bluuebunny/crossref_metadata_2025_split huggingface dataset:
Robotic High-Throughput Biomanufacturing and Functional Differentiation of Human Pluripotent Stem Cells
Authors: Tristan Carlos A. , Ormanoglu Pinar , Slamecka Jaroslav , Malley Claire , Chu Pei-Hsuan , Jovanovic Vukasin M. , Gedik Yeliz , Bonney Charles , Barnaeva Elena , Braisted John , Mallanna Sunil K. , Dorjsuren Dorjbal , Iannotti Michael J. , Voss Ty C. , Michael Sam , Simeonov Anton , Singeç Ilyas 
Published: August 2020

ABSTRACTEfficient translation of human induced pluripotent stem cells (hiPSCs) depends on implementing scalable cell manufacturing strategies that ensure optimal self-renewal and functional differentiation. Currently, manual culture of hiPSCs is highly variable and labor-intensive posing significant challenges for high-throughput applications. Here, we established a robotic platform and automated all essential steps of hiPSC culture and differentiation under chemically defined conditions. This streamlined approach allowed rapid and standardized manufacturing of billions of hiPSCs that can be produced in parallel from up to 90 different patient-and disease-specific cell lines. Moreover, we established automated multi-lineage differentiation to generate primary embryonic germ layers and more mature phenotypes such as neurons, cardiomyocytes, and hepatocytes. To validate our approach, we carefully compared robotic and manual cell culture and performed molecular and functional cell characterizations (e.g. bulk culture and single-cell transcriptomics, mass cytometry, metabolism, electrophysiology, Zika virus experiments) in order to benchmark industrial-scale cell culture operations towards building an integrated platform for efficient cell manufacturing for disease modeling, drug screening, and cell therapy. Combining stem cell-based models and non-stop robotic cell culture may become a powerful strategy to increase scientific rigor and productivity, which are particularly important during public health emergencies (e.g. opioid crisis, COVID-19 pandemic).
Developing Cyclic Peptomers as Broad-Spectrum Gram negative Bacterial Type III Secretion System Inhibitors
Authors: Lam Hanh N. , Lau Tannia , Lentz Adam , Sherry Jessica , Cabrera-Cortez Alejandro , Hug Karen , Engel Joanne , Lokey R. Scott , Auerbuch Victoria 
Published: August 2020

ABSTRACTAntibiotic resistant bacteria are an emerging global health threat. New antimicrobials are urgently needed. The injectisome type III secretion system (T3SS), required by dozens of Gram-negative bacteria for virulence but largely absent from non-pathogenic bacteria, is an attractive antimicrobial target. We previously identified synthetic cyclic peptomers, inspired by the natural product phepropeptin D, that inhibit protein secretion through theYersiniaYsc andPseudomonas aeruginosaPsc T3SSs, but do not inhibit bacterial growth. Here we describe identification of an isomer, 4EpDN, that is two-fold more potent (IC504 μM) than its parental compound. Furthermore, 4EpDN inhibited theYersiniaYsa and theSalmonellaSPI-1 T3SSs, suggesting that this cyclic peptomer has broad efficacy against evolutionarily distant injectisome T3SSs. Indeed, 4EpDN strongly inhibited intracellular growth ofChlamydia trachomatisin HeLa cells, which requires the T3SS. 4EpDN did not inhibit the unrelated Twin arginine translocation (Tat) system, nor did it impact T3SS gene transcription. Moreover, although the injectisome and flagellar T3SSs are evolutionarily and structurally related, the 4EpDN cyclic peptomer did not inhibit secretion of substrates through theSalmonellaflagellar T3SS, indicating that cyclic peptomers broadly but specifically target the injestisome T3SS. 4EpDN reduced the number of T3SS basal bodies detected on the surface ofY. enterocolitica, as visualized using a fluorescent derivative of YscD, an inner membrane ring with low homology to flagellar protein FliG. Collectively, these data suggest that cyclic peptomers specifically inhibit the injectisome T3SS from a variety of Gram-negative bacteria, possibly by preventing complete T3SS assembly.IMPORTANCETraditional antibiotics target both pathogenic and commensal bacteria, resulting in a disruption of the microbiota, which in turn is tied to a number of acute and chronic diseases. The bacterial type III secretion system (T3SS) is an appendage used by many bacterial pathogens to establish infection, but is largely absent from commensal members of the microbiota. In this study, we identify a new derivative of the cyclic peptomer class of T3SS inhibitors. These compounds inhibit the T3SS of the nosocomial ESKAPE pathogenPseudomonas aeruginosaand enteropathogenicYersiniaandSalmonella. The impact of cyclic peptomers is specific to the T3SS, as other bacterial secretory systems are unaffected. Importantly, cyclic peptomers completely block replication ofChlamydia trachomatis, the causative agent of genital, eye, and lung infections, in human cells, a process that requires the T3SS. Therefore, cyclic peptomers represent promising virulence blockers that can specifically disarm a broad spectrum of Gram-negative pathogens.
Fitting to the UK COVID-19 outbreak, short-term forecasts and estimating the reproductive number
Authors: Keeling Matt J. , Dyson Louise , Guyver-Fletcher Glen , Holmes Alex , Semple Malcolm G ,   ISARIC4C Investigators, Tildesley Michael J. , Hill Edward M. 
Published: August 2020

AbstractThe COVID-19 pandemic has brought to the fore the need for policy makers to receive timely and ongoing scientific guidance in response to this recently emerged human infectious disease. Fitting mathematical models of infectious disease transmission to the available epidemiological data provides a key statistical tool for understanding the many quantities of interest that are not explicit in the underlying epidemiological data streams. Of these, the effective reproduction number, R, has taken on special significance in terms of the general understanding of whether the epidemic is under control (R < 1). Unfortunately, none of the epidemiological data streams are designed for modelling, hence assimilating information from multiple (often changing) sources of data is a major challenge that is particularly stark in novel disease outbreaks.Here, focusing on the dynamics of the first-wave (March-June 2020), we present in some detail the inference scheme employed for calibrating the Warwick COVID-19 model to the available public health data streams, which span hospitalisations, critical care occupancy, mortality and serological testing. We then perform computational simulations, making use of the acquired parameter posterior distributions, to assess how the accuracy of short-term predictions varied over the timecourse of the outbreak. To conclude, we compare how refinements to data streams and model structure impact estimates of epidemiological measures, including the estimated growth rate and daily incidence.
Hospital Admission Rates, Length of Stay and In-hospital Mortality for Common Acute Care Conditions in COVID-19 vs. Pre-COVID-19 Era
Authors: Butt Adeel A. , Kartha Anand B. , Masoodi Naseer A. , Azad Aftab Mohammad , Asaad Nidal Ahmad , Alhomsi Mohamad Ussama , Saleh Huda A. H. , Bertollini Roberto , Abou-Samra Abdul-Badi 
Published: August 2020

AbstractBackgroundImpact of COVID-19 upon acute care admission rates and patterns are unknown. We sought to determine the change in rates and types of admissions to tertiary and specialty care hospitals in the COVID-19 era compared with pre-COVID-19 era.MethodsAcute care admissions to the largest tertiary care referral hospital, designated national referral centers for cardiac, cancer and maternity hospital in the State of Qatar during March 2020 (COVID-19 era) and January 2020 and March 2019 (pre-COVID-19 era) were compared. We calculated total admissions, and admissions for eight specific acute care conditions, in-hospital mortality rate and length of stay at each hospital.ResultsA total of 18,889 hospital admissions were recorded. A sharp decline ranging from 9%-75% was observed in overall admissions. A decline in both elective and non-elective surgeries was observed. A decline of 9%-58% was observed in admissions for acute appendicitis, acute coronary syndrome, stroke, bone fractures, cancer and live births, while an increase in admissions due to respiratory tract infections was observed. Overall length of stay was shorter in the COVID-19 period possibly suggesting lesser overall disease severity, with no significant change in in-hospital mortality. Unadjusted mortality rate for Qatar showed marginal increase in the COVID-19 period.ConclusionsWe observed a sharp decline in acute care hospital admissions, with a significant decline in admissions due to seven out of eight acute care conditions. This decline was associated with a shorter length of stay, but not associated with a change in in-hospital mortality rate.
Differential Brain Atrophy Patterns and Neurogenetic Profiles in Cognitively-Defined Alzheimer’s Disease Subgroups
Authors: Groot Colin , Grothe Michel J. , Mukherjee Shubhabrata , Jelistratova Irina , Jansen Iris , van Loenhoud Anna Catharina , Risacher Shannon L. , Saykin Andrew J. , Mac Donald Christine L. , Mez Jesse , Trittschuh Emily H. , Gryglewski Gregor , Lanzenberger Rupert , Pijnenburg Yolande A.L. , Barkhof Frederik , Scheltens Philip , van der Flier Wiesje M. , Crane Paul K. , Ossenkoppele Rik 
Published: August 2020

AbstractElucidating mechanisms underlying the clinical heterogeneity observed among individuals with Alzheimer’s disease (AD) is key to facilitate personalized treatments. We categorized 679 individuals with AD into subgroups based on a relative impairment in one cognitive domain (i.e. AD-Memory, AD-Executive-Functioning, AD-Language and AD-Visuospatial-Functioning). We compared atrophy patterns derived from MRI and identified patterns that closely matched the respective cognitive profiles, i.e. medial temporal lobe atrophy in AD-Memory, fronto-parietal in AD-Executive-Functioning, asymmetric left-temporal in AD-Language, and posterior in AD-Visuospatial-Functioning. We then determined spatial correlations between subgroup-specific atrophy and a transcriptomic atlas of gene expression, which revealed both shared (e.g. mitochondrial respiration and synaptic function/plasticity) and subgroup-specific (e.g. cell-cycle for AD-Memory, protein metabolism in AD-Language, and modification of gene expression in AD-Visuospatial-Functioning) biological pathways associated with each subgroup’s atrophy patterns. We conclude that cognitive heterogeneity in AD is related to neuroanatomical differences, and specific biological pathways may be involved in their emergence.
Haunted by the past: transformations and daily challenges of China's prosthetics
Authors: Wang Chunchun 
Published: August 2020

PurposeThe purpose of this paper is to examine the transformations of prosthetic practices in China, as well as the daily experiences and dilemmas arising from the everchanging practices since 1949. On the basis of materials, this paper explores an everyday perspective to review the history of technology.Design/methodology/approachEthnography was collected with the application of participant observations, informal interviews and in-depth interviews during a 13-months study at a rehabilitation center in Chengdu, China. The literature on prosthetic manufacturing was also reviewed for this paper.FindingsChina's prosthetic technology seems to evolve from traditional to modern. However, this progressive narrative – innovation-based timeline (Edgerton, 2006, xi) – has been challenged by daily practices. Due to institutional pressures, prosthetists are in a dilemma of selectively using their knowledge to create one kind of device for all prosthesis users with a certain kind of disability, thereby regulating the physical and social experiences of prosthesis users. Besides, prosthesis users are accustomed to prostheses made with old techniques, and must correct themselves from old experiences to the daily practices recognized by the selected techniques.Originality/valueThis paper provides a cross-cultural case to reexamine Edgerton's criticism of the progressive and orderly innovation-centric technological narrative. More importantly, it reviews the history and practices of China's prosthetics from daily experiences rather than Edgerton's concentration on technology; therefore, it provides an everyday perspective for future research on technological transformations.
Building community at distance: a datathon during COVID-19
Authors: Fritz Samantha , Milligan Ian , Ruest Nick , Lin Jimmy 
Published: August 2020

Purpose
This paper aims to use the experience of an in-person event that was forced to go virtual in the wake of COVID-19 as an entryway into a discussion on the broader implications around transitioning events online. It gives both practical recommendation to event organizers as well as broader reflections on the role of digital libraries during the COVID-19 pandemic and beyond.

Design/methodology/approach
The authors draw on their personal experiences with the datathon, as well as a comprehensive review of literature. The authors provide a candid assessment of what approaches worked and which ones did not.

Findings
A series of best practices are provided, including factors for assessing whether an event can be run online; the mixture of synchronous versus asynchronous content; and important technical questions around delivery. Focusing on a detailed case study of the shift of the physical team-building exercise, the authors note how cloud-based platforms were able to successfully assemble teams and jumpstart online collaboration. The existing decision to use cloud-based infrastructure facilitated the event’s transition as well. The authors use these examples to provide some broader insights on meaningful content delivery during the COVID-19 pandemic.

Originality/value
Moving an event online during a novel pandemic is part of a broader shift within the digital libraries’ community. This paper thus provides a useful professional resource for others exploring this shift, as well as those exploring new program delivery in the post-pandemic period (both due to an emphasis on climate reduction as well as reduced travel budgets in a potential period of financial austerity).
The role of social capital in Iranian agricultural students' acquisition of generic skills
Authors: Gholami Hesamedin , Alambeigi Amir , Farrokhnia Mohammadreza , Noroozi Omid , Karbasioun Mostafa 
Published: August 2020

PurposeThis study aims to investigate the role of social capital in Iranian agricultural students' acquisition of generic skills. For this purpose, the effect of various social capital dimensions on students' generic skills development was examined.Design/methodology/approachA survey was conducted among 190 third- and fourth-year undergraduate students in one of the colleges of agriculture and natural resources in Iran. The partial least square method was used to examine the relationships among various social capital dimensions (i.e. social values, social trust, social networks, social cohesion, social participation, social communications and information sharing) with students' generic skills.FindingsThe findings showed that social networks and social participation are effective factors in the generic skills development of students. A model designed for the development of students' generic skills based on their social capital level predicted up to 33% of generic skills' variances. Furthermore, the multi-group analysis showed that males and females vary on how various social capital dimensions affect their generic skills. In this respect, the social participation dimension had a significantly greater impact on female students' generic skills, whereas the generic skills of male students were influenced more by the social cohesion dimension.Practical implicationsDeveloping generic skills through social capital can be considered as an effective strategy in countries that do not have formal programs for developing students' generic skills. Additionally, higher education policymakers should present a more supportive approach for developing generic skills of female students through social participation in the campuses.Originality/valueSo far, no study has examined the relationships among various social capital dimensions and students' generic skills in Iran. The picture is even more unclear when it comes to the differences between male and female students. The results of this study confirmed the importance of social networks and social participation in the universities to support students and to improve their generic skills and, consequently, their employability competencies. Furthermore, it could be inferred that male and female students have similarities and also differences in terms of the effect of social capital on developing generic skills that can provide a path for future studies.
Does precarious employment ruin youth health and marriage? Evidence from Egypt using longitudinal data
Authors: Sharaf Mesbah Fathy , Rashad Ahmed Shoukry 
Published: August 2020

Purpose
This study aims to analyze whether precarious employment is associated with youth mental health, self-rated health and happiness in marriage and whether this association differs by sex.

Design/methodology/approach
This paper uses longitudinal data from the Survey of Young People in Egypt conducted in 2009 and 2014 and estimates a fixed-effects model to control for time-invariant unobserved individual heterogeneity. The analysis is segregated by sex.

Findings
The results indicate that precarious employment is significantly associated with poor mental health and less happiness in marriage for males and is positively associated with poor self-reported health for females. The adverse impact of precarious work is likely to be mediated through poor working conditions such as low salary, maltreatment at work, job insecurity and harassment from colleagues.

Social implications
Governmental policies that tackle job precariousness are expected to improve population health and marital welfare.

Originality/value
Egypt has witnessed a significant increase in the prevalence of precarious employment, particularly among youth, in recent decades, yet the evidence on its effect on the health and well-being of youth workers is sparse. This paper adds to the extant literature by providing new evidence on the social and health repercussions of job precariousness from an understudied region.
Detecting hate speech against politicians in Arabic community on social media
Authors: Guellil Imane , Adeel Ahsan , Azouaou Faical , Chennoufi Sara , Maafi Hanene , Hamitouche Thinhinane 
Published: August 2020

Purpose
This paper aims to propose an approach for hate speech detection against politicians in Arabic community on social media (e.g. Youtube). In the literature, similar works have been presented for other languages such as English. However, to the best of the authors’ knowledge, not much work has been conducted in the Arabic language.

Design/methodology/approach
This approach uses both classical algorithms of classification and deep learning algorithms. For the classical algorithms, the authors use Gaussian NB (GNB), Logistic Regression (LR), Random Forest (RF), SGD Classifier (SGD) and Linear SVC (LSVC). For the deep learning classification, four different algorithms (convolutional neural network (CNN), multilayer perceptron (MLP), long- or short-term memory (LSTM) and bi-directional long- or short-term memory (Bi-LSTM) are applied. For extracting features, the authors use both Word2vec and FastText with their two implementations, namely, Skip Gram (SG) and Continuous Bag of Word (CBOW).

Findings
Simulation results demonstrate the best performance of LSVC, BiLSTM and MLP achieving an accuracy up to 91%, when it is associated to SG model. The results are also shown that the classification that has been done on balanced corpus are more accurate than those done on unbalanced corpus.

Originality/value
The principal originality of this paper is to construct a new hate speech corpus (Arabic_fr_en) which was annotated by three different annotators. This corpus contains the three languages used by Arabic people being Arabic, French and English. For Arabic, the corpus contains both script Arabic and Arabizi (i.e. Arabic words written with Latin letters). Another originality is to rely on both shallow and deep leaning classification by using different model for extraction features such as Word2vec and FastText with their two implementation SG and CBOW.
Constructing common height maps with various entropy-based similarity metrics and utilizing layering method for heterogeneous robot teams
Authors: Akay Mehmet Caner , Temeltaş Hakan 
Published: August 2020

Purpose
Heterogeneous teams consisting of unmanned ground vehicles and unmanned aerial vehicles are being used for different types of missions such as surveillance, tracking and exploration. Exploration missions with heterogeneous robot teams (HeRTs) should acquire a common map for understanding the surroundings better. The purpose of this paper is to provide a unique approach with cooperative use of agents that provides a well-detailed observation over the environment where challenging details and complex structures are involved. Also, this method is suitable for real-time applications and autonomous path planning for exploration.

Design/methodology/approach
Lidar odometry and mapping and various similarity metrics such as Shannon entropy, Kullback–Leibler divergence, Jeffrey divergence, K divergence, Topsoe divergence, Jensen–Shannon divergence and Jensen divergence are used to construct a common height map of the environment. Furthermore, the authors presented the layering method that provides more accuracy and a better understanding of the common map.

Findings
In summary, with the experiments, the authors observed features located beneath the trees or the roofed top areas and above them without any need for global positioning system signal. Additionally, a more effective common map that enables planning trajectories for both vehicles is obtained with the determined similarity metric and the layering method.

Originality/value
In this study, the authors present a unique solution that implements various entropy-based similarity metrics with the aim of constructing common maps of the environment with HeRTs. To create common maps, Shannon entropy–based similarity metrics can be used, as it is the only one that holds the chain rule of conditional probability precisely. Seven distinct similarity metrics are compared, and the most effective one is chosen for getting a more comprehensive and valid common map. Moreover, different from all the studies in literature, the layering method is used to compute the similarities of each local map obtained by a HeRT. This method also provides the accuracy of the merged common map, as robots’ sight of view prevents the same observations of the environment in features such as a roofed area or trees. This novel approach can also be used in global positioning system-denied and closed environments. The results are verified with experiments.