Assessment of Illness Severity in Adults Hospitalized With Acute Respiratory Tract Infection due to Influenza, Respiratory Syncytial Virus, or Human Metapneumovirus.

BACKGROUND: Influenza, respiratory syncytial virus (RSV), and human metapneumovirus (hMPV) are common respiratory viruses causing similar symptoms. Optimal tools to assess illness severity for these viruses have not been defined. Using the Hospitalized Acute Respiratory Tract Infection (HARTI) study data, we report symptom severity by clinician-rated clinical severity scores (CSS) in adults with influenza, RSV, or hMPV and correlations between CSS and patient-reported outcomes (PROs). METHODS: HARTI was a global epidemiologic study in adults hospitalized with acute respiratory tract infections. Patients were assessed at enrollment within 24 h of admission with CSS and twice during hospitalization with CSS, Respiratory Infection Intensity and Impact Questionnaire™ (RiiQ™), and EQ-5D-5L. Data were summarized descriptively, stratified by pathogen and baseline and hospitalization characteristics. Domain (general, upper respiratory, and lower respiratory) and sign/symptom subscores are presented for CSS; sign/symptom subscores are presented for RiiQ™ results. RESULTS: Data from 635 patients with influenza, 248 with RSV, and 107 with hMPV were included. At enrollment, total CSS and general and lower respiratory signs/symptoms (LRS) scores were higher for RSV and hMPV than influenza. Between-pathogen differences were greatest for LRS scores. Dyspnea, rales/rhonchi, wheezing, and shortness of breath scores trended higher for RSV and hMPV than influenza. RiiQ™ scores for cough, fatigue, and short of breath were strongly correlated with corresponding clinician-rated symptoms. CONCLUSIONS: These findings support the use of PROs (e.g., the RiiQ™) correlating with clinician assessments to gauge patient well-being and aid patient management by accurately assessing respiratory illness severity due to RSV, hMPV, or influenza.

The complete mitochondrial genome of Chinese glass lizard Ophisaurus harti (Squamata: Anguidae).

The complete mitochondrial genome of Ophisaurus harti is a circular molecule of 17,163 bp in length, containing 13 protein-coding genes, 2 ribosomal RNAs, 22 transfer RNAs and a control region. The A + T content of the overall base composition of H-strand is 54.9% (T: 23.4%; C: 30.8%; A: 31.5%; G: 14.3%). COI gene begins with GTG as start codon, while other 12 protein-coding genes start with a typical ATG initiation codon. ND1. COI. ATP8. ATP6. ND4L and ND5 genes are terminated with TAA as stop codon, ND2. ND6 and Cyt b end with TAG, COIII ends with TA, COII and ND3 end with T and ND4 ends with TG.

A novel glucagon-like peptide 1 peptide identified from Ophisaurus harti.

Glucagon-like peptide 1 receptor (GLP1R) is a promising target for the treatment of type 2 diabetes. Because of the short half-life of endogenous GLP1 peptide, other GLP1R agonists are considered to be appealing therapeutic candidates. A high-throughput assay has been established to screen for GLP1R agonists in a 60 000-well natural product compound library fractionated from 670 different herbs/materials widely used in traditional Chinese medicines (TCMs). The screening is based on primary screen of GLP1R⁺ reporter gene assay with the counter screen in GLP1R⁻ cell line. An active fraction, A089-147, was identified from the screening. Fraction A089-147 was isolated from dried Ophisaurus harti, and the fact that its GLP1R agonist activity was sensitive to trypsin treatment indicates its peptidic nature. The active ingredient of A089-147 was later identified as O. harti GLP1 through transcriptome analysis. Chemically synthesized O. harti GLP1 showed GLP1R agonist activity and sensitivity to dipeptidase IV digestion. This study illustrated a comprehensive screening strategy to identify novel GLP1R agonists from TCMs libraries and at the same time underlined the difficulty of identifying a non-peptidic GLP1R agonist. The novel O. harti GLP1 peptide yielded from this study confirmed broader application of TCMs libraries in active peptide identification.