No abstract

Probiotic microorganisms such as lactic acid bacteria (LAB) exert a number of strain-specific health-promoting activities attributed to their immunomodulatory, anti-inflammatory and anti-carcinogenic properties. Despite recent attention, our understanding of the biological processes involved in the beneficial effects of LAB strains is still limited. To this end, the present study investigated the growth-inhibitory effects of Lactobacillus casei ATCC 393 against experimental colon cancer. Administration of live Lactobacillus casei (as well as bacterial components thereof) on murine (CT26) and human (HT29) colon carcinoma cell lines raised a significant concentration- and time-dependent anti-proliferative effect, determined by cell viability assays. Specifically, a dramatic decrease in viability of colon cancer cells co-incubated with 109 CFU/mL L. casei for 24 hours was detected (78% for HT29 and 52% for CT26 cells). In addition, live L. casei induced apoptotic cell death in both cell lines as revealed by annexin V and propidium iodide staining. The significance of the in vitro anti-proliferative effects was further confirmed in an experimental tumor model. Oral daily administration of 109 CFU live L. casei for 13 days significantly inhibited in vivo growth of colon carcinoma cells, resulting in approximately 80% reduction in tumor volume of treated mice. Tumor growth inhibition was accompanied by L. casei-driven up-regulation of the TNF-related apoptosis-inducing ligand TRAIL and down-regulation of Survivin. Taken together, these findings provide evidence for beneficial tumor-inhibitory, anti-proliferative and pro-apoptotic effects driven by this probiotic LAB strain.

No abstract

Although these results need replication and further biomechanical research, PRP may promote tendon healing acceleration.

The development of artificial intelligence (AI) algorithms has permeated the medical field with great success. The widespread use of AI technology in diagnosing and treating several types of cancer, especially colorectal cancer (CRC), is now attracting substantial attention. CRC, which represents the third most commonly diagnosed malignancy in both men and women, is considered a leading cause of cancer-related deaths globally. Our review herein aims to provide in-depth knowledge and analysis of the AI applications in CRC screening, diagnosis, and treatment based on current literature. We also explore the role of recent advances in AI systems regarding medical diagnosis and therapy, with several promising results. CRC is a highly preventable disease, and AI-assisted techniques in routine screening represent a pivotal step in declining incidence rates of this malignancy. So far, computer-aided detection and characterization systems have been developed to increase the detection rate of adenomas. Furthermore, CRC treatment enters a new era with robotic surgery and novel computer-assisted drug delivery techniques. At the same time, healthcare is rapidly moving toward precision or personalized medicine. Machine learning models have the potential to contribute to individual-based cancer care and transform the future of medicine.