Chronobiological Immunology: The Influence of Diurnal Variation on Circulating Lymphocytes
Bibliographic record
Abstract
There has been increasing interest surrounding the impact of the ‘biological clock’ on immunological responses. In 2017, the Nobel Prize in Physiology or Medicine was awarded to a team that discovered the genetic molecular mechanisms which regulate circadian rhythms. Many physiological events including immune responsiveness are linked to the circadian rhythm. Previous studies have demonstrated that a majority of patients with allergic rhinitis experience their most severe symptoms in the morning. A study of 765 patients in France with allergic rhinitis determined that the major symptoms of sneezing, stuffy nose and runny nose occur in the morning in approximately 70% of patients (1). While the increased severity of symptoms of allergic rhinitis with regards to circadian rhythm has been established, there is minimal evidence on the link between the symptom presentation and immune cell variation. One study analysed the diurnal variation of lymphocyte subsets of 25 healthy Caribbean participants, finding that CD4+ helper T-cell counts increased throughout the day, CD56+ and CD16+ natural killer cell counts showed no change and CD8+ cytotoxic T-cells and CD19+ B-cell counts increased between 8:30am and noon, demonstrating no change during the afternoon (2). While this study indicates some immune cell fluctuations, there is a lack of literature regarding the effect of time on lymphocyte subsets during the day. Due to the lack of data on the effect of diurnal variation on lymphocyte subsets, it is not clear whether the time of day should be a consideration during common blood tests. The aim of this study is to determine any variations between morning and afternoon blood collection on the prevalence of circulating CD3+, CD3+CD4+, CD3+CD8+, CD19+, CD16+ and CD56+ cells. 25 human participants will provide blood samples at 8:30am and 4:30pm timepoints in a single day. Participants will be randomly recruited and will consist of both males and females between 18 – 35 years of age. Samples will be analysed using flow cytometry (3) and live-cell gating will be conducted using propidium iodide assessment. A Student’s paired t-test will be applied as the primary form of statistical analysis to assess for any relevant diurnal variation induced changes. The literature suggesting that lymphocyte counts may increase during the night-time, and remain elevated throughout the morning also supports the observation that several immune conditions are exacerbated in the morning. As such, it is hypothesised that the prevalence of lymphocyte subpopulations will be the greatest in the morning sample. This study is being conducted as part of an Honours Research program with data collection 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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".