Objective To establish dynamic nomogram models for postoperative recurrence and survival risk of patients with AFP-negative hepatocellular carcinoma(ANHC)based on multimodal clinical data,to identify ANHC-specific prognostic biomarker combinations by integrating tumor biological characteristics and treatment response parameters through machine learning,and to provide an individualized risk assessment tool for overcoming the limitations of traditional serum biomarkers.Methods A retrospective analysis was performed for 421 ANHC patients who underwent hepatectomy in Eastern Hepatobiliary Surgery Hospital from April 2012 to December 2018,and they were randomly divided into training group with 210 patients and validation group with 211 patients.The univariate and multivariate Cox proportional-hazards regression models were used to identify independent prognostic factors and establish a nomogram model,and the receiver operating characteristic(ROC)curve,the calibration curve,and the decision curve analysis were used to assess the performance of the model.Related indicators were measured,including prealbumin(PA),white blood cell count(WBC),tumor size,and microvascular invasion.The chi-square test or the Fisher's exact test was used for comparison of categorical variables between two groups,and the independent-samples t test or the Mann-Whitney U test was used for comparison of continuous variables between two groups.Results The multivariate analysis showed that multiple tumors(hazard ratio[HR]=3.30,P<0.001),WBC(HR=1.05,P=0.005),blood glucose(HR=1.15,P=0.026),CA19-9(HR=1.17,P=0.005),and tumor size(HR=1.17,P<0.001)were independent risk factors for disease-free survival(DFS),while PA(HR=0.99,P=0.022)was a protective factor.Incomplete tumor capsule(HR=0.60,P=0.009),age(HR=1.02,P=0.035),prothrombin time(PT)(HR=1.27,P=0.023),CA19-9(HR=1.01,P<0.001),and tumor size(HR=1.15,P<0.001)were independent risk factors for overall survival(OS).The DFS nomogram achieved an AUC of 0.74(95%confidence interval[CI]:0.64-0.84)in the training group and 0.67(95%CI:0.57-0.77)in the validation group,while the OS nomogram had an AUC of 0.76(95%CI:0.64-0.88)and 0.73(95%CI:0.60-0.87),respectively.The calibration curve and the decision curve analysis showed that the models had good predictive accuracy and clinical practicability.Conclusion Preoperative indicators,including tumor number,PA,WBC,and tumor size,can effectively predict postoperative recurrence in ANHC patients,while tumor capsule integrity,age,and PT are significantly associated with OS.The nomogram models established have good performance and can provide a basis for individualized prognostic assessment.

Objective To establish dynamic nomogram models for postoperative recurrence and survival risk of patients with AFP-negative hepatocellular carcinoma(ANHC)based on multimodal clinical data,to identify ANHC-specific prognostic biomarker combinations by integrating tumor biological characteristics and treatment response parameters through machine learning,and to provide an individualized risk assessment tool for overcoming the limitations of traditional serum biomarkers.Methods A retrospective analysis was performed for 421 ANHC patients who underwent hepatectomy in Eastern Hepatobiliary Surgery Hospital from April 2012 to December 2018,and they were randomly divided into training group with 210 patients and validation group with 211 patients.The univariate and multivariate Cox proportional-hazards regression models were used to identify independent prognostic factors and establish a nomogram model,and the receiver operating characteristic(ROC)curve,the calibration curve,and the decision curve analysis were used to assess the performance of the model.Related indicators were measured,including prealbumin(PA),white blood cell count(WBC),tumor size,and microvascular invasion.The chi-square test or the Fisher's exact test was used for comparison of categorical variables between two groups,and the independent-samples t test or the Mann-Whitney U test was used for comparison of continuous variables between two groups.Results The multivariate analysis showed that multiple tumors(hazard ratio[HR]=3.30,P<0.001),WBC(HR=1.05,P=0.005),blood glucose(HR=1.15,P=0.026),CA19-9(HR=1.17,P=0.005),and tumor size(HR=1.17,P<0.001)were independent risk factors for disease-free survival(DFS),while PA(HR=0.99,P=0.022)was a protective factor.Incomplete tumor capsule(HR=0.60,P=0.009),age(HR=1.02,P=0.035),prothrombin time(PT)(HR=1.27,P=0.023),CA19-9(HR=1.01,P<0.001),and tumor size(HR=1.15,P<0.001)were independent risk factors for overall survival(OS).The DFS nomogram achieved an AUC of 0.74(95%confidence interval[CI]:0.64-0.84)in the training group and 0.67(95%CI:0.57-0.77)in the validation group,while the OS nomogram had an AUC of 0.76(95%CI:0.64-0.88)and 0.73(95%CI:0.60-0.87),respectively.The calibration curve and the decision curve analysis showed that the models had good predictive accuracy and clinical practicability.Conclusion Preoperative indicators,including tumor number,PA,WBC,and tumor size,can effectively predict postoperative recurrence in ANHC patients,while tumor capsule integrity,age,and PT are significantly associated with OS.The nomogram models established have good performance and can provide a basis for individualized prognostic assessment.

Evidence indicates that metabolic reprogramming characterized by the changes in cellular metabolic patterns contributes to the pathogenesis of pulmonary fibrosis(PF).It is considered as a promising ther-apeutic target anti-PF.The well-documented against PF properties of Tanshinone ⅡA(Tan ⅡA)have been primarily attributed to its antioxidant and anti-inflammatory potency.Emerging evidence suggests that TanⅡA may target energy metabolism pathways,including glycolysis and tricarboxylic acid(TCA)cycle.However,the detailed and advanced mechanisms underlying the anti-PF activities remain obscure.In this study,we applied[U-13C]-glucose metabolic flux analysis(MFA)to examine metabolism flux disruption and modulation nodes of Tan ⅡA in PF.We identified that Tan ⅡA inhibited the glycolysis and TCA flux,thereby suppressing the production of transforming growth factor-β1(TGF-β1)-dependent extracellular matrix and the differentiation and proliferation of myofibroblasts in vitro.We further revealed that Tan ⅡA inhibited the expression of key metabolic enzyme hexokinase 2(HK2)by inhibiting phosphoinositide 3-kinase(PI3K)/protein kinase B(Akt)/mammalian target of rapamycin(mTOR)/hypoxia-inducible factor 1α(HIF-1α)pathway activities,which decreased the accumulation of abnormal metabolites.Notably,we demonstrated that Tan ⅡA inhibited ATP citrate lyase(ACLY)activity,which reduced the collagen synthesis pathway caused by cytosol citrate consumption.Further,these results were validated in a mouse model of bleomycin-induced PF.This study was novel in exploring the mechanism of the occurrence and develop-ment of Tan ⅡA in treating PF using 13C-MFA technology.It provided a novel understanding of the mechanism of Tan ⅡA against PF from the perspective of metabolic reprogramming.

Lipotoxicity is a pivotal factor that initiates and exacerbates liver injury and is involved in the development of metabolic-associated fatty liver disease (MAFLD). However, there are few reported lipotoxicity inhibitors. Here, we identified a natural anti-lipotoxicity candidate, HN-001, from the marine fungus Aspergillus sp. C1. HN-001 dose- and time- dependently reversed palmitic acid (PA)-induced hepatocyte death. This protection was associated with IRE-1α-mediated XBP-1 splicing inhibition, which resulted in suppression of XBP-1s nuclear translocation and transcriptional regulation. Knockdown of XBP-1s attenuated lipotoxicity, but no additional ameliorative effect of HN-001 on lipotoxicity was observed in XBP-1s knockdown hepatocytes. Notably, the ER stress and lipotoxicity amelioration was associated with PLA2. Both HN-001 and the PLA2 inhibitor MAFP inhibited PLA2 activity, reduced lysophosphatidylcholine (LPC) level, subsequently ameliorated lipotoxicity. In contrast, overexpression of PLA2 caused exacerbation of lipotoxicity and weakened the anti-lipotoxic effects of HN-001. Additionally, HN-001 treatment suppressed the downstream pro-apoptotic JNK pathway. In vivo, chronic administration of HN-001 (i.p.) in mice alleviated all manifestations of MAFLD, including hepatic steatosis, liver injury, inflammation, and fibrogenesis. These effects were correlated with PLA2/IRE-1α/XBP-1s axis and JNK signaling suppression. These data indicate that HN-001 has therapeutic potential for MAFLD because it suppresses lipotoxicity, and provide a natural structural basis for developing anti-MAFLD candidates.

Objective:To develop a risk prediction model for the recurrence of diabetic foot ulcer (DFU) in diabetic patients and primarily validate its predictive value.Methods:Meta-analysis combined with retrospective cohort study was conducted. The Chinese and English papers on risk factors related to DFU recurrence publicly published in China Biology Medicine disc, China National Knowledge Infrastructure, Wanfang Database, VIP Database, and PubMed, Embase, Cochrane Library, and Web of Science, and the search time was from the establishment date of each database until March 31 st, 2022. The papers were screened and evaluated, the data were extracted, a meta-analysis was performed using RevMan 5.4.1 statistical software to screen risk factors for DFU recurrence, and Egger's linear regression was used to assess the publication bias of the study results. Risk factors for DFU recurrence mentioned in ≥3 studies and with statistically significant differences in the meta-analysis were selected as the independent variables to develop a logistic regression model for risk prediction of DFU recurrence. The medical records of 101 patients with DFU who met the inclusion criteria and were admitted to Affiliated Hospital of Guizhou Medical University from January 2019 to June 2022 were collected. There were 69 males and 32 females, aged (63±14) years. The receiver operating characteristic (ROC) curve of the predictive performance of the above constructed predictive model for DFU recurrence was drawn, and the area under the ROC curve, maximum Youden index, and sensitivity and specificity at the point were calculated. Dataset including data of 8 risk factors for DFU recurrence and the DFU recurrence rates of 10 000 cases was simulated using RStudio software and a scatter plot was drawn to determine two probabilities for risk division of DFU recurrence. Using the β coefficients corresponding to 8 DFU recurrence risk factors ×10 and taking the integer as the score of coefficient weight of each risk factor, the total score was obtained by summing up, and the cutoff scores for risk level division were calculated based on the total score × two probabilities for risk division of DFU recurrence. Results:Finally, 20 papers were included, including 3 case-control studies and 17 cohort studies, with a total of 4 238 cases and DFU recurrence rate of 22.7% to 71.2%. Meta-analysis showed that glycosylated hemoglobin >7.5% and with plantar ulcer, diabetic peripheral neuropathy, diabetic peripheral vascular disease, smoking, osteomyelitis, history of amputation/toe amputation, and multidrug-resistant bacterial infection were risk factors for the recurrence of DFU (with odds ratios of 3.27, 3.66, 4.05, 3.94, 1.98, 7.17, 11.96, 3.61, 95% confidence intervals of 2.79-3.84, 2.06-6.50, 2.50-6.58, 2.65-5.84, 1.65-2.38, 2.29-22.47, 4.60-31.14, 3.13-4.17, respectively, P<0.05). There were no statistically significant differences in publication biases of diabetic peripheral neuropathy, diabetic peripheral vascular disease, glycosylated hemoglobin >7.5%, plantar ulcer, smoking, multidrug-resistant bacterial infection, or osteomyelitis ( P>0.05), but there was a statistically significant difference in the publication bias of amputation/toe amputation ( t=-30.39, P<0.05). The area under the ROC curve of the predictive model was 0.81 (with 95% confidence interval of 0.71-0.91) and the maximum Youden index was 0.59, at which the sensitivity was 72% and the specificity was 86%. Ultimately, 29.0% and 44.8% were identified respectively as the cutoff for dividing the probability of low risk and medium risk, and medium risk and high risk for DFU recurrence, while the corresponding total scores of low, medium, and high risks of DFU recurrence were <37, 37-57, and 58-118, respectively. Conclusions:Eight risk factors for DFU recurrence are screened through meta-analysis and the risk prediction model for DFU recurrence is developed, which has moderate predictive accuracy and can provide guidance for healthcare workers to take interventions for patient with DFU recurrence risk.

Animals ; SARS-CoV-2 ; Antibodies, Neutralizing ; Macaca mulatta ; COVID-19/prevention & control* ; Antibodies, Viral ; Vaccines

Objective To investigate the role of phosphoglycerate kinase 1 (PGK1) in tumorigenesis and its potential post-translational modification sites were investigated by bioinformatics method and molecular biology experimental techniques, in order to provide evidence for PGK1 as a hepatocellular carcinoma ( HCC) diagnostic biomarker and therapeutic target. Methods From pan-cancer's point of view, 10 967 samples were obtained from the cancer genome database TCGAs, and the expression of PGK1 in different tumors was explored by using cBioPortal and UALCAN analysis tools; Focusing on HCC, the expression differences of PGK1 in hepatocellular carcinoma tumor tissues and normal tissues were further analyzed by using GEO database analysis, Real-time PCR, Western blotting and cell invasion assay;The String database was used to analyze the protein-protein interaction network and gene set enrichment analysis; The CSS-Palm database and bioinformatics method were used to predict protein post-translational modification sites on PGK1. Results The PGK1 gene was abnormally amplified and overexpressed in various solid tumors, including hepatocellular carcinoma, and overexpression of PGK1 was correlated with a poor prognosis in hepatocellular carcinoma. Multiple novel posttranslational modifications were existed on PGK1. Conclusion PGK1 is closely related to the occurrence and development of various cancers including HCC and glycolytic metabolism abnormalities. Epigenetic modifications can regulate PGK1 and affect its cellular function in HCC.

Recent population studies have significantly advanced our understanding of how age shapes the gut microbiota.However,the actual role of age could be inevitably confounded due to the complex and variable environmental factors in human populations.A well-controlled envi-ronment is thus necessary to reduce undesirable confounding effects,and recapitulate age-dependent changes in the gut microbiota of healthy primates.Herein we performed 16S rRNA gene sequenc-ing,characterized the age-associated gut microbial profiles from infant to elderly crab-eating maca-ques reared in captivity,and systemically revealed the lifelong dynamic changes of the primate gut microbiota.While the most significant age-associated taxa were mainly found as commensals such as Faecalibacterium,the abundance of a group of suspicious pathogens such as Helicobacter was exclusively increased in infants,underlining their potential role in host development.Importantly,topology analysis indicated that the network connectivity of gut microbiota was even more age-dependent than taxonomic diversity,and its tremendous decline with age could probably be linked to healthy aging.Moreover,we identified key driver microbes responsible for such age-dependent network changes,which were further linked to altered metabolic functions of lipids,carbohydrates,and amino acids,as well as phenotypes in the microbial community.The current study thus demon-strates the lifelong age-dependent changes and their driver microbes in the primate gut microbiota,and provides new insights into their roles in the development and healthy aging of their hosts.

Objective:To investigate the clinical characteristics of de novo malignancies (DNMs) after liver transplantation (LT) and to study the clinical management strategies.Methods:Adult LT recipients who were regularly followed-up in the Organ Transplantation Center, the Affiliated Hospital of Qingdao University from January 2005 to April 2021 were enrolled in this study. The clinical characteristics of DNMs were retrospectively analyzed. Of 601 LT recipients, there were 105 females and 496 males, aged (51.4±9.6) years old. They were divided into the DNMs group ( n=26) and the non-DNMs group ( n=575) according to whether there were DNMs on followed-up. Clinical data including age, sex, basic diseases before LT and operation time were collected. These patients were follow-up in outpatient clinics. Results:Twenty-six patients were diagnosed to develop DNMs after LT, but there were 28 DNMs (of which 2 patients were diagnosed to have DNMs twice). The incidence of DNMs after LT was 4.3% (26/601), the median time from LT to DNMs was 42 (20, 70) months, and the cumulative incidence rates of DNMs were 0.5%, 2.0%, 6.3%, 21.0% and 34.5% at 1, 3, 5, 10 and 15 years after LT, respectively. Among the 28 DNMs, digestive system tumors were most common, with 17 lesions (60.7%), followed by 3 lesions (11.1%) of lung cancer, 2 lesions (7.4%) of lymphoproliferative diseases, and 1 lesion (3.7%) of cervical cancer, thyroid cancer, soft palate cancer, eyelid cancer, laryngeal cancer, and prostate cancer. The follow-up time of 55.9 (36.6, 102.5) months in the DNMs group after LT was longer than the 33.4 (18.5, 58.9) months in the non-DNMs group ( P<0.001). The 1, 5, and 10 year survival rates of patients with DNMs after LT were 96.3%, 83.5%, and 49.8%, respectively. The 1, 5, and 10 year survival rates of patients with non-DNMs after LT were 94.5%, 77.7%, and 75.4%, respectively. There was no significant difference in the cumulative survival rates between the two groups (log rank=0.402, P=0.526). Conclusion:The incidence of DNMs in LT recipients was 4.3%. The majority of them were digestive system tumors. Early diagnosis and treatment of DNMs significantly improved the prognosis and quality of life of these patients.

Objective: To improve the N biomarker in the amyloid/taueurodegeneration system by radiomics and study its value for predicting cognitive progression in individuals with mild cognitive impairment (MCI). Materials and Methods: A group of 147 healthy controls (HCs) (72 male; mean age ± standard deviation, 73.7 ± 6.3 years), 197 patients with MCI (114 male; 72.2 ± 7.1 years), and 128 patients with Alzheimer’s disease (AD) (74 male; 73.7 ± 8.4 years) were included. Optimal A, T, and N biomarkers for discriminating HC and AD were selected using receiver operating characteristic (ROC) curve analysis. A radiomics model containing comprehensive information of the whole cerebral cortex and deep nuclei was established to create a new N biomarker. Cerebrospinal fluid (CSF) biomarkers were evaluated to determine the optimal A or T biomarkers. All MCI patients were followed up until AD conversion or for at least 60 months. The predictive value of A, T, and the radiomics-based N biomarker for cognitive progression of MCI to AD were analyzed using Kaplan-Meier estimates and the log-rank test. Results: The radiomics-based N biomarker showed an ROC curve area of 0.998 for discriminating between AD and HC. CSF Aβ42 and p-tau proteins were identified as the optimal A and T biomarkers, respectively. For MCI patients on the Alzheimer’s continuum, isolated A+ was an indicator of cognitive stability, while abnormalities of T and N, separately or simultaneously, indicated a high risk of progression. For MCI patients with suspected non-Alzheimer’s disease pathophysiology, isolated T+ indicated cognitive stability, while the appearance of the radiomics-based N+ indicated a high risk of progression to AD. Conclusion We proposed a new radiomics-based improved N biomarker that could help identify patients with MCI who are at a higher risk for cognitive progression. In addition, we clarified the value of a single A/T/N biomarker for predicting the cognitive progression of MCI.