Linking ultradian Growth Hormone secretion to the molecular structure of excitatory synapses in the vole hypothalamus
Bibliographic record
Abstract
Growth hormone (GH) is a pituitary hormone that is secreted in a pulsatile manner multiple times within a 24-hour period, establishing an ultradian secretion rhythm. GH release is controlled by two hypothalamic neuropeptides, GH-releasing hormone (GHRH) produced in the arcuate nucleus (ARC) and somatostatin (SOM) produced in the anterior periventricular nucleus (PeVN). The former works to stimulate GH secretion while the latter works to inhibit GH secretion. Our laboratory has found that the number of clusters of PSD-95 increase at bodies of GHRH cells during peaks of GH secretion and decrease when the hormone levels go down (GH troughs). However, the mechanisms that orchestrate these rapid changes in the ARC of the hypothalamus remain largely unknown. Previous studies on GH circuitry in our laboratory have used mice as the experimental animal. However, due to inconsistencies in their GH secretion patterns, we found it difficult to obtain tissue samples that corresponded to the peak of GH secretion. Specifically, since peaks last only around 40 minutes and are followed by 2-hour trough periods, the ability to predict the timing of GH secretion becomes crucial to minimize the numbers of animals used. Keeping in line with with the 3R’s formulated by Drs. William Russell and Rex Burch to improve the welfare of animals in research, specifically in this case, reduction in the animals used to obtain information, we propose using the common vole (Microtus arvalis) as an experimental animal. Studies done on this species have shown evidence of group synchronicity in behaviour and show promise for their use in neuroendocrine research. We hypothesized that voles might exhibit synchronous ultradian secretion patterns in which peaks and troughs would occur at similar time points between individuals. During a pilot experiment, voles were unhabituated to the blood collection procedure and GH rhythms were detected for all 4 animals indicating a resiliency of GH secretion to stress that has not typically been observed in other rodents. Furthermore, our data suggests that group synchronicity in voles does not occur by chance with 67% - 100% of animals being synchronous in each group tested. However, when testing hormone pattern predictability, only 1 out of 4 voles was found to be in a GH peak, indicating that predictability of secretion patterns may still be more difficult than hypothesized.Previous studies in our lab have tested antibody compatibility in M. arvalis with great success in synaptic markers (e.g., VGAT, VGLUT2, PSD-95, and Gephyrin). Thus we decided to use single-domain antibodies (also known as nanobodies) procured from the Camelidae family which allows for better tissue penetration due to their small size (12-14 kDa compared to 150 kDa in traditional antibodies). Also, due to their small size, nanobodies directly labeled with fluorophores exhibit a 1:1:1 conjugation ratio. This allows for more accurate PSD-95 quantification, as well as more accurate counting of synaptic clusters. Since our lab had never used nanobodies before, we needed to set up a working protocol to get the best possible signal-to-noise-ratio (SNR) and resolution. From this, we found the best working concentration for the PSD-95 nanobody to be 1:1000 (2.5 μg/ml). Next, we optimized STED imaging parameters to achieve the highest possible resolution which allowed for clearer identification of synaptic puncta and allowed us to count PSD-95 clusters in GHRH cells using a strong analysis tool: Statistical Object Distance Analysis (SODA) which uses strong statistical analysis such as complete spatial randomness, to assess coupling of synaptic partners in a more accurate and biologically significant way
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".