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Effectiveness of hyperbaric oxygen in traumatic brain injury patients: A systematic review and meta-analysis.

BACKGROUND: Traumatic brain injury (TBI) is the most common neurological disorder and a leading cause of global mortality and disability. Although growing evidence suggests potential benefits of Hyperbaric Oxygen Therapy (HBOT) for TBI, its efficacy remains controversial. METHODS: We systematically searched PubMed, Embase, Cochrane Library, and Web of Science from inception to March 2026. Randomized controlled trials (RCTs) evaluating HBOT versus any comparator including sham, standard care and no treatment in adults with TBI were included. Two independent reviewers screened records, extracted data, and assessed risk of bias using the Cochrane Risk of Bias tool. Heterogeneity was assessed using the I² statistic. Effect sizes were pooled using random/fixed-effects models per heterogeneity results. RESULTS: 8 studies involving 570 participants were included. HBOT significantly improved computerized cognitive performance (SMD = 0.23, 95% CI: 0.07-0.40, p = 0.004, I² = 0%), executive function and processing speed (SMD = -0.59, 95% CI: -0.93 to -0.26, p = 0.0005, I² = 30%), memory function (SMD = 0.33, 95% CI: 0.03-0.63, p = 0.03, I² = 0%), and sleep quality (MD = 1.98, 95% CI: 0.07-3.88, p = 0.04, I² = 65%). No significant benefits were observed for Glasgow Outcome Scale (RR = 1.57, 95% CI: 0.55-4.44, I² = 87%), PTSD symptoms (MD = -3.05, 95% CI: -7.05-0.95, I² = 67%), neurobehavioral symptoms (MD = -9.06, 95% CI: -32.13-14.00, I² = 97%), and emotional distress (SMD = 0.25, 95% CI: -0.32-0.81, I² = 85%). Most adverse events were mild and transient. CONCLUSION: HBOT demonstrates domain‑specific benefits for cognitive function and sleep quality in TBI patients, predominantly those with mild TBI. However, evidence for PTSD, neurobehavioral symptoms, and emotional distress remains uncertain. Furthermore, the applicability of current evidence to moderate-to-severe TBI populations is restricted.

Humans

Pelvic lymph node dissection in prostate cancer: current evidence, controversies, and future directions.

BACKGROUND: Pelvic lymph node dissection (PLND) remains controversial in the management of prostate cancer. Although it provides the most accurate pathological staging, its therapeutic value beyond staging has long been debated due to conflicting evidence and concerns regarding procedure-related morbidity. OBJECTIVE: To critically evaluate the contemporary role of PLND, particularly extended pelvic lymph node dissection (ePLND), in prostate cancer management in the context of modern imaging, risk stratification tools, and evolving oncologic endpoints. EVIDENCE ACQUISITION: A narrative review of recent literature was conducted, focusing on high-level evidence including randomized trials, observational studies, and contemporary guideline recommendations addressing the indications, extent, oncologic outcomes, and complications of PLND. EVIDENCE SYNTHESIS: Recent randomized and observational studies suggest that ePLND improves nodal staging accuracy and may be associated with modest improvements in metastasis-free survival (MFS) in selected patients with intermediate- and high-risk prostate cancer, although the absolute benefit remains limited and causality is not definitively established. Advances in molecular imaging, particularly prostate-specific membrane antigen (PSMA) PET/CT, together with multiparametric MRI, validated nomograms, and emerging genomic classifiers, now allow more precise identification of patients most likely to benefit from ePLND. The integration of these tools supports a more individualized surgical strategy, including image-guided and sentinel lymph node approaches designed to maximize staging accuracy while minimizing unnecessary dissection. CONCLUSIONS: In the contemporary PSMA imaging era, ePLND continues to play an important role in nodal staging and may contribute to improved oncologic outcomes in carefully selected patients.

Humans

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

Adductor Canal Block and Local Anesthetic Versus Local Anesthetic Alone in ACL Reconstruction: A Double-Blind Randomized Controlled Trial.

BACKGROUND: Effective postoperative analgesia is crucial for early recovery after anterior cruciate ligament reconstruction (ACLR). Local infiltration analgesia (LIA) and adductor canal block (ACB) are common regional techniques, but their combined efficacy remains unclear. PURPOSE: To compare the effectiveness of LIA alone versus LIA combined with ACB in patients undergoing ACLR, with primary outcomes including postoperative opioid consumption and quadriceps function. STUDY DESIGN: Randomized controlled trial; Level of evidence, 1. METHODS: A double-blind randomized controlled trial enrolled 100 patients undergoing ACLR under general anesthesia. Patients were randomized into 2 groups: LIA + sham (saline injection) (n = 50) and LIA + ACB (n = 50). The primary outcome was postoperative opioid consumption in the first 24 hours. Secondary outcomes included visual analog scale (VAS) pain score, quadriceps function assessed by straight leg raise (SLR) at 3 hours, Quality of Recovery-15 (QoR-15) score, and Knee Injury and Osteoarthritis Outcome Score (KOOS) at 1 week. Statistical analysis was performed using t tests and chi-square tests with a P value <.05 considered significant. RESULTS: There was no significant difference in 24-hour opioid consumption between the LIA + ACB and LIA-only groups (P = .109). Similarly, VAS pain scores at 24 hours postoperatively showed no significant differences between the groups (P = .0804). Early functional recovery, assessed by SLR performance at 3 hours, was equivalent between groups (P = .6711). Additionally, QoR-15 scores on postoperative day 1 and KOOS values at 1 week demonstrated no significant differences (P = .6486 and P = .9054, respectively). Intraoperative opioid consumption was not different between the groups (P = .127). CONCLUSION: These findings indicate that the addition of ACB to LIA does not yield postoperative analgesic in ACLR. Consequently, LIA alone suffices for routine ACLR, potentially enabling clinicians to optimize perioperative workflows without incurring the additional time, financial burden, and resources associated with routine ACB administration. TRIAL REGISTRATION: ClinicalTrials.gov; NCT04721119.

Humans

Gut microbial diversity at baseline conditions the clinical, microbiome, and metabolic response to paraprobiotic Lactiplantibacillus plantarum LRCC5282 in overweight adults.

The gut microbiota is increasingly recognized as a target for obesity management; however, whether baseline gut microbial diversity conditions responsiveness to microbiota-targeted interventions remains unclear. We aimed to investigate whether baseline gut microbial diversity is associated with responsiveness to a paraprobiotic derived from Lactiplantibacillus plantarum LRCC5282 (LP5282-P) in overweight adults. In a 12-week, randomized, double-blind, placebo-controlled, multicenter trial of 120 overweight adults, LP5282-P produced no significant between-group differences in any clinical outcome across the overall per-protocol population. However, in the low-diversity subgroup, LP5282-P was associated with significant reductions in body weight, body mass index, and circulating leptin levels. These clinical changes were accompanied by compositional shifts in the gut microbiota, including higher relative abundances of Christensenellaceae, Faecalibacterium, and Alistipes. Fecal metabolite profiles showed elevated acetate and butyrate concentrations and altered bile acid composition. Within the low-diversity subgroup, changes in the relative abundances of Akkermansia and Eubacterium were inversely correlated with changes in body weight, body fat mass, and leptin levels. In contrast, the high-diversity subgroup exhibited no consistent response across the outcome domains examined. Overall, baseline gut microbial diversity was associated with differential responsiveness to LP5282-P, supporting its potential use as a stratification variable in future microbiota-targeted intervention trials. Further studies integrating direct measures of microbial activity and host response are warranted to elucidate the biological pathways underlying this diversity-dependent responsiveness. Trial registration: Clinical Research Information Service (CRIS), KCT0008119.

Humans

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

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

Disinfection

"Orphaned bereavement": Toward a public health model for bereavement.

Bereavement is increasingly recognized as a public health concern, yet support systems in many welfare states continue to allocate support according to the circumstances of death rather than the functional needs of bereaved families. Existing bereavement frameworks have substantially advanced understanding of social recognition and public legitimacy but provide more limited guidance for understanding how institutional responsibility for bereaved families is organized. using Israel as a bereavement-saturated case, this study introduces the concept of orphaned bereavement to describe bereavement in which no institution holds clearly defined and continuing responsibility for identifying needs, coordinating support, and ensuring continuity of care. Drawing on 25 semi-structured interviews with five bereaved family members and 20 professionals, analyzed using reflexive thematic analysis, the analysis generated three interrelated themes: institutionalized invisibility and unequal recognition; reorganizing life in the absence of institutional support; and pathways toward a needs-based model of bereavement support. The findings extend existing theories of disenfranchized grief and grievability by introducing institutional responsibility as a complementary lens for understanding bereavement inequality and support a needs-based public health approach in which support is organized according to families' evolving functional needs rather than the circumstances of death.

Journal Article

Nitrogen sources and concentrations shape algal odor compounds: Key drivers of &#x3b2;-cyclocitral and &#x3b2;-ionone in water bodies of the lower Yangtze River.

Taste and odor (T&O) compounds derived from cyanobacterial blooms pose escalating threats to freshwater security worldwide, yet the drivers of specific T&O metabolites remain poorly constrained. Here, we investigated the dual effects of nitrogen (N) sources and concentrations on the production of &#x3b2;-cyclocitral and &#x3b2;-ionone, two algal-derived T&O compounds, through integrated field surveys (54 sites across lakes and rivers) in the eutrophic lower Yangtze River, China, and laboratory cultivation of typical cyanobacteria (Microcystis aeruginosa and Pseudanabaena cinerea). Our field data revealed that the concentrations of &#x3b2;-cyclocitral and &#x3b2;-ionone in lakes and rivers were not significantly different, but increased with the trophic level index. Redundancy analysis and Mantel analysis showed that Microcystis and Pseudanabaena were potentially dominant contributors to &#x3b2;-cyclocitral and &#x3b2;-ionone in the water column. Structural equation modeling and variation partitioning analysis showed that enhanced nitrate (NO3--N) significantly promoted the production of these compounds. Laboratory experiments demonstrated that inorganic N (NaNO&#x2083;) maximized total T&O yields by promoting algal biomass, whereas organic N (urea and glutamic acid) elevated the T&O production per unit biomass by 1.5- to 9.5-fold. Notably, Pseudanabaena exhibited a 2.3-fold higher &#x3b2;-ionone yield than Microcystis, with greater sensitivity to N concentrations. Our study highlights the critical role of nitrogen pollution, both source and concentration, in the production of T&O compounds by phytoplankton and provides reference data for managing T&O issues in rivers and shallow lakes.

Norisoprenoids

Effectiveness of Topical Huzhang Sanhuang with Standard Nursing for Chemotherapy-Induced Phlebitis: Randomized Controlled Study.

Chemotherapy-induced phlebitis (CIP) is a common complication of peripheral intravenous chemotherapy that can cause pain, local inflammation, treatment interruption, and diminished quality of life. This randomized controlled trial evaluated the efficacy and safety of the topical Huzhang Sanhuang (HZSH) formula, combined with standard nursing care, in managing CIP. Ninety-four hospitalized patients with CIP (grade I or higher) were randomly assigned in a 1:1 ratio to receive either topical HZSH formula plus standard nursing care (experimental group, n = 47) or 50% magnesium sulfate wet dressing plus standard nursing care (control group, n = 47) for 14 days. Prespecified outcomes included phlebitis grade, visual analog scale (VAS) pain score, high-sensitivity C-reactive protein (hs-CRP), interleukin-6 (IL-6), symptom resolution time, and safety indicators. By Day 14, patients in the experimental group demonstrated significantly greater improvement in phlebitis severity than those in the control group (risk ratio for grade &#x2265; II, 0.42; 95% confidence interval, 0.20-0.87; P = 0.012). The experimental group also showed significantly larger reductions in VAS pain scores, hs-CRP levels, and IL-6 concentrations (all P < 0.01). Kaplan-Meier analysis further demonstrated faster resolution of multiple local symptoms in the experimental group. Treatment adherence was high in both groups, and no serious adverse events or major safety concerns were observed. These findings indicate that the topical HZSH formula, combined with standard nursing care, is a safe and effective integrative nursing intervention that accelerates clinical recovery, alleviates local symptoms, and reduces the inflammatory burden in patients with chemotherapy-induced phlebitis.

Humans

Operationalizing Local Ecological Knowledge for Aquatic Biodiversity Conservation: A Systematic Review and Management Framework.

Effective conservation and management of aquatic biodiversity is severely constrained by the absence of long-term ecological data in small-scale, tropical, and data-poor fisheries, where roughly one-quarter to one-third of freshwater fish species and 37.5% of elasmobranchs are threatened with extinction once Data Deficient species are accounted for. Conventional monitoring and stock-assessment tools are often financially and technically inaccessible in these systems, leaving managers without the evidence needed to prioritize conservation action or implement precautionary governance. Local Ecological Knowledge (LEK) is a largely underutilized resource for natural resource management that can provide temporal depth, spatial resolution, and species-specific ecological insights unavailable from scientific records. We conducted a systematic review and bibliometric synthesis of 60 peer-reviewed studies (1997-2025) applying LEK to assess fish conservation status, examining how, where, and through what methods this knowledge has been used. Our analysis identifies four complementary pathways through which LEK informs conservation management: reconstructing multi-decadal population changes, documenting spatial contraction and habitat loss, detecting extreme rarity and local extirpation, and characterizing intrinsic sensitivity to exploitation based on life-history traits. Despite growing methodological rigor, freshwater systems and African fisheries remain critically underrepresented, and formal integration of LEK into fisheries governance and biodiversity assessment remains the exception rather than the rule. We propose a practical three-stage framework to operationalize LEK within existing management and conservation systems. Recognizing fishing communities as legitimate co-producers of ecological knowledge is both scientifically necessary and an equity imperative for achieving global biodiversity commitments under the Kunming-Montreal Global Biodiversity Framework.

Biodiversity

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 &#x3b2;2-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

A 20-Y Analysis of Motorcycle Trauma After Helmet Law Repeal.

INTRODUCTION: After Arkansas repealed its universal motorcycle helmet law in 1997, helmet use decreased and motorcycle-related injuries and fatalities increased. Long-term clinical and population-level impacts of this policy change remain incompletely characterized. This study integrates statewide crash and fatality data with trauma center data to evaluate trends in helmet use, injury severity, and mortality at scene and hospitalization. METHODS: We retrospectively reviewed motorcycle-related admissions and emergency department deaths at the state's only adult level I trauma center from 2004 to 2023 across three periods: 2004-2006, 2013-2015, and 2021-2023. Demographics, helmet use, injury severity, and outcomes were assessed. Logistic regression evaluated associations between helmet use, severe head injury (Abbreviated Injury Scale &#x2265;3), and inhospital mortality. Fatality data were obtained from the National Highway Traffic Safety Administration, and crash-level data (2015-2023) were obtained from the State Department of Transportation. RESULTS: Among 1104 trauma admissions, annual admissions nearly tripled over time, with nonhelmeted riders representing 64%-72%. Helmet use was independently associated with lower odds of severe head injury (odds ratio 0.48, P < 0.001). Nonhelmeted riders had higher on-scene fatality risk (relative risk 1.21). Severe head injuries increased and were strong predictors of inhospital mortality. Population-adjusted motorcycle fatality rates rose from 2.34 to 3.18 per 100,000 residents by 2021-2023. CONCLUSIONS: Motorcycle fatalities and severe head injuries increased during the postrepeal period and were associated with helmet nonuse and severe head trauma. Clinical and statewide data show consistent associations among helmet nonuse, severe head injury, and prehospital and in-hospital mortality, highlighting helmet use as a target for injury prevention policy.

Acute brain injury

Patient-reported outcomes with tarlatamab in extensive-stage small cell lung cancer after platinum-based chemotherapy: results from the phase 3 DeLLphi-304 trial.

BACKGROUND: Extensive-stage small cell lung cancer (ES-SCLC) is associated with a high symptom burden and impaired health-related quality of life (HRQoL). This prespecified analysis from the phase 3 DeLLphi-304 trial evaluated patient-reported outcomes (PROs) for tarlatamab versus standard-of-care (SoC) chemotherapy following first-line platinum-based therapy. METHODS: DeLLphi-304 is a multicenter, open-label, randomized phase 3 study in adults with ES-SCLC. PROs were assessed using validated instruments, including the EORTC QLQ-C30, EORTC QLQ-LC13, FACT-G GP5, BPI-SF, and the EQ-5D-5L visual analogue scale. Change from baseline, response rates, and time to deterioration in these PROs were analyzed. RESULTS: PRO data from all 509 patients enrolled were evaluated. Compliance with QLQ-C30 and QLQ-LC13 assessments remained above 69% through 19&#xa0;weeks. A higher proportion of patients receiving tarlatamab achieved symptom or functional improvement at 19&#xa0;weeks compared with SoC in chest pain (19% vs 10%), cough (35% vs 26%), dyspnea (22% vs 7%), physical functioning (13% vs 8%), and global health status (23% vs 15%), respectively. Tarlatamab also delayed deterioration in symptoms, physical functioning, and pain at worst relative to SoC. FACT-G GP5 results indicated that patients receiving tarlatamab were less bothered by treatment side effects over time. CONCLUSIONS: In addition to its previously reported antitumor activity, tarlatamab demonstrated clinically meaningful improvements in symptoms and HRQoL compared with SoC. These findings support a favorable benefit-risk profile of tarlatamab in patients previously treated for ES-SCLC.

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

To Treat or Not to Treat: Navigating Early-Stage CLL in the Era of Targeted Therapy.

Chronic lymphocytic leukemia (CLL) is most frequently diagnosed at early, asymptomatic stages (Rai 0/Binet A), in which a watch-and-wait strategy remains the standard of care, based on historical trials demonstrating no overall survival benefit from early treatment. Over the past two decades, however, substantial advances in genomic profiling-including immunoglobulin heavy-chain variable region (IGHV) mutational status, TP53 disruption, recurrent gene mutations, and complex karyotype-have uncovered marked biological heterogeneity among early-stage patients and substantially improved prediction of disease progression. In parallel, targeted therapies such as Bruton tyrosine kinase (BTK) inhibitors and venetoclax-based combinations have transformed the management of symptomatic CLL, raising renewed interest in whether early intervention might favorably alter the natural history of biologically high-risk disease. In this review, we critically examine the evolution of prognostication in early-stage CLL, integrate contemporary molecular and clinical risk models, and summarize evidence from both historical chemotherapy-era studies and modern early-intervention trials. We discuss key unresolved controversies, including reliance on surrogate endpoints, the risks of overtreatment, and the persistent absence of an overall survival benefit across all early-treatment strategies. Finally, we outline future research priorities, including refined genomic stratification, minimal residual disease-driven (MRD)-driven approaches, and combination targeted therapies currently under investigation. Despite renewed interest in preemptive treatment, available evidence supports continued observation for asymptomatic patients outside clinical trials.

Humans

Predictive value of anal sphincter electromyography for sacral neuromodulation test-phase outcomes.

BACKGROUND: Sacral neuromodulation (SNM) is an established therapy for refractory pelvic organ dysfunction. Anal sphincter electromyography (EMG) is commonly used preoperatively to assess sacral and peripheral nerve integrity. However, the prognostic significance of chronic neurogenic EMG changes for SNM outcomes remains unclear. OBJECTIVE: To evaluate whether chronic neurogenic changes on preoperative anal sphincter EMG predict the outcome of the SNM test phase. METHODS: We retrospectively analysed 62 consecutive patients with bladder and/or bowel dysfunction or pelvic pain who were candidates for SNM treatment and who underwent preoperative anal sphincter EMG. EMG findings were classified as normal or showing chronic neurogenic changes. SNM test-phase success was defined as a &#x2265;50% improvement of symptoms at 24&#xa0;days. Outcomes were compared between EMG groups. RESULTS: Of the 62 patients (49 women, 13 men), 30 (48%) had normal EMG findings and 32 (52%) showed chronic neurogenic changes. Overall, the SNM test phase was successful in 47 patients (76%). Success rates were similar in patients with normal EMG (72%) and neurogenic EMG changes (79%), with no statistically significant difference (p&#xa0;=&#xa0;0.878). Sex-stratified analyses revealed no significant association between EMG findings and test-phase success in women or men. CONCLUSIONS: Chronic neurogenic changes on anal sphincter EMG do not predict SNM test-phase outcomes. These findings suggest that abnormal sphincter EMG results should not be used as a standalone criterion to exclude patients from SNM therapy. SIGNIFICANCE: Signs of neurogenic damage on anal sphincter EMG are not an indicator of reduced neuromodulatory capacity or diminished clinical response to SNM.

Humans

AI-enabled viral genomics: from virus discovery to host prediction and emerging variant forecasting.

The rapid expansion of metagenomic sequencing has generated vast repositories of viral sequence data that far outpace our capacity to interpret them using conventional approaches. Highly divergent sequences, sparse functional annotation, and taxonomically uneven sampling present fundamental challenges for reference-dependent methods, which lose sensitivity precisely for novel and understudied viruses with high public health relevance. Artificial intelligence (AI) provides a new avenue to address these challenges by enabling predictive inference from viral genomes and proteins while reducing dependence on sequence similarity. In this Review, we discuss representative advances in AI for virus discovery, taxonomic classification and functional annotation, prediction of host range and zoonotic potential, and efforts toward forecasting emerging variants. These advances are transforming viral genomics from a largely descriptive discipline into one with increasing predictive capability. We also critically assess the major challenges that constrain current approaches, including the availability of high-quality and representative datasets, rigorous model evaluation, biological interpretability and responsible governance for increasingly capable AI models.

Artificial Intelligence

Systematic review of machine learning approaches for predicting sickle cell crisis and mortality risk at the climate-health nexus.

BACKGROUND: Sickle cell anemia (SCA) is a severe genetic blood disorder characterized by recurrent vaso-occlusive crises and increased mortality, with the greatest burden occurring in low- and middle-income countries. Climatic and environmental conditions, including temperature variability, humidity, rainfall, air pollution, and seasonal changes, have been associated with disease exacerbation. However, the extent to which these factors have been incorporated into predictive models remains unclear. This study systematically reviews the application of machine learning (ML) models for predicting SCA crises and mortality in relation to climate and environmental factors. METHODOLOGY: The PRISMA guidelines were used, and 34 peer-reviewed studies published between 2005 and 2026 were analyzed to identify the climate variables, ML approaches employed, and predictive performance. The reviewed studies applied a range of ML techniques, including artificial neural networks, random forests, support vector machines, decision trees, logistic regression, and deep learning models. Temperature, humidity, rainfall, wind speed, air quality indicators, and seasonal patterns were the most frequently examined environmental variables. RESULTS: The findings indicate that most existing models rely predominantly on clinical and demographic data, with limited integration of climate information and inadequate representation of high-burden regions, especially Sub-Saharan Africa. Studies incorporating environmental variables reported improved predictive performance and highlighted the potential of climate-informed early warning systems for SCA management. CONCLUSION: The review recommends development of interdisciplinary, climate-aware ML frameworks, expansion of longitudinal environmental datasets, and increased research in underrepresented regions to support climate-resilient and patient-centered SCA care.

Humans