Identification of the Predictive Models for the Treatment Response of Refractory/Relapsed B-Cell ALL Patients Receiving CAR-T Therapy.

Background/Aims: Chimeric antigen receptor (CAR) T cells for refractory or relapsed (r/r) B-cell acute lymphoblastic leukemia (ALL) patients have shown promising clinical effectiveness. However, the factors impacting the clinical response of CAR-T therapy have not been fully elucidated. We here aimed to identify the independent factors of CAR-T treatment response and construct the models for predicting the complete remission (CR) and minimal residual disease (MRD)-negative CR in r/r B-ALL patients after CAR-T cell infusion. Methods: Univariate and multivariate logistic regression analyses were conducted to identify the independent factors of CR and MRD-negative CR. The predictive models for the probability of remission were constructed based on the identified independent factors. Discrimination and calibration of the established models were assessed by receiver operating characteristic (ROC) curves and calibration plots, respectively. The predictive models were further integrated and validated in the internal series. Moreover, the prognostic value of the integration risk model was also confirmed. Results: The predictive model for CR was formulated by the number of white blood cells (WBC), central neural system (CNS) leukemia, TP53 mutation, bone marrow blasts, and CAR-T cell generation while the model for MRD-negative CR was formulated by disease status, bone marrow blasts, and infusion strategy. The ROC curves and calibration plots of the two models displayed great discrimination and calibration ability. Patients and infusions were divided into different risk groups according to the integration model. High-risk groups showed significant lower CR and MRD-negative CR rates in both the training and validation sets (p < 0.01). Furthermore, low-risk patients exhibited improved overall survival (OS) (log-rank p < 0.01), higher 6-month event-free survival (EFS) rate (p < 0.01), and lower relapse rate after the allogeneic hematopoietic stem cell transplantation (allo-HSCT) following CAR-T cell infusion (p = 0.06). Conclusions: We have established predictive models for treatment response estimation of CAR-T therapy. Our models also provided new clinical insights for the accurate diagnosis and targeted treatment of r/r B-ALL.

Clinical evidence for acupressure with the improvement of sleep disorders in hemodialysis patients: A systematic review and meta-analysis.

OBJECTIVE: To explore the efficacy of acupressure on the improvement of sleep disorders in patients undergoing hemodialysis. METHODS: A systematic review and meta-analysis was performed. Pubmed, Embase, the Cochrane database, and Chinese database were searched and sleep quality variables were extracted from eligible articles. The quality of original articles was assessed by the Modified Jadad Scale. Standard mean difference (SMD) and 95% confidential interval (CI) were pooled. RESULTS: Nine studies were included in the systematic review, and seven randomized controlled trials (RCTs) were eligible for meta-analysis. The pooled results showed significant improvement of quality of sleep using the acupressure massage (SMD = -0.81, 95%CI: -1.26, -0.36, P < 0.0001, I2 = 78.6%). No severe adverse event was reported during the acupressure intervention. CONCLUSIONS: The results provide further evidence favoring the efficacy and safety of acupressure on the improvement of quality of sleep in hemodialysis patients.

Simplified nomograms based on platelet-associated models for survival prediction in Asian hepatocellular carcinoma patients after surgery.

BACKGROUND & AIMS: Accumulating evidence showed platelets were closely related to hepatocellular carcinoma (HCC) prognosis. We here aimed to develop two simple-to-use nomograms based on the PLT-associated modified models to refine prognostic prediction of Asian HCC. METHODS: The nomograms were established using 684 eligible Asian patients who received curative resection for HCC, among which 456 and 228 were randomly assigned to the derivation and validation cohorts, respectively. Univariate and multivariate Cox analyses in the derivation set were used to identify the independent prognostic factors of the hepatectomy patients as the nomogram variables. We evaluated the discrimination and calibration of the nomograms by concordance indexes (C-index), calibration plots and Kaplan-Meier curves. The discrimination ability of the PLT-based nomograms was compared with the conventional staging systems using time-dependent receiver operating characteristic (ROC) curves. RESULTS: The nomogram for overall survival (OS) estimation was comprised of MPV/PC [mean platelet volume/platelet count], SII [systemic immune-inflammation index], NPS [neutrophil-platelet score], PAPAS [platelet count/age/ALP/AFP/AST index] and S index. And the nomogram for recurrence-free survival (RFS) prediction was of NPS, PAPAS and S index. The C-indexes of the OS nomogram in the derivation and validation sets were 0.704 and 0.707, and those of the RFS nomogram were 0.668 and 0.703. The calibration plots fitted well. The survival curves showed great discriminatory powers. The area under the curve (AUC) of our nomograms were significantly larger than that of the three conventional models (P < 0.05). CONCLUSIONS: The two PLT-based nomograms were accurate in predicting the OS and RFS of Asian HCC patients after hepatectomy.

Identification of a molecular subtyping system associated with the prognosis of Asian hepatocellular carcinoma patients receiving liver resection.

Hepatocellular carcinoma (HCC) remains a severe health issue worldwide, especially in Asia. To date, molecular classifications proposed for the overall survival (OS) or recurrence-free survival (RFS) prediction of Asian HCC patients after hepatectomy are quite few and limited in clinical practice. Here, we established a molecular subtyping system for Asian HCC to facilitate prognosis evaluation. Firstly, differentially expressed genes (DEGs) (FDR [false discovery rate] <0.05) between different types of liver cancer and non-tumor tissue were screened. Among the DEGs solely between HCC and non-tumor samples, 185 genes simultaneously significantly associated with the OS and RFS were identified as HCC-characteristic genes. The molecular subtypes were developed based on the expression profiles of the 185 genes in the training dataset (TCGA [The Cancer Genome Atlas] dataset) using non-negative matrix factorization (NMF) clustering method. Patients were then classified into Subtype1 and Subtype2 groups denoting unfavorable and favorable clinical outcome respectively. The robustness and effectiveness of the molecular subtype was confirmed in another independent dataset (GSE14520) by the same clustering approach and Kaplan-Meier analyses. Moreover, functional prediction analysis revealed that the identified molecular signature was involved in chemotaxis, apoptosis and cell development associated pathways. Besides, the molecular signature was closely related to the clinical characteristics including TNM stage, preoperative alpha-fetoprotein (AFP) level and TP53 mutation. Furthermore, integration of the molecular subtype and TNM stage was demonstrated to improve risk stratification. Taken together, our molecular subtyping system exhibited great utility and potential in prognosis prediction and therapeutic decision making of Asian HCC patients.

Seven-senescence-associated gene signature predicts overall survival for Asian patients with hepatocellular carcinoma.

BACKGROUND: Cellular senescence is a recognized barrier for progression of chronic liver diseases to hepatocellular carcinoma (HCC). The expression of a cluster of genes is altered in response to environmental factors during senescence. However, it is questionable whether these genes could serve as biomarkers for HCC patients. AIM: To develop a signature of senescence-associated genes (SAGs) that predicts patients' overall survival (OS) to improve prognosis prediction of HCC. METHODS: SAGs were identified using two senescent cell models. Univariate COX regression analysis was performed to screen the candidate genes significantly associated with OS of HCC in a discovery cohort (GSE14520) for the least absolute shrinkage and selection operator modelling. Prognostic value of this seven-gene signature was evaluated using two independent cohorts retrieved from the GEO (GSE14520) and the Cancer Genome Atlas datasets, respectively. Time-dependent receiver operating characteristic (ROC) curve analysis was conducted to compare the predictive accuracy of the seven-SAG signature and serum α-fetoprotein (AFP). RESULTS: A total of 42 SAGs were screened and seven of them, including KIF18B, CEP55, CIT, MCM7, CDC45, EZH2, and MCM5, were used to construct a prognostic formula. All seven genes were significantly downregulated in senescent cells and upregulated in HCC tissues. Survival analysis indicated that our seven-SAG signature was strongly associated with OS, especially in Asian populations, both in discovery and validation cohorts. Moreover, time-dependent ROC curve analysis suggested the seven-gene signature had a better predictive accuracy than serum AFP in predicting HCC patients' 1-, 3-, and 5-year OS. CONCLUSION: We developed a seven-SAG signature, which could predict OS of Asian HCC patients. This risk model provides new clinical evidence for the accurate diagnosis and targeted treatment of HCC.

IDH1 as a frequently mutated gene has potential effect on exosomes releasement by epigenetically regulating P2RX7 in intrahepatic cholangiocarcinoma.

Biliary tract cancers (BTCs) was heterogeneous and characterized by late diagnosis and fatal outcome. To identify new biomarkers for BTCs, we performed Robust Rank Aggreg (RRA) analysis and identified that IDH1 mutation was common in ICC, while IDH1R132C was the most frequent type. Moreover, we identified P2RX7 and other 45 genes as downregulated genes with hypermethylation in IDH1R132C mutated cells. The WGCNA results predicted that P2RX7 could influence cholangiocarcinoma by exosomes related manners. Finally, we confirmed that P2RX7 was downregulated in IDH1R132C mutated cells as well as the expression of CD9 and CD81 by experiments. In conclusion, IDH1R132C mutation was relatively prevalent in ICC. P2RX7 might be a potential downstream gene and it might be related to exosomes releasement.

Six-long non-coding RNA signature predicts recurrence-free survival in hepatocellular carcinoma.

BACKGROUND: Recent evidence shows that long non-coding RNAs (lncRNAs) are closely related to hepatogenesis and a few aggressive features of hepatocellular carcinoma (HCC). Increasing studies demonstrate that lncRNAs are potential prognostic factors for HCC. Moreover, several studies reported the combination of lncRNAs for predicting the overall survival (OS) of HCC, but the results varied. Thus, more effort including more accurate statistical approaches is needed for exploring the prognostic value of lncRNAs in HCC. AIM: To develop a robust lncRNA signature associated with HCC recurrence to improve prognosis prediction of HCC. METHODS: Univariate COX regression analysis was performed to screen the lncRNAs significantly associated with recurrence-free survival (RFS) of HCC in GSE76427 for the least absolute shrinkage and selection operator (LASSO) modelling. The established lncRNA signature was validated and developed in The Cancer Genome Atlas (TCGA) series using Kaplan-Meier curves. The expression values of the identified lncRNAs were compared between the tumor and non-tumor tissues. Pathway enrichment of these lncRNAs was conducted based on the significantly co-expressed genes. A prognostic nomogram combining the lncRNA signature and clinical characteristics was constructed. RESULTS: The lncRNA signature consisted of six lncRNAs: MSC-AS1, POLR2J4, EIF3J-AS1, SERHL, RMST, and PVT1. This risk model was significantly associated with the RFS of HCC in the TCGA cohort with a hazard ratio (HR) being 1.807 (95%CI [confidence interval]: 1.329-2.457) and log-rank P-value being less than 0.001. The best candidates of the six-lncRNA signature were younger male patients with HBV infection in relatively early tumor-stage and better physical condition but with higher preoperative alpha-fetoprotein. All the lncRNAs were significantly upregulated in tumor samples compared to non-tumor samples (P < 0.05). The most significantly enriched pathways of the lncRNAs were TGF-ß signaling pathway, cellular apoptosis-associated pathways, etc. The nomogram showed great utility of the lncRNA signature in HCC recurrence risk stratification. CONCLUSION: We have constructed a six-lncRNA signature for prognosis prediction of HCC. This risk model provides new clinical evidence for the accurate diagnosis and targeted treatment of HCC.

Combined eight-long noncoding RNA signature: a new risk score predicting prognosis in elderly non-small cell lung cancer patients.

The elderly are the majority of patients with non-small cell lung cancer (NSCLC). Compared to the overall population's predictive guidance, an effective predictive guidance for elderly patients can better guide patients' postoperative treatment and improve overall survival (OS) and disease-free survival (DFS). Recently, the long non-coding RNAs (lncRNAs) have been found to play an important role in predicting tumor prognosis. To identify potential lncRNAs to predict survival in elderly patients with NSCLC, in the present study, we chose 456 elderly patients with NSCLC and analyzed differentially expressed lncRNAs from four Gene Expression Omnibus (GEO) datasets (GSE30219, GSE31546, GSE37745 and GSE50081). We then constructed an eight-lncRNA formula to predict elderly patients' prognosis in NSCLC. Furthermore, we validated the prognostic values of the new risk model in two independent datasets, TCGA (n=670) and GSE31210 (n=130). Our data suggested a significant association between risk model and patients' prognosis. Finally, stratification analysis further revealed the eight-lncRNA signature was an independent factor to predict OS and DFS in stage I elderly patients from both the discovery and validation groups. Functional prediction revealed that 8 lncRNAs have potential effects on tumor immune processes such as lymphocyte activation and TNF production in NSCLC. In summary, our data provides evidence that the eight-lncRNA signature could serve as an independent biomarker to predict prognosis in elderly patients with NSCLC especially in elderly stage I patients.

Prognostic predictors for patients with hepatocellular carcinoma receiving adjuvant transcatheter arterial chemoembolization.

OBJECTIVES: We aimed to confirm the clinical effectiveness of postoperative adjuvant transcatheter arterial chemoembolization (PA-TACE) in patients with hepatocellular carcinoma after liver resection, and further identify the patients who could benefit most from PA-TACE. PATIENTS AND METHODS: Propensity score matching at a ratio of 1 : 2 was used between hepatectomy patients with and without receiving PA-TACE. Kaplan-Meier analysis was performed to compare overall survival and recurrence-free survival between two groups. Univariate COX regression and stratified analyses were performed to screen and identify survival predictors for PA-TACE patients. The identified predictive markers were validated in an external cohort. RESULTS: The propensity analysis matched 116 patients in PA-TACE group to 232 in the control group. Visible protective effect of PA-TACE was shown by survival curves in matched series (log-rank P=0.009 and 0.008), with hazard ratio of being 0.599 (95% confidence interval: 0.420-0.855) and 0.623 (95% confidence interval: 0.449-0.866), respectively, for overall survival and recurrence-free survival. The identified prognostic predictors for PA-TACE included TNM stage, tumor size and number, hepatitis B infection, spleen diameter, preoperative serum α-fetoprotein, alkaline phosphatase, γ-glutamyl transpeptidase and monocyte, and three risk signatures (aspartate aminotransferase-to-alanine aminotransferase ratio, neutrophil-to-lymphocyte ratio, and systemic immune-inflammation index). CONCLUSION: The treatment effectiveness of adjuvant transcatheter arterial chemoembolization for patients with hepatocellular carcinoma after surgery was validated in this study, and the best candidates for PA-TACE were identified as well, including patients with late-stage tumor, portal hypertension, and high preoperative serum levels of α-fetoprotein, alkaline phosphatase, γ-glutamyl transpeptidase, and monocytes.

A new risk score based on twelve hepatocellular carcinoma-specific gene expression can predict the patients' prognosis.

A large panel of molecular biomarkers have been identified to predict the prognosis of hepatocellular carcinoma (HCC), yet with limited clinical application due to difficult extrapolation. We here generated a genetic risk score system comprised of 12 HCC-specific genes to better predict the prognosis of HCC patients. Four genomics profiling datasets (GSE5851, GSE28691, GSE15765 and GSE14323) were searched to seek HCC-specific genes by comparisons between cancer samples and normal liver tissues and between different subtypes of hepatic neoplasms. Univariate survival analysis screened HCC-specific genes associated with overall survival (OS) in the training dataset for next-step risk model construction. The prognostic value of the constructed HCC risk score system was then validated in the TCGA dataset. Stratified analysis indicated this scoring system showed better performance in elderly male patients with HBV infection and preoperative lower levels of creatinine, alpha-fetoprotein and platelet and higher level of albumin. Functional annotation of this risk model in high-risk patients revealed that pathways associated with cell cycle, cell migration and inflammation were significantly enriched. In summary, our constructed HCC-specific gene risk model demonstrated robustness and potentiality in predicting the prognosis of HCC patients, especially among elderly male patients with HBV infection and relatively better general conditions.

A seven-long noncoding RNA signature predicts overall survival for patients with early stage non-small cell lung cancer.

Non-small cell lung cancer (NSCLC) is the most common cancer and cause of cancer-related mortality globally. Increasing evidence suggested that the long non-coding RNAs (lncRNAs) were involved in cancer-related death. To explore the possible prognostic lncRNA biomarkers for NSCLC patients, in the present study, we conducted a comprehensive lncRNA profiling analysis based on 1902 patients from Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) datasets. In the discovery phase, we employed 682 patients from the combination of four GEO datasets (GSE30219, GSE31546, GSE33745 and GSE50081) and conducted a seven-lncRNA formula to predict overall survival (OS). Next, we validated our risk-score formula in two independent datasets, TCGA (n=994) and GSE31210 (n=226). Stratified analysis revealed that the seven-lncRNA signature was significantly associated with OS in stage I patients from both discovery and validation groups (all P<0.001). Additionally, the prognostic value of the seven-lncRNA signature was also found to be favorable in patients carrying wild-type KRAS or EGFR. Bioinformatical analysis suggested that the seven-lncRNA signature affected patients' prognosis by influencing cell cycle-related pathways. In summary, our findings revealed a seven-lncRNA signature that predicted OS of NSCLC patients, especially in those with early tumor stage and carrying wild-type KRAS or EGFR.

A three-long non-coding RNA-expression-based risk score system can better predict both overall and recurrence-free survival in patients with small hepatocellular carcinoma.

Growing evidence indicates that long non-coding RNAs (lncRNAs) may be potential biomarkers and therapeutic targets for many disease conditions, including cancer. In this study, we constructed a risk score system of three lncRNAs (LOC101927051, LINC00667 and NSUN5P2) for predicting the prognosis of small hepatocellular carcinoma (sHCC) (maximum tumor diameter ≤5 cm). The prognostic value of this sHCC risk model was confirmed in TCGA HCC samples (TNM stage I and II). Stratified survival analysis revealed that the suitable patient groups of the sHCC lncRNA-signature included HBV-infected and cirrhotic patients with better physical conditions yet lower levels of albumin and higher levels of alpha-fetoprotein preoperatively. Besides, Asian patients with no family history of HCC or history of alcohol consumption can be predicted more precisely. Molecular functional analysis indicated that PYK2 pathway was significantly enriched in the high-risk patients. Pathway enrichment analysis indicated that the two lncRNAs (LINC00667 and NSUN5P2) associated with poor prognosis were closely related to cell cycle. The nomogram based on the lncRNA-signature for RFS prediction in sHCC patients exhibited good performance in recurrence risk stratification. In conclusion, we identified a novel three-lncRNA-expression-based risk model for predicting the prognosis of sHCC.

Identification of microRNA differentially expressed in three subtypes of non-small cell lung cancer and in silico functional analysis.

Emerging studies demonstrated that miRNAs played fundamental roles in lung cancer. In this study, we attempted to explore the clinical significance of the miRNA signature in different histological subtypes of non-small cell lung cancer (NSCLC). Three miRNome profiling datasets (GSE19945, GSE25508 and GSE51853) containing lung squamous cell carcinoma (SCC), lung adenocarcinoma (ADC) and large cell lung cancer (LCLC) samples were obtained for bioinformatics and survival analysis. Moreover, pathway enrichment and coexpression network were performed to explore underlying molecular mechanism. MicroRNA-375 (miR-375), miR-203 and miR-205 were identified as differentially expressed miRNAs (DEmiRNAs) which distinguished SCC from other NSCLC subtypes. Pathway enrichment analysis suggested that Hippo signaling pathway was combinatorically affected by above mentioned three miRNAs. Coexpression analysis of three miRNAs and the Hippo signaling pathway related genes were conducted based on another dataset, GSE51852. Four hub genes (TP63, RERE, TJP1 and YWHAE) were identified as the candidate targets of three miRNAs, and three of them (TP63, TJP1 and YWHAE) were validated to be downregulated by miR-203 and miR-375, respectively. Finally, survival analysis further suggested the prognostic value of three-miRNA signature in SCC patients. Taken together, our study compared the miRNA profiles among three histological subtypes of NSCLC, and suggested that a three-miRNA signature might be potential diagnostic and prognostic biomarkers for SCC patients.

Identification of Four Oxidative Stress-Responsive MicroRNAs, miR-34a-5p, miR-1915-3p, miR-638, and miR-150-3p, in Hepatocellular Carcinoma.

Increasing evidence suggests that oxidative stress plays an essential role during carcinogenesis. However, the underlying mechanism between oxidative stress and carcinogenesis remains unknown. Recently, microRNAs (miRNAs) are revealed to be involved in oxidative stress response and carcinogenesis. This study aims to identify miRNAs in hepatocellular carcinoma (HCC) cells which might involve in oxidative stress response. An integrated analysis of miRNA expression signature was performed by employing robust rank aggregation (RRA) method, and four miRNAs (miR-34a-5p, miR-1915-3p, miR-638, and miR-150-3p) were identified as the oxidative stress-responsive miRNAs. Pathway enrichment analysis suggested that these four miRNAs played an important role in antiapoptosis process. Our data also revealed miR-34a-5p and miR-1915-3p, but not miR-150-3p and miR-638, were regulated by p53 in HCC cell lines under oxidative stress. In addition, clinical investigation revealed that these four miRNAs might be involved in oxidative stress response by targeting oxidative stress-related genes in HCC tissues. Kaplan-Meier analysis showed that these four miRNAs were associated with patients' overall survival. In conclusion, we identified four oxidative stress-responsive miRNAs, which were regulated by p53-dependent (miR-34a-5p and miR-1915-3p) and p53-independent pathway (miR-150-3p and miR-638). These four miRNAs may offer new strategy for HCC diagnosis and prognosis.

Soluble triggering receptor expressed on myeloid cell-1 (sTREM-1): a potential biomarker for the diagnosis of infectious diseases.

Sensitive and useful biomarkers for the diagnosis and prognosis of infectious diseases have been widely developed. An example of these biomarkers is triggering receptor expressed on myeloid cell-1 (TREM-1), which is a cell surface receptor expressed on monocytes/macrophages and neutrophils. TREM-1 amplifies inflammation by activating the TREM-1/DAP12 pathway. This pathway is triggered by the interaction of TREM-1 with ligands or stimulation by bacterial lipopolysaccharide. Consequently, pro-inflammatory cytokines and chemokines are secreted. Soluble TREM-1 (sTREM-1) is a special form of TREM-1 that can be directly tested in human body fluids and well-known biomarker for infectious diseases. sTREM-1 level can be potentially used for the early diagnosis and prognosis prediction of some infectious diseases, including infectious pleural effusion, lung infections, sepsis, bacterial meningitis, viral infections (e.g., Crimean Congo hemorrhagic fever and dengue fever), fungal infections (e.g., Aspergillus infection), and burn-related infections. sTREM-1 is a more sensitive and specific biomarker than traditional indices, such as C-reactive protein and procalcitonin levels, for these infectious diseases. Therefore, sTREM-1 is a feasible biomarker for the targeted therapy and rapid and early diagnosis of infectious diseases.

Hydrogen-rich water protects against inflammatory bowel disease in mice by inhibiting endoplasmic reticulum stress and promoting heme oxygenase-1 expression.

AIM: To investigate the therapeutic effect of hydrogen-rich water (HRW) on inflammatory bowel disease (IBD) and to explore the potential mechanisms involved. METHODS: Male mice were randomly divided into the following four groups: control group, in which the mice received equivalent volumes of normal saline (NS) intraperitoneally (ip); dextran sulfate sodium (DSS) group, in which the mice received NS ip (5 mL/kg body weight, twice per day at 8 am and 5 pm) for 7 consecutive days after IBD modeling; DSS + HRW group, in which the mice received HRW (in the same volume as the NS treatment) for 7 consecutive days after IBD modeling; and DSS + HRW + ZnPP group, in which the mice received HRW (in the same volume as the NS treatment) and ZnPP [a heme oxygenase-1 (HO-1) inhibitor, 25 mg/kg] for 7 consecutive days after IBD modeling. IBD was induced by feeding DSS to the mice, and blood and colon tissues were collected on the 7th d after IBD modeling to determine clinical symptoms, colonic inflammation and the potential mechanisms involved. RESULTS: The DSS + HRW group exhibited significantly attenuated weight loss and a lower extent of disease activity index compared with the DSS group on the 7th d (P < 0.05). HRW exerted protective effects against colon shortening and colonic wall thickening in contrast to the DSS group (P < 0.05). The histological study demonstrated milder inflammation in the DSS + HRW group, which was similar to normal inflammatory levels, and the macroscopic and microcosmic damage scores were lower in this group than in the DSS group (P < 0.05). The oxidative stress parameters, including MDA and MPO in the colon, were significantly decreased in the DSS + HRW group compared with the DSS group (P < 0.05). Simultaneously, the protective indicators, superoxide dismutase and glutathione, were markedly increased with the use of HRW. Inflammatory factors were assessed, and the results showed that the DSS + HRW group exhibited significantly reduced levels of TNF-α, IL-6 and IL-1ß compared with the DSS group (P < 0.05). In addition, the pivotal proteins involved in endoplasmic reticulum (ER) stress, including p-eIF2α, ATF4, XBP1s and CHOP, were dramatically reduced after HRW treatment in contrast to the control group (P < 0.05). Furthermore, HRW treatment markedly up-regulated HO-1 expression, and the use of ZnPP obviously reversed the protective role of HRW. In the DSS + HRW + ZnPP group, colon shortening and colonic wall thickening were significantly aggravated, and the macroscopic damage scores were similar to those of the DSS + HRW group (P < 0.05). The histological study also showed more serious colonic damage that was similar to the DSS group. CONCLUSION: HRW has a significant therapeutic potential in IBD by inhibiting inflammatory factors, oxidative stress and ER stress and by up-regulating HO-1 expression.

Astaxanthin pretreatment attenuates acetaminophen-induced liver injury in mice.

BACKGROUND: Acetaminophen (APAP) is a conventional drug widely used in the clinic because of its antipyretic-analgesic effects. However, accidental or intentional APAP overdoses induce liver injury and even acute liver failure (ALF). Astaxanthin (ASX) is the strongest antioxidant in nature that shows preventive and therapeutic properties, such as ocular protection, anti-tumor, anti-diabetes, anti-inflammatory, and immunomodulatory effects. The aim of present study was to determine whether ASX pretreatment provides protection against APAP-induced liver failure. METHODS: Male C57BL/6 mice were randomly divided into 7 groups, including control, oil, ASX (30mg/kg or 60mg/kg), APAP and APAP+ASX (30mg/kg or 60mg/kg) groups. Saline, olive oil and ASX were administered for 14days. The APAP and APAP+ASX groups were given a peritoneal injection of 700mg/kg or 300mg/kg APAP to determine the 5-day survival rate and for further observation, respectively. Blood and liver samples were collected to detect alanine transaminase (ALT), aspartate transaminase (AST), inflammation, oxidative stress and antioxidant systems, and to observe histopathologic changes and key proteins in the mitogen-activated protein kinase (MAPK) family. RESULTS: ASX pretreatment before APAP increased the 5-day survival rate in a dose-dependent manner and reduced the ALT, AST, hepatic necrosis, reactive oxygen species (ROS) generation, lipid peroxidation (LPO), oxidative stress and pro-inflammatory factors. ASX protected against APAP toxicity by inhibiting the depletion of glutathione (GSH) and superoxide dismutase (SOD). Administration of ASX did not change the expression of c-Jun N-terminal kinase (JNK), extracellular signal-regulated kinase (ERK) and P38. However, phosphorylation of JNK, ERK and P38 was reduced, consistent with the level of tumor necrosis factor alpha (TNF-α) and TNF receptor-associated factor 2 (TRAF2). CONCLUSION: ASX provided protection for the liver against APAP hepatotoxicity by alleviating hepatocyte necrosis, blocking ROS generation, inhibiting oxidative stress, and reducing apoptosis by inhibiting the TNF-α-mediated JNK signal pathway and by phosphorylation of ERK and P38, which made sense in preventing and treating liver damage.