bluuebunny/crossref_metadata_2025_split huggingface dataset:
EGFR-driven profibrotic signals in AKI-to-CKD transition are blocked by TNF inhibition: Opportunities for etanercept treatment
Authors: Abdelmageed Mai M , Kefaloyianni Eirini , Arthanarisami Akshayakeerthi , Khamissi Fatima Zohra , Atkinson Jeffrey J. , Herrlich Andreas 
Published: April 2021

AbstractProximal-tubule-cell EGFR activation mediates tubule cell proliferation and repair early after kidney injury, while sustained EGFR activation causes kidney fibrosis. Inflammation is a key driver of AKI-to-CKD transition and fibrosis, but mechanisms of EGFR-driven profibrotic responses are not well understood. In a mouse model of AKI-to-CKD transition and CKD progression, we show that EGFR-inhibition significantly reduced kidney expression of many immunoregulatory molecules already by day two after injury, including the potent inflammatory cytokine tumor-necrosis-factor (TNF). Single nuclei RNA-sequencing analysis showed that macrophages were among the main early cellular sources of TNF in the injured kidney.In vitro, EGFR activation in macrophages increased macrophage TNF expression, while EGFR inhibitionin vivoreduced kidney macrophage accumulation, as early as two days after injury. Thus, profibrotic EGFR signaling increases kidney TNF levels both directly and indirectly. TNF inhibition did not alter tubule EGFR activation and in contrast to EGFR inhibition did not reduce early macrophage accumulation in the kidney, suggesting that TNF does not promote early infiltration of immune cells in the kidney, but rather regulates profibrotic functions of kidney and/or immune cells. TNF inhibition with etanerceptin vivoin AKI-injured mice downregulated a number of cytokines, including TNF itself. This cytokine downregulation overlapped with EGFR inhibition, and additional non-overlapping downregulated cytokines shared the same functions, predicting that TNF inhibition would prevent AKI-to-CKD transition like EGFR inhibition. Indeed, TNF-inhibition with etanercept reduced AKI-induced fibrosis to the same degree as the EGFR-inhibition, while the combination of both treatments showed no additive effect. In conclusion, our results identify TNF as a downstream effector of profibrotic EGFR activation and motivate the examination of TNF pathway inhibition in human AKI or CKD.Translational statementProximal tubule epidermal-growth-factor (EGFR) activation in mice and likely also in humans drives inflammation in the kidney after acute-kidney-injury (AKI) and causes chronic-kidney-disease (CKD) with fibrosis in a process termed AKI-to-CKD transition. Recent retrospective data shows that patients treated with TNF inhibitors show decreased incidence and progression of CKD. Our current work shows that TNF inhibition in mice is equally as effective as EGFR inhibition in preventing AKI-to-CKD transition and fibrosis. Thus, our results have translational potential and may stimulate examination of short-term TNF inhibition in AKI to prevent AKI-to-CKD transition or possibly of longer-term TNF inhibition in CKD to prevent CKD progression.
Spatiotemporal patterns of neuronal subtype genesis suggest hierarchical development of retinal diversity
Authors: West Emma R. , Lapan Sylvain W. , Lee ChangHee , Kajderowicz Kathrin M. , Li Xihao , Cepko Connie L. 
Published: April 2021

AbstractHow do neuronal subtypes emerge during development? Recent molecular studies have expanded our knowledge of existing neuronal diversity. However, the genesis of neuronal subtypes remains elusive and previous studies have been limited by a lack of quantitative methods for simultaneous detection of subtype diversityin situ. The bipolar interneurons of the mammalian retina represent a diverse neuronal class, characterized by distinct functions, morphologies, and recently discovered transcriptional profiles. Here, we developed a comprehensive spatiotemporal map of bipolar subtype genesis in the retina. Combining multiplexed detection of 16 RNA markers with timed delivery of EdU and BrdU, we analyzed more than 30,000 single cells in full retinal sections to classify all bipolar subtypes and their birthdates. We found that bipolar subtype birthdates are ordered and follow a centrifugal developmental axis. Spatial analysis revealed a striking oscillatory wave pattern of bipolar subtype birthdates, and lineage analyses suggest clonal restriction on homotypic subtype production. These results inspired a hierarchical model of neuronal subtype genesis in the mammalian retina, with the wave pattern of subtype birthdates arising from early asymmetric cell divisions among founding retinal progenitor cells. Our results provide an outline of the developmental logic that generates diverse neuronal subtypes, and establishes a framework for studying subtype diversification.
Design of the recombinant influenza neuraminidase antigen is crucial for protective efficacy
Authors: Gao Jin , Klenow Laura , Parsons Lisa , Malik Tahir , Phue Je-Nie , Gao Zhizeng , Withers Stephen G. , Cipollo John , Daniels Robert , Wan Hongquan 
Published: April 2021

ABSTRACTSupplementing influenza vaccines with recombinant neuraminidase (rNA) remains a promising approach for improving the suboptimal efficacy. However, correlations among rNA designs, properties, and protection have not been systematically investigated. Here, we performed a comparative analysis of several rNAs produced from different construct designs using the baculovirus/insect cell system. The rNAs were designed with different tetramerization motifs and NA domains from a recent H1N1 vaccine strain (A/Brisbane/02/2018) and were analyzed for enzymatic properties, antigenicity, thermal and size stability, and protection in mice. We found that rNAs containing the NA head-domain versus the full-ectodomain possess distinct enzymatic properties and that the molecular size stability is tetramerization domain-dependent, whereas protection is more contingent on the combination of the tetramerization and NA domains. Following single-dose immunizations, a rNA possessing the full-ectodomain, non-native enzymatic activity, and the tetramerization motif from the human vasodilator-stimulated phosphoprotein provided substantially higher protection than a rNA possessing the head-domain, native activity and the same tetramerization motif. In contrast, these two rNAs provided comparable protection when the tetramerization motif was exchanged with the one from the tetrabrachion protein. These findings demonstrate that the rNA design is crucial for the protective efficacy and should be thoroughly evaluated for vaccine development, as the unpredictable nature of the heterologous domain combination can result in rNAs with similar key attributes but vastly differ in protection.IMPORTANCEFor several decades it has been proposed that influenza vaccines could be supplemented with recombinant neuraminidase (rNA) to improve the efficacy. However, some key questions for manufacturing stable and immunogenic rNA remain to be answered. We show here that the tetramerization motifs and NA domains included in the rNA construct design can have a profound impact on the biochemical, immunological and protective properties. We also show that the single-dose immunization regimen is more informative for assessing the rNA immune response and protective efficacy, which is surprisingly more dependent on the specific combination of NA and tetramerization domains than common attributes for evaluating NA. Our findings may help to optimize the design of rNAs that can be used to improve or develop influenza vaccines.
Forward and Reverse Genetic Dissection of Morphogenesis Identifies Filament-CompetentCandida aurisStrains
Authors: Santana Darian J. , O’Meara Teresa R. 
Published: April 2021

AbstractCandida aurisis an emerging healthcare-associated pathogen of global concern. Although this organism does not display the same morphological plasticity as the related fungal pathogenCandida albicans, recent reports have identified numerousC. aurisisolates that grow in cellular aggregates or filaments. However, the genetic circuitry governingC. aurismorphology remains largely uncharacterized. Here, we developed anAgrobacterium-mediatedtransformation system to generate mutants exhibiting aggregating or filamentous cell morphologies. Aggregating strains were associated with disruption of homologs ofSaccharomyces cerevisiaechitinase and chitin synthase regulatory proteins, including components of the Regulation ofACE2Morphogenesis (RAM) pathway, while disruption of a homolog of theS. cerevisiae ELM1gene resulted in a novel filamentous strain ofC. auris. To facilitate targeted genetic manipulation, we developed a transiently expressed Cas9 and sgRNA expression system for use inC. auris. Transformation using this system significantly increased the efficiency of homologous recombination and targeted integration of a reporter cassette in all four clades ofC. auris. Using this system, we generated targeted deletion mutants to confirm the roles of RAM and Elm1 proteins in regulatingC. aurismorphogenesis. Overall, our findings provide novel insights into the genetic regulation of aggregating and filamentous morphogenesis inC. auris. Furthermore, the genetic manipulation tools described here will allow for inexpensive and efficient manipulation of theC. aurisgenome.ImportanceCandida aurisis an emerging and often multi-drug resistant fungal pathogen responsible for outbreaks globally. Current difficulties in performing genetic manipulation in this organism remain a barrier to understandingC. aurisbiology. Homologous recombination approaches can result in less than 1% targeted integration of a reporter cassette, emphasizing the need for new genetic tools specific for manipulatingC. auris. Here, we adapted Agrobacterium-mediated transformation and a transient Cas9 and sgRNA expression system for use in forward and reverse genetic manipulation ofC. auris. We demonstrated the efficacy of each system by uncovering genes underlying cellular morphogenesis inC. auris. We identified a novel filamentous mutant ofC. auris, demonstrating that this organism has maintained the capacity for filamentous growth. Our findings provide additional options for improving the genetic tractability ofC. auris, which will allow for further characterization of this emerging pathogen.
Dynamics and heterogeneity of Erk-induced immediate-early gene expression
Authors: Jena Siddhartha G. , Yu Catherine , Toettcher Jared E. 
Published: April 2021

SummaryMany canonical signaling pathways exhibit complex time-varying responses, yet how minutes-timescale pulses of signaling interact with the dynamics of transcription and gene expression remains poorly understood. Erk-induced immediate early gene (IEG) expression is a model of this interface, exemplifying both dynamic pathway activity and a rapid, potent transcriptional response. Here, we quantitatively characterize IEG expression downstream of dynamic Erk stimuli in individual cells. We find that IEG expression responds rapidly to acute changes in Erk activity, but only in a sub-population of stimulus-responsive cells. We find that while Erk activity partially predicts IEG expression, a majority of response heterogeneity is independent of Erk and can be rapidly tuned by different mitogenic stimuli and parallel signaling pathways. We extend our findings to anin vivocontext, the mouse epidermis, where we observe heterogenous immediate-early gene accumulation in both fixed tissue and single-cell RNA-sequencing data. Our results demonstrate that signaling dynamics can be faithfully transmitted to gene expression and suggest that the signaling-responsive population is an important parameter for interpreting gene expression responses.
A survey on the pedagogical features of language massive open online courses
Authors: Wong Billy Tak-ming 
Published: April 2021

PurposeThis paper examines the pedagogical features of massive open online courses (MOOCs) for language learning–known as language MOOCs. The mainstream pedagogy of MOOCs typically involves the provision of short videos and reading materials for self-study; discussion forums, mostly for peer-to-peer interaction on course content; and machine-graded quizzes for self-assessment. For language learning, which has been conventionally understood as skill development, the pedagogical features of relevant MOOCs have yet to be comprehensively surveyed.Design/methodology/approachThis study surveyed a total of 123 language MOOCs from the major MOOC platforms. The pedagogical features shown in these courses were identified and categorised according to the types of course materials and learning activities as well as the participation of learners and instructors.FindingsEnglish was the most common language taught in the courses. Over 80% of the courses took not more than six hours to complete. Most of these courses followed the typical approach of xMOOC delivery, with video watching, reading and auto-graded assessment being the most common learning activities. Less than half of the courses included discussion as part of learning, and instructors were involved in less than 30% of the discussion.Originality/valueThe findings show that, despite the technological advances in course delivery, current language MOOCs do not differ substantially from conventional distance language learning. Yet, the utilisation of computer-assisted language learning technology and the massive student base of MOOCs for creating a virtual social community are opportunities for developing learners' language proficiency on this learning environment.
Promoting digital citizenship education in junior secondary schools in Hong Kong: supporting schools in professional development and action research
Authors: Chong Eric King-man , Pao Shun Shing 
Published: April 2021

PurposeThis study investigated the effectiveness of a professional development project on digital citizenship education (DCE) conducted by a team at the Education University of Hong Kong. The project aimed to promote digital citizenship education in local junior secondary schools in Hong Kong and support the professional development of in-service teachers.Design/methodology/approachThis study was based on a departmental knowledge transfer and curriculum development project that provided professional development training workshops to in-service teachers from seven partner schools. This paper analyses some findings from the quantitative research questionnaires, lesson observations and qualitative interviews.FindingsEleven of the 12 participants reported that they were satisfied with the training workshops in the end. We also conducted paired sample t-tests of inferential data. The results show that after the workshops, the teachers tended to teach their students more about aspects of digital law, digital commerce and digital safety and security when teaching digital citizenship. This selection helps us to better understand the priorities of teachers in teaching digital citizenship.Originality/valueThis paper is the product of an original knowledge transfer and curriculum development project supported by the Education University of Hong Kong in the Hong Kong Special Administrative Region (Hong Kong SAR) of China. The topic of digital citizenship education has also been under developed since citizenship education has always been about conventional citizenship in the physical world.
Evaluation of postural-assist exoskeleton for manual material handling
Authors: Ogunseiju Omobolanle , Olayiwola Johnson , Akanmu Abiola , Olatunji Oluwole Alfred 
Published: April 2021

Purpose
Work-related musculoskeletal disorders constitute a severe problem in the construction industry. Workers' lower backs are often affected by heavy or repetitive lifting and prolonged awkward postures. Exoskeletal interventions are effective for tasks involving manual lifting and repetitive movements. This study aims to examine the potential of a postural-assist exoskeleton (a passive exoskeleton) for manual material handling tasks.

Design/methodology/approach
From an experimental observation of participants, the effects of postural-assist exoskeleton on tasks and workers were measured. Associated benefits of the exoskeleton were assessed through task performance, range of motion and discomfort.

Findings
Findings suggest that the exoskeleton influenced discomfort significantly, however range of motion decreased with lifting tasks. The reduced back flexion and increased hip flexion were also indicatives of the participants' responsiveness to the feedback from the exoskeleton. In addition, task completion time increased by 20%, and participants' back pain did not reduce.

Research limitations/implications
The work tasks were performed in a controlled laboratory environment and only wearable inertia measurement units (IMUs) were used to assess the risk exposures of the body parts.

Practical implications
This study opens a practical pathway to human-exoskeleton integration, artificial regeneration or enablement of impaired workforce and a window toward a new order of productivity scaling. Results from this study provide preliminary insights to designers and innovators on the influence of postural assist exoskeleton on construction work. Project stakeholders can be informed of the suitability of the postural assist exoskeletons for manual material handling tasks.

Originality/value
Little has been reported on the benefits and impact of exoskeletons on tasks' physical demands and construction workers' performance. This study adds value to the existing literature, in particular by providing insights into the effectiveness and consequences of the postural-assist exoskeleton for manual material handling tasks.
Machine learning-aided cost prediction and optimization in construction operations
Authors: Sharma Virok , Zaki Mohd , Jha Kumar Neeraj , Krishnan N. M. Anoop 
Published: April 2021

Purpose
This paper aims to use a data-driven approach towards optimizing construction operations. To this extent, it presents a machine learning (ML)-aided optimization approach, wherein the construction cost is predicted as a function of time, resources and environmental impact, which is further used as a surrogate model for cost optimization.

Design/methodology/approach
Taking a dataset from literature, the paper has applied various ML algorithms, namely, simple and regularized linear regression, random forest, gradient boosted trees, neural network and Gaussian process regression (GPR) to predict the construction cost as a function of time, resources and environmental impact. Further, the trained models were used to optimize the construction cost applying single-objective (with and without constraints) and multi-objective optimizations, employing Bayesian optimization, particle swarm optimization (PSO) and non-dominated sorted genetic algorithm.

Findings
The results presented in the paper demonstrate that the ensemble methods, such as gradient boosted trees, exhibit the best performance for construction cost prediction. Further, it shows that multi-objective optimization can be used to develop a Pareto front for two competing variables, such as cost and environmental impact, which directly allows a practitioner to make a rational decision.

Research limitations/implications
Note that the sequential nature of events which dictates the scheduling is not considered in the present work. This aspect could be incorporated in the future to develop a robust scheme that can optimize the scheduling dynamically.

Originality/value
The paper demonstrates that a ML approach coupled with optimization could enable the development of an efficient and economic strategy to plan the construction operations.
Application of Lean Six Sigma in conservative dentistry: an action research at an Indian dental college
Authors: Noronha Ajay , Bhat Shreeranga , Gijo E.V. , Antony Jiju , Bhat Suma 
Published: April 2021

PurposeThe article evaluates the obstacles, lessons learned and managerial implications of deploying Lean Six Sigma (LSS) in a dental college hospital in India.Design/methodology/approachThe work adopts the action research (AR) methodology to establish a case study, which is carried out using the LSS define–measure–analyze–improve–control (DAMIC) approach in a dental college. It uses LSS tools to enhance the productivity and performance of the Conservative Dentistry Department of a dental college and to unravel the obstacles and success factors in applying it to the education and healthcare sector together.FindingsThe root cause for high turn-around time (TAT) is ascertained using LSS tools and techniques. The effective deployment of the solutions to the root causes of variation assists the dental college to reduce the TAT of the Conservative Dentistry process from an average of 63.9 min–36.5 min (i.e. 42.9% improvement), and the process Standard Deviation (SD) was reduced from 2.63 to 2 min. This, in turn, raises the sigma level from 0.48 to 3.23, a noteworthy successful story for this dental college.Research limitations/implicationsWhile the results and recommendations of this research are focused on a single case study, it is to be noted that the case study is carried out with new users of LSS tools and techniques, especially with the assistance of interns. This indicates the applicability of LSS in dental colleges; thus, the adopted modality can be further refined to fit India's education and hospital sector together.Originality/valueThis article explains the implementation of LSS from an aspiring user viewpoint to assist dental colleges and policymakers in improving competitiveness. In addition, the medical education sector can introduce an LSS course in the existing programme to leverage the potential of this methodology to bring synergy and collaborative research between data-based thinking and the medical field based on the findings of this study. The most important contribution of this article is the illustration of the design of experiments (DOE) in the dental college process.
Air quality management using genetic algorithm based heuristic fuzzy time series model
Authors: Bhagat Lalit , Goyal Gunjan , Bisht Dinesh C.S. , Ram Mangey , Kazancoglu Yigit 
Published: April 2021

PurposeThe purpose of this paper is to provide a better method for quality management to maintain an essential level of quality in different fields like product quality, service quality, air quality, etc.Design/methodology/approachIn this paper, a hybrid adaptive time-variant fuzzy time series (FTS) model with genetic algorithm (GA) has been applied to predict the air pollution index. Fuzzification of data is optimized by GAs. Heuristic value selection algorithm is used for selecting the window size. Two algorithms are proposed for forecasting. First algorithm is used in training phase to compute forecasted values according to the heuristic value selection algorithm. Thus, obtained sequence of heuristics is used for second algorithm in which forecasted values are selected with the help of defined rules.FindingsThe proposed model is able to predict AQI more accurately when an appropriate heuristic value is chosen for the FTS model. It is tested and evaluated on real time air pollution data of two popular tourism cities of India. In the experimental results, it is observed that the proposed model performs better than the existing models.Practical implicationsThe management and prediction of air quality have become essential in our day-to-day life because air quality affects not only the health of human beings but also the health of monuments. This research predicts the air quality index (AQI) of a place.Originality/valueThe proposed method is an improved version of the adaptive time-variant FTS model. Further, a nature-inspired algorithm has been integrated for the selection and optimization of fuzzy intervals.