Children and adults differ significantly in physiology,biochemistry and immune function,which leads to sig-nificant differences in blood transfusion strategies between children and adults.To guide the clinical transfusion practice of pediatric patients and improve the prognosis of children,the National Health Commission organized the formulation and re-lease of the health industry standard Guideline for Pediatric Transfusion(WS/T 795-2022).This paper will briefly introduce some concepts that help understand of the Standard and the preparation process of the Standard,and explain and interpret the preparation of the"scope","general provisions"and"factors to consider"of the Standard,hoping to contribute to the understanding and implementation of the Standard.

Objective:To explore the feasibility of a classification prediction model for gamma pass rates (GPRs) under different intensity-modulated radiation therapy techniques for pelvic tumors using a radiomics-based machine learning approach, and compare the classification performance of four integrated tree models.Methods:With a retrospective collection of 409 plans using different IMRT techniques, the three-dimensional dose validation results were adopted based on modality measurements, with a GPR criterion of 3%/2 mm and 10% dose threshold. Then prediction were built models by extracting radiomics features based on dose documentation. Four machine learning algorithms were used, namely random forest (RF), adaptive boosting (AdaBoost), extreme gradient boosting (XGBoost), and light gradient boosting machine (LightGBM). Their classification performance was evaluated by calculating sensitivity, specificity, F1 score, and AUC value. Results:The RF, AdaBoost, XGBoost, and LightGBM models had sensitivities of 0.96, 0.82, 0.93, and 0.89, specificities of 0.38, 0.54, 0.62, and 0.62, F1 scores of 0.86, 0.81, 0.88, and 0.86, and AUC values of 0.81, 0.77, 0.85, and 0.83, respectively. XGBoost model showed the highest sensitivity, specificity, F1 score, and AUC value, outperforming the other three models. Conclusions:To build a GPR classification prediction model using a radiomics-based machine learning approach is feasible for plans using different intensity-modulated radiotherapy techniques for pelvic tumors, providing a basis for future multi-institutional collaborative research on GPR prediction.

Chronic obstructive pulmonary disease (COPD) is an important healthcare problem worldwide. Often, glucocorticoid (GC) resistance develops during COPD treatment. As a classic hypoglycemic drug, metformin (MET) can be used as a treatment strategy for COPD due to its anti-inflammatory and antioxidant effects, but its specific mechanism of action is not known. We aimed to clarify the role of MET on COPD and cigarette smoke extract (CSE)-induced GC resistance. Through establishment of a COPD model in rats, we found that MET could improve lung function, reduce pathological injury, as well as reduce the level of inflammation and oxidative stress in COPD, and upregulate expression of nuclear factor E2-related factor 2 (Nrf2), heme oxygenase-1 (HO-1), multidrug resistance protein 1 (MRP1), and histone deacetylase 2 (HDAC2). By establishing a model of GC resistance in human bronchial epithelial cells stimulated by CSE, we found that MET reduced secretion of interleukin-8, and could upregulate expression of Nrf2, HO-1, MRP1, and HDAC2. MET could also increase the inhibition of MRP1 efflux by MK571 significantly, and increase expression of HDAC2 mRNA and protein. In conclusion, MET may upregulate MRP1 expression by activating the Nrf2/HO-1 signaling pathway, and then regulate expression of HDAC2 protein to reduce GC resistance.

AIM: To explore the effect of Huatanjiangqi capsule medicated serum (HTJQ) on the resistance of human bronchial epithelial cells (16HBE) to glucocorticoid (GC) stimulated by cigarette smoke extract (CSE). METHODS: After 16HBE cells were treated with HTJQ, the effects of different concentrations of HTJQ on the viability of 16HBE cells were determined by CCK-8 method. 16HBE cells were pretreated with HTJQ, and then cultured with dexamethasone (DEX) and lipopolysaccharide (LPS) for 24 hours, the effect of HTJQ on glucocorticoid (GC) resistance of 16HBE cells was determined by Enzyme-linked immunosorbent assay (ELISA). The effects of HTJQ, sulforaphane (SFN) and glutathione (GSH) on the expression of NF-E2-related factors 2 (Nrf2), Heme oxygenase-1 (HO-1) and histone deacetylase 2 (HDAC2) in 16HBE cells stimulated by CSE were measured by Western blot, and the effects of HTJQ, SFN and GSH on interleukin-8 (IL-8) in 16HBE cells were measured by ELISA. RESULTS: HTJQ promoted the proliferation of 16HBE cells at 1 h, 2 h and 4 h, the results of ELISA and Western blot showed that CSE induced GC resistance and decreased the expression of Nrf2, HO-1 and HDAC2 in 16HBE cells, HTJQ significantly decreased IL-8 and improved GC sensitivity of 16HBE cells (P<0.01), and up-regulated the expression of Nrf2, HO-1 and HDAC2 (P<0.01). In addition, HTJQ significantly up-regulated the level of GSH in 16HBE cells (P<0.01). Nrf2 agonists SFN and GSH significantly improved the glucocorticoid sensitivity of 16HBE cells (P<0.01), and up-regulated the expression of Nrf2, HO-1 and HDAC2 (P<0.01). CONCLUSION: HTJQ improves the GC resistance of 16HBE cells by up-regulating the expression of Nrf2/HDAC2 protein and the level of intracellular GSH.

During the prevention and control of new coronavirus pneumonia, Fangzhuang community health service center gave full play the advantages of internet technology, developed and implemented the Intelligent Family Doctors Optimized Coordination Model for epidemic prevention in the community. An epidemic prevention and control team was established in the center, the team carried out the epidemic prevention and control with the opening of health records and by using "doctors around" APP. The center also opened the intelligent voice return visits, the 24-hour service hotline, and WeChat public column to provide consultation for the community residents; it also strentherned pre-check triage, realized the medical insurance sharing and the other measures. All these measures enabled the residents to have a correct understanding of the epidemic situation, eased their psychological panic, enhanced their sense of gain, and made residents more convenient to seek medical treatment nearby reducing interpersonal contact and aggregation, reduced the risk of cross-infection, and achieved accurate health management among community residents during COVID-19 epidemic.

The community is the first line of endemic prevention and control. Facing the challenge of epidemic outbreak, Fangzhuang Community Health Service Center applied the intelligent family doctor model to carry out joint community prevention and control of coronavirus disease 2019 (COVID-19) epidemic. The intelligent family doctor model is a people-centered, information-based approach, which integrates community resources to carry out health education, counseling and public opinion guidance. With this model the community health service center can effectively screen and follow up the key groups to strengthen the joint prevention and control of COVID-19; at the same time it also can manage the chronic disease and the elderly care. This article introduces the intelligent family doctor model, and analyzes its advantages and existing problems, to provide references for community epidemic prevention and control.

Objective: Apolipoprotein E (ApoE) is mainly synthesized in the liver. So far, it is unknown the relationship among APOE gene polymorphisms and WML, brain atrophy. Therefore, the aim of the study was to assess the associations of APOE gene polymorphisms in patients with WML and brain atrophy. Methods: A total of 58 patients with WML, 128 patients with brain atrophy, 112 patients with co-occurrence of WML and brain atrophy and 95 healthy elderly volunteers were recruited from Renmin Hospital of WuHan University. Results: Allele E3 was the most common allele. The alleles E2 had significantly higher levels of ApoB and lower age in WML group. The alleles E2 was associated with the lower level of ApoB, LDL-Ch, TCh, and sdLDL in co-occurrence group. The E3/E3 genotype has higher level of sdLDL, but lower age and female frequency in WML. The E3/E4 genotype had higher level of TG, but lower age in WML. Gender, Age, E2, Hyperhomocysteinemia and UA were also significantly associated with disease progression. Conclusion This study found that clinical data, lipids and metabolic complications were closely related to ApoE genotypes and alleles, and also disease progression and type.

Objective:To compare the accuracy of influenza-like illness (ILI) surveillance by automatic computer analysis based on electronic medical records and by doctor’s report.Methods:A total of 3 542 patients who presented to Yichang Central Hospital fever clinic, respiratory department or emergency department between April to October 2019 with an ICD-10 code for acute respiratory illness (J00-J22) and complete electronic medical information of ILI related syndromes were drawn as the study sample. Taking the classification of the study sample according to the ILI case definition by influenza surveillance professionals as the gold standard, draw the receiver operating characteristic (ROC) curve and calculate sensitivity, specificity, diagnostic consistency to compared the accuracy of ILI surveillance by automatic computer analysis and by doctor's report.Results:Median age of 3 542 cases was 30 (24, 38) years old; 1 179 cases (33.29%) compliance with the case definition, ILI reported by doctors was 1 306 cases (36.87%), and computer automatic identification ILI were 1 150 cases (32.47%); 1 391 (39.27%) cases were men. The results of automatic computer analysis and doctor report consistency of kappa values with gold standard judgment were 0.97 and 0.66 respectively; area under the ROC curve was 0.98 and 0.84, respectively. And the sensitivity and specificity of automatic computer analysis were higher than that of doctor's report (all P values were <0.001), the sensitivity was 96.95% and 82.27%, and the specificity was 99.70% and 85.78%, respectively. Conclusion:The automatic computer analysis based on electronic medical records can identified ILI cases with good sensitivity and specificity in ILI case surveillance.

Objective:To compare the accuracy of influenza-like illness (ILI) surveillance by automatic computer analysis based on electronic medical records and by doctor’s report.Methods:A total of 3 542 patients who presented to Yichang Central Hospital fever clinic, respiratory department or emergency department between April to October 2019 with an ICD-10 code for acute respiratory illness (J00-J22) and complete electronic medical information of ILI related syndromes were drawn as the study sample. Taking the classification of the study sample according to the ILI case definition by influenza surveillance professionals as the gold standard, draw the receiver operating characteristic (ROC) curve and calculate sensitivity, specificity, diagnostic consistency to compared the accuracy of ILI surveillance by automatic computer analysis and by doctor's report.Results:Median age of 3 542 cases was 30 (24, 38) years old; 1 179 cases (33.29%) compliance with the case definition, ILI reported by doctors was 1 306 cases (36.87%), and computer automatic identification ILI were 1 150 cases (32.47%); 1 391 (39.27%) cases were men. The results of automatic computer analysis and doctor report consistency of kappa values with gold standard judgment were 0.97 and 0.66 respectively; area under the ROC curve was 0.98 and 0.84, respectively. And the sensitivity and specificity of automatic computer analysis were higher than that of doctor's report (all P values were <0.001), the sensitivity was 96.95% and 82.27%, and the specificity was 99.70% and 85.78%, respectively. Conclusion:The automatic computer analysis based on electronic medical records can identified ILI cases with good sensitivity and specificity in ILI case surveillance.

Objective : To understand the spatial distribution of multidrug resistant/rifampicin resistant pulmonary tuberculosis（MDR/RR PTB）in Wenzhou from 2014 to 2017,and to provide the scientific basis for MDR/RR TB control and prevention. Methods : The data of MDR/RR PTB cases in Wenzhou from 2014 to 2017 were collected from the Tuberculosis Management Information System of the Chinese Disease Prevention and Control Information System,and was associated with the geographic information database of Wenzhou Survey and Mapping Research Institute. The global spatial autocorrelation analysis was carried out by ArcGIS 10.1 to determine if there was spatial clustering of MDR/RR PTB cases in Wenzhou. The specific clustering areas of the MDR/RR PTB in Wenzhou was analyzed by SaTScan 9.3 and presented by ArcGIS. Results : There were 452 MDR/RR PTB cases reported in Wenzhou from 2014 to 2017,with a total registration rate of 4.74/100 000. The incidence rate of MDR/RR PTB in Wenzhou was unevenly distributed;the areas with registration rates of more than 7.45/100 000 were the north-central parts of Yongjia,the south-central parts of Yueqing and the east-central parts of Wencheng. The results of global spatial autocorrelation analysis showed that there were obvious clustering for MDR/RR PTB in Wenzhou（Moran's I=0.321,Z=7.352,P<0.001）. The spatial scanning found two clusters：20 towns/streets in the southeastern part of Yongjia and the south of Yueqing were the primary clustering areas（RR=2.213,LLR=22.353,P<0.001）;Yangyi Street and Shuangyu Street in Lucheng were the secondary clustering areas（RR=2.488,LLR=9.889,P=0.004）. Conclusion The MDR/RR PTB cases reported from 2014 to 2017 in Wenzhou had spatial clustering. The high-incidence areas were in the southeast of Yongjia,south of Yueqing,Yangyi Street and Shuangyu Street of Lucheng.