A Nomogram Model for Predicting the Polyphenol Content of Pu-Erh Tea.

To investigate different contents of pu-erh tea polyphenol affected by abiotic stress, this research determined the contents of tea polyphenol in teas produced by Yuecheng, a Xishuangbanna-based tea producer in Yunnan Province. The study drew a preliminary conclusion that eight factors, namely, altitude, nickel, available cadmium, organic matter, N, P, K, and alkaline hydrolysis nitrogen, had a considerable influence on tea polyphenol content with a combined analysis of specific altitudes and soil composition. The nomogram model constructed with three variables, altitude, organic matter, and P, screened by LASSO regression showed that the AUC of the training group and the validation group were respectively 0.839 and 0.750, and calibration curves were consistent. A visualized prediction system for the content of pu-erh tea polyphenol based on the nomogram model was developed and its accuracy rate, supported by measured data, reached 80.95%. This research explored the change of tea polyphenol content under abiotic stress, laying a solid foundation for further predictions for and studies on the quality of pu-erh tea and providing some theoretical scientific basis.

Clinical Characteristics of Omicron SARS-CoV-2 Variant Infection After Non-mRNA-Based Vaccination in China.

Introduction: To date, little is known about the real-world protective role of Chinese inactivated and recombinant coronavirus disease 2019 (COVID-19) vaccines under the background of the long-term "Dynamic Zero COVID-19 Case" (i.e., no infection source) in China, especially when facing the widespread Omicron severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variant infection. Methods: In this prospective, single-center cohort study, the clinical characteristics of post-vaccination Omicron SARS-CoV-2 variant infection were investigated in the initial largest outbreak of Omicron SARS-CoV-2 variant infection that occurred between the 8 January, 2022 and 29 January, 2022 in Anyang City, Henan Province, China. The primary endpoints were the rates of severe and critical diseases or death. The secondary endpoints were the SARS-CoV-2 shedding duration and length of hospitalization. Results: A total of 380 post-vaccination patients infected with the Omicron SARS-CoV-2 variant were enrolled. The median age was 18 (interquartile range [IQR] 17-35) years, 219 (57.6%) cases were female, and 247 (65.0%) cases were students. Before confirmation of Omicron SARS-CoV-2 variant infection, patients had 3 (IQR 2-4) days of dry cough (40.3%), nasal congestion (26.3%), and sore throat (26.3%). On admission, 294 (77.4%) cases had normal chest computerized tomography (CT) imaging. Additionally, only 5 (1.3%), 30 (7.9%), 4 (4/342, 1.2%), and 7 (7/379, 0.2%) patients had lymphocyte counts <800 per mm3, C-reactive protein levels >10 mg/L, lactate dehydrogenase levels ≥250 U/L, and D-dimer levels ≥0.5 mg/L on admission, respectively. During hospitalization, 308 (81.1%) and 72 (18.9%) were identified as mild and moderate cases, respectively, and no one progressed to severe and critical types, with a SARS-CoV-2 shedding period and length of hospital stay of 17 (IQR 12-22) and 19 (IQR 15-24) days, respectively. Conclusion: The current study found that approximately 80% of individuals infected with the Omicron SARS-CoV-2 variant were mild, approximately 20% of patients were moderate, and no severe, critical, or fatal cases were identified in a prospective cohort including 380 participants vaccinated with non-mRNA-based vaccines. Discussion: This study supports the consideration of policy adjustments and changes to prevent and control the Omicron-predominant COVID-19 in China and other regions with high SARS-CoV-2 vaccination rates.

Clinical Characteristics of Omicron SARS-CoV-2 Variant Infection After Non-mRNA-Based Vaccination in China

Introduction To date, little is known about the real-world protective role of Chinese inactivated and recombinant coronavirus disease 2019 (COVID-19) vaccines under the background of the long-term “Dynamic Zero COVID-19 Case” (i.e., no infection source) in China, especially when facing the widespread Omicron severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variant infection. Methods In this prospective, single-center cohort study, the clinical characteristics of post-vaccination Omicron SARS-CoV-2 variant infection were investigated in the initial largest outbreak of Omicron SARS-CoV-2 variant infection that occurred between the 8 January, 2022 and 29 January, 2022 in Anyang City, Henan Province, China. The primary endpoints were the rates of severe and critical diseases or death. The secondary endpoints were the SARS-CoV-2 shedding duration and length of hospitalization. Results A total of 380 post-vaccination patients infected with the Omicron SARS-CoV-2 variant were enrolled. The median age was 18 (interquartile range [IQR] 17–35) years, 219 (57.6%) cases were female, and 247 (65.0%) cases were students. Before confirmation of Omicron SARS-CoV-2 variant infection, patients had 3 (IQR 2–4) days of dry cough (40.3%), nasal congestion (26.3%), and sore throat (26.3%). On admission, 294 (77.4%) cases had normal chest computerized tomography (CT) imaging. Additionally, only 5 (1.3%), 30 (7.9%), 4 (4/342, 1.2%), and 7 (7/379, 0.2%) patients had lymphocyte counts <800 per mm3, C-reactive protein levels >10 mg/L, lactate dehydrogenase levels ≥250 U/L, and D-dimer levels ≥0.5 mg/L on admission, respectively. During hospitalization, 308 (81.1%) and 72 (18.9%) were identified as mild and moderate cases, respectively, and no one progressed to severe and critical types, with a SARS-CoV-2 shedding period and length of hospital stay of 17 (IQR 12–22) and 19 (IQR 15–24) days, respectively. Conclusion The current study found that approximately 80% of individuals infected with the Omicron SARS-CoV-2 variant were mild, approximately 20% of patients were moderate, and no severe, critical, or fatal cases were identified in a prospective cohort including 380 participants vaccinated with non-mRNA-based vaccines. Discussion This study supports the consideration of policy adjustments and changes to prevent and control the Omicron-predominant COVID-19 in China and other regions with high SARS-CoV-2 vaccination rates.

The impact of meteorological factors and PM2.5 on COVID-19 transmission.

In this study, we analysed the relationship between meteorological factors and the number of patients with coronavirus disease 2019 (COVID-19). The study period was from 12 April 2020 to 13 October 2020, and daily meteorological data and the daily number of patients with COVID-19 in each state of the United States were collected. Based on the number of COVID-19 patients in each state of the United States, we selected four states (California, Florida, New York, Texas) for analysis. One-way analysis of variance ( ANOVA), scatter plot analysis, correlation analysis and distributed lag nonlinear model (DLNM) analysis were used to analyse the relationship between meteorological factors and the number of patients with COVID-19. We found that the significant influencing factors of the number of COVID-19 cases differed among the four states. Specifically, the number of COVID-19 confirmed cases in California and New York was negatively correlated with AWMD (P < 0.01) and positively correlated with AQI, PM2.5 and TAVG (P < 0.01) but not significantly correlated with other factors. Florida was significantly correlated with TAVG (positive) (P < 0.01) but not significantly correlated with other factors. The number of COVID-19 cases in Texas was only significantly negatively associated with AWND (P < 0.01). The influence of temperature and PM2.5 on the spread of COVID-19 is not obvious. This study shows that when the wind speed was 2 m/s, it had a significant positive correlation with COVID-19 cases. The impact of meteorological factors on COVID-19 may be very complicated. It is necessary to further explore the relationship between meteorological factors and COVID-19. By exploring the influence of meteorological factors on COVID-19, we can help people to establish a more accurate early warning system.

The Therapeutic Potential of Galectin-3 in the Treatment of Intrahepatic Cholangiocarcinoma Patients and Those Compromised With COVID-19.

The novel coronavirus pneumonia COVID-19 is characterized by all age susceptibility, which imposes a dramatic threat to the human species all over the world. According to current available data, the cytokine storm appears to be the most life-threatening symptom of severe COVID-19 cases accompanied with lung fibrosis. Galectin-3 (Gal-3), a member of soluble ß-galactoside-binding lectin families, has been implicated as a key regulator in various inflammation conditions in addition to its well-documented roles in cancer. The pro-inflammatory activity of Gal-3 in the inflammatory response and lung fibrosis of COVID-19 has been proposed by emerging studies, which suggested that inhibition of Gal-3 may represent a novel treatment approach for COVID-19 patients. Intrahepatic cholangiocarcinoma (ICC) is an aggressive malignancy with poor prognosis. ICC accounts for 10-25% of primary liver cancers with limited therapeutic options, which has higher incidence in Asian countries, particularly in China. Cancer patients, including ICC patients, are highly vulnerable to COVID-19 due to their impaired immune system. It is thus undoubtedly a challenge for our oncology department to establish effective treatment strategies under the influence of the COVID-19 crisis. According to our management procedures in the COVID-19 era, emergency treatment will be applied to ICC patients who are under life-threatening conditions, despite the COVID-19 infection. To the best of our knowledge, the modulatory function of Gal-3 in ICC is still barely explored to date. In order to evaluate the therapeutic potential of Gal-3 for ICC patients or those comprised with COVID-19, we herein report our preliminary investigation into roles of Gal-3 in ICC. Our results exhibited that the expression of Gal-3 was significantly up-regulated in ICC tissues, and a significant correlation was observed between its overexpression and malignant progression of ICC cells. We further discussed the activity and possible molecular mechanisms of Gal-3 in ICC, which may pave the ways for further exploring the possibility of Gal-3 as a potential therapeutic target for treating ICC patients or those with COVID-19-related conditions.

Hypertension is a clinically important risk factor for critical illness and mortality in COVID-19: A meta-analysis.

AIMS: As reported, hypertension may play an important role in adverse outcomes of coronavirus disease-2019 (COVID-19), but it still had many confounding factors. The aim of this study was to explore whether hypertension is an independent risk factor for critical COVID-19 and mortality. DATA SYNTHESIS: The Medline, PubMed, Embase, and Web of Science databases were systematically searched until November 2020. Combined odds ratios (ORs) with their 95% confidence interval (CIs) were calculated by using random-effect models, and the effect of covariates was analyzed using the subgroup analysis and meta-regression analysis. A total of 24 observational studies with 99,918 COVID-19 patients were included in the meta-analysis. The proportions of hypertension in critical COVID-19 were 37% (95% CI: 0.27 -0.47) when compared with 18% (95% CI: 0.14 -0.23) of noncritical COVID-19 patients, in those who died were 46% (95%CI: 0.37 -0.55) when compared with 22% (95% CI: 0.16 -0.28) of survivors. Pooled results based on the adjusted OR showed that patients with hypertension had a 1.82-fold higher risk for critical COVID-19 (aOR: 1.82; 95% CI: 1.19 - 2.77; P = 0.005) and a 2.17-fold higher risk for COVID-19 mortality (aOR: 2.17; 95% CI: 1.67 - 2.82; P < 0.001). Subgroup analysis results showed that male patients had a higher risk of developing to the critical condition than female patients (OR: 3.04; 95%CI: 2.06 - 4.49; P < 0.001) and age >60 years was associated with a significantly increased risk of COVID-19 mortality (OR: 3.12; 95% CI: 1.93 - 5.05; P < 0.001). Meta-regression analysis results also showed that age (Coef. = 2.3×10-2, P = 0.048) had a significant influence on the association between hypertension and COVID-19 mortality. CONCLUSIONS: Evidence from this meta-analysis suggested that hypertension was independently associated with a significantly increased risk of critical COVID-19 and inhospital mortality of COVID-19.

Association of body mass index (BMI) with critical COVID-19 and in-hospital mortality: A dose-response meta-analysis.

BACKGROUND AND PURPOSE: The coronavirus disease 2019 (COVID-19) pandemic presents an unprecedented health crisis to the entire world. As reported, the body mass index (BMI) may play an important role in COVID-19; however, this still remains unclear. The aim of this study was to explore the association between BMI and COVID-19 severity and mortality. METHODS: The Medline, PubMed, Embase and Web of science were systematically searched until August 2020. Random-effects models and dose-response meta-analysis were used to synthesize the results. Combined odds ratios (ORs) with their 95% confidence intervals (CIs) were calculated, and the effect of covariates were analyzed using subgroup analysis and meta-regression analyses. RESULTS: A total of 16 observational studies involving 109,881 patients with COVID-19 were included in the meta-analysis. The pooled results showed that patients with a BMI ≥ 30 kg/m2 had a 2.35-fold risk (OR = 2.35, 95%CI = 1.64-3.38, P < 0.001) for critical COVID-19 and a 2.68-fold risk for COVID-19 mortality (OR = 2.68, 95%CI = 1.65-4.37, P < 0.001) compared with patients with a BMI <30 kg/m2. Subgroup analysis results showed that patients with obesity and age > 60 years was associated with a significantly increased risk of critical COVID-19 (OR = 3.11, 95%CI = 1.73-5.61, P < 0.001) and COVID-19 mortality (OR = 3.93, 95%CI = 2.18-7.09, P < 0.001). Meta-regression analysis results also showed that age had a significant influence on the association between BMI and COVID-19 mortality (Coef. = 0.036, P = 0.048). Random-effects dose-response meta-analysis showed a linear association between BMI and both critical COVID-19(Pnon-linearity = 0.242) and mortality (Pnon-linearity = 0.116). The risk of critical COVID-19 and mortality increased by 9%(OR = 1.09, 95%CI = 1.04-1.14, P < 0.001) and 6%(OR = 1.06, 95%CI = 1.02-1.10, P = 0.002) for each 1 kg/m2 increase in BMI, respectively. CONCLUSIONS: Evidence from this meta-analysis suggested that a linear dose-response association between BMI and both COVID-19 severity and mortality. Further, obesity (BMI ≥ 30 kg/m2) was associated with a significantly increased risk of critical COVID-19 and in-hospital mortality of COVID-19.

Using simulation Technology to Analyze the COVID-19 Epidemic in Changsha, Hunan Province, China (preprint)

This study mainly uses simulation technology to simulate the COVID-19 epidemic in Changsha, Hunan Province, China, and analyze the impact of different prevention and control measures on the epidemic. we Collect the information of all COVID-19 patients in Changsha from January 21, 2020 to March 14, 2020 and relevant policies during the COVID-19 epidemic in Changsha. Established the SEIAR infectious disease dynamics model under natural conditions, and added isolation measures on this basis. Using Anylogic8.5, the COVID-19 epidemic in Changsha City was simulated under various conditions based on the established model.In this study we find that There were 242 COVID-19 patients in Changsha. including 121 males (50%) and 121 females (50%).Most cases occurred between February 6 and February 16. Through the calculation of the Rt during the epidemic in Changsha, it is found that it is reasonable to resume work on February 8, because the Rt value of Changsha dropped below 1 at this time.The simulation results show that reducing the contact rate of residents and reducing the success rate of virus transmission (wearing masks, disinfection, etc.) can effectively prevent the spread of COVID-19 and significantly reduce the number of peak patients.We believe that the disease is mainly spread by the respiratory tract. Therefore, the simulation results show that whether in the early or mid-stage of the epidemic, quarantining the names of residents or reducing the contact rate of residents is very effective in controlling the COVID-19 epidemic.