BS3 Chemical Crosslinking Assay: Evaluating the Effect of Chronic Stress on Cell Surface GABA<sub>A</sub> Receptor Presentation in the Rodent Brain
Bibliographic record
Abstract
Anxiety is a state of emotion that variably affects animal behaviors, including cognitive functions. Behavioral signs of anxiety are observed across the animal kingdom and can be recognized as either adaptive or maladaptive responses to a wide range of stress modalities. Rodents provide a proven experimental model for translational studies addressing the integrative mechanisms of anxiety at the molecular, cellular, and circuit levels. In particular, the chronic psychosocial stress paradigm elicits maladaptive responses mimicking anxiety-/depressive-like behavioral phenotypes that are analogous between humans and rodents. While previous studies show significant effects of chronic stress on neurotransmitter contents in the brain, the effect of stress on neurotransmitter receptor levels is understudied. In this article, we present an experimental method to quantitate the neuronal surface levels of neurotransmitter receptors in mice under chronic stress, especially focusing on gamma-aminobutyric acid (GABA) receptors, which are implicated in the regulation of emotion and cognition. Using the membrane-impermeable irreversible chemical crosslinker, bissulfosuccinimidyl suberate (BS3), we show that chronic stress significantly downregulates the surface availability of GABAA receptors in the prefrontal cortex. The neuronal surface levels of GABAA receptors are the rate-limiting process for GABA neurotransmission and could, therefore, be used as a molecular marker or a proxy of the degree of anxiety-/depressive-like phenotypes in experimental animal models. This crosslinking approach is applicable to a variety of receptor systems for neurotransmitters or neuromodulators expressed in any brain region and is expected to contribute to a deeper understanding of the mechanisms underlying emotion and cognition.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".