Upregulation of Hepatic Glutathione S-Transferase Alpha 1 Ameliorates Metabolic Dysfunction-Associated Steatosis by Degrading Fatty Acid Binding Protein 1.

Metabolic dysfunction-associated steatotic liver disease (MASLD) is the most common metabolic disease of the liver, characterized by hepatic steatosis in more than 5% of hepatocytes. However, despite the recent approval of the first drug, resmetirom, for the management of metabolic dysfunction-associated steatohepatitis, decades of target exploration and hundreds of clinical trials have failed, highlighting the urgent need to find new druggable targets for the discovery of innovative drug candidates against MASLD. Here, we found that glutathione S-transferase alpha 1 (GSTA1) expression was negatively associated with lipid droplet accumulation in vitro and in vivo. Overexpression of GSTA1 significantly attenuated oleic acid-induced steatosis in hepatocytes or high-fat diet-induced steatosis in the mouse liver. The hepatoprotective and anti-inflammatory drug bicyclol also attenuated steatosis by upregulating GSTA1 expression. A detailed mechanism showed that GSTA1 directly interacts with fatty acid binding protein 1 (FABP1) and facilitates the degradation of FABP1, thereby inhibiting intracellular triglyceride synthesis by impeding the uptake and transportation of free fatty acids. Conclusion: GSTA1 may be a good target for the discovery of innovative drug candidates as GSTA1 stabilizers or enhancers against MASLD.

A metric for quantitative evaluation of glioma margin changes in magnetic resonance imaging.

BACKGROUND: Gliomas differ from meningiomas in their margins, most of which are not separated from the surrounding tissue by a distinct interface. PURPOSE: To characterize the margins of gliomas quantitatively based on the margin sharpness coefficient (MSC) is significant for clinical judgment and invasive analysis of gliomas. MATERIAL AND METHODS: The data for this study used magnetic resonance image (MRI) data from 67 local patients and 15 open patients to quantify the intensity of changes in the glioma margins of the brain using MSC. The accuracy of MSC was assessed by consistency analysis and Bland-Altman test analysis, as well as invasive correlations using receiver operating characteristic (ROC) and Spearman correlation coefficients for subjects. RESULTS: In grading the tumors, the mean MSC values were significantly lower for high-grade gliomas (HGG) than for low-grade gliomas (LGG). The concordance correlation between the measured gradient and the actual gradient was high (HGG: 0.981; LGG: 0.993), and the Bland-Altman mean difference at the 95% confidence interval (HGG: -0.576; LGG: 0.254) and the limits of concordance (HGG: 5.580; LGG: 5.436) indicated no statistical difference. The correlation between MSC and invasion based on the margins of gliomas showed an AUC of 0.903 and 0.911 for HGG and LGG, respectively. The mean Spearman correlation coefficient of the MSC versus the actual distance of invasion was -0.631 in gliomas. CONCLUSION: The relatively low MSC on the blurred margins and irregular shape of gliomas may help in benign-malignant differentiation and invasion prediction of gliomas and has potential application for clinical judgment.

Circular RNA circFCHO2(hsa_circ_0002490) promotes the proliferation of melanoma by directly binding to DND1.

Circular RNAs (circRNAs) have been documented to play crucial roles in the biology of various cancers. However, their investigation in melanoma is still at an early stage, particularly as a broader mechanism beyond acting as miRNA sponges needs to be explored. We report here that circFCHO2(hsa_circ_0002490), a circRNA encompassing exons 19 and 20 of the FCHO2 gene, exhibited a consistent overexpression in melanoma tissues. Furthermore, elevated circFCHO2 levels demonstrated a positive correlation with the malignant phenotype and poor prognosis among the 158 melanoma patients studied. Besides, we observed that heightened levels of circFCHO2 promoted melanoma cell proliferation, migration, and invasion in vitro, along with contributing to tumor growth in vivo. Furthermore, we found differences in the secondary structure of circFCHO2 compared to most other circular RNA structures. It has fewer miRNA binding sites, while it has more RNA binding protein binding sites. We therefore speculate that circFCHO2 may have a function of interacting with RNA binding proteins. Mechanistically, it was confirmed by fluorescence in situ hybridization (FISH), RNA-pull down, RNA immunoprecipitation (RIP), and western blotting assays that circFCHO2 interacts with dead end protein homolog 1 (DND1) and reverses the inhibition of the PI3K/AKT signaling pathway by binding to DND1. Our findings reveal that circFCHO2 drives melanoma progression by regulating the PI3K/AKT signaling pathway through direct binding to DND1 and may serve as a potential diagnostic biomarker and therapeutic target for the treatment of melanoma.

Melanoma Derived Exosomes Amplify Radiotherapy Induced Abscopal Effect via IRF7/I-IFN Axis in Macrophages.

Radiotherapy (RT) can induce tumor regression outside the irradiation field, known as the abscopal effect. However, the detailed underlying mechanisms remain largely unknown. A tumor-bearing mouse model is successfully constructed by inducing both subcutaneous tumors and lung metastases. Single-cell RNA sequencing, immunofluorescence, and flow cytometry are performed to explore the regulation of tumor microenvironment (TME) by RT. A series of in vitro assays, including luciferase reporter, RNA Pulldown, and fluorescent in situ hybridization (FISH) assays, are performed to evaluate the detailed mechanism of the abscopal effect. In addition, in vivo assays are performed to investigate combination therapy strategies for enhancing the abscopal effect. The results showed that RT significantly inhibited localized tumor and lung metastasis progression and improved the TME. Mechanistically, RT promoted the release of tumor-derived exosomes carrying circPIK3R3, which is taken up by macrophages. circPIK3R3 promoted Type I interferon (I-IFN) secretion and M1 polarization via the miR-872-3p/IRF7 axis. Secreted I-IFN activated the JAK/STAT signaling pathway in CD8+ T cells, and promoted IFN-γ and GZMB secretion. Together, the study shows that tumor-derived exosomes promote I-IFN secretion via the circPIK3R3/miR-872-3p/IRF7 axis in macrophages and enhance the anti-tumor immune response of CD8+ T cells.

Rapid visualization of PD-L1 expression level in glioblastoma immune microenvironment via machine learning cascade-based Raman histopathology.

INTRODUCTION: Combination immunotherapy holds promise for improving survival in responsive glioblastoma (GBM) patients. Programmed death-ligand 1 (PD-L1) expression in immune microenvironment (IME) is the most important predictive biomarker for immunotherapy. Due to the heterogeneous distribution of PD-L1, post-operative histopathology fails to accurately capture its expression in residual tumors, making intra-operative diagnosis crucial for GBM treatment strategies. However, the current methods for evaluating the expression of PD-L1 are still time-consuming. OBJECTIVE: To overcome the PD-L1 heterogeneity and enable rapid, accurate, and label-free imaging of PD-L1 expression level in GBM IME at the tissue level. METHODS: We proposed a novel intra-operative diagnostic method, Machine Learning Cascade (MLC)-based Raman histopathology, which uses a coordinate localization system (CLS), hierarchical clustering analysis (HCA), support vector machine (SVM), and similarity analysis (SA). This method enables visualization of PD-L1 expression in glioma cells, CD8+ T cells, macrophages, and normal cells in addition to the tumor/normal boundary. The study quantified PD-L1 expression levels using the tumor proportion, combined positive, and cellular composition scores (TPS, CPS, and CCS, respectively) based on Raman data. Furthermore, the association between Raman spectral features and biomolecules was examined biochemically. RESULTS: The entire process from signal collection to visualization could be completed within 30 min. In an orthotopic glioma mouse model, the MLC-based Raman histopathology demonstrated a high average accuracy (0.990) for identifying different cells and exhibited strong concordance with multiplex immunofluorescence (84.31 %) and traditional pathologists' scoring (R2 ≥ 0.9). Moreover, the peak intensities at 837 and 874 cm-1 showed a positive linear correlation with PD-L1 expression level. CONCLUSIONS: This study introduced a new and extendable diagnostic method to achieve rapid and accurate visualization of PD-L1 expression in GBM IMB at the tissular level, leading to great potential in GBM intraoperative diagnosis for guiding surgery and post-operative immunotherapy.

Coordinatized lesion location analysis empowering ROI-based radiomics diagnosis on brain gliomas.

OBJECTIVES: To assess the value of coordinatized lesion location analysis (CLLA), in empowering ROI-based imaging diagnosis of gliomas by improving accuracy and generalization performances. METHODS: In this retrospective study, pre-operative contrasted T1-weighted and T2-weighted MR images were obtained from patients with gliomas from three centers: Jinling Hospital, Tiantan Hospital, and the Cancer Genome Atlas Program. Based on CLLA and ROI-based radiomic analyses, a fusion location-radiomics model was constructed to predict tumor grades, isocitrate dehydrogenase (IDH) status, and overall survival (OS). An inter-site cross-validation strategy was used for assessing the performances of the fusion model on accuracy and generalization with the value of area under the curve (AUC) and delta accuracy (ACC) (ACCtesting-ACCtraining). Comparisons of diagnostic performances were performed between the fusion model and the other two models constructed with location and radiomics analysis using DeLong's test and Wilcoxon signed ranks test. RESULTS: A total of 679 patients (mean age, 50 years ± 14 [standard deviation]; 388 men) were enrolled. Based on tumor location probabilistic maps, fusion location-radiomics models (averaged AUC values of grade/IDH/OS: 0.756/0.748/0.768) showed the highest accuracy in contrast to radiomics models (0.731/0.686/0.716) and location models (0.706/0.712/0.740). Notably, fusion models ([median Delta ACC: - 0.125, interquartile range: 0.130]) demonstrated improved generalization than that of radiomics model ([- 0.200, 0.195], p = 0.018). CONCLUSIONS: CLLA could empower ROI-based radiomics diagnosis of gliomas by improving the accuracy and generalization of the models. CLINICAL RELEVANCE STATEMENT: This study proposed a coordinatized lesion location analysis for glioma diagnosis, which could improve the performances of the conventional ROI-based radiomics model in accuracy and generalization. KEY POINTS: • Using coordinatized lesion location analysis, we mapped anatomic distribution patterns of gliomas with specific pathological and clinical features and constructed glioma prediction models. • We integrated coordinatized lesion location analysis into ROI-based analysis of radiomics to propose new fusion location-radiomics models. • Fusion location-radiomics models, with the advantages of being less influenced by variabilities, improved accuracy, and generalization performances of ROI-based radiomics models on predicting the diagnosis of gliomas.

TTFields Prolonged the PFS of Epithelioid Glioblastoma Patient: A Case Report.

Epithelioid glioblastoma (EGBM, classified as glioblastoma, IDH wild type, grade 4 according to the fifth edition of the World Health Organization (WHO) Classification of Tumors of the Central Nervous System (CNS) (WHO CNS5)) is a highly aggressive malignancy, with a median progression-free survival (mPFS) of about 6 months in adults. The application of tumor-treating fields (TTFields, possessing anti-cancer capabilities via anti-mitotic effects) in the maintenance of temozolomide (TMZ) chemotherapy showed a benefit for prolonging the mPFS of newly diagnosed glioblastoma (GBM) for patients for up to 6.9 months in the EF-14 clinical trial (NCT00916409). However, studies focusing on the effect of TTFields in EGBM treatment are very limited due to the rarity of EGBM. Here, we have reported a case of a 28-year-old male (recurrent left-sided limb twitching for 1 month and dizziness for 1 week) diagnosed with EGBM. A right frontal lobe occupancy was detected by magnetic resonance imaging (MRI), and a total tumor resection was performed. Meanwhile, a postoperative histopathology test, including immunohistochemistry and molecular characterization, was conducted, and the results revealed a BRAF V600E mutation, no co-deletion of 1p and 19q, and negative O-6-methylguanine DNA methyltransferase (MGMT) promoter methylation. Then, chemoradiotherapy was conducted, and TTFields and TMZ were performed sequentially. Notably, a long-term PFS of 34 months and a Karnofsky Performance Scale (KPS) of 90 were achieved by the patient on TTFields combined with TMZ, whose average daily usage of TTFields was higher than 90%.

Design, synthesis and biological evaluation of 2-((4-sulfamoylphenyl)amino)-pyrrolo[2,3-d]pyrimidine derivatives as CDK inhibitors.

To explore the potential use of CDK inhibitors in pancreatic ductal adenocarcinoma (PDAC) therapy, a series of novel 2-((4-sulfamoylphenyl)amino)-pyrrolo[2,3-d]pyrimidine derivatives was designed, synthesised, and investigated for inhibition on both CDK kinase activity and cellular proliferation of pancreatic cancer. Most of new sulphonamide-containing derivatives demonstrated strong inhibitory activity on CDK9 and obvious anti-proliferative activity in cell culture. Moreover, two new compounds suppressed cell proliferation of multiple human pancreatic cancer cell lines. The most potent compound 2g inhibited cancer cell proliferation by blocking Rb phosphorylation and induced apoptosis via downregulation of CDK9 downstream proteins Mcl-1 and c-Myc in MIA PaCa-2 cells. CDK9 knockdown experiment suggests its anti-proliferative activity is mainly mediated by CDK9. Additionally, 2g displayed moderate tumour inhibition effect in AsPC-1 derived xenograft mice model. Altogether, this study provided a new start for further optimisation to develop potential CDK inhibitor candidates for PDAC treatment by alone or combination use.

Deep Learning for Noninvasive Assessment of H3 K27M Mutation Status in Diffuse Midline Gliomas Using MR Imaging.

BACKGROUND: Determination of H3 K27M mutation in diffuse midline glioma (DMG) is key for prognostic assessment and stratifying patient subgroups for clinical trials. MRI can noninvasively depict morphological and metabolic characteristics of H3 K27M mutant DMG. PURPOSE: This study aimed to develop a deep learning (DL) approach to noninvasively predict H3 K27M mutation in DMG using T2-weighted images. STUDY TYPE: Retrospective and prospective. POPULATION: For diffuse midline brain gliomas, 341 patients from Center-1 (27 ± 19 years, 184 males), 42 patients from Center-2 (33 ± 19 years, 27 males) and 35 patients (37 ± 18 years, 24 males). For diffuse spinal cord gliomas, 133 patients from Center-1 (30 ± 15 years, 80 males). FIELD STRENGTH/SEQUENCE: 5T and 3T, T2-weighted turbo spin echo imaging. ASSESSMENT: Conventional radiological features were independently reviewed by two neuroradiologists. H3 K27M status was determined by histopathological examination. The Dice coefficient was used to evaluate segmentation performance. Classification performance was evaluated using accuracy, sensitivity, specificity, and area under the curve. STATISTICAL TESTS: Pearson's Chi-squared test, Fisher's exact test, two-sample Student's t-test and Mann-Whitney U test. A two-sided P value <0.05 was considered statistically significant. RESULTS: In the testing cohort, Dice coefficients of tumor segmentation using DL were 0.87 for diffuse midline brain and 0.81 for spinal cord gliomas. In the internal prospective testing dataset, the predictive accuracies, sensitivities, and specificities of H3 K27M mutation status were 92.1%, 98.2%, 82.9% in diffuse midline brain gliomas and 85.4%, 88.9%, 82.6% in spinal cord gliomas. Furthermore, this study showed that the performance generalizes to external institutions, with predictive accuracies of 85.7%-90.5%, sensitivities of 90.9%-96.0%, and specificities of 82.4%-83.3%. DATA CONCLUSION: In this study, an automatic DL framework was developed and validated for accurately predicting H3 K27M mutation using T2-weighted images, which could contribute to the noninvasive determination of H3 K27M status for clinical decision-making. EVIDENCE LEVEL: 2 Technical Efficacy: Stage 2.

Intratumoral CD73: An immune checkpoint shaping an inhibitory tumor microenvironment and implicating poor prognosis in Chinese melanoma cohorts.

Background: As a novel immune checkpoint, CD73 has been reported to play prominent roles in several malignancies. However, the significance of CD73 in melanoma remains ambiguous. This study sought to reveal the impact of CD73 on the tumor microenvironment (TME) and patients' prognosis, and to investigate whether CD73 could be a therapeutic target in Chinese melanomas, which were dominated by acral and mucosal subtypes. Methods: Two independent Chinese cohorts of 194 patients with melanoma were enrolled. CD73 and PD-L1 expression as well as CD8+ and CD56+ cell infiltrations were evaluated by immunohistochemistry in 194 resected melanoma samples. Clinical outcomes of patients were assessed utilizing the Kaplan-Meier plotter and Cox proportional hazard analysis. RNA-seq data was obtained from TCGA database. Gene set functional annotations were performed based on GO, KEGG and GSEA analysis. CIBERSORT, ssGSEA and TIMER were used to explore the association between CD73 and immune infiltration. These findings were validated by establishing tumor xenograft model, and functions of tumor-infiltrating immune cells were examined by flow cytometry and immunofluorescence. Results: High CD73 expression showed poorer clinical outcomes and was identified as an independent prognostic indicator for survival in two cohorts. Expression of CD73 was more prevalent than PD-L1 in Chinese melanoma cohorts (54.6% vs 23.2%). Co-expression of both immune checkpoints was infrequent (12.9%) in melanoma, and 54.4% of PD-L1 negative cases showed elevated expression of CD73. CD73high tumors showed a microenvironment with fewer CD8+ T cells and CD56+ NK cells infiltration, which displayed a dysfunctional phenotype. With the treatment of CD73 inhibitor APCP, the amount of CD8+ T cells and CD56+ NK cells infiltrated in tumors was elevated and the immunosuppressive effect of CD73 was eliminated. Conclusions: High CD73 expression was associated with an inhibitory TME and adverse clinical outcomes of melanoma. In comparison to PD-L1, CD73 was more prevalent and possessed more definite prognostic significance. Therefore, it may serve as a prognostic indicator and immunotherapeutic target next to PD-L1 in melanoma for Chinese population.

An automated approach for predicting glioma grade and survival of LGG patients using CNN and radiomics.

Objectives: To develop and validate an efficient and automatically computational approach for stratifying glioma grades and predicting survival of lower-grade glioma (LGG) patients using an integration of state-of-the-art convolutional neural network (CNN) and radiomics. Method: This retrospective study reviewed 470 preoperative MR images of glioma from BraTs public dataset (n=269) and Jinling hospital (n=201). A fully automated pipeline incorporating tumor segmentation and grading was developed, which can avoid variability and subjectivity of manual segmentations. First, an integrated approach by fusing CNN features and radiomics features was employed to stratify glioma grades. Then, a deep-radiomics signature based on the integrated approach for predicting survival of LGG patients was developed and subsequently validated in an independent cohort. Results: The performance of tumor segmentation achieved a Dice coefficient of 0.81. The intraclass correlation coefficients (ICCs) of the radiomics features between the segmentation network and physicians were all over 0.75. The performance of glioma grading based on integrated approach achieved the area under the curve (AUC) of 0.958, showing the effectiveness of the integrated approach. The multivariable Cox regression results demonstrated that the deep-radiomics signature remained an independent prognostic factor and the integrated nomogram showed significantly better performance than the clinical nomogram in predicting overall survival of LGG patients (C-index: 0.865 vs. 0.796, P=0.005). Conclusion: The proposed integrated approach can be noninvasively and efficiently applied in prediction of gliomas grade and survival. Moreover, our fully automated pipeline successfully achieved computerized segmentation instead of manual segmentation, which shows the potential to be a reproducible approach in clinical practice.

RP-Rs-fMRIomics as a Novel Imaging Analysis Strategy to Empower Diagnosis of Brain Gliomas.

Rs-fMRI can provide rich information about functional processes in the brain with a large array of imaging parameters and is also suitable for investigating the biological processes in cerebral gliomas. We aimed to propose an imaging analysis method of RP-Rs-fMRIomics by adopting omics analysis on rs-fMRI with exhaustive regional parameters and subsequently estimating its feasibility on the prediction diagnosis of gliomas. In this retrospective study, preoperative rs-fMRI data were acquired from patients confirmed with diffuse gliomas (n = 176). A total of 420 features were extracted through measuring 14 regional parameters of rs-fMRI as much as available currently in 10 specific narrow frequency bins and three parts of gliomas. With a randomly split training and testing dataset (ratio 7:3), four classifiers were implemented to construct and optimize RP-Rs-fMRIomics models for predicting glioma grade, IDH status and Karnofsky Performance Status scores. The RP-Rs-fMRIomics models (AUROC 0.988, 0.905, 0.801) were superior to the corresponding traditional single rs-fMRI index (AUROC 0.803, 0.731, 0.632) in predicting glioma grade, IDH and survival. The RP-Rs-fMRIomics analysis, featuring high interpretability, was competitive for prediction of glioma grading, IDH genotype and prognosis. The method expanded the clinical application of rs-fMRI and also contributed a new imaging analysis for brain tumor research.

Bicyclol ameliorates advanced liver diseases in murine models via inhibiting the IL-6/STAT3 signaling pathway.

Bicyclol, a synthetic hepatoprotective and anti-inflammatory agent approved in China, was widely used to treat various hepatitis accompanied by elevated serum aminotransferases. However, the pharmacological effects and mechanisms of bicyclol on advanced liver diseases, such as fibrosis/cirrhosis and hepatocellular carcinoma (HCC), remain to be explored. Here, we revealed that bicyclol prevents from formatting severe fibrosis, slows the progression of moderate liver fibrosis, accelerates the regression of moderate liver fibrosis, decreases the malignancy of HCC in rat models induced by diethylnitrosamine (DEN), and also blocks steatohepatitis to HCC in mice induced by western diet plus carbon tetrachloride and DEN. The detailed pharmacological mechanism showed that bicyclol alleviates chronic progressive liver diseases by inhibiting the levels of IL-6 and subsequent phosphorylated STAT3. Conclusion: Bicyclol plays significant protective roles in multiply stages of fibrosis/cirrhosis-HCC and nonalcoholic fatty liver disease-related HCC via inhibiting IL-6/STAT3 signaling pathway. Therefore, bicyclol might be a promising therapeutic strategy for treating advanced liver diseases.

Design, Synthesis, and Biological Evaluation of 2-((4-Bisarylmethyl-piperazin-1-yl)methyl)benzonitrile Derivatives as HCV Entry Inhibitors.

Viral entry inhibitors are absent in hepatitis C virus (HCV) treatment regimens although a dozen direct-acting antiviral (DAA) drugs are available now. Based on a previously identified HCV entry inhibitor L0909, chemical space exploration and structure-activity relationship (SAR) studies led to the discovery of a new derived scaffold 2-((4-bisarylmethyl-piperazin-1-yl)methyl)benzonitrile. Several new scaffold derivatives exhibited higher in vitro anti-HCV activity at low nanomolar concentrations compared to L0909. A biological study indicated that the high potency of active derivatives 3d, 3h, and 3i was primarily driven by the inhibitory effect on the virus entry stage. Moreover, an SPR experiment confirmed that this class of derivatives might target the HCV E1 protein. Pharmacokinetic studies indicated that compounds 3d and 3i are orally available and long-lasting in rat plasma after oral administration to rats by a single dose of 15 mg/kg. In conclusion, this work provided a novel 2-((4-bisarylmethyl-piperazin-1-yl)methyl)benzonitrile chemotype deserving further investigation into its antiviral therapeutic potential.

Apoptotic bodies extracted from adipose mesenchymal stem cells carry microRNA-21-5p to induce M2 polarization of macrophages and augment skin wound healing by targeting KLF6.

BACKGROUND: Adipose-derived mesenchymal stem cells (adMSCs) are suggested as potential tools for the treatment of regenerative diseases, including tissue repair. This study aimed to explore the function of adMSC-derived apoptotic bodies in skin wound healing and the molecules of action. METHODS: The acquired adMSCs and their-derived apoptotic bodies were identified. A murine model of full-thickness skin wounds was treated with apoptotic bodies. The wound healing process of mice and the pathological changes in wound tissues were examined. Ana-1 macrophages were treated with lipopolysaccharide (LPS) and apoptotic bodies for in vitro experiments. Polarization of macrophages was examined by immunofluorescence staining of the specific biomarkers and ELISA kits. Dermal microvascular endothelial cells (DMECs) or dermal fibroblasts (DFs) were co-cultured with apoptotic bodies or the LPS- and apoptotic bodies-treated Ana-1 cells. Downstream molecules mediated by apoptotic bodies were screened by microarray and bioinformatic analyses. RESULTS: Apoptotic bodies treatment accelerated skin wound healing in mice and promoted formation of granulation tissues and blood vessels in wound tissues. Apoptotic bodies treatment induced M2 polarization of macrophages. The angiogenesis ability of DMECs, and the viability and migration of DFs were increased when co-cultured with the apoptotic bodies-treated Ana-1 cells. MicroRNA (miR)-21-5p was abundantly expressed in ABs, and kruppel like factor 6 (KLF6) mRNA was confirmed as a target of miR-21-5p. Overexpression of KLF6 reduced M2 polarization of macrophages and blocked the promoting effect of apoptotic bodies on wound healing in vitro and in vivo. CONCLUSION: miR-21-5p carried by adMSC-derived apoptotic bodies targets KLF6 to induce M2 polarization of macrophages and augment skin wound healing.

Radiomics-based MRI for predicting Erythropoietin-producing hepatocellular receptor A2 expression and tumor grade in brain diffuse gliomas.

PURPOSE: EphA2 is a key factor underlying invasive propensity of gliomas, and is associated with poor prognosis of tumors. We aimed to develop a radiomics-based imaging index for predicting EphA2 expression in diffuse gliomas, and further estimating its value for grading of tumors. METHODS: A total of 182 patients with diffuse gliomas were included. All subjects underwent pre-operative MRI and post-operative pathological diagnosis. EphA2 expression of tumors was scored on pathological sections with immunohistochemical staining using monoclonal EphA2 antibody. MRI radiomics features were extracted from three-dimensional contrast-enhanced T1-weighted imaging and diffusion kurtosis imaging. Predictive models were constructed using machine learning-based radiomics features selection and three classifiers for predicting EphA2 expression and tumor grade. Features of best EphA2 expression model were subsequently used to construct another model of tumor grading. For each model, 146 cases (80%) were randomly picked as training and the rest 36 (20%) were testing cohorts. EphA2 expression was further correlated to the radiomics features in both grade models using Spearman's correlation. RESULTS: Logistic regression model presented highest performance for predicting EphA2 expression (AUC: 0.836/0.724 in training/validation set). Tumor gradings model guided by features from EphA2 expression model demonstrated comparable performance (AUC: 0.930/0.983) to that constructed directly using imaging radiomics features (AUC: 0.960/0.977). Two radiomics features which included in both LR-grade models showed strong correlation (P < 0.05) with EphA2 expression. CONCLUSION: The expression of EphA2 in gliomas could be predicted by radiomics features extracted from diffusion kurtosis MRI, which could also be used to assist tumor grading.

[Automated grading of glioma based on density and atypia analysis in whole slide images].

Glioma is the most common malignant brain tumor and classification of low grade glioma (LGG) and high grade glioma (HGG) is an important reference of making decisions on patient treatment options and prognosis. This work is largely done manually by pathologist based on an examination of whole slide image (WSI), which is arduous and heavily dependent on doctors' experience. In the World Health Organization (WHO) criteria, grade of glioma is closely related to hypercellularity, nuclear atypia and necrosis. Inspired by this, this paper designed and extracted cell density and atypia features to classify LGG and HGG. First, regions of interest (ROI) were located by analyzing cell density and global density features were extracted as well. Second, local density and atypia features were extracted in ROI. Third, balanced support vector machine (SVM) classifier was trained and tested using 10 selected features. The area under the curve (AUC) and accuracy (ACC) of 5-fold cross validation were 0.92 ± 0.01 and 0.82 ± 0.01 respectively. The results demonstrate that the proposed method of locating ROI is effective and the designed features of density and atypia can be used to predict glioma grade accurately, which can provide reliable basis for clinical diagnosis.

MR-Based Radiomics for Differential Diagnosis between Cystic Pituitary Adenoma and Rathke Cleft Cyst.

BACKGROUND: It is often tricky to differentiate cystic pituitary adenoma from Rathke cleft cyst with visual inspection because of similar MRI presentations between them. We aimed to design an MR-based radiomics model for improving differential diagnosis between them. METHODS: Conventional diagnostic MRI data (T1-,T2-, and postcontrast T1-weighted MR images) were obtained from 215 pathologically confirmed patients (105 cases with cystic pituitary adenoma and the other 110 cases with Rathke cleft cyst) and were divided into training (n = 172) and test sets (n = 43). MRI radiomics features were extracted from the imaging data, and semantic imaging features (n = 15) were visually estimated by two radiologists. Four classifiers were used to construct radiomics models through 5-fold crossvalidation after feature selection with least absolute shrinkage and selection operator. An integrated model by combining radiomics and semantic features was further constructed. The diagnostic performance was validated in the test set. Receiver operating characteristic curve was used to evaluate and compare the performance of the models at the background of diagnostic performance by radiologist. RESULTS: In test set, the combined radiomics and semantic model using ANN classifier obtained the best classification performance with an AUC of 0.848 (95% CI: 0.750-0.946), accuracy of 76.7% (95% CI: 64.1-89.4%), sensitivity of 73.9% (95% CI: 56.0-91.9%), and specificity of 80.0% (95% CI: 62.5-97.5%) and performed better than multiparametric model (AUC = 0.792, 95% CI: 0.674-0.910) or semantic model (AUC = 0.823, 95% CI: 0.705-0.941). The two radiologists had an accuracy of 69.8% and 74.4%, respectively, sensitivity of 69.6% and 73.9%, and specificity of 70.0% and 75.0%. CONCLUSIONS: The MR-based radiomics model had technical feasibility and good diagnostic performance in the differential diagnosis between cystic pituitary adenoma and Rathke cleft cyst.

TGF-ß isoforms inhibit hepatitis C virus propagation in transforming growth factor beta/SMAD protein signalling pathway dependent and independent manners.

Transforming growth factor beta (TGF-ß) plays an important role in the viral liver disease progression via controlling viral propagation and mediating inflammation-associated responses. However, the antiviral activities and mechanisms of TGF-ß isoforms, including TGF-ß1, TGF-ß2 and TGF-ß3, remain unclear. Here, we demonstrated that all of the three TGF-ß isoforms were increased in Huh7.5 cells infected by hepatitis C virus (HCV), but in turn, the elevated TGF-ß isoforms could inhibit HCV propagation with different potency in infectious HCV cell culture system. TGF-ß isoforms suppressed HCV propagation through interrupting several different stages in the whole HCV life cycle, including virus entry and intracellular replication, in TGF-ß/SMAD signalling pathway-dependent and TGF-ß/SMAD signalling pathway-independent manners. TGF-ß isoforms showed additional anti-HCV activities when combined with each other. However, the elevated TGF-ß1 and TGF-ß2, not TGF-ß3, could also induce liver fibrosis with a high expression of type I collagen alpha-1 and α-smooth muscle actin in LX-2 cells. Our results showed a new insight into TGF-ß isoforms in the HCV-related liver disease progression.

Relationship between postoperative lordosis distribution index and adjacent segment disease following L4-S1 posterior lumbar interbody fusion.

BACKGROUND: Adjacent segment disease (ASD) is an acknowledged problem of posterior lumbar interbody fusion (PLIF). Many studies have been reported concerning the role of lordosis distribution index (LDI) in spinal biomechanics. However, few reports have been published about the impact of LDI on ASD following L4-S1 PLIF. METHODS: The study enrolled 200 subjects who underwent L4-S1 PLIF for degenerative spine disease from 2009 to 2014. The average follow-up term was 84 months. Several lower lumbar parameters were measured, including lower lumbar lordosis (LLL), lumbar lordosis (LL), pelvic incidence (PI), and LDI on the pre and postoperative radiograph. Perioperative information, comorbidities, and operative data were documented. Kaplan-Meier curves were plotted for the comparisons of ASD-free survival of 3 different types of postoperative LDI subgroups. RESULTS: The incidence of ASD was found to be 8.5%. LL and LLL increased by 3.96° (38.71° vs 42.67°; P < 0.001) and 3.60° (26.22° vs 28.82°; P < 0.001) after lower lumbar fusion surgery, respectively. Lordosis distribution index (LDI) increased by 0.03 (0.66 vs 0.69, P = 0.004) postoperatively. A significant difference (P = 0.001) was observed when comparing the incidence of ASD among postoperative LDI subgroups. The Kaplan-Meier curves showed a marked difference in ASD-free survival between low and moderate LDI subgroup (log-rank test, P = 0.0012) and high and moderate LDI subgroup (log-rank test, P = 0.0005). CONCLUSION: Patients with abnormal postoperative LDI were statistically more likely to develop ASD than those who had normal postoperative LDI. Moreover, patients with low postoperative LDI were at greater risk for developing ASD than those with high postoperative LDI over time.