Grading of Gliomas by Contrast-Enhanced CT Radiomics Features.

Background: Gliomas, as Central Nervous System (CNS) tumors, are greatly common with 80% of malignancy. Treatment methods for gliomas, such as surgery, radiation therapy, and chemotherapy depend on the grade, size, location, and the patient's age. Objective: This study aimed to quantify glioma based on the radiomics analysis and classify its grade into High-grade Glioma (HGG) or Low-grade Glioma (LGG) by various machine-learning methods using contrast-enhanced brain Computerized Tomography (CT) scans. Material and Methods: This retrospective study involved acquiring and segmenting data, selecting and extracting features, classifying, analyzing, and evaluating classifiers. The study included a total of 62 patients (31 with LGG and 31 with HGG). The tumors were segmented by an experienced CT-scan technologist with 3D slicer software. A total of 14 shape features, 18 histogram-based features, and 75 texture-based features were computed. The Area Under the Curve (AUC) and Receiver Operating Characteristic Curve (ROC) were used to evaluate and compare classification models. Results: A total of 13 out of 107 features were selected to differentiate between LGGs and HGGs and to perform various classifier algorithms with different cross-validations. The best classifier algorithm was linear-discriminant with 93.5% accuracy, 96.77% sensitivity, 90.3% specificity, and 0.98% AUC in the differentiation of LGGs and HGGs. Conclusion: The proposed method can identify LGG and HGG with 93.5% accuracy, 96.77% sensitivity, 90.3% specificity, and 0.98% AUC, leading to the best treatment for glioma patients by using CT scans based on radiomics analysis.

Unsupervised deep learning registration model for multimodal brain images.

Multimodal image registration is a key for many clinical image-guided interventions. However, it is a challenging task because of complicated and unknown relationships between different modalities. Currently, deep supervised learning is the state-of-theart method at which the registration is conducted in end-to-end manner and one-shot. Therefore, a huge ground-truth data is required to improve the results of deep neural networks for registration. Moreover, supervised methods may yield models that bias towards annotated structures. Here, to deal with above challenges, an alternative approach is using unsupervised learning models. In this study, we have designed a novel deep unsupervised Convolutional Neural Network (CNN)-based model based on computer tomography/magnetic resonance (CT/MR) co-registration of brain images in an affine manner. For this purpose, we created a dataset consisting of 1100 pairs of CT/MR slices from the brain of 110 neuropsychic patients with/without tumor. At the next step, 12 landmarks were selected by a well-experienced radiologist and annotated on each slice resulting in the computation of series of metrics evaluation, target registration error (TRE), Dice similarity, Hausdorff, and Jaccard coefficients. The proposed method could register the multimodal images with TRE 9.89, Dice similarity 0.79, Hausdorff 7.15, and Jaccard 0.75 that are appreciable for clinical applications. Moreover, the approach registered the images in an acceptable time 203 ms and can be appreciable for clinical usage due to the short registration time and high accuracy. Here, the results illustrated that our proposed method achieved competitive performance against other related approaches from both reasonable computation time and the metrics evaluation.

Wharton jelly stem cells inhibits AGS gastric cancer cells through induction of apoptosis and modification of MAPK and NF-κB signaling pathways.

BACKGROUND: Gastric cancer) GC) is one of the most common cancer with high mortality worldwide. The human Wharton's jelly stem cells (hWJSCs) can inhibit several cancer cells through several molecular pathways. Therefore, the present study aimed to investigate anticancer effects of hWJSCs conditioned medium (hWJSC-CM) and cell-free lysate (hWJSC-CL) against of GC cell line AGS and underlying signaling pathways. METHODS: In this study, we evaluated the effects of hWJSC-CM and hWJSC-CL on viability, proliferation, migration, invasion, apoptosis, and MAPK and NF-κB signaling pathways in AGS cells. Moreover, mRNA expression of genes involved in apoptosis (BAX, BCL2, SMAC, and SURVIVIN), as well as expression of proteins involved in NF-κB and MAPK signaling pathways were evaluated. RESULTS: The obtained results showed that the hWJSC-CM and hWJSC-CL decreased viability, migration, and invasion of GC cell line AGS in a concentration and time dependent manner. We observed that the hWJSC-CM and hWJSC-CL induced apoptosis pathway through regulation of apoptosis involved genes mRNA expression. In addition, the hWJSC-CM and hWJSC-CL suppressed NF-κB signaling pathways as well as promoted MAPK signaling pathways. CONCLUSION: In general, our study suggested that the hWJSC-CM and hWJSC-CL inhibits proliferation and viability of GC cell line AGS through induction of apoptosis, as well as modification of NF-κB and MAPK signaling pathways.

Beyond hierarchical mixed nickel-cobalt hydroxide and ferric oxide formation onto the green carbons for energy storage applications.

To attain superior energy density concurrently with high power density, high-performance supercapacitors have been developed. Herein an innovative strategy has been adopted to fabricate unique binder-free electrodes composed of a unique porous structure of binary metal carbonate hydroxide nanomace-decorated hydrothermal porous carbon spheres (PCSs). Hierarchical nickel-cobalt carbonate hydroxide (NiCOCH) nanomaces, directly grown on PCSs, are used as positive electrodes for supercapacitors fabrication. Furthermore, Fe2O3@PCS composites, having benefits of highly reversible redox reaction in the negative potential window and highly porous structure, are employed as the negative electrode in the fabrication of the asymmetric supercapacitors (ASCs). The assembled NiCoCH@PCS// Fe2O3@PCS asymmetric devices with a wide electrochemical potential window not only have the merit of high energy and power densities but also receive benefits from remarkable cycle stability. These encouraging outcomes that are mutually beneficial, make these fabricated ASCs significantly ideal for high-performance electronics.

Developing oncolytic Herpes simplex virus type 1 through UL39 knockout by CRISPR-Cas9.

OBJECTIVES: Oncolytic Herpes simplex virus type 1 (HSV-1) has emerged as a promising strategy for cancer therapy. However, development of novel oncolytic mutants has remained a major challenge owing to low efficiency of conventional genome editing methods. Recently, CRISPR-Cas9 has revolutionized genome editing. MATERIALS AND METHODS: In this study, we aimed to evaluate the capability of CRISPR-Cas9 to manipulate the UL39 gene to create oncolytic HSV-1. Herein, three sgRNAs were designed against the UL39 gene and transfected into HEK-293 cell line followed by infection with HSV-1 KOS. RESULTS: After three rounds of plaque purification, several HSV-1 mutants were identified by PCR analysis and sequencing. One of these mutations in which 55 nucleotides were deleted resulted in a frameshift mutation that in turn produced a truncated protein with only 167 amino acids from 1137 amino acids. Functional analysis in Vero and primary fibroblast cells revealed that viral replication was significantly lower and plaque size was smaller in the HSV-1 mutant compared with HSV-1 KOS. Moreover, the relative amount of viral genome present in the supernatants of infected cells (Vero and primary fibroblast cells) with HSV-1 mutant was significantly decreased compared with those of HSV-1 KOS. CONCLUSION: Our data revealed that targeting UL39 with CRISPR-Cas9 could develop oncolytic HSV-1.

Effect of dental implantation on the hard and soft tissues around the adjacent natural teeth.

BACKGROUND: Dental implantation has become widespread for esthetic and functional rehabilitation following single tooth loss as a preferred alternative to conventional tooth-supported restorations. The main advantage of dental implant placement is that it does not require the preparation of the adjacent sound teeth. OBJECTIVES: The aim of this cohort study was to assess the effect of dental implantation on the hard and soft tissues around the adjacent natural teeth. MATERIAL AND METHODS: In this historical cohort, 34 'connect-type' TBR® implants (bone level), 4 mm in diameter, were submerged in the intact bone of 22 patients (7 males and 15 females). The intraoral and extraoral clinical examination as well as periapical radiography were carried out preoperatively or right after surgery (baseline), at 3 months postoperatively (the time of prosthetic delivery), and at 3 and 6 months after prosthetic delivery. The data was analyzed using the Friedman test (due to the non-normal distribution of the data). In case of presence of a significant difference, pairwise comparisons were performed using the post-hoc Wilcoxon test with the Bonferroni correction. All statistical analyses were performed with a 95% confidence interval (CI) using the SPSS for Windows, v. 16.0 software. The p­value <0.05 was considered statistically significant. RESULTS: The distance from the cementoenamel junction (CEJ) of the adjacent teeth to the bone crest significantly increased at different postoperative time points compared to baseline (p < 0.001). The changes in the papillae of the adjacent teeth were also significant at different postoperative time points (p = 0.04). The pocket depth of the adjacent teeth increased, although the value at 3 months postoperatively was not significantly different from the baseline value (p = 0.842). The distance from the implant shoulder to the bone crest of the adjacent teeth significantly increased at different postoperative time points compared to baseline (p < 0.001). CONCLUSIONS: Our results indicate that implant surgery significantly affects the soft and hard tissues around the adjacent natural teeth.

Complete genome sequence of a multi-recombinant echovirus 6 strain isolated from CSF in Ahvaz, Southwestern Iran.

BACKGROUND: Echovirus 6 (E6), is one of the main enteroviral serotypes, was initially isolated from patients with aseptic meningitis (AM) and is a major cause of hospitalization among children and adults worldwide. METHODS: A cerebrospinal fluid (CSF) sample was collected from patient with clinically suspected aseptic meningitis (AM) in August 2011. Following detection of a virus and subsequent virus serotyping, the whole genome sequence was determined. The sequence of the VP1 region of the isolated strain E6 RA/E6/Ahvaz/Iran/2011 showed 79% (>75%) nucleotide and 94% (>85%) amino acid homology with prototype strain D'Amori. The isolated strain was identified as an E6 serotype. A specimen was cultured in a human rhabdomyosarcoma (RD) cell line. Following propagation, the virus was further analyzed using the plaque assay technique, reverse transcription PCR (RT-PCR), rapid amplification of CDNA ends (RACE), TA cloning, sequencing, phylogenetic analysis, Simplot and boot scanning analyses (ver. 3.5) were applied to find evidence of recombination in the isolated strain. RESULTS: The isolated Echo6 strain RA/E6/Ahvaz/Iran/2011 has been recorded in GenBank with a partial and complete genome accession numbers (KX619440) (KX198605), respectively. The complete genomic sequence was 7435 nt, with a 742 bp 5' UTR, 117 bp 3' UTR, and an open reading frame (ORF) encoding a polypeptide of 2191 amino acids. The nucleotide analysis of the VP1 and structural genomic regions of the isolated strain showed high similarity with strain E6-10887-99 isolated from patient with facial nerve paresis in Russia in 1999. The recombinations evidence were observed in the isolated strain E6 RA/E6/Ahvaz/Iran/2011 and found to have a high levels of inter-serotypic exchanges in 2C and 3A-3C genomic regions with Echovirus13 and Echovirus14, respectively. CONCLUSION: Full genome sequence analysis of enteroviral is required to understand the epidemiological pattern and to evaluate the new enterovirus circulating in community.

Prevalence of Hepatitis C virus Genotype 3a in patients with Hodgkin and Non-Hodgkin Lymphoma.

BACKGROUND AND OBJECTIVES: Hepatitis C virus (HCV) is a major public health problem worldwide. Replication and persistence of HCV genome have been described in the liver tissue as well as B cells lymphocyte. Several investigations have reported that long-term persistence of HCV in B cells may result in Hodgkin and Non-Hodgkin lymphoma. This study was aimed to determine frequency of HCV RNA in histological tissues obtained from patients suffered from Hodgkin and Non-Hodgkin lymphoma. MATERIALS AND METHODS: 52 formalin-fixed paraffin-embedded tissue blocks including 23 (44.3%) Hodgkin and 29 (55.7%) Non-Hodgkin samples were collected and five micrometer sections were prepared. RNA was extracted and cDNA was synthesized. Two consecutive Nested RT-PCR assays were carried out for detection of HCV 5' UTR and core gene. RT-PCR products were sequenced and aligned to construct HCV phylogenic tree to evaluate the homology of sequences in comparison to the reference sequences retrieved from Genbank. RESULTS: Overall, 6 Non-Hodgkin (20.6%) and 3 Hodgkin lymphoma (13.04%) samples showed positive PCR results for both 5' UTR and HCV core RNA via nested PCR (P<0.469). Sequencing results revealed that all detected HCV RNA samples belonged to the genotype 3a. CONCLUSION: Despite low prevalence of HCV infection in Iran, high frequency of HCV RNA genotypes 3a (17.3%) has been found in patients with Hodgkin and Non-Hodgkin lymphoma. To improve treatment regimens, screening of HCV RNA in patients suffered from Hodgkin or Non-Hodgkin lymphoma is recommended which can be done through highly sensitive molecular means before and after immunosuppression status.