ANTITUMORAL POTENTIAL OF GREEN MICROALGAE EXTRACTS IN CHRONIC MYELOID LEUKEMIA (CML) IN VITRO MODEL
Bibliographic record
Abstract
Bioprospected microalgae collected from Northern Ontario, Canada water bodies have been shown to produce bioactive molecules, including carotenoids, polysaccharides, vitamins, and lipids with high pharmacological potential. Several studies in Canada with these microalgae have confirmed extracts with antioxidant, antimicrobial, and anticancer activity. Chronic myeloid leukemia (CML) is a clonal hematopoietic stem cell disorder and accounts for approximately 30% of the incidence of adult leukemias. Despite the use of tyrosine kinase inhibitors (TKIs) has improved the treatment and the prognosis of patients with CML therapeutic failures and adverse effects make treatment difficult, highlighting the need for the study of new molecules with antileukemic potential. This study aims to evaluate the in vitro antileukemic potential of different microalgae extracts in the K-562 cell line. Bioprospected microalgae strains S5, P981 ( Coccomyxa sp .), LL1 ( Scenedesmus sp .), LL2A, and CC ( Chlamydomonas sp .) were cultivated for 14 days in Bold's Basal Medium (BBM) with pH 7 under 16 hr:8 hr light-dark cycles, at 25°C, and were kept continuously agitated at 150 rpm. The microalgae were then harvested and methanol, ethanol, and aqueous extraction were performed on each strain. Tubes were placed under vacuum to evaporate the remaining solvent and the crude extract was weighted, DMSO was added to obtain a stock solution of microalgae extracts (ME) at 10 mg/mL. The CML in vitro model K-562 was plated in a 96-well plate and the microalgae extracts were added in a single dose (100 μg/mL) or in a concentration-response curve (200 μg/mL – 3.125 μg/mL) for 72 hours for evaluate the viability and the Half-maximal inhibitory concentration (IC 50 ) of the most cytotoxic ME, respectively by the MTT method. Fifteen extracts were produced, the ethanolic extracts from CC, LL2A, and P981 presented the highest inhibition percentages in the CML cell line, being 53.67 %, 54.69 %, and 47.09 %, respectively, and were chosen for the definition of the IC 50 . The extracts showed high antileukemic activity, being 80.22 μg/mL for CC, 91.93 μg/mL for LL2A, and 96.18 μg/mL for P918 ethanolic MEs. Previous studies from bioprospected microalgae collected from Northern Ontario have shown their antimicrobial, antiviral, antioxidant as well as antitumoral activity against ovarian and breast cancer cell lines. Ethanolic extracts possess compounds such as alkaloids, flavonoids, glycosides, terpenoids, tannins, saponins, and reducing sugars being sources of compounds with pharmaceutical properties. Our results demonstrated the antileukemic activity with an IC 50 of 80 – 96 μg/mL, corroborating with other studies in vitro . The initial results attested that the ethanolic extracts derived from green microalgae presented high antileukemic potential in the CML in vitro model, showing a promising source of new compounds with pharmacological activity. Further research is needed to visualize which compounds are present in the ethanolic ME that can confer its antileukemic activity and to better describe their mechanism of action in vitro and in vivo .
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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 | 0.000 |
| 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".