9,965 research outputs found
Toward a Standardized Strategy of Clinical Metabolomics for the Advancement of Precision Medicine
Despite the tremendous success, pitfalls have been observed in every step of a clinical metabolomics workflow, which impedes the internal validity of the study. Furthermore, the demand for logistics, instrumentations, and computational resources for metabolic phenotyping studies has far exceeded our expectations. In this conceptual review, we will cover inclusive barriers of a metabolomics-based clinical study and suggest potential solutions in the hope of enhancing study robustness, usability, and transferability. The importance of quality assurance and quality control procedures is discussed, followed by a practical rule containing five phases, including two additional "pre-pre-" and "post-post-" analytical steps. Besides, we will elucidate the potential involvement of machine learning and demonstrate that the need for automated data mining algorithms to improve the quality of future research is undeniable. Consequently, we propose a comprehensive metabolomics framework, along with an appropriate checklist refined from current guidelines and our previously published assessment, in the attempt to accurately translate achievements in metabolomics into clinical and epidemiological research. Furthermore, the integration of multifaceted multi-omics approaches with metabolomics as the pillar member is in urgent need. When combining with other social or nutritional factors, we can gather complete omics profiles for a particular disease. Our discussion reflects the current obstacles and potential solutions toward the progressing trend of utilizing metabolomics in clinical research to create the next-generation healthcare system.11Ysciescopu
Synthetic biology and microdevices : a powerful combination
Recent developments demonstrate that the combination of microbiology with micro-and nanoelectronics is a successful approach to develop new miniaturized sensing devices and other technologies. In the last decade, there has been a shift from the optimization of the abiotic components, for example, the chip, to the improvement of the processing capabilities of cells through genetic engineering. The synthetic biology approach will not only give rise to systems with new functionalities, but will also improve the robustness and speed of their response towards applied signals. To this end, the development of new genetic circuits has to be guided by computational design methods that enable to tune and optimize the circuit response. As the successful design of genetic circuits is highly dependent on the quality and reliability of its composing elements, intense characterization of standard biological parts will be crucial for an efficient rational design process in the development of new genetic circuits. Microengineered devices can thereby offer a new analytical approach for the study of complex biological parts and systems. By summarizing the recent techniques in creating new synthetic circuits and in integrating biology with microdevices, this review aims at emphasizing the power of combining synthetic biology with microfluidics and microelectronics
Plantmetabolomics.org: mass spectrometry-based Arabidopsis metabolomics—database and tools update
The PlantMetabolomics (PM) database (http://www.plantmetabolomics.org) contains comprehensive targeted and untargeted mass spectrum metabolomics data for Arabidopsis mutants across a variety of metabolomics platforms. The database allows users to generate hypotheses about the changes in metabolism for mutants with genes of unknown function. Version 2.0 of PlantMetabolomics.org currently contains data for 140 mutant lines along with the morphological data. A web-based data analysis wizard allows researchers to select preprocessing and data-mining procedures to discover differences between mutants. This community resource enables researchers to formulate models of the metabolic network of Arabidopsis and enhances the research community's ability to formulate testable hypotheses concerning gene functions. PM features new web-based tools for data-mining analysis, visualization tools and enhanced cross links to other databases. The database is publicly available. PM aims to provide a hypothesis building platform for the researchers interested in any of the mutant lines or metabolites
Integration and mining of malaria molecular, functional and pharmacological data: how far are we from a chemogenomic knowledge space?
The organization and mining of malaria genomic and post-genomic data is
highly motivated by the necessity to predict and characterize new biological
targets and new drugs. Biological targets are sought in a biological space
designed from the genomic data from Plasmodium falciparum, but using also the
millions of genomic data from other species. Drug candidates are sought in a
chemical space containing the millions of small molecules stored in public and
private chemolibraries. Data management should therefore be as reliable and
versatile as possible. In this context, we examined five aspects of the
organization and mining of malaria genomic and post-genomic data: 1) the
comparison of protein sequences including compositionally atypical malaria
sequences, 2) the high throughput reconstruction of molecular phylogenies, 3)
the representation of biological processes particularly metabolic pathways, 4)
the versatile methods to integrate genomic data, biological representations and
functional profiling obtained from X-omic experiments after drug treatments and
5) the determination and prediction of protein structures and their molecular
docking with drug candidate structures. Progresses toward a grid-enabled
chemogenomic knowledge space are discussed.Comment: 43 pages, 4 figures, to appear in Malaria Journa
Comparison of MRI Spectroscopy software packages performance and application on HCV-infected patients’ real data
Treballs Finals de Grau d'Enginyeria Biomèdica. Facultat de Medicina i Ciències de la Salut. Universitat de Barcelona. Curs: 2022-2023. Tutor/Director: Sala Llonch, Roser, Laredo Gregorio, Carlos1H MRS is conceived as a pioneer methodology for brain metabolism inspection and health status
appraisal. Post-processing interventions are required to obtain explicit metabolite quantification
values from which to derive diagnosis. On the grounds of addressing and covering such operation,
multiple software packages have been recently developed and launched leading to an amorphous
assortment of spectroscopic image processing tools, with lack of standardization and regulation.
The current study thereby intends to judge the coherence and consistency of compound estimation
outputs in terms of result variability by intercorrelation and intracorrelation analyses between
appointed programs, being LCModel, Osprey, TARQUIN, and spant toolbox. The examination is
performed on a 83-subject SVS short-TE 3T SIEMENS PRESS spectroscopic acquisitions’
collection, including healthy controls and HCV-infected patients assisted with DAA treatment. The
analytical core of the project assesses software performance through the creation of a Python script
in order to automatically compute and display the results sought. The statistical tests providing
enough information to draw substantial conclusions stem from extraction of coefficient of
determination (R2
), Pearson’s coefficient (r), and intraclass correlation coefficient (ICC) together
with representation of boxplots, rainclouds, and scatter plots easing data visualization. A clinical
implementation is also entailed on the same basis, whose purpose is to reveal actual DAA
treatment effect on HCV-infected patients by means of metabolite concentration alteration and
hypothetical restoration. Conclusions declare evident and alarming variability among MRS
platforms compromising the rigor, sharpness and systematization demanded in this discipline since
quantification results hold incoherences, although they do not seem to affect or oppose medical
determinations jeopardizing patient’s health. However, it would be interesting to extend the analysis
to a greater cohort of subjects to reinforce and get to more solid resolutions
merlin, an improved framework for the reconstruction of high-quality genome-scale metabolic models
Genome-scale metabolic models have been recognised as useful tools for better understanding living organisms metabolism. merlin (https://www.merlin-sysbio.org/) is an open-source and user-friendly resource that hastens the models reconstruction process, conjugating manual and automatic procedures, while leveraging the user's expertise with a curation-oriented graphical interface. An updated and redesigned version of merlin is herein presented. Since 2015, several features have been implemented in merlin, along with deep changes in the software architecture, operational flow, and graphical interface. The current version (4.0) includes the implementation of novel algorithms and third-party tools for genome functional annotation, draft assembly, model refinement, and curation. Such updates increased the user base, resulting in multiple published works, including genome metabolic (re-)annotations and model reconstructions of multiple (lower and higher) eukaryotes and prokaryotes. merlin version 4.0 is the only tool able to perform template based and de novo draft reconstructions, while achieving competitive performance compared to state-of-the art tools both for well and less-studied organisms.Centre of Biological Engineering (CEB, UMinho);
Portuguese Foundation for Science and Technology
(FCT) under the scope of the strategic funding of
UIDB/04469/2020 unit; this work is a result of the
project 22231/01/SAICT/2016: Biodata.pt Infraestrutura Portuguesa de Dados Biologicos, supported by the ´
PORTUGAL 2020 Partnership Agreement, through the
European Regional Development Fund (ERDF); FCT for
providing PhD scholarships [DFA/BD/08789/2021 J.C,
DFA/BD/8076/2020 E.C., SFRH/BD/139198/2018 to
F.C., SFRH/BD/131916/2017 R. Rodrigues]; FCT for the
Assistant Research contract of Oscar Dias obtained under
CEEC Individual 2018.info:eu-repo/semantics/publishedVersio
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