Relevance of Cytochrome P450s in Plants: Also One of Ron Estabrook's Research Interests
Bibliographic record
Abstract
I worked with Dr. Ronald Estabrook for nearly 10 years at The University of Texas Southwestern Medical Center in Dallas, Texas. In Ron's lab, when I joined I was initially involved in the isolation, purification, and characterization of cytochrome P450s and NADPH-P450(c) reductase(s) from plants, which was his new exploratory project at the time. We developed methods for the isolation, solubilization, and purification of P450s and NADPH-P450(c) reductase from plant tissue microsomes. We carried out number of in vitro experiments to study the involvement P450s and NADPH-P450(c) reductase in the biosynthesis of number of phytoalexins. We successfully isolated, purified, and cloned NADPH-P450(c) reductase from etiolated mung bean (Vigna radiate) seedlings. In addition, a series of studies were undertaken to show that purified mung bean NADPH-P450(c) reductase was able to catalyze P450-supported reactions for mammalian and bacterial P450s. My stay in Ron's lab was very educational and productive. He provided the necessary support and led the way through the maze in different research projects in the lab, which allowed me to understand the roles of P450s in humans, animals, plants, and microorganisms. He liked to teach and discover new things everyday in the lab. He is a great scientist, as well as loving and caring mentor.
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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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.007 |
| Insufficient payload (model declined to judge) | 0.004 | 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".