PREPARATION AND CHARACTERIZATION OF SELF-MICROEMUSIFYING DRUG DELIVERY SYSTEM (SMEDDS) OF CISPLATIN FOR ORAL USE IN OVARIAN CANCER TREATMENT
Bibliographic record
Abstract
Cancer is one of the most leading causes of death in the world.Ovarian cancer is the seventh most common cancer in women.Also, it has the highest, mortality rate among female reproductive system cancers (1).According to the American Cancer Society in 2018, 22240 new cases of ovarian cancer will be diagnosed and 14070 women will die of ovarian cancer in the United States (2).The highest incidences are related in Europe, Canada and the United States.The lowest incidences are reported in China and Africa.According to GLOBOCAN 2008 database, the incidence rates are reported as over 11 cases per 100000 in Europe, less than 3 cases per 100000 in Africa and 4-8 cases per 100000 in South American, Asian and Caribbean countries (3).The latest cancer mortality statistics of the World Health Organization (WHO) showed that mortality will increase by approximately 45% until 2030 (4).Ovarian cancer has different risk factors like family history, age, early age menarche, menopause, parity, oral contraceptive use, lactation, obesity, cigarette smoking and alcohol consumption (5-7).Epithelial ovarian cancer is the most common type of ovarian cancer.Early diagnosis increases the chances successful treatment.The pathogenesis of ovarian cancer hasnít been elucidated yet, but ovulation, hormonal factors and inflammations have an important role in it (8, 9).There are two types of ovarian tumors.Type I tumors tend to be less aggressive and slow-growing like low grade malign serous tumors, low grade malign endometrioid carcinoma and mucinous carcinoma.Type II tumors are more aggressive than Type I tumors.They are high grade malign serous carcinoma, carcinosarcoma and undifferentiated carcinoma (10, 11).Ovarian cancer is staged by using the FIGO staging system which has 4 stages.A tumor is limited to the ovary at stage I.During stage II, tumor involves one or both of the ovaries.Pelvic extension and primary peritoneal tumor occurred.At stage III, PHARMACEUTICAL TECHNOLOGY
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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) | 0.000 | 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) | 0.002 | 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".