Investigation of the Effects of N-Linked Glycans on the Stability of the Spike Protein in SARS-CoV-2 by Molecular Dynamics Simulations

We perform all-atom molecular dynamics simulations to study the effects of the N-linked glycans on the stability of the spike glycoprotein in SARS-CoV-2. After a 100 ns of simulation on the spike proteins without and with the N-linked glycans, we found that the presence of glycans increases the local stability in their vicinity; even though their effect on the full structure is negligible.

Quoi-sluices in French

Sluicing has traditionally been analyzed as an operation involving wh-movement and deletion (Merchant 2001). French is a language that has both fronted and wh-in situ strategies; on the surface, however, it seems that French sluices do not involve (overt) movement, in spite of this being an available option. For nearly all wh-words, the in situ and moved forms are the same; the exception is que/quoi ‘what’— que is found in fronted wh-questions alone, while quoi is found in situ. In sluicing, only quoi surfaces, suggesting that French may be a challenge for the movement-and-deletion approach (Dagnac 2019). By formalizing an analysis within a late insertion approach to the syntax-morphology interface, I argue that not only do sluices in French involve full structure, but that they involve movement as well. I assume that the wh-word is initially represented in the syntactic derivation as an abstract feature bundle. The morphological form is determined in the mapping of syntax to morphology by locality-dependent Vocabulary Insertion (VI) rules that are sensitive to C. These rules apply only after ellipsis occurs. Following Thoms (2010), I argue that C is targeted in sluicing, and as a result destroys the context that would trigger que. This analysis is able to capture sluicing in French, while explaining the behavior of quoi more generally.

A Combination of Structural, Genetic, Phenotypic and Enzymatic Analyses Reveals the Importance of a Predicted Fucosyltransferase to Protein O-Glycosylation in the Bacteroidetes

Diverse members of the Bacteroidetes phylum have general protein O-glycosylation systems that are essential for processes such as host colonization and pathogenesis. Here, we analyzed the function of a putative fucosyltransferase (FucT) family that is widely encoded in Bacteroidetes protein O-glycosylation genetic loci. We studied the FucT orthologs of three Bacteroidetes species—Tannerella forsythia, Bacteroides fragilis, and Pedobacter heparinus. To identify the linkage created by the FucT of B. fragilis, we elucidated the full structure of its nine-sugar O-glycan and found that l-fucose is linked β1,4 to glucose. Of the two fucose residues in the T. forsythia O-glycan, the fucose linked to the reducing-end galactose was shown by mutational analysis to be l-fucose. Despite the transfer of l-fucose to distinct hexose sugars in the B. fragilis and T. forsythia O-glycans, the FucT orthologs from B. fragilis, T. forsythia, and P. heparinus each cross-complement the B. fragilis ΔBF4306 and T. forsythia ΔTanf_01305 FucT mutants. In vitro enzymatic analyses showed relaxed acceptor specificity of the three enzymes, transferring l-fucose to various pNP-α-hexoses. Further, glycan structural analysis together with fucosidase assays indicated that the T. forsythia FucT links l-fucose α1,6 to galactose. Given the biological importance of fucosylated carbohydrates, these FucTs are promising candidates for synthetic glycobiology.

Joint Learning of Full-structure Noise in Hierarchical Bayesian Regression Models

We consider the reconstruction of brain activity from electroencephalography (EEG). This inverse problem can be formulated as a linear regression with independent Gaussian scale mixture priors for both the source and noise components. Crucial factors influencing accuracy of source estimation are not only the noise level but also its correlation structure, but existing approaches have not addressed estimation of noise covariance matrices with full structure. To address this shortcoming, we develop hierarchical Bayesian (type-II maximum likelihood) models for observations with latent variables for source and noise, which are estimated jointly from data. As an extension to classical sparse Bayesian learning (SBL), where across-sensor observations are assumed to be independent and identically distributed, we consider Gaussian noise with full covariance structure. Using the majorization-maximization framework and Riemannian geometry, we derive an efficient algorithm for updating the noise covariance along the manifold of positive definite matrices. We demonstrate that our algorithm has guaranteed and fast convergence and validate it in simulations and with real MEG data. Our results demonstrate that the novel framework significantly improves upon state-of-the-art techniques in the real-world scenario where the noise is indeed non-diagonal and fully-structured. Our method has applications in many domains beyond biomagnetic inverse problems.

Two-loop application of the Breitenlohner-Maison/’t Hooft-Veltman scheme with non-anticommuting γ5: full renormalization and symmetry-restoring counterterms in an abelian chiral gauge theory

We apply the BMHV scheme for non-anticommuting γ5 to an abelian chiral gauge theory at the two-loop level. As our main result, we determine the full structure of symmetry-restoring counterterms up to the two-loop level. These counterterms turn out to have the same structure as at the one-loop level and a simple interpretation in terms of restoration of well-known Ward identities. In addition, we show that the ultraviolet divergences cannot be canceled completely by counterterms generated by field and parameter renormalization, and we determine needed UV divergent evanescent counterterms. The paper establishes the two-loop methodology based on the quantum action principle and direct computations of Slavnov-Taylor identity breakings. The same method will be applicable to nonabelian gauge theories.

Native Metabolomics Identifies the Rivulariapeptolide Family of Protease Inhibitors

The identity and biological activity of most metabolites still remain unknown. A key bottleneck in the full exploration of this tremendous source of new structures and pharmaceutical activities is the compound purification needed for bioactivity assignments of individual compounds and downstream structure elucidation. To enable bioactivity-focused compound identification from complex mixtures, we developed a scalable native metabolomics approach that integrates non-targeted liquid chromatography tandem mass spectrometry, and simultaneous detection of protein binding via native mass spectrometry. While screening for new protease inhibitors from an environmental cyanobacteria community, native metabolomics revealed 30 cyclodepsipeptides as chymotrypsin binders. Mass spectrometry-guided purification then allowed for full structure elucidation of the most prevalent compounds via nuclear magnetic resonance spectroscopy, as well as orthogonal bioactivity studies. Together, these results identified the rivulariapeptolides as a family of serine protease inhibitors with nanomolar potency.

New canonical analysis for higher order topologically massive gravity

A detailed Gitman–Lyakhovich–Tyutin analysis for higher-order topologically massive gravity is performed. The full structure of the constraints, the counting of physical degrees of freedom, and the Dirac algebra among the constraints are reported. Moreover, our analysis presents a new structure into the constraints and we compare our results with those reported in the literature where a standard Ostrogradski framework was developed.

Prediction of Post-Diagnostic Decisions for Tested Hand Grenades’ Fuzes Using Decision Trees

The article presents a brief history of creation of decision trees and defines the purpose of the undertaken works. The process of building a classification tree, according to the CHAID method, is shown paying particular attention to the disadvantages, advantages, and characteristics features of this method, as well as to the formal requirements that are necessary to build this model. The tree’s building method for UZRGM (Universal Modernised Fuze of Hand Grenades) fuzes was characterized, specifying the features of the tested hand grenade fuzes and the predictors used that are necessary to create the correct tree model. A classification tree was built basing on the test results, assuming the accepted post-diagnostic decision as a qualitative dependent variable. A schema of the designed tree for the first diagnostic tests, its full structure and the size of individual classes of the node are shown. The matrix of incorrect classifications was determined, which determines the accuracy of incorrect predictions, i.e., correctness of the performed classification. A sheet with risk assessment and standard error for the learning sample and the v-fold cross-check were presented. On the selected examples, the quality of the resulting predictive model was assessed by means of a graph of the cumulative value of the lift coefficient and the "ROC" curve

Cartesian Differential Categories as Skew Enriched Categories

We exhibit the cartesian differential categories of Blute, Cockett and Seely as a particular kind of enriched category. The base for the enrichment is the category of commutative monoids—or in a straightforward generalisation, the category of modules over a commutative rig k. However, the tensor product on this category is not the usual one, but rather a warping of it by a certain monoidal comonad Q. Thus the enrichment base is not a monoidal category in the usual sense, but rather a skew monoidal category in the sense of Szlachányi. Our first main result is that cartesian differential categories are the same as categories with finite products enriched over this skew monoidal base. The comonad Q involved is, in fact, an example of a differential modality. Differential modalities are a kind of comonad on a symmetric monoidal k-linear category with the characteristic feature that their co-Kleisli categories are cartesian differential categories. Using our first main result, we are able to prove our second one: that every small cartesian differential category admits a full, structure-preserving embedding into the cartesian differential category induced by a differential modality (in fact, a monoidal differential modality on a monoidal closed category—thus, a model of intuitionistic differential linear logic). This resolves an important open question in this area.