Assessment of Cardiorespiratory Interactions During Spontaneous and Controlled Breathing: Non-linear Model-free Analysis

In this work, nonlinear model-free methods for bivariate time series analysis have been applied to study cardiorespiratory interactions. Specifically, entropy-based (i.e. Transfer Entropy and Cross Entropy) and Convergent Cross Mapping asymmetric coupling measures have been computed on heart rate and breathing time series extracted from electrocardiographic (ECG) and respiratory signals acquired on 19 young healthy subjects during an experimental protocol including spontaneous and controlled breathing conditions. Results evidence a bidirectional nature of cardiorespiratory interactions, and highlight clear similarities and differences among the three considered measures

Trefoil factor 2 (Tff2) deficiency in murine digestive tract influences the immune system

Background & Aims: The gastrointestinal trefoil factor family (TFF1, TFF2, TFF3) peptides are considered to play an important role in maintaining the integrity of the mucosa. The physiological role of TFF2 in the protection of the GI tract was investigated in TFF2 deficiency. Methods: TFF2-/- mice were generated and differential expression of various genes was assessed by using a mouse expression microarray, quantitative real time PCR, Northern blots or immunohistochemistry. Results: On an mRNA level we found 128 differentially expressed genes. We observed modulation of a number of crucial genes involved in innate and adaptive immunity in the TFF2-/- mice. Expression of proteasomal subunits genes (LMP2, LMP7 and PSMB5) involved in the MHC class I presentation pathway were modulated indicating the formation of immunoproteasomes improving antigen presentation. Expression of one subunit of a transporter (TAP1) responsible for importing degraded antigens into ER was increased, similarly to the BAG2 gene that modulates chaperone activity in ER helping proper loading on MHC class I molecules. Several mouse defensin (cryptdin) genes coding important intestinal microbicidal proteins were up-regulated as a consequence of TFF2 deficiency. Normally moderate expression of TFF3 was highly increased in stomach

Literature on applied machine learning in metagenomic classification: A scoping review

Applied machine learning in bioinformatics is growing as computer science slowly invades all research spheres. With the arrival of modern next-generation DNA sequencing algorithms, metagenomics is becoming an increasingly interesting research field as it finds countless practical applications exploiting the vast amounts of generated data. This study aims to scope the scientific literature in the field of metagenomic classification in the time interval 2008–2019 and provide an evolutionary timeline of data processing and machine learning in this field. This study follows the scoping review methodology and PRISMA guidelines to identify and process the available literature. Natural Language Processing (NLP) is deployed to ensure efficient and exhaustive search of the literary corpus of three large digital libraries: IEEE, PubMed, and Springer. The search is based on keywords and properties looked up using the digital libraries’ search engines. The scoping review results reveal an increasing number of research papers related to metagenomic classification over the past decade. The research is mainly focused on metagenomic classifiers, identifying scope specific metrics for model evaluation, data set sanitization, and dimensionality reduction. Out of all of these subproblems, data preprocessing is the least researched with considerable potential for improvement

Large-scale quantum-emitter arrays in atomically thin semiconductors.

Quantum light emitters have been observed in atomically thin layers of transition metal dichalcogenides. However, they are found at random locations within the host material and usually in low densities, hindering experiments aiming to investigate this new class of emitters. Here, we create deterministic arrays of hundreds of quantum emitters in tungsten diselenide and tungsten disulphide monolayers, emitting across a range of wavelengths in the visible spectrum (610-680 nm and 740-820 nm), with a greater spectral stability than their randomly occurring counterparts. This is achieved by depositing monolayers onto silica substrates nanopatterned with arrays of 150-nm-diameter pillars ranging from 60 to 190 nm in height. The nanopillars create localized deformations in the material resulting in the quantum confinement of excitons. Our method may enable the placement of emitters in photonic structures such as optical waveguides in a scalable way, where precise and accurate positioning is paramount

Improved understanding of dynamic water and mass budgets of high‐alpine karst systems obtained from studying a well‐defined catchment area

Large areas of Europe, especially in the Alps, are covered by carbonate rocks and in many alpine regions, karst springs are important sources for drinking water supply. Because of their high variability and heterogeneity, the understanding of the hydrogeological functioning of karst aquifers is of particular importance for their protection and utilisation. Climate change and heavy rainfall events are major challenges in managing alpine karst aquifers which possess an enormous potential for future drinking water supply. In this study, we present research from a high‐alpine karst system in the UNESCO Biosphere Reserve Großes Walsertal in Austria, which has a clearly defined catchment and is drained by only one spring system. Results show that (a) the investigated system is a highly dynamic karst aquifer with distinct reactions to rainfall events in discharge and electrical conductivity; (b) the estimated transient atmospheric CO2 sink is about 270 t/a; (c) the calculated carbonate rock denudation rate is between 23 and 47 mm/1000a and (d) the rainfall‐discharge behaviour and the internal flow dynamics can be successfully simulated using the modelling package KarstMod. The modelling results indicate the relevance of matrix storage in determining the discharge behaviour of the spring, particularly during low‐flow periods. This research and the consequent results can contribute and initiate a better understanding and management of alpine karst aquifers considering climate change with more heavy rainfall events and also longer dry periods.The investigated karst system contributes to the transient atmospheric CO2 sink with about 270 t/a. Carbonate denudation rates vary between 23 and 47 mm/1000a. Rainfall‐discharge modelling results indicate the importance of matrix storage particularly during low‐flow periods. imageBundesministerium für Bildung und Forschung http://dx.doi.org/10.13039/501100002347FP7 People: Marie‐Curie Actions http://dx.doi.org/10.13039/10001126

A robust, scanning quantum system for nanoscale sensing and imaging

Controllable atomic-scale quantum systems hold great potential as sensitive tools for nanoscale imaging and metrology. Possible applications range from nanoscale electric and magnetic field sensing to single photon microscopy, quantum information processing, and bioimaging. At the heart of such schemes is the ability to scan and accurately position a robust sensor within a few nanometers of a sample of interest, while preserving the sensor's quantum coherence and readout fidelity. These combined requirements remain a challenge for all existing approaches that rely on direct grafting of individual solid state quantum systems or single molecules onto scanning-probe tips. Here, we demonstrate the fabrication and room temperature operation of a robust and isolated atomic-scale quantum sensor for scanning probe microscopy. Specifically, we employ a high-purity, single-crystalline diamond nanopillar probe containing a single Nitrogen-Vacancy (NV) color center. We illustrate the versatility and performance of our scanning NV sensor by conducting quantitative nanoscale magnetic field imaging and near-field single-photon fluorescence quenching microscopy. In both cases, we obtain imaging resolution in the range of 20 nm and sensitivity unprecedented in scanning quantum probe microscopy

Loss of gastrokine-2 drives premalignant gastric inflammation and tumor progression

Chronic mucosal inflammation is associated with a greater risk of gastric cancer (GC) and, therefore, requires tight control by suppressive counter mechanisms. Gastrokine-2 (GKN2) belongs to a family of secreted proteins expressed within normal gastric mucosal cells. GKN2 expression is frequently lost during GC progression, suggesting an inhibitory role; however, a causal link remains unsubstantiated. Here, we developed Gkn2 knockout and transgenic overexpressing mice to investigate the functional impact of GKN2 loss in GC pathogenesis. In mouse models of GC, decreased GKN2 expression correlated with gastric pathology that paralleled human GC progression. At baseline, Gkn2 knockout mice exhibited defective gastric epithelial differentiation but not malignant progression. Conversely, Gkn2 knockout in the IL-11/STAT3-dependent gp130[superscript F/F] GC model caused tumorigenesis of the proximal stomach. Additionally, gastric immunopathology was accelerated in Helicobacter pylori–infected Gkn2 knockout mice and was associated with augmented T helper cell type 1 (Th1) but not Th17 immunity. Heightened Th1 responses in Gkn2 knockout mice were linked to deregulated mucosal innate immunity and impaired myeloid-derived suppressor cell activation. Finally, transgenic overexpression of human gastrokines (GKNs) attenuated gastric tumor growth in gp130[superscript F/F] mice. Together, these results reveal an antiinflammatory role for GKN2, provide in vivo evidence that links GKN2 loss to GC pathogenesis, and suggest GKN restoration as a strategy to restrain GC progression

Interdisciplinary project-based learning: technology for improving student cognition

The article studies a way of enhancing student cognition by using interdisciplinary project-based learning (IPBL) in a higher education institution. IPBL is a creative pedagogic approach allowing students of one area of specialisation to develop projects for students with different academic profiles. The application of this approach in the Ural State University of Economics resulted in a computer-assisted learning system (CALS) designed by IT students. The CALS was used in an analytical chemistry course with students majoring in Commodities Management and Expertise (‘expert’ students). To test how effective the technology was, the control and experimental groups were formed. In the control group, learning was done with traditional methods. In the experimental group, it was reinforced by IPBL. A statistical analysis of the results, with an application of Pearson χ 2 test, showed that the cognitive levels in both IT and ‘expert’ experimental groups improved as compared with the control groups. The findings demonstrated that IPBL can significantly enhance learning. It can be implemented in any institution of higher or secondary education that promotes learning, including the CALS development and its use for solving problems in different subject areas