Bibliographic record
Abstract
Growing retinal stem cell (RSC) clonal spheres in traditional static culture is associated with low expansion rate and poor survival attributed to loss of cells during the enzymatic dissociation steps. Another problematic issue is the difficulty to mimic in vivo stem cell niche conditions. Using our traditional lab protocol, only 0.2% of the pigmented ciliary epithelium cells (CE) give rise to floating RSC clonal spheres in serum free conditions. These issues have hindered our ability to study the signaling pathways governing RSC proliferation and expansion in vitro. To overcome these limitations, I used microcarriers (MCs) in a suspension stirring bioreactor (SSB) to help achieve sufficient numbers suitable for differentiation and transplantation. Using this new protocol, I achieved a significant (10-fold) enrichment of RSC yield compared to conventional static culture techniques using a combination of FACTIII MCs and relative hypoxia (5%) inside the bioreactor. My work showed that hypoxia (5% O2) was associated with better RSC expansion across all platforms which was attributed to hypoxia-induced boosting survival and/or symmetric division of stem cells. RSC spheres were thought to be unvaried and were randomly picked and placed on laminin extracellular matrix (ECM) in static plates. In my work, I found noticeable variance in the pigment distribution between RSC spheres which led me to categorize them into three different groups according to their pigmentation, I also noted that this variance in pigment level and distribution was associated with contrasting differentiation potentials. RSCs were classified into three morphological groups: heavily pigmented (HP), lightly pigmented (LP) and centrally pigmented (CP) spheres. Unlike the other two sphere types, CP spheres were capable of producing highly proliferative progenitors (producing large number of cobblestone-like cell lawns) in adherent culture that differentiate into retinal pigment epithelium (RPE) cells. I found that the individual stem cells that (clonally) formed the three sphere types appear homogeneous, but it is their downstream progenitors that are different. I showed that CP spheres contain a population of early RPE progenitors that respond to proliferative signals from the surrounding non-pigmented neural retinal cells while The HP and LP spheres do not respond to these signals.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| 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 | 0.001 | 0.000 |
| 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".