Miracle-dz/UniFAR-FTUs huggingface dataset:
Deltex2 represses MyoD expression and inhibits myogenic differentiation by acting as a negative regulator of Jmjd1c

Significance The data presented address a fundamental mechanism controlling the expression of a master regulator of cellular differentiation, MyoD, by a member of the Deltex family of proteins. We show that MyoD expression is regulated by modulation of histone methylation in its promoter region by the histone demethylase, Jjmd1c. These data provide insight into the epigenetic control of gene expression in the regulation of myogenic differentiation. The myogenic regulatory factor MyoD has been implicated as a key regulator of myogenesis, and yet there is little information regarding its upstream regulators. We found that Deltex2 inhibits myogenic differentiation in vitro, and that skeletal muscle stem cells from Deltex2 knockout mice exhibit precocious myogenic differentiation and accelerated regeneration in response to injury. Intriguingly, Deltex2 inhibits myogenesis by suppressing MyoD transcription, and the Deltex2 knockout phenotype can be rescued by a loss-of-function allele for MyoD. In addition, we obtained evidence that Deltex2 regulates MyoD expression by promoting the enrichment of histone 3 modified by dimethylation at lysine 9 at a key regulatory region of the MyoD locus. The enrichment is attributed to a Deltex2 interacting protein, Jmjd1c, whose activity is directly inhibited by Deltex2 and whose expression is required for MyoD expression in vivo and in vitro. Finally, we find that Deltex2 causes Jmjd1c monoubiquitination and inhibits its demethylase activity. Mutation of the monoubiquitination site in Jmjd1c abolishes the inhibitory effect of Deltex2 on Jmjd1c demethylase activity. These results reveal a mechanism by which a member of the Deltex family of proteins can inhibit cellular differentiation, and demonstrate a role of Deltex in the epigenetic regulation of myogenesis.
Physiological and Proteomic Responses of Continuous Cultures of Microcystis aeruginosa PCC 7806 to Changes in Iron Bioavailability and Growth Rate

ABSTRACT The hepatotoxin microcystin (MCYST) is produced by a variety of freshwater cyanobacterial species, including Microcystis aeruginosa. Interestingly, MCYST-producing M. aeruginosa strains have been shown to outcompete their nontoxic counterparts under iron-limiting conditions. However, the reasons for this are unclear. Here we examined the proteomic response of M. aeruginosa PCC 7806 continuous cultures under different iron and growth regimes. Iron limitation was correlated with a global reduction in levels of proteins associated with energy metabolism and photosynthesis. These proteomic changes were consistent with physiological observations, including reduced chlorophyll a content and reduced cell size. While levels of MCYST biosynthesis proteins did not fluctuate during the study period, both intra- and extracellular toxin quotas were significantly higher under iron-limiting conditions. Our results support the hypothesis that intracellular MCYST plays a role in protecting the cell against oxidative stress. Further, we propose that extracellular MCYST may act as a signaling molecule, stimulating MCYST production under conditions of iron limitation and enhancing the fitness of bloom populations. IMPORTANCE Microcystin production in water supply reservoirs is a global public health problem. Understanding the ecophysiology of hepatotoxic cyanobacteria, including their responses to the presence of key micronutrient metals such as iron, is central to managing harmful blooms. To our knowledge, this was the first study to examine proteomic and physiological changes occurring in M. aeruginosa continuous cultures under conditions of iron limitation at different growth rates.
Coronary bifurcation lesions treated with simple or complex stenting: 5-year survival from patient-level pooled analysis of the Nordic Bifurcation Study and the British Bifurcation Coronary Study.

AIMS Randomized trials of coronary bifurcation stenting have shown better outcomes from a simple (provisional) strategy rather than a complex (planned two-stent) strategy in terms of short-term efficacy and safety. Here, we report the 5-year all-cause mortality based on pooled patient-level data from two large bifurcation coronary stenting trials with similar methodology: the Nordic Bifurcation Study (NORDIC I) and the British Bifurcation Coronary Study: old, new, and evolving strategies (BBC ONE). METHODS AND RESULTS Both multicentre randomized trials compared simple (provisional T-stenting) vs. complex (culotte, crush, and T-stenting) techniques, using drug-eluting stents. We analysed all-cause death at 5 years. Data were collected from phone follow-up, hospital records, and national mortality tracking. Follow-up was complete for 890 out of 913 patients (97%). Both Simple and Complex groups were similar in terms of patient and lesion characteristics. Five-year mortality was lower among patients who underwent a simple strategy rather than a complex strategy [17 patients (3.8%) vs. 31 patients (7.0%); P = 0.04]. CONCLUSION For coronary bifurcation lesions, a provisional single-stent approach appears to be associated with lower long-term mortality than a systematic dual stenting technique.
Attention-Based Extraction of Structured Information from Street View Imagery

We present a neural network model — based on Convolutional Neural Networks, Recurrent Neural Networks and a novel attention mechanism — which achieves 84.2% accuracy on the challenging French Street Name Signs (FSNS) dataset, significantly outperforming the previous state of the art (Smith'16), which achieved 72.46%. Furthermore, our new method is much simpler and more general than the previous approach. To demonstrate the generality of our model, we show that it also performs well on an even more challenging dataset derived from Google Street View, in which the goal is to extract business names from store fronts. Finally, we study the speed/accuracy tradeoff that results from using CNN feature extractors of different depths. Surprisingly, we find that deeper is not always better (in terms of accuracy, as well as speed). Our resulting model is simple, accurate and fast, allowing it to be used at scale on a variety of challenging real-world text extraction problems.
VEGF blockade enhances the antitumor effect of BRAFV 600E inhibition

The development of resistance remains a major obstacle to long‐term disease control in cancer patients treated with targeted therapies. In BRAF‐mutant mouse models, we demonstrate that although targeted inhibition of either BRAF or VEGF initially suppresses the growth of BRAF‐mutant tumors, combined inhibition of both pathways results in apoptosis, long‐lasting tumor responses, reduction in lung colonization, and delayed onset of acquired resistance to the BRAF inhibitor PLX4720. As well as inducing tumor vascular normalization and ameliorating hypoxia, this approach induces remodeling of the extracellular matrix, infiltration of macrophages with an M1‐like phenotype, and reduction in cancer‐associated fibroblasts. At the molecular level, this therapeutic regimen results in a de novo transcriptional signature, which sustains and explains the observed efficacy with regard to cancer progression. Collectively, our findings offer new biological rationales for the management of clinical resistance to BRAF inhibitors based on the combination between BRAFV600E inhibitors with anti‐angiogenic regimens.
Unraveling Saproxylic Insect Interactions in Tree Hollows from Iberian Mediterranean Forest

Abstract Tree hollows are complex microhabitats in which a variety of abiotic and biotic factors shape the community assembly of saproxylic insects. Detecting non-random species co-occurrence patterns is a fundamental goal in ecology in order to understand the assembly mechanisms of communities. We study association patterns of species of Coleoptera and Diptera (Syrphidae), belonging to different trophic guilds, on 72 tree hollows at a local and regional scale in three protected areas in Mediterranean forests using a fixed–fixed null model. Our matrix-level analysis shows a tendency for segregation in species association (species exclusion) at the regional and site levels. However, the high complexity of tree-hollow habitats, offering different resources for a more or less specialized fauna, makes it difficult to prove competition interactions. Indeed, pairwise analysis shows a dominance of non-random aggregation patterns (species coexistence) at the local and regional levels. Both aggregation and segregation of non-random patterns were more common among species from different trophic guilds than within the same guilds, with predators being a common denominator for a high percentage of the inter-guild pairs. Our results suggest that predation and facilitation interactions, together with habitat segregation, are the main factors shaping tree-hollow assemblages, while competition seems to be less important. We conclude that species interactions take an important part of the process of assemblage structuration and special attention should be paid to ‘ecosystem engineers' and threatened species in the conservation of tree hollow assemblages.
Straggler Mitigation for Distributed Behavioral Simulation

Running large-scale behavioral simulations requires high computational power, which can be acquired by distributing computation workload to multiple computing nodes (i.e., workers) that run in parallel. The implementations of such systems commonly follow the Bulk Synchronous Parallel (BSP) model. However, implementations using BSP usually suffer from the straggler problem, where the delay of any worker slows down the entire simulation. The problem usually occurs due to communication delays or imbalanced workload among workers. To mitigate the straggler problem, we propose a novel parallel computational model, called Priority Synchronous Parallel (PSP) model. PSP exploits data dependencies of parallel processes to determine high priority data to be computed and synchronized while computing the remaining data. PSP is implemented and evaluated using traffic simulations for three large cities. The proposed technique shows significant performance improvements over the BSP model.
The ultimate and proximate mechanisms driving the evolution of long tails in forest deer mice

Understanding both the role of selection in driving phenotypic change and its underlying genetic basis remain major challenges in evolutionary biology. Here, we use modern tools to revisit a classic system of local adaptation in the North American deer mouse, Peromyscus maniculatus, which occupies two main habitat types: prairie and forest. Using historical collections, we find that forest‐dwelling mice have longer tails than those from nonforested habitat, even when we account for individual and population relatedness. Using genome‐wide SNP data, we show that mice from forested habitats in the eastern and western parts of their range form separate clades, suggesting that increased tail length evolved independently. We find that forest mice in the east and west have both more and longer caudal vertebrae, but not trunk vertebrae, than nearby prairie forms. By intercrossing prairie and forest mice, we show that the number and length of caudal vertebrae are not correlated in this recombinant population, indicating that variation in these traits is controlled by separate genetic loci. Together, these results demonstrate convergent evolution of the long‐tailed forest phenotype through two distinct genetic mechanisms, affecting number and length of vertebrae, and suggest that these morphological changes—either independently or together—are adaptive.
Indoor Localization Service Based on Hybrid Fingerprint Map

Indoor localization service based on magnetic field attracts increasing attention in the field of mobile computing in recent years. However, most of existing indoor localization methods based on magnetic field usually require the pedestrians to be equipped with a unified localization device, or take the magnetic value as the only characteristic of an indoor fingerprint map. Neither of these two kinds of methods could make sure that the indoor localization is ubiquitous, accurate and robust. Therefore, we propose a novel indoor hybrid fingerprint map and a robust Extended Particle Swarm Optimization Algorithm (EPSO). The proposed indoor hybrid fingerprint map is characterized by the variation trend of magnetic value and visible light intensity, which is suitable for most current smartphones that are usually integrated with the electronic compass and the light sensor. EPSO can correct not only the "data drifting" problem of sensors but also the logic error of localization called "wall crash". In addition, EPSO is still able to provide a high and robust localization accuracy when the attitude of smartphone is changed. Finally, we conduct a series of experiments and the experimental results show that EPSO is robust and it can achieve an accuracy within 1.7 m in the case of 80% localization errors.
The Effects of Enriched Environmental Intervention on the Parturition Outcome and Filial Health of Pregnant Mice With Chronic Pain

Chronic pain (CP) adversely impacts people’s health. However, the influence of CP on pregnant women and their fetuses remains unclear. Few reasonable interventions have been offered to these women. This study aimed to examine the effects of enriched environmental intervention (EEI) on the delivery outcome and offspring health of pregnant mice with CP. Forty pregnant mice were equally and randomly divided into four groups (control, sham, CP, and CP + EEI). Monoarthritis was induced by subcutaneous injection of the complete Freund’s adjuvant (100 μg/100 μl) into the left hind paw of mice on Day 0 of gestation. Sham mice received 100 µl of sterile phosphate-buffered saline subcutaneously. General health status and delivery outcomes of pregnant mice and general physical status, growth, and development of offspring were observed and compared between groups. CP mice exhibited less weight gain, higher rate of premature delivery, smaller litter size, lower live birth rate, lower filial birth weight, shorter filial tail length, and lower filial rates of achieving righting reflex and crawling compared to mice in the control/sham/CP + EEI groups. There were no significant differences between mice in the CP + EEI group and those in the control and sham groups. CP during pregnancy led to serious adverse impacts on both the mother and fetus mice in this study, and EEI was an effective treatment for these effects.
A Structural Approach to Offline Signature Verification Using Graph Edit Distance

Graphs provide a powerful representation formalism for handwritten signatures, capturing local properties as well as their relations. Yet, although introduced early for signature verification, only a few current systems rely on graph-based representations. A possible reason is the high computational complexity involved for matching two general graphs. In this paper, we introduce a novel structural approach to offline signature verification using an efficient cubic-time approximation of graph edit distance. We put forward several ways of creating, normalizing, and comparing signature graphs built from keypoints and investigate their performance on three benchmark datasets. The experiments demonstrate a promising performance of the proposed structural approach when compared with the state of the art.
Reconfigurable Support Vector Machine Classifier with Approximate Computing

Support Vector Machine (SVM) is one of the most popular machine learning algorithms. An energy-efficient SVM classifier is proposed in this paper, where approximate computing is utilized to reduce energy consumption and silicon area. A hardware architecture with reconfigurable kernels and overflow-resilient limiter is presented. For different applications, different kernels can be chosen and configured to achieve the optimum energy efficiency while achieving the performance requirement. For an epileptic seizure detection application, on average, 15% energy and 14% area savings are achieved with the proposed approximate SVM classifier compared to a fully-accurate SVM implementation with almost no accuracy degradation.
Anomalous Effect on the Phononic Thermal Conductivity of Silicene Nanoribbon by Hydrogenation

Silicene is a two-dimensional (2D) allotrope of silicon known to have a lower thermal conductivity than graphene; thus, more suitable for thermoelectric applications. This paper investigates the effect of hydrogenation on the thermal conductivity of silicene nanoribbon (SiNR) using equilibrium molecular dynamics (EMD) simulations. The simulations were carried out in Large-scale Atomic/Molecular Massively Parallel Simulator (LAMMPS) using a modified Tersoff potential that considers both Si-Si and Si-H interactions. The thermal conductivity of fully hydrogenated silicene nanoribbon (H-SiNR), also known as silicane nanoribbon, was found to be higher than that of pristine SiNR in all the temperatures and dimensions considered here. This anomalous enhancement in the thermal conductivity is similar to that found in hydrogenated silicon nanowires (H-SiNWs). A mechanism for this anomalous effect has been proposed relating the hydrogenation of SiNR with the stiffening and increase of the acoustic out-of-plane flexural (ZA) phonon modes. Also, for both SiNR and H-SiNR, the thermal conductivities generally increase as the dimensions are increased while they generally decrease as the temperatures are increased, in agreement to other reports.
Seflow: Efficient Flow Scheduling for Data-Parallel Jobs

Data-parallel jobs transfer massive amounts of data between a series of successive stages. The coflow abstraction is proposed to represent a group of parallel flows between two stages and efficiently improves stage-level performance. However, state-of-the-art coflow scheduling techniques are agnostic to the jobs' inter-coflow semantics and thus are suboptimal in reducing the average job completion times (JCT). To address this problem, in this paper we present the "semantic flow" (seflow) abstraction to express the job-level intercoflow semantics. A seflow comprises not only all the coflows of a job but also the relationship between the coflows. We design an efficient seflow scheduler which utilizes the rich seflow semantics of jobs to achieve better performance than seflow-agnostic scheduling for data-parallel jobs.
RRT* Combined with GVO for Real-Time Nonholonomic Robot Navigation in Dynamic Environment

Challenges persist in nonholonomic robot navigation in dynamic environments. This paper presents a framework for such navigation based on the model of generalized velocity obstacles (GVO). The idea of velocity obstacles has been well studied and developed for obstacle avoidance since being proposed in 1998. Though it has been proved to be successful, most studies have assumed equations of motion to be linear, which limits their application to holonomic robots. In addition, more attention has been paid to the immediate reaction of robots, while advance planning has been neglected. By applying the GVO model to differential drive robots and by combining it with RRT*, we reduce the uncertainty of the robot trajectory, thus further reducing the range of concern, and save both computation time and running time. By introducing uncertainty for the dynamic obstacles with a Kalman filter, we dilute the risk of considering the obstacles as uniformly moving along a straight line and guarantee the safety. Special concern is given to path generation, including curvature check, making the generated path feasible for nonholonomic robots. We experimentally demonstrate the feasibility of the framework.
Enabling Wide Area Data Analytics with Collaborative Distributed Processing Pipelines (CDPPs)

Life without the Internet is no longer possible nor thinkable. Consider the effects of a prolonged Internet outage: In the least impactful way, most of our kids and peers just would no longer be able to interact with their peers. They might severely miss out on the quality of their leisure time activities which increasingly relies on social networks, online games, YouTube, and other online entertainment offers. This may be a nuisance but still is tolerable. More seriously and economically relevant, manufacturing and trade would no longer work as all interactions inside and among companies rely on a working Internet. Indeed, just-in-time ordering mechanisms and Internet of Things-enhanced production chains within the Industry 4.0 framework would no longer be operational as old-style communication means such as phone and faxes have completely been replaced. Indeed, neither of these alternative mechanisms—faxes, phone, and also messaging—would be available either as they also rely on Internet technology. Even worse, the control of critical infrastructures would also be affected severely as they increasingly rely on the Internet for gathering input data and propagating control information. Moreover, all big data analytic applications, including financial transactions, would fail as they can no longer gather and process their input data. Even worse, the fact that there is “no communication without energy” nowadays also means that the reciprocal statement applies that there is no “energy without communication. ”
Field-Based Evidence of Single and Few Doses of Annual Ivermectin Treatment Efficacy in Eliminating Skin Microfilaria Load after a Decade of Intervention

Background Impact assessment of community-based ivermectin treatment control of onchocerciasis is required to determine its effectiveness. This study was conducted to evaluate geographic coverage and demographic ivermectin treatment compliance. Methods The number of village dosage were obtained from the community based distributors. Bioclinical data of participants comprising gender, age, number of treatment received from inception and dosage were obtained. Each participant was subjected to physical examination for palpable nodule and other skin clinical signs and symptoms of onchocerciasis. Visual acuity test was done using the Snellen illiterate E-chart. Eye examination was performed using touch loop and handheld ophthalmoscope. Skin snips from both iliac crests were incubated overnight at 28–32°C and emerged micrifilaria enumerated under an inverted microscope. The changes in epidemiological indices at post-decade of mass drug administration were compared with baseline data. Results Village annual ivermectin treatment doses averaged 62%, ranging between 10–100%. Individual treatment compliance rate was generally low with an average of 4 treatments and a range between 0–10. Despite variations in treatment compliance, there were significant improvements in some onchocercal morbidities. These include reduced number and severity of itching, visual impairment, papular onchodermatitis, onchocercomata (palpable nodules) and leopard skin. Ivermectin treatment halted development of new blind cases, except the case of a man who had optic nerve disease and became blind 2 years after ivermectin treatment had commenced. There was a significant overall reduction in parasite burden with very low mean skin microfilaria load of 1.7mf per skin snip and 3.7% skin mf prevalence, compared to baseline data of 17.7mf and 37.9% respectively. The palpable nodule was also drastically reduced from 14.5% to 6.4%. Outcome of this study has practically demonstrated that even a single dose ivermectin treatment is capable of clearing skin mf load on a long-term basis. This assertion is exemplified by the result obtained from Bomjock village that had taken treatment only at inception, and the prevalence rate was reduced from 70% to about 9.0% at post-decade of intervention. Conclusion It can be inferred that high demographic coverage with annual treatment doses, it is feasible to attain a shorter time (within a decade) contrary to the anticipated longer-term projection.