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Record W2168430670 · doi:10.1186/s12974-015-0397-2

New means to assess neonatal inflammatory brain injury

2015· review· en· W2168430670 on OpenAlexafffund
Chen Jin, Irene Londoño, Carina Mallard, Gregory A. Lodygensky

Bibliographic record

VenueJournal of Neuroinflammation · 2015
Typereview
Languageen
FieldMedicine
TopicNeonatal and fetal brain pathology
Canadian institutionsMontreal Heart InstituteUniversité de Montréal
FundersInstitute of Human Development, Child and Youth HealthFonds de Recherche du Québec - SantéVetenskapsrådetÅhlén-stiftelsenCanadian Institutes of Health ResearchStiftelsen Olle Engkvist ByggmästareHjärnfondenFondation Leducq
KeywordsMedicineExcitotoxicityNeuroprotectionTraumatic brain injuryNeurologyNeuroscienceIntensive care medicineBioinformaticsGlutamate receptorPsychiatryPsychologyInternal medicineBiology

Abstract

fetched live from OpenAlex

Preterm infants are especially vulnerable to infection-induced white matter injury, associated with cerebral palsy, cognitive and psychomotor impairment, and other adverse neurological outcomes. The etiology of such lesions is complex and multifactorial. Furthermore, timing and length of exposure to infection also influence neurodevelopmental outcomes. Different mechanisms have been posited to mediate the observed brain injury including microglial activation followed by subsequent release of pro-inflammatory species, glutamate-induced excitotoxicity, and vulnerability of developing oligodendrocytes to cerebral insults. The prevalence of such neurological impairments requires an urgent need for early detection and effective neuroprotective strategies. Accordingly, noninvasive methods of monitoring disease progression and therapy effectiveness are essential. While diagnostic tools using biomarkers from bodily fluids may provide useful information regarding potential risks of developing neurological diseases, the use of magnetic resonance imaging/spectroscopy has emerged as a promising candidate for such purpose. Various pharmacological agents have demonstrated protective effects in the immature brain in animal models; however, few studies have progressed to clinical trials with promising results.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.970
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.078
GPT teacher head0.367
Teacher spread0.289 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreReview

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".

Quick stats

Citations52
Published2015
Admission routes2
Has abstractyes

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