Miracle-dz/UniFAR-FTUs huggingface dataset:
Temporal changes in inflammatory mediator concentrations in an adjuvant model of temporomandibular joint inflammation.

AIMS To determine temporal changes in the concentrations found in the temporomandibular joint (TMJ) and trigeminal ganglion of 3 specific classes of inflammatory mediators commonly linked with conditions of joint inflammation. The intent was to determine whether concentrations of the neuropeptide calcitonin gene-related peptide (CGRP), the neurotrophin nerve growth factor (NGF), and the proinflammatory cytokines interleukin-1beta (IL1beta) and tumor necrosis factor-alpha (TNF-alpha) are altered in the trigeminal ganglion and TMJ tissues during various stages of adjuvant-induced inflammation of the rat TMJ. METHODS Adult male rats received bilateral TMJ injection of complete Freund's adjuvant (CFA), while control rats did not receive CFA treatment. The trigeminal ganglion and TMJ tissues were collected at 2 days, and 2, 4, and 6 weeks postinjection and analyzed using either radioimmunoassay or enzyme-linked immunosorbent assay. RESULTS In the trigeminal ganglion, both CGRP and NGF concentrations were significantly elevated in comparison to controls from 2 days to 4 weeks; however, the patterns of increase differed. Concentrations of each inflammatory mediator were significantly elevated in the TMJ tissues of CFA-injected animals at 2 days and continued to be significantly elevated throughout the 6-week period. CGRP content remained at peak levels from 2 days through 6 weeks, while peak content for NGF, IL-1beta, and TNF-alpha was found at 2 days through 2 weeks. CONCLUSION The results suggest that the development of CFA-induced inflammation of the TMJ was accompanied by a variable increase in the concentration of different classes of inflammatory mediators in both the trigeminal ganglion and TMJ tissues, which implies that each class of inflammatory mediator may play a significant role during different stages in the onset and exacerbation of the inflammatory process.
Evaluation of Different Reference Based Annotation Strategies Using RNA-Seq – A Case Study in Drososphila pseudoobscura

RNA-Seq is a powerful tool for the annotation of genomes, in particular for the identification of isoforms and UTRs. Nevertheless, several software tools exist and no standard strategy to obtain a reliable annotation is yet established. We tested different combinations of the most commonly used reference-based alignment tools (TopHat, GSNAP) in combination with two frequently used reference-based assemblers (Cufflinks, Scripture) and evaluated the potential of RNA-Seq to improve the annotation of Drosophila pseudoobscura. While GSNAP maps a higher proportion of reads, TopHat resulted in a more accurate annotation when used in combination with Cufflinks. Scripture had the lowest sensitivity. Interestingly, after subsampling to the same coverage for GSNAP and TopHat, we find that both mappers have similar performance, implying that the advantage of TopHat is mainly an artifact of the lower coverage. Overall, we observed a low concordance among the different approaches tested both at junction and isoform levels. Using data from both sexes of two adult strains of D. pseudoobscura we detected alternative splicing for about 30% of the FlyBase multiple-exon genes. Moreover, we extended the boundaries for 6523 genes (about 40%). We annotated 669 new genes, 45% of them with splicing evidence. Most of the new genes are located on unassembled contigs, reflecting their incomplete annotation. Finally, we identified 99 additional new genes that are not represented in the current genome contigs of D. pseudoobscura, probably due to location in genomic regions that are difficult to assemble (e.g. heterochromatic regions).
Visualization and structural analysis of the bacterial magnetic organelle magnetosome using atomic force microscopy

The unique ability of magnetotactic bacteria to navigate along a geomagnetic field is accomplished with the help of prokaryotic organelles, magnetosomes. The magnetosomes have well-ordered chain-like structures, comprising membrane-enveloped, nano-sized magnetic crystals, and various types of specifically associated proteins. In this study, we applied atomic force microscopy (AFM) to investigate the spatial configuration of isolated magnetosomes from Magnetospirillum magneticum AMB-1 in near-native buffer conditions. AFM observation revealed organic material with a ∼7-nm thickness surrounding a magnetite crystal. Small globular proteins, identified as magnetosome-associated protein MamA, were distributed on the mica surface around the magnetosome. Immuno-labeling with AFM showed that MamA is located on the magnetosome surface. In vitro experiments showed that MamA proteins interact with each other and form a high molecular mass complex. These findings suggest that magnetosomes are covered with MamA oligomers in near-native environments. Furthermore, nanodissection revealed that magnetosomes are built with heterogeneous structures that comprise the organic layer. This study provides important clues to the supramolecular architecture of the bacterial organelle, the magnetosome, and insight into the function of the proteins localized in the organelle.
Research and Productivity Growth Across Industries

What factors underlie industry differences in research intensity and productivity growth? We develop a multisector growth model using standard parameters to capture the main factors considered in the empirical R&D and productivity growth literature. Along the balanced growth path, we find that the primary factor behind industry differences in productivity growth is the extent to which new knowledge builds upon prior knowledge. In contrast, R&D intensity also depends upon the relative importance of different sources of prior knowledge. Quantitatively, we find that the key factor behind industry differences in both productivity growth and R&D intensity is the extent to which new knowledge builds upon prior knowledge, regardless of the source.
Marden's Tameness Conjecture: history and applications

Marden's Tameness Conjecture predicts that every hyperbolic 3-manifold with finitely generated fundamental group is homeomorphic to the interior of a compact 3-manifold. It was recently established by Agol and Calegari-Gabai. We will survey the history of work on this conjecture and discuss its many applications.
Call classification for automated troubleshooting on large corpora

This paper compares six algorithms for call classification in the framework of a dialog system for automated troubleshooting. The comparison is carried out on large datasets, each consisting of over 100,000 utterances from two domains: television (TV) and Internet (INT). In spite of the high number of classes (79 for TV and 58 for INT), the best classifier (maximum entropy on word bigrams) achieved more than 77% classification accuracy on the TV dataset and 81% on the INT dataset.
Dictionary learning for classification of indoor micro-Doppler signatures across multiple carriers

Micro-Doppler signatures of dynamic targets such as humans, animals and vehicles are very effective feature vectors for classification based on machine learning algorithms. In the existing works, the test data have been measured in nearly identical operating conditions to the training data that were gathered for the classifiers. However, this assumption may be violated in real life scenarios. In this work, we demonstrate that classification based on sparsity based dictionary learning can overcome this limitation. Here, we learn unique target class dictionaries from micro-Dopplers gathered at multiple carriers. Then we test the classifier using data gathered at another carrier (distinct from those used for training). We test the performance of the classification algorithm for both simulation and measurement data. Our results show a classification accuracy of 99% and 89% for simulated and measurement data respectively.
Multipotent stromal cells skew monocytes towards an anti-inflammatory interleukin-10-producing phenotype by production of interleukin-6

Multipotent stromal cells have immunomodulatory capacities and have been used in transplantation and autoimmune diseases. One of the effects of multipotent stromal cells involves the inhibition of dendritic cell differentiation. Since interleukin-6 and interleukin-10 are known to play a role in inhibiting immature dendritic cell differentiation, we hypothesized that these cytokines may also mediate the inhibitory effect of human multipotent stromal cells in immature dendritic cell differentiation. In order to test this hypothesis monocytes were cultured with interleukin-4 and granulocyte-monocyte colony-stimulating factor in the presence or absence of culture-expanded bone marrow-derived multipotent stromal cells. Neutralization and cytokine-depletion strategies were applied to reveal the cellular source and effect of interleukin-6 and interleukin-10. Addition of multipotent stromal cells to monocyte cultures significantly reduced the generation of immature dendritic cells (CD14−CD1a+) and resulted in the generation of CD14+CD1a− cells that displayed a significantly reduced immunostimulatory effect. We found that culture supernatants of co-cultures of multipotent stromal cells and monocytes contained higher concentrations of interleukin-6 and interleukin-10. Multipotent stromal cells produced interleukin-6 and neutralizing this interleukin-6 reversed the inhibitory effect of the multipotent cells. Interleukin-10 was not produced by multipotent stromal cells, but exclusively by monocytes after exposure to multipotent stromal cell-produced interleukin-6. In conclusion, through constitutive production of interleukin-6, multipotent stromal cells prevent the differentiation of monocytes towards antigen-presenting immunogenic cells and skew differentiation towards an anti-inflammatory interleukin-10-producing cell type.
Site amplification, attenuation, and scattering from noise correlation amplitudes across a dense array in Long Beach, CA

For accurate seismic hazard evaluation, both the spatial and frequency‐dependent variabilities in the amplitudes of earthquake ground motions are needed. While this information is rarely fully available due to the paucity of relevant seismic data, dense arrays like the 5200‐geophone array in Long Beach, California provide the opportunity to study this amplitude variability. Here we show that ambient noise correlation amplitudes from the Long Beach array can be used to directly determine frequency‐dependent site amplification factors. We analyze Rayleigh‐wavefield amplitude gradients from ambient noise correlations that are processed so that relative amplitudes satisfy the wave equation and are therefore meaningful. Ultimately, we construct maps of site amplification across Long Beach at frequencies of 0.67, 1.0, and 2.0 Hz. These maps correlate well with local structure, notably the Newport‐Inglewood Fault and also to known velocity structure. Through this process, we also obtain constraints on average attenuation structure and local scattering.
Why More Productive Sites Have More Species: An Experimental Test of Theory Using Tree‐Hole Communities

One of the most common explanations for an increase in species richness with productivity is what we have dubbed the “More Individuals Hypothesis. ” According to this hypothesis, more productive sites can support higher total abundances and, since species richness is an increasing function of total abundance, so will it be of productivity. This hypothesis assumes that communities are limited by productivity. We tested the More Individuals Hypothesis using the detritivorous aquatic insect communities of tree holes. When tree holes with varying levels of productivity (debris amount) were allowed to be colonized (through oviposition), more productive tree holes did have more species but not more individuals. Neither was total energy use strictly proportional to productivity. Only in communities forced to disassemble through productivity reductions were the predictions of the More Individuals Hypothesis satisfied. Ovipositing adults may prefer productive tree holes not because they contain more resources but because they are anticipated to be less likely to dry out. In tree holes, and more generally, the More Individuals Hypothesis is an insufficient explanation for increases in species richness with productivity because it neither accounts for the different processes of local coloni zation and extinction nor allows body size to correlate with extinction risk.
Deep Reinforcement Learning in Large Discrete Action Spaces

Being able to reason in an environment with a large number of discrete actions is essential to bringing reinforcement learning to a larger class of problems. Recommender systems, industrial plants and language models are only some of the many real-world tasks involving large numbers of discrete actions for which current methods are difficult or even often impossible to apply. An ability to generalize over the set of actions as well as sub-linear complexity relative to the size of the set are both necessary to handle such tasks. Current approaches are not able to provide both of these, which motivates the work in this paper. Our proposed approach leverages prior information about the actions to embed them in a continuous space upon which it can generalize. Additionally, approximate nearest-neighbor methods allow for logarithmic-time lookup complexity relative to the number of actions, which is necessary for time-wise tractable training. This combined approach allows reinforcement learning methods to be applied to large-scale learning problems previously intractable with current methods. We demonstrate our algorithm’s abilities on a series of tasks having up to one million actions.
Typographic enhancement of multiword units in second language text

This study examines the effect of typographic enhancement on L2 learners’ intake of multiword units from reading. EFL learners read texts in one of three versions: (1) with many multiword units underlined; (2) with half of these multiword units underlined; and (3) without any underlining. The learners were subsequently asked to identify the multiword units they remembered encountering in the texts. The purpose of the text version in which only half of the target units were underlined was to explore whether enhancement of a small number of word strings in a text also stimulates intake of others from that text. As expected, enhanced multiword units were remembered better than unenhanced ones, but there was no evidence that the benefit extended beyond the enhanced items. Cette etude s'interesse a l'effet, chez des lecteurs en langue seconde, d'une mise en relief typographique sur la memorisation d'expressions lexicales. Les participants sont confrontes a l'une de ces trois versions d'un texte en anglais: (a) la premiere ou certaines expressions lexicales sont soulignees, (b) la deuxieme ou seulement la moitie de ces expressions sont soulignees, (c) et la troisieme ou aucune n'est soulignee. Ulterieurement, les apprenants sont invites a identifier les expressions qu'ils se souviennent avoir rencontrees dans le texte. L'objectif de la deuxieme version du texte est d'examiner si la mise en evidence de quelques expressions peut avoir un effet benefique sur la memorisation d'autres expressions au sein d'un meme texte. Notre etude confirme que la memorisation des expressions soulignees est superieure a celle des expressions non-soulignees. Par ailleurs, la deuxieme version du texte ne revele aucun impact positif sur la memorisation des expressions non-soulignees
Feasibility Analysis of On-Line DVS Algorithms for Scheduling Arbitrary Event Streams

Performance boosting of modern computing systems has been constrained by the significant chip/circuit power dissipation. Dynamic voltage scaling (DVS) has been applied in the past decade for reducing the energy consumption by dynamically changing the supply voltage. On-line scheduling algorithms for DVS systems usually guarantee the real-time constraints of the system based on the condition that they can select any system speed that is sufficiently high to allow processing of all events within their deadlines. However, practical systems have a maximum available system speed and the feasibility of using on-line DVS algorithms needs to be verified during design time, i.e., they will never require during runtime a speed higher than the maximum available. This paper presents feasibility analysis of two on-line DVS algorithms that can compute in advance an upper bound on the system speed that these algorithms may require given that there is a single input event stream described by the worst-case event arrivals in interval domain. Moreover, we also present new results on the competitive ratios of the resulting schedules for energy consumption minimization with comparison to the off-line optimal solutions to show the effectiveness of the two algorithms. At the end, the performance of the different algorithms is evaluated.
Exploring the For-Profit Experience

The for-profit college sector is arguably the most controversial and least understood sector of higher education today. The past decade has ushered in a wealth of public concern and scrutiny as to whether for-profit colleges and universities are providing a quality education to underserved student populations. While their politicization has captured immense attention, there is far less empirical research on student experiences at for-profit institutions to better inform conceptual, institutional, and practical understanding of this sector of postsecondary education. Using ethnographic data from one midsize for-profit college in a suburban city, the author spent seven months exploring educational culture from the perspective of enrolled students. The findings illuminate four themes: (a) student desire for institutional transparency, (b) the perception of high-quality in-person instruction, (c) varied experiences based on student schedule and learning needs, and (d) the role of age in shaping peer interactions.
Prevalence and characteristics of the metabolic syndrome in the San Antonio Heart and Framingham Offspring Studies.

The metabolic syndrome may be a common phenotype increasing risk for type 2 diabetes and cardiovascular disease. We assessed the prevalence and characteristics of the metabolic syndrome among population-based samples of 3,224 white subjects attending Framingham Offspring Study (FOS) exam 5 (1991-1995) and 1,081 non-Hispanic white and 1,656 Mexican-American subjects attending the San Antonio Heart Study (SAHS) phase II follow-up exam (1992-1996). Subjects were approximately 50% women, aged 30-79 years, without diabetes, and classified with the metabolic syndrome according to criteria for obesity, dyslipidemia, hyperglycemia, and hypertension proposed by the Third Report of the National Cholesterol Education Program's Adult Treatment Panel (ATP III) or the World Health Organization (WHO). We used regression models to estimate rates across ethnic groups and to assess the association of the metabolic syndrome with insulin resistance and predicted 10-year coronary heart disease (CHD) risk. Among FOS white subjects, the age- and sex-adjusted prevalence of the metabolic syndrome was 24% by both ATP III and WHO criteria; among SAHS non-Hispanic white subjects, 23 and 21%, respectively; and among SAHS Mexican-American subjects, 31 and 30%. Rates were highest among Mexican-American women (ATP III, 33%) and lowest among white women (21%). Subjects with the metabolic syndrome by ATP III criteria had higher age-, sex-, and ethnicity-adjusted levels of fasting insulin (11.3 micro U/ml), homeostasis model assessment of insulin resistance (2.7), and predicted CHD risk (11.8%) than those without the syndrome (5.9 micro U/ml, 1.3, and 6.4%, respectively; all P = 0.0001); differences were similar using WHO criteria. We conclude that the metabolic syndrome typically affects 20-30% of middle-aged adults in the U.S. By any criteria, subjects with the metabolic syndrome are more insulin resistant and at increased predicted risk for CHD versus those without the metabolic syndrome.
The Importance of Having Arc: Expression of the Immediate-Early Gene Arc Is Required for Hippocampus-Dependent Fear Conditioning and Blocked by NMDA Receptor Antagonism

Long-lasting, experience-dependent changes in synaptic strength are widely thought to underlie the formation of memories. Many forms of learning-related plasticity are likely mediated by NMDA receptor activation and plasticity-related gene expression in brain areas thought to be important for learning and memory, including the hippocampus. Here, we examined the putative role of activity-regulated cytoskeletal-associated protein (Arc), an immediate-early gene (IEG) whose expression is tightly linked to the induction and maintenance of some forms of neuronal plasticity, in hippocampus-dependent and hippocampus-independent forms of learning. The extent to which learning-induced Arc expression may depend on NMDA receptor activation was also assessed. First, we observed an increase in Arc gene and protein products in both dorsal hippocampus (DH) and ventral hippocampus (VH) of male Sprague Dawley rats after hippocampus-dependent trace and contextual fear conditioning, but not after hippocampus-independent delay fear conditioning. Specific knockdown of Arc using antisense oligodeoxynucleotides (ODNs) in DH or VH attenuated the learning-related expression of Arc protein, and resulted in a dramatic impairment in trace and contextual, but not delay, fear conditioning. Finally, pretraining infusions of the NMDA receptor antagonist APV into the DH or VH blocked the learning-induced enhancement of Arc in a regionally selective manner, suggesting that NMDA receptor activation and Arc translation are functionally coupled to support hippocampus-dependent memory for fear conditioning. Collectively these results provide the first evidence suggesting that NMDA receptor-dependent expression of the IEG Arc in both DH and VH likely underlies the consolidation of a variety of forms of hippocampus-dependent learning.