Miracle-dz/UniFAR-FTUs huggingface dataset:
Long Noncoding RNA SSR42 Controls Staphylococcus aureus Alpha-Toxin Transcription in Response to Environmental Stimuli

Staphylococcus aureus is a major cause of life-threatening infections. The bacterium expresses alpha-toxin, a hemolysin and cytotoxin responsible for many of the pathologies of S. aureus. Alpha-toxin production is enhanced by subinhibitory concentrations of antibiotics. Here, we show that this process is dependent on the long noncoding RNA, SSR42. Further, SSR42 itself is regulated by several global regulators, thereby integrating environmental and nutritional signals that modulate hemolysis of the pathogen. ABSTRACT Staphylococcus aureus is a human pathogen causing a variety of diseases by versatile expression of a large set of virulence factors that most prominently features the cytotoxic and hemolytic pore-forming alpha-toxin. Expression of alpha-toxin is regulated by an intricate network of transcription factors. These include two-component systems sensing quorum and environmental signals as well as regulators reacting to the nutritional status of the pathogen. We previously identified the repressor of surface proteins (Rsp) as a virulence regulator. Acute cytotoxicity and hemolysis are strongly decreased in rsp mutants, which are characterized by decreased transcription of toxin genes as well as loss of transcription of a 1,232-nucleotide (nt)-long noncoding RNA (ncRNA), SSR42. Here, we show that SSR42 is the effector of Rsp in transcription regulation of the alpha-toxin gene, hla. SSR42 transcription is enhanced after exposure of S. aureus to subinhibitory concentrations of oxacillin which thus leads to an SSR42-dependent increase in hemolysis. Aside from Rsp, SSR42 transcription is under the control of additional global regulators, such as CodY, AgrA, CcpE, and σB, but is positioned upstream of the two-component system SaeRS in the regulatory cascade leading to alpha-toxin production. Thus, alpha-toxin expression depends on two long ncRNAs, SSR42 and RNAIII, which control production of the cytolytic toxin on the transcriptional and translational levels, respectively, with SSR42 as an important regulator of SaeRS-dependent S. aureus toxin production in response to environmental and metabolic signals. IMPORTANCE Staphylococcus aureus is a major cause of life-threatening infections. The bacterium expresses alpha-toxin, a hemolysin and cytotoxin responsible for many of the pathologies of S. aureus. Alpha-toxin production is enhanced by subinhibitory concentrations of antibiotics. Here, we show that this process is dependent on the long noncoding RNA, SSR42. Further, SSR42 itself is regulated by several global regulators, thereby integrating environmental and nutritional signals that modulate hemolysis of the pathogen.
Exploratory Studies Detecting Secondary Structures in Medium Resolution 3D Cryo-EM Images Using Deep Convolutional Neural Networks

Cryo-electron microscopy (cryo-EM) is an emerging biophysical technique for structural determination of protein complexes. However, accurate detection of secondary structures is still challenging when cryo-EM density maps are at medium resolutions (5-10 Å). Most of existing methods are image processing methods that do not fully utilize available images in the cryo-EM database. In this paper, we present a deep learning approach to segment secondary structure elements as helices and beta-sheets from medium-resolution density maps. The proposed 3D convolutional neural network is shown to detect secondary structure locations with an F1 score between 0.79 and 0.88 for six simulated test cases. The architecture was also applied to an experimentally-derived cryo-EM density map with good accuracy.
StreamChain: Do Blockchains Need Blocks?

Processing at block granularity and blockchains seem inseparable. The original role of blocks is to amortize the cost of cryptography (e.g., solving proof-of-work) and to make data transfers more efficient in a geo-distributed setting. While blocks are a simple and powerful tool for amortizing these costs, today in permissioned distributed ledgers, that are often neither geo-distributed, nor require proof-of-work, the benefits of operating on blocks are overshadowed by the large latencies they introduce. Our proposal is to switch the distributed ledger processing paradigm from block processing to stream transaction processing and rely on batching (i.e., block formation) only for amortizing the cost of disk accesses for commit operations. This paradigm shift enables shaving off end-to-end latencies by more than an order of magnitude and opens up new use-cases for permissioned ledgers. We demonstrate a proof-of-concept of our idea using Hyperledger Fabric, achieving end-to-end latencies of less than 10ms while maintaining relatively high throughput, namely close to 1500 tps.
Subliminal semantic number processing on smartphones

One potential method of improving the efficiency of human-computer interaction is to display information subliminally. Such information cannot be recalled consciously, but has some impact on the perceiver. However, it is not yet clear whether people can extract meaning from subliminal presentation of information in mobile contexts. We therefore explored subliminal semantic priming on smartphones. This builds on mixed evidence for subliminal priming across HCI in general, and mixed evidence for the effect of subliminal affective priming on smartphones. Our semi-controlled experiment (n=103) investigated subliminal processing of numerical information on smartphones. We found evidence that concealed transfer of information is possible to a very limited extent, but little evidence of a semantic effect. Overall, the impact is effectively negligible for practical applications. We discuss the implications of our results for real-world deployments and outline future research themes as HCI moves beyond mobile.
Feeding Stimulation Ability and Central Effects of Intraperitoneal Treatment of L-Leucine, L-Valine, and L-Proline on Amino Acid Sensing Systems in Rainbow Trout: Implication in Food Intake Control

To continue gathering knowledge on the central regulation of food intake in response to amino acids in teleost fish, using as a model rainbow trout (Oncorhynchus mykiss), we evaluated in a first experiment the feeding attractiveness of L-leucine, L-valine, and L-proline offered as an agar gel matrix. In a second experiment, we assessed the effect of intraperitoneal (IP) treatment with the same amino acids on food intake. In a third experiment, we carried out a similar IP administration of amino acids to evaluate the response of amino acid sensing mechanisms in the hypothalamus and telencephalon. Results are discussed in conjunction with an earlier study where leucine and valine were administered intracerebroventricularly (ICV). The attractiveness of amino acids does not appear to relate to their effects on food intake, at least when administrated by-passing ingestion and luminal absorption, since two attractive amino acids resulted in an anorexigenic (Leu) or no effects (Pro) on food intake while a non-attractive amino acid (Val) induced anorexigenic (IP treatment) or orexigenic (ICV treatment) responses. The effects of Leu on food intake might relate to the expression of hypothalamic neuropeptides and result from the direct activation of amino acid sensing systems. In contrast, while valine had few effects on hypothalamic amino acid sensing systems after ICV treatment, a significant amount of parameters become affected by IP treatment suggesting that the effect of Val after IP treatment is indirect. Proline had no relevant effects on amino acid sensing systems, neuropeptide expression, and food intake, which suggest that this amino acid might not have a relevant role in the homeostatic regulation of food intake through hypothalamic mechanisms. In telencephalon, the same amino acid sensing systems operating in hypothalamus appear to be present and respond to Leu and Val, but it is still unclear how they might relate to the control of food intake.
Does functional homogenization accompany taxonomic homogenization of British birds and how do biotic factors and climate affect these processes?

Abstract Environmental change has reshuffled communities often causing taxonomic homogenization rather than differentiation. Some studies suggest that this increasing similarity of species composition between communities is accompanied by an increase in similarity of trait composition—functional homogenization—although different methodologies have failed to come to any consistent conclusions. Functional homogenization could have a large effect on ecosystem functioning and stability. Here, we use the general definition of homogenization as “reduced spatial turnover over time” to compare changes in Simpson's beta diversity (taxonomic turnover) with changes in Rao's quadratic entropy beta diversity (functional turnover) in British breeding birds at three spatial scales. Using biotic and climatic variables, we identify which factors may predispose a site to homogenization. The change in turnover measures between two time periods, 20 years apart, was calculated. A null model approach was taken to identify occurrences of functional homogenization and differentiation independent of changes in taxonomic turnover. We used conditional autoregressive models fitted using integrated nested Laplace approximations to determine how environmental drivers and factors relating to species distributions affect changes in spatial turnover of species and functional diversity. The measurement of functional homogenization affects the chance of rejection of the null models, with many sites showing taxonomic homogenization unaccompanied by functional homogenization, although occurrence varies with spatial scale. At the smallest scale, while temperature‐related variables drive changes in taxonomic turnover, changes in functional turnover are associated with variation in growing degree days; however, changes in functional turnover become more difficult to predict at larger spatial scales. Our results highlight the multifactorial processes underlying taxonomic and functional homogenization and that redundancy in species traits may allow ecosystem functioning to be maintained in some areas despite changes in species composition.
Slow Recovery of Excitability Increases Ventricular Fibrillation Risk as Identified by Emulation

Purpose: Rotor stability and meandering are key mechanisms determining and sustaining cardiac fibrillation, with important implications for anti-arrhythmic drug development. However, little is yet known on how rotor dynamics are modulated by variability in cellular electrophysiology, particularly on kinetic properties of ion channel recovery. Methods: We propose a novel emulation approach, based on Gaussian process regression augmented with machine learning, for data enrichment, automatic detection, classification, and analysis of re-entrant biomarkers in cardiac tissue. More than 5,000 monodomain simulations of long-lasting arrhythmic episodes with Fenton-Karma ionic dynamics, further enriched by emulation to 80 million electrophysiological scenarios, were conducted to investigate the role of variability in ion channel densities and kinetics in modulating rotor-driven arrhythmic behavior. Results: Our methods predicted the class of excitation behavior with classification accuracy up to 96%, and emulation effectively predicted frequency, stability, and spatial biomarkers of functional re-entry. We demonstrate that the excitation wavelength interpretation of re-entrant behavior hides critical information about rotor persistence and devolution into fibrillation. In particular, whereas action potential duration directly modulates rotor frequency and meandering, critical windows of excitability are identified as the main determinants of breakup. Further novel electrophysiological insights of particular relevance for ventricular arrhythmias arise from our multivariate analysis, including the role of incomplete activation of slow inward currents in mediating tissue rate-dependence and dispersion of repolarization, and the emergence of slow recovery of excitability as a significant promoter of this mechanism of dispersion and increased arrhythmic risk. Conclusions: Our results mechanistically explain pro-arrhythmic effects of class Ic anti-arrhythmics in the ventricles despite their established role in the pharmacological management of atrial fibrillation. This is mediated by their slow recovery of excitability mode of action, promoting incomplete activation of slow inward currents and therefore increased dispersion of repolarization, given the larger influence of these currents in modulating the action potential in the ventricles compared to the atria. These results exemplify the potential of emulation techniques in elucidating novel mechanisms of arrhythmia and further application to cardiac electrophysiology.
Block Cooperation

Block-level cooperation is an endurance management technique that operates on top of error correction mechanisms to extend memory lifetimes. Once an error recovery scheme fails to recover from faults in a data block, the entire physical page associated with that block is disabled and becomes unavailable to the physical address space. To reduce the page waste caused by early block failures, other blocks can be used to support the failed block, working cooperatively to keep it alive and extend the faulty page’s lifetime. We combine the proposed technique with existing error recovery schemes, such as Error Correction Pointers (ECP) and Aegis, to increase memory lifetimes. Block cooperation is realized through metadata sharing in ECP, where one data block shares its unused metadata with another data block. When combined with Aegis, block cooperation is realized through reorganizing data layout, where blocks possessing few faults come to the aid of failed blocks, bringing them back from the dead. Our evaluation using Monte Carlo simulation shows that block cooperation at a single level (or multiple levels) on top of ECP and Aegis, boosts memory lifetimes by 28% (37%) and 8% (14%) on average, respectively. Furthermore, using trace-driven benchmark evaluation shows that lifetime boost can reach to 68% (30%) exploiting metadata sharing (or data layout reorganization).
A Solvent-Free Approach for Converting Cellulose Waste into Volatile Organic Compounds with Endophytic Fungi

Simple sugars produced from a solvent-free mechanocatalytic degradation of cellulose were evaluated for suitability as a growth medium carbon source for fungi that produce volatile organic compounds. An endophytic Hypoxylon sp. (CI-4) known to produce volatiles having potential value as fuels was initially evaluated. The growth was obtained on a medium containing the degraded cellulose as the sole carbon source, and the volatile compounds produced were largely the same as those produced from a conventional dextrose/starch diet. A second Hypoxylon sp. (BS15) was also characterized and shown to be phylogenetically divergent from any other named species. The degraded cellulose medium supported the growth of BS15, and approximately the same quantity of the volatile compounds was produced as from conventional diets. Although the major products from BS15 grown on the degraded cellulose were identical to those from dextrose, the minor products differed. Neither CI-4 or BS15 exhibited growth on cellulose that had not been degraded. The extraction of volatiles from the growth media was achieved using solid-phase extraction in order to reduce the solvent waste and more efficiently retain compounds having low vapor pressures. A comparison to more conventional liquid–liquid extraction demonstrated that, for CI-4, both methods gave similar results. The solid-phase extraction of BS15 retained a significantly larger variety of the volatile compounds than did the liquid–liquid extraction. These advances position the coupling of solvent-free cellulose conversion and endophyte metabolism as a viable strategy for the production of important hydrocarbons.
Microbiomarkers Discovery in Inflammatory Bowel Diseases using Network-Based Feature Selection

Discovery of disease biomarkers is a key step in translating advances in genomics into clinical practice. There is growing evidence that changes in gut microbial composition are associated with the onset and progression of Type 2 Diabetes (T2D), Obesity, and Inflammatory Bowel Disease (IBD). Reliable identification of the most informative features (i.e., microbes) for discriminating metagenomics samples from two or more groups (i.e., phenotypes) is a major challenge in computational metagenomics. We propose a Network-Based Biomarker Discovery (NBBD) framework for detecting disease biomarkers from metagenomics data. NBBD has two major customizable modules: i) A network inference module for inferring ecological networks from the abundances of microbial operational taxonomic units (OTUs); ii) A node importance scoring module for comparing the constructed networks for the chosen phenotypes and assigning a score to each node based on the degree to which the topological properties of the node differ across two networks. We empirically evaluated the proposed NBBD framework, using five network inference methods for inferring gut microbial networks combined with six node topological properties, on the identification of IBD biomarkers using a large dataset from a cohort of 657 and 316 IBD and healthy controls metagenomic biopsy samples, respectively. Our results show that NBBD is very competitive with some of the state-of-the-art feature selection methods including the widely used method based on random forest variable importance scores.
Free jejunal flap transfer containing multiple vascular pedicles for pharyngoesophageal reconstruction in conjunction with anterior mediastinal tracheostomy

When pharyngoesophagectomy is performed in conjunction with anterior mediastinal tracheostomy, reconstructing both the trachea and alimentary tract is extremely difficult. We developed a novel 1‐stage reconstructive procedure using a single free jejunal flap containing multiple vascular pedicles to decrease postoperative morbidity and mortality. Free jejunal flap transfer with multiple vascular pedicles could offer a viable option for reducing associated life‐threatening complications.
Snooze!: investigating the user-defined deferral of mobile notifications

Notifications on mobile devices are a prominent source of interruptions. Previous work suggests using opportune moments to deliver notifications to reduce negative effects. In this paper, we instead explore the manual deferral of notifications. We developed an Android app that allows users to "snooze" mobile notifications for a user-defined amount of time or to a user-defined point in time. Using this app, we conducted a year-long in-the-wild study with 295 active users. To complement the findings, we recruited 16 further participants who used the app for one week and subsequently interviewed them. In both studies, snoozing was mainly used to defer notifications related to people and events. The reasons for deferral were manifold, from not being able to attend notifications immediately to not wanting to. Daily routines played an important role in the deferral of notifications. Most notifications were deferred to the same day or next morning, and a deferral of more than two days was an exception. Based on our findings, we derive design implications that can inform the design of future smart notification systems.
A Novel Automatic Generation Control Method Based on the Ecological Population Cooperative Control for the Islanded Smart Grid

To achieve automatic generation control coordination in the islanded smart grid environment resulted from the increasing penetration of renewable energy, a novel ecological population cooperative control (EPCC) strategy is proposed in this paper. The proposed EPCC, based on the new win-loss criterion and the time tunnel idea, can compute the win-loss criterion accurately and converge to Nash equilibrium rapidly. Moreover, based on a multiagent system stochastic consensus game (MAS-SCG) framework, a frequent information exchange between agents (AGC units) is implemented to rapidly calculate optimal power command, which achieves the optimal cooperative control of the islanded smart grid. The PDWoLF-PHC(λ), WPH strategy (wolf pack hunting), DWoLF-PHC(λ), Q(λ)-learning, and Q-learning are implemented into the islanded smart grid model for the control performance analysis. Two case studies have been done, including the modified IEEE standard two-area load frequency control power system model and the islanded smart grid model with distributed energy and microgrids. The effectiveness, stronger robustness, and better adaptability in the islanded smart grid of the proposed method are verified. Compared with five other smart ones, EPCC can improve convergence speed than that of others by nearly 33.9%–50.1% and the qualification rate of frequency assessment effectively by 2%–64% and can reduce power generation cost.
Parklearn: creating, sharing and engaging with place-based activities for seamless mobile learning

The potential for mobile technology to support bespoke learning activities seamlessly across learning contexts has not been fully realized. We contribute insights gained from four months of field studies of place-based mobile learning in two different contexts: formal education with a primary school and informal, community-led learning with volunteers in a nearby park. For these studies we introduced ParkLearn: a platform for creating, sharing and engaging with place-based mobile learning activities through seamless learning experiences. The platform enables the creation of easily configurable learning activities that leverage the targeted learning environment and mobile devices' hardware to support situated learning. Learners' uploaded responses to activities can be viewed and shared via a website, supporting seamless follow-up classroom activities. By supporting creativity and independence for both learners and activity designers, ParkLearn promoted a sense of ownership, increased engagement in follow-up activities and supported the leveraging of physical and social communal learning resources.
Effects of assisted reproductive technologies in neonates with indications for surgery (2007-2016).

PURPOSE Recently, the number of births using assisted reproductive technologies (ART) has increased. An associated increase in the incidence of congenital malformations in babies conceived using this technology has also been reported. Therefore, we aimed to investigate the rate of malformations in babies with neonatal surgical diseases, who were conceived using ART. MATERIALS AND METHODS Between January 2007 and December 2016, 1737 patients were admitted to our hospital. We analyzed the incidence of congenital cardiac diseases, genetic anomalies, and congenital anomalies of the kidney and urinary tract (CAKUT) in neonates conceived by ART. The χ2 test and logistic regression analysis were used to assess the odds ratios (ORs) for congenital malformations. A P-value < 0.05 indicated statistical significance. RESULTS The OR for CAKUT was 16.94 for the first-birth neonates conceived using ART, [P < 0.05, AUC (area under the curve) = 0.86]. However, for non-surgery neonates, the OR for CAKUT was 5.99 (P = 0.15, AUC = 0.87), compared to 32.27 (P < 0.05, AUC = 0.93) for parallel conditions in surgery-neonates. CONCLUSION Neonates conceived using ART are prone to develop CAKUT, which will need surgical treatment. Therefore, more management is necessary for associated malformations in these babies, particularly in cases with CAKUT.