Assessing therapeutic response non-invasively in a neonatal rat model of acute inflammatory white matter injury using high-field MRI
Bibliographic record
Abstract
Perinatal infection and inflammatory episodes in preterm infants are associated with diffuse white matter injury (WMI) and adverse neurological outcomes. Inflammation-induced WMI was previously shown to be linked with later hippocampal atrophy as well as learning and memory impairments in preterm infants. Early evaluation of injury load and therapeutic response with non-invasive tools such as multimodal magnetic resonance imaging (MRI) would greatly improve the search of new therapeutic approaches in preterm infants. Our aim was to evaluate the potential of multimodal MRI to detect the response of interleukin-1 receptor antagonist (IL-1Ra) treatment, known for its neuroprotective properties, during the acute phase of injury on a model of neonatal WMI. Rat pups at postnatal day 3 (P3) received intracerebral injection of lipopolysaccharide with systemic IL-1Ra therapy. 24 h later (P4), rats were imaged with multimodal MRI to assess microstructure by diffusion tensor imaging (DTI) and neurochemical profile of the hippocampus with 1H-magnetic resonance spectroscopy. Astrocyte and microglial activation, apoptosis and the mRNA expression of pro-inflammatory and necroptotic markers were assessed. During the acute phase of injury, neonatal LPS exposure altered the concentration of hippocampus metabolites related to neuronal integrity, neurotransmission and membrane integrity and induced diffusivity restriction. Just 24 h after initiation of therapy, early indication of IL-1Ra neuroprotective effect could be detected in vivo by non-invasive spectroscopy and DTI, and confirmed with immunohistochemical evaluation and mRNA expression of inflammatory markers and cell death. In conclusion, multimodal MRI, particularly DTI, can detect not only injury but also the acute therapeutic effect of IL-1Ra suggesting that MRI could be a useful non-invasive tool to follow, at early time points, the therapeutic response in preterm infants.
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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 | 0.001 | 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) | 0.000 | 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".