1.Time-series analysis of daily temperature, atmospheric pressure, and pre-hospital cardiovascular and cerebrovascular disease emergencies in Yantai, Shandong Province, 2016–2022
Mingshun WU ; Qing ZHANG ; Liang CHANG ; Lan LI ; Suqiu YANG ; Jiarong LI ; Xinhui YU ; Linlin LI ; Jiawei FENG ; Tieying NI
Journal of Environmental and Occupational Medicine 2026;43(4):458-466
Background Meteorological factors are among the key extrinsic triggers for the onset and exacerbation of cardiovascular and cerebrovascular diseases (CVD). Against the backdrop of sustained global warming, elucidating the impact of ambient temperature and atmospheric pressure on CVD, especially on pre-hospital CVD emergent events, has become imperative for evidence-based prevention and emergency preparedness. Objective To quantify the temporal trends of daily mean temperature and atmospheric pressure and their associations with pre-hospital CVD emergent events in Yantai, and to explore effect modification by demographic subgroups and geographic areas, thereby providing an empirical basis for the rational allocation of emergency medical resources. Methods Pre-hospital CVD emergency data from January 1, 2016 to December 31, 2022 were selected from the Yantai 120 Emergency Medical Command System. Synchronous meteorological factors and environmental pollutant data were obtained from the websites of the National Oceanic and Atmospheric Administration and the National Centers for Environmental Information of the United States. Time-series analysis combined with distributed lag non-linear model was used to analyze the association between daily temperature, atmospheric pressure, and pre-hospital CVD emergencies. Average annual percentage changes (AAPC) were calculated using Joinpoint (version 5.2.0.0) to reflect temporal trends. Spearman correlation analysis was employed to screen variables with low collinearity for inclusion in the multi-pollutant adjusted models. Results From 2016 to 2022, a total of
2.Effectiveness of generative large language model MedGo in nursing decision-making for elderly patients with multimorbidity
Qiaoyun YAN ; Min LI ; Yawen YAN ; Yaqing NI ; Yun GU ; Jiawen QIN ; Haiping YU ; Haitao ZHANG ; Liming ZHAO
Chinese Journal of Clinical Medicine 2026;33(1):16-23
Objective To explore the effectiveness of the generative large language model MedGo in nursing decision-making for elderly patients with multimorbidity. Methods A quasi-randomized controlled trial study was conducted involving 6 junior nurses, 6 senior nurses and the MedGo model from January 1, 2025 to March 31, 2025 at the Emergency Internal Medicine Ward of Shanghai East Hospital Affiliated to Tongji University. Clinical data of 120 elderly patients with multimorbidity were analyzed to compare the performance of the three groups in four tasks (nursing diagnosis assessment, nursing intervention formulation, complication identification, and complication prevention) from three evaluation dimensions: decision-making time consumption, decision accuracy, and decision-making quality. Results In terms of decision-making time, the senior nurse group completed all four tasks faster than the junior nurse group (P<0.01), and the MedGo group completed all four tasks faster than the junior nurse group (P<0.001) and the senior nurse group (P<0.001). In terms of decision-making accuracy, senior nurse group scored higher than junior nurse group in all four tasks (P<0.001), while the MedGo group outperformed the senior nurse group only in complication identification (P<0.001). In terms of decision-making quality, the MedGo group scored higher than junior nurse group (P<0.001) and senior nurse group (P<0.001) in all four tasks. Conclusions The MedGo model demonstrates advantages of high efficiency, accuracy, and quality in nursing decision-making for elderly patients with multimorbidity; senior nurses outperform junior nurses in decision-making, providing diverse references for clinical nursing decision-making.
3.Mid-long term follow-up reports on head and neck rhabdomyosarcoma in children
Chao DUAN ; Sidou HE ; Shengcai WANG ; Mei JIN ; Wen ZHAO ; Xisi WANG ; Zhikai LIU ; Tong YU ; Lejian HE ; Xiaoman WANG ; Chunying CUI ; Xin NI ; Yan SU
Chinese Journal of Pediatrics 2025;63(1):62-69
Objective:To analyze the clinical characteristics of children with head and neck rhabdomyosarcoma (RMS) and to summarize the mid-long term efficacy of Beijing Children′s Hospital Rhabdomyosarcoma 2006 (BCH-RMS-2006) regimen and China Children′s Cancer Group Rhabdomyosarcoma 2016 (CCCG-RMS-2016) regimen.Methods:A retrospective cohort study. Clinical data of 137 children with newly diagnosed head and neck RMS at Beijing Children′s Hospital, Capital Medical University from March 2013 to December 2021 were collected. Clinical characteristic of patients at disease onset and the therapeutic effects of patients treated with the BCH-RMS-2006 and CCCG-RMS-2016 regimens were compared. The treatments and outcomes of patients with recurrence were also summarized. Survival analysis was performed by Kaplan-Meier method, and Log-Rank test was used for comparison of survival rates between groups.Results:Among 137 patients, there were 80 males (58.4%) and 57 females (41.6%), the age of disease onset was 59 (34, 97) months. The primary site in the orbital, non-orbital non-parameningeal, and parameningeal area were 10 (7.3%), 47 (34.3%), and 80 (58.4%), respectively. Of all patients, 32 cases (23.4%) were treated with the BCH-RMS-2006 regimen and 105 (76.6%) cases were treated with the CCCG-RMS-2016 regimen. The follow-up time for the whole patients was 46 (20, 72) months, and the 5-year progression free survival (PFS) and overall survival (OS) rates for the whole children were (60.4±4.4)% and (69.3±4.0)%, respectively. The 5-year OS rate was higher in the CCCG-RMS-2016 group than in BCH-RMS-2006 group ((73.0±4.5)% vs. (56.6±4.4)%, χ2=4.57, P=0.029). For the parameningeal group, the 5-year OS rate was higher in the CCCG-RMS-2016 group (61 cases) than in BCH-RMS-2006 group (19 cases) ((57.3±7.6)% vs. (32.7±11.8)%, χ2=4.64, P=0.031). For the group with meningeal invasion risk factors, the 5-year OS rate was higher in the CCCG-RMS-2016 group (54 cases) than in BCH-RMS-2006 group (15 cases) ((57.7±7.7)% vs. (30.0±12.3)%, χ2=4.76, P=0.029). Among the 10 cases of orbital RMS, there was no recurrence. In the non-orbital non-parameningeal RMS group (47 cases), there were 13 (27.6%) recurrences, after re-treatment, 7 cases survived. In the parameningeal RMS group (80 cases), there were 40 (50.0%) recurrences, with only 7 cases surviving after re-treatment. Conclusions:The overall prognosis for patients with orbital and non-orbital non-parameningeal RMS is good. However, children with parameningeal RMS have a high recurrence rate, and the effectiveness of re-treatment after recurrence is poor. Compared with the BCH-RMS-2006 regimen, the CCCG-RMS-2016 regimen can improve the treatment efficacy of RMS in the meningeal region.
4.Performance comparison of 5 automatic cell type annotation methods in scRNA-seq data
Jinghui NI ; Yu GAO ; Qiyue CHEN ; Ying ZHANG ; Yan LIU
Chinese Journal of Endemiology 2025;44(11):931-936
Objective:This study aims to analyze the performance of five automatic cell type annotation methods in single cell RNA sequencing (scRNA-seq) data.Methods:Simulated data were generated using the Splatter package in R language, taking into account two data characteristics: the number of cells and the number of genes. The actual data came from the GSE10245 scRNA seq dataset of non-small cell lung cancer in Gene Expression Omnibus (GEO) database, the data had been pre-processed and batch effects had been eliminated. The automatic cell type recognition (ACTINN) of neural networks, the single-cell type annotation method based on deep learning (scDeepSort), the reference batch transcriptome annotation scRNA seq R-package (SingleR), the cross platform and cross species scRNA seq data classifier (SingleCellNet), and the cross scRNA seq dataset projection (scMap-cell) were implemented using the Tensorflow library in Python. The performance evaluation indicators for cell type annotation included accuracy (ACC), F1-score, and Matthews correlation coefficient (MCC). Each method was validated using ten fold cross validation, and the average value was taken after 50 repeated runs for performance comparison between methods. The Dunnett's t-test in the DescTools package of R language was used for multiple comparisons between ACTINN and other four methods. Results:Under 12 different scenarios (3 levels of cell numbers × 4 levels of gene numbers), simulated data analysis showed that compared with scDeepSort, SingleR, SingleCellNet, and scMap-cell, the percentage increase in ACC value of ACTINN ranged from 3.31% to 14.59%, 1.38% to 13.03%, 12.98% to 25.25%, and 20.72% to 29.62%, respectively; the range of F1 score improvement percentages were 2.75% - 22.74%, 2.46% - 23.68%, 5.07% - 27.47%, and 10.27% - 31.47%, respectively; the percentage increase ranges for MCC values were 3.42% - 9.75%, 2.26% - 7.61%, 5.41% - 11.11%, and 8.27% - 15.22%, respectively. Actual data analysis showed that the ACC value of ACTINN was 81.0%, which was increased by 2.1%, 5.2%, 7.9%, and 8.9% compared with the above four methods, respectively; the F1-score value was 80.5%, which was increased by 2.3%, 5.9%, 2.4%, and 6.0%, respectively; the MCC value was 83.3%, which was increased by 0.9%, 2.5%, 3.4%, and 11.2%, respectively. The results of Dunnett's t-test showed that the difference was not statistically significant in ACC values between scDeepSort and ACTINN ( P = 0.821), in F1-score values between scDeepSort and ACTINN ( P = 0.498), and in MCC values between scDeepSort, SingleCellNet and ACTINN ( P = 0.904, 0.134). However, the differences were statistically significant in other multiple comparisons ( P < 0.05). Conclusions:ACTINN and scDeepSort have good performance in cell type annotation, with ACTINN showing outstanding performance and SingleR showing robust performance, while SingleCellNet and scMap-cell have relatively limited performance. This suggests that self-attention mechanism algorithm based on Transformer framework is expected to promote further development of automatic cell annotation methods.
5.Resting brain function study of executive function changes in patients with type 2 diabetes mellitus
Yanyan CUI ; Ying YU ; Bo HU ; Sining LI ; Xinyu CAO ; Pan DAI ; Minhua NI ; Xiaoyan BAI ; Yao TONG ; Lijuan DU ; Linfeng YAN ; Guangbin CUI
Journal of Practical Radiology 2025;41(9):1427-1431
Objective To explore the changes in neural activity in patients with type 2 diabetes mellitus(T2DM)and their corre-lation with executive function,and to analyze the neural mechanisms underlying the decline in executive function in T2DM patients.Methods Thirty-one T2DM patients(T2DM group)and thirty-two healthy controls(HC)(HC group)matched for body mass index(BMI)underwent resting-state functional magnetic resonance imaging(rs-fMRI)scans and N-back task tests were included.Differ-ences in the amplitude of low-frequency fluctuation(ALFF),regional homogeneity(ReHo),and seed-based functional connectivity(FC)between the two groups were compared,and partial correlation analyses were performed between the difference results and N-back task performance.Results The T2DM group showed prolonged reaction time(RT)in the 1-back and 2-back tasks.T2DM patients exhibited increased ALFF in the bilateral caudate nucleus,left medial superior frontal gyrus,and right postcentral gyrus,as well as elevated ReHo in the right putamen.FC analysis revealed significant alterations in FC between the caudate nucleus,putamen,and multiple brain regions in T2DM patients,with some of these FC changes significantly correlated with RT and accuracy(ACC)in the N-back task.Conclusion The decline in executive function in T2DM patients may be associated with abnormal neural activity in brain regions such as the striatum,salience network,and frontoparietal control network.FC further decreases under increased cognitive load.These findings provide evidence for the study of the neural mechanisms of executive function impairment in T2DM patients.
6.Study on the correlation between left ventricular myocardial fibrosis and right ventricular function injury in coronary heart disease via cardiac MR
Luying NI ; Qian ZHANG ; Changjin BAO ; Mengmeng YU ; Di ZHANG ; Xingyue JIANG
Journal of Practical Radiology 2025;41(10):1658-1662
Objective To investigate the relationship between left ventricular myocardial fibrosis and right ventricular function injury in coronary heart disease(CHD)using cardiac magnetic resonance(CMR).Methods A total of 40 CHD patients and 32 healthy volunteers were selected.Based on the late gadolinium enhancement(LGE)images,CHD patients were divided into LGE(+)and LGE(-)groups.Biventricular function parameters,T1 value of the left ventricular myocardium and left ventricular LGE extent(%LGE)were measured and compared between the two groups.Pearson or Spearman correlation analysis was used to analyze the relationship among CMR parameters.Multivariate logistic regression was used to analyze the related factors of right ventricular dysfunction.Results Compared with the LGE(-)group,the right ventricular ejection fraction(RVEF),right ventricular stroke volume index(RVSVI)and right ventricular fractional area change(RVFAC)were decreased in the LGE(+)group(P<0.05).RVEF,RVSVI and RVFAC were negatively correlated with%LGE and native T1 value of the left ventricular myocardium,and native T1 value of the left ventricular myocardium was independently correlated with right ventricular dysfunction(P<0.05).Conclusion CMR reveals the relationship between left ventricular myocardial fibrosis and right ventricular function injury in CHD patients,which is helpful for the early clinical detection and treatment of right ventricular injury.
7.Association between plasma complement levels and white matter microstructural abnormalities in first-episode schizophrenia
Lingqi JIAN ; Shiyi HU ; Hua YU ; Peiyan NI ; Junzhe RAN ; Wei WEI ; Liansheng ZHAO ; Chengcheng ZHANG ; Tao LI
Chinese Journal of Nervous and Mental Diseases 2025;51(8):469-474
Objective To investigate alterations in plasma complement levels and white matter imaging characteristics,along with their relationship in patients with first-episode schizophrenia(SCZ).Methods Thirty-eight patients with first-episode schizophrenia and 42 healthy controls were enrolled.Whole-brain diffusion tensor imaging(DTI)was performed using a Philips 3.0 T MRI scanner.Tract-based spatial statistics(TBSS)combined with the Johns Hopkins University(JHU)white matter labels atlas was used to extract and compare white matter characteristics between the two groups.Plasma levels of complement components(C1q,C3,C4,factor B,factor H,and factor P)were measured using the MILLIPLEX? human complement assay kit via multiplex analysis.Spearman correlation analysis was conducted to examine the association between plasma complement levels and white matter features.Results The radial diffusivity(RD)of the left fornix/stria terminalis was significantly higher in the patient group compared to the control group[(0.62±0.04)×10-3mm2/s vs.(0.60±0.03)×10-3mm2/s,PFDR=0.048)].Factor H[677.71(551.58,846.21)ng/mL vs.582.76(513.93,729.71)ng/mL,P=0.041]and factor P[71.36(57.30,95.99)ng/mL vs.60.08(46.67,80.03)ng/mL,P=0.011]were both significantly elevated compared to the control group.Moreover,RD values in the left fornix/stria terminalis were negatively correlated with plasma C3 levels in the patient group(r=-0.362,P=0.025).Conclusion Patients with first-episode schizophrenia exhibit white matter microstructural abnormalities in left fornix/stria terminalis,which are significantly associated with plasma complement levels.
8.The application value of multi-parameter quantitative analysis of spectral and perfusion CT in differentiat-ing pathological types of lung cancer
Xiaokun GAO ; Ziming XIE ; Guangyu TAO ; Yanbing SUN ; Hua REN ; Jiahui YU ; Lin ZHU ; Hong YU ; Qiming NI
The Journal of Practical Medicine 2025;41(19):3096-3105
Objective This study aims to explore the application value of spectral CT and perfusion CT parameters in the pathological classification and prognostic assessment of lung cancer.Methods A total of 94 lung cancer patients confirmed by pathology at Shanghai Chest Hospital from January 2023 to November 2024 were included in the study,including 49 cases of lung adenocarcinoma(LUAD),30 cases of lung squamous cell carci-noma(LUSC),and 15 cases of small cell lung cancer(SCLC).All patients underwent spectral CT combined with perfusion scanning using a 256-slice Revolution Apex from GE.Two radiologists independently measured the spectral and perfusion parameters of the three groups of images,including spectral curve slope(K),iodine concentration in the lesion area(ICL),effective atomic number(Zeff),surface permeability(PS),and perfusion index(PI),and established a lung cancer pathological subtype discrimination prediction model based on spectral CT radiomics features.All subjects were randomly divided into a training group and a validation group at a ratio of 3∶1.The discrimination efficacy of the spectral discrimination model between different pathological subtypes and the discrimination efficacy of arterial and venous phase images were compared in multiple dimensions.The performance of the model was evaluated using the receiver operating characteristic(ROC)curve.Results Statistical analysis showed that the spectral curve slope,ICL,NIC,and Zeff of LUAD patients were significantly higher than those of LUSC and SCLC patients(P<0.05),while there were no significant differences in these parameters between LUSC and SCLC patients(P>0.05).Among the perfusion CT parameters,surface permeability(PS)showed significant differences among the three groups(P<0.05),while blood volume(BV),blood flow(BF),perfusion index(PI),time to peak(TTP),and mean transit time(MTT)did not show statistical differences.The multi-factor logistic regression model based on spectral parameters showed strong discriminatory performance:the area under the curve(AUC)of the LUAD and LUSC discrimination model was 0.806/0.77(training group/test group)in the arterial phase and 0.867/0.9(training group/test group)in the venous phase;the AUC of the LUAD and SCLC discrimination model was 0.885/0.883(training group/test group)in the arterial phase and 0.851/0.776(training group/test group)in the venous phase.Conclusion This study indicates that the multi-dimensional functional metabolic analysis indicators of spectral and perfusion CT imaging have significant value in the differential diagnosis of lung cancer pathological subtypes.The diagnostic model constructed by combining multiple spectral parameters can significantly improve the discrimination efficacy of lung adenocarcinoma,squamous cell carcinoma,and small cell lung cancer,providing precise imaging evidence for the formulation of individualized treatment plans.
9.To investigate effect of adipose-derived mesenchymal stem cells on fistula wound repair in fistular-type Crohn's disease model rats based on miR-146a-IRAK axis
Jian NI ; Xiaowen ZHU ; Haitao YU
Chinese Journal of Immunology 2025;41(2):320-327
Objective:To investigate investigate repairing effect of adipose tissue-derived mesenchymal stem cell(ADSC)on fistula wounds in a rat model of fistula Crohn's disease(CD)and its regulation mechanism on miR-146a/interleukin-1 receptor-associ-ated kinase(IRAK)signaling axis.Methods:RT-PCR was used to detect the expression of miR-146a and mRNA expression of IRAK in the serum of 80 fistula-type CD patients treated with fistula after operation.Dual-luciferase gene reporter was used to analysis the re-lationship between miR-146a and IRAK.The rat CD successfully prepared fistula lesions and divided into control group(Con),ADSC intervention group(ADSC),ADSC+miR-146a-antagomir intervention group(ADSC+antagomir),ADSC+miR-146a-antagomir+siR-NA-IRAK intervention group(ADSC+antagomir+si),with 10 rats in each group.One hour after successful modeling,rats in ADSC group were injected with 2×106 cells/ml ADSC suspension into the area around the fistula,and subcutaneously injected 2 μg/kg of miR-146a-antagomir-NC.Rats in the ADSC+antagomir group were injected with 2×106 cells/ml ADSC suspension into the area around the fistula,and subcutaneously injected with 2 μg/kg of miR-146a-antagomir.Rats in the ADSC+antagomir+si group were injected with 2×106 cells/ml ADSC suspension into the area around the fistula,and subcutaneously injected with 2 μg/kg of miR-146a-an-tagomir+siRNA-IRAK.Rats in the Con group,were injected a dose of normal saline into the area around the fistula,and subcutaneous-ly injected 2 μg/kg of miR-146a-antagomir-NC.Each group was treated twice a day for 14 consecutive days.Flow cytometry was used to detect the apoptosis of fistula wound tissue in rats;kits were used to detect the contents of TNF-α and IL-6 in rats serum.Immuno-histochemistry was used to detect angiogenesis in the fistula wound tissue of the rats in each group.Western blot was used to detect the expressions of IRAK,apoptosis protein B-lymphoma-2(Bcl-2),Bcl-2-related x protein(Bax),vascular endothelial growth factor(VEGF)in fistula wound tissue.Results:The expression of miR-146a in the postoperative serum of patients with CD fistulae was sig-nificantly decreased,the mRNA expression of IRAK was significantly increased,and the differences were statistically significant(both P<0.05).miR-146a regulated the expression of IRAK.Compared with the Con group,the apoptosis rate,the contents of TNF-α and IL-6,the expressions of IRAK and Bax in the rat fistula wound of ADSC group,ADSC+antagomir group,ADSC+antagomir+si group were significantly decreased,the number of new blood vessels and the expression of Bcl-2 and VEGF in the fistula tissue were significantly increased.Compared with ADSC group,the apoptosis rate,the contents of TNF-α and IL-6,the expressions of IRAK and Bax in the rat fistula wound of ADSC+antagomir group,ADSC+antagomir+si group were significantly increased,the number of new blood vessels and the expressions of Bcl-2 and VEGF in the fistula tissue were significantly decreased.Compared with ADSC+an-tagomir group,the contents of TNF-α and IL-6,the expressions of IRAK and Bax in the rat fistula wound of ADSC+antagomir+si group were significantly decreased,the number of new blood vessels and the expressions of Bcl-2 and VEGF in the fistula tissue were significantly increased,and the differences were statistically significant(all P<0.05).Conclusion:ADSCs can significantly heal fistu-las after fistula lesions in CD model rats,which may be related to regulating the expression of miR-146a/IRAK,inhibiting cell apopto-sis,and promoting wound angiogenesis.
10.Prioritization of potential drug targets for diabetic kidney disease using integrative omics data mining and causal inference
Junyu ZHANG ; Jie PENG ; Chaolun YU ; Yu NING ; Wenhui LIN ; Mingxing NI ; Qiang XIE ; Chuan YANG ; Huiying LIANG ; Miao LIN
Journal of Pharmaceutical Analysis 2025;15(8):1787-1799
Diabetic kidney disease(DKD)with increasing global prevalence lacks effective therapeutic targets to halt or reverse its progression.Therapeutic targets supported by causal genetic evidence are more likely to succeed in randomized clinical trials.In this study,we integrated large-scale plasma proteomics,genetic-driven causal inference,and experimental validation to identify prioritized targets for DKD using the UK Biobank(UKB)and FinnGen cohorts.Among 2844 diabetic patients(528 with DKD),we identified 37 targets significantly associated with incident DKD,supported by both observational and causal evi-dence.Of these,22%(8/37)of the potential targets are currently under investigation for DKD or other diseases.Our prospective study confirmed that higher levels of three prioritized targets-insulin-like growth factor binding protein 4(IGFBP4),family with sequence similarity 3 member C(FAM3C),and prostaglandin D2 synthase(PTGDS)—were associated with a 4.35,3.51,and 3.57-fold increased likeli-hood of developing DKD,respectively.In addition,population-level protein-altering variants(PAVs)analysis and in vitro experiments cross-validated FAM3C and IGFBP4 as potential new target candidates for DKD,through the classic NLR family pyrin domain containing 3(NLRP3)-caspase-1-gasdermin D(GSDMD)apoptotic axis.Our results demonstrate that integrating omics data mining with causal inference may be a promising strategy for prioritizing therapeutic targets.

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