Reconstructing the three-dimensional GABAergic microcircuit of the striatum

A system's wiring constrains its dynamics, yet modelling of neural structures often overlooks the specific networks formed by their neurons. We developed an approach for constructing anatomically realistic networks and reconstructed the GABAergic microcircuit formed by the medium spiny neurons (MSNs) and fast-spiking interneurons (FSIs) of the adult rat striatum. We grew dendrite and axon models for these neurons and extracted probabilities for the presence of these neurites as a function of distance from the soma. From these, we found the probabilities of intersection between the neurites of two neurons given their inter-somatic distance, and used these to construct three-dimensional striatal networks. The MSN dendrite models predicted that half of all dendritic spines are within 100 mu m of the soma. The constructed networks predict distributions of gap junctions between FSI dendrites, synaptic contacts between MSNs, and synaptic inputs from FSIs to MSNs that are consistent with current estimates. The models predict that to achieve this, FSIs should be at most 1% of the striatal population. They also show that the striatum is sparsely connected: FSI-MSN and MSN-MSN contacts respectively form 7% and 1.7% of all possible connections. The models predict two striking network properties: the dominant GABAergic input to a MSN arises from neurons with somas at the edge of its dendritic field; and FSIs are interconnected on two different spatial scales: locally by gap junctions and distally by synapses. We show that both properties influence striatal dynamics: the most potent inhibition of a MSN arises from a region of striatum at the edge of its dendritic field; and the combination of local gap junction and distal synaptic networks between FSIs sets a robust input-output regime for the MSN population. Our models thus intimately link striatal micro-anatomy to its dynamics, providing a biologically grounded platform for further study

Study of the decays B->D_s1(2536)+ anti-D(*)

We report a study of the decays B -> D_s1(2536)+ anti-D(*), where anti-D(*) is anti-D0, D- or D*-, using a sample of 657 x 10^6 B anti-B pairs collected at the Upsilon(4S) resonance with the Belle detector at the KEKB asymmetric-energy e+e- collider. The branching fractions of the decays B+ -> D_s1(2536)+ anti-D0, B0 -> D_s1(2536)+ D- and B0 -> D_s1(2536)+ D*- multiplied by that of D_s1(2536)+ -> (D*0K+ + D*+K0) are found to be (3.97+-0.85+-0.56) x 10^-4, (2.75+-0.62+-0.36) x 10^-4 and (5.01+-1.21+-0.70) x 10^-4, respectively.Comment: 6 pages, 2 figues, submitted to PRD (RC

Cooperation of Sumoylated Chromosomal Proteins in rDNA Maintenance

SUMO is a posttranslational modifier that can modulate protein activities, interactions, and localizations. As the GFP-Smt3p fusion protein has a preference for subnucleolar localization, especially when deconjugation is impaired, the nucleolar role of SUMO can be the key to its biological functions. Using conditional triple SUMO E3 mutants, we show that defects in sumoylation impair rDNA maintenance, i.e., the rDNA segregation is defective and the rDNA copy number decreases in these mutants. Upon characterization of sumoylated proteins involved in rDNA maintenance, we established that Top1p and Top2p, which are sumoylated by Siz1p/Siz2p, most likely collaborate with substrates of Mms21p to maintain rDNA integrity. Cohesin and condensin subunits, which both play important roles in rDNA stability and structures, are potential substrates of Mms21, as their sumoylation depends on Mms21p, but not Siz1p and Siz2p. In addition, binding of cohesin and condensin to rDNA is altered in the mms21-CH E3-deficient mutant

A risk prediction model for the assessment and triage of women with hypertensive disorders of pregnancy in low-resourced settings: the miniPIERS (Pre-eclampsia Integrated Estimate of RiSk) multi-country prospective cohort study.

BACKGROUND: Pre-eclampsia/eclampsia are leading causes of maternal mortality and morbidity, particularly in low- and middle- income countries (LMICs). We developed the miniPIERS risk prediction model to provide a simple, evidence-based tool to identify pregnant women in LMICs at increased risk of death or major hypertensive-related complications. METHODS AND FINDINGS: From 1 July 2008 to 31 March 2012, in five LMICs, data were collected prospectively on 2,081 women with any hypertensive disorder of pregnancy admitted to a participating centre. Candidate predictors collected within 24 hours of admission were entered into a step-wise backward elimination logistic regression model to predict a composite adverse maternal outcome within 48 hours of admission. Model internal validation was accomplished by bootstrapping and external validation was completed using data from 1,300 women in the Pre-eclampsia Integrated Estimate of RiSk (fullPIERS) dataset. Predictive performance was assessed for calibration, discrimination, and stratification capacity. The final miniPIERS model included: parity (nulliparous versus multiparous); gestational age on admission; headache/visual disturbances; chest pain/dyspnoea; vaginal bleeding with abdominal pain; systolic blood pressure; and dipstick proteinuria. The miniPIERS model was well-calibrated and had an area under the receiver operating characteristic curve (AUC ROC) of 0.768 (95% CI 0.735-0.801) with an average optimism of 0.037. External validation AUC ROC was 0.713 (95% CI 0.658-0.768). A predicted probability ≥25% to define a positive test classified women with 85.5% accuracy. Limitations of this study include the composite outcome and the broad inclusion criteria of any hypertensive disorder of pregnancy. This broad approach was used to optimize model generalizability. CONCLUSIONS: The miniPIERS model shows reasonable ability to identify women at increased risk of adverse maternal outcomes associated with the hypertensive disorders of pregnancy. It could be used in LMICs to identify women who would benefit most from interventions such as magnesium sulphate, antihypertensives, or transportation to a higher level of care

Variation in 'fast-track' referrals for suspected cancer by patient characteristic and cancer diagnosis: evidence from 670 000 patients with cancers of 35 different sites.

BACKGROUND: In England, 'fast-track' (also known as 'two-week wait') general practitioner referrals for suspected cancer in symptomatic patients are used to shorten diagnostic intervals and are supported by clinical guidelines. However, the use of the fast-track pathway may vary for different patient groups. METHODS: We examined data from 669 220 patients with 35 cancers diagnosed in 2006-2010 following either fast-track or 'routine' primary-to-secondary care referrals using 'Routes to Diagnosis' data. We estimated the proportion of fast-track referrals by sociodemographic characteristic and cancer site and used logistic regression to estimate respective crude and adjusted odds ratios. We additionally explored whether sociodemographic associations varied by cancer. RESULTS: There were large variations in the odds of fast-track referral by cancer (P<0.001). Patients with testicular and breast cancer were most likely to have been diagnosed after a fast-track referral (adjusted odds ratios 2.73 and 2.35, respectively, using rectal cancer as reference); whereas patients with brain cancer and leukaemias least likely (adjusted odds ratios 0.05 and 0.09, respectively, for brain cancer and acute myeloid leukaemia). There were sex, age and deprivation differences in the odds of fast-track referral (P<0.013) that varied in their size and direction for patients with different cancers (P<0.001). For example, fast-track referrals were least likely in younger women with endometrial cancer and in older men with testicular cancer. CONCLUSIONS: Fast-track referrals are less likely for cancers characterised by nonspecific presenting symptoms and patients belonging to low cancer incidence demographic groups. Interventions beyond clinical guidelines for 'alarm' symptoms are needed to improve diagnostic timeliness

Synergistic effect of quinary molten salts and Ruthenium catalyst for high-power-density Lithium-carbon dioxide cell

With a recent increase in interest in metal-gas batteries, the lithium-carbon dioxide cell has attracted considerable attention because of its extraordinary carbon dioxide-capture ability during the discharge process and its potential application as a power source for Mars exploration. However, owing to the stable lithium carbonate discharge product, the cell enables operation only at low current densities, which significantly limits the application of lithium-carbon dioxide batteries and effective carbon dioxide-capture cells. Here, we investigate a high-performance lithium-carbon dioxide cell using a quinary molten salt electrolyte and ruthenium nanoparticles on the carbon cathode. The nitrate-based molten salt electrolyte allows us to observe the enhanced carbon dioxide-capture rate and the reduced discharge-charge over-potential gap with that of conventional lithium-carbon dioxide cells. Furthermore, owing to the ruthernium catalyst, the cell sustains its performance over more than 300 cycles at a current density of 10.0Ag(-1) and exhibits a peak power density of 33.4mWcm(-2). Lithium-carbon dioxide cells are challenging due to the sluggish electron transfer in the Lithium carbonate in aprotic electrolyte. Here, the authors report synergistic effect of molten salt electrolyte and Ruthenium catalyst to enhance the electrochemical performance of Lithium-carbon dioxide batterie

CRISPR-Cas9 screens in human cells and primary neurons identify modifiers of C9ORF72 dipeptide-repeat-protein toxicity.

Hexanucleotide-repeat expansions in the C9ORF72 gene are the most common cause of amyotrophic lateral sclerosis and frontotemporal dementia (c9ALS/FTD). The nucleotide-repeat expansions are translated into dipeptide-repeat (DPR) proteins, which are aggregation prone and may contribute to neurodegeneration. We used the CRISPR-Cas9 system to perform genome-wide gene-knockout screens for suppressors and enhancers of C9ORF72 DPR toxicity in human cells. We validated hits by performing secondary CRISPR-Cas9 screens in primary mouse neurons. We uncovered potent modifiers of DPR toxicity whose gene products function in nucleocytoplasmic transport, the endoplasmic reticulum (ER), proteasome, RNA-processing pathways, and chromatin modification. One modifier, TMX2, modulated the ER-stress signature elicited by C9ORF72 DPRs in neurons and improved survival of human induced motor neurons from patients with C9ORF72 ALS. Together, our results demonstrate the promise of CRISPR-Cas9 screens in defining mechanisms of neurodegenerative diseases

Micro-CT imaging reveals<i> Mekk3 </i>heterozygosity prevents cerebral cavernous malformations in <i>Ccm2</i>-deficient mice

Mutations in CCM1 (aka KRIT1), CCM2, or CCM3 (aka PDCD10) gene cause cerebral cavernous malformation in humans. Mouse models of CCM disease have been established by deleting Ccm genes in postnatal animals. These mouse models provide invaluable tools to investigate molecular mechanism and therapeutic approaches for CCM disease. However, the full value of these animal models is limited by the lack of an accurate and quantitative method to assess lesion burden and progression. In the present study we have established a refined and detailed contrast enhanced X-ray micro-CT method to measure CCM lesion burden in mouse brains. As this study utilized a voxel dimension of 9.5μm (leading to a minimum feature size of approximately 25μm), it is therefore sufficient to measure CCM lesion volume and number globally and accurately, and provide high-resolution 3-D mapping of CCM lesions in mouse brains. Using this method, we found loss of Ccm1 or Ccm2 in neonatal endothelium confers CCM lesions in the mouse hindbrain with similar total volume and number. This quantitative approach also demonstrated a rescue of CCM lesions with simultaneous deletion of one allele of Mekk3. This method would enhance the value of the established mouse models to study the molecular basis and potential therapies for CCM and other cerebrovascular diseases

Influenza Research Database: An integrated bioinformatics resource for influenza virus research

The Influenza Research Database (IRD) is a U.S. National Institute of Allergy and Infectious Diseases (NIAID)-sponsored Bioinformatics Resource Center dedicated to providing bioinformatics support for influenza virus research. IRD facilitates the research and development of vaccines, diagnostics and therapeutics against influenza virus by providing a comprehensive collection of influenza-related data integrated from various sources, a growing suite of analysis and visualization tools for data mining and hypothesis generation, personal workbench spaces for data storage and sharing, and active user community support. Here, we describe the recent improvements in IRD including the use of cloud and high performance computing resources, analysis and visualization of user-provided sequence data with associated metadata, predictions of novel variant proteins, annotations of phenotype-associated sequence markers and their predicted phenotypic effects, hemagglutinin (HA) clade classifications, an automated tool for HA subtype numbering conversion, linkouts to disease event data and the addition of host factor and antiviral drug components. All data and tools are freely available without restriction from the IRD website at https://www.fludb.org.National Institutes of Health/National Institute for Allergy and Infectious Diseases [HHSN272201400028C]. Funding for open access charge: J. Craig Venter Institute