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Record W2117136125 · doi:10.2174/187152811796117753

Neutrophil Gelatinase-Associated Lipocalin (NGAL) as a New Biomarker for Non – Acute Kidney Injury (AKI) Diseases

2011· review· en· W2117136125 on OpenAlexaff
Janice Giasson, Guo Hua Li, Yu Chen

Bibliographic record

VenueInflammation & Allergy - Drug Targets · 2011
Typereview
Languageen
FieldMedicine
TopicAcute Kidney Injury Research
Canadian institutionsDr. Everett Chalmers Regional HospitalHorizon Health Network
Fundersnot available
KeywordsLipocalinBiomarkerAcute kidney injuryMedicineKidney diseaseNeutrophil gelatinase-associated lipocalinImmunologyInternal medicineBiology

Abstract

fetched live from OpenAlex

Neutrophil gelatinase-associated lipocalin, or NGAL, an acute phase protein, is part of the lipocalin family. NGAL is highly induced in inflammatory conditions and ischemia, and is a critical component of innate immunity to bacterial infection. Recently, NGAL has been proven as an emerging biomarker for predicting acute kidney injury (AKI). Meanwhile, numerous studies have also demonstrated that NGAL may be a potential biomarker for the diagnosis, prediction, prevention, and prognosis of non-AKI diseases such as chronic kidney diseases, vascular disorders, cancer, preeclampsia, and allergies. This article systematically reviews the clinical utilities of NGAL as a new biomarker for non - AKI diseases. Keywords: NGAL, biomarker, non-AKI diseases, diagnosis, Acute kidney injury, Anti-neutrophilic cytoplasmic auto-antibodies, Chronic kidney disease, Cardiovascular Disorders, Neutrophil Gelatinase-Associated Lipocalin, vascular disorders, preeclampsia

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)0.006
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.330
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0040.002
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0040.002

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 head0.042
GPT teacher head0.356
Teacher spread0.314 · 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; both teacher heads agree on what is shown here.

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

Citations34
Published2011
Admission routes1
Has abstractyes

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