miR-34a-/- mice are susceptible to diet-induced obesity

Objective: MicroRNA (miR)−34a regulates inflammatory pathways, and increased transcripts have been observed in serum and subcutaneous adipose of subjects who have obesity and type 2 diabetes. Therefore, the role of miR-34a in adipose tissue inflammation and lipid metabolism in murine diet-induced obesity was investigated. Methods: Wild-type (WT) and miR-34a−/− mice were fed chow or high-fat diet (HFD) for 24 weeks. WT and miR-34a−/− bone marrow-derived macrophages were cultured in vitro with macrophage colony-stimulating factor (M-CSF). Brown and white preadipocytes were cultured from the stromal vascular fraction (SVF) of intrascapular brown and epididymal white adipose tissue (eWAT), with rosiglitazone. Results: HFD-fed miR-34a−/− mice were significantly heavier with a greater increase in eWAT weight than WT. miR-34a−/− eWAT had a smaller adipocyte area, which significantly increased with HFD. miR-34a−/− eWAT showed basal increases in Cd36, Hmgcr, Lxrα, Pgc1α, and Fasn. miR-34a−/− intrascapular brown adipose tissue had basal reductions in c/ebpα and c/ebpβ, with in vitro miR-34a−/− white adipocytes showing increased lipid content. An F4/80high macrophage population was present in HFD miR-34a−/− eWAT, with increased IL-10 transcripts and serum IL-5 protein. Finally, miR-34a−/− bone marrow-derived macrophages showed an ablated CXCL1 response to tumor necrosis factor-α. Conclusions: These findings suggest a multifactorial role of miR-34a in controlling susceptibility to obesity, by regulating inflammatory and metabolic pathways

Quantitative analysis of epithelial cells in urine from men with and without urethritis: implications for studying epithelial: pathogen interactions in vivo

<p>Abstract</p> <p>Background</p> <p>Epithelial cells in first catch urine (FCU) specimens from 87 men with and without urethritis were quantified. Epithelial cells were broadly categorised into transitional and squamous populations using morphological characteristics and immunostaining with anti-pan leukocyte and anti-cytokeratin monoclonal antibodies.</p> <p>Findings</p> <p>The majority (77/87 = 89%) of samples contained both transitional (76/87 = 87%; range 1 × 10⁴– 6 × 10⁵, median 6 × 10⁴) and squamous (57/87 = 66%; range 1 × 10⁴– 8 × 10⁵, median 2 × 10⁴) epithelial cells. The number of transitional cells correlated with the number of squamous cells (Spearman's rho = 0.697 p < 0.001). Squamous, but not transitional, cell numbers correlated with leukocyte numbers (Spearman's rho = 0.216 p = 0.045 and rho = 0.171 and p = 0.113, respectively). However there was no significant difference in epithelial cell numbers between men with and without urethritis. Nevertheless, some men with urethritis had relatively high numbers of transitional cells in their FCU. Transitional cells were morphologically heterogeneous and appeared to display complex cytokeratin phenotypes.</p> <p>Conclusion</p> <p>Further studies are required to explore the complexity of epithelial cell populations in urine. These would provide novel opportunities for studying cellular interactions of <it>C. trachomatis </it>in male urethral infections, about which little is currently known.</p

A Charter to Fundamentally Change the Role of Oral Corticosteroids in the Management of Asthma

Asthma affects 339 million people worldwide, with an estimated 5–10% experiencing severe asthma. In emergency settings, oral corticosteroids (OCS) can be lifesaving, but acute and long-term treatment can produce clinically important adverse outcomes and increase the risk of mortality. Therefore, global guidelines recommend limiting the use of OCS. Despite the risks, research indicates that 40–60% of people with severe asthma are receiving or have received long-term OCS treatment. Although often perceived as a low-cost option, long-term OCS use can result in significant health impairments and costs owing to adverse outcomes and increased utilization of healthcare resources. Alternative treatment methods, such as biologics, may produce cost-saving benefits with a better safety profile. A comprehensive and concerted effort is necessary to tackle the continued reliance on OCS. Accordingly, a threshold for OCS use should be established to help identify patients at risk of OCS-related adverse outcomes. Receiving a total dose of more than 500 mg per year should trigger a review and specialist referral. Changes to national and local policies, following examples from other chronic diseases, will be crucial to achieving this goal. Globally, multiple barriers to change still exist, but specific steps have been identified to help clinicians reduce reliance on OCS. Implementing these changes will result in positive health outcomes for patients and social and economic benefits for societies.</p

An Improved Global Model for Air-Sea Exchange of Mercury: High Concentrations over the North Atlantic

We develop an improved treatment of the surface ocean in the GEOS-Chem global 3-D biogeochemical model for mercury (Hg). We replace the globally uniform subsurface ocean Hg concentrations used in the original model with basin-specific values based on measurements. Updated chemical mechanisms for Hg0/HgII redox reactions in the surface ocean include both photochemical and biological processes, and we improved the parametrization of particle-associated Hg scavenging. Modeled aqueous Hg concentrations are consistent with limited surface water observations. Results more accurately reproduce high-observed MBL concentrations over the North Atlantic (NA) and the associated seasonal trends. High seasonal evasion in the NA is driven by inputs from Hg enriched subsurface waters through entrainment and Ekman pumping. Globally, subsurface waters account for 40% of Hg inputs to the ocean mixed layer, and 60% is from atmospheric deposition. Although globally the ocean is a net sink for 3.8 Mmol Hg y−1, the NA is a net source to the atmosphere, potentially due to enrichment of subsurface waters with legacy Hg from historical anthropogenic sources.Engineering and Applied Science

Mathematical description of bacterial traveling pulses

The Keller-Segel system has been widely proposed as a model for bacterial waves driven by chemotactic processes. Current experiments on {\em E. coli} have shown precise structure of traveling pulses. We present here an alternative mathematical description of traveling pulses at a macroscopic scale. This modeling task is complemented with numerical simulations in accordance with the experimental observations. Our model is derived from an accurate kinetic description of the mesoscopic run-and-tumble process performed by bacteria. This model can account for recent experimental observations with {\em E. coli}. Qualitative agreements include the asymmetry of the pulse and transition in the collective behaviour (clustered motion versus dispersion). In addition we can capture quantitatively the main characteristics of the pulse such as the speed and the relative size of tails. This work opens several experimental and theoretical perspectives. Coefficients at the macroscopic level are derived from considerations at the cellular scale. For instance the stiffness of the signal integration process turns out to have a strong effect on collective motion. Furthermore the bottom-up scaling allows to perform preliminary mathematical analysis and write efficient numerical schemes. This model is intended as a predictive tool for the investigation of bacterial collective motion

Comparison of quality control methods for automated diffusion tensor imaging analysis pipelines

© 2019 Haddad et al. The processing of brain diffusion tensor imaging (DTI) data for large cohort studies requires fully automatic pipelines to perform quality control (QC) and artifact/outlier removal procedures on the raw DTI data prior to calculation of diffusion parameters. In this study, three automatic DTI processing pipelines, each complying with the general ENIGMA framework, were designed by uniquely combining multiple image processing software tools. Different QC procedures based on the RESTORE algorithm, the DTIPrep protocol, and a combination of both methods were compared using simulated ground truth and artifact containing DTI datasets modeling eddy current induced distortions, various levels of motion artifacts, and thermal noise. Variability was also examined in 20 DTI datasets acquired in subjects with vascular cognitive impairment (VCI) from the multi-site Ontario Neurodegenerative Disease Research Initiative (ONDRI). The mean fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD), and radial diffusivity (RD) were calculated in global brain grey matter (GM) and white matter (WM) regions. For the simulated DTI datasets, the measure used to evaluate the performance of the pipelines was the normalized difference between the mean DTI metrics measured in GM and WM regions and the corresponding ground truth DTI value. The performance of the proposed pipelines was very similar, particularly in FA measurements. However, the pipeline based on the RESTORE algorithm was the most accurate when analyzing the artifact containing DTI datasets. The pipeline that combined the DTIPrep protocol and the RESTORE algorithm produced the lowest standard deviation in FA measurements in normal appearing WM across subjects. We concluded that this pipeline was the most robust and is preferred for automated analysis of multisite brain DTI data

Validating a prediction tool to determine the risk of nosocomial multidrug-resistant Gram-negative bacilli infection in critically ill patients: A retrospective case–control study

BACKGROUND:The Singapore GSDCS score was developed to enable clinicians predict the risk of nosocomial multidrug-resistant Gram-negative bacilli (RGNB) infection in critically ill patients. We aimed to validate this score in a UK setting. METHOD:A retrospective case-control study was conducted including patients who stayed for more than 24h in intensive care units (ICUs) across two tertiary National Health Service hospitals in London, UK (April 2011-April 2016). Cases with RGNB and controls with sensitive Gram-negative bacilli (SGNB) infection were identified. RESULTS:The derived GSDCS score was calculated from when there was a step change in antimicrobial therapy in response to clinical suspicion of infection as follows: prior Gram-negative organism, Surgery, Dialysis with end-stage renal disease, prior Carbapenem use and intensive care Stay of more than 5 days. A total of 110 patients with RGNB infection (cases) were matched 1:1 to 110 geotemporally chosen patients with SGNB infection (controls). The discriminatory ability of the prediction tool by receiver operating characteristic curve analysis in our validation cohort was 0.75 (95% confidence interval 0.65-0.81), which is comparable with the area under the curve of the derivation cohort (0.77). The GSDCS score differentiated between low- (0-1.3), medium- (1.4-2.3) and high-risk (2.4-4.3) patients for RGNB infection (P<0.001) in a UK setting. CONCLUSION:A simple bedside clinical prediction tool may be used to identify and differentiate patients at low, medium and high risk of RGNB infection prior to initiation of prompt empirical antimicrobial therapy in the intensive care setting

Genetic Mapping and Exome Sequencing Identify Variants Associated with Five Novel Diseases

The Clinic for Special Children (CSC) has integrated biochemical and molecular methods into a rural pediatric practice serving Old Order Amish and Mennonite (Plain) children. Among the Plain people, we have used single nucleotide polymorphism (SNP) microarrays to genetically map recessive disorders to large autozygous haplotype blocks (mean = 4.4 Mb) that contain many genes (mean = 79). For some, uninformative mapping or large gene lists preclude disease-gene identification by Sanger sequencing. Seven such conditions were selected for exome sequencing at the Broad Institute; all had been previously mapped at the CSC using low density SNP microarrays coupled with autozygosity and linkage analyses. Using between 1 and 5 patient samples per disorder, we identified sequence variants in the known disease-causing genes SLC6A3 and FLVCR1, and present evidence to strongly support the pathogenicity of variants identified in TUBGCP6, BRAT1, SNIP1, CRADD, and HARS. Our results reveal the power of coupling new genotyping technologies to population-specific genetic knowledge and robust clinical data