Immunomodulatory Macrophages Enable E-MNC Therapy for Radiation-Induced Salivary Gland Hypofunction
Bibliographic record
Abstract
A newly developed therapy using effective-mononuclear cells (E-MNCs) is reportedly effective against radiation-damaged salivary glands (SGs) due to anti-inflammatory and revascularization effects. However, the cellular working mechanism of E-MNC therapy in SGs remains to be elucidated. In this study, E-MNCs were induced from peripheral blood mononuclear cells (PBMNCs) by culture for 5-7 days in medium supplemented with five specific recombinant proteins (5G-culture). We analyzed the anti-inflammatory characteristics of macrophage fraction of E-MNCs using a co-culture model with CD3/CD28-stimulated PBMNCs. To test therapeutic efficacy in vivo, either E-MNCs or E-MNCs depleted of CD11b-positive cells were transplanted intraglandularly into mice with radiation-damaged SGs. Following transplantation, SG function recovery and immunohistochemical analyses of harvested SGs were assessed to determine if CD11b-positive macrophages contributed to tissue regeneration. The results indicated that CD11b/CD206-positive (M2-like) macrophages were specifically induced in E-MNCs during 5G-culture, and Msr1- and galectin3-positive cells (immunomodulatory macrophages) were predominant. CD11b-positive fraction of E-MNCs significantly inhibited the expression of inflammation-related genes in CD3/CD28-stimulated PBMNCs. Transplanted E-MNCs exhibited a therapeutic effect on saliva secretion and reduced tissue fibrosis in radiation-damaged SGs, whereas E-MNCs depleted of CD11b-positive cells and radiated controls did not. Immunohistochemical analyses revealed HMGB1 phagocytosis and IGF1 secretion by CD11b/Msr1-positive macrophages from both transplanted E-MNCs and host M2-macrophages. Thus, the anti-inflammatory and tissue-regenerative effects observed in E-MNC therapy against radiation-damaged SGs can be partly explained by the immunomodulatory effect of M2-dominant macrophage fraction.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".