Metabolic Signaling to the Central Nervous System: Routes Across the Blood Brain Barrier
Bibliographic record
Abstract
In order to maintain an ideal body weight, an organism must balance energy intake with energy expenditure. It is well known that metabolic signals derived in the periphery act in well-defined hypothalamic and brainstem neuronal circuits to control energy homeostasis. As such, peripheral signals that convey information regarding nutritional and metabolic status of the individual must be able to access and control these neuronal circuits in order to direct both food intake and energy expenditure. Within the hypothalamus, the arcuate nucleus of the hypothalamus has become recognized as a critical center in this integrated circuitry. Although there is considerable anatomical evidence indicating that the arcuate is protected by the blood brain barrier, neurons in this region have been repeatedly suggested to directly sense many circulating signals which do not readily diffuse across this barrier. In this review we will describe the hypothalamic circuitry involved in the regulation of energy homeostasis and will discuss data indicating that the arcuate nucleus is, in fact, protected by the blood brain barrier. We will then consider alternative mechanisms through which one specific circulating adipokine, leptin, can gain access to and influence central nervous sites involved in the regulation of energy homeostasis without the requirement for direct access from the peripheral circulation to arcuate neurons.
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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 | 0.000 | 0.000 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.003 |
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".