Diminished levels of the chemokine fractalkine in post-mortem prefrontal cortex in schizophrenia but not bipolar disorder
Bibliographic record
Abstract
Objectives Though the pathophysiology underlying schizophrenia (SCZ) and bipolar disorder (BD) is not fully understood, immune function may be dysregulated, with microglia, the brain’s resident immune cells, implicated in this process. Signalling between the neuronal chemokine fractalkine (CX3CL1) and its microglial receptor CX3CR1 facilitates neuron-microglia interactions, influencing microglial activation and synaptic function. As such, alterations in fractalkine signalling may contribute to immune and synaptic alterations observed in SCZ and BD.Methods Protein and mRNA expression of fractalkine, CX3CR1, and a disintegrin and metalloproteinase 10 (ADAM10), a sheddase that cleaves fractalkine, were quantified in post-mortem frontal cortex from individuals with SCZ (n = 35), BD (n = 34), and matched controls (n = 35) using immunoblotting and droplet digital PCR. In addition, the relationship between fractalkine pathway members and levels of the pre-synaptic protein SNAP-25 was examined.Results Fractalkine protein levels were significantly lower in SCZ relative to controls. Expression of members of the fractalkine signalling pathway was unchanged in BD. CX3CR1 protein levels were significantly correlated with SNAP-25 levels.Conclusions The observed deficit in fractalkine protein levels in SCZ is consistent with impaired neuron-microglia crosstalk in this disorder. Furthermore, our data are suggestive of an aberrant association between microglial function and synaptic density in SCZ.
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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 | 0.000 |
| 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) | 0.001 | 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".