Objective To understand the status of body image disturbance and its influencing factors in patients with ankylosing spondylitis (AS), so as to provide a scientific basis for the clinical management of AS. Methods A total of 353 AS patients admitted from January 2022 to December 2024 were selected as research subjects. Chinese version of Body Image Disturbance Questionnaire (BIDQ) was used to investigate the body image disturbance in AS patients. Single factor analysis was performed by t test and analysis of variance, and multiple factors were analyzed by multivariate linear regression. Results The total score of BIDQ in 342 AS patients was (25.01±4.22). Multivariate linear regression analysis results showed that self-paid medical expense, nighttime VAS score and negative emotion PANAS score could positively predict body image disturbance in AS patients (standardized regression coefficient=0.413, 0.413, 0.460, P<0.05), and PSSS score, positive emotion PANAS score and exercise management CDSSM score could negatively predict body image disturbance (standardized regression coefficient=-0.245, -0.134, -0.247, P<0.05). Conclusion The body image disturbance in AS patients is worthy of clinical attention. Nighttime pain, negative emotion and self-paid medical treatment can increase the risk of body image disturbance. Positive emotion, social support and high self-management level of exercise behavior can reduce the formation of body image disturbance, which can provide new ideas for clinical management of AS patients.

Objective To investigate the utility of combining breast mass growth orientation quantification with the S-Detect technique for predicting axillary lymph node(ALN)metastasis in breast cancer.Methods Data was collected from 163 breast cancer patients admitted to our hospital between March 2023 and October 2024,who were categorized into metastatic(n=62)and non-metastatic(n=101)groups based on ALN pathology results.All patients underwent routine preoperative ultrasound and S-Detect examination.Univariate and multivariate regression analyses were performed to assess the correlation between each observational index and ALN metastasis.Significant indexes were identified through screening,leading to the establishment of a logistic regression prediction model.The predictive value of the model was evaluated using receiver operating characteristic(ROC)curve analysis.Results The univariate analysis revealed statistically significant differences(P<0.05)in the maximum diameter of the mass,border characteristics,margin features,calcification patterns,orientation angle,and blood flow between the two groups.Multifactorial analysis demonstrated that calcification,border characteristics,orientation angle,margin features,and maximum diameter independently influenced the prediction of axillary lymph node(ALN)status in breast cancer patients(P<0.05).Consequently,a logistic regression prediction model was constructed as follows:Y=-7.995+2.299×maximal diameter+1.171×border+2.137×margin+1.397×calcication+0.034×orientation angle.The area under curve(AUC)for this combined prediction model was 0.869 which significantly outperformed each independent influencing factor alone(P<0.05),indicating good agreement between this joint prediction model and pathological results(Kappa=0.701,P<0.05).Conclusions Quantification of the orientation angle of a breast mass aids in predicting axillary lymph node(ALN)metastasis and enhances the interpretation and application of non-parallel orientations.The combination of quantifying growth orientation based on breast mass with artificial intelligence S-Detect technique demonstrates promising predictive value for ALN metastasis in breast cancer,providing a reference basis for personalized treatment.

Objective To investigate the utility of combining breast mass growth orientation quantification with the S-Detect technique for predicting axillary lymph node(ALN)metastasis in breast cancer.Methods Data was collected from 163 breast cancer patients admitted to our hospital between March 2023 and October 2024,who were categorized into metastatic(n=62)and non-metastatic(n=101)groups based on ALN pathology results.All patients underwent routine preoperative ultrasound and S-Detect examination.Univariate and multivariate regression analyses were performed to assess the correlation between each observational index and ALN metastasis.Significant indexes were identified through screening,leading to the establishment of a logistic regression prediction model.The predictive value of the model was evaluated using receiver operating characteristic(ROC)curve analysis.Results The univariate analysis revealed statistically significant differences(P<0.05)in the maximum diameter of the mass,border characteristics,margin features,calcification patterns,orientation angle,and blood flow between the two groups.Multifactorial analysis demonstrated that calcification,border characteristics,orientation angle,margin features,and maximum diameter independently influenced the prediction of axillary lymph node(ALN)status in breast cancer patients(P<0.05).Consequently,a logistic regression prediction model was constructed as follows:Y=-7.995+2.299×maximal diameter+1.171×border+2.137×margin+1.397×calcication+0.034×orientation angle.The area under curve(AUC)for this combined prediction model was 0.869 which significantly outperformed each independent influencing factor alone(P<0.05),indicating good agreement between this joint prediction model and pathological results(Kappa=0.701,P<0.05).Conclusions Quantification of the orientation angle of a breast mass aids in predicting axillary lymph node(ALN)metastasis and enhances the interpretation and application of non-parallel orientations.The combination of quantifying growth orientation based on breast mass with artificial intelligence S-Detect technique demonstrates promising predictive value for ALN metastasis in breast cancer,providing a reference basis for personalized treatment.

Objective: To analyze the epidemiological characteristics and trends of other infectious diarrhea among children under 18 years old in Guangzhou City from 2014 to 2020, and to explore the correlation between climatic factors and the incidence of the disease, so as to provide reference for the early prevention of infectious diseases. Methods: The data of cases of other infectious diarrhea and meteorological data of children under 18 years old in Guangzhou City from 2014 to 2020 were collected through the Chinese Infectious Disease Reporting System and the Guangzhou Meteorological Bureau. The correlation between meteorological factors and the incidence of other infectious diarrhea was analyzed using negative binomial regression. Results: A total of 104 566 cases of other infectious diarrhea among children under 18 years old were reported in Guangzhou City from 2014 to 2020, with a male to female ratio of 1.48∶1. The incidence rate was the highest in 2017 (980.83 per 100 000) and the lowest in 2020 (388.22 per 100 000). The peak of incidence occurred from October to March of the following year. Children under 5 years old accounted for 87.95% of all cases. The number of cases of other infectious diarrhea was negatively correlated with the temperature of the previous 6 days ( IRR = -0.07 ), and positively correlated with the temperature difference on the day of onset ( IRR =0.02) (both P <0.05). It was also positively correlated with the wind speed of the previous 7 days ( IRR=0.07, P <0.05), but there was no statistically significant correlation with the relative humidity on the day of onset ( IRR=-0.00, P >0.05). Conclusions Low temperature, large temperature difference, and high wind speed can increase the risk of other infectious diarrhea. It is necessary to strengthen the prediction and early warning in conjunction with meteorological changes, and warn kindergartens and schools to enhance preventive measures against the clustering of other infectious diarrhea cases.

The therapeutic effects of Yueju Pills on depression and cardiovascular diseases have been widely recognized. Previous studies have shown that the drug can significantly improve depressive-like behaviors induced by chronic unpredictable mild stress(CUMS) combined with atherosclerosis(AS). Given the complex pathogenesis of psychocardiac diseases, this study integrated metabolomics and network pharmacology to systematically elucidate the mechanism of Yueju Pills in alleviating depressive symptoms in psychocardiac diseases. The results demonstrate that, after Yueju Pill intervention, the levels of 9 abnormal metabolites in the hippocampus restore to normal ranges, primarily involving key pathways or signaling pathways, including the cyclic adenosine monophosphate(cAMP), mammalian target of rapamycin(mTOR), glycine/serine/threonine metabolism, and aminoacyl-tRNA biosynthesis. In a high-fat diet-induced CUMS ApoE~(-/-) mouse model, Yueju Pills significantly increases adenosine monophosphate(AMP) levels and decreases L-alanine and D-glyceric acid levels in the hippocampus. In conclusion, Yueju Pills exert antidepressant effects by regulating multiple metabolic axes, including glycine/serine/threonine metabolism and the cAMP, mTOR signaling pathways. Network pharmacology predictions reveal that the treatment of CUMS combined with AS by its core active components may be realized through modulating pathways concerning neuroinflammation and synaptic plasticity, including serine/threonine-protein kinase 1(AKT1), mitogen-activated protein kinase 1(MAPK1), and prostaglandin-endoperoxide synthase 2(PTGS2). This study provides a theoretical reference for the clinical application of Yueju Pills in alleviating the depressive symptoms of psychocardiac diseases.
Animals ; Network Pharmacology ; Mice ; Drugs, Chinese Herbal/administration & dosage* ; Metabolomics ; Male ; Depression/genetics* ; Humans ; Hippocampus/drug effects* ; Mice, Inbred C57BL ; Signal Transduction/drug effects*

Cemental tear is a rare and indetectable condition unless obvious clinical signs present with the involvement of surrounding periodontal and periapical tissues. Due to its clinical manifestations similar to common dental issues, such as vertical root fracture, primary endodontic diseases, and periodontal diseases, as well as the low awareness of cemental tear for clinicians, misdiagnosis often occurs. The critical principle for cemental tear treatment is to remove torn fragments, and overlooking fragments leads to futile therapy, which could deteriorate the conditions of the affected teeth. Therefore, accurate diagnosis and subsequent appropriate interventions are vital for managing cemental tear. Novel diagnostic tools, including cone-beam computed tomography (CBCT), microscopes, and enamel matrix derivatives, have improved early detection and management, enhancing tooth retention. The implementation of standardized diagnostic criteria and treatment protocols, combined with improved clinical awareness among dental professionals, serves to mitigate risks of diagnostic errors and suboptimal therapeutic interventions. This expert consensus reviewed the epidemiology, pathogenesis, potential predisposing factors, clinical manifestations, diagnosis, differential diagnosis, treatment, and prognosis of cemental tear, aiming to provide a clinical guideline and facilitate clinicians to have a better understanding of cemental tear.
Humans ; Dental Cementum/injuries* ; Consensus ; Diagnosis, Differential ; Cone-Beam Computed Tomography ; Tooth Fractures/therapy*

OBJECTIVE: Blood culture remains the gold standard for diagnosing bloodstream infections. Clinical laboratories must ensure the quality of blood culture processes from receipt to obtaining definitive results. We examined laboratory analytical indicators associated with positive blood culture results. METHODS: Blood cultures collected from Peking Union Medical College Hospital between January 1, 2020, and December 31, 2022, were retrospectively analyzed. The mode of transportation (piping logistics delivery vs. staff), source of blood cultures (outpatient/emergency department vs. inpatient department), rotation of personnel, and time of reception (8:00-19:59 vs. 20:00-07:59) were compared between blood culture-positive and -negative results. RESULTS: Between 2020 and 2022, the total positive rate of blood culture was 8.07%. The positive rate of blood cultures in the outpatient/emergency department was significantly higher than that in the inpatient department (12.46% vs. 5.83%; P < 0.0001). The time-to-detection of blood cultures was significantly affected by the delivery mode and personnel rotation. The blood culture positive rate of the total pre-analytical time within 1 h was significantly higher than that within 1-2 h or > 2 h ( P < 0.0170). CONCLUSION Laboratory analytical indicators such as patient source, transportation mode, and personnel rotation significantly impacted the positive detection rate or time of blood culture.
Blood Culture/statistics & numerical data* ; Humans ; Retrospective Studies ; Emergency Service, Hospital/statistics & numerical data*

Proteins are the basic building blocks of life. Studying the protein expression mechanism is essential for understanding the cellular organization principles and the development of biotechnology. Protein expression, involving transcription, translation, folding, and post-translational modification, is a complicatedly regulated process affected by various cellular components and sequence features of the expressed protein. Establishing protein expression models based on expression data is of great significance for probing into the regulatory factors and mechanisms of protein expression. Here we review the recent research progress in the mechanism models for quantitatively simulating the protein expression process and the prediction algorithms based on artificial intelligence for analyzing the regulatory factors. Chemical reaction network models have been developed to mathematically describe the elementary processes in protein expression and simulate the influences of various cellular components such as RNA polymerase and tRNA. However, the experimental determination of the huge number of model parameters is a big challenge. The main objective of data-driven AI models is to study the effects of protein/DNA sequences of the target protein on its expression, and subsequently optimize the sequences to improve protein expression. Methods combining mechanism models and AI models have the potential to deepen our understanding of protein expression processes, providing theoretical and technical support for the efficient production of high-value proteins and coordinate the regulation of different proteins.
Artificial Intelligence ; Proteins/metabolism* ; Algorithms ; Protein Biosynthesis

BACKGROUND: The available evidence regarding the benefits of percutaneous coronary intervention (PCI) on patients receiving dialysis with coronary artery disease (CAD) is limited and inconsistent. This study aimed to evaluate the association between PCI and clinical outcomes as compared with medical therapy alone in patients undergoing dialysis with CAD in China. METHODS: This multicenter, retrospective study was conducted in 30 tertiary medical centers across 12 provinces in China from January 2015 to June 2021 to include patients on dialysis with CAD. The primary outcome was major adverse cardiovascular events (MACE), defined as a composite of cardiovascular death, non-fatal myocardial infarction, and non-fatal stroke. Secondary outcomes included all-cause death, the individual components of MACE, and Bleeding Academic Research Consortium criteria types 2, 3, or 5 bleeding. Multivariable Cox proportional hazard models were used to assess the association between PCI and outcomes. Inverse probability of treatment weighting (IPTW) and propensity score matching (PSM) were performed to account for potential between-group differences. RESULTS: Of the 1146 patients on dialysis with significant CAD, 821 (71.6%) underwent PCI. After a median follow-up of 23.0 months, PCI was associated with a 43.0% significantly lower risk for MACE (33.9% [ n  = 278] vs . 43.7% [ n  = 142]; adjusted hazards ratio 0.57, 95% confidence interval 0.45-0.71), along with a slightly increased risk for bleeding outcomes that did not reach statistical significance (11.1% vs . 8.3%; adjusted hazards ratio 1.31, 95% confidence interval, 0.82-2.11). Furthermore, PCI was associated with a significant reduction in all-cause and cardiovascular mortalities. Subgroup analysis did not modify the association of PCI with patient outcomes. These primary findings were consistent across IPTW, PSM, and competing risk analyses. CONCLUSION This study indicated that PCI in patients on dialysis with CAD was significantly associated with lower MACE and mortality when comparing with those with medical therapy alone, albeit with a slightly increased risk for bleeding events that did not reach statistical significance.
Humans ; Percutaneous Coronary Intervention/methods* ; Male ; Female ; Coronary Artery Disease/drug therapy* ; Retrospective Studies ; Renal Dialysis/methods* ; Middle Aged ; Aged ; China ; Proportional Hazards Models ; Treatment Outcome

In recent years, the study of single-cell transcriptome sequencing technology in the heterogeneity of astrocytes (astrocytes) after spinal cord injury (SCI) has provided new perspectives on post-traumatic nerve regeneration and repair. To provide a review on the research progress of single-cell sequencing technology in astrocytes after spinal cord injury (SCI), and to more comprehensively and deeply elaborate the application of single-cell sequencing technology in the field of astrocytes after SCI. Single-cell sequencing technology can analyse the transcriptomes of individual cells in a high-throughput manner, thus revealing fine differences in cell types and states. By using single-cell sequencing technology, the heterogeneity of astrocytes after SCI and their association with nerve regeneration and repair were revealed. In conclusion, the application of single-cell sequencing technology provides an important tool to reveal the heterogeneity of astrocytes after SCI, to further explore the mechanisms of astrocytes in SCI, and to develop intervention strategies targeting their regulatory mechanisms in order to improve the therapeutic efficacy of SCI. The discovery of changes in astrocyte transcriptome dynamics has improved researchers' understanding of spinal cord injury lesion progression and provided new insights into the treatment of spinal cord injury at different time points. To date, all of these findings need to be validated by more basic research and sufficient clinical trials. In the future, single-cell sequencing technology, through interdisciplinary collaboration with bioinformatics, computer science, tissue engineering, and clinical medicine, is expected to open a new window for the treatment of spinal cord injury.
Spinal Cord Injuries/metabolism* ; Astrocytes/cytology* ; Single-Cell Analysis/methods* ; Humans ; Animals ; Transcriptome ; Nerve Regeneration