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Author: Yongxia Zhou
Publisher: Nova Medicine & Health
ISBN: 9781536190861
Category : Medical
Languages : en
Pages : 251
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Book Description
The well-known Alzheimer's Disease Neuroimaging Initiative (ADNI) Center provides the most advanced, comprehensive, multiparametric and up-to-date biomarkers for mild cognitive impairment (MCI) and early Alzheimer's disease (AD) projects, including neuroimaging, clinical assessments, biospecimens and genetic data. Recent developments in imaging techniques, including new molecular tracers for imaging disease burden and systematic multi-modal integration, have emerged to overcome the limitations of each single modality and individual-dependent variability. The MRI-based high-resolution structural and morphological changes in the brain, such as atrophy, and the abnormal activity/connectivity patterns of the hippocampus subfields and default mode network (DMN) modulation, together with the amyloid and tau neuropathological quantification using PET molecular tracers, could be used to predict brain changes and cognitive performance declines in early AD, including transitional MCI. Finally, a generalized and integrative model with multiple biomarkers could be built to target disease progression and symptom prediction as well as to optimize patient management.Multiomics investigates metabolomic, lipidomic, genomic, transcriptomic and proteomic perspectives by presenting an accurate biochemical profile of the organism in health and disease. The Alzheimer's Disease Metabolomics Consortium (ADMC) in partnership with ADNI is creating a comprehensive biochemical database for patients in the ADNI1 cohort, consisting of eight metabolomics datasets. The vast majorities of biospecimen data provide rich biological information to the human brain at normal and dementia status. One of the purposes is to reveal the connections between disease and multiomics such as obesity, hypertension, cholesterol imbalance and inflammation risks that might lead to neurodegenerative disease. Multiomic biomarker developments in the dementia field have provided earlier clues to novel treatments that help correct metabolic dysfunction and delay disease progression. Furthermore, the assembling of multiomics-based biomarkers including metabolites and lipids, cholesterol biosynthesis, purine metabolism, lipoprotein, bile acids, and genetics as well as their relation to the pathological amyloid and tau network could improve disease diagnosis sensitivity and reveal more diverse and complementary molecular pathways to allow for the advancement of early AD diagnosis and therapeutic prevention. In this book, we report on the significant differences of multiple biomarkers from the ADNI database including neuroimaging, clinical assessments and multiomic biospecimen/genetic data in MCI and early probable AD (pAD), and elucidate the interconnections among different metrics at various domains. Classification results with high accuracies (0.95-1) for each early dementia subtype including early MCI (EMCI), late MCI (LMCI) and pAD, and better prediction of clinical symptoms is achieved with these comprehensive biomarkers. Further longitudinal changes of imaging and neuropsychological biomarkers, and inter-correlations with baseline parameters are examined for a better illustration of disease progression association. Additionally, an analysis of the post-traumatic stress disorder biomarkers is performed with high classification accuracy. With illustrative and rigorous data analyses and confirmative results, this book provides readers with a full spectrum of biomarker research for early dementia diagnosis and treatment, and helps convey the technical development and data evaluation perspectives in advanced medical imaging and various disease application fields.
Author: Yongxia Zhou
Publisher: Nova Medicine & Health
ISBN: 9781536190861
Category : Medical
Languages : en
Pages : 251
Get Book Here
Book Description
The well-known Alzheimer's Disease Neuroimaging Initiative (ADNI) Center provides the most advanced, comprehensive, multiparametric and up-to-date biomarkers for mild cognitive impairment (MCI) and early Alzheimer's disease (AD) projects, including neuroimaging, clinical assessments, biospecimens and genetic data. Recent developments in imaging techniques, including new molecular tracers for imaging disease burden and systematic multi-modal integration, have emerged to overcome the limitations of each single modality and individual-dependent variability. The MRI-based high-resolution structural and morphological changes in the brain, such as atrophy, and the abnormal activity/connectivity patterns of the hippocampus subfields and default mode network (DMN) modulation, together with the amyloid and tau neuropathological quantification using PET molecular tracers, could be used to predict brain changes and cognitive performance declines in early AD, including transitional MCI. Finally, a generalized and integrative model with multiple biomarkers could be built to target disease progression and symptom prediction as well as to optimize patient management.Multiomics investigates metabolomic, lipidomic, genomic, transcriptomic and proteomic perspectives by presenting an accurate biochemical profile of the organism in health and disease. The Alzheimer's Disease Metabolomics Consortium (ADMC) in partnership with ADNI is creating a comprehensive biochemical database for patients in the ADNI1 cohort, consisting of eight metabolomics datasets. The vast majorities of biospecimen data provide rich biological information to the human brain at normal and dementia status. One of the purposes is to reveal the connections between disease and multiomics such as obesity, hypertension, cholesterol imbalance and inflammation risks that might lead to neurodegenerative disease. Multiomic biomarker developments in the dementia field have provided earlier clues to novel treatments that help correct metabolic dysfunction and delay disease progression. Furthermore, the assembling of multiomics-based biomarkers including metabolites and lipids, cholesterol biosynthesis, purine metabolism, lipoprotein, bile acids, and genetics as well as their relation to the pathological amyloid and tau network could improve disease diagnosis sensitivity and reveal more diverse and complementary molecular pathways to allow for the advancement of early AD diagnosis and therapeutic prevention. In this book, we report on the significant differences of multiple biomarkers from the ADNI database including neuroimaging, clinical assessments and multiomic biospecimen/genetic data in MCI and early probable AD (pAD), and elucidate the interconnections among different metrics at various domains. Classification results with high accuracies (0.95-1) for each early dementia subtype including early MCI (EMCI), late MCI (LMCI) and pAD, and better prediction of clinical symptoms is achieved with these comprehensive biomarkers. Further longitudinal changes of imaging and neuropsychological biomarkers, and inter-correlations with baseline parameters are examined for a better illustration of disease progression association. Additionally, an analysis of the post-traumatic stress disorder biomarkers is performed with high classification accuracy. With illustrative and rigorous data analyses and confirmative results, this book provides readers with a full spectrum of biomarker research for early dementia diagnosis and treatment, and helps convey the technical development and data evaluation perspectives in advanced medical imaging and various disease application fields.
Author: Luis Martí-Bonmatí
Publisher: Springer
ISBN: 3319435043
Category : Medical
Languages : en
Pages : 313
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Book Description
This is the first book to cover all aspects of the development of imaging biomarkers and their integration into clinical practice, from the conceptual basis through to the technical aspects that need to be considered in order to ensure that medical imaging can serve as a powerful quantification instrument capable of providing valuable information on organ and tissue properties. The process of imaging biomarker development is considered step by step, covering proof of concept, proof of mechanism, image acquisition, image preparation, imaging biomarker analysis and measurement, detection of measurement biases (proof of principle), proof of efficacy and effectiveness, and reporting of results. Sources of uncertainty in the accuracy and precision of measurements and pearls and pitfalls in gold standards and biological correlation are discussed. In addition, practical use cases are included on imaging biomarker implementation in brain, oncologic, cardiovascular, musculoskeletal, and abdominal diseases. The authors are a multidisciplinary team of expert radiologists and engineers, and the book will be of value to all with an interest in the quantitative imaging of biomarkers in personalized medicine.
Author: Fengfeng Zhou
Publisher: Frontiers Media SA
ISBN: 2889765709
Category : Science
Languages : en
Pages : 246
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Book Description
Author: Yongxia Zhou
Publisher: Ethics International Press
ISBN: 1804411043
Category : Science
Languages : en
Pages : 255
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Book Description
This book demonstrates the beneficial effects in brain circuits involving memory and attention, reward and social values, decision making and coordination, creativity and persistence of the skills and expertise of continuing education and exposure to the Arts; including chess practice, music/counting, college education and watching movies. These activities were reviewed and investigated using full-spectrum, advanced quantitative imaging techniques. The book highlights extensive applications for this research in common diseases, together with cutting-edge and full-spectrum static and dynamic, functional and structural, regional and inter-network, imaging and phenotypic scales. It will capture the interest of researchers in the areas of neurodevelopmental, neuroplasticity and neuropsychiatric imaging and correlation, as well as disease diagnosis and treatment, and could help convey the methodological innovation and neuroscientific applications of important educational, health and arts/science-related topics.
Author: Institute of Medicine
Publisher: National Academies Press
ISBN: 0309157277
Category : Medical
Languages : en
Pages : 335
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Book Description
Many people naturally assume that the claims made for foods and nutritional supplements have the same degree of scientific grounding as those for medication, but that is not always the case. The IOM recommends that the FDA adopt a consistent scientific framework for biomarker evaluation in order to achieve a rigorous and transparent process.
Author: Ali Samadikuchaksaraei
Publisher: BoD – Books on Demand
ISBN: 1789237998
Category : Medical
Languages : en
Pages : 102
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Book Description
Genomic variations and phenotypic diversity are closely linked and form the underlying mechanism for development of many human diseases. This book addresses the methods of detection, analysis, and interpretation of genomic variations in clinically relevant scenarios. If your research or clinical practice involves handling of genomic sequencing data, this book is for you. Topics covered include: methods for identifying genetic diversity, the workflow for analyzing whole exome and whole genome sequencing data, local ancestry deconvolution models, the value of molecular patterns and pattern biomarkers in cancer diagnosis and prognosis, and genotyping and profiling resistance-associated variants of hepatitis C. If your research or clinical practice involves handling of genomic sequencing data, this book is for you.
Author: Paolo Tieri
Publisher: Frontiers Media SA
ISBN: 2889196488
Category : Science (General)
Languages : en
Pages : 137
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Book Description
Stable, predictive biomarkers and interpretable disease signatures are seen as a significant step towards personalized medicine. In this perspective, integration of multi-omic data coming from genomics, transcriptomics, glycomics, proteomics, metabolomics is a powerful strategy to reconstruct and analyse complex multi-dimensional interactions, enabling deeper mechanistic and medical insight. At the same time, there is a rising concern that much of such different omic data –although often publicly and freely available- lie in databases and repositories underutilised or not used at all. Issues coming from lack of standardisation and shared biological identities are also well-known. From these considerations, a novel, pressing request arises from the life sciences to design methodologies and approaches that allow for these data to be interpreted as a whole, i.e. as intertwined molecular signatures containing genes, proteins, mRNAs and miRNAs, able to capture inter-layers connections and complexity. Papers discuss data integration approaches and methods of several types and extents, their application in understanding the pathogenesis of specific diseases or in identifying candidate biomarkers to exploit the full benefit of multi-omic datasets and their intrinsic information content. Topics of interest include, but are not limited to: • Methods for the integration of layered data, including, but not limited to, genomics, transcriptomics, glycomics, proteomics, metabolomics; • Application of multi-omic data integration approaches for diagnostic biomarker discovery in any field of the life sciences; • Innovative approaches for the analysis and the visualization of multi-omic datasets; • Methods and applications for systematic measurements from single/undivided samples (comprising genomic, transcriptomic, proteomic, metabolomic measurements, among others); • Multi-scale approaches for integrated dynamic modelling and simulation; • Implementation of applications, computational resources and repositories devoted to data integration including, but not limited to, data warehousing, database federation, semantic integration, service-oriented and/or wiki integration; • Issues related to the definition and implementation of standards, shared identities and semantics, with particular focus on the integration problem. Research papers, reviews and short communications on all topics related to the above issues were welcomed.
Author: Chad Brenner
Publisher: MDPI
ISBN: 3039217887
Category : Medical
Languages : en
Pages : 418
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Book Description
This collection of 25 research papers comprised of 22 original articles and 3 reviews is brought together from international leaders in bioinformatics and biostatistics. The collection highlights recent computational advances that improve the ability to analyze highly complex data sets to identify factors critical to cancer biology. Novel deep learning algorithms represent an emerging and highly valuable approach for collecting, characterizing and predicting clinical outcomes data. The collection highlights several of these approaches that are likely to become the foundation of research and clinical practice in the future. In fact, many of these technologies reveal new insights about basic cancer mechanisms by integrating data sets and structures that were previously immiscible. Accordingly, the series presented here bring forward a wide range of artificial intelligence approaches and statistical methods that can be applied to imaging and genomics data sets to identify previously unrecognized features that are critical for cancer. Our hope is that these articles will serve as a foundation for future research as the field of cancer biology transitions to integrating electronic health record, imaging, genomics and other complex datasets in order to develop new strategies that improve the overall health of individual patients.
Author: Emanuele Neri
Publisher: Springer Nature
ISBN: 3031285247
Category : Medical
Languages : en
Pages : 594
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Book Description
This book provides the reader with a focused review of multimodality imaging strategies (radiology and molecular imaging) in staging and re-staging the major types of cancer (i.e. thyroid, breast, colon-rectum, lung, prostate, pancreas, liver, head and neck, and hematological cancer), including rare neoplasms. In addition to presenting the possible diagnostic pathways for all oncologic diseases, the book identifies those interventions currently available in clinical practice (these being a branch of interventional radiology), while also examining and detailing molecular radiotherapy strategies. The work has an interdisciplinary appeal and, thanks to its highly informative and cutting-edge coverage, professionals as well as advanced students and residents in radiology, oncology and surgery will find it of particular interest.
Author: Ying Wang
Publisher: Frontiers Media SA
ISBN: 2832551807
Category : Science
Languages : en
Pages : 223
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Book Description
As the aging population degree is deepened, cognitive impairment has become a globally recognized public health problem. As an intermediate state from normal cognition (NC) to Alzheimer's disease (AD), mild cognitive impairment (MCI) has a highly variable cognitive trajectory, which contains three outcomes: 1) progression to AD and other types of dementia; 2) Maintaining stability; 3) Reversal to NC. Reversal of cognitive function can be achieved by taking positive and effective measures. Current studies mostly focus on factors affecting MCI to AD. World Health Organization and Alzheimer’s Disease International have also proposed relatively mature guidelines for risk factors. However, there are still some influencing factors that have not yet formed a unified conclusion. In addition, there are fewer studies and no consensus on the influencing factors for MCI to NC. Current forms of intervention for MCI are mainly non-pharmacological interventions, and there is a lack of randomized controlled trials with larger sample sizes and longer intervention periods to confirm the effect of pharmacological and non-pharmacological interventions. The purpose of this study is to explore the factors that influence the transition from MCI to AD or NC in aging adults, and to examine how the influencing factors make the cognitive function of aging adults with MCI deteriorate, improve or even reverse to NC and how are their reversal rates. This includes effective measures proven through pharmacological and non-pharmacological intervention studies and their impact on reversal. Influence factors include but are not limited to demographic factors (age, socioeconomic status, education), lifestyle (smoking, alcohol consumption, physical activity, nutrition, social participation), mental health (depression, loneliness), diseases (hypertension, diabetes, sleep disorders), biological markers (ß-amyloid, tau protein), and pharmacological factors (cholinesterase inhibitor, Aß monoclonal antibodies, drugs to rebalance the gut flora), etc., and submission of research results based on intervention trials is encouraged.
