Screening of microbes, isolation, genetic manipulation, and physiological optimization of Brevibacterium helvolum to produce and excrete thymidine and deoxyuridine in high concentrations.
Bibliographic record
Abstract
Analogues of deoxypyrimidines are used in the treatment of a variety of human ailments. Azidothymidine, or AZT, is one such analogue used to treat AIDS. Thymidine is the precursor of AZT, and its cost contributes to the high price of AZT. Attempts are being made to isolate and genetically manipulate microbes that can produce and excrete this compound in high concentrations. To this end, 145 different microbial species from Zeneca and the American Type Culture Collection were screened. Moreover, soil samples were collected from 36 different sites in England, and microbes from these samples were isolated and screened. >From approximately 25,000 isolates screened as single colonies and from 4,000 in liquid cultures, a strain of Brevibacterium helvolum showed the most promising results. Pyrimidine metabolic pathways of this bacterium were worked out, the isolate was genetically manipulated, and physiological conditions were optimized to increase the production of thymidine and deoxyuridine. These mutants of B. helvolum are considered to be of commercial importance.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".