International Journal of Biological Macromolecules, Год журнала: 2024, Номер 282, С. 137040 - 137040
Опубликована: Окт. 30, 2024
Язык: Английский
International Journal of Biological Macromolecules, Год журнала: 2024, Номер 282, С. 137040 - 137040
Опубликована: Окт. 30, 2024
Язык: Английский
Journal of Molecular Liquids, Год журнала: 2025, Номер unknown, С. 127510 - 127510
Опубликована: Апрель 1, 2025
Язык: Английский
Процитировано
1Next research., Год журнала: 2025, Номер unknown, С. 100228 - 100228
Опубликована: Март 1, 2025
Язык: Английский
Процитировано
0The Open Biomedical Engineering Journal, Год журнала: 2025, Номер 19(1)
Опубликована: Май 2, 2025
Objective Immune Checkpoint Inhibitors (ICIs) have transformed the field of oncology by improving capacity immune system to combat malignancies. This review investigates mechanisms ICIs, their adverse effects, resistance mechanisms, and role Artificial Intelligence (AI) And Machine Learning (ML) in predicting treatment outcomes. Methods Materials A literature search was conducted using PubMed, Google Scholar, Web Science identify pertinent studies, clinical trials, articles. The study concentrated on seven ICIs that been approved are designed target PD-1, PD-L1, CTLA-4 pathways. data were derived from guidelines expert opinions. Results illustrated efficacy a variety malignancies, such as renal cell carcinoma, non-small lung cancer, melanoma. Their utilization, whether monotherapy or conjunction with chemotherapy, radiotherapy, targeted therapies, has substantially enhanced survival. Nevertheless, management Immune-Related Adverse Events (irAEs) affect multiple organ systems is imperative. In certain patients, ICI also restricted mechanisms. AI/ML-driven models demonstrate potential for anticipating patient responses, optimizing strategies, reducing toxicity risks. Conclusion revolutionized cancer therapy; however, there still obstacles responses managing effects. emphasizes innovative use AI/ML improve precision safety ICI. additional research required due absence reliable predictive biomarkers variability responses. order enhance outcomes reduce toxicity, future should AI-driven incorporate multi-omics approaches.
Язык: Английский
Процитировано
0Applied Sciences, Год журнала: 2025, Номер 15(11), С. 6040 - 6040
Опубликована: Май 27, 2025
The vapor pressures, pv, of three ionic compounds used as starting materials deep eutectic systems, namely, tetrabutylammonium bromide (TBA-Br), trifluoromethanesulfonate (TBA-TFO), and bis(trifluoromethanesulfonyl)imide (TBA-NTF2), were measured using isothermal thermogravimetry. TBA-Br displays large values reaching ≈700 Pa at 170 °C. TBA-NTF2 is the less volatile liquid, with a pressure ≈1 240 °C, while TBA-TFO has slightly higher value about 3 same temperature. pv for NTF2-containing compound are comparable to those liquids containing anion. obtained mean vaporization enthalpy, ΔHvap, (≈170 kJ mol−1) than (≈145 mol−1). enthalpy fall within typical range observed liquids.
Язык: Английский
Процитировано
0International Journal of Biological Macromolecules, Год журнала: 2024, Номер 282, С. 137040 - 137040
Опубликована: Окт. 30, 2024
Язык: Английский
Процитировано
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