bluuebunny/crossref_metadata_2025_split huggingface dataset:
Behaviourally mediated camouflage in the furrowed crab (Xantho Hydrophilus)
Authors: Dyer Emilia , Stevens Martin 
Published: August 2024

AbstractCamouflage is a classic adaptation used to conceal an individual and avoid detection or recognition by both predator and prey. Research on camouflage spans both artificial systems and real animals, often focussing on the types of camouflage that exist and how they work. It has long been known that many animals also use behaviour to facilitate camouflage, but many questions remain, and most studies are limited to certain taxa such as moths and birds. Here we use behavioural choice experiments, testing the responses of furrowed crabs (Xantho hydrophilus) to backgrounds differing in brightness, substrate grain size, and complexity to determine if individuals use behavioural choice to facilitate camouflage. Crabs preferentially chose backgrounds that were more similar in brightness to their own appearance but showed no preference for substrate size. In addition, crabs showed some tentative, but not statistically significant, preferences for complex, high contrast environments, providing some support for recent theories on the importance of environmental complexity in facilitating improved camouflage. We also found that furrowed crabs exhibit reduced intraspecific variation in carapace colour with age, which most likely reflects ontogenetic changes in coloration that are common in crabs or may be due to greater predation on less well-camouflaged individuals. There was also some evidence that the propensity to choose backgrounds increased with age. Thus, individuals can improve their camouflage through substrate choice, and this may improve with age. These findings provide insights into the camouflage behaviour and ecology of crabs and other animals, with implications for the tuning and efficacy of camouflage strategies.
Impact of corticosteroid doses on prognosis of severe and critical COVID-19 patients with Omicron variant infection: a propensity score matching study
Authors: Wang Shiyao , Chen Ziying , Zhang Xinran , Wu Xiaojing , Wang Yuqiong , Zhang Qi , Huang Linna , Cui Xiaoyang , Cai Ying , Huang Xu , Xia Jingen , Gu Sichao , Li Min , Zhan Qingyuan 
Published: August 2024

Abstract
Background
There is lack of research on corticosteroid use for severe and critical COVID-19 patients with Omicron variant infection.

Methods
This multi-center retrospective cohort study involved 1167 patients from 59 ICUs across the mainland of China diagnosed with severe or critical SARS-CoV-2 Omicron variant infection between November 1, 2022, and February 11, 2023. Patients were segregated into two groups based on their corticosteroid treatment—usual dose (equivalent prednisone dose 30–50 mg/day) and higher dose (equivalent prednisone dose > 50 mg/day). The primary outcome was 28-day ICU mortality. Propensity score matching was used to compare outcomes between cohorts.

Results
After propensity score matching, 520 patients in the usual dose corticosteroid group and 260 patients in the higher dose corticosteroid group were included in the analysis, respectively. The mortality was significantly higher in the higher dose corticosteroid group (67.3%, 175/260) compared to the usual dose group (56.0%, 291/520). Logistic regression showed that higher doses of corticosteroids were significantly associated with increased mortality at 28-day (OR = 1.62,95% CI 1.19–2.21, p = 0.002) and mortality in ICU stay (OR = 1.66,95% CI 1.21–2.28, p = 0.002). Different types of corticosteroids did not affect the effect.

Conclusions
The study suggests that higher-dose corticosteroids may lead to a poorer prognosis for severe and critical COVID-19 patients with Omicron variant infection in the ICU. Further research is needed to determine the appropriate corticosteroid dosage for these patients.
The self-fulfilling prophecy in medicine
Authors: Mertens Mayli 
Published: August 2024

AbstractThis article first describes the mechanism of any self-fulfilling prophecy through discussion of its four conditions: credibility, employment, employment sensitivity, and realization. Each condition is illustrated with examples specific to the medical context. The descriptive account ends with the definition of self-fulfilling prophecy and an expansion on collective self-fulfilling prophecies. Second, the normative account then discusses the moral relevance of self-fulfilling prophecies in medicine. A self-fulfilling prophecy is typically considered problematic when the prediction itself changes the predicted outcome to match the prediction (transformative self-fulfillment). I argue that also self-fulfilling prophecies that do not change the outcome but change the ways in which the outcome was realized (operative self-fulfillment), have significant ethical and epistemic ramifications. Because it is difficult to distinguish, retrospectively, between a transformative and an operative self-fulfilling prophecy, and thus between a false or true positive, it becomes equally difficult to catch mistakes. Moreover, since the prediction necessarily turns out true, there is never an error signal warning that a mistake might have been made. On the contrary, accuracy is seen as the standard for quality assurance. As such, self-fulfilling prophecies inhibit our ability to learn, inviting repetition and exacerbation of mistakes. With the rise of automated diagnostic and prognostic procedures and the increased use of machine learning and artificial intelligence for the development of predictive algorithms, attention to self-fulfilling feedback loops is especially warranted. This account of self-fulfilling prophecies is practically relevant for medical research and clinical practice. With it, researchers and practitioners can detect and analyze potential self-fulfilling mechanisms in any medical case and take responsibility for their ethical and epistemic implications.
Sand Production Prediction with Machine Learning using Input Variables from Geological and Operational Conditions in the Karazhanbas Oilfield, Kazakhstan
Authors: Shabdirova Ainash , Kozhagulova Ashirgul , Samenov Yernazar , Minh Nguyen , Zhao Yong 
Published: August 2024

AbstractThis paper describes a comprehensive approach to predict sand production in the Karazhanbas oilfield using machine learning (ML) techniques. By analyzing data from 2000 wells, the research uncovered the complex dynamics of sand production and emphasized the critical need for accurately predicting the peak sand mass and its occurrence time. ML techniques can have a significant impact on prediction of sand production and on the optimization of oilfield operation, which can be improved with the combined use of enriched training data and domain-specific knowledge. The research underscored the influence of geological factors, especially fault proximity, on prediction accuracy. Domain and field knowledge is needed to formulate different production scenarios for prediction purposes such that the relevant data can be selected for the training of ML models. Moreover, new metrics are needed to evaluate model performance as the applied method is tailored for different operational strategies. As the peak sand mass is considered a pivotal event in field operation, new metrics in terms of peak prediction accuracy and peak time prediction accuracy were introduced to evaluate the performance of ML models. A suite of ML algorithms was employed in the study, which demonstrated notable accuracy in the classification of sand-producing wells.
Spontaneous Calcium Transients Recorded from Striatal Astrocytes in a Preclinical Model of Autism
Authors: Saavedra-Bonilla Hugo , Varman Durairaj Ragu , Reyes-Haro Daniel 
Published: August 2024

AbstractAutism spectrum disorder (ASD) is known as a group of neurodevelopmental conditions including stereotyped and repetitive behaviors, besides social and sensorimotor deficits. Anatomical and functional evidence indicates atypical maturation of the striatum. Astrocytes regulate the maturation and plasticity of synaptic circuits, and impaired calcium signaling is associated with repetitive behaviors and atypical social interaction. Spontaneous calcium transients (SCT) recorded in the striatal astrocytes of the rat were investigated in the preclinical model of ASD by prenatal exposure to valproic acid (VPA). Our results showed sensorimotor delay, augmented glial fibrillary acidic protein -a typical intermediate filament protein expressed by astrocytes- and diminished expression of GABAA-ρ3 through development, and increased frequency of SCT with a reduced latency that resulted in a diminished amplitude in the VPA model. The convulsant picrotoxin, a GABAA (γ-aminobutyric acid type A) receptor antagonist, reduced the frequency of SCT in both experimental groups but rescued this parameter to control levels in the preclinical ASD model. The amplitude and latency of SCT were decreased by picrotoxin in both experimental groups. Nipecotic acid, a GABA uptake inhibitor, reduced the mean amplitude only for the control group. Nevertheless, nipecotic acid increased the frequency but diminished the latency in both experimental groups. Thus, we conclude that striatal astrocytes exhibit SCT modulated by GABAA-mediated signaling, and prenatal exposure to VPA disturbs this tuning.
Integrated risk mapping for forest fire management using the analytical hierarchy process and ordered weighted average: a case study in southern Turkey
Authors: Özcan Zühal , Caglayan İnci , Kabak Özgür , Kılıç Gül Fatmagül 
Published: August 2024

Abstract
Forest fires pose a critical problem for natural environments and human settlements, necessitating effective risk management approaches. This study focuses on forest fire risk (FFR) mapping in the Antalya Forest, southern Turkey, by analyzing different criteria. Extensive literature research identifies nearly twenty criteria, which we re-evaluate based on expert opinions and study area characteristics, leading to the selection of four main criteria and fourteen sub-criteria. We process the data using Geographic Information System (GIS) software and calculate weights using the Analytical Hierarchy Process (AHP) and Ordered Weighted Average (OWA) techniques. The main criteria are topographic, meteorological, land use, and forest structure. In the AHP sub-criteria, precipitation, tree species, distance to settlement areas, and elevation receive high values. We classify the resultant FFR maps into five risk classes using both the Jenks Natural Breaks method and equal interval classification. We evaluate the accuracy of our maps using Receiver Operating Characteristic (ROC) analysis and Area Under Curve (AUC) values, based on historical forest fire data. The equal interval classification shows decreased alignment with historical fire data, especially for the AHP method, which performs significantly worse. Both OWA and AHP methods show better performance with Jenks classification compared to equal interval classification, indicating that Jenks Natural Breaks more effectively captures natural groupings in the data, making it a more suitable choice for risk mapping. Applying AHP and OWA in FFR mapping benefits regional forest management and highlights the universal applicability of these methodologies for broader environmental hazard assessments under changing climates.
Revealing dynamic co-authorship structure in the social sciences through blockmodeling: the Slovenian case (1991–2020)
Authors: Telarico Fabio Ashtar , Mali Franc , Žiberna Aleš 
Published: August 2024

AbstractScientific cooperation is gaining importance as worldwide trends in co-authorship indicate. While clustering is an established method in this field and several have studied scientific-cooperation dynamics within a single discipline, little literature exists on its interdisciplinary facet. This paper analyses the evolution of co-authorship amongst social scientists in Slovenia over the three decades between 1991 and 2020 using bibliographic databases. The identification of groups (clusters) of authors based on patterns in their co-authorship ties both within and across decades is carried out using network-analytical method called stochastic blockmodeling (SBM). Meanwhile, previous research used generalised blockmodeling accounting only for within-period ties. Additionally, a topic model is developed to tentatively assess whether co-authorship is driven by research interests, organisational or disciplinary affiliation. Notably, while focusing on the result of the SBM for generalised multipartite networks, the paper draw compares with other SBMs. Generally, the paper identifies clusters of authors that are larger and less cohesive than those found in previous works. Specifically, there are three main findings. First, disciplines appear to become less important over time. Second, institutions remain central, corroborating the suggestion that Slovenian R&D policy reinforces parochial research practices. Yet, whether organisational segregation is an issue remains unclear. Third, interdisciplinarity’s emergence has been slow and partial, thus supporting the idea of a ‘covert interdisciplinarity.’ Importantly, it seems that members of different clusters lack fluency in a meta-language enabling effective communication across cognate paradigms. And this may hinder the implementation of long-term, up-to-date research policies in the country.
Investigating intraspecific variability in the biological responses of sea urchins (Paracentrotus lividus) to seawater acidification
Authors: Asnicar Davide , Stranci Federica , Monti Silvia , Badocco Denis , Marčeta Tihana , Munari Marco , Marin Maria Gabriella 
Published: August 2024

AbstractAlterations in seawater chemistry posed by acidification may lead to immunological and antioxidant defence impairment in sea urchins, with differences among local populations. Here, we analyzed the effects of reduced pH on Paracentrotus lividus, with a multibiomarker approach, and the possible intraspecific variations in sea urchin responses. Two groups of animals with different ecological histories (i.e., the pattern of environmental characteristics and pressures experienced throughout the organism’s lifetime) were maintained at ambient pH and pH reduced of 0.4 units for 8 months. Changes in gonadosomatic index (GSI), immunological, and oxidative stress biomarkers were assessed in coelomic fluid, gonads, and digestive tract. Animals maintained at reduced pH showed limited impact of seawater acidification compared to the ambient pH condition. However, sea urchins from the two sites were differently influenced by the seawater pH (as shown by multivariate analyses). GSI and immunological and antioxidant status were differentially modulated between the two sexes, with generally higher values in females, but differences between sexes in relation to the pH of exposure were limited. Overall, our findings highlight that the impact of environmental stressors may differ in sea urchins from different locations. This has implications for the maintenance of P. lividus wild populations under future global change scenarios.
Senolytic intervention improves cognition, metabolism, and adiposity in female APPNL−F/NL−F mice
Authors: Fang Yimin , Peck Mackenzie R. , Quinn Kathleen , Chapman Jenelle E. , Medina David , McFadden Samuel A. , Bartke Andrzej , Hascup Erin R. , Hascup Kevin N. 
Published: August 2024

AbstractSenescent cells accumulate throughout the body and brain contributing to unhealthy aging and Alzheimer’s disease (AD). The APPNL−F/NL−F amyloidogenic AD mouse model exhibits increased markers of senescent cells and the senescence-associated secretory phenotype (SASP) in visceral white adipose tissue and the hippocampus before plaque accumulation and cognitive decline. We hypothesized that senolytic intervention would alleviate cellular senescence thereby improving spatial memory in APPNL−F/NL−F mice. Thus, 4-month-old male and female APPNL−F/NL−F mice were treated monthly with vehicle, 5 mg/kg dasatinib + 50 mg/kg quercetin, or 100 mg/kg fisetin. Blood glucose levels, energy metabolism, spatial memory, amyloid burden, and senescent cell markers were assayed. Dasatinib + quercetin treatment in female APPNL−F/NL−F mice increased oxygen consumption and energy expenditure resulting in decreased body mass. White adipose tissue mass was decreased along with senescence markers, SASP, blood glucose, and plasma insulin and triglycerides. Hippocampal senescence markers and SASP were reduced along with soluble and insoluble amyloid-β (Aβ)42 and senescence-associated-β-gal activity leading to improved spatial memory. Fisetin had negligible effects on these measures in female APPNL−F/NL−F mice while neither senolytic intervention altered these parameters in the male mice. Considering women have a greater risk of dementia, identifying senotherapeutics appropriate for sex and disease stage is necessary for personalized medicine.
Graphical Abstract
Implementation Science for HIV Prevention and Treatment in Indigenous Communities: a Systematic Review and Commentary
Authors: Kemp Christopher G. , Edwards Abagail J. , White Lauren , Kore Gauri , Thurman Pamela Jumper , Gaines Tommi , King Paula Toko , Cole Marama , Orellana E. Roberto 
Published: August 2024

Abstract
Purpose of Review
We systematically reviewed implementation research conducted in Indigenous communities in the Americas and the Pacific that focused on improving delivery of HIV preventive or treatment services. We highlight strengths and opportunities in the literature and outline principles for Indigenous-led, HIV-related implementation science.

Recent Findings
We identified 31 studies, revealing a consistent emphasis on cultural tailoring of services to Indigenous communities. Common barriers to implementation included stigma, geographic limitations, confidentiality concerns, language barriers, and mistrust. Community involvement in intervention development and delivery emerged as a key facilitator, and nearly half of the studies used community-based participatory research methods. While behavioral HIV prevention, especially among Indigenous youth, was a major focus, there was limited research on biomedical HIV prevention and treatment. No randomized implementation trials were identified.

Summary
The findings underscore the importance of community engagement, the need for interventions developed within Indigenous communities rather than merely adapted, and the value of addressing the social determinants of implementation success. Aligned to these principles, an indigenized implementation science could enhance the acceptability and reach of critical HIV preventive and treatment services in Indigenous communities while also honoring their knowledge, wisdom, and strength.
Life-Suspending Technologies, Cryonics, and Catastrophic Risks
Authors: Sauchelli Andrea 
Published: August 2024

AbstractI defend the claim that life-suspending technologies can constitute a catastrophic and existential security factor for risks structurally similar to those related to climate change. The gist of the argument is that, under certain conditions, life-suspending technologies such as cryonics can provide self-interested actors with incentives to efficiently tackle such risks—in particular, they provide reasons to overcome certain manifestations of generational egoism, a risk factor of several catastrophic and existential risks. Provided we have reasons to decrease catastrophic and existential risks such as climate change, we also have a (defeasible) reason for investing in developing and making life-suspending technologies (more) widespread.
Disruptive Technologies and Open Science: How Open Should Open Science Be? A ‘Third Bioethics’ Ethical Framework
Authors: Spitale Giovanni , Germani Federico , Biller-Andorno Nikola 
Published: August 2024

AbstractThis paper investigates the ethical implications of applying open science (OS) practices on disruptive technologies, such as generative AIs. Disruptive technologies, characterized by their scalability and paradigm-shifting nature, have the potential to generate significant global impact, and carry a risk of dual use. The tension arises between the moral duty of OS to promote societal benefit by democratizing knowledge and the risks associated with open dissemination of disruptive technologies. Van Rennselaer Potter's ‘third bioethics’ serves as the founding horizon for an ethical framework to govern these tensions. Through theoretical analysis and concrete examples, this paper explores how OS can contribute to a better future or pose threats. Finally, we provide an ethical framework for the intersection between OS and disruptive technologies that tries to go beyond the simple ‘as open as possible’ tenet, considering openness as an instrumental value for the pursuit of other ethical values rather than as a principle with prima facie moral significance.
Mathematical modeling of local balance in signed networks and its applications to global international analysis
Authors: Diaz-Diaz Fernando , Bartesaghi Paolo , Estrada Ernesto 
Published: August 2024

AbstractAlliances and conflicts in social, political and economic relations can be represented by positive and negative edges in signed networks. A cycle is said to be positive if the product of its edge signs is positive, otherwise it is negative. Then, a signed network is balanced if and only if all its cycles are positive. An index characterizing how much a signed network deviates from being balanced is known as a global balance index. Here we give a step forward in the characterization of signed networks by defining a local balance index, which characterizes how much a given vertex of a signed network contributes to its global balance. We analyze the mathematical foundations and unique structural properties of this index. Then, we apply this index to the study of the evolution of international relations in the globe for the period 1816–2014. In this way we detect and categorize major historic events based on balance fluctuations, helping our understanding towards new mixed approaches to history based on network theory.
Behavioral Animal Models and Neural-Circuit Framework of Depressive Disorder
Authors: Tian Xiangyun , Russo Scott J. , Li Long 
Published: August 2024

Abstract
Depressive disorder is a chronic, recurring, and potentially life-endangering neuropsychiatric disease. According to a report by the World Health Organization, the global population suffering from depression is experiencing a significant annual increase. Despite its prevalence and considerable impact on people, little is known about its pathogenesis. One major reason is the scarcity of reliable animal models due to the absence of consensus on the pathology and etiology of depression. Furthermore, the neural circuit mechanism of depression induced by various factors is particularly complex. Considering the variability in depressive behavior patterns and neurobiological mechanisms among different animal models of depression, a comparison between the neural circuits of depression induced by various factors is essential for its treatment. In this review, we mainly summarize the most widely used behavioral animal models and neural circuits under different triggers of depression, aiming to provide a theoretical basis for depression prevention.