Incorporating microglia‐like cells in human induced pluripotent stem cell‐derived retinal organoids
Bibliographic record
Abstract
Microglia are the primary resident immune cells in the retina. They regulate neuronal survival and synaptic pruning making them essential for normal development. Following injury, they mediate adaptive responses and under pathological conditions they can trigger neurodegeneration exacerbating the effect of a disease. Retinal organoids derived from human induced pluripotent stem cells (hiPSCs) are increasingly being used for a range of applications, including disease modelling, development of new therapies and in the study of retinogenesis. Despite many similarities to the retinas developed in vivo, they lack some key physiological features, including immune cells. We engineered an hiPSC co-culture system containing retinal organoids and microglia-like (iMG) cells and tested their retinal invasion capacity and function. We incorporated iMG into retinal organoids at 13 weeks and tested their effect on function and development at 15 and 22 weeks of differentiation. Our key findings showed that iMG cells were able to respond to endotoxin challenge in monocultures and when co-cultured with the organoids. We show that retinal organoids developed normally and retained their ability to generate spiking activity in response to light. Thus, this new co-culture immunocompetent in vitro retinal model provides a platform with greater relevance to the in vivo human retina.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".