Miracle-dz/UniFAR-FTUs huggingface dataset:
The postoperative Model for End stage Liver Disease score as a predictor of short-term outcome after transplantation of extended criteria donor livers

Background Recently, the postoperative Model for End stage Liver Disease score (POPMELD) was suggested as a definition of postoperative graft dysfunction and a predictor of outcome after liver transplantation (LT). Aim The aim of the present study was to validate this concept in the context of extended criteria donor (ECD) organs. Patients and methods Single-center prospectively collected data (OPAL study/01/11-12/13) of 116 ECD LTs were utilized. For each recipient, the Model for End stage Liver Disease (MELD) score was calculated for 7 postoperative days (PODs). The ability of international normalized ratio, bilirubin, aspartate aminotransferase, Donor Risk Index, a recent definition of early allograft dysfunction, and the POPMELD was compared to predict 90-day graft loss. Predictive abilities were compared by receiver operating characteristic curves, sensitivity and specificity, and positive and negative predictive values. Results The median Donor Risk Index was 1.8. In all, 60.3% of recipients were men [median age of 54 (23–68) years]. The median POD1–7 peak-aspartate aminotransferase value was 1052 (194–17 577) U/l. The rate of early allograft dysfunction was 22.4%. The 90-day graft survival was 89.7%. Out of possible predictors of the 90-day graft loss MELD on POD5 was the best predictor of outcome (area under the curve=0.84). A MELD score of 16 or more on POD5 predicted the 90-day graft loss with a specificity of 80.8%, a sensitivity of 81.8%, and a positive and negative predictive value of 31 and 97.7%. Conclusion A MELD score of 16 or more on POD5 is an excellent predictor of outcome in ECD donor LT. Routine evaluation of POPMELD scores might support clinical decision-making and should be reported routinely in clinical trials.
Adenosine-induced apoptosis in glomerular mesangial cells.

BACKGROUND Mesangial cell apoptosis is a mechanism of resolution of glomerular hypercellularity in inflammatory forms of glomerular injury in which adenosine (ADO) was shown to play an anti-inflammatory role. This, and the observation that mesangial cell have ADO receptors prompted us to determine whether ADO induces mesangial cell apoptosis and to explore underlying mechanisms. METHODS Cultured mouse mesangial cell were incubated in the presence or absence of ADO or ADO receptor agonists (R-PIA, NECA, IB-MECA, CGS26180) or antagonists (DPCPX, DPSPX, MRS1191) for 48 hours. Cell death was assessed by trypan blue exclusion analysis. Apoptosis was assessed by DNA fragmentation, TUNEL staining and flow cytometry. RESULTS ADO and the A3 ADO receptor agonist IB-MECA induced mesangial cell death, which was markedly attenuated by the A3 receptor antagonist MRS1191. The A1 receptor agonist R-PIA, A2 receptor agonist NECA or the A2a receptor agonist CGS-12680 had no effect. The IB-MECA-induced mesangial cell death was due to apoptosis. This occurred via a cAMP independent mechanism. RT-PCR analysis revealed presence of A3, A1 and A2b but lack of A2a receptor transcripts in MC total RNA. Western blot analysis of mesangial cell lysates revealed expression the A3 receptor protein only. CONCLUSION The observations indicate that ADO induces mesangial cell apoptosis via stimulation of the A3 receptor.
Generation and characterization of Tbx 1-AmCyan 1 transgenic reporter mouse line that selectively labels developing thymus primordium

Thymus development is a complicated process that includes highly dynamic morphological changes and reciprocal tissue interactions between endoderm-derived epithelial cells of the anterior foregut and neural crest-derived mesenchymal cells. We generated and characterized a Tbx1-AmCyan1 reporter transgenic mouse to visualize thymus precursor cells during early embryonic development. In transgenic embryos, AmCyan1 fluorescence was specifically detected in the endoderm of the developing 3rd and 4th pharyngeal pouches and later in thymus epithelium until E14.5. Cells expressing AmCyan1 that were isolated based on AmCyan1 fluorescence expressed endodermal, thymic, and parathyroid markers, but they did not express neural crest or endothelial markers; these findings indicated that this transgenic mouse strain could be used to collect thymic or parathyroid precursor cells or both. We also showed that in nude mice, which exhibit defects in thymus development, the thymus precursors were clearly labeled with AmCyan1. In summary, these AmCyan1-fluorescent transgenic mice are useful for investigating early thymus development.
SNP Selection and Classification of Genome-Wide SNP Data Using Stratified Sampling Random Forests

For high dimensional genome-wide association (GWA) case-control data of complex disease, there are usually a large portion of single-nucleotide polymorphisms (SNPs) that are irrelevant with the disease. A simple random sampling method in random forest using default mtry parameter to choose feature subspace, will select too many subspaces without informative SNPs. Exhaustive searching an optimal mtry is often required in order to include useful and relevant SNPs and get rid of vast of non-informative SNPs. However, it is too time-consuming and not favorable in GWA for high-dimensional data. The main aim of this paper is to propose a stratified sampling method for feature subspace selection to generate decision trees in a random forest for GWA high-dimensional data. Our idea is to design an equal-width discretization scheme for informativeness to divide SNPs into multiple groups. In feature subspace selection, we randomly select the same number of SNPs from each group and combine them to form a subspace to generate a decision tree. The advantage of this stratified sampling procedure can make sure each subspace contains enough useful SNPs, but can avoid a very high computational cost of exhaustive search of an optimal mtry, and maintain the randomness of a random forest. We employ two genome-wide SNP data sets (Parkinson case-control data comprised of 408 803 SNPs and Alzheimer case-control data comprised of 380 157 SNPs) to demonstrate that the proposed stratified sampling method is effective, and it can generate better random forest with higher accuracy and lower error bound than those by Breiman's random forest generation method. For Parkinson data, we also show some interesting genes identified by the method, which may be associated with neurological disorders for further biological investigations.
Notch Signalling Is Required for the Formation of Structurally Stable Muscle Fibres in Zebrafish

Background Accurate regulation of Notch signalling is central for developmental processes in a variety of tissues, but its function in pectoral fin development in zebrafish is still unknown. Methodology/Principal Findings Here we show that core elements necessary for a functional Notch pathway are expressed in developing pectoral fins in or near prospective muscle territories. Blocking Notch signalling at different levels of the pathway consistently leads to the formation of thin, wavy, fragmented and mechanically weak muscles fibres and loss of stress fibres in endoskeletal disc cells in pectoral fins. Although the structural muscle genes encoding Desmin and Vinculin are normally transcribed in Notch-disrupted pectoral fins, their proteins levels are severely reduced, suggesting that weak mechanical forces produced by the muscle fibres are unable to stabilize/localize these proteins. Moreover, in Notch signalling disrupted pectoral fins there is a decrease in the number of Pax7-positive cells indicative of a defect in myogenesis. Conclusions/Significance We propose that by controlling the differentiation of myogenic progenitor cells, Notch signalling might secure the formation of structurally stable muscle fibres in the zebrafish pectoral fin.
Polarity of spindle microtubules in Haemanthus endosperm

Structural polarities of mitotic spindle microtubules in the plant Haemanthus katherinae have been studied by lysing endosperm cells in solutions of neurotubulin under conditions that will decorate cellular microtubules with curved sheets of tubulin protofilaments. Microtubule polarity was observed at several positions in each cell by cutting serial thin sections perpendicular to the spindle axis. The majority of the microtubules present in a metaphase or anaphase half-spindle are oriented with their fast-growing or "plus" ends distal to the polar area. Near the polar ends of the spindle and up to about halfway between the kinetichores and the poles, the number of microtubules with opposite polarity is low: 8-20% in metaphase and 2-15% in anaphase cells. Direct examination of 10 kinetochore fibers shows that the majority of these microtubules, too, are oriented with their plus ends distal to the poles, as had been previously shown in animal cells. Sections from the region near the spindle equator reveal an increased fraction of microtubules with opposite polarity. Graphs of polarity vs. position along the spindle axis display a smooth transition from microtubules of one orientation near the first pole, through a region containing equal numbers of the two orientations, to a zone near the second pole where the opposite polarity predominates. We conclude that the spindle of endosperm cells is constructed from two sets of microtubules with opposite polarity that interdigitate near the spindle equator. The length of the zone of interdigitation shortens from metaphase through telophase, consistent with a model that states that during anaphase spindle elongation in Haemanthus, the interdigitating sets of microtubules are moved apart. We found no major changes in the distribution of microtubule polarity in the spindle interzone from anaphase to telophase when cells are engaged in phragmoplast formation. Therefore, the initiation and organization of new microtubules, thought to take place during phragmoplast assembly, must occur without significant alteration of the microtubule polarity distribution.
An Investigation of Phone Upgrades in Remote Community Cellular Networks

In the last decade, billions of people worldwide have upgraded from basic 2G feature phones to data-enabled 4G smartphones. In most cases, people upgrade in areas with 4G coverage (typically cities and large towns), but increasingly, people choose to upgrade in areas that only have 2G coverage or no cellular coverage at all. This counterintuitive behavior -- upgrading your phone despite living in an area that does not actively support many of the features of that new device -- is the focus of this work. We investigate the rates and reasons for 4G upgrades and adoption in two extremely remote areas in Indonesia and the Philippines. Our mixed-methods approach combines the quantitative analysis of several years of mobile phone registration logs with the qualitative analysis of multiple interviews in one of these communities. We learn that users are rapidly switching from 2G to 4G technology and skipping 3G entirely; the data suggest that these villages will soon have sufficient 4G phone adoption to justify the investment required to upgrade base stations to 4G technology. The interviews suggest people are making these switches primarily to support consumption of media such as games, videos, and music. Similarly, users switch devices because of damage, often leading to downgrades to more resilient feature phones. We also find that, despite the general value seen in more modern 4G phones, 2G phones are more shared and more active on the network.
Using Ideas from Behavioural Ecology to Understand Plants Fishing for nutrients in heterogeneous landscapes : modelling plant growth trade-offs in monocultures and mixed communities

The problem of how best to find and exploit essential resources, the quality and locations of which are unknown, is common throughout biology. For plants, the need to grow an efficient root system so as to acquire patchily distributed soil nutrients is typically complicated by competition between plants, and by the costs of maintaining the root system. Simple mechanistic models for root growth can help elucidate these complications, and here we argue that these models can be usefully informed by models initially developed for foraging fish larvae. Both plant and fish need to efficiently search a spatio-temporally variable environment using simple algorithms involving only local information, and both must perform this task against a backdrop of intraand inter-specific competition and background mortality. Here we develop these parallels by using simple stochastic models describing the growth and efficiency of four contrasting idealized root growth strategies. We show that plants which grow identically in isolation in homogeneous substrates will typically perform very differently when grown in monocultures, in heterogeneous nutrient landscapes and in mixed-species competition. In particular, our simulations show a consistent result that plants which trade-off rapid growth in favour of a more efficient and durable root system perform better, both on average and in terms of the best performing individuals, than more rapidly growing ephemeral root systems. Moreover, when such slower growing but more efficient plants are grown in competition, the overall community productivity can exceed that of the constituent monocultures. These findings help to disentangle many of the context-dependent behaviours seen in the experimental literature, and may form a basis for future studies at the level of complex population dynamics and life history evolution.
Perceptual based speech enhancement for normal-hearing and hearing-impaired individuals

This paper describes a new noise suppression scheme with the goal of improving speech-in-noise perception for hearing-impaired listeners. Following the work of Tsoukalas et al. (1997) [4], Arehart et al (2003) [3] implemented and evaluated a noise suppression algorithm based on an approach that used the auditory masked threshold in conjunction with a version of spectral subtraction to adjust the enhancement parameters based on the masked threshold of the noise across the frequency spectrum. That original formulation was based on masking properties of the normal auditory system, with its theoretical underpinnings based on MPEG-4 audio coding [6]. We describe here a revised formulation, which is more suitable for hearing aid applications and which addresses changes in masking that occur with cochlear hearing loss. In contrast to previous formulations, the algorithm described here is implemented with generalized minimum mean square error estimators, which provide improvements over spectral subtraction estimators [1]. Second, the frequency resolution of the cochlea is described with auditory ﬁlter equivalent rectangular bandwidths (ERBs) [2] rather than the critical band scale. Third, estimation of the auditory masked thresholds and masking spreading functions are adjusted to address elevated thresholds and broader auditory ﬁlters characteristic of cochlear hearing loss. Fourth, the current algorithm does not include the tonality offset developed for use in MPEG-4 audio coding applications. The scheme also shows an overall improvement of 11% in the Itakura-Saito distortion measure.
Object classification based on visual and extended features for video surveillance application

Object classification in computer vision is the task of classifying a given object in an image or video sequence to one of a set of predefined object categories. There are two main factors which affect the performance of object classification. These are image representation and classification. We investigate object classification using visual features such as Scale Invariant Feature Transform (SIFT), Speeded Up Robust Feature (SURF). These features are highly distinctive for textured objects while they ignore color information. But color is also very much important cue for object recognition. Considering this assumption, we use also color histogram as local features. For image representation, we use Bag of words (BoW) model and Naïve Bayes for classification. We extract visual and color descriptor at each interest point from image and combine them aiming to use as feature. The experimental result shows that our approach achieves 5% higher classification rate than only using visual descriptor.
Linguistically Motivated Complementizer Choice in Surface Realization

This paper shows that using linguistically motivated features for English that-complementizer choice in an averaged perceptron model for classification can improve upon the prediction accuracy of a state-of-the-art realization ranking model. We report results on a binary classification task for predicting the presence/absence of a that-complementizer using features adapted from Jaeger's (2010) investigation of the uniform information density principle in the context of that-mentioning. Our experiments confirm the efficacy of the features based on Jaeger's work, including information density--based features. The experiments also show that the improvements in prediction accuracy apply to cases in which the presence of a that-complementizer arguably makes a substantial difference to fluency or intelligiblity. Our ultimate goal is to improve the performance of a ranking model for surface realization, and to this end we conclude with a discussion of how we plan to combine the local complementizer-choice features with those in the global ranking model.
Professional and Non-Professional Intervention for Highly Anxious Primiparous Mothers

Summary Primiparous women (n = 627) were screened on state and trait anxiety measures in the post-partum period; sub-groups of highly anxious (n = 89), moderately anxious (n = 29), and minimally anxious (n = 29) mothers were derived and subsequently interviewed. The high-anxiety mothers were randomly assigned to a professional intervention, to a non-professional intervention, and to a control group, and their progress was reviewed over the following 12 months. Compliance, both in responding to progressive assessments and in accepting therapeutic intervention, was extremely high. Changes in anxiety levels for mothers not receiving an intervention were minimal over the study. In the high-anxiety sub-groups, there was a 19% reduction in state anxiety levels for those receiving a professional intervention, a 12% reduction for those receiving a nonprofessional intervention, and a 3% reduction in the controls. A planned contrast analysis determined that only professional intervention had a significant effect, intervention successfully lowering state anxiety levels to a value comparable with the moderately anxious mothers.
Decomposition Method for Oligopolistic Competitive Models with Common Pollution Regulation

We consider the general problem of industrial production in a set of countries subject to a common environmental regulation that limits the emissions of specific sectors. Due to these restrictions, the problem is treated as a generalized non-cooperative game where players (countries) have joint (environmental) constraints caused by the necessity of a common and compulsory emission regulation. The problem is to find a natural mechanism for attaining the corresponding generalized equilibrium state. We suggest a share allocation method, which yields a suitable decomposition type procedure and replaces the initial problem with a sequence of non-cooperative games on Cartesian product sets. We also show that its implementation can be simplified essentially after application of a regularized penalty method. In the case study, we take inspiration from the European Union Emission Trading System (EU-ETS) and we introduce an environmental regulation that restricts the carbon emissions of energy, cement, and steel sectors in some European countries. Our results confirm the important role played by energy sector in reducing carbon emissions.
Opinion and Relationship Mining in Online Forums

The Internet contains an increasing number of online forums where consumers exchange product opinions. It is important for companies to know how consumers judge their products and how these opinions are spread by interactions throughout online forums. With this knowledge it is possible to recognize risks and chances. However, classical opinion research is very time consuming and only possible to a certain extent. This paper introduces a system which automatically extracts opinions and communication relationships in forums by text mining and identifies influential users and trends by social network analysis.
Guest Editors’ Introduction: Smart Interaction with Consumers: From Co-Creation to Smart Partnership

This issue of the International Journal of Electronic Commerce shows how the traditional processes of value co-creation in commerce are shifting in the new, technology-enriched, retail environments toward smart partnerships between retailers and consumers. The articles included in the issue examine a wide range of subjects related to the emergence of these smart partnerships. In the past decade, marketing has shifted from a traditional productdominant view, considering the product as the basis of each strategy, to a service-dominant logic, based on the centrality of intangibility in terms of exchanges, relationships, and interactions [6, 11, 15]. Similarly, current marketing practices associated with progress in information and communication technologies have evolved, prompted by smarter information technology (IT) service innovations [3], by including new forms of interactions with consumers based on the extensive usage of social media, smartphones, mobile apps, ubiquitous systems, and so forth [10]. Smart technologies are able to enhance contact points between consumers and firms through emotional engagement, ease of use, user-friendly, highly realistic, and interactive interfaces, and entertaining scenarios, by creating new augmented reality-based scenarios where offline and online channels can be integrated to create value for consumers [1, 2, 4, 8, 9, 12, 13, 14]. Hence, they reinforce interactions between clients and firms through a huge emotional engagement and a collaborative scenario where consumers are able to actively participate in the creation of the final service (service co-creation) through a sort of “smart interaction” with technology, which replies with highly customized information and smart shopping environments [7, 11, 16]. As a consequence, consumers are involved in sort of smart partnerships with service providers with a common goal to achieve the most satisfying service. Therefore, the concept of “smartness” goes beyond pure applications of smart technologies, by requiring the definition of new forms of value co-creation and interactions with consumers, providing superior experiences and differentiating the final service and product. While this topic has been largely exploited by the game industry [5], e-commerce, with emphasis in e-retailing still lacks empirical studies on the creation of smart partnerships with end users/consumers. This is the main motivation for this issue of the journal, which aims at providing a deep understanding of the emerging concepts of smart interaction with consumers, where the co-creation process shifts to a smart partnership perspective in the current technology-mediated retail environments. The studies included in this issue were selected and revised, resulting in a strong collection outlining the recent advancements on the topic, implications for practitioners, and an agenda for future research. The issue opens with a study by Thomas Leclercq, Ingrid Poncin, and Wafa Hammedi, who investigate the role that gamification mechanics plays