Miracle-dz/UniFAR-FTUs huggingface dataset:
Integration of K+ and Cl– currents regulate steady‐state and dynamic membrane potentials in cultured rat microglia

The role of ion channels and membrane potential (Vm) in non‐excitable cells has recently come under increased scrutiny. Microglia, the brain's resident immune cells, express voltage‐gated Kv1.3 channels, a Kir2.1‐like inward rectifier, a swelling‐activated Cl– current and several other channels. We previously showed that Kv1.3 and Cl– currents are needed for microglial cell proliferation and that Kv1.3 is important for the respiratory burst. Although their mechanisms of action are unknown, one general role for these channels is to maintain a negative Vm. An impediment to measuring Vm in non‐excitable cells is that many have a very high electrical resistance, which makes them extremely susceptible to leak‐induced depolarization. Using non‐invasive Vm‐sensitive dyes, we show for the first time that the membrane resistance of microglial cells is several gigaohms; much higher than the seal resistance during patch‐clamp recordings. Surprisingly, we observed that small current injections can evoke large Vm oscillations in some microglial cells, and that injection of sinusoidal currents of varying frequency exposes a strong intrinsic electrical resonance in the 5‐ to 20‐Hz frequency range in all microglial cells tested. Using a dynamic current clamp that we developed to actively compensate for the damage done by the patch‐clamp electrode, we found that the Vm oscillations and resonance were more prevalent and larger. Both types of electrical behaviour required Kv1.3 channels, as they were eliminated by the Kv1.3 blocker, agitoxin‐2. To further determine how the ion currents integrate in these cells, voltage‐clamp recordings from microglial cells displaying these behaviours were used to analyse the biophysical properties of the Kv1.3, Kir and Cl– currents. A mathematical model that incorporated only these three currents reproduced the observed Vm oscillations and electrical resonance. Thus, the electrical behaviour of this ‘non‐excitable’ cell type is much more complex than previously suspected, and might reflect a more common oversight in high resistance cells.
Proteomic Dissection of Nanotopography-Sensitive Mechanotransductive Signaling Hubs that Foster Neuronal Differentiation in PC12 Cells

Neuronal cells are competent in precisely sensing nanotopographical features of their microenvironment. The perceived microenvironmental information will be “interpreted” by mechanotransductive processes and impacts on neuronal functioning and differentiation. Attempts to influence neuronal differentiation by engineering substrates that mimic appropriate extracellular matrix (ECM) topographies are hampered by the fact that profound details of mechanosensing/-transduction complexity remain elusive. Introducing omics methods into these biomaterial approaches has the potential to provide a deeper insight into the molecular processes and signaling cascades underlying mechanosensing/-transduction but their exigence in cellular material is often opposed by technical limitations of major substrate top-down fabrication methods. Supersonic cluster beam deposition (SCBD) allows instead the bottom-up fabrication of nanostructured substrates over large areas characterized by a quantitatively controllable ECM-like nanoroughness that has been recently shown to foster neuron differentiation and maturation. Exploiting this capacity of SCBD, we challenged mechanosensing/-transduction and differentiative behavior of neuron-like PC12 cells with diverse nanotopographies and/or changes of their biomechanical status, and analyzed their phosphoproteomic profiles in these settings. Versatile proteins that can be associated to significant processes along the mechanotransductive signal sequence, i.e., cell/cell interaction, glycocalyx and ECM, membrane/f-actin linkage and integrin activation, cell/substrate interaction, integrin adhesion complex, actomyosin organization/cellular mechanics, nuclear organization, and transcriptional regulation, were affected. The phosphoproteomic data suggested furthermore an involvement of ILK, mTOR, Wnt, and calcium signaling in these nanotopography- and/or cell mechanics-related processes. Altogether, potential nanotopography-sensitive mechanotransductive signaling hubs participating in neuronal differentiation were dissected.
Use of statistical programs for nonparametric tests of small samples often leads to incorrectPvalues: examples fromAnimal Behaviour


In recent years, the use of software for the calculation of statistical tests has become widespread. For many nonparametric tests, a number of statistical programs calculate significance levels based on algorithms appropriate for large samples only (‘asymptotic testing’). In behavioural sciences, however, small samples are common. In nonparametric tests, this requires the use of the ‘exact’ variant of the respective statistical test. Using the asymptotic variant of a nonparametric test with small sample sizes usually yields an incorrect P value, and consequently, this may lead to a false acceptance or rejection of the null hypothesis. With the frequent application of statistical packages, the inappropriate use of the asymptotic variant has unfortunately become quite common. We examined the results of nonparametric tests with small sample sizes published in a recent issue of Animal Behaviour and found that in more than half of the articles concerned, the asymptotic variant had apparently been inappropriately used and incorrect P values had been presented. Before describing this analysis of papers published in Animal Behaviour, we provide a short overview of the differences between asymptotic and exact testing and discuss the consequences of the inappropriate use of asymptotic tests.
Phishing Detection: A Case Analysis on Classifiers with Rules Using Machine Learning

A typical predictive approach in data mining that produces If-Then knowledge for decision making is rule-based classification. Rule-based classification includes a large number of algorithms that fall under the categories of covering, greedy, rule induction, and associative classification. These approaches have shown promising results due to the simplicity of the models generated and the user’s ability to understand, and maintain them. Phishing is one of the emergent online threats in web security domains that necessitates anti-phishing models with rules so users can easily differentiate among website types. This paper critically analyses recent research studies on the use of predictive models with rules for phishing detection, and evaluates the applicability of these approaches on phishing. To accomplish our task, we experimentally evaluate four different rule-based classifiers that belong to greedy, associative classification and rule induction approaches on real phishing datasets and with respect to different evaluation measures. Moreover, we assess the classifiers derived and contrast them with known classic classification algorithms including Bayes Net and Simple Logistics. The aim of the comparison is to determine the pros and cons of predictive models with rules and reveal their actual performance when it comes to detecting phishing activities. The results clearly showed that eDRI, a recently greedy algorithm, not only generates useful models but these are also highly competitive with respect to predictive accuracy as well as runtime when they are employed as anti-phishing tools.
Is newly diagnosed type 2 diabetes treated according to the guidelines? Results of the Polish ARETAEUS1 study.

INTRODUCTION There is a paucity of data on meeting treatment goals in patients with newly diagnosed type 2 diabetes (DM2). OBJECTIVES The aim of the study was to characterize Polish patients with newly diagnosed DM2, to assess management of hyperglycemia, and to estimate the proportion of patients achieving the criteria of disease control recommended by the national clinical practice guidelines published in 2008. PATIENTS AND METHODS ARETAEUS1 was a cross-sectional questionnaire-based study conducted in several regions of Poland in 2009 (January-April). It involved 1714 patients with DM2 of any age and sex, treated for less than 24 months, and recruited by randomly selected physicians. RESULTS Only 28.9% of patients with DM2 met the goal for glycated hemoglobin (HbA1c) control (<6.5%). In the total population, only 1.4% of all patients met all 3 goals (HbA1c, blood pressure, and lipid levels), 12.5%--2 goals, and 35.3%--only 1 goal; 50.7% did not meet any of the treatment goals. Achieving all of the treatment goals varied between the patient subgroups (in relation to the current diabetes treatment, age, sex, body mass index, and diabetes duration). CONCLUSIONS Most patients with newly diagnosed DM2 do not meet all their major treatment goals, which indicates relatively low adherence to the national guideline recommendations for diabetes control and primary cardiovascular prevention in DM2. Metformin seems to be underused and titration of other glucose lowering medications may be insufficiently target-driven. Assuming that adherence to the current clinical practice guidelines is beneficial for patients, we recommend that both practitioners and patients have increased awareness of these guidelines and of the ways to achieve and maintain treatment goals.
POT 1-interacting protein PIP 1 : a telomere length regulator that recruits POT 1 to the TIN 2 / TRF 1 complex

Human telomere length is controlled by a negative feedback loop based on the binding of TRF1 to doublestranded telomeric DNA. The TRF1 complex recruits POT1, a single-stranded telomeric DNA-binding protein necessary for cis-inhibition of telomerase. By mass spectrometry, we have identified a new telomeric protein, which we have named POT1-interacting protein 1 (PIP1). PIP1 bound both POT1 and the TRF1-interacting factor TIN2 and could tether POT1 to the TRF1 complex. Reduction of PIP1 or POT1 levels with shRNAs led to telomere elongation, indicating that PIP1 contributes to telomere length control through recruitment of POT1.
Pricing Capital Under Mandatory Unbundling and Facilities Sharing

The regulation of telecommunications, railroads, and other network industries has been based on mandatory unbundling and facilities sharing - entrants have the option to lease part or all of incumbents' facilities if and when they desire, at rates determined by regulators. This flexibility is of great value to entrants, but because investments are largely irreversible, it is costly to supply by incumbents. However, pricing formulas used by regulators to set lease rates for capital do not compensate incumbents for this flexibility, so that incumbents are effectively forced to subsidized entrants, discouraging further investments. This paper shows how pricing formulas used to set lease rates can be adjusted to account for the transfer of option value from incumbents to entrants, and estimates the average size of the adjustment for land-based local voice telecommunications in the U.S.
Magnetic phases of ultrathin Fe grown on Cu(100) as epitaxial wedges.

Magnetic wedges of Fe on Cu(100) are explored magneto-optically. In the region of 6--11 monolayers (ML) of fcc Fe grown at room temperature, in addition to a surface ferromagnetic layer with a Curie temperature [similar to]250 K, the Fe bulk is antiferromagnetic with a Neel temperature of [similar to]200 K. This fcc phase is stable only above a growth temperature of order [similar to]200 K, below which the ferromagnetic spin-reorientation transition occurs at [similar to]6 ML. The phase boundaries are delineated by cusps in the coercivity along the wedge.
A new paradigm for DNA polymerase specificity.

We show that T7 DNA polymerase exists in three distinct structural states, as reported by a conformationally sensitive fluorophore attached to the recognition (fingers) domain. The conformational change induced by a correct nucleotide commits the substrate to the forward reaction, and the slow reversal of the conformational change eliminates the rate of the chemistry step from any contribution toward enzyme specificity. Discrimination against mismatches is enhanced by the rapid release of mismatched nucleotides from the ternary E.DNA. deoxynucleoside triphosphate complex and by the use of substrate-binding energy to actively misalign catalytic residues to reduce the rate of misincorporation. Our refined model for enzyme selectivity extends traditional thermodynamic formalism by including substrate-induced structural alignment or misalignment of catalytic residues as a third dimension on the free-energy profile and by including the rate of substrate dissociation as a key kinetic parameter.
Historical perspective and recent insights into our understanding of the molecular and biochemical basis of the antitumor properties of mda-7/IL-24

A subtraction hybridization approach combined with a differentiation therapy model of human melanoma identified melanoma differentiation associated gene-7 (mda-7) as a gene up-regulated during induction of terminal differentiation. Based on conserved structure, chromosomal location and cytokine-like properties, mda-7, has now been classified as a member of the expanding interleukin (IL)-10 gene family and designated as mda-7/IL-24. Extensive in vitro and in vivo human tumor xenograft studies confirm that mda-7/IL-24 induces apoptosis specifically in tumor cells without harming normal cells. Unique properties of mda-7/IL-24 action also include potent “bystander antitumor” activity, an ability to exert anti-angiogenic effects, immune modulating ability and a capacity to enhance the sensitivity of tumor cells to radiotherapy, chemotherapy and monoclonal antibody therapy. Very recent studies from our groups further reveal autocrine regulation and chemoprevention facilitating properties of mda-7/IL-24. Based on these remarkable antitumor attributes, mda-7/IL-24 was evaluated by intratumoral injection with a replication incompetent adenovirus expressing this gene (Ad.mda-7; ING 241) in a phase I clinical trial in patients with metastatic melanomas and other advanced solid cancers. mda-7/IL-24 was well tolerated with significant clinical activity. This review highlights our current understanding of the molecular and biochemical basis of mda-7/IL-24 antitumor properties and highlights its potential as a viable gene-based therapy for a wide spectrum of primary and advanced cancers.
Analysis of sequences conferring autonomous replication in baker's yeast.

A method is presented for rapid sequencing and mapping of elements which support autonomous replication in yeast. The strategy relies on a novel phage M13 vector which allows detection of ARS (autonomously replicating sequence) function in cloned fragments. Deletion mapping of an ARS element linked to the HO gene of Saccharomyces cerevisiae has identified a 57‐bp region 3′ to the gene, which is essential for autonomous replication. This region shows sequence homology to other ARS elements.
A dynamic user-integrated cloud computing architecture

Cloud computing has been a hot point in the Internet information service. The architecture of existing cloud computing instances is powerful datacenter and weak clients which connect to network. However, it is still difficult to meet the architecture with China's network bandwidth. Meanwhile, establishment of a number of cloud computing centers must cause, to some extent, waste of resources for existing PC equipment. To solve these problems, we propose a dynamic user-integrated cloud computing architecture. In the architecture, it integrates clients with storage capacity and computing competency to datacenter dynamically, expanding the scale of cloud computing datacenter. Collaborate with clients, the datacenter provides services to the other users.
System level security modeling using attack trees

Vulnerabilities in intrusion tolerant systems have dependence on various dynamic aspects such as redundant mechanisms, fault and error recovery mechanisms, and different operation modes. The conventional nodes of attack trees can not adequately capture the attacks towards those systems, thus constructing security models for the systems is very difficult. This paper introduces new nodes to model the security of those systems. The nodes include: PAND node, k/n node, SEQ node, CSUB node, and Housing node. We provide the syntax and graphical representation for each node. The nodes allow us to model attacks that require exploitation of vulnerabilities which have dependence on ordering events, sequence-dependant events, conditional failures and mechanisms which involve configuration changes with time. We use the nodes to construct attack trees for different security related systems.
The effect of combining antitubulin agents on differentiated and undifferentiated human colon cancer cells

The cytotoxicity of sequential combinations of a taxoid [paclitaxel (TAX) or docetaxel (TXT)] with a vinca alkaloid [vinoreibine (NVB)] was compared in differentiated and undifferentiated HT29-D4 cells. Agents were titrated from low doses inducing no modification of microtubule network to high doses corresponding to the clinically relevant concentrations that block mitosis. For undifferentiated cells, the sequential combination NVB/TAX was more efficient than TAX/NVB (22% cell survival versus 37% for 5 nM TAX and NVB). Surprisingly, we successively obtained synergism for low doses of both compounds [NVB (1–5 nM) and TAX (1–15 nM)], then additivity and finally antagonism when one of the compounds was at the concentration inducing mitotic block. The three patterns of results were also obtained with NVB/TXT combinations. For the synergistic combinations at the lowest concentrations, cytotoxicity occurred by apoptosis following mitosis. For differentiated cells, the most cytotoxic combinations were 1 μM TAX or TXT for 3 days followed by 1 μM NVB for 3 days, and 0.75 nM TAX or TXT for 9 days followed by 1 μM NVB for 3 days, the latter producing synergistic effects. Cytotoxicity occurred by apoptosis for the two states of differentiation. Major differences depending on cell phenotype were demonstrated: low sensitivity of differentiated cells to antitubulin agents and the difference in apoptotic pathways since mitosis is not involved in differentiated cells.
The evolution of next-generation data center networks for high capacity computing

With the emergence of cloud computing, new data center architectures are being created to address the challenges of the new computing models. The scale of these next-generation data center networks drives the demand for high-density, low-latency and low-power networking solutions. These networks are being deployed with flat topologies, virtualization and low latency. The silicon solutions that are being developed to address these new networks are redefining the data center landscape. This paper and the presentation describe the cloud data model and the evolution of the data center, and then consider the technologies that are being developed to address the new paradigms. This paper also describes the silicon solutions (the underlying engines) and the challenges they must overcome to meet these requirements.
The Ras superfamily at a glance

The Ras superfamily of small guanosine triphosphatases (GTPases) comprise over 150 human members (Table S1 in [supplementary material][1]), with evolutionarily conserved orthologs found in Drosophila, C. elegans, S. cerevisiae, S. pombe, Dictyostelium and plants ([Colicelli, 2004][2]). The Ras
DISEASE PREDICTION IN DATA MINING TECHNIQUE – A SURVEY

Data mining is defined as sifting through very large amounts of data for useful information. Some of the most important and popular data mining techniques are association rules, classification, clustering, prediction and sequential patterns. Data mining techniques are used for variety of applications. In health care industry, data mining plays an important role for predicting diseases. For detecting a disease number of tests should be required from the patient. But using data mining technique the number of test should be reduced. This reduced test plays an important role in time and performance. This technique has an advantages and disadvantages. This research paper analyzes how data mining techniques are used for predicting different types of diseases. This paper reviewed the research papers which mainly concentrated on predicting heart disease, Diabetes and Breast cancer.
Integrating Specialist and Folk Knowledge with Affinity Propagation

Web users form a highly diverse group with varying interests, levels of expertise, enthusiasm, and expressiveness. This diversity is also manifested in the annotations users create to organize and label content on social Web sites. While several approaches have been proposed to mine social annotations, e.g., to create folksonomies, or taxonomies that reflect how a community organizes knowledge, these methods treat all users uniformly. We propose a framework to identify specialists, i.e., knowledgeable users who also create high quality annotations, and use their knowledge to guide the folksonomy learning problem. We illustrate the approach on social annotations extracted from the photosharing site Flickr and show that integrating specialist knowledge leads to more consistent and relevant folksonomies. Moreover, we show that including annotations from non-specialists leads to more comprehensive folksonomies than using specialist knowledge alone.
CLONING AND EXPRESSION OF A CYSTEINE PROTEINASE GENE FROM PARAGONIMUS WESTERMANI ADULT WORMS

A gene encoding a cysteine proteinase from Paragonimus westermani has been cloned and expressed in Escherichia coli. The cysteine proteinase cDNA fragment was amplified by reverse transcription–polymerase chain reaction (RT-PCR) using degenerate oligonucleotide primers derived from the conserved active site of the cysteine proteinase. The 5′ and 3′ regions of the gene were amplified using a PCR technique for the rapid amplification of cDNA ends. The cloned gene has an open reading frame of 687 bp and deduced amino acid sequence of 229. Sequence analysis and alignment showed significant homologies with the eukaryotic cysteine proteinases and conservation of the Cys, His, and Asp residues that form a catalytic triad. Analysis of the expressed protein on sodium dodecyl sulfate polyacrylamide gel electrophoresis showed that the molecular weight of the protein was approximately 28.5 kDa. The expressed protein reacted with the sera of patients with paragonimiasis but not with the sera of fascioliasis and clonorchiasis. These results suggest that the expressed protein may be valuable as a specific diagnostic material for the immunodiagnosis of paragonimiasis.