Bibliographic record
Abstract
Dr. Jeevan K. Prasain is an associate professor of pharmacology and toxicology at the University of Alabama at Birmingham. His current research focuses on delineation of unconventional cyclooxygenase (Cox)-independent prostaglandin (PG) synthesis mechanism, mass spectrometry-based metabolomics/lipidomics, biological activity, and uptake and metabolisms of dietary botanicals in vitro and in vivo. Dr. Prasain received his MSc in chemistry from Tribhuvan University located in Kathmandu, Nepal and went on to obtain his PhD in Japan from the Toyama Medical and Pharmaceutical University in pharmaceutical sciences. During his PhD tenure, he devoted much of his studies to natural product chemistry resulting in the discovery of several novel bioactive diarylheptanoids, subjects he went on to publish in several papers. After the completion of his PhD, he was awarded the Canadian Government Visiting Fellowship at the Biotechnology Research Institute (BRI) in Montreal, Canada to pursue postdoctoral research. During his time at BRI, Dr. Prasain was involved in drug discovery and high throughput screening of bioactive natural products from natural product libraries and their analysis by tandem mass spectrometry. Through this research, Dr. Prasain later went on to be a recipient of a Science and Technology Award at RIKEN in Tokyo Japan where he developed a mass spectrometry method for analysis of antibiotic cytochalasins. Based on his experiences in natural products research, he developed a great interest in dietary polyphenols in the promotion of health and prevention of chronic disease. Dr. Prasain joined the University of Alabama at Birmingham (UAB) as a postdoctoral fellow with Dr. Stephen Barnes in 2001, where he was later promoted to Assistant Professor in 2003. One of his research focuses was on the understanding of antidiabetic effects of puerarin, an isoflavone C-glucoside from Kudzu root and its metabolism and bioavailability. Kudzu root is well-known in traditional Chinese medicine, and various kudzu root based dietary supplements are available in the US market. Prasain's lab, in collaboration with Dr. Elias Meezan, also at UAB, demonstrated that puerarin treatment significantly improves glucose tolerance in C57 BL/6J ob/ob mice, an animal model of Type 2 diabetes mellitus. Specifically, puerarin blunts the rise in blood glucose levels after i.p. administration of glucose. Prasain et al. also found that in contrast to its O-glucoside isomer daidzin, puerarin is essentially absorbed without undergoing metabolism and is excreted in the urine mainly as an unchanged parent. In addition, in collaboration with Dr. Clinton Grubbs at UAB on the role of cranberry juice in bladder cancer prevention in animals, Prasain et al. demonstrated that commercially available cranberry juice concentrate can prevent urinary bladder cancers dose-dependently in N-butyl-N-(4-hydroxybutyl)-nitrosamine (OH-BBN) induced bladder carcinogenesis in rats when compared to the control group. This study also indicated that cranberry compounds once ingested reach the urinary bladder and concentrate in the urine in either the intact or in the metabolized forms and may prevent against the progression of carcinogenesis. This is because bladder cancers occur almost exclusively in the bladder epithelium, which is directly exposed to the urine stored in the bladder. In 2009, Dr. Prasain received an NIH R21 funding for investigating urinary metabolites of cranberry that protect against bladder cancer. The primary focus of this project was to understand what cranberry metabolites stored in the bladder are bioavailable and which metabolites are responsible against bladder carcinogenesis. The other focus of Dr. Prasain's lab is in the area of lipidomics, particularly profiling and characterizing PGs and other signaling lipids using tandem mass spectrometry. Using a combination of genetics, microinjection, and mass spectrometry, the late Dr. Michael Miller's and Dr. Prasain's labs discovered that C. elegans oocytes secrete sperm attractants F-series PGs derived from polyunsaturated fatty acid precursors. This NIH funded research led to an unanticipated discovery that C. elegans and mice generate specific F-series PGs without Cox enzymes. Over the past several years, much of the Dr. Prasain's lab effort has been to identify genes essential for Cox-independent PG synthesis and the signaling mechanisms that regulate PG functions in reproductive biology. The authors declare no conflict of interest.
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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 | 0.002 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.152 | 0.100 |
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".