Robotic surgery has applications in many medical specialties, including urology, general surgery, and surgical oncology. In the context of a widespread resource and personnel shortage in Low- and Middle-Income Countries (LMICs), the use of robotics in surgery may help to reduce physician burnout, surgical site infections, and hospital stays. However, a lack of haptic feedback and potential socioeconomic factors such as high implementation costs and a lack of trained personnel may limit its accessibility and application. Specific improvements focused on improved financial and technical support to LMICs can help improve access and have the potential to transform the surgical experience for both surgeons and patients in LMICs. This review focuses on the evolution of robotic surgery, with an emphasis on challenges and recommendations to facilitate wider implementation and improved patient outcomes.

Cardiac amyloidosis is caused by the extracellular deposition of amyloid fibrils in the heart, involving not only the myocardium but also any cardiovascular structure. Indeed, this progressive infiltrative disease also involves the cardiac valves and, specifically, shows a high prevalence with aortic stenosis. Misfolded protein infiltration in the aortic valve leads to tissue damage resulting in the onset or worsening of valve stenosis. Transthyretin cardiac amyloidosis and aortic stenosis coexist in patients > 65 years in about 4–16% of cases, especially in those undergoing transcatheter aortic valve replacement. Diagnostic workup for cardiac amyloidosis in patients with aortic stenosis is based on a multi-parametric approach considering clinical assessment, electrocardiogram, haematologic tests, basic and advanced echocardiography, cardiac magnetic resonance, and technetium labelled cardiac scintigraphy like technetium-99 m (99mTc)-pyrophosphate, 99mTc-3,3-diphosphono-1,2-propanodicarboxylic acid, and 99mTc-hydroxymethylene diphosphonate. However, a biopsy is the traditional gold standard for diagnosis. The prognosis of patients with coexisting cardiac amyloidosis and aortic stenosis is still under evaluation. The combination of these two pathologies worsens the prognosis. Regarding treatment, mortality is reduced in patients with cardiac amyloidosis and severe aortic stenosis after undergoing transcatheter aortic valve replacement. Further studies are needed to confirm these findings and to understand whether the diagnosis of cardiac amyloidosis could affect therapeutic strategies. The aim of this review is to critically expose the current state-of-art regarding the association of cardiac amyloidosis with aortic stenosis, from pathophysiology to treatment.

The evolution of AI and data science has aided in mechanizing several aspects of medical care requiring critical thinking: diagnosis, risk stratification, and management, thus mitigating the burden of physicians and reducing the likelihood of human error. AI modalities have expanded feet to the specialty of pediatric cardiology as well. We conducted a scoping review searching the Scopus, Embase, and PubMed databases covering the recent literature between 2002–2022. We found that the use of neural networks and machine learning has significantly improved the diagnostic value of cardiac magnetic resonance imaging, echocardiograms, computer tomography scans, and electrocardiographs, thus augmenting the clinicians’ diagnostic accuracy of pediatric heart diseases. The use of AI-based prediction algorithms in pediatric cardiac surgeries improves postoperative outcomes and prognosis to a great extent. Risk stratification and the prediction of treatment outcomes are feasible using the key clinical findings of each CHD with appropriate computational algorithms. Notably, AI can revolutionize prenatal prediction as well as the diagnosis of CHD using the EMR (electronic medical records) data on maternal risk factors. The use of AI in the diagnostics, risk stratification, and management of CHD in the near future is a promising possibility with current advancements in machine learning and neural networks. However, the challenges posed by the dearth of appropriate algorithms and their nascent nature, limited physician training, fear of over-mechanization, and apprehension of missing the ‘human touch’ limit the acceptability. Still, AI proposes to aid the clinician tomorrow with precision cardiology, paving a way for extremely efficient human-error-free health care.

Introduction: As artificial intelligence (AI)-assisted diagnosis gained immense popularity, it is imperative to consider its utility and efficiency in the early diagnosis of colorectal cancer (CRC), responsible for over 1.8 million cases and 881 000 deaths globally, as reported in 2018. Improved adenoma detection rate, as well as better characterizations of polyps, are significant advantages of AI-assisted colonoscopy (AIC). This systematic review (SR) investigates the effectiveness of AIC in the early diagnosis of CRC as compared to conventional colonoscopy. Materials and Methods: Electronic databases such as PubMed/Medline, SCOPUS, and Web of Science were reviewed for original studies (randomized controlled trials, observational studies), SRs, and meta-analysis between 2017 and 2022 utilizing Medical Subject Headings terminology in a broad search strategy. All searches were performed and analyzed according to the Preferred Reporting Items for Systematic Reviews and Meta-Analysis methodology and were conducted from November 2022. A data extraction form based on the Cochrane Consumers and Communication Review group’s extraction template for quality assessment and evidence synthesis was used for data extraction. All included studies considered for bias and ethical criteria and provided valuable evidence to answer the research question. Results: The database search identified 218 studies, including 87 from PubMed, 60 from SCOPUS, and 71 from Web of Science databases. The retrieved studies from the databases were imported to Rayyan software and a duplicate article check was performed, all duplicate articles were removed after careful evaluation of the data. The abstract and full-text screening was performed in accordance with the following eligibility criteria: Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) for observational studies; Preferred Reporting Items for Systematic Reviews and Meta-Analysis for review articles, ENTREQ for narrative studies; and modified JADAD for randomized controlled trials. This yielded 15 studies that met the requirements for this SR and were finally included in the review. Conclusion: AIC is a safe, highly effective screening tool that can increase the detection rate of adenomas, and polyps resulting in an early diagnosis of CRC in adults when compared to conventional colonoscopy. The results of this SR prompt further large-scale research to investigate the effectiveness in accordance with sex, race, and socioeconomic status, as well as its influence on prognosis and survival rate.

Glioblastoma multiforme (GBM) is one of the most aggressive glial cell tumors in adults. Although current treatment options for GBM offer some therapeutic benefit, median survival remains poor and does not generally exceed 14 months. Several genes, such as isocitrate dehydrogenase (IDH) enzyme and O6-methylguanine-DNA methyltransferase (MGMT), have been implicated in pathogenesis of the disease. Treatment is often adapted based on the presence of IDH mutations and MGMT promoter methylation status. Recent GBM cell line studies have associated Nuclear Factor Erythroid 2-Related Factor 2 (Nrf2) expression with high-grade tumors. Increased Nrf2 expression is often found in tumors with IDH-1 mutations. Nrf2 is an important transcription factor with anti-apoptotic, antioxidative, anti-inflammatory, and proliferative properties due to its complex interactions with multiple regulatory pathways. In addition, evidence suggests that Nrf2 promotes GBM cell survival in hypoxic environment,by up-regulating hypoxia-inducible factor-1α (HIF-1α) and vascular endothelial growth factor (VEGF). Downregulation of Nrf2 has been shown to improve GBM sensitivity to chemotherapy drugs such as Temozolomide. Thus, Nrf2 could be a key regulator of GBM pathways and potential therapeutic target. Further research efforts exploring an interplay between Nrf2 and major molecular signaling mechanisms could offer novel GBM drug candidates with a potential to significantly improve patients prognosis.