Neurexins and Neuroligins: Recent Insights from Invertebrates
Bibliographic record
Abstract
During brain development, each neuron must find and synapse with the correct pre- and postsynaptic partners. The complexity of these connections and the relatively large distances some neurons must send their axons to find the correct partners makes studying brain development one of the most challenging, and yet fascinating disciplines in biology. Furthermore, once the initial connections have been made, the neurons constantly remodel their dendritic and axonal arbours in response to changing demands. Neurexin and neuroligin are two cell adhesion molecules identified as important regulators of this process. The importance of these genes in the development and modulation of synaptic connectivity is emphasised by the observation that mutations in these genes in humans have been associated with cognitive disorders such as Autism spectrum disorders, Tourette syndrome and Schizophrenia. The present review will discuss recent advances in our understanding of the role of these genes in synaptic development and modulation, and in particular, we will focus on recent work in invertebrate models, and how these results relate to studies in mammals.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".