julilili42/papers huggingface dataset:
Clinical Applications of Metabolic Models in SBML Format
2020-01-30

The diagnosis and prognosis of diseases are still a severe problem in the clinical environment. It remains challenging to find the right drug with only minimal side effects while maximizing the patient׳s outcome. The fact that individual patients respond differently to the same treatment exacerbates this situation. For these reasons, it has become increasingly important to look at the intracellular environment. This intricate biological system with thousands of interactions is too complex to be fully comprehended. A promising way to analyze biological systems is by applying computer modeling and simulations. In many studies, such methods have successfully demonstrated their ability to describe and visualize biological behavior and complexity. Due to the increasing use of computational models in systems biology, the development of a standard model interchange language is prerequisite. A standardized modeling language enables clinicians, biologists, and bioinformaticians to exchange models between various software tools. Furthermore, incorporating clinical data into such models becomes straightforward and applicable to a wide range of analyses. The Systems Biology Markup Language (SBML) constitutes the most commonly accepted representation format. A plethora of databases provides systems biology models in SBML format for download. Various tools are available for working with these models, including editing, visualization, simulation, the de novo model construction, and more. This chapter introduces fundamental aspects of systems biology modeling in personalized medicine, including the basics of SBML and selected software applications. A use-case example of modeling glycolysis in human cancer cells concludes the discussion.
C–P vs C–H Bond Cleavage of Triphenylphosphine at Platinum(0): Mechanism of Formation, Reactivity, Redox Chemistry, and NMR Chemical Shift Calculations of a μ-Phosphanido Diplatinum(II) Platform
2020-01-30

Transition-metal phosphanides M–PR2 are key intermediates in catalytic C–P bond functionalization. M–PR2 formation from tertiary phosphines through P–C bond cleavage widens the scope beyond P–H functionalized substrates, but mechanistic understanding of this reaction still is fragmentary. Starting from a defined coordination complex has allowed monitoring the reaction of a Pt-PPh3 moiety and Pt(0) by NMR spectroscopy. Initial Pt(0) transfer is rate-limiting and leads to products from PPh3-borne ortho-C–H and C–P bond cleavage along kinetically distinct pathways. Albeit kinetically favored, the reversibility of C–H bond cleavage eventually leads to thermodynamically preferred C–P bond scission. This pathway affords a robust [Pt(μ-PPh2)Pt] core structure whose redox chemistry and reactivity toward external ligands are reported. Organometallic products have been substantiated by a combination of magnetic resonance and absorption spectroscopies, X-ray diffraction, and DFT computations.
Pre-Twin Screen - A Multi-Disciplinary Approach for a Personalized Prenatal Diagnostics and Care for Twin Pregnancies
2020-01-30

The prevalence of twin pregnancies is rising globally due to increased assisted conception and advanced maternal age in pregnancy. Twin pregnancies have 5-9 times higher frequencies of fetal chromosomal and structural abnormalities, often deliver preterm, and have high prevalence of gestational diabetes mellitus (GDM), preeclampsia (PE), and intrauterine growth restriction (IUGR) compared to singletons.
A metric on the space of neutron star models in general relativity and modified gravity
2020-01-30

Some pairs of neutron star models can intuitively be thought of as being `closer' together than others, in the sense that more precise observations might be required to distinguish between them than would be necessary for other pairs. In this paper, borrowing ideas from the study of geometrodynamics, we introduce a mathematical formalism to define a geometric distance between stellar models, to provide a quantitative meaning to this notion of closeness. In particular, it is known that the set of all metrics on a Riemannian manifold itself admits the structure of a Riemannian manifold (`configuration manifold'), which comes equipped with a canonical metric. By thinking of a stationary star as being a particular metric, the structure of which is determined through the Tolman-Oppenheimer-Volkoff relations and their generalisations, points on a suitably restricted configuration manifold can be thought of as representing different stars, and distances between these points can be computed. We develop the necessary mathematical machinery to build the configuration manifold of neutron star models, and provide some worked examples to illustrate how this space might be used in future studies of stellar structure.
Diversity and Accessibility in WeNet: Accommodating the Needs of Users with Disabilities
2020-01-30

&lt;p&gt;The WeNet project aspires to develop a social media tool to foster community social relations, particularly among student populations. Diversity is an integral part of WeNet conceptually and practically. Considering the diverse needs and preferences of users, and connecting users to benefit from each other&rsquo;s diversity, is a major goal of the WeNet research and development activities. Accordingly, we contemplate and accommodate different aspects of diversity to reach inclusive and diversity-aware technological solutions. A significant diversity aspect that is frequently ignored is disability. Visual impairment requires the most technical accommodations to enable students to use WeNet. Therefore, the focus of this paper is on how blind and visually impaired people use assistive technology, and how we can consider their needs within the WeNet framework. Thereby, we build on the social model of disability. This paper thus tackles how technical requirements should be prepared to meet the needs of the blind and visually impaired, and how we can provide equal accessibility within the WeNet proposed scenarios.&lt;/p&gt;
Correlation guided Network Integration (CoNI) reveals novel genetic regulators of hepatic metabolism
2020-01-30

ABSTRACT The steadily increasing amount of newly generated omics data of various types from genomics to metabolomics is a chance and a challenge to systems biology. To fully use its potential, one key is the meaningful integration of different types of omics. We here present a fully unsupervised and versatile correlation-based method, termed Correlation guided Network Integration (CoNI), to integrate multi-omics data into a hypergraph structure that allows for identification of effective regulators. Our approach further unravels single transcripts mapped to specific densely connected metabolic sub-graphs or pathways. By applying our method on transcriptomics and metabolomics data from murine livers under standard chow or high-fat-diet, we isolated eleven genes with a regulatory effect on hepatic metabolism. Subsequent in vitro and ex vivo experiments in human liver cells and human obtained liver biopsies validated seven candidates including INHBE and COBLL1 , to alter lipid metabolism and to correlate with diabetes related traits such as overweight, hepatic fat content and insulin resistance (HOMA-IR). Last, we successfully applied our methods to an independent data-set to confirm its versatile and transferable character.
T2 relaxation times of macromolecules and metabolites in the human brain at 9.4 T
2020-01-31

Purpose Relaxation times can contribute to spectral assignment. In this study, effective T 2 relaxation times ( ) of macromolecules are reported for gray and white matter–rich voxels in the human brain at 9.4 T. The of macromolecules are helpful to understand their behavior and the effect they have on metabolite quantification. Additionally, for absolute quantification of metabolites with magnetic resonance spectroscopy, appropriate T 2 values of metabolites must be considered. The T 2 relaxation times of metabolites are calculated after accounting for TE/sequence‐specific macromolecular baselines. Methods Macromolecular and metabolite spectra for a series of TEs were acquired at 9.4 T using double inversion–recovery metabolite‐cycled semi‐LASER and metabolite‐cycled semi‐LASER, respectively. The T 2 relaxation times were calculated by fitting the LCModel relative amplitudes of macromolecular peaks and metabolites to a mono‐exponential decay across the TE series. Furthermore, absolute concentrations of metabolites were calculated using the estimated relaxation times and internal water as reference. Results The of macromolecules are reported, which range from 13 ms to 40 ms, whereas, for metabolites, they range from 40 ms to 110 ms. Both macromolecular and metabolite T 2 relaxation times are observed to follow the decreasing trend, with increasing B 0 . The linewidths of metabolite singlets can be fully attributed to T 2 and B 0 components. However, in addition to these components, macromolecule linewidths have contributions from J‐coupling and overlapping resonances. Conclusion The T 2 relaxation times of all macromolecular and metabolite peaks at 9.4 T in vivo are reported for the first time. Metabolite relaxation times were used to calculate the absolute metabolite concentrations.
Learning to validate the quality of detected landmarks
2020-01-31

We present a new loss function for the validation of image landmarks detected\\nvia Convolutional Neural Networks (CNN). The network learns to estimate how\\naccurate its landmark estimation is. This loss function is applicable to all\\nregression-based location estimations and allows the exclusion of unreliable\\nlandmarks from further processing. In addition, we formulate a novel batch\\nbalancing approach which weights the importance of samples based on their\\nproduced loss. This is done by computing a probability distribution mapping on\\nan interval from which samples can be selected using a uniform random selection\\nscheme. We conducted experiments on the 300W, AFLW, and WFLW facial landmark\\ndatasets. In the first experiments, the influence of our batch balancing\\napproach is evaluated by comparing it against uniform sampling. In addition, we\\nevaluated the impact of the validation loss on the landmark accuracy based on\\nuniform sampling. The last experiments evaluate the correlation of the\\nvalidation signal with the landmark accuracy. All experiments were performed\\nfor all three datasets.\\n
What the Zebrafish’s Eye Tells the Zebrafish’s Brain: Retinal Ganglion Cells for Prey Capture and Colour Vision
2020-01-31

ABSTRACT In vertebrate vision, the tetrachromatic larval zebrafish permits non-invasive monitoring and manipulating of neural activity across the nervous system in vivo during ongoing behaviour. However, despite a perhaps unparalleled understanding of links between zebrafish brain circuits and visual behaviours, comparatively little is known about what their eyes send to the brain in the first place via retinal ganglion cells (RGCs). Major gaps in knowledge include any information on spectral coding, and information on potentially critical variations in RGC properties across the retinal surface to acknowledge asymmetries in the statistics of natural visual space and behavioural demands. Here, we use in vivo two photon (2P) imaging during hyperspectral visual stimulation as well as photolabeling of RGCs to provide the first eye-wide functional and anatomical census of RGCs in larval zebrafish. We find that RGCs’ functional and structural properties differ across the eye and include a notable population of UV-responsive On-sustained RGCs that are only found in the acute zone, likely to support visual prey capture of UV-bright zooplankton. Next, approximately half of RGCs display diverse forms of colour opponency - long in excess of what would be required to satisfy traditional models of colour vision. However, most information on spectral contrast was intermixed with temporal information. To consolidate this series of unexpected findings, we propose that zebrafish may use a novel “dual-achromatic” strategy segregated by a spectrally intermediate background subtraction system. Specifically, our data is consistent with a model where traditional achromatic image-forming vision is mainly driven by long-wavelength sensitive circuits, while in parallel UV-sensitive circuits serve a second achromatic system of foreground-vision that serves prey capture and, potentially, predator evasion.
The Body Image Approach Test (BIAT): A Potential Measure of the Behavioral Components of Body Image Disturbance in Anorexia and Bulimia Nervosa?
2020-01-31

A disturbed body image with fluctuating behavioral patterns of body related avoidance (BA) and body checking (BC) characterizes individuals with eating disorders (EDs) such as anorexia (AN) or bulimia nervosa (BN). So far, these behavioral body image components are mostly assessed via self-report instruments thereby neglecting their behavioral and partially automatic characteristics. Therefore, behavioral measures of BA and BC are needed. The present study investigates a behavioral assessment task for BA and BC in a sample of patients with diagnosed EDs and healthy controls. The sample consisted of 40 women diagnosed with either BN (<i>N</i> = 19) or AN (<i>N</i> = 21; ED sample) and 24 non-eating disordered, healthy female controls (HC). Within the Body Image Approach Task (BIAT) participants viewed photos of their own body (self-image) and a matched control body (other-image) by zooming the photos closer toward them (image became more focused) on the screen. The BIAT yields zoom-levels recorded separately for self- relative to other-images. Further measures were attractiveness ratings of these body images as well as questionnaire measures of BA, BC, and general ED symptomatology. Results showed that despite strong body dissatisfaction and clearly negative ratings of self- relative to other-images in both EDs, no group differences were found in approach to self-images on zoom-level as measured with the BIAT. Correlational analysis in each group indicated that zoom-level was positively related to BA scores in the HC group only. Yet, stepwise regression analyses revealed that attractiveness ratings explained most of the variance accounted by BA in predicting zoom-level. In sum, the BIAT seems suitable to assess BA and self-rated body attractiveness, but only in healthy individuals with subclinical levels on these constructs. It does not seem to capture the body image satisfaction or the behavioral components of body image disturbances in AN or BN or it conflates the opposed influences of BA and BC. Further experimentation is needed to adapt measures of behavioral body image components to the processes evoked in patients with ED during confrontation with body images.
Fivefold Fracture in a Perilunate Fracture Dislocation Involving Scaphoid, Capitate, Hamate, Triquetrum and Lunate: A Case Report
2020-01-31

This case report presents a very rare fracture combination in a perilunate dislocation including the scaphoid, capitate, hamate and triquetrum and the cornu anterior of the lunate, with an intact scapholunate ligament in a left wrist. An open reduction and internal fixation of the scaphoid, capitate, hamate and triquetrum was performed.
Dense urban scene reconstruction using stereo depth image triangulation
2020-01-31

In this paper, we present a novel 3D scene reconstruction framework from a single front-mounted stereo camera on a moving vehicle. We propose image triangulations to efficiently render a 3D scene only from 2D textures, while introducing tube meshes as an effective way to render out-of-frustum points. Furthermore, we derive a 3D extended Kalman filter to fuse stereo estimates temporally between frames and showcase a render pipeline, which exploits OpenGL shaders to offload computational costs from the CPU to the GPU. Our approach is able to increase the stereo accuracy compared to competing approaches on the KITTI visual odometry dataset. We also introduce a challenging view prediction evaluation scenario on the SYNTHIA dataset, in which our approach comes out on top in terms of SSIM, 1-NCC error and completeness.
Semantic segmentation networks of 3D point clouds for RGB-D indoor scenes
2020-01-31

This paper focuses on the semantic segmentation networks of 3D point clouds for indoor scenes. We first reduce the PointNet structure to get a reduced point network (RPN) that achieves the same performance but has less training and evaluation time comparing with PointNet. Secondly, we propose two solutions to get scale invariance and robust test performance: one is modifying RPN to get the robust performance and adding stable multi-scaling layers (MPN); another is introducing a novel point-based network based on Angular coordinates instead of Euclidean coordinates for point representation (APN). The ablation study of our networks (RPN, MPN, APN) is done. Compared to state-of-the-art semantic segmentation networks based on 3D point clouds, the experimental results show that our MPN and APN networks both achieve higher training and evaluation accuracy, as well as mean intersection over union (IoU) and overall accuracy on two benchmarks. We also have better qualitative segmentation results when directly test on another benchmark indoor scenes as well as real corridor scenes from our robots RGB-D mapping.
Interferon-γ signaling synergizes with LRRK2 in human neurons and microglia
2020-01-31

Abstract Increasing evidence suggests a role for interferons (IFNs) in neurodegeneration. Parkinson’s disease (PD) associated kinase LRRK2 has been implicated in IFN type II (IFN) response in infections and nigral neuronal loss. However, whether and how LRRK2 synergizes with IFN-γ still remains unclear. Here, we employed dopaminergic (DA) neurons and microglia differentiated from patient induced pluripotent stem cells to unravel the role of IFN-γ in LRRK2-PD. We show that IFN-γ induces LRRK2 expression in both DA neurons and microglial cells. LRRK2-G2019S, the most common PD-associated mutation, sensitizes DA neurons to IFN-γ by decreasing AKT phosphorylation. IFN-γ suppresses NFAT activity in both neurons and microglia and synergistically enhances LRRK2-induced defects of NFAT activation. Furthermore, LRRK2-G2019S negatively regulates NFAT via calcium and microtubule dynamics. Importantly, we uncover functional consequences of the reduction of NFAT activity in both cell types, namely defects of neurite elongation and alteration of microglial activation profile and motility. We propose that synergistic IFN-γ/LRRK2 activation serves as a direct link between inflammation and neurodegeneration in PD.
PGRMC1 phosphorylation affects cell shape, motility, glycolysis, mitochondrial form and function, and tumor growth
2020-01-31

Abstract Background: Progesterone Receptor Membrane Component 1 (PGRMC1) is expressed in many cancer cells, where it is associated with detrimental patient outcomes. It contains phosphorylated tyrosines which evolutionarily preceded deuterostome gastrulation and tissue differentiation mechanisms. Results: We demonstrate that manipulating PGRMC1 phosphorylation status in MIA PaCa-2 (MP) cells imposes broad pleiotropic effects. Relative to parental cells over-expressing hemagglutinin-tagged wild-type (WT) PGRMC1-HA, cells expressing a PGRMC1-HA-S57A/S181A double mutant (DM) exhibited reduced levels of proteins involved in energy metabolism and mitochondrial function, and altered glucose metabolism suggesting modulation of the Warburg effect. This was associated with increased PI3K/Akt activity, altered cell shape, actin cytoskeleton, motility, and mitochondrial properties. An S57A/Y180F/S181A triple mutant (TM) indicated the involvement of Y180 in PI3K/Akt activation. Mutation of Y180F strongly attenuated subcutaneous xenograft tumor growth in NOD-SCID gamma mice. Elsewhere we demonstrate altered metabolism, mutation incidence, and epigenetic status in these cells. Conclusions: Altogether, these results indicate that mutational manipulation of PGRMC1 phosphorylation status exerts broad pleiotropic effects relevant to cancer and other cell biology.
The Ethics of AI Ethics: An Evaluation of Guidelines
2020-02-01

Abstract Current advances in research, development and application of artificial intelligence (AI) systems have yielded a far-reaching discourse on AI ethics. In consequence, a number of ethics guidelines have been released in recent years. These guidelines comprise normative principles and recommendations aimed to harness the “disruptive” potentials of new AI technologies. Designed as a semi-systematic evaluation, this paper analyzes and compares 22 guidelines, highlighting overlaps but also omissions. As a result, I give a detailed overview of the field of AI ethics. Finally, I also examine to what extent the respective ethical principles and values are implemented in the practice of research, development and application of AI systems—and how the effectiveness in the demands of AI ethics can be improved.
Co-incidence of Damage and Microbial Patterns Controls Localized Immune Responses in Roots
2020-02-01

Recognition of microbe-associated molecular patterns (MAMPs) is crucial for the plant's immune response. How this sophisticated perception system can be usefully deployed in roots, continuously exposed to microbes, remains a mystery. By analyzing MAMP receptor expression and response at cellular resolution in Arabidopsis, we observed that differentiated outer cell layers show low expression of pattern-recognition receptors (PRRs) and lack MAMP responsiveness. Yet, these cells can be gated to become responsive by neighbor cell damage. Laser ablation of small cell clusters strongly upregulates PRR expression in their vicinity, and elevated receptor expression is sufficient to induce responsiveness in non-responsive cells. Finally, localized damage also leads to immune responses to otherwise non-immunogenic, beneficial bacteria. Damage-gating is overridden by receptor overexpression, which antagonizes colonization. Our findings that cellular damage can "switch on" local immune responses helps to conceptualize how MAMP perception can be used despite the presence of microbial patterns in the soil.
FLASHDeconv: Ultrafast, High-Quality Feature Deconvolution for Top-Down Proteomics
2020-02-01

Top-down mass spectrometry (TD-MS)-based proteomics analyzes intact proteoforms and thus preserves information about individual protein species. The MS signal of these high-mass analytes is complex and challenges the accurate determination of proteoform masses. Fast and accurate feature deconvolution (i.e., the determination of intact proteoform masses) is, therefore, an essential step for TD data analysis. Here, we present FLASHDeconv, an algorithm achieving higher deconvolution quality, with an execution speed two orders of magnitude faster than existing approaches. FLASHDeconv transforms peak positions (m/z) within spectra into log m/z space. This simple transformation turns the deconvolution problem into a search for constant patterns, thereby greatly accelerating the process. In both simple and complex samples, FLASHDeconv reports more genuine feature masses and substantially fewer artifacts than other existing methods. FLASHDeconv is freely available for download here: https://www.openms.org/flashdeconv/. A record of this paper's Transparent Peer Review process is included in the Supplemental Information.