Literature DB >> 27212803

Towards point of care testing for C. difficile infection by volatile profiling, using the combination of a short multi-capillary gas chromatography column with metal oxide sensor detection.

N D McGuire1, R J Ewen1, B de Lacy Costello1, C E Garner1, C S J Probert2, K Vaughan1, N M Ratcliffe1.   

Abstract

Rapid volatile profiling of stool sample headspace was achieved using a combination of short multi-capillary chromatography column (SMCC), highly sensitive heated metal oxide semiconductor (MOS) sensor and artificial neural network (ANN) software. For direct analysis of biological samples this prototype offers alternatives to conventional GC detectors and electronic nose technology. The performance was compared to an identical instrument incorporating a long single capillary column (LSCC). The ability of the prototypes to separate complex mixtures was assessed using gas standards and homogenised in house 'standard' stool samples, with both capable of detecting more than 24 peaks per sample. The elution time was considerably faster with the SMCC resulting in a run time of 10 minutes compared to 30 minutes for the LSCC. The diagnostic potential of the prototypes was assessed using 50 C. difficile positive and 50 negative samples. The prototypes demonstrated similar capability of discriminating between positive and negative samples with sensitivity and specificity of 85% and 80% respectively. C. difficile is an important cause of hospital acquired diarrhoea, with significant morbidity and mortality around the world. A device capable of rapidly diagnosing the disease at the point of care would reduce cases, deaths and financial burden.

Entities:  

Keywords:  Clostridium difficile; artificial neural network; gas chromatography; gastro-intestinal; metal oxide semiconductor; multicapillary column; sensor; stool; volatile

Year:  2014        PMID: 27212803      PMCID: PMC4874467          DOI: 10.1088/0957-0233/25/6/065108

Source DB:  PubMed          Journal:  Meas Sci Technol        ISSN: 0957-0233            Impact factor:   2.046


  23 in total

1.  Laboratory diagnosis of Clostridium difficile infection: in a state of transition or confusion or both?

Authors:  M H Wilcox
Journal:  J Hosp Infect       Date:  2011-07-19       Impact factor: 3.926

Review 2.  Overcoming barriers to effective recognition and diagnosis of Clostridium difficile infection.

Authors:  M H Wilcox
Journal:  Clin Microbiol Infect       Date:  2012-12       Impact factor: 8.067

3.  Production of volatile organic compounds by mycobacteria.

Authors:  Ruth McNerney; Kim Mallard; Phyllis Ifeoma Okolo; Claire Turner
Journal:  FEMS Microbiol Lett       Date:  2012-01-16       Impact factor: 2.742

4.  Volatile organic compounds from feces and their potential for diagnosis of gastrointestinal disease.

Authors:  Catherine E Garner; Stephen Smith; Ben de Lacy Costello; Paul White; Robert Spencer; Chris S J Probert; Norman M Ratcliffe
Journal:  FASEB J       Date:  2007-02-21       Impact factor: 5.191

5.  Fecal microbiome and volatile organic compound metabolome in obese humans with nonalcoholic fatty liver disease.

Authors:  Maitreyi Raman; Iftikhar Ahmed; Patrick M Gillevet; Chris S Probert; Norman M Ratcliffe; Steve Smith; Rosemary Greenwood; Masoumeh Sikaroodi; Victor Lam; Pam Crotty; Jennifer Bailey; Robert P Myers; Kevin P Rioux
Journal:  Clin Gastroenterol Hepatol       Date:  2013-02-27       Impact factor: 11.382

6.  Application of ion mobility spectrometry for the detection of human urine.

Authors:  Joanna Rudnicka; Paweł Mochalski; Agapios Agapiou; Milt Statheropoulos; Anton Amann; Bogusław Buszewski
Journal:  Anal Bioanal Chem       Date:  2010-09-05       Impact factor: 4.142

7.  Headspace-multicapillary column-ion mobility spectrometry for the direct analysis of 2,4,6-trichloroanisole in wine and cork samples.

Authors:  Isabel Márquez-Sillero; Soledad Cárdenas; Miguel Valcárcel
Journal:  J Chromatogr A       Date:  2012-09-29       Impact factor: 4.759

Review 8.  Metal oxide semi-conductor gas sensors in environmental monitoring.

Authors:  George F Fine; Leon M Cavanagh; Ayo Afonja; Russell Binions
Journal:  Sensors (Basel)       Date:  2010-06-01       Impact factor: 3.576

9.  Electronic nose based on independent component analysis combined with partial least squares and artificial neural networks for wine prediction.

Authors:  Teodoro Aguilera; Jesús Lozano; José A Paredes; Fernando J Alvarez; José I Suárez
Journal:  Sensors (Basel)       Date:  2012-06-11       Impact factor: 3.576

10.  Comparison of a frozen human foreskin fibroblast cell assay to an enzyme immunoassay and toxigenic culture for the detection of toxigenic Clostridium difficile.

Authors:  Alastair J Strachan; Natalie E Evans; O Martin Williams; Robert C Spencer; Rosemary Greenwood; Chris J Probert
Journal:  Diagn Microbiol Infect Dis       Date:  2012-10-26       Impact factor: 2.803

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  5 in total

1.  The use of a gas chromatography-sensor system combined with advanced statistical methods, towards the diagnosis of urological malignancies.

Authors:  Raphael B M Aggio; Ben de Lacy Costello; Paul White; Tanzeela Khalid; Norman M Ratcliffe; Raj Persad; Chris S J Probert
Journal:  J Breath Res       Date:  2016-02-11       Impact factor: 3.262

Review 2.  Application of Electronic-Nose Technologies and VOC-Biomarkers for the Noninvasive Early Diagnosis of Gastrointestinal Diseases .

Authors:  Alphus Dan Wilson
Journal:  Sensors (Basel)       Date:  2018-08-09       Impact factor: 3.576

3.  Faecal volatile biomarkers of Clostridium difficile infection.

Authors:  Mitesh Patel; Dawn Fowler; Jeremy Sizer; Christopher Walton
Journal:  PLoS One       Date:  2019-04-15       Impact factor: 3.240

4.  A targeted metabolomic protocol for quantitative analysis of volatile organic compounds in urine of children with celiac disease.

Authors:  Natalia Drabińska; Hafiz Abdul Azeem; Urszula Krupa-Kozak
Journal:  RSC Adv       Date:  2018-10-29       Impact factor: 4.036

5.  Machine Learning Approaches to Identify Discriminative Signatures of Volatile Organic Compounds (VOCs) from Bacteria and Fungi Using SPME-DART-MS.

Authors:  Mehak Arora; Stephen C Zambrzycki; Joshua M Levy; Annette Esper; Jennifer K Frediani; Cassandra L Quave; Facundo M Fernández; Rishikesan Kamaleswaran
Journal:  Metabolites       Date:  2022-03-08
  5 in total

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