous Outcome Subject to Detection Limits.

Mixed-type outcome data occur when the outcome variable's distribution is a mixture of both continuous and discrete ordinal variables. Such mixed-type outcomes are common in biomedical, psychological, and the health sciences, particularly for variables having either a detection or quantitation limit. When interest lies in identifying a combination of genomic features associated with a mixed-type outcome, any method used would require a variable selection strategy for high-dimensional data. Unfortunately, few variable selection methods exist for modeling a mixed-type outcome when the covariate space is high dimensional. This study develops a high-dimensional penalized cumulative probability model (CPM), to allow for the identification of genomic features associated with mixed-type outcome of interest. We demonstrated how such model may be estimated using the iterative penalization procedure-the generalized monotone incremental forward stagewise (GMIFS) algorithm. The Model-X knockoffs procedure was combined with the estimation algorithm to control the false discovery rates (FDR) when performing variable selection. Through extensive simulation studies, our penalized CPM was shown to outperform alternative methods in terms of controlled variable selection performance by achieving high statistical power with the FDR being controlled at the target level. We demonstrate the utility of our method by applying it to predict estimated glomeruli filtration rate (eGFR) in kidney transplant recipients at 24 months post-transplant using baseline gene expression data as predictors. Our CPM model identified five genes associated with this mixed-type outcome which have important links to renal disease, which may provide prognostic guidance for kidney transplantation recipients.

Models, Statistical

How do we counsel patients on short- and long-term complications after hypospadias repair? - A survey study.

INTRODUCTION: Hypospadias correction remains one of the most performed pediatric urologic procedures, affecting up to 1/150 males born in the United States. Current studies suggest that surgical counseling has a significant impact on shared decision making, decisional regret, and long-term follow-up. However, no set paradigm currently exists for long-term follow-up or counseling. We sought to obtain consensus from established pediatric urologists the optimal content and potential short, intermediate, and long-term complications to be considered when counseling patients and parents of patients with hypospadias. METHODS: We conducted an IRB-approved survey study, which sampled the responses of Pediatric Urologists from National and International listservs. A google scholar search was performed using key words including "hypospadias" and "long-term complications." Descriptions of pertinent short, intermediate and long-term complications were identified and compiled from existing patient handouts. Survey items were then developed asking respondents to rate proposed descriptions, provide potential edits, and describe their overall approach to counseling. RESULTS: A total of 290 surgeons were contacted with 120 (41 %) responding. In total, 89 respondents (74 %) identified as male and 105 (88 %) had undergone a pediatric urology fellowship. Most surgeons described a reliance on verbal counseling (95 %) with the assistance of hand-drawn diagrams (75 %) to explain long-term care, rather than electronic or audiovisual materials (3-12 %). Of note, fewer surgeons endorsed routine discussion of long-term complications (Range 29.2 %-50.8 %) than shorter-term complications (56.7 %-89.2 %). On a Likert scale, physicians reported that they were mostly satisfied (72 %) with their current approaches to counseling. DISCUSSION: Perioperative counseling has an important yet often overlooked role in surgical care. The aim of this study was to better understand current counseling practices in pediatric hypospadias to identify gaps in urologic care and areas for improvement as one of the most common conditions treated by pediatric urologists. Our results suggest that surgeons who perform hypospadias repairs have potential to include more comprehensive discussion during post-operative follow-up. We proposed a preliminary counselling guide for these concerns which incorporates language from the most commonly selected complication description by survey respondents. Future studies will involve expert consensus and patient input to confirm the adequacy of the content, the method of delivery, content appearance, and accommodations for health literacy. Limitations of the study include small sample size and response bias. The results are reflective of the summed responses of participants and are not reflective of individual providers or practices. Importantly, this study omits the input of other advanced practice providers (nurse practitioners, physician assistants, etc.), nurses, and ancillary staff who are also crucial to hypospadias care. The proposed counseling guide represents a first attempt at creating standardization of hypospadias counseling. CONCLUSION: Surgeons who perform hypospadias repair do not routinely discuss long-term complications after repair, though are overall satisfied with their counseling practices. Better tools, such as improved multimodal counseling guides, could be used to deliver this counseling efficiently and accurately to ensure patients receive optimal long-term care. Future studies will focus on developing educational materials for short, intermediate, and long-term counseling on complications after hypospadias repair with input from patients and clinicians.

Humans

Measuring Coping Strategies in Daily Life: A Systematic Review of Experience Sampling Methodology and Daily Diary Studies.

Advances in daily diary methods and experience sampling method (ESM) have improved the study of coping strategies in daily life and their role in shaping health and well-being. In this review, we examine study designs, measurement approaches, and analytical practices used to investigate coping in natural contexts. We performed a systematic review of studies published before 5 December 2025 that used daily diary or ESM to measure coping strategies over multiple days or moments. Studies were examined with regard to sampling schemes, assessment frequency and duration, measurement of coping strategies, incorporation of stressor appraisals, and analytic techniques used to model coping processes. Fifty-five studies met the inclusion criteria. Results indicated that 80% employed end-of-day diary designs, generally lasting 1-3 weeks, whereas higher-frequency ESM protocols were less common and ranged 2-14 days. Coping strategies were often assessed using abbreviated or single-item measures, frequently adapted from established questionnaires. Many studies incorporated appraisals such as perceived stressor intensity or controllability, enabling tests of coping flexibility. Multilevel modelling was the dominant analytic approach, allowing researchers to distinguish within-person dynamics from between-person differences. However, analyses were predominantly concurrent, and temporally ordered models remained comparatively rare. Overall, the literature demonstrates substantial progress in capturing coping in everyday contexts, yet heterogeneity in measurement and limited use of temporal modelling constrain cumulative knowledge about the temporal links between coping and psychological and physiological health outcomes. Future research would benefit from greater alignment between theoretical assumptions, assessment strategies, and analytic methods.

Humans

ReMeDy: A Flexible Statistical Framework for Region-Based Detection of DNA Methylation Dysregulation.

Region-based epigenome-wide association studies have demonstrated improved statistical power and biological interpretability compared with probe-wise analyses of DNA methylation data. However, most existing region-based methods characterize methylation dysregulation primarily through changes in mean methylation levels associated with a phenotype of interest. Substantial evidence indicates that phenotype-associated methylation alterations may also manifest through changes in methylation variability or through joint shifts in mean and variability. Despite this, no existing statistical framework jointly models mean-variance methylation changes in a region-based manner. We propose ReMeDy, a flexible statistical framework that uses a hierarchical likelihood approach within a generalized linear model setting to identify differentially methylated regions, variably methylated regions, and regions exhibiting joint differential and variable methylation at a genome-wide scale. Unlike existing models, ReMeDy operates directly on biologically defined co-methylated regions, allowing it to naturally capture spatial correlation inherent in DNA methylation array data, while avoiding reliance on heuristic, user-defined tuning parameters such as smoothing spans and kernel bandwidths that can substantially influence results and introduce subjectivity. Through extensive simulation studies and comprehensive benchmarking against popular models, we demonstrate that ReMeDy maintains false discovery and Type-I error rates at nominal levels while achieving consistently higher statistical power across a wide range of realistic scenarios. Application to population-level DNA methylation data further shows that ReMeDy identifies biologically meaningful regions and pathways implicated in complex human diseases that are not captured by conventional mean-based analyses alone. ReMeDy is implemented as an open-source R package and is freely available at https://github.com/SChatLab/ReMeDy.

DNA Methylation

Genomic and Molecular Interaction Analysis of NodD1 in a Novel Bradyrhizobium yuanmingense sp. B64 Isolate for Nodulation and Symbiosis of Legume Plants.

Rhizobial bacteria are known for their ability to fix nitrogen for leguminous plants and their essential function for sustainable agriculture. This study characterizes the taxonomic status and functional potential of the Bradyrhizobium B64 isolate using integrated genomic and molecular approaches. The whole genome of the B64 isolate was sequenced via Illumina paired-end technology. Species delimitation was performed using average nucleotide identity (ANI) and digital DNA-DNA Hybridization (dDDH). The NodD1 protein structure was modeled using AlphaFold3 and validated by Ramachandran plot analysis. Molecular docking was then conducted to evaluate interactions between NodD1 and four signaling flavonoids: Apigenin, Daidzein, Genistein, and Naringenin. Genomic analysis revealed a maximum ANI of 94.4% and dDDH values between 51.4 and 62.4%. Since these values fall below the standard prokaryotic thresholds (ANI&#x2009;<&#x2009;95%; dDDH&#x2009;<&#x2009;70%), the B64 isolate is identified as a novel species. Physiological assays confirmed nitrogen fixation (1.97 ppm), IAA production (3.67 ppm), and phosphate solubilization (26.10 ppm). Structural validation showed 100% of NodD1 residues in allowed regions, ensuring high model reliability. Docking simulations demonstrated strong binding affinities across all flavonoids, with binding free energies ranging from -&#x2009;8.8 to -&#x2009;9.0&#xa0;kcal/mol. Daidzein exhibited the highest thermodynamic stability (-&#x2009;9.0&#xa0;kcal/mol), whereas apigenin showed the most extensive residue interaction network. The B64 isolate is a novel Bradyrhizobium species with a high symbiotic capacity. The stable NodD1-flavonoid interactions provide a molecular basis for efficient nodulation, positioning B64 as a promising candidate for developing lipo-chitooligosaccharide (LCO)-based biofertilizers.

Bradyrhizobium

An integrated multiscale air quality modelling framework for industrial park pollution: Linking local emissions to regional transport.

Capturing the spatiotemporal distribution of pollutants in industrial parks remains challenging for regional air quality models because of their coarse resolution (3 km), resulting in uncertainties in local emission quantification. To address this, we developed the Integrated Multiscale Air Quality Modelling System for Industry (IAQMS-Industry), coupling the regional Nested Air Quality Prediction Modelling System (NAQPMS) with a city-scale chemical transport model. This framework integrates point-source locations and Gaussian plume dispersion to simulate particulate matter with a diameter smaller than 2.5 micrometres (PM2.5) at 100 m resolution. Applied to the Beijing Yi Zhuang and Tangshan industrial parks and evaluated against observations. The coupled model achieved a normalized mean bias (NMB) ranging from 3.1 % to 6.2 %, improving upon NAQPMS (-16.9 % to -7.7 %). Spatial analysis revealed that coarse regional grids underestimated the PM2.5&#x200b; concentrations at industrial sites by smoothing gradients, whereas IAQMS-Industry successfully resolved spatial patterns. Industrial point emissions accounted for 22.9 %-26.4 % of PM2.5 in the coupled model, which was significantly greater than the regional model estimates of 1.6 %-13.7 %. These findings indicate that regional models overestimate pollutant dispersion processes in industrial parks while underestimating local industrial impacts. By explicitly resolving point-source dynamics and linking them to regional transport, IAQMS-Industry provides a robust tool for designing targeted emission controls in industrial cities and balancing local air quality improvements with minimized regional pollution outflow. This study underscores the necessity of multiscale modelling for accurate source apportionment and informed environmental governance in industrial zones.

Air Pollution

The influence of organizational culture on medication safety practices and associated risk factors in the community setting: A systematic review.

BACKGROUND: Increasing attention has been given to the role of organizational culture in influencing medication safety practices across healthcare settings. The lack of widely accepted standardized instrumentation makes operational measurement of organizational culture and medication safety challenging. The purpose of this systematic review was to examine the impact of organizational culture on medication safety within community healthcare settings. METHODS: MEDLINE, CINAHL, Scopus, and Nursing & Allied Health were searched in August 2025 using keywords, subject terms, field codes, and Boolean operators to identify papers relevant to the review question; bibliographies of included studies were also reviewed. Screening and full-text review were completed independently by two reviewers with a third to adjudicate conflicts. The Critical Appraisal Skills Programme was used for quality assessment. The PRISMA statement guided the development and implementation of the review. RESULTS: Thirteen articles were included representing various community settings. Most studies reported on untoward medication events, but few measured systematically collected safety data before and after an intervention. Organizational culture was seldom defined or operationalized. Most studies were methodologically sound, but the overall level of evidence was weak to moderate. CONCLUSION: Organizational culture influences medication safety through aspects such as communication channels, teamwork, training, and an environment that allows error and near-miss reporting. Few studies explicitly evaluate the causal impact of culture interventions on measurable medication safety outcomes in community healthcare settings. Further research should incorporate standardized measurement tools and intervention-based, pre-post designs to better understand how organizational culture influences medication safety in community healthcare settings.

Organizational Culture

Discovery of NAT-6-321056 as a novel modulator of VEGFR2 signaling to suppress tumor angiogenesis.

Vascular endothelial growth factor receptor 2 (VEGFR2) is a master regulator of angiogenesis and cancer progression. However, current VEGFR2 modulators face significant challenges, including off-target toxicity and acquired resistance, underscoring the urgent need for novel therapeutic agents with improved efficacy and safety profiles. Here, we reported that virtual screening of 39,442 natural products from the ZINC natural products-derived library, coupled with molecular docking and molecular dynamics (MD) simulations to evaluate the binding stability of candidate compounds, identified NAT-6-321056 as a highly promising modulator of VEGFR2 signaling. Biological evaluations demonstrated that NAT-6-321056 exerted potent inhibition on the growth of a broad spectrum of cancer cells, including both solid tumors and hematological malignancies. In EA.hy 926 endothelial cells and SK-N-DZ neuroblast cells, the compound significantly suppressed proliferation, migration, and invasion. Microscale thermophoresis (MST) confirmed direct binding of NAT-6-321056 to VEGFR2 with favorable affinity. Kinase profiling against a panel of 33 kinases indicated that NAT-6-321056 exhibited a multi-kinase modulation profile. Mechanistic studies revealed that NAT-6-321056 suppressed the expression of hypoxia-inducible factor 1-alpha (HIF-1&#x3b1;) and was associated with reduced VEGFR2 phosphorylation and attenuation of the downstream ERK/JNK/AKT signaling pathways. Moreover, NAT-6-321056 exhibited robust in vivo anti-angiogenic effects in both the chick chorioallantoic membrane (CAM) assay and transgenic zebrafish vascular fluorescence imaging models. Computational absorption, distribution, metabolism, excretion, and toxicity (ADMET) prediction suggested acceptable drug-like properties. Collectively, these findings demonstrated that NAT-6-321056 is a promising modulator of VEGFR2 signaling with potent anti-angiogenic activity and represents a viable candidate for cancer therapy.

Vascular Endothelial Growth Factor Receptor-2

Effects of intensive lifestyle interventions with calorie-carbohydrate-restricted diet versus time-restricted eating on appetite and binge eating in type 2 diabetes: A randomized controlled trial.

The impact of intensive lifestyle interventions on appetite regulation and binge eating in individuals with type 2 diabetes (T2D) remains unclear. This study evaluated the effects of combined lifestyle interventions on appetite responses and binge eating in overweight or obese adults with T2D. In a randomized trial, 120 participants with T2D were allocated to three groups (n&#xa0;=&#xa0;40 each): (1) Calorie-carbohydrate restriction (CCR), (2) Time-restricted eating with CCR (TRE&#xa0;+&#xa0;CCR), or (3) Control. Intervention groups received structured exercise and behavioral education based on the Information-Motivation-Behavioral Skills model. Appetite perceptions (hunger, satiety, desire to eat, and prospective food consumption) and binge eating (Binge Eating Scale; BES and objective binge episodes) were evaluated at baseline, week 12, and week 24 using linear mixed models. Both CCR and TRE&#xa0;+&#xa0;CCR significantly improved subjective appetite compared with the control group at 12 and 24 weeks (all p&#xa0;<&#xa0;0.01). At 24 weeks, hunger decreased by -24.1&#x202f;mm (95% CI: -35.8, -12.5) in the CCR group and -32.7&#x202f;mm (95% CI: -44.2, -21.3) in the TRE&#xa0;+&#xa0;CCR group. Satiety also increased by 21.7&#x202f;mm (95% CI: 9.46, 33.9) and 29.4&#x202f;mm (95% CI: 17.4, 41.4), respectively. Significant reductions were observed for desire to eat and prospective food consumption. In contrast, changes in BES and objective binge episodes were not significantly different between groups at any time point. No significant differences were detected between the CCR and the TRE&#xa0;+&#xa0;CCR groups. Intensive lifestyle interventions incorporating CCR or TRE&#xa0;+&#xa0;CCR effectively reduced appetite in adults with T2D but did not significantly affect binge eating. Future research should target individuals with higher baseline BES scores to clarify potential benefits for binge eating behavior.

Humans

Epigenetics and In Silico Transcriptome Analysis of Pediatric Acute Myeloid Leukemia.

Pediatric acute myeloid leukemia (AML) is a heterogeneous hematologic malignancy that accounts for about 15%-20% of childhood leukemias. Despite therapeutic advances, relapses remain common, and survival for high-risk patients is below 60%. Unlike adult AML, pediatric AML displays distinct genetic mutations, including FLT3-ITD, NPM1, KMT2A rearrangements, and core-binding factors (CBF) fusions, as well as extensive epigenetic dysregulation. Aberrant DNA methylation, histone modifications, and altered non-coding RNA expressions disrupt hematopoietic differentiation and activate oncogenic transcriptional networks. Recent advances in silico transcriptomic analysis have transformed the study of pediatric AML by integrating gene expression and epigenetic data to identify molecular drivers and regulatory networks. Computational RNA-seq pipelines and pathway analyses have highlighted key epigenetic regulators, including DNMT3A, TET2, and HDACs, as potential therapeutic targets. Multi-omics approaches combining transcriptomic, methylomic, and chromatin accessibility data are increasingly used to define biomarkers for diagnosis, prognosis, and therapeutic response. This review provides a comprehensive overview of the molecular and epigenetic landscape of pediatric AML, emphasizing the power of in silico transcriptome analysis to uncover disease mechanisms, refine patient stratification, and guide the development of precision-based epigenetic therapies aimed at improving long-term outcomes in children with AML.

Humans