Effects of aldo-keto reductase family 1 member A on osteoblast differentiation associated with lactate production in MC3T3-E1 preosteoblastic cells
Bibliographic record
Abstract
Aldo-keto reductase family 1 member A (AKR1A) is an NADPH-dependent aldehyde reductase widely expressed in mammalian tissues. In this study, induced differentiation of MC3T3-E1 preosteoblasts was found to increase AKR1A gene expression concomitantly increased NOx− (nitrite + nitrate), increased glucose uptake, increased [NAD(P)+]/[NAD(P)H] and lactate production but decreased reactive oxygen species (ROS) without changes in endothelial nitric oxide synthase (eNOS) expression in differentiated osteoblasts (OBs). A study using gain- and loss-of-function MC3T3-E1 cells indicated that AKR1A is essential for modulating OB differentiation and gene expression of collagen 1 A1, receptor activator of nuclear factor kappa-B ligand, and osteoprotegerin in OBs. Immunofluorescence microscopy also revealed that changes in AKR1A expression altered extracellular collagen formation in differentiated OBs. Consistently, analyses of alkaline phosphatase activity and calcium deposits of matrix mineralization by Alizarin Red S staining verified that AKR1A is involved in the regulation of OB differentiation and bone matrix formation. In addition, AKR1A gene alterations affected the levels of NOx−, eNOS expression, glucose uptake, [NAD(P)+]/[NAD(P)H] dinucleotide redox couples, lactate production, and ROS in differentiated OBs. Herein, we report that AKR1A-mediated denitrosylation may play a role in the regulation of lactate metabolism as well as redox homeostasis in cells, providing an efficient way to quickly gain energy and to significantly reduce oxidative stress for OB differentiation.
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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".