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At least 631 records · Page 35

On the use of vibronic coherence to identify reaction coordinates for ultrafast excited-state dynamics of transition metal-based chromophores

In this study, the question of whether one can use information from quantum coherence as a means of identifying vibrational degrees of freedom that are active along an excited-state reaction coordinate is discussed. Specifically, we are exploring the notion of whether quantum oscillations observed in single-wavelength kinetics data exhibiting coherence dephasing times that are intermediate between that expected for either pure electronic or pure vibrational dephasing are vibronic in nature and therefore may be coupled to electronic state-to-state evolution. In the case of a previously published Fe(ιι) polypyridyl complex, coherences observed subsequent to 1 A 1 → 1 MLCT excitation were linked to large-amplitude motion of a portion of the ligand framework; dephasing times on the order of 200–300 fs suggested that these degrees of freedom could be associated with ultrafast (~100 fs) conversion from the initially formed MLCT excited state to lower-energy, metal-centered ligand-field excited state(s) of the compound. Incorporation of an electronically benign but sterically restrictive Cu(ι) ion into the superstructure designed to interfere with this motion yielded a compound exhibiting a ~25-fold increase in the compound’s MLCT lifetime, a result that was interpreted as confirmation of the initial hypothesis. However, new data acquired on a different chemical system – Cr(acac') 3 (where acac' represents various derivatives of acetylacetonate) – yielded results that call into question this same hypothesis. Coherences observed subsequent to 4 A 2 → 4 T 2 ligand-field excitation on a series of molecules implicated similar vibrational degrees of freedom across the series, but exhibited dephasing times ranging from 340 fs to 2.5 ps without any clear correlation to the dynamics of excited-state evolution in the system. Taken together, the results obtained on both of these chemical platforms suggest that while identification of coherences can indeed point to degrees of freedom that should be considered as candidate modes for defining reaction trajectories, our understanding of the factors that determine the interplay across coherences, dephasing times, and electronic and geometric structure is insufficient at the present time to view this parameter as a robust metric for differentiating active versus spectator modes for ultrafast dynamics.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

An activity-based probe library for identifying promiscuous amide hydrolases

A fluorogenic substrate library was developed to detect amide hydrolase activity in soil-derived chitin-degrading bacteria. Hit compounds were converted into pull-down probes for chemoproteomic enrichment, identifying previously unannotated proteins now linked to putative hydrolases. This approach prioritizes candidate hydrolases for further experimental validation with potential applications in the environment, biomanufacturing, and medicine.

Activity based probes↗

Structure based virtual screening identifies small molecule effectors for the sialoglycan binding protein Hsa

Infective endocarditis (IE) is a cardiovascular disease often caused by bacteria of the viridans group of streptococci, which includes Streptococcus gordonii and Streptococcus sanguinis. Previous research has found that serine-rich repeat (SRR) proteins on the S. gordonii bacterial surface play a critical role in pathogenesis by facilitating bacterial attachment to sialylated glycans displayed on human platelets. Despite their important role in disease progression, there are currently no anti-adhesive drugs available on the market. Here, we performed structure-based virtual screening using an ensemble docking approach followed by consensus scoring to identify novel small molecule effectors against the sialoglycan binding domain of the SRR adhesin protein Hsa from the S. gordonii strain DL1. The screening successfully predicted nine compounds which were able to displace the native ligand (sialyl-T antigen) in an in vitro assay and bind competitively to Hsa. Furthermore, hierarchical clustering based on the MACCS fingerprints showed that eight of these small molecules do not share a common scaffold with the native ligand. This study indicates that SRR family of adhesin proteins can be inhibited by diverse small molecules and thus prevent the interaction of the protein with the sialoglycans. This opens new avenues for discovering potential drugs against IE.

60 APPLIED LIFE SCIENCES↗

Possibilities of identifying cyber attack in noisy space of n-dimensional abstract system

This article briefly mentions some selected options of current concept for identifying cyber attacks from the perspective of the new cyberspace of real system. In the cyberspace, there is defined n-dimensional abstract system containing elements of the spatial arrangement of partial system elements such as micro-environment of cyber systems surrounded by other suitably arranged corresponding noise space. This space is also gradually supplemented by a new image of dynamic processes in a discreet environment, and corresponding again to n-dimensional expression of time space defining existence and also the prediction for expected cyber attacksin the noise space. Noises are seen here as useful and necessary for modern information and communication technologies (e.g. in processes of applied cryptography in ICT) and then the so-called useless noises designed for initial (necessary) filtering of this highly aggressive environment and in future expectedly offensive background in cyber war (e.g. the destruction of unmanned means of an electromagnetic pulse, or for destruction of new safety barriers created on principles of electrostatic field or on other principles of modern physics, etc.). The key to these new options is the expression of abstract systems based on the models of microelements of cyber systems and their hierarchical concept in structure of n-dimensional system in given cyberspace. The aim of this article is to highlight the possible systemic expression of cyberspace of abstract system and possible identification in time-spatial expression of real environment (on microelements of cyber systems and their surroundings with noise characteristics and time dimension in dynamic of microelements’ own time and externaltime defined by real environment). The article was based on a partial task of faculty specific research.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Strong-field coherence breaking as a tool for identifying methyl rotor states in microwave spectra: 2-hexanone

The rotational spectrum of 2-hexanone was recorded over the 8–18 GHz region using a chirped pulse Fourier transform microwave spectrometer. Strong field coherence breaking (SFCB) was utilized to selectively modulate the intensities of rotational transitions belonging to the two lowest energy conformers of 2-hexanone, aiding the assignment. In addition, the SFCB method was applied for the first time to selectively identify rotational transitions built off the two lowest energy hindered methyl rotor states of each conformer, 0a1 and 1e. Since these two states have rotational energy levels with different nuclear spin symmetries, their intensities could be selectively modulated by the resonant monochromatic pulses used in the SFCB method. Here, the difference spectra, final fit, and structural parameters are discussed for the three assigned conformers of 2-hexanone.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Identifying crystal structures and chemical reactions at the interface of stanene on Bi 2 Te 3

Synthesizing monolayers and heterostructures is an enabling approach to extract new physical phenomena from bulk materials. Among the structures amenable to this approach is stanene, which is a monolayer of tin, similar to graphene, and has been predicted to host one-dimensional topological states at its edges. Stanene can be tuned by decorating with different adatoms, which makes it a promising platform on which to engineer topological devices. Here, we deposit Sn on Bi 2 Te 3 and characterize the growth using anomalous synchrotron x-ray scattering and x-ray photoelectron spectroscopy (XPS). X-ray diffraction data reveal the formation of epitaxial Sn-based structures, along with penetration of Sn into the Bi 2 Te 3 , with Sn intercalating between the upper 10 Bi 2 Te 3 quintuple layers. Additionally, XPS data show deposited Sn reacting to form SnTe and Bi at the Bi 2 Te 3 surface. The calculated heat of reaction for Sn and Bi2Te3 is consistent with an exothermic reaction to SnTe and Bi. Using thermodynamic calculations as a guide, we identify several candidate substrates that can stabilize the stanene phase.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Measuring the electron temperature and identifying plasma detachment using machine learning and spectroscopy

A machine learning approach has been implemented to measure the electron temperature directly from the emission spectra of a tokamak plasma. This approach utilized a neural network (NN) trained on a dataset of 1865 time slices from operation of the DIII-D tokamak using extreme ultraviolet/vacuum ultraviolet emission spectroscopy matched with high-accuracy divertor Thomson scattering measurements of the electron temperature, T e . This NN is shown to be particularly good at predicting T e at low temperatures (T e < 10 eV) where the NN demonstrated a mean average error of less than 1 eV. Trained to detect plasma detachment in the tokamak divertor, a NN classifier was able to correctly identify detached states (T e < 5 eV) with a 99% accuracy (an F 1 score of 0.96) at an acquisition rate 10× faster than the Thomson scattering measurement. The performance of the model is understood by examining a set of 4800 theoretical spectra generated using collisional radiative modeling that was also used to predict the performance of a low-cost spectrometer viewing nitrogen emission in the visible wavelengths. Furthermore, these results provide a proof-of-principle that low-cost spectrometers leveraged with machine learning can be used to boost the performance of more expensive diagnostics on fusion devices and be used independently as a fast and accurate T e measurement and detachment classifier.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Association mapping, transcriptomics, and transient expression identify candidate genes mediating plant–pathogen interactions in a tree

Invasive microbes causing diseases such as sudden oak death negatively affect ecosystems and economies around the world. The deployment of resistant genotypes for combating introduced diseases typically relies on breeding programs that can take decades to complete. To reflect how this process can be accelerated, we employed a genome-wide association mapping of ca. 1,000 resequenced Populus trichocarpa trees individually challenged with Sphaerulina musiva, an invasive fungal pathogen. Among crucial associations, three loci associated with resistance were identified and predicted to encode one putative membrane-bound L-type receptor-like kinase and two receptor-like proteins. A susceptibility-associated locus was predicted to encode a putative G-type D-mannose–binding receptor-like kinase. Multiple lines of evidence, including allele analysis, transcriptomics, binding assays, and overexpression, support the hypothesized function of these candidate genes in the P. trichocarpa response to S. musiva.

59 BASIC BIOLOGICAL SCIENCES↗

Identifying spinon excitations from dynamic structure factor of spin-1/2 Heisenberg antiferromagnet on the Kagome lattice

Significance In frustrated quantum magnets, the interplay between quantum fluctuation and geometric frustration may prevent magnetic ordering and result in exotic quantum spin liquids, where the spin degrees of freedom form disordered liquid-like states with novel fractionalized excitations. Here, we study the dynamical response of spin liquids on a Kagome lattice Heisenberg antiferromagnet. Our results reproduce the main observations in the inelastic neutron scattering measurements of herbertsmithite and unveil the spin liquid nature of the ground state with fractionalized spinon excitations. By crossing the quantum-phase transition between the spin liquid and magnetically ordered phase, we identify the condensation of two-spinon bound state as the driving force.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Exploiting regulatory heterogeneity to systematically identify enhancers with high accuracy

Identifying functional enhancer elements in metazoan systems is a major challenge. Large-scale validation of enhancers predicted by ENCODE reveal false-positive rates of at least 70%. We used the pregrastrula-patterning network of Drosophila melanogaster to demonstrate that loss in accuracy in held-out data results from heterogeneity of functional signatures in enhancer elements. We show that at least two classes of enhancers are active during early Drosophila embryogenesis and that by focusing on a single, relatively homogeneous class of elements, greater than 98% prediction accuracy can be achieved in a balanced, completely held-out test set. The class of well-predicted elements is composed predominantly of enhancers driving multistage segmentation patterns, which we designate segmentation driving enhancers (SDE). Prediction is driven by the DNA occupancy of early developmental transcription factors, with almost no additional power derived from histone modifications. We further show that improved accuracy is not a property of a particular prediction method: after conditioning on the SDE set, naïve Bayes and logistic regression perform as well as more sophisticated tools. Applying this method to a genome-wide scan, we predict 1,640 SDEs that cover 1.6% of the genome. An analysis of 32 SDEs using whole-mount embryonic imaging of stably integrated reporter constructs chosen throughout our prediction rank-list showed >90% drove expression patterns. We achieved 86.7% precision on a genome-wide scan, with an estimated recall of at least 98%, indicating high accuracy and completeness in annotating this class of functional elements.

54 ENVIRONMENTAL SCIENCES↗

Reaction intermediates during operando electrocatalysis identified from full solvent quantum mechanics molecular dynamics

Electrocatalysis provides a powerful means to selectively transform molecules, but a serious impediment in making rapid progress is the lack of a molecular-based understanding of the reactive mechanisms or intermediates at the electrode–electrolyte interface (EEI). Recent experimental techniques have been developed for operando identification of reaction intermediates using surface infrared (IR) and Raman spectroscopy. However, large noises in the experimental spectrum pose great challenges in resolving the atomistic structures of reactive intermediates. To provide an interpretation of these experimental studies and target for additional studies, we report the results from quantum mechanics molecular dynamics (QM-MD) with explicit consideration of solvent, electrode–electrolyte interface, and applied potential at 298 K, which conceptually resemble the operando experimental condition, leading to a prototype of operando QM-MD (o-QM-MD). With o-QM-MD, we characterize 22 possible reactive intermediates in carbon dioxide reduction reactions ( C O 2 RRs). Furthermore, we report the vibrational density of states (v-DoSs) of these intermediates from two-phase thermodynamic (2PT) analysis. Accordingly, we identify important intermediates such as chemisorbed C O 2 ( b - C O 2 ), *HOC-COH, *C-CH, and *C-COH in our o-QM-MD likely to explain the experimental spectrum. Indeed, we assign the experimental peak at 1,191 cm −1 to the mode of C-O stretch in *HOC-COH predicted at 1,189 cm −1 and the experimental peak at 1,584 cm −1 to the mode of C-C stretch in *C-COD predicted at 1,581 cm −1 . Interestingly, we find that surface ketene (*C=C=O), arising from *HOC-COH dehydration, also shows signals at around 1,584 cm −1 , which indicates a nonelectrochemical pathway of hydrocarbon formation at low overpotential and high pH conditions.

36 MATERIALS SCIENCE↗

GDGT cyclization proteins identify the dominant archaeal sources of tetraether lipids in the ocean

Glycerol dibiphytanyl glycerol tetraethers (GDGTs) are distinctive archaeal membrane-spanning lipids with up to eight cyclopentane rings and/or one cyclohexane ring. The number of rings added to the GDGT core structure can vary as a function of environmental conditions, such as changes in growth temperature. This physiological response enables cyclic GDGTs preserved in sediments to be employed as proxies for reconstructing past global and regional temperatures and to provide fundamental insights into ancient climate variability. Yet, confidence in GDGT-based paleotemperature proxies is hindered by uncertainty concerning the archaeal communities contributing to GDGT pools in modern environments and ambiguity in the environmental and physiological factors that affect GDGT cyclization in extant archaea. To properly constrain these uncertainties, a comprehensive understanding of GDGT biosynthesis is required. Here in this paper, we identify 2 GDGT ring synthases, GrsA and GrsB, essential for GDGT ring formation in Sulfolobus acidocaldarius . Both proteins are radical S-adenosylmethionine proteins, indicating that GDGT cyclization occurs through a free radical mechanism. In addition, we demonstrate that GrsA introduces rings specifically at the C-7 position of the core GDGT lipid, while GrsB cyclizes at the C-3 position, suggesting that cyclization patterns are differentially controlled by 2 separate enzymes and potentially influenced by distinct environmental factors. Finally, phylogenetic analyses of the Grs proteins reveal that marine Thaumarchaeota, and not Euryarchaeota, are the dominant source of cyclized GDGTs in open ocean settings, addressing a major source of uncertainty in GDGT-based paleotemperature proxy applications.

59 BASIC BIOLOGICAL SCIENCES↗

Spatiotemporal analysis identifies ABF2 and ABF3 as key hubs of endodermal response to nitrate

Nitrate is a nutrient and a potent signal that impacts global gene expression in plants. However, the regulatory factors controlling temporal and cell type–specific nitrate responses remain largely unknown. We assayed nitrate-responsive transcriptome changes in five major root cell types of the Arabidopsis thaliana root as a function of time. We found that gene-expression response to nitrate is dynamic and highly localized and predicted cell type–specific transcription factor (TF)–target interactions. Among cell types, the endodermis stands out as having the largest and most connected nitrate-regulatory gene network. ABF2 and ABF3 are major hubs for transcriptional responses in the endodermis cell layer. We experimentally validated TF–target interactions for ABF2 and ABF3 by chromatin immunoprecipitation followed by sequencing and a cell-based system to detect TF regulation genome-wide. Validated targets of ABF2 and ABF3 account for more than 50% of the nitrate-responsive transcriptome in the endodermis. Moreover, ABF2 and ABF3 are involved in nitrate-induced lateral root growth. Our approach offers an unprecedented spatiotemporal resolution of the root response to nitrate and identifies important components of cell-specific gene regulatory networks.

59 BASIC BIOLOGICAL SCIENCES↗

A protein phosphatase 1 specific phos phatase ta rgeting p eptide (PhosTAP) to identify the PP1 phosphatome

Phosphoprotein phosphatases (PPPs) are the key serine/threonine phosphatases that regulate all essential signaling cascades. In particular, Protein Phosphatase 1 (PP1) dephosphorylates ~80% of all ser/thr phosphorylation sites. Here, we developed a phosphatase targeting peptide (PhosTAP) that binds all PP1 isoforms and does so with a stronger affinity than any other known PP1 regulator. This PhosTAP can be used as a PP1 recruitment tool for Phosphorylation Targeting Chimera (PhosTAC)-type recruitment in in vitro and cellular experiments, as well as in phosphoproteomics experiments to identify PP1-specific substrates and phosphosites. The latter is especially important to further our understanding of cellular signaling, as the identification of substrates and especially phosphosites that are targeted by specific phosphatases lags behind that of their kinase counterparts. Using PhosTAP-based proteomics, we show that, counter to our current understanding, many PP1 regulators are also substrates, that the number of residues between regulator PP1-binding and phosphosites vary significantly, and that PP1 counteracts the activities of mitotic kinases. Finally, we also found that Haspin kinase is a direct substrate of PP1 and that its PP1-dependent dephosphorylation modulates its activity during anaphase. Together, we show that PP1-specific PhosTAPs are a powerful tool for +studying PP1 activity in vitro and in cells.

Science & Technology - Other Topics↗

Use of a neutralizing antibody helps identify structural features critical for binding of Clostridium difficile toxin TcdA to the host cell surface

Clostridium difficile is a clinically significant pathogen that causes mild-to-severe (and often recurrent) colon infections. Disease symptoms stem from the activities of two large, multidomain toxins known as TcdA and TcdB. The toxins can bind, enter, and perturb host cell function through a multistep mechanism of receptor binding, endocytosis, pore formation, autoproteolysis, and glucosyltransferase-mediated modification of host substrates. Monoclonal antibodies that neutralize toxin activity provide a survival benefit in preclinical animal models and prevent recurrent infections in human clinical trials. However, the molecular mechanisms involved in these neutralizing activities are unclear. To this end, we performed structural studies on a neutralizing monoclonal antibody, PA50, a humanized mAb with both potent and broad-spectrum neutralizing activity, in complex with TcdA. Electron microscopy imaging and multiangle light-scattering analysis revealed that PA50 binds multiple sites on the TcdA C-terminal combined repetitive oligopeptides (CROPs) domain. A crystal structure of two PA50 Fabs bound to a segment of the TcdA CROPs helped define a conserved epitope that is distinct from previously identified carbohydrate-binding sites. Binding of TcdA to the host cell surface was directly blocked by either PA50 mAb or Fab and suggested that receptor blockade is the mechanism by which PA50 neutralizes TcdA. These findings highlight the importance of the CROPs C terminus in cell-surface binding and a role for neutralizing antibodies in defining structural features critical to a pathogen's mechanism of action. We conclude that PA50 protects host cells by blocking the binding of TcdA to cell surfaces.

59 BASIC BIOLOGICAL SCIENCES↗

Identifying Inconsistencies in Fission Product Yield Evaluations with Prompt Neutron Emission

Here, we present a self-consistency analysis of fission product yield evaluations. Anomalous yields are determined using a series of simple conservation checks and comparing charge distributions with common parameterizations. The summed average prompt neutron multiplicity for both products as a function of the heavy product mass is derived directly from the independent fission product yields with a procedure utilizing average charge conservation. This procedure is validated with Monte Carlo simulations of the de-excitation of the fission fragments in a Hauser-Feshbach statistical decay framework. The derived is compared with experimental data, when available, and then used to determine the prompt neutron multiplicity for the various evaluations. The propagated errors on from the average charge conservation method are significantly lower than the simple summation rules, which reveals that some evaluations are inconsistent with prompt neutron data. We propose possible solutions to remedy the observed inconsistencies and identify sources of the observed differences in between the various evaluation libraries.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Identifying candidate structured RNAs in CRISPR operons

Noncoding RNAs with secondary structures play important roles in CRISPR-Cas systems. Many of these structures likely remain undiscovered. We used a large-scale comparative genomics approach to predict 156 novel candidate structured RNAs from 36,111 CRISPR-Cas systems. A number of these were found to overlap with coding genes, including palindromic candidates that overlapped with a variety of Cas genes in type I and III systems. Among these 156 candidates, we identified 46 new models of CRISPR direct repeats and 1 tracrRNA. This tracrRNA model occasionally overlapped with predicted cas9 coding regions, emphasizing the importance of expanding our search windows for novel structure RNAs in coding regions. We also demonstrated that the antirepeat sequence in this tracrRNA model can be used to accurately assign thousands of predicted CRISPR arrays to type II-C systems. This study highlights the importance of unbiased identification of candidate structured RNAs across CRISPR-Cas systems.

59 BASIC BIOLOGICAL SCIENCES↗