Macrophage inflammatory response increases in adult female exposed to neonate stress
Bibliographic record
Abstract
Abstract Impacts of stress on the immune system vary depending on the nature, intensity, and time during which stress is experienced (eg, acute stress is pro-inflammatory vs chronic stress is anti-inflammatory). However, there is limited knowledge on the long-term impact of early life stress on immune responses. Given that immune programming occurs early in life and that immunity and stress both involve sexual dimorphisms, our hypothesis is that neonatal maternal separation (NMS) induces sex-specific immune alterations. Objective Our objective is to evaluate the influence of early life stress on immune response in adult and its dimorphism related to biological sex. Methods We used a well-established rat model of early life stress, NMS, in which we observed sex-specific modulations of the myeloid compartment. Thus, we evaluated the impact of NMS on macrophage activation using LPS stimulation of bone-marrow derived macrophages (BMDM) in vitro. Expression of activation (MHCII, CD40, CD86 and CD80) and maturation markers (SIRPα, CD11b, CD200 and CD200R) were analyzed by flow cytometry. TNF levels were measured by ELISA. Results LPS stimulation of female NMS BMDM had higher expression of activation markers compared to controls. Inflammatory cytokine levels, TNF, increased after LPS stimulation and further increased in female NMS, whereas male NMS level was lower than control male. Futhermore, LPS stimulation lowered CD200 receptor (CD200R) to a greater extent in male NMS than in female NMS. Conclusion These results suggest that NMS accentuates the pro-inflammatory response in adult female (but not in male) and will provide a strong base for improving sex-specific interventions in the context of diseases involving stress and the immune system. Supported by grants from CIHR, QRHN and CRIUCPQ
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".