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10.1186/s40168-017-0368-1 http://scihub22266oqcxt.onion/10.1186/s40168-017-0368-1 C5684761!5684761!29132405     free     free     free Deprecated: Implicit conversion from float 233.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 233.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 233.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 233.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 233.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 233.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 233.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 267.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 267.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       Microbiome 2017 ; 5 (ä): ä Nephropedia Template TP {{tp|p=29132405|t=2017. Identifying predictive features of Clostridium difficile infection recurrence before, during, and after primary antibiotic treatment |pdf=|usr=}}{{29132405}} gab.com Text Identifying predictive features of Clostridium difficile infection recurrence before, during, and after primary antibiotic treatment JO: Microbiome http://www.kidney.de/pget.php?&tw=1&pmid=29132405 #FOAvip Background: Colonization by the pathogen Clostridium difficile often occurs in the background of a disrupted microbial community. Identifying specific organisms conferring resistance to invasion by C. difficile is desirable because diagnostic and therapeutic strategies based on the human microbiota have the potential to provide more precision to the management and treatment of Clostridium difficile infection (CDI) and its recurrence. Methods: We conducted a longitudinal study of adult patients diagnosed with their first CDI. We investigated the dynamics of the gut microbiota during antibiotic treatment, and we used microbial or demographic features at the time of diagnosis, or after treatment, to predict CDI recurrence. To check the validity of the predictions, a meta-analysis using a previously published dataset was performed. Results: We observed that patients? microbiota ?before? antibiotic treatment was predictive of disease relapse, but surprisingly, post-antibiotic microbial community is indistinguishable between patients that recur or not. At the individual OTU level, we identified Veillonella dispar as a candidate organism for preventing CDI recurrence; however, we did not detect a corresponding signal in the conducted meta-analysis. Conclusion: Although in our patient population, a candidate organism was identified for negatively predicting CDI recurrence, results suggest the need for larger cohort studies that include patients with diverse demographic characteristics to generalize species that robustly confer colonization resistance against C. difficile and accurately predict disease relapse. Electronic supplementary material: The online version of this article (10.1186/s40168-017-0368-1) contains supplementary material, which is available to authorized users. Twit Text FOAVip Identifying predictive features of Clostridium difficile infection recurrence before, during, and after primary antibiotic treatment ????Microbiome http://www.kidney.de/pget.php?&tw=1&pmid=29132405 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=29132405 #FOAvip English Wikipedia <ref>{{Cite pmid|29132405}}</ref> Identifying predictive features of Clostridium difficile infection recurrence before, during, and after primary antibiotic treatment #MMPMID29132405 Pakpour S; Bhanvadia A; Zhu R; Amarnani A; Gibbons SM; Gurry T; Alm EJ; Martello LA Microbiome 2017[]; 5 (ä): ä PMID29132405show ga Background: Colonization by the pathogen Clostridium difficile often occurs in the background of a disrupted microbial community. Identifying specific organisms conferring resistance to invasion by C. difficile is desirable because diagnostic and therapeutic strategies based on the human microbiota have the potential to provide more precision to the management and treatment of Clostridium difficile infection (CDI) and its recurrence. Methods: We conducted a longitudinal study of adult patients diagnosed with their first CDI. We investigated the dynamics of the gut microbiota during antibiotic treatment, and we used microbial or demographic features at the time of diagnosis, or after treatment, to predict CDI recurrence. To check the validity of the predictions, a meta-analysis using a previously published dataset was performed. Results: We observed that patients? microbiota ?before? antibiotic treatment was predictive of disease relapse, but surprisingly, post-antibiotic microbial community is indistinguishable between patients that recur or not. At the individual OTU level, we identified Veillonella dispar as a candidate organism for preventing CDI recurrence; however, we did not detect a corresponding signal in the conducted meta-analysis. Conclusion: Although in our patient population, a candidate organism was identified for negatively predicting CDI recurrence, results suggest the need for larger cohort studies that include patients with diverse demographic characteristics to generalize species that robustly confer colonization resistance against C. difficile and accurately predict disease relapse. Electronic supplementary material: The online version of this article (10.1186/s40168-017-0368-1) contains supplementary material, which is available to authorized users. äIdentifying predictive features of Clostridium difficile infection rec(epmc).pdf DeepDyve Pubget Overpricing