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PubMed2026

A systematic review and meta-analysis of visuospatial attentional deficits in Parkinson's patients.

Parkinson's disease (PD) is a neurodegenerative condition primarily characterized by motor deficits, yet cognitive impairments are increasingly recognized. While deficits in executive functioning are well documented even in the absence of cognitive decline, evidence of attentional deficits in PD remains inconsistent, and the role of motor symptom lateralization is unclear. In this systematic review and meta-analysis, we examined visual attention in right-handed, cognitively unimpaired idiopathic PD patients, focusing on the canonical attentional domains (sustained, selective, divided) and processes (alerting, endogenous and exogenous orienting, reorienting), as well as visuospatial bias. Four databases were searched for studies comparing PD patients with healthy controls. Meta-analytic estimates were derived using Hedges' g within random-effects models, and studies that could not be quantitatively integrated were summarized narratively. In addition, studies directly comparing patients with left- and right-predominant motor symptoms (LPD vs. RPD) were reviewed qualitatively. Across 51 studies, PD patients exhibited deficits in sustained, selective, and divided attention. Among attentional processes, only exogenous orienting was impaired, whereas alerting, endogenous orienting, and reorienting were preserved. Findings from the few studies examining visuospatial bias indicated small, context-dependent shifts in spatial attention rather than a consistent directional bias. These findings indicate that PD patients show visual-attentional impairments, particularly under high-demand conditions, while basic alertness and voluntary orienting appear preserved. Exogenous orienting deficits and subtle rightward spatial tendencies in LPD suggest disruption of right-hemisphere attentional networks. These results have implications for early cognitive assessment, rehabilitation strategies, and understanding the neural bases of attentional dysfunction in PD.

Humans↗

PubMed2026

Assay-dependent variability in peptide biomarker quantification: experimental evidence from renalase in chronic kidney disease.

BACKGROUND: Renalase is a promising biomarker for kidney disease, but published levels vary widely between studies. We hypothesised that variability in commercial enzyme-linked immunosorbent assays (ELISAs) kits and matrix effects (serum vs plasma) drive these inconsistencies. METHODS: Paired serum and plasma samples from 56 participants (28 chronic kidney disease (CKD) stages 2-5, 28 healthy controls) were tested using three commercial renalase ELISAs (BTLAB, Cloud-Clone, EIAab). We assessed intra-assay precision, inter-assay agreement (Spearman's rank correlation and Bland-Altman analysis on log10-transformed values), matrix effects, and associations with estimated glomerular filtration rate (eGFR). Diagnostic performance was evaluated by Receiver operating characteristic (ROC) analysis. RESULTS: Inter-assay renalase concentrations differed markedly (up to orders of magnitude), with weak inter-assay correlations (r ≤ 0.25). Bland-Altman analyses revealed large, systematic biases between kits. Only the BTLAB assay showed consistent serum/plasma agreement, a significant correlation with eGFR (ρ ≈ 0.32-0.42, p < 0.05), and moderate discriminatory performance for CKD in serum (AUC = 0.70) and plasma (AUC = 0.68). Cloud-Clone and EIAab produced divergent results and strong matrix-dependent biases. CONCLUSIONS: Observed variability among commercial ELISA platforms may compromise comparability between studies. Harmonisation, standardised reference materials, and cross-validation are necessary before renalase assays can be used reliably in clinical practice.

Humans↗

PubMed2026

Hot vs cold knife for endoscopic ablation of posterior urethral valves: a systematic review by the EAU-YAU paediatric urology working group.

INTRODUCTION: Posterior urethral valves (PUV) are the most frequent cause of congenital lower urinary tract obstruction in males. Despite early surgical ablation, up to 22% of patients develop chronic kidney disease and 11% progress to end-stage renal disease. Multiple endoscopic modalities have been described for valve ablation but the optimal technique remains uncertain. This systematic review aims to determine whether cold or hot knife ablation provides superior effectiveness for primary endoscopic treatment of PUV in a single surgical session. MATERIAL AND METHODS: A systematic search of PubMed and Embase databases was conducted to identify studies comparing cold and hot knife techniques for endoscopic ablation of PUV in children, covering all publications up to December 2025. The review was performed in accordance with PRISMA 2020 guidelines and was prospectively registered in PROSPERO (ID CRD420251180556). Original studies including patients <18 years who underwent primary valve ablation with postoperative cystoscopy or VCUG and ≥6 months of follow-up were included. Quality assessment was done using RoB 2.0 for randomized trials and MINORS for observational studies. RESULTS: A total of 1581 studies were identified, of which 26 met the inclusion criteria, comprising one randomized controlled trial, five prospective, and 20 retrospective studies constituting a sum of 1725 paediatric patients. The overall methodological quality of included studies was moderate, with marked heterogeneity in design, follow-up duration, and outcome reporting, limiting direct comparisons across series. Thus statistical analysis was not possible. Of these, 829 (48.1%) underwent cold valve ablation and 896 (51.9%) underwent hot ablation techniques. Within the cold group, most patients were treated with a cold knife (80.2%), followed by balloon dilatation (7%), the Mohan valvotome (6.5%), cold hook (5%), and, rarely, a modified venous valvulotome (1.3%). Among hot techniques, 32.8% of procedures were performed by electro-fulguration with a resectoscope, 29.4% using a Bugbee electrode, 23.8% with a hook electrode and 14% with laser-based systems. Follow-up ranged from 6 months to 22 years across studies. Single-session success rates for valve ablation ranged from 22% to 100% in the cold resection group and from 71.4% to 100% in the hot resection group. Reintervention for residual valves was reported in 0%-78% of cold cases and in 0%-28.6% of hot resections. Urethral stricture rates ranged from 0% to 11.1% after cold incision and from 0% to 23.8% after hot techniques. Reporting of postoperative outcomes such as urinary tract infection, incontinence, bladder dysfunction, vesicoureteral reflux (VUR) resolution, hydronephrosis improvement, and renal function varied widely among studies and was assessed using different methodologies. CONCLUSIONS: Both cold and hot ablation techniques for PUV achieved high single-session success rates and low complication rates. Cold resection appeared slightly safer, although this finding should be interpreted cautiously given the heterogeneity and observational nature of the available data.

Humans↗

PubMed2026

Misalignment between ultra-processed status and 'better for you' claims on premix alcohol products.

BACKGROUND: Premix alcohol products (also known as ready-to-drink beverages) are a rapidly expanding alcohol category and frequently marketed using 'better for you' claims (e.g., 'Low sugar', 'Natural'). Little is known about the extent to which these products are ultra-processed or whether marketing claims align with ultra-processed status. This study aimed to address this evidence gap by auditing ingredient disclosure on premix products, assessing the ultra-processed status of these products, and determining the prevalence of 'better for you' claims with a particular focus on claims relating to ultra-processed status. METHODS: 534 premix alcohol products sold in major Australian retail outlets were assessed. Products were evaluated for compliance with mandatory ingredient disclosure, classified according to ultra-processed status based on the presence of indicators of ultra-processing (additives and other industrial ingredients), and analysed to determine the prevalence and types of 'better for you' marketing claims. RESULTS: Only 79% of assessed products displayed an ingredients list. Among compliant products, 98% contained at least one additive or ingredient indicative of ultra-processing, most commonly flavours, carbonating agents, colours, and sweeteners. One-third (33%) of products containing an ultra-processing indicator displayed a claim suggesting naturalness or minimal processing. Substantially higher proportions of ultra-processed products than non-ultra-processed products carried health-related claims. DISCUSSION AND CONCLUSIONS: Premix beverages available in Australia are overwhelmingly ultra-processed, yet many are marketed in ways that may mislead consumers about their composition and healthfulness. Stronger regulatory oversight of ingredient disclosure and marketing claims in this sector is urgently needed to support informed consumer decision-making.

Alcoholic Beverages↗

PubMed2026

Exploring the perceptions, experiences, and behaviours that nurses and midwives face in relation to sleep: A systematic review of qualitative evidence.

BACKGROUND: The importance of sleep for nurses and midwives is increasingly being recognised. Poor sleep is known to have negative impacts on physical health, mental wellbeing, and work performance. This has prompted efforts to promote and support staff sleep. However, further efforts are needed to understand how nurses and midwives consider and manage sleep to ensure that meaningful and effective interventions are adopted and sustained. AIMS: This review of qualitative evidence aims to examine nurses' and midwives' perceptions, experiences, and behaviours around sleep. METHODS: This review followed JBI's systematic meta-aggregative approach including development of an a priori protocol. A systematic search of six electronic databases (MEDLINE, Embase, Emcare, PsycINFO, CINAHL, and Scopus) was undertaken to identify qualitative studies that examine nurses' and midwives' perceptions, experiences, and behaviours related to sleep. The search was conducted on the 10th of October 2024. Study selection, quality appraisal, data extraction, and synthesis followed JBI approaches and the ConQual approach was used to report assessment of synthesised findings. RESULTS: Thirty-three studies were included for review, and 245 findings were aggregated into 24 categories and nine synthesised findings related to the perceptions, behaviours, and experiences. While sleep was perceived as important, poor sleep was often understood as an expected and inevitable part of the job and that there was a need to always be awake to provide continual care. Experiences influencing sleep related to personal circumstances and work-related factors, as well as professional training and institutional practices. A range of behaviours, including planning time to sleep, using sleep aids, modifying the sleep environment, and altering daytime behaviours were also described. CONCLUSION: This review identified a range of perceptions, behaviours, and experiences that may influence the sleep of nurses and midwives which are vital to supporting individual and workforce wellbeing and safe, effective clinical practice. Insights from this review can be used to better understand nurses' and midwives' relationship with sleep and to develop and enhance targeted sleep interventions and programs that aim to promote and support healthy sleep among nurses and midwives. Open Science Framework Registration: 10.17605/OSF.IO/F32UM.

Humans↗

PubMed2026

Distress Intolerance, Social Anxiety, and Depressive Symptoms in Adolescents: Evidence from Random-Intercept Cross-Lagged Panel and Cross-Lagged Panel Network Analyses.

Social anxiety and depressive symptoms frequently co-occur during adolescence, yet the mechanisms underlying their longitudinal associations remain insufficiently understood. Distress intolerance has been proposed as a transdiagnostic risk factor implicated across internalizing symptoms. However, it remains unclear whether distress intolerance is predicted by social anxiety and depressive symptoms, as well as the underlying mechanisms among these three constructs. The specific symptoms most centrally involved in these cross-domain associations remain poorly understood. The present study investigated the longitudinal associations among distress intolerance, social anxiety, and depressive symptoms using a dual-method framework combining random-intercept cross-lagged panel models (RI-CLPM) and cross-lagged panel network (CLPN) analyses. A total of 1,378 Chinese adolescents (Mage = 12.57, SDage = 0.63; 50.4% female) were assessed at three time points with six-month intervals between waves. The RI-CLPM analyses revealed that higher distress intolerance prospectively predicted subsequent increases in both social anxiety and depressive symptoms, whereas elevated social anxiety and depressive symptoms in turn predicted subsequent increases in distress intolerance. Moreover, distress intolerance mediated the longitudinal associations between social anxiety and depressive symptoms. Additionally, distress intolerance was also indirectly associated with its own subsequent levels through social anxiety and depressive symptoms. The CLPN analyses revealed that fear of negative evaluation and fatigue were the strongest predictors of other network nodes from T1 to T2 and from T2 to T3, respectively. In contrast, distress intolerance symptoms were predominantly predicted by other nodes in both cross-lagged networks. These findings extend prior views of distress intolerance as a unidirectional vulnerability by showing that distress intolerance is also predicted by social anxiety and depressive symptoms and accounts for part of their longitudinal associations across adolescence.

Humans↗

PubMed2026

Infertility treatment in women with epilepsy: A systematic review.

BACKGROUND: The impact of assisted reproductive technologies (ART) on seizure control in women with epilepsy remains incompletely understood. METHODS: A systematic review was conducted according to PRISMA guidelines. EMBASE, MEDLINE, CINAHL, Scopus, and the Cochrane Library were searched from inception to March 2025. Eligible studies included observational studies and case-based reports involving women undergoing infertility treatment. RESULTS: A total of 1216 publications were identified, of which four studies met the inclusion criteria, including case reports, a case series, and a cohort study. These studies included 16 women aged 25-46 years undergoing infertility treatment, all but one of whom had epilepsy. Interventions involved in vitro fertilization (IVF), ovulation induction, and hormonal therapies. Patients were treated with a range of antiseizure medications (ASMs), including carbamazepine, clobazam, lamotrigine, levetiracetam, oxcarbazepine, valproate, and zonisamide, either as monotherapy or in combination. Seizure frequency was generally stable, with most patients maintaining baseline seizure control. Seizure exacerbations were uncommon and primarily associated with hormonal therapy and reduced ASM levels, particularly reduced lamotrigine levels. Reported events included breakthrough seizures in the setting of decreased lamotrigine concentrations, seizure clusters associated with follitropin beta, and a new-onset seizure following dehydroepiandrosterone exposure. Across studies, multiple ART attempts resulted in live births with different ASM regimens, as well as in patients not receiving ASMs. CONCLUSION: Available evidence suggests that ART is feasible in women with epilepsy, with most patients maintaining stable seizure control. Hormonal therapy may affect ASM pharmacokinetics and seizure threshold, thereby warranting close monitoring. Larger prospective studies are needed to better define ASM-specific effects and optimize care.

Humans↗

PubMed2025

Influence of soil types with different soil-forming process on the qualitative and quantitative detection of microplastics by near-infrared spectroscopy.

Microplastics (MPs) have become a pressing global environmental threat, with soils-acting as sinks for MPs from multiple sources-gaining increasing attention. Near-infrared (NIR) spectroscopy offers a promising tool for MPs detection due to its rapid, non-destructive, and field-applicable features. Although previous studies have focused on the effects of individual soil components on the NIR detection performance of MPs, there is still a lack of systematic research on how the complex background-formed by the coupling of multiple physicochemical properties in natural soils-affects detection performance. This study focuses on soil types with different soil-forming processes, selected five representative agricultural soils to systematically evaluate how the combinations of physicochemical properties they represented affect the performance of NIR-based qualitative and quantitative analysis of MPs in soils. The results demonstrated that soil type significantly affected both the spectral response and detection performance of MPs. Brown Pedocals and Brown Earth exhibited clearer characteristic absorption and stronger linear responses, achieving higher identification accuracy under low (<1.5 %) or zero MPs concentrations and the best quantitative performance (R2 ≥ 0.988, prediction set root mean square error (RMSEP) ≤ 0.110 %). In contrast, Phaeozem and Red Soil were more prone to misclassification at low concentrations, while Fluvo-aquic Soil showed the poorest quantitative performance. This study is the first to reveal, at a holistic level, the critical constraints posed by natural soil complexity on the NIR detection of MPs, offering targeted empirical evidence to support the application of NIR technology in real-world soil environments.

Soil↗

PubMed2026

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↗

PubMed2026

Multimodal alignment improves generalizability of genomic biomarker prediction in computational pathology.

Computational pathology models that use digitized histopathology whole-slide images have the potential to become a cost-effective and scalable alternative to molecular assays for the prediction of genomic biomarkers, a key task in precision oncology. However, as new genomic biomarkers are discovered or quantified, large, labeled datasets must be prospectively collected to train new models. To address this challenge, we developed multimodal alignment for biomarker learning and generalization (MARBLE), a multimodal contrastive pretraining strategy that integrates structured biomarker knowledge into representation learning of histopathology images. MARBLE aligns histopathology-derived representations with representations of genomic biomarkers generated by a large language model (LLM) and a protein language model (PLM). This biologically informed alignment enables data-efficient generalization to novel, out-of-distribution biomarkers. Using the MSK-IMPACT cohort of over 40,000 patients across multiple biomarker panel versions, we design experiments grounded in real-world data to demonstrate the value of our proposed approach.

CP: computational biology↗

PubMed2026

Driving Under the Influence of Cannabis Among U.S. Young Adults Who Use Cannabis: Evidence From the 2021-2024 National Survey on Drug Use and Health.

PURPOSE: To estimate the prevalence of driving under the influence of cannabis (DUIC) and identify associated factors among U.S. young adult drivers reporting past-year cannabis use. METHODS: This cross-sectional study analyzed pooled 2021-2024 National Survey on Drug Use and Health. The analytic data were restricted to drivers aged 18-25 years who reported past-year cannabis use (N = unweighted 17,141; weighted N = 10,814,381). The outcome was self-reported past-year DUIC. Independent variables included demographics, substance use, mental health, cannabis-related perceptions, and driving behaviors. These relationships were assessed by modified Poisson regression. RESULTS: The weighted prevalence of DUIC was 28.0%, representing approximately over three million young adults. DUIC prevalence increased with cannabis use frequency, from 2.51 times higher among those using cannabis 12-49 days (adjusted prevalence ratio [APR]: 2.51; 95% confidence interval [CI]: 2.29-2.75) to 3.63 times higher among those reporting use on 300-365 days (APR: 3.63; 95% CI: 3.60-3.76), compared with those using cannabis 1-11 days. Cannabis use disorder (APR: 2.34; 95% CI: 2.06-2.65), simultaneous alcohol and cannabis use (APR: 1.29; 95% CI: 1.28-1.30), and perceived easy cannabis availability (APR: 2.36; 95% CI: 2.33-2.39) were also associated with higher prevalence of DUIC. Nonenrollment in school and living in a state with a medical cannabis law were associated with lower DUIC prevalence. DISCUSSION: DUIC is highly prevalent among U.S. young adults who use cannabis, with a clear graded association across categories of cannabis use frequency. Public health interventions should address frequent use, cannabis use disorder, alcohol-cannabis co-use, and perceived cannabis availability.

Humans↗

PubMed2026

Health bill beneath the plastic feast: A phthalate contamination alert from takeout food containers.

The rapid growth of takeout food consumption in China has raised concerns regarding exposure to phthalic acid esters (PAEs) from food packaging. This study investigated the presence, source, contribution, and health risk of PAEs in commonly used takeout containers. Widespread contamination was observed, with total PAE concentrations ranging from below the limit of detection to 222,000 ng/g. Diisobutyl phthalate (DIBP), dibutyl phthalate (DBP), and bis(2-ethylhexyl) phthalate (DEHP) were identified as the predominant compounds, accounting for 7.50 %, 14.7 %, and 18.7 % of the total concentration, respectively. These PAEs may originated from additives during manufacturing and potential contamination of raw materials. Human exposure assessment showed that daily exposure doses of DIBP, DBP, and DEHP via container ranged from 0.00 to 2340 ng/(kg·day) among frequent takeout consumers, contributing substantially to overall PAE body burdens. To further assess exposure and associated risks, a nationwide online questionnaire survey was conducted across China. Based on this national-scale behavioral dataset, the health risks among Chinese residents were evaluated. Although the modeled non-carcinogenic risks of DIBP, DBP, and DEHP remained within acceptable limits, the simulation suggested that approximately 70 % of participants may experience potential exceedance of the carcinogenic risk threshold for DEHP. The frequency of takeout food consumption was identified as the most important factor affecting PAE exposure. These findings underscore the importance of limiting takeout frequency and reducing reliance on plastic containers to mitigate health risks. This study provides scientific evidence to support the development of safer packaging materials and informs public health strategies.

Phthalic Acids↗

PubMed2026

Journey Mapping of the Patient Experience from Diagnosis to End of Life in Lung Cancer: A Qualitative Meta-Synthesis.

OBJECTIVES: This study aimed to systematically synthesize the lived experiences and journey narratives of lung cancer patients across disease stages, and identify key tasks and pain points during the disease course through patient journey mapping, providing evidence for comprehensive disease management throughout the patient journey. METHODS: Ten databases, including PubMed, Embase, Web of Science, Scopus, PsycINFO, CINAHL, Cochrane Library, CNKI, Wanfang, and SinoMed, were systematically searched, with a search period from database inception to August 15, 2025. The JBI Critical Appraisal Tool for qualitative studies was used to evaluate the quality of studies, and the results were integrated using a meta-aggregative approach. RESULTS: Thirteen studies were included. Based on the patient journey mapping, the lung cancer patient journey comprises four potential stages: evaluation and diagnosis, initial treatment, maintenance therapy, and end-of-life. A total of 30 themes emerged within three dimensions: tasks, emotions, and pain points. Each dimension of each stage consists of 2-3 themes. CONCLUSION: The journey of lung cancer patients is protracted and complex, characterized by stage-specific needs and challenges. Future management strategies should be tailored to these distinct phases, providing precision supportive care to optimize treatment outcomes and enhance patients' quality of life. IMPLICATIONS FOR NURSING PRACTICE: This Patient Journey Map integrates routine clinical pathways with patients' lived experiences across each stage, revealing stage-specific challenges and providing targets for tailored nursing interventions. The framework promotes multidisciplinary, digitally enabled supportive care and indicates the importance of including patients' social circles to enhance patient-centered outcomes.

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

Applications of quantum AI in brain disorder diagnosis: A systematic review.

BACKGROUND AND OBJECTIVE: Brain disorder diagnosis and prediction remain challenging because neuroimaging, electrophysiological, behavioral, and multimodal data are high-dimensional, noisy, heterogeneous, and limited by small clinical cohorts. This systematic review synthesised applications of quantum artificial intelligence (QAI) for brain disorder diagnosis, prediction, detection, and monitoring. METHODS: Following PRISMA guidelines, studies published from 2016 to 13 January 2026 were retrieved from Scopus, Web of Science, and IEEE Xplore. After screening, 36 studies met the eligibility criteria and were qualitatively analysed according to disorder category, data modality, QAI method, implementation setting, validation strategy, and performance. RESULTS: At the broader disease-group level, neurodegenerative disorders were the most frequently investigated, followed by mental health and psychiatric disorders. At the individual level, Parkinson's disease and schizophrenia were the leading applications, followed by depression, anxiety, Alzheimer's disease, and stress-related tasks. MRI-based modalities were the most frequently used data source, followed by multimodal data and EEG. Methodologically, primary QAI approaches were dominated by quantum neural and QDL architectures, followed by quantum-inspired optimization or feature-selection methods and quantum-kernel/conventional QML classifiers. Qiskit/IBM Quantum and PennyLane were the most frequently reported quantum software frameworks. However, most studies relied on simulators, classical quantum-inspired implementations, or unclear implementation settings, with limited real-hardware evaluation. CONCLUSIONS: QAI shows emerging potential for brain disorder analysis, particularly through hybrid quantum-classical learning, quantum neural architectures, quantum-kernel methods, and quantum-inspired optimization. Nevertheless, current evidence remains preliminary and requires larger datasets, subject-level and external validation, fair classical benchmarking, noise-resilient circuits, real quantum hardware evaluation, explainability, and clinical validation.

Humans↗

PubMed2026

Clinical outcomes of fusion vs excision in the treatment of painful type II accessory naviculars: A matched cohort study.

BACKGROUND: For painful Type II accessory naviculars, whether to remove or fuse them remains unclear based on the current literature. This study aimed to investigate the clinical outcomes of fusion versus excision in treating painful type II accessory naviculars. METHODS: This retrospective comparative study included and followed 54 eligible patients (from May 2017 to March 2023). After 1:1 propensity score matching (PSM), 34 patients (17 fusion versus 17 excision) were analyzed. Outcomes included Visual Analog Scale (VAS), American Orthopaedic Foot and Ankle Society (AOFAS) midfoot score, Tegner score, complication rates, and radiographic measurements. Receiver operating characteristic (ROC) curve analysis was performed to identify the appropriate accessory navicular size cutoff for predicting nonunion following fusion. RESULTS: The mean follow-up was 35.0 ± 9.9 months. The fusion and excision groups showed significant and comparable VAS and AOFAS score improvements (p < .001). The fusion group had a higher complication rate (41.2% vs. 5.9%, p = .039), primarily nonunion and persistent pain. ROC curve analysis identified 50.3 mm² as the cutoff for nonunion risk; sizes < 50.3 mm² predicted high nonunion likelihood. CONCLUSIONS: Both fusion and excision are effective treatments for painful type II accessory naviculars, demonstrating acceptable pain and functional improvement during midterm follow-up. However, the lower complication rate along with relatively superior functional recovery favors the excision technique. For accessory naviculars smaller than 50.3 mm2, excision may be a better choice. LEVEL OF EVIDENCE: Level III, retrospective comparative study.

Humans↗

PubMed2026

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

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

Humans↗

PubMed2026

The effects of visuomotor training and tDCS stimulation on visuomotor integration and visual processing: an electrophysiological approach.

BACKGROUND: Visuomotor integration coordinates visual and motor cortical activity to produce goal-directed responses and can be indexed by Rolandic Mu-rhythm suppression and visual evoked potential (VEP) P100 parameters. Perceptual-motor training improves visuomotor performance, and transcranial direct current stimulation (tDCS) over primary motor cortex (M1) has been reported to enhance motor learning when paired with training. This study examined whether anodal M1 tDCS augments the effects of Senaptec visuomotor training in healthy adults. METHODS: Sixty participants were randomized to active anodal tDCS (five 10-minute sessions, 1 mA; n = 31) or sham (n = 29) over M1 immediately before each Senaptec training session; 53 completed all sessions and post-testing. Outcomes were Mu-suppression ratios, VEP P100 latency and amplitude, and Senaptec measures of visual sensitivity and visuomotor control. RESULTS: Active tDCS produced no augmentation of any outcome, with no significant group × time interaction for any measure, consistent across composite and task-level analyses. Training alone produced no change in Mu suppression or visuomotor control. By contrast, both groups showed significant training-related gains in visual sensitivity, including near-far quickness and stereopsis, accompanied by shorter P100 latencies and larger amplitudes, indicating more efficient early visual processing. CONCLUSIONS: A clear dissociation emerged: training produced robust improvements in early visual processing, whereas neither tDCS nor training altered sensorimotor (Mu) or visuomotor-control measures. The tDCS results should be interpreted cautiously given the modest dose and limited power to detect small effects, rather than as evidence of inefficacy. Tablet-based perceptual training enhanced visual processing independent of neuromodulation.

Humans↗