A standardized pathology report for gastric cancer: 2nd edition

The first edition of ‘A Standardized Pathology Report for Gastric Cancer’ was initiated by the Gastrointestinal Pathology Study Group of the Korean Society of Pathologists and published 17 years ago. Since then, significant advances have been made in the pathologic diagnosis, molecular genetics, and management of gastric cancer (GC). To reflect those changes, a committee for publishing a second edition of the report was formed within the Gastrointestinal Pathology Study Group of the Korean Society of Pathologists. This second edition consists of two parts: standard data elements and conditional data elements. The standard data elements contain the basic pathologic findings and items necessary to predict the prognosis of GC patients, and they are adequate for routine surgical pathology service. Other diagnostic and prognostic factors relevant to adjuvant therapy, including molecular biomarkers, are classified as conditional data elements to allow each pathologist to selectively choose items appropriate to the environment in their institution. We trust that the standardized pathology report will be helpful for GC diagnosis and facilitate large-scale multidisciplinary collaborative studies

Stochastic learning with Back Propagation

Despite of remarkable progress on deep learning, its hardware implementation beyond deep learning acceleration is still behind the software deep learning due in part to lack of hardware-compatible learning algorithm. In this paper, a learning method called the stochastic learning with backpropagation (SLBP) algorithm was proposed. The network of concern consists of ternary synaptic weight, favorable to be implemented in a resistance-based crossbar array. Every training epoch, the SLBP algorithm evaluates weight update probability at which the corresponding weight is updated in a stochastic manner. The algorithm was used to train a denoising autoencoder, which identified the successful reduction in noise (increase in peak signal-to-noise ratio by approximately 68%). Notably, the SLBP algorithm achieves an 86% reduction in memory usage compared with a real-valued autoencoder trained using a backpropagation algorithm.N

Artificial Neural Network for Response Inference of a Nonvolatile Resistance-Switch Array

An artificial neural network was utilized in the behavior inference of a random crossbar array (10 × 9 or 28 × 27 in size) of nonvolatile binary resistance-switches (in a high resistance state (HRS) or low resistance state (LRS)) in response to a randomly applied voltage array. The employed artificial neural network was a multilayer perceptron (MLP) with leaky rectified linear units. This MLP was trained with 500,000 or 1,000,000 examples. For each example, an input vector consisted of the distribution of resistance states (HRS or LRS) over a crossbar array plus an applied voltage array. That is, for a M × N array where voltages are applied to its M rows, the input vector was M × (N + 1) long. The calculated (correct) current array for each random crossbar array was used as data labels for supervised learning. This attempt was successful such that the correlation coefficient between inferred and correct currents reached 0.9995 for the larger crossbar array. This result highlights MLP that leverages its versatility to capture the quantitative linkage between input and output across the highly nonlinear crossbar array

Diagnostic and Prognostic Roles of CDX2 Immunohistochemical Expression in Colorectal Cancers

The study is aimed to evaluate the diagnostic and prognostic role of the immunohistochemical expression of the Caudal-type homeobox transcription factor 2 (CDX2) in colorectal cancers (CRCs) through a meta-analysis. By searching relevant databases, 38 articles were eligible to be included in this study. We extracted the information for CDX2 expression rates and the correlation between CDX2 expression and clinicopathological characteristics. The estimated rates of CDX2 expression were 0.882 [95% confidence interval (CI) 0.774–0.861] and 0.893 (95% CI 0.820–0.938) in primary and metastatic CRCs, respectively. Furthermore, based on their histologic subtype, CDX2 expression rates of adenocarcinoma and medullary carcinoma were 0.886 (95% CI 0.837–0.923) and 0.436 (95% CI 0.269–0.618), respectively. There was a significant difference in CDX2 expression rates between adenocarcinoma and medullary carcinoma in the meta-regression test (p V600E mutation than in CRCs without mutation. Patients with CDX2 expression had better overall and cancer-specific survival rates than those without CDX2 expression. Thus, CDX2 is a useful diagnostic and prognostic marker CRCs

Clinicopathological Significances and Prognostic Role of Intratumoral Budding in Colorectal Cancers

Background: This study aims to evaluate the clinicopathological significance and prognostic implications of intratumoral budding (ITB) in colorectal cancers (CRCs) through a meta-analysis. Methods: We performed the meta-analysis using 13 eligible studies and investigated the rates of CRCs with high ITB. The correlation between ITB and clinicopathological characteristics, including disease-free survival, was evaluated. Results: The estimated rate of CRCs with high ITB was 0.233 (95% confidence interval (CI) 0.177–0.299) in overall CRCs. High ITB was significantly correlated with tumor grade, lymphatic invasion, perineural invasion, pT stage, and lymph node metastasis. In addition, ITBs were more frequently found in medullary and signet-ring cell carcinomas than in conventional adenocarcinomas and mucinous carcinomas. However, the high ITB rate was not correlated with tumor border, tumor-infiltrating lymphocytes, or microsatellite instability. CRCs with a good response after neoadjuvant therapy revealed a lower rate of high ITB than those with a poor response (hazard ratio (HR) 0.114, 95% CI 0.070–0.179 vs. 0.321, 95% CI 0.204–0.467). In addition, CRCs with high ITB had a worse disease-free survival than those with low ITB (HR 1.426, 95% CI 1.092–1.863). Conclusions: The ITB was significantly correlated with aggressive tumor behaviors and a worse prognosis in CRCs. The detection of ITB, as a histological parameter, can be useful for predicting clinicopathologic features and the prognosis of CRC

Synthesis, characterization, and thin-film transistor response of Benzo[i]pentahelicene-3,6-dione

Organic semiconductors hold the promise of simple, large area solution deposition, low thermal budgets as well as compatibility with flexible substrates, thus emerging as viable alternatives for cost-effective (opto)-electronic devices. In this study, we report the optimized synthesis and characterization of a helically shaped polycyclic aromatic compound, namely benzopentahelicene-3,6-dione, and explored its use in the fabrication of organic field effect transistors. In addition, we investigated its thermal, optical absorption, and electrochemical properties. Finally, the single crystal X-ray characterization is reported