BACKGROUND:Cervical disc herniation can cause pain in the neck and shoulder area,as well as radiating pain in the upper limbs.The incidence rate is increasing year by year and tends to affect younger individuals.Fully understanding the biomechanical characteristics of the cervical spine in adolescents is of great significance for preventing and delaying the onset of cervical disc herniation in this age group. OBJECTIVE:To reconstruct cervical spine models for both healthy adolescents and adolescent patients with cervical disc herniation utilizing finite element analysis techniques,to analyze the motion range of the C1-T1 cervical vertebrae as well as the biomechanical characteristics of the annulus fibrosus,nucleus pulposus,endplates,and the cartilage of the small joints. METHODS:A normal adolescent's cervical spine and an adolescent patient with cervical disc herniation were selected in this study.The continuous scan cervical spine CT raw image data were imported into Mimics 21.0 in DICOM format.The C1-T1 vertebrae were reconstructed separately.Subsequently,the established models were imported into the 3-Matic software for disc reconstruction.The perfected models were then imported into Hypermesh software for meshing of the vertebrae,nucleus pulposus,annulus fibrosus,and ligaments,creating valid geometric models.After assigning material properties,the final models were imported into ABAQUS software to observe the joint motion range of the C1-C7 cervical vertebrae segments under different conditions,and to analyze the biomechanical characteristics of the annulus fibrosus,nucleus pulposus,endplates,and small joint cartilage of each cervical spine segment. RESULTS AND CONCLUSION:(1)In six different conditions,the joint motion range of the C1 vertebra in the cervical spine models of both normal adolescent and adolescent patient with cervical disc herniation was higher than that of the other vertebrae.Additionally,the joint motion range of each cervical spine segment in normal adolescent was greater than that in adolescent patient with cervical disc herniation.(2)In the cervical spine model of normal adolescent,the maximum stress values in the annulus fibrosus and nucleus pulposus were found on the left side during C2-3 flexion conditions(0.43 MPa and 0.17 MPa,respectively).In the cervical spine model of adolescent patient with cervical disc herniation,the maximum stress values were found on the left side during C7-T1 flexion conditions(0.54 MPa and 0.18 MPa,respectively).(3)In the cervical spine model of normal adolescent,the maximum stress value on the endplate was found on the left side of the upper endplate of C3 during flexion conditions(1.46 MPa).In the model of adolescent patient with cervical disc herniation,the maximum stress value on the endplate was found on the left side of the lower endplate of C7 during flexion conditions(1.32 MPa).(4)In the cervical spine model of normal adolescent,the maximum stress value in the small joint cartilage was found in the C2-3 left rotation conditions(0.98 MPa).In adolescent patient with cervical disc herniation,the stress in the small joint cartilage significantly increased under different conditions,especially in C1-2,with the maximum stress found during left flexion(3.50 MPa).(5)It is concluded that compared to normal adolescent,adolescent patient with cervical disc herniation exhibits altered cervical curvature and a decrease in overall joint motion range in the cervical spine.In adolescent with cervical disc herniation,there is a significant increase in stress on the annulus fibrosus,nucleus pulposus,and endplates in the C7-T1 segment.The stress on the left articular cartilage of the C1-2 is notable.Abnormal cervical curvature may be the primary factor causing these stress changes.

Objective: To explore the differences in the gut microbiota of primary school students with different levels of sugar sweetened beverage intake, so as to provide scientific evidence for better identification of health risks in children and the development of targeted health policies. Methods: In June 2022, a total of 192 healthy primary school students from Chengdu were selected using a stratified cluster random sampling method. The sugar sweetened beverage intake was assessed through a dietary frequency questionnaire. Based on the median daily sugar sweetened beverage intake, primary school students were categorized into a low intake group ( n =96) and a high intake group ( n =96). The gut microbiota in fresh fecal samples from the two groups of primary school students was analyzed using 16S rRNA high throughput sequencing, and the diversity and community structure differences in the gut microbiota were compared. Results: Children in the low intake group had a sugar sweetened beverage intake of (21.3±1.6) mL/d, while the high intake group had an intake of (269.6±37.3) mL/d. Diversity analysis results showed that there were no statistically significant differences between the low intake and the high intake group in terms of α diversity metrics: Observed_otus index [298.50 (259.75, 342.25), 305.50 (244.25, 367.75)], Goods_coverage index [1.00 (1.00, 1.00), 1.00 (1.00, 1.00)], Chao index [304.18 (260.75, 348.78), 305.88 (245.68, 370.88)], Shannon index [5.88 (5.29, 6.45), 5.71 (4.89, 6.28)] and Simpson index [0.95 (0.91, 0.97), 0.94 (0.88, 0.97)] ( Z =-0.64, -0.76, -0.54, -1.76, -1.67, P >0.05). Furthermore, no statistically significant difference was observed in β diversity between the two groups ( R 2=0.006, P >0.05). At the genus level, the abundance of Blautia [0.033 (0.018, 0.055)] and Fusicatenibacter [0.009 (0.005, 0.015)] were higher in the low intake group compared to the high intake group [0.024 (0.013, 0.041),0.006 (0.003, 0.011)]and differences were statistically significant ( Z =-2.52, -2.81, P <0.05). LEfSe analysis highlighted intergroup differences primarily in Blautia, Fusicatenibacter and Sarcina( LDA= 3.56,3.12,3.53, P <0.05). Conclusions There is no significant difference in the diversity and overall structure of the gut microbiota in primary school students with different levels of sugar sweetened beverage intake. However, there are species variations at the genus level. The information can serve as a scientific basis for identifying health risks in primary school students and formulating targeted health strategies.

Cough variant asthma （CVA） is a chronic respiratory disease with cough as its main symptom. The occurrence of CVA is closely related to non-specific airway inflammation， and its pathogenesis involves environmental， genetic， immune， and other factors. In recent years， the advantages of traditional Chinese medicine （TCM） in the treatment of CVA have attracted the attention of experts and scholars in China and abroad， especially its prominent role in regulating immune balance， relieving cough symptoms in CVA patients， and reducing recurrence. T Helper cells 1 （Th1）， T helper cells 2 （Th2）， T helper cells 17 （Th17）， and regulatory T cells （Treg） are derived from CD4⁺ T cells. Immune imbalance of Th1/Th2 and Th17/Treg is a new hotspot in the pathogenesis of CVA and a potential key target in the treatment of CVA by TCM. Th cell subsets are in dynamic balance under physiological conditions， maintaining respiratory immune homeostasis in which pro-inflammatory cytokines and anti-inflammatory cytokines are balanced. Immature helper T cells （Th0） can be differentiated into Th1， Th2， Th17， Treg， and other cell subsets due to cytokine types in the microenvironment in the stage of CVA maturation. The proliferation of Th2 cells leads to eosinophilic airway inflammation. Excessive differentiation of Th17 cells induces neutrophil airway inflammation. Th1/Th2 and Th17/Treg cells are mutually restricted in number and function， and the immune imbalance of Th1/Th2 and Th17/Treg is easy to aggravate the generation of inflammatory response. Restoring immune balance is particularly important for the airway anti-inflammatory therapy of CVA. In this paper， the imbalance of Th1/Th2 and Th17/Treg and the pathogenesis of CVA were systematically expounded. Meanwhile， the latest research on the regulation of immune imbalance by TCM compound， single TCM， and its effective ingredients in the treatment of CVA was reviewed. It provides ideas and references for revealing the scientific connotation of TCM regulating immune balance therapy of CVA， as well as the development of clinical treatment and basic research of CVA.

Background::Clinical opportunistic screening is a cost-effective cancer screening modality. This study aimed to establish an easy-to-use diagnostic model serving as a risk stratification tool for identification of individuals with malignant gastric lesions for opportunistic screening.Methods::We developed a questionnaire-based diagnostic model using a joint dataset including two clinical cohorts from northern and southern China. The cohorts consisted of 17,360 outpatients who had undergone upper gastrointestinal endoscopic examination in endoscopic clinics. The final model was derived based on unconditional logistic regression, and predictors were selected according to the Akaike information criterion. External validation was carried out with 32,614 participants from a community-based randomized controlled trial.Results::This questionnaire-based diagnostic model for malignant gastric lesions had eight predictors, including advanced age, male gender, family history of gastric cancer, low body mass index, unexplained weight loss, consumption of leftover food, consumption of preserved food, and epigastric pain. This model showed high discriminative power in the development set with an area under the receiver operating characteristic curve (AUC) of 0.791 (95% confidence interval [CI]: 0.750–0.831). External validation of the model in the general population generated an AUC of 0.696 (95% CI: 0.570–0.822). This model showed an ideal ability for enriching prevalent malignant gastric lesions when applied to various scenarios.Conclusion::This easy-to-use questionnaire-based model for diagnosis of prevalent malignant gastric lesions may serve as an effective prescreening tool in clinical opportunistic screening for gastric cancer.

Objective To investigate the expression of long non-coding RNA(lncRNA)colon cancer associ-ated transcript 2(CCAT2)and N-myc downstream regulated gene(NDRG)1 in colorectal cancer(CRC)tis-sues and their relationship with clinicopathological features and prognosis.Methods A total of 96 patients with CRC who underwent radical surgery in Nantong Hospital of Traditional Chinese Medicine from February 2018 to February 2020 were selected as the research objects.Quantitative real-time PCR was used to detect the mRNA expression of lncRNA CCAT2 and NDRG1 in tissues.The expression of NDRG1 protein was detected by immunohistochemistry.Kaplan-Meier curve was used to analyze the prognosis differences of patients with different lncRNA CCAT2 and NDRG1 mRNA expression groups.Multivariate Cox regression was used to an-alyze the prognostic factors of CRC.Results The expression of lncRNA CCAT2 in cancer tissues was higher than that in adjacent tissues,and the expression of NDRG1 mRNA and protein was lower than that in adjacent tissues(P＜0.05).The expression of lncRNA CCAT2 was higher and the expression of NDRG1 mRNA was lower in TNM stage Ⅲ CRC patients with lymph node metastasis than in TNM stage Ⅰ-Ⅱ CRC patients without lymph node metastasis(P＜0.05).The 3-year cumulative survival rate of lncRNA CCAT2 high ex-pression group was lower than that of lncRNA CCAT2 low expression group,while the 3-year cumulative sur-vival rate of NDRG1 mRNA high expression group was higher than that of NDRG1 mRNA low expression group,and the difference was statistically significant(P＜0.05).TNM stage,lymph node metastasis,lncRNA CCAT2 and NDRG1 mRNA were the prognostic factors of CRC(P＜0.05).Conclusion The expression of lncRNA CCAT2 is increased and the expression of NDRG1 is decreased in CRC tissues.Both lncrna CCAT2 and NDRG1 are involved in the progression of CRC and can be used as new indicators for evaluating the sur-vival and prognosis of CRC patients.

Objective:To develop and validate a predictive model of 28-day mortality in sepsis based on lactate dehydrogenase-to-albumin ratio (LAR).Methods:Sepsis patients diagnosed in the department of intensive care medicine of the First Affiliated Hospital of Soochow University from August 1, 2017 to September 1, 2022 were retrospective selected. Clinical data, laboratory indicators, disease severity scores [acute physiology and chronic health evaluation Ⅱ(APACHEⅡ), sequential organ failure assessment (SOFA)] were collected. Patients were divided into death group and survival group according to whether they died at 28 days, and the difference between the two groups was compared. The dataset was randomly divided into training set and validation set according to 7∶3. Lasso regression method was used to screen the risk factors affecting the 28-day death of sepsis patients, and incorporating multivariate Logistic regression analysis (stepwise regression) were included, a prediction model was constructed based on the independent risk factors obtained, and a nomogram was drawn. The nomogram prediction model was established. Receiver operator characteristic curve (ROC curve) was drawn to analyze and evaluate the predictive efficacy of the model. Hosmer-Lemeshow test, calibration curve and decision curve analysis (DCA) were used to evaluate the accuracy and clinical practicability of the model, respectively.Results:A total of 394 patients with sepsis were included, with 248 survivors and 146 non-survivors at 28 days. Compared with the survival group, the age, proportion of chronic obstructive pneumonia, respiratory rate, lactic acid, red blood cell distribution width, prothrombin time, activated partial thromboplastin time, alanine aminotransferase, aspartate aminotransferase, blood urea nitrogen, creatinine, blood potassium, blood phosphorus, LAR, SOFA score, and APACHEⅡ score in the death group were significantly increased, while oxygenation index, monocyte count, platelet count, fibrinogen, total cholesterol, triglycerides, high-density lipoprotein, low-density lipoprotein, and blood calcium were significantly reduced. In the training set, LAR, age, oxygenation index, blood urea nitrogen, lactic acid, total cholesterol, fibrinogen, blood potassium and blood phosphorus were screened by Lasso regression. Multivariate Logistic regression analysis finally included LAR [odds ratio ( OR) = 1.029, 95% confidence interval (95% CI) was 1.014-1.047, P < 0.001], age ( OR = 1.023, 95% CI was 1.005-1.043, P = 0.012), lactic acid ( OR = 1.089, 95% CI was 1.003-1.186, P = 0.043), oxygenation index ( OR = 0.996, 95% CI was 0.993-0.998, P = 0.002), total cholesterol ( OR = 0.662, 95% CI was 0.496-0.865, P = 0.003) and blood potassium ( OR = 1.852, 95% CI was 1.169-2.996, P = 0.010). A total of 6 predictor variables were used to establish a prediction model. ROC curve showed that the area under the curve (AUC) of the model in the training set and validation set were 0.773 (95% CI was 0.715-0.831) and 0.793 (95% CI was 0.703-0.884), which was better than APACHEⅡ score (AUC were 0.699 and 0.745) and SOFA score (AUC were 0.644 and 0.650), and the cut-off values were 0.421 and 0.309, the sensitivity were 62.4% and 82.2%, and the specificity were 82.2% and 68.9%, respectively. The results of Hosmer-Lemeshow test and calibration curve showed that the predicted results of the model were in good agreement with the actual clinical observation results, and the DCA showed that the model had good clinical application value. Conclusion:The prediction model based on LAR has a good predictive value for 28-day mortality in patients with sepsis and can guide clinical decision-making.

Malaria is a significant global infectious disease that once wreaked havoc in China as well. In recent years, the global malaria control situation has stagnated, and China is also facing a huge threat of imported malaria. So, effective malaria vaccines are urgently needed as a supplementary strategy to the existing prevention and control measures. Compared to vaccines targeting the erythrocytic stage and those designed to block transmission, vaccines aimed at preventing infection during the pre-erythrocytic stage have attracted more attention and have made a series of progress in recent years. At present, the only two malaria vaccines recommended by the World Health Organization (WHO) are pre-erythrocytic vaccines. In this paper, the current situation and trend of pre-erythrocytic malaria vaccine research and development are reviewed, intending to provide a reference for the research, development, and application of malaria vaccines in the future.

Objective: To investigate the mechanisms of work-family conflict (WFC) and work-family enrichment (WFE) between job demands and subjective well-being (SWB) among nurses. Methods: A total of 1 420 nurses were selected as the study subjects from five tertiary public hospitals in Shandong Province using two-stage sampling method. Job Demands-Resources Scale, Work-Family Relationship Scale and General Well-Being Scale were used for investigating the job demands, job resources, WFC, WFE, and SWB. Results: The average score of SWB in nurses was (75.5±15.1). Job demands had a negative effect on SWB in nurses (standardized regression coefficient=-0.17, P<0.01). WFC and WFE played parallel mediating roles in the relationship between job demands and SWB, with the mediating effect values of -0.29 and -0.07, respectively (both P<0.01). The interaction of job resources and job demands positively affected WFC (standardized regression coefficient<0.01, P<0.01). Conclusion: Job demands affect SWB through the mediating roles of WFC and WFE, and the impact of job demands on WFC is moderated by job resources. The effect of job demands on WFC is relatively strong in nurses with high levels of job resources, but the difference in the effect of high and low levels of job resources is small.

ObjectiveTo systematically review the clinical experience of four sessions of Masters of Traditional Chinese Medicine and two sessions of National Famous Chinese Medicine Practitioners in treating ulcerative colitis （UC）. Data mining and analysis were conducted to clarify the diagnosis and treatment ideas and characteristics of prescription used by these famous doctors in treating UC. MethodsRelevant literature on the treatment of UC by renowned doctors was retrieved from the establishment of the database until March 31， 2023. The literature was collected from databases such as China National Knowledge Infrastructure （CNKI）， Wanfang Data Knowledge Service Platform， Chinese Science and Technology Periodicals Database， and China Biomedical Literature Database. The data mining techniques including frequency analysis， association rules， and cluster analysis were conducted using the Ancient and Modern Medical Case Cloud Platform V2.3.5. ResultsA total of 157 literatures were included in this study， including 115 clinical case data. The study found that UC can be categorized into 14 types of syndrome patterns for treatment， including large intestine dampness-heat syndrome （75，65.22%）， syndrome of dampness stagnancy due to spleen deficiency （23， 20.00%）， spleen-kidney yang deficiency syndrome （21， 18.26%）. The main affected organs were the spleen （85， 73.91%） and large intestine （75， 65.22%）， and they were closely related to liver （24， 20.87%） and the kidney （21， 18.26%）. The predominant pathogenic factors were dampness （83， 72.17%） ， heat （80， 69.57%） and qi deficiency （65， 56.52%）. The treatment involved 30 kinds of treatment methods， including heat-clearing and dampness-draining method （75， 65.22%）， pleen-tonifying and qi-boosting method （25，21.74%） and spleen-invigorating and dampness-transforming method （23， 20.00%）. The medication involved 187 ingredients， with the most commonly used being heat-clearing herbs （37， 19.79%） and tonifying herbs （27， 14.44%）. The tastes of the herbs were mostly sweet （85， 45.45%） ， bitter （80， 42.78%） ， and pungent （71， 37.97%）. The association rules revealed 16 high-frequency combinations mainly composed of Huanglian （黄连）， Baishao （白芍） and Gancao （甘草） along with Baizhu （白术）， Fuling （茯苓）， Muxiang （木香） and Danggui （当归）. ConclusionFamous doctors are skilled in diagnosing and treating UC based on the differentiation of the zang-fu organs and qi-blood. The key pathological mechanism is “spleen deficiency as the root， and large intestine damp-heat as the manifestation”. The core treatment approach is “heat-clearing， spleen-tonifying， and dampness-draining”， with the inclusion of “regulating qi and blood， and balancing cold and heat”.

Objective:To establish a machine learning model for the diagnosis of clinically significant prostate cancer based on transrectal contrast-enhanced ultrasound parameters and clinically relevant data.Methods:A retrospective analysis was performed on 151 patients in Chongqing University Cancer Hospital who underwent transrectal contrast-enhanced ultrasonography and transrectal ultrasound-guided needle biopsy from November 2018 to September 2021. The time intensity curve was drawn using VueBox software and 12 parameters such as rise time, peak time, average transit time, peak intensity, and rising slope were quantitatively analyzed. Age, total prostate-specific antigen, free prostate-specific antigen, free prostate-specific antigen ratio, volume, prostate-specific antigen density, and transrectal contrast-enhanced ultrasonography parameters, a total of 18 characteristic parameters, were analyzed and screened through relevant attribute values and information gain attribute values. The screening features were trained and tested by the machine learning single algorithm and integrated algorithm, and then the model was evaluated by the F1 value and the area under the ROC curve(AUC).Results:Using the related attribute value and the information gain attribute value, 12 variables and 5 variables were screened out respectively to establish a machine learning model. The model established by the ensemble algorithm was better than the single algorithm. For the two variable selection methods, the AUC (0.810 vs 0.789) and F1 values (0.748 vs 0.742) of the Bagging ensemble algorithm model, which basic algorithm was decision tree, were the highest, followed by Logistic regression and support vector machine(SVM) in order of AUC and F1 values.Conclusions:Based on transrectal contrast-enhanced ultrasound parameters and clinical data, the Bagging ensemble model based on decision tree has the best performance in diagnosing clinically significant prostate cancer.