Miracle-dz/UniFAR-FTUs huggingface dataset:
Topoisomerase IIα C-terminal Domain Mutations and Catalytic Function

Topoisomerase IIα is a nuclear enzyme needed for dealing with topological entanglements in the DNA arising from replication and transcription. The N-terminal region and core of the protein are utilized in the catalytic cycle of the enzyme, which generates a transient double-stranded break in one segment of DNA and passes another segment through the break. The C-terminal domain is a large, intrinsically disordered region that appears to be involved in regulating the function of the enzyme both in terms of substrate selection and the level of activity of the enzyme. In a previous study, we explored eleven targeted mutations to the C-terminal domain. This present study explores six of these mutants to determine whether there are any defects in closure of the N-terminal clamp and whether an experimental compound known as a Cu(II)-thiosemicarbazone affects DNA cleavage with the mutants. Based upon our results, the mutants are able to close the N-terminal clamp, but some of the mutants that displayed the least clamp closing activity also had the lowest catalytic activity. Further, Cu-APY-ETSC did impact the ability of the enzymes to cleave DNA to similar levels as seen with the WT enzyme. These results lay the groundwork for additional analyses of the C-terminal domain and indicate the C-terminal domain regions tested did not influence the action of Cu-APY-ETSC except at the level of coordination between the two active sites.
Asymmetric light transmission effect based on an evolutionary optimized semi-Dirac cone dispersion photonic structure

Emre Bor,1,2 Mirbek Turduev,2,* Utku Görkem Yasa,1,3 Hamza Kurt,1 and Kestutis Staliunas4,5 1Department of Electrical and Electronics Engineering, TOBB University of Economics and Technology, Ankara 06560, Turkey 2Department of Electrical and Electronics Engineering, TED University, Ankara 06420, Turkey 3TÜBİTAK BİLGEM / İLTAREN Research Institute, Şehit Yzb. İlhan Tan Kışlası, Ümitköy, Ankara 06800, Turkey 4Departament de Física, Universitat Politècnica de Catalunya, Colom 11, E-08222 Terrassa, Barcelona, Spain 5Institució Catalana de Recerca i Estudis Avançats, Passeig Lluís Companys 23, E-08010 Barcelona, Spain
Exact result for mixed triple two-point correlations of velocity and velocity gradients in isotropic turbulence

ABSTRACTOn the grounds of Kolmogorov's 4/5 law analytical relations for triple two-point correlations of velocity and velocity gradients in homogeneous isotropic incompressible turbulence are derived. The corresponding correlation tensor can be expressed in terms of dissipation e, the second-order longitudinal velocity structure function and one more scalar function of distance between the points. However, some components of the tensor do not depend on . The derived analytical results are in agreement with the data obtained from direct numerical simulations. The function can be well approximated in the inertial range by a constant value that depends on the dissipation e only. The application of the obtained correlators in the turbulent transport theory is discussed.
Ribosome subunit attrition and activation of the p53–MDM4 axis dominate the response of MLL-rearranged cancer cells to WDR5 WIN site inhibition

The chromatin-associated protein WD Repeat Domain 5 (WDR5) is a promising target for cancer drug discovery, with most efforts blocking an arginine-binding cavity on the protein called the "WIN" site that tethers WDR5 to chromatin. WIN site inhibitors (WINi) are active against multiple cancer cell types in vitro, the most notable of which are those derived from MLL-rearranged (MLLr) leukemias. Peptidomimetic WINi were originally proposed to inhibit MLLr cells via dysregulation of genes connected to hematopoietic stem cell expansion. Our discovery and interrogation of small molecule WIN site inhibitors, however, revealed that they act in MLLr cell lines to suppress ribosome protein gene (RPG) transcription, induce nucleolar stress, and activate p53. Because there is no precedent for an anti-cancer strategy that specifically targets RPG expression, we took an integrated multi-omics approach to further interrogate the mechanism of action of WINi in MLLr cancer cells. We show that WINi induce depletion of the stock of ribosomes, accompanied by a broad yet modest translational choke and changes in alternative mRNA splicing that inactivate the p53 antagonist MDM4. We also show that WINi are synergistic with agents including venetoclax and BET-bromodomain inhibitors. Together, these studies reinforce the concept that WINi are a novel type of ribosome-directed anti-cancer therapy and provide a resource to support their clinical implementation in MLLr leukemias and other malignancies.
A comprehensive experimental comparison between federated and centralized learning

Purpose Federated learning is an upcoming machine learning paradigm which allows data from multiple sources to be used for training of classifiers without the data leaving the source it originally resides. This can be highly valuable for use cases such as medical research, where gathering data at a central location can be quite complicated due to privacy and legal concerns of the data. In such cases, federated learning has the potential to vastly speed up the research cycle. Although federated and central learning have been compared from a theoretical perspective, an extensive experimental comparison of performances and learning behavior still lacks. Methods We have performed a comprehensive experimental comparison between federated and centralized learning. We evaluated various classifiers on various datasets exploring influences of different sample distributions as well as different class distributions across the clients. Results The results show similar performances under a wide variety of settings between the federated and central learning strategies. Federated learning is able to deal with various imbalances in the data distributions. It is sensitive to batch effects between different datasets when they coincide with location, similar as with central learning, but this setting might go unobserved more easily. Conclusion Federated learning seems robust to various challenges such as skewed data distributions, high data dimensionality, multiclass problems and complex models. Taken together, the insights from our comparison gives much promise for applying federated learning as an alternative to sharing data.
Characterization of covalent inhibitors that disrupt the interaction between the tandem SH2 domains of SYK and FCER1G phospho-ITAM

RNA sequencing and genetic data support spleen tyrosine kinase (SYK) and high affinity immunoglobulin epsilon receptor subunit gamma (FCER1G) as putative targets to be modulated for Alzheimer’s disease (AD) therapy. FCER1G is a component of Fc receptor complexes that contain an immunoreceptor tyrosine-based activation motif (ITAM). SYK interacts with the Fc receptor by binding to doubly phosphorylated ITAM (p-ITAM) via its two tandem SH2 domains (SYK-tSH2). Interaction of the FCER1G p-ITAM with SYK-tSH2 enables SYK activation via phosphorylation. Since SYK activation is reported to exacerbate AD pathology, we hypothesized that disruption of this interaction would be beneficial for AD patients. Herein, we developed biochemical and biophysical assays to enable the discovery of small molecules that perturb the interaction between the FCER1G p-ITAM and SYK-tSH2. We identified two distinct chemotypes using a high-throughput screen (HTS) and orthogonally assessed their binding. Both chemotypes covalently modify SYK-tSH2 and inhibit its interaction with FCER1G p-ITAM.
Analyzing interaction of rhodacyanine inhibitor ‘MKT-077’ with Plasmodium falciparum HSP70 nucleotide binding domains

MKT-077 and its derivatives are rhodacyanine inhibitors that hold potential in treatment of cancer, neurodegenerative diseases and malaria. These allosteric drugs act by inhibiting the ATPase action of heat shock proteins of 70kDa (HSP70). MKT-077 accumulates in the mitochondria and displays differential activity against HSP70 homologs. The four Plasmodium falciparum HSP70s (PfHSP70) are present at various subcellular locations to perform distinct functions. In the present study, we have used bioinformatics tools to understand interactions between MKT-077 and PfHSP70s. Nature of the identified interactions is primarily hydrophobic with different PfHSP70 homologs showing variable propensity to bind MKT-077. Our molecular docking approach has helped us to predict the binding pocket and specific residues on PfHSP70s that are involved in interacting with MKT-077. Information derived from this article may form the foundation for design and development of MKT-077 based drugs against malaria.
A three dimensional transient growth and DNS analysis of 'high tail' and 'flat tail' aircraft configurations

This paper investigates the transient growth response of perturbations added to counter-rotating four vortex systems. The paper also compares the transient response of the wakes behind ‘high tail’ configuration aircraft, such as the C-17 Globemaster, with that of the wakes behind more conventional ‘flat tail’ aircraft, such as the Boeing 747-400. Transient growth is computed using the method of Barkley et al. [Int. J. Numer. Meth. Fluids 57, 1435–1458], and this is the first application of this method to multiple vortex pair systems. The study conducted found that when the perturbations found from the transient growth analysis that lead to optimal energy growth are used to perturb a four vortex system then the perturbations grow rapidly and have a significant effect on the base vortex system. It also found that when the vortex pair that simulates the vortices shed off an aircraft tail is vertically displaced, the growthrate of the perturbations is approximately double that of the ‘flat tail’ configuration in a three-dimensional direct numerical simulation.
Mode splitting induced by an arbitrarily shaped Rayleigh scatterer in a whispering-gallery microcavity

Yinglun Xu,1 Shui-Jing Tang,1,2,3 Xiao-Chong Yu,1,2 You-Ling Chen,4,* Daquan Yang,5 Qihuang Gong,1,2,3 and Yun-Feng Xiao1,2,3,† 1State Key Laboratory for Mesoscopic Physics and School of Physics, Peking University, Beijing 100871, People’s Republic of China 2Collaborative Innovation Center of Quantum Matter, Beijing 100871, People’s Republic of China 3Collaborative Innovation Center of Extreme Optics, Shanxi University, Taiyuan 030006, Shanxi, People’s Republic of China 4State Key Laboratory on Integrated Optoelectronics, Institute of Semiconductors, Chinese Academy of Sciences, Beijing 100083, China 5State Key Laboratory of Information Photonics and Optical Communications, School of Information and Communication Engineering, Beijing University of Posts and Telecommunications, Beijing 100876, China
Long-term root electrotropism reveals habituation and hysteresis

Plant roots sense many physical and chemical cues in soil, such as gravity, humidity, light and chemical gradients, and respond by redirecting their growth towards or away from the source of the stimulus. This process is called tropism. While gravitropism is the tendency to follow the gravitational field downwards, electrotropism is the alignment of growth with external electric fields and the induced ionic currents. Although root tropisms are at the core of their ability to explore large volumes of soil in search of water and nutrients, the molecular and physical mechanisms underlying most of them remain poorly understood. We have previously provided a quantitative characterization of root electrotropism in Arabidopsis (Arabidopsis thaliana) primary roots exposed for 5 hours to weak electric fields, showing that auxin asymmetric distribution is not necessary but that cytokinin biosynthesis is. Here, we extend that study showing that long-term electrotropism is characterized by a complex behavior. We describe overshoot and habituation as key traits of long-term root electrotropism in Arabidopsis and provide quantitative data about the role of past exposures in the response to electric fields (hysteresis). On the molecular side, we show that cytokinin, although necessary for root electrotropism, is not asymmetrically distributed during the bending. Overall, the data presented here represent a significant step forward towards the understanding of the molecular mechanisms regulating electrotropism in plants and provide a quantitative platform for future studies on the genetics of this and other tropisms.
More than just density: the role of egg number, food volume and container dimensions in mediating larval competition in Drosophila melanogaster

Flies of the genus Drosophila have been extensively used as model systems to study competition. Experiments using larval crowding in these species have furthered our understanding of competition ecology, stress-adaptation, density-dependent selection and population dynamics. Historically, larval competition has been induced by crowding the larvae in high density cultures, compared to low-density controls. However, recent studies have shown that two larval cultures having the same total eggs per mL food density, with different absolute quantities of eggs and food, can differ greatly in their density-specific fitness functions. Similarly, populations adapted to two types of cultures achieving the same density through different means, can also evolve different traits. Thus, it is clear that there is more to larval crowding than just eggs/food density, which has until now been the benchmark variable for quantifying larval crowding in Drosophila studies. In the current study, we explore the consequences of implementing crowding in different ways, using a three-way factorial experiment with egg number and food volume, cast into different food column heights or cylindrical vials with different diameters. We find that not just the same density, but cultures having the same egg number and food volume combination but experienced in food columns of varying height and diameter can have very different pre-adult survivorship and development times. We further propose a new variable for quantifying larval crowding – effective density, which is the density within the larval feeding band, a volume of food close to the surface, with access to air, wherein a majority of the larvae feed. We show that effective density is a much better predictor of the outcomes of competition than the popularly used total eggs/food density.
Diagnóstico nutrimental y validación de dosis de fertilización para limón persa

El bajo rendimiento promedio de 7 Mg ha–1 que obtienen aproximadamente el 70% de los productores de limon Persa (Citrus latifolia Tan.), en la region norte de Veracruz, Mexico, en comparacion con el obtenido en Florida, EE. UU. , de 21 Mg ha–1, es atribuido principalmente al manejo inadecuado de la fertilizacion de las plantaciones. Para contribuir a solucionar este problema, en un huerto localizado en el ejido Chavarrillo, municipio de Emiliano Zapata, Veracruz, se estudiaron cuatro tratamientos de fertilizacion por restitucion de nutrimentos deficientes, de acuerdo con la metodologia de Etchevers y se compararon con un testigo absoluto y una formula regional; esta ultima contenia mas del doble de nitrogeno (N) que las formulas propuestas. Los datos para los tratamientos de fertilizacion por restitucion se derivaron del analisis de suelos de la huerta y de los requerimientos nutrimentales del limon Persa y se validaron con diagnosticos foliares interpretados con los metodos DRIS y Kenworthy. Los arboles del tratamiento de la formula generada por restitucion, multiplicada por 1.5 (lo estimado en una aplicacion), tuvieron una produccion de fruta de 22.6 Mg ha–1, con diferencias significativas con relacion a los arboles testigo, con el cual se obtuvieron 14.3 Mg ha–1 de fruta. Los arboles tratados con la formula regional produjeron 16.2 Mg ha–1 de fruta. La calidad del fruto (color, diametro ecuatorial, jugo, bagazo y acidez) no fue modificada por los tratamientos estudiados. Solo la concentracion nutrimental de N y Zn en las hojas aumento en forma significativa por las formulas de restitucion
Bayesian Method in Linear Model and Constant Time Series Model Using Non-Informative Prior Under Phenology

Abstract: Climate Change is very recent topic at global level for discussion for all of us. Phenology is one of the main bioindicators to track climate change effects on ecosystem. The present study is devoted to derive results of coherent interest in the field of phenology from Bayesian point of view. In this paper we have developed the phenological probability models using linear model and constant time series model. The comparison of both the models has also been done using the concept of residual sum of square and Bayes’ factor.
Incremental Self-Organization of Spatio-Temporal Spike Pattern Detection

Brains learn new information while retaining previously acquired information. It is not known by what mechanisms synapses preserve previously stored memories while they are plastic and absorb new content. To understand how this stability-plasticity dilemma might be resolved, we investigate a one layer self-supervised neural network that incrementally learns to recognize new spatio-temporal spike patterns without overwriting existing memories. A plausible combination of Hebbian mechanisms, hetero-synaptic plasticity, and synaptic scaling enables unsupervised learning of spatio-temporal input patterns by single neurons. Acquisition of different patterns is achieved in networks where differentiation of selectivities is enforced by pre-synaptic hetero-synaptic plasticity. But only when the training spikes are both, jittered and stochastic past memories are found to persist despite ongoing learning. This input variability selects a subset of weights and drives them into a regime where synaptic scaling induces self-stabilization. Thereby our model provides a novel explanation for the stability of synapses related to preexisting contents despite ongoing plasticity, and suggests how nervous systems could incrementally learn and exploit temporally precise Poisson rate codes. Significance statement Activity-dependent changes in synaptic efficacy are thought to underlie learning. While ongoing synaptic plasticity is necessary for learning new content, it is detrimental to the traces of previously acquired memories. Here, we show how memories for spatiotemporal patterns can be protected from overwriting. A combination of biologically plausible synaptic plasticity mechanisms turns single neurons into detectors of statistically dominant input patterns. For networks, we find that memory stability is achieved when the patterns to be learned are temporally sloppy and noisy, as opposed to being frozen. This variability drives the relevant synaptic weights to large efficacies, where they become self-reinforcing and continue to support the initially learned patterns. As a result, such a network can incrementally learn one pattern after another.
Functional and anatomical connectivity predict brain stimulation’s mnemonic effects

Closed-loop direct brain stimulation is a promising tool for modulating neural activity and behavior. However, it remains unclear how to optimally target stimulation to modulate brain activity in particular brain networks that underlie particular cognitive functions. Here, we test the hypothesis that stimulation’s behavioral and physiological effects depend on the stimulation target’s anatomical and functional network properties. We delivered closed-loop stimulation as 47 neurosurgical patients studied and recalled word lists. Multivariate classifiers, trained to predict momentary lapses in memory function, triggered stimulation of the lateral temporal cortex (LTC) during the study phase of the task. We found that LTC stimulation specifically improved memory when delivered to targets near white matter pathways. Memory improvement was largest for targets near white matter that also showed high functional connectivity to the brain’s memory network. These targets also reduced low-frequency activity in this network, an established marker of successful memory encoding. These data reveal how anatomical and functional networks mediate stimulation’s behavioral and physiological effects, provide further evidence that closed-loop LTC stimulation can improve episodic memory, and suggest a method for optimizing neuromodulation through improved stimulation targeting.
Character Profile of the Higgs boson

Elementary particle physics describes and measures the properties of the smallest, most fundamental particles that make up the universe. The Standard Model of elementary particle physics provides a fundamental description of particles, their dynamics and interactions. The particles embedded into the theory are, a priori, massless, while observed particles have mass. In order to explain the origin of the elementary particle masses, the Brout-Englert-Higgs mechanism is introduced. The mechanism introduces the existence of one real scalar field, with the Higgs boson as excitation, however it does not predict its mass. To verify that the Higgs mechanism is the origin of elementary particle masses is one of the main goals of the Large Hadron Collider (LHC) programs at CERN. Higgs physics at the ATLAS detector has reached an exciting new phase of precision measurements, but the analyses are still mostly set up for conducting searches. The research shown in this thesis has provided measurements in the Higgs sector, placed limits on new physics, and, with the Analytic Lagrangian Morphing tool, opened the door for precision measurements of Higgs physics at the LHC. Searches for extensions to the standard model can also be performed with this tool. This thesis includes reinterpretations of the Run 1 results, results of the ongoing Run 2 and prospects for the full second run and the High Luminosity LHC. An exciting, interesting and productive new phase of precision measurements in Higgs physics at the ATLAS detector has started.
Direct numerical simulations of three-dimensional hypersonic flow over a flat plate with periodic holes

A numerical study is presented which investigates, through direct numerical simulation (DNS) of the Navier-Stokes equations, the main characteristics of a three-dimensional (3D) hypersonic flow at Mach 6 over a at plate with periodic pores in both the streamwise and spanwise directions. Some preliminary two-dimensional (2D) simulations have been run first, through which an initial validation of the numerical code, a grid convergence study, and a parametric study showing the sensitivity of the solution to different Reynolds numbers and wall temperatures have been performed. The method used to carry out the numerical simulations consists of a 6th-order central differencing base scheme, in conjunction with a shock-capturing symmetric 6th-order weighted-essentially-non-oscillatory (WENO) scheme, which provides higher numerical stability in the critical regions of strong gradients while minimising the numerical dissipation in smooth regions. The results show the capabilities of the code in carrying out high-resolution simulations with relatively low computational cost for the present configuration. The viscosity effects relative to a lower Reynolds number have been found to enhance fluid trapping and recirculation within the pores in the 2D case, however in the 3D case internal recirculation is enhanced at the higher Reynolds number via more influent 3D flow effects. Moreover, acoustic waves have been found to be radiated from the pore edges into the boundary layer, which are stronger at the lower Reynolds number. An increase of the radiated acoustic-field amplitude has been observed to be induced also by wall cooling. The three-dimensional characteristics of the flow nearby the pores are presented and discussed for two different Reynolds numbers.