Dohnralston0830

In Experiment 2, AWS exhibited higher kinematic variability than AWNS across the feedback conditions. Under 25-ms DAF, the spatiotemporal index of AWS decreased significantly compared to the other feedback conditions. AWS showed lower overall percent determinism than AWNS, but their percent determinism increased under 50-ms DAF to approximate that of AWNS. Conclusions Auditory feedback manipulations can alter speech fluency and kinematic variability in AWS. Longer latency auditory feedback delays induce speech disruptions, while subtle auditory feedback manipulations potentially benefit speech motor control. Both AWS and AWNS are susceptible to auditory feedback during speech production, but AWS appear to exhibit a distinct continuum of sensitivity.Purpose The goal of this study was to characterize and quantify maternal use of decontextualized and contextualized input during mother-child interactions including young children with Down syndrome (DS). Method Participants included 22 mother-child dyads with DS (M age = 42.8 months) and 22 mother-child dyads with typical development (M age = 44.0 months). Parent-child language samples were collected during free-play, book reading, and snack time, and coded for maternal decontextualized (i.e., pretend, explanatory, and narrative talk) and contextualized input (i.e., descriptions, conversation, praise, questions, and directives). Results Mothers of children with DS used a larger proportion of pretend talk compared to other types of decontextualized input and also used a larger proportion of questions, conversation, and descriptions compared to other types of contextualized language. Mothers of children with DS generally used a smaller proportion of decontextualized input compared to mothers of children with typical development, with the exception of pretend talk. Maternal decontextualized input was not related to children's age or language ability in DS. Conclusions Findings shed new light on the early language environments of children with DS, providing important insight into the ways that mothers of children with DS are incorporating decontextualized and contextualized talk into early mother-child conversations. Additional implications and future directions are discussed.Turkish delights (lokum) are traditional confectionery products that contain mainly sucrose as the sugar source and starch as the gelling agent. However, manufacturers sometimes might prefer to use corn syrup instead of sucrose to decrease the cost. This jeopardizes the originality of Turkish delights and leads to production of adulterated samples. In this study, Turkish delights were formulated using sucrose (original sample) and different types of corn syrups (SBF10, SCG40, and SCG60). Results clearly indicated that corn-syrup-containing samples had improved textural properties and were less prone to crystallization. However, this case affected authenticity of the products negatively. Both time domain nuclear magnetic resonance (TD NMR) and fast field cycling nuclear magnetic resonance (FFC NMR) techniques were found to be effective to discriminate the original samples from the corn-syrup-containing samples. In addition, quantitative analysis of FFC NMR showed that, apart from the rotational motions, molecules in Turkish delights (mainly water and also sugar molecules) undergo two types of translational dynamics.Data-independent acquisition (DIA) is becoming a leading analysis method in biomedical mass spectrometry. The main advantages include greater reproducibility and sensitivity and a greater dynamic range compared with data-dependent acquisition (DDA). However, the data analysis is complex and often requires expert knowledge when dealing with large-scale data sets. Here we present DIAproteomics, a multifunctional, automated, high-throughput pipeline implemented in the Nextflow workflow management system that allows one to easily process proteomics and peptidomics DIA data sets on diverse compute infrastructures. The central components are well-established tools such as the OpenSwathWorkflow for the DIA spectral library search and PyProphet for the false discovery rate assessment. In addition, it provides options to generate spectral libraries from existing DDA data and to carry out the retention time and chromatogram alignment. The output includes annotated tables and diagnostic visualizations from the statistical postprocessing and computation of fold-changes across pairwise conditions, predefined in an experimental design. DIAproteomics is well documented open-source software and is available under a permissive license to the scientific community at https//www.openms.de/diaproteomics/.Neuropeptides mediate cell-cell signaling in the nervous and endocrine systems. The neuropeptidome is the spectrum of peptides generated from precursors by proteolysis within dense core secretory vesicles (DCSV). DCSV neuropeptides and contents are released to the extracellular environment where further processing for neuropeptide formation may occur. To assess the DCSV proteolytic capacity for production of neuropeptidomes at intravesicular pH 5.5 and extracellular pH 7.2, neuropeptidomics, proteomics, and protease assays were conducted using chromaffin granules (CG) purified from adrenal medulla. CG are an established model of DCSV. The CG neuropeptidome consisted of 1239 unique peptides derived from 15 proneuropeptides that were colocalized with 64 proteases. Distinct CG neuropeptidomes were generated at the internal DCSV pH of 5.5 compared to the extracellular pH of 7.2. Class-specific protease inhibitors differentially regulated neuropeptidome production involving aspartic, cysteine, serine, and metallo proteases. The substrate cleavage properties of CG proteases were assessed by multiplex substrate profiling by mass spectrometry (MSP-MS) that uses a synthetic peptide library containing diverse cleavage sites for endopeptidases and exopeptidases. Parallel inhibitor-sensitive cleavages for neuropeptidome production and peptide library proteolysis led to elucidation of six CG proteases involved in neuropeptidome production, represented by cathepsins A, B, C, D, and L and carboxypeptidase E (CPE). The MSP-MS profiles of these six enzymes represented the majority of CG proteolytic cleavages utilized for neuropeptidome production. These findings provide new insight into the DCSV proteolytic system for production of distinct neuropeptidomes at the internal CG pH of 5.5 and at the extracellular pH of 7.2.Combinations of dienes and dienophiles were examined in order to elicit possible combinations for thermoreversible crosslinking units. Comparison of experimental results and quantum calculations indicated that reaction kinetics and activation energy were much better prediction factors than change in enthalpy for the prediction of successful cycloaddition. Further testing on diene-dienophile pairs that underwent successful cycloaddition determined the feasibility of thermoreversibility/retro-reaction of each of the Diels-Alder compounds. Heating and testing of the compounds in the presence of a trapping agent allowed for experimental determination of reverse kinetics and activation energy for the retro-reaction. The experimental values were in good agreement with quantum calculations. The combination of chemical calculations with experimental results provided a strong insight into the structure-property relationships and how quantum calculations can be used to examine the feasibility of the thermoreversibility of new Diels-Alder complexes in potential polymer systems or to fine-tune thermoreversible Diels-Alder systems already in use.Porous polymerized high internal phase emulsion (polyHIPE) monoliths are synthesized by using Span 80 with different cosurfactants. The results reveal that the void size can be reduced by employing cosurfactants, except for Tween 20. Furthermore, the openness of polyHIPEs changes by using different cosurfactants or by varying their concentration. To further investigate the effect of cosurfactants, we perform rheology measurements on the interface of the aqueous and oil phase. This study demonstrates the important role of interfacial elasticity in the successful preparation of polyHIPEs with different morphologies. Additionally, this study suggests that the increase in interfacial elasticity hinders the formation of interconnections between pores, known as windows. Finally, the compression test is performed to investigate the effect of the pore structure on the mechanical properties.Hybrids of graphene and metal plasmonic nanostructures are promising building blocks for applications in optoelectronics, surface-enhanced scattering, biosensing, and quantum information. An understanding of the coupling mechanism in these hybrid systems is of vital importance to its applications. Previous efforts in this field mainly focused on spectroscopic studies of strong coupling within the hybrids with no spatial resolution. Here we report direct imaging of the local plasmonic coupling between single Au nanocapsules and graphene step edges at the nanometer scale by photon-induced near-field electron microscopy in an ultrafast electron microscope for the first time. The proximity of a step in the graphene to the nanocapsule causes asymmetric surface charge density at the ends of the nanocapsules. Computational electromagnetic simulations confirm the experimental observations. The results reported here indicate that this hybrid system could be used to manipulate the localized electromagnetic field on the nanoscale, enabling promising future plasmonic devices.The gas-phase rotational spectrum of (cyanomethylene)cyclopropane, (CH2)2C═CHCN, generated by a Wittig reaction between the hemiketal of cyclopropanone and (cyanomethylene)triphenylphosphorane, is presented for the first time. This small, highly polar nitrile is a cyclopropyl-containing structural isomer of pyridine. The rotational spectra of the ground state and two vibrationally excited states were observed, analyzed, and least-squares fit from 130 to 360 GHz. Over 3900 R-, P-, and Q-branch, ground-state rotational transitions were fit to low-error, partial octic, A- and S-reduced Hamiltonians, providing precise determinations of the spectroscopic constants. The two lowest-energy vibrationally excited states, ν17 and ν27, form a Coriolis-coupled dyad displaying small a- and b-type resonances. Transitions for these two states were measured and least-squares fit to a two-state, partial octic, A-reduced Hamiltonian in the Ir representation with nine Coriolis-coupling terms (Ga, GaJ, GaK, GaJJ, Fbc, FbcJ, FbcK, Gb, and GbJ). The observation of many resonant transitions and nine nominal interstate transitions enabled a very accurate and precise energy difference between ν17 and ν27 to be determined ΔE17,27 = 29.8975453 (33) cm-1. The spectroscopic constants presented herein provide the foundation for future astronomical searches for (cyanomethylene)cyclopropane.Computational methods such as machine learning approaches have a strong track record of success in predicting the outcomes of in vitro assays. Epacadostat In contrast, their ability to predict in vivo endpoints is more limited due to the high number of parameters and processes that may influence the outcome. Recent studies have shown that the combination of chemical and biological data can yield better models for in vivo endpoints. The ChemBioSim approach presented in this work aims to enhance the performance of conformal prediction models for in vivo endpoints by combining chemical information with (predicted) bioactivity assay outcomes. Three in vivo toxicological endpoints, capturing genotoxic (MNT), hepatic (DILI), and cardiological (DICC) issues, were selected for this study due to their high relevance for the registration and authorization of new compounds. Since the sparsity of available biological assay data is challenging for predictive modeling, predicted bioactivity descriptors were introduced instead. Thus, a machine learning model for each of the 373 collected biological assays was trained and applied on the compounds of the in vivo toxicity data sets.