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Record W4380626171 · doi:10.1093/ndt/gfad063c_6352

#6352 CLINICAL AND MOLECULAR SPECTRUM OF V-LESION

2023· article· en· W4380626171 on OpenAlexaff
Anna Buxeda, María José Pérez‐Sáez, Betty Odette Chamoun Huacon, Javier Gimeno, Irina Torres Rodriguez, Julio Pascual, Michael Mengel, Benjamin Adam, Marta Crespo

Bibliographic record

VenueNephrology Dialysis Transplantation · 2023
Typearticle
Languageen
FieldMedicine
TopicTransplantation: Methods and Outcomes
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsMedicineLesionBiopsyEtiologyPathologyInternal medicineGastroenterology

Abstract

fetched live from OpenAlex

Abstract Background and Aims Isolated v-lesion is an increasingly recognized but clinically challenging entity. Some studies suggest that isolated v+ early post-transplant may be caused by non-alloimmune etiologies such as ischemic injury. We aimed to characterize the allograft outcomes of isolated v-lesions according to post-transplant time (early: ≤1 month vs. late: >1 month) and further understand the significance of this lesion by characterizing its molecular phenotype in comparison with other forms of rejection v+. Method The NanoString B-HOT panel (770 genes) was used to measure the expression of six literature-derived gene sets in 92 archival FFPE kidney biopsies from two centers, including transplant biopsies with isolated v-lesion (n = 23), antibody-mediated rejection (ABMR) with v+ (n = 26), pure T-cell mediated rejection (TCMR) with v+ (n = 10), mixed rejection v+ (n = 23), and normal implant biopsies (Normal, n = 10). The evaluated gene sets included transcripts previously associated with ABMR, DSA (DSAST), endothelial injury (ENDAT), TCMR, early injury, and late injury. Gene expression was compared between groups using principal component and class comparison analyses. Death-censored graft survival according to diagnosis and time after KT was assessed. Results Isolated v+ early conferred the worst death-censored graft survival one year after the biopsy (40%) when compared to isolated v+ late (100%) or other forms of rejection (≥82%, p = 0.034). The principal component analysis demonstrated significant molecular overlap between sample groups (PC1: 29.4%, PC2: 8.1%). However, gene set analysis showed lower expression of TCMR-related genes in isolated v+ groups compared to TCMR and mixed rejection (p<0.001). Both Isolated v+ early and late had lower ABMR-related genes than ABMR, mixed rejection, and TCMR groups (p ≤ 0.022). Moreover, isolated v+ late showed lower DSAST and ENDAT gene set expression than ABMR (p ≤ 0.046); and lower early injury gene set expression than isolated v+ early, ABMR, TCMR, and mixed rejection (p ≤ 0.026). Late injury gene set expression was highest in TCMR and mixed rejection compared to the other groups (p ≥ 0.034). Conclusion These results suggest that early and late isolated v+ lesions display lower expression of TCMR-related genes than TCMR and mixed rejection and lower expression of ABMR-related genes than ABMR. Isolated v+ early confers a bad prognosis and is associated with higher expression of early injury genes compared to isolated v+ late, suggesting a different ethology.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0070.001

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 head0.037
GPT teacher head0.362
Teacher spread0.326 · 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 source (direct Gemma or distilled Codex), not a consensus.

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

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Citations0
Published2023
Admission routes1
Has abstractyes

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