Inhibition of mitochondrial over-division by (+)-14,15-Dehydrovincamine attenuates cisplatin-induced acute kidney injury via the JNK/Mff pathway.

Cisplatin-induced acute kidney injury (AKI) is characterized by mitochondrial damage and apoptosis, and safe and effective therapeutic agents are urgently needed. Renal tubular epithelial cells, the main site of AKI, are enriched with a large number of mitochondria, which are crucial for the progression of AKI with an impaired energy supply. Vincamine has anti-inflammatory and antioxidant effects in mouse AKI models. As a natural compound derived from Tabernaemontana pandacaqui, (+)-14, 15-Dehydrovincamine and Vincamine differ in structure by only one double bond, and the role and exact mechanism of (+)-14, 15-Dehydrovincamine remains to be elucidated in AKI. The present study demonstrated that (+)-14,15-Dehydrovincamine significantly ameliorated mitochondrial dysfunction and maintained mitochondrial homeostasis in a cisplatin-induced AKI model. Furthermore, (+)-14,15-Dehydrovincamine ameliorates cytochrome C-dependent apoptosis in renal tubular epithelial cells. c-Jun NH2-terminal kinase (JNK) was identified as a potential target protein of (+)-14,15-Dehydrovincamine attenuating AKI by network pharmacological analysis. (+)-14,15-Dehydrovincamine inhibited cisplatin-induced JNK activation, mitochondrial fission factor (Mff) phosphorylation, and dynamin-related protein 1 (Drp1) translocation to the mitochondria in renal tubular epithelial cells. Meanwhile, the JNK activator anisomycin restored Mff phosphorylation and Drp1 translocation, counteracting the protective effect of (+)-14,15-Dehydrovincamine on mitochondrial dysfunction in cisplatin-induced TECs injury. In conclusion, (+)-14,15-Dehydrovincamine reduced mitochondrial fission, maintained mitochondrial homeostasis, and attenuated apoptosis by inhibiting the JNK/Mff/Drp1 pathway, which in turn ameliorated cisplatin-induced AKI.

Screening and molecular docking verification of feature genes related to phospholipid metabolism in hepatocarcinoma caused by hepatitis B.

BACKGROUND: The progression of tumours is related to abnormal phospholipid metabolism. This study is anticipated to present a fresh perspective for disease therapy targets of hepatocarcinoma caused by hepatitis B virus in the future by screening feature genes related to phospholipid metabolism. METHODS: This study analysed GSE121248 to pinpoint differentially expressed genes (DEGs). By examining the overlap between the metabolism-related genes and DEGs, the research focused on the genes involved in phospholipid metabolism. To find feature genes, functional enrichment studies were carried out and a network diagram was proposed. These findings were validated via data base of The Cancer Genome Atlas (TCGA). Further analyses included immune infiltration studies and metabolomics. Finally, the relationships between differentially abundant metabolites and feature genes were confirmed by molecular docking, providing a thorough comprehension of the molecular mechanisms. RESULTS: The seven genes with the highest degree of connection (PTGS2, IGF1, SPP1, BCHE, NR1I2, NAMPT, and FABP1) were identified as feature genes. In the TCGA database, the seven feature genes also had certain diagnostic efficiency. Immune infiltration analysis revealed that feature genes regulate the infiltration of various immune cells. Metabolomics successfully identified the different metabolites of the phospholipid metabolism pathway between patients and normal individuals. The docking study indicated that different metabolites may play essential roles in causing disease by targeting feature genes. CONCLUSIONS: In this study, for the first time, it reveals the possible involvement of genes linked to phospholipid metabolism-related genes using bioinformatics analysis. Identifying genes and probable therapeutic targets could provide clues for the further treatment of disease.

A case study: Lecanicillium infection detected in the human body.

Lecanicillium dimorphum and Lecanicillium psalliotae are fungi that exist naturally in plants or insects, and are generally considered non-pathogenic to humans. However, in this case, we cultured Lecanicillium from the synovial fluid of a patient, and identified it through genome sequencing and sequence alignment as Lecanicillium dimorphum or Lecanicillium psalliotae. Due to the conservation of sequences, we can only identify the genus and not the species. There are very few reports on the human infection and pathogenicity of these two fungi, and this case also cannot completely prove that the pathogenic agent is this fungus. But this case also holds clinical significance, as the discovery of Lecanicillium in a human sample can alert the clinician to the presence of an uncommon mold with unclear clinical significance.

Fusobacterium nucleatum bacteremia complicated with intracranial Porphyromonas gingivalis and HSV-1 infection: a case report and literature review.

BACKGROUND: Fusobacterium nucleatum (F. nucleatum) belongs to the genus Fusobacterium, which is a gram-negative obligate anaerobic bacterium. Bacteremia associated with F. nucleatum is a serious complication, which is not common in clinic, especially when it is combined with other intracranial pathogenic microorganism infection. We reported for the first time a case of F. nucleatum bacteremia combined with intracranial Porphyromonas gingivalis (P. gingivalis) and herpes simplex virus type 1(HSV-1) infection. CASE PRESENTATION: A 60-year-old woman was admitted to our hospital with a headache for a week that worsened for 2 days. Combined with history, physical signs and examination, it was characterized as ischemic cerebrovascular disease (ICVD). F. nucleatum was detected in blood by matrix-assisted laser desorption/ionization time-offight mass spectrometry (MALDI-TOF-MS). Meanwhile, P. gingivalis and HSV-1 in cerebrospinal fluid (CSF) were identified by metagenome next generation sequencing (mNGS). After a quick diagnosis and a combination of antibiotics and antiviral treatment, the patient recovered and was discharged. CONCLUSION: To our knowledge, this is the first report of intracranial P. gingivalis and HSV-1 infection combined with F. nucleatum bacteremia.

PTX3 promotes breast cancer cell proliferation and metastasis by regulating PKCζbreast cancer, pentraxin 3, protein kinase Cζ, proliferation, metastasis.

Breast cancer (BC) is the most commonly diagnosed cancer in women, providing a leading cause of death from malignancy. Pentraxin 3 (PTX3) and protein kinase C ζ (PKCζ) are both known to exert important roles in the progression of multiple types of tumors, including BC. The present study aimed to explore both their interaction and their role in promoting the proliferation and metastasis of BC. The expression level of PTX3 was found to be elevated both in patients with BC and in BC cells; furthermore, it was found to be associated with lymph node metastasis in patients with BC. Knockdown of PTX3 decreased the rate of cell proliferation and the effects of a series of metastasis-associated cellular processes, including cell chemotaxis, migration, adhesion and invasion, as well as diminishing actin polymerization of the MDA-MB-231 and MCF7 BC cells, and decreasing tumor pulmonary metastasis in vivo. Mechanistically, PTX3 and PKCζ were found to be colocalized intracellularly, and they were co-translocated to the cell membrane upon stimulation with epidermal growth factor. Following the knockdown of PTX3, both the phosphorylation and membrane translocation of PKCζ were significantly impaired, suggesting that PTX3 regulates the activation of PKCζ. Taken together, the findings of the present study have shown that PTX3 may promote the proliferation and metastasis of BC cells through regulating PKCζ activation to enhance cell migration, cell chemotaxis, cell invasion and cell adhesion.

Establishment and Validation of a Blood Test-based Nomogram to Diagnose Patients with AFP-negative HCC.

BACKGROUND: Hepatocellular carcinoma (HCC) is the fourth leading cause of cancer death worldwide. Alpha-protein (AFP) is the most widely used blood biomarker for HCC. However, elevated serum AFP is only observed in part of HCC. AIMS: This study aimed to develop an efficient nomogram model to distinguish patients with alpha- protein-negative HCC and liver cirrhosis. OBJECTIVES: A total of 1130 patients (508 HCC patients + 622 cirrhosis patients) were enrolled in the training cohort. A total of 244 HCC patients and 246 cirrhosis patients were enrolled in the validation cohort. METHODS: A total of 41 parameters about blood tests were analyzed with logistic regression. The nomogram was based on independent factors and validated both internally and externally. RESULTS: Independent factors were eosinophils %, hemoglobin concentration distribution width, fibrinogen, platelet counts, total bile acid, and mitochondria aspartate aminotransferase. The calibration curve for the probability of HCC showed good agreement between prediction by nomogram and actual observation. The concordance index was 0.851. In the validation cohort, the nomogram distinguished HCC from liver cirrhosis with an area under the curve of receiver operating characteristic of 0.754. CONCLUSION: This proposed nomogram was an accurate and useful method to distinguish patients with AFP-negative HCC from liver cirrhosis.

The diagnostic value of lipoprotein-associated phospholipase A2 in early diabetic nephropathy.

OBJECTIVE: The aim of this study was to investigate diagnosis of lipoprotein-associated phospholipase A2 (Lp-PLA2) in early diabetic nephropathy (DN). METHODS: A total of 342 type 2 diabetes mellitus (T2DM) patients hospitalized in department of metabolism and nephrology in our hospital from January 2019 to December 2019 were randomly selected. Patients were divided into three groups via urine albumin level: diabetes mellitus (DM) group, simple diabetes group (114 patients, urinary albumin creatinine ratio (UACR) < 30 mg/g); DN1 group, early DN group (114 patients, UACR: 30-300 mg/g); DN2 group: clinical DN group (114 patients, UACR > 300mg/g). Eighty healthy adults were examined at the same time. Lp-PLA2, fasting blood glucose (FBG), creatinine (Cr), triglyceride (TG), total cholesterol (TCHOL), high-density lipoprotein (HDL), low-density lipoprotein (LDL), haemoglobin A1c (HbA1c), blood urea nitrogen/creatinine (BUN/Cr), estimated glomerular filtration rate (eGFR), 24-h urine protein, albumin and creatinine of all subjects were detected and compared. Pearson's correlation analysis and multiple ordered logistic regression were used to investigate the correlation between serum Lp-PLA2 level and DN. The possibility of Lp-PLA2 in the diagnosis of early DN was studied by using the subject working curve. RESULTS: Lp-PLA2 level in DN1 and DN2 groups was significantly higher than that in DM group, with statistical difference (p < .05). With the progression of DN, the level of Lp-PLA2 gradually increased p < .05. Lp-PLA2 was positively correlated with FBG, TG, LDL and HbA1c (R = 0.637, p < .01; R = 0.314, p = .01; R = 0.213, p = .01; R = 0.661, p ≤ .01), was negatively correlated with HDL (r = -0.230, p < .01). The results showed that Lp-PLA2 was an independent factor in the evaluation of early DN. The area under the curve for the evaluation of serum Lp-PLA2 level in early DN was 0.841, the optimal critical value was 155.9 ng/mL, the sensitivity was 88% and the specificity was 76.2%. CONCLUSIONS: Lp-PLA2 is an independent factor for the evaluation of early DN, and can be used as an important potential specific indicator for the diagnosis of early DN, meanwhile monitoring the progression of DN.

Brachybacterium muris Detected in a Hepatocellular Carcinoma Patient with Pleural Effusion: A Case Report.

Background: Brachybacterium muris is a species of Gram positive and strictly aerobic bacterium. It was first reported in 2003 after being isolated from the liver of a laboratory mouse strain. It was also found on human skin and nasal cavity. Herein, we present the first case pleural effusion infection in humans caused by Brachybacterium muris. Case Presentation: A 65-year-old man was admitted to our hospital for a 4-week history of fever, accompanied by chills, occasional abdominal pain, occasional chest tightness and shortness of breath. On the day of hospitalization, thoracentesis was performed and 1000mL of yellow cloudy fluid was released. Result of pleural fluid culture was positive and B. muris was identified using 16S rDNA amplification and sequence comparisons. Conclusion: To our knowledge, this is the first report of pleural effusion infection caused by B. muris. B. muris can be pathogenic in humans.

A multi-subgroup predictive model based on clinical parameters and laboratory biomarkers to predict in-hospital outcomes of plasma exchange-centered artificial liver treatment in patients with hepatitis B virus-related acute-on-chronic liver failure.

Background: Postoperative risk stratification is challenging in patients with hepatitis B virus-related acute-on-chronic liver failure (HBV-ACLF) who undergo artificial liver treatment. This study characterizes patients' clinical parameters and laboratory biomarkers with different in-hospital outcomes. The purpose was to establish a multi-subgroup combined predictive model and analyze its predictive capability. Methods: We enrolled HBV-ACLF patients who received plasma exchange (PE)-centered artificial liver support system (ALSS) therapy from May 6, 2017, to April 6, 2022. There were 110 patients who died (the death group) and 110 propensity score-matched patients who achieved satisfactory outcomes (the survivor group). We compared baseline, before ALSS, after ALSS, and change ratios of laboratory biomarkers. Outcome prediction models were established by generalized estimating equations (GEE). The discrimination was assessed using receiver operating characteristic analyses. Calibration plots compared the mean predicted probability and the mean observed outcome. Results: We built a multi-subgroup predictive model (at admission; before ALSS; after ALSS; change ratio) to predict in-hospital outcomes of HBV-ACLF patients who received PE-centered ALSS. There were 110 patients with 363 ALSS sessions who survived and 110 who did not, and 363 ALSS sessions were analyzed. The univariate GEE models revealed that several parameters were independent risk factors. Clinical parameters and laboratory biomarkers were entered into the multivariate GEE model. The discriminative power of the multivariate GEE models was excellent, and calibration showed better agreement between the predicted and observed probabilities than the univariate models. Conclusions: The multi-subgroup combined predictive model generated accurate prognostic information for patients undergoing HBV-ACLF patients who received PE-centered ALSS.

Identifying Mitochondrial Transcription Factor A As a Potential Biomarker for the Carcinogenesis and Prognosis of Prostate Cancer.

Aims: Mitochondrial functional transformation contributes to the carcinogenesis of the prostate by meeting the metabolic needs of cancer cells. Mitochondrial transcription factor A (TFAM) is a pivotal regulator that maintains homeostasis of mitochondrial function. However, its role in prostate carcinogenesis has not been well elucidated. Materials and Methods: In the present study, we analyzed the expression of TFAM in normal prostate tissue and prostate cancer using public databases; a prostate-tissue chip was used to verify the results. The expression of TFAM in normal cells and in prostate cancer cells was determined by western blotting analysis. We knocked down TFAM in the prostate cancer cell line PC3 using a specific shRNA to explore the potential effects of TFAM in prostatic carcinogenesis. Results: We observed higher expression levels of TFAM in prostate cancer tissue than in normal prostate tissue and tumor adjacent normal tissues. A receiver operating characteristic curve was drawn that demonstrated the diagnostic efficacy of using TFAM expression for prostate cancer prognoses. Elevated levels of TFAM may indicate poorer overall survival in prostate cancer patients. Western blotting assays also showed that relative to the normal prostatic epithelial cell line RWPE-1, prostate cancer cell lines PC3 and DU145 expressed more TFAM protein. Furthermore, knockdown of TFAM inhibited the colony-formation capability of PC3 cells. Conclusion: Collectively, these results suggest that TFAM promotes carcinogenesis of the prostate, and may constitute a marker to be used in the diagnosis and prognosis of prostate cancer.

Programmed cell death and infectious diseases / 中国热带医学

@#Abstract: Cell death is a fundamental biological phenomenon that is essential for the survival and development of organisms. Cell death can be either a spontaneous programmed process by the host or an accidentally triggered process. According to the different signaling pathway activated by various stimulates, programmed cell death exhibits the lytic or non-lytic morphology. For example, apoptosis, a typical non-lytic form of cell death, exhibits cell shrinkage and induces the formation of apoptotic bodies. Pyroptosis mediated by cysteine-containing aspartate-specific protease-1/11 (caspase-1/11) and necroptosis can induce inflammatory reactions and promote cell lysis to release inflammatory cytokines via triggering the pore-forming mechanism of the cell membrane, representing a typical modes of lytic cell death. In addition, the release of reactive oxygen species caused by the damaged mitochondria may further trigger ferroptosis during the pathogen infection. Programmed cell death can play an immune defensive role by eliminating infected cells and intracellular pathogens and stimulating the innate immune response through the resulting cell corpses. Here, we discuss the molecular mechanisms of five programmed cell death pathways: apoptosis, pyroptosis, ferroptosis, necroptosis and PANoptosis. We describe their roles in the innate immune defense against bacterial infections and give a brief statement of the interactions between the different programmed cell death, hoping to provide new insights for in-depth study of the pathogenic mechanisms of infectious diseases.

Diagnostic and prognostic nomograms for newly diagnosed intrahepatic cholangiocarcinoma with brain metastasis: A population-based analysis.

Brain metastasis (BM) is one of the rare metastatic sites of intrahepatic cholangiocarcinoma (ICC). ICC with BM can seriously affect the quality of life of patients and lead to a poor prognosis. The aim of this study was to establish two nomograms to estimate the risk of BM in ICC patients and the prognosis of ICC patients with BM. Data on 19,166 individuals diagnosed with ICC were retrospectively collected from the Surveillance, Epidemiology, and End Results (SEER) database. Independent risk factors and prognostic factors were identified by the logistic and the Cox regression, respectively. Next, two nomograms were developed, and their discrimination was estimated by concordance index (C-index) and calibration plots, while the clinical benefits of the prognostic nomogram were evaluated using the receiver operating characteristic (ROC) curves, the decision curve analysis (DCA), and the Kaplan-Meier analyses. The independent risk factors for BM were T stage, N stage, surgery, alpha-fetoprotein (AFP) level, and tumor size. T stage, surgery, radiotherapy, and bone metastasis were prognostic factors for overall survival (OS). For the prognostic nomogram, the C-index was 0.759 (95% confidence interval (CI) = 0.745-0.773) and 0.764 (95% CI = 0.747-0.781) in the training and the validation cohort, respectively. The calibration curves revealed a robust agreement between predictions and actual observations probability. The area under curves (AUCs) for the 3-, 6-, and 9-month OS were 0.721, 0.727, and 0.790 in the training cohort and 0.702, 0.777, and 0.853 in the validation cohort, respectively. The DCA curves yielded remarkable positive net benefits over a wide range of threshold probabilities. The Kaplan-Meier analysis illustrated that the nomogram could significantly distinguish the population with different survival risks. We successfully established the two nomograms for predicting the incidence of BM and the prognosis of ICC patients with BM, which may assist clinicians in choosing more effective treatment strategies.

CONSORT-Characteristics and metabolic phenotype of gut microbiota in NAFLD patients.

ABSTRACT: Patients with nonalcoholic fatty liver disease (NAFLD) have symptoms of a gut microbiota disorder with abnormal amino acid and glycolipid metabolism. This study was designed to analyze the characteristics of gut microbiota in patients with NAFLD, predict the gut microbiota phenotype, explore its role in the diagnosis of NAFLD, and establish its significance in disease progression.The characteristics of the gut microbiota in NAFLD patients (n = 28, 45.8 ±â€Š14.2 years, male/female = 18/10) and healthy subjects (n = 20, 49.6 ±â€Š4.8 years, male/female = 14/6) during March-May 2020 were analyzed using 16S rRNA sequencing technology and the phenotypes with large differences were predicted using the Tax4Fun method. The metabolites in the fecal samples of the patients were analyzed using mass spectrometry, and their correlation with different microorganisms was examined. The accuracy of the gut microbiota in diagnosing NAFLD was investigated by receiver operating characteristic curve analysis.We found that the microbial diversity and Bacteroides/Firmicutes (BF) ratio changed significantly (P < .05) in the feces of NAFLD patients. Phenotypic prediction showed that there were significant differences in the phenotypes of amino acid, glucose, and lipid metabolism of gut microbiota in the NAFLD group (P < .05). receiver operating characteristic curve analysis revealed that combination of Bacteroides and the BF ratio resulted in 88% and 100% sensitivity and specificity, respectively, when used for NAFLD diagnosis. Metabolomics and bioinformatics analysis revealed changes in the metabolism of nicotinate, nicotinamide, and pyrimidine; signaling pathways of calcium and oxytocin; pancreatic secretion with metabolites such as uracil, xanthine, and biliverdin; and enzymes such as xanthine dehydrogenase and xanthine oxidase (P < .05).Therefore, the phenotypic changes may be a potential marker for NAFLD and we considered that a combined analysis of Bacteroides and BF ratio had good diagnostic accuracy for NAFLD.

Metabolomics Identifies Biomarker Signatures to Differentiate Pancreatic Cancer from Type 2 Diabetes Mellitus in Early Diagnosis.

METHODS: Plasma metabolic profiles in 26 PC patients, 27 DM patients, and 23 healthy volunteers were examined using an ultraperformance liquid chromatography coupled with tandem mass spectrometry platform. Differential metabolite ions were then identified using the principal component analysis (PCA) model and the orthogonal partial least-squares discrimination analysis (OPLS-DA) model. The diagnosis performance of metabolite biomarkers was validated by logistic regression models. RESULTS: We established a PCA model (R2X = 23.5%, Q2 = 8.21%) and an OPLS-DA model (R2X = 70.0%, R2Y = 84.9%, Q2 = 69.7%). LysoPC (16 : 0), catelaidic acid, cerebronic acid, nonadecanetriol, and asparaginyl-histidine were found to identify PC, with a sensitivity of 89% and a specificity of 91%. Besides, lysoPC (16 : 0), lysoPC (16 : 1), lysoPC (22 : 6), and lysoPC (20 : 3) were found to differentiate PC from DM, with higher accuracy (68% versus 55%) and higher AUC values (72% versus 63%) than those of CA19-9. The diagnostic performance of metabolite biomarkers was finally validated by logistic regression models. CONCLUSION: We succeeded in screening differential metabolite ions among PC and DM patients and healthy individuals, thus providing a preliminary basis for screening the biomarkers for the early diagnosis of PC.

Identification and Validation of Hub Genes Associated With Hepatocellular Carcinoma Via Integrated Bioinformatics Analysis.

Hepatocellular carcinoma (HCC) is the most common malignant tumor of the liver, with high morbidity and mortality, yet its molecular mechanisms of tumorigenesis are still unclear. In this study, gene expression profile of GSE62232 was downloaded from the Gene Expression Omnibus (GEO). The RNA-seq expression data and relative clinical information were retrieved from the Cancer Genome Atlas (TCGA) database. The datasets were analyzed by differential gene expression analysis and Weighted Gene Co-expression Network Analysis (WGCNA) to obtain the overlapping genes. Then, we performed a functional enrichment analysis to understand the potential biological functions of these co-expression genes. Finally, we constructed the protein-protein interaction (PPI) analysis combined with survival analysis. MARCO, CLEC4M, FCGR2B, LYVE1, TIMD4, STAB2, CFP, CLEC4G, CLEC1B, FCN2, FCN3 and FOXO1 were identified as the candidate hub genes using the CytoHubba plugin of Cytoscape. Based on survival analysis, the lower expression of FCN3 and FOXO1 were associated with worse overall survival (OS) in HCC patients. Furthermore, the expression levels of FCN3 and FOXO1 were validated by the Human Protein Atlas (HPA) database and the qRT-PCR. In summary, our findings contribute new ideas for the precise early diagnosis, clinical treatment and prognosis of HCC in the future.

Prognostic Nomograms to Predict Overall Survival and Cancer-Specific Survival of Patients With Pancreatic Neuroendocrine Tumors: A Population-Based Study.

OBJECTIVE: The objective of this research was to construct and validate prognostic nomograms predicting overall survival (OS) and cancer-specific survival (CSS) in patients with pancreatic neuroendocrine tumors (pNETs). METHODS: We extracted 3787 patients with pNETs from the Surveillance, Epidemiology and End Results database. Nomograms for estimating 3- and 5-year OS and CSS were first established. Then, we used Harrell's Concordance Index, calibration plots, and the area under receiver operating characteristic curve to evaluate the nomograms. The Kaplan-Meier curve was plotted to evaluate the different survival outcomes. RESULTS: In the multivariate analysis, age, grade, functional status, American Joint Committee on Cancer stage, and surgery were associated with OS and CSS. The established nomograms had good discriminative ability, with a Harrell's Concordance Index of 0.830 for OS and 0.855 for CSS. The calibration plots also revealed good agreement. The area under receiver operating characteristic curve values of the nomograms predicting 3- and 5-year OS and CSS rates were 0.836, 0.816 and 0.859, 0.841, respectively. In addition, Kaplan-Meier curve indicated that patients with higher risk had worse survival outcomes. CONCLUSIONS: We have proposed and validated the nomograms predicting OS and CSS of pNETs. They can be convenient individualized tools to facilitate clinical decision making.

Clinical Parameters and Metabolomic Biomarkers That Predict Inhospital Outcomes in Patients With ST-Segment Elevated Myocardial Infarctions.

BACKGROUND: Postoperative risk stratification is challenging in patients with ST-segment elevation myocardial infarction (STEMI) who undergo percutaneous coronary intervention. This study aimed to characterize the metabolic fingerprints of patients with STEMI with different inhospital outcomes in the early stage of morbidity and to integrate the clinical baseline characteristics to develop a prognostic prediction model. METHODS: Plasma samples were collected retrospectively from two propensity score-matched STEMI cohorts from May 6, 2020 to April 20, 2021. Cohort 1 consisted of 48 survivors and 48 non-survivors. Cohort 2 included 48 patients with unstable angina pectoris, 48 patients with STEMI, and 48 age- and sex-matched healthy controls. Metabolic profiling was generated based on ultra-performance liquid chromatography and a mass spectrometry platform. The comprehensive metabolomic data analysis was performed using MetaboAnalyst version 5.0. The hub metabolite biomarkers integrated into the model were tested using multivariate linear support vector machine (SVM) algorithms and a generalized estimating equation (GEE) model. Their predictive capabilities were evaluated using areas under the curve (AUCs) of receiver operating characteristic curves. RESULTS: Metabonomic analysis from the two cohorts showed that patients with STEMI with different outcomes had significantly different clusters. Seven differentially expressed metabolites were identified as potential candidates for predicting inhospital outcomes based on the two cohorts, and their joint discriminative capabilities were robust using SVM (AUC = 0.998, 95% CI 0.983-1) and the univariate GEE model (AUC = 0.981, 95% CI 0.969-0.994). After integrating another six clinical variants, the predictive performance of the updated model improved further (AUC = 0.99, 95% CI 0.981-0.998). CONCLUSION: A survival prediction model integrating seven metabolites from non-targeted metabonomics and six clinical indicators may generate a powerful early survival prediction model for patients with STEMI. The validation of internal and external cohorts is required.

The prognostic analysis of different metastatic patterns in pancreatic neuroendocrine tumors patients: A population based analysis.

OBJECTIVE: To evaluate the prognostic value of pancreatic neuroendocrine tumors (pNETs) with different metastatic patterns. METHODS: Data of pNETs cases were extracted from the Surveillance, Epidemiology, and End Result (SEER) database. They were classified according to the different metastatic patterns. We utilized chi-square test to compare the clinical and metastasis characteristics among different groups. We used Kaplan-Meier analysis and log-rank testing for survival comparisons. Adjusted HRs with 95% CIs was calculated using Cox regression model to estimate prognostic factors. P < .05 was considered statistically significant. RESULTS: Among the 3909 patients, liver is the most metastatic organ, and isolated brain metastasis is the least common. At the same time, many patients have had multiple metastases. We studied the overall survival (OS) and cancer-specific survival (CCS) of the groups. OS: Non-organ metastasis: 5-year OS = 77.1%; Bone metastasis: median survival time (MST) = 56 m, 5-year OS = 42.7%; Liver metastasis: MST = 24 m, 5-year OS = 25.5%; Lung metastasis: MST = 14 m, 5-year OS = 33.7%; multiple metastases: MST = 7m, 5-year OS = 12.0%. CCS: Non-organ metastasis: 5-year OS = 84.2%; Bone metastasis: 5-year OS = 52.5%; Liver metastasis: MST = 27 m, 5-year OS = 28.6%; Lung metastasis: MST = 49 m, 5-year OS = 40.1%; multiple metastases: MST = 8 m, 5-year OS = 14.5%. In addition, the results showed that there were all statistical significances between the surgery and the no surgery group (all, P < .001). Multivariate analysis revealed that brain metastasis, multiple metastases, age over 60 years, unmarried, grade III/IV, regional/distant and no surgery were independently associated with decreased OS and CCS. CONCLUSIONS: pNETs patients without organ metastasis had the best survival outcomes, while multiple had the worst outcomes. There were no significant differences in bone metastasis, liver metastasis and lung metastasis. Surgery was still an option for patients with metastasis.

HCV core antigen is a useful predictor during pegylated-interferon/ribavirin therapy in patients with hepatitis C virus genotype 1b.

Enzyme immunoassays for quantifying hepatitis C virus (HCV) core antigen (Ag) have been proposed as an alternative to HCV RNA detection. The present study aimed to investigate the early kinetics of serum HCVcAg and its usefulness in predicting virological responses.The clinical data of 135 patients with chronic hepatitis C treated with pegylated interferon alpha (PEG-IFN-α) and ribavirin was retrospectively collected. The patients were grouped according to their treatment outcomes as follows: sustained virological response (SVR), nonsustained virological response (N-SVR), and relapse.Higher HCVcAg and HCV RNA levels were observed in patients in the N-SVR group than in the other groups at baseline. HCVcAg better predicted rapid virological response (RVR) compared with HCV RNA and had a predictive value similar to that of HCV RNA for SVR and early virological response. In the relapse group, HCV RNA decreased to 0 after 48 weeks, whereas HCVcAg was still detectable, indicating that HCVcAg more sensitively predicted relapse in antiviral therapy than HCV RNA.For patients treated with PEG-INF-α and ribavirin, HCVcAg may more sensitively predict relapse than HCV RNA.

[High-performance liquid chromatography-mass spectrometry-based serum metabolic profiling in patients with HBV-related hepatocellular carcinoma].

OBJECTIVE: To explore the diagnostic value of the serum metabolites identified by high-performance liquid chromatography-mass spectrometry (HPLC/MS) for hepatitis B virus (HBV)-related hepatocellular carcinoma (HCC). METHODS: A total of 126 patients admitted to Tianjin Third Central Hospital were enrolled, including 27 patients with HBV-related hepatitis with negative viral DNA (DNA-N), 24 with HBV-related hepatitis with positive viral DNA, 24 with HBV-related liver cirrhosis, 27 with HBV-related HCC undergoing surgeries or radiofrequency ablation, and 24 with HBV-related HCC receiving interventional therapy, with 25 healthy volunteers as the normal control group. Serum samples were collected from all the subjects for HPLC/MS analysis, and the data were pretreated to establish an orthogonal partial least- squares discriminant analysis (OPLS-DA) model. The differential serum metabolites were preliminarily screened by comparisons between the HBV groups and the control group, and the characteristic metabolites were identified according to the results of non-parametric test. The potential clinical values of these characteristic metabolites were evaluated using receiver operator characteristic curve (ROC) analysis. RESULTS: A total of 25 characteristic metabolites were identified in the HBV- infected patients, including 9 lysophosphatidylcholines, 2 fatty acids, 17α-estradiol, sphinganine, 5-methylcytidine, vitamin K2, lysophosphatidic acid, glycocholic acid and 8 metabolites with few reports. The patients with HBV- related HCC showed 22 differential serum metabolites compared with the control group, 4 differential metabolites compared with patients with HBV-related liver cirrhosis; 10 differential metabolites were identified in patients with HBV-related HCC receiving interventional therapy compared with those receiving surgical resection or radiofrequency ablation. From the normal control group to HBV-related HCC treated by interventional therapy, many metabolites underwent variations following a similar pattern. CONCLUSIONS: We identified 25 characteristic metabolites in patients with HBV-related HCC, and these metabolites may have potential clinical values in the diagnosis of HBV-related HCC. The continuous change of some of these metabolites may indicate the possibility of tumorigenesis, and some may also have indications for the choice of surgical approach.