Uso racional de los medicamentos versus uso responsable de los medicamentos y prescripción por principio activo
Bibliographic record
Abstract
Vitamin B1 (thiamin, B1) is an essential micronutrient for cells, yet intriguingly in aquatic systems most bacterioplankton are unable to synthesize it <i>de novo</i> (auxotrophy), requiring an exogenous source. Cycling of this valuable metabolite in aquatic systems has not been fully investigated and vitamers (B1-related compounds) have only begun to be measured and incorporated into the B1 cycle. Here, we identify potential key producers and consumers of B1 and gain new insights into the dynamics of B1 cycling through measurements of B1 and vitamers (HMP: 4-amino-5-hydroxymethyl-2-methylpyrimidine, HET: 4-methyl-5-thiazoleethanol, FAMP: <i>N</i>-formyl-4-amino-5-aminomethyl-2-methylpyrimidine) in the particulate and dissolved pool in a temperate coastal system. Dissolved B1 was not the primary limiting nutrient for bacterial production and was relatively stable across seasons with concentrations ranging from 74-117 pM, indicating a balance of supply and demand. However, vitamer concentration changed markedly with season as did transcripts related to vitamer salvage and transport suggesting use of vitamers by certain bacterioplankton, e.g. <i>Pelagibacterales</i>. Genomic and transcriptomic analyses showed that up to 78% of the bacterioplankton taxa were B1 auxotrophs. Notably, <i>de novo</i> B1 production was restricted to a few abundant bacterioplankton (e.g. <i>Vulcanococcus</i>, BACL14 (<i>Burkholderiales</i>), <i>Verrucomicrobiales</i>) across seasons. In summer, abundant picocyanobacteria were important putative B1 sources, based on transcriptional activity, leading to an increase in the B1 pool. Our results provide a new dynamic view of the players and processes involved in B1 cycling over time in coastal waters, and identify specific priority populations and processes for future study.
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How this classification was reachedexpand
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 | 0.006 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.010 |
| Insufficient payload (model declined to judge) | 0.035 | 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; both teacher heads agree on what is shown here.
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".