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PubMed2026

A hybrid effectiveness-implementation trial to integrate precision skin cancer risk feedback in federally qualified health centers.

BACKGROUND: Skin cancers are the most common type of cancer in the United States, occur in all segments of the population, and are preventable. Our previous research with primary care patients' demonstrated interest in and efficacy of a precision prevention intervention providing feedback on MC1R risk level (higher versus average) in combination with prevention education materials relative to a standard educational intervention. Our current study is a hybrid type 1 effectiveness-implementation trial deployed at six federally-qualified health centers. This paper presents the study protocol. METHODS: A community advisory panel will guide development of study materials and measures. Staff training at each clinic will be completed in-person. Patients will be approached and screened in-person. Those completing genetic testing and the baseline survey will be randomized to the precision versus standard intervention for each risk level with a target sample size of 286 for each combination. Primary outcomes of effectiveness, assessed at 6 and 12 months, include a tanning score (5 items assessing intentional and unintentional tanning), number of sunburns, conduct of a skin self-examination, and electronic health record documentation of clinician-patient communication about skin cancer prevention. Effectiveness comparisons will focus on the precision relative to the standard intervention among higher risk participants. Implementation data will be collected to identify barriers and facilitators. RESULTS: Effectiveness and implementation outcomes will be evaluated following study completion. CONCLUSIONS: Results will guide subsequent scale-up of the precision intervention, including modifications of the intervention as well as methods for implementation. CLINICAL TRIALS IDENTIFIER: NCT07222995.

Humans↗

PubMed2026

Strategy for enhanced production of A40926B0 in Nonomuraea gerenzanensis using an efficient CRISPR/AsCas12f1 system.

The global emergence of vancomycin-resistant Gram-positive pathogens underscores the urgent need for efficient production of novel lipoglycopeptide antibiotics. Dalbavancin, a last-resort therapeutic agent, relies on its key biosynthetic precursor A40926B0, whose industrial manufacture is severely limited by the low yield of wild-type Nonomuraea gerenzanensis and inefficient genetic tools for this rare actinomycete. Here, we developed a high-efficiency CRISPR/AsCas12f1 genome editing system and applied systematic metabolic engineering to boost A40926B0 biosynthesis. First, conjugation conditions were optimized to elevate the transfer efficiency in N. gerenzanensis D11. The hypercompact AsCas12f1 nuclease showed markedly lower cytotoxicity than SpCas9 and enabled 100% gene deletion efficiency with preferred PAMs (TTTG, CTTG, GTTG). Second, we strengthened the shikimate pathway via multiple genetic strategies: overexpressing feedback-resistant DAHP synthase (aroG fbr ) and chorismate mutase/prephenate dehydrogenase (tyrA fbr ), as well as knocking out pheA. This manipulation blocks the phenylalanine synthetic branch and redirects metabolic flux toward the l-tyrosine branch. Third, we engineered the branched-chain fatty acid (BCFA) pathway via promoter replacement of bkdA2B2C2, LipAB, fabF and deletion of acdH to enhance isododecanoyl side-chain supply. The combinatorial engineering yielded strain B-13, which produced 1740 mg/L A40926B0 in shake flasks. Finally, 50-L fed-batch fermentation with continuous maltodextrin feeding further increased the titer to 1817 mg/L, the highest reported titer to date. This work establishes a robust CRISPR editing tool for N. gerenzanensis and provides valuable engineering references for precursor-oriented strain improvement targeting lipoglycopeptide antibiotics, offering insights for the industrial scale production of A40926B0.

A40926B0↗

PubMed2026

Assessing the public health impact of routinely collected electronic healthcare record data in NICE guidelines: A systematic review of CPRD research.

OBJECTIVES: Evidence used in NICE guidance has traditionally prioritised randomised controlled trials, but increasing availability of electronic health record (EHR) data has expanded opportunities for real-world evidence. The Clinical Practice Research Datalink (CPRD) is a commonly used UK primary care EHR resource, yet the extent to which CPRD studies have informed NICE guidelines in the past decade is unclear. STUDY DESIGN: The systematic review was conducted in accordance with PRISMA guidelines. METHODS: We conducted a systematic review of CPRD studies in PubMed, MEDLINE, and Embase published between 04/16-09/25. For each eligible CPRD study, targeted searches of NICE guidelines were performed to identify explicit citations in NICE guidelines. Two reviewers screened and extracted data independently, resolving disagreements by consensus or third reviewer. Guideline information, number of guidelines over time, type of guidelines, and disease area guidelines (using British National Formulary (BNF) chapters) were described. RESULTS: 7181 records were identified. After de-duplication, 2704 unique CPRD studies were screened against NICE guidelines. Of these, 92 CPRD-based studies met inclusion criteria and were cited across 67 NICE documents. The annual number of NICE guidelines citing CPRD studies increased between 2016 and 2025; 1.5% of identified guidelines published in 2016 and 27.7% in 2025. The guideline citing the most CPRD studies was cancer related. The most common types of guidelines included clinical guidelines (49.3%) and technology appraisals (32.8%). Guidelines made up 12 different BNF categories, most frequently central nervous system related (23.9%; n = 16). CONCLUSION: Observational CPRD studies are increasingly referenced in NICE guidelines across multiple disease areas, supporting the growing role of EHR data in national guideline development.

Clinical studies↗

PubMed2026

The application of artificial intelligence in healthcare practice: A mapping review of systematic reviews.

Artificial intelligence (AI) is rapidly transforming healthcare practice, with growing evidence supporting its use in diagnosis, prognosis, treatment planning, and operational decision-making. The proliferation of systematic reviews in recent years underscores the need for an updated synthesis of the literature to inform research, policy, and practice. We searched PubMed, Web of Science, Scopus, IEEE Xplore, and CINAHL for systematic reviews and meta-analyses published between 2019 and February 2026. Eligible reviews focused on AI applications in healthcare practice, were peer-reviewed, and written in English. A total of 368 reviews met the inclusion criteria. Publication volume increased steadily, peaking in 2025. AI research was concentrated in high-density domains, such as radiology, oncology, and critical care. Across reviews, diagnostic imaging, electronic health record (EHR) data, and biomarkers/laboratory results accounted for 68% of training data sources, though newer data types, such as wearable device and sensor data, emerged from 2022 onward. Diagnosis, prognosis, and treatment comprised over 80% of AI applications, with novel uses emerging in recent years, such as AI-assisted clinical documentation (e.g., ambient documentation tools) and patient education. Ethical concerns were reported in 78.5% of reviews, with privacy, model accuracy, data and algorithmic bias, and explainability as recurrent themes. The proportion of reviews reporting ethical concerns increased from 2021 to 2025. AI applications in healthcare are expanding in scope, diversifying in data sources, and evolving toward novel clinical and operational uses. The human-centered AI or augmented intelligence paradigm, integrating computational precision with clinical expertise, holds significant promise but will require parallel advances in governance, regulatory frameworks, and ethical oversight to ensure safe adoption.

Artificial Intelligence↗

PubMed2026

Cloning of two Hsp70 genes and association analysis between SNP haplotypes and high temperature tolerance trait in red swamp crayfish (Procambarus clarkii).

Aquaculture is suffering the challenge from high temperature climate. Two Hsp70 genes, PcHsp70-1 and PcHsp70-2, as key genes involved in the high temperature tolerance of red swamp crayfish (Procambarus clarkii) were identified and cloned in this study. Their molecular features and expression patterns were characterized, revealing the distinct tissue-specific upregulation expression under high temperature stress (33 °C). Two SNPs, PcHsp70-1 (SNP258) and PcHsp70-2 (SNP555) were examined to associate with high temperature tolerance in three populations (n = 675). The genotypes of PcHsp70-1-SNP258 (GA) and PcHsp70-2-SNP555 (TT) were significantly associated with stronger high temperature tolerance. Notably, individuals carrying the haplotype of Hap I (GG + TT) showed a survival rate exceeding 70% under high temperature stress, whereas, the Hap VIII (AA + CT) showed it at 5.2%. RNA interference of PcHsp70-1 resulted in a significant decrease expression of the gene GSH-Px and its encoding protein (glutathione peroxidase) activity, and damage in intestinal tissue under high temperature stress. The transcriptome result revealed that PcHsp70-1 participates in regulation of the pathways related to cytoskeletal construction, immune response, apoptosis, and antioxidant defense. These findings indicate that PcHsp70 genes are crucial for the cellular stress response under high temperature stress. The developed Kompetitive Allele Specific PCR (KASP) markers provide valuable tools for the marker-assisted selection of high temperature tolerant crayfish varieties, supporting the sustainable development of aquaculture under the challenge of global warming.

Animals↗

PubMed2026

Decoding the spatiotemporal patterns of food spoilage microbial communities: Integrating multi-omics and artificial intelligence to enable precision preservation.

In the global food supply chain, food wastage caused by spoilage has resulted in significant economic losses, food shortages, and environmental pressure. This process is fundamentally driven by the spatiotemporal dynamics of microbial communities. However, traditional research methods struggle to elucidate the complex mechanisms of spatial heterogeneity, interspecies interactions, and functional succession. This limits the development of effective preservation strategies. This review systematically reviews the cutting-edge progress of integrating multi-omics technologies and artificial intelligence (AI) to study food spoilage microbial communities, breaking through this bottleneck. We propose an intelligent theoretical framework that could potentially analyze microbial metabolic activities and predict dynamic shelf life if implemented. The conceptual framework integrates multidimensional data, including spatial metabolomics, temporal metatranscriptomics, single-cell transcriptomics, and longitudinal metagenomics. It can also be combined with AI models, such as graph neural networks. The article elaborates on the principles and applications of spatio-temporal monitoring technologies, such as nano secondary ion mass spectrometry, hyperspectral imaging, and the Internet of Things sensing. Through illustrative cases of typical perishable foods, it also explores how such a multi-omics - AI system might be applied to spoilage warning and precise intervention. Additionally, the article addresses the current challenges in data coverage, model generalization, and federated learning implementation. Then the research further explores emerging areas such as engineered probiotics, edge AI, and microfluidic sensing. These areas are targeted at transforming food preservation from an empirical control approach to a data-driven, precise regulatory framework. This transformation provides theoretical support and technical approaches for developing a smart, sustainable food preservation system.

Multiomics↗

PubMed2026

Effectiveness of peer recovery support services for substance use disorders: A systematic review of healthcare utilization, behavioral health, and engagement outcomes.

BACKGROUND: Peer recovery support services (PRS) delivered by individuals with lived experience of substance use, are increasingly incorporated into substance use disorder (SUD) care systems to improve care engagement, reduce acute care use, and support recovery. However, existing systematic reviews have focused on substance use outcomes, with limited attention to healthcare utilization, psychosocial functioning, and outcomes across settings, and populations. METHODS: This systematic review, registered in PROSPERO (CRD42023469279), synthesized peer-reviewed studies from 2003 to 2026 evaluating PRS for individuals with alcohol or drug-related SUD. Using MEDLINE, Embase, PsycINFO, and CINAHL, the review included 53 studies primarily conducted in high-income countries that reported quantitative outcomes across substance use, healthcare utilization, behavioral health, and treatment engagement. Risk of bias was assessed using Cochrane RoB 2, ROBINS-I, and ROBINS-E tools. RESULTS: Overall, evidence was most favorable for selected treatment-linkage and engagement outcomes, whereas findings for substance use, emergency department use, hospitalization, overdose, and mortality were inconsistent. Uncontrolled longitudinal studies frequently reported improvements in depression and anxiety, but no randomized trials evaluated these outcomes, limiting causal inference. Exploratory cross-study patterns suggested that sustained navigation, practical assistance, and repeated peer contact were more often present in programs reporting favorable outcomes; however, these components were not independently evaluated. Substantial heterogeneity, frequent multicomponent interventions, high risk of bias in many nonrandomized studies, and limited long-term and economic data constrain conclusions. CONCLUSIONS: Findings support the promise of PRS while underscoring the need for more rigorous comparative studies, cost-effectiveness data, and further research in low- and middle-income countries.

Humans↗

PubMed2026

Parents' Awareness of Their Adolescents' Sexual Behaviors and Experiences: A Concordance Analysis.

PURPOSE: Adolescence is a developmental period during which sexual exploration is normative. Parental awareness of adolescents' sexual behaviors can be protective during this stage; however, research suggests both parents and adolescents tend to avoid open conversations about these sensitive issues. This study aimed to examine concordance between parent proxy-reports and adolescent self-reports across three domains of adolescents' sexual behaviors and experiences. METHODS: Data were collected from a national sample of 522 parent-adolescent dyads (aged 15-17 years) from the AmeriSpeak panel (data collected May-September 2022). Prevalence-adjusted bias-adjusted kappa (PABAK) statistics were calculated to evaluate agreement. RESULTS: Findings revealed weak-to-moderate concordance regarding adolescents sending and receiving sexual photos (PABAKs = 0.54-0.79), whereas stronger concordance was observed for experiences related to nonconsensual sharing of sexual photos (PABAKs = 0.92-0.94), with high agreement largely driven by low reported prevalence of these experiences. Strong concordance regarding whether adolescents had ever had sex (PABAK = 0.80) was largely driven by both parents and adolescents reporting the adolescent had not had sex. Concordance regarding sexually transmitted infection and pregnancy prevention methods varied, ranging from weak to strong agreement across specific methods (or lack thereof; PABAKs = -0.07-0.79). DISCUSSION: Results highlight significant discrepancies in parents' knowledge about their adolescents' sexual behaviors and experiences. Interventions aimed at enhancing trust and open dialogue between parents and adolescents about sexuality-related topics, as well as ensuring adolescents have a variety of trusted sources to consult for sexual information, can help adolescents make informed sexual health decisions.

Humans↗

PubMed2026

Orofacial Cleft Disparities in American Indian and Alaska Native Populations: A Systematic Review and Meta-Analysis.

ObjectiveTo evaluate the prevalence, access to care, and health outcomes of orofacial clefts (OFCs) among American Indian and Alaska Native (AI/AN) populations through a systematic review and meta-analysis.DesignSystematic review and meta-analysis performed in accordance with PRISMA 2020 guidelines and registered with PROSPERO (CRD420251035364).SettingUS-based population registries, hospital databases, and institutional or community-level retrospective studies involving AI/AN populations.Patients and ParticipantsAI/AN individuals with OFCs compared with non-Hispanic White patients.InterventionsPrimary cleft lip and palate repair, secondary cleft-related procedures, and multidisciplinary cleft care.Main Outcome Measure(s)Prevalence of OFCs, timing of cleft surgery, discharge disposition, access to specialists, and qualitative determinants of disparities.ResultsEighteen studies including more than 1985 AI/AN patients were identified. Meta-analysis of 5 studies estimated a pooled OFC prevalence of 15 per 10 000 live births (95% confidence interval: 5-49), with substantial heterogeneity (I2 = 99.8%). Individual studies reported significantly higher OFC prevalence in AI/AN populations compared to non-Hispanic Whites (odds ratio range: 1.44-2.68). Geographic maldistribution of craniofacial-trained surgeons, increased odds of nonhome discharge, and delayed cleft palate repair were consistently observed barriers. Qualitative analyses highlighted structural inequities, perceived racism, and lack of culturally responsive care as major contributors to disparities.ConclusionsAI/AN populations face a disproportionately high burden of OFCs alongside structural barriers to timely, culturally competent care. Addressing these disparities requires community-engaged, multidisciplinary interventions that improve geographic access and integrate culturally responsive approaches to care.

Humans↗

PubMed2026

Cytonuclear conflict and reticulate evolution in the Morelloid clade (Solanum, Solanaceae): Insights from genome skimming and network Phylogenomics.

The Morelloid clade (black nightshades) is one of the most strongly supported clades within the megadiverse Solanum genus. It comprises 76 globally distributed, non-spiny herbaceous and suffrutescent species. While often erroneously considered poisonous weeds, several species are economically important as orphan crops. The clade is closely related to tomato and potato but, due to a lack of focused breeding efforts, remains a putative reservoir of genetic diversity for crop improvement. Despite this potential, we lack fundamental knowledge on the evolution of the Morelloid clade. The group includes polyploid species with unknown parental origins-likely reflecting reticulate processes such as hybridization, introgression, and associated backcrossing events. Prior analyses have been unable to disentangle these processes, leaving the mechanisms underlying reticulate evolution in the Morelloid clade poorly understood. Here, we use genome skimming to produce a well-supported maximum likelihood plastid phylogeny from complete circularized plastomes and a coalescent-based species tree from combined Angiosperms353 and conserved ortholog set nuclear markers. Our dataset, composed of previously published data and deep genome skimming from herbarium samples, spans 26 Morelloid species. To investigate phylogenetic discordance, we used a nuclear phylogenetic network, multispecies coalescent simulations, a fused rooted nuclear chloroplast tree, and quantification of nuclear gene tree concordance. We show that incongruence between nuclear and plastid trees is pervasive and cannot be explained by incomplete lineage sorting alone. Instead, our results demonstrate that events consistent with repeated chloroplast capture have shaped the reticulate evolutionary history of the clade, especially among African polyploid and Pan-American diploid lineages.

Phylogeny↗

PubMed2025

Influence of soil types with different soil-forming process on the qualitative and quantitative detection of microplastics by near-infrared spectroscopy.

Microplastics (MPs) have become a pressing global environmental threat, with soils-acting as sinks for MPs from multiple sources-gaining increasing attention. Near-infrared (NIR) spectroscopy offers a promising tool for MPs detection due to its rapid, non-destructive, and field-applicable features. Although previous studies have focused on the effects of individual soil components on the NIR detection performance of MPs, there is still a lack of systematic research on how the complex background-formed by the coupling of multiple physicochemical properties in natural soils-affects detection performance. This study focuses on soil types with different soil-forming processes, selected five representative agricultural soils to systematically evaluate how the combinations of physicochemical properties they represented affect the performance of NIR-based qualitative and quantitative analysis of MPs in soils. The results demonstrated that soil type significantly affected both the spectral response and detection performance of MPs. Brown Pedocals and Brown Earth exhibited clearer characteristic absorption and stronger linear responses, achieving higher identification accuracy under low (<1.5 %) or zero MPs concentrations and the best quantitative performance (R2 ≥ 0.988, prediction set root mean square error (RMSEP) ≤ 0.110 %). In contrast, Phaeozem and Red Soil were more prone to misclassification at low concentrations, while Fluvo-aquic Soil showed the poorest quantitative performance. This study is the first to reveal, at a holistic level, the critical constraints posed by natural soil complexity on the NIR detection of MPs, offering targeted empirical evidence to support the application of NIR technology in real-world soil environments.

Soil↗

PubMed2026

Associations Between Health-Related Physical Fitness and Accelerometry-Based Energy Expenditure in Physiotherapy Workers.

BACKGROUND AND PURPOSE: Although it has been assumed that higher physical activity (PA) levels will contribute to better physical fitness (PF) performance, the interplay between these two has yet to be investigated. Moreover, the majority of studies have been presented in children and adolescents, and older adults, while little is known about the correlation in the adult working population of physiotherapists. Therefore, the main purpose of the study was to examine associations between objectively measured PA and health-related PF. METHODS: We recruited 50 physiotherapists (72.6% women) from several public and private settings in the city of Zagreb. The SenseWearArmbandPro3 (SWA), a triaxial accelerometer placed on the nondominant hand for 7 consecutive days, was used to capture total energy expenditure (TEE) and active EE (AEE). Cardiorespiratory fitness included the Harvard step test, and muscular fitness was composed of sit-ups in 60 sec and the Handgrip strength. Flexibility was evaluated using the Toe-touch test. RESULTS: TEE and AEE were moderately and positively correlated with the Harvard step test (r = 0.65 and 0.62, p < 0.001), sit-ups (r = 0.70 and 0.59, p < 0.001), and the Handgrip strength test (r = 0.74 and 0.64, p < 0.001). No significant correlation with the Toe-touch test was observed (r = -0.25 and -0.19, p > 0.05). When models were adjusted for age, weaker, but significant positive correlations remained. DISCUSSION: The findings suggest that both cardiorespiratory and muscular fitness are positively associated with PA, whereas no statistically significant association with flexibility was detected. Thus, it is not surprising that we obtained moderate to almost strong correlations between TEE and AEE with cardiorespiratory and muscular fitness. CONCLUSIONS: In physiotherapists, TEE and AEE yield moderate correlations with health-related PF, especially for cardiorespiratory and muscular fitness.

Humans↗

PubMed2026

The hidden threat from food-derived carbon dots: Formation, biodistribution, and potential health risks.

Food-derived carbon dots (CDs) are a new class of carbon-based nanoparticles generated during the thermal processing of food matrices. These nanomaterials have been extensively studied for their unique fluorescence, good biocompatibility, and tunable surface chemistry in food detection, intelligent packaging, and biomedical applications. However, their nanoscale size and high surface activity have raised safety concerns regarding biological interactions, in vivo biodistribution, and potential long-term health hazards. Although CDs have traditionally been regarded as low-toxicity materials due to their favorable biocompatibility, the potential hidden risks of CDs have not received sufficient attention. CDs exhibit dose-dependent toxicity, not only accumulating in various tissues and organs but also potentially inducing oxidative stress and interfering with cellular metabolic functions. Therefore, this review summarizes the advances in sources, synthetic strategies, and core properties of CDs, with a special focus on in vivo biological interactions, fates, and potential safety challenges. In addition, it is proposed that the standardized detection and risk assessment system should be established to further explore the long-term health effects of CDs under real dietary exposure, thereby ensuring their safety and sustainable application.

Carbon Quantum Dots↗

PubMed2026

Cost-Effectiveness of Electronic Patient-Reported Outcome Measure Interventions in Cancer: Systematic Review and Parameter Extraction for Economic Modeling.

BACKGROUND: Complex digital interventions that integrate electronic patient-reported outcome measures (ePROM) into clinical practice in cancer have the potential to improve quality of life, increase survival, and reduce health resource use and costs. Such systems can help patients with cancer self-manage chemotherapy symptoms, reduce clinicians' workloads through automated decision support, and resolve problems earlier. However, more research on the cost-effectiveness of ePROM monitoring is needed. OBJECTIVE: This paper comprises two complementary components: (1) a systematic literature review summarizing and evaluating the quantitative and qualitative evidence related to the cost-effectiveness of ePROM monitoring and (2) a health economic model parameter extraction. We also conducted supplementary targeted searches and scoping to provide context to our findings. METHODS: We searched Ovid (including MEDLINE and Embase), Scopus, and the International Health Technology Assessment Database for original English-language papers published on or before March 2025 using search strings that combined terms related to ePROMs, health economics, and cancer/oncology. We included papers reporting health economic-related outcomes for ePROM interventions designed for adult cancer populations and excluded screening tools and conference abstracts. RESULTS: We included 34 publications from 27 unique studies and identified and analyzed 26 ePROM-integrated interventions within these. Most (23/26) of the included interventions explicitly described some form of alert handling and automated decision support based on remote ePROM monitoring. Of the 34 publications, 5 presented full cost-effectiveness analysis results, of which 3 were highly uncertain and lacked clear differences in costs and health outcomes between ePROMs and standard care; conversely, 2 presented strong evidence of cost-effectiveness due to quality-of-life improvements, reduced hospitalizations, and potentially more autonomy in health-related travel (eg, ePROM-monitored patients can drive or walk to the hospital instead of using taxis or ambulances). A further 5 publications reported partial health economic results (eg, cost-consequence and budget impact), of which 1 detected no difference in strategies; in contrast, 4 reported lower health resource use and costs of ePROMs, mainly due to hospitalization reductions. Overall, 12 of the 27 studies included a qualitative component but mostly focused on user experience and design-related themes; only 2 of these addressed economic-specific themes (eg, changes in workflow and resource use due to ePROM implementation and integration), indicating some potential for time saving due to ePROM monitoring. CONCLUSIONS: Some ePROM-integrated interventions demonstrated cost-effectiveness in cancer care, but the evidence base remains limited. Where evidence does exist, cost-effectiveness appears driven by reduced hospitalization and improved quality of life. Qualitative research within the included studies rarely addressed economic questions. We provide a detailed parameter extraction for use in future economic modeling and recommend research priorities, including quantitative mapping of ePROM symptom data onto health resource use patterns, and qualitative work exploring how ePROM implementation affects clinical workloads and patient-perspective costs.

Humans↗

PubMed2026

Systematic review of machine learning approaches for predicting sickle cell crisis and mortality risk at the climate-health nexus.

BACKGROUND: Sickle cell anemia (SCA) is a severe genetic blood disorder characterized by recurrent vaso-occlusive crises and increased mortality, with the greatest burden occurring in low- and middle-income countries. Climatic and environmental conditions, including temperature variability, humidity, rainfall, air pollution, and seasonal changes, have been associated with disease exacerbation. However, the extent to which these factors have been incorporated into predictive models remains unclear. This study systematically reviews the application of machine learning (ML) models for predicting SCA crises and mortality in relation to climate and environmental factors. METHODOLOGY: The PRISMA guidelines were used, and 34 peer-reviewed studies published between 2005 and 2026 were analyzed to identify the climate variables, ML approaches employed, and predictive performance. The reviewed studies applied a range of ML techniques, including artificial neural networks, random forests, support vector machines, decision trees, logistic regression, and deep learning models. Temperature, humidity, rainfall, wind speed, air quality indicators, and seasonal patterns were the most frequently examined environmental variables. RESULTS: The findings indicate that most existing models rely predominantly on clinical and demographic data, with limited integration of climate information and inadequate representation of high-burden regions, especially Sub-Saharan Africa. Studies incorporating environmental variables reported improved predictive performance and highlighted the potential of climate-informed early warning systems for SCA management. CONCLUSION: The review recommends development of interdisciplinary, climate-aware ML frameworks, expansion of longitudinal environmental datasets, and increased research in underrepresented regions to support climate-resilient and patient-centered SCA care.

Humans↗

PubMed2026

BIOCARD framework: integrating fecal bile acids, lipids, and metabolites to assess response to a cardiovascular health intervention.

Cardiovascular disease (CVD) remains a leading cause of morbidity and mortality, particularly in under-resourced populations. Although nutritional interventions are important for CVD prevention, their outcomes are commonly evaluated using conventional clinical and behavioral indicators, which may not fully capture early molecular responses. In this study, we developed the BIOCARD framework, an exploratory fecal multi-omics platform integrating bile acids, lipids, and metabolites to evaluate intervention outcomes related to cardiovascular health. Fecal samples were collected from caregiver-child participants enrolled in a 10-week randomized controlled trial comparing a multicomponent garden-based intervention (SHA) with an education-only control group (MSP). Fecal polar metabolites, lipids, and bile acids were analyzed by UHPLC-HRMS-based approaches and integrated with conventional health indicators. Traditional clinical indicators in the present study showed limited sensitivity for detecting intervention-related differences. In contrast, fecal multi-omics analyzes revealed intervention-associated differences in metabolites, lipids, and bile acids, with children showing more apparent molecular variation than parents. Network analysis further revealed associations between selected molecular features and cardiovascular-related indicators, including blood pressure, body fat, skin carotenoids, and Healthy Eating Index scores. Together, these findings suggest that the BIOCARD framework may serve as an exploratory molecular approach to complement traditional outcome measures and improve the evaluation of nutritional interventions for cardiovascular health.

Humans↗

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

Exploring the role of successful exercise-induced body weight loss on cardiometabolic health in individuals with metabolic syndrome.

BACKGROUND AND AIM: High-intensity interval training (HIIT) is known to improve cardiorespiratory fitness (i.e., VO2MAX), a key marker of cardiometabolic health in individuals with metabolic syndrome (MetS). Nonetheless, body weight loss is widely recognized as a crucial factor in reducing insulin resistance and improving metabolic risk factors. Thus, we aimed to determine the importance of body weight loss following exercise training on improving MetS. METHODS AND RESULTS: Two hundred and twenty-eight adults (55.3 ± 7.9 yr) with overweight/obesity (32.5 ± 4.6 kg·m-2) and MetS were randomized to: a) standard health care non-exercise group (CONTROL group, N=58) or b) standard health care plus 16 weeks of HIIT (EXER group, N=170). MetS (MetS z-score), insulin resistance (HOMA-IR), cardiorespiratory fitness (VO2PEAK), maximal cycling power (WPEAK), and body weight/composition were assessed. After intervention, EXER group participants were divided according to their weight loss response to training: i) those achieving the weight loss predicted from estimated exercise energy expenditure (-BW group, n=78; -3.3 ± 2.2 kg); ii) those not reaching the expected weight loss (=BW group, n=38; -0.7 ± 0.5 kg); iii) and those who gained weight (+BW group, n=54; 1.1 ± 1.0 kg). VO2PEAK significantly improved regardless of body weight loss response (-BW, 0.3 ± 0.3; =BW, 0.2 ± 0.3; +BW, 0.3 ± 0.2 L·min-1; all p < 0.001) compared to CONTROL group (0.0 ± 0.3 L·min-1). However, significant improvements in MetS z-score (-0.31 ± 0.41) and HOMA-IR (-0.7 ± 1.6) were observed only in the -BW group (both p < 0.001). CONCLUSIONS: Exercise recommendations should consider that greater improvements in MetS are observed when interventions are accompanied by successful body weight loss. CLINICAL TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT05120778.

Humans↗