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Pharmacological Research - Modern Chinese Medicine ; : 100085, 2022.
Article in English | ScienceDirect | ID: covidwho-1763936

ABSTRACT

The vascular niche is a microenvironment located around capillaries and is mainly composed of endothelial cells, pericytes, macrophages, lymphocytes, mesenchymal stem cells, and hematopoietic stem cells. Studies have found that the vascular niche not only functions to regulate cell growth and differentiation in normal tissues, but also has an important role in regulating fibrosis in various organs and tissues in disease states. Coronavirus disease 2019 (COVID-19) is a systemic disease that broke out in 2019, caused by SARS-CoV-2 infection, which results in pulmonary inflammation, systemic multi-organ damage, and an inflammatory cytokine storm. Recently, the vascular niche has been found to play a role in COVID-19-related multi-organ damage. In this review, we introduce the important role of the vascular niche in organ fibrosis and COVID-19-related organ damage, summarize some of the cellular signaling pathways in the vascular niche that promote fibrosis, and discuss the treatment of organ fibrosis in Traditional Chinese medicine and Western medicine.

2.
J Raman Spectrosc ; 52(5): 949-958, 2021 May.
Article in English | MEDLINE | ID: covidwho-1095641

ABSTRACT

The outbreak of COVID-19 coronavirus disease around the end of 2019 has become a pandemic. The preferred method for COVID-19 detection is the real-time polymerase chain reaction (RT-PCR)-based technique; however, it also has certain limitations, such as sample-dependent procedures with a relatively high false negative ratio. We propose a safe and efficient method for screening COVID-19 based on Raman spectroscopy. A total of 177 serum samples are collected from 63 confirmed COVID-19 patients, 59 suspected cases, and 55 healthy individuals as a control group. Raman spectroscopy is adopted to analyze these samples, and a machine learning support-vector machine (SVM) method is applied to the spectrum dataset to build a diagnostic algorithm. Furthermore, 20 independent individuals, including 5 asymptomatic COVID-19 patients and 5 symptomatic COVID-19 patients, 5 suspected patients, and 5 healthy patients, were sampled for external validation. In these three groups-confirmed COVID-19, suspected, and healthy individuals-the distribution of statistically significant points of difference showed highly consistency for intergroups after repeated sampling processes. The classification accuracy between the COVID-19 cases and the suspected cases is 0.87 (95% confidence interval [CI]: 0.85-0.88), and the accuracy between the COVID-19 and the healthy controls is 0.90 (95% CI: 0.89-0.91), while the accuracy between the suspected cases and the healthy control group is 0.68 (95% CI: 0.67-0.73). For the independent test dataset, we apply the obtained SVM model to the classification of the independent test dataset to have all the results correctly classified. Our model showed that the serum-level classification results were all correct for independent test dataset. Our results suggest that Raman spectroscopy could be a safe and efficient technique for COVID-19 screening.

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