Objective: To analyze the association between poor sleep characteristics and the coexistence of negative emotions and overweight/obesity among college students, so as to provide a scientific basis for improving their physical and mental health. Methods: From November to December 2023, a convenience sampling method was used to survey 6 600 college students from nine universities in Jiangxi, Hunan, and Hubei provinces. The Depression Anxiety and Stress Scale-21 (DASS-21), Insomnia Severity Index (ISI), Pittsburgh Sleep Quality Index (PSQI), and physical examinations were employed to assess negative emotions, poor sleep characteristics, and overweight/obesity. Chi square test and Logistic regression were used to analyze the impact of poor sleep characteristics on the coexistence of negative emotions and overweight/obesity. Results: The coexistence rates of different categories of negative emotions (depression, anxiety, stress) and overweight/obesity were 6.1% ( n= 405), 8.0% ( n =529), and 3.3% ( n =217), respectively. Gender, grade level, major, maternal education level, annual family income, physical activity level, only child status, and carbonated beverage consumption were statistically associated with the coexistence rates of different categories of negative emotions and overweight/obesity ( χ 2=4.01-35.18, all P <0.05). Logistic regression analysis showed that after adjusting for gender, grade level, major, only child status, maternal education level, annual family income, physical activity level, and carbonated beverage consumption, poor sleep characteristics were significantly associated with an increased risk of the coexistence of negative emotions and overweight/obesity ( OR =1.41-6.65); moderate and poor sleep quality levels were significantly associated with an increased risk of the coexistence of different categories of negative emotions and overweight/obesity among female students ( OR =1.99-4.71) (all P <0.05). Conclusions Poor sleep characteristics are associated with the coexistence of negative emotions and overweight/obesity among college students. Greater attention should be paid to sleep issues in this population, and sleep education should be actively promoted to reduce the risk of comorbid negative emotions and overweight/obesity.

BACKGROUND: The FAVOR (Comparison of Quantitative Flow Ratio Guided and Angiography Guided Percutaneous Intervention in Patients with Coronary Artery Disease) III China trial demonstrated that percutaneous coronary intervention (PCI) lesion selection using quantitative flow ratio (QFR) measurement, a novel angiography-based approach for estimating fractional flow reserve, improved two-year clinical outcomes compared with standard angiography guidance. This study aimed to assess the cost-effectiveness of QFR-guided PCI from the perspective of the current Chinese healthcare system. METHODS: This study is a pre-specified analysis of the FAVOR III China trial, which included 3825 patients randomized between December 25, 2018, and January 19, 2020, from 26 centers in China. Patients with stable or unstable angina pectoris or those ≥72 hours post-myocardial infarction who had at least one lesion with a diameter stenosis between 50% and 90% in a coronary artery with a ≥2.5 mm reference vessel diameter by visual assessment were randomized to a QFR-guided strategy or an angiography-guided strategy with 1:1 ratio. During the two-year follow-up, data were collected on clinical outcomes, quality-adjusted life-years (QALYs), estimated costs of index procedure hospitalization, outpatient cardiovascular medication use, and rehospitalization due to major adverse cardiac and cerebrovascular events (MACCE). The primary analysis calculated the incremental cost-effectiveness ratio (ICER) as the cost per MACCE avoided. An ICER of ¥10,000/MACCE event avoided was considered economically attractive in China. RESULTS: At two years, the QFR-guided group demonstrated a reduced rate of MACCE compared to the angiography-guided group (10.8% vs . 14.7%, P <0.01). Total two-year costs were similar between the groups (¥50,803 ± 21,121 vs . ¥50,685 ± 23,495, P = 0.87). The ICER for the QFR-guided strategy was ¥3055 per MACCE avoided, and the probability of QFR being economically attractive was 64% at a willingness-to-pay threshold of ¥10,000/MACCE avoided. Sensitivity analysis showed that QFR-guided PCI would become cost-saving if the cost of QFR were below ¥3682 (current cost: ¥3800). Cost-utility analysis yielded an ICER of ¥56,163 per QALY gained, with a 53% probability of being cost-effective at a willingness-to-pay threshold of ¥85,000 per QALY gained. CONCLUSION: In patients undergoing PCI, a QFR-guided strategy appears economically attractive compared to angiographic guidance from the perspective of the Chinese healthcare system. TRIAL REGISTRATION ClinicalTrials.gov , NCT03656848.
Humans ; Cost-Benefit Analysis ; Percutaneous Coronary Intervention/methods* ; Male ; Female ; Coronary Angiography/methods* ; Middle Aged ; Aged ; Coronary Artery Disease/surgery* ; Quality-Adjusted Life Years ; Fractional Flow Reserve, Myocardial/physiology*

This study aimed to explore the pharmacological mechanism of Yourenji Capsules(YRJ) in improving osteoporosis by combining network pharmacology and proteomics technologies. The SD rats were randomly divided into a blank control group and a 700 mg·kg~(-1) YRJ group. The rats were subjected to gavage administration with the corresponding drugs, and the blank serum, drug-containing serum, and YRJ samples were compared using ultra performance liquid chromatography-quadrupole time-of-flight tandem mass spectrometry(UPLC-Q-TOF-MS/MS) to analyze the main components absorbed into blood. Network pharmacology analysis was conducted based on the YRJ components absorbed into blood to obtain related targets of the components and target genes involved in osteoporosis, and Venn diagrams were used to identify the intersection of drug action targets and disease targets. The STRING database was used for protein-protein interaction(PPI) network analysis of potential target proteins to construct a PPI network. Gene Ontology(GO) functional enrichment and Kyoto Encyclopedia of Genes and Genomes(KEGG) pathway enrichment were performed using Enrichr to investigate the potential mechanism of action of YRJ. Ovariectomy(OVX) was performed to establish a rat model of osteoporosis, and the rats were divided into a sham group, a model group, and a 700 mg·kg~(-1) YRJ group. The rats were given the corresponding drugs by gavage. The femurs of the rats were subjected to label-free proteomics analysis to detect differentially expressed proteins, and GO functional enrichment and KEGG pathway enrichment analyses were performed on the differentially expressed proteins. With the help of network pharmacology and proteomics results, the mechanism by which YRJ improves osteoporosis was predicted. The analysis of the YRJ components absorbed into blood revealed 23 bioactive components of YRJ, and network pharmacology results indicated that key targets involved include tumor necrosis factor(TNF), tumor protein p53(TP53), protein kinase(AKT1), and matrix metalloproteinase 9(MMP9). These targets are mainly involved in osteoclast differentiation, estrogen signaling pathways, and nuclear factor-kappa B(NF-κB) signaling pathways. Additionally, the proteomics analysis highlighted important pathways such as peroxisome proliferator-activated receptor(PPAR) signaling pathways, mitogen-activated protein kinase(MAPK) signaling pathways, and β-alanine metabolism. The combined approaches of network pharmacology and proteomics have revealed that the mechanism by which YRJ improves osteoporosis may be closely related to the regulation of inflammation, osteoblast, and osteoclast metabolic pathways. The main pathways involved include the NF-κB signaling pathways, MAPK signaling pathways, and PPAR signaling pathways, among others.
Animals ; Drugs, Chinese Herbal/administration & dosage* ; Osteoporosis/metabolism* ; Proteomics ; Rats ; Rats, Sprague-Dawley ; Network Pharmacology ; Female ; Protein Interaction Maps/drug effects* ; Capsules ; Humans ; Signal Transduction/drug effects*

This paper aims to explore the effect of electrical stimulation of triboelectric nanogenerators (TENGs) on the osteogenic and other biological behaviors of mouse embryonic osteoblast precursor cells (MC3T3-E1 cells) on titanium surfaces. First, an origami-type TENG was fabricated, and its electrical output performance was tested. The optimal current of the generator and the feasibility of the experiment were verified by the CCK-8 assay and scratch assay. At the optimal current, the osteogenic conditions of the cells in each group were determined by quantitative analysis of the total protein content, alkaline phosphatase (ALP) activity, and alizarin red staining (ARS) on the titanium surface. Finally, the adhesion and spreading of cells on the titanium surface after electrical stimulation were observed. The results showed that the TENG had good electrical output performance, with an open-circuit voltage of 65 V and a short-circuit current of 42 μA. Compared with the rest of the current, a current strength of 30 μA significantly improved cell proliferation and migration, osteogenesis, and adhesion and spreading capabilities. The above results confirm the safety and operability of TENG in biomedical applications, laying the foundation for future TENG applications in reducing the time of bone integration around titanium implants after surgery.
Titanium/chemistry* ; Osteogenesis ; Animals ; Mice ; Osteoblasts/cytology* ; Electric Stimulation/instrumentation* ; Cell Adhesion ; Cell Proliferation ; Surface Properties ; Cell Differentiation ; Nanotechnology

PURPOSE: Septic shock is associated with high mortality and poor outcomes among sepsis patients with coagulopathy. Although traditional statistical methods or machine learning (ML) algorithms have been proposed to predict septic shock, these potential approaches have never been systematically compared. The present work aimed to develop and compare models to predict septic shock among patients with sepsis. METHODS: It is a retrospective cohort study based on 484 patients with sepsis who were admitted to our intensive care units between May 2018 and November 2022. Patients from the 908th Hospital of Chinese PLA Logistical Support Force and Nanchang Hongdu Hospital of Traditional Chinese Medicine were respectively allocated to training (n=311) and validation (n=173) sets. All clinical and laboratory data of sepsis patients characterized by comprehensive coagulation indexes were collected. We developed 5 models based on ML algorithms and 1 model based on a traditional statistical method to predict septic shock in the training cohort. The performance of all models was assessed using the area under the receiver operating characteristic curve and calibration plots. Decision curve analysis was used to evaluate the net benefit of the models. The validation set was applied to verify the predictive accuracy of the models. This study also used Shapley additive explanations method to assess variable importance and explain the prediction made by a ML algorithm. RESULTS: Among all patients, 37.2% experienced septic shock. The characteristic curves of the 6 models ranged from 0.833 to 0.962 and 0.630 to 0.744 in the training and validation sets, respectively. The model with the best prediction performance was based on the support vector machine (SVM) algorithm, which was constructed by age, tissue plasminogen activator-inhibitor complex, prothrombin time, international normalized ratio, white blood cells, and platelet counts. The SVM model showed good calibration and discrimination and a greater net benefit in decision curve analysis. CONCLUSION The SVM algorithm may be superior to other ML and traditional statistical algorithms for predicting septic shock. Physicians can better understand the reliability of the predictive model by Shapley additive explanations value analysis.
Humans ; Shock, Septic/blood* ; Machine Learning ; Male ; Female ; Retrospective Studies ; Middle Aged ; Aged ; Sepsis/complications* ; ROC Curve ; Cohort Studies ; Adult ; Intensive Care Units ; Algorithms ; Blood Coagulation ; Critical Illness

Isolated male epispadias typically presents with preputial defects and dorsal urethral dehiscence. A less common subtype, known as concealed epispadias, is distinguished by an intact prepuce. Despite its clinical relevance, there is limited literature on this variant. In this study, we retrospectively analyzed the clinical data of 86 pediatric patients with isolated male epispadias treated in Beijing Children's Hospital (Beijing, China) from May 2004 to July 2023, including 19 cases of concealed epispadias and 67 of nonconcealed epispadias. We compared clinical characteristics, preoperative diagnostics, surgical techniques, postoperative outcomes, and sexual function during follow-up between the concealed and nonconcealed groups. No significant differences were observed between the two groups regarding surgical methods, postoperative complications, or rates of urinary incontinence. However, notable distinctions were found in the age at initial diagnosis, timing of surgery, frequency of incontinence, location of the urethral meatus, and postoperative urinary incontinence scores (all P < 0.05). Given the absence of penopubic epispadias in concealed cases, we categorized glans and penile epispadias within nonconcealed epispadias as distal epispadias ( n = 40) and subsequently compared them with concealed epispadias cases. The postoperative urinary incontinence scores did not differ significantly between the concealed and distal epispadias groups. These findings suggest that concealed epispadias represents a relatively milder form of the condition, characterized by the absence of penopubic involvement, lower rates of urinary incontinence, and favorable surgical outcomes. However, the intact prepuce in concealed cases underscores the need for careful identification and early diagnosis.
Humans ; Male ; Retrospective Studies ; Epispadias/classification* ; China ; Tertiary Care Centers ; Child, Preschool ; Child ; Postoperative Complications/epidemiology* ; Urinary Incontinence/epidemiology* ; Urethra/surgery* ; Infant ; Penis/surgery* ; Adolescent ; Urologic Surgical Procedures, Male/methods* ; East Asian People

Cardiac fibrosis is characterized by an elevated amount of extracellular matrix (ECM) within the heart. However, the persistence of cardiac fibrosis ultimately diminishes contractility and precipitates cardiac dysfunction. Circular RNAs (circRNAs) are emerging as important regulators of cardiac fibrosis. Here, we elucidate the functional role of a specific circular RNA CELF1 in cardiac fibrosis and delineate a novel feedback loop mechanism. Functionally, circ-CELF1 was involved in enhancing fibrosis-related markers' expression and promoting the proliferation of cardiac fibroblasts (CFs), thereby exacerbating cardiac fibrosis. Mechanistically, circ-CELF1 reduced the ubiquitination-degradation rate of BRPF3, leading to an elevation of BRPF3 protein levels. Additionally, BRPF3 acted as a modular scaffold for the recruitment of histone acetyltransferase KAT7 to facilitate the induction of H3K14 acetylation within the promoters of the Celf1 gene. Thus, the transcription of Celf1 was dramatically activated, thereby inhibiting the subsequent response of their downstream target gene Smad7 expression to promote cardiac fibrosis. Moreover, Celf1 further promoted Celf1 pre-mRNA transcription and back-splicing, thereby establishing a feedback loop for circ-CELF1 production. Consequently, a novel feedback loop involving CELF1/circ-CELF1/BRPF3/KAT7 was established, suggesting that circ-CELF1 may serve as a potential novel therapeutic target for cardiac fibrosis.

Identifying drug-drug interactions (DDIs) is essential to prevent adverse effects from polypharmacy. Although deep learning has advanced DDI identification, the gap between powerful models and their lack of clinical application and evaluation has hindered clinical benefits. Here, we developed a Multi-Dimensional Feature Fusion model named MDFF, which integrates one-dimensional simplified molecular input line entry system sequence features, two-dimensional molecular graph features, and three-dimensional geometric features to enhance drug representations for predicting DDIs. MDFF was trained and validated on two DDI datasets, evaluated across three distinct scenarios, and compared with advanced DDI prediction models using accuracy, precision, recall, area under the curve, and F1 score metrics. MDFF achieved state-of-the-art performance across all metrics. Ablation experiments showed that integrating multi-dimensional drug features yielded the best results. More importantly, we obtained adverse drug reaction reports uploaded by Xiangya Hospital of Central South University from 2021 to 2023 and used MDFF to identify potential adverse DDIs. Among 12 real-world adverse drug reaction reports, the predictions of 9 reports were supported by relevant evidence. Additionally, MDFF demonstrated the ability to explain adverse DDI mechanisms, providing insights into the mechanisms behind one specific report and highlighting its potential to assist practitioners in improving medical practice.

Adenomyosis is a common gynecological disease characterized by the invasion of endometrial glands and stroma into the myometrium of uterus, the pathological mechanism of which remains unclear yet. Disturbed lipid metabolism extensively affects abnormal cell proliferation and invasion in various diseases. However, the lipidome signature of human myometrium, which could be crucial in the development of adenomyosis, remains unknown. In this study, we generated the first lipidome profiling of human myometrium using a high-coverage and quantitative lipidomics approach based on ultra-performance liquid chromatography (UPLC) coupled with triple quadrupole (QqQ)-mass spectrometry (MS). A total of 317 lipid species were successfully quantified in the myometrial tissues from women with (n = 38) or without (n = 65) adenomyosis who underwent hysterectomy at Peking Union Medical College Hospital (Bejing, China). Up to 83 lipid species showed significant alternations in content between the two groups. These lipid aberrations involved multiple metabolic pathways, and emphasized inflammation, cell migration, and immune dysregulation upon adenomyosis. Moreover, receiver operating characteristic (ROC) curve analysis found that the combination of five lipid species could accurately distinguished the myometrial samples from women with and without adenomyosis with an area under the curve (AUC) of 0.906. Desorption electrospray ionization MS imaging (MSI) further underscored the heterogeneous distributions of these lipid markers in the adenomyosis lesion and adjacent myometrial tissue. Collectively, these results extremely improved our understanding on the molecular basis of adenomyosis, and could shed light on developing potential biomarkers and new therapeutic directions for adenomyosis.