bluuebunny/crossref_metadata_2025_split huggingface dataset:
Interior photon counting computed tomography for quantification of coronary artery calcium: pre-clinical phantom study
Authors: Juntunen Mikael A K , Sepponen Pasi , Korhonen Kristiina , Pohjanen Vesa-Matti , Ketola Juuso , Kotiaho Antti , Nieminen Miika T , Inkinen Satu I 
Published: July 2020

Abstract
Computed tomography (CT) is the reference method for cardiac imaging, but concerns have been raised regarding the radiation dose of CT examinations. Recently, photon counting detectors (PCDs) and interior tomography, in which the radiation beam is limited to the organ-of-interest, have been suggested for patient dose reduction. In this study, we investigated interior PCD-CT (iPCD-CT) for non-enhanced quantification of coronary artery calcium (CAC) using an anthropomorphic torso phantom and ex vivo coronary artery samples. We reconstructed the iPCD-CT measurements with filtered back projection (FBP), iterative total variation (TV) regularization, padded FBP, and adaptively detruncated FBP and adaptively detruncated TV. We compared the organ doses between conventional CT and iPCD-CT geometries, assessed the truncation and cupping artifacts with iPCD-CT, and evaluated the CAC quantification performance of iPCD-CT. With approximately the same effective dose between conventional CT geometry (0.30 mSv) and interior PCD-CT with 10.2 cm field-of-view (0.27 mSv), the organ dose of the heart was increased by 52.3% with interior PCD-CT when compared to CT. Conversely, the organ doses to peripheral and radiosensitive organs, such as the stomach (55.0% reduction), were often reduced with interior PCD-CT. FBP and TV did not sufficiently reduce the truncation artifact, whereas padded FBP and adaptively detruncated FBP and TV yielded satisfactory truncation artifact reduction. Notably, the adaptive detruncation algorithm reduced truncation artifacts effectively when it was combined with reconstruction detrending. With this approach, the CAC quantification accuracy was good, and the coronary artery disease grade reclassification rate was particularly low (5.6%). Thus, our results confirm that CAC quantification can be performed with the interior CT geometry, that the artifacts are effectively reduced with suitable interior reconstruction methods, and that interior tomography provides efficient patient dose reduction.
Solving quantum statistical mechanics with variational autoregressive networks and quantum circuits
Authors: Liu Jin-Guo , Mao Liang , Zhang Pan , Wang Lei 
Published: July 2020

Abstract
We extend the ability of an unitary quantum circuit by interfacing it with a classical autoregressive neural network. The combined model parametrizes a variational density matrix as a classical mixture of quantum pure states, where the autoregressive network generates bitstring samples as input states to the quantum circuit. We devise an efficient variational algorithm to jointly optimize the classical neural network and the quantum circuit to solve quantum statistical mechanics problems. One can obtain thermal observables such as the variational free energy, entropy, and specific heat. As a byproduct, the algorithm also gives access to low energy excitation states. We demonstrate applications of the approach to thermal properties and excitation spectra of the quantum Ising model with resources that are feasible on near-term quantum computers.
Fear of Cancer Recurrence and Inhibited Disclosure: Testing the Social-Cognitive Processing Model in Couples Coping With Breast Cancer
Authors: Soriano Emily C , Otto Amy K , LoSavio Stefanie T , Perndorfer Christine , Siegel Scott D , Laurenceau Jean-Philippe 
Published: July 2020

Abstract

Background
Withholding cancer-related concerns from one’s partner (protective buffering) and feeling that one’s partner is inaccessible or unresponsive to such disclosure (social constraints) are two interpersonal interaction patterns that separately have been linked to poorer adjustment to cancer.

Purpose
Guided by the Social-Cognitive Processing Model, we examined the joint effects of social constraints and protective buffering on fear of cancer recurrence (FCR) in survivors and spouses. Social constraints and protective buffering were hypothesized to emerge as independent predictors of higher FCR.

Methods
Early-stage breast cancer survivors and spouses (N = 79 couples; 158 paired individuals) completed up to five repeated measures of FCR, social constraints, protective buffering, and relationship quality during the year postdiagnosis. A second-order growth curve model was estimated and extended to test the time-varying, within-person effects of social constraints and protective buffering on a latent FCR variable, controlling for relationship quality.

Results
As hypothesized, greater social constraints and protective buffering significantly (p &lt; .05) predicted higher concurrent FCR at the within-person level, controlling for global relationship quality and change in FCR over time. The fixed effects were found to be similar for both survivors and spouses.

Conclusions
Findings suggest that interaction patterns resulting in inhibited disclosure are associated with greater FCR for both survivors and spouses, consistent with the Social-Cognitive Processing Model. This work adds to the growing body of research highlighting the social context of FCR.
Hacking Adaptation: Updating, Porting, and Forking the Shakespearean Source Code
Authors: Winckler Reto 
Published: July 2020

AbstractThis essay proposes that computer hacking can provide us with an appropriate framework through which to rethink the basic workings of adaptation in general and Shakespeare adaptation in particular in the twenty-first century. Building on the work of Thomas Leitch and Sarah Cardwell in adaptation studies and Christopher Kelty in the anthropology of the hacker movement, the essay positions itself as an alternative to Douglas Lanier’s model of the Shakespeare rhizome. The central argument is that understanding Shakespeare’s works as source code, and adaptations of them as hacks of that source code, as well as sources of future hacks, makes it possible to account for and work with the difficult but crucial notions of the source and of fidelity, while resolving many of the theoretical, practical, and political problems which motivated scholars to avoid or try to overcome those notions in the past.
Association of Interactions Between Mammographic Density Phenotypes and Established Risk Factors With Breast Cancer Risk, by Tumor Subtype and Menopausal Status
Authors: Chen Hongjie , Yaghjyan Lusine , Li Christopher , Peters Ulrike , Rosner Bernard , Lindström Sara , Tamimi Rulla M 
Published: July 2020

AbstractPrevious studies suggest that the association between mammographic density (MD) and breast cancer risk might be modified by other breast cancer risk factors. In this study, we assessed multiplicative interactions between MD measures and established risk factors on the risk of invasive breast cancer overall and according to menopausal and estrogen receptor status. We used data on 2,137 cases and 4,346 controls from a nested case-control study within the Nurses’ Health Study (1976–2004) and Nurses’ Health Study II (1989–2007), whose data on percent mammographic density (PMD) and absolute area of dense tissue and nondense tissue (NDA) were available. No interaction remained statistically significant after adjusting for number of comparisons. For breast cancer overall, we observed nominally significant interactions (P &lt; 0.05) between nulliparity and PMD/NDA, age at menarche and area of dense tissue, and body mass index and NDA. Individual nominally significant interactions across MD measures and risk factors were also observed in analyses stratified by either menopausal or estrogen receptor status. Our findings help provide further insights into potential mechanisms underlying the association between MD and breast cancer.
Attitudinal social norms
Authors: van Wietmarschen Han 
Published: July 2020

Abstract
On Bicchieri's view, social norms most centrally involve a pattern of preferences among the members of a relevant population; according to Brennan, Eriksson, Goodin, and Southwood, social norms most centrally involve patterns of normative attitudes among the members of a given group. This paper argues, first, that social norms can require attitudes as well as behaviour, and, second, that the existence of such attitudinal social norms speaks in favour of the preference-based view and against the normative attitudes-based view.
XI—Rights Externalism and Racial Injustice
Authors: Darby Derrick 
Published: July 2020

AbstractRights externalism, a view I defend in Rights, Race, and Recognition, takes social recognition to be a condition for being a rights bearer. I vindicate this view by answering two recent critics. I concede some ground, particularly with respect to their reservations about what we gain, but argue that claims about what we stand to lose are overblown. I conclude that rights externalism is not detrimental to the critique of racial injustice, and that embracing it has noteworthy virtues. The most significant is that it affords us a conception of rights that takes the realities of lived experiences seriously.
X—Why Trust Science? Reliability, Particularity and the Tangle of Science
Authors: Cartwright Nancy 
Published: July 2020

Abstract
In evaluating science, philosophers tends to focus on general laws and on their truth. I urge a shift in focus to the reliability of the panoply of outputs science produces (‘the tangle of science’) and in tandem, from the general to the particular. Here I give five arguments to support this, including (a) many, many scientific outputs (measures, devices, empirical studies, model organisms, and so on), which must be supposed reliable if we are to warrant our general principles, aren’t truth-apt; and (b) reliability invites the crucial question, ‘Reliable for what?’ Getting clear the particular purpose is essential for effective action and just evaluation.
IDRMutPred: predicting disease-associated germline nonsynonymous single nucleotide variants (nsSNVs) in intrinsically disordered regions
Authors: Zhou Jing-Bo , Xiong Yao , An Ke , Ye Zhi-Qiang , Wu Yun-Dong 
Published: July 2020

Abstract

Motivation
Despite of the lack of folded structure, intrinsically disordered regions (IDRs) of proteins play versatile roles in various biological processes, and many nonsynonymous single nucleotide variants (nsSNVs) in IDRs are associated with human diseases. The continuous accumulation of nsSNVs resulted from the wide application of NGS has driven the development of disease-association prediction methods for decades. However, their performance on nsSNVs in IDRs remains inferior, possibly due to the domination of nsSNVs from structured regions in training data. Therefore, it is highly demanding to build a disease-association predictor specifically for nsSNVs in IDRs with better performance.

Results
We present IDRMutPred, a machine learning-based tool specifically for predicting disease-associated germline nsSNVs in IDRs. Based on 17 selected optimal features that are extracted from sequence alignments, protein annotations, hydrophobicity indices and disorder scores, IDRMutPred was trained using three ensemble learning algorithms on the training dataset containing only IDR nsSNVs. The evaluation on the two testing datasets shows that all the three prediction models outperform 17 other popular general predictors significantly, achieving the ACC between 0.856 and 0.868 and MCC between 0.713 and 0.737. IDRMutPred will prioritize disease-associated IDR germline nsSNVs more reliably than general predictors.

Availability and implementation
The software is freely available at http://www.wdspdb.com/IDRMutPred.

Supplementary information
Supplementary data are available at Bioinformatics online.
The asymptotic distribution of modularity in weighted signed networks
Authors: Ma Rong , Barnett Ian 
Published: July 2020

Summary
Modularity is a popular metric for quantifying the degree of community structure within a network. The distribution of the largest eigenvalue of a network’s edge weight or adjacency matrix is well studied and is frequently used as a substitute for modularity when performing statistical inference. However, we show that the largest eigenvalue and modularity are asymptotically uncorrelated, which suggests the need for inference directly on modularity itself when the network is large. To this end, we derive the asymptotic distribution of modularity in the case where the network’s edge weight matrix belongs to the Gaussian orthogonal ensemble, and study the statistical power of the corresponding test for community structure under some alternative models. We empirically explore universality extensions of the limiting distribution and demonstrate the accuracy of these asymptotic distributions through Type I error simulations. We also compare the empirical powers of the modularity-based tests and some existing methods. Our method is then used to test for the presence of community structure in two real data applications.
Conflict Management in High-Stakes Illegal Drug Transactions
Authors: Bouchard Martin , Soudijn Melvin , Reuter Peter 
Published: July 2020

Abstract
We draw from aspects of Black’s theory of conflict management to (1) provide a description of the types of disputes occurring at the highest levels of the drug trade and (2) examine whether conflicts that end in violence differed from those that found a peaceful resolution. A mixed-methods approach was used to analyse 33 incidents of smuggling transaction failures at the highest levels of the cocaine trade in the Netherlands. The results show that outcomes were determined by the way in which conflicts arose; lost product due to negligence and fraud increased the likelihood of violence. The fragile equilibrium between peaceful or violent resolution depended on whether the guilty party accepted blame or provided evidence that could account for losses.
Cerebrovascular disease in patients with COVID-19: neuroimaging, histological and clinical description
Authors: Hernández-Fernández Francisco , Sandoval Valencia Hernán , Barbella-Aponte Rosa Angélica , Collado-Jiménez Rosa , Ayo-Martín Óscar , Barrena Cristina , Molina-Nuevo Juan David , García-García Jorge , Lozano-Setién Elena , Alcahut-Rodriguez Cristian , Martínez-Martín Álvaro , Sánchez-López Antonio , Segura Tomás 
Published: July 2020

Abstract
Since the appearance of the first case of coronavirus disease 2019 (COVID-19) a pandemic has emerged affecting millions of individuals worldwide. Although the main clinical manifestations are respiratory, an increase in neurological conditions, specifically acute cerebrovascular disease, has been detected. We present cerebrovascular disease case incidence in hospitalized patients with SARS-CoV-2 infection. Patients were confirmed by microbiological/serological testing, or on chest CT semiology. Available data on co-morbidity, laboratory parameters, treatment administered, neuroimaging, neuropathological studies and clinical evolution during hospitalization, measured by the modified Rankin scale, were analysed. A bivariate study was also designed to identify differences between ischaemic and haemorrhagic subtypes. A statistical model of binary logistic regression and sensitivity analysis was designed to study the influence of independent variables over prognosis. In our centre, there were 1683 admissions of patients with COVID-19 over 50 days, of which 23 (1.4%) developed cerebrovascular disease. Within this group of patients, cerebral and chest CT scans were performed in all cases, and MRI in six (26.1%). Histological samples were obtained in 6/23 cases (two brain biopsies, and four arterial thrombi). Seventeen patients were classified as cerebral ischaemia (73.9%, with two arterial dissections), five as intracerebral haemorrhage (21.7%), and one leukoencephalopathy of posterior reversible encephalopathy type. Haemorrhagic patients had higher ferritin levels at the time of stroke (1554.3 versus 519.2, P = 0.004). Ischaemic strokes were unexpectedly frequent in the vertebrobasilar territory (6/17, 35.3%). In the haemorrhagic group, a characteristic radiological pattern was identified showing subarachnoid haemorrhage, parieto-occipital leukoencephalopathy, microbleeds and single or multiple focal haematomas. Brain biopsies performed showed signs of thrombotic microangiopathy and endothelial injury, with no evidence of vasculitis or necrotizing encephalitis. The functional prognosis during the hospital period was unfavourable in 73.9% (17/23 modified Rankin scale 4–6), and age was the main predictive variable (odds ratio = 1.5; 95% confidence interval 1.012–2.225; P = 0.043). Our series shows cerebrovascular disease incidence of 1.4% in patients with COVID-19 with high morbidity and mortality. We describe pathological and radiological data consistent with thrombotic microangiopathy caused by endotheliopathy with a haemorrhagic predisposition.
Integration of FDG-PET/CT in the Diagnostic Workup for Staphylococcus aureus Bacteremia: A Prospective Interventional Matched-cohort Study
Authors: Ghanem-Zoubi Nesrin , Kagna Olga , Abu-Elhija Jawad , Mustafa-Hellou Mona , Qasum Majd , Keidar Zohar , Paul Mical 
Published: July 2020

Abstract

Background
Staphylococcus aureus bacteremia (SAB) is uniquely characterized by focal pyogenic complications that might not be apparent clinically. We investigated the benefit of adding fluorodeoxyglucose–positron emission tomography/computed tomography (FDG-PET/CT) in the workup of patients with SAB.

Methods
In a matched-cohort study patients with SAB (intervention group) were prospectively recruited to undergo FDG-PET/CT 7–14 days after diagnosis. Treatment was directed by FDG-PET/CT findings. Clinical outcomes were compared with a control group of patients with SAB who had not undergone FDG-PET/CT, matched by age, Charlson score, methicillin susceptibility, and survival duration to FDG-PET/CT. The primary outcome was 90-day mortality. Residual confounding was controlled through regression analyses.

Results
During the study period 149 patients with 151 separate episodes of SAB underwent FDG-PET/CT and were compared with 150 matched patients with 151 SAB episodes. Patients in the intervention group acquired infections more frequently in the community and had less frequently solid malignancies and more frequently high-risk SAB. Ninety-day mortality in the intervention group was significantly lower than in the control group (21/151 [13.9%] vs 43/151 [28.5%], P = .002). The difference remained significant in a subgroup analysis of patients with community-onset infections without malignancy and among patients with low-risk SAB. Controlling for other risk factors for mortality, FDG-PET/CT performance among all patients was independently associated with lower mortality (OR, .39; 95% CI, .18–.84). Patients in the intervention group had longer duration of treatment and more focus control procedures performed compared with the control group.

Conclusions
FDG-PET/CT in patients with SAB seems to improve survival through guidance of treatment duration and co-interventions.
Investigator-initiated Randomized Controlled Trials in Infectious Diseases: Better Value for Money for Registration Trials of New Antimicrobials
Authors: Paul Mical , Harbarth Stephan , Huttner Angela , Thwaites Guy E , Theuretzbacher Ursula , Bonten Marc J M , Leibovici Leonard 
Published: July 2020

Abstract
Randomized controlled trials (RCTs) conducted by the industry are expensive, especially trials conducted for registration of new drugs for multidrug-resistant (MDR) bacteria. Lower-cost investigator-initiated trials have recently been successful in recruiting patients with severe infections caused by MDR bacteria. In this viewpoint, we contrast the aims, methods, and resulting costs of industry-led and investigator-initiated trials and ask whether contemporary registration trial costs are justified. Contract research organizations, delivering and monitoring industry-sponsored trials at a significant cost, have little incentive to make trials more efficient or less expensive. The value of universal monitoring of all trial data is questionable. We propose that clinical trial networks play a more influential role in RCT design and planning, lead adaptive risk-based trial monitoring, and work with the industry to maximize efficient recruitment and lower costs in registration trials for the approval of new antimicrobials.
Single-cell analysis of SARS-CoV-2 receptor ACE2 and spike protein priming expression of proteases in the human heart
Authors: Liu Hanning , Gai Shujie , Wang Xiaoyi , Zeng Juntong , Sun Cheng , Zhao Yan , Zheng Zhe 
Published: July 2020

Abstract

Aims
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) directly binds to ACE2 (angiotensin-converting enzyme 2) to facilitate cellular entry. Compared with the lung or respiratory tract, the human heart exhibits greater ACE2 expression. However, little substantial damage was found in the heart tissue, and no viral particles were observed in the cardiac myocytes. This study aims to analyse ACE2 and SARS-CoV-2 spike (S) protein proteases at the single-cell level, to explore the cardiac involvement in COVID-19 and improve our understanding of the potential cardiovascular implications of COVID-19.

Methods and Results
With meta-analysis, the prevalence of cardiac injury in COVID-19 patients varies from 2% [95% confidence interval (CI) 0–5%, I2 = 0%] in non-ICU patients to 59% (95% CI 48–71%, I2 = 85%) in non-survivors. With public single-cell sequence data analysis, ACE2 expression in the adult human heart is higher than that in the lung (adjusted P &lt; 0.0001). Inversely, the most important S protein cleavage protease TMPRSS2 (transmembrane protease serine protease-2) in the heart exhibits an extremely lower expression than that in the lung (adjusted P &lt; 0.0001), which may restrict entry of SARS-CoV-2 into cardiac cells. Furthermore, we discovered that other S protein proteases, CTSL (cathepsin L) and FURIN (furin, paired basic amino acid cleaving enzyme), were expressed in the adult heart at a similar level to that in the lung, which may compensate for TMPRSS2, mediating cardiac involvement in COVID-19.

Conclusion
Compared with the lung, ACE2 is relatively more highly expressed in the human heart, while the key S protein priming protease, TMPRSS2, is rarely expressed. The low percentage of ACE2+/TMPRSS2+ cells reduced heart vulnerability to SARS-CoV-2 to some degree. CTSL and FURIN may compensate for S protein priming to mediate SARS-CoV-2 infection of the heart.