Biology subjects

Nguyen, V. A.

Publications and source records attributed to Nguyen, V. A..

5 recordsLinked to original sources

bioRxiv2026

Development and cross-cohort evaluation of a multimodal deep-learning model for ER, PR and HER2 status classification in breast cancer

Background. Estrogen receptor (ER), progesterone receptor (PR) and HER2 status guide systemic treatment in breast cancer. Multimodal models are rarely benchmarked against key biomarker molecular baselines or evaluated for cross-cohort calibration. We assessed incremental value, dependence on label-proximal HER2 transcripts, and transport of discrimination and calibration. Methods. A model combining whole-slide images, transcriptomes, age and stage was developed in TCGA-BRCA (1051 patients; ER/PR/HER2 analysis sets: 1001/998/1006) and evaluated in CPTAC-BRCA (120 patients; 118/113/95). CPTAC had been observed during earlier development and included 13 HER2-positive cases. Analyses included paired model comparisons, transcript removal, alternative loss functions and recalibration. Internal discrimination used pooled out-of-fold predictions; external discrimination used fold-mean estimates, with ensemble calibration reported separately. Internal calibration and macro-AUC uncertainty were interpreted as exploratory. Results. Internal AUCs were 0.943 for ER, 0.901 for PR, and 0.860 for HER2; external AUCs were 0.952, 0.937, and 0.918, respectively. External macro-AUC was 0.936 for the multimodal model and 0.957 for logistic regression using ESR1, PGR, and ERBB2 (difference -0.021). Removal of the extended 29-transcript 17q12-q21 region changed HER2 AUC by -0.035 [-0.058 to -0.013] (95% CI) internally and by -0.042 [-0.089 to -0.007] externally relative to the baseline multimodal model. For external 15-model ensemble predictions, recalibrated HER2 expected calibration error (ECE) was 0.236, exceeding the ECE reference ceiling of 0.125, while calibration-in-the-large was -1.657 [-2.373 to -1.023] (profile-likelihood 95% CI), indicating systematic overprediction. ER and PR also showed overprediction. In paired fold-mean comparisons, HER2 ECE and Brier score favoured the three-transcript model (ESR1, PGR, and ERBB2). Conclusions. A multimodal deep-learning model achieved high discrimination across cohorts but did not demonstrate clear incremental value over a parsimonious three-transcript baseline, while cross-cohort calibration remained a substantial challenge. These findings highlight the importance of evaluating incremental value, calibration, and clinical utility alongside discrimination when assessing AI-based prediction models for medical use.

bioinformatics↗

bioRxiv2026

Histomonas meleagridis infection and vaccination protection in chickens -- a metabolomics study

Histomonosis, caused by Histomonas meleagridis, is a severe disease in poultry with main pathological lesions in ceca and liver, leading to significant animal suffering and economic losses, with no licensed treatments available. While cecal pathology and microbiota disruption have been documented, the metabolic consequences of infection and vaccination remain poorly understood. Here, we used untargeted LC-MS metabolomics to profile cecal tissue and luminal digesta in a controlled vaccination-challenge chicken trial (n=100, 25 birds/group), including uninfected and unvaccinated but challenged controls, together with birds vaccinated either cloacally, or orally via an edible gel following challenge, across five post-challenge timepoints. Results showed that H. meleagridis infection caused extensive, time-dependent disruption of the cecal metabolome, especially at 7-14 days post-infection (DPI). At DPI 14, 325 tissue and 359 digesta metabolites were significantly altered in unvaccinated challenged birds. Infection was associated with depletion of microbiota-related metabolites, including dicarboxylic acids, tryptophan indoles, phytochemical derivatives, bilirubin catabolites, phenolics, vitamins, and secondary bile acids, alongside accumulation of microbial substrates and fermentation products. Changes in the host-associated metabolites indicated mucosal inflammation, epithelial injury, mitochondrial and amino acid metabolic disturbance, oxidative stress, and membrane lipid remodeling. Cloacal vaccination provided greater metabolic protection than oral vaccination, with 78.3% of disrupted metabolites preserved at DPI 14, compared with 60.7% vaccination by oral gel delivery, pointing towards the importance of vaccine take. By DPI 21, cloacally vaccinated birds showed nearly complete metabolic recovery across most pathway groups, whereas gel-vaccinated birds retained broader metabolic disturbance. These findings reveal histomonosis as a disruption of the cecal host-microbiota metabolic interface and provide a metabolite-level framework for future studies of pathogenesis, vaccine development, and prevention strategies.

pharmacology and toxicology↗

bioRxiv2022

Modelling the spread and mitigation of an emerging vector-borne pathogen:citrus greening in the U.S.

Predictive models, based upon epidemiological principles and fitted to surveillance data, play an increasingly important role in shaping regulatory and operational policies for emerging outbreaks. Data for parameterising these strategically important models are often scarce when rapid actions are required to change the course of an epidemic invading a new region. We provide a flexible toolkit for landscape-scale disease management, which is applicable to a range of emerging pathogens including vector-borne pathogens for both endemic and invading epidemic vectors. We use the toolkit to analyse and predict the spread of Huanglongbing disease or citrus greening in the U.S. We estimate epidemiological parameters using survey data from one region (Texas) and show how to transfer and test parameters to construct predictive spatio-temporal models for another region (California). The models are used to screen effective coordinated and reactive management strategies for different regions.

ecology↗

bioRxiv2021

Visual Processing During the Interictal Period Between Migraines: A Meta-Analysis

Migraine is a poorly understood neurological disorder and a leading cause of disability in young adults. Migraines are characterized by severe pulsating unilateral headache and visual symptoms. Whether visual function is also impaired in the interictal period between migraines remains controversial. Thus, this meta-analysis investigated the evidence for altered visual function as measured electrophysiologically via pattern-reversal visual evoked potential (VEP) amplitudes and habituation in adult migraineurs with or without visual aura and control in the interictal period. Twenty-three studies were selected for random effects meta-analysis, demonstrating slightly diminished VEP amplitudes and substantially reduced habituation in the early P100 component in migraineurs without aura and with aura compared to controls. No differences were found between migraineurs with and without aura. Although heterogeneity between studies and insufficient published data for VEP latencies and the earlier N75 VEP component data was observed and require further testing, P100 anomalies may indicate abnormal functioning of the fast-conducting magnocellular visual pathway, in episodic migraineurs.

neuroscience↗

bioRxiv2021

PRE-CLINICAL IMMUNE RESPONSE AND SAFETY EVALUATION OF THE PROTEIN SUBUNIT VACCINE NANOCOVAX FOR COVID-19

The Coronavirus disease-2019 (COVID-19) pandemic caused by the Severe Acute Respiratory Syndrome coronavirus 2 (SARS-CoV-2), has become a dire global health concern. The development of vaccines with high immunogenicity and safety is crucial for control of the global COVID-19 pandemic and prevention of further illness and fatalities. Here, we report development of SARS-CoV-2 vaccine candidate, Nanocovax, based on recombinant protein production of the extracellular (soluble) portion of the S protein of SARS-CoV-2. The results showed that Nanocovax induced high levels of S protein-specific IgG, as well neutralizing antibody in three animal models including Balb/C mice, Syrian hamsters, and non-human primate (Macaca leonina). In addition, the viral challenge study using the hamster model showed that Nanocovax protected the upper respiratory tract from SARS-CoV-2 infection. No adverse effects were induced by Nanocovax in swiss mice (Musmusculus var. Albino), Rats (Rattus norvegicus), and New Zealand rabbits. These pre-clinical results indicated that Nanocovax is safe and effective.

immunology↗