eIF4G stimulates the activity of the DEAD box protein eIF4A by a conformational guidance mechanism

The activity of eIF4A, a key player in translation initiation, is regulated by other translation factors through currently unknown mechanisms. Here, we provide the necessary framework to understand the mechanism of eIF4A's regulation by eIF4G. In solution, eIF4A adopts a defined conformation that is different from the crystal structure. Binding of eIF4G induces a ‘half-open' conformation by interactions with both domains, such that the helicase motifs are pre-aligned for activation. A primary interface acts as an anchor for complex formation. We show here that formation of the secondary interface is essential for imposing the ‘half-open' conformation on eIF4A, and it is critical for the functional interaction of eIF4G with eIF4A. Via this bipartite interaction, eIF4G guides the transition of eIF4A between the ‘half-open' and closed conformations, and stimulates its activity by accelerating the rate-limiting step of phosphate release. Subtle changes induced by eIF4G may be amplified by input signals from other translation factors, leading to an efficient regulation of translation initiatio

Cluster Density Profiles as a Test of Modified Gravity

We present a new test of gravitational interactions at the r\sim(0.2-20)Mpc scale, around the virial radius of dark matter halos measured through cluster-galaxy lensing of maxBCG clusters from the Sloan Digital Sky Survey (SDSS). We employ predictions from self-consistent simulations of f(R) gravity to find an upper bound on the background field amplitude of f_R0<3.5x10^-3 at the 1D-marginalized 95% confidence level. As a model-independent assessment of the constraining power of cluster profiles measured through weak gravitational lensing, we also constrain the amplitude F_0 of a phenomenological modification based on the profile enhancement induced by f(R) gravity when not including effects from the increased cluster abundance in f(R). In both scenarios, dark-matter-only simulations of the concordance model corresponding to f_R0=0 and F_0=0 are consistent with the lensing measurements, i.e., at the 68% and 95% confidence level, respectively.Comment: 19 pages, 10 figures, 3 tables; new figure added to new version, removed F_0>0 prio

eIF4G stimulates the activity of the DEAD box protein eIF4A by a conformational guidance mechanism

The activity of eIF4A, a key player in translation initiation, is regulated by other translation factors through currently unknown mechanisms. Here, we provide the necessary framework to understand the mechanism of eIF4A’s regulation by eIF4G. In solution, eIF4A adopts a defined conformation that is different from the crystal structure. Binding of eIF4G induces a ‘half-open’ conformation by interactions with both domains, such that the helicase motifs are pre-aligned for activation. A primary interface acts as an anchor for complex formation. We show here that formation of the secondary interface is essential for imposing the ‘half-open’ conformation on eIF4A, and it is critical for the functional interaction of eIF4G with eIF4A. Via this bipartite interaction, eIF4G guides the transition of eIF4A between the ‘half-open’ and closed conformations, and stimulates its activity by accelerating the rate-limiting step of phosphate release. Subtle changes induced by eIF4G may be amplified by input signals from other translation factors, leading to an efficient regulation of translation initiation

Brain-based classification of youth with anxiety disorders: transdiagnostic examinations within the ENIGMA-Anxiety database using machine learning

Neuroanatomical findings on youth anxiety disorders are notoriously difficult to replicate, small in effect size, and have limited clinical relevance. These concerns have prompted a paradigm shift towards highly powered (i.e., big data) individual-level inferences, which are data-driven, transdiagnostic, and neurobiologically informed. Hence, we uniquely built/validated supervised neuroanatomical machine learning (ML) models for individual-level inferences, using the largest up to date neuroimaging database on youth anxiety disorders: ENIGMA Anxiety Consortium (N=3,343; Age: 10-25 years; Global Sites: 32). Modest, yet robust, brain-based classifications were achieved for specific anxiety disorders (Panic Disorder), but also transdiagnostically for all anxiety disorders when patients were subgrouped according to their sex, medication status, and symptom severity (AUC’s 0.59-0.63). Classifications were driven by neuroanatomical features (cortical thickness/surface area, subcortical volumes) in fronto-striato-limbic and temporo-parietal regions. This benchmark study provides estimates on individual-level classification performances that can be realistically achieved with ML using neuroanatomical data, within a large, heterogenous, and multi-site sample of youth with anxiety disorders

Lensing is low: cosmology, galaxy formation or new physics?

We present high signal-to-noise galaxy-galaxy lensing measurements of the BOSS CMASS sample using 250 square degrees of weak lensing data from CFHTLenS and CS82. We compare this signal with predictions from mock catalogs trained to match observables including the stellar mass function and the projected and two dimensional clustering of CMASS. We show that the clustering of CMASS, together with standard models of the galaxy-halo connection, robustly predicts a lensing signal that is 20-40% larger than observed. Detailed tests show that our results are robust to a variety of systematic effects. Lowering the value of $S_{\rm 8}=\sigma_{\rm 8} \sqrt{\Omega_{\rm m}/0.3}$ compared to Planck2015 reconciles the lensing with clustering. However, given the scale of our measurement ($r<10$ $h^{-1}$ Mpc), other effects may also be at play and need to be taken into consideration. We explore the impact of baryon physics, assembly bias, massive neutrinos, and modifications to general relativity on $\Delta\Sigma$ and show that several of these effects may be non-negligible given the precision of our measurement. Disentangling cosmological effects from the details of the galaxy-halo connection, the effects of baryons, and massive neutrinos, is the next challenge facing joint lensing and clustering analyses. This is especially true in the context of large galaxy samples from Baryon Acoustic Oscillation surveys with precise measurements but complex selection functions.Comment: 26 pages. Submitted to MNRAS. Comments welcom

ENIGMA-anxiety working group : Rationale for and organization of large-scale neuroimaging studies of anxiety disorders

Altres ajuts: Anxiety Disorders Research Network European College of Neuropsychopharmacology; Claude Leon Postdoctoral Fellowship; Deutsche Forschungsgemeinschaft (DFG, German Research Foundation, 44541416-TRR58); EU7th Frame Work Marie Curie Actions International Staff Exchange Scheme grant 'European and South African Research Network in Anxiety Disorders' (EUSARNAD); Geestkracht programme of the Netherlands Organization for Health Research and Development (ZonMw, 10-000-1002); Intramural Research Training Award (IRTA) program within the National Institute of Mental Health under the Intramural Research Program (NIMH-IRP, MH002781); National Institute of Mental Health under the Intramural Research Program (NIMH-IRP, ZIA-MH-002782); SA Medical Research Council; U.S. National Institutes of Health grants (P01 AG026572, P01 AG055367, P41 EB015922, R01 AG060610, R56 AG058854, RF1 AG051710, U54 EB020403).Anxiety disorders are highly prevalent and disabling but seem particularly tractable to investigation with translational neuroscience methodologies. Neuroimaging has informed our understanding of the neurobiology of anxiety disorders, but research has been limited by small sample sizes and low statistical power, as well as heterogenous imaging methodology. The ENIGMA-Anxiety Working Group has brought together researchers from around the world, in a harmonized and coordinated effort to address these challenges and generate more robust and reproducible findings. This paper elaborates on the concepts and methods informing the work of the working group to date, and describes the initial approach of the four subgroups studying generalized anxiety disorder, panic disorder, social anxiety disorder, and specific phobia. At present, the ENIGMA-Anxiety database contains information about more than 100 unique samples, from 16 countries and 59 institutes. Future directions include examining additional imaging modalities, integrating imaging and genetic data, and collaborating with other ENIGMA working groups. The ENIGMA consortium creates synergy at the intersection of global mental health and clinical neuroscience, and the ENIGMA-Anxiety Working Group extends the promise of this approach to neuroimaging research on anxiety disorders

New methods and models for diffusion-weighted magnetic resonance imaging of the kidney

Diffusionsgewichtete MR-Bilder sind ein wichtiger Bestandteil für die klinische Diagnostik verschiedener Pathologien, wie z.B. bei Schlaganfall oder Tumoren. Meistens wird ein mono-exponentielles Diffusionsmodell verwendet und über verschiedene Raumrichtungen gemittelt. Der Einfluss von Fluss auf das diffusionsgewichtete Signal und eine mögliche Richtungsabhängigkeit werden dabei vernachlässigt. Dabei machen Diffusionsmodelle, die mehr Eigenschaften des Signals abbilden, unter Umständen eine genauere Diagnostik möglich. Mit DTI wird die Richtungsabhängigkeit der Diffusion erfasst und bei IVIM wird der Beitrag von Fluss zum Signal berücksichtigt. Die Niere ist ein stark strukturiertes Organ und weist Anisotropie in der Diffusion auf. Außerdem ist die Niere ein sehr gut durchblutetes Organ. DTI und IVIM beschreiben also unabhängig voneinander zwei wichtige Aspekte des diffusionsgewichteten Signals in der Niere, ohne dass der Vorteil des jeweils anderen Modells Beachtung findet. In dieser Arbeit wurde das Modell IVOF zur umfassenden Beschreibung von Diffusionssignal vorgestellt, bei dem sowohl die Richtungsabhängigkeit der Diffusion, als auch das Signal der fließenden Spins und deren Richtungsabhängigkeit abgebildet wird. Die Vorteile von DTI und IVIM werden also in IVOF vereint und darüber hinaus auch die mögliche Anisotropie die Flusssignals berücksichtigt. Es konnte gezeigt werden, dass dieses Modell das diffusionsgewichtete Signal in der menschlichen Niere besser beschreibt als die herkömmlichen Modelle (DTI und IVIM) und auch besser als eine Kombination von DTI und IVIM, bei der ein isotroper Flussanteil des Signals angenommen wird. Es wurde weiterhin gezeigt, dass selbst wenn der Flussanteil im verwendeten Diffusionsmodell berücksichtigt wird, der tatsächlich gemessene Flussanteil in der Niere von der Art der Messung, d.h. Bewegungsempfindlichkeit des Gradientenschemas abhängt. Das bedeutet, dass der mikroskopische Fluss in der Niere nicht, wie häufig angenommen, komplett zeitlich inkohärent ist. Bei Vergleichen von IVIM Studien an der Niere ist es deshalb notwendig, die Bewegungsempfindlichkeit der jeweiligen Gradientenschemata zu berücksichtigen. Wie groß das absolute Verhältnis von kohärent zu inkohärent fließendem Signal ist, konnte nicht festgestellt werden. Ebenso wenig konnte die absolute Flussgeschwindigkeit bzw. die Art des Flusses (Laminare Strömung, Pfropfenströmung, oder andere) ermittelt werden. TSE hat sich als vielversprechendes, artefaktfreies Verfahren für die Aufnahme diffusionsgewichteter Bilder der Niere gezeigt. Im Vergleich mit dem Standardverfahren EPI wurden ähnliche Werte der Parameter von DTI und IVIM gefunden. Abweichungen zwischen EPI und TSE sind vor allem durch die Unschärfe der TSE Bilder aufgrund von T2-Zerfall zu erklären. Bis zur klinischen Anwendbarkeit diffusionsgewichteter TSE Bilder bzw. Parameterkarten sind noch einige Weiterentwicklungen der Methode nötig. Vor allem sind schärfere TSE Bilder erstrebenswert und es sollten mehrere Schichten in einer klinisch vertretbaren Zeitspanne aufgenommen werden, ohne dass dabei die zulässigen SAR Grenzwerte überschritten werden. Bei allen Untersuchungen in dieser Arbeit handelt es sich um Machbarkeitsstudien. Daher wurden alle Messungen nur an erwachsenen, gesunden Probanden durchgeführt, um zu zeigen, dass das jeweilige vorgeschlagene Modell zu den Daten passt bzw. dass die vorgeschlagene Methode prinzipiell funktioniert. Bei welchen Pathologien die hier vorgeschlagenen Methoden und Modelle einen diagnostischen Nutzen haben, muss in zukünftigen Studien erforscht werden. Außerdem wurden keine b- Werte zwischen 0 und 200 s/mm2 aufgenommen, bei denen fließende Spins noch signifikant zum Signal beitragen. Betrachtet man die Ergebnisse der Diffusionsbildgebung mit verschiedenen m1 in dieser Arbeit, dann ist neben dem b-Wert auch die Bewegungsempfindlichkeit m1 nötig, um das Signal in diesem Bereich korrekt zu beschreiben. Alles in allem sollte der Beitrag von Fluss zum diffusionsgewichteten MR-Signal in der Niere immer berücksichtigt werden. Die vielfältigen Einflüsse, die unterschiedliche Parameter auf das Signal von Mikrofluss haben, wurden in dieser Arbeit untersucht und präsentieren weiterhin ein spannendes Feld für kommende Studien. Diffusionsgewichtete TSE Sequenzen sind auch für die klinische Diagnostik eine potentielle Alternative zu Artefakt-anfälligen EPI Sequenzen. Bis dahin sollten jedoch die Bildschärfe und Abdeckung der diffusionsgewichteten TSE Sequenz weiter verbessert werden.Diffusion-weighted magnetic resonance (MR) imaging plays an important role in clinical diagnosis of various pathologies, such as stroke or tumors. Oftentimes a mono-exponential diffusion model is used and multiple diffusion directions are averaged. The potential influence of flow and a possible anisotropy of the signal are then neglected. Diffusion models that take these properties of the signal into account may allow a more accurate diagnosis. Diffusion tensor imaging (DTI) captures the directional dependence of diffusion, while the Intravoxel Incoherent Motion (IVIM) model accounts for the contribution of flow to the signal. Kidneys are strongly structured organs and exhibit anisotropic diffusion. Furthermore, kidneys are well perfused organs. DTI and IVIM both describe independently two important features of the diffusion-weighted signal in the kidneys, but neglect the advantages of the other model. The here presented work introduces a comprehensive diffusion model named Intravoxel Oriented Flow (IVOF). IVOF includes the possibilities of anisotropic diffusion and of flow. This way IVOF combines the advantages of DTI and IVIM and furthermore, accredits the possibility of anisotropic flow signal. It was shown that this model fits diffusion-weighted signal in the human kidney better than the standard diffusion models DTI and IVIM. IVOF even performs better than a combination of DTI and IVIM with an isotropic flow fraction. Moreover, it was shown that the actually measured flow fraction of the diffusionweighted signal in the kidneys depends on the imaging protocol, i.e. on the first gradient moment m1 of the diffusion gradient scheme. This means that the microscopic\ud flow in the kidneys is not completely temporally incoherent, in contrast to what is often assumed. Therefore, a comparison of renal IVIM studies needs to pay attention to the used gradient schemes and their respective m1. The absolute ratio of coherent to incoherent flow signal could not be determined in this work and is subject to future work. The flow profile (whether laminar flow, plug flow or other) and the mean flow velocity should also be investigated in further studies. Turbo-Spin-Echo (TSE) proofed to be an artifact-free and promising tool for acquiring diffusion-weighted images of the kidney. Similar DTI and IVIM parameters were found when images where acquired with TSE compared to Echo-Planar Imaging (EPI). Differences between parameters acquired with EPI and TSE may be explained by blurring in the TSE images, which is caused by T2 -decay. Before diffusion-weighted TSE images and parameter maps can be used for clinical diagnosis, some further improvements of the method are necessary. Sharper TSE images are preferable and multiple slices need to be acquired within a clinically reasonable scan time without exceeding specific absorption rate limits. All studies described in this work are feasibility studies. For this reason, all measurements were performed on healthy, adult volunteers to show that the proposed diffusion model fits the data or that the proposed acquisition method works in principle. The diagnostic value of the here proposed methods and models should be investigated in future studies. No b-values between 0 and 200 s/mm2 were acquired. In this range, the signal of flowing spins contributes significantly to the total signal. With regard to the results in this work concerning diffusion-weighted imaging with multiple first gradient moments it is likely that the b-value is not sufficient to describe the signal in this regime. The first gradient moment of the diffusion-weighting gradients may be crucial to describe the signal correctly. All in all it is important to always consider the contribution of flow to the diffusionweighted MR signal in the kidneys. Manifold influences of acquisition parameters to the signal of micro flow were presented in this work and provide an interesting field for further research. Diffusion-weighted TSE sequences are a potential alternative to artifact-prone EPI sequences. However, for clinical application of diffusion-weighted TSE blurring needs to be reduced and 3-dimensional coverage should be increased

Impact of massive parallelization on two-photon absorption micro- and nanofabrication

International audienceThe use of two-photon absorption (TPA) for polymerization, also known as 3D Lithography, Direct Laser Writing, or High-Precision 3D Printing is gaining increasing attraction in industrial fabrication of micro- and nanostructures. Mainly due to its vast freedom in design and high-resolution capabilities, TPA enables the fabrication of designs which are not feasible or far too complicated to be achieved with conventional fabrication methods. TPA is a scanning technology and fabrication in 3D requires axial overwritings. High industrial throughput fabrication can be achieved by intelligent fabrication strategies combined with an excellent material basis. Further boosting the throughput can be achieved by multispot exposure strategies. In this paper, massive parallelization is demonstrated which was realized by using a beam splitting diffractive optical element (DOE). Simultaneous fabrication using commercially available acrylate-based hybrid resin with 121 parallel focal spots arranged as 11 x 11 array is reported. Structures fabricated by a single laser beam and by 121 parallel beams are compared to each other with regard to shape and polymerization threshold. It was found that polymerization is strongly increased when parallel beams are used, especially for the central beams. As a result, polymerization threshold is lower in the center of the 11 x 11 array compared to the edges of the array. Furthermore, structures at the center of the 11 x 11 array are bigger compared to structures at the edges of the array when assigning equal intensity to all diffracted beams. These results are attributed to diffusion of photo initiators, quenchers, and radicals

Machine Learning-Based Identification of Target Groups for Thrombectomy in Acute Stroke

Whether endovascular thrombectomy (EVT) improves functional outcome in patients with large-vessel occlusion (LVO) stroke that do not comply with inclusion criteria of randomized controlled trials (RCTs) but that are considered for EVT in clinical practice is uncertain. We aimed to systematically identify patients with LVO stroke underrepresented in RCTs who might benefit from EVT. Following the premises that (i) patients without reperfusion after EVT represent a non-treated control group and (ii) the level of reperfusion affects outcome in patients with benefit from EVT but not in patients without treatment benefit, we systematically assessed the importance of reperfusion level on functional outcome prediction using machine learning in patients with LVO stroke treated with EVT in clinical practice (N=5235, German-Stroke-Registry) and in patients treated with EVT or best medical management from RCTs (N=1488, Virtual-International-Stroke-Trials-Archive). The importance of reperfusion level on outcome prediction in an RCT-like real-world cohort equaled the importance of EVT treatment allocation for outcome prediction in RCT data and was higher compared to an unselected real-world population. The importance of reperfusion level was magnified in patient groups underrepresented in RCTs, including patients with lower NIHSS scores (0-10), M2 occlusions, and lower ASPECTS (0-5 and 6-8). Reperfusion level was equally important in patients with vertebrobasilar as with anterior LVO stroke. The importance of reperfusion level for outcome prediction identifies patient target groups who likely benefit from EVT, including vertebrobasilar stroke patients and among patients underrepresented in RCT patients with low NIHSS scores, low ASPECTS, and M2 occlusions