GC/HRMS Analysis of E‑Liquids Complements In Vivo Modeling Methods and can Help to Predict Toxicity
收藏NIAID Data Ecosystem2026-05-02 收录
下载链接:
https://figshare.com/articles/dataset/GC_HRMS_Analysis_of_E_Liquids_Complements_In_Vivo_Modeling_Methods_and_can_Help_to_Predict_Toxicity/25976287
下载链接
链接失效反馈官方服务:
资源简介:
Tobacco smoking is a major risk factor for disease development,
with the user inhaling various chemicals known to be toxic. However,
many of these chemicals are absent before tobacco is “burned”.
Similar, detailed data have only more recently being reported for
the e-cigarette with regards to chemicals present before and after
the e-liquid is “vaped.” Here, zebrafish were dosed
with vaped e-liquids, while C57-BL/6J mice were vaped using nose-cone
only administration. Preliminary assessments were made using e-liquids
and GC/HRMS to identify chemical signatures that differ between unvaped/vaped
and flavored/unflavored samples. Oxidative stress and inflammatory
immune cell response assays were then performed using our in vivo
models. Chemical signatures differed, e.g., between unvaped/vaped
samples and also between unflavored/flavored e-liquids, with known
chemical irritants upregulated in vaped and unvaped flavored e-liquids
compared with unflavored e-liquids. However, when possible respiratory
irritants were evaluated, these agents were predominantly present
in only the vaped e-liquid. Both oxidative stress and inflammatory
responses were induced by a menthol-flavored but not a tobacco-flavored
e-liquid. Thus, chemical signatures differ between unvaped versus
vaped e-liquid samples and also between unflavored versus flavored
e-liquids. These flavors also likely play a significant role in the
variability of e-liquid characteristics, e.g., pro-inflammatory and/or
cytotoxic responses.
创建时间:
2024-06-05



