There was a low representation of AA in the studies in this review. Opportunities exist to engage AA in e-Health/m-Health research, but researchers must go beyond the traditional one-size-fits-all approach to determine what mixture of incentives and recruitment/retention strategies would work best for a particular health condition, population group, or community.

Findings underscore the importance of screening for substance use, even among youth enrolled in elementary/middle school. In addition, school prevention programs should begin in elementary school (third grade) and target alcohol use.

Objectives C-terminal Agrin Fragment (CAF) has been proposed as a potential circulating biomarker for predicting changes in physical function among older adults. To determine the effect of a one-year PA intervention on changes in CAF concentrations and to evaluate baseline and longitudinal associations between CAF concentrations and indices of physical function. Design Ancillary study to the Lifestyle Interventions and Independence for Elders Pilot (LIFE-P), a multi-site randomized clinical trial designed to evaluate the effects of chronic exercise on the physical function of older adults at risk for mobility disability. Setting Four academic research centers within the U.S. Participants Three hundred thirty three older adults aged 70 to 89 with mild to moderate impairments in physical function. Intervention A 12-month intervention of either structured physical activity (PA) or health education promoting successful aging (SA). Measurements Serum CAF concentrations and objectives measures of physical function – i.e. gait speed and performance on the Short Physical Performance Battery (SPPB). Results The group*time interaction was not significant for serum CAF concentrations (p=0.265), indicating that the PA intervention did not significantly reduce serum CAF levels compared to SA. Baseline gait speed was significantly correlated with baseline CAF level (r = −0.151, p= 0.006), however the association between CAF and SPPB was not significant. Additionally, neither baseline nor the change in CAF concentrations strongly predicted the change in either performance measure following the PA intervention. Conclusion In summary, the present study shows that a one-year structured PA program did not reduce serum CAF levels among mobility-limited older adults. However, further study is needed to definitively determine the utility of CAF as a biomarker of physical function.

Colorectal cancer (CRC) is the second most frequently diagnosed type of cancer and a major worldwide public health concern. Despite the global efforts in the development of modern therapeutic strategies, CRC prognosis is strongly correlated with the stage of the disease at diagnosis. Early detection of CRC has a huge impact in decreasing mortality while pre-lesion detection significantly reduces the incidence of the pathology. Even though the management of CRC patients is based on robust diagnostic methods such as serum tumor markers analysis, colonoscopy, histopathological analysis of tumor tissue, and imaging methods (computer tomography or magnetic resonance), these strategies still have many limitations and do not fully satisfy clinical needs due to their lack of sensitivity and/or specificity. Therefore, improvements of the current practice would substantially impact the management of CRC patients. In this view, liquid biopsy is a promising approach that could help clinicians screen for disease, stratify patients to the best treatment, and monitor treatment response and resistance mechanisms in the tumor in a regular and minimally invasive manner. Liquid biopsies allow the detection and analysis of different tumor-derived circulating markers such as cell-free nucleic acids (cfNA), circulating tumor cells (CTCs), and extracellular vesicles (EVs) in the bloodstream. The major advantage of this approach is its ability to trace and monitor the molecular profile of the patient’s tumor and to predict personalized treatment in real-time. On the other hand, the prospective use of artificial intelligence (AI) in medicine holds great promise in oncology, for the diagnosis, treatment, and prognosis prediction of disease. AI has two main branches in the medical field: (i) a virtual branch that includes medical imaging, clinical assisted diagnosis, and treatment, as well as drug research, and (ii) a physical branch that includes surgical robots. This review summarizes findings relevant to liquid biopsy and AI in CRC for better management and stratification of CRC patients.

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