Liquid Biopsy and Artificial Intelligence as Tools to Detect Signatures of Colorectal Malignancies: A Modern Approach in Patient's Stratification.

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.

Participation of African Americans in e-Health and m-Health Studies: A Systematic Review.

BACKGROUND: African Americans (AA) experience high levels of health disparities for several diseases, yet remain underrepresented in clinical trials and other types of research. The high ownership of smartphones among AA puts them in a unique position to be recruited into e-Health/m-Health interventions. OBJECTIVE: This article is a systematic review of the participation of AA in e-Health/m-Health interventions, the diseases/health conditions targeted, and the recruitment and retention strategies used. MATERIALS AND METHODS: A systematic review was done with PubMed, PsycINFO, Web of Science, EBSCOhost, and CINAHL databases, as well as hand searches of 14 journals. The search was restricted to studies conducted in the United States and that were published between January 2000 and June 2016. Twenty-three distinct search terms were used. RESULTS: After removal of duplicates, 565 studies were screened and assessed for eligibility, and 56 met the inclusion criteria. Eight studies had exclusively AA participants. Eighty percent of the studies had female participants. Participants were recruited primarily from clinics/healthcare facilities. Forty-five percent of the studies provided monetary incentives. Only five studies addressed retention of participants. The diseases/health conditions that were studied included overweight/obesity, diabetes, physical activity, cardiovascular conditions, nutrition, prenatal health, and HIV. CONCLUSION: 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.

Prioritizing Alcohol Prevention: Establishing Alcohol as the Gateway Drug and Linking Age of First Drink With Illicit Drug Use.

BACKGROUND: Given ever-reducing budgets of community and school substance use prevention programs, there is a call for identifying the first substance in the sequence leading to polydrug use. METHODS: Examining data from a nationally representative sample of 2835 United States 12th graders, we sought to determine (1) the first substance adolescents use; (2) order in which adolescents progress through alcohol, tobacco, and marijuana use; and (3) impact of age of initial substance use on lifetime and frequency of illicit substance use. RESULTS: Alcohol is the most commonly used substance, and the majority of polysubstance using respondents consumed alcohol prior to tobacco or marijuana initiation. Respondents initiating alcohol use in sixth grade reported significantly greater lifetime illicit substance use (M = 1.9, standard deviation [SD] = 1.7, p < .001) and more frequent illicit substance use (M = 6.0, SD = 6.5, p < .001) than those initiating alcohol use in ninth grade or later. Overall, effect sizes for these differences were large (eta squared = 0.30 and 0.28, respectively). CONCLUSIONS: 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.