Upper limits on the strength of periodic gravitational waves from PSR J1939+2134

The first science run of the LIGO and GEO gravitational wave detectors presented the opportunity to test methods of searching for gravitational waves from known pulsars. Here we present new direct upper limits on the strength of waves from the pulsar PSR J1939+2134 using two independent analysis methods, one in the frequency domain using frequentist statistics and one in the time domain using Bayesian inference. Both methods show that the strain amplitude at Earth from this pulsar is less than a few times $10^{-22}$.Comment: 7 pages, 1 figure, to appear in the Proceedings of the 5th Edoardo Amaldi Conference on Gravitational Waves, Tirrenia, Pisa, Italy, 6-11 July 200

Improving the sensitivity to gravitational-wave sources by modifying the input-output optics of advanced interferometers

We study frequency dependent (FD) input-output schemes for signal-recycling interferometers, the baseline design of Advanced LIGO and the current configuration of GEO 600. Complementary to a recent proposal by Harms et al. to use FD input squeezing and ordinary homodyne detection, we explore a scheme which uses ordinary squeezed vacuum, but FD readout. Both schemes, which are sub-optimal among all possible input-output schemes, provide a global noise suppression by the power squeeze factor, while being realizable by using detuned Fabry-Perot cavities as input/output filters. At high frequencies, the two schemes are shown to be equivalent, while at low frequencies our scheme gives better performance than that of Harms et al., and is nearly fully optimal. We then study the sensitivity improvement achievable by these schemes in Advanced LIGO era (with 30-m filter cavities and current estimates of filter-mirror losses and thermal noise), for neutron star binary inspirals, and for narrowband GW sources such as low-mass X-ray binaries and known radio pulsars. Optical losses are shown to be a major obstacle for the actual implementation of these techniques in Advanced LIGO. On time scales of third-generation interferometers, like EURO/LIGO-III (~2012), with kilometer-scale filter cavities, a signal-recycling interferometer with the FD readout scheme explored in this paper can have performances comparable to existing proposals. [abridged]Comment: Figs. 9 and 12 corrected; Appendix added for narrowband data analysi

Guidelines and Recommendations on Yeast Cell Death Nomenclature

Elucidating the biology of yeast in its full complexity has major implications for science, medicine and industry. One of the most critical processes determining yeast life and physiology is cellular demise. However, the investigation of yeast cell death is a relatively young field, and a widely accepted set of concepts and terms is still missing. Here, we propose unified criteria for the definition of accidental, regulated, and programmed forms of cell death in yeast based on a series of morphological and biochemical criteria. Specifically, we provide consensus guidelines on the differential definition of terms including apoptosis, regulated necrosis, and autophagic cell death, as we refer to additional cell death routines that are relevant for the biology of (at least some species of) yeast. As this area of investigation advances rapidly, changes and extensions to this set of recommendations will be implemented in the years to come. Nonetheless, we strongly encourage the authors, reviewers and editors of scientific articles to adopt these collective standards in order to establish an accurate framework for yeast cell death research and, ultimately, to accelerate the progress of this vibrant field of research

Guidelines and recommendations on yeast cell death nomenclature

Elucidating the biology of yeast in its full complexity has major implications for science, medicine and industry. One of the most critical processes determining yeast life and physiology is cel-lular demise. However, the investigation of yeast cell death is a relatively young field, and a widely accepted set of concepts and terms is still missing. Here, we propose unified criteria for the defi-nition of accidental, regulated, and programmed forms of cell death in yeast based on a series of morphological and biochemical criteria. Specifically, we provide consensus guidelines on the differ-ential definition of terms including apoptosis, regulated necrosis, and autophagic cell death, as we refer to additional cell death rou-tines that are relevant for the biology of (at least some species of) yeast. As this area of investigation advances rapidly, changes and extensions to this set of recommendations will be implemented in the years to come. Nonetheless, we strongly encourage the au-thors, reviewers and editors of scientific articles to adopt these collective standards in order to establish an accurate framework for yeast cell death research and, ultimately, to accelerate the pro-gress of this vibrant field of research

Block of Voltage-Gated Sodium Channels by Aripiprazole in a State-Dependent Manner

Aripiprazole is an atypical antipsychotic drug, which is prescribed for many psychiatric diseases such as schizophrenia and mania in bipolar disorder. It primarily acts as an agonist of dopaminergic and other G-protein coupled receptors. So far, an interaction with ligand- or voltage-gated ion channels has been classified as weak. Meanwhile, we identified aripiprazole in a preliminary test as a potent blocker of voltage-gated sodium channels. Here, we present a detailed analysis about the interaction of aripiprazole with the dominant voltage-gated sodium channel of heart muscle (hNav1.5). Electrophysiological experiments were performed by means of the patch clamp technique at human heart muscle sodium channels (hNav1.5), heterologously expressed in human TsA cells. Aripiprazole inhibits the hNav1.5 channel in a state- but not use-dependent manner. The affinity for the resting state is weak with an extrapolated Kr of about 55 µM. By contrast, the interaction with the inactivated state is strong. The affinities for the fast and slow inactivated state are in the low micromolar range (0.5–1 µM). Kinetic studies indicate that block development for the inactivated state must be described with a fast (ms) and a slow (s) time constant. Even though the time constants differ by a factor of about 50, the resulting affinity constants were nearly identical (in the range of 0.5 µM). Besides this, aripirazole also interacts with the open state of the channel. Using an inactivation deficit mutant, an affinity of about 1 µM was estimated. In summary, aripiprazole inhibits voltage-gated sodium channels at low micromolar concentrations. This property might add to its possible anticancer and neuroprotective properties

Relative tissue expression of homologous torsins can explain the neuronal specific importance of DYT1 dystonia-associated torsinA

status: publishe

Interactome of Two Diverse RNA Granules Links mRNA Localization to Translational Repression in Neurons

Transport of RNAs to dendrites occurs in neuronal RNA granules, which allows local synthesis of specific proteins at active synapses on demand, thereby contributing to learning and memory. To gain insight into the machinery controlling dendritic mRNA localization and translation, we established a stringent protocol to biochemically purify RNA granules from rat brain. Here, we identified a specific set of interactors for two RNA-binding proteins that are known components of neuronal RNA granules, Barentsz and Staufen2. First, neuronal RNA granules are much more heterogeneous than previously anticipated, sharing only a third of the identified proteins. Second, dendritically localized mRNAs, e.g., Arc and CaMKIIα, associate selectively with distinct RNA granules. Third, our work identifies a series of factors with known roles in RNA localization, translational control, and RNA quality control that are likely to keep localized transcripts in a translationally repressed state, often in distinct types of RNPs

Machine learning identifies ICU outcome predictors in a multicenter COVID-19 cohort

Background: Intensive Care Resources are heavily utilized during the COVID-19 pandemic. However, risk stratification and prediction of SARS-CoV-2 patient clinical outcomes upon ICU admission remain inadequate. This study aimed to develop a machine learning model, based on retrospective & prospective clinical data, to stratify patient risk and predict ICU survival and outcomes. Methods: A Germany-wide electronic registry was established to pseudonymously collect admission, therapeutic and discharge information of SARS-CoV-2 ICU patients retrospectively and prospectively. Machine learning approaches were evaluated for the accuracy and interpretability of predictions. The Explainable Boosting Machine approach was selected as the most suitable method. Individual, non-linear shape functions for predictive parameters and parameter interactions are reported. Results: 1039 patients were included in the Explainable Boosting Machine model, 596 patients retrospectively collected, and 443 patients prospectively collected. The model for prediction of general ICU outcome was shown to be more reliable to predict “survival”. Age, inflammatory and thrombotic activity, and severity of ARDS at ICU admission were shown to be predictive of ICU survival. Patients’ age, pulmonary dysfunction and transfer from an external institution were predictors for ECMO therapy. The interaction of patient age with D-dimer levels on admission and creatinine levels with SOFA score without GCS were predictors for renal replacement therapy. Conclusions: Using Explainable Boosting Machine analysis, we confirmed and weighed previously reported and identified novel predictors for outcome in critically ill COVID-19 patients. Using this strategy, predictive modeling of COVID-19 ICU patient outcomes can be performed overcoming the limitations of linear regression models. Trial registration “ClinicalTrials” (clinicaltrials.gov) under NCT04455451