bluuebunny/crossref_metadata_2025_split huggingface dataset:
Comparison and benchmark of deep learning methods for non-coding RNA classification
Authors: Creux Constance , Zehraoui Farida , Radvanyi François , Tahi Fariza 
Published: November 2023

AbstractThe involvement of non-coding RNAs in biological processes and diseases has made the exploration of their functions crucial. Most non-coding RNAs have yet to be studied, creating the need for methods that can rapidly classify large sets of non-coding RNAs into functional groups, or classes. In recent years, the success of deep learning in various domains led to its application to non-coding RNA classification. Multiple novel architectures have been developed, but these advancements are not covered by current literature reviews. We present an exhaustive comparison of the different methods proposed in the state-of-the-art and describe their associated datasets. Moreover, the literature lacks objective benchmarks. We perform experiments to fairly evaluate the performance of various tools for non-coding RNA classification on popular datasets. The robustness of methods to non-functional sequences and sequence boundary noise is explored. We also measure computation time and CO2emissions. With regard to these results, we assess the relevance of the different architectural choices and provide recommendations to consider in future methods. Datasets and reproducible codes are available athttps://evryrna.ibisc.univ-evry.fr/evryrna/ncBench.Author summaryRNA can either encode proteins, which perform different functions in the genome, or be non-coding. Non-coding RNAs represent around 98% of the genome, and were long thought to be non-functional. It has now been proven that non-coding RNAs can have diverse biological functions and be involved in diseases. A large proportion of non-coding RNAs has not yet been studied. The function of specific non-coding RNAs can be studied experimentally, but experiments are costly and time-consuming. One possibility to massively characterize the function of non-coding RNAs is to use computational methods to classify them into functional groups, or classes. Recent computational methods for non-coding RNA classification are all based on deep learning, as it leads to faster runtime and improved performance. Our work presents and compares the different approaches adopted in the state-of-the-art, as well as the non-coding RNA datasets that are used. We also present a comprehensive benchmark, measuring classification performance in different conditions, computation time, and CO2emissions. The descriptions and comparisons provided are meant to guide researchers in the field, whether wanting to use existing tools or to develop new ones.
Unbiased MD simulations characterize lipid binding to lipid transfer proteins
Authors: Srinivasan Sriraksha , Alvarez Lorenzo Daniel , Vanni Stefano 
Published: November 2023

AbstractThe molecular characterization of lipid binding to lipid transfer proteins (LTPs) is fundamental to the understanding of several aspects of their mechanistic mode of action. However, obtaining lipid-bound structures of LTPs is not straightforward owing to caveats in current experimental structural biology approaches. As a result, several structures of LTPs, and most notably almost all of those that have been proposed to act as bridges between membrane organelles, do not provide the precise location of their endogenous lipid ligands. To address this limitation, computational approaches are a powerful alternative methodology, but they are often limited by the high flexibility of lipid substrates. In this work, we develop anin silicoprotocol based on unbiased coarse grain molecular simulations in which lipids placed in bulk solvent away from the protein can spontaneously bind to LTPs. This approach accurately determines binding pockets in LTPs and provides a working hypothesis for the pathway via which lipids enter LTPs. We apply this approach to characterize lipid binding to bridge-like LTPs belonging to the Vps13-Atg2 family, for which the lipid localization inside the protein is currently unknown. Overall, our work paves the way to determine binding pockets and entry pathways for several LTPs in an inexpensive, fast, and accurate manner.
ASM Variants in the Spotlight: A Structure-Based Atlas for Unraveling Pathogenic Mechanisms in Lysosomal Acid Sphingomyelinase
Authors: Scrima Simone , Lambrughi Matteo , Tiberti Matteo , Fadda Elisa , Papaleo Elena 
Published: November 2023

AbstractLysosomal acid sphingomyelinase (ASM), a critical enzyme in lipid metabolism encoded by the SMPD1 gene, plays a crucial role in sphingomyelin hydrolysis in lysosomes. ASM deficiency leads to acid sphingomyelinase deficiency, a rare genetic disorder with diverse clinical manifestations, and the protein can be found mutated in other diseases. We employed a structure-based framework to comprehensively understand the functional implications of ASM variants, integrating pathogenicity predictions with molecular insights derived from molecular dynamics simulations in a lysosomal membrane environment. Our analysis, encompassing over 400 variants, establishes a structural atlas of missense variants of lysosomal ASM, associating mechanistic indicators with pathogenic potential. Our study highlights variants that influence structural stability or exert local and long-range effects at functional sites. To validate our predictions, we compared them to available experimental data on residual catalytic activity in 135 ASM variants. Notably, our findings also suggest applications of the resulting data for identifying cases suited for enzyme replacement therapy. This comprehensive approach enhances the understanding of ASM variants and provides valuable insights for potential therapeutic interventions.
The Chloroplast RNA Binding Protein CP29A supportsrbcLexpression during cold acclimation
Authors: Lenzen Benjamin , Rösch Florian , Ruwe Hannes , Kachariya Nitin , Legen Julia , Sattler Michael , Small Ian , Schmitz-Linneweber Christian 
Published: November 2023

AbstractThe chloroplast genome encodes key components of the photosynthetic light reaction machinery as well as the large subunit of the enzyme central for carbon fixation, RuBisCo. Its expression is predominantly regulated post-transcriptionally, with nuclear-encoded RNA binding proteins (RBPs) playing a key role. Mutants of chloroplast gene expression factors often exhibit impaired chloroplast biogenesis, especially in cold conditions. Low temperatures pose a challenge for plants as this leads to electron imbalances and oxidative damage. A well-known response of plants to this problem is to increase the production of RuBisCo and other Calvin Cycle enzymes in the cold, but how this is achieved is unclear. The chloroplast RBP CP29A has been shown to be essential for cold resistance in growing leaf tissue ofArabidopsis thaliana.Here, we examined CP29A-RNA interaction sites at nucleotide resolution. We discovered that CP29A preferentially binds to the 5’-UTR ofrbcL, downstream of the binding site of the pentatricopeptide repeat (PPR) protein MRL1. MRL1 is an RBP known to be necessary for the accumulation ofrbcL. InArabidopsismutants lacking CP29A, we were unable to observe significant effects onrbcL, possibly due to CP29A’s restricted role in a limited number of cells at the base of leaves. In contrast, CRISPR/Cas9-induced mutants of tobacco NtCP29A exhibit cold-dependent photosynthetic deficiencies throughout the entire leaf blade. This is associated with a parallel reduction inrbcLmRNA and RbcL protein accumulation. Our work unravels the molecular player behind cold acclimation of the photosynthetic dark reaction.Significance StatementThis study unveils the critical role of CP29A, a chloroplast-localized RNA binding protein, in facilitating plants’ acclimation to cold environments. Through advanced molecular techniques, we discovered that CP29A specifically targets the rbcL mRNA, vital for the production of RuBisCo—a key enzyme in photosynthesis and the most abundant protein on Earth. Our findings elucidate a previously unknown mechanism of how plants adjust to cold stress by regulating RuBisCo levels, highlighting the intricate interplay between nuclear and chloroplast genomes. This research not only advances our understanding of plant cold acclimation but also provides insights that could help enhance plant resilience and productivity when facing temperature challenges.
Predictive machine learning model for mental health issues in higher education students due to COVID-19 using HADS assessment
Authors: Krishnan Reshmy , Kumari Shantha , Badi Ali Al , Jeba Shermina , James Menila 
Published: November 2023

PurposeStudents pursuing different professional courses at the higher education level during 2021–2022 saw the first-time occurrence of a pandemic in the form of coronavirus disease 2019 (COVID-19), and their mental health was affected. Many works are available in the literature to assess mental health severity. However, it is necessary to identify the affected students early for effective treatment.Design/methodology/approachPredictive analytics, a part of machine learning (ML), helps with early identification based on mental health severity levels to aid clinical psychologists. As a case study, engineering and medical course students were comparatively analysed in this work as they have rich course content and a stricter evaluation process than other streams. The methodology includes an online survey that obtains demographic details, academic qualifications, family details, etc. and anxiety and depression questions using the Hospital Anxiety and Depression Scale (HADS). The responses acquired through social media networks are analysed using ML algorithms – support vector machines (SVMs) (robust handling of health information) and J48 decision tree (DT) (interpretability/comprehensibility). Also, random forest is used to identify the predictors for anxiety and depression.FindingsThe results show that the support vector classifier produces outperforming results with classification accuracy of 100%, 1.0 precision and 1.0 recall, followed by the J48 DT classifier with 96%. It was found that medical students are affected by anxiety and depression marginally more when compared with engineering students.Research limitations/implicationsThe entire work is dependent on the social media-displayed online questionnaire, and the participants were not met in person. This indicates that the response rate could not be evaluated appropriately. Due to the medical restrictions imposed by COVID-19, which remain in effect in 2022, this is the only method found to collect primary data from college students. Additionally, students self-selected themselves to participate in this survey, which raises the possibility of selection bias.Practical implicationsThe responses acquired through social media networks are analysed using ML algorithms. This will be a big support for understanding the mental issues of the students due to COVID-19 and can taking appropriate actions to rectify them. This will improve the quality of the learning process in higher education in Oman.Social implicationsFurthermore, this study aims to provide recommendations for mental health screening as a regular practice in educational institutions to identify undetected students.Originality/valueComparing the mental health issues of two professional course students is the novelty of this work. This is needed because both studies require practical learning, long hours of work, etc.
Exploring e-deal proneness: the interplay of price consciousness and anticipatory regret
Authors: Cheah Isaac , Shimul Anwar Sadat , 't Hart Brian 
Published: November 2023

PurposeThis research investigates the factors influencing consumers' intention to purchase e-deals from group buying websites, focussing on e-deal proneness, price consciousness and anticipatory regret.Design/methodology/approachThree studies (n = 539) were conducted using data collected from an online consumer panel and tested via structural equation modelling and PROCESS macro in SPSS.FindingsThe findings suggest that subjective norms, perceived behavioural control and attitudes positively influence consumers' e-deal purchase intention. Additionally, price consciousness amplifies the relationship between consumers' e-deal proneness and purchase intention, and price-conscious respondents are more likely to have the intention to buy e-deals when faced with some form of anticipatory regret.Practical implicationsBased on the research findings, practitioners are advised to prioritise social norms and entertainment value when promoting the attractiveness of e-deals, using strategies such as social media and influencer marketing. Brands should also emphasise the value of e-deals by showcasing comparative price savings and discounts to motivate consumers to buy.Originality/valueThis paper addresses an interesting and practical issue related to the effects of group buying websites, focussing on e-deal proneness, price consciousness and anticipatory regret.
Family involvement in ownership and governance and internal auditing quality
Authors: Ginesti Gianluca , Santonastaso Rosalinda , Macchioni Riccardo 
Published: November 2023

Purpose
This paper aims to investigate the impact of family involvement in ownership and governance on the quality of internal auditing.

Design/methodology/approach
Leveraging a hand-collected data set of listed family firms from 2014 to 2020, this study uses regression analyses to investigate the impact of family ownership, family involvement on the board, family CEO and the generational stage of the family business on the quality of internal auditing.

Findings
The results provide evidence that family ownership is positively associated with the quality of internal auditing, while later generational stages of family businesses have the opposite effect. Additional analyses reveal that the presence of a sustainability board sub-committee moderates the relationship between generational stages of family businesses and the quality of internal auditing function.

Research limitations/implications
This paper does not consider country-institutional factors and other potentially family-related antecedents or governance factors that may affect the quality of internal auditing.

Practical implications
The results are informative for investors and non-family stakeholders interested in understanding under which conditions family-related factors influence the quality of internal auditing functions.

Originality/value
This study offers fresh evidence regarding the relationship between family-related factors and the quality of internal auditing and board sub-committees that moderate such a relationship in family businesses.
A paradigm shift toward the application of blockchain in enhancing quality information management
Authors: Sati Abdulrahman , Al-Tabtabai Hashem 
Published: November 2023

Purpose
Lack of trust and poor quality of construction deliverables have become a serious matter nowadays. This is due to the absence of a uniform and decentralized system for managing quality information. In Kuwait’s industry, many incidents have been recorded as a lack of confidence in the authenticity and integrity of the documented data in the system. This paper aims to shed the light on a framework that would tackle this matter.

Design/methodology/approach
A designed framework using Blockchain technology (Hyperledger Fabric) has been used to create a transparent and decentralized environment between the parties. A digitalized informative checklist referred to as “Smart Construction Inspection Checklist (SCIC)” has been initiated to enhance the poor information recorded between the parties.

Findings
The framework has provided a transparent, immutable, traceable and decentralized environment in which all parties are involved in transactions. In addition, the integration of the SCIC in the blockchain environment provided an advantage in which all the necessary criteria of inspection will be stated, checked by the consultant and validated by the client to approve the transaction. A preliminary testing has been conducted to support the proposed framework.

Originality/value
This study fulfils the gap in the state of art for further studies to practically apply the framework that will enhance the quality of information management in Kuwait’s industry.
Does workplace spirituality predict turnover intention in small- and medium-sized enterprises (SMEs)
Authors: Pariyanti Eka , Adawiyah Wiwiek Rabiatul , Wulandari Siti Zulaikha 
Published: November 2023

PurposeThe main objective of this study is to examine the relationship between person-organization fit (P-O fit), job satisfaction (JS), workplace spirituality (WS) and turnover intentions in small and medium-sized enterprises (SMEs) and the moderate role of WS in these relationships.Design/methodology/approachResearch data were collected by cross-sectional data collection methods. The sample contains 242 employees of SMEs in Indonesia. The analytical method used to test research hypotheses is moderate regression analysis.FindingsThe results show that P-O fit is an antecedent that can reduce turnover intention. JS has a negative effect on turnover intention and WS has a negative effect on turnover intention. WS moderates the relationship between P-O fit and turnover intention and the relationship between JS and turnover intention.Research limitations/implicationsThis study enhances the understanding of the importance of WS in reducing employee turnover intentions. This research also contributes to the research model based on fit theory and social exchange theory.Practical implicationsThe practical implication of this research is to improve P-O fit in employees. Managers can manage the right people for the environment and the right environment for the individual. In other words, the organization must choose both. The most basic way to create a P-O fit for employees is to recruit employees suitable to organizational goals because, in general, SMEs rarely have a written vision and mission.Social implicationsThrough the of spirituality in the workplace, employees will experience a sense of meaning and purpose in their work, foster a sense of unity through positive relationships and achieve alignment between personal and organizational values. Consequently, this will diminish the inclination to seek employment elsewhere.Originality/valueAlthough turnover intention in employees is considered necessary, there is still minimal research that discusses turnover intention and WS in SMEs. To the authors' knowledge, no one has tested WS on the relationship between PO fit and JS with turnover intention in SMEs.
Effect of construction project managers’ conflict management styles on team resilience: a moderated mediation model of team followership and team power distance
Authors: Ma Li , Lu Yongqiang 
Published: November 2023

Purpose
The purpose of this study is to examine how construction project managers’ conflict management styles (CMSs) affect project team resilience from the perspective of social identity theory.

Design/methodology/approach
This study adopted a cross-sectional survey design and collected paired data from 110 construction project managers and 474 employees in China. Based on the data collected, the authors tested the proposed hypotheses using hierarchical regression analysis.

Findings
The results show that a project manager’s cooperative CMS positively affects team resilience, and a project manager’s competitive and avoidant CMS negatively affects team resilience. Team followership plays a mediating role in this relationship. The team power distance moderates the effects of a project manager’s cooperative and avoidant CMSs on team followership.

Originality/value
This paper enriches the existing literature on conflict management in construction projects and have potential guiding significance and application value for team resilience management practices.
Midwifery students’ perceptions on ethical rights of women using assisted reproductive technologies
Authors: Ejder Tekgündüz Sibel , Gürol Ayşe , Ejder Apay Serap 
Published: November 2023

Purpose
This study aims to understand how midwifery students view ethical rights concerning the usage of reproductive technologies.

Design/methodology/approach
A series of focus groups were conducted with midwifery students who were asked to discuss four novel scenarios highlighting some of the most controversial issues on the ethics of assisted reproductive technologies. The sample consisted of third-year students studying at the Department of Midwifery of a university in the fall semester of the 2020–2021 academic year. In total, 60 students aged between 20 and 23 participated in the study (mean age 21.5 years).

Findings
Four scenarios that may be encountered in the use of assisted reproductive techniques were presented to the students. These scenarios were about IVF treatment, using the preimplantation gender identification technique, surrogate mother and using frozen zygotes. Four themes were identified from the analysis of the focus group data related to all four scenarios. These themes were: female reproduction, sex selection, surrogacy and reproductive cloning.

Originality/value
This study reveals what midwifery students consider essential components of assisted reproduction techniques, focusing on the professional attributes of shared decision-making. The results suggest that student midwives are sensitive to the range of ethical dilemmas associated with the increased use of technology in human reproduction, and construct distinct bound arise in relation to what is considered of benefit or good to the mother, parents, the child and to society. They also expressed their opposition to the excessive use of technological intervention, preferring instead to maintain a more naturalistic approach to reproduction.
Redirecting to sustainable menstrual products – a holistic approach for improving public health
Authors: Ahuja Prerna , Singh Navjit 
Published: November 2023

Purpose
Access to good menstrual products is a human rights concern. It is essential for normalising the life during menstrual cycles by making available all the resources necessary for managing them. Sustainable menstrual products are the novel products which can improve the women menstrual lifestyles and reduce the discomfort associated with menstruation. However, these products are not readily adopted by the women due to their perception resulting from various factors. Hence, this study aims to figure out these perceptions, which can promote and hinder the adoption of these products.

Design/methodology/approach
A survey was conducted for the purpose of data collection. The study uses questionnaire as a research instrument to gain an insight on women health beliefs towards sustainable menstrual products. Data was collected from the women respondents through convenience sampling. Structural equation modelling was applied to analyse the data.

Findings
The findings suggest that women with appropriate knowledge had a positive perception towards the sustainable menstrual products, further leading to positive behaviour. It was also noted that marketing efforts through cues to action had an impact on their behavioural patterns. The policymakers and the marketers can focus on such prospects to advocate the use of sustainable menstrual products so that healthcare is improved.

Originality/value
To the best of the authors’ knowledge, this is the first study that provides a comprehensive framework for analysing the impact of women health beliefs towards behaviour of sustainable menstrual products. The study adds meaningful insights to the sustainable menstrual literature.