Background: The integration of Artificial Intelligence (AI) technology in cancer care has gained unprecedented global attention over the past few decades. This has impacted the way that cancer care is practiced and delivered across settings. The purpose of this study was to explore the perspectives and experiences of healthcare professionals (HCPs) on cancer treatment and the need for AI. This study is a part of the INCISIVE European Union H2020 project's development of user requirements, which aims to fully explore the potential of AI-based cancer imaging technologies. Methods: A mixed-methods research design was employed. HCPs participating in cancer care in the UK, Greece, Italy, Spain, Cyprus, and Serbia were first surveyed anonymously online. Twenty-seven HCPs then participated in semi-structured interviews. Appropriate statistical method was adopted to report the survey results by using SPSS. The interviews were audio recorded, verbatim transcribed, and then thematically analysed supported by NVIVO. Results: The survey drew responses from 95 HCPs. The occurrence of diagnostic delay was reported by 56% (n = 28/50) for breast cancer, 64% (n = 27/42) for lung cancer, 76% (n = 34/45) for colorectal cancer and 42% (n = 16/38) for prostate cancer. A proportion of participants reported the occurrence of false positives in the accuracy of the current imaging techniques used: 64% (n = 32/50) reported this for breast cancer, 60% (n = 25/42) for lung cancer, 51% (n = 23/45) for colorectal cancer and 45% (n = 17/38) for prostate cancer. All participants agreed that the use of technology would enhance the care pathway for cancer patients. Despite the positive perspectives toward AI, certain limitations were also recorded. The majority (73%) of respondents (n = 69/95) reported they had never utilised technology in the care pathway which necessitates the need for education and training in the qualitative finding; compared to 27% (n = 26/95) who had and were still using it. Most, 89% of respondents (n = 85/95) said they would be opened to providing AI-based services in the future to improve medical imaging for cancer care. Interviews with HCPs revealed lack of widespread preparedness for AI in oncology, several barriers to introducing AI, and a need for education and training. Provision of AI training, increasing public awareness of AI, using evidence-based technology, and developing AI based interventions that will not replace HCPs were some of the recommendations. Conclusion: HCPs reported favourable opinions of AI-based cancer imaging technologies and noted a number of care pathway concerns where AI can be useful. For the future design and execution of the INCISIVE project and other comparable AI-based projects, the characteristics and recommendations offered in the current research can serve as a reference.

(1) Background: A proposed approach to promote periodontal tissue regeneration in cases of peri-implantitis is the local administration of growth factors at the implant site. Recombinant human bone morphogenetic protein-2 (rh-BMP-2) can effectively promote bone regeneration and osseointegration and the development of appropriate carriers for its delivery is of paramount importance. The aim of the present study was to develop SBA-15 mesoporous nanoparticles (MSNs) with varying porosity, evaluate their biocompatibility with human Periodontal Ligament Cells (hPDLCs) and to investigate their effectiveness as carriers of rh-BMP-2. (2) Methods: SBA-15 type mesoporous silicas were synthesized via sol–gel reaction. The calcined SBA-15 samples were characterized by N₂ porosimetry, Fourier transform–infrared spectrometry (FTIR), Scanning (SEM) and Transmission Electron Microscopy (TEM). Rh-BMP-2 loading and release kinetics were evaluated by UV spectroscopy. (3) Results: MSNs presented hexagonally arranged, tubular pores of varying length and diameter. Slightly higher loading capacity was achieved for SBA-15 with large pores that presented good hemocompatibility. MTT assay revealed no cytotoxic effects for all the tested materials, while SBA-15 with large pores induced a significant upregulation of cell viability at day 5. (4) Conclusions: SBA-15 MSNs may prove a valuable delivery platform towards the effective release of bone-inducing proteins.

Finding new ways to cost-effectively facilitate population screening and improve cancer diagnoses at an early stage supported by data-driven AI models provides unprecedented opportunities to reduce cancer related mortality. This work presents the INCISIVE project initiative towards enhancing AI solutions for health imaging by unifying, harmonizing, and securely sharing scattered cancer-related data to ensure large datasets which are critically needed to develop and evaluate trustworthy AI models. The adopted solutions of the INCISIVE project have been outlined in terms of data collection, harmonization, data sharing, and federated data storage in compliance with legal, ethical, and FAIR principles. Experiences and examples feature breast cancer data integration and mammography collection, indicating the current progress, challenges, and future directions.

Background: Artemisia absinthium (A. absinthium), commonly known as absinthe, is a perennial plant with distinctive broad ovate pointed leaves of a silvery-gray color, reaching a height of 1.5 m. The utilization of this herb as a source of natural compounds and as the primary ingredient in the alcoholic beverage absinthe has recently seen a resurgence following a period of prohibition. This study investigates the biological effects of A. absinthium extract on healthy human periodontal ligament stem cells (hPDLSCs) and the human tongue squamous carcinoma cell line (HSC-3). Methods: A. absinthium element characterization was performed using High-Performance Liquid Chromatography (HPLC) and the Folin method. Alizarin assays evaluated the osteogenic capacity of human periodontal ligament cells (hPDLSCs) while CCK-8 and MTT determined the cytotoxicity of the extract against HSC-3 and hPDLSCs. Results: High artemisinin levels were detected, revealing a concentration of 89 μM (25 μg/mL). The total phenolic concentration of the extract was 1.07 mM +/− 0.11. The in vitro cytotoxicity assays revealed the biocompatible profile of the Artemisia extract in hPDLSCs without exhibiting any osteogenic potential. After 24 h of incubation with HSC-3, Artemisia extract (10 µM) decreased cancer cell viability by 99% and artemisinin by 64%, and increased the expression of Caspase 3 and 9 almost six and two times, respectively. Conclusions: In summary, our preliminary findings suggest that A. absinthium extract exhibits a toxic effect against carcinoma cell lines without affecting healthy human periodontal ligament stem cells.