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All-inside repair is an effective treatment for medial meniscus posterior root tears: a systematic review and meta-analysis of biomechanical and clinical evidence.

BACKGROUND: Medial meniscus posterior root tears (MMPRTs) reproduce the biomechanics of subtotal meniscectomy. Repair is favored, but the role of all-inside repair (AR) remains unclear relative to transtibial pull-out (TP). This study aimed to review the biomechanical and clinical evidence on AR for MMPRTs. METHODS: A systematic review was conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines and registered in the International Prospective Register of Systematic Reviews (PROSPERO). MEDLINE, Embase, Scopus, and the Cochrane Central Register of Controlled Trials (CENTRAL) were searched. Outcomes included patient-reported outcome measures (PROMs), magnetic resonance imaging (MRI), and biomechanical performance. When available, random-effects meta-analysis was performed. RESULTS: Thirteen studies were included. AR restored contact mechanics and showed load to failure comparable to TP, with lower stiffness. Meta-analysis showed lower conversion to total knee arthroplasty with AR versus non-repair (RR 0.18, 95% CI 0.05-0.58), and no significant PROM differences between AR and TP. CONCLUSIONS: AR showed favorable biomechanical properties and improved outcomes versus non-repair. Compared with TP, no significant clinical differences were observed. AR may represent a reasonable option in selected scenarios.

Humans

The landscape of pruning for large language models: A systematic review and unified taxonomy.

Confronting the inherent tension between the exceptional capabilities and the immense computational costs of Large Language Models (LLMs), pruning has become a crucial technique for achieving efficient deployment. However, a systematic analytical framework dedicated specifically to LLM pruning remains absent. In this paper, we aim to bridge this gap. We first elucidate the theoretical foundations that underpin the effectiveness of pruning, namely overparameterization and redundancy, and then propose a multidimensional taxonomy that organizes existing approaches along the axes of granularity, timing, and criteria. Building upon this unified perspective, we further analyze performance recovery mechanisms and the broader evaluation ecosystem, while also exploring forward-looking challenges such as interpretability, automation, and hardware-algorithm co-design. Through this comprehensive synthesis, we seek to provide an integrated and coherent analytical lens for advancing both research and practice in LLM pruning.

Large Language Models

Genetic Diversity Analysis of Red Fox Populations (Vulpes vulpes L., 1758) in Natural and Anthropogenic Isolation.

This study presents a comparative analysis of the genetic structure and diversity of three red fox (Vulpes vulpes L.) populations representing different microevolutionary scenarios: panmixia (free-ranging Belarusian foxes), geographic isolation (free-ranging Scottish foxes), and anthropogenic selection (farm-bred foxes). Using a validated set of STR markers, multivariate statistical analysis was conducted to assess the genetic structure and the degree of genetic erosion across the studied groups. The wild red fox population in Belarus has been shown to maintain a state close to panmixia (PHWE = 0.090), characterized by a high effective population size (Ne = 694) and high allelic diversity. The island population from Scotland exhibits moderate gene pool depletion (Ne = 75.9) and a pronounced heterozygote deficiency (FIS = 0.18). Critical genetic erosion, which was characterized by a minimal effective population size (Ne = 60.2) and allelic fixation, was detected in the farm-bred group. The genetic distance between farm-bred and wild foxes (FST = 0.279; p = 0.001) reflects both the phylogeographic divergence between the Nearctic ancestors of farmed lineages and Palearctic wild populations, and the consequences of prolonged anthropogenic isolation, genetic drift, and selective breeding. These data indicate that artificial isolation and the impacts of genetic drift and targeted selection lead to a substantial depletion of the species' adaptive potential.

Animals

Empathic Accuracy and Behavioral Empathy After a Moderate Dose of Beer.

OBJECTIVES: Empathic accuracy (EA) represents a person's ability to correctly infer the emotions of another person. One past study in men found lower EA for positive emotions after a moderate dose of hard liquor compared to after placebo, particularly among non-hazardous drinkers. The present study aimed to replicate this finding, using a moderate dose of beer and a mixed design. Moreover, we added a novel measure of behavioral empathy. METHODS: Participants (62% men) completed the Alcohol Use Disorders Identification Test, Empathy Quotient, and Revised Drinking Motives Questionnaire. Before and after drinking either beer (6.6% alcohol, n = 28) or its 0.0% equivalent (placebo, n = 38), they watched videoclips of targets talking about emotional autobiographical events and rated how targets felt while talking. Behavioral empathy was assessed by presenting participants with painful scenarios and asking whether they would help the people in pain. RESULTS: The previous finding of lower EA for positive emotions after alcohol was not replicated. Nonetheless, after alcohol non-hazardous drinkers were less willing to help people in pain. Trait affective empathy (i.e., a person's long-term disposition to experience emotional responses congruent to another's feelings) and the drinking to cope motive did not significantly moderate the findings. CONCLUSIONS: Although alcohol may alter empathy, its effects are not consistent and may depend on the dose and type of alcohol consumed. The moderating roles of trait empathy and trait aggressivity deserves further study.

Humans

Voluntary Knowledge Brokering to Promote Evidence-Based Nursing Practice: A Qualitative Study.

Knowledge brokering is a process of connecting knowledge producers with users to facilitate evidence-based practice through relationship building and information sharing. This descriptive qualitative study aimed to clarify knowledge brokering by nurses in Japanese hospitals. Twelve registered nurses in Japanese hospitals participated. They had over 5 years' clinical experience, including experience in conducting research, particularly staff research, and education. Data were collected through semi-structured individual interviews and analyzed using qualitative content analysis. The analysis revealed a central theme: continuous efforts to foster empathy among colleagues and spontaneously promote evidence-based practice: multifaceted brokering activities by clinical nurses. Findings identified 10 categories categorized into four interconnected gears: establishing the foundational ground, assessing clinical needs and staff readiness, tailoring and diffusing evidence, and sustaining and evolving evidence-based practice. Even nurses without formal titles voluntarily bridged the research-practice gap, providing new insights into informal brokering. Brokers communicated considerately, balanced evidence with clinical context, negotiated practical compromises, and fostered staff research competency.

Humans

Your story, your brand: A career core competency for nurses.

Intentional management of one's professional story, or narrative discipline , is now a core competency and responsibility for nurses at all career stages. Workforce mobility, interdisciplinary collaboration, broadening career opportunities, and the expansion of digital platforms have elevated the importance of how nurses are perceived by colleagues, organizations, and the public. Increasingly, a nurse's professional story and digital footprint influence professional opportunities, career advancement, and even employment decisions.Many companies invest heavily in brand management to build trust and emotional connection with the people they serve. Importantly, narrative discipline also contributes directly to healthy work environments by reinforcing trust, role clarity, respect, and psychological safety. Drawing from leadership practice, emerging research on nurses' social media use, healthy work environment principles, and guidance from national nurse leadership organizations, this article outlines how nurses can align personal, professional, and enterprise identities; use language deliberately; and engage with discipline and integrity. Practical strategies are provided to help nurses move from passive narrative formation to intentional storytelling that supports career development, workforce engagement, organizational trust, and the sustainability of the nursing profession.

Humans

Financial Literacy Skills Instruction Among Autistic Individuals: A Systematic Review.

PURPOSE: Financial literacy skills are crucial for an independent life in modern societies. However, it does not appear that researchers have examined financial literacy skills among autistic individuals. This manuscript uses a systematic review to identify existing research which examines financial literacy skill instruction for autistic individuals. METHOD: We used a systematic review strategy to identify approximately 9500 articles. These articles proceeded through abstract and full-text screening for relevance. RESULTS: We identified two studies which directly taught financial literacy skills, and ten more which taught more basic money skills (such as calculating change). Neither of the two studies which taught financial literacy skills did so as an exclusive focus; both taught these skills alongside other objectives, as part of a larger intervention. CONCLUSIONS: Research on financial literacy skill instruction among autistic individuals is lacking, though there is a foundation of research examining money skills and related life skills to build upon. We recommend additional research on financial literacy skill instruction, ideally designed with the unique skills and needs of autistic individuals in mind, and with their input.

Humans

Analysis of deep learning techniques in computer-aided diagnosis for meniscus injuries: a systematic literature review.

Meniscus informatics is a growing subject of study in the healthcare industry. One of the major hindrances to the healthcare system's transformation is obtaining knowledge and meaningful information from complicated, high-dimensional and diverse sources. Modern biomedical research, for instance, has seen an increase in the use of complex, dissimilar, poorly documented, and generally unstructured electronic health records, imaging, sensor data and text, even after many current techniques have been used to extract more robust and useful elements from the data for analysis. New efficient standards for building end-to-end learning models from complex data are therefore needed. Therefore, the current study aims to examine the most recent research on the use of deep learning techniques for diagnosing meniscus tears and recommend creating comprehensive and meaningful interpretable structures that might benefit the healthcare industry. We also draw attention to shortcomings and the need for better technique development, and we provide new perspectives about this exciting new development in the field.

Humans

UV-based homogeneous disinfection process for removal of antibiotic resistance genes: Efficiency, mechanisms and influencing factors.

The proliferation and dissemination of antibiotic resistance genes (ARGs) in aquatic environments pose a serious threat to global public health. Ultraviolet-driven homogeneous advanced oxidation processes (UV-AOPs) represent a prospective suite of technologies for the efficient removal of ARGs. This review critically assesses recent advances in the application of UV-AOPs, specifically UV/hydrogen peroxide (UV/H2O2), UV/peracetic acid (UV/PAA), UV/persulfate (UV/PS), and UV/chlorine (UV/Cl), for the elimination of extracellular ARGs and intracellular ARGs. The underlying mechanisms involve direct ultraviolet-induced DNA damage, including pyrimidine dimer formation and strand breakage, as well as oxidation mediated by radicals such as hydroxyl radicals, sulfate radicals, carbon-centered radicals, and reactive chlorine species. The relative contribution of radical and non-radical pathways is strongly influenced by water chemistry and process conditions. We further expound on the critical operational and environmental factors governing ARG removal kinetics, including UV wavelength and fluence, oxidant type and dosage, ARG sequence characteristics, pH, ubiquitous anions, and dissolved organic matter, which collectively affect radical generation, quenching, and reaction microenvironments. Notably, for i-ARGs, UV-AOPs facilitate degradation not only through direct radical attack but also by disrupting cellular integrity and permeabilizing membranes, thereby enhancing the exposure of genetic materials to oxidative and photolytic damage. This review synthesizes current understanding to provide a mechanistic basis for the design and optimization of UV-AOP systems, highlighting their potential as effective barriers against the dissemination of antibiotic resistance in water reuse and purification scenarios.

Disinfection

ReMeDy: A Flexible Statistical Framework for Region-Based Detection of DNA Methylation Dysregulation.

Region-based epigenome-wide association studies have demonstrated improved statistical power and biological interpretability compared with probe-wise analyses of DNA methylation data. However, most existing region-based methods characterize methylation dysregulation primarily through changes in mean methylation levels associated with a phenotype of interest. Substantial evidence indicates that phenotype-associated methylation alterations may also manifest through changes in methylation variability or through joint shifts in mean and variability. Despite this, no existing statistical framework jointly models mean-variance methylation changes in a region-based manner. We propose ReMeDy, a flexible statistical framework that uses a hierarchical likelihood approach within a generalized linear model setting to identify differentially methylated regions, variably methylated regions, and regions exhibiting joint differential and variable methylation at a genome-wide scale. Unlike existing models, ReMeDy operates directly on biologically defined co-methylated regions, allowing it to naturally capture spatial correlation inherent in DNA methylation array data, while avoiding reliance on heuristic, user-defined tuning parameters such as smoothing spans and kernel bandwidths that can substantially influence results and introduce subjectivity. Through extensive simulation studies and comprehensive benchmarking against popular models, we demonstrate that ReMeDy maintains false discovery and Type-I error rates at nominal levels while achieving consistently higher statistical power across a wide range of realistic scenarios. Application to population-level DNA methylation data further shows that ReMeDy identifies biologically meaningful regions and pathways implicated in complex human diseases that are not captured by conventional mean-based analyses alone. ReMeDy is implemented as an open-source R package and is freely available at https://github.com/SChatLab/ReMeDy.

DNA Methylation

Genome-wide insights into the evolutionary and demographic history of the red alga Mazzaella laminarioides: Evidence for speciation with ancient migration along the southeast Pacific coast.

The mechanisms driving lineage divergence in red algae remain unexplored, despite the group's remarkable diversity and ancient evolutionary history. The red alga Mazzaella laminarioides, a Chilean intertidal species complex composed of three parapatric cryptic lineages (North, Center, South), offers a valuable system to evaluate these processes, as its life history combines severe dispersal limitation with a haploid-diploid cycle that may influence the emergence of reproductive barriers. We reconstructed its evolutionary history using whole-genome sequencing and nuclear genome assembly of representative individuals from each lineage. Phylogenomic analyses based on 1,507 single-copy orthologs recovered three deeply divergent lineages with limited nuclear discordance consistent with incomplete lineage sorting. For both splits, demographic modelling was most consistent with an Ancient Migration scenario, although support over strict isolation was moderate, suggesting that divergence may have begun with low asymmetric ancestral gene flow followed by subsequent loss of connectivity, demographic bottlenecks, and later population expansion. Coding sequence analyses revealed lineage-specific dN/dS heterogeneity; only one South-lineage locus passed FDR correction (metaxin-1, mitochondrial protein import), with two further South-lineage candidates in chlorophyll and heme biosynthesis falling below the FDR threshold. Together, these signals suggest that divergent selective pressures on energy acquisition may have contributed to divergence at the southern end of the distribution. These results add to the small but growing body of whole-genome data for red algae and, alongside recent macroalgal studies, suggest that ancestral connectivity could be a recurrent feature of lineage divergence even in marine organisms with extremely restricted dispersal.

Rhodophyta

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

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

Wetlands

Flux rewiring enables native D-glucosamine production in Escherichia coli.

D-Glucosamine is an industrially important amino sugar used in pharmaceuticals, nutraceuticals, and functional materials, yet its production remains dominated by chemical extraction from chitinous biomass, raising sustainability and allergen concerns. Escherichia coli natively synthesizes D-glucosamine directly from D-glucose through endogenous metabolism, revealing an underutilized amino sugar biosynthetic capability. Building on this native pathway, D-glucosamine production was enhanced through targeted genetic modifications and systematic optimization of nitrogen metabolism and cultivation conditions, reaching 9.2 g L-1 under shake-flask conditions. This work extends a phosphorylation-dephosphorylation strategy previously developed for neutral rare sugars to amino sugar biosynthesis, demonstrating the broader applicability of this metabolic design principle. Phosphatase identity emerged as a key control point for product formation: YbiV was the most effective phosphatase for selective D-glucosamine production, whereas alternative phosphatases redirected flux toward D-sedoheptulose. This enzyme-dependent flux partitioning further enabled tunable co-production of D-glucosamine and D-sedoheptulose. Native amino sugar biosynthesis in E. coli provides a controllable framework for producing chemically distinct sugars through endogenous metabolism and establishes a generalizable strategy for engineering amino sugar and other nitrogen-containing metabolite biosynthesis.

Escherichia coli

Time to subsequent therapy (TTST) as an endpoint in clinical studies: development of standardized documentation of subsequent therapy through systematic literature review, expert interviews, and Delphi survey.

BACKGROUND: The endpoint Time to Subsequent Therapy (TTST) is an intermediate endpoint used in research and regulatory assessments. TTST denotes initiation of subsequent therapy and is a clearly definable, clinically relevant event for healthcare professionals. However, it has not been systematically established to which extent TTST is subjectively meaningful to patients. The objective of this study was to define TTST as a patient-relevant intermediate endpoint. METHODS: The study examined five oncological indications (breast cancer, prostate cancer, melanoma, multiple myeloma, and non-small cell lung cancer) using a systematic literature review, analysis of case report forms used in international randomized controlled trials, review of German Federal Joint Committee (G-BA) documents, semi-structured interviews and a two-stage Delphi survey with healthcare professionals, patients, and relatives. RESULTS: A total of 35 individuals participated in qualitative interviews. Most of them rated TTST as particularly significant. The Delphi Survey included 264 interviewees in round one, and 117 in round two. Patient-relevance of TTST was confirmed by 81% of respondents (95% confidence interval 76%, 85%). Nine treatment scenarios that justify TTST were identified. To capture patient-relevance, prospective collection of reasons for and consequences of therapy change are required. A checklist with standardized response formats plus free-text fields was developed: a comprehensive master checklist for flexible, complete documentation and a short version focused on therapy change-specific items. CONCLUSIONS: TTST is an intermediate endpoint whose systematic documentation of characteristics demonstrating patient-relevance can be standardized in research and clinical practice using the developed checklists.

Humans

Toward real-time quantification of driving risks: a systematic review and research agenda of risk field theory.

In complex traffic systems, driving risk often evolves in a continuous and progressive manner prior to crash occurrence. How to effectively represent and analyze such latent risk states remains a central challenge in traffic safety research. In recent years, risk field-based approaches have introduced spatial and spatiotemporal continuous modeling paradigms, providing new perspectives for characterizing the distribution of traffic risk and its dynamic evolution. Motivated by the rapid growth of this research area and the lack of a systematic synthesis, this paper presents a comprehensive review of studies applying risk field theory to driving safety and traffic risk analysis. Following the PRISMA guidelines, relevant literature was collected through multi-database searches and analyzed using a combination of bibliometric analysis and qualitative review. The review systematically summarizes the theoretical foundations, modeling elements, data sources, analytical methods, and application domains of risk field-related research. Particular attention is given to studies that conceptualize traffic risk as a continuous field, complemented by a broader review of traffic risk factor literature to identify key elements and analytical dimensions involved in risk field modeling. On this basis, the paper synthesizes research progress in major application areas, including traffic safety state representation, driving behavior analysis, traffic conflict assessment, and autonomous driving and human-machine cooperative systems. Differences and commonalities among existing studies are compared in terms of modeling strategies, data support, and application scenarios. Through this systematic review, the paper clarifies the main research themes and methodological trends of risk field-based studies, providing a structured framework for understanding the evolution and application of this approach and offering methodological insights for risk perception modeling and safety-oriented decision support in intelligent transportation systems (ITS).

Humans

The potential of clustering methods for pre-test triage in sleep medicine: A systematic review.

Sleep disorders exhibit substantial heterogeneity, and traditional classifications may not fully capture clinically relevant subtypes. Clustering techniques can identify patient subgroups that improve phenotypic characterization and may support personalized management. This systematic review evaluated the application of clustering in sleep medicine, with particular focus on its potential use as a pre-test triage tool prior to formal sleep testing. PubMed/MEDLINE, Embase, Web of Science, and Scopus were searched to February 2025. Eligible studies applied clustering to classify sleep disorders in adults. Two reviewers independently conducted screening, data extraction, and risk-of-bias assessment using QUADAS-2. The protocol was registered on PROSPERO. Fifty-one studies (1983-2025) were included, predominantly focused on obstructive sleep apnea (OSA) (n = 38, 74%). Hierarchical clustering (n = 20) and K-means clustering (n = 14) were the most frequently used techniques. Internal validation was reported in only 18% of studies, and external validation was reported in only 1 study. Seven studies relied exclusively on baseline clinical, demographic, or questionnaire data, representing pre-test scenarios, whereas most incorporated polysomnography-derived variables, limiting their applicability to early clinical stratification. Hierarchical clustering was the most commonly applied method; however, the overall lack of validation limits confidence in the robustness and clinical applicability of identified phenotypes. The potential role of clustering as a pre-test triage strategy remains largely unexplored, as most studies focused on post-diagnostic phenotyping and were affected by incorporation bias. Future research should prioritize pre-test clinical variables, rigorously validate internally and externally, and adopt standardized methodological and reporting practices to facilitate clinical translation.

Humans

Review: The African turquoise killifish as a model for the integrative physiology of vertebrate aging.

With increasing emphasis on extending healthy lifespan, aging research requires vertebrate models that permit efficient mechanistic investigation and intervention testing within practical time and cost constraints. The African turquoise killifish (Nothobranchius furzeri) has attracted growing attention because it combines an exceptionally short life cycle with an intact vertebrate physiological context and an expanding genetic toolkit, enabling relatively rapid evaluation of candidate aging interventions and mechanistic analysis across molecular, tissue, and organismal levels. This review assesses N. furzeri from an integrative-physiology perspective, focusing on germline-soma interactions, gut microbiota-host crosstalk, nutrient sensing and metabolic remodeling, temperature responsiveness, and AMPK-mTOR-linked programs. It also examines expanding genome-engineering and reporter approaches that support mechanistic and tissue-resolved investigation of these physiological processes. Building on recent reviews of killifish biology, disease modeling, regeneration, and the hallmarks of aging, we synthesize evidence across major intervention domains, distinguish established phenotypic effects from incompletely resolved mechanisms, and highlight functional endpoints, methodological standardization, and the appropriate interpretation of the model's translational relevance. Together, these features position N. furzeri as a strategically useful vertebrate platform for rapid mechanistic testing, intervention evaluation, and prioritization of aging-related pathways. Future progress will require improved methodological standardization, tissue-resolved causal studies, and question-driven cross-species validation where appropriate.

Animals

Positive psychology interventions during pregnancy: A systematic review.

Positive psychology interventions (PPI) have been applied and demonstrated evidence in various population groups. The present systematic review focused on the types and influence of PPI on the physical and psychological health of pregnant women. Studies that matched the selection criteria were identified on EBSCOhost, PsychINFO, Web of Science, PubMed, Scopus and four positive psychology journals. From the 2528 records identified, finally eight studies were included in the review. PPI in this review were delivered utilising various positive psychology components such as hope, gratitude and optimism based on existing theories, for example, the strengths theory, broaden-and-build theory, and hope theory. Most interventions were conducted from 14 gestational weeks onwards and were delivered via virtual platforms or mobile applications. As a result of this systematic review, it was identified that PPIs for maternal well-being were aimed at improving (1) physical health, including labour pain, nausea and vomiting; (2) psychological health, including stress, emotions, anxiety and depression; and (3) subjective health, including life satisfaction, perceived social support and quality of life. Most of the selected studies provided significant evidence towards improvement of well-being outcomes from administering PPI. For future studies, in-depth PPI integrated coping and support approaches should be further evidenced among diverse pregnant populations.

Humans