bluuebunny/crossref_metadata_2025 huggingface dataset:
Single-cell functional genomics of natural killer cell evasion in blood cancers
Authors: Dufva Olli , Gandolfi Sara , Huuhtanen Jani , Dashevsky Olga , Saeed Khalid , Klievink Jay , Nygren Petra , Bouhlal Jonas , Lahtela Jenni , Näätänen Anna , Ghimire Bishwa R , Hannunen Tiina , Ellonen Pekka , Duàn Hanna , Theodoropoulos Jason , Laajala Essi , Härkönen Jouni , Pölönen Petri , Heinäniemi Merja , Yamano Shizuka , Shirasaki Ryosuke , Barbie David , Roth Jennifer , Romee Rizwan , Sheffer Michal , Lähdesmäki Harri , Lee Dean A. , De Matos Simoes Ricardo , Kankainen Matti , Mitsiades Constantine S , Mustjoki Satu
Published: August 2022

Natural killer (NK) cells are emerging as a promising therapeutic option in cancer. To better understand how cancer cells evade NK cells, we studied interacting NK and blood cancer cells using single-cell and genome-scale functional genomics screens. At single-cell resolution, interaction of NK and cancer cells induced distinct activation states in both cell types depending on the cancer cell lineage and molecular phenotype, ranging from more sensitive myeloid to more resistant B-lymphoid cancers. CRISPR screens uncovered cancer cell-intrinsic genes driving sensitivity and resistance, including antigen presentation and death receptor signaling mediators, adhesion molecules, protein fucosylation genes, and transcriptional regulators. CRISPR screens with a single-cell transcriptomic readout revealed how these cancer cell genes influenced the gene expression landscape of both cell types, including regulation of activation states in both cancer and NK cells by IFNγ signaling. Our findings provide a resource for rational design of NK cell-based therapies in blood cancers.

HIGHLIGHTS

Transcriptomic states of interacting NK cells and cancer cells depend on cancer cell lineage

Molecular correlates of increased sensitivity of myeloid compared to B-lymphoid cancers include activating receptor ligands NCR3LG1, PVR, and ULBP1

New regulators of NK cell resistance from 12 genome-scale CRISPR screens include blood cancer-specific regulators SELPLG, SPN, and MYB

Single-cell transcriptomics CRISPR screens targeting 65 genome-wide screen hits identify MHC-I, IFNy, and NF-κB regulation as underlying mechanisms
Metabolic enhancement of mammalian developmental pausing
Authors: van der Weijden Vera A. , Stoetzel Maximilian , Fauler Beatrix , Iyer Dhanur P. , Shahraz Mohammed , Meierhofer David , Rulands Steffen , Alexandrov Theodore , Mielke Thorsten , Bulut-Karslioglu Aydan
Published: August 2022

The quest to model and modulate embryonic development became a recent cornerstone of stem cell and developmental biology. Mammalian developmental timing is adjustable in vivo by preserving preimplantation embryos in a dormant state called diapause. Inhibition of the growth regulator mTOR (mTORi) pauses mouse development in vitro, yet constraints to pause duration are unrecognized. By comparing the response of embryonic and extraembryonic stem cells to mTORi-induced pausing, we identified lipid usage as a bottleneck to developmental pausing. Enhancing fatty acid oxidation (FAO) boosts embryo longevity, while blocking it reduces the pausing capacity. Genomic and metabolic analyses of single embryos point toward a deeper dormant state in FAO-enhanced pausing and reveal a link between lipid metabolism and embryo morphology. Our results lift a constraint on in vitro embryo survival and suggest that lipid metabolism may be a critical metabolic transition relevant for longevity and stem cell function across tissues.

One-Sentence Summary

Facilitating fatty acid oxidation by carnitine supplementation enhances mTOR inhibition-mediated developmental pausing.
Mechanistic Insight into AP-Endonuclease 1 Cleavage of Abasic Sites at Stalled Replication Forks
Authors: Hoitsma Nicole M. , Norris Jessica , Khoang Thu H. , Kaushik Vikas , Antony Edwin , Hedglin Mark , Freudenthal Bret D.
Published: August 2022

1.

Many types of DNA damage stall replication fork progression, including abasic sites. AP-Endonuclease 1 (APE1) has been shown to cleave abasic sites in ssDNA substrates. Importantly, APE1 cleavage of ssDNA at a replication fork has significant biological implications by generating double strand breaks that could collapse the replication fork. Despite this, the molecular basis and efficiency of APE1 processing abasic sites at a replication fork remains elusive. Here, we investigate APE1 cleavage of several abasic substrates that mimic potential APE1 interactions at replication forks. We determine that APE1 has robust activity on these substrates, similar to dsDNA, and report rapid rates for cleavage and product release. X-ray crystal structures visualize the APE1 active site, highlighting that a similar mechanism is used to process ssDNA substrates as canonical APE1 activity on dsDNA. However, mutational analysis reveals R177 to be uniquely critical for the APE1 ssDNA cleavage mechanism. Additionally, we investigate the interplay between APE1 and Replication Protein A (RPA), the major ssDNA-binding protein at replication forks, revealing that APE1 can cleave an abasic site while RPA is still bound to the DNA substrate. Together, this work provides molecular level insights into abasic ssDNA processing by APE1, including the presence of RPA.
Cortical interneuron development is affected in leukodystrophy 4H
Authors: Dooves Stephanie , Kok Liza M.L. , Holmes Dwayne B. , Breeuwsma Nicole , Breur Marjolein , Bugiani Marianna , Wolf Nicole I. , Heine Vivi M.
Published: August 2022

4H leukodystrophy is a rare genetic disorder classically characterized by hypomyelination, hypodontia and hypogonadotropic hypogonadism. With the discovery that 4H is caused by mutations that affect RNA polymerase III, mainly involved in the transcription of small non-coding RNAs, also patients with atypical presentations with mainly a neuronal phenotype were identified. Pathomechanisms of 4H brain abnormalities are still unknown and research is hampered by a lack of preclinical models. We aimed to identify cells and pathways that are affected by 4H mutations using induced pluripotent stem cell models.

RNA sequencing analysis on induced pluripotent stem cell-derived cerebellar cells revealed several differentially expressed genes between 4H patients and control samples, including reduced ARX expression. As ARX is involved in early brain and interneuron development, we studied and confirmed interneuron changes in primary tissue of 4H patients. Subsequently, we studied interneuron changes in more depth and analyzed induced pluripotent stem cell-derived cortical neuron cultures for changes in neuronal morphology, synaptic balance, network activity and myelination. We showed a decreased percentage of GABAergic synapses in 4H, which correlated to increased neuronal network activity. Treatment of cultures with GABA antagonists led to a significant increase in neuronal network activity in control cells but not in 4H cells, also pointing to lack of inhibitory activity in 4H. Myelination and oligodendrocyte maturation in cultures with 4H neurons was normal, and treatment with sonic hedgehog agonist SAG did not improve 4H related neuronal phenotypes. qPCR analysis revealed increased expression of parvalbumin interneuron marker ERBB4, suggesting that the development rather than generation of interneurons may be affected in 4H.

Together, these results indicate that interneurons are involved, possibly parvalbumin interneurons, in disease mechanisms of 4H leukodystrophy.
Mitochondrial networks of microglia adapt in a sex-specific manner upon injury-induced stress and UCP2 knockout
Authors: Maes Margaret E , Colombo Gloria , Schoot Uiterkamp Florianne E. , Sternberg Felix , Venturino Alessandro , Pohl Elena E , Siegert Sandra
Published: August 2022

Balanced and dynamic mitochondrial networks are essential for cell survival and function. Mitochondrial networks remodel their connectivity, content and subcellular localization to support optimized energy production under conditions of increased stress.In vivo, stressors can arise from the environment, such as in neuronal injury, or from mutation-induced cellular dysfunction. Cells programmed to identify and respond to these stress signals, like microglia, rely on optimized mitochondrial function, however we know very little about mitochondrial networks of microgliain vivoor their adaptation to environmental or cellular stressors.

Here, we define the mitochondrial networks of retinal microglia in physiological conditionsin vivoand evaluate network alterations by taking advantage of a microglia-selective mitochondria-labeled mouse model. First, we demonstrate significant differences in the mitochondrial networks of microgliain vivoandin vitro.Then, we induced neuronal injury in thein vivoenvironment using optic nerve crush, where responsive microglia exhibit more fragmented mitochondrial networks with increased content and perinuclear localization, supporting a state of increased cellular stress. Surprisingly, when we selectively increase cellular stress by knocking out the mitochondria-associated gene uncoupling protein 2 (UCP2), only male UCP2KOmicroglia establish a hyperfused mitochondrial network after injury, indicating sex differences in microglial stress mitigation. Ovariectomy in UCP2KOfemales elicits a shift toward the male hyperfused mitochondrial phenotype suggesting that circulating estrogens are a contributing factor to the differences in microglial stress mitigation.
The absence of gastrointestinal redox dyshomeostasis in the brain-first rat model of Parkinson’s disease induced by bilateral intrastriatal 6-hydroxydopamine
Authors: Homolak Jan , Joja Mihovil , Grabaric Gracia , Schiatti Emiliano , Virag Davor , Perhoc Ana Babic , Knezovic Ana , Barilar Jelena Osmanovic , Salkovic-Petrisic Melita
Published: August 2022

The gut-brain axis plays an important role in Parkinson’s disease (PD) by acting as a route for vagal propagation of aggregated α-synuclein in the gut-first endophenotype and as a mediator of gastrointestinal dyshomeostasis via the nigro-vagal pathway in the brain-first endophenotype of the disease. One important mechanism by which the gut-brain axis may promote PD is by regulating gastrointestinal redox homeostasis as overwhelming evidence suggests that oxidative stress plays a key role in the etiopathogenesis and progression of PD and the gastrointestinal tract maintains redox homeostasis of the organism by acting as a critical barrier to environmental and microbiological electrophilic challenges. The present aim was to utilize the bilateral intrastriatal 6-hydroxydopamine (6-OHDA) brain-first PD model to study the effects of isolated central pathology on redox homeostasis of the gastrointestinal tract. Three-month-old male Wistar rats were either not treated (intact controls; CTR) or treated bilaterally intrastriatally with vehicle (CIS) or 6-OHDA (6-OHDA). Motor deficits were assessed with the rotarod performance test and the duodenum, ileum, and colon were dissected for biochemical analyses 12 weeks after the treatment. Lipid peroxidation, total antioxidant capacity, low-molecular thiols, and protein sulfhydryls, the activity of total and Mn/Fe superoxide dismutases, and total and azide-insensitive catalase/peroxidase were measured. Univariate and multivariate models of redox biomarkers provide solid evidence against the existence of pronounced gastrointestinal redox dyshomeostasis. The results indicate that the dysfunction of the nigro-vagal system and not motor deficit may be a key mediator of gastrointestinal dyshomeostasis in brain-first 6-OHDA-induced rodent models of PD.
Global maps of lake surface water temperatures reveal pitfalls of air-for-water substitutions in ecological prediction
Authors: Armitage David W.
Published: August 2022

In modeling species distributions and population dynamics, spatially-interpolated climatic data are often used as proxies for real, on-the-ground measurements. For shallow freshwater systems, this practice may be problematic as interpolations used for surface waters are generated from terrestrial sensor networks measuring air temperatures. Using these may therefore bias statistical estimates of species’ environmental tolerances or population projections – particularly among pleustonic and epilimnetic organisms. Using a global database of millions of daily satellite-derived lake surface water temperatures (LSWT), I trained machine learning models to correct for the correspondence between air and LSWT as a function of atmospheric and topographic predictors, resulting in the creation of monthly high-resolution global maps of air-LSWT offsets, corresponding uncertainty measures, and derived LSWT-based bioclimatic layers for use by the scientific community. I then compared the performance of these LSWT layers and air temperature-based layers in population dynamic and ecological niche models (ENM). While generally high, the correspondence between air temperature and LSWT was quite variable and often nonlinear depending on the spatial context. These LSWT predictions were better able to capture the modeled population dynamics and geographic distributions of two common aquatic plant species. Further, ENM models trained with LSWT predictors more accurately captured lab-measured thermal response curves. I conclude that these predicted LSWT temperatures perform better than raw air temperatures when used for population projections and environmental niche modeling, and should be used by practitioners to derive more biologically-meaningful results. These global LSWT predictions and corresponding error estimates and bioclimatic layers have been made freely available to all researchers in a permanent archive.
Effective Matrix Designs for COVID-19 Group Testing
Authors: Brust David , Brust Johannes J.
Published: August 2022

Background

Grouping samples with low prevalence of positives into pools and testing these pools can achieve considerable savings in testing resources compared with individual testing in the context of COVID-19. We review published pooling matrices, which encode the assignment of samples into pools and describe decoding algorithms, which decode individual samples from pools. Based on the findings we propose new one-round pooling designs with high compression that can efficiently be decoded by combinatorial algorithms. This expands the admissible parameter space for the construction of pooling matrices compared to current methods.

Results

By arranging samples in a grid and using polynomials to construct pools, we develop direct formulas for an Algorithm (Polynomial Pools (PP)) to generate assignments of samples into pools. Designs from PP guarantee to correctly decode all samples with up to a specified number of positive samples. PP includes recent combinatorial methods for COVID-19, and enables new constructions that can result in more effective designs.

Conclusion

For low prevalences of COVID-19, group tests can save resources when compared to individual testing. Constructions from the recent literature on combinatorial methods have gaps with respect to the designs that are available. We develop a method (PP), which generalizes previous constructions and enables new designs that can be advantageous in various situations.
Mapping of genomic regions linked to stemphylium blight (Stemphylium botryosum Wallr.) resistance in lentil using linkage mapping and marker-trait association analysis
Authors: Adobor Stanley , Gela Tadesse S. , Banniza Sabine , Vandenberg Albert
Published: August 2022

Stemphylium blight caused by Stemphylium botryosum, is a foliar disease of lentil. It affects the productivity and milling quality of lentil crops, mainly in South Asia and Canada. Development of stemphylium blight resistant cultivars by introgression of resistance alleles from crop wild relatives of lentil, such as Lens ervoides, is one strategy of disease control. The objective of this study was to identify genomic regions associated with stemphylium blight resistance by combining linkage mapping and marker-trait association analysis. A total of 182 genotypes of a lentil advanced backcross population (LABC-01) developed from the backcross of the interspecific L. culinaris × L. ervoides line LR-59-81 (donor) and cultivar CDC Redberry (recurrent) and 101 diverse lentil accessions selected by stratified random sampling from a lentil diversity panel were genotyped and evaluated for stemphylium blight reactions. Quantitative trait locus (QTL) analysis identified four loci contributing to stemphylium blight resistance on lentil chromosomes 2, 4 and 5. Marker trait association analysis detected five significant single nucleotide polymorphism (SNP) markers associated with stemphylium blight resistance within QTLs regions and seven SNP markers outside the QTLs regions on chromosomes 1, 2, 3, 5, and 7. The markers associated with stemphylium blight resistance may be useful for marker-assisted selection of resistant cultivars after validation.
Valproic acid exposure affects social visual lateralization and asymmetric gene expression in zebrafish larvae
Authors: Messina Andrea , Sovrano Valeria Anna , Baratti Greta , Musa Alessia , Adiletta Alice , Sgadò Paola
Published: August 2022

Cerebral asymmetry is critical for typical brain function and development, at the same time altered brain lateralization seems to be associated with neuropsychiatric disorders. In autism spectrum disorders (ASD) studies have suggested reduced functional and structural cerebral asymmetry, reporting changes in asymmetric activation of brain structures involved in language and social processing, and increased prevalence of left-handedness. Zebrafish are increasingly emerging as model species to study brain lateralization, using asymmetric development of the habenula, a phylogenetically old brain structure associated with social and emotional processing, to investigate the relationship between brain asymmetry and social behavior. We exposed 5-hour post-fertilization zebrafish embryos to valproic acid (VPA), a compound used to model the core signs of ASD in many vertebrate species, and assessed social interaction, visual lateralization and gene expression in the thalamus and the telencephalon. VPA-exposed zebrafish exhibit social deficits and a deconstruction of social visual laterality to the mirror. We also observe changes in the asymmetric expression of the epithalamic markerleftoverand in telencephalic gene expression in adult zebrafish. Our data indicate that VPA exposure neutralizes the animals’ visual field bias, with a complete loss of the left-eye use bias in front of their own mirror image, and alters brain asymmetric gene expression, opening new perspectives to investigate brain lateralization and its link to atypical social cognitive development, considering zebrafish as an animal model for the autistic syndrome.
PyWGCNA: A Python package for weighted gene co-expression network analysis
Authors: Rezaie Narges , Reese Fairlie , Mortazavi Ali
Published: August 2022

Motivation

Weighted gene co-expression network analysis (WGCNA) is frequently used to identify modules of genes that are co-expressed across many RNA-seq samples. However, the current R implementation is slow, not designed to compare modules between multiple WGCNA networks, and results are hard to interpret and visualize. We introduce the PyWGCNA Python package designed to identify and compare co-expression modules from RNA-seq data.

Results

We apply PyWGCNA to two distinct datasets of brain bulk RNA-seq from MODEL-AD to identify modules associated with the genotypes. We compare the resulting modules to each other to find modules with significant overlap across the datasets.

Availability

The PyWGCNA library for Python 3 is available on PyPi at https://pypi.org/project/PyWGCNA and on GitHub at https://github.com/mortazavilab/PyWGCNA.
DeepGenePrior: A deep learning model to prioritize genes affected by copy number variants
Authors: Rahaie Zahra , Rabiee Hamid R. , Alinejad-Rokny Hamid
Published: August 2022

The genetic etiology of neurodevelopmental disorders is highly heterogeneous. They are characterized by abnormalities in the development of the central nervous system, which lead to diminished physical or intellectual capabilities. Determining which gene is the driver of disease (not just a passenger), termed ‘gene prioritization,’ is not entirely known. In terms of disease-gene associations, genome-wide explorations are still underdeveloped due to the reliance on previous discoveries when spotting new genes and other evidence sources with false positive or false negative relations. This paper introduces DeepGenePrior, a model based on deep neural networks that prioritizes candidate genes in Copy Number Variant (CNV) mediated diseases. Based on the well-studied Variational AutoEncoder (VAE), we developed a score to measure the impact of the genes on the target diseases.

Unlike other methods that use prior data on gene-disease associations to prioritize candidate genes (using the guilt by association principle), the current study exclusively relies on copy number variants. Therefore, the procedure can identify disease-associated genes regardless of prior knowledge or auxiliary data sources. We identified genes that distinguish cases from disorders (autism, schizophrenia, and developmental delay). A 12% increase in fold enrichment was observed in brain-expressed genes compared to previous studies, while 15% more fold enrichment was found in genes associated with mouse nervous system phenotypes. We also explored sex dimorphism for the disorders and discovered genes that overexpress more in one gender than the other. Additionally, we investigated the gene ontology of the putative genes with WebGestalt and the associations between the causative genes and the other phenotypes in the DECIPHER dataset. Furthermore, some genes were jointly present in the top genes associated with the three disorders in this study (i.e., autism spectrum disorder, schizophrenia, and developmental delay); namely, deletions in ZDHHC8, DGCR5, and CATG00000022283 were common between them. These findings suggest the common etiology of these clinically distinct conditions.

With DeepGenePrior, we address the obstacles in existing gene prioritization studies. This study identified promising candidate genes without prior knowledge of diseases or phenotypes using deep learning.
Genome-wide analysis of Structural Variants in Parkinson’s Disease using Short-Read Sequencing data
Authors: Billingsley Kimberley J. , Ding Jinhui , Jerez Pilar Alvarez , Illarionova Anastasia , Grenn Francis P. , Makarious Mary B. , Moore Anni , Vitale Daniel , Reed Xylena , Hernandez Dena , Torkamani Ali , Ryten Mina , Hardy John ,   UK Brain Expression Consortium (UKBEC), Chia Ruth , Scholz Sonja W. , Traynor Bryan J. , Dalgard Clifton L. , Ehrlich Debra J. , Tanaka Toshiko , Ferrucci Luigi , Beach Thomas.G. , Serrano Geidy E. , Quinn John P. , Bubb Vivien J. , Collins Ryan L , Zhao Xuefang , Walker Mark , Pierce-Hoffman Emma , Brand Harrison , Talkowski Michael , Casey Bradford , Cookson Mark R , Markham Androo , Nalls Mike , Mahmoud Medhat , Sedlazeck Fritz J , Blauwendraat Cornelis , Gibbs J. Raphael , Singleton Andrew B.
Published: August 2022

Parkinson’s disease is a complex neurodegenerative disorder, affecting approximately one million individuals in the USA alone. A significant proportion of risk for Parkinson’s disease is driven by genetics. Despite this, the majority of the common genetic variation that contributes to disease risk is unknown, in-part because previous genetic studies have focussed solely on the contribution of single nucleotide variants. Structural variants represent a significant source of genetic variation in the human genome. However, because assay of this variability is challenging, structural variants have not been cataloged on a genome-wide scale, and their contribution to the risk of Parkinson’s disease remains unknown. In this study, we 1) leveraged the GATK-SV pipeline to detect and genotype structural variants in 7,772 short-read sequencing data and 2) generated a subset of matched whole-genome Oxford Nanopore Technologies long-read sequencing data from the PPMI cohort to allow for comprehensive structural variant confirmation. We detected, genotyped, and tested 3,154 “high-confidence” common structural variant loci, representing over 412 million nucleotides of non-reference genetic variation. Using the long-read sequencing data, we validated three structural variants that may drive the association signals at known Parkinson’s disease risk loci, including a 2kb intronic deletion within the gene LRRN4. Further, we confirm that the majority of structural variants in the human genome cannot be detected using short-read sequencing alone, encompassing on average around 4 million nucleotides of inaccessible sequence per genome. Therefore, although these data provide the most comprehensive survey of the contribution of structural variants to the genetic risk of Parkinson’s disease to date, this study highlights the need for large-scale long-read datasets to fully elucidate the role of structural variants in Parkinson’s disease.
Isolation and characterization of SARS-CoV-2 in Kenya
Authors: Makio Albina , Irekwa Robinson Mugasiali , Munyao Matthew Mutinda , Njoroge Caroline Wangui , Rotich Peter Kipkemboi , Nyandwaro Tonny Teya , Yego Joanne Jepkemei , Mwangi Anne Wanjiru , Kimotho James Hungo , Tanui Ronald , Rutto Vincent , Nzou Samson Muuo
Published: August 2022

The emergence of Severe Acute Respiratory Syndrome-Coronavirus-2 (SARS-CoV-2) from Wuhan, China, in December 2019 raised a global health concern that eventually became a pandemic affecting almost all countries worldwide. The respiratory disease has infected over 530 million people worldwide, with over 950,000 deaths recorded. This has led scientists to focus their efforts on understanding the virus to develop effective means to diagnose, treat, prevent, and control this pandemic. One of the areas of focus is isolation of this virus, which plays a crucial role in understanding the viral dynamics in the laboratory. In this study, we report the isolation and detection of locally circulating SARS-CoV-2 in Kenya. The isolates were cultured on Vero Cercopithecus cell line (CCL-81) cells, RNA extraction conducted from the supernatants, and reverse transcriptase-polymerase chain reaction (RT-PCR). Genome sequencing was done to profile the strains phylogenetically and identify novel and previously reported mutations. Vero CCL-81 cells were able to support the growth of SARS-CoV-2 in vitro, and mutations were detected from the two isolates sequenced (001 and 002). These virus isolates will be expanded and made available to the Kenya Ministry of Health and other research institutions to advance SARS-CoV-2 research in Kenya and the region.

Author Summary

The Coronavirus disease 2019 (COVID-19) pandemic is caused by a type of coronavirus that emerged in Wuhan, China in December 2019 and later spread to almost all countries. Many countries are still finding ways to contain it. The virus has been studied in many ways to investigate its origin, infectivity, and evolution. Different variants of the virus have emerged and spread, causing a lot of concern as to whether the pandemic will end soon. Significant studies have proven the ability of the virus to grow in the laboratory using cell lines that offer the necessary conditions. Therefore, this study sought to find out the growth of the virus in specific monkey cell line and the variant circulating within the Kenyan population. We found that the selected cell lines supported viral growth outside a human host system. In addition, the circulating virus was found to have evolved to enhance its survival mechanism. This is the first study in Kenya to report this virus’s isolation, culture, and identification in monkey kidney cells. These cells supported the growth of the virus in the laboratory and analysing the genome of the growth products showed the virus was related to previously reported strains with multiple changes in its whole DNA sequence.
Mind the Gap! Developing Patient Responsive Information for Epilepsy
Authors: Jones Sarah , Angus-Leppan Heather
Published: August 2022

Technology must adapt to changing expectations about shifting patient needs and accessing health services. Standardised websites provide information often in the “frequently asked questions” format. There is little research about how much these answer the questions of people with epilepsy (PWE).

This study used social media data to analyse the questions PWE have relating to “what would you ask a neurologist/epileptologist” and “do you have any questions relating to your epilepsy”. The study resulted in 2752 questions from PWE in Europe, North America and Australia, presented in the raw data format of natural language. Questions were themed using an unsupervised topic modelling algorithm to process and categorise the data into an aggregated question set.

Many of the questions are not currently answered by Epilepsy charity and medical websites, and many centre on restrictions and fears about lifestyle. This study acts as the first stage toward the supervised topic classification: providing a list of questions to be submitted for answering by healthcare professionals required for a Virtual Assistant.

The ultimate aim of the project is to generate a Virtual Assistant/Chatbot for the use of PWE to provide accurate and interactive responses to their real questions.
The divergent effects of neat food presentation on purchase likelihood: the moderating role of time-related positioning
Authors: Quach Sara , Septianto Felix , Thaichon Park
Published: August 2022

Purpose

Underpinned by the fit-fluency framework, this research aims to explore the effect of visual entropy (i.e. the neatness or disorder of food presentation) on the likelihood to purchase under different time-related positioning conditions.

Design/methodology/approach

Two experiments were conducted with customers who are located in the USA via Amazon Mechanical Turk. Study 1 employed a 2 (visual entropy: neat vs non-neat) × 2 (time-related positioning: traditional vs modern) between-subjects design using four advertisements for a fictitious ice cream brand. Study 2 employed a 2 (visual entropy: neat vs non-neat) × 2 (time-related positioning: traditional vs modern) between-subjects design using four book covers for fruit salad recipes.

Findings

The findings demonstrate low entropy (i.e. neatness) increases purchase likelihood when being paired with modern positioning, whilst high entropy (i.e. non-neat presentation) positively influences the propensity to purchase a traditional product on account of temporal fit. These relationships are mediated by perceived quality and nostalgia.

Originality/value

This research extends the understanding of visual entropy and addresses the inconclusive evidence of the impact of the neatness of product presentation on consumer behavior. The authors elucidate the mechanisms behind which neatness and non-neatness of food presentation affect purchase likelihood when different types of time-related positioning are featured.
Development and validation of a framework for preventing and mitigating construction delay using 4D BIM platform in Bangladeshi construction sector
Authors: Nafe Assafi Mohammad , Hossain Md. Mehrab , Chileshe Nicholas , Datta Shuvo Dip
Published: August 2022

Purpose

As a developing nation, Bangladesh still has scarce technological applications in the construction sector, which results in construction delays. This paper aims to propose a framework that will diminish manual labor, reduce human error and apply four-dimensional (4D) building information modeling (BIM)-based solutions to mitigate and prevent construction project delays.

Design/methodology/approach

First, a systematic literature review was conducted on analyzing the construction delay scenario in the context of Bangladesh and other countries. Next, a 4D BIM-based framework was developed using Autodesk Navisworks Manage. Finally, it was used to run on-site simulations on an ongoing construction project which faced delays because of design errors and inefficient planning.

Findings

Affirmative results were found from applying these methods through real-time project simulation. The current status of the project and the status after using BIM technology were compared. It was observed that during both the preconstruction and execution phases, the application of 4D BIM could reduce the delay posed by design error and inefficient planning.

Practical implications

The project manager and the design engineers can use these frameworks to review their projects. For the design engineers, the preconstruction phase portion of the framework will help identify the probable errors in the design. For the project managers, keeping track of time using the execution phase portion of the framework will be resourceful.

Originality/value

To the best of the authors’ knowledge, this study is the first to assess the significant delay factors endemic in Bangladesh and develop a BIM-based technological solution. This study is solely dedicated to reforming the construction techniques in Bangladesh through the application of 4D BIM technology.
Grey system theory in sustainable development research—a literature review (2011−2021)
Authors: Hu Mingli , Liu Wenjie
Published: August 2022

Purpose

As the grey systems theory has been widely used in the field of sustainable development (SD) research, in the following, a short literature overview will be put forward, starting from the usage of these theories in the economic development, social inclusion and environmental protection contributions to the evolving process of SD during 2011–2021. The purpose of this paper is to identify some key studies from all the SD areas in which the grey systems can be used in order to open and to bring the researchers to new domains in which they can reveal their interest and in which they can successfully use the methods offered by the grey systems theory.

Design/methodology/approach

Using the search engine offered by the Google Scholar and the Web of Science (WoS), a literature review has been performed for the grey systems applications on SD research on both grey relational analysis (GRA) and grey forecasting. In addition, some grey evaluation theories – clustering evaluation models and grey target decision models – have also been presented.

Findings

Many grey models are widely used in the field of SD. Compared with other methods such as grey prediction, grey evaluation and decision-making model, GRA technology is the most used method, and the research using this method is more than three times that of all other methods.

Research limitations/implications

The present paper identifies some of the most representative examples in which the grey system theory (GST) has been used, but, in the same time, there are a lot of studies that have not been mentioned here due to the lack of space.

Originality/value

The present paper focuses on the SD applications in which GST has been successfully used, bringing to the reader a general overview on this field and, in the same time, enables new research perspectives.
Value-based nudging of ethnic garments: a conjoint study to differentiate the value perception of ethnic products across Indian Markets
Authors: Banerjee Arnab , Dutta Tanusree , Mishra Aditya Shankar
Published: August 2022

Purpose

Handloom products often fail to infiltrate the global or mainland market, resulting in small localized markets, limited demand and profitability. Recent times have also witnessed a decline in the weaving population of India. Assam, accounting for a third of all households engaged in the handloom industry in India, has been widely hit by unemployment, migration and demotivation among weavers due to lack of profitability in the sector. This research aims to study the case of Assam as an exemplar to identify the barriers and cognitive biases impacting the sales of such ethnic apparel and propose nudges as interventions to address such concerns.

Design/methodology/approach

A conjoint-based experimental study was used to understand and compare the cognitive biases of two study groups: an ethnic group from Assam and a non-ethnic group from various Tier I and Tier II cities of India. The groups were exposed to a variety of ethnic Assamese and ethnic non-Assamese products to understand their value perception using conjoint analysis.

Findings

Results indicate a potential lack of cognitive fluency when dealing with Assamese ethnic garments, triggering System II thinking among the non-ethnic (national buyer) group. The underlying cause may be the inability to attribute substitution of the given product for a more familiar product. The results suggest that exposure may lead to priming, which in turn can increase cognitive fluency.

Originality/value

Within the limits of the literature reviewed, designing a conjoint-based experiment and proposing the use of nudge to popularize certain ethnic garments are novel contributions of this study.
Ecotourism a solution or deception for conservation: a case of Bhitarkanika Wildlife Sanctuary, Odisha, India
Authors: Das Madhumita , Chatterjee Bani
Published: August 2022

Purpose

The quest for alternative approaches to tourism has introduced ecotourism. However, in many instances, ecotourism becomes “green washing” process where revenue generation becomes prominent and protection of environmental assets is kept aside. The present article attempts to examine the impact of ecotourism policy on conservation in Bhitarkanika Wildlife Sanctuary (BKWS), Odisha, India.

Design/methodology/approach

Using social exchange theory (SET), the article examines whether ecotourism reduces the dependency of the local communities on natural resources and also the impact of ecotourism on conservation of biodiversity in BKWS.

Findings

The study using a mixed method approach finds that ecotourism in BKWS is able to provide economic benefits to the villagers. The economic benefits from diversified employment opportunities are able to motivate locals to conserve biodiversity. However, the socio-cultural impact is hardly experienced by the villagers.

Research limitations/implications

By examining the linkage of conservation with community development in a diverse society like India, the paper finds the linkage of conservation with development. The paper has also widened the existing ecotourism literature of India and Odisha. The study adopted SET so as to get a comprehensive understanding at the ground level, forming the basis for future research and further conceptual development.

Practical implications

The results of the study will help policy makers to develop an effective conservation strategy by integrating tourism, conservation and sustainable development of the locals so as to make ecotourism a successful approach in BKWS.

Originality/value

For a growing ecotourism site like BKWS, the current study is the first to assess impact of ecotourism on conservation and local people.
“Unchaining the doctor from the desk”: deliberate team-based care in action
Authors: Robertson Caroline , Jones Tabitha , Southwell Philippa
Published: August 2022

Purpose

As a model of integrated care (IC), deliberate team-based care (DTBC) can help address workforce shortages facing rural communities by improving the health and wellbeing of healthcare providers. This study focuses on a GP practice implementing DTBC in rural Australia. The aim of this research was to understand the perspectives of the healthcare workers involved and to ascertain factors impacting on the day to day running of the model, patient care and clinician work-life. The authors conducted a qualitative study on the experiences of the DTBC workers.

Design/methodology/approach

Team members were invited to participate in semi-structured interviews (n = 9). Interviews were analysed using an iterative thematic analysis, summarised, collated and explored for emergent themes.

Findings

Key themes included: creating change from old ways of doing things, development and implementation processes outlining how the model evolved and how it ran from day to day, model outcomes for patients and clinicians, as well as practical considerations like funding, technology and time.

Originality/value

Building DTBC from the ground up has produced a high functioning team who demonstrate trust and equality, share information freely and all have a voice which is heard and respected. By acting as a champion and a leader, the GP has created a psychologically safe environment allowing the team to share knowledge, collaborate in problem solving and provide effective patient care which is holistic and community grounded. This work environment holds promise for creating improved work-life for rural clinicians and potential for workforce retention.
Social relation and physical lane aggregator: integrating social and physical features for multimodal motion prediction
Authors: Chen Qiyuan , Wei Zebing , Wang Xiao , Li Lingxi , Lv Yisheng
Published: August 2022

Purpose

The purpose of this paper aims to model interaction relationship of traffic agents for motion prediction, which is critical for autonomous driving. It is obvious that traffic agents’ trajectories are influenced by physical lane rules and agents’ social interactions.

Design/methodology/approach

In this paper, the authors propose the social relation and physical lane aggregator for multimodal motion prediction, where the social relations of agents are mainly captured with graph convolutional networks and self-attention mechanism and then fused with the physical lane via the self-attention mechanism.

Findings

The proposed methods are evaluated on the Waymo Open Motion Dataset, and the results show the effectiveness of the proposed two feature aggregation modules for trajectory prediction.

Originality/value

This paper proposes a new design method to extract traffic interactions, and the attention mechanism is used in each part of the model to extract and fuse different relational features, which is different from other methods and improves the accuracy of the LSTM-based trajectory prediction method.
A predictive multi-objective condition-based maintenance (CBM) policy considering ecological factors
Authors: Cai Ronghua , Yang Jiamei , Xu Xuemin , Jiang Aiping
Published: August 2022

Purpose

The purpose of this paper is to propose an improved multi-objective optimization model for the condition-based maintenance (CBM) of single-component systems which considers periodic imperfect maintenance and ecological factors.

Design/methodology/approach

Based on the application of non-periodic preventive CBM, two recursion models are built for the system: hazard rate and the environmental degradation factor. This paper also established an optimal multi-objective model with a normalization process. The multiple-attribute value theory is used to obtain the optimal preventive maintenance (PM) interval. The simulation and sensitivity analyses are applied to obtain further rules.

Findings

An increase in the number of the occurrences could shorten the duration of a maintenance cycle. The maintenance techniques and maintenance efficiency could be improved by increasing system availability, reducing cost rate and improving degraded condition.

Practical implications

In reality, a variety of environmental situations may occur subsequent to the operations of an advanced manufacturing system. This model could be applied in real cases to help the manufacturers better discover the optimal maintenance cycle with minimized cost and degraded condition of the environment, helping the corporations better fulfill their CSR as well.

Originality/value

Previous research on single-component condition-based predictive maintenance usually focused on the maintenance costs and availability of a system, while ignoring the possible pollution from system operations. This paper proposed a modified multi-objective optimization model considering environment influence which could more comprehensively analyze the factors affecting PM interval.
Effects of the COVID-19 pandemic on architectural education: bibliometric and content analyses
Authors: Metinal Yusuf Berkay , Gumusburun Ayalp Gulden
Published: August 2022

Purpose

The impact of the coronavirus disease 2019 (COVID-19) pandemic on architectural education (AE) was investigated, and a framework was proposed to reduce the impacts' negative consequences.

Design/methodology/approach

Systematic literature review, bibliometric and content analyses were combined to gain an in-depth understanding of the effects of the pandemic on AE and projections for its future. Relevant documents were extracted from the Web of Science (WoS) database. Bibliometric connections in the context of AE and COVID-19 pandemic were explored using text-mining and content analysis was performed.

Findings

The challenges, development tendencies and collaboration networks in AE during the pandemic were quantitatively and qualitatively analyzed. The most influential articles, journals, authors and countries/regions were highlighted using a bibliometric analysis. The analysis of keyword tendencies and clusters indicates that new concepts have emerged in AE research during the pandemic involving online, in-person and hybrid education. Using content analysis of 57 subtopics, 39 (18) were categorized as having negative (positive) effects. A comprehensive mitigation framework was designed to reduce the impact of the pandemic on AE.

Research limitations/implications

The study findings can enable practitioners to construct effective solutions to COVID-19- and other disaster-related problems regarding AE. The implications, obstacles and mitigation framework presented can help identify gaps in the literature and guide further research.

Originality/value

This paper presents the first bibliometric and content analysis of AE and COVID-19 pandemic-related studies published from January 2020 to June 2022 to highlight several research directions and academic development within the field.
Development and application of the R.I.S.E. model (relevance, impact, significance and excellence) in higher education in Macau
Authors: Song Yonghua , Du Jianxia , Zhou Mingming
Published: August 2022

Purpose

The increasing societal requirement requests higher education institutions to be more responsive to socioeconomic needs and new governmental demands. This study aims to present a self-developed multidimensional quality assurance and assessment model for higher education institutions – R.I.S.E model (relevance, impact, significance and excellence) – as a tool for quality assessment in higher education institutions.

Design/methodology/approach

The model was first described at a conceptual level, followed by the examination of its applicability by presenting a case of a university in Macau to substantiate the model with real-life evidence.

Findings

Results showed that the model can be used as an assessment tool to analyze, evaluate and reflect upon the status quo of higher education institutions. Facilitators can use all or part of the model either as a useful baseline to assess performance and prioritize “next steps” or to compare performance across time to determine progress in achieving goals and objectives.

Originality/value

The new model proposed in this study presents multiple perspectives when assessing higher education systems, especially in the transforming stage of a university, to meet upgrading requirements from both the society and the academic community.