Leveraging 5G technology for robotic surgery and cancer care.

BACKGROUND: The field of robotic surgery has seen significant advancements in the past few years and it has been adopted in many large hospitals in the United States and worldwide as a standard for various procedures in recent years. However, the location of many hospitals in urban areas and a lack of surgical expertise in the rural areas could lead to increased travel time and treatment delays for patients in need of robotic surgical management, including cancer patients. The fifth generation (5G) networks have been deployed by various telecom companies in multiple countries worldwide. Our aim is to update the readers about the novel technology and the current scenario of surgical procedures performed using 5G technology. In this article, we also discuss how the technology could aid cancer patients requiring surgical management, the future perspectives, the potential challenges, and the limitations, which would need to overcome prior to widespread real-life use of the technology for cancer care. RECENT FINDINGS: The expansion of 5G technology has enabled some countries to conduct remote surgical procedures, tele-mentored and real-time interactive procedures on animal models, cadavers, and humans, demonstrating that 5G networks could offer a potential solution to previously experienced latency and reliability hurdles during the remote surgeries performed in the 2000s. CONCLUSION: New technological advancements could serve as a ground for emerging novel therapeutic applications. While limitations and challenges related to the 5G infrastructure, cost, compatibility, and security exist; researching to overcome the limitations and comprehend the potential benefits of integrating the technology into practice would be imminent before widespread clinical use. Remote and tele-mentored 5G-powered procedures could offer a new tool in improving the care of patients requiring robotic surgical management such as prostate cancer patients.

Differential Effects of Rapamycin on Glucose Metabolism in Nine Inbred Strains.

Studies in mice suggest that rapamycin has a negative impact on glucose homeostasis by inducing insulin resistance. However, results have been inconsistent and difficult to assess because the strains, methods of treatment, and analysis vary among studies. Using a consistent protocol, we surveyed nine inbred strains of mice for the effect of rapamycin on various aspects of glucose metabolism. Across all strains, rapamycin significantly delayed glucose clearance after challenge. However, rapamycin showed no main effect on systemic insulin sensitivity. Analysis of individual strains shows that rapamycin induced higher glucose values at 15 minutes post-challenge in 7/9 strains. However, only three strains show rapamycin-induced reduction in glucose clearance from 15 to 120 minutes. Although pancreatic insulin content was reduced by rapamycin in seven strains, none showed reduced serum insulin values. Although one strain showed no effects of rapamycin on glucose metabolism (129), another showed increased systemic insulin sensitivity (B6). We suggest that rapamycin likely inhibits insulin production and secretion in most strains while having strain-specific effects on glucose clearance without altering systemic insulin sensitivity. This strain survey indicates that genetic differences greatly influence the metabolic response to rapamycin.

Rapamycin treatment benefits glucose metabolism in mouse models of type 2 diabetes.

Numerous studies suggest that rapamycin treatment promotes insulin resistance, implying that rapamycin could have negative effects on patients with, or at risk for, type 2 diabetes (T2D). New evidence, however, indicates that rapamycin treatment produces some benefits to energy metabolism, even in the context of T2D. Here, we survey 5 mouse models of T2D (KK, KK-Ay, NONcNZO10, BKS-db/db, TALLYHO) to quantify effects of rapamycin on well-recognized markers of glucose homeostasis within a wide range of T2D environments. Interestingly, dietary rapamycin treatment did not exacerbate impaired glucose or insulin tolerance, or elevate circulating lipids as T2D progressed. In fact, rapamycin increased insulin sensitivity and reduced weight gain in 3 models, and decreased hyperinsulinemia in 2 models. A key covariate of this genetically-based, differential response was pancreatic insulin content (PIC): Models with low PIC exhibited more beneficial effects than models with high PIC. However, a minimal PIC threshold may exist, below which hypoinsulinemic hyperglycemia develops, as it did in TALLYHO. Our results, along with other studies, indicate that beneficial or detrimental metabolic effects of rapamycin treatment, in a diabetic or pre-diabetic context, are driven by the interaction of rapamycin with the individual model's pancreatic physiology.