Miracle-dz/UniFAR-FTUs huggingface dataset:
Cellular toxicity of iHAP1 and DT-061 does not occur through PP2A-B56 targeting

PP2A is an abundant phosphoprotein phosphatase that acts as a tumor suppressor. For this reason, compounds able to activate PP2A are attractive anticancer agents. The small molecule compounds iHAP1 and DT-061 have recently been reported by Leonard et al. (2020) and Morita et al. (2020) in Cell to selectively stabilize specific PP2A-B56 complexes which mediate cell killing. Here, we show that this is not the case and question key findings in these papers. Through genome wide CRISPR-Cas9 screens, we uncover the biological pathways targeted by these compounds. We find that iHAP1 directly blocks microtubule assembly both in vitro and in vivo and thus acts as a microtubule poison. In contrast, DT-061 disrupts both the Golgi apparatus and the endoplasmic reticulum and we directly visualize DT-061 in cytoplasmic granules that co-localize with Golgi markers. Our work demonstrates that iHAP1 and DT-061 cannot be used for dissecting PP2A-B56 biology.
BRIEF REPORT Association between change in self-reported sugar intake and a sugar biomarker (δC) in children at increased risk for type 1 diabetes

We examined whether change in added sugar intake is associated with change in δC, a novel sugar biomarker, in thirty-nine children aged 5–10 years selected from a Colorado (USA) prospective cohort of children at increased risk for type 1 diabetes. Reported added sugar intake via FFQ and δC in erythrocytes were measured at two time points a median of 2 years apart. Change in added sugar intake was associated with change in the δC biomarker, where for every 1-g increase in added sugar intake between the two time points, there was an increase in δC of 0⋅0082 (P = 0⋅0053), independent of change in HbA1c and δN. The δC biomarker may be used as a measure of compliance in an intervention study of children under the age of 10 years who are at increased risk for type 1 diabetes, in which the goal was to reduce dietary sugar intake.
Exploring Unmet Needs from an Online Metastatic Breast Cancer Support Group: A Qualitative Study

Background and Objective: Despite the increasing treatment options for patients with metastatic breast cancer (MBC), unmet needs remain common, especially in low and middle-income countries where resources are limited and MBC patients face many challenges. They often join support groups to cope with their unmet needs. Currently, many MBC patients connect with each other via online support group in view of the constant availability of support and rapid information exchange. The objective of this study is to determine the unmet needs of women with MBC from an online support group. Material and Methods: Messages in an online support group of twenty-two MBC patients over a period of three years from August 2016 till August 2019 were thematically analyzed. Results: Three themes were generated, (1) unmet information needs (2) unmet financial needs (3) unmet support needs. Women needed information on side effects of treatment, new treatment options and availability of clinical trials. Although Malaysia has universal health care coverage, access to treatment remains a major challenge. When treatment was not available in the public hospitals, or waiting lists were too long, women were forced to seek treatment in private hospitals, incurring financial catastrophe. Insufficient private insurance and inadequate social security payments force many women to consider stopping treatment. Women felt that they were not getting support from their clinicians in the public sector, who were quick to stop active treatment and advise palliation. On the other hand, clinicians in the private sector advise expensive treatment beyond the financial capability of the patients. Women with families also face the challenge of managing their family and household in addition to coping with their illness. Conclusions: There is a need for healthcare professionals, policy makers, and civil society to better address the needs of MBC patients through patient-centered, multidisciplinary and multi-organizational collaboration.
A Novel Earwax Self-Sampling Device: A Feasibility Study

(1) Background: Earwax might provide the long-term concentration of substances that are altered in chronic diseases. Standardised earwax extraction has to be exclusively performed by clinicians. We investigated the safety, reliability, and tolerance of a novel self-sampling earwax device in comparison with a clinical method; (2) Methods: We compared the reliability between both methods in a longitudinal study. We first cleaned both ears at baseline in 37 controls. Secondly, we obtained a sample a month after by extracting earwax from the right ear with a novel self-sampling device, and from the left ear by using the clinical method. Reliability of both methods was measured by coefficients of variation; (3) Results: The weight of the baseline samples was not significantly different between ear sides. The reliability of the two methods was not significantly different. The self-extraction method removed eight times more earwax than the clinical method. The new method proved to be well tolerated; (4) Conclusions: The novel device was as reliable as the clinical method in sampling earwax. In view of its practicality, safety, tolerability and efficiency, the new method may have clinical applications at a reduced cost.
Classical and Quantum Gravity Supersymmetric AdS5 solutions of type IIB supergravity

We analyse the most general bosonic supersymmetric solutions of type IIB supergravity whose metrics are warped products of five-dimensional anti-de Sitter space (AdS5) with a five-dimensional Riemannian manifold M5. All fluxes are allowed consistent with SO(4, 2) symmetry. We show that the necessary and sufficient conditions can be phrased in terms of a local identity structure on M5. For a special class, with constant dilaton and vanishing axion, we reduce the problem to solving a second-order nonlinear ODE. We find an exact solution of the ODE which reproduces a solution first found by Pilch and Warner. A numerical analysis of the ODE reveals an additional class of local solutions giving complete metrics on S5 but with three-form flux and Killing spinors that are not globally defined. PACS numbers: 11.25. Tq, 04.65. +e
Poor Response to Checkpoint Immunotherapy in Uveal Melanoma Highlights the Persistent Need for Innovative Regional Therapy Approaches to Manage Liver Metastases

Simple Summary Uveal melanoma is a cancer that develops from melanocytes in the eye. This disease is extremely rare and has a strong predilection for liver metastasis, which has a poor long-term prognosis with overall survival of 6 months and 1 year mortality of 80%. Immunotherapy and checkpoint inhibitors have revolutionized treatment for cutaneous melanoma but have largely been proven to be ineffective in uveal melanoma. The poor response associated with systemic chemotherapy and immunotherapy approaches coupled with the fact that most metastatic disease is isolated to the liver suggests a persistent need for regional treatment approaches. Of regional therapies, hepatic perfusion continued to be associated with the best survival outcomes of up to 27 months. Additional therapies that target the unique biology of uveal melanoma are desperately needed. Until these treatments are developed and proven, isolated hepatic perfusion remains a viable treatment option. Abstract Uveal melanoma is a cancer that develops from melanocytes in the posterior uveal tract. Metastatic uveal melanoma is an extremely rare disease that has a poor long-term prognosis, limited treatment options and a strong predilection for liver metastasis. Median overall survival has been reported to be 6 months and 1 year mortality of 80%. Traditional chemotherapy used in cutaneous melanoma is ineffective in uveal cases. Surgical resection and ablation is the preferred therapy for liver metastasis but is often not feasible due to extent of disease. In this review, we will explore treatment options for liver metastases from uveal melanoma, with a focus on isolated hepatic perfusion (IHP). IHP offers an aggressive regional therapy approach that can be used in bulky unresectable disease and allows high-dose chemotherapy with melphalan to be delivered directly to the liver without systemic effects. Long-term median overall survival has been reported to be as high as 27 months. We will also highlight the poor responses associated with checkpoint inhibitors, including an overview of the biological rationale driving this lack of immunotherapy effect for this disease. The persistent failure of traditional treatments and immunotherapy suggest an ongoing need for regional surgical approaches such as IHP in this disease.
A multiparametric assessment of Prion disease

Human prion diseases are fatal neurodegenerative disorders which cause cognitive impairment and neurological deficits. Our previous studies in mice-intracerebrally inoculated with misfolded prion proteins using quantitative magnetic resonance imaging shows great promise for monitoring prion protein misfolding in vivo. However, little work has been carried out using quantitative MRS, MT and quantitative T1 and T2 during the course of the disease. Additional measures of tissue status are necessary for improving the sensitivity and specificity of clinical diagnosis as in many cases clinical forms of prion disease are commonly mistaken for other forms of dementia. Using in vivo MT significant changes were detected in cortex and thalamus of late stage prion infected when compared to control mice. To our surprise a significant increase of MTR was detected in thalamus and cortex between the group of control mice suggestive of developmental changes occurring in healthy brain. Using quantitative T2 maps significantly higher values were measured in thalamus of prion mice at all stages of the disease (T2=40msec, p=0.001) while T1was found to be significantly higher in cortex (T1=1.89sec, p= 0.0007) and hippocampus of only late stage prion mice when compared to aged-matched controls (T1=1.67sec). Using quantitative MRS significant changes were detected in glutamate (Glu) and myo-inositol (Ins) at all stages of prion disease compared with the control group. NAA, Cr, Lactate and Lipids were only found to be significantly different at early and late stages of the disease while Taurine (Tau) was only significantly increased in the asymptomatic stage without any significant change in the early and late stage of the disease. These changes in MRI and MRS signals, which precede overt clinical signs of disease, could provide insights into the pathogenesis of this disease and may enable early detection of pathology.
ε-Caprolactone polymerization using titanium complexes immobilized onto silica based materials functionalized with ionic liquids: insights into steric, electronic and support effects

Heterogeneous catalysts comprised of titanium immobilized on silica imidazolium-based systems have been synthesized for the ring opening polymerization of e-caprolactone. Titanium isopropoxide as a metallic precursor was grafted onto ionic liquid-functionalized silica surfaces or alternatively first grafted onto silica followed by reaction with 1-methyl-3-[(triethoxysilyl)propyl]imidazolium chloride. These materials have been characterized by X-ray diffraction (XRD), X-ray fluorescence (XRF), N2 adsorption–desorption, transmission electron microscopy (TEM) with microanalysis by energy-dispersive X-ray (EDX), 29Si, 13C and 49/47Ti solid-state NMR spectroscopy (MAS NMR), Fourier-transform infrared spectroscopy (FT-IR), UV-vis diffuse reflectance spectroscopy (DRUV-vis), thermogravimetric analysis (TG-DTG) and solid state electrochemical techniques. Different ionic liquid compounds have been tested with different silica supports (mesoporous silica nanoparticles, SBA-15 and high surface area silica). Thus, the effect of the ionic liquid in the chemical environment of the anchored titanium complex has been determined. In addition, the stability and reusability of the catalysts have been studied.
Changes of soil properties and input-output balance of nutrients in land-use systems following rain forest conversion in Central Sulawesi, Indonesia

Indonesia has nearly 50% of Asia’s and 10% of the worlds remaining tropical rainforest, but deforestation rates are among the highest worldwide and rainforest area is declining rapidly (FAO 2001). The most important factor for deforestation is agriculture. We wanted to study the sustainability of land-use systems in conversion areas in respect to soil fertility. We studied maize- and cacao/coffee-agroforests, which are the main non-irrigated land-use systems of the upland rainforest margin areas in Central Sulawesi. The study objective of this study were: • To quantify changes of soil properties under maize cultivation and agroforestry compared to natural forest and to measure the effect of the duration of cultivation (chronosequence). • To measure the input-output balance of nutrients in maize and agroforestry compared to natural forest. Soils were generally fertile, with high base cation saturation, cation exchange capacity and pHvalues. Carbon and nitrogen-stocks were highest in natural forest and lower in maize and agroforestry. In maize both C and N decreased with time, whereas in agroforestry they increased slightly. Maize fields had lost on average approximately 25% of the below-ground C-pool compared to natural forest. Soil bulk density was highest in agroforestry, in maize an increase was observed in time and in agroforestry it remained stable on a high level. In both managed systems Ca-saturation of CEC increased and K-saturation decreased during cultivation. We measured nutrient-input by precipitation, and output by leaching and harvest export on unfertilized maize- and agroforestry-sites. We found low nutrient input through rain, only potassium was imported in considerable amounts. Exports of Mg, Ca was mainly by leaching, whereas N and K was exported mainly by removal of crop harvest. Highest nutrient exports were found in the agroforestry system, maize was intermediate and lowest were found in the forest sites. All systems, including the forest sites, had negative balance of macronutrients, indicating open nutrient cycles on these soils even in natural forests.
Transformation of plant residues into soil organic matter : Chemical characterization of plant tissue, isolated soil fractions, and whole soils

During the stabilization of plant residues into soil humus, organic matter is transformed continuously to different chemical compounds. To obtain a better understanding of these changes, we used 13 C nuclear magnetic resonance ( 13 C NMR) and pyrolysis-field ionization mass spectrometry (Py-FIMS) to characterize plant tissue, isolated fractions, and whole surface soils and subsoils from a forest system and a maize (Zea mays L.) system. Both methods indicated that chemical components of the light fraction (LF) were similar to those in the plant material from which the LF was derived, but a lesser amount of carbohydrates and a greater amount of sterols in the LF signalled the early stages of decomposition of organic matter in soil. Accumulation of alkyl C in the maize LF was attributed to microbial structures or metabolites. Larger differences in the abundance and range of organic components were observed between the LF and sand-size fraction (SSF) of the soil under maize. The mass spectra showed that fewer lignin monomers and dimers, lipids, and alky-aromatic compounds were present in the SSF compared with the LF. Carbon-13 NMR data indicated that the SSF contained relatively lesser amounts of carbohydrates and aliphatic compounds and had a higher degree of aromaticity than the LF. Differences between the organic matter in the soils under forest and maize reflected the effects of deforestation, cultivation, and cropping to maize on soil organic matter. Carbon-13 NMR results indicated that the surface soil under maize had less O-alkyl and alkyl C but more aromatic and carboxyl C than the forest soil. In addition, Py-FIMS results indicated that lipids and sterols, which are derived from plant material, were reduced in the soil under maize. Microbial degradation of these high-molecular-weight compounds probably resulted in their transformation into polysaccharides in the soil humus. The presence of numerous N-compounds in the soils under maize was attributed to N from fertilizers that had been stabilized in heterocyclic forms.
Breakpoint detection through neural nets A feasibility study

A variety of statistical methods are available to detect sudden changes, or breakpoints, in time series when used as multi-temporal change detection technique. However, these methods are unreliable in the presence of noise. Neural nets might detect breakpoints better. These deep learning models are able to generalize and optimize well, even in the presence of noise. This research tests the feasibility of different neural net architectures to detect breakpoints in generic linear time series. Two relatively simple neural nets are proposed, combined with four different descriptions of breakpoint, and trained on synthetic data. The neural nets are tested on two datasets: On a separate synthetic dataset and on Australian rainuse-efficieny (RUE) time series, a surrogate for dryland ecosystem functioning. Some of the neural nets built performed exceptionally well on synthetic data, outperforming a benchmark statistical method with margin. The direct translation to RUE time series was less successful. The results shows great promise for the use of neural nets in change detection. A generalist change detection approach by use of neural nets is likely not optimal. Current developments in deep learning, as well as choosing the right user-case, show great promise to unlock the full potential of neural nets in time series analysis.
Daily sampling of early SARS-CoV-2 infection reveals substantial heterogeneity in infectiousness

The dynamics of SARS-CoV-2 replication and shedding in humans remain poorly understood. We captured the dynamics of infectious virus and viral RNA shedding during acute infection through daily longitudinal sampling of 60 individuals for up to 14 days. By fitting mechanistic models, we directly estimate viral reproduction and clearance rates, and overall infectiousness for each individual. Significant person-to-person variation in infectious virus shedding suggests that individual-level heterogeneity in viral dynamics contributes to superspreading. Viral genome load often peaked days earlier in saliva than in nasal swabs, indicating strong compartmentalization and suggesting that saliva may serve as a superior sampling site for early detection of infection. Viral loads and clearance kinetics of B.1. 1.7 and non-B.1. 1.7 viruses were indistinguishable, however B.1. 1.7 exhibited a significantly slower pre-peak growth rate in saliva. These results provide a high-resolution portrait of SARS-CoV-2 infection dynamics and implicate individual-level heterogeneity in infectiousness in superspreading.
Maximum Mean Discrepancy Test is Aware of Adversarial Attacks

The maximum mean discrepancy (MMD) test could in principle detect any distributional discrepancy between two datasets. However, it has been shown that the MMD test is unaware of adversarial attacks -- the MMD test failed to detect the discrepancy between natural and adversarial data. Given this phenomenon, we raise a question: are natural and adversarial data really from different distributions? The answer is affirmative -- the previous use of the MMD test on the purpose missed three key factors, and accordingly, we propose three components. Firstly, the Gaussian kernel has limited representation power, and we replace it with an effective deep kernel. Secondly, the test power of the MMD test was neglected, and we maximize it following asymptotic statistics. Finally, adversarial data may be non-independent, and we overcome this issue with the wild bootstrap. By taking care of the three factors, we verify that the MMD test is aware of adversarial attacks, which lights up a novel road for adversarial data detection based on two-sample tests.
Coupling‐based convergence assessment of some Gibbs samplers for high‐dimensional Bayesian regression with shrinkage priors

We consider Markov chain Monte Carlo (MCMC) algorithms for Bayesian high‐dimensional regression with continuous shrinkage priors. A common challenge with these algorithms is the choice of the number of iterations to perform. This is critical when each iteration is expensive, as is the case when dealing with modern data sets, such as genome‐wide association studies with thousands of rows and up to hundreds of thousands of columns. We develop coupling techniques tailored to the setting of high‐dimensional regression with shrinkage priors, which enable practical, non‐asymptotic diagnostics of convergence without relying on traceplots or long‐run asymptotics. By establishing geometric drift and minorization conditions for the algorithm under consideration, we prove that the proposed couplings have finite expected meeting time. Focusing on a class of shrinkage priors which includes the ‘Horseshoe’, we empirically demonstrate the scalability of the proposed couplings. A highlight of our findings is that less than 1000 iterations can be enough for a Gibbs sampler to reach stationarity in a regression on 100,000 covariates. The numerical results also illustrate the impact of the prior on the computational efficiency of the coupling, and suggest the use of priors where the local precisions are Half‐t distributed with degree of freedom larger than one.
The Picture of BLR in 2.5D FRADO: Dynamics and Geometry

The dynamics of the broad line region (BLR) in active galaxies is an open question; direct observational constraints suggest a predominantly Keplerian motion, with possible traces of inflow or outflow. In this paper we study in detail the physically motivated BLR model of Czerny & Hryniewicz based on the radiation pressure acting on dust at the surface layers of the accretion disk (AD). We consider here a nonhydrodynamical approach to the dynamics of the dusty cloud under the influence of radiation coming from the entire AD. We use here a realistic description of the dust opacity, and we introduce two simple geometrical models of the local shielding of the dusty cloud. We show that the radiation pressure acting on dusty clouds is strong enough to lead to dynamical outflow from the AD surface, so the BLR has a dynamical character of a (mostly failed) outflow. The dynamics strongly depends on the Eddington ratio of the source. Large Eddington ratio sources show a complex velocity field and large vertical velocities with respect to the AD surface, while for lower Eddington ratio sources vertical velocities are small and most of the emission originates close to the AD surface. Cloud dynamics thus determines the 3D geometry of the BLR.
Critical endpoint of QCD in a finite volume

We investigate the impact of finite volume and the corresponding restrictions on long-range correlations on the location of the critical endpoint in the QCD phase diagram. To this end, we employ a sophisticated combination of lattice Yang–Mills theory and a (truncated) version of Dyson– Schwinger equations in Landau gauge for 2 + 1 quark flavors that has been studied extensively in the past. In the infinite-volume limit, this system predicts a critical endpoint at moderate temperature and large chemical potential. We study this system at small and intermediate volumes and determine the dependence of the location of the critical endpoint on the boundary conditions and the volume of a three-dimensional cube with edge length L. We demonstrate that noticeable volume effects of more than five percent only occur for L . 5 fm and that volumes as large as L3 & (8 fm)3 are very close to the infinite-volume limit.