Background Prehospital emergency medical personnel (PEMP) are exposed to long-term high-pressure work, which can exacerbate psychological distress and impair job satisfaction and sleep quality. However, in-depth research on the interactions among these factors is lacking. Objective To assess the status of psychological distress, job satisfaction, and sleep quality of PEMP in Guangzhou and to explore the mediating role of sleep quality in the relationship between psychological distress and job satisfaction. Methods From February to May 2025, 1085 PEMP from "120" emergency network hospitals in Guangzhou were selected using convenience sampling. Data were collected via the General Information Questionnaire, Kessler Psychological Distress Scale, Minnesota Satisfaction Questionnaire, and Pittsburgh Sleep Quality Index. Statistical analyses were performed using SPSS 25.0, and The mediation model of sleep quality in linking psychological distress and job satisfaction was constructed using AMOS 28.0. The bias-corrected Bootstrap method was employed to assessed the significance of the mediating effect. Results A total of 1063 valid responses were received (97.97% valid response rate). The mean scores were: psychological distress (27.99±10.75), job satisfaction (69.45±15.84), and sleep quality (9.82±4.47). Significant differences in the three scores were found across gender, age, monthly night shift frequency, and hospital grade (P<0.05). Higher job satisfaction was linked to lower psychological distress and better sleep quality and its dimensions, while psychological distress directly correlated with poorer sleep quality (P<0.01). Sleep quality partially mediated the relationship between psychological distress and job satisfaction, with a mediating effect of −0.195, accounting for 43.62% of the total effect. Conclusion The participants report moderate psychological distress, moderate-to-high job satisfaction, and poor sleep quality. Psychological distress directly affects job satisfaction and indirectly through its impact on sleep quality. Interventions aimed at improving sleep health and mental health are essential to improve personnel well-being and work efficiency.

Background Prehospital emergency medical personnel (PEMP) are exposed to long-term high-pressure work, which can exacerbate psychological distress and impair job satisfaction and sleep quality. However, in-depth research on the interactions among these factors is lacking. Objective To assess the status of psychological distress, job satisfaction, and sleep quality of PEMP in Guangzhou and to explore the mediating role of sleep quality in the relationship between psychological distress and job satisfaction. Methods From February to May 2025, 1085 PEMP from "120" emergency network hospitals in Guangzhou were selected using convenience sampling. Data were collected via the General Information Questionnaire, Kessler Psychological Distress Scale, Minnesota Satisfaction Questionnaire, and Pittsburgh Sleep Quality Index. Statistical analyses were performed using SPSS 25.0, and The mediation model of sleep quality in linking psychological distress and job satisfaction was constructed using AMOS 28.0. The bias-corrected Bootstrap method was employed to assessed the significance of the mediating effect. Results A total of 1063 valid responses were received (97.97% valid response rate). The mean scores were: psychological distress (27.99±10.75), job satisfaction (69.45±15.84), and sleep quality (9.82±4.47). Significant differences in the three scores were found across gender, age, monthly night shift frequency, and hospital grade (P<0.05). Higher job satisfaction was linked to lower psychological distress and better sleep quality and its dimensions, while psychological distress directly correlated with poorer sleep quality (P<0.01). Sleep quality partially mediated the relationship between psychological distress and job satisfaction, with a mediating effect of −0.195, accounting for 43.62% of the total effect. Conclusion The participants report moderate psychological distress, moderate-to-high job satisfaction, and poor sleep quality. Psychological distress directly affects job satisfaction and indirectly through its impact on sleep quality. Interventions aimed at improving sleep health and mental health are essential to improve personnel well-being and work efficiency.

Single-cell analysis of phenotypic plasticity could improve the development of more effective therapeutics. Still, the development of tools to measure single-cell heterogeneity has lagged due to difficulties in manipulating and culturing single cells. Here, we describe a single-cell culture and phenotyping platform that employs a starburst microfluidic network and automatic liquid handling system to capture single cells for long-term culture and multi-dimensional analysis and quantify their clonal properties via their surface biomarker and secreted cytokine/growth factor profiles. Studies performed on this platform found that cells derived from single-cell cultures maintained phenotypic equilibria similar to their parental populations. Single-cell cultures exposed to chemotherapeutic drugs stochastically disrupted this balance to favor stem-like cells. They had enhanced expression of mRNAs and secreted factors associated with cell signaling, survival, and differentiation. This single-cell analysis approach can be extended to analyze more complex phenotypes and screen responses to therapeutic targets.

Objective To evaluate the early efficacy and safety of the regimens containing delamanid and linezolid in the treatment of rifampicin resistant tuberculosis(RR-TB).Methods A total of 47 patients diagnosed with RR-TB at Public Health Clinical Center of Chengdu from August 2020 to December 2021 were enrolled,including 22 cases(46.8％)of multidrug-resistant tuberculosis(MDR-TB),8 cases(17.0％)of RR-TB,and 17 cases(36.2％)of pre-extensively drug-resistant tuberculosis(pre-XDR-TB).All patients were treated with a regimen based on delamanid and linezolid.The efficacy and safety were evaluated at 24 weeks of treatment.Results Among the 47 patients,46(97.9％)completed 24 weeks of treatment and 1(2.1％)was lost to follow-up.At 24 weeks,the sputum culture conversion rate was 100％in the 43 patients with positive baseline sputum culture.The median conversion time was 2(2,8)weeks.Imaging examination showed absorption in 46 patients(97.9％).Overall,40 patients(85.1％)experienced varying degrees of adverse events(AEs)within 24 weeks.Eleven patients(23.4％)experienced AEs possibly related to delamanid,mainly including QTcF interval prolongation(12.8％),gastrointestinal reactions(8.5％),dizziness(2.1％),headache(2.1％),and allergy(2.1％).Six patients permanently discontinued delamanid due to AEs including gastrointestinal reactions(6.4％),prolonged QTcF interval(2.1％),severe dizziness(2.1％),and drug allergy(2.1％).Patients with low baseline CD4+T lymphocyte counts(OR=0.991,95％CI:0.984-0.999)were more likely to experience delamanid-related AEs.Thirty patients(63.8％)experienced AEs possibly related to linezolid,including myelosuppression(55.3％),peripheral neuropathy(6.4％),optic neuritis occurred(2.1％),and allergy(2.1％).Three patients(6.4％)discontinued linezolid permanently due to severe anemia,peripheral neuropathy,and allergy.Conclusions The treatment regimens containing delamanid and linezolid for RR-TB showed a high sputum culture conversion rate and good tolerance at 24 weeks.Attention should be paid to gastrointestinal reactions and cellular immunity during treatment.

Objective To evaluate the early efficacy and safety of the regimens containing delamanid and linezolid in the treatment of rifampicin resistant tuberculosis(RR-TB).Methods A total of 47 patients diagnosed with RR-TB at Public Health Clinical Center of Chengdu from August 2020 to December 2021 were enrolled,including 22 cases(46.8％)of multidrug-resistant tuberculosis(MDR-TB),8 cases(17.0％)of RR-TB,and 17 cases(36.2％)of pre-extensively drug-resistant tuberculosis(pre-XDR-TB).All patients were treated with a regimen based on delamanid and linezolid.The efficacy and safety were evaluated at 24 weeks of treatment.Results Among the 47 patients,46(97.9％)completed 24 weeks of treatment and 1(2.1％)was lost to follow-up.At 24 weeks,the sputum culture conversion rate was 100％in the 43 patients with positive baseline sputum culture.The median conversion time was 2(2,8)weeks.Imaging examination showed absorption in 46 patients(97.9％).Overall,40 patients(85.1％)experienced varying degrees of adverse events(AEs)within 24 weeks.Eleven patients(23.4％)experienced AEs possibly related to delamanid,mainly including QTcF interval prolongation(12.8％),gastrointestinal reactions(8.5％),dizziness(2.1％),headache(2.1％),and allergy(2.1％).Six patients permanently discontinued delamanid due to AEs including gastrointestinal reactions(6.4％),prolonged QTcF interval(2.1％),severe dizziness(2.1％),and drug allergy(2.1％).Patients with low baseline CD4+T lymphocyte counts(OR=0.991,95％CI:0.984-0.999)were more likely to experience delamanid-related AEs.Thirty patients(63.8％)experienced AEs possibly related to linezolid,including myelosuppression(55.3％),peripheral neuropathy(6.4％),optic neuritis occurred(2.1％),and allergy(2.1％).Three patients(6.4％)discontinued linezolid permanently due to severe anemia,peripheral neuropathy,and allergy.Conclusions The treatment regimens containing delamanid and linezolid for RR-TB showed a high sputum culture conversion rate and good tolerance at 24 weeks.Attention should be paid to gastrointestinal reactions and cellular immunity during treatment.

Objective To explore the association between the ratio of red blood cell distribution width to albumin level(RAR)and the risk of non-valvular atrial fibrillation(NVAF)in patients with hyperuricemia.Methods A total of 8 277 patients with hyperuricemia who underwent physi-cal examinations at the Physical Examination Center of Northern Jiangsu People's Hospital from January 2021 to June 2024 were enrolled.From them,185 patients with AF were assigned into a case group,and 740 patients without AF were into a control group in a ratio of 1∶4 with propen-sity score matching(PSM).Logistic regression analysis,restricted cubic spline analysis,and sub-group analysis were employed to investigate the association between RAR and the risk of NVAF in hyperuricemic patients.Results The case group had significantly larger ratio of smoking,high-er levels of red blood cell distribution width,total bilirubin,hematocrit,and RAR index,but lower albumin,low-density lipoprotein cholesterol(LDL-C)and triglyceride(TG)levels,and smaller ra-tio of fatty liver than the control group(P＜0.01).Multivariate logistic regression analysis showed that the patients at Q2,Q3,and Q4 quartiles of RAR index have higher risk for AF than those at Q1 quartile(OR=2.843,OR=4.263,OR=7.801,P＜0.01).The effect of RAR index was significant when below the breakpoint of 2.85(OR=1.492,95％CI:1.151-1.993,P=0.004).Subgroup analysis indicated significant interactions between RAR index and age as well as smok-ing(P interaction＜0.05).The area under curve value of RAR index in predicting NVAF occurrence in male hyperuricemic patients was 0.679(95％CI:0.632-0.725).Conclusion In patients with hyperuricemia,a higher RAR index is associated with an increased risk of NVAF.RAR index has guiding significance for diagnosing male hyperuricemic patients complicated with AF.

Objective To explore the association between the ratio of red blood cell distribution width to albumin level(RAR)and the risk of non-valvular atrial fibrillation(NVAF)in patients with hyperuricemia.Methods A total of 8 277 patients with hyperuricemia who underwent physi-cal examinations at the Physical Examination Center of Northern Jiangsu People's Hospital from January 2021 to June 2024 were enrolled.From them,185 patients with AF were assigned into a case group,and 740 patients without AF were into a control group in a ratio of 1∶4 with propen-sity score matching(PSM).Logistic regression analysis,restricted cubic spline analysis,and sub-group analysis were employed to investigate the association between RAR and the risk of NVAF in hyperuricemic patients.Results The case group had significantly larger ratio of smoking,high-er levels of red blood cell distribution width,total bilirubin,hematocrit,and RAR index,but lower albumin,low-density lipoprotein cholesterol(LDL-C)and triglyceride(TG)levels,and smaller ra-tio of fatty liver than the control group(P＜0.01).Multivariate logistic regression analysis showed that the patients at Q2,Q3,and Q4 quartiles of RAR index have higher risk for AF than those at Q1 quartile(OR=2.843,OR=4.263,OR=7.801,P＜0.01).The effect of RAR index was significant when below the breakpoint of 2.85(OR=1.492,95％CI:1.151-1.993,P=0.004).Subgroup analysis indicated significant interactions between RAR index and age as well as smok-ing(P interaction＜0.05).The area under curve value of RAR index in predicting NVAF occurrence in male hyperuricemic patients was 0.679(95％CI:0.632-0.725).Conclusion In patients with hyperuricemia,a higher RAR index is associated with an increased risk of NVAF.RAR index has guiding significance for diagnosing male hyperuricemic patients complicated with AF.

Objective:To construct a machine-learning model for predicting the progression of pancreatic cystic lesions (PCLs) based on clinical and CT features, and to evaluate its predictive performance in internal/external testing cohorts.Methods:Baseline clinical and radiological data of 200 PCLs in 177 patients undergoing abdominal thin slice enhanced CT examination at Peking Union Medical College Hospital from July 2014 to December 2022 were retrospectively collected. PCLs were divided into progressive and non-progressive groups according to whether the signs indicated for surgery by the guidelines of the European study group on PCLs were present during three-year follow-up. 200 PCLs were randomly divided into training (150 PCLs) and internal testing cohorts (50 PCLs) at the ratio of 1∶3. 15 PCLs in 14 patients at Jinling Affiliated Hospital of Medical School of Nanjing University from October 2011 to May 2020 were enrolled as external testing cohort. The clinical and CT radiological features were recorded. Multiple feature selection methods and machine-learning models were implemented and combined to identify the optimal machine-learning model based on the 10-fold cross-validation method. Receiver operating characteristics (ROC) curve was drawn and area under curve (AUC) was calculated. The model with the highest AUC was determined as the optimal model. The optimal model's predictive performance was evaluated on testing cohort by calculating AUC, sensitivity, specificity and accuracy. Permutation importance was used to assess the importance of optimal model features. Calibration curves of the optimal model were established to evaluate the model's clinical applicability by Hosmer-Lemeshow test.Results:In training and internal testing cohorts, the progressive and non-progressive groups were significantly different on history of pancreatitis, lesions size, main pancreatic duct diameter and dilation, thick cyst wall, presence of septation and thick septation (all P value <0.05) In internal testing cohort, the two groups were significantly different on gender, lesion calcification and pancreatic atrophy (all P value <0.05). In external testing cohort, the two groups were significantly different on lesions size and pancreatic duct dilation (both P<0.05). The support vector machine (SVM) model based on five features selected by F test (lesion size, thick cyst wall, history of pancreatitis, main pancreatic duct diameter and dilation) achieved the highest AUC of 0.899 during cross-validation. SVM model for predicting the progression of PCLs demonstrated an AUC of 0.909, sensitivity of 82.4%, specificity of 72.7%, and accuracy of 76.0% in the internal testing cohort, and 0.944, 100%, 77.8%, and 86.7% in the external testing cohort. Calibration curved showed that the predicted probability by the model was comparable to the real progression of PCLs. Hosmer-Lemeshow goodness-of-fit test affirmed the model's consistency with actual PCLs progression in testing cohorts. Conclusions:The SVM model based on clinical and CT features can help doctors predict the PCLs progression within three-year follow-up, thus achieving efficient patient management and rational allocation of medical resource.

Keloids are benign skin tumors resulting from the excessive proliferation of connective tissue in wound skin. Precise prediction of keloid risk in trauma patients and timely early diagnosis are of paramount importance for in-depth keloid management and control of its progression. This study analyzed four keloid datasets in the high-throughput gene expression omnibus (GEO) database, identified diagnostic markers for keloids, and established a nomogram prediction model. Initially, 37 core protein-encoding genes were selected through weighted gene co-expression network analysis (WGCNA), differential expression analysis, and the centrality algorithm of the protein-protein interaction network. Subsequently, two machine learning algorithms including the least absolute shrinkage and selection operator (LASSO) and the support vector machine-recursive feature elimination (SVM-RFE) were used to further screen out four diagnostic markers with the highest predictive power for keloids, which included hepatocyte growth factor (HGF), syndecan-4 (SDC4), ectonucleotide pyrophosphatase/phosphodiesterase 2 (ENPP2), and Rho family guanosine triphophatase 3 (RND3). Potential biological pathways involved were explored through gene set enrichment analysis (GSEA) of single-gene. Finally, univariate and multivariate logistic regression analyses of diagnostic markers were performed, and a nomogram prediction model was constructed. Internal and external validations revealed that the calibration curve of this model closely approximates the ideal curve, the decision curve is superior to other strategies, and the area under the receiver operating characteristic curve is higher than the control model (with optimal cutoff value of 0.588). This indicates that the model possesses high calibration, clinical benefit rate, and predictive power, and is promising to provide effective early means for clinical diagnosis.
Humans ; Keloid/genetics* ; Nomograms ; Algorithms ; Calibration ; Machine Learning

Stimulator of interferon genes (STING) is a cytosolic DNA sensor which is regarded as a potential target for antitumor immunotherapy. However, clinical trials of STING agonists display limited anti-tumor effects and dose-dependent side-effects like inflammatory damage and cell toxicity. Here, we showed that tetrahedral DNA nanostructures (TDNs) actively enter macrophages to promote STING activation and M1 polarization in a size-dependent manner, and synergized with Mn²⁺ to enhance the expressions of IFN-β and iNOS, as well as the co-stimulatory molecules for antigen presentation. Moreover, to reduce the cytotoxicity of Mn²⁺, we constructed a TDN-MnO₂ complex and found that it displayed a much higher efficacy than TDN plus Mn²⁺ to initiate macrophage activation and anti-tumor response both in vitro and in vivo. Together, our studies explored a novel immune activation effect of TDN in cancer therapy and its synergistic therapeutic outcomes with MnO₂. These findings provide new therapeutic opportunities for cancer therapy.