A Method for Amending Loose Smokeless Tobacco With Menthol for Administration in Clinical Studies
Bibliographic record
Abstract
INTRODUCTION: Menthol has long been incorporated as a flavor additive in tobacco products and can impact use behaviors. Despite its inclusion in some of the most popular flavored smokeless tobacco (ST) products (eg, "mint" flavored products), few studies have systematically investigated the impact of menthol on ST use behaviors in prospective empirical studies. Rigorous investigation of ST menthol content on behavioral and physiological outcomes requires ST products with stable and precise levels of menthol; however, commercial product composition variability prevents product comparisons when evaluating the effects of systematic changes in menthol content on clinical outcomes. AIMS AND METHODS: We developed amended loose moist snuff ST products by treating commercially available, unflavored loose ST with an ethanol-based menthol spiking solution or a nonmentholated ethanol control solution to develop test products with different levels of menthol: 0, 1, 3, and 5 mg menthol/g tobacco. We evaluated the stability of menthol content in these products over 24 months and evaluated menthol exposure associated with the products through pharmacokinetic analysis of plasma menthol-glucuronide in human participants (n = 22). RESULTS: Menthol content of the amended products was on target, homogenous, and stable for up to 24 months. Menthol exposure (menthol-glucuronide Cmax and AUC) significantly differed between each test product. CONCLUSIONS: These data suggest that stable products with nonoverlapping menthol content can be developed using a menthol spiking solution and can be subsequently administered for clinical assessments of mentholated loose ST. IMPLICATIONS: The results from this study suggest that a menthol spiking solution can be used to mentholate unflavored, loose ST to a target menthol content. With this method, the ST menthol content was stable for at least 24 months, and the products exposed users to menthol in a dose-dependent manner. This method yielded loose ST products with precise, stable levels of menthol to allow systematic evaluation of ST menthol content on clinical outcomes. The method may have applications for systematically evaluating changes in other tobacco product ingredients.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.013 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.004 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".