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PubMed2026

Artificial Intelligence Cannot Replace Peer Reviewers but May Help Editors Triage: A Comparative Analysis of a Large Language Model and Human Reviewer Recommendations at the American Journal of Sports Medicine.

BACKGROUND: The peer review system faces increasing strain from rising manuscript volumes, reviewer fatigue, and well-documented interreviewer disagreement. Large language models (LLMs) have shown potential to support the peer review process, but their ability to replicate editorial decisions at high-impact medical journals and their utility as manuscript screening tools remain unknown. PURPOSE: To compare the agreement between an LLM and the final editorial decision on manuscripts submitted to the American Journal of Sports Medicine and to evaluate the potential of LLMs as a manuscript screening tool. STUDY DESIGN: Cross-sectional agreement study. METHODS: Fifty-four manuscripts randomly selected from submissions to the American Journal of Sports Medicine (September 2024-October 2024) were reviewed by a locally deployed LLM (Ministral 3 14B; Mistral AI) using a standardized prompt. The artificial intelligence (AI) produced a categorical recommendation (reject, cascade, revision, or accept) and a numerical score (0-100) for each manuscript. Agreement with the final editorial decision was assessed by Cohen kappa (4-category model) for pooled human reviewers (n = 139 reviews) and the AI (n = 54). Screening performance was evaluated by positive predictive value (PPV), sensitivity, and specificity. RESULTS: Pooled human reviewers demonstrated fair agreement with the final decision (κ = 0.181 [P < .001]; 42.4% agreement), while the AI demonstrated slight, nonsignificant agreement (κ = 0.126 [P = .099]; 37.0% agreement). The AI recommended revision for 61.1% of manuscripts, of which 72.7% were ultimately rejected or cascaded, demonstrating systematic "revision bias." When the AI recommended rejection, 54.5% of those manuscripts were ultimately rejected and 27.3% were cascaded; when the AI recommended cascade, 50% were rejected and 50% were cascaded. However, when the AI recommended rejection or cascade (n = 21), 90.5% received a final decision of rejection or cascade (PPV, 90.5%; specificity, 81.8%). Manuscripts with an AI score <70 were rejected or cascaded 88.0% of the time (PPV, 88.0%). CONCLUSION: AI cannot replicate the nuanced judgment of human peer reviewers at a high-impact sports medicine journal. When AI recommended rejection or cascade, 90.5% of manuscripts received that final decision (descriptive PPV, 90.5%; 95% CI, 71.1%-97.3%), suggesting potential utility as an exploratory first-pass screening tool warranting further validation in larger cohorts. However, AI could not reliably distinguish manuscripts destined for outright rejection from those that would be cascaded to a sister journal-an important limitation for editorial triage applications.

Sports Medicine↗

PubMed2026

Behind the Curtain of Care. Nurses' Experiences Providing Care to Consumers With Alcohol and Other Drug Issues: A Qualitative Scoping Review.

AIM: To scope and synthesise qualitative literature relating to nurses' experiences of providing care to consumers with alcohol and other drug issues and explore how meaning is constructed in practice. DESIGN: Scoping review. METHODS: A scoping review was conducted following Arksey and O'Malley's framework. Findings were analysed using thematic analysis. DATA SOURCES: Systematic searches were conducted between September and November 2025 across Medline, Emcare, CINAHL and Google Scholar, using controlled vocabulary and keywords relevant to nurses' experiences of providing care to consumers with alcohol and other drug issues. RESULTS: Twenty-four studies from 12 countries were included. Seven themes were identified: emotional aspects of care, education, training and skills in practice, the spectrum of stigma, ethical issues in professional practice, navigating pain management, limited support, and how meaning is constructed in practice. CONCLUSION: Nurses' experiences of providing care to consumers with alcohol and other drug issues are shaped by multiple intersecting factors influencing care delivery and professional practice. Further research is needed to examine how workplace culture, language and interpersonal interactions influence healthcare experiences, and inform education, service development and support needs. REPORTING METHOD: Reported in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) checklist. PATIENT OR PUBLIC CONTRIBUTION: No patient or public contribution.

alcohol and other drugs↗

PubMed2025

Enhanced fracture detection on radiographs with AI assistance for clinicians: a systematic review and meta-analysis.

BACKGROUND: Emergency radiographic interpretation for fractures is prone to missed or misdiagnoses. Artificial intelligence (AI) is expected to become a powerful tool to assist clinicians in fracture detection. PURPOSE: A systematic review and meta-analysis was performed to assess whether AI improves clinicians' ability to detect fractures on radiographs. MATERIALS AND METHODS: A literature search was conducted in PubMed, Web of Science, and Cochrane Library for studies published between January 1, 2010, and October 10, 2025. A meta-analysis of diagnostic accuracy studies was performed using a Summary Receiver Operating Characteristic (SROC) curve. The quality of included studies was assessed using the Quality Assessment of Diagnostic Accuracy Studies 2 (QUADAS-2) tool. Subgroup analysis and meta-regression were conducted to explore potential sources of heterogeneity. RESULTS: A total of 26 studies were included . The pooled sensitivity of clinicians increased from 77% (95% CI: 72-81) to 87% (95% CI: 83-90) with AI assistance, while the pooled specificity improved from 88% (95% CI: 85-90) to 92% (95% CI: 89-94). The corresponding AUC values were 0.90 (95% CI: 0.87-0.92) before and 0.95 (95% CI: 0.93-0.97) after AI assistance. Eight studies were rated as high risk of bias. Subgroup analysis and meta-regression identified potential sources of heterogeneity, including fracture location, AI model type, high risk of bias, and reference standards. CONCLUSION: AI assistance significantly improves clinicians' diagnostic performance in detecting fractures on radiographs for extremity and trunk fractures.

Humans↗

PubMed2026

Health-Related quality of life (HRQoL) and health state utility values (HSUV) in patients with head and neck Cancer: A systematic review and Meta-Analysis.

BACKGROUND: Head and neck cancer (HNC) and its treatment can substantially impair speech, swallowing, eating, appearance, and social functioning, resulting in persistent reductions in health-related quality of life (HRQoL). Although the EuroQol 5-Dimensions questionnaire (EQ-5D) is widely used to assess generic HRQoL and derive health state utility values (HSUVs), EQ-5D-based evidence in HNC has not been comprehensively synthesized. This study aimed to summarize EQ-5D-based HRQoL and HSUVs in HNC, estimate pooled utility and EQ-VAS scores, explore subgroup differences, and identify predictors of poorer HRQoL. METHODS: A systematic review and meta-analysis was conducted according to PRISMA guidelines and registered in PROSPERO (CRD420261307907). PubMed, EMBASE, Web of Science, Cochrane Library, and Scopus were searched from inception to February 10, 2026. Studies reporting baseline EQ-5D utility values and/or EQ-VAS scores in patients with HNC were included. Random-effects meta-analyses using the DerSimonian-Laird (DL) estimator with the Hartung-Knapp-Sidik-Jonkman (HKSJ) adjustment were performed to pool mean scores. Between-study variance (τ2) and 95 % prediction intervals (PI) were calculated to capture parameter dispersion. Subgroup analyses were conducted across clinical and methodological vectors. RESULTS: Twenty studies involving 7,403 patients were included. The pooled mean EQ-5D utility score was 0.79 (95 % CI: 0.75-0.83; τ2 = 0.0011; 95 % PI: 0.72-0.86). The pooled mean EQ-VAS score was 69.36 (95 % CI: 65.71-73.01; τ2 = 38.4586; 95 % PI: 55.11-83.61). Extreme heterogeneity was observed (I2 = 96.4 % and 97.1 %, respectively). Utility values were significantly higher in studies utilizing the EQ-5D-5 L than the EQ-5D-3 L version (0.82 vs. 0.76). By tumor subsite, nasopharyngeal cancer showed the highest utility value (0.85, exploratory), whereas oral cancer demonstrated the lowest (0.73). Adjusted multivariable models revealed that advanced stage, high treatment intensity, severe pharyngolaryngeal pain, dysphagia, malnutrition, and older age were robust predictors of poorer HRQoL. CONCLUSIONS: Patients with HNC experience substantial and persistent HRQoL impairment, with meaningful variations driven by tumor subsites and instrument versions. In light of the extreme heterogeneity, these pooled findings establish a macro-level, broad reference estimate rather than a fixed target. These parameters directly inform localized survivorship care planning, health technology evaluations, and cost-utility decision-making modeling in head and neck oncology.

Humans↗

PubMed2026

Beyond antigen matching: compatibility intelligence theory for transfusion as an emergent biological system.

BACKGROUND: Despite major advances in serologic testing, extended phenotyping, and blood group genomics, clinically similar transfusion exposures may result in markedly different immune and clinical outcomes. Existing compatibility strategies do not fully explain this biological variability. OBJECTIVES: To examine transfusion compatibility as an emergent donor-recipient biological state and propose a systems-level conceptual framework that integrates established biological determinants into a testable model for future precision transfusion medicine. METHODS: This narrative review critically synthesizes current evidence from blood group genomics, recipient immunobiology, inflammation, disease-specific biology, transfusion medicine, and computational prediction. The proposed framework distinguishes Compatibility Intelligence Theory (CIT) as a biological interpretation from Precision Transfusion Intelligence (PTI) as its potential clinician-supervised translational application. RESULTS: The review argues that transfusion compatibility is shaped by interactions among donor genetics, recipient immune biology, inflammatory physiology, disease context, transfusion history, and longitudinal adaptation rather than by antigen matching alone. CIT provides an organizational framework for integrating these determinants, whereas PTI describes a possible clinician-supervised translation. To address current feasibility, the revised framework separates variables into routinely measurable, contextually available but incompletely standardized, and research-stage domains, and proposes a staged strategy for deriving rather than assuming their quantitative weights. Any clinical implementation would require comparative validation against current serologic, phenotypic, and genotype-based practice. CONCLUSIONS: Compatibility Intelligence Theory offers a testable systems-level framework for understanding transfusion compatibility without replacing established transfusion practices. The framework is not presented as a ready-to-use score: currently measurable variables can be organized for structured risk review, whereas inflammatory, immunogenetic, and multi-omic inputs require prospective standardization and validation. If future studies demonstrate incremental predictive and patient-centered benefit, CIT-informed PTI could support an adaptive, evidence-based extension of current precision transfusion practice.

Humans↗

PubMed2026

Characteristics of children with ureteroceles presenting for urological evaluation in the modern medical era.

INTRODUCTION: Historically, children with ureteroceles presented symptomatically and were managed surgically. It is unclear if this changed in the modern medical era of prenatal imaging and shared decision making. We aimed to describe the presentation and management of ureteroceles during initial urological evaluation of children in the era of widespread prenatal ultrasonography. PATIENTS AND METHODS: We retrospectively reviewed records of children (<18 years old [yo]) initially evaluated at our center with a ureterocele (2011-2020). We analyzed demographics, renal anatomy, initial presentation for evaluation, and initial management with non-parametric statistics. Febrile urinary tract infections (fUTIs, ≥ 38 °C) were classified as 1) urosepsis (positive urine culture admitted to pediatric intensive care), 2) documented (positive urine culture) or 3) family-reported. RESULTS: We identified 188 children (65% female). Median age at presentation was 1.2 months old (mo) (IQR 18 days-4.4 mo). Antenatally-detected congenital anomalies of the kidney and urinary tract (aCAKUT) were noted in 143 (76%) children with a confirmed postnatal diagnosis of ureterocele. Overall, 129/188 (69%) children presented without symptoms and 59 (31%) presented with symptoms. fUTI was the most common symptomatic presentation (46/188, 24%): urosepsis (6 children), documented (30), and family-reported (10). Children with aCAKUT presented earlier than those without aCAKUT (27 days vs. 1.6 yo, p < 0.0001). They were also less likely to present with symptoms (11% vs. 96%, p < 0.0001), including fUTIs (7% vs. 78%, p < 0.0001). In total, 108 children (57%) were initially managed with transurethral incision, 73 (39%) were observed, and 7 (4%) had reconstructive surgery. Asymptomatic children with aCAKUT (42%) and symptomatic children without aCAKUT (37%) were more likely to be observed than symptomatic children with aCAKUT (7%, p = 0.02). Among 143 children with aCAKUT, those on antibiotic prophylaxis were less likely to present with a history of a fUTI compared to those not on prophylaxis (4/106 vs. 6/37, 4% vs. 16%, p = 0.02). COMMENT: We present a large observational study describing clinical and anatomical characteristics of children presenting with ureteroceles in a medical era of ubiquitous prenatal ultrasonography. Our retrospective study was limited by incomplete documentation of all antenatal ultrasonography and adherence with antibiotic prophylaxis. Long-term clinical outcomes will be the focus of future work. CONCLUSION: In contrast to historical cohorts, most children presented to urologists with asymptomatic ureteroceles diagnosed with aCAKUT. Most children without aCAKUT presented with a fUTI. Overall, 39% of children were initially observed, indicating an increased use of observation in the modern medical era.

Humans↗

PubMed2026

Construction of precision clinical-proteomics risk model based on machine learning for predicting heart failure in type II diabetes mellitus.

BACKGROUND AND AIMS: Heart failure (HF) is a severe complication in type 2 diabetes mellitus (T2DM), but current risk stratification scores have limited predictive accuracy. We aimed to develop novel prediction tools integrating clinical variables with proteomics to improve risk stratification of hospitalization for HF in T2DM. METHODS AND RESULTS: In this study, we included 2111 UK Biobank participants with T2DM but no prior HF, and profiled 2920 proteins to predict 10-year incident HF hospitalization. Participants were randomly divided into training (70%), tuning (10%), and validation (20%) sets.Three prediction models were developed: a Clinical model based on demographic characteristics, comorbidities, medication use, and laboratory indices; a Protein model based on 40 proteins selected by the Light Gradient Boosting Machine (LGBM); and the Clinical OMics and Protein ASSessment for Heart Failure (COMPASS-HF) model, which integrated both clinical variables and the LGBM-selected proteins. Models were evaluated for area under the curve (AUC), sensitivity, and specificity. During follow-up, 168 participants (7.96%) developed incident HF. The COMPASS-HF model showed better discrimination than the Clinical model, with an AUC of 0.897 (95% CI: 0.850-0.945) versus 0.790 (95% CI: 0.723-0.856). It also demonstrated higher sensitivity (0.882; 95% CI: 0.725-0.967) and consistent performance in subgroups. COMPASS-HF effectively stratified risk of hospitalization for HF, with cumulative incidence rates of 31.9% in the high-risk group and 1.2% in the low-risk group. CONCLUSIONS: By combining clinical and proteomic variables, we developed a high-performance HF prediction model for T2DM, enabling precise risk stratification and informing early intervention strategies.

Humans↗

PubMed2026

Accelerated Diagnostic Pathways for Suspected Acute Coronary Syndrome in Practice: A Randomized Trial of 0/1-Hour vs 0/3-Hour Troponin Testing.

BACKGROUND: For suspected acute coronary syndrome (ACS), guidelines recommend using high-sensitivity troponins (hs-cTn) in accelerated diagnostic pathways (ADPs) with 0/1-hour recommended over 0/3-hour ADP. However, implementation of these ADPs, with universal use of hs-cTns, has not been directly compared in randomized trials OBJECTIVES: This study sought to compare the efficiency and safety of the European Society of Cardiology (ESC) 0/1-hour and a 0/3-hour ADP when implemented in real-world clinical practice. METHODS: This pragmatic, randomized, noninferiority implementation trial compared the safety and efficiency of clinician decision making using these 2 pathways. To prevent incorporation bias, an independent hs-cTnI was used for formal adjudication using the fourth universal definition of myocardial infarction (MI). Efficiency was judged by the proportion of patients discharged within 4 hours. The safety endpoint was major adverse cardiac events (MACE) within 30 days (adjudicated index or representation type 1 MI, cardiovascular death, and urgent coronary revascularization) for those who were considered not to have ACS and discharged. The noninferiority margin, for absolute difference in sensitivity, between the ESC 0/1-hour and the 0/3-hour ADP was set at 3%, assessed with a 1-sided 97.5% CI. RESULTS: From December 2021 to July 2024, of 13,983 screened 3,543 individual patients with suspected ACS were recruited and consented from 2 major emergency departments in North-West England, with 100% follow-up achieved for all representations to any national hospital. The median age was 60 years (IQR: 49.5-70.5 years), 53% were men, 6.7%, and 7.6% had adjudicated index type 1 MI and MACE within 30 days, respectively. The turnaround time from sample to result for central laboratory hs-cTnT was 81 minutes (IQR: 69-101 minutes). The proportion of patients discharged within 4 hours was relatively low and did not differ substantially (21.8% vs 19.2%, P = 0.07). In addition, the 0/1-hour pathway was noninferior for safety, in patients discharged, compared with the 0/3-hour pathway, absolute difference in sensitivity was +4.2% (1-sided 97.5% CI: -2.5) in favor of the 0/1-hour pathway. The calculated sensitivities were 93.7% (95% CI: 88.4%-97.1%) vs 89.5% (95% CI: 82.7%-94.3%), respectively. CONCLUSIONS: Implementation of the ESC 0/1-hour pathway failed to discharge significantly more patients within 4 hours of presentation compared with the 0/3-hour ADP. In addition, The ESC 0/1-hour was noninferior to the 0/3-hour hs-cTn pathway for safety of discharge, although safety for both pathways was less than that imputed by observational studies. This trial demonstrates that perceived benefits to emergency department efficiency of a reduced sampling interval are mitigated by central laboratory turnaround times as well as system constraints. (Pragmatic Randomised Trial of the ESC 0/1 Versus 0/3 Hour Troponin Pathway [MACROS2]; NCT05322395).

Acute Coronary Syndrome↗

PubMed2026

Portable metagenomics for preventive surveillance and outbreak control in livestock and poultry: Pathogen detection, resistome profiling, and antimicrobial stewardship.

Conventional diagnostics for livestock and poultry outbreaks commonly rely on culture or targeted PCR panels, which may be too slow or too narrow to guide early control decisions. Portable metagenomics, particularly real-time nanopore sequencing, offers a route to broad pathogen detection, antimicrobial-resistance gene profiling, and outbreak investigation within an integrated workflow. This implementation-focused review evaluates how near-point-of-care metagenomics may support preventive veterinary medicine through earlier detection, surveillance, cohorting, biosecurity decisions, and antimicrobial stewardship. We synthesize sample-to-answer workflows for enteric and respiratory disease in food-producing animals, including sampling, nucleic-acid extraction, host depletion or target enrichment, library preparation, sequencing, bioinformatics, quality control, and interpretation. Applications in calf diarrhea, bovine respiratory disease, poultry outbreaks, mastitis, and resistome monitoring are considered alongside the central limitation that detection alone does not establish causation. Pathogen and resistance-gene signals must therefore be interpreted with clinical signs, lesions, epidemiology, controls, and confirmatory testing. We also propose a minimum reporting checklist, intended as a practical framework rather than a validated consensus standard. Portable metagenomics is not a replacement for conventional diagnostics, but appropriately validated workflows can reduce uncertainty during time-sensitive outbreaks and support more judicious antimicrobial use.

Animals↗

PubMed2026

Long-term hormone therapy for perimenopausal and postmenopausal women.

BACKGROUND: Hormone therapy is widely provided to control menopausal symptoms and has been used for the management and prevention of cardiovascular disease, osteoporosis and dementia in older women. This is an updated version of a Cochrane review first published in 2005. OBJECTIVES: To assess the long-term effects of prolonged use (at least one year) of hormone therapy on mortality, cardiovascular outcomes, cancer, gallbladder disease, fractures and cognition in perimenopausal and postmenopausal women. SEARCH METHODS: We used the Cochrane Gynaecology and Fertility Group Specialised Register, CENTRAL, MEDLINE, three other databases and two trial registers, together with reference checking, citation searching and contact with study authors to identify the studies included in the review. The latest search date was 26 September 2024. SELECTION CRITERIA: We included randomised, double-blind trials in which peri- or postmenopausal women took hormone therapy or placebo for at least one year. We included various oestrogen formulations, with or without progestogens. We focused on studies assessing hormone therapy's effects on long-term clinical outcomes, including death, coronary events and cancer. Hormone therapy's efficacy in managing menopausal symptoms was beyond the scope of this review, and is assessed in other Cochrane reviews. DATA COLLECTION AND ANALYSIS: Two review authors independently selected studies, assessed risk of bias and extracted data. We calculated risk ratios (RRs) for dichotomous data and mean differences (MDs) for continuous data, along with 95% confidence intervals (CIs). We assessed the certainty of the evidence using GRADE. MAIN RESULTS: We included 24 studies - with two newly added in this update - involving 45,660 participants. We derived nearly 70% of the data from two well-conducted studies: the Heart and Estrogen/progestin Replacement Study (HERS 1998) and the large, multi-component Women's Health Initiative research programme, which included two hormone therapy arms (WHI 1998). Across all the studies, most participants were postmenopausal American women with one or more comorbidities. The mean participant age in most studies was over 60 years. Only one included study focused on perimenopausal women. We present full results for all included studies with available data in the main review. The results presented below are drawn from WHI 1998, in which the combined hormone therapy arm and the oestrogen-only arm were run concurrently, with women assigned to the appropriate trial based on their uterus status. One study with 16,608 postmenopausal women with an intact uterus compared combined continuous hormone therapy (conjugated equine oestrogen and medroxyprogesterone acetate) to placebo, and measured outcomes at an average of 5.6 years of follow-up. Based on this study, combined continuous hormone therapy probably makes little to no difference to the risk of a coronary event (RR 1.17, 95% CI 0.95 to 1.44; moderate-certainty evidence). It may increase the risk of stroke (RR 1.39, 95% CI 1.09 to 2.09; low-certainty evidence) and venous thromboembolism (RR 2.03, 95% CI 1.55 to 6.64; low-certainty evidence). Compared to placebo, combined continuous hormone therapy probably increases the risk of breast cancer (RR 1.27, 95% CI 1.03 to 1.56; moderate-certainty evidence) and probably makes little to no difference to the risk of lung cancer (RR 1.06, 95% CI 0.77 to 1.46; moderate-certainty evidence). It may increase gallbladder disease requiring surgery (RR 1.64, 95% CI 1.30 to 2.06; 14,203 participants; low-certainty evidence), and probably reduces the risk of all clinical fractures (RR 0.78, 95% CI 0.71 to 0.86; moderate-certainty evidence). One study including 10,739 postmenopausal women who had undergone a hysterectomy compared oestrogen-only (conjugated equine oestrogen) hormone therapy to placebo, and measured outcomes at an average of seven years' follow-up. Based on this study, oestrogen-only hormone therapy probably makes little to no difference to the risk of coronary events (RR 0.94, 95% CI 0.78 to 1.13), venous thromboembolism (RR 1.32, 95% CI 1.00 to 1.74) and breast cancer (RR 0.79, 95% CI 0.61 to 1.01), all with moderate-certainty evidence. It may make little to no difference to the risk of lung cancer (RR 1.04, 95% CI 0.73 to 1.48; low-certainty evidence). Oestrogen-only hormone therapy probably increases the risk of stroke (RR 1.33, 95% CI 1.06 to 1.67) and gallbladder disease requiring surgery (RR 1.78, 95% CI 1.42 to 2.24), and probably reduces the risk of all clinical fractures (RR 0.73, 95% CI 0.65 to 0.80), all with moderate-certainty evidence. We judged most included studies to have a low risk of bias for most domains. The overall certainty of evidence for the main comparisons was moderate. The main limitation was that only about 30% of women were 50 to 59 years old at baseline, the age group most likely to consider hormone therapy for vasomotor symptoms. AUTHORS' CONCLUSIONS: Long-term follow-up of women using hormone therapy suggests that the risk profiles vary between combined hormone therapy and oestrogen-only therapy. Oestrogen-only hormone therapy probably makes little to no difference to coronary events, and probably increases the risk of stroke and gallbladder disease. It probably makes little to no difference in the risk of breast cancer, and probably reduces the risk of all fractures. Combined hormone therapy may increase the risk of thromboembolism and probably increases the risk of breast cancer. These results should be interpreted with caution as they are based on one study using oral hormone therapy, which may not represent the risks of the hormone therapy currently used in clinical practice.

Humans↗

PubMed2026

Blinding integrity in psychedelic research: Evidence from a comparative randomized controlled trial of psilocybin, MDMA, and methylphenidate in healthy volunteers.

Maintaining effective blinding is a major methodological challenge in psychedelic research. This study provides a comprehensive evaluation of blinding integrity in 120 healthy volunteers who received either psilocybin, MDMA, or methylphenidate (active placebo) in a double-blind, randomized controlled trial. Using a multi-level assessment incorporating forced-choice substance guesses, certainty ratings, decision factors, and subjective substance effects, the analyses characterize blinding integrity and its relation to the substance experience. Results indicate that overall blinding was insufficient, with psilocybin showing the highest rates of functional unblinding, MDMA moderate levels, and methylphenidate the lowest. As an active placebo, methylphenidate provided more effective blinding for MDMA than for psilocybin. Incorporating certainty levels of substance guesses revealed a more differentiated pattern, with lower functional unblinding rates. Decision factors and subjective substance experiences were associated with phenomenological substance effects. Prior substance experiences did not influence accuracy of forced-choice substance guesses. These findings provide empirical guidance for the design and reporting of blinding procedures in psychedelic trials and underscore the value of systematic, multi-level assessment of blinding integrity.

Humans↗

PubMed2026

An individualized nomogram for predicting progression-free survival in systemic anaplastic large cell lymphoma: a multicenter, retrospective, and internally validated study.

OBJECTIVES: To develop an individualized nomogram for predicting disease progression risk in systemic anaplastic large cell lymphoma (sALCL). METHODS: Independent predictors of progression-free survival (PFS) were identified using Cox regression in a multicenter retrospective cohort of 109 sALCL patients (2010-2022). These were incorporated into a three-factor nomogram, evaluated via bootstrapped internal validation (1000 resamples), ROC analysis, C-index, decision curve analysis (DCA), and clinical impact curve (CIC). RESULTS: A total of 29 PFS events occurred during a median follow-up of 31 months. Multivariable modelling selected serum β2-microglobulin elevation, extranodal disease, and front-line chemotherapy choice (CHOP versus CHOPE or BV+CHP) as autonomous progression drivers. Upon internal bootstrap validation, the nomogram yielded strong prognostic accuracy, achieving AUCs of 0.81, 0.85 and 0.87 for 1-, 3- and 5-year progression-free survival, alongside a corrected C-index of 0.779 (95% CI: 0.699 - 0.861). Calibration plots showed close agreement between predicted and observed outcomes, while DCA confirmed superior net clinical benefit versus conventional IPI or Ann Arbor stratification across multiple decision thresholds. CONCLUSION: This first sALCL-specific nomogram integrates clinical and treatment variables to provide personalized PFS risk estimation. While internally validated, this exploratory, observation-based tool requires external validation and recalibration in prospective cohorts before clinical implementation.

Humans↗

PubMed2026

Molecular Diagnostics for WHO Priority Bacterial Pathogens: A Bibliometric Mapping of Diagnostic Platforms, Resistance Markers, and Antimicrobial Resistance Research Trends.

Antimicrobial resistance (AMR) constrains effective treatment and carries implications for infection control, surveillance, and public health. The World Health Organization (WHO) priority bacterial pathogen framework has intensified the need for diagnostic innovation by redefining research priorities around organisms combining high disease burden with complex resistance profiles. Molecular diagnostics have accordingly moved beyond culture-based workflows, integrating rapid pathogen identification, resistance-marker detection, genomic surveillance, and clinical decision support. The present study conducted a bibliometric mapping of the literature on WHO priority pathogens. Rather than addressing resistance at a general level or a single pathogen or technology, it integrates priority pathogens, molecular platforms, and resistance markers within a single framework, tracing their joint thematic and temporal evolution along an explicit pathogen-platform-marker axis. Scopus-indexed articles and reviews (2000-2025) were retrieved, yielding 1746 publications after screening adapted from the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Analyses used Bibliometrix/Biblioshiny, R, and VOSviewer. The literature expanded markedly after 2018, led by China and the United States. Methicillin-resistant Staphylococcus aureus (MRSA), Mycobacterium tuberculosis, Enterococcus faecium, and the Enterobacterales-carbapenemase axis constituted the principal thematic cores, whereas conventional polymerase chain reaction (PCR)/nucleic acid amplification testing (NAAT) and whole-genome sequencing were the dominant platforms. Overall, the field has evolved from pathogen detection into an AMR-centered translational domain encompassing resistance prediction, genomic epidemiology, surveillance, and clinical decision support. Diagnostic development, stewardship, and surveillance depend on hybrid workflows coupling rapid marker-targeted assays with genome-based characterization, delivering actionable resistance within clinically meaningful timeframes, and extending coverage to underrepresented pathogens and platforms.

Humans↗

PubMed2026

Artificial intelligence (AI) uses in stereotactic radiosurgery (SRS): diagnosis with brain metastasis (BM) - A systematic review.

BACKGROUND: Brain metastases (BM) are the most common intracranial tumors in adults, and stereotactic radiosurgery (SRS) has become a mainstay of management. However, several diagnostic challenges persist in the SRS pathway, particularly the differentiation of radiation necrosis (RN) from true tumor progression, which conventional MRI and even advanced imaging techniques often cannot reliably resolve. Recent advances in artificial intelligence (AI) offer the potential to address these diagnostic limitations. This systematic review synthesizes current literature on AI applications for MRI-based diagnostic decision support in BM patients undergoing SRS, with a focus on radiomics and deep learning tools for distinguishing RN from progression, classifying molecular and histologic subtypes, and predicting treatment response. METHODS: A systematic review was performed in accordance with PRISMA guidelines. PubMed, Web of Science, and Scopus were searched using a targeted query combining terms related to AI, brain metastasis, diagnosis or imaging, and SRS. After screening 483 records and applying strict inclusion and exclusion criteria, 18 studies published between 2015 and 2025 were included. Data were extracted on study design, cohort characteristics, imaging modality, AI methodology, validation strategy, and reported diagnostic performance. RESULTS: Among the 18 included studies, AI models demonstrated strong performance across diagnostic tasks in the BM-SRS pathway. The differentiation of RN from true tumor progression was the most extensively studied application, addressed by 14 of 18 studies, with reported AUCs ranging from 0.71 to 0.94. Support vector machines, random-forest ensembles, convolutional neural networks, and transformer-based multimodal architectures were widely used. The literature evolved from single-sequence radiomic classifiers in 2018 to multimodal deep learning frameworks fusing imaging with clinical and genomic data in 2025. Contrast-enhanced T1-weighted MRI was the dominant imaging input, and texture-based radiomic features (GLCM, GLSZM, GLDM, and wavelet-derived features) were the most consistently predictive. The highest-performing models reached AUCs of 0.85-0.91 through multimodal integration of imaging with clinical and genomic features, and consistently outperformed expert neuroradiologist read on matched cases. Remaining studies addressed longitudinal segmentation-based detection of local failure and adverse radiation effects, BRAF mutation status in melanoma BM, early Gamma Knife treatment response, and primary tumor histology classification, with more variable performance. CONCLUSION: AI models, particularly those integrating MRI-derived radiomic features with clinical and genomic data, show high accuracy in supporting diagnostic decisions for BM patients treated with SRS. The post-SRS differentiation of radiation necrosis from true tumor progression has reached the greatest level of maturity and is closest to clinical translation, with potential to reduce unnecessary biopsies, personalize surveillance intervals, and rationalize treatment-pathway decisions. Other diagnostic applications, including molecular subtyping and primary tumor histology classification, remain exploratory and require further multicenter validation. Integration of AI tools into multidisciplinary tumor-board workflows, combined with prospective validation and standardized reporting, will be essential to realize the full clinical benefits of AI in SRS for brain metastases.

Humans↗

PubMed2026

Artificial intelligence for anticancer drug discovery from natural products of macroalgae and sponges: A systematic review.

Marine natural products (MNPs) from macroalgae and marine sponges have inspired clinically important anticancer agents, including the cytarabine pharmacophore and the eribulin scaffold, while cyanobacterial dolastatin chemistry supplies the auristatin payloads of several marine-inspired antibody-drug conjugates (ADCs) such as brentuximab vedotin. Artificial intelligence (AI) methods, encompassing both classical machine learning (ML) with hand-engineered features and modern deep learning (DL) with many-layered neural networks, are increasingly supporting key decisions in natural-product anticancer drug discovery, including bioactivity prediction, target identification, absorption, distribution, metabolism, excretion and toxicity (ADMET) filtering, generative analogue design, and the selection of preclinical candidates. DL architectures relevant to this field include graph neural networks, transformer-based molecular generators, diffusion models for protein-ligand docking, and convolutional networks for mass spectrometry, while classical ML contributes interpretable fingerprint-based bioactivity models and molecular networking for dereplication. This review follows a systematic literature review methodology to organize the landscape of AI methods now applied to MNP anticancer discovery, distinguishing ML and DL approaches where relevant, situating them within the chemical context of macroalgal and sponge-derived oncology leads, and critically examining published case studies, including validation level (computational, in vitro, in vivo, clinical). The principal bottleneck for medical translation has shifted partly from algorithmic capability toward data infrastructure and experimental validation. Sparse, heterogeneous, and taxonomically biased bioactivity records limit what current models can learn and reduce the reliability of AI-prioritized candidates entering the preclinical pipeline. A roadmap is proposed that prioritizes open MNP-specific benchmarks, symbiont-aware modeling, and active learning loops with synthesizability and ADMET constraints. These AI workflows may accelerate the prioritization of marine-derived anticancer leads and support earlier, more evidence-based translational decisions in oncology drug development.

Biological Products↗

PubMed2026

Could the preoperative urethral curve be used to predict immediate urinary continence following Retzius-sparing robot-assisted radical prostatectomy? A retrospective multi-center study.

PURPOSE: Immediate urinary continence (UC) recovery following Retzius-sparing robot-assisted radical prostatectomy (RS-RARP) remains highly variable, highlighting the need for reliable preoperative prediction. We aimed to develop and validate models to identify patients likely to achieve immediate UC recovery following RS-RARP. MATERIALS AND METHODS: A total of 580 prostate cancer patients who underwent RS-RARP from four medical centers were assigned to a training set (n=348), an internal validation set (n=103) and an external validation set (n=129). Independent predictors were identified through univariate analysis and LASSO regression. A nomogram was constructed using multivariate logistic regression. Its performance was evaluated with receiver operating characteristic (ROC) curve, calibration curves, and decision curve analysis. RESULTS: Immediate UC recovery was observed in 84.5% (294/348) of patients in the training cohort, 80.6% (83/103) in the internal validation cohort, and 81.4% (105/129) in the external validation cohort, respectively. Multivariate analysis identified membranous urethral length (MUL) (OR=1.23, P=0.029) and urethral curvature (OR=2.84, P<0.001) as independent predictors, while prostate volume (PV) (OR=0.84, P <0.001) as a protective factor. The nomogram integrating MUL, PV, and urethral curvature demonstrated superior predictive accuracy, with an AUC of 0.87 (95% CI, 0.83-0.91) in the training cohort. The bootstrap-corrected calibration slope was 0.96, and the Brier score was 0.08. Calibration curves and decision curve analysis confirmed the predictive accuracy and clinical utility of the nomogram. CONCLUSIONS: Our study introduces a novel quantitative method for assessing urethral curvature. The mpMRI-based model, integrating urethral curvature and prostate spatial configuration, offers enhanced predictive accuracy for postoperative immediate UC recovery.

Humans↗

PubMed2026

Beyond predictive performance: A systematic review and critical methodological appraisal of AI/ML and conventional modelling strategies in breast, colorectal, and pancreatic Cancer.

BACKGROUND: Predictive modelling for cancer risk, treatment-related complications, and survival is central to precision oncology. Conventional logistic regression (LR) and Cox proportional hazards (CoxPH) regression remain widely used but are limited when modelling nonlinear interactions, high-dimensional imaging features, and multimodal clinical-metabolic predictors. Artificial intelligence (AI) and machine learning (ML) methods offer expanded capability through automated feature extraction, ensemble learning, and flexible survival modelling, but the evidence on when AI/ML adds value over conventional models across cancer sites and predictive tasks remains fragmented. OBJECTIVE: To systematically evaluate the methodological performance, validation strategies, and translational limitations of AI/ML models compared with conventional statistical models in published predictive-modelling studies for breast, colorectal, or pancreatic cancer. METHODS: PubMed, Scopus, and Web of Science were searched for studies published between January 2019 and March 2025. Two reviewers independently conducted title-and-abstract screening, full-text eligibility assessment, and PROBAST risk-of-bias assessment. Sixty-five studies (n = 907,567 participants) were narratively synthesised by cancer site, predictive task, model family, comparator, validation strategy, predictor modality, and calibration or explainability reporting. RESULTS: The 65 studies comprised breast cancer (n = 35), colorectal cancer (n = 21), and pancreatic cancer (n = 9). AI/ML superiority over LR and CoxPH was task- and data-dependent. CNN- and U-Net-based models predominated in imaging and body-composition tasks, tree-based ensembles consistently outperformed LR for tabular perioperative complication prediction, and CoxPH remained competitive, and in the largest pancreatic risk study, superior to XGBoost (C-index 0.802 vs 0.723) in well-structured datasets. PROBAST analysis-domain risk was moderate in 54 of 65 studies (83%), driven by limited external validation, sparse calibration reporting (11/65), and few decision-curve analyses (7/65). CONCLUSION: AI/ML adds the most methodological value in imaging-derived feature extraction and nonlinear perioperative prediction, while conventional regression remains preferable in large, structured datasets with linear predictors. Clinical translation requires standardised body-composition definitions, external validation, calibration assessment, decision-curve analysis, and explainability, in line with TRIPOD+AI and CLAIM standards.

Humans↗

PubMed2026

Probiotic-derived extracellular vesicles as food-based nanocarriers: Mechanisms, functional applications, and future perspectives in food systems.

Probiotic-derived extracellular vesicles (PDEVs) are a promising type of postbiotic nanoparticle derived by fermentation of probiotics, and have gained growing interest as a potential application in food science and nutrition. These are lipid bilayer vesicles of nanoscale, which are naturally released by probiotic cells and contain a wide variety of bioactive molecules, such as proteins, nucleic acids, and metabolites. Moreover, PDEVs are highly stable, biocompatible, and can be easily engineered to have surfaces with high functionality, which makes them good candidates in functional engineering. In contrast to traditional live probiotics, PDEVs overcome the difficulties of preserving microbial viability during processing and storage, thus providing superior safety, stability, and predictable biological performance. This is a systematic review of the various functions of PDEVs in food systems. We conclude on the processes through which PDEVs control intestinal barrier integrity, alter gut microbiota composition, and alter host immune responses, and their potential to enhance gut health when added to functional foods. In addition to their health-promoting effects, PDEVs have shown significant potential as natural antimicrobial agents to preserve food and as effective nanocarriers of hydrophobic bioactive compounds, including fucoxanthin, to improve their stability, bioavailability, and targeted delivery. Moreover, PDEVs can be used as new regulators of microbial fermentation. However, it should be noted that a lot of the evidence that is available is still preliminary and the effectiveness of these applications in real food-processing and storage conditions has not been fully proven. Although they have potential, there are a number of challenges that still hinder the widespread use of PDEVs in the food industry. These involve the creation of scalable and cost-effective production processes, batch-to-batch consistency, vesicle stability in a variety of food matrices, and regulatory and safety considerations. Other emerging engineering approaches, such as surface functionalization and cargo loading, are also discussed in this review and could further increase the specificity, functionality, and application versatility of PDEVs in food systems. Moving forward, the incorporation of PDEVs into the next generation functional foods, novel food preservation methods, and customized nutrition plans should be prioritized in future studies. Further developments in these fields can make PDEVs useful platforms at the interface of food microbiology, nanotechnology, and human health.

Probiotics↗