Research into aging is progressing, amid a focus on anti-aging. While genetic factors are known to be involved in aging, acquired factors such as environment and lifestyle also have a major influence, with some scientists attributing more than half of aging to them. The main acquired factor is the epigenome, which controls gene function through DNA methylation, among others. As epigenetic alterations play a key role in shedding light on the mechanisms of aging, efforts to investigate the inhibition of aging and treatments that regard aging as a disease look set to advance worldwide.

Epigenetics is a mechanism that changes the way genes are used, without changing the DNA sequence itself. The mechanism determines when and where genes are turned on or off by using DNA methylation to switch genes off, and also by finely controlling the switch by regulating the action of histones, the proteins around which DNA is wrapped. The crux of the matter is that even where genetic information is the same, gene function is influenced by environmental factors and life experiences. As such, epigenetics has become a major focus of research in many fields, including cancer, metabolic diseases, and other lifestyle diseases.

The mechanisms by which cancer cells transfer mitochondria into T cells and replace the T cells’ healthy mitochondria are being elucidated. A subsequent study is now starting to reveal the specific mechanisms involved. At the same time, fresh puzzles have come to light. For example, if mitochondrial DNA mutates, energy production within cells naturally diminishes, slowing the growth of the cancer cells and thus disadvantaging them. As a number of other questions have yet to be explained, research into mitochondria derived from cancer cells continues to warrant close attention.

The decline in mitochondrial function resulting from aging is known to cause a range of diseases, including stroke, neurodegenerative disorders, cardiomyopathy, and cancer. This relationship between mitochondria and aging is a key topic in research focused on healthy life expectancy. One of the many and varied impacts of aging is its connection to autophagy, the mechanism whereby old organelles and proteins are broken down. A decline in autophagy leads to the accumulation of aged mitochondria, resulting in cellular damage. Attention is focusing on the existence of substances that delay this functional decline.

Obesity triggers high blood pressure, high blood sugar, and lipid abnormalities, leading on to such serious diseases as arteriosclerosis, heart attack, stroke, dementia, and diabetes. It would thus be fair to say that obesity truly is the prime culprit in lifestyle diseases. Remedying obesity is also a pressing issue in order to extend healthy life expectancy and curb medical expenses, but there was hitherto no effective means of combatting it. However, scientists have now shed light for the first time on the mechanism via which the numerous mitochondria in brown adipocytes mediate the activation of this type of adipose tissue and thereby encourage fat burning. Hopes are growing that this will be the trump card in tackling obesity.

The rise in temperatures shows no sign of stopping. Japan is beset by such high summer temperatures each year that the expression “record-breaking heat“ has already become a cliché, and severe health impacts are becoming clearly visible. The number of heat stroke deaths has surged, surpassing 2,000 mark, reaching in 2024. This is 5.5 times the number of deaths due to natural disasters. Furthermore, the number of heat-related deaths—deaths due to the exacerbation of pre-existing conditions such as heart disease or respiratory illness triggered by the heat—is estimated to be about seven times the number due to heat stroke. Excessive heat has serious effects on health and a variety of diseases. Scientists say that initiatives covering society as a whole are crucial, as it is no longer possible to avoid these effects through individual efforts alone.

As AI learns, it evolves and changes its output. In this sense, it differs radically from conventional medical devices and pharmaceuticals, which are required to deliver stable performance and effects, so the ethical issues it entails are complex. In clinical practice, physicians must take the greatest care to avoid excessive reliance on AI in supporting clinical decisions, lest they lose sight of their essential mission as physicians. AI also raises many issues for those receiving medical care, including the handling of personal information and the role of patients as users. Now is the time to discuss the kind of medical care we should aim to deliver by leveraging new technologies.

The accuracy of endoscopy is steadily increasing. Thanks to high-definition imagingsensors, colonoscopies are able to detect minute lesions, thereby helping to ensure early detection. However, as endoscopists are responsible for image interpretation and diagnosis, missed lesions remain unavoidable. AI-based diagnostic imaging systems aim to address this issue. Trained on 250,000 images of lesions from approximately 12,000 cases, the AI system performed automated analysis in real-time. However, a persistent limitation is that AI system cannot detect lesions that are also missed by humans. Therefore, further evolution of such AI system is demanding.

When consulting a medical institution, the first place most people approach for an examination is a department or clinic specializing in internal medicine. At the same time, internists —— physicians specializing in internal medicine —— must conduct a comprehensive differential diagnosis process to reach an accurate judgment. However, as a diverse array of symptoms may occur in a patient, the limits of a physician’s experience and knowledge may not encompass diseases with few cases. The Japanese Society of Internal Medicine has published the J-CaseMap case search database to serve as a diagnostic tool. But as this database covers only rare diseases, physicians need to have the ability to distinguish the false from the genuine in the information generated by the AI.

The field of medical care has already seen several AI booms. In what can only be described as a breakthrough, many hospitals have now started to use image recognition technology based on AI-powered deep learning. If the technology evolves further, it could prove highly effective in identifying pathological changes that humans tend to overlook and hard-to-diagnose diseases. As such, there are hopes that it could become a reliable assistant for physicians. On the other hand, reliance on learned content means there is a risk that bias in the training data will be reflected in the results. If such issues can be overcome, it might become possible to deliver a completely different style of medical care.