bluuebunny/crossref_metadata_2025_split huggingface dataset:
Safety and efficacy of tolvaptan in real‑world Japanese patients with autosomal dominant polycystic kidney disease: final results of SLOW‑PKD surveillance
Authors: Mochizuki Toshio , Muto Satoru , Suzue Kyoko , Komaniwa Satoshi , Tanaka Toshiki , Fukuta Yasuhiko , Yamashige Yuko 
Published: February 2025

Abstract

Background
Tolvaptan, a vasopressin type 2 receptor antagonist, has been used to treat autosomal dominant polycystic kidney disease in Japan since 2014.

Methods
This long-term, real-world, post-marketing surveillance (PMS) was conducted in Japan from March 2014 to March 2022. Safety was assessed based on adverse drug reactions (ADRs). For efficacy, changes in the slope of total kidney volume (TKV) and estimated glomerular filtration rate (eGFR) were assessed before and during the administration of tolvaptan.

Results
A total of 1676 patients were enrolled, with mean TKV (n = 1000) of 2149 ± 1339 mL and eGFR (n = 1641) of 44.4 ± 21.7 mL/min/1.73 m2. Frequent ADRs were hepatic function abnormal (9.6%), hyperuricaemia (8.3%), and thirst (8.1%). Most of the increased alanine aminotransferase exceeding 3 times the upper limit of the reference level occurred from 3  to  14 months after the start of treatment, but about 20% was observed after 15 months. There was no increase in ADRs over 36 months, suggesting that no other safety concerns need to be monitored during administration over 3–7 years. The mean slope of the estimated TKV increase before and during tolvaptan treatment was 6.58 and 3.71%/year, respectively (P = 0.0020). The mean slope of eGFR decline was − 3.63 and − 3.26 mL/min/1.73 m2/year, respectively (P = 0.2728).

Conclusion
There were no major problems with the safety of tolvaptan treatment, and efficacy in limiting TKV increase in this PMS was comparable to the previous, pivotal randomized control trials.

Trial registration ClinicalTrials.gov; NCT02847624.
Proximity forest 2.0: a new effective and scalable similarity-based classifier for time series
Authors: Tan Chang Wei , Herrmann Matthieu , Salehi Mahsa , Webb Geoffrey I. 
Published: February 2025

Abstract
Time series classification (TSC) is a challenging task due to the diversity of types of features that may be relevant for different classification tasks, including trends, variance, frequency, magnitude, and various patterns. To address this challenge, several alternative classes of approach have been developed. While kernel, neural network, and hybrid approaches perform well overall, some specialized approaches are better suited for specific tasks. In this paper, we propose a new similarity-based classifier, Proximity Forest version 2.0 (PF 2.0), which outperforms previous state-of-the-art similarity-based classifiers across the UCR benchmark and outperforms other state-of-the-art methods on specific datasets in the benchmark that are best addressed by similarity-base methods. PF 2.0 incorporates three recent advances in time series similarity measures — (1) computationally efficient early abandoning and pruning to speedup elastic similarity computations; (2) a new elastic similarity measure, Amerced Dynamic Time Warping (

$${{\,\textrm{ADTW}\,}}$$

ADTW

); and (3) cost function tuning. It rationalizes the set of similarity measures employed, reducing the eight base measures of the original PF to four and using the first derivative transform with all similarity measures, rather than a limited subset. It also incorporates HYDRA, a dictionary-based transform. We have re-implemented PF 1.0 and implemented PF 2.0 framework in Java, making the PF framework more efficient.
Professional Development in Autism and Multilingualism for Behavior Analysts:
Authors: Martin Loya Melanie R , Meadan Hedda , Yan Xun 
Published: February 2025

Abstract

Purpose
Autistic children and their families from heritage-language-speaking homes are underrepresented in empirical research and would benefit from receiving care tailored to their linguistic and cultural needs. Board Certified Behavior Analysts (BCBAs) commonly support autistic children in the United States but have reported limited knowledge and training in how to support bilingual children, their families, nor the bilingual staff who support them. The following research question was addressed: Do BCBA leaders in autism care who complete an asynchronous online professional development training demonstrate (a) increased knowledge, (b) improved self-efficacy, and (c) improved attitudes toward supporting multilingual Applied Behavior Analysis (ABA) staff and recipients of multilingual ABA services compared to BCBA leaders in a waitlist-control group?

Method
Part of a larger sequential exploratory mixed methods study, this randomized waitlist control trial measured the impacts of a professional development training related to autism and multilingualism in ABA care on BCBAs’ knowledge, self-efficacy, and attitudes. Social validity data were also collected and analyzed using descriptive statistics.

Results
The training significantly increased the intervention group’s knowledge and reported self-efficacy compared to participants in the waitlist control group but had no significant effect on participants’ attitudes. In addition, participants perceived the training as socially valid.

Conclusion
Implications highlight the need for more attention on professional development research for autism providers, to examine pre-service training, and for clinical leaders to examine their workplace environment to promote effective and fair practices.
Atypical Resting-State EEG Graph Metrics of Network Efficiency Across Development in Autism and Their Association with Social Cognition: Results from the LEAP Study
Authors: de Jonge E. , Garcés P. , de Bildt A. , Groen Y. , Jones E. J. H. , Mason L. , Holt R. J. , Hayward H. , Murphy D. , Oakley B. , Charman T. , Ahmad J. , Baron-Cohen S. , Johnson M. H. , Banaschewski T. , Durston S. , Oranje B. , Bölte S. , Buitelaar J. ,   The EU-AIMS LEAP group, Hoekstra P. J. , Dietrich A. 
Published: February 2025

Abstract
Autism has been associated with differences in functional brain network organization. However, the exact nature of these differences across development compared to non-autistic individuals and their relationship to autism-related social cognition, remains unclear. This study first aimed to identify EEG resting-state network characteristics in autistic versus non-autistic children, adolescents, and adults. Second, we investigated associations with social cognition measures. Analyzing resting-state EEG data from the EU-AIMS Longitudinal European Autism Project, we compared network metrics (global efficiency, clustering coefficient, and small-worldness) between 344 autistic and non-autistic individuals within and across age groups in four frequency bands (delta, theta, alpha, and beta). If significant, we explored their relationships to measures of empathy (empathy quotient), complex emotion recognition [reading the mind in the eyes task (RMET)], and theory of mind (animated shapes task). Compared to their non-autistic peers, autistic adolescents showed lower alpha global efficiency, while autistic adults showed lower alpha clustering and small-worldness. No network differences were observed among children. In adolescents, higher long-range integration was tentatively associated with higher RMET scores; in those with high autistic traits, higher long-range integration related to fewer parent-reported empathic behaviors. No brain-behavior relationships were observed in adults. Our findings suggest subtle differences in network topology between autistic and non-autistic individuals, with less efficient long-range efficiency during adolescence, and less local and overall network efficiency in adulthood. Furthermore, long-range integration may play a role in complex emotion recognition and empathy difficulties associated with autism in adolescence.
Resistance Exercise Training on Musculoskeletal, Metabolic and Psychological Health in Sedentary Office Workers – Systematic Review and Meta-analysis
Authors: Chandrasekaran Baskaran , Bairapareddy Kalyana Chakravarthy , Rao Chythra R. 
Published: February 2025

Abstract

Purpose
To consolidate the emerging evidence on the effectiveness of resistance training (RT) in reducing the health risks among sedentary office workers.

Methods
Four electronic databases were searched for evidence from its inception till september 20, 2024. Studies were included if they examined any form of RT program targeting musculoskeletal, metabolic, or psychological health outcomes in office workers aged 18 years or older using PICOS criteria (Population – office workers, Intervention – RT program, Comparison – placebo or sham control and Outcomes – musculoskeletal, cardiometabolic and psychological health variables). Two reviewers independently screened the studies for risk of bias and assessed the certainty of the evidence.

Results
Out of 60 identified studies, 17 studies were eligible for narrative synthesis, and 16 were included in the meta-analysis. Modest reductions in neck (SMD = -1.76, I2 = 88%, p < 0.00001) and shoulder discomfort (SMD = -13.29, I2 = 91%, p < 0.00001), while marginal improvement in shoulder (SMD = 4.13, I2 = 99%, p = 0.03) and neck extensor muscle strength (SMD = 9.07, I2 = 9%, p < 0.00001). The cardiometabolic and mental health risk markers remain unaltered. High uncertainty of evidence was observed due to high heterogeneity, risk of bias, inconsistency and publication bias.

Conclusion
Limited evidence demonstrate supervised RT programs of any dose has a potential to improve muscular strength and discomfort while potential cardiometabolic and mental health risk outcomes remain unaltered. However, more high-quality research trials are needed to understand the effects of RT on health benefits.
Post-selection confidence bounds for prediction performance
Authors: Rink Pascal , Brannath Werner 
Published: February 2025

Abstract
In machine learning, the selection of a promising model from a potentially large number of competing models and the assessment of its generalization performance are critical tasks that need careful consideration. Typically, model selection and evaluation are strictly separated tasks, splitting the sample at hand into training, validation, and evaluation sets, and only computing a single confidence interval for the prediction performance of the final selected model. We however regard the selection problem as a simultaneous inference problem and propose an algorithm to compute valid lower confidence bounds for multiple models that have been selected based on their prediction performance in the evaluation set. For this, we use bootstrap tilting and a maxT-type multiplicity correction. Various simulation experiments show that this leads to lower confidence bounds for the conditional performance that are at least as good as bounds from standard methods, and that reliably reach the nominal coverage probability. Also, a better performing final prediction model is selected this way, especially when the sample size is small. The approach is universally applicable for any combination of prediction models, any model selection strategy, and any prediction performance measure that accepts weights.
Concepts of self in dementia research: towards theoretical integration
Authors: van Woerkum-Rooker T. J. 
Published: February 2025

Abstract
Research on understanding the self of persons with dementia (PWD) has increased significantly in the past decades across various fields of research. This has led to a profusion of novel conceptualizations of self. Meanwhile, the rise in dementia diagnoses worldwide presents us with complex global societal and individual challenges. Since the understanding of the self of PWD is vital for improving their well-being, autonomy and care needs, this article argues that there is a need to integrate and systematize these conceptualizations of self. The current state of conceptual unclarity undermines the wellbeing of PWD, since it impedes the exchange and development of (empirical) research results and ideas. With the aim of uniting and systematizing the conceptualizations of self in research on PWD, in order to develop a pragmatic, clustered approach based on the research of the field itself which can be applied in an empirical setting with PWD, this article departs from the literature reviews from the various fields involved in the research on the self of PWD. By focusing on the theoretical overlap between the conceptualizations of self employed in these reviews, four overarching clusters of self-aspects can be formulated: minimal, embodied-embedded, reflective and socially-embedded self-aspects. These clusters jointly provide the ground for self-continuity in PWD. This clustered approach provides a framework which unites the current field of research, within which new findings can be integrated and which can be applied in an empirical setting.
Biocultural evolution, narratives, and emerging cultures of sustainability
Authors: Glynn Pierre D. , Cockerill Kristan , Helgeson Jennifer F. , Newman Gregory J. , Glynn Simone A. , White Paul A. 
Published: February 2025

Abstract
Biocultural evolution has created propensities that guide, largely unconsciously, how species think and behave. Human anthropocentrism leads to a lack of recognition of the propensities shared by Homo sapiens and other species. Human narratives and values reflect these propensities even as they also affect evolution and possible pathways of (un)sustainability for social-ecological systems (SES). Signals and narratives provide information and affective communication that simplify SES complexities and guide thought and behavior. This paper presents key propensities, signals, and a narrative typology to raise conscious awareness of their roles in shaping largely unconscious human priorities that emanate from biocultural evolution and that are unsuited to modern challenges. Four dimensions of values (i.e., experiential, utilitarian, communitarian, transcendental) are also considered, and the transcendental concept of a “realm of knowledge-ends” is presented. The concept posits that because of the cumulative knowledge that they represent, biological and cultural entities ought to be afforded worth and value as “ends-in-themselves”, transcending their immediate utilities. Local-to-regional-to-global approaches are mentioned that could help strive toward this goal and improve global SES sustainability. A case study from New Zealand illustrates how four foundational elements (biocultural propensities, signals, narratives, and values) in the conceptual framework presented by this paper can be used: (a) to enhance critical reflective thinking and analyze modern natural resources and environmental situations; and (b) to create and use records of engagement and decision-making for improved participatory processes and societal engagement. Paying attention to biocultural propensities, signals, narratives, and values can improve sustainability pathways.
Does the Self-Reported Classification on the Income Scale at the Regional Level Correlate with Quality of Life?
Authors: Murgaš František , Macků Karel , Petrovič František 
Published: February 2025

Abstract
Inspired by the well-known Easterlin paradox stating that higher income over time does not lead to a higher level of happiness, this study explores the impact of self-reported income (affluence) on the quality of life in Slovakia at two levels - national and regional. We innovatively use data from the World Value Survey on respondents’ subjective self-assignment to income groups to describe affluence, complemented with the subjective quality of life evaluation. The study reveals that while a generally positive (albeit weak) correlation exists between self-reported income and quality of life, the strength of this relationship is not uniform across all income groups - in the highest income group, this correlation is not significant. Furthermore, deviations from the general relationship exist not only across income groups but also across geographic regions. In two of the eight regions of Slovakia, but without an obvious geographical pattern, regional analysis revealed an insignificant relationship between affluence and quality of life. The findings indicate that subjective income perceptions significantly influence the quality of life assessments, but the data from subjective surveys have inherent limitations for exact quantification. Our results highlight the importance of subjective income assessments in understanding the quality of life, which has implications for public policy, particularly in addressing regional disparities within countries, and emphasise the relevance of specific data used in the context of Slovak conditions.
Professional development research on promoting productive practices for teachers’ handling of typical tasks of mathematics teaching: a systematic review
Authors: Shure Victoria , Lehmann Malte , Friesen Marita , Roesken-Winter Bettina , Prediger Susanne 
Published: February 2025

Abstract
While existing surveys on professional development (PD) programs for mathematics teachers revealed a substantial growth in PD research studies, there has been a call for more in-depth reports. Inspired by reviews on practice-based pre-service teacher education, this systematic review focuses on PD activities developed and investigated for enhancing teachers’ practices for handling relevant tasks of mathematical teaching, to provide an overview of the state of PD research for practicing teachers. To accomplish this, keywords were used to identify relevant research, complemented by hand-searched papers which are in the core of the topic yet do not use the keywords. Based on the full-text analysis of 32 peer-reviewed studies, this systematic review uncovered the emphasis of the most studies on the task of supporting and enhancing student learning followed by noticing and assessing student thinking, with variation in associated teaching practices. Differences in the level of reporting on PD activities were revealed concerning both the PD design and the research about PD. Tendencies in the types of frameworks for designing PD were also found, with almost half the studies situating teacher learning in practice. Overall, this review not only advances the field by making findings on teacher practices to handle tasks of teaching more comparable, but by gaining insights into the types of corresponding PD activities.
Juglone Encapsulation in PLGA Nanoparticles Improves Solubility and Enhances Apoptosis in HeLa Cells
Authors: Yilmaz Duygu Elif , Gumus Busra , Demirci Hasan 
Published: February 2025

Abstract
The anticancer potential of juglone, a naphthoquinone derived from walnut trees, has been extensively studied; however, its hydrophobicity and toxicity obstruct its therapeutic applications. This study aimed to overcome these challenges by encapsulating juglone into poly (lactic-co-glycolic acid) (PLGA) nanoparticles and evaluating their antiproliferative and apoptotic effects on HeLa cells. Juglone nanoparticles (JNP) were obtained by single emulsion solvent evaporation method. Its key physicochemical properties, such as particle size, zeta potential, drug loading, release yield, and encapsulation efficiency values were calculated as 207.45 ± 1.67 nm, −24.12 ± 2.21 mV, 47.80, 66.90 and 90.12%, respectively. JNP’s antiproliferative effects were compared to those of free juglone on HeLa cells. The calculated IC50 values for free juglone and JNPs were 17.07 µM and 20.64 µM, respectively. Both formulations exhibited comparable dose-dependent antiproliferative effects across the tested concentrations. However, the nanoparticle-based delivery system demonstrated enhanced apoptotic activity, as evidenced by increased caspase-3 activation and greater suppression of BCL-2 levels relative to free juglone. These findings were further corroborated by TUNEL and immunocytochemical analyses, which confirmed the superior apoptotic induction by the nanosystem. Collectively, the results highlight the potential advantages of PLGA-based nanoparticle systems for the delivery of juglone, thereby improving its water solubility—a key limiting factor for its use—while minimizing its toxicity. These findings offer a promising approach for its application as an effective anticancer agent via nanoparticle-based delivery.

Graphical Abstract
An overview of Metaverse in healthcare. Potential application in forensic and legal medicine
Authors: Ferorelli Davide , Sirago Gianmarco , Calò Francesco , Vinci Annachiara , Visci Paolo , Solarino Biagio , Dell’Erba Alessandro 
Published: February 2025

Abstract
In this review, we holistically consider healthcare as an ecosystem that includes forensic pathology and legal medicine and probe why these areas have largely ignored the use of Metaverse. This effort is directed at understanding the potential impact of virtual worlds on these areas and ultimately asks if forensic sciences are missing an opportunity or multiple opportunities. We reviewed the scientific literature to identify clinical trials and observational or other study types using PubMed Central, Web of Science, Scopus, and Cochrane, including terms related to the Metaverse and healthcare, with a screen of 1,200 relevant articles. Applications were from future clinical applications, training, treatment, prediction/prevention, and diagnosis, focusing on finding blanks in forensic and legal medicine. The study carried out in-depth research with the Metaverse regarding all areas of medicine. Despite this, significant forensic pathology or legal medicine research has yet to be identified. The gap may implicate a critical oversight in forensic areas, specifically autopsies, crime scene investigation, and field reconstruction of legal cases that could benefit from implementing virtual simulations. In this regard, incorporating virtual environments in these areas can provide new training tools, case scenarios, and even a revision mechanism for cold cases, leading to an essential trend in the evolution of legal medicine.
Transportation security at hubs: addressing key challenges across modes of transport
Authors: O’Kelly Morton E. 
Published: February 2025

Abstract
This paper examines critical vulnerabilities in transportation security across ports, highways, railways, and aviation. It highlights key threats, including cyber-attacks, terrorism, and systemic infrastructure weaknesses, demonstrating how disruptions at transport hubs can cause cascading effects on global supply chains. The analysis focuses on five strategic defense measures: networked defense, hub protection, targeted resource allocation, asymmetrical threat anticipation, and prevention-focused strategies. Findings emphasize the necessity of coordinated international security efforts, advanced monitoring technologies, and proactive risk mitigation. The paper concludes with recommendations for improved cybersecurity frameworks, enhanced operational resilience, and better human-factor considerations in transportation security.
Examples in Discrete Iteration of Arbitrary Intervals of Slopes
Authors: Contreras Manuel D. , Cruz-Zamorano Francisco J. , Rodríguez-Piazza Luis 
Published: February 2025

Abstract
Given a compact interval

$$[a,b] \subset [0,\pi ]$$

[
a
,
b
]
⊂
[
0
,
π
]

, we construct a parabolic self-map of the upper half-plane whose set of slopes is [a, b]. The nature of this construction is completely discrete and explicit: we explicitly construct a self-map and we explicitly show in which way its orbits wander towards the Denjoy–Wolff point. We also analyze some properties of the Herglotz measure corresponding to such example, which yield the regularity of such self-map in its Denjoy–Wolff point.