Association between cadmium and androgen receptor protein expression differs in prostate tumors of African American and European American men

Cadmium is a known carcinogen that has been implicated in prostate cancer, but how it affects prostate carcinogenesis in humans remains unclear. Evidence from basic science suggests that cadmium can bind to the androgen receptor causing endocrine disruption. The androgen receptor is required for normal prostate development and is the key driver of prostate cancer progression. In this study, we examined the association between cadmium content and androgen receptor protein expression in prostate cancer tissue of African American (N = 22) and European American (N = 30) men. Although neither overall tumor cadmium content (log transformed) nor androgen receptor protein expression level differed by race, we observed a race-cadmium interaction with regard to androgen receptor expression (P = 0.003) even after accounting for age at prostatectomy, smoking history, and Gleason score. African American men had a significant positive correlation between tumor tissue cadmium content and androgen receptor expression (Pearson correlation = 0.52, P = 0.013), while European Americans showed a non-significant negative correlation between the two (Pearson correlation = -0.19, P = 0.31). These results were unchanged after further accounting for tissue zinc content or dietary zinc or selenium intake. African American cases with high-cadmium content (>median) in tumor tissue had more than double the androgen receptor expression (0.021 vs. 0.008, P = 0.014) of African American men with low-cadmium level. No difference in androgen receptor expression was observed in European Americans by cadmium level (high 0.015 vs. low 0.011, P = 0.30). Larger studies are needed to confirm these results and if upheld, determine the biologic mechanism by which cadmium increases androgen receptor protein expression in a race-dependent manner. Our results suggest that cadmium may play a role in race disparities observed in prostate cancer.

MP81-20 NON-INVASIVE, DUAL-LABELING TECHNOLOGY FOR CELL TRACKING IN STEM CELL THERAPY FOR ERECTILE DYSFUNCTION

LBA7 HUMAN PLACENTAL STEM CELLS PROMOTE ERECTILE FUNCTION RECOVERY IN A RODENT NEUROVASCULAR ERECTILE DYSFUNCTION MODEL

PCN147 - COST-EFFECTIVENESS SIMULATION AND ANALYSIS OF COLORECTAL CANCER SCREENING IN SHANGHAI POPULATION, CHINA: COMPARISON BETWEEN URBAN AND RURAL RESIDENTS

The interplay of proactive personality and internship quality in Chinese university graduates' job search success: The role of career adaptability

Aryl hydrocarbon receptor is activated in patients and mice with chronic kidney disease

Patients with chronic kidney disease (CKD) are exposed to uremic toxins and have an increased risk of cardiovascular disease. Some uremic toxins, like indoxyl sulfate, are agonists of the transcription factor aryl hydrocarbon receptor (AHR). These toxins induce a vascular procoagulant phenotype. Here we investigated AHR activation in patients with CKD and in a murine model of CKD. We performed a prospective study in 116 patients with CKD stage 3 to 5D and measured the AHR-Activating Potential of serum by bioassay. Compared to sera from healthy controls, sera from CKD patients displayed a strong AHR-Activating Potential; strongly correlated with eGFR and with the indoxyl sulfate concentration. The expression of the AHR target genes Cyp1A1 and AHRR was up-regulated in whole blood from patients with CKD. Survival analyses revealed that cardiovascular events were more frequent in CKD patients with an AHR-Activating Potential above the median. In mice with 5/6 nephrectomy, there was an increased serum AHR-Activating Potential, and an induction of Cyp1a1 mRNA in the aorta and heart, absent in AhR -/- CKD mice. After serial indoxyl sulfate injections, we observed an increase in serum AHR-AP and in expression of Cyp1a1 mRNA in aorta and heart in WT mice, but not in AhR -/- mice. Thus, the AHR pathway is activated both in patients and mice with CKD. Hence, AHR activation could be a key mechanism involved in the deleterious cardiovascular effects observed in CKD.

Secondary hardening in laser rapidly solidified Fe68(MoWCrVCoNiAlCu)32 medium-entropy high-speed steel coatings

Biocompatible Bi(OH)3 nanoparticles with reduced photocatalytic activity as possible ultraviolet filter in sunscreens

In this study we investigate readily synthesised Bi(OH)3 nanoparticles as a novel, multifunctional ultraviolet filter for sunscreen. The absorbance of Bi(OH)3 NPs in the ultraviolet region is comparable to that of both ZnO and TiO2 NPs used in commercial sunscreens. In vitro photoprotection results show that the combination of TiO2/Bi(OH)3 is more efficient than TiO2/ZnO over the whole UV range, with an increase in sun protection factor of 28%. The emulsions show rheological properties comparable to those of commercial sunscreens. The combination of TiO2/Bi(OH)3 led to insignificant damage on pre-painted steel panels after exterior exposure for twelve weeks. We also demonstrate that the addition of Bi(OH)3 NPs reduces the degradation of crystal violet by photocatalytically active TiO2 or ZnO NPs under ultraviolet exposure. Finally, assessment of the biocompatibility of Bi(OH)3 with HaCaT keratinocytes and Madin-Darby Canine Kidney (MDCK) cells in vitro is described.

Mechanical behavior and size effect of the staggered bio-structure materials

3D multi-scale FCN with random modality voxel dropout learning for Intervertebral Disc Localization and Segmentation from Multi-modality MR Images

Intervertebral discs (IVDs) are small joints that lie between adjacent vertebrae. The localization and segmentation of IVDs are important for spine disease diagnosis and measurement quantification. However, manual annotation is time-consuming and error-prone with limited reproducibility, particularly for volumetric data. In this work, our goal is to develop an automatic and accurate method based on fully convolutional networks (FCN) for the localization and segmentation of IVDs from multi-modality 3D MR data. Compared with single modality data, multi-modality MR images provide complementary contextual information, which contributes to better recognition performance. However, how to effectively integrate such multi-modality information to generate accurate segmentation results remains to be further explored. In this paper, we present a novel multi-scale and modality dropout learning framework to locate and segment IVDs from four-modality MR images. First, we design a 3D multi-scale context fully convolutional network, which processes the input data in multiple scales of context and then merges the high-level features to enhance the representation capability of the network for handling the scale variation of anatomical structures. Second, to harness the complementary information from different modalities, we present a random modality voxel dropout strategy which alleviates the co-adaption issue and increases the discriminative capability of the network. Our method achieved the 1st place in the MICCAI challenge on automatic localization and segmentation of IVDs from multi-modality MR images, with a mean segmentation Dice coefficient of 91.2% and a mean localization error of 0.62 mm. We further conduct extensive experiments on the extended dataset to validate our method. We demonstrate that the proposed modality dropout strategy with multi-modality images as contextual information improved the segmentation accuracy significantly. Furthermore, experiments conducted on extended data collected from two different time points demonstrate the efficacy of our method on tracking the morphological changes in a longitudinal study.