julilili42/papers huggingface dataset:
A simple 230 MHz Photodetector Based on Exfoliated WSe2 Multilayers
2023-09-21

We demonstrate 230 MHz photodetection and a switching energy of merely 27 fJ by using WSe2 multilayers and a very simple device architecture. This improvement over previous, slower WSe2 devices is enabled by systematically reducing the RC constant of the devices through decreasing the photoresistance as well as the capacitance. In contrast to MoS2, reducing the WSe2 thickness toward monolayers only weakly decreases the response time, highlighting that ultrafast photodetection is also possible with atomically thin WSe2. Our work provides new insights into the temporal limits of pure transition metal dichalcogenide photodetectors and suggests that Gigahertz photodetection with these materials should be feasible.
Inherent Fluorescence Demonstrates Immunotropic Properties for Novel Janus Kinase 3 Inhibitors
2023-09-21

There is a general question in small molecule pharmacology about how apparent compound concentrations in blood, plasma, and organs actually relate to actual amounts at the target site of a compound. In this study, we used inherently fluorescent JAK3 ligands and their macrolide conjugates to investigate the relationship between physical properties, apparent bulk concentration, and organ and subcellular distribution. In vitro uptake into immune cells suggested that much of the substance was associated with granules or organelles. Samples from murine pharmacokinetic studies were analyzed by both conventional mass spectrometry and cryofluorescence microscopy methods to show the distribution of a compound within organs and cells without artifacts of fixation. These observations confirm the uptake of granules observed in vitro. Data from macrolides carrying either a coumarin fluorophore or a JAK3 inhibitor were similar, suggesting that the distribution is directed by the properties of the larger macrolide. These data show a propensity for azalide macrolides to concentrate in the lung and gut epithelia and suggest that the plasma- or whole-blood-derived estimates of drug levels almost certainly underestimate concentrations of macrolides in the mucous membranes. Thus, their apparent efficacy at sub-bacteriostatic doses may reflect their higher levels in barrier layers.
Applying a Web-Based Training to Foster Self-Regulated Learning – Effects of an Intervention for Large Numbers of Participants
2023-09-21

Trainings on self-regulated learning (SRL) have been shown to be effective in improving both competence of self-regulated learning and objective measures of performance. However, human trainers can reach only a limited number of people at a time. Web-based trainings (WBT) could improve efficiency, as they can be distributed to potentially unlimited numbers of participants. We developed a WBT based on the process model of SRL by Schmitz and Wiese (2006) and tested it with 211 university students in a randomized control evaluation study including additional process analyses of learning diaries. Results showed that the training had significant effects on SRL knowledge, SRL behavior measured by questionnaires and diaries, as well as on self-efficacy. Time-series analyses revealed a positive linear trend in SRL for the training group but not for the control group as well as intervention effects for each of the three WBT lessons.
Inverse problem of analog gravity systems
2023-09-21

Analog gravity models of black holes and exotic compact objects provide a unique opportunity to study key properties of such systems in controlled laboratory environments. In contrast to astrophysical systems, analog gravity systems can be prepared carefully and their dynamical aspects thus investigated in unprecedented ways. While gravitational wave scattering properties of astrophysical compact objects are more connected to quasinormal modes, laboratory experiments can also access the transmission and reflection coefficients, which are otherwise mostly relevant for Hawking radiation related phenomena. In this work, we report two distinct results. First, we outline a semiclassical, nonparametric method that allows for the reconstruction of the effective perturbation potential from the knowledge of transmission and reflection coefficients for certain types of potentials in the Schrödinger wave equation admitting resonant tunneling. Second, we show how to use our method by applying it to an imperfect draining vortex, which has been suggested as an analog of extreme compact objects. Although the inverse problem is, in general, not unique, choosing physically motivated assumptions and requiring the validity of semiclassical theory, we demonstrate that the method provides efficient and accurate results.
Closed-Loop Brain Stimulation
2023-09-22

In the same way that beauty lies in the eye of the beholder, what a stimulus does to the brain is determined not simply by the nature of the stimulus but by the nature of the brain that is receiving the stimulus at that instant in time. Over the past decades, therapeutic brain stimulation has typically applied open-loop fixed protocols and has largely ignored this principle. Only recent neurotechnological advancements have enabled us to predict the nature of the brain (i.e., the electrophysiological brain state in the next instance in time) with sufficient temporal precision in the range of milliseconds using feedforward algorithms applied to electroencephalography time-series data. This allows stimulation exclusively whenever the targeted brain area is in a prespecified excitability or connectivity state. Preclinical studies have shown that repetitive stimulation during a particular brain state (e.g., high-excitability state), but not during other states, results in lasting modification (e.g., long-term potentiation) of the stimulated circuits. Here, we survey the evidence that this is also possible at the systems level of the human cortex using electroencephalography-informed transcranial magnetic stimulation. We critically discuss opportunities and difficulties in developing brain state-dependent stimulation for more effective long-term modification of pathological brain networks (e.g., in major depressive disorder) than is achievable with conventional fixed protocols. The same real-time electroencephalography-informed transcranial magnetic stimulation technology will allow closing of the loop by recording the effects of stimulation. This information may enable stimulation protocol adaptation that maximizes treatment response. This way, brain states control brain stimulation, thereby introducing a paradigm shift from open-loop to closed-loop stimulation.
Thermodynamics of Quantum Trajectories on a Quantum Computer
2023-09-22

Quantum computers have recently become available as noisy intermediate-scale quantum devices. Already these machines yield a useful environment for research on quantum systems and dynamics. Building on this opportunity, we investigate open-system dynamics that are simulated on a quantum computer by coupling a system of interest to an ancilla. After each interaction the ancilla is measured, and the sequence of measurements defines a quantum trajectory. Using a thermodynamic analogy, which identifies trajectories as microstates, we show how to bias the dynamics of the open system in order to enhance the probability of quantum trajectories with desired properties, e.g., particular measurement patterns or temporal correlations. We discuss how such a biased-generally non-Markovian-dynamics can be implemented on a unitary, gate-based quantum computer and show proof-of-principle results on the publicly accessible ibmq_jakarta machine. While our analysis is solely conducted on small systems, it highlights the challenges in controlling complex aspects of open-system dynamics on digital quantum computers.
Cluster Analysis to Explore Clinical Subphenotypes of Eosinophilic Granulomatosis With Polyangiitis
2023-09-22

Objective Previous studies suggested that distinct phenotypes of eosinophilic granulomatosis with polyangiitis (EGPA; formerly known as Churg-Strauss syndrome) could be determined by the presence or absence of antineutrophil cytoplasmic antibodies (ANCA), reflecting predominant vasculitic or eosinophilic processes, respectively. This study explored whether ANCA-based clusters or other clusters can be identified in EGPA. Methods This study used standardized data of 15 European centers for patients with EGPA fulfilling widely accepted classification criteria. We used multiple correspondence analysis, hierarchical cluster analysis, and a decision tree model. The main model included 10 clinical variables (musculoskeletal [MSK], mucocutaneous, ophthalmological, ENT, cardiovascular, pulmonary, gastrointestinal, renal, central, or peripheral neurological involvement); a second model also included ANCA results. Results The analyses included 489 patients diagnosed between 1984 and 2015. ANCA were detected in 37.2% of patients, mostly perinuclear ANCA (85.4%) and/or antimyeloperoxidase (87%). Compared with ANCA-negative patients, those with ANCA had more renal ( P &lt; 0.001) and peripheral neurological involvement ( P = 0.04), fewer cardiovascular signs ( P &lt; 0.001), and fewer biopsies with eosinophilic tissue infiltrates ( P = 0.001). The cluster analyses generated 4 (model without ANCA) and 5 clusters (model with ANCA). Both models identified 3 identical clusters of 34, 39, and 40 patients according to the presence or absence of ENT, central nervous system, and ophthalmological involvement. Peripheral neurological and cardiovascular involvement were not predictive characteristics. Conclusion Although reinforcing the known association of ANCA status with clinical manifestations, cluster analysis does not support a complete separation of EGPA in ANCA-positive and -negative subsets. Collectively, these data indicate that EGPA should be regarded as a phenotypic spectrum rather than a dichotomous disease.
Simulation-based inference for efficient identification of generative models in computational connectomics
2023-09-22

Recent advances in connectomics research enable the acquisition of increasing amounts of data about the connectivity patterns of neurons. How can we use this wealth of data to efficiently derive and test hypotheses about the principles underlying these patterns? A common approach is to simulate neuronal networks using a hypothesized wiring rule in a generative model and to compare the resulting synthetic data with empirical data. However, most wiring rules have at least some free parameters, and identifying parameters that reproduce empirical data can be challenging as it often requires manual parameter tuning. Here, we propose to use simulation-based Bayesian inference (SBI) to address this challenge. Rather than optimizing a fixed wiring rule to fit the empirical data, SBI considers many parametrizations of a rule and performs Bayesian inference to identify the parameters that are compatible with the data. It uses simulated data from multiple candidate wiring rule parameters and relies on machine learning methods to estimate a probability distribution (the ‘posterior distribution over parameters conditioned on the data’) that characterizes all data-compatible parameters. We demonstrate how to apply SBI in computational connectomics by inferring the parameters of wiring rules in an in silico model of the rat barrel cortex, given in vivo connectivity measurements. SBI identifies a wide range of wiring rule parameters that reproduce the measurements. We show how access to the posterior distribution over all data-compatible parameters allows us to analyze their relationship, revealing biologically plausible parameter interactions and enabling experimentally testable predictions. We further show how SBI can be applied to wiring rules at different spatial scales to quantitatively rule out invalid wiring hypotheses. Our approach is applicable to a wide range of generative models used in connectomics, providing a quantitative and efficient way to constrain model parameters with empirical connectivity data.
Microbiome Metabolome Integration Platform (MMIP): a web-based platform for microbiome and metabolome data integration and feature identification
2023-09-22

Abstract A microbial community maintains its ecological dynamics via metabolite crosstalk. Hence, knowledge of the metabolome, alongside its populace, would help us understand the functionality of a community and also predict how it will change in atypical conditions. Methods that employ low-cost metagenomic sequencing data can predict the metabolic potential of a community, that is, its ability to produce or utilize specific metabolites. These, in turn, can potentially serve as markers of biochemical pathways that are associated with different communities. We developed MMIP (Microbiome Metabolome Integration Platform), a web-based analytical and predictive tool that can be used to compare the taxonomic content, diversity variation and the metabolic potential between two sets of microbial communities from targeted amplicon sequencing data. MMIP is capable of highlighting statistically significant taxonomic, enzymatic and metabolic attributes as well as learning-based features associated with one group in comparison with another. Furthermore, MMIP can predict linkages among species or groups of microbes in the community, specific enzyme profiles, compounds or metabolites associated with such a group of organisms. With MMIP, we aim to provide a user-friendly, online web server for performing key microbiome-associated analyses of targeted amplicon sequencing data, predicting metabolite signature, and using learning-based linkage analysis, without the need for initial metabolomic analysis, and thereby helping in hypothesis generation.
Tumor sialylation controls effective anti-cancer immunity in breast cancer
2023-09-22

Abstract Breast cancer is the most common cancer among women. However, the use of immune checkpoint inhibitors, that have revolutionized treatment of multiple cancers, unfortunately remain largely ineffective in most breast cancer patients. Here, we report the most comprehensive glycoproteome map in breast tumor cells, pointing to a key role of sialic acid modifications in mammary cancer. Genetic and pharmacologic inhibition of sialylation repolarizes the tumor microenvironment, leading to a reduction in myeloid-derived suppressor cells and a significant increase in Tcf7 + memory and CD8 + effector T cells. Mechanistically, sialylation controls cell surface expression of MHC class I and PD-1-ligand on the tumor cells. Functionally, in vivo interference with sialylation on breast cancer cells licenses CD8 + T cells to effectively kill the tumors. In multiple immunotherapy-resistant breast tumor models, we also show that the abrogation of sialylation sensitizes to anti-PD-1 immune checkpoint therapy. We further demonstrate that hyper-sialylation occurs in over half of human breast cancers tested and correlates with poor T cell infiltration. Our results establish sialylation as a central immunoregulator in breast cancer, orchestrating multiple pathways of immune evasion. Targeting tumor sialylation licenses immunologically inert mammary tumors to be efficiently eliminated by anti-cancer immunity and sensitizes to immune checkpoint therapy.
On the Spin Dependence of Detection Times and the Nonmeasurability of Arrival Times
2023-09-22

According to a well-known principle of quantum physics, the statistics of the outcomes of any quantum experiment are governed by a Positive Operator-Valued Measure (POVM). In particular, for experiments designed to measure a specific physical quantity, like the time of a particle's first arrival at a surface, this principle establishes that if the probability distribution of that quantity does not arise from a POVM, no such experiment exists. Such is the case with the arrival time distributions proposed by Das and Dürr [arXiv:1802.07141], due to the nature of their spin dependence.
Ground Truth Validation of Sentinel-2 Data Using Mobile Wireless Ad Hoc Sensor Networks (MWSN) in Vegetation Stands
2023-09-22

Satellite-based remote sensing (RS) data are increasingly used to map and monitor local, regional, and global environmental phenomena and processes. Although the availability of RS data has improved significantly, especially in recent years, operational applications to derive value-added information products are still limited by close-range validation and verification deficits. This is mainly due to the gap between standardized and sufficiently available close-range and RS data in type, quality, and quantity. However, to ensure the best possible linkage of close-range and RS data, it makes sense to simultaneously record close-range data in addition to the availability of environmental models. This critical gap is filled by the presented mobile wireless ad hoc sensor network (MWSN) concept, which records sufficient close-range data automatically and in a standardized way, even at local and regional levels. This paper presents a field study conducted as part of the Durable Environmental Multidisciplinary Monitoring Information Network (DEMMIN), focusing on the information gained with respect to estimating the vegetation state with the help of multispectral data by simultaneous observation of an MWSN during a Sentinel-2A (S2A) overflight. Based on a cross-calibration of the two systems, a comparable spectral characteristic of the data sets could be achieved. Building upon this, an analysis of the data regarding the influence of solar altitude, test side topography and land cover, and sub-pixel heterogeneity was accomplished. In particular, variations due to spatial heterogeneity and dynamics in the diurnal cycle show to what extent such complementary measurement systems can improve the data from RS products concerning the vegetation type and atmospheric conditions.
Orientation of Cobalt-Phthalocyanines on Molybdenum disulfide: Distinguishing between Single Crystals and Small Flakes
2023-09-22

Heterostructures consisting of transition metal dichalcogenides (TMDCs) and organic molecules are currently of enormous interest for a variety of applications. Comparably weakly interacting molecules like phthalocyanines exhibit a high potential for the tuning of electronic properties of TMDCs. Knowledge of the molecular orientation is a prerequisite for the understanding of the nature and strength of the interfacial interaction. We study the molecular orientation of cobalt phthalocyanine (CoPc) and perfluorinated (CoPcF16) on both large molybdenum disulfide (MoS2) single crystals and small MoS2 flakes using synchrotron-based techniques: X-ray absorption spectroscopy (XAS) at the Co L3 edge and spectromicroscopy in a photoemission electron microscope (PEEM). We show that the orientation can be radically different on both substrates. Whereas on large crystals an almost flat-lying orientation is observed, significant tilt angles were found on smaller flakes. The orientation depends crucially on the number of MoS2 layers and/or the size of flat terraces.
Evolutionary dynamics of proteinaceous MAMPs reveals intrabacterial antagonism of plant immune perception
2023-09-22

This submission contains Extended Figures, an HTML database, and raw experimental data from "Evolutionary dynamics of proteinaceous MAMPs reveals intrabacterial antagonism of plant immune perception" by Stevens et al. See file description for more information. Preprint DOI: https://doi.org/10.1101/2023.09.21.558511 New data has been upload after manuscript revisions and the new running title is "Natural variation of immune epitopes reveals intrabacterial antagonism".
Investigation of sex differences in mutation carriers of the Dominantly Inherited Alzheimer Network
2023-09-23

Abstract INTRODUCTION Studies suggest distinct differences in the development, presentation, progression, and response to treatment of Alzheimer's disease (AD) between females and males. We investigated sex differences in cognition, neuroimaging, and fluid biomarkers in dominantly inherited AD (DIAD). METHODS Three hundred twenty‐five mutation carriers (55% female) and one hundred eighty‐six non‐carriers (58% female) of the Dominantly Inherited Alzheimer Network Observational Study were analyzed. Linear mixed models and Spearman's correlation explored cross‐sectional sex differences in cognition, cerebrospinal fluid (CSF) biomarkers, Pittsburgh compound B positron emission tomography ( 11 C‐PiB PET) and structural magnetic resonance imaging (MRI). RESULTS Female carriers performed better than males on delayed recall and processing speed despite similar hippocampal volumes. As the disease progressed, symptomatic females revealed higher increases in MRI markers of neurodegeneration and memory impairment. PiB PET and established CSF AD markers revealed no sex differences. DISCUSSION Our findings suggest an initial cognitive reserve in female carriers followed by a pronounced increase in neurodegeneration coupled with worse performance on delayed recall at later stages of DIAD.
Uncovering NOTCH1 as a Promising Target in the Treatment of MLL-Rearranged Leukemia
2023-09-23

MLL rearrangement (MLLr) is responsible for the development of acute leukemias with poor outcomes. Therefore, new therapeutic approaches are urgently needed. The NOTCH1 pathway plays a critical role in the pathogenesis of many cancers including acute leukemia. Using a CRISPR/Cas9 MLL-AF4/-AF9 translocation model, the newly developed NOTCH1 inhibitor CAD204520 with less toxic side effects allowed us to unravel the impact of NOTCH1 as a pathogenic driver and potential therapeutic target in MLLr leukemia. RNA sequencing (RNA-seq) and RT-qPCR of our MLLr model and MLLr cell lines showed the NOTCH1 pathway was overexpressed and activated. Strikingly, we confirmed this elevated expression level in leukemia patients. We also demonstrated that CAD204520 treatment of MLLr cells significantly reduces NOTCH1 and its target genes as well as NOTCH1 receptor expression. This was not observed with a comparable cytarabine treatment, indicating the specificity of the small molecule. Accordingly, treatment with CAD204520 resulted in dose-dependent reduced proliferation and viability, increased apoptosis, and the induction of cell cycle arrest via the downregulation of MLL and NOTCH1 target genes. In conclusion, our findings uncover the oncogenic relevance of the NOTCH1 pathway in MLLr leukemia. Its inhibition leads to specific anti-leukemic effects and paves the way for further evaluation in clinical settings.
Pangenome graph layout by Path-Guided Stochastic Gradient Descent
2023-09-23

Abstract Motivation The increasing availability of complete genomes demands for models to study genomic variability within entire populations. Pangenome graphs capture the full genomic similarity and diversity between multiple genomes. In order to understand them, we need to see them. For visualization, we need a human readable graph layout: A graph embedding in low (e.g. two) dimensional depictions. Due to a pangenome graph’s potential excessive size, this is a significant challenge. Results In response, we introduce a novel graph layout algorithm: the Path-Guided Stochastic Gradient Descent (PG-SGD). PG-SGD uses the genomes, represented in the pangenome graph as paths, as an embedded positional system to sample genomic distances between pairs of nodes. This avoids the quadratic cost seen in previous versions of graph drawing by Stochastic Gradient Descent (SGD). We show that our implementation efficiently computes the low dimensional layouts of gigabase-scale pangenome graphs, unveiling their biological features. Availability We integrated PG-SGD in ODGI which is released as free software under the MIT open source license. Source code is available at https://github.com/pangenome/odgi . Contact egarris5@uthsc.edu