julilili42/papers huggingface dataset:
Cerebellar Morphology and Behavioral Profiles in Mice Lacking Heparan Sulfate Ndst Gene Function
2020-07-11

Disruption of the Heparan sulfate (HS)-biosynthetic gene N-acetylglucosamine N-Deacetylase/N-sulfotransferase 1 (Ndst1) during nervous system development causes malformations that are composites of those caused by mutations of multiple HS binding growth factors and morphogens. However, the role of Ndst function in adult brain physiology is less explored. Therefore, we generated mice bearing a Purkinje-cell-specific deletion in Ndst1 gene function by using Cre/loxP technology under the control of the Purkinje cell protein 2 (Pcp2/L7) promotor, which results in HS undersulfation. We observed that mutant mice did not show overt changes in the density or organization of Purkinje cells in the adult cerebellum, and behavioral tests also demonstrated normal cerebellar function. This suggested that postnatal Purkinje cell development and homeostasis are independent of Ndst1 function, or that impaired HS sulfation upon deletion of Ndst1 function may be compensated for by other Purkinje cell-expressed Ndst isoforms. To test the latter possibility, we additionally deleted the second Purkinje-cell expressed Ndst family member, Ndst2. This selectively abolished reproductive capacity of compound mutant female, but not male, mice, suggesting that ovulation, gestation, or female reproductive behavior specifically depends on Ndst-dependent HS sulfation in cells types that express Cre under Pcp2/L7 promotor control.
Tracking evoked responses to auditory and visual stimuli in fetuses exposed to maternal high‐risk conditions
2020-07-11

Abstract Magnetoencephalography (MEG) has been successfully applied to record fetal auditory (auditory evoked response [AER]) and visual evoked responses (VER). In this study, we report the AER and VER development trajectory by tracking the evoked response detectability and latency from recordings starting at 27 weeks of gestation in pregnancies classified as high risk. Fetal MEG and ultrasound recordings were performed on 158 pregnant women, and the total number of fetal auditory and visual tests conducted was 321 and 237, respectively. The overall evoked response analysis showed 237 AER (73.8%) and 164 VER detections (69.2%). The mean AER latency was 290.7 ( SD 125.5) ms and the mean VER latency was 293.7 ( SD 114.5) ms. The rate of decrease (95% confidence limits) in average AER and VER first‐peak latency between 100–350 ms was 1.97 (−1.86, +5.81) ms/week and 1.35 (−3.83, +6.53) ms/week, respectively. This trend in high‐risk fetuses conforms to the general trajectory of decrease in latency with gestational age progression, even though this decrease was non‐significant, as reported in the case of normal growing fetuses. Although there was a significant difference in detection rates between male and female fetuses, this was not reflected in either latency values or the sensory modality applied. Furthermore, the main factors that had the most significant effect on response detectability included the presence of intervening layers of adipose tissue between the fetal head and stimulus source and an increase in the maternal body mass index.
Predicting and Mapping of Soil Organic Carbon Using Machine Learning Algorithms in Northern Iran
2020-07-12

Estimation of the soil organic carbon (SOC) content is of utmost importance in understanding the chemical, physical, and biological functions of the soil. This study proposes machine learning algorithms of support vector machines (SVM), artificial neural networks (ANN), regression tree, random forest (RF), extreme gradient boosting (XGBoost), and conventional deep neural network (DNN) for advancing prediction models of SOC. Models are trained with 1879 composite surface soil samples, and 105 auxiliary data as predictors. The genetic algorithm is used as a feature selection approach to identify effective variables. The results indicate that precipitation is the most important predictor driving 14.9% of SOC spatial variability followed by the normalized difference vegetation index (12.5%), day temperature index of moderate resolution imaging spectroradiometer (10.6%), multiresolution valley bottom flatness (8.7%) and land use (8.2%), respectively. Based on 10-fold cross-validation, the DNN model reported as a superior algorithm with the lowest prediction error and uncertainty. In terms of accuracy, DNN yielded a mean absolute error of 0.59%, a root mean squared error of 0.75%, a coefficient of determination of 0.65, and Lin’s concordance correlation coefficient of 0.83. The SOC content was the highest in udic soil moisture regime class with mean values of 3.71%, followed by the aquic (2.45%) and xeric (2.10%) classes, respectively. Soils in dense forestlands had the highest SOC contents, whereas soils of younger geological age and alluvial fans had lower SOC. The proposed DNN (hidden layers = 7, and size = 50) is a promising algorithm for handling large numbers of auxiliary data at a province-scale, and due to its flexible structure and the ability to extract more information from the auxiliary data surrounding the sampled observations, it had high accuracy for the prediction of the SOC base-line map and minimal uncertainty.
Reliable evaluation of adversarial robustness with an ensemble of diverse parameter-free attacks
2020-07-12

The field of defense strategies against adversarial attacks has significantly grown over the last years, but progress is hampered as the evaluation of adversarial defenses is often insufficient and thus gives a wrong impression of robustness. Many promising defenses could be broken later on, making it difficult to identify the state-of-the-art. Frequent pitfalls in the evaluation are improper tuning of hyperparameters of the attacks, gradient obfuscation or masking. In this paper we first propose two extensions of the PGD-attack overcoming failures due to suboptimal step size and problems of the objective function. We then combine our novel attacks with two complementary existing ones to form a parameter-free, computationally affordable and user-independent ensemble of attacks to test adversarial robustness. We apply our ensemble to over 50 models from papers published at recent top machine learning and computer vision venues. In all except one of the cases we achieve lower robust test accuracy than reported in these papers, often by more than , identifying several broken defenses.
Minimally distorted Adversarial Examples with a Fast Adaptive Boundary Attack
2020-07-12

The evaluation of robustness against adversarial manipulation of neural networks-based classifiers is mainly tested with empirical attacks as methods for the exact computation, even when available, do not scale to large networks. We propose in this paper a new white-box adversarial attack wrt the -norms for aiming at finding the minimal perturbation necessary to change the class of a given input. It has an intuitive geometric meaning, yields quickly high quality results, minimizes the size of the perturbation (so that it returns the robust accuracy at every threshold with a single run). It performs better or similar to state-of-the-art attacks which are partially specialized to one -norm, and is robust to the phenomenon of gradient masking.
Confidence-Calibrated Adversarial Training: Generalizing to Unseen Attacks
2020-07-12

Adversarial training yields robust models against a specific threat model, e.g., adversarial examples. Typically robustness does not generalize to previously unseen threat models, e.g., other norms, or larger perturbations. Our confidence-calibrated adversarial training (CCAT) tackles this problem by biasing the model towards low confidence predictions on adversarial examples. By allowing to reject examples with low confidence, robustness generalizes beyond the threat model employed during training. CCAT, trained only on adversarial examples, increases robustness against larger , , and attacks, adversarial frames, distal adversarial examples and corrupted examples and yields better clean accuracy compared to adversarial training. For thorough evaluation we developed novel white- and black-box attacks directly attacking CCAT by maximizing confidence. For each threat model, we use attacks with up to restarts and iterations and report worst-case robust test error, extended to our confidence-thresholded setting, across all attacks.
Temporal associations between sleep slow oscillations, spindles and ripples
2020-07-12

Abstract The systems consolidation of memory during slow‐wave sleep (SWS) is thought to rely on a dialogue between hippocampus and neocortex that is regulated by an interaction between neocortical slow oscillations (SOs), thalamic spindles and hippocampal ripples. Here, we examined the occurrence rates of and the temporal relationships between these oscillatory events in rats, to identify the possible direction of interaction between these events under natural conditions. To facilitate comparisons with findings in humans, we combined frontal and parietal surface EEG with local field potential (LFP) recordings in medial prefrontal cortex (mPFC) and dorsal hippocampus (dHC). Consistent with a top‐down driving influence, EEG SO upstates were associated with an increase in spindles and hippocampal ripples. This increase was missing in SO upstates identified in mPFC recordings. Ripples in dHC recordings always followed the onset of spindles consistent with spindles timing ripple occurrence. Comparing ripple activity during co‐occurring SO‐spindle events with that during isolated SOs or spindles, suggested that ripple dynamics during SO‐spindle events are mainly determined by the spindle, with only the SO downstate providing a global inhibitory signal to both thalamus and hippocampus. As to bottom‐up influences, we found an increase in hippocampal ripples ~200 ms before the SO downstate, but no similar increase of spindles preceding SO downstates. Overall, the temporal pattern is consistent with a loop‐like scenario where, top‐down, SOs can trigger thalamic spindles which, in turn, regulate the occurrence of hippocampal ripples. Ripples, bottom‐up, and independent from thalamic spindles, can contribute to the emergence of neocortical SOs.
Evaluation of optimal education level to implement structured reporting into ultrasound training
2020-07-12

Aims: Reporting of head and neck ultrasound (HNU) has been outlined to be a major obstacle during ultrasound training due to a lack of standardized structure, content and terminology. Consequently, overall report quality differs significantly between various examiners posing a severe risk factor for information loss and miscommunication. Therefore, the present study’s purpose is to compare the overall quality of free text reports (FTR) and structured reports (SR) of HNU at various stages of training in order to determine the optimal educational level to implement SR.Material and methods: Typical pathologies in HNU were reported upon using SR and FTR by medical students, junior residents and senior residents. The reports were assessed for overall quality, time efficiency and readability. Additionally, user satisfaction was determined using a questionnaire.Results: SRs exhibited a significantly superior report quality (93.1% vs. 45.6%, p&lt;0.001) at all training levels. Overall time efficiency was significantly better for SRs, especially at the stages of medical school and early residency (89.4 s vs. 160.2 s., p&lt;0.001). Using structured reporting also increased user satisfaction significantly (VAS 8.6 vs. 3.9, p&lt;0.001).Conclusions: Implementing structured reporting of HNU results in a superior report quality at all training stages. Greatest benefits for time efficiency are achieved by implementation during medical school. Therefore, structured reporting of HNU should be implemented early on in the training of HNU.
Acute changes in systemic glycaemia gate access and action of GLP-1R agonist on brain structures controlling energy homeostasis
2020-07-12

ABSTRACT The control of body weight and glucose homeostasis are the bedrock of type 2 diabetes medication. Therapies based on co-administration of glucagon-like peptide-1 (GLP-1) long-acting analogues and insulin are becoming popular in the treatment of T2D. Both insulin and GLP-1 receptors (InsR and GLP1-R, respectively) are expressed in brain regions critically involved in the regulation of energy homeostasis, suggesting a possible cooperative action. However, the mechanisms underlying the synergistic action of insulin and GLP-1R agonists on body weight loss and glucose homeostasis remain largely under-investigated. In this study, we provide evidence that peripheral insulin administration modulates the action of GLP-1R agonists onto fatty acids oxidation. Taking advantage of fluorescently labeled insulin and GLP-1R agonists, we found that glucoprivic condition, either achieved by insulin or by 2-deoxyglucose (2-DG), acts as a permissive signal on the blood-brain barrier (BBB) at circumventricular organs, including the median eminence (ME) and the area postrema (AP), enhancing the passage and action of GLP-1-R agonists. Mechanistically, this phenomenon relied on the release of tanycyctic vascular endothelial growth factor A (VEGF-A) and it was selectively impaired after calorie-rich diet exposure. Finally, we found that in human subjects, low blood glucose also correlates with enhanced blood-to-brain passage of insulin suggesting that changes in glycaemia also affect passage of peptide hormones into the brain in humans. In conclusion, we describe a yet unappreciated mechanism by which acute variations of glycaemia gate the entry and action of circulating energy-related signals in the brain. This phenomenon has physiological and clinical relevance implying that glycemic control is critical to harnessing the full benefit of GLP-1R agonist co-treatment in body weight loss therapy.
Review of Particle Physics
2020-07-13

Abstract The Review summarizes much of particle physics and cosmology. Using data from previous editions, plus 3,324 new measurements from 878 papers, we list, evaluate, and average measured properties of gauge bosons and the recently discovered Higgs boson, leptons, quarks, mesons, and baryons. We summarize searches for hypothetical particles such as supersymmetric particles, heavy bosons, axions, dark photons, etc. Particle properties and search limits are listed in Summary Tables. We give numerous tables, figures, formulae, and reviews of topics such as Higgs Boson Physics, Supersymmetry, Grand Unified Theories, Neutrino Mixing, Dark Energy, Dark Matter, Cosmology, Particle Detectors, Colliders, Probability and Statistics. Among the 120 reviews are many that are new or heavily revised, including a new review on High Energy Soft QCD and Diffraction and one on the Determination of CKM Angles from B Hadrons. The Review is divided into two volumes. Volume 1 includes the Summary Tables and 98 review articles. Volume 2 consists of the Particle Listings and contains also 22 reviews that address specific aspects of the data presented in the Listings. The complete Review (both volumes) is published online on the website of the Particle Data Group (pdg.lbl.gov) and in a journal. Volume 1 is available in print as the PDG Book. A Particle Physics Booklet with the Summary Tables and essential tables, figures, and equations from selected review articles is available in print and as a web version optimized for use on phones as well as an Android app.
Neural circuits in the mouse retina support color vision in the upper visual field
2020-07-13

Abstract Color vision is essential for an animal’s survival. It starts in the retina, where signals from different photoreceptor types are locally compared by neural circuits. Mice, like most mammals, are dichromatic with two cone types. They can discriminate colors only in their upper visual field. In the corresponding ventral retina, however, most cones display the same spectral preference, thereby presumably impairing spectral comparisons. In this study, we systematically investigated the retinal circuits underlying mouse color vision by recording light responses from cones, bipolar and ganglion cells. Surprisingly, most color-opponent cells are located in the ventral retina, with rod photoreceptors likely being involved. Here, the complexity of chromatic processing increases from cones towards the retinal output, where non-linear center-surround interactions create specific color-opponent output channels to the brain. This suggests that neural circuits in the mouse retina are tuned to extract color from the upper visual field, aiding robust detection of predators and ensuring the animal’s survival.
COVID-19/SARS-CoV-2 Infection: Lysosomes and Lysosomotropism Implicate New Treatment Strategies and Personal Risks
2020-07-13

In line with SARS and MERS, the SARS-CoV-2/COVID-19 pandemic is one of the largest challenges in medicine and health care worldwide. SARS-CoV-2 infection/COVID-19 provides numerous therapeutic targets, each of them promising, but not leading to the success of therapy to date. Neither an antiviral nor an immunomodulatory therapy in patients with SARS-CoV-2 infection/COVID-19 or pre-exposure prophylaxis against SARS-CoV-2 has proved to be effective. In this review, we try to close the gap and point out the likely relationships among lysosomotropism, increasing lysosomal pH, SARS-CoV-2 infection, and disease process, and we deduce an approach for the treatment and prophylaxis of COVID-19, and cytokine release syndrome (CRS)/cytokine storm triggered by bacteria or viruses. Lysosomotropic compounds affect prominent inflammatory messengers (e.g., IL-1B, CCL4, CCL20, and IL-6), cathepsin-L-dependent viral entry of host cells, and products of lysosomal enzymes that promote endothelial stress response in systemic inflammation. As supported by recent clinical data, patients who have already taken lysosomotropic drugs for other pre-existing conditions likely benefit from this treatment in the COVID-19 pandemic. The early administration of a combination of antivirals such as remdesivir and lysosomotropic drugs, such as the antibiotics teicoplanin or dalbavancin, seems to be able to prevent SARS-CoV-2 infection and transition to COVID-19.
Ancestors of domestic cats in Neolithic Central Europe: Isotopic evidence of a synanthropic diet
2020-07-13

Significance Most of today’s domesticates began as farm animals, but cat domestication took a different path. Cats became commensal of humans somewhere in the Fertile Crescent, attracted to early farmers’ settlements by rodent pests. Cat remains from Poland dated to 4,200 to 2,300 y BCE are currently the earliest evidence for the migration of the Near Eastern wildcat to Central Europe. Tracking the possible synanthropic origin of that migration, we used stable isotopes to investigate the paleodiet. We found that the ecological balance was already changed due to the expansion of Neolithic farmlands. We conclude that among the Late Neolithic Near Eastern wildcats from Poland were free-living individuals, who preyed on rodent pests and shared ecological niches with native European wildcats.
The impact of an audience response system on a summative assessment, a controlled field study
2020-07-13

Abstract Background Audience response systems allow to activate the audience and to receive a direct feedback of participants during lectures. Modern systems do not require any proprietary hardware anymore. Students can directly respond on their smartphone. Several studies reported about a high level of satisfaction of students when audience response systems are used, however their impact on learning success is still unclear. Methods In order to evaluate the impact of an audience response system on the learning success we implemented the audience response system eduVote into a seminar series and performed a controlled crossover study on its impact on assessments. One hundred fifty-four students in nine groups were taught the same content. In four groups, eduVote was integrated for the first topic while five groups were taught this topic without the audience response systems. For a second topic, the groups were switched: Those groups who were taught before using eduVote were now taught without the audience response system and vice versa. We then analysed the impact of the audience response system on the students’ performance in a summative assessment and specifically focused on questions dealing with the topic, for which the audience response system was used during teaching. We further assessed the students’ perception on the use of eduVote using questionnaires. Results In our controlled crossover study we could not confirm an impact of the audience response system eduVote on long-term persistence i.e. the students’ performance in the summative assessment. Our evaluation revealed that students assessed the use of eduVote very positively, felt stronger engaged and better motivated to deal with the respective topics and would prefer their integration into additional courses as well. In particular we identified that students who feel uncomfortable with answering questions in front of others profit from the use of an audience response system during teaching. Conclusions Audience response systems motivate and activate students and increase their engagement during classes. However, their impact on long-term persistence and summative assessments may be limited. Audience response systems, however, specifically allow activating students which cannot be reached by the traditional way of asking questions without such an anonymous tool.
Performance of a rapid diagnostic test for the detection of Cryptosporidium spp. in African children admitted to hospital with diarrhea
2020-07-13

The weak performance of the studied RDT suggests the need to carefully evaluate available commercial RDTs before their use as standard tools in clinical trials and community survey of Cryptosporidium infections in pediatric cohorts.
A Novel C1-Esterase Inhibitor Oxygenator Coating Prevents FXII Activation in Human Blood
2020-07-13

The limited hemocompatibility of currently used oxygenator membranes prevents long-term use of artificial lungs in patients with lung failure. To improve hemocompatibility, we developed a novel covalent C1-esterase inhibitor (C1-INH) coating. Besides complement inhibition, C1-INH also prevents FXII activation, a very early event of contact phase activation at the crossroads of coagulation and inflammation. Covalently coated heparin, as the current anticoagulation gold standard, served as control. Additionally, a combination of both coatings (C1-INH/heparin) was established. The coatings were tested for their hemocompatibility by dynamic incubation with freshly drawn human whole blood. The analysis of various blood and plasma parameters revealed that C1-INH-containing coatings were able to markedly reduce FXIIa activity compared to heparin coating. Combined C1-INH/heparin coatings yielded similarly low levels of thrombin-antithrombin III complex formation as heparin coating. In particular, adhesion of monocytes and platelets as well as the diminished formation of fibrin networks were observed for combined coatings. We could show for the first time that a covalent coating with complement inhibitor C1-INH was able to ameliorate hemocompatibility. Thus, the early inhibition of the coagulation cascade is likely to have far-reaching consequences for the other cross-reacting plasma protein pathways.