Objective: To investigate the health-related quality of life and its influencing factors in elderly patients with metabolic syndrome (MS), so as to provide the evidence for improving health-related quality of life in older adults with chronic diseases. Methods: In 2021, elderly MS patients aged ≥60 years from four districts in Nanjing City were selected as the study subjects using a multi-stage random sampling method. Data on social demographic information, lifestyle, disease history and blood biochemical indicators were collected through questionnaire surveys, physical examination and laboratory tests. Health utility value and EuroQol Visual Analog Scale (EQ-VAS) score were assessed using the EuroQol 5-dimension 3-level questionnaire. Factors affecting health-related quality of life were identified with the Tobit regression model and multiple linear regression model. Results: A total of 3 378 elderly MS patients were included, with a median age of 67.00 (interquartile range, 7.00) years. There were 1 558 males (46.12%) and 1 820 females (53.88%). The median (interquartile range) of health utility value and EQ-VAS score were 1.00 (0.03) and 80.00 (15.00). Tobit regression and multiple linear regression analysis showed that gender (female, β=-0.034), education level (middle school, β=0.024; junior college and above, β=0.046), marital status (married, β=0.014), physical activity (sufficient, β=0.013), vegetable intake (meet standard, β=-0.009) and fruit intake (meet standard, β=0.016) were the influencing factors of health utility value. Residence (urban area, β=1.933) and alcohol consumption (yes, β=1.761) were influencing factors of EQ-VAS score. Age, cardiovascular and cerebrovascular diseases, malignant tumors and chronic respiratory diseases were the influencing factors of health utility value and EQ-VAS score. Conclusion Age, sex, marital status, residence, lifestyle and disease are mainly associatied with the health-related quality of life in elderly MS patients.

With the rapid development of generative artificial intelligence(GAI)technologies,their widespread application in academic research and writing is continuously expanding the boundaries of sci-entific inquiry.However,this trend has also raised a series of ethical and regulatory challenges,inclu-ding issues related to authorship,content authenticity,citation accuracy,and accountability.In light of the growing involvement of AI in generating academic content,establishing an open,controllable,and trustworthy ethical governance framework has become a key task for safeguarding research integrity and maintaining trust within the academic community.This expert consensus outlines ethical requirements across key stages of AI-assisted academic writing-including topic selection,data management,citation practices,and authorship attribution.It aims to clarify the boundaries and ethical obligations surrounding AI use in academic writing,ensuring that technological tools enhance efficiency without compromising in-tegrity.The goal is to provide guidance and institutional support for building a responsible and sustainable research ecosystem.

Apical microsurgery is accurate and minimally invasive, produces few complications, and has a success rate of more than 90%. However, due to the lack of awareness and understanding of apical microsurgery by dental general practitioners and even endodontists, many clinical problems remain to be overcome. The consensus has gathered well-known domestic experts to hold a series of special discussions and reached the consensus. This document specifies the indications, contraindications, preoperative preparations, operational procedures, complication prevention measures, and efficacy evaluation of apical microsurgery and is applicable to dentists who perform apical microsurgery after systematic training.
Microsurgery/standards* ; Humans ; Apicoectomy ; Contraindications, Procedure ; Tooth Apex/diagnostic imaging* ; Postoperative Complications/prevention & control* ; Consensus ; Treatment Outcome

Pulpotomy, which belongs to vital pulp therapy, has become a strategy for managing pulpitis in recent decades. This minimally invasive treatment reflects the recognition of preserving healthy dental pulp and optimizing long-term patient-centered outcomes. Pulpotomy is categorized into partial pulpotomy (PP), the removal of a partial segment of the coronal pulp tissue, and full pulpotomy (FP), the removal of whole coronal pulp, which is followed by applying the biomaterials onto the remaining pulp tissue and ultimately restoring the tooth. Procedural decisions for the amount of pulp tissue removal or retention depend on the diagnostic of pulp vitality, the overall treatment plan, the patient's general health status, and pulp inflammation reassessment during operation. This statement represents the consensus of an expert committee convened by the Society of Cariology and Endodontics, Chinese Stomatological Association. It addresses the current evidence to support the application of pulpotomy as a potential alternative to root canal treatment (RCT) on mature permanent teeth with pulpitis from a biological basis, the development of capping biomaterial, and the diagnostic considerations to evidence-based medicine. This expert statement intends to provide a clinical protocol of pulpotomy, which facilitates practitioners in choosing the optimal procedure and increasing their confidence in this rapidly evolving field.
Humans ; Calcium Compounds/therapeutic use* ; Consensus ; Dental Pulp ; Dentition, Permanent ; Oxides/therapeutic use* ; Pulpitis/therapy* ; Pulpotomy/standards*

CD47 is an immune checkpoint widely regarded as a 'don't eat me' signal. CD47-based anti-cancer therapy has received considerable attention, with a significant number of clinical trials conducted. While anti-cancer therapies based on CD47 remain a focal point of interest among researchers, it is noteworthy that an increasing number of studies have found that CD47-based therapy ameliorated the pathological status of non-cancer diseases. This review aims to provide an overview of the recent progress in comprehending the role of CD47-based therapy in non-cancer diseases, including diseases of the circulatory system, nervous system, digestive system, and so on. Furthermore, we sought to delineate the promising mechanisms of CD47-based therapy in treating non-cancer diseases. Our findings suggest that CD47-based agents may exert their effect by regulating phagocytosis, regulating T cells, dendritic cells, and neutrophils, and regulating the secretion of cytokines and chemokines. Additionally, we put forward the orientation of further research to bring to light the potential of CD47 and its binding partners as a target in non-cancer diseases.

Ovarian tumor (OT) is the most lethal form of gynecologic malignancy, with minimal improvements in patient outcomes over the past several decades. Metastasis is the leading cause of ovarian cancer-related deaths, yet the underlying mechanisms remain poorly understood. Psychological stress is known to activate the glucocorticoid receptor (NR3C1), a factor associated with poor prognosis in OT patients. However, the precise mechanisms linking NR3C1 signaling and metastasis have yet to be fully elucidated. In this study, we demonstrate that chronic restraint stress accelerates epithelial-mesenchymal transition (EMT) and metastasis in OT through an NR3C1-dependent mechanism involving nuclear protein 1 (NUPR1). Mechanistically, NR3C1 directly regulates the transcription of NUPR1, which in turn increases the expression of snail family transcriptional repressor 2 (SNAI2), a key driver of EMT. Clinically, elevated NR3C1 positively correlates with NUPR1 expression in OT patients, and both are positively associated with poorer prognosis. Overall, our study identified the NR3C1/NUPR1 axis as a critical regulatory pathway in psychological stress-induced OT metastasis, suggesting a potential therapeutic target for intervention in OT metastasis.

Objective To explore the risk factors for 28-day mortality of sepsis-associated acute kidney injury(SA-AKI)patients and to develop a nomogram risk prediction model.Methods A retrospective cohort study was conducted,involving 184 patients with SA-AKI admitted to the intensive care unit(ICU)of the 940th Hospital of Joint Logistic Support Force of PLA between January 2017 and December 2022.Patients were categorized into survival(n=135)and non-survival(n=49)groups based on 28-day mortality.Clinical data were collected,and statistically significant risk factors were preliminarily screened.Multivariate stepwise logistic regression analysis was performed to identify independent risk factors for 28-day mortality of SA-AKI patients.A nomogram predictive model was constructed using these factors,and internally validated with the Bootstrap method.The receiver operating characteristic curve(ROC curve)was drawn,and the area under the ROC curve(AUC)was calculated to verify the predictive value and accuracy of the model.Results The 28-day mortality rate among 184 SA-AKI patients was 26.6％(49/184).Multivariate stepwise logistic regression analysis identified multiple organ dysfunction syndrome(MODS)(OR=16.393,95％CI 4.317-62.254,P＜0.001),high acute physiology and chronic health evaluation Ⅱ(APACHE Ⅱ)score(OR=1.097,95％CI 1.036-1.161,P=0.002),low oxygenation index(OR=0.992,95％CI 0.986-0.998,P=0.015),low neutrophil count(OR=0.912,95％CI 0.860-0.968,P=0.002)and low fibrinogen concentration(OR=0.733,95％CI 0.549-0.978,P=0.034)as independent risk factors.The prediction model equation was P=1/1+e-logit(P),logit(P)=-1.626+2.797×MODS+0.092×AP ACHE Ⅱ+(-0.311)×fibrinogen+(-0.092)×neutrophil count+(-0.008)×oxygenation index.Internal validation with 1000 Bootstrap resamples showed high consistency between predicted and actual values.ROC analysis showed an AUC of 0.911(95％CI 0.868-0.955,P＜0.05)for the model,with 93.9％sensitivity and 78.5％specificity at a cut-off of 0.194.The Hosmer-Lemeshow test confirmed good calibration(P=0.62),and decision-making curve analysis demonstrated clinical utility within the high-risk threshold range(0.1-0.9).Conclusions MODS,high APACHE Ⅱ score,low oxygenation index,low neutrophil count,and low fibrinogen concentration are independent risk factors for 28-day mortality in SA-AKI patients.The developed nomogram risk prediction model may provide important guidance for predicting 28-day mortality in SA-AKI patients.

Objective To investigate plasma protein expression changes in heatstroke patients using proteomics technology and to identify reliable prognostic biomarkers.Methods A retrospective analysis was conducted on 20 heatstroke patients hospitalized at the 908th Hospital of the Chinese PLA Joint Logistics Support Force from July 2022 to February 2024.Patients were divided into survival(n=16)and death groups(n=4)based on 28-day outcomes.Fasting venous blood samples were collected from both groups for proteomic analysis.Liquid chromatography-mass spectrometry(LC-MS/MS)was used to identify and screen differentially expressed proteins.Kyoto Encyclopedia of Genes and Genomes(KEGG)and Gene Ontology(GO)enrichment analyses were performed.LASSO regression was applied to screen key prognostic biomarkers,and receiver operating characteristic(ROC)curve analysis was used to evaluate their predictive value.Results A total of 27 upregulated and 90 downregulated proteins were identified between the two groups.These proteins were primarily involved in biological processes such as immune responses,complement activation,and metabolic processes.LASSO regression analysis indicated that actin-related protein 2(ARP2),cysteine-rich scavenger receptor type 1 M130(CD163),and catalase(CAT)could serve as effective biomarkers for evaluating heatstroke prognosis.ROC curve analysis demonstrated that ARP2 had higher diagnostic efficacy(AUC=0.98,sensitivity=0.80,specificity=1.00)compared to CD163(AUC=0.94,sensitivity=0.76,specificity=1.00),CAT(AUC=0.96,sensitivity=0.67,specificity=1.00),and acute physiology and chronic health evaluation Ⅱ(APACHE Ⅱ)score(AUC=0.79,sensitivity=0.44,specificity=1.00).Conclusion Elevated plasma ARP2 level has good clinical value for predicting poor prognosis in heatstroke patients.

Objective To evaluate the efficacy of Compound Fipronil Spot-on Solution in repelling canine ticks.Methods A total of 140 dogs infested with ticks were randomly selected from regions in southern and northern China and assigned to four groups:southern test drug group,southern control drug group,northern test drug group,and northern control drug group.Each group comprised 35 dogs.Each dog was administered the prescribed dose.The number of ticks was counted on days 1,7,14,21,and 28 following the administration.The negative conversion and average reduction rates of the tick population were then subjected to statistical analyse.Results The mean efficacy of the test drug was 100%in both the southern and northern cohorts,28 days post-treatment.The control drug showed comparable efficacy,reaching a mean reduction of 100%in both regions by the same time point.No additional clinical manifestations or adverse events were observed across all treated dogs.Conclusions Compound Fipronil Spot-on Solutions effectively treats and prevents ticks in dogs in different regions of China.A single dose remains effective for up to 28 days,thus providing a convenient,effective solution.

With the rapid development of generative artificial intelligence(GAI)technologies,their widespread application in academic research and writing is continuously expanding the boundaries of sci-entific inquiry.However,this trend has also raised a series of ethical and regulatory challenges,inclu-ding issues related to authorship,content authenticity,citation accuracy,and accountability.In light of the growing involvement of AI in generating academic content,establishing an open,controllable,and trustworthy ethical governance framework has become a key task for safeguarding research integrity and maintaining trust within the academic community.This expert consensus outlines ethical requirements across key stages of AI-assisted academic writing-including topic selection,data management,citation practices,and authorship attribution.It aims to clarify the boundaries and ethical obligations surrounding AI use in academic writing,ensuring that technological tools enhance efficiency without compromising in-tegrity.The goal is to provide guidance and institutional support for building a responsible and sustainable research ecosystem.