clinical cohort / trial

This paper introduces Mendelnoulli, a longitudinal model that captures age-dependent effects of inherited variation on disease trajectories, showing improved discrimination and identification of disease risks.

This study uses polygenic scores to identify pleiotropic effects of psychiatric dimensions across medical and laboratory phenotypes, revealing biological links between mental health and physical conditions.

This study identifies CETP activity and early SAA levels as prognostic biomarkers in sepsis-associated ARDS, showing they predict improved survival and reduced disease severity.

This study integrates clinical and T-cell immune profiling to identify early biomarkers of response to CD3xBCMA bispecific antibody therapy in multiple myeloma.

This paper develops a multi-omics machine learning model to predict breast cancer survival, finding that epigenetic features are the strongest predictors.

The paper identifies DPP9 as a genetic susceptibility gene for checkpoint inhibitor pneumonitis and shows IL-18 blockade could be a therapeutic strategy.

The paper shows that Peyer's patch LysoDCs generate microbiota-specific Th17 responses distinct from those in mesenteric lymph nodes, with functional consequences for mucosal immunity.

This study compares phantomless and inline phantom-based densitometric calibration of vertebral properties from CT scans, finding a strong correlation between the two methods using air and aorta as calibration regions.

This study characterizes a leptospirosis outbreak in dogs in Los Angeles County, finding that all isolates were Leptospira interrogans serovar Canicola, with urine PCR as the most sensitive test and ICFs as a potential source.

This study shows HS3ST1 deficiency worsens lung injury and increases mortality after trauma and hemorrhagic shock, particularly with fresh frozen plasma resuscitation.

This study examines how type 2 diabetes affects prostate cancer progression, finding associations with advanced tumor stage, lymph node involvement, and altered tumor cell dissemination and vascular characteristics.

This paper develops a hybrid PINN-DE framework for parameter estimation in tumor-immune dynamics of bladder cancer, showing improved accuracy and efficiency compared to individual methods.

The paper identifies anti-CE1 antibodies that reduce HCC incidence and mortality by mediating NK cell ADCC against ASPH-expressing tumor cells through epitope mimicry.

WildAlert detects wildlife health anomalies using AI and real-time clinical data, identifying events like HPAI and algal blooms before confirmed outbreaks.

This study identifies metabolic factors associated with disease activity and complications in Crohn's disease using regression analysis and predictive models.

This study compares vibriosis incidence and causative species between equatorial Singapore and temperate United States, finding higher incidence in Singapore with stable rates, while US rates are rising, suggesting ecological impacts of warming oceans.

This study identifies IL-17 and COX2 as negative regulators of protective immunity in tuberculosis, showing that Ly6G+ granulocytes are a major source of IL-17 and their inhibition reduces bacterial burden and pathology.

The paper examines the cross-sectional association between dietary supplements and anti-HAV antibodies using NHANES data, finding no significant association overall but a significant positive link with vitamin D.

The paper introduces an adaptive feature-weighted stacking ensemble model for predicting prolonged length of stay in elderly trauma patients, showing improved predictive accuracy over standard methods.

The paper presents a harmonized nonhuman cancer database with tumors from 41,539 individuals across 825 species, revealing tissue-specific cancer incidence patterns.

The paper applies mathematical tumor growth models to clinical data to estimate growth rates and assess treatment response, finding strong correlations between growth rates and overall survival.

This paper introduces SpaMIL, a spatial transcriptomics-based multiple instance learning framework for patient-level outcome prediction in glioblastoma, achieving high prognostic accuracy.

This study compares antioxidant enzyme activity and lipid peroxidation levels between type 2 diabetes patients with good and poor glycemic control and healthy controls in Cameroon.

This study shows that activating RET mutations in medullary thyroid cancer (MTC) cells promote osteoblastic bone metastases by increasing osteoprotegerin (OPG), which inhibits bone resorption and is linked to poor patient survival.

The paper describes the Hope for Others rapid autopsy program for metastatic breast cancer, detailing its protocols, sample collection, and findings on metastasis research and model development.

This paper introduces CereBRLSIM, a digital twin that predicts cerebral blood flow and CVR mechanisms in neurocritical care patients with higher accuracy than machine learning models.

The paper identifies novel subgroups in myeloid malignancies using a network-based clustering approach that integrates genomic and clinical features, improving prognostic accuracy.

This paper develops a multimodal transformer model using H&E images and text reports to predict recurrence scores in hormone receptor-positive breast cancer, achieving high accuracy and generalizability.

This study examines the association between dietary vitamin B1 intake and endometriosis risk using NHANES 2003-2006 data, finding a significant protective effect at higher intakes.

This study identifies clinical, genetic, and spatial factors affecting glioblastoma multiforme survival using retrospective patient data.