bluuebunny/crossref_metadata_2025_split huggingface dataset:
ASTRA: a deep learning algorithm for fast semantic segmentation of large-scale astrocytic networks
Authors: Bonato Jacopo , Curreli Sebastiano , Romanzi Sara , Panzeri Stefano , Fellin Tommaso 
Published: May 2023

AbstractChanges in the intracellular calcium concentration are a fundamental fingerprint of astrocytes, the main type of glial cell. Astrocyte calcium signals can be measured with two-photon microscopy, occur in anatomically restricted subcellular regions, and are coordinated across astrocytic networks. However, current analytical tools to identify the astrocytic subcellular regions where calcium signals occur are time-consuming and extensively rely on user-defined parameters. These limitations limit reproducibility and prevent scalability to large datasets and fields-of-view. Here, we present Astrocytic calcium Spatio-Temporal Rapid Analysis (ASTRA), a novel software combining deep learning with image feature engineering for fast and fully automated semantic segmentation of two-photon calcium imaging recordings of astrocytes. We applied ASTRA to several two-photon microscopy datasets and found that ASTRA performed rapid detection and segmentation of astrocytic cell somata and processes with performance close to that of human experts, outperformed state-of-the-art algorithms for the analysis of astrocytic and neuronal calcium data, and generalized across indicators and acquisition parameters. We also applied ASTRA to the first report of two-photon mesoscopic imaging of hundreds of astrocytes in awake mice, documenting large-scale redundant and synergistic interactions in extended astrocytic networks. ASTRA is a powerful tool enabling closed-loop and large-scale reproducible investigation of astrocytic morphology and function.
Collective signalling drives rapid jumping between cell states
Authors: Westbrook Elizabeth R. , Lenn Tchern , Chubb Jonathan R. , Antolović Vlatka 
Published: May 2023

AbstractDevelopment can proceed in “fits and starts”, with rapid transitions between cell states involving concerted transcriptome-wide changes in gene expression. However, it is not clear how these transitions are regulated in complex cell populations, in which cells receive multiple inputs. It is also not clear to what extent these rapid transitions represent developmental commitment. Here we address these issues usingDictyosteliumcells undergoing development in their physiological niche. A continuous single cell transcriptomics time series reveals a sharp “jump” in global gene expression marking functionally different cell states. By simultaneously live imaging the physiological dynamics of transcription and signalling over millimetre length scales, we show that the jump coincides with the onset of collective oscillations of cAMP, the positive feedback signal for multicellular development. Different jump genes respond to distinct dynamic features of signalling. The late gene expression changes of the jump are almost completely dependent on cAMP. In contrast, transcript changes at the onset of the jump require additional input. The spatial boundary marking the jump divides cells separated by only a few minutes of developmental time, with cells missing a jump then waiting several hours for the onset of the next wave of cAMP oscillations. This timing variability contrasts the prevailing developmental paradigm of a timed synchronous process and is associated with substantial pre-jump transcriptome variability. The coupling of collective signalling with gene expression is a potentially powerful strategy to drive robust cell state transitions in heterogeneous signalling environments. Based on the context of the jump, we also conclude that sharp gene expression transitions may not be sufficient for commitment.
SlumberNet: Deep learning classification of sleep stages using residual neural networks
Authors: Jha Pawan K. , Valekunja Utham K. , Reddy Akhilesh B. 
Published: May 2023

AbstractSleep research is fundamental to understanding health and well-being, as proper sleep is essential for maintaining optimal physiological function. Here we present SlumberNet, a novel deep learning model based on residual network (ResNet) architecture, designed to classify sleep states in mice using electroencephalogram (EEG) and electromyogram (EMG) signals. Our model was trained and tested on data from mice undergoing baseline sleep, sleep deprivation, and recovery sleep, enabling it to handle a wide range of sleep conditions. Employing k-fold cross-validation and data augmentation techniques, SlumberNet achieved high levels of accuracy (∼98%) in predicting sleep stages and showed robust performance even with a small and diverse training dataset. Comparison of SlumberNet’s performance to manual sleep stage classification revealed a significant reduction in analysis time (∼50x faster), without sacrificing accuracy. Our study showcases the potential of deep learning to facilitate sleep research by providing a more efficient, accurate, and scalable method for sleep stage classification. Our work with SlumberNet demonstrates the power of deep learning in sleep research, and looking forward, SlumberNet could be adapted to human EEG analysis and sleep stage classification. Thus, SlumberNet could be a valuable tool in understanding both sleep physiology and disorders in mammals.
Cross-feeding affects the target of resistance evolution to an antifungal drug
Authors: Durand Romain , Jalbert-Ross Jordan , Fijarczyk Anna , Dubé Alexandre K. , Landry Christian R. 
Published: May 2023

AbstractPathogenic fungi are a cause of growing concern. Developing an efficient and safe antifungal is challenging because of the similar biological properties of fungal and host cells. Consequently, there is an urgent need to better understand the mechanisms underlying antifungal resistance to prolong the efficacy of current molecules. A major step in this direction would be to be able to predict or even prevent the acquisition of resistance. We leverage the power of experimental evolution to quantify the diversity of paths to resistance to the antifungal 5-fluorocytosine (5-FC), commercially known as flucytosine. We generated hundreds of independent 5-FC resistant mutants derived from two genetic backgrounds from wild isolates ofSaccharomyces cerevisiae. Through automated pin-spotting, whole-genome and amplicon sequencing, we identified the most likely causes of resistance for most strains. Approximately a third of all resistant mutants evolved resistance through a pleiotropic drug response, a potentially novel mechanism in response to 5-FC, marked by cross-resistance to fluconazole. These cross-resistant mutants are characterized by a loss of respiration and a strong tradeoff in drug-free media. For the majority of the remaining two thirds, resistance was acquired through loss-of-function mutations inFUR1, which encodes an important enzyme in the metabolism of 5-FC. We describe conditions in which mutations affecting this particular step of the metabolic pathway are favored over known resistance mutations affecting a step upstream, such as the well-known target cytosine deaminase encoded byFCY1. This observation suggests that ecological interactions may dictate the identity of resistance hotspots.Author summaryDetermining the paths evolution takes to make microbes resistant to antimicrobials is key to drug stewardship. Flucytosine is one of the oldest antifungals available. It is often used to treat cryptococcal infections. However, despite decades of use in the clinic, some details of its metabolism and of the mechanisms of resistance evolution still elude us. Flucytosine resistance is most often acquired specifically by inactivating a gene essential for the activation of this prodrug. We show that among many paths possible, one is overrepresented and involves a diversity of mutations that prevent enzyme expression or its activity. This path is preferred because these mutations also protect from the activation of the prodrug by non-mutant cells. A second, less frequent path to resistance, putatively involves a generalized response, which leads to fungal cells having an increased efflux capacity. The same mutants end up being resistant to the distinct and most widely used antifungal fluconazole. Our results show that the paths followed by evolution are influenced by microecological conditions and that resistance to unrelated drugs can emerge from the same mutations.
Structures of 9-1-1 DNA checkpoint clamp loading at gaps from start to finish and ramification to biology
Authors: Zheng Fengwei , Georgescu Roxana E. , Yao Nina Y. , O’Donnell Michael E. , Li Huilin 
Published: May 2023

SUMMARYRecent structural studies show the Rad24-RFC loads the 9-1-1 checkpoint clamp onto a recessed 5′ end by binding the 5′ DNA on Rad24 at an external surface site and threading the 3′ ssDNA into the well-established internal chamber and into 9-1-1. We find here that Rad24-RFC loads 9-1-1 onto DNA gaps in preference to a recessed 5′ DNA end, thus presumably leaving 9-1-1 on a 3′ ss/ds DNA after Rad24-RFC ejects from the 5′ gap end and may explain reports of 9-1-1 directly functioning in DNA repair with various TLS polymerases, in addition to signaling the ATR kinase. To gain a deeper understanding of 9-1-1 loading at gaps we report high-resolution structures of Rad24-RFC during loading of 9-1-1 onto 10-nt and 5-nt gapped DNAs. At a 10-nt gap we captured five Rad24-RFC–9-1-1 loading intermediates in which the 9-1-1 DNA entry gate varies from fully open to fully closed around DNA using ATPγS, supporting the emerging view that ATP hydrolysis is not needed for clamp opening/closing, but instead for dissociation of the loader from the clamp encircling DNA. The structure of Rad24-RFC–9-1-1 at a 5-nt gap shows a 180° axially rotated 3′-dsDNA which orients the template strand to bridge the 3′- and 5′- junctions with a minimum 5-nt ssDNA. The structures reveal a unique loop on Rad24 that limits the length of dsDNA in the inner chamber, and inability to melt DNA ends unlike RFC, thereby explaining Rad24-RFC’s preference for a preexisting ssDNA gap and suggesting a direct role in gap repair in addition to its checkpoint role.
Challenges faced by ESL in-service teachers enrolled in a teacher education programme via open distance learning in Malaysia
Authors: Ooi Li Hsien , Othman Juliana 
Published: May 2023

PurposeThe purpose of this study was to examine the challenges experienced by in-service English as a Second Language (ESL) teachers in an open distance learning (ODL) institution of higher learning in Malaysia. Many in-service ESL teachers who do not have the necessary teaching qualifications are seeking to obtain their teaching qualifications via the ODL mode of studies as it allows them to work as teachers while obtaining their teaching qualifications at the same time. They face multiple challenges which lead to high attrition rates, a concern for ODL institutions of higher learning worldwide.Design/methodology/approachA qualitative research design using a case study approach was used in this study where in-depth interviews were conducted with four in-service ESL teachers who are currently enrolled in an undergraduate Teaching English as a Second Language (TESL) programme conducted via ODL.FindingsThe research is exploratory in nature. Findings highlighted four major challenges by these in-service ESL teachers: (1) financial difficulties, (2) work commitments, (3) family sacrifices and (4) emotional stress. However, technological use was not considered a challenge as mentioned by literature.Practical implicationsFindings from the study may be useful to ODL institutions to provide relevant support to ODL students to improve student retention rates in ODL institutions.Originality/valueThis study may be considered as a baseline analysis on the challenges experienced by in-service ESL teachers in ODL institution of higher learning in Malaysia. Further in-depth studies are needed to understand how ODL institutions can better support their education programme students to complete their teacher education programmes.
Research on two-stage public opinion evolution configuration path based on fuzzy-set qualitative comparative analysis
Authors: Hou Yanhui , Meng Fan , Wang Jiakun , Li Yun 
Published: May 2023

PurposeUnder the background of coexistence of information overload and information fragmentation, it is of great significance to identify influencing factors and reveal the evolution logic of public opinion for public opinion governance.Design/methodology/approachTaking 24 hot social events as research cases, firstly, the evolution process of public opinion was divided into initial stage and response stage. Secondly, eight antecedent variables were extracted for qualitative comparative analysis of fuzzy sets. Finally, the configuration path of public opinion evolution results was summarized.FindingsThe research showed that compared with the initial stage, the influencing factors in the reaction stage played a key role in the continuous evolution of public opinion. The influencing factors in the initial stage and response stage played an indispensable role in promoting the evolution of public opinion to calm down.Practical implicationsThis research can provide reference for regulators to timely grasp the initiative, discourse power and leadership of public opinion development.Originality/valueResearch on the two-stage configuration path of public opinion evolution is helpful to clarify the key factors affecting the evolution trend of online public opinion of hot events.
The impact of building regulations on indoor environmental quality: the case of detached houses in Jordan
Authors: Ali Hikmat , Abed Amal , Rababah Alaa 
Published: May 2023

PurposeAs numerous research studies have investigated the effect of the built environment on human contentment, building regulations have advanced as a direct impact on indoor environmental quality (IEQ) to include thermal, lighting, air quality and acoustics systems. Yet, while IEQ and residents' satisfaction have been discussed thoroughly in previous research, only a few studies have researched the role of building regulations as motivating factors in the housing context, specifically in Jordan.Design/methodology/approachA mixed-method approach was adopted to address this issue involving genotype analysis for building morphology and simulation using Design Builder software. This helped to understand the impact of building regulations variables, including building setback, the height of an adjacent building, orientation and building geometry. Meanwhile, an online survey was conducted to include 410 residents spread out in various building categories (A, B, C and D).FindingsThe results of this study revealed that building regulation of setbacks, the height of adjacent buildings and orientation are significant parameters that directly affect IEQ and residents' satisfaction. In addition, based on this study, the matter was clear that the highest total satisfaction resulted based on the highest comfort level in terms of temperature and daylight obtained due to larger setback and lower building height. Yet, this finding undermined smart growth principles due to the limited scope of building regulation that focused only on spatial and physical dimensions, so improving to include environmental aspects such as passive design strategies that appreciate natural ventilation and lighting is necessary, which positively impact IEQ.Originality/valueThe concept of IEQ and residents' satisfaction have been discussed thoroughly, but only a few studies have researched the role of building regulations as motivating factors in the housing context specifically in Jordan.
CEO characteristics and firm performance: evidence from a Southeast Asian country
Authors: Suherman Suherman , Mahfirah Titis Fatarina , Usman Berto , Kurniawati Herni , Kurnianti Destria 
Published: May 2023

PurposeThe purpose of this study was to investigate how chief executive officer (CEO) characteristics, including age, education, nationality and particularly gender, influence firm performance in a developing Southeast Asian Country (Indonesia).Design/methodology/approachThe study uses balanced firm-level panel data for 203 nonfinancial companies listed on the Indonesia Stock Exchange from 2010 to 2020. Return on assets, return on equity and Tobin’s Q were used to measure firm performance. The data were analyzed using panel data regression analysis, including a fixed effects model with clustered standard errors.FindingsThe results indicate that female CEOs, education and nationality enhance firm performance, while CEO age can either improve or reduce firm performance. Numerous robustness checks were performed; the results were consistent with those in the main analysis.Research limitations/implicationsIndividual characteristics should be considered when appointing CEOs. Some CEO characteristics enhance firm performance. Female CEOs bring new perspectives, while older CEOs’ longer experience adds a competitive advantage. More educated CEOs have a better ability to deal with challenging intellectual activities, and CEOs from foreign countries better understand international market regulations. However, some characteristics may reduce firm performance, for example, older CEOs are more conservative and unable to adapt to changing business environments.Originality/valueThis study contributes to corporate governance studies by synthesizing CEO characteristics and investigating their relationship with firm performance. Moreover, it emphasizes that developing countries such as Indonesia have different economic, legal, social and cultural environments than developed countries, especially Western countries.
Decoding Asian consumers' willingness to pay for organic food product: a configurational-based approach
Authors: Marozzo Veronica , Costa Alessandra , Crupi Antonio , Abbate Tindara 
Published: May 2023

PurposeThis study aims to examine the most influential drivers, both product-specific and consumer-specific, affecting Asian consumers' willingness to pay (WTP) for organic olive oil.Design/methodology/approachTo individuate the most influential drivers of WTP for organic products and to assess their effect, in terms of configurational paths and consumer profiles, this study sequentially employs explorative factor analysis approach and a fuzzy-set qualitative comparative analysis method. The survey is carried out in different areas of Asia (e.g. Pakistan, Vietnam and China).FindingsThe results suggest that Asian consumers' WTP for organic products is described by consumer-specific drivers (gender, occupation and household size) as well as product-specific drivers (product authenticity and sustainability, consumer ethnocentrism and food fraud risk perception).Originality/valueThe findings of the study permit the identification of different drivers that move consumers' WTP for organic olive oil. The study contributes to setting the ground for companies to propose and implement efficacious marketing strategies for organic olive oil in importing countries, such as Asia.
The moderating role of market uncertainty in the effectiveness of government policies and R&D activities promoting innovation in manufacturing firms
Authors: Kim Young-Ah , Kim Kyung-Ah , Moffatt Peter G. 
Published: May 2023

PurposeThe purpose of this study is to examine the impact of government support policies and research and development (R&D) activities on product innovation under market uncertainty.Design/methodology/approachThis study applies logistic regression analysis to a sample of 4,000 South Korean manufacturing firms in order to investigate the impact of government policies and R&D activities of the firm on firm innovation performance, with particular interest in the moderating role of the firm's perceived market uncertainty (PMU).FindingsPolicies supporting industry/university/institute/local collaboration are found to have greater benefit under high PMU. Surprisingly, support for a consortium among different-sized firms has a negative effect on product innovation, although this negative effect disappears under high PMU. Both support for the protection of intellectual property (IP) and support for the resolution of manpower shortages have strong positive effects on the propensity to innovate products, but in both cases the moderating effects of uncertainty are negative. Finally, all types of R&D activities have positive effects on the propensity to innovate, more so for new product innovation than for improved product innovation.Originality/valueTo the best of the authors' knowledge, this is the first study to examine analytically the moderating effect of PMU in the effectiveness of government policies promoting innovation in the manufacturing sector. The study is potentially useful both for policymakers in deciding which policies to implement under prevailing market conditions; and for entrepreneurs choosing between different forms of government support, particularly given the abnormal levels of market uncertainty prevailing in the Covid-19 era.
Startup category membership and boundary expansion in the field of artificial intelligence
Authors: Truong Yann 
Published: May 2023

PurposeAn important but neglected area of investigation in digital entrepreneurship is the combined role of both core and peripheral members of an emerging technological field in shaping the symbolic and social boundaries of the field. This is a serious gap as both categories of members play a distinct role in expanding the pool of resources of the field. I address this gap by exploring how membership category is related to funding decisions in the emerging field of artificial intelligence (AI).Design/methodology/approachThe first quantitative study involved a sample of 1,315 AI-based startups which were founded in the period of 2011–2018 in the United States. In the second qualitative study, the author interviewed 32 members of the field (core members, peripheral members and investors) to define the boundaries of their respective role in shaping the social boundaries of the AI field.FindingsThe author finds that core members in the newly founded field of AI were more successful at attracting funding from investors than peripheral members and that size of the founding team, number of lead investors, number of patents and CEO approval were positively related to funding. In the second qualitative study, the author interviewed 30 members of the field (core members, peripheral members and investors) to define their respective role in shaping the social boundaries of the AI field.Research limitations/implicationsThis study is one of the first to build on the growing literature in emerging organizational fields to bring empirical evidence that investors adapt their funding strategy to membership categories (core and peripheral members) of a new technological field in their resource allocation decisions. Furthermore, I find that core and peripheral members claim distinct roles in their participation and contribution to the field in terms of technological developments, and that although core members attract more resources than peripheral members, both actors play a significant role in expanding the field’s social boundaries.Practical implicationsCore AI entrepreneurs who wish to attract funding may consider operating in fewer categories in order to be perceived as core members of the field, and thus focus their activities and limited resources to build internal AI capabilities. Entrepreneurs may invest early in filing a patent to signal their in-house AI capabilities to investors.Social implicationsThe social boundaries of an emerging technological field are shaped by a multitude of actors and not only the core members of the field. The author should pay attention to the role of each category of actors and build on their contributions to expand a promising field.Originality/valueThis paper is among the first to build on the growing literature in emerging organizational fields to study the resource acquisition strategies of entrepreneurs in a newly establishing technological field.