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Record W4366827702 · doi:10.3389/fbioe.2023.1144624

Effective-mononuclear cell (E-MNC) therapy alleviates salivary gland damage by suppressing lymphocyte infiltration in Sjögren-like disease

2023· article· en· W4366827702 on OpenAlexaff
Kayo Hasegawa, Jorge Luis Montenegro Raudales, Takashi Ito, Takako Yoshida, Ryo Honma, Mayumi Iwatake, Simon D. Tran, Makoto Seki, Izumi Asahina, Yoshinori Sumita

Bibliographic record

VenueFrontiers in Bioengineering and Biotechnology · 2023
Typearticle
Languageen
FieldMedicine
TopicSalivary Gland Disorders and Functions
Canadian institutionsMcGill University
FundersJapan Society for the Promotion of Science
KeywordsPeripheral blood mononuclear cellNOD miceImmunologyImmune systemNodCD3Autoimmune diseaseCD8CD28MedicineAntibodyBiologyDiabetes mellitusIn vitroEndocrinology

Abstract

fetched live from OpenAlex

Introduction: Sjögren syndrome (SS) is an autoimmune disease characterized by salivary gland (SG) destruction leading to loss of secretory function. A hallmark of the disease is the presence of focal lymphocyte infiltration in SGs, which is predominantly composed of T cells. Currently, there are no effective therapies for SS. Recently, we demonstrated that a newly developed therapy using effective-mononuclear cells (E-MNCs) improved the function of radiation-injured SGs due to anti-inflammatory and regenerative effects. In this study, we investigated whether E-MNCs could ameliorate disease development in non-obese diabetic (NOD) mice as a model for primary SS. Methods: E-MNCs were obtained from peripheral blood mononuclear cells (PBMNCs) cultured for 7 days in serum-free medium supplemented with five specific recombinant proteins (5G culture). The anti-inflammatory characteristics of E-MNCs were then analyzed using a co-culture system with CD3/CD28-stimulated PBMNCs. To evaluate the therapeutic efficacy of E-MNCs against SS onset, E-MNCs were transplanted into SGs of NOD mice. Subsequently, saliva secretion, histological, and gene expression analyses of harvested SG were performed to investigate if E-MNCs therapy delays disease development. Results: First, we characterized that both human and mouse E-MNCs exhibited induction of CD11b/CD206-positive cells (M2 macrophages) and that human E-MNCs could inhibit inflammatory gene expressions in CD3/CD28- stimulated PBMNCs. Further analyses revealed that Msr1-and galectin3-positive macrophages (immunomodulatory M2c phenotype) were specifically induced in E-MNCs of both NOD and MHC class I-matched mice. Transplanted E-MNCs induced M2 macrophages and reduced the expression of T cell-derived chemokine-related and inflammatory genes in SG tissue of NOD mice at SS-onset. Then, E-MNCs suppressed the infiltration of CD4-positive T cells and facilitated the maintenance of saliva secretion for up to 12 weeks after E-MNC administration. Discussion: Thus, the immunomodulatory actions of E-MNCs could be part of a therapeutic strategy targeting the early stage of primary SS.

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 score0.268
Threshold uncertainty score0.694

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.005
GPT teacher head0.209
Teacher spread0.203 · 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

Citations7
Published2023
Admission routes1
Has abstractyes

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