bluuebunny/crossref_metadata_2025 huggingface dataset:
Direct imaging of neural activity reveals neural circuits via spatiotemporal activation mapping
Authors: Keum Jae-Youn , Toi Phan Tan , Park Semi , Chun Heejung , Park Jang-Yeon
Published: August 2024

Two years ago, our group reported direct imaging of neuronal activity (DIANA), a functional magnetic resonance imaging (fMRI) technique that directly detects neuronal activity at high spatiotemporal resolution. In this study, we successfully reproduced the DIANA response in medetomidine-anesthetized mice using forelimb electrical stimulation at 11.7 T. More importantly, we showed that multiple neural circuits can be effectively revealed by DIANA fMRI through spatiotemporal activation mapping. The spatiotemporal activation mapping proposed here utilizes the temporal information of the DIANA response, that is, the time when the DIANA response reaches its peak, which is a unique feature that distinguishes it from the activation mapping method used in existing fMRI. Based on DIANA activation areas, we identified several neural circuits involved in forelimb sensory processing in the somatosensory network, which includes multiple brain regions: ventral posterolateral nucleus of the thalamus (VPL), posteromedial thalamic nucleus (POm), forelimb primary somatosensory cortex (S1FL), secondary somatosensory cortex (S2), primary motor cortex (M1), and secondary motor cortex (M2). Additionally, we also identified a pain-related neural circuit involving brain regions of the anterior cingulate cortex (ACC) and mediodorsal nucleus (MD). Interestingly, the spatiotemporal activation mapping also allowed us to identify subregions with different DIANA response times within the same functional region (e.g., VPL, POm, S1FL, and S2). Our study highlights the potential of DIANA fMRI to advance our understanding of sensory information processing throughout the brain and to provide insight into the spatiotemporal dynamics of brain networks at the level of neural circuits.
Morphology-dependent entry kinetics and spread of influenza A virus
Authors: Peterl Sarah , Lahr Carmen M. , Schneider Carl N. , Meyer Janis , Podlipensky Xenia , Lechner Vera , Villiou Maria , Eis Larissa , Klein Steffen , Funaya Charlotta , Cavalcanti-Adam Elisabetta Ada , Graw Frederik , Selhuber-Unkel Christine , Rohr Karl , Chlanda Petr
Published: August 2024

Influenza A viruses (IAV) display a broad variety of morphologies ranging from spherical to long filamentous virus particles. These diverse phenotypes are believed to allow the virus to overcome various immunological and pulmonary barriers during entry into the airway epithelium and influence the viral entry pathway. Remarkably, lab-adapted IAV strains lost this morphological variance and exhibit preferred spherical morphology. However, it remains unclear which factors lead to this lab-adapted preference and which pulmonary defense factors are responsible for the preferred filamentous morphology in physiological settings. In this study, we established fluorescent reporter viruses with spherical or filamentous morphology but with the same surface glycoproteins. We developed a correlative fluorescence and scanning electron microscopy workflow to analyze the impact of viral morphology on cell-to-cell spread and identify conditions under which IAV with either spherical or filamentous morphology confer an advantage. Our findings demonstrate that filamentous IAV cell-to-cell spread is significantly slower in various cell lines, which can explain the predominant spherical morphology in lab-adapted strains. This observation is consistent with delayed entry kinetics of filamentous viruses structurally analyzed by cellular cryo-electron tomography. We found that cellular junction integrity and mucin do not exert morphology-dependent inhibition of IAV cell-to-cell spread. On the other hand, filamentous virions confer an advantage under the pressure exerted by neutralizing antibodies against hemagglutinin.
The conserved biochemical activity and function of an early metazoan phosphatidylinositol 5 phosphate 4-kinase regulates growth and development
Authors: Krishnan Harini , Muzaffar Suhail , Sharma Sanjeev , Ramya Visvanathan , Ghosh Avishek , Sowdhamini Ramanathan , Raghu Padinjat
Published: August 2024

The ability to co-ordinate function between multiple cells is a critical requirement for multi-cellularity. This co-ordination is mediated by hormones or growth factors, molecules secreted by one cell type that can convey information to the other cells and influence their behaviour. Hormone-dependent signalling is mediated by second messenger systems;phosphoinositides (PIs) generated by lipid kinase activity are one such key second messenger system. Phosphatidylinositol 5 phosphate 4-kinase (PIP4K) is a lipid kinase that phosphorylates phosphatidylinositol 5-phosphate (PI5P) to generate phosphatidylinositol 4,5 bisphosphate [PI(4,5)P2]. Following a comprehensive bioinformatics analysis of ca. 23296 proteomes covering the tree of life, we find that PIP4K is a metazoan-specific enzyme, although its homologs are also found in choanoflagellate genomes. To understand their function in early metazoans, we experimentally analysed the biochemical activity and physiological function of PIP4K from several early metazoans. We find that the PIP4K enzyme from an early branching metazoan spongeAmphimedon queenslandica(AqPIP4K), regarded as the earliest evolved metazoan, shows a biochemical activity highly conserved with human PIP4K; AqPIP4K is able to selectively phosphorylate PI5P to generate PI(4,5)P2just as effectively as the human enzyme. Further, AqPIP4K was able to rescue the reduced cell size, growth and development phenotype in larvae of a null mutant inDrosophilaPIP4K. These phenotypes are regulated through activity of the hormone insulin, acting via the cell surface insulin receptor, a member of the receptor tyrosine kinase family, that is unique to metazoans. Together, our findings indicate that in early metazoans, AqPIP4K is likely to function in a signal transduction pathway that is required for receptor tyrosine kinase signalling. Overall, our work defines PIP4K as a signal transduction motif required to regulate receptor tyrosine kinase signalling for intercellular communication in the earliest forms of metazoa.
Cardiac p16 Expression Following Vape Exposure with Nicotine Shows Sex-Specific Induction in Males but not Females
Authors: Shain Abraham , Savko Clarissa , Rokaw Sophie , Jaafar Faid , Rieder Abigail , Wright Morgan K , Phillips Joy Arlene , Konja Nickolas , Michael Sama , Mathews Haley , Jerjees Gina , Bailey Barbara , Sussman Mark
Published: August 2024

Vaping is marketed as a safe alternative to traditional cigarette smoking, but multiple studies demonstrate deleterious cardiopulmonary effects including cardiac function decline and fibrotic remodeling with alveolar size enlargement. Nicotine, a common constituent of vaping aerosol, stimulates p16 expression in pulmonary tissue but the impact on cardiac tissue remains unclear. In this study, mice were exposed to e-cigarette vape aerosol either containing nicotine (Vape Nicotine; VN) or without nicotine (Vape 0; V0). Non-exposed (No Vape; NoV) mice were used as controls. Cardiac effects were assessed by echocardiography, histology, and immunofluorescence to determine changes in function, morphology, p16, and Discoidin Domain Receptor 2 (DDR2). VN depressed cardiac function and increased collagen deposition relative to V0 and NoV. Interestingly, p16 expression was increased in cardiomyocytes and interstitial cells of male mice while remaining unchanged in females. In contrast to VN, V0 had no significant impact on cardiac function or p16 expression in males. Furthermore, collagen deposition in the V0 group was significantly lower than the VN group. Subsequent cardiac fibroblast analysis using DDR2 revealed increased expression within the V0 group relative to VN and NoV. Collectively, these findings show collagen accumulation as well as p16 expression prompted by vaping is mediated by nicotine as a constituent of vape juice. In contrast, vape aerosol alone promotes accrual of cardiac fibroblasts without concomitant changes in collagen accumulation or p16 expression. These results are the first to identify p16 induction with pathologic collagen deposition by exposure to vape aerosol containing nicotine in male cardiac tissue. The underlying basis for sex-specific differences in cardiac responses to vape aerosol exposure warrant further investigation, particularly those involving cellular and molecular changes that may lead to pathologic changes later in life.
Rapidin vitromethod to assemble and transfer DNA fragments into the JCVI-syn3B minimal synthetic bacterial genome through Cre/loxPsystem
Authors: Uenoyama Atsuko , Kiyama Hana , Mimura Mone , Miyata Makoto
Published: August 2024

JCVI-syn3B (syn3B), a minimal synthetic bacterium that only possesses essential genes, facilitates the examination of heterogeneous gene functions in minimal life. Conventionally,Escherichia coliis used to construct DNA fragments for gene transfer into the syn3B genome through Cre/loxPsystem. However, the construction process is challenging and time-consuming due to various issues, including the inhibition ofE. coligrowth and unexpected recombination, especially with AT-rich DNA sequences such as those found inMycoplasmagenes. Therefore, in this study, we aimed to develop a new transformation method to overcome these issues. We assembled the vector and target DNA fragments using an in vitro homologous recombination system and subsequently transferred the products into the syn3B genome. We obtained approximately 103∼104recombinant colonies per milliliter of the original culture in eight days, which is four days shorter than the conventional period, without any recombination issues, even for AT-rich DNA. This method may be applicable to other gene manipulation systems based on Cre/loxPsystem.

Significance

A rapid and trouble free method was developed to transfer genes to the genome of minimal synthetic bacterium JCVI-Syn3B through Cre/loxPsystem. This method can be applied to Cre/loxP-based gene manipulation system in various research fields.
Prevalence of the Calvin-Benson-Bassham cycle in chemolithoautotrophic psychrophiles and the potential for cold-adapted Rubisco
Authors: Harrison Kaitlin , Rapp Josephine Z. , Jaffe Alexander L. , Deming Jody W. , Young Jodi
Published: August 2024

The act of fixing inorganic carbon into the biosphere is largely facilitated by one enzyme, Rubisco. Beyond well-studied plants and cyanobacteria, many bacteria use Rubisco for chemolithoautotrophy in extreme environments on Earth. Here, we characterized the diversity of chemolithoautotrophic Rubiscos in subzero environments. First, we surveyed subzero environments and found that the Calvin-Benson-Bassham cycle was the most prevalent chemolithoautotrophic pathway. Second, we uncovered potential for chemolithoautotrophy in metagenomes from two distinct subzero, hypersaline Arctic environments: 40-kyr relic marine brines encased within permafrost (cryopeg brines) and first-year sea ice. Again, the Calvin-Benson-Bassham cycle was the dominant chemolithoautotrophic pathway in both environments, though with different Rubisco forms. From cryopeg brine, we reconstructed four metagenome-assembled genomes with the potential for chemolithoautotrophy, of which the sulfur-oxidizing genusThiomicrorhabduswas most abundant. A broader survey ofThiomicrorhabdusgenomes from diverse environments identified a core complement of three Rubisco forms (II, IAc, IAq) with distinct patterns of gain and loss. We developed a model framework and compared these different Rubisco forms across [CO2], [O2], and temperature. We found that form II outcompetes form I at low O2, but cold temperatures minimize this advantage. However, further inspection of form II from cold environments uncovered signals of thermal adaptation of key amino acids which resulted in a more exposed active site. These modifications suggest that these form II Rubisco proteins may have unique kinetics or thermal stability. This work can help address the limits of autotrophic functionality in extreme environments on Earth and other planetary bodies.

Importance

Autotrophy, or the fixation of inorganic carbon to biomass, is a key factor in life’s ability to thrive on Earth. Research on autotrophy has focused on plants and algae, but many bacteria are also autotrophic and can survive and thrive under more extreme conditions. These bacteria are a window to past autotrophy on Earth, as well as potential autotrophy in extreme environments elsewhere in the Universe. Our study focused on dark, cold, saline environments, which are likely to be found on Enceladus and Europa, as well as in the Martian subsurface. We found compelling evidence of cold adaptation in a key autotrophic enzyme, Rubisco, which could expand the known boundaries of autotrophy in rapidly disappearing icy environments on Earth. We also present a novel model framework that can be used to probe the limits of autotrophy not only on Earth but also on key astrobiological targets like Enceladus and Europa.
Host-derivedLactobacillus plantarumalleviates hyperuricemia by improving gut microbial community and hydrolase-mediated degradation of purine nucleosides
Authors: Fu Yang , Luo Xiao-Dan , Li Jin-Ze , Mo Qian-Yuan , Wang Xue , Zhao Yue , Zhang You-Ming , Luo Hao-Tong , Xia Dai-Yang , Ma Wei-Qing , Chen Jian-Ying , Wang Li-Hua , Deng Qiu-Yi , Ben Lukuyu , Saleemi Muhammad Kashif , Jiang Xian-Zhi , Chen Juan , Miao Kai , Lin Zhen-Ping , Zhang Peng , Ye Hui , Cao Qing-Yun , Zhu Yong-Wen , Yang Lin , Tu Qiang , Wang Wen-Ce
Published: August 2024

Abstract

Gut microbiota has been considered to be associated with the development of hyperuricemia (HUA) and gout. Some prebiotics from different sources had the potential alleviation function in HUA. However, whether host-derived potential probiotics, like Lactobacillus, from the gut of HUA animals could prevent the development of HUA is still uncertain.

In this study, we established a HUA geese model and isolated aLactobacillus plantarumstrain, SQ001, from the cecum of HUA geese. Nucleoside co-culture and metabolomics analyses revealed thatL. plantarumSQ001 is involved in the absorption and hydrolysis of nucleosides. Whole genome analysis showed there are four genes related with nucleosides hydrolysis inL. plantarumSQ001. The function of iunH, a nucleoside hydrolase gene, was further confirmed by heterologous expression and knockout assays. Oral administration ofL. plantarumSQ001 in HUA geese models upregulated theLactobacillusabundance and reduced serum uric acid (UA) levels. Likewise, in mouse models,L. plantarumSQ001 increased theL. plantarumabundance and lowered serum UA levels by reducing hepatic UA synthesis protein XO and renal UA reabsorption protein GLUT9 expression, while increasing renal UA excretion protein ABCG2 expression.

Our findings demonstrated that host-derived probiotics from geese could alleviate gut microbe dysbiosis and HUA in its host and mouse model. This study provides insights into the potential probiotic role ofLactobacillus plantarumin HUA or gout therapy.

Graphical abstract
Diet outperforms microbial transplant to drive microbiome recovery post-antibiotics
Authors: Kennedy Megan S , Freiburger Andrew , Cooper Michael , Beilsmith Kathleen , St. George Marissa L , Kalski Martin , Cham Candace , Guzzetta Alex , Ng Siew C , Chan Francis K , Rubin David , Henry Chris S , Bergelson Joy , Chang Eugene B
Published: August 2024

High-fat, low-fiber Western-style diets (WD) induce microbiome dysbiosis characterized by reduced taxonomic diversity and metabolic breadth, which in turn increases risk for a wide array of metabolic, immune and systemic pathologies. Recent work has established that WD can impair microbiome resilience to acute perturbations like antibiotic treatment, although we know little about the mechanism of impairment and the specific host consequences of prolonged post-antibiotic dysbiosis. Here, we characterize the trajectory by which the gut microbiome recovers its taxonomic and functional profile after antibiotic treatment in mice on regular chow (RC) and WD, and find that only mice on RC undergo a rapid successional process of recovery. Metabolic modeling indicates that RC diet promotes the development of syntrophic cross-feeding interactions, while on WD, a dominant taxon monopolizes readily available resources without releasing syntrophic byproducts. Intervention experiments reveal that an appropriate dietary resource environment is both necessary and sufficient for rapid and robust microbiome recovery, whereas microbial transplant is neither. Furthermore, prolonged post-antibiotic dysbiosis in mice on WD renders them susceptible to infection by the intestinal pathogen Salmonella enterica serovar Typhimurium. Our data challenge widespread enthusiasm for fecal microbiota transplant (FMT) as a strategy to address dysbiosis and demonstrate that specific dietary interventions are, at minimum, an essential prerequisite for effective FMT, and may afford a safer, more natural, and less invasive alternative to FMT.
Enhanced Sampling Simulations of RNA-peptide Binding using Deep Learning Collective Variables
Authors: Kumari Nisha , Dhull Sonam , Karmakar Tarak
Published: August 2024

Enhanced sampling (ES) simulations of biomolecular recognition such as binding of small molecules to proteins and nucleic acids targets, protein-protein association, and protein-nucleic acids interactions have been gaining significant attention in the simulation community due to their ability to sample long timescale processes. However, a key challenge in implementing collective variable (CV)-based enhanced sampling methods is the selection of appropriate CVs that can distinguish the system’s metastable states and, when biased, can effectively sample these states. This challenge is particularly acute when simulating the binding of a flexible molecule to a conformationally rich host molecule, such as the binding of a peptide to an RNA. In such cases, a large number of CVs are required to capture the conformations of both the host and the guest, as well as the binding process. In our work, we employed the recently developed Deep Targeted Discrimination Analysis (DeepTDA) method to design CVs for the study of the binding of a cyclic peptide, L22 to a TAR RNA of HIV as a prototypical system. These CVs were used in the on-the-fly probability-based enhanced sampling and well-tempered metadynamics simulations to sample reversible binding and unbinding of L22 peptide to the TAR RNA target. The enhanced sampling simulations revealed multiple binding and unbinding events, which enabled the calculation of the free energy surface for the peptide binding process. Our results demonstrate the potential of the DeepTDA method for designing CVs to study complex biomolecular recognition processes.
Optogenetic Stimulation of Nociceptive Escape Behaviors inDrosophilaLarvae
Authors: Mauthner Stephanie E. , Tracey W. Daniel
Published: August 2024

In animals, noxious stimuli activate a neural process called nociception.Drosophilalarvae perform a rolling escape locomotion behavior in response to nociceptive sensory stimuli. Noxious mechanical, thermal, and chemical stimuli each trigger this same escape response in larvae. The polymodal sensory neurons that initiate the rolling response have been identified based on the expression patterns of genes that are known to be required for nociception responses. The synaptic output of these neurons, known as class IV multidendritic sensory neurons, is required for behavioral responses to thermal, mechanical, and chemical triggers of the rolling escape locomotion. Importantly, optogenetic stimulation of the class IV multidendritic neurons has also shown that the activation of those cells is sufficient to trigger nociceptive rolling. Optogenetics uses light-activated ion channels expressed in neurons of interest to bypass the normal physiological transduction machinery so that the cell may be activated in response to light that is applied by the investigator. This protocol describes an optogenetic technique that uses channelrhodopsin-2 (ChR2) to activate larval nociceptors and trigger nociceptive rolling. First, we explain how to set up the necessary genetic crosses and culture the larval progeny. Next, we describe how to perform the optogenetic nociception assay on third-instar larvae.
Nociception inDrosophilaLarvae
Authors: Borjon Lydia J. , Mauthner Stephanie E. , Tracey W. Daniel
Published: August 2024

Nociception is the sensory modality by which animals sense stimuli associated with injury or potential tissue damage. WhenDrosophilalarvae encounter a noxious thermal, chemical, or mechanical stimulus, they perform a stereotyped rolling behavior. These noxious stimuli are detected by polymodal nociceptor neurons that tile the larval epidermis. Although several types of sensory neurons feed into the nociceptive behavioral output, the highly branched class IV multidendritic arborization neurons are the most critical. At the molecular level,Drosophilanociception shares many conserved features with vertebrate nociception, making it a useful organism for medically relevant research in this area. Here, we review three larval assays for nociceptive behavior using mechanical stimuli, optogenetic activation, and the naturalistic stimuli of parasitoid wasp attacks. Together, the assays described have been successfully used by many laboratories in studies of the molecular, cellular, and circuit mechanisms of nociception. In addition, the simple nature of the assays we describe can be useful in teaching laboratories for undergraduate students.
Competition of long-range interactions and noise at a ramped quench dynamical quantum phase transition: The case of the long-range pairing Kitaev chain
Authors: Baghran R. , Jafari R. , Langari A.
Published: August 2024

The nonequilibrium dynamics of long-range pairing Kitaev model with noiseless/noisy linear time dependent chemical potential, is investigated in the framework of dynamical quantum phase transitions (DQPTs). We have shown that for the ramp crossing a single quantum critical point, while the short-range pairing Kitaev model displays a single critical time scale, the long-range pairing induces a region with three DQPTs time scales. We have found that the region with three DQPTs time scales shrinks in the presence of the noise. In addition, we have uncovered that for a quench crossing two critical points, the critical sweep velocity above which the DQPTs disappear enhances by the long-range pairing exponent while decreases in the presence of the noise. On the basis of numerical simulations, we have shown that noise diminishes the long-range pairing inductions.

Published by the American Physical Society
2024
Can digital transformation improve sustainable performance of manufacturing firms? Empirical evidence based on core technology capabilities
Authors: Xi Xi , Yang Jing , Wang Ce
Published: August 2024

Purpose

The purpose of this study is to solve the problem that existing researches ignore the long-term and staged nature of digital transformation, failing to conduct specific discussions for different stages. It responded the call by constructing a three-stage evolutionary model to analyze the impact of digital transformation at different stages on the sustainable performance of manufacturing enterprises. The moderating effect of core technology capabilities is also explored, guided by the theory of assimilation innovation.

Design/methodology/approach

Based on the panel data of Chinese listed manufacturing companies from 2012 to 2020, this study empirically investigate the impact of digital transformation (digital process, digital operation and digital ecology) on sustainability performance (economic performance and environmental performance).

Findings

The findings indicate that digital operations and digital ecology significantly improve economic performance and environmental performance. Furthermore, the core technological capacity of the enterprise serves to modify the positive correlation between digital transformation at each stage and sustainable performance to some extent. In other words, when an enterprise is equipped with the requisite technological capacity, the digital transformation at each stage accelerates both economic performance and environmental performance, which in turn is conducive to an improvement in the enterprise’s sustainable development performance.

Originality/value

The findings contribute to the theoretical framework of digital transformation and sustainable development in all stages of enterprises. Furthermore, they provide guidance for achieving sustainable development through the implementation of digital transformation and the enhancement of core technological capacity.
Short-term study abroad (STSA): a review of key risks and challenges
Authors: Bradly Andrew , Iskhakova Marina , Ott Dana L.
Published: August 2024

Purpose

The purpose of this paper is to provide a comprehensive overview of the key risks and challenges of Short-Term Study Abroad (STSA), so higher education practitioners and global mobility providers can design effective and safe STSA programmes. The Institute of International Education defines STSA as programmes of up to eight weeks in length, with this standard now widely accepted by both practitioners and scholars (Iskhakova and Bradly, 2022).

Design/methodology/approach

This study draws from a comprehensive review of STSA risks literature, cases of published “incidents”, “safety practices”, “risk lists” and examples by global mobility professionals. The paper also draws upon the extensive practical experiences that the authors have acquired through their management of risks while delivering numerous STSA international business programmes for undergraduate students across seven different global destinations (India, USA, UAE, Russia, Croatia, Slovenia and Vietnam).

Findings

Through the analysis, the authors identify 42 types of risks and challenges that may be encountered in the delivery of STSA programmes that we group into 12 categories.

Practical implications

The results serve as an effective guide for planning, designing and delivering effective and safe STSA programmes for global mobility practitioners worldwide. The authors also provide an agenda and specific directions for future research on the topic to global mobility scholars.

Originality/value

For those designing STSA programmes, an in-depth understanding of the nature and range of risks during study tours is needed, including how to ensure in-country experiences are safe for all participants while achieving the intended learning outcomes.
I can’t get satisfaction: examining the moderating role of service brand authenticity in the relationship of imperfect experiences and satisfaction
Authors: Anninou Ioanna , Stavraki Georgia , Floh Arne
Published: August 2024

Purpose

This study aims to examine the moderating role of dimensions of brand authenticity (continuity, credibility, integrity and symbolism) in the relationship between evaluations of imperfect experiences and satisfaction within a service experience context. Building on prior research arguing for the subjective evaluation of service experiences as well as for the use of signals during dynamic experiences that build a shield to protect a brand, it assumes that service experiences range across a continuum of experiential perfection/imperfection.

Design/methodology/approach

Two Web-based surveys, one pilot (N = 231) and one main (N = 349) have been conducted. The survey methodology was complemented by a (moderated) structural equation modelling approach taken for the data analysis.

Findings

The findings indicate that imperfect experiences in a restaurant context have a negative influence on satisfaction. Brand continuity, credibility, integrity and symbolism authenticity weaken the negative relationship between imperfect experiences and satisfaction, but this effect seems to depend on the type of experiential imperfections.

Originality/value

The current study provides theoretical and preliminary empirical evidence explaining how dynamic interactions with customers can impact subsequent static experiences. The authors found that the strength of the relationship between imperfect experiential elements and satisfaction does not only depend on perceived brand authenticity and does not always weaken when brand authenticity is present.
Unlocking resilience: the impact of Industry 4.0 technologies on manufacturing firms' response to the COVID-19 pandemic
Authors: Madrid-Guijarro Antonia , Maldonado-Guzmán Gonzalo , Rodríguez-González Rubén
Published: August 2024

Purpose

This research investigates the impact of Industry 4.0 technologies (I4.0) on the resilience of manufacturing firms against the COVID-19 pandemic. The study explores the mediating effects linked to the firm’s supply chain resilience and absorptive capacity in this relationship.

Design/methodology/approach

The empirical analysis involves 304 manufacturing firms and uses Partial Least Squares Structural Equation Modeling (PLS-SEM). A two-step hierarchical component model has been employed, considering the statistical analysis validation (reliability and validity) of the LOC and HOC models. The choice of the manufacturing industry is justified due to its degree of automation in emerging economies, such as Mexico, and its significant impact on job creation and the national gross domestic product.

Findings

The results confirm the positive impact of I4.0 technologies on companies’ resilience to COVID-19. They also support the indirect effects of the firm’s supply chain resilience and absorptive capacity. Absorptive capacity was found to have a higher significant indirect effect than supply chain resilience. Consequently, the study accentuates the significance of leveraging external knowledge and highlights the role of acquisition, assimilation, transformation, and exploitation capabilities in enhancing absorptive capacity.

Research limitations/implications

The implications of this research extend to both manufacturing companies and public administrations, suggesting the need for I4.0 technologies implementation and supportive policies aimed at fostering absorptive capacity.

Originality/value

This research contributes to the literature by filling gaps in empirical studies in the context of developing economies. It provides valuable insights into the effects of I4.0 on absorptive capacity, supply chain resilience, and COVID-19 resilience, particularly in non-essential supply chains. It enriches the understanding of how I4.0 impacts the absorptive capacity and resilience of the supply chain during the COVID-19 crisis.
How big data analytics and artificial intelligence facilitate digital supply chain transformation: the role of integration and agility
Authors: Ma Lina , Chang Ruijie
Published: August 2024

Purpose

Under the digital wave and the new industrial competition pattern, the automobile industry is facing multiple challenges such as the redefinition of new technologies and supply chain changes. The purpose of this study is to link big data analytics and artificial intelligence (BDA-AI) with digital supply chain transformation (DSCT) by taking Chinese automobile industry firms as a sample and to consider the role of supply chain internal integration (SCII), supply chain external integration (SCEI) and supply chain agility (SCA) between them.

Design/methodology/approach

Data were collected from 192 Chinese firms in the automotive industry and analyzed using partial least squares structural equation modeling (PLS-SEM). Importance-performance map analysis is used to extend the standard results reporting of path coefficient estimates in PLS-SEM.

Findings

The results indicate that BDA-AI, SCII, SCEI and SCA positively influence DSCT. In addition, this study found that SCII, SCEI and SCA play an intermediary role in BDA-AI and DSCT.

Originality/value

The paper enriches the research on the mechanism of digital resources affecting DSCT and expands the research of organizational information processing theory in the context of digital transformation. The paper explores how the resources deployed by firms change the strategic measures of firms from the perspective of responsiveness. By exploring the positive impact of SCA as a response capability on the DSCT strategy and its intermediary role between digital resources and DSCT, which is helpful to the further theoretical development of logistics and supply chain disciplines.
The impact of market competitors on the demand for reinsurance
Authors: Chang Vincent Y.L.
Published: August 2024

Purpose

According to the market competition theory, a firm’s decision-making is influenced by the behaviors or strategies of its competitors. The repercussions of competition include market-stealing and spillover effects. Relatively few studies in the reinsurance literature discuss the effect of competitors on an insurer’s decision-making. This study aims to fill a gap in the reinsurance literature by comparing insurers' reinsurance demand to their competitors' reinsurance purchases.

Design/methodology/approach

This study uses unbalanced panel data for the US property-liability insurance industry from 2006 to 2017 to determine the impact of competitors' reinsurance purchases on insurers' reinsurance demand. This study employs the Mixed Effect Model and the Quantile Regression to test the proposed hypotheses.

Findings

The evidence suggests that the affiliated reinsurance purchases of competitors have a positive and substantial effect on the affiliated reinsurance demand of insurers, crediting mimicking the reinsurance strategy. Interestingly, the market-stealing effect is supported while the non-affiliated reinsurance metric is used. Remarkably, given insurers with low non-affiliated reinsurance purchases, the finding sustains the mimicking reinsurance strategy. Nevertheless, the market-stealing effect remains a concern for insurers with a high non-affiliated reinsurance purchase.

Originality/value

The new findings concerning competitor effects analysis fill a void in the reinsurance literature. Risk diversification, capital substitution, and real services demand may play a crucial role in determining the market-stealing effect, leading to a decrease in market share. Insurers can mitigate the market-stealing effect of competitors by accessing expertise and capital substitution through non-affiliated reinsurance purchases.
Predictive digital twin technologies for achieving net zero carbon emissions: a critical review and future research agenda
Authors: Elghaish Faris , Matarneh Sandra , Hosseini M. Reza , Tezel Algan , Mahamadu Abdul-Majeed , Taghikhah Firouzeh
Published: August 2024

Purpose

Predictive digital twin technology, which amalgamates digital twins (DT), the internet of Things (IoT) and artificial intelligence (AI) for data collection, simulation and predictive purposes, has demonstrated its effectiveness across a wide array of industries. Nonetheless, there is a conspicuous lack of comprehensive research in the built environment domain. This study endeavours to fill this void by exploring and analysing the capabilities of individual technologies to better understand and develop successful integration use cases.

Design/methodology/approach

This study uses a mixed literature review approach, which involves using bibliometric techniques as well as thematic and critical assessments of 137 relevant academic papers. Three separate lists were created using the Scopus database, covering AI and IoT, as well as DT, since AI and IoT are crucial in creating predictive DT. Clear criteria were applied to create the three lists, including limiting the results to only Q1 journals and English publications from 2019 to 2023, in order to include the most recent and highest quality publications. The collected data for the three technologies was analysed using the bibliometric package in R Studio.

Findings

Findings reveal asymmetric attention to various components of the predictive digital twin’s system. There is a relatively greater body of research on IoT and DT, representing 43 and 47%, respectively. In contrast, direct research on the use of AI for net-zero solutions constitutes only 10%. Similarly, the findings underscore the necessity of integrating these three technologies to develop predictive digital twin solutions for carbon emission prediction.

Practical implications

The results indicate that there is a clear need for more case studies investigating the use of large-scale IoT networks to collect carbon data from buildings and construction sites. Furthermore, the development of advanced and precise AI models is imperative for predicting the production of renewable energy sources and the demand for housing.

Originality/value

This paper makes a significant contribution to the field by providing a strong theoretical foundation. It also serves as a catalyst for future research within this domain. For practitioners and policymakers, this paper offers a reliable point of reference.
Soil nitrogen regulates root carbon secretion in the context of global change: A global meta‐analysis
Authors: Zeng Jia , Li Xiangyang , Xing Liheng , Chen Ling , Li Yu , Wang Xing , Zhang Qi , Yang Gang , Ren Chengjie , Yang Gaihe , Han Xinhui
Published: August 2024

The secretion of root exudates plays a crucial regulatory role in the process of soil carbon cycling. It is also significantly affected by global change factors (GCFs), yet the general patterns of these changes have not been fully explored, which greatly limits the accurate establishment of carbon cycling models under the background of global change.

To address this, we conducted a meta‐analysis that included 1926 data pairs to examine the effects of global variability on root exudates. Furthermore, we performed multi‐model inference using Akaike's information criterion (AIC) to assess the relative importance of multiple factors such as annual average temperature (AAT), type of ecosystem, intensity of treatment, duration and more.

The findings revealed that GCFs generally improved the production of root exudates. While the addition of nitrogen and its interaction with increased temperature significantly reduced the rate of root carbon secretion, all other factors significantly promoted it. Interestingly, as the intensity of warming increased, the rate of root carbon secretion caused by warming displayed a downward trend, with a threshold of 3.6°C. Furthermore, the influence of GCFs on root carbon secretion was found to be regulated by soil nitrogen, confirming the importance of nutrients from the rhizosphere in this process.

These results underscore the importance of GCFs in root exudates and emphasize the crucial role of soil total nitrogen in the regulation of root carbon secretion. They also provide valuable scientific parameters for the development of more accurate models for the global‐change carbon cycle.

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Unravelling arthropod movement in natural landscapes: Small‐scale effects of body size and weather conditions
Authors: Logghe Garben , Taelman Charlotte , Van Hecke Florian , Batsleer Femke , Maes Dirk , Bonte Dries
Published: August 2024

Arthropod movement has been noticeably understudied compared to vertebrates. A crucial knowledge gap pertains to the factors influencing arthropod movement at habitat boundaries, which has direct implications for population dynamics and gene flow. While larger arthropod species generally achieve greater dispersal distances and large‐scale movements are affected by weather conditions, the applicability of these relationships at a local scale remains uncertain. Existing studies on this subject are not only scarce but often limited to a few species or laboratory conditions.

To address this knowledge gap, we conducted a field study in two nature reserves in Belgium, focusing on both flying and cursorial (non‐flying) arthropods. Over 200 different arthropod species were captured and released within a circular setup placed in a resource‐poor environment, allowing quantification of movement speed and direction. By analysing the relationship between these movement variables and morphological (body size) as well as environmental factors (temperature and wind), we aimed to gain insights into the mechanisms driving arthropod movement at natural habitat boundaries.

For flying species, movement speed was positively correlated with both body size and tailwind speed. In contrast, movement speed of cursorial individuals was solely positively related with temperature. Notably, movement direction was biased towards the vegetated areas where the arthropods were originally caught, suggesting an internal drive to move towards suitable habitat. This tendency was particularly strong in larger flying individuals and under tailwind conditions. Furthermore, both flying and cursorial taxa were hindered from moving towards the habitat by strong upwind.

In conclusion, movement speed and direction at patch boundaries are dependent on body size and prevailing weather conditions, and reflect an active decision‐making process.
Bioplastics in the basket of Italians: A hybrid framework for understanding the adoption of bioplastic food packaging
Authors: Califano Giovanbattista , Lombardi Alessia , Del Giudice Teresa , Caracciolo Francesco , Cembalo Luigi
Published: August 2024

This study provides a comprehensive understanding of the factors influencing Italian consumers' choice of biodegradable and compostable packaging by using a hybrid framework that integrates the theory of planned behaviour with a discrete choice experiment. By analysing the interplay between internal and external factors and rational consumer evaluations, the research clarifies that consumers' choices can be explained by a combination of economic and psychological models, offering a more accurate representation of the driving forces behind consumer decisions. Applying latent class analysis, we identify consumer segments based on packaging preferences for packaged salad, knowledge of waste disposal rules and the psychological characteristics of a statistically representative sample of Italian consumers. The integration of a comprehensive behavioural model allows for the identification of psychological determinants that influence consumer behaviour, outlining detailed profiles of both early adopters and those most opposed to this technology. This research contributes to the literature on sustainable packaging and offers insights to marketers and policymakers for promoting the adoption of sustainable packaging.
The agency of a marmalade machine: Gender, class and mechanical gadgets in the British Kitchen, c.1870–1938
Authors: Carpenter Katie
Published: August 2024

This article explores the marmalade machine, a mechanical device designed to slice orange peel. These niche objects were manufactured between roughly 1870 and 1938 in Britain. As a so‐called ‘labour‐saving’ gadget, the marmalade machine sliced orange peel quickly and effectively, removing the tedious process of slicing orange peel by hand. However, like many labour‐saving technologies, it also required an extended skillset from the housewife, by necessitating a mechanical and intellectual engagement from the user. Drawing on an eclectic range of source material, including physical examination of the machines, this article argues that the marmalade machine possessed agency through its affordances.
Clustering and unconstrained ordination with Dirichlet process mixture models
Authors: Stratton Christian , Hoegh Andrew , Rodhouse Thomas J. , Green Jennifer L. , Banner Katharine M. , Irvine Kathryn M.
Published: August 2024

Assessment of similarity in species composition or abundance across sampled locations is a common goal in multi‐species monitoring programs. Existing ordination techniques provide a framework for clustering sample locations based on species composition by projecting high‐dimensional community data into a low‐dimensional, latent ecological gradient representing species composition. However, these techniques require specification of the number of distinct ecological communities present in the latent space, which can be difficult to determine in advance.

We develop an ordination model capable of simultaneous clustering and ordination that allows for estimation of the number of clusters present in the latent ecological gradient. This model draws latent coordinates for each sample location from a Dirichlet process mixture model, affording researchers with probabilistic statements about the number of clusters present in the latent ecological gradient.

The model is compared to existing methods for simultaneous clustering and ordination via simulation and applied to two empirical datasets; JAGS code to fit the proposed model is provided in an appendix. The first dataset concerns presence‐absence records of fish in the Doubs river in eastern France and the second dataset describes presence‐absence records of plant species in Craters of the Moon National Monument and Preserve (CRMO) in Idaho, USA. Results from both analyses align with existing ecological gradients at each location.

Development of the Dirichlet process ordination model provides wildlife managers with data‐driven inferences about the number of distinct communities present across monitored locations, allowing for more cost‐effective monitoring and reliable decision‐making for conservation management.
Proton pump inhibitor effect on esophageal protein signature of eosinophilic esophagitis, prediction, and evaluation of treatment response
Authors: Molina‐Jiménez Francisca , Ugalde‐Triviño Lola , Arias‐González Laura , Armenteros Elisa , Relaño‐Rupérez Carlos , Casabona Sergio , Moreno‐Monteagudo José Andrés , Pérez‐Fernández María Teresa , Martín‐Domínguez Verónica , Fernández‐Pacheco Jennifer , Laserna‐Mendieta Emilio José , Muñoz‐Hernández Patricia , García‐Martínez Jorge , Muñoz Javier , Lucendo Alfredo J. , Santander Cecilio , Majano Pedro
Published: August 2024

Background

Recently, we have identified a dysregulated protein signature in the esophageal epithelium of eosinophilic esophagitis (EoE) patients including proteins associated with inflammation and epithelial barrier function; however, the effect of proton pump inhibitor (PPI) treatment on this signature is unknown. Herein, we used a proteomic approach to investigate: (1) whether PPI treatment alters the esophageal epithelium protein profile observed in EoE patients and (2) whether the protein signature at baseline predicts PPI response.

Methods

We evaluated the protein signature of esophageal biopsies using a cohort of adult EoE (n = 25) patients and healthy controls (C) (n = 10). In EoE patients, esophageal biopsies were taken before (pre) and after (post) an 8‐week PPI treatment, determining the histologic response. Eosinophil count PostPPI was used to classify the patients: ≥15 eosinophils/hpf as non‐responders (non‐responder) and < 15 eosinophils/hpf as responders (R). Protein signature was determined and differentially accumulated proteins were characterized to identify altered biological processes and signaling pathways.

Results

Comparative analysis of differentially accumulated proteins between groups revealed common signatures between three groups of patients with inflammation (responder‐PrePPI, non‐responder‐PrePPI, and non‐responder‐PostPPI) and without inflammation (controls and responder‐PostPPI). PPI therapy almost reversed the EoE specific esophageal protein signature, which is enriched in pathways associated with inflammation and epithelial barrier function, in responder‐PostPPI. Furthermore, we identified a set of candidate proteins to differentiate responder‐PrePPI and non‐responder‐PrePPI EoE patients before treatment.

Conclusion

These findings provide evidence that PPI therapy reverses the alterations in esophageal inflammatory and epithelial proteins characterizing EoE, thereby providing new insights into the mechanism of PPI clinical response. Interestingly, our results also suggest that PPI response could be predicted at baseline in EoE.