Acute gut inflammation reduces neural activity and spine maturity in hippocampus but not basolateral amygdala
Bibliographic record
Abstract
Gastrointestinal tract (gut) inflammation increases stress and threat-coping behaviors, which are associated with altered activity in fear-related neural circuits, such as the basolateral amygdala and hippocampus. It remains to be determined whether inflammation from the gut affects neural activity by altering dendritic spines. We hypothesized that acute inflammation alters dendritic spines in a brain region-specific manner. Here we show that acute gut inflammation (colitis) evoked by dextran sodium sulfate (DSS) did not affect the overall spine density in the CA1 region of hippocampus, but increased the relative proportion of immature spines to mature spines on basal dendrites of pyramidal neurons. In contrast, in animals with colitis, no changes in spine density or composition on dendrites of pyramidal cells was observed in the basolateral amygdala. Rather, we observed decreased spine density on dendrites of stellate neurons, but not the relative proportions of mature vs immature spines. We used cFos expression evoked by the forced swim task as a measure of neural activity during stress and found no effect of DSS on the density of cFos immunoreactive neurons in basolateral amygdala. In contrast, fewer CA1 neurons expressed cFos in mice with colitis, relative to controls. Furthermore, CA1 cFos expression negatively correlated with active stress-coping in the swim task and was negatively correlated with gut inflammation. These data reveal that the effects of acute gut inflammation on synaptic remodeling depend on brain region, neuronal phenotype, and dendrite location. In the hippocampus, a shift to immature spines and hypoactivity are more strongly related to colitis-evoked behavioral changes than is remodeling in basolateral amygdala.
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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 | 0.001 |
| 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".