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Record W2092739326 · doi:10.1002/path.3975

Reactive murine lymph nodes uniquely permit parenchymal access for T cells that enter via the afferent lymphatics

2011· article· en· W2092739326 on OpenAlexaff
Liv Eidsmo, Angus T. Stock, William R. Heath, Sammy Bedoui, Francis R. Carbone

Bibliographic record

VenueThe Journal of Pathology · 2011
Typearticle
Languageen
FieldMedicine
TopicMultiple Sclerosis Research Studies
Canadian institutionsCarbon Engineering (Canada)
Fundersnot available
KeywordsLymph node stromal cellLymphatic systemLymph nodeLymphHigh endothelial venulesParenchymaPathologyAxillary lymph nodesLymphatic EndotheliumMedicineBiologyAnatomyInternal medicineMetastasis

Abstract

fetched live from OpenAlex

Whereas naïve T cells access the lymph nodes predominantly via the high endothelial venules, their effector counterparts can also enter via the afferent lymphatics. It is unclear if such cells are confined to the lymphatic spaces during their transit through the lymph node or whether they can access the lymphocyte- and dendritic cell-rich parenchyma with its potentially stimulatory environment. We used a flank HSV inoculation model that featured neuronal-mediated movement of virus to distinct areas of skin to study the lymphatic-mediated transit of activated T cells between different skin-draining lymph nodes. These experiments showed that activated T cells released from the brachial lymph node, draining the primary site of inoculation, entered the downstream axillary lymph node. These activated T cells accessed the subcapsular areas of the axillary lymph node via lymphatic vessels exiting the upstream brachial node regardless of whether the former drained skin that was associated with active infection. However, T cells remained within the sinusoidal network of the axillary lymph node unless it was directly associated with peripheral infection. Thus, activated T cells that enter a given lymph node using the afferent lymphatics do not have automatic access to the parenchyma unless it is a reactive node involved with peripheral inflammation or infection.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.527
Threshold uncertainty score0.342

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 science0.0010.000
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 head0.170
GPT teacher head0.363
Teacher spread0.193 · 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

Citations14
Published2011
Admission routes1
Has abstractyes

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