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Record W4210690080 · doi:10.1126/sciadv.abm0142

Dipeptidase-1 governs renal inflammation during ischemia reperfusion injury

2022· article· en· W4210690080 on OpenAlexaff
Arthur Lau, Jennifer J. Rahn, Mona Chappellaz, Hyunjae Chung, Hallgrímur Benediktsson, Dominique Bihan, Anne von Mäßenhausen, Andreas Linkermann, Craig N. Jenne, Stephen M. Robbins, Donna L. Senger, Ian A. Lewis, Justin Chun, Daniel A. Muruve

Bibliographic record

VenueScience Advances · 2022
Typearticle
Languageen
FieldMedicine
TopicAcute Kidney Injury Research
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsKidneyAcute kidney injuryInflammationMonocyteMedicineRenal ischemiaPharmacologyPeritubular capillariesImmunologyIschemiaReperfusion injuryInternal medicine

Abstract

fetched live from OpenAlex

The mechanisms that drive leukocyte recruitment to the kidney are incompletely understood. Dipeptidase-1 (DPEP1) is a major neutrophil adhesion receptor highly expressed on proximal tubular cells and peritubular capillaries of the kidney. Renal ischemia reperfusion injury (IRI) induces robust neutrophil and monocyte recruitment and causes acute kidney injury (AKI). Renal inflammation and the AKI phenotype were attenuated in Dpep1 −/− mice or mice pretreated with DPEP1 antagonists, including the LSALT peptide, a nonenzymatic DPEP1 inhibitor. DPEP1 deficiency or inhibition primarily blocked neutrophil adhesion to peritubular capillaries and reduced inflammatory monocyte recruitment to the kidney after IRI. CD44 but not ICAM-1 blockade also decreased neutrophil recruitment to the kidney during IRI and was additive to DPEP1 effects. DPEP1, CD44, and ICAM-1 all contributed to the recruitment of monocyte/macrophages to the kidney following IRI. These results identify DPEP1 as a major leukocyte adhesion receptor in the kidney and potential therapeutic target for AKI.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.045
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.011
GPT teacher head0.323
Teacher spread0.312 · 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 designBench or experimental
Domainnot available
GenreEmpirical

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

Citations93
Published2022
Admission routes1
Has abstractyes

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