Miracle-dz/UniFAR-FTUs huggingface dataset:
Structural Modeling and In Silico Analysis of Human Superoxide Dismutase 2

Aging in the world population has increased every year. Superoxide dismutase 2 (Mn-SOD or SOD2) protects against oxidative stress, a main factor influencing cellular longevity. Polymorphisms in SOD2 have been associated with the development of neurodegenerative diseases, such as Alzheimer’s and Parkinson’s disease, as well as psychiatric disorders, such as schizophrenia, depression and bipolar disorder. In this study, all of the described natural variants (S10I, A16V, E66V, G76R, I82T and R156W) of SOD2 were subjected to in silico analysis using eight different algorithms: SNPeffect, PolyPhen-2, PhD-SNP, PMUT, SIFT, SNAP, SNPs&GO and nsSNPAnalyzer. This analysis revealed disparate results for a few of the algorithms. The results showed that, from at least one algorithm, each amino acid substitution appears to harmfully affect the protein. Structural theoretical models were created for variants through comparative modelling performed using the MHOLline server (which includes MODELLER and PROCHECK) and ab initio modelling, using the I-Tasser server. The predicted models were evaluated using TM-align, and the results show that the models were constructed with high accuracy. The RMSD values of the modelled mutants indicated likely pathogenicity for all missense mutations. Structural phylogenetic analysis using ConSurf revealed that human SOD2 is highly conserved. As a result, a human-curated database was generated that enables biologists and clinicians to explore SOD2 nsSNPs, including predictions of their effects and visualisation of the alignment of both the wild-type and mutant structures. The database is freely available at http://bioinfogroup.com/database and will be regularly updated.
The study on Detecting Near-Duplicate WebPages

Reprinting information among websites produces a great deal redundant WebPages. To improve search efficiency and user satisfaction, an algorithm to Detect near-Duplicate WebPages (DDW) is proposed. In the course of developing a near-duplicate detection system for a multi-billion page repository, we make two research contributions. First, we consider both syntactic and semantic information to present and compute documentspsila similarities. Second, after classifying web-pages into different categories, we index feature in each category then search for near-duplicates only in the same category. From Google searching results for 72 queries, we select 5835 near-duplicate WebPages manually. Then insert them into an existing collection which contains about 768,763 WebPages, as the test data. The experimental results demonstrate that our approach outperforms I-Match algorithms. In large-scale test, approximate linear time and space complexity are gotten.
An active learning curriculum improves fellows’ knowledge and faculty teaching skills: a medical student perspective

We read with great interest the article by Inra et al 1 which discusses the benefits of using an active learning curriculum to improve faculty teaching skills and help fellows retain more knowledge compared to traditional teaching methods. As current medical students, we can vouch for the effectiveness of this approach in improving the way material can be taught, hence would like to offer our perspective on this. The study conducted on gastroenterology fellows evaluated the use of an active learning method to improve knowledge base and boost gastroenterology training exam (GTE) results. The results suggested an improvement in GTE scores and an increase in learner satisfaction compared to lecture-based teaching. A similar study was carried out in undergraduate medical education in the neurological field which looked at the effectiveness of team-based learning with real patients. This assessed the effects on knowledge retention and in-class engagement. The outcome matched that of the currently analyzed study, emphasizing the need for adapting newer methods of
The Roles of Angiogenesis in Malignant Melanoma: Trends in Basic Science Research over the Last 100 Years

Blood vessels arose during evolution carrying oxygen and nutrients to distant organs via complex networks of blood vessels penetrating organs and tissues. Mammalian cells require oxygen and nutrients for survival, of which oxygen has a diffusion limit of 100 to 200 μm between cell and blood vessel. For growth beyond this margin, cells must recruit new blood vessels, first by vasculogenesis, where embryonic vessels form from endothelial precursors, then angiogenesis which is the sprouting of interstitial tissue columns into the lumen of preexisting blood vessels. Angiogenesis occurs in many inflammatory diseases and in many malignant disease states, including over 90% of solid tumours. Malignant melanoma (MM) is the most lethal skin cancer, highly angiogenic, highly metastatic, and refractory to all treatments. Raised serum levels of vascular endothelial growth factor (VEGF) strongly correlate MM disease progression and poor prognosis. Melanoma cells secrete several proangiogenic cytokines including VEGF-A, fibroblast growth factor (FGF-2), platelet growth factor (PGF-1), interleukin-8 (IL-8), and transforming growth factor (TGF-1) that modulate the angiogenic switch, changing expression levels during tumour transition from radial to invasive vertical and then metastatic growth. We highlight modern and historical lines of research and development that are driving this exciting area of research currently.
SCALING AND MULTIFRACTAL CHARACTER OF MATRIX CRACKING IN CARBON FIBRE-REINFORCED CROSS-PLY LAMINATES

SUMMARY The paper presents the interpretation of the experimental data on the matrix cracking in the carbon fibre-reinforced epoxy laminates under tensile cyclic loading. The conception of the characteristic damage state is verified in terms of the temporal scaling of matrix cracking. Additional information on the character of the cracks' distribution along the axis of the specimen is obtained by utilization of the concept of multifractals. The proposed procedure of the experimental data treatment is applied for the various loading histories and composite structures (stacking order). The ways of the utilization of obtained characteristics in mechanical models of matrix cracking is discussed.
A composite HII region luminosity function in H alpha of unprecedented statistical weight

Context. Statistical properties of HII region populations in disk galaxies yield important clues to the physics of massive star formation. Aims. We present a set of HII region catalogues and luminosity functions for a sample of 56 spiral galaxies in order to derive the most general form of their luminosity function. Methods. HII region luminosity functions are derived for individual galaxies which, after photometric calibration, are summed to form a total luminosity function comprising 17,797 HII regions from 53 galaxies. Results. The total luminosity function, above its lower limit of completeness, is clearly best fitted by a double power law with a significantly steeper slope for the high luminosity portion of the function. This change of slope has been reported in the literature for individual galaxies, and occurs at a luminosity of log L = 38.6\pm0.1 (L in erg/s) which has been termed the Stromgren luminosity. A steep fall off in the luminosity function above log L = 40 is also noted, and is related to an upper limit to the luminosities of underlying massive stellar clusters. Detailed data are presented for the individual sample galaxies. Conclusions. The luminosity functions of HII regions in spiral galaxies show a two slope power law behaviour, with a significantly steeper slope for the high luminosity branch. This can be modelled by assuming that the high luminosity regions are density bounded, though the scenario is complicated by the inhomogeneity of the ionized interstellar medium. The break, irrespective of its origin, is of potential use as a distance indicator for disc galaxies.
Brentuximab Vedotin (SGN-35)

Brentuximab vedotin (SGN-35) is an antibody-drug conjugate (ADC) directed against the CD30 antigen expressed on Hodgkin lymphoma and anaplastic large cell lymphoma. SGN-35 consists of the cAC10 chimerized IgG1 monoclonal antibody SGN30, modified by the addition of a valine-citrulline dipeptide linker to permit attachment of the potent inhibitor of microtubule polymerization monomethylauristatin E (MMAE). In phase II trials, SGN-35 produced response rates of 75% in patients with Hodgkin lymphoma (n = 102) and 87% in patients with anaplastic large cell lymphoma (n = 30). Responses to SGN-35 might be related not only to the cytotoxic effect due to release of MMAE within the malignant cell but also to other effects. First, SGN-35 may signal malignant cells through CD30 ligation to deliver an apoptotic or proliferative response. The former would amplify the cytotoxicity of MMAE. A proliferative signal delivered in the context of MMAE intoxication could enhance cell death. Second, the efficacy of SGN-35, particularly in Hodgkin lymphoma, might be attributed to its effect on the tumor microenvironment. Diffusion of free MMAE from the targeted tumor cells could result in a bystander effect that kills the normal supporting cells in close proximity to the malignant cells. The elimination of T regulatory cells that inhibit cytotoxic effector cells and elimination of cells that provide growth factor support for Hodgkin/Reed–Sternberg cells could further enhance the cytotoxic activity of SGN-35. Here we review the biology of SGN-35 and the clinical effects of SGN-35 administration. Clin Cancer Res; 17(20); 6428–36. ©2011 AACR.
Improvement of the Results of Statistical Machine Translation System using Anusaaraka

This paper describes an efficient experimental approach for the improvement of translation quality of phrase based statistical machine translation system by utilizing the insights of the rule based machine translation. As the most primitive step it is believed that appending large and accurately designed linguistic resources such as multiword bilingual dictionaries to the existing training corpus contributes a lot towards the enhancement of phrase alignment quality and phrase coverage of the Statistical Machine Translation (SMT) system. Further improvement in translation coverage can be achieved by improving the dictionary by introducing morphsyntactic word forms of the foreign language words instead of simple root word forms, and its corresponding translations in native language. As in real time testing scenario, the test corpus may possess different morphological extensions of the root word which is not covered by standard dictionaries. As a matter of fact addition of such dictionaries to the corpus enriches it and provides a solution to the improper translations previously generated due to occurrences of morph-syntactic extensions instead of the root word form. As the proposed approach towards further improvement, the intelligence of Anusaaraka and huge computational ability of SMT is integrated to achieve better translations. Anusaaraka is a machine translation system based on Panini’s Astadhyayi grammatical rules and an expert when the English-Hindi phrase alignment is concerned. It does it by comparing its output translation with the accurate manual translation and extracting out the best possible option. The bi-lingual phrase pairs thus obtained are highly accurate and when appended to the training corpus of statistical machine translation system results as better phrase alignment structure, hence better translation quality.
Connecting IPv6 Islands over IPv4 MPLS Using IPv6 Provider Edge Routers (6PE)

This document explains how to interconnect IPv6 islands over a Multiprotocol Label Switching (MPLS)-enabled IPv4 cloud. This approach relies on IPv6 Provider Edge routers (6PE), which are Dual Stack in order to connect to IPv6 islands and to the MPLS core, which is only required to run IPv4 MPLS. The 6PE routers exchange the IPv6 reachability information transparently over the core using the Multiprotocol Border Gateway Protocol (MP-BGP) over IPv4. In doing so, the BGP Next Hop field is used to convey the IPv4 address of the 6PE router so that dynamically established IPv4-signaled MPLS Label Switched Paths (LSPs) can be used without explicit tunnel configuration. [STANDARDS-TRACK]
Identification of MicroRNA-21 as a Biomarker for Chemoresistance and Clinical Outcome Following Adjuvant Therapy in Resectable Pancreatic Cancer

Background Pancreatic ductal adenocarcinoma (PDAC) has a dismal prognosis. The high risk of recurrence following surgical resection provides the rationale for adjuvant therapy. However, only a subset of patients benefit from adjuvant therapy. Identification of molecular markers to predict treatment outcome is therefore warranted. The aim of the present study was to evaluate whether expression of novel candidate biomarkers, including microRNAs, can predict clinical outcome in PDAC patients treated with adjuvant therapy. Methodology/Principal Findings Formalin-fixed paraffin embedded specimens from a cohort of 82 resected Korean PDAC cases were analyzed for protein expression by immunohistochemistry and for microRNA expression using quantitative Real-Time PCR. Cox proportional hazards model analysis in the subgroup of patients treated with adjuvant therapy (N = 52) showed that lower than median miR-21 expression was associated with a significantly lower hazard ratio (HR) for death (HR = 0.316; 95%CI = 0.166–0.600; P = 0.0004) and recurrence (HR = 0.521; 95%CI = 0.280–0.967; P = 0.04). MiR-21 expression status emerged as the single most predictive biomarker for treatment outcome among all 27 biological and 9 clinicopathological factors evaluated. No significant association was detected in patients not treated with adjuvant therapy. In an independent validation cohort of 45 frozen PDAC tissues from Italian cases, all treated with adjuvant therapy, lower than median miR-21 expression was confirmed to be correlated with longer overall as well as disease-free survival. Furthermore, transfection with anti-miR-21 enhanced the chemosensitivity of PDAC cells. Conclusions Significance Low miR-21 expression was associated with benefit from adjuvant treatment in two independent cohorts of PDAC cases, and anti-miR-21 increased anticancer drug activity in vitro. These data provide evidence that miR-21 may allow stratification for adjuvant therapy, and represents a new potential target for therapy in PDAC.
Fuzzy weighted average filtering for mixture noises

The classic nonlinear filter performs well in impulse noise suppression and edge preserving. However, the classic nonlinear filtering is not good at reducing the mixture of Gaussian noise and impulse noise. In this paper, we investigate the nonlinear filtering techniques to eliminate the mixture of impulse noise and Gaussian noise. Based on fuzzy theory, we present a weighted average filter by making use of the fuzzy membership functions to optimize the weights of the filter. Computational results, which have been obtained from experiments for noise attenuation, indicate that the new algorithm is promising.
pH-Insensitive FRET Voltage Dyes

Many high-throughput ion channel assays require the use of voltage-sensitive dyes to detect channel activity in the presence of test compounds. Dye systems employing Förster resonance energy transfer (FRET) between 2 membrane-bound dyes are advantageous in combining high sensitivity, relatively fast response, and ratiometric output. The most widely used FRET voltage dye system employs a coumarin fluorescence donor whose excitation spectrum is pH dependent. The authors have validated a new class of voltage-sensitive FRET donors based on a pyrene moiety. These dyes are significantly brighter than CC2-DMPE and are not pH sensitive in the physiological range. With the new dye system, the authors demonstrate a new high-throughput assay for the acid-sensing ion channel (ASIC) family. They also introduce a novel method for absolute calibration of voltage-sensitive dyes, simultaneously determining the resting membrane potential of a cell. (Journal of Biomolecular Screening 2007:656-667)
N-Gram Based Filler Model for Robust Grammar Authoring

We propose a technique for rapid speech application development that generates robust semantic context-free grammars (CFG) given rigid CFGs as input. Users' speech does not always conform to rigid CFGs, so robust grammars improve the caller's experience. Our system takes a simple CFG and then generates a hybrid n-gram/CFG that is written in the W3C SRGS format and thus can run in many standard automatic speech recognition engines. The hybrid network leverages an application-independent word n-gram which can be shared across different applications. In addition, our tool allows developers to provide a few example sentences to adapt the n-gram for improved accuracy. Our experiments show the robust CFG has no loss in accuracy for test utterances that can be covered by the rigid CFG, but offers large improvements for cases where the user's sentence cannot be covered by the rigid CFG. It also has a much better rejection for utterances that contain no slot at all. With a few example sentences for adaptation, our robust CFG can achieve the recognition accuracy close to the class-based n-gram LM customized for the application
Smoking-related health risks among persons with HIV in the Strategies for Management of Antiretroviral Therapy clinical trial.

OBJECTIVES We sought to determine smoking-related hazard ratios (HRs) and population-attributable risk percentage (PAR%) for serious clinical events and death among HIV-positive persons, whose smoking prevalence is higher than in the general population. METHODS For 5472 HIV-infected persons enrolled from 33 countries in the Strategies for Management of Antiretroviral Therapy clinical trial, we evaluated the relationship between baseline smoking status and development of AIDS-related or serious non-AIDS events and overall mortality. RESULTS Among all participants, 40.5% were current smokers and 24.8% were former smokers. Adjusted HRs were higher for current than for never smokers for overall mortality (2.4; P < .001), major cardiovascular disease (2.0; P = .002), non-AIDS cancer (1.8; P = .008), and bacterial pneumonia (2.3; P < .001). Adjusted HRs also were significantly higher for these outcomes among current than among former smokers. The PAR% for current versus former and never smokers combined was 24.3% for overall mortality, 25.3% for major cardiovascular disease, 30.6% for non-AIDS cancer, and 25.4% for bacterial pneumonia. CONCLUSIONS Smoking contributes to substantial morbidity and mortality in this HIV-infected population. Providers should routinely integrate smoking cessation programs into HIV health care.
Generalized processor sharing networks with exponentially bounded burstiness arrivals

We consider virtual circuit packet switching communication networks that employ processor sharing type service disciplines and study their stability. We employ an exponential characterization (EBB) introduced in a previous work to analyze this type of systems in a stochastic setting. We first examine the general processor sharing (GPS) and packet based (PGPS) servers in isolation, and then proceed to interconnected networks of such servers. In all these cases we show that the natural throughout condition is a necessary and sufficient condition for stability. <<ETX>>
Time Course of Shape and Category Selectivity Revealed by EEG Rapid Adaptation

A hallmark of human cognition is the ability to rapidly assign meaning to sensory stimuli. It has been suggested that this fast visual object categorization ability is accomplished by a feedforward processing hierarchy consisting of shape-selective neurons in occipito-temporal cortex that feed into task circuits in frontal cortex computing conceptual category membership. We performed an EEG rapid adaptation study to test this hypothesis. Participants were trained to categorize novel stimuli generated with a morphing system that precisely controlled both stimulus shape and category membership. We subsequently performed EEG recordings while participants performed a category matching task on pairs of successively presented stimuli. We used space–time cluster analysis to identify channels and latencies exhibiting selective neural responses. Neural signals before 200 msec on posterior channels demonstrated a release from adaptation for shape changes, irrespective of category membership, compatible with a shape- but not explicitly category-selective neural representation. A subsequent cluster with anterior topography appeared after 200 msec and exhibited release from adaptation consistent with explicit categorization. These signals were subsequently modulated by perceptual uncertainty starting around 300 msec. The degree of category selectivity of the anterior signals was strongly predictive of behavioral performance. We also observed a posterior category-selective signal after 300 msec exhibiting significant functional connectivity with the initial anterior category-selective signal. In summary, our study supports the proposition that perceptual categorization is accomplished by the brain within a quarter second through a largely feedforward process culminating in frontal areas, followed by later category-selective signals in posterior regions.
Recognizing sketched multistroke primitives

Sketch recognition attempts to interpret the hand-sketched markings made by users on an electronic medium. Through recognition, sketches and diagrams can be interpreted and sent to simulators or other meaningful analyzers. Primitives are the basic building block shapes used by high-level visual grammars to describe the symbols of a given sketch domain. However, one limitation of these primitive recognizers is that they often only support basic shapes drawn with a single stroke. Furthermore, recognizers that do support multistroke primitives place additional constraints on users, such as temporal timeouts or modal button presses to signal shape completion. The goal of this research is twofold. First, we wanted to determine the drawing habits of most users. Our studies found multistroke primitives to be more prevalent than multiple primitives drawn in a single stroke. Additionally, our studies confirmed that threading is less frequent when there are more sides to a figure. Next, we developed an algorithm that is capable of recognizing multistroke primitives without requiring special drawing constraints. The algorithm uses a graph-building and search technique that takes advantage of Tarjan's linear search algorithm, along with principles to determine the goodness of a fit. Our novel, constraint-free recognizer achieves accuracy rates of 96% on freely-drawn primitives.
Fractality of Massive Graphs: Scalable Analysis with Sketch-Based Box-Covering Algorithm

Analysis and modeling of networked objects are fundamental pieces of modern data mining. Most real-world networks, from biological to social ones, are known to have common structural properties. These properties allow us to model the growth processes of networks and to develop useful algorithms. One remarkable example is the fractality of networks, which suggests the self-similar organization of global network structure. To determine the fractality of a network, we need to solve the so-called box-covering problem, where preceding algorithms are not feasible for large-scale networks. The lack of an efficient algorithm prevents us from investigating the fractal nature of large-scale networks. To overcome this issue, we propose a new box-covering algorithm based on recently emerging sketching techniques. We theoretically show that it works in near-linear time with a guarantee of solution accuracy. In experiments, we have confirmed that the algorithm enables us to study the fractality of million-scale networks for the first time. We have observed that its outputs are sufficiently accurate and that its time and space requirements are orders of magnitude smaller than those of previous algorithms.