Immunosenescence in the nursing home elderly
Bibliographic record
Abstract
BACKGROUND: To describe T-cell and natural killer (NK) cell phenotypes within nursing home elderly. METHODS: Nursing home elderly were recruited from four nursing homes in Hamilton, Ontario between September 2010 and December 2011. Healthy adults were recruited from McMaster University between September 2011 and December 2011. Nursing home elderly ≥65 years were eligible; those on immunosuppressive medications were excluded. Healthy adults ≥18-64 years were eligible. CD8+ and CD4+ T-cells% and their subsets, T-regs% and NK cell subset% were compared between the nursing home elderly and healthy adults. RESULTS: 262 nursing home elderly were enrolled; median age 87 years and 81% were female. 16 healthy adults were enrolled; median age 31 and 50% were female. There was no significant difference between CD8+ T-cell% in nursing home and healthy adults (median 17.1 versus 18.0, p = 0.56), however there were fewer naïve CD8 + T-cell% (median 0.9 versus 5.2, p < 0.001), more terminally differentiated CD8 + T-cell% (median 7.3 versus 4.1, p = 0.004) and more senescent T-cell% (median 5.3 versus 3.1, p = 0.04) in the nursing home elderly. There were more CD4+ T-cell% in the nursing home elderly compared to healthy adults (median 45.5 versus 37.1, p = 0.001). Nursing home elderly had a higher CD4+/CD8+ ratio than healthy adults (2.6 versus 1.9, p = 0.048), higher T-reg% (median 1.8 versus 0.8, p < 0.001) and increased mature NK cell% (median 12.1 versus 5.4, p = 0.001) compared to healthy adults. CONCLUSION: Differences in naïve CD8+ T-cells, terminally differentiated and senescent CD8+ T-cells, T-regs and NK cell subsets were similar to studies involving community dwelling elderly. In contrast, the CD4+/CD8+ ratio was higher in nursing home elderly.
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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 | 0.001 |
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".