Miracle-dz/UniFAR-FTUs huggingface dataset:
Mechanistic picture for conformational transition of a membrane transporter at atomic resolution

Significance Membrane transporters rely on large-scale conformational changes for their function. Despite considerable effort, however, details of such structural transitions are largely unknown, leaving many fundamental questions regarding the transport mechanism in this important family of membrane proteins unanswered. Here, we present a nonequilibrium approach to characterize the conformational transition of MsbA, a member of the ATP-binding cassette exporter family, which is involved in transport of diverse substrates across the membrane. The design of the study is based on complex, system-specific reaction coordinates and protocols resulting in an unprecedented level of detail on the nature of conformational coupling and the mechanism of transport. The presented approach opens opportunities for investigating large-scale conformational changes of other membrane transporters. During their transport cycle, ATP-binding cassette (ABC) transporters undergo large-scale conformational changes between inward- and outward-facing states. Using an approach based on designing system-specific reaction coordinates and using nonequilibrium work relations, we have performed extensive all-atom molecular dynamics simulations in the presence of explicit membrane/solvent to sample a large number of mechanistically distinct pathways for the conformational transition of MsbA, a bacterial ABC exporter whose structure has been solved in multiple functional states. The computational approach developed here is based on (i) extensive exploration of system-specific biasing protocols (e.g., using collective variables designed based on available low-resolution crystal structures) and (ii) using nonequilibrium work relations for comparing the relevance of the transition pathways. The most relevant transition pathway identified using this approach involves several distinct stages reflecting the complex nature of the structural changes associated with the function of the protein. The opening of the cytoplasmic gate during the outward- to inward-facing transition of apo MsbA is found to be disfavored when the periplasmic gate is open and facilitated by a twisting motion of the nucleotide-binding domains that involves a dramatic change in their relative orientation. These results highlight the cooperativity between the transmembrane and the nucleotide-binding domains in the conformational transition of ABC exporters. The approach introduced here provides a framework to study large-scale conformational changes of other membrane transporters whose computational investigation at an atomic resolution may not be currently feasible using conventional methods.
Efficient Hardware Architecture for Compressed Sensing with DFT Sensing Matrix

The reconstruction of a sparse signal from an undersampled set of linear measurements can be found in many engineering fields. In some practical applications, the measurements are usually acquired through low-resolution analog-to-digital converters because of the limitations in hardware complexity and power consumption. In this paper, we present the first hardware architectural design for an optimal signal recovery from coarsely quantized measurements, in which the sensing matrix is a partial discrete Fourier transform matrix. The optimal signal recovery can be achieved using a novel turbo-type algorithm. We develop a variety of approximations at the algorithm level and employ pipelining and folding techniques, which enable high-efficiency and low-complexity implementation.
COMPLEXITY OF VILLAMAYOR'S ALGORITHM IN THE NON-EXCEPTIONAL MONOMIAL CASE

We study monomial ideals, always locally given by a monomial, like a reasonable first step to estimate in general the number of monoidal transformations of Villamayor's algorithm of resolution of singularities. The resolution of a monomial ideal $\langle X_1^{a_1}\,{\cdot}\, \cdots \,{\cdot}\, X_n^{a_n}\rangle$ is interesting due to its identification with the particular toric problem $\langle Z^c- X_1^{a_1}\,{\cdot}\, \cdots \,{\cdot}\, X_n^{a_n}\rangle$. In the special case, when all the exponents ai are greater than or equal to the critical value c, we construct the largest branch of the resolution tree which provides an upper bound involving partial sums of Catalan numbers. This case will be called "minimal codimensional case". Partial sums of Catalan numbers (starting 1,2,5,…) are 1,3,8,22,…. These partial sums are well known in Combinatorics and count the number of paths starting from the root in all ordered trees with n + 1 edges. Catalan numbers appear in many combinatorial problems, counting the .
Molecular Basis for Atovaquone Resistance in Pneumocystis jirovecii Modeled in the Cytochrome bc1Complex of Saccharomyces cerevisiae*

Atovaquone is a substituted hydroxynaphthoquinone that is widely used to prevent and clear Plasmodium falciparum malaria and Pneumocystis jirovecii pneumonia. Atovaquone inhibits respiration in target organisms by specifically binding to the ubiquinol oxidation site at center P of the cytochrome bc1 complex. The failure of atovaquone treatment and mortality of patients with malaria and P. jirovecii pneumonia has been linked to the appearance of mutations in the cytochrome b gene. To better understand the molecular basis of atovaquone resistance, we have introduced seven of the mutations from atovaquone-resistant P. jirovecii into the cytochrome b gene of Saccharomyces cerevisiae and thus obtained cytochrome bc1 complexes resistant to inhibition by atovaquone. In these enzymes, the IC50 for atovaquone increases from 25 nm for the enzyme from wild-type yeast to >500 nm for some of the mutated enzymes. Modeling of the changes in cytochrome b structure and atovaquone binding with the mutated bc1 complexes provides the first quantitative explanation for the molecular basis of atovaquone resistance.
Multiple discrete-energy ion features in the inner magnetosphere: 9 February 1998, event

Abstract. Multiple discrete-energy ion bands observed by the Polar satellite in the inner magnetosphere on 9 February 1998 were investigated by means of particle simulation with a realistic model of the convection electric field. The multiple bands appeared in the energy vs. L spectrum in the 1–100 keV range when Polar traveled in the heart of the ring current along the outbound and inbound paths. We performed particle tracing, and simulated the energy vs. L spectra of proton fluxes under the dipole magnetic field, the corotation electric field, and the realistic convection electric field model with its parameters depending on the solar wind data. Simulated spectra are shown to agree well with the observed ones. A better agreement is achieved when we rotate the convection electric potential eastward by 2h inMLT and we change the distribution function in time in the near-Earth magnetotail. It is concluded that the multiple bands are likely produced by two processes for this particular event, that is, changes in the convection electric field (for >3keV protons) and changes in the distribution function in the near-Earth magnetotail (for Key words. Magnetospheric physics (energetic particles, trapped; electric field) – Space plasma physics (numerical simulation studies)
Scene classification with semantic Fisher vectors

With the help of a convolutional neural network (CNN) trained to recognize objects, a scene image is represented as a bag of semantics (BoS). This involves classifying image patches using the network and considering the class posterior probability vectors as locally extracted semantic descriptors. The image BoS is summarized using a Fisher vector (FV) embedding that exploits the properties of the space of these descriptors. The resulting representation is referred to as a semantic Fisher vector. Two implementations of a semantic FV are investigated. First involves modeling the BoS with a Dirichlet Mixture and computing the Fisher gradients for this model. Due to the difficulty of mixture modeling on a non-Euclidean probability simplex, this approach is shown to be unsuccessful. A second implementation is derived using the interpretation of semantic descriptors as parameters of a multinomial distribution. Like the parameters of any exponential family, these can be projected into their natural parameter space. For a CNN, this is shown equivalent to using inputs of its soft-max layer as patch descriptors. A semantic FV is then computed as a Gaussian Mixture FV in the space of these natural parameters. This representation is shown to outperform other alternatives such as FVs of features from the intermediate CNN layers or a classifier obtained by adapting (fine-tuning) the CNN. The proposed FV represents an embedding for object classification probabilities. As an image representation, therefore, it is complementary to the features obtained from a scene classification CNN. A combination of the two representations is shown to achieve state-of-the-art results on MIT Indoor scenes and SUN datasets.
A proteomic glimpse into human ureter proteome

Urine has evolved as one of the most important biofluids in clinical proteomics due to its noninvasive sampling and its stability. Yet, it is used in clinical diagnostics of several disorders by detecting changes in its components including urinary protein/polypeptide profile. Despite the fact that majority of proteins detected in urine are primarily originated from the urogenital (UG) tract, determining its precise source within the UG tract remains elusive. In this article, we performed a comprehensive analysis of ureter proteome to assemble the first unbiased ureter dataset. Next, we compared these data to urine, urinary exosome, and kidney mass spectrometric datasets. Our result concluded that among 2217 nonredundant ureter proteins, 751 protein candidates (33.8%) were detected in urine as urinary protein/polypeptide or exosomal protein. On the other hand, comparing ureter protein hits (48) that are not shown in corresponding databases to urinary bladder and prostate human protein atlas databases pinpointed 21 proteins that might be unique to ureter tissue. In conclusion, this finding offers future perspectives for possible identification of ureter disease‐associated biomarkers such as ureter carcinoma. In addition, the ureter proteomic dataset published in this article will provide a valuable resource for researchers working in the field of urology and urine biomarker discovery. All MS data have been deposited in the ProteomeXchange with identifier PXD002620 (http://proteomecentral.proteomexchange.org/dataset/PXD002620).
The Explanatory Value of the Cognitive Unconscious

This dissertation defends the explanatory value of unconscious mental states. Unconscious mental states are a subject’s information-bearing states with certain properties. These states possess features that make them mental states but do not possess the properties that make them conscious mental states. The claim is that some human behaviors, driven by perceptual and cognitive mental states, are best explained by employing unconscious mental states of one kind or another. The general idea is that the explanatory value of unconscious mental states equals the number of a subject’s behaviors valuably explained by their mental states minus the number of the subject’s behaviors that are valuably explained by their conscious mental states. Support for the claim that some human behaviors are best explained by employing unconscious mental states comes in three forms. First, there is a coherent informationprocessing model for mental states. This model can account for certain of a subject’s perceptually and cognitively driven behaviors, in part or whole, with unconscious mental states. Second, independent criteria regarding human subject’s conscious mental states support explanations that use unconscious mental states. Finally, unconscious mental states are supported by the success of models that employ such states found in modern psychological and neurological explanations of some human behaviors. This dissertation will also support the idea that the set of unconscious mental states in human subjects are moderately unified, made of various kinds, and are numerous. Unconscious mental states in empirical psychology and neuroscience are often called a subject’s “cognitive unconscious” (Kihlstrom 1987). The explanatory value of the “cognitive unconscious” has been recently attacked, for example by Searle (1990), as well as others. This dissertation defends the explanatory value of the cognitive unconscious against these attacks. This dissertation is dedicated to my unconscious; without its help I could not have read, much less written, this work CONTENTS CHAPTER General Introduction 1 1 The Cognitive Unconscious: A Brief Sketch 4 1.1 The Human Mind and the Information-Processing Framework 4 1.2 Brief Sketch of the Cognitive Unconscious 8 1.2. 1 Intuitive Illustration of the Cognitive Unconscious 13 1.3 Further Clarifications 15 1.4 Summary and Overview 16 2 The Three-Tiered Information-Processing Model of the Human Mind 17 2.
Myxoid Cellular Neurothekeoma: A New Entity of S100-Negative, CD68-Positive Myxoid Neurothekeoma

Neurothekeoma is a rare cutaneous neoplasm, occurring as a cutaneous papule or nodule on the face, shoulders, and upper extremities. Neurothekeoma has been subclassified as either the myxoid, cellular, or mixed type, depending on the amount of myxoid matrix and on immunohistochemical analysis. We observed a clinical case with conflicting histopathological and immunohistochemical findings. In this case, microscopic examination showed the typical presentation of myxoid neurothekeoma; however, immunohistochemical staining was negative for S100 protein and positive for CD68, which is the characteristic pattern of cellular neurothekeoma. We report a very rare form of myxoid cellular neurothekeoma of the face in a young woman.
Who cares about Sarcastic Tweets? Investigating the Impact of Sarcasm on Sentiment Analysis.

Sarcasm is a common phenomenon in social media, and is inherently difficult to analyse, not just automatically but often for humans too. It has an important effect on sentiment, but is usually ignored in social media analysis, because it is considered too tricky to handle. While there exist a few systems which can detect sarcasm, almost no work has been carried out on studying the effect that sarcasm has on sentiment in tweets, and on incorporating this into automatic tools for sentiment analysis. We perform an analysis of the effect of sarcasm scope on the polarity of tweets, and have compiled a number of rules which enable us to improve the accuracy of sentiment analysis when sarcasm is known to be present. We consider in particular the effect of sentiment and sarcasm contained in hashtags, and have developed a hashtag tokeniser for GATE, so that sentiment and sarcasm found within hashtags can be detected more easily. According to our experiments, the hashtag tokenisation achieves 98% Precision, while the sarcasm detection achieved 91% Precision and polarity detection 80%.
Trust Mechanisms for Efficiency Improvement in Collaborative Working Environments

We apply the notion of trust to situations of document editing, to select the successive editors of the document and avoid unnecessary readings by all collaborators after each modification. Two mechanisms using trust to improve that process are proposed, and compared to the situation without trust. Simulation results suggest that trust can improve the efficiency of the collaborative work.
Basic Fibroblast Growth Factor-Mediated Overexpression of Vascular Endothelial Growth Factor in 1F6 Human Melanoma Cells is Regulated by Activation of PI-3K and p38 MAPK

Background: 1F6 human melanoma xenografts overexpressing either the 18 kD (18kD) form or all (ALL) forms of human basic fibroblast growth factor (bFGF) demonstrate an abundant number of microvessels and accelerated growth. We now examined whether bFGF mediates vascular endothelial growth factor (VEGF) expression. Methods: Quantitative RT-PCR was used to determine bFGF and VEGF mRNA, VEGF protein secretion was measured by ELISA and VEGF promoter activation was assessed by a dual luciferase activity assay. Western blot was carried out to detect phosphorylation of bFGF-regulated target proteins. Results: In 1F6-18kD and 1F6-ALL clones VEGF mRNA was increased 4- to 5-fold and VEGF protein secretion was highly stimulated due to activation of the VEGF promotor. PI-3K, p38 MAPK and ERK1/2 MAPK pathways were activated, while inhibition of PI-3K or p38 resulted in, respectively, 55% and up to 70% reduction of VEGF mRNA overexpression. A concurrent 60% decrease in VEGF protein secretion was mostly apparent upon inhibition of PI-3K. Inhibition of ERK1/2 hardly affected VEGF mRNA or protein secretion. Two unselected human melanoma cell lines with high metastatic potential contained high bFGF and VEGF, while three non- or sporadically metastatic cell lines displayed low bFGF and VEGF. Conclusion: These data indicate that stimulation of VEGF protein secretion in response to bFGF overexpression may contribute to increased vascularization and enhanced aggressiveness in melanoma.
Nodes Having a Major Influence to Break Cooperation Define a Novel Centrality Measure: Game Centrality

Cooperation played a significant role in the self-organization and evolution of living organisms. Both network topology and the initial position of cooperators heavily affect the cooperation of social dilemma games. We developed a novel simulation program package, called ‘NetworGame’, which is able to simulate any type of social dilemma games on any model, or real world networks with any assignment of initial cooperation or defection strategies to network nodes. The ability of initially defecting single nodes to break overall cooperation was called as ‘game centrality’. The efficiency of this measure was verified on well-known social networks, and was extended to ‘protein games’, i.e. the simulation of cooperation between proteins, or their amino acids. Hubs and in particular, party hubs of yeast protein-protein interaction networks had a large influence to convert the cooperation of other nodes to defection. Simulations on methionyl-tRNA synthetase protein structure network indicated an increased influence of nodes belonging to intra-protein signaling pathways on breaking cooperation. The efficiency of single, initially defecting nodes to convert the cooperation of other nodes to defection in social dilemma games may be an important measure to predict the importance of nodes in the integration and regulation of complex systems. Game centrality may help to design more efficient interventions to cellular networks (in forms of drugs), to ecosystems and social networks.
Advancing Emotion Theory with Multivariate Pattern Classification

Characterizing how activity in the central and autonomic nervous systems corresponds to distinct emotional states is one of the central goals of affective neuroscience. Despite the ease with which individuals label their own experiences, identifying specific autonomic and neural markers of emotions remains a challenge. Here we explore how multivariate pattern classification approaches offer an advantageous framework for identifying emotion-specific biomarkers and for testing predictions of theoretical models of emotion. Based on initial studies using multivariate pattern classification, we suggest that central and autonomic nervous system activity can be reliably decoded into distinct emotional states. Finally, we consider future directions in applying pattern classification to understand the nature of emotion in the nervous system.
Differential roles of STAT1 and STAT1 in fludarabine-induced cell cycle arrest and apoptosis in human B cells

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The Effect of Health Literacy and Self-efficacy on Treatment Adherence of Hypertensive Elders

Background/Objectives: To investigate how and how much health literacy and self-efficacy can make an influence on treatment adherence of hypertensive elders. Methods/Statistical Analysis: Participants were those aged 65 or older who regularly visited one of five seniors welfare centers hosted by D metropolitan ward offices, were diagnosed with hypertension, and voluntarily agreed to participate in this study after. In total, the questionnaires of 190 respondents were selected for the final analysis. Hierarchical multiple regression analysis was conducted to identify the effect of participants' health literacy and self-efficacy on treatment adherence. Findings: First, model that inputs as explanatory variables which were general characteristics of the participant: age, level of education, and gender variables and disease related characteristics: number of associated disease, duration of hypertension, level of stress were statistically significant, and explained 4.8% of treatment adherence. Stress and gender were predictor variables, and these variables were statistically related to treatment adherence. In the second step, when capability of oral health literacy and functional health literacy variables were put in the control condition of general characteristics and disease related characteristics, this model was statistically significant and explained 7.0% of treatment adherence. Predictor variables were stress, gender, and oral health literacy, and they were statistically related to treatment adherence. In the third step, when self-efficacy was put in the control condition of general characteristics and disease- related characteristics, this model was statistically significant and the explanatory power increased to 38%. Self-efficacy and level of education were shown as major predictor variables. Application/Improvements: To promote the treatment adherence of hypertensive elders, it is necessary to develop and apply programs for self-efficacy improvement.
Error awareness and the insula: links to neurological and psychiatric diseases

Becoming aware of errors that one has committed might be crucial for strategic behavioral and neuronal adjustments to avoid similar errors in the future. This review addresses conscious error perception (“error awareness”) in healthy subjects as well as the relationship between error awareness and neurological and psychiatric diseases. We first discuss the main findings on error awareness in healthy subjects. A brain region, that appears consistently involved in error awareness processes, is the insula, which also provides a link to the clinical conditions reviewed here. Then we focus on a neurological condition whose core element is an impaired awareness for neurological consequences of a disease: anosognosia for hemiplegia (AHP). The insular cortex has been implicated in both error awareness and AHP, with anterior insular regions being involved in conscious error processing and more posterior areas being related to AHP. In addition to cytoarchitectonic and connectivity data, this reflects a functional and structural gradient within the insula from anterior to posterior. Furthermore, studies dealing with error awareness and lack of insight in a number of psychiatric diseases are reported. Especially in schizophrenia, attention-deficit hyperactivity disorder, (ADHD) and autism spectrum disorders (ASD) the performance monitoring system seems impaired, thus conscious error perception might be altered.