Objective:To explore the relationship between depressive symptoms and stressors among post-graduates and the role of coping styles and psychological suzhi between them.Methods:A total of 775 postgradu-ates were recruited.They were assessed with the Center for Epidemiological Studies Depression Scale(CES-D),Psychological Stressors Scale of Postgraduates(PSSP),Simplified Coping Style Questionnaire(SCSQ),and Col-lege Students Psychological Suzhi Brief Mental Health Version(CSPS-B-MH).Results:The detection rate of de-pression among postgraduates was 52.0％.Postgraduate stressors were positively associated with depression(β=0.47).Coping styles played a partial mediating role in the relationship between stressors and depression in postgrad-uates,with the mediation effect accounting for 24.76％of the total effect.Psychological suzhi was shown to moder-ate the effect of stressors on depression(β=-0.07)and positive coping on depression(β=-0.05).Conclusion:Postgraduate stressors could affect depression through the mediating role of coping styles and the moderating role of psychological suzhi.

Objective To develop and validate a nomogram model that integrates systemic inflammatory markers to predict the likelihood of pelvic lymph node metastasis(PLNM)in prostate cancer patients prior to surgery.Methods This study retrospectively analyzed the clinical data and preoperative inflammatory markers—including neutrophil-to-lymphocyte ratio(NLR),platelet-to-lymphocyte ratio(PLR),systemic immune-inflammation index(SII),and monocyte-to-lymphocyte ratio(MLR)—of patients diagnosed with prostate cancer.Univariate and multi-variate logistic regression analyses were conducted to identify markers that were significantly associated with PLNM.Based on the results of the multivariate analysis,a nomogram was developed and its predictive accuracy was assessed using receiver operating characteristic curves(ROC)and calibration plots.Results Among the 334 enrolled patients with prostate cancer,107 were identified with PLNM.Univariate analysis revealed statistically significant differences in free prostate-specific antigen(fPSA),Gleason score,NLR,PLR,MLR,and SII between the PLNM and non-pelvic lymph node metastasis(NPLNM)groups(P<0.05).Multivariate analysis confirmed that fPSA,Gleason score,and SII were independent predictors of PLNM(P<0.05).A nomogram incorporating these predic-tors exhibited strong discriminative ability,with an area under the ROC curve(AUC)of 0.79(95%CI:0.73～0.84).Calibration analysis further demonstrated good consistency between the predicted and observed probabilities of PLNM.Conclusions This study successfully developed a nomogram model based on systemic inflammatory markers for preoperative prediction of pelvic lymph node metastasis in prostate cancer.Owing to its user-friendly design and high predictive accuracy,this tool may serve as a valuable complementary method to conventional imaging techniques,thereby supporting personalized treatment decision-making.

Objective:To explore the incidence, clinical features, genetic variant characteristics and prognosis of Glutaric acidemia type I (GA1) among neonates from Henan Province.Methods:A total of 814 625 neonates undergoing screening for inherited metabolic diseases by tandem mass spectrometry (MS/MS) at the Third Affiliated Hospital of Zhengzhou University from January 2016 to December 2022 were selected as the study subjects. A retrospective method was adopted to collect the clinical data of the patients. Whole exome sequencing was carried out to detect GCDH gene variants in individuals with positive results by GA1 newborn screening, and Sanger sequencing was used to verify the candidate variants. Based on the guidelines from the American College of Medical Genetics and Genomics (ACMG), the pathogenicity of candidate variants was rated. This study was approved by the Medical Ethics Committee of the Hospital (Approval Number: 2019 Medical Ethics Review No. 67). Results:Eight cases of GA1 were diagnosed among the 814 625 neonates. Blood glutaryl carnitine (C5DC) and urine glutaric acid (GA) levels of the 8 children were higher than the normal reference values. In total 12 variants were detected, all of which were missense variants. c. 1064G>A (p.Arg355His) was the most common one, accounting for 21.4% (3/14). Three GCDH gene variants, including 1297G>C (p.Ala433Pro), c. 467G>A (p.Gly156Asp) and c. 1125T>G (p.Cys375Trp), were previously unreported. REVEL software analysis predicted that all of the three variants were harmful. 3D protein structure modeling indicated that the three variants may cause amino acid residue alterations, and c. 1297G>C (p.Ala433Pro) and c. 1125T>G (p.Cys375Trp) may result in increase in hydrogen bonds and may affect the function of GCDH protein. By December 2023, one of the eight children had deceased, and another child had severe clinical symptoms with poor prognosis. Six children had a good prognosis, of which two had mild motor development delay and four had normal development without clinical symptoms. Conclusion:The incidence of GA1 in newborns screened by MS/MS in Henan Province is 1/101 828, and the carrier rate of pathogenic GCDH variants is 1/160. The c. 1064G>A (p.Arg355His) may be the hotspot variant of the GCDH gene among children with GA1 in Henan. Discovery of the three novel variants has enriched the mutational spectrum of the GCDH gene and provide a basis for the early diagnosis, treatment, prognosis and genetic counseling of this disease.

Objective:To evaluate the differential expression of RNA in blood monocytes in patients with Juvenile idiopathic arthritis (JIA) treated with TNF antagonists (TNFi), and to explore the effect and mechanism of gene expression on the efficacy of JIA.Methods:A total of 29 children with JIA treated with methotrexate (MTX) and TNFi in Guangzhou Women and Children′s Medical Center of Guangzhou Medical University from April 2021 to November 2023 were enrolled. After 6 months, the children were divided into two groups according to the treatment effect, 13 cases in the ineffective group and 16 cases in the effective group, the peripheral blood of the children was collected, the blood mononuclear cells were isolated for transcriptome sequencing, the differentially expressed genes between the groups were analyzed, the signaling pathways and metabolic pathways related to the efficacy of TNFi were analyzed by GO and KEGG enrichment, and the mechanism related to the efficacy of TNFi was explored. This study was approved by Medical Ethics Committee of the Guangzhou Women and Children′s Medical Center of Guangzhou Medical University (Ethics No.: 2023-330B00).Results:There was a statistically significant difference in the gender and age distribution between the two groups of children ( P<0.05), while no statistically significant differences were observed in disease duration, rheumatoid antibody levels, or JIA subtypes ( P> 0.05). After sequencing data quality control and comparison of reference genomes, a total of 18 523 protein-coding genes were identified in all children′s samples. A total of 705 differentially expressed genes (DEGs) were identified between the effective group and the invalid group through differential analysis, of which 579 were up-regulated in the effective group and 126 in the inactive group. GO function and KEGG pathway enrichment analysis showed that DEG was significantly enriched in 55 GO entries and 32 KEGG metabolic pathways, which were mainly related to IL-1β; production and regulation, cytokine production and regulation, cytokine-cytokine receptor interaction, immune response regulation, and Toll-like receptor signaling pathway. Conclusion:DEG between the effective and ineffective groups of TNFi treatment may be involved in the biological processes such as cytokine production and regulation, cytokine-receptor interaction, and immune response regulation, which will be helpful to predict the efficacy and prognosis of TNFi treatment for JIA.

Objective:To understand the difficulties in the development of community-based integrated general and specialized medical care in Shanghai, and to provide a scientific basis for further proposing strategies to promote the development of integrated general and specialized medical care.Methods:A mixed-methods study was used in this study. In the first stage, a quantitative method was used. From August to December 2023, 30 community health centers (CHCs) were randomly selected from 239 CHCs in the city that provided integrated general specialist care. In each of these CHCs, a questionnaire was administered to a manager and a general practitioner involved in integrated care for specific diseases. The content of the questionnaire included general demographic information and questions related to the integration of general and specialized care, covering six aspects: community-specific disease diagnosis and treatment, examination items, drug configuration, patient sources, support from specialists, and referrals. In the second stage, a qualitative method was used. From January to February 2024, face-to-face semi-structured interviews were conducted with the managers and general practitioners of the CHCs who had completed the questionnaire survey in the previous stage, to further understand the reasons for the difficulties in integrating general and specialist care.Results:(1) Quantitative research: a total of 30 community health center managers and 30 general practitioners participated in the questionnaire survey. The survey found that the top four difficulties were: lack of technology for diagnosis and treatment of special diseases (49, 81.7%), shortage of clinical medical technical examination (36, 60.0%), and insufficient drug configuration (33, 55.0%) and few patients with special diseases in the community (33, 55.0%). (2) Qualitative research: 12 community health center managers and 10 general practitioners participated in the interviews. The interviews explained the difficulties identified in the research from different angles, such as "lack of support from higher-level medical institutions, lack of ancillary examinations and drugs, and a single form of cooperation between and lower-level medical institutions". At the same time, the interviewees mentioned the difficulty of "insufficient staff involved in community-based integrated care", which complemented the research.Conclusions:There are difficulties in many aspects of community-based comprehensive and specialized treatment, such as collaboration between hospitals and community health institutions, specialist and general practitioner resources, patient sources, specialized treatment-related examination items and drugs, which need to be solved in a variety of ways to further promote the development of community-based integration of general practice and specialty care.

Objective To investigate the incidence and types of patient-ventilator asynchrony(PVA)in mechanically ventilated patients within the intensive care unit(ICU),and to identify associated high-risk factors,thereby providing a basis for reducing PVA,enhancing mechanical ventilation efficiency,and refining ventilation strategies.Methods A prospective observational study was conducted among patients admitted to the general ICU of the Affiliated Hospital of Guizhou Medical University from October to December 2024 who were receiving mechanical ventilation.Inclusion criteria were as follows:age ≥18 years and mechanical ventilation duration ≥12 hours.Exclusion criteria included complete controlled mechanical ventilation,palliative care or do-not-resuscitate status,and lack of informed consent.Senior respiratory therapists performed daily bedside observations of ventilator waveforms for 10～15 minutes between 08:00 and 12:00.PVA was diagnosed based on pressure-time and flow-time waveforms,with the types of PVA being recorded.Demographic and clinical data,including age,sex,body mass index(BMI),primary diagnosis,comorbidities,APACHEⅡ score at ICU admission,blood gas analysis,ventila-tion mode and parameters,analgesia and sedation status,duration of mechanical ventilation,and length of ICU stay,were collected.The incidence and types of PVA during the observation period were analyzed.Univariate and multivariate logistic regression analyses were performed to identify high-risk factors for PVA.Clinical outcomes were compared between patients with and without PVA.Results A total of 105 patients and 453 episodes of assisted mechanical ventilation waveforms were analyzed.Among these,60.95％(64/105)experienced at least one episode of PVA.Of the 453 ventilation waveforms assessed,35.76％(162/453)demonstrated PVA.The types of PVA,ranked by incidence,were as follows:cycling mismatch(12.58％,57/453),double triggering(11.92％,54/453),ineffective triggering(9.49％,43/453),flow starvation(5.30％,24/453),and exhalation flow limitation(1.77％,8/453).The incidence of PVA varied significantly across different ventilation modes:45.7％in volume-assist/control ventilation(V-A/C),38.1％in pressure-assist/control ventilation(P-A/C),42.9％in synchronized intermittent mandatory ventilation(SIMV),and 16.7％in pressure support ventilation(PSV)(P<0.001).Multi-variate logistic regression analysis revealed that the mechanical ventilation mode[reference:PSV;V-A/C:OR=4.687,95％CI:2.140～10.263,P<0.001;P-A/C:OR=2.922,95％CI:1.489～5.734,P=0.002;SIMV:OR=4.682,95％CI:1.758～12.466,P=0.002]and actual respiratory rate(OR=1.07,95％CI:1.016～1.127,P=0.011)were significant high-risk factors for PVA.Patients with PVA had a significantly longer duration of mechanical ventilation[8.21(5.35,13.91)days vs.3.00(1.96,5.71)days,P<0.001]compared to those without PVA.Conclusions PVA is commonly observed in ICU patients receiving assisted invasive mechanical ventilation,with cycling mismatch,double triggering,and ineffective triggering being the most prevalent types.The incidence of PVA tends to be lower when using the PSV mode.Clinically,real-time monitoring of patient-ventilator synchrony via ventilator waveforms,along with the optimization of ventilator modes and parameters,should be employed to minimize the occurrence of PVA and enhance the efficiency of mechanical ventilation.

The clinical detection of paroxysmal atrial fibrillation(PAF)remains challenging due to its transient and stochastic characteristics,and existing dynamic mode decomposition methods have limitations in modal redundancy reduction and feature extraction when processing single-channel noisy electrocardiogram(ECG)signals.Therefore,a signal analysis method based on high-order dynamic mode decomposition is proposed.It captures high-order correlations within ECG signals through tensor decomposition techniques and decomposes complex signals into physically interpretable dynamic modes.A stability evaluation framework for signal subsystem is established based on modal interaction relationships.By incorporating quantitative indicators including proportion of modes reflecting system instability,modal distribution entropy,and eigenvalue spectrum divergence,a feature discrimination model for PAF is developed.Experimental validation using the MIT-BIH atrial fibrillation database reveals statistically significant differences(P<0.05)in stability-related features between PAF episodes and normal sinus rhythms.The classification model based on support vector machine achieves an average recognition accuracy of 96.15%.These results demonstrate that the proposed method can effectively analyze nonlinear dynamic characteristics in noisy single-lead ECG signals,thereby establishing a novel quantitative analytical framework for early detection and accurate diagnosis of PAF.

Objective:To translate the Birth Satisfaction Scale-Revised (BSS-R) into Chinese and assesses the psychometric properties of this tool.Methods:Following the Beaton cross-cultural adaptation guidelines, the Chinese version of BSS-R was formed through forward translation, back translation, expert consultation, and pre-testing. The present study was conducted in a sample of 347 women took part between 6-8 weeks postpartum, from the postpartum clinics of two tertiary hospitals in Sichuan province.Results:Totally 340 questionnaires were effectively collected with a majority of respondents aged 30-39 accounting for 64.7% of the total. The Chinese version of BSS-R comprises 10 items, which were classified into three domains as stress experienced during labour, women′s personal attributes, and quality of care provision. The Cronbach α coefficient was 0.745 for the total scale and ranged from 0.523 to 0.738 for sub-scales. The split-half reliability was 0.746 for the total scale, and ranged from 0.523 to 0.733 for sub-scales. Exploratory factor analysis revealed the presence of three components with eigen values greater than 1, explaining a total variance of 58.868%. The fit indices showed that the original correlated three factor model of Chinese version of BSS-R was adequate.Conclusions:The Chinese version of BSS-R can be considered a clear, easily understandable and convenient tool for assessing the women′s birth satisfaction in Chinese cultural context.

Objective To investigate the incidence and types of patient-ventilator asynchrony(PVA)in mechanically ventilated patients within the intensive care unit(ICU),and to identify associated high-risk factors,thereby providing a basis for reducing PVA,enhancing mechanical ventilation efficiency,and refining ventilation strategies.Methods A prospective observational study was conducted among patients admitted to the general ICU of the Affiliated Hospital of Guizhou Medical University from October to December 2024 who were receiving mechanical ventilation.Inclusion criteria were as follows:age ≥18 years and mechanical ventilation duration ≥12 hours.Exclusion criteria included complete controlled mechanical ventilation,palliative care or do-not-resuscitate status,and lack of informed consent.Senior respiratory therapists performed daily bedside observations of ventilator waveforms for 10～15 minutes between 08:00 and 12:00.PVA was diagnosed based on pressure-time and flow-time waveforms,with the types of PVA being recorded.Demographic and clinical data,including age,sex,body mass index(BMI),primary diagnosis,comorbidities,APACHEⅡ score at ICU admission,blood gas analysis,ventila-tion mode and parameters,analgesia and sedation status,duration of mechanical ventilation,and length of ICU stay,were collected.The incidence and types of PVA during the observation period were analyzed.Univariate and multivariate logistic regression analyses were performed to identify high-risk factors for PVA.Clinical outcomes were compared between patients with and without PVA.Results A total of 105 patients and 453 episodes of assisted mechanical ventilation waveforms were analyzed.Among these,60.95％(64/105)experienced at least one episode of PVA.Of the 453 ventilation waveforms assessed,35.76％(162/453)demonstrated PVA.The types of PVA,ranked by incidence,were as follows:cycling mismatch(12.58％,57/453),double triggering(11.92％,54/453),ineffective triggering(9.49％,43/453),flow starvation(5.30％,24/453),and exhalation flow limitation(1.77％,8/453).The incidence of PVA varied significantly across different ventilation modes:45.7％in volume-assist/control ventilation(V-A/C),38.1％in pressure-assist/control ventilation(P-A/C),42.9％in synchronized intermittent mandatory ventilation(SIMV),and 16.7％in pressure support ventilation(PSV)(P<0.001).Multi-variate logistic regression analysis revealed that the mechanical ventilation mode[reference:PSV;V-A/C:OR=4.687,95％CI:2.140～10.263,P<0.001;P-A/C:OR=2.922,95％CI:1.489～5.734,P=0.002;SIMV:OR=4.682,95％CI:1.758～12.466,P=0.002]and actual respiratory rate(OR=1.07,95％CI:1.016～1.127,P=0.011)were significant high-risk factors for PVA.Patients with PVA had a significantly longer duration of mechanical ventilation[8.21(5.35,13.91)days vs.3.00(1.96,5.71)days,P<0.001]compared to those without PVA.Conclusions PVA is commonly observed in ICU patients receiving assisted invasive mechanical ventilation,with cycling mismatch,double triggering,and ineffective triggering being the most prevalent types.The incidence of PVA tends to be lower when using the PSV mode.Clinically,real-time monitoring of patient-ventilator synchrony via ventilator waveforms,along with the optimization of ventilator modes and parameters,should be employed to minimize the occurrence of PVA and enhance the efficiency of mechanical ventilation.

Objective:To develop an artificial intelligence (AI)-based platelet review strategy to identify abnormal platelet histograms with no significant difference between initial impedance platelet count (PLT-I) and PLT-F results.Methods:This study included 5 119 routine blood analysis in Nanfang Hospital of Southern Medical University and its Ganzhou branch from July 2023 and March 2024. Specimens exhibiting abnormal platelet histograms and an initial platelet count >40×10?/L underwent review using the fluorescent platelet count (PLT-F) channel. Consistency of the results was defined as a difference between impedance platelet count (PLT-I) and PLT-F less than ±20% of the PLT-F results. A deep learning model was developed using platelet and red blood cell histogram data from a training set of 3 807 specimens. The model′s diagnostic performance was evaluated on an independent external validation set ( n=805) using receiver operating characteristic (ROC) curve analysis. Changes in the number of reviewed samples and sample turnaround time were analyzed to assess its clinical utility. Results:The deep learning model based on platelet and red blood cell histograms achieved an area under the ROC curve (AUC) of 0.854 in the training set. At a cutoff value of 0.1, the sensitivity was 0.954 and specificity was 0.358. The model could reduce review by 16.80% (190/1 131). In the validation set, the AUC was 0.805, with a sensitivity of 0.955 and specificity of 0.307, corresponding to a reduction of 17.41% (47/270) in reviewed specimens.Conclusion:The platelet review prediction model developed based on deep learning technology can efficiently identify samples with consistent results before and after review, reducing unnecessary reviews and shortening specimen testing time, thereby improving the efficiency of platelet test.