Digital health tools for the passive monitoring of depression: a systematic review of methods.

The use of digital tools to measure physiological and behavioural variables of potential relevance to mental health is a growing field sitting at the intersection between computer science, engineering, and clinical science. We summarised the literature on remote measuring technologies, mapping methodological challenges and threats to reproducibility, and identified leading digital signals for depression. Medical and computer science databases were searched between January 2007 and November 2019. Published studies linking depression and objective behavioural data obtained from smartphone and wearable device sensors in adults with unipolar depression and healthy subjects were included. A descriptive approach was taken to synthesise study methodologies. We included 51 studies and found threats to reproducibility and transparency arising from failure to provide comprehensive descriptions of recruitment strategies, sample information, feature construction and the determination and handling of missing data. The literature is characterised by small sample sizes, short follow-up duration and great variability in the quality of reporting, limiting the interpretability of pooled results. Bivariate analyses show consistency in statistically significant associations between depression and digital features from sleep, physical activity, location, and phone use data. Machine learning models found the predictive value of aggregated features. Given the pitfalls in the combined literature, these results should be taken purely as a starting point for hypothesis generation. Since this research is ultimately aimed at informing clinical practice, we recommend improvements in reporting standards including consideration of generalisability and reproducibility, such as wider diversity of samples, thorough reporting methodology and the reporting of potential bias in studies with numerous features.

Multivalent presentation of a hydrolytically stable GM(3) lactone mimetic as modulator of melanoma cells motility and adhesion.

A hydrolytically stable mimetic of the tumour antigen GM(3) lactone is used to decorate multivalent scaffolds. Two of them positively interfere on melanoma cell adhesion, migration and resistance to apoptosis (anoikis). Notably, their ability to hamper melanoma-cells adhesion and reduce the metastatic potential is enhanced when the two scaffolds, presenting a different shape, are used in combination.

Self-organization of mixtures of fluorocarbon and hydrocarbon amphiphilic thiolates on the surface of gold nanoparticles.

Self-assembled monolayers composed of a mixture of thiolate molecules, featuring hydrocarbon or perfluorocarbon chains (H- and F-chains) terminating with a short poly(oxoethylene) (PEG) moiety, are the most extreme example of surfactant immiscibility on gold nanoparticles reported so far. The phase segregation between H-chains and F-chains and the consequent, peculiar folding of PEG chains are responsible for the increased affinity of a selected radical probe for the fluorinated region, which increases as the size of the fluorinated domains decrease, independently of the shape of such domains. This feature has been revealed by ESR measurements and an in silico innovative multiscale molecular simulations approach in explicit water. Our results reveal an underlying mechanism of a transmission of the organization of the monolayer from the inner region close to the gold surface toward the external hydrophilic PEG region. Moreover, this study definitively proves that a mixed monolayer is a complex system with properties markedly different from those characterizing the parent homoligand monolayers.