Species- and organ-specificity of secretory proteins derived from human prostate and seminal vesicles

Polyclonal antibodies against semenogelin (SG) isolated from human seminal vesicle secretion and acid phosphatase (PAP), β‐microseminoprotein (β‐MSP), and Prostate‐Specific Antigen (PSA) derived from human prostatic fluid, as well as a monoclonal antibody against β‐MSP were used for immunocytochemical detection of the respective antigens in different organs from different species. SG immunoreactivity was detected in the epithelium of the pubertal and adult human and in monkey seminal vesicle, ampulla of the vas deferens, and ejaculatory duct. PAP, β‐MSP, and PSA immunoreactivities were detected in the pubertal and adult human prostate and the cranial and caudal monkey prostate. With the exception of a weak PSA immunoreactivity in the proximal portions of the ejaculatory duct, none of the latter antisera reacted with seminal vesicle, ampullary, and ejaculatory duct epithelium. Among the non‐primate species studied (dog, bull, rat, guinea pig) only the canine prostatic epithelium displayed a definite immunoreactivity with the PAP antibody and a moderate reaction with the PSA antibody. No immunoreaction was seen in bull and rat seminal vesicle and canine ampulla of the vas deferens with the SG antibody. The same was true for the (ventral) prostate of rat, bull, and dog for β‐MSP. The epithelium of the rat dorsal prostate showed a slight cross‐reactivity with the monoclonal antibody against β‐MSP and one polyclonal antibody against PSA. The findings indicate a rather strict species‐dependent expression of human seminal proteins which show some similarities in primates, but only marginal relationship to species with different physiology of seminal fluid

Using Approximate Bayesian Computation by Subset Simulation for Efficient Posterior Assessment of Dynamic State-Space Model Classes

Approximate Bayesian Computation (ABC) methods have gained in popularity over the last decade because they expand the horizon of Bayesian parameter inference methods to the range of models for which an analytical formula for the likelihood function might be difficult, or even impossible, to establish. The majority of the ABC methods rely on the choice of a set of summary statistics to reduce the dimension of the data. However, as has been noted in the ABC literature, the lack of convergence guarantees induced by the absence of a vector of sufficient summary statistics that assures intermodel sufficiency over the set of competing models hinders the use of the usual ABC methods when applied to Bayesian model selection or assessment. In this paper, we present a novel ABC model selection procedure for dynamical systems based on a recently introduced multilevel Markov chain Monte Carlo method, self-regulating ABC-SubSim, and a hierarchical state-space formulation of dynamic models. We show that this formulation makes it possible to independently approximate the model evidence required for assessing the posterior probability of each of the competing models. We also show that ABC-SubSim not only provides an estimate of the model evidence as a simple by-product but also gives the posterior probability of each model as a function of the tolerance level, which allows the ABC model choices made in previous studies to be understood. We illustrate the performance of the proposed framework for ABC model updating and model class selection by applying it to two problems in Bayesian system identification: a single-degree-of-freedom bilinear hysteretic oscillator and a three-story shear building with Masing hysteresis, both of which are subject to a seismic excitation

The relationship between biophysical variables and halocarbon distributions in the waters of the Amundsen and Ross Seas, Antarctica

Little is known regarding the distribution of volatile halogenated organic compounds (halocarbons) in Antarctic waters and their relation to biophysical variables. During the austral summer (December to January) in 2007-08 halocarbon and pigment concentrations were measured in the Amundsen (100-130 degrees W) and Ross Sea (158 degrees W-160 degrees E). In addition, halocarbons were determined in air, snow and sea ice. The distribution of halocarbons was influenced to a large extent by sea ice, and to a much lesser extent by pelagic biota. Concentrations of naturally produced halocarbons were elevated in the surface mixed layer in ice covered areas compared to open waters in polynyas and in the bottom waters of the Ross Sea. Higher concentrations of halocarbons were also found in sea ice brine compared to the surface waters. Incubations of snow revealed an additional source of halocarbons. The distribution of halocarbons also varied considerably between the Amundsen and Ross Seas, mainly due to the different oceanographic settings. For iodinated compounds, weak correlations were found with the presence of pigments indicative of Phaeocystis, mainly in the Ross Sea. Surface waters of the Amundsen and Ross Seas are a sink for bromoform (saturation anomalies, SA, -83 to 11%), whereas sea ice was found to be both a source and sink (SA -61-97%). In contrast, both surface waters and sea ice were found to be a source of chloroiodomethane (SA -6-1 200% and 91-22 000 resp.). Consequently, polar waters can have a substantial impact on global halocarbon budgets and need to be included in large-scale assessments. (C) 2012 Elsevier B.V. All rights reserved

Contribution of sea ice in the Southern Ocean to the cycling of volatile halogenated organic compounds

The contribution of sea ice to the flux of biogenic volatile halogenated organic compounds to the atmosphere in the Southern Ocean is currently not known. To approach this question, we measured halocarbons in sea ice, sea ice brine, and surface water of the Amundsen and Ross Seas. Concentrations in sea ice of these compounds, normalized to seawater salinity, ranged from 0.2 to 810 pmol L-1. Salinity-normalized chlorophyll a concentrations in the ice ranged from 3.5 to 190 mu gL(-1). Our results suggest biological production of halocarbons in sea ice, with maxima of halogenated organics and chlorophyll a commonly found in the interior of the ice cores. Iodinated VHOCs were found to be more enriched in sea ice than brominated ones. Furthermore, depth distributions indicated a transport of halocarbons from sea ice to air and underlying water

Approximate Bayesian Computation by Subset Simulation for model selection in dynamical systems

Approximate Bayesian Computation (ABC) methods are originally conceived to expand the horizon of Bayesian inference methods to the range of models for which only forward simulation is available. However, there are well-known limitations of the ABC approach to the Bayesian model selection problem, mainly due to lack of a sufficient summary statistics that work across models. In this paper, we show that formulating the standard ABC posterior distribution as the exact posterior PDF for a hierarchical state-space model class allows us to independently estimate the evidence for each alternative candidate model. We also show that the model evidence is a simple by-product of the ABC-SubSim algorithm. The validity of the proposed approach to ABC model selection is illustrated using simulated data from a three-story shear building with Masing hysteresis

Cold SO_2 molecules by Stark deceleration

We produce SO_2 molecules with a centre of mass velocity near zero using a Stark decelerator. Since the initial kinetic energy of the supersonic SO_2 molecular beam is high, and the removed kinetic energy per stage is small, 326 deceleration stages are necessary to bring SO_2 to a complete standstill, significantly more than in other experiments. We show that in such a decelerator possible loss due to coupling between the motional degrees of freedom must be considered. Experimental results are compared with 3D Monte-Carlo simulations and the quantum state selectivity of the Stark decelerator is demonstrated.Comment: 7 pages, 5 figure

STATCOM evaluation in electrified railway using V/V and Scott power transformers

Rail transport has always been one of the greatest economic boosters of several world nations, allowing the freight and passenger transport. In addition, it is the most secure and economic land transportation mode. From the energetic perspective, the electric locomotives emerge as one of the most efficient land transportation mode, as well as allow a more sustainable development. However, when an electric locomotive is connected to the three-phase power grid, power quality (PQ) deterioration arise, leading to the distortion and unbalance of the three-phase power grid currents and voltages which imply higher operational costs, raising economic and functional issues. In order to overcome the PQ deterioration phenomena, several solutions based power electronics technology have been studied and developed. These solutions vary in terms of control, functionality, implementation costs and complexity. One of the existing solutions is a static synchronous compensator (STATCOM), which compensates the three-phase currents imbalance and harmonics. In this paper, a comprehensive review of the electrified railway systems is carried out, identifying the electric PQ phenomena which may appear due to the non-linear dynamic traction loads. Following this topic, a computational simulation of the STATCOM is presented, making analysis of its behavior regarding the PQ improvement in electrified railway systems. Two case studies are presented: (i) a traction power system fed with V/V power transformer; (ii) a traction power system fed with Scott power transformer.This work has been supported by FCT – Fundação para a Ciência e Tecnologia with-in the Project Scope: UID/CEC/00319/2019. This work has been supported by the FCT Project QUALITY4POWER PTDC/EEI-EEE/28813/2017, and by the FCT Project DAIPESEV PTDC/EEI-EEE/30382/2017. Mr. Luis A. M. Barros is supported by the doctoral scholarship PD/BD/143006/2018 granted by the Portuguese FCT foundation. Mr. Mohamed Tanta was supported by FCT PhD grant with a reference PD/BD/127815/2016