Regulation of Neuron Survival through an Intersectin-Phosphoinositide 3'-Kinase C2 -AKT Pathway

While endocytosis attenuates signals from plasma membrane receptors, recent studies suggest that endocytosis also serves as a platform for the compartmentalized activation of cellular signaling pathways. Intersectin (ITSN) is a multidomain scaffolding protein that regulates endocytosis and has the potential to regulate various biochemical pathways through its multiple, modular domains. To address the biological importance of ITSN in regulating cellular signaling pathways versus in endocytosis, we have stably silenced ITSN expression in neuronal cells by using short hairpin RNAs. Decreasing ITSN expression dramatically increased apoptosis in both neuroblastoma cells and primary cortical neurons. Surprisingly, the loss of ITSN did not lead to major defects in the endocytic pathway. Yeast two-hybrid analysis identified class II phosphoinositide 3′-kinase C2β (PI3K-C2β) as an ITSN binding protein, suggesting that ITSN may regulate a PI3K-C2β-AKT survival pathway. ITSN associated with PI3K-C2β on a subset of endomembrane vesicles and enhanced both basal and growth factor-stimulated PI3K-C2β activity, resulting in AKT activation. The use of pharmacological inhibitors, dominant negatives, and rescue experiments revealed that PI3K-C2β and AKT were epistatic to ITSN. This study represents the first demonstration that ITSN, independent of its role in endocytosis, regulates a critical cellular signaling pathway necessary for cell survival

Measurement of double beta decay of 100Mo to excited states in the NEMO 3 experiment

The double beta decay of 100Mo to the 0^+_1 and 2^+_1 excited states of 100Ru is studied using the NEMO 3 data. After the analysis of 8024 h of data the half-life for the two-neutrino double beta decay of 100Mo to the excited 0^+_1 state is measured to be T^(2nu)_1/2 = [5.7^{+1.3}_{-0.9}(stat)+/-0.8(syst)]x 10^20 y. The signal-to-background ratio is equal to 3. Information about energy and angular distributions of emitted electrons is also obtained. No evidence for neutrinoless double beta decay to the excited 0^+_1 state has been found. The corresponding half-life limit is T^(0nu)_1/2(0^+ --> 0^+_1) > 8.9 x 10^22 y (at 90% C.L.). The search for the double beta decay to the 2^+_1 excited state has allowed the determination of limits on the half-life for the two neutrino mode T^(2nu)_1/2(0^+ --> 2^+_1) > 1.1 x 10^21 y (at 90% C.L.) and for the neutrinoless mode T^(0nu)_1/2(0^+ --> 2^+_1) > 1.6 x 10^23 y (at 90% C.L.).Comment: 23 pages, 7 figures, 4 tables, submitted to Nucl. Phy

Monitoring HSVtk suicide gene therapy: the role of [18F]FHPG membrane transport

Favourable pharmacokinetics of the prodrug are essential for successful HSVtk/ganciclovir (GCV) suicide gene therapy. [F-18] FHPG PET might be a suitable technique to assess the pharmacokinetics of the prodrug GCV noninvasively, provided that [F-18] FHPG mimics the behaviour of GCV. Since membrane transport is an important aspect of the pharmacokinetics of the prodrug, we investigated the cellular uptake mechanism of [F-18] FHPG in an HSVtk expressing C6 rat glioma cell line and in tumour- bearing rats. The nucleoside transport inhibitors dipyridamol, NBMPR and 2- chloroadenosine did not significantly affect the [F-18] FHPG uptake in vitro. Thymidine and uridine significantly decreased [F-18] FHPG uptake by 84 and 58%, respectively, but an enzyme assay revealed that this decline was due to inhibition of the HSVtk enzyme rather than membrane transport. Nucleobase transport inhibitors, thymine and adenine, caused a 58 and 55% decline in tracer uptake, respectively. In vivo, the ratio of [F-18] FHPG uptake in C6tk and C6 tumours decreased from 3.070.5 to 1.070.2 after infusion of adenine. Thus, in our tumour model, [F-18] FHPG transport exclusively occurred via purine nucleobase transport. In this respect, FHPG does not resemble GCV, which is predominantly taken up via the nucleoside transporter, but rather acyclovir, which is also taken up via the purine nucleobase carrier

Health Industries in the Twentieth Century. Introduction

This article is the introduction to the special issue' Health Industries in the Twentieth Century'. It offers a broad literature review of scholarly works about the history of health and medicine, and stresses the opportunities for business historians to tackle the field of healthcare

Spatiotemporal scaling of North American continental interior wetlands: implications for shorebird conservation

Within interior North America, erratic weather patterns and heterogeneous wetland complexes cause wide spatio-temporal variation in the resources available to migrating shorebirds. Identifying the pattern-generating components of landscape-level resources and the scales at which shorebirds respond to these patterns will better facilitate conservation efforts for these species. We constructed descriptive models that identified weather variables associated with creating the spatio-temporal patterns of shorebird habitat in ten landscapes in north-central Oklahoma. We developed a metric capable of measuring the dynamic composition and configuration of shorebird habitat in the region and used field data to empirically estimate the spatial scale at which shorebirds respond to the amount and configuration of habitat. Precipitation, temperature, solar radiation and wind speed best explained the incidence of wetland habitat, but relationships varied among wetland types. Shorebird occurrence patterns were best explained by habitat density estimates at a 1.5 km scale. This model correctly classified 86 % of shorebird observations. At this scale, when habitat density was low, shorebirds occurred in 5 % of surveyed habitat patches but occurrence reached 60 % when habitat density was high. Our results suggest scale dependence in the habitat-use patterns of migratory shorebirds. We discuss potential implications of our results and how integrating this information into conservation efforts may improve conservation strategies and management practices

Artificial intelligence for classification of temporal lobe epilepsy with ROI-level MRI data: A worldwide ENIGMA-Epilepsy study

Artificial intelligence has recently gained popularity across different medical fields to aid in the detection of diseases based on pathology samples or medical imaging findings. Brain magnetic resonance imaging (MRI) is a key assessment tool for patients with temporal lobe epilepsy (TLE). The role of machine learning and artificial intelligence to increase detection of brain abnormalities in TLE remains inconclusive. We used support vector machine (SV) and deep learning (DL) models based on region of interest (ROI-based) structural (n = 336) and diffusion (n = 863) brain MRI data from patients with TLE with (“lesional”) and without (“non-lesional”) radiographic features suggestive of underlying hippocampal sclerosis from the multinational (multi-center) ENIGMA-Epilepsy consortium. Our data showed that models to identify TLE performed better or similar (68–75%) compared to models to lateralize the side of TLE (56–73%, except structural-based) based on diffusion data with the opposite pattern seen for structural data (67–75% to diagnose vs. 83% to lateralize). In other aspects, structural and diffusion-based models showed similar classification accuracies. Our classification models for patients with hippocampal sclerosis were more accurate (68–76%) than models that stratified non-lesional patients (53–62%). Overall, SV and DL models performed similarly with several instances in which SV mildly outperformed DL. We discuss the relative performance of these models with ROI-level data and the implications for future applications of machine learning and artificial intelligence in epilepsy care

Structural brain abnormalities in the common epilepsies assessed in a worldwide ENIGMA study

Progressive functional decline in the epilepsies is largely unexplained. We formed the ENIGMA-Epilepsy consortium to understand factors that influence brain measures in epilepsy, pooling data from 24 research centres in 14 countries across Europe, North and South America, Asia, and Australia. Structural brain measures were extracted from MRI brain scans across 2149 individuals with epilepsy, divided into four epilepsy subgroups including idiopathic generalized epilepsies (n =367), mesial temporal lobe epilepsies with hippocampal sclerosis (MTLE; left, n = 415; right, n = 339), and all other epilepsies in aggregate (n = 1026), and compared to 1727 matched healthy controls. We ranked brain structures in order of greatest differences between patients and controls, by meta-Analysing effect sizes across 16 subcortical and 68 cortical brain regions. We also tested effects of duration of disease, age at onset, and age-by-diagnosis interactions on structural measures. We observed widespread patterns of altered subcortical volume and reduced cortical grey matter thickness. Compared to controls, all epilepsy groups showed lower volume in the right thalamus (Cohen's d = \ue2 '0.24 to \ue2 '0.73; P < 1.49 7 10 \ue2 '4), and lower thickness in the precentral gyri bilaterally (d = \ue2 '0.34 to \ue2 '0.52; P < 4.31 7 10 \ue2 '6). Both MTLE subgroups showed profound volume reduction in the ipsilateral hippocampus (d = \ue2 '1.73 to \ue2 '1.91, P < 1.4 7 10 \ue2 '19), and lower thickness in extrahippocampal cortical regions, including the precentral and paracentral gyri, compared to controls (d = \ue2 '0.36 to \ue2 '0.52; P < 1.49 7 10 \ue2 '4). Thickness differences of the ipsilateral temporopolar, parahippocampal, entorhinal, and fusiform gyri, contralateral pars triangularis, and bilateral precuneus, superior frontal and caudal middle frontal gyri were observed in left, but not right, MTLE (d = \ue2 '0.29 to \ue2 '0.54; P < 1.49 7 10 \ue2 '4). Contrastingly, thickness differences of the ipsilateral pars opercularis, and contralateral transverse temporal gyrus, were observed in right, but not left, MTLE (d = \ue2 '0.27 to \ue2 '0.51; P < 1.49 7 10 \ue2 '4). Lower subcortical volume and cortical thickness associated with a longer duration of epilepsy in the all-epilepsies, all-other-epilepsies, and right MTLE groups (beta, b < \ue2 '0.0018; P < 1.49 7 10 \ue2 '4). In the largest neuroimaging study of epilepsy to date, we provide information on the common epilepsies that could not be realistically acquired in any other way. Our study provides a robust ranking of brain measures that can be further targeted for study in genetic and neuropathological studies. This worldwide initiative identifies patterns of shared grey matter reduction across epilepsy syndromes, and distinctive abnormalities between epilepsy syndromes, which inform our understanding of epilepsy as a network disorder, and indicate that certain epilepsy syndromes involve more widespread structural compromise than previously assumed

Investigation of epimer formation in amide coupling reactions: an experiment for advanced undergraduate students

An experiment is described to investigate how the choice of coupling agent and reaction conditions affects the ratio of epimers formed in the sensitive amide-coupling reaction between N-Boc or N-benzoyl (R)-phenylglycine and (S)-valine methyl ester. The experiment, which is suitable for third-year undergraduates, is designed to teach about important synthetic methods and reaction mechanisms, and to develop skills in designing experiments, data analysis, and team work

Two PI 3-Kinases and One PI 3-Phosphatase Together Establish the Cyclic Waves of Phagosomal PtdIns(3)P Critical for the Degradation of Apoptotic Cells

Cyclic oscillations in the level of phosphatidylinositol 3-phosphate in phagosomes, regulated by two phosphoinositide kinases and one phosphatase, are critical for phagosome maturation and degradation of apoptotic cells

A large, curated, open-source stroke neuroimaging dataset to improve lesion segmentation algorithms.

Accurate lesion segmentation is critical in stroke rehabilitation research for the quantification of lesion burden and accurate image processing. Current automated lesion segmentation methods for T1-weighted (T1w) MRIs, commonly used in stroke research, lack accuracy and reliability. Manual segmentation remains the gold standard, but it is time-consuming, subjective, and requires neuroanatomical expertise. We previously released an open-source dataset of stroke T1w MRIs and manually-segmented lesion masks (ATLAS v1.2, N = 304) to encourage the development of better algorithms. However, many methods developed with ATLAS v1.2 report low accuracy, are not publicly accessible or are improperly validated, limiting their utility to the field. Here we present ATLAS v2.0 (N = 1271), a larger dataset of T1w MRIs and manually segmented lesion masks that includes training (n = 655), test (hidden masks, n = 300), and generalizability (hidden MRIs and masks, n = 316) datasets. Algorithm development using this larger sample should lead to more robust solutions; the hidden datasets allow for unbiased performance evaluation via segmentation challenges. We anticipate that ATLAS v2.0 will lead to improved algorithms, facilitating large-scale stroke research