14 research outputs found

    Chemistry-induced Intrinsic Stress Variations During the Chemical Vapor Deposition of Polycrystalline Diamond

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    Intrinsic tensile stresses in polycrystalline films are often attributed to the coalescence of neighboring grains during the early stages of film growth, where the energy decrease associated with converting two free surfaces into a grain boundary provides the driving force for creating tensile stress. Several recent models have analyzed this energy trade off to establish relationships between the stress and the surface∕interfacial energy driving force, the elastic properties of the film, and the grain size. To investigate these predictions, experiments were conducted with diamond films produced by chemical vapor deposition. A multistep processing procedure was used to produce films with significant variations in the tensile stress, but with essentially identical grain sizes. The experimental results demonstrate that modest changes in the deposition chemistry can lead to significant changes in the resultant tensile stresses. Two general approaches were considered to reconcile this data with existing models of stress evolution. Geometric effects associated with the shape of the growing crystal were evaluated with a finite element model of stress evolution, and variations in the surface∕interfacial energy driving force were assessed in terms of both chemical changes in the deposition atmosphere and differences in the crystal growth morphology. These attempts to explain the experimental results were only partially successful, which suggests that other factors probably affect intrinsic tensile stress evolution due to grain boundary formation

    Identifying New Potential Biomarkers in Adrenocortical Tumors Based on mRNA Expression Data Using Machine Learning

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    Simple Summary Using a visual-based clustering method on the TCGA RNA sequencing data of a large adrenocortical carcinoma (ACC) cohort, we were able to classify these tumors in two distinct clusters largely overlapping with previously identified ones. As previously shown, the identified clusters also correlated with patient survival. Applying the visual clustering method to a second dataset also including benign adrenocortical samples additionally revealed that one of the ACC clusters is more closely located to the benign samples, providing a possible explanation for the better survival of this ACC cluster. Furthermore, the subsequent use of machine learning identified new possible biomarker genes with prognostic potential for this rare disease, that are significantly differentially expressed in the different survival clusters and should be further evaluated. Abstract Adrenocortical carcinoma (ACC) is a rare disease, associated with poor survival. Several “multiple-omics” studies characterizing ACC on a molecular level identified two different clusters correlating with patient survival (C1A and C1B). We here used the publicly available transcriptome data from the TCGA-ACC dataset (n = 79), applying machine learning (ML) methods to classify the ACC based on expression pattern in an unbiased manner. UMAP (uniform manifold approximation and projection)-based clustering resulted in two distinct groups, ACC-UMAP1 and ACC-UMAP2, that largely overlap with clusters C1B and C1A, respectively. However, subsequent use of random-forest-based learning revealed a set of new possible marker genes showing significant differential expression in the described clusters (e.g., SOAT1, EIF2A1). For validation purposes, we used a secondary dataset based on a previous study from our group, consisting of 4 normal adrenal glands and 52 benign and 7 malignant tumor samples. The results largely confirmed those obtained for the TCGA-ACC cohort. In addition, the ENSAT dataset showed a correlation between benign adrenocortical tumors and the good prognosis ACC cluster ACC-UMAP1/C1B. In conclusion, the use of ML approaches re-identified and redefined known prognostic ACC subgroups. On the other hand, the subsequent use of random-forest-based learning identified new possible prognostic marker genes for ACC

    Melanoma Extracellular Vesicles Generate Immunosuppressive Myeloid Cells by Upregulating PD-L1 via TLR4 Signaling

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    Tumor cell-derived extracellular vesicles (EV) convert normal myeloid cells into myeloid-derived suppressor cells (MDSC), inhibiting antitumor immune responses. Here, we show that EV from Ret mouse melanoma cells upregulate the expression of programmed cell death ligand 1 (PD-L1) on mouse immature myeloid cells (IMC), leading to suppression of T-cell activation. PD-L1 expression and the immunosuppressive potential of EV-generated MDSC were dependent on the expression of Toll-like receptors (TLR). IMC from Tlr4(-/-) mice failed to increase T-cell PD-L1 expression and immunosuppression with Ret-EV treatment, and this effect was dependent on heat-shock protein 86 (HSP86) as HSP86-deficient Ret cells could not stimulate PD-L1 expression on normal IMC; IMC from Tlr2(-/-) and Tlr7(-/-) mice demonstrated similar results, although to a lesser extent. HSP86-deficient Ret cells slowed tumor progression in vivo associated with decreased frequency of tumor-infiltrating PD-L1(+) CD11b(+) Gr1(+) MDSC. EV from human melanoma cells upregulated PD-L1 and immunosuppression of normal monocytes dependent on HSP86. These findings highlight a novel EV-mediated mechanism of MDSC generation from normal myeloid cells, suggesting the importance of EV targeting for tumor therapy.Significance: These findings validate the importance of TLR4 signaling in reprogramming normal myeloid cells into functional myeloid-derived suppressor cells

    The role of adrenal venous sampling (AVS) in primary bilateral macronodular adrenocortical hyperplasia (PBMAH): a study of 16 patients

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    OBJECTIVE Primary bilateral macronodular adrenocortical hyperplasia (PBMAH) is a rare cause of ACTH-independent Cushing's syndrome. Current guidelines recommend bilateral adrenalectomy for PBMAH, but several studies showed clinical effectiveness of unilateral adrenalectomy despite bilateral disease in selected patients. Our aim was to evaluate the gain of information which can be obtained through adrenal venous sampling (AVS) based cortisol lateralization ratios for guidance of unilateral adrenalectomy. DESIGN We performed a retrospective analysis of 16 patients with PBMAH and clinical overt cortisol secretion in three centers METHODS: Selectivity of adrenal vein sampling during AVS was defined as a gradient of cortisol or a reference adrenal hormone ≥2.0 between adrenal and peripheral vein. Lateralization was assumed if the dominant to non-dominant ratio of cortisol to reference hormone was ≥4.0. RESULTS AVS was technically successful in all patients based on absolute cortisol levels and in 13 of 16 patients (81%) based on reference hormone levels. Lateralization was documented in 8 of 16 patients. In patients with lateralization, in 5 of 8 cases this occurred toward morphologically larger adrenals, while in 3 patients lateralization was present in bilaterally identical adrenals. The combined volume of adrenals correlated positively with urinary free cortisol, suggesting that adrenal size is the dominant determinant of cortisol secretion. CONCLUSIONS In this study the gain of information through AVS for unilateral adrenalectomy was limited in patients with PBMAH and marked adrenal asymmetry
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