Background: Previous research suggested that Chinese Medicine (CM) Formula Huashibaidu granule might shorten the disease course in coronavirus disease 2019 (COVID-19) patients. This research aimed to investigate the early treatment effect of Huashibaidu granule in well-managed patients with mild COVID-19.Methods: An unblinded cluster-randomized clinical trial was conducted at the Dongxihu FangCang hospital. Two cabins were randomly allocated to a CM or control group, with 204 mild COVID-19 participants in each cabin. All participants received conventional treatment over a 7 day period, while the ones in CM group were additionally given Huashibaidu granule 10 g twice daily. Participants were followed up to their clinical endpoint. The primary outcome was worsening symptoms before the clinical endpoint. The secondary outcomes were cure and discharge before the clinical endpoint and alleviation of composite symptoms after the 7 days of treatment.Results: All 408 participants were followed up to their clinical endpoint and included in statistical analysis. Baseline characteristics were comparable between the two groups (P > 0.05). The number of worsening patients in the CM group was 5 (2.5%), and that in the control group was 16 (7.8%) with a significant difference between groups (P = 0.014). Eight foreseeable mild adverse events occurred without statistical difference between groups (P = 0.151).Conclusion: Seven days of early treatment with Huashibaidu granule reduced the likelihood of worsening symptoms in patients with mild COVID-19. Our study supports Huashibaidu granule as an active option for early treatment of mild COVID-19 in similar well-managed medical environments.Clinical Trial Registration:www.chictr.org.cn/showproj.aspx?proj=49408, identifier: ChiCTR2000029763.

Aims. To explore the relationships of procollagen type 1 N-terminal propeptide (P1NP) and β cross-linked C-telopeptide of type 1 collagen (β-CTX) with bone mineral density (BMD) in postmenopausal women. Methods. All postmenopausal women were selected from a community-based case-control study. The anteroposterior L1-L4 and left proximal femur BMD were measured. P1NP and β-CTX were also collected and tested. The main correlation analysis was applied to explore the relationships of BMD, P1NP, and β-CTX. Results. The total 1055 postmenopausal women were enrolled. The BMD at all sites kept a decrease continually with age ( P < 0.01 ). In addition, the level of β-CTX increased significantly from 45 to 50 years old and remained at a high level in the later stage, while the level of P1NP changed little or even decreased with age. Logistic regression model showed that β-CTX has better ability to predict BMD than P1NP, as demonstrated by an area under the curve (AUC) of 0.63. Conclusion. P1NP and β-CTX are important markers to monitor bone metabolism. This trial is registered with ChiCTR-SOC-17013090. The date of registration is Oct. 23, 2017.

BackgroundPrimary liver cancer is a common clinical malignancy. Traditional Chinese medicine (TCM) is an alternative treatment for primary liver cancer. TCM effectively improves the survival rate and quality of life of patients, but high-level evidence is lacking.Patients and methodsThis study determined whether the combination of TCM and conventional cancer treatment affects the survival of liver cancer patients. Patients were selected from 5 tertiary hospitals in Henan Province. Two thousand and sixty-seven patients with primary liver cancer were included in the study for analysis. Patients who received adjunctive TCM treatment and underwent treatment for more than 1 month were classified as the TCM intervention cohort, i.e., the exposure group. Patients who did not receive adjunctive TCM treatment or who received adjunctive TCM treatment for less than 1 month were classified as the non-TCM intervention cohort, i.e., the non-exposed group. The main outcome indicators were the survival outcome and survival time of primary liver cancer patients. The propensity score inverse probability weighting method was used to balance the differences in the observed characteristics between the groups.ResultsThe primary cohort comprised 2,067 patients with primary liver cancer, including 462 patients who received adjunctive TCM treatment and 1,605 patients who did not receive adjunctive TCM treatment. Multiple logistic (binary) regression analysis results showed that adjunctive TCM treatment may reduce the mortality of primary liver cancer patients (regression coefficient = −0.82, P<0.001). The results of the Kaplan-Meier survival analysis indicated that the survival rate and median survival time of the exposure group before and after propensity score weighting were greater than those of the control group (P<0.0001). Multiple Cox regression analysis showed that adjunctive TCM treatment was an independent protective factor for survival in liver cancer patients (regression coefficient = −0.2477, hazard ratio (HR) = 0.7806, 95% confidence interval (CI) [0.6311–0.9655]), and cancer embolus was an independent risk factor (regression coefficient = 1.0546, HR = 0.3483, 95% CI [0.2831–0.4286]).ConclusionAdjuvant treatment with TCM has a protective effect on the prognosis of patients with primary liver cancer; it can reduce the mortality of primary liver cancer and prolong the survival time of patients. Cancer embolus is a risk factor that impacts the therapeutic effect of treatment in liver cancer patients.

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Background Discovering potential predictive risks in the super precarcinomatous phase of hepatocellular carcinoma (HCC) without any clinical manifestations is impossible under normal paradigm but critical to control this complex disease. Methods In this study, we utilized a proposed sequential allosteric modules (AMs)-based approach and quantitatively calculated the topological structural variations of these AMs. Results We found the total of 13 oncogenic allosteric modules (OAMs) among chronic hepatitis B (CHB), cirrhosis and HCC network used SimiNEF. We obtained the 11 highly correlated gene pairs involving 15 genes (r > 0.8, P < 0.001) from the 12 OAMs (the out-of-bag (OOB) classification error rate < 0.5) partial consistent with those in independent clinical microarray data, then a three-gene set (cyp1a2-cyp2c19-il6) was optimized to distinguish HCC from non-tumor liver tissues using random forests with an average area under the curve (AUC) of 0.973. Furthermore, we found significant inhibitory effect on the tumor growth of Bel-7402, Hep 3B and Huh7 cell lines in zebrafish treated with the compounds affected those three genes. Conclusions These findings indicated that the sequential AMs-based approach could detect HCC risk in the patients with chronic liver disease and might be applied to any time-dependent risk of cancer.