The cardiac troponin C mutation Leu29Gln found in a patient with hypertrophic cardiomyopathy does not alter contractile parameters in skinned murine myocardium

The present study investigates the effects of the first mutation of troponin C (hcTnCL29Q) found in a patient with hypertrophic cardiomyopathy (HCM) on force–pCa relations and the interplay with phosphorylation of sarcomeric PKA substrates. In triton-skinned murine cardiac fibers, the endogenous mcTnC was extracted and the fibers were subsequently reconstituted with recombinant wild-type and mutant hcTnC. Force–pCa relations of preparations containing hcTnCL29Q or hcTnCWT were similar. Incubation of fibers reconstituted with the recombinant proteins with phosphatase to dephosphorylate sarcomeric PKA substrates induced an increase in Ca2+ sensitivity, slightly more pronounced (0.04 pCa units) in hcTnCL29Q-containing fibers. Incubation of the dephosphorylated fibers with PKA induced significant rightward shifts of force–pCa relations of similar magnitude with both, hcTnCL29Q and hcTnCWT. No significant effects of hcTnCL29Q on the velocity of unloaded shortening were observed. In conclusion, no major differences in contractile parameters of preparations containing hcTnCL29Q compared to hcTnCWT were observed. Therefore, it appears unlikely that hcTnCL29Q induces the development of HCM by affecting the regulation of Ca2+-activated force and interference with PKA-mediated modulation of the Ca2+ sensitivity of contraction

High-Intensity Interval Training Interventions in Children and Adolescents: A Systematic Review

BackgroundWhilst there is increasing interest in the efficacy of high-intensity interval training in children and adolescents as a time-effective method of eliciting health benefits, there remains little consensus within the literature regarding the most effective means for delivering a high-intensity interval training intervention. Given the global health issues surrounding childhood obesity and associated health implications, the identification of effective intervention strategies is imperative.ObjectivesThe aim of this review was to examine high-intensity interval training as a means of influencing key health parameters and to elucidate the most effective high-intensity interval training protocol.MethodsStudies were included if they: (1) studied healthy children and/or adolescents (aged 5–18 years); (2) prescribed an intervention that was deemed high intensity; and (3) reported health-related outcome measures.ResultsA total of 2092 studies were initially retrieved from four databases. Studies that were deemed to meet the criteria were downloaded in their entirety and independently assessed for relevance by two authors using the pre-determined criteria. From this, 13 studies were deemed suitable. This review found that high-intensity interval training in children and adolescents is a time-effective method of improving cardiovascular disease biomarkers, but evidence regarding other health-related measures is more equivocal. Running-based sessions, at an intensity of >90% heart rate maximum/100–130% maximal aerobic velocity, two to three times a week and with a minimum intervention duration of 7 weeks, elicit the greatest improvements in participant health.ConclusionWhile high-intensity interval training improves cardiovascular disease biomarkers, and the evidence supports the effectiveness of running-based sessions, as outlined above, further recommendations as to optimal exercise duration and rest intervals remain ambiguous owing to the paucity of literature and the methodological limitations of studies presently available

Inhibiting androgen receptor nuclear entry in castration-resistant prostate cancer

Clinical resistance to the second-generation antiandrogen enzalutamide in castration resistant prostate cancer (CRPC), despite persistent androgen receptor (AR) activity in tumors, highlights the unmet medical need for next generation antagonists. We have identified and characterized tetra-aryl cyclobutanes (CBs) as a new class of competitive AR antagonists that exhibit a unique mechanism of action. These CBs are structurally distinct from current antiandrogens (hydroxyflutamide, bicalutamide, and enzalutamide), and inhibit AR-mediated gene expression, cell proliferation, and tumor growth in several models of CRPC. Conformational profiling revealed that CBs stabilize an AR conformation resembling an unliganded receptor. Using a variety of techniques, it was determined that the AR:CB complex was not recruited to AR-regulated promoters and, like apo AR, remains sequestered in the cytoplasm bound to heat shock proteins. Thus, we have identified third generation AR antagonists whose unique mechanism of action suggests that they may have therapeutic potential in CRPC

RET Germline Mutations Identified by Exome Sequencing in a Chinese Multiple Endocrine Neoplasia Type 2A/Familial Medullary Thyroid Carcinoma Family

BACKGROUND: Whole exome sequencing provides a labor-saving and direct means of genetic diagnosis of hereditary disorders in which the pathogenic gene harbors a large cohort of exons. We set out to demonstrate a suitable example of genetic diagnosis of MEN 2A/FMTC (multiple endocrine neoplasia type 2/familial medullary thyroid carcinoma) using this approach. METHODOLOGY/PRINCIPAL FINDINGS: We sequenced the whole exome of six individuals from a large Chinese MEN2A/FMTC pedigree to identify the variants of the RET (REarranged during Transfection) protooncogene and followed this by validation. Then prophylactic or surgical thyroidectomy with modified or level VI lymph node dissection and adrenalectomy were performed for the carriers. The cases were closely followed up. Massively parallel sequencing revealed four missense mutations of RET. We unexpectedly discovered that the proband's daughter with MEN 2A-related MTC presented a novel p.C634Y/V292M/R67H/R982C compound mutation, due to the involvement of p.C634Y in the proband with MEN 2A and p.V292M/R67H/R982C in the proband's husband with FMTC. In the maternal origin, p.C634Y caused bilateral MTC in all 5 cases and bilateral pheochromocytoma in 2 of the 5; the earliest onset age was 28 years. In the paternal origin, one of the six p.V292M/R67H/R982C carriers presented bilateral MTC (70 years old), one only had bilateral C-cell hyperplasia (44 years), two had bilateral multi-nodules (46 and 48 years) and two showed no abnormality (22 and 19 years). CONCLUSIONS/SIGNIFICANCE: The results confirmed the successful clinical utility of whole exome sequencing, and our data suggested that the p.C634Y/V292M/R67H/R982C mutation of RET exhibited a more aggressive clinical phenotype than p.C634Y or p.V292M/R67H/R982C, while p.V292M/R67H/R982C presented a relatively milder pathogenicity of MTC and likely predisposed to FMTC

Regulation of Septin Dynamics by the Saccharomyces cerevisiae Lysine Acetyltransferase NuA4

In the budding yeast Saccharomyces cerevisiae, the lysine acetyltransferase NuA4 has been linked to a host of cellular processes through the acetylation of histone and non-histone targets. To discover proteins regulated by NuA4-dependent acetylation, we performed genome-wide synthetic dosage lethal screens to identify genes whose overexpression is toxic to non-essential NuA4 deletion mutants. The resulting genetic network identified a novel link between NuA4 and septin proteins, a group of highly conserved GTP-binding proteins that function in cytokinesis. We show that acetyltransferase-deficient NuA4 mutants have defects in septin collar formation resulting in the development of elongated buds through the Swe1-dependent morphogenesis checkpoint. We have discovered multiple sites of acetylation on four of the five yeast mitotic septins, Cdc3, Cdc10, Cdc12 and Shs1, and determined that NuA4 can acetylate three of the four in vitro. In vivo we find that acetylation levels of both Shs1 and Cdc10 are reduced in a catalytically inactive esa1 mutant. Finally, we determine that cells expressing a Shs1 protein with decreased acetylation in vivo have defects in septin localization that are similar to those observed in NuA4 mutants. These findings provide the first evidence that yeast septin proteins are acetylated and that NuA4 impacts septin dynamics

Pharmacokinetic-Pharmacodynamic Modeling in Pediatric Drug Development, and the Importance of Standardized Scaling of Clearance.

Pharmacokinetic/pharmacodynamic (PKPD) modeling is important in the design and conduct of clinical pharmacology research in children. During drug development, PKPD modeling and simulation should underpin rational trial design and facilitate extrapolation to investigate efficacy and safety. The application of PKPD modeling to optimize dosing recommendations and therapeutic drug monitoring is also increasing, and PKPD model-based dose individualization will become a core feature of personalized medicine. Following extensive progress on pediatric PK modeling, a greater emphasis now needs to be placed on PD modeling to understand age-related changes in drug effects. This paper discusses the principles of PKPD modeling in the context of pediatric drug development, summarizing how important PK parameters, such as clearance (CL), are scaled with size and age, and highlights a standardized method for CL scaling in children. One standard scaling method would facilitate comparison of PK parameters across multiple studies, thus increasing the utility of existing PK models and facilitating optimal design of new studies

Euclid preparation: XXIV. Calibration of the halo mass function in (?)CDM cosmologies

Euclid s photometric galaxy cluster survey has the potential to be a very competitive cosmological probe. The main cosmological probe with observations of clusters is their number count, within which the halo mass function (HMF) is a key theoretical quantity. We present a new calibration of the analytic HMF, at the level of accuracy and precision required for the uncertainty in this quantity to be subdominant with respect to other sources of uncertainty in recovering cosmological parameters from Euclid cluster counts. Our model is calibrated against a suite of N-body simulations using a Bayesian approach taking into account systematic errors arising from numerical effects in the simulation. First, we test the convergence of HMF predictions from different N-body codes, by using initial conditions generated with different orders of Lagrangian Perturbation theory, and adopting different simulation box sizes and mass resolution. Then, we quantify the effect of using different halo finder algorithms, and how the resulting differences propagate to the cosmological constraints. In order to trace the violation of universality in the HMF, we also analyse simulations based on initial conditions characterised by scale-free power spectra with different spectral indexes, assuming both Einsteinde Sitter and standard CDM expansion histories. Based on these results, we construct a fitting function for the HMF that we demonstrate to be sub-percent accurate in reproducing results from 9 different variants of the CDM model including massive neutrinos cosmologies. The calibration systematic uncertainty is largely sub-dominant with respect to the expected precision of future massobservation relations; with the only notable exception of the effect due to the halo finder, that could lead to biased cosmological inference

Euclid: Covariance of weak lensing pseudo-C_ell estimates. Calculation, comparison to simulations, and dependence on survey geometry

An accurate covariance matrix is essential for obtaining reliable cosmological results when using a Gaussian likelihood. In this paper we study the covariance of pseudo-C_ estimates of tomographic cosmic shear power spectra. Using two existing publicly available codes in combination, we calculate the full covariance matrix, including mode-coupling contributions arising from both partial sky coverage and non-linear structure growth. For three different sky masks, we compare the theoretical covariance matrix to that estimated from publicly available N-body weak lensing simulations, finding good agreement. We find that as a more extreme sky cut is applied, a corresponding increase in both Gaussian off-diagonal covariance and non-Gaussian super-sample covariance is observed in both theory and simulations, in accordance with expectations. Studying the different contributions to the covariance in detail, we find that the Gaussian covariance dominates along the main diagonal and the closest off-diagonals, but further away from the main diagonal the super-sample covariance is dominant. Forming mock constraints in parameters describing matter clustering and dark energy, we find that neglecting non-Gaussian contributions to the covariance can lead to underestimating the true size of confidence regions by up to 70 per cent. The dominant non-Gaussian covariance component is the super-sample covariance, but neglecting the smaller connected non-Gaussian covariance can still lead to the underestimation of uncertainties by 10--20 per cent. A real cosmological analysis will require marginalisation over many nuisance parameters, which will decrease the relative importance of all cosmological contributions to the covariance, so these values should be taken as upper limits on the importance of each component

Euclid: Estimation of the impact of correlated readout noise for flux measurements with the euclid NISP instrument

The Euclid satellite, to be launched by ESA in 2022, will be a major instrument for cosmology for the next decades. Euclid is composed of two instruments: the Visible instrument and the Near Infrared Spectrometer and Photometer (NISP). In this work, we estimate the implications of correlated readout noise in the NISP detectors for the final in-flight flux measurements. Considering the multiple accumulated readout mode, for which the UTR (Up The Ramp) exposure frames are averaged in groups, we derive an analytical expression for the noise covariance matrix between groups in the presence of correlated noise. We also characterize the correlated readout noise properties in the NISP engineering-grade detectors using long dark integrations. For this purpose, we assume a (1/f)α-like noise model and fit the model parameters to the data, obtaining typical values of $\sigma ={19.7}_{-0.8}^{+1.1}$ e− Hz−0.5, ${f}_{\mathrm{knee}}=({5.2}_{-1.3}^{+1.8})\times {10}^{-3}\,\mathrm{Hz}$ and $\alpha ={1.24}_{-0.21}^{+0.26}$. Furthermore, via realistic simulations and using a maximum likelihood flux estimator we derive the bias between the input flux and the recovered one. We find that using our analytical expression for the covariance matrix of the correlated readout noise we diminish this bias by up to a factor of four with respect to the white noise approximation for the covariance matrix. Finally, we conclude that the final bias on the in-flight NISP flux measurements should still be negligible even in the white readout noise approximation, which is taken as a baseline for the Euclid on-board processing to estimate the on-sky flux

Euclid: Identification of asteroid streaks in simulated images using deep learning

The material composition of asteroids is an essential piece of knowledge in the quest to understand the formation and evolution of the Solar System. Visual to near-infrared spectra or multiband photometry is required to constrain the material composition of asteroids, but we currently have such data, especially in the near-infrared wavelengths, for only a limited number of asteroids. This is a significant limitation considering the complex orbital structures of the asteroid populations. Up to 150 000 asteroids will be visible in the images of the upcoming ESA Euclid space telescope, and the instruments of Euclid will offer multiband visual to near-infrared photometry and slitless near-infrared spectra of these objects. Most of the asteroids will appear as streaks in the images. Due to the large number of images and asteroids, automated detection methods are needed. A non-machine-learning approach based on the StreakDet software was previously tested, but the results were not optimal for short and/or faint streaks. We set out to improve the capability to detect asteroid streaks in Euclid images by using deep learning. We built, trained, and tested a three-step machine-learning pipeline with simulated Euclid images. First, a convolutional neural network (CNN) detected streaks and their coordinates in full images, aiming to maximize the completeness (recall) of detections. Then, a recurrent neural network (RNN) merged snippets of long streaks detected in several parts by the CNN. Lastly, gradient-boosted trees (XGBoost) linked detected streaks between different Euclid exposures to reduce the number of false positives and improve the purity (precision) of the sample. The deep-learning pipeline surpasses the completeness and reaches a similar level of purity of a non-machine-learning pipeline based on the StreakDet software. Additionally, the deep-learning pipeline can detect asteroids 0.25-0.5 magnitudes fainter than StreakDet. The deep-learning pipeline could result in a 50% increase in the number of detected asteroids compared to the StreakDet software. There is still scope for further refinement, particularly in improving the accuracy of streak coordinates and enhancing the completeness of the final stage of the pipeline, which involves linking detections across multiple exposures