bluuebunny/crossref_metadata_2025_split huggingface dataset:
Rnf144b alleviates the inflammatory responses and cardiac dysfunction in sepsis
Authors: Guo Rennan , Wang Jingjing , Tang Wen , Xiao Dong 
Published: April 2023

AbstractAimsSepsis is an inflammatory disease with high mortality and morbidity. Inflammation plays an essential role in sepsis, and suppressing inflammation has been shown to ameliorate sepsis. Rnf144b is an ubiquitin E3 ligation with anti‐inflammation activities. Its precise roles in sepsis remain unknown. Here, we explored the function of Rnf144b in sepsis.Methods and resultsWe generated conditional knockout mice with Rnf144b deficiency in the myeloid cells. We monitored the Rnf144b expression in peripheral blood mononuclear cells from healthy donor and patients with sepsis, and in lipopolysaccharides (LPS)‐treated bone marrow‐derived macrophages (BMDMs). The cytokine expression between wild‐type BMDMs and Rnf144b‐deficient BMDMs after LPS and CpG treatments was compared. The survival rate and cardiac function were monitored. The activation of TANK binding kinase 1 and nuclear factor kappa‐B was examined by Western blot and real‐time PCR. Up‐regulated expression of Rnf144b was observed in peripheral blood mononuclear cells from patients with sepsis. LPS induced the expression of Rnf144b in BMDMs. Rnf144b‐deficient BMDMs produced more inflammatory cytokines after LPS or CpG stimulation. Septic mice with Rnf144b deficiency in myeloid cells had higher mortality and exacerbated cardiac dysfunction. Rnf144b interacted with TANK binding kinase 1 and Rnf144b deficiency resulted in impaired activation of TBK1 but enhanced activation of nuclear factor kappa‐B.ConclusionsRnf144b prevents inflammatory responses and cardiac dysfunction in sepsis.
Encapsulation of Microperoxidase‐8 into MIL‐101(Cr/Fe) Nanoparticles: A New Biocatalyst for the Epoxidation of Styrene
Authors: Kesse Xavier , Sicard Clémence , Steunou Nathalie , Mahy Jean‐Pierre , Ricoux Rémy 
Published: April 2023

AbstractA new biocatalyst MP8@MIL‐101(Cr/Fe) was prepared by immobilization of a heme octapeptide, Microperoxidase 8 (MP8) within a mixed metal MOF, MIL‐101(Cr/Fe). Both MIL‐101(Cr/Fe) and MP8@MIL‐101(Cr/Fe) were characterized by PXRD, FTIR spectroscopy and TGA. The catalytic activity of MP8@MIL‐101(Cr/Fe) for the oxidation of styrene by H2O2 and tBuOOH was then examined under various reaction conditions (nature of the co‐solvent and of the oxidant, concentration of the oxidant and of the substrate, time, pH) and compared to that of MP8 alone. Under the best conditions used, MP8@MIL‐101(Cr/Fe) was then shown to catalyze the oxidation of styrene about 3 times more efficiently than MP8 alone with approximately 50 % selectivity for styrene oxide.
Lung cancer subtyping from gene expression data using general and enhanced Fuzzy min–max neural networks
Authors: Singh Yashpal , Susan Seba 
Published: April 2023

AbstractIn this article, we address the problem of lung cancer diagnosis from gene expression data, which is now recognized as an effective means for early treatment and prevention of cancer. Specifically, we employ Fuzzy min–max (FMM) classifier for the task which is a well‐known neuro‐fuzzy neural network. The idea is to take advantage of the fuzzy class definitions whose boundaries are set using the min–max hyperbox constructed for each class. We implement two advanced FMM neural network architectures: general Fuzzy min–max (GFMM) and enhanced Fuzzy min–max (EFMM) for the classification of lung cancer subtypes from gene expression data. The advantage of GFMM is that it involves very simple operations for hyperbox manipulation, and can handle both labeled and unlabeled data. On the other hand, EFMM proposes three heuristic rules related to hyperbox expansion, contraction and the overlap test, which enhances the learning algorithm. We perform the classification of gene expression data using these two models, and then we analyze the performance by visualizing the hyperboxes obtained after training, and compare the accuracies of these classifiers with the state of the art. Least absolute shrinkage and selection operator (LASSO) is used for selecting the informative genes from the high‐dimensional gene expression data. From the empirical results, we observe that GFMM with LASSO gives the best performance of all, with validation accuracy of 98.04% and cross‐validation accuracy of 94.06%.
Simulation of spatially varying ground motion of urban buildings based on wavelet packet neural network
Authors: Du Zhenyu , Guo Tong , Wang Jishuai , Yu Shuqi 
Published: April 2023

AbstractSite‐structure cluster interaction (SSCI) has a significant effect on the seismic response of densely distributed buildings, and rationally and effectively quantifying its effect when modelling the urban seismic damage can provide more optimal decisions to mitigate earthquake disasters. This paper focuses on the input motion of the structures, by extracting the main influential parameters of SSCI and adopting the loosely typed wavelet packet neural network to rapidly simulate the spatially varying ground motion in the urban environment. In the proposed framework, the wavelet packet energy ratio is presented to describe the variation of ground motion characteristics and used as the sole output to carry out the multi‐resolution spectral modulation, and the training samples were accumulated by a validated finite element simulation method. The developed surrogate model considers the effects of a series of factors, including the earthquake intensity, site condition, configuration of structure cluster, structural dynamic characteristics and spacing, and is superior to the one using conventional artificial neural network. It is verified by a virtual test that the waveshape and spectral features of the predicted ground motion agree well with the target result with an error of peak acceleration being only 1.23%. The suggested approach has the advantages of better modulation precision and lower sample size requirement. Moreover, it is almost zero cost to use the developed surrogate model to correct the ground motion of urban buildings and to consider the influence of SSCI, and the structural seismic response can be more factually displayed in the time and space domains. These specialties make it a promising technique in the rapid assessment of urban seismic damage.
Numerical analysis of phase change material filled with metal foam inside a cylindrical capsule
Authors: Asker Mustafa , Al‐Rawi Mohammad , Genceli Hadi 
Published: April 2023

AbstractThis research study performs a numerical assessment of the inward solidification of phase change material (PCM) integrated with metal foam (MF) encapsulated in a horizontal cylindrical geometry. The cylinder is not at melting temperature at the beginning, and its outer surface is subjected to convection boundary conditions. The 1D phase change model is resolved by applying the temperature transforming technique using an in‐house computer program written in C++. Four different MF materials, aluminum, copper, nickel, and stainless steel, with various porosities, are used to examine the thermal behavior of the storage system. It is found that the use of copper as a MF with higher effective thermal conductivity remarkably enhances the elapsed time for complete solidification. Additionally, for a porosity value of 0.92, the time for total solidification of copper is diminished by 94%, while the complete solidification time for Stainless Steel is decreased by 65% in comparison to the situation where no MF is used.
To Understand Inequity, Bioethics Needs to Sort Things Out
Authors: Cho Mildred K. 
Published: April 2023

AbstractBioethics is reexamining how to implement diversity, equity, inclusion, and justice concerns into scholarship. However, bioethicists should question the categories used to define diversity. The act of categorization is value laden, and classification systems confer power and benefits and generate harms. For example, what conditions count as disabilities? We should consider the equity implications of offering only “male” and “female” options for self‐identification in health records. However, we should also interrogate all ideas about categorization, including how categories are formed, why they are formed, and who decides. Bioethicists cannot comprehend fully what equity and justice mean for underrepresented, underserved, or marginalized people until there is an understanding of how the boundaries of marginalization are created.
Love Your Patient as Yourself: On Reviving the Broken Heart of American Medical Ethics
Authors: Tate Tyler , Clair Joseph 
Published: April 2023

AbstractThis article presents a radical claim: American medical ethics is broken, and it needs love to be healed. Due to a unique set of cultural and economic pressures, American medical ethics has adopted a mechanistic mode of ethical reasoning epitomized by the doctrine of principlism. This mode of reasoning divorces clinicians from both their patients and themselves. This results in clinicians who can ace ethics questions on multiple‐choice tests but who fail either to recognize a patient's humanity or to navigate the ethical quandaries into which they are frequently thrown. Drawing on personal experience as well as the philosophical work of Augustine of Hippo, Simone Weil, and Iris Murdoch, we propose a novel ethical approach grounded in a conception of neighbor love, specifically, the virtue of love understood as attention to a sufferer's humanity. We conclude with five practical recommendations for reimagining medical ethics education oriented around the virtue of love.
Automated labelling of radiology reports using natural language processing: Comparison of traditional and newer methods
Authors: Chng Seo Yi , Tern Paul J. W. , Kan Matthew R. X. , Cheng Lionel T. E. 
Published: April 2023

AbstractAutomated labelling of radiology reports using natural language processing allows for the labelling of ground truth for large datasets of radiological studies that are required for training of computer vision models. This paper explains the necessary data preprocessing steps, reviews the main methods for automated labelling and compares their performance. There are four main methods of automated labelling, namely: (1) rules‐based text‐matching algorithms, (2) conventional machine learning models, (3) neural network models and (4) Bidirectional Encoder Representations from Transformers (BERT) models. Rules‐based labellers perform a brute force search against manually curated keywords and are able to achieve high F1 scores. However, they require proper handling of negative words. Machine learning models require preprocessing that involves tokenization and vectorization of text into numerical vectors. Multilabel classification approaches are required in labelling radiology reports and conventional models can achieve good performance if they have large enough training sets. Deep learning models make use of connected neural networks, often a long short‐term memory network, and are similarly able to achieve good performance if trained on a large data set. BERT is a transformer‐based model that utilizes attention. Pretrained BERT models only require fine‐tuning with small data sets. In particular, domain‐specific BERT models can achieve superior performance compared with the other methods for automated labelling.
Is Asian flushing syndrome a disadvantage in the labor market?
Authors: Kawaguchi Daiji , Lee Jungmin , Lin Ming‐Jen , Yokoyama Izumi 
Published: April 2023

AbstractA large fraction of people in East Asia are incapable of digesting alcohol because of a genetic deficiency. This study examines whether the variation in alcohol tolerance contributes to inequality in the labor market. We conduct our original surveys in Japan, Taiwan, and Korea with the measurement of respondents' degree of alcohol tolerance by a bio‐marker test. We find that alcohol‐tolerant men consume significantly more alcohol, but their earnings and hours worked do not differ from those of alcohol‐intolerant men. Despite a prevalent view that drinking alcohol is indispensable to establish good relationships with colleagues and business partners, our results suggest that there is no systematic impact of alcohol tolerance on labor market outcomes.
Coriolis force impact on the magnetorotating fluid radiating from a moving porous upright plate with viscous dissipation
Authors: Venkateswarlu B. , Satya Narayana P. V. 
Published: April 2023

AbstractThe effects of wall velocity and radiating Coriolis force (CF) on convective flow over a moving porous vertical plate in a rotating fluid due to a magnetic field and viscous dissipation have been investigated. Assume that the resiliency impact emerges from a combination of concentration and temperature. Utilizing the convenient affinity renovations, the nonlinear partial differential equations are renewed into ordinary differential equations, which are solved numerically by a resourceful shooting technique using the Range–Kutta–Fehlberg scheme. The results are inspected and illustrated graphically for a choice of stream factors on the speed, warmth, and concentration profiles, as well as the shear and couple pressures and the rates of heat and mass exchange at the plate. It can be noted that the reading of the CF reveals that the temperature and concentration fields show opposing tendencies to the velocity profiles. The heat and concentration fields decrease with increasing wall velocity, but the velocity profiles react in the opposite direction. The goal of this review is to determine the impacts of Coriolis and wall velocity causes in terms of geography, which are the deflection of airplanes, winds, missiles, and currents in the ocean. Moreover, the effects of Coriolis power are given more attention in practical designs and applications of rotating systems imposed through flow.
Influence of thermophoretic deposition and viscous dissipation on magnetohydrodynamic flow with variable viscosity and thermal conductivity
Authors: Das Utpal Jyoti , Majumdar Nayan Mani , Patgiri Indushri 
Published: April 2023

AbstractIn this study, we numerically explore the impact of varying viscosity and thermal conductivity on a magnetohydrodynamic flow problem over a moving nonisothermal vertical plate with thermophoretic effect and viscous dissipation. The boundary conditions and flow‐regulating equations are converted into ordinary differential equations with the aid of similarity substitution. The MATLAB bvp4c solver is used to evaluate the numerical solution of the problem and it is validated by executing the numerical solution with previously published studies. The impacts of several factors, including the magnetic parameter, Eckert number, heat source parameter, thermal conductivity parameter, stratification parameter, Soret, Dufour, Prandtl number, and Schmidt number are calculated and shown graphically. Also, the skin friction coefficient, Nusselt number, and Sherwood number are calculated. Fluid velocity, temperature, and concentration significantly drop as the thermophoretic parameter and thermal stratification parameter increases. As thermal conductivity rises, it is seen that the velocity of the fluid and temperature inside the boundary layer rise as well. Also, the Soret effect drops temperature and concentration profile. The applications of this type of problem are found in the processes of nuclear reactors, corrosion of heat exchangers, lubrication theory, and so forth.
The predictive power of commodity prices for future economic growth: Evaluating the role of economic development
Authors: Enilov Martin 
Published: April 2023

AbstractThis paper investigates the extent to which commodity prices can predict economic growth, the growth exposure of the countries to specific commodity group, and whether the country stage of development matters for growth dependency on commodities. We use a novel time‐varying mixed‐frequency vector autoregressive model to jointly estimate causality between monthly commodity prices and quarterly economic growth for the period from January 1980 to March 2020. Our findings suggest that growth dependency on commodities varies over time and across different synthetic measures, but in general solid evidence of predictability is determined. The overall commodity index shows better performance in predicting economic growth than the segregated proxies of either fuel or non‐fuel commodities in developed economies. However, the overall commodity index is as effective as the fuel index in predicting economic growth for their developing counterparts. We develop a new index of global commodity growth connectivity (GCGCI) to determine the economic growth dependency on commodities over time. Our results show that economic growth dependency on commodities has increased at least three times with financialization of commodity markets. The GCGCI for all commodities reveals a higher growth dependency on commodities in developing countries than developed ones in the post‐financialization period. Interestingly, we find that growth decreases its reliance on fuel commodities in both developed and developing countries after financialization of commodity markets. Our findings bear implications for policymakers to design stabilization policies in an attempt to protect economies vulnerable to commodity price shocks and lay the foundation for sustainable economic growth.
Regression discontinuity design with multivalued treatments
Authors: Caetano Carolina , Caetano Gregorio , Carlos Escanciano Juan 
Published: April 2023

SummaryWe study identification and estimation in the regression discontinuity design with a multivalued treatment. We show that heterogeneity in the first stage discontinuities can be used for the identification of the marginal treatment effects under an alternative assumption, namely, the homogeneity of the LATEs along some covariates. This assumption can often be tested and relaxed. Our estimator can be programmed as a simple two‐stage least squares regression, and packaged standard errors and tests can also be used. We apply our method to estimate the effect of Medicare insurance coverage on health care utilization.
Revaluation of overselected stimuli: Emergence of control by underselected stimuli depends on degree of overselectivity
Authors: Gomes‐Ng Stephanie , Kim Peter B. C. , Cowie Sarah , Elliffe Douglas 
Published: April 2023

AbstractStimulus overselectivity describes strong control by one stimulus element at the expense of other equally relevant elements. Research suggests that control by underselected stimuli emerges following extinction of the overselected stimulus (“revaluation”) and the emergence is larger when overselectivity is greater. We compared such revaluation effects with a control compound or condition in two experiments. Human participants chose between compound S+ and S‐ stimuli. Then, to assess control by compound‐stimulus elements, participants chose between individual elements in a testing phase without feedback. The S+ element chosen most often (the overselected element) underwent revaluation, during which choice of that element was extinguished and choice of a novel element reinforced. Thereafter, participants completed a retesting phase. Revaluation reduced choice of the overselected element. Choice of the underselected element decreased for participants with low overselectivity but increased for participants with high overselectivity. This was not the case for a control compound that did not undergo revaluation (Experiments 1 and 2) or in a control condition in which the overselected element continued to be reinforced during revaluation (Experiment 2). These findings suggest that overselectivity levels may modulate revaluation effects, and they also highlight the importance of the contingency change in postrevaluation changes in stimulus control.
Blood biochemistry parameters of Broad snouted caiman, Caiman latirostris subjected to stress conditions, appliying micro‐volume techniques
Authors: Moleón María Soledad , Santiago Gonzalo , Hilevski Samuel , Siroski Pablo Ariel 
Published: April 2023

AbstractPlasma biochemistry values represent a crucial and minimally invasive tool for evaluating nutritional and physiological condition of the animal. Biochemical data provides valuable information in those species exposed to environmental stressors. In this study, we aimed to apply for the first time micro‐volume plasma tests to measured total plasma protein, albumin, and glucose in juvenile Caiman latirostris and to compare our results with other studies reporting crocodilian biochemistry values. We found that caimans from heat treatment were heavier, longer and had higher levels of glucose than those from the control group. Conversely, food restricted caimans had less growth, body condition and had 32.1% lower albumin concentrations than those from the control group. While no significant differences were observed in any parameters measured from water restricted caimans compared with control group. The values obtained for each of the biochemical determinations were lower than those previously reported for adult of C. latirostris, but similar finding for protein concentration compared with Alligator mississippiensis. Micro technique offers the advantage of increasing information and at the same time a greater physiological understanding of the crocodilians species.
Outcomes and performance of risk scores in acute lower gastrointestinal bleeding
Authors: Saleepol Aniwat , Kaosombatwattana Uayporn 
Published: April 2023

AbstractBackground and AimTreatment of acute lower gastrointestinal bleeding (LGIB) remains problematic, and clinical data is limited compared to that of upper GIB. This study aimed to describe the clinical outcomes and predictors of rebleeding and validate the performance of proposed scoring systems in patients with acute overt LGIB.MethodsPatients with LGIB who underwent colonoscopies between 2013 and 2018 were retrospectively reviewed. Overt LGIB patients who presented within 72 h after bleeding onset were included. Demographics, comorbidities, initial management, endoscopic finding, and treatment outcomes were collected. Factors associated with rebleeding were explored, and the performance of Oakland, NOBLAD, and Strate scores regarding mortality and rebleeding were validated.ResultsA total of 537 patients from 3402 (age 72 years, 63–80) were included. Of this, 53% took antithrombotic agents and 59% required red cell transfusion, with a median of 4 red cell units. The most common diagnoses were diverticular bleeding (31.3%) and colorectal polyp/cancer (28.9%). The median time to colonoscopy was 2.3 days, and 80.3% of patients did not receive any hemostatic intervention. The 30‐day mortality and rebleeding were 2.6% and 18.3%, respectively. Patients with radiation proctitis, angioectasia, diverticulosis and using dual antiplatelet drugs were associated with recurrent bleeding. The risk scores showed low performance in predicting recurrent bleeding and mortality.ConclusionAcute, overt LGIB was common among elders with comorbidities. The rebleeding risk was mostly linked to underlying lesions and the use of antiplatelet drugs. The performance of current risk stratification scores remains unsatisfactory and requires further development.