bluuebunny/crossref_metadata_2025_split huggingface dataset:
Small Molecule Inhibitors Targeting Methyltransferase-Like (METTL) Proteins Against Hepatocellular Carcinoma: A Comprehensive Drug Repurposing Approach
Authors: Morshed Md Niaz , Parvez Md Sorwer Alam , Akanda Rakibul Islam , Saha Manash Kumar , Fardous Jannatul , Hosen Mohammad Jakir 
Published: March 2023

ABSTRACTAn efficient and durable multi-targeted therapeutic drug against hepatocellular carcinoma (HCC) has recently been a growing concern for tackling the chemoresistance of approved anti-HCC drugs. Recent studies indicated that methyltransferase-like (METTL) proteins including METTL1, METTL3, METTL6, METTL16, and METTL18, have overexpressed and associated with the progression of HCC malignancy, and making them excellent biomarkers. Here, we present a series of bioinformatics study including novel compound repurposing approach, molecular docking, pharmacophore modeling, and molecular dynamic simulation, which revealed two first-in-class highly potent catalytic multi-target inhibitors (ZINC70666503 and ZINC13000658 with 87% and 82% drug scores, respectively) of methyltransferase-like proteins. Comparatively, these two inhibitors showed a notable binding affinity against studied METTL proteins. Furthermore, ADME and toxicity analysis suggested that these two commercially available compounds have good drug-likeliness properties with no potent toxic effects. Of note, the molecular dynamics study supported their conformational stability and high selectivity at the pocket of proteins’ adenosine moiety of S-Adenosyl Methionine. However, this comprehensive analysis needsin vivovalidation to facilitate multi-targeting therapeutic development against hepatocellular carcinoma.
Ocular following eye movements in marmosets follow complex motion trajectories
Authors: Pattadkal Jagruti J. , Barr Carrie , Priebe Nicholas J. 
Published: March 2023

AbstractOcular following eye movements help stabilize images on the retina and offer a window to study motion interpretation by visual circuits. We use these ocular following eye movements to study motion integration behavior in the marmosets. We characterize ocular following responses in the marmosets using different moving stimuli such as dot patterns, gratings, and plaids. The marmosets can accurately track motion along different directions and exhibit spatial frequency and speed sensitivity that closely matches the sensitivity reported in neurons from their motion selective area MT. Marmosets are also able to track the integrated motion of plaids, with tracking direction consistent with intersection of constraints model of motion integration. Marmoset ocular following responses are similar to responses in macaques and humans with certain species-specific differences in peak sensitivities. Such motion sensitive eye movement behavior in combination with direct access to cortical circuitry makes the marmoset model well suited to study the neural basis of motion integration.Significance statementOcular following is a reflexive eye tracking behavior in response to large visual field motion. It reflects the properties of underlying motion sensing circuits. One of the primary motion sensing areas in primates is area MT. In the primate species of marmosets, this and other cortical areas are easily accessible due to their lissencephalic brain. We demonstrate ocular following behavior in the marmosets for simple and complex motion trajectories and describe its characteristics. We then use ocular following to distinguish between different motion integration models. Our results show the utility of ocular following to study the neural basis for motion sensing in marmosets.
A Pillar and Perfusion Plate Platform for Robust Human Organoid Culture and Analysis
Authors: Kang Soo-Yeon , Kimura Masaki , Shrestha Sunil , Lewis Phillip , Lee Sangjoon , Cai Yuqi , Joshi Pranav , Acharya Prabha , Liu Jiafeng , Yang Yong , Sanchez J. Guillermo , Ayyagari Sriramya , Alsberg Eben , Wells James M. , Takebe Takanori , Lee Moo-Yeal 
Published: March 2023

AbstractHuman organoids have potential to revolutionizein vitrodisease modeling by providing multicellular architecture and function that are similar to thosein vivo. This innovative and evolving technology, however, still suffers from assay throughput and reproducibility to enable high-throughput screening (HTS) of compounds due to cumbersome organoid differentiation processes and difficulty in scale-up and quality control. Using organoids for HTS is further challenged by lack of easy-to-use fluidic systems that are compatible with relatively large organoids. Here, we overcome these challenges by engineering “microarray three-dimensional (3D) bioprinting” technology and associated pillar and perfusion plates for human organoid culture and analysis. High-precision, high-throughput stem cell printing and encapsulation techniques were demonstrated on a pillar plate, which was coupled with a complementary deep well plate and a perfusion well plate for static and dynamic organoid culture. Bioprinted cells and spheroids in hydrogels were differentiated into liver and intestine organoids forin situfunctional assays. The pillar/perfusion plates are compatible with standard 384-well plates and HTS equipment, and thus may be easily adopted in current drug discovery efforts.
BOLD Moments: modeling short visual events through a video fMRI dataset and metadata
Authors: Lahner Benjamin , Dwivedi Kshitij , Iamshchinina Polina , Graumann Monika , Lascelles Alex , Roig Gemma , Gifford Alessandro Thomas , Pan Bowen , Jin SouYoung , Ratan Murty N. Apurva , Kay Kendrick , Oliva Aude , Cichy Radoslaw 
Published: March 2023

AbstractStudying the neural basis of human dynamic visual perception requires extensive experimental data to evaluate the large swathes of functionally diverse brain neural networks driven by perceiving visual events. Here, we introduce the BOLD Moments Dataset (BMD), a repository of whole-brain fMRI responses to over 1,000 short (3s) naturalistic video clips of visual events across ten human subjects. We use the videos’ extensive metadata to show how the brain represents word- and sentence-level descriptions of visual events and identify correlates of video memorability scores extending into the parietal cortex. Furthermore, we reveal a match in hierarchical processing between cortical regions of interest and video-computable deep neural networks, and we showcase that BMD successfully captures temporal dynamics of visual events at second resolution. With its rich metadata, BMD offers new perspectives and accelerates research on the human brain basis of visual event perception.
Manipulation of the nucleoscaffold potentiates cellular reprogramming kinetics
Authors: Yang Benjamin A. , da Rocha André Monteiro , Newton Isabel , Shcherbina Anna , Wong Sing-Wan , Fraczek Paula M. , Larouche Jacqueline A. , Hiraki Harrison L. , Baker Brendon M. , Shin Jae-Won , Takayama Shuichi , Thouless M. D. , Aguilar Carlos A. 
Published: March 2023

AbstractSomatic cell fate is an outcome set by the activities of specific transcription factors and the chromatin landscape and is maintained by gene silencing of alternate cell fates through physical interactions with the nuclear scaffold. Here, we evaluate the role of the nuclear scaffold as a guardian of cell fate in human fibroblasts by comparing the effects of transient loss (knockdown) and mutation (progeria) of functional Lamin A/C, a core component of the nuclear scaffold. We observed that Lamin A/C deficiency or mutation disrupts nuclear morphology, heterochromatin levels, and increases access to DNA in lamina-associated domains. Changes in Lamin A/C were also found to impact the mechanical properties of the nucleus when measured by a microfluidic cellular squeezing device. We also show that transient loss of Lamin A/C accelerates the kinetics of cellular reprogramming to pluripotency through opening of previously silenced heterochromatin domains while genetic mutation of Lamin A/C into progerin induces a senescent phenotype that inhibits the induction of reprogramming genes. Our results highlight the physical role of the nuclear scaffold in safeguarding cellular fate.
A Bayesian model for genomic prediction using metabolic networks
Authors: Onogi Akio 
Published: March 2023

AbstractMotivationGenomic prediction is now an essential technique in breeding and medicine, and it is interesting to see how omics data can be used to improve prediction accuracy. Precedent work proposed a metabolic network-based method in biomass prediction of Arabidopsis; however, the method consists of multiple steps that possibly degrade prediction accuracyResultsWe proposed a Bayesian model that integrates all steps and jointly infers all fluxes of reactions related to biomass production. The proposed model showed higher accuracies than methods compared both in simulated and real data. The findings support the previous excellent idea that metabolic network information can be used for prediction.Availability and implementationAll R and stan scripts to reproduce the results of this study are available athttps://github.com/Onogi/MetabolicModeling.Contactonogiakio@gmail.comSupplementary informationThis study provides no supplementary information
Length estimation of fish detected as non-occluded using a smartphone application and deep learning techniques
Authors: Shibata Yasutoki , Iwahara Yuka , Manano Masahiro , Kanaya Ayumi , Sone Ryota , Tamura Satoko , Kakuta Naoya , Nishino Tomoya , Ishihara Akira , Kugai Shungo 
Published: March 2023

AbstractUncertainty in stock assessment can be reduced if accurate and precise length composition of catch is available. Length data are usually manually collected, although this method is costly and time-consuming. Recently, some studies have estimated fish species and length from images using deep learning by installing camera systems in fishing vessels or a fish auction center. Once the deep learning model is properly trained, it does not require expensive and time-consuming manual labor. However, several previous studies have focused on monitoring fishing practices using an electronic monitoring system (EMS); therefore, it is necessary to solve many challenges, such as counting the total number of fish in the catch. In this study, we proposed a new deep learning-based method to estimate fish length using images. Species identification was not performed by the model, and images were taken manually by the measurers; however, length composition was obtained only for non-occluded fish detected by the model. A smartphone application was developed to calculate scale information (cm/pixel) from a known size fish box in fish images, and the Mask R-CNN (Region-based convolutional neural networks) model was trained using 76,161 fish to predict non-occluded fish. Two experiments were conducted to confirm whether the proposed method resulted in errors in the length composition. First, we manually measured the total length (TL) for each of the five fish categories and estimated the TL using deep learning and calculated the bias. Second, multiple fish in a fish box were photographed simultaneously, and the difference between the mean TL estimated from the non-occluded fish and the true TL from all fish was calculated. The results indicated that the biases of all five species categories were within ± 3%. Moreover, the difference was within ± 1.5% regardless of the number of fish in the fish box. In the proposed method, deep learning was used not to replace the measurer but to increase their measurement efficiency. The proposed method is expected to increase opportunities for the application of deep learning-based fish length estimation in areas of research that are different from the scope of conventional EMS.
Extraordinary peptide-binding mode of a songbird MHC class-I molecule suggests mechanism to counter pathogen immune evasion
Authors: Eltschkner Sandra , Mellinger Samantha , Buus Sören , Nielsen Morten , Paulsson Kajsa M , Lindkvist-Petersson Karin , Westerdahl Helena 
Published: March 2023

AbstractLong-distance migratory animals such as birds and bats have evolved to withstand selection imposed by pathogens across the globe, and pathogen richness is known to be particularly high in tropical regions. Immune genes, so-called Major Histocompatibility Complex (MHC) genes, are highly duplicated in songbirds compared to other vertebrates, and this high MHC diversity has been hypothesised to result in a unique adaptive immunity. To understand the rationale behind the evolution of the high MHC genetic diversity in songbirds, we determined the structural properties of an MHC class I protein, Acar3, from a long-distance migratory songbird, the great reed warblerAcrocephalus arundinaceus(in short:Acar). The structure of Acar3 was studied in complex with pathogen-derived antigens and shows an overall antigen presentation similar to human MHC class I. However, the peptides bound to Acar3 display an unusual conformation: Whereas the N-terminal ends of the peptides display enhanced flexibility, the conformation of their C-terminal halves is rather static. This uncommon peptide-binding mode in Acar3 is facilitated by a central Arg residue within the peptide-binding groove that fixes the backbone of the peptide at its central position, and potentially permits successful interactions between MHC class I and innate immune receptors. Our study highlights the importance of investigating the immune system of wild animals, such as birds and bats, to uncover unique immune mechanisms which may neither exist in humans nor in model organisms.
Classical solutions for the generalized Kadomtsev–Petviashvili I equations
Authors: Georgiev Svetlin , Boukarou Aissa , Bouhali Keltoum , Zennir Khaled 
Published: March 2023

PurposeThis paper is devoted to the generalized Kadomtsev–Petviashvili I equation. This study aims to propose a new approach for investigation for the existence of at least one global classical solution and the existence of at least two nonnegative global classical solutions. The main arguments in this paper are based on some recent theoretical results.Design/methodology/approachThis paper is devoted to the generalized Kadomtsev–Petviashvili I equation. This study aims to propose a new approach for investigation for the existence of at least one global classical solution and the existence of at least two nonnegative global classical solutions. The main arguments in this paper are based on some recent theoretical results.FindingsThis paper is devoted to the generalized Kadomtsev–Petviashvili I equation. This study aims to propose a new approach for investigation for the existence of at least one global classical solution and the existence of at least two nonnegative global classical solutions. The main arguments in this paper are based on some recent theoretical results.Originality/valueThis article is devoted to the generalized Kadomtsev–Petviashvili I equation. This study aims to propose a new approach for investigation for the existence of at least one global classical solution and the existence of at least two nonnegative global classical solutions. The main arguments in this paper are based on some recent theoretical results.
Achieving transparency in business processes by developing and implementing ethical climate: an integrated model of ethical leadership and engagement
Authors: Burhan Qurat-ul-Ain , Khan Muhammad Asif , Malik Muhammad Faisal 
Published: March 2023

PurposeThe current research aims to investigate the role of ethical leadership in improving business processes and the impact of ethical leadership on employee engagement with mediating role of relational identification and ethical climate. Although ethical leadership displays and promotes morality in their followers, current literature is silent about the inclusion of relational identification and ethical climate. The present study intends to develop and test a model with the chain of mediation in the relationship between ethical leadership and employee engagement.Design/methodology/approachA total of237 responses were collected from the banking sector using quantitative research techniques, and data were gathered through a self-administrated questionnaire. Exploratory and confirmatory factor analyses were used through SEM- MPLUS to generate the results and test hypotheses.FindingsThe results suggested a significant impact of ethical leadership on employee engagement through relational identification and ethical climate (moral obligations, moral convictions and elevation). By using the results, practical and theoretical implications are discussed.Research limitations/implicationsBesides all the proposed hypotheses that have been accepted, there are some limitations associated with this study. One limitation is usage of single source information, as the data were collected only from the banking sector employees. Moreover, only three variables are taken in the context of ethical climate (moral obligations, moral convictions and elevation). However, some other variables could also be included under the umbrella of ethical climate, e.g. moral virtue. Future researchers should also add different employee attitudes, such as job involvement, job satisfaction and organizational commitment, other than employee engagement.Originality/valueAn abundance of research is conducted on ethical leadership; however, with the development of knowledge and new thoughts related to identification and ethical climate, there is a strong need to conduct the research by including other overlooked possible paths.
Regulating sharing platforms in lateral exchange markets: the role of power and trust
Authors: Tang Xiaofei , Luo Yong (Eddie) , Zhou Pan , Lowe Ben 
Published: March 2023

PurposeThis paper aims to examine different types of sharing platforms based on risk perceptions of product/service providers and users, and to illustrate appropriate platform regulation preferences.Design/methodology/approachA survey was used (N= 540) to collect data on platform participants’ risk perceptions and regulation preferences in the Chinese (N= 263) and the US markets (N= 277). Cluster analysis and multiple correspondence analysis were used to categorise platforms and match their regulation preferences with the risk characteristics.FindingsThe results show that i) four types of sharing platforms are categorised in terms of the risk perceived by the supply and demand side, and ii) four types of regulation preferences are clustered, drawing on the power and trust elements proposed from the slippery slope framework. Furthermore, coercive power regulation is favoured by participants of platforms with high supply risk and low demand risk, legitimate power regulation is preferred by actors of platforms with low supply risk and high demand risk, reason-based trust regulation is preferred by actors of platforms with high supply and demand risk, and implicit trust regulation is favoured by participants of platforms with low supply and demand risk.Research limitations/implicationsThis paper develops an empirical typology of platforms based on risk perceptions of providers and users, and advances our understanding about lateral exchange markets from a consumer perspective.Practical implicationsThis paper provides implications for platforms to regulate transactions through two mechanisms – the power of platforms and trust in platform participants.Originality/valueRegulating by power ensures transaction security while regulating by trust enhances transaction efficiency, so it is important to configure the power and trust elements in platform regulation in an appropriate manner. To the best of the authors’ knowledge, this paper is one of the first attempts at addressing platform regulation and shows how consumers’ risk perception of platforms can lead to important implications for theory and practice in marketing and better regulation of platform transactions.
Difficulties to digitalize: ambidexterity challenges in law firms
Authors: Kronblad Charlotta , Pregmark Johanna E. , Berggren Rita 
Published: March 2023

PurposeThis paper aims to understand what prevents established law firms from embracing digitalization and discusses barriers to solving the emerging ambidexterity problem. Law firms have been organized in the same way for decades. However, digital opportunities are emerging and new competitors are challenging established firms. This presents established law firms with an ambidexterity problem: How can law firms simultaneously uphold their successful way of working while entering a new world of digitalization, artificial intelligence (AI) and machine learning?Design/methodology/approachPrevious research suggests that law firms are slow in digital transformation, compared to other Professional Service Firms (PSFs). In this paper, the authors explore why this happens. Interview data from representatives in law firms are complemented with data from architects as well as legal industry data and field notes. The data have been analyzed to spot patterns and emerging themes.FindingsThe authors find that established law firms face structural and cultural barriers to applying ambidextrous solutions. When comparing law firms with architecture firms, the authors see that while established architecture firms have combined digital exploration with ongoing exploitation, established law firms have focused on exploitation, leaving digital exploration to new legal tech firms. This difference can be attributed to industry context and professional culture.Originality/valueThis paper shows that both structural and contextual ambidexterity is a challenge for established law firms. This paper contributes to the understanding of barriers to embrace digital technology, and supports practitioners in efforts to remove these barriers.
Corporate social responsibility and risk-taking in banking
Authors: Shao Yingying , Baradwaj Babu G. , Dewally Michaël , Liu Pu 
Published: March 2023

Purpose
The purpose of this study is to examine whether banks’ commitment to corporate social responsibility (CSR) is related to the diversification of their activities and whether CSR, as a result, affects banks’ risk profile.

Design/methodology/approach
Using a sample of 215 publicly traded U.S. bank holding companies between 1996 and 2016, this study applies regression analysis to examine the links between CSR and activity diversification and risk-taking. It also conducts a mediation test to determine whether CSR affects risk through its influence on banks’ activity diversification.

Findings
The results of this study show that banks engaging in positive CSR activities significantly increase the diversification of their banking activities, consistent with the theory that CSR serves as an implicit risk hedging strategy. Mediation analysis provides evidence that this translates into more stable and less risky banks.

Originality/value
This study contributes to the literature by suggesting that activity diversification is a channel through which CSR reduces bank risk and improves asset quality.