Miracle-dz/UniFAR-FTUs huggingface dataset:
The Identification of Protein Kinase C Iota as a Regulator of the Mammalian Heat Shock Response Using Functional Genomic Screens

Background The heat shock response is widely used as a surrogate of the general protein quality control system within the cell. This system plays a significant role in aging and many protein folding diseases as well as the responses to other physical and chemical stressors. Methods/Principal Findings In this study, a broad-based functional genomics approach was taken to identify potential regulators of the mammalian heat shock response. In the primary screen, a total of 13724 full-length genes in mammalian expression vectors were individually co-transfected into human embryonic kidney cells together with a human HSP70B promoter driving firefly luciferase. A subset of the full-length genes that showed significant activation in the primary screen were then evaluated for their ability to hyper-activate the HSP70B under heat shock conditions. Based on the results from the secondary assay and gene expression microarray analyses, eight genes were chosen for validation using siRNA knockdown. Of the eight genes, only PRKCI showed a statistically significant reduction in the heat shock response in two independent siRNA duplexes compared to scrambled controls. Knockdown of the PRKCI mRNA was confirmed using quantitative RT-PCR. Additional studies did not show a direct physical interaction between PRKCI and HSF1. Conclusions/Significance The results suggest that PRKCI is an indirect co-regulator of HSF1 activity and the heat shock response. Given the underlying role of HSF1 in many human diseases and the response to environmental stressors, PRKCI represents a potentially new candidate for gene-environment interactions and therapeutic intervention.
5-Lipoxygenase Activating Protein (FLAP) Dependent Leukotriene Biosynthesis Inhibition (MK591) Attenuates Lipid A Endotoxin-Induced Inflammation

The Lipid A moiety of endotoxin potently activates TLR-4 dependent host innate immune responses. We demonstrate that Lipid-A mediated leukotriene biosynthesis regulates pathogen-associated molecular patterns (PAMP)-dependent macrophage activation. Stimulation of murine macrophages (RAW264.7) with E. coli 0111:B4 endotoxin (LPS) or Kdo2-lipid A (Lipid A) induced inflammation and Lipid A was sufficient to induce TLR-4 mediated macrophage inflammation and rapid ERK activation. The contribution of leukotriene biosynthesis was evaluated with a 5-lipoxygenase activating protein (FLAP) inhibitor, MK591. MK591 pre-treatment not only enhanced but also sustained ERK activation for up to 4 hours after LPS and Lipid A stimulation while inhibiting cell proliferation and enhancing cellular apoptosis. Leukotriene biosynthesis inhibition attenuated inflammation induced by either whole LPS or the Lipid A fraction. These responses were regulated by inhibition of the key biosynthesis enzymes for the proinflammatory eicosanoids, 5-lipoxygenase (5-LO), and cyclooxygenase-2 (COX-2) quantified by immunoblotting. Inhibition of leukotriene biosynthesis differentially regulated TLR-2 and TLR-4 cell surface expression assessed by flow cytometry, suggesting a close mechanistic association between TLR expression and 5-LO associated eicosanoid activity in activated macrophages. Furthermore, MK591 pre-treatment enhanced ERK activation and inhibited cell proliferation after LPS or Lipid A stimulation. These effects were regulated in part by increased apoptosis and modulation of cell surface TLR expression. Together, these data clarify the mechanistic association between 5-lipoxygenase activating protein-mediated leukotriene biosynthesis and 5-LO dependent eicosanoid metabolites in mediating the TLR-dependent inflammatory response after endotoxin exposure typical of bacterial sepsis.
Leveraging electronic healthcare record standards and semantic web technologies for the identification of patient cohorts.

BACKGROUND The secondary use of electronic healthcare records (EHRs) often requires the identification of patient cohorts. In this context, an important problem is the heterogeneity of clinical data sources, which can be overcome with the combined use of standardized information models, virtual health records, and semantic technologies, since each of them contributes to solving aspects related to the semantic interoperability of EHR data. OBJECTIVE To develop methods allowing for a direct use of EHR data for the identification of patient cohorts leveraging current EHR standards and semantic web technologies. MATERIALS AND METHODS We propose to take advantage of the best features of working with EHR standards and ontologies. Our proposal is based on our previous results and experience working with both technological infrastructures. Our main principle is to perform each activity at the abstraction level with the most appropriate technology available. This means that part of the processing will be performed using archetypes (ie, data level) and the rest using ontologies (ie, knowledge level). Our approach will start working with EHR data in proprietary format, which will be first normalized and elaborated using EHR standards and then transformed into a semantic representation, which will be exploited by automated reasoning. RESULTS We have applied our approach to protocols for colorectal cancer screening. The results comprise the archetypes, ontologies, and datasets developed for the standardization and semantic analysis of EHR data. Anonymized real data have been used and the patients have been successfully classified by the risk of developing colorectal cancer. CONCLUSIONS This work provides new insights in how archetypes and ontologies can be effectively combined for EHR-driven phenotyping. The methodological approach can be applied to other problems provided that suitable archetypes, ontologies, and classification rules can be designed.
Rotational Invariant Estimator for General Noisy Matrices

We investigate the problem of estimating a given real symmetric signal matrix C from a noisy observation matrix M in the limit of large dimension. We consider the case where the noisy measurement M comes either from an arbitrary additive or multiplicative rotational invariant perturbation. We establish, using the replica method, the asymptotic global law estimate for three general classes of noisy matrices, significantly extending previously obtained results. We give exact results concerning the asymptotic deviations (called overlaps) of the perturbed eigenvectors away from the true ones, and we explain how to use these overlaps to “clean” the noisy eigenvalues of M. We provide some numerical checks for the different estimators proposed in this paper and we also make the connection with some well-known results of Bayesian statistics.
Faunistic patterns of leaf beetles (Coleoptera, Chrysomelidae) within elevational and temporal gradients in Sierra de San Carlos, Mexico

Abstract The study of biodiversity of Chrysomelidae in Mexico and its variation within ecological gradients has increased recently, although important areas in the country remain to be explored. We conducted a faunistic inventory and analyzed the elevational and temporal variation of leaf beetle communities in the Sierra de San Carlos, in the state of Tamaulipas, in northeastern Mexico. This is an area with high to extreme priority for conservation, and due to its insular geographical position and to the vegetational communities present, it must be considered as a sky island. We selected seven sample sites distributed in different elevations within three localities, and comprising different vegetational communities. At each site, we randomly delimited 12 sample plots of 400 m2 where sampling was conducted by entomological sweep netting and collecting directly by hand. Sampling was conducted monthly at each plot, for a total of 1,008 samples between February 2013 and January 2014. By the end of the study, we had obtained a total of 3,081 specimens belonging to six subfamilies, 65 genera, and 113 species, with Trichaltica scabricula (Crotch, 1873) being recorded for first time in Mexico. Species richness was less than the values observed at other studies conducted in the same region, which is attributed to differences in the number of plant species and to the insular location of Sierra de San Carlos; however, the higher diversity values suggest a higher quality of natural resources and vegetational communities. No consistent pattern of leaf beetle communities was correlated with elevation, although higher values of species richness and diversity were obtained at the highest elevation site. The seasonal gradient showed that the rainy season is most favorable for leaf beetle communities. We found that species composition was different between sites and months, and also that there exists a significant association between the abundance obtained at each site and particular months. These results highlight the importance of different microhabitats for species distribution, and suggest that each species of Chrysomelidae has a differential response to environmental factors that vary within the elevational gradient and according to seasons. Also, we confirm and emphasize the important status of Sierra de San Carlos as a key natural area for biological conservation.
Generating Visual Summaries of Geographic Areas Using Community-Contributed Images

In this paper, we present a novel approach for automatic visual summarization of a geographic area that exploits user-contributed images and related explicit and implicit metadata collected from popular content-sharing websites. By means of this approach, we search for a limited number of representative but diverse images to represent the area within a certain radius around a specific location. Our approach is based on the random walk with restarts over a graph that models relations between images, visual features extracted from them, associated text, as well as the information on the uploader and commentators. In addition to introducing a novel edge weighting mechanism, we propose in this paper a simple but effective scheme for selecting the most representative and diverse set of images based on the information derived from the graph. We also present a novel evaluation protocol, which does not require input of human annotators, but only exploits the geographical coordinates accompanying the images in order to reflect conditions on image sets that must necessarily be fulfilled in order for users to find them representative and diverse. Experiments performed on a collection of Flickr images, captured around 207 locations in Paris, demonstrate the effectiveness of our approach.
A Framework to Evaluate the Performance and Satisfaction of Virtual Teams in On-line Learning Environment

This paper describes the development of a framework which can be used to evaluate the performance and satisfaction of virtual teams in an online education environment. A comprehensive literature review of existing virtual team research is used to develop a framework and this is then substantiated against existing theories in relation to Computer Mediated Communication (CMC). The framework is distinct and feasible; provides social and task dimension; and provides the relationships between variables. In addition, each variable is discussed and the clues of methodology design are presented.
Lighting for improving balance in older adults with and without risk for falls.

SIR—The visual system acquires sensory information about self-position and location of objects in the environment and, together with sensory input from the vestibular and somatosensory systems, helps maintain balance. The dependence on visual information for the maintenance of postural stability and control increases with age due to age-related changes that occur in the vestibular and somatosensory systems [1–10]. Lighting that enhances veridical visual information about the environment for older adults could be a practical and effective intervention to reduce falls risk. Figueiro et al. [11] showed that, in healthy, non-faller older adults, a wall-plug nightlight (NL) was associated with significantly greater sway in the early phase of the sit-to-stand (STS) test than was found with a novel NL system providing low-level ambient illumination and enhanced horizontal and vertical (H/V) visual information. The present study aimed to extend these findings by testing the effectiveness of a similar NL system on another measure, the weight transfer time (WTT), in two groups of older adults, those with and without fall risks. A longer WTT should be associated with more difficulty in getting up [12–14]. It was hypothesised that compared with wall-plug NLs, WTT in the STS test would be better with the novel NL system for both groups, and that the effect would be larger for fallers than for non-fallers. It was also hypothesised that a high contrast (black on white versus white on white) veridical stimulus would be better for postural stability and control than a low contrast stimulus.
Drosophila Fatty Acid Taste Signals through the PLC Pathway in Sugar-Sensing Neurons

Taste is the primary sensory system for detecting food quality and palatability. Drosophila detects five distinct taste modalities that include sweet, bitter, salt, water, and the taste of carbonation. Of these, sweet-sensing neurons appear to have utility for the detection of nutritionally rich food while bitter-sensing neurons signal toxicity and confer repulsion. Growing evidence in mammals suggests that taste for fatty acids (FAs) signals the presence of dietary lipids and promotes feeding. While flies appear to be attracted to fatty acids, the neural basis for fatty acid detection and attraction are unclear. Here, we demonstrate that a range of FAs are detected by the fly gustatory system and elicit a robust feeding response. Flies lacking olfactory organs respond robustly to FAs, confirming that FA attraction is mediated through the gustatory system. Furthermore, flies detect FAs independent of pH, suggesting the molecular basis for FA taste is not due to acidity. We show that low and medium concentrations of FAs serve as an appetitive signal and they are detected exclusively through the same subset of neurons that sense appetitive sweet substances, including most sugars. In mammals, taste perception of sweet and bitter substances is dependent on phospholipase C (PLC) signaling in specialized taste buds. We find that flies mutant for norpA, a Drosophila ortholog of PLC, fail to respond to FAs. Intriguingly, norpA mutants respond normally to other tastants, including sucrose and yeast. The defect of norpA mutants can be rescued by selectively restoring norpA expression in sweet-sensing neurons, corroborating that FAs signal through sweet-sensing neurons, and suggesting PLC signaling in the gustatory system is specifically involved in FA taste. Taken together, these findings reveal that PLC function in Drosophila sweet-sensing neurons is a conserved molecular signaling pathway that confers attraction to fatty acids.
Image sentiment analysis using deep convolutional neural networks with domain specific fine tuning

Images are the easiest medium through which people can express their emotions on social networking sites. Social media users are increasingly using images and videos to express their opinions and share their experiences. Sentiment analysis of such large scale visual content can help better extract user sentiments toward events or topics, such as those in image tweets, so that prediction of sentiment from visual content is complementary to textual sentiment analysis. Significant progress has been made with this technology, however, there is little research focus on the picture sentiments. In this work, an image sentiment prediction framework is built with Convolutional Neural Networks (CNN). Specifically, this framework is pretrained on a large scale data for object recognition to further perform transfer learning. Extensive experiments were conducted on manually labeled Flickr image dataset. To make use of such labeled data, we employ a progressive strategy of domain specific fine tuning of the deep network. The results show that the proposed CNN training can achieve better performance in image sentiment analysis than competing networks.
Upper secondary and first-year university students’ explanations of animal behaviour: to what extent are Tinbergen’s four questions about causation, ontogeny, function and evolution, represented?

ABSTRACT In 1963, the Nobel Prize-winning ethologist Niko Tinbergen proposed a framework for the scientific study of animal behaviour by outlining four questions that should be answered to have a complete understanding: causation, ontogeny, function and evolution. At present, Tinbergen’s framework is still considered the best way to guide animal behavioural research. Given the importance in science instruction of demonstrating how scientists work and ask questions, we investigated to what extent Tinbergen’s questions are addressed in biology textbooks in secondary education in Flanders, Belgium, and represented in upper-secondary and first-year university students’ explanations of behaviour in general and of specific animal behaviours. Our results revealed that teaching of animal behaviour mainly addresses ontogeny and causation, and that Tinbergen’s framework is not explicitly referred to. Students typically addressed only one or two questions, with the majority addressing causation or both causation and ontogeny when explaining behaviour in general, but function or causation and function when explaining specific animal behaviours. This high prevalence of function may be due to teleological thinking. Evolution was completely neglected, even in university students who had recently completed an evolution course. Our results revealed that transfer of the concepts of ontogeny and evolution was (almost) absent. We argue why Tinbergen’s framework should be an integral part of any biology curriculum.
Lighting estimation from a single image containing multiple planes

In this paper, we present a novel lighting estimation algorithm for the scene containing two or more planes. This paper focuses on near point light source estimation. We first detect planar markers to estimate the poses of the 3D planes in the scene. Then we estimate the shading image from the captured image. A near point light source lighting model is used to define an objective function for light source estimation in this paper. The output of the proposed method is the lighting parameters estimated from minimizing the objective function. In the experiments, we test the proposed algorithm on synthetic data and real dataset. Our experimental results show the proposed algorithm outperforms the state-of-the-art lighting estimation method. Moreover, we develop an augmented reality system that includes lighting estimation by using the proposed algorithm.
Effect of Short- and Long-Range Interactions on Trp Rotamer Populations Determined by Site-Directed Tryptophan Fluorescence of Tear Lipocalin

In the lipocalin family, the conserved interaction between the main α-helix and the β-strand H is an ideal model to study protein side chain dynamics. Site-directed tryptophan fluorescence (SDTF) has successfully elucidated tryptophan rotamers at positions along the main alpha helical segment of tear lipocalin (TL). The rotamers assigned by fluorescent lifetimes of Trp residues corroborate the restriction expected based on secondary structure. Steric conflict constrains Trp residues to two (t, g −) of three possible χ1 (t, g −, g +) canonical rotamers. In this study, investigation focused on the interplay between rotamers for a single amino acid position, Trp 130 on the α-helix and amino acids Val 113 and Leu 115 on the H strand, i.e. long range interactions. Trp130 was substituted for Phe by point mutation (F130W). Mutations at positions 113 and 115 with combinations of Gly, Ala, Phe residues alter the rotamer distribution of Trp130. Mutations, which do not distort local structure, retain two rotamers (two lifetimes) populated in varying proportions. Replacement of either long range partner with a small amino acid, V113A or L115A, eliminates the dominance of the t rotamer. However, a mutation that distorts local structure around Trp130 adds a third fluorescence lifetime component. The results indicate that the energetics of long-range interactions with Trp 130 further tune rotamer populations. Diminished interactions, evident in W130G113A115, result in about a 22% increase of α-helix content. The data support a hierarchic model of protein folding. Initially the secondary structure is formed by short-range interactions. TL has non-native α-helix intermediates at this stage. Then, the long-range interactions produce the native fold, in which TL shows α-helix to β-sheet transitions. The SDTF method is a valuable tool to assess long-range interaction energies through rotamer distribution as well as the characterization of low-populated rotameric states of functionally important excited protein states.
Trade Reforms and Income Inequality in Colombia

* We wish to thank Hector Mejia at DANE and Andreas Blom at the World Bank for providing us with the data. We are also grateful to Cristina Gamboa, Adriana Kugler, Jairo Nunez Mendez, and Ximena Pena for answering our numerous questions about the data and the Colombian reforms, and to Ravi Kanbur for useful comments and suggestions at an earlier stage of this project. Goldberg gratefully acknowledges financial support from the Alfred P. Sloan Foundation through a Faculty Research Fellowship.
Urine Arsenic Concentrations and Species Excretion Patterns in American Indian Communities Over a 10-year Period: The Strong Heart Study

Background Arsenic exposure in drinking water disproportionately affects small communities in some U.S. regions, including American Indian communities. In U.S. adults with no seafood intake, median total urine arsenic is 3.4 μg/L. Objective We evaluated arsenic exposure and excretion patterns using urine samples collected over 10 years in a random sample of American Indians from Arizona, Oklahoma, and North and South Dakota who participated in a cohort study from 1989 to 1999. Methods We measured total urine arsenic and arsenic species [inorganic arsenic (arsenite and arsenate), methylarsonate (MA), dimethylarsinate (DMA), and arsenobetaine] concentrations in 60 participants (three urine samples each, for a total of 180 urine samples) using inductively coupled plasma/mass spectrometry (ICPMS) and high-performance liquid chromatography/ICPMS, respectively. Results Median (10th, 90th percentiles) urine concentration for the sum of inorganic arsenic, MA, and DMA at baseline was 7.2 (3.1, 16.9) μg/g creatinine; the median was higher in Arizona (12.5 μg/g), intermediate in the Dakotas (9.1 μg/g), and lower in Oklahoma (4.4 μg/g). The mean percentage distribution of arsenic species over the sum of inorganic and methylated species was 10.6% for inorganic arsenic, 18.4% for MA, and 70.9% for DMA. The intraclass correlation coefficient for three repeated arsenic measurements over a 10-year period was 0.80 for the sum of inorganic and methylated species and 0.64, 0.80, and 0.77 for percent inorganic arsenic, percent MA, and percent DMA, respectively. Conclusions This study found low to moderate inorganic arsenic exposure and confirmed long-term constancy in arsenic exposure and urine excretion patterns in American Indians from three U.S. regions over a 10-year period. Our findings support the feasibility of analyzing arsenic species in large population-based studies with stored urine samples.