Miracle-dz/UniFAR-FTUs huggingface dataset:
The kinase ALK stimulates the kinase ERK5 to promote the expression of the oncogene MYCN in neuroblastoma

Targeting the kinase ERK5 may disrupt the activation of an oncogenic transcription factor in a subset of neuroblastoma patients. A New Target in Neuroblastoma Neuroblastoma is a common and aggressive pediatric cancer caused by various molecular abnormalites. Similar to other cancers, poor prognosis correlates with increased abundance or activation of the cell surface receptor tyrosine kinase ALK or increased abundance of the transcription factor MYCN. An ALK inhibitor used in the clinic is not wholly effective, and there are no therapies to directly target MYCN. Umapathy et al. found that ALK stimulated the expression of the gene encoding MYCN through a pathway involving several kinases in patient tumor cells. Targeting one of these kinases, ERK5, decreased the abundance of MYCN and suppressed proliferation in ALK-positive neuroblastoma cells in culture. Combined inhibition of ALK and ERK5 was more effective than the ALK inhibitor alone in limiting tumor growth in a mouse model. Thus, ERK5 represents a new target for treating ALK-driven cancers. Anaplastic lymphoma kinase (ALK) is an important molecular target in neuroblastoma. Although tyrosine kinase inhibitors abrogating ALK activity are currently in clinical use for the treatment of ALK-positive (ALK+) disease, monotherapy with ALK tyrosine kinase inhibitors may not be an adequate solution for ALK+ neuroblastoma patients. Increased expression of the gene encoding the transcription factor MYCN is common in neuroblastomas and correlates with poor prognosis. We found that the kinase ERK5 [also known as big mitogen-activated protein kinase (MAPK) 1 (BMK1)] is activated by ALK through a pathway mediated by phosphoinositide 3-kinase (PI3K), AKT, MAPK kinase kinase 3 (MEKK3), and MAPK kinase 5 (MEK5). ALK-induced transcription of MYCN and stimulation of cell proliferation required ERK5. Pharmacological or RNA interference–mediated inhibition of ERK5 suppressed the proliferation of neuroblastoma cells in culture and enhanced the antitumor efficacy of the ALK inhibitor crizotinib in both cells and xenograft models. Together, our results indicate that ERK5 mediates ALK-induced transcription of MYCN and proliferation of neuroblastoma, suggesting that targeting both ERK5 and ALK may be beneficial in neuroblastoma patients.
NIFAS: visual analysis of domain evolution in proteins

MOTIVATION Multi-domain proteins have evolved by insertions or deletions of distinct protein domains. Tracing the history of a certain domain combination can be important for functional annotation of multi-domain proteins, and for understanding the function of individual domains. In order to analyze the evolutionary history of the domains in modular proteins it is desirable to inspect a phylogenetic tree based on sequence divergence with the modular architecture of the sequences superimposed on the tree. RESULT A Java applet, NIFAS, that integrates graphical domain schematics for each sequence in an evolutionary tree was developed. NIFAS retrieves domain information from the Pfam database and uses CLUSTAL W to calculate a tree for a given Pfam domain. The tree can be displayed with symbolic bootstrap values, and to allow the user to focus on a part of the tree, the layout can be altered by swapping nodes, changing the outgroup, and showing/collapsing subtrees. NIFAS is integrated with the Pfam database and is accessible over the internet (http://www.cgr.ki.se/Pfam). As an example, we use NIFAS to analyze the evolution of domains in Protein Kinases C.
Cellular Microbiology of Mycoplasma canis

ABSTRACT Mycoplasma canis can infect many mammalian hosts but is best known as a commensal or opportunistic pathogen of dogs. The unexpected presence of M. canis in brains of dogs with idiopathic meningoencephalitis prompted new in vitro studies to help fill the void of basic knowledge about the organism's candidate virulence factors, the host responses that it elicits, and its potential roles in pathogenesis. Secretion of reactive oxygen species and sialidase varied quantitatively (P < 0.01) among strains of M. canis isolated from canine brain tissue or mucosal surfaces. All strains colonized the surface of canine MDCK epithelial and DH82 histiocyte cells and murine C8-D1A astrocytes. Transit through MDCK and DH82 cells was demonstrated by gentamicin protection assays and three-dimensional immunofluorescence imaging. Strains further varied (P < 0.01) in the extents to which they influenced the secretion of tumor necrosis factor alpha (TNF-α) and the neuroendocrine regulatory peptide endothelin-1 by DH82 cells. Inoculation with M. canis also decreased major histocompatibility complex class II (MHC-II) antigen expression by DH82 cells (P < 0.01), while secretion of gamma interferon (IFN-γ), interleukin-6 (IL-6), interleukin-10 (IL-10), and complement factor H was unaffected. The basis for differences in the responses elicited by these strains was not obvious in their genome sequences. No acute cytopathic effects on any homogeneous cell line, or consistent patterns of M. canis polyvalent antigen distribution in canine meningoencephalitis case brain tissues, were apparent. Thus, while it is not likely a primary neuropathogen, M. canis has the capacity to influence meningoencephalitis through complex interactions within the multicellular and neurochemical in vivo milieu.
Multimodal Segmental-Based Modeling of Tennis Video Broadcasts

Efficient multimodal fusion is a key feature of future video indexing systems. Hidden Markov models provide a powerful framework for video structure analysis but they require all video modalities to be strictly synchronous. Taking as a case study tennis broadcasts analysis, we introduce into video indexing segment models, a generalization of hidden Markov Models, where the fusion of different modalities can be performed with relaxed synchrony constraints. Segment models were experimentally proved to perform marginally better compared to hidden Markov models
Reasoning about Actions and Planning in LTL Action Theories

In this paper, we study reasoning about actions and planning with incomplete information in a setting where the dynamic system is specified by adopting Linear Temporal Logic (ltl). Specifically, we study: (i) reasoning about action effects (i.e., projection, historical queries, etc.), in such a setting; (ii) when actions can be legally executed, assuming a non-prescriptive approach, where executing an action is possible in a given situation unless forbidden by the system specification; (iii) the problem of finding conformant plans for temporally extended goals that consist of arbitrary ltl formulas, thus allowing for expressing sophisticated dynamic requirements. For each of these problems we establish techniques and characterize the computational complexity. For the last two problems we make use of a second-order variant of ltl.
NS5 of Dengue Virus Mediates STAT2 Binding and Degradation

ABSTRACT The mammalian interferon (IFN) signaling pathway is a primary component of the innate antiviral response. As such, viral pathogens have devised multiple mechanisms to antagonize this pathway and thus facilitate infection. Dengue virus (DENV) encodes several proteins (NS2a, NS4a, and NS4b) that have been shown individually to inhibit the IFN response. In addition, DENV infection results in reduced levels of expression of STAT2, which is required for IFN signaling (M. Jones, A. Davidson, L. Hibbert, P. Gruenwald, J. Schlaak, S. Ball, G. R. Foster, and M. Jacobs, J. Virol. 79:5414-5420, 2005). Translation of the DENV genome results in a single polypeptide, which is processed by viral and host proteases into at least 10 separate proteins. To date, no single DENV protein has been implicated in the targeting of STAT2 for decreased levels of expression. We demonstrate here that the polymerase of the virus, NS5, binds to STAT2 and is necessary and sufficient for its reduced level of expression. The decrease in protein level observed requires ubiquitination and proteasome activity, strongly suggesting an active degradation process. Furthermore, we show that the degradation of but not binding to STAT2 is dependent on the expression of the polymerase in the context of a polyprotein that undergoes proteolytic processing for NS5 maturation. Thus, the mature form of NS5, when not expressed as a precursor, was able to bind to STAT2 but was unable to target it for degradation, establishing a unique role for viral polyprotein processing in providing an additional function to a viral polypeptide. Therefore, we have identified both a novel mechanism by which DENV evades the innate immune response and a potential target for antiviral therapeutics.
Bed Topography Reconstruction in a Large Amplitude Meandering Flume: Application of Close Range Photogrammetry

Natural rivers are characterized by continuous variations in bed topography, especially along curved reaches. High resolution topographic data are necessary to analyze the mutual interactions between the downstream flow and the cross-stream flow, which determine the distribution of the bed-shear stress along the channel. Because of the difficulty in acquiring good and accurate data in rivers, the major part of studies have been conducted in laboratory flumes. This paper reports on a laboratory study in which the automatic digital photogrammetric survey was applied to derive the high-resolution Digital Surface Model (DSM) of the bed topography in a large amplitude meandering flume. In order to assess the advantages of the procedure, the bed profiles obtained by the DSM have been compared with those obtained using a servo-controlled vertical profiler (PV09) has been operated and discussed.
The Influence of CB, Silica and CaCO3 on Tensile and Morphological Properties of vPE/rPE/EPDM Blends

The virgin polyethylene (vPE) and recycled polyethylene (rPE) was melt blended with ethylene propylene diene terpolymer (EPDM) in different ratio by using a Haake Rheomix at 180°C and 50 rpm were prepared. The characterization such as tensile properties and morphology were examined. Results indicated that, the tensile strength and youngs modulus of vPE/rPE/EPDM with CB show the highest value compared to silica and CaCO3 except for elongation at break. The scanning electron microscopy (SEM) studies proved that, better dispersion and less agglomeration of CB and silica filled particles as compared to the CaCO3.
Learning to rank for quantity consensus queries

Web search is increasingly exploiting named entities like persons, places, businesses, addresses and dates. Entity ranking is also of current interest at INEX and TREC. Numerical quantities are an important class of entities, especially in queries about prices and features related to products, services and travel. We introduce Quantity Consensus Queries (QCQs), where each answer is a tight quantity interval distilled from evidence of relevance in thousands of snippets. Entity search and factoid question answering have benefited from aggregating evidence from multiple promising snippets, but these do not readily apply to quantities. Here we propose two new algorithms that learn to aggregate information from multiple snippets. We show that typical signals used in entity ranking, like rarity of query words and their lexical proximity to candidate quantities, are very noisy. Our algorithms learn to score and rankquantity intervals directly, combining snippet quantity and snippet text information. We report on experiments using hundreds of QCQs with ground truth taken from TREC QA, Wikipedia Infoboxes, and other sources, leading to tens of thousands of candidate snippets and quantities. Our algorithms yield about 20% better MAP and NDCG compared to the best-known collective rankers, and are 35% better than scoring snippets independent of each other.
GIScience Journals Ranking and Evaluation: An International Delphi Study

Researchers’ fame in most scientific fields is closely linked to their publishing capacity, both in terms of quantity and quality. In GIScience, as in other fields, this situation demands that the researcher evaluate and to be very familiar with the scientific journals in which they could publish. Some specialized journals (e.g. Journal of Citation Reports or JCR) are devoted to ranking these reviews according to various methods and criteria. Compared to other scientific communities, GIScience is relatively new and constantly evolving. Therefore, the journals of this field do not benefit from any real formal ranking yet. The objective of this paper is to present the process and results of a study aimed at addressing this gap. More specifically, the challenge is to elaborate an importance ranking of the scientific journals in the field of GIScience. To do so, both a qualitative (Delphi study carried out with 40 international experts) and a quantitative (JCR impact factor) approach has been implemented. This triangulation method leads to an early global ranking of the journals of this field.
GINS2 is a novel prognostic biomarker and promotes tumor progression in early-stage cervical cancer

GINS complex subunit 2 (GINS2), a member of the GINS complex, is involved in DNA replication. GINS2 is upregulated in a variety of aggressive tumors. However, its role in cervical cancer carcinogenesis remains to be elucidated. We investigated the clinical significance of GINS2 in patients with early-stage cervical cancer and its biological functions in cervical cancer progression. GINS2 expression was analyzed in cervical cancer cell lines and in 8 matched cervical cancer samples at the mRNA and protein levels using real-time PCR and western blotting, respectively. GINS2 protein expression in 155 paraffin-embedded cervical cancer specimens was validated using immunohistochemistry. Statistical analysis was used to evaluate its clinicopathological significance. Short hairpin RNA interference, anchorage-independent growth ability, colony formation assay, wound healing ability, Transwell assays and western blotting were used to determine the effects of GINS2 on the aggressive phenotype of cervical cancer cells. There was obvious upregulation of GINS2 in the cervical cancer cell lines and tumor specimens compared to that in the normal cervical tissues. Significant correlations were identified between GINS2 expression and squamous cell carcinoma antigen (SCC-Ag; P<0.001), deep stromal invasion (P=0.021), vital status (P<0.001), recurrence (P<0.001) and pelvic lymph node metastasis (PLNM; P<0.001). Moreover, patients with higher GINS2 expression had shorter overall survival (OS) compared to patients with low GINS2 expression. Multivariate analysis revealed that GINS2 may serve as an independent risk factor of poor prognosis in early-stage cervical cancer. In addition, GINS2 downregulation markedly suppressed cell proliferation and tumorigenic ability, as well as cell migration and invasion. Our findings suggest that GINS2 is a novel indicator of PLNM and a valuable prognostic biomarker in early-stage cervical cancer, and subsequently is a valuable molecular target for cervical cancer diagnosis and treatment.
Analysis of finite element approximations of a phase field model for two-phase fluids

This paper studies a phase field model for the mixture of two immiscible and incompressible fluids. The model is described by a nonlinear parabolic system consisting of the nonstationary Stokes equations coupled with the Allen-Cahn equation through an extra phase induced stress term in the Stokes equations and a fluid induced transport term in the Allen-Cahn equation. Both semi-discrete and fully discrete finite element methods are developed for approximating the parabolic system. It is shown that the proposed numerical methods satisfy a discrete energy law which mimics the basic energy law for the phase field model. Error estimates are derived for the semi-discrete method, and the convergence to the phase field model and to its sharp interface limiting model are established for the fully discrete finite element method by making use of the discrete energy law. Numerical experiments are also presented to validate the theory and to show the effectiveness of the combined phase field and finite element approach.
Achievable Rates and Training Optimization for Uplink Multiuser Massive MIMO Systems

We study the performance of uplink transmission in a large-scale (massive) MIMO system, where all the transmitters have single antennas and the receiver (base station) has a large number of antennas. Specifically, we first derive the rates th at are possible through minimum mean-squared error (MMSE) channel estimation and three linear receivers: maximum ratio combining (MRC), zero-forcing (ZF), and MMSE. Based on the derived rates, we quantify the amount of energy savings that are possible through increased number of base-station antennas or increased coherence interval. We also analyze achievable total degrees of freedom of such a system without assuming channel state information at the receiver, which is shown to be the same as that of a point-to-point MIMO channel. Linear receiver is sufficient when the number of users is less than the number of antennas. Otherwise, nonlinear processing is necessary to achieve the full degrees of freedom. Finally, the training period and optimal training energy allocation under the average and peak power constraints are optimized jointly to maximize the achievable sum rate when either MRC or ZF receiver is adopted at the receiver.
Spectrofluorimetric and isotachophoretic determination of maprotiline in human blood serum

Maprotiline determination in blood serum samples was investigated by the use of both capillary isotachophoresis and spectrofluorimetric techniques. The analyte had to be enriched before determination and extraction with n‐heptane was used for this purpose. The preliminary separation enabled the determination of maprotiline in blood serum at therapeutic concentration levels.
A step in the right direction : Botdetection in MMORPGs using movement analysis

Massively multiplayer online role playing games (MMORPG) is a genre in computer games which is gaining a lot of popularity all over the world. Cheating in these games can often be done by the use of a bot program. Such a program controls a character and allows the player to gain an unfair advantage over legitimate players, because repetitive and often boring tasks can be performed without any effort. Several methods for detecting bots have been proposed in the past. The method described in this research focuses on differences in the frequency of occurrence of different angles in the movement of bots and humans. A histogram is made based on the distribution of angles and a nearest centroid classifier is used. The result of this method is a classification rate of 100% on the used dataset.
Development of indirect ring tension test for fracture characterization of asphalt mixtures

OF DISSERTATION DEVELOPMENT OF INDIRECT RING TENSION TEST FOR FRACTURE CHARACTERIZATION OF ASPHALT MIXTURES Low temperature cracking is a major distress in asphalt pavements. Several test configurations have been introduced to characterize the fracture properties of hot mix (HMA); however, most are considered to be research tools due to the complexity of the test methods or equipment. This dissertation describes the development of the indirect ring tension (IRT) fracture test for HMA, which was designed to be an effective and userfriendly test that could be deployed at the Department of Transportation level. The primary advantages of this innovative and yet practical test include: relatively large fracture surface test zone, simplicity of the specimen geometry, widespread availability of the required test equipment, and ability to test laboratory compacted specimens as well as field cores. Numerical modeling was utilized to calibrate the stress intensity factor formula of the IRT fracture test for various specimen dimensions. The results of this extensive analysis were encapsulated in a single equation. To develop the test procedure, a laboratory study was conducted to determine the optimal test parameters for HMA material. An experimental plan was then developed to evaluate the capability of the test in capturing the variations in the mix properties, asphalt pavement density, asphalt material aging, and test temperature. Five plant-produced HMA mixtures were used in this extensive study, and the results revealed that the IRT fracture test is highly repeatable, and capable of capturing the variations in the fracture properties of HMA. Furthermore, an analytical model was developed based on the viscoelastic properties of HMA to estimate the maximum allowable crack size for the pavements in the experimental study. This analysis indicated that the low-temperature cracking potential of the asphalt mixtures is highly sensitive to the fracture toughness and brittleness of the HMA material. Additionally, the IRT fracture test data seemed to correlate well with the data from the distress survey which was conducted on the pavements after five years of service. The maximum allowable crack size analysis revealed that a significant improvement could be realized in terms of the pavements performance if the HMA were to be compacted to a higher density. Finally, the IRT fracture test data were compared to the results of the disk-shaped compact [DC(t)] test. The results of the two tests showed a strong correlation; however, the IRT test seemed to be more repeatable.
PROTEIN HYDROGELS AS TISSUE ENGINEERING SCAFFOLDS

Hydrogels aim to mimic the natural living environment by entrapping large amount of water or biological fluids in their polymeric network. There has been growing interest in the development of peptide and protein hydrogels, due to their improved biocompatibility, biodegradability and biological properties in comparison to purely synthetic polymer hydrogels. Under the appropriate conditions, biomacromolecular protein hydrogels can self-assemble into ordered meso- to macroscopic supramolecules with better resulting networks that promote tissue development. The work presented here mainly focuses on producing protein hydrogels with controlled physical properties useful for tissue regeneration process and drug delivery applications. Hen egg white lysozyme (HEWL) hydrogels were studied in the presence of water and different reducing agents forming three HEWL systems including HEWL/water, HEWL/DTT and HEWL/TCEP gels. Strong, self-supporting HEWL gels were successfully prepared in the range of pH 2 to 7, using a temperature of 85�C. At pH 2, the protein denaturation in water was relatively slow resulting in a high percentage of turn structure (~50%) that promotes HEWL gelation after 3 days of heating. No lysozyme gelation in water was observed at pH 3, 4 and 7 even after 21 days of heating. A small quantity of DTT (~20 mM) was added to encourage lysozyme unfolding and HEWL/DTT samples formed gels at higher pH including at physiological pH. The pH 2 HEWL/water gel was found to be stronger but more brittle than pH 7 HEWL/DTT gel. It was observed there were some irregularities in the distribution of pH 2 fibrils (~7�m in length) that form large pore sizes within the network. The pH 7 sample contained shorter and stiff fibrils with repetitive polygon-shaped mesh network. The use of TCEP, which is a stronger reductant than DTT, led to the formation of self-supporting HEWL gels between pH 3.5 and 5.5. The highest storage modulus was observed at pH 5, which is related to the high ? -sheet content of the sample (~45%). In addition, a promising strategy has been devised to form thermoresponsive HEWL hydrogels by synthesising and incorporating a small fraction of lysozyme-PNIPAAm bioconjugates into the major protein matrix. Results show the thermoresponsive nature of PNIPAAm was conferred to HEWL protein that exhibits higher storage stability in response to changing temperature.