Host Transcription Profile in Nasal Epithelium and Whole Blood of Hospitalized Children Under 2 Years of Age With Respiratory Syncytial Virus Infection.

Background: Most insights into the cascade of immune events after acute respiratory syncytial virus (RSV) infection have been obtained from animal experiments or in vitro models. Methods: In this study, we investigated host gene expression profiles in nasopharyngeal (NP) swabs and whole blood samples during natural RSV and rhinovirus (hRV) infection (acute versus early recovery phase) in 83 hospitalized patients <2 years old with lower respiratory tract infections. Results: Respiratory syncytial virus infection induced strong and persistent innate immune responses including interferon signaling and pathways related to chemokine/cytokine signaling in both compartments. Interferon-α/ß, NOTCH1 signaling pathways and potential biomarkers HIST1H4E, IL7R, ISG15 in NP samples, or BCL6, HIST2H2AC, CCNA1 in blood are leading pathways and hub genes that were associated with both RSV load and severity. The observed RSV-induced gene expression patterns did not differ significantly in NP swab and blood specimens. In contrast, hRV infection did not as strongly induce expression of innate immunity pathways, and significant differences were observed between NP swab and blood specimens. Conclusions: We conclude that RSV induced strong and persistent innate immune responses and that RSV severity may be related to development of T follicular helper cells and antiviral inflammatory sequelae derived from high activation of BCL6.

Direct whole-genome deep-sequencing of human respiratory syncytial virus A and B from Vietnamese children identifies distinct patterns of inter- and intra-host evolution.

Human respiratory syncytial virus (RSV) is the major cause of lower respiratory tract infections in children ,2 years of age. Little is known about RSV intra-host genetic diversity over the course of infection or about the immune pressures that drive RSV molecular evolution. We performed whole-genome deep-sequencing on 53 RSV-positive samples (37 RSV subgroup A and 16 RSV subgroup B) collected from the upper airways of hospitalized children in southern Vietnam over two consecutive seasons. RSV A NA1 and RSV B BA9 were the predominant genotypes found in our samples, consistent with other reports on global RSV circulation during the same period. For both RSV A and B, the M gene was the most conserved, confirming its potential as a target for novel therapeutics. The G gene was the most variable and was the only gene under detectable positive selection. Further, positively selected sites inG were found in close proximity to and in some cases overlapped with predicted glycosylation motifs, suggesting that selection on amino acid glycosylation may drive viral genetic diversity. We further identified hotspots and coldspots of intra-host genetic diversity in the RSV genome, some of which may highlight previously unknown regions of functional importance.

Efficient Machine Reading Comprehension for Health Care Applications: Algorithm Development and Validation of a Context Extraction Approach.

BACKGROUND: Extractive methods for machine reading comprehension (MRC) tasks have achieved comparable or better accuracy than human performance on benchmark data sets. However, such models are not as successful when adapted to complex domains such as health care. One of the main reasons is that the context that the MRC model needs to process when operating in a complex domain can be much larger compared with an average open-domain context. This causes the MRC model to make less accurate and slower predictions. A potential solution to this problem is to reduce the input context of the MRC model by extracting only the necessary parts from the original context. OBJECTIVE: This study aims to develop a method for extracting useful contexts from long articles as an additional component to the question answering task, enabling the MRC model to work more efficiently and accurately. METHODS: Existing approaches to context extraction in MRC are based on sentence selection strategies, in which the models are trained to find the sentences containing the answer. We found that using only the sentences containing the answer was insufficient for the MRC model to predict correctly. We conducted a series of empirical studies and observed a strong relationship between the usefulness of the context and the confidence score output of the MRC model. Our investigation showed that a precise input context can boost the prediction correctness of the MRC and greatly reduce inference time. We proposed a method to estimate the utility of each sentence in a context in answering the question and then extract a new, shorter context according to these estimations. We generated a data set to train 2 models for estimating sentence utility, based on which we selected more precise contexts that improved the MRC model's performance. RESULTS: We demonstrated our approach on the Question Answering Data Set for COVID-19 and Biomedical Semantic Indexing and Question Answering data sets and showed that the approach benefits the downstream MRC model. First, the method substantially reduced the inference time of the entire question answering system by 6 to 7 times. Second, our approach helped the MRC model predict the answer more correctly compared with using the original context (F1-score increased from 0.724 to 0.744 for the Question Answering Data Set for COVID-19 and from 0.651 to 0.704 for the Biomedical Semantic Indexing and Question Answering). We also found a potential problem where extractive transformer MRC models predict poorly despite being given a more precise context in some cases. CONCLUSIONS: The proposed context extraction method allows the MRC model to achieve improved prediction correctness and a significantly reduced MRC inference time. This approach works technically with any MRC model and has potential in tasks involving processing long texts.

Massive fish death associated with the toxic cyanobacterial Planktothrix sp. bloom in the Béni-Haroun Reservoir (Algeria).

In July 2017, a massive bloom of the potentially toxic cyanobacterial species Planktothrix sp. was observed in the Béni-Haroun Reservoir (Algeria), which was followed by a massive fish death. Many questions were raised in association with the role of cyanotoxins and the fish massive mortality. The objective of this paper is twofold: (1) to investigate the variability of physicochemical and cyanobacterial parameters (chlorophyll-a, phycocyanin, allophycocyanin, and microcystins) throughout the period of July 2017 to June 2018; and (2) to determine the free and total MC levels in viscera and muscle tissues of the common carp (Cyprinus carpio), which are found dead in the considered reservoir in October 2017. Our results showed microcystin (MC) concentrations in water samples (by the protein phosphatase PP2A assay) had reached 651.2 ng MC-LR equiv./L. Total MC levels (free + bound) in the viscera and muscle tissues of sampled dead fish were at 960.24 and 438.54 µg MC-LR equiv./kg dw, respectively. It is assumed that high concentrations of MC observed in the tissues of common carp induced a strong degradation of the visceral contents resulting in the complete lysis of the hepatopancreas, and presumably the massive fish death.

Respiratory Syncytial Virus and Other Viral Infections among Children under Two Years Old in Southern Vietnam 2009-2010: Clinical Characteristics and Disease Severity.

BACKGROUND: Despite a high burden of respiratory syncytial virus (RSV) infections among children, data on demographic and clinical characteristics of RSV are scarce in low and middle income countries. This study aims to describe the viral etiologies, the demographic, epidemiological, and clinical characteristics of children under two years of age who were hospitalized with a lower respiratory tract infections (LRTI), focusing on RSV (prevalence, seasonality, subgroups, viral load) and its association with disease severity. METHODS: A prospective study among children under two years of age, hospitalized with LRTI was conducted in two referral pediatric hospitals in Ho Chi Minh City, Vietnam, from May 2009 to December 2010. Socio-demographic, clinical data and nasopharyngeal swabs were collected on enrolment and discharge. Multiplex real-time RT-PCR (13 viruses) and quantitative RSV RT-PCR were used to identify viral pathogens, RSV load and subgroups. RESULTS: Among 632 cases, 48% were RSV positive. RSV infections occurred at younger age than three other leading viral infections i.e rhinovirus (RV), metapneumovirus (MPV), parainfluenza virus (PIV-3) and were significantly more frequent in the first 6 months of life. Clinical severity score of RSV infection was significantly higher than PIV-3 but not for RV or MPV. In multivariate analysis, RV infection was significantly associated with severity while RSV infection was not. Among RSV infections, neither viral load nor viral co-infections were significantly associated with severity. Young age and having fever at admission were significantly associated with both RSV and LRTI severity. A shift in RSV subgroup predominance was observed during two consecutive rainy seasons but was not associated with severity. CONCLUSION: We report etiologies, the epidemiological and clinical characteristics of LRTI among hospitalized children under two years of age and risk factors of RSV and LRTI severity.