A novel exosome-related prognostic risk model for thyroid cancer.

AIM: The aim was to build an exosome-related gene (ERG) risk model for thyroid cancer (TC) patients. METHODS: Note that, 510 TC samples from The Cancer Genome Atlas database and 121 ERGs from the ExoBCD database were obtained. Differential gene expression analysis was performed to get ERGs in TC (TERGs). Functional enrichment analyses including Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) were conducted on the TERGs. Then we constructed a model based on LASSO Cox regression analysis. Kaplan-Meier survival analysis was applied and a Nomogram model was also built. The immune landscape was evaluated by CIBERSORT. RESULTS: Thirty-eight TERGs were identified and their functions were enriched on 591 GO terms and 30 KEGG pathways. We built a Risk Score model based on FGFR3, ADRA1B, and POSTN. Risk Scores were significantly higher in T4 than in other stages, meanwhile, it didn't significantly differ in genders and TNM N or M classifications. The nomogram model could reliably predict the overall survival of TC patients. The mutation rate of BRAF and expression of cytotoxic T-lymphocyte-associated protein 4 were significantly higher in the high-risk group than in the low-risk group. The risk score was significantly correlated to the immune landscape. CONCLUSION: We built a Risk Score model using FGFR3, ADRA1B, and POSTN which could reliably predict the prognosis of TC patients.

Simulation of a new respiratory phase sorting method for 4D-imaging using optical surface information towards precision radiotherapy.

BACKGROUND: Respiratory signal detection is critical for 4-dimensional (4D) imaging. This study proposes and evaluates a novel phase sorting method using optical surface imaging (OSI), aiming to improve the precision of radiotherapy. METHOD: Based on 4D Extended Cardiac-Torso (XCAT) digital phantom, OSI in point cloud format was generated from the body segmentation, and image projections were simulated using the geometries of Varian 4D kV cone-beam-CT (CBCT). Respiratory signals were extracted respectively from the segmented diaphragm image (reference method) and OSI respectively, where Gaussian Mixture Model and Principal Component Analysis (PCA) were used for image registration and dimension reduction respectively. Breathing frequencies were compared using Fast-Fourier-Transform. Consistency of 4DCBCT images reconstructed using Maximum Likelihood Expectation Maximization algorithm was also evaluated quantitatively, where high consistency can be suggested by lower Root-Mean-Square-Error (RMSE), Structural-Similarity-Index (SSIM) value closer to 1, and larger Peak-Signal-To-Noise-Ratio (PSNR) respectively. RESULTS: High consistency of breathing frequencies was observed between the diaphragm-based (0.232 Hz) and OSI-based (0.251 Hz) signals, with a slight discrepancy of 0.019Hz. Using end of expiration (EOE) and end of inspiration (EOI) phases as examples, the mean±1SD values of the 80 transverse, 100 coronal and 120 sagittal planes were 0.967, 0,972, 0.974 (SSIM); 1.657 ± 0.368, 1.464 ± 0.104, 1.479 ± 0.297 (RMSE); and 40.501 ± 1.737, 41.532 ± 1.464, 41.553 ± 1.910 (PSNR) for the EOE; and 0.969, 0.973, 0.973 (SSIM); 1.686 ± 0.278, 1.422 ± 0.089, 1.489 ± 0.238 (RMSE); and 40.535 ± 1.539, 41.605 ± 0.534, 41.401 ± 1.496 (PSNR) for EOI respectively. CONCLUSIONS: This work proposed and evaluated a novel respiratory phase sorting approach for 4D imaging using optical surface signals, which can potentially be applied to precision radiotherapy. Its potential advantages were non-ionizing, non-invasive, non-contact, and more compatible with various anatomic regions and treatment/imaging systems.

A Simulation Study on the Effect of Residual Stress on the Multi-Layer Selective Laser Melting Processes Considering Solid-State Phase Transformation.

The selective laser melting (SLM) manufacturing process is a complex process involving moving a molten pool, rapid non-equilibrium solidification and solid phase transformation. If the thermal residual stress is too large, it may lead to warping, cracking and failure of the structures. The present work aims to establish a thermo-mechanical framework to predict temperature evolutions, molten pool configurations and residual stresses of materials in the SLM process, based on the toolpath-mesh intersection method. Moreover, the influences of the laser power, process parameters and mesh size have been discussed. The stress concentration occurred at the interface between the melt layer and substrate results in warping deformation of the materials. This work provides a novel method to reveal the resulting physical mechanism inside the molten pool in terms of residual stresses and distortions.

An integrated RNA-Seq and network study reveals that valproate inhibited progesterone production in human granulosa cells.

BACKGROUND: Valproate (VPA) is an antiepileptic drug (AEDs) with an ideal effect against epilepsy as well as other neuropsychiatric diseases. There is considerable evidence that women taking VPA are prone to reproductive endocrine disorders. However, few studies have been published about VPA effects on human ovarian granulosa cells. METHODS: By treating human ovarian granulosa cell line KGN with VPA, the cell viability and progesterone production function were evaluated. RNA-sequencing was applied to uncover the global gene expression upon VPA treatment. RESULTS: We revealed that VPA dose-dependently repressed the viability of KGN. VPA treatment at 600 µM inhibited the progesterone production. The mRNA and protein expression of CYP11A1 and STAR, two key enzymes in the biosynthesis of progesterone, were both suppressed. Gene set enrichment analysis and Kyoto Encyclopedia of Genes and Genomes pathway analysis of the transcriptome revealed classical functions of VPA as a neuromodulator and regulator of histone acetylation modifications. In addition to this, VPA commonly affected many steroid metabolism related genes in follicle cells, such as promoting the expression of vitamin D receptor (VDR). CONCLUSION: Our findings suggest that VPA caused steroids metabolism pathways disturbance related with ovarian function and inhibited progesterone biosynthesis by inhibiting the expression of steroidogenesis genes. Our research may provide theoretical basis for the better use of VPA and the possible ways to counteract its side effects.

The comparison of accuracy and practicability between ultrasound and spiral CT in the diagnosis of intestinal obstruction: A protocol for systematic review and meta-analysis.

BACKGROUND: Acute abdominal pain is often caused by intestinal obstruction, with high morbidity, and mortality, so that the early diagnosis is particularly important. Currently, both spiral CT and ultrasound are common imaging diagnostic methods. However, the accuracy and practicality of the diagnosis are controversial. Therefore, the purpose of this study is to systematically evaluate the accuracy and practicality of spiral CT and ultrasound in the diagnosis of intestinal obstruction. METHODS: Retrieval of English database (PubMed, Embase, Web of Science, the Cochrane Library) and Chinese database (CNKI, WAN FANG, VIP, CBMDISC) by computers. From the establishment of the database to October 2020, a diagnostic experimental study on the diagnosis of intestinal obstruction by ultrasound and spiral CT was conducted. Two researchers independently conducted data extraction and quality evaluation of literature on the included studies, and Meta Disc1.4 and RevMan5.3 were used for meta-analysis on the included literature. RESULTS: Sensitivity, specificity, po-sitive Likelihood ratio, NE-Gative likelihood ratio, diagnostic odds ratio and other indicators were used to determine the diagnostic efficacy of ultrasound and helical CT. CONCLUSION: This study is aimed at providing an evidence-based basis for clinicians to choose an appropriate or optimal diagnostic method by comparison of the accuracy and practicality between spiral CT and ultrasound in the diagnosis of intestinal obstruction. ETHICS AND DISSEMINATION: The private information from individuals will not be published. This systematic review also will not involve endangering participant rights. Ethical approval is not required. The results may be published in a peer-reviewed journal or disseminated in relevant conferences. OSF REGISTRATION NUMBER: DOI 10.17605/ OSF.IO / Q5RNS.

Bisphenol A decreases progesterone synthesis in human ovarian granulosa cells.

Evidences indicate that the decline of female fertility is becoming a common problem over the past few decades. Environmental exposure of Bisphenol A (BPA) has been considered as an endocrine-disrupting chemical deleteriously affecting human reproductions. To better understand the effect of BPA exposure on human ovarian granulosa cells, we treated human ovarian granulosa cell line (KGN) with increasing concentrations (0.1, 1, 10, and 100 µM) of BPA for 24 hr. About 0.1, 1, and 10 µM BPA did not significantly affect the viability of KGN while 100 µM of BPA caused a statistically significant decrease in the viability of KGN. Treatment KGN with 10 µM BPA resulted in a significant decrease in progesterone biosynthesis. The treatment also significantly increased the expression of ATP binding cassette subfamily A member 1 (ABCA1) and steroidogenic acute regulatory protein (STAR). In the current study, exposure to BPA could lead to decreased progesterone production probably through the upregulation of ABCA1 in human granulosa cells.