Sex differences in B cell frequencies and antibody responses following influenza vaccination in healthcare workers during the 2019–2020 season
Bibliographic record
Abstract
Abstract Annual influenza vaccination for healthcare workers (HCWs) is required at Johns Hopkins to reduce influenza spread in healthcare facilities. We conducted a clinical study to evaluate sex differences in virus-specific antibody-producing B cells (i.e., plasmablasts) following receipt of the seasonal influenza vaccine in a highly vaccinated population of healthcare workers. To understand sex differences in immune responses to the influenza vaccine in the HCWs, 83 participants consented to blood draws at baseline and 75 participants returned for the 7- and 28-days post-vaccination survey and blood draw. Participants received their annual quadrivalent influenza vaccine (QIV). Influenza A specific plasmablasts were quantified at baseline and day 7 post-vaccination. Males had a significantly greater percentage of influenza-specific plasmablasts than females after vaccination (p<0.0003) Plasma collected at baseline and at day 28 post-vaccination was used to measure neutralizing antibody (nAb) titers against H1N1 and H3N2 vaccine viruses. Neutralizing antibody responses against either the H1N1 and H3N2 viruses increase after vaccination to the same degree in both males and females. The proportion of plasmablasts at day 7 was significantly associated with the vaccine-induced fold rise in nAb. This relationship differed by sex, whereby for a given proportion of plasmablasts, females tended to mount a greater fold-rise in nAb than males. These data suggest that despite having potentially fewer plasmablasts after vaccination, females mount an antiviral antibody response to the influenza vaccine viruses equivalent to males. Identification of transcriptional differences in plasmablasts from male and female HCWs is ongoing.
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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) | 0.000 | 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) | 0.003 | 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 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".