bluuebunny/crossref_metadata_2025_split huggingface dataset:
Synergism of rMV-Hu191 with cisplatin to treat gastric cancer by acid sphingomyelinase-mediated apoptosis requiring integrity of lipid raft microdomains
Authors: Lv Yao , Zhang Chu-di , Wang Yi-long , Zhou Dong-ming , Zhu Meng-ying , Hao Xiao-qiang , Wang Jin-hu , Gu Wei-zhong , Shen Hong-qiang , Lou Jin-gan , Wu Ben-qing , Chen Pei-chun , Zhao Zheng-yan 
Published: July 2021

AbstractBackgroundDDP-based chemotherapy is one of the first-line treatment in GC. However, the therapeutic efficacy of DDP is limited due to side effects. Therefore, it is of great significance to develop novel adjuvants to synergize with DDP. We had demonstrated previously that rMV-Hu191 had antitumor activity in GC. Here we examined the synergism of rMV-Hu191 with DDP in vitro and in vivo.MethodsCellular proliferation, the synergistic effect and cell apoptosis were evaluated by CCK-8 assay, ZIP analysis and flow cytometry, respectively. The protein levels and location of ASMase were monitored by western blot and immunofluorescence assay. shRNA and imipramine were used to regulate the expression and activity of ASMase. MβCD was administrated to disrupt lipid rafts. Mice bearing GC xenografts were used to confirm the synergism in vivo.ResultsFrom our data, combinational therapy demonstrated synergistic cytotoxicity both in resistant GC cell lines from a Chinese patient and drug-nonresistant GC cell lines, and increased cell apoptosis, instead of viral replication. Integrity of lipid rafts and ASMase were required for rMV-Hu191- and combination-induced apoptosis. The ASMase was delivered to the lipid raft microdomains at the initial stage of rMV-Hu191 treatment. In vivo GC mice xenografts confirmed the synergism of combinational treatment, together with increased apoptosis and trivial side-effects.ConclusionsThis is the first study to demonstrate that rMV-Hu191 combined with DDP could be used as a potential therapeutic strategy in GC treatment and the ASMase and the integrity of lipid rafts are required for the synergistic effects.
Influence of growing up in the city or near an airport on the physiological stress of tree sparrow nestlings (Passer montanus)
Authors: Redondo Iraida , Muriel Jaime , de Castro Díaz Cristina , Aguirre José I. , Gil Diego , Pérez-Rodríguez Lorenzo 
Published: July 2021

AbstractUrbanization constitutes one of the major transformations of natural habitats, creating new areas characterized by multiple potential wildlife stressors. Birds that live in highly anthropized zones are confronted with physiological and behavioural challenges caused by these stressors. Here, we investigated if several health parameters differed between three subpopulations of tree sparrow nestlings subjected to different levels of anthropogenic pollution, and particularly noise pollution: a quiet rural area, a noisy rural area adjacent to an airport and a heavily urbanized area. We compared body condition, oxidative stress markers and baseline corticosterone levels, expecting urban nestlings to be in overall worse condition as compared to rural (rural and rural airport) birds. In addition, we expected nestlings exposed to aircraft noise to show intermediate stress levels. We found that rural-airport nestlings had the highest levels of antioxidant capacity of plasma and did not differ from rural counterparts in the rest of the parameters. By contrast, urban nestlings were in slightly worse body condition and had lower antioxidant capacity than rural and rural-airport individuals. Our results suggest that aircraft noise does not constitute a significant stressor for nestlings. In contrast, urban conditions constitute a more challenging situation, negatively impacting different physiological systems. Although nestlings seem able to buffer these challenges in the short-term, further research should explore the long-term potential consequences of early exposure to these conditions.
How healthcare structures and communication delivery influence trust: a parallel-group randomized controlled trial
Authors: Cantarutti Stephen , Pothos Emmanuel M. 
Published: July 2021

AbstractBackgroundAccording to recent polling, public trust in the healthcare sector remains low relative to other industries globally. The implications of low healthcare trust permeate throughout the industry in a number of ways, most visibly by discouraging therapy compliance.MethodsThis study investigated four putative determinants of trust in healthcare-related scenarios: individuals vs. collective groups as communicators of healthcare advice; expert vs. laypeople as providers of healthcare communication; public vs. private healthcare sector; and positive vs. negative information. Two hundred seventy-four participants were recruited via Prolific Academic and were presented with four statements in random order, related to a positive reflection of the public healthcare sector, a negative reflection of the public healthcare sector, a positive reflection of the private healthcare sector and a negative reflection of the private healthcare sector. According to these reflection, participants were repeatedly asked to rate the system on its trustworthiness. Trust outcomes were constructed using a four-dimension framework, consisting of benevolence, reliability, competence and predictability.ResultsClaims relating to the public sector had a significantly stronger impact on benevolence and reliability than claims relating to the private sector; claims from individuals had a significantly stronger impact on all trust variables than claims from collectives; and claims from laypeople had a significantly greater impact on reliability and competence ratings than claims from experts.ConclusionsThe findings in this study offer insight into the patterns with which trust decisions are made in healthcare contexts. More importantly, this research offers a novel perspective of how different factors interact to affect the various facets of trust. These results provide a foundation for future study in this evolving area, and offer insights into designing effective communication strategies that cultivate greater levels of individual trust in the healthcare sector.
What is Causal Specificity About, and What is it Good for in Philosophy of Biology?
Authors: Ferreira Ruiz María 
Published: July 2021

AbstractThe concept of causal specificity is drawing considerable attention from philosophers of biology. It became the rationale for rejecting (and occasionally, accepting) a thesis of causal parity of developmental factors. This literature assumes that attributing specificity to causal relations is at least in principle a straightforward (if not systematic) task. However, the parity debate in philosophy of biology seems to be stuck at a point where it is not the biological details that will help move forward. In this paper, I take a step back to reexamine the very idea of causal specificity and its intended role in the parity dispute in philosophy of biology. I contend that the idea of causal specificity across variations as currently discussed in the literature is irreducibly twofold in nature: it is about two independent components that are not mutually entailed. I show this to be the source of prior complications with the notion of specificity itself that ultimately affect the purposes for which it is often invoked, notably to settle the parity dispute.
A scoping review of clinical reasoning research with Asian healthcare professionals
Authors: Lee Ching-Yi , Jenq Chang-Chyi , Chandratilake Madawa , Chen Julie , Chen Mi-Mi , Nishigori Hiroshi , Wajid Gohar , Yang Pai-Hsuang , Yusoff Muhamad Saiful Bahri , Monrouxe Lynn 
Published: July 2021

AbstractClinical reasoning is the thought process that guides practice. Although a plethora of clinical reasoning studies in healthcare professionals exists, the majority appear to originate from Western cultures. A scoping review was undertaken to examine clinical reasoning related research across Asian cultures. PubMed, SciVerse Scopus, Web of Science and Airiti Library databases were searched. Inclusion criteria included full-text articles published in Asian countries (2007 to 2019). Search terms included clinical reasoning, thinking process, differential diagnosis, decision making, problem-based learning, critical thinking, healthcare profession, institution, medical students and nursing students. After applying exclusion criteria, n = 240 were included in the review. The number of publications increased in 2012 (from 5%, n = 13 in 2011 to 9%, n = 22) with a steady increase onwards to 12% (n = 29) in 2016. South Korea published the most articles (19%, n = 46) followed by Iran (17%, n = 41). Nurse Education Today published 11% of the articles (n = 26), followed by BMC Medical Education (5%, n = 13). Nursing and Medical students account for the largest population groups studied. Analysis of the articles resulted in seven themes: Evaluation of existing courses (30%, n = 73) being the most frequently identified theme. Only seven comparative articles showed cultural implications, but none provided direct evidence of the impact of culture on clinical reasoning. We illuminate the potential necessity of further research in clinical reasoning, specifically with a focus on how clinical reasoning is affected by national culture. A better understanding of current clinical reasoning research in Asian cultures may assist curricula developers in establishing a culturally appropriate learning environment.
Evaluating longitudinal dispersion of scalars in rural channels of agro-urban environments
Authors: Peruzzi Cosimo , Galli Andrea , Chiaradia Enrico A. , Masseroni Daniele 
Published: July 2021

AbstractIn agro-urban environments, the water resource conveyed by rural channels is susceptible to a gradual impoverishment due to the continuous combined sewer overflow release, constituting a pending and urgent issue for water management companies and the entire community. Reliable one-dimensional longitudinal dispersion coefficients D are required to model and study the hydrodynamics and water quality patterns at the scale of rural channel networks. Empirical formulas are usually adopted to estimate D but the accuracy in the prediction could be questionable. In order to identify which are the most suitable formulas to determine D in rural channels, field tracer measurements were carried out in three rural channels with typical geometry and configuration. The obtained D values were then compared with the most commonly used predicting formulas that the literature provides. The accuracy of the predictors was further checked by simulating different flow rates inside the tested channels by using a one-dimensional hydraulic model. Starting from the obtained results, indications and guidelines to choose the most suitable formulas to predict D in rural channels were provided. These indications should be followed when developing realistic quality models in the agro-urban environments, especially in those cases where direct measurements of the longitudinal dispersion coefficient D are not available.
Modelling the Diffusion Coefficients of Dilute Gaseous Solutes in Hydrocarbon Liquids
Authors: Aljeshi Yasser A. , Taib Malyanah Binti Mohd , Trusler J. P. Martin 
Published: July 2021

AbstractIn this work, we present a model, based on rough hard-sphere theory, for the tracer diffusion coefficients of gaseous solutes in non-polar liquids. This work extends an earlier model developed specifically for carbon dioxide in hydrocarbon liquids and establishes a general correlation for gaseous solutes in non-polar liquids. The solutes considered were light hydrocarbons, carbon dioxide, nitrogen and argon, while the solvents were all hydrocarbon liquids. Application of the model requires knowledge of the temperature-dependent molar core volumes of the solute and solvent, which can be determined from pure-component viscosity data, and a temperature-independent roughness factor which can be determined from a single diffusion coefficient measurement in the system of interest. The new model was found to correlate the experimental data with an average absolute relative deviation of 2.7 %. The model also successfully represents computer-simulation data for tracer diffusion coefficients of hard-sphere mixtures and reduces to the expected form for self-diffusion when the solute and solvent become identical.
Variances of Surface Area Estimators Based on Pixel Configuration Counts
Authors: Kampf Jürgen 
Published: July 2021

AbstractThe surface area of a set which is only observed as a binary pixel image is often estimated by a weighted sum of pixel configurations counts. In this paper we examine these estimators in a design based setting—we assume that the observed set is shifted uniformly randomly. Bounds for the difference between the essential supremum and the essential infimum of such an estimator are derived, which imply that the variance is in $$O(t^2)$$

O
(

t
2

)

as the lattice distance t tends to zero. In particular, it is asymptotically neglectable compared to the bias. A simulation study shows that the theoretically derived convergence order is optimal in general, but further improvements are possible in special cases.
Gaussian processes with skewed Laplace spectral mixture kernels for long-term forecasting
Authors: Chen Kai , van Laarhoven Twan , Marchiori Elena 
Published: July 2021

AbstractLong-term forecasting involves predicting a horizon that is far ahead of the last observation. It is a problem of high practical relevance, for instance for companies in order to decide upon expensive long-term investments. Despite the recent progress and success of Gaussian processes (GPs) based on spectral mixture kernels, long-term forecasting remains a challenging problem for these kernels because they decay exponentially at large horizons. This is mainly due to their use of a mixture of Gaussians to model spectral densities. Characteristics of the signal important for long-term forecasting can be unravelled by investigating the distribution of the Fourier coefficients of (the training part of) the signal, which is non-smooth, heavy-tailed, sparse, and skewed. The heavy tail and skewness characteristics of such distributions in the spectral domain allow to capture long-range covariance of the signal in the time domain. Motivated by these observations, we propose to model spectral densities using a skewed Laplace spectral mixture (SLSM) due to the skewness of its peaks, sparsity, non-smoothness, and heavy tail characteristics. By applying the inverse Fourier Transform to this spectral density we obtain a new GP kernel for long-term forecasting. In addition, we adapt the lottery ticket method, originally developed to prune weights of a neural network, to GPs in order to automatically select the number of kernel components. Results of extensive experiments, including a multivariate time series, show the beneficial effect of the proposed SLSM kernel for long-term extrapolation and robustness to the choice of the number of mixture components.
Floods in Provence-Alpes-Côte d'Azur and lessons for French flood risk governance
Authors: Kougkoulos Ioannis , Merad Myriam , Cook Simon J. , Andredakis Ioannis 
Published: July 2021

AbstractFrance experiences catastrophic floods on a yearly basis, with significant societal impacts. In this study, we use multiple sources (insurance datasets, scientific articles, satellite data, and grey literature) to (1) analyze modern flood disasters in the PACA Region; (2) discuss the efficiency of French public policy instruments; (3) perform a SWOT analysis of French flood risk governance (FRG); and (4) suggest improvements to the FRG framework. Despite persistent government efforts, the impacts of flood events in the region have not lessened over time. Identical losses in the same locations are observed after repeated catastrophic events. Relative exposure to flooding has increased in France, apparently due to intense urbanization of flood-prone land. We suggest that the French FRG could benefit from the following improvements: (1) regular updates of risk prevention plans and tools; (2) the adoption of a build back better logic; (3) taking undeclared damages into account in flood risk models; (4) better communication between the actors at the different steps of each cycle (preparation, control, organization, etc.); (5) better communication between those responsible for risk prevention, emergency management, and disaster recovery; (6) an approach that extends the risk analysis outside the borders of the drainage basin; and (7) increased participation in FRG from local populations.
Marxism as Spinozism? One episode in the history of Soviet philosophy
Authors: Soboleva Maja 
Published: July 2021

AbstractThis paper seeks to reconstruct philosopher Aleksandr Bogdanov’s approach to the philosophy of Spinoza in the context of the debate against Plekhanov. I demonstrate that the Soviet interest in Spinoza’s theory has never been purely historical, but rather, it served an important function in developing the theoretical foundations for Marxist philosophy. However, Bogdanov was one of only a very few who objected strongly to Plekhanov’s attempt to relate Spinoza’s philosophy to Marxism in a direct way. Two principles underlie Bogdanov’s critique: one being methodological, the other—systematic. The methodological principle has a hermeneutical character, since it demands that we treat historical concepts by taking into account their context and their changes during the time. According to Bogdanov, failing to fulfil this principle results in the dogmatization and instrumentalization of philosophy, and transforms it into political doctrine. The systematic principle concerns Bogdanov’s radical rethinking of the relationship between extension and thought. I argue that by rethinking Spinoza’s concepts in the framework of “ideo-empirical parallelism”, Bogdanov develops his own theory of cognition, which he called “empiriomonism”. When considered in historical context, I argue that these debates can serve as a window into the foundational role the Spinoza’s philosophy has played in the formation of different versions of Russian Marxism, as well as in the development of Russian Marxism in general.
The effects of inflow of agricultural biogas digestate on bivalves’ behavior
Authors: Mbah Jasper Tembeck , Chmist-Sikorska Joanna , Szoszkiewicz Krzysztof , Czekała Wojciech 
Published: July 2021

AbstractThis study focused on the reaction of bivalve molluscs to biogas digestate, which is a waste product of an increasingly developing biogas production in rural areas worldwide. The effects of biogas digestate on aquatic organisms are not fully known, and neither this substance nor any types of manure were tested in the monitoring based on valvometry, which is a biomonitoring method based on bivalve behavior. The change in bivalves functioning in biogas digestate inflow was studied using three different diluted digestate concentrations. Exposure to the highest concentration of digestate induced a decline of mean shell opening and activity time of Unio tumidus species. A significant difference in behavioral patterns was recorded during the first 10 min after exposure to the digestate. A Gradual decreasing tendency of shell opening levels was apparent under the highest concentration reaching 55% compared to the pretreatment value. Also, a decreasing tendency was observed under the medium concentration (82.4% of initial level) after 2 h, while an increase in shell opening levels was recorded in the most diluted digestate. This research work proved that the inflow of biogas digestate has significant impact on bivalves’ behavior. Unio tumidus is a sensitive indicator of biogas digestate inflow in the aquatic environment. Moreover, it proved that the opening and closing activities over time depend on the concentration of the digestate. Therefore, the mollusk bivalves might be utilized in early warning systems to detect organic pollutants in water.
Three-dimensional deep learning with spatial erasing for unsupervised anomaly segmentation in brain MRI
Authors: Bengs Marcel , Behrendt Finn , Krüger Julia , Opfer Roland , Schlaefer Alexander 
Published: July 2021

Abstract

Purpose

Brain Magnetic Resonance Images (MRIs) are essential for the diagnosis of neurological diseases. Recently, deep learning methods for unsupervised anomaly detection (UAD) have been proposed for the analysis of brain MRI. These methods rely on healthy brain MRIs and eliminate the requirement of pixel-wise annotated data compared to supervised deep learning. While a wide range of methods for UAD have been proposed, these methods are mostly 2D and only learn from MRI slices, disregarding that brain lesions are inherently 3D and the spatial context of MRI volumes remains unexploited.

Methods

We investigate whether using increased spatial context by using MRI volumes combined with spatial erasing leads to improved unsupervised anomaly segmentation performance compared to learning from slices. We evaluate and compare 2D variational autoencoder (VAE) to their 3D counterpart, propose 3D input erasing, and systemically study the impact of the data set size on the performance.

Results

Using two publicly available segmentation data sets for evaluation, 3D VAEs outperform their 2D counterpart, highlighting the advantage of volumetric context. Also, our 3D erasing methods allow for further performance improvements. Our best performing 3D VAE with input erasing leads to an average DICE score of 31.40% compared to 25.76% for the 2D VAE.

Conclusions

We propose 3D deep learning methods for UAD in brain MRI combined with 3D erasing and demonstrate that 3D methods clearly outperform their 2D counterpart for anomaly segmentation. Also, our spatial erasing method allows for further performance improvements and reduces the requirement for large data sets.