Osteoporosis is a systemic disease, and epidemiological projections indicate that by 2050, approximately 23.43% of the Chinese population over 50 years of age will be affected. Given the poor prognosis associated with osteoporosis, the exploration of safe and effective natural products is of considerable significance. Studies investigating the chemical constituents of traditional Chinese medicine in cellular and/or animal models have demonstrated bone-protective effects. Although most of these compounds lack clinical data, they hold considerable potential as lead candidates for drug development. In-depth study of the structure-activity relationship of these natural products not only contributes to elucidating the mechanisms of action but also provides a theoretical basis for the development of novel antiosteoporosis therapies. This review summarizes natural products with potential antiosteoporotic effects reported between 2020 and 2024. Overall, plant-derived natural compounds exhibit antiosteoporotic effects by regulating bone remodeling, inflammation, and oxidative stress, highlighting their promise as multitarget therapeutic candidates.

OBJECTIVE To explore the application of autoregressive integrated moving average model(ARIMA)in prediction of prevalence trends of carbapenem-resistant Klebsiella pneumoniae(CRKP)in intensive care unit(ICU)so as to provide scientific bases for formulating prevention strategies for CRKP infection in ICU.METHODS The number of CRKP strains that were monthly isolated from the ICU patients of Jiangnan University Affiliated Hospital between Jan.2021 and Jan.2024 was collected,the duplicate samples from the same patient were excluded,and totally 555 strains of CRKP were finally enrolled in the study.The time series differencing was performed by using R statistical software,the ARIMA model was established,the parameters of the model were determined by means of autocorrelation function(ACF)and partial autocorrelation function(PACF)images.The optimal model was screened out by Akaike information criterion(AIC)and root-mean-square error(RMSD),the robustness of the residual sequences was assessed by Box-Ljung test.The data that were detected from Sep.2023 to Jan.2024 were assigned as the validation set,the prediction accuracy of the model was assessed,and the dy-namic trend of the CRKP strains from Feb.2024 to Apr.2024 was predicted.RESULTS The isolation rate of CRKP strains in ICU showed dynamic change from 2021 to 2023(x2=66.906,P=0.001),sputum and midstream urine were the major sources.The minimal AIC of the optimal ARIMA model(8,1,10)was 222.1,with RMSE 3.67.Box-Ljung(x2=0.104,P=0.746)test indicated that there was no autocorrelation among the residual se-quences.Both the actual CRKP and the predictive value firstly rose then descended from Sep.2023 to Jan.2024,and the average relative error of the model was 9.62％for prediction.The number of isolated CRKP strains predic-ted by the model might reached to the lowest point in Feb.2024 and then showed an upward trend,and it might reach to a high peak in Apr.CONCLUSION ARIMA model is effective for short-term prediction and dynamic anal-ysis of prevalence trend of CRKP strains in the ICU so as to provide theoretical basis for early warning of hospital-associated infection and take corresponding prevention measures.

OBJECTIVE To explore the application of autoregressive integrated moving average model(ARIMA)in prediction of prevalence trends of carbapenem-resistant Klebsiella pneumoniae(CRKP)in intensive care unit(ICU)so as to provide scientific bases for formulating prevention strategies for CRKP infection in ICU.METHODS The number of CRKP strains that were monthly isolated from the ICU patients of Jiangnan University Affiliated Hospital between Jan.2021 and Jan.2024 was collected,the duplicate samples from the same patient were excluded,and totally 555 strains of CRKP were finally enrolled in the study.The time series differencing was performed by using R statistical software,the ARIMA model was established,the parameters of the model were determined by means of autocorrelation function(ACF)and partial autocorrelation function(PACF)images.The optimal model was screened out by Akaike information criterion(AIC)and root-mean-square error(RMSD),the robustness of the residual sequences was assessed by Box-Ljung test.The data that were detected from Sep.2023 to Jan.2024 were assigned as the validation set,the prediction accuracy of the model was assessed,and the dy-namic trend of the CRKP strains from Feb.2024 to Apr.2024 was predicted.RESULTS The isolation rate of CRKP strains in ICU showed dynamic change from 2021 to 2023(x2=66.906,P=0.001),sputum and midstream urine were the major sources.The minimal AIC of the optimal ARIMA model(8,1,10)was 222.1,with RMSE 3.67.Box-Ljung(x2=0.104,P=0.746)test indicated that there was no autocorrelation among the residual se-quences.Both the actual CRKP and the predictive value firstly rose then descended from Sep.2023 to Jan.2024,and the average relative error of the model was 9.62％for prediction.The number of isolated CRKP strains predic-ted by the model might reached to the lowest point in Feb.2024 and then showed an upward trend,and it might reach to a high peak in Apr.CONCLUSION ARIMA model is effective for short-term prediction and dynamic anal-ysis of prevalence trend of CRKP strains in the ICU so as to provide theoretical basis for early warning of hospital-associated infection and take corresponding prevention measures.

Objective:To screen high-risk population of chronic obstructive pulmonary disease (COPD) and to analyze the risk factors in Haicang District of Xiamen City.Methods:A questionnaire survey was conducted from February 2023 to May 2023 among residents who visited or underwent physical examinations at five community health service centers in Haicang District of Xiamen City selected by cluster sampling method. The self-designed general information questionnaire, COPD population screening questionnaire (COPD-PS) and COPD screening questionnaires (COPD-SQ) were applied in the survey. Individuals with COPD-PS scale>5 or COPD-SQ scale>16 were defined as COPD high-risk group. The association of COPD risk with gender, age, smoking, family history of COPD, history of tuberculosis, history of COVID-19 infection, and using coal/woodstove for cooking or heating was analyzed with chi-square test and binary logistic regression analysis.Results:A total of 4 260 questionnaires were distributed and 4 221 valid questionnaires were collected with a recovery rate of 99.6%. Among all respondents there were 1 904 males (45.11%) and 2 317 females (54.89%); and 217 individuals aged 40-<50 (5.14%), 434 aged 50-<60 (10.28%), 2 194 aged 60-<70 (51.98%), 1 302 aged 70-<80 (30.85%) and 74 aged≥80 (1.76%). The results showed that there were 269 respondents (6.4%) scored≥5 on the COPD-PS scale, 534 residents (12.7%) scored≥16 on the COPD-SQ scale, 646 (15.3%) scored≥5 on the COPD-PS scale or≥16 on the COPD-SQ scale. Male gender ( OR=2.592, 95% CI:2.135-3.146), second-hand smoke exposure ( OR=3.763, 95% CI:2.944-4.810), frequently catching cold before the age of 14 ( OR=3.804, 95% CI:2.927-4.944), history of tuberculosis ( OR=2.575, 95% CI:1.224-5.418), hypertension ( OR=1.547, 95% CI:1.277-1.875), and diabetes ( OR=1.791, 95% CI:1.027-3.121) were independently associated with the high-risk of COPD, while the history of COVID-19 ( OR=0.583, 95% CI:0.476-0.714) was a protective factor for COPD risk. Conclusion:Males, exposure to second-hand smoke, frequently catching cold before the age of 14, history of tuberculosis, hypertension, and diabetes will increase the risk of COPD, while the history of COVID-19 is a protective factor.

Objective:To optimize the forming technology of Zuojin concentrated pills. Methods: Single factor test was used to optimize the types of excipients and wetting agents with the shaping result as the index. Orthogonal test was used to optimize the forming technology taking the dissolution time,shaping rate and appearance quality as the evaluation indices,and the proportion of excipients, the rate of drugs to excipients and wetting agent amount as the investigation factors. Results: The best forming technology of Zuojin concentrated pills was as follows:MCC and PVP-K30 were used as the excipients with the ratio of 3:1,the ratio of drugs to excipients was 1:1,5% water was used as the wetting agent to obtain the damp mass,and then Zuojin concentrated pills were prepared in a pill machine. Conclusion:The optimized forming technology is stable with good reproducibility,and the pills are round and smooth with u-niform color,whose quality meets the requirements described in Chinese Pharmacopoeia(2015 edition,partⅣ,page 0108 for concen-trated pills). The study provides reference for the further study.

Objective To investigate the effects of desflurane on hemodynamics in aged patients.Methods Thirty ASA gradeⅠ Ⅱaged patients,scheduled for elective surgery,were studied. Anesthesia was induced with intravenous thiopentol,succinylcholine and fentanyl.After intubation coesophageal Doppler monitor was performed to measure CO,PV,HR,FTC,CVP,CI,MAP and SVR following inhalation of desflurane at 0 5MAC,1 0MAC,1 5MAC and 2 0MAC respectively.Results Compared with those before inhalation desflurane,MAP and SVR decreased more significantly at 1 0MAC,1 5MAC and 2 0MAC(P0 05),HR and FTC increased significantly at 1.0MAC,1.5MAC and 2.0MAC(P