Objective To explore the relationship between the polymorphism of excision repair cross-complementation group 1 (ERCC1) C8092A locus and the efficacy and prognosis of platinum-based chemotherapy for lung cancer (LC), and to provide a theoretical basis for precision treatment of LC. Methods From January 2014 to October 2017, 120 patients from two tertiary hospitals in Haikou City, and with pathologically confirmed lung cancer treated with platinum-based chemotherapy were selected as the research objects. After informed consent was obtained, peripheral blood samples were collected for DNA extraction, and the genotype of ERCC1 C8092A locus was detected by mass spectrometry. WHO's Response Evaluation Criteria in Solid Tumours (RECIST) was used to judge patients' chemotherapy efficacy and patients' survival status was obtained by telephone follow-up and other means. Results Among the 120 LC patients, the genotype frequencies of ERCC1 C8092A locus were 67 cases of CC wildtype (55.8%), 45 cases of CA heterozygous type (37.5%), and 8 cases of AA rare mutation type (6.7%), which conformed to Hardy-Weinberg equilibrium (χ2=0.140, P>0.05). The total effective rate of chemotherapy was 32.5%, with the highest effective rate in patients with the CA genotype (42.2%) at the ERCC1 C8092A locus and the lowest in patients with the CC genotype (25.4%). The overall one-year survival rate was 68.3% and the three-year survival rate was 35.8%. The patients with ERCC1 C8092A AA genotype had the lowest survival rate, with a one-year survival rate of 50.0% and three-year survival rate of only 25.0%. However, there were no statistical differences in the overall survival rate among the three genotypes of carriers of ERCC1 C8092A (χ2=0.328, P=0.849). Conclusions The polymorphism of ERCC1 C8092A locus is associated with the efficacy of platinum-based chemotherapy for LC, and patients with CA genotype have the highest efficacy. The one-year and three-year survival rates of patients with CC genotype are significantly higher than those of CA and AA genotypes.

[Objective] To explore the value of the TyG index for predicting postoperative recurrence in persistent atrial fibrillation (AF) patients combined with on-alcoholic fatty liver disease (NAFLD) undergoing catheter ablation. [Methods] This study was a single-center, retrospective, cohort study. Clinical data of patients who underwent catheter ablation during hospitalization or outpatient visits at The First Affiliated Hospital of Xi’an Jiaotong University from January 2021 to December 2022 were retrospectively collected. The patients were divided into recurrence and non-recurrence groups based on whether AF recurred within 1 year after the procedure. General clinical data and relevant laboratory test results were collected, and the preoperative TyG index was calculated. The risk factors for AF recurrence after catheter ablation in these patients were analyzed using univariate and multivariate COX proportional hazards regression models. The value of the TyG index for predicting AF recurrence was assessed using receiver operating characteristic (ROC) curve analysis. [Results] We recruited 167 patients, among whom 103 were males and 64 were females. The mean follow-up time was 12±1.3 months, with 52 cases of AF recurrence and 115 ones of non-recurrence. Compared with the non-recurrence group, the TyG index was higher in the recurrence group (9.62±0.96 vs. 8.26±0.46, P<0.05). Multivariate COX regression analysis showed that the preoperative TyG index (HR=1.35, 95% CI: 1.10-1.60, P<0.05) and postoperative electrocardiogram P-wave dispersion (HR=1.51, 95% CI: 1.32-1.70, P<0.001) were risk factors for AF recurrence after catheter ablation in persistent AF patients with NAFLD. The ROC curve analysis showed that the area under the curve (AUC) for the TyG index in predicting AF recurrence after catheter ablation in these patients was 0.846 (95% CI: 0.773-0.919, P<0.001). [Conclusion] The TyG index is an effective indicator for predicting atrial fibrillation recurrence after catheter ablation in persistent AF patients combined with NAFLD.

Objective To analyze the diversity and composition changes of gut fungal communities between mouse model of total parental nutrition(TPN)and normal control mice.Methods After mouse model of TPN was constructed,fresh feces were collected from TPN mice(n=5)and normal control mice(n=5).Internal transcribed spacer(ITS)DNA sequencing was applied to determine intestinal fungi,and then bioinformatics analysis was conducted to identify the differences in fungal diversity,structure,and functional properties between the 2 groups of mice.Results There were significant differences in Alpha diversity(P＜0.05)and Beta diversity(P＜0.01)of intestinal fungi between the 2 groups.In the TPN model group,the relative abundances of Candida,Penicillium,Aspergillus and Talaromyces were obviously reduced(all P＜0.01).LEfSe analysis indicated that the above 4 strains were notably enriched in the normal control mice.Conclusion TPN mice exhibit characteristic changes in the composition of gut fungal flora compared to normal control mice.Dysfunction of gut fungal community may promote the occurrence of TPN related complications,and regulating the balance of gut fungal community may become a new strategy for preventing TPN related complications.

Objective To observe the value of machine learning model for predicting the risk of dementia in patients with depression.Methods Totally 31 587 depression patients from UK Biobank database were retrospectively enrolled and divided into dementia group(n=896)or non-dementia group(n=30 691)based on follow-up data showed developed dementia or not,also divided into training set(n=18 952)or test set(n=12 635)at the ratio of 6:4.Based on interviews and questionnaire surveys,a total of 190 factors including demographic characteristics,lifestyle,health status,physical indicators and imaging data were included and screened to establish models with light gradient boosting machine(LightGBM),ridge regression(Ridge)and adaptive boosting(AdaBoost),and the value for predicting the risk of dementia in patients with depression was observed.Results A total of 10 factors were ultimately enrolled,including age,waist circumference,employment status,daytime rest,daytime doze or drowsiness,duration of mobile phone use,number of family members,duration of depression,guilt and seeking medical attention due to psychological issues.Based on the above factors,the models were established.In training set,the area under the curve(AUC)of LightGBM,Ridge and AdaBoost model for predicting dementia risk in patients with depression was 0.914,0.832 and 0.889,respectively,and the differences between each 2 models were significant(all P＜0.05);while in test set,the AUC was 0.866,0.842 and 0.859,respectively,except for LightGBM and AdaBoost,the other with significant differences between each two(both P＜0.05).The calibration curve showed that the LightGBM model had the best fit.Conclusion LightGBM machine learning model was helpful for predicting the risk of dementia in patients with depression.

【Objective】 To investigate the clinical characteristics, long-term follow-up rate, level and control rate of low-density lipoprotein cholesterol (LDL-C) in patients with atherosclerotic cardiovascular disease (ASCVD) aged ≥75 years who underwent percutaneous coronary intervention (PCI) during hospitalization. 【Methods】 We selected ASCVD patients aged ≥75 years with PCI from January 2016 to December 2020 in The First Affiliated Hospital of Xi’an Jiaotong University, collected the baseline data of the patients and the follow-up of 1 month, 3 months, 6 months and 12 months after discharge by HIS system, and analyzed their LDL-C and control rate at each follow-up. 【Results】 A total of 1 129 patients were enrolled in this study, aged 78 (ranging from 75 to 89) years. Among them 72.1% were male; myocardial infarction was the main type of ASCVD (71.5% ); hypertension was the most common risk factor, accounting for 85.2% (717/842), followed by diabetes, 58.6% (493/842); 74.6% met the ultra-high risk criteria of the 2020 Chinese Expert Consensus on Lipid Management in Ultra-High Risk ASCVD Patients, and the LDL-C control rate was only 8.1% . The four routine follow-up rates of 1 129 elderly ASCVD patients were 49.5%, 24.1%, 17.1%, and 24.6%, respectively. The detection rates of LDL-C during follow-up were 26.3%, 5.3%, 10.4%, and 13.8%, respectively. LDL-C control rates in ultra-high risk ASCVD were 59.4%, 45.1%, 37.1%, and 17.6%, respectively, while LDL-C control rates in non-ultra-high risk ASCVD patients were 67.3%, 55.6%, 47.4%, and 44.0%, respectively. 【Conclusion】 The elderly patients with ASCVD-PCI were mainly ultra-high risk patients. The routine follow-up rate and the LDL-C compliance rate during follow-up were low and showed a downward trend.

Objective:To explore the β-amyloid (Aβ) deposition pattern of subjects with the preclinical Alzheimer′s disease (AD), community-derived amnestic mild cognitive impairment (aMCI) and normal cognition (NC) from communities of Shanghai.Methods:According to the inclusion and exclusion criteria, 273 subjects (104 males, 169 females; age (64.2±7.6) years) were recruited from Shanghai community and memory clinics from December 2018 to July 2020. All subjects underwent MRI, 18F-AV45 PET imaging and neuropsychological scale tests and were grouped into AD, aMCI and NC groups based on clinical diagnosis. Differences in demographic information, the neuropsychological scale tests′ scores and positive rate of Aβ deposition among each group were analyzed by one-way analysis of variance or χ2 test. Aβ deposition patterns of AD and MCI groups were analyzed at voxel level, and the differences of Aβ deposition among different groups were compared. Results:Among 273 patients, the positive rates of Aβ deposition in AD, aMCI and NC groups were 84.4%(38/45), 36.4%(20/55) and 23.1%(40/173), respectively ( χ2=58.37, P<0.001). Among AD, aMCI, NC and NC (Aβ-) groups ( n=132), the education years of AD group was the lowest ((9.7±4.6) years; F=8.86, P<0.001). In addition, there were significant differences in the scores of several neuropsychological scale tests among AD, aMCI, NC groups and NC (Aβ-) group ( F values: 27.68-235.50, all P<0.001). Compared with subjects in NC(Aβ-) group, the Aβ depositions in the aMCI and AD groups were widely distributed in the whole cerebral cortex; and AD group had higher Aβ deposition in bilateral frontal, parietal, temporal, occipital lobe, cingulate gyrus and precuneus than aMCI group. Conclusions:The positive rate of Aβ deposition in the preclinical AD population from the Shanghai community is obtained. There are significant different Aβ deposition patterns in subjects at different stages of AD.

Objective:To explore the association of the impaired cognition and the deposition of β-amyloid (Aβ) in normal cognitive (NC) and mild cognitive impairment (MCI).Methods:From December 2018 to January 2021, 305 subjects (113 males, 192 females; age (64.0±7.7) years) who completed neuropsychological tests and MRI in Shanghai Sixth People′s Hospital, Shanghai Jiao Tong University and 18F-florbetapir (AV45) PET imaging in Huashan Hospital, Fudan University were retrospectively analyzed. The subjects were divided into MCI group and NC group based on neuropsychological tests, and each group was further divided into Aβ-positive and Aβ-negative based on PET imaging results. Independent-sample t test, Mann-Whitney U test and χ2 test were used to analyze the data. Results:There were 118 subjects in MCI group and 187 subjects in NC group. The Aβ-positive rate in MCI group (37.3%, 44/118) was higher than that in NC group (26.2%, 49/187; χ2=4.19, P=0.041). The assessment performances of MCI group in general cognitive function, memory function, language function and executive function were inferior to those of NC group ( t values: from -10.63 to -6.31, z values: from -11.01 to -6.03, all P<0.001). The Auditory Verbal Learning Test-Long Delay Recall (AVLT-LDR) score of Aβ-positive subjects was lower than that of Aβ-negative subjects in MCI group (1.00(0.00, 3.00) and 3.00(1.00, 4.00); z=-2.49, P=0.013). The Montreal Cognitive Assessment Basic (MoCA-B) score of Aβ-positive subjects was lower than that of Aβ-negative subjects in NC group (25.29±2.67 and 26.36±2.42; t=-2.61, P=0.010). Conclusion:Compared to Aβ-negative subjects, MCI patients with Aβ-positive perform worse on memory tests, and NC subjects with Aβ-positive perform worse on general cognitive function.

Objective:To establish standard spatial brain template and ROIs template of 11C-methyl- N-2β-carbomethoxy-3β-(4-fluorophenyl)tropane (CFT) PET images for automated quantitative analysis of dopamine transporter (DAT) distribution. Methods:From May 2014 to December 2015, 11C-CFT PET and MRI T 1 brain images of 16 healthy volunteers (3 males, 13 females; age (63.3±6.9) years) from Huashan Hospital, Fudan University were co-registered and smoothed using statistical parametric mapping(SPM)5 software based on MATLAB to create a standard spatial brain template. The ROIs template was established by ScAnVp procedures. These templates were clinically verified by using 11C-CFT PET images of 37 healthy volunteers (23 males, 14 females; age (61.7±7.1) years), 32 Parkinson′s disease (PD) patients (20 males, 12 females; age (61.1±5.4) years), 10 multiple system atrophy with predominant parkinsonism (MSA-P) patients (7 males, 3 females; age (60.8±7.1) years) and 10 progressive supranuclear palsy (PSP) patients (5 males, 5 females; age (58.4±6.1) years) from Huashan Hospital, Fudan University between January 2014 and March 2019. One-way analysis of variance was used to analyze data. Results:Based on the 11C-CFT PET images and MRI T 1 images of healthy volunteers, a standard spatial brain template for normalization of 11C-CFT PET images was created. The ROIs template was established including seven regions: bilateral caudate, anterior putamen, posterior putamen (along the long axis) and the occipital cortex. The ROIs template was accurately aligned in each verification group. The normal reference values of semi-quantitative DAT distribution in caudate, anterior putamen and posterior putamen were obtained (1.84±0.13, 2.18±0.16, 1.77±0.11). The semi-quantitative values of 11C-CFT uptake in each ROI in patients were significantly lower than those in healthy volunteers ( F values: 49.79-283.83, all P<0.05). Conclusion:The established brain templates with accurate spatial alignment for 11C-CFT image analysis can provide foundational tools for the application of 11C-CFT PET imaging in clinical practice and scientific research.

Objective:To explore gene expression and metabolic capacity changes of brown adipose tissue(BAT)during different gestation periods.Methods:A normal pregnancy model was established using C57BL/6J mice, while infertile mice of the same age were served as the control group. The morphological alteration of BAT during pregnancy as well as the gene expression of uncoupling protein 1(UCP1) and other fat browning and mitochondrial marker genes were detected. Moreover, BATs from early and late gestation were selected to screen differentially expressed genes in relation to pregnancy progressing by RNA sequencing(RNA-seq), and gene ontology(GO) and Kyoto gene and gene sequencing(KEGG)were performed.Results:With pregnancy progressing, the size of BAT lipid droplets was substantially enlarged, UCP1 protein expression was decreased( P<0.01), and the fat browning marker genes(Ucp1, Dio2, and Pgc1α)and the mitochondrial marker gene CytC were downregulated( P<0.001). Additionally, a total of 1 298 distinct genes were identified by RNA-seq, 906 of which were upregulated and 392 were downregulated at later stage of pregnancy. GO and KEGG analyses revealed that the differentially expressed genes were mainly enriched in bioregulatory functional pathways such as lipid metabolism, sex steroid hormones, and inflammatory factors. Conclusion:BAT in mice showed larger lipid droplets and reduced thermogenic and metabolic capacity during late gestation, and BAT gene expression was significantly different in different periods of gestation, so reduced metabolic capacity of BAT may contribute to metabolic abnormality during pregnancy.

Objective:To investigate the tau deposition pattern in Alzheimer′s disease (AD) and its correlation with cognition by 18F-MK6240 PET imaging. Methods:From August 2021 to February 2022, 46 elderly people over 55 years old (16 males, 30 females; age (68.9±7.7) years) were included from outpatient and community in Shanghai. Structural brain MRI, β-amyloid (Aβ) PET imaging, tau-PET imaging and comprehensive neuropsychological tests batteries were conducted. The subjects were divided into AD group ( n=16) and normal cognition (NC) group ( n=30) according to the 2018 National Institute on aging and Alzheimer′s Association (NIA-AA) diagnostic criteria. Quantitative analysis was conducted to investigate the tau deposition pattern in AD after preprocessing 18F-MK6240 PET images with MRI images. SUV ratio (SUVR) of brain regions such as entorhinal cortex, hippocampus, parahippocampal gyrus, amygdala, insular lobe, frontal lobe, precuneus, occipital lobe, thalamus and putamen were analyzed, with cerebellum as reference region. The differences of tau deposition in brain regions between AD and NC groups were analyzed by independent-sample t test. The associations between SUVR and Mini-Mental State Examination (MMSE) score and Montreal Cognitive Assessment-Basic (MoCA-B) score were analyzed by Pearson correlation analysis. Results:AD displayed a significant tau deposition in frontal lobes, temporal lobes and parietal lobes compared with NC. SUVR of brain regions in AD group were higher than those in NC group ( t values: 3.37-9.61, all P<0.05). SUVR in brain regions were negatively correlated with MMSE score ( r values: from -0.735 to -0.350, all P<0.05) and MoCA-B score ( r values: from -0.723 to -0.367, all P<0.05). Conclusion:18F-MK6240 PET can demonstrate the tau deposition in the brain of AD patients, and the tau deposition is related to cognitive function.