Supplementation‐dependent differences in the rates of embryonic stem cell self‐renewal, differentiation, and apoptosis
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Although it is known that leukemia inhibitory factor (LIF) supports the derivation and expansion of murine embryonic stem (ES) cells, it is unclear whether this is due to inhibitory effects of LIF on ES cell differentiation or stimulatory effects on ES cell survival and proliferation. Using an ES cell line transgenic for green fluorescent protein (GFP) expression under control of the Oct4 promoter, we were able to simultaneously track the responses of live Oct4-GFP-positive (ES) and -negative (differentiated) fractions to LIF, serum, and other growth factors. Our findings show that, in addition to inhibiting differentiation of undifferentiated cells, the administration of LIF resulted in a distinct dose-dependent survival and proliferation advantage, thus enabling the long-term propagation of undifferentiated cells. Competitive responses from the differentiated cell fraction could only be elicited upon addition of serum, fibroblast growth factor-4 (FGF-4), or insulin-like growth factor-1 (IGF-1). The growth factors did not induce additional differentiation of ES cells, but rather they significantly improved the proliferation of already differentiated cells. Our analyses show that, by adjusting culture conditions, including the type and amount of growth factors or cytokines present, the frequency of media exchange, and the presence or absence of serum, we could selectively and specifically alter the survival, proliferation, and differentiation dynamics of the two subpopulations, and thus effectively control population outputs. Our findings therefore have important applications in engineering stem cell culture systems to predictably generate desired stem cells or their derivatives for various regenerative therapies.
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.
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) | 0.000 | 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) | 0.000 | 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 it