Alzheimer’s disease (AD) is a neurodegenerative disorder and the most common form of dementia characterized by cognitive and memory impairment. One of the mechanism involved in the pathogenesis of AD, is the oxidative stress being involved in AD‘s development and progression. In addition, several studies proved that chronic viral infections, mainly induced by Human herpesvirus 1 (HHV-1), Cytomegalovirus (CMV), Human herpesvirus 2 (HHV-2), and Hepatitis C virus (HCV) could be responsible for AD’s neuropathology. Despite the large amount of data regarding the pathogenesis of Alzheimer’s disease (AD), a very limited number of therapeutic drugs and/or pharmacological approaches, have been developed so far. It is important to underline that, in recent years, natural compounds, due their antioxidants and anti-inflammatory properties have been largely studied and identified as promising agents for the prevention and treatment of neurodegenerative diseases, including AD. The ester of epigallocatechin and gallic acid, (−)-Epigallocatechin-3-Gallate (EGCG), is the main and most significantly bioactive polyphenol found in solid green tea extract. Several studies showed that this compound has important anti-inflammatory and antiatherogenic properties as well as protective effects against neuronal damage and brain edema. To date, many studies regarding the potential effects of EGCG in AD’s treatment have been reported in literature. The purpose of this review is to summarize the in vitro and in vivo pre-clinical studies on the use of EGCG in the prevention and the treatment of AD as well as to offer new insights for translational perspectives into clinical practice.

The emergence from anesthesia is the stage of general anesthesia featuring the patient’s progression from the unconsciousness status to wakefulness and restoration of consciousness. This complex process has precise neurobiology which differs from that of induction. Despite the medications commonly used in anesthesia allow recovery in a few minutes, a delay in waking up from anesthesia, called delayed emergence, may occur. This phenomenon is associated with delays in the operating room, and an overall increase in costs. Together with the emergence delirium, the phenomenon represents a manifestation of inadequate emergence. Nevertheless, in delayed emergence, the transition from unconsciousness to complete wakefulness usually occurs along a normal trajectory, although slowed down. On the other hand, this awakening trajectory could proceed abnormally, possibly culminating in the manifestation of emergence delirium. Clinically, delayed emergence often represents a challenge for clinicians who must make an accurate diagnosis of the underlying cause to quickly establish appropriate therapy. This paper aimed at presenting an update on the phenomenon, analyzing its causes. Diagnostic and therapeutic strategies are addressed. Finally, therapeutic perspectives on the “active awakening” are reported.

Although proper pain evaluation is mandatory for establishing the appropriate therapy, self-reported pain level assessment has several limitations. Data-driven artificial intelligence (AI) methods can be employed for research on automatic pain assessment (APA). The goal is the development of objective, standardized, and generalizable instruments useful for pain assessment in different clinical contexts. The purpose of this article is to discuss the state of the art of research and perspectives on APA applications in both research and clinical scenarios. Principles of AI functioning will be addressed. For narrative purposes, AI-based methods are grouped into behavioral-based approaches and neurophysiology-based pain detection methods. Since pain is generally accompanied by spontaneous facial behaviors, several approaches for APA are based on image classification and feature extraction. Language features through natural language strategies, body postures, and respiratory-derived elements are other investigated behavioral-based approaches. Neurophysiology-based pain detection is obtained through electroencephalography, electromyography, electrodermal activity, and other biosignals. Recent approaches involve multimode strategies by combining behaviors with neurophysiological findings. Concerning methods, early studies were conducted by machine learning algorithms such as support vector machine, decision tree, and random forest classifiers. More recently, artificial neural networks such as convolutional and recurrent neural network algorithms are implemented, even in combination. Collaboration programs involving clinicians and computer scientists must be aimed at structuring and processing robust datasets that can be used in various settings, from acute to different chronic pain conditions. Finally, it is crucial to apply the concepts of explainability and ethics when examining AI applications for pain research and management.

Unlike traditional video games developed solely for entertainment purposes, game-based learning employs intentionally crafted approaches that seamlessly merge entertainment and educational content, resulting in captivating and effective learning encounters. These pedagogical methods include serious video games and gamification. Serious games are video games utilized as tools for acquiring crucial (serious) knowledge and skills. On the other hand, gamification requires integrating gaming elements (game mechanics) such as points, leaderboards, missions, levels, rewards, and more, into a context that may not be associated with video gaming activities. They can be dynamically (game dynamics) combined developing various strategic approaches. Operatively, gamification adopts simulation elements and leverages the interactive nature of gaming to teach players specific skills, convey knowledge, or address real-world issues. External incentives stimulate internal motivation. Therefore, these techniques place the learners in the central role, allowing them to actively construct knowledge through firsthand experiences.Anesthesia, pain medicine, and critical care demand a delicate interplay of technical competence and non-technical proficiencies. Gamification techniques can offer advantages to both domains. Game-based modalities provide a dynamic, interactive, and highly effective opportunity to learn, practice, and improve both technical and non-technical skills, enriching the overall proficiency of anesthesia professionals. These properties are crucial in a discipline where personal skills, human factors, and the influence of stressors significantly impact daily work activities. Furthermore, gamification can also be embraced for patient education to enhance comfort and compliance, particularly within pediatric settings (game-based distraction), and in pain medicine through stress management techniques. On these bases, the creation of effective gamification tools for anesthesiologists can present a formidable opportunity for users and developers.This narrative review comprehensively examines the intricate aspects of gamification and its potentially transformative influence on the fields of anesthesiology. It delves into theoretical frameworks, potential advantages in education and training, integration with artificial intelligence systems and immersive techniques, and also addresses the challenges that could arise within these contexts.

Meat is a crucial nutrient for human health since it represents a giant supply of proteins, minerals, and vitamins. On the opposite hand, the intake of red and processed meat is taken into account dangerous due to its potential of carcinogenesis and cancer risk improvement, particularly for colorectal cancer (CRC), although it has been reported that also the contaminations of beef infected by oncogenic bovine viruses could increase colorectal cancer’s risk. Regarding the mechanisms underlying the potential carcinogenicity of red and processed meat, different hypotheses have been proposed. A suggested mechanism describes the potential role of the heterocyclic amines (HACs) and polycyclic aromatic hydrocarbons (PHAs) in carcinogenesis induced by DNA mutation. Another hypothesis states that heme, through the lipid peroxidation process and therefore the formation of N-nitroso compounds (NOCs), produces cytotoxic and genotoxic aldehydes, resulting in carcinogenesis. Furthermore, a recent proposed hypothesis, is based on the combined actions between the N-Glycolylneuraminic acid (Neu5Gc) and genotoxic compounds. The purpose of this narrative review is to shed a light on the mechanisms underlying the potential carcinogenicity of red and processed meat, by summarizing the data reported in literature on this topic.