Objective:To investigated the relationship between magnetic resonance imaging(MRI)parameters and the molecular pathology of primary central nervous system lymphoma(PCNSL).Methods:We retrospectively analyzed 26 patients from The First Affiliated Hospital of Harbin Medical University between January 2020 and June 2023 classified into germinal center B-cell like(GCB)and non-germinal center B-cell like(non-GCB)groups based on cell origin,into Ki-67≥75%and<75%groups based on the Ki-67 index,into BCL-2+and BCL-2-groups based on BCL-2 expression,and into responsive and non-responsive groups based on their response to MAP+Bruton's tyrosine kinase inhib-itor(BTKi)treatment.We extracted and compared first-order parameters between the groups,including mean value,standard deviation,variance,coefficient of variation,skewness,kurtosis,and entropy from baseline MRI images.Results:Four parameters(variance,kurtosis,skewness,and coefficient of variation)showed no significant differences between groups.However,three parameters(mean,standard devi-ation,and entropy)significantly differed between the groups based on Ki-67 and BCL-2 expression.For the Ki-67 index,the three parameters'areas under the curve(AUC)were 0.731,0.831,and 0.913,respectively.For BCL-2 expression,the mean and standard deviation AUCs were 0.889 and 0.938,respectively.In addition,the mean and entropy parameters significantly differed between the groups categorized by cell origin and treatment responsiveness(P<0.05).Multi-parameter joint analysis demonstrated greater identification accuracy compared to util-izing individual quantitative parameters from texture analysis.Conclusions:The mean,standard deviation,and entropy MRI parameters can help predict Ki-67 and BCL-2 expression in patients with PCNSL and have evaluative functions for treatment.They are beneficial for preoper-ative non-invasive assessment of tumor malignancy,providing vidence for prognosis and treatment planning.

Objective To investigate changes and clinical significance in plasma free amino acid levels during the progression from chronic hepatitis B(CHB)to liver cirrhosis(LC)and ultimately to hepatocellular carcinoma(HCC).Methods The plasma samples of 49 CHB patients,43 CHB-related LC patients and 50 CHB-related HCC patients were analyzed using the Hitachi L-8900 amino acid analyzer.The differences in amino acid levels were compared between groups.Simultaneously,the MetaboAnalyst website was used to analyze the relevant amino acid metabolism pathways.Results A total of 16 amino acids with different expression levels were identified.During the development from CHB to HCC,plasma levels of cystine,phenylalanine and glycine gradually increased,while the ratio of branched chain amino acids/aromatic amino acids gradually decreased.Compared with the CHB and the LC groups,levels of taurine,methionine,tyrosine,ornithine,glutamate,isoleucine and tryptophan were significantly increased in the HCC group,while the level of arginine was significantly lower.Compared with the CHB group,levels of serine,alanine and proline were higher in the LC and the HCC groups,while the level of valine was also higher in the HCC group(all P＜0.05).The metabolic pathway analysis of three groups showed significant changes in various metabolic pathways,including phenylalanine,tyrosine,tryptophan biosynthesis,phenylalanine metabolism,glycine,serine,threonine metabolism,valine,leucine,isoleucine biosynthesis,and taurine metabolism.In addition,by constructing a network diagram of amino acid enzyme gene interactions,a total of 79 metabolic enzyme genes related to amino acid expression were discovered.Conclusion Plasma levels of amino acids are of certain guiding significance for early warning and prognosis of HCC and can provide a theoretical basis and methodological basis for the diagnosis and treatment of HCC in the future.

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.

Objective:To screen the pivotal genes involved in the occurrence and development of HBV-associated HCC. Additionally, perform validation and biological function analysis to evaluate changes in the expression of pivotal genes and their prognostic value in patients with hepatocellular carcinoma.Methods:The GSE121248 gene expression profile data of HBV-HCC patients were searched and downloaded from the GEO database. The R language was used to compare the differences in gene expression between hepatocellular carcinoma and paracancerous tissues. KEGG and GO function enrichment analyses were performed on the differential genes. PPI plots and pivotal gene screening were carried out through online tools like STRING and Cytoscape software. 369 cases of hepatocellular carcinoma and 160 healthy controls in TCGA and GTEx were used as validation cohorts to verify the expression levels of the pivotal genes. A Kaplan-Meier plot was drawn to evaluate the prognostic value of the pivotal gene.Results:A total of 120 differentially expressed genes were screened, of which 89 were up-regulated and 31 were down-regulated. Differential genes were mainly enriched in the metabolic pathways related to retinol metabolism, cytochrome P450 metabolism, and the p53 signaling pathway. The top 10 differential genes were selected as pivotal genes by the Cytoscape plug-in cytoHubba. There were significant differences in the expression levels of four types of CCNB1, CDK1, RRM2, and TOP2A genes in the validation cohort. All four types of genes were up-regulated. Survival analysis showed that patients with elevated expression levels of four genes had a poorer prognosis, with statistical differences in results.Conclusion:Four types of genes, CCNB1, CDK1, RRM2, and TOP2A, have high expression levels in patients with HBV-HCC and are correlated to shorter survival times, making them a potential target for diagnosis, prognosis, and treatment.

Objective:To investigate the change and clinical significance of serum alkaline phosphatase (ALP) level in patients with acute spontaneous intracerebral hemorrhage(AICH).Methods:81 patients with AICH admitted to the Neurosurgery Department of Tianjin Third Central Hospital from January 2019 to October 2020 were retrospectively analyzed. 81 patients with non cerebral hemorrhage who came from the health examination center or complained of dizziness and had no hepatobiliary and skeletal diseases were selected as the control group. The clinical data of all the patients were recorded, including gender, age, Glasgow Coma Scale (GCS) score, hemorrhage location, liver function indexes, the history of hypertension, diabetes, heart disease, smoking, drinking, and so on. The differences in clinical data between the two groups were compared. Pearson correlation was used to analyze the correlation between liver function indexes and GCS score. The independent risk factors for AICH were screened by binary logistic regression, and the receiver operating characteristic (ROC) curve was used to evaluate the value of serum ALP in predicting intracerebral hemorrhage.Results:Serum ALP level in AICH group was significantly higher than that in the control group [85.0(70.0, 103.0) U/L vs 65.0(54.5, 71.5)U/L, Z=6.740, P<0.001]. Pearson correlation analysis showed that serum ALP had a negative correlation with GCS score ( r=0.255, P=0.022). Binary logistic regression analysis showed that hypertension ( OR=20.440, 95% CI 8.572-48.737) and ALP ( OR=1.077, 95% CI 1.049-1.105) were risk factors for intracerebral hemorrhage. Serum ALP level was an independent risk factor ( OR=1.069, 95% CI 1.038-1.101) for AICH after adjusting for confounding variables including age, AST, history of hypertension. ROC curve showed that the area under the curve (AUC) of serum ALP in predicting intracerebral hemorrhage was 0.807 (95% CI 0.740-0.873, P<0.001), with sensitivity of 67.9% and specificity of 81.5%. Conclusions:Serum ALP level may be related to the occurrence and severity of AICH. Therefore, serum ALP level can be used as a reference index to evaluate the occurrence, severity of patients with AICH.

Objective:To study the changes of urinary metabolic profile, screen metabolic ions characterization with clinical diagnostic value, and a disease differentiation model establishment, in an attempt to help the clinical diagnosis of hepatocellular carcinoma patients.Methods:A case-control study was conducted. Ultra-performance liquid chromatography/mass spectrometry (UPLC-MS) were used to analyze urine samples of 32 patients with hepatocellular carcinoma, 28 patients with liver cirrhosis and 28 healthy persons, respectively. The orthogonal partial least squares discriminant analysis (OPLS-DA) and the principal component analysis (PCA) model were constructed using MZmine2.0 and SIMCA-P + 12.0.1.0 software for preliminary screening of metabolites. The metabolic ions selected in the final test were analyzed by SPSS, and the markers were analyzed and screened by one-way analysis of variance. Finally, the sensitivity and specificity of the selected markers were analyzed by calculating the area under the receiver operating characteristic (ROC) curve. One-way analysis of variance was used to compare quantitative indicators between groups.Results:OPLS-DA model parameters were R2X = 35.3%, R2Y = 86.9%, and Q2 = 72.2%, which had a good identification value. A total of 26 characteristic ions were screened, of which 17 were identified. 14, 19-Dihydroaspidospermatine had a high value in distinguishing healthy person with hepatocellular carcinoma patients, and the area under the receiver operating characteristic curve was higher than 0.9. The area under the ROC curve for distinguishing liver cancer with liver cirrhosis patients was 0.88, which was higher than the ROC curve of alpha-fetoprotein (0.75).Conclusion:Based on the UPLC-MS platform, the PCA and OPLS-DA models were successfully constructed, and the characteristic metabolic ions in the urine were extracted and identified, which has a certain value in assisting clinical screening of hepatocellular carcinoma patients.

To provide new ideas for clinical diagnosis and treatment of coronavirus disease 2019 (COVID-19), this study explore the expression level and prognostic value of platelet parameters in mild, moderate and severe COVID-19. This is a retrospective analysis. From January to May 2020, a total of 69 patients who were diagnosed with COVID-19 in the Third Central Hospital and the Jinnan Hospital (both situated in Tianjin) were enrolled in the disease group. According to the severity, these patients were divided into mild group (15 cases), moderate group (46 cases), and severe group (8 cases). In the same period, 70 non-infected patients were enrolled in control group. The level of white blood cell count (WBC), absolute neutrophil count (NEU#), absolute lymphocyte count (LY#), neutrophil-lymphocyte ratio (NLR), red blood cell count (RBC), hemoglobin (Hb), platelet count (PLT), mean platelet volume (MPV), platelet distribution width (PDW), and platelet-large contrast ratio (P-LCR) before and after treatment were analyzed. Binary logistic regression analysis is used to establish a mathematical model of the relationship between these indexes and the outcome of severe COVID-19 patients. The receiver operating characteristic(ROC) curve is used to further explore the prognosis value of MPV, P-LCR, NLR separately and jointly in COVID-19 patients. Compare to the control group, WBC and NE# increase ( Z=-5.63, P<0.01; Z=-9.19, P<0.01) and LY# decrease ( Z=-9.34, P<0.01) in the severe group; NLR increase with the aggravation of the disease, there is significant difference between groups ( Z=17.61, P<0.01); PLT, PDW, MPV and P-LCR decrease with the aggravation of the disease, there is significant difference between groups ( Z=9.47, P<0.01; Z=11.41, P<0.01; Z =16.76, P<0.01; Z=13.97, P<0.01). Binary logistic regression analysis shows MPV, P-LCR and NLR have predictive value for severe COVID-19 patients. There is a negative correlation between MPV, P-LCR and severe COVID-19 patients ( OR=1.004, P=0.034; OR=1.097, P=0.046). There is a positive correlation between NLR and severe COVID-19 patients ( OR=1.052, P=0.016). MPV and P-LCR of patients with good prognosis after treatment were significantly higher than those before treatment ( Z=-6.47, P<0.01; Z=-5.36, P<0.01). NLR was significantly lower than that before treatment ( Z=-8.13, P<0.01). MPV and P-LCR in poor prognosis group were significantly lower than those before treatment ( Z=-9.46, P<0.01; Z=-6.81, P<0.01). NLR was significantly higher than that before treatment ( Z=-3.24, P<0.01). There were significant differences between good and poor prognosis groups before and after treatment in MPV, P-LCR and NLR ( P<0.01). Combination of these three indexes, ROC shows the AUC is 0.931, the sensitivity is 91.5%, the specificity is 94.1%, the positive predictive value is 88.9%, and the negative predictive value is 87.4%, which is better than any of these indexes separately. Changes in these parameters are closely related to clinical stage of COVID-19 patients. MPV, P-LCR and NLR are of great value in the prediction and prognosis of severe COVID-19 patients.

To provide new ideas for clinical diagnosis and treatment of coronavirus disease 2019 (COVID-19), this study explore the expression level and prognostic value of platelet parameters in mild, moderate and severe COVID-19. This is a retrospective analysis. From January to May 2020, a total of 69 patients who were diagnosed with COVID-19 in the Third Central Hospital and the Jinnan Hospital (both situated in Tianjin) were enrolled in the disease group. According to the severity, these patients were divided into mild group (15 cases), moderate group (46 cases), and severe group (8 cases). In the same period, 70 non-infected patients were enrolled in control group. The level of white blood cell count (WBC), absolute neutrophil count (NEU#), absolute lymphocyte count (LY#), neutrophil-lymphocyte ratio (NLR), red blood cell count (RBC), hemoglobin (Hb), platelet count (PLT), mean platelet volume (MPV), platelet distribution width (PDW), and platelet-large contrast ratio (P-LCR) before and after treatment were analyzed. Binary logistic regression analysis is used to establish a mathematical model of the relationship between these indexes and the outcome of severe COVID-19 patients. The receiver operating characteristic(ROC) curve is used to further explore the prognosis value of MPV, P-LCR, NLR separately and jointly in COVID-19 patients. Compare to the control group, WBC and NE# increase ( Z=-5.63, P<0.01; Z=-9.19, P<0.01) and LY# decrease ( Z=-9.34, P<0.01) in the severe group; NLR increase with the aggravation of the disease, there is significant difference between groups ( Z=17.61, P<0.01); PLT, PDW, MPV and P-LCR decrease with the aggravation of the disease, there is significant difference between groups ( Z=9.47, P<0.01; Z=11.41, P<0.01; Z =16.76, P<0.01; Z=13.97, P<0.01). Binary logistic regression analysis shows MPV, P-LCR and NLR have predictive value for severe COVID-19 patients. There is a negative correlation between MPV, P-LCR and severe COVID-19 patients ( OR=1.004, P=0.034; OR=1.097, P=0.046). There is a positive correlation between NLR and severe COVID-19 patients ( OR=1.052, P=0.016). MPV and P-LCR of patients with good prognosis after treatment were significantly higher than those before treatment ( Z=-6.47, P<0.01; Z=-5.36, P<0.01). NLR was significantly lower than that before treatment ( Z=-8.13, P<0.01). MPV and P-LCR in poor prognosis group were significantly lower than those before treatment ( Z=-9.46, P<0.01; Z=-6.81, P<0.01). NLR was significantly higher than that before treatment ( Z=-3.24, P<0.01). There were significant differences between good and poor prognosis groups before and after treatment in MPV, P-LCR and NLR ( P<0.01). Combination of these three indexes, ROC shows the AUC is 0.931, the sensitivity is 91.5%, the specificity is 94.1%, the positive predictive value is 88.9%, and the negative predictive value is 87.4%, which is better than any of these indexes separately. Changes in these parameters are closely related to clinical stage of COVID-19 patients. MPV, P-LCR and NLR are of great value in the prediction and prognosis of severe COVID-19 patients.

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.
Carcinoma, Hepatocellular ; blood ; diagnosis ; virology ; Case-Control Studies ; Chromatography, High Pressure Liquid ; DNA, Viral ; blood ; Hepatitis B virus ; genetics ; Hepatitis B, Chronic ; blood ; virology ; Humans ; Liver Cirrhosis ; virology ; Liver Neoplasms ; blood ; diagnosis ; virology ; Mass Spectrometry ; Metabolome ; Metabolomics ; ROC Curve