By conceptualizing tissue-biofluid as information channels, significant biofluid proxies can be identified and then used for guided development of clinical diagnostics. Candidate biomarkers are then predicted based on information transfer criteria across the tissue-biofluid channels. Significant biofluid-tissue relationships can be used to prioritize clinical validation of biomarkers.
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An information-theoretic framework for biomarker discovery, integrating biofluid and tissue information, has been introduced; this approach takes advantage of functional synergy between certain biofluids and tissues, with the potential for clinically significant findings (not possible if tissues and biofluids were considered separately). By conceptualizing tissue biofluids as information channels, significant biofluid proxies were identified and then used for guided development of clinical diagnostics. Candidate biomarkers were then predicted, based on information-transfer criteria across the tissue-biofluid channels. Significant biofluid-tissue relationships can be used to prioritize the clinical validation of biomarkers.
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Biofluids are more readily accessible, unlike more invasive or unfeasible techniques (such as tissue biopsy). Biofluids contain proteins from tissues and serve as effective hormonal communicators. The tissue acts as a transmitter of information, and the biofluid (sampled by physician) acts as a receiver. The informativeness of the biofluid relies on the fidelity of the channel.
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Red blood cells Biological fluid mechanics, or biofluid mechanics, is the study of both gas and liquid fluid flows in or around biological organisms. An often studied liquid biofluid problem is that of blood flow in the human cardiovascular system. Under certain mathematical circumstances, blood flow can be modeled by the Navier–Stokes equations. In vivo whole blood is assumed to be an incompressible Newtonian fluid.
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Sources of noise which decrease fidelity include the addition of proteins derived from other tissues (or from the biofluid itself); proteins may also be lost through glomerular filtration. These factors can significantly influence the protein composition of a biofluid. In addition, simply looking at protein overlap would miss information transmission occurring through classes of proteins and protein-protein interactions. Instead, the proteins' projection onto functional, drug, and disease spaces allow measurement of the functional distance between tissue and biofluids.
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Proximity in these abstract spaces signifies a low level of distortion across the information channel (and, hence, high performance by the biofluid). However, current approaches to biomarker prediction have analyzed tissues and biofluids separately.
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Huge research efforts focus these days to understand intrinsic biofluid dynamics to shed light on mechanisms in physiology and pathophysiology. This list contains details of some of the major research groups focusing efforts in this area.
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This difference, combined with the ability of the kidneys to handle abnormally high or abnormally low concentrations of metabolites, makes urine a particularly useful biofluid for medical diagnostics. In fact, urinary metabolites have been used to characterize nearly 220 diseases.
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Biofluid dynamics may be considered as the discipline of biological engineering or biomedical engineering in which the fundamental principles of fluid dynamics are used to explain the mechanisms of biological flows and their interrelationships with physiological processes, in health and in diseases/disorder. It can be considered as the conjuncture of mechanical engineering and biological engineering. It spans from cells to organs, covering diverse aspects of the functionality of systemic physiology, including cardiovascular, respiratory, reproductive, urinary, musculoskeletal and neurological systems etc. Biofluid dynamics and its simulations in computational fluid dynamics (CFD) apply to both internal as well as external flows.
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Internal flows such as cardiovascular blood flow and respiratory airflow, and external flows such as flying and aquatic locomotion (i.e., swimming). Biological fluid Dynamics (or Biofluid Dynamics) involves the study of the motion of biological fluids (e.g. blood flow in arteries, animal flight, fish swimming, etc.).
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Bovine metabolomic database Bovine Metabolome Database is a free web database about metabolites information of bovine (cow). It collects 7859 metabolites totally. Each metabolite host properties like CAS name, IUPAC name, structure diagram, formula, and biofluid location. It fills the lack of the information in bovine field.
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Lee Waite, Jerry Fine (2007). "Applied BioFluid Mechanics", The Mc Graw Hill Companies, Inc. Otto Frank published the "Fundamental form of the arterial pulse," which contained his "Windkessel theory" of circulation in 1890. He also perfected optical manometers and capsules for the precise measurement of intra-cardiac pressures and volumes.
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It can be either circulatory system or respiratory systems. Understanding the circulatory system is one of the major areas of research. The respiratory system is very closely linked to the circulatory system and is very complex to study and understand. The study of Biofluid Dynamics is also directed towards finding solutions to some of the human body related diseases and disorders.
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The usefulness of the subject can also be understood by seeing the use of Biofluid Dynamics in the areas of physiology in order to explain how living things work and about their motions, in developing an understanding of the origins and development of various diseases related to human body and diagnosing them, in finding the cure for the diseases related to cardiovascular and pulmonary systems.
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Goyal has authored journal articles and text books such as: "Introduction to Agriclimatology", Management of Drip/trickle or Micro Irrigation, and Biofluid Dynamics of Human Body Systems On 16 September 2005, Goyal was named "Father of Irrigation Engineering in Puerto Rico for the 20th Century" by the ASABE – Puerto Rico Section, for his pioneer work on irrigation, evapotranspiration, climatology, and soil and water engineering.
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The NINDS Parkinson's Disease Biomarkers Program brings together various stakeholders to create a resource of longitudinal biofluid samples from PD patients and controls and their associated clinical assessment data for biomarker discovery research. Neuroimaging and genomic data are also available for some of the samples. All samples are stored at the NINDS Human Genetics Repository at Coriell Institute and can be requested through the PDBP Data Management Resource.
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Shukla had proposed a new deterministic theory regarding the effect of surface roughness in lubrication. He has done significant work on biofluid dynamics, in particular peristaltic transport of faeces in intestines and on interaction of biorheological aspects of blood flow and arterial stenosis. He has also made contributions in the area of population dynamics of interacting species and mathematical theory of epidemics by taking into account environmental effects.
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Dimensional Analysis and Self-Similarity Methods for Engineers and Scientists (2015). doi:10.1007/978-3-319-13476-5 To achieve kinematic similarity in a scaled model, dimensionless numbers in fluid dynamics come into consideration. For example, Reynolds number of the model and the prototype must match. There are other dimensionless numbers that will also come into consideration, such as Womersley numberLee Waite, Ph.D., P.E.; Jerry Fine, Ph.D.: Applied Biofluid Mechanics, Second Edition.
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The proteomic networks contain many biomarkers that are proxies for development and illustrate the potential clinical application of this technology as a way to monitor normal and abnormal fetal development. An information theoretic framework has also been introduced for biomarker discovery, integrating biofluid and tissue information. This new approach takes advantage of functional synergy between certain biofluids and tissues with the potential for clinically significant findings not possible if tissues and biofluids were considered individually.
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MetaboMiner is a tool which can be used to automatically or semi-automatically identify metabolites in complex biofluids from 2D-NMR spectra. MetaboMiner is able to handle both 1H-1H total correlation spectroscopy (TOCSY) and 1H-13C heteronuclear single quantum correlation (HSQC) data. It identifies compounds by comparing 2D spectral patterns in the NMR spectrum of the biofluid mixture with specially constructed libraries containing reference spectra of approximately 500 pure compounds. MetaboMiner protocol is available via MetaboMiner website.
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The clinical data includes information on >10,000 metabolite-biofluid concentrations and metabolite concentration information on more than 600 different human diseases. The biochemical data includes 5,688 protein (and DNA) sequences and more than 5000 biochemical reactions that are linked to these metabolite entries. Each metabolite entry in the HMDB contains more than 110 data fields with 2/3 of the information being devoted to chemical/clinical data and the other 1/3 devoted to enzymatic or biochemical data.
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"Biofluid Mechanics," Annual Review Fluid Mechanics, 21(1989)167:204. By knowing the Reynolds and Womersley numbers for a given flow it is possible to calculate both the transient and the convective boundary layer thicknesses, and relate them to a flow in another system. The boundary layer thickness is also useful in knowing when the fluid can be treated as an ideal fluid. This is at a distance that is larger than both boundary layer thicknesses.
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On 20 January 2015, Abcam announced the acquisition of Firefly BioWorks, a privately held company based in Cambridge, Massachusetts (US), for . Firefly developed a novel multiplex assay platform for the detection of biomarkers, based on a microfabrication technology developed by Daniel Pregibon and Patrick Doyle at Massachusetts Institute of Technology, and launched its first products for the multiplex detection of microRNA from RNA and crude biofluid. Firefly was rebranded to FirePlex in 2016. On 11 November 2015, Abcam announced the acquisition of AxioMx.
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SEAS has research laboratories dedicated to high-performance computing, nanotechnology, robotics, transportation engineering, among other fields, including: ;Biomedical engineering research Biomedical engineering research at the George Washington University includes biofluid dynamics, medical imaging, cardiac electrophysiology, plasma medicine, therapeutic ultrasound, nanomedicine and tissue engineering. ;Cybersecurity research Cybersecurity research is spread across six laboratories at the George Washington University including Dr. Zhang's laboratory which focuses on data security, the Cyber Security Policy and Research Institute, and Dr. Monteleoni's laboratory in Machine Learning.
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In 2012 Fauci became a fellow of the Society for Industrial and Applied Mathematics "for contributions to computational biofluid dynamics and applications.". In 2016 she was selected as the annual Sonia Kovalevsky Lecturer by the Association for Women in Mathematics.. In 2018, she because a Fellow of the American Physical Society. She was elected as a Fellow of the American Mathematical Society in the 2020 Class, for "contributions to computational fluid dynamics and applications, and for service to the applied mathematical community".
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The History of Bio-Fluid Dynamics may be considered very old dating back to 2700-2600 BC when for the first time a written document on circulation of blood and theories of Chinese medicine called "Internal Classics" was written by the Chinese emperor Huang ti also called as the yellow emperor.Lee Waite, Jerry Fine (2007). "Applied Bio-Fluid Mechanics", The Mc Graw Hill Companies, Inc. The Most notable names related to the field of biofluid Dynamics are of William Harvey, Jean Louis Marie Poiseuille, and Otto Frank.
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Biofluid Dynamics refers to the study of fluid Dynamics of basic biological fluids such as blood, air etc. and has immense applications in the field of diagnosing, treating and certain surgical procedures related to the disorders/diseases which originate in the body relating to cardiovascular, pulmonary, synovial systems etc. The different types of cardiovascular diseases include Aneurysms, Angina, Atherosclerosis, Stroke, Different types of Cerebrovascular disease, Heart Failure, Coronary Heart diseases and Myocardial infarction or Heart attacks. The Computational Fluid dynamics (CFD) models prepared through software, of the arteries, veins etc.
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It has been shown that a macropore size of 200–500 µm is preferred for ingrowths of new bone tissues and transportation of body fluids. The lower bound is controlled by the size of cells (~20 µm), and the upper bound is related to the specific surface area through the availability of binding sites. Finer pores further help in tissue growth and biofluid movement. Anisotropic, elongated pores (such as those attainable via the freeze-casting technique) may be beneficial in bone implants in that they can further mimic the structure of bone.
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Maithili Sharan (born 4 January 1953) is an Indian mathematician who specialises in mathematical modelling, biofluid mechanics, Air Pollution and atmospheric boundary layer. He was awarded in 1992 the Shanti Swarup Bhatnagar Prize for Science and Technology, the highest science award in India, in the mathematical sciences category. Maithili Sharan's notable findings relate to development of mathematical models for the transport of gases in pulmonary and systemic circulations including brain and dispersion of air pollutants in low wind conditions, numerical simulation of Bhopal gas leak, and weak wind nocturnal boundary layer.
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Because an organism's metabolome is largely defined by its genome, different species will have different metabolomes. Indeed, the fact that the metabolome of a tomato is different than the metabolome of an apple is the reason why these two fruits taste so different. Furthermore, different tissues, different organs and biofluids associated with those organs and tissues can also have distinctly different metabolomes. The fact that different organisms and different tissues/biofluids have such different metabolomes has led to the development of a number of organism-specific and biofluid-specific metabolome databases.
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The clinical information includes data on >10,000 metabolite-biofluid concentrations, metabolite concentration information on more than 600 different human diseases and pathway data for more than 200 different inborn errors of metabolism. The biochemical information includes nearly 6000 protein (and DNA) sequences and more than 5000 biochemical reactions that are linked to these metabolite entries. The HMDB supports a wide variety of online queries including text searches, chemical structure searches, sequence similarity searches and spectral similarity searches. This makes it particularly useful for metabolomic researchers who are attempting to identify or understand metabolites in clinical metabolomic studies.
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The MSEA web server is a freely available web server for performing metabolite set enrichment analysis on human or mammalian metabolomics data. The required input is either a list of compound names or compound names and concentrations. The output is a set of graphs and tables with embedded hyperlinks to the pertinent pathway images and descriptors. The Metabolite Set Enrichment Analysis offered by the web server is based on a curated library of more 5000 predefined metabolite sets covering various human metabolic pathways (nearly 100), hundreds of human disease states (in 3 different biofluids), human biofluid and tissue locations as well as human SNP-metabolite associations (4500 different SNP associations).
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As an analytical technique, MS is a very sensitive method that requires very little sample (<1 ng of material or <10 μL of a biofluid) and can generate signals for thousands of metabolites from a single sample. MS instruments can also be configured for very high throughput metabolome analyses (hundreds to thousands of samples a day). Quantification of metabolites and the characterization of novel compound structures is more difficult by MS than by NMR. LC-MS is particularly amenable to detecting hydrophobic molecules (lipids, fatty acids) and peptides while GC-MS is best for detecting small molecules (<500 Da) and highly volatile compounds (esters, amines, ketones, alkanes, thiols).
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General schema showing the relationships of the genome, transcriptome, proteome, and metabolome (lipidome). The metabolome refers to the complete set of small-molecule chemicals found within a biological sample. The biological sample can be a cell, a cellular organelle, an organ, a tissue, a tissue extract, a biofluid or an entire organism. The small molecule chemicals found in a given metabolome may include both endogenous metabolites that are naturally produced by an organism (such as amino acids, organic acids, nucleic acids, fatty acids, amines, sugars, vitamins, co-factors, pigments, antibiotics, etc.) as well as exogenous chemicals (such as drugs, environmental contaminants, food additives, toxins and other xenobiotics) that are not naturally produced by an organism.
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Scientists at the University of Alberta have been systematically characterizing specific biofluid metabolomes including the serum metabolome, the urine metabolome, the cerebrospinal fluid (CSF) metabolome and the saliva metabolome. These efforts have involved both experimental metabolomic analysis (involving NMR, GC-MS, ICP-MS, LC-MS and HPLC assays) as well as extensive literature mining. According to their data, the human serum metabolome contains at least 4200 different compounds (including many lipids), the human urine metabolome contains at least 3000 different compounds (including hundreds of volatiles and gut microbial metabolites), the human CSF metabolome contains nearly 500 different compounds while the human saliva metabolome contains approximately 400 different metabolites, including many bacterial products.
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Sheldon Weinbaum: (born July 26, 1937 in Brooklyn, New York, United States) is an American biomedical engineer and biofluid mechanician. He is a CUNY Distinguished Professor Emeritus of Biomedical and Mechanical Engineering at The City College of New York. He is one of nineteen living individuals (edited 9/21/15) who is a member of all three U.S. national academies (National Academy of Science, National Academy of Engineering and National Academy of Medicine) and also the American Academy of Arts and Sciences.Bulletin Board: Triple Crown of Academies New York Times 10/23/2002 He was the founding director (1994–1999) of the New York Center for Biomedical Engineering, a regional research consortium involving the BME program at The City College and eight of the premier health care institutions in New York City.
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As a major organ for excretion, the kidney removes waste materials and chemicals from the body, such as increased concentrations of intermediary metabolites of a particular pathway, making urine (the waste product from the kidney) particularly useful for medical diagnostics. The key advantages of using urine as a biofluid are: (1) its sterility; (2) accessibility and non- invasive method of collection; and (3) it being largely free from interfering proteins or lipids. Although the human urine metabolome is a subset of the human serum metabolome, more than 484 compounds identified in urine by Bouatra et al. (either experimentally or via literature review) were not previously reported to be in blood. The same group hypothesised that this is because the kidneys do an extraordinary job of removing and/or concentrating certain metabolites from the blood, hence, compounds far below the limit of detection in blood (using today’s instrumentation) are well above the detection limit in urine.
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