Miracle-dz/UniFAR-FTUs huggingface dataset:
The Role of Aquaporin and Tight Junction Proteins in the Regulation of Water Movement in Larval Zebrafish (Danio rerio)

Teleost fish living in freshwater are challenged by passive water influx; however the molecular mechanisms regulating water influx in fish are not well understood. The potential involvement of aquaporins (AQP) and epithelial tight junction proteins in the regulation of transcellular and paracellular water movement was investigated in larval zebrafish (Danio rerio). We observed that the half-time for saturation of water influx (K u) was 4.3±0.9 min, and reached equilibrium at approximately 30 min. These findings suggest a high turnover rate of water between the fish and the environment. Water influx was reduced by the putative AQP inhibitor phloretin (100 or 500 μM). Immunohistochemistry and confocal microscopy revealed that AQP1a1 protein was expressed in cells on the yolk sac epithelium. A substantial number of these AQP1a1-positive cells were identified as ionocytes, either H+-ATPase-rich cells or Na+/K+-ATPase-rich cells. AQP1a1 appeared to be expressed predominantly on the basolateral membranes of ionocytes, suggesting its potential involvement in regulating ionocyte volume and/or water flux into the circulation. Additionally, translational gene knockdown of AQP1a1 protein reduced water influx by approximately 30%, further indicating a role for AQP1a1 in facilitating transcellular water uptake. On the other hand, incubation with the Ca2+-chelator EDTA or knockdown of the epithelial tight junction protein claudin-b significantly increased water influx. These findings indicate that the epithelial tight junctions normally act to restrict paracellular water influx. Together, the results of the present study provide direct in vivo evidence that water movement can occur through transcellular routes (via AQP); the paracellular routes may become significant when the paracellular permeability is increased.
Review article: renal function assessment in cirrhosis – difficulties and alternative measurements

Background Renal function in patients with cirrhosis is important prognostically, both before and following liver transplantation. Its prognostic impact is reflected by the inclusion of serum creatinine in the model for end‐stage liver disease score, which is now used for recipient prioritization on liver transplantation waiting lists in the USA.
Adaptive boosting techniques in heterogeneous and spatial databases

Combining multiple classifiers is an effective technique for improving classification accuracy by reducing the variance through manipulating the training data distributions. In many large-scale data analysis problems involving heterogeneous databases with attribute instability, however, standard boosting methods do not improve local classifiers (e.g. k-nearest neighbors) due to their low sensitivity to data perturbation. Here, we propose an adaptive attribute boosting technique to coalesce multiple local classifiers each using different relevant attribute information. To reduce the computational costs of k-nearest neighbor (k-NN) classifiers, a novel fast k-NN algorithm is designed. We show that the proposed combining technique is also beneficial when boosting global classifiers like neural networks and decision trees. In addition, a modification of the boosting method is developed for heterogeneous spatial databases with unstable driving attributes by drawing spatial blocks of data at each boosting round. Finally, when heterogeneous data sets contain several homogeneous data distributions, we propose a new technique of boosting specialized classifiers, where instead of a single global classifier for each boosting round, there are specialized classifiers responsible for each homogeneous region. The number of regions is identified through a clustering algorithm performed at each boosting iteration. New boosting methods applied to synthetic spatial data and real life spatial data show improvements in prediction accuracy for both local and global classifiers when unstable driving attributes and heterogeneity are present in the data. In addition, boosting specialized experts significantly reduces the number of iterations needed for achieving the maximal prediction accuracy.
Burn-in temperature projections for deep sub-micron technologies

Burn-in faces significant challenges in recent CMOS technologies. The self-generated heat of each IC in a burn-in environment contributes to larger currents that can lead to further increase in junction temperatures, possible thermal run away, and yield-loss of good parts. Calculations show that the junction temperature is increasing by 1.45X/generation. This paper estimates the increase in junction temperature with scaling and discusses the optimal burn-in temperature with scaling. Our research indicates that the burn-in temperature must also be reduced with technology scaling. The impact on commercial burn-in ovens is also described.
Scalable multipartite subgraph enumeration for integrative analysis of heterogeneous experimental functional genomics data

Functional genomics, the effort to understand the role of genomic elements in biological processes, has led to an avalanche of diverse experimental and semantic information defining associations between genes and various biological concepts across species and experimental paradigms. Integrating this rapidly expanding wealth of heterogeneous data, and finding consensus among so many diverse sources for specific research questions, require highly sophisticated big data structures and algorithms for harmonization and scalable analysis. In this context, multipartite graphs can often serve as useful structures for representing questions about the role of genes in multiple, frequently-occurring disease processes. The main focus of this paper is on finding and analyzing efficient algorithms for dense subgraph enumeration in such graphs. An O(3n/3)-time procedure was devised to enumerate all maximal k-partite cliques in a k-partite graph, where k ≥ 3. The maximum number of such cliques is also shown to obey this bound, and thus this procedure obtains the best possible asymptotic performance. Empirical testing on both real and synthetic data is conducted. Concrete applications to biological data are described, as are scalability issues in the context of big data analysis.
Potential merger of ancient lineages in a passerine bird discovered based on evidence from host-specific ectoparasites

The merger of formerly isolated lineages is hypothesized to occur in vertebrates under certain conditions. However, despite many demonstrated instances of introgression between taxa in secondary contact, examples of lineage mergers are rare. Preliminary mtDNA sequencing of a Malagasy passerine, Xanthomixis zosterops (Passeriformes: Bernieridae), indicated a possible instance of merging lineages. We tested the hypothesis that X. zosterops lineages are merging by comparing mtDNA sequence and microsatellite data, as well as mtDNA sequence data from host-specific feather lice in the genus Myrsidea (Phthiraptera: Menoponidae). Xanthomixis zosterops comprises four deeply divergent, broadly sympatric, cryptic mtDNA clades that likely began diverging approximately 3.6 million years ago. Despite this level of divergence, the microsatellite data indicate that the X. zosterops mtDNA clades are virtually panmictic. Three major phylogroups of Myrsidea were found, supporting previous allopatry of the X. zosterops clades. In combination, the datasets from X. zosterops and its Myrsidea document a potential merger of previously allopatric lineages that likely date to the Pliocene. This represents the first report of sympatric apparent hybridization among more than two terrestrial vertebrate lineages. Further, the mtDNA phylogeographic pattern of X. zosterops, namely the syntopy of more than two deeply divergent cryptic clades, appears to be a novel scenario among vertebrates. We highlight the value of gathering multiple types of data in phylogeographic studies to contribute to the study of vertebrate speciation.
The Power of Pedagogy

The concept of ‘pedagogy' has become increasingly important as a frame of reference for debate about teaching and learning. In this book the authors analyze and explore contemporary ideas of pedagogy through the work of key figures including Freire, Montessori, and Vygotsky, and explain how a new conception of pedagogy could transform educational institutions, particularly schools. In locating pedagogy as central to the process of education the authors: explore the historical and cultural antecedents of our understanding of pedagogy; analyse the way understanding of the working of the human mind influences teaching and learning; review and critique ideas about learning and the construction of knowledge; examine the way new forms of communication are impacting on the processes and purposes of pedagogic activity. Highly relevant for masters and doctoral students of education, this book will also be of interest to educational practitioners undertaking research on issues related to pedagogy, both in the UK and internationally.
Singular integrals on self-similar sets and removability for Lipschitz harmonic functions in Heisenberg groups

In this paper we study singular integrals on small (that is, measure zero and lower than full dimensional) subsets of metric groups. The main examples of the groups we have in mind are Euclidean spaces and Heisenberg groups. In addition to obtaining results in a very general setting, the purpose of this work is twofold; we shall extend some results in Euclidean spaces to more general kernels than previously considered, and we shall obtain in Heisenberg groups some applications to harmonic (in the Heisenberg sense) functions of some results known earlier in Euclidean spaces.
Exploiting Parse Structures for Native Language Identification

Attempts to profile authors according to their characteristics extracted from textual data, including native language, have drawn attention in recent years, via various machine learning approaches utilising mostly lexical features. Drawing on the idea of contrastive analysis, which postulates that syntactic errors in a text are to some extent influenced by the native language of an author, this paper explores the usefulness of syntactic features for native language identification. We take two types of parse substructure as features---horizontal slices of trees, and the more general feature schemas from discriminative parse reranking---and show that using this kind of syntactic feature results in an accuracy score in classification of seven native languages of around 80%, an error reduction of more than 30%.
Journal of Graph Algorithms and Applications Drawing Planar Graphs with Large Vertices and Thick Edges

We consider the problem of representing size information in the edges and vertices of a planar graph. Such information can be used, for example, to depict a network of computers and information traveling through the network. We present an efficient linear-time algorithm which draws edges and vertices of varying 2-dimensional areas to represent the amount of information flowing through them. The algorithm avoids all occlusions of nodes and edges, while still drawing the graph on a compact integer grid.
A novel hybrid method for determining the depth of anesthesia level: Combining ReliefF feature selection and random forest algorithm (ReliefF+RF)

Depth of anesthesia is a matter of great importance in surgery. Determination of depth of anesthesia is a time consuming and difficult task carried out by experts. This study aims to decide a method that can classify EEG data automatically with a high accuracy and, so will help the experts for determination process. This study consists of three stages: feature extraction of EEG signals, feature selection, and classification. In the feature extraction stage, 41 feature parameters are obtained. Feature selection stage is important to eliminate redundant attributes and improve prediction accuracy and performance in terms of computational time. Effective feature selection algorithms such as minimum redundancy maximum relevance (mRMR); ReliefF; and Sequential Forward Selection (SFS) are preferred at the feature selection stage to select a set of features which best represent EEG signals. These obtained features are used as input parameters of the classification algorithms. At the classification stage, six different classification algorithms such as random forest (RF); feed-forward neural network (FFNN); C4.5 decision tree algorithm (C4.5); support vector machines (SVM); naive bayes; and radial basis function neural network (RBF) are preferred to classify the problem. A comparison is provided between computation times and accuracy rates of these different classification algorithms. The experimental results show that better results according to other classifiers when the obtained attributes by ReliefF algorithm are used with RF classifier.
Bereavement and Support : Healing in a Group Environment

A Theoretical Overview The Why and Wherefore of Bereavement Support Groups What is a Bereavement Support Group? Why Have a Bereavement Support Group? Getting Them to Come Self-Generated Publicity Outreach Setting up a Bereavement Support Group The Facilitator Organisational Skills Screening the Participants Goals Guidelines Structured Bereavement Support Groups Unstructured Bereavement Support Groups Groups for Special Populations Suicide Survivors Survivors of Homicide Victims Death by Drunken Driver Death of a Child Community Disaster Children Grief Groups Group Participants Reference List.
Regulation of platelet-activating factor-mediated protein tyrosine phosphatase 1B activation by a Janus kinase 2/calpain pathway

Atherosclerosis is a pro-inflammatory condition underlying many cardiovascular diseases. Platelet-activating factor (PAF) and interleukin 6 (IL-6) are actively involved in the onset and progression of atherosclerotic plaques. The involvement of monocyte-derived macrophages is well characterized in the installation of inflammatory conditions in the plaque, but less is known about the contribution of monocyte-derived dendritic cells (Mo-DCs). In the same way, the involvement of calcium, phospholipase C and A2 in PAF-induced IL-6 production, in different cells types, has been shown; however, the importance of the Jak/STAT pathway and its regulation by protein-tyrosine phosphatases in this response have not been addressed. In this study, we report that PAF stimulates PTP1B activity via Jak2, thereby modulating PAF-induced IL-6 production. Using HEK 293 cells stably transfected with the PAF receptor in order to discriminate the pathway components, our results suggest that Jak2 modulates PAF-induced IL-6 production via both positive and negative pathways. Jak2 kinase activity was necessary for maximal transactivation of the IL-6 promoter, as seen by luciferase assays, whereas the same kinase also downregulated this promoter transactivation through the activation of a calcium/calpain/PTP1B pathway. The same pathways were operational in monocyte-derived dendritic cells, since PAF-induced PTP1B activation negatively regulated PAF-induced IL-6 mRNA production and, in addition, Jak2 activated calpain, one of the components involved in PAF-induced PTP1B activation. Results obtained in this study indicate that Jak2 activation is important for maximal IL-6 promoter transactivation by PAF and that PTP1B is involved in the negative regulation of this transactivation. However, PTP1B does not directly regulate Jak2 activation, but rather Jak2 regulates PAF-induced PTP1B activation.
Hospitalization for Infection and Risk of Acute Ischemic Stroke: The Cardiovascular Health Study

Background and Purpose— Little is known about the acute precipitants of ischemic stroke, although evidence suggests infections contribute to risk. We hypothesized that acute hospitalization for infection is associated with the short-term risk of stroke. Methods— The case-crossover design was used to compare hospitalization for infection during case periods (90, 30, or 14 days before an incident ischemic stroke) and control periods (equivalent time periods exactly 1 or 2 years before stroke) in the Cardiovascular Health Study, a population-based cohort of 5888 elderly participants from 4 US sites. Odds ratios (ORs) and 95% confidence intervals (95% CIs) were calculated by conditional logistic regression. Confirmatory analyses assessed hazard ratios of stroke from Cox regression models, with hospitalization for infection as a time-varying exposure. Results— During a median follow-up of 12.2 years, 669 incident ischemic strokes were observed in participants without a baseline history of stroke. Hospitalization for infection was more likely during case than control time periods; for 90 days before stroke, OR=3.4 (95% CI, 1.8 to 6.5). The point estimates of risks were higher when we examined shorter intervals: for 30 days, OR=7.3 (95% CI, 1.9 to 40.9), and for 14 days, OR=8.0 (95% CI, 1.7 to 77.3). In survival analyses, risk of stroke was associated with hospitalization for infection in the preceding 90 days, adjusted hazard ratio=2.4 (95% CI, 1.6 to 3.4). Conclusions— Hospitalization for infection is associated with a short-term increased risk of stroke, with higher risks observed for shorter intervals preceding stroke.
ECT Remission Rates in Psychotic Versus Nonpsychotic Depressed Patients: A Report from CORE

Objective To compare the relative efficacy of electroconvulsive therapy (ECT) in psychotic and nonpsychotic patients with unipolar major depression. Methods The outcome of an acute ECT course in 253 patients with nonpsychotic (n = 176) and psychotic (n = 77) unipolar major depression was assessed in the first phase of an ongoing National Institute of Mental Health-supported four-hospital collaborative study of continuation treatments after successful ECT courses. ECT was administered with bilateral electrode placement at 50% above the titrated seizure threshold. The remission criteria were rigorous: a score ≤10 on the 24-item Hamilton Rating Scale for Depression (HRSD) after 2 consecutive treatments, and a decrease of at least 60% from baseline. Results The overall remission rate was 87% for study completers. Among these, patients with psychotic depression had a remission rate of 95% and those with nonpsychotic depression, 83%. Improvement in symptomatology, measured by the HRSD, was more robust and appeared sooner in the psychotic patients compared with the nonpsychotic patients. Conclusion Bilateral ECT is effective in relieving severe major depression. Remission rates are higher and occur earlier in psychotic depressed patients than in nonpsychotic depressed patients. These data support the argument that psychotic depression is a distinguishable nosological entity that warrants separate treatment algorithms.
Oncogenic transformation alters cisplatin‐induced apoptosis in rat embryo fibroblasts

We have investigated whether cellular transformation by different oncogenes alters their responsiveness to the chemotherapeutic agent cis‐diamminedichloroplatinum(lI) (cDDP). Rat‐6 (R6) embryo fibroblasts transformed by v‐myc, rc‐mos (rearranged mouse c‐mos), v‐src and activated c‐H‐ras oncogenes displayed differential sensitivities to cDDP, and the lC50 values of cDDP decreased by approximately 3.0‐, 1.2‐, 2.0‐ and 1.5‐fold, respectively. Over‐expression of rnyc, but not ras, srcor mos, induced apoptosis in R6 cells. Nevertheless, all oncogenes influenced cellular susceptibility to apoptosis triggered by cDDP as judged by the appearance of condensed chromatin, formation of apoptotic bodies and internucleosomal cleavage of genomic DNA to 180 bp multimers, yielding a “laddered” ectrophoretic profile on agarose gel. There was a correlation between the time‐ and concentration‐dependent enhancement of cDDP‐induced DNAfragmentation and potentiation of cDDP sensitivity by various oncogenes. Oncogenic transformation led to a decrease in expression of the PKCr isoform, and stable transfection of PKCr in R6 cells prevented cDDP‐induced apoptosis and protected cells against cDDP cytotoxicity. Our results indicate that the differential sensitivity of oncogenetransformed cells to cDDP may be associated with the ability of various oncogenes to influence cDDP‐induced apoptosis.
Prosodic boundary strength and the location of pre-nuclear phrasal prominence

The assignment of pre-nuclear phrasal prominence in sequences like THIRteen MEN (vs. thirTEEN) is not fully understood. We propose that the location of pre-nuclear prominence in thirteen is sensitive to the strength of the prosodic boundary separating the clashing words thirteen and men: a weaker prosodic boundary should invite early prominence on THIRteen. Eleven speakers read 14 potentially clashing word pairs in syntactic contexts likely to elicit a stronger boundary (NP+ VP: How does the canteen cook these days? ) or a weaker boundary (Pre-modifier+NOUN: Who is the canteen cook these days? ). Syntactic condition had significant effects in the predicted direction on the strength of the critical prosodic boundary. Results suggest that boundary strength modifies the relative prominence of the two syllables in the first word (e.g. canteen), but analyses of F0 and duration suggest that the effect is primarily, or perhaps even exclusively, localised on the 2 syllable, e.g. -teen.
Accuracy and Precision of Head Motion Information in Multi-Channel Free Induction Decay Navigators for Magnetic Resonance Imaging

Free induction decay (FID) navigators were found to qualitatively detect rigid-body head movements, yet it is unknown to what extent they can provide quantitative motion estimates. Here, we acquired FID navigators at different sampling rates and simultaneously measured head movements using a highly accurate optical motion tracking system. This strategy allowed us to estimate the accuracy and precision of FID navigators for quantification of rigid-body head movements. Five subjects were scanned with a 32-channel head coil array on a clinical 3T MR scanner during several resting and guided head movement periods. For each subject we trained a linear regression model based on FID navigator and optical motion tracking signals. FID-based motion model accuracy and precision was evaluated using cross-validation. FID-based prediction of rigid-body head motion was found to be with a mean translational and rotational error of 0.14±0.21 mm and 0.08±0.13°, respectively. Robust model training with sub-millimeter and sub-degree accuracy could be achieved using 100 data points with motion magnitudes of ±2 mm and ±1° for translation and rotation. The obtained linear models appeared to be subject-specific as inter-subject application of a “universal” FID-based motion model resulted in poor prediction accuracy. The results show that substantial rigid-body motion information is encoded in FID navigator signal time courses. Although, the applied method currently requires the simultaneous acquisition of FID signals and optical tracking data, the findings suggest that multi-channel FID navigators have a potential to complement existing tracking technologies for accurate rigid-body motion detection and correction in MRI.