Miracle-dz/UniFAR-FTUs huggingface dataset:
Theranostics CRISPR/Cas9-based genome-wide screening for deubiquitinase subfamily identifies USP1 regulating MAST1-driven cisplatin-resistance in cancer cells

Background: Cisplatin is one of the frontline anticancer agents. However, development of cisplatin-resistance limits the therapeutic efficacy of cisplatin-based treatment. The expression of microtubule-associated serine/ threonine kinase 1 (MAST1) is a primary factor driving cisplatin-resistance in cancers by rewiring the MEK pathway. However, the mechanisms responsible for MAST1 regulation in conferring drug resistance is unknown. Methods: We implemented a CRISPR/Cas9-based, genome-wide, dual screening system to identify deubiquitinating enzymes (DUBs) that govern cisplatin resistance and regulate MAST1 protein level. We analyzed K48- and K63-linked polyubiquitination of MAST1 protein and mapped the interacting domain between USP1 and MAST1 by immunoprecipitation assay. The deubiquitinating effect of USP1 on MAST1 protein was validated using rescue experiments, in vitro deubiquitination assay, immunoprecipitation assays, and half-life analysis. Furthermore, USP1-knockout A549 lung cancer cells were generated to validate the deubiquitinating activity of USP1 on MAST1 abundance. The USP1-MAST1 correlation was evaluated using bioinformatics tool and in different human clinical tissues. The potential role of USP1 in regulating MAST1-mediated cisplatin resistance was confirmed using a series of in vitro and in vivo experiments. Finally, the clinical relevance of the USP1-MAST1 axis was validated by application of small-molecule inhibitors in a lung cancer xenograft model in NSG mice. Results: The CRISPR/Cas9-based dual screening system identified USP1 as a novel deubiquitinase that interacts, stabilizes, and extends the half-life of MAST1 by preventing its K48-linked polyubiquitination. The expression analysis across human clinical tissues revealed a positive correlation between USP1 and MAST1. USP1 promotes MAST1-mediated MEK1 activation as an underlying mechanism that contributes to cisplatin-resistance in cancers. Loss of USP1 led to attenuation of MAST1-mediated cisplatin-resistance both in vitro and in vivo . The combined pharmacological inhibition of USP1 and MAST1 using small-molecule inhibitors further abrogated MAST1 level and synergistically enhanced cisplatin efficacy in a mouse xenograft model. Conclusions: Overall, our study highlights the role of USP1 in the development of cisplatin resistance and uncovers the regulatory mechanism of MAST1-mediated cisplatin resistance in cancers. Co-treatment with USP1 and MAST1 inhibitors abrogated tumor growth and synergistically enhanced cisplatin efficacy, suggesting a novel alternative combinatorial therapeutic strategy that could further improve MAST1-based therapy in patients with cisplatin-resistant tumors.
Survival of biological therapeutics in psoriasis: retrospective analysis of 3-years data in a Turkish registry, PSORTAKSIS

Background/aim PSORTAKSIS is a psoriasis registry, which is used for follow-up of patients in Kayseri City Education and Research Hospital, Dermatology Clinic since 2016 in Turkey. PSORTAKSIS includes demographic data, follow-up clinical findings, laboratory output, and treatment information of patients. Here, drug survivals of biologic therapeutics (BT) according to three-year data of PSORTAKSIS will be presented. Materials and methods Drug survival of BT in PSORTAKSIS was analyzed from 2016 to March 2019. Results 158 patients (111 of them BT-naive) with psoriasis under BT were enrolled in the current study. Drug survival analysis of patients with ongoing BT (158 treatment periods) revealed mean survival time as 15.49 months for ustekinumab, 15.37 months for adalimumab, 14.00 months for etanercept, 5 months for infliximab, and 4.59 months for secukinumab. The differences between drug survivals of BT were statistically significant (log-rank test, χ2 = 79.915, p < 0.0001). Age of onset was found to be the only independent risk factor of drug survival according to regression analysis (p = 0.029). Conclusion As a conclusion, drug survival of UST was significantly higher than that of TNF-alpha inhibitors and SEC in the treatment of psoriasis. This study revealed that among predictors, age at disease onset may influence drug survival.
Psychological Profiles and Their Relevance with Temporomandibular Disorder Symptoms in Preorthodontic Patients

Background Temporomandibular disorders (TMDs) refer to a group of heterogenous musculoskeletal diseases with diverse clinical symptoms and an undetermined aetiology. The psychological profiles were closely related to the onset and treatment outcomes of TMDs. Objective To examine the relevance between psychological profiles and different symptoms of TMDs in preorthodontic patients. Methods The study was conducted among 570 preorthodontic patients. TMDs symptoms were recorded by the Diagnostic Criteria for TMD (DC/TMD) symptom questionnaire. The seven-item Generalized Anxiety Disorder Scale (GAD-7), the nine-item Patient Health Questionnaire (PHQ-9), and the Pain Catastrophizing Scale (PCS) were used for the evaluation of anxiety, depression, and pain catastrophizing levels. The relevance of three psychological profiles with TMDs and subtypes was evaluated with Spearman's rank correlation test and logistic regression analysis (P < 0.05). Results 34.56% of the enrolled preorthodontic patients were diagnosed with TMDs. Scores of GAD-7, PHQ-9, and PCS were significantly higher in the TMDs group than in the non-TMDs group. Participants with anxiety, depression, or high pain catastrophizing had a higher prevalence of both pain-related TMDs symptoms and intra-articular TMDs symptoms. The correlations among pain-related TMDs, intra-articular TMDs, and scores on the psychological scales were significant (P < 0.05). The adjusted logistic regression model revealed that anxiety, depression, and high pain catastrophizing were significant risk factors for TMDs with an odds ratio (OR) of 2.196, 1.741, and 1.601, respectively. Depression was associated with higher pain-related TMDs prevalence (OR = 2.136), while anxiety and depression were associated with higher intra-articular TMDs prevalence (OR = 2.341 and 1.473). Conclusion Anxiety, depression, and high pain catastrophizing were comorbid psychological conditions of TMDs. Depression was the top risk factor for pain-related TMDs, while anxiety rendered the highest risk for intra-articular TMDs. Inclusion of psychological assessments in preorthodontic evaluation might yield great benefits in TMDs screening.
An efficient object tracking method based on adaptive nonparametric approach

In this paper, an efficient method for object tracking based on nonparametric approach is presented. The density we estimated is based on an adaptive kernel model, which is driven by the intensity difference between the target and the background. The background-weighted histogram for statistics of feature takes into account the relevance between the target and background. What is more, this approach extends the range that is needed for searching object. The target model is updated according to the change of the object and environment. Experimental results on real image sequences demonstrate its robust performance in visual tracking and require less iteration computations when compared to other method.
Running head: Writing Explanations to a Fictitious Student Learning by Writing Explanations: Is Explaining to a Fictitious Student More Effective Than Self-Explaining? Writing Explanations to a Fictitious Student

Research demonstrated that oral explaining to a fictitious student improves learning. Whether these findings replicate in written contexts, and whether instructional explaining is more effective than other explaining strategies such as self-explaining is unclear. In two experiments, we compared written instructional explaining to written self-explaining, and also included written retrieval and a baseline control condition. In Experiment 1 ( N = 147, between-participants-design, laboratory experiment), we obtained no effect of explaining. In Experiment 2 ( N = 51, within-participants-design, field-experiment), only self-explaining was more effective than our control conditions for attaining transfer. Self-explaining was more effective than instructional explaining. A cumulating meta-analysis on students’ learning revealed a small effect of instructional explaining (conceptual knowledge: g = 0.29, transfer: g = 0.22), which was moderated by the modality of explaining (oral explaining > written explaining). These findings indicate that when students writing explanations are better off self-explaining than explaining to a fictitious student. Nevertheless, our findings suggest that if written explaining activities are implemented, self-explaining may be the better alternative than instructional explaining.
Some Types of Knowledge Used in Understanding Physics.

ABSTRACT This paper posits a cognitive model for understanding and learning physics that is an alternative to the formal deductive system. Recent findings of Fuller, Karplus, Lawson, and others are cited in arguing against using a formal deductive approach to teaching physics. The model demonstrates types of action-oriented knowledge structures as they actually exist and operate in a person, including practical knowledge, qualitative physical models, concrete mathematical models and written symbol manipulation. A major aspect of the theory is that the ability to link together structures from these different domains is crucial to understanding a topic in physics. Each of these structures is defined and examples of student learning are given to support the theory. It is stated that some links are simple associations learned by rote while others are formed when one domain assimilates and interprets a structure from another domain. Finally, the paper provides a list of five pedagogical implications derived from this theory that provide a framework for discussing some interesting pedagogical problems. (CW)
Critical phenomena in the dynamical visibility graph

We have investigated the time series by the mapping them to the complex network. We have studied the behavior of the relative number of clusters in dynamic visibility graphs near the critical value of the angle of view. Time series of different nature both artificial and experimental were numerically investigated. In all cases, the dependence of the relative number of clusters on the proximity to the critical angle of view had a power law behavior. Thus, it was shown that there is a similarity between the behavior of the relative number of clusters and the order parameter in the second-order phase transition theory and percolation theory. Each time series is characterized by its own value of the critical index - an analog of the critical index in second-order phase transition theory.
Divergence-type 2 + 1 dissipative hydrodynamics applied to heavy-ion collisions

We apply divergence-type theory (DTT) dissipative hydrodynamics to study the 2+1 space-time evolution of the fireball created in Au+Au relativistic heavy-ion collisions at {radical}(s{sub NN})=200 GeV. DTTs are exact hydrodynamic theories that do not rely on velocity gradient expansions and therefore go beyond second-order theories. We numerically solve the equations of motion of the DTT for Glauber initial conditions and compare the results with those of second-order theory based on conformal invariance (Baier-Romatschke-Son-Starinets model) and with data. We find that the charged-hadron minimum-bias elliptic flow reaches its maximum value at lower p{sub T} in the DTT, and that the DTT allows for a value of {eta}/s slightly larger than that of the BRSS. Our results show that the differences between viscous hydrodynamic formalisms are a significant source of uncertainty in the precise extraction of {eta}/s from experiments.
Relativistic Quantum Mechanics

Chapter summary 36 The aim of this chapter is to introduce a relativistic formalism which can be used to describe particles and their interactions. The emphasis is given to those elements of the formalism which can be carried on to Relativistic Quantum Fields (RQF), which underpins the theoretical framework of high energy particle physics. We begin with a brief summary of special relativity, concentrating on 4-vectors and spinors. One-particle states and their Lorentz transformations follow, leading to the Klein–Gordon and the Dirac equations for probability amplitudes; i.e. Relativistic Quantum Mechanics (RQM). Readers who want to get to RQM quickly, without studying its foundation in special relativity can skip the first sections and start reading from the section 1.3. Intrinsic problems of RQM are discussed and a region of applicability of RQM is defined. Free particle wave functions are constructed and particle interactions are described using their probability currents. A gauge symmetry is introduced to derive a particle interaction with a classical gauge field.
Progenitor neutron stars of the lightest and heaviest millisecond pulsars

The recent mass measurements of two binary millisecond pulsars, PSR J1614-2230 and PSR J0751+1807 with a mass M=1.97+/-0.04 Msun and M= 1.26 +/- 0.14 Msun, respectively, indicate a wide range of masses for such objects and possibly also a broad spectrum of masses of neutron stars born in core-collapse supernovae. Starting from the zero-age main sequence binary stage, we aim at inferring the birth masses of PSR J1614-2230 and PSR J0751+1807 by taking the differences in the evolutionary stages preceding their formation into account. Using simulations for the evolution of binary stars, we reconstruct the evolutionary tracks leading to the formation of PSR J1614-2230 and PSR J0751+1807. We analyze in detail the spin evolution due to the accretion of matter from a disk in the intermediate-mass/low-mass X-ray binary. We consider two equations of state of dense matter, one for purely nucleonic matter and the other one including a high-density softening due to the appearance of hyperons. Stationary and axisymmetric stellar configurations in general relativity are used, together with a recent magnetic torque model and observationally-motivated laws for the decay of magnetic field. The estimated birth mass of the neutron stars PSR J0751+1807 and PSR J1614-2230 could be as low as 1.0 Msun and as high as 1.9 Msun, respectively. These values depend weakly on the equation of state and the assumed model for the magnetic field and its accretion-induced decay. The masses of progenitor neutron stars of recycled pulsars span a broad interval from 1.0 Msun to 1.9 Msun. Including the effect of a slow Roche-lobe detachment phase, which could be relevant for PSR J0751+1807, would make the lower mass limit even lower. A realistic theory for core-collapse supernovae should account for this wide range of mass.
Quantum Hashing

We present a version of quantum hash function based on non-binary discrete functions. The proposed quantum procedure is"classical-quantum", that is, it takes a classical bit string as an input and produces a quantum state. The resulting function has the property of a one-way function (pre-image resistance), in addition it has the properties analogous to classical cryptographic hash second pre-image resistance and collision resistance. This function can be naturally used in a quantum digital signature protocol.
Evaluation of Antioxidant and Cytotoxic Potency of Thespesia populnea Leaf Extract

A large tree called Thespesia populnea (Malvaceae) is found in the tropical and coastal forests of India. In different parts of the plant, T. populnea has been shown to have antifertility, antibacterial, anti-inflammatory, antioxidant, purgative, and hepatoprotective properties. The goal of the current investigation was to find out how T. populnea leaves affected the HCT15 colorectal cancer cell line. All the in vitro experiments were conducted using aqueous and ethanol extracts. Thespesia populnea L. was subjected to a preliminary phytochemical study, which found the presence of alkaloids, flavonoids, saponin, tannin, proteins, anthraquinone, polyphenol, and carbohydrates in both extracts with the exception of terpenoids and glycosides. The aqueous extract had the greatest total phenolic and flavonoid content, with 168.04 mg of GAE per g, 34.22 mg per g, and 4.81 mg per g, respectively. It also exhibited the highest DPPH radical scavenging activity, at 81.82 per cent. This research demonstrated that T. populnea leaf is a potential source of antioxidants. These extracts were examined for their capacity to kill colorectal cancer cells in a test tube (HCT15). Aqueous extract has a high extractive percentage of 55.56 per cent at 100 µg/ml. All of the investigated cell lines had a dose-dependent viability inhibition from both aqueous and ethanol extract.
Frequency-domain gravitational waves from nonprecessing black-hole binaries. I. New numerical waveforms and anatomy of the signal

In this paper we discuss the anatomy of frequency-domain gravitational-wave signals from nonprecessing black-hole coalescences with the goal of constructing accurate phenomenological waveform models. We first present new numerical-relativity simulations for mass ratios up to 18, including spins. From a comparison of different post-Newtonian approximants with numerical-relativity data we select the uncalibrated SEOBNRv2 model as the most appropriate for the purpose of constructing hybrid post-Newtonian/numerical-relativity waveforms, and we discuss how we prepare time-domain and frequency-domain hybrid data sets. We then use our data together with results in the literature to calibrate simple explicit expressions for the final spin and radiated energy. Equipped with our prediction for the final state we then develop a simple and accurate merger-ringdown model based on modified Lorentzians in the gravitational-wave amplitude and phase, and we discuss a simple method to represent the low frequency signal augmenting the TaylorF2 post-Newtonian approximant with terms corresponding to higher orders in the post-Newtonian expansion. We finally discuss different options for modelling the small intermediate frequency regime between inspiral and merger ringdown. A complete phenomenological model based on the present work is presented in a companion paper [S. Khan et al., following paper, Phys. Rev. D 93 044007 (2016)].
Fast Algorithms and Efficient Statistics: Density Estimation in Large Astronomical Datasets

In this paper, we outline the use of Mixture Models in density estimation of large astronomical databases. This method of density estimation has been known in Statistics for some time but has not been implemented because of the large computational cost. Herein, we detail an implementation of the Mixture Model density estimation based on multi-resolutional KD-trees which makes this statistical technique into a computationally tractable problem. We provide the theoretical and experimental background for using a mixture model of Gaussians based on the Expectation Maximization (EM) Algorithm. Applying these analyses to simulated data sets we show that the EM algorithm - using the AIC penalized likelihood to score the fit - out-performs the best kernel density estimate of the distribution while requiring no ``fine--tuning'' of the input algorithm parameters. We find that EM can accurately recover the underlying density distribution from point processes thus providing an efficient adaptive smoothing method for astronomical source catalogs. To demonstrate the general application of this statistic to astrophysical problems we consider two cases of density estimation: the clustering of galaxies in redshift space and the clustering of stars in color space. From these data we show that EM provides an adaptive smoothing of the distribution of galaxies in redshift space (describing accurately both the small and large-scale features within the data) and a means of identifying outliers in multi-dimensional color-color space (e.g. for the identification of high redshift QSOs). Automated tools such as those based on the EM algorithm will be needed in the analysis of the next generation of astronomical catalogs (2MASS, FIRST, PLANCK, SDSS) and ultimately in in the development of the National Virtual Observatory.
Portable Infrared Reflectometer Designed and Manufactured for Evaluating Emittance in the Laboratory or in the Field

The optical properties of materials play a key role in spacecraft thermal control. In space, radiant heat transfer is the only mode of heat transfer that can reject heat from a spacecraft. One of the key properties for defining radiant heat transfer is emittance, a measure of how efficiently a surface can reject heat in comparison to a perfect black body emitter. Heat rejection occurs in the infrared region of the spectrum, nominally in the range of 2 to 25 mm. To calculate emittance, one obtains the reflectance over this spectral range, calculates spectral absorptance by difference, and then uses Kirchhoff s Law and the Stefan-Boltzmann equation to calculate emittance. A new portable infrared reflectometer, the SOC 400t, was designed and manufactured to evaluate the emittance of surfaces and coatings in the laboratory or in the field. It was developed by Surface Optics Corporation under a contract with the NASA Glenn Research Center at Lewis Field to replace the Center s aging Gier-Dunkle DB-100 infrared reflectometer. The specifications for the new instrument include a wavelength range of 2 to 25 mm; reflectance repeatability of +/-1 percent; self-calibrating, near-normal spectral reflectance measurements; a full scan measurement time of 3.5 min, a sample size of 1.27 cm (0.5 in.); a spectral resolution selectable from 4, 8, 16, or 32/cm; and optical property characterization utilizing an automatic integration to calculate total emittance in a selectable temperature range.
ournal of C osmology and A stroparticle hysics J Precision cosmology with time delay lenses: high resolution imaging requirements

Lens time delays are a powerful probe of cosmology, provided that the gravitational potential of the main deﬂector can be modeled with suﬃcient precision. Recent work has shown that this can be achieved by detailed modeling of the host galaxies of lensed quasars, which appear as “Einstein Rings” in high resolution images. The distortion of these arcs and counter-arcs, as measured over a large number of pixels, provides tight constraints on the diﬀerence between the gravitational potential between the quasar image positions, and thus on cosmology in combination with the measured time delay. We carry out a systematic exploration of the high resolution imaging required to exploit the thousands of lensed quasars that will be discovered by current and upcoming surveys with the next decade. Speciﬁcally, we simulate realistic lens systems as imaged by the Hubble Space Telescope (HST), James Webb Space Telescope (JWST), and ground based adaptive optics images taken with Keck or the Thirty Meter Telescope (TMT). We compare the performance of these pointed observations with that of images taken by the Euclid (VIS), Wide-Field Infrared Survey Telescope (WFIRST) and Large Synoptic Survey Telescope (LSST) surveys. We use as our metric the precision with which the slope γ (cid:48) of the total mass density proﬁle ρ tot ∝ r − γ (cid:48) for the main deﬂector can be measured. Ideally, we require that the statistical error on γ (cid:48) be less than 0.02, such that it is subdominant to other sources of random and systematic uncertainties. We ﬁnd that survey data will likely have suﬃcient depth and resolution to meet the target only for the brighter gravitational lens systems, comparable to those discovered by the SDSS survey. For fainter systems, that will be discovered by current and future surveys, targeted follow-up will be required. However, the exposure time required with upcoming facilitites such as JWST, the Keck Next Generation Adaptive Optics System, and TMT, will only be of order a few minutes per system, thus making the follow-up of hundreds of systems a practical and eﬃcient cosmological probe.