bluuebunny/crossref_metadata_2025_split huggingface dataset:
A new species of Cichlidogyrus Paperna, 1960 (Platyhelminthes: Monogenea: Dactylogyridae) infecting tilapias in Lake Kariba (Zimbabwe), with a discussion on its phylogenetic position
Authors: Geraerts Mare , Huyse Tine , Vanhove Maarten P. M. , Artois Tom 
Published: May 2022

AbstractMonogeneans dominate the external parasite fauna of bony fish. During recent years, examination of more populations of species of Cichlidogyrus Paperna, 1960 has led to the (re)description of several species. Cichlidogyrus halli (Price & Kirk, 1967) Price, 1968, for example, has been redescribed several times in the past and has been proposed to encompass many (pseudo)cryptic species. In Lake Kariba (Zimbabwe), specimens of a species of Cichlidogyrus were found that morphologically resemble C. halli. These specimens were found on the gills of native Oreochromis cf. mortimeri and Coptodon rendalli (Boulenger, 1897), and introduced Nile tilapia Oreochromis niloticus (Linnaeus, 1758). A detailed study of the morphology of these specimens, including morphometrics, and a thorough comparison with specimens of C. halli is presented. Part of the COI gene and 18S-ITS1 fragment were sequenced and analysed to provide insight into the phylogenetic placement of these specimens within the Cichlidogyrus-Scutogyrus monophylum. We found that C. halli and the new specimens sp. nov. are sister clades within the same monophyletic clade, and that clear morphological and morphometric differences are present in the dorsal bar of the haptor and accessory piece of the male copulatory organ. Based on these results, the new specimens are described as a new species: C. chloeae sp. nov. The role of introduced Nile tilapia as a potential reservoir for native parasites raises concern for potential spillbacks and stresses the need for further monitoring of monogeneans on native and introduced tilapias.
A human adenovirus encoding IFN-γ can transduce Tasmanian devil facial tumour cells and upregulate MHC-I
Authors: Kayigwe Ahab N. , Darby Jocelyn M. , Lyons A. Bruce , Patchett Amanda L. , Lisowski Leszek , Liu Guei-Sheung , Flies Andrew S. 
Published: May 2022

AbstractThe devil facial tumour disease (DFTD) has led to a massive decline in the wild Tasmanian devil (Sarcophilus harrisii) population. The disease is caused by two independent devil facial tumours (DFT1 and DFT2). These transmissible cancers have a mortality rate of nearly 100%. An adenoviral vector-based vaccine has been proposed as a conservation strategy for the Tasmanian devil. This study aimed to determine if a human adenovirus serotype 5 could express functional transgenes in devil cells. As DFT1 cells do not constitutively express major histocompatibility complex class I (MHC-I), we developed a replication-deficient adenoviral vector that encodes devil interferon gamma (IFN-γ) fused to a fluorescent protein reporter. Our results show that adenoviral-expressed IFN-γ was able to stimulate upregulation of beta-2 microglobulin, a component of MHC-I, on DFT1, DFT2, and devil fibroblast cell lines. This work suggests that human adenoviruses can serve as vaccine platform for devils and potentially other marsupials.
A unified neural account of contextual and individual differences in altruism
Authors: Hu Jie , Konovalov Arkady , Ruff Christian C. 
Published: May 2022

AbstractAltruism is critical for cooperation and productivity in human societies, but is known to vary strongly across contexts and individuals. The origin of these differences is largely unknown, but may in principle reflect variations in different types of neurocognitive processes that temporally unfold during altruistic decision making (ranging from initial perceptual processing via value computations to final integrative choice mechanisms). Here, we address this question by examining altruistic choices in different inequality contexts with computational modeling and EEG. Our results show that across all contexts and individuals, wealth distribution choices recruit a similar late decision process evident in model-predicted evidence accumulation signals over parietal regions. Contextual and individual differences in behavior related instead to initial processing of stimulus-locked inequality-related value information in centroparietal and centrofrontal sensors, as well as to gamma-band synchronization of these value-related signals with parietal response-locked evidence-accumulation signals. Our findings suggest separable biological bases for individual and contextual differences in altruism and emphasize that these reflect differences in processing of choice-relevant information.
Topological defects govern mesenchymal condensations, offering a morphology-based tool to predict cartilage differentiation
Authors: Makhija Ekta , Zheng Yang , Wang Jiahao , Leong Han Ren , Othman Rashidah Binte , Ng Ee Xien , Lee Eng Hin , Tucker Kellogg Lisa , Lee Yie Hou , Yu Hanry , Poon Zhiyong , Van Vliet Krystyn Joy 
Published: May 2022

AbstractA critical initial stage of skeletal morphogenesis involves formation of highly compact aggregates of mesenchymal cells, known as mesenchymal condensations, appearing as regularly-spaced pattern of spots. Conventional computational models to understand their patterning have been based on chemotaxis, haptotaxis, and reaction-diffusion equations. In this work, we investigate the mesenchymal condensations from a different perspective, namely topological defects within liquid crystal-like pattern. Using bone marrow-derived mesenchymal stromal cells (bm-MSCs), we observed emergence of cellular swirls in confluent in-vitro cultures, followed by appearance of mesenchymal condensations at the centers of the selfassembled swirls. Specifically, the condensations appeared at the ‘comet-like’ (+1/2) and ‘spiral-shaped’ (+1) topological defect sites within the swirl pattern. Next, with the rationale that cellular swirls precede skeletal morphogenesis, and supported with the qualitative observation that swirl pattern-features are donor-specific, we probed the correlation between swirl pattern and the chondrogenic differentiation outcome of bm-MSCs. Towards this, we first generated and imaged cellular swirls systematically across 5 donors by controlling seeding density, culture vessel geometry, and culture duration. We observed that the swirl pattern features quantified as variance of coherency correlated strongly with the cartilage matrix proteins, sulfated glycosaminoglycan and collagen-II, quantified from the standard in-vitro chondrogenic differentiation assay. Our work shows that swirl-pattern quantification provides a novel and powerful tool to predict efficacy of bm-MSCs for in-vitro cartilage regeneration.Significance StatementMesenchymal condensation is a critical stage in the formation of bone and cartilage, where the mesenchymal cells form high density cell clusters that are regularly spaced. In this work, we inspect the patterning of these condensations in-vitro from a novel perspective. We first show that at high density, bone-marrow-derived mesenchymal stromal cells (bm-MSCs) self-assemble to form cellular swirls resembling the vortices in a turbulent flow. This is followed by cell aggregations at the centers of the vortices, which show correspondence to mesenchymal condensations. Interestingly, we observed that the swirl pattern made by bm-MSCs isolated from human donors, varies from individual to individual and correlates with their propensity to differentiate into cartilage. This suggests that swirl pattern quantification via image analysis can be used to predict differentiation outcome, in context of regenerative cell therapy.
Benchmarks in antimicrobial peptide prediction are biased due to the selection of negative data
Authors: Sidorczuk Katarzyna , Gagat Przemysław , Pietluch Filip , Kała Jakub , Rafacz Dominik , Bąkała Laura , Słowik Jadwiga , Kolenda Rafał , Rödiger Stefan , Fingerhut Legana C H W , Cooke Ira R , Mackiewicz Paweł , Burdukiewicz Michał 
Published: May 2022

AbstractAntimicrobial peptides (AMPs) are a heterogeneous group of short polypeptides that target microorganisms but also viruses and cancer cells. Due to their lower selection for resistance compared to traditional antibiotics, AMPs have been attracting the ever-growing attention from researchers, including bioinformaticians. Machine learning represents the most cost-effective method for novel AMP discovery and consequently many computational tools for AMP prediction have been recently developed. In this article, we investigate the impact of negative data sampling on model performance and benchmarking. We generated 660 predictive models using 12 machine learning architectures, a single positive data set and 11 negative data sampling methods; the architectures and methods were defined on the basis of published AMP prediction software. Our results clearly indicate that similar training and benchmark data set, i.e. produced by the same or a similar negative data sampling method, positively affect model performance. Consequently, all the benchmark analyses that have been performed for AMP prediction models are significantly biased and, moreover, we do not know which model is the most accurate. To provide researchers with reliable information about the performance of AMP predictors, we also created a web server AMPBenchmark for fair model benchmarking. AMPBenchmark is available at http://BioGenies.info/AMPBenchmark.
Activation mechanism of Small Heat Shock Protein HSPB5 revealed by disease-associated mutants
Authors: Woods Christopher N , Janowska Maria K , Ulmer Lindsey D , Sidhu Jasleen Kaur , Stone Natalie L , James Ellie I , Guttman Miklos , Bush Matthew F , Klevit Rachel E 
Published: May 2022

AbstractFound from bacteria to humans, small heat shock proteins (sHSPs) are the least understood protein chaperones. HSPB5 (or αB-crystallin) is among the most widely expressed of the ten human sHSPs, including in muscle, brain, and eye lens where it is constitutively present at very high levels and carries out a myriad of functions. A high content of disorder in HSPB5 has stymied efforts to uncover how its structure gives rise to function. To uncover its mechanisms of action, we compared human HSPB5 and two disease-associated mutants, R120G and D109H. Expecting to learn how the mutations lead to loss of function, we found instead that the mutants are constitutively activated chaperones while wild-type HSPB5 can transition reversibly between non-activated (low activity) and activated (high activity) states in response to changing conditions. Techniques that provide information regarding interactions and accessibility of disordered regions revealed that the disordered N-terminal regions (NTR) that are required for chaperone activity exist in a complicated interaction network within HSPB5 oligomers and are sequestered from solvent in non-activated states. Either mutation or an activating pH change cause rearrangements in the network that expose parts of the NTR, making them more available to bind an aggregating client. While beneficial in the short-term, failure of the mutants to adopt a state with lower activity and lower NTR accessibility leads to increased co-aggregation propensity and, presumably, early cataract. The results support a model where chaperone activity and solubility are modulated through the quasi-ordered NTR and its multiple competing interactions.SignificanceSmall heat shock proteins (sHSPs) are the oldest known protein chaperones, but how they recognize misfolding proteins in early stages of aggregation is unknown. Disordered regions within sHSPs are critical to their function, raising the question of how disorder recognizes disorder. We investigated a human sHSP (HSPB5) and two disease mutants using approaches that provide residue-level information in regions of disorder. The findings reveal that large, heterogeneous oligomers of HSPB5 contain complicated networks of interactions involving their disordered regions that protect them from solvent. Conditions associated with stress or disease mutations cause a rearrangement of the interaction network and enhancement of chaperone activity. The study provides new information regarding how disordered regions are modulated in a network of competing interactions.
Data science approaches provide a roadmap to understanding the role of abscisic acid in defence
Authors: Stevens Katie , Johnston Iain. G. , Luna Estrella 
Published: May 2022

AbstractAbscisic acid is a plant hormone well known to regulate abiotic stress responses. ABA is also recognised for its role in biotic defence, but there is currently a lack of consensus on whether it plays a positive or negative role. Here, we used supervised machine learning to analyse experimental observations on ABA to identify the most influential factors determining disease phenotypes. ABA concentration, plant age and pathogen lifestyle were identified in our computational predictions. We explored these predictions with new experiments in tomato, demonstrating that phenotypes after ABA treatment were highly dependent on plant age and pathogen lifestyle. Integration of these new results into the statistical framework refined the quantitative model of ABA influence, suggesting a framework for proposing and exploiting further research to make more progress on this complex question. Our approach provides a unifying road map to guide future studies involving the role of ABA in defence.
Reported Health Benefits of a Vegan Dog Food – A Likert Scale-type Survey of 100 Guardians
Authors: Davies Mike 
Published: May 2022

AbstractIntroductionThere has been a surge in feeding plant-based foods to pets and advocates extol the health benefits of this practice. However, there is a lack of scientific evidence to support health claims for vegan diets in dogs.AimsThis study aimed to quantify perceived health changes by dog guardians following the feeding of a single brand of UK-produced vegan food for a period of 3 to 12 months.MethodsDog guardians registered as feeding the vegan food for 3 - 12 months were invited to participate in an online Likert Scale-type survey of observations reflecting health status.Results100 guardians completed the survey. The vegan food was acceptable (palatable), and appetite and body weight were not adversely affected. Changes, including improvements, were reported in the following areas: body condition score (BCS), activity, faecal consistency, faecal colour, frequency of defaecation, flatus frequency, flatus antisocial smell, coat glossiness, scales in haircoat (dandruff), redness of the skin (erythema, inflammation), crusting of the external ear canals (otitis externa), itchiness (scratching; pruritus), anxiety, aggressive behaviour and coprophagia.ConclusionsThis is the first study to quantitatively document guardian reports of specific positive health benefits associated with feeding a UK vegan dog food. Further prospective, randomised, controlled clinical trials are needed to validate and determine the significance of these observations.
Beyond the dyad: uncovering higher-order structure within cohesive animal groups
Authors: Musciotto Federico , Papageorgiou Danai , Battiston Federico , Farine Damien R. 
Published: May 2022

ABSTRACTRevealing the consequences of social structure in animal societies is largely determined by our ability to accurately estimate functionally relevant patterns of social contact among individuals. To date, studies have predominantly built up social structure from dyadic connections. However, many associations or interactions can involve more than two individuals participating together, which current approaches cannot distinguish from independent sets of dyadic connections. Here we demonstrate the application of higher-order networks to detect the central roles of dominance and sex in structuring social groups of vulturine guineafowl (Acryllium vulturinum). Specifically, we find that while females and low-ranking group members engage in more dyadic interactions, males and more dominant group members are substantially more likely to be observed forming hyperlinks—edges that contain more than two individuals (e.g. a triad). These results demonstrate how higher-order networks can provide a deeper understanding of the multidimensionality in the difference of centrality among group members.
A novel discrete grey model with time-delayed power term and its application in solar power generation volume forecasting
Authors: Li Ye , Bai Xue , Liu Bin , Yang Yuying 
Published: May 2022

PurposeIn order to accurately forecast nonlinear and complex characteristics of solar power generation in China, a novel discrete grey model with time-delayed power term (abbreviated as TDDGM(1,1,tα) is proposed in this paper.Design/methodology/approachFirstly, the time response function is deduced by using mathematical induction, which overcomes the defects of the traditional grey model. Then, the genetic algorithm is employed to determine the optimal nonlinear parameter to improve the flexibility and adaptability of the model. Finally, two real cases of installed solar capacity forecasting are given to verify the proposed model, showing its remarkable superiority over seven existing grey models.FindingsGiven the reliability and superiority of the model, the model TDDGM(1,1,tα) is applied to forecast the development trend of China's solar power generation in the coming years. The results show that the proposed model has higher prediction accuracy than the comparison models.Practical implicationsThis paper provides a scientific and efficient method for forecasting solar power generation in China with nonlinear and complex characteristics. The forecast results can provide data support for government departments to formulate solar industry development policies.Originality/valueThe main contribution of this paper is to propose a novel discrete grey model with time-delayed power term, which can handle nonlinear and complex time series more effectively. In addition, the genetic algorithm is employed to search for optimal parameters, which improves the prediction accuracy of the model.
Understanding employees’ information security–related stress and policy compliance intention: the roles of information security fatigue and psychological capital
Authors: Chen Hao , Liu Mengya , Lyu Tu 
Published: May 2022

Purpose
This study aims to explore the emotion-based mediator of information security fatigue in the relationship between employees’ information security–related stress (SRS) and information security policy (ISP) compliance intention and the effects of psychological capital (PsyCap) on relieving SRS and promoting compliance.

Design/methodology/approach
The authors tested a series of hypotheses by applying partial least squares–based structural equation modeling to survey data from 488 employees in Chinese enterprises.

Findings
The results suggest that the relationship between SRS and ISP compliance intention is fully mediated by information security fatigue. Employees’ SRS promotes their information security fatigue, which reduces their intention to follow ISPs. In addition, employees with high PsyCap may experience low levels of SRS and information security fatigue, which promotes their willingness to comply with ISPs.

Originality/value
This study extends knowledge by introducing information security fatigue and PsyCap to the field of information security management, and it calls attention to the effects on information security behaviors of employee emotions and positive psychological resources in an organization. The authors reveal the emotion-based mediating effect of information security fatigue and the positive influence of PsyCap in information security management.
Global analysis of timely COVID-19 vaccinations: improving governance to reinforce response policies for pandemic crises
Authors: Benati Igor , Coccia Mario 
Published: May 2022

PurposeThe goal of this study is to analyze the relationship between public governance and COVID-19 vaccinations during early 2021 to assess the preparedness of countries to timely policy responses to cope with pandemic crises.Design/methodology/approachThis global study elaborates descriptive statistics, correlations, regression analyses and Independent Samples T-Test on 112 countries, comparing those with high/low level of governance, to determine whether statistical evidence supports the hypothesis that good governance can improve the timely administration of vaccines.FindingsBivariate correlation reveals that doses of vaccines administered × 100 inhabitants have a high positive association with the General Index of Governance (r = 0.58, p-value <0.01). The result is confirmed by partial correlation (controlling density of population per km2): r = 0.584, p-value <0.001. The coefficient of regression in the models also indicates that an increase in the General Index of Governance improves the expected administration of doses of COVID-19 vaccines (p-value <0.001).Research limitations/implicationsAlthough this study has provided interesting results that are, of course, tentative, it has several limitations. First, a limitation is the lack of data in several countries. Second, not all the possible confounding factors that affect the vaccination against COVID-19 are investigated, such as country-specific health investments and expenditures, and these aspects should be examined in the future development of this research. A third limit is related to the measurement of governance through the World Governance Indicators, which are based only on perceptions and can be biased by different socio-economic factors.Practical implicationsThe identification of factors determining the timely vaccinations may help to design best practices of health policy for improving the resilience of countries to face pandemic crises.Social implicationsThe improvement of preparedness of countries through good governance can foster a rapid rollout of vaccinations to cope with pandemic threats and the negative effects of their socio-economic impact.Originality/valueThis study presents a global analysis of the role of public governance for timely vaccinations to face pandemic crises in society.
Assessment of science, technology and innovation parks based on helices actors linkages
Authors: Amaral Marcelo G. , da Hora André Luis Furtado , Schocair Marília Medeiros 
Published: May 2022

Purpose
This study aims to examine the evolution of three science, technology and innovation parks (STIPs) located in the state of Rio de Janeiro, Brazil, from the perspective of the university–industry–government linkages.

Design/methodology/approach
This is a multiple case study organized in two stages: first, bibliographic and documentary research to develop a theoretical framework and description of the innovation environments; and second, interviews and forms filling with 13 managers and stakeholders, combined with participant observation. The analysis and assessment of the evolution of each environment are based on a tool named Amaral’s Model for Innovation Environment Management (AMIEM).

Findings
There are critical issues for the development of STIPs, namely, governance structure, government participation and the relationship with knowledge sources such as universities. The time of existence is not a significant factor in reaching evolution. Although common factors are present in all environments, local particularities, specific characteristics, regional vocations, management leadership and other elements have an impact on park performance.

Practical implications
AMIEM is an assessment tool and a technological product, useful in mapping and evaluating innovation environments.

Social implications
STIPs are dynamic and maturing, requiring active management and engagement with government and companies.

Originality/value
The results allow a better comprehension of the evolution and management of the STIPs located in the state of Rio de Janeiro. Another contribution lies in the organization of information to design public policies.