High glucose concentrations mask cellular phenotypes in a stem cell model of tuberous sclerosis complex
Bibliographic record
Abstract
Tuberous sclerosis complex (TSC) is a neurodevelopmental disorder caused by deletions in the TSC1 or TSC2 genes that is associated with epilepsy in up to 90% of patients. Seizures are suggested to start in benign brain tumors, cortical tubers, or in the perituberal tissue making these tubers an interesting target for further research into mechanisms underlying epileptogenesis in TSC. Animal models of TSC insufficiently capture the neurodevelopmental biology of cortical tubers, and hence, human stem cell-based in vitro models of TSC are being increasingly explored in attempts to recapitulate tuber development and epileptogenesis in TSC. However, in vitro culture conditions for stem cell-derived neurons do not necessarily mimic physiological conditions. For example, very high glucose concentrations of up to 25 mM are common in culture media formulations. As TSC is potentially caused by a disruption of the mechanistic target of rapamycin (mTOR) pathway, a main integrator of metabolic information and intracellular signaling, we aimed to examine the impact of different glucose concentrations in the culture media on cellular phenotypes implicated in tuber characteristics. Here, we present preliminary data from a pilot study exploring cortical neuronal differentiation on human embryonic stem cells (hES) harboring a TSC2 knockout mutation (TSC2-/-) and an isogenic control line (TSC2+/+). We show that the commonly used high glucose media profoundly mask cellular phenotypes in TSC2-/- cultures during neuronal differentiation. These phenotypes only become apparent when differentiating TSC2+/+ and TSC2-/- cultures in more physiologically relevant conditions of 5 mM glucose suggesting that the careful consideration of culture conditions is vital to ensuring biological relevance and translatability of stem cell models for neurological disorders such as TSC. This article is part of the Special Issue "Proceedings of the 7th London-Innsbruck Colloquium on Status Epilepticus and Acute Seizures".
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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 | 0.000 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".