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Predictive diagnostics and personalized medicine for the prevention of chronic degenerative diseases
Licastro Federico,Caruso Calogero
Immunity & Ageing , 2010, DOI: 10.1186/1742-4933-7-s1-s1
Abstract: Progressive increase of mean age and life expectancy in both industrialized and emerging societies parallels an increment of chronic degenerative diseases (CDD) such as cancer, cardiovascular, autoimmune or neurodegenerative diseases among the elderly. CDD are of complex diagnosis, difficult to treat and absorbing an increasing proportion in the health care budgets worldwide. However, recent development in modern medicine especially in genetics, proteomics, and informatics is leading to the discovery of biomarkers associated with different CDD that can be used as indicator of disease’s risk in healthy subjects. Therefore, predictive medicine is merging and medical doctors may for the first time anticipate the deleterious effect of CDD and use markers to identify persons with high risk of developing a given CDD before the clinical manifestation of the diseases. This innovative approach may offer substantial advantages, since the promise of personalized medicine is to preserve individual health in people with high risk by starting early treatment or prevention protocols. The pathway is now open, however the road to an effective personalized medicine is still long, several (diagnostic) predictive instruments for different CDD are under development, some ethical issues have to be solved. Operative proposals for the heath care systems are now needed to verify potential benefits of predictive medicine in the clinical practice. In fact, predictive diagnostics, personalized medicine and personalized therapy have the potential of changing classical approaches of modern medicine to CDD.
The Shape of the Urine Stream — From Biophysics to Diagnostics  [PDF]
Andrew P. S. Wheeler, Samir Morad, Noor Buchholz, Martin M. Knight
PLOS ONE , 2012, DOI: 10.1371/journal.pone.0047133
Abstract: We develop a new computational model of capillary-waves in free-jet flows, and apply this to the problem of urological diagnosis in this first ever study of the biophysics behind the characteristic shape of the urine stream as it exits the urethral meatus. The computational fluid dynamics model is used to determine the shape of a liquid jet issuing from a non-axisymmetric orifice as it deforms under the action of surface tension. The computational results are verified with experimental modelling of the urine stream. We find that the shape of the stream can be used as an indicator of both the flow rate and orifice geometry. We performed volunteer trials which showed these fundamental correlations are also observed in vivo for male healthy volunteers and patients undergoing treatment for low flow rate. For healthy volunteers, self estimation of the flow shape provided an accurate estimation of peak flow rate (). However for the patients, the relationship between shape and flow rate suggested poor meatal opening during voiding. The results show that self measurement of the shape of the urine stream can be a useful diagnostic tool for medical practitioners since it provides a non-invasive method of measuring urine flow rate and urethral dilation.
Stroke genetics: prospects for personalized medicine  [cached]
Markus Hugh S
BMC Medicine , 2012, DOI: 10.1186/1741-7015-10-113
Abstract: Epidemiologic evidence supports a genetic predisposition to stroke. Recent advances, primarily using the genome-wide association study approach, are transforming what we know about the genetics of multifactorial stroke, and are identifying novel stroke genes. The current findings are consistent with different stroke subtypes having different genetic architecture. These discoveries may identify novel pathways involved in stroke pathogenesis, and suggest new treatment approaches. However, the already identified genetic variants explain only a small proportion of overall stroke risk, and therefore are not currently useful in predicting risk for the individual patient. Such risk prediction may become a reality as identification of a greater number of stroke risk variants that explain the majority of genetic risk proceeds, and perhaps when information on rare variants, identified by whole-genome sequencing, is also incorporated into risk algorithms. Pharmacogenomics may offer the potential for earlier implementation of 'personalized genetic' medicine. Genetic variants affecting clopidogrel and warfarin metabolism may identify non-responders and reduce side-effects, but these approaches have not yet been widely adopted in clinical practice.
Reinventing Diagnostics for Personalized Therapy in Oncology  [PDF]
Diponkar Banerjee
Cancers , 2010, DOI: 10.3390/cancers2021066
Abstract: Human cancers are still diagnosed and classified using the light microscope. The criteria are based upon morphologic observations by pathologists and tend to be subject to interobserver variation. In preoperative biopsies of non-small cell lung cancers, the diagnostic concordance, even amongst experienced pulmonary pathologists, is no better than a coin-toss. Only 25% of cancer patients, on average, benefit from therapy as most therapies do not account for individual factors that influence response or outcome. Unsuccessful first line therapy costs Canada CAN$1.2 billion for the top 14 cancer types, and this extrapolates to $90 billion globally. The availability of accurate drug selection for personalized therapy could better allocate these precious resources to the right therapies. This wasteful situation is beginning to change with the completion of the human genome sequencing project and with the increasing availability of targeted therapies. Both factors are giving rise to attempts to correlate tumor characteristics and response to specific adjuvant and neoadjuvant therapies. Static cancer classification and grading systems need to be replaced by functional classification systems that not only account for intra- and inter- tumor heterogeneity, but which also allow for the selection of the correct chemotherapeutic compounds for the individual patient. In this review, the examples of lung and breast cancer are used to illustrate the issues to be addressed in the coming years, as well as the emerging technologies that have great promise in enabling personalized therapy.
Myocarditis—Personalized Medicine by Expanded Endomyocardial Biopsy Diagnostics  [PDF]
Dirk Lassner, Maria Rohde, Christine Sabine Siegismund, Uwe Kühl, Ulrich Michael Gross, Felicitas Escher, Carsten Tsch?pe, Heinz-Peter Schultheiss
World Journal of Cardiovascular Diseases (WJCD) , 2014, DOI: 10.4236/wjcd.2014.46042
Abstract: Myocarditis and dilated cardiomyopathy (DCM) are acute or chronic disorders of myocardium. The gold standard for final confirmation of causative reasons of these heart muscle diseases is the endomyocardial biopsy (EMB) analysis. Due to focal pathology, diagnostics are failing if the EMB does not contain the area of interest. Personalized medicine comprises the genetic information together with the phenotypic and environmental factors to yield a tailored healthcare for each individual and removes the limitations of the “one-size-fits-all” therapy approach. This provides the opportunity to translate therapies from bench to bedside, to diagnose and predict disease, and to improve patient-tailored treatments based on the unique signatures of a patient’s disease. Furthermore, novel treatment schedules can be identified which have eventually the chance to enhance long-term survivals. Global biomarkers such as specific gene expression signatures or miRNA profiles not only have the potential to reduce this problem but also add valuable information for individualized therapy decisions. In future, multiplex approaches allowing rapid and absolutely reliable identification of inflammatory or virally-induced myocardial diseases will replace singleplex methods such as direct detection of viral genomes in one single biopsy. Gene or miRNA profiles are upcoming diagnostic biomarkers for cardiomyopathies which are not only detectable in tissue samples but in body fluids as well. Consequently, a systemic diagnostic approach by determination of distinct expression pattern in e.g., peripheral blood samples will support the characterization of distinct cardiomyopathies by means of non-invasive methods.
Statistical design of personalized medicine interventions: The Clarification of Optimal Anticoagulation through Genetics (COAG) trial
Benjamin French, Jungnam Joo, Nancy L Geller, Stephen E Kimmel, Yves Rosenberg, Jeffrey L Anderson, Brian F Gage, Julie A Johnson, Jonas H Ellenberg, the COAG (Clarification of Optimal Anticoagulation through Genetics) Investigators
Trials , 2010, DOI: 10.1186/1745-6215-11-108
Abstract: The statistical design of the Clarification of Optimal Anticoagulation through Genetics (COAG) trial serves as an illustrative example of a personalized medicine intervention that uses each subject's genotype information. The COAG trial is a multicenter, double blind, randomized clinical trial that will compare two approaches to initiation of warfarin therapy: genotype-guided dosing, the initiation of warfarin therapy based on algorithms using clinical information and genotypes for polymorphisms in CYP2C9 and VKORC1; and clinical-guided dosing, the initiation of warfarin therapy based on algorithms using only clinical information.We determine an absolute minimum detectable difference of 5.49% based on an assumed 60% population prevalence of zero or multiple genetic variants in either CYP2C9 or VKORC1 and an assumed 15% relative effectiveness of genotype-guided warfarin initiation for those with zero or multiple genetic variants. Thus we calculate a sample size of 1238 to achieve a power level of 80% for the primary outcome. We show that reasonable departures from these assumptions may decrease statistical power to 65%.In a personalized medicine intervention, the minimum detectable difference used in sample size calculations is not a known quantity, but rather an unknown quantity that depends on the genetic makeup of the subjects enrolled. Given the possible sensitivity of sample size and power calculations to these key assumptions, we recommend that they be monitored during the conduct of a personalized medicine intervention.clinicaltrials.gov: NCT00839657The recent availability of lower-cost genetic testing has motivated medical researchers to determine whether patient care and safety is improved by using a patient's genetic information to initiate and manage drug therapy [1]. To evaluate scientific hypotheses regarding a personalized medicine intervention, a randomized clinical trial can be used to contrast outcomes between subjects randomized to receive genotype-
PAVE: Program for assembling and viewing ESTs
Carol Soderlund, Eric Johnson, Matthew Bomhoff, Anne Descour
BMC Genomics , 2009, DOI: 10.1186/1471-2164-10-400
Abstract: The PAVE (Program for Assembling and Viewing ESTs) assembler takes advantage of the 5' and 3' mate-pair information by requiring that the mate-pairs be assembled into the same contig and joined by n's if the two sub-contigs do not overlap. It handles the depth of 454 data sets by "burying" similar ESTs during assembly, which retains the expression level information while circumventing time and space problems. PAVE uses MegaBLAST for the clustering step and CAP3 for assembly, however it assembles incrementally to enforce the mate-pair constraint, bury ESTs, and reduce incorrect joins and splits. The PAVE data management system uses a MySQL database to store multiple libraries of ESTs along with their metadata; the management system allows multiple assemblies with variations on libraries and parameters. Analysis routines provide standard annotation for the contigs including a measure of differentially expressed genes across the libraries. A Java viewer program is provided for display and analysis of the results. Our results clearly show the benefit of using the PAVE assembler to explicitly use mate-pair information and bury ESTs for large contigs.The PAVE assembler provides a software package for assembling Sanger and/or 454 ESTs. The assembly software, data management software, Java viewer and user's guide are freely available.ESTs have been prevalent in genomic research since the first large scale EST project in 1991 [1]. There are many EST projects that study the gene content of genome, tissue, or condition-specific transcripts (e.g. see Additional file 1: List of EST papers, section 4). In October 2005, 454 Life Sciences released the GS 20 pyrosequencer that generates over 100,000 reads per run with an average length of 110 bases [2-4]. In January 2007, they released the GS FLX that generates over 200,000 reads with length between 200–300. Table 1 shows the growth of the number of ESTs in GenBank in relation to their length. Many of the short sequences released af
New horizons in Biophysics
Elizabeth C Moylan
BMC Biophysics , 2011, DOI: 10.1186/2046-1682-4-1
Abstract: This month PMC Biophysics joins the BMC series of journals as BMC Biophysics. The 'P to B' transition is not some strange quirk of molecular dynamics but the consequence of integrating PhysMath Central journals into Springer and BioMed Central portfolios which has resulted in a very welcome addition to the BMC series. Previously, PMC Biophysics had been published by PhysMath Central but will now be published by BioMed Central - as is the case with all journals in the BMC series. When BioMed Central was founded in 2000, the BMC series of journals were among the first to be launched. Since then, this portfolio of journals have grown rapidly and become well-recognised in the research communities they serve. We are committed to the future of BMC Biophysics and the journal will be in good company among the many successful titles in the BMC series.Under the stewardship of its Editor-in-Chief, Huan-Xiang Zhou, PMC Biophysics was originally launched in 2008 in response to the gathering strength of the open access movement and the multidisciplinary nature of research in biological physics [1]. BMC Biophysics will maintain this ethos, and continue to publish articles in experimental and theoretical aspects of biological processes from the microscopic to macroscopic level. Topics include (but are not limited to) thermodynamics, structural stability and dynamics of biological macromolecules and mesoscale cellular processes. We also welcome studies on membrane biophysics, nucleic acids, signalling and interaction networks and novel biophysical methods. In keeping with recent developments, we have also broadened the scope of the journal to explicitly cover computational and theoretical biophysics.As with the other journals in the BMC-series stable, BMC Biophysics has an international Editorial Board which retains much of the PMC Biophysics Editorial Board with additional new faces [2] and comprises Section Editors, Associate Editors and Editorial Advisors. We are delighted that H
CURRENT TRENDS IN BIOPHYSICS
Victor,A.Bloomfield
生物物理学报 , 1988,
Abstract: IntroductionBiophysics is an important and vigorous discipline,but one that is sodiverse that it resists easy definition.In its early days,biophysics had strongcontacts with physiology particularly electroyhysiology and muscle physiology,and with radiation biology and photobiology.More recently the discipline hasbecome substantially more molecular,because of major advances in biochemistry,instrumentation,and computer technology.In order to identify the most pro-mising areas for future advance,it is important to identify the areas of grea-test current activity.Methodology
Biophysics software for interdisciplinary education and research  [PDF]
J. M. Deutsch
Physics , 2013, DOI: 10.1119/1.4869198
Abstract: Biophysics is a subject that is spread over many disciplines and transcends the skills and knowledge of the individual student. This makes it challenging both to teach and to learn. Educational materials are described to aid in teaching undergraduates biophysics in an interdisciplinary manner. Projects have been devised on topics that range from x-ray diffraction to the Hodgkin Huxley equations. They are team-based and encourage collaboration. The projects make extensive use of software written in Python/Scipy which can be modified to explore a large range of possible phenomena. The software can also be used in lectures and in the teaching of more traditional biophysics courses.
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