DECIPHERING THE ROLE OF EXPERIMENTALLY VALIDATED NICOTIANA TABACUM (TOBACCO) MIRNAS IN HUMAN HEALTH – A COMPUTATIONAL GENOMICS ASSESSMENT
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
Tobacco (Nicotiana tabacum) is considered as the tropical model plant for research especially for alkaloid like nicotine. One of the public health problems worldwide is harmful usage of tobacco that kills half of their consumers. On the other hand, Nicotiana tabacum was used as chief medicinal plants by native Americans, Amazonian and ancient Indians to cure poisonous reptiles’ bites and multiple diseases. MicroRNA (miRNA) is a prime gene regulator amongst the class of small-RNAs which binds with mRNA using translational repression or cleavage mechanism. Till the date, tobacco plant derived miRNAs were studied to check stress response in different biotic and abiotic condition and phylogenetic analysis, plant growth and development. Thus, cross-kingdom approach helps to understand the possible regulation as well as modulation in human health targeted by tobacco specific miRNAs. Tobacco derived miRNAs along with their targets were predicted and functionally annotated, pathway enrichment and disease association were studied in this study. Conclusively, we can report that N. tabacum miRNAs showed association with carcinoma and multiple neural, cardiac disorders.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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