bluuebunny/crossref_metadata_2025_split huggingface dataset:
Should we replace radiologists with deep learning? Pigeons, error and trust in medical AI
Authors: Alvarado Ramón 
Published: October 2021

AbstractThe sudden rise in the ability of machine learning methodology, such as deep neural networks, to identify and predict with great accuracy instances of malignant cell growth from radiological images has led prominent developers of this technology, such as Geoffrey Hinton, to hold the view that “[…] we should stop training radiologists.” Similar views exist in other contexts regarding the replacement of humans with artificial intelligence (AI) technologies. The assumption in these kinds of views is that deep neural networks are better than human radiologists in that they are more accurate, less costly, and have more predictive power than their human counterparts. In this paper, I argue that these considerations, even if true, are simply inadequate as reasons for us to allocate the kind of trust suggested by Hinton and others to these sorts of artifacts. In particular, I show that if the same considerations were true of something other than an AI device, say a pigeon, we would not have sufficient reason to trust them in the same way as suggested of deep neural networks in a medical setting. If this is the case then these considerations are also insufficient to trust AI enough to replace radiologists. Furthermore, I argue that the reliability of AI methodologies such as deep neural networks—which are at the center of this argument—is something that has not yet been established, and doing so faces fundamental challenges. Because of these challenges, it is not possible to ascribe the level of reliability expected from the deployment of a medical device. So, not only are the reasons cited in favor of the deployment of AI technologies in medical settings not sufficient/adequate even if they are true, but knowing whether they are true or not faces non‐trivial epistemic challenges. If this is so, then we have no good reasons to advocate replacing radiologists with AI methodologies such as deep neural networks.
Digitally supported public health interventions through the lens of structural injustice: The case of mobile apps responding to violence against women and girls
Authors: Sauerborn Ela , Eisenhut Katharina , Ganguli‐Mitra Agomoni , Wild Verina 
Published: October 2021

AbstractMobile applications (apps) have gained significant popularity as a new intervention strategy responding to violence against women and girls. Despite their growing relevance, an assessment from the perspective of public health ethics is still lacking. Here, we base our discussion on the understanding of violence against women and girls as a multidimensional, global public health issue on structural, societal and individual levels and situate it within the theoretical framework of structural injustice, including epistemic injustice. Based on a systematic app review we previously conducted, we evaluate the content and functions of apps through the lens of structural injustice. We argue that technological solutions such as apps may be a useful tool in the fight against violence against women and girls but have to be situated within the broader frame of public health that considers the structural dimensions of such violence. Ultimately, the concerns raised by structural injustice are—alongside key concerns of safety, data privacy, importance of human supportive contact, and so forth—crucial dimensions in the ethical assessment of such apps. However, research on the role and relevance of apps as strategies to address the structural and epistemic dimensions of violence remains scarce. This article aims to provide a foundation for further discussion in this area and could be applicable to other areas in public health policy and practice.
Integrating sample similarities into latent class analysis: a tree‐structured shrinkage approach
Authors: Li Mengbing , Park Daniel E. , Aziz Maliha , Liu Cindy M. , Price Lance B. , Wu Zhenke 
Published: October 2021

AbstractThis paper is concerned with using multivariate binary observations to estimate the probabilities of unobserved classes with scientific meanings. We focus on the setting where additional information about sample similarities is available and represented by a rooted weighted tree. Every leaf in the given tree contains multiple samples. Shorter distances over the tree between the leaves indicate a priori higher similarity in class probability vectors. We propose a novel data integrative extension to classical latent class models with tree‐structured shrinkage. The proposed approach enables (1) borrowing of information across leaves, (2) estimating data‐driven leaf groups with distinct vectors of class probabilities, and (3) individual‐level probabilistic class assignment given the observed multivariate binary measurements. We derive and implement a scalable posterior inference algorithm in a variational Bayes framework. Extensive simulations show more accurate estimation of class probabilities than alternatives that suboptimally use the additional sample similarity information. A zoonotic infectious disease application is used to illustrate the proposed approach. The paper concludes by a brief discussion on model limitations and extensions.
Does investor protection affect corporate dividend policy? Evidence from Asian markets
Authors: Athari Seyed Alireza 
Published: October 2021

AbstractThis study investigates the nexus between investor protection and dividend policy for 517 listed nonfinancial firms operating in Asian countries between the period 2008 and 2017. The dynamic panel data model (System‐GMM) reveals that stronger investor protection is associated with higher dividend payouts, and firms increase dividends, specifically in response to the rise of the extent of disclosure and director liability and also ease of shareholder suits. Besides, results highlight that firms pay out fewer dividends in cases of growth opportunity particularly in environments with stronger investor protection, a more developed financial market, and a common‐law system. Results are robust when alternative specifications are implemented.
A global ecological signal of extinction risk in terrestrial vertebrates
Authors: Munstermann Maya J. , Heim Noel A. , McCauley Douglas J. , Payne Jonathan L. , Upham Nathan S. , Wang Steve C. , Knope Matthew L. 
Published: October 2021

AbstractTo determine the distribution and causes of extinction threat across functional groups of terrestrial vertebrates, we assembled an ecological trait data set for 18,016 species of terrestrial vertebrates and utilized phylogenetic comparative methods to test which categories of habitat association, mode of locomotion, and feeding mode best predicted extinction risk. We also examined the individual categories of the International Union for Conservation of Nature Red List extinction drivers (e.g., agriculture and logging) threatening each species and determined the greatest threats for each of the four terrestrial vertebrate groups. We then quantified the sum of extinction drivers threatening each species to provide a multistressor perspective on threat. Cave dwelling amphibians (p < 0.01), arboreal quadrupedal mammals (all of which are primates) (p < 0.01), aerial and scavenging birds (p < 0.01), and pedal (i.e., walking) squamates (p < 0.01) were all disproportionately threatened with extinction in comparison with the other assessed ecological traits. Across all threatened vertebrate species in the study, the most common risk factors were agriculture, threatening 4491 species, followed by logging, threatening 3187 species, and then invasive species and disease, threatening 2053 species. Species at higher risk of extinction were simultaneously at risk from a greater number of threat types. If left unabated, the disproportionate loss of species with certain functional traits and increasing anthropogenic pressures are likely to disrupt ecosystem functions globally. A shift in focus from species‐ to trait‐centric conservation practices will allow for protection of at‐risk functional diversity from regional to global scales.
Thromboelastography profiles for controlled circulatory death donors: Validating the role of heparin
Authors: Crannell W. Christian , Sally Mitch , McConnell Keeley , Connelly Chris , Maynard Erin , Dewey Elizabeth , Abt Peter , Enestvedt C. Kristian 
Published: October 2021

AbstractControlled donation after circulatory death (cDCD) liver transplants are associated with increased ischemic‐type biliary complications. Microvascular thrombosis secondary to decreased donor fibrinolysis may contribute to bile duct injury. We hypothesized that cDCD donors are hypercoagulable with impaired fibrinolysis and aim to use thromboelastography to characterize cDCD coagulation profiles.
Dorothy Hodgkin Lecture 2021: Drugs, genes and diabetes
Authors: Pearson Ewan R. 
Published: October 2021

AbstractGlycaemic response to metformin and sulphonylureas is heritable – with ~34%–37% of variation explainable by common genetic variation. The premise of this review is that by understanding how genetic variation contributes to drug response we can gain insights into the mechanisms of action of diabetes drugs. Here, I focus on two old drugs, metformin and sulphonylureas, where I would suggest we still have a lot to learn about their mechanism of action or their optimal use in clinical care. The fact that reduced function variants of the key transporter that takes metformin into the liver (OCT1) do not alter glycaemic response to metformin suggests that metformin does not need to get into the liver to work. A subsequent GWAS of metformin response identifies a robust variant that alters GLUT2 expression – which may support increasing evidence that metformin works primarily in the gut. For sulphonylureas, observation from patients with neonatal diabetes due to activating KATP channel mutations treated with sulphonylureas identified a novel role for sulphonylureas to enable β‐cell incretin response. This work led to recent studies of low‐dose sulphonylurea (20 mg gliclazide) in T2DM, which identified that at this dose sulphonylureas augment the incretin effect and increase β‐cell glucose sensitivity, without increasing hypoglycaemia risk. This work, prompted by studies in monogenic diabetes, suggests that we have historically been using sulphonylureas at too high a dose. With increasing availability of genetic data pharmacogenomic studies in patients with diabetes should reveal mechanistic insights into old and new diabetes drugs, with the potential for optimized use and novel therapies.
The automated pancreas: A review of technologies and clinical practice
Authors: Biester Torben , Tauschmann Martin , Chobot Agata , Kordonouri Olga , Danne Thomas , Kapellen Thomas , Dovc Klemen 
Published: October 2021

AbstractInsulin pumps and glucose sensors are effective in improving diabetes therapy and reducing acute complications. The combination of both devices using an algorithm‐driven interoperable controller makes automated insulin delivery (AID) systems possible. Many AID systems have been tested in clinical trials and have proven safety and effectiveness. However, currently, none of these systems are available for routine use in children younger than 6 years in Europe. For continued use, both users and prescribers must have sound knowledge of the features of the individual AID systems. Presently, all systems require various user interactions (e.g. meal announcements) because fully automated systems are not yet developed. Open‐source systems are non‐regulated variants to circumvent existing regulatory conditions. There are risks here for both users and prescribers. To evaluate AID therapy, the metric data of the glucose sensors, ‘time in target range’ and ‘glucose management index’, are novel recognized and suitable parameters allowing a consultation based on real glucose and insulin pump download data from the daily life of people with diabetes. Read out via cloud‐based software or automatic download of such individual treatment data provides the ideal technical basis for shared decision‐making through telemedicine, which must be further evaluated for general use.
Distal nail embedding treatment using autogenous nails
Authors: Kashiyama Kazuya , Nakano Motoi , Higashi Akihito , Ashizuka Shoko , Moriuchi Yuki , Iwao Atsuhiko , Tanaka Katsumi 
Published: October 2021

AbstractA regrowing nail tip after nail avulsion may excessively curve and invaginate into the nail bed. This is treated as a type of ingrown toenail, and is known as distal nail embedding. In most cases, further growth restores the original shape evenly over the nail bed. However, it is often painful and such cases may require treatment. We report a surgical approach that we applied to six cases of distal nail embedding involving pain or deformity of nails caused by a nail tip invaginating into the nail bed and/or cessation of forward nail growth. As our method involves removing a portion of the embedded tip edge nail and inserting the removed nail into the remaining depressed portion, the nail can grow over the bulge. In all six patients in whom we applied this method, the pain and nail deformity resolved and there was no recurrence. We used autogenous nails, which can reduce the pressure imbalance on a nail bed, and this contributed to improving the morphology of nails and nail beds. In addition, the risk of a hypertrophied nail is reduced because half of the nail adheres to the nail bed. Special materials are unnecessary and this method can be conducted with simple outpatient department procedures. There were no cases of a fixed nail section detaching due to a bulge at the nail tip. The inserted nail was maintained in all cases for several months until the nail grew over the bulge.
Pollen analysis of cavity‐nesting bees (Hymenoptera: Anthophila) and their food webs in a city
Authors: da Rocha‐Filho Léo C. , Montagnana Paula C. , Araújo Thayane N. , Moure‐Oliveira Diego , Boscolo Danilo , Garófalo Carlos A. 
Published: October 2021

1. Urban areas can host speciose bee communities due partially to the species‐rich combination of both native and alien plant species found in these landscapes. However, in intensively‐constructed zones, it could be expected to record a low plant diversity used by bees because of the high proportion of paved surfaces in these areas.2. We investigated the influence of urbanisation on the cavity‐nesting bee‐plant community and interaction network structures in a medium‐sized city. The floral diversity used by nesting females in cell provisioning was retrieved from the pollen content obtained from trap‐nests collected in 11 sites located in an urban landscape gradient.3. Eighty pollen types belonging to 20 families were identified in the 155 pollen samples analysed. At least seven alien plant species were identified in samples from all sampling points. The landscape analysis revealed a positive influence of the proportion of green areas on the pollen type richness, although the null model was also selected as best model. Likewise, all network metrics but connectance were not influenced by any of the landscape variables.4. Our findings demonstrated that notwithstanding the sampling sites the floral diversity used by bees and the alien pollen type richness were similar. Likewise, the bee‐plant networks were modular, asymmetric, and highly specialised. The positive adaptation that cavity‐nesting bee species present in urban environments and the presence of bee species that can explore a diverse flora may indicate that the local variation in the landscape had little influence on their interactions with plants.
Applications of a conceptual framework to assess climate controls of forest tree diseases
Authors: Hennon Paul E. , Frankel Susan J. , Woods Alex J. , Worrall James J. , Ramsfield Tod D. , Zambino Paul J. , Shaw Dave C. , Ritóková Gabriela , Warwell Marcus V. , Norlander Daniel , Mulvey Robin L. , Shaw Charles G. 
Published: October 2021

AbstractA conceptual framework for climate involvement in forest tree diseases was applied to seven examples to demonstrate its suitability for different disease types: cases where climate favours pathogen biology which then leads to tree mortality or where diseases are caused primarily by climate‐driven physiological injury or stress to trees. Hypotheses for climate involvement are derived from detection and monitoring data to express associations of weather or climate factors with disease development at several spatial and temporal scales. Research findings contribute to an understanding of temperature, precipitation and related climate variables that influence biotic and abiotic diseases. To demonstrate use of the framework, we accessed information from the literature which exposed data and information gaps. Among various simulated approaches to test associations of climate and disease, we found disease risk factor models that use climate inputs derived from monitoring and research provide the best understanding of climate–disease relationships. These model outputs project future disease scenarios that can be used to inform climate adaptation strategies. Conservation and management implications for current and likely future climatic conditions are provided for each disease example. The most common guidance in managed landscapes is to move the imperilled tree species to areas of lower projected climate risk and to favour non‐host, climate‐adapted tree species where the disease is occurring.
A fatal case of COVID‐19‐associated acute necrotizing encephalopathy
Authors: Ziemele Dace , Ķauķe Gundega , Skrējāne Krista , Jaunozoliņa Līga , Karelis Guntis 
Published: October 2021

AbstractIntroductionAn increasing number of published reports on SARS‐CoV‐2 neurological manifestations have revealed a wide spectrum of symptoms, diagnostic features, and outcomes. We report a fatal case of a COVID‐19‐associated acute necrotizing encephalopathy (ANE).Case reportWe report a 70‐year‐old man brought to the hospital after a generalized tonic‐clonic seizure. He was confused and disoriented. Nasopharyngeal swab testing for SARS‐CoV‐2 was positive. A head computed tomography (CT) scan and cerebrospinal fluid (CSF) analysis showed no signs of acute pathology. After recurrent seizures, he was sedated and intubated. Throughout the days that followed he remained in a therapeutic coma. After discontinuation of sedatives, he remained unconscious. A repeated head CT scan showed signs of pontine edema, and brain magnetic resonance imaging (MRI) revealed inhomogeneous hyperintensities with microhemorrhages and small autonecrotic cavities in both thalami, brain stem, and cerebellar peduncles. With a high suspicion of a COVID‐19‐associated ANE, the patient was started on high‐dose glucocorticoids; however, he died the next day. The CSF tested negative for SARS‐CoV‐2.DiscussionA variety of COVID‐19 neurological manifestations have been reported to date, including various forms of encephalitis and encephalopathy. In our patient, encephalopathy with seizures was the presenting symptom of SARS‐CoV‐2 infection. The radiological findings on days 8 and 9 were consistent with an ANE. The precise pathogenesis of ANE remains unclear; however, an immune‐mediated mechanism is suspected. Early diagnostics with prompt administration of immunomodulators may be lifesaving. Suspicion of a COVID‐19‐related encephalopathy/encephalitis should be raised in all patients with altered mental status, seizures, and/or coma.
Short‐chain fatty acids during pregnancy in multiple sclerosis: A prospective cohort study
Authors: Cuello Juan Pablo , Martínez Ginés María Luisa , García Domínguez José Manuel , Tejeda‐Velarde Amalia , Lozano Ros Alberto , Higueras Yolanda , Meldaña Rivera Ariana , Goicochea Briceño Haydee , Garcia‐Tizon Santiago , de León‐Luis Juan , Medina Heras Silvia , Fernández Velasco José Ignacio , Pérez‐Pérez Silvia , García‐Martínez María Ángel , Pardo‐Rodríguez Beatriz , Domínguez‐Mozo María Inmaculada , García‐Calvo Estefanía , Estévez Héctor , Luque‐García Jose Luis , Villar Luisa Maria , Alvarez‐Lafuente Roberto 
Published: October 2021

AbstractBackground and purposeShort‐chain fatty acids (SCFAs) can have pro‐ or anti‐inflammatory properties, but their relationship with multiple sclerosis (MS) relapses during pregnancy remains unknown. This study aimed to explore SCFA profiles in MS patients during pregnancy and to assess their association with the appearance of relapses during pregnancy and postpartum.MethodsWe prospectively included 53 pregnant MS patients and 21 healthy control women. Patients were evaluated during pregnancy and puerperium. SCFAs were measured by liquid chromatography–mass spectrometry.ResultsSixteen patients (32%) had relapses during pregnancy or puerperium, and 37 (68%) did not. All MS patients showed significant increases in acetate levels during pregnancy and the postpartum period compared to non‐MS women. However, propionate and butyrate values were associated with disease activity. Their values were higher in nonrelapsing patients and remained similar to the control group in relapsing patients. The variable that best identified active patients was the propionate/acetate ratio. Ratios of <0.36 during the first trimester were associated with higher inflammatory activity (odds ratio = 165, 95% confidence interval = 10.2–239.4, p < 0.01). Most nonrelapsing patients showed values of >0.36, which were similar to those in healthy pregnant women.ConclusionsLow propionate/acetate ratio values during the first trimester of gestation identified MS patients at risk of relapses during pregnancy and the postpartum period.
Synthesizing drivers of fish functional responses across species
Authors: Buba Yehezkel , DeLong John P , Belmaker Jonathan 
Published: October 2021

AbstractFishes are subject to numerous stressors, including climate change, fishing and impacts by alien species. One of the challenges in understanding species and community responses to these stressors is identifying how they modify predator–prey interactions, a key process shaping aquatic food webs. Here, we aim to synthesize how species traits, such as size, activity level and alien status, and environmental factors, such as water temperature, shape the functional response: the change in predator consumption rate in relation to changes in prey density. We compiled over 300 fish functional responses and examined sources of variation in two key parameters dictating its shape: handling times and space clearance rates. We found that compared to cold waters, warmer waters were characterized by decreased handling times and increased space clearance rates for smaller predators, but had an opposite effect for bigger predators, suggesting that, across species, altered predation rates may underlie the decrease in size at higher temperatures (the temperature‐size rule). We also found that the negative effect of increased temperature on the functional response of larger predators is more pronounced in active species. Finally, we found that known alien species do not exhibit different functional response parameters when examined on their native prey, suggesting that alien species are not primed for invasion via their high functional response. Together, these asymmetric changes imply that, across species, warmer waters may alter predator–prey relationships differentially according to predator size, prey size and activity levels.