The synergistic effects between Vorinostat and Tamoxifen observed through a phase II study on breast cancer patients resistant to hormone therapy may involve more than the modulation of ER-alpha to reverse Tamoxifen resistance in ERBC cells. RT-qPCR of genes expressed in Tamoxifen resistant cells, trefoil factor 1(TFF1) and v-myc avian myelocytomatosis viral oncogene homolog (MYC), were evaluated along with ESR1 and Diablo as a control. MYC was observed to have increased expression in the treated cells, whereas the other genes had a decrease in their expression levels after the cells were treated for 3 days with Vorinostat IC30 of 1 µM. As for targeting the AR, MCF7 Tamoxifen sensitive and resistant cells were not affected by the AR antagonists to determine an IC50. The cell viability for all MCF7 sub-clones only decreased for high concentrations of 5.56 µM - 50 µM in Bicalutamide and 16.67 µM – 50 µM of MDV1300. Furthermore, hormone depletion of MCF7 G11 Tamoxifen resistant sub-clones did not show a great response to DHT stimulation or the AR antagonists. In the RT-qPCR, the MCF7 G11 cells showed an increase in mRNA expression for ER, AR, and PR after 4 hours of treatment with estradiol. As for the DHT treatment, ER, AR, PR, and PSA had a minimal increase in the fold change, but the fold change in AR was less than in the estradiol treatment. The Mayo Clinic will investigate the possible usage of AR as a biomarker through immunohistochemistry.
As life expectancy increases worldwide, age related diseases are becoming greater health concerns. One of the most prevalent age-related diseases in the United States is dementia, with Alzheimer’s disease (AD) being the most common form, accounting for 60-80% of cases. Genetics plays a large role in a person’s risk of developing AD. Familial AD, which makes up less than 1% of all AD cases, is caused by autosomal dominant gene mutations and has almost 100% penetrance. Genetic risk factors are believed to make up about 49%-79% of the risk in sporadic cases. Many different genetic risk factors for both familial and sporadic AD have been identified, but there is still much work to be done in the field of AD, especially in non-Caucasian populations. This review summarizes the three major genes responsible for familial AD, namely APP, PSEN1 and PSEN2. Also discussed are seven identified genetic risk factors for sporadic AD, single nucleotide polymorphisms in the APOE, ABCA7, NEDD9, CASS4, PTK2B, CLU, and PICALM genes. An overview of the main function of the proteins associated with the genes is given, along with the supposed connection to AD pathology.
In the weeks following the first imported case of Ebola in the U. S. on September 29, 2014, coverage of the very limited outbreak dominated the news media, in a manner quite disproportionate to the actual threat to national public health; by the end of October, 2014, there were only four laboratory confirmed cases of Ebola in the entire nation. Public interest in these events was high, as reflected in the millions of Ebola-related Internet searches and tweets performed in the month following the first confirmed case. Use of trending Internet searches and tweets has been proposed in the past for real-time prediction of outbreaks (a field referred to as “digital epidemiology”), but accounting for the biases of public panic has been problematic. In the case of the limited U. S. Ebola outbreak, we know that the Ebola-related searches and tweets originating the U. S. during the outbreak were due only to public interest or panic, providing an unprecedented means to determine how these dynamics affect such data, and how news media may be driving these trends.
Methodology
We examine daily Ebola-related Internet search and Twitter data in the U. S. during the six week period ending Oct 31, 2014. TV news coverage data were obtained from the daily number of Ebola-related news videos appearing on two major news networks. We fit the parameters of a mathematical contagion model to the data to determine if the news coverage was a significant factor in the temporal patterns in Ebola-related Internet and Twitter data.
Conclusions
We find significant evidence of contagion, with each Ebola-related news video inspiring tens of thousands of Ebola-related tweets and Internet searches. Between 65% to 76% of the variance in all samples is described by the news media contagion model.