SUMOylation of DISC1: a potential role in neural progenitor proliferation in the developing cortex

DISC1 is a multifunctional, intracellular scaffold protein. At the cellular level, DISC1 plays a pivotal role in neural progenitor proliferation, migration, and synaptic maturation. Perturbation of the biological pathways involving DISC1 is known to lead to behavioral changes in rodents, which supports a clinical report of a Scottish pedigree in which the majority of family members with disruption of the DISC1 gene manifest depression, schizophrenia, and related mental conditions. The discrepancy between modest evidence in genetics and strong biological support for the role of DISC1 in mental conditions suggests a working hypothesis that regulation of DISC1 at the protein level, such as posttranslational modification, may play a role in the pathology of mental conditions. In this study, we report on the SUMOylation of DISC1. This posttranslational modification occurs on lysine residues where the small ubiquitin-related modifier (SUMO) and its homologs are conjugated to a large number of cellular proteins, which in turn regulates their subcellular distribution and protein stability. By using in silico, biochemical, and cell-biological approaches, we now demonstrate that human DISC1 is SUMOylated at one specific lysine 643 (K643). We also show that this residue is crucial for proper neural progenitor proliferation in the developing cortex

Rat Stem-Cell Factor Induces Splenocytes Capable Of Regenerating The Thymus

Cytokine regulation of prethymic T-lymphoid progenitor-cell proliferation and/or differentiation has not been well-defined, although much is known of cytokine regulation of hemopoietic stem- and progenitor-cell development. Here we use a recently identified hemopoietic growth factor, stem-cell factor (SCF) (a form of the c-kit ligand), and a transplant model of thymocyte regeneration to assess the effect of SCF on the in vivo generation of prethymic, thymocyte progenitor-cell activity. We show that recombinant rat SCF (rrSCF164 administered to weanling rats selectively induces an increase in thymocyte progenitor activity in the spleens of treated rats as compared to rats treated with vehicle, polyethylene glycol (PEG)-conjugated rat albumin, or recombinant human granulocyte colony-stimulating factor (rhG-CSF). These data demonstrate that administration of SCF in vivo affects extrathymic-origin thymocyte regenerating cells and may influence, directly or indirectly, early prethymic stages of T-cell lymphopoiesis in addition to its known effect on early stages of myelopoiesis and erythropoiesis

Grazing and No-Till Cropping Impacts on Nitrogen Retention in Dryland Agroecosystems

As the world\u27s population increases, marginal lands such as drylands are likely to become more important for food production. One proven strategy for improving crop production in drylands involves shifting from conventional tillage to no-till to increase water use efficiency, especially when this shift is coupled with more intensive crop rotations. Practices such as no-till that reduce soil disturbance and increase crop residues may promote C and N storage in soil organic matter, thus promoting N retention and reducing N losses. By sampling soils 15 yr after a N tracer addition, this study compared long-term soil N retention across several agricultural management strategies in current and converted shortgrass steppe ecosystems: grazed and ungrazed native grassland, occasionally mowed planted perennial grassland, and three cropping intensities of no-till dryland cropping. We also examined effects of the environmental variables site location and topography on N retention. Overall, the long-term soil N retention of \u3e18% in these managed semiarid ecosystems was high compared with published values for other cropped or grassland ecosystems. Cropping practices strongly influenced long-term N retention, with planted perennial grass systems retaining \u3e90% of N in soil compared with 30% for croplands. Grazing management, topography, and site location had smaller effects on long-term N retention. Estimated 15-yr N losses were low for intact and cropped systems. This work suggests that semiarid perennial grass ecosystems are highly N retentive and that increased intensity of semiarid land management can increase the amount of protein harvested without increasing N losses

Objective assessment of dietary patterns by use of metabolic phenotyping:A randomised, controlled, crossover trial

BACKGROUND: Accurate monitoring of changes in dietary patterns in response to food policy implementation is challenging. Metabolic profiling allows simultaneous measurement of hundreds of metabolites in urine, the concentrations of which can be affected by food intake. We hypothesised that metabolic profiles of urine samples developed under controlled feeding conditions reflect dietary intake and can be used to model and classify dietary patterns of free-living populations. METHODS: In this randomised, controlled, crossover trial, we recruited healthy volunteers (aged 21–65 years, BMI 20–35 kg/m(2)) from a database of a clinical research unit in the UK. We developed four dietary interventions with a stepwise variance in concordance with the WHO healthy eating guidelines that aim to prevent non-communicable diseases (increase fruits, vegetables, whole grains, and dietary fibre; decrease fats, sugars, and salt). Participants attended four inpatient stays (72 h each, separated by at least 5 days), during which they were given one dietary intervention. The order of diets was randomly assigned across study visits. Randomisation was done by an independent investigator, with the use of opaque, sealed, sequentially numbered envelopes that each contained one of the four dietary interventions in a random order. Participants and investigators were not masked from the dietary intervention, but investigators analysing the data were masked from the randomisation order. During each inpatient period, urine was collected daily over three timed periods: morning (0900–1300 h), afternoon (1300–1800 h), and evening and overnight (1800–0900 h); 24 h urine samples were obtained by pooling these samples. Urine samples were assessed by proton nuclear magnetic resonance ((1)H-NMR) spectroscopy, and diet-discriminatory metabolites were identified. We developed urinary metabolite models for each diet and identified the associated metabolic profiles, and then validated the models using data and samples from the INTERMAP UK cohort (n=225) and a healthy-eating Danish cohort (n=66). This study is registered with ISRCTN, number ISRCTN43087333. FINDINGS: Between Aug 13, 2013, and May 18, 2014, we contacted 300 people with a letter of invitation. 78 responded, of whom 26 were eligible and invited to attend a health screening. Of 20 eligible participants who were randomised, 19 completed all four 72 h study stays between Oct 2, 2013, and July 29, 2014, and consumed all the food provided. Analysis of (1)H-NMR spectroscopy data indicated that urinary metabolic profiles of the four diets were distinct. Significant stepwise differences in metabolite concentrations were seen between diets with the lowest and highest metabolic risks. Application of the derived metabolite models to the validation datasets confirmed the association between urinary metabolic and dietary profiles in the INTERMAP UK cohort (p<0·0001) and the Danish cohort (p<0·0001). INTERPRETATION: Urinary metabolite models developed in a highly controlled environment can classify groups of free-living people into consumers of diets associated with lower or higher non-communicable disease risk on the basis of multivariate metabolite patterns. This approach enables objective monitoring of dietary patterns in population settings and enhances the validity of dietary reporting. FUNDING: UK National Institute for Health Research and UK Medical Research Council

Database Evaluation for Muscle and Nerve Diseases - DEMAND: An academic neuromuscular coding system

Background: A database which documents the diagnosis of neuromuscular patients is useful for determining the types of patients referred to academic centers and for identifying participants for clinical trials and other studies. The ICD-9 or ICD-10 numeric systems are insufficiently detailed for this purpose. Objective: To develop a database for neuromuscular diagnoses Methods: We developed a detailed diagnostic coding system for neuromuscular diseases called DEMAND: Database Evaluation for Muscle and Nerve Diseases that has been adopted by neuromuscular clinics at University of Texas Health Science Center San Antonio (UTHSCSA), Ohio State University (OSU), University of Kansas Medical Center (KUMC), and University of Texas Southwestern (UTSW). At the initial visit, patients are assigned a diagnostic code which can be revised later if appropriate. Fields include patient’s name, date of birth, and diagnostic code. The neuromuscular database consisted of 457 codes. Each code has a prefix (MUS or PNS) followed by a three-digit number. Depending on whether muscle or nerve is primarily involved, there are eight broad groups: motor neuron disease (MUS codes 100-139); neuromuscular junction disorders (MUS 200-217); acquired and hereditary myopathies (MUS 300-600s); acquired and hereditary polyneuropathies (PNS 100-400); mononeuropathies (PNS 500s); plexopathies (PNS 600s); radiculopathies (PNS 700s); and mononeuritis multiplex (PNS 800s). Results: During a period of 10 years, 17,163 of patients were entered (1,752 at UTHSCSA, 1,840 at OSU, 3,699 at KUMC, 9,872 at UTSW). The number of patients in several broad categories are: 3,080 motor neuron disease; 1,575 neuromuscular junction disease; 1,851 muscular dystrophies; 633 inflammatory myopathies; 1,090 hereditary neuropathies; 1,001 immune-mediated polyneuropathies; 620 metabolic/toxic polyneuropathies; 535 mononeuropathies; 296 plexopathies; and 769 radiculopathies. Conclusion: A detailed diagnostic neuromuscular database can be utilized at multiple academic centers. The database should be simple without too many fields to complete, to ensure compliance during busy clinic operations. This database has been very useful in identifying groups of patients for retrospective, observational studies and for prospective treatment studies including trials for Amyotrophic Lateral Sclerosis (ALS), Muscular Dystrophies (MD), Myasthenia Gravis (MG), and retrospective studies of Primary Lateral Sclerosis (PLS), chronic inflammatory demyelinating neuropathy (CIDP), etc

Tracking Spending Among Commercially Insured Beneficiaries Using a Distributed Data Model

T imely, local data are important to policy-makers, providers, patients, payers, and employers working to slow the growth of healthcare spending, which is a major focus of federal, state, and local healthcare reform initiatives. Community-based multistakeholder coalitions have formed across the country in an effort to influence their local healthcare markets and reduce costs. More than 40 percent of people in the United States live in a community with a multistakeholder coalition aimed at improving health and healthcare, including collaboratives focused on improving the exchange of health information, accelerating engagement by key local opinion leaders and stakeholders, or promoting quality improvement. 1 All of these entities, however, lack the local data needed to determine if their efforts are making a difference. The factors contributing to rising healthcare spending differ across communities and depend on local context; understanding the drivers of local spending growth is complicated by the variety of inputs. Provider culture and supply, various market segments (outpatient, inpatient, long-term care), payer mix, regulation, and the competitiveness of hospital and physician markets all affect pricing, utilization, and ultimately, the total cost of care. Research has shown that the relative contribution of these factors varies across markets and that drivers of commercial spending are not necessarily the same as drivers of Medicare spending. Chernew et al found that commercial spending was not correlated with Medicare spending across hospital referral regions. ABSTRACT Objectives To explore the feasibility of using a distributed data model for ongoing reporting of local healthcare spending, specifically to investigate the contribution of utilization and pricing to geographic variation and trends in reimbursements for commercially insured beneficiaries younger than 65 years. Study Design Retrospective descriptive analysis. Methods Commercial claims were obtained for beneficiaries in 5 states for the years 2008 to 2010 using a distributed data model. Claims were aggregated to the hospital service area (HSA) level and healthcare utilization was quantified using a novel, National Quality Forum-endorsed measure that is independent of price and allows for the calculation of resource use across all services in standardized units. We examined trends in utilization, prices, and reimbursements over time. To examine geographic variation, we mapped resource use by HSA in the 3 states from which we had data from multiple insurers. We calculated the correlation between commercial and Medicare reimbursements and utilization. Medicare claims were obtained from the Dartmouth Atlas

Search for the standard model Higgs boson in the H to ZZ to 2l 2nu channel in pp collisions at sqrt(s) = 7 TeV

A search for the standard model Higgs boson in the H to ZZ to 2l 2nu decay channel, where l = e or mu, in pp collisions at a center-of-mass energy of 7 TeV is presented. The data were collected at the LHC, with the CMS detector, and correspond to an integrated luminosity of 4.6 inverse femtobarns. No significant excess is observed above the background expectation, and upper limits are set on the Higgs boson production cross section. The presence of the standard model Higgs boson with a mass in the 270-440 GeV range is excluded at 95% confidence level.Comment: Submitted to JHE

The Change Up Project : using social norming theory with young people to address domestic abuse and promote healthy relationships

This paper presents the findings of a secondary analysis of data collected during a pilot project, Change Up, which used a social norming approach (SNA) to address domestic violence and abuse (DVA) with young people aged 13–14. A SNA is based upon a well-articulated theory of behavior and evidence-based methodology for addressing social justice issues. This reflects a paradigm shift focusing upon strengths and positives, rather than pathologizing behaviours. Adopting a SNA, the Change Up project comprised a baseline survey followed by the intervention (workshop and peer-to-peer campaign), ending with a post-intervention survey. It was delivered in two high schools in a UK city between 2015 and 16. A secondary analysis of the survey data collected during the surveys and qualitative data collected at the end of each workshop was undertaken and this is reported here. Change Up data illustrates that most young people in the sample thought that DVA is unacceptable. There was, however, a gender difference in the norms held about the social acceptability of girls using physical violence against boys (and vice versa). The analysis of Change Up data indicates that a social norming approach to DVA programs aimed at young people can be successful in promoting attitude and behaviour change. It also highlights a continuing need for young people’s education about relationships and gender equality