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PubMed2026

Therapeutic approaches for the treatment of bovine metritis: a systematic review of clinical, reproductive and productive outcomes.

Bovine metritis is a complex multifactorial disease associated with substantial clinical and economic impact due to reduced milk production, subfertility, and increased culling rates. Considerable uncertainty remains regarding the comparative efficacy of the many therapeutic strategies used to manage it. This systematic review aimed to summarize and critically evaluate the available evidence on therapeutic approaches for bovine metritis, with respect to clinical cure, reproductive performance, productive performance, and culling. A literature search conducted in PubMed, Web of Science and CABI Digital Library (2010-2025) identified 18 randomized controlled clinical trials eligible for inclusion. Risk of bias was assessed independently by two reviewers using the Cochrane RoB 2 tool. Given substantial clinical and methodological heterogeneity across studies, findings were synthesized narratively by outcome, without meta-analytic pooling, and the certainty of evidence was assessed using GRADE for the comparisons supported by more than one study. Overall, systemic antimicrobial therapies consistently improved short-term clinical cure rates, although their effects on long-term reproductive and productive performance remained inconsistent. In selected cases, nonsteroidal anti-inflammatory drugs (NSAIDs) showed clinical outcomes comparable to antimicrobial treatments, allowing reductions in antimicrobial use ranging from 50% to 92%. Alternative approaches, such as intrauterine flavonoid, chitosan or dextrose-based therapies, produced inconsistent results that appeared to correlate with disease severity and treatment protocol. The evidence base is limited by substantial heterogeneity in disease definitions, postpartum timing of diagnosis, and cure criteria across studies, and by the near-universal absence of allocation concealment in the primary literature; these limitations restrict the certainty of most conclusions to low or moderate. Therefore, effective metritis control should move beyond symptom resolution and incorporate integrated and preventive strategies targeting inflammatory and metabolic dysregulation during the transition period.

Animals↗

PubMed2025

Improving Community-Based Care for Adolescents with ADHD: a Randomized Controlled Trial of Artificial Intelligence-Assisted Fidelity Supports.

Cognitive-behavioral treatments (CBTs) for adolescents with ADHD demonstrate promise of long-term effects on outcome. However, their implementation in routine care community clinics faces barriers that impact quantity, efficiency, and quality of delivery, as well as client outcomes. This study is a randomized controlled trial designed to evaluate the impact of an AI-assisted service delivery model on therapist implementation of Supporting Teens' Autonomy Daily (STAND), a CBT blended with Motivational Interviewing (MI) for adolescents with ADHD. Adolescents with ADHD (N = 51), who were clients at three community mental health agencies, received treatment from 23 therapists. There was randomization of adolescents and therapists to AI-assisted or standard implementation supports. In addition to standard supports (i.e., training, standard facilitation resources, technical assistance, case supervision), AI-assisted support package included digitized facilitation resources housed in a clinical dashboard (Care4), feedback on content fidelity, and AI-generated feedback on MI implementation quality. The AI-assisted group was associated with more efficient treatment delivery and lower number of appointments attended by the adolescent. There was also a significant decrement in MI quality over time in the AI-assisted group compared to the standard support group. Feedback in focus groups indicated that therapists perceived a task-oriented mindset to be associated with receipt of the AI-assisted support package, leading therapists to prioritize efficiency over relational aspects of therapy. Following the results of this trial, a future, larger RCT should examine the impact of the AI-assisted implementation model on mental health outcomes and cost savings to organizations, third party payers, and clients. Trial registration number: NCT05135065; https://www.clinicaltrials.gov ; Registered September 2021.

Humans↗

PubMed2026

A genome-wide coverage-based pipeline for the identification of host-derived candidate DNA biomarkers from cell-free blood.

We have created a new data-analysis pipeline for the discovery of host-specific candidate DNA biomarkers derived from sequencing data of cell-free blood. Unlike approaches that rely on specific molecular or genetic signatures, our method leverages the coverage distribution of cell-free DNA sequences mapped to a reference genome, applying statistical analyses to identify informative short genomic regions for biomarker discovery. The pipeline is applicable to diverse diseases and can be used to analyze cell-free DNA sequences from plasma or serum to identify candidate biomarkers that are characteristic of disease states in mammals. Core functionalities were developed in Java and integrated with open-source software tools for the preprocessing of raw sequencing data, complemented by Python scripts for the machine-learning analysis and statistical validation. The pipeline is designed for HPC use and users can access the pipeline through a Galaxy workflow, which offers a user-friendly web interface for input selection prior to execution and analysis progress monitoring. Performance tests, carried out using duplicate sets of COVID-19 samples and controls, showed linear scalability of execution time with an increasing dataset size, as well as a substantial reduction in execution time through parallelized computation, whereby each HPC node is used to process the data of one chromosome. Further statistical tests confirmed the quality of the pipeline's results by showing that the set of identified candidate biomarkers remained stable across varying dataset sizes.

Biomarkers↗

PubMed2026

Bioactive peptides for meat quality and preservation: Integrating peptidomics and computational screening.

Bioactive peptides generated from meat proteins, fermented meat products, and slaughter by-products have attracted increasing attention as functional molecules for improving meat quality and preservation. In meat systems, peptides can be produced through endogenous postmortem proteolysis, microbial fermentation, gastrointestinal digestion, or controlled enzymatic hydrolysis of underutilized animal by-products. These peptides are closely associated with key meat science endpoints, including postmortem tenderization, oxidative stability, color retention, flavor development, microbial inhibition, and the valorization of processing by-products. However, although high-resolution peptidomics has greatly expanded the identification of meat-derived peptide sequences, their translation into practical meat applications remains limited by matrix interactions, processing stability, sensory constraints, safety concerns, and insufficient validation in real meat systems. This review synthesizes recent advances in meat-related peptidomics and computational screening, including sequence-based prediction, machine learning, molecular docking, molecular dynamics, stability assessment, and safety-oriented filtering. Particular attention is given to how these approaches can prioritize peptides with antioxidant, antimicrobial, flavor-modulating, and preservation-related functions under meat-specific technological constraints. By integrating peptide generation pathways, mass spectrometry-based identification, in silico prioritization, and meat quality endpoints, this review proposes a stage-gated framework for translating meat-derived bioactive peptides from discovery to application. Future research should strengthen matrix-specific validation, standardized peptidomic reporting, and safety assessment to support the use of bioactive peptides in meat quality improvement, clean-label preservation, and circular utilization of meat industry by-products.

Animals↗

PubMed2026

BMT4me En Español: Multisite Feasibility and Usability Testing of a Spanish-Language mHealth Adherence Support App for Spanish-Speaking Caregivers of Children After Hematopoietic Stem Cell Transplantation and Cancer Treatment.

BACKGROUND: Medication nonadherence during the first 100 days after pediatric hematopoietic stem cell transplantation (HSCT) and during oncology treatment increases risk for complications. BMT4me is a caregiver-facing mobile health (mHealth) application providing medication reminders, symptom tracking, and note-taking features to support medication management. Spanish-speaking caregivers are frequently excluded from digital adherence interventions due to the lack of language-accessible tools. PROCEDURE: We conducted a multisite, mixed-methods usability testing of a Spanish-language version of BMT4me ("BMT4me en Español") with Spanish-speaking caregivers of children (ages 2-17 years) post-HSCT or with an oncology diagnosis on active treatment. Caregivers completed a facilitated, three-step usability session (unobtrusive observation, interactive observation, and debriefing), followed by a semi-structured interview, and then completed the system usability scale (SUS). Quantitative outcomes were summarized descriptively; qualitative data were analyzed using content analysis with constant comparison. RESULTS: Fifteen participants enrolled at each site for a total of 30 participants. Across both sites, the recruitment rate was 91%. All participants completed all parts of the study. The SUS score (M = 80.09; SD = 17.35) was above average (>68). Two key qualitative themes emerged: (1) the perceived positive impact of BMT4me on managing a serious illness and (2) the acceptance and sociocultural relevance of BMT4me for Spanish-speaking families. Caregivers also shared suggestions to add educational content and multiuser functionalities to BMT4me. CONCLUSIONS: The acceptance and perceived positive impact of the Spanish BMT4me app indicates that socioculturally relevant, Spanish mHealth interventions have strong potential to support Spanish-speaking caregivers in pediatric oncology and HSCT settings. CLINICAL TRIALS NCT: NCT06361173.

Adolescent↗

PubMed2026

BRAIN-Diabetes: Acceptability of an adapted FINGER multidomain intervention among adults living with type 2 diabetes in rural border regions across the island of Ireland.

BackgroundIndividuals with type 2 diabetes mellitus (T2DM) face increased risk of cognitive decline and dementia. Multidomain lifestyle interventions offer a non-pharmacological strategy to support brain health in this high-risk group.ObjectiveThis study examined the acceptability of a culturally adapted FINGER-based intervention among adults living with T2DM in rural border regions of Ireland (BRAIN-Diabetes Trial).MethodsA 6-month pilot randomized controlled trial was conducted. The intervention group received a multidomain program targeting diet, physical activity, and computerized cognitive training (CCT). The control group received standard care. Acceptability was assessed using questionnaires (all participants) and semi-structured interviews (intervention participants). Quantitative data were analyzed descriptively and qualitative data using template analysis, guided by four a-priori themes: trial participation and engagement, dietary behavior change, exercise behavior change, and CCT behavior change.ResultsQuestionnaire data (intervention: n = 28; control: n = 36) indicated high overall acceptability. Dietary and exercise components were rated most positively, while CCT component was less well received. Interviews (n = 25) highlighted facilitators to trial engagement, including perceived health improvements, and social connection, with time constraints and limited personalization as barriers. Dietary change was supported by tailored guidance but hindered by cost and availability. Facilitators for exercise included accessible resources and perceived benefits, with barriers including competing priorities. CCT engagement was mixed, with challenges including digital access and repetitiveness.ConclusionsThe Brain-Diabetes intervention was acceptable and feasible among adults with T2DM. Personalized support and accessible resources were key to engagement. Future work should refine delivery to enhance scalability and long-term adherence among high-risk groups.

Humans↗

PubMed2026

Exercise with motor cortex high-definition transcranial direct current stimulation enhances cardiovascular efficiency and lower-limb function in multiple sclerosis: A crossover, double-blind, and proof-of-principle study.

Combining exercise with high-definition transcranial direct current stimulation (HD-tDCS) could offer a strategy to help people with Multiple Sclerosis improve outcomes. In this crossover study, participants with MS (Expanded Disability Status Scale ≥3.0, n = 12) and controls (n = 10) completed baseline testing, followed by three randomized experimental conditions: 1) exercise+active HD-tDCS; 2) exercise+sham HD-tDCS; and 3) HD-tDCS alone. Exercise performance metrics [heart rate, work rate, heart rate-to-work rate (HR/WR) ratio, and perceived exertion] were compared across the exercise conditions. Secondary outcomes included the Symbol Digit Modalities Test (SDMT), Timed 25-Foot Walk (T25F), Nine-Hole Peg Test (9HPT), and acute symptom ratings (fatigue and pain), assessed pre-, immediately post-, and 1h-Post. Cardiovascular efficiency (HR/WR ratio) significantly improved during exercise+HD-tDCS compared to exercise alone, particularly in older MS participants (p = 0.010). SDMT declined immediately post HD-tDCS alone, 1h-post-exercise alone, and at both time points during exercise+active HD-tDCS (p < 0.05). Both groups increased walking speed only post-exercise+active HD-tDCS, while no condition affected upper-limb function (p < 0.05). These results are in line with the tDCS literature in the general population, suggesting that tDCS improves exercise performance and selectively improves engaged motor function. The trade-off between physical and cognitive outcomes underscores the importance of personalized neuromodulation strategies in neurorehabilitation to maximize therapeutic benefits while minimizing adverse effects, and warrants further large-scale, long-term investigations of this approach in MS.

Humans↗

PubMed2026

Educational Effects of Electronic Documents and Videos on Parents' Responses to Acute Illness in Young Children: A Randomized Controlled Trial.

AIM: This study compared changes associated with electronic document-based and video-based education for parents responding to acute illness in young children, focusing on self-reported knowledge, anxiety, and satisfaction. METHODS: A randomized controlled trial with pre- and post-intervention measurements was conducted among 140 adults in Japan who self-reported raising a child under 3 years of age and having experienced their child's acute illness. Participants were assigned to an electronic document group or a video group (n = 70 each). Self-reported knowledge was assessed using a researcher-developed questionnaire, and anxiety was measured using the State-Trait Anxiety Inventory. Pre-post changes and between-group differences in change scores were examined. RESULTS: Total self-reported knowledge scores increased significantly in both groups (p < 0.01), with no significant between-group difference. The video group showed significant improvements in items related to symptoms requiring attention at home and information sources, whereas the electronic document group improved in items related to symptoms requiring medical consultation and emergency calls. State and trait anxiety did not change significantly in either group. Satisfaction was high in both groups. CONCLUSIONS: Both educational formats may support parents' learning about responses to acute illness in young children, although appropriate formats may differ according to the educational content. Information provision alone may have limited effects on anxiety; therefore, future parent education should incorporate interactive and reassurance-focused approaches. TRIAL REGISTRATION: UMIN-CTR: UMIN000056457.

Humans↗

PubMed2026

A systematic review of macaque brain stimulation: Trends and future directions.

Neurostimulation techniques can powerfully modulate neural circuit activity and provide causal insights into the relationship between brain function and behavior. Macaque monkeys have long been a key animal model for brain stimulation studies. While stimulating the macaque brain with one or a few electrodes has already taught us much about brain function and dysfunction, recent technological advances promise a future with more precise stimulation using many more electrodes. However, such possibilities also increase the number of choices an experimenter has when designing their study. We can learn from a rich past, but a comprehensive overview of which brain regions have been studied and with what stimulation parameters is lacking. Here, we present a PRISMA-compliant systematic review of 734 macaque brain stimulation studies using electrical and/or optogenetic stimulation. We find a striking bias in which brain areas have traditionally been stimulated: a mere 10 brain regions account for half of all studies, with the remainder of studies investigating approximately 150 other areas. Across studies, stimulation frequency robustly predicted direct behavioral effects independent of brain region, while amplitude did not. Future studies could more systematically explore less studied regions through lower stimulation frequencies (e.g., 20-50 Hz) alongside established ranges (∼200 Hz). Tools such as fMRI or optical imaging can capture neural circuit engagement evoked by these frequencies, even when behavioral effects are absent or remain subtle. Our synthesis offers a guide towards the next steps in high-channel-count, high-precision stimulation approaches.

Animals↗

PubMed2026

Association between Kidney Tubular Secretory Clearance with Cognitive Function among Adults with CKD in the Systolic Blood Pressure Intervention Trial.

BACKGROUND: Persons with CKD are disproportionally affected with cognitive impairment, yet the pathophysiology linking the two conditions is unclear. Because kidney tubule secretion is essential for clearance of medications, uremic toxins, and metabolites, we hypothesized that worse tubular secretion would be associated with reduced cognitive function in CKD. METHODS: The Systolic Blood Pressure Intervention Trial tested a systolic blood pressure target <120 mmHg vs. <140 mmHg in hypertensive individuals at high cardiovascular risk. In paired blood and urine specimens from 1,937 participants with eGFR <60 ml/min/1.73m2, we measured 10 endogenous tubule-secreted metabolites and calculated a urine/plasma ratio for each, then averaged these to generate a summary secretion score. We used unadjusted and multivariable-adjusted linear regression and mixed models to evaluate cross-sectional and longitudinal associations of the secretion score with the Montreal Cognitive Assessment, Digit Symbol Coding, and Logical Memory immediate and delayed tests-measured at baseline and months 24 and 48 of follow-up. Multivariable Cox regression evaluated associations with incident probable dementia and mild cognitive impairment, adjudicated by prespecified criteria. RESULTS: Mean age was 73 ± 9 years, 41% were women, mean eGFR was 48.2 ± 11.4 ml/min/1.73m2, median albuminuria was 14.8 [7.1-48.6] mg/g. Lower secretion score was associated with a 0.06 higher adjusted logical memory delayed score (95% CI: 0.02, 0.11) but not with other cognitive tests at baseline or longitudinal cognitive decline. After a median 4.1 years of follow-up, 118 developed probable dementia and 187 developed mild cognitive impairment. Each 1-SD lower secretion score was associated with lower risk of probable dementia (HR 0.78, 95% CI: 0.63, 0.98) but not mild cognitive impairment. CONCLUSIONS: Among Systolic Blood Pressure Intervention Trial participants with CKD, lower estimated tubular secretion was not associated with worse cognition at baseline or during longitudinal follow-up.

Journal Article↗

PubMed2026

Investigation of Fatty Acid Metabolism-Associated Molecular CPOX and the Underlying Mechanism in Follicular Lymphoma.

Dysregulated lipid metabolism is a key driver of follicular lymphoma (FL). This study aimed to explore the lipid metabolism-related genes (LMRGs) and clarify the underlying roles and mechanisms in FL. Bioinformatics methods, including differential analysis, WGCNA, machine learning, and Mendelian randomization, were utilized to select the LMRGs in FL. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were conducted to investigate the function of the key LMRG. Receiver operator characteristic (ROC) was used to evaluate the diagnostic value of the key gene CPOX. A pan-cancer analysis investigated CPOX's expression level and immune correlations. In vitro experiments using FL cell lines (WSU-FSCCL, DOHH2) validated CPOX expression, and CPOX knockdown in DOHH2 cells was used to assess its impact on viability, migration, invasion, and fatty acid metabolism. CPOX was confirmed to be a risk factor, significantly overexpressed in FL, and exhibited effective diagnostic ability in FL (AUC = 0.731). Functional analysis linked CPOX to mitochondrial function, oxidative phosphorylation, and heme metabolic process. Pan-cancer indicated the dysregulated CPOX across multiple cancers and closely correlation with immune characteristics. Experimentally, CPOX was higher in the more invasive DOHH2 cells; and CPOX knockdown suppressed FL progression and reduced lipid droplet formation, triglyceride, total cholesterol, and free fatty acid levels. In conclusion, this study fills the gap in understanding the significance of lipid metabolism-related molecules in FL, and innovatively proposes that CPOX is a risk factor for FL. Knockdown of CPOX inhibits the FL progression, which is regulated by fatty acid metabolism.

Lymphoma, Follicular↗

PubMed2026

Decoding the spatiotemporal patterns of food spoilage microbial communities: Integrating multi-omics and artificial intelligence to enable precision preservation.

In the global food supply chain, food wastage caused by spoilage has resulted in significant economic losses, food shortages, and environmental pressure. This process is fundamentally driven by the spatiotemporal dynamics of microbial communities. However, traditional research methods struggle to elucidate the complex mechanisms of spatial heterogeneity, interspecies interactions, and functional succession. This limits the development of effective preservation strategies. This review systematically reviews the cutting-edge progress of integrating multi-omics technologies and artificial intelligence (AI) to study food spoilage microbial communities, breaking through this bottleneck. We propose an intelligent theoretical framework that could potentially analyze microbial metabolic activities and predict dynamic shelf life if implemented. The conceptual framework integrates multidimensional data, including spatial metabolomics, temporal metatranscriptomics, single-cell transcriptomics, and longitudinal metagenomics. It can also be combined with AI models, such as graph neural networks. The article elaborates on the principles and applications of spatio-temporal monitoring technologies, such as nano secondary ion mass spectrometry, hyperspectral imaging, and the Internet of Things sensing. Through illustrative cases of typical perishable foods, it also explores how such a multi-omics - AI system might be applied to spoilage warning and precise intervention. Additionally, the article addresses the current challenges in data coverage, model generalization, and federated learning implementation. Then the research further explores emerging areas such as engineered probiotics, edge AI, and microfluidic sensing. These areas are targeted at transforming food preservation from an empirical control approach to a data-driven, precise regulatory framework. This transformation provides theoretical support and technical approaches for developing a smart, sustainable food preservation system.

Multiomics↗

PubMed2026

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

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

Artificial intelligence↗

PubMed2026

Integrative quantum and systems biology of cancer: From molecular fluctuations to ecological outcomes.

This review treats cancer as a multiscale adaptive system, asks what the framework must predict to be worth adopting, and separates at each scale what the evidence establishes from what is proposed. It is an expert narrative synthesis, not a systematic review, and states the limits of that design. Proton transfer and tautomeric shifts contribute to spontaneous mispairing but do not license claims of directed or non-random mutation: replication timing, three-dimensional chromatin organization, sequence context and known mutagenic processes explain most mutational heterogeneity, leaving any quantum contribution as a residual against that baseline. The Waddington quasi-potential is bounded: outside detailed balance the dynamics are not gradient-derivable and require a probability-flux term. Hysteresis, rate-limited bimodality and return to state after perturbation distinguish an attractor from a transcriptomic cluster. Single-cell karyotype and live-imaging evidence supports whole-genome doubling as an unstable intermediate of heterogeneous origin and context-dependent consequence, not a uniform adaptive strategy. Systems and synthetic biology, virtual cells and digital twins are assessed against benchmarks, not promise. Tissue-scale ecology is reported with the spatial measurements now quantifying it, including evidence that stromal niche construction is not uniformly tumor-supporting. RNA modification is a layer in its own right, showing that the interpretation of a regulatory signal, not its magnitude, is biologically decisive. A dedicated section states the framework's commitments, the observable and evidence at each scale, and what would falsify them, asking what this adds to somatic mutation theory with clonal evolution and plasticity.

Neoplasms↗

PubMed2026

Molecular Landscape and Advanced Diagnostic Technologies for BRAF Mutations in Cancer: From Quantitative PCR and ddPCR to CRISPR-Based Platforms.

BRAF mutations are key oncogenic alterations across multiple malignancies, including melanoma, thyroid carcinoma, colorectal cancer, non-small cell lung cancer, glioma, and hairy cell leukemia. The most prevalent variant, BRAF-V600E, induces constitutive activation of the MAPK signaling pathway, promoting tumor progression and influencing therapeutic responsiveness. Accurate detection of BRAF alterations is therefore essential for molecular classification, prognostic assessment, treatment selection, and resistance surveillance. This review summarizes the molecular heterogeneity of BRAF mutations and critically evaluates current diagnostic methodologies. Conventional approaches such as allele-specific PCR and Sanger sequencing are compared with advanced quantitative platforms, including high-resolution melting analysis, droplet digital PCR, and next-generation sequencing, with emphasis on analytical sensitivity, mutation coverage, and clinical applicability. Emerging technologies such as CRISPR-based assays, rolling circle amplification systems, and nanoparticle-based biosensors and point-of-care diagnostic platforms are also discussed for their potential to enhance ultra-sensitive detection, particularly in liquid biopsy settings. These emerging tools are highlighted for their potential to enable ultra-sensitive, rapid, and decentralized mutation detection, particularly in liquid biopsy settings. Key challenges, including intratumoral heterogeneity, low allele-frequency variants, FFPE-associated artifacts, and clonal evolution under therapeutic pressure, are examined within a translational framework. In addition, we examine critical barriers to clinical implementation, including standardization, cost, and global accessibility of molecular diagnostics, and outline potential solutions through scalable technologies and decentralized testing strategies. We propose that optimal BRAF testing requires a mutation subclass-informed and clinically integrated strategy combining comprehensive baseline profiling with longitudinal molecular monitoring. Future diagnostic paradigms will likely integrate multi-omics data and artificial intelligence (AI)-assisted interpretation to refine precision oncology implementation. Looking forward, we propose that optimal BRAF testing will require integration of multi-omics profiling with AI-assisted interpretation, enabling automated variant classification, real-time clinical decision support, and improved prediction of therapeutic response and resistance.

Humans↗

PubMed2026

Presentation, management, and outcomes of anterior inferior cerebellar artery dissecting and fusiform aneurysms: a systematic review and institutional case series.

Dissecting and fusiform aneurysms of the anterior inferior cerebellar artery (AICA) are rare and poorly characterized lesions. This study provides a comprehensive patient-level synthesis to date, combining a systematic review with institutional data to describe their clinical presentation, diagnostic workup, management strategies, and outcomes. A systematic review was conducted according to PRISMA guidelines. Studies were included if they reported on dissecting or fusiform AICA aneurysms. Individual patient data were extracted and supplemented with a single-institution case series. Outcomes, complications, and radiological evolution were analyzed descriptively. Forty-nine patients from 36 studies and 6 patients from our institution were included in this study. In the systematic review cohort, most aneurysms presented with subarachnoid hemorrhage (n = 38/49, 77.6%). Compressive cranial neuropathies, particularly including the vestibulocochlear system, were common in patients with unruptured aneurysms. Diagnosis often required digital subtraction angiography after the initial non-invasive imaging. Endovascular treatment, most commonly parent artery occlusion, was employed in 61.2% (n = 30/49) of cases. However, ischemic complications occurred in 23.3% (n = 7/30), especially in proximal (A1-A2) lesions. Bypass surgery was reported selectively for proximal aneurysms with inadequate collateral flow. As an alternative surgical approach, decompression or trapping was pursued based on aneurysm morphology or clinical context. Conservative management was typically reserved for select patients with poor-grade SAH, high procedural risk, or patient refusal of intervention. Overall, 81.4% (n = 35/43) of patients with available follow-up achieved good functional outcomes. Management of AICA dissecting and fusiform aneurysms is highly individualized. Endovascular approaches were frequently used to secure ruptured lesions or lesions considered at high risk, but periprocedural ischemic risk in perforator-rich segments remains a notable concern. Bypass procedures were reported in selected proximal aneurysms with limited collateralization. Conservative management was reserved for highly selected high-risk or anatomically inaccessible cases. Clinical trial registration: This study is not a clinical trial.

Humans↗

PubMed2026

Virtual Reality Mastoidectomy as Precadaver Training for Novices: A Randomized Crossover Study.

OBJECTIVES: To compare cognitive load during virtual reality (VR) simulation and cadaveric dissection (CD) mastoidectomy training in novice learners. To determine whether training order influences cognitive load, characterize cognitive load progression during the procedure, and assess whether VR training improves subsequent cadaveric performance. METHODS: In this randomized crossover study, 24 core surgical trainees with no prior mastoidectomy experience performed a cortical mastoidectomy in both VR and CD settings. Participants were randomized to either VR-first or CD-first training sequences. Cognitive load was measured using a bespoke auditory reaction-time device at baseline and 10, 30, and 50 min. Relative reaction time (RRT) served as an objective index of cognitive load. Cadaveric performance was assessed using the Modified Welling Scale by two blinded otologists. RESULTS: Cognitive load was significantly lower during VR than CD, with mean RRT rising 26% from baseline in VR versus 60% in CD (p < 0.001). Training order did not affect cognitive load in either modality, and RRT increased progressively throughout mastoidectomy in both VR and CD. Participants who began with VR achieved significantly higher cadaveric performance scores than those who began with CD (mean 9.50 vs. 4.96; p < 0.001), and inter-rater reliability for performance scoring was high. CONCLUSION: VR mastoidectomy reduces cognitive load and enhances subsequent cadaveric performance in novice trainees, supporting its role as a cognitively optimized precadaver training modality that complements, rather than replaces, cadaveric dissection. These findings suggest VR enhances early learning efficiency and resource utilization in novice otolaryngology training. LEVEL OF EVIDENCE: N/A.

Humans↗

PubMed2026

Individual differences in brain dynamics across a social cognition network induced by cortico-cerebellar tDCS in adults with autism spectrum disorder (ASD).

Autism spectrum disorder (ASD) is a neurodevelopmental condition with core diagnostic domains of social communication impairments, restricted interests and repetitive behaviors. Idiosyncratic brain organization is a potential hallmark of ASD. Previous transcranial direct current stimulation (tDCS) studies often targeted dorsolateral prefrontal cortex, with changes oin brain dynamics averaged across the cohort. We utilized a magnetoencephalographic (MEG) array to characterize individual differences in brain dynamics induced by cortico-cerebellar tDCS across nodes of a social cognition network. A randomized, sham-controlled, double-blind, within-subject clinical trial was conducted in a cohort of 24 young adults with ASD or high autistic traits. Two separate sessions of computerized social learning activities were combined with verum/sham tDCS, with anodal electrode over right temporoparietal junction (TPJ) and cathode on right deltoid. Following stimulation, theta- and alpha-band activity were evaluated within nodes of a social cognition network: bilateral TPJ, fusiform, medial prefrontal cortex and Crus I/II of cerebellum. Idiosyncratic participant-specific up- and down-regulation of theta- and alpha-band activity occurred across the network. Activity in right Crus I/II, a region inundated by the stimulation current, strongly correlated with the change of activity summed across all cerebral cortical nodes in theta- but not alpha-band. Intrinsic theta-band activity is believed to mediate input/output relationships in cerebellar cortex and to drive synaptic plasticity. These results suggest that theta-band stimulation of cerebellar cortex might be an effective therapy for individuals on the autism spectrum who present with cerebellar hyperactivity.

Humans↗