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PubMed2026

A study on the differences in recovery effects of different types of nutritional supplements on competitive performance of esports athletes under mental fatigue.

BACKGROUND: To compare the effects of different nutritional supplements on the recovery of core competitive performance abilities in esports athletes following mental fatigue and to observe changes in the autonomic nervous system during recovery after nutritional supplementation by monitoring heart rate variability (HRV). METHODS: A randomized crossover within-subject controlled experimental design was adopted, including nutritional supplement type (caffeine, nitrate, Ginkgo biloba extract, catechins, placebo) × mental fatigue state (initial, fatigued, post-supplementation). Twenty high-level first-person shooter (FPS) esports athletes were recruited. Mental fatigue was induced using a Stroop task. After ingesting the different supplements and resting for 60 minutes, the participants completed assessments of shooting accuracy, shooting stability, spatial localization, and multitasking ability using the KovaaK's simulation trainer. HRV indices were also recorded to evaluate changes in autonomic regulation. RESULTS: For shooting accuracy, compared with the placebo condition, all four supplements significantly improved shooting accuracy scores following mental fatigue (all p < 0.05); however, no significant differences were observed among the effects of the different supplements. For shooting stability, caffeine, nitrate, and catechins produced significant recovery effects on shooting stability (all p  < 0.05); however, no significant differences were observed among the effects of these three supplements. For spatial localization and multitasking ability, the improvements in these two abilities in the post-supplementation state may have resulted from natural recovery, and none of the four nutritional supplements demonstrated a significant recovery effect. The HRV results showed that indices including RMSSD and SDNN changed under some supplement conditions. CONCLUSIONS: Mental fatigue significantly reduced the competitive performance of esports athletes. Four types of nutritional supplements all promoted the recovery of shooting accuracy, while caffeine, nitrate, and catechins promoted the recovery of shooting stability. However, no additional recovery advantages of the nutritional supplements over placebo were identified for spatial localization or multitasking ability. Changes in HRV may reflect changes in autonomic regulation during recovery, but further research is still warranted.

Humans↗

PubMed2025

A Systematic Review of Help-Seeking Barriers for Racial-Ethnic Minority Caregivers Accessing Autism Diagnostic and Intervention Services.

Caregivers play an essential role in early help-seeking and intervention for children with Autism Spectrum Disorder (ASD). Caregivers, therefore, provide a crucial role in helping to address the racial and ethnic disparity identified in accessing ASD intervention and diagnostic services (Bejarano-Martín et al., Journal of Autism and Developmental Disorders 50(9), 3380-3394, 2020). Unfortunately, racial-ethnic minority caregivers of children with autism (CCA) are less likely to contact a physician or healthcare professionals about their concerns and more likely to delay their contact to have their child evaluated (Zeleke et al., Journal of Autism and Developmental Disorders 49(10), 4320-4331, 2019). However, little evidence exists to explain why such a gap exists in the help-seeking behaviors between White and racial-ethnic minority CCA. To address this knowledge gap, we conducted a systematic literature review to identify articles that have studied barriers in help-seeking for racial-ethnic minority CCA. A broad literature search across four databases was conducted (i.e., PubMed, PsycINFO, Education Resources Information Center, and Child Development and Adolescent Studies). The coding team identified 17 articles on help-seeking barriers for racial-ethnic minority CCA. A thematic analysis was used to narratively synthesize the help-seeking barriers identified across these 17 studies. Four themes emerged from our findings: logistical barriers, provider competence, ASD literacy, and cultural stigma. We also provided clinical recommendations for healthcare providers working with families with racial-ethnic minority CCA.

Humans↗

PubMed2026

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↗

PubMed2026

CRISPR-Cas and Infectious Diseases: A Decade of Translational Advances in Molecular Biotechnology.

CRISPR-Cas systems have emerged as a versatile tool for diagnosing, treating, and preventing infectious diseases. This review highlights translational advancements in CRISPR-Cas-based applications, concentrating on the past decades in diagnostics, therapeutic genome editing, and vaccine development. The article highlights key platforms like DETECTR and SHERLOCK, which enable rapid, sensitive pathogen detection, and explores CRISPR-Cas9 systems in therapeutic strategies for directly targeting viral genomes and combating antimicrobial resistance. It also examines the role of CRISPR-Cas9 in engineering live-attenuated and personalized neoantigen vaccines. Principal findings demonstrate a clear progression from experimental proof-of-concept to preclinical applications primarily in CRISPR-based diagnostics and the engineering of live-attenuated vaccine candidates, whereas translation in CRISPR-based therapeutics and personalized neoantigen vaccines for infectious diseases remains at earlier, more exploratory stages. CRISPR-based diagnostics have progressed further toward clinical evaluation than therapeutics due to delivery and safety constraints, while personalized neoantigen vaccines are included mainly as an emerging, comparative concept for infectious diseases rather than a mature application. This review uniquely integrates CRISPR-based diagnostics, therapeutics, and vaccine development within a single infectious disease framework, critically assesses their current maturity, and systematically highlights technical, regulatory, and ethical barriers alongside realistic future priorities. The review concludes that while CRISPR-Cas holds transformative potential for infectious disease management, significant challenges in delivery efficiency, off-target effects, and ethical regulation must be addressed to ensure safe and equitable clinical translation.

Humans↗

PubMed2026

Higher Rates of PASS and SCB After Arthroscopic Subspine Decompression Are Associated With a Positive Diagnostic AIIS Injection: A Propensity Score-Matched Cohort Study.

BACKGROUND: Hip arthroscopy effectively treats femoroacetabular impingement syndrome (FAIS), but persistent pain may be related to concomitant extra-articular pathology such as subspine impingement syndrome (SSI). Standard diagnosis of SSI often relies on 3-dimensional computed tomography (3D-CT) morphology (Hetsroni type II/III), although this morphology is common in individuals who are asymptomatic and correlates poorly with symptoms. PURPOSE: To compare minimum 2-year clinical outcomes after arthroscopic subspine decompression in patients with concurrent FAIS and type II/III anterior inferior iliac spine (AIIS) morphology, stratified by diagnostic method: 3D-CT morphology alone versus 3D-CT morphology plus a positive ultrasound-guided diagnostic injection. STUDY DESIGN: Cohort study; Level of evidence, 3. METHODS: This study included patients aged 18 to 55 years with type II/III AIIS morphology who underwent primary hip arthroscopy for FAIS and SSI between January 2021 and November 2023 and had minimum 2-year follow-up. Patients diagnosed by CT morphology alone (CT classification group) were propensity score matched 1:1 to patients with a positive ultrasound-guided AIIS injection (injection group), with 57 patients per group. Matching variables were age, sex, body mass index, lateral center-edge angle, alpha angle, Tönnis grade, and Beighton score. All patients underwent arthroscopic subspine decompression. Patient-reported outcomes and rates of achieving the minimal clinically important difference, Patient Acceptable Symptom State (PASS), and substantial clinical benefit (SCB) were compared. RESULTS: Preoperative patient-reported outcome scores were similar between groups (all P > .05). At minimum 2-year follow-up, the injection group had significantly better scores on the modified Harris Hip Score (90.8 vs 84.2), Hip Outcome Score-Activities of Daily Living (88.4 vs 82.4), Hip Outcome Score-Sports Subscale (71.9 vs 64.1), 12-item International Hip Outcome Tool (83.9 vs 76.1), and visual analog scale for pain (1.2 vs 2.0) (all P < .001). Minimal clinically important difference rates were high in both groups, with higher rates in the injection group for modified Harris Hip Score (93% vs 77%; P = .033) and Hip Outcome Score-Activities of Daily Living (91% vs 75%; P = .042). PASS and SCB rates were significantly higher in the injection group across all patient-reported outcome measures (all P < .05). Revision and complication rates were low and did not differ significantly between groups. CONCLUSION: Both groups improved significantly after arthroscopic subspine decompression. However, patients with a positive ultrasound-guided diagnostic AIIS injection achieved higher PASS and SCB rates than those selected by CT morphology alone, suggesting that injection-confirmed SSI may improve patient selection for subspine decompression.

Humans↗

PubMed2026

Automated CEAP Classification of Venous Duplex Reports Using Multimodal Artificial Intelligence.

OBJECTIVE: To develop and internally validate a prototype multimodal artificial intelligence system for automated CEAP (Clinical, Etiological, Anatomical and Pathophysiological) classification of venous duplex ultrasound (VDUS) reports, integrating natural language processing of free-text components with computer vision analysis of hand-drawn anatomical diagrams. METHODS: Single centre retrospective observational study using routinely collected clinical data. One thousand consecutive venous duplex ultrasound reports from Cambridge University Hospitals NHS Foundation Trust, UK (July 2024 - May 2025) were labelled according to the CEAP classification, excluding the Etiological component, which could not be reliably determined from duplex reports alone. Transfer learning was applied using ClinicalBERT for text and MobileNetV3 for diagrammatic data. Clinical classes were predicted from request line text. Text- and image-based pathophysiological models were developed for four anatomical territories (Great Saphenous Vein, Small Saphenous Vein, Deep system, Perforators), combined using late fusion with probability averaging. RESULTS: The clinical CEAP model achieved accuracy of 0.91, macro-F1 of 0.82, and macro-AUC of 0.98. Pathophysiological prediction varied, with text models broadly outperforming image models. Fusion yielded heterogeneous benefits, improving SSV performance but reducing Deep system accuracy. The performance of the final pathophysiological CEAP fusion models varied across anatomical territories: accuracy ranged from 0.70-0.92 and macro-AUC from 0.80-0.92. CONCLUSION: This study demonstrates the feasibility of automated CEAP classification from VDUS reports. Despite class imbalance affecting minority class predictions, the strong discriminatory performance validates this multimodal ML model for extracting clinically meaningful information from real-world data. This approach offers potential, pending external validation, to streamline vascular services through automated triage and guideline-compliant decision making.

Artificial intelligence↗

PubMed2026

Long-term consequences of childhood sexual abuse: An umbrella review of diagnostic meta-analyses.

BACKGROUND: Childhood sexual abuse (CSA) is a public health issue with an estimated worldwide prevalence of 12.7%, potentially leading to a host of lifelong and significant mental, physical, and behavioral health. The aim of this study was to comprehensively map the long-term consequences of childhood sexual abuse on physical, psychiatric, and behavioral health outcomes. METHODS: An umbrella review of meta-analyses of observational studies, registered on PROSPERO, was conducted to examine the diverse repercussions of childhood sexual abuse on adult health. Three bibliographic databases (PsycINFO, PubMed and Scopus) were searched from the inception of the respective databases to November 1st, 2022. Thirty-eight meta-analyses representing about 20 million individuals were analyzed, revealing a range of long-lasting consequences associated with CSA. RESULTS: Among physical pathologies, cervical cancer and functional neurological syndromes emerged as the most prominent, exhibiting significantly elevated odds ratios (ORs) of 4.18 IC95% and 3.30 IC95%, respectively. Sleep disorders and borderline personality disorders were the most prevalent mental health disorders associated with CSA, with respective ORs of 16.17 IC95% and 5.96 IC95%. Early sexual initiation (OR=3.59 IC95%, sexual assault (OR=3.36 IC95%, and prostitution (OR=3.24 IC95%) emerged as the most common behavioral consequences. Notably, no significant differences in the consequences of CSA were observed between men and women, except for reproductive health outcomes. DISCUSSION: When faced with certain pathologies, clinicians should consider and discuss sexual abuse with their patients. The consequences of abuse have a multifactorial origin, which is a weakness, as are the problems of defining abuse. The strength of our study is that it lists the consequences published in high-quality studies. CONCLUSION: This umbrella review provides compelling evidence of the profound and far-reaching impact of childhood sexual abuse on a broad spectrum of physical, mental, and behavioral health issues.

Humans↗

PubMed2026

Not just when, but how: An exploratory dual-control approach to video feedback in motor learning.

The present study provides exploratory evidence for a novel dual-control paradigm. It examines whether combining temporal over video feedback timing with learner-controlled interactive playback functions (pause, slow-motion, rewind) would enhance motor skill acquisition beyond temporal autonomy alone. Sixty-four novice adults were randomly assigned to one of four conditions: Full Control (self-controlled timing + interactive replay), Partial Control (self-controlled timing + non-interactive replay), Yoked Full Control (externally controlled timing + interactive replay), or Yoked Partial Control (externally controlled timing + non-interactive replay). Motor accuracy (Radial Error), movement consistency (Bivariate Variable Error), technical execution, and self-efficacy were assessed at pre-test, 24-h retention, and 72-h retention following two acquisition sessions on a dart-throwing task (120 trials total). The Full Control group demonstrated the greatest and most durable learning gains across all outcomes. The Group × Time interaction was significant across all dependent variables (η2ₚ ranging from 0.140 to 0.234), with Full Control demonstrating superior retention at both 24 and 72 h relative to other groups (though differences relative to Partial Control were more pronounced at 72-h retention). Critically, the Yoked Full Control group showed comparatively weaker outcomes despite access to the same interactive playback functions. These findings suggest that interactive video tools may be most useful when learners can regulate both when feedback is accessed and how it is inspected. Theoretical and practical implications for the design of learner-centered video feedback systems are discussed.

Humans↗

PubMed2026

Improving insurance deduction identification: a hybrid artificial intelligence model using machine learning and expert systems.

PURPOSE: Financial challenges in healthcare systems worldwide, especially in low- and middle-income countries like Iran, have increased hospitals' reliance on insurance reimbursements. Unrecognized insurance deductions often cause severe financial shortages, making efficient deduction management crucial. This study aimed to design a hybrid intelligent system for identifying and predicting insurance deductions by combining machine learning and expert system frameworks. DESIGN/METHODOLOGY/APPROACH: A mixed-methods design was applied in four stages. First, a scoping review identified the causes and patterns of insurance deductions. Second, interviews with 15 insurance experts produced a validated checklist and a dataset from inpatient billing records. Third, using the CRISP-DM methodology, machine learning algorithms were developed and tested in SPSS Modeler alongside a fuzzy expert system developed in MATLAB. Finally, the model was validated using the holdout method. FINDINGS: Four categories of deduction drivers were identified: service provision, registration errors, document submission issues, and revenue conversion processes. The CHAID decision tree outperformed other algorithms with a 99% precision rate and the lowest Mean Absolute Error (9.43). A brief assessment of potential overfitting was conducted to ensure that the CHAID model's high accuracy was interpreted cautiously and supported by the validation results. The fuzzy expert system with validated rules was adaptable for deduction classification, especially for cases unsuitable for quantitative modeling. ORIGINALITY/VALUE: The hybrid model improves detection and prevention of deductions, offering actionable insights for hospital administrators, insurers, and policymakers. Its implementation can enhance hospital information systems, streamline claims processing, and optimize revenue management amid financial constraints.

Machine Learning↗

PubMed2025

Systematic Review of Symptoms of Catatonia in Autism Spectrum Disorder.

Catatonia is a complex neuropsychiatric syndrome characterized by disturbances in mood, motor function, behavior and speech. It is increasingly recognized in individuals with autism spectrum disorder (ASD), although its identification remains challenging due to the overlapping clinical features of the two conditions. Shared characteristics, such as echophenomena, mannerisms, social indifference and repetitive behaviors can obscure accurate diagnosis. Although reports suggest a significant prevalence of catatonia among individuals with ASD, the condition remains poorly understood and frequently under recognized, leading to substantial diagnostic and treatment challenges. A systematic review was conducted to characterize the symptoms of catatonia in individuals with ASD. The literature search included peer-reviewed journal articles published in English from 1980 onward, focusing on studies examining co-occurring catatonia and ASD. A qualitative framework analysis was implemented to evaluate 45 peer-reviewed studies, with findings interpreted in relation to, and extending beyond, the diagnostic criteria for catatonia outlined in the International Classification of Diseases, 11th revision (ICD-11). The objective was to identify symptom patterns extending beyond current diagnostic frameworks and to support improved clinical recognition and diagnostic precision in ASD populations. The review identified six primary symptom clusters associated with catatonia in individuals with ASD: (1) psychomotor activity, (2) speech disturbances, (3) changes in behavior/skills/functions, (4) mental health symptoms, (5) physiological symptoms, and (6) symptoms related to arousal and awareness. Notably, several symptoms observed within these clusters are not currently included in the ICD-11 diagnostic criteria for catatonia. These additional symptoms include tics, motor compliance, incoherent speech, self-injury, impaired cognition, and appetite changes, suggesting a broader clinical presentation of catatonia in ASD populations than is presently captured in existing diagnostic frameworks. The findings of this review highlight the significance of enhancing clinicians' awareness and understanding of how catatonia manifests in individuals with ASD. Most notably, six symptom clusters, psychomotor changes, speech disturbances, behavioral and functional regression, affective and psychiatric symptoms, physiological symptoms, and arousal/awareness disturbances, were observed. Several symptoms identified in this review are not included in the current diagnostic criteria, and their recognition may facilitate in earlier identification and timely intervention, potentially preventing the severe consequences of untreated catatonia in this population.

Humans↗

PubMed2026

Distal versus proximal radial access for diagnostic cerebral angiography: comparative outcomes and learning curve analysis.

BACKGROUND AND PURPOSE: Distal transradial access (dTRA) is an alternative to proximal transradial access (pTRA) for neuroangiography, but comparative real-world data and evidence on its early learning curve remain limited. We compared procedural performance and access-site complications between dTRA and pTRA and evaluated the early learning curve of dTRA. METHODS: We retrospectively analyzed 470 diagnostic cerebral angiography procedures, representing 421 unique patients, performed via radial access at a single center between January 2025 and February 2026, including 237 dTRA and 233 pTRA procedures. Baseline characteristics, including age, sex, body mass index (BMI) category, aortic arch type, and antiplatelet/anticoagulant use, procedural performance, and clinically assessed access-site events were compared between groups. Radial artery occlusion (RAO) was assessed by postoperative bedside pulse examination and confirmed with Doppler ultrasound when clinical findings were uncertain. Multivariable logistic regression was used to evaluate predictors of RAO, persistent bleeding or repeated compression, hand edema, and a composite access-site event endpoint. Because repeated procedures occurred in a subset of patients and event counts were limited, first-procedure sensitivity analysis and analyses of infrequent outcomes were interpreted cautiously. The dTRA learning process was assessed in the first 100 dTRA cases performed by a single operator using multivariable regression, cumulative sum (CUSUM) analysis, segmented trend analysis, and phase-based comparisons. RESULTS: Baseline characteristics were comparable between groups, including age, male sex, BMI category, aortic arch type, and antiplatelet/anticoagulant use. Compared with pTRA, dTRA was associated with more puncture attempts (3.0 [2.0-4.0] vs 2.0 [1.0-3.0], P < 0.001), longer puncture time (2.0 [1.0-5.0] vs 2.0 [1.0-3.0] min, P = 0.003), lower first-pass success (19.4% vs 35.2%, P < 0.001), and a higher crossover rate (11.4% vs 6.0%, P = 0.037). However, dTRA was associated with a lower clinically assessed RAO rate (2.5% vs 7.7%, P = 0.011). On multivariable analysis, pTRA was independently associated with higher odds of RAO (OR 3.27, 95% CI 1.26-8.49, P = 0.015) and the composite access-site event endpoint (OR 3.12, 95% CI 1.55-6.28, P = 0.001). Similar findings were observed in a sensitivity analysis restricted to the first procedure per patient. In the first 100 dTRA cases, cumulative dTRA experience was independently associated with shorter total procedure time (beta = -0.074 min/case, P = 0.009), while CUSUM and moving-average analyses suggested that the major learning effect occurred within approximately the first 10-15 cases. CONCLUSIONS: In this retrospective single-operator cohort, dTRA was associated with lower clinically assessed RAO than pTRA despite greater access difficulty. The early learning effect was mainly reflected in shorter total procedure time. These findings support the feasibility of dTRA but should be interpreted cautiously given the study's observational design and limited anatomical data.

Humans↗

PubMed2026

Global Seroprevalence of Q Fever Antibodies to Coxiella burnetii in Children and Adolescents : A Systematic Review and Meta-analysis.

OBJECTIVE: To comprehensively determine global estimates of Q fever seroprevalence in children and adolescents by conducting a systematic review and meta-analysis. DATA SOURCES: Searches of published articles in MEDLINE, Embase and Scopus databases were conducted from inception until February 2025. STUDY SELECTION: Cross-sectional studies reporting seroprevalence of Q fever/ Coxiella burnetii antibodies, using any established laboratory test, in any population of healthy children and adolescents <20 years old were included. The quality of eligible articles was assessed using a modified Newcastle-Ottawa Scale. DATA EXTRACTION: Data from eligible articles were extracted using a standardized form, which included year of publication, year(s) the study was conducted, numbers of antibody-positive cases/specific population, age, country, geographic region, serology test used and antibody titer cutoff value. DATA SYNTHESIS: DerSimonian and Laird random effects models were used to calculate pooled seroprevalence estimates and 95% confidence intervals in data from 41 eligible articles reporting 42 studies comprising 9841 children and adolescents. Q fever seroprevalence was observed in multiple countries across 7 geographic regions, and varied markedly between countries and regions, with the highest estimate observed by an individual country in Ethiopia (45%) and by region in the Middle East (14%). Seroprevalence estimates were higher in older children and adolescents ≥10 years (15%) compared with younger children <10 years of age (8%). CONCLUSION: Despite varying geographical prevalence, our findings demonstrate that widespread exposure to Q fever antigens occurs across multiple global regions in children and adolescents to potentially serious C. burnetii infection, indicating that diagnostic surveillance and preventive measures should be considered in both endemic and previously unreported areas.

Humans↗

PubMed2026

A framework for delivering real-time, instrument-relative navigation in transoral robotic surgery.

Transoral robotic surgery (TORS) is a minimally invasive, inside-out technique that, compared with traditional open approaches, provides fewer post-operative complications, shorter hospital stays, and improved survival for early-stage head and neck cancer. However, TORS is limited by its steep learning curve and poor visualization of deep tumor margins. This randomized crossover study evaluated a surgical navigation system's potential to enhance accuracy and user experience with real-time, instrument-relative feedback. Seven Teflon beads (d = 2.381 mm) were embedded at the tongue base of a porcine pharynx-and-larynx model. Tongue blade compression and retraction were applied to the model to mimic intraoperative tissue deformation, reproducing the anatomical shifts that occur relative to preoperative imaging. Eight participants used the da Vinci Surgical system to localize the beads by placing pins under two conditions: (a) preoperative computed tomography with no navigation; (b) model-based visual navigation with quantitative instrument-to-target metrics. Surgical accuracy was determined by calculating the target localization error (TLE, pin-to-bead Euclidean distance) and the angular error (AE, pin axis trajectory to bead). Accounting for training level and bead depth, surgical navigation reduced TLE by 5.44 mm (95% CI, 4.02-6.86 mm; p = 2.00e-11) and AE by 8.47 degrees (95% CI, 6.21-10.72 degrees; p = 5.17e-11). Impressions of the system were generally favorable using a 5-point Likert survey and task duration (p = 0.26) or cognitive workload via the NASA-Task Load Index (p = 0.22) were not significantly affected. The navigation system demonstrated translational promise, offering improved target localization accuracy and more consistent performance across experience levels, two critical determinants of surgical quality in TORS.

Robotic Surgical Procedures↗

PubMed2026

Integrated salivary proteomic and metabolomic analyses reveal molecular characterization and novel biomarker panels of chronic obstructive pulmonary disease.

Chronic obstructive pulmonary disease (COPD) is a respiratory disorder characterized by chronic inflammation, oxidative stress, and metabolic dysregulation. The lack of convenient and easily-accessible non-invasive diagnostic approaches remains a major clinical challenge. This study applied an integrated saliva-based proteomic and untargeted metabolomic strategy to identify potential biomarkers for COPD classification. Comprehensive multi-omics analyses identified 225 differentially abundant proteins and 60 differentially abundant metabolites between patients with COPD and healthy controls, including 24 biologically relevant endogenous metabolites. Functional enrichment analyses revealed pronounced dysregulation of mitochondrial energy metabolism, redox homeostasis, lipid remodeling, and inflammatory-related pathways in COPD. By integrating salivary proteomic and metabolomic biomarkers, a stepwise feature selection combined with LASSO logistic regression was used to construct diagnostic models, yielding an optimized biomarker panel consisting of 11 proteins and 2 endogenous metabolites. This integrated model achieved excellent diagnostic performance, with an area under the ROC curve of 0.96. Collectively, these findings demonstrate that integrated salivary proteomic and metabolomic profiling provides a robust, non-invasive approach for COPD classification and offers a promising foundation for the development of biosensor-based diagnostic platforms and early disease detection. SIGNIFICANCE: Chronic obstructive pulmonary disease (COPD) remains a major global health burden. Current diagnostic approaches rely largely on spirometry and clinical assessment, which are limited in sensitivity for early-stage disease and unsuitable for large-scale screening. This study employs an integrated saliva-based proteomic and metabolomic strategy to identify non-invasive biomarkers for COPD classification. Our findings reveal coordinated dysregulation of mitochondrial energy metabolism, redox homeostasis, and lipid remodeling in COPD, highlighting the interconnected roles of metabolic reprogramming, oxidative stress, and inflammation in disease pathophysiology. Notably, a robust diagnostic panel comprising 11 proteins and 2 endogenous metabolites was established, achieving excellent classification performance (AUC of 0.96). To our knowledge, the integrated application of salivary proteomics and metabolomics for COPD diagnosis remains largely unexplored, underscoring the significance and translational potential of our findings.

Humans↗

PubMed2026

Predicting ACL injury risk in athletes: A systematic review of machine learning-based models.

BACKGROUND: Early ACL injury risk identification in athletes is essential. This systematic review examines machine learning (ML) models for predicting ACL injuries, evaluating their methodological quality, performance, and reliability. METHOD: A comprehensive electronic search was conducted across PubMed, Scopus, Web of Science, and IEEE Xplore databases, supplemented by Google Scholar for grey literature, covering articles published between January 1, 2015, and August 30, 2025. Eligible studies were appraised using the Prediction Model Study Risk of Bias Assessment Tool (PROBAST) for methodological quality and risk of bias, and the Transparent Reporting of a Multivariable Prediction Model for Individual Prognosis or Diagnosis (TRIPOD) guidelines for quality of evidence. RESULTS: Ten studies were included. PROBAST showed eight studies had moderate risk of bias and two low risk. TRIPOD found only two studies met quality criteria. ML models included logistic regression (n = 5), support vector machines (n = 4), k-nearest neighbor (n = 3), decision trees (n = 3), random forests (n = 5), neural networks (n = 2), linear discriminant analysis (n = 1), and pre-trained CNNs (n = 1). AUC ranged from 0.63 to 0.98. Accuracy (reported in six studies) ranged from 26% to 95%; however, these values should be interpreted with caution due to the absence of confidence intervals, lack of class imbalance handling, and limited external validation across studies. Tree-based ensemble methods such as random forest achieved competitive accuracy (74-86%), while SVM, a non-ensemble classifier, reported accuracy ranging from 71% to 95%; however, the highest values were obtained in studies with notably small sample sizes (n = 12 to n = 39), raising concerns about overfitting and generalizability. CONCLUSION: Current ML algorithms show promise for identifying athletes at high ACL injury risk and detecting relevant risk factors. Although study quality was generally satisfactory, future research should prioritize external validation and model interpretability to support clinical translation.

Humans↗

PubMed2026

Robotic-assisted transbronchial biopsy versus computed tomography-guided transthoracic needle biopsy for peripheral pulmonary lesions: a systematic review and meta-analysis of direct comparative studies.

Robotic-assisted bronchoscopy (RAB) and computed tomography-guided transthoracic biopsy (CTTB) are competing strategies for sampling peripheral pulmonary lesions (PPLs). Whether they differ in yield or safety is uncertain. To our knowledge, this is the first systematic review restricted to direct comparisons. We searched MEDLINE, Europe PMC, Scopus, Web of Science and ClinicalTrials.gov from inception to 7 July 2026 for studies directly comparing RAB with CTTB in adults with PPLs. The primary outcome was strict 2024 American Thoracic Society/American College of Chest Physicians diagnostic yield. Risk of bias was assessed with ROBINS-I and certainty with GRADE. A cohort-genealogy step identified, per outcome, the largest set of cohorts sharing no patients; only that set was pooled, with Hartung-Knapp and Mantel-Haenszel sensitivity analyses. Five retrospective studies from one US health system were eligible. Four share patients; at most three cohorts are mutually independent. Across those three, diagnostic yield was comparable (risk ratio [RR] 0.99, 95% confidence interval [CI] 0.93-1.06; I²=24%; Hartung-Knapp 0.87-1.13), with an identical relative effect under strict and intermediate definitions although absolute yields fell from 88% to 74-84% under strict criteria. Pneumothorax requiring a chest tube and/or admission was about three-quarters less frequent with RAB across all three cohorts (RR 0.25, 95% CI 0.14-0.46; I²=0%; Hartung-Knapp 0.07-0.96). Strict yield (RR 0.99) and any pneumothorax (RR 0.06) were reported by two cohorts each and neither survives the few-studies correction. RAB took about 50 min longer than CTTB where same-session staging endobronchial ultrasound was counted in the robotic time, but only about 8 min longer than CTTB where it was not. Only one cohort reported yield by lesion size category and none reported yield by bronchus sign or lung zone, so lesion-level subgroups could not be pooled. Certainty was low for pleural complications and very low elsewhere. Low-certainty evidence indicates that RAB is associated with fewer pleural complications, with no statistically detectable difference in diagnostic yield; equivalence was not formally established. Because all evidence is retrospective, confined to one health system, and almost never stratified by lesion size or accessibility, these findings are hypothesis-generating and require a multicenter randomized trial.

Humans↗

PubMed2026

Routine methods misidentify Serratia spp.: Limitations of MALDI-TOF MS revealed by whole-genome sequencing.

Accurate species-level identification within the genus Serratia remains challenging due to extensive phenotypic overlap and high genomic relatedness among closely related and recently described taxa. This study presents an evaluation of routine and genome-based identification approaches applied to clinical Serratia isolates, integrating phenotypic assays, MALDI-TOF MS (Bruker Daltonics), 16S rRNA gene sequencing, and Whole-Genome Sequencing (WGS). A total of 103 isolates collected from a teaching hospital were analyzed. WGS was performed on a subset of isolates. Conventional biochemical methods classified all isolates as Serratia marcescens, whereas MALDI-TOF MS identified 60.1% as S. marcescens, 11.6% as S. ureilytica, and 28.1% just at the genus level. Peak analysis from MALDI-TOF MS revealed specific peaks associated with S. marcescens and S. ureilytica, but limited discriminatory power. WGS of six isolates initially identified as S. ureilytica by MALDI-TOF MS revealed reclassification as Serratia sarumanii (n = 5) and Serratia montpellierensis (n = 1), supported by Average Nucleotide Identity (ANI), Average Amino Acid Identity (AAI), and Digital DNA-DNA Hybridization (dDDH) thresholds. In contrast, 16S rRNA analysis showed limited species-level resolution. Phylogenomic and SNP-based analyses confirmed these classifications with strong support. Overall, this study underscores the critical role of high-resolution genomic approaches for precise species identification and highlights the need for continuous expansion and curation of MALDI-TOF MS reference databases to support reliable clinical diagnostics and epidemiological surveillance of emerging Serratia species.

Spectrometry, Mass, Matrix-Assisted Laser Desorpti↗

PubMed2026

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↗