Bibliographic record
Abstract
Abstract Over the past decade, the metabolic alterations that occur during tumorigenesis have been recognized as a key feature required for the transformation and maintenance of malignant cells. In order to meet the demands of unrestrained growth, tumor cells must adopt metabolic phenotypes that provide sufficient energy generation, biosynthetic precursor molecules, maintenance of redox/oxidative stress balance and intracellular biochemical homeostasis for growth and survival. Many of these deregulated pathways may predispose premalignant cells to genomic instability resulting to aneuploidy. These phenotypes allow tumor cells to cease functioning as part of an integrated tissue, and evolve independently along a trajectory ultimately leading to malignant disease. During this process, cells must adapt to abnormal microenvironmental conditions that develop after tissue architecture and homeostatic regulation are disrupted. Based on recent work, we will provide an overview of the metabolic alterations, such as mutations in isocitrate dehydrogenase genes that occur in malignancies of the myeloid an lymphoid system. Although the importance of these metabolic alterations to specific disease states, including Acute Myeloid Leukemia and T cell lymphomas, remains to be determined, there may be opportunities for novel therapeutic intervention. Recent advances based on these molecular changes will be discussed. Disclosures No relevant conflicts of interest to declare.
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.
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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".