Immunometabolic analysis of primary murine group 2 innate lymphoid cells: a robust step-by-step approach
Bibliographic record
Abstract
Group 2 Innate Lymphoid Cells (ILC2s) have recently been shown to exert key regulatory functions in both innate and adaptive immune response networks that drive the establishment and progression of type 2 immunity. Although mainly tissue resident, ILC2s and their crosstalk within tissue microenvironments influence metabolism at both the local and systemic levels. In turn, the energetic demand and metabolic status within these systems shape the diverse phenotypes and effector functions of ILC2s. Deciphering these metabolic networks in ILC2s is therefore essential in understanding their various roles in health as well as their associated pathophysiologies. Here we detail a framework of experimental approaches to study key immunometabolic states of primary murine ILC2s and link them to unique phenotypes and their corresponding functionality. Utilizing flow cytometry, Single Cell ENergetic metabolism by profilIng Translation inHibition (SCENITH), and the Seahorse platform we provide a framework that allows in-depth analysis of cellular bioenergetic states to determine the immunometabolic wiring of ILC2s. Connecting immunometabolic states and networks to ILC2 phenotypes and effector functions with this method will allow future in-depth studies to assess the potential of novel pharmaceutics in altering ILC2 functionality in clinical settings.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 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".