Search

Abstract Background Non-suicidal self-injury (NSSI) is a significant public health concern among adolescents with major depressive disorders (MDD). Although previous research has linked child maltreatment (CM) to NSSI, the precise mechanisms remain unclear. This study aims to investigate the association between CM, cognitive reappraisal (CR), negative coping styles (NC) and NSSI in adolescents with MDD, from the perspectives of both Latent Variable Theory and the Network Theory of Mental Disorder. Methods A sample of 651 adolescents with MDD was recruited from January to December 2023. Data on CM, CR, NC, and NSSI were collected through paper-based self-reported questionnaires. Data analysis primarily involved structural equation modeling and network analysis. Results The reporting rate of NSSI among adolescents with MDD was 48.2%. CM showed a significant positive correlation with NSSI. NSSI was affected by CM through three paths: the mediating role of CR, the mediating role of NC, and the chain mediating role of both CR and NC. Emotional abuse (EA) was the central node, while NSSI, EA, and “The urge to cry quietly when faced with troubles“(NC10) were the key bridge nodes. Conclusions This study is the first to use both structural equation modeling and network analysis to explore the explore the relationship between CM, CR, NC, and NSSI in adolescents with MDD, providing a theoretical basis for future early prevention and targeted interventions for adolescents with MDD.

Abstract Objective The relationship between thyrotropin (TSH), free triiodothyronine (FT3), free thyroxine (FT4) and diabetic kidney disease (DKD) is still controversial, and this study analyzed the correlation between TSH, FT3, FT4 and DKD in patients with type 2 diabetes mellitus (T2DM). Methods T2DM patients (1216) were divided into five groups based on serum TSH, FT3, and FT4 levels, differences in urinary albumin excretion rate (UACR), estimated glomerular filtration rate (eGFR) were compared. Binary logistic regression verified independent correlations among TSH, FT3, FT4 and UACR, eGFR. TSH and FT3 predictive values for DKD were analyzed using receiver operating characteristic (ROC) curves. Results The prevalence of albuminuria with decreased eGFR was higher in T2DM patients with subclinical hypothyroidism and overt hypothyroidism than that in patients with normal thyroid function. TSH positively correlated with UACR (r = 0.133, p

Abstract Background High-grade serous ovarian cancer (HGSOC) is a common gynecologic malignancy with a poor prognosis. The traditional Chinese medicine formula Erzhimaoling decoction (EZMLD) has anticancer potential. This study aims to elucidate the anticancer effects of EZMLD on HGSOC in vitro and in vivo. Materials and methods EZMLD-containing serum was prepared from Sprague–Dawley rats for treating SKOV3 ovarian cancer cells at varying concentrations for 24 h and 48 h to determine the IC50. Concentrations of 0%, 5%, and 10% for 24 h were chosen for subsequent in vitro experiments. The roles of METTL3 and METTL14 in SKOV3 cells were explored by overexpressing these genes and combining EZMLD with METTL3/14 knockdown. Investigations focused on cell viability and apoptosis, apoptosis-related protein expression, and KRT8 mRNA m6A modification. For in vivo studies, 36 BALB/c nude mice were divided into six groups involving EZMLD (6.75, 13.5, and 27 g/kg) and METTL3 or METTL14 knockdowns, with daily EZMLD gavage for two weeks. Results In vitro, EZMLD-containing serum had IC50 values of 8.29% at 24 h and 5.95% at 48 h in SKOV3 cells. EZMLD-containing serum decreased SKOV3 cell viability and increased apoptosis. EZMLD upregulated METTL3/14 and FAS-mediated apoptosis proteins, while downregulating Keratin 8 (KRT8). EZMLD increased KRT8 mRNA m6A methylation. METTL3/14 overexpression reduced SKOV3 cell viability and increased apoptosis, while METTL3/14 knockdown mitigated EZMLD's effects. In vivo, EZMLD suppressed SKOV3 xenografts growth, causing significant apoptosis and modulating protein expression. Conclusions EZMLD has therapeutic potential for ovarian cancer and may be considered for other cancer types. Future research may explore its broader effects beyond cell apoptosis.

Abstract Efficiency of calculating a dynamic response is an important point of the compliant mechanism for posture adjustment. Dynamic modeling with low orders of a 2R1T compliant parallel mechanism is studied in the paper. The mechanism with two out-of-plane rotational and one lifting degrees of freedom (DoFs) plays an important role in posture adjustment. Based on elastic beam theory, the stiffness matrix and mass matrix of the beam element are established where the moment of inertia is considered. To improve solving efficiency, a dynamic model with low orders of the mechanism is established based on a modified modal synthesis method. Firstly, each branch of the RPR type mechanism is divided into a substructure. Subsequently, a set of hypothetical modes of each substructure is obtained based on the C-B method. Finally, dynamic equation of the whole mechanism is established by the substructure assembly. A dynamic experiment is conducted to verify the dynamic characteristics of the compliant mechanism.

Abstract This study aimed to synchronously determine epitranscriptome-wide RNA N6-methyladenosine (m6A) modifications and mRNA expression profile in high grade serous ovarian cancer (HGSOC). The methylated RNA immunoprecipitation sequencing (MeRIP-seq) was used to comprehensively examine the m6A modification profile and the RNA-sequencing (RNA-seq) was performed to analyze the mRNA expression profile in HGSOC and normal fallopian tube (FT) tissues. Go and KEGG analyses were carried out in the enrichment of those differentially methylated and expressed genes. MeRIP-seq data showed 53,794 m6A methylated peaks related to 19,938 genes in the HGSOC group and 51,818 m6A peaks representing 19,681 genes in the FT group. RNA-seq results revealed 2321 upregulated and 2486 downregulated genes in HGSOC. Conjoint analysis of MeRIP-seq and RNA-seq data identified differentially expressed genes in which 659 were hypermethylated (330 up- and 329 down-regulated) and 897 were hypomethylated (475 up- and 422 down-regulated). Functional enrichment analysis indicated that these differentially modulated genes are involved in pathways related to cancer development. Among methylation regulators, the m6A eraser (FTO) expression was significantly lower, but the m6A readers (IGF2BP2 and IGF2BP3) were higher in HGSOC, which was validated by the subsequent real-time PCR assay. Exploration through public databases further corroborated their possible clinical application of certain methylation regulators and differentially expressed genes. For the first time, our study screens the epitranscriptome-wide m6A modification and expression profiles of their modulated genes and signaling pathways in HGSOC. Our findings provide an alternative direction in exploring the molecular mechanisms of ovarian pathogenesis and potential biomarkers in the diagnosis and predicting the prognosis of the disease.

Abstract The online physician interactive community (OPIC) is a platform designed for medical workers to discuss medical issues. Physician users can create content in OPIC by posting and replying to posts to discuss the solutions of medical problems with other users. The OPIC plays an important role in bringing together physicians from different medical specialties and disseminating medical experience. However, most OPIC users are not very active in replying to posts, which makes it difficult to fulfill users’ needs for medical information exchange and the development of OPIC is difficult. Current research has given little attention to the communication of physician users in the OPIC. It is necessary to examine how reposting links are established between users in OPIC. This study builds a user interaction network based on the perspective of social network analysis using user repost data from a well-known OPIC in China. Then, an exponential random graph model (ERGM) was applied to quantitatively analyze this user interaction network. Some reposting patterns among OPIC users were discovered. There is significant reciprocity in OPIC of reposting interactions between users. Users with homogeneous characteristics in terms of professional status, community honor status, and geographic location were more likely to interact with each other. In addition, users who added a profile, had a higher level of social effort, and generated more neutral content were more likely to receive responses from others. This study reveals the interaction patterns between physician users in OPIC, which enriches the related research within the OPIC domain and helps to improve communication between users in OPIC.

Transglutaminase (EC 2.3.2.13, TGase), an enzyme that catalyzes the formation of covalent cross-links between protein or peptide molecules, plays a critical role in commercial food processing, medicine, and textiles. TGase from Streptomyces is the sole commercial enzyme preparation for cross-linking proteins. In this study, we revealed that the SOS response repressor protein LexA in Streptomyces mobaraensis not only triggers morphological development but also enhances TGase synthesis. The absence of lexA significantly diminished TGase production and sporulation. Although LexA does not bind directly to the promoter region of the TGase gene, it indirectly stimulates transcription of the tga gene, which encodes TGase. Furthermore, LexA directly enhances the expression of genes associated with protein synthesis and transcription factors, thus favorably influencing TGase synthesis at both the transcriptional and posttranscriptional levels. Moreover, LexA activates four crucial genes involved in morphological differentiation, promoting spore maturation. Overall, our findings suggest that LexA plays a dual role as a master regulator of the SOS response and a significant contributor to TGase regulation and certain aspects of secondary metabolism, offering insights into the cellular functions of LexA and facilitating the strategic engineering of TGase overproducers.

ObjectiveTo explore the correlations between diabetic nephropathy (DN) and serum levels of glutathione peroxidase 4 (GPX4), acyl-CoA synthetase long-chain family member 4 (ACSL4), iron, transferrin (Tf), and ferritin in patients with type 2 diabetes mellitus (T2DM).MethodsAccording to the urinary albumin excretion rate(UAER) or estimated glomerular filtration rate (eGFR) levels, a total of 123 patients with T2DM were separately divided into normoalbuminuria (NO), microalbuminuria (MI), macroalbuminuria (MA) groups, and G1 (eGFR ≥ 90 mL/min), G2 (eGFR ≤ 60 mL/min to < 90 mL/min), and G3 groups (eGFR< 60 mL/min), with 33 healthy participants as the control (HC). The differences in serum GPX4, ACSL4, iron, Tf, and ferritin levels between groups were compared, and the relationships between these levels were analysed. The independent correlations between UAER or DN severity and serum GPX4, ACSL4, iron, Tf, and ferritin levels were analysed by multiple linear and multinomial logistic regression, respectively.ResultsTo the patients with T2DM, with the increase in UAER levels, GPX4, iron, and Tf levels gradually decreased, whereas ACSL4 levels increased, meanwhile with the decrease in eGFR levels, GPX4 and Tf levels gradually decreased, whereas ACSL4 levels increased. UAER were independently and positively correlated with ACSL4 [β = 17.53, 95% confidence interval (CI; 11.94, 23.13)] and negatively correlated with GPX4 [β = −1.633, 95% CI (−2.77, -0.496)] and Tf [β = −52.94, 95% CI (-95.78, −10.11)].The NO and MI groups were considered as reference groups, respectively. The severity of DN was negatively correlated with serum GPX4 [odds ratio (OR) = 0.925 and 0.902, p =0.015 and 0.001], and Tf (OR = 0.109 and 0.119, p =0.043 and 0.034), and positively correlated with ACSL4 (OR = 1.952 and 1.865, both p

Objective: To investigate the application value of normalized apparent diffusion coefficient (ADC) values and prostate-specific antigen density (PSAD) in category 3 Prostate Imaging Reporting and Data System (PI-RADS) version 2.1 lesions when the serum prostate-specific antigen (PSA) level is in the grey zone of 4～10 ng/mL. Methods: From January 2018 to June 2022, 58 patients with PI-RADS v2.1 scores of 3 and PSA values of 4~10 ng/mL were selected. According to the pathological results, the patients were divided into the PCa (20 cases) and non-PCa (38 cases) groups. The clinical data of the patients were collected, including age, PSA, prostate volume (PV), and PSAD (PSA/V) calculated by formula. Meanwhile, the ADC values of the lesion area and the normal tissue in the peripheral zone were measured on the ADC image, and the standardized apparent diffusion coefficient value was calculated, namely ADCn (ADC lesion/ADC peripheral zone). Statistical software was used to determine the statistical significance of the differences of ADCn and PSAD between the two groups. Receiver operating characteristic (ROC) curves were used to compare the diagnostic efficacy of the two for PCa in lesions with PI-RADS v2.1 score of 3. Results: Age and PSA did not differ significantly between the two groups. Compared to the non-PCa group, the PCa group showed lower ADCn (0.52 vs. 0.69) and higher PSAD (0.28 vs. 0.18). The area under the ROC curve (AUC), sensitivity, and specificity of ADCn and PSAD in the diagnosis of PCa were 0.849, 85.2%, and 81.6 % and 0.813, 85.0%, and 78.4%, respectively. For an optimal diagnostic threshold of 0.373, the AUC, sensitivity, and specificity of PCa were 0.962, 90.0%, and 89.5%, respectively. Conclusions: ADCn and PSAD can assist in PCa detection in lesions category 3 PI-RADS v2.1 lesions in the PSA gray area. The combination of ADCn and PSAD can significantly improve the diagnostic sensitivity and specificity.

BackgroundSome eating habits may be related to the development of gastrointestinal diseases, obesity, and related metabolic dysfunctions. Because of long working hours, and shift schedules, physicians are more likely to form such eating habits and have a high risk of developing these diseases.ObjectivesWe aimed to investigate the association between physicians’ eating habits and their health perception and diseases.MethodsBetween 24 June and 5 August 2020, we performed convenience sampling of in-service physicians in hospitals in mainland China. A questionnaire was administered to collect data pertaining to basic sociodemographic characteristics, eating habits, health-related information such as body mass index classification, and prevalence of common diseases. The associations among eating habits and perceived suboptimal health status, micronutrient deficiency-related diseases, obesity, and related metabolic diseases were analysed.ResultsThe prevalence of unhealthy eating habits was high: more eating out-of-home (53.4% in hospital canteens, 23.0% in restaurants and takeaways), fewer meals at home, irregular meals (30.5%), and eating too fast (the duration

Soil interparticle forces can pose important effects on soil aggregate stability and rainfall splash erosion. Meanwhile, these interparticle forces are strongly influenced by specific ion effects. In this study, we applied three monovalent cations (Li+, Na+, and K+) with various concentrations to investigate the influence of specific ion effects on aggregate stability and splash erosion via pipette and rainfall simulation methods. The specific ion effects on soil interparticle forces were quantitatively evaluated by introducing cationic non-classical polarization. The results showed that aggregate stability and splash erosion had strong ion specificity. Aggregate breaking strength and splash erosion rate at the same salt concentration followed the sequence as Li+ > Na+ > K+. With decreasing salt concentration, the difference in aggregate breaking strength or splash erosion rate between different cation systems increased initially (1–10–2 mol L–1) and later was nearly invariable (10–2–10–4 mol L–1). The experimental results were well quantitatively explained by soil interparticle forces considering cationic non-classical polarization. Furthermore, both aggregate breaking strength and splash erosion rate of three cations revealed a strong positive linear relation with net force subjected to cationic non-classical polarization (R2 = 0.81, R2 = 0.81). These results demonstrated that different non-classical polarization of cations resulted in different soil interparticle forces, and thus led to differences in aggregate stability and splash erosion. Our study provides valuable information to deeply understand the mechanisms of rainfall splash erosion.

Abstract A novel compliant mechanism with RPR degrees of freedom (DOF) is proposed where R and P represent rotation and translation DOFs, respectively. The proposed compliant mechanism is obtained from dimension synthesizing a 2-RPU-UPR rigid parallel mechanism with the method of optimization of motion/force transfer characteristic. R, P and U represent rotation, translation and universal pairs, respectively. Firstly, inverse kinematics and Jacobian matrix are analyzed for the dimensional synthesis. Then, output transmission indexes of branches in the parallel mechanism are given. Dimensional synthesis is completed based on the normalized design parameter. And optimization of flexure joints based on constrained energy is carried out. Afterwards, the novel compliant mechanism is obtained by direct replacing method. Mechanical model of the compliant mechanism including static stiffness and input stiffness is built based on the pseudo-rigid body modeling method and virtual work principle. Finally, FEA simulation by Ansys Workbench is carried out to verify DOF, effectiveness of the dimension synthesis, and compliant model. Optimization of motion/force transfer characteristic is first applied for the design of compliant mechanisms to suppress drift of rotation axis in the paper.

Abstract Background To investigate whether metformin monotherapy or adjunctive therapy improves the prognosis in patients with any type of cancer compared to non-metformin users (age ≥18). Methods Databases (Medline, Embase, and the Cochrane Central Register of Controlled Trials) and clinical trial registries ( ClinicalTrials.gov ; the World Health Organization International Clinical Trials Registry Platform) were screened for randomized, controlled trials (RCT) reporting at least progression-free survival (PFS) and/or overall survival (OS). Main outcome measures included hazard ratios (HR), and combined HRs and 95% confidence intervals (CI) were calculated using random-effects models. Results Of the 8419 records screened, 22 RCTs comprising 5943 participants were included. Pooled HRs were not statistically significant in both PFS (HR 0.97, 95% CI 0.82–1.15, I 2 = 50%) and OS (HR 0.98, 95% CI 0.86–1.13, I 2 = 33%) for patients with cancer between the metformin and control groups. Subgroup analyses demonstrated that metformin treatment was associated with a marginally significant improvement in PFS in reproductive system cancers (HR 0.86, 95% CI 0.74–1.00) and a significantly worse PFS in digestive system cancers (HR 1.45, 95% CI 1.03–2.04). The PFS or OS was observed consistently across maintenance dose, diabetes exclusion, median follow-up, risk of bias, and combined antitumoral therapies. Conclusion Metformin treatment was not associated with cancer-related mortality in adults compared with placebo or no treatment. However, metformin implied beneficial effects in the PFS of the patients with reproductive system cancers but was related to a worse PFS in digestive system cancers. Systematic review registration PROSPERO registration number CRD42022324672.

Diabetic cardiomyopathy (DCM) is a serious complication of type 1 and type 2 diabetes, which leads to the aggravation of myocardial fibrosis, disorders involving systolic and diastolic functions, and increased mortality of patients with diabetes through mechanisms such as glycolipid toxicity, inflammatory response, and oxidative stress. Ferroptosis is a form of iron-dependent regulatory cell death that is attributed to the accumulation of lipid peroxides and an imbalance in redox regulation. Increased production of lipid reactive oxygen species (ROS) during ferroptosis promotes oxidative stress and damages myocardial cells, leading to myocardial systolic and diastolic dysfunction. Overproduction of ROS is an important bridge between ferroptosis and DCM, and ferroptosis inhibitors may provide new targets for the treatment of patients with DCM.

Background and objectiveGlycation is a common post-transcriptional modification of proteins. Previous studies have shown that advanced glycation end modified transferrin (AGE-Tf) levels in diabetic rat kidney tissues were increased; however, its role in diabetic nephropathy remains unclear. In this study, differences in glycation degree and Tf sites induced by differing high glucose concentrations in vitro and the effect on total iron binding capacity (TIBC) were observed. Moreover, the effect of AGE-Tf on human renal tubular epithelial cells (HK-2) was investigated.MethodsIn vitro Tf was incubated with increasing glucose concentrations (0 mM, 5.6 mM, 11.1 mM, 33.3 mM, 100 mM, 500 mM, and 1,000 mM) for AGE-Tf. Differences in AGE-Tf glycation degree and TIBC level were analyzed via colorimetric method. The AGE-Tf glycation sites were identified with LC-MS/MS. HK-2 cells were treated with AGE-Tf prepared with different glucose concentrations (33.3 mM and 500 mM) in vitro. The effects of AGE-Tf on HK-2 cell viability, proliferation, oxidative stress index, and Tf receptor expression levels were then observed.ResultsWith increasing glucose concentrations (100 mM, 500 mM, and 1,000 mM) in vitro, Tf glycation degree was significantly increased. The TIBC levels of AGE-Tf were decreased significantly with increasing glucose concentrations (33.3 mM, 100 mM, 500 mM, and 1,000 mM). Four glycated modification sites in Tf and 17 glycated modification sites were detected in AGE-Tf (500 mM) by LC-MS/MS. The structural types of AGEs were CML, G-H1, FL-1H2O, FL, and MG-H1. No significant differences were found in the survival rate of HK-2 cells among the AGE-Tf (500 mM), AGE-Tf (33.3 mM), and Tf groups (all p > 0.05). The apoptosis rate of HK-2 cells in the AGE-Tf (500 mM) group was significantly higher than that in the AGE-Tf (33.3 mM) group. Additionally, both of them were significantly higher than that in the Tf group (both p < 0.05). The MDA levels of HK-2 cells in the AGE-Tf (500 mM) and AGE-Tf (33.3 mM) groups were higher than that in the Tf group, but not significantly (both p > 0.05). The T-AOC level of HK-2 in the AGE-Tf (500 mM) group was significantly lower than that in the AGE-Tf (33.3 mM) and Tf groups (both p < 0.001). The GSH level of HK-2 cells in the AGE-Tf (500 mM) group was significantly lower than that in the Tf group (p < 0.05). The expression level of TfR in the AGE-Tf (500 mM) group was also significantly lower than that in the Tf group (p < 0.05).ConclusionThe degree and sites of Tf glycation were increased in vitro secondary to high-glucose exposure; however, the binding ability of Tf to iron decreased gradually. After HK-2 was stimulated by AGE-Tf in vitro, the apoptosis of cells was increased, antioxidant capacity was decreased, and TfR expression levels were downregulated.

There is a growing demand for health popular science information from the public. Online paid health popular science information provides a new channel for the public to obtain health popular science information and can meet users’ demands for high-quality health popular science information. In order to improve the popularity of online paid health popular science information, it is urgent to investigate the factors influencing users’ intention to pay for online health popular science information. Paid online health popular science information can provide users with higher-quality health knowledge, while monetary compensation can incentivize publishers to create and promote the sustainability of social media platforms. Therefore, paid online health popular science information is important for readers, creators, and platforms. Therefore, this study investigates the factors influencing users’ intentions to purchase online health popular science information based on the health belief model (HBM). Our research data were obtained by a questionnaire and empirically analyzed by SmartPLS structural equation modeling. The results of this study indicate that the greater the perceived susceptibility, severity, and irreplaceability of health problems, the greater the intention of users to purchase health information when they read the summary portion of paid online health popular science information. And the higher the perceived risk and the more unreasonable the price of the online health popular science information, the lower the intention to purchase. Moreover, both the perceived susceptibility and perceived severity significantly attenuated the negative impacts of perceived health popular science information risk and perceived price unreasonableness on users’ intentions to purchase online health popular science information. This study not only enriches and extends the application of the health belief model, but also has important positive implications for the development of online paid health popular science information.

Abstract Purpose To explore the association of genes in “PD-L1 expression and PD-1 check point pathway in cancer” to radiotherapy survival benefit. Methods and materials Gene expression data and clinical information of cancers were downloaded from TCGA. Radiotherapy survival benefit was defined based on interaction model. Fast backward multivariate Cox regression was performed using stacking multiple interpolation data to identify radio-sensitive (RS) genes. Results Among the 73 genes in PD-L1/PD-1 pathway, we identified 24 RS genes in BRCA data set, 25 RS genes in STAD data set and 20 RS genes in HNSC data set, with some crossover genes. Theoretically, there are two types of RS genes. The expression level of Type I RS genes did not affect patients' overall survival (OS), but when receiving radiotherapy, patients with different expression level of Type I RS genes had varied survival benefit. Oppositely, Type II RS genes affected patients' OS. And when receiving radiotherapy, those with lower OS could benefit a lot. Type II RS genes in BRCA had strong positive correlation and closely biological interactions. When performing cluster analysis using these related Type II RS genes, patients could be divided into RS group and non-RS group in BRCA and METABRIC data sets. Conclusions Our study explored potential radio-sensitive biomarkers of several main cancer types in an important tumor immune checkpoint pathway and revealed a strong association between this pathway and radiotherapy survival benefit. New types of RS genes could be identified based on expanded definition to RS genes.

Thyroid cancer is a common malignancy of the endocrine system, with papillary thyroid cancer (PTC) being the most common type of pathology. The incidence of PTC is increasing every year. Histone acetylation modification is an important part of epigenetics, regulating histone acetylation levels through histone acetylases and histone deacetylases, which alters the proliferation and differentiation of PTC cells and affects the treatment and prognosis of PTC patients. Histone deacetylase inhibitors induce histone acetylation, resulting in the relaxation of chromatin structure and activation of gene transcription, thereby promoting differentiation, apoptosis, and growth arrest of PTC cells.

Online health counseling (OHC) is increasingly important in modern healthcare. This development has attracted considerable attention from researchers. However, the reality of the lack of physician–patient communication and dissatisfaction with online health services remains prevalent, and more research is needed to raise awareness about important issues related to OHC services, especially in terms of patient satisfaction and depth of interaction (i.e., the product of the number of interactions and the relevance of the content). This study constructs an empirical model to explore the relationship between physicians’ online writing language style (inclusive language and emojis), depth of physician–patient interactions, and patient satisfaction. The study obtained 5064 online health counseling records from 337 pediatricians and analyzed them using text mining and empirical methods. The results showed that physicians’ inclusive language (β = 0.3198, p < 0.05) and emojis (β = 0.6059, p < 0.01) had a positive impact on patient satisfaction. In addition, the depth of the physician–patient interaction partially mediated this effect. This study promotes a better understanding of the mechanisms of physician–patient interactions in online settings and has important implications for how online physicians and platforms can better provide online healthcare services.

(1) Background: The COVID-19 epidemic is still global and no specific drug has been developed for COVID-19. Vaccination can both prevent infection and limit the spread of the epidemic. Eliminating hesitation to the COVID-19 vaccine and achieving early herd immunity is a common goal for all countries. However, efforts in this area have not been significant and there is still a long way to go to eliminate vaccine hesitancy. (2) Objective: This study aimed to uncover differences in the characteristics and sentiments of COVID-19 vaccine hesitators on Chinese social-media platforms and to achieve a classification of vaccine-hesitant groups. (3) Methods: COVID-19-vaccine-hesitation posts and user characteristics were collected on the Sina Microblog platform for posting times spanning one year, and posts were identified for hesitation types. Logistic regression was used to conduct user-group analysis. The differences in user characteristics between the various types of COVID-19 vaccine posts were analysed according to four user characteristics: gender, address type, degree of personal-information disclosure, and whether they followed health topics. Sentiment analysis was conducted using sentiment analysis tools to calculate the sentiment scores and sentiment polarity of various COVID-19 vaccine posts, and the K–W test was used to uncover the sentiment differences between various types of COVID-19-vaccine-hesitation posts. (4) Results: There are differences in the types of COVID-19-vaccine-hesitation posts posted by users with different characteristics, and different types of COVID-19-vaccine-hesitation posts differ in terms of sentiment. Differences in user attributes and user behaviors are found across the different COVID-19-vaccine-hesitation types. Ultimately, two COVID-19-vaccine-hesitant user groups were identified: Body-related and Non-bodily-related. Users who posted body-related vaccine-hesitation posts are more often female, disclose more personal information and follow health topics on social-media platforms. Users who posted non-bodily-related posts are more often male, disclose less personal information, and do not follow health topics. The average sentiment score for all COVID-19-vaccine-hesitant-type posts is less than 0.45, with negative-sentiment posts outweighing positive- and neutral-sentiment posts in each type, among which the “Individual rights” type is the most negative. (5) Conclusions: This paper complements the application of user groups in the field of vaccine hesitation, and the results of the analysis of group characteristics and post sentiment can help to provide an in-depth and comprehensive analysis of the concerns and needs of COVID-19 vaccine hesitators. This will help public-health agencies to implement more targeted strategies to eliminate vaccine hesitancy and improve their work related to the COVID-19 vaccine, with far-reaching implications for COVID-19-vaccine promotion and vaccination.

Today’s diverse health needs place greater demands on physicians. However, individual doctors have limited capabilities and may encounter many unsolvable medical problems. The physician online community provides a platform for physicians to communicate with each other and help each other. Physicians can post for help about problems they encounter at work. The number of responses to physicians’ posts is critical to whether or not the problem is resolved. This study collected information on 13,226 posts from a well-known physician online community in China to analyze the factors that influence the number of post replies. In the analysis of the post content of the physician online community, this study innovatively introduces word usage features in the medical field. TextMind was used to extract the rate of several types of words in posts that frequently appear when describing medical information. Ultimately, we found that the rate of time words, visual words, auditory words, and physiological process words used in posts had a positive and significant effect on the number of post responses. A series of new post features has been found to have an impact on the number of post replies in physician online communities. This finding is beneficial for physicians to quickly obtain peer assistance through online platforms, increasing the likelihood of solving workplace challenges and improving physician care, as well as the success of physician online communities.

During the COVID-19 epidemic, social media has become the main channel for people to learn information related to the epidemic, among which information in the form of videos has played a significant role in the prevention and control of COVID-19. However, few studies have analyzed the process of knowledge learning of individuals through watching COVID-19 videos. Therefore, to explore the process of COVID-19 video viewers’ knowledge acquisition, this paper constructs a knowledge learning path model based on the cognitive mediation model and dual coding theory. A sample of 255 valid questionnaires was collected to validate this model. The results of this study show that an individual’s perceived risk of COVID-19 affects their surveillance motivation positively, while surveillance motivation further stimulates the attention and elaboration about the information in COVID-19 videos. Among them, attention positively influences the elaboration about the information. Ultimately, both an individual’s attention and elaboration positively influence the knowledge he or she acquires from the COVID-19 videos. This paper not only verifies the hypothesized relationships in the original cognitive mediation model, but also extends the model to the context of video knowledge learning. Analyzing the knowledge learning process of COVID-19 video viewers, this paper can provide suggestions for government propaganda departments and relevant media to improve public knowledge of COVID-19.

Depression has become one of the most common mental illnesses, and the widespread use of social media provides new ideas for detecting various mental illnesses. The purpose of this study is to use machine learning technology to detect users of depressive patients based on user-shared content and posting behaviors in social media. At present, the existing research mostly uses a single detection method, and the unbalanced class distribution often leads to a low recognition rate. In addition, a large number of irrelevant or redundant features in high-dimensional data sets interfere with the accuracy of recognition. To solve this problem, this paper proposes a hybrid feature selection and stacking ensemble strategy for depression user detection. First, recursive elimination method and extremely randomized trees method are used to calculate feature importance and mutual information value, calculate feature weight vector, and select the optimal feature subset according to the feature weight. Second, naive bayes, k-nearest neighbor, regularized logistic regression and support vector machine are used as base learners, and a simple logistic regression algorithm is used as a combination strategy to build a stacking model. Experimental results show that compared with other machine learning algorithms, the proposed hybrid method, which integrates feature selection and ensemble, has a higher accuracy of 90.27% in identifying online patients. We believe this study will help develop new methods to identify depressed people in social networks, providing guidance for future research.

Abstract Background In recent years, online pharmacies have been accepted by increasingly more consumers, and the prospects for online pharmacies are optimistic. This article explores the consumers’ satisfaction factors addressed in Business to Customer (B2C) online pharmacy reviews and analyzes the sentiments expressed in the reviews. The goal of this work is to help B2C online pharmacy enterprises identify consumers’ concerns, continuously improve the health services level. Methods This article was based on the Latent Dirichlet Allocation (LDA) topic model. From a third-party platform-based B2C online pharmacy and a proprietary B2C online pharmacy (JD Pharmacy and J1.COM, respectively), 136,630 pieces of over-the-counter (OTC) drug review data posted from January 1, 2015 to December 31, 2018 were selected as samples and used to explore the satisfaction factors of B2C online pharmacy consumers regarding the entire drug purchasing process. Then, the sentiments expressed in the drug reviews were analyzed with SnowNLP. Result Categorization of the 12 factors identified by LDA showed that 5 factors were related to logistics; these 5 factors, which also included the most drug reviews, made up 38.5% of the reviews. The number of factors related to drug prices was second, with 3 factors, and reviews of drug prices made up 25.5% of the reviews. Customer service and drug effects each had two related factors, and a smaller percentage of these reviews (13.95%) were related to drug effects. Consumers still maintain positive opinions of JD Pharmacy and J1.COM. However, some opinions on logistics and drug prices are expressed. Conclusion The most important task for online pharmacies is to improve logistics. It is better to develop self-built logistics. Both types of B2C online pharmacies can improve consumer viscosity by implementing marketing strategies. With regard to customer service, focusing on improving employees’ service attitudes is necessary.

Abstract Aims/Introduction Iron metabolism can directly or indirectly affect the occurrence and development of type 2 diabetes. This meta‐analysis and systematic review aimed to analyze the association between serum iron metabolism indicators and type 2 diabetes. Materials and Methods The databases PubMed and Embase were searched for studies on the correlations between serum iron metabolism indicators (iron, ferritin, transferrin, hepcidin and soluble transferrin receptor) and type 2 diabetes since January 2006. Relevant data were extracted from the included studies, and meta‐analysis was carried out. Results A total of 12 case–control and cohort studies were analyzed. Of the 12 studies, 11 described the correlation between serum ferritin levels and type 2 diabetes. The median and high serum ferritin concentrations were significantly associated with the risks of type 2 diabetes (odds ratio [OR] 1.20, 95% confidence interval [CI] 1.08–1.33 and OR 1.43, 95% CI 1.29–1.59, respectively). However, the low concentration was not correlated with the risk of type 2 diabetes (OR 0.99, 95% CI 0.89–1.11). No significant association was observed between serum soluble transferrin receptor and type 2 diabetes, whereas the soluble transferrin receptor‐to‐ferritin ratio was significantly inversely related to the risk of type 2 diabetes in the median and high ratio subgroups (OR 0.71, 95% CI 0.51, 0.99 and OR 0.65, 95% CI 0.45–0.95). Conclusions The elevated serum ferritin was one of the risk factors for type 2 diabetes, and soluble transferrin receptor‐to‐ferritin ratio was inversely related to the risk of type 2 diabetes. A systematic review showed that serum transferrin and hepcidin might be directly or indirectly related to the development of diabetes.

The public demand for popular science knowledge regarding health is increasing, and physicians’ popular science practices on online medical platforms are becoming frequent. Few studies have been conducted to address the relationship between specific characteristics of popular science articles by physicians and their performance. This study explored the impact of the characteristics of popular science articles on physicians’ performance based on the elaboration likelihood model (ELM) from the central path (topic focus and readability) and the peripheral path (form diversity). Data on four diseases, namely, lung cancer, brain hemorrhage, hypertension, and depression, were collected from an online medical platform, resulting in relevant personal data from 1295 doctors and their published popular science articles. Subsequently, the independent variables were quantified using thematic analysis and formula calculation, and the research model and hypotheses proposed in this paper were verified through empirical analysis. The results revealed that the topic focus, readability, and form diversity of popular science articles by physicians had a significant positive effect on physicians’ performance. This study enriches the research perspective on the factors influencing physicians’ performance, which has guiding implications for both physicians and platforms, thereby providing a basis for patients to choose physicians and enabling patients to receive popular science knowledge regarding health in an effective manner.

(1) Background: Abundant evidence has shown that the COVID-19 vaccine booster is highly effective against the Omicron variant. It is of great practical significance to explore the factors influencing the intention to receive COVID-19 booster shots. (2) Methods: We introduced expectation confirmation theory as the basis to construct a model of the factors of the vaccination intention for COVID-19 vaccine boosters. We obtained two batches of questionnaires through Chinese social platforms, with a valid sample size of 572. To test the model, we used SmartPLS3.0 software for empirical analysis. (3) Results: In terms of the characteristics of the vaccine itself, perceived vaccine efficacy and perceived vaccine safety had significant positive effects on expectation confirmation. Regarding vaccination services, perceived vaccination convenience also had a significant positive effect on expectation confirmation. Expectation confirmation positively affected the vaccination intention for the COVID-19 vaccine boosters. Furthermore, the results showed two moderating effects: first, health consciousness negatively moderated the positive effect of perceived vaccine safety on expectation confirmation; second, the time interval since the last dose negatively moderated the positive effect of perceived vaccine efficacy on expectation confirmation. (4) Conclusions: Our research demonstrated that there is an expectation confirmation process for previous COVID-19 vaccines before people consider whether to obtain a booster shot. Perceived vaccine efficacy and perceived vaccine safety remained important factors in receiving COVID-19 booster shots, and our conclusions were consistent with previous literature. In this study, multiple dimensions such as distance and cost were used to measure perceived vaccination convenience. This new variable improve the explanatory power of the convenience of the vaccination service and enrich the variables of the factor model of vaccination intention. In addition, the moderating effects of health consciousness and time interval were found. The findings can provide a theoretical reference for public health institutions to help them understand the formation process of people’s intention to receive the COVID-19 vaccine booster.

(1) Background: The coronavirus variants have posed serious challenges for the prevention and control of the COVID-19 pandemic. Individuals selectively watch and forward videos that help them reduce the damage caused by the virus. Therefore, the factors influencing video viewing and sharing in the context of the COVID-19 pandemic caused by virus variation must be explored. (2) Method: Based on a combination of uncertainty reduction theory and functional emotion theory, this paper designed hypotheses regarding how content relevance and emotional consistency affect video views and shares. We used the support vector machine (SVM) classification algorithm to measure the content relevance between videos and virus variant topics. We performed sentiment analysis of video text to evaluate the emotional consistency between videos and virus variant topics. Then, we used empirical analysis to build the model. (3) Results: The trained SVM classifier was effective in judging whether the video text was related to virus variant topics (F = 88.95%). The content relevance between COVID-19 videos and virus variant topics was generally low. The results showed that the higher the content relevance, the more views (IRR = 1.005, p = 0.017) and shares (IRR = 1.008, p = 0.009) the video received. Individuals were more willing to view (IRR = 1.625, p < 0.001) and share (IRR = 1.761, p < 0.001) COVID-19 videos with high emotional consistency with virus variant topics. (4) Conclusions: The results of empirical analysis showed that content relevance and emotional consistency between videos and virus variant topics significantly positively impacted video views and shares. The trained SVM classifier can support public health departments in monitoring and assessing the COVID-19 pandemic. Our study provides management advice while helping individuals reduce harm and inform next-step decisions.

Abstract Background The placenta is a highly specialized temporary organ that is related to fetal development and pregnancy outcomes, and epidemiological data demonstrate an increased risk of placental abnormality after in vitro fertilization and embryo transfer (IVF-ET). Methods This study examines alterations in the transcriptome profile of first-trimester placentas from IVF-ET pregnancies and analyzes the potential mechanisms that play a role in the adverse perinatal outcomes associated with IVF-ET procedures. Four human placental villi from first-trimester samples were obtained through fetal bud aspiration from patients subjected to IVF-ET due to oviductal factors. An additional four control human placental villi were derived from a group of subjects who spontaneously conceived a twin pregnancy. We analyzed their transcriptomes by microarray. Then, RT-qPCR and immunohistochemistry were utilized to analyze several dysregulated genes to validate the microarray results. Biological functions and pathways were analyzed with bioinformatics tools. Results A total of 3405 differentially regulated genes were identified as significantly dysregulated (> 2-fold change; P

Online depression communities offer people with depressed symptoms new opportunities to obtain health information and provide social support for each other to fight against the depression. We sought to investigate whether usage of online community help improve depression outcomes and determine which types of usage behaviors have positive or negative effects on depression. We proposed that two dimensions of the sense of belonging (sense of identity and trust) and three dimensions of the sense of support (informational, emotional, and socializing) have significant effects on depression, and further considered gender difference and its effect on depression. We obtained a dataset consisting of 465,337 posts from 244 members from a popular online depression community to test all 10 proposed hypotheses. The results reveal that (i) the sense of shared identity, trust, informational support, and emotional support have positive effects on depression, while socializing support have negative effects on depression, and (ii) the sense of shared identity and trust have more positive effects on depression for female users than male users while socializing support has a more negative effect on depression for female users than for male users. The findings have important practical implications for designers and managers of online depression communities.

Matrine is a natural product extracted from the root of Sophora flavescens that has been shown to be a promising alternative drug in different types of cancer. Here, we aimed to investigate the antitumor effects of matrine on human papillary thyroid cancer (PTC) and explore the underlying molecular mechanisms. Our data demonstrated the following findings. (a) The expression of miR-182-5p was significantly upregulated in PTC tissues and cell lines. (b) Matrine inhibited the expression of miR-182-5p and induced the apoptosis of TCP-1 and BCPAP cells in a dose-dependent manner. (c) Matrine increased caspase3 expression levels and reduced Bcl-2 expression levels in both TCP-1 and BCPAP cells. (d) Matrine appreciably inhibited PTC tumor growth in vivo. (e) After miR-182-5p overexpression, matrine-induced apoptosis and caspase3 activation were inhibited, and the matrine-induced decrease in Bcl-2 expression was abolished. (f) Overexpression of miR-182-5p counteracted the inhibitory effects of matrine on PTC tumor growth. In conclusion, these results demonstrate that matrine exerts antitumor effects possibly by inducing the apoptosis of TCP-1 and BCPAP cells, decreasing the level of Bcl-2, activating caspase3 and suppressing PTC tumor growth by downregulating the expression of miR-182-5p. These findings explain the anticancer mechanisms of matrine in PTC and identify miR-182-5p as an effective target of matrine in PTC treatment.

The paper studies the characterization and evaluation technology of rotation accuracy of hydrostatic spindle under the influence of unbalance. The dynamic model of the motion error of the hydrostatic spindle is established based on the dynamic parameters. The variation law of motion error of spindle rotor is analyzed under the unbalanced mass. The paper finds that with the increase of the spindle speed, the amplitude of the spindle error motion will increase, and the inclination angle θ error is more sensitive to the change in the rotational speed. In the total synthesis accuracy, the proportion of synchronization error decreases with the increase of the rotational speed. Finally, the least squares evaluation algorithm is used to evaluate the rotation error of the hydrostatic spindle, and a method for evaluating the rotation accuracy of the hydrostatic spindle with high calculation accuracy and calculation efficiency is proposed.

Background Ecological stoichiometry (C:N:P ratios) in soil is an important indicator of the elemental balance in ecological interactions and processes. Long-term natural vegetation plays an important role in the accumulation and distribution of soil stoichiometry. However, information about the effects of long-term secondary forest succession on soil stoichiometry along a deep soil profile is still limited. Methods We selected Ziwuling secondary succession forest developed from farmland as the study area, investigated the concentrations and stoichiometry of soil organic carbon (SOC), total nitrogen (TN), and total phosphorus (TP) at a depth of 0–100 cm along a 90-year succession chronosequence, including farmland (control), grassland, shrub, early forest, and climax forest. Results SOC and TN concentrations significantly increased with increasing restoration age, whereas soil P concentration remained relatively stable across various successional stages. SOC and TN concentrations decreased with an increase in soil depth, exhibiting distinct soil nutrient “surface-aggregation” (high nutrients concentration in the top soil layer). The soil C:P and N:P ratios increased with an increase in restoration age, whereas the variation of the C:N ratio was small and relatively stable across vegetation succession. The nutrient limitation changed along with vegetation succession, transitioning from limited N in the earlier successional stages to limited P in the later successional stages. Conclusion Our results suggest that more nitrogen input should be applied to earlier succession stages, and more phosphorus input should be utilized in later succession stages in order to address limited availability of these elements. In general, natural vegetation restoration was an ecologically beneficial practice for the recovery of degraded soils in this area. The findings of this study strengthen our understanding of the changes of soil nutrient concentration and nutrient limitation after vegetation restoration, and provide a simple guideline for future vegetation restoration and reconstruction efforts on the Loess Plateau.

Mindfulness metacognitive practice that can be performed in the workplace. Drawing on the theory of conservation of resources, we test a moderated mediating model of how and when employee mindfulness has a positive effect on work engagement. Via analysis of data from 311 employees from 83 teams at different times, this study investigates the relationship between employee mindfulness and work engagement as well as the moderating effect of team mindfulness and the mediating effect of recovery level. The results from this multi-wave field study show that the mindfulness of the individual employee has a positive influence on work engagement and that recovery level plays a mediating role. Team mindfulness positively moderates the relationship between individual mindfulness and work engagement. This conclusion may bridge the relationship between mindfulness and work engagement theory.

Placenta is a temporary critical organ related to fetal development and pregnancy outcomes. And epidemiologic data demonstrate an increased risk of placental abnormality after in vitro fertilization and embryo transfer (IVF-ET). This study aims to explore the molecular mechanism for PPAR signaling pathway in placenta subjected to IVF-ET in the first trimester. Four first trimester placenta samples from double chorionic twins to single reduction in IVF-ET only because of oviducts factors. The other four control placenta samples from double chorionic twin were derived from those unplanned spontaneously conceived pregnancy after the legal termination. Affymetrix HG-U133 Plus 2.0 Array was performed to evaluate the global gene expressions. We confirmed microarray results from 10 significant differential genes using RT-qPCR. And 10 deregulated gene products were stained in the first trimester placenta by immunohistochemistry. These differentially expressed genes in IVF-ET placentas were submitted to functional annotation of clustering tools of bioinformatics resources and gene ontology enrichment analysis. Schematic representation of placental PPAR signaling pathway was labelled by Kyoto Encyclopedia of Genes and Genomes (KEGG). Analysis results of early placental PPAR signaling pathway gene expression from 8 women demonstrated 34 genes with a significant change in expression between IVF-ET and control group, 25 up-regulated; 9 down-regulated. KEGG pathway analysis indicated that IVF-ET manipulation extensively over-activated PPAR signaling pathway. Immune tolerance, trophoblast invasion, syncytia formation, lipid and glucose metabolism, inflammatory response and other complex biological functions were disturbed. RT-qPCR results and proteins staining intensity were consisted with microarray. Placental gene expressions and functions in PPAR signaling pathway were affected by IVF-ET treatment in the first trimester, which may offer a potential mechanism for the pathogenesis of various adverse outcomes during the perinatal period.

(1) Background: The COVID-19 pandemic is globally rampant, and it is the common goal of all countries to eliminate hesitation in taking the COVID-19 vaccine and achieve herd immunity as soon as possible. However, people are generally more hesitant about the COVID-19 vaccine than about other conventional vaccines, and exploring the specific reasons for hesitation with the COVID-19 vaccine is crucial. (2) Methods: this paper selected text data from a social platform to conduct qualitative analysis of the text to structure COVID-19 vaccine hesitancy reasons, and then conducted semiautomatic quantitative content analysis of the text through a supervised machine-learning method to classify them. (3) Results: on the basis of a large number of studies and news reports on vaccine hesitancy, we structured 12 types of the COVID-19 vaccine hesitancy reasons. Then, in the experiment, we conducted comparative analysis of three classifiers: support vector machine (SVM), logistic regression (LR), and naive Bayes classifier (NBC). Results show that the SVM classification model with TF-IDF and SMOTE had the best performance. (4) Conclusions: our study structured 12 types of COVID-19 vaccine hesitancy reasons through qualitative analysis, filling in the gaps of previous studies. At the same time, this work provides public health institutions with a monitoring tool to support efforts to mitigate and eliminate COVID-19 vaccine hesitancy.

(1) Background: During the COVID-19 pandemic, users share and obtain COVID-19 information through video platforms, but only a few COVID-19 videos become popular among most audiences. Therefore, it is a very interesting and important research question to explore the influencing factors of the popularity of COVID-19 videos during the COVID-19 pandemic; (2) Our research collects video data related to the keyword “COVID-19” on video platform, the data are analyzed by content analysis and empirical analysis. We then constructed a theoretical model based on the information adoption model; (3) A total of 251 videos were divided into three categories. The least common category was the data and analysis category (11.2%), followed by the prevention and control status category (13.5%); the knowledge and general science category was the most common (75.3%). From the perspective of video quality, the information sources of most videos are relatively reliable, and the content of medical information is low. The research results showed that short video lengths, longer descriptions, more reliable video sources and lower medical information content were more popular with audiences. Audiences are more likely to be attracted to videos in the prevention and control status category and knowledge and general science category. Videos uploaded by uploaders who have a higher influence are more popular with audiences; (4) Conclusions: During the COVID-19 pandemic, information quality (video length, description length, video content type, and medical information and content index) and source credibility (information source reliability, influence and certification type) all significantly influence the popularity level of COVID-19 videos. Our research conclusions can provide management suggestions for the platform, make videos released by uploaders more popular with audiences, and help audiences better understand COVID-19 information and make prevention and control efforts.

Online consultation based on Internet technology is gradually becoming the main way to seek health information and professional assistance. Online user reviews, such as content reviews and star ratings, are an important basis for reflecting users’ views on the effectiveness of health services. Here, we used user reviews related to online psychological consultation services for content feature mining and usefulness analyses. We used a professional online psychological counseling service platform in China to collect user reviews that were liked by users as a data sample for a content analysis. An LDA topic model, dictionary-based sentiment analysis, and the NRC Word-Emotion Association Lexicon were used to extract the topic, sentiment, and context features of the content of 4254 useful reviews, and the influence of these features on the usefulness of the reviews was verified by a multiple linear regression analysis. Our results show that the content of online reviews by psychological counseling users presented a positive emotional attitude as a whole and expressed more views on the process, effects, and future expectations of counseling than on other topics. There was a significant correlation between the topic, sentiment, and context features of a user review and its usefulness: reviews giving high scores and containing topics such as “ease emotions” and “consulting expectations” received more user likes. However, the usefulness of a review was significantly reduced if it was in existence for too long. This research provides valuable suggestions for understanding the needs and emotional attitudes of users with mental health problems in terms of online psychological consultation; identifying the factors that affect the number of likes a review receives can help platform users write better consultation evaluations and thereby provide greater usefulness. In addition, the use of online reviews generated by users for content analysis effectively supplements the current research on online psychological counseling in terms of data and methods.

An online community is one of the important ways for people with mental disorders to receive assistance and obtain support. This study aims to help users with mental disorders to obtain more support and communication through online communities, and to provide community managers with the possible influence mechanisms based on the information adoption model. We obtained a total of 49,047 posts of an online mental health communities in China, over a 40-day period. Then we used a combination of text mining and empirical analysis. Topic and sentiment analysis were used to derive the key variables—the topic of posts that the users care about most, and the emotion scores contained in posts. We then constructed a theoretical model based on the information adoption model. As core independent variables of information quality, on online mental health communities, the topic of social experience in posts (0.368 ***), the topic of emotional expression (0.353 ***), and the sentiment contained in the text (0.002 *) all had significant positive relationships with the number of likes and reposts. This study found that the users of online mental health communities are more attentive to the topics of social experience and emotional expressions, while they also care about the non-linguistic information. This study highlights the importance of helping community users to post on community-related topics, and gives administrators possible ways to help users gain the communication and support they need.

Online medical team is an emerging online medical model in which patients can choose a doctor to register and consult. A doctor’s reputation cannot be ignored. It is worth studying how that online reputation affects the focal doctor’s appointment numbers on the online medical team. Based on the online reputation mechanism and social interdependence theory, this study empirically studied the impact of the focal doctor’s own reputation and other teammates’ reputation on his/her appointment numbers. Our data include 31,143 doctors from 6103 online expert teams of Guahao.com. The results indicate that for a leader doctor, his/her appointment numbers are not related to his/her own reputation, and there was an inverted U-shaped relationship with the ordinary doctors’ reputations on the team. For an ordinary doctor, his/her appointment numbers were positively correlated with his/her own reputation and positively correlated with his/her leader’s reputation and there was an inverted U-shaped relationship with the other ordinary doctors’ reputations. The research showed that there is a positive spillover effect on the team leader’s reputation. There are two relationships between team doctors: competition and cooperation. This study provides guidance for the leader to select team members and the ordinary doctor to select a team.

Potassium dihydrogen phosphate crystals exhibit excellent nonlinear optical properties that are significantly affected by the surface morphology of the crystal. To comprehensively examine and characterize the morphological features of these crystals, the machined surfaces of workpieces are analyzed using wavelet, fractal, and power spectral density (PSD) methods. First, the fractal method is employed to analyze the features of the machined surfaces of different materials and examine the relationship between the surface roughness and fractal dimension of different materials. Then, the morphological anisotropy of the machined surfaces is analyzed using the two-dimensional PSD method. Based on the orientation of the machined surfaces of the workpieces, the tangential waves on the surfaces are analyzed using wavelet-transform and PSD methods. From a frequency-domain perspective, the scales of various influencing factor signals are identified. Additionally, the frequency range of the spindle vibration is determined based on the machining experiment. On this basis, the cause of the machined surface waviness errors is revealed.

A novel type synthesis method for a class of spatial multi-loop coupled mechanisms with translational degrees of freedom is proposed in the paper. The novel class of spatial multi-loop coupled mechanisms has a stable topology layout which consists of three branches and three coupled chains. The basic idea of the new structural synthesis method lies at replacing the inputs of one mechanism by the outputs of another, thereby combining several mechanisms, where the topology split method for the topological layout and corresponding degree of freedom splitting principle are provided. The synthesis of the target mechanism is transformed into synthesis of corresponding serial and parallel mechanisms thereby, and a class of spatial multi-loop coupled mechanisms is synthesized. To validate the new synthesis method and to present a theoretical basis for future application, kinematic analysis of a single translational mobility (1T) spatial multi-loop coupled mechanism and a symmetrical two translational degrees of freedom (2T) spatial multi-loop coupled mechanism is performed. This article enriches the family of the spatial mechanisms for further instructing the study of spatial multi-loop coupled mechanisms.

Background: The posts related to Adverse Drug Reaction (ADR) on social websites are believed to be valuable resource for post-marketing drug surveillance. Beyond domain feature, the aim of this study was to find a more effective method to detect ADR related post. Methods: We conducted experiment on posts using sentiment features from March 8 to May 20 in 2016 in Shanghai of China. Firstly, the diabetes posts were collected; the 1814 posts were annotated by hand. Secondly, sentiment features set were generated and the (CHI) statistics were used to select feature. Finally, we evaluated the effectiveness of our method using the different feature sets. Results: By comparing the posts detection performance of different feature sets, using sentiment features by CHI statistics can improve ADR related post detection performance. By comparing the ADR-related group with the non-ADR group, performance of ADR related post detection was better than the performance of non-ADR post detection. We could obtain highest performance owing to introducing sentiment feature and using CHI feature selection technique, and the method was proved to be effective during detecting post related to ADR. Conclusion: By using sentiment feature and CHI feature selection technique, we can get an effective method to detect post related to ADR.

Traditional methods and theories on synthesizing parallel mechanisms are not applicable to related researches on hybrid mechanisms, thus hampering the design of innovative coupled mechanisms. Polyhedrons with attractive appearance and particular geometrical construction provide many choices for coupled inventions. A novel mechanism with one translational degree of freedom based on a regular triangular bipyramid is proposed in this article. First, the basic equivalent geometrical model is spliced with new-designed components substituting for vertexes and edges by revolution joints (R-pairs) only. The expected motion for the basic coupled model can be achieved by adding links to modify the constraint sets and arrange spatial allocation of an elementary loop based on the screw theory. Then, the mobility of one branch is calculated to investigate the movability of the novel structure, and a Denavit–Hartenberg (D-H) model with properties of symmetry is implemented to investigate the inverse kinematic analysis. Furthermore, a numerical example is given to verify the correctness of analysis results and related motion simulation is conducted to illustrate the potential application of the proposed novel system as an executing manipulator for mobile robots.

User-generated medical messages on Internet contain extensive information related to adverse drug reactions (ADRs) and are known as valuable resources for post-marketing drug surveillance. The aim of this study was to find an effective method to identify messages related to ADRs automatically from online user reviews.We conducted experiments on online user reviews using different feature set and different classification technique. Firstly, the messages from three communities, allergy community, schizophrenia community and pain management community, were collected, the 3000 messages were annotated. Secondly, the N-gram-based features set and medical domain-specific features set were generated. Thirdly, three classification techniques, SVM, C4.5 and Naïve Bayes, were used to perform classification tasks separately. Finally, we evaluated the performance of different method using different feature set and different classification technique by comparing the metrics including accuracy and F-measure.In terms of accuracy, the accuracy of SVM classifier was higher than 0.8, the accuracy of C4.5 classifier or Naïve Bayes classifier was lower than 0.8; meanwhile, the combination feature sets including n-gram-based feature set and domain-specific feature set consistently outperformed single feature set. In terms of F-measure, the highest F-measure is 0.895 which was achieved by using combination feature sets and a SVM classifier. In all, we can get the best classification performance by using combination feature sets and SVM classifier.By using combination feature sets and SVM classifier, we can get an effective method to identify messages related to ADRs automatically from online user reviews.

Recently, health-related social media services, especially online health communities, have rapidly emerged. Patients with various health conditions participate in online health communities to share their experiences and exchange healthcare knowledge. Exploring hot topics in online health communities helps us better understand patients' needs and interest in health-related knowledge. However, the statistical topic analysis employed in previous studies is becoming impractical for processing the rapidly increasing amount of online data. Automatic topic detection based on document clustering is an alternative approach for extracting health-related hot topics in online communities. In addition to the keyword-based features used in traditional text clustering, we integrate medical domain-specific features to represent the messages posted in online health communities. Three disease discussion boards, including boards devoted to lung cancer, breast cancer and diabetes, from an online health community are used to test the effectiveness of topic detection. Experiment results demonstrate that health-related hot topics primarily include symptoms, examinations, drugs, procedures and complications. Further analysis reveals that there also exist some significant differences among the hot topics discussed on different types of disease discussion boards.

AimThe role of insulin glargine as a risk factor for cancer is controversial in human studies. The aim of this meta-analysis was to evaluate the relationship between insulin glargine and cancer incidence.MethodsAll observational studies and randomized controlled trials evaluating the relationship of insulin glargine and cancer risk were identified in PubMed, Embase, Web of Science, Cochrane Library and the Chinese Biomedical Medical Literature Database, through March 2012. Odds ratios (ORs) with corresponding 95% confidence interval (CI) were calculated with a random-effects model. Confidence in the estimates of the obtained effects (quality of evidence) was assessed by using the Grading of Recommendations Assessment, Development, and Evaluation approach.ResultsA total of 11 studies including 448,928 study subjects and 19,128 cancer patients were finally identified for the meta-analysis. Insulin glargine use was associated with a lower odds of cancer compared with non-glargine insulin use (OR 0.81, 95% CI 0.68 to 0.98, P = 0.03; very low-quality evidence). Glargine did not increase the odds of breast cancer (OR 0.99, 95% CI 0.68 to 1.46, P = 0.966; very low-quality evidence). Compared with non-glargine insulin, no significant association was found between insulin glargine and prostate cancer, pancreatic cancer and respiratory tract cancer. Insulin glargine use was associated with lower odds of other site-specific cancer.ConclusionsResults from the meta-analysis don't support the link between insulin glargine and an increased risk of cancer and the confidence in the estimates of the effects is very low. Further studies are needed to examine the relation between insulin glargine and cancer risk, especially breast cancer.

Extracytoplasmic function (ECF) σ factors, the largest group of alternative σ factors, play important roles in response to environmental stresses. Tt-RpoE1 is annotated as an ECF σ factor in Thermoanaerobacter tengcongensis. In this study, we revealed that the Tt-tolB gene located downstream of the Tt-rpoE1 gene encoded the cognate anti-σ factor, which could inhibit the transcription activity of Tt-RpoE1 by direct interaction with Tt-RpoE1 via its N-terminal domain. By in vitro transcription assay, the auto-regulation ability of Tt-RpoE1 was determined, and band shift assay showed that Tt-RpoE1 preferred to bind a fork-junction promoter DNA. With truncation or base-specific scanning mutations, the contribution of the nucleotides in -35 and -10 regions to interaction between Tt-RpoE1 and promoter DNA was explored. The promoter recognition pattern of Tt-RpoE1 was determined as 5' tGTTACN(16)CGTC 3', which was further confirmed by in vitro transcription assays. This result showed that the Tt-RpoE1-recognized promoter possessed a distinct -10 motif (-13CGTC-10) as the recognition determinant, which is distinguished from the -10 element recognized by σ(70). Site-directed mutagenesis in Region 2.4 of Tt-RpoE1 indicated that the "D" residue of DXXR motif was responsible for recognizing the -12G nucleotide. Our results suggested that distinct -10 motif may be an efficient and general strategy used by ECF σ factors in adaptive response regulation of the related genes.