IPseU-NCP: Identifying RNA pseudouridine sites using random forest and NCP-encoded features

© 2019 Nguyen-Vo et al. Background: Pseudouridine modification is most commonly found among various kinds of RNA modification occurred in both prokaryotes and eukaryotes. This biochemical event has been proved to occur in multiple types of RNAs, including rRNA, mRNA, tRNA, and nuclear/nucleolar RNA. Hence, gaining a holistic understanding of pseudouridine modification can contribute to the development of drug discovery and gene therapies. Although some laboratory techniques have come up with moderately good outcomes in pseudouridine identification, they are costly and required skilled work experience. We propose iPseU-NCP - an efficient computational framework to predict pseudouridine sites using the Random Forest (RF) algorithm combined with nucleotide chemical properties (NCP) generated from RNA sequences. The benchmark dataset collected from Chen et al. (2016) was used to develop iPseU-NCP and fairly compare its performances with other methods. Results: Under the same experimental settings, comparing with three state-of-the-art methods including iPseU-CNN, PseUI, and iRNA-PseU, the Matthew's correlation coefficient (MCC) of our model increased by about 20.0%, 55.0%, and 109.0% when tested on the H. sapiens (H_200) dataset and by about 6.5%, 35.0%, and 150.0% when tested on the S. cerevisiae (S_200) dataset, respectively. This significant growth in MCC is very important since it ensures the stability and performance of our model. With those two independent test datasets, our model also presented higher accuracy with a success rate boosted by 7.0%, 13.0%, and 20.0% and 2.0%, 9.5%, and 25.0% when compared to iPseU-CNN, PseUI, and iRNA-PseU, respectively. For majority of other evaluation metrics, iPseU-NCP demonstrated superior performance as well. Conclusions: iPseU-NCP combining the RF and NPC-encoded features showed better performances than other existing state-of-the-art methods in the identification of pseudouridine sites. This also shows an optimistic view in addressing biological issues related to human diseases

Predicting Drug-Induced Liver Injury using Convolutional Neural Network and Molecular Fingerprint-embedded features

© 2020 American Chemical Society. As a critical issue in drug development and postmarketing safety surveillance, drug-induced liver injury (DILI) leads to failures in clinical trials as well as retractions of on-market approved drugs. Therefore, it is important to identify DILI compounds in the early-stages through in silico and in vivo studies. It is difficult using conventional safety testing methods, since the predictive power of most of the existing frameworks is insufficiently effective to address this pharmacological issue. In our study, we employ a natural language processing (NLP) inspired computational framework using convolutional neural networks and molecular fingerprint-embedded features. Our development set and independent test set have 1597 and 322 compounds, respectively. These samples were collected from previous studies and matched with established chemical databases for structural validity. Our study comes up with an average accuracy of 0.89, Matthews's correlation coefficient (MCC) of 0.80, and an AUC of 0.96. Our results show a significant improvement in the AUC values compared to the recent best model with a boost of 6.67%, from 0.90 to 0.96. Also, based on our findings, molecular fingerprint-embedded featurizer is an effective molecular representation for future biological and biochemical studies besides the application of classic molecular fingerprints

Predicting Drug-Induced Liver Injury Using Convolutional Neural Network and Molecular Fingerprint-Embedded Features

© 2020 American Chemical Society. As a critical issue in drug development and postmarketing safety surveillance, drug-induced liver injury (DILI) leads to failures in clinical trials as well as retractions of on-market approved drugs. Therefore, it is important to identify DILI compounds in the early-stages through in silico and in vivo studies. It is difficult using conventional safety testing methods, since the predictive power of most of the existing frameworks is insufficiently effective to address this pharmacological issue. In our study, we employ a natural language processing (NLP) inspired computational framework using convolutional neural networks and molecular fingerprint-embedded features. Our development set and independent test set have 1597 and 322 compounds, respectively. These samples were collected from previous studies and matched with established chemical databases for structural validity. Our study comes up with an average accuracy of 0.89, Matthews's correlation coefficient (MCC) of 0.80, and an AUC of 0.96. Our results show a significant improvement in the AUC values compared to the recent best model with a boost of 6.67%, from 0.90 to 0.96. Also, based on our findings, molecular fingerprint-embedded featurizer is an effective molecular representation for future biological and biochemical studies besides the application of classic molecular fingerprints

Dengue in Adults Admitted to a Referral Hospital in Hanoi, Vietnam

Knowledge of adult dengue virus (DENV) infection from Hanoi, Vietnam, is limited. In 2008, we prospectively studied 143 (77 male) confirmed (nonstructural 1 antigen enzyme-linked immunosorbent assay [ELISA], DENV polymerase chain reaction, paired serology) adult dengue patients of median age 23.5 (range 16-72) years. They were admitted to the National Hospital for Tropical Diseases, Hanoi, on median illness day (D) 5 (range 1-8). By D8, 141 (98.6%) were afebrile. Platelet counts and hematocrit (median, interquartile range [IQR]) nadired and peaked on D5 and D4, respectively: 40,000/μL (10,000-109,000/μL), 43.4% (34.9-49.7%). Four (2.8%) patients had severe dengue: 1) D10 shock (N = 1) and 2) aspartate aminotransferase (AST) ≥ 1,000 IU/L (N = 3, D5 and D7). Of 143 patients, 118 (82.5%) had ≥ 1 warning sign (World Health Organization [WHO] 2009 criteria): mucosal bleeding 66/143 (46.1%), soft tissue edema 54/143 (37.7%), and ultrasound detected plasma leakage (pleural effusions/ascites) 30/129 (23.25%). 138 (96.5%) patients received intravenous (IV) fluids: 3 L (IQR: 0.5-8.5 L). Most patients had non-severe dengue with warning signs. High rates of edema and plasma leakage may be explained partly by liberal use of IV fluids. Studies are needed on optimizing fluid management in non-severe adult dengue

Influenza A H5N1 Clade 2.3.4 Virus with a Different Antiviral Susceptibility Profile Replaced Clade 1 Virus in Humans in Northern Vietnam

BACKGROUND: Prior to 2007, highly pathogenic avian influenza (HPAI) H5N1 viruses isolated from poultry and humans in Vietnam were consistently reported to be clade 1 viruses, susceptible to oseltamivir but resistant to amantadine. Here we describe the re-emergence of human HPAI H5N1 virus infections in Vietnam in 2007 and the characteristics of the isolated viruses. METHODS AND FINDINGS: Respiratory specimens from patients suspected to be infected with avian influenza in 2007 were screened by influenza and H5 subtype specific polymerase chain reaction. Isolated H5N1 strains were further characterized by genome sequencing and drug susceptibility testing. Eleven poultry outbreak isolates from 2007 were included in the sequence analysis. Eight patients, all of them from northern Vietnam, were diagnosed with H5N1 in 2007 and five of them died. Phylogenetic analysis of H5N1 viruses isolated from humans and poultry in 2007 showed that clade 2.3.4 H5N1 viruses replaced clade 1 viruses in northern Vietnam. Four human H5N1 strains had eight-fold reduced in-vitro susceptibility to oseltamivir as compared to clade 1 viruses. In two poultry isolates the I117V mutation was found in the neuraminidase gene, which is associated with reduced susceptibility to oseltamivir. No mutations in the M2 gene conferring amantadine resistance were found. CONCLUSION: In 2007, H5N1 clade 2.3.4 viruses replaced clade 1 viruses in northern Vietnam and were susceptible to amantadine but showed reduced susceptibility to oseltamivir. Combination antiviral therapy with oseltamivir and amantadine for human cases in Vietnam is recommended

Ventilator-associated respiratory infection in a resource-restricted setting: impact and etiology

Ventilator-associated respiratory infection (VARI) is a significant problem in resource-restricted intensive care units (ICUs), but differences in casemix and etiology means VARI in resource-restricted ICUs may be different from that found in resource-rich units. Data from these settings are vital to plan preventative interventions and assess their cost-effectiveness, but few are available.We conducted a prospective observational study in four Vietnamese ICUs to assess the incidence and impact of VARI. Patients ≥ 16 years old and expected to be mechanically ventilated > 48 h were enrolled in the study and followed daily for 28 days following ICU admission.Four hundred fifty eligible patients were enrolled over 24 months, and after exclusions, 374 patients' data were analyzed. A total of 92/374 cases of VARI (21.7/1000 ventilator days) were diagnosed; 37 (9.9%) of these met ventilator-associated pneumonia (VAP) criteria (8.7/1000 ventilator days). Patients with any VARI, VAP, or VARI without VAP experienced increased hospital and ICU stay, ICU cost, and antibiotic use (p < 0.01 for all). This was also true for all VARI (p < 0.01 for all) with/without tetanus. There was no increased risk of in-hospital death in patients with VARI compared to those without (VAP HR 1.58, 95% CI 0.75-3.33, p = 0.23; VARI without VAP HR 0.40, 95% CI 0.14-1.17, p = 0.09). In patients with positive endotracheal aspirate cultures, most VARI was caused by Gram-negative organisms; the most frequent were Acinetobacter baumannii (32/73, 43.8%) Klebsiella pneumoniae (26/73, 35.6%), and Pseudomonas aeruginosa (24/73, 32.9%). 40/68 (58.8%) patients with positive cultures for these had carbapenem-resistant isolates. Patients with carbapenem-resistant VARI had significantly greater ICU costs than patients with carbapenem-susceptible isolates (6053 USD (IQR 3806-7824) vs 3131 USD (IQR 2108-7551), p = 0.04) and after correction for adequacy of initial antibiotics and APACHE II score, showed a trend towards increased risk of in-hospital death (HR 2.82, 95% CI 0.75-6.75, p = 0.15).VARI in a resource-restricted setting has limited impact on mortality, but shows significant association with increased patient costs, length of stay, and antibiotic use, particularly when caused by carbapenem-resistant bacteria. Evidence-based interventions to reduce VARI in these settings are urgently needed

Genome-wide association study identifies susceptibility loci for dengue shock syndrome at MICB and PLCE1

Hypovolemic shock (dengue shock syndrome (DSS)) is the most common life-threatening complication of dengue. We conducted a genome-wide association study of 2,008 pediatric cases treated for DSS and 2,018 controls from Vietnam. Replication of the most significantly associated markers was carried out in an independent Vietnamese sample of 1,737 cases and 2,934 controls. SNPs at two loci showed genome-wide significant association with DSS. We identified a susceptibility locus at MICB (major histocompatibility complex (MHC) class I polypeptide-related sequence B), which was within the broad MHC region on chromosome 6 but outside the class I and class II HLA loci (rs3132468, Pmeta = 4.41 × 10−11, per-allele odds ratio (OR) = 1.34 (95% confidence interval: 1.23–1.46)). We identified associated variants within PLCE1 (phospholipase C, epsilon 1) on chromosome 10 (rs3765524, Pmeta = 3.08 × 10−10, per-allele OR = 0.80 (95% confidence interval: 0.75–0.86)). We identify two loci associated with susceptibility to DSS in people with dengue, suggesting possible mechanisms for this severe complication of dengue. </p