Selected article for: "classifier machine learning and machine learning"

Author: Ganesan, Sukirth M; Dabdoub, Shareef M; Nagaraja, Haikady N; Scott, Michelle L; Pamulapati, Surya; Berman, Micah L; Shields, Peter G; Wewers, Mary Ellen; Kumar, Purnima S
Title: Adverse effects of electronic cigarettes on the disease-naive oral microbiome.
  • Cord-id: pryajg1m
  • Document date: 2020_5_1
  • ID: pryajg1m
    Snippet: Six percent of Americans, including 3 million high schoolers, use e-cigarettes, which contain potentially toxic substances, volatile organic compounds, and metals. We present the first human study on the effects of e-cigarette exposure in the oral cavity. By interrogating both immunoinflammatory responses and microbial functional dynamics, we discovered pathogen overrepresentation, higher virulence signatures, and a brisk proinflammatory signal in clinically healthy e-cigarette users, equivalent
    Document: Six percent of Americans, including 3 million high schoolers, use e-cigarettes, which contain potentially toxic substances, volatile organic compounds, and metals. We present the first human study on the effects of e-cigarette exposure in the oral cavity. By interrogating both immunoinflammatory responses and microbial functional dynamics, we discovered pathogen overrepresentation, higher virulence signatures, and a brisk proinflammatory signal in clinically healthy e-cigarette users, equivalent to patients with severe periodontitis. Using RNA sequencing and confocal and electron microscopy to validate these findings, we demonstrate that the carbon-rich glycol/glycerol vehicle is an important catalyst in transforming biofilm architecture within 24 hours of exposure. Last, a machine-learning classifier trained on the metagenomic signatures of e-cigarettes identified as e-cigarette users both those individuals who used e-cigarettes to quit smoking, and those who use both e-cigarettes and cigarettes. The present study questions the safety of e-cigarettes and the harm reduction narrative promoted by advertising campaigns.

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