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Record W2283302117 · doi:10.1097/tp.0000000000000867

Elevated Urinary Matrix Metalloproteinase-7 Detects Underlying Renal Allograft Inflammation and Injury

2015· article· en· W2283302117 on OpenAlexafffund
Julie Ho, David N. Rush, Oleg V. Krokhin, Mihaela Antonovici, Ang Gao, Jennifer Bestland, Chris Wiebe, Brett Hiebert, Claudio Rigatto, Ian W. Gibson, John A. Wilkins, Peter Nickerson

Bibliographic record

VenueTransplantation · 2015
Typearticle
Languageen
FieldMedicine
TopicRenal Transplantation Outcomes and Treatments
Canadian institutionsWinnipeg Regional Health AuthorityUniversity of Manitoba
FundersCanadian Institutes of Health ResearchSatellite HealthcareManitoba Medical Service Foundation
KeywordsMedicineUrinary systemUrologyGastroenterologyInternal medicinePathologyFibrosisCreatinineInflammation

Abstract

fetched live from OpenAlex

BACKGROUND: The urinary CXC chemokine ligand (CXCL)10 detects renal transplant inflammation noninvasively, but has limited sensitivity and specificity. In this study, we performed urinary proteomic analysis to identify novel biomarkers that may improve the diagnostic performance of urinary CXCL10 for detecting alloimmune inflammation in renal transplant patients. METHODS: In preliminary studies, adult renal transplant patients with normal histology (n = 5), interstitial fibrosis and tubular atrophy (n = 6), subclinical (n = 6) and clinical rejection (n = 6), underwent in-depth urine protein compositional analysis with LC-MS/MS, and matrix metalloproteinase-7 (MMP7) were identified as a potential candidate for the diagnosis of renal allograft inflammation. Urine MMP7 performance was then studied in a larger, prospective adult renal transplant population (n = 148 urines from n = 133 patients) with matched surveillance/indication biopsies. The diagnostic performance of urinary MMP7 and CXCL10 in combination was next evaluated using concordance (C-) statistics, net reclassification improvement and integrated discrimination improvement indices, to determine whether it was better than CXCL10 alone. RESULTS: Urinary MMP7:creatinine (Cr) was lower in normal transplants compared to those with inflammation: glomerulonephritis (P = 0.009), viral nephropathies (P = 0.002), interstitial fibrosis and tubular atrophy and inflammation (P = 0.04), borderline (P = 0.08), subclinical (P = 0.01) and clinical rejection (P = 0.0006), and acute tubular necrosis (P < 0.0001). Urinary MMP7:Cr and CXCL10:Cr significantly distinguished noninflamed from inflamed biopsies (area under the curve, 0.74 and 0.70, respectively). The addition of urinary MMP7:Cr to CXCL10:Cr improved the diagnostic performance for subclinical and clinical inflammation/injury by integrated discrimination improvement (P = 0.002) and net reclassification improvement (P = 0.006) analyses. CONCLUSIONS: Urinary MMP7:Cr improves the overall diagnostic performance of urinary CXCL10:Cr for distinguishing normal histology from subclinical and clinical inflammation/injury, but not subclinical inflammation alone.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
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 score0.400
Threshold uncertainty score0.594

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.047
GPT teacher head0.328
Teacher spread0.281 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations31
Published2015
Admission routes2
Has abstractyes

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