Objective To explore an artificial intelligence (AI)-based method for automated hand hygiene monitoring and to compare the effectiveness of three algorithms (UniFormerV2, TDN, C3D) in recognizing hand hygiene steps in surgical settings, thereby aiding hospital infection control. Methods From April to October 2024, we non-invasively collected 641 video recordings of healthcare staff performing hand hygiene at four-bay scrub sinks in two tertiary hospitals using overhead HD cameras. The dataset was annotated by five trained experts for model training and validation. Results Following training on 385 samples, internal validation (n=119) showed the C3D model achieved 81% accuracy, 87% recall, and an 83% F1-score. The TDN model achieved 93%, 91%, and 92% for the same metrics. The UniFormerV2 model outperformed both, with an accuracy, recall, and F1-score of 93%—an improvement of over 10 percentage points compared to traditional CNNs (TDN, C3D). It also achieved an 84% accuracy in external validation, demonstrating strong generalization. Conclusion The UniFormerV2 model is more accurate than CNN-based models for hand hygiene step recognition and shows robust performance in external validation. It presents a viable tool for healthcare facilities to enhance hand hygiene management, ultimately improving medical quality and patient safety.

BACKGROUND:In recent years,improving the health of skeletal muscles through exercise has become an important research concern for scholars.Appropriate exercise has a positive effect on skeletal muscles.Among them,how to activate the sphingosine kinase1(SphK1)/sphingosine-1-phase(S1P)/sphingosine-1-phase receptor2(S1PR2)signaling pathway during exercise so as to improve the health of skeletal muscles is receiving attention from researchers. OBJECTIVE:To investigate how exercise improves the health of skeletal muscles through the SphK1/S1P/S1PR2 signaling pathway,and to explore new methods for treating related muscle diseases in order to improve human skeletal muscle health. METHODS:The first author searched for relevant literature from the establishment of the database to the present in the Web of Science,PubMed,CNKI,WanFang,and VIP databases.The search terms were"signaling pathway,SphK1,S1P,S1PR2,skeletal muscle,satellite cell,myogenesis,exercise"in Chinese and English.Finally,69 articles were included for review and analysis. RESULTS AND CONCLUSION:The SphK1/S1P/S1PR2 signaling pathway is a complex regulatory network that triggers downstream signal transduction processes by SphK1 to catalyze the interaction between S1P and receptors such as S1PR2,thereby regulating multiple biological functions of cells,tissues,organs,and systems.The SphK1/S1P/S1PR2 signaling pathway can regulate satellite cell proliferation and myoblast differentiation,improving myogenesis.The physiological basis of the SphK1/S1P/S1PR2 signaling pathway and the potential impact of exercise on it were analyzed through literature research.Acute aerobic exercise can increase the expression of SphK1 in skeletal muscle.Both human and animal studies have confirmed that acute and long-term exercise can increase the expression of S1P in skeletal muscle.In addition,studies have shown that long-term resistance exercise can increase the expression of S1PR2 in skeletal muscle.Some experimental results indicate that acute and long-term exercise have no significant effect on muscle or blood S1P levels,and the reason for different results may be due to different research subjects,methods,intensities,and frequencies selected,while the specific mechanism is not yet clear.Research suggests that exercise can promote the expression of the SphK1/S1P/S1PR2 signaling pathway in skeletal muscle and regulate downstream related signaling pathways.Research on this signaling pathway may provide new strategies and methods for the treatment of skeletal muscle diseases,thereby improving skeletal muscle health.In the future,we should deepen the research on the association between SphK1/S1P/S1PR2 signaling pathway and skeletal muscle health,further reveal its regulatory relationship with satellite cells and myoblasts as well as its interactions with the upstream and downstream pathways,explore its clinical application value,take into account the changes of this pathway when formulating the rehabilitation program,explore the specific mechanisms by which different types of exercise affect the SphK1/S1P/S1PR2 signaling pathway in skeletal muscles,and use the SphK1/S1P/S1PR2 signaling pathway as a potential therapeutic target for diseases.Further development and application of human muscle models should be developed to improve research depth and accuracy.

OBJECTIVE To construct and evaluate nomogram prediction model for refractory chemotherapy-induced nausea and vomiting （CINV）. METHODS The data of malignant tumor patients who received chemotherapy at the Third People’s Hospital of Zhengzhou from January 2017 to December 2023 were collected. These patients were categorized into the occurrence group and the non-occurrence group according to the occurrence of refractory CINV. Multivariate Logistic regression analysis was employed to screen predictive factors for refractory CINV and constructing a nomogram prediction model. Model performance was assessed via receiver operating characteristic curve analysis. Model calibration was evaluated using Bootstrap resampling. Decision curve analysis （DCA） was used to determine the clinical net benefit of three strategies under different risk thresholds. Clinical impact curves were utilized to assess the clinical value of the model at different risk thresholds. Shapley additive explanations （SHAP） analysis was performed to evaluate individual factor contributions to the predictive model. RESULTS A total of 388 patients were included， with 219 experiencing refractory CINV. Multivariate Logistic regression identified 11 predictive factors for refractory CINV， including gastrointestinal disease history， anticipated nausea and vomiting， chemotherapy-induced emetic risk classification， and electrolyte levels， etc. The model’s area under the curve was 0.80 [95% confidence interval （0.76， 0.84）]， with a mean error of 0.036. DCA demonstrated the prediction model had higher clinical net benefit when the risk threshold was between 0.05 and 0.85. SHAP analysis revealed the top three predictive factors as gastrointestinal disease history （0.924）， chemotherapy- induced emetic risk classification （0.866）， and electrolyte levels （0.581）. CONCLUSIONS Eleven factors， including gastrointestinal disease history， anticipated nausea and vomiting， chemotherapy-induced emetic risk classification， and electrolyte levels， are identified as predictors of refractory CINV. The model based on these factors has good predictive ability， which can be used to predict the risk of refractory CINV.

Background: Gestational diabetes mellitus (GDM) is a metabolic disorder posing significant risks to maternal and infant health, with a lack of effective early screening markers. Therefore, identifying early screening biomarkers for GDM with higher sensitivity and specificity is urgently needed. Methods: High-throughput sequencing was employed to screen for key circular RNAs (circRNAs), which were then evaluated using reverse transcription quantitative polymerase chain reaction. Logistic regression analysis was conducted to examine the relationship between clinical characteristics, circRNA expression, and adverse pregnancy outcomes. The diagnostic accuracy of circRNAs for early and mid-pregnancy GDM was assessed using receiver operating characteristic curves. Pearson correlation analysis was utilized to explore the relationship between circRNA levels and oral glucose tolerance test results. A predictive model for early GDM was established using logistic regression. Results: Significant alterations in circRNA expression profiles were detected in GDM patients, with hsa_circ_0031560 and hsa_ circ_0000793 notably upregulated during the first and second trimesters. These circRNAs were associated with adverse pregnancy outcomes and effectively differentiated GDM patients, with second trimester cohorts achieving an area under the curve (AUC) of 0.836. In first trimester cohorts, these circRNAs identified potential GDM patients with AUCs of 0.832 and 0.765, respectively. The early GDM prediction model achieved an AUC of 0.904, validated in two independent cohorts. Conclusion Hsa_circ_0031560, hsa_circ_0000793, and the developed model serve as biomarkers for early prediction or midterm diagnosis of GDM, offering clinical tools for early GDM screening.

Background: Gestational diabetes mellitus (GDM) is a metabolic disorder posing significant risks to maternal and infant health, with a lack of effective early screening markers. Therefore, identifying early screening biomarkers for GDM with higher sensitivity and specificity is urgently needed. Methods: High-throughput sequencing was employed to screen for key circular RNAs (circRNAs), which were then evaluated using reverse transcription quantitative polymerase chain reaction. Logistic regression analysis was conducted to examine the relationship between clinical characteristics, circRNA expression, and adverse pregnancy outcomes. The diagnostic accuracy of circRNAs for early and mid-pregnancy GDM was assessed using receiver operating characteristic curves. Pearson correlation analysis was utilized to explore the relationship between circRNA levels and oral glucose tolerance test results. A predictive model for early GDM was established using logistic regression. Results: Significant alterations in circRNA expression profiles were detected in GDM patients, with hsa_circ_0031560 and hsa_ circ_0000793 notably upregulated during the first and second trimesters. These circRNAs were associated with adverse pregnancy outcomes and effectively differentiated GDM patients, with second trimester cohorts achieving an area under the curve (AUC) of 0.836. In first trimester cohorts, these circRNAs identified potential GDM patients with AUCs of 0.832 and 0.765, respectively. The early GDM prediction model achieved an AUC of 0.904, validated in two independent cohorts. Conclusion Hsa_circ_0031560, hsa_circ_0000793, and the developed model serve as biomarkers for early prediction or midterm diagnosis of GDM, offering clinical tools for early GDM screening.

Background/Aims: Reflux symptoms frequently present in patients diagnosed with functional dyspepsia (FD). This investigation sought to elucidate the contribution of gastroesophageal reflux in the overlap relationship. Methods: Consecutive patients presenting with reflux symptoms and/or FD symptoms were prospectively included. Comprehensive assessments, including symptoms evaluation, endoscopy, esophageal functional examinations (high-resolution manometry and reflux monitoring), and proton pump inhibitor (PPI) treatment efficacy evaluation, were conducted in these patients. Results: The study enrolled 315 patients, 43.2% of which had concurrent FD symptoms and overlapping reflux symptoms. Notably, a mere 28.7% of patients in the overlap symptoms group had objective gastroesophageal reflux disease evidences (the grade of esophagitis≥ B or the acid exposure time ≥ 4.2%). Functional heartburn was demonstrated to be the main cause of overlapping reflux symptoms(55.1%). Reflux parameters analysis revealed that the reflux burden in the overlap symptoms group paralleled that of the FD symptoms group, with both registering lower levels than the reflux symptoms group (P < 0.05). Furthermore, PPI response rates were notably diminished in the overlap symptoms group (P < 0.001), even for those with objective gastroesophageal reflux disease evidences. Conclusions The study illuminated that overlapping reflux symptoms in FD was common. Strikingly, these symptoms primarily diverged from reflux etiology and exhibited suboptimal responses to PPI intervention. These findings challenge prevailing paradigms and accentuate the imperative for nuanced therapeutic approaches tailored to the distinctive characteristics of overlapping reflux symptoms in the context of FD.

This paper primarily investigated the protective effects and potential mechanisms of total saponins from Ginseng Radix et Rhizoma and Notoginseng Radix et Rhizoma in alleviating isoprenaline(ISO)-induced hypertrophy and damage in H9c2 cardiomyocytes. Initially, H9c2 cardiomyocytes were used as the research subject to analyze the effects of ISO at different concentrations on cell hypertrophy and damage. On this basis, the H9c2 cardiomyocytes were divided into blank, model, and high-dose(200 μg·mL~(-1)), medium-dose(100 μg·mL~(-1)), and low-dose(50 μg·mL~(-1)) groups of total saponins from Ginseng Radix et Rhizoma and Notoginseng Radix et Rhizoma. Cell hypertrophy and damage models were induced by treating cells with 400 μmol·L~(-1) ISO for 24 hours. The Incucyte live-cell analysis system was utilized to observe the status, size changes, and confluence of the cells in each group. Cell viability was detected by using the CCK-8 assay. Western blot analysis was employed to detect the expression of Ras-associated protein 7A(RAB7A), sequestosome 1(SQSTM1/p62), autophagy-related protein Beclin1, and microtubule-associated protein 1 light chain 3(LC3). Immunofluorescence was used to detect the expression level of the autophagy marker Beclin1 in H9c2 cells. The results demonstrated that compared with the blank group, the model group showed a significant reduction in cell viability(P<0.01) and a marked increase in cell hypertrophy, with an average cell length growth of 13.53%. Compared with the model group, the high-dose, medium-dose, and low-dose groups of total saponins from Ginseng Radix et Rhizoma and Notoginseng Radix et Rhizoma exhibited reduced hypertrophy, with respective growths of 6.89%, 8.30%, and 8.49% and a significant decrease in growth rates(P<0.01). Cell viability in the high-dose of total saponins from Ginseng Radix et Rhizoma and Notoginseng Radix et Rhizoma was also significantly increased(P<0.01). Western blot and immunofluorescence results indicated that compared with the blank group, the model group showed changes in Beclin1, RAB7A, and p62 expression, as well as the LC3Ⅱ/LC3Ⅰ ratio, although most changes were not statistically significant. In the groups treated with total saponins from Ginseng Radix et Rhizoma and Notoginseng Radix et Rhizoma, the expression of autophagy-related proteins Beclin1 and RAB7A and the LC3Ⅱ/LC3Ⅰ ratio were significantly increased(P<0.05), while p62 expression significantly decreased(P<0.05). These findings collectively suggested that pretreatment of cells with total saponins from Ginseng Radix et Rhizoma and Notoginseng Radix et Rhizoma significantly enhanced autophagy activity in cells. In summary, total saponins from Ginseng Radix et Rhizoma and Notoginseng Radix et Rhizoma inhibit ISO-induced hypertrophy and damage in H9c2 cells by promoting autophagy, demonstrating potential cardioprotective effects and providing new insights and scientific evidence for their preventive and therapeutic use in cardiovascular diseases.
Autophagy/drug effects* ; Saponins/pharmacology* ; Panax notoginseng/chemistry* ; Panax/chemistry* ; Animals ; Rats ; Cell Line ; Drugs, Chinese Herbal/pharmacology* ; Rhizome/chemistry* ; Isoproterenol/adverse effects* ; Myocytes, Cardiac/cytology* ; Hypertrophy/drug therapy*

Continuous manufacturing, as an innovative pharmaceutical production model, offers advantages such as high production efficiency and ease of control compared to traditional batch production, aligning with the future trend of drug production moving toward greater efficiency and intelligence. However, the development of continuous manufacturing technology in wet granulation has been slow. On one hand, this is closely related to its high technical complexity, substantial equipment investment costs, and stringent process control requirements. On the other hand, the long-term use of the traditional batch production model has created strong path dependence, and the lack of mature standardized processes further increases the difficulty of technological transformation. To promote the deep integration of wet granulation technology with continuous manufacturing, this review systematically outlines the current application of wet granulation in continuous manufacturing. It focuses on the development of key technologies such as online detection, process modeling, and process scale-up, with the aim of providing a reference for process innovation and application in wet granulation.
Drug Compounding/instrumentation* ; Technology, Pharmaceutical/methods* ; Drugs, Chinese Herbal/chemistry* ; Models, Theoretical