bluuebunny/crossref_metadata_2025 huggingface dataset:
Is 7-days home BP measurement comparable to 24-hours Ambulatory BP Measurement?
Authors: Islam Sheikh Mohammed Shariful , Karmakar Chandan , Ahmed Imran , Maddison Ralph
Published: October 2021

High blood pressure (BP) or hypertension is a significant risk factor for the global burden of cardiovascular diseases. Home blood pressure measurements (HBPM) have been recommended for hypertension diagnosis, treatment initiation and medication titration, but guidelines for the number of measurements and duration are inconsistent. This study compared the accuracy of 3 home BP measurements per day for seven days with 24-hour ambulatory BP measurements. We examined 24-hour ambulatory BP measurements (ABPM) and HBPM during-morning, afternoon, and evening each day for seven days in healthy community living volunteers. Standardized Bland-Altman scatterplots and limits of agreement (LOA) were used to assess absolute reliability and the variability of measurement biases. We used nonparametric Mann-Whitney U-tests to compare the mean (SD) of the devices. Correlations between HBPM and 24-hour ABPM measurements were statistically significant at p<0.05. The high correlation coefficient (r=0.75) was observed between the systolic BP retrieved from two devices compared to moderate correlation (r=0.46) among diastolic BP. A significant difference was found for systolic BP (P<0.05) between the HBPM and ABPM but was non-significant for diastolic BP (P>0.05). In Bland-Altman plots, the LOA between HBPM and ABPM was 0.07-26.23 mmHg for SBP and 11.24 -16.20 mmHg for DBP. The overall mean difference (bias) in SBP and DBP was 13.08 and 2.48, respectively. Our results suggest that HBPM three times per day for seven days can potentially be used where ABPM is unavailable. Further studies in a diverse group of people with hypertension are needed.
De novo Prediction of Cell-Drug Sensitivities Using Deep Learning-based Graph Regularized Matrix Factorization
Authors: Ren Shuangxia , Tao Yifeng , Yu Ke , Xue Yifan , Schwartz Russell , Lu Xinghua
Published: October 2021

Application of artificial intelligence (AI) in precision oncology typically involves predicting whether the cancer cells of a patient (previously unseen by AI models) will respond to any of a set of existing anticancer drugs, based on responses of previous training cell samples to those drugs. To expand the repertoire of anticancer drugs, AI has also been used to repurpose drugs that have not been tested in an anticancer setting, i.e., predicting the anticancer effects of a new drug on previously unseen cancer cells de novo. Here, we report a computational model that addresses both of the above tasks in a unified AI framework. Our model, referred to as deep learning-based graph regularized matrix factorization (DeepGRMF), integrates neural networks, graph models, and matrix-factorization techniques to utilize diverse information from drug chemical structures, their impact on cellular signaling systems, and cancer cell cellular states to predict cell response to drugs. DeepGRMF learns embeddings of drugs so that drugs sharing similar structures and mechanisms of action (MOAs) are closely related in the embedding space. Similarly, DeepGRMF also learns representation embeddings of cells such that cells sharing similar cellular states and drug responses are closely related. Evaluation of DeepGRMF and competing models on Genomics of Drug Sensitivity in Cancer (GDSC) and Cancer Cell Line Encyclopedia (CCLE) datasets show its superiority in prediction performance. Finally, we show that the model is capable of predicting effectiveness of a chemotherapy regimen on patient outcomes for the lung cancer patients in The Cancer Genome Atlas (TCGA) dataset.*
AlphaDesign: A de novo protein design framework based on AlphaFold
Authors: Jendrusch Michael , Korbel Jan O. , Sadiq S. Kashif
Published: October 2021

De novo protein design is a longstanding fundamental goal of synthetic biology, but has been hindered by the difficulty in reliable prediction of accurate high-resolution protein structures from sequence. Recent advances in the accuracy of protein structure prediction methods, such as AlphaFold (AF), have facilitated proteome scale structural predictions of monomeric proteins. Here we develop AlphaDesign, a computational framework for de novo protein design that embeds AF as an oracle within an optimisable design process. Our framework enables rapid prediction of completely novel protein monomers starting from random sequences. These are shown to adopt a diverse array of folds within the known protein space. A recent and unexpected utility of AF to predict the structure of protein complexes, further allows our framework to design higher-order complexes. Subsequently a range of predictions are made for monomers, homodimers, heterodimers as well as higher-order homo-oligomers - trimers to hexamers. Our analyses also show potential for designing proteins that bind to a pre-specified target protein. Structural integrity of predicted structures is validated and confirmed by standard ab initio folding and structural analysis methods as well as more extensively by performing rigorous all-atom molecular dynamics simulations and analysing the corresponding structural flexibility, intramonomer and interfacial amino-acid contacts. These analyses demonstrate widespread maintenance of structural integrity and suggests that our framework allows for fairly accurate protein design. Strikingly, our approach also reveals the capacity of AF to predict proteins that switch conformation upon complex formation, such as involving switches from α-helices to β-sheets during amyloid filament formation. Correspondingly, when integrated into our design framework, our approach reveals de novo design of a subset of proteins that switch conformation between monomeric and oligomeric state.
Realization of phosphorylation hypothesis of sleep by mammalian CaMKIIβ
Authors: Tone Daisuke , Ode Koji L. , Zhang Qianhui , Fujishima Hiroshi , Yamada Rikuhiro G. , Nagashima Yoshiki , Matsumoto Katsuhiko , Wen Zhiqing , Yoshida Shota Y. , Mitani Tomoki T. , Ohno Rei-ichiro , Ukai-Tadenuma Maki , Garçon Junko Yoshida , Kaneko Mari , Shi Shoi , Ukai Hideki , Miyamichi Kazunari , Okada Takashi , Sumiyama Kenta , Kiyonari Hiroshi , Ueda Hiroki R.
Published: October 2021

The reduced sleep duration observed inCamk2aandCamk2bknockout mice revealed the role of Ca2+/calmodulin-dependent protein kinase II (CaMKII)α/CAMKIIβ as sleep-promoting kinases and lead to the phosphorylation hypothesis of sleep. However, the underlying mechanism of sleep regulation by kinases and protein phosphorylation is largely unknown. Here, we demonstrate that the phosphorylation states of CaMKIIβ regulates sleep duration and sleep needs. Importantly, the activation or inhibition of CaMKIIβ can increase or decrease sleep duration by almost two-fold, supporting the role of CaMKIIβ as a core sleep regulator in mammals. This sleep regulation depends on the kinase activity of CaMKIIβ in excitatory neurons. Furthermore, CaMKIIβ mutants mimicking different phosphorylation states can regulate various sleep steps including sleep induction, sleep maintenance, and sleep cancelation. Key CaMKIIβ residues responsible for the mode switch undergo ordered (auto-)phosphorylation. We thus propose that ordered multi-site phosphorylation of CaMKIIβ underlies multi-step sleep regulation in mammals.
SARS-CoV-2 variants exhibit increased kinetic stability of open spike conformations as an evolutionary strategy
Authors: Yang Ziwei , Han Yang , Ding Shilei , Finzi Andrés , Mothes Walther , Lu Maolin
Published: October 2021

SARS-CoV-2 variants of concern harbor mutations in the Spike (S) glycoprotein that confer more efficient transmission and dampen the efficacy of COVID-19 vaccines and antibody therapies. S mediates virus entry and is the primary target for antibody responses. Structural studies of soluble S variants have revealed an increased propensity towards conformations accessible to receptor human Angiotensin-Converting Enzyme 2 (hACE2). However, real-time observations of conformational dynamics that govern the structural equilibriums of the S variants have been lacking. Here, we report single-molecule Förster Resonance Energy Transfer (smFRET) studies of S variants containing critical mutations, including D614G and E484K, in the context of virus particles. Investigated variants predominantly occupied more open hACE2-accessible conformations, agreeing with previous structures of soluble trimers. Additionally, these S variants exhibited decelerated transitions in hACE2-accessible/bound states. Our finding of increased S kinetic stability in the open conformation provides a new perspective on SARS-CoV-2 adaptation to the human population.
A Penalized Linear Mixed Model with Generalized Method of Moments for Complex Phenotype Prediction
Authors: Wang Xiaqiong , Wen Yalu
Published: October 2021

Linear mixed models have long been the method of choice for risk prediction analysis on high-dimensional genomic data. However, it remains computationally challenging to simultaneously model a large amount of genetic variants that can be noise or have predictive effects of complex forms. In this work, we have developed a penalized linear mixed model with generalized method of moments (pLMMGMM) estimators for prediction analysis. pLM-MGMM is built within the linear mixed model framework, where random effects are used to model the joint predictive effects from all genetic variants within a region. Fundamentally different from existing methods that usually focus on linear relationships and use empirical criteria for feature screening, pLMMGMM can jointly consider a large number of genetic regions and efficiently select those harboring variants with both linear and non-linear predictive effects. Through theoretical investigations, we have shown that our method has the selection consistency, estimation consistency and asymptotic normality. Through extensive simulations and the analysis of PET-imaging outcomes, we have demonstrated that pLMMGMM outperformed existing models and it can accurately detect regions that harbor risk factors with various forms of predictive effects.
Topological Constraints on Noise Propagation in Gene Regulatory Networks
Authors: Mahajan Tarun , Singh Abhyudai , Dar Roy D.
Published: October 2021

Gene expression, the production of protein from DNA and mRNA in the biological cell, is inherently stochastic. Cells with identical DNA exhibit fluctuations or ‘noise’ in gene expression. This noise propagates over gene regulatory networks (GRNs), which encode gene-gene interactions. The propagated ‘extrinsic’ noise interacts and combines with ‘intrinsic’ noise to affect biological decisions. Consequently, it is essential to understand how GRN topology affects total noise. Recently, uncertainty principles were established for noise propagation over GRN. In particular, in ring GRNs, exactly one node can have noise reduction below the intrinsic limit. We establish necessary and sufficient conditions for noise reduction in ring GRN. Specifically, for two- and three-node rings, an odd number of negative regulations is necessary for noise reduction. Further, sufficiency is ensured if sensitivities to input for feedforward and feedback regulations are bounded from below and above, respectively. These constraints are valid even if the ring GRN are regulated by an upstream gene. Finally, we use graph theory to decompose noise propagation in a general directed network over its strongly connected components. The combination of graph theory and stochastic processes may be a general framework for studying noise propagation.
White matter microstructural and morphometric alterations in autism: Implications for intellectual capabilities
Authors: Yeh Chun-Hung , Tseng Rung-Yu , Ni Hsing-Chang , Cocchi Luca , Chang Jung-Chi , Hsu Mei-Yun , Tu En-Nien , Wu Yu-Yu , Chou Tai-Li , Gau Susan Shur-Fen , Lin Hsiang-Yuan
Published: October 2021

Background

Neuroimage literature of autism spectrum disorder (ASD) has a moderate-to-high risk of bias, partially because those combined with intellectual impairment (II) and/or minimally verbal (MV) status are generally ignored. We aimed to provide more comprehensive insights into white matter alterations of ASD, inclusive of individuals with II (ASD-II-Only) or MV expression (ASD-MV).

Methods

Sixty-five participants with ASD (ASD-Whole; 16.6±5.9 years; comprising 34 intellectually able youth, ASD-IA, and 31 intellectually impaired youth, ASD-II, including 24 ASD-II-Only plus 7 ASD-MV) and 38 demographic-matched typically developing controls (TDC; 17.3±5.6 years) were scanned in accelerated diffusion-weighted MRI. Fixel-based analysis was undertaken to investigate the categorical differences in fiber density (FD), fiber cross-section (FC), and a combined index (FDC), and brain-symptom/cognition associations.

Results

ASD-Whole had reduced FD in the anterior and posterior corpus callosum and left cerebellum Crus I, and smaller FDC in right cerebellum Crus II, compared to TDC. ASD-II, relative to TDC, showed almost identical alterations to those from ASD-Whole vs. TDC. ASD-II-Only had greater FD/FDC in the isthmus-splenium of callosum than ASD-MV. Autistic severity negatively correlated with FC in right Crus I. Non-verbal full-scale IQ positively correlated with FC/FDC in cerebellum VI. FD/FDC of the right dorsolateral prefrontal cortex showed a diagnosis-by-executive function interaction.

Limitations

We could not preclude the potential effects of age and sex from the ASD cohort, although statistical tests suggested that these factors were not influential. Our results could be confounded by variable psychiatric comorbidities and psychotropic medication uses in our ASD participants recruited from outpatient clinics, which is nevertheless closer to a real-world presentation of ASD. The outcomes related to ASD-MV were considered preliminaries due to the small sample size within this subgroup.

Finally, our study design did not include intellectual impairment-only participants without ASD to disentangle the mixture of autistic and intellectual symptoms.

Conclusions

ASD-associated white matter alterations appear driven by individuals with II and potentially further by MV. Results suggest that changes in the corpus callosum and cerebellum are key for psychopathology and cognition associated with ASD. Our work highlights an essential to include understudied sub-populations on the spectrum in research.
The neurodevelopmental disorder-linked PHF14 complex that forms biomolecular condensates detects DNA damage and promotes repair
Authors: Käsper Eva-Lotta , Hwang In-Young , Grötsch Helga , Fung Herman Kar Ho , Sérandour Aurélien A. , Arecco Niccolò , Oellers Ronald , Poliński Patryk , Gomez-Monedero Almudena Garcia , Müller Christoph W. , Noh Kyung-Min
Published: October 2021

Numerous chromatin-associated proteins have been linked to neurodevelopmental disorders, yet their molecular functions often remain elusive. PHF14, HMG20A, TCF20 and RAI1 are components of a putative chromatin-associated complex and have been implicated in neurological disorders. Here, we found that Phf14 knockout embryonic stem cells and neural progenitor cells exhibit impaired cell cycle progression and proliferation, inadequate protection of stalled replication forks, and decreased DNA repair. The PHF14 complex rapidly assembles at DNA damage sites and binds to DNA through HMG20A. The PHF14 complex forms DNA-containing phase separated droplets in vitro, where TCF20 facilitates droplet formation. Furthermore, TCF20 maintenance at DNA damage sites is destabilized upon pathological mutation. Our results suggest that the PHF14 complex contributes to DNA damage repair by sensing damaged sites and forming biomolecular condensates, thus supporting cell cycle progression, especially in neural progenitor cells whose spatiotemporal pool is critical for proper brain development.
Locus-Specific DNA Methylation Editing in Mammalian Cells using a CRISPR-Based System
Authors: Smith Jim , Banerjee Rakesh , Waly Reema , Urbano Arthur , Gimenez Gregory , Day Robert , Eccles Michael R. , Weeks Robert J. , Chatterjee Aniruddha
Published: October 2021

DNA methylation is a key epigenetic modification implicated in the pathogenesis of numerous human diseases, including cancer development and metastasis. Gene promoter methylation changes are widely associated with transcriptional deregulation and disease progression. The advent of CRISPR-based technologies has provided a powerful toolkit for locus-specific manipulation of the epigenome. Here, we describe a comprehensive global workflow for the design and application of a dCas9-SunTag-based tool for editing a DNA methylation locus in human melanoma cells, alongside protocols for downstream techniques used to evaluate subsequent methylation and gene expression changes in methylation-edited cells. Using transient system delivery, we demonstrate both highly efficacious methylation and demethylation of the EBF3 promoter, a putative epigenetic driver of melanoma metastasis, achieving up to 304.00% gain of methylation and 99.99% relative demethylation, respectively. Further, we employ a novel, targeted screening approach to confirm minimal off-target activity and high on-target specificity of our editing sys-tem within our target locus.
Control of protein activity by photoinduced spin polarized charge reorganization
Authors: Ghosh Shirsendu , Banerjee-Ghosh Koyel , Levy Dorit , Scheerer David , Riven Inbal , Shin Jieun , Gray Harry B. , Naaman Ron , Haran Gilad
Published: October 2021

Considerable electric fields are present within living cells, and the role of bioelectricity has been well established at the organismal level. Yet little is known about electric-field effects on protein function. Here we use phototriggered charge injection from a site-specifically attached ruthenium photosensitizer to directly demonstrate the effects of charge redistribution within a protein. We find that binding of an antibody to phosphoglycerate kinase (PGK) is increased two folds under illumination. Remarkably, illumination is found to suppress the enzymatic activity of PGK by a factor as large as three. These responses are sensitive to the photosensitizer position on the protein. Surprisingly, left (but not right) circularly polarized light elicits these responses, indicating that the electrons involved in the observed dynamics are spin polarized, due to spin filtration by protein chiral structures. Our results directly establish the contribution of electrical polarization as an allosteric signal within proteins. Future experiments with phototriggered charge injection will allow delineation of charge rearrangement pathways within proteins and will further depict their effects on protein function.

Significance Statement

The role of well-placed charges within proteins in mediating biological functions, from protein-protein association to enzyme kinetics, is well documented. Here we go beyond this static picture and show that charge motions can exert significant effects on protein function. Injecting charge from a photosensitizer, we demonstrate a three-fold decrease in enzymatic activity and a two-fold increase of antibody-antigen binding. These effects depend on the specific position of the photosensitizer on the protein. Our results point to charge reorganization as a form of allostery that complements known allosteric mechanisms such as conformational changes and dynamics.
G2 stem cells orchestrate time-directed, long-range coordination of calcium signaling during skin epidermal regeneration
Authors: Moore Jessica L , Gao Feng , Matte-Martone Catherine , Du Shuangshuang , Lathrop Elizabeth , Ganesan Smirthy , Shao Lin , Bhaskar Dhananjay , Cox Andy , Hendry Caroline , Rieck Bastian , Krishnaswamy Smita , Greco Valentina
Published: October 2021

Skin epidermal homeostasis is maintained via constant regeneration by stem cells, which must communicate to balance their self-renewal and differentiation. A key molecular pathway, Ca2+ signaling has been implicated as a signal integrator in developing and wounded epithelial tissues[1, 2, 3, 4]. Yet how stem cells carry out this signaling across a regenerative tissue remains unknown due to significant challenges in studying signaling dynamics in live mice, limiting our understanding of the mechanisms of stem cell communication during homeostasis. To interpret high dimensional signals that have complex spatial and temporal patterns, we combined optimized imaging of Ca2+ signaling in thousands of epidermal stem cells in living mice with a new machine learning tool, Geometric Scattering Trajectory Homology (GSTH). Using a combination of signal processing, data geometry, and topology, GSTH captures patterns of signaling at multiple scales, either between direct or distant stem cell neighbors. Here we show that epidermal stem cells display dynamic intercellular Ca2+ signaling among neighborhoods of up to 10 cells that is surprisingly coordinated and directed through time across a pool of thousands of stem cells. We find that this collective coordination is an emergent property of the stem cell compartment, distinct from excitatory quiescent neuronal tissues. We demonstrate that cycling stem cells, specifically G2 cells, govern homeostatic patterns of Ca2+ signaling. Stem cells in different cell cycle stages dynamically regulate localization of the gap junction component Connexin43 (Cx43). Lastly, we uncouple global from local communication and identify Cx43 as the molecular mediator necessary for connectivity between local signaling neighborhoods. This work provides resolution in how stem cells at different stages of the cell cycle communicate and how that diversity of phases is essential for tissue wide communication and signaling flow during epidermal regeneration. Our approach provides a framework to investigate stem cell populations and their signaling dynamics, previously not possible.
Consequences of alanine-126 mutations in helix-3 on structure and functions of Rad6 E2 ubiquitin-conjugating enzymes
Authors: Shukla Prakash K. , Sinha Dhiraj , Leng Andrew M. , Bissell Jesse E. , Thatipamula Shravya , Ganguly Rajarshi , Skalicky Jack J. , Shrieve Dennis C. , Chandrasekharan Mahesh B.
Published: October 2021

Rad6, an E2 ubiquitin-conjugating enzyme conserved from yeast to humans, functions in transcription, genome maintenance and proteostasis. The contributions of many conserved secondary structures of Rad6 and its human homologs UBE2A and UBE2B to their biological functions are not understood. A mutant RAD6 allele with a missense substitution at alanine-126 (A126) of helix-3 that causes defects in telomeric gene silencing, DNA repair and protein degradation was reported over two decades ago. Here, using a combination of genetics, biochemical, biophysical, and computational approaches, we discovered that helix-3 A126 mutations compromise the ability of Rad6 to ubiquitinate target proteins without disrupting interactions with partner E3 ubiquitin-ligases that are required for their various biological functions in vivo. Explaining the defective in vitro or in vivo ubiquitination activities, molecular dynamics simulations and NMR showed that helix-3 A126 mutations cause local disorder of the catalytic pocket of Rad6 in addition to disorganizing the global structure of the protein to decrease its stability in vivo. We also show that helix-3 A126 mutations deform the structures of UBE2A and UBE2B, the human Rad6 homologs, and compromise the in vitro ubiquitination activity and folding of UBE2B. In summary, our studies reveal that the conserved helix-3 is a crucial structural constituent that controls the organization of catalytic pockets, enzymatic activities, and biological functions of the Rad6-family E2 ubiquitin-conjugating enzymes.
Architect: a tool for producing high-quality metabolic models through improved enzyme annotation
Authors: Nursimulu Nirvana , Moses Alan M. , Parkinson John
Published: October 2021

Motivation

Constraints-based modeling is a powerful framework for understanding growth of organisms. Results from such simulation experiments can be affected at least in part by the quality of the metabolic models used. Reconstructing a metabolic network manually can produce a high-quality metabolic model but is a time-consuming task. At the same time, current methods for automating the process typically transfer metabolic function based on sequence similarity, a process known to produce many false positives.

Results

We created Architect, a pipeline for automatic metabolic model reconstruction from protein sequences. First, it performs enzyme annotation through an ensemble approach, whereby a likelihood score is computed for an EC prediction based on predictions from existing tools; for this step, our method shows both increased precision and recall compared to individual tools. Next, Architect uses these annotations to construct a high-quality metabolic network which is then gap-filled based on likelihood scores from the ensemble approach. The resulting metabolic model is output in SBML format, suitable for constraints-based analyses. Through comparisons of enzyme annotations and curated metabolic models, we demonstrate improved performance of Architect over other state-of-the-art tools.

Availability

Code for Architect is available at https://github.com/ParkinsonLab/Architect.

Contact

john.parkinson@utoronto.ca

Supplementary information

Supplementary data are available at Bioinformatics online.
Loss of KRASG12D feedback regulation involving splicing factor SRSF1 accelerates pancreatic cancer
Authors: Wan Ledong , Lin Kuan-Ting , Rahman Mohammad Alinoor , Wang Zhikai , Jensen Mads A. , Park Youngkyu , Tuveson David A. , Krainer Adrian R.
Published: October 2021

The gene encoding KRAS GTPase is recurrently mutated in pancreatic ductal adenocarcinoma (PDAC), triggering the formation of precursor lesions, i.e., acinar-to-ductal metaplasia (ADM) and pancreatic intraepithelial neoplasia (PanIN). However, the majority of pancreatic cells from KC (LSL-KrasG12D/+; Pdx-1-Cre) mice expressing the KrasG12D mutation remain morphologically normal for a long time, suggesting the existence of compensatory feedback mechanisms that buffer aberrant KrasG12D signaling, and that additional steps are required for disrupting cell homeostasis and promoting transformation. Here we report a feedback mechanism in which the ubiquitously expressed splicing factor SRSF1—which is associated with cell transformation in multiple cell types—is downregulated in the majority of morphologically normal pancreas cells with the KrasG12D mutation. Conversely, increasing SRSF1 expression disrupts cell homeostasis by activating MAPK signaling, in part by regulating alternative splicing and mRNA stability of interleukin 1 receptor type 1 (Il1r1). This disruption in homeostasis in turn accelerates KrasG12D-mediated PDAC initiation and progression. Our results demonstrate the involvement of SRSF1 in the pancreatic-cell homeostatic response against the KrasG12D mutation, dysregulation of which facilitates PDAC initiation.

One-Sentence Summary

Splicing factor SRSF1 is involved in KRASG12D feedback regulation and pancreatic-cancer tumorigenesis.
Social ties, access to loans, and loan repayments in savings and loan associations: evidence from rural Tanzania
Authors: Pamuk Haki , van Asseldonk Marcel , Ruben Ruerd , Kweka Tumainiely , Wattel Cor , Hella Joseph Phillip
Published: October 2021

Purpose

Institutional structures of rural savings and loan associations influence their performances. One of the guiding principles for defining clear group membership boundaries is by setting rules on who has access. Social ties is a prominent requirement for membership. The objective of the current study is to provide quantitative evidence on the role of social ties membership criteria for the performance of saving and loan associations.

Design/methodology/approach

A cross-sectional survey was conducted in July–August 2019 comprising 48 associations in 13 villages in the Iringa District of Tanzania. In the current study, the authors use two indicators to measure the social ties between members, namely social closed association (the association applies criteria to accept only members who are relatives, friends or from the same hamlet) and physical distance (the fraction of members from other villages).

Findings

The authors find that associations are diverse both in terms of social ties, physical distance and performance, even in a small homogeneous region like Iringa District. Providing loans more easily to members with social ties has a negative relationship with loan repayment rates. Associations applying the social closeness criteria experience higher default rates than those not applying. The default rates become even worse when the fraction of member members from other villages increases in the socially tied associations.

Practical implications

Physically distant members are more likely to default as they perceive less social pressure in an association with socially tied members. Development practitioners and policy makers should integrate the potential implications.

Originality/value

The authors provide empirical evidence on the relevance of social ties on credit access and repayment in savings and loan associations, using a novel multi-level data on financial performance in the context of community-based finance organizations in rural areas.
Investment returns from reputation investing: do good firms provide good returns?
Authors: Beck Kristine L. , Chong James , Niendorf Bruce D.
Published: October 2021

Purpose

This study aims to examine whether a good corporate reputation leads to superior investment returns. Theory and empirics provide support for the idea that a good corporate reputation improves firm value, but much of the previous research fails to consider the risk of the companies they study and relies only on accounting measures of performance such as return on assets. A complete picture of the relationship between corporate reputation and shareholder value should include risk-adjusted returns and correlation with benchmark returns.

Design/methodology/approach

The Harris Poll Reputation Quotient (RQ), based on the reputations of the 100 most visible companies, suggests that companies with a “solid reputation” are more likely to be attractive investments. The authors construct portfolios using deciles and the RQ categories, rebalancing annually as RQ rankings are updated. Returns are adjusted for risk using Jensen's alpha, the information ratio, the Sharpe ratio, Modigliani and Modigliani's M2 measure, and Muralidhar's M3 measure.

Findings

The results indicate that choosing a portfolio based on the highest RQ-ranked firms does outperform the market on a risk-adjusted basis, and that the relationship between rankings and time-weighted returns is roughly monotonic. The authors also observe that corporate reputation is persistent, and that the best and worst most-visible firms are more likely to be privately held.

Originality/value

This research adds to the literature by including both market-based return measures and risk in the examination of the relationship between corporate reputation and financial performance.
Effect of botanical origin on stability and crystallization of honey during storage
Authors: Schiassi Maria Cecília Evangelista Vasconcelos , Souza Vanessa Rios de , Alves Nathila Angela , Lago Amanda Maria Teixeira , Silva Sérgio Henrique , Carvalho Gabriel Ribeiro , de Resende Jaime Vilela , Queiroz Fabiana
Published: October 2021

Purpose

The purpose of this paper was to study the effect of botanical origin on the characteristics of single-flower honeys (assa-peixe, coffee, eucalyptus, laranjeira and vassourinha), polyfloral (silvestre), extrafloral (sugarcane) and honeydew (bracatinga) during storage.

Design/methodology/approach

The honeys were stored at 14 °C, and the analysis of water activity, color, absorbance, rheological behavior and microscopic analysis were performed during 6 months (T0, T30, T60, T90, T120, T150 and T180 days); quantification of sugars (fructose (F) and glucose (G)), moisture (M), F/G and G/M ratio only at T0.

Findings

All honeys showed changes during storage, and sugarcane honey stood out for presenting greater crystallization, influenced by the high content of glucose and fructose. Coffee honey showed the least crystallization. The crystallization of honeys influenced the increase in water activity, Newtonian viscosity, color and absorbance. The composition of the honeys directly influenced the crystallization process during storage.

Originality/value

Crystallization is a natural process that occurs spontaneously in honey. Thus, the knowledge of the crystallization rate of honeys from different origins (botanical and geographical) during storage, is of great importance and interest for the industry, beekeepers and consumers, since each type of honey crystallizes in different ways and periods.
Exploring the link between entrepreneurship education and entrepreneurial intentions: the moderating role of educational fields
Authors: Duong Cong Doanh
Published: October 2021

Purpose

The purpose of this research is to integrate the prediction from entrepreneurship education with the theory of planned behaviors (TPB) to build a conceptual framework and estimate the effect of entrepreneurship education on entrepreneurial intention over and above key predictors from an extended TPB model. Also, the moderating impacts of educational fields in the paths from entrepreneurial education, attitude toward entrepreneurship, subjective norms and perceived behavioral control to entrepreneurial intention are tested in this study.

Design/methodology/approach

The study used a sample of 559 university students who received entrepreneurship education at 12 universities from Vietnam. Confirmatory factor analysis was utilized to test the validity and reliability of all variables and regression analyses were used to estimate coefficient paths. Then, bootstrapping method with the PROCESS approach was utilized to test the indirect correlations.

Findings

The study reveals that attitude toward entrepreneurship and perceived behavioral control were positively and strongly associated with entrepreneurial intention, while the linkage between subjective norms and entrepreneurial intention was not significant. Also, the findings show that even though entrepreneurship education did not have a direct effect on entrepreneurial intention, it increased entrepreneurial intention via attitude toward entrepreneurship and perceived behavioral control. In addition, this study finds that educational fields moderate the associations between predictors and entrepreneurial intention.

Practical implications

This study offers both universities and policymakers options to foster youths' entrepreneurial activities.

Originality/value

This study is expected to significantly contribute to entrepreneurship literature by enriching our understanding of the interesting and crucial linkages between entrepreneurship education, attitude toward entrepreneurship, subjective norms, perceived behavioral control and entrepreneurial intention. Additionally, the current research reveals that for economic and business management students, the paths are driven from entrepreneurial education, attitude toward entrepreneurship, subjective norms and perceived behavioral control to intention to engage in entrepreneurial activities has become stronger when compared to students of majors in engineering and others.
Covid-19 and performance disclosure: does governance matter?
Authors: Elmarzouky Mahmoud , Albitar Khaldoon , Hussainey Khaled
Published: October 2021

Purpose

This paper aims to investigate whether Covid-19 related information is associated with a higher level of performance disclosure in the annual reports. Furthermore, it examines the moderating effect of corporate governance on the relationship between Covid-19 and the performance disclosure by using three governance mechanisms: board size, board independence and gender diversity.

Design/methodology/approach

The authors use quantitative content analysis. The authors applied an automated textual analysis technique to measure the level of Covid-19 information and performance disclosure for the UK Financial Times Stock Exchange all-share non-financial firms.

Findings

The authors found a significant positive relationship between the Covid-19 disclosure and the firm performance disclosure in the annual reports. The authors also find that both board independence and gender diversity moderate the relationship between the Covid-19 related information and the level of performance disclosure in the annual reports. The authors further run a robustness analysis, which confirms the main results.

Practical implications

The finding is beneficial for the regulatory setters to better understand whether firms provide generic or meaningful Covid-19 information linked to the firm’s performance. The unique findings of this paper are relevant to regulators, governments, management, shareholders and academics.

Originality/value

The authors contribute to the literature in a unique and core research area not researched previously. The paper links the Covid-19 disclosure with the firm performance from the corporate narrative perspective. The paper underlines governance factors as a moderating role in this relationship by considering three main mechanisms: board size, board independence and gender diversity.
On the feasibility of reverse mortgages in Colombia
Authors: Benavides Franco Julian , Alonso Cifuentes Julio César , Carabalí Mosquera Jaime Andrés , Sosa Anibal
Published: October 2021

Purpose

The Colombian Government proposed a reverse mortgage mechanism to complement retirement income in Colombia. This paper aims to study its feasibility by valuing its premia.

Design/methodology/approach

Under a reverse mortgage scheme, banks issue put options on an owner’s home. To value the option, the authors apply a risk-neutral canonical approach modeling its three sources of risk: home future value, interest rate levels and homeowner life expectancy.

Findings

In all, premia values do not seem too high. However, if future interest rates are above the simulations or home appreciation is below its historical behavior, the premia could sharply increase, jeopardizing the system viability. Limiting the loan-to-home-value ratio or fixed-term annuities are feasible alternatives to keep premium increases at bay. Complementary mechanisms may also help.

Research limitations/implications

The home price and interest rate path estimation do not include inflation dynamics; in recent years inflation level was very low. However, the future does not offer any warrants. Future research also should cap the maximum loss the bank can endure. The pandemic may cause demographic changes affecting the viability of the reverse mortgage (R.M.) program in Colombia.

Practical implications

Based on the analysis, this work suggests possible government policies to help creditors and to maintain bank risks at a reasonable level.

Social implications

An adequate reverse mortgage program may help the policymakers in Colombia to face the adverse environment for Colombia’s housing market and the pressure of its pension system. A good R.M. program generates incentives to purchase homes, given the possibility of receiving an additional rent after retirement.

Originality/value

The paper develops an econometrical improvement over previous work. The authors present a time-series analysis that includes stationarity and co-integration information to model the data-generation process of house prices and interest rates in a multivariate fashion. The authors also improve the valuation formula. Moreover, the paper presents a novel application to Colombia. The authors obtain our demographic data from the United Nations Population Division applying the Lee-Carter method to model mortality rates, which provides ample possibilities to extend reverse mortgage assessment to additional. Finally, this is the first scholarly effort to evaluate the R.M. for the Colombian case.
An ensemble learning model for driver drowsiness detection and accident prevention using the behavioral features analysis
Authors: Sharanabasappa  , Nandyal Suvarna
Published: October 2021

Purpose

In order to prevent accidents during driving, driver drowsiness detection systems have become a hot topic for researchers. There are various types of features that can be used to detect drowsiness. Detection can be done by utilizing behavioral data, physiological measurements and vehicle-based data. The existing deep convolutional neural network (CNN) models-based ensemble approach analyzed the behavioral data comprises eye or face or head movement captured by using a camera images or videos. However, the developed model suffered from the limitation of high computational cost because of the application of approximately 140 million parameters.

Design/methodology/approach

The proposed model uses significant feature parameters from the feature extraction process such as ReliefF, Infinite, Correlation, Term Variance are used for feature selection. The features that are selected are undergone for classification using ensemble classifier.

Findings

The output of these models is classified into non-drowsiness or drowsiness categories.

Research limitations/implications

In this research work higher end camera are required to collect videos as it is cost-effective. Therefore, researches are encouraged to use the existing datasets.

Practical implications

This paper overcomes the earlier approach. The developed model used complex deep learning models on small dataset which would also extract additional features, thereby provided a more satisfying result.

Originality/value

Drowsiness can be detected at the earliest using ensemble model which restricts the number of accidents.
Airport service quality dimension and measurement: a systematic literature review and future research agenda
Authors: Usman Agus , Azis Yudi , Harsanto Budi , Azis Anton Mulyono
Published: October 2021

Purpose

The purpose of this paper is to outline the evolution of research on airport service quality and measurement index of passenger satisfaction to explore opportunities for future research direction.

Design/methodology/approach

A systematic literature review was conducted involving a total final sample 27 articles published during 2000–2020, the source of the database used in this study is Emerald, ScienceDirect, Harzing's Publish or Perish with API Key based on set of inclusion/exclusion criteria for analysis and synthesis to meet the purpose of the paper.

Findings

Dimensions of measuring airport service quality are currently based on a process approach. There are eight dimensions of ASQ measurement practiced by the industry, which is different from the five dimensions of service quality measurement generally. There is still a theoretical and empirical gap, so one of the challenges in applying the ASQ measurement dimensions is bridging research with applications in the airport industry. Other findings, research on airport service quality measurement is currently focused on passenger satisfaction. The integration of expectation-disconfirmation theory and service profit chain models can be used in service quality, passenger satisfaction and profitability.

Research limitations/implications

This paper seeks to contribute to and analyze limited articles on service quality at airports and identify further research areas.

Originality/value

This paper tries to explain the development of research on the dimensions of measuring service quality at airports. The author identifies a gap in airport service quality measurement dimensions used by researchers and the industry. The author believes that this study can provide a comprehensive thought on using airport service quality measurement dimensions for future research.
Consumers' intention to adopt virtual grocery shopping: do technological readiness and the optimisation of consumer learning matter?
Authors: Thomas-Francois Kimberly , Somogyi Simon
Published: October 2021

Purpose

It has generally been anticipated that the growth of Internet technology and e-commerce would result in virtual grocery shopping (VGS) becoming a normal way of life for consumers worldwide. However, the adoption of VGS, except in China and other Asian countries, has been quite slow and there is little understanding for this reason. Using Canada as a research context, the purpose of this study was to investigate the attitudes of consumers towards VGS with a focus on their technological readiness and the impact of the optimisation of consumer learning.

Design/methodology/approach

A quantitative research methodology was undertaken using cluster analysis with descriptive statistics to segment the different groups of consumers from a sample of 1,034 adult respondents. Structural equation modelling (SEM) was then used to test a theoretical model for consumers’ intention to adopt VGS.

Findings

The study found that the attitudes of consumers towards virtual shopping, convenience motivation, perceived ease of use (PEOU), perceived risk and consumer learning are all factors that impact consumers' intention to adopt virtual food shopping. The research also identified four segments of consumers in the Canadian market based on their attitudes and intention to adopt VGS. These results allow grocers to target the consumer groups favourable to VGS and provide insights on the factors that can be manipulated via marketing strategies to reach these consumers.

Practical implications

Retailers are provided with insights on consumers behaviour that will allow them to target specific segments with shopping modalities.

Originality/value

This research investigated VGS, focussing on consumer learning as a socio-cultural influence as well as the consumer's technological readiness as an intention to adopt to this modality of shopping for food. These constructs have not been investigated by previous studies on food grocery shopping.
Safe operation of gas pipelines based on the control of stress corrosion cracking
Authors: Ryakhovskikh Ilya , Kashkovskiy Roman , Kaverin Aleksandr , Stolov Vladimir , Zhedulov Sergey
Published: October 2021

Purpose

The paper is devoted to the phenomenon of stress corrosion cracking (SCC), which is an urgent problem for major operator companies that use large-diameter gas transport systems built in the second half of the last century. The aim of the study is to predict the operability of gas pipelines with SCC and ensure their safe operation.

Design/methodology/approach

The methodology of the article mainly consisted of strength calculations, mathematical and analytical approaches.

Findings

The paper describes practical methods of assessing the residual service life and operability of pipes with SCC defects as part of gas pipelines, the developed approaches to assessing the point of failure of pipes, provides recommendations for developing requirements to ILI smart tools in order to detect cracks and the methods of pipe repair depending on the SCC defect parameters.

Originality/value

The originality of the study consists in the analytical description of the point of destruction of gas pipelines with SCC, assessment of their performance, as well as the definition of modern requirements for the accuracy of in-line inspection to ensure the detection of potentially dangerous SCC defects.