Miracle-dz/UniFAR-FTUs huggingface dataset:
Role of CcpA in Regulation of the Central Pathways of Carbon Catabolism in Bacillus subtilis

ABSTRACT The Bacillus subtilis two-dimensional (2D) protein index contains almost all glycolytic and tricarboxylic acid (TCA) cycle enzymes, among them the most abundant housekeeping proteins of growing cells. Therefore, a comprehensive study on the regulation of glycolysis and the TCA cycle was initiated. Whereas expression of genes encoding the upper and lower parts of glycolysis (pgi,pfk, fbaA, and pykA) is not affected by the glucose supply, there is an activation of the glycolytic gap gene and the pgk operon by glucose. This activation seems to be dependent on the global regulator CcpA, as shown by 2D polyacrylamide gel electrophoresis analysis as well as by transcriptional analysis. Furthermore, a high glucose concentration stimulates production and excretion of organic acids (overflow metabolism) in the wild type but not in the ccpAmutant. Finally, CcpA is involved in strong glucose repression of almost all TCA cycle genes. In addition to TCA cycle and glycolytic enzymes, the levels of many other proteins are affected by theccpA mutation. Our data suggest (i) that ccpAmutants are unable to activate glycolysis or carbon overflow metabolism and (ii) that CcpA might be a key regulator molecule, controlling a superregulon of glucose catabolism.
A Comparison of Surface and Internally Measured Myoelectric Signals for use in Prosthetic Control

INTRODUCTION The surface myoelectric signal (MES) has proven to be an effective control input for powered prostheses. Pattern recognition based controllers use multi-channel surface MES as inputs to discriminate between the desired classes of limb activation. There are two major methods which may be pursued to increase the accuracy of the controller: 1) use signal processing to extract more information from the input signals; or 2) provide more informative raw signals to the controller. As a result of recent technological advances, it is reasonable to assume that there will soon be implantable myoelectric sensors which will enable the internal MES to be used as inputs to controllers [1]. An internal MES measurement should have less muscular crosstalk allowing for more independent control sites. However, it remains unclear if this benefit outweighs the loss of the more global information contained in the surface MES. This study compares the classification accuracy of several pattern based myoelectric controllers which use information extracted from surface MES to the same controllers which use information extracted from finewire intramuscular MES.
RNA Degradome Studies Give Insights into Ribosome Dynamics[OPEN]

RNA metabolism is key to a number of crucial processes in the cell, including transcription, RNA splicing, translation, and gene regulation. For efficient translation, mature mRNAs must have a 7-methylguanosine cap on the 5′ end to help recruit the translation machinery and protect the mRNA from
Implementing real-time transactional security property using timed edit automata

Timed edit automaton is action sequence transformer which takes a sequence of actions as input and produces another sequence of actions according to the policy it implements. If the input action sequence obeys the policy then timed edit automaton produces same actions sequence or an equivalent action sequence. If the input action sequence does not obey the policy then the timed edit automaton produces modified action sequence. Timed edit automaton is suitable for implementing real-time transactional security property.
Grounding Collaborative Learning in Semantics-Based Critiquing

In this paper we investigate the use of Latent Semantic Analysis (LSA), Critiquing Systems, and Knowledge Building to support computer-based teaching of English composition. We have built and tested an English Composition Critiquing System that makes use of LSA to analyze student essays and compute feedback by comparing their essays with teacher’s model essays. LSA values are input to a critiquing component to provide a user interface for the students. A software agent can also use the critic feedback to coordinate a collaborative knowledge building session with multiple users (students and teachers). Shared feedback provides seed questions that can trigger discussion and extended reflection about the next phase of writing. We present the first version of a prototype we have built, and report the results from three experiments. We end the paper by describing our plans for future work.
Dexamethasone increases aquaporin-2 protein expression in ex vivo inner medullary collecting duct suspensions

Aquaporin-2 (AQP2) is the vasopressin-regulated water channel that controls renal water reabsorption and plays an important role in the maintenance of body water homeostasis. Excessive glucocorticoid as often seen in Cushing's syndrome causes water retention. However, whether and how glucocorticoid regulates AQP2 remains unclear. In this study, we examined the direct effect of dexamethasone on AQP2 protein expression and activity. Dexamethasone increased AQP2 protein abundance in rat inner medullary collecting duct (IMCD) suspensions. This was confirmed in HEK293 cells transfected with AQP2 cDNA. Cell surface protein biotinylation showed an increase of dexamethasone-induced cell membrane AQP2 expression and this effect was blocked by glucocorticoid receptor antagonist RU486. Functionally, dexamethasone treatment of oocytes injected with an AQP2 cRNA increased water transport activity as judged by cell rupture time in a hypo-osmotic solution (66 ± 13 s in dexamethasone vs. 101 ± 11 s in control, n = 15). We further found that dexamethasone treatment reduced AQP2 protein degradation, which could result in an increase of AQP2 protein. Interestingly, dexamethasone promoted cell membrane AQP2 moving to less buoyant lipid raft submicrodomains. Taken together, our data demonstrate that dexamethasone promotes AQP2 protein expression and increases water permeability mainly via inhibition of AQP2 protein degradation. The increase in AQP2 activity promotes water reabsorption, which may contribute to glucocorticoid-induced water retention and hypertension.
Food Waste Valorization

During the industrial processing of agricultural or animal products, large amounts of waste are produced. These wastes, generated in large amounts throughout the seasons of the year, can be considered the most abundant renewable resources on earth. Due to the large availability and richness in components of these raw materials, there is a great interest in their reuse, both from an economical and environmental point of view. This economical interest is based on the fact that a high quantity of such wastes could be used as low-cost raw materials for the production of new value-added compounds, with a further production cost reduction. The environmental concern is derived from their composition, especially the agro-industrial wastes that can contain potentially toxic compounds, which may cause deterioration of the environment when uncontrolled wastes are either burned, left on the soil to decay naturally, or buried underground. Moreover, these materials exhibit both high biochemical oxygen demand (BOD) and chemical oxygen demand (COD) values and give rise to serious pollution problems if not properly discarded. Recycling and transformation of food wastes represent a great opportunity in supporting sustainable development by their conversion into value-added products through the fermentation process.
Production visualization for the ASCI One TeraFLOPS machine

The delivery of the first one tera-operations/sec computer has significantly impacted production data visualization, affecting data transfer, post processing, and rendering. Terascale computing has motivated a need to consider the entire data visualization system; improving a single algorithm is not sufficient. This paper presents a systems approach to decrease by a factor of four the time required to prepare large data sets for visualization. For daily production use, all stages in the processing pipeline from physics simulation code to pixels on a screen, must be balanced to yield good overall performance. Performance of the initial visualization system is compared with recent improvements. "Lessons learned" from the coordinated deployment of improved algorithms also are discussed, including the need for 64 bit addressing and a fully parallel data visualization pipeline.
Planning for dynamic multi-agent planar manipulation with uncertainty: a game theoretic approach

This paper addresses the planning problem for multi-agent dynamic manipulation in the plane. The objective of planning is to design the forces exerted on the object by agents with which the object can follow a given trajectory in spite of the uncertainty on pressure distribution. The main novelty of the proposed approach is the integration of noncooperative game and cooperative game between agents in hierarchical manner. Based on the dynamic model of the pushed object, the coordination problem is solved in two levels. In the lower control level, a fictitious force controller is designed by using minimax technique to achieve the tracking performance. The design procedure is divided into two steps. First, a linear nominal controller is designed via full-state linearization with desired eigenvalue assignment. Next, a minimax control scheme is specified to optimally attenuate the worst-case effect of the uncertainty due to pressure distribution and achieve a minimax tracking performance. In the coordination level, a cooperative game is formulated between agents to distribute the fictitious force, and the objective of the game is to minimize the worst-case interaction force between agents and the object. Simulations are carried out on three-agent manipulations, results demonstrate the effectiveness of the planning method.
Implicitly Learning a User Interest Profile for Personalization of Web Search Using Collaborative Filtering

The increasing abundance of content on the web has made information filtering even more important in helping users find information related to their interests. Personalization of web search is one such effort, that aims at improving the efficiency with which a user finds results relevant to his query. This is done by keeping track of a user's individual interests, and taking it into account while returning search results. We propose a robust user modeling technique that implicitly creates a Dynamic Category Interest Tree (DCIT), using a general ontology of the web and a set of web pages collected over time that give an insight into a user's interests. The DCIT is designed to use a fuzzy classification technique to keep track of what topics a user is interested in, his amount of interest in a topic, as well as reflect his changing interests overtime. The DCIT consists of a general ontology of the web, where each node represents a topic and consists of keywords that are usually used to describe that topic or category. Additional keywords that the user frequently associates with a topic, such as names of important people, organizations, or a specialized terminology, etc. Are also incorporated into the relevant topic. We use the Apriori Algorithm to extract these associated words from the user's web history in order to more accurately define the user's categories of interest. The DCIT is initially created by a content based approach using only the browsing history of the user, and is later further enhanced through collaborative filtering using the k-nearest neighbour-based algorithm. We propose a technique to re-rank the results from a search engine according to their relevance to a user, based on his implicitly learned DCIT. According to experimental results, our DCIT based ranking often outperforms search engines such as Google when it comes to retrieving web pages that are more relevant to a user's interest.
The impact of active queue management on multimedia congestion control

Multimedia applications that transmit long continuous streams of data across the Internet will continue to stress networking technologies for the years to come. To help improve the performance of congestion avoidance protocols like TCP and to punish non-adaptive UDP-based applications, the IETF is considering the widespread deployment of random early detection (RED) queue management. We examine the impact of RED queue management on multimedia applications and their congestion control mechanisms. Our results show that even in ideal scenarios, the use of TCP-based congestion control in conjunction with active queue management based on RED will add significantly more bandwidth jitter over both short and long time scales, making it particularly difficult for adaptive, TCP-compatible, multimedia applications to converge on a single, fixed sending rate.
Data model integration of SPM transport in the Dutch coastal zone

Suspended Particulate Matter (SPM) is an important environmental parameter in coastal seas such as the North Sea. Our description and understanding of the complex dynamical SPM transport system can be much improved by means of an integration of remote sensing data and numerical modelling. SPM data products retrieved from MERIS RR ocean colour by VU-IVM, which include information on the uncertainty in the data, are very suitable to be used to update the Delft3D-WAQ sediment transport model in an Ensemble Kalman Filtering approach. The sediment transport model proper is provided with information on water motion from the Delft3D-Flow hydrodynamic model and with surface wave parameters from a combination of SWAN wave model data and wave buoy observations, such that a robust modelling system results. The robustness of both data and model are prerequisites for a successful Kalman Filtering. Eventually, the assimilation of the mostly daily MERIS observations enables to overcome the limitations of cloud cover and restriction to the sea surface layer inherent to space borne ocean colour observations.
Translating the A1C Assay Into Estimated Average Glucose Values

OBJECTIVE—The A1C assay, expressed as the percent of hemoglobin that is glycated, measures chronic glycemia and is widely used to judge the adequacy of diabetes treatment and adjust therapy. Day-to-day management is guided by self-monitoring of capillary glucose concentrations (milligrams per deciliter or millimoles per liter). We sought to define the mathematical relationship between A1C and average glucose (AG) levels and determine whether A1C could be expressed and reported as AG in the same units as used in self-monitoring. RESEARCH DESIGN AND METHODS—A total of 507 subjects, including 268 patients with type 1 diabetes, 159 with type 2 diabetes, and 80 nondiabetic subjects from 10 international centers, was included in the analyses. A1C levels obtained at the end of 3 months and measured in a central laboratory were compared with the AG levels during the previous 3 months. AG was calculated by combining weighted results from at least 2 days of continuous glucose monitoring performed four times, with seven-point daily self-monitoring of capillary (fingerstick) glucose performed at least 3 days per week. RESULTS—Approximately 2,700 glucose values were obtained by each subject during 3 months. Linear regression analysis between the A1C and AG values provided the tightest correlations (AGmg/dl = 28.7 × A1C − 46.7, R2 = 0.84, P < 0.0001), allowing calculation of an estimated average glucose (eAG) for A1C values. The linear regression equations did not differ significantly across subgroups based on age, sex, diabetes type, race/ethnicity, or smoking status. CONCLUSIONS—A1C levels can be expressed as eAG for most patients with type 1 and type 2 diabetes.
Node Similarities from Spreading Activation

In this paper we propose two methods to derive two different kinds of node similarities in a network based on their neighborhood. The first similarity measure focuses on the overlap of direct and indirect neighbors. The second similarity compares nodes based on the structure of their - possibly also very distant - neighborhoods. Instead of using standard node measures, both similarities are derived from spreading activation patterns over time. Whereas in the first method the activation patterns are directly compared, in the second method the relative change of activation over time is compared. We apply both methods to a real-world graph dataset and discuss the results.
Machine‐learning scoring functions to improve structure‐based binding affinity prediction and virtual screening

Docking tools to predict whether and how a small molecule binds to a target can be applied if a structural model of such target is available. The reliability of docking depends, however, on the accuracy of the adopted scoring function (SF). Despite intense research over the years, improving the accuracy of SFs for structure‐based binding affinity prediction or virtual screening has proven to be a challenging task for any class of method. New SFs based on modern machine‐learning regression models, which do not impose a predetermined functional form and thus are able to exploit effectively much larger amounts of experimental data, have recently been introduced. These machine‐learning SFs have been shown to outperform a wide range of classical SFs at both binding affinity prediction and virtual screening. The emerging picture from these studies is that the classical approach of using linear regression with a small number of expert‐selected structural features can be strongly improved by a machine‐learning approach based on nonlinear regression allied with comprehensive data‐driven feature selection. Furthermore, the performance of classical SFs does not grow with larger training datasets and hence this performance gap is expected to widen as more training data becomes available in the future. Other topics covered in this review include predicting the reliability of a SF on a particular target class, generating synthetic data to improve predictive performance and modeling guidelines for SF development. WIREs Comput Mol Sci 2015, 5:405–424. doi: 10.1002/wcms.1225
Duffy antigen receptor for chemokines and its involvement in patterning and control of inflammatory chemokines

Leukocyte functions are linked to their migratory responses, which, in turn, are largely determined by the expression profile of classical chemokine receptors. Upon binding their cognate chemokines, these G-protein-coupled receptors (GPCRs) initiate signaling cascades and downstream molecular and cellular responses, including integrin activation and cell locomotion. Chemokines also bind to an alternative subset of chemokine receptors, which have serpentine structure characteristic for GPCRs but lack DRYLAIV consensus motive required for coupling to G-proteins. Duffy antigen receptor for chemokines (DARC) is a member of this atypical receptor subfamily. DARC binds a broad range of inflammatory CXC and CC chemokines and is expressed by erythrocytes, venular endothelial cells, and cerebellar neurons. Erythrocyte DARC serves as blood reservoir of cognate chemokines but also as a chemokine sink, buffering potential surges in plasma chemokine levels. Endothelial cell DARC internalizes chemokines on the basolateral cell surface resulting in subsequent transcytosis of chemokines and their immobilization on the tips of apical microvilli. These DARC-mediated endothelial cell interactions allow chemokines produced in the extravascular tissues to optimally function as arrest chemokines on the luminal endothelial cell surface.
Frequency domain space time coding for MIMO FIR channels

It is known that linearly proceding the source symbols prior to their transmission through an FIR channel can facilitate the identification of the channel and improve the source estimates. This paper propounds the use of a new class of linear precoders which explicitly add algebraic redundancy in the frequency domain. These precoders naturally guard against narrowband interference and channel spectral nulls. This paper also demonstrates how these precoders can be used for novel space time coding over MIMO FIR channels.
{2,6-Bis[(2,6-diisopropylphosphanyl)oxy]-4-fluorophenyl-κ3 P,C 1,P′}(1H-pyrazole-κN 2)nickel(II) hexafluorophosphate

The title compound, [Ni(C18H30FO2P2)(C3H4N2)]PF6, was prepared by halide abstraction with TlPF6 in the presence of CH3CN in CDCl3 from the respective neutral pincer chlorido analogue followed by addition of pyrazole. The PO—C—OP pincer ligand acts in typical trans-P2 tridentate fashion to generate a distorted square-planar nickel structure. The Ni—N(pyrazole) distance is 1.925 (2) Å and the plane of the pyrazole ligand is rotated 56.2 (1)° relative to the approximate square plane surrounding the NiII center in which the pyrazole is bound to the NiII atom through its sp 2-hybridized N atom. This Ni—N distance is similar to bond lengths in the other reported NiII pincer-ligand square-planar pyrazole complex structures; however, its dihedral angle is significantly larger than any of those for the latter set of pyrazole complexes.
Albuminuria, Expression of Nicotinamide Adenine Dinucleotide Phosphate Oxidase and Monocyte Chemoattractant Protein-1 in the Renal Tubules of Hypertensive Dahl Salt-Sensitive Rats

In chronic renal diseases, experimental and human data suggest that excess albumin filtered through the glomerular capillary barrier is over-reabsorbed by proximal tubular cells, thereby activating these cells and upregulating the expression of chemokines. On the other hand, a high-salt diet has been shown to induce proteinuria in hypertensive Dahl salt-sensitive (DSS) rats, accompanied with the expression of reduced nicotinamide adenine dinucleotide phosphate (NADPH) oxidase in the kidney. In the current study, we therefore examined albuminuria and the expressions of NADPH oxidase and monocyte chemoattractant protein-1 (MCP-1) in the renal tubular cells in hypertensive DSS rats, as well as the effects of the antioxidant N-acetylcysteine (NAC) on each of these parameters. DSS rats were fed a normal-salt diet (0.24% NaCl), a high-salt diet (8% NaCl), or a high-salt diet plus NAC supplementation (15 mg/mL drinking water) for 4 weeks. The high-salt diet provoked an increase in glomerular injuries accompanied with albuminuria and in urinary H2O2 and MCP-1 excretion. Immunohistochemical analysis showed the prominent expression of MCP-1 in the dilated tubular cells, where the NADPH oxidase subunit p47phox was also expressed. The current results suggest that albuminuria caused expression of NADPH oxidase and MCP-1 in the dilated renal tubules, resulting in interstitial inflammation and migration of mononuclear cells in DSS rats, because blockade of albuminuria by NAC counteracted the p47phox and MCP-1 expression.