Decrease in Central Venous Catheter Placement and Complications Due to Utilization of Ultrasound-Guided Peripheral Intravenous Catheters

Poster presented at: American College of Emergency Physicians (ACEP) conference. Introduction: -Up to 40% of ED visits include diagnostic blood tests and 26% result in administration of IV fluids necessitating successful peripheral intravenous (IV) catheter placement.1 -There is a subset of patients with difficult IV access (DIVA) in which traditional cannulation methods are unsuccessful resulting in central venous cannulation (CVC). -CVCs have a 5-15 percent complication rate2 and attributable costs per CVC related infection have been estimated at $34,508-$56,000.3 -Ultrasound-guided peripheral IV catheters (USGPIVs) provide a method of potentially decreasing the need for CVC placement, however due to poor durability of USGPIVs the actual reduction in CVCs is unclear. -This study set out to quantify the reduction in CVCs in patients with DIVA by utilization of USGPIVs. Paper will be be published in: American Journal of Emergency Medicin

A Quick Mind with Letters Can Be a Slow Mind with Natural Scenes: Individual Differences in Attentional Selection

Background Most people show a remarkable deficit in reporting the second of two targets (T2) when presented 200–500 ms after the first (T1), reflecting an ‘attentional blink’ (AB). However, there are large individual differences in the magnitude of the effect, with some people, referred to as ‘non-blinkers’, showing no such attentional restrictions. Methodology/Principal Findings Here we replicate these individual differences in a task requiring identification of two letters amongst digits, and show that the observed differences in T2 performance cannot be attributed to individual differences in T1 performance. In a second experiment, the generality of the non-blinkers' superior performance was tested using a task containing novel pictures rather than alphanumeric stimuli. A substantial AB was obtained in non-blinkers that was equivalent to that of ‘blinkers’. Conclusion/Significance The results suggest that non-blinkers employ an efficient target selection strategy that relies on well-learned alphabetic and numeric category sets.University of Groningen. Research School Behavioural and Cognitive Neuroscience

Facile synthesis and defect optimization of 2D-layered MoS2 on TiO2 heterostructure for industrial effluent, wastewater treatments

Supplementary information is available for this paper at https://doi.org/10.1038/s41598-020-78268-4.Copyright © The Author(s) 2020. Current research is paying much attention to heterojunction nanostructures. Owing to its versatile characteristics such as stimulating morphology, affluent surface-oxygen-vacancies and chemical compositions for enhanced generation of reactive oxygen species. Herein, we report the hydrothermally synthesized TiO2@MoS2 heterojunction nanostructure for the effective production of photoinduced charge carriers to enhance the photocatalytic capability. XRD analysis illustrated the crystalline size of CTAB capped TiO2, MoS2@TiO2 and L-Cysteine capped MoS2@TiO2 as 12.6, 11.7 and 10.2 nm, respectively. The bandgap of the samples analyzed by UV–Visible spectroscopy are 3.57, 3.66 and 3.94 eV. PL spectra of anatase phase titania shows the peaks present at and above 400 nm are ascribed to the defects in the crystalline structure in the form of oxygen vacancies. HRTEM reveals the existence of hexagonal layered MoS2 formation on the spherical shaped TiO2 nanoparticles at the interface. X-ray photoelectron spectroscopy recommends the chemical interactions between MoS2 and TiO2, specifically, oxygen vacancies. In addition, the electrochemical impedance spectroscopy studies observed that L-MT sample performed low charge transfer resistance (336.7 Ω cm2) that promotes the migration of electrons and interfacial charge separation. The photocatalytic performance is evaluated by quantifying the rate of Congo red dye degradation under visible light irradiation, and the decomposition efficiency was found to be 97%. The electron trapping recombination and plausible photocatalytic mechanism are also explored, and the reported work could be an excellent complement for industrial wastewater treatment.MHRD-SPARC; UKIERI; DST-SERB; RUSA 2.0; COMPETE agency, PT2020; EU-EC/MSCA-COFUND-2015-FP Nano TRAIN for Growth II; INSPIRE Faculty Scheme; SERB-EMRhttps://doi.org/10.1038/s41598-020-78268-

Complex machine-learning algorithms and multivariable logistic regression on par in the prediction of insufficient clinical response to methotrexate in rheumatoid arthritis

The goals of this study were to examine whether machine-learning algorithms outper-form multivariable logistic regression in the prediction of insufficient response to methotrexate (MTX); secondly, to examine which features are essential for correct prediction; and finally, to in-vestigate whether the best performing model specifically identifies insufficient responders to MTX (combination) therapy. The prediction of insufficient response (3-month Disease Activity Score 28-Erythrocyte-sedimentation rate (DAS28-ESR) > 3.2) was assessed using logistic regression, least absolute shrinkage and selection operator (LASSO), random forest, and extreme gradient boosting (XGBoost). The baseline features of 355 rheumatoid arthritis (RA) patients from the “treatment in the Rotterdam Early Arthritis CoHort” (tREACH) and the U-Act-Early trial were combined for analyses. The model performances were compared using area under the curve (AUC) of receiver operating characteristic (ROC) curves, 95% confidence intervals (95% CI), and sensitivity and specificity. Fi-nally, the best performing model following feature selection was tested on 101 RA patients starting tocilizumab (TCZ)-monotherapy. Logistic regression (AUC = 0.77 95% CI: 0.68–0.86) performed as well as LASSO (AUC = 0.76, 95% CI: 0.67–0.85), random forest (AUC = 0.71, 95% CI: 0.61 = 0.81), and XGBoost (AUC = 0.70, 95% CI: 0.61–0.81), yet logistic regression reached the highest sensitivity (81%). The most important features were baseline DAS28 (components). For all algorithms, models with six features performed similarly to those with 16. When applied to the TCZ-monotherapy group, logistic regression’s sensitivity significantly dropped from 83% to 69% (p = 0.03). In the current dataset, logistic regression performed equally well compared to machine-learning algorithms in the prediction of insufficient response to MTX. Models could be reduced to six features, which are more conducive for clinical implementation. Interestingly, the prediction model was specific to MTX (combination) therapy response

The sulfur pathway and diagnosis of sulfate depletion in grapevine

Sulfur is an essential nutrient to all plant species. Plants assimilate sulfur in a well-described pathway, which has been taken up by roots. Regulatory mech- anism has been the subject of many research papers. However, recent studies highlighted differences between crop plants and the model plant Arabidopsis thaliana. Our work focuses on the identification of genes involved in the sulfur metabolism in the Vitis vinifera genome, and their response to sulfur deficiency and other abiotic stress endured by grapevine in the field, namely water stress. Here, we describe the identification and brief characterization of the first assimilation enzymes involved in the sulfur pathway, the enzyme responsible for sulfur activa- tion, ATP sulfurylase (ATPS), and the two enzymes that reduce sulfate to sulfide, Adenosine 50-phosphosulate reductase (APR) and Sulfite reductase (SiR). A reduc- tion was observed in the number of ATPS and APR isoforms identified in V. vinifera genome when compared to A. thaliana or Glycine max genomes. Two ATPS isoforms were present in the Vitis genome, of which only ATPS1 transcript was detected in the tested tissues, and one APR isoform, suggesting an absence of redundancy in the role of both enzymes. ATPS1, APR and SiR transcript level was up-regulated in response to 2 days exposure to sulfur deficiency in V. vinifera cell cultures, which was completely reversed by the addition of GSH to the culture medium. Apparently, oxidative stress triggered GSH has a pivotal role in the regulation of ATPS1, APR and SiR transcription level, since their up-regulation was observed in mRNA from field grapevine berries under water stress, which is known to induce oxidative stress.info:eu-repo/semantics/publishedVersio

Prediction of Methotrexate Intolerance in Juvenile Idiopathic Arthritis: A prospective, observational cohort study

Background: Methotrexate (MTX) is an effective and safe drug in the treatment of juvenile idiopathic arthritis (JIA). Despite its safety, MTX-related gastrointestinal adverse effects before and after MTX administration, termed MTX intolerance, occur frequently, leading to non-compliance and potentially premature MTX termination. The aim of this study was to construct a risk model to predict MTX intolerance. Methods: In a prospective JIA cohort, clinical variables and single nucleotide polymorphisms were determined at MTX start. The Methotrexate Intolerance Severity Score was employed to measure MTX intolerance in the first year of treatment. MTX intolerance was most prevalent at 6 or 12months after MTX start, which was defined as the outcome for the prediction model. The model was developed in 152 patients using multivariable logistic regression analysis and subsequently internally validated using bootstrapping. Results: The prediction model included the following predictors: JIA category, antinuclear antibody, parent/patient assessment of pain, Juvenile Arthritis Disease Activity Score-27, thrombocytes, alanine aminotransferase and creatinine. The model classified 77.5% of patients correctly, and 66.7% of patients after internal validation by bootstrapping. The lowest predicted risk of MTX intolerance was 18.9% and the highest predicted risk was 85.9%. The prediction model was transformed into a risk score (range 0-17). At a cut-off of 6, sensitivity was 82.0%, specificity 56.1%, positive predictive value was 58.7% and negative predictive value 80.4%. Conclusions: This clinical prediction model showed moderate predictive power to detect MTX intolerance. To develop into a clinically usable tool, it should be validated in an independent cohort and updated with new predictors. Such an easy-to-use tool could then assist clinicians in identifying patients at risk to develop MTX intolerance, and in turn to monitor them closely and intervene timely in order to prevent the development of MTX intolerance

Development and validation of a prognostic multivariable model to predict insufficient clinical response to methotrexate in rheumatoid arthritis

Objective The objective was to predict insufficient response to 3 months methotrexate (MTX) in DMARD naïve rheumatoid arthritis patients. Methods A Multivariable logistic regression model of rheumatoid arthritis patients starting MTX was developed in a derivation cohort with 285 patients starting MTX in a clinical multicentre, stratified single-blinded trial, performed in seven secondary care clinics and a tertiary care clinic. The model was validated in a validation cohort with 102 patients starting MTX at a tertiary care clinic. Outcome was insufficient response (disease activity score (DAS)28 >3.2) after 3 months of MTX treatment. Clinical characteristics, lifestyle variables, genetic and metabolic biomarkers were determined at baseline in both cohorts. These variables were dichotomized and used to construct a multivariable prediction model with backward logistic regression analysis. Results The prediction model for insufficient response in the derivation cohort, included: DAS28>5.1, Health Assessment Questionnaire>0.6, current smoking, BMI>25 kg/m2, ABCB1 rs1045642 genotype, ABCC3 rs4793665 genotype, and erythrocyte-folate<750 nmol/L. In the derivation cohort, AUC of ROC curve was 0.80 (95%CI: 0.73–0.86), and 0.80 (95%CI: 0.69–0.91) in the validation cohort. Betas of the prediction model were transformed into total risk score (range 0–8). At cutoff of 4, probability for insufficient response was 44%. Sensitivity was 71%, specificity 72%, with positive and negative predictive value of 72% and 71%. Conclusions A prognostics prediction model for insufficient response to MTX in 2 prospective RA cohorts by combining genetic, metabolic, clinical and lifestyle variables was developed and validated. This model satisfactorily identified RA patients with high risk of insufficient response to MTX

Axisymmetric compressible boundary layer on a long thin moving cylinder

The steady laminar boundary layer flow on a thin and isothermal moving cylinder in a viscous compressible fluid at rest is studied in this paper. The fluid considered is a model fluid in which ϱ∼ T −1 and μ∼ T ω . The transformed non-similar boundary layer equations are solved numerically using a very efficient numerical method for some values of ω and wall enthalpy g ω parameters. The skin friction coefficient and Nusselt number are calculated for Pr=0.7 and some values of ω and g ωPeer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/41705/1/707_2005_Article_BF01291848.pd

Analysis of copy number variation in men with non-obstructive azoospermia

BACKGROUND: Recent findings demonstrate that single nucleotide variants can cause non-obstructive azoospermia (NOA). In contrast, copy number variants (CNVs) were only analysed in few studies in infertile men. Some have reported a higher prevalence of CNVs in infertile versus fertile men. OBJECTIVES: This study aimed to elucidate if CNVs are associated with NOA. MATERIALS AND METHODS: We performed array-based comparative genomic hybridization (aCGH) in 37 men with meiotic arrest, 194 men with Sertoli cell-only phenotype, and 21 control men. We filtered our data for deletions affecting genes and prioritized the affected genes according to a literature search. Prevalence of CNVs was compared between all groups. Exome data of 2,030 men were screened to detect further genetic variants in prioritized genes. Modelling was performed for the protein encoded by the novel candidate gene TEKT5 and we stained for TEKT5 in human testicular tissue. RESULTS: We determined the cause of infertility in two individuals with homozygous deletions of SYCE1 and in one individual with a heterozygous deletion of SYCE1 combined with a likely pathogenic missense variant on the second allele. We detected heterozygous deletions affecting MLH3, EIF2B2, SLX4, CLPP and TEKT5, in one subject each. CNVs were not detected more frequently in infertile men compared with controls. DISCUSSION: While SYCE1 and MLH3 encode known meiosis-specific proteins, much less is known about the proteins encoded by the other identified candidate genes, warranting further analyses. We were able to identify the cause of infertility in one out of the 231 infertile men by aCGH and in two men by using exome sequencing data. CONCLUSION: As aCGH and exome sequencing are both expensive methods, combining both in a clinical routine is not an effective strategy. Instead, using CNV calling from exome data has recently become more precise, potentially making aCGH dispensable