ObjectiveTo explore the effects of the Tai Chi training on bone density， bone turnover markers， and heart rate variability for people with high-risk osteoporosis， and to provide evidence for the prevention of osteoporosis at early stage. MethodsSixty-six cases of people with high risk of osteoporosis were included， and they were divided into 33 cases each in the intervention group and the control group using the random number table method. The control group received osteoporosis health education three times a week， and the intervention group received Tai Chi training under the guidance of a trainer three times a week for 40 mins each time on the basis of the control group， and both groups were intervened for 12 weeks. Dual-energy X-ray absorptiometry was used to measure the bone density of L₁~L₄ vertebrae， bilateral femoral necks and bilateral total hips in the two groups before and after the intervention； enzyme-linked immunosorbent assay was used to determine bone turnover markers before and after the intervention， including pro-collagen type Ⅰ pro-amino-terminal prepropyl peptide （P1NP） and β-collagen type Ⅰ cross-linking carboxy-terminal peptide （β-CTX）. Seven cases with good compliance in the intervention group were selected. After wearing the heart rate sensor， they successively performed Tai Chi training and walking activities recommended by the guideline for 20 mins each， and the heart rate variability （HRV） during exercise was collected， including time-domain indexes such as standard deviation of normal sinus intervals （SDNN）， root-mean-square of the difference between adjacent RR intervals （RMSSD）， frequency-domain metrics such as low-frequency power （LF）， high-frequency power （HF）， and low-frequency/high-frequency power ratio （LF/HF）， as well as nonlinear metrics such as approximate entropy （ApEn）， sample entropy （SampEn）. ResultsFinally， 63 cases were included in the outcome analysis， including 30 cases in the intervention group and 33 cases in the control group. After the intervention， the differences of L₁~L₄ vertebrae， bone density of bilateral femoral neck and bilateral total hip in the intervention group were not statistically significant when compared with those before intervention （P＞0.05）， while the bone density of all parts of the control group decreased significantly compared with that before intervention （P＜0.05）， and the difference in the bone density of the L₁~L₄ vertebrae， bilateral femoral neck， and the right total hip before and after the intervention of the intervention group was smaller than that of the control group （P＜0.05）. The differences in P1NP and β-CTX between groups before and after intervention was not statistically significant （P＞0.05）. Compared with walking exercise， LF decreased， HF increased and LF/HF decreased during Tai Chi exercise （P＜0.05）； the time domain indexes and non-linear indexes between groups had no statistically significant difference （P＞0.05）. ConclusionTai Chi exercise can maintain lumbar， hip， and femoral bone density and improve sympathetic/parasympathetic balance in people at high risk for osteoporosis， but cannot significantly improve bone turnover markers.

Objective:To analyze the diagnostic value of bedside capsule endoscopy in patients with acute or severe gastrointestinal bleeding.Methods:Clinical data from patients who underwent bedside capsule endoscopy due to acute or severe suspected gastrointestinal bleeding in Nanfang Hospital, Southern Medical University from June 2018 to September 2021 were analyzed retrospectively. The efficacy of capsule endoscopy in detecting upper gastrointestinal tract and small intestinal bleeding was evaluated.Results:A total of 74 patients underwent bedside capsule endoscopy for suspected acute or severe gastrointestinal bleeding. Five patients were excluded due to failure of examination due to retention of capsule endoscope in the gastric lumen, and 69 were included in the study, of whom 54 patients with a definitive diagnosis of gastrointestinal hemorrhage. The positive detection rate of the capsule endoscopy was 83.33% (45/54), including 17 cases of ulcer, 5 cases of erosion, 5 cases of vascular malformation, 4 protrusion mass, 4 diverticulum, 5 obscure gastrointestinal bleeding, 1 stenosis , 1 active mucosal blood exudation, 1 gastric retention, 1 mucosal swelling, and 1 mucosal wrinkle change. The sensitivity and specificity of capsule endoscopy in the diagnosis of upper gastrointestinal bleeding were 92.31% (12/13) and 75.00% (3/4) respectively. The sensitivity and specificity of capsule endoscopy for diagnosing small intestinal bleeding were 80.49% (33/41) and 90.91% (10/11) respectively.Conclusion:Bedside capsule endoscopy demonstrates high sensitivity and specificity in the diagnosis of gastrointestinal bleeding, showing potential advantages in bedside applications for acute and severe gastrointestinal bleeding.

OBJECTIVES: To characterize fine particulate matter (PM _2.5)-bound polycyclic aromatic hydrocarbons (PAHs) emitted from different cooking fumes and their exposure routes and assess their health-associated impact to provide a reference for health risk prevention from PAH exposure across different age and sex groups. METHODS: Sixteen PM _2.5-bound PAHs emitted from 11 cooking styles were analyzed using GC-MS/MS. The health hazards of these PAHs in the Handan City population (stratified by age and sex) were predicted using the incremental lifetime cancer risk ( ILCR) model. The respiratory deposition doses ( RDDs) of the PAHs in children and adults were calculated using the PM _2.5 deposition rates in the upper airway, tracheobronchial, and alveolar regions. RESULTS: The total concentrations of PM _2.5-bound PAHs ranged from 61.10 to 403.80 ng/m ³. Regardless of cooking styles, the ILCR _total values for adults (1.23 × 10 ^-6 to 3.70 × 10 ^-6) and older adults (1.28 × 10 ^-6 to 3.88 × 10 ^-6) exceeded the acceptable limit of 1.00 × 10 ^-6. With increasing age, the ILCR _total value first declined and then increased, varying substantially among the population groups. Cancer risk exhibited particularly high sensitivity to short exposure to barbecue-derived PAHs under equivalent body weights. Furthermore, barbecue, Sichuan and Hunan cuisine, Chinese cuisine, and Chinese fast food were associated with higher RDDs for both adults and children. CONCLUSION ILCR _total values exceeded the acceptable limit for both females and males of adults, with all cooking styles showing a potentially high cancer risk. Our findings serve as an important reference for refining regulatory strategies related to catering emissions and mitigating health risks associated with cooking styles.
Humans ; Polycyclic Aromatic Hydrocarbons/analysis* ; Cooking/methods* ; Male ; Female ; Particulate Matter/analysis* ; Adult ; Child ; Middle Aged ; Air Pollutants/analysis* ; Adolescent ; Air Pollution, Indoor/analysis* ; Young Adult ; Child, Preschool ; Aged ; China ; Inhalation Exposure ; Age Factors ; Sex Factors ; Cities ; Infant

OBJECTIVE To analysis the clinical and pathological characteristics of lymph nodes metastasis in pediatric patients with differentied thyroid carcinoma(pDTC),and to develop a nomogram for predicting lymph nodes metastasis in patients with pDTC.METHODS Four cohorts were integrated in this study,including internal training cohort(1419 cases)and validation cohort(609 cases)from the Surveillance,Epidemiology,and End Results(SEER)database of the National Cancer Institute,TCGA-pDTC cohort(20 cases from the Cancer Genome Atlas Program)and YHD-pDTC cohort(39 cases from true world).The least absolute shrinkage and selection operator(Lasso)and logistic regression were used to screen factors related to lymph nodes metastasis in the presence and exclusion of T stage in pDTCs based on internal training cohort and construct nomograms.Calibration curve,receiver operating characteristic(ROC)curve,area under the ROC curve(AUC)and decision curve analysis(DCA)were used to evaluate model performance in the other three cohorts.RESULTS Multivariate logistic regression results showed that pathology[OR(95%CI):0.020(0.010-0.060),P<0.001],M stage[OR(95%CI):29.550(3.190-273.490),P=0.003],and T stage[OR(95%CI):2.210(1.820-2.680),P<0.001]were independent factors affecting lymph nodes metastasis in pDTCs.Through the internal training set,internal validation set,YHD-pDTC cohort and TCGA-pDTC cohort,the AUC values were 0.734(0.709,0.758),0.752(0.716,0.788),0.969(0.920,1),and 0.600(0.342,0.858)in that order,and the calibration curves are close to the perfect reference line.T stage is a better predictor of lymph nodes metastasis than extraperitoneal intrusion and tumor size.CONCLUSION Pathology,M stage,and T stage are risk factors for predicting lymph nodes metastasis in pDTCs.The nomogram established on this basis can make individualized predictions of the probability of lymph nodes metastasis in pDTCs.

Houpo Qiwutang originated from the Synopsis of the Golden Chamber， and it consists of seven medicines： Magnoliae Officinalis Cortex， Rhei Radix et Rhizoma， Aurantii Fructus Immaturus， Cinnamomi Ramulus， Zingiberis Rhizoma Recens， Glycyrrhizae Radix et Rhizoma， and Jujubae Fructus. It is a basic formula for the treatment of abdominal fullness. Through the bibliometric method， the historical history， drug base， preparation and dosage， decoction method， and ancient and modern applications of Houpu Qiwu Tang were analyzed by means of textual research. The research finds that Houpu Qiwu Tang has been passed down through the generations in an orderly manner with fewer changes. The drug base of this formula is basically clear， and the base of Magnoliae Officinalis Cortex， Rhei Radix et Rhizoma， Cinnamomi Ramulus， Zingiberis Rhizoma Recens， and Jujubae Fructus is consistent with the 2020 edition of Chinese Pharmacopoeia. The mainstream base of Aurantii Fructus Immaturus is the dried young fruit of Citrus aurantium of Rutaceae family， and the historical mainstream base of Glycyrrhizae Radix et Rhizoma is the dried root of Glycyrrhiza uralensis of Leguminosae family. The modern dosage of this formula is 110.40 g of Magnoliae Officinalis Cortex， 41.40 g of Rhei Radix et Rhizoma， 69 g of Aurantii Fructus Immaturus， 27.60 g of Cinnamomi Ramulus， 69 g of Zingiberis Rhizoma Recens， 41.40 g of Glycyrrhizae Radix et Rhizoma， and 30 g of Jujubae Fructus. In addition， the decoction method is to add 2 000 mL of water with the above seven flavors of the medicine， boil it to 800 mL， and then take 160 mL in a warm state each time. The amount of the medicine taken for each time is 22.08 g of Magnoliae Officinalis Cortex， 8.28 g of Rhei Radix et Rhizoma， 13.80 g of Aurantii Fructus Immaturus， 5.52 g of Cinnamomi Ramulus， 13.80 g of Zingiberis Rhizoma Recens， 8.28 g of Glycyrrhizae Radix et Rhizoma， and 6 g of Jujubae Fructus. The modern application of this formula involves the digestive system， respiratory system， and urinary system. It is more advantageous in digestive system diseases such as early postoperative inflammatory bowel obstruction， functional dyspepsia， gastric pain， functional abdominal distension， and gastric reflux esophagitis. By comprehensively examining the key information of Houpu Qiwu Tang， this paper aims to provide literature support for the development and clinical application of this formula.

Objective Hepatitis C is a kind of infectious disease with great harm and strong concealment.Accurate trend prediction is an important measure to ensure accurate intervention.This paper aims to confirm the effectiveness of multivariate time series prediction method and Internet data and provide a better data and method basis for hepatitis C prediction.Methods The data of the monthly incidence of hepatitis C in Chongqing from 2011 to 2018 were included,including infectious disease incidence data and Internet prediction data.To screen important features,this paper introduces the theoretical basis of feature entropy,and proposes an adaptive correlation entropy weight method(ACEW)for feature selection through the steps of collinearity removal,directional evaluation and information content evaluation.After that,this paper constructed a multivariate time series model(CNN-BILLSTM-Attention)and carried out the characteristic performance test(including prospective evaluation and posterior evaluation)and model efficiency exploration.Results Prospective evaluation revealed that the variables selected by ACEW had low consistency with each other,and the weight distribution calculated by each variable was relatively equal.The posterior evaluation revealed that the feature set screened by ACEW could obtain the best prediction information in each model.In the exploration of model effectiveness,the overall performance of multivariate time series prediction model is significantly better than that of univariate model.When ACEW and CNN-BILSTM-Attention are combined,the MSE,MAE,RMSE,MAPE and R2 on the test set are 0.0223,0.0649,0.0771,5.9285 and 0.9156,respectively.Conclusion In the study of predicting the incidence of hepatitis C,data fusion and method improvement are studied in this paper.The improved feature selection method(ACEW)can provide an opportunity for the regulation of hepatitis C,and the multivariate time series prediction model can improve the performance of hepatitis C trend prediction,to effectively control and prevent hepatitis C,which has better public health prevention and control significance.

Objective Hepatitis C is a kind of infectious disease with great harm and strong concealment.Accurate trend prediction is an important measure to ensure accurate intervention.This paper aims to confirm the effectiveness of multivariate time series prediction method and Internet data and provide a better data and method basis for hepatitis C prediction.Methods The data of the monthly incidence of hepatitis C in Chongqing from 2011 to 2018 were included,including infectious disease incidence data and Internet prediction data.To screen important features,this paper introduces the theoretical basis of feature entropy,and proposes an adaptive correlation entropy weight method(ACEW)for feature selection through the steps of collinearity removal,directional evaluation and information content evaluation.After that,this paper constructed a multivariate time series model(CNN-BILLSTM-Attention)and carried out the characteristic performance test(including prospective evaluation and posterior evaluation)and model efficiency exploration.Results Prospective evaluation revealed that the variables selected by ACEW had low consistency with each other,and the weight distribution calculated by each variable was relatively equal.The posterior evaluation revealed that the feature set screened by ACEW could obtain the best prediction information in each model.In the exploration of model effectiveness,the overall performance of multivariate time series prediction model is significantly better than that of univariate model.When ACEW and CNN-BILSTM-Attention are combined,the MSE,MAE,RMSE,MAPE and R2 on the test set are 0.0223,0.0649,0.0771,5.9285 and 0.9156,respectively.Conclusion In the study of predicting the incidence of hepatitis C,data fusion and method improvement are studied in this paper.The improved feature selection method(ACEW)can provide an opportunity for the regulation of hepatitis C,and the multivariate time series prediction model can improve the performance of hepatitis C trend prediction,to effectively control and prevent hepatitis C,which has better public health prevention and control significance.

Objective:To analyze the diagnostic value of bedside capsule endoscopy in patients with acute or severe gastrointestinal bleeding.Methods:Clinical data from patients who underwent bedside capsule endoscopy due to acute or severe suspected gastrointestinal bleeding in Nanfang Hospital, Southern Medical University from June 2018 to September 2021 were analyzed retrospectively. The efficacy of capsule endoscopy in detecting upper gastrointestinal tract and small intestinal bleeding was evaluated.Results:A total of 74 patients underwent bedside capsule endoscopy for suspected acute or severe gastrointestinal bleeding. Five patients were excluded due to failure of examination due to retention of capsule endoscope in the gastric lumen, and 69 were included in the study, of whom 54 patients with a definitive diagnosis of gastrointestinal hemorrhage. The positive detection rate of the capsule endoscopy was 83.33% (45/54), including 17 cases of ulcer, 5 cases of erosion, 5 cases of vascular malformation, 4 protrusion mass, 4 diverticulum, 5 obscure gastrointestinal bleeding, 1 stenosis , 1 active mucosal blood exudation, 1 gastric retention, 1 mucosal swelling, and 1 mucosal wrinkle change. The sensitivity and specificity of capsule endoscopy in the diagnosis of upper gastrointestinal bleeding were 92.31% (12/13) and 75.00% (3/4) respectively. The sensitivity and specificity of capsule endoscopy for diagnosing small intestinal bleeding were 80.49% (33/41) and 90.91% (10/11) respectively.Conclusion:Bedside capsule endoscopy demonstrates high sensitivity and specificity in the diagnosis of gastrointestinal bleeding, showing potential advantages in bedside applications for acute and severe gastrointestinal bleeding.

Objective To construct a time series analysis fusion tool using multisource internet data and then accurately predict the incidence trend of hepatitis in Chongqing.Methods The incidence rate of hepatitis were obtained from the database of the Centre for Health and Disease Control.Air pollutant data were obtained from the official website of the China Environmental Monitoring Station,climate data were obtained from the National Meteorological Galaxy Center,and network index data were obtained through Baidu search engine.The time duration was from November 2013 to May 2023.Based on existing time series analysis methods,multisource data were used to correct the residual part of the decomposition model.A delayed input neural network(DINN)was constructed based on the respective advantages of non autoregressive(NAR)and long short-term memory(LSTM)recurrent neural networks.Afterwards,optimization modules such as the Nutcracker Optimization Algorithm(NOA)and Joint Quantile Huber Loss(JQHL)were added to the foundation,and then DINN+was constructed.Results Compared to common single-input models and synchronous multi-input models,DINN achieved the best prediction performance.After adding hyperparameters and loss function optimization,the predictive performance of DINN+was further improved,with a mean-square error(MSE)of 0.170 9,a mean absolute error(MAE)of 0.461 2,a root-mean-square error(RMSE)of 0.582 1,a mean absolute percentage error(MAPE)of 0.062 6,and a R-square(R2)of 0.884 0 in a testing set.Conclusion Based on the ideas of diverse methods and multidimensional data fusion,we propose a DINN+optimization model with good accuracy and generalization ability on the basis of previous time series analysis.This model enriches and supplements the methodological research content of using multisource data to calibrate infectious disease time series prediction analysis and can serve as a new benchmark for future analysis of influencing factors and trend prediction of infectious disease public health.