Polarization reversal in KTP single crystals with surface dielectric layer and at elevated temperatures

The research was made possible in part by Government of the Russian Federation (Act 211, Agreement 02.A03.21.0006) by RFBR (grant 16-02-00724), and by President of Russian Federation grant for young scientists (Contract 14.Y30.17.2837-MK). The equipment of the Ural Center for Shared Use “Modern nanotechnology” Ural Federal University was used

Searching for new genes associated with the familial hypercholesterolemia phenotype using whole-genome sequencing and machine learning

One of the most common congenital metabolic disorders is familial hypercholesterolemia. Familial hyper-cholesterolemia is a condition caused by a type of genetic defect leading to a decreased rate of removal of low-density lipoproteins from the bloodstream and a pronounced increase in the blood level of total cholesterol. This disease leads to the early development of cardiovascular diseases of atherosclerotic etiology. Familial hypercholesterolemia is a monogenic disease that is predominantly autosomal dominant. Rare pathogenic variants in the LDLR gene are present in 75–85 % of cases with an identified molecular genetic cause of the disease, and variants in other genes (APOB, PCSK9, LDLRAP1, ABCG5, ABCG8, and others) occur at a frequency of < 5 % in this group of patients. A negative result of genetic screening for pathogenic variants in genes of the low-density lipoprotein receptor and its ligands does not rule out a diagnosis of familial hypercholesterolemia. In 20–40 % of cases, molecular genetic testing fails to detect changes in the above genes. The aim of this work was to search for new genes associated with the familial hypercholesterolemia phenotype by modern high-tech methods of sequencing and machine learning. On the basis of a group of patients with familial hypercholesterolemia (enrolled according to the Dutch Lipid Clinic Network Criteria and including cases confirmed by molecular genetic analysis), decision trees were constructed, which made it possible to identify cases in the study population that require additional molecular genetic analysis. Five probands were identified as having the severest familial hypercholesterolemia without pathogenic variants in the studied genes and were analyzed by whole-genome sequencing on the HiSeq 1500 platform (Illumina). The whole-genome sequencing revealed rare variants in three out of five analyzed patients: a heterozygous variant (rs760657350) located in a splicing acceptor site in the PLD1 gene (c.2430-1G>A), a previously undescribed single-nucleotide deletion in the SIDT1 gene [c.2426del (p.Leu809CysfsTer2)], new missense variant c.10313C>G (p.Pro3438Arg) in the LRP1B gene, and single-nucleotide deletion variant rs753876598 [c.165del (p.Ser56AlafsTer11)] in the CETP gene. All these variants were found for the first time in patients with a clinical diagnosis of familial hypercholesterolemia. Variants were identified that may influence the formation of the familial hypercholesterolemia phenotype

Gas emissions, minerals, and tars associated with three coal fires, Powder River Basin, USA.

Ground-based surveys of three coal fires and airborne surveys of two of the fires were conducted near Sheridan, Wyoming. The fires occur in natural outcrops and in abandoned mines, all containing Paleocene-age subbituminous coals. Diffuse (carbon dioxide (CO(2)) only) and vent (CO(2), carbon monoxide (CO), methane, hydrogen sulfide (H(2)S), and elemental mercury) emission estimates were made for each of the fires. Additionally, gas samples were collected for volatile organic compound (VOC) analysis and showed a large range in variation between vents. The fires produce locally dangerous levels of CO, CO(2), H(2)S, and benzene, among other gases. At one fire in an abandoned coal mine, trends in gas and tar composition followed a change in topography. Total CO(2) fluxes for the fires from airborne, ground-based, and rate of fire advancement estimates ranged from 0.9 to 780mg/s/m(2) and are comparable to other coal fires worldwide. Samples of tar and coal-fire minerals collected from the mouth of vents provided insight into the behavior and formation of the coal fires

The United States of America and Scientific Research

To gauge the current commitment to scientific research in the United States of America (US), we compared federal research funding (FRF) with the US gross domestic product (GDP) and industry research spending during the past six decades. In order to address the recent globalization of scientific research, we also focused on four key indicators of research activities: research and development (R&D) funding, total science and engineering doctoral degrees, patents, and scientific publications. We compared these indicators across three major population and economic regions: the US, the European Union (EU) and the People's Republic of China (China) over the past decade. We discovered a number of interesting trends with direct relevance for science policy. The level of US FRF has varied between 0.2% and 0.6% of the GDP during the last six decades. Since the 1960s, the US FRF contribution has fallen from twice that of industrial research funding to roughly equal. Also, in the last two decades, the portion of the US government R&D spending devoted to research has increased. Although well below the US and the EU in overall funding, the current growth rate for R&D funding in China greatly exceeds that of both. Finally, the EU currently produces more science and engineering doctoral graduates and scientific publications than the US in absolute terms, but not per capita. This study's aim is to facilitate a serious discussion of key questions by the research community and federal policy makers. In particular, our results raise two questions with respect to: a) the increasing globalization of science: “What role is the US playing now, and what role will it play in the future of international science?”; and b) the ability to produce beneficial innovations for society: “How will the US continue to foster its strengths?

Tunable Mid-Infrared Laser Sources for Trace-Gas Analysis

We demonstrate advanced experimental approaches to photoacoustic gas detection with tunable mid-infrared (mid-IR) laser sources of different types. A gas analyzer for registration of various gas components based on a tunable narrow-linewidth optical parametric oscillator (OPO) was designed and investigated. Using this OPO, the possibility of measuring the trace concentration (~2÷3 ppm) of methane (CH4) in air was experimentally shown. The gas detection capability was enhanced by introducing injection seeding into the OPO. Another gas analyzer was based on a quantum cascade laser (tunable within the range ~7.6 ÷7.7 μm) and a resonant differential photoacoustic detector. Detection of the ultra-low concentration (~0.3 ppm) of methane in air was achieved (the standard dispersion was (1σ) ≈ (10–11) ppb with an integration time of 10 s). We compare the presented approaches and outline their further development. © 2021 Institute of Physics Publishing. All rights reserved.This work was partially supported by the Ministry of Science and Higher Education of the Russian Federation (grant FSUS-2020-0036). The Fan-out MgO: PPLN chip was prepared by A.A. and V.S with support from Russian Foundation for Basic Research (grant RFBR-mk-18-29-20077). The CH4 spectroscopic experiments were funded by RFBR, project number 19-32-60055

Expression profiling of hypothetical genes in Desulfovibrio vulgaris leads to improved functional annotation

Hypothetical (HyP) and conserved HyP genes account for >30% of sequenced bacterial genomes. For the sulfate-reducing bacterium Desulfovibrio vulgaris Hildenborough, 347 of the 3634 genes were annotated as conserved HyP (9.5%) along with 887 HyP genes (24.4%). Given the large fraction of the genome, it is plausible that some of these genes serve critical cellular roles. The study goals were to determine which genes were expressed and provide a more functionally based annotation. To accomplish this, expression profiles of 1234 HyP and conserved genes were used from transcriptomic datasets of 11 environmental stresses, complemented with shotgun LC–MS/MS and AMT tag proteomic data. Genes were divided into putatively polycistronic operons and those predicted to be monocistronic, then classified by basal expression levels and grouped according to changes in expression for one or multiple stresses. One thousand two hundred and twelve of these genes were transcribed with 786 producing detectable proteins. There was no evidence for expression of 17 predicted genes. Except for the latter, monocistronic gene annotation was expanded using the above criteria along with matching Clusters of Orthologous Groups. Polycistronic genes were annotated in the same manner with inferences from their proximity to more confidently annotated genes. Two targeted deletion mutants were used as test cases to determine the relevance of the inferred functional annotations

The potential of urinary metabolites for diagnosing multiple sclerosis

A definitive diagnostic test for multiple sclerosis (MS) does not exist; instead physicians use a combination of medical history, magnetic resonance imaging, and cerebrospinal fluid analysis (CSF). Significant effort has been employed to identify biomarkers from CSF to facilitate MS diagnosis; however none of the proposed biomarkers have been successful to date. Urine is a proven source of metabolite biomarkers and has the potential to be a rapid, non-invasive, inexpensive, and efficient diagnostic tool for various human diseases. Nevertheless, urinary metabolites have not been extensively explored as a source of biomarkers for MS. Instead, we demonstrate that urinary metabolites have significant promise for monitoring disease-progression, and response to treatment in MS patients. NMR analysis of urine permitted the identification of metabolites that differentiate experimental autoimmune encephalomyelitis (EAE)-mice (prototypic disease model for MS) from healthy and MS drug-treated EAE mice

Research activity and capability in the European reference network MetabERN

BACKGROUND: MetabERN is one of the 24 European Reference Networks created according to the European Union directive 2011/24/EU on patient's rights in cross border healthcare. MetabERN associates 69 centres in 18 countries, which provide care for patients with Hereditary Metabolic Diseases, and have the mission to reinforce research and provide training for health professionals in this field. MetabERN performed a survey in December 2017 with the aim to produce an overview documenting research activities and potentials within the network. As the centres are multidisciplinary, separated questionnaires were sent to the clinical, university and laboratory teams. Answers were received from 52 out of the 69 centres of the network, covering 16 countries. A descriptive analysis of the information collected is presented. RESULTS: The answers indicate a marked interest of the respondents for research, who expressed high motivation and commitment, and estimated that the conditions to do research in their institution were mostly satisfactory. They are active in research, which according to several indicators, is competitive and satisfies standards of excellence, as well as the education programs offered in the respondent's universities. Research in the centres is primarily performed in genetics, pathophysiology, and epidemiology, and focuses on issues related to diagnosis. Few respondents declared having activity in human and social sciences, including research on patient's quality of life, patient's awareness, or methods for social support. Infrastructures offering services for medical research were rarely known and used by respondents, including national and international biobanking platforms. In contrast, respondents often participate to patient registries, even beyond their specific field of interest. CONCLUSIONS: Taken as a whole, these results provide an encouraging picture of the research capacities and activities in the MetabERN network, which, with respect to the number and representativeness of the investigated centres, gives a comprehensive picture of research on Hereditary Metabolic Diseases in Europe, as well as the priorities for future actions. Marginal activity in human and social sciences points out the limited multidisciplinary constitution of the responding teams with possible consequences on their current capability to participate to patient's empowerment programs and efficiently collaborate with patient's advocacy groups