Altered functional brain network connectivity and glutamate system function in transgenic mice expressing truncated Disrupted-in-Schizophrenia 1

Considerable evidence implicates DISC1 as a susceptibility gene for multiple psychiatric diseases. DISC1 has been intensively studied at the molecular, cellular and behavioral level, but its role in regulating brain connectivity and brain network function remains unknown. Here, we utilize a set of complementary approaches to assess the functional brain network abnormalities present in mice expressing a truncated Disc1 gene (Disc1tr Hemi mice). Disc1tr Hemi mice exhibited hypometabolism in the prefrontal cortex (PFC) and reticular thalamus along with a reorganization of functional brain network connectivity that included compromised hippocampal–PFC connectivity. Altered hippocampal–PFC connectivity in Disc1tr Hemi mice was confirmed by electrophysiological analysis, with Disc1tr Hemi mice showing a reduced probability of presynaptic neurotransmitter release in the monosynaptic glutamatergic hippocampal CA1–PFC projection. Glutamate system dysfunction in Disc1tr Hemi mice was further supported by the attenuated cerebral metabolic response to the NMDA receptor (NMDAR) antagonist ketamine and decreased hippocampal expression of NMDAR subunits 2A and 2B in these animals. These data show that the Disc1 truncation in Disc1tr Hemi mice induces a range of translationally relevant endophenotypes underpinned by glutamate system dysfunction and altered brain connectivity

A standardized framing for reporting protein identifications in mzIdentML 1.2

Inferring which protein species have been detected in bottom-up proteomics experiments has been a challenging problem for which solutions have been maturing over the past decade. While many inference approaches now function well in isolation, comparing and reconciling the results generated across different tools remains difficult. It presently stands as one of the greatest barriers in collaborative efforts such as the Human Proteome Project and public repositories such as the PRoteomics IDEntifications (PRIDE) database. Here we present a framework for reporting protein identifications that seeks to improve capabilities for comparing results generated by different inference tools. This framework standardizes the terminology for describing protein identification results, associated with the HUPO-Proteomics Standards Initiative (PSI) mzIdentML standard, while still allowing for differing methodologies to reach that final state. It is proposed that developers of software for reporting identification results will adopt this terminology in their outputs. While the new terminology does not require any changes to the core mzIdentML model, it represents a significant change in practice, and, as such, the rules will be released via a new version of the mzIdentML specification (version 1.2) so that consumers of files are able to determine whether the new guidelines have been adopted by export software

A gene regulatory network cooperatively controlled by Pdx1 and Sox9 governs lineage allocation of foregut progenitor cells

The generation of pancreas, liver, and intestine from a common pool of progenitors in the foregut endoderm requires the establishment of organ boundaries. How dorsal foregut progenitors activate pancreatic genes and evade the intestinal lineage choice remains unclear. Here, we identify Pdx1 and Sox9 as cooperative inducers of a gene regulatory network that distinguishes the pancreatic from the intestinal lineage. Genetic studies demonstrate dual and cooperative functions for Pdx1 and Sox9 in pancreatic lineage induction and repression of the intestinal lineage choice. Pdx1 and Sox9 bind to regulatory sequences near pancreatic and intestinal differentiation genes and jointly regulate their expression, revealing direct cooperative roles for Pdx1 and Sox9 in gene activation and repression. Our study identifies Pdx1 and Sox9 as important regulators of a transcription factor network that initiates pancreatic fate and sheds light on the gene regulatory circuitry that governs the development of distinct organs from multi-lineage-competent foregut progenitors

Porous silica-pillared MXenes with controllable interlayer distances for long-life Na-ion batteries

MXenes are a recently discovered class of two-dimensional materials that have shown great potential as electrodes in electrochemical energy storage devices. Despite their promise in this area, MXenes can still suffer limitations in the form of restricted ion accessibility between the closely spaced multistacked MXene layers, causing low capacities and poor cycle life. Pillaring, a strategy where a secondary species is inserted between layers, has been used to increase interlayer spacings in clays with great success, but has had limited application in MXenes. We report a new amine-assisted pillaring methodology that successfully intercalates silica-based pillars between Ti3C2 layers. Using this technique, the interlayer spacing can be controlled with the choice of amine and calcination temperature, up to a maximum of 3.2 nm, the largest interlayer spacing reported for an MXene. Another effect of the pillaring is a dramatic increase in surface area, achieving BET surface areas of 235 m2 g-1, a sixty-fold increase over the unpillared material and the highest reported for MXenes using an intercalation-based method. The intercalation mechanism was revealed by different characterisation techniques, allowing the surface chemistry to be optimised for the pillaring process. The porous MXene was tested for Na-ion battery applications, and showed superior capacity, rate capability and remarkable stability compared with non-pillared materials, retaining 98.5% capacity between the 50th and 100th cycles. These results demonstrate the applicability and promise of pillaring techniques applied to MXenes, providing a new approach to optimising their properties for a range of applications. Porous MXenes are very promising materials for a range of applications including energy storage, conversion, catalysis and gas separations

Resonant X ray photoelectron spectroscopy identification of atomic contributions to valence states

Valence electronic structure is crucial for understanding and predicting reactivity. Valence non resonant Xray photoelectron spectroscopy NRXPS provides a direct method for probing the overall valence electronic structure. However, it is often difficult to separate the varying contributions to NRXPS; for example, contributions of solutes in solvents or functional groups in complex molecules. In this work we show that valence resonant X ray photoelectron spectroscopy RXPS is a vital tool for obtaining atomic contributions to valence states. We combine RXPS with NRXPS and density functional theory calculations to demonstrate the validity of using RXPS to identify atomic contributions for a range of solutes both neutral and ionic and solvents both molecular solvents and ionic liquids . Furthermore, the one electron picture of RXPS holds for all of the closed shell molecules ions studied, although the situation for an open shell metal complex is more complicated. Factors needed to obtain a strong RXPS signal are investigated in order to predict the types of systems RXPS will work best for; a balance of element electronegativity and bonding type is found to be important. Additionally, the dependence of RXPS spectra on both varying solvation environment and varying local covalent bonding is probed. We find that RXPS is a promising fingerprint method for identifying species in solution, due to the spectral shape having a strong dependence on local covalency but a weak dependence on solvation environmen

Measurement of the Probability of Gluon Splitting into Charmed Quarks in Hadronic Z Decays

We have measured the probability, n(g->cc~), of a gluon splitting into a charm-quark pair using 1.7 million hadronic Z decays collected by the L3 detector. Two independent methods have been applied to events with a three-jet topology. One method relies on tagging charmed hadrons by identifying a lepton in the lowest energy jet. The other method uses a neural network based on global event shape parameters. Combining both methods, we measure n(g->cc~)= [2.45 +/- 0.29 +/- 0.53]%

Inclusive Jet Production in Two-Photon Collisions at LEP

Inclusive jet production, e+e- -> e+e- \ee$ jet X, is studied using 560/pb of data collected at LEP with the L3 detector at centre-of-mass energies between 189 and 209 GeV. The inclusive differential cross section is measured using a k_t jet algorithm as a function of the jet transverse momentum, pt, in the range 3<pt<50 GeV for a pseudorapidity, eta, in the range -1<eta<1. This cross section is well represented by a power law. For high pt, the measured cross section is significantly higher than the NLO QCD predictions, as already observed for inclusive charged and neutral pion production

GRB 011121: A massive star progenitor

Of the cosmological gamma-ray bursts, GRB 011121 has the lowest redshift, z = 0.36. More importantly, the multicolor excess in the afterglow detected in the Hubble Space Telescope (HST) light curves is compelling observational evidence of an underlying supernova. Here we present near-infrared and radio observations of the afterglow, and from our comprehensive afterglow modeling, we find evidence favoring a wind-fed circumburst medium. Lacking X-ray data, we are unable to conclusively measure the mass-loss rate, M, but obtain an estimate, M ∼ 2 × 10-7/νw3 M⊙yr-1, where νw3 is the speed of the wind from the progenitor in units of 103 km s-1. This M is similar to that inferred for the progenitor of the Type Ibc supernova SN 1998bw that has been associated with the peculiar burst GRB 980425. Our data, taken in conjunction with the HST results of Bloom et al., provide a consistent picture: the long-duration GRB 011121 had a massive star progenitor that exploded as a supernova at about the same time as the gamma-ray burst event. Finally, we note that the gamma-ray profile of GRB 011121 is similar to that of GRB 980425

Transformer-based biomarker prediction from colorectal cancer histology: A large-scale multicentric study.

Deep learning (DL) can accelerate the prediction of prognostic biomarkers from routine pathology slides in colorectal cancer (CRC). However, current approaches rely on convolutional neural networks (CNNs) and have mostly been validated on small patient cohorts. Here, we develop a new transformer-based pipeline for end-to-end biomarker prediction from pathology slides by combining a pre-trained transformer encoder with a transformer network for patch aggregation. Our transformer-based approach substantially improves the performance, generalizability, data efficiency, and interpretability as compared with current state-of-the-art algorithms. After training and evaluating on a large multicenter cohort of over 13,000 patients from 16 colorectal cancer cohorts, we achieve a sensitivity of 0.99 with a negative predictive value of over 0.99 for prediction of microsatellite instability (MSI) on surgical resection specimens. We demonstrate that resection specimen-only training reaches clinical-grade performance on endoscopic biopsy tissue, solving a long-standing diagnostic problem

A spitzer survey of deep drilling fields to be targeted by the Vera C. Rubin observatory legacy survey of space and time

The Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST) will observe several Deep Drilling Fields (DDFs) to a greater depth and with a more rapid cadence than the main survey. In this paper, we describe the 'DeepDrill' survey, which used the Spitzer Space Telescope Infrared Array Camera (IRAC) to observe three of the four currently defined DDFs in two bands, centred on 3.6 and 4.5 μm. These observations expand the area that was covered by an earlier set of observations in these three fields by the Spitzer Extragalactic Representative Volume Survey (SERVS). The combined DeepDrill and SERVS data cover the footprints of the LSST DDFs in the Extended Chandra Deep Field-South (ECDFS) field, the ELAIS-S1 field (ES1), and the XMM-Large-Scale Structure Survey field (XMM-LSS). The observations reach an approximate 5σ point-source depth of 2 μJy (corresponding to an AB magnitude of 23.1; sufficient to detect a 1011 M⊙ galaxy out to z ≈ 5) in each of the two bands over a total area of ≈ 29 deg2. The dual-band catalogues contain a total of 2.35 million sources