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PubMed2026

Fused Deposition Modeling (FDM) of polyether-ether-ketone (PEEK) dental implants: A systematic review of the effect of printing parameters on mechanical behaviour and surface quality.

PURPOSE: This systematic review evaluated how FDM printing parameters influence mechanical behaviour and surface characteristics of 3D-printed PEEK and identified parameter combinations linked to the most favourable mechanical performance and surface quality. MATERIALS AND METHODS: An electronic search was conducted in: MEDLINE (Ovid), PubMed, Embase, Web of Science, Scopus, and Compendex (last update: January 2025). Studies that evaluated the effect of FDM printing parameters on mechanical and surface properties of PEEK were included. Outcomes comprised compressive, tensile, and flexural strengths, elastic modulus, fracture toughness, surface hardness, roughness, and wettability. RESULTS: Of 4005 reports screened, 54 manuscripts were included. 92.6% (n = 50) of articles showed low risk-of-bias, while 7.4% (n = 4) showed medium risk-of-bias. Tensile strength was the most investigated mechanical parameter (78%), followed by elastic modulus (41%), flexural strength (30%), compressive strength (20%), and fracture toughness (6%). Surface roughness was the most evaluated surface property (30%), followed by hardness (17%) and wettability (6%). Across studies, higher printing temperatures, lower printing speed, thinner layer thickness, and maximum infill ratio in a horizontal printing orientation were associated with higher strengths, less warpage, increased accuracy, and improved surface quality. CONCLUSION: Specific combinations of FDM printing parameters can significantly improve the mechanical and surface properties of PEEK. However, it is difficult to meet all the optimal conditions simultaneously. Thus, balancing between different parameters must be considered in practical production.

Benzophenones↗

PubMed2026

Development and validation of a comprehensive prognostic model for 28-day ICU mortality in non-traumatic subarachnoid hemorrhage: an analysis based on the MIMIC-IV database.

BACKGROUND: Due to the complex pathophysiology of non-traumatic subarachnoid hemorrhage (SAH), accurate risk prediction remains a challenge. Our aim is to develop and validate a comprehensive prognostic model that integrates demographic characteristics, vital signs, laboratory parameters, and more, to provide clinical decision-making support in real-world practice. METHODS: We conducted a retrospective cohort study of 785 Non-traumatic subarachnoid hemorrhage patients. The cohort was randomly divided into a training set (n = 549) and a validation set (n = 236). Feature selection was performed using LASSO regression, followed by backward stepwise Cox regression for optimization. A nomogram was constructed based on independent predictive factors, and model performance was assessed using discrimination, calibration, and decision curve analysis. To prevent immortal-time bias, all predictors were anchored to a fixed early (first-24-hour) measurement window, treatment variables were modelled as binary indicators rather than cumulative exposures, and a five-model sensitivity analysis with baseline-severity adjustment was performed. RESULTS: The development of our model followed a systematic approach: first, 15 potential predictive factors were selected via LASSO regression, which were then refined to 12 independent predictors using backward stepwise Cox regression. The final predictive factors included: Ventilation, AHT, Nimodipine 60 mg, Age, SAPS.II, Input amount, Calcium total, Platelet count, White blood cells, Anion gap, pH, and Chloride. The integrated model demonstrated excellent predictive ability for 7-day, 14-day, and 21-day mortality in both the training set (AUC: 0.972, 0.934, 0.898) and the validation set (AUC: 0.968, 0.948, 0.911). Calibration curves and decision curve analysis confirmed the model's reliability and clinical utility across different time points. We constructed a nomogram for individualized risk prediction. Univariate Kaplan-Meier survival analysis demonstrated significant stratification of survival outcomes by each predictor, while restricted cubic spline analysis revealed non-linear relationships between continuous variables and mortality risk. Random survival forest analysis identified the top three predictive factors (Nimodipine 60 mg, Ventilation, AHT) and compared them with our full 12-variable model, confirming superior performance of the integrated model at all time points. At the 28-day primary endpoint, the model achieved a time-dependent AUC of 0.898 (training) and 0.904 (validation); after restricting predictors to the early baseline window, the leakage-controlled model retained good discrimination (validation C-index 0.803). CONCLUSIONS: Our ICU 28-day mortality prognosis model demonstrated robust performance in predicting ICU 28-day mortality in non-traumatic subarachnoid hemorrhage. The model, through the nomogram, provides individualized risk assessment, aiding clinical decision-making and patient stratification.

Humans↗

PubMed2026

Macroprolactinemia as a diagnostic pitfall in hyperprolactinemia: a systematic review and quantitative synthesis.

CONTEXT: Macroprolactinemia is a well-recognized cause of hyperprolactinemia and an important diagnostic pitfall in endocrine practice. However, interpretation of published quantitative prolactin data remains sparse as studies vary in confirmation method, assay platform, polyethylene glycol (PEG) recovery cutoff, and reporting of prolactin measurement. EVIDENCE ACQUISITION: PubMed, Embase, Scopus, Web of Science, the Cochrane Library, and Google Scholar were systematically searched. Eligible studies reported macroprolactinemia-specific quantitative prolactin data in patients with confirmed macroprolactinemia defined by PEG precipitation, gel filtration chromatography (GFC), or both. Two reviewers independently performed study selection, data extraction, and quality assessment. Findings were summarized using study-level descriptive synthesis. The review was prospectively registered in PROSPERO and conducted in accordance with PRISMA 2020 guidelines. EVIDENCE SYNTHESIS: Forty-five studies encompassing 2853 macroprolactinemia cases from 21 413 screened patients with hyperprolactinemia across 22 countries were included. Among 33 studies eligible for primary quantitative analysis, the median study-level central total prolactin attributed to macroprolactinemia was 61.4 ng/mL ([IQR] 42.0-80.0; range 28.1-137.6), and the median study-level post-PEG monomeric prolactin was 11.7 ng/mL (IQR 8.3-13.2; range 4.0-17.0)). The median study-level maximum total prolactin was 264.5 ng/mL (IQR 97.0-425.5; range 81.8-663.0); extreme elevations were attributable to coexisting prolactinomas. CONCLUSION: In confirmed macroprolactinemia, total prolactin elevation is typically moderate, and post-PEG monomeric prolactin is usually within or near the normal range. The post-PEG monomeric prolactin value, rather than percent recovery alone, is the most informative parameter for distinguishing isolated macroprolactinemia from coexisting true hyperprolactinemia. These quantitative benchmarks may help clinicians to avoid unnecessary investigation or treatment.

Humans↗

PubMed2026

Genomic and Molecular Interaction Analysis of NodD1 in a Novel Bradyrhizobium yuanmingense sp. B64 Isolate for Nodulation and Symbiosis of Legume Plants.

Rhizobial bacteria are known for their ability to fix nitrogen for leguminous plants and their essential function for sustainable agriculture. This study characterizes the taxonomic status and functional potential of the Bradyrhizobium B64 isolate using integrated genomic and molecular approaches. The whole genome of the B64 isolate was sequenced via Illumina paired-end technology. Species delimitation was performed using average nucleotide identity (ANI) and digital DNA-DNA Hybridization (dDDH). The NodD1 protein structure was modeled using AlphaFold3 and validated by Ramachandran plot analysis. Molecular docking was then conducted to evaluate interactions between NodD1 and four signaling flavonoids: Apigenin, Daidzein, Genistein, and Naringenin. Genomic analysis revealed a maximum ANI of 94.4% and dDDH values between 51.4 and 62.4%. Since these values fall below the standard prokaryotic thresholds (ANI < 95%; dDDH < 70%), the B64 isolate is identified as a novel species. Physiological assays confirmed nitrogen fixation (1.97 ppm), IAA production (3.67 ppm), and phosphate solubilization (26.10 ppm). Structural validation showed 100% of NodD1 residues in allowed regions, ensuring high model reliability. Docking simulations demonstrated strong binding affinities across all flavonoids, with binding free energies ranging from - 8.8 to - 9.0 kcal/mol. Daidzein exhibited the highest thermodynamic stability (- 9.0 kcal/mol), whereas apigenin showed the most extensive residue interaction network. The B64 isolate is a novel Bradyrhizobium species with a high symbiotic capacity. The stable NodD1-flavonoid interactions provide a molecular basis for efficient nodulation, positioning B64 as a promising candidate for developing lipo-chitooligosaccharide (LCO)-based biofertilizers.

Bradyrhizobium↗

PubMed2026

Target Capture of Ancient Shell DNA Enables Phylogenetic Reconstruction of Deep-Sea Molluscs.

Target capture is widely used to enrich endogenous DNA from calcium phosphate skeletal material in vertebrates, but its performance on calcium carbonate hard parts widely produced by invertebrates remains poorly understood. Here, we compared DNA recovery from four fresh and 12 ancient (eight radiocarbon-dated to 1671-1135 years old before present) deep-sea vesicomyid clam shells, including species Archivesica marissinica, A. nanshaensis and A. okutanii, using whole-genome sequencing (WGS) or target capture of ultraconserved elements (UCEs). WGS achieved 16.65% on-target read recovery of UCEs from fresh soft tissue, but < 1% from shell specimens. By contrast, UCE capture in the same specimen increased on-target reads by up to 155-fold, reaching 29.84% in fresh shells and up to 72-fold, reaching 19.89% in ancient shells. Target capture of UCEs recovered 142-1001 loci per sample compared to 0-230 with WGS alone. Ancient shells of A. marissinica and A. okutanii, based on reads mapped with bwa-mem2 and bbmap, exhibited characteristic post-mortem DNA damage signals, with average 5'-end C-to-T misincorporation rates of 3.46% and 15.97%, respectively, exceeding the levels observed in fresh A. marissinica shells (maximum 1.24%). UCE-based phylogenetic reconstructions incorporating shell ancient DNA recovered two major clades within Pliocardiinae, consistent with published phylogenomic trees. Together, these findings demonstrate that target-capture enrichment enables effective recovery of highly degraded DNA from ancient mollusc shells and supports robust phylogenetic inference at the intrageneric scale, expanding the utility of shells-one of the most abundant invertebrate remains-for evolutionary, biogeographic and conservation studies.

Animals↗

PubMed2026

Diagnostic performance of machine learning models versus established risk stratification for intracranial aneurysm rupture: a systematic review and bivariate meta-analysis.

BACKGROUND: Machine learning (ML) models have been proposed to improve the discrimination of intracranial aneurysm rupture status beyond established clinical risk stratification tools. However, reported performance is heterogeneous and the relative contribution of model architecture and feature dominance remains unclear. METHODS: We performed a Preferred Reporting Items for Systematic Reviews and Meta-Analyses-diagnostic test accuracy systematic review and diagnostic meta-analysis of studies evaluating ML models for intracranial aneurysm rupture discrimination. PubMed, Embase and CENTRAL were searched to February 2026. Sensitivity and specificity were pooled using a bivariate random-effects model, with summary receiver operating characteristic curves generated across training, internal testing and external validation datasets. Models were compared with regression-based approaches and Population, Hypertension, Age, Size of aneurysm, Earlier subarachnoid haemorrhage, Site of aneurysm (PHASES) scores. Subgroup and meta-regression analyses explored associations between algorithm family and feature domain. RESULTS: Sixty-two retrospective cohorts (29 709 patients 209 models) met the inclusion criteria. In training datasets, pooled sensitivity and specificity for ML were 0.81 (95% CI 0.75 to 0.85) and 0.83 (0.80-0.86), with an area under the curve (AUC) of 0.878, exceeding PHASES (AUC 0.667). In testing datasets, ML retained higher discrimination (AUC 0.837) than regression models (0.806) and PHASES (0.646). In external validation, sensitivity was preserved (0.82), but specificity declined (0.66). Deep learning demonstrated the highest AUCs (training and testing). Incorporation of haemodynamic or radiomic features improved pooled discrimination relative to morphology alone. Evidence of small-study effects and mostly unclear Prediction Model Risk Of Bias Assessment Tool ratings were observed. CONCLUSIONS: ML approaches demonstrate higher pooled discrimination for aneurysm rupture status than conventional risk scores in retrospective datasets, but reduced external validation specificity and heterogeneity limit confidence for clinical translation. Prospective, externally validated, calibrated models are required before integration into routine cerebrovascular risk stratification.

Humans↗

PubMed2026

Early-stage trajectories of social-occupational functioning and long-term functional outcome prediction in early psychosis: A 12-year follow-up of the randomized controlled trial on extended early intervention.

BACKGROUND: Functional impairment in psychosis often persists despite symptomatic remission. There is a paucity of research examining early-course psychosocial functioning trajectories, and none has been conducted to examine relationship between the trajectories and prospective long-term functional outcomes in early psychosis sample. METHODS: We conducted 12-year follow-up of a randomized controlled trial on extended early intervention for first-episode psychosis to identify early-course social-occupational functioning trajectories and their baseline predictors and associations with 12-year outcomes. Participants who completed Social and Occupational Functioning Scale (SOFAS) scores at three or more timepoints between baseline and 3-year follow-up were included in the study. Premorbid adjustment, illness characteristics, symptom severity, functioning, and treatment profiles were assessed. Latent growth mixture modeling was employed to derive early-course social-occupational functioning trajectories based on SOFAS scores over 3-year follow-up. RESULTS: A total of 148 participants were included in this study, with 106 patients having completed the 12-year follow-up. Our results identified four distinct trajectories, including persistently-good class, gradually-improved class, suboptimal-stable class, and persistently-poor class. Patients in persistently-poor class had more severe negative symptoms at baseline compared to patients in persistently-good class. Patients with persistently-poor trajectory had worse long-term outcomes than those with other classes in the majority of functional measures at 12-year follow-up. CONCLUSIONS: The majority of patients were classified in early-stage suboptimal or poor functional trajectories. Above one-fourth of the participants exhibited persistently-poor social-occupational functioning trajectory, which predicted worse functional outcomes at 12-year follow-up. These findings highlighted the importance of tracking functional changes during the initial years of illness.

Humans↗

PubMed2026

Age at menopause and subjective cognitive symptoms predict digital cognitive outcomes at the gynecological Well-Woman visit.

INTRODUCTION: Women are at increased risk for Alzheimer's Disease (AD). Growing evidence suggests that the menopausal transition may represent a vulnerable window for development of AD-related pathology. Yet, women are diagnosed with AD later than men. Conducting routine cognitive screenings and integrating information about both cognitive symptoms and age at menopause may help address sex-based disparities in detection and prevention. This study investigated whether subjective cognitive symptoms, in combination with age at menopause, were associated with performance on a digital cognitive task in postmenopausal women. METHODS: 183 postmenopausal women (mean age = 63.8, range = 45-85) were recruited after their Well-Woman visit. Participants completed the Screener for Cognitive Problems in Everyday Life (SCoPE) to assess subjective cognitive symptoms, followed by a sensitive measure of objective cognition: the Linus Health Digital Clock and Recall (DCR™). Information was also collected on age at menopause. We examined associations of subjective cognitive symptoms and age at menopause with digital cognitive performance, adjusting for age, education and depression. Model fit was evaluated using adjusted R2, AIC, and BIC. RESULTS: 48.1% of women reported one or more cognitive symptoms on the SCoPE. On objective testing, 73.2% scored in the normal range, 20.8% in the borderline range, and 6.0% in the impaired range. SCoPE total score was negatively associated with objective cognitive performance in adjusted models (B = -.12, p = .03). Age at menopause showed a significant quadratic association with cognitive performance (B = -0.006, p<.001). SCoPE total was not associated with DCR subtests, while age at menopause predicted both Delayed Recall and Clock Drawing. CONCLUSION: Subjective cognitive symptoms and age at menopause were associated with lower performance on a sensitive, objective cognitive test. Findings support routine cognitive screening and suggest that subjective cognitive symptoms as well as age at menopause are associated with cognitive function.

Humans↗

PubMed2026

Pharmacokinetics of injectable favipiravir: phase I, randomized, double-blind, placebo-controlled study in healthy East Asian subjects.

Favipiravir, an oral antiviral medication, has been approved in Japan for the treatment of patients with novel or re-emerging influenza and severe fever with thrombocytopenia syndrome (SFTS). Randomized, double-blind, placebo-controlled trials were conducted in an East Asian population to characterize the pharmacokinetics and tolerability of an injectable favipiravir formulation. In the single-ascending dose trial, subjects received a single intravenous (IV) dose of 300-2,400 mg of favipiravir. In the multiple dose trial, 1,800 mg was administered twice daily on the first day, followed by 800 mg twice daily for the subsequent 10 days, which is the approved tablet dose for SFTS in Japan. This multiple-dose trial was divided into a cohort receiving intravenous administration throughout the treatment period (IV cohort) and a cohort switching to oral administration from Day 6 (Switching cohort). After a single administration of ≤2,400 mg, the pharmacokinetic parameters increased in a dose-dependent manner but showed slight deviation from linearity. The geometric mean maximum plasma concentration following a single 2,400 mg dose was 126 (range: 110 to 138) μg/mL. In the IV cohort, the trough (at 12 h post-dose) plasma concentrations were maintained at approximately 85 μg/mL after Day 2. These concentrations were approximately 20% higher than those achieved with the same oral doses. In the Switching cohort, these concentrations were maintained throughout the treatment. No serious adverse events were observed. These findings support advancing injectable favipiravir into clinical evaluation.CLINICAL TRIALSThis study is registered with the Japan Registry of Clinical Trials as jRCT2071210042 and jRCT2071210126.

Humans↗

PubMed2026

Microbial signal profiles and organism-level concordance between plasma metagenomic sequencing and blood culture in suspected bloodstream infection.

Plasma metagenomic next-generation sequencing (mNGS) and blood culture detect different components of the microbial signal and frequently produce discordant organism reports. We characterized microbial signal class, report-derived burden, organism-level concordance, and independent clinical attribution in a retrospective, single-center, episode-level cohort. Among 329 episodes with evaluable plasma mNGS reports, 315 had blood culture performed; 232 were mNGS positive/culture negative and 53 were positive by both methods. In the 232 discordant episodes, the recorded routine-care diagnosis classified 124 as bloodstream infection (BSI) and 108 as non-BSI. Nonviral signals were present in 78.2% and 42.6%, respectively (P < 0.001), and median maximum report-derived sequence counts were 98.5 and 11.5 (P < 0.001). Two laboratory physicians then independently reviewed source records using structured criteria while masked to the recorded BSI label and mNGS organism and sequence-count information. Initial agreement for the five-category BSI assessment was 97.6% (Cohen's kappa, 0.960). Within the mNGS-positive/culture-negative subgroup, adjudicated BSI likelihood showed a modest ordinal association with report burden (Spearman rho = 0.190; P = 0.004), while mNGS organisms were considered supported in 1 episode, plausible in 158, unlikely or contaminant in 72, and unresolved in 1. Among 53 dual-positive episodes, 33 (62.3%) shared at least one species, but only 5 (9.4%) had complete species-set concordance. Plasma mNGS and blood culture therefore frequently generated non-equivalent organism sets. Signal class and report burden contributed graded contextual evidence, but organism-level attribution required clinical review and orthogonal microbiology rather than binary positivity alone.

Humans↗

PubMed2026

Evaluation of the clinical and mechanistic role of MCM2 expression in the prediction of meningioma recurrence after radiotherapy.

OBJECTIVE: Postoperative radiotherapy is an effective treatment for meningiomas; however, treatment response varies among patients. In addition, practical methods for predicting tumor recurrence after radiotherapy have not been well established. Minichromosome maintenance protein 2 (MCM2), a key regulator of DNA replication licensing, was recently implicated in highly proliferative molecular subtypes of meningioma. In this study, the authors evaluated whether MCM2 immunohistochemical expression predicts response to radiotherapy in patients with meningiomas. METHODS: The authors retrospectively analyzed the records of patients with WHO grade 1-3 meningiomas treated with resection followed by radiotherapy at a single institution between July 2003 and November 2023. The MCM2 labeling index was assessed immunohistochemically, and patients were stratified into MCM2-high and -low groups using a cutoff of 35%. Progression-free survival (PFS) was defined as the interval from the completion of radiation therapy to postoperative radiological tumor recurrence or regrowth. Patients who showed no progression were censored at their last follow-up. PFS was estimated using Kaplan-Meier analysis and subsequently evaluated with Cox proportional hazards models. To further investigate the biological mechanisms associated with MCM2 expression, comprehensive transcriptomic analyses, including gene set enrichment analysis, was performed to elucidate the molecular processes that occur within MCM2-high tumors. RESULTS: The study population included 15 men (42%) and 21 women (58%), with a mean age of 63 years. Ten tumors (28%) were classified as MCM2-high meningiomas and 26 (72%) as MCM2-low meningiomas. High MCM2 expression was significantly associated with WHO grades 2-3 histology and higher Ki-67 labeling indices. During a median follow-up of 2.52 years, tumor progression after radiotherapy occurred in 47% of the patients. High MCM2 expression (HR 8.34, p = 0.03) was significantly associated with shorter PFS and remained an independent predictor of recurrence after adjustment for WHO grade, tumor size, and Ki-67 labeling index. Transcriptomic analyses of MCM2-high tumors revealed upregulation of cell proliferation-related pathways, accompanied by increased signaling through the E2F8-CHEK1 axis associated with radiation resistance and suppression of the TNF-α signaling pathway implicated in radiosensitivity. CONCLUSIONS: In meningiomas, high MCM2 expression is associated with early recurrence following radiotherapy. The study findings suggest that this association is driven by diverse biological mechanisms related to cell cycle regulation and radioresistance. Immunohistochemical assessment of MCM2 expression may serve as a practical and accessible biomarker for risk stratification and may support the future development of individualized postoperative radiotherapy strategies.

Humans↗

PubMed2026

Applications of artificial intelligence in robot-assisted surgery: a systematic review.

To characterize applications of artificial intelligence (AI) in robot-assisted surgery, summarize technical and clinical performance, and assess the quality of the available evidence. PubMed, Web of Science Core Collection, and Scopus were searched for English-language journal articles published from 1 January 2020 through 31 October 2025. Randomized, observational, model-development, validation, and feasibility studies evaluating AI in robot-assisted surgery or closely related image-guided minimally invasive workflows were eligible. Two reviewers independently performed study selection, data extraction, and risk-of-bias assessment. Owing to heterogeneity in surgical procedures, AI tasks, analytical units, validation strategies, and outcomes, findings were synthesized descriptively without statistical pooling. The review was registered in the International Prospective Register of Systematic Reviews (CRD420251175699). Seventeen studies were included: seven clinical prediction or decision-support studies, eight intraoperative recognition, segmentation, or image-guided studies, and two training or workflow studies. Five prediction studies reported area-under-the-curve values of 0.74-0.95. Technical studies reported F1 or Dice scores of 0.525-0.995 and task-specific accuracies of 0.840-0.998. Two randomized studies suggested benefits for personalized suturing feedback and automated camera control, but neither established improved patient outcomes. Only one study had low overall risk of bias; the remaining studies were at high or unclear risk or raised some concerns. AI applications in robot-assisted surgery show promise for prediction, intraoperative perception, training, and workflow support. Evidence primarily demonstrates technical feasibility rather than established clinical effectiveness. Independent multicenter validation and prospective evaluation of patient, educational, and workflow outcomes are required before widespread implementation.

Robotic Surgical Procedures↗

PubMed2026

Non-parametric differential methylation analysis characterizes histotype-specific promoter regions in epithelial ovarian cancer.

Epithelial ovarian cancer (EOC) is a heterogenous disease with frequent late-stage diagnosis and high mortality rates, for which no reliable screening tests exist. In recent years, epigenetic biomarkers in the form of DNA methylation in CpG-rich regions have gained increased attention in the scientific community due to their robust nature and accessibility, allowing for diagnosis without the need for invasive surgery. In this study, we investigated the aberrant methylation of promoter regions in early stage EOC through non-parametric methods, with the purpose of characterizing candidate epigenetic biomarkers. The approach was used on a cohort of early stage EOC samples, and results were compared to existing programs for differential methylation. Significant regions were then used to construct a CpG panel for stratifying EOC histotypes through predictive classification in external data. Identified promoter regions were highly reproducible across cohorts, and the constructed CpG model stratified histotypes in external cohorts through predictive classification. Comparisons against other DMP and DMR callers showed a degree of homogeneity between results but also revealed promoter regions that were overlooked despite clear signs of aberrant methylation. Finally, EOC histotypes were found to differ in their methylation distribution types, and results indicate that methods sensitive to non-normally distributed data may be poorly suited to compare groups with different distribution types. The non-parametric approach identified aberrantly methylated promoter regions that were highly reproducible across cohorts. Results from predictive classification indicate that these regions may be useful for the purpose of EOC histotype stratification.

Humans↗

PubMed2026

Impact of Albuminuria-Lowering Treatments on Cardiovascular Predictive Ceramides in Diabetes: Post Hoc Analysis of the ROTATE Trials.

AIM: Cardiovascular disease (CVD) is the leading cause of mortality in individuals with diabetes. Diabetic kidney disease, closely related to CVD risk, is prevalent in up to 40% of this population. Emerging evidence suggests ceramide lipids as accurate biomarkers for CVD. We assessed the effect of four albuminuria-lowering drugs on CVD-related ceramides in diabetes by post hoc analysis of the ROTATE trials. MATERIALS AND METHODS: Twenty six adults with type 1 (T1D) as well as 37 with type 2 diabetes (T2D) with a urine albumin-creatinine ratio (UACR) of 30-500 mg/g participated in a 4-week 4-time randomized crossover study with periods of telmisartan, empagliflozin, linagliptin and baricitinib treatment, each separated by a 4-week washout period. Blood samples were collected at the beginning and end of each period and ceramide lipids (Cer16, Cer18, Cer20, Cer22, Cer24 and Cer24:1) were measured. The effect of each treatment was evaluated using linear mixed-effect models. RESULTS: At baseline, individuals with T2D had greater levels of Cer22 and Cer24 compared to the individuals with T1D. Among the treatments, linagliptin was the only drug that demonstrated a reduction of Cer22, Cer24 and Cer24:1 from baseline by 22.6% (95% CI: -33.58; -9.79, p = 0.001), 25.7% (95% CI: -38.94; -9.69, p = 0.003) and 19.6% (95% CI: -31.34; -5.95, p = 0.007), respectively. No changes in the ceramides were observed for the other drugs. CONCLUSION: Our exploratory findings suggest that certain albuminuria-lowering drugs may affect ceramide levels as a secondary effect. However, further mechanistic investigations are needed.

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

A Sentiment-Based Comparison of AI- and Physician-Generated Empathic Statements in Palliative Care.

CONTEXT: Empathic communication promotes trust in patient-provider relationships. As healthcare integrates artificial intelligence (AI) into patient communication, we have yet to understand how these models' communication compares to that of physicians. OBJECTIVES: Our primary objectives were to examine patient preferences for AI-generated vs. palliative care physician-generated empathic statements addressing fear and anxiety around cancer treatment, and to analyze associations between linguistic features and patient preferences. METHODS: We conducted a secondary analysis of the PALL-AI trial, a randomized controlled survey comparing cancer patients' preferences of AI- to physician-generated empathic statements. Physicians and AI were provided the same prompt with a maximum sentence length. Patient preferences for each statement were measured in blinded surveys. We analyzed sentiment of the statements using the Valence Aware Dictionary and Sentiment Reasoner (VADER) and the National Research Council Canada (NRC) Emotion Lexicon. We evaluated associations between sentiment scores and patient preferences using Spearman's correlation coefficients. RESULTS: A total of 105 patients completed blinded surveys, preferring the AI-generated statement 72.4% of the time. VADER sentiment analysis showed all three AI statements displayed positive sentiment, while all three physician statements displayed negative sentiment. Controlling for statement length, AI statements used twice as many positive words as human statements. However, they contained a similar number of negative words. Of the eight NRC emotions, "trust" and "joy" demonstrated the strongest correlations with patient preference. CONCLUSION: Patients preferred AI-generated statements around cancer care over those from palliative care physicians when standardized for prompt and statement length. Analysis shows AI-generated statements contain more positive language which may be the factor driving patient preference toward AI.

Humans↗

PubMed2026

ADAM10's combined influence on the diagnostic usefulness of IL 22, IL 10, IL-17 A, and IL-17D in autism spectrum disorders: Predicted role on gut leakiness as co-morbidity.

Autism spectrum disorder (ASD) is a complex neurodevelopmental disorder with increasing global prevalence but a lack of reliable diagnostic biomarkers. Emerging evidence suggests that immune dysregulation, gut-brain axis dysfunction, and increased intestinal permeability play key roles in ASD pathophysiology. This study investigated the combined diagnostic value of ADAM10 and cytokines (IL-10, IL-22, IL-17 A, and IL-17D). Multivariable logistic regression produces an improved ROC curve that improves diagnostic accuracy over individual markers by combining numerous predictors into a single risk score (linear predictor). The technique, which frequently raises individual marker AUCs, entails modelling a binary result, calculating the probability, and visualizing ROC based on the projected probabilities. In this case-control study, plasma levels of ADAM10, IL-10, IL-22, IL-17 A, and IL-17D were measured in 37 male children with ASD and 37 age-matched controls. Group comparisons, correlation analyses, and receiver operating characteristic (ROC) curve analyses, including combined ROC models, were performed. ADAM10, IL-22, and IL-17 A levels were significantly reduced in children with ASD compared to controls, whereas IL-10 and IL-17D showed no significant differences. ADAM10, IL-17 A, and IL-22 demonstrated good diagnostic performance, with AUC values of 0.886, 0.855, and 0.812, respectively. In contrast, IL-10 and IL-17D showed poor discriminatory ability, with AUC values of 0.524 and 0.599, respectively. Combined ROC analysis markedly improved diagnostic accuracy, with all panels including ADAM10 achieving AUC values above 0.90, and some reaching as high as 0.988, with high sensitivity and specificity. The combination of ADAM10 with selected cytokines significantly enhances diagnostic performance compared to individual markers, supporting a link between immune dysregulation, barrier dysfunction, and gut permeability in ASD.

Humans↗

PubMed2026

HPV circulating tumor DNA as a potential prognostic and predictive biomarker in head and neck squamous cell carcinoma: a systematic review.

PURPOSE: Human papillomavirus circulating tumor DNA (HPVctDNA) has emerged as a promising prognostic biomarker in HPV-related head and neck squamous cell carcinoma (HNSCC). This systematic review aimed to synthesize current evidence on the diagnostic accuracy and prognostic value of HPVctDNA in HNSCC management. MATERIAL/METHODS: We systematically reviewed a PubMed-indexed database of studies published between January 2012 and September 2025. Eligible studies were assessed for design, primary tumor site and stage, treatment modality, HPVctDNA detection method, diagnostic accuracy (sensitivity and specificity), and reported clinical endpoints. Descriptive syntheses were performed; sensitivity and specificity were standardized to proportions and summarized as median values per group. RESULTS: A total of 60 studies, including 8,234 patients were analyzed, of which 41 (68.3%) focused exclusively on oropharyngeal squamous cell carcinoma (OPSCC) and 17 (28.3%) included mixed HPV-related HNSCC subsites and HPV-positive cancers of unknown primary. The median follow-up across the included studies was 23 months. Among the included studies, 19 were retrospective (31.7%) and 33 were prospective (55.0%), with a small proportion of cross-sectional and randomized clinical trials. Overall, 40 (66.7%) evaluated the role of HPVctDNA in a curative setting. Plasma was the most common sample type, analyzed in 55 studies (91.7%), while 5 studies also included saliva. Detection methods varied: 40 employed droplet digital PCR (ddPCR), 16 used quantitative PCR (qPCR) and 4 applied NGS-based assays. Most of these studies (38, 63.3%) evaluated the prognostic utility of HPVctDNA, while only 4 (6.7%) assessed HPVctDNA in a screening or diagnostic setting. Regarding diagnostic accuracy, the median sensitivity across evaluable studies was 91.1%, while the median specificity was 99.4%. In OPSCC-only cohorts, the median sensitivity and specificity were 89.4% and 99.4%, respectively. Dynamic changes in HPVctDNA levels during or after treatment were consistently associated with outcomes: clearance or sustained negativity correlated with higher response rates, improved progression-free survival and overall survival, while persistent positivity or increasing levels predicted disease progression and recurrence. CONCLUSIONS: HPVctDNA demonstrates high diagnostic and prognostic accuracy in HPV-related HNSCC, especially OPSCC, supporting its use for prognosis, treatment monitoring and early detection of recurrence. However, prospective interventional studies are still required to demonstrate that HPVctDNA-guided treatment decisions improve clinical outcomes before routine implementation.

Humans↗