Advanced modeling of bioenergetics in the mitochondrial electron transport chain with emphasis on complex IV
Bibliographic record
Abstract
BACKGROUND: Mitochondrial bioenergetics are essential for cellular function, specifically the intricacies of the electron transport chain (ETC), with Complex IV playing a crucial role in unraveling the mechanisms governing energy production. Mathematical models offer a valuable approach to simulate these complex processes, providing insights into normal mitochondrial function and aberrations associated with various diseases, including neurodegenerative disorders. Our research focuses on introducing and refining a mathematical model, emphasizing Complex IV in the ETC, with objectives including incorporating mitochondrial activity modulation using inhibiting and uncoupling reagents, akin to oxygen consumption experiments. Rigorous validation, calibrating against Oroboros Oxygraph-2k data from C57BL/6 mouse mitochondria, ensures accurate reproduction of dynamic bioenergetic activities. The developed graphical user interface (GUI) complements objectives, providing an in silico platform for seamless hypothesis testing (in MATLAB). METHOD: Employing an innovative kinetic methodology, our research integrates inhibiting reagents (oligomycin, rotenone, antimycin A, FCCP) into the developed computational model to simulate bioenergetic responses across varied physiological conditions. Optimization of the Mean Square Error (MSE) objective function using multiple optimizing algorithms, including the genetic algorithm, and calibration against Oroboros Oxygraph-2k data using freshly isolated mitochondria from C57BL/6 mice ensures rigorous validation of the model's precision under both unperturbed and perturbed scenarios. These outcomes unequivocally affirm the model's efficacy in accurately simulating the intricate contributions of Complex IV to bioenergetics. RESULT: The outcomes highlight the model's efficacy in reproducing bioenergetic activities, mirroring experimental outcomes. The GUI facilitates user-friendly in silico simulations, offering a valuable complement to traditional experiments. Beyond bioenergetics, the model proves beneficial in studying mitochondrial dysfunction, presenting insights into neurodegenerative diseases. The model's potential for early detection and therapeutic intervention contributes to advancements in understanding and treating neurological disorders. CONCLUSION: Our refined mathematical model successfully simulates mitochondrial bioenergetics, emphasizing Complex IV dynamics. Validated against experimental data, the model accurately reproduces bioenergetic activities and demonstrates the potential for studying mitochondrial dysfunction and neurodegenerative diseases. The integration of inhibiting and uncoupling reagents, along with the user-friendly GUI, enhances accessibility and usability. Our research contributes to advancing the medical understanding, emphasizing the role of computational models in unraveling mitochondrial complexities in neurological disorders.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".