Spatial transcriptomic analysis of adult hippocampal neurogenesis in the human brain
Bibliographic record
Abstract
Background Adult hippocampal neurogenesis has been extensively characterized in rodent models, but its existence in humans remains controversial. We sought to assess the phenomenon in postmortem human hippocampal samples by combining spatial transcriptomics and multiplexed fluorescent in situ hybridization. Methods We computationally examined the spatial expression of various canonical neurogenesis markers in postmortem dentate gyrus (DG) sections from young and middle-aged sudden-death males. We conducted in situ assessment of markers expressed in neural stem cells, proliferative cells, and immature granule neurons in postmortem DG sections from infant, adolescent, and middle-aged males. Results We examined frozen DG tissue from infant ( n = 1, age 2 yr), adolescent ( n = 1, age 16 yr), young adult ( n = 2, mean age 23.5 yr), and middle-aged ( n = 2, mean age 42.5 yr) males, and frozen-fixed DG tissue from middle-aged males ( n = 6, mean age 43.5 yr). We detected very few cells expressing neural stem cell and proliferative markers in the human DG from childhood to middle age. However, at all ages, we observed a substantial number of DG cells expressing the immature neuronal marker DCX. Most DCX + cells displayed an inhibitory phenotype, while the remainder were non-committed or excitatory in nature. Limitations The study was limited by small sample sizes and included samples only from males. Conclusion Our findings indicate very low levels of hippocampal neurogenesis throughout life and the existence of a local reserve of plasticity in the adult human hippocampus. Overall, our study provides important insight into the distribution and phenotype of cells expressing neurogenesis markers in the adult human hippocampus.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".