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874 results on '"Wishart, D."'

1. Diet changes due to urbanization in South Africa are linked to microbiome and metabolome signatures of Westernization and colorectal cancer

Author

Ramaboli, M. C., Ocvirk, S., Khan Mirzaei, M., Eberhart, B. L., Valdivia-Garcia, M., Metwaly, A., Neuhaus, K., Barker, G., Ru, J., Nesengani, L. T., Mahdi-Joest, D., Wilson, A. S., Joni, S. K., Layman, D. C., Zheng, J., Mandal, R., Chen, Q., Perez, M. R., Fortuin, S., Gaunt, B., Wishart, D., Methé, B., Haller, D., Li, J. V., Deng, L., Swart, R., and O’Keefe, S. J. D.

Published
2024
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2. Competitive Fragmentation Modeling of ESI-MS/MS spectra for putative metabolite identification

Author

Allen, F., Greiner, R., and Wishart, D.

Subjects
Computer Science - Computational Engineering, Finance, and Science
Abstract

Electrospray tandem mass spectrometry (ESI-MS/MS) is commonly used in high throughput metabolomics. One of the key obstacles to the effective use of this technology is the difficulty in interpreting measured spectra to accurately and efficiently identify metabolites. Traditional methods for automated metabolite identification compare the target MS or MS/MS spectrum to the spectra in a reference database, ranking candidates based on the closeness of the match. However the limited coverage of available databases has led to an interest in computational methods for predicting reference MS/MS spectra from chemical structures. This work proposes a probabilistic generative model for the MS/MS fragmentation process, which we call Competitive Fragmentation Modeling (CFM), and a machine learning approach for learning parameters for this model from MS/MS data. We show that CFM can be used in both a MS/MS spectrum prediction task (ie, predicting the mass spectrum from a chemical structure), and in a putative metabolite identification task (ranking possible structures for a target MS/MS spectrum). In the MS/MS spectrum prediction task, CFM shows significantly improved performance when compared to a full enumeration of all peaks corresponding to substructures of the molecule. In the metabolite identification task, CFM obtains substantially better rankings for the correct candidate than existing methods (MetFrag and FingerID) on tripeptide and metabolite data, when querying PubChem or KEGG for candidate structures of similar mass., Comment: Preprint. The final publication is available at Springer via http://dx.doi.org/10.1007/s11306-014-0676-4. Metabolomics 2014

Published
2013
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32. A blood-based signature of cerebrospinal fluid A beta(1-42) status

Author

Goudey, B., Fung, B.J., Schieber, C., Faux, N.G., Weiner, M.W., Aisen, P., Petersen, R., Jack, C.R., Jagust, W., Trojanowki, J.Q., Toga, A.W., Beckett, L., Green, R.C., Saykin, A.J., Morris, J., Shaw, L.M., Kaye, J., Quinn, J., Silbert, L., Lind, B., Carter, R., Dolen, S., Schneider, L.S., Pawluczyk, S., Beccera, M., Teodoro, L., Spann, B.M., Brewer, J., Vanderswag, H., Fleisher, A., Heidebrink, J.L., Lord, J.L., Mason, S.S., Albers, C.S., Knopman, D., Johnson, K., Doody, R.S., Villanueva-Meyer, J., Chowdhury, M., Rountree, S., Dang, M., Stern, Y., Honig, L.S., Bell, K.L., Ances, B., Morris, J.C., Carroll, M., Creech, M.L., Franklin, E., Mintun, M.A., Schneider, S., Oliver, A., Marson, D., Griffth, R., Clark, D., Geldmacher, D., Brockington, J., Roberson, E., Natelson Love, M., Grossman, H., Mitsis, E., Shah, R.C., deToledo-Morrell, L., Duara, R., Varon, D., Greig, M.T., Roberts, P., Albert, M., Onyike, C., D'Agostino, D., Kielb, S., Galvin, J.E., Cerbone, B., Michel, C.A., Pogorelec, D.M., Rusinek, H., Leon, M.J. de, Glodzik, L., De Santi, S., Doraiswamy, P.M., Petrella, J.R., Borges-Neto, S., Wong, T.Z., Coleman, E., Smith, C.D., Jicha, G., Hardy, P., Sinha, P., Oates, E., Conrad, G., Porsteinsson, A.P., Goldstein, B.S., Martin, K., Makino, K.M., Ismail, M.S., Brand, C., Mulnard, R.A., Thai, G., McAdams-Ortiz, C., Womack, K., Mathews, D., Quiceno, M., Levey, A.I., Lah, J.J., Cellar, J.S., Burns, J.M., Swerdlow, R.H., Brooks, W.M., Apostolova, L., Tingus, K., Woo, E., Silverman, D.H.S., Lu, P.H., Bartzokis, G., Graff-Radford, N.R., Parftt, F., Kendall, T., Johnson, H., Farlow, M.R., Hake, A.M., Matthews, B.R., Brosch, J.R., Herring, S., Hunt, C., Dyck, .H. van, Carson, R.E., MacAvoy, M.G., Varma, P., Chertkow, H., Bergman, H., Hosein, C., Black, S., Stefanovic, B., Caldwell, C., Hsiung, Ging-Yuek Robin, Feldman, H., Mudge, B., Assaly, M., Finger, E., Pasternack, S., Rachisky, I., Trost, D., Kertesz, A., Bernick, C., Munic, D., Mesulam, M.-M., Lipowski, K., Weintraub, S., Bonakdarpour, B., Kerwin, D., Wu, C.-K., Johnson, N., Sadowsky, C., Villena, T., Turner, R.S., Reynolds, B., Sperling, R.A., Johnson, K.A., Marshall, G., Yesavage, J., Taylor, J.L., Lane, B., Rosen, A., Tinklenberg, J., Sabbagh, M.N., Belden, C.M., Jacobson, S.A., Sirrel, S.A., Kowall, N., Killiany, R., Budson, A.E., Norbash, A., Johnson, P.L., Obisesan, T.O., Wolday, S., Allard, J., Lerner, A., Ogrocki, P., Tatsuoka, C., Fatica, P., Fletcher, E., Maillard, P., Olichney, J., DeCarli, C., Carmichael, O., Kittur, S., Borrie, M., Lee, T.-Y., Bartha, R., Johnson, S., Asthana, S., Carlsson, C.M., Potkin, S.G., Preda, A., Nguyen, D., Tariot, P., Burke, A., Trncic, N., Reeder, S., Bates, V., Capote, H., Rainka, M., Scharre, D.W., Kataki, M., Adeli, A., Zimmerman, E.A., Celmins, D., Brown, A.D., Pearlson, G.D., Blank, K., Anderson, K., Flashman, L.A., Seltzer, M., Hynes, M.L., Santulli, R.B., Sink, K.M., Gordineer, L., Williamson, J.D., Garg, P., Watkins, F., Ott, B.R., Querfurth, H., Tremont, G., Salloway, S., Malloy, P., Correia, S., Rosen, H.J., Miller, B.L., Perry, D., Mintzer, J., Spicer, K., Bachman, D., Pomara, N., Hernando, R., Sarrael, A., Relkin, N., Chaing, G., Lin, M., Ravdin, L., Smith, A., Raj, B.A., Fargher, K., Saykin, A., Nho, K., Kling, M., Toledo, J., Shaw, L., Trojanowski, J., Farrer, L., Kastsenmueller, G., Arnold, M., Wishart, D., Wurtz, P., Bhattcharyya, S., Duijin, C. van, Mangravite, L., Han, X., Hankemeier, T., Fiehn, O., Barupal, D., Thiele, I., Heinken, A., Meikle, P., Price, N., Funk, C., Jia, W., Kueider-Paisley, A., Tenebaum, J., Black, C., Moseley, A., Thompson, W., Mahmoudiandehkorki, S., Baillie, R., Welsh-Bohmer, K., Plassman, B., and Epidemiology

Subjects
Male, 0301 basic medicine, Apolipoprotein E, Oncology, medicine.medical_specialty, Amyloid, Amyloid beta, lcsh:Medicine, Article, 03 medical and health sciences, Apolipoproteins E, 0302 clinical medicine, Cerebrospinal fluid, Alzheimer Disease, Predictive Value of Tests, Internal medicine, medicine, Humans, Dementia, Cognitive decline, lcsh:Science, Aged, Aged, 80 and over, Amyloid beta-Peptides, Multidisciplinary, biology, Chemokine CCL26, business.industry, lcsh:R, Alzheimer’s Disease Metabolomics Consortium, Alzheimer’s Disease Neuroimaging Initiative, medicine.disease, Peptide Fragments, 3. Good health, 030104 developmental biology, biology.protein, Chromogranin A, Female, lcsh:Q, Alzheimer's disease, business, Biomarkers, 030217 neurology & neurosurgery, Alzheimer's Disease Neuroimaging Initiative
Abstract

It is increasingly recognized that Alzheimer’s disease (AD) exists before dementia is present and that shifts in amyloid beta occur long before clinical symptoms can be detected. Early detection of these molecular changes is a key aspect for the success of interventions aimed at slowing down rates of cognitive decline. Recent evidence indicates that of the two established methods for measuring amyloid, a decrease in cerebrospinal fluid (CSF) amyloid β1−42 (Aβ1−42) may be an earlier indicator of Alzheimer’s disease risk than measures of amyloid obtained from Positron Emission Tomography (PET). However, CSF collection is highly invasive and expensive. In contrast, blood collection is routinely performed, minimally invasive and cheap. In this work, we develop a blood-based signature that can provide a cheap and minimally invasive estimation of an individual’s CSF amyloid status using a machine learning approach. We show that a Random Forest model derived from plasma analytes can accurately predict subjects as having abnormal (low) CSF Aβ1−42 levels indicative of AD risk (0.84 AUC, 0.78 sensitivity, and 0.73 specificity). Refinement of the modeling indicates that only APOEε4 carrier status and four plasma analytes (CGA, Aβ1−42, Eotaxin 3, APOE) are required to achieve a high level of accuracy. Furthermore, we show across an independent validation cohort that individuals with predicted abnormal CSF Aβ1−42 levels transitioned to an AD diagnosis over 120 months significantly faster than those with predicted normal CSF Aβ1−42 levels and that the resulting model also validates reasonably across PET Aβ1−42 status (0.78 AUC). This is the first study to show that a machine learning approach, using plasma protein levels, age and APOEε4 carrier status, is able to predict CSF Aβ1−42 status, the earliest risk indicator for AD, with high accuracy.

Published
2019

34. Identifying client project manager competency in Indonesian construction project

Author

Marto, A, Olivia, M, Ridwan, R, Andrio, D, Wishart, D, Saputra, E, Yamamoto, K, Wibisono, G, Pringgana, G, Agus Ariawan, I M, Infantri Yekti, M, Ketut Sudarsana, I D, Negara, Kartika Puspa, Lamari, Fiona, Susilawati, Connie, Trigunarsyah, Bambang, Marto, A, Olivia, M, Ridwan, R, Andrio, D, Wishart, D, Saputra, E, Yamamoto, K, Wibisono, G, Pringgana, G, Agus Ariawan, I M, Infantri Yekti, M, Ketut Sudarsana, I D, Negara, Kartika Puspa, Lamari, Fiona, Susilawati, Connie, and Trigunarsyah, Bambang

Abstract

The influence of active client involvement towards project construction success is gaining recognition in the last few decades. The growing concern on the client involvement has drifted the perception towards client away from the passive role into contributor of project success. During client involvement in the construction project, a representative from client or client project manager (CPM) should be complemented with certain competencies in order to succeed in commissioning construction projects. Evidence shows that some public construction projects in Indonesia failed due to the lack of competency of client project managers. Whilst most of the previous studies concern on the competency of general project managers, this paper specifically investigates competency of project manager from client side who works as a civil servant and commissioning public construction sectors. This paper aims to identify the important competencies required by CPM in construction projects in Indonesia and examine current Indonesian CPM competency standard. Relative Importance Index (RII) was employed to assess the important level of competencies. The findings will enrich understanding on client project manager competency and become a basis to undergird further empirical research in client project manager development areas.

Published
2019

35. Systems Biology and Multi-Omics Integration: Viewpoints from the Metabolomics Research Community

Author

Pinu, FR, Beale, DJ, Paten, AM, Kouremenos, K, Swarup, S, Schirra, HJ, Wishart, D, Pinu, FR, Beale, DJ, Paten, AM, Kouremenos, K, Swarup, S, Schirra, HJ, and Wishart, D

Abstract

The use of multiple omics techniques (i.e., genomics, transcriptomics, proteomics, and metabolomics) is becoming increasingly popular in all facets of life science. Omics techniques provide a more holistic molecular perspective of studied biological systems compared to traditional approaches. However, due to their inherent data differences, integrating multiple omics platforms remains an ongoing challenge for many researchers. As metabolites represent the downstream products of multiple interactions between genes, transcripts, and proteins, metabolomics, the tools and approaches routinely used in this field could assist with the integration of these complex multi-omics data sets. The question is, how? Here we provide some answers (in terms of methods, software tools and databases) along with a variety of recommendations and a list of continuing challenges as identified during a peer session on multi-omics integration that was held at the recent 'Australian and New Zealand Metabolomics Conference' (ANZMET 2018) in Auckland, New Zealand (Sept. 2018). We envisage that this document will serve as a guide to metabolomics researchers and other members of the community wishing to perform multi-omics studies. We also believe that these ideas may allow the full promise of integrated multi-omics research and, ultimately, of systems biology to be realized.

Published
2019

37. Enhancement of mixing in high-speed heated jets using a counterflowing nozzle

Author

Strykowski, P.J., Krothapalli, A., and Wishart, D.

Subjects
Jets -- Fluid dynamics, Nozzles -- Usage, Aerodynamics, Supersonic -- Research, Aerodynamics -- Research, Aerospace and defense industries, Business
Abstract

A collar was placed around a converging nozzle and suction was applied to it to simulate counterflowing streams in the proximity of the jet. This was conducted in a study of the effect of annular counter flow on mixing of high-speed subsonic jets and underexpanded supersonic jets. Primary jet was operated between 0.4 and 1.2 exit Mach numbers for temperatures ranging between 20 and 400 degrees centigrade. Moderate levels of counterflow increased mixing between jet and surrounding flow.

Published
1993

38. The chemical shift index: a fast and simple method for the assigment of protein secondary structure through NMR spectroscopy

Author

Wishart, D. S., Sykes, B.D., and Richards, F.M.

Subjects
Proteins -- Structure, Nuclear magnetic resonance spectroscopy -- Evaluation, Biological sciences, Chemistry
Abstract

A study was done on a new method for secondary structure determination based on chemical shift propensity. The method is similar to a digital filtration technique where measured chemical shifts are filtered using preassigned threshold. This produces easily interpretable description of chemical shifts and better visual presentation compared to conventional data-smoothing techniques.

Published
1992

47. Unraveling the unknown areas of the human metabolome: the role of infrared ion spectroscopy

Author

Martens, J.K., Berden, G., Bentlage, Herman, Coene, K.L.M., Engelke, U.F., Wishart, D., Scherpenzeel, M. van, Kluijtmans, L.A., Wevers, R.A., Oomens, J., Martens, J.K., Berden, G., Bentlage, Herman, Coene, K.L.M., Engelke, U.F., Wishart, D., Scherpenzeel, M. van, Kluijtmans, L.A., Wevers, R.A., and Oomens, J.

Abstract

Contains fulltext : 191841.pdf (Publisher’s version ) (Open Access)

Published
2018

48. FoodComEx - a chemical library for food compounds and related metabolites

Author

Manach, Claudine, Weinert, C., Pujos-Guillot, Estelle, Ulaszewska, M., Giacomoni, Franck, Mattivi, F., Urpi-Sarda, M., Andres-Lacueva, C., Kulling, S.E., Dragsted, L.O., Wishart, D., Fiamoncini, Jarlei, Unité de Nutrition Humaine (UNH), Institut National de la Recherche Agronomique (INRA)-Université Clermont Auvergne [2017-2020] (UCA [2017-2020]), Max Rubner-Institut, Centro Ricerca e Innovazione, Fondazione Edmund Mach, Instituto Agrario S. Michele all' Adige, University of Barcelona, University of Copenhagen = Københavns Universitet (KU), University of Alberta, and University of Copenhagen = Københavns Universitet (UCPH)

Subjects
[SDV]Life Sciences [q-bio], ComputingMilieux_MISCELLANEOUS
Abstract

International audience

Published
2017

49. Supersonic jet control via point disturbances inside the nozzle

Author

Wishart, D. P, Krothapalli, A, and Mungal, M. G

Subjects
Aerodynamics
Abstract

Experiments on supersonic jet control via point disturbances inside the nozzle were conducted using a pressure-matched converging-diverging nozzle with an exit diameter of 3.11 cm and an exit Mach number of 2.1. The disturbance generators are situated on the supersonic nozzle wall between the throat and the jet exit plane; the resulting fluid-mechanical disturbances are observed at the intersection of the disturbance cone and the jet lip. It is demonstrated that a single disturbance generator leads to a polygonal jet appearance, while two symmetric disturbances lead to a symmetric rectangular jet shape and two nonsymmetric disturbances lead to a star-like appearance. Significant cusps are formed in all cases.

Published
1993

50. Urinary metabolomics fingerprinting around parturition identifies metabolites that differentiate lame dairy cows from healthy ones.

Author

Eckel, E. F., Zhang, G., Dervishi, E., Zwierzchowski, G., Mandal, R., Wishart, D. S., and Ametaj, B. N.

Abstract

Lameness is a very important disorder of periparturient dairy cows with implications on milk production and composition as well as with consequences on reproductive performance. The aetiology of lameness is not clear although there have been various hypotheses suggested over the years. The objective of this study was to metabotype the urine of dairy cows prior to, during and after the onset of lameness by evaluating at weeks −8, −4 pre-calving, the week of lameness diagnosis, and +4 and +8 weeks post-calving. We used a metabolomics approach to analyse urine samples collected from dairy cows around calving (6 cows with lameness v. 20 healthy control cows). A total of 153 metabolites were identified and quantified using an in-house MS library and classified into 6 groups including: 11 amino acids (AAs), 39 acylcarnitines (ACs), 3 biogenic amines (BAs), 84 glycerophospholipids, 15 sphingolipids and hexose. A total of 23, 36, 40, 23 and 49 metabolites were observed to be significantly different between the lame and healthy cows at −8 and −4 weeks pre-calving, week of lameness diagnosis as well as at +4 and +8 weeks post-calving, respectively. It should be noted that most of the identified metabolites were elevated; however, a few of them were also lower in lame cows. Overall, ACs and glycerophospholipids, specifically phosphatidylcholines (PCs), were the metabolite groups displaying the strongest differences in the urine of pre-lame and lame cows. Lysophosphatidylcholines (LysoPCs), although to a lesser extent than PCs, were altered at all time points. Alterations in urinary AA concentrations were also observed during the current study for four time points. During the pre-calving period, there was an observed elevation of arginine (−8 week), tyrosine (−8 week) and aspartate (−4 week), as well as a depression of urinary glutamate (−4 weeks). In the current study, it was additionally observed that concentrations of several sphingomyelins and one BA were altered in pre-lame and lame cows. Symmetric dimethylarginine was elevated at both −8 weeks pre-calving and the week of lameness diagnosis. Data showed that urinary fingerprinting might be a reliable methodology to be used in the future to differentiate lame cows from healthy ones. [ABSTRACT FROM AUTHOR]

Published
2020
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