International Journal of Biological Macromolecules, Journal Year: 2024, Volume and Issue: 282, P. 137040 - 137040
Published: Oct. 30, 2024
Language: Английский
International Journal of Biological Macromolecules, Journal Year: 2024, Volume and Issue: 282, P. 137040 - 137040
Published: Oct. 30, 2024
Language: Английский
Journal of Molecular Liquids, Journal Year: 2025, Volume and Issue: unknown, P. 127510 - 127510
Published: April 1, 2025
Language: Английский
Citations
1Next research., Journal Year: 2025, Volume and Issue: unknown, P. 100228 - 100228
Published: March 1, 2025
Language: Английский
Citations
0The Open Biomedical Engineering Journal, Journal Year: 2025, Volume and Issue: 19(1)
Published: May 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.
Language: Английский
Citations
0Applied Sciences, Journal Year: 2025, Volume and Issue: 15(11), P. 6040 - 6040
Published: May 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.
Language: Английский
Citations
0International Journal of Biological Macromolecules, Journal Year: 2024, Volume and Issue: 282, P. 137040 - 137040
Published: Oct. 30, 2024
Language: Английский
Citations
2