Objective To analyze the main causes and risk factors of unplanned reoperation after liver transplantation. Methods The clinical data of 242 liver transplant recipients in the First Affiliated Hospital of Anhui Medical University from January 2015 to December 2024 were retrospectively analyzed. According to whether unplanned reoperation was performed during the same hospitalization after surgery, the recipients were divided into the reoperation group (n=36) and the non-reoperation group (n=206). The preoperative, intraoperative and postoperative data of the two groups, as well as donor and graft-related data, were compared to analyze the risk factors of unplanned reoperation after liver transplantation and the survival status of the two groups. Results Among the 242 liver transplant recipients, 36 underwent unplanned reoperations, with a total of 54 procedures including various laparotomies, endoscopic and interventional surgeries, among which there were 20 laparotomies, 18 endoscopic surgeries and 16 interventional surgeries. The most common cause of unplanned reoperation was biliary complications (20 times), followed by vascular complications (17 times). Compared with the non-reoperation group, the reoperation group had longer graft cold ischemia time, higher postoperative fatality rate of recipients, longer length of stay in the intensive care unit and postoperative hospital stay, and higher total hospitalization costs (all P<0.05). The incidence of unplanned reoperation was higher in recipients who underwent split liver transplantation (P<0.05). Multivariate analysis showed that intraoperative blood loss ≥1 000 mL, positive culture of graft perfusate and split liver transplantation were independent risk factors for unplanned reoperation (all P<0.05). The postoperative 7-day, 1-month, 3-month and 6-month survival rates of recipients in the reoperation group and the non-reoperation group were 100% vs. 98.1%, 88.9% vs. 94.2%, 69.4% vs. 90.8% and 66.7% vs. 90.8%, respectively, and the postoperative survival rate of recipients in the reoperation group was lower than that in the non-reoperation group (P<0.05). Conclusions The main causes of unplanned reoperation after liver transplantation are biliary complications, vascular complications, abdominal incision infection and intra-abdominal hemorrhage. Intraoperative massive blood loss, positive culture of graft perfusate and split liver transplantation are the risk factors associated with unplanned reoperation after liver transplantation.

In recent years， hyperuricemia （HUA） has shown a rapidly increasing incidence and tends to occur in increasingly young people， with a wide range of cardiac， renal， joint， and cancerous hazards and all-cause mortality associations. Western medicine treatment has limitations such as large liver and kidney damage， medication restriction， and easy recurrence. The intestine is the major extra-renal excretion pathway for uric acid （UA）， and the intestinal microecology can be regulated to promote UA degradation. It offers great potential to develop UA-lowering strategies that target the intestinal microecology， which are promising to provide safer and more effective therapeutic approaches. Traditional Chinese medicine （TCM） can treat HUA via multiple targets and multiple pathways from a holistic view， with low toxicity and side effects. Studies have shown that intestinal microecology is a crucial target for TCM in the treatment of HUA. However， its specific mechanism of action has not been fully elucidated. Focusing on the key role of intestinal microecology in HUA， this review explores the relationship between intestinal microecology and HUA in terms of intestinal flora， intestinal metabolites， intestinal UA transporters， and intestinal barriers. Furthermore， we summarize the research progress in TCM treatment of HUA by targeting the intestinal microecology， with the aim of providing references for the development of TCM intervention strategies for HUA and the direction of future research.

Objective To investigate the association between birth weight and dementia risk and the mediating roles of chronic diseases,and to assess potential biological pathways underlying the birth weight-associated dementia risk based on large-scale proteomics.Methods We used data from 279 743 participants aged 40 to 69 years enrolled in the UK Biobank.Birth weight was categorized into low birth weight(≤2 500 g),normal birth weight(2 500-3 999 g),and macrosomia(≥4 000 g).Multivariable Cox proportional hazards regression models were used to assess the associations between birth weight categories and all-cause dementia and its subtypes(Alzheimer's disease and vascular dementia).Proteomics analyses were conducted to identify proteins and the potential pathways involved.Results Low birth weight was associated with higher risks for all-cause dementia and its subtypes.The hazard ratios were 1.18(95%CI,1.08-1.30)for all-cause dementia,1.14(95%CI,1.00-1.31)for Alzheimer's disease,and 1.22(95%CI,1.01-1.48)for vascular dementia.A non-linear relationship was observed between birth weight and dementia risk(P for nonlinearity<0.001).Certain cardiometabolic diseases in middle-aged adults,such as diabetes,stroke,hypertension,and dyslipidemia,played a significant mediating role in the relationship between low birth weight and dementia risk,with the mediation proportion being 6.3%to 15.8%.Proteomic analyses identified 21 proteins linked to both low birth weight and all-cause dementia risk,which were significantly enriched in the pathways for viral protein interaction with cytokines and cytokine receptors,adipocytokine signaling,and cytokine-cytokine receptor interaction.Conclusion Low birth weight is positively associated with dementia risk.Cardiometabolic diseases in middle-aged adults may mediate the relationship between low birth weight and dementia risk.A number of proteins and the associated pathways underscore the relationship between low birth weight and dementia risk.

Colorectal cancer is one of the most prevalent malignant tumors in the digestive system globally,with both its incidence and mortality showing an upward trend.In recent years,immunother-apy has become a research focus in the prognosis of CRC.Different states of tumor-infiltrating lym-phocytes(TILs)in patients have distinct impacts on tumor progression.The diversity of TILs and their interactions among cells reflect the complex relationship between tumors and the immune system.Patients with mismatch repair-deficient and microsatellite instability-high(dMMR/MSI-H)molecular phenotypes exhibit higher levels of TILs.Moreover,immune checkpoint inhibitors(ICIs),which are relevant targeted drugs for immune checkpoint blockade,also demonstrate a higher response rate in colorectal cancer patients with dMMR/MSI-H molecular phenotypes.This article reviewed the basic characteristics and prognostic value of TILs,as well as the relationship between dMMR/MSI-H and the immunological characteristics of colorectal cancer patients.

Objective:To investigate the effect of GBP3 on replication of adult T-lymphocytic leukemia virus type 1(HTLV-1).Methods:Expression of GBP3 in HTLV-1-infected HeLa cell and THP1 cell was detected by Western blot.The knock-down efficiency of siRNAs targeting GBP3 in HeLa and THP1 cells was evaluated by Western blot.Effects of GBP3 overexpression or knockdown on expression of HTLV-1 proviral transcripts Tax,px,HBZ,Gag,ENV,5'UTR,and viral proteins Tax,p19 were investigated by RT-qPCR and Western blot.GTPase-defective mutant of GBP3,GBP3K51A was constructed to explore whether the effects of GBP3 on HTLV-1 infection were dependent on its GTPase activity.Results:GBP3 expression was upregulated in HTLV-1 infected HeLa and THP1 cells.GBP3 overexpression decreased expression of HTLV-1 proviral transcripts and viral proteins,whereas the knockdown of GBP3 has the opposite effects.Overexpression of GBP3K51A increased expression of HTLV-1 proviral transcripts and viral proteins.Conclusion:HTLV-1 virus infection can induce expression of GBP3;overexpression of GBP3 inhibits virus replication and may depend on GTPase.

Objective:To investigate the efficacy of preoperative ultrasound-guided injection of carbon nanoparticle suspension in cervical lymph node dissection for thyroid cancer reoperation.Methods:Ninety-four patients undergoing reoperation for thyroid cancer admitted by the same physician team of the Department of Thyroid and Breast Surgery of the Ninety-sixty Hospital of the People’s Liberation Army (PLA) from Jan. 2019 to Sep. 2024 were retrospectively analyzed. According to the different scope of the initial surgery, they were divided into the re-specification clearance group, the regional lymph node clearance group, and the metastatic lymph node dissection group, and the groups were subdivided into the carbon nanoparticle group and the control group according to whether they were injected with carbon nanoparticle before the surgery or not. The t-test, χ2-test, and non-parametric test were used to compare the age, gender, surgical method, duration of surgery, total number of lymph nodes detected, and positive lymph node detection rate between the nano-charcoal group and the control group in the three groups. Results:There was no statistically significant difference between the three groups in terms of age, gender, surgical methods, or the total number of lymph nodes detected (all P>0.05) , and the difference between the surgical time of the carbon nanoparticle group in the re-regulation clearance group and the control group was not statistically significant ( P>0.05) ; the surgical time of the carbon nanoparticle group was shorter than that of the control group in both the regional lymph node clearance and the metastatic lymph node dissection groups, and the difference was statistically significant (all P<0.05) ; the positive detection rate of lymph nodes in the carbon nanoparticle group was higher than that in the control group among the three groups, and the difference was statistically significant (all P<0.05) . Conclusion:In the operation of cervical lymph node dissection for papillary thyroid cancer, preoperative ultrasound-guided injection of carbon nanoparticle can accurately localize the lymph nodes, increase the positive detection rate of lymph nodes, reduce the difficulty of surgical operation, and shorten the operation time.

ObjectiveTo analyze the epidemiological characteristics and influencing factors of SARS-CoV-2 reinfection by conducting follow-up investigations among community residents who experienced their first SARS-CoV-2 infection between March and June 2022, so as to provide a scientific basis for predicting future epidemic trends and adjusting prevention and control strategies. MethodsA cohort study was conducted in Xuhui District, Shanghai. A total of 1 208 individuals with a documented primary SARS-CoV-2 infection between March and June 2022 were enrolled and followed-up longitudinally. Data were collected using structured questionnaire surveys to assess the reinfection rate, incidence density, and clinical manifestations of SARS-CoV-2 reinfection. A logistic regression model was used to analyze the influencing factors of SARS-CoV-2 reinfection. ResultsA total of 497 SARS-CoV-2 reinfection cases were observed among the 1 208 research subjects, with a reinfection rate of 41.14% and an incidence density of 0.63 cases per 1 000 person-days. The cumulative reinfection rates at 6, 9, 12, 15, and 18 months following the initial infection were 0.08%, 15.31%, 19.04%, 33.53%, and 38.25%, respectively. Compared with the primary infection, reinfection was more likely to be symptomatic, with a greater severity of fever, dry cough, sore throat, and runny nose. Being female, younger age, and symptom duration ≥7 days during the primary infection were identified as influencing factors for SARS-CoV-2 reinfection, while a higher socioeconomic status can reduce the risk of SARS-CoV-2 reinfection. ConclusionSARS-CoV-2 reinfection is relatively common and often symptomatic. Age, gender, income level, and the duration of symptoms during the primary infection are identified as infuencing factors for SARS-CoV-2 reinfection. Continuous monitoring of reinfection in the population is recommended, along with the development of effective strategies to mitigate the impact of reinfection.

Objective:To investigate the preventive and therapeutic effects and mechanisms of Dachaihu decoction(DCD)on dextran sodium sulfate(DSS)-induced ulcerative colitis(UC)and liver injury in mice,as well as the association between DCD benefits and gut microbiota modulation.Methods:Mice were treated with DCD(20.10 and 10.05 g/kg)for 2 weeks,with free access to drinking water containing 3%DSS in the second week to induce UC.Histopathological examination,RT-qPCR and 16S rRNA sequencing were used to investigate the effect of DCD on UC mice.Results:DCD pretreatment significantly alleviated weight loss,bloody diarrhea with mucus,histopathological abnormalities of the colon,and colon shortening in mice with DSS-induced UC.In addition,DCD pretreat-ment significantly upregulated the levels of Occludin,ZO-1,and MUC-2 in the colon and protected the intestinal barrier of mice.DCD pretreatment also alleviated inflammatory cell infiltration in the colon and the liver and significantly reduced the expression levels of the proinflammatory factors such as IL-1β,IL-6,TNF-α,iNOS,COX-2,and NLRP3,thereby exerting a protective effect against UC and liver injury.It should be noted that DCD corrected gut micro-biota imbalance in UC mice by enriching probiotic bacteria such as Lactobacillus and Bifidobacterium and reducing harmful bacteria such as Norank_f_Desulfovibrionaceae and Escherichia-Shigella.Conclusion:DCD can alleviate DSS-induced UC and exert a liver-protecting effect by protecting intestinal barrier,inhibiting inflam-mation,and regulating gut microbiota.

Objective:To investigate the influencing factors for sarcopenia in hospitalized patients,to construct a risk prediction model for sarcopenia in elderly hospitalized patients,and to provide a quantitative tool for early screening and intervention of sarcopenia based on the integration of multi-dimensional indicators.Methods:A retrospective analysis was performed for the data of 2105 elderly patients who were hospitalized in The First Affiliated Hospital of Chongqing Medical University from March 2016 to June 2023.The least absolute shrinkage and selection operator analysis was used for the screening of variables,and the logistic regression analysis was used to investigate the influencing factors for sarcopenia.A predictive model was constructed,and internal and external validation was performed.The Shapley additive explanations model was used to analyze feature contributions,and a nomogram model was constructed to visualize and interpret the results.Results:The 1259 patients from March 2016 to December 2020 were randomly divided into a training set with 882 patients and an internal test set with 377 patients at a ratio of 7∶3,and the 846 patients from January 2021 to June 2023 were established as the external validation set.A total of 489 cases of sarcopenia(55.44%)were detected in the training set.The logistic regression analysis based on the training set showed that asthenia,dependence on Activity of Daily Living,malnutrition,and in-creasing age were risk factors for sarcopenia(odds ratio[OR]>1,P<0.05),and male sex,normal body mass index,and overweight were protective factors against sarcopenia(OR<1,P<0.05).The model had an AUC of 0.876(95%CI=0.854-0.899)in the training set,0.883(95%CI=0.849-0.918)in the internal test set,and 0.750(95%CI=0.717-0.783)in the external validation set,suggesting that the model had good performance.The decision curve analysis showed that the nomogram model had a good clinical value.Conclu-sion:The predictive model for sarcopenia has good performance and holds promise for clinical application.

Objective:To screen the optimal machine learning model for predicting the recurrence condition of hepatocellular carcinoma (HCC) at different time points post-surgery, based on the cutoff value of the Ki67 positive proliferation index condition calculated from recurrence-free survival and combined with various clinical features.Methods:retrospective study included initially treated patients with solitary HCC who underwent radical surgery at the Fifth Medical Center of the PLA General Hospital from January 2013 to March 2023. Data included general clinical data, preoperative laboratory parameters, and surgical pathology information about the subjects. The postoperative recurrence status was assessed by querying the medical record system or by telephone follow-up. The Ki67 positive index cutoff value was determined by the X-tile software based on the patient's recurrence-free survival status and time analysis. Survival rates were calculated using the Kaplan-Meier method, and survival curves were plotted. The study population was randomly divided into training and testing groups in a 7:3 ratio using a computer-generated random number method. The minimum redundancy maximum relevance (mRMR) method was used for feature variable selection. Predictive models for postoperative HCC recurrence conditions in patients with HCC were constructed using random forest, support vector machine, logistic regression, and gradient boosting decision tree machine learning algorithms. Inter-group comparisons for continuous data were performed using the t-test or Mann-Whitney U test. Inter-group comparisons of enumeration data were performed using the Pearson χ2 test, continuity-corrected χ2 test, or Fisher's exact test. Results:The cutoff values for the Ki67 positivity index were 0.3 and 0.5 in 510 cases, with a follow-up time ranging from 1.2 to 11.4 years (median: 6.2 years). The recurrence-free survival time was between 1 and 135 months (median: 32 months), with recurrence-free survival rates post-surgery at 1, 2, 3, and 5 years were 87.5%, 77.1%, 61.2%, and 54.5%, respectively. The top five variables predicted HCC recurrence and non-recurrence conditions following surgical follow-up at 6 months, 1 year, 2 years, and beyond 2 years, in accordance with information obtained by the mRMR screen out. The Ki67 positivity index screened a successfully constructed machine learning model to predict HCC recurrence and non-recurrence conditions following surgical follow-up at 6 months, 1 year, 2 years, and beyond 2 years. The machine learning model based on the gradient boosting decision tree algorithm had the best prediction performance among them (areas under the receiver operating characteristic curves for predicting HCC recurrence within six months in the training and validation sets were 0.996 and 0.946, and accuracies were 0.972 and 0.935, respectively).Conclusion:A machine learning model was successfully constructed using the Ki67 positivity index combined with four readily available clinical features to predict HCC recurrence. The machine learning model based on the gradient boosting decision tree algorithm demonstrated the best performance in terms of predicting HCC recurrence within six months after surgery.