Modeling new immunoregulatory therapeutics as antimicrobial alternatives for treating Clostridium difficile infection.
The current treatment paradigm in Clostridium difficile infection is the administration of antibiotics contributing to the high rates of recurrent infections. Recent alternative strategies, such as fecal microbiome transplantation and anti-toxin antibodies, have shown similar efficacy in the treatme...
| Publicado en: | Artificial Intelligence in Medicine Vol. 78; pp. 1 - 14 |
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| Autores principales: | , , , , , , |
| Formato: | research Journal Article |
| Publicado: |
Elsevier B.V.
May2017
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=124382559&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 124382559 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 09333657 3HY jtl: Artificial Intelligence in Medicine issn: 09333657 maglogo: N pubinfo: dt: May2017 vid: 78 pid: 1004 pub: Elsevier B.V. artinfo: ui: 124382559 124382559 NLM28764868 124382559 10.1016/j.artmed.2017.05.003 NLM28764868 124382559 ppf: 1 ppct: 13 formats: tig: atl: Modeling new immunoregulatory therapeutics as antimicrobial alternatives for treating Clostridium difficile infection. aug: au: Leber, Andrew Hontecillas, Raquel Abedi, Vida Tubau-Juni, Nuria Zoccoli-Rodriguez, Victoria Stewart, Caroline Bassaganya-Riera, Josep affil: Nutritional Immunology and Molecular Medicine Laboratory 1 , Biocomplexity Institute, Virginia Tech, Blacksburg, VA, United States sug: subj: Clostridioides Difficile Clostridium Infections Therapy Animal Studies Antiinfective Agents Antibiotics Therapeutic Use Computer Simulation Microbiologic Phenomena ab: The current treatment paradigm in Clostridium difficile infection is the administration of antibiotics contributing to the high rates of recurrent infections. Recent alternative strategies, such as fecal microbiome transplantation and anti-toxin antibodies, have shown similar efficacy in the treatment of C. difficile associated disease (CDAD). However, barriers exist for either treatment or other novel treatments to displace antibiotics as the standard of care. To aid in the comparison of these and future treatments in CDAD, we developed an in silico pipeline to predict clinical efficacy with nonclinical results. The pipeline combines an ordinary differential equation (ODE)-based model, describing the immunological and microbial interactions in the gastrointestinal (GI) mucosa, with machine learning algorithms to translate simulated output quantities (i.e. time of clearance, quantity of commensal bacteria, T cell ratios) into clinical predictions based on prior preclinical, translational and clinical trial data. As a use case, we compare the efficacy of lanthionine synthetase C-like 2 (LANCL2), a novel immunoregulatory target with promising efficacy in inflammatory bowel disease (IBD), activation with antibiotics, fecal microbiome transplantation and anti-toxin antibodies in the treatment of CDAD. We further validate the potential of LANCL2 pathway activation, in a mouse model of C. difficile infection in which it displays an ability to decrease weight loss and inflammatory cell types while protecting against mortality. The computational pipeline can serve as an important resource in the development of new treatment modalities. pubtype: Academic Journal doctype: research Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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