Smoking-induced microbial dysbiosis in health and disease
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Smoking is associated with an increased risk of cancer, pulmonary and cardiovascular diseases, but the precise mechanisms by which such risk is mediated remain poorly understood. Additionally, smoking can impact the oral, nasal, oropharyngeal, lung and gut microbiome composition, function, and secreted molecule repertoire. Microbiome changes induced by smoking can bear direct consequences on smoking-related illnesses. Moreover, smoking-associated dysbiosis may modulate weight gain development following smoking cessation. Here, we review the implications of cigarette smoking on microbiome community structure and function. In addition, we highlight the potential impacts of microbial dysbiosis on smoking-related diseases. We discuss challenges in studying host-microbiome interactions in the context of smoking, such as the correlations with smoking-related disease severity versus causation and mechanism. In all, understanding the microbiome's role in the pathophysiology of smoking-related diseases may promote the development of rational therapies for smoking- and smoking cessation-related disorders, as well as assist in smoking abstinence.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 it