Objective To analyze the influencing factors for postoperative anastomotic leak (AL) in carcinoma of the esophagus and gastroesophageal junction and construct a nomogram predictive model. Methods The patients who underwent radical esophagectomy at Jinling Hospital Affiliated to Nanjing University School of Medicine from January 2018 to June 2020 were included in this study. Relevant variables were screened using univariate and multivariate logistic regression analyses. A nomogram was then developed to predict the risk factors associated with postoperative AL. The predictive performance of the nomogram was validated using the receiver operating characteristic (ROC) curve. Results A total of 468 patients with carcinoma of the esophagus and gastroesophageal junction were included in the study, comprising 354 males and 114 females, with a mean age of (62.8±7.2) years. The tumors were predominantly located in the middle or lower esophagus, and 51 (10.90%) patients experienced postoperative AL. Univariate logistic regression analysis indicated that age, body mass index (BMI), tumor location, preoperative albumin levels, diabetes mellitus, anastomosis technique, anastomosis site, and C-reactive protein (CRP) levels were potentially associated with AL (P<0.05). Multivariate logistic regression analysis identified age, BMI, tumor location, diabetes mellitus, anastomosis technique, and CRP levels as independent risk factors for AL (P<0.05). A nomogram was developed based on the findings from the multivariate logistic regression analysis. The area under the receiver operating characteristic (ROC) curve was 0.803, indicating a strong concordance between the actual observations and the predicted outcomes. Furthermore, decision curve analysis demonstrated that the newly established nomogram holds significant value for clinical decision-making. Conclusion The predictive model for postoperative AL in patients with carcinoma of the esophagus and gastroesophageal junction demonstrates strong predictive validity and is essential for guiding clinical monitoring, early detection, and preventive strategies.

In recent years, robot-assisted esophagectomy has become increasingly widespread, but the esophagogastric anastomosis step remains relatively complex and cumbersome. Currently, commonly used gastrointestinal reconstruction anastomosis techniques include end-to-end anastomosis, end-to-side anastomosis, and side-to-side anastomosis. Depending on the anastomosis method, they can be further divided into manual anastomosis and mechanical anastomosis, with common instruments including circular staplers and linear staplers. In esophageal cancer surgery, the choice of esophagogastric anastomosis technique is typically based on the tumor’s location and size as well as the surgeon’s preference. Each anastomosis technique has its advantages and disadvantages. With continuous improvements in anastomosis techniques and updates in stapling instruments, the incidence of complications after esophagogastric anastomosis has been effectively reduced. However, safely and efficiently completing gastrointestinal reconstruction during surgery remains a significant challenge. Scholars have made extensive explorations in this field, actively proposing and achieving various reconstruction methods, leading to significant progress. This article reviews the research progress of robot-assisted esophagogastric anastomosis techniques from both the anastomosis techniques and methods perspectives.

Background Atmospheric fine particulate matter (PM_2.5) can disrupt the metabolic homeostasis of the liver and accelerate the progression of liver diseases, but there are few studies on the effects of sub-chronic PM_2.5 exposure on the liver metabolome. Objectives To investigate the effects of sub-chronic exposure to concentrated PM_2.5 on hepatic metabolomics in mice by liquid chromatography-mass spectrometry (LC-MS), and to identify potentially affected metabolites and metabolic pathways. Methods Twelve male C57BL/6J (6 weeks old) mice were randomly divided into two groups: a concentrated PM_2.5 exposure group and a clean air exposure group. The mice were exposed to concentrated PM_2.5 using the "Shanghai Meteorological and Environmental Animal Exposure System" at Fudan University. The exposure duration was 8 h per day, 6 d per week, for a total of 8 weeks. The mice's liver tissues were collected 24 h after the completion of exposure. LC-MS was performed to assess changes in the hepatic metabolome. Orthogonal partial least squares discriminant analysis and t-test were employed to identify differentially regulated metabolites between the two groups under the conditions of variable important in projection (VIP)≥1.0 and P<0.05. Metabolic pathway enrichment analysis was performed using MetaboAnalyst 5.0 software and the Kyoto Encyclopedia of Genes and Genomes (KEGG). Results A total of 297 differentially regulated metabolites were identified between the concentrated PM_2.5 exposure group and the clean air group. Among these metabolites, 142 were upregulated and 155 were downregulated. A total of 38 metabolic pathways were altered, with 7 pathways showing significant perturbation (P<0.05). These pathways involved amino acid metabolism, glucose metabolism, nucleotide metabolism, as well as cofactor and vitamin metabolism. The 7 significant metabolic pathways were pantothenic acid and coenzyme A biosynthesis; purine metabolism; amino sugar and nucleotide sugar metabolism; arginine biosynthesis; alanine, aspartate and glutamate metabolism; aminoacyl-tRNA biosynthesis; and fructose and mannose metabolism. Conclusion The results from metabolomics analysis suggest that sub-chronic exposure to PM_2.5 may disrupt hepatic energy metabolism and induce oxidative stress damage. Aspartic acid, succinic acid, ornithine, fumaric acid, as well as purine and xanthine derivatives, were identified as potential early biomarkers of hepatic response to sub-chronic PM_2.5 exposure.

OBJECTIVE To analyze the effect of Huanglian Jiedu Decoction(HLJDD)on the intestinal flora and metabolites of Parkinson's disease(PD)model mice,and explore the mechanism of HLJDD in intervening in PD based on 16S rRNA technology and non-targeted metabolomics technology.METHODS The PD model of mice was induced by subcutaneous injection of MPTP 20 mg·kg-1·d-1 and peritoneal injection of probenecid 200 mg·kg-1·d-1,and the weight and behavior indexes of mice were measured after drug intervention.HPLC-QTRAP-MS/MS technique was used to detect the levels of neurotransmitters in the striatum of mice.The levels of striatal inflammatory factors were detected by ELISA.The changes of intestinal flora in mice were analyzed by 16S rRNA technology.UHPLC-Q-TOF-MS was used to detect endogenous metabolites in mouse striatum,Orthogonal partial least squares discriminant analysis(OPLS-DA)was adopted to screen potential differential metabolites,and MetaboAnalyst 5.0 was introduced to predict metabolic pathways associated with PD.RESULTS HLJDD significantly improved the motor symptoms and neuroinflammation of PD mice(P<0.01),regulated the level of neurotransmitters,and corrected the intestinal microbiota disorder of PD mice,manifes-ted by the increase of intestinal microbial diversity and the restoration of microbiota profile.After treatment with HLJDD,the abun-dance of Prevotella and Akkermansia in PD mice was significantly increased,and the abundance of Clostridium was decreased(P<0.01).The abnormal metabolite levels were restored mainly by regulating the tryptophan metabolic pathway in the feces and striatum of PD model mice.CONCLUSION HLJDD can significantly improve the pathological damage of PD model mice,and the regulation of disordered intestinal flora and tryptophan metabolism pathway may be the potential mechanism of HLJDD to intervene in PD.

V-ATPases are a class of multi-subunit protein complexes that utilize energy derived from ATP hydrolysis for mediating H + transport across cell membranes, which plays an important role in a range of life activities by acidifying the intracellular and extracellular environment. Variants of V-ATPase genes may lead to complete or partial loss of V-ATPase activity, which in turn may impair the ability of type A intercalated cells in renal tubules to pump H + into the tubular lumen, ultimately resulting in the onset of autosomal recessive distal renal tubular acidosis (dRTA). With the rapid development of molecular techniques, ATP6V0A4 and ATP6V1B1 have now been identified as the pathogenic genes for dRTA. Moreover, animal and cell experiments have substantiated the implication of V-ATPase subunit genes including ATP6V1C2 and ATP6V1G3 in the development of dRTA, though clinical evidence is still limited. This article has reviewed recent progress on the genetic and molecular mechanisms of V-ATPase subunit gene variants which can lead to dRTA, which may shed light on the diagnosis and treatment of this disease.

ObjectiveBased on the network pharmacology system and quantitative spectroscopy of traditional Chinese medicine（TCM） compounds， a topological network analysis method with equilibrium constant as the core was established to further explore the interaction between allergenic components and their network targets in Shuanghuanglian injection（SHLI）， in order to provide new ideas and experimental basis for identifying and screening potential allergens of SHLI. MethodAfter one week of adaptive feeding， 72 SPF-grade SD male rats were randomly divided into blank group， SHLI standard group， Lonicerae Japonicae Flos（LJF） group， Scutellariae Radix（SR） group， Forsythiae Fructus（FF） group， and 7 groups of SHLI matching groups（groups 1-7）， with 6 rats in each group. Rats in each group were administered the drug intravenously and blood samples were taken after steady state， high performance liquid chromatography（HPLC） characterization profiles of the testing drugs and plasma components in each group were established， and the peak area changes of the drugs and plasma components in each group were calculated after the component groups were classified. Enzyme-linked immunosorbent assay（ELISA） was used to determine the changes of immunoglobulin E（IgE）， histamine（HIS）， tryptase（TPS）， total complement（CH50） and terminal complement complex（C5b-9） in animal blood samples. MATLAB R2020b v9.9.0 software was used to calculate the network balance constants of the component groups with the targets， and the eigenvalues of the matrices composed of network equilibrium constants were calculated and ranked according to their values. ResultELISA results showed that， compared with the blank group， groups 1-3 could significantly increase the IgE level， groups 1-2， groups 4-6 and SHLI standard group could significantly increase the HIS level， group 4 could significantly increase the CH50 level， groups 1， 3-4， LJF group and FF group could significantly increase the TPS level， SR group could significantly increase the C5b-9 level， and the differences were all statistically significant（P<0.05）. According to the retention time of chromatographic peaks， it was classified into 6 component groups from C1 to C6 by HPLC. The order of the network balance constants of each component group was C6>C4>C1>C5>C3>C2， indicating that C6 had the greatest effect on the allergic reaction， and was most likely to be the allergen. The sequence of eigenvalues was C2>C5b-9>C3>C1>CH50>C6>C5>IgE>TPS>C4>HIS， indicating that component group C2 had the greatest contribution to the whole network. ConclusionBased on the correlation analysis of SHLI component group and allergy-like target network， this study clarified that component group C6 may be a potential allergen in SHLI， and the component group C2 may be a key node in the mechanism of drug action， which can provide new strategies and methods for the screening of allergens in TCM injections.

Objective To explore the application value of simultaneous multi-slice(SMS)technique in diffusion tensor imaging(DTI)for evaluating brain glioma.Methods Thirty-four brain glioma patients were prospectively enrolled,and brain conventional DTI and SMS-DTI were acquired.The subjective scores of image quality,signal-to-noise ratio(SNR)and contrast-to-noise ratio(CNR)were compared between SMS-DTI and conventional DTI,so were the numbers of whole brain fiber bundles,tumor relative fractional anisotropy(rFA)and relative mean diffusivity(rMD)obtained based on SMS-DTI and conventional DTI.Results Among 34 patients,there were 23 cases of high-grade glioma and 11 cases of low-grade glioma.No significant difference of subjective scores of image quality,tumor edge clarity nor magnetic susceptibility artifacts was found between SMS-DTI and conventional DTI(all P＞0.05).SNR and CNR on SMS-DTI were both lower than those on conventional DTI(both P＜0.05).No significant difference of the numbers of whole brain fiber bundles,rFA nor rMD of gliomas with different pathological grades was detected based on SMS-DTI compared with those on conventional DTI(all P＞0.05).Conclusion SMS applicated in DTI for evaluating brain gliomas was able to shorten acquisition time under the condition of ensuring image quality and quantitative analysis accuracy.

Sodium and water retention are key and controllable risk factors that contribute to the increased risk of morbidity and mortality in patients with heart failure,and long-term continuous and effective volume management is an important strategy to help patients achieve an individualized state of optimal volume balance.The gradual application of digital health technology in the field of cardiovascular disease has provided new possibilities for volume management in patients with heart failure,while the relevant domestic studies and reports remain fewer.This article reviews the application of digital health technology in the assessment of volume status,management of volume status,volume hsk waming,health education and follow-up in patients with heart failure,and analyzes the existing problems and countermeasures,to provide a reference for digital volume management in out-of-hospital heart failure patients.

By analyzing the of genetic testing data of patients with renal polycystic kidney disease and their relatives, this study aims to identify unreported novel gene mutation sites associated with autosomal dominant polycystic kidney disease (ADPKD). Structural prediction software was employed to investigate protein structural changes before and after mutations, explore genotype-phenotype correlations, and enrich the ADPKD gene database. In this single-center retrospective study, patients with multiple renal cysts diagnosed from January 2019 to February 2023 at the Zhong Da Hospital Southeast University were included. Genetic and clinical data of patients and their families were collected. Unreported novel gene mutation sites associated with ADPKD were identified. The AlphaFold v2.3.1 software was used to predict protein structures. Changes in protein structure before and after mutations were compared to explore genotype-phenotype correlations and enrich the ADPKD gene database. Twelve mutated genes associated with renal cysts were detected in 52 families. Nineteen novel gene mutation sites associated with ADPKD were identified, including 17 mutations in the PKD1 gene (one splicing mutation, seven frameshift mutations, four nonsense mutations, one whole-codon insertion, and four missense mutations); one ALG9 missense mutation; and one chromosomal structural variation. Truncating mutations in the PKD1 gene were correlated with a more severe clinical phenotype, while non-truncating mutations were associated with greater clinical heterogeneity. Numerous novel gene mutation sites associated with ADPKD remain unreported. Therefore, it is essential to analyze the pathogenicity of these novel mutation sites, establish genotype-phenotype correlations, and enrich the ADPKD gene database.

Objective:To analyze the mutation pathogenicity of the novel compound heterozygous mutation in the PKHD1 gene causing autosomal recessive polycystic kidney disease (ARPKD) family, expand the PKHD1 gene mutation database, and explore the genotype-phenotype correlations of PKHD1 gene mutation causing ARPKD. Methods:Clinical data and peripheral blood of a patient with ARPKD caused by the novel compound heterozygous mutation in the PKHD1 gene and their family members were collected. High-throughput sequencing was used to detect pathogenic mutations in the proband, and PCR amplification and Sanger sequencing were used to verify the pathogenic mutations in the family. AlphaFold software was applied to predict changes in protein structure in the present or absent mutations, and the pathogenicity of mutations was analyzed. Results:The patient was a young male who underwent splenectomy due to liver cirrhosis and hypersplenism at age 7. He developed end-stage renal disease at age 22, requiring maintenance peritoneal dialysis, and died of severe pneumonia and septic shock at age 24. Genetic testing revealed three compound heterozygous mutations in the PKHD1 gene inherited from his parents: a missense mutation (c.5935G>A) inherited from the father and a missense mutation (c.1187G>A) and a novel splice mutation (c.6332+1_6332+2insG) from the mother. The single missense mutation allele likely contributed to the prolonged survival. c. 6332+1_ 6332+2insG is a novel splicing mutation that has not been reported in the past, which can lead to early termination of protein translation. This discovery expands the PKHD1 gene mutation database. c. 1187G>A (p.S396N) and c.5935G>A (p.G1979R) occur in the PA14 and G8 domains of the protein, respectively, and are associated with early and severe liver phenotypes in patients. Conclusions:The mutation types and amino acid localization of the PKHD1 gene are associated with the heterogeneity of clinical phenotypes in ARPKD patients. Analyzing structural changes in proteins before and after mutations can help understand the pathogenicity at a molecular level, establishing genotype-phenotype correlations and providing valuable insights for assessing prognosis and identifying high-risk ARPKD patients early.