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PubMed2026

Analysis of deep learning techniques in computer-aided diagnosis for meniscus injuries: a systematic literature review.

Meniscus informatics is a growing subject of study in the healthcare industry. One of the major hindrances to the healthcare system's transformation is obtaining knowledge and meaningful information from complicated, high-dimensional and diverse sources. Modern biomedical research, for instance, has seen an increase in the use of complex, dissimilar, poorly documented, and generally unstructured electronic health records, imaging, sensor data and text, even after many current techniques have been used to extract more robust and useful elements from the data for analysis. New efficient standards for building end-to-end learning models from complex data are therefore needed. Therefore, the current study aims to examine the most recent research on the use of deep learning techniques for diagnosing meniscus tears and recommend creating comprehensive and meaningful interpretable structures that might benefit the healthcare industry. We also draw attention to shortcomings and the need for better technique development, and we provide new perspectives about this exciting new development in the field.

Humans↗

PubMed2026

The utility of 18F-fluorodeoxyglucose PET/computed tomography in relapsing polychondritis: a systematic review and meta-analysis.

Relapsing polychondritis is a rare chronic autoimmune inflammation of the cartilage associated with life-threatening respiratory complications. Currently, no clear role of imaging modalities such as 18F-fluorodeoxyglucose (FDG) PET/computed tomography (CT) is defined in the literature. This systematic review and meta-analysis provide current evidence on the PET-positivity rate and utility in relapsing polychondritis. Prospective or retrospective studies with more than five patients of suspected relapsing polychondritis who underwent 18F-FDG PET/CT during their management and reported a PET-positivity rate were included. Low-sample-size studies describing chondritis due to other aetiologies or utilizing PET-based radiopharmaceuticals other than FDG were excluded. A systematic search using relevant keywords was conducted across four databases (PubMed, Embase, Scopus and Web of Science) to include studies up to 25 April 2025. The Joanna Briggs Institute critical appraisal tools were used for risk-of-bias analysis. Data were analysed using the R software package (v4.3.1; 2023). Out of 962 articles, three with a total of 97 patients were included. With a pooled PET-positivity rate of 94% [95% confidence interval (CI): 73-99%, I2 = 0%, P = 0.76] and a pooled baseline SUVmax of 4.0 (95% CI: 3.5-4.6, I2 = 32%, P = 0.23), 18F-FDG PET identified asymptomatic cartilage involvement in more than 25% patients and PET parameters correlated well with inflammatory markers. It had a higher positivity rate for inaccessible sites, such as peripheral airways, and was crucial in treatment monitoring. The pooled PET-positivity rate of 18F-FDG PET in relapsing polychondritis is high but requires prospective large-sample-size studies to explore the diagnostic accuracy and prognostic implications of 18F-FDG PET in relapsing polychondritis.

Polychondritis, Relapsing↗

PubMed2026

Ruling out pediatric bacterial epididymo-orchitis with urinalysis - The case for minimizing unnecessary antibiotic prescription.

INTRODUCTION: Epididymo-orchitis in pediatric patients is predominantly non-bacterial, often stemming from viral or reactive etiologies. Despite guidelines recommending conservative management for non-bacterial cases, antibiotic overtreatment remains prevalent in the outpatient setting. We evaluated the diagnostic accuracy of urinalysis in ruling out bacterial infection to support antibiotic stewardship in this population. METHODS: We conducted a cross-sectional diagnostic accuracy study using electronic health records from a large health maintenance organization in Israel. The cohort included patients younger than 18 years with a diagnosis of epididymo-orchitis or clinically overlapping entities (acute scrotum, appendage torsion) who had paired urinalysis and urine culture results within one week of diagnosis. Logistic regression and ROC curve analysis were performed to assess the ability of urinalysis parameters to predict positive urine cultures. RESULTS: Of 682 eligible cases, confirmed bacterial infection was rare, occurring in only 17 patients (2.5%). Nitrite positivity was the strongest independent predictor of infection (OR 43.98; p < 0.001). A prediction model incorporating all urinalysis parameters yielded an area under the curve (AUC) of 0.825 and achieved a 97.7% classification accuracy for correctly predicting negative cultures. Despite the low prevalence of infection, antibiotics were prescribed in 237 cases (34.7%). Urinary anatomic abnormalities were significantly associated with culture positivity. CONCLUSIONS: Bacterial coinfection in pediatric epididymo-orchitis is uncommon. Urinalysis serves as a highly accurate screening tool to rule out bacterial etiology. A negative urinalysis supports withholding antibiotics in this setting, reserving treatment for children with positive markers or known anatomic abnormalities. This evidence-based approach This evidence-based approach has the potential to reduce unnecessary antibiotic exposure, however prospective studies are needed to validate these findings before broad implementation.

Humans↗

PubMed2026

Herbicolin A, an antifungal lipopeptide produced by Pantoea agglomerans APC 4211 is a promising biocontrol agent against food spoilage fungi.

Fungal contamination of food with yeast and molds is associated with major economic losses due to spoilage and also poses health risks in the form of mycotoxin production. The strain Pantoea agglomerans APC 4211 isolated from leaves of Ilex aquifolium (holly tree) has broad spectrum antifungal activity against a variety of food spoilage fungi. Genomic analysis of the strain confirmed the presence of biosynthetic gene clusters potentially encoding for the enzymatic machinery required for the production of the antifungal lipopeptide herbicolin A. Matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS) analysis of the cell-free supernatant (CFS) confirmed the presence of molecular masses corresponding to herbicolin A (1300.8 Da), and herbicolin B (1138 Da). Purified herbicolin A has desirable properties for biotechnological applications, including potent antifungal activity against a range of spoilage fungi, thermal stability and resistance to proteases. The lipopeptide has low cytotoxicity against epithelial cell lines and has minimum inhibitory concentrations (MICs) lower than those of some commercial antifungal drugs (0.2-2.5 mg/L). In a model dairy system (10% skim milk), herbicolin A demonstrated excellent solubility and stability, effectively eliminating Aspergillus niger and Penicillium notatum at a concentration of 5 mg/L. Overall, the study determines herbicolin's A spectrum against food spoilage organisms and examines potential applications in food. In conclusion, herbicolin A is a potent, naturally occurring antifungal agent with the potential to be applied as a biopreservative in food systems, providing a safe, clean-label, and efficient compound for synthetic preservatives replacement.

Pantoea↗

PubMed2026

Baseline Computed Tomography Coronary Angiography and Polygenic Risk Profiles in Adults With Type 2 Diabetes: A Cross-Sectional Analysis From the VOLTAIRE Study.

AIMS: To characterise baseline clinical, anatomical, and genetic cardiovascular risk profiles in participants enrolled in the VOLTAIRE (Evaluation of Polygenic Scores and CT Imaging in Risk Factor Modification in Patients with Type 2 Diabetes) study and examine concordance across these domains. METHODS: This analysis included adults with T2D who completed baseline computed tomography coronary angiography (CTCA) and polygenic risk score (PRS) assessment prior to randomisation in the VOLTAIRE study. Coronary atherosclerosis was evaluated using coronary artery calcium (CAC) score and CTCA-derived stenosis severity. Clinical risk was assessed using the New Zealand Society for the Study of Diabetes 5-year cardiovascular risk calculator. Polygenic risk for coronary artery disease was assessed using a genome-wide PRS and categorised into tertiles. RESULTS: Among 126 participants with T2D (mean age 57.5 ± 8.7 years; 62.7% male), coronary atherosclerotic burden was highly heterogeneous: 34.9% had CAC = 0, whereas 19.8% had CAC ≥ 400. Moderate-to-severe coronary stenosis (≥ 50%) was present in 40.5% of participants overall, including 20.4% of those classified as low clinical risk. PRS distribution was variable (low 37.3%, intermediate 35.7%, high 27.0%). Overlap between anatomical, genetic, and clinical domains was limited, with only 8.7% of participants classified as high risk across all three. CONCLUSIONS: Substantial heterogeneity and limited overlap exist between anatomical, genetic, and clinical cardiovascular risk measures in T2D. These findings support a multimodal approach to risk assessment integrating imaging and genetic profiling. TRIAL REGISTRATION: https://www. CLINICALTRIALS: gov; ID: NCT07091162.

Aged↗

PubMed2026

In silico identification of DNMT1 inhibitors from the PlantCyc database through computational approach to assess the anti-cancer potential of nutraceutical compounds in breast cancer.

Breast cancer accounts for a disproportionate share of global cancer-related deaths, with 670,000 fatalities and 2.3 million new diagnoses recorded in women during 2022 alone. Existing treatment modalities carry considerable toxicity burdens, and resistance to available agents remains an unresolved clinical problem. DNA methyltransferase 1 (DNMT1), the enzyme chiefly responsible for maintaining genome-wide methylation patterns during DNA replication, has been mapped out as a high-value target in breast cancer because its dysregulation silences tumour suppressor genes through promoter hypermethylation. The present work involves hierarchical in silico workflow to screen 4549 plant-derived compounds from the PlantCyc database (v16.0.3) against the human DNMT1 catalytic domain (PDB ID: 4WXX). Ten top-scoring compounds were taken forward for molecular docking via AutoDock Vina; Quercetin and Kaempferol both recorded the highest binding affinities at -9.5 kcal/mol, Wogonin (-9.3 kcal/mol) and Xanthohumol (-8.1 kcal/mol) also emerged as strong binders. Pharmacokinetic evaluation using ADMET-AI confirmed that all 10 compounds met Lipinski's rule of five, with human intestinal absorption values at or above 0.98. Wogonin and Xanthohumol were selected for a 100 ns all-atom molecular dynamics (MD) simulation in GROMACS due to their well-rounded ADMET profiles and limited existing data on their specific interactions with DNMT1 in breast cancer. Across all measured trajectory metrics, backbone RMSD, residue fluctuation, radius of gyration, solvent-accessible surface area, and intermolecular hydrogen bond count, Wogonin formed a more stable, compact complex. These findings suggest that Wogonin and Xanthohumol are non-toxic nutraceutical candidates suitable for DNMT1 targeted epigenetic therapy, with computational foundation strong enough to facilitate future in vitro and in vivo validation work.

Humans↗

PubMed2026

A systematic review of human avoidance learning: Cognition, computation, and methods.

Avoidance behaviour is fundamental for survival but can become maladaptive in clinical conditions. A large body of literature has accumulated on the dynamics of human avoidance learning. However, current theories and overviews do not provide an exhaustive account of this evidence. In this systematic review, we identify N = 116 studies on human avoidance learning. We analyse these studies with the goal of distilling robust empirical phenomena as a basis for theory-building, and examine their diagnostic value in differentiating between competing theories. We find that the evidence is difficult to reconcile with foundational two-factor and classical safety-signal accounts, and most strongly supports expectancy- and inference-based views, in which avoidance responses are selected with respect to represented consequences. At the same time, no current framework provides a complete account of the evidence: several findings point to an additional role for operant valuation, Pavlovian influences, and contextual or latent-state control over the expression of avoidance. Methodologically, we observe that the problem setting in the most common experimental paradigms is radically simpler than real-world avoidance and therefore unlikely to expose the limits of inferential or reflective mechanisms. Consequently, we argue that paradigms with greater computational demands and more realistic action affordances are required to identify the mechanisms underlying avoidance learning. Collectively, these insights provide a foundation for theoretical refinement, computational modelling, and methodological innovation, with implications for advancing interventions targeting maladaptive avoidance.

Humans↗

PubMed2026

AI echo INSIGHT study: A prospective blinded randomized trial of artificial intelligence echocardiogram interpretation.

BACKGROUND: Transthoracic echocardiography (TTE) is the most commonly performed cardiac imaging modality with over 30 million studies annually. Demand for timely expert interpretation continues to outpace capacity, creating diagnostic delays and inter-observer variability that impact patient care. Recent research has suggested computer vision artificial intelligence (AI) models can generate accurate preliminary comprehensive TTE reports, however, prospective evaluation is needed to determine whether AI-assisted TTE interpretation can improve clinician efficiency while preserving diagnostic accuracy. METHODS: AI ECHO INSIGHT is a prospective randomized blinded clinical trial conducted at Kaiser Permanente Northern California that will evaluate 1200 historical TTE studies (1000 consecutive unselected studies plus 200 with moderate or greater valvular disease) interpreted using three workflows: (1) AI-generated preliminary report finalized by a blinded cardiologist (AI-assisted); (2) cardiologist-generated preliminary report finalized by a blinded cardiologist (cardiologist-assisted); and (3) sonographer-generated preliminary report finalized by a blinded cardiologist (sonographer-assisted). The primary outcome is the rate of substantial change between preliminary and final reports, comparing the AI-assisted workflow to the pooled cardiologist-assisted and sonographer-assisted workflows. Secondary outcomes include cardiologist interpretation time for report finalization, superiority testing for diagnostic accuracy, and reporting consistency. CONCLUSION: AI ECHO INSIGHT is a prospective randomized blinded clinical trial evaluating the clinical impact of AI-assisted TTE interpretation on diagnostic accuracy, cardiologist efficiency, and reporting consistency in real-world echocardiography workflows. TRIAL REGISTRATION: ClinicalTrials.gov registration number NCT07229300.

Humans↗

PubMed2026

Meta-PseU: A meta-classifier for robust prediction of RNA pseudouridine modification sites from long sequences.

BACKGROUND AND OBJECTIVES: Pseudouridine (Ψ) represents one of the most abundant and conserved RNA modifications. Ψ provides an additional hydrogen-bond donor that enhances RNA structural stability and modulates translation. It participates in diverse biological processes, including RNA-protein interactions, splicing, translational control, and stress responses. Aberrant pseudouridylation is implicated in cancer, neurodegenerative disorders, and autoimmune diseases. Despite its biological importance, experimental identification of Ψ sites remains time-consuming and costly, limiting the feasibility of transcriptome-wide profiling. Computational approaches have therefore become essential complements to experimental techniques. However, state-of-the-art machine-learning and deep-learning predictors often suffer from limited generalizability due to small training datasets. To overcome these issues, we aim at constructing new long-sequence datasets and developing a novel Ψ site predictor. METHODS: New long-sequence datasets were constructed as benchmarks for RNA Ψ-site prediction. The Ψ modification sites in RMBase 3.0 were mapped to the reference genomes across three species of human, mouse, and yeast, and the RNA sequences with a length of 201 were generated by extending the upstream and downstream from the mapped, central sites. To eliminate sequence redundancy, the sequences were clustered using CD-HIT with a 70% sequence identity threshold. We developed Meta-PseU, a logistic regression-based meta-classifier that considered 118 machine learning and deep learning classifiers. The datasets and programs are freely accessible at https://github.com/kuratahiroyuki/MetaPseU. RESULTS: By optimizing model configuration, we proposed the Meta-PseU model stacking 32 machine learning and deep learning classifiers out of 118 classifiers. Meta-PseU substantially improved model generalizability, overcoming a key limitation of existing approaches. It greatly outperformed state-of-the-art predictors and achieved increasing accuracy with increasing sequence length. CONCLUSIONS: Long-sequence datasets were newly constructed as benchmarks for RNA Ψ-site prediction. Meta-PseU offers a new framework for robust Ψ-site identification by using long sequences.

Pseudouridine↗

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

Affective reactivity to a remote computer-based Trier Social Stress Test during a planned quit attempt: associations with short-term cigarette smoking lapse risk.

BACKGROUND: The Trier Social Stress Test (TSST) elicits affective responses and has been linked to smoking behavior. However, its remote use during a planned quit attempt-when stress reactivity may influence early lapse-remains understudied. OBJECTIVE: To quantify affective reactivity to a remotely administered TSST on a planned quit date following overnight abstinence and evaluate associations with cigarette use and lapse within 48 h. METHODS: This secondary analysis used data from a randomized controlled trial of adult smokers completing a remotely administered TSST following overnight nicotine abstinence. Urge, anxiety, and stress were assessed using visual analog scales and summarized using area under the curve (AUC) metrics. Smoking outcomes included cigarette count and lapse within 48 h. Associations were estimated using generalized estimating equations. RESULTS: In adjusted models, anxiety reactivity-but not urge or stress-was associated with cigarette count and lapse. Greater anxiety exposure (AUCtot) and change above baseline (AUCab) were associated with higher cigarette count (IRR=1.0004, 95%CI:1.0002-1.001, p=.002; IRR=1.01, 95%CI: 1.002-1.01, p=.002) and increased odds of lapse (OR=1.001, 95%CI: 1.0001-1.002, p=.03; OR=1.02, 95%CI: 1.001-1.03, p=.03). Effect sizes were small. CONCLUSIONS: Anxiety reactivity under nicotine deprivation was associated with increased cigarette use and lapse 48 h post quit attempt, suggesting individual differences in stress-evoked anxiety may serve as a behavioral marker for early lapse. Remote TSST administration appears feasible for eliciting affective responses on a quit date.

Humans↗

PubMed2026

Virtual surgical planning-assisted versus free-hand head and neck reconstruction: Systematic review, meta-analysis, and a novel classification.

Virtual surgical planning (VSP)-assisted reconstruction is increasingly used as an alternative to conventional free-hand (FH) techniques in mandibular and maxillary free-flap reconstruction. This systematic review and meta-analysis compared clinical outcomes and proposed a Reconstruction Complexity-Completeness classification. PubMed/MEDLINE, Scopus, Web of Science, Google Scholar, and reference lists were searched from inception to 20 June 2026. Comparative studies were eligible. Risk of bias was assessed using RoB 2 or the Newcastle-Ottawa Scale. Random-effects meta-analyses used restricted maximum likelihood estimation and Hartung-Knapp adjustment. Forty-two studies included 2763 patients (1204 VSP; 1559 FH). VSP significantly reduced operative time (33 studies; MD -64.75 min, 95% CI -83.51 to -46.00), ischemia time (15 studies; MD -37.40 min, 95% CI -48.97 to -25.82), and hospital stay (16 studies; MD -1.75 days, 95% CI -3.43 to -0.08). VSP was associated with significantly lower odds of bony non-union (OR 0.31, 95% CI 0.16-0.59) and malocclusion (OR 0.14, 95% CI 0.03-0.64), whereas flap loss, surgical site infection, and plate exposure did not differ significantly. VSP-assisted reconstruction was associated with improved operative efficiency, shorter hospitalization, and lower odds of bony non-union and malocclusion, while no statistically significant differences were detected in flap loss, surgical site infection, or plate exposure. The proposed classification may support complexity-adjusted reporting and comparison.

Humans↗

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↗

PubMed2026

Non-destructive prediction of lead content in oilseed rape leaves by fluorescence hyperspectral technology based on neural network.

Based on fluorescence hyperspectral imaging (FHSI), this study targeted rapid, non-destructive quantification of lead (Pb) content in oilseed rape leaves treated with varying silicon (Si) concentrations, acquiring fluorescence spectra over the 484.43-1001.61 nm wavelength range. To optimize spectral data quality, preprocessing methods (Savitzky-Golay smoothing, first derivative, detrending) were comprehensively compared. Characteristic wavelengths were then selected via interval variable iterative shrinkage, which effectively compressed data dimensionality and reduced computational load. A hybrid SE-CL1DA model, fusing a 1D convolutional neural network, a long short-term memory network and SE attention mechanism was constructed, with Bayesian optimization tuning hyperparameters to boost stability. The BO-SE-CL1DA outperformed both traditional machine learning and insufficiently optimized deep learning model (Rp2=0.9609, RMSE = 0.0377 mg/kg, RPD = 5.1736), thus enabling accurate Pb estimation, supporting Si-regulated heavy metal stress management and facilitating agricultural contamination monitoring.

Plant Leaves↗

PubMed2026

Exploratory identification and cellular functional characterization of ppiabl as a candidate gene associated with growth traits in Paralichthys olivaceus.

The Japanese flounder (Paralichthys olivaceus) is an important mariculture species. However, the genetic mechanisms underlying its growth traits remain poorly understood. To explore the genetic basis of growth variation, whole-genome resequencing was performed in a cultured cohort of 60 individuals, followed by exploratory genome-wide association analysis and candidate-gene prioritization. The results revealed heritability estimates of 0.40 for body weight and 0.24 for body length, with substantial overlap in associated loci between the two traits. Exploratory association and variant-annotation analyses prioritized ppiabl, which carries a nonconservative missense variant, as a candidate gene for further investigation. Tissue expression analysis showed that ppiabl was highly expressed in muscle tissue. This gene encodes a protein belonging to the conserved peptidyl-prolyl cis-trans isomerase family. In Japanese flounder primary muscle cells, ppiabl knockdown was associated with altered expression of growth-related genes and an increased G1-phase fraction, whereas overexpression produced changes in the opposite direction. In line with this, fast-growing individuals were found to have significantly larger muscle fiber areas than slow-growing ones. These findings suggest that ppiabl may be involved in muscle-related cellular processes associated with growth variation in Japanese flounder, although its contribution to whole-animal growth requires further validation. Overall, this exploratory study prioritizes ppiabl as a candidate gene potentially associated with growth-related cellular processes in Japanese flounder, although validation in larger independent populations and in vivo models is required.

Animals↗

PubMed2026

Clinical performance of two lithium disilicate CAD/CAM materials in posterior Class II inlay restorations: A 48-month randomised split-mouth clinical trial.

OBJECTIVES: To compare the clinical performance of Amber Mill (AM) and IPS e.max CAD (EM) lithium disilicate computer-aided design/computer-aided manufacturing (CAD/CAM) materials in posterior Class II inlay restorations and characterise their baseline properties. METHODS: Thirty-four adults received paired AM and EM posterior Class II inlays (68 restorations) in a triple-blind randomised split-mouth trial followed for 48 months. Restorations were evaluated at baseline and annually using revised World Dental Federation (FDI) criteria, with fracture and retention as the primary endpoint. Baseline characterisation included flexural strength, shear bond strength, translucency parameter, and scanning electron microscopy. McNemar, Wilcoxon signed-rank, Friedman, one-way analysis of variance, Tukey post hoc, and inter-rater agreement analyses were used. RESULTS: At 48 months, 18 paired participants were available for primary analysis. Failures occurred in 2 of 18 AM restorations and in 3 of 18 EM restorations, corresponding to success rates of 88.9% and 83.3%, respectively, with no significant between-material difference (McNemar p = 1.000). No catastrophic bulk ceramic fracture was observed. Secondary FDI scores remained mostly within the clinically acceptable range; marginal staining deteriorated over time in both groups (p < .001) without significant between-material differences. Baseline material testing showed significant material- and translucency-dependent differences in flexural strength, shear bond strength, and translucency. CONCLUSIONS: Within the limitations of the 48-month follow-up and the tested Class II inlay indication, AM showed clinical performance comparable to EM. Observed clinical complications were related to retention or marginal/interface behaviour. CLINICAL SIGNIFICANCE: For posterior Class II lithium disilicate CAD/CAM inlays, medium-term complications were mainly retention/interface-related, suggesting adhesive-interface durability may be as important as baseline ceramic strength.

Humans↗

PubMed2026

Efficacy and safety of rib-guided percutaneous thoracic sympathetic radiofrequency thermocoagulation at two different targets for primary palmar hyperhidrosis: a randomized controlled trial.

OBJECTIVES: To compare the efficacy and safety of computed tomography-guided percutaneous thoracic sympathetic radiofrequency thermocoagulation (RFT) targeting the upper versus lateral margin of the fourth rib head for severe primary palmar hyperhidrosis (PPH). METHODS: Patients with severe PPH were randomly divided into Group U (upper margin target) and Group L (lateral margin target). Outcome measures included 1-year recurrence rate, Hyperhidrosis Disease Severity Scale (HDSS), Dermatology Life Quality Index (DLQI), palm skin temperature, finger perfusion index (PI), compensatory hyperhidrosis and patient satisfaction. RESULTS: Both groups (n = 55 each, 110 sides) successfully underwent RFT. No preprocedural PI differences were found (p > 0.05). Immediately post-RFT, PI in Group L was significantly higher than in Group U (left p = 0.025, right p = 0.013). No significant differences in HDSS grades were observed between groups before and at 1 day, 2 weeks, 1 month and 3 months post-procedure. However, at 6 and 12 months, Group L showed significantly lower HDSS grades (left p = 0.033 and 0.016; right p = 0.039 and 0.025) and lower DLQI scores (p = 0.037 and 0.024) than Group U. Patient satisfaction did not differ within 6 months, but Group L had significantly higher satisfaction at 12 months (p = 0.036). CONCLUSIONS: Targeting the lateral margin of the fourth rib head for RFT achieved greater efficacy, better quality of life and higher patient satisfaction compared to the upper margin target.

Humans↗

PubMed2026

A contextual activity score (CAS) for inferring ADAR-associated transcriptional activity across RNA-seq, single-cell, and spatial transcriptomics.

BACKGROUND AND OBJECTIVE: Adenosine-to-inosine RNA editing, catalyzed by Adenosine Deaminases Acting on RNA (ADARs), is a widespread modification involved in neural function, immune regulation, and cancer. The Alu Editing Index (AEI) is the standard metric to estimate ADAR activity but requires raw sequencing reads and is poorly suited for single-cell and spatial transcriptomic data. This study aimed to develop an alternative framework for inferring ADAR-associated transcriptional activity from gene expression data across diverse transcriptomic technologies. METHODS: We developed the Contextual Activity Score (CAS), a framework based on transcriptional signatures from ADAR perturbation experiments. Context-specific signatures were generated for human neurons, mouse neurons, and cancer models to infer ADAR1 and ADAR2 activity. CAS was computed from normalized gene expression matrices using regulon-based enrichment analysis. Performance was evaluated by comparing with the Alu Editing Index across bulk RNA sequencing datasets, simulated sequencing depths, and library preparation protocols. RESULTS: CAS showed strong concordance with the Alu Editing Index across multiple datasets, while remaining robust to reduced sequencing depth and different library protocols. Unlike the Alu Editing Index, CAS can be applied to single-cell and spatial transcriptomic data and enables the independent assessment of ADAR2 activity. In cancer and neuronal contexts, CAS captured biologically meaningful variations in ADAR-associated transcriptional activity at sample, cell-type, and spatial levels. CONCLUSION: CAS provides a scalable approach applicable across multiple RNA-seq protocols for estimating ADAR-associated transcriptional activity using gene expression data. This method, implemented in an open-source R package for broad adoption, expands the ability to study ADAR-associated transcriptional activity across transcriptomic modalities where direct editing quantification is challenging, such as single-cell and spatial transcriptomics.

Adenosine Deaminase↗