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PubMed2026

Patient experiences of diagnostic uncertainty in musculoskeletal care: a systematic review of qualitative studies.

BACKGROUND: Diagnosis plays a central role in musculoskeletal care. However, establishing a clear diagnosis is often challenging, and diagnostic uncertainty is common. OBJECTIVES: To explore patient experiences of diagnostic uncertainty in musculoskeletal care. METHODS: Five databases (CINAHL, Embase, MEDLINE, AMED, Web of Science) were searched from inception to October 2025. Qualitative studies involving semi-structured interviews with adults receiving care for MSK conditions were included. Methodological quality was appraised using the Joanna Briggs Institute Qualitative Checklist. Data were synthesised using thematic synthesis, and confidence in findings was assessed using the Grading of Recommendations Assessment, Development, and Evaluation Confidence in the Evidence from Reviews of Qualitative Research approach (GRADE-CERQual). RESULTS: Twenty-six studies involving 462 participants were included. Critical appraisal identified 23 studies with varying methodological limitations; all studies were included in the synthesis. Nine descriptive themes were synthesised into three analytical themes: (1) patient expectations and perceived meanings of a diagnosis and interpretations of diagnostic uncertainty; (2) the multi-dimensional experience of diagnostic uncertainty; and (3) the role of contextual factors, particularly communication and the therapeutic relationship, in shaping experiences of diagnostic uncertainty. Using GRADE-CERQual, confidence in these themes was rated as low, moderate and very low, respectively. CONCLUSION: Diagnostic uncertainty is a subjective and multi-dimensional experience shaped in part by patients' expectations and the meanings attributed to diagnosis. Its impact spans predominantly cognitive and affective domains and may influence clinical presentation. Patient-centred communication and strong therapeutic relationships may support patients in navigating diagnostic uncertainty in musculoskeletal care.

Adult↗

PubMed2026

Predictive evolutionary genomics: principles, validation, and practice.

Climate change and habitat loss are driving rapid evolutionary responses in populations world-wide, which creates an urgent need for evolutionary forecasting in conservation and agriculture. Such forecasting can be categorized into three time scales: trait-based models that use multivariate quantitative genetic equations to project correlated phenotypic responses up to c. 20 generations, allele-based analyses that model allele frequency dynamics up to 100 generations, and composite adaptation scores that aggregate many small effects to yield predictions across longer horizons. However, these approaches have remained largely disconnected. Here, we present a Bayesian framework that integrates these three complementary approaches for evolutionary prediction. Our framework combines genomic, phenotypic, and environmental data to yield probabilistic predictions with explicit uncertainty. We show how predictive evolutionary forecasts can be validated with experimental evolution, field experimentation, historical specimens, and reciprocal transplants. These validated forecasts can help advance conservation and agricultural programmes by helping predict which populations are at risk of future extinction, optimizing breeding programmes for future climates, and planning ecosystem management under environmental change. By supporting a shift towards more predictive approaches in evolutionary biology, this framework may help improve our ability to manage biodiversity and food security in a changing world.

Genomics↗

PubMed2026

AI-driven snapshot hyperspectral imaging for on-line sorting systems in food industry: From real-time sensing to intelligent decision-making.

High-throughput food sorting requires rapid, non-destructive detection of external defects, foreign materials, and internal quality attributes in heterogeneous food matrices. Conventional scanning hyperspectral imaging may suffer from motion-induced spatial-spectral mismatches, whereas snapshot hyperspectral imaging (S-HSI) captures spectral images within a single integration time. However, its advantage is limited by trade-offs in resolution, signal-to-noise ratio (SNR), reconstruction uncertainty, and calibration stability, which are further amplified by variable tissue structure, surface reflection, moisture, and fat distribution in foods. This review critically examines artificial intelligence (AI)-driven S-HSI for on-line food sorting within a sensing-representation-decision-execution framework. Compact architectures are compared according to their physical constraints, food-sorting suitability, and ability to support mapping between spectral responses and physicochemical quality attributes. AI strategies are reviewed for spectral reconstruction, image restoration, spatial-spectral representation, band selection, uncertainty-aware decision-making, and edge implementation. AI can partially compensate for snapshot-specific limitations, but current evidence remains largely limited to laboratory or prototype studies. Future work should link system performance to food safety and quality outcomes by reporting throughput, decision latency, calibration drift, missed-detection risk, false-rejection cost, and closed-loop sorting success.

Hyperspectral Imaging↗

PubMed2026

Emerging hantavirus risks in mass gatherings: epidemiology, diagnostic challenges, and outbreak preparedness.

Hantaviruses are emerging rodent borne zoonotic pathogens of increasing global public health concern because of their high mortality, expanding ecological distribution, and potential for international dissemination. Although traditionally associated with sporadic rural outbreaks, recent ecological disruption, climate variability, urbanization, and increased global mobility have heightened concerns regarding hantavirus risks in mass gathering settings. This review critically examines the epidemiology, transmission uncertainty, diagnostic and surveillance challenges, and preparedness strategies related to hantavirus infections in the context of mass gatherings, including religious events, refugee settlements, cruise tourism, sporting events, and temporary accommodations. Particular emphasis is placed on the 2026 multinational cruise ship associated outbreak linked to the MV Hondius, which highlighted vulnerabilities related to delayed diagnosis, international passenger dispersal, and uncertainties surrounding possible human to human transmission of Andes virus. Current evidence indicates that hantavirus transmission occurs primarily through inhalation of aerosolized rodent excreta; however, controversies regarding limited interpersonal transmission, environmental persistence, and asymptomatic infections continue to complicate risk assessment and outbreak preparedness. Diagnostic limitations, underreporting, insufficient environmental surveillance, and lack of mass gathering specific preparedness frameworks remain major public health challenges, especially in resource limited settings. Strengthening proactive preparedness through integrated One Health approaches, ecological surveillance, genomic monitoring, AI driven epidemic intelligence, and coordinated international response systems is essential for mitigating future risks. The review emphasizes the urgent need for multidisciplinary research and evidence based policy development to improve global preparedness against emerging hantavirus associated threats in increasingly interconnected mass gathering environments.

Humans↗

PubMed2026

Interest holder-driven research priorities in sexual and reproductive health for migrant and refugee adolescents and young adults in Australia.

OBJECTIVE: To identify and prioritise sexual and reproductive health research priorities for migrant and refugee adolescents and young adults in Australia using a priority setting partnership approach. METHODS: A James Lind Alliance priority setting partnership was conducted with 92 interest holders: 31 youth from migrant and refugee backgrounds and 61 professionals (healthcare providers, researchers, policymakers and community leaders), recruited online and in-person. The priority setting partnership process included a rapid evidence scan, an online uncertainty survey, evidence verification, interim prioritisation and a final consensus workshop. RESULTS: Eighty-three research uncertainties yielded 11 final priorities across four sexual and reproductive health domains: sexual and reproductive health literacy, sexual violence prevention, accessible services and maternal health. A striking divergence emerged between youth and professional priorities only 3 achieved combined high-priority consensus. Youth prioritised a broader range of topics, including abortion access (rated high by youth but low by professionals), while professionals prioritised fewer areas. Two priorities achieved consensus: community-based maternal health support and barriers to reporting gender-based violence. CONCLUSION: This is the first priority setting partnership to identify sexual and reproductive health research priorities for migrant and refugee youth in Australia and to uniquely highlight substantial misalignment between youth and professional priorities. IMPLICATIONS FOR PUBLIC HEALTH: These identified priorities provide a foundation for targeted research, culturally responsive policy and more equitable sexual and reproductive health service provision for migrant and refugee adolescents and young adults.

Australia↗

PubMed2026

Development and validation of a liquid chromatography-tandem mass spectrometry method for the quantification of twenty-five steroids in equine serum.

Steroids are potential biomarkers for monitoring equine pregnancy. However, immunoassays currently used for their quantification suffer from cross-reactivity and limited specificity, thus requiring more accurate methods. This study reports the development and validation of a robust liquid chromatography-tandem mass spectrometry (LC-MS/MS) method for simultaneous quantification of 25 steroids covering the main biosynthetic pathways of progestogens, corticosteroids, androgens, and estrogens. Steroids were extracted by protein precipitation followed by evaporation, derivatization, and reconstitution before LC-MS/MS analysis. A surrogate matrix was used for calibration and validation to avoid endogenous interference. Validation was performed according to and partly adapted from Clinical and Laboratory Standards Institute guidelines (CLSI), including linearity, trueness, precision, limits of detection and quantification, measurement uncertainty, recovery, matrix effects, carryover, selectivity, and stability. Calibration curves were fitted using the best-performing weighted linear or quadratic regression model, yielding excellent linearity (R2 > 0.990), trueness between -9.0% and 2.3%, and intra- and inter-day precision <6.3%. Lower limits of quantification ranged from 2.07 to 2250 pg/mL depending on physiological analytes concentration. Extraction recovery averaged 24.3-114.9%, matrix effects were acceptable, and accuracy ranged from 94.4% to 98.9%. No carryover or interferences were detected. Measurement uncertainty remained <15%. This study presents the first LC-MS/MS method partially validated per CLSI criteria for the quantification of 24 steroids in equine serum. The method offers a sensitive and specific alternative to immunoassays and provides a robust tool for equine steroid profiling with potential applications in pregnancy monitoring, placentitis diagnosis, and fetal sex determination.

Animals↗

PubMed2026

An exploratory analysis of decision-making in population affinity estimation among forensic anthropology practitioners in the United States.

Population affinity estimation in forensic anthropology often involves the integration of multiple pieces of information, including visual (nonmetric) and metric data. This study examines how practitioners interpret and synthesize visual and metric information and their decision-making processes. A Qualtrics survey was developed using two cases: Case 1 presented clear nonmetric signal but ambiguous metric signal, while Case 2 showed more ambiguous nonmetric signal but clear metric signal. Practitioners were asked to estimate population affinity based on visual assessment, Fordisc data, and provide a final, integrated assessment. A total of 22 valid survey responses were received, with the majority of survey respondents reporting more than 10 years of forensic anthropology experience and holding a PhD degree. Results showed that there is substantial variability in Fordisc use and interpretation. Across both cases, participants synthesized conflicting visual and metric information, converged toward the stronger signal, and came to more consistent final estimates relative to the more ambiguous input. These findings highlight variability in practitioner decision-making but suggest that integration of nonmetric and metric information in population affinity estimation can moderate decision-making uncertainty. The results have implications for forensic anthropology education, training, and proficiency testing.

Humans↗

PubMed2026

Portable metagenomics for preventive surveillance and outbreak control in livestock and poultry: Pathogen detection, resistome profiling, and antimicrobial stewardship.

Conventional diagnostics for livestock and poultry outbreaks commonly rely on culture or targeted PCR panels, which may be too slow or too narrow to guide early control decisions. Portable metagenomics, particularly real-time nanopore sequencing, offers a route to broad pathogen detection, antimicrobial-resistance gene profiling, and outbreak investigation within an integrated workflow. This implementation-focused review evaluates how near-point-of-care metagenomics may support preventive veterinary medicine through earlier detection, surveillance, cohorting, biosecurity decisions, and antimicrobial stewardship. We synthesize sample-to-answer workflows for enteric and respiratory disease in food-producing animals, including sampling, nucleic-acid extraction, host depletion or target enrichment, library preparation, sequencing, bioinformatics, quality control, and interpretation. Applications in calf diarrhea, bovine respiratory disease, poultry outbreaks, mastitis, and resistome monitoring are considered alongside the central limitation that detection alone does not establish causation. Pathogen and resistance-gene signals must therefore be interpreted with clinical signs, lesions, epidemiology, controls, and confirmatory testing. We also propose a minimum reporting checklist, intended as a practical framework rather than a validated consensus standard. Portable metagenomics is not a replacement for conventional diagnostics, but appropriately validated workflows can reduce uncertainty during time-sensitive outbreaks and support more judicious antimicrobial use.

Animals↗

PubMed2026

Ancient DNA and Human Physiology.

Ancient DNA (aDNA) enables the reconstruction of chronologically sampled genomes from ancient humans, animals, plants, pathogens, and microorganisms, as well as environmental DNA, providing a record of biological changes through time. Improvements in short and degraded DNA extraction methods and low-cost sequencing now enable the generation of broad, cross-regional datasets that expand evolutionary analyses from past population demography to biological mechanisms. By tracking temporal shifts of allele frequencies, integrating functional genomics resources (e.g., gene expression, chromatin structure variation), modeling population demography to separate selection from genetic drift, and aligning genetic changes with archaeological, cultural, and climatic data, aDNA has the potential to link sequence variation to physiological function within their temporal and environmental contexts. In this review, we summarize illustrative case studies from aDNA research spanning complex traits, dietary adaptations, and responses to pathogens and other environmental changes, showing how human biology has evolved under multiple selective pressures through time. These dated signals help triage experimental work and expose mechanisms that are rare or absent in living cohorts. Although some challenges remain, such as geographic and temporal sampling disparities, limitations in data resolution and variant detection, and genotype-phenotype uncertainties, rapid methodological progress and stronger ethical frameworks are expanding what can be inferred, making aDNA a promising tool for refining physiological pathways, their timing, and their drivers.

Humans↗

PubMed2026

Effects of exercise snacking on neuromuscular performance in insufficiently active adults: A systematic review and meta-analysis.

OBJECTIVE: To examine the effects of exercise snacking (ES) on neuromuscular performance in insufficiently active adults. METHODS: Six databases were searched from inception to July 17, 2026. Randomized controlled trials and non-randomized studies of interventions involving insufficiently active adults undertaking ES interventions were included. Outcomes were functional performance, muscular strength, and muscular power. A three-level random-effects meta-analysis was performed. Risk of bias was assessed with RoB 2 or ROBINS-I, and certainty of evidence was evaluated using GRADE. RESULTS: Nine studies (13 reports) involving 313 participants were included. In the primary three-level model, ES showed a small positive overall effect on neuromuscular performance (g = 0.37, 95% CI 0.16-0.58, p = 0.001), which remained supported under trial-clustered robust inference with small-sample adjustment. Domain-specific estimates for muscular power/velocity, functional performance, and muscular strength were positive but imprecise and were not statistically supported after small-sample robust adjustment. Robust moderator tests provided no evidence of between-subgroup differences, and the certainty of evidence was low for all outcomes. CONCLUSION: Current low-certainty evidence suggests that ES may produce a small improvement in overall neuromuscular performance. However, domain-specific effects remain uncertain because of the limited number of independent trials, and the overall prediction interval crossed zero, indicating uncertainty across future populations and settings. Larger, preregistered randomized controlled trials are needed to confirm these preliminary findings.

Adult↗

PubMed2026

Measuring economic efficiency in adult intensive care units: A systematic review of methods, metrics, and evidence.

OBJECTIVES: Intensive care units (ICUs) consume substantial hospital resources, yet "efficiency" is inconsistently defined and measured. This study systematically reviewed how economic efficiency has been conceptualised and quantified in adult ICUs and appraised the quality of evidence. METHODS: Following PRISMA 2020 and a PROSPERO-registered protocol (CRD420251107866), we searched MEDLINE, Embase, CINAHL, Cochrane Library and Web of Science (2000-August 2025), plus global grey sources. Eligible studies explicitly defined efficiency and reported an efficiency metric/model linking ICU inputs (e.g., staff, beds/capacity, time, consumables, or costs) to outputs/outcomes (e.g., throughput/discharges, length of stay/resource use, risk-adjusted mortality). Dual independent screening and extraction were performed. Study quality was appraised using MMAT, and findings were synthesised narratively (SWiM), given heterogeneity. RESULTS: 39 studies (2001-2025) from 17 countries were included, all from high-income or upper-middle-income settings. Four methodological families were identified: (1) frontier modelling (predominantly DEA; occasional SFA/RFDH), (2) benchmarking indicators (risk-adjusted mortality and LOS/resource-use ratios; "efficiency matrix" quadrant classification), (3) cost-outcome evaluations, and (4) operational/process metrics. Across families, variation in decision-making units, input/output selection, and risk adjustment limited comparability; long-term and patient-reported outcomes were absent, and equity considerations were uncommon. CONCLUSIONS: ICU efficiency research is feasible but fragmented and often methodologically limited. Standardised definitions, validated risk adjustment, uncertainty quantification, and inclusion of patient-centred and equity-relevant outcomes are needed before efficiency metrics can reliably inform value-based decision making.

Intensive Care Units↗

PubMed2026

Rational design of high-productivity perfusion processes for CHO Cells: From growth inhibitory strategies to model-driven optimization.

While perfusion culture for Chinese hamster ovary (CHO) cells offers advantages such as continuous operation and flexibility, it suffers from product loss through cell bleeding and difficulties in reaching high productivity due to sustained rapid cell growth. Growth inhibitory strategies are widely used to enhance productivity in fed‑batch processes; however, their practical implementation and comparative effectiveness in perfusion processes remain insufficiently explored. Meanwhile, process development often relies on costly trial‑and‑error approaches. Here, we systematically compared three growth inhibitory strategies in perfusion culture-low cell‑specific perfusion rate (CSPR), sodium butyrate, and mild hypothermia-with respect to cell growth, metabolism, productivity, and product quality. Genome‑scale metabolic flux sampling analysis revealed that low‑CSPR and sodium butyrate induce a convergent up‑regulation of energy metabolism, correlating with greater gains in specific productivity (qp). Building on this insight, we developed a growth‑kinetic model for the combined low‑CSPR + butyrate strategy, incorporating parameter uncertainty. This model‑guided framework enabled the rational design of two distinct high‑productivity perfusion processes: a sustained mode that achieved robust long‑term stability alongside substantial productivity gains, and a high‑intensity mode that pushed qp and daily volumetric titer to their maxima, with increases of up to 108.94% and 190.36%, respectively, in a model CHO cell line with a moderate baseline productivity. Our study provides a proof‑of‑concept framework for perfusion intensification, from strategy selection to rational process design.

Animals↗

PubMed2026

Reproductive Intentions and Fertility Preservation Among Transgender and Nonbinary Individuals: A Cross-Sectional Study in Brazil.

PURPOSE: This study evaluated reproductive intentions, fertility-related knowledge, prior fertility counseling, and factors associated with reproductive intentions among transgender and nonbinary individuals receiving care at a Brazilian public reference center. METHODS: This cross-sectional study with a qualitative component was conducted between July and November 2025 in a specialized gender-affirming care clinic in Brazil. Quantitative data included sociodemographic characteristics, reproductive history, gender-affirming hormone therapy (GAHT), and fertility-related variables. Logistic regression was used to assess factors associated with desire for future parenthood. Responses to a single open-ended question regarding perceived effects of GAHT on fertility were analyzed using thematic content analysis. RESULTS: Eighty-two participants were included (mean age 27.5 ± 7.4 years). Most identified as transgender men (65.9%), followed by transgender women (26.8%) and nonbinary individuals (7.3%); 79.3% were receiving GAHT. Although 63.4% expressed a desire for future parenthood, only 7.3% had children. Current interest in fertility preservation was reported by 20.8% (15/72). Having children (adjusted odds ratio [aOR] = 0.03; 95% confidence interval [CI]: 0.001-0.62; p = 0.023) and each additional year of GAHT duration (aOR = 0.83; 95% CI: 0.70-0.99; p = 0.038) were associated with lower odds of desiring future parenthood. Sex assigned at birth was not independently associated with reproductive intentions. Qualitative analysis revealed misconceptions, uncertainty, and conditional beliefs regarding fertility. CONCLUSIONS: Desire for future parenthood was common among transgender and nonbinary individuals, whereas engagement with fertility preservation remained limited. These findings highlight the need for longitudinal, patient-centered reproductive counseling integrated into gender-affirming care.

fertility preservation↗

PubMed2026

The future of pediatric vesicoureteral reflux management.

BACKGROUND AND OBJECTIVE: Vesicoureteral reflux (VUR) is a common condition in pediatric urology, yet important uncertainties persist regarding risk stratification, imaging strategies, and prevention of long-term renal damage. Emerging technologies may help address these challenges. This review provides a forward-looking overview of recent advances in artificial intelligence (AI) and immunomodulation that may influence future management of pediatric VUR. METHODS: A forward-looking literature review was performed using the PubMed database (January 2000-March 2025), focusing on studies addressing AI, immunomodulation, or vaccination in the context of VUR and urinary tract infections. Criteria of inclusion were the relevance to pediatric VUR, the novelty of the proposed concept, the potential clinical implications and, for the AI literature, the existence of a clinical evaluation of the algorithm on a dataset from patients. KEY FINDINGS AND LIMITATIONS: AI-based models show promising performance in supporting clinical decision-making, including prediction of the need for voiding cystourethrography, automated grading of VUR, estimation of recurrent urinary tract infection risk and prediction of chemoprophylaxis. These tools may facilitate more individualized diagnostic and therapeutic strategies, although current evidence is largely retrospective and requires prospective validation. Immunization and immunomodulatory approaches aim to reduce infection burden and modulate inflammatory pathways associated with renal scarring. While early experimental and adult clinical data are encouraging, pediatric-specific evidence remains limited, and clinical applicability in children with VUR is not yet established. CONCLUSION: Artificial intelligence and immunologically targeted strategies represent complementary, emerging approaches that may contribute to more personalized management of pediatric VUR. At present, both should be regarded as exploratory tools whose clinical impact will depend on further validation and appropriately designed pediatric studies.

Humans↗

PubMed2026

Trends in demographic and health survey publications based on a bibliometric analysis.

BACKGROUND: The Demographic and Health Surveys (DHS) Program, launched in 1984, provides high-quality population health data that underpins a vast body of global health research. However, the scale and growth patterns of DHS-based publications remain underexplored, particularly as donor funding uncertainties threaten program sustainability. OBJECTIVE: We examine temporal trends in DHS-based research output from 1984 to 2025, quantifying growth patterns and publication delays to inform understanding of the program's global research expansion. METHODS: A systematic bibliometric review was conducted following PRISMA guidelines across PubMed, Scopus, Web of Science, Dimensions, Wiley, and CINAHL. Eligible peer-reviewed articles using DHS data between 1984 and 2025 were identified. Annual publication counts were analyzed, segmented regression identified growth inflection points, and timeliness was assessed by calculating lag between survey completion and publication. RESULTS: Over 10,000 DHS-based publications were identified. Annual output rose from isolated studies in the 1980s to several hundred annually by the 2010s. Segmentation analysis revealed two rapid growth phases: a 56-publications/year increase from 2004-2012, and a 71-publications/year increase from 2012 to 2024. Despite this growth, median lag from survey completion to publication remained approximately 5 years, with only a modest recent improvement (Kendall's τ =  -0.623, p < 0.001). CONCLUSION: DHS data have fueled exponential growth in global health research over four decades, confirming their vital role in evidence generation. However, persistent publication delays highlight the need to shorten the pathway from data collection to dissemination through strengthened research capacity in low- and middle-income countries. Sustained funding is essential to maintain this critical evidence source.

Bibliometrics↗

PubMed2026

Littoral and wetland vegetation decrease carbon emissions from dry inland waters.

Lakes are recognized as active components of the inland water carbon (C) cycle, as organic matter is processed by microbial respiration, inducing large carbon dioxide (CO2) and methane (CH4) emissions. In the context of long-lasting drought periods, large uncertainties remain about: (1) the influence of wet-dry cycle on CO2 and CH4 fluxes in littoral zones and lacustrine wetlands; and (2) the contribution of emergent vegetation to C fluxes in dry inland waters. At the water-land interface of two shallow lakes, this study focuses on CO2 and CH4 fluxes from vegetated and bare dry inland waters in relation to hydrological fluctuations. Three seasonal campaigns were conducted to measure daytime CO2 and CH4 fluxes in pelagic, littoral and wetland surface waters, as well as in temporarily air-exposed sediments, using floating and static chambers, respectively. Our results reveal that wet-dry cycle in the littoral zone and wetlands strongly influence gaseous C fluxes through contrasting patterns, especially in late summer, when the biological processes are most active (primary production and respiration). In air-exposed littoral zones, organic-poor sandy sediments presented the lowest CO2 and CH4 emissions, whereas in air-exposed lacustrine wetlands, water-saturated sediments accumulated high amounts of plant-derived organic matter, promoting intense microbial activity and the highest C emissions. However, amphiphytes and helophytes vegetation in exposed littoral zones and wetlands reversed the direction of C fluxes, inducing the highest CO2 uptake due to high photosynthesis rates. This study underlines the relevance of considering vegetation in dry inland waters, particularly in lacustrine littoral zones and wetlands, to obtain comprehensive lake C budgets, especially under climate change scenarios.

Wetlands↗

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

Anabolic androgen therapy in critically ill adults: A systematic review and meta-analysis.

Critical illness is characterized by a catabolic, proinflammatory state. Anabolic agents, such as testosterone, have therefore been proposed as therapeutic targets. Our objectives were to assess the effects of testosterone in critically ill populations on patient-important outcomes and identify design limitations to inform future studies. We searched for randomized control trials (RCTs) through Medline, Embase, and EBM Reviews databases from inception through February 24, 2026, including English language articles enrolling adults (≥18 years) admitted to ICU where anabolic androgen therapies (AAT) were compared with placebo or standard of care. Studies had to report at least one of: mortality, ICU and hospital lengths of stay, or duration of mechanical ventilation. We extracted data independently using a standardized data extraction tool, and feedback was received from all co-authors to ensure agreement. For each outcome, we performed meta-analyses using a random-effects model with inverse variance weighting in RevMan. We used the GRADE approach to assess certainty in pooled estimates of effect. Of 1325 screened articles, we found 4 that fit our inclusion criteria. Together, we judged risk of bias as 'some concerns' in 3 trials and 'high' in the final trial, and ultimately found that the effects of anabolic-androgen therapy on patient-important outcomes uncertain. With the uncertainty of current evidence for the effects of anabolic-androgen therapy in critically ill adults, there is insufficient support for its routine use. Future randomized evidence is needed to determine whether anabolic-androgen therapy improves clinically-important outcomes and better define its safety profile in critically ill adults.

Humans↗