The medicinal use of Malvae Semen has a long history. In this paper， by consulting the ancient materia medica， prescription， agronomy， literature and other aspects of the classics， the name， origin， evolution of scientific name， quality， harvesting and processing， functions and indications and others of Malvae Semen were systematically sorted out and verified， so as to provide a basis for the development and utilization of famous classical formulas containing this herb. According to the textual research， Shennong Bencaojing began to use Dongkuizi as the correct name， which was used in the past dynasties， and there were also aliases such as Kuicaizi， Huacai， and Kuizi. Through the original research， it can be seen that Kuicai is the mainstream original plant of Malvae Semen， that is， Malva verticillata var. crispa， the Alcea rosea and M. cathayensis are also used. In modern times， the seeds of Abutilon theophrasti have been passed off as Malvae Semen， while the seeds of M. verticillata var. crispa have rarely been used in medicine. And Abutili Semen has been another medicinal material with different efficacy since the collection of Newly Revised Materia Medica in the Tang dynasty. Since the Ming and Qing dynasties， the cultivation of Kuicai has been decreasing， while A. theophrasti is more common and easy to obtain， and Abutili Semen and Malvae Semen are similar in morphology and confused， which should be corrected. In addition， Malvae Fructus is a Mongolian customary medicinal herb， which is different from the traditional use of seeds in traditional Chinese medicine. Kuicai， as an important vegetable in history， was widely cultivated and gradually shrunk after the Song dynasty， it is now mainly produced in southern provinces. The quality evaluation of Malvae Semen is better for those with dry bodies， full grain， grayish brown color， no mud， and no impurities. The harvesting is generally in the autumn and winter. After drying， it is seeded， sieved peel and impurities， mashed， or slightly stir-fried to yellow-white color with gentle fire. It is sweet， cold and slippery in nature and taste， with the main effects of laxation， diuresis， lactation and elimination of swelling. The efficacy of Abutili Semen is clearing heat and removing toxicity， promoting diuresis and removing nebula， the efficacy is quite different from that of Malvae Semen. Based on the results of textual research， it is suggested that M. verticillata var. crispa should be used as the medicinal source of Malvae Semen in the development of famous classical formulas， the corresponding processing methods should be selected according to the requirements of drug processing in the formulas， while the raw products are recommended to be used if the processing is not specified.

The medicinal use of Malvae Semen has a long history. In this paper， by consulting the ancient materia medica， prescription， agronomy， literature and other aspects of the classics， the name， origin， evolution of scientific name， quality， harvesting and processing， functions and indications and others of Malvae Semen were systematically sorted out and verified， so as to provide a basis for the development and utilization of famous classical formulas containing this herb. According to the textual research， Shennong Bencaojing began to use Dongkuizi as the correct name， which was used in the past dynasties， and there were also aliases such as Kuicaizi， Huacai， and Kuizi. Through the original research， it can be seen that Kuicai is the mainstream original plant of Malvae Semen， that is， Malva verticillata var. crispa， the Alcea rosea and M. cathayensis are also used. In modern times， the seeds of Abutilon theophrasti have been passed off as Malvae Semen， while the seeds of M. verticillata var. crispa have rarely been used in medicine. And Abutili Semen has been another medicinal material with different efficacy since the collection of Newly Revised Materia Medica in the Tang dynasty. Since the Ming and Qing dynasties， the cultivation of Kuicai has been decreasing， while A. theophrasti is more common and easy to obtain， and Abutili Semen and Malvae Semen are similar in morphology and confused， which should be corrected. In addition， Malvae Fructus is a Mongolian customary medicinal herb， which is different from the traditional use of seeds in traditional Chinese medicine. Kuicai， as an important vegetable in history， was widely cultivated and gradually shrunk after the Song dynasty， it is now mainly produced in southern provinces. The quality evaluation of Malvae Semen is better for those with dry bodies， full grain， grayish brown color， no mud， and no impurities. The harvesting is generally in the autumn and winter. After drying， it is seeded， sieved peel and impurities， mashed， or slightly stir-fried to yellow-white color with gentle fire. It is sweet， cold and slippery in nature and taste， with the main effects of laxation， diuresis， lactation and elimination of swelling. The efficacy of Abutili Semen is clearing heat and removing toxicity， promoting diuresis and removing nebula， the efficacy is quite different from that of Malvae Semen. Based on the results of textual research， it is suggested that M. verticillata var. crispa should be used as the medicinal source of Malvae Semen in the development of famous classical formulas， the corresponding processing methods should be selected according to the requirements of drug processing in the formulas， while the raw products are recommended to be used if the processing is not specified.

BACKGROUND: The role of inflammation in the development of gestational diabetes mellitus (GDM) has recently become a focus of research. The systemic immune-inflammation index (SII) and systemic inflammation response index (SIRI), novel indices, reflect the body's chronic immune-inflammatory state. This study aimed to investigate the associations between the SII or SIRI and GDM. METHODS: A prospective birth cohort study was conducted at Beijing Obstetrics and Gynecology Hospital from February 2018 to December 2020, recruiting participants in their first trimester of pregnancy. Baseline SII and SIRI values were derived from routine clinical blood results, calculated as follows: SII = neutrophil (Neut) count × platelet (PLT) count/lymphocyte (Lymph) count, SIRI = Neut count × monocyte (Mono) count/Lymph count, with participants being grouped by quartiles of their SII or SIRI values. Participants were followed up for GDM with a 75-g, 2-h oral glucose tolerance test (OGTT) at 24-28 weeks of gestation using the glucose thresholds of the International Association of Diabetes and Pregnancy Study Groups (IADPSG). Logistic regression was used to analyze the odds ratios (ORs) (95% confidence intervals [CIs]) for the the associations between SII, SIRI, and the risk of GDM. RESULTS: Among the 28,124 women included in the study, the average age was 31.8 ± 3.8 years, and 15.76% (4432/28,124) developed GDM. Higher SII and SIRI quartiles were correlated with increased GDM rates, with rates ranging from 12.26% (862/7031) in the lowest quartile to 20.10% (1413/7031) in the highest quartile for the SII ( Ptrend <0.001) and 11.92-19.31% for the SIRI ( Ptrend <0.001). The ORs (95% CIs) of the second, third, and fourth SII quartiles were 1.09 (0.98-1.21), 1.21 (1.09-1.34), and 1.39 (1.26-1.54), respectively. The SIRI findings paralleled the SII outcomes. For the second through fourth quartiles, the ORs (95% CIs) were 1.24 (1.12-1.38), 1.41 (1.27-1.57), and 1.64 (1.48-1.82), respectively. These associations were maintained in subgroup and sensitivity analyses. CONCLUSION The SII and SIRI are potential independent risk factors contributing to the onset of GDM.
Humans ; Female ; Pregnancy ; Diabetes, Gestational/immunology* ; Prospective Studies ; Adult ; Inflammation/immunology* ; Glucose Tolerance Test ; Birth Cohort

ObjectiveTo analyze the epidemiological characteristics of clustered vomiting and diarrhea outbreaks in Minhang District of Shanghai, to identify the influencing factors of outbreak scale and duration of epidemic, and to provide scientific evidence for further strengthening surveillance early-warning efforts in key settings and for optimizing prevention and control measures. MethodsThe data for describing epidemiological characteristics of clustered vomitting and diarrhea outbreaks in Minhang District from 2018 to 2023 were collected, multivariable logistic regression models were applied to analyze the influencing factors for epidemic scale,and Spearman rank correlation analyses were applied to analyze the factors duration. ResultsA total of 136 clustered vomiting and diarrhea outbreaks were reported in Minhang District from 2018 to 2023, all occurring in school settings, with an overall attack rate of 0.90%. The outbreaks exhibited distinct seasonality, predominantly occurring from October to December (43.38%) and March to May (32.35%). The primary settings were preschools (45.59%) and elementary schools (44.12%), with students accounted for the majority of cases (99.48%). The predominant clinical manifestation was vomiting (90.44%), with person-to-person contact being the primary transmission route (98.53%). Norovirus genogroup Ⅱ was identified as the main pathogen (71.32%). Standardized terminal disinfection of outbreak sites (OR=0.39, 95%CI=0.20‒0.74) and effective isolation of affected classes (OR=0.23, 95%CI=0.09‒0.57) were significant protective factors for reducing outbreak scale. Both response time (r=0.64, P<0.001) and the number of case generations (r=0.71, P<0.001) showed positive correlations with outbreak duration. ConclusionSchools are the key settings for the prevention and control of clustered vomiting and diarrhea outbreaks in Minhang District, with peak occurring in autumn and spring. Early detection, timely reporting, and prompt response to outbreaks are crucial. Strengthening school-based surveillance systems and standardizing outbreak management protocols are of particular importance.

Objective: To understand current situation epidemiology and associated factors of suicidal ideation among high school students in Yixing, so as to provide basis for targeted intervention. Methods: From March to May 2019, a questionnaire survey was conducted on 12 799 students from 3 junior high schools and 4 senior high schools in Yixing City, Jiangsu Province, using a stratified cluster random sampling method. Latent profile analysis was used to classify suicidal ideation among high school students, the chi square test was used to compare the differences in suicidal ideation among different characteristics of students, multiple Logistic regression was used to analyze influencing factors, a risk predictive nomogram model was constructed and then verified. Results: Three latent classes of suicidal ideation among high school students was divided into three categories were observed: none or mild, moderate, and severe. Among them, 3 034 (23.7%) had moderate suicidal ideation and 753 (5.9%) had severe suicidal ideation. The Logistic regression results showed that gender was female, academic performance was lower midrange, smoking, drinking, popularity with classmates(less popular and unpopularity), family member relationships(general/occasional contradictions/contradictions), trust in others(more trusted/less trusted/less trusted at all), past or current relationships, physical bullying, relationship bullying, verbal bullying, and sexual bullying were the influencing factors for severe suicidal ideation among students ( OR =3.27； 2.18 ；1.63；1.72；2.66, 6.05；3.00,3.29, 6.38；1.71, 6.04, 12.48； 2.50； 1.59； 2.16； 1.45； 1.63, P <0.05). The nomogram prediction model had good discrimination. Conclusions Suicide ideation is influenced by multiple factors. Family and peer situations, as well as being bullied, are all related to the degree the severity of suicidal ideation. Efforts can be made to improve students family and interpersonal relationships, control bullying, then reduce their suicidal ideation which might help prevent suicide ideation among students.

Abstract: This study aims to find out the causes for the dissolution of unqualified samples found during evaluation sampling of lansoprazole enteric-coated preparations by the laser infrared imaging system and orbitrap high resolution mass spectrometry, with suggestions for improvement. Lansoprazole enteric-coated preparations were tested by current standard, the dissolution of a batch of samples was below the limit and other items were in line with the standard. Considering that this product is unstable to acid and alkali, the following exploratory experiments were designed from different dimensions, based on the conclusion of the unannounced inspection of the company, to explore the reasons for the unqualified batch, including the influence of high-temperature and high-humidity storage environment on the key quality properties of the sample, the influence of 2-hour acid resistance test on dissolution result, the imaging of the core and the measure of coating layer thickness, the optimization of chromatographic conditions of related substances, and the analysis of the source of impurities. It was found that improper storage in circulation and poor coating process caused the low dissolution of this batch: the high-temperature and high-humidity storage environment possible in the circulation process led to the decreasing efficacy of disintegrating agent in the samples and thus the difficulty to release the active pharmaceutical ingredient fully; the coating solution could not be uniformly sprayed on the core, resulting in thin isolation layer and different thickness, which then affected the protection of the main drug against acid degradation. The above two reasons together resulted in unqualified dissolution of this batch. The overall quality of lansoprazole enteric-soluble preparation is good, but the formulation and process in some companies need to be optimized; and the temperature and humidity in the circulation process need to be controlled in strict accordance with the regulations.

BACKGROUND:Traditional 3D dental segmentation methods usually utilize predefined spatial geometric features,such as curvature and normal vectors,as the reference information for tooth segmentation. OBJECTIVE:To propose an algorithm for complex 3D dental segmentation and deeply explore the correlation between segmentation results and application scenarios. METHODS:A 3D dental segmentation algorithm based on dual stream extraction of structural features and spatial features was established,and the modular design of split flow was used to avoid feature confusion.Among them,the attention mechanism on the structural feature flow was used to capture the fine-grained semantic information required for tooth segmentation,and the Tran Net based on the spatial feature flow was used to ensure the robustness of the model to complex tooth and jaw segmentation.This algorithm verified its effectiveness and reliability based on clinical datasets including healthy dental jaws and complex dental jaws such as missing teeth,malocclusion and dentition crowding.The segmentation performance of the model was measured in terms of overall accuracy,mean intersection over union,and directional cut discrepancy. RESULTS AND CONCLUSION:The overall segmentation accuracy of this algorithm in the clinical data set is 97.08%,and the segmentation effect is superior to that of other competitive methods from the qualitative and quantitative perspectives.It is verified that the structural feature flow designed in this paper can extract more precise local details of tooth shape from coordinate and normal information by constructing an attention aggregation mechanism,and the spatial feature flow designed in this paper can ensure the robustness of the model to complex teeth such as missing teeth,dislocated teeth,and crowded dentition by constructing a transformation network(Tran Net).Therefore,this tooth segmentation algorithm is highly reliable for clinicians'practical reference.

Objective: To investigate the changes of microorganisms and metabolites in joint effusion of patients with Rheumatoid arthritis(RA), Osteoarthritis(OA) and Urarthritis(UA). To provide new ideas for the study of the effect of microbiota on the pathogenesis of arthritis. Methods: Joint effusion samples were collected from 20 patients with RA, 20 patients with OA, and 20 patients with UA. 16S rRNA gene sequencing and untargeted ultra-high performance Liquid chromatography-mass spectrometry(LC-MS) were used to explore the differences in microorganisms and metabolites among the three groups. Pearson correlation analysis was used to detect the correlation between effusion microbiota and metabolites. Results: There were differences in microbial diversity and microbiota composition among the three groups. Combined with VIP>1 from OPLS-DA andP<0.05 from two-tailed Students t-test, 45 differential metabolites(Between RA and OA groups), 38 differential metabolites(Between UA and OA groups) and 16 differential metabolites(Between RA and UA groups), were identified. GO analysis and KEGG pathway analysis showed that the differential metabolic pathways among the three groups were mainly concentrated in citric acid cycle(TCA cycle), nucleotide metabolism, amino acid metabolism and glycolysis pathway. Correlation analysis of joint effusion microbiota and metabolites suggested that bacteria enriched in the three groups of joint effusion, such asPrevotella,Clostridium ruminosus,Prevotellaceae＿UCG-001, were related to many key metabolites such as lysozyme, uric acid, glucose, and L-glutamine. Conclusion This study shows that there are a variety of bacterial flora in joint cavity effusion of RA, OA, and UA patients, and the differential metabolites produced by them are involved in the pathogenesis of the three types of arthritis by affecting a variety of metabolic pathways.

Objective: To explore cyberbullying and risk factors of middle school students, and to provide a reference for cyberbullying prevention in school settings. Methods: A stratified cluster random sampling method was used to select 12 940 students from three junior high schools and four senior high schools in Yixing City of Jiangsu Province, China, to conduct a questionnaire survey from March 1 to May 31, 2019. The Chi -square test was performed to compare differences in the prevalence of cyberbullying among groups with different sociodemographic characteristics, and the multivariate Logistic regression model was employed to analyze the risk factors. A risk predictive nomogram model was constructed and then verified. Results: Middle school students were found to be victims of cyberbullying at a rate of 12.3%. The Logistic regression results showed that alcohol use ( OR =1.93), lack of emotional management ( OR =1.30), feeling unsafe ( OR =1.70), not trusting people ( OR =1.66), increased daily online time ( OR =1.39), higher frequency of using social software or websites ( OR =2.24), poor relationships with family members ( OR =1.46), parental neglect ( OR =1.50), class leadership ( OR =1.30) and poor relationships with classmates ( OR =1.34) were risk factors for middle school students who were victims of cyberbullying ( P <0.05). Based on these 10 independent risk factors, the nomogram prediction model, had good discrimination ( AUC =0.73). Conclusion Cyberbullying is common among middle school students. Internet use, parental neglect and class leadership all have an impact on cyberbullying.

Background/Aims: The accuracy of endosonographers in diagnosing gastric subepithelial lesions (SELs) using endoscopic ultrasonography (EUS) is influenced by experience and subjectivity. Artificial intelligence (AI) has achieved remarkable development in this field. This study aimed to develop an AI-based EUS diagnostic model for the diagnosis of SELs, and evaluated its efficacy with external validation. Methods: We developed the EUS-AI model with ResNeSt50 using EUS images from two hospitals to predict the histopathology of the gastric SELs originating from muscularis propria. The diagnostic performance of the model was also validated using EUS images obtained from four other hospitals. Results: A total of 2,057 images from 367 patients (375 SELs) were chosen to build the models, and 914 images from 106 patients (108 SELs) were chosen for external validation. The sensitivity, specificity, positive predictive value, negative predictive value, and accuracy of the model for differentiating gastrointestinal stromal tumors (GISTs) and non-GISTs in the external validation sets by images were 82.01%, 68.22%, 86.77%, 59.86%, and 78.12%, respectively. The sensitivity, specificity, positive predictive value, negative predictive value, and accuracy in the external validation set by tumors were 83.75%, 71.43%, 89.33%, 60.61%, and 80.56%, respectively. The EUS-AI model showed better performance (especially specificity) than some endosonographers.The model helped improve the sensitivity, specificity, and accuracy of certain endosonographers. Conclusions We developed an EUS-AI model to classify gastric SELs originating from muscularis propria into GISTs and non-GISTs with good accuracy. The model may help improve the diagnostic performance of endosonographers. Further work is required to develop a multi-modal EUS-AI system.