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Research on key factors influencing Chinese designers’ use of AIGC: An extension based on TAM and TRI

With the rapid development of AI intelligent technology, AIGC can bring an innovative revolution to art creation, providing designers with unlimited possibilities but also challenges. These challenges affect the willingness to adopt and constrain the sustainable development of AIGC. The purpose of this study is to analyse the factors of designers’ adoption intention behaviours. This study reconstructed the research model by combining the factors of AIGC technology characteristics and interactivity, technology acceptance model, technology readiness model, etc. The empirical study was conducted from the dual perspectives of AIGC application characteristics and designers’ psychology, in order to predict the factors that predict designers’ behavioural intentions to use AIGC. In this study, a questionnaire survey was conducted among designers in China and 462 valuable responses were received. Through structural equation modelling (SEM) analysis, the study found that: (1) AIGC’s technical features and interactivity positively affect perceived ease of use, and perceived usefulness, but the interactive features do not directly affect perceived usefulness; perceived ease of use and perceived usefulness positively affect designers’ intention to adopt AIGC applications; (2) optimism and innovation positively affect technical features and designers’ intention to adopt; Insecurity negatively affects designers’ willingness to adopt, and insecurity does not affect technical features; discomfort does not affect designers’ technical features and willingness to adopt. This study further extends the theoretical models of TAM(Technology Acceptance Model) and TRI(Technology Readiness Model), provides a theoretical basis for studying designers’ adoption behaviour of AIGC, and enriches the application groups and domains of the theoretical models of TAM and TRI. The results of this study provide inspiration for the development, design, and marketing of AIGC applications, contributing to the realisation and further adoption of AIGC applications, as well as to the professional development of designers.

Benefits of equilibrium between microbiota- and host-derived ligands of the aryl hydrocarbon receptor after stroke in aged male mice

Educational constraints on marital sorting and income mobility

This paper examines the effect of educational assortative mating on overall income mobility in terms of both inter- and intragenerational mobility. In recent years, educational assortative mating has become a trend in China, and this marital sorting pattern not only contributes to marriage stability but is also related to increased income mobility. Educational assortative mating affects the distribution of educational resources among families with diffferent educational qualifications. Families with higher educational qualifications have more educational resources, thus obtaining a more solid income status. Educational assortative mating has the most significant influence on the income mobility of the low-income group, as high-quality educational resources are the key to enabling this group to raise its income status. This paper argues that, in the future, income mobility should be promoted by evenly distributing social education resources and reducing the resource constraints on the upward mobility of the low-income group.

Drug repurposing for Alzheimer’s disease and other neurodegenerative disorders

The impact of digital industry development on regional economic resilience: Evidence from China

With the outbreak of the global public health crisis in 2019, enhancing the resilience of regional economies has become the current focal point. Existing studies have mostly focused on the region itself, lacking exploration of regional economic resilience from the aspects of dynamics, multiple perspectives, and multidimensional integration. At the same time, the digital industry, as an emerging sector, should not only consider its impact on economic development itself, but also focus on whether it can continuously and effectively enhance the level of regional economic resilience, in order to cope with crises that may arise at any time. Therefore, through empirical methods, we conducted a detailed study of the spatial correlation and internal driving factors between the digital industry and regional economic resilience, aiming to build a more valuable theoretical framework based on existing research findings and explore a regional resilience development strategy centered around the digital industry. This paper, combining conclusions and methods from existing literature, attempts to expand the definition of regional economic resilience, evaluation index system, and the relationship with the digital industry from the perspective of evolutionary economic geography. This article empirically examines data from 30 provinces in China from 2014 to 2022 (excluding Tibet, Hong Kong, Macau, and Taiwan due to lack of data). Firstly, this paper employs a two-way fixed effects model to examine the direct relationship between digital industry development and regional economic resilience. The research results indicate that the development of the digital industry can effectively enhance regional economic resilience. Secondly, the role of spatial location, as an important aspect of evolutionary economic geography, is also considered in this paper. The spatial Durbin model is used to discover spatial spillover effects of digital industry development on regional economic resilience under different spatial location relationships. Finally, this paper considers environmental regulations as a threshold variable to study the impact of the digital industry on regional economic resilience under different levels of environmental regulation. The results indicate that when the degree of environmental regulation is less than 0.0011, the digital industry can more effectively empower the enhancement of regional economic resilience levels. In conclusion, this paper finds that while emphasizing the role of the digital industry in the resilient development of regional economies, it is also essential to promote regional cooperation for mutual benefit and win-win results. This will accelerate the transformation of digital enterprises, optimize industrial structures, and achieve green development.

Axin formation inhibitor 1 aggravates hepatic ischemia‒reperfusion injury by promoting the ubiquitination and degradation of PPARβ

The impact of top management team tenure heterogeneity on innovation efficiency of declining firms

Most firms will experience a decline in their development process. The contraction in demand and the impact of COVID-19 have exacerbated a firm’s performance. Under the dilemma of resources reduction and recovery, the declining firm pays more attention to the efficient utilization of the diminishing innovation resources. Based on upper echelon theory and principal-agent theory, this study investigates the impacts of top management team (TMT) tenure heterogeneity and ownership concentration on innovation efficiency. The sample consists of 534 firm observations after PSM nearest-neighbour matching, sourced from A-share listed manufacturing firms in Shanghai and Shenzhen from 2015 to 2019. Innovation efficiency of declining firms is measured using the Malmquist Index method. The fixed-effects (FE) model, PSM-DID model, and stepwise regression are employed to test our hypotheses. The main findings conclude that TMT tenure heterogeneity improves innovation efficiency, and the effect in declining firms is stronger compared to normal firm. Moreover, the concentrated ownership structure inhibits this positive effect because of the excessive tight control over TMT, and this inhibitory effect is stronger in declining firms than normal firms. The robustness checks of alternative variables and alternative regression model, and the addressing of endogenous problem, further support these findings. Efficiency improvement is crucial for the recovery of declining firm. The introduction of an efficiency perspective bridges the gaps in the existing literature. This study contributes to the literature on upper echelon theory and principal-agent theory by integrating them into the context of declining firms. The continuous interaction between the replacement TMT members and ownership restructuring shapes the dynamic capability of declining firms, contributing to the dynamic capability literature. The findings also provide practical guidelines for declining firms, such as replacing top management members and diluting equity, to achieve recovery. It is noted that an excessive focus on efficiency can also lead to neglecting thorough strategic change.

Human skeletal muscle fiber heterogeneity beyond myosin heavy chains

A statistical insight to exploration of medicinal wastewater as a source of thermostable lipase-producing microorganisms

Bacteria are ubiquitous and capable of thriving in diverse environments, including industrial effluents, which often present harsh physical and chemical conditions. These microorganisms produce various intracellular and extracellular biomolecules that enable adaptation, tolerance, and utilization of such extreme environments. Recognizing the growing industrial demand for thermostable lipases, this study focuses on the isolation, characterization, and optimization of lipase-producing bacteria from medicinal wastewater collected from a factory in North 24 Parganas, Kolkata, West Bengal, India. Nineteen lipase-producing bacterial isolates were obtained from nutrient agar plates and screened using tributyrin agar (TBA) plates. Extracellular lipolytic activity was confirmed via the cup-plate method with Tween 20/80 agar and methyl red as the indicator. The isolates were characterized morphologically and through biochemical tests. Extracellular lipase activity was quantified spectrophotometrically using para-nitrophenyl palmitate (pNPP) as a substrate in 50 mM Tris-HCl buffer, with absorbance measured at 410 nm after incubation at 65°C for 20 minutes to assess thermostability. Of the 19 isolates, 11 produced thermolabile lipases, while 8 exhibited thermostable lipase activity. Among these, three isolates (MWS14, MWS6, and MWS18) demonstrated high thermostable lipase production, with MWS18 being the most productive. Ribotyping and BLAST analysis revealed that these isolates shared 99% sequence similarity with Enterococcus, Bacillus, and Serratia species, respectively. Statistical analysis using the Kruskal-Wallis H-test confirmed significant differences in lipase production among the three groups of isolates. The study also predicts greater lipase production potential in Gram-negative bacterial strains compared to Gram-positive isolates. These findings highlight the industrial relevance of medicinal wastewater as a source of thermostable lipase-producing bacteria.

Lipogenic enzyme FASN promotes mutant p53 accumulation and gain-of-function through palmitoylation

Abstract The tumor-suppressive function of p53 is frequently disrupted by mutations in cancers. Missense mutant p53 (mutp53) protein often stabilizes and accumulates to high levels in cancers to promote tumorigenesis through the gain-of-function (GOF) mechanism. Currently, the mechanism of mutp53 accumulation and GOF is incompletely understood. Here, we identify the lipogenic enzyme FASN as an important regulator of mutp53 accumulation and GOF. FASN interacts with mutp53 to enhance mutp53 palmitoylation, which inhibits mutp53 ubiquitination to promote mutp53 accumulation and GOF. Blocking FASN genetically or by small-molecule inhibitors suppresses mutp53 palmitoylation to inhibit mutp53 accumulation, which in turn inhibits the growth of mutp53 tumors in orthotopic and subcutaneous xenograft tumor models and transgenic mice, as well as the growth of human tumor organoids carrying mutp53. Our results reveal that mutp53 palmitoylation is an important mechanism underlying mutp53 accumulation and GOF, and targeting FASN is a potential therapeutic strategy for cancers carrying mutp53.

State-trace analysis meets personality measurement: Why the Big Five tests are not based on five latent dimensions and how to fix them

Unidimensionality is a fundamental yet often overlooked prerequisite for measurement. In the context of psychological measurement, the central question is whether a set of items can be logically reduced to a single latent factor. This study advocates for the application of state-trace analysis, an underutilized method from mathematical psychology, as a decisive tool to address this question. State-trace analysis provides a simple, general, and rigorous criterion for unidimensionality: monotonicity between item pairs. Identifying items within a factor that violate this criterion is straightforward, offering a practical approach to evaluating unidimensionality. This paper demonstrates the utility of state-trace analysis through exemplary applications within the framework of the five-factor model, analyzing data from the International Personality Item Pool-NEO-120 (N = 618, 000) and the NEO Personality Inventory–Revised (N1 = 857, N2 = 500). The findings reveal that maintaining the five-factor model requires significant revisions to numerous items, highlighting the potential of state-trace analysis to enhance personality measurement beyond existing methodologies. The paper concludes by discussing strategies to promote broader adoption of this method and how future designs in personality research can be tailored to effectively incorporate state-trace analysis.

Time-resolved oxidative signal convergence across the algae–embryophyte divide

Abstract The earliest land plants faced a significant challenge in adapting to environmental stressors. Stress on land is unique in its dynamics, entailing swift and drastic changes in light and temperature. While we know that land plants share with their closest streptophyte algal relatives key components of the genetic makeup for dynamic stress responses, their concerted action is little understood. Here, we combine time-course stress profiling using photophysiology, transcriptomics on 2.7 Tbp of data, and metabolite profiling analyses on 270 distinct samples, to study stress kinetics across three 600-million-year-divergent streptophytes. Through co-expression analysis and Granger causal inference we predict a gene regulatory network that retraces a web of ancient signal convergences at ethylene signaling components, osmosensors, and chains of major kinases. These kinase hubs already integrated diverse environmental inputs since before the dawn of plants on land.

Fundus autofluorescence features specific for EYS-associated retinitis pigmentosa

Purpose To assess the utility of fundus autofluorescence (FAF) patterns for predicting the EYS genotype in retinitis pigmentosa (RP) patients. Methods This retrospective, multi-institutional study analyzed FAF images from 200 RP patients (74 with EYS and 126 without EYS) from Singapore and Japan. Seven FAF patterns including the infinity sign and a broad banded hyper-autofluorescent leading edge were evaluated for their association with the EYS genotype. Results The infinity sign and broad banded hyperautofluorescent leading edge occurred more frequently in EYS eyes (p = 0.0014 and p = 0.036 respectively). Logistic regression analysis showed that the infinity sign was predictive of EYS (p = 0.003). The combined FAF parameters predicted EYS with a specificity of 95.20%, sensitivity of 25.68% and accuracy of 69.50%, with a cut-off value 0.5 based on the probability of seven FAF parameters. Conclusions In this multinational cohort study of patients with RP, we demonstrated that specific FAF patterns, particularly the infinity sign, have clinical utility in identifying patients with EYS-associated disease. These findings may be useful for clinicians and geneticists when genotyping patients with RP, and may also enhance our understanding of underlying pathophysiology of EYS-associated RP, which is a prevalent cause of RP in Asia and elsewhere.

Sequencing of <scp>d</scp>/<scp>l</scp>-DNA and XNA by Templated-Synthesis

A decision point between transdifferentiation and programmed cell death priming controls KRAS-dependent pancreatic cancer development

Abstract KRAS-dependent acinar-to-ductal metaplasia (ADM) is a fundamental step in the development of pancreatic ductal adenocarcinoma (PDAC), but the involvement of cell death pathways remains unclear. Here, we show that key regulators of programmed cell death (PCD) become upregulated during KRAS-driven ADM, thereby priming transdifferentiated cells to death. Using transgenic mice and primary cell and organoid cultures, we show that transforming growth factor (TGF)-β-activated kinase 1 (TAK1), a kinase regulating cell survival and inflammatory pathways, prevents the elimination of transdifferentiated cells through receptor-interacting protein kinase 1 (RIPK1)-mediated apoptosis and necroptosis, enabling PDAC development. Accordingly, pharmacological inhibition of TAK1 induces PCD in patient-derived PDAC organoids. Importantly, cell death induction via TAK1 inhibition does not appear to elicit an overt injury-associated inflammatory response. Collectively, these findings suggest that TAK1 supports cellular plasticity by suppressing spontaneous PCD activation during ADM, representing a promising pharmacological target for the prevention and treatment of PDAC.

Development of lifestyle assessment: A Delphi survey of multi-faceted health experts

Objective In the field of health promotion, there’s a growing focus on adopting an academic approach to assess and evaluate the intricate and ever-evolving nature of lifestyles. This approach is crucial for shaping and improving a healthy way of life. Systematic measurement of lifestyles is essential for enhancing overall health and well-being, encompassing physical, mental, and social dimensions. This study’s goal is to create an assessment tool that measures the diversity and intensity of lifestyle behaviors linked to human health. Our efforts involved developing quantitative measurement items that encompass the holistic concepts of health and lifestyle and validating them. Methods Between March and April 2023, we gathered insights from 14 experts in lifestyle and health. Building on previous research, we conducted a Delphi survey twice. In the initial survey, we collected expert opinions through open and closed-ended questions about lifestyle evaluation items. After the first survey, we corrected several items that didn’t meet the Content Validity Ratio (CVR) standard before proceeding. We presented the first survey’s findings to an expert panel, leading to a consensus. Results The initial Delphi round produced 76 items, and the second round resulted in 72 items after adjusting those with CVR scores of 0.51 or less. The final Content Validity Ratio was 0.83, signifying a robust validation process, with a convergence of 0.50 and a consensus level of 0.75. Conclusion In summary, this study successfully developed a comprehensive lifestyle assessment tool using a modified Delphi technique. The 72 items are categorized into eight subcategories and four overarching themes. This tool provides a systematic approach to evaluate lifestyles, promoting health and well-being across physical, mental, and social dimensions. It also assists in identifying specific lifestyle elements that require more in-depth intervention strategies, all while preserving the academic integrity of the content.

Boosting mechanical durability under high humidity by bioinspired multisite polymer for high-efficiency flexible perovskite solar cells

Abstract Flexible perovskite solar cells (FPSCs) with high stability in moist air are required for their practical applications. However, the poor mechanical stability under high humidity air remains a critical challenge for flexible perovskite devices. Herein, inspired by the exceptional wet adhesion of mussels via dopamine groups, we propose a multidentate-cross-linking strategy, which combine multibranched structure and adequate dopamine anchor sites in three-dimensional hyperbranched polymer to directly chelate perovskite materials in multiple directions, therefore construct a vertical scaffold across the bulk of perovskite films from the bottom to the top interfaces, intimately bind to the perovskite grains and substrates with a strong adhesion ability, and enhance mechanical durability under high humidity. Consequently, the modified rigid PSCs achieve superior PCE up to 25.92%, while flexible PSCs exhibit a PCE of 24.43% and maintain 94.1% of initial PCE after 10,000 bending cycles with a bending radius of 3 mm under exposed to 65% humidity.

Systematic representation and optimization enable the inverse design of cross-species regulatory sequences in bacteria

Rh(II) and Chiral Phosphoric Acid Co-catalyzed Selective O–H Insertions for Stereodivergent <i>O</i>-Alkylation of Glycosides

Deciphering neuronal variability across states reveals dynamic sensory encoding

Abstract Influenced by non-stationary factors such as brain states and behavior, neurons exhibit substantial response variability even to identical stimuli. However, it remains unclear how their relative impact on neuronal variability evolves over time. To address this question, we designed an encoding model conditioned on latent states to partition variability in the mouse visual cortex across internal brain dynamics, behavior, and external visual stimulus. Applying a hidden Markov model to local field potentials, we consistently identified three distinct oscillation states, each with a unique variability profile. Regression models within each state revealed a dynamic composition of factors influencing spiking variability, with the dominant factor switching within seconds. The state-conditioned regression model uncovered extensive diversity in source contributions across units, varying in accordance with anatomical hierarchy and internal state. This heterogeneity in encoding underscores the importance of partitioning variability over time, particularly when considering the influence of non-stationary factors on sensory processing.