The term “hemp” refers to Cannabis sativa cultivars grown for industrial purposes that are characterized by lower levels of tetrahydrocannabinol (THC), the active principle responsible for Cannabis psychotropic effects. Hemp is an extraordinary crop, with enormous social and economic value, since it can be used to produce food, textiles, clothing, biodegradable plastics, paper, paint, biofuel, and animal feed, as well as lighting oil. Various parts of the hemp plant represent a valuable source of food and ingredients for nutritional supplements. While hemp inflorescence is rich in nonpsychoactive, yet biologically active cannabinoids, such as cannabidiol (CBD), which exerts potent anxiolytic, spasmolytic, as well as anticonvulsant effects, hempseed has a pleasant nutty taste and represents a valuable source of essential amino acids and fatty acids, minerals, vitamins, and fibers. In addition, hempseed oil is a source of healthy polyunsaturated fatty acids, and hemp sprouts are rich in antioxidants. This review article aims to provide a comprehensive outlook from a multidisciplinary perspective on the scientific evidence supporting hemp beneficial properties when consumed as food or supplement. Marketing of hemp-derived products is subjected to diversified and complex regulations worldwide for several reasons, including the fact that CBD is also the active principal of pharmaceutical agents and that regulatory bodies in some cases ban Cannabis inflorescence regardless of its THC content. Some key regulatory aspects of such a complex scenario are also analyzed and discussed in this review article.

Many efforts to reduce prostate specific antigen (PSA) overdiagnosis and overtreatment have been made. To this aim, Prostate Health Index (Phi) and Prostate Cancer Antigen 3 (PCA3) have been proposed as new more specific biomarkers. We evaluated the ability of phi and PCA3 to identify prostate cancer (PCa) at initial prostate biopsy in men with total PSA range of 2–10 ng/ml. The performance of phi and PCA3 were evaluated in 300 patients undergoing first prostate biopsy. ROC curve analyses tested the accuracy (AUC) of phi and PCA3 in predicting PCa. Decision curve analyses (DCA) were used to compare the clinical benefit of the two biomarkers. We found that the AUC value of phi (0.77) was comparable to those of %p2PSA (0.76) and PCA3 (0.73) with no significant differences in pairwise comparison (%p2PSA vs phi p = 0.673, %p2PSA vs. PCA3 p = 0.417 and phi vs. PCA3 p = 0.247). These three biomarkers significantly outperformed fPSA (AUC = 0.60), % fPSA (AUC = 0.62) and p2PSA (AUC = 0.63). At DCA, phi and PCA3 exhibited a very close net benefit profile until the threshold probability of 25%, then phi index showed higher net benefit than PCA3. Multivariable analysis showed that the addition of phi and PCA3 to the base multivariable model (age, PSA, %fPSA, DRE, prostate volume) increased predictive accuracy, whereas no model improved single biomarker performance. Finally we showed that subjects with active surveillance (AS) compatible cancer had significantly lower phi and PCA3 values (p<0.001 and p = 0.01, respectively). In conclusion, both phi and PCA3 comparably increase the accuracy in predicting the presence of PCa in total PSA range 2–10 ng/ml at initial biopsy, outperforming currently used %fPSA.