bluuebunny/crossref_metadata_2025_split huggingface dataset:
Analytical and Clinical Validation of AIM-NASH: A Digital Pathology Tool for Artificial Intelligence-based Measurement of Nonalcoholic Steatohepatitis Histology
Authors: Pulaski Hanna , Harrison Stephen A. , Mehta Shraddha S. , Sanyal Arun J , Vitali Marlena C. , Manigat Laryssa C. , Hou Hypatia , Madasu Christudoss Susan P. , Hoffman Sara M. , Stanford-Moore Adam , Egger Robert , Glickman Jonathan , Resnick Murray , Patel Neel , Taylor Cristin E. , Myers Robert P. , Chung Chuhan , Patterson Scott D. , Sejling Anne-Sophie , Minnich Anne , Baxi Vipul , Subramaniam G. Mani , Anstee Quentin M. , Loomba Rohit , Ratziu Vlad , Montalto Michael C , Beck Andrew H , Wack Katy 
Published: May 2024

AbstractMetabolic-dysfunction associated steatohepatitis (MASH) is a major cause of liver-related morbidity and mortality, yet treatment options are limited. Manual scoring of liver biopsies, currently the gold standard for clinical trial enrollment and endpoint assessment, suffers from high reader variability. This study represents the most comprehensive multi-site analytical and clinical validation of an AI-based pathology system, Artificial Intelligence-based Measurement of Nonalcoholic Steatohepatitis (AIM-NASH), to assist pathologists in MASH trial histology scoring. AIM-NASH demonstrated high repeatability and reproducibility compared to manual scoring. AIM-NASH-assisted reads by expert MASH pathologists were superior to unassisted reads in accurately assessing inflammation, ballooning, NAS >= 4 with >=1 in each score category, and MASH resolution, while maintaining non-inferiority in steatosis and fibrosis assessment. These findings suggest AIM-NASH could mitigate reader variability, providing a more reliable assessment of therapeutics in MASH clinical trials.
Data-modeling the interplay between single cell shape, single cell protein expression, and tissue state
Authors: Tamir Yuval , Bussi Yuval , Owczarek Claudia , Luque Luciana , Torrisi Giuseppe , Rose Leor Ariel , Kliper-Gross Orit , Sander Chris , Schumacher Linus , Parsons Maddy , Keren Leeat , Zaritsky Assaf 
Published: May 2024

AbstractChanges in cell shape are fundamentally involved in signaling, intracellular organization, function, and intercellular interactions within tissues, in health and disease. Investigating the interplay between cell shape and protein expression was limited, until recently, by the number of proteins that can be imaged simultaneously or by population averaging. We combined spatial multiplexed single cell imaging and machine learning to systematically investigate the intricate relationships between cell shape and protein expression in the context of heterogeneous human cells in their native state in human tissue samples in situ. Our analysis established a universal bi-directional link between the cell’s shape and its protein expression across different cell types, diseases, and disease states in human tissues, enabling new applications. Machine learning interpretability showed that the contribution of shape features to a prediction can potentially infer new protein functions. Unbiased screening of the links between all pairs consisting of one protein and one cell type identified a subpopulation of large p53-positive tumor cells across two cancers. Ultimately, inclusion of single cell shape properties enhanced Graph Neural Network disease state prediction. Our results open the door to unraveling the intricate connections between protein expression at the single cell level, cell shape, tissue organization, and tissue state in a physiological context.
Design, Construction, and Validation of a Yeast-Displayed Chemically Expanded Antibody Library
Authors: Rezhdo Arlinda , Hershman Rebecca L. , Van Deventer James A. 
Published: May 2024

AbstractIn vitrodisplay technologies, exemplified by phage and yeast display, have emerged as powerful platforms for antibody discovery and engineering. However, the identification of antibodies that disrupt target functions beyond binding remains a challenge. In particular, there are very few strategies that support identification and engineering of either protein-based irreversible binders or inhibitory enzyme binders. Expanding the range of chemistries in antibody libraries has the potential to lead to efficient discovery of function-disrupting antibodies. In this work, we describe a yeast display-based platform for the discovery of chemically diversified antibodies. We constructed a billion-member antibody library that supports the presentation of a range of chemistries within antibody variable domains via noncanonical amino acid (ncAA) incorporation and subsequent bioorthogonal click chemistry conjugations. Use of a polyspecific orthogonal translation system enables introduction of chemical groups with various properties, including photo-reactive, proximity-reactive, and click chemistry-enabled functional groups for library screening. We established conjugation conditions that facilitate modification of the full library, demonstrating the feasibility of sorting the full billion-member library in “protein-small molecule hybrid” format in future work. Here, we conducted initial library screens after introducingO-(2-bromoethyl)tyrosine (OBeY), a weakly electrophilic ncAA capable of undergoing proximity-induced crosslinking to a target. Enrichments against donkey IgG and protein tyrosine phosphatase 1B (PTP1B) each led to the identification of several OBeY-substituted clones that bind to the targets of interest. Flow cytometry analysis on the yeast surface confirmed higher retention of binding for OBeY-substituted clones compared to clones substituted with ncAAs lacking electrophilic side chains after denaturation. However, subsequent crosslinking experiments in solution with ncAA-substituted clones yielded inconclusive results, suggesting that weakly reactive OBeY side chain is not sufficient to drive robust crosslinking in the clones isolated here. Nonetheless, this work establishes a multi-modal, chemically expanded antibody library and demonstrates the feasibility of conducting discovery campaigns in chemically expanded format. This versatile platform offers new opportunities for identifying and characterizing antibodies with properties beyond what is accessible with the canonical amino acids, potentially enabling discovery of new classes of reagents, diagnostics, and even therapeutic leads.Table of Contents Figure
Single-nucleus transcriptomics reveal the cytological mechanism of conjugated linoleic acids in regulating intramuscular fat deposition
Authors: Wang Liyi , Liu Shiqi , Zhang Shu , Wang Yizhen , Zhou Yanbing , Shan Tizhong 
Published: May 2024

AbstractConjugated linoleic acids (CLAs) can serve as a nutritional intervention to regulate quality, function and fat infiltration in skeletal muscles but the specific cytological mechanisms are still unknown. Here, we applied single-nucleus RNA-sequencing (snRNA-seq) to characterize the cytological mechanism of CLAs regulates fat infiltration in skeletal muscles based on pig models. We investigated the regulatory effects of CLAs on cell populations and molecular characteristics in pig muscles and found CLAs could promote the transformation of fast glycolytic myofibers into slow oxidative myofibers. We also observed three subpopulations including SCD+/DGAT2+, FABP5+/SIAH1+, and PDE4D+/PDE7B+subclusters in adipocytes and CLAs could increase the percentage of SCD+/DGAT2+adipocytes. RNA velocity analysis showed FABP5+/SIAH1+and PDE4D+/PDE7B+adipocytes could differentiate into SCD+/DGAT2+adipocytes. We further verified the differentiated trajectory of mature adipocytes and identified PDE4D+/PDE7B+adipocytes could differentiate into SCD+/DGAT2+and FABP5+/SIAH1+adipocytes by using high IMF content Laiwu pig models. The cell-cell communication analysis identified the interaction network between adipocytes and other subclusters such as fibro/adipogenic progenitors (FAPs). Pseudotemporal trajectory analysis and RNA velocity analysis also showed FAPs could differentiate into PDE4D+/PDE7B+preadipocytes and we discovered the differentiated trajectory of preadipocytes into mature adipocytes. Besides, we found CLAs could promote FAPs differentiate into SCD+/DGAT2+adipocytes via inhibiting c-Jun N-terminal kinase (JNK) signalling pathwayin vitro. This study provides a foundation for regulating fat infiltration in skeletal muscles by using nutritional strategies and provides potential opportunities to serve pig as an animal model to study human fat infiltrated diseases.
APOE Impacts Lipid Trafficking in Retinal Pigment Epithelium Cells
Authors: Richards Sarah E.V. , Demirs John , Jose Sandra , Fan Lin , Xu YongYao , Esterberg Robert , Huang Chia-Ling , Wilson Christopher W. , Saint-Geniez Magali , Liao Sha-Mei 
Published: May 2024

AbstractAge-related macular degeneration (AMD) is typified by the formation of lipid-rich drusen under the retinal pigment epithelium (RPE) layer. Apolipoprotein E (APOE) is a known genetic risk factor for AMD and a substantial component of drusen, however, the mechanism by which APOE variants contribute to AMD pathology remains unclear. APOE is the primary cholesterol and lipid transport protein of the central nervous system, as well as a component circulating lipoproteins. To better understand how APOE-dependent lipid transport may impact AMD risk, we generated isogenic APOE iPS-RPE cells expressing each of the common human APOE isoforms, as well as an APOE knockout line. APOE knockout cells showed significant morphological and barrier function deficits, suggesting that APOE is essential for RPE health. Furthermore, we observed that APOE abundance is isoform-dependent in RPE cells and that lipid transport is deficient in APOE knockout RPE cells, as well as in RPE cells expressing APOE2, a variant associated with higher risk of AMD. Contrastingly, cells expressing APOE4 seem to respond strongly to lipid challenges by upregulating APOE to support efficient lipid transport. Our results suggest that disease associated APOE variants may impact lipid transport in RPE, contributing to the formation of drusen and impairing cellular function.
Job-field underemployment: its effect on career obstacles in the Israeli labor market
Authors: More Sharon 
Published: May 2024

PurposeThe purpose of the current article is to examine the effect of the inefficient allocation of academic individuals in the Israeli labor market in terms of mismatch between their fields of education and occupation – a phenomenon referred in the literature as “horizontal mismatch” and “job-field underemployment” – on their duration of unemployment, in the local labor market.Design/methodology/approachA sample size of 8,554 participants have taken part in the survey by the Central Bureau of Statistics: Undergraduate students at academic institutions in Israel in the academic year of 2010–2011, who were sampled again in the academic year of 2017–2018, to determine the nature of their integration into the labor market, and the quality of their career progress. The study’s methodology is statistical-correlational, and its data mainly based on the answers of the participants in the research tool (questionnaire). A T-test for independent samples (via SPSS) has proven the key results.FindingsThe average cumulative annual duration of unemployment, as of graduation with a bachelor’s degree, among the mismatched graduates, was found to be higher than the average cumulative annual duration of unemployment among the matched graduates.Originality/valueThe current study’s originality lays both in its large sample size (8,554), and in the repeatability element of its sampling (test-retest reliability). Also, its findings regarding the consequences of the nature of the match between the educational field and occupational field – on the quality of integration of academics in the Israeli labor market, are pioneers in this field.
Emission reduction pressure and enterprise digital transformation: do enterprise innovation and digital economy matter?
Authors: Li Xiuping , Yang Ye 
Published: May 2024

PurposeCoordinating low-carbonization and digitalization is a practical implementation pathway to achieve high-quality economic development. Regions are under great emission reduction pressure to achieve low-carbon development. However, why and how regional emission reduction pressure influences enterprise digital transformation is lacking in the literature. This study empirically tests the impact of emission reduction pressure on enterprise digital transformation and its mechanism.Design/methodology/approachThis article takes the data of non-financial listed companies from 2011 to 2020 as a sample. The digital transformation index is measured by entropy value method. The bidirectional fixed effect model was used to test the hypothesis.FindingsThe research results show that emission reduction pressure forces enterprise digital transformation. The mechanism lies in that emission reduction pressure improves digital transformation by promoting enterprise innovation, and digital economy moderates the nexus between emission reduction pressure and digital transformation. Furthermore, the effect of emission reduction pressure on digital transformation is more significant for non-state-owned, mature and high-tech enterprises.Originality/valueThis paper discusses the mediating role of enterprise innovation between carbon emission reduction pressure and enterprise digital transformation, as well as the moderating role of digital economy. The research expands the body of knowledge about dual carbon targets, digitization and technological innovation. The author’s findings help update the impact of regional digital economy development on enterprise digital transformation. It also provides theoretical guidance for the realization of digital transformation by enterprise innovation.
The impact of the interaction of independent and cooperative innovation on firm digitization: the moderating role of managerial discretion
Authors: Gao Jiaxin , Gu Xin , Yang Xue 
Published: May 2024

PurposeThis study aims to deliver a new perspective on how the interaction of independent and cooperative innovation affects firm digitization. Based on resource constraint theory, this study argues that the aforementioned interaction negatively affects firm digitization. The moderating role of managerial discretion is also discussed in light of the principles of the awareness-motivation-capability (AMC) framework.Design/methodology/approachThe proposed hypotheses are empirically tested using a negative binomial modeling approach. The data used are from A-share listed companies in China’s Shanghai and Shenzhen stock markets from 2006 to 2020.FindingsThis study suggests that the interaction of independent innovation and cooperative innovation negatively impacts digitization. In addition, this study argues that environmental discretion and organizational discretion weaken the negative impact of the mentioned interaction on digitization. However, additional discretion in the Chinese context has no effect on above relationships.Originality/valueThis study explores the impact of the interaction of independent and cooperative innovation on digitization and incorporates managerial discretion into this framework based on the AMC framework.
(Re)Framing sustainable careers: toward a conceptual model and future research agenda
Authors: Donald William E. , Van der Heijden Beatrice I.J.M. , Manville Graham 
Published: May 2024

PurposeBy adopting a Social Exchange Theory (SET) lens, this paper aims to integrate the often-fragmented literature streams of Vocational Behavior (VB), Career Development (CD), and Human Resource Management (HRM) to offer a conceptual model for framing sustainable careers.Design/methodology/approachA conceptual approach is taken whereby eight propositions are developed to integrate the fragmented literature streams of VB, CD, and HRM.FindingsWe posit that external factors and career counseling moderate the positive relationship between employability capital and self-perceived employability. We also argue that self-perceived employability is positively associated with career success and that career crafting moderates this relationship. Finally, we propose that career success is positively associated with a sustainable career, which, in turn, is positively associated with a sustainable organization.Practical implicationsThe practical contribution comes from informing VB, CD, and HRM policies and practices to maximize sustainable outcomes for individuals and organizations. The paper concludes with recommendations for future research.Originality/valueThe theoretical contribution comes from integrating the three literature streams to offer a conceptual model as the basis for further interdisciplinary collaborations.
Financial mechanism for sustainability: the case of China’s green financial system and corporate green investment
Authors: Khalid Fahad , Su Chih-Yi , Weiwei Kong , Voinea Cosmina L. , Srivastava Mohit 
Published: May 2024

PurposeThis study empirically evaluates the effect of China’s 2016 Green Financial System (GFS) framework on corporate green development, focusing on the role of green investment in achieving sustainability.Design/methodology/approachThis study uses a quasinatural experiment design to combine difference-in-difference and propensity score matching methods for analysis. It examines 799 polluting and 1,130 nonpolluting firms from 2013 to 2020, enabling a comprehensive assessment of the GFS framework’s influence.FindingsThis study affirms a statistically significant positive influence of the GFS framework on escalating green investment levels in polluting firms. Robust sensitivity analyses, encompassing parallel trend assessment, entropy balancing test, and alternative proxies, corroborate these findings. A mediation analysis identifies the implementation of an environmental management system as the potential underlying mechanism. A cross-sectional analysis identifies high financial slack, high profitability, mandatory CSR regulations, and marketization level as the influencing factors.Research limitations/implicationsThe study’s findings have critical implications for policymakers, regulators, and companies. Demonstrating the effectiveness of the GFS framework in driving green investment underscores the importance of aligning financial systems with sustainability goals.Originality/valueThis study contributes novel empirical evidence on the positive effect of China’s GFS framework on corporate green development. The quasinatural experiment design, coupled with comprehensive sensitivity analyses, strengthens the robustness of the findings.
A modified Green-Naghdi fractional order model for analyzing thermoelectric MHD
Authors: Hendy Mohamed M. , Ezzat Magdy A. 
Published: May 2024

Purpose
Whereas, the classical Green-Naghdi Type II (GN-II) model struggles to accurately represent the thermo-mechanical behavior of thermoelectric MHD due to its inability to account for the memory effect. A new mathematical model of the GN-II theory incorporates a fractional order of heat transport to address this issue.

Design/methodology/approach
The employment of the matrix exponential method, which forms the basis of the state-space approach in contemporary theory, is central to this strategy. The resulting formulation, together with the Laplace transform techniques, is applied to a variety of problems. Solutions to a thermal shock problem and to a problem of a layer media both without heat sources are obtained. Also, a problem with the distribution of heat sources is considered. The numerical technique is used to achieve the Laplace transform inversion.

Findings
According to the numerical results and its graphs, the influences of the fractional order parameters, figure-of-merit factor, thermoelectric power and Peltier coefficient on the behavior of the field quantities are investigated in the new theory.

Originality/value
The new modeling of thermoelectric MHD has advanced significantly as a result of this work, providing a more thorough and precise tool for forecasting the behavior of these materials under a range of thermal and magnetic conditions.
Mental health matters: individual, organizational and leadership dynamics on employee mental wellness through organizational interventions
Authors: Mehta Mita , Golani Taniya , Saxena Abhineet , Saxena Priti 
Published: May 2024

Purpose
This study aims to discover the complex relationships between individual factors (IF), organizational culture (OC) and leadership styles that impact employee mental health (MH) in the post-pandemic age. Considering the changing nature of the workforce, which has been made worse by the COVID-19 epidemic, the research attempts to clarify the complex interactions between these components.

Design/methodology/approach
This research uses the structural equation modeling (SEM) methodology. The authors collected data from 383 information technology sector employees and used the partial least squares SEM tool to analyze. The SEM analysis models the relationships between IF, OC and organizational leadership (OL), examining how these factors collectively influence employee MH. In addition, the study explores the mediating effects of organizational interventions (OI) to assess the pathways through which these interventions impact the observed relationships.

Findings
OL and OC significantly impact employees’ MH. Also, OI plays a role in mediating variables in fortifying this relationship; one of the viable explanations for this may be that unlike IF, OL and OC are more comprehensive in coverage and influence the overall organization.

Originality/value
The present study suggests the crucial role of OL and the OC in ensuring better employee MH, emphasizing how organizations navigate these transformative shifts, which are critical for realizing their full potential professionally and personally.