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The presence of "ill-posed samples" specifically in low-volume datasets leads to accuracy decrement in the learning procedure and the generalization of neural networks. Such samples can be caused by various reasons such as noise contamination, corrupted sensors, or even, the complex distribution of physical properties governing the problem. The peak ground acceleration (PGA) datasets are definitely among the last mentioned. Focusing on speed and accuracy, a method for calculating earthquake magnitude based on the PGA data recorded at a single station along with hypocentral information has been presented in this research. Here, after training a deep neural network, the regression errors of the training data samples are clustered into two groups, namely well and ill posed using the grey wolf optimization algorithm. Instead of being removed, the data samples with low learning rates are then modified using samples selected from the other cluster in a fusional form. Then, two separate models are used and trained independently for the clusters. Next, in addition to the routine procedure of network generalization, every new sample is first checked whether is more likely to belong to which group of the clustered data, and after processing, the corresponding trained model is used. The results of the experiments show that using the proposed method results in magnitude calculation with an error order of less than 0.212 units of moment magnitude with a probability of more than 99.7%, which is superior to the conventional methods some of which were reviewed in this research. [ABSTRACT FROM AUTHOR]

The novel derivatives of tetrahydropyridothienopyrimidine-based compounds have been designed and efficiently synthesized with good yields through seven steps reaction. The anticancer activity of compounds 11a-y has been evaluated against MCF-7, PC-3, HEPG-2, SW-480, and HUVEC cell lines by MTT assay. The target compounds showed IC50 values between 2.81–29.6 μg/mL and were compared with sorafenib as a reference drug. Among them, compound 11n showed high cytotoxic activity against four out of five examined cell lines and was 14 times more selective against MRC5. The flow cytometric analysis confirmed the induction of apoptotic cell death by this compound against HUVEC and MCF-7 cells. In addition, 11n caused sub-G1 phase arrest in the cell cycle arrest. Besides, this compound induced anti-angiogenesis in CAM assay and increased the level of caspase-3 by 5.2 fold. The western-blot analysis of the most active compound, 11n, revealed the inhibition of VEGFR-2 phosphorylation. Molecular docking study also showed the important interactions for compound 11n. [ABSTRACT FROM AUTHOR]

BRCA1 and BRCA2 are two prominent genes that account for about 20–40% of inherited breast cancer. Mutations in these genes are often associated with clustering of especially early-onset cancers in the family. The spectrum of BRCA variants showed a significant difference between geographic regions and ethnicities. The frequency and spectrum of BRCA mutations in Iran, a country in southwest Asia, have not yet been thoroughly studied. Here, for the first time, all published and not published BRCA pathogenic variants are presented. Among 1040 high risk families (1258 cases) which were detected, 116 families were found to carry pathogenic variants in either BRCA1 or BRCA2. Altogether 89 distinct types of pathogenic variants have been detected in Iran, including 41 in BRCA1 and 48 in BRCA2. 16 out of 89 mutations had not been previously reported in Iran and are presented for the first time in this article, among which 4 mutations are novel worldwide. 20% of families had one of the seven most commonly observed mutations, including c.81-1G > C, c.66_67delAG, c.4609C>T, c.1568delT, c.1961delA, in BRCA1 and: c.3751_3752insA, c.8585dupT in BRCA2. Combining the data from published articles and our study which has not been published before, a comprehensive table is created as a reference for entire BRCA pathogenic variants and their frequencies in Iran. [ABSTRACT FROM AUTHOR]

The present study aimed to improve the understanding of non-uterine leiomyosarcoma (NULMS) prognostic genes through system biology approaches. This cancer is heterogeneous and rare. Moreover, gene interaction networks have not been reported in NULMS yet. The datasets were obtained from the public gene expression databases. Seven co-expression modules were identified from 5000 most connected genes; using weighted gene co-expression network analysis. Using Cox regression, the modules showed favorable (HR = 0.6, 95% CI = 0.4–0.89, P = 0.0125), (HR = 0.65, 95% CI = 0.44–0.98, P = 0.04) and poor (HR = 1.55, 95% CI = 1.06–2.27, P = 0.025) prognosis to the overall survival (OS) (time = 3740 days). The first one was significant in multivariate HR estimates (HR = 0.4, 95% CI = 0.28–0.69, P = 0.0004). Enriched genes through the Database for Annotation, Visualization, and Integrated Discovery (DAVID) revealed significant immune-related pathways; suggesting immune cell infiltration as a favorable prognostic factor. The most significant protective genes were ICAM3, NCR3, KLRB1, and IL18RAP, which were in one of the significant modules. Moreover, genes related to angiogenesis, cell–cell adhesion, protein glycosylation, and protein transport such as PYCR1, SRM, and MDFI negatively affected the OS and were found in the other related module. In conclusion, our analysis suggests that NULMS might be a good candidate for immunotherapy. Moreover, the genes found in this study might be potential candidates for targeted therapy. [ABSTRACT FROM AUTHOR]

A novel series of 1-(5-(benzylthio)-1,3,4-thiadiazol-2-yl)-3-phenylurea derivatives (5a–l) were designed and synthesized as sorafenib analogs. The in vitro cytotoxicity effects of synthesized compounds were evaluated against four different human cancer cells including MCF-7, HepG2, A549, and HeLa cell lines. The biological results showed that most of the compounds significantly prevented the proliferation of tested cancer cells. In particular, 2-F, 4-Cl, and 2,6-diF substituted derivatives (5d, 5g, and 5k) showed promising activities, especially against Hela cancer cells (IC50 = 0.37, 0.73 and 0.95 µM, respectively) which were significantly more potent than sorafenib as the reference drug (IC50 = 7.91 µM). Flow cytometry analysis revealed that the prototype compounds (5d, 5g, and 5k) significantly induced apoptotic cell death in HeLa cancer cells and blocked the cell cycle at the sub-G1 phase. Moreover, in silico docking study confirmed the binding of the prototype compound to the active site of VEGFR-2. [ABSTRACT FROM AUTHOR]

Carcinoembryonic antigen (CEA) family members play important roles in malignancies and are introduced as biomarkers in different types of cancers. Among them CEACAM19 (CEAL1) gene, a new member of the CEA family, remains to be fully elucidated. The aim of this study was investigating the mRNA expression level of CEACAM19 in tumor samples of breast cancer patients compared to breast tissue of normal individuals. We evaluated the expression level of this gene in 75 breast tumors by using real-time quantitative PCR. Also, we studied the correlation between CEACAM19 expression and clinicopathological features and hormone receptors status, including estrogen receptor (ER), progesterone receptor (PR) and human epidermal growth factor receptor 2 of patients. Out of the enrolled patients, six of them (7.9%) showed low expression, ten (13.2%) showed normal expression and 59 (77.6%) showed high expression of CEACAM19. There was a significant correlation between high expression of CEACAM19 gene in tumor samples compared to normal tissues ( P = 0.039). No significant correlation was seen between clinicopathological factors and disease-free survival with mRNA levels of CEACAM19 in tumor samples, while the difference between the expression of CEACAM19 in ER/PR-positive and ER/PR-negative breast cancer patients was statistically significant ( P = 0.046). In conclusion, CEACAM19 showed high expression in tumor samples compared to normal mammary tissue. In addition, CEACAM19 may represent as a novel therapeutic target in certain subgroups of breast cancer patients such as ER/PR-negative. Critical roles of CEA proteins in tumor progression may nominate them as robust potential targets for therapeutic intervention in near future. [ABSTRACT FROM AUTHOR]