Miracle-dz/UniFAR-FTUs huggingface dataset:
GS-5806 Inhibits a Broad Range of Respiratory Syncytial Virus Clinical Isolates by Blocking the Virus-Cell Fusion Process

ABSTRACT Respiratory syncytial virus (RSV) is a leading cause of lower respiratory tract infections in infants and young children. In addition, RSV causes significant morbidity and mortality in hospitalized elderly and immunocompromised patients. Currently, only palivizumab, a monoclonal antibody against the RSV fusion (F) protein, and inhaled ribavirin are approved for the prophylactic and therapeutic treatment of RSV, respectively. Therefore, there is a clinical need for safe and effective therapeutic agents for RSV infections. GS-5806, discovered via chemical optimization of a hit from a high-throughput antiviral-screening campaign, selectively inhibits a diverse set of 75 RSV subtype A and B clinical isolates (mean 50% effective concentration [EC50] = 0.43 nM). The compound maintained potency in primary human airway epithelial cells and exhibited low cytotoxicity in human cell lines and primary cell cultures (selectivity > 23,000-fold). Time-of-addition and temperature shift studies demonstrated that GS-5806 does not block RSV attachment to cells but interferes with virus entry. Follow-up experiments showed potent inhibition of RSV F-mediated cell-to-cell fusion. RSV A and B variants resistant to GS-5806, due to mutations in F protein (RSV A, L138F or F140L/N517I, and RSV B, F488L or F488S), were isolated and showed cross-resistance to other RSV fusion inhibitors, such as VP-14637, but remained fully sensitive to palivizumab and ribavirin. In summary, GS-5806 is a potent and selective RSV fusion inhibitor with antiviral activity against a diverse set of RSV clinical isolates. The compound is currently under clinical investigation for the treatment of RSV infection in pediatric, immunocompromised, and elderly patients.
A Virtual Reality System for the Assessment and Rehabilitation of the Activities of Daily Living

Successful rehabilitation with respect to the activities of daily living (ADL) requires accurate and effective assessment and training. A number of studies have emphasized the requirement for rehabilitation methods that are both relevant to the patient's real world environment, and that can also be transferred to other daily living tasks. Virtual reality (VR) has many advantages over other ADL rehabilitation techniques, and offers the potential to develop a human performance testing and training environment. Therefore, in this study, the virtual supermarket was developed and the possibility of using a VR system to assess and train cognitive ability in ADL investigated. This study demonstrates that VR technology offers great promise in the field of ADL training.
Two-Dimensional (2D) and Three-Dimensional (3D) Cell Culturing in Drug Discovery

Cell culture is an indispensable in vitro tool used to improve our perception and understanding of cell biology, the development of tissue engineering, tissue morphology, mechanisms of diseases and drug action. Efficient cell culturing techniques both in vitro and in vivo allow researchers to design and develop new drugs in preclinical studies. Two-dimensional (2D) cell cultures have been used since 1900s and are still a dominant method in many biological studies. However, 2D cell cultures poorly imitate the conditions in vivo. Recently three-dimensional (3D) cell cultures have received remarkable attention in studies such as drug discovery and development. Optimization of cell culture conditions is very critical in ensuring powerful experimental reproducibility, which may help to find new therapies for cancer and other diseases. In this chapter, we discuss the 2D and 3D cell culture technologies and their role in drug discovery.
Cerebellarlike Corrective Model Inference Engine for Manipulation Tasks

This paper presents how a simple cerebellumlike architecture can infer corrective models in the framework of a control task when manipulating objects that significantly affect the dynamics model of the system. The main motivation of this paper is to evaluate a simplified bio-mimetic approach in the framework of a manipulation task. More concretely, the paper focuses on how the model inference process takes place within a feedforward control loop based on the cerebellar structure and on how these internal models are built up by means of biologically plausible synaptic adaptation mechanisms. This kind of investigation may provide clues on how biology achieves accurate control of non-stiff-joint robot with low-power actuators which involve controlling systems with high inertial components. This paper studies how a basic temporal-correlation kernel including long-term depression (LTD) and a constant long-term potentiation (LTP) at parallel fiber-Purkinje cell synapses can effectively infer corrective models. We evaluate how this spike-timing-dependent plasticity correlates sensorimotor activity arriving through the parallel fibers with teaching signals (dependent on error estimates) arriving through the climbing fibers from the inferior olive. This paper addresses the study of how these LTD and LTP components need to be well balanced with each other to achieve accurate learning. This is of interest to evaluate the relevant role of homeostatic mechanisms in biological systems where adaptation occurs in a distributed manner. Furthermore, we illustrate how the temporal-correlation kernel can also work in the presence of transmission delays in sensorimotor pathways. We use a cerebellumlike spiking neural network which stores the corrective models as well-structured weight patterns distributed among the parallel fibers to Purkinje cell connections.
38 Cache-Oblivious Data Structures

University of Southern Denmark 38.1 The Cache-Oblivious Model . 38-1 38.2 Fundamental Primitives . 38-3 Van Emde Boas Layout • k-Merger 38.3 Dynamic B-Trees . 38-8 Density Based • Exponential Tree Based 38.4 Priority Queues . 38-12 Merge Based Priority Queue: Funnel Heap • Exponential Level Based Priority Queue 38.5 2d Orthogonal Range Searching . 38-21 Cache-Oblivious kd-Tree • Cache-Oblivious Range Tree
Mammographic Breast Density as a General Marker of Breast Cancer Risk

Mammographic breast density is a strong risk factor for breast cancer but whether breast density is a general marker of susceptibility or is specific to the location of the eventual cancer is unknown. A study of 372 incident breast cancer cases and 713 matched controls was conducted within the Mayo Clinic mammography screening practice. Mammograms on average 7 years before breast cancer were digitized, and quantitative measures of percentage density and dense area from each side and view were estimated. A regional density estimate accounting for overall percentage density was calculated from both mammogram views. Location of breast cancer and potential confounders were abstracted from medical records. Conditional logistic regression was used to estimate associations, and C-statistics were used to evaluate the strength of risk prediction. There were increasing trends in breast cancer risk with increasing quartiles of percentage density and dense area, irrespective of the side of the breast with cancer (Ptrends < 0.001). Percentage density from the ipsilateral side [craniocaudal (CC): odds ratios (ORs), 1.0 (ref), 1.7, 3.1, and 3.1; mediolateral oblique (MLO): ORs, 1.0 (ref), 1.5, 2.2, and 2.8] and the contralateral side [CC: ORs, 1.0 (ref), 1.8, 2.2, and 3.7; MLO: ORs, 1.0 (ref), 1.6, 1.9, and 2.5] similarly predicted case-control status (C-statistics, 0.64-65). Accounting for overall percentage density, density in the region where the cancer subsequently developed was not a significant risk factor [CC: 1.0 (ref), 1.3, 1.0, and 1.2; MLO: 1.0 (ref), 1.1, 1.0, and 1.1 for increasing quartiles]. Results did not change when examining mammograms 3 years on average before the cancer. Overall mammographic density seems to represent a general marker of breast cancer risk that is not specific to breast side or location of the eventual cancer. (Cancer Epidemiol Biomarkers Prev 2007;16(1):43–9)
Metabolism of Dichloromethylcatechols as Central Intermediates in the Degradation of Dichlorotoluenes by Ralstonia sp. Strain PS12

ABSTRACT Ralstonia sp. strain PS12 is able to use 2,4-, 2,5-, and 3,4-dichlorotoluene as growth substrates. Dichloromethylcatechols are central intermediates that are formed by TecA tetrachlorobenzene dioxygenase-mediated activation at two adjacent unsubstituted carbon atoms followed by TecB chlorobenzene dihydrodiol dehydrogenase-catalyzed rearomatization and then are channeled into a chlorocatechol ortho cleavage pathway involving a chlorocatechol 1,2-dioxygenase, chloromuconate cycloisomerase, and dienelactone hydrolase. However, completely different metabolic routes were observed for the three dichloromethylcatechols analyzed. Whereas 3,4-dichloro-6-methylcatechol is quantitatively transformed into one dienelactone (5-chloro-2-methyldienelactone) and thus is degraded via a linear pathway, 3,5-dichloro-2-methylmuconate formed from 4,6-dichloro-3-methylcatechol is subject to both 1,4- and 3,6-cycloisomerization and thus is degraded via a branched metabolic route. 3,6-Dichloro-4-methylcatechol, on the first view, is transformed predominantly into one (2-chloro-3-methyl-trans-) dienelactone. In situ 1H nuclear magnetic resonance analysis revealed the intermediate formation of 2,5-dichloro-4-methylmuconolactone, showing that both 1,4- and 3,6-cycloisomerization occur with this muconate and indicating a degradation of the muconolactone via a reversible cycloisomerization reaction and the dienelactone-forming branch of the pathway. Diastereomeric mixtures of two dichloromethylmuconolactones were prepared chemically to proof such a hypothesis. Chloromuconate cycloisomerase transformed 3,5-dichloro-2-methylmuconolactone into a mixture of 2-chloro-5-methyl-cis- and 3-chloro-2-methyldienelactone, affording evidence for a metabolic route of 3,5-dichloro-2-methylmuconolactone via 3,5-dichloro-2-methylmuconate into 2-chloro-5-methyl-cis-dienelactone. 2,5-Dichloro-3-methylmuconolactone was transformed nearly exclusively into 2-chloro-3-methyl-trans-dienelactone.
Function of the nuclear receptor FTZ‐F1 during the pupal stage in Drosophila melanogaster

The nuclear receptor βFTZ‐F1 is expressed in most cells in a temporally specific manner, and its expression is induced immediately after decline in ecdysteroid levels. This factor plays important roles during embryogenesis, larval ecdysis, and early metamorphic stages. However, little is known about the expression pattern, regulation and function of this receptor during the pupal stage. We analyzed the expression pattern and regulation of ftz‐f1 during the pupal period, as well as the phenotypes of RNAi knockdown or mutant animals, to elucidate its function during this stage. Western blotting revealed that βFTZ‐F1 is expressed at a high level during the late pupal stage, and this expression is dependent on decreasing ecdysteroid levels. By immunohistological analysis of the late pupal stage, FTZ‐F1 was detected in the nuclei of most cells, but cytoplasmic localization was observed only in the oogonia and follicle cells of the ovary. Both the ftz‐f1 genetic mutant and temporally specific ftz‐f1 knockdown using RNAi during the pupal stage showed defects in eclosion and in the eye, the antennal segment, the wing and the leg, including bristle color and sclerosis. These results suggest that βFTZ‐F1 is expressed in most cells at the late pupal stage, under the control of ecdysteroids and plays important roles during pupal development.
Algorithms for Storytelling

We formulate a new data mining problem called storytelling as a generalization of redescription mining. In traditional redescription mining, we are given a set of objects and a collection of subsets defined over these objects. The goal is to view the set system as a vocabulary and identify two expressions in this vocabulary that induce the same set of objects. Storytelling, on the other hand, aims to explicitly relate object sets that are disjoint (and, hence, maximally dissimilar) by finding a chain of (approximate) redescriptions between the sets. This problem finds applications in bioinformatics, for instance, where the biologist is trying to relate a set of genes expressed in one experiment to another set, implicated in a different pathway. We outline an efficient storytelling implementation that embeds the CARTwheels redescription mining algorithm in an A* search procedure, using the former to supply next move operators on search branches to the latter. This approach is practical and effective for mining large data sets and, at the same time, exploits the structure of partitions imposed by the given vocabulary. Three application case studies are presented: a study of word overlaps in large English dictionaries, exploring connections between gene sets in a bioinformatics data set, and relating publications in the PubMed index of abstracts.
Conformal boundary states for free bosons and fermions

A family of conformal boundary states for a free boson on a circle is constructed. The family contains superpositions of conventional U(1)-preserving Neumann and Dirichlet branes, but for general parameter values the boundary states are fundamental and preserve only the conformal symmetry. The relative overlaps satisfy Cardy's condition, and each boundary state obeys the factorisation constraint. It is also argued that, together with the conventional Neumann and Dirichlet branes, these boundary states already account for all fundamental conformal D-branes of the free boson theory. The results can be generalised to the situation with N = 1 world-sheet supersymmetry, for which the family of boundary states interpolates between superpositions of non-BPS branes and combinations of conventional brane anti-brane pairs.
Representing Normal Programs with Clauses

We present a new method for transforming normal logic programs into sets of clauses. This transformation is based on a novel characterization of stable models in terms of level numberings and it uses atomic normal programs, which are free of positive body atoms, as an intermediary representation. The corresponding translation function possesses a unique combination of properties: (i) a bijective relationship is established between stable models and classical models, (ii) the models coincide up to the set of atoms At(P) appearing in a program P, and (iii) the length of the translation as well as the translation time are of order ‖P‖ x log2 |At(P)| where ‖P‖ is the length of the program P. Our preliminary experiments with an implementation of the transformation, namely translators called LP2ATOMI0 and LP2SAT, and SAT solvers such as CHAFF and RELSAT suggest that our approach is competitive when the task is to compute not just one but all stable models for a normal program given as input.
Sample-based synthesis of photo-realistic talking heads

The paper describes a system that generates photo-realistic video animations of talking heads. First the system derives head models from existing video footage using image recognition techniques. It locates, extracts and labels facial parts such as mouth, eyes, and eyebrows into a compact library. Then, using these face models and a text-to-speech synthesizer, it synthesizes new video sequences of the head where the lips are in synchrony with the accompanying soundtrack. Emotional cues and conversational signals are produced by combining head movements, raising eyebrows, wide open eyes, etc. with the mouth animation. For these animations to be believable, care has to be taken aligning the facial parts so that they blend smoothly into each other and produce seamless animations. Our system uses precise multi channel facial recognition techniques to track facial parts, and it derives the exact 3D position of the head, enabling the automatic extraction of normalized face parts. Such talking head animations are useful because they generally increase intelligibility of the human machine interface in applications where content needs to be narrated to the user, such as educative software.
Assessing the Surface Distortion of Plaster Molds Made with the Use of SLA Models

The method of determining the accuracy of polymer molds in plaster forms has been discussed. Distortion of the surface of molds and plaster molds has been assessed. It has been found that the presence of monolithic and porous structure in the samples does not change the accuracy of the surfaces when forms are prepared for removing the material of the model. It has been found that in case of full-mold casting it is more expedient to form the mold cavity with cellular adjustable structures of molding prototypes.
Detecting Hidden Causality in Network Connections

Upon success, certain network attacks manifest by causing the victim host to change its network-visible connection behavior, such as by starting a new service that the attacker probes to confirm success, “phoning home” to a host controlled by the attacker, or further propagating the attack (e.g., worms or spam relays). One characteristic of such change in network behavior is the presence of unusual causal relationships between connections. Based on this observation, we develop a statistical test that a network monitor can use to identify these causal relationships, and an accompanying set of filtering mechanisms to winnow down the full set of causal relationships to those that are unexpected. We evaluate our mechanism on two large Internet traces, finding that while its detection is incomplete (non-negligible false negatives), it unearths numerous instances of interesting activity. We also find that the rate of false alarms, while not low enough to enable automatic responses to intrusions, is only a few tens per day for a busy site that sees over 2.5 million connections a day.
Bioactive Peptides Control Receptor for Advanced Glycated End Product-Induced Elevation of Kidney Insulin Receptor Substrate 2 and Reduce Albuminuria in Diabetic Mice

BACKGROUND/AIMS Sixteen-week-old db/db mice exhibit significantly elevated blood glucose and albuminuria. Kidney mesangial cell matrix expansion and collagen IV synthesis correlate with disease progression, but the underlying mechanism is unclear. METHODS Adaptive biochemical datasets were generated in cultured 293 kidney cells and in db/db mice. RESULTS In animals receiving daily subcutaneous bolus injections (weeks 8-13) of 20 microg/day humanin or 40 microg/day protein kinase C (NPKC) (a PKC-beta2 inhibitor peptide), there was a significant reduction in albuminuria, insulin receptor substrate 2 (IRS-2) and phospho-Akt (Ser473) levels in kidney tissue extracts (p < 0.05 in all cases). Elevated IRS-2 (not IRS-1), altered Akt1 and selective phosphorylation of p-Akt/Ser473 and p-IRS-1/Ser307 (but not p-Akt/Thr308 or p-IRS-2/Ser731) are correlates of the receptor for advanced glycated end product activation and are linked to albuminuria in vivo, whereas in P38 peptide-treated animals, collagen IV synthesis can be uncoupled from albuminuria altogether. CONCLUSION Taken together, our results suggest that elevated IRS-2 and altered Akt phosphorylation may be more closely tied to the cause of diabetic kidney disease in db/db mice than mesangial matrix expansion per se, though both may originate from elevated circulatory glucose, and mesangial matrix expansion may independently exacerbate kidney dysfunction.
Rich and Dynamic Library Catalogs: A Case Study of Online Search Interfaces

We redesign the user interface of an online library catalog, leveraging current web technologies that allow dynamic and fine-grained user interaction. Over the course of our iterative design and test cycle, we identified four key areas where such dynamic web technologies can be used to improve the support for typical information seeking strategies: namely, 1) the use of overview + details, 2) a tabular data display, 3) using tabs as a history mechanism and 4) embedding a suggestion bar. We believe that the revised affordances created by our changes in these four areas will inform the design of future search interfaces. ACM Classification: H5.2 [Information interfaces and presentation]: User Interfaces. Graphical user interfaces. General terms: Design, Human Factors
Coprophagy in Lepidoptera : observational and experimental evidence in the pyralid moth Aglossa pinguinalis

Larvae of Lepidoptera are mainly herbivores, and only the larval stages of Bradypodicola and Cryptoses pyralid moths are known to be specialized coprophages. Here, we report coprophagy as a main feeding habit for the larvae of another pyralid moth, Aglossa pinguinalis, on the basis of observational and experimental evidence. The larvae of this moth require two years to complete development, and construct silk tubes connecting the food source with a shelter chamber. Larvae of A. pinguinalis were mostly found inside caves, where they were about 700 times more abundant than in the open ®eld. Inside the caves, observational results indicate that 98% of the larvae fed mostly on excrement and only 2% were recorded as eating other kinds of detritus (decayed mushrooms). No larvae were recorded eating plant detritus in the censuses nor in experimental detritus patches. The larvae did not show preferences for different types of excrement in the caves. Experimental dog and sheep excrement corroborated this result, showing that the abundance of larvae did not differ between these two excrement types over the entire study. We suggest that habitat selection of A. pinguinalis is ecologically similar to the trophic specialization of Bradypodicola and Cryptoses, in spite of the differences in natural history traits among these moths. Feeding on dry excrement inside caves, or in buried sloth dung, may re ̄ect the constraints for Lepidoptera successfully to colonize excrement: in more exposed excrement, they cannot compete with other coprophagous specialists owing to the lack of parental care (e.g. resource relocation) and slow growth rates. We hypothesize that coprophagous Lepidoptera will be restricted to competitionand predation-free habitats and resources, feeding on excrement inside caves and animal burrows.