Computational methods have made substantial progress in improving the accuracy and throughput of pathology workflows for diagnostic, prognostic, and genomic prediction. Still, lack of ...interpretability remains a significant barrier to clinical integration. We present an approach for predicting clinically-relevant molecular phenotypes from whole-slide histopathology images using human-interpretable image features (HIFs). Our method leverages >1.6 million annotations from board-certified pathologists across >5700 samples to train deep learning models for cell and tissue classification that can exhaustively map whole-slide images at two and four micron-resolution. Cell- and tissue-type model outputs are combined into 607 HIFs that quantify specific and biologically-relevant characteristics across five cancer types. We demonstrate that these HIFs correlate with well-known markers of the tumor microenvironment and can predict diverse molecular signatures (AUROC 0.601-0.864), including expression of four immune checkpoint proteins and homologous recombination deficiency, with performance comparable to 'black-box' methods. Our HIF-based approach provides a comprehensive, quantitative, and interpretable window into the composition and spatial architecture of the tumor microenvironment.
Abstract
We present high-resolution
K
-band emission spectra of the quintessential hot Jupiter HD 189733 b from the Keck Planet Imager and Characterizer. Using a Bayesian retrieval framework, we fit ...the dayside pressure–temperature profile, orbital kinematics, mass-mixing ratios of H
2
O, CO, CH
4
, NH
3
, HCN, and H
2
S, and the
13
CO/
12
CO ratio. We measure mass fractions of
logH
2
O
=
−
2.0
−
0.4
+
0.4
and
logCO
=
−
2.2
−
0.5
+
0.5
, and place upper limits on the remaining species. Notably, we find logCH
4
< −4.5 at 99% confidence, despite its anticipated presence at the equilibrium temperature of HD 189733 b assuming local thermal equilibrium. We make a tentative (∼3
σ
) detection of
13
CO, and the retrieved posteriors suggest a
12
C/
13
C ratio similar to or substantially less than the local interstellar value. The possible
13
C enrichment would be consistent with accretion of fractionated material in ices or in the protoplanetary disk midplane. The retrieved abundances correspond to a substantially substellar atmospheric C/O = 0.3 ± 0.1, while the carbon and oxygen abundances are stellar to slightly superstellar, consistent with core-accretion models which predict an inverse correlation between C/O and metallicity. The specific combination of low C/O and high metallicity suggests significant accretion of solid material may have occurred late in the formation process of HD 189733 b.
Background subtraction, or foreground detection, is a challenging problem in video processing. This problem is mainly concerned with a binary classification task, which designates each pixel in a ...video sequence as belonging to either the background or foreground scene. Traditional approaches for tackling this problem lack the power of capturing deep information in videos from a dynamic environment encountered in real-world applications, thus often achieving low accuracy and unsatisfactory performance. In this paper, we introduce a new 3-D atrous convolutional neural network, used as a deep visual feature extractor, and stack convolutional long short-term memory (ConvLSTM) networks on top of the feature extractor to capture long-term dependences in video data. This novel architecture is named a 3-D atrous ConvLSTM network. The new network can capture not only deep spatial information but also long-term temporal information in the video data. We train the proposed 3-D atrous ConvLSTM network with focal loss to tackle the class imbalance problem commonly seen in background subtraction. Experimental results on a wide range of videos demonstrate the effectiveness of our approach and its superiority over existing methods.
Despite intense interest in discovering drugs that cause G-protein-coupled receptors (GPCRs) to selectively stimulate or block arrestin signalling, the structural mechanism of receptor-mediated ...arrestin activation remains unclear
. Here we reveal this mechanism through extensive atomic-level simulations of arrestin. We find that the receptor's transmembrane core and cytoplasmic tail-which bind distinct surfaces on arrestin-can each independently stimulate arrestin activation. We confirm this unanticipated role of the receptor core, and the allosteric coupling between these distant surfaces of arrestin, using site-directed fluorescence spectroscopy. The effect of the receptor core on arrestin conformation is mediated primarily by interactions of the intracellular loops of the receptor with the arrestin body, rather than the marked finger-loop rearrangement that is observed upon receptor binding. In the absence of a receptor, arrestin frequently adopts active conformations when its own C-terminal tail is disengaged, which may explain why certain arrestins remain active long after receptor dissociation. Our results, which suggest that diverse receptor binding modes can activate arrestin, provide a structural foundation for the design of functionally selective ('biased') GPCR-targeted ligands with desired effects on arrestin signalling.
Abstract
The eccentricity of a planet’s orbit and the inclination of its orbital plane encode important information about its formation and history. However, exoplanets detected via direct imaging ...are often only observed over a very small fraction of their period, making it challenging to perform reliable physical inferences given wide, unconstrained posteriors. The aim of this project is to investigate biases (deviation of the median and mode of the posterior from the true values of orbital parameters, and the width and coverage of their credible intervals) in the estimation of orbital parameters of directly imaged exoplanets, particularly their eccentricities, and to define general guidelines to perform better estimations of uncertainty. For this, we constructed various orbits and generated mock data for each spanning ∼0.5% of the orbital period. We used the Orbits For The Impatient algorithm to compute orbit posteriors and compared those to the true values of the orbital parameters. We found that the inclination of the orbital plane is the parameter that most affects our estimations of eccentricity, with orbits that appear near edge on producing eccentricity distributions skewed away from the true values and often bimodal. We also identified a degeneracy between eccentricity and inclination that makes it difficult to distinguish posteriors of face-on, eccentric orbits and edge-on, circular orbits. For the exoplanet-imaging community, we propose practical recommendations, guidelines, and warnings relevant to orbit fitting.
Introduction: First-line intervention for the metabolic disorders or type 2 Diabetes is lifestyle change, including weight management, diet, and increased physical activity. This study evaluated the ...associations between health professional (HP) weight discussions and weight management practices among high risk safety-net patients.
Methods: Cross-sectional data on adults (aged≥18 years) with self-reported diabetes, hypertension or hyperlipidemia from the 2014 National Health Center Patient Survey (HCPS) was analyzed. The HCPS is a nationally representative survey of patients receiving care at safety-net health centers. Outcome (binary) was whether patients tried to lose weight in prior 12 months. Independent variables were HP discussing the weight problem, talking about weight loss options (i.e., exercise), suggesting a nutritionist visit, or offering weight loss medication. Logistic regression models with complex sampling design was used to test the association between HP weight discussions and the outcome, adjusted for psycho-sociodemographic covariates.
Results: Of 3671 patients, 55.5% (n=2039) tried to lose weight in prior 12 months. Women (62.4%) and Hispanic race/ethnicity (62.8%) were associated with a higher prevalence of attempting to lose weight in prior 12 months. In the fully adjusted model, having received HP’s weight discussion (AOR=5.54, 95%CI: 3.59-8.56), suggest exercise (AOR=3.61, 95% CI: 2.37-5.49), and recommend a nutritionist visit (AOR=2.59, 95% CI: 1.67-4.01) were associated for increased likelihood of attempting weight loss.
Conclusions: HP advice to lose weight may increase patients’ motivation to lose weight and weight loss behavior. Better training for HPs in delivering high-value care such as brief weight counselling could lead to improved chronic disease health outcomes for safety-net patient populations.
Disclosure
J. J. Wang: None. Z. Shi: None. A. Yan: None.
Abstract
The formation and evolution pathway for the directly imaged multiplanetary system HR 8799 remains mysterious. Accurate constraints on the chemical composition of the planetary atmosphere(s) ...are key to solving the mystery. We perform a detailed atmospheric retrieval on HR 8799 c to infer the chemical abundances and abundance ratios using a combination of photometric data along with low- and high-resolution spectroscopic data (
R
∼ 20–35,000). We specifically retrieve C/H, O/H, and C/O and find them to be
0.55
−
0.39
+
0.36
,
0.47
−
0.32
+
0.31
, and
0.67
−
0.15
+
0.12
at 68% confidence. The superstellar C and O abundances, yet a stellar C/O ratio, reveal a potential formation pathway for HR 8799 c. Planet c, and likely the other gas giant planets in the system, formed early on (likely within ∼1 Myr), followed by further atmospheric enrichment in C and O through the accretion of solids beyond the CO ice line. The enrichment either preceded or took place during the early phase of the inward migration to the current planet locations.
ABSTRACT
Although the source active regions of some coronal mass ejections (CMEs) were identified in CME catalogues, vast majority of CMEs do not have an identified source active region. We propose a ...method that uses a filtration process and machine learning to identify the sunspot groups associated with a large fraction of CMEs and compare the physical parameters of these identified sunspot groups with properties of their corresponding CMEs to find mechanisms behind the initiation of CMEs. These CMEs were taken from the Coordinated Data Analysis Workshops (CDAW) data base hosted at NASA’s website. The Helioseismic and Magnetic Imager (HMI) Active Region Patches (HARPs) were taken from the Stanford University’s Joint Science Operations Center (JSOC) data base. The source active regions of the CMEs were identified by the help of a custom filtration procedure and then by training a long short-term memory network (LSTM) to identify the patterns in the physical magnetic parameters derived from vector and line-of-sight magnetograms. The neural network simultaneously considers the time series data of these magnetic parameters at once and learns the patterns at the onset of CMEs. This neural network was then used to identify the source HARPs for the CMEs recorded from 2011 till 2020. The neural network was able to reliably identify source HARPs for 4895 CMEs out of 14 604 listed in the CDAW data base during the aforementioned period.
Increasingly, circular economy (CE) has been adopted globally to operationalize supply chain sustainability. The development of industry 4.0 technologies provides a new opportunity to improve the ...effectiveness and efficiency of adoption of CE, in particular, from the waste management perspective. More recently, scholars acknowledge the need for more studies on industry 4.0 and CE-driven sustainability aspects in supply chains. This research aims to fill the literature void and make a contribution from the perspective of smart waste management in supply chains using industry 4.0-based CE operations. Eleven key drivers were identified through semi-structured interviews, administered to experienced supply chain practitioners in China. A fuzzy DEMATEL method was used to analyse the interrelationships among these key drivers. The results show that the most fundamental causal drivers of smart waste management are overcoming operational challenges, recovering value, speeding up operations, saving cost and improving profit. There is a virtuous cycle between market demand and the improving price-performance ratio of industry 4.0 technologies. Our findings are part of the development of a bottom-up approach to adopting smart waste management in supply chains. The interrelationships identified in this research provide valuable insights into driving forces. Organizations, policy makers and technology providers can apply these insights when utilizing industry 4.0 technologies to improve supply chain waste management in line with the CE principle, and to achieve supply chain sustainability.
Abstract
Coronal mass ejections (CMEs) are massive solar eruptions, which have a significant impact on Earth. In this paper, we propose a new method, called DeepCME, to estimate two properties of ...CMEs, namely, CME mass and kinetic energy. Being able to estimate these properties helps better understand CME dynamics. Our study is based on the CME catalog maintained at the Coordinated Data Analysis Workshops Data Center, which contains all CMEs manually identified since 1996 using the Large Angle and Spectrometric Coronagraph (LASCO) on board the Solar and Heliospheric Observatory. We use LASCO C2 data in the period between 1996 January and 2020 December to train, validate, and test DeepCME through 10-fold cross validation. The DeepCME method is a fusion of three deep-learning models, namely ResNet, InceptionNet, and InceptionResNet. Our fusion model extracts features from LASCO C2 images, effectively combining the learning capabilities of the three component models to jointly estimate the mass and kinetic energy of CMEs. Experimental results show that the fusion model yields a mean relative error (MRE) of 0.013 (0.009, respectively) compared to the MRE of 0.019 (0.017, respectively) of the best component model InceptionResNet (InceptionNet, respectively) in estimating the CME mass (kinetic energy, respectively). To our knowledge, this is the first time that deep learning has been used for CME mass and kinetic energy estimations.
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