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Soliton-based single-point pulse wave velocity model: A quantum mechanical approach(Biomedical Signal Processing and Control, Elsevier BV, 2021-10-20) [Article]Cardiovascular diseases (CVDs) are one of the strongest contributors to mortality rates worldwide. To assess the severity of a clinical situation, various indices of CVD risk have been established, one of them being the arterial stiffness. Arterial stiffness is the quantification of the arterial elasticity. There exist several methodologies to assess the level of arterial stiffness where their non-invasiveness is a matter of great importance. The pulse wave velocity (PWV) is used as an indicator of the arterial stiffness and satisfies the non-invasiveness requirement. Specifically, the carotid-femoral PWV-based method is considered one of the most trustworthy methodology in quantifying the arterial stiffness. This paper proposes a new model for the PWV along with insights on a real scenario implementation. The model utilizes Semi-classical signal analysis (SCSA) as the main signal processing framework to analyze the blood pressure waveform. The proposed model is suggested to be used as an add-on to existing methodologies, bringing the feature of single-point measurement, once a calibration phase has preceded. The use of such a model can eliminate the pulse propagation time-delay, one of the dominant sources of PWV error. Additionally, the single-point measurement paves the way of prolonged PWV monitoring that can reveal new clinical features of the PWV. The model was validated both in a theoretical and data basis, validating its predicted hyperbolic PWV behavior with respect to the SCSA parameters.
NERO: a biomedical named-entity (recognition) ontology with a large, annotated corpus reveals meaningful associations through text embedding(npj Systems Biology and Applications, Springer Science and Business Media LLC, 2021-10-20) [Article]Machine reading (MR) is essential for unlocking valuable knowledge contained in millions of existing biomedical documents. Over the last two decades1,2, the most dramatic advances in MR have followed in the wake of critical corpus development3. Large, well-annotated corpora have been associated with punctuated advances in MR methodology and automated knowledge extraction systems in the same way that ImageNet4 was fundamental for developing machine vision techniques. This study contributes six components to an advanced, named entity analysis tool for biomedicine: (a) a new, Named Entity Recognition Ontology (NERO) developed specifically for describing textual entities in biomedical texts, which accounts for diverse levels of ambiguity, bridging the scientific sublanguages of molecular biology, genetics, biochemistry, and medicine; (b) detailed guidelines for human experts annotating hundreds of named entity classes; (c) pictographs for all named entities, to simplify the burden of annotation for curators; (d) an original, annotated corpus comprising 35,865 sentences, which encapsulate 190,679 named entities and 43,438 events connecting two or more entities; (e) validated, off-the-shelf, named entity recognition (NER) automated extraction, and; (f) embedding models that demonstrate the promise of biomedical associations embedded within this corpus.
Cryo-EM structure of human Pol κ bound to DNA and mono-ubiquitylated PCNA(Nature Communications, Springer Science and Business Media LLC, 2021-10-19) [Article]AbstractY-family DNA polymerase κ (Pol κ) can replicate damaged DNA templates to rescue stalled replication forks. Access of Pol κ to DNA damage sites is facilitated by its interaction with the processivity clamp PCNA and is regulated by PCNA mono-ubiquitylation. Here, we present cryo-EM reconstructions of human Pol κ bound to DNA, an incoming nucleotide, and wild type or mono-ubiquitylated PCNA (Ub-PCNA). In both reconstructions, the internal PIP-box adjacent to the Pol κ Polymerase-Associated Domain (PAD) docks the catalytic core to one PCNA protomer in an angled orientation, bending the DNA exiting the Pol κ active site through PCNA, while Pol κ C-terminal domain containing two Ubiquitin Binding Zinc Fingers (UBZs) is invisible, in agreement with disorder predictions. The ubiquitin moieties are partly flexible and extend radially away from PCNA, with the ubiquitin at the Pol κ-bound protomer appearing more rigid. Activity assays suggest that, when the internal PIP-box interaction is lost, Pol κ is retained on DNA by a secondary interaction between the UBZs and the ubiquitins flexibly conjugated to PCNA. Our data provide a structural basis for the recruitment of a Y-family TLS polymerase to sites of DNA damage.
Cell-to-Cell Communication During Plant-Pathogen Interaction(Molecular Plant-Microbe Interactions®, Scientific Societies, 2021-10-19) [Article]Recognition of pathogen activates cellular signaling such as ROS, MAPK, Ca2+ signaling which ultimately fine-tunes the cell to cell communication. These further coordinates with the hormone signaling to execute the defense response at local and systemic level. Interestingly, phytopathogens have also evolved to manipulate the cellular and hormonal signaling and/or exploit hosts cell to cell connection in multiple ways at multiple levels. Overall, the triumph over the pathogen depends on prime decisions and actions-how the plant maintain, regulate and eventually break the intercellular communication through apoplastic and symplastic routes. Here, we review how intercellular communication in plants is mediated, manipulated and maneuvered during plant-pathogen interaction. Key words: Cell to cell communication, plant defense, plasmodesmata, phytohormones
Rayleigh Wave Dispersion Spectrum Inversion Across Scales(Surveys in Geophysics, Springer Science and Business Media LLC, 2021-10-19) [Article]Traditional approaches of using dispersion curves for S-wave velocity reconstruction have limitations, principally, the 1D-layered model assumption and the automatic/manual picking of dispersion curves. At the same time, conventional full-waveform inversion (FWI) can easily converge to a non-global minimum when applied directly to complicated surface waves. Alternatively, the recently introduced wave equation dispersion spectrum inversion method can avoid these limitations, by applying the adjoint state method on the dispersion spectra of the observed and predicted data and utilizing the local similarity objective function to depress cycle skipping. We apply the wave equation dispersion spectrum inversion to three real datasets of different scales: tens of meters scale active-source data for estimating shallow targets, tens of kilometers scale ambient noise data for reservoir characterization and a continental-scale seismic array data for imaging the crust and uppermost mantle. We use these three open datasets from exploration to crustal scale seismology to demonstrate the effectiveness of the inversion method. The dispersion spectrum inversion method adapts well to the different-scale data without any special tuning. The main benefits of the proposed method over traditional methods are that (1) it can handle lateral variations; (2) it avoids direct picking dispersion curves; (3) it utilizes both the fundamental and higher modes of Rayleigh waves, and (4) the inversion can be solved using gradient-based local optimizations. Compared to the conventional 1D inversion, the dispersion spectrum inversion requires more computational cost since it requires solving the 2D/3D elastic wave equation in each iteration. A good match between the observed and predicted dispersion spectra also leads to a reasonably good match between the observed and predicted waveforms, though the inversion does not aim to match the waveforms.