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Record W2911325183 · doi:10.1111/tid.13060

Cytokine profile in lung transplant recipients with <i>Aspergillus</i> spp colonization

2019· article· en· W2911325183 on OpenAlexaff
Sabina Herrera, Wajiha Gohir, Farid Foroutan, Claire Aguilar, S. Juvet, Tereza Martinu, Deepali Kumar, Atul Humar, Coleman Rotstein, Shaf Keshavjee, L.G. Singer, Shahid Husain

Bibliographic record

VenueTransplant Infectious Disease · 2019
Typearticle
Languageen
FieldMedicine
TopicTransplantation: Methods and Outcomes
Canadian institutionsToronto General HospitalUniversity of TorontoTed Rogers Centre for Heart ResearchUniversity Health Network
Fundersnot available
KeywordsMedicineAspergillusCytokineColonizationLungInternal medicineGastroenterologyAspergillosisAntifungalImmunologyMicrobiologyBiology

Abstract

fetched live from OpenAlex

We studied cytokine profiles in BAL of LTRs with Aspergillus spp colonization who did not progress to IPA in the absence of antifungal prophylaxis. This was a retrospective, single center case-control study. BAL samples were analyzed for cytokines. Patients with Aspergillus spp in BAL who did not receive prophylaxis and did not develop IPA were compared to LTRs with Aspergillus spp that received prophylaxis, LTRs with IPA and controls. Twenty-one patients with Aspergillus colonization who did not develop IPA, seven patients with suspected IPA who received prophylaxis, 4 IPA and 19 controls were included. IPA group had significantly higher levels (median [IQR]) of MIP-1 beta compared to the Suspected IPA group (5 vs 5 P: 0.03). The Suspected IPA group had significantly higher levels of IL-12 (11.38 vs 1 P: 0.0001), IL-1 RA (86.11 vs 23.98 P: 0.0118), IP-10 (22.47 vs 0.86 P: 0.0151), HGF (40.92 vs 16.82 P: 0.0055), and MIG (169.62 vs 5 P: 0.0005) than Colonization group. We have identified a unique cytokine signature in patients with Aspergillus colonization that do not develop IPA. Our study forms basis for a larger study to use these cytokines profile to identify patients at a lower risk of developing IPA.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

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

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 head0.008
GPT teacher head0.255
Teacher spread0.247 · 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 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".

Quick stats

Citations5
Published2019
Admission routes1
Has abstractyes

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