bluuebunny/crossref_metadata_2025 huggingface dataset:
Bayesian inference by visuomotor neurons in prefrontal cortex
Authors: Langlois Thomas , Charlton Julie A. , Goris Robbe L. T.
Published: September 2024

Perceptual judgements of the environment emerge from the concerted activity of neural populations in decision-making areas downstream of sensory cortex [1, 2, 3]. When the sensory input is ambiguous, perceptual judgements can be biased by prior expectations shaped by environmental regularities [4, 5, 6, 7, 8, 9, 10, 11]. These effects are examples of Bayesian inference, a reasoning method in which prior knowledge is leveraged to optimize uncertain decisions [12, 13]. However, it is not known how decision-making circuits combine sensory signals and prior expectations to form a perceptual decision. Here, we study neural population activity in the prefrontal cortex of macaque monkeys trained to report perceptual judgments of ambiguous visual stimuli under two different stimulus distributions. We analyze the component of the neural population response that represents the formation of the perceptual decision (the decision variable, DV), and find that its dynamical evolution reflects the integration of sensory signals and prior expectations. Prior expectations impact the DV’s trajectory both before and during stimulus presentation such that DV trajectories with a smaller dynamic range result in more biased and less sensitive perceptual decisions. These results reveal a mechanism by which prefrontal circuits can execute Bayesian inference.
Deconvolving organogenesis in space and time via spatial transcriptomics in thick tissues
Authors: Asami Soichiro , Yin Chenshuo , Garza Luis A. , Kalhor Reza
Published: September 2024

Organ development is guided by a space-time landscape that constraints cell behavior. This landscape is challenging to characterize for the hair follicle – the most abundant mini organ – due to its complex microscopic structure and asynchronous development. We developed 3DEEP, a tissue clearing and spatial transcriptomic strategy for characterizing tissue blocks up to 400 µm in thickness. We captured 371 hair follicles at different stages of organogenesis in 1 mm3of skin of a 12-hour-old mouse with 6 million transcripts from 81 genes. From this single time point, we deconvoluted follicles by age based on whole-organ molecular pseudotimes to animate a stop-motion 3D atlas of follicle development along its trajectory. We defined molecular stages for hair follicle organogenesis and characterized the order of emergence for its structures, differential signaling dynamics at its top and bottom, morphogen shifts preceding and accompanying structural changes, and series of structural changes leading to the formation of its canal and opening. We further found that hair follicle stem cells and their niche are established and stratified early in organogenesis, before the formation of the hair bulb. Overall, this work demonstrates the power of increased depth of spatial transcriptomics to provide a four-dimensional analysis of organogenesis.
Optimization of H9c2 differentiation leads to calcium-active and striated cardiac cells without addition of retinoic acid
Authors: Brock Judith , Hörning Marcel
Published: September 2024

As a reliable alternative to animal testing in cardiovascular research, it is crucial to improve differentiation of immortalized cell lines. In this study, we focused on optimizing the differentiation efficiency of the H9c2 cell line into cardiomyocytes using a high-throughput, automated image processing approach. While previous studies used protocols involving retinoic acid to enhance cardiac differentiation, we applied a simplified medium composition that results in higher differentiation rates. Along that line, we differentiated H9c2 cells into cardiomyocytes, which not only showed sarcomere-characteristic striation but also periodic intracellular calcium signaling for the first time. As a second step, we examined the potential application of polyacrylamide hydrogels (E = 12 kPa) with defined fibronectin coating densities. The optimum fibronectin density of 2.6 µg/cm2found for single cells was investigated to further improve the differentiation efficiency. However, the differentiation and proliferation dynamics dominate the adhesion forces between the cells and the hydrogel, and thus, result in premature clustering and detachment. In conclusion, we identified an optimized differentiation protocol and provided a basis for the further investigation necessary to potentially use hydrogels as natural cell environment, aiming to raise the differentiation efficiency even more.
Embodied processing in whisker somatosensory cortex during exploratory behaviour in freely moving mice
Authors: Gantar Luka , Burgess Matthew A. , Mansour Neveen , Rusco-Portabella Joaquín , Námešná Alžbeta , Gill David , Harris Isabella , Orlowska-Feuer Patrycja , Ebrahimi Aghileh S. , Storchi Riccardo , Petersen Rasmus S.
Published: September 2024

Sensory systems have evolved to solve computational challenges that animals face during behaviour in their natural environments. To illuminate how sensory cortex operates under such conditions, we investigated the function of neurons in whisker-related Somatosensory Cortex (wS1) of freely moving mice, engaged in tactile exploratory behaviour. By recording neural activity from wS1 whilst tracking the mouse body in 3D, we found that wS1 neurons are substantially modulated by body state (configuration of individual body-parts and their derivatives), even in the absence of whisker afferent input. Most neurons were modulated by multiple dimensions of body state, with the most prominently encoded being the angle of the head to the body and locomotion speed. Overall, our data suggest that sensory cortex functions as an embodied representation, which integrates signals from its associated sense organ within a body schema.
Machine learning based crystal collimator alignment optimization
Authors: Ricci Gianmarco , D’Andrea Marco , Di Castro Mario , Matheson Eloise , Mirarchi Daniele , Mostacci Andrea , Redaelli Stefano
Published: September 2024

In the CERN Large Hadron Collider (LHC), bent crystals are used to efficiently deflect beam halo particles toward secondary collimators used as absorbers. In this crystal collimation scheme, a crystal with a length of a few millimeters can produce a deflection equivalent to a magnetic field of hundreds of Tesla at LHC top energies, improving the cleaning performance of the machine. However, crystals must be in optimal alignment with respect to the circulating beam to maximize the efficiency of the channeling process. A newly developed machine learning model automatically classifies the channeling condition of crystals using beam loss monitor signals during slow rotation of the crystal. This advancement represents a crucial step toward refining the process of identifying the optimal channeling orientation. The algorithm has been tested for the fist time in operation with Pb ion beams at the record energy of 6.8 Z TeV demonstrating its reliability.

Published by the American Physical Society
2024
Temperature dependence of the AB lines and optical properties of the carbon–antisite-vacancy pair in
4H−SiC
Authors: Bulancea-Lindvall Oscar , Davidsson Joel , Ivanov Ivan G. , Gali Adam , Ivády Viktor , Armiento Rickard , Abrikosov Igor A.
Published: September 2024

Defects in semiconductors have in recent years been revealed to have interesting properties in the venture towards quantum technologies. In this regard, silicon carbide has shown great promise as a host for quantum defects. In particular, the ultrabright AB photoluminescence lines in 4H−SiC are observable at room temperature and have been proposed as a single-photon quantum emitter. These lines have previously been studied and assigned to the carbon–antisite-vacancy (CAV) pair. In this paper, we report on new measurements of the AB lines’ temperature dependence, and carry out an in-depth computational study on the optical properties of the CAV defect. We find that the CAV defect has the potential to exhibit several different zero-phonon luminescences with emissions in the near-infrared telecom band, in its neutral and positive charge states. However, our measurements show that the AB lines only consist of three nonthermally activated lines instead of the previously reported four lines; meanwhile, our calculations on the CAV defect are unable to find optical transitions in full agreement with the AB-line assignment. In light of our results, the identification of AB lines and the associated room-temperature emission require further study.

Published by the American Physical Society
2024
Beyond the classroom: the evolving spectrum of ESD research in Japan
Authors: Ohira Yuko
Published: September 2024

Purpose

Education for Sustainable Development (ESD) has been robustly endorsed through policy mechanisms, prompting numerous context-specific voluntary initiatives in Japanese schools and communities. However, this field remains in its infancy. This study aimed to investigate the literature on ESD in Japan to reveal research trends, identify research gaps and propose areas for future research, from early childhood to higher and non-formal education.

Design/methodology/approach

This study employed a qualitative design with a Systematic Literature Review (SLR) approach to analyze 88 peer-reviewed empirical studies on ESD in Japan from 2005 to 2023.

Findings

This study has revealed an observable increase in the number of ESD-related publications, especially after 2015. Most studies emphasize formal education, particularly from elementary school to universities. These articles were categorized into seven thematic foci, with “Pedagogical Approaches and Material Development in ESD” being the most prevalent. There has been an evident shift in Japan from traditional lecture-style methods toward learner-centered ESD pedagogies. However, the country lags behind the global education community in terms of research on and the implementation of Teacher Education for Sustainable Development and the Whole-School Approach.

Research limitations/implications

The study is confined to peer-reviewed, empirical publications in Japanese or English, potentially overlooking significant non-empirical works and studies in other languages. This limitation could mean missing out on broader insights and perspectives. Furthermore, as a qualitative analysis, there's an inherent risk of bias in interpreting data and categorizing themes. These constraints suggest caution in generalizing the findings and indicate areas for further research, such as expanding the linguistic and methodological scope and enhancing objectivity in analysis.

Practical implications

The findings suggest a pressing need for Japan to refine its approach to ESD, particularly in teacher training and school management, aligning more closely with global practices. For practical application, this involves adopting more holistic teacher education programs and school management strategies that integrate ESD principles comprehensively. Recognizing the unique challenges of Japan's educational culture is crucial for developing tailored strategies that not only follow global best practices but also resonate locally. These insights aim to guide meaningful interventions, promoting an education system adept at addressing sustainability challenges.

Originality/value

Categorizing the literature into formal and non-formal settings and subsequently into seven themes offers a clear depiction of the research trends. A comparison of Japan's specific advancements and challenges in ESD with global trends, particularly in pedagogy, teacher education and institutional management, highlights the areas needing further exploration.
Local government debt and firm’s outward foreign direct investment
Authors: Wang Zifeng , Ning Zhiyuan , Wu Fei
Published: September 2024

Purpose

The purpose of this study is to provide evidence that government financing behavior has an impact on the outward foreign direct investment (OFDI) of enterprises.

Design/methodology/approach

This paper uses debt data from local government financing vehicles to measure the local government debt in China. Based on the data of listed manufacturing firms in China from 2010 to 2018, this paper uses the Tobit model to verify the impact of local government debt and firms' OFDI.

Findings

The results indicate that local government debt impedes firms' OFDI, with a more pronounced impact on state-owned enterprises (SOEs) and those with higher political connections. Furthermore, our study suggests that the dampening effect of local governments on firms' OFDI is mitigated in regions following the implementation of the Local Government Debt Management Act.

Originality/value

This study verifies the negative impact of local government debt activity on firms' overseas investments. This is not due to debt crowding out, but rather to the fact that local governments prefer to keep resources locally to stimulate the economy. This paper offers novel insights into the theoretical mechanisms by which local government behavior influences firms' investment activities in emerging markets.
Effect of macro- and micro-morphology on fluid film properties based on plasto-elastohydrodynamic lubrication
Authors: Wang Tianci , Lu Yan , Zhang Hao , Liu Jianxi , Zheng Yunfei , Tu Fuquan
Published: September 2024

Purpose

The developed plasto-elastohydrodynamic lubrication (PEHL) model is used to demonstrate the permanent change of macro morphology by critical high local stress at micro asperities in contact, which may further affect the fluid-film characteristics.

Design/methodology/approach

Geometric morphology is integrated into the PEHL model to elucidate the fluid-film properties governed by both macro- and micromorphologies.

Findings

Results show the model, accounting for combination of elastic and plastic deformations, realistically reveals fluid film distribution affected by the significant pressure highly concentrated within surface micro roughness interaction. The designed macroscopic textured surface mitigates the fluid film rupture phenomenon and prevents accumulated wear degradation from plastic deformation.

Originality/value

The PEHL model takes into account both elastic and plastic deformations and realistically reveals the fluid film distribution affected by large pressures that are highly concentrated in surface micro-roughness interactions. The macro-textured surfaces are designed to mitigate fluid film rupture phenomena and prevent cumulative wear caused by plastic deformation.

Peer review

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-05-2024-0170/
The roles of key suppliers in network formation when reshoring
Authors: Baraldi Enrico , Ciabuschi Francesco , Fratocchi Luciano , Pedroletti Daniel , Picciotti Antonio
Published: September 2024

Purpose

Reshoring implies the reconfiguration of supply networks. Focusing on the specific case of a born-offshored firm that engaged in reshoring of outsourced activities, this study aims to analyse how initial key suppliers in the home country can help the reshoring firm to organize a new supply network.

Design/methodology/approach

The research is qualitative and based on a single exploratory case study. The data was collected from multiple primary and secondary sources, and using different techniques, such as in-depth interviews, direct observation and network pictures.

Findings

The study provides insights on how an initial key supplier can enable its customers’ reshoring in the home country. Specifically, the authors identify 10 roles played by a key supplier. The results also identify supply network formation as an essential component of the reshoring process.

Originality/value

This paper provides unique contributions. Firstly, it presents the specific and under-explored case of a born-offshored firm engaged in outsourced reshoring; secondly, it sheds light on the roles that key suppliers may play for the reshoring process; thirdly, it explores the formation of business relationships in the context of reshoring. In essence, the paper contributes to the reshoring literature, by stressing the importance of supply network formation in the reshoring process and by identifying the multiplicity of roles that key suppliers can play when implementing reshoring, and to the industrial marketing and purchasing (IMP) literature, by showing how relationships and networks develop during reshoring, a phenomenon so far understudied by IMP scholars.
Analyzing the impact of investor sentiment on S&P 500 prices using deep learning models
Authors: Khalife Danielle , Yammine Jad , El Bazi Tatiana , Zaki Chamseddine , Jabbour Al Maalouf Nada
Published: September 2024

Purpose

This study aims to investigate to what extent the predictability of the standard and poor’s 500 (S&P 500) price levels is enhanced by investors’ sentiments extracted from social media content, specifically platform X.

Design/methodology/approach

Two recurrent neural network (RNN) models are developed. The first RNN model is merely based on historical records and technical indicators. In addition to the variables included in the first RNN model, the second RNN model comprises the outputs of the sentiment analysis, performed using the TextBlob library. The study was conducted between December 28, 2011, and December 30, 2021, over 10 years, to obtain better results by feeding the RNN models with a significant quantity of data by extending the period and capturing an extensive timespan.

Findings

Comparing the performance of both models reveals that the second model, with sentiment analysis inputs, yields superior outcomes. The mean absolute error (MAE) of the second model registered 72.44, approximately 50% lower than the MAE of the technical model, its percentage value, the mean absolute percentage error, recorded 2.16%, and finally, the median absolute percentage error reached a value of 1.30%. This underscores the significant influence of digital platforms in influencing the behavior of certain assets like the S&P 500, emphasizing the relevance of sentiment analysis from social media in financial forecasting.

Originality/value

This study contributes to the growing body of literature by highlighting the enhanced predictive power of deep learning models that incorporate investor sentiment from social media, thereby advancing the application of behavioral finance in financial forecasting.
Exploring the influence of online restaurant promotions on consumer behavioral intentions
Authors: Wareebor Sukanya , Suttikun Chompoonut , Mahasuweerachai Patcharaporn
Published: September 2024

Purpose

Consumer behavior is evolving rapidly due to the increasing role of technology in daily life. Online food ordering has emerged as a key channel in this changing landscape. This paper investigates the relationships between online promotions, consumer skepticism, information sharing on social media and the intention to purchase food and beverages through online delivery services.

Design/methodology/approach

Measures were developed based on a review of existing literature. Data from 402 participants were analyzed using Structural Equation Modeling (SEM).

Findings

The study reveals that online promotions significantly impact consumers' sharing of restaurant posts. Additionally, consumer skepticism about online food sales affects both their sharing behavior and their intention to purchase online. Engagement in sharing restaurant posts online is a strong predictor of online food purchasing intentions.

Practical implications

The findings offer valuable insights for restaurant operators, policymakers and technology developers in the competitive online food delivery sector. They emphasize the importance of implementing innovative promotions and crafting appealing food presentations. These strategies can accelerate customer decision-making, attract new customers and contribute to market expansion and customer base sustainability.

Originality/value

This research provides significant insights for restaurant owners and contributes to the limited literature on online promotions, consumer skepticism and information sharing in the restaurant industry. It also lays the groundwork for future studies aimed at deepening understanding in this field.
Lifetime deals: the role of software service offering in convincing consumers
Authors: Sorkun Metehan Feridun , İdin Noyan Alperen
Published: September 2024

Purpose

This study aims to reveal consumer purchase intentions for Software-as-a-Service (SaaS) lifetime deals and the role of service offerings in shaping these intentions.

Design/methodology/approach

Lifetime deals − an aggressive market penetration strategy − have the potential to allow startups to gain market share, user base and the cash necessary for growth. However, startups need to mitigate consumer concerns for which service offering design plays a key role. Drawing on expectancy-value and signaling theories, this study developed a research model and then conducted empirical research on 2,173 consumers via choice-based conjoint analysis to reveal the critical service offering attributes for consumer utility in lifetime deals in the SaaS presentation tool market context. After using the hierarchical Bayes model to derive each respondent’s part-worth utilities for service offering attributes, the hypotheses were tested via the factor score regression method.

Findings

The results show that the service offering attributes of low price, refund option, human support and feature updates enhance consumer utility in SaaS lifetime deals. Three of these four attributes, namely, low price, refund option and feature updates, enhance consumers' purchase intentions by reducing their concerns about the service’s performance, seller and lifespan, respectively.

Originality/value

This study elucidates consumer purchase intentions for SaaS services in digital marketplaces. By investigating a widespread market entry strategy − lifetime deals − it shows consumer preferences and behavior for these deals in the fast-growing online tools market. This study also shows how startups can use lifetime deals through a well-designed service offering to mitigate various consumer concerns.
Digital health startups: growth financing and valuation drivers that signal strength for investors
Authors: Burton Kristin , Heath Michele , Luse William
Published: September 2024

Purpose

The study investigates the impact of various factors on the number of active investors in digital health startups. Through nine hypotheses, we examine the influence of metrics such as patents, online presence, financial aspects and company valuation on investor interest. The results reveal positive associations between these metrics and investor numbers, highlighting their role in signaling strength and attracting investment. This research enhances the understanding of investor valuation in digital health startups, emphasizing the importance of credible signals for building trust and securing funding. However, we acknowledge limitations in data analysis methods and suggest future research to explore industry signals, longitudinal trends and failed startups for comprehensive insights.

Design/methodology/approach

This study delves into the design methodology and approach, aiming to fill gaps in understanding investor roles in valuing digital health ventures. We focus on deciphering factors driving valuations for these startups to secure growth financing. Using signaling theory, we investigate how entrepreneurs communicate their latent strengths to bridge information gaps, aiding investment decisions. We analyze a sample of 482 healthcare startups from the Pitchbook database using Poisson regression in SPSS.

Findings

This research sheds light on the factors driving investor interest in digital health startups. Despite the critical role of entrepreneurs in patient care innovations, the relationship between investor characteristics and funding for digital health technologies still needs exploration. We examine factors influencing investor valuation in healthcare startups and identify patents, social followers and financial disclosures as pivotal elements shaping investor interest. The findings show that all factors for active investors are significant for all variables except similar unique visitors.

Originality/value

These results significantly enhance our understanding of investor decision-making in digital health startups. They confirm the importance of various signals, like patent activity, online presence and financial performance, in attracting investor attention. We utilize unique data sources, offering insights into investors' behavior across different funding stages. In conclusion, these findings underscore investors' crucial role in the growth and funding of healthcare tech startups, emphasizing the need for robust signals to attract investment.
Are library data and metadata dying or nearly dead? A discussion for everyone
Authors: Frederick Donna Ellen
Published: September 2024

Purpose

This paper aims to inform noncataloguers about the current and historical significance of both machine readable cataloguing (MARC) records and traditional cataloguing as well as introduce them to current struggles to modernize.

Design/methodology/approach

The approach of this column is to break-down what may appear to be a crisis in the modernization of library cataloguing and metadata by placing the issues in their historical context and considering existing technologies in a user-friendly manner.

Findings

MARC-based cataloguing is well-established, robust and widely used in many library applications. It is not easily replaced and attempts to do so have had very slow progress. Although change is expected in the future, it may lay with solutions based on Artificial Intelligence (AI) technologies.

Originality/value

Although there are many papers discussing the merits of traditional cataloguing and the need for new methods and standards, few are written from a nontechnical point of view and for noncataloguers or those not working in systems departments. This column's intended audience is all library workers with an emphasis on those who are not familiar with MARC.
A test of moderated serial mediation model of compulsive buying among Gen Z fandoms moderated by trash talking
Authors: Suprawan Lokweetpun , Oentoro Wanny , Suttharattanagul Sarinya L.
Published: September 2024

Purpose

The study aims to identify the factors that influence young consumers’ compulsive buying, particularly Gen Z consumers who exhibit fandom qualities such as sharing the same interests and being willing to collaborate with others. This study investigates the direct and indirect impact of brand love and brand addiction on the relationship between social media addiction and compulsive buying.

Design/methodology/approach

The study collected data from 338 Gen Z fandoms. The snowball sampling approach is used to determine and collect data from the sample. To test for hypotheses, the study used the PROCESS macro with bootstrapping techniques to explore the direct and indirect relationships, as well as the moderated serial mediation model in this study.

Findings

The study found that social media addiction influences compulsive buying via the hierarchical linkages between brand love and brand addiction. Trash talking functions as a stimulant, amplifying the effect of brand addiction on compulsive buying.

Research limitations/implications

The data were collected from young Thai consumers; thus, the generalizability aspect of the research is limited and needs to be tested in different countries and cultures.

Originality/value

This research provides several key contributions to the understanding of compulsive buying behavior among Gen Z, particularly within the context of a developing country. By integrating the stimulus-organism-response framework and psychological theories, this study offers a nuanced understanding of how social media addiction influences emotional and behavioral outcomes. Previous studies have primarily focused on these variables in isolation. The study fills this gap by demonstrating the sequential pathway through which social media addiction translates into compulsive buying behavior via brand love and brand addiction.
Tree species richness suppresses red imported fire ant invasion in a subtropical plantation forest
Authors: Wang Pengyang , Wu Donghao , Wang Yongjia , Shen Zhiqiang , Li Buhang , Shu Zufei , Chu Chengjin
Published: September 2024

The ecological resistance to the invasion of alien species has been extensively researched at the within‐trophic level; however, the effect of cross‐trophic interactions remains largely unknown. The red imported fire ant (RIFA, Solenopsis invicta) is a globally invasive species, and a cross‐trophic interaction study between RIFAs and plants may provide a more comprehensive understanding and management of its invasion.

We hypothesized that the diversity of trees, which are the primary producers supporting terrestrial ecosystems, could suppress the invasion of omnivorous RIFAs by regulating food resources (e.g. plants and arthropods) and the microenvironment (e.g. soil microclimate) as well as enhancing competition with other carnivorous ants. To test this hypothesis, we investigated RIFA abundance and mound numbers across tree species richness gradients in a subtropical plantation forest.

Using structural equation models, we discovered that tree species richness had contrasting effects on RIFA abundance and mound numbers. RIFA abundance directly decreased with higher tree species richness because of the dilution effect (i.e. lower abundance of preferred tree species). In contrast, RIFA mound numbers indirectly increased with tree species richness via an increase in arthropod abundance (excluding ants) (i.e. more ample food resources for RIFA). Moreover, warmer soil temperatures decreased RIFA abundance, whereas other carnivorous ant species richness and abundance negatively affected RIFA abundance and mound numbers.

Synthesis and applications: Our findings demonstrate that the ecological resistance to RIFA invasion is influenced by tree species richness in a complex manner; specifically, the relative strengths of the effects of tree species characteristics, native competitors and environmental conditions are likely to impact the power of ecological resistance. This highlights the importance of cross‐trophic interactions underlying the resistance of complex ecosystems to alien species invasion; therefore, maintaining diverse tree communities in controlled systems (e.g. suburban and urban green spaces) should be viewed as a potential strategy for controlling RIFA invasion.
Effects of water limitation and competition on tree carbon allocation in an Earth system modelling framework
Authors: Lichstein Jeremy W. , Zhang Tao , Weng Ensheng , Farrior Caroline E. , Dybzinski Ray , Malyshev Sergey , Shevliakova Elena , Birdsey Richard A. , Pacala Stephen W.
Published: September 2024

Earth system models (ESMs) have a limited capacity to represent plant functional diversity and shifts in trait distributions. Approaches to improving the representation of this complexity in ESMs include (i) optimality‐based approaches that predict trait–environment responses and (ii) explicitly modelling coexistence and community assembly. These approaches are expected to converge only when optimality‐based approaches identify competitively dominant strategies, which often differ from strategies that maximize ecosystem functioning or fitness components in monoculture.

We used two models, LM3‐PPA (a vegetation demographic model designed as an ESM component) and BiomeE (a computationally efficient analog for LM3‐PPA), to explore how water limitation affects carbon allocation strategies of canopy trees. We compared competitive allocation strategies and those that maximize biomass or productivity in monoculture. We did not explicitly model coexistence or community assembly. Rather, we used model experiments to identify competitive and maximizing strategies in a two‐dimensional trait space under different precipitation and mortality scenarios.

At 10 eastern US locations, we simulated historical, wet and dry climate scenarios, novel drought and three different mortality scenarios (low, medium or high sensitivity to water deficit). For each site and scenario, we identified the competitive strategy and three maximizing strategies (maximum biomass, productivity or drought‐tolerance).

Root: leaf ratios tended to increase and leaf area tended to decrease with increasing water stress (increasing water limitation and its effects on mortality). However, relative to maximizing strategies, competitive strategies shifted towards greater allocation to roots and leaves with increasing water stress.

Competitive overinvestments (greater allocation to roots and leaves by competitive strategies compared with maximizing strategies) were robust across different modelling contexts, including vegetation parameter sets (Acer vs. Populus), models (LM3‐PPA vs. BiomeE) and uncalibrated vsersus calibrated BiomeE versions.

Synthesis: The theoretical prediction that competitive and maximizing allocation strategies differ under water limitation is confirmed for a demographic model designed as an ESM component. Optimality‐based trait predictions can simplify representing trait diversity in ESMs but do not always correspond to competitive outcomes. Explicitly modelling coexistence and community assembly in ESMs is challenging but is likely the most general approach to representing trait diversity.
The test–retest reliability and validity of food photography and food diary analyses
Authors: Curtis Christopher , Hills Samuel P. , Arjomandkhah Nicola , Cooke Carlton , Ranchordas Mayur K. , Russell Mark
Published: September 2024

Aims

To assess test–retest reliability of both food photography and food diary methods and validity of these data against known values derived from food labels.

Methods

Test–retest reliability analyses of food diary and food photography were compared using single foodstuffs using intra‐class correlation coefficients, coefficients of variation, and limits of agreement. For food diaries, 24‐h test–retest reliability was also examined. Validity was assessed against weighed analyses. As part of habitual intake, a single foodstuff (randomly allocated from 14 common foods) was consumed by 26 participants over 24‐h. On two occasions (14 days apart), single‐blind dietary analyses allowed estimation of foodstuff‐specific energy and macronutrient content and 24‐h intakes.

Results

For food diaries, test–retest reliability was acceptable (weight, energy, carbohydrate, protein, and fat: all intra‐class correlation coefficients: >0.990, coefficient of variation percentage: <0.1%, limits of agreements: <0.1 to <0.1, p > 0.05, and effect size: <0.01). For food photography, test–retest reliability was acceptable for weight, energy, carbohydrate, and protein (all intra‐class correlation coefficients: >0.898, coefficient of variation percentage: 3.6%–6.2%, limits of agreements: 1.1 to – 44.9, and effect size: 0.01–0.12). Food photography validity was worse than food diaries for all variables (percentage difference: 8.8%–15.3%, coefficient of variation percentage: 7.5%–13.8%, all p ≤ 0.05, and effect size: 0.001–0.11).

Conclusions

Greater reliability and validity occurred in food diaries versus food photography. These findings suggest that using food photography may lead to an underestimation of energy and macronutrient content, which may have implications for dietary interventions and nutritional strategies.
A cross‐sectional study assessing the role of interventional radiology services in regional and remote Australia
Authors: Clements Warren , Zia Adil , Chang Kelvin , Brown Nicholas , Koukounaras Jim , Joseph Tim , Lukies Matthew W , Phan Tuan , Goh Gerard S , Varma Dinesh , Tomlinson Heath , Bolger Mark , Kavnoudias Helen
Published: September 2024

Introduction

It is estimated that 8% of hospitalised patients require treatment from Interventional Radiology (IR). However, little is known about the potential impact of IR on regional and remote Australians, including Indigenous patients. This study aimed to assess treatments performed by IRs on regional/remote patients to predict future IR workforce and governance needs.

Methods

Single‐centre cross‐sectional study at a tertiary Victorian hospital. Patients were identified when they had an advanced IR treatment between 1 January 2022 and 2024. Basic procedures such as biopsy and drain insertion were not included. The primary outcome was the type and volume of IR treatments performed on patients who were transferred from a regional or remote home location for treatment.

Results

Of 3485 advanced IR interventions, 908 procedures (26.0%) from patients who lived in a regional or remote location were included with 36.5% female, of mean age 55.6 years (SD 17.9). 1.4% identified as Indigenous which is similar to the Indigenous population incidence in Victoria of 1.0%. Of this group, 350 (38.5%) were either a day procedure, overnight elective admission, or simple inpatient procedure which could have been performed in a regional centre, which included 1.1% Indigenous patients.

Conclusion

There is an unmet need for IR services in regional and remote Australia, with many patients being transferred to our metropolitan centre for treatment that could be performed in regional IR hubs. This data will be important to drive government and hospital planning including capital infrastructure, workforce modelling and future recognition of IR as a new specialty in Australia.
Bringing circuit theory into spatial occupancy models to assess landscape connectivity
Authors: Kervellec Maëlis , Couturier Thibaut , Bauduin Sarah , Chenesseau Delphine , Defos du Rau Pierre , Drouet‐Hoguet Nolwenn , Duchamp Christophe , Steinmetz Julien , Vandel Jean‐Michel , Gimenez Olivier
Published: September 2024

Occupancy models were originally developed to better understand species distribution while accounting for imperfect detection. Because species distribution is not only shaped by habitat quality but also by the ability of individuals to reach suitable habitats, spatial dynamic occupancy models have been proposed to extend the original framework by defining that site colonisation was a function of the Euclidean distance to occupied sites. However, not all sites in the landscape are equally accessible due to the presence of barriers, that of corridors, etc. To account for connectivity between sites, the Euclidean distance has recently been replaced by a least‐cost path distance, which explicitly accounts for landscape resistance, but assumes that individuals will follow the optimal route.

To relax this assumption, we first developed a new spatial occupancy model that incorporates commute‐time distance derived from circuit theory to model accessibility across sites. This distance has the advantage of modelling movement as a random walk and accounting for the fact that colonisation could be achieved from multiple paths. Our approach allows for the explicit estimation of landscape connectivity from detection/non‐detection data and a direct measure of connectivity uncertainty.

We implemented the model in the Bayesian framework using the nimble R package, which allows useful R connectivity functions to be called from within the model. Second, we carried out a simulation study to assess the performance of our model by considering four scenarios depicting an increasing level of landscape resistance. Third, to illustrate our new approach, we studied the recolonisation of two carnivores in France.

We quantified the degree to which rivers facilitate Eurasian otter (Lutra lutra) colonisation and highways impede Eurasian lynx (Lynx lynx) colonisation. Overall, spatial occupancy models provide a flexible framework to accommodate any distance metric designed to align with species dispersal ecology.
Bayesian estimation of spatially varying mortality risk using tagged animal data
Authors: Poulton Anna J. , Villegas‐Ríos David , Freitas Carla , Moland Even , Olsen Esben M. , Sethi Suresh A. , Ellner Stephen P.
Published: September 2024

The survival of animals is impacted by landscapes of spatially varying mortality factors including habitat type, predation risk or harvest risk, among others. Characterization of these spatial mortality processes is important for managing animal populations and their habitats, yet this information has proved challenging to capture. Advances in telemetry now make it possible to monitor tagged individuals' locations through time for a wide range of taxa, providing opportunity to assess movement and mortality simultaneously through spatial time‐to‐event data. Existing time‐to‐event modelling frameworks have largely ignored spatially varying mortality processes or have treated an animal's location as fixed at a regional level.

Here we present a general spatial survival model for analysing time‐to‐event data arising from animal telemetry. Our model has a flexible Cox regression form and can estimate the effects of conventional non‐spatial risk factors (size, seasonality, etc.), spatial covariates (e.g. habitat type) and spatial variation in risk not explained by covariates on mortality. We show how to fit our model using Bayesian methods and demonstrate applications of our model with several simulated examples and two animal telemetry case studies.

Our model produced consistent and unbiased parameter estimates throughout simulations with a variety of spatial and non‐spatial hazards. In the first case study, data from 147 tagged caribou in British Columbia, Canada, revealed a spatially heterogeneous mortality landscape with caribou survival varying by elevation, likely in response to space use by predators. Our second case study involved a dataset of 390 acoustically tagged Atlantic cod in a southern Norwegian fjord where a marine protected area (MPA) was established during the study. We found that the MPA led to a shift from mostly fishing mortality to mostly natural mortality within the fjord and that these risks had markedly different spatial hazard patterns.

Our spatial time‐to‐event model can make use of data from a variety of widely used telemetry technologies to characterize landscapes of mortality risks for different taxa. Our work provides new opportunities to inform the spatial ecology and management of fish and wildlife populations.
SQuID (subcutaneous insulin in diabetic ketoacidosis): Clinician acceptability
Authors: Griffey Richard T. , Schneider Ryan M. , Girardi Margo , LaRossa Gina , Yeary Julianne , Frawley Laura , Ancona Rachel , Kaser Taylor , Suarez Dan , Cruz‐Bravo Paulina
Published: September 2024

Background

We previously implemented the SQuID protocol (subcutaneous insulin in diabetic ketoacidosis [DKA]) demonstrating safe, effective treatment of low‐ to moderate‐severity DKA in a non–intensive care unit setting. Since success and sustainability of interventions rely on staff buy‐in, we assessed acceptability of SQuID among emergency department (ED) and inpatient clinicians.

Methods

We conducted a cross‐sectional study in an urban academic hospital (March 2023–November 2023), surveying ED nurses (RNs) and physicians (MDs) and floor RNs and MDs treating patients on SQuID via emailed survey links. Clinicians could only take the survey once. We used Sekhon's Theoretical Framework of Acceptability, validated for staff acceptability of a new intervention, assessing eight domains with 5‐point Likert responses. Clinicians were asked about prior experience with SQuID, and we assessed ED MD and RN preference (SQuID vs. intravenous [IV] insulin). Surveys included free‐text boxes for comments. We present descriptive statistics including proportions with 95% confidence interval and medians with interquartile ranges (IQRs) and conducted thematic analysis of free‐text comments.

Results

Our overall response rate (107/133) was 80% (34/42 ED RNs, 13/16 floor RNs, 47/57 ED MDs, 13/17 floor MDs), with first‐time users of SQuID ranging from 7.7% (hospitalist MDs) to 35.3% (ED RNs) of participants. ED clinicians preferred SQuID over IV insulin (67% vs. 12%, 21% no preference). Acceptability was high across all domains and clinician types (median 4, IQR 4–5). Overall percentage of positive responses (4s and 5s) across domains was 92% (ED RNs [89%], floor RNs [89%], ED MDs [97%], floor MDs [87%]). We identified several themes among participant comments.

Conclusions

Acceptability was high across clinician types; 65% of ED clinicians preferred SQuID to IV insulin. Clinicians liked SQuID (affective attitude), found it easy to use (burden), were confident in its use (self‐efficacy), felt that it improved outcomes (perceived effectiveness), found that it was fair to patients (ethicality), found that it made sense (intervention coherence), and found that it did not interfere with other activities (opportunity cost).
Time to use the right classification to predict the severity of checkpoint inhibitor‐induced liver injury, as assessed for causality using the updated RUCAM
Authors: Hountondji Lina , Faure Stéphanie , Palassin Pascale , Viel Philine Witkowski Durand , Dupuy Marie , Larrey Dominique , Lamoureux Anouck , Coustal Cyrille , Pureur Dimitri , Lesage Candice , Assenat Éric , Rivière Benjamin , Faillie Jean‐Luc , Quantin Xavier , Pageaux Georges‐Philippe , Maria Alexandre Thibault Jacques , Meunier Lucy
Published: September 2024

Background and Aims

While immune checkpoint inhibitors (ICIs) are revolutionising cancer therapy, checkpoint inhibitor‐induced liver injury is a significant immune‐related side effect of this immunotherapy. This study focuses on the severity classifications and characteristics of patients with checkpoint inhibitor‐induced hepatitis.

Methods

A retrospective analysis of patients with severe Checkpoint Inhibitor‐induced hepatitis grade 3 and 4 according to the recommended Common Terminology Criteria for Adverse Events (CTCAE) classification was conducted. Data on clinicobiological characteristics, treatment and outcomes were collected from 3 university hospitals, and causality was assessed by using the updated Roussel Uclaf Causality Assessment Method. The severity of hepatitis was assessed using the Model for End‐stage Liver Disease score, the Drug‐Induced Liver Injury Network, and the Drug‐Induced Liver Injury International Expert Working Group classifications.

Results

We retrospectively included 100 patients presenting various hepatitis patterns with a median time to onset of 20 days after checkpoint inhibitors. Severity grading varied significantly among the classifications used. A lower incidence of severe cases was observed when using the Drug‐Induced Liver Injury classifications instead of the recommended CCTCAE classification, and this was correlated with outcomes.

Conclusions

This retrospective study challenges the efficacy of the CTCAE classification in defining the severity of Checkpoint Inhibitor‐induced hepatitis and suggests that the traditional hepatology‐focused scores may be more relevant. The CTCAE classification is inconsistent and gives equal weight to jaundice and elevated transaminases, which leads to steroid overtreatment and limits the rechallenge of ICIs.