Objective: To investigate the prevalence and influencing factors of menopausal syndrome among postmenopausal women in Pan'an County, Zhejiang Province, so as to provide the basis for guiding the health management of postmenopausal women. Methods: From May 2023 to April 2024, the postmenopausal women aged 40 to 69 years in Pan'an County were selected using the random cluster sampling method. Demographic information, lifestyle and prevalence of gynecological diseases were collected through questionnaire surveys. The prevalence of menopausal syndrome was assessed by modified Kupperman Score Scale. Factors affecting menopausal syndrome were analyzed by a multivariable logistic regression model. Results: A total of 816 postmenopausal women were surveyed, with an mean age of (57.63±2.92) years and a mean natural menopause age of (49.85±2.13) years. There were 574 cases with menopausal syndrome, with a prevalence of 70.34%. Flashes and sweating, insomnia and irritability were common symptoms, accounting for 62.87%, 47.43% and 41.18%, respectively. Multivariable logistic regression analysis showed that monthly personal income of ≤5 000 yuan (<3 000 yuan, OR=3.124, 95%CI: 1.829-5.335; 3 000-5 000 yuan, OR=2.399, 95%CI: 1.370-4.201) and having gynecological diseases (OR=1.970, 95%CI: 1.292-3.004) were associated with a higher risk of menopausal syndrome, while average (OR=0.141, 95%CI: 0.072-0.276) or sufficient sleep quality (OR=0.095, 95%CI: 0.049-0.185) were associated with a lower risk of menopausal syndrome. Conclusion The prevalence of menopausal syndrome among postmenopausal women in Pan'an County is relatively high, and is mainly influenced by personal economic status, sleep quality and the presence of gynecological diseases.

The auxin/indole-3-acetic acid (Aux/IAA) gene family is an important regulator for plant growth hormone signaling, involved in plant growth, development, as well as response to environmental stresses. In the present study, we identified SmIAA7 which is potentially associated with Salvia miltiorrhiza leaf development through comparatively analyzed the transcriptome data from different pinnate leaves. SmIAA7 was successfully isolated from S. miltiorrhiza using the specific primers. Then subsequent bioinformatic analysis, prokaryotic expression and purification, subcellular localization, and induction expression analysis under auxin and abiotic stress were performed. The full-length of SmIAA7 contained an ORF of 684 bp encoding a protein of 227 amino acid with a molecular weight of 25.3 kD. Conserved domain analysis showed that SmIAA7 contains the conserved Aux_IAA domain (pfam02309). Sequence analysis and phylogenetic tree analysis results indicated SmIAA7 was phylogenetically close to IAA7 and IAA14 from other plants, suggesting SmIAA7 involved in plant growth and development as well as response to environmental stresses. The prokaryotic expression vector pET28a-SmIAA7 was constructed and SmIAA7 recombinant protein was successfully expressed in E. coli Rosetta (DE3) strain. Subcellular localization experiment demonstrated that SmIAA7 localized in the nucleus of plant cells. Real-time fluorescence quantitative PCR results showed that the expression level of SmIAA7 was upregulated in response to auxin. Drought, low temperature, and salt stress significantly increased the transcript level of SmIAA7 gene. This study lays a foundation for further elucidating the role of SmIAA7 in leaf development, signal transduction, and stress defense in S. miltiorrhiza.

ObjectiveTo explore the effectiveness of health information dissemination and its influencing factors using the "Shanghai CDC" WeChat public account as a case study, providing references for public health institutions to optimize the use of official new media platforms for effective publicity. MethodsA total of 1 030 headline articles published on the "Shanghai CDC" WeChat public account between 2016 and 2019 were analyzed using content analysis and non-parametric tests to examine the impact of factors such as titles and content categories. ResultsFrom 2016 to 2019, the number of WeChat public account followers increased by 280 000, with the articles accumulating over 8.8 million views. The median (P₂₅, P₇₅) open rate of articles was 5.90% (3.69%, 10.31%), and the median (P₂₅, P₇₅) sharing and forwarding rate was 6.60% (4.25%, 9.17%). Factors such as the use of first- and second-person pronouns, degree adverbs, negative adverbs, explicit viewpoints, and title length all significantly affected the open rate of articles, with OR (95%CI) values of 0.175 (0.041‒0.756), 32.606 (2.350‒452.432), 4.079 (1.093‒15.230), 0.106 (0.028‒0.409), and 1.184 (1.063‒1.319),respectively (all P<0.05). In terms of content, statistical significant differences in dissemination effectiveness were observed across article categories and themes (P<0.05). In terms of article categories, articles related to news hotspots and service information had higher open rates of 9.58% and 14.00%, respectively. These two types of articles also obtained higher sharing and forwarding rates of 7.65% and 9.16%, respectively. In terms of article topics, compared with healthy life and health products, among the top four topics in terms of publication volume, the open rates of articles about infectious diseases and disease-causing biology and immunization programs were higher, accounting for 7.88% and 6.88%, respectively, with no significant difference in sharing and forwarding rates. ConclusionThe "Shanghai CDC" WeChat public account demonstrated good dissemination effectiveness. Enhancing article titles by increasing informational content and degree adverbs (e.g., "highly," "most," and "extremely") and negative adverbs (e.g., "no") can improve dissemination reach. Public health WeChat accounts should incorporate news hotspots or service information in their articles. While maintaining their strengths in disseminating knowledge on infectious diseases and immunization programs, they should also enhance public education in other professional fields within their scope of responsibility to improve the overall dissemination impact of health information.

Surface plasmon resonance （SPR） sensor is an optical detection technique enables real-time and dynamic monitoring of biological samples. SPR-based biosensors have remarkable characteristics such as label-free detection and high sensitivity, making them important tools for studying molecular interactions. The recognition element, which plays a critical role in SPR sensors,which could specifically identify and capture of target analytes, closely influencing the selectivity performance of the sensor. The progress on SPR sensors in pharmaceutical research were reviewed, which focused on the application of recognition elements such as antibodies, aptamers, molecularly imprinted polymers, and metal nanoparticles.

Objective: To explore glymphatic impairment in pediatric refractory epilepsy (RE) using multi-parameter magnetic resonance imaging (MRI), assess its relationship with white-matter (WM) abnormalities and clinical indicators, and preliminarily evaluate the performance of multi-parameter MRI in discriminating RE from drug-sensitive epilepsy (DSE). Materials and Methods: We retrospectively included 70 patients with DSE (mean age, 9.7 ± 3.5 years; male:female, 37:33) and 26 patients with RE (9.0 ± 2.9 years; male:female, 12:14). The diffusion tensor imaging analysis along the perivascular space (DTI-ALPS) index as well as fractional anisotropy (FA), mean diffusivity (MD), and nodal efficiency values were measured and compared between patients with RE and DSE. With sex and age as covariables, differences in the FA and MD values were analyzed using tract-based spatial statistics, and nodal efficiency was analyzed using a linear model. Pearson’s partial correlation was analyzed. Receiver operating characteristic (ROC) curves were used to evaluate the discrimination performance of the MRI-based machine-learning models through five-fold cross-validation. Results: In the RE group, FA decreased and MD increased in comparison with the corresponding values in the DSE group, and these differences mainly involved the callosum, right and left corona radiata, inferior and superior longitudinal fasciculus, and posterior thalamic radiation (threshold-free cluster enhancement, P < 0.05). The RE group also showed reduced nodal efficiency, which mainly involved the limbic system, default mode network, and visual network (false discovery rate, P < 0.05), and significantly lower DTI-ALPS index (F = 2.0, P = 0.049). The DTI-ALPS index was positively correlated with FA (0.25 ≤ r ≤ 0.32) and nodal efficiency (0.22 ≤ r ≤ 0.37), and was negatively correlated with the MD (-0.24 ≤ r≤ -0.34) and seizure frequency (r = -0.47). A machine-learning model combining DTI-ALPS, FA, MD, and nodal efficiency achieved a cross-validated ROC curve area of 0.83 (sensitivity, 78.2%; specificity, 84.8%). Conclusion Pediatric patients with RE showed impaired glymphatic function in comparison with patients with DSE, which was correlated with WM abnormalities and seizure frequency. Multi-parameter MRI may be feasible for distinguishing RE from DSE.

Objective: To explore glymphatic impairment in pediatric refractory epilepsy (RE) using multi-parameter magnetic resonance imaging (MRI), assess its relationship with white-matter (WM) abnormalities and clinical indicators, and preliminarily evaluate the performance of multi-parameter MRI in discriminating RE from drug-sensitive epilepsy (DSE). Materials and Methods: We retrospectively included 70 patients with DSE (mean age, 9.7 ± 3.5 years; male:female, 37:33) and 26 patients with RE (9.0 ± 2.9 years; male:female, 12:14). The diffusion tensor imaging analysis along the perivascular space (DTI-ALPS) index as well as fractional anisotropy (FA), mean diffusivity (MD), and nodal efficiency values were measured and compared between patients with RE and DSE. With sex and age as covariables, differences in the FA and MD values were analyzed using tract-based spatial statistics, and nodal efficiency was analyzed using a linear model. Pearson’s partial correlation was analyzed. Receiver operating characteristic (ROC) curves were used to evaluate the discrimination performance of the MRI-based machine-learning models through five-fold cross-validation. Results: In the RE group, FA decreased and MD increased in comparison with the corresponding values in the DSE group, and these differences mainly involved the callosum, right and left corona radiata, inferior and superior longitudinal fasciculus, and posterior thalamic radiation (threshold-free cluster enhancement, P < 0.05). The RE group also showed reduced nodal efficiency, which mainly involved the limbic system, default mode network, and visual network (false discovery rate, P < 0.05), and significantly lower DTI-ALPS index (F = 2.0, P = 0.049). The DTI-ALPS index was positively correlated with FA (0.25 ≤ r ≤ 0.32) and nodal efficiency (0.22 ≤ r ≤ 0.37), and was negatively correlated with the MD (-0.24 ≤ r≤ -0.34) and seizure frequency (r = -0.47). A machine-learning model combining DTI-ALPS, FA, MD, and nodal efficiency achieved a cross-validated ROC curve area of 0.83 (sensitivity, 78.2%; specificity, 84.8%). Conclusion Pediatric patients with RE showed impaired glymphatic function in comparison with patients with DSE, which was correlated with WM abnormalities and seizure frequency. Multi-parameter MRI may be feasible for distinguishing RE from DSE.

Objective: To explore glymphatic impairment in pediatric refractory epilepsy (RE) using multi-parameter magnetic resonance imaging (MRI), assess its relationship with white-matter (WM) abnormalities and clinical indicators, and preliminarily evaluate the performance of multi-parameter MRI in discriminating RE from drug-sensitive epilepsy (DSE). Materials and Methods: We retrospectively included 70 patients with DSE (mean age, 9.7 ± 3.5 years; male:female, 37:33) and 26 patients with RE (9.0 ± 2.9 years; male:female, 12:14). The diffusion tensor imaging analysis along the perivascular space (DTI-ALPS) index as well as fractional anisotropy (FA), mean diffusivity (MD), and nodal efficiency values were measured and compared between patients with RE and DSE. With sex and age as covariables, differences in the FA and MD values were analyzed using tract-based spatial statistics, and nodal efficiency was analyzed using a linear model. Pearson’s partial correlation was analyzed. Receiver operating characteristic (ROC) curves were used to evaluate the discrimination performance of the MRI-based machine-learning models through five-fold cross-validation. Results: In the RE group, FA decreased and MD increased in comparison with the corresponding values in the DSE group, and these differences mainly involved the callosum, right and left corona radiata, inferior and superior longitudinal fasciculus, and posterior thalamic radiation (threshold-free cluster enhancement, P < 0.05). The RE group also showed reduced nodal efficiency, which mainly involved the limbic system, default mode network, and visual network (false discovery rate, P < 0.05), and significantly lower DTI-ALPS index (F = 2.0, P = 0.049). The DTI-ALPS index was positively correlated with FA (0.25 ≤ r ≤ 0.32) and nodal efficiency (0.22 ≤ r ≤ 0.37), and was negatively correlated with the MD (-0.24 ≤ r≤ -0.34) and seizure frequency (r = -0.47). A machine-learning model combining DTI-ALPS, FA, MD, and nodal efficiency achieved a cross-validated ROC curve area of 0.83 (sensitivity, 78.2%; specificity, 84.8%). Conclusion Pediatric patients with RE showed impaired glymphatic function in comparison with patients with DSE, which was correlated with WM abnormalities and seizure frequency. Multi-parameter MRI may be feasible for distinguishing RE from DSE.

Objective: To explore glymphatic impairment in pediatric refractory epilepsy (RE) using multi-parameter magnetic resonance imaging (MRI), assess its relationship with white-matter (WM) abnormalities and clinical indicators, and preliminarily evaluate the performance of multi-parameter MRI in discriminating RE from drug-sensitive epilepsy (DSE). Materials and Methods: We retrospectively included 70 patients with DSE (mean age, 9.7 ± 3.5 years; male:female, 37:33) and 26 patients with RE (9.0 ± 2.9 years; male:female, 12:14). The diffusion tensor imaging analysis along the perivascular space (DTI-ALPS) index as well as fractional anisotropy (FA), mean diffusivity (MD), and nodal efficiency values were measured and compared between patients with RE and DSE. With sex and age as covariables, differences in the FA and MD values were analyzed using tract-based spatial statistics, and nodal efficiency was analyzed using a linear model. Pearson’s partial correlation was analyzed. Receiver operating characteristic (ROC) curves were used to evaluate the discrimination performance of the MRI-based machine-learning models through five-fold cross-validation. Results: In the RE group, FA decreased and MD increased in comparison with the corresponding values in the DSE group, and these differences mainly involved the callosum, right and left corona radiata, inferior and superior longitudinal fasciculus, and posterior thalamic radiation (threshold-free cluster enhancement, P < 0.05). The RE group also showed reduced nodal efficiency, which mainly involved the limbic system, default mode network, and visual network (false discovery rate, P < 0.05), and significantly lower DTI-ALPS index (F = 2.0, P = 0.049). The DTI-ALPS index was positively correlated with FA (0.25 ≤ r ≤ 0.32) and nodal efficiency (0.22 ≤ r ≤ 0.37), and was negatively correlated with the MD (-0.24 ≤ r≤ -0.34) and seizure frequency (r = -0.47). A machine-learning model combining DTI-ALPS, FA, MD, and nodal efficiency achieved a cross-validated ROC curve area of 0.83 (sensitivity, 78.2%; specificity, 84.8%). Conclusion Pediatric patients with RE showed impaired glymphatic function in comparison with patients with DSE, which was correlated with WM abnormalities and seizure frequency. Multi-parameter MRI may be feasible for distinguishing RE from DSE.

OBJECTIVE To estimate the cost-effectiveness of penpulimab combined with chemotherapy versus chemotherapy alone in first-line treatment of advanced squamous non-small-cell lung cancer （sq-NSCLC）. METHODS From the perspective of Chinese health system， cost-utility analysis was used to evaluate the cost-effectiveness of penpulimab combined with chemotherapy （paclitaxel + carboplatin） versus chemotherapy （paclitaxel + carboplatin） in first-line treatment of sq-NSCLC. A three-health states Markov model was constructed with R packages， and clinical data used in the model were derived from the AK105-302 clinical trial. Costs and utilities were collected from the open-access database and published literature. The quality-adjusted life-years （QALY） was used as the utility index， and the willingness-to-pay （WTP） threshold was set at three times China’s per capita GDP in 2024， equivalent to 287 247 yuan/QALY. The cost-effectiveness of the schemes was evaluated by comparing the incremental cost- utility ratios （ICER） of the two schemes with the WTP threshold. One-way sensitivity analysis and probabilistic sensitivity analysis （PSA） were used to verify the stability of the basic analysis results. RESULTS Compared with chemotherapy， penpulimab combined with chemotherapy increased 0.73 QALY with an incremental cost of 150 681.93 yuan， and the ICER was 206 413.60 yuan/QALY. One-way sensitivity analysis showed that the utility of progression-free survival was the most sensitive factor on ICERs. At the WTP threshold of 3 times China’s per capita GDP， the economic probability of this scheme was 98.80%. At the WTP threshold of 1 times China’s per capita GDP， the probability of ICER being cost-effective was less than 0.01%. CONCLUSIONS For patients with advanced sq-NSCLC， penpulimab combined with chemotherapy is a cost-effective first-line treatment option when WTP threshold is 3 times China’s per capita GDP.

Objective: To explore glymphatic impairment in pediatric refractory epilepsy (RE) using multi-parameter magnetic resonance imaging (MRI), assess its relationship with white-matter (WM) abnormalities and clinical indicators, and preliminarily evaluate the performance of multi-parameter MRI in discriminating RE from drug-sensitive epilepsy (DSE). Materials and Methods: We retrospectively included 70 patients with DSE (mean age, 9.7 ± 3.5 years; male:female, 37:33) and 26 patients with RE (9.0 ± 2.9 years; male:female, 12:14). The diffusion tensor imaging analysis along the perivascular space (DTI-ALPS) index as well as fractional anisotropy (FA), mean diffusivity (MD), and nodal efficiency values were measured and compared between patients with RE and DSE. With sex and age as covariables, differences in the FA and MD values were analyzed using tract-based spatial statistics, and nodal efficiency was analyzed using a linear model. Pearson’s partial correlation was analyzed. Receiver operating characteristic (ROC) curves were used to evaluate the discrimination performance of the MRI-based machine-learning models through five-fold cross-validation. Results: In the RE group, FA decreased and MD increased in comparison with the corresponding values in the DSE group, and these differences mainly involved the callosum, right and left corona radiata, inferior and superior longitudinal fasciculus, and posterior thalamic radiation (threshold-free cluster enhancement, P < 0.05). The RE group also showed reduced nodal efficiency, which mainly involved the limbic system, default mode network, and visual network (false discovery rate, P < 0.05), and significantly lower DTI-ALPS index (F = 2.0, P = 0.049). The DTI-ALPS index was positively correlated with FA (0.25 ≤ r ≤ 0.32) and nodal efficiency (0.22 ≤ r ≤ 0.37), and was negatively correlated with the MD (-0.24 ≤ r≤ -0.34) and seizure frequency (r = -0.47). A machine-learning model combining DTI-ALPS, FA, MD, and nodal efficiency achieved a cross-validated ROC curve area of 0.83 (sensitivity, 78.2%; specificity, 84.8%). Conclusion Pediatric patients with RE showed impaired glymphatic function in comparison with patients with DSE, which was correlated with WM abnormalities and seizure frequency. Multi-parameter MRI may be feasible for distinguishing RE from DSE.