Robust, reproducible and quantitative analysis of thousands of proteomes by micro-flow LC-MS/MS

Nano-flow liquid chromatography tandem mass spectrometry (nano-flow LC-MS/MS) is the mainstay in proteome research because of its excellent sensitivity but often comes at the expense of robustness. Here we show that micro-flow LC-MS/MS using a 1x150 mm column shows excellent reproducibility of chromatographic retention time (2000 samples of human cell lines, tissues and body fluids. Deep proteome analysis identifies >9000 proteins and >120,000 peptides in 16 h and sample multiplexing using tandem mass tags increases throughput to 11 proteomes in 16 h. The system identifies >30,000 phosphopeptides in 12 h and protein-protein or protein-drug interaction experiments can be analyzed in 20 min per sample. We show that the same column can be used to analyze >7500 samples without apparent loss of performance. This study demonstrates that micro-flow LC-MS/MS is suitable for a broad range of proteomic applications

Successive Increases in the Resistance of Drosophila to Viral Infection through a Transposon Insertion Followed by a Duplication

To understand the molecular basis of how hosts evolve resistance to their parasites, we have investigated the genes that cause variation in the susceptibility of Drosophila melanogaster to viral infection. Using a host-specific pathogen of D. melanogaster called the sigma virus (Rhabdoviridae), we mapped a major-effect polymorphism to a region containing two paralogous genes called CHKov1 and CHKov2. In a panel of inbred fly lines, we found that a transposable element insertion in the protein coding sequence of CHKov1 is associated with increased resistance to infection. Previous research has shown that this insertion results in a truncated messenger RNA that encodes a far shorter protein than the susceptible allele. This resistant allele has rapidly increased in frequency under directional selection and is now the commonest form of the gene in natural populations. Using genetic mapping and site-specific recombination, we identified a third genotype with considerably greater resistance that is currently rare in the wild. In these flies there have been two duplications, resulting in three copies of both the truncated allele of CHKov1 and CHKov2 (one of which is also truncated). Remarkably, the truncated allele of CHKov1 has previously been found to confer resistance to organophosphate insecticides. As estimates of the age of this allele predate the use of insecticides, it is likely that this allele initially functioned as a defence against viruses and fortuitously “pre-adapted” flies to insecticides. These results demonstrate that strong selection by parasites for increased host resistance can result in major genetic changes and rapid shifts in allele frequencies; and, contrary to the prevailing view that resistance to pathogens can be a costly trait to evolve, the pleiotropic effects of these changes can have unexpected benefits

Deep strong light-matter coupling in plasmonic nanoparticle crystals

In the regime of deep strong light–matter coupling, the coupling strength exceeds the transition energies of the material, fundamentally changing its properties; for example, the ground state of the system contains virtual photons and the internal electromagnetic field gets redistributed by photon self-interaction. So far, no electronic excitation of a material has shown such strong coupling to free-space photons. Here we show that three-dimensional crystals of plasmonic nanoparticles can realize deep strong coupling under ambient conditions, if the particles are ten times larger than the interparticle gaps. The experimental Rabi frequencies (1.9 to 3.3 electronvolts) of face-centred cubic crystals of gold nanoparticles with diameters between 25 and 60 nanometres exceed their plasmon energy by up to 180 per cent. We show that the continuum of photons and plasmons hybridizes into polaritons that violate the rotating-wave approximation. The coupling leads to a breakdown of the Purcell effect—the increase of radiative damping through light–matter coupling—and increases the radiative polariton lifetime. The results indicate that metallic and semiconducting nanoparticles can be used as building blocks for an entire class of materials with extreme light–matter interaction, which will find application in nonlinear optics, the search for cooperative effects and ground states, polariton chemistry and quantum technology

Characterizing mammographic images by using generic texture features

Introduction Although mammographic density is an established risk factor for breast cancer, its use is limited in clinical practice because of a lack of automated and standardized measurement methods. The aims of this study were to evaluate a variety of automated texture features in mammograms as risk factors for breast cancer and to compare them with the percentage mammographic density (PMD) by using a case-control study design. Methods A case-control study including 864 cases and 418 controls was analyzed automatically. Four hundred seventy features were explored as possible risk factors for breast cancer. These included statistical features, moment-based features, spectral-energy features, and form-based features. An elaborate variable selection process using logistic regression analyses was performed to identify those features that were associated with case-control status. In addition, PMD was assessed and included in the regression model. Results Of the 470 image-analysis features explored, 46 remained in the final logistic regression model. An area under the curve of 0.79, with an odds ratio per standard deviation change of 2.88 (95% CI, 2.28 to 3.65), was obtained with validation data. Adding the PMD did not improve the final model. Conclusions Using texture features to predict the risk of breast cancer appears feasible. PMD did not show any additional value in this study. With regard to the features assessed, most of the analysis tools appeared to reflect mammographic density, although some features did not correlate with PMD. It remains to be investigated in larger case-control studies whether these features can contribute to increased prediction accuracy

An Imperfect Dopaminergic Error Signal Can Drive Temporal-Difference Learning

An open problem in the field of computational neuroscience is how to link synaptic plasticity to system-level learning. A promising framework in this context is temporal-difference (TD) learning. Experimental evidence that supports the hypothesis that the mammalian brain performs temporal-difference learning includes the resemblance of the phasic activity of the midbrain dopaminergic neurons to the TD error and the discovery that cortico-striatal synaptic plasticity is modulated by dopamine. However, as the phasic dopaminergic signal does not reproduce all the properties of the theoretical TD error, it is unclear whether it is capable of driving behavior adaptation in complex tasks. Here, we present a spiking temporal-difference learning model based on the actor-critic architecture. The model dynamically generates a dopaminergic signal with realistic firing rates and exploits this signal to modulate the plasticity of synapses as a third factor. The predictions of our proposed plasticity dynamics are in good agreement with experimental results with respect to dopamine, pre- and post-synaptic activity. An analytical mapping from the parameters of our proposed plasticity dynamics to those of the classical discrete-time TD algorithm reveals that the biological constraints of the dopaminergic signal entail a modified TD algorithm with self-adapting learning parameters and an adapting offset. We show that the neuronal network is able to learn a task with sparse positive rewards as fast as the corresponding classical discrete-time TD algorithm. However, the performance of the neuronal network is impaired with respect to the traditional algorithm on a task with both positive and negative rewards and breaks down entirely on a task with purely negative rewards. Our model demonstrates that the asymmetry of a realistic dopaminergic signal enables TD learning when learning is driven by positive rewards but not when driven by negative rewards

South American Hydrological Balance and Paleoceanography during the Late Pleistocene and Holocene (SAMBA) – Cruise No. M125, March 21 – April 15, 2016 - Rio de Janeiro (Brazil) – Fortaleza (Brazil)

R/V METEOR expedition M125 (“SAMBA”) focused on the influence of paleoceanographic changes off NE Brazil on the continental hydrological cycle. For this purpose, we obtained 202 m of gravity (24 stations) and piston cores (9) at seven sections on the shelf and continental slope close to river mouths from Cabo Frio in the south to the Rio Sao Francisco in the north. Coring stations were determined after intensive echosounder surveys (total: 1221 NM). On-board foraminiferal biostratigraphy, as well as color and XRF-scanning already provided first stratigraphic constraints, indicating the preservation of different regional paleoclimatic signals at the respective sections. Based on the preliminary stratigraphy, we retrieved high-resolution archives, covering Holocene sediments on the shelf and late Pleistocene sediments on the slope. These high-resolution archives are complemented by long-term records covering up to 900 ka of continuous sedimentation at deeper sites at smaller rivers. For proxy-calibration and the study of present-day sedimentation dynamics and biogeochemical processes, surface sediments were sampled via multicorer (47), Van Veen Grab (6) and box corer (3). Water samples for determination of the water chemistry (trace elements, stable and radiogenic isotopes) and nutrient composition were retrieved by 55 CTD/Rosette casts. In addition, we run multinet-hauls at seven stations to investigate the planktonic foraminiferal communities in the water column down to 700 m water depth, complemented by filtering water from the ship’s pump twice a day

kusterlab/curve_curator: Accepted manuscript (v0.2.1)

Analysis platform for large-scale dose-dependent dat

kusterlab/curve_curator: v0.3.0

<ul> <li>Add MSFragger support</li> <li>Better reports to the console & log file</li> <li>Minor improvements and fixes (#1, #2, #3, #5)</li> <li>Fixing problems with NaNs during thresholding (#4, #6, #7)</li> </ul&gt