Bacterial cell products signal to mouse colonic nociceptive dorsal root ganglia neurons
Bibliographic record
Abstract
This study examined whether bacterial cell products that might gain access to the intestinal interstitium could activate mouse colonic nociceptive dorsal root ganglion (DRG) neurons using molecular and electrophysiological recording techniques. Colonic projecting neurons were identified by using the retrograde tracer fast blue and Toll-like receptor (TLR) 1, 2, 3, 4, 5, 6, 9, adapter proteins Md-1 and Md-2, and MYD88 mRNA expression was observed in laser-captured fast blue-labeled neurons. Ultrapure LPS 1 microg/ml phosphorylated p65 NF-kappaB subunits increased transcript for TNF-alpha and IL-1beta and stimulated secretion of TNF-alpha from acutely dissociated DRG neurons. In current-clamp recordings from colonic DRG neurons, chronic incubation (24 h) of ultrapure LPS significantly increased neuronal excitability. In acute studies, 3-min superfusion of standard-grade LPS (3-30 microg/ml) reduced the rheobase by up to 40% and doubled action potential discharge rate. The LPS effects were not significantly different in TLR4 knockout mice compared with wild-type mice. In contrast to standard-grade LPS, acute application of ultrapure LPS did not increase neuronal excitability in whole cell recordings or afferent nerve recordings from colonic mesenteric nerves. However, acute application of bacterial lysate (Escherichia coli NLM28) increased action potential discharge over 60% compared with control medium. Moreover, lysate also activated afferent discharge from colonic mesenteric nerves, and this was significantly increased in chronic dextran sulfate sodium salt mice. These data demonstrate that bacterial cell products can directly activate colonic DRG neurons leading to production of inflammatory cytokines by neurons and increased excitability. Standard-grade LPS may also have actions independent of TLR signaling.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".