Loss of Neurons in Magnocellular and Parvocellular Layers of the Lateral Geniculate Nucleus in Glaucoma
Bibliographic record
Abstract
OBJECTIVES: To determine whether there is loss of lateral geniculate nucleus relay neurons, which convey visual information to the visual cortex, in experimental glaucoma in monkeys. METHOD: Four cynomolgus monkeys with experimentally induced glaucoma in the right eye (referred to as the glaucoma group) and 5 control monkeys were studied. In both groups, the same conditions of fixation, tissue processing, staining, and measurement were used. In each monkey, the left lateral geniculate nucleus target neurons in magnocellular layer 1 and parvocellular layers 4 and 6, connected to the right glaucomatous eye, were studied. Immunocytochemistry with antibody to parvalbumin was used to specifically label relay neurons connecting to the visual cortex. The number of parvalbumin-immunoreactive neurons was estimated using an unbiased 3-dimensional counting method. The t test was used to compare the experimental and control groups. RESULTS: The mean ( SD) number of neurons in mavnocellular layer 1 was significantly decreased in the glaucoma group compared with the control group (20 692 9567 vs 37 687 8017; P = .02). The mean ( SD) number of neurons in parvocellular layers 4 and 6 was significantly decreased in the glaucoma group compared with the control group (100 141 44 906 vs 174 090 39 136; P = .03). Data are given as the mean SD. CONCLUSION: Significant loss of lateral geniculate nucleus relay neurons terminating in the primary visual cortex occurs in the magnocellular and parvocellular layers in an experimental monkey model of glaucoma. CLINICAL RELEVANCE: Knowledge of the fate of neurons in the central visual system may lead to a better understanding of the nature and progression of visual loss in glaucomatous optic neuropathy.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".