bluuebunny/crossref_metadata_2025_split huggingface dataset:
Unveiling therapeutic frontiers: DON/DRP-104 as innovative Plasma kallikrein inhibitors against carcinoma-associated hereditary angioedema shocks - a comprehensive molecular dynamics exploration
Authors: Oduro-Kwateng Ernest , Soliman Mahmoud E. S. 
Published: June 2024

AbstractHuman plasma kallikrein (PKa) is a member of the serine protease family and serves as a key mediator of the kallikrein-kinin system (KKS), which is known for its regulatory roles in inflammation, vasodilation, blood pressure, and coagulation. Genetic dysregulation of KKS leads to Hereditary Angioedema (HAE), which is characterized by spontaneous, painful swelling in various body regions. Importantly, HAE frequently coexists with various cancers. Despite substantial efforts towards the development of PKa inhibitors for HAE, there remains a need for bifunctional agents addressing both anti-cancer and anti-HAE aspects, especially against carcinoma-associated comorbid HAE conditions. Consequently, we investigated the therapeutic potential of the anti-glutamine prodrug, isopropyl(S)-2-((S)-2-acetamido-3-(1H-indol-3-yl)-propanamido)-6-diazo-5-oxo-hexanoate (DRP-104), and its active form, 6-Diazo-5-oxo-l-norleucine (DON), recognized for their anti-cancer properties, as novel PKa inhibitors. Utilizing structure-based in silico methods, we conducted a comparative analysis with berotralstat, a clinically approved HAE prophylactic, and sebetralstat, an investigational HAE therapeutic agent, in Phase 3 clinical trials. Inhibiting PKa with DON resulted in relatively heightened structural stability, rigidity, restricted protein folding, and solvent-accessible loop exposure, contributing to increased intra-atomic hydrogen bond formation. Conversely, PKa inhibition with DRP-104 induced restricted residue flexibility and significantly disrupted the critical SER195-HIS57 arrangement in the catalytic triad. Both DON and DRP-104, along with the reference drugs, induced strong cooperative intra-residue motion and bidirectional displacement in the PKa architecture. The results revealed favorable binding kinetics of DON/DRP-104, showing thermodynamic profiles that were either superior or comparable to those of the reference drugs. These findings support their consideration for clinical investigations into the management of carcinoma-associated HAE.
Exploring prognostic values of DNA ploidy, stroma-tumor fraction and nucleotyping in stage II colon cancer patients
Authors: Lou Yutong , Yang Lujing , Xu Shaojun , Tan Luxin , Bai Yanhua , Wang Lin , Sun Tingting , Zhou Lixin , Feng Li , Lian Shenyi , Wu Aiwen , Li Zhongwu 
Published: June 2024

Abstract
Purpose
To assess the prognostic value of three novel biomarkers, DNA ploidy, stroma-tumor fraction, and nucleotyping, seeking for more accurate stratification in stage II colon cancer.

Methods
A total of 417 patients with complete follow up information were enrolled in this study and divided into three clinical risk groups. IHC was performed to examine MSI status. DNA ploidy, stroma and nucleotyping were estimated using automated digital imaging system. Kaplan–Meier survival curves, Cox proportional hazards regression models, and correlation analyses were carried out to process our data.

Results
In the whole cohort of stage II colon cancer, nucleotyping and DNA ploidy were significant prognostic factors on OS in univariate analyses. The combination of nucleotyping and DNA ploidy signified superior OS and DFS. Difference was not significant between low-stroma and high-stroma patients. In multivariable analyses, nucleotyping and the combination of nucleotyping and DNA ploidy were proven the dominant contributory factors for OS. In the low-risk group, we found the combination of nucleotyping and DNA ploidy as the independent prognostic factor statistically significant in both univariate and multivariable, while in the high-risk group, the nucleotyping.

Conclusions
Our study has proven nucleotyping and the combination of DNA ploidy and nucleotyping as independent prognostic indicators, thus expanding the application of nucleotyping as a predictor from high risk stage II colon cancer to whole risks.
Infection episodes and islet autoantibodies in children at increased risk for type 1 diabetes before and during the COVID-19 pandemic
Authors: Zeller Ivo , Weiss Andreas , Arnolds Stefanie , Schütte-Borkovec Katharina , Arabi Sari , von dem Berge Thekla , Casteels Kristina , Hommel Angela , Kordonouri Olga , Larsson Helena Elding , Lundgren Markus , Rochtus Anne , Snape Matthew D. , Szypowka Agnieszka , Vatish Manu , Winkler Christiane , Bonifacio Ezio , Ziegler Anette-Gabriele ,   for the GPPAD Study Group
Published: June 2024

Abstract
Objectives
To determine the impact of the COVID-19 pandemic on the incidence rates of infection and islet autoimmunity in children at risk for type 1 diabetes.

Methods
1050 children aged 4 to 7 months with an elevated genetic risk for type 1 diabetes were recruited from Germany, Poland, Sweden, Belgium and the UK. Reported infection episodes and islet autoantibody development were monitored until age 40 months from February 2018 to February 2023.

Results
The overall infection rate was 311 (95% Confidence Interval [CI], 304–318) per 100 person years. Infection rates differed by age, country, family history of type 1 diabetes, and period relative to the pandemic. Total infection rates were 321 per 100 person-years (95% CI 304–338) in the pre-pandemic period (until February 2020), 160 (95% CI 148–173) per 100 person-years in the first pandemic year (March 2020—February 2021; P < 0.001) and 337 (95% CI 315–363) per 100 person-years in subsequent years. Similar trends were observed for respiratory and gastrointestinal infections. Islet autoantibody incidence rates were 1.6 (95% CI 1.0–2.4) per 100 person-years in the pre-pandemic period, 1.2 (95% CI 0.8–1.9) per 100 person-years in the first pandemic year (P = 0.46), and 3.4 (95% CI 2.3–4.8) per 100 person-years in subsequent years (P = 0.005 vs. pre-pandemic year; P < 0.001 vs. first pandemic year).

Conclusions
The COVID-19 pandemic was associated with significantly altered infection patterns. Islet autoantibody incidence rates increased two-fold when infection rates returned to pre-pandemic levels.
Research on charging strategy based on improved particle swarm optimization PID algorithm
Authors: Wang Xiuzhuo , Tang Yanfeng , Li Zeyao , Xu Chunsheng 
Published: June 2024

AbstractAiming at the electric vehicle charging pile control system has the characteristics of multi-parameter, strong coupling and non-linearity, and the existing traditional PID control and fuzzy PID control methods have the problems of slow charging speed, poor control performance and anti-interference ability, as well as seriously affecting the service life of the battery, this paper designs a kind of improved particle swarm algorithm to optimize the PID controller of the charging control system for electric vehicle charging piles, and utilizes the improved particle swarm algorithm to Adaptive and precise adjustment of proportional, integral and differential parameters, so that the system quickly reaches stability, so as to improve the accuracy of the system control output current or voltage. Simulation results show that the optimized system response speed of the improved particle swarm algorithm is improved by 3.077 s, the overshooting amount is reduced by 1.01%, and there is no oscillation, which has strong adaptability and anti-interference ability, and can significantly improve the control accuracy and charging efficiency of the charging pile control system.
Forecasting VIX using Bayesian deep learning
Authors: Hortúa Héctor J. , Mora-Valencia Andrés 
Published: June 2024

AbstractRecently, deep learning techniques are gradually replacing traditional statistical and machine learning models as the first choice for price forecasting tasks. In this paper, we leverage probabilistic deep learning for inferring the volatility index VIX. We employ the probabilistic counterpart of WaveNet, Temporal Convolutional Network (TCN), and Transformers. We show that TCN outperforms all models with an RMSE around 0.189. In addition, it has been well known that modern neural networks provide inaccurate uncertainty estimates. For solving this problem, we use the standard deviation scaling to calibrate the networks. Furthermore, we found out that MNF with Gaussian prior outperforms Reparameterization Trick and Flipout models in terms of precision and uncertainty predictions. Finally, we claim that MNF with Cauchy and LogUniform prior distributions yield well-calibrated TCN, and Transformer and WaveNet networks being the former that best infer the VIX values for one and five-step-ahead forecasting, and the probabilistic Transformer model yields an adequate forecasting for the COVID-19 pandemic period.
Network-based time series modeling for COVID-19 incidence in the Republic of Ireland
Authors: Armbruster Stephanie , Reinert Gesine 
Published: June 2024

AbstractNetwork-based time series models have experienced a surge in popularity over the past years due to their ability to model temporal and spatial dependencies, arising from the spread of infectious disease. The generalised network autoregressive (GNAR) model conceptualises time series on the vertices of a network; it has an autoregressive component for temporal dependence and a spatial autoregressive component for dependence between neighbouring vertices in the network. Consequently, the choice of underlying network is essential. This paper assesses the performance of GNAR models on different networks in predicting COVID-19 cases for the 26 counties in the Republic of Ireland, over two distinct pandemic phases (restricted and unrestricted), characterised by inter-county movement restrictions. Ten static networks are constructed, in which vertices represent counties, and edges are built upon neighbourhood relations, such as railway lines. We find that a GNAR model based on the fairly sparse Economic hub network explains the data best for the restricted pandemic phase while the fairly dense 21-nearest neighbour network performs best for the unrestricted phase. Across phases, GNAR models have higher predictive accuracy than standard ARIMA models which ignore the network structure. For county-specific predictions, in pandemic phases with more lenient or no COVID-19 regulation, the network effect is not quite as pronounced. The results indicate some robustness to the precise network architecture as long as the densities of the networks are similar. An analysis of the residuals justifies the model assumptions for the restricted phase but raises questions regarding their validity for the unrestricted phase. While generally performing better than ARIMA models which ignore network effects, there is scope for further development of the GNAR model to better model complex infectious diseases, including COVID-19.
Performance assessment of large-scale rooftop solar PV system: a case study in a Malaysian Public University
Authors: Govindarajan Logeswaran , Batcha Mohd Faizal Bin Mohideen , Abdullah Mohammad Kamil Bin 
Published: June 2024

AbstractAdopting rooftop solar PV systems in various domestic and non-domestic sectors (including commercial, industrial, and agricultural) exhibits their commitment to green energy ventures. This study intends to evaluate the effectiveness of a grid-connected solar system that has been installed so far: a 6.9 MWp photovoltaic (PV) system implemented at University Tun Hussein Onn (UTHM) in Batu Pahat, Johor. This green energy system was installed as a part of the Self-Consumption (SELCO) program utilizing a Supply Agreement for Renewable Energy (SARE) contract. To assess the mounted energy system's efficiency, performance monitoring was carried out between December 2021 and November 2022. By evaluating the enactment of the 6.9 MWp solar system at UTHM, this present work has attempted to compile the achievement of implementation of self-consumption in terms of performance analysis and financial benefits to consumer. Based on International Electrotechnical Commission (IEC) 61724 standard, this study also investigates several performance characteristics of the PV system, such as final yield, clearness index (CI), array yield, PV module efficiency, inverter efficiency, reference yield, and capacity factor (CF) performance ratio (PR). Moreover, an assessment of Carbon Dioxide ($${CO}_{2})$$

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avoidance was also conducted to quantify the amount of $${CO}_{2}$$

CO

2

reduction achieved. In addition, the self-consumption ratio and self-sufficiency ratio pattern for solar power plant in UTHM has been assessed. The monthly clearness index at the project location from December 2021 to November 2022 ranges from 0.63 to 0.66. The PV system was monitored throughout this time and generated 8529 MWh of energy. The installed PV system has shown an efficiency of 11.86%, a final yield of 108.28%, and a PR of 0.78, respectively. Further, the installed 6.9 MWp PV system at UTHM will cut $${CO}_{2}$$

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2

emissions by 5450 tons annually. The 6.9 MWp solar PV system is also estimated to reduce 25.1 RM mil in 25 years. Making the system larger to 6.9 MWp would reduce the consumption from the grid during the week, makes it possible to achieve self-consumption levels of up to 100% and self-sufficiency of this solar plant is relatively low ranges from 22 to 35%. The research finding bridges the gap between policy makers, investors, and the public regarding acceptance of the large-scale Self-Consumption (SELCO) and strengthen the strategic collaborations between solar service provider and educational bodies to support of the government’s agenda to achieve carbon emission intensity reduction in Malaysia.
Graphical Abstract
Usability Testing of a Web Tool for Dissemination and Implementation Science Models
Authors: Gomes Rebekah Natalie , Ford Bryan S. , Tabak Rachel G. , Brownson Ross C. , Malone Sara , Padek Maggie , Glasgow Russell E. , Rabin Borsika 
Published: June 2024

AbstractDissemination and Implementation science is dedicated to increasing the speed of evidence-based research translated into practice as guided by one or multiple D&I theories, models, and frameworks. The Dissemination and Implementation Models in Health Research and Practice web tool guides users on how to plan, select, combine, adapt, use, and assess theories, models, and frameworks. This paper describes usability testing to update the web tool. Iterative user testing was conducted with implementation science research and clinical participants to facilitate updates and optimize the functionality of the tool. A multi-step protocol involved quantitative and qualitative data collection including a survey, interviews, and a usability testing session. Data from the pre-testing surveys were summarized as frequencies. Data from the usability testing sessions were analyzed using a hybrid adapted deductive rapid matrix qualitative analysis. Data from the interviews were analyzed by deductive a priori coding. Fifteen interviewees represented different research and clinical groups and levels of expertise utilizing D&I TMFs. Participants were purposively selected to represent a range of disciplines and D&I expertise, all invited via one-time email. The 847 total interview comments were reduced by similarity to 259 comments, and 142 were feasible changes fitting the priorities of the web tool. Changes to content, format, and functionality are described in this paper. The iterative usability testing elicited improvements to the web tool including adding more examples, definitions, visuals, and tutorials and simplifying the written content. The web tool remains flexible for additions concerning health equity, de-implementation, and other issues.
Determinants of adolescents’ pro-sustainable behavior: a systematic literature review using PRISMA
Authors: Bhattarai Prakash C. , Shrestha Richan , Ray Subhasis , Knez Rajna 
Published: June 2024

AbstractClimate change is a serious contemporary issue around the world. Adolescents are mostly affected due to climate change. Thus, they are expected to behave in an environmentally appropriate manner, which requires the identification of factors influencing pro-sustainable behavior/pro-environmental behavior. The literature offers a wide range of factors influencing adolescents’ pro-sustainable behavior; nonetheless, these factors are not provided with some common themes. Furthermore, no study integrates dispersed research of the area with a comprehensive systematic review. With this consideration, a systematic review was carried out to find comprehensive factors influencing the pro-sustainable behavior of adolescents. For the review, all 21 interdisciplinary studies on factors influencing adolescents' ecological behavior, published between 2010 and 2023 and indexed in Scopus and Web of Science, were analyzed. The analysis revealed that the number of studies in the area increased after 2020, especially in developed countries, and most studies utilized quantitative research methods. The identified key factors influencing adolescents’ pro-environmental behavior are categorized into demographic, internal, and external factors. The findings can be helpful for future researchers to have rigorous discourse on the issue and expand the research in developing countries using mixed methods research. The policy maker can use findings to motivate adolescents to participate in climate change mitigation.
A multiscale analysis of the relationship between urbanization and CO2 emissions using geo-weighted regression model
Authors: Song Shixiong , Tan Haoqi , Zhang Ye , Ma Yongxi 
Published: June 2024

AbstractIt is of great practical significance to explore the relationship between urbanization and CO2 emissions for the low-carbon development of cities. However, the multiscale assessment of spatial relationship between population, land and economic urbanization and CO2 emissions is lacked. In this study, we first adopted the spatial statistical methods to evaluate the spatial pattern of China’s CO2 emissions in 2019. Then, we spatially quantified China’s urbanization of land, population and economy based on statistical data. Finally, we used the geo-weighted regression model to explore the spatial relationship between urbanization and CO2 emissions at the national-economic zone-province scale. The results displayed that there is obvious spatial heterogeneity in the relationship between China’s urbanization and CO2 emissions. The significant positive correlation between urbanization and CO2 emissions were mainly located in the northeastern, eastern and southwestern regions, consistent with the characteristics of the Heihe–Tengchong Line. The uneven development of land, population and economic urbanization would lead to more CO2 emissions. We suggest that China should attend the balanced development of urban land, population and economy, and avoid the additional carbon emissions caused by incongruence, to further the development of low-carbon cities.
A scoping review on occupational therapy services with forcibly displaced individuals in low to middle income countries
Authors: Hassan Humairaa , Paruk Juwairiyya , Gordhan Heema , Maseko Lebogang 
Published: June 2024

AbstractThis study underscores the distinctive role of occupational therapy in advancing the health and wellbeing of forcibly displaced individuals (FDIs), who often encounter contextual and systemic barriers and medical complications that prevent them from engaging in daily tasks. These injustices can be mitigated through health promotion and prevention strategies that aim to enhance participation in daily life activities. There has been limited research in low- to middle-income countries (LMICs) in relation to occupational therapy services for FDIs despite most FDIs originating from LMICs. To address this gap, this study adopted Arksey and O’Malley’s framework for a scoping review to consolidate existing knowledge on the occupational therapy health promotion and prevention of disease and disability services for FDIs in LMICs. Searches were conducted on six online databases. Six studies aligned with the inclusion criteria. Findings revealed that most occupational therapy services are directed towards refugees in Jordan, which contains one of the largest refugee camps. FDIs from Africa and internally displaced people receive the least number of interventions. The occupational therapy services outlined in the six sources primarily consist of health education talks, early childhood interventions, and health promotion activities centred around various occupations such as work and sports groups. Recommendations for policy guidelines include incorporating occupational therapy services within the stipulated FDI services. Our approach aims to situate the contribution of occupational therapy health promotion and prevention of disease and disability services within the broader context of FDIs’ overall health and wellbeing.
Self-compassion, burnout, and biomarkers in a sample of healthcare workers during the COVID-19 pandemic: a cross-sectional correlational study
Authors: Bégin Catherine , Gilbert-Ouimet Mahée , Truchon Manon 
Published: June 2024

Abstract
Background
Burnout among healthcare professionals is a serious problem with multiple consequences for the individuals and organizations affected. Thus, accessible and effective interventions are still needed to prevent and attenuate burnout. Self-compassion has recently been well supported in preventing and reducing burnout in various professions. Current research also demonstrated protective associations between self-compassion and well-being and/or psychological health indicators. Few studies are available on this topic during the COVID-19 pandemic or on healthcare workers from Quebec or Canada. Moreover, only a limited number of studies have looked at the associations of self-compassion with physiological variables.
This cross-sectionnal correlational study attempts to evaluate the association between self-compassion and burnout, among healthcare workers from Quebec (Canada) during the COVID-19 pandemic (n = 416 participants). Associations between their respective components are also tested. A secondary objective is to evaluate if self-compassion is also associated with a set of 38 biomarkers of inflammation (n = 83 participants), potentially associated with the physiological stress response according to the literature.
Participants meeting eligibility criteria (e.g.: residing in the province of Quebec, being 18 years of age or older, speaking French, and having been involved in providing care to COVID-19 patients) were recruited online. Participants completed the Occupational Health and Well-being Questionnaire, and some participated in a blood sample collection protocol.

Results
Results showed significant negative associations between self-compassion, exhaustion, and depersonalization, and a significant positive correlation with professional efficacy. Some self-compassion subscales (mindfulness, self-judgment, isolation, overidentification) were significantly negatively associated with certain biomarkers, even after controlling for confounding variables.

Conclusions
This study adds to the existing literature by supporting the association of self-compassion with burnout, and reveals associations between self-compassion and physiological biomarkers related to the stress response. Future research directions are discussed.