Application of advanced on-board processing concepts to future satellite communications systems

An initial definition of on-board processing requirements for an advanced satellite communications system to service domestic markets in the 1990's is presented. An exemplar system architecture with both RF on-board switching and demodulation/remodulation baseband processing was used to identify important issues related to system implementation, cost, and technology development

Detection of rifampicin and izoniazid resistance in Mycobacterium tuberculosis strains from Samara Region (Central Russia)

Recently high rates of tuberculosis incidence and prevalence are observed in civilian and prisons sectors in Russia. One of the main reasons for high morbidity levels and ineffectiveness of treatment is wide spreading of drug resistant Mycobacterium tuberculosis strains, but accurate and comprehensive information on levels of drug resistance among strains circulating in Central Russia is unavailable. Rifampicin and izoniazid resistance detection in TB isolates from Samara (Central Russia) civilian and prison TB hospitals and dispensaries in 2000–2002 by revealing mutations in rpoB, katG and inhA genes using Macroarray technique. Methods: A total of 342 M. tuberculosis isolates were tested using Macroarray method. It is based on multiplex amplification of rpoB, katG and inhA genes fragments (with three pairs of biotin labeled primers) following by dothybridization with normal and mutant oligonucleotide probes (fragments of rpoB, katG and inhA genes in which mutations occur) immobilized on nylon membrane strips. Mycobacterial DNA was extracted by heating of cell suspensions following by chloroform extraction. Streptavidin-alkaline phosphatase color development system was used for visualization of results

A Clinical Tool to Identify Candidates for Stress-First Myocardial Perfusion Imaging

Objectives: This study sought to develop a clinical model that identifies a lower-risk population for coronary artery disease that could benefit from stress-first myocardial perfusion imaging (MPI) protocols and that can be used at point of care to risk stratify patients. Background: There is an increasing interest in stress-first and stress-only imaging to reduce patient radiation exposure and improve patient workflow and experience. Methods: A secondary analysis was conducted on a single-center cohort of patients undergoing single-photon emission computed tomography (SPECT) and positron emission tomography (PET) studies. Normal MPI was defined by the absence of perfusion abnormalities and other ischemic markers and the presence of normal left ventricular wall motion and left ventricular ejection fraction. A model was derived using a cohort of 18,389 consecutive patients who underwent SPECT and was validated in a separate cohort of patients who underwent SPECT (n = 5,819), 1 internal cohort of patients who underwent PET (n=4,631), and 1 external PET cohort (n = 7,028). Results: Final models were made for men and women and consisted of 9 variables including age, smoking, hypertension, diabetes, dyslipidemia, typical angina, prior percutaneous coronary intervention, prior coronary artery bypass graft, and prior myocardial infarction. Patients with a score ≤1 were stratified as low risk. The model was robust with areas under the curve of 0.684 (95% confidence interval [CI]: 0.674 to 0.694) and 0.681 (95% CI: 0.666 to 0.696) in the derivation cohort, 0.745 (95% CI: 0.728 to 0.762) and 0.701 (95% CI: 0.673 to 0.728) in the SPECT validation cohort, 0.672 (95% CI: 0.649 to 0.696) and 0.686 (95% CI: 0.663 to 0.710) in the internal PET validation cohort, and 0.756 (95% CI: 0.740 to 0.772) and 0.737 (95% CI: 0.716 to 0.757) in the external PET validation cohort in men and women, respectively. Men and women who scored ≤1 had negative likelihood ratios of 0.48 and 0.52, respectively. Conclusions: A novel model, based on easily obtained clinical variables, is proposed to identify patients with low probability of having abnormal MPI results. This point-of-care tool may be used to identify a population that might qualify for stress-first MPI protocols

Dupilumab improves lung function in patients with uncontrolled, moderate-to-severe asthma

Background: Dupilumab, a fully human monoclonal antibody, blocks the shared receptor component for interleukin-4 and interleukin-13, key drivers of type 2 inflammation. In the phase 3 LIBERTY ASTHMA QUEST trial (NCT02414854) in patients with uncontrolled, moderate-to-severe asthma, add-on dupilumab 200 mg or 300 mg every 2 weeks reduced exacerbations and improved forced expiratory volume in 1 s (FEV1) and quality of life over 52 weeks. This analysis evaluates dupilimab's effect on lung function in the overall population, and subgroups with baseline elevated type 2 inflammatory biomarkers. Methods: Patients were randomised to 52 weeks of subcutaneous dupilumab 200 mg every 2 weeks, 300 mg every 2 weeks, or matched-volume placebos. Lung function outcomes were analysed in the overall population, in patients with ≥150 eosinophils·µL−1, ≥300 eosinophils·µL−1, ≥25 ppb fractional exhaled nitric oxide (FeNO), and both ≥150 eosinophils·µL−1 and ≥25 ppb FeNO, at baseline. Results: Dupilumab treatment (200 mg and 300 mg every 2 weeks) resulted in significant improvements versus placebo after 52 weeks in pre-bronchodilator FEV1 (0.20 and 0.13 L, respectively, versus placebo) and post-bronchodilator FEV1 (0.19 and 0.13 L, respectively), forced vital capacity (FVC) (0.20 and 0.14 L, respectively), forced expiratory flow (0.19 and 0.13 L·s−1, respectively) and pre-bronchodilator FEV1/FVC ratio (1.75% and 1.61%, respectively) in the overall population (p<0.001). Difference versus placebo in post-bronchodilator FEV1 slope of change (weeks 4–52) was significant (0.04 L·year−1; p<0.05). Greater improvements were achieved in patients with elevated baseline blood eosinophil and/or FeNO levels for most outcomes. Conclusions: Dupilumab improves lung function outcomes, including large and small airway measurements and fixed airway obstruction, in patients with uncontrolled, moderate-to-severe asthma; particularly in patients with elevated biomarkers of type 2 inflammation

Haploinsufficiency of the NOTCH1 Receptor as a Cause of Adams-Oliver Syndrome With Variable Cardiac Anomalies.

BACKGROUND: Adams-Oliver syndrome (AOS) is a rare disorder characterized by congenital limb defects and scalp cutis aplasia. In a proportion of cases, notable cardiac involvement is also apparent. Despite recent advances in the understanding of the genetic basis of AOS, for the majority of affected subjects, the underlying molecular defect remains unresolved. This study aimed to identify novel genetic determinants of AOS. METHODS AND RESULTS: Whole-exome sequencing was performed for 12 probands, each with a clinical diagnosis of AOS. Analyses led to the identification of novel heterozygous truncating NOTCH1 mutations (c.1649dupA and c.6049_6050delTC) in 2 kindreds in which AOS was segregating as an autosomal dominant trait. Screening a cohort of 52 unrelated AOS subjects, we detected 8 additional unique NOTCH1 mutations, including 3 de novo amino acid substitutions, all within the ligand-binding domain. Congenital heart anomalies were noted in 47% (8/17) of NOTCH1-positive probands and affected family members. In leukocyte-derived RNA from subjects harboring NOTCH1 extracellular domain mutations, we observed significant reduction of NOTCH1 expression, suggesting instability and degradation of mutant mRNA transcripts by the cellular machinery. Transient transfection of mutagenized NOTCH1 missense constructs also revealed significant reduction in gene expression. Mutant NOTCH1 expression was associated with downregulation of the Notch target genes HEY1 and HES1, indicating that NOTCH1-related AOS arises through dysregulation of the Notch signaling pathway. CONCLUSIONS: These findings highlight a key role for NOTCH1 across a range of developmental anomalies that include cardiac defects and implicate NOTCH1 haploinsufficiency as a likely molecular mechanism for this group of disorders

DOCK6 Mutations Are Responsible for a Distinct Autosomal-Recessive Variant of Adams-Oliver Syndrome Associated with Brain and Eye Anomalies

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Expression of phosphorylated eIF4E-binding protein 1, but not of eIF4E itself, predicts survival in male breast cancer

Background: Male breast cancer is rare and treatment is based on data from females. High expression/activity of eukaryotic initiation factor 4E (eIF4E) denotes a poor prognosis in female breast cancer, and the eIF4E pathway has been targeted therapeutically. eIF4E activity in female breast cancer is deregulated by eIF4E over-expression and by phosphorylation of its binding protein, 4E-BP1, which relieves inhibitory association between eIF4E and 4E-BP1. The relevance of the eIF4E pathway in male breast cancer is unknown. Methods: We have assessed expression levels of eIF4E, 4E-BP1, 4E-BP2 and phosphorylated 4E-BP1 (p4E-BP1) using immunohistochemistry in a large cohort of male breast cancers (n=337) and have examined correlations with prognostic factors and survival. Results: Neither eIF4E expression or estimated eIF4E activity were associated with prognosis. However, a highly significant correlation was found between p4E-BP1 expression and disease-free survival, linking any detectable p4E-BP1 with poor survival (univariate log rank p=0.001; multivariate HR 8.8, p=0.0001). Conclusions: Our data provide no support for direct therapeutic targeting of eIF4E in male breast cancer, unlike in females. However, as p4E-BP1 gives powerful prognostic insights that are unrelated to eIF4E function, p4E-BP1 may identify male breast cancers potentially suitable for therapies directed at the upstream kinase, mTOR

New Results from HAYSTAC's Phase II Operation with a Squeezed State Receiver

A search for dark matter axions with masses $>10 \mu eV/c^{2}$ has been performed using the HAYSTAC experiment's squeezed state receiver to achieve sub-quantum limited noise. This report includes details of the design and operation of the experiment previously used to search for axions in the mass ranges $16.96-17.12$ and $17.14-17.28 \mu eV/c^{2}$($4.100-4.140$GHz) and $4.145-4.178$GHz) as well as upgrades to facilitate an extended search at higher masses. These upgrades include improvements to the data acquisition routine which have reduced the effective dead time by a factor of 5, allowing for the new region to be scanned $\sim$1.6 times faster with comparable sensitivity. No statistically significant evidence of an axion signal is found in the range $18.44-18.71\mu eV/c^{2}$($4.459-4.523$GHz), leading to an aggregate upper limit exclusion at the $90\%$ level on the axion-photon coupling of $2.06\times g_{\gamma}^{KSVZ}$.Comment: 20 pages, 16 figure

Unsupervised learning to characterize patients with known coronary artery disease undergoing myocardial perfusion imaging

PURPOSE Patients with known coronary artery disease (CAD) comprise a heterogenous population with varied clinical and imaging characteristics. Unsupervised machine learning can identify new risk phenotypes in an unbiased fashion. We use cluster analysis to risk-stratify patients with known CAD undergoing single-photon emission computed tomography (SPECT) myocardial perfusion imaging (MPI). METHODS From 37,298 patients in the REFINE SPECT registry, we identified 9221 patients with known coronary artery disease. Unsupervised machine learning was performed using clinical (23), acquisition (17), and image analysis (24) parameters from 4774 patients (internal cohort) and validated with 4447 patients (external cohort). Risk stratification for all-cause mortality was compared to stress total perfusion deficit (< 5%, 5-10%, ≥10%). RESULTS Three clusters were identified, with patients in Cluster 3 having a higher body mass index, more diabetes mellitus and hypertension, and less likely to be male, have dyslipidemia, or undergo exercise stress imaging (p < 0.001 for all). In the external cohort, during median follow-up of 2.6 [0.14, 3.3] years, all-cause mortality occurred in 312 patients (7%). Cluster analysis provided better risk stratification for all-cause mortality (Cluster 3: hazard ratio (HR) 5.9, 95% confidence interval (CI) 4.0, 8.6, p < 0.001; Cluster 2: HR 3.3, 95% CI 2.5, 4.5, p < 0.001; Cluster 1, reference) compared to stress total perfusion deficit (≥10%: HR 1.9, 95% CI 1.5, 2.5 p < 0.001; < 5%: reference). CONCLUSIONS Our unsupervised cluster analysis in patients with known CAD undergoing SPECT MPI identified three distinct phenotypic clusters and predicted all-cause mortality better than ischemia alone