julilili42/papers huggingface dataset:
Multicentric study applying the european laryngological society classification of benign laryngotracheal stenosis in adults treated by tracheal or cricotracheal resection and anastomosis
2019-09-11

Objectives/Hypothesis Introduction and widespread use of cricotracheal resection and anastomosis (CTRA) as routine treatment for high‐grade benign laryngotracheal stenosis (LTS) led to the need for a new classification system that could accurately predict surgical outcomes by integrating crucial stenosis and patient‐related information. In 2015, the European Laryngological Society (ELS) proposed a new classification for benign LTS. We retrospectively tested it in adults treated at three referral centers to assess its reliability in predicting surgical outcomes. Study Design Retrospective cohort study. Methods We included 166 adults treated by open tracheal resection and anastomosis (TRA) and CTRA procedures, restaged according to the ELS classification evaluating grade of stenosis (I–IV, Myer‐Cotton), number of subsites involved, and presence of systemic comorbidities. We correlated these parameters with decannulation, number of retreatments, and complications. Results Final decannulation was predicted by a proposed ELS score ≥ IIIb, history of previous treatment, and length of resection ( P &lt; .05). Decannulation was achieved in 99% of patients without and in 88% of patients with surgical complications ( P &lt; .01). The incidence of surgical complications was related to the proposed ELS score ( P &lt; .01); an ELS score &lt; IIIb showed a lower complication rate compared to patients with a ≥ IIIb score (32.8% vs. 57.7%, P &lt; .01). Additional treatment was required in 73 (44%) patients (mean = 2.7 ± 2.2, range = 1–11). ELS score ≥ IIIb, length of resection, and occurrence of surgical complications predicted the number of such treatments ( P &lt; .05, P &lt; .05, and P &lt; .001, respectively). Conclusions ELS classification of benign LTS is able to accurately predict success in adult TRA/CTRA procedures and may be helpful in choice of therapy and patient counseling. Level of Evidence 2b Laryngoscope , 130:1640–1645, 2020
Simulation-Based Training of the Rapid Evaluation and Management of Acute Stroke (STREAM)—A Prospective Single-Arm Multicenter Trial
2019-09-11

<b>Introduction:</b> Acute stroke care delivered by interdisciplinary teams is time-sensitive. Simulation-based team training is a promising tool to improve team performance in medical operations. It has the potential to improve process times, team communication, patient safety, and staff satisfaction. We aim to assess whether a multi-level approach consisting of a stringent workflow revision based on peer-to-peer review and 2-3 one-day <i>in situ</i> simulation trainings can improve acute stroke care processing times in high volume neurocenters within a 6 months period. <b>Methods and Analysis:</b> The trial is being carried out in a pre-test-post-test design at 7 tertiary care university hospital neurocenters in Germany. The intervention is directed at the interdisciplinary multiprofessional stroke teams. Before and after the intervention, process times of all direct-to-center stroke patients receiving IV thrombolysis (IVT) and/or endovascular therapy (EVT) will be recorded. The primary outcome measure will be the "door-to-needle" time of all consecutive stroke patients directly admitted to the neurocenters who receive IVT. Secondary outcome measures will be intervention-related process times of the fraction of patients undergoing EVT and effects on team communication, perceived patient safety, and staff satisfaction via a staff questionnaire. <b>Interventions:</b> We are applying a multi-level intervention in cooperation with three "STREAM multipliers" from each center. First step is a central meeting of the multipliers at the sponsor's institution with the purposes of algorithm review in a peer-to-peer process that is recorded in a protocol and an introduction to the principles of simulation training and debriefing as well as crew resource management and team communication. Thereafter, the multipliers cooperate with the stroke team trainers from the sponsor's institution to plan and execute 2-3 one-day simulation courses <i>in situ</i> in the emergency department and CT room of the trial centers whereupon they receive teaching materials to perpetuate the trainings. <b>Clinical Trial Registration:</b> STREAM is a registered trial at https://clinicaltrials.gov/ct2/show/NCT03228251.
CT-morphologic and CT-textural patterns of response in inoperable soft tissue sarcomas treated with pazopanib—a preliminary retrospective cohort study
2019-09-11

Objective: To analyze patterns of response in soft tissue sarcomas exposed to pazopanib using CT-morphologic and textural features and their suitability for evaluating therapeutic response. Methods: Retrospective evaluation of CT response and texture patterns in 33 patients (23 female; mean age: 61.2 years, range, 30–85 years) with soft tissue sarcomas treated with pazopanib from October 2008 to July 2017. Response evaluation was based on modified (m)CHOI-criteria and RECISTv.1.1 and classified as partial response (PR), stable disease (SD), progressive disease (PD). The following CT-texture (CTTA)-parameters were calculated: mean, entropy and uniformity of intensity/average/skewness/entropy of co-occurrence matrix and contrast of neighboring-gray-level-dependence-matrix. Results: Following mCHOI-criteria, 12 patients achieved PR, 7 SD and 14 PD. As per RECISTv.1.1 9 patients obtained PR, 9 SD and 15 PD. Frequent patterns of response were tumor liquefaction and necrosis (n=4/33, 12.1% each). Further patterns included shrinkage and cavitation (n=2/33, 6.1% each). In responders, differences in mean heterogeneity (p=0.01), intensity (p=0.03), average (p=0.03) and entropy of skewness (p=0.01) were found at follow-up whereas in non-responders, CTTA-parameters did not change significantly. Baseline-CTTA-features differed between responders and non-responders in terms of uniformity of skewness (p=0.045). Baseline-CTTA-parameters did not correlate with any morphologic response pattern. Conclusion: Most frequent patterns of response to pazopanib were tumor liquefaction and necrosis. Single CT-textural features show strong association with the response to pazopanib—although limited in relation to specific response patterns. Advances in knowledge: Tumor liquefication and necrosis are important patterns of response to pazopanib. CT-texture analysis has limited associations with specific response patterns.
Coincidence of the freezing and the onset of caging in hard sphere and Lennard-Jones fluids
2019-09-11

In this article, we examine the collective particle dynamics, as expressed by the time correlation function of the longitudinal particle current density, of several different fluids in the vicinity of their freezing points/lines. We consider and compare results obtained by dynamic light scattering for a suspension of hard spheres and by molecular dynamics for fluids with hard sphere and Lennard-Jones interactions. The latter are performed along both an isotherm and an isochore. In all cases, we find a qualitative change in the collective dynamics, within the resolution of the data, when their respective freezing lines are crossed. We associate this change with the onset of caging. The new results for the Lennard-Jones fluid reported here confirm that the occurrence of caging, found previously for systems of hard spheres, is a more general feature that distinguishes a metastable fluid from one in thermodynamic equilibrium.
Synthetic resampling strategies and machine learning for digital soil mapping in Iran
2019-09-12

Abstract Most common machine learning (ML) algorithms usually work well on balanced training sets, that is, datasets in which all classes are approximately represented equally. Otherwise, the accuracy estimates may be unreliable and classes with only a few values are often misclassified or neglected. This is known as a class imbalance problem in machine learning and datasets that do not meet this criterion are referred to as imbalanced data. Most datasets of soil classes are, therefore, imbalanced data. One of our main objectives is to compare eight resampling strategies that have been developed to counteract the imbalanced data problem. We compared the performance of five of the most common ML algorithms with the resampling approaches. The highest increase in prediction accuracy was achieved with SMOTE (the synthetic minority oversampling technique). In comparison to the baseline prediction on the original dataset, we achieved an increase of about 10, 20 and 10% in the overall accuracy, kappa index and F‐score, respectively. Regarding the ML approaches, random forest (RF) showed the best performance with an overall accuracy, kappa index and F‐score of 66, 60 and 57%, respectively. Moreover, the combination of RF and SMOTE improved the accuracy of the individual soil classes, compared to RF trained on the original dataset and allowed better prediction of soil classes with a low number of samples in the corresponding soil profile database, in our case for Chernozems. Our results show that balancing existing soil legacy data using synthetic sampling strategies can significantly improve the prediction accuracy in digital soil mapping (DSM). Highlights Spatial distribution of soil classes in Iran can be predicted using machine learning (ML) algorithms. The synthetic minority oversampling technique overcomes the drawback of imbalanced and highly biased soil legacy data. When combining a random forest model with synthetic sampling strategies the prediction accuracy of the soil model improves significantly. The resulting new soil map of Iran has a much higher spatial resolution compared to existing maps and displays new soil classes that have not yet been mapped in Iran.
Genomic and clinical predictors of lacosamide response in refractory epilepsies
2019-09-12

Abstract Objective Clinical and genetic predictors of response to antiepileptic drugs (AEDs) are largely unknown. We examined predictors of lacosamide response in a real‐world clinical setting. Methods We tested the association of clinical predictors with treatment response using regression modeling in a cohort of people with refractory epilepsy. Genetic assessment for lacosamide response was conducted via genome‐wide association studies and exome studies, comprising 281 candidate genes. Results Most patients (479/483) were treated with LCM in addition to other AEDs. Our results corroborate previous findings that patients with refractory genetic generalized epilepsy (GGE) may respond to treatment with LCM. No clear clinical predictors were identified. We then compared 73 lacosamide responders, defined as those experiencing greater than 75% seizure reduction or seizure freedom, to 495 nonresponders (&lt;25% seizure reduction). No variants reached the genome‐wide significance threshold in our case‐control analysis. Significance No genetic predictor of lacosamide response was identified. Patients with refractory GGE might benefit from treatment with lacosamide.
AMPK Subunits Harbor Largely Nonoverlapping Genetic Determinants for Body Fat Mass, Glucose Metabolism, and Cholesterol Metabolism
2019-09-12

Abstract Context Adenosine monophosphate (AMP)-activated protein kinase (AMPK) is a heterotrimeric enzyme and central regulator of cellular energy metabolism. The impact of single nucleotide polymorphisms (SNPs) in all 7 AMPK subunit genes on adiposity, glucose metabolism, and lipid metabolism has not yet been systematically studied. Objective To analyze the associations of common SNPs in all AMPK genes, and of different scores thereof, with adiposity, insulin sensitivity, insulin secretion, blood glucose, low-density lipoprotein (LDL) cholesterol, high-density lipoprotein (HDL) cholesterol, total cholesterol, and triglycerides. Study Design and Methods A cohort of 2789 nondiabetic participants from the Tübingen Family study of type 2 diabetes, metabolically characterized by oral glucose tolerance test and genotyped by genome-wide SNP array, was analyzed. Results We identified 6 largely nonoverlapping SNP sets across 4 AMPK genes (PRKAA1, PRKAA2, PRKAG2, PRKAG3) associated with adiposity, insulin sensitivity, insulin secretion, blood glucose, total/LDL cholesterol, or HDL cholesterol, respectively. A genetic score of body-fat-increasing alleles revealed per-allele effect sizes on body mass index (BMI) of +0.22 kg/m2 (P = 2.3 × 10–7), insulin sensitivity of −0.12 × 1019 L2/mol2 (P = 9.9 × 10–6) and 2-hour blood glucose of +0.02 mmol/L (P = 0.0048). Similar effects on blood glucose were observed with scores of insulin-sensitivity-reducing, insulin-secretion-reducing and glucose-raising alleles, respectively. A genetic cholesterol score increased total and LDL cholesterol by 1.17 mg/dL per allele (P = 0.0002 and P = 3.2 × 10–5, respectively), and a genetic HDL score decreased HDL cholesterol by 0.32 mg/dL per allele (P = 9.1 × 10–6). Conclusions We describe largely nonoverlapping genetic determinants in AMPK genes for diabetes-/atherosclerosis-related traits, which reflect the metabolic pathways controlled by the enzyme. Formation of trait-specific genetic scores revealed additivity of allele effects, with body-fat-raising alleles reaching a marked effect size. (J Clin Endocrinol Metab 105: 14–25, 2020)
Learning Divisive Normalization in Primary Visual Cortex
2019-09-12

Abstract Divisive normalization (DN) is a prominent computational building block in the brain that has been proposed as a canonical cortical operation. Numerous experimental studies have verified its importance for capturing nonlinear neural response properties to simple, artificial stimuli, and computational studies suggest that DN is also an important component for processing natural stimuli. However, we lack quantitative models of DN that are directly informed by measurements of spiking responses in the brain and applicable to arbitrary stimuli. Here, we propose a DN model that is applicable to arbitrary input images. We test its ability to predict how neurons in macaque primary visual cortex (V1) respond to natural images, with a focus on nonlinear response properties within the classical receptive field. Our model consists of one layer of subunits followed by learned orientation-specific DN. It outperforms linear-nonlinear and wavelet-based feature representations and makes a significant step towards the performance of state-of-the-art convolutional neural network (CNN) models. Unlike deep CNNs, our compact DN model offers a direct interpretation of the nature of normalization. By inspecting the learned normalization pool of our model, we gained insights into a long-standing question about the tuning properties of DN that update the current textbook description: we found that within the receptive field oriented features were normalized preferentially by features with similar orientation rather than non-specifically as currently assumed. Author summary Divisive normalization (DN) is a computational building block throughout sensory processing in the brain. We currently lack an understanding of what role this normalization mechanism plays when processing complex stimuli like natural images. Here, we use modern machine learning methods to build a general DN model that is directly informed by data from primary visual cortex (V1). Contrary to high-predictive deep learning models, our DN-based model’s parameters offer a straightforward interpretation of the nature of normalization. Within the receptive field, we found that neurons responding strongly to a specific orientation are preferentially normalized by other neurons that are highly active for similar orientations, rather than being normalized by all neurons as it is currently assumed by textbook models.
Visual properties of human retinal ganglion cells
2019-09-12

The retinal output is the sole source of visual information for the brain. Studies in non-primate mammals estimate that this information is carried by several dozens of retinal ganglion cell types, each informing the brain about different aspects of a visual scene. Even though morphological studies of primate retina suggest a similar diversity of ganglion cell types, research has focused on the function of only a few cell types. In human retina, recordings from individual cells are anecdotal or focus on a small subset of identified types. Here, we present the first systematic ex-vivo recording of light responses from 342 ganglion cells in human retinas obtained from donors. We find a great variety in the human retinal output in terms of preferences for positive or negative contrast, spatio-temporal frequency encoding, contrast sensitivity, and speed tuning. Some human ganglion cells showed similar response behavior as known cell types in other primates, while we also recorded light responses that have not been described previously. This first extensive description of the human retinal output should facilitate interpretation of primate data and comparison to other mammalian species, and it lays the basis for the use of ex-vivo human retina for in-vitro analysis of novel treatment approaches.
AMPK subunits harbor largely non-overlapping genetic determinants for body fat mass, glucose- and cholesterol metabolism
2019-09-12

Abstract Context AMP-activated protein kinase (AMPK) is a heterotrimeric enzyme and central regulator of cellular energy metabolism. The impact of single nucleotide polymorphisms (SNPs) in all seven subunit genes on adiposity, glucose- and lipid metabolism has not been systematically studied yet. Objective To analyze the associations of common SNPs in all AMPK genes, and of different scores thereof, with adiposity, insulin sensitivity, insulin secretion, blood glucose, total-, LDL- and HDL-cholesterol and triglycerides. Study Design and Methods A cohort of 2789 non-diabetic subjects from the Tübingen Family study of type-2 diabetes, metabolically characterized by oral glucose tolerance test and genotyped by genome-wide SNP array was analyzed. Results We identified largely non-overlapping SNP sets across four AMPK genes (PRKAA1, PRKAA2, PRKAG2, PRKAG3) associated with adiposity, insulin sensitivity, insulin secretion, blood glucose, total-/LDL-cholesterol or HDL-cholesterol, respectively. A genetic score of body-fat-increasing alleles revealed per-allele effect sizes on BMI of +0.22 kg/m2 (p=2.3·10-7), insulin sensitivity of -0.12·1019 L2/mol2 (p=9.9·10-6) and 2-h blood glucose of +0.02 mmol/L (p=0.0048). Similar effects on blood glucose were observed with scores of insulin-sensitivity-reducing, insulin-secretion-reducing and glucose-raising alleles, respectively. A genetic cholesterol score increased total- and LDL-cholesterol by 1.17 mg/dL per allele (p=0.0002 and p=3.2·10-5, respectively), and a genetic HDL score decreased HDL-cholesterol by 0.32 mg/dL per allele (p=9.1·10-6). Conclusions We describe largely non-overlapping genetic determinants in AMPK genes for diabetes-/atherosclerosis-related traits which reflect the metabolic pathways controlled by the enzyme. Formation of trait-specific genetic scores revealed additivity of allele effects, with body-fat-raising alleles reaching a marked effect size.
RELXILL_NK: A Black Hole Relativistic Reflection Model for Testing General Relativity
2019-09-12

In this paper, we briefly present RELXILL_NK, the first and currently only readily available model of the relativistic reflection spectrum of black hole accretion disks that includes non-Kerr solutions for the black hole spacetime, thus allowing for tests of the Kerr hypothesis and general relativity (GR). RELXILL_NK makes use of a general relativistic ray-tracing code to calculate the relativistic effects of any well-behaved, stationary, axisymmetric, and asymptotically flat black hole spacetime, while the disk physics is handled through the non-relativistic X-ray reflection code XILLVER. A number of different flavors are available within RELXILL_NK; we summarize and compare these flavors using the Johannsen metric for the black hole spacetime.
What Is Expressed When Emotions Are Expressed in Art?
2019-09-12

The author argues for a Collingwoodian claim: if an emotion is expressed in art, it is not a content which exists prior to, and independent of, its expression. Artistic emotion expressions rather clarify and complete emotions. The autor backs up this claim by Musil’s Lewinian theory of emotion which displays significant parallels to recent Enactivist Theories of Emotion: it states that embodiment in action (in a broad sense) is necessary in any case in order for nonspecific dispositions to emotions to shape and consolidate into specific fully fledged, genuine emotions. Two ways of shaping and consolidating are distinguished. One way is to categorise emotions in terms of their so-called “formal objects” by associating nonspecific dispositions to emotions via action with specific paradigm scenarios. Another way is to put these categories to the test by expressing exemplary individual experiences which go beyond the existing repertoire of paradigm scenarios. Art, when it expresses emotions, shapes and consolidates in the second way. Art challenges the existing system of emotion types which is at the same time to challenge the corresponding system of evaluations and values. The presented argument draws upon the notions of expressing developed by Dorit Bar-On and Philipp J. Koch.
Presence of the Jehol Biota turtle &lt;i&gt;Ordosemys liaoxiensis&lt;/i&gt; in the Early Cretaceous Hengtongshan Formation of southern Jilin Province, China
2019-09-12

Abstract. Recently, a vertebrate assemblage of the Jehol Biota has been reported from the Early Cretaceous Hengtongshan Formation of Xingling Town, Meihekou City, Jilin Province, China. It is dominated by the fishes Lycoptera and Sinamia and the sinemydid turtle Ordosemys. Here, we describe the turtle specimens and referral to Ordosemys liaoxiensis, otherwise known from the older Yixian Formation of the Jehol Biota. It is characterized by a subcircular shell, wide vertebral scales, well-developed plastral fenestrae, and a major contribution from the xiphiplastra to enclose the hypo-xiphiplastral fenestra. As the first Mesozoic turtle of Jilin Province, this record represents the first tetrapod to indicate the presence of the Jehol Biota in the region. Given the geographic and temporal distance from the Yixian Formation, future collections from the Hengtongshan Formation have good potential for evaluating spatiotemporal patterns of the Jehol Biota.
Variational and Dyson-Schwinger Equations of QCD
2019-09-12

Dyson--Schwinger equations are an established, powerful non-perturbative tool for QCD. In the Hamiltonian formulation of QCD they allow for variational calculations with non-Gaussian wave functionals: by means of DSEs the various -point functions, needed in expectation values of observables like the Hamiltonian, can be expressed in terms of the variational kernels of the trial Ansatz for the vacuum wave functional. Equations of motion for these variational kernels are derived by minimizing the energy density, renormalized, and solved numerically. We determine the chiral condensate from the renormalized quark propagator.