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Record W2169909508 · doi:10.1002/pros.20466

Presence of prostate cancer metastasis correlates with lower lymph node reactivity

2006· article· en· W2169909508 on OpenAlexafffund
Gannon Philippe Olivier, Alam Fahmy Mona, Bégin Louis Réal, Djoukhadjian Audrey, Abdelali Filali‐Mouhim, Lapointe Réjean, Anne‐Marie Mes‐Masson

Bibliographic record

VenueThe Prostate · 2006
Typearticle
Languageen
FieldMedicine
TopicInflammatory Biomarkers in Disease Prognosis
Canadian institutionsHôpital Notre-DameUniversité de MontréalHôpital du Sacré-Cœur de MontréalCentre Hospitalier de l’Université de Montréal
FundersInstitut Du Cancer de MontréalInstitute of Cancer ResearchAstraZeneca
KeywordsMedicineProstate cancerMetastasisProstateFollicular hyperplasiaPathologyHyperplasiaLymphLymph nodeCancerStromal cellImmunohistochemistryCD68Internal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Several reports suggest that the dissemination of neoplastic cells and cancer progression are associated with the generation of an immunosuppressive environment. METHODS: In this report, we investigated immunological effects of prostate cancer by comparing metastastic and non-metastatic pelvic lymph nodes (LNs) from 25 patients with carcinomatous involvement of LNs to the non-metastatic LNs from 26 control patients with no metastatic involvement by immunohistochemistry and histological analyses. RESULTS: Our results showed a decreased abundance of CD20+ B lymphocytes (P = 0.031), CD38+ activated lymphocytes (P = 0.038), and CD68+ macrophages (P < 0.001), and less evidence of follicular hyperplasia (P = 0.014), sinus hyperplasia (P < 0.001), and fibrosis (P=0.028) in metastatic LNs comparatively to control LNs. Finally, we observed that metastatic LNs were significantly smaller than control LNs (P = 0.005). CONCLUSIONS: Our results suggest that the development of prostate cancer LN metastasis is accompanied with smaller LN size and decreased LN reactivity suggesting the development of an immununosuppressive microenvironment.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.224
Threshold uncertainty score0.570

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 studies0.0000.001
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 head0.009
GPT teacher head0.248
Teacher spread0.239 · 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 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

Citations31
Published2006
Admission routes2
Has abstractyes

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