Sigma1 Targeting to Suppress Aberrant Androgen Receptor Signaling in Prostate Cancer.

Suppression of androgen receptor (AR) activity in prostate cancer by androgen depletion or direct AR antagonist treatment, although initially effective, leads to incurable castration-resistant prostate cancer (CRPC) via compensatory mechanisms including resurgence of AR and AR splice variant (ARV) signaling. Emerging evidence suggests that Sigma1 (also known as sigma-1 receptor) is a unique chaperone or scaffolding protein that contributes to cellular protein homeostasis. We reported previously that some Sigma1-selective small molecules can be used to pharmacologically modulate protein homeostasis pathways. We hypothesized that these Sigma1-mediated responses could be exploited to suppress AR protein levels and activity. Here we demonstrate that treatment with a small-molecule Sigma1 inhibitor prevented 5α- dihydrotestosterone-mediated nuclear translocation of AR and induced proteasomal degradation of AR and ARV, suppressing the transcriptional activity and protein levels of both full-length and splice-variant AR. Consistent with these data, RNAi knockdown of Sigma1 resulted in decreased AR levels and transcriptional activity. Furthermore, Sigma1 physically associated with ARV7 and A

Response of Autonomic Nervous System to Body Positions: Fourier and Wavelet Analysis

Two mathematical methods, the Fourier and wavelet transforms, were used to study the short term cardiovascular control system. Time series, picked from electrocardiogram and arterial blood pressure lasting 6 minutes, were analyzed in supine position (SUP), during the first (HD1), and the second parts (HD2) of $90^{\circ}$ head down tilt and during recovery (REC). The wavelet transform was performed using the Haar function of period $T=2^j$ ($$,2,$...$,6) to obtain wavelet coefficients. Power spectra components were analyzed within three bands, VLF (0.003-0.04), LF (0.04-0.15) and HF (0.15-0.4) with the frequency unit cycle/interval. Wavelet transform demonstrated a higher discrimination among all analyzed periods than the Fourier transform. For the Fourier analysis, the LF of R-R intervals and VLF of systolic blood pressure show more evident difference for different body positions. For the wavelet analysis, the systolic blood pressures show much more evident difference than the R-R intervals. This study suggests a difference in the response of the vessels and the heart to different body positions. The partial dissociation between VLF and LF results is a physiologically relevant finding of this work.Comment: RevTex,8 figure

Bayesian Regression Inference Using a Normal Mixture Model

In this thesis we develop a two component mixture model to perform a Bayesian regression. We implement our model computationally using the Gibbs sampler algorithm and apply it to a dataset of differences in time measurement between two clocks. The dataset has ``good time measurements and ``bad time measurements that were associated with the two components of our mixture model. From our theoretical work we show that latent variables are a useful tool to implement our Bayesian normal mixture model with two components. After applying our model to the data we found that the model reasonably assigned probabilities of occurrence to the two states of the phenomenon of study; it also identified two processes with the same slope, different intercepts and different variances

Probabilistic Methodology and Techniques for Artefact Conception and Development

The purpose of this paper is to make a state of the art on probabilistic methodology and techniques for artefact conception and development. It is the 8th deliverable of the BIBA (Bayesian Inspired Brain and Artefacts) project. We first present the incompletness problem as the central difficulty that both living creatures and artefacts have to face: how can they perceive, infer, decide and act efficiently with incomplete and uncertain knowledge?. We then introduce a generic probabilistic formalism called Bayesian Programming. This formalism is then used to review the main probabilistic methodology and techniques. This review is organized in 3 parts: first the probabilistic models from Bayesian networks to Kalman filters and from sensor fusion to CAD systems, second the inference techniques and finally the learning and model acquisition and comparison methodologies. We conclude with the perspectives of the BIBA project as they rise from this state of the art

How costly is it for poor farmers to lift themselves out of poverty?

The main objective of this paper is to provide estimates of the cost of moving out of subsistence for Madagascar's farmers. The analysis is based on a simple asset-return model of occupational choice. Estimates suggest that the entry (sunk) cost associated with moving out of subsistence can be quite large - somewhere between 124 and 153 percent of a subsistence farmer's annual production. Our results make it possible to identify farm characteristics likely to generate large gains, if moved out of subsistence, yielding useful information for the targeting of trade-adjustment assistance programs.Markets and Market Access,Rural Poverty Reduction,Economic Theory&Research,Agribusiness,Access to Markets

The Non-Equilibrium Green Function (NEGF) Method

The Non-Equilibrium Green Function (NEGF) method was established in the 1960's through the classic work of Schwinger, Kadanoff, Baym, Keldysh and others using many-body perturbation theory (MBPT) and the diagrammatic theory for non-equilibrium processes. Much of the literature is based on the original MBPT-based approach and this makes it inaccessible to those unfamiliar with advanced quantum statistical mechanics. We obtain the NEGF equations directly from a one-electron Schr\"odinger equation using relatively elementary arguments. These equations have been used to discuss many problems of great interest such as quantized conductance, (integer) quantum Hall effect, Anderson localization, resonant tunneling and spin transport without a systematic treatment of many-body effects. But it goes beyond purely coherent transport allowing us to include phase-breaking interactions (both momentum-relaxing and momentum-conserving as well as spin-conserving and spin-relaxing) within a self-consistent Born approximation. We believe that the scope and utility of the NEGF equations transcend the MBPT-based approach originally used to derive it. NEGF teaches us how to combine quantum dynamics with "contacts" much as Boltzmann taught us how to combine classical dynamics with "contacts", using the word contacts in a broad, figurative sense to denote all kinds of entropy-driven processes. We believe that this approach to "contact-ing" the Schr\"odinger equation should be of broad interest to anyone working on device physics or non-equilibrium statistical mechanics in general.Comment: To appear in Springer Handbook of Semiconductor Devices (2021