bluuebunny/crossref_metadata_2025_split huggingface dataset:
Benchmarking of Small Molecule Feature Representations for hERG, Nav1.5, and Cav1.2 Cardiotoxicity Prediction
Authors: Arab Issar , Egghe Kristof , Laukens Kris , Chen Ke , Barakat Khaled , Bittremieux Wout 
Published: August 2023

AbstractIn the field of drug discovery, there is a substantial challenge in seeking out chemical structures that possess desirable pharmacological, toxicological, and pharmacokinetic properties. Complications arise when drugs interfere with the functioning of cardiac ion channels, leading to serious cardiovascular consequences. The discontinuation and removal of numerous approved drugs from the market or at late development stages in the pipeline due to such inhibitory effects further highlight the urgency of addressing this issue. Consequently, the early prediction of potential blockers targeting cardiac ion channels during the drug discovery process is of paramount importance. This study introduces a deep learning framework that computationally determines the cardiotoxicity associated with the voltagegated potassium channel (hERG), the voltage-gated calcium channel (Cav1.2), and the voltage-gated sodium channel (Nav1.5) for drug candidates. The predictive capabilities of three feature representations—molecular fingerprints, descriptors, and graph-based numerical representations— are rigorously benchmarked. Additionally, a novel training and evaluation dataset framework is presented, enabling predictive model training of drug off-target cardiotoxicity using a comprehensive and large curated dataset covering these three cardiac ion channels. To facilitate these predictions, a robust and comprehensive small molecule cardiotoxicity prediction tool named CToxPred has been developed. It is made available as open source under the permissive MIT license athttps://github.com/issararab/CToxPred.
A 3D-printed and freely available device to measure the zebrafish optokinetic response before and after injury
Authors: Hermans Ashley , Tajnai Sophia , Tieman Allison , Young Sarah , Franklin Ashley , Horutz Mackenzie , Henle Steven 
Published: August 2023

AbstractZebrafish have eyes similar to humans, making them a beneficial model organism for studying vision. However, zebrafish are different in that they can regenerate their optic nerve after injury, which most other animals cannot. Measuring vision in people who have communicative ability is achieved using eye charts. Because fish cannot use an eye chart, we utilize the optokinetic response (OKR) that is present in virtually all vertebrates to determine if a zebrafish has eyesight. To this end, we have developed an inexpensive OKR setup that uses 3D-printed and off-the-shelf parts. This setup has been designed and used by undergraduate researchers and is also scalable to a classroom lab setup. We demonstrate that this setup is fully functional for assessing OKR, and we use it to illustrate the return of the OKR following optic nerve injury in adult zebrafish.
Novel Insights into the Aortic Mechanical Properties of Mice Modeling Hereditary Aortic Diseases
Authors: Dubacher Nicolo , Sugiyama Kaori , Smith Jeffrey D. , Nussbaumer Vanessa , Csonka Máté , Ferenczi Szilamér , Kovács Krisztina J. , Caspar Sylvan M. , Lamberti Lisa , Meienberg Janine , Yanagisawa Hiromi , Sheppard Mary B. , Matyas Gabor 
Published: August 2023

ABSTRACTOBJECTIVEHereditary aortic diseases (hADs) increase the risk of aortic dissections and ruptures. Recently, we have established an objective approach to measure the rupture force of the murine aorta, thereby explaining the outcomes of clinical studies and assessing the added value of approved drugs in vascular Ehlers-Danlos syndrome (vEDS). Here, we applied our approach to six additional mouse hAD models.APPROACH AND RESULTWe used two mouse models of Marfan syndrome (MFS) as well as one smooth-muscle-cell-specific knockout (SMKO) ofEfemp2and three CRISPR/Cas9-engineered knock-in models (Ltbp1,Mfap4, andTimp1). One of the two MFS models was subjected to 4-week-long losartan treatment. Per mouse, three rings of the thoracic aorta were prepared, mounted on a tissue puller, and uniaxially stretched until rupture. The aortic rupture force of the SMKO and both MFS models was significantly lower compared with wild-type mice but in both MFS models higher than in mice modeling vEDS. In contrast, theLtbp1,Mfap4, andTimp1knock-in models presented no impaired aortic integrity. As expected, losartan treatment reduced aneurysm formation but surprisingly had no impact on the aortic rupture force of our MFS mice.CONCLUSIONSOur read-out system can characterize the aortic biomechanical integrity of mice modeling not only vEDS but also related hADs, allowing the aortic-rupture-force- focused comparison of mouse models. Furthermore, aneurysm progression alone may not be a sufficient read-out for aortic rupture, as antihypertensive drugs reducing aortic dilatation might not strengthen the weakened aortic wall. Our results may enable identification of improved medical therapies of hADs.HighlightsAssay to measure the aortic rupture force as read-out for the biomechanical integrity identified weakened murine thoracic aorta prior to micro- and macroscopic changes inFbn1+/C1041Gmice.Despite reducing aneurysm growth, losartan treatment did not have any impact on the aortic rupture force ofFbn1mgR/mgRmice modeling MFS.Smooth-muscle-cell-knock-out ofEfemp2significantly impaired the rupture force of the murine ascending aorta.Aortic rupture force measurements could clarify the causality of novel candidate gene(s)/variant(s) in mouse models of aortic diseases.Graphical Abstract
MarsGT: Multi-omics analysis for rare population inference using single-cell graph transformer
Authors: Wang Xiaoying , Duan Maoteng , Li Jingxian , Ma Anjun , Xu Dong , Li Zihai , Liu Bingqiang , Ma Qin 
Published: August 2023

AbstractRare cell populations are key in neoplastic progression and therapeutic response, offering potential intervention targets. However, their computational identification and analysis often lag behind major cell types. To fill this gap, we introduced MarsGT: Multi-omics Analysis for Rare population inference using Single-cell Graph Transformer. It identifies rare cell populations using a probability-based heterogeneous graph transformer on single-cell multi-omics data. MarsGT outperformed existing tools in identifying rare cells across 400 simulated and four real human datasets. In mouse retina data, it revealed unique subpopulations of rare bipolar cells and a Müller glia cell subpopulation. In human lymph node data, MarsGT detected an intermediate B cell population potentially acting as lymphoma precursors. In human melanoma data, it identified a rare MAIT-like population impacted by a high IFN-I response and revealed the mechanism of immunotherapy. Hence, MarsGT offers biological insights and suggests potential strategies for early detection and therapeutic intervention of disease.
LC-UV/RI-MS2as the analytical platform for bioconversion of sustainable carbon sources: a showcase of 1,4-butanediol plastic monomer degradation usingUstilago trichophora
Authors: Phan An N.T. , Prigolovkin Lisa , Blank Lars M. 
Published: August 2023

ABSTRACTPlastic usage by microbes as a carbon source is a promising strategy to increase the recycling quota. 1,4-butanediol (BDO) is a common monomer derived from polyesters and polyurethanes. It presents in the complex mixture from the plastic degradation process. In this study,Ustilago trichophorawas found to be an efficient cell-factory to valorize BDO. To investigate product formation byU. trichophora, we refined the traditional ion exclusion liquid chromatography method by examining eluent, eluent concentrations, oven temperatures, and organic modifiers to make the chromatography compatible with mass spectrometry. An LC-UV/RI-MS2method is presented here to identify and quantify extracellular metabolites in the cell cultures. With this method, we successfully identified thatU. trichophorasecreted malic acid, succinic acid, erythritol, and mannitol into the culture medium. Adaptive laboratory evolution followed by medium optimization significantly improvedU. trichophoragrowth on BDO and especially malic acid production. Overall, the carbon yield on the BDO substrate was approximately 33% malic acid. This is the first report on a Ustilaginaceae fungus that was able to convert BDO into versatile chemical building blocks. SinceU. trichophorais not genetically engineered, it is a promising microbial host to produce malic acid from BDO, thereby contributing to the development of the envisaged sustainable bioeconomy.
Human sensorimotor resting state beta events and 1/f response show good test-retest reliability
Authors: Pauls Amande , Nurmi Pietari , Ala-Salomäki Heidi , Renvall Hanna , Kujala Jan , Liljeström Mia 
Published: August 2023

AbstractNeurological conditions affecting the sensorimotor system have a profound impact on individuals’ physical independence and are associated with a considerable socioeconomic burden. Reliable functional biomarkers allowing early diagnosis of these conditions or targeting treatment and rehabilitation can reduce this burden. Magnetoencephalography (MEG) can non-invasively measure the brain’s salient rhythmic patterns such as the somatomotor (‘rolandic’) rhythm. This rhythm shows intermittent high amplitude ‘events’ in the beta (14-30 Hz) frequency range which predict behavior across tasks and species and are altered by neurological diseases affecting the sensorimotor system. Thus, the sensorimotor resting beta phenotype is a promising candidate biomarker of sensorimotor function. A prerequisite for use as a biomarker is that it can be quantified reliably across different measurement sessions. Here, using MEG, we assessed the test-retest stability of spontaneously occurring sensorimotor power spectral characteristics, including both aperiodic (1/f) as well as beta band fluctuations (‘beta events’) in a cohort of 50 healthy human controls. Test-retest reliability across two separate measurement sessions was assessed using the intraclass correlation coefficient (ICC). Beta events were determined using a thresholding-based approach on a narrow-band filtered amplitude envelope obtained using Morlet wavelet decomposition across a range of parameters (recording length, amplitude threshold and filtering bandwidth). We find that both aperiodic power spectral features as well as several beta event characteristics show good to excellent testretest stability. Especially aperiodic component power spectral features (ICC 0.77-0.88), but also measures of beta event amplitude (ICC 0.74-0.82) were found to be very stable, while measures of individual beta event duration were less reliable, especially for the left hemisphere (ICC right ∼0.7, left ∼0.55). Recordings of 2-3 minutes were sufficient to obtain stable results for most parameters. Important for potential clinical applications, automatization of beta event extraction was successful in 86 % of cases. Beta event rate and duration measures were more sensitive to analysis parameters than the measures of event amplitude. The results suggest the sensorimotor beta phenotype is a stable feature of an individual’s resting brain activity even for short, 2-3 minute recordings which can be easily measured in patient populations, facilitating its use as a potential clinical biomarker.
Leveraging collaborations to increase the impact of food sharing platforms
Authors: Michelini Laura , Grieco Cecilia , Dentchev Nikolay 
Published: August 2023

PurposeThe purpose of the paper is to explore how collaborations can increase the impact of food sharing platforms, which offer the potential to reduce food waste by facilitating contact between suppliers and consumers. With this comes the need to address the twofold challenge of being digital and having an economic and social-environmental mission. Thus, adopting a system perspective and recognizing stakeholders as part of a value network can maximize the generated impact.Design/methodology/approachA multiple case study analysis has been conducted on 12 food sharing platforms. Data have been collected through semi-structured interviews, triangulated with internal and external documents and content analysed.FindingsThe research outlines the systems of collaboration found in food sharing platforms characterized by two levels of actors (platform players and business players) and five different types of collaboration that can help platforms maximize their impact (boosting the network effect; capturing value; enhancing the business model; extending the type of impact; and scaling up).Originality/valueThe research offers important contributions for the advancement of the field, adding evidence on the opportunities offered by collaborations to generate impact for business and society in the context of the sharing economy and food industry. The research allows to identify the concept of “sustainability-oriented sharing platforms” as a subset of sharing economy platforms characterized by a dual mission and related challenges. From a managerial point of view, the study highlights how designing and implementing collaborations with the stakeholders can increase platforms' impact consistently with the life cycle and short- and long-term perspectives.
Board chairman characteristics and impression management: an empirical investigation. Further analysis
Authors: Al-Sayani Yahya Mohammed , Al-Matari Ebrahim Mohammed , Mohamad Nor Mohamad Naimi , Amran Noor Afza , Alsayani Mohammed Ahmed 
Published: August 2023

PurposeThe purpose of this study is to look at the structure of the interactions between the board of directors’ chairman qualities such as chairman independence, tenure, ethnicity, age- and impression management (IM).Design/methodology/approachThe research population consists of non-financial Malaysian companies listed on Bursa Malaysia’s Main Market, using data gathered via annual reports and DataStream. The study relies on the ordinary least square regression to test the direct relationships between the directors’ chairman characteristics and IM. Moreover, robustness and sensitivity tests were used to examine the effectiveness of chairman characteristics with IM. Furthermore, the results rely on the FGLS regression as an additional test. The study found that chairman independence, chairman ethnicity and chairman age have a significant impact on IM.FindingsThe results reveal that chairman independence has a negative association with qualitative IM (IMSC1). Moreover, chairman ethnicity has a positively significant relationship with qualitative IM (IMSC1) and quantitative IM (IMSC2). Also, the effectiveness of chairman characteristics has a negative and significant association with IMSC1.Originality/valueThe primary goal of this paper is to fill a gap in the literature and to open up opportunities for more in-depth research on the subject. So far, there has been no research into the impact of the board chairman’s (BC) personality on IM. This study serves as a warning to policymakers, businesses and their stakeholders, as well as researchers, about the importance of BC characteristics, which may impede the effectiveness of corporate governance mechanisms. The paper provides a framework for investigating these characteristics in the context of IM.
Blockchain solutions for scientific paper peer review: a systematic mapping of the literature
Authors: Farias Fávaro Allan , Marcelino Roderval , Cechinel Cristian 
Published: August 2023

PurposeThis paper presents a review of the state of the art on the application of blockchain and smart contracts to the peer-review process of scientific papers. The paper seeks to analyse how the main characteristics of the existing blockchain solutions in this field to detect opportunities for the improvement of future applications.Design/methodology/approachA systematic review of the literature on the subject was carried out in three databases recognized by the research community (IEEE Xplore, Scopus and Web of Science) and the Frontiers in Blockchain journal. A total of 1,967 articles were initially found, and after the exclusion process, the 26 remaining articles were classified according to the following dimensions: System Type, Open Access, Review Type, Reviewer Incentive, Token Economy, Blockchain Access, Blockchain Identification, Blockchain Used, Paper Storage, Anonymity and Maturity of the solution.FindingsResults show that the solutions are normally concerned on offering incentives to the reviewers' work (often monetary). Other common general preferences among the solutions are the adoption of open reviews, the use of Ethereum, the implementation of publishing ecosystems and the use of InterPlanetary File System to the storage of the papers.Originality/valueThere are currently no studies covering the main aspects of blockchain solutions in the field of scientific peer review. The present study provides an overall review of the topic, summarizing important information on the current research and helping new adopters to develop solutions grounded on the existing literature.
In pursuit of a suitable machine learning algorithm for hardness prediction of aluminium alloy
Authors: Chhabri Suman , Hazra Krishnendu , Choudhury Amitava , Sinha Arijit , Ghosh Manojit 
Published: August 2023

PurposeBecause of the mechanical properties of aluminium (Al), an accurate prediction of its properties has been challenging. Researchers are seeking reliable models for predicting the mechanical strength of Al alloys owing to the continuous emergence of new Al alloys and their applications. There has been widespread use of empirical and statistical models for the prediction of different mechanical properties of Al and Al alloy, such as linear and nonlinear regression. Nevertheless, the development of these models requires laborious experimental work, and they may not produce accurate results depending on the relationship between the Al properties, mix of other compositions and curing conditions.Design/methodology/approachNumerous machine learning (ML) models have been proposed as alternative approaches for predicting the strengths of Al and its alloys. The hardness of Al alloys has been predicted by implementing various ML algorithms, such as linear regression, ridge regression, lasso regression and artificial neural network (ANN). This investigation critically analysed and discussed the application and performance of models generated by linear regression, ridge regression, lasso regression and ANN algorithms using different mechanical properties as training parameters.FindingsConsidering the definition of the problem, linear regression has been found to be the most suitable algorithm in predicting the hardness values of AA7XXX alloys as the model generated by it best fits the data set.Originality/valueThe work presented in this paper is original and not submitted anywhere else.
Virtual and augmented reality as predictors of users’ intention to use Lagos State Public Library, Lagos State, Nigeria
Authors: Adeyemi Ismail Olatunji , Sulaiman Kabir Alabi , Abdulsalam Zaidat Motolani , Issa Abdulwahab Olanrewaju 
Published: August 2023

Purpose
Virtual reality (VR) and augmented reality (AR) are a significant part of smart libraries in the information age. Hence, their adoption is inevitable in the technological age. This study aims to examine VR and AR as predictors of library users’ intention to make use of public libraries.

Design/methodology/approach
The study adopts a descriptive survey approach. Using the random sampling technique, a questionnaire was adopted to collect data from the users of public libraries in Ikorodu Local Government, Lagos State, Nigeria. The sample size for the study is 229. Data were analysed using the IBM-Statistical Packages for Social Sciences (version 23). Descriptive statistics (frequency counts and simple percentage) and inferential statistical (simple linear regression and Sobel test) were used to analyse collected data.

Findings
The findings revealed that the users have a positive valence towards VR and AR. Results showed that library users would be influenced by subjective norms to make use of VR and AR. Findings revealed that users need the cooperation of librarians to use the technologies.

Originality/value
The study established that the users have a positive attitude and normative beliefs towards using the library if VR and AR technologies are introduced in library and information services in public libraries. This provides a theoretical underpinning to use VR and AR to enhance users’ intention to use public library.
Beliefs and therapeutic practices related to traumatic memories among Italian cognitive behavioral therapists and trainees
Authors: Zappalà Angelo , Mangiulli Ivan , Santtila Pekka , Loftus Elizabeth F. , Otgaar Henry 
Published: August 2023

Purpose
The purpose of this study was to investigate cognitive behavior therapists and trainees’s beliefs about various aspects of traumatic memory and to investigate cognitive behavior therapists’ practices in relation to alleged traumatic experiences and whether they are linked with their beliefs about various aspects of traumatic memory.

Design/methodology/approach
In the current study, the authors surveyed, by a questionnaire (in Italian), certified Italian cognitive behavioral (CB) therapists and trainees with respect to their beliefs in traumatic memories and whether they discussed about the possibility of repressed memory with their patients.

Findings
The majority of participants held strong beliefs about many controversial aspects related to traumatic memory, such as the mind being able to block out of consciousness memories of traumatic experiences. Also, more than half of CB therapists stated that they sometimes discussed about the importance of traumatic events in the genesis of their patient’s disorder and half of them sometimes talked with patients about memories for traumatic events of which they may be unaware. Such practices could lead to false memories of abuse

Originality/value
One particularly novel finding relates to the evidence that therapists reported that they had discussed with patients the importance of traumatic events in the genesis of their illness and frequently noted that they talked about the possibility of repressed memories with them. In turn, patients may be induced to recall traumatic experiences from their lives, thereby producing false memories which may tear families apart and could even lead to wrongful convictions.