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PubMed2026

A multi-scale fusion model based on multi-phase contrast-enhanced CT for predicting pancreatic cancer resectability.

Purpose.Develop a multi-scale fusion model (MSFM) based on multi-phase contrast-enhanced computed tomography (CECT) to predict pancreatic cancer (PC) resectability, thereby assisting expert decision-making.Methods.This retrospective study enrolled 280 patients with PC from four institutions, which were randomly divided into a training cohort (202 patients) and an independent test cohort (78 patients). Three-phase CECT images (arterial, venous, and delayed phases) were used for modeling. The MSFM comprises two sub-networks: (1) a multi-phase fusion network for extracting cross-phase shared fusion features, (2) a phase-specific branch network for capturing phase-specific features; and a post-fusion strategy to generate the final predictive score by integrating the shared fusion features and three groups of phase-specific features. Additionally, a human-machine fusion deep learning model (HMfDL) was constructed by fusing the predictive score of the MSFM with expert assessments.Results.In the independent test, the MSFM achieved an AUC (area under the receiver operating characteristic curve) of 0.8385 (95% CI: 0.7521-0.9249), accuracy of 84.62%, sensitivity of 72.00%, and specificity of 90.57%. This performance outperformed single-phase models (AUC range: 0.7638-0.7781), two-phase models (AUC range: 0.7826-0.7864), and ten states-of-the-art classifiers (AUC range: 0.7404-0.7796). The HMfDL further improved the performance, reaching an AUC of 0.8626 (95% CI: 0.7853-0.9400), accuracy of 91.03%, sensitivity of 80.00%, and specificity of 96.23%. Notably, the HMfDL corrected 58.82% of misdiagnosis made by experts.Conclusions. The MSFM effectively fuses multi-phase CECT to enable highly accurate predictions of PC resectability, and provides valuable support for expert decision-making through HMfDL.

Humans↗

PubMed2026

Holmium laser enucleation of the prostate for the treatment of lower urinary tract symptoms in men with benign prostatic hyperplasia.

RATIONALE: A range of surgical options is available for the treatment of benign prostatic hyperplasia (BPH), including holmium laser enucleation of the prostate (HoLEP). The evidence is unclear regarding differences in functional, perioperative, and morbidity outcomes between these modalities. OBJECTIVES: To assess the effects of holmium laser enucleation of the prostate compared with other surgical treatments for lower urinary tract symptoms in men with benign prostatic hyperplasia. SEARCH METHODS: We searched multiple databases (including MEDLINE, Embase, CENTRAL, Web of Science, LILACS, and the International HTA database), trial registries, and conference abstracts through April 08, 2026. ELIGIBILITY CRITERIA: We only included randomized trials of men over 40 years of age with a prostate volume of at least 20 mL (assessed by digital rectal examination, ultrasound, or conventional imaging) who exhibited lower urinary tract symptoms (LUTS) defined by an International Prostate Symptom Score (IPSS) of eight or greater undergoing surgical interventions for BPH. OUTCOMES: The critical outcomes measured were the urologic symptoms score, the quality-of-life score, and major adverse events. The important outcomes measured were: re-treatment, erectile function, ejaculatory function, transfusions, acute urinary retention, indwelling urinary catheter duration, and hospital stay duration. RISK OF BIAS: We used the Cochrane risk of bias tool (RoB 1) to assess for potential sources of bias on a study and outcome level basis. SYNTHESIS METHODS: We pooled outcome data using the random-effects model and performed meta-analyses using the Mantel-Haenszel method. We assessed statistical heterogeneity in the pooled data by visually inspecting forest plots and using the I2 statistic to quantify it. We used the GRADE framework to assess the certainty of evidence. INCLUDED STUDIES: We included 52 trials that included 6242 participants that compared HoLEP to other surgical interventions for benign prostatic hyperplasia. The median age of participants across the studies ranged from 65 to 74 years. The baseline prostate volume ranged from 30 cc to 142 cc. Baseline IPSS scores ranged from 19.6 to 28.6 (range 0-35). SYNTHESIS OF RESULTS: We prioritized comparing HoLEP with transurethral resection of the prostate (TURP) at short-term follow-up (up to 12 months), because TURP is the long-standing reference standard and the predominant comparator in randomized surgical trials. Findings for the four remaining comparisons (laser ablation, alternative energy source enucleation, other minimally invasive therapies, and simple prostatectomy), for long-term follow-up, and for all remaining outcomes are reported in full in the review. Compared to TURP, at short-term follow-up: Critical outcomes - HoLEP may result in little to no difference in short-term urologic symptom scores measured using the IPSS (range 0 to 35; lower values reflect fewer symptoms) (MD -0.67, 95% CI -1.20 to -0.14; I² = 93%; 14 studies, 1666 participants, low-certainty evidence). - HoLEP may result in little to no difference in short-term quality of life (range 0 to 6; lower values reflect better quality of life) (MD -0.04, 95% CI -0.23 to 0.15; I² = 73%; 6 studies, 876 participants, low-certainty evidence). - HoLEP may result in little to no difference in short-term major adverse events (RR 0.75, 95% CI 0.35 to 1.58; I² = 0%; 10 studies, 1147 participants, low-certainty evidence). Important outcomes - HoLEP likely results in little to no difference in re-treatment (RR 0.45, 95% CI 0.14 to 1.50; I² = 0%; 8 studies, 813 participants, moderate-certainty evidence). - HoLEP likely results in little to no difference in erectile function (MD -0.03, 95% CI -0.47 to 0.42; I² = 0%; 3 studies, 518 participants, moderate-certainty evidence). - Ejaculatory function: we did not find any data for this outcome. - HoLEP likely reduces the need for blood transfusion (RR 0.19, 95% CI 0.09 to 0.42; I² = 0%; 15 studies, 1755 participants, moderate-certainty evidence). AUTHORS' CONCLUSIONS: Compared with TURP, HoLEP may achieve similar relief of urologic symptoms, similar quality of life, and similar rates of major adverse events in the first 12 months after surgery, and probably similar re-treatment rates and erectile function. HoLEP likely reduces the need for blood transfusion; this is the only advantage of HoLEP that the randomized evidence, as summarized here, supports as clinically important. There was insufficient evidence to assess outcomes in the subset of individuals with larger prostates or on anticoagulation. Future research should prioritize long-term trials reporting sexual function and urinary incontinence outcomes, recruit men with very large prostates (≥ 150 cc) or on anticoagulation therapy, and evaluate cost-effectiveness and training requirements. FUNDING: No external funding was received for this review. REGISTRATION: The protocol for this review was published in the Cochrane Database 2019 (https://doi.org/10.1002/14651858.CD013291).

Humans↗

PubMed2026

Effectiveness of an AI-based home exercise app for rehabilitation of rotator cuff-related shoulder pain: A randomized controlled trial.

BACKGROUND: Rotator cuff-related shoulder pain contributes to disability and healthcare use. Although therapeutic exercise is first-line treatment, limited supervision and adherence may reduce its effectiveness; digital rehabilitation with real-time feedback may address these limitations. OBJECTIVES: To evaluate the effectiveness of adding a digital rehabilitation program to standard physiotherapy on pain, function, fear-avoidance beliefs, and healthcare utilization. DESIGN: Single-center, assessor-blinded, randomized controlled trial with two parallel groups. METHOD: Forty-six adults (mean age 59 years) with rotator cuff-related shoulder pain were randomized to 12 weeks of conventional physiotherapy or physiotherapy plus an AI-based digital rehabilitation program using computer vision for real-time feedback and performance monitoring. Outcomes were assessed at baseline and at 2, 4, and 12 weeks. Pain intensity (NPRS) was primary outcome; secondary outcomes included upper limb function (QuickDASH), fear-avoidance beliefs (FABQ), and post-intervention healthcare utilization. Analyses followed an intention-to-treat approach. RESULTS: Pain reduction exceeded the MCID (1.3) at 4 and 12 weeks. Between-group differences favoured the intervention at Weeks 2 and 4 (MD -0.7; 95% CI -1.13 to -0.14 and MD -1.01; 95% CI -1.8 to -0.2, respectively). Upper limb function improved more at Week 4 (MD -7.3; 95% CI -12.3 to -2.2). FABQ scores decreased more at Week 12 (MD -7.6; 95% CI -14 to -0.5). Fewer participants in the experimental group required post-intervention healthcare (3 vs 10; p = 0.02). CONCLUSION: Adding AI-based home exercise app to conventional treatment improve pain and may improve function and reduce healthcare utilization in rotator cuff-related shoulder pain.

Humans↗

PubMed2026

Application of Three-Dimensionally Printed Surgical Guides in Precise Sacral Tumor Excision and Defect Reconstruction.

OBJECTIVE: Precise resection of sacral tumors remains technically demanding due to their deep anatomical location and close proximity to critical neurovascular structures. Conventional freehand techniques often result in suboptimal resection margins, excessive blood loss, and compromised lumbopelvic stability. This study evaluated whether patient-specific three-dimensional (3D)-printed guiding templates improve surgical accuracy and perioperative outcomes in sacral tumor resection and reconstruction. METHODS: Nineteen patients undergoing en bloc sacral tumor resection (S1-S3 involvement) with spinopelvic reconstruction (2006-2020) were retrospectively analyzed. Patients were divided into a 3D-printing group (n = 10) and a conventional freehand group (n = 9). In the 3D-printing group, computer-aided design and 3D-printed templates were used for osteotomy, screw placement, and defect reconstruction. Perioperative metrics, surgical accuracy, and complications were compared between groups using Welch's t-test and the Hodges-Lehmann method; oncologic events during follow-up were recorded descriptively. RESULTS: The 3D-printing group demonstrated significantly shorter operative time (456.5 ± 62.36 vs. 574.44 ± 114.58 min, p = 0.012), reduced blood loss (4081.40 ± 838.99 vs. 5090.0 ± 1059.67 mL, p = 0.034), and fewer fluoroscopic exposures (4.2 ± 0.79 vs. 10.0 ± 1.58, p < 0.001) compared with the conventional group. Osteotomy accuracy was also superior in the 3D-printing group, with significantly lower angular deviation (3.33° ± 0.45° vs. 6.79° ± 2.16°, p = 0.0012). Postoperative complication rates were comparable (30% vs. 44.4%, p = 0.649), but hospital stay was significantly shorter in the 3D-printing group (10.7 ± 2.71 vs. 18.11 ± 4.01 days, p < 0.001). CONCLUSION: Patient-specific 3D-printed guiding templates enhance precision in sacral tumor excision and reconstruction, improving surgical efficiency and perioperative safety. This computer-assisted, template-guided approach represents a valuable advancement for complex sacral oncologic surgery.

Humans↗

PubMed2026

A hybrid effectiveness-implementation trial to integrate precision skin cancer risk feedback in federally qualified health centers.

BACKGROUND: Skin cancers are the most common type of cancer in the United States, occur in all segments of the population, and are preventable. Our previous research with primary care patients' demonstrated interest in and efficacy of a precision prevention intervention providing feedback on MC1R risk level (higher versus average) in combination with prevention education materials relative to a standard educational intervention. Our current study is a hybrid type 1 effectiveness-implementation trial deployed at six federally-qualified health centers. This paper presents the study protocol. METHODS: A community advisory panel will guide development of study materials and measures. Staff training at each clinic will be completed in-person. Patients will be approached and screened in-person. Those completing genetic testing and the baseline survey will be randomized to the precision versus standard intervention for each risk level with a target sample size of 286 for each combination. Primary outcomes of effectiveness, assessed at 6 and 12 months, include a tanning score (5 items assessing intentional and unintentional tanning), number of sunburns, conduct of a skin self-examination, and electronic health record documentation of clinician-patient communication about skin cancer prevention. Effectiveness comparisons will focus on the precision relative to the standard intervention among higher risk participants. Implementation data will be collected to identify barriers and facilitators. RESULTS: Effectiveness and implementation outcomes will be evaluated following study completion. CONCLUSIONS: Results will guide subsequent scale-up of the precision intervention, including modifications of the intervention as well as methods for implementation. CLINICAL TRIALS IDENTIFIER: NCT07222995.

Humans↗

PubMed2026

Precision targeting of teacher burnout using network-informed ecological momentary interventions.

Teacher well-being affects classroom functioning and workforce stability, yet generic digital programs rarely use person-specific affect dynamics to select support. This cluster-randomised trial evaluated whether micro-interventions selected from high expected influence (EI) nodes in teachers' contemporaneous affect networks produced larger changes in burnout-related EI and everyday happiness than content-matched random allocation. The objectives were to estimate allocation effects on changes in estimated network summaries and happiness, evaluate network change as a statistical mediator, examine personality moderation, and benchmark simpler allocation rules. A two-arm cluster randomised platform trial was conducted in 84 public schools across four urban districts in H Province. After a 14 day baseline of ecological momentary assessment (EMA), person specific partial correlation networks were estimated for happiness, exhaustion, detachment, efficacy and rumination. An optimisation engine prioritised three brief micro-intervention types per teacher according to baseline EI, while the active control received the same library without network information. EMA continued for 8 weeks; Bayesian multilevel models, permutation-based mediation, and benchmarking analyses were applied. EI-based targeting produced larger reductions in the composite EI-change index than active control (mean difference 0.11, 95% credible interval 0.08 to 0.14) and higher week 7 EMA happiness (4.4 points on a 0 to 100 scale, 95% credible interval 2.7 to 6.0), with a positive arm by week slope difference of 0.62 points per week (95% credible interval 0.39 to 0.85). Model-based mediation estimates were consistent with approximately one half of the happiness difference being statistically associated with change in the composite EI-change index (average conditional mediation estimate 3.5 points, 95% credible interval 2.0 to 5.2). Benchmarking showed smaller gains under severity, threshold, or group-level centrality rules. Effects were stronger among teachers higher in conscientiousness. The findings indicate that integrating EMA, network modelling, and EI-driven optimisation yields measurable gains beyond content-matched exposure, providing a proof of concept for district-scale precision mental health that requires prospective implementation testing. Replication in additional regions, expanded node sets, and longer follow up are warranted to assess durability and generalisability.

Female↗

PubMed2026

The mighty microproteins: from versatile cellular regulators to precision medicine therapeutics.

Microproteins, are tiny proteins encoded by small open reading frame (sORF), translation of these non-canonical open reading frames (ncORFs) has been implicated in diverse biological processes and diseases. This review summarizes recent developments in the discovery, biogenesis, and functional characterization of microproteins, and their involvement in various disease, with special focus on their roles in cancer, cardiovascular, metabolic, neurodegenerative and immune-related disorders. We emphasize the regulation of key cellular pathways by microproteins, including mitochondrial homeostasis, apoptosis, metabolic reprogramming, and immune signaling, all of which affect disease initiation and progression. Emerging evidence also supports their potential as disease biomarkers and therapeutic candidates for precision medicine. Finally, the review critically discusses the current challenges including discrepancies in microprotein annotation, the limitations of ribosome profiling and proteogenomic approaches, the gap between computationally predicted and experimentally validated microproteins, and the need for rigorous orthogonal validation by means of CRISPR-based genome editing, ribosome release assays, mutational analysis, high-resolution mass spectrometry, and functional studies. Finally, we review recent development of AI-assisted ORF prediction, single-cell translatomics, spatial proteomics, and integrated multi-omics as emerging technologies reshaping. Microprotein discovery and functional annotation. Finally, we discuss the translational potential of microproteins and highlight the remaining challenges to clinical application, including peptide stability, pharmacokinetics, tissue-specific delivery, immunogenicity, and the need for rigorous preclinical and clinical validation. Together, this review provides an updated and critical overview of the rapidly evolving microprotein field and highlights future research priorities for translating these molecules into clinically useful biomarkers and precision therapeutics.

Microproteins↗

PubMed2026

Retrosigmoid craniotomy surgical guide: The way forward for precise exposure of the transverse-sigmoid sinuses.

INTRODUCTION: The retrosigmoid craniotomy is the workhorse approach to the cerebellopontine angle. Accurate localisation of the transverse-sigmoid junction (TSJ) is key for optimised exposure and cerebellar retraction. Various methods, both anatomical and navigational, have been used but with suboptimal results. We utilised a 3D-printed retrosigmoid surgical guide in an attempt to overcome this and report our early outcomes and experiences in the design, production and utilisation of the guide. METHODS: This is a prospective cohort study of the patients with retrosigmoid craniotomies performed using the surgical guides. Patient demographics and diagnoses, along with the accuracy of the planned burrhole and craniotomy, need for craniotomy extension, presence of venous sinus injury, set-up time, and cost were reported. RESULTS: There were ten cerebellopontine angle cases in which the surgical guides were utilised, three petrous meningiomas, two trigeminal neuralgias, two metastasis, and three other tumours. The planned burrhole and craniotomy were precise in all cases with accurate exposure of the TSJ and no requirement for craniotomy extension. The mean set up time was 3.9 min, and the mean cost of the surgical guides was USD 470.90. One elderly patient had an intraoperative transverse sinus injury related to adherent dura that was planned for exposure. CONCLUSION: The 3D-printed surgical guide is a potential solution to the rapid, precise and consistent identification of the TSJ when performing a retrosigmoid craniotomy. We present our early experience and discuss nuances in the designing, production, and intraoperative phases to optimise the precision of this guide. We suggest two methods to avoid sinus injury in elderly patients: either to plan the craniotomy to the edge of the sinus, or to plan sinus exposure but to use burr drills rather than the osteotome, as in our case, to expose the sinus.

Humans↗

PubMed2026

Engineered MXene-based nanozyme platform: NIR-II photothermal and dual enzyme-mimetic potentiated chemodynamic synergy for precision tumor eradication.

The antioxidant defense barrier in the tumor microenvironment, particularly glutathione (GSH), considerably restricts the therapeutic efficacy of chemodynamic therapy (CDT). Moreover, CDT generally exhibits relatively mild therapeutic efficacy owing to its intrinsic reaction kinetics, making it difficult to achieve complete tumor eradication within a short time. To address these issues, we construct a functionalized nanotherapeutic platform, Nb2CTx@Ru-PEG2000-FA (NCRPF), for tumor photothermal ablation and enhanced CDT resulting from GSH depletion. NCRPF possesses three key advantages: 1. Efficient near-infrared II photothermal conversion (η = 42.08%), raising the tumor temperature above 45 °C within 90 s for rapid ablation; 2. Dual peroxidase-like and glutathione peroxidase-like activities, simultaneously depleting GSH and generating a burst of ·OH to eliminate residual tumors; 3. Targeted tumor accumulation with 2.9-fold higher efficiency than passive diffusion. Both in vitro and in vivo results confirm that this combined strategy achieves complete tumor eradication with favorable biosafety. Collectively, the NCRPF nanotherapeutic system provides a powerful new paradigm with high translational potential for the complete eradication of breast cancer.

Animals↗

PubMed2026

Machine learning vs. traditional methods for predicting postoperative cardiac complications after non-cardiac surgery: a systematic review and Bayesian network meta-analysis.

INTRODUCTION: Accurate prediction of peri-operative cardiac complications is critical to optimise pre-operative decision-making. Traditional risk prediction scores, such as the Revised Cardiac Risk Index, show only modest discrimination. Machine learning can model complex, non-linear relationships but their predictive performance compared with traditional scores remains unclear. METHODS: We performed a systematic review and Bayesian network meta-analysis. The primary outcome was postoperative adverse cardiac events following non-cardiac surgery. Prediction models were assessed relative to the Revised Cardiac Risk Index. As many studies evaluated multiple versions of each model type, the highest performing ('best version') and lowest performing ('worst version') results were analysed. Models were ranked using the surface under the cumulative ranking curve (SUCRA). RESULTS: Thirteen studies evaluating 54 models and 927,113 patients were included. Machine learning approaches generally outperformed traditional risk scores. Automated machine learning ranked highest (SUCRA 96.6) showed the greatest improvement in the best version analysis (mean difference (MD) 0.28 (95%CrI 0.16-0.40)) and remained superior in the sensitivity analysis (MD 0.30 (95%CrI 0.14-0.45)). Gradient boosting models showed superior performance over the Revised Cardiac Risk Index across analysis (best version: MD 0.20 (95%CrI 0.14-0.26), worst version: MD 0.18 (95%CrI 0.12-0.25), SUCRA 82.4). The Gupta Perioperative Risk for Myocardial Infarction or Cardiac Arrest score outperformed the Revised Cardiac Risk Index in the best version analysis (MD 0.16 (95%CrI 0.01-0.32)). Between-study heterogeneity was low. None of the included studies externally validated their machine learning models and only six were judged to be at low risk of bias. DISCUSSION: Most machine learning models showed better discrimination than traditional risk scores, with automated machine learning and gradient boosting models ranking highest. However, study quality, calibration reporting and absence of external validation limit immediate clinical adoption. Prospective, multicentre evaluation is required before integration of these models into peri-operative practice.

Humans↗

PubMed2026

A Multi-omics Regulated Cell Death Framework Defines Immune Phenotypes and Guides Precision Therapy in Colorectal Cancer.

Colorectal cancer (CRC) is molecularly and immunologically heterogeneous, contributing to variable treatment response. Because regulated cell death (RCD) intersects with tumor metabolism, immune regulation, and therapeutic susceptibility, we built an RCD-centered framework for CRC stratification. Multi-cohort transcriptomic data were used to infer RCD subtypes with non-negative matrix factorization (NMF) and non-negative least squares (NNLS). Genomic, bulk RNA-seq, single-cell RNA-seq, and spatial transcriptomic datasets were integrated to characterize subtype-associated biology. Machine-learning models were developed for immunotherapy response and survival-risk estimation. Candidate compounds were screened by GDSC2-based drug-sensitivity modeling and molecular docking, and FSTL3 was functionally assessed in vitro. The framework separated CRC samples into two RCD-related phenotypes resembling immune-hot and immune-cold states. RCD1 showed immune activation and higher mutational burden, whereas RCD2 showed immune-suppressed features, intratumoral heterogeneity, and aggressive biology. RCD-associated signatures showed potential for predicting immunotherapy response and survival risk. Dasatinib was prioritized for immune-cold, high-risk tumors, with preliminary evidence supporting its activity in CRC cells, while functional assays suggested a role for FSTL3 in growth, invasion, epithelial-mesenchymal transition, and apoptosis regulation. These findings suggest that RCD-based multi-omics analysis may refine CRC stratification and help generate therapeutic hypotheses.

Colorectal cancer↗

PubMed2026

Efficient homologous replacement and deletion of large genomic fragments through template-jumping prime editing in rice.

Homologous replacement of genomic sequences with large DNA fragments (> 100 bp) holds great potential for crop breeding, yet an efficient method to achieve such edits is lacking in plants. Here, in rice, we developed template-jumping prime editing (TJ-PE), a recently reported PE strategy for large targeted insertion, as an efficient tool for homologous replacement with DNA fragments ranging from dozens to hundreds of base pairs, and using TJ-PE, we replaced genomic fragments of up to 340 bp with homologous fragments of the same length. In addition, our TJ-PE tool also enabled precise deletion of 944- to 2024-bp fragments in rice, with efficiencies of up to 34.6% for c. 2000-bp precise deletions. Collectively, this study expands the editing scope of PE in rice and establishes TJ-PE as a generalist tool for precise deletion and replacement of large DNA fragments.

Oryza↗

PubMed2026

Metagenome-scale modeling to assess microbiome metabolic complementarity for precision microbiota transplantation therapies.

Fecal microbiota transplantation (FMT) holds therapeutic promise beyond recurrent Clostridioides difficile infection, but clinical outcomes remain unpredictable and donor-selection strategies remain limited, in part because the role of donor‒recipient metabolic interactions in shaping the post-FMT community remains poorly understood. Here, we leverage metagenome-scale metabolic modeling to quantify metabolic niche complementarity between donor and recipient microbiomes and predict post-FMT community composition. Using MICOM-derived metabolic models, we show that donor genomes whose metabolic flux profiles are more dissimilar from the recipient community colonize at significantly higher rates in a murine FMT model. In a human IBS trial, the same metric predicted post-FMT community composition via leave-one-out cross-validation and captured known disease-associated alterations in short-chain fatty acid, sulfur, and gas metabolism. We then performed 2,548 in silico FMT simulations between IBS-D/M patients and donors from the OpenBiome biobank to evaluate personalized donor screening, identifying super-donors characterized by high taxonomic diversity, broad metabolic niche coverage, and community interaction networks dominated by cross-feeding rather than competition. Together, these results support metabolic niche complementarity as a potential determinant of post-FMT community composition and provide a mechanistic basis for evaluating donor-recipient metabolic compatibility. This framework offers a scalable approach for generating testable hypotheses for personalized donor selection.

Fecal Microbiota Transplantation↗

PubMed2026

Comparative Effectiveness of Pharmacogenomics for Treatment of Depression.

PURPOSE/BACKGROUND: Pharmacogenomics (PGx), or the use of genetic information to assess drug-gene interactions, is an important step toward precision medicine. It is unclear if clinician use of PGx yields better outcomes for their patients. This study compared the effectiveness of combinatorial PGx-guided plus guideline-informed treatment (PGx+GIT) with guideline-informed treatment (GIT) alone to improve well-being in individuals with major depressive disorder. METHODS/PROCEDURES: Eligible participants (N=201) were randomized to PGx+GIT or GIT alone. PGx was measured with the proprietary GeneSight combinatorial test. PGx+GIT participant clinicians received test results within 2 business days to inform decisions about medication changes. Participants completed the World Health Organization Well-Being Index (WHO-5), Patient Health Questionnaire (PHQ-9), and PROMIS Profile physical functioning and social roles and activity domains every 2 weeks for 2 months and then every 2 months for the remaining 10 months. Monthly medication changes operationalized as necessary clinical adjustments were tracked with the medication recommendation tracking form. FINDINGS/RESULTS: Both groups improved average well-being over the 12-month study period (model-based change in WHO-5 per log (week) [95% CI]: 4.1 [3.3, 5.0] PGx+GIT and 4.8 [4.0, 5.5] GIT). PGx+GIT did not result in superior improvement in well-being (model-based difference [95% CI]: -0.6 [-1.8, 0.5], P =0.270), or any secondary outcomes. The effect of randomized treatment on well-being was not moderated by depression severity, number of previous failed medications for major depressive disorder, or presence of a comorbid condition. IMPLICATIONS/CONCLUSIONS: These data suggest PGx+GIT was not superior to GIT alone, possibly due to a ceiling effect of GIT, or PGx did not yield better results.

Humans↗

PubMed2026

Construction of precision clinical-proteomics risk model based on machine learning for predicting heart failure in type II diabetes mellitus.

BACKGROUND AND AIMS: Heart failure (HF) is a severe complication in type 2 diabetes mellitus (T2DM), but current risk stratification scores have limited predictive accuracy. We aimed to develop novel prediction tools integrating clinical variables with proteomics to improve risk stratification of hospitalization for HF in T2DM. METHODS AND RESULTS: In this study, we included 2111 UK Biobank participants with T2DM but no prior HF, and profiled 2920 proteins to predict 10-year incident HF hospitalization. Participants were randomly divided into training (70%), tuning (10%), and validation (20%) sets.Three prediction models were developed: a Clinical model based on demographic characteristics, comorbidities, medication use, and laboratory indices; a Protein model based on 40 proteins selected by the Light Gradient Boosting Machine (LGBM); and the Clinical OMics and Protein ASSessment for Heart Failure (COMPASS-HF) model, which integrated both clinical variables and the LGBM-selected proteins. Models were evaluated for area under the curve (AUC), sensitivity, and specificity. During follow-up, 168 participants (7.96%) developed incident HF. The COMPASS-HF model showed better discrimination than the Clinical model, with an AUC of 0.897 (95% CI: 0.850-0.945) versus 0.790 (95% CI: 0.723-0.856). It also demonstrated higher sensitivity (0.882; 95% CI: 0.725-0.967) and consistent performance in subgroups. COMPASS-HF effectively stratified risk of hospitalization for HF, with cumulative incidence rates of 31.9% in the high-risk group and 1.2% in the low-risk group. CONCLUSIONS: By combining clinical and proteomic variables, we developed a high-performance HF prediction model for T2DM, enabling precise risk stratification and informing early intervention strategies.

Humans↗

PubMed2026

Manual, digital, and AI tumour-infiltrating lymphocyte scoring: a secondary analysis of the APHINITY randomised trial.

BACKGROUND: Stromal tumour-infiltrating lymphocytes (sTILs) are prognostic in early-stage HER2-positive breast cancer, but their role in the context of dual HER2 blockade remains undefined. We evaluated manual, digital, and artificial intelligence (AI)-based sTIL quantification, together with AI-derived spatial metrics, for prognostic and treatment-benefit stratification using tumour samples from the phase 3 APHINITY trial. METHODS: In the APHINITY trial, 4805 patients were randomly assigned to receive chemotherapy plus trastuzumab with pertuzumab or chemotherapy plus trastuzumab with placebo. Median follow-up was 74·1 months (IQR 68·3-75·4). We analysed 4262 haematoxylin and eosin-stained images using manual assessment, an automated digital approach, AI-based lymphocyte quantification (AI percentage lymphocytes), and two AI-derived spatial features (AI-TIL and immune hotspot). Interobserver reproducibility was assessed in 262 randomly chosen tumour samples scored independently by five pathologists. Multivariable Cox models were used to assess associations between TIL levels and invasive disease-free survival (primary outcome in APHINITY), distant recurrence-free interval, and overall survival. The heterogeneity of pertuzumab benefit was evaluated using subgroup analyses, subpopulation treatment effect pattern plot analyses, and nested Cox models with treatment-by-biomarker interaction terms. FINDINGS: Manual scoring showed high interobserver reproducibility (intraclass correlation coefficient 0·84 [95% CI 0·79-0·88]). Concordance between manual and automated methods was modest. AI-based scoring (AI percentage lymphocytes) reclassified 120 (11·6%) of 1035 node-positive tumours from immune-low (by manual scoring) to immune-high; this subgroup of patients showed greater separation of 5-year invasive disease-free survival curves between pertuzumab and placebo groups compared with patients whose tumours were concordantly classified as immune-low by both manual and AI-based approaches. Higher levels of TILs were associated with improved invasive disease-free survival for all sTIL measurement approaches and spatial measurements (hazard ratios [HRs] 0·41-0·93). Pertuzumab was associated with improved invasive disease-free survival at higher sTIL levels across all measurement approaches (HRs 0·36-0·48), but was not associated with higher values of spatial measures. The largest 6-year absolute improvements with pertuzumab were observed in patients with node-positive disease whose tumours scored in the highest level of immune infiltration of manual sTIL scoring (≥70·0%; mean absolute improvement 12·1 percentage points [SD 2·8]). In nested prognostic and predictive models, AI-based immune hotspot scores provided the most consistent additional information when combined with any sTIL measurement (all p<0·010). INTERPRETATION: Standardised manual sTIL scoring was reproducible, and digital and AI-based methods showed consistent prognostic stratification and potential for treatment-benefit stratification despite only modest correlation between platforms. AI spatial metrics provided complementary information beyond sTIL density and could support more scalable immune assessment. Future studies are needed to validate these approaches in independent cohorts and to clarify their clinical utility for stratifying contemporary HER2-directed therapies. FUNDING: None.

Humans↗

PubMed2026

Exploring precision risk in pediatric vesicoureteral reflux: Innate immune gene variations and reflux outcomes in the RIVUR cohort.

INTRODUCTION: Children with vesicoureteral reflux (VUR) are at increased risk for morbidity from recurrent urinary tract infections (UTIs), yet the factors influencing spontaneous VUR resolution remain poorly defined. This study evaluates whether genetic variations in key urinary innate immune effectors (DEFA1A3, DMBT1, and RNASE7) influences VUR resolution and interacts with prophylaxis to alter clinical response. METHODS: We conducted a secondary analysis of 303 RIVUR participants with available DEFA1A3 and DMBT1 copy number variation (CNV) data and RNASE7 rs1263872 genotype. Primary outcomes were (1) VUR improvement (decrease in grade) and (2) VUR resolution at study exit. Multivariable logistic regression models included genotype, treatment, and their interactions, adjusting for age, sex, baseline grade (high vs low), laterality, bowel/bladder dysfunction, and any UTI. Internal validation used 2000-sample bootstrap with bias-corrected and accelerated confidence intervals and influence diagnostics. RESULTS: Clinical covariates did not significantly predict VUR improvement. Children with DEFA1A3 CNV >5 had higher odds of improvement (OR 2.36, 95% CI 1.12-4.96, p = 0.023), an effect that remained significant in bootstrap analyses. High-grade VUR was associated with lower odds of resolution (OR 0.34, 95% CI 0.12-0.94, p = 0.038). A significant interaction was observed between prophylaxis and high DMBT1 copy number for VUR resolution (interaction OR 2.99, 95% CI 1.11-8.04, p = 0.031); no interaction was seen for improvement. RNASE7 rs1263872 was not associated with either outcome. CONCLUSION: Innate immune gene variation may contribute to heterogeneity in VUR outcomes. High DEFA1A3 copy number was associated with reflux improvement and a DMBT1-prophylaxis interaction was associated with reflux resolution. The results of this study is hypothesis-generating and prompt further evaluation to assess whether a subset of children may experience structural benefit from prophylaxis or have a more favorable natural history based on their innate immune genotype.

Humans↗

PubMed2026

Multi-omic biomarkers in cardiovascular disease: Discovery to clinical translation.

Cardiovascular disease (CVD) remains the leading cause of mortality worldwide, necessitating improved risk stratification and early detection strategies. Multiomics approaches that integrate genomics, transcriptomics, proteomics, metabolomics, and epigenomics offer unprecedented opportunities for biomarker discovery and precision medicine in cardiovascular care. This narrative review examines the current landscape of multiomics biomarkers for CVD, tracing their evolution from discovery to clinical translation. We synthesize evidence from recent studies evaluating the clinical utility of integrated omics approaches across diverse cardiovascular conditions, including atherosclerotic cardiovascular disease, heart failure, and atrial fibrillation. High-throughput proteomics has identified novel protein signatures that enhance cardiovascular risk prediction beyond traditional risk factors. Metabolomics has revealed pathway-specific biomarkers, including trimethylamine N-oxide and lipid species, associated with atherogenesis. Polygenic risk scores derived from genomic data demonstrate incremental value when combined with clinical risk scores. Multiomics biomarkers represent a transformative approach to cardiovascular risk assessment and disease management.

Humans↗