Miracle-dz/UniFAR-FTUs huggingface dataset:
DAC Is Involved in the Accumulation of the Cytochrome b6/f Complex in Arabidopsis1[W][OA]

The biogenesis and assembly of photosynthetic multisubunit protein complexes is assisted by a series of nucleus-encoded auxiliary protein factors. In this study, we characterize the dac mutant of Arabidopsis (Arabidopsis thaliana), which shows a severe defect in the accumulation of the cytochrome b6/f complex, and provide evidence suggesting that the efficiency of cytochrome b6/f complex assembly is affected in the mutant. DAC is a thylakoid membrane protein with two predicted transmembrane domains that is conserved from cyanobacteria to vascular plants. Yeast (Saccharomyces cerevisiae) two-hybrid and coimmunoprecipitation analyses revealed a specific interaction between DAC and PetD, a subunit of the cytochrome b6/f complex. However, DAC was found not to be an intrinsic component of the cytochrome b6/f complex. In vivo chloroplast protein labeling experiments showed that the labeling rates of the PetD and cytochrome f proteins were greatly reduced, whereas that of the cytochrome b6 protein remained normal in the dac mutant. DAC appears to be a novel factor involved in the assembly/stabilization of the cytochrome b6/f complex, possibly through interaction with the PetD protein.
Protecting effect of caffeine against vinblastine (an anticancer drug) induced genotoxicity in mice

Abstract Vinblastine a DNA non-intercalating agent has wide application against several human neoplasms, and found to cause cytogenotoxicity. In this study, clastogenotoxicity of vinblastine (1.5 mg/kg b w) and its prevention by caffeine at different doses (25, 50 and 100 mg/kg b w) administered intraperitoneally was assessed in in vivo mice. It was found that micronucleus level had decreased significantly (up to 28.8%) in 100 mg caffeine treated group at 30 h post treatment. However, it did not exhibit protective effect against chromosomal aberration in spaermatogonial cells at 24 h post treatment. The frequencies of aberrant primary spermatocytes had decreased significantly in 25 and 100 mg caffeine at 4th week of post treatment. Similarly, in 100 mg of caffeine administered, abnormal sperm level had reduced (4.01%) significantly at 8th week post treatment. Thus, caffeine decreased the vinblastine induced chromosomal aberrations and mitotic index in bone marrow cells. In conclusion, this study shows that caffeine exerts protective effect against vinblastin induced cytogenotoxicity. Further studies on molecular mechanism are interesting in order to develop it as an effective drug in cancer chemotherapy.
Physiological Roles of the Dual Phosphate Transporter Systems in Low and High Phosphate Conditions and in Capsule Maintenance of Streptococcus pneumoniae D39

Unlike most bacteria, Streptococcus pneumoniae (pneumococcus) has two evolutionarily distinct ABC transporters (Pst1 and Pst2) for inorganic phosphate (Pi) uptake. The genes encoding a two-component regulator (PnpRS) are located immediately upstream of the pst1 operon. Both the pst1 and pst2 operons encode putative PhoU-family regulators (PhoU1 and PhoU2) at their ends. This study addresses why S. pneumoniae contains dual Pi uptake systems and the regulation and contribution of the Pst1 and Pst2 systems in conditions of high (mM) Pi amount and low (μM) Pi amount. We show that in unencapsulated mutants, both pst1 and pst2 can be deleted, and Pi is taken up by a third Na+/Pi co-transporter, designated as NptA. In contrast, either pst1 or pst2 is unexpectedly required for the growth of capsule producing strains. We used a combination of mutational analysis, transcript level determinations by qRT-PCR and RNA-Seq, assays for cellular PnpR~P amounts by SDS-PAGE, and pulse-Pi uptake experiments to study the regulation of Pi uptake. In high Pi medium, PhoU2 serves as the master negative regulator of Pst2 transporter function and PnpR~P levels (post-transcriptionally). ΔphoU2 mutants have high PnpR~P levels and induction of the pst1 operon, poor growth, and sensitivity to antibiotics, possibly due to high Pi accumulation. In low Pi medium, Pst2 is still active, but PnpR~P amount and pst1 operon levels increase. Together, these results support a model in which pneumococcus maintains high Pi transport in high and low Pi conditions that is required for optimal capsule biosynthesis.
Adipocyte Fatty Acid Storage Factors Enhance Subcutaneous Fat Storage in Postmenopausal Women

Increases in weight have been associated with corresponding increases in insulin resistance in postmenopausal women. Although estrogen has significant impact on body fat and body fat distribution, the cellular mechanisms that influence this process are not yet known. We measured adipose tissue fatty acid (FA) storage and FA storage factors in 12 premenopausal and 11 postmenopausal women matched for age and body composition. Postmenopausal women had lower postprandial FA oxidation (indirect calorimetry), greater meal FA, and direct free FA (FFA) storage than premenopausal women, including two-fold greater meal FA storage in the femoral depot. The fed/fasted activities of adipose tissue lipoprotein lipase were not significantly different between premenopausal and postmenopausal women. In contrast, adipocyte acyl-CoA synthetase and diacylglycerol acyltransferase activities in postmenopausal women were significantly upregulated and were positively correlated with direct FFA storage rates. These findings suggest that the propensity for subcutaneous adipose tissue FA storage is increased in postmenopausal women, more so from changes in adipocyte FA storage factors than from adipose tissue lipoprotein lipase activity. Our results suggest that female sex steroids, most likely estrogen, have important effects on adipose tissue FA storage and FA oxidation that could promote fat gain in postmenopausal women.
Impact of nutrition on the pathophysiology of bovine trypanosomiasis

Trypanosomiasis is a major veterinary problem over much of sub-Saharan Africa and is frequently associated with undernutrition. There is growing evidence that nutrition can have a profound effect on the pathophysiological features of animal trypanosomiasis. These features include anaemia, pyrexia, body weight changes, reduced feed intake and diminished productivity including reduced draught work output, milk yield and reproductive capacity. Anaemia is a principal characteristic of trypanosomiasis and the rate at which it develops is influenced by both protein and energy intakes. Pyrexia is associated with increased energy demands for maintenance which is ultimately manifested by reductions in voluntary activity levels and productivity. Weight changes in trypanosomiasis are markedly influenced by the levels of protein intake. High intakes allow infected animals to grow at the same rate as uninfected controls providing energy intake is adequate whilst low energy levels can exacerbate the adverse effects of trypanosomiasis on body weight. Reductions in feed intake are less apparent in animals which are provided with high protein diets and where intake is limited by the disease animals will often exhibit preferential selection of higher quality browse. Further studies are required to evaluate the minimum levels of protein and energy supplementation required to ameliorate the adverse effect of trypanosomiasis, the nature and quality of protein supplement to achieve these benefits and the influence these have on digestive physiology.
Motion Segmentation in the Presence of Outlying, Incomplete, or Corrupted Trajectories

In this paper, we study the problem of segmenting tracked feature point trajectories of multiple moving objects in an image sequence. Using the affine camera model, this problem can be cast as the problem of segmenting samples drawn from multiple linear subspaces. In practice, due to limitations of the tracker, occlusions, and the presence of nonrigid objects in the scene, the obtained motion trajectories may contain grossly mistracked features, missing entries, or corrupted entries. In this paper, we develop a robust subspace separation scheme that deals with these practical issues in a unified mathematical framework. Our methods draw strong connections between lossy compression, rank minimization, and sparse representation. We test our methods extensively on the Hopkins155 motion segmentation database and other motion sequences with outliers and missing data. We compare the performance of our methods to state-of-the-art motion segmentation methods based on expectation-maximization and spectral clustering. For data without outliers or missing information, the results of our methods are on par with the state-of-the-art results and, in many cases, exceed them. In addition, our methods give surprisingly good performance in the presence of the three types of pathological trajectories mentioned above. All code and results are publicly available at http://perception.csl. uiuc.edu/coding/motion/.
P Personality and Memory

Personality influences our emotions, thoughts, and memories. The salience of our emotional experiences, the valence of emotional memories we recall, and how we dwell on these memories are influenced by the unique characteristics that define us as individuals. Indeed, empirical evidence suggests a critical impact of emotion on cognition and a high variability of these effects between individuals with different personality traits (Haas and Canli 2008). The focus here is on the role of personality traits in the impact of emotion on memory. It is well established that emotional events are better remembered than neutral ones and that this effect is typically observed in relation to long-term episodic memory (EM) – i.e., memory for specific events experienced in everyday life (Dolcos et al. 2012). However, emotions can also interfere with working memory (WM) – i.e., temporary maintenance and manipulation of information – when emotions are presented as distraction that interferes with one’s focus on the task at hand (Iordan et al. 2013). Importantly, these opposing effects of emotion on memory can be influenced by chronically activated biases in attention and emotion processing associated with more general personality traits. For instance, extraversion, a personality trait characterized by sociability and a tendency to experience more positive affect (John and Srivastava 1999), is associated with biases toward positive information (Derryberry and Reed 1994). In contrast, neuroticism and anxiety, personality traits characterized by heightened sensitivity and reactivity to negative emotional stimuli (Ormel et al. 2013), typically reflecting responses to challenging situations eliciting perceived or anticipated stress, are associated with biases toward negative information (MacLeod and Mathews 1988; Reed
Rapid increase in dispersal during range expansion in the invasive ladybird Harmonia axyridis

The evolutionary trajectories associated with demographic, genetic and spatial disequilibrium have become an issue of growing interest in population biology. Invasive species provide unique opportunities to explore the impact of recent range expansion on life‐history traits, making it possible to test for a spatial arrangement of dispersal abilities along the expanding range, in particular. We carried out controlled experiments in laboratory conditions to test the hypothesis of an increase in dispersal capacity with range expansion in Harmonia axyridis, a ladybird that has been invading Europe since 2001. We found a marked increase in the flight speed of the insects from the core to the front of the invasion range in two independent sampling transects. By contrast, we found that two other traits associated with dispersal (endurance and motivation to fly off) did not follow the same spatial gradient. Our results provide a striking illustration of the way in which predictable directional genetic changes may occur rapidly for some traits associated with dispersal during biological invasions. We discuss the consequences of our results for invasion dynamics and the evolutionary outcomes of spatially expanding populations.
New topologies for genetic search space

We propose three distance measures for genetic search space. One is a distance measure in the population space that is useful for understanding the working mechanism of genetic algorithms. Another is a distance measure in the solution space for K-grouping problems. This can be used for normalization in crossover. The third is a level distance measure for genetic algorithms, which is useful for measuring problem difficulty with respect to genetic algorithms. We show that the proposed measures are metrics and the measures are efficiently computed.
Novel Ensemble Predictor for Gram-Positive Bacterial Protein Sequences

In the fields of bioinformatics and drug discovery, prediction of bacterial proteins is an important research. We proposed a novel classifier ensemble scheme for the prediction of Gram-positive bacterial protein. The proposed methodology exploits diversity in decision space through different machine learning techniques. However, diversity in feature spaces is exploited using physicochemical properties of amino acids compounds. Further, three different classification models are employed to further explore diversity in decision space. First individual ensemble (IE) predictors are developed using a single feature extraction technique. Their results are then combined to develop improved performance composite ensemble (CE) for Gram-positive bacterial protein sequences. The predictive performance of IE and CE predictors are evaluated for two standard datasets. We investigated the prediction results of our novel scheme for this problem is better than any previous approach so far to the best of our knowledge.
ZipML: Training Linear Models with End-to-End Low Precision, and a Little Bit of Deep Learning

Recently there has been significant interest in training machine-learning models at low precision: by reducing precision, one can reduce computation and communication by one order of magnitude. We examine training at reduced precision, both from a theoretical and practical perspective, and ask: is it possible to train models at end-to-end low precision with provable guarantees? Can this lead to consistent order-ofmagnitude speedups? We mainly focus on linear models, and the answer is yes for linear models. We develop a simple framework called ZipML based on one simple but novel strategy called double sampling. Our ZipML framework is able to execute training at low precision with no bias, guaranteeing convergence, whereas naive quantization would introduce significant bias. We validate our framework across a range of applications, and show that it enables an FPGA prototype that is up to 6.5× faster than an implementation using full 32-bit precision. We further develop a variance-optimal stochastic quantization strategy and show that it can make a significant difference in a variety of settings. When applied to linear models together with double sampling, we save up to another 1.7× in data movement compared with uniform quantization. When training deep networks with quantized models, we achieve higher accuracy than the state-of-theart XNOR-Net. ETH Zurich, Switzerland Massachusetts Institute of Technology, USA IST Austria, Austria University of Rochester, USA. Correspondence to: Hantian Zhang <hantian.zhang@inf.ethz. ch>, Ce Zhang <ce.zhang@inf.ethz. ch>. Proceedings of the 34 th International Conference on Machine Learning, Sydney, Australia, PMLR 70, 2017. Copyright 2017 by the author(s). (a) Linear Regression (c) 3D Reconstruction 32Bit 12Bit (b) FPGA Speed Up (d) Deep Learning Machine Learning Models Data Movement Channels Speed up because of our techniques Gradient Input Samples Model Linear Models De Sa et la. , Alistarh et al., . 1. Double Sampling 2. Data-Optimal Encoding Stochastic Rounding Very Significant Speed up (Up to 10x) Deep Learning Courbariaux et al., Rastegari et al., . Data-Optimal Encoding Significant Speed up 0 25 50 75 100 32-bit Full Precision Double Sampling 4-bit #Epochs Tr ai ni ng L os s #Epochs (a) Linear Regression (b) LS-SVM 0 25 50 75 100 . 3
Identification of virulent Rhodococcus equi by amplification of gene coding for 15- to 17-kilodalton antigens

During a survey of the prevalence of virulent Rhodococcus equi at horse-breeding farms by plasmid and protein profiles, cryptic plasmids of various sizes were found in 66 (3.8%) of 1,725 isolates from feces of horses and 129 (5.9%) of 2,200 isolates from soil. Twenty-two isolates, which contained cryptic plasmids of different sizes, were found by plasmid profiles, and their protein profiles and mouse pathogenicities were examined. Of the 22 isolates, 7 were virulent R. equi, contained both virulence and cryptic plasmids, and expressed 15- to 17-kDa antigens. The remaining 15 isolates were avirulent and did not express the antigens: 6 strains contained cryptic plasmids of two different sizes and 9 strains contained cryptic plasmids of various sizes. A PCR assay was developed for the rapid identification of virulence plasmids of R. equi. Oligonucleotide primers, derived from the sequence of a gene coding for the 15- to 17-kDa virulence-associated antigens of R. equi, amplified a 564-bp product from all the tested isolates harboring a virulence plasmid. This PCR product hybridized with virulence plasmid DNA in the Southern hybridization assay. Virulence plasmid-cured derivatives and all of the tested isolates harboring cryptic plasmids only were negative. The PCR is a rapid, sensitive, and specific test for the identification of virulent R. equi from environmental isolates compared with standard techniques, such as plasmid and protein profiles and the mouse pathogenicity test, and is considered to be a useful tool for epidemiological studies.
A new approach to interdomain routing based on secure multi-party computation

Interdomain routing involves coordination among mutually distrustful parties, leading to the requirements that BGP provide policy autonomy, flexibility, and privacy. BGP provides these properties via the distributed execution of policy-based decisions during the iterative route computation process. This approach has poor convergence properties, makes planning and failover difficult, and is extremely difficult to change. To rectify these and other problems, we propose a radically different approach to interdomain-route computation, based on secure multi-party computation (SMPC). Our approach provides stronger privacy guarantees than BGP and enables the deployment of new policy paradigms. We report on an initial exploration of this idea and outline future directions for research.
Everyday perception for mobile manipulation in human environments

This work describes a modular perception system for mobile robotic manipulation which improves over time. The two key features of this system are the automatic adaption to its environment and the large set of available perception methods. In order to adapt to a changing environment, the system learns success statistics over executed perception tasks and acquires new perceptual models. The perception system can handle different perceptual tasks which are processed by an automatically selected triple of sensor, model and method. This triple is selected based on logical restrictions and the success statistics.
Learning Content Selection Rules for Generating Object Descriptions in Dialogue

A fundamental requirement of any task-oriented dialogue system is the ability to generate object descriptions that refer to objects in the task domain. The subproblem of content selection for object descriptions in task-oriented dialogue has been the focus of much previous work and a large number of models have been proposed. In this paper, we use the annotated COCONUT corpus of task-oriented design dialogues to develop feature sets based on Dale and Reiter's (1995) incremental model, Brennan and Clark's (1996) conceptual pact model, and Jordan's (2000b) intentional influences model, and use these feature sets in a machine learning experiment to automatically learn a model of content selection for object descriptions. Since Dale and Reiter's model requires a representation of discourse structure, the corpus annotations are used to derive a representation based on Grosz and Sidner's (1986) theory of the intentional structure of discourse, as well as two very simple representations of discourse structure based purely on recency. We then apply the rule-induction program RIPPER to train and test the content selection component of an object description generator on a set of 393 object descriptions from the corpus. To our knowledge, this is the first reported experiment of a trainable content selection component for object description generation in dialogue. Three separate content selection models that are based on the three theoretical models, all independently achieve accuracies significantly above the MAJORITY CLASS baseline (17%) on unseen test data, with the intentional influences model (42.4%) performing significantly better than either the incremental model (30.4%) or the conceptual pact model (28.9%). But the best performing models combine all the feature sets, achieving accuracies near 60%. Surprisingly, a simple recency-based representation of discourse structure does as well as one based on intentional structure. To our knowledge, this is also the first empirical comparison of a representation of Grosz and Sidner's model of discourse structure with a simpler model for any generation task.
Stimulated single‐cell force spectroscopy to quantify cell adhesion receptor crosstalk

To control their attachment to substrates and other cells, cells regulate their adhesion receptors. One regulatory process is receptor crosstalk, where the binding of one type of cell adhesion molecule influences the activity of another type. To identify such crosstalk and gain insight into their mechanisms, we developed the stimulated single‐cell force spectroscopy assay. In this assay, the influence of a cells adhesion to one substrate on the strength of its adhesion to a second substrate is examined. The assay quantifies the adhesion of the cell and the contributions of specific adhesion receptors. This allows mechanisms by which the adhesion is regulated to be determined. Using the assay we identified crosstalk between collagen‐binding integrin α1β1 and fibronectin‐binding integrin α5β1 in HeLa cells. This crosstalk was unidirectional, from integrin α1β1 to integrin α5β1, and functioned by regulating the endocytosis of integrin α5β1. The single‐cell assay should be expandable for the screening and quantification of crosstalk between various cell adhesion molecules and other cell surface receptors.
MIMO decoding based on stochastic reconstruction from multiple projections

Least squares (LS) fitting is one of the most fundamental techniques in science and engineering. It is used to estimate parameters from multiple noisy observations. In many problems the parameters are known a-priori to be bounded integer valued, or they come from a finite set of values on an arbitrary finite lattice. In this case finding the closest vector becomes NP-Hard problem. In this paper we propose a novel algorithm, the Tomographic Least Squares Decoder (TLSD), that not only solves the ILS problem, better than other sub-optimal techniques, but also is capable of providing the a-posteriori probability distribution for each element in the solution vector. The algorithm is based on reconstruction of the vector from multiple two-dimensional projections. The projections are carefully chosen to provide low computational complexity. Unlike other iterative techniques, such as the belief propagation, the proposed algorithm has ensured convergence. We also provide simulated experiments comparing the algorithm to other sub-optimal algorithms.