Search

IntroductionOnline health communities have become the main source for people to obtain health information. However, the existence of poor-quality health information, misinformation, and rumors in online health communities increases the challenges in governing information quality. It not only affects users’ health decisions but also undermines social stability. It is of great significance to explore the factors that affect users’ ability to discern information in online health communities.MethodsThis study integrated the Stimulus-Organism-Response Theory, Information Ecology Theory and the Mindsponge Theory to constructed a model of factors influencing users’ health information discernment abilities in online health communities. A questionnaire was designed based on the variables in the model, and data was collected. Utilizing Structural Equation Modeling (SEM) in conjunction with fuzzy-set Qualitative Comparative Analysis (fsQCA), the study analyzed the complex causal relationships among stimulus factors, user perception, and the health information discernment abilities.ResultsThe results revealed that the dimensions of information, information environment, information technology, and information people all positively influenced health information discernment abilities. Four distinct configurations were identified as triggers for users’ health information discernment abilities. The core conditions included information source, informational support, technological security, technological facilitation, and perceived risk. It was also observed that information quality and emotional support can act as substitutes for one another, as can informational support and emotional support.DiscussionThis study provides a new perspective to study the influencing factors of health information discernment abilities of online health community users. It can provide experiences and references for online health community information services, information resource construction and the development of users’ health information discernment abilities.

BackgroundThe information epidemic emerged along with the COVID-19 pandemic. While controlling the spread of COVID-19, the secondary harm of epidemic rumors to social order cannot be ignored. ObjectiveThe objective of this paper was to understand the characteristics of rumor dissemination before and after the pandemic and the corresponding rumor management and debunking mechanisms. This study aimed to provide a theoretical basis and effective methods for relevant departments to establish a sound mechanism for managing network rumors related to public health emergencies such as COVID-19. MethodsThis study collected data sets of epidemic rumors before and after the relaxation of the epidemic prevention and control measures, focusing on large-scale network rumors. Starting from 3 dimensions of rumor content construction, rumor propagation, and rumor-refuting response, the epidemic rumors were subdivided into 7 categories, namely, involved subjects, communication content, emotional expression, communication channels, communication forms, rumor-refuting subjects, and verification sources. Based on this framework, content coding and statistical analysis of epidemic rumors were carried out. ResultsThe study found that the rumor information was primarily directed at a clear target audience. The main themes of rumor dissemination were related to the public’s immediate interests in the COVID-19 field, with significant differences in emotional expression and mostly negative emotions. Rumors mostly spread through social media interactions, community dissemination, and circle dissemination, with text content as the main form, but they lack factual evidence. The preferences of debunking subjects showed differences, and the frequent occurrence of rumors reflected the unsmooth channels of debunking. The χ2 test of data before and after the pandemic showed that the P value was less than .05, indicating that the difference in rumor content before and after the pandemic had statistical significance. ConclusionsThis study’s results showed that the themes of rumors during the pandemic are closely related to the immediate interests of the public, and the emotions of the public accelerate the spread of these rumors, which are mostly disseminated through social networks. Therefore, to more effectively prevent and control the spread of rumors during the pandemic and to enhance the capability to respond to public health crises, relevant authorities should strengthen communication with the public, conduct emotional risk assessments, and establish a joint mechanism for debunking rumors.

Background: Androgen deprivation therapy (ADT) is the mainstay of treatment for prostate cancer, yet dynamic molecular changes from hormone-sensitive to castration-resistant states in patients treated with ADT remain unclear. Methods: In this study, we combined the dynamic network biomarker (DNB) method and the weighted gene co-expression network analysis (WGCNA) to identify key genes associated with the progression to a castration-resistant state in prostate cancer via the integration of single-cell and bulk RNA sequencing data. Based on the gene expression profiles of CRPC in the GEO dataset, the DNB method was used to clarify the condition of epithelial cells and find out the most significant transition signal DNB modules and genes included. Then, we calculated gene modules associated with the clinical phenotype stage based on the WGCNA. IHC was conducted to validate the expression of the key genes in CRPC and primary PCa patients Results:Nomograms, calibration plots, and ROC curves were applied to evaluate the good prognostic accuracy of the risk prediction model. Results: By combining single-cell RNA sequence data and bulk RNA sequence data, we identified a set of DNBs, whose roles involved in androgen-associated activities indicated the signals of a prostate cancer cell transition from an androgen-dependent state to a castration-resistant state. In addition, a risk prediction model including the risk score of four key genes (SCD, NARS2, ALDH1A1, and NFXL1) and other clinical–pathological characteristics was constructed and verified to be able to reasonably predict the prognosis of patients receiving ADT. Conclusions: In summary, four key genes from DNBs were identified as potential diagnostic markers for patients treated with ADT and a risk score-based nomogram will facilitate precise prognosis prediction and individualized therapeutic interventions of CRPC.

IntroductionIn the response to and prevention and control of the Novel coronavirus pneumonia, the COVID-19 vaccine does not provide lifelong immunity, and it is therefore important to increase the rate of booster shots of the COVID-19 vaccine. In the field of information health science, research has found that information frames have an impact in changing individual attitudes and health behaviors.ObjectiveThis study focuses on the effects of different influencing factors on the public’s willingness to receive the booster shots of the COVID-19 vaccine under two information frameworks.MethodsAn online questionnaire was conducted to explore the effects of demographic characteristics, personal awareness, social relationships, risk disclosure, perceived booster vaccination protection rate, and duration of protection under the assumption of an information framework. T test and one-way analysis were used to testing the effect of variables.Results(1) The persuasion effect under the gain frame is higher than that under the loss frame (B = 0.863 vs. B = 0.746); (2) There was no significant difference in subjects’ intention of booster vaccination in terms of gender, age, income, occupation, educational background and place of residence. Whether family members received booster vaccination was strongly correlated with their intention of vaccination under the loss framework (p = 0.017, M = 4.63, SD = 0.664). (3) The higher the understanding of COVID-19, the higher the degree of compliance with the government’s COVID-19 prevention and control measures, and the higher the willingness to strengthen vaccination; (4) Risk disclosure has a significant impact on people’s willingness to receive COVID-19 booster shots (M = 2.48, under the loss framework; M = 2.44, under the gain framework); (5) Vaccine protection rate and duration of protection have an impact on people’s willingness to vaccinate. Increased willingness to vaccinate when the protection rate of booster vaccine approaches 90% (M = 4.76, under the loss framework; M = 4.68, under the gain framework). When the vaccine protection period is 2 years, people are more willing to receive a booster vaccine; and the willingness to receive a booster shot is stronger under the loss framework (M = 4.60, SD = 0.721, p = 0.879).ConclusionThe impact of the information framework on COVID-19 vaccination intentions is different, and the disclosure of relevant health information should focus on the impact of the information framework and content on the public’s behavior toward strengthening vaccination. Therefore, in the face of public health emergencies, public health departments, healthcare institutions, and other sectors can consider adopting the Gainful Information Framework tool to disseminate health information to achieve better persuasion and promote public health behavior change enhancing public health awareness, and promoting universal vaccination.

Abstract Organic persistent luminescence (pL) systems with photoresponsive dynamic features have valuable applications in the fields of data encryption, anticounterfeiting, and bioimaging. Photoinduced radical luminescent materials have a unique luminous mechanism with the potential to achieve dynamic pL. It is extremely challenging to obtain radical pL under ambient conditions; on account of it, it is unstable in air. Herein, a new semialiphatic polyimide‐based polymer (A0) is developed, which can achieve dynamic pL through reversible conversion of radical under photoexcitation. A “joint–donor–spacer–acceptor” molecular design strategy is applied to effectively modulate the intramolecular charge‐transfer and charge‐transfer complex interactions, resulting in effective protection of the radical generated under photoirradiation. Meanwhile, polyimide‐based polymers of A1–A4 are obtained by doping different amine‐containing fluorescent dyes to modulate the dynamic afterglow color from green to red via the triplet to singlet Förster resonance energy‐transfer pathway. Notably, benefiting from the structural characteristics of the polyimide‐based polymer, A0–A4 have excellent processability, thermal stability, and mechanical properties and can be applied directly in extreme environments such as high temperatures and humidity.

ObjectiveTo investigate the relationship among information processing, risk/benefit perception and the COVID-19 vaccination intention of OHCs users with the heuristic-systematic model (HSM).MethodsThis study conducted a cross-sectional questionnaire via an online survey among Chinese adults. A structural equation model (SEM) was used to examine the research hypotheses.ResultsSystematic information processing positively influenced benefit perception, and heuristic information processing positively influenced risk perception. Benefit perception had a significant positive effect on users' vaccination intention. Risk perception had a negative impact on vaccination intention. Findings revealed that differences in information processing methods affect users' perceptions of risk and benefit, which decide their vaccination intention.ConclusionOnline health communities can provide more systematic cues and users should process information systematically to increase their perceived benefits, consequently increase their willingness to receive COVID-19 vaccine.

(1) Background: Cell proliferation (Ki-67) has important clinical value in the treatment and prognosis of non-small cell lung cancer (NSCLC). However, current detection methods for Ki-67 are invasive and can lead to incorrect results. This study aimed to explore a deep learning classification model for the prediction of Ki-67 and the prognosis of NSCLC based on FDG-PET/CT images. (2) Methods: The FDG-PET/CT scan results of 159 patients with NSCLC confirmed via pathology were analyzed retrospectively, and the prediction models for the Ki-67 expression level based on PET images, CT images and PET/CT combined images were constructed using Densenet201. Based on a Ki-67 high expression score (HES) obtained from the prediction model, the survival rate of patients with NSCLC was analyzed using Kaplan–Meier and univariate Cox regression. (3) Results: The statistical analysis showed that Ki-67 expression was significantly correlated with clinical features of NSCLC, including age, gender, differentiation state and histopathological type. After a comparison of the three models (i.e., the PET model, the CT model, and the FDG-PET/CT combined model), the combined model was found to have the greatest advantage in Ki-67 prediction in terms of AUC (0.891), accuracy (0.822), precision (0.776) and specificity (0.902). Meanwhile, our results indicated that HES was a risk factor for prognosis and could be used for the survival prediction of NSCLC patients. (4) Conclusions: The deep-learning-based FDG-PET/CT radiomics classifier provided a novel non-invasive strategy with which to evaluate the malignancy and prognosis of NSCLC.

With the rapid development of the Internet and the normalization of COVID-19 epidemic prevention and control, Online health communities (OHCs) have gradually become one of the important ways for people to obtain health information, and users have to go through a series of information processing when facing the massive amount of data. Understanding the factors influencing user information processing is necessary to promote users’ health literacy, health knowledge popularization and health behavior shaping. Based on the Heuristic-Systematic Model (HSM), Information Ecology Theory, Privacy Trade-Off and Self-Efficacy Theory, we constructed a model of factors influencing user information processing in online health communities. We found that information quality and emotional support had indirect effects on heuristic and systematic information processing, and these effects were mediated by privacy concerns and self-efficacy. In our research model, systematic information processing was most positively influenced directly by self-efficacy. Privacy concerns had a direct negative correlation with both dual information processing pathways. Therefore, OHCs managers should develop relevant regulations to ensure the information quality in OHCs and improve privacy protection services to promote user information processing by improving users’ self-efficacy and reducing their privacy concerns. Providing a user-friendly and interactive environment for users is also recommended to create more emotional support, thus facilitating more systematic information processing.

Introduction Persistent infection with high-risk human papillomavirus (hrHPV) is the main cause of cervical cancer. Thus, the effective treatment against HPV represents an opportunity to reduce the incidence of cervical cancer. Although various treatments are effective in treating HPV infection, they still provide limited benefit in reducing the rate of cervical cancer due to the lack of implementation of a standardised protocol in many low/middle-income areas. This proposed cohort study aims to describe the status quo of treatment, attributions of the treatment decision-making process and potential factors influencing treatment decisions.Methods and analysis This is a mixed-method, 5-year prospective longitudinal study in Lueyang County, China, one of the areas with the highest cervical cancer incidence rates and lowest mean income in China. We will enrol women with hrHPV infection (at least one HPV type in the 13 high‐risk subtypes) diagnosed via a county-wide HPV infection and cervical cancer screening programme. The study procedures describe the treatment patterns and explore the potential influencing factors in treatment decision-making through questionnaires, laboratory examinations and in-depth interviews. All participants will be evaluated at baseline and at 6, 12, 24, 36, 48 and 60 months. The primary outcome is the treatment pattern, the type and duration of which will be described later. The secondary outcomes include guideline compliance and changes in the HPV infection status. The HPV impact profile, intimate relationship satisfaction, and costs within different management groups are also described and compared.Ethics and dissemination This study was reviewed, and all of the relevant approvals were obtained from the Ethics Committee of the Maternity Service Centre of Lueyang Maternal and Child Health Care Hospital (2021-001). The findings from this study will be disseminated through peer-reviewed publications, conference presentations and academic workshops.Trial registration number ChiCTR2100053757.

BackgroundThe self-management ability of patients with hypertension is poor, and self-quantification increases gradually with the development of electronics. Self-quantification for patients with hypertension has important implications for individual health. However, there is a lack of relevant scales at present, and we aim to develop a self-quantified scale for patients with hypertension.MethodsThe instrument was developed based on protection motivation theory with literature review, a qualitative interview study and focus group discussions, and pilot testing. A total of 360 patients with hypertension were investigated using the scale. The psychometric properties of the scale were evaluated concerning validity and reliability employing internal consistency reliability, split-half reliability, test-retest reliability, content validity (S-CVI/Ave and I-CVI), and construct validity (exploratory factor analysis and confirmatory factor analysis).ResultsThe final scale had 30 items with seven sub-domains. The Cronbach's α for all domains was 0.900 with a range of 0.817–0.938. The split-half reliability coefficient for all domains was 0.743 with a range of 0.700–0.888. The test-retest reliability coefficient for all domains was 0.880 with a range of 0.849–0.943. The S-CVI/Ave for all domains was 0.922 with a range of 0.906- 0.950, and the I-CVI of each item was a range of 0.800–1.000. The result of confirmatory factor analysis of this scale showed that χ2/df was 2.499, RMSEA = 0.065, GFI=0.865, NFI=0.894, IFI=0.934, TLI=0.914, CFI=0.933, RFI=0.865. The Pearson's coefficients between the total scale and every domain were ranging from 0.347 to 0.695, and each domain ranged from 0.130 to 0.481.ConclusionThe scale has good validity and reliability and can be used as a self-quantification scale for patients with hypertension.

ObjectiveThe main objectives of this study were to use the effect of information framing (different expressions of the same issue, e.g., positive messages and negative messages) to explore key factors that influence the attitude of and intention of the public toward wearing masks and to understand the internal and external factors of intervention on information framing perception.MethodsThis study performed an online questionnaire survey to explore the influence of demographic characteristics, information framing, social norms, and information credibility on the attitude of the public toward masks and their intention to wear them.Results(1) Information framing had a significant impact on the attitudes of people toward masks and their intention to wear them, and the persuasion effect of gain-framed messages was higher than that of loss-framed messages. (2) Gender, income, occupation, educational background, and residence have no significant difference in attitude and intention to wear masks. There was a significant correlation between age and wearing of masks (p = 0.041 < 0.05). (3) Social norms affected people's perception of information framing and their attitude toward wearing masks, but only the impact of loss-framed messages on intention was significant. (4) Information framing affected people's perception of information credibility, which had a positive impact on their intention to wear masks; however, information credibility only had a significant impact on attitude toward wearing masks under the gain-framed messages and played an intermediary role.ConclusionThe impact of information framing on the attitude of people toward masks and their intention to wear them varies. Individuals involved in the publicity of health information related to this issue should pay attention to the influence of information framing and content on the public wearing masks as a means of enhancing public health awareness.

(1) Objective: To explore Chinese residents’ willingness to receive COVID-19 vaccine booster shots and identify predictors of the level of willingness based on the health belief model (HBM). (2) Methods: The snowball sampling method was used to distribute online questionnaires. A chi-square test was used to analyze the relationship between different variables. The causal relationship between HBM-related factors and booster vaccination intentions was explored by Structural equation modeling (SEM). (3) Results: A total of 898 complete responses were included; 64.3% had already received the booster injection. Most respondents intended to vaccinate themselves, while 16.1% were hesitant. Nearly half of the respondents chose to take the booster injection to support China’s vaccination policy. Using the SEM, perceived susceptibility and perceived barriers were found to have a negative effect on booster vaccination intentions, whereas perceived benefit and cues to action positively affected booster vaccination intentions in the HBM. (4) Conclusions: Factors included in this study have different effects on the willingness to take the COVID-19 booster injections. Sociodemographic characteristics and characteristics of participants’ COVID-19 vaccination have a significant effect on the willingness to receive vaccine booster shots. The HBM constructs can serve as good predictors of the acceptance of vaccine booster shots with the exception of perceived severity, which may benefit health officials in terms of conducting targeted strategies in vaccine programs.

Cardiovascular diseases are an important group of diseases that seriously affect quality of life. Thus, their treatment warrants further study. Heparin-binding protein (HBP) is a granulocyte protein derived from neutrophils. When an infection occurs, neutrophils release HBP, which can lead to elevated HBP levels in the blood. Therefore, HBP family members are said to be important indicators of infection. However, basic evidence is still lacking to confirm the possible relationship between HBP and cardiovascular diseases. Using bioinformatics methods, we investigated the role of the HBP network in normal hearts and hearts from patients with cardiovascular disease. First, we used the Open Targets database to obtain a list of HBP-encoding mRNAs related to atherosclerosis, myocarditis, myocardial infarction, and myocardial ischemia. Then, we constructed an HBP gene interaction network map using STRING. Clustering coefficients were calculated using Cytoscape, and MCODE was used for subnet analysis. Finally, the proposed interstitial network of HBPs was established and analyzed by Metascape enrichment analysis of the relevant signaling pathways. The aggregation coefficient of the HBP interaction network was higher among hearts with the four cardiovascular diseases, atherosclerosis (0.496), myocarditis (0.631), myocardial infarction (0.532), and myocardial ischemia (0.551), than in normal hearts. Metascape analysis showed that “NABA_MATRISOME_ASSOCIATED” was a typical pathway with the highest p value associated with epithelialization in all four diseases. Moreover, a large number of important HBPs were identified that may be significant for the treatment of these diseases. Therefore, HBPs do have a highly atopic connectivity network in cardiovascular diseases, and specific HBPs or signaling pathways may be used as targets for the development of new treatments for cardiovascular diseases.

Objective: To investigate the uptake and vaccination willingness of the COVID-19 vaccine among Chinese residents and analyze the difference and factors that impact vaccination. Methods: The snowball sampling method was used to distribute online questionnaires. Relevant sociodemographic data along with the circumstances of COVID-19 vaccination were collected from the respondents. The χ2 test, independent samples t test and binary logistic regression analysis were used to analyze the data. Results: Among 786 respondents, 84.22% had been vaccinated. Over 80% of the vaccinated population have completed all the injections because of supporting the national vaccination policies of China, while the unvaccinated population (23.91%) is mainly due to personal health status. Meanwhile, statistical analysis revealed that the main predictors of not being vaccinated were younger age (3 to 18 years old), personal health status, and lower vaccinated proportion of family members and close friends (p < 0.05). Conclusions: There was a high level of uptake of the COVID-19 vaccine in China, and people who have not been vaccinated generally had a low willingness to vaccinate in the future. Based on our results, it suggested the next work to expand the coverage of the COVID-19 vaccination should be concentrated on targeted publicity and education for people who have not been vaccinated.

In this paper, we utilize the Internet big data tool, namely Baidu Index, to predict the development trend of the new coronavirus pneumonia epidemic to obtain further data. By selecting appropriate keywords, we can collect the data of COVID-19 cases in China between 1 January 2020 and 1 April 2020. After preprocessing the data set, the optimal sub-data set can be obtained by using random forest feature selection method. The optimization results of the seven hyperparameters of the LightGBM model by grid search, random search and Bayesian optimization algorithms are compared. The experimental results show that applying the data set obtained from the Baidu Index to the Bayesian-optimized LightGBM model can better predict the growth of the number of patients with new coronary pneumonias, and also help people to make accurate judgments to the development trend of the new coronary pneumonia.

The aims of the study were (1) to explore information framing effect on the public’s intention to receive the COVID-19 vaccination and (2) to understand the key factors influencing the intention of COVID-19 vaccinations in China. An online questionnaire survey was conducted to explore the influence of demographic characteristics, individual awareness, social relationship, risk disclosure, perceived vaccine efficacy, and protection duration under the assumptions of information framing. The results showed that (1) the persuasion effect under loss frame was higher than that under gain frame (B = 0.616 vs. 0.552); (2) there was no significant difference between sex, age, income, occupation, educational background and residence for the participants’ intention to be vaccinated; whether family members/friends were vaccinated had a strong correlation with their vaccination intention under the gain frame; (3) the higher the understanding of COVID-19 and the compliance with government COVID-19 prevention and control measures were, the higher the vaccination intention was; (4) risk disclosure had the greatest impact on people‘s COVID-19 vaccination intention; (5) perceived vaccine effectiveness and duration of protection had little effect on people’s intention to receive vaccination. The influence of information framing on the intention of COVID-19 vaccination is different. The publicity of relevant health information should pay attention to the influence of information framing and contents on the behavior of public vaccination, so as to enhance public health awareness and promote the vaccination of the whole population.

To evaluate the health information literacy (HIL) level and influencing factors among digital immigrants in rural China and to investigate their obstacles of online health information seeking. Cross-sectional study. Digital immigrants aged 45 to 65 in rural China. Self-assessment questionnaires and a semi-structured interview were developed to measure HIL among 1,132 participants. Nonparametric tests and multiple linear regression were employed to explain the influencing factors. The HIL level of digital immigrants is low. Age, education level, and experience of Internet use impacted their HIL. Digital immigrants primarily accessed the Internet via mobile terminals, but their poor information skills, their lack of HIL education, and the low readability of online health information are major barriers of online health information seeking. Although respondents recognized the positive effects of health-related information on health promotion, their abilities to seek, evaluate, and apply health information were weak. The government should incorporate HIL into the national health literacy promotion program and strengthen legislative supervision of online health information.

Recognized as the primary RNA virus to be categorized and extensively studied, the tobacco mosaic virus (TMV) is foundational to advancements in virology, molecular biology, and biomaterials. Over the past few decades, the deep comprehension of the TMV coat protein (TMVcp) molecular structure and assembly principles has stimulated a surge in research on TMVcp structural design using genetic engineering and chemical modification techniques. The unique characteristics of TMVcp, including its nanoscale orderly structure, ease of modification, and considerable drug loading capacity, have enabled significant progress in its biomedical applications. This review summarizes the advanced strategies deployed for TMVcp design and multidimensional assembly and underscores the prototypical applications of TMVcp‐based biomaterials in bioimaging, drug delivery, tissue engineering, and biosensing. Ultimately, the future prospects of TMVcp research in structural design and biomedical applications are explored, which encompass artificial intelligence‐guided structural and functional design, the development of stimulus‐responsive biomaterials, and potential clinical translation.

Chaigui granules (CG) are a compound composed of six herbal medicines with significant antidepressant effects. However, the antidepressant mechanism of CG remains unclear. In the present study, we attempted to elucidate the antidepressant mechanism of CG by regulating purine metabolism and purinergic signaling. First, the regulatory effect of CG on purine metabolites in the prefrontal cortex (PFC) of chronic unpredictable mild stress (CUMS) rats was analyzed by ultra high-performance liquid chromatography tandem mass spectrometry (UHPLC-MS/MS) targeted quantitative analysis. Meanwhile, purinergic receptors (P2X7 receptor (P2X7R), A1 receptor (A1R) and A2A receptor (A2AR)) and signaling pathways (nod-like receptor protein 3 (NLRP3) inflammasome pathway and cyclic adenosine monophosphate (cAMP)-protein kinase A (PKA) pathway) associated with purine metabolism were analyzed by western blotting and enzyme-linked immunosorbent assay (ELISA). Besides, antidepressant mechanism of CG by modulating purine metabolites to activate purinergic receptors and related signaling pathways was dissected by exogenous supplementation of purine metabolites and antagonism of purinergic receptors in vitro. An in vivo study showed that the decrease in xanthine and the increase in four purine nucleosides were closely related to the antidepressant effects of CG. Additionally, purinergic receptors (P2X7R, A1R and A2AR) and related signaling pathways (NLRP3 inflammasome pathway and cAMP-PKA pathway) were also significantly regulated by CG. The results of exogenous supplementation of purine metabolites and antagonism of purinergic receptors showed that excessive accumulation of xanthine led to activation of the P2X7R-NLRP3 inflammasome pathway, and the reduction of adenosine and inosine inhibited the A1R-cAMP-PKA pathway, which was significantly ameliorated by CG. Overall, CG could promote neuroprotection and ultimately play an antidepressant role by inhibiting the xanthine-P2X7R-NLRP3 inflammasome pathway and activating the adenosine/inosine-A1R-cAMP-PKA pathway.

It is challenging to investigate semantic change detection (SCD) in bi-temporal high-resolution (HR) remote sensing images. For the non-changing surfaces in the same location of bi-temporal images, existing SCD methods often obtain the results with frequent errors or incomplete change detection due to insufficient performance on overcoming the phenomenon of intraclass differences. To address the above-mentioned issues, we propose a novel multi-task consistency enhancement network (MCENet) for SCD. Specifically, a multi-task learning-based network is constructed by combining CNN and Transformer as the backbone. Moreover, a multi-task consistency enhancement module (MCEM) is introduced, and cross-task mapping connections are selected as auxiliary designs in the network to enhance the learning of semantic consistency in non-changing regions and the integrity of change features. Furthermore, we establish a novel joint loss function to alleviate the negative effect of class imbalances in quantity during network training optimization. We performed experiments on publicly available SCD datasets, including the SECOND and HRSCD datasets. MCENet achieved promising results, with a 22.06% Sek and a 37.41% Score on the SECOND dataset and a 14.87% Sek and a 30.61% Score on the HRSCD dataset. Moreover, we evaluated the applicability of MCENet on the NAFZ dataset that was employed for cropland change detection and non-agricultural identification, with a 21.67% Sek and a 37.28% Score. The relevant comparative and ablation experiments suggested that MCENet possesses superior performance and effectiveness in network design.

BackgroundAssociations between high serum uric acid (SUA) and cardiovascular diseases have been reported. However, few studies have been conducted to explore the relationship between SUA and long-term all-cause mortality in coronary artery disease (CAD) patients. Our study aims to investigate the relationship between SUA and long-term all-cause mortality in patients with CAD.MethodsFrom January 2007 to December 2018, we divided 33,034 patients with CAD admitted in the Guangdong Provincial People's Hospital into five groups (quintile 1: SUA

AimThis study investigated the prevalence and mortality associated with moderate or severe mitral regurgitation (MR) among patients undergoing percutaneous coronary intervention (PCI), with or without heart failure (HF).MethodsWe analyzed patients undergoing PCI without mitral valve surgery from the Cardiorenal ImprovemeNt (CIN) study (ClinicalTrials.gov NCT04407936). Patients without echocardiography to determine MR occurrence or lacking follow-up death data were excluded. Primary endpoints were 1-year and long-term all-cause mortality, with a median follow-up time of 5 years (interquartile range: 3.1–7.6).ResultsOf 28,358 patients undergoing PCI treatment [mean age: 62.7 ± 10.7; women: 6,749 (25.6%)], 3,506 (12.4%) had moderate or severe MR, and there was a higher rate of moderate or severe MR in HF group than non-HF group (28.8 vs. 5.6%, respectively). Regardless of HF conditions, patients with moderate or severe MR were older and had worse cardio-renal function and significantly increased 1-year mortality [adjusted hazard ratio (aHR): 1.82, 95% confidence interval (CI): 1.51–2.2], and long-term mortality [aHR: 1.43, 95% CI: 1.3–1.58]. There was no significant difference between patients with HF and those with non-HF (P for interaction > 0.05).ConclusionOne-eighth of the patients undergoing PCI had moderate or severe MR. Furthermore, one-third and one-seventeenth experienced moderate or severe MR with worse cardiorenal function in the HF and non-HF groups, and increased consistent mortality risk. Further studies should explore the efficacy of mitral interventional procedures for moderate or severe MR after PCI treatment, regardless of HF.