Ceramic component reliability with the restructured NASA/CARES computer program

The Ceramics Analysis and Reliability Evaluation of Structures (CARES) integrated design program on statistical fast fracture reliability and monolithic ceramic components is enhanced to include the use of a neutral data base, two-dimensional modeling, and variable problem size. The data base allows for the efficient transfer of element stresses, temperatures, and volumes/areas from the finite element output to the reliability analysis program. Elements are divided to insure a direct correspondence between the subelements and the Gaussian integration points. Two-dimensional modeling is accomplished by assessing the volume flaw reliability with shell elements. To demonstrate the improvements in the algorithm, example problems are selected from a round-robin conducted by WELFEP (WEakest Link failure probability prediction by Finite Element Postprocessors)

Reliability analysis of laminated CMC components through shell subelement techniques

An updated version of the integrated design program Composite Ceramics Analysis and Reliability Evaluation of Structures (C/CARES) was developed for the reliability evaluation of ceramic matrix composites (CMC) laminated shell components. The algorithm is now split into two modules: a finite-element data interface program and a reliability evaluation algorithm. More flexibility is achieved, allowing for easy implementation with various finite-element programs. The interface program creates a neutral data base which is then read by the reliability module. This neutral data base concept allows easy data transfer between different computer systems. The new interface program from the finite-element code Matrix Automated Reduction and Coupling (MARC) also includes the option of using hybrid laminates (a combination of plies of different materials or different layups) and allows for variations in temperature fields throughout the component. In the current version of C/CARES, a subelement technique was implemented, enabling stress gradients within an element to be taken into account. The noninteractive reliability function is now evaluated at each Gaussian integration point instead of using averaging techniques. As a result of the increased number of stress evaluation points, considerable improvements in the accuracy of reliability analyses were realized

DNA damage predicts prognosis and treatment response in colorectal liver metastases superior to immunogenic cell death and T cells

Preclinical models indicate that DNA damage induces type I interferon (IFN), which is crucial for the induction of an anti-tumor immune response. In human cancers, however, the association between DNA damage and an immunogenic cell death (ICD), including the release and sensing of danger signals, the subsequent ER stress response and a functional IFN system, is less clear. Methods: Neoadjuvant-treated colorectal liver metastases (CLM) patients, undergoing liver resection in with a curative intent, were retrospectively enrolled in this study (n=33). DNA damage (gammaH2AX), RNA and DNA sensors (RIG-I, DDX41, cGAS, STING), ER stress response (p-PKR, p-eIF2alpha, CALR), type I and type II IFN- induced proteins (MxA, GBP1), mature dendritic cells (CD208), and cytotoxic and memory T cells (CD3, CD8, CD45RO) were investigated by an immunohistochemistry whole-slide tissue scanning approach and further correlated with recurrence-free survival (RFS), overall survival (OS), radiographic and pathologic therapy response. Results: gammaH2AX is a negative prognostic marker for RFS (HR 1.32, 95% CI 1.04-1.69, p=0.023) and OS (HR 1.61, 95% CI 1.23-2.11, p<0.001). A model comprising of DDX41, STING and p-PKR predicts radiographic therapy response (AUC=0.785, p=0.002). gammaH2AX predicts prognosis superior to the prognostic value of CD8. CALR positively correlates with GBP1, CD8 and cGAS. A model consisting of gammaH2AX, p-eIF2alpha, DDX41, cGAS, CD208 and CD45RO predicts pathological therapy response (AUC=0.944, p<0.001). Conclusion: In contrast to preclinical models, DNA damage inversely correlated with ICD and its associated T cell infiltrate and potentially serves as a therapeutic target in CLM

An APRI+ALBI Based Multivariable Model as Preoperative Predictor for Posthepatectomy Liver Failure.

OBJECTIVE AND BACKGROUND Clinically significant posthepatectomy liver failure (PHLF B+C) remains the main cause of mortality after major hepatic resection. This study aimed to establish an APRI+ALBI, aspartate aminotransferase to platelet ratio (APRI) combined with albumin-bilirubin grade (ALBI), based multivariable model (MVM) to predict PHLF and compare its performance to indocyanine green clearance (ICG-R15 or ICG-PDR) and albumin-ICG evaluation (ALICE). METHODS 12,056 patients from the National Surgical Quality Improvement Program (NSQIP) database were used to generate a MVM to predict PHLF B+C. The model was determined using stepwise backwards elimination. Performance of the model was tested using receiver operating characteristic curve analysis and validated in an international cohort of 2,525 patients. In 620 patients, the APRI+ALBI MVM, trained in the NSQIP cohort, was compared with MVM's based on other liver function tests (ICG clearance, ALICE) by comparing the areas under the curve (AUC). RESULTS A MVM including APRI+ALBI, age, sex, tumor type and extent of resection was found to predict PHLF B+C with an AUC of 0.77, with comparable performance in the validation cohort (AUC 0.74). In direct comparison with other MVM's based on more expensive and time-consuming liver function tests (ICG clearance, ALICE), the APRI+ALBI MVM demonstrated equal predictive potential for PHLF B+C. A smartphone application for calculation of the APRI+ALBI MVM was designed. CONCLUSION Risk assessment via the APRI+ALBI MVM for PHLF B+C increases preoperative predictive accuracy and represents an universally available and cost-effective risk assessment prior to hepatectomy, facilitated by a freely available smartphone app

Delay-Induced Transient Increase and Heterogeneity in Gene Expression in Negatively Auto-Regulated Gene Circuits

A generic feature in all intracellular biochemical processes is the time required to complete the whole sequence of reactions to yield any observable quantity-from gene expression to circadian rhythms. This widespread phenomenon points towards the importance of time delay in biological functions. Theoretically time delay is known to be the source of instability, and has been attributed to lead to oscillations or transient dynamics in several biological functions. Negative feedback loops, common in biochemical pathways, have been shown to provide stability and withstand considerable variations and random perturbations of biochemical parameters. The interaction of these two opposing factors-of instability and homeostasis-are features that are widespread in intracellular processes. To test the effect of these divergent forces in the dynamics of gene expression, we have designed and constructed simple negatively auto-regulated gene circuits consisting of a basic regulator and transcriptional repressor module, and compared it with one, which has delayed repression. We show, both theoretically and experimentally, that delayed repression induces transient increase and heterogeneity in gene expression before the gain of stability effected by the negative feedback. This design, therefore, seems to be suitable for conferring both stability and variability in cells required for adaptive response to a noisy environment

ICAR: endoscopic skull‐base surgery

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