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Purpose It was reported that individual heterogeneity among malignancies (IHAM) might correlate well to the prognosis of lung cancer; however, seldom radiomic study is on this field. Standard deviation (SD) in statistics could scale average amount of variability of a variable; therefore, we used SD of CT feature (FeatureSD) among primary tumor and malignant lymph nodes (LNs) in an individual to represent IHAM, and its prognostic ability was explored. Methods The enrolled patients who had accepted PET/CT scans were selected from our previous study (ClinicalTrials.gov, NCT03648151). The patients had primary tumor and at least one LN, and standardized uptake value of LN higher than 2.0 and 2.5 were enrolled as the cohort 1 (n = 94) and 2 (n = 88), respectively. FeatureSD from the combined or thin-section CT were calculated among primary tumor and malignant LNs in each patient, and were separately selected by the survival XGBoost method. Finally, their prognostic ability was compared to the significant patient characteristics identified by the Cox regression. Results In the univariate and multivariate Cox analysis, surgery, target therapy, and TNM stage were significantly against OS in the both cohorts. In the survival XGBoost analysis of the thin-section CT dataset, none FeatureSD could be repeatablely ranked on the top list of the both cohorts. For the combined CT dataset, only one FeatureSD ranked in the top three of both cohorts, but the 3 significant factors in the Cox regression were not even on the list. Both in the cohort 1 and 2, C-index of the model composed of the 3 factors could be improved by integrating the continuous FeatureSD; furthermore, that of each factor was obviously lower than FeatureSD. Conclusion Standard deviation of CT features among malignant foci within an individual was a powerful prognostic factor in vivo for lung cancer patients.

For years, the consumption of a diet rich in fruits and vegetables has been considered healthy, increasing longevity, and decreasing morbidities. With the assistance of basic research investigating the potential mechanisms, it has become clear that the beneficial effects of plant-based foods are mainly due to the large amount of bioactive phenolic compounds contained. Indeed, substantial dietary intervention studies in humans have supported that the supplementation of polyphenols have various health-promoting effects, especially in the elderly population. In vitro examinations on the anti-aging mechanisms of polyphenols have been widely performed, using different types of natural and synthetic phenolic compounds. The aim of this review is to critically evaluate the experimental evidence demonstrating the beneficial effects of polyphenols on aging-related diseases. We highlight the potential anti-aging mechanisms of polyphenols, including antioxidant signaling, preventing cellular senescence, targeting microRNA, influencing NO bioavailability, and promoting mitochondrial function. While the trends on utilizing polyphenols in preventing aging-related disorders are getting growing attention, we suggest the exploration of the beneficial effects of the combination of multiple polyphenols or polyphenol-rich foods, as this would be more physiologically relevant to daily life. Published version