1H NMR Profiling of Honey Bee Brains across Varying Ages and Seasons
Bibliographic record
Abstract
) provide a useful model for studying aging because of the differences in longevity between the relatively short-lived summer and long-lived winter bees, as well as bees lacking signs of cognitive senescence as they age. Bee brains were dissected from newly emerged, 14-day-, and 28-day- old bees in mid- and late summer, as well as brood nest bees in fall, winter, and spring, before, during, and after overwintering, respectively. Brains were examined with nuclear magnetic resonance (NMR) spectroscopy to analyze their metabolome. Nine variable importance in projection (VIP) variables were identified, primarily amino acids and choline derivatives. Differences in metabolite concentrations were found with different ages of summer bees, mostly between newly emerged and 14-day- old bees, such as a decrease in phenylalanine and an increase in β-alanine, but there were also changes in older adults, such as o-phosphocholine that declined in 28-day- old bees. Differences in brood nest bees were observed, including a decline in tryptophan and an increase in β-alanine. These may provide distinct metabolomic signatures with age and season. Such research holds promise for a better understanding of the complex interplays between bee physiology, development, and aging, which has implications for improving bee health and management.
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) | 0.000 | 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) | 0.001 | 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".