ORCID Profile
0000-0002-3416-2572
Current Organisations
Universidad del Valle
,
Murdoch University
,
Imperial College London
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Publications
Integrative Modeling of Plasma Metabolic and Lipoprotein Biomarkers of SARS-CoV-2 Infection in Spanish and Australian COVID-19 Patient Cohorts
Publisher: American Chemical Society (ACS)
Date: 12-07-2021
Selective polarization transfer using a single rf field
Publisher: AIP Publishing
Date: 07-2008
DOI: 10.1063/1.2939572
Abstract: NMR is a popular and mature technique used in fields as erse as chemistry, biology, or material science. One reason for this versatility lies in its ability to correlate the nuclei that are present in one molecule to another. This provides the researcher with correlation maps allowing for studies of the molecules at an atomic level. Selective experiments allow isolation of one such correlation to focus on spins of interest. This leads to a savings in precious experimental time by reducing the dimension of the experiment, which in turn may enable one to record more elaborate experiments that would otherwise not be amenable within reasonable acquisition times. Here, we present an alternative method to selectively transfer magnetization using a single rf field. This technique, which we call single field polarization transfer, allows to obtain longitudinal two-spin order of two scalar-coupled spins when only one of them is irradiated. The method is easy to implement and does not depend on stringent conditions, such as Hartmann–Hahn matching for selective cross-polarization transfers or very long inversion pulses and identification of coupling satellites in selective population inversion experiments.
Fast and accurate algorithm for the simulation of NMR spectra of large spin systems
Publisher: Elsevier BV
Date: 04-2011
DOI: 10.1016/J.JMR.2010.12.008
Abstract: The computational cost for the simulation of NMR spectra grows exponentially with the number of nuclei. Today, the memory available to store the Hamiltonian limits the size of the system that can be studied. Modern computers enable to tackle systems containing up to 13 spins [1], which obviously does not allow to study most molecules of interest in research. This issue can be addressed by identifying groups of spins or fragments that are not or only weakly interacting together, i.e., that only share weakly coupled spin pairs. Such a fragmentation is only permitted in the weak coupling regime, i.e., when the coupling interaction is weak compared to the difference in chemical shift of the coupled spins. Here, we propose a procedure that removes weak coupling interactions in order to split the spin system efficiently and to correct a posteriori for the effect of the neglected couplings. This approach yields accurate spectra when the adequate interactions are removed, i.e., between spins only involved in weak coupling interactions, but fails otherwise. As a result, the computational time for the simulation of 1D spectra grows linearly with the size of the spin system.
Classification of Coffee Beans by GC-C-IRMS, GC-MS, and1H-NMR
Publisher: Hindawi Limited
Date: 2016
DOI: 10.1155/2016/8564584
Abstract: In a previous work using 1 H-NMR we reported encouraging steps towards the construction of a robust expert system for the discrimination of coffees from Colombia versus nearby countries (Brazil and Peru), to assist the recent protected geographical indication granted to Colombian coffee in 2007. This system relies on fingerprints acquired on a 400 MHz magnet and is thus well suited for small scale random screening of s les obtained at resellers or coffee shops. However, this approach cannot easily be implemented at harbour’s installations, due to the elevated operational costs of cryogenic magnets. This limitation implies shipping the s les to the NMR laboratory, making the overall approach slower and thereby more expensive and less attractive for large scale screening at harbours. In this work, we report on our attempt to obtain comparable classification results using alternative techniques that have been reported promising as an alternative to NMR: GC-MS and GC-C-IRMS. Although statistically significant information could be obtained by all three methods, the results show that the quality of the classifiers depends mainly on the number of variables included in the analysis hence NMR provides an advantage since more molecules are detected to obtain a model with better predictions.
Mutual Diffusion Driven NMR: a new approach for the analysis of mixtures by spatially resolved NMR spectroscopy
Publisher: Wiley
Date: 02-02-2017
DOI: 10.1002/MRC.4561
Abstract: We introduce a new approach for resolving the NMR spectra of mixtures that relies on the mutual diffusion of dissolved species when a concentration gradient is established within the NMR tube. This is achieved by cooling down a biphasic mixture of triethylamine and deuterated water below its mixing temperature, where a single phase is expected. Until equilibrium is reached, a gradient of concentration, from 'pure' triethylamine to 'pure' water, establishes within the tube. The amount of time required to reach this equilibrium is controlled by the mutual diffusion coefficient of both species. Moreover, a gradient of concentration exists for each additional compound dissolved in this system, related to the partition coefficient for that compound in the original biphasic state. Using slice selective experiments, it was possible to measure these concentration gradients and use them to separate signals from all the present species. We show the results acquired for a mixture composed of n-octanol, methanol, acetonitrile and benzene and compare them with those obtained by pulse field gradient NMR. Copyright © 2016 John Wiley & Sons, Ltd.
Overview of the Nomenclature and Network of Contributors to the Development of Bioreactors for Human Gut Simulation Using Bibliometric Tools: A Fragmented Landscape
Publisher: American Chemical Society (ACS)
Date: 12-09-2022
Seized Ecstasy Pills: Infrared Spectra and Image Datasets
Publisher: MDPI AG
Date: 09-12-2020
DOI: 10.3390/DATA5040116
Abstract: According to the World Drug Report 2020, cocaine and ecstasy are the most consumed stimulant drugs, with 19 and 27 million estimated users in 2018. In this context, large efforts are being made to design fast and cost-effective analytical methods to track and monitor the distribution networks of these synthetic drugs. Here, we share two datasets of ecstasy pills seized in the northeast of Switzerland between 2010 and 2011. The first contains 621 forensic-grade images of pills, while the second one consists of 486 mid-infrared (mIR) spectra. While both sets are not covering the same seizure, both provide high-quality data with orthogonal information to evaluate clustering and dimension reduction methods.
Food Allergy Readiness and Anaphylaxis Management in Early Childhood Education and Care in Western Australia
Publisher: SAGE Publications
Date: 12-2018
Abstract: WITH THE INCREASE IN prevalence of food allergy (FA) in young children, early childhood education and care (ECEC) providers are likely to have more enrolments of children who are at risk of anaphylaxis. This study examines the status of FA management in ECEC, and assesses the services’ current readiness to prevent and manage FA. A cross-sectional study comprising an online survey with multiple-choice and open-ended questions was conducted with 53 long day care services in Western Australia. Among the respondents, 83 per cent of services had at least one child enrolled with FA, 96 per cent had an FA policy, and 91 per cent required staff to undertake anaphylaxis training. A high level of self-reported confidence and skills were demonstrated however, gaps were identified in risk-minimisation knowledge, use of adrenaline (epinephrine) autoinjectors and available resources. Extensive promotion of available resources will help improve compliance with anaphylaxis guidelines.
Enhancement of PHA Production by a Mixed Microbial Culture Using VFA Obtained from the Fermentation of Wastewater from Yeast Industry
Publisher: MDPI AG
Date: 11-04-2022
DOI: 10.3390/FERMENTATION8040180
Abstract: Wastewater from the yeast production industry (WWY) is potentially harmful to surface water due to its high nitrogen and organic matter content it can be used to produce compounds of higher commercial value, such as polyhydroxyalkanoates (PHA). PHA are polyester-type biopolymers synthesized by bacteria as energy reservoirs that can potentially substitute petrochemical-derived plastics. In this exploratory work, effluent from WWY was used to produce PHA, using a three-step setup of mixed microbial cultures involving one anaerobic and two aerobic reactors. First, volatile fatty acids (VFA 2.5 g/L) were produced on an anaerobic batch reactor (reactor A) fed with WWY, using a heat pretreated sludge inoculum to eliminate methanogenic activity. Concurrently, PHA-producing bacteria were enriched using synthetic VFA in a sequencing batch reactor (SBR, reactor C) operated for 78 days. Finally, a polyhydroxybutyrate (PHB)-producing reactor (reactor B) was assembled using the inoculum enriched with PHA-producing bacteria and the raw and distilled effluent from the anaerobic reactor as a substrate. A maximum accumulation of 17% of PHB based on cell dry weight was achieved with a yield of 1.2 g PHB/L when feeding with the distilled effluent. Roche 454 16S rRNA gene licon pyrosequencing of the PHA-producing reactor showed that the microbial community was dominated by the PHA-producing bacterial species Paracoccus alcalophilus (32%) and Azoarcus sp. (44%). Our results show promising PHB accumulation rates that outperform previously reported results obtained with real substrates and mixed cultures, demonstrating a sustainable approach for the production of PHA less prone to contamination than a pure culture.
Integrative Plasma Metabolic and Lipidomic Modelling of SARS-CoV-2 Infection in Relation to Clinical Severity and Early Mortality Prediction
Publisher: MDPI AG
Date: 18-07-2023
Abstract: An integrative multi-modal metabolic phenotyping model was developed to assess the systemic plasma sequelae of SARS-CoV-2 (rRT-PCR positive) induced COVID-19 disease in patients with different respiratory severity levels. Plasma s les from 306 unvaccinated COVID-19 patients were collected in 2020 and classified into four levels of severity ranging from mild symptoms to severe ventilated cases. These s les were investigated using a combination of quantitative Nuclear Magnetic Resonance (NMR) spectroscopy and Mass Spectrometry (MS) platforms to give broad lipoprotein, lipidomic and amino acid, tryptophan-kynurenine pathway, and biogenic amine pathway coverage. All platforms revealed highly significant differences in metabolite patterns between patients and controls (n = 89) that had been collected prior to the COVID-19 pandemic. The total number of significant metabolites increased with severity with 344 out of the 1034 quantitative variables being common to all severity classes. Metabolic signatures showed a continuum of changes across the respiratory severity levels with the most significant and extensive changes being in the most severely affected patients. Even mildly affected respiratory patients showed multiple highly significant abnormal biochemical signatures reflecting serious metabolic deficiencies of the type observed in Post-acute COVID-19 syndrome patients. The most severe respiratory patients had a high mortality (56.1%) and we found that we could predict mortality in this patient sub-group with high accuracy in some cases up to 61 days prior to death, based on a separate metabolic model, which highlighted a different set of metabolites to those defining the basic disease. Specifically, hexosylceramides (HCER 16:0, HCER 20:0, HCER 24:1, HCER 26:0, HCER 26:1) were markedly elevated in the non-surviving patient group (Cliff’s delta 0.91–0.95) and two phosphoethanolamines (PE.O 18:0/18:1, Cliff’s delta = −0.98 and PE.P 16:0/18:1, Cliff’s delta = −0.93) were markedly lower in the non-survivors. These results indicate that patient morbidity to mortality trajectories is determined relatively soon after infection, opening the opportunity to select more intensive therapeutic interventions to these “high risk” patients in the early disease stages.
“Ask Ernö”: a self-learning tool for assignment and prediction of nuclear magnetic resonance spectra
Publisher: Springer Science and Business Media LLC
Date: 05-05-2016
A case of right unilateral ultra-brief ECT in refractory mania with in situ cranial metallic object
Publisher: SAGE Publications
Date: 12-05-2020
Comparison of Attenuated Total Reflectance Mid-Infrared, Near Infrared, and 1H-Nuclear Magnetic Resonance Spectroscopies for the Determination of Coffee’s Geographical Origin
Publisher: Hindawi Limited
Date: 11-2017
DOI: 10.1155/2017/7210463
Abstract: The sensorial properties of Colombian coffee are renowned worldwide, which is reflected in its market value. This raises the threat of fraud by adulteration using coffee grains from other countries, thus creating a demand for robust and cost-effective methods for the determination of geographical origin of coffee s les. Spectroscopic techniques such as Nuclear Magnetic Resonance (NMR), near infrared (NIR), and mid-infrared (mIR) have arisen as strong candidates for the task. Although a body of work exists that reports on their in idual performances, a faithful comparison has not been established yet. We evaluated the performance of 1 H-NMR, Attenuated Total Reflectance mIR (ATR-mIR), and NIR applied to fraud detection in Colombian coffee. For each technique, we built classification models for discrimination by species ( C. arabica versus C. canephora (or robusta )) and by origin (Colombia versus other C. arabica ) using a common set of coffee s les. All techniques successfully discriminated s les by species, as expected. Regarding origin determination, ATR-mIR and 1 H-NMR showed comparable capacity to discriminate Colombian coffee s les, while NIR fell short by comparison. In conclusion, ATR-mIR, a less common technique in the field of coffee adulteration and fraud detection, emerges as a strong candidate, faster and with lower cost compared to 1 H-NMR and more discriminating compared to NIR.
Pathways to care in children- perspectives from a child guidance clinic in South India
Publisher: Elsevier BV
Date: 12-2020
A patient-centric characterization of systemic recovery from SARS-CoV-2 infection
Publisher: Cold Spring Harbor Laboratory
Date: 19-06-2022
DOI: 10.1101/2022.06.18.22276437
Abstract: The biology driving in idual patient responses to SARS-CoV-2 infection remains ill understood. Here, we developed a patient-centric framework leveraging detailed longitudinal phenotyping data, covering a year post disease onset, from 215 SARS-CoV-2 infected subjects with differing disease severities. Our analyses revealed distinct “systemic recovery” profiles with specific progression and resolution of the inflammatory, immune, metabolic and clinical responses, over weeks to several months after infection. In particular, we found a strong intra-patient temporal covariation of innate immune cell numbers, kynurenine- and host lipid-metabolites, which suggested candidate immunometabolic pathways putatively influencing restoration of homeostasis, the risk of death and of long COVID. Based on these data, we identified a composite signature predictive of systemic recovery on the patient level, using a joint model on cellular and molecular parameters measured soon after disease onset. New predictions can be generated using the online tool shiny.mrc-bsu.cam.ac.uk/apps/covid-systemic-recovery-prediction-app , designed to test our findings prospectively.
Coffee’s country of origin determined by NMR: The Colombian case
Publisher: Elsevier BV
Date: 05-2015
DOI: 10.1016/J.FOODCHEM.2014.11.160
Abstract: The determination of the origin of coffee beans by NMR fingerprinting has been shown promising and classification has been reported for s les of different countries and continents. Here we show that this technique can be extended and applied to discriminate coffee s les from one country against all others, including its closest neighbors. Very high classification rates are reported using a large number of spectra (>300) acquired over a two-year period. As original aspects it can be highlighted that this study was performed in fully automatic mode and with non-deuterated coffee extracts. This is achieved using a series of experiments to procure a robust suppression of the solvent peaks. As is, the method represents a cost effective opportunity for countries to protect their national productions.
Monitoring of illicit pill distribution networks using an image collection exploration framework
Publisher: Elsevier BV
Date: 11-2012
DOI: 10.1016/J.FORSCIINT.2012.10.004
Abstract: This paper proposes a novel approach for the analysis of illicit tablets based on their visual characteristics. In particular, the paper concentrates on the problem of ecstasy pill seizure profiling and monitoring. The presented method extracts the visual information from pill images and builds a representation of it, i.e. it builds a pill profile based on the pill visual appearance. Different visual features are used to build different image similarity measures, which are the basis for a pill monitoring strategy based on both discriminative and clustering models. The discriminative model permits to infer whether two pills come from the same seizure, while the clustering models groups of pills that share similar visual characteristics. The resulting clustering structure allows to perform a visual identification of the relationships between different seizures. The proposed approach was evaluated using a data set of 621 Ecstasy pill pictures. The results demonstrate that this is a feasible and cost effective method for performing pill profiling and monitoring.
1D and 2D NMR spectra of coffee from 27 countries
Publisher: Research Square Platform LLC
Date: 08-12-2021
DOI: 10.21203/RS.3.RS-1146879/V1
Abstract: 715 green coffee s les were gathered by Almacafé S.A. (Bogotá, Colombia) between 2012 and 2014 from 27 different countries and analysed at the Nuclear Magnetic Resonance (NMR) laboratory at Universidad del Valle (Cali, Colombia). Over 1000 methanolic coffee extracts were prepared and a total of 4563 spectra were acquired in a fully automatic manner using a 400 MHz NMR spectrometer (Bruker Biospin, Germany). The dataset spans the variance that could be expected for an industrial application of origin monitoring, including s les from different harvest time, collected over several years and processed by at least two distinct operators. The resulting 1D and 2D spectra can be used to develop and evaluate feature extraction methods, multivariate algorithms and automation monitoring techniques, as a dataset for teaching, or as a reference for new studies on similar s les and approach.
The value of universally available raw NMR data for transparency, reproducibility, and integrity in natural product research
Publisher: Royal Society of Chemistry (RSC)
Date: 2019
DOI: 10.1039/C7NP00064B
Abstract: With contributions from the global natural product (NP) research community, and continuing the Raw Data Initiative, this review collects a comprehensive demonstration of the immense scientific value of disseminating raw nuclear magnetic resonance (NMR) data, independently of, and in parallel with, classical publishing outlets.
Secondary deuterium isotope effects on the acidity of glycine
Publisher: Elsevier BV
Date: 11-2010
DOI: 10.1016/J.SAA.2010.08.016
Abstract: Secondary deuterium isotope effects (IE) on the acidity (pK(a)) of glycine were measured by ¹³C NMR titration. It was found that deuteration decreases the pK(a) by 0.034 ± 0.002. The experimental data are supported by theoretical calculations, which, in turn, allowed to relate the acidity decrease to the lowering of glycine vibrational frequencies upon deuteration.
NMReDATA, a standard to report the NMR assignment and parameters of organic compounds
Publisher: Wiley
Date: 16-05-2018
DOI: 10.1002/MRC.4737
Complex mixtures by NMR and complex NMR for mixtures: experimental and publication challenges
Publisher: Wiley
Date: 17-10-2016
DOI: 10.1002/MRC.4533
Abstract: Untargeted strategies have changed the rules of the game in complex mixture analysis, introducing an amazing potential for medical and biological applications that is just starting to be tapped. But with great power come great challenges although untargeted mixture analysis opens the road for many exciting possibilities, the road is still full of perils. On the one hand, this article highlights some of the difficulties that need to be sorted for mixture analysis by NMR to fulfill its potential, along with insight on how they may be managed. Highlighted key points include the need for ‘computer friendly’ solutions for sharing data, experimental design and algorithm to facilitate the steady growth of knowledge and modeling ability in the field, and the need for large‐scale studies to improve confidence in newly identified biomarkers. On the other hand, the second part of this article presents some breakthroughs in NMR experiments that, when combined, may modify the landscape of mixture analysis. Copyright © 2016 John Wiley & Sons, Ltd.
Diagnostic Potential of the Plasma Lipidome in Infectious Disease: Application to Acute SARS-CoV-2 Infection
Publisher: MDPI AG
Date: 20-07-2021
Abstract: Improved methods are required for investigating the systemic metabolic effects of SARS-CoV-2 infection and patient stratification for precision treatment. We aimed to develop an effective method using lipid profiles for discriminating between SARS-CoV-2 infection, healthy controls, and non-SARS-CoV-2 respiratory infections. Targeted liquid chromatography–mass spectrometry lipid profiling was performed on discovery (20 SARS-CoV-2-positive 37 healthy controls 22 COVID-19 symptoms but SARS-CoV-2negative) and validation (312 SARS-CoV-2-positive 100 healthy controls) cohorts. Orthogonal projection to latent structure-discriminant analysis (OPLS-DA) and Kruskal–Wallis tests were applied to establish discriminant lipids, significance, and effect size, followed by logistic regression to evaluate classification performance. OPLS-DA reported separation of SARS-CoV-2 infection from healthy controls in the discovery cohort, with an area under the curve (AUC) of 1.000. A refined panel of discriminant features consisted of six lipids from different subclasses (PE, PC, LPC, HCER, CER, and DCER). Logistic regression in the discovery cohort returned a training ROC AUC of 1.000 (sensitivity = 1.000, specificity = 1.000) and a test ROC AUC of 1.000. The validation cohort produced a training ROC AUC of 0.977 (sensitivity = 0.855, specificity = 0.948) and a test ROC AUC of 0.978 (sensitivity = 0.948, specificity = 0.922). The lipid panel was also able to differentiate SARS-CoV-2-positive in iduals from SARS-CoV-2-negative in iduals with COVID-19-like symptoms (specificity = 0.818). Lipid profiling and multivariate modelling revealed a signature offering mechanistic insights into SARS-CoV-2, with strong predictive power, and the potential to facilitate effective diagnosis and clinical management.
Teaching NMR spectra analysis with nmr.cheminfo.org
Publisher: Wiley
Date: 19-04-2018
DOI: 10.1002/MRC.4733
Abstract: Teaching spectra analysis and structure elucidation requires students to get trained on real problems. This involves solving exercises of increasing complexity and when necessary using computational tools. Although desktop software packages exist for this purpose, nmr.cheminfo.org platform offers students an online alternative. It provides a set of exercises and tools to help solving them. Only a small number of exercises are currently available, but contributors are invited to submit new ones and suggest new types of problems.
Non-severe burns induce a prolonged systemic metabolic phenotype indicative of a persistent inflammatory response post-injury
Publisher: Cold Spring Harbor Laboratory
Date: 28-04-2023
DOI: 10.1101/2023.04.24.537960
Abstract: Globally, burns are a significant cause of injury that can cause substantial acute trauma as well as lead to increased incidence of chronic co-morbidity and disease. To date, research has primarily focused on the systemic response to severe injury, with little in the literature reported on impact of non-severe injuries ( % total burn surface area TBSA). To elucidate the metabolic consequences of non-severe burn injury, longitudinal plasma was collected from adults (n=35) who presented at hospital with a non-severe burn injury at admission, and at 6 week follow up. A cross-sectional baseline s le was also collected from non-burn control participants (n=14). S les underwent multiplatform metabolic phenotyping using 1 H nuclear magnetic resonance spectroscopy and liquid chromatography-mass spectrometry to quantify 112 lipoprotein and glycoproteins signatures and 852 lipid species from across 20 subclasses. Multivariate data modelling (Orthogonal projection to latent structures-discriminate analysis) revealed alterations in lipoprotein and lipid metabolism when comparing baseline control to hospital admission s les, with the phenotypic signature found to be sustained at follow up. Univariate (Mann-Whitney U) testing and OPLS-DA indicated specific increases in GlycB (p-value .0e -4 ), low density lipoprotein-2 subfractions (Variable importance in projection score VIP .83e -1 ) and monoacyglyceride (20:4)(p-value .0e -4 ) and decreases in circulating anti-inflammatory high-density lipoprotein-4 subfractions (VIP .75e -1 ), phosphatidylcholines, phosphatidylglycerols, phosphatidylinositols and phosphatidylserines. The results indicate a persistent systemic metabolic phenotype that occurs even in cases of non-severe burn injury. The phenotype is indicative of an acute inflammatory profile which continues to be sustained post-injury, suggesting an impact on systems health beyond the site of injury. The phenotypes contained metabolic signatures consistent with chronic inflammatory states reported to have elevated incidence post-burn injury. Such phenotypic signatures may provide patient stratification opportunities, to identify in idual responses to injury, personalise intervention strategies and improve acute care, reducing risk of chronic co-morbidity.
Analysis of the Metabolic Response of Planktonic Cells and Biofilms of Klebsiella pneumoniae to Sublethal Disinfection with Sodium Hypochlorite Measured by NMR
Publisher: MDPI AG
Date: 30-06-2022
DOI: 10.3390/MICROORGANISMS10071323
Abstract: Klebsiella pneumoniae is a pathogenic agent able to form biofilms on water storage tanks and pipe walls. This opportunistic pathogen can generate a thick layer as one of its essential virulence factors, enabling the bacteria to survive disinfection processes and thus develop drug resistance. Understanding the metabolic differences between biofilm and planktonic cells of the K. pneumoniae response to NaClO is key to developing strategies to control its spread. In this study, we performed an NMR metabolic profile analysis to compare the response to a sublethal concentration of sodium hypochlorite of biofilm and planktonic cells of K. pneumoniae cultured inside silicone tubing. Metabolic profiles revealed changes in the metabolism of planktonic cells after a contact time of 10 min with 7 mg L−1 of sodium hypochlorite. A decrease in the production of metabolites such as lactate, acetate, ethanol, and succinate in this cell type was observed, thus indicating a disruption of glucose intake. In contrast, the biofilms displayed a high metabolic heterogeneity, and the treatment did not affect their metabolic signature.
HastaLaVista, a web-based user interface for NMR-based untargeted metabolic profiling analysis in biomedical sciences: towards a new publication standard
Publisher: Springer Science and Business Media LLC
Date: 12-2019
DOI: 10.1186/S13321-019-0399-7
Abstract: Metabolic profiling has been shown to be useful to improve our understanding of complex metabolic processes. Shared data are key to the analysis and validation of metabolic profiling and untargeted spectral analysis and may increase the pace of new discovery. Improving the existing portfolio of open software may increase the fraction of shared data by decreasing the amount of effort required to publish them in a manner that is useful to others. However, a weakness of open software, when compared to commercial ones, is the lack of user-friendly graphical interface that may discourage inexperienced researchers. Here, a web-browser-oriented solution is presented and demonstrated for metabolic profiling analysis that combines the power of R for back-end statistical analyses and of JavaScript for front-end visualisations and user interactivity. This unique combination of statistical programming and web-browser visualisation brings enhanced data interoperability and interactivity into the open source realm. It is exemplified by characterizing the extent to which bariatric surgery perturbs the metabolisms of rats, showing the value of the approach in iterative analysis by the end-user to establish a deeper understanding of the system perturbation. HastaLaVista is available at: ( wist/hastaLaVista , 10.5281/zenodo.3544800 ) under MIT license. The approach described in this manuscript can be extended to connect the interface to other scripting languages such as Python, and to create interfaces for other types of data analysis.
Composition dependent transport diffusion in non-ideal mixtures from spatially resolved nuclear magnetic resonance spectroscopy
Publisher: Royal Society of Chemistry (RSC)
Date: 2018
DOI: 10.1039/C8CP05539D
Abstract: Nuclear magnetic resonance (NMR) spectroscopy can also be used for the measurement of the Fick diffusion coefficient.
TiO2 modified with polyoxotungstates should induce visible-light absorption and high photocatalytic activity through the formation of surface complexes
Publisher: Elsevier BV
Date: 07-2016
A patient-centric modeling framework captures recovery from SARS-CoV-2 infection
Publisher: Springer Science and Business Media LLC
Date: 30-01-2023
DOI: 10.1038/S41590-022-01380-2
Abstract: The biology driving in idual patient responses to severe acute respiratory syndrome coronavirus 2 infection remains ill understood. Here, we developed a patient-centric framework leveraging detailed longitudinal phenotyping data and covering a year after disease onset, from 215 infected in iduals with differing disease severities. Our analyses revealed distinct ‘systemic recovery’ profiles, with specific progression and resolution of the inflammatory, immune cell, metabolic and clinical responses. In particular, we found a strong inter-patient and intra-patient temporal covariation of innate immune cell numbers, kynurenine metabolites and lipid metabolites, which highlighted candidate immunologic and metabolic pathways influencing the restoration of homeostasis, the risk of death and that of long COVID. Based on these data, we identified a composite signature predictive of systemic recovery, using a joint model on cellular and molecular parameters measured soon after disease onset. New predictions can be generated using the online tool shiny.mrc-bsu.cam.ac.uk/apps/covid-19-systemic-recovery-prediction-app , designed to test our findings prospectively.
SARS-CoV-2 Infection Biomarkers Reveal an Extended RSAD2 Dependant Metabolic Pathway
Publisher: Cold Spring Harbor Laboratory
Date: 08-05-2023
DOI: 10.1101/2023.05.08.23289637
Abstract: We present compelling evidence for the existence of an extended innate viperin dependent pathway which provides crucial evidence for an adaptive response to viral agents like SARS-CoV-2. We show the in vivo biosynthesis of a family of endogenous cytosine metabolites with potential antiviral activity. Two dimensional Nuclear magnetic resonance (NMR) spectroscopy revealed a characteristic spin-system motif indicating the presence of an extended panel of urinary metabolites during the acute viral replication phase. Mass spectrometry additionally allowed the characterization and quantification of the most abundant serum metabolites showing potential diagnostic value of the compounds for viral infections. In total, we unveiled ten nucleoside (cytosine and uracil based) analogue structures, eight of which were previously unknown in humans. The molecular structures of the nucleoside analogues and their correlation with an array of serum cytokines, including IFN-α2, IFN-γ and IL-10, suggest an association with the viperin enzyme contributing to an endogenous innate immune defence mechanism against viral infection.
Metabolomic Profile in Patients with Malignant Disturbances of the Prostate: An Experimental Approach
Publisher: Publicidad Permanyer, SLU
Date: 06-2022
Abstract: Purpose To identify metabolites in humans that can be associated with the presence of malignant disturbances of the prostate. Methods In the present study, we selected male patients aged between 46 and 82 years who were considered at risk of prostate cancer due to elevated levels of prostate-specific antigen (PSA) or abnormal results on the digital rectal examination. All selected patients came from two university hospitals (Hospital Universitario del Valle and Clínica Rafael Uribe Uribe) and were ided into 2 groups: cancer (12 patients) and non-cancer (20 patients). Cancer was confirmed by histology, and none of the patients underwent any previous treatment. Standard protocols were applied to all the collected blood s les. The resulting plasma s les were kept at -80°C, and a profile of each one was acquired by nuclear magnetic resonance (NMR) using established experiments. Multivariate analyses were applied to this dataset, first to establish the quality of the data and identify outliers, and then, to model the data. Results We included 12 patients with cancer and 20 without it. Two patients were excluded due to contamination with ethanol. The remaining ones were used to build an Orthogonal Projections to Latent Structures Discriminant Analysis (OPLS-DA) model (including 15 non-cancer and 10 cancer patients), with acceptable discrimination (Q2 = 0.33). This model highlighted the role of lactate and lipids, with a positive association of these two metabolites and prostate cancer. Conclusions The primary discriminative metabolites between patients with and without prostate cancer were lactate and lipids. These might be the most reliable biomarkers to trace the development of cancer in the prostate.
Fast and shift-insensitive similarity comparisons of NMR using a tree-representation of spectra
Publisher: Elsevier BV
Date: 08-2013
Comprehensive Lipidomic Workflow for Multicohort Population Phenotyping Using Stable Isotope Dilution Targeted Liquid Chromatography-Mass Spectrometry
Publisher: American Chemical Society (ACS)
Date: 24-02-2023
Correction: The value of universally available raw NMR data for transparency, reproducibility, and integrity in natural product research
Publisher: Royal Society of Chemistry (RSC)
Date: 2019
DOI: 10.1039/C8NP90041H
Abstract: Correction for ‘The value of universally available raw NMR data for transparency, reproducibility, and integrity in natural product research’ by James B. McAlpine et al. , Nat. Prod. Rep. , 2018, DOI: 10.1039/c7np00064b.
The C6H6 NMR repository: An integral solution to control the flow of your data from the magnet to the public
Publisher: Wiley
Date: 03-11-2017
DOI: 10.1002/MRC.4669
Abstract: NMR is a mature technique that is well established and adopted in a wide range of research facilities from laboratories to hospitals. This accounts for large amounts of valuable experimental data that may be readily exported into a standard and open format. Yet the publication of these data faces an important issue: Raw data are not made available instead, the information is slimed down into a string of characters (the list of peaks). Although historical limitations of technology explain this practice, it is not acceptable in the era of Internet. The idea of modernizing the strategy for sharing NMR data is not new, and some repositories exist, but sharing raw data is still not an established practice. Here, we present a powerful toolbox built on recent technologies that runs inside the browser and provides a means to store, share, analyse, and interact with original NMR data. Stored spectra can be streamlined into the publication pipeline, to improve the revision process for instance. The set of tools is still basic but is intended to be extended. The project is open source under the Massachusetts Institute of Technology (MIT) licence.
Direct low field J-edited diffusional proton NMR spectroscopic measurement of COVID-19 inflammatory biomarkers in human serum
Publisher: Royal Society of Chemistry (RSC)
Date: 2022
DOI: 10.1039/D2AN01097F
Abstract: A JEDI NMR pulse experiment incorporating relaxation, diffusion and J-modulation peak editing was implemented at a low field (80 MHz) spectrometer system to quantify two recently discovered plasma markers of SARS-CoV-2 infection and general inflammation.
Evaluation of photocatalytic disinfection of crude water for drinking-water production
Publisher: Elsevier BV
Date: 04-2002
Diffusion and Relaxation Edited Proton NMR Spectroscopy of Plasma Reveals a High-Fidelity Supramolecular Biomarker Signature of SARS-CoV-2 Infection
Publisher: American Chemical Society (ACS)
Date: 12-02-2021
Clinical prediction of wound re-epithelisation outcomes in non-severe burn injury using the plasma lipidome
Publisher: Cold Spring Harbor Laboratory
Date: 30-07-2023
DOI: 10.1101/2023.07.28.550938
Abstract: Impaired wound healing in burn injuries can lead to complications such as skin graft loss, infection, and increased risk of scarring, which impacts long-term patient outcomes and quality of life. While wound repair in severe burns has received substantial research attention, poor wound outcomes in cases of non- severe burns (classified as % of the total body surface area (TBSA)) remain relatively understudied despite also having considerable physiological impact and constituting the majority of hospital admissions for burns. Predicting outcomes in the early stages of healing would decrease financial and patient burden, and aid in preventing long-term complications from poor wound healing. Lipids have been implicated in inflammation and tissue repair processes and may play essential roles in burn wound healing. Longitudinal plasma s les were collected from patients (n=20) with non-severe ( % TBSA) flame or scald burns over a 6-week period including timepoints pre- and post-surgical intervention. S les were analysed using liquid chromatography-tandem mass spectrometry and nuclear magnetic resonance spectroscopy to detect 850 lipid species and 112 lipoproteins. Statistical analyses, including orthogonal projection to latent structures-discriminant analysis was performed to identify changes associated with either re-epithelialisation or delayed wound re-epithelisation. The results demonstrated that the plasma lipid and lipoprotein profiles at admission could predict wound re-epithelisation outcomes at two weeks post-surgery, and that these discriminatory profiles were maintained over a 6-week period. Triacylglycerides, diacylglycerides (DAG) and low density lipoprotein (LDL) subfractions were associated with delayed wound closure, with DAG(18:2_18:3) and LDL/High density lipoprotein (HDL) ratio having the most influence (p-value 0.02, Cliff’s delta 0.7), while HDL subfractions, phosphatidylinositols, phosphatidylcholines (PC), and phosphatidylserines were associated with re-epithelisation at two weeks post-surgery, with PC(16:0_18:1) and HDL-2 apolipoprotein-A1 showing the greatest influence on the model (p-value 0.01, Cliff’s delta -0.7). We demonstrate clinical prediction of wound re-epithelisation in non-severe burn patients using lipid and lipoprotein profiling. Further validation of the models will potentially lead to personalised intervention strategies to enhance injury outcomes, reducing the risk of chronic complications post-burn injury. Demonstration of wound healing prediction from time of hospital admission for non-severe burns. Plasma lipid and lipoprotein profiles within 48 hours of admission to hospital with non-severe burn injury are distinctly different between patients whose wounds re-epithelialized within two weeks and those with delayed re-epithelisation. Patients with delayed wound re-epithelisation have a persistent lipid and lipoprotein signature from burns admission up to six weeks post-injury.
1D and 2D NMR spectra of coffee from 27 countries
Publisher: GigaScience Press
Date: 21-04-2022
DOI: 10.46471/GIGABYTE.50
Abstract: Between 2012 and 2014, 715 green coffee s les were gathered by Almacafé S.A. (Bogotá, Colombia) from 27 countries. These were analysed at the nuclear magnetic resonance (NMR) laboratory at Universidad del Valle (Cali, Colombia). Over 1000 methanolic coffee extracts were prepared and 4563 spectra were acquired in a fully automatic manner using a 400 MHz NMR spectrometer (Bruker Biospin, Germany). The dataset spans the variance that could be expected for an industrial application of origin monitoring, including s les from different harvest times, collected over several years, and processed by at least two distinct operators. The resulting 1D and 2D spectra can be used to develop and evaluate feature extraction methods, multivariate algorithms, and automation monitoring techniques. They can also be used as datasets for teaching, or as a reference for new studies of similar s les and approaches.
Improving the efficiency of branch-and-bound complete-search NMR assignment using the symmetry of molecules and spectra
Publisher: AIP Publishing
Date: 17-02-2015
DOI: 10.1063/1.4907898
Abstract: Nuclear magnetic resonance (NMR) assignment of small molecules is presented as a typical ex le of a combinatorial optimization problem in chemical physics. Three strategies that help improve the efficiency of solution search by the branch and bound method are presented: 1. reduction of the size of the solution space by resort to a condensed structure formula, wherein symmetric nuclei are grouped together 2. partitioning of the solution space based on symmetry, that becomes the basis for an efficient branching procedure and 3. a criterion of selection of input restrictions that leads to increased gaps between branches and thus faster pruning of non-viable solutions. Although the ex les chosen to illustrate this work focus on small-molecule NMR assignment, the results are generic and might help solving other combinatorial optimization problems.
Structural Analysis from Classroom to Laboratory
Publisher: American Chemical Society (ACS)
Date: 31-05-2012
DOI: 10.1021/ED200476H
Effects of protein-pheromone complexation on correlated chemical shift modulations
Publisher: Springer Science and Business Media LLC
Date: 12-2005
DOI: 10.1007/S10858-005-3355-Y
Abstract: Major urinary protein (MUP) is a pheromone-carrying protein of the lipocalin family. Previous studies by isothermal titration calorimetry (ITC) show that the affinity of MUP for the pheromone 2-methoxy-3-isobutylpyrazine (IBMP) is mainly driven by enthalpy, with a small unfavourable entropic contribution. Entropic terms can be attributed in part to changes in internal motions of the protein upon binding. Slow internal motions can lead to correlated or anti-correlated modulations of the isotropic chemical shifts of carbonyl C' and amide N nuclei. Correlated chemical shift modulations (CSM/CSM) in MUP have been determined by measuring differences of the transverse relaxation rates of zero- and double-quantum coherences ZQC{C'N} and DQC{C'N}, and by accounting for the effects of correlated fluctuations of dipole-dipole couplings (DD/DD) and chemical shift anisotropies (CSA/CSA). The latter can be predicted from tensor parameters of C' and N nuclei that have been determined in earlier work. The effects of complexation on slow time-scale protein dynamics can be determined by comparing the temperature dependence of the relaxation rates of APO-MUP (i.e., without ligand) and HOLO-MUP (i.e., with IBMP as a ligand).
Incomplete systemic recovery and metabolic phenoreversion in Post-Acute-Phase nonhospitalized COVID-19 Patients: Implications for assessment of Post-Acute COVID-19 syndrome
Publisher: American Chemical Society (ACS)
Date: 19-05-2021
Multiple Reversible Dynamics of Pyrimidine Based Acylhydrazones
Publisher: Wiley
Date: 18-06-2020
Effect of Operational Parameters on the Cultivation of the Gut Microbiome in Continuous Bioreactors Inoculated with Feces: A Systematic Review
Publisher: American Chemical Society (ACS)
Date: 18-04-2023
Fully automatic assignment of small molecules' NMR spectra without relying on chemical shift predictions
Publisher: Wiley
Date: 06-06-2015
DOI: 10.1002/MRC.4272
Abstract: We present a method for the automatic assignment of small molecules' NMR spectra. The method includes an automatic and novel self-consistent peak-picking routine that validates NMR peaks in each spectrum against peaks in the same or other spectra that are due to the same resonances. The auto-assignment routine used is based on branch-and-bound optimization and relies predominantly on integration and correlation data chemical shift information may be included when available to fasten the search and shorten the list of viable assignments, but in most cases tested, it is not required in order to find the correct assignment. This automatic assignment method is implemented as a web-based tool that runs without any user input other than the acquired spectra.
A new method for the comparison of 1H NMR predictors based on tree-similarity of spectra
Publisher: Springer Science and Business Media LLC
Date: 25-03-2014
Abstract: A methodology based on spectral similarity is presented that allows to compare NMR predictors without the recourse to assigned experimental spectra, thereby making the task of benchmarking NMR predictors less tedious, faster, and less prone to human error. This approach was used to compare four popular NMR predictors using a dataset of 1000 molecules and their corresponding experimental spectra. The results found were consistent with those obtained by directly comparing deviations between predicted and experimental shifts.
Plasma lipoprotein subclass variation in middle-aged and older adults: Sex-stratified distributions and associations with health status and cardiometabolic risk factors
Publisher: Elsevier BV
Date: 07-2023
Triple quantum decoherence under multiple refocusing: Slow correlated chemical shift modulations of C′ and N nuclei in proteins
Publisher: Springer Science and Business Media LLC
Date: 03-2004
Characterization of diet-dependent temporal changes in circulating short-chain fatty acid concentrations: A randomized crossover dietary trial
Publisher: Elsevier BV
Date: 11-2022
DOI: 10.1093/AJCN/NQAB211
Evidence of slow motions by cross-correlated chemical shift modulation in deuterated and protonated proteins
Publisher: Springer Science and Business Media LLC
Date: 02-2004
Tutorials: A powerful source of knowledge transfer and inspiration
Publisher: Wiley
Date: 17-02-2020
DOI: 10.1002/MRC.5008
Decomposition of mixtures' spectra by multivariate curve resolution of rapidly acquired TOCSY experiments
Publisher: Wiley
Date: 26-07-2010
DOI: 10.1002/MRC.2654
Abstract: A method is presented that allows for retrieving 1D spectra of the in idual components of a mixture from a sparsely acquired 2D-TOCSY spectrum. The decomposition of the 2D-TOCSY data into pure 1D traces is achieved using a non-negative matrix factorization algorithm, also known as multivariate curve resolution analysis. Here, we show that the algorithm can be applied to data processed in the direct dimension only. Thus, our method can be applied to non-linearly s led experiments or data acquired with few indirect points. An ex le is shown for the spectra of a mixture of six amino acids, acquired in 15 min.
Insights into the associations between the gut microbiome, its metabolites, and heart failure
Publisher: American Physiological Society
Date: 12-2023
J-Edited DIffusional Proton Nuclear Magnetic Resonance Spectroscopic Measurement of Glycoprotein and Supramolecular Phospholipid Biomarkers of Inflammation in Human Serum
Publisher: American Chemical Society (ACS)
Date: 05-01-2022
DOI: 10.1021/ACS.ANALCHEM.1C04576
Abstract: Proton nuclear magnetic resonance (NMR)
Exploration of human serum lipoprotein supramolecular phospholipids using statistical heterospectroscopy in n-Dimensions (SHY-n): Identification of potential cardiovascular risk biomarkers related to SARS-CoV-2 infection
Publisher: American Chemical Society (ACS)
Date: 03-2022
DOI: 10.1021/ACS.ANALCHEM.1C05389
Abstract: SARS-CoV-2 infection causes a significant reduction in lipoprotein-bound serum phospholipids give rise to supramolecular phospholipid composite (SPC) signals observed in diffusion and relaxation edited
Related Organisations
Imperial College London
Location: United Kingdom of Great Britain and Northern Ireland
Related Funding Activities
No related grants have been discovered for Julien Wist.