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1.
Cells ; 10(12)2021 12 08.
Article in English | MEDLINE | ID: covidwho-1598446

ABSTRACT

Organ-specific proteins (OSPs) possess great medical potential both in clinics and in biomedical research. Applications of them-such as alanine transaminase, aspartate transaminase, and troponins-in clinics have raised certain concerns of their organ specificity. The dynamics and diversity of protein expression in heterogeneous human populations are well known, yet their effects on OSPs are less addressed. Here, we used mice as a model and implemented a breadth study to examine the panorgan proteome for potential variations in organ specificity in different genetic backgrounds. Using reasonable resources, we generated panorgan proteomes of four in-bred mouse strains. The results revealed a large diversity that was more profound among OSPs than among proteomes overall. We defined a robustness score to quantify such variation and derived three sets of OSPs with different stringencies. In the meantime, we found that the enriched biological functions of OSPs are also organ-specific and are sensitive and useful to assess the quality of OSPs. We hope our breadth study can open doors to explore the molecular diversity and dynamics of organ specificity at the protein level.


Subject(s)
Organ Specificity/genetics , Proteins/genetics , Proteome/genetics , Proteomics , Animals , Genetic Variation/genetics , Humans , Mice
3.
J Proteome Res ; 20(12): 5241-5263, 2021 12 03.
Article in English | MEDLINE | ID: covidwho-1483082

ABSTRACT

The study of proteins circulating in blood offers tremendous opportunities to diagnose, stratify, or possibly prevent diseases. With recent technological advances and the urgent need to understand the effects of COVID-19, the proteomic analysis of blood-derived serum and plasma has become even more important for studying human biology and pathophysiology. Here we provide views and perspectives about technological developments and possible clinical applications that use mass-spectrometry(MS)- or affinity-based methods. We discuss examples where plasma proteomics contributed valuable insights into SARS-CoV-2 infections, aging, and hemostasis and the opportunities offered by combining proteomics with genetic data. As a contribution to the Human Proteome Organization (HUPO) Human Plasma Proteome Project (HPPP), we present the Human Plasma PeptideAtlas build 2021-07 that comprises 4395 canonical and 1482 additional nonredundant human proteins detected in 240 MS-based experiments. In addition, we report the new Human Extracellular Vesicle PeptideAtlas 2021-06, which comprises five studies and 2757 canonical proteins detected in extracellular vesicles circulating in blood, of which 74% (2047) are in common with the plasma PeptideAtlas. Our overview summarizes the recent advances, impactful applications, and ongoing challenges for translating plasma proteomics into utility for precision medicine.

4.
Mini Rev Med Chem ; 2021 Aug 04.
Article in English | MEDLINE | ID: covidwho-1346361

ABSTRACT

Since the outbreak of COVID-19, it has been an epidemic for nearly a year. COVID-19 has brought painful disasters to people all over the world. It not only threatens lives and health, but also induces economic crises. At present, promising methods to eradicate COVID-19 mainly include drugs and vaccines. Enzyme inhibitors have always been a reliable strategy for the treatment of related diseases. Scientists worldwide have worked together to study COVID-19, have obtained the structure of key SARS-CoV-2 associated enzymes, and reported the research of inhibitors of these enzymes. This article summarizes COVID-19-related enzyme inhibitors' recent development, mainly including 3CLpro, PLpro, TMPRSS2, and RdRp inhibitors, hoping to provide valuable weapons in the ensuing battle against COVID-19.

5.
Mini Rev Med Chem ; 21(14): 1888-1908, 2021.
Article in English | MEDLINE | ID: covidwho-1323038

ABSTRACT

Virus is a type of noncellular organism, which is simple in structure, small in size and contains only one kind of nucleic acid (RNA or DNA). It must be parasitized in living cells and proliferates by replication. Viruses can infect plants or animals, which leads to many epidemic diseases, such as the current pandemic COVID-19. Viral infectious diseases have brought serious threats to the health of people around the world. Natural products are chemical substances that are usually produced by living organisms and have biological or pharmacological activity. Many of these natural products show antiviral activity. Based on the increasing importance of antiviral research, this paper focuses on the discovery and development of antiviral natural products since 2010.


Subject(s)
Antiviral Agents/pharmacology , Biological Products/pharmacology , COVID-19/drug therapy , Drug Discovery , SARS-CoV-2 , Animals , Antiviral Agents/chemistry , Biological Products/chemistry , Humans , Plant Viruses/drug effects
6.
Mini Rev Med Chem ; 21(14): 1888-1908, 2021.
Article in English | MEDLINE | ID: covidwho-1119515

ABSTRACT

Virus is a type of noncellular organism, which is simple in structure, small in size and contains only one kind of nucleic acid (RNA or DNA). It must be parasitized in living cells and proliferates by replication. Viruses can infect plants or animals, which leads to many epidemic diseases, such as the current pandemic COVID-19. Viral infectious diseases have brought serious threats to the health of people around the world. Natural products are chemical substances that are usually produced by living organisms and have biological or pharmacological activity. Many of these natural products show antiviral activity. Based on the increasing importance of antiviral research, this paper focuses on the discovery and development of antiviral natural products since 2010.


Subject(s)
Antiviral Agents/pharmacology , Biological Products/pharmacology , COVID-19/drug therapy , Drug Discovery , SARS-CoV-2 , Animals , Antiviral Agents/chemistry , Biological Products/chemistry , Humans , Plant Viruses/drug effects
8.
Open Med (Wars) ; 15(1): 723-727, 2020.
Article in English | MEDLINE | ID: covidwho-732981

ABSTRACT

In December 2019, novel coronavirus pneumonia-19 (COVID-19) was discovered in the viral pneumonia cases that occurred in Wuhan, China, and then quickly spread around the world. This report described the clinical course of two COVID-19 patients and the purpose of the study was to discuss the combination of chest CT and clinical features for diagnosis of COVID-19. The first case was a typical COVID-19 case. A 66-year-old female presented to our hospital with a 3-day history of fever. She had contact with a COVID-19 patient. Chest CT showed a typical COVID-19 appearance. She was diagnosed with COVID-19 by a positive nucleic acid test. The second case was a 50-year-old male with a 2-day history of fever. He denied having been to Wuhan. Chest CT also showed typical features of COVID-19 pneumonia. COVID-19 nucleic acid tests were repeated up to seven times and the results remained controversial. Eventually, he was diagnosed with COVID-19. Our study shows that chest CT has high sensitivity for diagnosis of COVID-19 in clinical practice, particularly when the nucleic acid test is negative. The chest CT should be considered as a diagnostic tool for the COVID-19 screening, comprehensive evaluation, and follow-up and patients would benefit from effective treatments in time.

9.
Eur Radiol ; 30(12): 6517-6527, 2020 Dec.
Article in English | MEDLINE | ID: covidwho-621502

ABSTRACT

OBJECTIVES: To utilize a deep learning model for automatic detection of abnormalities in chest CT images from COVID-19 patients and compare its quantitative determination performance with radiological residents. METHODS: A deep learning algorithm consisted of lesion detection, segmentation, and location was trained and validated in 14,435 participants with chest CT images and definite pathogen diagnosis. The algorithm was tested in a non-overlapping dataset of 96 confirmed COVID-19 patients in three hospitals across China during the outbreak. Quantitative detection performance of the model was compared with three radiological residents with two experienced radiologists' reading reports as reference standard by assessing the accuracy, sensitivity, specificity, and F1 score. RESULTS: Of 96 patients, 88 had pneumonia lesions on CT images and 8 had no abnormities on CT images. For per-patient basis, the algorithm showed superior sensitivity of 1.00 (95% confidence interval (CI) 0.95, 1.00) and F1 score of 0.97 in detecting lesions from CT images of COVID-19 pneumonia patients. While for per-lung lobe basis, the algorithm achieved a sensitivity of 0.96 (95% CI 0.94, 0.98) and a slightly inferior F1 score of 0.86. The median volume of lesions calculated by algorithm was 40.10 cm3. An average running speed of 20.3 s ± 5.8 per case demonstrated the algorithm was much faster than the residents in assessing CT images (all p < 0.017). The deep learning algorithm can also assist radiologists make quicker diagnosis (all p < 0.0001) with superior diagnostic performance. CONCLUSIONS: The algorithm showed excellent performance in detecting COVID-19 pneumonia on chest CT images compared with resident radiologists. KEY POINTS: • The higher sensitivity of deep learning model in detecting COVID-19 pneumonia were found compared with radiological residents on a per-lobe and per-patient basis. • The deep learning model improves diagnosis efficiency by shortening processing time. • The deep learning model can automatically calculate the volume of the lesions and whole lung.


Subject(s)
Algorithms , Betacoronavirus , Coronavirus Infections/diagnosis , Coronavirus Infections/epidemiology , Deep Learning , Lung/diagnostic imaging , Pandemics , Pneumonia, Viral/diagnosis , Pneumonia, Viral/epidemiology , Tomography, X-Ray Computed/methods , COVID-19 , China/epidemiology , Female , Humans , Male , Middle Aged , SARS-CoV-2
10.
Theranostics ; 10(14): 6372-6383, 2020.
Article in English | MEDLINE | ID: covidwho-494062

ABSTRACT

Background: The risk factors for adverse events of Coronavirus Disease-19 (COVID-19) have not been well described. We aimed to explore the predictive value of clinical, laboratory and CT imaging characteristics on admission for short-term outcomes of COVID-19 patients. Methods: This multicenter, retrospective, observation study enrolled 703 laboratory-confirmed COVID-19 patients admitted to 16 tertiary hospitals from 8 provinces in China between January 10, 2020 and March 13, 2020. Demographic, clinical, laboratory data, CT imaging findings on admission and clinical outcomes were collected and compared. The primary endpoint was in-hospital death, the secondary endpoints were composite clinical adverse outcomes including in-hospital death, admission to intensive care unit (ICU) and requiring invasive mechanical ventilation support (IMV). Multivariable Cox regression, Kaplan-Meier plots and log-rank test were used to explore risk factors related to in-hospital death and in-hospital adverse outcomes. Results: Of 703 patients, 55 (8%) developed adverse outcomes (including 33 deceased), 648 (92%) discharged without any adverse outcome. Multivariable regression analysis showed risk factors associated with in-hospital death included ≥ 2 comorbidities (hazard ratio [HR], 6.734; 95% CI; 3.239-14.003, p < 0.001), leukocytosis (HR, 9.639; 95% CI, 4.572-20.321, p < 0.001), lymphopenia (HR, 4.579; 95% CI, 1.334-15.715, p = 0.016) and CT severity score > 14 (HR, 2.915; 95% CI, 1.376-6.177, p = 0.005) on admission, while older age (HR, 2.231; 95% CI, 1.124-4.427, p = 0.022), ≥ 2 comorbidities (HR, 4.778; 95% CI; 2.451-9.315, p < 0.001), leukocytosis (HR, 6.349; 95% CI; 3.330-12.108, p < 0.001), lymphopenia (HR, 3.014; 95% CI; 1.356-6.697, p = 0.007) and CT severity score > 14 (HR, 1.946; 95% CI; 1.095-3.459, p = 0.023) were associated with increased odds of composite adverse outcomes. Conclusion: The risk factors of older age, multiple comorbidities, leukocytosis, lymphopenia and higher CT severity score could help clinicians identify patients with potential adverse events.


Subject(s)
Betacoronavirus , Coronavirus Infections/diagnosis , Pneumonia, Viral/diagnosis , Adolescent , Adult , Age Factors , Aged , Aged, 80 and over , COVID-19 , Child , Child, Preschool , China/epidemiology , Comorbidity , Coronavirus Infections/epidemiology , Coronavirus Infections/mortality , Female , Hospital Mortality , Humans , Infant , Kaplan-Meier Estimate , Male , Middle Aged , Pandemics , Pneumonia, Viral/epidemiology , Pneumonia, Viral/mortality , Prognosis , Proportional Hazards Models , Retrospective Studies , Risk Factors , SARS-CoV-2 , Theranostic Nanomedicine , Thorax/diagnostic imaging , Tomography, X-Ray Computed , Young Adult
11.
Zhongguo Zhong Yao Za Zhi ; 45(10): 2239-2248, 2020 May.
Article in Chinese | MEDLINE | ID: covidwho-398793

ABSTRACT

To analyze the development of coronavirus disease 2019(COVID-19), this study systematically retrieved relevant Chinese and English literatures from both CNKI and Web of Science database platforms by bibliometric research method and CiteSpace 5.5.R2 software to obtain information and visualize relevant literatures. A total of 695 Chinese and 446 English literatures were included in this paper. Statistics showed that China had published most of the literatures and established close cooperation with the United States and the United Kingdom. Through the analysis, Tongji Medical College of Huazhong University of Science and Technology and its affiliated hospitals published the largest number of the publications. Moreover, the highly productive journals including Journal of Traditional Chinese Medicine and The Lancet covered eight major fields, such as medicine, medical virology, radiation medicine, infectious disease, and traditional Chinese medicine. Besides, a total of 35 special COVID-19 funds were recently established to subsidize these studies. The key words and themes analysis indicated that protein structure of COVID-19, receptor targets and mechanisms of action, integration of traditional Chinese and Western medicine, screening and development of antiviral drugs from traditional Chinese medicine and Western medicine, vaccine research as well as epidemiological characteristics and prediction are current study hotspots. This study provides a reference for researchers to rapidly master main study directions of COVID-19 and screen out relevant literatures.


Subject(s)
Betacoronavirus , Bibliometrics , Coronavirus Infections , Pandemics , Pneumonia, Viral , COVID-19 , China , Humans , SARS-CoV-2 , United Kingdom , United States
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