This article reported a patient who initially presented with insomnia complaints and was subsequently diagnosed with severe obstructive sleep apnea （OSA） on polysomnography （PSG）. The patient tried continuous positive airway pressure （CPAP）but gave up because wear the ventilator made it more difficult to fall asleep. Then the patient only received group cognitive behavioral therapy for insomnia （CBT-I）， which not only alleviated insomnia severity but also promoted severe OSA into mild status. Such case suggested that， firstly， due to the high comorbidity of insomnia and OSA， evaluation of OSA should be considered a part worth enough attention of the clinical diagnosis and treatment of insomnia patients. Secondly， by relieving insomnia， CBT-I can alleviate both nocturnal apnea and daytime somnolence in patients with comorbid insomnia and sleep apnoea （COMISA）， so the application of CBT-I should be emphasized in the treatment of such patients. ［Funded by the Central Government-guided Local Science and Technology Development Fund Project （number， 2022ZY0028）］

Objective To establish a differential model of phlegm and blood stasis pattern and qi deficiency and blood stasis pattern in stable angina pectoris using radiomics.Methods A total of 91 patients with stable angina pectoris who underwent coronary artery CT angiography in Affiliated Hospital of Liaoning University of Traditional Chinese Medicine from January 2021 to January 2022 were collected,including 47 cases of phlegm and blood stasis pattern and 44 cases of qi deficiency and blood stasis pattern.The patients were divided into train set(64 cases)and test set(27 cases)according to the ratio of 7∶3 by stratified random sampling method.3D-slicer software was used to extract the radiomics features of pericoronary adipose tissue(PCAT)images.Principal component analysis was used to visualize the distribution of radiomics features of pattern of phlegm and blood stasis and pattern of qi deficiency and blood stasis.The least absolute shrinkage and selection operator regression analysis and support vector machine decreasing feature elimination were used for feature selection.The multinomial logistics regression was used for model construction.The receiver operating characteristic(ROC)curve was used to verify the model in the train set and the test set to evaluate the effectiveness of the radiomics features in differentiating phlegm and blood stasis pattern and qi deficiency and blood stasis pattern.Finally,Spearman coefficient was used to analyze the correlation between the differential features and clinical physicochemical data.Results A total of 837 radiomics features were extracted from PCAT images by 3D-slicer software.In the principal component analysis,PC1 and PC2 explained 77.9%and 8.1%of the total variance,respectively,and there was a relatively obvious separation trend between the two pattern groups.After feature screening,7 radiomics features were used to construct the differential model of phlegm and blood stasis pattern and qi deficiency and blood stasis pattern.The area under the ROC curve(AUC)of the differential model was 0.844 in the train set and 0.834 in the test set.Spearman correlation analysis showed that the differential features were significantly correlated with cTnI,neutrophil,triglyceride,total cholesterol,and leukocyte.Conclusion The CT radiomics model based on PCAT has a high discrimination efficiency for stable angina pectoris with phlegm and blood stasis pattern and qi deficiency and blood stasis pattern.

Objective Under the background of"breaking the Five-Only"and the evaluation reform of healthcare professionals'titles,it analyzed the willingness of healthcare professionals in public hospitals to disseminate health knowledge and its incentives and constraints.Furthermore,it explored potential pathways to improve the willingness of healthcare professionals to popular science and disseminate health knowledge.Methods From November to Decem-ber 2022,a self-designed online questionnaire was used to survey healthcare professionals in four tertiary hospitals in Shanghai.The questionnaire included basic information of healthcare professionals,analysis of the current situa-tion and demands of healthcare professionals in health knowledge dissemination,willingness of healthcare profes-sionals to disseminate health knowledge and influencing factors.Results A total of 762 healthcare professionals partici-pated in this survey,79.9%(608/762)expressed willingness to promote the dissemination of health knowledge.A multiple-factor logistic regression analysis revealed that intermediate professional title,achieving personal value and so-cial responsibility,increasing patient resources,professional title promotion,science promotion-related awards,being included in performance appraisals,and difficulty in capturing science promotion skills were the influential factors affecting the dissemination of health knowledge among healthcare professionals(P＜0.05).Conclusion The willing-ness of healthcare professionals to disseminate health knowledge was strong,and hospitals should motivate health-care professionals to disseminate health knowledge through building a long-term incentive mechanism,strengthening training in science popularization ability,and improving humanistic qualities.

Objective To screen Cuproptosis genes and characteristic genes for differential prognosis in acute mye-loid leukemia(AML)and explore their prognosis in AML as well as their biological roles and correlations in the immune and tumor microenvironment.Methods AML clinical,transcriptome,genomic,and copy number data were downloaded from three major databases,TCGA,GEO,and UCSC,and Cuproptosis genes were collected from published studies.From the perspective of multiomics,the effects of Cuproptosis gene and characteristic gene on survival,immunity,tumor microenvironment,stem cell correlation and drug sensitivity were studied by various bioinformatics methods,meta-analysis and secondary typing.Results One Cuproptosis gene was identified as a differential prognostic gene in AML and five characteristic genes were identified as influencing the prognosis of AML patients by influencing Cuproptosis,and a prognostic model was established.The differential genes were mainly concentrated in mitochondrial activity,REDOX enzyme and energy metabolism.In terms of immunity,macrophage M0,neutrophils,activated memory CD4 T cells and Tregs were positively correlated with risk score,while macro-phage M2,resting mast cells,immature CD4 T cells,helper follicular T cells and memory B cells were negatively correlated with risk score.In terms of tumor microenvironment,the immune cell score of the low-risk group was lower than that of the high-risk group,and in the total score,the tumor microenvironment score of the low-risk group was also lower than that of the high-risk group,indicating that the tumor purity of the high-risk group was lower than that of the low-risk group.However,there was no significant association between stem cells in the high-risk and low-risk groups,and a total of 14 drugs were found to be sensitive to treat AML.Conclusion Cuproptosis gene and characteristic gene are closely related to immune and tumor microenvironment in AML by constructing a prognostic model of AML.

Objective:To explore the relationship between the triglyceride glucose (TyG) index and the risk of developing hypertension among rural Chinese adults.Methods:A prospective cohort study was conducted from 2007 to 2008, involving 20 194 adults selected through random cluster sampling from a rural community in Luoyang City, Henan Province. Follow-ups were carried out in 2013-2014 and 2018-2020. After excluding participants with hypertension at baseline, those with missing TyG index data, individuals who passed away during follow-up, and those with incomplete hypertension status at the second visit, 9 802 participants were included in the analysis. Baseline and follow-up assessments included questionnaire interviews, physical measurements (including blood pressure), and blood sample collection for fasting lipid and glucose levels. Participants were divided into four groups according to TyG index quartiles, and a modified Poisson regression model was utilized to assess the association between TyG index quartiles and hypertension risk.Results:The study cohort comprised 9 802 participants with a median age of 48 (39, 57) years, including 3 803 males (38.80%). Participants were distributed across TyG index quartiles as follows: TyG<8.2 group (2 224 individuals), TyG 8.2-8.5 group (2 653 individuals), TyG 8.6-8.9 (2 441 individuals), and TyG≥9.0 (2 484 individuals). Over a follow-up period of (11.1±1.3) years, 3 378 subjects developed hypertension, resulting in a cumulative incidence of 34.46% (3 378/9 802). The risk of hypertension increased with higher TyG index quartiles ( Ptrend<0.05). Compared to the TyG<8.2, the TyG 8.2-8.5 ( RR=1.11, 95% CI 1.01-1.22, P=0.023), TyG 8.6-8.9 ( RR=1.16, 95%CI 1.06-1.27, P=0.023), and TyG≥9.0 ( RR=1.20, 95%CI 1.10-1.31, P=0.023) exhibited increased hypertension risk after adjusting for age, gender, educational level, and other potential confounders. Subgroup analyses based on gender and age at baseline yielded results consistent with the main analysis. Conclusions:The TyG index is positively correlated with the risk of developing hypertension in the rural adult population.

Objective:To discuss the association between occupational acid fog exposure and accelerated biological aging of the workers,and to clarify its related risk factors.Methods:A total of 341 male workers exposed to occupational acid fog and 201 male workers without occupational exposure were selected as the study subjects,and they were divided into exposure group and control group,respectively.The general informations of the subjects in two groups were collected through questionnaires and physical examinations.The levels of red blood cell count(RBC),platelet count(PLT),albumin(ALB),urea(Urea),creatinine(CR),triglycerides(TG),total cholesterol(TC),glycated hemoglobin(HBA1c),and high-sensitivity C-reactive protein(Hs-CRP)in serum of the subjects in two groups were detected.The Klemera-Doubal method(KDM)was used to construct the composite aging measure,KDM-biological age(BA)(KDM-BA).The model parameters were trained using samples from the 2009 China Health and Nutrition Survey(CHNS)Database to calculate the BA acceleration of the subjects in two groups;stratified analysis based on the population characteristics was conducted to analyze the BA of the subjects in two groups with different population characteristics;generalized linear model was used to analyze the factors influencing BA acceleration due to acid fog exposure.Results:The model parameters were trained using samples from the 2009 CHNS Database,including 8 133 cases aged 20-79 years,of which 3 788 were male.The levels of Urea,CR,HBA1c,ALB,and TC,as well as systolic blood pressure(SBP),total working years,sleep duration,and body mass index(BMI)of the subjects between two groups had significant differences(P<0.05).Compared with control group,the BA acceleration of the subjects in exposure group was significantly increased(P<0.05).In entire population and exposure group,the BA acceleration in the smokers was significantly higher than that in the non-smokers(P<0.05).In entire population,control group,and exposure group,the BA accelerations of the subjects in different BMI groups were significantly decreased with the increase of BMI(P<0.05).Compared with control group,the BA acceleration of the subjects in exposure group was significantly increased(P<0.05),including those under 40 years old,with total working years of 4-7 years,Han nationality,unmarried,smokers,and sleep duration 6-7 h,and with overweight.Acid fog exposure,smoking,and BMI were associated with the BA acceleration(β=0.72,95%CI:0.24-1.21;β=0.59,95%CI:0.11-1.06;β=-0.29,95%CI:-0.35—-0.22).Conclusion:Occupational acid fog exposure may accelerate the biological aging in the workers,and acid fog is a risk factor to accelerate the biological aging of the body.

Objective:Integrating genes and GEO database related cuproptosis chips,to analyze connection between cupropto-sis genes,immune infiltration and myocardial infarction(MI),construct risk prediction model,predict Western medicine and Chi-nese medicine,analyze miRNA-mRNA regulatory network,and to provides a new research direction for the future study of MI-related cuproptosis mechanism and immune infiltration.Methods:By GEO database retrieval of MI related chips,standardized processing and MI-related cuproptosis genes screening were performed,and immunoinfiltration analysis and quantification were performed based on the treated gene expression matrix,correlation between immune infiltrating cells and function was analyzed,as well as their differ-ences in MI group and the control group.Cuproptosis genes that most related to MI in immune infiltration were screened out,and the risk model was constructed to analyze the risk probability of cuproptosis genes in MI.The Enrichr website and Coremine Medical data-base were used to predict cuproptosis-related genes in MI in Western medicine and traditional Chinese medicine.Finally,the up-stream mirnas of FDX1 and SLC31A1 were predicted by miRTarBase,Starbase and Targetscan databases,and miRNA-mRNA regula-tory networks were constructed.Results:Correlation of immune infiltration showed that Tfh cells and B cells had the strongest positive correlation(r=0.68),while regulatory T cells and iDC had the strongest negative correlation(r=-0.63);the difference analysis of im-mune infiltration showed that the differences among mast cells,NK cells and Th1 cells in the MI group at the cellular level were the most significant(P<0.001);and the differences in APC co-inhibition and MHCⅠ at the functional level were the most significant(P<0.001).Six genes with the highest correlation between immune cells and immune function were screened out:ATP7A,DLD,FDX1,LIAS,LIPT1 and SLC31A1.Results of the risk model showed that the high levels of FDX1 and SLC31A1 were negatively correlated with the risk prediction of MI.A total of 21 Western medicines and 30 traditional medicines were predicted by database comparison.miRTarBase,Starbase and Targetscan databases predicted 9 upstream miRNAs of cuproptosis-related genes in MI,including has-miR-122-5p.Conclusion:Tfh cells,B cells,para-inflammatory,typeⅠinterferon response and other related immune cells and functions may play important roles in pathogenesis and prognosis of MI.FDX1 and SLC31A1 as the key genes of cuproptosis process,are negatively correlated with MI.A total of 30 kinds of traditional Chinese medicines including Spirulina,sheep liver,Wen ezhu,Pian jianghuang and Yujin may have potential value in treatment of MI.Finally,9 miRNAs including has-miR-122-5p may play an important role in the regulation of cuproptosis in myocardial infarction.

Objective To investigate the mechanism by which Ginkgo biloba extract reduces myocardial injury in rats with myocardial infarction(MI).Methods Bioinformatics was used to identify key targets of Ginkgo biloba extract in the treatment of MI in rats.An MI rat model was established via coronary artery ligation.Rats were randomly assigned to the model group,Betaloc ZOK group(2.5 mg/kg),and low-,medium-,and high-dose Ginkgo biloba extract groups(50,100,and 200 mg/kg,respectively).A sham-operation group was included for comparison.Following six weeks of gavage administration,myocardial tissues were examined using hematoxylin-eosin and Sirius red staining to assess pathological changes.Wheat germ agglutinin staining was used to observe cardiomyocyte hypertrophy.Western blotting was performed to evaluate changes in the expression of MCODE core targets,including HIF1α,MAPK14,MMP9,and CXCR4.Results Compared to the sham-operation group,the model group exhibited irregular arrangement of cardiomyocytes,significant inflam-matory infiltration,and a marked increase in type Ⅰ and Ⅲ collagen fibers in the myocardial tissue(P＜0.05).Additionally,significant upregulation in the expression of MCODE core target proteins(P＜0.05)was observed.In contrast,compared to the model group,low-,medium-,and high-dose Ginkgo biloba extract groups displayed more orderly arrangement of cardiomyocytes,reduced inflammatory infil-tration,significantly decreased levels of type Ⅰ and Ⅲ collagen fibers(P＜0.05),notable downregulation in the expression of p-MAPK14,MMP9,and CXCR4 proteins(P＜0.05),and significantly increased expression of HIF1α protein(P＜0.05).Conclusion Ginkgo biloba extract may exert protective effects on myocardial cells following MI by inhibiting the formation of neutrophil extracellular traps.

As of May 3, 2023, the Coronavirus disease 2019 (COVID-19) pandemic has resulted in more than 760 million confirmed cases and over 6.9 million deaths. Several patients have developed pneumonia, which can deteriorate into acute respiratory distress syndrome. The primary etiology may be attributed to cytokine storm, which is triggered by the excessive release of proinflammatory cytokines and subsequently leads to immune dysregulation. Considering that high levels of interleukin-6 (IL-6) have been detected in several highly pathogenic coronavirus-infected diseases, such as severe acute respiratory syndrome in 2002, the Middle East respiratory syndrome in 2012, and COVID-19, the IL-6 pathway has emerged as a key in the pathogenesis of this hyperinflammatory state. Thus, we review the history of cytokine storm and the process of targeting IL-6 signaling to elucidate the pivotal role played by tocilizumab in combating COVID-19.
Humans ; COVID-19 ; Interleukin-6 ; Cytokine Release Syndrome ; SARS-CoV-2 ; Cytokines ; Biology

Objective : A convolutional neural network (CNN) model was established to automatically analyze flow cytometry (FCM) data to achieve the preliminary diagnosis of acute myeloid leukemia(AML) , and explore the feasibility of applying CNN model to FCM data analysis. Methods : The exploratory study of CNN application was carried out using the bone marrow FCM data obtained by the FlowRepository database and the Clinical Testing Center of Xinjiang Uygur Autonomous Region People ′ s Hospital , and the data had been clinically confirmed whether AML was present. Among them , the public data was divided into training sets , validation sets and test sets according to 6 ∶ 2 ∶ 2 , and local data was used for external test; In order to adapt the FCM data to the CNN model , an FCM data structure based on the image matrix principle was proposed , and after preprocessing the original data , the variables related to the preliminary diagnosis of AML were extracted , including sidescattered light and the expression levels of CD45 , CD13 , CD33 , HLA⁃DR , CD117 , CD34 , and each variable was written into the matrix. Cell sampling and data augmentation methods were used to increase the sample size of the training set , the keras software package was used to build the LeNet⁃5 CNN model in Python , and the training set and the validation set were used for model training and parameter tuning respectively to evaluate the performance of the model on the test set. Results : The accuracy of CNN to identify AML on the two test sets was 0. 931 , 0. 851 , the sensitivity was 0. 667 , 0. 636 , the specificity was 0. 968 , 0. 940 , and the area under the receiver operating characteristic curve was 0. 940 and 0. 917. Conclusion Based on the proposed FCM data structure , the CNN model can realize the preliminary diagnosis of AML , indicating that CNN has certain application value in FCM data analysis.