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PubMed2026

Multi-omics panorama of glaucoma: Pathogenesis, biomarkers, and novel therapeutic strategies.

Glaucoma is a group of irreversible, blinding eye diseases characterized by progressive loss of retinal ganglion cells, leading to gradual visual field defects that severely impact patients' quality of life. Its complex pathophysiological mechanisms remain incompletely understood, limiting the development of early diagnostic and effective therapeutic strategies. Advances in omics technologies have provided new insights into elucidating the pathophysiology of glaucoma. We summarize specific alterations in genomics, transcriptomics, proteomics, metabolomics, epigenomics, and microbiomics associated with glaucoma. We emphasize the systematic analysis of disease mechanisms, identification of clinically applicable biomarkers, and discovery of novel therapeutic targets through the integration of these data. This approach paves new pathways for glaucoma subtype diagnosis and personalized treatment, while also outlining future research directions and challenges.

Humans↗

PubMed2026

Ribosomal protein S3: a critical regulator of human disease mechanisms.

Ribosomal protein S3 (RPS3) is an essential structural component of the 40S ribosomal subunit, yet growing evidence highlights crucial extraribosomal roles in genome maintenance, cell-cycle control, and immune signaling. Dysregulation of RPS3 contributes to diverse human disorders, including cancer, inflammatory diseases, neurodegeneration, and resistance to antimicrobial and anticancer therapies. As a cofactor of NF-κB and a participant in DNA damage responses, RPS3 occupies a node that integrates stress signaling with transcriptional reprogramming, enabling both protective and pathological outcomes. The present review critically evaluates mechanistic insights into RPS3 biology, emphasizing recent findings that delineate its context-dependent effects, discrepancies across models, and remaining gaps that restrict translational applications. Understanding these complexities is essential to assess RPS3's potential as a biomarker and therapeutic target.

Humans↗

PubMed2026

Community-driven advances in computational mass spectrometry: The perspective of EuBIC-MS members.

Advances in data acquisition, artificial intelligence, and integrative bioinformatics are driving the rapid evolution of computational mass spectrometry, and in turn, transforming modern proteomics, metabolomics, and lipidomics. These developments have greatly increased the scale and complexity of mass spectrometry data, underscoring the importance of evolving accurate, transparent, efficient and reproducible data processing workflows. Addressing these challenges requires collaborative innovation that brings together expertise in software engineering, statistics, and biology. The European Bioinformatics Community for Mass Spectrometry (EuBIC-MS), an initiative of the European Proteomics Association (EuPA), fosters a culture of open, community-driven development through its biennial Developers Meetings and Winter Schools. This commentary summarizes the scientific background and outcomes of the EuBIC-MS Developers Meeting 2025, which took place in Novacella, Italy. Three keynote presentations highlighted major frontiers in the field: deep proteome and phosphoproteome profiling, text mining for protein-protein interaction extraction, and scalable proteomics for AI-driven drug discovery. Seven community-selected hackathons addressed emerging challenges such as single-cell proteomics data analysis, FAIR metadata extraction, deep learning frameworks, R-Python interoperability, and DIA validation. Together, these efforts demonstrate the potential for scientific and technical innovation to arise from open collaboration, and highlight how community-driven initiatives can accelerate progress in computational mass spectrometry. SIGNIFICANCE: Modern proteomics increasingly depends on computational advances to translate complex, high-dimensional data into biological knowledge. The EuBIC-MS Developers Meeting 2025 exemplifies how community-driven collaboration can directly accelerate this process by bringing together experts from bioinformatics, statistics, and experimental proteomics to co-develop open, interoperable, and reproducible analytical tools. By fostering shared software frameworks, transparent benchmarking, and collaborative problem solving, the EuBIC-MS community helps ensure that technological innovation translates into reliable biological insights. This collaborative model strengthens the foundation for quantitative, system-level understanding of proteomes and establishes a sustainable path for integrating artificial intelligence and next-generation data acquisition into routine biological discovery. This commentary shows some current highlights in the field of computational mass spectrometry and community-based approaches undertaken during the most recent Developers Meeting to solve these challenges. The approaches discussed and initiated during the meeting - ranging from deep proteome profiling and phosphosite mapping to text mining, single-cell data analysis, and FAIR metadata extraction - address key bottlenecks that currently limit the biological interpretability and comparability of proteomics data.

Mass Spectrometry↗

PubMed2026

Obesity in obstetric anesthesia: A systematic review.

Maternal obesity presents complex challenges for anesthetic management, with implications spanning neonatal, cardiovascular, airway, neuraxial, and procedural domains. This review synthesizes evidence on how elevated maternal body mass index (BMI) impacts perioperative evaluations, risks, complications, and outcomes, in addition to anesthetic modalities and efficacy in the pregnant population. Given the increasing global prevalence of maternal obesity, anesthesiologists must refine clinical practices, employing tailored, evidence-based strategies to mitigate risks and enhance patient outcomes. This review aims to provide anesthesiologists and obstetricians with key considerations and best practices for managing obstetric anesthesia patients with obesity. Clinical recommendations herein are based on current research and evaluated using Oxford Centre for Evidence-Based Medicine for level of evidence and class of recommendation.

Humans↗

PubMed2026

Navigating Social Media: Balancing Connectivity With Media Literacy to Combat Misinformation and Protect Mental Well-Being.

BACKGROUND: The pervasive use of social media has created a complex digital ecosystem where high connectivity coexists with significant challenges, including the rapid spread of misinformation, particularly regarding mental health, and documented negative impacts on psychological well-being. Platform architectures designed for engagement maximization have been identified as central factors in both issues. OBJECTIVE: This paper critically analyzes the interconnected relationships between social media use, misinformation dissemination, and mental health impacts, with particular attention to psychiatric misinformation across diagnostic categories (e.g., depression, anxiety, ADHD). A primary objective is to evaluate the potential of advanced critical digital literacy frameworks to serve as protective mechanisms against these dual threats. METHODS: A systematic search was conducted following PRISMA 2020 guidelines across APA PsycInfo, PubMed, JSTOR, and Google Scholar for literature published between January 2018 and March 2026 (updated from the original 2023 search). The search yielded 2672 records. After removing 624 duplicates, 2048 records underwent title and abstract screening, with 1802 excluded. The remaining 246 full-text articles were assessed for eligibility, resulting in 86 studies included in the final qualitative synthesis. Inter-rater reliability was established (Cohen's κ = 0.82). Quality assessment was conducted using the Joanna Briggs Institute Checklist, AXIS, and CASP tools, with findings weighted by methodological quality. A thematic analysis was undertaken to synthesize findings. RESULTS: The analysis reveals that core architectural features of social media platforms, algorithmic curation and engagement-based metrics, simultaneously foster environments ripe for misinformation spread and contribute to psychological distress, including anxiety, depression, and harmful social comparison. Psychiatric misinformation specifically (e.g., inaccurate claims about treatment effectiveness, diagnostic criteria, and medication side effects) represents a growing concern, particularly on image- and video-based platforms. The findings indicate that conventional media literacy approaches focused solely on fact-checking are insufficient. Instead, a critical digital literacy framework encompassing algorithmic awareness, data literacy, and emotional awareness is essential for building user resilience, with evidence from high-quality systematic reviews supporting this approach. CONCLUSIONS: Navigating the complexities of modern social media requires an integrated approach combining "pedagogies of play" for experiential skill development with advocacy for structural change (e.g., algorithmic transparency, well being by design principles). This dual strategy empowers individual users to critically engage with digital content while advocating for ethical platform design, thereby safeguarding both mental well-being and democratic discourse. Implications for educators, mental health professionals (including competencies for addressing patient encounters with psychiatric misinformation), policymakers, and platform designers are discussed.

Humans↗

PubMed2026

Cooperative anaerobic catabolism of chlorinated organic compounds: implications for sustainable bioremediation.

Biodegradation research historically followed a reductionist approach focused on axenic (pure) cultures capable of catabolizing the specific contaminant(s) of interest. While this approach has substantially advanced our understanding of the microbiology, physiology, biochemistry, and genetics of contaminant degradation under laboratory conditions, it does not capture the complexity of natural and engineered environments. During in situ bioremediation, microbiomes are exposed to mixtures of contaminants, and microbial interactions profoundly influence contaminant transformation and fate. In anoxic environments, degradation of chlorinated compounds is often sustained by metabolic cooperation among taxonomically and physiologically distinct microorganisms. Through the exchange of metabolites such as hydrogen, formate, acetate, and other nutrients, microbial populations establish interdependent networks that overcome thermodynamic and physiological constraints, enabling self-sustaining systems of contaminant transformations that would be inefficient or impossible with individual organisms. We highlight examples of microbial interactions that underpin anaerobic catabolism of chlorinated contaminants, including systems resulting in self-sustained anaerobic bioremediation.

Biodegradation, Environmental↗

PubMed2026

Exploring Professional Experiences in Caring for Vulnerable Migrants in an Italian Rural Reception Centre: A Qualitative Study Using Multidimensional Textual Analysis-Professional Experiences in Rural Migrant Care.

AIM: This study aims to explore the experiences, strengths, challenges, and potential improvements for professionals in managing the complex needs of vulnerable migrants (VM) in an Italian rural reception centre. METHODS: A qualitative study using semi-structured interviews was conducted in April 2024. Data were analysed using the Automatic Analysis of Textual Data, based on Fraire's seven-step model for Exploratory Multidimensional Data Analysis. DATA SOURCES: Data were collected from 16 professionals working in a rural reception centre in southern Italy. Interviews were conducted and analysed using AATD in April 2024. FINDINGS: The analysis identified two main dimensions of professionals' roles: balancing systemic responsibilities with personal engagement and managing immediate needs versus long-term integration goals. Professionals face significant challenges, such as resource scarcity, bureaucratic inefficiencies, and emotional fatigue, which impact their well-being and the quality of care provided to migrants. Resilience, adaptability, and multidisciplinary collaboration were identified as key strengths. CONCLUSION: The study highlights the dual nature of professionals' work in reception centres, requiring them to balance operational tasks with emotional involvement in migrant care. Targeted interventions and systemic reforms are necessary to support professionals and enhance the quality of care for vulnerable migrants, particularly in resource-constrained rural settings. IMPLICATIONS FOR PRACTICE AND/OR PATIENT CARE: This study underscores the importance of providing targeted support to professionals working in reception centres, including training in intercultural competence, stress management, and coping strategies. Policies should address systemic challenges and provide resources to enhance healthcare delivery and social integration programs. REPORTING METHOD: This study adhered to the EQUATOR guidelines for reporting qualitative research (COREQ). The findings were reported in compliance with these guidelines, ensuring methodological rigour and transparency. PATIENT OR PUBLIC CONTRIBUTION: No patient or public contribution. IMPLICATIONS FOR THE PROFESSION AND/OR PATIENT CARE: This study highlights the critical need for targeted support and training for professionals working in reception centres, particularly in rural settings. To improve care for vulnerable migrants, professionals should receive training in intercultural competence, stress management, and coping strategies to better navigate the complex challenges they face. Furthermore, systemic changes are necessary to alleviate the pressures on reception centres, such as streamlining bureaucratic processes and enhancing healthcare infrastructure, particularly in rural areas where resources are limited. By addressing these needs, we can improve the well-being of both the professionals and the migrants they serve, fostering more effective support systems and better care outcomes. Additionally, fostering multidisciplinary collaboration and community engagement can contribute to more comprehensive and sustainable care models. PROTOCOL REGISTRATION: The Ethics Committee of the University of Rome Tor Vergata approved this study on 07/07/2021 (protocol registration number 160.21).

Humans↗

PubMed2026

Spatial transcriptomics of Ciona adult brains reveals functional zonalization and insights into neural gland function.

The ascidian Ciona is a pivotal chordate model for illuminating the evolutionary origins of the vertebrate brain. Here, spatial transcriptomics of the adult Ciona neural complex, combined with image-based computational super-resolution mapping, resolved distinct tissue domains including the cerebral ganglion, neural gland, ciliated funnel, neural gland duct/dorsal strand, and body wall muscle. Within the cerebral ganglion, high-resolution mapping revealed clear molecular zonalization separating the cortex and medulla, alongside regional specialization within the cortex itself. The neural gland exhibited localized enrichment of genes associated with extracellular matrix and cell-cell interactions. These spatial features suggest that the neural gland functions as a homeostatic and signaling interface, reminiscent of primitive vertebrate meninges or choroid plexus. Overall, this spatially defined gene expression map provides a foundational framework for understanding functional regionalization in the tunicate brain and its evolutionary relationship to vertebrate nervous systems.

Ciona↗

PubMed2026

Clinical Efficacy and Learning Curve of Far-Lateral Approach (FLA) in Uni-Portal Non-Coaxial Spinal Endoscopic Surgery (UNSES) in the Treatment of Lumbar Degenerative Diseases: A Prospective Study.

BACKGROUND: Uniportal non-coaxial spinal endoscopic surgery (UNSES) via far-lateral approach (FLA) is an innovative minimally invasive procedure for lumbar degenerative diseases, particularly far-lateral disc herniation and foraminal stenosis. However, complex lateral lumbar anatomy and strict endoscope-instrument coordination create a distinct learning curve that may compromise early surgical efficiency and safety. This study aimed to evaluate the efficacy and safety, quantify the learning curve, and to provide clinical guidance for the standardized promotion and application of this technology. METHODS: A total of 40 consecutive patients with lumbar degenerative diseases who underwent UNSES via FLA by a single surgeon between January 2025 and December 2025 were included. All data were analyzed using SPSS 26.0 statistical software (IBM, USA). Primary outcomes included operation time, blood loss, fluoroscopy frequency, and intraoperative complication rate. Secondary outcomes were VAS, ODI, and modified Macnab criteria at 1, 3, and 6 months postoperatively. The learning curve and the inflection point of the learning curve was determined using cumulative sum (CUSUM) analysis. The differences in clinical indicators between early and proficient stage were compared. RESULT: Operation time, blood loss, and fluoroscopy times decreased significantly with case accumulation (p < 0.05). CUSUM identified an inflection point at the 16th case, after which operation time stabilized at (55.3 ± 8.6) min, much shorter than the early phase (89.5 ± 10.3) min (p < 0.001). Before the 16th case, the curve was in an upward trend; after the 16th case, the curve tended to be flat, indicating the proficiency stage. Postoperative VAS and ODI improved significantly than those before surgery at each follow-up time (p < 0.05). There was no significant difference in postoperative VAS score and ODI between the two groups at each follow-up time point (p > 0.05). The total complication rate was 12.5% (5/40), were cured by conservative treatment. The total excellent-good rate was 90.0% (36/40). L5/S1 and Bertolotti's syndrome were independent factors affecting the learning curve. CONCLUSION: UNSES via FLA is a safe and effective minimally invasive technique for treating complex lumbar degenerative diseases. It has a certain learning curve, and the inflection point is about the 16th case. After mastering the key techniques such as anatomical positioning, endoscopic manipulation and hemostasis, the surgeon can gradually reach the proficiency stage, with significantly improved surgical efficiency and clinical efficacy, and controllable complications. This study provides a theoretical basis for the clinical training and technology promotion of UNSES via FLA.

Humans↗

PubMed2026

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↗

PubMed2026

Whole-Genome Deep Learning Predicts Chemotherapy Response in Colorectal Cancer.

Chemotherapy response in colorectal cancer (CRC) exhibits significant heterogeneity, with current clinical predictors failing to capture complex genomic determinants of resistance. We developed a hybrid deep learning framework integrating convolutional neural networks (CNNs) and bidirectional long short-term memory (BiLSTM) networks to analyze whole-genome somatic mutations, evolutionary conservation, chromatin accessibility, and 3D genome architecture in 2,546 TCGA patients. An attention mechanism identified predictive genomic regions. The model achieved an AUC of 0.92 (95% CI: 0.89-0.94) in cross-validation and 0.88 (95% CI: 0.85-0.91) in independent validation, outperforming clinical models (ΔAUC = +0.18, p < 0.001). Key predictors included non-coding variants in TP53, KRAS, and PIK3CA regulatory regions. Triple-positive patients (mutations in all 3 regions) had significantly worse progression-free survival (HR = 4.7, p < 0.001). Our framework enables accurate chemotherapy response prediction and reveals novel non-coding resistance mechanisms, advancing precision oncology in CRC.

Humans↗

PubMed2026

Loss, persistence and reversal of phenotypic traits.

The irreversibility of complex trait loss has long been a tenet of evolutionary biology. However, this idea is increasingly at odds with the numerous documented exceptions across the Tree of Life. We synthesise this growing body of evidence across a diverse array of taxa and traits, exploring the evolutionary conditions that enable evolutionary reversal. By integrating macroevolutionary, genetic, and developmental information, we argue that trait reversal is commonly fostered by some form of persistence in the generative developmental pathway of the lost trait. We identify three overarching modes of trait reversal and support them with multiple case studies: by pleiotropy (the involvement of the same generative components in other traits and/or functions), by plasticity (environment-dependent expression of the trait) and by hemiplasy (persistence in another lineage, followed by reticulate evolution). We also examine important affinities between trait reversal and evolutionary novelties, undermining a neat distinction between what is old and what is new in evolution. This survey may provide a useful framework for future explorations of the developmental mechanisms underlying these still overlooked macroevolutionary dynamics.

Phenotype↗

PubMed2026

Pilot Distractions and Interruptions in Airlines: Ranking of Sources by Analytic Hierarchy Process.

ObjectiveThis work establishes a methodological framework for sources of pilot distraction and interruptions in a structured model that can be used as a tool for cockpit design/procedure assessment.BackgroundPilots must complete complex tasks, and distractions can impair performance and lead to errors that can cause aircraft accidents. Although various cockpit distractors are examined individually, there is no integrated approach.MethodDistraction and interruption sources were identified through a literature review and confirmed/extended by interviews with airline pilots. Associated weights were determined through pairwise comparisons, yielding a hierarchical model using the Analytic Hierarchy Process.Results26 sources of pilot distraction and interruptions were quantified and categorized into four categories: communication, head-down time, responding to abnormal conditions & unexpected situations, and searching for traffic.ConclusionA taxonomic structure for assessment is achieved with the top 5 sources identified as communications, technical interruptions, experience in type, environmental factors, operational irregularities, and airspace high terrain, accounting for 63.07%.ApplicationThe structured system is a flexible assessment scale that provides a taxonomic framework for airline risk management, supports future research, and cockpit design efforts.

Humans↗

PubMed2026

Mechanisms of Hematopoietic Stem Cell Aging and Emerging Rejuvenation Strategies.

Hematopoietic stem cell (HSCs) aging is a complex biological process driven by both cell-intrinsic alterations and extrinsic cues from the bone marrow niche. Understanding these mechanisms is critical for developing therapies against aging-related hematopoietic disorders. This review synthesizes recent advances in the molecular mechanisms underlying HSCs aging, including microenvironmental aging, genomic instability, epigenetic dysregulation, mitochondrial dysfunction, and aberrant nuclear mechanotransduction. We summarize that the functional decline of HSCs during aging drives a compensatory expansion of the phenotypically defined stem cell pool, leading to an aberrant increase in cell number. We also highlight aging-associated HSCs heterogeneity, including CD150high and P-selectin-positive subsets that enrich for myeloid-biased or functionally compromised HSCs states while emphasizing that surface phenotype alone may not fully indicate functional rejuvenation. Finally, we discuss emerging rejuvenation strategies-including targeting myeloid-biased HSCs, modulating inflammatory pathways, and implementing epigenetic or metabolic interventions-supported by cutting-edge technologies such as single-cell multi-omics, gene editing, and computational modeling. These approaches hold promise for counteracting age-related hematopoietic decline and restoring immune competence.

Humans↗

PubMed2026

Metal-organic frameworks nanozyme-integrated portable microneedle patch for visual bacterial monitoring in meat.

Foodborne microbial contamination is a major global health concern, with conventional methods often being time-consuming and complex. Herein, we developed a novel portable biosensor by integrating microneedle patch technology and a metal-organic framework (Fe/Cu-NBDC MOF) nanozyme, enabling rapid, on-site, visual detection of bacteria in meat. The sensing system works by encapsulating aptamer-functionalized MOF nanozymes within a hydrogel patch, where their catalytic sites are initially blocked by the aptamer. In the presence of Staphylococcus aureus (S. aureus) as the target, the specific aptamer's binding to bacteria exposes numerous catalytic sites, further activating the chromogenic reaction of the tetramethylbenzidine‑hydrogen peroxide (TMB-H₂O₂) system, enabling visual detection of S. aureus. The biosensor demonstrates a detection limit of 82 CFU/mL with excellent specificity to successfully apply to commercial mutton. By integrating sampling, enrichment, and visual detection into a single compact device, this platform offers a practical, efficient solution for rapid on-site screening of foodborne pathogens.

Biosensing Techniques↗

PubMed2026

Flavoromics-based profiling reveals taste and aroma differences between infant formula and breast milk.

Flavor differences between infant formula (IF) and breast milk (BM) are considered a potential factor affecting infants' acceptance of IF. This experiment employs flavoromics combined with multivariate statistical analysis to systematically compare the flavor profiles of IF and BM. Electronic tongue analysis and amino acid correlation revealed that IF was characterised by pronounced saltiness and umami richness, whereas BM exhibited greater bitterness and astringency. Volatile compound profiling identified five key flavor constituents in IF, predominantly aldehydes such as hexanal and pentanal. In contrast, BM contained a broader array of compounds-including acids, aldehydes, and esters-resulting in a more complex flavor profile. Kyoto Encyclopedia of Genes and Genomes (KEGG)-based metabolic pathway annotation, together with fatty acid profiling, suggested that some volatiles may be associated with lipid oxidation, Maillard reaction and sulfur-containing amino acid degradation pathways, offering a theoretical basis for the targeted optimisation of IF flavor.

Humans↗

PubMed2026

Clopidogrel vs Aspirin According to Diabetes Mellitus: A Prespecified Analysis of the SMART-CHOICE 3 Trial.

BACKGROUND: Recent trials support the superior efficacy of clopidogrel compared to aspirin monotherapy after completion of dual antiplatelet therapy (DAPT) in patients who have undergone percutaneous coronary intervention (PCI). However, limited evidence is available in patients with diabetes mellitus (DM). OBJECTIVES: This study sought to evaluate the comparative efficacy and safety of clopidogrel vs aspirin monotherapy according to the presence of DM. METHODS: This was a prespecified analysis of the SMART-CHOICE 3 trial, which was a multicenter, open-label, randomized controlled trial comparing clopidogrel vs aspirin monotherapy in patients with complex coronary lesions or high-risk clinical characteristics. From August 2020 to July 2023, a total of 5,506 patients who underwent PCI and standard DAPT duration and had complex coronary lesions, DM, or previous myocardial infarction, were randomized to clopidogrel or aspirin monotherapy groups. The primary endpoint was major adverse cardiac and cerebrovascular events (MACCE), which was defined as a composite of death from any cause, myocardial infarction, or stroke. RESULTS: Of 5,506 patients, 2,089 had DM (1,039 in the clopidogrel group and 1,050 in the aspirin group). At a median follow-up of 2.3 years (IQR: 1.6-3.0 years), DM patients had a higher risk of MACCE compared to non-DM patients (6.8% vs 4.7%; HR: 1.44, 95% CI: 1.10-1.87; P = 0.008). Clopidogrel showed a significantly lower risk of MACCE than aspirin in DM patients (4.5% vs 9.1%; HR: 0.57, 95% CI: 0.38-0.86; P = 0.008). There was no significant interaction between DM and antiplatelet monotherapy regarding MACCE (P for interaction = 0.124). The risk of bleeding was comparable between the 2 groups in DM patients (2.9% vs 2.9%; HR: 1.06, 95% CI: 0.57-1.95; P = 0.855). CONCLUSIONS: Among DM patients who completed the standard duration of DAPT after PCI, clopidogrel monotherapy was associated with a lower risk of a composite of death from any cause, myocardial infarction, and stroke compared with aspirin monotherapy, without increased rates of bleeding. There was no significant interaction between DM and antiplatelet monotherapy with respect to MACCE. (SMART-CHOICE 3 [SMart Angioplasty Research Team: CHoice of Optimal Anti-Thrombotic Strategy in Patients Undergoing Implantation of Coronary Drug-Eluting Stents 3]; NCT04418479).

Humans↗

PubMed2026

Urban Design Quality and Clinical Mental Health: A Systematic Review.

ObjectivesThis systematic review synthesizes empirical evidence on core urban design dimensions that affect clinical mental health outcomes and examines how environmental exposures mediate or moderate these relationships.BackgroundUrban design has increasingly been recognized as a determinant of psychological well-being, yet a standardized framework to evaluate its mental health impact remains underdeveloped.MethodsFollowing PRISMA 2020 guidelines, we systematically reviewed 19 quantitative empirical studies published through January 2025, examining relationships between outdoor urban design features and validated clinical mental health indicators across four major databases.ResultsFindings reveal that urban design influences clinical mental health outcomes (depression, anxiety, stress, cognitive decline) through two objective spatial scales: street-level features (imageability, enclosure, human scale, complexity) and neighborhood environments (land use mix, density, green infrastructure). Environmental exposures (traffic, noise, air pollution) operate as perceptual and experiential mechanisms that mediate or moderate the mental health effects of these spatial design features.ConclusionsWe propose an integrated three-domain conceptual framework distinguishing objective spatial design scales from subjective exposure mechanisms. This framework provides evidence-based guidance for urban planners and policymakers toward creating mentally healthier urban environments.

Humans↗