Biology subjects

Duong, T. D.

Publications and source records attributed to Duong, T. D..

3 recordsLinked to original sources

bioRxiv2026

First-Trimester Non-Invasive Prediction of Preterm Birth Using Cell-Free DNA Fragmentomics

ObjectiveTo develop and validate a cell-free DNA (cfDNA) fragmentomic classifier for the early prediction of spontaneous preterm birth (PTB) using routine first-trimester non-invasive prenatal testing (NIPT) data. MethodsA nested case-control study was conducted within a prospective multicenter Vietnamese cohort comprising 286 pregnancies, including 82 spontaneous PTB cases and 204 term controls. Maternal plasma cfDNA collected during routine first-trimester NIPT (median gestational age, 12 weeks) was sequenced to a depth of approximately 20 million reads per sample. Five fragmentomic feature categories including copy number alterations, end-motif composition, nucleosome distance, fragment length, and joint fragment-lengthxend-motif were evaluated for PTB prediction. Machine learning classifiers were developed in a training cohort (n = 228, 65 PTB vs 163TB) and tested in a validation cohort (n = 58, 17 PTB vs 41 TB). ResultsAmong the five fragmentomic feature classes evaluated, 4-mer end-motif (EM) profiles exhibited the most pronounced differences between PTB and term control samples. Consistent with these findings, the EM-based classifier demonstrated the highest discriminative performance in the validation cohort, achieving an AUC of 0.970 (95% CI, 0.912-1.000). At a specificity >90%, the model achieved a sensitivity of 94% (95% CI, 78-100%). ConclusionThese findings demonstrate that cfDNA EM signatures derived from routine first-trimester NIPT can accurately identify pregnancies at risk of spontaneous preterm birth, without additional blood collection or sequencing, thereby extending the clinical utility of existing prenatal screening infrastructure. KEY POINTSO_ST_ABSWhat is already known about this topic?C_ST_ABSO_LICurrent first-trimester prediction strategies based on maternal characteristics, cervical length, and biochemical markers have limited predictive accuracy, particularly in nulliparous women. C_LIO_LIExisting cfDNA-based approaches have shown only modest performance or require additional assays, limiting clinical applicability. C_LI What does this study add?O_LIExisting NIPT sequencing data can be repurposed (without additional blood sampling or sequencing) for accurate prediction of spontaneous preterm birth (AUC=0.970). C_LIO_LIA classifier employing 4-mer end-motif (EM) profiles achieved an AUC of 0.970. At a specificity >90%, the model achieved a sensitivity of 94%. C_LI

genomics↗

bioRxiv2021

Identifying genomic regions and candidate genes selected during the breeding of rice in Vietnam

Background and aimsVietnam harnesses a rich diversity of rice landraces adapted to a broad range of conditions, which constitute a largely untapped source of genetic diversity for the continuous improvement of rice cultivars. We previously identified a strong population structure in Vietnamese rice, which is captured in five Indica and four Japonica subpopulations, including an outlying Indica-5 group. Here, we leveraged on that strong differentiation, and the 672 rice genomes generated, to identify genes within genomic regions putatively selected during domestication and breeding of rice in Vietnam. MethodologyWe identified significant distorted patterns in allele frequency (XP-CLR method) and population differentiation scores (FST), resulting from differential selective pressures between native subpopulations, and compared them with QTLs previously identified by GWAS in the same panel. We particularly focused on the outlying Indica-5 subpopulation because of its likely novelty and differential evolution. ResultsWe identified selection signatures in each of the Vietnamese subpopulations and carried out a comprehensive annotation of the 52 regions selected in Indica-5, which represented 8.1% of the rice genome. We annotated the 4,576 genes in these regions, verified the overlap with QTLs identified in the same diversity panel and the comparison with a FST analysis between subpopulations, to select sixty-five candidate genes as promising breeding targets, several of which harboured alleles with non-synonymous substitutions. ConclusionsOur results highlight genomic differences between traditional Vietnamese landraces, which are likely the product of adaption to multiple environmental conditions and regional culinary preferences in a very diverse country. We also verified the applicability of this genome scanning approach to identify potential regions harbouring novel loci and alleles to breed a new generation of sustainable and resilient rice. Key MessageWe localised regions in the rice genome selected during breeding by comparing allele frequency patterns among Vietnamese rice subpopulations. We characterised candidate genes in the Indica-5 subpopulation with breeding potential.

plant biology↗

bioRxiv2019

Heart rate variability as an indicator of autonomic nervous system disturbance in tetanus

Autonomic nervous system dysfunction (ANSD) is a significant cause of mortality in tetanus. Currently diagnosis relies on non-specific clinical signs. Heart rate variability (HRV) may indicate underlying autonomic nervous system activity and represents a potentially valuable non-invasive tool for ANSD diagnosis in tetanus. HRV was measured from 3 5-minute ECG recordings during a 24-hour period in a cohort patients with severe tetanus, all receiving mechanical ventilation. HRV measurements from all subjects - 5 with ANSD (Ablett Grade 4) and 4 patients without ANSD (Ablett Grade 3) - showed HRV was lower than reported ranges for healthy individuals. Comparing different severities of tetanus, raw data for both time and frequency measurements of HRV were reduced in those with ANSD compared to those without. Differences were statistically significant in all except root mean square standard deviation RMSSD (p=0.07) indicating HRV may be a valuable tool in ANSD diagnosis.

pathology↗