Hyperleptinemia, Visceral Adiposity, and Decreased Glucose Tolerance in Mice with a Targeted Disruption of the Histidine Decarboxylase Gene
Bibliographic record
Abstract
Histamine has been referred to as an anorexic factor that decreases appetite and fat accumulation and affects feeding behavior. Tuberomammillary histaminergic neurons have been implicated in central mediation of peripheral metabolic signals such as leptin, and centrally released histamine inhibits ob gene expression. Here we have characterized the metabolic phenotype of mice that completely lack the ability to produce histamine because of targeted disruption of the key enzyme in histamine biosynthesis (histidine decarboxylase, HDC). Histochemical analyses confirmed the lack of HDC mRNA, histamine immunoreactivity, and histaminergic innervation throughout the brain of gene knockout mouse. Aged histamine-deficient (HDC-/-) mice are characterized by visceral adiposity, increased amount of brown adipose tissue, impaired glucose tolerance, hyperinsulinemia, and hyperleptinemia. Histamine-deficient animals are not hyperphagic but gain more weight and are calorically more efficient than wild-type controls. These metabolic changes presumably are due to the impaired regulatory loop between leptin and hypothalamic histamine that results in orexigenic dominance through decreased energy expenditure, attenuated ability to induce uncoupling protein-1 mRNA in the brown adipose tissue and defect in mobilizing energy stores. Our results further support the role of histamine in regulation of energy homeostasis.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".