ChatGPT is a Potential Zero-Shot Dependency Parser

Pre-trained language models have been widely used in dependency parsing task and have achieved significant improvements in parser performance. However, it remains an understudied question whether pre-trained language models can spontaneously exhibit the ability of dependency parsing without introducing additional parser structure in the zero-shot scenario. In this paper, we propose to explore the dependency parsing ability of large language models such as ChatGPT and conduct linguistic analysis. The experimental results demonstrate that ChatGPT is a potential zero-shot dependency parser, and the linguistic analysis also shows some unique preferences in parsing outputs.Comment: 10 page

Effects of multiple occupancy and inter-particle interactions on selective transport through narrow channels: theory versus experiment

Many biological and artificial transport channels function without direct input of metabolic energy during a transport event and without structural rearrangements involving transitions from a 'closed' to an 'open' state. Nevertheless, such channels are able to maintain efficient and selective transport. It has been proposed that attractive interactions between the transported molecules and the channel can increase the transport efficiency and that the selectivity of such channels can be based on the strength of the interaction of the specifically transported molecules with the channel. Herein, we study the transport through narrow channels in a framework of a general kinetic theory, which naturally incorporates multi-particle occupancy of the channel and non-single-file transport. We study how the transport efficiency and the probability of translocation through the channel are affected by inter-particle interactions in the confined space inside the channel, and establish conditions for selective transport. We compare the predictions of the model with the available experimental data - and find good semi-quantitative agreement. Finally, we discuss applications of the theory to the design of artificial nano-molecular sieves.Comment: 27 pages, 6 figures, 1 Appendix, in press in Biophysical Journa

Kinetic modelling of hydrogen transfer deoxygenation of a prototypical fatty acid over a bimetallic Pd60Cu40 catalyst: an investigation of the surface reaction mechanism and rate limiting step

Herein, for the first time, we demonstrate a novel continuous flow process involving the application of tetralin as a hydrogendonor solvent for the catalytic conversion of oleic acid to diesel-like hydrocarbons, using an efficient and stable carbonsupported bimetallic PdCu catalyst. Using Pd60Cu40/C, where 60:40 is the molar ratio of each metal, at optimum reactionconditions (360 °C and WHSV = 1 h-1), 90.5% oleic acid conversion and 80.5% selectivity to C17 and C18 paraffinic hydrocarbonswere achieved. Furthermore, a comprehensive mechanistic based kinetic modelling - considering power rate law, L-H andE-R models was conducted. Kinetic expressions derived from the three kinetic models were investigated in rate data fittingthrough nonlinear regression using a Levenberg-Marquardt algorithm. Based on the statistical discrimination criteria, theexperimental data of the dehydrogenation reaction of tetralin was best fitted by an L-H rate equation assuming the surfacereaction as the rate controlling step. On the contrary, the kinetic data of the oleic acid deoxygenation reaction was wellcorrelated with an L-H rate equation assuming single site adsorption of oleic acid with dissociative H2 adsorption. It wasfound that the rate limiting step of the overall reaction was the hydrogenation of oleic acid with an activation energy of 75.0± 5.1 kJ mol-1 whereas the dehydrogenation of tetralin had a lower activation energy of 66.4 ± 2.7 kJ mol-1

Quantitative trait loci mapping for lameness associated phenotypes in Holstein Friesian dairy cattle

Lameness represents a significant challenge for the dairy cattle industry, resulting in economic losses and reduced animal health and welfare. The existence of underlying genomic variation for lameness associated traits has the potential to improve selection strategies by using genomic markers. Therefore, the aim of this study was to identify genomic regions and potential candidate genes associated with lameness traits. Lameness related lesions and digital cushion thickness were studied using records collected by our research team, farm records, and a combination of both. Genome-wide analyses were performed to identify significant genomic effects, and a combination of single SNP association analysis and regional heritability mapping was used to identify associated genomic regions. Significant genomic effects were identified for several lameness related traits: Two genomic regions were identified on chromosome 3 associated with digital dermatitis and interdigital hyperplasia, one genomic region on chromosome 23 associated with interdigital hyperplasia, and one genomic region on chromosome 2 associated with sole haemorrhage. Candidate genes in those regions are mainly related to immune response and fibroblast proliferation. Quantitative trait loci (QTL) identified in this study could enlighten the understanding of lameness pathogenesis, providing an opportunity to improve health and welfare in dairy cattle with the addition of these regions into selection programs

Ionic Interactions in Biological and Physical Systems: a Variational Treatment

Chemistry is about chemical reactions. Chemistry is about electrons changing their configurations as atoms and molecules react. Chemistry studies reactions as if they occurred in ideal infinitely dilute solutions. But most reactions occur in nonideal solutions. Then everything (charged) interacts with everything else (charged) through the electric field, which is short and long range extending to boundaries of the system. Mathematics has recently been developed to deal with interacting systems of this sort. The variational theory of complex fluids has spawned the theory of liquid crystals. In my view, ionic solutions should be viewed as complex fluids. In both biology and electrochemistry ionic solutions are mixtures highly concentrated (~10M) where they are most important, near electrodes, nucleic acids, enzymes, and ion channels. Calcium is always involved in biological solutions because its concentration in a particular location is the signal that controls many biological functions. Such interacting systems are not simple fluids, and it is no wonder that analysis of interactions, such as the Hofmeister series, rooted in that tradition, has not succeeded as one would hope. We present a variational treatment of hard spheres in a frictional dielectric. The theory automatically extends to spatially nonuniform boundary conditions and the nonequilibrium systems and flows they produce. The theory is unavoidably self-consistent since differential equations are derived (not assumed) from models of (Helmholtz free) energy and dissipation of the electrolyte. The origin of the Hofmeister series is (in my view) an inverse problem that becomes well posed when enough data from disjoint experimental traditions are interpreted with a self-consistent theory.Comment: As prepared for Faraday Discussion, Pavel Jungwirth Organizer, 3 - 5 September 2012, Queens College Oxford, UK on Ion Specific Hofmeister Effects. Version 2 has significant typo corrections in eq. 1 and eq. 4, and has been reformatted to be easier to rea

Different Rho GTPase–dependent signaling pathways initiate sequential steps in the consolidation of long-term potentiation

The releasable factor adenosine blocks the formation of long-term potentiation (LTP). These experiments used this observation to uncover the synaptic processes that stabilize the potentiation effect. Brief adenosine infusion blocked stimulation-induced actin polymerization within dendritic spines along with LTP itself in control rat hippocampal slices but not in those pretreated with the actin filament stabilizer jasplakinolide. Adenosine also blocked activity-driven phosphorylation of synaptic cofilin but not of synaptic p21-activated kinase (PAK). A search for the upstream origins of these effects showed that adenosine suppressed RhoA activity but only modestly affected Rac and Cdc42. A RhoA kinase (ROCK) inhibitor reproduced adenosine's effects on cofilin phosphorylation, spine actin polymerization, and LTP, whereas a Rac inhibitor did not. However, inhibitors of Rac or PAK did prolong LTP's vulnerability to reversal by latrunculin, a toxin which blocks actin filament assembly. Thus, LTP induction initiates two synaptic signaling cascades: one (RhoA-ROCK-cofilin) leads to actin polymerization, whereas the other (Rac-PAK) stabilizes the newly formed filaments

Electroactive smart materials: novel tools for tailoring bacteria behavior and fight antimicrobial resistance

Despite being very simple organisms, bacteria possess an outstanding ability to adapt to different environments. Their long evolutionary history, being exposed to vastly different physicochemical surroundings, allowed them to detect and respond to a wide range of signals including biochemical, mechanical, electrical, and magnetic ones. Taking into consideration their adapting mechanisms, it is expected that novel materials able to provide bacteria with specific stimuli in a biomimetic context may tailor their behavior and make them suitable for specific applications in terms of anti-microbial and pro-microbial approaches. This review maintains that electroactive smart materials will be a future approach to be explored in microbiology to obtain novel strategies for fighting the emergence of live threatening antibiotic resistance.This work was supported by national funds through FCT (Fundação para a Ciência e Tecnologia) and by ERDF through COMPETE2020—Programa Operacional Competitividade e Internacionalização (POCI) in the framework of the Strategic Programs UID/FIS/04650/2019. This work was also supported by FCT through project LungChek ENMed/0049/2016. MF and EC thank FCT for the SFRH/BPD/121464/2016 and SFRH/BD/145455/2019 grant, respectively. Finally, the authors acknowledge funding by the Spanish Ministry of Economy and Competitiveness (MINECO) through the project MAT201676039-C4-3-R (AEI/FEDER, UE) and from the Basque Government Industry and Education Departments under the ELKARTEK and PIBA (PIBA-2018-06) programs, respectively.info:eu-repo/semantics/publishedVersio

A Structural Model of the Pore-Forming Region of the Skeletal Muscle Ryanodine Receptor (RyR1)

Ryanodine receptors (RyRs) are ion channels that regulate muscle contraction by releasing calcium ions from intracellular stores into the cytoplasm. Mutations in skeletal muscle RyR (RyR1) give rise to congenital diseases such as central core disease. The absence of high-resolution structures of RyR1 has limited our understanding of channel function and disease mechanisms at the molecular level. Here, we report a structural model of the pore-forming region of RyR1. Molecular dynamics simulations show high ion binding to putative pore residues D4899, E4900, D4938, and D4945, which are experimentally known to be critical for channel conductance and selectivity. We also observe preferential localization of Ca2+ over K+ in the selectivity filter of RyR1. Simulations of RyR1-D4899Q mutant show a loss of preference to Ca2+ in the selectivity filter as seen experimentally. Electrophysiological experiments on a central core disease mutant, RyR1-G4898R, show constitutively open channels that conduct K+ but not Ca2+. Our simulations with G4898R likewise show a decrease in the preference of Ca2+ over K+ in the selectivity filter. Together, the computational and experimental results shed light on ion conductance and selectivity of RyR1 at an atomistic level