bluuebunny/crossref_metadata_2025_split huggingface dataset:
Increasing number of implantation failures and pregnancy losses associated with elevated Th1/Th2 cell ratio
Authors: Kuroda Keiji , Nakagawa Koji , Horikawa Takashi , Moriyama Azusa , Ojiro Yuko , Takamizawa Satoru , Ochiai Asako , Matsumura Yuko , Ikemoto Yuko , Yamaguchi Koushi , Sugiyama Rikikazu 
Published: April 2021

AbstractProblemWe aimed to assess whether an imbalance of T‐helper (Th) 1 and Th2 cells contributes to implantation failure and pregnancy loss.Method of studyIn this cross‐sectional study, 197 consecutive patients with a history of repeated implantation failure (RIF) after three or more embryo transfer (ET) cycles and/or recurrent pregnancy loss (RPL) after two or more clinical pregnancy losses underwent Th cell testing. After excluding 42 women aged ≥44 and 9 with vitamin D supplementation, we recruited 146 women including 79 with RIF and 81 with RPL. Fourteen women had a history of both RIF and RPL. We also recruited 45 fertile women and 40 general infertile women without a history of in vitro fertilization treatment. This study was approved by the local ethics committee.ResultsThere was no significant difference in IFN‐γ‐producing Th1 and IL‐4‐producing Th2 cell levels between the fertile and general infertile women, but Th1 cell levels and the Th1/Th2 cell ratio were significantly higher in the women with ≥4 ET cycles and ≥2 pregnancy losses than in the fertile and general infertile women. In the general infertile women, the total livebirth rates including natural conception after two ET cycles in the normal and high Th1/Th2 groups (Th1/Th2 <11.8 and ≥11.8, respectively) were 66.7% and 87.5%, respectively (p = .395).ConclusionsA high Th1/Th2 cell ratio was linked to ≥4 implantation failure cycles and ≥2 pregnancy losses but not to general infertility.
Systematic review of machine learning models for personalised dosing of heparin
Authors: Falconer Nazanin , Abdel‐Hafez Ahmad , Scott Ian A. , Marxen Sven , Canaris Stephen , Barras Michael 
Published: April 2021

AimTo identify and critically appraise studies of prediction models, developed using machine learning (ML) methods, for determining the optimal dosing of unfractionated heparin (UFH).MethodsEmbase, PubMed, CINAHL, Web of Science, International Pharmaceutical Abstracts and IEEE Xplore databases were searched from inception to 31 January 2020 to identify relevant studies using key search terms synonymous with artificial intelligence or ML, ‘prediction’, ‘dose’, ‘activated partial thromboplastin time (aPTT)’ and ‘UFH.’ Studies had to have used ML methods for developing models that predicted optimal dose of UFH or target therapeutic aPTT levels in the hospital setting. The CHARMS Checklist was used to assess quality and risk of bias of included studies.ResultsOf 8393 retrieved abstracts, 61 underwent full text review and eight studies met inclusion criteria. Four studies described models for predicting aPTT, three studies described models predicting optimal dose of heparin during dialysis and one study described a model that used surrogate outcomes of clotting and bleeding to predict a therapeutic aPTT. Studies varied widely in reporting of study participants, feature characterisation and selection, handling of missing data, sample size calculations and the intended clinical application of the model. Only one study conducted an external validation and no studies evaluated model impacts in clinical practice.ConclusionStudies of ML models for UFH dosing are few and none report a model ready for routine clinical use. Existing studies are limited by low methodological quality, inadequate reporting of study factors and absence of external validation and impact analysis.
Relations among positivity, positive affect in school, and learning flow in elementary school students: A longitudinal mediation model
Authors: Wu Renshuang , Huebner Eugene Scott , Zhou Jianhua , Tian Lili 
Published: April 2021

BackgroundLearning flow is an optimal learning experience representing full engagement in one’s studies. The belief–affect–engagement model and control‐value theory suggest that positivity would be a motivator of learning flow, while positive affect in school would be a mediator of the relation between positivity and learning flow.AimsThe current research aimed to examine (1) the longitudinal relations among positivity, positive affect in school, and learning flow, and (2) the mediational role of positive affect in school between positivity and learning flow.Sample and MethodA sample of 4681 Chinese elementary school students (44.9% girls; Mage = 9.87 years, SD = 0.70 at Time 1) completed reliable measures for each construct on four occasions across 2 years, using 6‐month intervals. Structural equation modelling was used for examining study hypotheses.ResultsAfter controlling for gender, age, and family socioeconomic status, the results showed that (1) positivity, positive affect in school, and learning flow reciprocally facilitated each other directly; (2) positive affect in school mediated the relation between positivity and later learning flow, as well as the relation between learning flow and later positivity.ConclusionsThese findings revealed that positivity, positive affect in school, and learning flow form a complex, dynamic system, suggesting that school professionals should consider monitoring and developing interventions based upon these variables as early as elementary school.
Interleukin‐1β exacerbates disease and is a potential therapeutic target to reduce pulmonary inflammation during severe influenza A virus infection
Authors: Bawazeer Abdulah OS , Rosli Sarah , Harpur Christopher M , Docherty Callum AH , Mansell Ashley , Tate Michelle D 
Published: April 2021

AbstractHyperinflammatory responses including the production of NLRP3‐dependent interleukin (IL)‐1β is a characteristic feature of severe and fatal influenza A virus (IAV) infections. The NLRP3 inflammasome has been shown to play a temporal role during severe IAV immune responses, with early protective and later detrimental responses. However, the specific contribution of IL‐1β in modulating IAV diseasein vivois currently not well defined. Here, we identified that activation of NLRP3‐dependent IL‐1β responses occurs rapidly following HKx31 H3N2 infection, prior to the onset of severe IAV disease. Mature IL‐1β was detectablein vivoin both hemopoietic and nonhemopoietic cells. Significantly, therapeutic inhibition of IL‐1β in the airways with intranasal anti‐IL‐1β antibody treatment from day 3 postinfection, corresponding to the onset of clinical signs of disease, significantly prolonged survival and reduced inflammation in the airways. Importantly, early targeting of IL‐1β from day 1 postinfection also improved survival. Together, these studies specifically define a role for IL‐1β in contributing to the development of hyperinflammation and disease and indicate that targeting IL‐1β is a potential therapeutic strategy for severe IAV infections.
Classification and analysis of outcome predictors in non‐critically ill COVID‐19 patients
Authors: Venturini Sergio , Orso Daniele , Cugini Francesco , Crapis Massimo , Fossati Sara , Callegari Astrid , Pellis Tommaso , Tonizzo Maurizio , Grembiale Alessandro , Rosso Alessia , Tamburrini Mario , D'Andrea Natascia , Vetrugno Luigi , Bove Tiziana 
Published: April 2021

AbstractBackgroundEarly detection of severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2)‐infected patients who could develop a severe form of COVID‐19 must be considered of great importance to carry out adequate care and optimise the use of limited resources.AimsTo use several machine learning classification models to analyse a series of non‐critically ill COVID‐19 patients admitted to a general medicine ward to verify if any clinical variables recorded could predict the clinical outcome.MethodsWe retrospectively analysed non‐critically ill patients with COVID‐19 admitted to the general ward of the hospital in Pordenone from 1 March 2020 to 30 April 2020. Patients' characteristics were compared based on clinical outcomes. Through several machine learning classification models, some predictors for clinical outcome were detected.ResultsIn the considered period, we analysed 176 consecutive patients admitted: 119 (67.6%) were discharged, 35 (19.9%) dead and 22 (12.5%) were transferred to intensive care unit. The most accurate models were a random forest model (M2) and a conditional inference tree model (M5) (accuracy = 0.79; 95% confidence interval 0.64–0.90, for both). For M2, glomerular filtration rate and creatinine were the most accurate predictors for the outcome, followed by age and fraction‐inspired oxygen. For M5, serum sodium, body temperature and arterial pressure of oxygen and inspiratory fraction of oxygen ratio were the most reliable predictors.ConclusionsIn non‐critically ill COVID‐19 patients admitted to a medical ward, glomerular filtration rate, creatinine and serum sodium were promising predictors for the clinical outcome. Some factors not determined by COVID‐19, such as age or dementia, influence clinical outcomes.
LncRNA PWAR6 regulates proliferation and migration by epigenetically silencing YAP1 in tumorigenesis of pancreatic ductal adenocarcinoma
Authors: Huang Shanshan , Li Yaqi , Hu Jinhua , Li Li , Liu Zhen , Guo Hui , Jiang Bailing , Chen Jun , Li Junhe , Xiang Xiaojun , Deng Jun , Xiong Jianping 
Published: April 2021

AbstractLong non‐coding RNAs (lncRNAs) are a novel class of regulators in multiple cancer biological processes. However, the functions of lncRNAs in pancreatic ductal adenocarcinoma (PDAC) remain largely unknown. In this study, we identified PWAR6 as a frequently down‐regulated lncRNA in PDAC samples as well as a panel of pancreatic cancer cell lines. Down‐regulated PWAR6 was associated with multiple clinical outcomes, including advanced tumour stage, distant metastasis, and overall survival of PDAC patients. In our cell‐based assays, ectopic expression of PWAR6 dramatically repressed PDAC cells proliferation, invasion and migration, accelerated apoptosis, and induced cell cycle arrest at G0/G1 phase. In contrast, depletion of PWAR6 mediated by siRNA exhibited opposite effects on PDAC cell behaviours. In vivo study further validated the anti‐tumour role of PWAR6 in PDAC. By taking advantage of available online sources, we also identified YAP1 as a potential PWAR6 target gene. Negative correlation between YAP1 and PWAR6 expressions were observed in both online database and our PDAC samples. Notably, rescue experiments further indicated that YAP1 is an important downstream effector involved in PWAR6‐mediated functions. Mechanistically, PWAR6 could bind to methyltransferase EZH2, a core component of Polycomb Repressive Complex 2 (PRC2) in regulating gene expression, and scaffold EZH2 to the promoter region of YAP1, resulting in epigenetic repression of YAP1. In conclusion, our data manifest the vital roles of PWAR6 in PDAC tumorigenesis and underscore the potential of PWAR6 as a promising target for PDAC diagnosis and therapy.
Macrophage‐derived exosomes mediate silica‐induced pulmonary fibrosis by activating fibroblast in an endoplasmic reticulum stress‐dependent manner
Authors: Qin Xiaofeng , Lin Xiaofang , Liu Lang , Li Ying , Li Xiang , Deng Zhenghao , Chen Huiping , Chen Hui , Niu Zhiyuan , Li Zisheng , Hu Yongbin 
Published: April 2021

AbstractMacrophages play a key role in silicosis, and exosomes are potent mediators of intercellular communication. This suggests that macrophage‐derived exosomes have a potential contribution to the pathogenesis of silicosis. To investigate whether macrophage‐derived exosomes promote or inhibit lung fibrosis, in vitro, silica‐exposed macrophage‐derived exosomes (SiO2‐Exos) were collected and cocultured with fibroblasts. The expression of collagen I and α‐SMA was evaluated. Furthermore, the endoplasmic reticulum (ER) stress markers BIP, XBP1s and P‐eIF2α were assessed after treatment with or without the ER stress inhibitor 4‐PBA. In vivo, mice were pre‐treated with the exosome secretion inhibitor GW4869 prior to silica exposure. After sacrifice, lung tissues were histologically examined, and the expression of proinflammatory cytokines (TNF‐α, IL‐1β and IL‐6) in bronchoalveolar lavage fluid (BALF) was measured. The results showed that the expression of collagen I and α‐SMA was up‐regulated after treatment with SiO2‐Exos, accompanied by increased expression of BIP, XBP1s and P‐eIF2α. Pre‐treatment with 4‐PBA reversed this effect. More importantly, an in vivo study demonstrated that pre‐treatment with GW4869 decreased lung fibrosis and the expression of TNF‐α, IL‐1β and IL‐6 in BALF. These results suggested that SiO2‐Exos are profibrogenic and that the facilitating effect is dependent on ER stress.
VA home‐based primary care interdisciplinary team structure varies with Veterans' needs, aligns with PACE regulation
Authors: Chan Caitlin S. , Davis Darlene , Cooper Dayna , Edes Thomas , Phibbs Ciaran S. , Intrator Orna , Kinosian Bruce 
Published: April 2021

AbstractBackgroundInterdisciplinary team (IDT) care is central to home‐based primary care (HBPC) of frail elders. Traditionally, all HBPC disciplines managed a patient (Full IDT), a costly approach to maintain. The recent PACE (Program of All‐inclusive Care for the Elderly) regulation provides for a flexible approach of annual assessments from a core team with involvement of additional disciplines dependent upon patient needs (Core+). Current Department of Veterans Affairs (VA) HBPC guidance specifies Full IDTs care for medically complex and functionally impaired Veterans similar to PACE participants. We evaluated whether VA HBPC has adopted the flexible structure of the PACE regulation, aligned to Veteran needs.DesignCross‐sectional analysis.SettingAll 139 VA HBPC programs administered across 379 sites.ParticipantsAbout 55,173 Veterans enrolled in HBPC during fiscal year 2018.MeasurementsPatients' HBPC physician, nurse, psychologist/psychiatrist, social worker, therapist, dietitian, and pharmacist visits were grouped into interdisciplinary team types. Patient frailty was classified using VA HNHR v2 (High‐Need High‐Risk version 2, a measure of high, medium, and low risk of long‐term institutionalization). Medical complexity was measured by clusters of impairment in the JEN frailty index (JFI). JFI clusters were validated by VA's Nosos measure to project cost and Care Assessment Need (CAN) measure of hospitalization and mortality risk.ResultsHBPC provided Full IDT care to 21%, Core+ care to 54%, and Home Health+ (HHA+) care (skilled home health services plus additional disciplines, without primary care) to 16% of Veterans. Team type was associated with medical complexity (X2 2863.5 [66 df], p < 0.0001). High‐risk Veterans (72% of sample) were more likely to receive Full IDT care (X2 62.9, 1 df), p < 0.0001), while low‐risk Veterans (28%) were more likely to receive HHA+ care (X2 314.8, 1 df, p < 0.0001).ConclusionThere is a strong association between HBPC team patterns and patient frailty, indicating tailoring of care to match Veteran needs.
First Impressions Stick: Market Entry Strategies and Category Priming in the Digital Domain
Authors: Aversa Paolo , Huyghe Annelore , Bonadio Giulia 
Published: April 2021

AbstractThe rise of the ‘digital age’ presents unique challenges for firms entering new markets and deciding ‘where’ to compete – a pivotal topic in corporate strategy. Particularly, it is not clear what the opportunities and implications are for digital new entrants as they position their disruptive business offerings in the category system, in particular vis‐à‐vis non‐market stakeholders. In this article, we qualitatively investigate how two icons of the ‘sharing economy’, Uber and BlaBlaCar, pursued two distinct categorization strategies which were incumbent‐focused and economic versus emergent‐focused and non‐economic. Our longitudinal comparative case study reveals how digital new entrants, through self‐categorization, can enduringly impact the nature of the responses of non‐market stakeholders. The mechanism at play is ‘category priming’ – the process of directing stakeholders’ selective attention towards, or away from, the commonalities shared with a specific market category – and its stickiness over time. In particular, the distinct categorization strategies primed stakeholders to focus (Uber) or not focus (BlaBlaCar) on similarities between the entrant and an established category, which triggered polarized responses from media and regulators and resulted in a ‘sticky’ association regardless of repositioning efforts. Our contribution dissects the constituents and consequences of these strategies and discusses implications for future research on digital market entry, strategic categorization, and business models.
Natural disasters, public housing, and the role of disaster aid
Authors: Davlasheridze Meri , Miao Qing 
Published: April 2021

AbstractIt has been widely recognized that socially disadvantaged populations are highly vulnerable to natural disasters. Nonetheless, little is known about how disasters affect housing affordability, particularly for those who depend on public housing. Using a national sample of counties over the period 2005–2016, this study examines the effects of flooding and federal disaster aid on the provision of public housing across the United States. We estimate a panel fixed‐effects model with an instrumental variable to account for the endogeneity of disaster aid. Results show that severe floods reduce the number of public housing units, prolong the average waiting time, and increase tenant‐paid rents for public housing. Meanwhile, we find that the Federal Emergency Management Agency's Public Assistance (PA) aid can help restore the supply of public housing and lower the rents paid by tenants in the aftermath of flood events. Our findings suggest that natural disasters place particularly high stress on the socially vulnerable, and post‐disaster aid can alleviate some of the adverse impact of disasters on those who depend on public housing.
Neural Representations of Task Context and Temporal Order During Action Sequence Execution
Authors: Shahnazian Danesh , Senoussi Mehdi , Krebs Ruth M. , Verguts Tom , Holroyd Clay B. 
Published: April 2021

AbstractRoutine action sequences can share a great deal of similarity in terms of their stimulus response mappings. As a consequence, their correct execution relies crucially on the ability to preserve contextual and temporal information. However, there are few empirical studies on the neural mechanism and the brain areas maintaining such information. To address this gap in the literature, we recently recorded the blood‐oxygen level dependent (BOLD) response in a newly developed coffee–tea making task. The task involves the execution of four action sequences that each comprise six consecutive decision states, which allows for examining the maintenance of contextual and temporal information. Here, we report a reanalysis of this dataset using a data‐driven approach, namely multivariate pattern analysis, that examines context‐dependent neural activity across several predefined regions of interest. Results highlight involvement of the inferior‐temporal gyrus and lateral prefrontal cortex in maintaining temporal and contextual information for the execution of hierarchically organized action sequences. Furthermore, temporal information seems to be more strongly encoded in areas over the left hemisphere.
Insights Into Thermal Transactions of a Novel Rotating Packed Bed
Authors: Saurabh  , Kumar Sandeep , Murthy D. S. 
Published: April 2021

Abstract
The field of the rotating packed bed (RPB) and its applications in the transfer processes are multidisciplinary in nature. The achievement of significant volume reduction by employing the RPB in distillation towers has been fairly established in the mass transfer domain. Nevertheless, the prospect of RPB in the heat transfer domain still remains dormant. The current work addresses this very issue by exploring the characteristics of thermal transactions across the novel RPB device. This study succinctly presents the related aspects with multi-phase flow of participating fluids in the counter-current direction across the porous, rotating packed bed structure. However, the simultaneous involvement of these multivariate intrinsic attributes makes the understanding of the transfer phenomenon quite complex upon viewing from the experimental perspective alone. Hence, the computational fluid dynamics (CFD) tool has been used for the assimilation of the physical understanding of the thermal transactions along with the effects of operating parameters. The thermal contours, main effect, and surface plots for heat transfer rate directly contribute toward a better appreciation of the thermal transaction mechanism and could be employed for suitable volume reduction in heat exchanger devices.
Analysis of Heat Transfer Enhancement in a Micro-Scale Heat Sink Structure
Authors: Long Wei , Song Zixuan , Ren Tao , Liu Yun 
Published: April 2021

Abstract
With the increasing power requirements of electronic devices, high heat flux will cause serious damage to the devices. Based on the basic theory of micro-nano heat transfer, the series and topological microchannel heat sink models are established. The flow field characteristics and temperature distribution in the heat sink are analyzed by numerical calculation. The effects of channel structure on temperature, pressure drop, the Nusselt number, and enhanced heat transfer factor are compared, and the micro-mechanism of heat transfer enhancement in microchannels is clarified. It is found that the Nusselt number of the flow field can be significantly increased by adding the triangular groove in the microchannel, and the enhanced heat transfer factor in the channel can be greatly improved by the topological structure. Further analysis of the factors such as angle α, diameter ratios γ, and topological structures of the triangular groove shows that when α = 70 deg, the Nusselt number of the flow field is 3.1 times of that of the straight channel and the enhanced heat transfer factor is 2.7 times of that of it; compared with the straight channel, the comprehensive heat transfer performance of the microchannel with γ = 1/2 is improved by 31%; when using variable cross-sectional topology microchannel with triangle structure (T.Tr.N.) topology, the convective heat transfer of the microchannel is 2.6 times of that of the straight channel and the comprehensive heat transfer performance is increased by 5.9 times.