Miracle-dz/UniFAR-FTUs huggingface dataset:
Novel epigenetic clock for fetal brain development predicts fetal epigenetic age for iPSCs and iPSC-derived neurons

Induced pluripotent stem cells (iPSCs) and their differentiated neurons (iPSC-neurons) are a widely used cellular model in the research of the central nervous system. However, it is unknown how well they capture age-associated processes, particularly given that pluripotent cells are only present during the early stages of mammalian development. Epigenetic clocks utilize coordinated age-associated changes in DNA methylation to make predictions that correlate strongly with chronological age, and is has been shown that the induction of pluripotency rejuvenates predicted epigenetic age. As existing clocks are not optimized for the study of brain development, to investigate more precisely the epigenetic age of iPSCs and iPSC-neurons, here, we establish the fetal brain clock (FBC), a bespoke epigenetic clock trained in prenatal neurodevelopmental samples. Our data show that the FBC outperforms other established epigenetic clocks in predicting the age of fetal brain samples. We then applied the FBC to DNA methylation data of cellular datasets that have profiled iPSCs and iPSC-derived neuronal precursor cells and neurons and find that these cell types are characterized by a fetal epigenetic age. Furthermore, while differentiation from iPSCs to neurons significantly increases the epigenetic age, iPSC-neurons are still predicted as having fetal epigenetic age. Together our findings reiterate the need for better understanding of the limitations of existing epigenetic clocks for answering biological research questions and highlight a potential limitation of iPSC-neurons as a cellular model for the research of age-related diseases as they might not fully recapitulate an aged phenotype.
Stability of ripple events during task engagement in human hippocampus

Periods of cognitive disengagement, such as rest or sleep, are thought to support the progressive consolidation of episodic memories. During these states, the hippocampus displays transient high-frequency oscillatory bursts, known as ripples, which are thought to promote interactions with the neocortex, consolidating memory traces. More recent findings have suggested ripples in the human hippocampus may also occur during task engagement, particularly for tasks requiring episodic memory processes. However, it is unclear if hippocampal ripples occur during other cognitive states or whether ripple properties are modulated by specific types of task demands. In addition, identifying genuine hippocampal ripple events in the human brain can be methodological challenging. To address these questions, we used intracranial recordings from the human hippocampus to quantify ripple events across perceptual, memory and resting task states. Using spectro-temporal identification of hippocampal ripples, we observed highly similar ripple event properties across tasks, with a modest yet significant increase in ripple properties (rate, duration & amplitude) during resting task states. These ripple event attributes did not differ between hemisphere, nor across or within the time of day examined. Supporting data further highlighted that while hippocampal ripples occurred during all task states, these rates were typically lower than that observed during sleep. Together, these findings highlight that hippocampal ripples occur consistently, but sparsely, during a broad range of cognitive task states. Such findings may be incorporated into existing models of systems consolidation, whereby hippocampal ripples help to initially establish latent memory traces.
An Intelligent Learning Environment for Computational Thinking

In this work, we present a novel intelligent environment for learning the core concepts of Computational Thinking. This learning environment can recognize learning-centered emotions presented by the students, performing different interventions automatically, depending on the students’ affective states. Tests were conducted to compare learning gain, and additionally, an acceptance technology model was applied to validate the students’ acceptance of this learning tool. During the cognitive evaluation, a control group had an average increase in score of MD = . 636 while an experimental group reported an increase of MD = . 772, which indicate a greater gain in knowledge for the experimental group. During the experiment, the system inferred a total of 2,139 emotions from the students. 56.66% of these emotions were in the categories of committed and interested, 42.22% belonged to excited and concentrated, and only 1.22% of the values were in the category of bored.
Cooperative spectrum sensing optimal threshold selection in cognitive radio networks

In this article, an optimal threshold level value to improve spectrum sensing performance that satisfies minimum error probability is derived. Determining the threshold level to minimize sensing error with the minimum number of samples required can improve the detection performance, thus resulting in enhanced spectrum usage. A closed‐form expression for the optimal threshold level is derived, and further simplified by using the sensing error function along with the optimal weights and transmit powers to the decision‐making fusion center. Numerical results are provided and show improved sensing performance compared to conventional schemes.
Determination of minimum inhibitory concentration (MIC) and minimum bactericidal concentration (MBC) using a novel dilution tube method

A novel ‘dilution tube method’ (DTM) which is a modification of the ‘dilution method’ (DM) is hereby described for the determination of minimum inhibitory concentration (MIC) and minimum bactericidal concentration (MBC). This new DTM uses only broth medium in tubes and the required antibiotic. MIC and MBC for Escherichia coli, Klebsiella pneumoniae and Staphylococcus aureus were determined in tubes by double diluting (or higher dilutions), broths containing gentamicin concentrations that inhibit bacterial growth, and incubating at 37°C for 18 to 24 h. The tube for MIC showed growth and appeared turbid after incubation while that for MBC remained clear. The results obtained using DTM agrees completely with those obtained with DM. The advantages of this novel DTM include the elimination of extra stress, time and costs associated with preparing and inoculating agar medium as done in DM. Key words: Antibiotics, minimum inhibitory concentration, minimum bactericidal concentration, dilution tube method, dilution method.
Graph Analytics on Proximity Data to Fight Contagion

As social distancing has become the new normal, it is eminent for enterprises and administrations to make decisions based on analytics on human proximity data Graph Analytics can serve as an essential technology to understand human network behaviors and contact tracing inferences in pandemic and post-pandemic scenarios A large amount of work has happened on epidemiology of pandemics However, a formal application of graph analytics backed by visualization and mapping of graph algorithms has remained neglected in pandemic scenarios This paper has addressed this important need backed by graph modeling, methods and analytics © 2020 CEUR-WS All rights reserved
Modeling Knowledge Change Behaviors in Learning-related Tasks

In Search as Learning (SAL) research, when and how learning occurs during the search process has been a focus that attracts research attention. The goal of this study is to explore and characterize searchers’ knowledge change patterns in the context of learning-related tasks from a process perspective. A user experiment was conducted, and participants were asked to search for two learning-related search tasks in a laboratory environment, and draw mind maps before and during search to keep a record of what they know about the task. Searchers’ knowledge change behaviors during the search process were extracted from their mind maps and analyzed based on the "Actions-Tactics-Strategies (ATS)" research path. In this study, we report current preliminary analysis, which discovered twenty-five types of knowledge change actions, and identified eight types of knowledge change tactics using bottom-up clustering methods. The findings are the basis for our further exploration of searchers’ learning strategies during the whole session, also present a complete behavioral and cognitive picture of searchers’ knowledge change process, for search systems providing assistance at different stages of searching and learning.
Digital Humanities and Natural Language Processing: "Je t'aime... Moi non plus"

In spite of the increasingly large textual datasets humanities researchers are confronted with, and the need for automatic tools to extract information from them, we observe a lack of communication and diverging goals between the communities of Natural Language Processing (NLP) and Digital Humanities (DH). This contrasts with the wealth of potential opportunities that could arise from closer collaborations. We argue that more efforts are needed to make NLP tools work for DH datasets so that that NLP research applied to humanities data receives more attention, leading to the development of evaluation approaches tailored towards relevant research questions. This has the potential to bring methodological advances to NLP, while at the same time confronting DH datasets with powerful state-of-the-art techniques.
Analytical evaluation and critical appraisal of early commercial SARS-CoV-2 immunoassays for routine use in a diagnostic laboratory

ABSTRACT Background: The objective of this study was to evaluate the performance characteristics of early commercial SARS-CoV-2 antibody assays in mild and asymptomatic subjects to enable the selection of suitable immunoassays for routine diagnostic use. Methods: We used serum samples from a pre-COVID era patient cohort (n = 50, pre-December 2019), designated SARS-CoV-2 negative, and serum samples from a SARS-CoV-2 RT-PCR-positive cohort (n = 90) taken > 14 days post-symptom onset (April–May 2020). Six ELISA assays were evaluated, including one confirmation assay to investigate antibody specificity. We also evaluated one point-of-care lateral flow device (LFIA) and one high throughput electrochemiluminescence immunoassay (CLIA). Results: The ELISA specificities ranged from 84% to 100%, with sensitivities ranging from 75.3% to 90.0%. The LFIA showed 100% specificity and 80% sensitivity using smaller sample numbers. The Roche CLIA immunoassay showed 100% specificity and 90.7% sensitivity. When used in conjunction, the Euroimmun nucleocapsid (NC) and spike-1 (S1) IgG ELISA assays had a sensitivity of 95.6%. The confirmation Dia.Pro IgG assay showed 92.6% of samples tested contained both NC and S1 antibodies, 32.7% had NC, S1 and S2 and 0% had either S1 or S2 only. Conclusions: The Roche assay and the Euroimmun NC and S1 assays had the best sensitivity overall. Combining the assays detecting NC and S1/S2 antibody increased diagnostic yield. These first-generation assays were not calibrated against reference material and the results were reported qualitatively. A portfolio of next-generation SARS-CoV-2 immunoassays will be necessary to investigate herd and vaccine-induced immunity.
FINDING TYPICAL TESTORS BY USING AN EVOLUTIONARY STRATEGY

The concept of testors appeared in the middle of the fifties. Testors and particularly typical testors, have been used in feature selection and supervised classification problems. Deterministic algorithms have usually been used to find typical testors. In this paper a new approach to find typical testors of a basic matrix is described. This approach is based on the application of the Univariate Marginal Distribution Algorithm as the kernel of an optimization strategy. The behavior of this algorithm is at least as well as the simple Genetic Algorithms with uniform crossover for the same kind of problems, but it is simpler and less costly in computational terms. Several experiments confirm the validity of this approach.
ENTIRE MULTIVARIATE VECTOR-VALUED FUNCTIONS OF BOUNDED L-INDEX: ANALOG OF FRICKE’S THEOREM

V. P. Baksa, A. I. Bandura. Entire multivariate vector-valued functions of bounded L-index: analog of Fricke’s theorem, Mat. Stud. 54 (2020), 56–63. We consider a class of vector-valued entire functions F : C → C. For this class of functions there is introduced a concept of boundedness of L-index in joint variables. Let | · |p be a norm in C. Let L(z) = (l1(z), . , ln(z)), where lj(z) : C → R+ is a positive continuous function. An entire vector-valued function F : C → C is said to be of bounded L-index (in joint variables), if there exists n0 ∈ Z+ such that
Recursive Active Control for Controlling Chaos in Nonlinear Bloch Equations

The problem of chaos control in the nonlinear Bloch equations is considerd based on a new control technique. The new control technique combines a recursive approach and active control mechanism to design control functions that suppresses chaotic behaviours in nonlinear Bloch equations. The effeciency of the proposed Recursive Active Control (RAC) is demonstrated with numerical simulations.
Optimization of Growth Temperature Conditions for the Production of Heterologous and Homologous Membrane Proteins In anaerobic photoheterotrophic Rhodobacter sphaeroides

We describe the use of fluorescent protein fusions as a method for optimizing and accurately quantifying membrane protein expression in Rhodobacter. Membrane proteins (MP) are a difficult class of proteins to study; however, their medical and biotechnical importance makes them compelling to address the associated challenges. Difficulties of expressing membrane proteins have been reported in number of other protein expression systems such as Escherichia coli, yeast and mammalian cell culture. The anaerobic photoheterotroph, Rhodobacter sphaeroides, has the desirable characteristic of large quantities of intracellular membranes (typically absent in prokaryotes) as a result of the need to assemble the photosynthetic apparatus which facilitates ATP formation in light, without oxygen formation. The genetic engineering strategy focused on the use of the natural photosynthetic expression machinery to drive expression of the MP of interest in Rhodobacter sphaeroides. Anaerobic photoheterotrophic growth can be implemented in anaerobic photobioreactors where it has been previously proven to achieve biomass yields of more than 9.2 grams cells dry weight per liter (gDW/L) have been achieved. The expression of homologous and heterologous proteins was studied using fluorescent fusion tags and optimized with respect to temperature. The homologous water-transport membrane protein Aquaporin Z (rAqpZ) and heterologous human kidney Aquaporin 9 (human AQP9) and human Ocluddin (human OCLN) were successfully expressed in the Rhodobacter. Expression levels were quantified by monitoring sample fluorescence and Western Blot densitometry (WBD) of Monomeric Banana YFP (mBanana). Correlations between off-line sampled culture fluorescence and WBD were
The Relationship Between School Turnaround and Student Outcomes: A Meta-Analysis

School turnaround has emerged as a predominant strategy to improve chronically low-performing schools, although the approach remains controversial. This meta-analysis synthesizes results from 35 studies to examine the relationship between school turnaround and various student outcomes. We find that school turnaround is associated with improved attendance, standardized test scores, and graduation rates. When separating the results by the different turnaround models, transformation, turnaround, and restart models are associated with improvements in student test scores. We find no evidence of a significant relationship between school closure or state turnaround conducted under No Child Left Behind (NCLB) waivers and student test scores. We describe how changes in organizational operations, human capital, and the governance and/or management of low-performing schools might have contributed to this observed relationship.
Probing Mechanical Flexibility and Discrete Stepping of an Ultra-Fast Ring ATPase - eScholarship

DNA translocation is a fundamental process in biology, required for essential cellular processes including recombination, replication, and chromosome segregation. The SpoIIIE motor is a homo-hexameric dsDNA translocase, part of the ASCE [Additional Strand Conserved E (glutamate)] superfamily of oligomeric ring NTPases. SpoIIIE is found in the bacterium Bacillus subtilis, its biological role is to actively translocate DNA to ensure the proper segregation of sister chromatids. SpoIIIE accomplishes this task by coupling the chemical energy provided by ATP to generate mechanical work, pumping the DNA across a cellular membrane at a rate of 4 kbp/s. While generating mechanical work is a common function of ring NTPases, the timing and order of individual power strokes applies this work in a nuanced manner to better suit particular biological tasks. Understanding the mechanical aspects of fast DNA translocation provides a unique insight into the diverse mechanical strategies employed by these large class of ring NTPases. Using single-molecule optical trapping techniques, I present real-time measurements of SpoIIIE DNA translocation. By challenging the motor with different lengths of modified DNA substrates, I have determined that SpoIIIE makes critical phosphate contacts with the DNA backbone during translocation and characterized the periodicity of motor-DNA interactions, suggesting a fundamental step size of 2 bp. Furthermore, velocity dependence on an applied external load and various concentrations of ATP, ADP and Pi have demonstrated that translocation is coupled to phosphate release. Finally, ATP analogue experiments are presenting an emerging model of a unique, partially coordinated mechanism of hydrolysis between the individual subunits of SpoIIIE.
Facilitating Flexible Force Feedback Design with Feelix

In the last decade, haptic actuators have improved in quality and efficiency, enabling easier implementation in user interfaces. One of the next steps towards a mature haptics field is a larger and more diverse toolset that enables designers and novices to explore with the design and implementation of haptic feedback in their projects. In this paper, we look at several design projects that utilize haptic force feedback to aid interaction between the user and product. We analysed the process interaction designers went through when developing their haptic user interfaces. Based on our insights, we identified requirements for a haptic force feedback authoring tool. We discuss how these requirements are addressed by 'Feelix', a tool that supports sketching and refinement of haptic force feedback effects.
Viscoelastic testing in liver transplantation

Despite the lack of large randomized clinical studies, viscoelastic tests (VETs) have been a critical armamentarium for hemostatic control in liver transplantation (LT) since the 1960s. Many transplant institutions have adopted VETs in their clinical practice. Several small‐size randomized clinical trials on LT patients have suggested that VET‐guided hemostatic treatment algorithms have led to decreased indications for and amounts of transfused blood products, especially fresh‐frozen plasma, compared to standard laboratory‐based hemostatic management. VETs have also been reported to offer insight into the diagnosis and prediction of LT patients' development of hypercoagulability‐related morbidity and mortality. There is still a need for VET device–specific hemostatic algorithms in LT, and clinicians must take into account the tendency to underestimate the coagulation capacity of VETs in patients with end‐stage liver disease where hemostasis is rebalanced.
An immunochemistry-based screen for chemical inhibitors of DNA-protein interactions and its application to human CGGBP1

Background Inhibition of DNA-binding of proteins by small-molecule chemicals holds immense potential in manipulating the activities of DNA-binding proteins. Such a chemical inhibition of DNA-binding of proteins can be used to modulate processes such as replication, transcription, DNA repair and maintenance of epigenetic states. This prospect is currently challenged with the absence of robust and generic protocols to identify DNA-protein interactions. Additionally, much of the current approaches to designing inhibitors requires structural information of the target proteins. Methods We have developed a simple dot blot and immunodetection-based assay to screen chemical libraries for inhibitors of DNA-protein interactions. The assay has been applied to a library of 1685 FDA-approved chemicals to discover inhibitors of CGGBP1, a multifunctional DNA-binding protein with no known structure. Additional in vitro and in cellulo assays have been performed to verify and supplement the findings of the screen. Results Our primary screen has identified multiple inhibitors of direct or indirect interactions between CGGBP1 and genomic DNA. Of these, one inhibitor, Givinostat, was found to inhibit direct DNA-binding of CGGBP1 in the secondary screen using purified recombinant protein as the target. DNA and chromatin immunoprecipitation assays reinforced the findings of the screen that Givinostat inhibits CGGBP1-DNA binding. Conclusions The assay we have described successfully identifies verifiable inhibitors of DNA-binding of protein; in this example, the human CGGBP1. This assay is customizable for a wide range of targets for which primary antibodies are available. It works with different sources of the target protein, cell lysates or purified recombinant preparations and does not require special equipment, DNA modifications or protein structural data. This assay is scalable and highly adaptable with the potential to discover inhibitors of transcription factors with implications in cancer biology.
Spike-timing-dependent plasticity can account for aftereffects of dual-site transcranial alternating current stimulation

Background Transcranial alternating current stimulation (tACS), applied to two brain sites with different phase lags, has been shown to modulate stimulation-outlasting functional connectivity between the targeted regions. Objective Here, we test if spike-timing-dependent plasticity (STDP) can explain stimulation-outlasting connectivity modulation by dual-site tACS and explore the effects of tACS parameter choices. Methods Networks with two populations of spiking neurons were simulated. Synapses between the populations were subject to STDP. We re-analyzed resting-state EEG data to validate the model. Results Simulations showed stimulation-outlasting connectivity changes between in- and anti-phase tACS, dependent on both tACS frequency and conduction delays. Importantly, the model predicted that the largest effects would occur for short conduction delays between the stimulated regions, which agreed with experimental EEG connectivity modulation by 10 Hz tACS. Conclusion STDP can explain connectivity aftereffects of dual-site tACS. However, not all combinations of tACS frequency and application sites are expected to effectively modulate connectivity via STDP. We therefore suggest using appropriate computational models and/or EEG analysis for planning and interpretation of dualsite tACS studies relying on aftereffects.