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PubMed2026

Optimising Exercise Prescription: A Meta-Analysis Examining the Dose Response of Exercise Duration on Cardiorespiratory Fitness Following HIIT and MICT.

BACKGROUND: High-intensity interval training (HIIT) is often promoted as a time-efficient alternative to moderate-intensity continuous training (MICT) for improving cardiorespiratory fitness, yet the duration of HIIT sessions varies considerably across studies. OBJECTIVE: We aimed to characterise the dose-response relationship between exercise session duration and the improvement in cardiorespiratory fitness for HIIT and MICT. METHODS: A dose-response meta-analysis of randomised controlled trials comparing exercise duration in HIIT and MICT, following Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) guidelines and registered in PROSPERO (CRD42022335590). Effect sizes were calculated using a random-effects meta-analysis. The primary outcome was maximal oxygen uptake (VO2max). Secondary outcomes included blood pressure, lipid profiles, glucose metabolism markers and body composition measures. A one-stage random-effects dose-response meta-analysis was performed to examine the relationship between exercise duration and adaptations. We searched PubMed and Google Scholar; eligibility criteria for selecting studies were randomised controlled trials in humans, published in English and exercise interventions lasting at least 4 weeks. RESULTS: We identified 69 randomised controlled trials (2387 participants). High-intensity interval training elicited greater improvements in VO2max than MICT (d = 0.38, 95% confidence interval 0.27-0.49, p < 0.001). High-intensity interval training demonstrated a non-linear dose-response relationship between exercise session duration and VO2max, with 80% of maximal effect (changes in VO2max = 3.45 mL/kg/min) achieved with only ~11 min/session (95% confidence interval 9.5-40.2). Moderate-intensity interval training showed a linear dose-response relationship between exercise session duration and VO2max, requiring ~52 min/session to achieve 80% of the maximal observed effect (95% confidence interval 30.4-55.8). The dose-response relationship was consistent across populations. High-intensity interval training and MICT had comparable effects in improving cardiometabolic risk factors. CONCLUSIONS: High-intensity interval training demonstrated a non-linear dose response, with 80% of maximal effect on VO2max in ~11 min/session, whilst MICT required four to five times longer to reach similar responses. The different types of training had comparable effects on cardiometabolic risk factors.

Journal Article↗

PubMed2026

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↗

PubMed2026

Long-term heat exposure reshapes muscle molecular regulation and enhances thermal tolerance in Clarias fuscus.

Rapid fluctuations in water temperature driven by global warming have become a major abiotic stressor affecting muscle function in teleost fish. This study examined the effects of long-term thermal conditions on heat tolerance in Clarias fuscus. Fish were maintained for 90 days at either a normal temperature group (NT, 26 °C) or a high-temperature group (HT, 34 °C). Subsequently, muscle histology, and transcriptomic profiles were observed following acute high-temperature exposure (34 °C) and after temperature recovery (26 °C). Histological analysis showed that fish from the NT under acute high-temperature stress exhibited severe muscle damage (atrophy, myofilament disruption, and myolysis), whereas fish from the HT displayed markedly reduced lesions. RNA-seq profiling revealed 5769 differentially expressed genes (DEGs) in the NT and 3292 DEGs in the HT following acute temperature challenges. Functional enrichment indicated that, in the HT, modulation of key cell cycle regulators (e.g., ccna, ccnb, cdk1, cdk2) contributed to alleviating muscle damage caused by temperature fluctuations. In the NT, genes associated with ribosome biogenesis (e.g., nop56, riok2, riok1) were up-regulated and then down-regulated during temperature fluctuation, whereas p53 in the cell cycle pathway showed the opposite expression pattern. These findings demonstrate long-term heat exposure reshapes molecular expression and regulatory mechanisms in the muscle of C. fuscus, thereby enhancing thermal tolerance and adaptability, and providing a theoretical basis for breeding heat-resistant, high-quality aquaculture strains.

Animals↗

PubMed2026

Validated UPLC-MS/MS quantification and intracellular PK-PD Modeling of periplocin-related cardiac glycosides in H/R-injured H9c2 cells.

Reliable intracellular quantification is essential for characterizing the target-site disposition and exposure-response relationships of bioactive natural products. In this study, an ultra-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) method was developed and validated for the simultaneous determination of periplocin and four related cardiac glycoside metabolites in H9c2 cell lysates. Acceptable linearity, precision, recovery, and stability were achieved for intracellular quantification. Cells were treated with each compound at 50 μM, and intracellular concentrations and cell viability were monitored over 48 h. In hypoxia/reoxygenation (H/R) -injured cells, the time to maximum intracellular concentration was shortened for all five compounds, indicating altered cellular disposition under injury conditions. Cell viability was improved by all compounds during the observation period. Pharmacokinetic-pharmacodynamic (PK-PD) integration was performed using a sigmoid Emax model, and acceptable model fits were obtained, with Akaike information criterion (AIC) values ranging from 79.22 to 130.46. Low apparent EC50 values were estimated under this single-dose design, whereas the estimated Ke0 values suggested delayed equilibration with the effect compartment. These findings indicate that sustained cytoprotective responses can be produced by periplocin and related metabolic markers in injured cardiomyocytes. This intracellular bioanalytical strategy provides a quantitative approach for linking cellular exposure to pharmacodynamic response and may support further evaluation of periplocin-related cardiac glycosides.

Tandem Mass Spectrometry↗

PubMed2026

Perinatal depression, maternal thyroid status and fetus/infant health and development: A systematic review.

BACKGROUND: Thyroid hormones are known to influence both maternal depression and child developmental outcomes, while maternal depression independently affects child outcomes. The potential interaction between thyroid dysfunction and depression in shaping child development remains insufficiently explored. The present study addresses such interplay. METHODS: Following PRISMA 2020 and JBI guidelines, three databases were searched through December 2025 for primary studies on maternal thyroid status, perinatal depression, and child development. Risk of bias (RoB) was assessed using validated tools. Due to clinical and methodological heterogeneity, data were synthesized narratively following SWiM guidelines. RESULTS: Eleven studies were included. Beyond independent risks for preterm birth and behavioral problems, limited evidence supports a synergistic model, while most studies likely reflect the simple co-occurrence of risks. Maternal thyroid peroxidase antibodies (TPO-Ab) were associated with child externalizing problems exclusively in the presence of clinical depression. High depressive symptoms also attenuated the cognitive benefits of prenatal iodine supplementation. Thyroid status appears to function as a risk moderator rather than a mediator. However, 50% of observational studies presented high RoB, primarily due to participant attrition. CONCLUSION: Findings are still scarce to support a synergistic risk model where specific maternal thyroid parameters (i.e. thyroid autoimmunity and iodine status) may moderate the impact of depressive symptoms on child development. Despite the high RoB in half of the studies, results highlight the need for integrated screening protocols. Simultaneously assessing mental health and thyroid status may optimize risk stratification for high-risk mother-infant dyads.

Female↗

PubMed2026

Upscaling Genotyping by Amplicon Sequencing With GBAS-GUI.

Genotyping by amplicon sequencing (GBAS) is a relatively low-cost approach for generating genotypic data compared with established genomic methods, making it highly scalable and particularly suitable for large-scale genetic monitoring projects. However, most existing analytical pipelines are either marker-specific, insufficiently scalable, or lacking efficient data management systems for the long-term integration of genotypic information, limiting the full potential of GBAS. Here, we address this gap by introducing GBAS-GUI (https://github.com/sonnenbe-dot/GBAS-GUI), a pipeline capable of generating GBAS-based genotypic data for a wide variety of loci at scale. GBAS-GUI integrates a graphical user interface with multiple checkpoints to improve accessibility and robustness. It implements multiprocessing architecture and a relational database that links genotypic data with associated sample metadata to enhance scalability and data management. The pipeline further enables marker screening through automated calculation of polymorphism information content (PIC) and implements a strategy to recover homologous genotypic information from paralogous loci with non-overlapping amplicon length ranges. Using multiple empirical datasets, we demonstrate substantial improvements in processing speed, database management and handling artefacts related to co-amplification of unspecific regions and duplicates of the same genomic region. We further show that incorporating the full sequence information captured by an amplicon increases marker information content beyond what is achievable with length-based genotyping alone and expands the analytical versatility of GBAS. Overall, GBAS-GUI provides a robust, scalable and versatile framework that unlocks the potential of GBAS for large-scale population genetic and phylogeographic studies.

Genotyping Techniques↗

PubMed2026

Comparison of paralog identification methods and their impact on species tree topologies in target capture phylogenomics within the Sindora clade (Detarioideae: Leguminosae).

Target capture is a common method of generating high throughput DNA sequencing data for phylogenetic reconstruction of species relationships, for which single copy genes are usually most informative. However, a pervasive problem with target capture is that putatively single copy genes may in fact be paralogs resulting from gene duplication, which are problematic for phylogenetic inference because their evolutionary history may differ from the divergence history of species. Here, we use as a case study a target enrichment dataset of 88 species of Detarioideae (Leguminosae) with a focus on the Sindora clade to examine approaches for handling paralogs, including the built-in paralog handling functions in HybPiper and CAPTUS, plus subsequent steps using Putative Paralog Detection and the tree-based Yang & Smith orthology inference approach. We compare the paralogs flagged using these methods and verify their performance with BLAST mapping against a reference genome sequence of Sindora glabra, and then subsequently compare the species tree topologies produced across these methods. Our comparisons of paralogs flagged across the Sindora clade show that the Putative Paralog Detection pipeline was the most accurate in identifying paralogs in terms of its similarity to the BLAST mapping, followed by the built-in paralog identification function of CAPTUS. However, the results we recovered for the Detarioideae subfamily suggest that the largest differences in species tree topology resulted from the use of paralog-filtered alignments (such as with the Putative Paralog Detection pipeline and the Yang & Smith orthology inference approaches) rather than just by removing the sequences of identified paralogous genes. This was the true for HybPiper-assembled datasets but was not seen in CAPTUS-assembled datasets. In all comparisons, the topological differences caused by different paralog handling methods tended to be confined to clades where processes such as hybridisation and introgression are prevalent. Our study provides a roadmap to establish the best approach to identify, eliminate or separate paralogs in the absence of a chromosomally contiguous reference genome for a study group, and highlights the importance of careful data inspection and processing in addition to understanding the extent of paralogy and paralog characteristics (e.g. sequence divergence between copies) for their study group.

Phylogeny↗

PubMed2026

Infant Dietary Patterns and Early Childhood Weight Outcomes: A Secondary Analysis from the Starting Early Program Trial.

BACKGROUND: The Starting Early Program (StEP) promotes healthy nutrition during early life and leads to healthier child weight, but whether dietary patterns contribute to weight or mediate StEP weight outcomes has not been studied. OBJECTIVES: This secondary analysis identified infant dietary patterns in StEP, determined associations between dietary patterns and child weight outcomes, and examined whether dietary patterns mediated the relationship between StEP and child weight. METHODS: Data were from 377 mother-infant dyads in a randomized trial testing the efficacy of StEP. Dietary patterns at 10 months were identified using latent class analysis. Child weights were abstracted from medical records at 12, 24, and 36 months. Associations between infant dietary patterns and weight-for-age z-score (WFAz) and likelihood of being classified as overweight (WFA ≥85th percentile) were assessed using linear and logistic multivariable regression models. Mediation was used to assess intervention effects on WFAz via impacts on infant dietary patterns. RESULTS: Four classes of infant dietary patterns were identified: Breastfed-High variety, Formula fed-High variety, Formula fed-Low variety, and Mixed fed-Low variety. Compared to the Breastfed-High variety class, infants in the Formula fed-Low variety class had higher WFAz and were more likely to be classified as overweight at 24 and 36 months. Participation in StEP increased membership in Breastfed-High variety, which mediated the association between StEP and lower WFAz at 24 months. CONCLUSIONS: Infant dietary patterns were identified, and some were associated with child overweight. StEP was associated with a dietary pattern most consistent with guidelines, which mediated intervention effects on child weight.

Humans↗

PubMed2026

Microbial signal profiles and organism-level concordance between plasma metagenomic sequencing and blood culture in suspected bloodstream infection.

Plasma metagenomic next-generation sequencing (mNGS) and blood culture detect different components of the microbial signal and frequently produce discordant organism reports. We characterized microbial signal class, report-derived burden, organism-level concordance, and independent clinical attribution in a retrospective, single-center, episode-level cohort. Among 329 episodes with evaluable plasma mNGS reports, 315 had blood culture performed; 232 were mNGS positive/culture negative and 53 were positive by both methods. In the 232 discordant episodes, the recorded routine-care diagnosis classified 124 as bloodstream infection (BSI) and 108 as non-BSI. Nonviral signals were present in 78.2% and 42.6%, respectively (P < 0.001), and median maximum report-derived sequence counts were 98.5 and 11.5 (P < 0.001). Two laboratory physicians then independently reviewed source records using structured criteria while masked to the recorded BSI label and mNGS organism and sequence-count information. Initial agreement for the five-category BSI assessment was 97.6% (Cohen's kappa, 0.960). Within the mNGS-positive/culture-negative subgroup, adjudicated BSI likelihood showed a modest ordinal association with report burden (Spearman rho = 0.190; P = 0.004), while mNGS organisms were considered supported in 1 episode, plausible in 158, unlikely or contaminant in 72, and unresolved in 1. Among 53 dual-positive episodes, 33 (62.3%) shared at least one species, but only 5 (9.4%) had complete species-set concordance. Plasma mNGS and blood culture therefore frequently generated non-equivalent organism sets. Signal class and report burden contributed graded contextual evidence, but organism-level attribution required clinical review and orthogonal microbiology rather than binary positivity alone.

Humans↗

PubMed2026

Effects of phytosterols supplementation on hepatic lipid metabolism and metabolic outcomes in obese rodent models: a systematic review and meta-analysis.

This study aimed to synthesize and quantitatively assess the available evidence on the effects of phytosterol supplementation on hepatic lipid metabolism and obesity-related metabolic outcomes in obese rodent models, integrating biochemical, histological, and molecular evidence. A systematic search was conducted in electronic databases (PubMed, EMBASE, and Web of Science). Data on study design, population, intervention, outcomes, and risk of bias were extracted and analyzed. A quantitative meta-analysis was performed. Meta-analysis showed reductions in body weight, serum triglycerides, total cholesterol, LDL-C, VLDL-C, glucose, liver weight, hepatic cholesterol, hepatic triglycerides, and nonalcoholic fatty liver disease activity score. No significant changes were observed for adiposity index, HDL-C, insulin, or hepatic expression of PPARα, FAS, and SREBP1c. Conversely, CPT1A expression was significantly increased following PS supplementation. Subgroup analyses indicated that the beneficial effects on lipid and hepatic outcomes were generally consistent across rodent species (mice, rats, and hamsters), obesity induction models, and routes of administration, although the magnitude of responses varied between strains, with C57BL/6 mice showing more pronounced metabolic improvements. Additional analyses suggested that treatment duration and phytosterol composition may modulate specific outcomes, whereas dose-response meta-regression identified dose-dependent associations for serum and hepatic cholesterol, and PPARα expression in dietary supplementation studies. Overall, the available preclinical evidence suggests that phytosterol supplementation may improve several metabolic and hepatic outcomes in rodent models of obesity. However, the substantial heterogeneity across studies highlights the need for standardized experimental protocols and future clinical studies before these findings can be translated to human health.

Animals↗

PubMed2026

Performance comparison of rapid and native barcoding methods for Oxford Nanopore sequencing of Poliovirus Viral Protein 1 (VP1) amplicons.

Accurate and timely sequencing of poliovirus is critical for global eradication efforts, particularly for molecular epidemiology based on the typing region of the genome, viral protein 1 (VP1). While Oxford Nanopore Technologies (ONT) sequencing has expanded capabilities for poliovirus surveillance, the relative performance of different ONT library preparation methods, including ligation-based (Native Barcoding) and transposase-based (Rapid Barcoding) approaches, has not been systematically evaluated. In this study, we compared rapid barcoding and native barcoding workflows for sequencing VP1 amplicons from 17 type 2 poliovirus-positive samples, each processed in triplicate. Native barcoding generated significantly more sequencing output, producing approximately 2.3-fold greater total read yield than rapid barcoding, and demonstrated higher run-to-run reproducibility (R2 = 0.979-0.998 vs. 0.847-0.929, respectively; p < 0.001). In addition, native barcoding generated 80% of the total yield achieved by rapid barcoding within approximately 7 h, whereas rapid barcoding required approximately 40 h to reach the same output. Despite these differences, both methods produced identical VP1 consensus sequences across all samples, with comparable read quality (median per-base Q-scores of approximately Q17-Q18). Rapid barcoding provided substantial practical advantages, reducing hands-on library preparation time (55 vs. 200 min) and per-sample cost ($12.82 vs. $16.54), while simplifying workflow and reducing technical complexity. These findings indicate that sequencing yield may not be a determinant of downstream analytical outcomes for poliovirus VP1 ONT sequencing. Rapid barcoding therefore represents a cost-effective and efficient approach for routine poliovirus surveillance, whereas native barcoding remains advantageous in applications requiring rapid data generation or maximal sequencing depth.

Poliovirus↗

PubMed2025

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 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↗

PubMed2026

Simultaneous determination of imiquimod and terbinafine in skin permeation studies: Validation of a liquid chromatography method with fluorescence detection.

Chromoblastomycosis is a chronic, neglected subcutaneous mycosis posing significant therapeutic challenges. A topical strategy combining terbinafine (TBF), an antifungal, with imiquimod (IMQ), a TLR-7/8 agonist immunomodulator, has emerged a promising alternative. However, no validated analytical method is currently available to simultaneously quantify both drugs in skin, which is crucial for novel formulation development. This study reports the development and validation of a simple HPLC method with fluorescence detection (excitation 236 nm, emission 340 nm) for the simultaneous determination of TBF and IMQ extracted from porcine skin. Separation was achieved on a C8 reversed-phase column (125 × 4.0 mm, 5 μm) using a mobile phase of methanol and water (60,40, v/v), both containing 0.1% formic acid at a flow rate of 0.8 mL/min. The method showed excellent linearity (r > 0.999) over 0.01-1.0 μg/mL for IMQ and 0.1-2.0 μg/mL for TBF. Intra- and inter-day precision demonstrated coefficients of variation below 5%, and recovery rates from skin (79-105%) confirmed accuracy. Limits of detection were 0.001 μg/mL for IMQ and 0.004 μg/mL for TBF, with quantification limits of 0.02 μg/mL and 0.16 μg/mL, respectively. This selective, sensitive, and reproducible method represents a valuable analytical tool for supporting the development and quality control of topical formulations for chromoblastomycosis and other fungal skin diseases.

Animals↗

PubMed2026

Comparison of summative assessments between simulated electronic health records versus traditional paper-based patient cases: A non-inferiority randomized controlled trial.

INTRODUCTION: Electronic health records are fundamental to contemporary pharmacy practice, yet evidence supporting their use in pharmacy education is lacking. This single-center, non-inferiority randomized controlled trial with blinded outcome assessment evaluated whether delivering patient cases via a simulated academic EHR (aEHR) was non-inferior to a traditional paper-based format in student exam performance. METHODS: 53 third-year PharmD students at the University of British Columbia were randomized 1:1 to complete a mock summative examination using either the aEHR or paper-based case delivery, stratified by self-reported EHR comfort level. The primary outcome was mean written exam score (%). Non-inferiority was pre-specified at a margin of 14%. Adjusted linear regression was used for the primary analysis, with a multiple imputation sensitivity analysis. Student perceptions were explored through post-exam focus groups analyzed using inductive thematic analysis. RESULTS: 42 students (21 per group) completed the exam and were included in the primary analysis. Mean scores were 66% (SD 11) in the aEHR group and 68% (SD 10) in the paper group. The adjusted mean difference (paper minus aEHR) was -2.2% (95% CI -9.2% to +4.8%), satisfying non-inferiority but not superiority. Sensitivity analysis (n = 53) yielded consistent results (-2.3%; 95% CI -7.1% to +4.1%). Focus groups revealed initial student anxiety with the aEHR but recognized its alignment with clinical practice. DISCUSSION: These findings support the feasibility of integrating simulated EHRs into summative pharmacy assessments without compromising performance. CONCLUSION: Simulated EHRs are a non-inferior assessment medium compared with paper-based formats and represent a viable step toward technology-driven pharmacy practice environments.

Humans↗

PubMed2026

Symptom Burden After Dialysis Initiation and Its Association With Hospitalization.

RATIONALE & OBJECTIVE: Symptom burden is distressing for patients living with kidney failure, but there is limited information about the combination of symptoms and individual symptoms that most strongly predict health care use in this group. We classified and summarized patients' symptom burden levels and changes over time and estimated associations with hospitalizations among patients receiving incident hemodialysis. STUDY DESIGN: Longitudinal, observational. SETTING & PARTICIPANTS: Individuals initiating dialysis in the United States. EXPOSURE: Kidney Disease Quality of Life-36 (KDQOL-36) measure. OUTCOME: First hospitalization after dialysis initiation. ANALYTICAL APPROACH: Latent transition analysis was used to identify symptom burden classes using the KDQOL-36. Cox regression models were used to assess whether individual KDQOL-36 symptoms and symptom burden groups were associated with hospitalization risk after dialysis initiation, independent of demographics and comorbid conditions. RESULTS: 1,818 participants were Black (29%), were aged >65 years (59%), were women (42%), had diabetes (49%), and had hypertension (74%). Latent transition analysis identified the following 3 symptom burden groups: (1) low (low severity of all symptoms and kidney disease impacts), (2) moderate (high physical health impact and overall burden of kidney disease), and (3) high (high levels of all symptoms and kidney disease impact). After adjusting for patient characteristics, all KDQOL-36 scales except the Effects of Kidney Disease scale were associated with a higher hazard of hospitalization. Using the symptom burden groups, a high symptom burden was associated with a 20% increase in the hazard of hospitalization. A 1-category worsening in pain interference and in fatigue was associated with a 12% and an 8% increased hazard of hospitalization, respectively. LIMITATIONS: Findings may not generalize outside the United States. CONCLUSIONS: Pain interference and fatigue, as well as an overall symptom burden, are useful prognostic indicators in patients receiving in-center hemodialysis. Symptom burden should remain a treatment target in hemodialysis.

Hemodialysis↗

PubMed2026

Clustering patterns of behavioral and metabolic risk factors for noncommunicable diseases in Iran: findings from a national STEPS survey.

BACKGROUND: Noncommunicable diseases (NCDs) are the leading cause of mortality in Iran, driven by behavioral and metabolic risk factors that frequently co-occur. OBJECTIVE: To identify patterns of co-occurring behavioral and metabolic NCD risk factors among Iranian adults and characterize their demographic and socioeconomic correlates. METHODS: This cross-sectional study analyzed data from 16,618 adults aged ≥25 years who participated in Iran's 2021 nationally representative STEPS survey. Thirteen behavioral and metabolic variables, including physical activity, nutrition score, smoking frequency, alcohol intake, salt intake, body mass index, blood pressure, fasting plasma glucose, and lipid markers, were entered into a K-means clustering analysis. Clusters were characterized by their risk profiles and demographic/socioeconomic attributes. Multinomial logistic regression examined associations between cluster membership and sociodemographic factors. RESULTS: Five distinct behavioral-metabolic clusters emerged. The smokers-drinkers (SD) cluster (3.1%) comprised mostly older, less-educated men with high smoking and alcohol use. The healthy-low-risk (HLR) cluster (40.3%) showed favorable profiles and included younger, more educated individuals. The physically active (PA) cluster (6.6%) was characterized mainly by younger men with markedly high physical activity levels. The dyslipidemic (DLP) cluster (26.0%) exhibited high dyslipidemia and overweight prevalence, while the hypertensive-diabetic (HTD) cluster (24.0%) had the highest obesity, hypertension, and diabetes rates, common among older urban adults. CONCLUSION: Behavioral and metabolic NCD risk factors in Iran formed five distinct co-occurrence patterns. Nearly half of adults belonged to metabolically high-risk clusters, highlighting the need for targeted prevention strategies that combine lifestyle interventions with screening and management of obesity, hypertension, diabetes, and dyslipidemia.

Humans↗

PubMed2026

Online Social Anxiety in the Digital Age: Transitions, Predictors, and Mental Health Associations in Emerging Adulthood.

BACKGROUND: Online social anxiety (OSA), a multidimensional form of social evaluative anxiety in online social contexts, disproportionately affects emerging adults who constitute the largest active group of media users and face heightened psychological sensitivity due to growing pressures and immature sociocognitive regulation during the transition to adulthood. However, its heterogeneity, transitions, and longitudinal associations with mental health outcomes remain underexplored. METHODS: This study utilized data from two waves of a three-wave longitudinal survey, with 849 Chinese participants (Meanage = 21.6 years; 50.4 percent female) assessed at 4-month intervals. Individuals were classified using latent profile analysis and the stability and changes of profiles were assessed via latent transition analysis (LTA). Multinomial logistic regressions were conducted separately at baseline and follow-up to identify correlates of profile membership. Predictors of profile transitions were examined using manual three-step LTA models, and associations between latent transition patterns and follow-up mental health outcomes were examined using BCH-LTA distal outcome analyses controlling for the corresponding baseline symptom level. RESULTS: Four profiles of OSA were identified: low, privacy-sensitive, moderate-high, and high OSA. Extreme profiles (low/high OSA) showed high stability (80.4 percent and 79.1 percent), while privacy-sensitive OSA exhibited the lowest stability (55.1 percent). Profile memberships were influenced by social-cognitive biases and digital interaction, particularly fear of negative evaluation and online interpersonal trust, whereas profile transitions were mainly associated with anxiety. Transitions toward less severe OSA profiles were generally associated with better subsequent mental health, whereas transitions toward more severe profiles corresponded to poorer outcomes, particularly for offline social anxiety. CONCLUSION: OSA was heterogeneous in its manifestation, severity and transitions. Personalized and early interventions targeting profile-specific vulnerabilities are critical to prevent the worsening of OSA and mitigate its psychological burden.

Humans↗

PubMed2026

Unravelling bioanalytical innovations, degradation processes, and impurity landscapes of VEGFR inhibitors.

From pre-formulation studies to clinical trials, VEGFR-targeted small-molecule tyrosine kinase inhibitors (TKIs) require rigorous analytical standards. Bioanalysis, stability-indicating studies, and impurity profiling are used to examine chromatographic advances for VEGFR-targeted TKIs like sunitinib, pazopanib, axitinib, sorafenib, cabozantinib, vandetanib, apatinib, lenvatinib, nintedanib, and regorafenib. An LC-MS/MS and UPLC-MS/MS routinely show sub ng/mL performance, as shown by LLOQs (0.2 ng/mL) for sunitinib and axitinib, 1 ng/mL for pazopanib, 5-7 ng/mL for sorafenib, 0.5-1.5 ng/mL for regorafenib metabolic products, and 0.1-0.5 ng/mL for lenvatinib. These approaches are used for pharmacokinetics and therapeutic drug monitoring due to their good correlation coefficient of 0.1-10,000 ng/mL, accuracy of 95%-108%, and precision of 15% RSD. UPLC-QTOF-MS/MS distinguishes degradants and metabolites during forced degradation studies, enabling structural elucidation following ICH M7 risk evaluation protocol. HPTLC/MLC offers fast, sensitive screenings, while RP-HPLC/DAD or HPLC-UV offer reliable, cost-effective routine quality-control solutions with LOD/LOQ in the μg/mL range and linearity of 10-240 μg/mL. This review lists the structures and CAS numbers of ten VEGFR-2 TKI degradants and metabolites, as well as pharmacopeial impurities in SMILES forms. It will be useful for future method development and regulatory applications. To ensure VEGFR-targeted TKI quality, safety, and therapeutic efficacy, LC-MS/MS for trace quantification and HRMS for structure elucidation provide a robust, future-oriented framework. To improve VEGFR-targeted TKI quality, safety, and regulatory compliance, analytical development should focus on HRMS-based impurity characterization, AI-assisted degradation prediction, green chromatography, and harmonized bioanalytical validation.

Humans↗