Digital therapeutics (DTx) are emerging as a pivotal tool in promoting longevity by addressing non-communicable diseases (NCDs) such as diabetes, cardiovascular diseases, and mental health disorders. These software-driven interventions offer personalized, evidence-based treatments that can be accessed via digital devices, making healthcare more accessible and scalable. One of the key advancements in DTx is the integration of artificial intelligence (AI) and machine learning (ML) to tailor interventions based on individual health data. This personalization enhances the effectiveness of treatments and supports preventive care by identifying risk factors early. The need for digital therapeutics is underscored by the rising prevalence of NCDs, which are responsible for a significant portion of global mortality and healthcare costs. Traditional healthcare systems often struggle to provide timely and personalized care, especially in low-resource settings. DTx can bridge this gap by offering cost-effective solutions that are easily scalable. Moreover, digital therapeutics can address health inequities by providing low-cost interventions to underserved populations, thereby reducing the burden of NCDs and improving overall health outcomes. As technology continues to evolve, the potential for DTx to enhance longevity and quality of life becomes increasingly promising. Recent advancements in longevity medicine and technology have focused on extending both lifespan and healthspan, ensuring that people not only live longer but also maintain good health throughout their extended years. This review article highlights these advancements that are contributing to this compelling subject of Longevity.

This study is a literature review with a qualitative approach. It is justified by the significant increase in diseases acquired through lifestyle habits that generate health risks, which impair and are responsible for decreasing longevity and decreasing quality of life, such as hypertension, depression, obesity and respiratory tract diseases. Physical activity is recognized as a protective factor for health, and its benefits are associated with the reduction of chronic diseases and a decrease in the risk of premature death from diseases related to a sedentary lifestyle. The objective of this research is to search and identify, within the scientific literature, if there are in fact contributions from the practice of physical activity in subjects diagnosed with depression. For the categorization of studies and selection of materials, the following keywords were determined: physical exercise and depression and physical activity and depression. As inclusion criteria for data analysis and interpretation, the following were considered: articles in Portuguese, full texts, published in health journals, between the years 2005 to 2015. As exclusion criteria, we considered articles found by descriptors that did not contain one or more of the inclusion criteria. In this study, articles were selected by searching the Scientific Electronic Library Online (SciELO) and Lilacs. The choice of these databases was prioritized due to the quality and reliability of the materials available, and their easy access. 77 articles were found, of which 4 were selected to be part of this research. It can be noted that physical activity showed positive aspects and possible contributions and can be considered as a bias in an adjunct to conventional pharmacological treatments. The need for further clarification about the disease in relation to psychological, social and physiological issues is also evident, thus opening the possibility for further studies and research on the subject, so that in this way they can guide possible interventions that help in the treatment of the depression.

A Changing World Demands Optimized Health Surveillance Systems – and How Data Engineering Can Help There is a growing urgency to manage the public health and emergency response practices effectively today, in light of complex and emerging health threats. Fortunately, a host of new tools, including big and streaming data sources, methods such as machine learning, new types of hardware like blockchain or secure enclaves, and means of data storage and retrieval, have emerged. But, with these innovations comes a grand challenge: how to blend with, and adapt them to, the traditional public health practices. The long-in-place infrastructures and protocols to protect and ensure the welfare of communities are in need of change, or at least update, to enhance their marked longevity of impact directly on the health outcomes and community wellbeing they were designed to fortify. It is in this vein that the essay is written and composed. The investigation in this essay is to query what, particularly, might be the aspects and influences of the emerging veritable cornucopia of new data engineering frameworks that are either being developed specifically for health surveillance and wellness, or are available to be co opted from devices and services already thriving in the current market and research milieu. Knowing what these ways may be could well aid in molding their uptake and spread, ensuring their beneficial impacts on those communities who stand to gain the most. The essay is divided into several key segments. After this introduction, section two details the research methods. In the section that follows, the maximum health outcome potentials of these novel frameworks are reviewed. Part four of the essay takes a more critical approach, addressing how the success of these methods may be hindered and future research avenues. Lastly, the concluding information suggests some actions to take to aid best suit the implementation of these ways, and suggests some thoughts for further research after the completion of these inquiriestrand [1].