Adult ; COVID-19/virology* ; China ; Cross Infection/virology* ; Epidemics ; Female ; Health Personnel/statistics & numerical data* ; Hospitals/statistics & numerical data* ; Hospitals, Isolation/statistics & numerical data* ; Humans ; Male ; Multiple Pulmonary Nodules/diagnostic imaging* ; Retrospective Studies ; SARS-CoV-2/physiology* ; Tomography, X-Ray Computed ; Young Adult

Based on fingerprint and network pharmacology,the whole process quality control of Zhuru Decoction was conducted and efficacy-related substances were predicted.The fingerprints of raw materials,decoction pieces and Zhuru Decoction were established,and 25 common peaks were identified,including 9 common chromatographic peaks of 3'-hydroxy puerarin,puerarin,3'-methoxy puerarin,puerarin,aperioside,daidzin,daidzein,liquiritin,glycyrrhizic acid and 6-gingerol, with similarity all greater than 0.95.The main groups of pharmacodynamic substances can be transferred from raw materials,decoction pieces to Zhuru Decoction step by step,with a clear affiliation relationship.Based on the testability and traceability,the active ingredients were screened,and the network relationship of "component-target-pathway" was constructed and analyzed for the nine chemical components screened by network pharmacology.The enriched pathways included energy metabolism,alcoholism,and smooth muscle contraction and relaxation-related pathways.The nine active components of Zhuru Decoction may achieve the effects of clearing heat, alleviating a hangover, harmonizing stomach and stopping vomiting through these signaling pathways.Based on transitive and traceable properties of the above 9 components as well as their close relationship to the efficacy of Zhuru Decoction,these 9 components can be identified as potential efficacy-related substances and provide basis for the overall quality control of Zhuru Decoction.
Drugs, Chinese Herbal ; Glycyrrhizic Acid ; Prescriptions ; Quality Control

Objective To discuss the application value of CT scanning technology in cause of death determination of medical dispute cases. Methods From July 2017 to December 2018, postmortem CT imaging data of 12 medical dispute cases were collected. CT imaging diagnosis results and anatomy findings as well as differences between antemortem and postmortem CT diagnosis were compared. The advantages and disadvantages of CT routine tests of the cadavers in terms of the diagnosis of disease and damage were analyzed. Results The comparison between CT imaging diagnosis and anatomical findings showed that CT scans had advantages in the diagnosis of disease and damage with large differences in density changes, such as atelectasis, pneumonia, calcification, fracture and hemorrhage, etc. The comparison of CT diagnosis in antemortem and postmortem examination showed that the cadavers of medical dispute cases were well preserved and that postmortem CT scan was meaningful for the diagnosis of antemortem diseases. Conclusion Virtual anatomy technology has a relatively high application value in postmortem examination of medical dispute cases. It can provide effective information for the appraisers before the autopsy and can also provide a reference for cause of death analysis when the anatomy cannot be performed.
Autopsy ; Cadaver ; Dissent and Disputes ; Humans ; Postmortem Changes ; Tomography, X-Ray Computed

Objective:To analyze the dynamic change rule of gut microbiota in patients with extremely severe burns using 16S ribosomal RNA (rRNA) high-throughput sequencing technology.Methods:Five patients with extremely severe burns who were admitted to Hwa Mei Hospital of University of Chinese Academy of Sciences from February to June 2017 and conformed to the inclusion criteria were included in the prospective observational study. All patients were males with age of 32-48 years. Fecal samples were collected in the shock stage (within 3 days after injury), early stage of acute infection (4-14 d after injury), middle stage of acute infection (15-28 d after injury), late stage of acute infection (from 29 d after injury to 1 week before discharge) and within 1 week before discharge. The number of samples was 5 in each stage. The fecal pH value was measured using a pH meter. High-throughput sequencing technology was applied for sequencing of 16S rRNA V3 and V4 regions of fecal samples. QIIME software was used to analyze the number of operational taxonomic units (OTUs), α diversity (Chao1 index and Shannon index), and the relative abundance of gut microbiota at the phylum and family levels. Unweighted pair group method with arithmetic mean clustering method was used to analyze the β diversity of gut microbiota, and Tax4Fun was used to predict functional changes of gut microbiota. Data were statistically analyzed with one-way analysis of variance for repeated measurement, Bonferroni method, Wilcoxon rank sum test for paired samples, and Bonferroni correction.Results:(1) The pH value of feces in the early and middle stages of acute infection in patients with extremely severe burns in this group was 7.40±0.45 and 7.56±0.45 respectively, which were significantly higher than 6.68±0.36 in the shock stage ( P<0.05 or P<0.01). (2) A total of 2 333 584 efficient and high-quality sequences were obtained, and the length of the sequences was about 415 bp. A total of 1 209 OTUs were obtained. The sequencing coverage of all samples was over 99.0%. The number of OTUs and Chao1 index in the early, middle, and late stages of acute infection in patients with extremely severe burns in this group were significantly lower than those in the shock stage ( Z=2.023, P<0.05). The number of OTUs and Chao1 index within 1 week before discharge were significantly higher than those in the early, middle, and late stages of acute infection, and Shannon index within 1 week before discharge was significantly higher than that in the early and middle stages of acute infection ( Z=2.023, P<0.05). (3) The structure of gut microbiota in the shock stage in patients with extremely severe burns in this group was highly similar to that within 1 week before discharge, and lowly similar to that in the early, middle, and late stages of acute infection. The analysis of individual sample showed that the clustering rule of most of the samples was in accordance with that of the staged samples. The weighted Unifrac distance of gut microbiota in the shock stage was significantly shorter than that in the early, middle, and late stages of acute infection ( Z=3.326, 2.570, 2.690, P<0.05 or P<0.01), while the weighted Unifrac distance of gut microbiota in the other stages was similar. (4) At the phylum level, compared with that in the shock stage, the relative abundance of Firmicutes was decreased in the early, middle, and late stages of acute infection, while the relative abundance of Bacteroidetes and Proteobacteria increased. However, the relative abundance of the above three phyla within 1 week before discharge was similar to that in the shock stage. At the family level, the top five dominant bacteria in relative abundance in different stages after injury were quite different. The relative abundance of dominant five family bacteria in the shock stage was decreased in the early, middle, and late stages of acute infection. The relative abundance of non-dominant bacteria such as Enterobacteriaceae, Streptococcaceae, and Bacteroidaceae in the shock stage increased significantly in the early, middle, and late stages of acute infection, which became new dominant families in these stages. The relative abundance of some acid-producing bacteria within 1 week before discharge resumed to the similar level in the shock stage. (5) Functions such as some amino acid metabolism, glycolysis and gluconeogenesis, and pyruvate metabolism of gut microbiota were obviously weaker in the early and middle stages of acute infection than those in the shock stage. Functions such as some amino acid metabolism and carbohydrate metabolism of gut microbiota were significantly enhanced in the late stage of acute infection compared with that in the shock stage. The distributions of functional genes in gut microbiota were similar between the shock stage and within 1 week before discharge. Conclusions:The internal environment and gut microbial compositions in extremely severe burned patients change significantly in the early and middle stages of acute infection. The pH value increases, the bacterial species and diversity decrease, especially the relative abundance of acid-produced bacteria is significantly reduced, which gradually recover with the improvement of the patient′s condition. The pH value and the changes of Proteobacteria and acid-producing bacteria could be considered as suitable parameters for reflecting the disorder level of gut microbiota in patients with extremely severe burns.

Objective: To analyze clonal evolution and clinical significance of trisomy 8 in patients with acquired bone marrow failure. Methods: The clinical data of 63 patients with acquired bone marrow failure accompanied with isolated trisomy 8 (+8) from June 2011 to September 2018 were analyzed retrospectively, the clonal evolution patterns and relationship with immmunosuppressive therapy were summarized. Results: Totally 24 male and 39 female patients were enrolled, including 39 patients with aplastic anemia (AA) and 24 patients with relatively low-risk myelodysplastic syndrome (MDS) . Mean size of+8 clone in MDS patients[65% (15%-100%) ]was higher than that of AA patients[25% (4.8%-100%) , z=3.48, P=0.001]. The patients were was divided into three groups (<30%, 30%-<50%,and ≥50%) according to the proportion of+8 clone. There was significant difference among the three groups between AA[<30%:55.6% (20/36) ; 30-50%: 22.2% (8/36) ; ≥50%22.2% (8/36) ]and MDS patients[<30%:19.0% (4/21) ; 30%-<50%:19.0% (4/21) ; ≥50%61.9% (13/21) ] (P=0.007) . The proportion of AA patients with+8 clone <30% was significantly higher than that of MDS patients (P=0.002) ; and the proportion of AA patients with+8 clone ≥50%was significantly lower than that of MDS patients (P=0.002) . The median age of AA and MDS patients was respectively 28 (7-61) years old and 48.5 (16-72) years old. Moreover, there was no correlation between age and+8 clone size in AA or MDS (r_s=0.109, P=0.125; r_s=-0.022, P=0.924, respectively) . There was statistical difference in total iron binding capacity, transferrin and erythropoietin between high and low clone group of AA patients (P=0.016, P=0.046, P=0.012, respectively) , but no significant difference in MDS patients. The immunosuppressive therapy (IST) efficacy of AA and MDS patients was respectively 66.7% and 43.8% (P=0.125) . Comparing with initial clone size (27.3%) , the +8 clone size (45%) of AA patients was increased 1-2 year after IST, but no statistical difference (z=0.83, P=0.272) . Consistently, there was no significant change between initial clone size (72.5%) and 1-2 year clone size (70.5%) after IST in MDS patients. There was no significant difference in IST efficient rate between +8 clone size expansion and decline group of in AA patients at 0.5-<1, 1-2 and>2 years after IST. We found four dynamic evolution patterns of +8 clone, which were clone persistence (45%) , clone disappearance (30%) , clone emergence (10%) and clone recurrence (15%) . Conclusions AA patients had a low clone burden, while MDS patients had a high burden of +8 clone. The +8 clone of AA patients didn’t significantly expanded after IST, and the changes of +8 clone also had no effect on IST response.