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Dis Markers ; 2022: 4713045, 2022.
Article in English | MEDLINE | ID: covidwho-1673529


PURPOSE: Histidine-rich glycoprotein (HRG) is abundant in serum and has been implicated in several processes including blood coagulation and immune response. This prospective study is aimed at exploring HRG as a biomarker in patients hospitalized for community-acquired pneumonia (CAP). METHODS: A total of 160 patients (73 severe CAP, 57 nonsevere CAP), and 30 healthy controls were enrolled in 2019. Demographic and clinical data were recorded for all patients. Serum HRG concentration was measured upon admission using ELISA. RESULTS: HRG levels were significantly lower in severe CAP patients compared with other groups, regardless of etiology, and were negatively correlated with serum interleukin-6 and disease severity index scores. Combination of CURB-65, PSI, and APACHE II scores with HRG values significantly improved the accuracy of predicting 30-day mortality in these patients. Cox regression analysis showed that HRG could serve as an independent risk factor for 30-day mortality. Notably, patients with HRG ≤ 16.92 µg/mL had significantly lower cumulative survival than those with HRG > 16.92 µg/mL. CONCLUSION: Serum HRG levels are lower in patients with severe CAP and are negatively correlated with disease severity scores. Measurement of HRG upon admission can provide valuable prognostic information for patients with CAP.

Community-Acquired Infections/blood , Community-Acquired Infections/mortality , Pneumonia/blood , Pneumonia/mortality , Proteins/analysis , Adult , Aged , Female , Humans , Male , Middle Aged , Prognosis , Prospective Studies , Survival Rate
Comb Chem High Throughput Screen ; 2021 Aug 11.
Article in English | MEDLINE | ID: covidwho-1354797


BACKGROUND: High throughput screening systems are automated labs for the analysis of many biochemical substances in the drug discovery and virus detection process. This paper was motivated by the problem of automating testing for viruses and new drugs using high throughput screening systems. The emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) at the turn of 2019-2020 presented extradentary challenges to public health. Existing approaches to test viruses and new drugs do not use optimal schedules and are not efficient. OBJECTIVE: The scheduling of activities performed by various resources in a high throughput screening system affects its efficiency, throughput, operations cost, and quality of screening. This study aims to minimize the total screening (flow) time and ensure the consistency and quality of screening. METHODS: This paper develops innovative mixed integer models that efficiently compute optimal schedules for screening many microplates to identify new drugs and determine whether samples contain viruses. The methods integrate job-shop and cyclic scheduling. Experiments are conducted for a drug discovery process of screening an enzymatic assay and a general process of detecting SARS-CoV-2. RESULTS: The method developed in this article can reduce screening time by as much as 91.67%. CONCLUSION: The optimal schedules for high throughput screening systems greatly reduce the total flow time and can be computed efficiently to help discover new drugs and detect viruses.

Pathogens ; 10(2)2021 Jan 25.
Article in English | MEDLINE | ID: covidwho-1110464


Despite progress in intensive care, the morbidity and mortality of patients with community-acquired pneumonia (CAP) remains high. Furthermore, the predictive and prognostic utility of resistin-like molecule beta (RELM-ß) in patients with CAP is uncertain. This study investigated the role of RELM-ß in patients with CAP and evaluated its correlation with disease severity and the risk of death. A prospective, multicenter study was conducted in 2017, and admission serum levels of RELM-ß were detected using quantitative enzyme-linked immunosorbent assay. A total of 114 and 112 patients with severe CAP (SCAP) and non-severe CAP (NSCAP) were enrolled, respectively, with 15 healthy controls. Patients with SCAP, especially non-survivors, had significantly higher levels of serum RELM-ß than patients with NSCAP. RELM-ß levels positively correlated with severity scores and consistently predicted SCAP in patients with CAP (area under the curve = 0.794). Increased levels of RELM-ß were closely related to the severity and prognosis of patients with CAP. The accuracy of 30-day mortality predictions of CURB-65 (confusion, urea, respiratory rate, blood pressure, and age ≥ 65 years) can be significantly improved when combined with RELM-ß levels. The level of RELM-ß can assist clinicians in risk stratification of patients with CAP in early stages.