Analyzing Dendritic Growth in a Population of Immature Neurons in the Adult Dentate Gyrus Using Laminar Quantification of Disjointed Dendrites
Bibliographic record
Abstract
In the dentate gyrus (DG) of the hippocampus, new granule neurons are continuously produced throughout adult life. A prerequisite for the successful synaptic integration of these neurons is the sprouting and extension of dendrites into the molecular layer of the DG. Thus, studies aimed at investigating the developmental stages of adult neurogenesis often use dendritic growth as an important indicator of neuronal health and maturity. Based on the known topography of the DG, characterized by distinct laminar arrangement of granule neurons and their extensions, we have developed a new method for analysis of dendritic growth in immature adult-born granule neurons. The method is comprised of laminar quantification of cell bodies, primary, secondary and tertiary dendrites separately and independently from each other. In contrast to most existing methods, laminar quantification of dendrites does not require the use of exogenous markers and does not involve arbitrary selection of individual neurons. The new method relies on immunohistochemical detection of endogenous markers such as doublecortin to perform a comprehensive analysis of a sub-population of immature neurons. Disjointed, "orphan" dendrites that often appear in the thin histological sections are taken into account. Using several experimental groups of rats and mice, we demonstrate here the suitable techniques for quantifying neurons and dendrites, and explain how the ratios between the quantified values can be used in a comparative analysis to indicate variations in dendritic growth and complexity.
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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 | 0.001 | 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 | 0.001 |
| 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".