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Record W3113496724 · doi:10.1073/pnas.2013686117

Two populations of self-maintaining monocyte-independent macrophages exist in adult epididymis and testis

2020· article· en· W3113496724 on OpenAlexaff
Ming Wang, Yalong Yang, Dilay Cansever, Yiming Wang, Crystal Kantores, Sébastien Messiaen, Delphine Moison, Gabriel Livera, Svetoslav Chakarov, Tobias Weinberger, Christopher Stremmel, Monika Fijak, Britta Klein, Christiane Pleuger, Zhe‐Xiong Lian, Wentao Ma, Qingzhi Liu, Kathrin Klee, Kristian Händler, Thomas Ulas, Andreas Schlitzer, Joachim L. Schultze, Burkhard Becher, Melanie Greter, Zhaoyuan Liu, Florent Ginhoux, Slava Epelman, Christian Schulz, Andreas Meinhardt, Sudhanshu Bhushan

Bibliographic record

VenueProceedings of the National Academy of Sciences · 2020
Typearticle
Languageen
FieldImmunology and Microbiology
TopicImmune cells in cancer
Canadian institutionsUniversity of TorontoToronto General HospitalTed Rogers Centre for Heart ResearchUniversity Health Network
FundersNational Natural Science Foundation of ChinaChina Scholarship CouncilDeutsche Forschungsgemeinschaft
KeywordsEpididymisBiologyMacrophageHaematopoiesisYolk sacImmune systemMonocyteCell biologyBone marrowImmunologyProgenitor cellMyeloidStem cellEmbryoGeneticsSpermIn vitro

Abstract

fetched live from OpenAlex

macrophage populations of epididymis and testis arise sequentially from yolk sac erythro-myeloid progenitors, embryonic hematopoiesis, and nascent neonatal monocytes. While monocytes were the major developmental source of both epididymal and testicular macrophages, both populations self-maintain in the steady-state independent of bone marrow hematopoietic precursors. However, after radiation-induced macrophage ablation or during infection, bone marrow-derived circulating monocytes are recruited to the epididymis and testis, giving rise to inflammatory macrophages that promote tissue damage. These results define the layered ontogeny, maintenance and inflammatory response of macrophage populations in the male reproductive organs.

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)0.001
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 score0.059
Threshold uncertainty score0.263

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 head0.049
GPT teacher head0.317
Teacher spread0.268 · 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

Citations109
Published2020
Admission routes1
Has abstractyes

Explore more

Same venueProceedings of the National Academy of SciencesSame topicImmune cells in cancerFrench-language works237,207