ObjectiveTo analyze the risk factors for long-term cardiovascular events in patients undergoing long-term peritoneal dialysis （PD）， and to construct and validate a visual nomogram prediction model based on multiple parameters. MethodsA prospective cohort study was conducted， consecutively enrolling 248 maintenance PD patients （dialysis duration ≥ 3 months）. Demographic characteristics， clinical indicators， laboratory parameters， and echocardiographic indices （including left ventricular ejection fraction ［LVEF］， ratio of early diastolic mitral inflow velocity to early diastolic mitral annular velocity （E/e’）， etc.） were collected. The composite endpoint was defined as the occurrence of cardiovascular events or cardiovascular death， with non-cardiovascular death as the competing risk and loss to follow-up or the end of follow-up as censoring events. Fine-Gray competing risks model was used to screen independent predictors， based on which a nomogram model was constructed. Internal validation was performed using the Bootstrap method （1 000 resamplings）， and the concordance index （C-index） and time-dependent receiver operating characteristic （time-dependent ROC） curve were calculated to evaluate the model performance. ResultsWith a median follow-up of 29 months （interquartile range： 24–35 months）， 88 patients （35.48%） reached the composite endpoint， including 80 cases of cardiovascular events and 8 cases of cardiovascular death， and 4 patients died of non-cardiovascular causes. Multivariate Fine-Gray analysis revealed that age， diabetes mellitus， hemoglobin （HGB） level and E/e' ratio were independent influencing factors of the composite endpoint. Specifically， each 1-year increase in age was associated with a 3.0% increase in the risk of the composite endpoint （HR=1.030， P=0.006）； patients with diabetes mellitus had a 167.9% higher risk compared with non-diabetic patients （HR=2.679， P=0.007）； each 1g/L increase in HGB level contributed to a 1.5% reduction in the risk （HR=0.985， P=0.003）； and each 0.1 increase in E/e' ratio led to a 7.2% increase in the risk （HR=1.072， P=0.045）. The nomogram model had a C-index of 0.76 （95% CI： 0.698–0.820）， and the AUC of the time-dependent ROC curve reached 0.849 at 23 months of follow-up. ConclusionIncreased age， complicated with diabetes mellitus， decreased HGB， and elevated E/e' ratio are independent risk factors of long-term occurrence of cardiovascular events and cardiovascular death in patients undergoing long-term PD. The nomogram model constructed based on the above variables has good predictive value and clinical applicability， which can provide a reference for cardiovascular risk stratification and individualized intervention in long-term PD patients.

ObjectiveTo observe the prognosis effect of soluble programmed death ligand-1（sPD-L1） in treating patients with advanced lung adenocarcinoma treated with epidermal growth factor receptor-tyrosine kinase inhibitors（EGFR-TKIs） and the influence of Yiqi Yangyin Jiedu prescription. MethodA prospective cohort-controlled study was conducted to enroll patients treated with EGFR-TKIs in the first line of treatment，who were admitted to the Oncology Department of Longhua Hospital and Shanghai Chest Hospital from May 1^st， 2021 to June 30^th， 2023， and they were evaluated as non-progressive and identified with deficiency of Qi and Yin after one month of treatment. The patients were divided into an exposed group （EGFR-TKIs combined with Yiqi Yangyin Jiedu prescription） and a non-exposed group （EGFR-TKIs alone）according to whether or not they were treated with Yiqi Yangyin Jiedu prescription and were treated until disease progression， or death and intolerable adverse reactions occurred. The enzyme-linked immunosorbent assay （ELISA） was applied to detect the level of sPD-L1 in patients at the time of enrollment and disease progression，and Cox risk proportionality model was used to analyze the independent prognostic factors affecting disease progression of patients treated with EGFR-TKIs. ResultA total of 90 patients （39 in the exposed group and 51 in the non-exposed group） undergoing disease progression after EGFR-TKI treatment were enrolled. At the time of enrolment and after disease progression，the levels of serum sPD-L1 in the 90 patients were 12.06 （27.54） ng·L^-1 and 41.99 （62.93） ng·L^-1，respectively. Compared with that at the time of enrollment， the serum sPD-L1 level in the 90 patients was significantly increased after disease progression （P<0.01）. The serum sPD-L1 level in patients in the exposed group was 12.27 （24.78） ng·L^-1 and 29.57 （61.12）ng·L^-1 respectively at the time of enrolment and after disease progression. In the non-exposed group， patients had serum sPD-L1 levels of 11.81 （28.46） ng·L^-1 and 49.54 （74.12） ng·L^-1 respectively at the time of enrolment and after disease progression. Compared with that at the time of enrollment， the serum sPD-L1 level in the two groups of patients was significantly increased after disease progression （P<0.01）. In addition， compared with that in the non-exposed group， the sPD-L1 level in the exposed group was greatly reduced after disease progression（P<0.01）. Cox multifactorial analysis showed that sPD-L1 level and age at the time of enrolment were associated with patients' progression-free survival（PFS），and that low levels of sPD-L1 （<12.06 ng·L^-1） prolonged the PFS and reduced the risk of disease progression in patients treated with EGFR-TKIs compared with high levels of sPD-L1. ConclusionElevated sPD-L1 level is a poor prognostic factor for the long-term efficacy of EGFR-TKIs，and treatment with Yiqi Yangiin Jiedu prescription can down-regulate sPD-L1 level of patients treated with EGFR-TKIs.

BACKGROUND: The contraction behaviors of cardiomyocytes (CMs), especially contraction synchrony, are crucial factors reflecting their maturity and response to drugs. A wider field of view helps to observe more pronounced synchrony differences, but the accompanied greater computational load, requiring more computing power or longer computational time. METHODS: We proposed a method that directly correlates variations in optical field brightness with cardiac tissue contraction status (CVB method), based on principles from physics and photometry, for rapid video analysis in wide field of view to obtain contraction parameters, such as period and contraction propagation direction and speed. RESULTS: Through video analysis of human induced pluripotent stem cell (hiPSC)-derived CMs labeled with green fluorescent protein (GFP) cultured on aligned and random nanofiber scaffolds, the CVB method was demonstrated to obtain contraction parameters and quantify the direction and speed of contraction within regions of interest (ROIs) in wide field of view. The CVB method required less computation time compared to one of the contour tracking methods, the LucasKanade (LK) optical flow method, and provided better stability and accuracy in the results. CONCLUSION This method has a smaller computational load, is less affected by motion blur and out-of-focus conditions, and provides a potential tool for accurate and rapid analysis of cardiac tissue contraction synchrony in wide field of view without the need for more powerful hardware.

BACKGROUND: The contraction behaviors of cardiomyocytes (CMs), especially contraction synchrony, are crucial factors reflecting their maturity and response to drugs. A wider field of view helps to observe more pronounced synchrony differences, but the accompanied greater computational load, requiring more computing power or longer computational time. METHODS: We proposed a method that directly correlates variations in optical field brightness with cardiac tissue contraction status (CVB method), based on principles from physics and photometry, for rapid video analysis in wide field of view to obtain contraction parameters, such as period and contraction propagation direction and speed. RESULTS: Through video analysis of human induced pluripotent stem cell (hiPSC)-derived CMs labeled with green fluorescent protein (GFP) cultured on aligned and random nanofiber scaffolds, the CVB method was demonstrated to obtain contraction parameters and quantify the direction and speed of contraction within regions of interest (ROIs) in wide field of view. The CVB method required less computation time compared to one of the contour tracking methods, the LucasKanade (LK) optical flow method, and provided better stability and accuracy in the results. CONCLUSION This method has a smaller computational load, is less affected by motion blur and out-of-focus conditions, and provides a potential tool for accurate and rapid analysis of cardiac tissue contraction synchrony in wide field of view without the need for more powerful hardware.

BACKGROUND: The contraction behaviors of cardiomyocytes (CMs), especially contraction synchrony, are crucial factors reflecting their maturity and response to drugs. A wider field of view helps to observe more pronounced synchrony differences, but the accompanied greater computational load, requiring more computing power or longer computational time. METHODS: We proposed a method that directly correlates variations in optical field brightness with cardiac tissue contraction status (CVB method), based on principles from physics and photometry, for rapid video analysis in wide field of view to obtain contraction parameters, such as period and contraction propagation direction and speed. RESULTS: Through video analysis of human induced pluripotent stem cell (hiPSC)-derived CMs labeled with green fluorescent protein (GFP) cultured on aligned and random nanofiber scaffolds, the CVB method was demonstrated to obtain contraction parameters and quantify the direction and speed of contraction within regions of interest (ROIs) in wide field of view. The CVB method required less computation time compared to one of the contour tracking methods, the LucasKanade (LK) optical flow method, and provided better stability and accuracy in the results. CONCLUSION This method has a smaller computational load, is less affected by motion blur and out-of-focus conditions, and provides a potential tool for accurate and rapid analysis of cardiac tissue contraction synchrony in wide field of view without the need for more powerful hardware.

Objective To screen long non-coding RNA(lncRNA)associated with lymph node metasta-sis in papillary thyroid carcinoma(PTC)and verify its function in vitro,so as to provide a theoretical basis for elucidating the molecular mechanism of lymph node metastasis in PTC.Methods lncRNA+mRNA microar-ray was used to detect the differential expression of lncRNA and mRNA in PTC cancer tissues with and with-out lymph node metastasis.Real time fluorescence quantitative PCR(qPCR)verified target differential lncR-NAs.Lentivirus was used as vector to construct high and low lncRNA expression PTC cell lines.Cell counting kit-8(CCK-8),cell scratches assay,Transwell assay,cell clone formation assay were used to detect the effects of target lncRNA on proliferation,migration,invasion,clonal formation of PTC cells.Results Compared with 5 cases of PTC tissues without lymph node metastasis,gene chips detected 119 lncRNA and 53 mRNA expres-sion levels upregulated,while 263 lncRNA and 198 mRNA expression levels down regulated in 5 cases of PTC tissues with lymph node metastasis.Furthermore,21 lncRNAs were selected for validation in the original 10 PTC samples,and the results showed that,compared with PTC tissues without lymph node metastasis,lncR-NAs FLJ20444,DPP10-AS1 and ENST00000567197 were highly expressed in PTC tissues with lymph node metastasis,while uc021thd.1,LNC00944,ENST00000429730 and BLNK were lowly expressed(P＜0.05).In addition,qPCR results of another 30 fresh PTC tissues showed that compared with PTC tissues without lymph node metastasis,DPP10-AS1 was highly expressed and LNC00944 was lowly expressed in PTC tissues with lymph node metastasis(P＜0.05).Cell function experiments showed that the proliferation,migration,invasion,and colony formation abilities of PTC cells in the DPP10-AS1 high expression group were higher than those in the DPP10-AS1 low expression group,and the differences were statistically significant(P＜0.05).Conclusion lncRNA DPP10-AS1 may play a role in PTC metastasis through certain signaling pathways.

Objective To Study the value of effected ejection fraction(eEF)in assessment of cardiac function in elderly patients with heart failure.Methods A total of 1 134 elderly inpatients in this hospital from January 2019 to December 2023 were selected as the research subjects.After admission,relevant examinations and tests were completed,and the cardiac function classification of the New York Heart Association(NYHA)was carried out.Sequential electrocardiogram(ECG)and echocardiogram examinations were completed before treatment.Age,under-lying diseases,left ventricular ejection fraction(LVEF),N-terminal pro-brain natriuretic peptide(NT-proB-NP),and QT interval(QTc)of the ECG were included for classification and statistics,and eEF was obtained,and the evaluation value of eEF on cardiac function was analyzed.Results The numbers of patients with NY-HA cardiac function grades Ⅰ—Ⅳ were 86,434,454 and 160,respectively,and LVEF decreased with the in-crease of the NHYA cardiac function grade.There was statistically significant differences in LVEF among dif-ferent NHYA cardiac function classifications(P＜0.05).The QTc of the patients was(434.71±40.96)ms,the eEF was(8.73±2.03)ms,and the ln(NT-proBN)was 7.05±1.70.QTc,eEF,and ln(NT-proBN)all in-creased with the increase of the NHYA cardiac function classification,and there were statistically significant differences in indicators above among different NHYA cardiac function classfications(P＜0.05).There was a low correlation between QTc of the ECG,age and cardiac insufficiency(r＜0.5,P＜0.05);there was a high correlation between eEF,LVEF,and ln(NT-proBNP)and cardiac insufficiency(r≥0.5,P＜0.05).Conclusion eEF still has discriminatory value for patients with heart failure with preserved ejection fraction,and it is a good indicator for evaluating the cardiac function of elderly patients with heart failure.

BACKGROUND: The contraction behaviors of cardiomyocytes (CMs), especially contraction synchrony, are crucial factors reflecting their maturity and response to drugs. A wider field of view helps to observe more pronounced synchrony differences, but the accompanied greater computational load, requiring more computing power or longer computational time. METHODS: We proposed a method that directly correlates variations in optical field brightness with cardiac tissue contraction status (CVB method), based on principles from physics and photometry, for rapid video analysis in wide field of view to obtain contraction parameters, such as period and contraction propagation direction and speed. RESULTS: Through video analysis of human induced pluripotent stem cell (hiPSC)-derived CMs labeled with green fluorescent protein (GFP) cultured on aligned and random nanofiber scaffolds, the CVB method was demonstrated to obtain contraction parameters and quantify the direction and speed of contraction within regions of interest (ROIs) in wide field of view. The CVB method required less computation time compared to one of the contour tracking methods, the LucasKanade (LK) optical flow method, and provided better stability and accuracy in the results. CONCLUSION This method has a smaller computational load, is less affected by motion blur and out-of-focus conditions, and provides a potential tool for accurate and rapid analysis of cardiac tissue contraction synchrony in wide field of view without the need for more powerful hardware.

Schizophrenia (SZ) stands as a severe psychiatric disorder. This study applied diffusion tensor imaging (DTI) data in conjunction with graph neural networks to distinguish SZ patients from normal controls (NCs) and showcases the superior performance of a graph neural network integrating combined fractional anisotropy and fiber number brain network features, achieving an accuracy of 73.79% in distinguishing SZ patients from NCs. Beyond mere discrimination, our study delved deeper into the advantages of utilizing white matter brain network features for identifying SZ patients through interpretable model analysis and gene expression analysis. These analyses uncovered intricate interrelationships between brain imaging markers and genetic biomarkers, providing novel insights into the neuropathological basis of SZ. In summary, our findings underscore the potential of graph neural networks applied to multimodal DTI data for enhancing SZ detection through an integrated analysis of neuroimaging and genetic features.
Humans ; Schizophrenia/pathology* ; Diffusion Tensor Imaging/methods* ; Male ; Female ; Adult ; Brain/metabolism* ; Young Adult ; Middle Aged ; White Matter/pathology* ; Gene Expression ; Nerve Net/diagnostic imaging* ; Graph Neural Networks

ObjectiveTo analyze the distribution, drug resistance characteristics, and changing trends of Acinetobacter baumannii (AB) isolated from environmental surfaces and healthcare workers’ hands in a grade Ⅱ level A general hospital in Xuhui District of Shanghai from 2018 to 2023, and to provide reference for infection control in the hospital. MethodsEnvironmental samples were collected quarterly from critical surfaces and healthcare workers’ hands in the intensive care unit (ICU), geriatrics, and respiratory departments from 2018 to 2023. Clinical isolates were obtained from all patients with AB infections in ICU, geriatrics, respiratory department, rehabilitation department, infectious diseases department, emergency department, cardiology department, and orthopedics of the hospital from 2018 to 2023. Retrospective analyses were performed on AB detection rates, strain origins, resistance rates to commonly used antimicrobial agents, and resistance gene features, comparing the antimicrobial resistance between clinically isolated strains and environmentally isolated strains. ResultsFrom 2018 to 2023, a total of 1 416 samples were collected from the hospital and a total of 272 strains of AB were detected, with a positive detection rate of 19.21%. The detection rate gradually decreased year-on-year (χ²_trend=45.290, P<0.001). The majority of samples originated from patient-contacted items (34.56%, 94/272), followed by shared items (26.84%, 73/272) and healthcare worker-contacted items (15.07%, 41/272). From 2018 to 2023, the resistance rate of AB on environmental surfaces and healthcare workers’ hands to commonly tested antibiotics in the hospital ranged from 10% to 40%. The resistance rates to cefotaxime (42.52%) and piperacillin (38.58%) were relative high, while the resistance to polymyxin E (1.57%), polymyxin B (2.36%), and doxycycline (3.94%) maintained low. The annual fluctuations in resistance to cefotaxime, piperacillin, ceftriaxone, tobramycin, doxycycline, minocycline and cotrimoxazole were statistically significant (all P<0.05). There were statistically significant differences in the resistance of clinical and environmental isolates to ampicillin/sulbactam, cefepime, ceftazidime, subamphetamine, meropenem, piperacillin, aztreonam, gentamicin, tobramycin, minocycline, ciprofloxacin, levofloxacin, and cotrimoxazole in the hospital from 2018 to 2023 (all P<0.05). The resistance rate of clinical isolates was generally high, especially to β-lactam and quinolone drugs, which were mostly above 80% [such as cefepime (93.86%), cefotaxime (97.37%), imipenem (98.25%), and ciprofloxacin (99.12%)]. The resistance rate of environmental isolated strains to similar antibiotics was relatively lower, mostly concentrated at 10%‒30%. The whole-genome sequencing of 34 carbapenem-resistant Acinetobacter baumannii (CRAB) strains isolated from the hospital environment in 2023 revealed that the main resistance mechanism was overexpression of efflux pumps (51.97%), followed by changes in target sites (32.46%). Among the 34 CRAB strains, carbapenem resistance genes OXA-23 and OXA-51 were detected in 6 strains (17.65%), while genes such as KPC, IMP, VIM, and SIM were not detected. ConclusionFrom 2018 to 2023, AB in the hospital environment exhibited high resistance rates to certain antimicrobial agents and carried multiple resistance genes, indicating a potential transmission risk. It is necessary to further strengthen bacterial resistance monitoring and hospital infection control, and use antibiotics reasonably.