Clinical validation of a ctDNA-Based Assay for Multi-Cancer Detection: An Interim Report from a Vietnamese Longitudinal Prospective Cohort Study of 2795 Participants.

The SPOT-MAS assay "Screening for the Presence Of Tumor by Methylation And Size" detects the five most common cancers in Vietnam by evaluating circulating tumor DNA in the blood. Here, we validated its performance in a prospective multi-center clinical trial, K-DETEK. Our analysis of 2795 participants from 14 sites across Vietnam demonstrates its ability to detect cancers in asymptomatic individuals with a positive predictive value of 60%, with 83.3% accuracy in detecting tumor location. We present a case report to support further using SPOT-MAS as a complementary method to achieve early cancer detection and provide the opportunity for early treatment.

Epidemiological Characteristics of Advanced Hepatocellular Carcinoma in the Northern Region of Vietnam.

Epidemiological characteristics of hepatocellular carcinoma (HCC) in Southern Vietnam has been well reported as in Globocan 2018 while data from the North has still not been fully presented. Therefore, we conducted this retrospective descriptive study on 198 advanced HCC patients treated at 3 major hospitals in Northern Vietnam to describe demographic features, HCC risk factors, and correlation among them in patients with advanced HCC. This information will lead to prevention efforts and provide information for allocating funds for treatment. The median age at diagnosis was 57 years (range: 19-86) and the male/female ratio was 8.9/1. The proportions of hepatitis B virus (HBV) and hepatitis C virus (HCV) infection were 81.3% and 5.6%, respectively. Hepatitis C virus infection rate was significantly higher in patients <50 years old (12.5% vs 3.3%, P = .016). There was no significant difference in age or viral hepatitis infection status by gender. Only 7.6% of patients diagnosed with advanced HCC were asymptomatic. In conclusion, with the high rate of HBV infection among patients with advanced HCC, it is necessary for increasing prevention efforts in HBV screening. Furthermore, HCV infection should be noticed in patients with advanced HCC younger than 50 years old.

Tomato Fruit Detection Using Modified Yolov5m Model with Convolutional Neural Networks.

The farming industry is facing the major challenge of intensive and inefficient harvesting labors. Thus, an efficient and automated fruit harvesting system is required. In this study, three object classification models based on Yolov5m integrated with BoTNet, ShuffleNet, and GhostNet convolutional neural networks (CNNs), respectively, are proposed for the automatic detection of tomato fruit. The various models were trained using 1508 normalized images containing three classes of cherry tomatoes, namely ripe, immature, and damaged. The detection accuracy for the three classes was found to be 94%, 95%, and 96%, respectively, for the modified Yolov5m + BoTNet model. The model thus appeared to provide a promising basis for the further development of automated harvesting systems for tomato fruit.

Classification of Tomato Fruit Using Yolov5 and Convolutional Neural Network Models.

Four deep learning frameworks consisting of Yolov5m and Yolov5m combined with ResNet50, ResNet-101, and EfficientNet-B0, respectively, are proposed for classifying tomato fruit on the vine into three categories: ripe, immature, and damaged. For a training dataset consisting of 4500 images and a training process with 200 epochs, a batch size of 128, and an image size of 224 × 224 pixels, the prediction accuracy for ripe and immature tomatoes is found to be 100% when combining Yolo5m with ResNet-101. Meanwhile, the prediction accuracy for damaged tomatoes is 94% when using Yolo5m with the Efficient-B0 model. The ResNet-50, EfficientNet-B0, Yolov5m, and ResNet-101 networks have testing accuracies of 98%, 98%, 97%, and 97%, respectively. Thus, all four frameworks have the potential for tomato fruit classification in automated tomato fruit harvesting applications in agriculture.

Comparative analysis of microRNA expression profiles in shoot and root tissues of contrasting rice cultivars (Oryza sativa L.) with different salt stress tolerance.

Rice is the second-most important primary crop in the world and one of the most susceptible crops to salt stress. Soil salinization hinders seedling growth and decreases crop yield by inducing ionic and osmotic imbalances, photosynthesis disturbances, cell wall alterations, and gene expression inhibition. Plants have developed a range of defense mechanisms to adapt to salt stress. One of the most effective means is to make use of plant microRNAs (miRNAs) as post-transcriptional regulators to regulate the expression of developmental genes in order to mitigate the detrimental effects of salt stress. In this study, the miRNA sequencing data between two contrasting rice cultivars, salt-tolerant Doc Phung (DP) and salt-sensitive IR28 seedlings, were compared under control and salt stress (150 mM NaCl) conditions to determine the salt stress-responsive miRNAs. Comparative analysis of miRNA sequencing data detected a total of 69 differentially expressed miRNAs in response to salt stress treatment. Among them, 18 miRNAs from 13 gene families, MIR156, MIR164, MIR167, MIR168, MIR171, MIR396, MIR398, MIR1432, MIR1846, MIR1857, MIR1861, MIR3979, and MIR5508, were identified to be specifically and significantly expressed in the shoot and root tissues of DP seedlings. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses further revealed that these detected miRNAs regulate a range of essential biological and stress response processes, including gene transcription, osmotic homeostasis, root formation, ROS scavenger synthesis, and auxin and abscisic acid signaling pathways. Our findings provide more insight into the miRNA-mediated responsive mechanisms of rice under salt stress and should benefit the improvement of salt stress tolerance in rice.

Draft Genome Sequence of Marinobacter sp. Strain C7 Isolated from Seawater in Con Bung Coast, Vietnam.

Marinobacter sp. strain C7 was isolated from seawater collected on the Con Bung coast, Vietnam. Here, we report a draft genome sequence of strain C7 consisting of 4,057,300 bp with 59.2% GC content and 109 contigs. The genome sequence of strain C7 provides an overview of its halophilic properties.

Characterization of a thermophilic cytochrome P450 of the CYP203A subfamily from Binh Chau hot spring in Vietnam.

Cytochromes P450 (CYPs or P450s) comprise a superfamily of heme-containing monooxygenases that are involved in a variety of biological processes. CYPs have broad utilities in industry, but most exhibit low thermostability, limiting their use on an industrial scale. Highly thermostable enzymes can be obtained from thermophiles in geothermal areas, including hot springs, offshore oil-producing wells and volcanoes. Here, we report the identification of a gene encoding for a thermophilic CYP from the Binh Chau hot spring metagenomic database, which was designated as P450-T2. The deduced amino acid sequence showed the highest identity of 73.15% with CYP203A1 of Rhodopseudomonas palustris, supporting that P450-T2 is a member of the CYP203A subfamily. Recombinant protein expression yielded 541 nm. The optimal temperature and pH of P450-T2 were 50 °C and 8.0, respectively. The half-life of P450-T2 was 50.2 min at 50 °C, and its melting temperature was 56.80 ± 0.08 °C. It was found to accept electrons from all tested redox partners systems, with BmCPR-Fdx2 being the most effective partner. Screening for putative substrates revealed binding of phenolic compounds, such as l-mimosine and emodin, suggesting a potential application of this new thermophilic P450 in the production of the corresponding hydroxylated products.