Human umbilical cord mesenchymal stem cells promote steroid-induced osteonecrosis of the femoral head repair by improving microvascular endothelial cell function.

Recently, there has been growing interest in using cell therapy through core decompression (CD) to treat osteonecrosis of the femoral head (ONFH). Our study aimed to investigate the effectiveness and mechanism of human umbilical cord mesenchymal stem cells (hUCMSCs) in treating steroid-induced ONFH. We constructed a steroid-induced ONFH rabbit model as well as dexamethasone (Dex)-treated bone microvascular endothelial cells (BMECs) model of human femoral head. We injected hUCMSCs into the rabbit femoral head via CD. The effects of hUCMSCs on steroid-induced ONFH rabbit model and Dex-treated BMECs were evaluated via micro-CT, microangiography, histology, immunohistochemistry, wound healing, tube formation, and western blotting assay. Furthermore, we conducted single-cell RNA sequencing (scRNA-seq) to examine the characteristics of endothelial cells, the activation of signaling pathways, and inter-cellular communication in ONFH. Our data reveal that hUCMSCs improved the femoral head microstructure and bone repair and promoted angiogenesis in the steroid-induced ONFH rabbit model. Importantly, hUCMSCs improved the migration ability and angioplasty of Dex-treated BMECs by secreting COL6A2 to activate FAK/PI3K/AKT signaling pathway via integrin α1ß1.

Nanocomposites based on nanoceria regulate the immune microenvironment for the treatment of polycystic ovary syndrome.

The immune system is closely associated with the pathogenesis of polycystic ovary syndrome (PCOS). Macrophages are one of the important immune cell types in the ovarian proinflammatory microenvironment, and ameliorate the inflammatory status mainly through M2 phenotype polarization during PCOS. Current therapeutic approaches lack efficacy and immunomodulatory capacity, and a new therapeutic method is needed to prevent inflammation and alleviate PCOS. Here, octahedral nanoceria nanoparticles with powerful antioxidative ability were bonded to the anti-inflammatory drug resveratrol (CeO2@RSV), which demonstrates a crucial strategy that involves anti-inflammatory and antioxidative efficacy, thereby facilitating the proliferation of granulosa cells during PCOS. Notably, our nanoparticles were demonstrated to possess potent therapeutic efficacy via anti-inflammatory activities and effectively alleviated endocrine dysfunction, inflammation and ovarian injury in a dehydroepiandrosterone (DHEA)-induced PCOS mouse model. Collectively, this study revealed the tremendous potential of the newly developed nanoparticles in ameliorating the proinflammatory microenvironment and promoting the function of granulosa cells, representing the first attempt to treat PCOS by using CeO2@RSV nanoparticles and providing new insights in combating clinical PCOS.

Identification and validation of long noncoding RNA AC083900.1 and RP11-283C24.1 for prediction of progression of osteosarcoma.

BACKGROUND: The role of cuproptosis, an emerging cell death pathway that makes a remarkable contribution to tumor progression, remains elusive in osteosarcoma (OS), in addition to its regulator, including long-no-coding RNAs (lncRNAs) that are also a critical factor for fueling OS. METHODS: Transcriptome and clinical data from 70 normal human bone tissue samples and 84 frozen clinical osteosarcoma samples were included in this study. Cuproptosis-associated lncRNAs (CRlncs) were identified through differential expression and co-expression analyses. Univariate Cox regression was performed to screen for prognostic lncRNAs, then we used least absolute shrinkage and selection operator regression to distinguish prognosis-related CRlncs (AC083900.1 and RP11-283C24.1) for modeling the CRlncs prognostic signature (CLPS) by multivariate Cox regression using the stepwise method. CLPS performance was tested by independent prognostic analyses, survival curve and receiver operating characteristic (ROC) curve. In addition, the molecular and immune mechanisms that underlie the unfavorable prognosis of CLPS-identified high-risk group were elucidated. RESULT: AC083900.1 and RP11-283C24.1 have been identified as the most important CRlncs for OS progression (hazard ratio: 3.498 and 2.724, respectively), and the derived CLPS demonstrated outstanding performance for the prediction of OS prognosis (AUC of 0.799 and 0.778 in the training and test sets, both adj-p < 0.05 in survival curve). As was anticipated, CLPS also outperformed a recent clinical prognostic approach that only achieved an AUC of 0.682 [metastasis]. It is notable that AC083900.1 progressed OS metastasis, evidenced by its high expression in metastatic OS, its high correlation to metastasis-related genes, and its high AUC of 0.683 for the prediction of metastasis. Mechanistically, AC083900.1 and RP11-283C24.1 dysregulated many critical biological processes regarding humoral immune response, immunoglobulin complex, etc.; while reducing the infiltration of many cytotoxic immune cells (B-cells, TIL, neutrophils, etc.). It is encouraging that BMS-509744 and KIN001-135 demonstrated high therapeutic implications for CLPS-identified high-risk OS, and the low-risk counterpart was sensitive to SB-216763. Quantitative RT-PCR analysis showed that both AC083900.1 and RP11-283C24.1 were significantly upregulated in different osteosarcoma cell lines. CONCLUSION: This study elucidated the roles and mechanisms of AC083900.1 and RP11-283C24.1 in the development of OS, fostering a reliable prognostic approach and treatment for OS patients.

Probing the Potential of Defense Response-Associated Genes for Predicting the Progression, Prognosis, and Immune Microenvironment of Osteosarcoma.

BACKGROUND: The defense response is a type of self-protective response of the body that protects it from damage by pathogenic factors. Although these reactions make important contributions to the occurrence and development of tumors, the role they play in osteosarcoma (OS), particularly in the immune microenvironment, remains unpredictable. METHODS: This study included the clinical information and transcriptomic data of 84 osteosarcoma samples and the microarray data of 12 mesenchymal stem cell samples and 84 osteosarcoma samples. We obtained 129 differentially expressed genes related to the defense response (DRGs) by taking the intersection of differentially expressed genes with genes involved in the defense response pathway, and prognostic genes were screened using univariate Cox regression. Least absolute shrinkage and selection operator (LASSO) penalized Cox regression and multivariate Cox regression were then used to establish a DRG prognostic signature (DGPS) via the stepwise method. DGPS performance was examined using independent prognostic analysis, survival curves, and receiver operating characteristic (ROC) curves. In addition, the molecular and immune mechanisms of adverse prognosis in high-risk populations identified by DGPS were elucidated. The results were well verified by experiments. RESULT: BNIP3, PTGIS, and ZYX were identified as the most important DRGs for OS progression (hazard ratios of 2.044, 1.485, and 0.189, respectively). DGPS demonstrated outstanding performance in the prediction of OS prognosis (area under the curve (AUC) values of 0.842 and 0.787 in the training and test sets, respectively, adj-p < 0.05 in the survival curve). DGPS also performed better than a recent clinical prognostic approach with an AUC value of only 0.674 [metastasis], which was certified in the subsequent experimental results. These three genes regulate several key biological processes, including immune receptor activity and T cell activation, and they also reduce the infiltration of some immune cells, such as B cells, CD8+ T cells, and macrophages. Encouragingly, we found that DGPS was associated with sensitivity to chemotherapeutic drugs including JNK Inhibitor VIII, TGX221, MP470, and SB52334. Finally, we verified the effect of BNIP3 on apoptosis, proliferation, and migration of osteosarcoma cells through experiments. CONCLUSIONS: This study elucidated the role and mechanism of BNIP3, PTGIS, and ZYX in OS progression and was well verified by the experimental results, enabling reliable prognostic means and treatment strategies to be proposed for OS patients.

Gastrodin alleviates rat chondrocyte senescence and mitochondrial dysfunction through Sirt3.

Several researchers have focused on understanding the pathogenesis and treatment strategies for osteoarthritis (OA). Gastrodin (GAS) is a potential anti-inflammatory agent. In this study, we constructed an in vitro OA chondrocyte model by treating chondrocytes with IL-1ß. Next, we determined the expression of aging-related markers and mitochondrial functions in chondrocytes treated with GAS. Further, we constructed a "drug-component-target-pathway-disease" interactive network and determined the effect of GAS on the functions and pathways related to OA. Finally, we constructed the OA rat model by removing the medial meniscus of the right knee and transection of the anterior cruciate ligament. The results revealed that GAS reduced senescence and improved mitochondrial functions in OA chondrocytes. We used network pharmacology and bioinformatics to screen for key molecules Sirt3 and the PI3K-AKT pathway involved in regulating the effect of GAS on OA. Further studies showed an increase in SIRT3 expression and reduced chondrocyte aging, mitochondrial damage, and the phosphorylation of the PI3K-AKT pathway. The results showed that GAS ameliorates pathological changes related to aging, increases SIRT3 expression, and protects the ECM in the OA rat model. These results were consistent with our bioinformatics results and previous studies. In summary, GAS slows down the aging of chondrocytes and mitochondrial damage in OA by regulating the phosphorylation of the PI3K-AKT pathway via SIRT3.

Ensemble deep learning enhanced with self-attention for predicting immunotherapeutic responses to cancers.

Introduction: Despite the many benefits immunotherapy has brought to patients with different cancers, its clinical applications and improvements are still hindered by drug resistance. Fostering a reliable approach to identifying sufferers who are sensitive to certain immunotherapeutic agents is of great clinical relevance. Methods: We propose an ELISE (Ensemble Learning for Immunotherapeutic Response Evaluation) pipeline to generate a robust and highly accurate approach to predicting individual responses to immunotherapies. ELISE employed iterative univariable logistic regression to select genetic features of patients, using Monte Carlo Tree Search (MCTS) to tune hyperparameters. In each trial, ELISE selected multiple models for integration based on add or concatenate stacking strategies, including deep neural network, automatic feature interaction learning via self-attentive neural networks, deep factorization machine, compressed interaction network, and linear neural network, then adopted the best trial to generate a final approach. SHapley Additive exPlanations (SHAP) algorithm was applied to interpret ELISE, which was then validated in an independent test set. Result: Regarding prediction of responses to atezolizumab within esophageal adenocarcinoma (EAC) patients, ELISE demonstrated a superior accuracy (Area Under Curve [AUC] = 100.00%). AC005786.3 (Mean [|SHAP value|] = 0.0097) was distinguished as the most valuable contributor to ELISE output, followed by SNORD3D (0.0092), RN7SKP72 (0.0081), EREG (0.0069), IGHV4-80 (0.0063), and MIR4526 (0.0063). Mechanistically, immunoglobulin complex, immunoglobulin production, adaptive immune response, antigen binding and others, were downregulated in ELISE-neg EAC subtypes and resulted in unfavorable responses. More encouragingly, ELISE could be extended to accurately estimate the responsiveness of various immunotherapeutic agents against other cancers, including PD1/PD-L1 suppressor against metastatic urothelial cancer (AUC = 88.86%), and MAGE-A3 immunotherapy against metastatic melanoma (AUC = 100.00%). Discussion: This study presented deep insights into integrating ensemble deep learning with self-attention as a mechanism for predicting immunotherapy responses to human cancers, highlighting ELISE as a potential tool to generate reliable approaches to individualized treatment.

Dissecting the effect of sphingolipid metabolism gene in progression and microenvironment of osteosarcoma to develop a prognostic signature.

Sphingolipid metabolism (SM) fuels tumorigenesis and the malignant progression of osteosarcoma (OS), which leads to an unfavorable prognosis. Elucidating the molecular mechanisms underlying SM in osteosarcoma and developing a SM-based prognostic signature could be beneficial in the clinical setting. This study included 88 frozen OS samples to recognize the vital SM-relevant genes in the development of OS utilizing univariate Cox regression. The Least Absolute Shrinkage and Selection Operator (LASSO) regression analysis was conducted on the SM- relevant genes to minimize the risk of overfitting. The prognostic signature was generate utilizing the multivariable Cox regression analysis and was verified in the validation cohort. Moreover, cellular and molecular mechanisms associated with SM have an unfavorable prognosis for OS patients and have been widely studied. Resultantly, an SM-based prognostic risk model was established according to critical prognostic genes (CBS, GLB1, and HACD1), which had an excellent ability to predict the prognosis of OS patients (AUC for the train cohort was 0.887 and AUC for validation cohort was 0.737). The high-risk OS patients identified based on this prognostic signature had significantly poor immune microenvironment, indicated by significantly low immune score (mean=216.290 ± 662.463), reduced infiltrations of 25 immune cells, including NK cells (LogFC= -0.3597), CD8+T cells ((LogFC=-0.2346), Cytolytic activity ((LogFC=-0.1998), etc. The immunosuppressive microenvironment could be due to dysregulated SM of glycolipids. Further, a nomogram was constructed by integrating the SM-based prognostic signature and clinical paraments to facilitate clinical application. The nomogram could accurately predict the prognosis of OS invalids. Collectively, this study clarified the function of SM in the development of OS and helped develop a tool for risk stratification based on SM-related genes with application in clinical settings. The results of our study will aid in identifying high-risk patients and provide individualized treatments.

A novel inflammation-associated prognostic signature for clear cell renal cell carcinoma.

Clear cell renal cell carcinoma (ccRCC) are typically situated in a complex inflammatory and immune microenvironment, which has been reported to contribute to the unfavorable prognosis of patients with ccRCC. There would be beneficial clinical implications for elucidating the roles of its molecular characteristics in the inflammatory microenvironment. This is because it would facilitate the development of reliable biomarkers for pre-stratification prior to the designation of individualized treatment strategies. In the present study, RNA-sequencing data from 607 patients were retrospectively analyzed to elucidate the profile of inflammatory molecules. Based on this, an inflammatory prognostic signature (IPS) was developed and further validated using clinical ccRCC samples. Subsequently, the associated mechanisms in terms of the immune microenvironment and molecular pathways were then investigated. This proposed IPS was found to exhibit superior accuracy compared with the criterion of a good prognostic model for the prediction of patient prognosis from ccRCC [area under the receiver operating characteristic curve (AUC)=0.811] in addition to being an independent factor for prognostic risk stratification [hazard ratio: 11.73 (95% CI, 26.98-5.10); log-rank test, P<0.001]. Pathologically, ccRCC cells identified as high-risk according to their IPS presented with a more malignant tumor structure, including voluminous eosinophilic cytoplasm, acinar/lamellar/tubular growth patterns and atypic nuclei. High-risk ccRCC also exhibited higher infiltration levels by four types of immune cells, including T regulatory cells, but lower infiltration levels by mast cells. Pathways associated with immune-inflammation interaction, including the IL-17 pathway, were found to be upregulated in IPS-identified high-risk ccRCC. Furthermore, by combining the IPS with clinical factors, an integrated prognostic index was developed and validated for increasing the accuracy of patient risk-stratification for ccRCC (AUC=0.911). In conclusion, the complex regulatory mechanisms and molecular characteristics involved in ccRCC-inflammation interaction, coupled with their prognostic potential, were systematically elucidated in the present study. This may have important implications in furthering the understanding into the molecular mechanisms underlying this ccRCC-inflammation interaction, which can in turn be exploited for identifying high-risk patients with ccRCC prior to designing their clinical treatment strategy.

Salidroside alleviates oxidative stress and apoptosis via AMPK/Nrf2 pathway in DHT-induced human granulosa cell line KGN.

In the past few years, emerging evidence established persistent oxidative stress to be a key player in the pathogenesis of polycystic ovary syndrome (PCOS). Particularly, it damages the function of granulosa cells, and thus hinders the development of follicles. The present study aimed to explore and establish the protective effects of salidroside on dihydrotestosterone (DHT)-induced Granulosa-like tumor cell line (KGN), mediated via antioxidant mechanisms. The study assessed the positive effects of salidroside on DHT-induced apoptosis, reactive oxygen species (ROS) accumulation, damage of antioxidant capacity, and mitochondrial membrane potential depolarization. Interestingly, salidroside partly reversed DHT mediated effects, via stimulation of nuclear factor erythroid 2-related factor 2 (Nrf2) signaling pathway and the downstream antioxidant proteins heme oxygenase-1(HO-1) and quinine oxidoreductase 1(NQO1). Additionally, the knockdown of Nrf2 partly moderated the antioxidant and anti-apoptosis effects of salidroside in DHT-treated KGN cells. Mechanistically, AMP-activated protein kinase (AMPK) was identified to be the upstream signaling involved in salidroside-induced Nrf2 activation, as silencing of AMPK partly prevented the upregulation of Nrf2 and the downstream proteins HO-1 and NQO1. Altogether, the present study is the first to effectively demonstrate the inhibitory effect of salidroside on DHT-stimulated oxidative stress and apoptosis in KGN cells, which was dependent on Nrf2 activation that involved AMPK.

Machine-intelligence for developing a potent signature to predict ovarian response to tailor assisted reproduction technology.

The prediction of poor ovarian response (POR) for stratified interference is a critical clinical issue that has received an increasing amount of recent concern. Anthropogenic diagnostic modes remain too simple for the handling of actual clinical complexity. Therefore, this study conducted extensive selection using models that were derived from a variety of machine learning algorithms, including random forest (RF), decision trees, eXtreme Gradient Boosting (XGBoost), support vector machine (SVM), and artificial neural networks (ANN) for the development of two models called the COS pre-launch model (CPLM) and the hCG pre-trigger model (HPTM) to assess POR based on different requirements. The results demonstrated that CPLM constructed using ANN achieved the highest AUC result of all the algorithms in COS pre-launch (AUC=0.859, C-index=0.87, good calibration), and HPTL constructed using random forest was found to be the most effective in hCG pre-trigger (AUC=0.903, C-index=0.90, good calibration). It is notable that CPLM and HPTM exhibited better performance than common clinical characteristics (0.895 [CPLM], and 0.903 [HPTM] in comparison to 0.824 [anti-Müllerian hormone (AMH)], and 0.799 [antral follicle count (AFC)]). Furthermore, variable importance figure elucidated the values of AMH, AFC, and E2 level and follicle number on hCG day, which provides important theoretical guidance and experimental data for further application. Generally, the CPLM and HPTM can offer effective POR prediction for patients who are receiving assisted reproduction technology (ART), and has great potential for guiding the clinical treatment of infertility.

Association between CT-Quantified Body Composition and Recurrence, Survival in Nonmetastasis Colorectal Cancer Patients Underwent Regular Chemotherapy after Surgery.

BACKGROUND: Body mass index, measured at colorectal cancer (CRC) diagnosis has been associated with recurrence and survival outcomes. Computed tomography- (CT-) defined body compositions accurately reflect body mass, but there was no consistent perspective on the influence of visceral adipose tissue (VAT) and skeletal muscle mass (SM) on the prognosis of nonmetastasis CRC, especially in the patients underwent surgery and regularly standard chemotherapy. METHODS: We investigated the associations of CT-quantified body composition (VAT and SM) with CRC patients successively underwent surgery and regular 8-12 of periods standard chemotherapy. All of the CT images were obtained at the level of the L3/4 spinal level. The prognostic value of the body compositions was analyzed using the Cox regression model, and precise clinical nomograms were established. RESULTS: In XELOX-treated patients, progression-free survival (PFS) (P = 0.025) and overall survival (OS) (P = 0.032) were lower in the high-SM than in the low-SM group. The univariate analysis demonstrated that compared with low-SM patients, patients with high-SM showed a strikingly poor prognosis in both OS (P = 0.0512) and PFS in the T4 subgroup (P = 0.0417), while contrary to the T2-3 subgroup. CONCLUSIONS: CT-quantified body compositions have a significant influence on CRC patients successively underwent curative resection and regularly standard chemotherapy with the endpoints of 1-year, 3-year, and 5-year both OS and PFS. Patients with high-SM showed a strikingly poor prognosis in OS and PFS in the T4 subgroup; however, the prognosis role of body composition was opposite in T2-3 patients.

Development and validation of a noninvasive clinical scoring system to predict significant fibrosis in patients with nonalcoholic fatty liver disease.

BACKGROUND: The aims of this study were to identify risk factors for significant fibrosis (SF) by assessing physical and laboratory parameters and develop and validate a clinical score and nomogram for the prediction of SF in patients with nonalcoholic fatty liver disease (NAFLD). METHODS: This retrospective study included 225 patients with histologically confirmed NAFLD who were divided into two cohorts using 10-fold cross validation for model training and validation. The clinical score and nomogram were used to predict the NAFLD outcome. RESULTS: The model for predicting SF (stage ≥ 2) including the free T4/free T3 ratio, low-density lipoprotein cholesterol, homeostatic model assessment for insulin resistance (HOMA-IR), percentage of appendicular skeletal muscle mass and aspartate aminotransferase (AST) level in the training and validation cohorts yielded an area under the receiver operator characteristic curve (AUROC) of 0.79 and 0.78, respectively. The AUROC of the combined clinical score for the prediction of SF was 0.82 (95% CI, 0.75-0.89) at a cutoff value of 3 points, with a sensitivity (SE) of 77.19%, specificity (SP) of 82.88%, positive predictive value (PPV) of 63.77%, and negative predictive value (NPV) of 90.30%. The nomogram had good performance in quantitatively predicting the risk probability of SF. CONCLUSION: Our study showed that a noninvasive clinical scoring system using easily available physical and laboratory variables can identify patients with NAFLD with or without SF with a high degree of accuracy. Application of this system may decrease the need for staging liver biopsy specimens and allow early identification and intervention in these high-risk patients.

Exploration of the molecular characteristics of the tumor-immune interaction and the development of an individualized immune prognostic signature for neuroblastoma.

Neuroblastoma (NBL) exists in a complex tumor-immune microenvironment. Immune cell infiltration and tumor-immune molecules play a critical role in tumor development and significantly impact the prognosis of patients. However, the molecular characteristics describing the NBL-immune interaction and their prognostic potential have yet to be investigated systematically. We first employed multiple machine learning algorithms, such as Gene Sets Enrichment Analysis and cell type identification by estimating relative subsets of RNA transcripts, to identify immunophenotypes and immunological characteristics in NBL patient data from public databases and then investigated the prognostic potential and regulatory networks of identified immune-related genes involved in the NBL-immune interaction. The immunity signature combining nine immunity genes was confirmed as more effective for individual risk stratification and survival outcome prediction in NBL patients than common clinical characteristics (area under the curve [AUC] = 0.819, C-index = 0.718, p < .001). A mechanistic exploration revealed the regulatory network of molecules involved in the NBL-immune interaction. These immune molecules were also discovered to possess a significant correlation with plasma cell infiltration, MYCN status, and the level of chemokines and macrophage-related molecules (p < .001). A nomogram was constructed based on the immune signature and clinical characteristics, which showed high potential for prognosis prediction (AUC = 0.856, C-index = 0.755, p < .001). We systematically elucidated the complex regulatory mechanisms and characteristics of the molecules involved in the NBL-immune interaction and their prognostic potential, which may have important implications for further understanding the molecular mechanism of the NBL-immune interaction and identifying high-risk NBL patients to guide clinical treatment.

Alginate Suppresses Liver Fibrosis Through the Inhibition of Nuclear Factor-κB Signaling.

PURPOSE: Liver fibrosis (or liver scarring) is a causative factor for hepatitis, cirrhosis and hepatocellular carcinoma (HCC). Alginate (Agn) isolated from brown algae is known to slow the proliferation of fibroblasts, through the mechanisms of these effects remain undefined. This study explored the benefits of Agn on hepatic health and its associated mechanism(s) of action in hepatic stellate cells (HSC-T6s). MATERIALS AND METHODS: To assess the effects of Agn, HSC-T6s were treated with PDGF and cell proliferation, colony formation, cell migration, cell invasiveness and apoptosis were assessed. Rat models of liver fibrosis were produced through 12-week injections of intraperitoneal (IP) carbon tetrachloride (CCl4). Rats were Agn-treated from weeks 8 to 12, and liver damage was assessed through Masson's and H & E staining. Gene expression profiles were assayed via RT-PCR, Western blot and commercial ELISA kits. RESULTS: Agn reduced the proliferation of HSC-T6s and increased apoptotic rates through the downregulation of the Bcl-2:Bax ratio. Agn also inhibited the invasion and migration of HSC-T6s, prevented ECM deposition, and reduced the occurrence of liver fibrosis in rat models. Agn also prevented IκBα and p65 phosphorylation. CONCLUSION: Agn prevents liver fibrosis through its attenuation of HSC activation and division through the suppression of NF-κB in in vitro and animal models. This highlights how the clinical use of Agn can prevent hepatic fibrosis.

Prognosis of patients with newly diagnosed glioblastoma treated with molecularly targeted drugs combined with radiotherapy vs temozolomide monotherapy: A meta-analysis.

BACKGROUND: Glioblastoma (GB) is one of the most common malignancies with limited standard therapies such as surgery, radiotherapy (RT) plus temozolomide (TMZ). Molecularly targeted drugs have been investigated among various clinical trials and are expected to develop in the field of tumor therapy, while the efficacy remains uncertain due to limited previous results. Thus, we focus on the evaluation of molecularly targeted drugs to clarify its overall effectiveness in terms of treating newly diagnosed GB. METHODS: Electronic databases were searched for eligible literatures updated to April 2018. Randomized-controlled trials were included to assess the efficacy and safety of molecularly targeted drugs in patients with newly diagnosed GB. The main outcomes were further calculated including the following parameters: PFS (progression-free survival), OS (overall survival) as well as AEs (adverse events). All data were pooled along with their 95% confidence interval using RevMan software. Sensitivity analyses and heterogeneity were evaluated quantitatively. RESULTS: The combination of molecularly targeted drugs with TMZ + RT had no significant effects on OS (OR = 0.96, 95%CI = 0.89-1.04, P = .36). Meanwhile, the combination regimen significantly improved the PFS of patients with newly diagnosed GB (OR = 0.86 ,95% CI 0.75-0.98, P = .02). The rate of AEs (OR = 1.68,95%CI = 1.44-1.97, P < .00001) was higher in patients receiving molecularly targeted drugs, which was comparable to the contemporary group. CONCLUSION: Longer PFS and a higher rate of AEs were observed with the addition of molecularly targeted drugs to standard chemoradiation in patients harboring newly diagnosed GB. Nevertheless, compared with the control arm, the regimen did not significantly prolong OS.

Indole-3-Carbinol Induces Apoptosis of Hepatic Stellate Cells through K63 De-Ubiquitination of RIP1 in Rats.

BACKGROUND/AIMS: The apoptosis of activated hepatic stellate cells (HSCs) is the central event in the reversal of liver fibrosis. K63 de-ubiquitinated receptor-interacting protein (RIP)1 promotes apoptosis in tumor necrosis factor (TNF)-α signaling pathway. In the previous study, we have proved that indole-3-carbinol (I3C) could reverse different models of liver fibrosis in rats, but the mechanism is still unclear. Thus, the present research aimed to demonstrate the induction of I3C on apoptosis of HSCs and the underlying molecular mechanism. METHODS: HSC-T6, an immortalized rat liver stellate cell line, was treated for 24 hours with 25, 50 and 100 µM of I3C. The apoptosis of HSC-T6 was analyzed by flow cytometric analysis, acridine orange staining and RT-PCR, respectively. K63 de-ubiquitination of RIP1 and the expression of ubiquitin ligases and deubiquitinases were analyzed by Co-IP assay and western blot. Knockdown of deubiquitinases was undertaken by small interfering RNA (siRNA). RESULTS: The results of flow cytometric analysis indicated that the apoptotic rate of HSC-T6 was induced by I3C in a dose-dependent manner. Observation by acridine orange staining exhibited nuclear condensation and apoptotic bodies in I3C treated cells. Consistently, the expression ratio of Bax/bcl-2 was markedly increased by I3C. These results indicated that I3C could significantly induce apoptosis of HSC-T6 cells. Furthermore, Co-IP assay revealed K63 de-ubiquitination of RIP1 by I3C, associated with the induction of caspase 8. Although I3C had no effect on the expression of ubiquitin ligases cellular inhibitor of apoptosis 1/2 (cIAP1/2), the protein level of deubiquitinase cylindromatosis (CYLD) was significantly induced by I3C. Moreover, CYLD silencing reversed the pro-apoptosis induction effect of I3C and reduced the expression ratio of Bax/bcl-2 in HSC-T6 cells. CONCLUSION: These results demonstrated that I3C could induce apoptosis of HSC through RIP1 K63 de-ubiquitination by upregulating deubiquitinase CYLD.

Flavonoids and isoflavonoids from Sophorae Flos improve glucose uptake in vitro.

Glucose uptake assay-guided fractionations on the methanol extract of Sophorae Flos led to the isolation of the flavonoids rutin (1), narcissin (2), quercetin (3), tamarixetin (4), and kaempferol (5) and the isoflavonoids cajanin (6), genistein (7), orobol (8), and pratensein (9). Among them, 1, 4, 5, 6, 8, and 9 significantly improved basal glucose uptake in HepG2 cells. Their improving effects were concentration dependent. Compounds 4, 5, 6, and 9 exhibited effects stronger than that of rosiglitazone, which has been used as an antidiabetic drug. However, 2, 3, and 7 did not show any improving effects. Stimulating glucose uptake into peripheral cells may be responsible for reducing the level of blood glucose in the circulation. Therefore, these findings demonstrate a potential to develop these flavonoids and isoflavonoids as hypoglycemic drugs.

Cytotoxic lignans from the stem bark of Magnolia officinalis.

Three new lignans, 4'-methoxymagndialdehyde ( 1), 4'-methoxymagnaldehyde B ( 2), and 4'-methoxymagnaldehyde E ( 3), were isolated from hexane- and EtOAc-soluble fractions of the stem bark of Magnolia officinalis, together with eight known compounds ( 4- 11). The structures of compounds 1- 3 were determined on the basis of spectroscopic and physicochemical data analysis. Compounds 1- 11 were tested in vitro for their cytotoxic activity against the K562, HeLa, and A549 cancer cell lines. Among the compounds tested, compound 1 showed the most potent cytotoxic activity against these cancer cell lines, with IC50 values of 3.9, 1.5, and 3.7 microg/mL, respectively.

Cytotoxicity of triterpenes isolated from Aceriphyllum rossii.

Bioassay-guided fractionation of a MeOH extract of the whole plant of Aceriphyllum rossii (Saxifragaceae) led to the isolation of two new triterpenes, 3alpha,23-isopropylidenedioxyolean-12-en-27-oic acid (1) and 23-hydroxy-3-oxoolean-12-en-27-oic acid (2), together with six known triterpenes, 3-oxoolean-12-en-27-oic acid (3), 3alpha-hydroxyolean-12-en-27-oic acid (4), beta-peltoboykinolic acid (5), aceriphyllic acid A (6), oleanolic acid (7), and gypsogenic acid (8). The structures of these compounds were elucidated on the basis of physicochemical and spectroscopic analyses. These compounds were evaluated for in vitro cytotoxicity against the K562 and HL-60 cell lines. Olean-12-en-27-oic acid derivatives (1-6) exhibited considerable cytotoxicity against K562 and HL-60 cell lines with IC(50) values ranging from 12.2 to 28.7 microM and from 12.1 to 25.8 microM, respectively.

Cytotoxic constituents from angelicae sinensis radix.

Cytotoxic bioassay-guided fractionation of methanol extract of Angelicae Sinensis Radix led to the isolation of a new dimeric Z-ligustilide, named neodiligustilide (1), together with three known compounds, Z-ligustilide (2), 11(S),16(R)-dihydroxy-octadeca-9Z, 17-dien-12,14-diyn-1-yl acetate (3), and 3(R),8(S)-falcarindiol (4). Among them, 2 showed the strongest cytotoxicity against L1210 and K562 cell lines with IC50 values of 2.27 +/- 0.10 and 4.78 +/- 0.18 microM, respectively, while 1 showed moderate cytotoxicity with IC50 values of 5.45 +/- 0.19 and 9.87 +/- 0.14 microM. Two polyacetylenes, 3 and 4, showed cytotoxicity only against L1210 cell line with IC50 values of 2.60 +/- 0.90 and 2.87 +/- 0.49 microM, respectively.