Miracle-dz/UniFAR-FTUs huggingface dataset:
Rheumatoid Arthritis and miRNAs: A Critical Review through a Functional View

Rheumatoid arthritis (RA) is a systemic autoimmune disease with severe joint inflammation and destruction associated with an inflammatory environment. The etiology behind RA remains to be elucidated; most updated concepts include the participation of environmental, proteomic, epigenetic, and genetic factors. Epigenetic is considered the missing link to explain genetic diversification among RA patients. Within epigenetic factors participating in RA, miRNAs are defined as small noncoding molecules with a length of approximately 22 nucleotides, capable of gene expression modulation, either negatively through inhibition of translation and degradation of the mRNA or positively through increasing the translation rate. Over the last decade and due to the feasibility of the identification of miRNAs among different tissues and compartments, they have been proposed as biomarkers for diagnosis, prognosis, and response to treatment in different pathologies. Nevertheless, miRNAs seem to be important regulators of networks instead of single genes; their hypothetical use as biomarkers needs to rely on a functional integrative description of their effects in the biological process of autoimmune conditions which until now is missing. Therefore, we underwent a bibliographic search for review and original articles related to miRNAs and their possible implications in rheumatoid arthritis. We found 48 different studies using the key words “miRNAs” or “micro-RNAs” and “rheumatoid arthritis” with restriction of publication dates from 2011 to 2016, in humans, using the English language. After a critical reading, we provide in this paper a functional view with respect to miRNA biogenesis, interaction with targets that are expressed in specific cells and tissues, during different stages of inflammatory responses associated with RA, and recognized specific areas where miRNAs might also have a pathogenic role but remain undescribed. Our results will be useful in designing future research projects that can support miRNAs as biomarkers or therapeutic targets in RA.
NOX4 Expression in Human Microglia Leads to Constitutive Generation of Reactive Oxygen Species and to Constitutive IL-6 Expression

Reactive oxygen species (ROS) generation by microglia is implicated in neuroinflammation and neurotoxicity, as well as in host defense, cell proliferation and excitatory amino acid release. Recent studies demonstrate that primary microglia preparations not only express the phagocyte NADPH oxidase NOX2, but also the NOX1 and NOX4 isoforms. Here we investigated the relationship between neuroinflammation and NOX isoform expression in the human microglia cell line clone 3 (HMC3). HMC3 cells are typical microglia, as suggested by the constitutive expression of Iba-1 and CD14, and IFN-γ-induced expression of CD11b, CD68 and MHCII. However, the characteristics of NOX isoform expression and ROS generation by HMC3 cells were unexpected. RT-PCR demonstrated abundant expression of NOX4, but almost no NOX2 mRNA. ROS generation was constitutive and appeared predominantly intracellular, as superoxide was detected within intracellular vesicles, while the cell-permeable H2O2 was found in the extracellular space. ROS generation by HMC3 was efficiently suppressed by siRNA directed against NOX4, but not by control siRNA. NOX4 suppression did not alter expression of the microglia-typical genes MHCII, CD68 and CD11b, nor did it affect the expression of iNOS, VEGF or TGF-β. However, there was a marked decrease in IL-6 mRNA. Taken together, we demonstrate a constitutive NOX4-dependent ROS generation in a microglial cell line which leads to expression of IL-6 mRNA. The possibility that microglia could switch from tightly regulated NOX2-dependent ROS generation to constitutive NOX4-dependent ROS generation is of interest for the understanding of the role of microglia in maintaining the balance between neuroprotection and neuroinflammatory damage.
Collaborative Dynamic Sparse Topic Regression with User Profile Evolution for Item Recommendation

In many time-aware item recommender systems, modeling the accurate evolution of both user profiles and the contents of items over time is essential. However, most existing methods focus on learning users' dynamic interests, where the contents of items are assumed to be stable over time. They thus fail to capture the dynamic changes in the item's contents. In this paper, we present a novel method CDUE for time-aware item recommendation, which captures the evolution of both user's interests and item's contents information via topic dynamics. Specifically, we propose a dynamic sparse topic model to track the evolution of topics for changes in items' contents over time and adapt a vector autoregressive model to profile users' dynamic interests. The item's topics and user's interests and their evolutions are learned collaboratively and simultaneously into a unified learning framework. Experimental results on two real-world data sets demonstrate the quality and effectiveness of the proposed method and show that our method can be used to make better future recommendations.
Comparing the catch composition, profitability and discard survival from different trammel net designs targeting common spiny lobster (Palinurus elephas) in a Mediterranean fishery

In the Balearic Islands, different trammel net designs have been adopted to promote fisheries sustainability and reduce discards. Here, we compare the catch performance of three trammel net designs targeting the spiny lobster Palinurus elephas in terms of biomass, species composition and revenue from commercial catches and discards. Designs differ in the netting fiber type (standard polyfilament, PMF, or a new polyethylene multi-monofilament, MMF) and the use of a guarding net or greca, a mesh piece intended to reduce discards. Catches were surveyed by an on-board observer from 1,550 netting walls corresponding to 70 nets. The number of marketable species captured indicated that the lobster trammel net fishery has multiple targets, which contribute significantly to the total revenue. The discarded species ranged from habitat-forming species to elasmobranches, but the magnitude of gear-habitat interactions on the long term dynamics of benthos remains unclear. No relevant differences in revenue and weight of discards were detected after Bayesian analyses. However, the species composition of discards was different when using greca. Interestingly, high immediate survival was found for discarded undersized lobsters, while a seven day survival assessment, using captive observation, gave an asymptotic estimate of survival probability as 0.64 (95% CI [0.54–0.76]). Therefore, it is recommended that it would be beneficial for this stock if an exemption from the EU landing obligation regulation was sought for undersized lobsters in the Balearic trammel net fishery.
Learning Pixel-wise Labeling from the Internet without Human Interaction

Deep learning stands at the forefront in many computer vision tasks. However, deep neural networks are usually data-hungry and require a huge amount of well-annotated training samples. Collecting sufficient annotated data is very expensive in many applications, especially for pixel-level prediction tasks such as semantic segmentation. To solve this fundamental issue, we consider a new challenging vision task, Internetly supervised semantic segmentation, which only uses Internet data with noisy image-level supervision of corresponding query keywords for segmentation model training. We address this task by proposing the following solution. A class-specific attention model unifying multiscale forward and backward convolutional features is proposed to provide initial segmentation "ground truth". The model trained with such noisy annotations is then improved by an online fine-tuning procedure. It achieves state-of-the-art performance under the weakly-supervised setting on PASCAL VOC2012 dataset. The proposed framework also paves a new way towards learning from the Internet without human interaction and could serve as a strong baseline therein. Code and data will be released upon the paper acceptance.
Age differences in the neural response to negative feedback

ABSTRACT Affective processing is one domain that remains relatively intact in healthy aging. Investigations into the neural responses associated with reward anticipation have revealed that older and younger adults recruit the same midbrain reward regions, but other evidence suggests this recruitment may differ depending on the valence (gain, loss) of the incentive cue. The goal of the current study was to examine functional covariance during gain and loss feedback in younger and healthy older adults. A group of 15 older adults (mean age = 68.5) and 16 younger adults (mean age = 25.4) completed a revised Monetary Incentive Delay task (rMID; Knutson, Westdorp, Kaiser, & Hommer, 2000) while in the fMRI scanner. The rMID is a reaction time task where successful performance, either gaining a reward or avoiding a loss, is defined by hitting a button during the brief presentation of a visual target. Participants receive gain and loss anticipation cues before each trial and feedback after each trial with four possible outcomes: +$5.00, +0.00, -$5.00, and -$0.00. Using seed-voxel partial least squares analyses, with seed voxels in the caudate and ventromedial prefrontal cortex, whole-brain functional covariance revealed that younger and older adults engage the same network of regions to support general feedback processing. However, older adults engaged two additional networks to support processing of negative feedback, gain_miss (+0), loss_miss (-$5), and loss_hit (−0), specifically. These findings are in line with theories of a positivity effect in aging and may have implications for reward-stimulus learning and decision making following performance-contingent negative feedback.
Marker-Assisted Introgression of Saltol QTL Enhances Seedling Stage Salt Tolerance in the Rice Variety “Pusa Basmati 1”

Marker-assisted selection is an unequivocal translational research tool for crop improvement in the genomics era. Pusa Basmati 1 (PB1) is an elite Indian Basmati rice cultivar sensitive to salinity. Here, we report enhanced seedling stage salt tolerance in improved PB1 genotypes developed through marker-assisted transfer of a major QTL, Saltol. A highly salt tolerant line, FL478, was used as the Saltol donor. Parental polymorphism survey using 456 microsatellite (SSR)/QTL-linked markers revealed 14.3% polymorphism between PB1 and FL478. Foreground selection was carried out using three Saltol-linked polymorphic SSR markers RM8094, RM493, and RM10793 and background selection by 62 genome-wide polymorphic SSR markers. In every backcross generation, foreground selection was restricted to the triple heterozygotes of foreground markers, which was followed by phenotypic and background selections. Twenty-four near isogenic lines (NILs), with recurrent parent genome recovery of 96.0–98.4%, were selected after two backcrosses followed by three selfing generations. NILs exhibited agronomic traits similar to those of PB1 and additional improvement in the seedling stage salt tolerance. They are being tested for per se performance under salt-affected locations for release as commercial varieties. These NILs appear promising for enhancing rice production in salinity-affected pockets of Basmati Geographical Indication (GI) areas of India.
End-to-end driving simulation via angle branched network

Imitation learning for end-to-end autonomous driving has drawn attention from academic communities. Current methods either only use images as the input which is ambiguous when a car approaches an intersection, or use additional command information to navigate the vehicle but not automated enough. Focusing on making the vehicle drive along the given path, we propose a new navigation command that does not require human's participation and a novel model architecture called angle branched network. Both the new navigation command and the angle branched network are easy to understand and effective. Besides, we find that not only segmentation information but also depth information can boost the performance of the driving model. We conduct experiments in a 3D urban simulator and both qualitative and quantitative evaluation results show the effectiveness of our model.
Suicide Risk Assessment: Trust an Implicit Probe or Listen to the Patient?

Previous research suggests implicit cognition can predict suicidal behavior. This study examined the utility of the death/suicide implicit association test (d/s-IAT) in acute and prospective assessment of suicide risk and protective factors, relative to clinician and patient estimates of future suicide risk. Patients (N = 128; 79 female; 111 Caucasian) presenting to an emergency department were recruited if they reported current suicidal ideation or had been admitted because of an acute suicide attempt. Patients completed the d/s-IAT and self-report measures assessing three death-promoting (e.g., suicide ideation) and two life-sustaining (e.g., zest for life) factors, with self-report measures completed again at 3- and 6-month follow-ups. The clinician and patient provided risk estimates of that patient making a suicide attempt within the next 6 months. Results showed that among current attempters, the d/s-IAT differentiated between first time and multiple attempters; with multiple attempters having significantly weaker self-associations with life relative to death. The d/s-IAT was associated with concurrent suicidal ideation and zest for life, but only predicted the desire to die prospectively at 3 months. By contrast, clinician and patient estimates predicted suicide risk at 3- and 6-month follow-up, with clinician estimates predicting death-promoting factors, and only patient estimates predicting life-sustaining factors. The utility of the d/s-IAT was more pronounced in the assessment of concurrent risk. Prospectively, clinician and patient predictions complemented each other in predicting suicide risk and resilience, respectively. Our findings indicate collaborative rather than implicit approaches add greater value to the management of risk and recovery in suicidal patients.
Leakage currents and gas generation in advanced wet tantalum capacitors

Currently, military grade, established reliability wet tantalum capacitors are among the most reliable parts used for space applications. This has been achieved over the years by extensive testing and improvements in design and materials. However, a rapid insertion of new types of advanced, high volumetric efficiency capacitors in space systems without proper testing and analysis of degradation mechanisms might increase risks of failures. The specifics of leakage currents in wet electrolytic capacitors is that the conduction process is associated with electrolysis of electrolyte and gas generation resulting in building up of internal gas pressure in the parts. The risk associated with excessive leakage currents and increased pressure is greater for high value advanced wet tantalum capacitors, but it has not been properly evaluated yet. In this work, in Part I, leakages currents in various types of tantalum capacitors have been analyzed in a wide range of voltages, temperatures, and time under bias. Gas generation and the level of internal pressure have been calculated in Part II for different case sizes and different hermeticity leak rates to assess maximal allowable leakage currents. Effects related to electrolyte penetration to the glass seal area have been studied and the possibility of failures analyzed in Part III. Recommendations for screening and qualification to reduce risks of failures have been suggested. Table of
Learning a face space for experiments on human identity

Generative models of human identity and appearance have broad applicability to behavioral science and technology, but the exquisite sensitivity of human face perception means that their utility hinges on the alignment of the model's representation to human psychological representations and the photorealism of the generated images. Meeting these requirements is an exacting task, and existing models of human identity and appearance are often unworkably abstract, artificial, uncanny, or biased. Here, we use a variational autoencoder with an autoregressive decoder to learn a face space from a uniquely diverse dataset of portraits that control much of the variation irrelevant to human identity and appearance. Our method generates photorealistic portraits of fictive identities with a smooth, navigable latent space. We validate our model's alignment with human sensitivities by introducing a psychophysical Turing test for images, which humans mostly fail. Lastly, we demonstrate an initial application of our model to the problem of fast search in mental space to obtain detailed "police sketches" in a small number of trials.
Smoking, Blood Pressure, and Cardiovascular Disease Mortality in a Large Cohort of Chinese Men with 15 Years Follow-up

Background: To examine the joint effects of smoking and blood pressure on the risk of mortality from cardiovascular disease (CVD) in a cohort of Chinese men. Methods: This study followed a cohort of 213,221 men over 40 years of age who were recruited from 45 district/counties across China between 1990–1991, and whose cause-specific mortality was examined for 15 years, up to 31 December 2005. We calculated hazard ratios for all-cause mortality and CVD, ischemic heart disease (IHD), and stroke mortality for the combined sets of smoking status and blood pressure levels using the Cox proportional hazard model, adjusting for potential individual-level and contextual-level risk factors. Results: During the 15 years of follow-up, 52,795 deaths occurred, including 18,833 deaths from CVD, 3744 deaths from IHD, and 11,288 deaths from stroke. The risk of mortality from CVD, IHD, and stroke increased significantly, with increased systolic blood pressure (SBP), diastolic blood pressure (DBP), and with more pack years of smoking. Compared with never-smokers with normal blood pressure, the hazard ratios and 95% CI of CVD, IHD, and stroke mortality for those who smoked over 20 pack years with hypertension were remarkably increased to 2.30 (95% CI: 2.12–2.50), 1.78 (95% CI: 1.48–2.14), and 2.74 (95% CI: 2.45–3.07), respectively. Conclusion: There was a combined effect on the risk of CVD, IHD, and stroke mortality between smoking and hypertension. The joint efforts on smoking cessation and lowered blood pressure should be made to prevent cardiovascular disease mortality in Chinese men.
Hypoxia-induced expression of CXCR4 favors trophoblast cell migration and invasion via the activation of HIF-1α

The placenta initially develops in a low-oxygen environment up to week 8–10 of gestation, and a low oxygen level is a critical factor in the regulation of trophoblast migration and invasion. CXC chemokine receptor 4 (CXCR4) is transcriptionally activated by hypoxia in cancer cells. However, whether CXCR4 is involved in hypoxia-inducible factor (HIF)-1α-dependent trophoblastic migration and invasion in a physiologically hypoxic environment (3% O2) remains to be fully elucidated and requires further investigation. In the present study, the expression of CXCR4 in first-trimester villi was investigated, as was the response of the trophoblast to hypoxia, and the role of CXCR4 and HIF-1α in trophoblast migration and invasion. CXCR4 was significantly elevated in the first-trimester villi compared with normal full-term placentas. In vitro, the expression of CXCR4 at the mRNA and protein levels was increased in JEG3 cells exposed to 3% O2 in a time-dependent manner, and the migratory and invasive abilities of the JEG3 cells were upregulated. In addition, CXCR4 knockdown by transfection with CXCR4-specific small interfering (si)RNA decreased the migration and invasion of JEG3 cells exposed to 3% O2. Furthermore, synthetic siRNA specific for HIF-1α significantly suppressed the expression of CXCR4 in JEG3 cells exposed to 3% O2, whereas pcDNA-HIF-1α significantly increased the expression of CXCR4. These results indicated that the hypoxia-induced expression of CXCR4 promoted trophoblast cell migration and invasion via the activation of HIF-1α, which is crucial during placentation.
A PTAS for a Class of Stochastic Dynamic Programs

We develop a framework for obtaining polynomial time approximation schemes (PTAS) for a class of stochastic dynamic programs. Using our framework, we obtain the first PTAS for the following stochastic combinatorial optimization problems: \probemax: We are given a set of $n$ items, each item $i\in [n]$ has a value $X_i$ which is an independent random variable with a known (discrete) distribution $\pi_i$. We can {\em probe} a subset $P\subseteq [n]$ of items sequentially. Each time after {probing} an item $i$, we observe its value realization, which follows the distribution $\pi_i$. We can {\em adaptively} probe at most $m$ items and each item can be probed at most once. The reward is the maximum among the $m$ realized values. Our goal is to design an adaptive probing policy such that the expected value of the reward is maximized. To the best of our knowledge, the best known approximation ratio is $1-1/e$, due to Asadpour \etal~\cite{asadpour2015maximizing}. We also obtain PTAS for some generalizations and variants of the problem and some other problems.
The Benefit in Free Information Disclosure When Selling Information to People

This paper studies the benefit for information providers in free public information disclosure in settings where the prospective information buyers are people. The underlying model, which applies to numerous real-life situations, considers a standard decision making setting where the decision maker is uncertain about the outcomes of her decision. The information provider can fully disambiguate this uncertainty and wish to maximize her profit from selling such information. We use a series of AMT-based experiments with people to test the benefit for the information provider from reducing some of the uncertainty associated with the decision maker's problem, for free. Free information disclosure of this kind can be proved to be ineffective when the buyer is a fully-rational agent. Yet, when it comes to people we manage to demonstrate that a substantial improvement in the information provider's profit can be achieved with such an approach. The analysis of the results reveals that the primary reason for this phenomena is people's failure to consider the strategic nature of the interaction with the information provider. Peoples' inability to properly calculate the value of information is found to be secondary in its influence.
Class Percentage of Students With Reading Difficulties on Content Knowledge and Comprehension

We examined the efficacy of a content acquisition and reading comprehension intervention implemented in eighth-grade social studies classrooms. Using a within-teacher randomized control design, 18 eighth-grade teachers’ social studies classes were randomly assigned to a treatment or comparison condition. Teachers taught all their classes (treatment and comparison) using the same content; however, in the treatment classes, teachers used instructional practices that included comprehension canopy, essential words, knowledge acquisition, and team-based learning. Students with reading comprehension difficulties in the treatment classes (n = 359) outperformed students with reading comprehension difficulties in the comparison classes (n = 331) on measures of content knowledge acquisition and content reading comprehension but not general reading comprehension. In addition, the proportion of students with reading comprehension difficulties in classes moderated outcomes for content knowledge acquisition and content reading comprehension.