Biosignals reflect pair-dynamics in collaborative work : EDA and ECG study of pair-programming in a classroom environment

Collaboration is a complex phenomenon, where intersubjective dynamics can greatly affect the productive outcome. Evaluation of collaboration is thus of great interest, and can potentially help achieve better outcomes and performance. However, quantitative measurement of collaboration is difficult, because much of the interaction occurs in the intersubjective space between collaborators. Manual observation and/or self-reports are subjective, laborious, and have a poor temporal resolution. The problem is compounded in natural settings where task-activity and response-compliance cannot be controlled. Physiological signals provide an objective mean to quantify intersubjective rapport (as synchrony), but require novel methods to support broad deployment outside the lab. We studied 28 student dyads during a self-directed classroom pair-programming exercise. Sympathetic and parasympathetic nervous system activation was measured during task performance using electrodermal activity and electrocardiography. Results suggest that (a) we can isolate cognitive processes (mental workload) from confounding environmental effects, and (b) electrodermal signals show role-specific but correlated affective response profiles. We demonstrate the potential for social physiological compliance to quantify pair-work in natural settings, with no experimental manipulation of participants required. Our objective approach has a high temporal resolution, is scalable, non-intrusive, and robust.Peer reviewe

Protein-Protein Interaction Site Predictions with Three-Dimensional Probability Distributions of Interacting Atoms on Protein Surfaces

Protein-protein interactions are key to many biological processes. Computational methodologies devised to predict protein-protein interaction (PPI) sites on protein surfaces are important tools in providing insights into the biological functions of proteins and in developing therapeutics targeting the protein-protein interaction sites. One of the general features of PPI sites is that the core regions from the two interacting protein surfaces are complementary to each other, similar to the interior of proteins in packing density and in the physicochemical nature of the amino acid composition. In this work, we simulated the physicochemical complementarities by constructing three-dimensional probability density maps of non-covalent interacting atoms on the protein surfaces. The interacting probabilities were derived from the interior of known structures. Machine learning algorithms were applied to learn the characteristic patterns of the probability density maps specific to the PPI sites. The trained predictors for PPI sites were cross-validated with the training cases (consisting of 432 proteins) and were tested on an independent dataset (consisting of 142 proteins). The residue-based Matthews correlation coefficient for the independent test set was 0.423; the accuracy, precision, sensitivity, specificity were 0.753, 0.519, 0.677, and 0.779 respectively. The benchmark results indicate that the optimized machine learning models are among the best predictors in identifying PPI sites on protein surfaces. In particular, the PPI site prediction accuracy increases with increasing size of the PPI site and with increasing hydrophobicity in amino acid composition of the PPI interface; the core interface regions are more likely to be recognized with high prediction confidence. The results indicate that the physicochemical complementarity patterns on protein surfaces are important determinants in PPIs, and a substantial portion of the PPI sites can be predicted correctly with the physicochemical complementarity features based on the non-covalent interaction data derived from protein interiors

International Consensus Statement on Rhinology and Allergy: Rhinosinusitis

Background: The 5 years since the publication of the first International Consensus Statement on Allergy and Rhinology: Rhinosinusitis (ICAR‐RS) has witnessed foundational progress in our understanding and treatment of rhinologic disease. These advances are reflected within the more than 40 new topics covered within the ICAR‐RS‐2021 as well as updates to the original 140 topics. This executive summary consolidates the evidence‐based findings of the document. Methods: ICAR‐RS presents over 180 topics in the forms of evidence‐based reviews with recommendations (EBRRs), evidence‐based reviews, and literature reviews. The highest grade structured recommendations of the EBRR sections are summarized in this executive summary. Results: ICAR‐RS‐2021 covers 22 topics regarding the medical management of RS, which are grade A/B and are presented in the executive summary. Additionally, 4 topics regarding the surgical management of RS are grade A/B and are presented in the executive summary. Finally, a comprehensive evidence‐based management algorithm is provided. Conclusion: This ICAR‐RS‐2021 executive summary provides a compilation of the evidence‐based recommendations for medical and surgical treatment of the most common forms of RS

Structures of Down syndrome kinases, DYRKs, reveal mechanisms of kinase activation and substrate recognition.

Dual-specificity tyrosine-(Y)-phosphorylation-regulated kinases (DYRKs) play key roles in brain development, regulation of splicing, and apoptosis, and are potential drug targets for neurodegenerative diseases and cancer. We present crystal structures of one representative member of each DYRK subfamily: DYRK1A with an ATP-mimetic inhibitor and consensus peptide, and DYRK2 including NAPA and DH (DYRK homology) box regions. The current activation model suggests that DYRKs are Ser/Thr kinases that only autophosphorylate the second tyrosine of the activation loop YxY motif during protein translation. The structures explain the roles of this tyrosine and of the DH box in DYRK activation and provide a structural model for DYRK substrate recognition. Phosphorylation of a library of naturally occurring peptides identified substrate motifs that lack proline in the P+1 position, suggesting that DYRK1A is not a strictly proline-directed kinase. Our data also show that DYRK1A wild-type and Y321F mutant retain tyrosine autophosphorylation activity

The 2019 Magnetic Resonance Velocimetry Challenge

While magnetic resonance velocimetry (MRV) has been used in technological flow studies for over 30 years, it has not yet reached the levels of usage as more traditional experimental techniques such as particle image velocimetry or laser Doppler anemometry. This work involves a relatively simple U-bend geometry with complex three-dimensional turbulent flow characteristics which was shared with four research groups, including a combined effort from the U.S. Military Academy/Stanford University, and teams from Hanyang University, the University of Rostock, and the Mayo Clinic. The geometry—including upstream flow development—was shipped between groups with nominally similar experimental conditions, and the acquired data are presented including both two- and three-dimensional comparisons. In addition, details on how each team conducted the MRV experiments are provided, with each team using a different set of procedures and hardware. The results are remarkably similar, with only a few variations at the flow regions with the highest in-plane velocity gradients showing differences outside the combined uncertainty of the results

Hypoxia-inducible factor (HIF) asparagine hydroxylase is identical to factor inhibiting HIF (FIH) and is related to the cupin structural family.

Activity of the hypoxia-inducible factor (HIF) complex is controlled by oxygen-dependent hydroxylation of prolyl and asparaginyl residues. Hydroxylation of specific prolyl residues by 2-oxoglutarate (2-OG)-dependent oxygenases mediates ubiquitinylation and proteasomal destruction of HIF-alpha. Hydroxylation of an asparagine residue in the C-terminal transactivation domain (CAD) of HIF-alpha abrogates interaction with p300, preventing transcriptional activation. Yeast two-hybrid assays recently identified factor inhibiting HIF (FIH) as a protein that associates with the CAD region of HIF-alpha. Since FIH contains certain motifs present in iron- and 2-OG-dependent oxygenases we investigated whether FIH was the HIF asparaginyl hydroxylase. Assays using recombinant FIH and HIF-alpha fragments revealed that FIH is the enzyme that hydroxylates the CAD asparagine residue, that the activity is directly inhibited by cobalt(II) and limited by hypoxia, and that the oxygen in the alcohol of the hydroxyasparagine residue is directly derived from dioxygen. Sequence analyses involving FIH link the 2-OG oxygenases with members of the cupin superfamily, including Zn(II)-utilizing phosphomannose isomerase, revealing structural and evolutionary links between these metal-binding proteins that share common motifs