bluuebunny/crossref_metadata_2025 huggingface dataset:
Integrative analysis of lncRNAs in rheumatoid arthritis: from bioinformatics to experimental validation
Authors: Golestanifar Ahmad , Masroor Arezo , Khedri Hengameh , Saberiyan Mohammadreza , Nejatizadeh Azim
Published: February 2025

Rheumatoid arthritis (RA) is a chronic autoimmune disease characterized by progressive joint damage and systemic inflammation. Despite advances in treatment, challenges persist in early diagnosis and personalized therapy. Long non-coding RNAs (lncRNAs) have emerged as pivotal regulators in immune pathways and inflammation, offering potential as diagnostic biomarkers and therapeutic targets. Using GEO datasets (GSE169082, GSE124373), we identified differentially expressed genes in peripheral blood mononuclear cells of RA patients. Functional enrichment and pathway analyses were conducted to elucidate their roles. Key lncRNAs (LINC00963, SNHG15, SNHG3) were experimentally validated via real-time PCR in patient samples. Protein–protein interaction networks and ceRNA networks were constructed to explore molecular interactions. Analysis revealed significant up-regulation of LINC00963, SNHG15, and SNHG3 in RA patients, correlating with inflammatory markers and immune cell profiles. ROC analysis demonstrated high diagnostic potential, particularly for SNHG3 (AUC: 84.3%). Pathway enrichment highlighted immune activation and disrupted autophagic processes. This study identifies novel lncRNAs with diagnostic and therapeutic potential in RA, emphasizing the integration of computational and experimental approaches. These findings lay the groundwork for precision medicine strategies to improve RA management.
Development of 3D-structured tilt capillary valve for lab-on-a-disc devices
Authors: Murano Yuito , Yamamoto Shoji , Matsuzawa Hayato , Morioka Kazuhiro , Hemmi Akihide , Nakajima Hizuru
Published: February 2025

Lab-on-a-disc (LoD) devices utilize centrifugal force to regulate fluid movement and are widely employed in biochemical applications. LoDs facilitate biochemical analysis by integrating different essential steps such as mixing samples and reagents, separating target components from the sample, and detecting analytes in a single platform. This integration on a single disc substrate enables the miniaturization and automation of various biochemical workflows. However, current LoD systems frequently rely on active valves, which increase complexity and limit versatility. To address these challenges, this study employed 3D printing technology to develop a 3D-structured tilt capillary valve acting as a passive control mechanism. Tilt capillary valves with inclination angles ranging from 50° to 80° were fabricated, and their burst rotational speeds and repeatability were compared with those of conventional capillary and slope valves. The tilt capillary valve demonstrated superior performance, achieving high-speed fluid control with relative standard deviations ranging from 1.5 to 2.1%. This improvement was attained by distributing the effects of centrifugal and gravitational forces along the inclined flow path. Additionally, the capillary structure stabilized the effects of surface tension, further enhancing reproducibility. These findings suggest that the developed tilt capillary valve enhances the LoD system performance, enabling more precise and rapid fluid control. The enhanced passive valve presented in this study can be implemented in advanced microfluidic device designs, presenting considerable potential for biochemical assays, point-of-care applications, environmental monitoring, and food safety testing.
The narratives of war (NoW) corpus of written testimonies of the Russia-Ukraine war
Authors: Zasiekin Serhii , Zasiekina Larysa , Altman Emilie , Hryntus Mariia , Kuperman Victor
Published: February 2025

Documentation and analysis of psychological states experienced by witnesses and survivors of catastrophic events is a critical concern of psychological research. This paper introduces the new corpus of written testimonies collected from nearly 1500 Ukrainian civilians from May 2022–January 2024, during Russia’s invasion of Ukraine. The texts are available in the original Ukrainian and the English translation. The Narratives of War (NoW) corpus additionally contains demographic and geographic data on respondents, as well as their scores in tests of PTSD symptoms and moral injury. The paper provides a detailed introduction into the method of data collection and corpus structure. It also reports a quantitative frequency-based “keyness” analysis that identifies words particularly representative of the NoW corpus, as compared to the reference corpus of Ukrainian texts that predates the war with Russia. These key words shed light on the psychological state of witnesses of war. With its materials collected during the ongoing war, the corpus contributes to the body of knowledge for studies of the psychological impact of war and trauma on civilian populations.
The Exponential of the Lattice Laplacian Operator and the Mean-Square Attractor of A Stochastic Lattice System
Authors: Kloeden Peter E. , Lorenz Thomas
Published: February 2025

The exponential

$$e^{\Lambda t}$$

e

Λ
t

of the lattice Laplacian operator

$$\Lambda $$

Λ

was introduced in the 1970 s, but, unlike its counterpart for parabolic partial differential equations, has not yet been used to investigate lattice dynamical systems. Here its properties are investigated in the weighted sequence space

$$\ell _{\rho }^2$$

ℓ

ρ

2

. Then it is used to formulate and to establish the existence and uniqueness of mean-square solutions of a nonlocal stochastic lattice system with coefficient functions depending on the expectation of the solution. Finally, it is used to show that the mean-square random dynamical system so generated possesses a mean-square random attractor.
Lithium Divertor Targets and Walls for the ASTER Liquid Stellarator Reactor, Distributed Divertor
Authors: Queral V. , de Castro A. , Varela J. , Cabrera S. , Fernández I. , Spong D. , Rincón E.
Published: February 2025

Stellarators may have advantages for certain liquid metal options as Plasma Facing Components (PFC) for divertor targets and first walls due to the wide range of possible magnetic configurations, which additionally are free of disruptions and fast field variations. In a previous work (V. Queral et al., IEEE Trans. Plasma Sci. 52, 2024), a concept of stellarator reactor (ASTER-CP) based on swirling Li-molten salts and liquid lithium floating on the molten salt as PFC was presented. The divertor matters were not studied then and, thus, they are being studied and experimentally tested now.

The ASTER-CP reactor concept, the initial liquid metal experiments and potential concepts for the ASTER-CP divertor and first wall are reported. Concerning the experiments, several small scale experiments of galinstan in a small rotating cylinder under magnetic field have been produced, including one experiment with high viscosity galinstan-mixture for increased thickness of layer. An experiment of floating lithium on the molten salt LiCl-PbCl2 gave fast volatilization/decomposition of the molten salt. Particularly for divertors, the traditional free-flow, Capillary Porous Systems and ‘divertorlets’ have been studied for application to ASTER-CP. Surface waves (hot spots), lack of enough surface fluid turbulence and excessive fluid speed are the main issues found in fast free-flow. The perhaps original concept of Distributed Divertor and Equi-power Surface is tentatively proposed and studied, taking advantage of stellarator fields and low recycling regime.
Evaluation, thresholds, and practical commitments: the grammar of adjectival mildness
Authors: Beltrama Andrea
Published: February 2025

Mildly positive adjectives (henceforth, MPAs)—e.g., decent, acceptable, adequate—are typically used to express a moderately favorable evaluation of an object. In this manuscript, I present an investigation of the semantics and pragmatics of this class of expressions. I outline a proposal of MPAs as predicates whose positive form relies on particular type of functional standard which I refer to as a necessity standard: a threshold corresponding to the minimum value that an object must have in order to be pursued in compliance with the norms and requirements in place in the current world. The article provides two core contributions. On an empirical level, it enriches our understanding of the typology of gradable predicates, highlighting MPAs’ profile as strikingly overlapping with that of both relative and absolute predicates, two classes of gradable adjectives that are normally thought of as disjoint. Second, it affords a novel perspective on how gradability and modality, in conjunction with categories of human action such as value and practical commitments, are reflected in the grammatical behavior of these predicates and ultimately work together to enable us to express assessments in communication.
Bargaining Competition and Vertical Mergers: The Problem of Model Selection
Authors: Boshoff Willem H. , Froeb Luke M. , Marais Wihan , Minnie Roan J. , Tschantz Steven
Published: February 2025

The assumptions that distinguish bargaining models from one another are rarely observed, but can predetermine their predictions. In this paper, we map various popular bargaining models into vertical merger predictions across two competitive landscapes that consist of either one upstream firm and two downstream firms, or vice-versa. The models’ assumptions vary with respect to: (i) How parties bargain (Derived Demand versus Nash-in-Nash versus Nash-in-Shapley); and (ii) Over what (linear wholesale prices versus two-part prices versus quantity). The paper and accompanying online vertical merger simulator are designed to help economists and enforcers select the bargaining model that best characterizes observed pre-merger competition, and the loss of such competition following a vertical merger, in a given setting. The paper is designed to supplement the horizontal and vertical merger simulators that have been developed by economists who have served at the Federal Trade Commission and Justice Department.
Industry Compliance Costs Under the Renewable Fuel Standard: Evidence from Compliance Credits
Authors: Wardle Arthur R. , Akhundjanov Sherzod B.
Published: February 2025

The renewable fuel standard (RFS), which requires oil refineries to blend ethanol into domestic fuel supplies, is a market-based policy that implements tradable compliance credits so as better to equalize compliance costs across firms. We exploit unanticipated regulatory announcements that caused major swings in the prices of these compliance credits to retrieve reduced-form estimates of how the RFS affects the stock prices of publicly-traded refining firms. Our analysis reveals no significant stock price response among smaller firms in our sample and a small but statistically significant price response among large refiners. These findings are relevant to policy in that they cast doubt on concerns that the RFS allows integrated refiners to abuse merchant refiners. Our findings also shed light on the necessity of small refinery exemptions, which are intended to shield small, financially vulnerable refiners from RFS compliance costs.
Prediction of daily childhood asthma exacerbation from ambient meteorological, environmental risk factors and respiratory viruses, Philadelphia, PA, 2011 to 2016
Authors: Huang Wanyu , Robinson Lucy F. , Auchincloss Amy H. , Schinasi Leah H. , Moore Kari , Melly Steven , Forrest Christopher B. , Kenyon Chén C. , De Roos Anneclaire J.
Published: February 2025

Childhood asthma exacerbation has multiple risk factors that occur concurrently in the environment — including extreme meteorological conditions, air pollution, aeroallergens, and respiratory virus infections. Few studies have predicted asthma exacerbation based on multiple time-varying environmental risk factors, together. In this study, we constructed an autoregressive integrated moving average (ARIMA) model to predict “high-risk” days for childhood asthma exacerbation in Philadelphia, PA from 2011 to 2016, during the aeroallergen season of each year, using a total of 28,540 asthma exacerbation case events identified from electronic health record (EHR) data. We selected predictors from quantile weighted sum regression (gQWS), incorporating temporal lags and season-stratification (early- vs. late-season), which were entered subsequently into multivariable ARIMA models. We found that daily nitrogen dioxide (NO2), as well as monthly rhinovirus and respiratory syncytial virus (RSV) infection levels, were higher on the predicted “high-risk” days, as compared to days with lower childhood asthma exacerbation risk. The model performed better for late-season asthma exacerbation (July to October) than for early season (March to June). Future work and continued research is needed to facilitate local health guidelines pertaining to childhood asthma exacerbation.
Sex estimation with convolutional neural networks using the patella magnetic resonance image slices
Authors: Cavlak Nevin , Çınarer Gökalp , Erkoç Mustafa Fatih , Kılıç Kazım
Published: February 2025

Conducting sex estimation based on bones through morphometric methods increases the need for automatic image analyses, as doing so requires experienced staff and is a time-consuming process. In this study, sex estimation was performed with the EfficientNetB3, MobileNetV2, Visual Geometry Group 16 (VGG16), ResNet50, and DenseNet121 architectures on patellar magnetic resonance images via a developed model. Within the scope of the study, 6710 magnetic resonance sagittal patella image slices of 696 patients (293 males and 403 females) were obtained. The performance of artificial intelligence algorithms was examined through deep learning architectures and the developed classification model. Considering the performance evaluation criteria, the best accuracy result of 88.88% was obtained with the ResNet50 model. In addition, the proposed model was among the best-performing models with an accuracy of 85.70%. When all these results were examined, it was concluded that positive sex estimation results could be obtained from patella magnetic resonance image (MRI) slices without the use of the morphometric method.
Refugee Integration in Germany: The Interplay of Othering, Digital Exclusion, and Identity Negotiation
Authors: Berg Miriam
Published: February 2025

This study explores the multifaceted experiences of refugees in Hamburg, Germany, with a focus on how various forms of othering—social, cultural, linguistic, and digital—affect their integration. Through qualitative interviews with 62 refugees, the findings reveal that language acquisition, while often regarded as essential for integration, does not shield refugees from exclusion. Othering extends beyond linguistic differences, intersecting with gender, race, and religious identity, further complicating integration efforts, particularly for women. Additionally, the study identifies digital exclusion as another form of othering, termed “digital othering,” which restricts refugees’ access to social and economic participation while adversely affecting their psychological well-being and identity formation. Despite these challenges, refugees exhibit significant self-agency in navigating social and digital barriers. The findings underscore the need for a comprehensive approach to integration that transcends language proficiency and economic participation, addressing both social and digital forms of othering. This study calls for policies promoting equitable digital access, transforming digital spaces into platforms for empowerment, and fostering a more inclusive society. Drawing on social identity theory and the concept of othering, the research shows how societal narratives and digital exclusion intersect to shape refugee integration, advocating for inclusive strategies to tackle systemic inequalities.
Data Hazards as An Ethical Toolkit for Neuroscience
Authors: García Susana Román , Welsh Ceilidh , Di Cara Nina H. , Sterratt David C. , Romanò Nicola , Stefan Melanie I.
Published: February 2025

The Data Hazards framework (Zelenka, Di Cara, & Contributors, 2024) is intended to encourage thinking about the ethical implications of data science projects. It takes the form of community-designed data hazard labels, similar to warning labels on chemicals, that can encourage reflection and discussion on what ethical risks are associated with a project and how they can be mitigated. In this article, we explain how the Data Hazards framework can apply to neuroscience. We demonstrate how the hazard labels can be applied to one of our own projects, on the computational modelling of postsynaptic mechanisms.

Graphical Abstract
Retaking assessment system based on the inspiratory state of chest X-ray image
Authors: Matsubara Naoki , Teramoto Atsushi , Takei Manabu , Kitoh Yoshihiro , Kawakami Satoshi
Published: February 2025

When taking chest X-rays, the patient is encouraged to take maximum inspiration and the radiological technologist takes the images at the appropriate time. If the image is not taken at maximum inspiration, retaking of the image is required. However, there is variation in the judgment of whether retaking is necessary between the operators. Therefore, we considered that it might be possible to reduce variation in judgment by developing a retaking assessment system that evaluates whether retaking is necessary using a convolutional neural network (CNN). To train the CNN, the input chest X-ray image and the corresponding correct label indicating whether retaking is necessary are required. However, chest X-ray images cannot distinguish whether inspiration is sufficient and does not need to be retaken, or insufficient and retaking is required. Therefore, we generated input images and labels from dynamic digital radiography (DDR) and conducted the training. Verification using 18 dynamic chest X-ray cases (5400 images) and 48 actual chest X-ray cases (96 images) showed that the VGG16-based architecture achieved an assessment accuracy of 82.3% even for actual chest X-ray images. Therefore, if the proposed method is used in hospitals, it could possibly reduce the variability in judgment between operators.
Simulating nanoparticle concentration using stochastic models to improve indoor air quality in the industry
Authors: Cebolla-Alemany Joaquim , Martí Marcel Macarulla , Viana Mar , Gasso-Domingo Santiago , Moreno-Martín Verónica , Bou David , San Félix Vicenta , López-Carreño Rubén D.
Published: February 2025

In industrial scenarios, nanoparticles are incidentally generated in high concentrations during diverse material transformation processes, presenting potential health hazards for exposed workers. Consequently, as an indoor air quality management measure, their concentration is commonly reduced through localized forced ventilation. However, the control of these systems usually relies on traditional rule-based algorithms, which cannot deploy efficient control strategies such as model predictive control. To solve this issue, we propose a novel grey-box reduced order model method, never used before for industrial indoor nanoparticles. This approach can be deployed in model predictive control algorithms in buildings and does not present the data-reliance and transferability issues of black-box modeling. To test this model, a data collection campaign was conducted under real-world operating conditions in an industrial-scale thermal spraying booth, aiming to test the method’s viability for model calibration and validation of indoor total nanoparticle concentration through the maximum likelihood method, statistical validation tests, and physical viability assessment. Results for three different lumped sum models illustrate the effectiveness of grey-box modeling in industrial scenarios with confined processes and forced ventilation systems, handling observations’ noise and background concentration fluctuations, and allowing a performance comparison between models. Further research could be conducted to study the viability of indoor total nanoparticle concentration reduced order models with higher spatial resolution, non-confined sources, and natural airflows.
Genetic counselling for psychiatric conditions: exploring current perceptions of family physicians and psychiatrists in Portugal
Authors: Ribeiro B. , Homem de Melo I. , Sequeira A. , Moldovan R. , Paneque M.
Published: February 2025

Genetic counselling emerged as a specialized healthcare discipline in the 1960s, and since then, various sub-specialties have developed globally, namely and more recently, psychiatric genetic counselling. This study provides a pioneering exploration of family physicians and psychiatrists’ perceptions regarding genetic counselling provision and its potentialities in the context of psychiatric illnesses in Portugal. A qualitative methodology with semi-structured interviews was used. Among the participants, five were family physicians, and six were psychiatrists. Thematic analysis revealed three themes: (1) the role of genetics in healthcare, (2) barriers to psychiatric genetic counselling implementation, and (3) perceived benefits associated with its implementation. Results show that while the importance of genetics in psychiatric disorders is acknowledged, there is low literacy about genetic counselling practice from the professional groups interviewed. Also, the availability and mainstreaming of genetic testing seem to influence how genetic counselling is perceived and utilized. There is a perceived need for training and guidelines that foster the dissemination of genetics into healthcare, specifically mental healthcare. A holistic and patient-centred approach is considered essential in managing psychiatric disorders and, by extension, in psychiatric genetic counselling, as it addresses both medical and psychosocial factors. Although psychiatrists and family physicians are keen to integrate psychiatric genetic counselling into their patients’ care, it seems that certain fundamental challenges still persist in genetic healthcare provision. Future research should contribute for a more comprehensive evaluation of the readiness for psychiatric genetic counselling implementation in the country.
Valorization of green market waste for sequential biohydrogen and biomethane production
Authors: Özmıhçı Serpil , Hacıoğlu İlknur , Karapınar İlgi , Küs Meltem
Published: February 2025

High organic carbon wastes can be used for biofuel production for reducing raw material costs. Green market wastes (GMW) are one of the raw material candidates to generate biofuel by fermentation with low-cost production and high yield of fuel formation. Biohydrogen and biomethane are potential gaseous energy sources that can be obtained through sequential fermentation of GMW. In this study, the ground and hydrolyzed GWM (a mixture of lettuce, parsley, spring onion, and dill) solid–liquid mixture was first valorized for biohydrogen, then the organic acid-rich residue of biohydrogen fermentation was subjected to biomethane production. Biohydrogen and biomethane were produced at mesophilic (37 °C) and thermophilic (55 °C) temperatures. The initial GWM amount varied between 1000 and 5000 g ww at mesophilic biohydrogen production. The highest cumulative hydrogen formation (CHF) and the rate were obtained at 5000 g ww as CHF = 8.9 L and 916 mL H2 /L day, respectively. Thermophilic biohydrogen fermentation was conducted at 1000 and 5000 g ww and CHF reached 14.2 L at 5000 g ww GMW. The yield of hydrogen formation was 1.6 times higher at thermophilic than at mesophilic conditions. The residues from two fermentation temperatures of 5000 g ww GMW were used to produce biomethane under both fermentation conditions. Mesophilic and thermophilic conditions resulted in cumulative biomethane formations (CMF) of 8.3 L and 5.8 L, and biomethane production yields of 0.17 mL CH4/g VFA and 0.13 mL CH4/g VFA, respectively. The findings revealed that GMW is a suitable substrate for efficient biohydrogen and biomethane production.

Graphical Abstract
Operational Modeling of the Nexus Between Water-Distribution and Electricity Systems
Authors: Gu Weiying , Sioshansi Ramteen
Published: February 2025

Purpose of Review

We survey operational models of water-distribution systems. Although such modeling is important in its own right, our focus is motivated by the growing desire to examine and manage the nexus between water-distribution and electricity systems. As such, our survey discusses computational challenges in modeling water-distribution systems, co-ordination dynamics between water-distribution and electricity systems, and gaps in the literature.

Recent Findings

Modeling water-distribution systems is made difficult by their highly non-linear and non-convex physical properties. Co-ordinating water-distribution and electricity systems, especially with the growing supply and demand uncertainties of the latter, requires fast optimization techniques for real-time system management. Although many works suggest means of co-ordinating the two systems, practical applications are limited, due to the systems having separate and autonomous management and ownership. Nonetheless, recent works are navigating this challenge, by seeking methods to foster improved co-ordination of the two systems while respecting their autonomy. Additionally, with the backdrop of increased security threats, there is a growing need to bolster infrastructure protection, which is complicated by the intertwined nature of the two systems.

By providing a steady supply of potable water to satisfy residential, commercial, agricultural, and industrial demands, water-distribution systems are pivotal components of modern society and infrastructure. The extant literature presents many models and optimization strategies that are tailored for operating water-distribution systems. Yet, there remain unexplored problems, particularly related to simplifying model computation, capturing the flexibility of water-distribution systems, and capturing interdependencies between water-distribution and other systems and infrastructures. Future research that addresses these gaps will allow greater operational efficiency and resilience.
Applying the Cognitive Model of Post-Traumatic Stress to Examine the Role of Appraisals, Trauma Memory, and Coping Strategies Following Pediatric Injury: A Systematic Review
Authors: Patronick Jamie , Molloy Kelly R. , Bothwell Sabrina J. , Wade Shari L.
Published: February 2025

Following a traumatic injury, 25–57% of children will develop clinically significant post-traumatic stress symptoms (PTSS). The cognitive model of post-traumatic stress disorder posits that PTSS develop based on the encoding of trauma memories and the individual’s appraisals of the event and its sequelae. In addition, the behaviors and cognitive strategies used to cope with distress are proposed to serve as causal and maintaining factors for PTSS. The purpose of this study was to systematically review and summarize the role of psychological processing factors, including cognitive appraisals, trauma memory, and coping styles, on the development of PTSS in children following injury. Systematic searches were conducted in May 2024 for articles published at any time in PubMed, APA PsycInfo, and PTSDpubs databases. Included articles analyzed the association between cognitive appraisals, trauma memories, and/or coping strategies and PTSS in children (ages 5–18) who received medical treatment for a single-incident traumatic injury. Data were extracted related to study and sample characteristics, measures, and findings regarding the association between psychological processes and PTSS. The quality of included studies was assessed using the Quality Assessment Tool for Observational Cohort and Cross-Sectional Studies. The titles and abstracts of 836 articles were screened, and 105 full text articles were reviewed, resulting in 34 eligible articles. Articles were rated as being of “good” (44%) or “fair” (56%) quality. Studies examined cognitive appraisals (n = 18), trauma memory characteristics (n = 15), and coping strategies (n = 13). Several factors were associated with PTSS, including maladaptive cognitive appraisals, guilt, avoidant coping, and decreased cohesion, accuracy, and context in the trauma narrative. This review provides support for the cognitive model of PTSS when applied to pediatric injury populations. Limitations of the current literature are noted, including lack of evidence of temporal associations and relationships between variables in the cognitive model. Findings can be used to identify cognitive-behavioral treatment targets and ascertain the ideal timing for screening and preventative interventions.
A novel three-way distance-based fuzzy large margin distribution machine for imbalance classification
Authors: Liu Li , Guo Jinrui , Yin Ziqi , Chen Rui , Huang Guojun
Published: February 2025

Class imbalance is a prevalent issue in practical applications, which poses significant challenges for classifiers. The large margin distribution machine (LDM) introduces the margin distribution of samples to replace the traditional minimum margin, resulting in extensively enhanced classification performance. However, the hyperplane of LDM tends to be skewed toward the minority class, due to the optimization property for margin means. Moreover, the absence of non-deterministic options and measurement of the confidence level of samples further restricts the capability to manage uncertainty in imbalanced classification tasks. To solve these problems, we propose a novel three-way distance-based fuzzy large margin distribution machine (3W-DBFLDM). Specifically, we introduce a distance-based factor to mitigate the impact of sample size imbalance on classification results by increasing the distance weights of the minority class. Additionally, three-way decision model is introduced to deal with uncertainty, and the model’s robustness is further enhanced by utilizing the fuzzy membership degree that reflects the importance level of each input point. Comparative experiments conducted on UCI datasets demonstrate that the 3W-DBFLDM model surpasses other models in classification accuracy, stability, and robustness. Furthermore, the cost comparison experiment validate that the 3W-DBFLDM model reduces the overall decision cost.
Quantification of Workload Across the Careers of Division I Women’s Lacrosse Athletes: A Case Series
Authors: Gentry Jordan , Bunn Jennifer A. , Myers Bradley J.
Published: February 2025

Purpose

This study aimed to describe athlete workload over the course of a four-year collegiate lacrosse career.

Methods

Workload was evaluated each day of training and games using global positioning system microtechnology. Total workload for each athlete was calculated for each season of each year for total distance, high-intensity distance, accelerations, decelerations, and sprints. Data were tabulated as absolute and relative workloads with absolute workload representing an individual athlete and relative workload representing that athlete’s percentage of team mean workload.

Results

The workload of the entire lacrosse team was collected over four years containing the full career of six athletes. Across the five workload variables analyzed, athletes either maintained a workload near team mean workload or demonstrated an increase in workload towards the end of their careers.

Conclusion

As careers progressed, the variation in athlete workload decreased, and athletes approached the team’s average workload. Microtechnology may be useful in monitoring athlete workload over the course of a career.
Assessing the contribution of climate resilient agricultural technologies in advancing sustainable development goals in Telangana, India
Authors: Naik Boda Mahesh , Singh A. K. , Venkatesan P. , Maji Saikat , Sunil Jhade , Naik M. Ramesh
Published: February 2025

Climate change poses enormous challenges for agriculture in developing countries, impacting farmers' livelihoods. Farmers are extremely affected by their need to adapt to changing climatic variations. Climate resilient technologies are an effective means to protect farming systems from climate variability. National Innovations on Climate Resilient Agriculture (NICRA) is a flagship initiative of the Indian Council of Agricultural Research (ICAR), New Delhi which has demonstrated, and promoted the application of climate-resilient technologies in the most vulnerable 151 districts across 28 states and 1 union territory in India. This study has been conducted to investigate the extent to which CRA technologies are being adopted by the farmers in the NICRA project executed in villages of Suryapet and Khammam districts in Telangana state, India. It further studied the factors affecting the extent of adoption of CRA technologies and whether these technologies help achieve the United Nations (UN) Sustainable Development Goals (SDGs). A structured interview was carried out to obtain data from 200 respondents. Data was analyzed using normalization of the adoption index and step-wise multiple regression analysis. Results discovered medium to high levels of adoption of CRA technologies by the farmers with interventions like deep ploughing, in situ moisture conservation technologies, improved paddy varieties, crop diversification, crop rotation, deworming in sheep and goats, improved backyard poultry breeds and Custom Hiring Centres were highly adopted by the farmers. Factors like innovative proneness, availability of water resources, economic motivation, farming system, land holding, and risk-taking ability have significantly contributed to the adoption of CRA technologies. Results revealed that NICRA interventions facilitated the achievement of various SDGs, viz., SDG-1 (no poverty), SDG-2 (zero hunger), SDG-3 (good health and well-being), SDG-8 (decent work and economic growth), SDG-12 (responsible consumption and production), SDG-13 (climate action), and SDG-15 (life on land). The study recommends increasing awareness among farmers and enhancing their capacity through various programmes by extension personnel to further improve the adoption of CRA technologies and achieve SDGs.
Virtuous Wonder
Authors: MacTaggart Eric
Published: February 2025

Many theorists note the important role that wonder can play in our lives. Yet, little attention has been given to the associated character virtue; characterizations of it do not go much further than basic sketches that draw on Aristotle’s view about emotional dispositions that are proper to virtue. This paper fleshes out such sketches, which helps us understand what type of virtue this trait is. The account of virtuous wonder I develop here vindicates brief suggestions in the literature that this trait is an intellectual and aesthetic virtue and reveals in what sense it is a moral and environmental virtue.
Metamorphoses of a Monument: The Materializations of the Karabel Relief (Turkey)
Authors: Strupler Néhémie
Published: February 2025

This article examines the processes involved in materializing the past. The recording of archaeological objects plays a pivotal role in establishing artefacts as valuable data that can be categorized, classified, and analysed to turn into historical narratives. It contributes significantly to shaping our understanding of the past: while conveying information about the objects themselves, this documentation inherently captures the subjective context of its recording and continues to influence our interpretations. In this article, both objective details and subjective conceptions are analysed from the records (drawings, photographs, reports) made at the rock figure of Karabel (Turkey), a monumental bas-relief discovered by European explorers in the 1830s. The author uses Karabel's diverse and controversial interpretations to examine how knowledge and ideas about the past evolve. To counterbalance the conventional linear interpretation of the past, he offers some insights into non-academic aspects of the monument.
A Systematic Review on the Role of Glucagon-Like Peptide-1 (GLP-1) Receptor Agonists on Alcohol-Related Behaviors: Potential Therapeutic Strategy for Alcohol Use Disorder
Authors: Zheng Yang Jing , Soegiharto Crystaleene , Au Hezekiah C.T. , Valentino Kyle , Le Gia Han , Wong Sabrina , Teopiz Kayla M. , Rhee Taeho Greg , Guillen-Burgos Hernan F. , Cao Bing , McIntyre Roger S.
Published: February 2025

Introduction:

Extant literature implicates the role of glucagon-like peptide-1 (GLP-1) and GLP-1 receptor agonists (GLP-1RAs) on modulating alcohol-associated behaviors, with a particular emphasis of these agents on neural circuits subserving reward and appetite control. Herein, we explore the potential effects of GLP-1RAs on alcohol-associated behaviors in brain regions implicated in reward processing facilitating the repurposing of these agents for the treatment and prevention of problematic drinking. Understanding how GLP-1's analogs interact with alcohol-related behaviors may underscore the development of therapeutic strategies for alcohol use disorder (AUD) and those with comorbid metabolic disorders.

Methods:

A systematic review was conducted, wherein relevant literature was identified through Web of Science, PubMed, and OVID (MedLINE, Embase, AMED, PsycInfo, JBI EBP) from database inception to October 27th, 2024. Preclinical and clinical studies examining the association between GLP-1RAs and alcohol-related behaviors were assessed.

Results:

Preclinical studies (n = 19) indicate that GLP-1RAs attenuate alcohol-related behaviors, with exenatide demonstrating significant dose-dependent effects in high alcohol-consuming phenotypes. Semaglutide and liraglutide are associated with reduced alcohol intake, though their effects were often transient. In human studies (n = 2) with AUD, semaglutide significantly reduced alcohol consumption, while exenatide showed mixed results, with reductions in alcohol drinking within high BMI subpopulations.

Discussion:

Extant preclinical and clinical literature provides preliminary support for the potential therapeutic role of GLP-1RAs in attenuating alcohol consumption and preference. There is a need for large well controlled studies evaluating the effect of GLP-1RAs as a treatment strategy for behavioral modifications in individuals living with alcohol use disorder.
Classical Studies and the Public Humanities
Authors: Kindt Julia
Published: February 2025

This article introduces the reader to current work at the intersection of classical studies and the public humanities. It begins from the observation that in recent years, efforts by classical scholars to relate to a wider public have intensified and taken on a new quality. Not so long ago, public-facing research was considered detrimental to “real” scholarship. By contrast, as this article sets out to show, there is now a growing interest in a true exchange of perspectives, knowledges, and methodologies with stakeholders outside of the confines of the academe. I argue that some of the most interesting work in this space emerges from the way in which the aims and objectives of the public humanities intersect with several trends currently driving classical studies. These include the emergence of the digital humanities, the maturing of classical reception studies, and the (often difficult) conversations around calls to “decolonize” the classics.
Turbulence and transport in mirror geometries in the Large Plasma Device
Authors: Travis Phil , Carter Troy
Published: February 2025

Thanks to advances in plasma science and enabling technology, mirror machines are being reconsidered for fusion power plants and as possible fusion volumetric neutron sources. However, cross-field transport and turbulence in mirrors remains relatively understudied compared with toroidal devices. Turbulence and transport in mirror configurations were studied utilizing the flexible magnetic geometry of the Large Plasma Device (LAPD). Multiple mirror ratios from

$M=1$

to

$M=2.68$

and three mirror-cell lengths from

$L=3.51$

to

$L=10.86$

m were examined. Langmuir and magnetic probes were used to measure profiles of density, temperature, potential and magnetic field. The electric field-fluctuation-driven

${\tilde {\boldsymbol{E}}} \times {\boldsymbol{B}}$

particle flux, where

$\boldsymbol{B}$

is the background field, was calculated from these quantities. Two probe correlation techniques were used to infer wavenumbers and two-dimensional structure. Cross-field particle flux and density fluctuation power decreased with increased mirror ratio. Core density and temperatures remain similar with mirror ratio, but radial line-integrated density increased. The physical expansion of the plasma in the mirror cell by using a higher field in the source region may have led to reduced density fluctuation power through the increased gradient scale length. This increased scale length reduced the growth rate and saturation level of rotational interchange and drift-like instabilities. Despite the introduction of magnetic curvature, no evidence of mirror-driven instabilities – interchange, velocity space or otherwise – were observed. For curvature-induced interchange, many possible stabilization mechanisms were present, suppressing the visibility of the instability.
Use of surrogate endpoints in health technology assessment: a review of selected NICE technology appraisals in oncology
Authors: Wheaton Lorna , Bujkiewicz Sylwia
Published: February 2025

Objectives

Surrogate endpoints, used to substitute for and predict final clinical outcomes, are increasingly being used to support submissions to health technology assessment agencies. The increase in the use of surrogate endpoints has been accompanied by literature describing the frameworks and statistical methods to ensure their robust validation. The aim of this review was to assess how surrogate endpoints have recently been used in oncology technology appraisals by the National Institute for Health and Care Excellence (NICE) in England and Wales.

Methods

This article identifies technology appraisals in oncology published by NICE between February 2022 and May 2023. Data are extracted on the use and validation of surrogate endpoints including purpose, evidence base, and methods used.

Results

Of the 47 technology appraisals in oncology available for review, 18 (38 percent) utilized surrogate endpoints, with 37 separate surrogate endpoints being discussed. However, the evidence supporting the validity of the surrogate relationship varied significantly across putative surrogate relationships with 11 providing randomized controlled trial evidence, 7 providing evidence from observational studies, 12 based on the clinical opinion, and 7 providing no evidence for the use of surrogate endpoints.

Conclusions

This review supports the assertion that surrogate endpoints are frequently used in oncology technology appraisals in England and Wales and despite the increasing availability of statistical methods and guidance on appropriate validation of surrogate endpoints, this review highlights that use and validation of surrogate endpoints can vary between technology appraisals, which can lead to uncertainty in decision making.
The efficacy of pomegranate flower on the radiation-induced oral mucositis in the head and neck malignancy: a phase II clinical trial
Authors: Mosalaei Ahmad , Dayani Maliheh , Ansari Mansour , Nasrolahi Hamid , Mohammadianpanah Mohammad , Omidvari Shapour , Andalibi Susan , Mohammad Hosseini Ehsan
Published: February 2025

Introduction:

Oral mucositis (OM) emerged in the late 1980s to describe the adverse effects of radiation therapy (RT) on the oral mucosa. OM is the most common and clinically significant acute adverse effect of radiotherapy for head and neck cancer. Symptoms of OM vary from pain and discomfort to an inability to tolerate food or fluids, and it may affect the quality of life, breaks in treatment, hospitalisation, and therefore cancer treatment and outcome. This study aimed to evaluate the pomegranate flower’s efficacy in preventing and treating radiation-induced mucositis due to antioxidant, anti-inflammatory and anti-cancer effects.

Methods and materials:

This phase II clinical trial was conducted on 50 patients (case and control) with head and neck malignancy. Patients in the case groups were instructed to rinse their mouths with 5 mg Pomegranate powder with 15 cc of sterile water three times a day. The patients in the control group rinsed their mouths with normal saline mouthwash, which is the most relatively accepted preventive and supportive care in this setting. The onset and degree of radiation-induced mucositis were graded during treatment, with ‘WHO mucositis grading’ and the ‘quality of life questionnaire’ (QLQ-OES18).

Result:

Forty-eight patients were analysed. There was a significant difference between the two groups on onset and severity of mucositis in the two groups. There were longer intervals for the incidence of different grades of mucositis in the case group, in comparison with the control groups (P value < 0·05). Also, Complaints of dysphagia in the case groups were lower than in the control.

Conclusion:

Pomegranate flower seems to be effective at the time of onset, and the severity of oral mucositis during head and neck radiation. It could be a simple, potent, and inexpensive agent, which is easily available.
Method for determining a Prostate Cancer LET Sensitivity Index (PCLSI) using tumour-specific DDR mutations for proton RBE
Authors: Artz Mark E. , Vieceli Michael J. , Park Jiyeon , Saki Mohammad , Zhang Yawei , Brooks Eric D. , Mendenhall Nancy P. , Johnson Perry B. , Grewal Hardev S.
Published: February 2025

Purpose:

This study introduces the prostate cancer linear energy transfer sensitivity index (PCLSI) as a novel method to predict relative biological effectiveness (RBE) in prostate cancer using linear energy transfer (LET) in proton therapy based on screening for DNA repair mutations.

Materials and Methods:

Five prostate cancer cell lines with DNA repair mutations known to cause sensitivity to LET and DNA repair inhibitors were examined using published data. Relative Du145 LET sensitivity data were leveraged to deduce the LET equivalent of olaparib doses. The PCLSI model was built using three of the prostate cancer cell lines (LNCaP, 22Rv1 and Du145) with DNA mutation frequency from patient cohorts. The PCLSI model was compared against two established RBE models, McNamara and McMahon, for LET-optimized prostate cancer treatment plans.

Results:

The PCLSI model relies on the presence of eight DNA repair mutations: AR, ATM, BRCA1, BRCA2, CDH1, ETV1, PTEN and TP53, which are most likely to predict increased LET sensitivity and RBE in proton therapy. In the LET-optimized plan, the PCLSI model indicates that prostate cancer cells with these DNA repair mutations are more sensitive to increased LET than the McNamara and McMahon RBE models, with expected RBE increases ranging from 11%–33% at 2keV/µm.

Conclusions:

The PCLSI model predicts increasing RBE as a function of LET in the presence of certain genetic mutations. The integration of LET-optimized proton therapy and genetic mutation profiling could be a significant step toward the use of individualized medicine to improve outcomes using RBE escalation without the potential toxicity of physical dose escalation.