Living together, feeding apart: How to measure individual food consumption in social house mice

In many studies with animals kept in groups, scientists need information about each individual's food access without disturbance or separation of the animals. We developed an automatic feeding device that allows measurement of individual food consumption and experimental manipulation of individual food availability in small social mammals, such as house mice. The feeding device is based on radio frequency identification that triggers access to a motor-driven metal arm filled with food pellets and is mediated with the help of subcutaneously implanted transponders

DOK2 inhibits EGFR-mutated lung adenocarcinoma

Somatic mutations in the EGFR proto-oncogene occur in ~15% of human lung adenocarcinomas and the importance of EGFR mutations for the initiation and maintenance of lung cancer is well established from mouse models and cancer therapy trials in human lung cancer patients. Recently, we identified DOK2 as a lung adenocarcinoma tumor suppressor gene. Here we show that genomic loss of DOK2 is associated with EGFR mutations in human lung adenocarcinoma, and we hypothesized that loss of DOK2 might therefore cooperate with EGFR mutations to promote lung tumorigenesis. We tested this hypothesis using genetically engineered mouse models and find that loss of Dok2 in the mouse accelerates lung tumorigenesis initiated by oncogenic EGFR, but not that initiated by mutated Kras. Moreover, we find that DOK2 participates in a negative feedback loop that opposes mutated EGFR; EGFR mutation leads to recruitment of DOK2 to EGFR and DOK2-mediated inhibition of downstream activation of RAS. These data identify DOK2 as a tumor suppressor in EGFR-mutant lung adenocarcinoma

Immunohistochemical detection of macrophage migration inhibitory factor in fetal and adult bovine epididymis: Release by the apocrine secretion mode?

Originally defined as a lymphokine inhibiting the random migration of macrophages, the macrophage migration inhibitory factor (MIF) is an important mediator of the host response to infection. Beyond its function as a classical cytokine, MIF is currently portrayed as a multifunctional protein with growth-regulating properties present in organ systems beyond immune cells. In previous studies, we detected substantial amounts of MIF in the rat epididymis and epididymal spermatozoa, where it appears to play a role during post-testicular sperm maturation and the acquisition of fertilization ability. To explore its presence in other species not yet examined in this respect, we extended the range of studies to the bull. Using a polyclonal antibody raised against MIF purified from bovine eye lenses, we detected MIF in the epithelium of the adult bovine epididymis with the basal cells representing a prominently stained cell type. A distinct accumulation of MIF at the apical cell pole of the epithelial cells and in membranous vesicles localized in the lumen of the epididynnal duct was obvious. In the fetal bovine epididymis, we also detected MIF in the epithelium, whereas MIF accumulation was evident at the apical cell surface and in apical protrusions. By immuno-electron microscopy of the adult bovine epididymis, we localized MIF in apical protrusions of the epithelial cells and in luminal membrane-bound vesicles that were found in close proximity to sperm cells. Although the precise origin of the MIF-containing vesicles remains to be delineated, our morphological observations support the hypothesis that they become detached from the apical surface of the epididymal epithelial cells. Additionally, an association of MIF with the outer dense fibers of luminal spermatozoa was demonstrated. Data obtained in this study suggest MIF release by an apocrine secretion mode in the bovine epididymis. Furthermore, MIF localized in the basal cells of the epithelium and in the connective tissue could be responsible for regulating the migration of macrophages in order to avoid contact of immune cells with spermatozoa that carry a wide range of potent antigens. Copyright (c) 2006 S. Karger AG, Basel

Interaction Analysis between HLA-DRB1 Shared Epitope Alleles and MHC Class II Transactivator CIITA Gene with Regard to Risk of Rheumatoid Arthritis

HLA-DRB1 shared epitope (SE) alleles are the strongest genetic determinants for autoantibody positive rheumatoid arthritis (RA). One of the key regulators in expression of HLA class II receptors is MHC class II transactivator (CIITA). A variant of the CIITA gene has been found to associate with inflammatory diseases

Graphical models for inferring single molecule dynamics

<p>Abstract</p> <p>Background</p> <p>The recent explosion of experimental techniques in single molecule biophysics has generated a variety of novel time series data requiring equally novel computational tools for analysis and inference. This article describes in general terms how graphical modeling may be used to learn from biophysical time series data using the variational Bayesian expectation maximization algorithm (VBEM). The discussion is illustrated by the example of single-molecule fluorescence resonance energy transfer (smFRET)<it> versus</it> time data, where the smFRET time series is modeled as a hidden Markov model (HMM) with Gaussian observables. A detailed description of smFRET is provided as well.</p> <p>Results</p> <p>The VBEM algorithm returns the model’s evidence and an approximating posterior parameter distribution given the data. The former provides a metric for model selection via maximum evidence (ME), and the latter a description of the model’s parameters learned from the data. ME/VBEM provide several advantages over the more commonly used approach of maximum likelihood (ML) optimized by the expectation maximization (EM) algorithm, the most important being a natural form of model selection and a well-posed (non-divergent) optimization problem.</p> <p>Conclusions</p> <p>The results demonstrate the utility of graphical modeling for inference of dynamic processes in single molecule biophysics.</p

Bayesian inference of accurate population sizes and FRET efficiencies from single diffusing biomolecules.

It is of significant biophysical interest to obtain accurate intramolecular distance information and population sizes from single-molecule Förster resonance energy transfer (smFRET) data obtained from biomolecules in solution. Experimental methods of increasing cost and complexity are being developed to improve the accuracy and precision of data collection. However, the analysis of smFRET data sets currently relies on simplistic, and often arbitrary methods, for the selection and denoising of fluorescent bursts. Although these methods are satisfactory for the analysis of simple, low-noise systems with intermediate FRET efficiencies, they display systematic inaccuracies when applied to more complex systems. We have developed an inference method for the analysis of smFRET data from solution studies based on rigorous model-based Bayesian techniques. We implement a Monte Carlo Markov chain (MCMC) based algorithm that simultaneously estimates population sizes and intramolecular distance information directly from a raw smFRET data set, with no intermediate event selection and denoising steps. Here, we present both our parametric model of the smFRET process and the algorithm developed for data analysis. We test the algorithm using a combination of simulated data sets and data from dual-labeled DNA molecules. We demonstrate that our model-based method systematically outperforms threshold-based techniques in accurately inferring both population sizes and intramolecular distances.This is the final published version. It's also available from ACS in Analytical Chemistry: http://pubs.acs.org/doi/pdf/10.1021/ac501188r

Single Molecule Conformational Memory Extraction: P5ab RNA Hairpin

Extracting kinetic models from single molecule data is an important route to mechanistic insight in biophysics, chemistry, and biology. Data collected from force spectroscopy can probe discrete hops of a single molecule between different conformational states. Model extraction from such data is a challenging inverse problem because single molecule data are noisy and rich in structure. Standard modeling methods normally assume (i) a prespecified number of discrete states and (ii) that transitions between states are Markovian. The data set is then fit to this predetermined model to find a handful of rates describing the transitions between states. We show that it is unnecessary to assume either (i) or (ii) and focus our analysis on the zipping/unzipping transitions of an RNA hairpin. The key is in starting with a very broad class of non-Markov models in order to let the data guide us toward the best model from this very broad class. Our method suggests that there exists a folding intermediate for the P5ab RNA hairpin whose zipping/unzipping is monitored by force spectroscopy experiments. This intermediate would not have been resolved if a Markov model had been assumed from the onset. We compare the merits of our method with those of others

New Petro‐aggression in the Middle East: Saudi Arabia in the Spotlight

That hydrocarbon abundance may lead to more violence is an established truism in the literature on the resource curse. Looking at the Middle East, however, the literature relates bellicose state behaviour entirely to oil-producing revolutionary republics. Instead, dynastic monarchies are claimed to be the more peacefully behaving actors. Current developments turn this conclusion upside down, however. Since 2015 at the latest, the foreign policy of Saudi Arabia, the leading monarchy in the Middle East, has transformed from multi-dependence to petro-aggression. By discussing this striking transformation, the paper puts forward a framework looking at the interaction of three crucial dimensions: first, the decreasing power projection towards the Middle East by the United States, the decade-long hegemon, due to gradual changes in world energy markets and war fatigue at home; second, the lasting fiscal potency of the Saudi regime; and, third, the personalization of the Saudi monarchy under King Salman as a historically contingent result of transferring power to the generation of Ibn Saud's grandsons