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Heterogeneity in Teriflunomide Treatment Arms: A Systematic Review and Meta‑Regression of Randomised Multiple Sclerosis Trials.

BACKGROUND: Teriflunomide is widely used as an active comparator in Phase 3 randomised trials for relapsing multiple sclerosis (RMS). Temporal changes in disease activity within teriflunomide-treated cohorts have not been systematically examined. OBJECTIVES: To assess temporal trends in relapse and disability outcomes across teriflunomide arms of Phase 3 multiple sclerosis (MS) trials and identify predictors of between-trial heterogeneity. METHODS: We performed a systematic review and meta-analysis of Phase 3 randomised controlled trials including a teriflunomide arm. PubMed, Scopus, and ClinicalTrials.gov were searched up to October 2025. Annualised relapse rate (ARR) and 12- and 24-week confirmed disability worsening (CDW) were extracted together with baseline characteristics. Risk of bias was assessed using the Cochrane Risk of Bias 2 tool. Random-effects meta-analyses, meta-regression, and sensitivity analyses were performed. RESULTS: Twelve teriflunomide cohorts from eight trials involving 4,900 adults with RMS were included. ARR ranged from 0.11 to 0.37 with substantial heterogeneity (I2 = 94%). Trial start year was inversely associated with ARR and explained a large proportion of between-study variability in exploratory meta-regression analyses. Confirmed disability worsening outcomes also showed substantial heterogeneity with a weaker trend toward lower event rates in more recent trials. CONCLUSION: Teriflunomide-treated trial populations have shifted toward lower relapse activity over time, and trial start year was the principal predictor of between-trial heterogeneity in ARR in exploratory analyses. These findings most plausibly reflect evolving recruitment and diagnostic practices rather than changes in drug efficacy. Accounting for these temporal dynamics is essential when interpreting outcomes from RMS trial using teriflunomide as comparator.

Humans

Comprehensive multi-post-translational modifications profiling reveals age-associated remodeling in skeletal muscle.

Sarcopenia, characterized by the progressive loss of skeletal muscle mass and function, is a major hallmark of aging. Post-translational modifications (PTMs) play essential roles in regulating protein activity and cellular homeostasis; however, how multiple PTMs are remodeled during skeletal muscle aging remains incompletely characterized. Here, we performed comprehensive multi-layered proteomic profiling of skeletal muscle from young (3-month-old) and aged (24-month-old) mice, systematically quantifying the global proteome together with five major PTMs: acetylation, phosphorylation, N-glycosylation, O-glycosylation, and ubiquitination. In total, we identified 5 337 proteins and mapped thousands of PTM sites, generating an integrated atlas of age-associated proteomic and PTM remodeling in skeletal muscle. Pathway enrichment analyses revealed distinct modification-specific patterns: acetylation and phosphorylation were predominantly associated with metabolic and mitochondrial-related pathways; N-glycosylation was enriched in immune- and secretory pathway-related processes; O-glycosylation was associated with muscle contraction-related pathways; and ubiquitination was preferentially linked to cytoskeletal organization in muscle cells. Correlation analyses further uncovered diverse association patterns among different PTMs across protein- and modification-level datasets. Phosphorylation and ubiquitination exhibited consistent positive associations, whereas acetylation and ubiquitination showed both inverse and concordant co-variation patterns across subsets of proteins. Phosphorylation and O-glycosylation displayed heterogeneous association patterns across different proteins, and acetylation and phosphorylation demonstrated positive correlations with distinct age-associated directional changes across protein subsets. Together, these results provide a comprehensive, multi-dimensional view of age-associated remodeling of the skeletal muscle proteome and multiple PTM layers, offering a valuable resource for understanding molecular alterations accompanying muscle aging and sarcopenia.

Animals

Specialized pro-resolving mediators in obesity and overweight conditions: A systematic review of human and animal evidence on comparative differences and associations.

Obesity and overweight are characterized by persistent low-grade inflammation. Specialized pro-resolving mediators (SPMs), polyunsaturated fatty acid-derived metabolites, actively promote inflammatory resolution, and their dysregulation has been linked to unresolved inflammation and metabolic disturbances in obesity. This systematic review synthesized human and animal evidence on adiposity-related differences and associations in SPMs and SPM precursors. The protocol was prospectively registered in PROSPERO (CRD420251067464). PubMed/MEDLINE, Scopus, Web of Science, and Embase were searched up to 22 May 2026. Eligible studies included human and animal research comparing SPMs and/or SPM precursors between overweight/obese and normal-weight/lean groups or assessing their associations with adiposity indices. Due to heterogeneity across matrices and analytical platforms, findings were synthesized narratively. Twenty-seven unique studies were included, providing 28 experimental datasets (14 animal and 14 human). The most consistent alterations were observed in adipose tissue and circulation, where overweight/obesity was frequently associated with lower concentrations of SPMs and/or SPM precursors. In humans, circulating Resolvin E1 showed reproducible reductions and was inversely associated with adiposity measures in several cohorts. In contrast, selected metabolites, including SPM Lipoxin A4 and the SPM precursors 15-HETE and 18-HEPE, exhibited mixed directionality across studies. Evidence for hepatic and central nervous system compartments was limited and heterogeneous. Overall, available evidence suggests that excess adiposity is associated with altered SPM and precursor profiles, most consistently in adipose tissue and circulation, whereas hepatic and central nervous system findings remain inconsistent. Future studies using standardized quantification and tissue-specific designs are needed to clarify whether targeting pro-resolving pathways has translational potential in obesity-related metabolic dysfunction.

Animals

Plasma proteome profiling identifies XPNPEP3 as a novel biomarker associated with metabolic dysfunction-associated steatotic liver disease in patients with type 2 diabetes mellitus.

OBJECTIVE: To identify plasma protein differences between type 2 diabetes mellitus (T2DM) patients with and without metabolic dysfunction-associated steatotic liver disease (MASLD), and to evaluate the diagnostic potential of X-prolyl aminopeptidase 3 (XPNPEP3) for identifying MASLD in T2DM patients. METHODS: Twenty T2DM inpatients were categorized into groups with and without MASLD and their plasma samples were analyzed using data-independent acquisition mass spectrometry, followed by bioinformatics analysis to identify differentially expressed proteins. The cohort was then expanded to 84 patients, and plasma XPNPEP3 levels were validated by enzyme-linked immunosorbent assay. Correlation between XPNPEP3 and clinical indicators were evaluated, and diagnostic performance was determined via receiver operating characteristic (ROC) analysis. Immunohistochemistry was employed to compare hepatic XPNPEP3 expression between the two groups. RESULTS: Proteomic analysis identified 176 differentially expressed proteins, with XPNPEP3 exhibiting the most significant down-regulation by fold change. In the validation cohort, plasma XPNPEP3 was significantly lower in T2DM+MASLD versus T2DM alone. XPNPEP3 levels were negatively correlated with diabetes duration, liver function markers, and triglyceride levels, and was identified as an independent factor inversely associated with MASLD in T2DM.ROC analysis demonstrated strong diagnostic performance for XPNPEP3, further enhanced when combined with BMI and diabetes duration.  Immunohistochemistry confirmed reduced hepatic XPNPEP3 expression in T2DM+MASLD patients. CONCLUSIONS: Lower plasma XPNPEP3 is independently associated with MASLD in T2DM patients and demonstrates strong diagnostic potential, positioning XPNPEP3 as a promising biomarker for diagnosing MASLD in T2DM patients and a novel target for non-invasive diagnostic tool development.

Humans

Investigating telomere length and hTERT-MNS16A VNTR polymorphism in Bipolar disorder: Insights into clinical features.

OBJECTIVE: To compare leukocyte telomere length (LTL; T/S ratio) and hTERT-MNS16A VNTR polymorphism between patients with bipolar disorder (BD) and healthy controls, and to examine their associations with clinical features in BD. METHODS: A total of 179 participants (100 BD patients, 79 healthy controls) were enrolled. Relative LTL was assessed by qPCR-based T/S ratio; hTERT-MNS16A VNTR genotyping by PCR and gel electrophoresis. Clinical variables including episode frequency, illness duration, age at onset, symptom severity scales, first episode polarity, and family history of mood disorder were evaluated. RESULTS: No significant differences were observed between BD patients and healthy controls in T/S ratio or hTERT-MNS16A VNTR genotype distributions (all p > 0.05). Within the BD group, S allele carriers (L/S or S/S) had significantly more depressive episodes than L/L homozygotes (1.45 &#xb1; 2.58 vs. 0.61 &#xb1; 1.52; p = .040). Significant inverse correlations were identified between T/S ratio and depressive episode count (&#x3c1; = -0.220, p = .028) and total mood episodes (&#x3c1; = -0.207, p = .039). Multivariable negative binomial regression revealed four independent predictors of depressive episode frequency: lower T/S ratio (p = 0.005), S allele carriage (L/S or S/S genotypes) (p = 0.001), first depressive episode polarity (p < 0.001), and family history of mood disorder (p = 0.035). CONCLUSION: Although LTL and hTERT-MNS16A VNTR genotype did not differ between BD patients and healthy controls, shorter telomere length and S allele carriage were independently associated with higher depressive episode frequency within the BD group, implicating telomere biology and hTERT genetic variation in the biological substrate of depressive illness burden.

Humans

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

Critical illness is characterized by a catabolic, proinflammatory state. Anabolic agents, such as testosterone, have therefore been proposed as therapeutic targets. Our objectives were to assess the effects of testosterone in critically ill populations on patient-important outcomes and identify design limitations to inform future studies. We searched for randomized control trials (RCTs) through Medline, Embase, and EBM Reviews databases from inception through February 24, 2026, including English language articles enrolling adults (&#x2265;18&#xa0;years) admitted to ICU where anabolic androgen therapies (AAT) were compared with placebo or standard of care. Studies had to report at least one of: mortality, ICU and hospital lengths of stay, or duration of mechanical ventilation. We extracted data independently using a standardized data extraction tool, and feedback was received from all co-authors to ensure agreement. For each outcome, we performed meta-analyses using a random-effects model with inverse variance weighting in RevMan. We used the GRADE approach to assess certainty in pooled estimates of effect. Of 1325 screened articles, we found 4 that fit our inclusion criteria. Together, we judged risk of bias as 'some concerns' in 3 trials and 'high' in the final trial, and ultimately found that the effects of anabolic-androgen therapy on patient-important outcomes uncertain. With the uncertainty of current evidence for the effects of anabolic-androgen therapy in critically ill adults, there is insufficient support for its routine use. Future randomized evidence is needed to determine whether anabolic-androgen therapy improves clinically-important outcomes and better define its safety profile in critically ill adults.

Humans

Computational metabolomics at scale: from open data to insight.

Metabolomics data are currently generated at scale thanks to the evolution of technologies that have led to marked improvements in the number of metabolites detected, spanning all chemical classes. These data are increasingly submitted to public repositories for data reuse, integration, and interpretation. Despite the availability of public resources and associated computational tools, the field still lacks a widely adopted, consistent data and analytics infrastructure capable of transforming this wealth of information into scientific insight. Indeed, the metabolomics field is just now scratching the surface of being able to harness the power of new computational technologies. In this review, we summarize discussions from the "Dagstuhl-Seminar 24181 Computational Metabolomics: Towards Molecules, Models, and their Meaning" with a focus on public data availability, open data standards, data and knowledge integration, and education. Our goal is to raise awareness and adoption of the latest open science resources while highlighting key areas needing further development.

Metabolomics

The Efficacy of Pharmacotherapy Intervention on Anthropometric Outcomes in Survivors of Childhood Brain Tumors: An Updated Systematic Review and Meta-Analysis.

INTRODUCTION: Many survivors of childhood brain tumors face long-term adverse health outcomes like obesity. Uncertainties surround the effect of interventions to manage obesity-related outcomes in survivors of childhood brain tumors. The goal of this updated systematic review and meta-analysis was to provide the best estimate of the treatment efficacy of pharmacotherapy intervention on anthropometric outcomes in this pediatric population. METHODS: We searched CENTRAL, MEDLINE, EMBASE, CINAHL, PsycINFO, PubMed, ClinicalTrials.gov, and ProQuest for articles published from January 1, 2015, to January 31, 2025. A meta-analysis was performed using the generic inverse-variance method in RevMan 5.4. Heterogeneity was assessed using the Cochrane Q test and the I2 statistic. We used the GRADE approach to determine the certainty of evidence. RESULTS: A total of six studies met the inclusion criteria: four newly identified studies published after January 1, 2015 (125 participants), and two from the previously published review (23 participants). The pooled estimate showed no significant change in body mass index z-score after intervention (mean difference&#x2009;=&#x2009;-0.02; 95% CI: -0.06 to 0.02, I2&#x2009;=&#x2009;0%; 4 studies, 94 participants; low certainty of evidence). Similar pooled effects were observed across other outcomes; however, individual studies reported significant changes in some outcomes within the treatment groups after the intervention. CONCLUSION: Pharmacological agents showed no significant change in anthropometric outcomes for survivors of childhood brain tumors. Further trials are needed to assess the efficacy of pharmacological agents and to identify subgroups most likely to benefit.

Humans

Risk-Benefit of Phase 2 Monotherapy Trials in Adult Solid Cancers: A Systematic Review and Meta-Analysis.

Phase 2 (and phase 1 dose expansion, which we label phase 2 for the purposes of this study) cancer trials are the first direct tests of a new drug's efficacy. Because efficacy evidence is lacking, the therapeutic status of drug administration during ethical review is uncertain. We compared the efficacy and safety of cancer monotherapies in phase 2&#xa0;with phase 3, where clinical equipoise underwrites a therapeutic status for drug administration. In this systematic review and meta-analysis, we searched Clinicaltrials.gov for phase 2 and 3 investigational monotherapy drug trials in six solid malignancies, with primary completion dates 2015-2020, inclusive. Two independent reviewers completed data extraction. Effects were estimated using an inverse-variance weighted random-effects model meta-analysis of proportions using the R package meta. We analyzed 130 phase 2 and 52 phase 3 trial arms, enrolling 6665 and 18,694 patients. The pooled objective response rate was 7% (95% CI 5%-11%) in phase 2 versus 24% in phase 3 (95% CI 17%-31%; p&#x2009;<&#x2009;0.0001). The median PFS and OS were shorter in phase 2 compared to phase 3 (3.23 vs. 5.43&#x2009;months, p&#x2009;<&#x2009;0.0001; 9.46 vs. 14.44&#x2009;months, p&#x2009;=&#x2009;0.0001). The pooled rate of drug-related grade 3-4 adverse events was 30% (95% CI 23%-37%) in phase 2 and 25% (95% CI 19%-32%) in phase 3. Monotherapies delivered in phase 2 cancer trials present diminished risk-benefit compared with phase 3 and align with historic estimates for phase 1. Though there may be exceptions, risks for drug administration in phase 2 should generally be justified by appeals to research rather than therapeutic value.

Humans

From fear to empowerment: the&#xa0;impact of employees AI awareness on workplace well-being - a new insight from the JD-R model.

PURPOSE: The primary purpose of the study was to explore the impact of health workers' awareness of artificial intelligence (AI) on their workplace well-being, addressing a critical gap in the literature. By examining this relationship through the lens of the Job demands-resources (JD-R) model, the study aimed to provide insights into how health workers' perceptions of AI integration in their jobs and careers could influence their informal learning behaviour and, consequently, their overall well-being in the workplace. The study's findings could inform strategies for supporting healthcare workers during technological transformations. DESIGN/METHODOLOGY/APPROACH: The study employed a quantitative research design using a survey methodology to collect data from 420 health workers across 10 hospitals in Ghana that have adopted AI technologies. The study was analysed using OLS and structural equation modelling. FINDINGS: The study findings revealed that health workers' AI awareness positively impacts their informal learning behaviour at the workplace. Again, informal learning behaviour positively impacts health workers' workplace well-being. Moreover, informal learning behaviour mediates the relationship between health workers' AI awareness and workplace wellbeing. Furthermore, employee learning orientation was found to strengthen the effect of AI awareness on informal learning behaviour. RESEARCH LIMITATIONS/IMPLICATIONS: While the study provides valuable insights, it is important to acknowledge its limitations. The study was conducted in a specific context (Ghanaian hospitals adopting AI), which may limit the generalizability of the findings to other healthcare settings or industries. Self-reported data from the questionnaires may be subject to response biases, and the study did not account for potential confounding factors that could influence the relationships between the variables. PRACTICAL IMPLICATIONS: The study offers practical implications for healthcare organizations navigating the digital transformation era. By understanding the positive impact of health workers' AI awareness on their informal learning behaviour and well-being, organizations can prioritize initiatives that foster a learning-oriented culture and provide opportunities for informal learning. This could include implementing mentorship programs, encouraging knowledge-sharing among employees and offering training and development resources to help workers adapt to AI-driven changes. Additionally, the findings highlight the importance of promoting employee learning orientation, which can enhance the effectiveness of such initiatives. ORIGINALITY/VALUE: The study contributes to the existing literature by addressing a relatively unexplored area - the impact of AI awareness on healthcare workers' well-being. While previous research has focused on the potential job displacement effects of AI, this study takes a unique perspective by examining how health workers' perceptions of AI integration can shape their informal learning behaviour and, subsequently, their workplace well-being. By drawing on the JD-R model and incorporating employee learning orientation as a moderator, the study offers a novel theoretical framework for understanding the implications of AI adoption in healthcare organizations.

Humans

Outcomes at rapid diagnostic centres and the association between non-specific symptoms and cancer: A systematic review and meta-analyses of up to 21,392 patients.

INTRODUCTION: Cancer remains a leading cause of mortality and poses a significant public health challenge. Several non-specific symptoms (NSSs) often indicate non-serious disease but can also accompany malignancy even in the absence of organ-specific signs. Therefore, the aim of the study was to comprehensively delineate the association between the most common NSSs (weight loss, fatigue, pain and nausea/appetite loss) and cancer or non-cancer diagnoses. METHODS: Database searches of PubMed and Embase were conducted applying search criteria to identify studies that investigated common NSSs in cancer patients diagnosed through rapid diagnostic centres (RDCs). The quality of the included studies was assessed using a modified Newcastle-Ottawa Scale (NOS). For each symptom, pooled relative risks (RRs) with 95% confidence intervals were derived using random-effects meta-analysis. RESULTS: Eleven studies met the inclusion criteria. All studies were considered to be of high methodological quality. The most frequent disease locations for cancer entities included hematologic, lung and lower gastrointestinal. Together with miscellaneous, rheumatic, and musculoskeletal conditions, these were the most common for non-cancer diagnoses. Nausea/appetite loss showed a statistically significant association with cancer (RR=1.20, 95%-CI 1.07-1.35). Pain showed a non-significant association (RR=1.07, 95%-CI 0.75-1.53) with substantial between-study heterogeneity, and weight loss showed a non-significant inverse trend (RR=0.92, 95%-CI 0.84-1.02). Fatigue showed no association with cancer (RR=1.00, 95%-CI 0.85-1.18). DISCUSSION/CONCLUSION: NSSs may be valuable for cancer risk assessment, but the associations remain modest. The complexity of patients' clinical presentations suggests that additional factors likely influence the cancer risk. Future research should examine symptom combinations and, where data allow, perform subgroup analyses.

Humans

Multi-omic biomarkers in cardiovascular disease: Discovery to clinical translation.

Cardiovascular disease (CVD) remains the leading cause of mortality worldwide, necessitating improved risk stratification and early detection strategies. Multiomics approaches that integrate genomics, transcriptomics, proteomics, metabolomics, and epigenomics offer unprecedented opportunities for biomarker discovery and precision medicine in cardiovascular care. This narrative review examines the current landscape of multiomics biomarkers for CVD, tracing their evolution from discovery to clinical translation. We synthesize evidence from recent studies evaluating the clinical utility of integrated omics approaches across diverse cardiovascular conditions, including atherosclerotic cardiovascular disease, heart failure, and atrial fibrillation. High-throughput proteomics has identified novel protein signatures that enhance cardiovascular risk prediction beyond traditional risk factors. Metabolomics has revealed pathway-specific biomarkers, including trimethylamine N-oxide and lipid species, associated with atherogenesis. Polygenic risk scores derived from genomic data demonstrate incremental value when combined with clinical risk scores. Multiomics biomarkers represent a transformative approach to cardiovascular risk assessment and disease management.

Humans

Efficacy and safety of revascularization in patients with chronic limb-threatening ischemia by kidney function.

BACKGROUND: The optimal revascularization strategy for patients with chronic limb-threatening ischemia (CLTI) with chronic kidney disease (CKD) remains unknown. We evaluated whether the efficacy and safety of surgical vs endovascular revascularization differ by kidney function. METHODS: In this post hoc secondary analysis of BEST-CLI trial (NCT02060630), 1,704 patients with CLTI were stratified by baseline estimated glomerular filtration rate (eGFR, mL/min/1.73 m&#xb2;): non-CKD (eGFR &#x2265; 90), mild-moderate CKD (eGFR 45-89), advanced CKD (eGFR < 45 or dialysis). The primary outcome was a composite of major adverse limb events (MALE) or death. We estimated the difference in restricted mean time lost (RMTL, in days) adjusted for inverse probability treatment weights. RESULTS: Surgical revascularization was significantly associated with fewer days with MALE or death in non-CKD (RMTL difference: -127.8 days; 95% CI -176.1, -79.6) and mild-moderate CKD (-63.2 days; 95% CI -104.7, -21.8) but not in advanced CKD (-16.4 days; 95% CI -78.8, 46.0; P interaction = .02). This attenuation reflected a diminishing mortality benefit with more severe CKD (P interaction = .01), whereas the association with fewer days with MALE remained consistent across CKD strata (P interaction = .34). Major adverse cardiovascular events and serious adverse events were more common with more severe CKD but did not differ significantly by treatment. CONCLUSIONS: Surgical vs endovascular revascularization was consistently associated with fewer days with MALE across CKD strata. However, its association with mortality varied by kidney function, attenuating the overall benefit for the composite endpoint of MALE or death. These results support individualized revascularization strategies, but require prospective confirmation. TRIAL REGISTRATION: The BEST CLI trial is registered at ClinicalTrials.gov (NCT02060630).

Humans

The return of measles: a dangerous comeback.

PURPOSE OF REVIEW: Measles has reemerged as a significant global public health threat, with increasing morbidity and mortality associated with declining vaccination rates. This review summarizes current global outbreaks, history of measles, vaccination and elimination status, vaccine hesitancy, and outbreak response and lessons learned highlighting different novel digital epidemiological tools. RECENT FINDINGS: Measles continues to surge worldwide with an estimated 11 million infections in 2024, which is more than prepandemic levels. Developing and developed countries are both facing measles outbreaks, with the United States at risk of losing measles elimination status. Recent studies have showed that worldwide percentages of two-dose measles vaccination were lower than 95% that is required to interrupt measles transmission in all WHO regions. Novel epidemiological tools such as interactive simulators, real-time use of dynamic models, serosurveillance, and others are transforming measles outbreak response and enable earlier outbreak detection, tracking, and targeted public health interventions. SUMMARY: Vaccine hesitancy is one of the top global health threats and developing a tailored evidence-based approach is necessary to establish and maintain measles elimination.

Humans

Carboxyl group number and acidity of organic acids regulate structural reorganization and low glycemic index in cassava pyrodextrins via molecular interactions.

Transforming high-glycemic cassava starch into functional dietary fiber via pyrodextrinization is a promising way to valorize tuber crops, yet the molecular mechanisms catalyzed by organic acids with different carboxyl numbers and acidity remain unclear. This study investigates how carboxyl number and acidity of acetic acid (AA), tartaric acid (TA), and citric acid (CA) affect structural reorganization and low glycemic properties of cassava pyrodextrins. Compared with AA, TA, and CA with stronger acidity and more carboxyl groups promoted more extensive hydrolysis, transglycosylation, repolymerization, and esterification. These changes increased indigestible glycosidic linkages and the branching degree, while reducing molecular weight. Molecular docking confirmed stronger hydrogen-bonding interactions between TA/CA and starch chains. Furthermore, TA- and CA-catalyzed pyrodextrins exhibited superior anti-digestive properties with resistant starch up to 54.26% and an estimated glycemic index as low as 42.46, highlighting the critical role of carboxyl numbers and acidities in modulating the functionality of pyrodextrins.

Manihot

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

SGLF-Net:Staged Global-to-Local Cross-Scale Fusion Network for Colonoscopic Polyp Segmentation.

Polyp segmentation in colonoscopy images plays a pivotal role in computer-aided medical diagnosis and the early prevention of colorectal cancer. However, existing methods often suffer from performance degradation when confronted with extreme polyp scale variation and polyp boundary ambiguity. To address these challenges, we propose the Staged Global-to-Local Cross-Scale Fusion Network (SGLF-Net), which adopts a novel staged global-to-local learning paradigm to progressively refine segmentation from coarse global semantics to fine-grained local details. Specifically, the Global Semantic Perception Stage integrates a Swin Transformer Encoder and a Dynamic Attentive Decoder (DAD) to construct comprehensive multi-scale contextual representations. The Local Detail Refinement Stage employs an Edge-aware Dynamic Attentive Decoder (E-DAD) to enhance structural fidelity and boundary precision through explicit edge-guided supervision. Furthermore, we introduce the Cross Spatial-Scale Feature Aggregation and Reconstitution (CSSAR) module, equipped with hybrid attention mechanisms, to facilitate efficient semantic structural interaction between the two cascaded stages. Extensive experiments on five public benchmark datasets demonstrate that SGLF-Net consistently outperforms state-of-the-art methods in both segmentation accuracy and boundary preservation.

Journal Article

Detoxifying biotransformation of chloramphenicol by Exiguobacterium sp. CAP4 and its bioaugmentation of chloramphenicol biodegradation in simulated wastewater.

The extensive use of chloramphenicol (CAP) in livestock leads the accumulation of CAP in livestock manures, threatening environmental and human health. Therefore, eliminating or reducing CAP concentration in manures before its re-utilization and application through microbial remediation is necessary. Exiguobacterium sp. CAP4, isolated from the plastisphere in duck manures, was capable of degrading CAP with the biodegradation efficiency of 97.8 % at initial CAP concentration of 5 mg/L within 4 days. A total of twenty-four biotransformation products were determined, including two novel transformation products, TP166 and TP203, enriched the integrity of CAP biodegradation pathways. Furthermore, the biotransformation process was proposed as a detoxifying process through biotransformation products toxicity evaluation. Notably, Exiguobacterium sp. CAP4 successfully colonized in the cow manures after inoculation, and bioaugmented the biodegradation of CAP in virgin cow manures. This study significantly extended our understanding of the CAP biotransformation fate, and provided a promising bacterial strain for bioremediation of CAP containing wastewater in situ.

Chloramphenicol