Objective To investigate the distribution of traditional Chinese medical syndromes and clinical characteristics of influenza in South of Five Ridges.Methods A retrospective analysis was carried out in 162 cases of influenza patients admitted from outpatient department,emergency department and inpatient department of the First Affiliated Hospital of Guangzhou University of Chinese Medicine from 2014 to 2016.The distribution of clinical manifestations and syndrome types of the included influenza patients was analyzed.Results The average age of the included influenza patients was 35.76 ± 11.4 years old.The clinical syndromes were mainly characterized by fever,aversion to cold and chills,fatigue and weakness.And damp-accumulation manifestations of heaviness in the body,poor appetite,dry mouth without willing to drink,nausea and vomiting were also predominant.The main syndrome types were wind-heat attacking defense phase syndrome,wind-cold fettering exterior syndrome,heat-toxin attacking lung syndrome,heat-toxin accumulating lung syndrome,and damp syndrome.Of the syndrome types,wind-heat attacking defense phase syndrome and heat-toxin attacking lung syndrome were the leading types,accounting for 77.79％ and interweaving with damp syndrome and heat-damp syndrome.Conclusion The syndromes of influenza patients in South of Five Ridges are usually complicated by damp syndrome or damp-heat syndrome,and the predominant syndrome type is wind-heat interweaved with damp syndrome,which is correlated with the climate being damp and hot in South of Five Ridges.

Objective To evaluate the potential feasibility of γ-H2AX foci as a biodosimetry after exposure to ionizing radiation by comparing DNA double-strand break repair kinetics in rat blood lymphocytes with that in human lymphocytes.Methods Peripheral blood lymphocytes separated from Sprague-Dawley(SD) male rats and healthy adults were exposed to γ-rays,and some rats were also subjected to total body irradiation.The inductions of DNA repair-related foci of γ-H2AX,pATM (S1981) and pDNA-PKcs (T2609) were detected with immunofluorescence staining technique at different time points post-irradiation,and the status of their co-localization was analyzed.Results The induction kinetics of γ-H2AX foci in rat lymphocytes was similar to that observed in human lymphocytes.The frequencies of γ-H2AX foci peaked at 30 min after γ-ray irradiation (trst =62.64,th =28.52,P ＜ 0.05),then decreased rapidly after 6 h post-irradiation (trat =45.96,th =14.80,P ＜0.05),and the residual foci number remained only about 3％-8％ of its maximal value at 24 h post-irradiation.At 30 min after γ-ray irradiation,the frequencies of pATM (S1981) and pDNA-PKcs (T2609) foci in rat and human lymphocytes significantly higher than those of nonirradiated control (trat =21.05,25.80,th =11.07,29.52,P ＜ 0.05),and the frequencies of co-localization of pATM (S1981) or pDNA-PKcs (T2609) foci with γ-H2AX foci also markedly increased by 26％-32％ in irradiated lymphocytes of rat and human (trat =5.34,9.14,thuman =18.32,51.28,P ＜0.05).Moreover,γ-H2AX foci incidence in rat lymphocytes in vitro was consistent with that induced by total body irradiation of rat.The number of γ-H2AX foci in irradiated rat lymphocytes increased with irradiation dose in a linear dose-dependent manner,its slope was similar to that of irradiated human lymphocytes reported by other laboratory.Conclusions Rat is a useful animal model to evaluate radiation biodosimetry with γ-H2AX foci in lymphocytes.The co-activation of ATM and DNA-PK plays an important role in DSB repair in the irradiated lymphocytes of rat and human.

Objective To determine the median effective dose (ED50 ) of ropivacaine for spinal anesthesia when combined with sufentanil in patients undergoing caesarean section. Methods Twenty-eight ASA Ⅰ or Ⅱ parturients, aged 18-40 yr, weighing 50-110 kg, undergoing cesarean section under combined spinal-epidural anesthesia, were enrolled in this study. Combined spinal-epidural anesthesia was performed at L2,3 interspace. The mixture of ropivacaine and 5 fig sufentanil was injected into the subarachnoid space over 30 s. The initial dose of ropivacaine was 11 mg. The dose was increased/decreased by 1 mg in the next patient. The ED50 and 95% confidence interval were calculated by up-and-down method. Results The ED50 of ropivacaine was 7.780 mg (95% confidence interval 6.850-8.836 mg). Conclusion When combined with sufentanil 5 μg, the ED50 of ropivacaine for spinal anesthesia is 7.780 mg in patients undergoing caesarean section.

OBJECTIVETo explore the relation between genetic polymorphisms of NQO1, GSTT1 and risks of chronic benzene poisoning (BP).

METHODSA case-control study was conducted. 152 BP patients and 152 workers occupationally exposed to benzene without poisoning manifestations were investigated. Polymerase chain reaction (PCR), denaturing high-performance liquid chromatography(DHPLC) and sequencing were used to detect the single nucleotide polymorphisms(SNPs) of the promoter and complete coding-region of NQO1 gene. Multiple PCR was used to detect GSTT1 genotype.

RESULTSIn smoking population, there was 7.73-fold (95% CI: 1.71-34.97, P = 0.010) of risk in BP subjects carrying NQO1c. 609 T/T genotype, compared with those carrying C/C and C/T. genotype. In drinking population, the individuals carrying the 6th extron of NQO1c. 609 T/T homozygote genotype had a 11.00-fold(95% CI: 1.89-63.83, P = 0.005) risk of BP compared to those with NQO1c. 609 C/T and C/C genotypes.

CONCLUSIONThe subjects carrying NQO1c. 609 T/T genotype and together with the habit of smoking or drinking may be more susceptible to BP.

Benzene ; poisoning ; Case-Control Studies ; Ethanol ; adverse effects ; Genotype ; Glutathione Transferase ; genetics ; Humans ; NAD(P)H Dehydrogenase (Quinone) ; genetics ; Occupational Diseases ; genetics ; Occupational Exposure ; Polymorphism, Single Nucleotide ; Smoking ; adverse effects

Objective:To develop a prototype artificial intelligence immunofluorescence image recognition system for classification of antinuclear antibodies in order to meet the growing clinical requirements for an automatic readout and classification of immunof luorescence patterns for antinuclear antibody (ANA) images.Methods:Immunofluorescence images with positive results of ANA in Xinhua Hospital Affiliated to Shanghai Jiao Tong University School of Medicine from April 2020 to December 2021 were collected. Three senior technicians independently and in parallel interpreted the Immunofluorescence images to determine the ANA results. Then the images were labeled according to the ANA International Consensus on Fluorescence Patterns (ICAP) classification criteria. There were 7 labeled groups: Fine speckled, Coarse speckled, Homogeneous, nucleolar, Centromere, Nuclear dots and Nuclear envelope. Each group was randomly divided into training dataset and validation dataset at a ratio of 9∶1 by using random number table. On the deep learning framework PyTORCH 1.7, the convolutional neural network (CNN) training platform was constructed based on ResNet-34 image classification network, and the automatic ANA recognition system was established. After the model was established, the test set was set up separately, the judgment results of the model were output by ranking the prediction probability, with the results of the 2 senior technicians was taken as "golden standard". Parameters such as accuracy, precision, recall and F1-score were used as indicators to evaluate the performance of the model.Results:A total of 23138 immunofluorescence images were obtained after segmentation and annotation. A total of 7 models were trained, and the effects of different algorithms, image processing and enhancement methods on the model were compared. The ResNet-34 model with the highest accuracy andswas selected as the final model, with the classification accuracy of 93.31%, precision rate of 91%, and recall rate of 90% and F1-score of 91% in the test set. The overall coincidence rate between the model and manual interpretation was 90.05%, and the accuracy of recognition of nucleolus was the highest, with the coincidence rate reaching 100% in the test set.Conclusion:The current AI system developed based on deep learning of the ANA immunofluorescence images in the present study showed the ability to recognize ANA pattern, especially in the common, typical, simple pattern.

Objective:The decline in nutritional status in patients with severe pneumonia may contribute to an increase in in-hospital mortality. Enteral nutrition support can improve the nutritional status of patients, and is relatively easy to manage, with low cost and fewer serious complications. On the other hand, adverse reactions such as gastric retention and gastric microbiota translocation may increase the incidence of nosocomial pneumonia and increase the uncertainty of patient prognosis. There is no predictive model for in-hospital death in severe pneumonia patients receiving enteral nutrition support. The objective of this study was to investigate the risk factors of in-hospital death in patients with severe pneumonia receiving enteral nutrition support and to establish a prognostic model for such patients.Methods:This was a single-center retrospective study. Patients with severe pneumonia who were hospitalized in Peking Union Medical College Hospital and received enteral nutrition support were included from January 1, 2015 to December 31, 2020. The primary endpoints were in-hospital mortality rate and unordered discharge rate. The independent risk factors were determined using univariate and multifactorial logistic regression analysis, the nomogram scoring model was constructed, and the decision curve analysis (DCA) was performed.Results:A total of 632 severe pneumonia patients who received enteral nutrition support were included. Patients were divided into death and survival groups according to the presence or absence of in-hospital death, and 24 parameters were found with significant differences between groups. Nine parameters were independent predictors of mortality, namely the duration of ventilator use, the presence of malignant hyperplasia diseases, the maximal levels of platelet and prothrombin during hospitalization, and the nadir levels of alanine aminotransferase, serum albumin, sodium, potassium, and blood glucose. Based on these variables, a risk prediction scoring model was established (ROC = 0.782; 95% CI: 0.744 to 0.819, concordance index: 0.772). Calibration curves, DCA, and clinical impact curve were plotted to evaluate the goodness of function, accuracy, and applicability of the predictive nomogram, using the training and test sets. Conclusion:This study summarized the clinical characteristics of patients with severe pneumonia receiving enteral nutrition support and developed a scoring model to identify risk factors and establish prognostic models.