bluuebunny/crossref_metadata_2025_split huggingface dataset:
ProT-VAE: Protein Transformer Variational AutoEncoder for Functional Protein Design
Authors: Sevgen Emre , Moller Joshua , Lange Adrian , Parker John , Quigley Sean , Mayer Jeff , Srivastava Poonam , Gayatri Sitaram , Hosfield David , Korshunova Maria , Livne Micha , Gill Michelle , Ranganathan Rama , Costa Anthony B. , Ferguson Andrew L. 
Published: January 2023

AbstractThe data-driven design of protein sequences with desired function is challenged by the absence of good theoretical models for the sequence-function mapping and the vast size of protein sequence space. Deep generative models have demonstrated success in learning the sequence to function relationship over natural training data and sampling from this distribution to design synthetic sequences with engineered functionality. We introduce a deep generative model termed the Protein Transformer Variational AutoEncoder (ProT-VAE) that furnishes an accurate, generative, fast, and transferable model of the sequence-function relationship for data-driven protein engineering by blending the merits of variational autoencoders to learn interpretable, low-dimensional latent embeddings and fully generative decoding for conditional sequence design with the expressive, alignment-free featurization offered by transformers. The model sandwiches a lightweight, task-specific variational autoencoder between generic, pre-trained transformer encoder and decoder stacks to admit alignment-free training in an unsupervised or semi-supervised fashion, and interpretable low-dimensional latent spaces that facilitate understanding, optimization, and generative design of functional synthetic sequences. We implement the model using NVIDIA’s BioNeMo framework and validate its performance in retrospective functional prediction and prospective design of novel protein sequences subjected to experimental synthesis and testing. The ProT-VAE latent space exposes ancestral and functional relationships that enable conditional generation of novel sequences with high functionality and substantial sequence diversity. We anticipate that the model can offer an extensible and generic platform for machine learning-guided directed evolution campaigns for the data-driven design of novel synthetic proteins with “super-natural” function.
A harmonized public resource of deeply sequenced diverse human genomes
Authors: Koenig Zan , Yohannes Mary T. , Nkambule Lethukuthula L. , Zhao Xuefang , Goodrich Julia K. , Kim Heesu Ally , Wilson Michael W. , Tiao Grace , Hao Stephanie P. , Sahakian Nareh , Chao Katherine R. , Walker Mark A. , Lyu Yunfei ,   gnomAD Project Consortium, Rehm Heidi L. , Neale Benjamin M. , Talkowski Michael E. , Daly Mark J. , Brand Harrison , Karczewski Konrad J. , Atkinson Elizabeth G. , Martin Alicia R. 
Published: January 2023

AbstractUnderrepresented populations are often excluded from genomic studies due in part to a lack of resources supporting their analyses. The 1000 Genomes Project (1kGP) and Human Genome Diversity Project (HGDP), which have recently been sequenced to high coverage, are valuable genomic resources because of the global diversity they capture and their open data sharing policies. Here, we harmonized a high quality set of 4,094 whole genomes from HGDP and 1kGP with data from the Genome Aggregation Database (gnomAD) and identified over 153 million high-quality SNVs, indels, and SVs. We performed a detailed ancestry analysis of this cohort, characterizing population structure and patterns of admixture across populations, analyzing site frequency spectra, and measuring variant counts at global and subcontinental levels. We also demonstrate substantial added value from this dataset compared to the prior versions of the component resources, typically combined via liftover and variant intersection; for example, we catalog millions of new genetic variants, mostly rare, compared to previous releases. In addition to unrestricted individual-level public release, we provide detailed tutorials for conducting many of the most common quality control steps and analyses with these data in a scalable cloud-computing environment and publicly release this new phased joint callset for use as a haplotype resource in phasing and imputation pipelines. This jointly called reference panel will serve as a key resource to support research of diverse ancestry populations.
A Model-Based Hierarchical Bayesian Approach to Sholl Analysis
Authors: Vonkaenel Erik , Feidler Alexis , Lowery Rebecca , Andersh Katherine , Love Tanzy , Majewska Ania , Mccall Matthew N 
Published: January 2023

SummaryDue to the link between microglial morphology and function, morphological changes in microglia are frequently used to identify pathological immune responses in the central nervous system. In the absence of pathology, microglia are responsible for maintaining homeostasis, and their morphology can be indicative of how the healthy brain behaves in the presence of external stimuli and genetic differences. Despite recent interest in high throughput methods for morphological analysis, Sholl analysis is still the gold standard for quantifying microglia morphology via imaging data. Often, the raw data are naturally hierarchical, minimally including many cells per image and many images per animal. However, existing methods for performing downstream inference on Sholl data rely on truncating this hierarchy so rudimentary statistical testing procedures can be used. To fill this longstanding gap, we introduce a fully parametric model-based approach for analyzing Sholl data. We generalize our model to a hierarchical Bayesian framework so that inference can be performed without aggressive reduction of otherwise very rich data. We apply our model to three real data examples and perform simulation studies comparing the proposed method with a popular alternative.
Metabolic responses to food and temperature in deep-sea isopods,Bathynomus doederleini
Authors: Tanaka Shogo , Ono Yurika , Tanimae Shin-ichiro , Moriyama Toru , Fujimoto Shingo , Yagi Mitsuharu 
Published: January 2023

ABSTRACTMetabolic rate, the energy required per unit of time for an organism to sustain life, is influenced by both intrinsic and extrinsic factors. Despite the similarities among living organisms across the various domains of life, it has been observed that those adapted to deep-sea environments exhibit notable distinctions from those in shallower waters, even when accounting for size and temperature. However, as deep-sea organisms are infrequently kept in captivity for prolonged periods, investigations into their potential metabolic responses to food and temperature have yet to be conducted. In this study, we demonstrate the impact of food (specific dynamic action:SDA) and temperature (Q10) on the metabolic rate of the deep-sea isopodBathynomus doederleini. Positive correlations were found betweenSDAparameters (peak, time to peak, duration, and factorial scope) and meal size in deep-sea organisms. The postprandial metabolic rate, at a meal size of 45.4%, increased by approximately 6.5-fold, and the duration was 20 days. Within the temperature range of their natural habitat, the overallQ10was 2.36, indicating that a 10 °C increase would lead to a 2.4-fold increase in resting metabolic rate. The mean metabolic rate of this species, corrected for the equivalent temperature, was significantly 63% lower than the metabolic scaling rule for aquatic invertebrates. This low metabolic rate suggests that deep-sea isopods can survive for a year on a mere few grams of whale blubber at a water temperature of 10.5 °C. This information is crucial for understanding the metabolic strategies and consequences of adaptation to a deep-sea environment.
Evaluating the mouse neural precursor line, SN4741, as a suitable proxy for midbrain dopaminergic neurons
Authors: Boyd Rachel J. , McClymont Sarah A. , Barrientos Nelson B. , Hook Paul W. , Law William D. , Rose Rebecca J. , Waite Eric L. , Avramopoulos Dimitrios , McCallion Andrew S. 
Published: January 2023

ABSTRACTTo overcome the ethical and technical limitations ofin vivohuman disease models, the broader scientific community frequently employs model organism-derived cell lines to investigate of disease mechanisms, pathways, and therapeutic strategies. Despite the widespread use of certainin vitromodels, many still lack contemporary genomic analysis supporting their use as a proxy for the affected human cells and tissues. Consequently, it is imperative to determine how accurately and effectively any proposed biological surrogate may reflect the biological processes it is assumed to model. One such cellular surrogate of human disease is the established mouse neural precursor cell line, SN4741, which has been used to elucidate mechanisms of neurotoxicity in Parkinson disease for over 25 years. Here, we are using a combination of classic and contemporary genomic techniques – karyotyping, RT-qPCR, single cell RNA-seq, bulk RNA-seq, and ATAC-seq – to characterize the transcriptional landscape, chromatin landscape, and genomic architecture of this cell line, and evaluate its suitability as a proxy for midbrain dopaminergic neurons in the study of Parkinson disease. We find that SN4741 cells possess an unstable triploidy and consistently exhibits low expression of dopaminergic neuron markers across assays, even when the cell line is shifted to the non-permissive temperature that drives differentiation. The transcriptional signatures of SN4741 cells suggest that they are maintained in an undifferentiated state at the permissive temperature and differentiate into immature neurons at the non-permissive temperature; however, they may not be dopaminergic neuron precursors, as previously suggested. Additionally, the chromatin landscapes of SN4741 cells, in both the differentiated and undifferentiated states, are not concordant with the open chromatin profiles ofex vivo, mouse E15.5 forebrain- or midbrain-derived dopaminergic neurons. Overall, our data suggest that SN4741 cells may reflect early aspects of neuronal differentiation but are likely not a suitable a proxy for dopaminergic neurons as previously thought. The implications of this study extend broadly, illuminating the need for robust biological and genomic rationale underpinning the use ofin vitromodels of molecular processes.
Exploring barriers to collaborative innovation in supply chains – a study of a supplier and two of its industrial customers
Authors: Anderson Helén , Müllern Tomas , Danilovic Mike 
Published: January 2023

PurposeThe purpose is to identify and explore barriers to overcome for developing collaborative innovation between a global service supplier and two of its industrial customers in Sweden.Design/methodology/approachThe research had an action-based research approach in which the researchers were interacting and collaborating with the practitioners in the companies. The empirical part includes primary data from multiple interviews, and two workshops with dialogues with participants from the involved companies. The use of complementary data collection methods gave rich input to understanding the context for collaborative innovation, and to uncovering barriers, to develop solutions for collaborative innovation. The empirical barriers were analysed using theoretically derived barriers from a literature review. The analysis generated four broad themes of barriers which were discussed and led to conclusions and theoretical and practical implications on: the customer's safety culture, the business model, the parties' understanding of innovation and the management of collaborative innovation in supply chains.FindingsThe thematic analysis generated four broad themes: the customer's safety culture, the business model, the parties' understanding of innovation and the management of collaborative innovation. These themes where analysed using theoretically derived barriers from a literature review. The industrial context, the understanding of innovation and its management created barriers.Originality/valueThe unique access to the service supplier and its two independent industrial customers adds a rich contextual framing to the process of identifying and exploring the barriers to collaborative innovation. The conclusion emphasizes the importance of an industrial business context, the business logic in terms of business models and for the understanding and management of collaborative innovation.
Using a unified model of TPB, NAM and SOBC to understand students’ energy-saving behaviors: moderation role of group-level factors and media publicity
Authors: Duong Cong Doanh 
Published: January 2023

Purpose
This study aims to integrate the theory of planned behavior (TPB), norm activation model (NAM) and stimulus–organism–behavior–consequences theory (SOBC) with the moderators to investigate the main determinants of energy-saving behaviors as well as how group-level factors and media publicity significantly facilitate the energy-saving intention-behavior linkage among dormitory students in higher education institutions (HEIs).

Design/methodology/approach
A valid sample of 325 dormitory students resided in universities of Vietnam and a three-step analysis approach via SPSS 28.0 and AMOS 25.0 were used to test the hypothesized model.

Findings
This study yields that external stimuluses (subjective norms and perceived behavioral control) positively and strongly stimulate energy–energy attitude, while internal stimuluses (ascription of responsibility, awareness of consequences) arouse personal norms. Both internal and external stimuluses were found to have serially mediation effects on energy-saving behaviors via attitude toward energy saving, personal norms and energy-saving intention. Remarkably, group interaction and media publicity exert prominent positive moderation effects on the energy-saving intention–behavior relationship.

Practical implications
The findings of this research can be valuable for HEIs and policymakers to inspire university students’ energy conservation behavior for sustainable development goals.

Originality/value
This study contributed to the proenvironmental literature by adopting the SOBC paradigm that strengthens the integration of TPB and NAM models to explore the main determinants of dormitory students’ energy-saving behaviors, explain the underlying mediation mechanisms of organisms and behavioral responses and illustrate the moderation role of group-level factors and media publicity.
The configuration of the largest Brazilian banks' board of directors: trajectories and capitals of Latin America's financial elite
Authors: Vila Marcio Luis , Candido Silvio Eduardo Alvarez , Ferratti Gustavo Mendonca , Sacomano Neto Mário 
Published: January 2023

PurposeThis study aims to analyze the configuration of the board of directors of the five largest banks operating in Brazil, which are members of a financial elite that directly influences the socioeconomic life in Latin America.Design/methodology/approachThis assessment is inspired by Bourdieu's sociological approach and in the discussion on his work in organization studies and economic sociology. It addresses the organization as a field and investigates its associated field of power. The authors conducted qualitative research and relationally analyzed data related to the trajectory and the social properties of the councilors using the statistical technique called multiple correspondence analysis (MCA).FindingsThe results show that forms of social and cultural capital are particularly influential in the production of distinctions among banks' board members. Moreover, councils' priorities and configurations are diverse: some idealized and based on knowledge, others pragmatic and based on customs, others still anchored in a double logic of market satisfaction and family wealth preservation.Practical implicationsUnderstanding the objective power relations among these top agents may be crucial for effectively regulating certain aspects of their activities. Furthermore, understanding how different forms of capital affect the relative position of the board members may help us reduce representative bias in what seems today an inner circle.Originality/valueThis study is relevant because it makes an in-depth analysis of the composition of one of the most influential financial elites in Latin America, combining sociological theory and advanced statistical techniques for qualitative grouping (MCA).
Curbing unethical consumer behaviour: the role of religiosity, consumer ethical beliefs and anticipated guilt
Authors: Hassan Syed Masroor , Rahman Zillur 
Published: January 2023

Purpose
This paper aims to investigate the role of personal and affective factors in curbing unethical consumer behaviour (UCB). Specifically, this study scrutinizes how religiosity, consumer ethical beliefs (CEBs) and anticipated guilt influence UCB.

Design/methodology/approach
Using a survey-based approach, the author distributed offline and online questionnaires among students enrolled in a public university in Roorkee, India and analysed the data using structural equation modelling.

Findings
The results provide evidence that intrinsically religious individuals develop strong ethical beliefs, which can help them to refrain from unethical behaviour and adopt ethical conduct. Also, individuals prone to experiencing anticipated guilt show less inclination to commit unethical behaviour.

Research limitations/implications
This research presents significant theoretical and practical implications to facilitate academic understanding and managerial decision-making in the context of consumer ethics.

Originality/value
This research is one of the few empirical studies in the Indian context that simultaneously examines the antecedents and consequences of CEB.
Modelling the adoption of agro-advisory mobile applications: a theoretical extension and analysis using result demonstrability, trust, self-efficacy and mobile usage proficiency
Authors: Soodan Vishal , Jamwal Mohit , Rana Nripendra P. , Sharma Deeksha , Chakraborty Supernova 
Published: January 2023

PurposeThis paper aims to explore the determinants of intention towards the use of agro-advisory mobile applications by extending the technology acceptance model (TAM) with addition of the following constructs: result demonstrability (RD), trust, self-efficacy (SE) and mobile usage proficiency (MUP).Design/methodology/approachThe study employed a survey on farmers (n = 446), which was analysed through structural equation modelling using Analysis of Moment Structures (AMOS).FindingsThe results show that RD and farmer's trust on agro-advisory mobile apps (AAMA) positively impact their perceptions of usefulness. Also, farmer's SE and MUP positively affect their perceptions of ease of using AAMA. Further, interestingly, farmer's attitude towards the AAMA fully mediates the relationship between perceived usefulness and perceived ease of use on intention to use them.Research limitations/implicationsUnderstanding the antecedents of agro-advisory mobile application offers a unique contribution to policymakers, private firms, and non-government organizations by proving key insights on the acceptance of agriculture based mobile technologies in context of developing nations.Originality/valueTo the best of author's knowledge, this is one of the first research enquiries on the adoption of agro-advisory mobile applications. The new theoretical framework adds to the original TAM and offers novel insights that are helpful in augmenting the current understanding on AAMA and their acceptance by the beneficiaries.
How does the price structure of two-sided markets affect transaction volume and market share: evidence from the Korean credit card market
Authors: Jo Yoonseo , Lee Kaun Y. 
Published: January 2023

This study aims to empirically examine the impact of the price structure of two-sided markets on transaction volume and market share (MS) in the context of the Korean credit card industry. The Korean credit card market differs from those in the United States (U.S.) or Europe in terms of transaction structure (i.e. a three-party system in Korea vs a four-party system in the U.S. or Europe) and government policy. In addition to the merchant discount rate and the cardholder annual membership fee rate, the authors included and analyzed exogenous variables to eliminate any endogeneity. Based on the analysis results, the authors found that credit card usage performance (i.e. transaction volume) increases with an increase in the relative price ratio (merchant discount rate ÷ cardholder membership fee rate) paid by merchants and cardholders, provided that the total price (merchant discount rate + cardholder membership fee rate) paid by merchants and cardholders remains constant. Therefore, this study is the first to confirm that the Korean credit card market operated as the theoretical mechanism of a two-sided market during the analysis period. This effect can only be observed in specific cases such as the launch of the so-called “Chief Executive Officer(CEO)-designed card.” When a new CEO takes office in a credit card company and launches a “CEO-designed card,” there is a significant increase in not only card usage performance but MS as well owing to the price structure changes caused by expanding the benefits that customers derive from card use.
Suicide attempts as turning points
Authors: Lester David 
Published: January 2023

Purpose
The purpose of this study is to examine why an attempt at suicide does not always indicate the beginning of a life with poor mental health.

Design/methodology/approach
Case studies, supplemented by follow-up studies of attempted suicides.

Findings
One of the strongest predictors of a healthy life after the suicide attempt was found to be improvement in the appropriateness of behavior toward others and improved adult functioning.

Originality/value
The results suggest that behavioral coaching, in addition to traditional psychiatric treatment, could help attempted suicides move on with their lives productively.