MétaCan
Menu
Back to cohort
Record W4312105047

Modulation of Human Neutrophil Peptides on P. aeruginosa Killing, Epithelial Cell Inflammation and Mesenchymal Stromal Cell Secretome Profiles

2019· article· en· W4312105047 on OpenAlexaboutno aff
Y Morita, Y Huang, Patricia C. Liaw, Jiang Wu, Julie Khang, Diana Islam, Yu Kang, Li Y, H Zhang

Bibliographic record

VenueDOAJ (DOAJ: Directory of Open Access Journals) · 2019
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicS100 Proteins and Annexins
Canadian institutionsnot available
Fundersnot available
KeywordsMesenchymal stem cellStromal cellInflammationCellCell biologyInterleukin 8BiologyMicrobiologyChemistryImmunologyCancer researchBiochemistry
DOInot available

Abstract

fetched live from OpenAlex

Qingqing Dai,1,* Yasumasa Morita,2,* Yongbo Huang,3 Patricia C Liaw,4 Jianfeng Wu,5 Julie Khang,6 Diana Islam,6 Kaijiang Yu,7 Yimin Li,3 Haibo Zhang3,8–10 1Department of Critical Care Medicine, The 2nd Affiliated Hospital of Harbin Medical University, Harbin, Heilongjiang, People’s Republic of China; 2Department of Emergency and Critical Care Medicine, Chiba Aoba Municipal Hospital, Chiba, Japan; 3The State Key Laboratory of Respiratory Disease, and The 1st Affiliated Hospital of Guangzhou Medical University, Guangzhou, People’s Republic of China; 4Department of Medicine, McMaster University, Hamilton, Canada; 5Department of Critical Care Medicine, The 1st Affiliated Hospital of Sun Yat-Sen University, Guangzhou, People’s Republic of China; 6Keenan Research Center for Biomedical Science of Unity Health Toronto, Toronto, Canada; 7Department of Critical Care Medicine, The 1st Affiliated Hospital of Harbin Medical University, Harbin, Heilongjiang, People’s Republic of China; 8Interdepartmental Division of Critical Care Medicine, University of Toronto, Ontario, Canada; 9Departments of Anesthesia, University of Toronto, Ontario, Canada; 10Physiology, University of Toronto, Ontario, Canada*These authors contributed equally to this workCorrespondence: Kaijiang Yu 23 Youzheng Street, Harbin, Heilongjiang 150001, People’s Republic of ChinaTel/Fax +86 451-8555-2666Email drkaijiang@163.comYimin Li 151 Yanjiang Road West, Guangzhou, Guangdong 510120, People’s Republic of ChinaTel/Fax +86 20-8306-2961Email dryiminli@vip.163.comObjective: Neutrophil infiltration and release of the abundant human neutrophil peptides (HNP) are a common clinical feature in critically ill patients. We tested a hypothesis that different cell types respond to HNP differently in lung microenvironment that may influence the host responses.Methods: Plasma concentrations of HNP were measured in healthy volunteers and patients with sepsis. Cells including the bacteria P. aeruginosa, human lung epithelial cells and mesenchymal stromal cells (MSCs) were exposed to various concentrations of HNP. Bacterial killing, epithelial cell inflammation, MSC adhesion and behaviours were examined after HNP stimulation.Results: Incubation of P. aeruginosa or stimulation of human lung epithelial cells with HNP resulted in bacterial killing or IL-8 production at a dose of 50 μg/mL, while MSC adhesion and alternations of secretome profiles took place after HNP stimulation at a dose of 10 μg/mL. The secretome profile changes were characterized by increased release of the IL-6 family members such as C-reactive protein (CRP), leukemia inhibitory factor (LIF) and interleukin (IL-11), and first apoptosis signal (FAS) and platelet-derived growth factor-AA as compared to a vehicle control group.Conclusion: Stimulation of MSCs with HNP resulted in changes of secretome profiles at 5-fold lower concentration than that required for bacterial killing and lung epithelial inflammation. This undisclosed risk factor of HNP in lung environment should be taken into consideration when MSCs are applied as cell therapy in inflammatory lung diseases.Keywords: defensins, sepsis, lung injury, cytokines

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)0.000
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 score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
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 science0.0000.000
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 head0.072
GPT teacher head0.440
Teacher spread0.368 · 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
Published2019
Admission routes1
Has abstractyes

Explore more

Same venueDOAJ (DOAJ: Directory of Open Access Journals)Same topicS100 Proteins and AnnexinsFrench-language works237,207