Search PubMedSearch

SEARCH · Search PubMed

Results for “Large-vessel occlusion”

Search indexed PubMed citations on genomics, clinical trials, systematic reviews and public health. Explore titles, authors and supplied subject terms, then open the PubMed record.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

289 records · Page 6Linked to original sources

GLP-1 Receptor Agonists and Musculoskeletal Outcomes: A Systematic Literature Review and Meta-Analysis.

INTRODUCTION: Glucagon-like peptide-1 receptor agonists (GLP-1 RAs) are increasingly used for the treatment of type 2 diabetes and obesity, but their effects on musculoskeletal health remain completely misunderstood. OBJECTIVE: This systematic review/meta-analysis aims to synthesise clinical data on the effects of GLP-1 RAs on key relevant bone, muscle, and joint outcomes. METHODS: MEDLINE, Cochrane Central Register of Controlled Trials (CENTRAL) (both via Ovid&#xae; platform) and Embase were searched from inception to March 2025 to identify relevant randomised controlled trials (RCTs) or real-world evidence (RWE) studies to be included. This bibliographic search was completed manually. A random-effect model meta-analysis was performed for any outcome reported in at least 2 studies. Subgroup analyses were performed on the type of GLP-1 RAs, type of comparator used and study design. Sensitivity analyses (i.e., leave-out sensitivity analyses and analyses restricted to the most adjusted effect estimate) were performed to test the robustness of the data. The strength of evidence was assessed using GRADE. This work has been performed in adherence with PRISMA statement. (PROSPERO Record ID: CRD420251024082). RESULTS: From 1148 potentially relevant references, 60 articles (46 RCTs, 13 RWE studies and 1 pharmacovigilance study, comprising 1,250,717 individuals) met our inclusion criteria. Different GLP-1 RAs were represented across the panel of studies, i.e., semaglutide, liraglutide, exenatide, dulaglutide, tirzepatide (dual agonist gastric inhibitory polypeptide [GIP]/GLP-1) and others. No effect on bone outcomes (i.e., bone mineral density [all sites] and fractures [all sites]) were observed when the meta-analytical models included the most adjusted effect size. Regarding muscle outcomes, a significant decrease of lean body mass/fat-free mass was consistently observed with GLP-1 RAs in the global model (k = 28, standardised mean difference [SMD] 0.52, 95% confidence interval [CI] -0.8; -0.23, I2 88%, p-value for heterogeneity <0.0001), which remained robust in all sensitivity analyses. Subgroup analyses showed that the effect was mainly driven by liraglutide and semaglutide, with a decrease in lean body mass/fat-free mass observed when GLP-1 RAs were compared with placebo. No publication bias was found. Regarding joint outcome, models revealed no significant change in The Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) pain, physical function and stiffness. CONCLUSIONS: This meta-analysis is the first to investigate the effects of GLP-1 RAs on a large panel of musculoskeletal health outcomes. While no significant effects were observed on bone- or joint-related outcomes, GLP-1 RAs were associated with reductions in lean body mass/fat-free mass, although the certainty of evidence was low and these changes appeared largely related to weight loss. Whether these changes translate into clinically meaningful impairments in muscle function or physical performance remains uncertain. Further studies in this field, including those looking at muscle function, strength or performance and using multivariate models considering confounding are needed to better reinforce the models and final findings.

Journal Article

A Meta-learning-driven strategy for adulteration detection in sweet potato starch and vermicelli using Raman spectroscopy.

To address the widespread adulteration of sweet potato starch and its vermicelli with cheaper starches and overcome conventional supervised learning's dependency on large labeled datasets, this study developed a few-shot discrimination method integrating Raman spectroscopy with meta-learning. We constructed a meta-learning framework using cassava- and wheat-adulterated sweet potato starch as the source domain for training, with potato-adulterated sweet potato starch and cassava-adulterated sweet potato vermicelli as two target domains for testing. Raman spectra showed high consistency between sweet potato vermicelli and its raw starch, laying the foundation for cross-domain detection. Testing yielded comprehensive classification accuracies of 95.33% and 98.00% for the two target domains, significantly outperforming SVM, RF, and CNN (max. 85.24%). This approach effectively identifies subtle starch variety differences in complex adulteration, providing novel food quality inspection solutions and verifying the feasibility of raw material-to-finished product cross-domain detection.

Ipomoea batatas

Examining Behavioral Interventions for Infancy and Early Toddlerhood: A Systematic Review of Intervention Effects, Parameters, and Participants.

Rapid advancement is paving the way to identify children who would likely benefit from early intervention during the first years of life, prior to the onset of significant delays in development. With the widely acknowledged benefits of early intervention, key questions arise: Does behavioral intervention targeted to infancy and early toddlerhood improve developmental outcomes? What procedures might be used, and under what circumstances? Who do these interventions work for? The current review comprehensively examined the literature on behavioral interventions based in operant learning, focused on key developmental areas with children in the first two years of life. We located and synthesized 69 studies with unique participant cohorts that included 1735 children. The search revealed many studies focused on the first year of life, of which a large proportion investigated approaches to increase communication. We provide implications, limitations, and future directions on how behavioral interventions for infants and young toddlers can inform current practice and future intervention research this population.

Humans

AI-enabled viral genomics: from virus discovery to host prediction and emerging variant forecasting.

The rapid expansion of metagenomic sequencing has generated vast repositories of viral sequence data that far outpace our capacity to interpret them using conventional approaches. Highly divergent sequences, sparse functional annotation, and taxonomically uneven sampling present fundamental challenges for reference-dependent methods, which lose sensitivity precisely for novel and understudied viruses with high public health relevance. Artificial intelligence (AI) provides a new avenue to address these challenges by enabling predictive inference from viral genomes and proteins while reducing dependence on sequence similarity. In this Review, we discuss representative advances in AI for virus discovery, taxonomic classification and functional annotation, prediction of host range and zoonotic potential, and efforts toward forecasting emerging variants. These advances are transforming viral genomics from a largely descriptive discipline into one with increasing predictive capability. We also critically assess the major challenges that constrain current approaches, including the availability of high-quality and representative datasets, rigorous model evaluation, biological interpretability and responsible governance for increasingly capable AI models.

Artificial Intelligence

Making waves: toward systems-level interpretation of hormonal and endogenous biomarkers in wastewater-based epidemiology.

Wastewater-based epidemiology (WBE) has proven invaluable for population health monitoring, most notably during the COVID-19 pandemic. Yet current WBE largely relies on exogenous markers such as drugs, pathogens, and their metabolites, limiting surveillance to what communities are exposed to. We argue for expanding WBE towards endogenous biomarkers, particularly hormones, which provide insights into physiological stress, metabolic function, and endocrine activity. Hormone-based WBE offers new opportunities to capture population-level biological responses to societal and environmental stressors, disasters, and chronic disease burdens at the community scale. This perspective outlines a systems-level framework for integrating hormonal signals in wastewater with clinical data, behavioral indicators, environmental factors, and digital markers to support more robust and context-aware public health surveillance. We highlight key technical considerations, interpretive challenges, and opportunities for translational pilot studies. By moving beyond exposure tracking toward more integrated interpretation of biological responses, hormone-informed WBE may contribute to more resilient, inclusive, and actionable public health infrastructure.

Humans

Effect of semaglutide on kidney outcomes in the SELECT, FLOW, and SOUL trials: a prespecified pooled analysis.

BACKGROUND: The GLP-1 receptor agonist semaglutide reduces clinically important kidney outcomes in people with type 2 diabetes and chronic kidney disease (CKD). We aimed to assess the pooled effects of semaglutide on kidney outcomes in prespecified analyses of participant-level data from the diverse populations of the SELECT, FLOW, and SOUL randomised placebo-controlled trials. METHODS: Participants with CKD (FLOW) or atherosclerotic cardiovascular disease (SELECT and SOUL) were randomly assigned semaglutide (once-weekly subcutaneous 1&#xb7;0 mg [FLOW], once-weekly subcutaneous 2&#xb7;4 mg [SELECT], or once-daily oral 14 mg [SOUL]) or matching placebo, added to standard of care. The primary outcome in this pooled analysis was time to first occurrence of a kidney composite, defined as onset of persistent 50% or greater reduction in estimated glomerular filtration rate (eGFR), kidney failure (persistent eGFR <15 mL/min per 1&#xb7;73 m2, or initiation of kidney replacement therapy), kidney-related death, or cardiovascular-related death. Safety was also assessed. FINDINGS: The pooled participants from the trials (N=30&#x2008;787) had a mean follow-up of 39&#xb7;5-47&#xb7;5 months. Among participants assigned to semaglutide, 973 first events of the primary kidney composite occurred compared with 1134 first events for placebo (hazard ratio [HR] 0&#xb7;84 [95% CI 0&#xb7;77-0&#xb7;91]). First events of a narrower secondary kidney composite (excluding cardiovascular-related death from the primary outcome) were also reduced with semaglutide versus placebo (347 and 416, respectively; 0&#xb7;80 [0&#xb7;69-0&#xb7;92]). Safety outcomes were overall similar between groups, and in line with other GLP-1 receptor agonist trials. Serious adverse events were numberically lower with semaglutide than with placebo. INTERPRETATION: Data pooled from three large phase 3 trials suggest that semaglutide reduces the risk of major kidney outcomes in a broad population with cardio-kidney-metabolic disease while having a favourable risk-benefit profile. In people with cardio-kidney-metabolic disease, with and without diabetes, semaglutide (oral or injected) prevents kidney-related and cardiovascular complications and induces adverse events in line with GLP-1 receptor agonist studies, regardless of baseline characteristics within the cardio-kidney-metabolic spectrum. This was a participant-level analysis conducted in a large database of three randomised controlled trials of similar design and examining the same treatment, but there were some differences in participants' baseline characteristics, and in the dose and route of administration of treatment. This pooled analysis adds evidence for the benefit of GLP-1 receptor agonists in general, and semaglutide in particular, in a broad population of people with cardio-kidney-metabolic disease, suggesting that the benefit of semaglutide might not be explained only by its glycaemic effects, weight-management effects, or both. FUNDING: Novo Nordisk.

Humans

Psychiatric mental health nurse practitioner outcomes after completion of a 1-year postgraduate fellowship.

Psychiatric mental health nurse practitioners (PMHNPs) are an essential and growing part of the health care workforce, especially in community settings. To address PMHNPs' increasing presence in community psychiatry, a 1-year postgraduate PMHNP fellowship in community psychiatry was developed with the goals of enhancing clinical competency and employment retention in underserved public sector settings. Data on 5 cohorts and 31 fellows are presented in this article. PMHNP fellows, preceptors, didactics, and clinical sites were evaluated across several time points including baseline and 6 and 12 months. The program has graduated 100% of fellows with largely positive feedback. Fellows reported significant improvements in competency across the domains of 1) assessment and diagnosis, 2) treatment, and 3) professionalism and leadership. These items were substantiated by clinical preceptors' ratings of fellows' clinical skills from 6-month and 12-month time points. Relatedly, clinical sites, preceptors, and didactics were all rated highly by fellows. After the program, 90.3% of graduates remained working in the public sector including correctional settings, community clinics, and safety net hospitals.

Community psychiatry

Functional role and regulatory network of miR-22-3p in chicken hepatic lipid metabolism.

Although microRNA-22-3p (miR-22-3p) is abundantly expressed in the avian liver, its epigenetic role in lipid homeostasis remains largely uncharacterized. To elucidate its in vivo function, 14-day-old female Qingyuan Partridge chickens were intravenously injected with lentiviral vectors to establish miR-22-3p overexpression and knockdown models. Phenotypic analysis demonstrated that miR-22-3p knockdown significantly elevated hepatic triglyceride (TG) levels (p&#xa0;<&#xa0;0.05) and drove marked steatosis, whereas its overexpression reduced TG content. Transcriptome sequencing (RNA-Seq) revealed profound metabolic remodeling, identifying 23 core lipid-associated genes (e.g., ELOVL6, FADS2, ACSBG2, and PTGIS) heavily enriched in steroid biosynthesis, fatty acid metabolism, and elongation pathways. In conclusion, miR-22-3p functions as a bidirectional epigenetic rheostat that negatively regulates hepatic lipid deposition by orchestrating a multilayered polygenic network, providing novel molecular targets for mitigating avian metabolic disorders and optimizing production traits in indigenous poultry breeds.

Animals

Boosting kynurenic acid in kombucha via substrate selection: metagenomic and biochemical insights.

Kombucha is gaining global popularity for its health benefits. This study explored the use of chestnut honey, a rich source of kynurenic acid (KYNA), to produce kombucha enriched with this metabolite. Five variants were prepared using different green/black tea blends and carbon sources: white sugar or acacia honey (controls) versus chestnut honey. Samples were analyzed for tryptophan metabolites, physicochemical properties, and microbial diversity. Komagataeibacter and Enterobacter were predominant bacterial genera in SCOBY. Candida and Aspergillus were predominated in the single sample analyzed for fungi. During fermentation, tryptophan decreased, while kynurenine increased. KYNA levels remained largely stable during fermentation and were mainly influenced by the fermentation substrate. No melatonin pathway derivatives were detected. On day 7, chestnut honey yielded kombucha with 381.680-739.915&#xa0;&#x3bc;mol/L KYNA and elevated myricetin. Overall, chestnut honey-based kombucha represents a system in which substrate composition appears to be the main factor influencing KYNA levels in the final beverage.

Kynurenic Acid

Epigenetic drift and LINE-1 activation in aging brain: Implications for neurodegenerative disease.

Brain aging and age-associated neurological diseases, such as Alzheimer's Disease (AD), Parkinson's Disease (PD), and Amyotrophic Lateral Sclerosis (ALS), are largely attributed to epigenetic drift which is characterized by the gradual accumulation of alterations in neural cell methylation patterns over time. These methylation changes are particularly evident in transposable element (TE)-derived sequences such as Long interspersed element-1 (LINE-1) which comprises approximately 17% of the human genome. During aging, LINE-1 elements gradually lose their methylation, as well as the regulatory safeguard mechanisms that usually keep them inactive. This repression loss can lead to LINE-1 reactivation, contributing to harmful effects including genomic instability, neuroinflammation, and more. Together these findings indicate that impaired epigenetic maintenance, especially in repetitive genome regions, plays a key role in biological aging of neurons and glial cells. In this narrative review, we discuss the methylation dynamics and regulatory mechanisms of LINE-1 retrotransposons, their activation processes during aging, and contribution to age-associated neurological diseases. We also highlight the potential of targeting LINE-1 methylation to restore methylation homeostasis, epigenetic stability and delay brain aging.

Humans

Food-derived extracellular vesicles as delivery platforms for medicine-food homology components in metabolic syndrome.

Diet-induced obesity and associated metabolic syndromes have become major global public health challenge, highlighting the urgent need for safe and effective strategies. Recently, food-derived extracellular vesicles (FDEVs) have garnered increasing attention as natural nanocarriers due to their excellent biocompatibility and specific targeted delivery capabilities. FDEVs can efficiently deliver medicine-food homology components (MFHCs) to precisely regulate lipid metabolism, inflammatory responses, and insulin sensitivity, thereby improving obesity and its metabolic abnormalities. This systematic review summarizes recent advances in the use of FDEVs as delivery vehicles for MFHCs to suppress diet-induced obesity and metabolic syndrome, with a particular focus on the underlying molecular mechanisms, including signaling pathway regulation and cellular metabolic remodeling. In addition, the clinical translational potential and industrial application prospects of FDEVs are evaluated, and key challenges related to preparation techniques, safety assessment, and large-scale production are discussed. By integrating current evidence, this review aims to provide theoretical framework and future perspectives for the development of FDEVs as a novel targeted delivery platform and treatment of metabolic diseases.

Extracellular Vesicles

Oxidative potential of fresh vs. O&#x2083;-aged PM2.5 across urban and rural sources in China.

Fine particulate matter (PM2.5) is a major health risk, yet its impacts are still largely assessed using mass concentration, which does not capture toxicity. Recently, oxidative potential (OP) has emerged as a more relevant metric, reflecting the ability of particles to generate reactive oxygen species. A current challenge, especially in China, is understanding how emission sources and ozone (O3) aging affect PM2.5 toxicity, given that O3 is an increasingly important pollutant there. A work by Ma and co-workers published in J. Environ. Sci. (doi.org/10.1016/j.jes.2024.04.023) addressed this by evaluating the OP of fresh and O3-aged PM2.5 from multiple sources in China using the dithiothreitol (DTT) assay. Biomass burning particles exhibited the highest OP, up to 35 times greater than suburban PM2.5, driven by water-soluble organics and transition metals. While O3 aging generally reduced OP, it also induced complex chemical transformations. These findings highlight that PM2.5 toxicity is dynamic and source-dependent, underscoring the need to move beyond mass-based air quality metrics.

Particulate Matter

Insights into the regulation of the HOTAIR proximal promoter.

HOTAIR (HOX transcript antisense RNA) is a HOXC-cluster long intervening non-coding RNA (lincRNA) whose cancer relevance is tightly coupled to how its transcription is wired into hormone, hypoxia, inflammatory, and developmental signaling. HOTAIR is known to associate with cancer cell proliferation, motility, tumor invasion, and metastasis. The present mini-review focuses on the regulatory architecture and mechanistic complexity of HOTAIR transcriptional regulation, with emphasis on three organizing principles. First, we consider the impact of promoter choice between a canonical proximal promoter (P1), which supports the 2.2-2.4 kb transcript, and an alternative upstream promoter/TSS (P2), which contributes to context-dependent transcription initiation. Second, we examine the long-distance enhancer-promoter communication between HOTAIR distal enhancer and P1/P2. Third, we summarize the recent epigenetic and epi-transcriptomic mechanisms involved in HOTAIR transcript initiation and elongation. A combination of these events determines isoform-specific transcription to govern cell-type-, context-, and cancer specific modulation of HOTAIR expression that promotes tumor formation and cancer progression. Finally, the review proposes how large-scale RNA datasets, long-read sequencing, and isoform-specific studies can refine our understanding of this versatile lincRNA's regulation.

Humans

LC-IMS-MS profiling of avocado acetogenins reveals tissue-dependent distribution and cultivar-specific metabolic signatures.

This study presents a comprehensive characterisation of acetogenin-related metabolites in avocado using an LC-IMS-MS workflow. A total of 26 metabolites were semi-quantified across peel, pulp and seed tissues from three cultivars (Hass, Bacon and Fuerte). The integration of ion mobility spectrometry enabled the generation of the first experimental database of collision cross section (CCS) values for avocado acetogenins, improving confidence in metabolite annotation. Results revealed a pronounced tissue-dependent distribution, with seeds and pulp as the primary reservoir of several acetogenins, whereas the peel consistently exhibited lower concentrations. In contrast, acetogenin levels remained largely stable throughout ripening. Clear cultivar-dependent differences were observed, with Hass displaying a distinct metabolic profile compared to Bacon and Fuerte. Multivariate analysis confirmed these findings, showing tissue-dependent cultivar differentiation. This study provides new insights into avocado chemical diversity and highlights the potential of avocado by-products as consistent and promising sources of bioactive acetogenins.

Persea

Loneliness and Personality: Noise- and Bias-Free True Correlations Between Loneliness and the Big Five Personality Domains.

OBJECTIVE: While loneliness is intertwined with many mental and physical health problems, its origins are not yet well understood. We sought to better understand its link to personality in a large national cohort. METHODS: Combining self- and informant ratings in multiple samples, we conducted the largest study to date to examine loneliness' true correlations (rtrues) with the Big Five personality traits, free of single-method biases and transient and random errors. RESULTS: Across three samples (Estonian-speaking, N&#x2009;=&#x2009;20,893; Russian-speaking, N&#x2009;=&#x2009;762; English-speaking, N&#x2009;=&#x2009;599), we found a strong relationship between loneliness and Neuroticism (rtrue&#x2009;=&#x2009;0.60-0.70). Loneliness also had robust but much weaker associations with Extraversion (rtrue&#x2009;=&#x2009;-0.20 to -0.30), and only weak associations (rtrue&#x2009;=&#x2009;0.10 to -0.20) with Agreeableness, Conscientiousness, and Openness. Collectively, the Big Five accounted for over 50% of loneliness variance. In a subsample, the associations were only slightly smaller longitudinally over approximately 10&#x2009;years. CONCLUSION: Overall, feeling lonely is more closely related to Neuroticism than previously understood, and the association endures over time.

Humans

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.&#xa0;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

Nephropathies Associated with Sickle Cell Trait and How to Study Them.

Sickle cell trait (SCT), which carries a single point mutation in the hemoglobin-&#x3b2; (HBB) gene, has long been considered a benign condition. However, epidemiological evidence challenges this assumption, revealing that individuals with SCT face an elevated risk of renal dysfunction. However, this field of study remains ill-defined as it has focused on sickle cell disease (SCD), where renal complications are severe. As SCT is more prevalent than SCD, consequences of nephropathies in this group translate into a substantial and largely unaddressed public health burden. Clinical data, primarily observational, implicate age and sex in the development of SCT-associated nephropathies. These manifestations span glomerular hyperfiltration, tubular damage, hematuria, renal papillary necrosis, renal medullary carcinoma, and progression to chronic kidney disease, all complications that cluster disproportionately in older male individuals. Despite this, the mechanistic basis of SCT nephropathy, the thresholds at which renal injury becomes clinically significant, and the optimal strategies for early identification and prevention remain inadequately defined. In vitro studies have primarily focused on SCD blood cell biology, with SCT receiving comparatively little attention. Humanized murine models (i.e., Berkeley and Townes) have recapitulated some SCT-associated renal phenotypes but need to be more fully characterized. This review aims to provide an overview of the biology of sickle cell trait nephropathies, the gaps in our knowledge, and the model systems we can use to fill those gaps.

Journal Article

Morphology-Encoded Colorimetric Hydrogen Sensing Using Embedded Reactive Pd Absorbers in Fabry-Perot Cavities.

Chemical reactions offer a powerful strategy for generating visible optical responses through localized changes in absorption, dielectric environment, and interfacial wetting. A palladium (Pd)-embedded Fabry-Perot cavity is introduced as a reaction-active optical platform in which structural color is governed by intracavity absorption coupled with reaction-induced dielectric perturbation. Positioning Pd within the dielectric spacer creates a spatially controllable reactive absorber whose vertical location relative to the standing-wave field dictates wavelength-selective absorption within the cavity. The morphology of the embedded Pd layer provides an additional design parameter by modulating both optical loss and interfacial wetting. Under hydrogen exposure in the presence of oxygen, catalytic water formation at the Pd/polymer interface generates localized dielectric heterogeneity and interfacial water droplets, thereby perturbing the optical path length and amplifying the visible response. As a result, the cavity exhibits pronounced, morphology-dependent color transitions that are inaccessible through dielectric-layer engineering or Pd/PdH refractive-index changes alone, enabling direct visual hydrogen sensing under ambient light, as well as flexible optical devices capable of large-area patterning. These findings establish a design framework for reaction-active optical cavities that translate localized chemistry into a colorimetric hydrogen sensing mechanism.

Fabry&#x2013;Perot resonator