Objective To explore the feasibility of the multiplexed sensitivity encoding diffusion weighted imaging(MUSE-DWI)sequence in neck MRI,and to compare with traditional single-shot echo-planar imaging diffusion weighted imaging(SS-EPI-DWI)sequence.Methods Thirty healthy volunteers underwent MUSE-DWI and SS-EPI-DWI sequences scanning in neck.Two groups of images were independently scored by two radiologists for magnetic sensitivity artifact,chemical shift artifact,geometric distortion and overall image quality.The noise,signal-to-noise ratio(SNR)and contrast-to-noise ratio(CNR)of the regions of interest(ROI)of the two groups of images were measured and compared on the nasopharyngeal fossa layer,parotid gland layer,glottic layer and thyroid layer.Results Qualitative analysis showed that the image quality scores of MUSE-DWI sequence were significantly better than those of SS-EPI-DWI sequence in terms of magnetic sensitivity artifact,chemical shift artifact,geometric distortion and overall image quality(P<0.001).Quantitative analysis showed that the noise values of ROIs of MUSE-DWI sequence were significantly lower than those of SS-EPI-DWI sequence(P<0.001).The SNR and CNR of ROIs of MUSE-DWI sequence were higher than those of SS-EPI-DWI sequence(P<0.001).Conclusion MUSE-DWI sequence can significantly reduce geometric distortion,magnetic sensitivity artifact and chemical shift artifact,and SNR and CNR of images are significantly increased compared with SS-EPI-DWI sequence,which is more suitable for neck MRI scanning.

ObjectiveTo assess the microstructural involvement of gray matter in recovered COVID-19 patients using Synthetic MRI. MethodsThis study was conducted in 29 recovered COVID-19 patients， including severe group （SG， n=11） and ordinary group （OG， n=18）. Healthy volunteers matched by age， sex， BMI and years of education were selected as a healthy control group （HC=23 cases）. Each subject underwent synthetic MRI to generate quantitative T₁ and T₂ maps， and the T₁ and T₂ maps were segmented into 90 regions of interest （ROIs） using automatic anatomical labeling （AAL） mapping. T₁ and T₂ values for each ROI were obtained by averaging all voxels within the ROIs. The T₁ and T₂ values of the 90 brain regions between the three groups were compared. ResultsRelative to HC， the SG had significantly higher T2 values in bilateral orbital superior frontal gyrus， bilateral parahippocampal gyrus， bilateral putamen， bilateral middle temporal gyrus， bilateral Inferior temporal gyrus， left orbital superior frontal gyrus， left orbital inferior frontal gyrus， left gyrus rectus， left anterior cingulate and paracingulate gyri， right median cingulate and paracingulate gyri， left posterior cingulate gyrus， and left supramarginal gyrus （P＜0.05）； Relative to OG， SG showed significantly increased T₂ values in the left rectus gyrus， left parahippocampal gyrus， bilateral middle temporal gyrus， and bilateral inferior temporal gyrus （P＜0.05）. Relative to HC， the T₁ values of SG were significantly increased in bilateral orbital superior frontal gyrus， left rectus gyrus， left anterior cingulate and paracingulate gyri， right posterior cingulate gyrus， left parahippocampal gyrus， left lingual gyrus， left putamen， left thalamus（P＜0.05）； Relative to OG， the T₁ values of SG were significantly higher in the right posterior cingulate gyrus， right calcarine fissure and surrounding cortex， and left putamen （P＜0.05）. ConclusionsEven after recovering from COVID-19， patients may still have persistent or delayed damage to their brain gray matter structure， which is correlated with the severity of the condition. SyMRI can serve as a sensitive tool to assess the extent of microstructural damage to the central nervous system， aiding in early diagnosis of the disease.

Objective:To investigate the risk factors and prognostic value of the textbook outcome (TO) in patients with advanced gastric cancer (AGC) who underwent neoadjuvant chemotherapy followed by surgical resection.Methods:This is a retrospective cohort study. A total of 253 patients with AGC who underwent neoadjuvant chemotherapy combined with gastrectomy and D2 lymphadenectomy in the Department of Gastric Surgery, Fujian Medical University Union Hospital from January 2010 to December 2019 were retrospectively included. There were 195 males and 58 females, aged (60.3±10.0) years (range: 27 to 75 years). The patients were then divided into the TO group ( n=168) and the non-TO group ( n=85). Multivariate Logistic regression was used to analyze the independent predictors of TO. Univariate and multivariate Cox analysis were used to analyze independent prognosis factors for overall survival (OS) and disease-free survival (DFS). Propensity score matching was performed to balance the TO and non-TO groups, and the Kaplan-Meier method was used to calculate survival rates and draw survival curves. Results:Among the 253 patients, 168 patients (66.4%) achieved TO. The Eastern Cooperative Oncology Group score ( OR=0.488, 95% CI: 0.278 to 0.856, P=0.012) and ypN stage ( OR=0.626, 95% CI:0.488 to 0.805, P<0.01) were independently predictive of TO. Multivariate analysis revealed that TO was an independent risk factor for both OS ( HR=0.662, 95% CI: 0.457 to 0.959, P=0.029) and DFS ( HR=0.687, 95% CI: 0.483 to 0.976, P=0.036). After matching, the 5-year OS rate (42.2% vs. 27.8%) and the 5-year DFS rate (37.5% vs. 27.8%) were significantly higher in the TO group than in the non-TO group (both P<0.05). Furthermore, patients in the non-TO group benefited significantly from postoperative chemotherapy (both P<0.05), but those in the TO group did not (both P>0.05). Conclusion:TO is an independent prognosis factor in patients undergoing neoadjuvant chemotherapy and surgery for AGC and is associated with postoperative chemotherapy benefits.

Objective:To investigate and explore the clinical significance of the expression levels and differences of autophagy related genes ATG3, ATG5, ATG12, ATG16, LC3 and Beclin-1 in peripheral blood mononuclear cells of patients with refractory moderate-to-severe rheumatoid arthritis (RA), who were treated with abatacept.Methods:Peripheral blood samples of 30 patients admitted to the affiliated hospital of North Sichuan Medical College from June 2020 to June 2022 were collected before and after abatacept treatment. Autophagy associated genes were detected by RT-qPCR and, autophagy associated proteins were detected by Western Blot. Correlation analysis with clinical parameters was performed. SPSS26.0 and GraphPad Prism 9.0 were used for statistical analysis, Independent sample t-test was used for comparison between groups, and non-normal distribution data were expressed as M ( Q1, Q3), Spearman correlation analysis was used to analyze the correlation between variables, and P<0.05 was considered statistically significant. Results:①Compared with the mRNA expression levels of ATG12(0.007 6±0.005 9), ATG16(0.003 1±0.002 2) and LC3(0.038 2±0.017 1) before treatment, after 24 weeks treatment with abatacept, the mRNA expression levels of ATG12 (0.011 4±0.003 1) and ATG16 (0.004 2±0.000 7) increased ( t=-2.49, P=0.042; t=-2.15, P=0.038), and the mRNA expression level of LC3 (0.022 6±0.008 3) was decreased ( t=3.28, P=0.003) after 24 weeks of abatacept treatment.②After 24 weeks, the expression level of ATG16 mRNA in the remission group (0.004 8±0.000 8) was higher than that in the non-remission group (0.003 8±0.000 3) ( t=-3.41, P=0.003). The expression level of LC3 mRNA in remission group (0.027 3±0.007 3) was lower than that in non-remission group (0.017 9±0.006 5) ( t=3.69, P=0.017). ③ATG5 mRNA expression level was positively correlated with TJC, ESR and anti-CCP antibody ( r=0.75, P=0.049; r=0.43, P=0.044; r=0.97, P=0.011). The expression level of ATG12 mRNA was negatively correlated with DAS28, ESR and hsCRP ( r=-0.46, P=0.025; r=-0.51, P=0.026; r=-0.41, P=0.031). The expression level of ATG16 mRNA was positively correlated with ESR and hsCRP ( r=0.50, P=0.030; r=0.40, P=0.024). The expression level of Beclin-1 mRNA was significantly higher than TJC, RF-IgG and anti-CCP antibody were negatively correlated ( r=-0.51, P=0.025; r=-0.42, P=0.035; r=-0.81, P=0.043). The expression level of LC-3 mRNA was positively correlated with ESR and hsCRP ( r=0.55, P=0.028; r=0.56, P=0.024). ④Compared with the protein expression level before the treatment, of ATG12 (0.675 3±0.036 3), which (1.547 7±0.080 5) increased after 24 weeks of treatment ( t=-7.80, P=0.001). Compared with the protein expression levels of ATG16 (0.817 1±0.089 0), LC3Ⅱ (0.807 1±0.072 1) and IL-1β (1.129 7±0.118 9) before treatment, 24 weeks after, the protein expression levels of ATG16 (0.424 6±0.103 5), LC3Ⅱ (0.353 7±0.056 9) and IL-1β (0.346 7±0.050 8) decreased ( t=2.62, P=0.042; t=2.88, P=0.045; t=2.25, P=0.038) 24 weeks after treatment. Conclusion:Autophagy related genes is associated with several clinical presentations and disease activity. The results of this study suggest that autophageius are involved in the pathogenesis of RA. Abatacept may be a potential autophage modulator by regulating autophagy related genes including ATG12、ATG16 and LC3.

Objective:To investigate the risk factors and prognostic value of the textbook outcome (TO) in patients with advanced gastric cancer (AGC) who underwent neoadjuvant chemotherapy followed by surgical resection.Methods:This is a retrospective cohort study. A total of 253 patients with AGC who underwent neoadjuvant chemotherapy combined with gastrectomy and D2 lymphadenectomy in the Department of Gastric Surgery, Fujian Medical University Union Hospital from January 2010 to December 2019 were retrospectively included. There were 195 males and 58 females, aged (60.3±10.0) years (range: 27 to 75 years). The patients were then divided into the TO group ( n=168) and the non-TO group ( n=85). Multivariate Logistic regression was used to analyze the independent predictors of TO. Univariate and multivariate Cox analysis were used to analyze independent prognosis factors for overall survival (OS) and disease-free survival (DFS). Propensity score matching was performed to balance the TO and non-TO groups, and the Kaplan-Meier method was used to calculate survival rates and draw survival curves. Results:Among the 253 patients, 168 patients (66.4%) achieved TO. The Eastern Cooperative Oncology Group score ( OR=0.488, 95% CI: 0.278 to 0.856, P=0.012) and ypN stage ( OR=0.626, 95% CI:0.488 to 0.805, P<0.01) were independently predictive of TO. Multivariate analysis revealed that TO was an independent risk factor for both OS ( HR=0.662, 95% CI: 0.457 to 0.959, P=0.029) and DFS ( HR=0.687, 95% CI: 0.483 to 0.976, P=0.036). After matching, the 5-year OS rate (42.2% vs. 27.8%) and the 5-year DFS rate (37.5% vs. 27.8%) were significantly higher in the TO group than in the non-TO group (both P<0.05). Furthermore, patients in the non-TO group benefited significantly from postoperative chemotherapy (both P<0.05), but those in the TO group did not (both P>0.05). Conclusion:TO is an independent prognosis factor in patients undergoing neoadjuvant chemotherapy and surgery for AGC and is associated with postoperative chemotherapy benefits.

Human beings are inevitably exposed to toxic substances as a result of influences of potential contamination factors in the environment,food and medicines,which poses a threat to human health.In order to effectively screen and prevent the exposure or intake of such substances,it is neces-sary to develop in vitro assays for the detection and toxicity evaluation of toxic substances.High content screening(HCS)has been recognized as an important tool for toxicity testing and risk assessment of compounds due to its high throughput and automation advantages,and has been widely used in in vitro toxicology research.In this review,we described the system components of HCS and its workflow in toxicity screening and toxicity evaluation by focusing on cases of their application in toxicity detection and evaluation studies,including the cytotoxicity,hepatotoxicity,nephrotoxicity,genotoxicity,neurotox-icity,cardiotoxicity,and developmental toxicity.In addition,the applications and developments of machine learning in HCS were explored,especially to the advantages of supervised and unsupervised machine learning strategies for high throughput image screening and data analysis.Finally,the future applications of HCS in toxicity screening and evaluation are outlined,especially in terms of binding new models and gene editing technology.

Objective:To investigate the influencing factors of operation time for laparos-copic sleeve gastrectomy (LSG) and analyze the learning curve of LSG in sarcopenic obesity (SO) and non-sarcopenic obesity (NSO).Methods:The retrospective cohort study was conducted. The clinical data of 240 obesity patients who underwent LSG in the Fujian Medical University Union Hospital from January 2018 to June 2022 were collected. There were 52 males and 188 females, aged (30±8)years. Patients underwent L3 vertebral body horizontal axial computer tomography (CT) scanning before and after receiving LSG to accurately segment muscles and fats. Observation indicators: (1) treatment and follow-up; (2) influencing factors of operation time for LSG; (3) cumulative sum (CUSUM) of learning curve; (4) comparison of clinical data between patients in the initial and profi-cient stages. Measurement data with normal distribution were represent as Mean± SD, and comparison between groups was conducted using the t test. Measurement data with skewed distribution were represented as M(IQR), and comparison between groups was conducted using the non-parameter test. Count data were described as absolute numbers, and comparison between groups was conducted using the chi-square test. Univariate and multivariate analyses were conducted using the Logistic regression model. The CUSUM of learning curve was calculated and the fitting process was conducted on scatter plot of learning curves. Results:(1) Treatment and follow-up. Of the 240 patients, there were 97 cases of SO and 143 cases of NSO. All 240 patients underwent LSG successfully, without conversion to open surgery. The operation time of 240 patients was (108±23)minutes. None of patient died during the perioperative period and all patients underwent follow-up during the postoperative 6 months. (2) Influencing factors of operation time for LSG. Results of multivariate analysis showed that SO was an independent factor influencing operation time for LSG ( odds ratio=2.207, 95% confidence interval as 1.207-4.038, P<0.05). (3) CUSUM of learning curve. Results of CUSUM of operation time in patients of SO and NSO showed that the best fit equation of patients of SO was y=-4E-08x 6+1E-05x 5-0.001 1x 4+0.063 1x 3-1.89x 2+28.126x-48.671 (x means the number of surgical cases), with goodness-of-fit R 2 as 0.833, and the best fit equation of patients of NSO was y=3E-09x 6-1E-06x 5+0.000 2x 4-0.010 9x 3+0.063 8x 2+12.053x-65.025 (x means the number of surgical cases), with goodness-of-fit R 2 as 0.716. Based on the trend of CUSUM of learning curve of operation time, the peak value of number of surgical cases in patients of SO and NSO was 81 and 36, respec-tively, which was used to divide the learning curve as two stages of the initial stage and the proficient stage. (4) Comparison of clinical data between patients in the initial and proficient stages. ① Of the 97 patients of SO, there were 81 cases and 16 cases in the initial stage and the proficient stage of LSG, with the operation time, postoperative duration of hospital stay as (119±23)minutes, (5.9±2.3)days and (106±21)minutes, (4.7±0.5)days, showing significant differences between them ( t=2.074, 2.147, P<0.05). ②Of the 143 patients of NSO, there were 36 cases and 107 cases in the initial stage and the proficient stage of LSG, with gender (female), height, preoperative body mass, defatted body mass, operation time, postoperative duration of hospital stay, body mass at postoperative 6 month, body mass index (BMI) at postoperative 6 month, percentage of excess weight loss (EWL%) at postoperative 6 month, cases with EWL% >100% at postoperative 6 month, excess BMI at post-operative 6 month as 20, (170±10)cm, (110±25)kg, (57±12)kg, (108±22)minutes, (6.1±1.6)days, (80±16)kg, (27.63±4.22)kg/m2, 83%±35%, 9, 1.99(6.03)kg/m2 and 87, (164±8)cm, (99±20)kg, (52±12)kg, (100±19)minutes, (4.7±1.1)days, (71±16)kg, (25.89±4.48)kg/m2, 103%±42%, 48, 0.31(5.82)kg/m2, showing significant differences between them ( χ2=9.484, t=3.266, 2.424, 2.141, 2.137, 5.821, 2.740, 1.993, -2.524, χ2=4.432, Z=-2.300, P<0.05). Conclusions:SO is an independent factor influencing operation time for LSG. It is suggested that the surgeons need to finish 81 cases and 36 cases master LSG in patients of SO and NSO.

Objective:To investigate the mechanism of action and prognostic value of Dynamin 3 (DNM3) in gastric cancer.Methods:The bioinformatic analysis, experimental study and retrospective cohort study was conducted. The clinicopathological data, fresh gastric cancer tissues, paired normal tissues and the corresponding paraffin sections of 153 gastric cancer patients who underwent radical gastrectomy in Fujian Medical University Union Hospital from January 2013 to July 2018 were collected. Tissues and the corresponding paraffin sections were subjected to quanti-tative real-time polymerase chain reaction, immunoblotting assay, flow cytometric cell cycle assay and immunohistochemical staining, respectively, and clinicopathological data were used for prognostic analysis. The stomach adenocarcinoma (STAD) dataset from the Cancer Genome Atlas (TCGA) database was collected for bioinformatic analysis. Observation indicators: (1) DNM3 gene expression in TCGA-STAD in gastric cancer; (2) mutations and copy number alterations of DNM3 in gastric cancer; (3) methylation level of promoter of DNM3 in gastric cancer; (4) relative protein expression of DNM3 and p53 in gastric cancer; (5) DNM3 correlation and enrichment analysis; (6) ratio of G0/G1 phase, S phase and G2/M phase of cell cycle progression; (7) correlation between immune cell infiltration and DNM3 in gastric cancer; (8) correlation between results of immunohistochemical (IHC) staining and clinical features; (9) analysis of independent factors influencing 5-year overall survival rate of gastric cancer patients. Measurement data with normal distribution were represented as Mean±SD, and comparison among multiple groups was conducted using the ANOVA and further comparison between two groups was conducted using the LSD. Comparison between two groups was conducted using the t test. Measurement data with skewed distribution were represented as M( Q1, Q3), and comparison between groups was conducted using the Mann-Whitney U test. Count data were described as absolute numbers or percentages, and compari-son between groups was conducted using the chi-square test or Fisher exact probability. Comparison of ordinal data was conducted using the rank sum test. The Pearson correlation coefficient or Spearman correlation coefficient was used to test the correlation between groups. Univariate and multivariate analyses were conducted using the COX proportional risk regression model. The Kaplan-Meier method was used to draw survival curves and calculate survival rates, and the Log-Rank test was used for survival analysis. The Benjamini-Hochberg false discovery rate correction was used for adjusting of the P-value. Results:(1) DNM3 gene expression in TCGA-STAD. The expression levels of DNM3 gene in the 27 tumor tissues and paired normal tissues of the TCGA-STAD database were 0.775(0.605,1.161) and 1.216(0.772,1.681), showing a significant difference between them ( Z=?2.64, P<0.05). The messenger RNA (mRNA) expression levels of DNM3 gene in 48 pairs of gastric cancer tissues and paired normal tissues of the author′s center were 4.370(2.870,6.040) and 2.520(0.850,4.170), showing a significant difference between them ( Z=?4.39, P<0.05). (2) Mutations and copy number alterations of DNM3 in gastric cancer. There were 16 gastric cancer patients in the TCGA-STAD database with DNM3 mutation or somatic copy number alterations, including 6 cases with missense mutations, 1 case with truncated mutation, 8 cases with copy number gain and 1 case with copy number loss. The mRNA expression levels of DNM3 gene before and after mutation in the 370 gastric cancer patients of the TCGA-STAD database were 6.13(5.40,7.08) and 5.02(3.98,5.46), showing a significant difference between them (Log 2FC=?1.11, Z=?2.59, P<0.05). (3) Methylation level of promoter of DNM3 in gastric cancer. There were 372 gastric cancer patients in the TCGA-STAD database undergoing DNM3 methylation and mRNA examinations, and the results showed that levels of methylation and mRNA expression of DNM3 was 0.198 (-0.458, 0.301) and 6.014 (5.141, 6.628), respectively. The levels of methylation in DNM3 was negatively correlated with its mRNA expression ( r=?0.38, P<0.05). Results of follow-up in 32 patients showed that the 3-year overall survival rate of 16 cases with high levels of methylation in DNM3 and 16 cases with low levels of methylation in DNM3 was 18.8% and 41.3%, respectively, showing a significant difference between them ( hazard ratio=1.40, P<0.05). Results of immunoblot-ting assay showed that the relative expression level of DNM3 protein in the AGS cells treated with 0, 0.5, and 1.0 μmol/L of 5-azacytidin was 0.270±0.020, 0.357±0.051 and 0.599±0.039, respectively, showing a significant difference among the three groups ( F=57.84, P<0.05). The relative expression level of DNM3 protein in the HGC-27 cells treated with 0, 0.5, and 1.0 μmol/L of 5-azacytidin was 0.316±0.038, 0.770±0.031 and 0.877±0.052, respectively, showing a significant difference among the three groups ( F=156.30, P<0.05). (4) Relative protein expression of DNM3 and p53 in gastric cancer. Results of immunoblotting assay showed that the relative expression of DNM3 and p53 protein was 0.688±0.047 and 0.872±0.041 in the AGS cells transfected with pCMV-DNM3 plasmid, versus 0.249±0.029 and 0.352±0.020 in the AGS cells transfected with control plasmid, showing significant differences in the above indicators between the two types of cells ( t=13.77,19.74, P<0.05). The relative expression of DNM3 and p53 protein was 0.969±0.069 and 1.464±0.081 in the HGC-27 cells transfected with pCMV-DNM3 plasmid, versus 0.456±0.048 and 0.794±0.052 in the HGC-27 cells transfected with control plasmid, showing significant differences in the above indicators between the two types of cells ( t=10.57, 12.06, P<0.05). (5) DNM3 correlation and enrichment analysis. Results of correlation analysis showed that DNM3 was positively correlated with genes such as RBMS3, CNTN4 and PDE1A ( r=0.52, 0.52, 0.50, P<0.05) and negatively correlated with genes such as SLC25A39, PAICS and GAPDH ( r=?0.41, ?0.40, ?0.40, P<0.05) in gastric cancer. Results of gene set enrichment analysis showed that the set of genes related to ribosome and oxidative phosphorylation were upregulated in gastric cancer patients with DNM3 low expression [normalized enrichment score (NES)=?3.30, ?2.16, P<0.05], while the set of genes related to immunomodulatory interactions between lymphocytes and non-lymphoid cells were upregulated in gastric cancer patients with DNM3 high expression (NES=1.67, P<0.05). Results of gene ontology analysis showed that the low expression of DNM3 was associated with the separation of mitotic sister chromatid (No.0000070), nonsense-mediation of nuclear transcriptional mRNA catabolic process, sister chromatid separation (No.0000819), nuclear transcriptional mRNA catabolic process and regulation of oxidative phos-phorylation (NES=?2.29, ?3.10, ?2.33, ?2.56, ?2.68, P<0.05). Results of Kyoto encycl opedia of genes and genomes analysis showed that metabolic pathway related to ribosome and oxidative phosphory-lation were upregulated and crosstalked in gastric cancer with low expression of DNM3 (NES=?3.34, ?2.21, P<0.05). (6) Ratio of G0/G1 phase, S phase and G2/M phase of cell cycle progression. Results of flow cytometric cell cycle experiments showed that the proportions of G0/G1 phase, S phase and G2/M phase in the cell cycle was 65.1%±3.0%, 17.3%±3.0% and 17.6%±1.0% in the AGS cells transfected with pCMV-DNM3 plasmid, versus 53.4%±4.0%, 26.3%±2.0% and 20.3%±3.0% in the AGS cells transfected with control plasmid, showing significant differences in the proportions of G0/G1 phase and S phase in the two types of cells ( t=4.05, 4.32, P<0.05). (7) Correlation between immune cell infiltration and DNM3 in gastric cancer. Results of immune cell infiltration examination showed that the expression level of DNM3 was positively associated with mast cells, NK cells, pDCs, B cells, follicular helper T cells, effector memory T cells, T cells, central memory T cells, CD8 T cells, DC cells, macrophages, γ-δ T cells (Tgd), iDCs and eosinophils infiltration (Spearman correlation coefficients as 0.41, 0.29, 0.26, 0.20, 0.22, 0.22, 0.13, 0.16, 0.15, 0.14, 0.14, 0.17, 0.18, 0.22, P<0.05) and negatively associated with Th17 cell, Th2 cells and NK CD56 dim cells infiltration ( r=?0.18, ?0.23, ?0.10, P<0.05). (8) Correlation between results of IHC staining and clinical features. Results of IHC staining analysis showed that the IHC score of DNM3 was 3(2,4) in the 105 gastric cancer tissues, versus 6(4,9) in the 105 paired normal tissues, showing a significant difference between them ( Z=-7.35, P<0.05). There were significant differences in gender, tumor location and N stating between the 70 patients with low expression of DNM3 and the 35 patients with high expression of DNM3 ( χ2=4.29, 7.67, 6.86, P<0.05). (9) Analysis of independent factors influencing 5-year overall survival rate of gastric cancer patients. Results of multivariate analysis showed that stage pT3?4 and low IHC score of DNM3 were independent risk factors for 5-year overall survival rate of gastric cancer patients ( hazard ratio=1.91, 0.51, 95% confidence interval as 1.06?3.43, 0.26?0.98, P<0.05). The 5-year overall survival rate was 44.3% in patients with low expression of DNM3, versus 65.7% in gastric cancer patients with high expression of DNM3, showing a significant difference between them ( χ2=5.02, P<0.05). Conclusion:DNM3 is a tumor suppressor and an independent predictor of poor prognosis for gastric cancer, which may regulate gastric cancer cell cycle and immunosuppression in the tumor microenvironment through methylation.

Objective:To investigate the construction and application value of a predictive model for prolonged surgical duration in Da Vinci robotic radical gastrectomy for gastric cancer.Methods:The retrospective cohort study was conducted. The clinicopathological data of 534 patients who underwent Da Vinci robotic radical gastrectomy for gastric cancer in the Fujian Medical University Union Hospital from August 2016 to August 2021 were collected. There were 389 males and 145 females, aged (60±11)years. All 534 patients were randomly divided into the training dataset of 374 cases and the validation dataset of 160 cases with a ratio of 7∶3 based on random number method in the SPSS 25.0 software. Observation indicators: (1) incidence of prolonged surgical duration; (2) intraoperative and postoperative conditions in patients with prolonged surgical duration and without prolonged surgical duration; (3) complications in patients with prolonged surgical duration and without prolonged surgical duration; (4) analysis of risk factors influencing prolonged surgical duration; (5) construction and evaluation of an artificial neural network predictive model for pro-longed surgical duration. Measurement data with normal distribution were represented as Mean± SD, and comparison between groups was conducted using the independent sample t test. Measurement data with skewed distribution were represented as M( Q1, Q3), and comparison between groups was conducted using the Mann-Whitney U test. Count data were described as absolute numbers or per-centages, and comparison between groups was conducted using the chi-square test or Fisher exact probability. Comparison of ordinal data was analyzed using the nonparametric test. Univariate and multivariate analyses were conducted using the Logistic regression model. Based on the results of univariate analysis, a multilayer perceptron was employed to train an artificial neural network pre-dictive model for prolonged surgical duration. The receiver operating characteristic (ROC) curve was drawn, and the area under curve (AUC), the accuracy, sensitivity, specificity, positive predictive value, and negative predictive value were used to assess the model′s performance. Results:(1) Incidence of prolonged surgical duration. Of 534 patients, 284 cases underwent total gastrectomy, and 250 cases underwent distal gastrectomy, with operation time of (206±42)minutes and (187±36)minutes, res-pectively. Cases with prolonged surgical duration and without prolonged surgical duration who under-went total gastrectomy were 41 and 243, and cases with prolonged surgical duration and without prolonged surgical duration who underwent distal gastrectomy were 40 and 210. The gender (male, female), age, body mass index (BMI), tumor diameter, tumor location (upper stomach, middle stomach, lower stomach, mixed type), cases with neoadjuvant therapy, cases with preoperative American Society of Anesthesiologists (ASA) score as 1, 2, 3, cases with clinical T staging as stage T1, stage T2, stage T3, stage T4a, cases with clinical N staging as stage N0, stage N1, stage N2, stage N3, cases with clinical TNM staging as stage Ⅰ, stage Ⅱ, stage Ⅲ, cases with surgical resection scope as total gastrec-tomy or distal gastrectomy, cases with digestive tract reconstruction method as Billroth-Ⅰ anasto-mosis, Billroth-Ⅱ anastomosis, Roux-en-Y anastomosis, cases with surgeon experiences as ≤20 cases or >20 cases were 61,20, (61±9)years, (24±3)kg/m2, 4.0(2.5, 5.0)cm, 34, 10, 33, 4, 1, 3, 73, 5, 3, 6, 26, 46, 14, 41, 19, 7, 5, 13, 63, 41, 40, 1, 33, 47, 5, 76 in the 81 patients with prolonged surgical duration, versus 328, 125, (60±11)years, (23±3)kg/m2, 3.5(2.0, 5.0)cm, 129, 71, 227, 26, 6, 45, 382, 26, 73, 100, 118, 162, 211, 180, 52, 10, 138, 108,207, 243, 210, 13,200, 240, 15, 438 in the 453 patients without prolonged surgical duration, showing significant differences in the BMI, clinical T staging, clinical N staging, clinical TNM staging ( t=-3.68, Z=-4.63, -5.53, -5.56, P<0.05), and no significant difference in the gender, age, tumor diameter, tumor location, preoperative ASA score, surgical resec-tion scope, digestive tract reconstruction method, and surgeon experiences ( χ2=0.29, t=-0.95, Z=-1.27, χ2=5.92, Z=-1.46, χ2=0.25, 1.35, 0.87, P>0.05). There was no significant difference in cases with neoadjuvant therapy between them ( P>0.05). (2) Intraoperative and postoperative conditions in patients with prolonged surgical duration and without prolonged surgical duration. The operation time, volume of intraoperative blood loss, the number of lymph nodes dissected, time to postopera-tive first ambulation, time to postoperative anal exhaust, time to postoperative first intake of liquid diet, time to postoperative first intake of semi-liquid diet, duration of postoperative hospital stay were (261±34)minutes, 50(30, 50)mL, 39±15, (2.3±0.6)days, (3.4±0.9)days, (4.1±1.2)days, (5.7±1.2)days, 8.0(7.0, 9.0)days in the 81 patients with prolonged surgical duration, versus (186±29)minutes, 30(20,50)mL, 42±14, (2.2±0.6)days, (3.4±0.8)days, (4.1±1.1)days, (5.7±1.4)days, 8.0(7.0, 9.0)days in the 453 patients without prolonged surgical duration, showing significant differences in operation time, volume of intraoperative blood loss ( t=-20.46, Z=-3.32, P<0.05), and no significant difference in the number of lymph nodes dissected, time to postoperative first ambulation, time to postopera-tive anal exhaust, time to postoperative first intake of liquid diet, time to first intake of semi-liquid diet, duration of postoperative hospital stay ( t=1.87, -0.87, -0.16, 0.28, 0.03, Z=-1.45, P>0.05). (3) Complications in patients with prolonged surgical duration and without prolonged surgical duration. The overall incidence of complications, incidence of surgical complications (abdominal infection, anastomotic fistula, abdominal bleeding, incision-related complications, intestinal obstruction, lymphatic fistula), incidence of medical complications (pulmonary infection, liver-related complications) were 22.22%(18/81), 0, 0, 2.47%(2/81), 0, 8.64%(7/81), 1.23%(1/81), 12.35%(10/81), 1.23%(1/81) in the 81 patients with prolonged surgical duration, versus 13.47%(61/453), 2.65%(12/453), 0.44%(2/453), 1.77%(8/453), 0.44%(2/453), 3.31%(15/453), 0, 7.28%(33/453), 1.55%(7/453) in the 453 patients without prolonged surgical duration, showing a significant difference in the overall incidence of complications ( χ2=4.18, P<0.05), and no significant difference in the incidence of abdo-minal infection, anastomotic fistula, abdominal bleeding, incision-related complications, intestinal obstruction, lymphatic fistula, liver-related complications ( P>0.05). There was no significant difference in the incidence of pulmonary infection between them ( χ2=2.38, P>0.05). (4) Analysis of risk factors influencing prolonged surgical duration. Results of univariate analysis showed that BMI ≥25 kg/m2, tumor located in the lower stomach, clinical T3-T4a stage, clinical N1-N3 stage were correlated factors influencing prolonged surgical duration in Da Vinci robotic radical gastrectomy for gastric cancer ( odds ratio=1.88, 0.40, 6.24, 6.51, 3.08, 3.39, 17.15, 95% confidence interval as 1.03-3.42, 0.21-0.76, 1.40-27.76, 1.50-28.30, 1.43-6.60, 1.29-8.92, 4.84-60.74, P<0.05). Results of multivariate analysis showed that BMI ≥25 kg/m2, clinical T3 stage, clinical N3 stage were independent risk factors influencing prolonged surgical duration in Da Vinci robotic radical gastrectomy for gastric cancer ( odds ratio=2.31, 4.97, 11.08, 95% confidence interval as 1.19-4.46, 1.05-23.55, 2.72-45.13, P<0.05). (5) Construction and evaluation of an artificial neural network predictive model for pro-longed surgical duration. The BMI, tumor location, clinical T staging, and clinical N staging were incorporated into a multilayer perceptron to construct an artificial neural network predictive model for prolonged surgical duration. Results of ROC curve showed that the AUC, accuracy, sensitivity, specificity, positive predictive value, negative predictive value of the predictive model in the training dataset were 0.73 (95% confidence interval as 0.68-0.78), 91.4%, 68.1%, 94.8%, 65.3%, 95.4%. The above indicators of the predictive model in the validation dataset 0.72 (95% confidence interval as 0.65-0.79), 88.1%, 67.6%, 93.7%, 74.2%, 91.5%. Conclusions:BMI ≥25 kg/m2, clinical T3 stage, clinical N3 stage are independent risk factors influencing prolonged surgical duration in Da Vinci robotic radical gastrectomy for gastric cancer. The artificial neural network predictive model con-structed based on BMI, tumor location, clinical T staging, and clinical N staging can effectively predict patients at high risk of prolonged surgical duration in Da Vinci robotic radical gastrectomy for gastric cancer.

Objective:To explore the molecular mechanism of cell death of the peripheral blood mononuclear cells (PBMCs) of patients with primary gouty arthritis, and provide new idea for the treatment of gout.Methods:Peripheral blood samples and clinical data were collected from 30 patients with acute gout (AG), 30 patients with intermittent gout (IG) and 40 healthy controls(HC). Real-time fluorescence quantitative detection of cell apoptosis related molecules, including the mRNA expression level of nucleotide binding oligomerization domain like domain like receptor protein 3(NLRP3), cysteine aspartic proteinase-1/4/5 (caspase-1/4/5), Gasdermin A/B/C/E. And NLRP3, precursor caspase-1 (pro-caspase-1), clipped caspase-1 (caspase-1 + p10), Gasdermin D(GSDMD), N segment GSDMD (GSDMD-N), precursor IL-1β (pro IL-1β), mature IL-1β (clevated IL-1β)were detected by western blot. The measurement data of normal or approximate normal distribution were analyzed by independent sample t test or one-way variance analysis (ANOVA), the measurement data of non-normal distribution were analyzed by Mann-Whitney U test or Kruskal-Wallis H test, and the counting data was compared by Chi-square test. Pearson's correlation analysis was used for the continuous variables with normal distribution, and Spearman's correlation analysis was used for the continuous variables with non-normal distribution. The logistic regression analysis was used to assess risk factors. Results:① There were no significant differences in MPR and BMI between AG and IG ( χ2=0.64, P=0.426; t=0.04, P=0.972), and there was significant difference in disease course [25.0 (9.8, 63.0), 54.0 (33.0, 102.0)mouth, Z=2.01, P=0.044]. Comparison of labora-tory parameters: there were statistical significant differences in ESR between AG and IG ( t=5.24, P<0.001), eGFR, GR, LY, RBC, HCT, UA, Creatinin, ALT and AST. ② In the three groups, the expression lev-els of caspase-1, GSDMC, GSDMD, GSDME, NLRP3 mRNA were statistically significantly different. In AG and IG groups, mRNA expression levels of caspase-1 (1.55±0.62), (1.58±0.62), GSDMD (4.7±1.4), (3.5±1.53), NLRP3 [2.63(2.03, 4.10), 2.39(1.57, 3.49)] were higher than those of the HC group [(1.24±0.59), 1.16±0.71, 1.16 (0.50, 2.34)] ( P=0.037, P=0.023, P<0.001, P<0.001, P<0.001, P<0.001). In IG group, mRNA expression levels of GS-DMD (3.53±1.53) were lower than those of AG group (4.68±1.43) ( P<0.001).The mRNA expression levels of GS-DMC and GSDME [0.57(0.33, 0.78), (0.32±0.15)]were lower than those of the HC group [0.80 (0.47, 1.86), (1.06 ± 0.36) ( P=0.004, P<0.001), and the mRNA expression levels of GSDME (0.62±0.29) in the IG group were lower ( P=0.004, P<0.001), However, in the IG group, GSDMC and GSDME [0.87 (0.51, 1.53), (0.62±0.29)] were higher than those in the AG group [0.57 (0.33, 0.78), (0.32±0.15)] ( P=0.003, P<0.001). ③ The expression levels of NLRP3, pro-caspase-1, caspase-1 + p10, GSDMD, GSDMD-N, pro-IL-1β, clevated IL-1β protein were statistically different among the three groups [( F=50.04, P<0.001; F=9.65, P=0.013; F=30.71, P=0.001; F=7.38, P=0.024; F=23.66, P=0.001; F=30.11, P=0.001; F=6.01, P=0.036]. The expression of NLRP3 protein in the AG group (1.14±0.12) was significantly higher than that in the IG and HC group (0.35±0.18), (0.17±0.03) (all P=0.001), the expression levels of Pro caspase-1, caspase-1+p10 protein in the AG (1.11±0.15), (0.93±0.38) and IG (0.98±0.14), (1.14±0.17) group were higher than those in the HC (0.42±0.28), (0.29±0.16) ( P=0.006, P=0.015). The expression levels of GSDMD protein in the AG group (1.04±0.16) were higher than those in the IG and HC group(0.53±0.26), (0.39±0.22) ( P=0.029, P=0.011). The expression level of GSDMD-N protein in the AG and IG group (0.97±0.06), (0.90±0.04) was higher than that in the HC (0.27±0.23) ( P=0.001, P=0.001). The expression level of pro-IL-1β protein in the AG group (1.01±0.06) was significantly higher than that in the IG and HC group (0.32±0.14), (0.64±0.11) ( P<0.001, P=0.006), but lower than that in the HC (0.64±0.11) ( P=0.011). The expression of clevated IL-1β protein was higher in the AG group (1.08±0.20) than in the HC group (0.33±0.24) ( P=0.014). ④ Negative correlation between NLRP3, GSDMD and LY ( r=-0.32, P=0.001; r=-0.24, P=0.017) and positive correlation between GSDMD and WBC, GR ( r=0.43, P<0.001; r=0.23, P=0.019) were found and Logistic regression analysis showed that the GSDMD and NLRP3 were risk factors for AG [ OR ( 95%CI)=11.29 (3.92, 32.48), P<0.001; OR( 95%CI)=2.21(1.00, 4.85), P=0.049]. GSDMD was risk factor for IG [ OR( 95%CI)=6.84(2.52, 18.53), P<0.001]; While GSDMD was the protective factor for IG [ OR( 95%CI)=0.61(0.41, 0.30), P=0.013]. Conclusion:The expression's of NLRP3, Caspase-1 and GSDMD are increased in PBMCs of AG patients, while the expression's of GSDMC and GSDME are decreased. NLRP3/Caspase-1/GSDMD may be associated with the onset of acute gouty arthritis.