Abstract 4548: Erythrose kill cancer cell in vitro and inhibit tumor growth in vivo
Bibliographic record
Abstract
Abstract In general, mutations in oncogenes and tumor suppressor genes are believed to represent the fundamental cause of carcinogenesis. Mitochondrial deficiency (Warburg effect) may be a direct or indirect consequence of these mutations. Accordingly, tumor cells depend on glycolysis rather than mitochondrial oxidative metabolism as energy source for their survival and proliferation. Targeting this kind of metabolism could offer a possibility for cancer treatment. Erythrose was used as an alternative energy source to test its inhibitory effect on several tumor cell lines in vitro and in vivo. Cancer cell lines (breast BT474 and MCF-7, brain U87mg, pancreas Panc-1, HEL, LL-2 Lewis lung, and colorectal CT26 and SW480 lines) were grown in DMEM + 10% FBS media with different concentrations of D-erythrose and cell growth was tested with the Trypan blue assay. In general, 70% of cancer cells did not survive after 24 hrs of culture with 500mg/L D-erythrose. Addition of ZnCl2 (40µM) doubled the cancer killing effect at 400mg/L D-erythrose. In addition, LL-2 Lewis lung cells were subcutaneously introduced into the immunocompetent C57BL/6 mice. After allowing tumor growth to 2.7±0.4mm wide diameters, a daily subcutaneous injection beside the tumor with D-erythrose (∼1g/kg bw) was administered for 25 days; controls received a PBS injection instead. Tumor growth in erythrose-treated mice was inhibited more than 90% by weight. We hypothesize that the administration of erythrose leads to CO2 production from oxidation in cytosol or mitochondria. Carbonic acid is formed from CO2 and water, accelerated by carbonic anhydrase (a zinc enzyme), which can convert lactate to lactic acid, and cause intracellular acidosis and cancer death since cancer cells have increased lactate production. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 101st Annual Meeting of the American Association for Cancer Research; 2010 Apr 17-21; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2010;70(8 Suppl):Abstract nr 4548.
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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) | 0.001 | 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) | 0.004 | 0.001 |
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".