bluuebunny/crossref_metadata_2025_split huggingface dataset:
Multisystem inflammatory syndrome in adults: Characteristics, treatment, and outcomes
Authors: Lai Chih‐Cheng , Hsu Chi‐Kuei , Hsueh Shun‐Chung , Yen Muh‐Yong , Ko Wen‐Chien , Hsueh Po‐Ren 
Published: December 2022

AbstractFollowing the rapidly increasing number of multisystem inflammatory syndromes in children (MIS‐C), a similar clinical scenario has been observed in adult patients. Although its prevalence is low and probably related to underdiagnosis, its development can be associated with high mortality. Multisystem inflammatory syndrome in adults (MIS‐A) can develop following both asymptomatic and symptomatic severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) infection and in previously healthy people. Like MIS‐C, MIS‐A is a multisystem disease that can involve the cardiovascular, respiratory, gastrointestinal, dermatologic, hematologic, and neurologic systems. In addition to the clinical manifestations, the diagnosis of MIS‐A requires laboratory evidence of inflammation and SARS‐CoV‐2 infection. The appropriate treatment for MIS‐A remains unclear; anti‐inflammatory agents, including intravenous immunoglobulin and corticosteroids, are commonly used. However, there are still many unknowns regarding MIS‐A. Further studies are needed to determine the true prevalence, pathogenesis, and effective treatment for MIS‐A.
Shared genetics and causal associations between COVID‐19 and multiple sclerosis
Authors: Baranova Ancha , Cao Hongbao , Teng Shaolei , Su Kuan‐Pin , Zhang Fuquan 
Published: December 2022

AbstractNeuroinflammation caused by COVID‐19 negatively impacts brain metabolism and function, while pre‐existing brain pathology may contribute to individuals' vulnerability to the adverse consequences of COVID‐19. We used summary statistics from genome‐wide association studies (GWAS) to perform Mendelian randomization (MR) analyses, thus assessing potential associations between multiple sclerosis (MS) and two COVID‐19 outcomes (severe acute respiratory syndrome coronavirus 2 [SARS‐CoV‐2] infection and COVID‐19 hospitalization). Genome‐wide risk genes were compared between the GWAS datasets on hospitalized COVID‐19 and MS. Literature‐based analysis was conducted to construct molecular pathways connecting MS and COVID‐19. We found that genetic liability to MS confers a causal effect on hospitalized COVID‐19 (odd ratio [OR]: 1.09, 95% confidence interval: 1.03−1.16) but not on SARS‐CoV‐2 infection (1.03, 1.00−1.05). Genetic liability to hospitalized COVID‐19 confers a causal effect on MS (1.15, 1.02−1.30). Hospitalized COVID‐19 and MS share five risk genes within two loci, including TNFAIP8, HSD17B4, CDC37, PDE4A, and KEAP1. Pathway analysis identified a panel of immunity‐related genes that may mediate the links between MS and COVID‐19. Our study suggests that MS was associated with a 9% increased risk for COVID‐19 hospitalization, while hospitalized COVID‐19 was associated with a 15% increased risk for MS. Immunity‐related pathways may underlie the link between MS on COVID‐19.
Thought experiments: No argument here—We need more of them
Authors: Gardner William L. 
Published: December 2022

SummaryThought experiments are defined by Aguinis et al. as “judgments about what would happen if an imagined scenario were real.” They demonstrated through a multidisciplinary literature review that thought experiments have been used productively to generate and test theory in a wide variety of fields, including psychology, economics, medicine, sociology, marketing, and finance. Despite their utility, they concluded that thought experiments are vastly underutilized within the field of organizational behavior (OB). They go on to present a taxonomy of four basic types based on a theory's stage of development (early vs. late) and a study's theoretical objective (confirmation vs. disconfirmation). To help OB scholars effectively apply thought experiments, they provided a decision‐tree for evaluating the potential utility of a thought experiment and which of the four types would be most appropriate. Next, they advanced a set of best‐practice recommendations and showed how they could be applied within the domain of workplace allyship. Rather than contesting these points in this “counterpoint” article, I seek to reinforce them, as I have no argument against the notion that thought experiments are powerful methodological tools for advancing and testing theory that are underutilized by OB scholars. Nonetheless, I contend that given their definition of thought experiments, more OB works have employed them than surfaced from their review, and I provide three examples that their search terms missed. Finally, to bolster their overarching points, I explore how the theory generated in these three conceptual articles could have been strengthened through more extensive applications of their best‐practice recommendations.
Intraseasonal‐to‐seasonal evolution of soil moisture‐based droughts and floods in observation‐based datasets and Coupled Model Intercomparison Project Phase 6 models
Authors: Wei Jiangfeng , Su Weitao , Song Yuanyuan , Sun Shanlei , Zhou Botao , Chen Haishan 
Published: December 2022

AbstractDroughts and floods are extreme events that have tremendous socioeconomic impact. Many studies have investigated their possible variations under the effects of climate changes, while their intraseasonal‐to‐seasonal characteristics have received less attention. Based on observation‐constrained monthly soil moisture (SM) datasets since 1980, we analysed the spatiotemporal characteristics of global SM at the intraseasonal‐to‐seasonal time scales and the associated influencing factors. The results were then used to evaluate the performance of simulations by Coupled Model Intercomparison Project Phase 6 (CMIP6) models. It is found that the frequencies of extreme wet events are slightly higher than those of extreme dry events, but their spatial distributions are similar and are both affected by precipitation variability. Extreme events tend to have longer durations than nonextreme events, and their global mean durations are 4–5 months. Globally, dry events persist longer than wet events. Maximum SM anomalies are strongly affected by earlier precipitation and this effect is stronger in a transitional climate. The onset and peak times of SM anomalies in a year occur most frequently near the peak time of precipitation rather than that of SM. Approximately half of CMIP6 models overestimate the durations of both dry and wet events and approximately one third of models only underestimate wet events durations. Different versions of the same model produce similar event durations. The findings of this study enhance understanding of the intraseasonal‐to‐seasonal variabilities of global droughts and floods and could provide guidance for future study of land–atmosphere interactions and prediction of extreme events.
Who are the founders of venture capital‐backed initial public offering companies in the United States?
Authors: Zhu Jinjing 
Published: December 2022

AbstractPrior research acknowledged the importance of founders in affecting firm strategy and performance, but large empirical analyses of profiles of entrepreneurial founders are scant, in part because of the difficulty in collecting founder data. This study represents the first effort to study entrepreneurial founders across half a century. Using a hand‐collected unique and comprehensive dataset, this research sheds light on the demographic, educational, and career characteristics of founders for the venture capital (VC)‐backed initial public offering (IPO) companies during 1960–2015. The research has useful implications for researchers and practitioners. By understanding who the founders are and where they come from, this article scratches the surface of founder characteristics and firm performance from which further work could build on and provides useful information for founders who are likely to seek VC‐funding and IPO to build realistic expectations, VC firms who are interested in investing in potentially rewarding and promising new ventures to select good targets, and governments that struggle to promote entrepreneurial efforts and enhance economic development, in general, to come up with appropriate policies.
A systematic literature review and bibliometric analysis of research on COVID‐19 in strategy journals
Authors: Guyottot Olivier , Le Fur Eric 
Published: December 2022

AbstractThis article presents a literature review and a bibliometric analysis of academic research on COVID‐19 in strategy journals. The research topic is highly relevant considering the importance and the impact of the COVID‐19 pandemic on companies' strategies worldwide and the fact that this pandemic has represented at the same time danger and opportunity for companies. The study comprises a review of 241 articles published in peer‐reviewed journals from 2020 to the first quarter of 2022. Bibliometric and science mapping methods apply indicators identifying the most prominent journals, authors, countries, institutions, and topics. This approach allows a literature review highlighting the importance of five clusters on the COVID‐19 impact on strategy journals: entrepreneurship, innovation, digital transformation, leadership, and resilience. They are strongly interrelated, and this study shows there are still many areas for further research within and outside these clusters. COVID‐19 context offers perfect conditions to test theories and implement new research projects considering the high risk for other events of this type in the future.
Effect of 3D printing conditions and post‐printing fermentation on pearl millet fortified idli
Authors: Raja Vijayakumar , Moses Jeyan Arthur , Anandharamakrishnan Chinnaswamy 
Published: December 2022

AbstractBACKGROUNDThree‐dimensional (3D) printing is an emerging technology with numerous applications in the development of novel foods to meet personalized and special dietary needs. Using 3D printing, foods with modified textures and consistency can be prepared conveniently. In this work, an indigenous rice–black gram batter was fortified with pearl millet flour and 3D printed in the in‐house developed extrusion‐based food printer, Controlled Additive‐manufacturing Robotic Kit (CARK™). The impact of material supply composition was investigated along with optimization of different printing parameters and an in‐depth analysis of post‐printing fermentation kinetics was undertaken. The shape changes in the 3D printed constructs during fermentation were analyzed using a pixel‐count‐based image‐processing technique that correlates with the change in surface area.RESULTSThe addition of millet flour resulted in accelerated fermentation. At 20% w/w level, better printability with higher precision and layer definition was obtained at 800 mm min−1 of printing speed, 360 rpm extrusion motor speed, and 1.22 mm nozzle diameter with an extrusion rate of 15.57 mm3 s−1. The constructs of pearl millet flour (PMF) fortified idli batter have shown good structural stability and creep recovery. Fermentation‐assisted shape change was found to be significantly influenced by infill levels. Both raw and steamed constructs with 40% infill showed around 37% lower hardness than 100% infill constructs due to a porous inner structure with reduced expansion in the surface area/volume during fermentation.CONCLUSIONThe results of the study provide insights into the scope of printing fermented foods through the food‐to‐food fortification approach and textural modification of foods using 3D printing by varying the infill levels. © 2022 Society of Chemical Industry.
Impact of endolymphatic hydrops on DPOAE in subjects with normal to mild hearing loss
Authors: Inagaki Kei , Yoshida Tadao , Kobayashi Masumi , Sugimoto Satofumi , Fukunaga Yukari , Hara Daisuke , Naganawa Shinji , Sone Michihiko 
Published: December 2022

AbstractObjectiveThe increased endolymph volume affects a shift in the organ of Corti and basilar membrane in ears with endolymphatic hydrops (EH), which might affect distortion‐product otoacoustic emissions (DPOAE) by altering the operating point of the outer hair cells. We investigated how changes in DPOAE are related to the distribution site of EH.Study DesignProspective study.MethodsAmong 403 patients with hearing or vestibular symptoms who underwent contrast‐enhanced magnetic resonance imaging (MRI) for the diagnosis of EH and subsequent DPOAE testing, subjects whose hearing levels on pure tone audiometry were ≤35 dB at all frequencies were included in this study. In patients with EH on MRI, the presence and amplitude of DPOAE were evaluated between groups with hearing levels of ≤25 dB at all frequencies versus hearing levels of >25 dB at one or more frequencies.ResultsThere were no differences in the distribution of EH between groups. The amplitude of DPOAE had no clear correlation with the presence of EH. However, in both groups, there was a significantly higher probability of the presence of a DPOAE response from 1001 to 6006 Hz in cases with EH in the cochlea.ConclusionAmong patients whose hearing levels were ≤35 dB at all frequencies, better responses on DPOAE testing were found in subjects with EH in the cochlea. Alteration of DPOAEs in the early stages of hearing impairment could indicate morphological changes in the inner ear with altered basilar membrane compliance due to EH.Level of Evidence4
High ebullitive, millennial‐aged greenhouse gas emissions from thermokarst expansion of peatland lakes in boreal western Canada
Authors: Kuhn McKenzie A. , Schmidt Megan , Heffernan Liam , Stührenberg Jördis , Knorr Klaus‐Holger , Estop‐Aragonés Cristian , Broder Tanja , Gonzalez Moguel Regina , Douglas Peter M. J. , Olefeldt David 
Published: December 2022

AbstractMethane (CH4) and carbon dioxide (CO2) emissions from small peatland lakes may be highly sensitive to climate warming and thermokarst expansion caused by permafrost thaw. We studied effects of thermokarst expansion on ebullitive CH4 and CO2 fluxes and diffusive CH4 fluxes from a peatland thaw lake in boreal western Canada. Ebullitive CH4 fluxes from the thaw edge (236 ± 61 mg CH4 m−2 d−1) were double and quadruple that of the stable lake edge and center, respectively. Modeled diffusive CH4 fluxes did not differ between the thawing and stable edges (~ 50 mg CH4 m−2 d−1) but were double that of the center. Radiocarbon (14C) analysis of CH4 and CO2 bubbles from the thaw edge was older (~ 1211 and 1420 14C yr BP) than from the stable edge and the center (modern to ~ 102 and 50 14C yr BP, respectively). Incubations indicated that deep, old peat sediment was more labile along the thaw edge than in the center. While our study suggested increase CH4 emissions partly derived from millennial‐aged carbon along the thaw edge, accounting for these emissions only increased the estimated total lake CH4 emissions by ~ 10%, which is a much smaller contribution than measured from thermokarst lakes in yedoma regions. Our study suggests that it is important to account for landscape history and lake types when studying the processes that govern the sensitivity of lake greenhouse gas emissions to climate change.
Molecular Property Prediction with Photonic Chip‐Based Machine Learning
Authors: Zhang Hui , Lau Jonathan Wei Zhong , Wan Lingxiao , Shi Liang , Shi Yuzhi , Cai Hong , Luo Xianshu , Lo Guo‐Qiang , Lee Chee‐Kong , Kwek Leong Chuan , Liu Ai Qun 
Published: December 2022

AbstractMachine learning methods have revolutionized the discovery process of new molecules and materials. However, the intensive training process of neural networks for molecules with ever‐increasing complexity has resulted in exponential growth in computation cost, leading to long simulation time and high energy consumption. Photonic chip technology offers an alternative platform for implementing neural networks with faster data processing and lower energy usage compared to digital computers. Photonics technology is naturally capable of implementing complex‐valued neural networks at no additional hardware cost. Here, the capability of photonic neural networks for predicting the quantum mechanical properties of molecules is demonstrated. To the best of knowledge, this work is the first to harness photonic technology for machine learning applications in computational chemistry and molecular sciences, such as drug discovery and materials design. It is further shown that multiple properties can be learned simultaneously in a photonic chip via a multi‐task regression learning algorithm, which is also the first of its kind as well, as most previous works focus on implementing a network in the classification task.
Severi varieties on blow‐ups of the symmetric square of an elliptic curve
Authors: Ciliberto Ciro , Dedieu Thomas , Galati Concettina , Knutsen Andreas Leopold 
Published: December 2022

AbstractWe prove that certain Severi varieties of nodal curves of positive genus on general blow‐ups of the twofold symmetric product of a general elliptic curve are nonempty and smooth of the expected dimension. This result, besides its intrinsic value, is an important preliminary step for the proof of nonemptiness of Severi varieties on general Enriques surfaces.
ARASsort: A new sorting based multiple attribute decision‐making algorithm
Authors: Gül Sait 
Published: December 2022

AbstractMultiple attribute decision‐making (MADM) tools can effectively support the decision analysts in selecting the best alternative among many, ranking the alternatives in decreasing or increasing order of preference, or allocating the alternatives into pre‐defined ordered classes/categories. Even though the literature provides the analyst with precious sorting‐based MADM tools such as PROMSORT, UTADIS, AHPSort, TOPSISsort, and so forth, the majority of the methods can be found complex and hard to be understood by the researchers and practitioners who are not familiar with the mathematical notions and computations of MADM (distance calculation, threshold and preference function determination, and so on). To provide a simpler but powerful MADM tool aiming at sorting the alternatives into classes, this study proposes a sorting‐based additive ratio assessment algorithm which is called ARASsort. For limiting (interval‐based) and central (reference‐based) profiles describing the categories, we have developed two algorithms: ARASsort‐lp and ARASsort‐cp, respectively. Their applicability was shown in two examples: green supplier evaluation and economic freedom evaluation of countries. The validity of algorithms was presented by demonstrating the class assignment similarities between the results obtained by ARASsort, VIKORsort, and TOPSISsort. The findings show that ARASsort works well because it shows a higher level of class assignment similarities with the other methods.
Report of A Family with Adult‐Onset Leukoencephalopathy with Axonal Spheroids and Pigmented Glia (ALSP) Without Mutations in CSF1R, AARS1 or AARS2
Authors: Dulski Jarosław , Koga Shunsuke , Dickson Dennis W. , Wszolek Zbigniew K. 
Published: December 2022

ABSTRACTBackgroundAdult‐onset leukoencephalopathy with axonal spheroids and pigmented glia (ALSP) is a rare neurodegenerative disorder with characteristic clinicopathological features. Identification of pathogenic mutations in CSF1R, AARS1, and AARS2 genes led to increased recognition and diagnosis of the ALSP.ObjectivesThis paper presents the first family with typical clinical, radiological, and pathological features of ALSP, yet negative for CSF1R, AARS1, and AARS2 mutations.MethodsThe index case was a 30‐year‐old male who presented with gait difficulty, followed by cognitive decline and incontinence.ResultsNeurological examination evidenced progressive dementia, dysarthria, spasticity, parkinsonism, and severe gait disturbances. Brain MRI showed confluent white matter abnormalities with scattered foci of restricted diffusion, and atrophy of the corpus callosum. He was suspected of ALSP; however, the extensive genetic work‐up did not find pathogenic mutation. He died at 33 years, and brain autopsy was performed. He had myelin staining pallor and axonal swellings, spheroids, and pigmented glia in affected white matter. His father developed similar symptoms in his early 40s and died at 46 years. Neuropathological examination also confirmed ALSP diagnosis. We found two similar cases in the literature with typical ALSP features but negative for CSF1R mutation; however, none were tested for AARS1 and AARS2 mutations.ConclusionsWe draw attention to a new entity within the ALSP disease spectrum that needs further investigation. As the disease‐modifying therapy is already available for ALSP‐CSF1R, there is a strong need to identify the genetic cause of patients such as these in the ALSP spectrum, enabling research toward implementing effective treatment.
Type 2 Diabetes and Parkinson's Disease: A Focused Review of Current Concepts
Authors: Cullinane Patrick W. , de Pablo Fernandez Eduardo , König Annekatrin , Outeiro Tiago Fleming , Jaunmuktane Zane , Warner Thomas T. 
Published: December 2022

AbstractHighly reproducible epidemiological evidence shows that type 2 diabetes (T2D) increases the risk and rate of progression of Parkinson's disease (PD), and crucially, the repurposing of certain antidiabetic medications for the treatment of PD has shown early promise in clinical trials, suggesting that the effects of T2D on PD pathogenesis may be modifiable. The high prevalence of T2D means that a significant proportion of patients with PD may benefit from personalized antidiabetic treatment approaches that also confer neuroprotective benefits. Therefore, there is an immediate need to better understand the mechanistic relation between these conditions and the specific molecular pathways affected by T2D in the brain. Although there is considerable evidence that processes such as insulin signaling, mitochondrial function, autophagy, and inflammation are involved in the pathogenesis of both PD and T2D, the primary aim of this review is to highlight the evidence showing that T2D‐associated dysregulation of these pathways occurs not only in the periphery but also in the brain and how this may facilitate neurodegeneration in PD. We also discuss the challenges involved in disentangling the complex relationship between T2D, insulin resistance, and PD, as well as important questions for further research. © 2022 International Parkinson and Movement Disorder Society.
Benchmark accuracy of predicted NMR observables for quadrupolar 14N and 17O nuclei in molecular crystals
Authors: Hartman Joshua D. , Spock Lilian E. , Harper James K. 
Published: December 2022

AbstractNuclear quadrupole resonances for
and 17O nuclei are exquisitely sensitive to interactions with surrounding atoms. As a result, nitrogen and oxygen solid‐state nuclear magnetic resonance (ssNMR) provides a powerful tool for investigating structure and dynamics in complex systems. First‐principles calculations are increasingly used to facilitate spectral assignment and to evaluate and adjust crystal structures. Recent work combining the strengths of planewave density functional theory (DFT) calculations with a single molecule correction obtained using a higher level of theory has proven successful in improving the accuracy of predicted chemical shielding (CS) tensors and 17O quadrupolar coupling constants (
). Here we extend this work by examining the accuracy of predicted 14N and 17O electric field gradient (EFG) tensor components obtained using alternative planewave‐corrections involving cluster and two‐body fragment‐based calculations. We benchmark the accuracy of CS and EFG tensor predictions for both nitrogen and oxygen using planewave, two‐body fragment, and enhanced planewave‐corrected techniques. Combining planewave and two‐body fragment calculations reduces the error in predicted 17O
values by 35% relative to traditional planewave calculations. These enhanced planewave‐correction methods improve the accuracy of 17O and 14N EFG tensor components by 15% relative to planewave DFT but yield minimal improvement relative to a simple molecular correction. However, in structural environments involving either high symmetry or strong intermolecular interactions, enhanced planewave‐corrected methods provide a distinct advantage.