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https://www.readbyqxmd.com/read/29679721/effectiveness-evaluation-of-digital-virtual-simulation-application-in-teaching-of-gross-anatomy
#1
Xiaohua Deng, Guowei Zhou, Bing Xiao, Zirui Zhao, Yicheng He, Chujun Chen
INTRODUCTION: digital virtual simulation (DVS) is increasingly used to supplement the teaching of anatomy. DVS can provide the students with three-dimensional (3D) stereoscopic images and precise structures in anatomy teaching. We investigated the effects of digital virtual simulation (DVS) application in gross anatomy teaching. MATERIALS AND METHODS: fourth-year medical students (n=120), majoring clinical medicine in 2013 grade from Xiangya School of Medicine, Central South University, were assigned into four classes...
April 18, 2018: Annals of Anatomy, Anatomischer Anzeiger: Official Organ of the Anatomische Gesellschaft
https://www.readbyqxmd.com/read/29678043/an-automated-technique-to-construct-a-knowledge-base-of-traditional-chinese-herbal-medicine-for-cancers-an-exploratory-study-for-breast-cancer
#2
Phung Anh Nguyen, Hsuan-Chia Yang, Rong Xu, Yu-Chuan Jack Li
Traditional Chinese Medicine utilization has rapidly increased worldwide. However, there is limited database provides the information of TCM herbs and diseases. The study aims to identify and evaluate the meaningful associations between TCM herbs and breast cancer by using the association rule mining (ARM) techniques. We employed the ARM techniques for 19.9 million TCM prescriptions by using Taiwan National Health Insurance claim database from 1999 to 2013. 364 TCM herbs-breast cancer associations were derived from those prescriptions and were then filtered by their support of 20...
2018: Studies in Health Technology and Informatics
https://www.readbyqxmd.com/read/29669699/a-systems-approach-to-refine-disease-taxonomy-by-integrating-phenotypic-and-molecular-networks
#3
Xuezhong Zhou, Lei Lei, Jun Liu, Arda Halu, Yingying Zhang, Bing Li, Zhili Guo, Guangming Liu, Changkai Sun, Joseph Loscalzo, Amitabh Sharma, Zhong Wang
The International Classification of Diseases (ICD) relies on clinical features and lags behind the current understanding of the molecular specificity of disease pathobiology, necessitating approaches that incorporate growing biomedical data for classifying diseases to meet the needs of precision medicine. Our analysis revealed that the heterogeneous molecular diversity of disease chapters and the blurred boundary between disease categories in ICD should be further investigated. Here, we propose a new classification of diseases (NCD) by developing an algorithm that predicts the additional categories of a disease by integrating multiple networks consisting of disease phenotypes and their molecular profiles...
April 6, 2018: EBioMedicine
https://www.readbyqxmd.com/read/29665274/combining-multiplex-sers-nanovectors-and-multivariate-analysis-for-in-situ-profiling-of-circulating-tumor-cell-phenotype-using-a-microfluidic-chip
#4
Yizhi Zhang, Zhuyuan Wang, Lei Wu, Shenfei Zong, Binfeng Yun, Yiping Cui
Isolating and in situ profiling the heterogeneous molecular phenotype of circulating tumor cells are of great significance for clinical cancer diagnosis and personalized therapy. Herein, an on-chip strategy is proposed that combines size-based microfluidic cell isolation with multiple spectrally orthogonal surface-enhanced Raman spectroscopy (SERS) analysis for in situ profiling of cell membrane proteins and identification of cancer subpopulations. With the developed microfluidic chip, tumor cells are sieved from blood on the basis of size discrepancy...
April 17, 2018: Small
https://www.readbyqxmd.com/read/29645007/statistical-methods-for-clinical-trial-designs-in-the-new-era-of-cancer-treatment
#5
Beibei Guo, Rui Zhang
Recent success of immunotherapy and other targeted therapies in cancer treatment has signaled the advent of precision medicine. Unlike conventional trial designs that aim to find an optimal treatment ignoring inter-patient heterogeneity, clinical trial designs for precision medicine must take into account patients' variability in genes, environments, and lifestyle. This article provides a review of recent research development of clinical trial designs toward this trend.
February 2018: Biostatistics and biometrics open access journal
https://www.readbyqxmd.com/read/29643545/-necessity-and-feasibility-of-data-sharing-of-cohort-studies
#6
Y Yang, H Y Zhao, S Y Zhan
Cohort study is one of the important epidemiological methods which plays an irreplaceable status and role in etiological study. Using cohort study design, we can accurately and continuously collect genetic and environmental information, and identify and validate omics biomarkers to provide evidences for precision public health and medicine. However, results from a new cohort would not be available for at least ten years, as five years would be needed for funding, planning and enrolment, and another five for following up even the earliest analyses of the most common diseases; results for most cancers would take longer, with an unaffordable budget for many research investigators or institutions...
April 18, 2018: Beijing da Xue Xue Bao. Yi Xue Ban, Journal of Peking University. Health Sciences
https://www.readbyqxmd.com/read/29628841/appearance-of-population-intervention-comparison-and-outcome-as-research-question-in-the-title-of-articles-of-three-different-anesthesia-journals-a-pilot-study
#7
Abdelazeem Eldawlatly, Hussain Alshehri, Abdullah Alqahtani, Abdulaziz Ahmad, Fatma Al-Dammas, Amir Marzouk
Background: It is well known in the evidence-based medicine practice that framing the research question is the most important and crucial part of the research integrity. Population, Intervention, Comparison, and Outcome (PICO) is a specialized framework used by most researchers to formulate a research question and to facilitate literature review. The aim of this study is to investigate the representation of the PICO frame in the title of published articles in three different anesthesia journals...
April 2018: Saudi Journal of Anaesthesia
https://www.readbyqxmd.com/read/29621323/performance-comparison-of-three-dna-extraction-kits-on-human-whole-exome-data-from-formalin-fixed-paraffin-embedded-normal-and-tumor-samples
#8
Eric Bonnet, Marie-Laure Moutet, Céline Baulard, Delphine Bacq-Daian, Florian Sandron, Lilia Mesrob, Bertrand Fin, Marc Delépine, Marie-Ange Palomares, Claire Jubin, Hélène Blanché, Vincent Meyer, Anne Boland, Robert Olaso, Jean-François Deleuze
Next-generation sequencing (NGS) studies are becoming routinely used for the detection of novel and clinically actionable DNA variants at a pangenomic scale. Such analyses are now used in the clinical practice to enable precision medicine. Formalin-fixed paraffin-embedded (FFPE) tissues are still one of the most abundant source of cancer clinical specimen, unfortunately this method of preparation is known to degrade DNA and therefore compromise subsequent analysis. Some studies have reported that variant detection can be performed on FFPE samples sequenced with NGS techniques, but few or none have done an in-depth coverage analysis and compared the influence of different state-of-the-art FFPE DNA extraction kits on the quality of the variant calling...
2018: PloS One
https://www.readbyqxmd.com/read/29610393/journey-from-oncologist-to-cancer-survivor-and-patient-advocate-in-the-era-of-precision-medicine
#9
Burton M Needles
In 2013, the American Association for Cancer Research (AACR) introduced the "Precision Medicine Series" of symposia. The goal of these conferences is to "highlight the incredible technology and advances in cancer research that together are enabling treatments that are precisely targeted to the unique molecular and genetic characteristics of an individual's cancer." This new series of AACR conferences reflects how patient treatment has evolved and continues to progress toward personalized treatments/medicine...
April 2018: Cold Spring Harbor Molecular Case Studies
https://www.readbyqxmd.com/read/29605454/how-to-integrate-quantitative-information-into-imaging-reports-for-oncologic-patients
#10
L Martí-Bonmatí, E Ruiz-Martínez, A Ten, A Alberich-Bayarri
Nowadays, the images and information generated in imaging tests, as well as the reports that are issued, are digital and represent a reliable source of data. Reports can be classified according to their content and to the type of information they include into three main types: organized (free text in natural language), predefined (with templates and guidelines elaborated with previously determined natural language like that used in BI-RADS and PI-RADS), or structured (with drop-down menus displaying questions with various possible answers that have been agreed on with the rest of the multidisciplinary team, which use standardized lexicons and are structured in the form of a database with data that can be traced and exploited with statistical tools and data mining)...
March 28, 2018: Radiología
https://www.readbyqxmd.com/read/29581134/data-analysis-strategies-in-medical-imaging
#11
Chintan Parmar, Joseph D Barry, Ahmed Hosny, John Quackenbush, Hugo Jwl Aerts
Radiographic imaging continues to be one of the most effective and clinically useful tools within oncology. Sophistication of artificial intelligence (AI) has allowed for detailed quantification of radiographic characteristics of tissues using predefined engineered algorithms or deep learning methods. Precedents in radiology as well as a wealth of research studies hint at the clinical relevance of these characteristics. However, there are critical challenges associated with the analysis of medical imaging data...
March 26, 2018: Clinical Cancer Research: An Official Journal of the American Association for Cancer Research
https://www.readbyqxmd.com/read/29575056/subgroup-analysis-with-semiparametric-models-toward-precision-medicine
#12
Ao Yuan, Xiaofei Chen, Yizhao Zhou, Ming T Tan
In analyzing clinical trials, one important objective is to classify the patients into treatment-favorable and nonfavorable subgroups. Existing parametric methods are not robust, and the commonly used classification rules ignore the fact that the implications of treatment-favorable and nonfavorable subgroups can be different. To address these issues, we propose a semiparametric model, incorporating both our knowledge and uncertainty about the true model. The Wald statistics is used to test the existence of subgroups, while the Neyman-Pearson rule to classify each subject...
March 25, 2018: Statistics in Medicine
https://www.readbyqxmd.com/read/29562524/revolution-of-alzheimer-precision-neurology-passageway-of-systems-biology-and-neurophysiology
#13
Harald Hampel, Nicola Toschi, Claudio Babiloni, Filippo Baldacci, Keith L Black, Arun L W Bokde, René S Bun, Francesco Cacciola, Enrica Cavedo, Patrizia A Chiesa, Olivier Colliot, Cristina-Maria Coman, Bruno Dubois, Andrea Duggento, Stanley Durrleman, Maria-Teresa Ferretti, Nathalie George, Remy Genthon, Marie-Odile Habert, Karl Herholz, Yosef Koronyo, Maya Koronyo-Hamaoui, Foudil Lamari, Todd Langevin, Stéphane Lehéricy, Jean Lorenceau, Christian Neri, Robert Nisticò, Francis Nyasse-Messene, Craig Ritchie, Simone Rossi, Emiliano Santarnecchi, Olaf Sporns, Steven R Verdooner, Andrea Vergallo, Nicolas Villain, Erfan Younesi, Francesco Garaci, Simone Lista
The Precision Neurology development process implements systems theory with system biology and neurophysiology in a parallel, bidirectional research path: a combined hypothesis-driven investigation of systems dysfunction within distinct molecular, cellular, and large-scale neural network systems in both animal models as well as through tests for the usefulness of these candidate dynamic systems biomarkers in different diseases and subgroups at different stages of pathophysiological progression. This translational research path is paralleled by an "omics"-based, hypothesis-free, exploratory research pathway, which will collect multimodal data from progressing asymptomatic, preclinical, and clinical neurodegenerative disease (ND) populations, within the wide continuous biological and clinical spectrum of ND, applying high-throughput and high-content technologies combined with powerful computational and statistical modeling tools, aimed at identifying novel dysfunctional systems and predictive marker signatures associated with ND...
March 16, 2018: Journal of Alzheimer's Disease: JAD
https://www.readbyqxmd.com/read/29547989/pupillometer-use-validation-for-use-in-military-and-occupational-medical-surveillance-and-response-to-organophosphate-and-chemical-warfare-agent-exposure
#14
Luke Mease, Reema Sikka, Randall Rhees
Introduction: To analyze the effectiveness and suitability of pupillometer use in military and occupational medicine, specifically when pupil size is measured as part of medical surveillance. Pupil size is the most sensitive physical exam finding in vapor exposure to substances that inhibit acetylcholinesterase, such as nerve agent (chemical warfare) and organophosphates (used in agriculture). Pupillometer use permits real-time, accurate pupil measurements, which are of significant value in occupational setting where exposure to organophosphates is suspected and in dynamic military settings where it may be unclear if service members were exposed to nerve agent or not...
March 14, 2018: Military Medicine
https://www.readbyqxmd.com/read/29547950/a-new-method-for-the-high-precision-assessment-of-tumor-changes-in-response-to-treatment
#15
P D Tar, N A Thacker, M Babur, Y Watson, S Cheung, R A Little, R G Gieling, K J Williams, J P B O'Connor
Motivation: Imaging demonstrates that preclinical and human tumors are heterogeneous, i.e. a single tumor can exhibit multiple regions that behave differently during both normal development and also in response to treatment. The large variations observed in control group tumors can obscure detection of significant therapeutic effects due to the ambiguity in attributing causes of change. This can hinder development of effective therapies due to limitations in experimental design, rather than due to therapeutic failure...
March 14, 2018: Bioinformatics
https://www.readbyqxmd.com/read/29545900/investigating-a-multigene-prognostic-assay-based-on-significant-pathways-for-luminal-a-breast-cancer-through-gene-expression-profile-analysis
#16
Haiyan Gao, Mei Yang, Xiaolan Zhang
The present study aimed to investigate potential recurrence-risk biomarkers based on significant pathways for Luminal A breast cancer through gene expression profile analysis. Initially, the gene expression profiles of Luminal A breast cancer patients were downloaded from The Cancer Genome Atlas database. The differentially expressed genes (DEGs) were identified using a Limma package and the hierarchical clustering analysis was conducted for the DEGs. In addition, the functional pathways were screened using Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses and rank ratio calculation...
April 2018: Oncology Letters
https://www.readbyqxmd.com/read/29537985/unsupervised-analysis-of-transcriptomics-in-bacterial-sepsis-across-multiple-datasets-reveals-three-robust-clusters
#17
Timothy E Sweeney, Tej D Azad, Michele Donato, Winston A Haynes, Thanneer M Perumal, Ricardo Henao, Jesús F Bermejo-Martin, Raquel Almansa, Eduardo Tamayo, Judith A Howrylak, Augustine Choi, Grant P Parnell, Benjamin Tang, Marshall Nichols, Christopher W Woods, Geoffrey S Ginsburg, Stephen F Kingsmore, Larsson Omberg, Lara M Mangravite, Hector R Wong, Ephraim L Tsalik, Raymond J Langley, Purvesh Khatri
OBJECTIVES: To find and validate generalizable sepsis subtypes using data-driven clustering. DESIGN: We used advanced informatics techniques to pool data from 14 bacterial sepsis transcriptomic datasets from eight different countries (n = 700). SETTING: Retrospective analysis. SUBJECTS: Persons admitted to the hospital with bacterial sepsis. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: A unified clustering analysis across 14 discovery datasets revealed three subtypes, which, based on functional analysis, we termed "Inflammopathic, Adaptive, and Coagulopathic...
March 13, 2018: Critical Care Medicine
https://www.readbyqxmd.com/read/29534296/estimating-individualized-treatment-rules-for-ordinal-treatments
#18
Jingxiang Chen, Haoda Fu, Xuanyao He, Michael R Kosorok, Yufeng Liu
Precision medicine is an emerging scientific topic for disease treatment and prevention that takes into account individual patient characteristics. It is an important direction for clinical research, and many statistical methods have been proposed recently. One of the primary goals of precision medicine is to obtain an optimal individual treatment rule (ITR), which can help make decisions on treatment selection according to each patient's specific characteristics. Recently, outcome weighted learning (OWL) has been proposed to estimate such an optimal ITR in a binary treatment setting by maximizing the expected clinical outcome...
March 13, 2018: Biometrics
https://www.readbyqxmd.com/read/29531073/predicting-cancer-outcomes-from-histology-and-genomics-using-convolutional-networks
#19
Pooya Mobadersany, Safoora Yousefi, Mohamed Amgad, David A Gutman, Jill S Barnholtz-Sloan, José E Velázquez Vega, Daniel J Brat, Lee A D Cooper
Cancer histology reflects underlying molecular processes and disease progression and contains rich phenotypic information that is predictive of patient outcomes. In this study, we show a computational approach for learning patient outcomes from digital pathology images using deep learning to combine the power of adaptive machine learning algorithms with traditional survival models. We illustrate how these survival convolutional neural networks (SCNNs) can integrate information from both histology images and genomic biomarkers into a single unified framework to predict time-to-event outcomes and show prediction accuracy that surpasses the current clinical paradigm for predicting the overall survival of patients diagnosed with glioma...
March 12, 2018: Proceedings of the National Academy of Sciences of the United States of America
https://www.readbyqxmd.com/read/29523131/traditional-chinese-medicine-pharmacovigilance-in-signal-detection-decision-tree-based-data-classification
#20
Jian-Xiang Wei, Jing Wang, Yun-Xia Zhu, Jun Sun, Hou-Ming Xu, Ming Li
BACKGROUND: Traditional Chinese Medicine (TCM) is a style of traditional medicine informed by modern medicine but built on a foundation of more than 2500 years of Chinese medical practice. According to statistics, TCM accounts for approximately 14% of total adverse drug reaction (ADR) spontaneous reporting data in China. Because of the complexity of the components in TCM formula, which makes it essentially different from Western medicine, it is critical to determine whether ADR reports of TCM should be analyzed independently...
March 9, 2018: BMC Medical Informatics and Decision Making
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