Background: The COVID-19 pandemic has increased the impact and spread of mental illness and made health services difficult to access; therefore, there is a need for remote, pervasive forms of mental health monitoring. Digital phenotyping is a new approach that uses measures extracted from spontaneous interactions with smartphones (eg, screen touches or movements) or other digital devices as markers of mental status. Objective: This review aimed to evaluate the feasibility of using digital phenotyping for predicting relapse or exacerbation of symptoms in patients with mental disorders through a systematic review of the scientific literature. Methods: Our research was carried out using 2 bibliographic databases (PubMed and Scopus) by searching articles published up to January 2023. By following the PRISMA (Preferred Reporting Items for Systematic Review and Meta-Analysis) guidelines, we started from an initial pool of 1150 scientific papers and screened and extracted a final sample of 29 papers, including studies concerning clinical populations in the field of mental health, which were aimed at predicting relapse or exacerbation of symptoms. The systematic review has been registered on the web registry Open Science Framework. Results: We divided the results into 4 groups according to mental disorder: schizophrenia (9/29, 31%), mood disorders (15/29, 52%), anxiety disorders (4/29, 14%), and substance use disorder (1/29, 3%). The results for the first 3 groups showed that several features (ie, mobility, location, phone use, call log, heart rate, sleep, head movements, facial and vocal characteristics, sociability, social rhythms, conversations, number of steps, screen on or screen off status, SMS text message logs, peripheral skin temperature, electrodermal activity, light exposure, and physical activity), extracted from data collected via the smartphone and wearable wristbands, can be used to create digital phenotypes that could support gold-standard assessment and could be used to predict relapse or symptom exacerbations. Conclusions: Thus, as the data were consistent for almost all the mental disorders considered (mood disorders, anxiety disorders, and schizophrenia), the feasibility of this approach was confirmed. In the future, a new model of health care management using digital devices should be integrated with the digital phenotyping approach and tailored mobile interventions (managing crises during relapse or exacerbation).

Chronic obstructive pulmonary disease (COPD) is a heterogeneous inflammatory condition characterized by progressive airflow limitation, which may be caused by genetic and environmental factors. Furthermore, epigenetic mechanisms could provide valuable insights into the complex interactions between environment and genes and subsequent development of the disease. The aim of this study is to provide a systematic review of the latest knowledge on epigenetic modifications that characterize COPD, summarizing epigenetic factors that could serve as potential novel biomarkers and therapeutic targets for the treatment of COPD patients. We queried the PubMed and Scopus electronic databases with specific keywords, in May 2024, according to the PRISMA guidelines, and articles were included if they met all the inclusion criteria and survived a quality assessment. We identified 5414 publications in our systematic search. Among them, only 51 articles met the criteria of COPD-associated epigenetic modifications in human patients compared to the control group. Eight studies described DNA methylation, one study histone modifications, and forty-two studies non-coding RNAs. Apoptosis and inflammatory pathways have been found to be the main mechanisms regulated by epigenetic elements in COPD patients. In addition, non-coding RNAs may be useful as biomarkers or therapeutic targets of pulmonary disease. Future studies will be needed to confirm the role of epigenetic elements associated with COPD.

Total sleep deprivation (TSD) has a major impact on sustained attention as reported by previous studies that have investigated effects of TSD, however by using classical neuropsychological tests that lack ecological validity. To study the effects of TSD on daily-life activities, we carried out an ecological evaluation of sustained attention using a virtual reality task requiring driving along an unpredictable path. We enrolled 30 volunteers who underwent two experimental sessions: baseline (after normal sleep night) and after 36 h of total TSD. We assessed changes in sustained attentional performance by analysing the series of visuomotor adjustments while driving. After TSD, we found greater inaccuracy and longer attentional lapses. Furthermore, the visuomotor adjustments series exhibited higher long-range correlations (self-similarity) which has been associated with greater cognitive efforts. Sustained attention assessed by the ecological task requiring visuomotor coordination gets worse after 36 h of total TSD together with greater cognitive effort.

Assessing mobility in daily life can provide significant insights into several clinical conditions, such as Chronic Obstructive Pulmonary Disease (COPD). In this paper, we present a comprehensive analysis of wearable devices’ performance in gait speed estimation and explore optimal device combinations for everyday use. Using data collected from smartphones, smartwatches, and smart shoes, we evaluated the individual capabilities of each device and explored their synergistic effects when combined, thereby accommodating the preferences and possibilities of individuals for wearing different types of devices. Our study involved 20 healthy subjects performing a modified Six-Minute Walking Test (6MWT) under various conditions. The results revealed only little performance differences among devices, with the combination of smartwatches and smart shoes exhibiting superior estimation accuracy. Particularly, smartwatches captured additional health-related information and demonstrated enhanced accuracy when paired with other devices. Surprisingly, wearing all devices concurrently did not yield optimal results, suggesting a potential redundancy in feature extraction. Feature importance analysis highlighted key variables contributing to gait speed estimation, providing valuable insights for model refinement.

Carotid atherosclerosis remains one of the primary etiological factors underlying ischemic stroke, contributing to adult neurological disability and mortality. In recent years, non-coding RNAs (ncRNAs) have emerged as key regulators of gene expression, actively modulating molecular pathways involved in atherogenesis. This systematic review, the first to be exclusively focused on carotid atherosclerosis, aimed at synthesizing current findings on the differential expression of ncRNAs throughout the natural history of the disease, thus providing the first comprehensive attempt to delineate a stage-specific ncRNA expression profile in carotid disease. A comprehensive literature search was conducted in PubMed and Scopus databases in January 2025, following PRISMA guidelines. Original studies involving human subjects with carotid atherosclerosis, evaluating the expression of intracellular or circulating ncRNAs, were included and then categorized according to their association with cardiovascular risk factors, carotid intima-media thickness (cIMT), presence of atherosclerotic plaques, plaque vulnerability, clinical symptoms, and ischemic stroke. Out of 148 articles initially identified, 49 met the inclusion criteria and were analyzed in depth. Among the different classes of ncRNAs, microRNAs (miRNAs) were the most frequently reported as dysregulated, followed by circular RNAs (circRNAs) and long non-coding RNAs (lncRNAs). Notably, the majority of identified ncRNAs were implicated in key pathogenic mechanisms such as inflammatory signaling, vascular smooth muscle cell (VSMC) phenotypic modulation, and ABCA1-mediated cholesterol efflux. Collectively, the evidence underscores the association and possible involvement of ncRNAs in the initiation and progression of carotid atherosclerosis and its cerebrovascular complications. Their relative stability in biological fluids and cell-specific expression profiles highlight their strong potential as minimally invasive biomarkers and—possibly—novel therapeutic targets.