Radiomics, the high-throughput mining of quantitative image features from standard-of-care medical imaging that enables data to be extracted and applied within clinical-decision support systems to improve diagnostic, prognostic, and predictive accuracy, is gaining importance in cancer research. Radiomic analysis exploits sophisticated image analysis tools and the rapid development and validation of medical imaging data that uses image-based signatures for precision diagnosis and treatment, providing a powerful tool in modern medicine. Herein, we describe the process of radiomics, its pitfalls, challenges, opportunities, and its capacity to improve clinical decision making, emphasizing the utility for patients with cancer. Currently, the field of radiomics lacks standardized evaluation of both the scientific integrity and the clinical relevance of the numerous published radiomics investigations resulting from the rapid growth of this area. Rigorous evaluation criteria and reporting guidelines need to be established in order for radiomics to mature as a discipline. Herein, we provide guidance for investigations to meet this urgent need in the field of radiomics.

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Rationale: Coronavirus disease (COVID-19) is a global threat to health. Its inflammatory characteristics are incompletely understood. Objectives: To define the cytokine profile of COVID-19 and to identify evidence of immunometabolic alterations in those with severe illness. Methods: Levels of IL-1β, IL-6, IL-8, IL-10, and sTNFR1 (soluble tumor necrosis factor receptor 1) were assessed in plasma from healthy volunteers, hospitalized but stable patients with COVID-19 (COVID stable patients), patients with COVID-19 requiring ICU admission (COVID ICU patients), and patients with severe community-acquired pneumonia requiring ICU support (CAP ICU patients). Immunometabolic markers were measured in circulating neutrophils from patients with severe COVID-19. The acute phase response of AAT (alpha-1 antitrypsin) to COVID-19 was also evaluated. Measurements and Main Results: IL-1β, IL-6, IL-8, and sTNFR1 were all increased in patients with COVID-19. COVID ICU patients could be clearly differentiated from COVID stable patients, and demonstrated higher levels of IL-1β, IL-6, and sTNFR1 but lower IL-10 than CAP ICU patients. COVID-19 neutrophils displayed altered immunometabolism, with increased cytosolic PKM2 (pyruvate kinase M2), phosphorylated PKM2, HIF-1α (hypoxia-inducible factor-1α), and lactate. The production and sialylation of AAT increased in COVID-19, but this antiinflammatory response was overwhelmed in severe illness, with the IL-6:AAT ratio markedly higher in patients requiring ICU admission ( P < 0.0001). In critically unwell patients with COVID-19, increases in IL-6:AAT predicted prolonged ICU stay and mortality, whereas improvement in IL-6:AAT was associated with clinical resolution ( P < 0.0001). Conclusions: The COVID-19 cytokinemia is distinct from that of other types of pneumonia, leading to organ failure and ICU need. Neutrophils undergo immunometabolic reprogramming in severe COVID-19 illness. Cytokine ratios may predict outcomes in this population.

The results indicate that the ACTN3 R577X polymorphism influences the response of quadriceps muscle power to ST in older adults.

Previous reports have shown a lower proportion of the ACTN3 X/X genotype (R577X nonsense polymorphism) in sprint-related athletes compared to the general population, possibly attributed to impairment of muscle function related to a-actinin-3 deficiency. In the present study, we examined the frequency of the X/X genotype in both Black and White elite-level bodybuilders and strength athletes in comparison to the general population. A reference population of 668 Whites (363 men and 305 women) and 208 Blacks (98 men and 110 women) was genotyped for the ACTN3 R577X polymorphism. Strength athletes (52 white and 23 black; 4 women) consisting predominantly of world class and locally competitive bodybuilders, and elite powerlifters were recruited and similarly genotyped. Significantly lower X/X genotype frequencies were observed in the athletes (6.7%) vs controls (16.3%; P ¼ 0.005). The X/X genotype was significantly lower in White athletes (9.7%) vs controls (19.9%; P ¼ 0.018). No black athletes (0%) were observed with the X/X genotype, though this finding only approached statistical significance vs controls (4.8%; P ¼ 0.10). The results indicate that the ACTN3 R577X nonsense allele (X) is underrepresented in elite strength athletes, consistent with previous reports indicating that a-actinin-3 deficiency appears to impair muscle performance.

A paradigm shift from current population based medicine to personalized and participative medicine is underway. This transition is being supported by the development of clinical decision support systems based on prediction models of treatment outcome. In radiation oncology, these models 'learn' using advanced and innovative information technologies (ideally in a distributed fashion - please watch the animation: http://youtu.be/ZDJFOxpwqEA) from all available/appropriate medical data (clinical, treatment, imaging, biological/genetic, etc.) to achieve the highest possible accuracy with respect to prediction of tumor response and normal tissue toxicity. In this position paper, we deliver an overview of the factors that are associated with outcome in radiation oncology and discuss the methodology behind the development of accurate prediction models, which is a multi-faceted process. Subsequent to initial development/validation and clinical introduction, decision support systems should be constantly re-evaluated (through quality assurance procedures) in different patient datasets in order to refine and re-optimize the models, ensuring the continuous utility of the models. In the reasonably near future, decision support systems will be fully integrated within the clinic, with data and knowledge being shared in a standardized, dynamic, and potentially global manner enabling truly personalized and participative medicine.

The human androgen receptor (AR) gene contains a CAG (glutamine) repeat polymorphism in exon 1 that is inversely associated with transcriptional activity of the AR. We studied the association of AR CAG repeat length, fat-free mass (FFM), and testosterone in two independent cohorts: 294 Caucasian men, aged 55-93 yr, from the Study of Osteoporotic Risk in Men (STORM), and 202 Caucasian volunteers (112 men and 90 women), aged 19-90 yr, from the Baltimore Longitudinal Study of Aging (BLSA). Subjects were genotyped to determine the number of AR CAG repeats and grouped as carrying either < 22 or > or =22 repeats. Whole body soft tissue composition was measured by dual-energy X-ray absorptiometry. Men with greater CAG repeat number exhibited significantly greater total FFM than those with fewer CAG repeats in both cohorts (STORM: 59.2 +/- 0.3 vs. 58.0 +/- 0.4 kg, P = 0.02; BLSA: 57.2 +/- 1.1 vs. 53.8 +/- 1.1 kg, P = 0.04). Similar results were observed for total FFM normalized to height. No differences were seen in women in the BLSA cohort. In the BLSA cohort, serum testosterone levels were higher in subjects with greater repeat number (P = 0.003). This same pattern approached significance in the STORM cohort (P = 0.07). In conclusion, the androgen receptor CAG repeat polymorphism is associated with FFM in men in two independent cohorts. Additional studies are needed to confirm this observation and to clarify the mechanisms involved.

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