Prenatal exposure to soy and selenium reduces prostate cancer risk factors in TRAMP mice more than exposure beginning at six weeks.

BACKGROUND: Diets high in soy and selenium (Se) decrease prostate cancer risk factors in healthy rats. The purpose of this study was to determine whether treatment with high levels of soy and/or supplemental Se would decrease prostate cancer risk factors in the Transgenic Adenocarcinoma of Mouse Prostate (TRAMP) mouse, and whether timing of the introduction of these nutrients would affect risk reduction. METHODS: Male hemizygous [C57BL/6 × FVB]F1 TRAMP mice were exposed to stock diets high or devoid of soy, with or without a supplement of Se-methylselenocysteine (MSC) starting at conception (10 mg Se/L in drinking water of pregnant/nursing dams; daily bolus of 4 mg Se/kg body weight to pups after weaning) or at 6 weeks of age in a 2 × 2 factorial design. Mice were killed at 12 weeks (n per dietary treatment = 20-30). RESULTS: Liver and serum Se concentrations were increased by MSC supplementation (P < 0.001), high-soy diet (P < 0.05), and initiation of dietary treatments at conception (P < 0.05). MSC supplementation had greater effects in mice fed the zero-soy basal diet, compared to the high-soy formulation (Pinteraction < 0.01). These same three interventions, individually and interactively, decreased body weight and epididymal fat pad weights, and steady state levels of mRNA for Cyp19a1 (aromatase) and Srd5a1 (5α-reductase). In contrast, MSC was the only treatment that decreased urogenital tract weights (P < 0.001), serum IGF-1 levels (P < 0.002), and Gleason scores (P < 0.05). CONCLUSIONS: Supplemental MSC reduces risk of prostate cancer in TRAMP mice. Basal diet composition (zero- vs. high-soy) can modify MSC's chemopreventive effects. Initiation of dietary treatments from conception maximizes chemopreventive effects of MSC. Prenatal Se status may have long-lasting effects on development and progression of prostate cancer.

Combination effects of dietary soy and methylselenocysteine in a mouse model of prostate cancer.

BACKGROUND: High dietary intake of soy or selenium (Se) is associated with decreased risk of prostate cancer. Soy constituents and various chemical forms of Se have each been shown to downregulate expression of the androgen receptor (AR) and AR-regulated genes in the prostate. We hypothesized that downregulation of AR and AR-regulated genes by the combination of these dietary components would inhibit tumorigenesis in the TRansgenic Adenocarcinoma of Mouse Prostate (TRAMP) mouse. METHODS: Male mice were exposed from conception to stock diets high or low in soy, with or without a supplement of Se-methylseleno-L-cysteine (MSC) in a 2 × 2 factorial design. Mice were sacrificed at 18 weeks. Prostate histopathology, urogenital tract (UGT) weight, hepatic activity of androgen-metabolizing enzymes, and expression of AR, AR-regulated, and AR-associated FOX family genes, in the dorsolateral prostate were examined. RESULTS: High soy intake decreased activity of hepatic aromatase and 5α-reductase, expression of AR, AR-regulated genes, FOXA1, UGT weight, and tumor progression, and upregulated protective FOXO3. Supplemental MSC upregulated AKR1C14, which reduces 5α-dihydrotestosterone. CONCLUSIONS: Soy is an effective pleiotropic dietary agent for prevention of prostate cancer. The finding of effects of soy on FOX family gene expression in animals is novel. Combination effects of supplemental MSC may depend upon the soy content of the basal diet to which it is added.

Don't Fear the Artificial Intelligence: A Systematic Review of Machine Learning for Prostate Cancer Detection in Pathology.

CONTEXT.­: Automated prostate cancer detection using machine learning technology has led to speculation that pathologists will soon be replaced by algorithms. This review covers the development of machine learning algorithms and their reported effectiveness specific to prostate cancer detection and Gleason grading. OBJECTIVE.­: To examine current algorithms regarding their accuracy and classification abilities. We provide a general explanation of the technology and how it is being used in clinical practice. The challenges to the application of machine learning algorithms in clinical practice are also discussed. DATA SOURCES.­: The literature for this review was identified and collected using a systematic search. Criteria were established prior to the sorting process to effectively direct the selection of studies. A 4-point system was implemented to rank the papers according to their relevancy. For papers accepted as relevant to our metrics, all cited and citing studies were also reviewed. Studies were then categorized based on whether they implemented binary or multi-class classification methods. Data were extracted from papers that contained accuracy, area under the curve (AUC), or κ values in the context of prostate cancer detection. The results were visually summarized to present accuracy trends between classification abilities. CONCLUSIONS.­: It is more difficult to achieve high accuracy metrics for multiclassification tasks than for binary tasks. The clinical implementation of an algorithm that can assign a Gleason grade to clinical whole slide images (WSIs) remains elusive. Machine learning technology is currently not able to replace pathologists but can serve as an important safeguard against misdiagnosis.

Valvular regurgitation and surgery associated with fenfluramine use: an analysis of 5743 individuals.

BACKGROUND: Use of fenfluramines for weight loss has been associated with the development of characteristic plaques on cardiac valves causing regurgitation. However, previously published studies of exposure to fenfluramines have been limited by relatively small sample size, short duration of follow-up, and the lack of any estimate of the frequency of subsequent valvular surgery. We performed an observational study of 5743 users of fenfluramines examined by echocardiography between July 1997 and February 2004 in a single large cardiology clinic. RESULTS: The prevalence of at least mild aortic regurgitation (AR) or moderate mitral regurgitation (MR) was 19.6% in women and 11.8% in men (p < 0.0001 for gender difference). Duration of use was strongly predictive of mild or greater AR (p < 0.0001 for trend), MR (p = 0.002), and tricuspid regurgitation (TR) (p < 0.0001), as was earlier scan date (p < 0.0001 for those scanned prior to 1 January 2000 versus later). Increasing age was also independently associated with increased risk of AR and MR (both p < 0.0001). With mean follow-up of 30.3 months, AR worsened in 15.2%, remained the same in 63.1%, and improved in 21.7%. Corresponding values for MR were 24.8%, 47.4% and 27.9%. Pulmonary hypertension was strongly associated with MR but not AR. Valve surgery was performed on 38 patients (0.66% of 5743), 25 (0.44%) with clear evidence of fenfluramine-related etiology. CONCLUSION: Regurgitant valvulopathy was common in individuals exposed to fenfluramines, more frequent in females, and associated with duration of use in all valves assessed. Valve surgery was performed as frequently for aortic as mitral valves and some tricuspid valve surgeries were also performed. The incidence of surgery appeared to be substantially increased compared with limited general population data.