Molecular staging of gastric cancer with a novel panel of prognostic microRNAs.

2017 ◽  
Vol 35 (4_suppl) ◽  
pp. 52-52
Author(s):  
Yanghee Woo ◽  
Carolyn E. Behrendt ◽  
Yuman Fong

52 Background: Molecular heterogeneity of gastric cancer discerns patient survival in ways that clinically-based prediction models cannot. To date, individual microRNAs(miRs) expressed by gastric tumors have been associated with survival. We offer a unique molecular-based method of prognosticating the survival of gastric cancer patients with an efficient panel of miRs. Methods: From The Cancer Genome Atlas(TCGA), we studied subjects with gastric adenocarcinoma, who had undergone R0-R1 resection and had data on clinical characteristics, overall survival (OS), and miR expression. Of miRs quantified by TCGA, miRs expressed by at least 15% of subjects’ tumors were evaluated as continuous variables. From 10 replicate samples, each containing 80% of current subjects, miRs were selected using proportional hazards regression adjusted for age with stepwise selection. Cross-validated miRs were retained for the panel if they optimized an accelerated failure-time model of OS using the full cohort. Results: Among subjects (n=254, age 64.7+10.9 years), median OS was 2.38 (95% Confidence Interval: 2.09-3.85) years. Of the 913 evaluable miRs, 10 distinct miRs (miR-373, miR-548ay, miR-659, miR-891a, miR-1243, miR- 4685, miR-6718, miR-6733, miR-6808, and miR-8072) were cross-validated as being prognostic and retained for the age-adjusted panel. Panel-predicted survival estimates, grouped into tertiles, distinguished progressively worse survival at 2 years, OS was 81.0%+5.1% for upper tertile, 61.5%+6.3% for middle tertile, and 29.6%+6.3% for lower tertile. As shown in Table 1, each tertile included subjects at all levels of TNM stage, and tertile was not significantly associated with stage (chi-square test, p=0.26). Conclusions: This unique miRs panel represents a molecular staging system for gastric cancer that has the potential to prognosticate patients' survival more accurately than existing clinical systems can. [Table: see text]

Author(s):  
G. Vijayalakshmi

With the increasing demand for high availability in safety-critical systems such as banking systems, military systems, nuclear systems, aircraft systems to mention a few, reliability analysis of distributed software/hardware systems continue to be the focus of most researchers. The reliability analysis of a homogeneous distributed software/hardware system (HDSHS) with k-out-of-n : G configuration and no load-sharing nodes is analyzed. However, in practice the system load is shared among the working nodes in a distributed system. In this paper, the dependability analysis of a HDSHS with load-sharing nodes is presented. This distributed system has a load-sharing k-out-of-(n + m) : G configuration. A Markov model for HDSHS is developed. The failure time distribution of the hardware is represented by the accelerated failure time model. The software faults are detected during software testing and removed upon failure. The Jelinski–Moranda software reliability model is used. The maintenance personal can repair the system up on both software and hardware failure. The dependability measures such as reliability, availability and mean time to failure are obtained. The effect of load-sharing hosts on system hazard function and system reliability is presented. Furthermore, an availability comparison of our results and the results in the literature is presented.


2020 ◽  
Vol 43 (12) ◽  
Author(s):  
Satya Narayan Panda ◽  
Arun Kumar Gopalaswamy

Purpose Staged financing is a prominent feature of the venture capital investment process. With staged financing, venture capitalists (VCs) may choose to either make an investment or delay it at each round. The purpose of this paper is to investigate the influence of market uncertainty, project-specific uncertainty and agency problems on these decisions. Design/methodology/approach The study uses data from Indian firms that received venture capital funding between 2000 and 2017. The duration between funding rounds is analysed using survival analysis. An accelerated failure time model is used to estimate the influence of market uncertainty, project-specific uncertainty and agency problems on the length of time between funding rounds. Findings VCs delay investment when there are high levels of uncertainty in the market; if market uncertainty increases by 1%, delay in funding increases by more than 6% (almost a month) on average. There is no statistically significant relationship found between the funding duration and project-specific uncertainty. Agency problems motivate VCs to invest sooner. An increase in agency problems results in a reduction of 55% (almost five months) in the length of time before the next funding round. Practical implications This study has useful business policy implications. It provides VCs with real option value drivers such as market uncertainty, agency problems, which influence the timing of decisions in staged investment processes. It will help to make the choice between investing and delaying at each round of financing more robust. Further, it is useful for VCs to differentiate between market uncertainty and agency problems against the backdrop of their different implications for staging decisions. Originality/value Few studies have examined staging decisions from a real options perspective in the context of a developed economy and very few from a developing economy perspective. This study increases understanding of staging decisions in the Indian context.


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