Bibliographic record
Abstract
Nicotine, in the form of tobacco smoking, is the most commonly abused drug throughout the world. It contributes to the harmful tobacco smoking habit leading to high morbidity and mortality throughout the world. The drug has addictive properties and causes drug dependence. Apart from these effects, nicotine alters a number of metabolic pathways such as lipid profile and glucose homeostasis leading to increased risk of cardiovascular diseases. Present study investigated the metabolic and behavioral effects of nicotine in stressed mice. For this purpose adult male mice were subjected to chronic nicotine treatment(3.08 mg/100 ml in drinking water) for 3 weeks followed by forced swim test (FST) and serum glucose, lipid profile and tryptophan were investigated. When swim stressed mice were compared with chow control, it was found that serum glucose (P<0.001), total cholesterol (P<0.001), triglycerides (P<0.01), and LDL cholesterol (P<0.01) were increased. Similarly glucose concentration (P<0.05), total cholesterol (P<0.05), triglycerides (P<0.01) and LDL cholesterol (P<0.05) were increased in drug treated swim stressed mice. However HDL remained unaltered in both groups. Serum tryptophan was decreased (P<0.01) in swim stressed and nicotine treated swim stressed mice. During FST, swimming behavior was significantly increased at the cost of climbing with no change in immobility in nicotine treated mice as compared to controls. It is concluded that nicotine worsens lipid profile and glucose homeostasis in stressful situations thereby increasing the risk of cardiovascular diseases in chronic smokers and the drug induced behavioral alterations may be related to the serotonergic pathway.
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.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".