Ming Zhou – författare

**Selected for 2026 Doody's Core Titles in Urology**Designed for quick reference and efficient, accurate sign-outs, Uropathology, 2nd Edition, provides superbly illustrated, expert guidance in a time-saving format. This updated volume in the High-Yield Pathology series is highly templated for ease of use, featuring bulleted text, authoritative content, and high-quality images that comprehensively cover both non-neoplastic and neoplastic entities, making it easy to recognize the classic manifestations of urologic diseases and quickly confirm your diagnoses.

With the advent of proteomics came the development of technologies, primarily mass spectrometry, which allowed high-throughput identification of proteins in complex mixtures.  While the mass spectrometer resides at the heart of proteomics, its ability to characterize biological samples is only as good as the sample preparation and data analysis tools used in any study.  In Proteomics for Biomarker Discovery, expert researchers in the field detail many of the methods which are now commonly used to study proteomics. These include methods and techniques include both label-free approaches and those that utilize stable isotopes incorporated both during cell growth or added via a chemical reaction once the proteome is extracted from the cell. Written in the highly successful Methods in Molecular Biology™ series format, chapters include introductions to their respective topics, lists of the necessary materials and reagents, step-by-step, readily reproducible laboratory protocols, and key tips on troubleshooting and avoiding known pitfalls.

Authoritative and practical, Proteomics for Biomarker Discovery seeks to aid scientists in the further study the different sample preparation and data analysis tools used in proteomics today.

This book retains the core contents of the successful first edition and covers all the practical issues related to prostate biopsy diagnosis in day-to-day practice. It uses abundant algorithms, flow charts, and tables to simulate a pathologist’s thought process and assist decision making during evaluation of prostate biopsies.  Chapters address the most effective ways to evaluate a prostate biopsy and how to formulate a diagnostic approach upon encountering a specific clinical problem. Pertinent new information is incorporated in all chapters, particularly in how novel diagnostic tools such as MRI and genomic tests may affect prostate biopsy practice and diagnosis. An entirely new chapter on pattern-based approaches to prostate biopsy interpretation has been added.

The second edition of Prostate Biopsy Interpretation: An Illustrated Guide is not meant to be an all-encompassing, definitive bibliography of pathology of prostate cancer. Instead, it provides practicingsurgical pathologists and trainees a quick and handy reference for all the practical issues relevant to day-to-day interpretation of prostate biopsy.

This book covers all the practical issues related to the interpretation of prostatic biopsies in day-to-day practice, including: biopsy sampling and processing; the diagnosis of limited cancer; differentiation of prostate cancers from benign lesions and recognition of histologic variants; the recognition and clinical significance of “atypical” diagnoses and HGPIN; the identification of recently described entities; the contemporary approach to Gleason grading; the utility of immunohistochemical markers and emerging molecular markers; and the reporting of prostate biopsies. Algorithms, flow charts, and tables are used throughout to simulate the thought and decision-making process upon encountering common clinical scenarios during sign-out of prostate biopsy. The book is richly illustrated with carefully selected, high-quality color images and will appeal especially to practicing surgical pathologists as well as pathology residents and fellows in training.

This book constitutes the refereed proceedings of the Second China Conference on Knowledge Graph and Semantic Computing, CCKS 2017, held in Chengdu, China, in August 2017.

The 11 revised full papers and 6 revised short papers presented were carefully reviewed and selected from 85 submissions. The papers cover wide research fields including the knowledge graph, the Semantic Web, linked data, NLP, knowledge representation, graph databases.