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In the field of glioma, transcriptome subtypes have been considered as an important diagnostic and prognostic biomarker that may help improve the treatment efficacy. However, existing identification methods of transcriptome subtypes are limited due to the relatively long detection period, the unattainability of tumor specimens via biopsy or surgery, and the fleeting nature of intralesional heterogeneity. Acetylcysteine In search of a superior model over previous ones, this study evaluated the efficiency of eXtreme Gradient Boosting (XGBoost)-based radiomics model to classify transcriptome subtypes in glioblastoma patients.

This retrospective study retrieved patients from TCGA-GBM and IvyGAP cohorts with pathologically diagnosed glioblastoma, and separated them into different transcriptome subtypes groups. GBM patients were then segmented into three different regions of MRI enhancement of the tumor core (ET), non-enhancing portion of the tumor core (NET), and peritumoral edema (ED). We subsequently used handcrafted radiore) could be expected as a potential combination for classifying transcriptome subtypes with high performance and might raise public attention for further research on radiomics-based GBM models.The purpose of the study was to determine the frequency of vision diagnoses after concussion in adolescents and evaluate the sensitivity and specificity of physician-administered screening for detecting convergence and accommodative disorders post-concussion. We enrolled participants 11 to 17 years old, assessed 4 to 12 weeks following a diagnosed concussion. During the initial concussion examination, a sports medicine physician measured the near point of convergence (NPC), monocular accommodative amplitude (AA), and symptoms using the Convergence Insufficiency Symptom Survey (CISS). A comprehensive oculomotor evaluation was performed by an optometrist. One hundred and thirteen adolescents were enrolled, with a mean age of 15.2 years. Seventy-nine of the 113 (70%) participants had at least one oculomotor diagnosis after concussion, with the most common problems being vergence disorders (60%) and accommodative disorders (57%). The most common vergence disorder was convergence insufficiency (35%). Among accommodative disorders, the most common problem was accommodative insufficiency (35%). In all, 47% of the participants had more than one oculomotor diagnosis following concussion. The sensitivity of physician screening using measures of NPC, AA, and CISS for detecting convergence and accommodative insufficiency was 63%, 43%, 48%, respectively. The results of this study provide additional evidence that vision problems are common in adolescents with persistent concussion symptoms in the sub-acute phase 4 to 12 weeks post-concussion, and current physician screening methods using the NPC, AA, or the CISS underperform. Thus, it is prudent that adolescents with post-concussion symptoms lasting more than 4 weeks post injury receive a comprehensive oculomotor examination.Graphene acoustic transducers have high sensitivity in receiving mode. However, they are used in transmitting mode with low radiation performance. A graphene acoustic transducer with high sensitivity and radiation performance is proposed in this study. The transducer is composed of graphene diaphragm, an insulating layer embedded in a copper planar coil, and a bottom layer plated with copper. The proposed capacitive transducer is driven by electrostatic and electromagnetic excitation. The sensitivity and radiation performance of the transducer are analyzed by transceiver theory and simulation models. The results demonstrate that the proposed capacitive transducer has excellent acoustic performance with sensitivity of -42 dB and the sound pressure level of 106 dB at 4 kHz with a 20-turn coil that is more than doubled compared without a copper coil. In addition, the radiation performance of the transducer is discussed by the coil parameters including coil turns and coil current, which can provide a theoretical basis for further experiments.To uncover the genetic underpinnings of brain disorders, brain imaging genomics usually jointly analyzes genetic variations and imaging measurements. Meanwhile, other biomarkers such as proteomic expressions can also carry valuable complementary information. Therefore, it is necessary yet challenging to investigate the underlying relationships among genetic variations, proteomic expressions, and neuroimaging measurements, which stands a chance of gaining new insights into the pathogenesis of brain disorders. Given multiple types of biomarkers, using sparse multi-view canonical correlation analysis (SMCCA) and its variants to identify the multi-way associations is straightforward. However, due to the gradient domination issue caused by the naive fusion of multiple SCCA objectives, SMCCA is suboptimal. In this paper, we proposed two adaptive SMCCA (AdaSMCCA) methods, i.e. the robustness-aware AdaSMCCA and the uncertainty-aware AdaSMCCA, to analyze the complicated associations among genetic, proteomic, and neuroimaging biomarkers. We also imposed a data-driven feature grouping penalty to the genetic data with aim to uncover the joint inheritance of neighboring genetic variations. An efficient optimization algorithm, which is guaranteed to converge, was provided. Using two state-of-the-art SMCCA as benchmarks, we evaluated robustness-aware AdaSMCCA and uncertainty-aware AdaSMCCA on both synthetic data and real neuroimaging, proteomics, and genetic data. Both proposed methods obtained higher associations and cleaner canonical weight profiles than comparison methods, indicating their promising capability for association identification and feature selection. In addition, the subsequent analysis showed that the identified biomarkers were related to Alzheimer's disease, demonstrating the power of our methods in identifying multi-way bi-multivariate associations among multiple heterogeneous biomarkers.In this article, STEM-EELS methodology is described to investigate the composition of sensitive crystalline Silicon/amorphous aluminum oxide (c-Si/a-AlOx) interface of an a AlOx/amorphous hydrogenated silicon nitride (a-AlOx/a-SiNxH) passivation stack of a c-Si solar cell. In this stack, a-AlOx has the distinctive characteristic to provide both chemical and field effect passivation, which need further research to be more controlled in order to improve solar cell efficiency. a-AlOx is known to be unstable under the electron-beam, so we first present a detailed study on the electron-beam radiation damage to c-Si/a-AlOx interface. This interface can indeed undergo several electron-beam irradiation damage like sputtering, knock-on or radiolysis if precautions are not taken. Radiolysis damage has been found to be the dominant radiation damage. Thus, several STEM-EELS acquisition parameters like acceleration voltage, electron dose and scan orientation were taken into account and modified to limit this radiolysis damage.
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