1,723 research outputs found

    Cyclooxygenase 2 promotes cell survival by stimulation of dynein light chain expression and inhibition of neuronal nitric oxide synthase activity

    Get PDF
    Cyclooxygenase 2 (COX-2) inhibits nerve growth factor (NGF) withdrawal apoptosis in differentiated PC12 cells. The inhibition of apoptosis by COX-2 was concomitant with prevention of caspase 3 activation. To understand how COX-2 prevents apoptosis, we used cDNA expression arrays to determine whether COX-2 regulates differential expression of apoptosis-related genes. The expression of dynein light chain (DLC) (also known as protein inhibitor of neuronal nitric oxide synthase [PIN]) was significantly stimulated in PC12 cells overexpressing COX-2. The COX-2-dependent stimulation of DLC expression was, at least in part, mediated by prostaglandin E(2). Overexpression of DLC also inhibited NGF withdrawal apoptosis in differentiated PC12 cells. Stimulation of DLC expression resulted in an increased association of DLC/PIN with neuronal nitric oxide synthase (nNOS), thereby reducing nNOS activity. Furthermore, nNOS expression and activity were significantly increased in differentiated PC12 cells after NGF withdrawal. This increased nNOS activity as well as increased nNOS dimer after NGF withdrawal were inhibited by COX-2 or DLC/PIN overexpression. An nNOS inhibitor or a membrane-permeable superoxide dismutase (SOD) mimetic protected differentiated PC12 cells from NGF withdrawal apoptosis. In contrast, NO donors induced apoptosis in differentiated PC12 cells and potentiated apoptosis induced by NGF withdrawal. The protective effects of COX-2 on apoptosis induced by NGF withdrawal were also overcome by NO donors. These findings suggest that COX-2 promotes cell survival by a mechanism linking increased expression of prosurvival genes coupled to inhibition of NO- and superoxide-mediated apoptosis

    PoTeC: A German Naturalistic Eye-tracking-while-reading Corpus

    Full text link
    The Potsdam Textbook Corpus (PoTeC) is a naturalistic eye-tracking-while-reading corpus containing data from 75 participants reading 12 scientific texts. PoTeC is the first naturalistic eye-tracking-while-reading corpus that contains eye-movements from domain-experts as well as novices in a within-participant manipulation: It is based on a 2x2x2 fully-crossed factorial design which includes the participants' level of study and the participants' discipline of study as between-subject factors and the text domain as a within-subject factor. The participants' reading comprehension was assessed by a series of text comprehension questions and their domain knowledge was tested by text-independent background questions for each of the texts. The materials are annotated for a variety of linguistic features at different levels. We envision PoTeC to be used for a wide range of studies including but not limited to analyses of expert and non-expert reading strategies. The corpus and all the accompanying data at all stages of the preprocessing pipeline and all code used to preprocess the data are made available via GitHub: https://github.com/DiLi-Lab/PoTeC

    ScanDL: A Diffusion Model for Generating Synthetic Scanpaths on Texts

    Get PDF
    Eye movements in reading play a crucial role in psycholinguistic research studying the cognitive mechanisms underlying human language processing. More recently, the tight coupling between eye movements and cognition has also been leveraged for language-related machine learning tasks such as the interpretability, enhancement, and pre-training of language models, as well as the inference of reader- and text-specific properties. However, scarcity of eye movement data and its unavailability at application time poses a major challenge for this line of research. Initially, this problem was tackled by resorting to cognitive models for synthesizing eye movement data. However, for the sole purpose of generating human-like scanpaths, purely data-driven machine-learning-based methods have proven to be more suitable. Following recent advances in adapting diffusion processes to discrete data, we propose ScanDL, a novel discrete sequence-to-sequence diffusion model that generates synthetic scanpaths on texts. By leveraging pre-trained word representations and jointly embedding both the stimulus text and the fixation sequence, our model captures multi-modal interactions between the two inputs. We evaluate ScanDL within- and across-dataset and demonstrate that it significantly outperforms state-of-the-art scanpath generation methods. Finally, we provide an extensive psycholinguistic analysis that underlines the model's ability to exhibit human-like reading behavior. Our implementation is made available at https://github.com/DiLi-Lab/ScanDL

    ScanDL: A Diffusion Model for Generating Synthetic Scanpaths on Texts

    Full text link
    Eye movements in reading play a crucial role in psycholinguistic research studying the cognitive mechanisms underlying human language processing. More recently, the tight coupling between eye movements and cognition has also been leveraged for language-related machine learning tasks such as the interpretability, enhancement, and pre-training of language models, as well as the inference of reader- and text-specific properties. However, scarcity of eye movement data and its unavailability at application time poses a major challenge for this line of research. Initially, this problem was tackled by resorting to cognitive models for synthesizing eye movement data. However, for the sole purpose of generating human-like scanpaths, purely data-driven machine-learning-based methods have proven to be more suitable. Following recent advances in adapting diffusion processes to discrete data, we propose ScanDL, a novel discrete sequence-to-sequence diffusion model that generates synthetic scanpaths on texts. By leveraging pre-trained word representations and jointly embedding both the stimulus text and the fixation sequence, our model captures multi-modal interactions between the two inputs. We evaluate ScanDL within- and across-dataset and demonstrate that it significantly outperforms state-of-the-art scanpath generation methods. Finally, we provide an extensive psycholinguistic analysis that underlines the model's ability to exhibit human-like reading behavior. Our implementation is made available at https://github.com/DiLi-Lab/ScanDL.Comment: EMNLP 202

    The Effectiveness of Exercise Interventions for the Management of Frailty: A Systematic Review

    Get PDF
    This systematic review examines the effectiveness of current exercise interventions for the management of frailty. Eight electronic databases were searched for randomized controlled trials that identified their participants as “frail” either in the title, abstract, and/or text and included exercise as an independent component of the intervention. Three of the 47 included studies utilized a validated definition of frailty to categorize participants. Emerging evidence suggests that exercise has a positive impact on some physical determinants and on all functional ability outcomes reported in this systematic review. Exercise programs that optimize the health of frail older adults seem to be different from those recommended for healthy older adults. There was a paucity of evidence to characterize the most beneficial exercise program for this population. However, multicomponent training interventions, of long duration (≥5 months), performed three times per week, for 30–45 minutes per session, generally had superior outcomes than other exercise programs. In conclusion, structured exercise training seems to have a positive impact on frail older adults and may be used for the management of frailty

    Competition of crystal field splitting and Hund's rule coupling in two-orbital magnetic metal-insulator transitions

    Full text link
    Competition of crystal field splitting and Hund's rule coupling in magnetic metal-insulator transitions of half-filled two-orbital Hubbard model is investigated by multi-orbital slave-boson mean field theory. We show that with the increase of Coulomb correlation, the system firstly transits from a paramagnetic (PM) metal to a {\it N\'{e}el} antiferromagnetic (AFM) Mott insulator, or a nonmagnetic orbital insulator, depending on the competition of crystal field splitting and the Hund's rule coupling. The different AFM Mott insulator, PM metal and orbital insulating phase are none, partially and fully orbital polarized, respectively. For a small JHJ_{H} and a finite crystal field, the orbital insulator is robust. Although the system is nonmagnetic, the phase boundary of the orbital insulator transition obviously shifts to the small UU regime after the magnetic correlations is taken into account. These results demonstrate that large crystal field splitting favors the formation of the orbital insulating phase, while large Hund's rule coupling tends to destroy it, driving the low-spin to high-spin transition.Comment: 4 pages, 4 figure

    The Magic Number Problem for Subregular Language Families

    Full text link
    We investigate the magic number problem, that is, the question whether there exists a minimal n-state nondeterministic finite automaton (NFA) whose equivalent minimal deterministic finite automaton (DFA) has alpha states, for all n and alpha satisfying n less or equal to alpha less or equal to exp(2,n). A number alpha not satisfying this condition is called a magic number (for n). It was shown in [11] that no magic numbers exist for general regular languages, while in [5] trivial and non-trivial magic numbers for unary regular languages were identified. We obtain similar results for automata accepting subregular languages like, for example, combinational languages, star-free, prefix-, suffix-, and infix-closed languages, and prefix-, suffix-, and infix-free languages, showing that there are only trivial magic numbers, when they exist. For finite languages we obtain some partial results showing that certain numbers are non-magic.Comment: In Proceedings DCFS 2010, arXiv:1008.127

    Identification of a 1-deoxy-D-xylulose-5-phosphate synthase (DXS) mutant with improved crystallographic properties

    Get PDF
    In this report, we describe a truncated Deinococcus radiodurans 1-deoxy-D-xylulose-5-phosphate synthase (DXS) protein that retains enzymatic activity, while slowing protein degradation and showing improved crystallization properties. With modern drug-design approaches relying heavily on the elucidation of atomic interactions of potential new drugs with their targets, the need for co-crystal structures with the compounds of interest is high. DXS itself is a promising drug target, as it catalyzes the first reaction in the 2-C-methyl-D-erythritol 4-phosphate (MEP)-pathway for the biosynthesis of the universal precursors of terpenes, which are essential secondary metabolites. In contrast to many bacteria and pathogens, which employ the MEP pathway, mammals use the distinct mevalonate-pathway for the biosynthesis of these precursors, which makes all enzymes of the MEP-pathway potential new targets for the development of anti-infectives. However, crystallization of DXS has proven to be challenging: while the first X-ray structures from Escherichia coli and D. radiodurans were solved in 2004, since then only two additions have been made in 2019 that were obtained under anoxic conditions. The presented site of truncation can potentially also be transferred to other homologues, opening up the possibility for the determination of crystal structures from pathogenic species, which until now could not be crystallized. This manuscript also provides a further example that truncation of a variable region of a protein can lead to improved structural data
    corecore