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Lung Inflammation and Pulmonary Intravascular Macrophage Recruitment in L‐Arginine‐Induced Acute Necrotizing Pancreatitis in Mouse

2016· article· en· W2603160226 on OpenAlexafffundabout
Vanessa Vrolyk, Bruce Wobeser, Nguyen Phuong Khanh Le, Baljit Singh

Bibliographic record

VenueThe FASEB Journal · 2016
Typearticle
Languageen
FieldMedicine
TopicPancreatitis Pathology and Treatment
Canadian institutionsUniversity of Saskatchewan
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsNecrotizing pancreatitisMacrophageInflammationMedicineLungPathologyPancreatitisAcute pancreatitisAlveolar macrophagePulmonary vasculatureNecrosisInternal medicineChemistry

Abstract

fetched live from OpenAlex

Human patients suffering from severe acute pancreatitis are at higher risk of developing acute lung injury with high morbidity and mortality rates. Although there are many studies on the mechanisms leading to acute lung injury associated with acute pancreatitis in experimental models, there has not been any investigation on the induction of pulmonary intravascular macrophages (PIMs), a pro‐inflammatory cell normally present in cattle, pig, and horses, during this pathological condition in animal models. Therefore, we tested the hypothesis that lungs from mice with L‐arginine‐induced acute necrotizing pancreatitis (ANP) will be inflamed along with the recruitment of PIMs, compared to lungs of control mice. ANP was induced in C57BL/6 mice by administering two intraperitoneal injections, one hour apart, of a sterile L‐arginine monohydrochloride 9% solution at the dose of 4.5g/kg per injection, and mice were euthanized at 24h (n=7), 72h (n=7) and 120h (n=7) post‐injections. Control mice (n=9) received the same injections but with physiological sterile saline. ANP was confirmed by a pathologist using a histological grading system for pancreatic necrosis, infiltration of inflammatory cells and edema, which generated total ANP severity scores as follows: median (with range) of 0 for controls, 1 (0–3) for the 24h group, 8 (6–10) for the 72h group and 4 (2–10) for the 120h group. Serum amylase was significantly increased in the 24h group (5528±1210 U/L) and the 72h group (6547±1275 U/L), but not in the 120h group (1399±62 U/L), compared to control (1483±48 U/L), p<0.001. The lung histological grading revealed infiltration of mononuclear phagocytes in the lungs of mice in the 72h group only, compared to the control lungs (p<0.001). Immunohistochemistry with anti‐macrophage CD‐68 antibody revealed an increase of monocytes/macrophages present in alveolar septa of the lungs of all mice with ANP, suggesting PIMs induction, compared with control mice (p<0.01), with cell counts (median; range) as follows: control mice (81; 55–147), 24h group (150; 115–190), 72h group (190; 118–200) and 120h group (135; 97–194). Bioplex assay on lung homogenates identified increased levels of IL‐6 (p < 0,0001), IL‐10 (p < 0,01), and MCP‐1 (p < 0,05) in the 24h group only, compared to control mice. Immunohistochemistry for vWF revealed granular staining in the alveolar septal capillaries of some ANP mice, but not in control mice, suggesting activation of the lung microvasculature endothelium during ANP. The data show that lung inflammation in mice with L‐arginine‐induced ANP is initiated as early as 24h and is characterised by the infiltration of septal mononuclear phagocytes, most probably PIMs, as well as by increased lung concentrations of IL‐6, IL‐10 and MCP‐1. Because of the established role of PIMs in lung inflammation, the mouse model of ANP will be a useful tool to investigate the biology of PIMs in ANP‐associated lung inflammation. Support or Funding Information Natural Sciences and Engineering Research Council of Canada

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)0.001
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0040.002

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 head0.023
GPT teacher head0.277
Teacher spread0.254 · 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 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

Citations0
Published2016
Admission routes3
Has abstractyes

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