Salivary Functional Antibody Secretion Is Reduced in Older Adults: A Potential Mechanism of Increased Susceptibility to Bacterial Infection in the Elderly
Bibliographic record
Abstract
Background.Bacterial infections in the elderly are common and associated with high morbidity and mortality, with pneumonia the second commonest cause of death.Reductions in antibodies against specific bacterial antigens in saliva and serum could contribute to infection risk in older adults, although they have yet to be examined in relation to age.Method.IgG, IgA and IgM antibody levels in paired saliva and serum samples were measured against 12 pneumococcal, 4 meningococcal and haemophilus polysaccharide antigens and diphtheria and tetanus toxoids in healthy younger (n = 28, 21-34 years) and older (n = 44, 60-80 years) adults.Results.Older adults had lower antibody concentrations in saliva than young adults, with the most striking differences observed for salivary antibody secretion rates.In serum, older adults registered lower concentrations for only a minority of antibodies.Young adults who had previously received a polysaccharide pneumococcal vaccination (PPV23) had higher levels of anti-pneumococcal antibodies in serum and in saliva.Only minor differences were observed in antibody levels between older adults who had/had not received PPV23, and there was no evidence of memory in saliva.Conclusions.Age differences were much greater in salivary antibodies than in serum; older adults had reduced salivary secretion rates of antibodies across bacterial antigens.This decline in local immunity may contribute to increased infection risk in the elderly.The poor memory from pneumococcal vaccination in serum and saliva suggests that PPV23 may be ineffective in older adults for both systemic and local protection. Key Words: Immune Function-Infection-BacteriaAge-related immune decline and dysregulation, immunosenescence, is associated with increased susceptibility to bacterial and viral infections (1).Infectious diseases in the elderly are more common and severe than in younger adults (2), with pneumonia being the second commonest cause of death in over 75s and community acquired pneumonia accounting for a fifth of all deaths (3,4).Streptococcus pneumoniae causes up to half of community acquired pneumonia and is a commensal bacteria of the upper respiratory tract but can Downloaded from https://academic.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".