bluuebunny/crossref_metadata_2025_split huggingface dataset:
Response of host immune system to tick borne encephalitis virus
Authors: Stibraniova Iveta , Bartikova Pavlina , Dzubara Jozef 
Published: January 2025

Tick-borne encephalitis virus (TBEV, Flaviviridae), a small enveloped flavivirus with an unsegmented positive-stranded RNA genome, is the most prominent member of the mammalian group of tick-borne flaviviruses. TBEV, originally isolated in 1937, is identified as Orthoflavivirus encephalitidis now. TBEV causes the most important arboviral disease of the human central nervous system (CNS) in Europe and Northeast Asia. It is transmitted to hosts primarily by ticks of the genus Ixodes and Dermacentor, but can also be acquired by ingestion of infected unpasteurized dairy products. Approximately one-third of all human TBEV infections are associated with severe clinical neurological disease. The remaining two-thirds are asymptomatic or present with mild clinical symptoms. In hosts, TBEV tend to induce different types of immune effector mechanisms. Components of innate immunity - natural killer cells, complement proteins, macrophages and dendritic cells usually provide rapid and intense protection in the acute phase of infectious diseases. In turn, cell-mediated immunity provided by T and B lymphocytes plays an important role in virus clearance and protective immunity, and thus influences the outcome of disease. The virus-host relationship is not passive. Therefore, viruses themselves respond actively to host immune defence activities. This is made possible by a number of mechanisms that ensure their escape from the host’s immune surveillance. The aim of this review is to summarize the history of the last 50 years as well as advances in research on the immunology of TBEV, specifically in the Central European area.
Case Report: Efficacy and safety of recombinant growth hormone therapy in a girl with Loeys–Dietz syndrome
Authors: Dyrka Kamil , Jamsheer Aleksander , Bartecki Michal , Bobkowski Waldemar , Pawelec-Wojtalik Malgorzata , Rajewska-Tabor Justyna , Tomaszewska Andzelika , Balcerzak Justyna , Aniol Zuzanna , Niedziela Marek , Obara-Moszynska Monika 
Published: January 2025

BackgroundLoeys–Dietz syndrome (LDS) is a clinically and genetically heterogeneous, autosomal dominant aortic aneurysm syndrome with widespread systemic involvement. We present the case of a 16.5-year-old girl with LDS type 2 (LDS2) caused by a heterozygous pathogenic variant, c.1582C&gt;T (p.Arg528Cys), in the transforming growth factor-beta receptor type 2 (TGFBR2) gene who was treated with recombinant growth hormone (rGH) due to coexisting GH deficiency (GHD). This case report (observational study) presents the efficacy of rGH therapy and the safety aspects of this treatment, including aortal imaging follow-up (echocardiography, ECHO). To our knowledge, this is the first investigation of the effects of long-term rGH treatment on aortic dimensions in an LDS patient.Case summaryLDS was recognized in the patient in the 2nd year of life. After the 3rd year of life, growth deceleration was observed. At age 6, GHD was recognized [the maximum GH after stimulation 7.2 ng/ml; insulin-like growth factor-1 (IGF-1), 35 ng/ml; N: 84–447]. At age 6.5 years, rGH was initiated (height standard deviation score, htSDS −2.4), which continued for up to 14.25 years (htSDS-1.4). Her height at 16.5 years was 155 cm. The dose of rGH was 0.025–0.028 mg/kg/day. After the age of 16 months, widening of the aortic root was observed via echocardiography. At nearly 16 years, due to dilated aortic root (Z score +5.95), the girl underwent a plastic operation on the aorta, which had a satisfactory outcome. The patient's current status is stable, but the management of patients with LDS requires multidisciplinary cooperation due to the many coexisting comorbidities.ConclusionsAlthough aortic dilatation occurs in most LDS patients, the possible influence of GH therapy on aortic size must be considered. However, whether IGF-1, the main biochemical marker of GH activity, can be independently associated with increased aortic diameter has not been determined. In addition to its growth-promoting effect, the wide influence of GH on the human body, metabolic status, and muscle strength is also significant. The extremely low IGF-1 level before rGH therapy in the present patient and the strict monitoring of the IGF1/IGFBP3 ratio during rGH administration seem to be safe and beneficial for therapy.
Exploring the pivotal variables of tongue diagnosis between patients with chronic kidney disease and health participants
Authors: Hsu Po-Chi , Chen Jia-Ming , Chang Chia-Chu , Chang Yu-Jun , Chiu Ping-Fang , Chiang John Y. , Lo Lun-Chien 
Published: January 2025

IntroductionChronic kidney disease (CKD) is a significant global health problem associated with high morbidity and mortality rates. Traditional Chinese Medicine (TCM) utilizes tongue diagnosis to differentiate symptoms and predict prognosis. This study examines the relationship between tongue characteristics and CKD severity using an automatic tongue diagnosis system (ATDS), which captures tongue images non-invasively to provide objective diagnostic information.MethodsThis cross-sectional, case-control study was conducted from July 1, 2019, to December 31, 2021. Participants were divided into three groups based on estimated glomerular filtration rate (eGFR): control (eGFR &gt; 60 ml/min/1.732), CKD stage 3 (30 ≤ eGFR &lt; 60 ml/min/1.732), and CKD stage 4–5 (eGFR &lt; 30 ml/min/1.732). Tongue images were analyzed using ATDS to extract nine primary features: tongue shape, color, fur, saliva, fissures, ecchymosis, tooth marks, and red dots. Statistical analyses included non-parametric methods and ordinal logistic regression.ResultsThis study revealed that significant differences in the fur thickness, tongue color, amount of ecchymosis, and saliva among three groups. Ordinal logistic regression indicated that pale tongue color (OR: 2.107, P &lt; 0.001), bluish tongue color (OR: 2.743, P = 0.001), yellow fur (OR: 3.195, P &lt; 0.001), wet saliva (OR: 2.536, P &lt; 0.001), and ecchymoses (OR: 1.031, P = 0.012) were significantly associated with increased CKD severity. Additionally, each red dot and tooth mark decreased the odds of severe CKD.ConclusionTongue features such as paleness, wet saliva, yellow fur, and ecchymosis are prevalent in CKD patients and can serve as early clinical indicators of the disease. This study demonstrates that TCM tongue diagnosis, facilitated by ATDS, is a valuable, non-invasive method for identifying CKD and distinguishing its stages.
Enhancing patient education on the role of tibial osteotomy in the management of knee osteoarthritis using a customized ChatGPT: a readability and quality assessment
Authors: Fahy Stephen , Oehme Stephan , Milinkovic Danko Dan , Bartek Benjamin 
Published: January 2025

IntroductionKnee osteoarthritis (OA) significantly impacts the quality of life of those afflicted, with many patients eventually requiring surgical intervention. While Total Knee Arthroplasty (TKA) is common, it may not be suitable for younger patients with unicompartmental OA, who might benefit more from High Tibial Osteotomy (HTO). Effective patient education is crucial for informed decision-making, yet most online health information has been found to be too complex for the average patient to understand. AI tools like ChatGPT may offer a solution, but their outputs often exceed the public's literacy level. This study assessed whether a customised ChatGPT could be utilized to improve readability and source accuracy in patient education on Knee OA and tibial osteotomy.MethodsCommonly asked questions about HTO were gathered using Google's “People Also Asked” feature and formatted to an 8th-grade reading level. Two ChatGPT-4 models were compared: a native version and a fine-tuned model (“The Knee Guide”) optimized for readability and source citation through Instruction-Based Fine-Tuning (IBFT) and Reinforcement Learning from Human Feedback (RLHF). The responses were evaluated for quality using the DISCERN criteria and readability using the Flesch Reading Ease Score (FRES) and Flesch-Kincaid Grade Level (FKGL).ResultsThe native ChatGPT-4 model scored a mean DISCERN score of 38.41 (range 25–46), indicating poor quality, while “The Knee Guide” scored 45.9 (range 33–66), indicating moderate quality. Cronbach's Alpha was 0.86, indicating good interrater reliability. “The Knee Guide” achieved better readability with a mean FKGL of 8.2 (range 5–10.7, ±1.42) and a mean FRES of 60 (range 47–76, ±7.83), compared to the native model's FKGL of 13.9 (range 11–16, ±1.39) and FRES of 32 (range 14–47, ±8.3). These differences were statistically significant (p &lt; 0.001).ConclusionsFine-tuning ChatGPT significantly improved the readability and quality of HTO-related information. “The Knee Guide” demonstrated the potential of customized AI tools in enhancing patient education by making complex medical information more accessible and understandable.
Do future biology teachers bug out with higher insect-related knowledge and more positive attitudes? A comparison of different education levels
Authors: Gutowski Roxanne , Novotný Petr , Janštová Vanda , Großschedl Jörg 
Published: January 2025

IntroductionGlobal species extinction rates are increasing, with a particularly severe impact on insects. Biology teachers are crucial in raising students’ awareness of insects’ importance for the economy (e.g., food production) and ecosystems. Consequently, it is essential for biology teachers to possess comprehensive knowledge about insects and to maintain a positive attitude toward them.MethodsTherefore, our cross-sectional study examines the knowledge and attitudes of students across five educational levels with a particular focus on pre-service teachers: levels 1 to 3 represent secondary school students (n = 362) at different stages, while levels 4 and 5 represent pre-service biology teachers (n = 212) in the bachelor’s and master’s programs.Results and discussionOur results show a moderate to strong positive correlation between knowledge and attitudes across all education levels. Participants with a higher educational level have more knowledge on average. Participants in levels 1, 4, and 5 have more positive attitudes than those in levels 2 and 3. No gender differences were observed regarding knowledge but regarding attitudes, with males showing a more positive attitude.ConclusionResults indicate that pre-service biology teachers are well prepared, showing good insect-related knowledge and relatively positive attitudes.
Interactive effect of phenylalanine with duration of diabetes on the risk of small vessel disease in Chinese patients with T2DM
Authors: Zheng Jun , Zhang Wei , Miao Yu-Yang , Li Xue-Rui , Luo Wei-Ming , Yang Xi-Lin , Fang Zhong-Ze , Zhang Qiang 
Published: January 2025

AimsFew prior studies have explored the relationship between phenylalanine and diabetic small vessel disease (SVD) in patients with different durations of type 2 diabetes mellitus(T2DM). Our study aimed to explore whether phenylalanine is associated with the risk of SVD and to further explore whether phenylalanine interacted with the duration of T2DM to alter the risk of SVD.Materials and methodsA total of 1,032 T2DM patients were enrolled using the Liaoning Medical University First Affiliated Hospital (LMUFAH) system. SVD was defined as patients with diabetic nephropathy (DN) or diabetic retinopathy (DR) alone, or both. Serum amino acids were measured by mass spectrometry (MS) technology. A binary logistic regression model was used to examine associations of phenylalanine with SVD risk. Restricted cubic spline (RCS) regression was used to draw the odds ratio curves of plasma phenylalanine for SVD. Additive interaction analysis was employed to test the interaction of low phenylalanine with a long duration of T2DM for SVD.ResultsAmong the 1,032 T2DM patients, 286 (27.7%) had SVD. Phenylalanine &lt;42μmol/L was associated with a markedly increased risk of SVD (OR 1.76, 95%CI 1.23 to 2.51), which was enhanced by a duration of T2DM of ≥5 years to 4.83 (95%CI 2.97-7.87) with significant additive interactions. The inclusion of phenylalanine and duration of T2DM into a traditional risk factor model substantially increased the area under the receiver operating characteristic curve from 0.67 to 0.71 (95% CI 0.70 to 0.75) (P &lt;0.05).ConclusionsIn Chinese patients with T2DM, phenylalanine &lt;42μmol/L was associated with an increased risk of SVD, which was further amplified by a duration of T2DM of ≥5 years.
Optimization method of time of use electricity price considering losses in distributed photovoltaic access distribution network
Authors: Li Tianshou , Xu Qing , Li Weiwu , Wang Xinying , Liu Zhengying 
Published: January 2025

Currently, the time-of-use pricing model for electricity focuses on a single objective, often overlooking various factors that influence electricity costs. This oversight can lead to significant disparities in peak and off-peak electricity usage within the distribution network following optimization. Therefore, a new time of using electricity price optimization method is proposed that takes into account the losses of distributed photovoltaic access to the distribution network. Considering the topology structure of the distribution network after the integration of distributed photovoltaic, this paper calculates the comprehensive losses generated by the operation of the distribution network. Also, this paper constructs a time of use electricity price optimization mathematical model with the objectives of minimizing network loss, minimizing load variance, minimizing peak valley difference of equivalent load, and maximizing user satisfaction. And refer to the basic requirements for electricity pricing in the distribution network, set a series of constraints for optimizing electricity prices. Applying an improved imperialist competition algorithm this paper integrates Tent chaotic reverse learning to solve a multi-objective optimization model and obtain an optimized time of use electricity pricing plan. The experimental results show that after the implementation of this optimization method, the peak valley difference of the daily power load curve of the distribution network is only 350 MW, demonstrating superior peak shaving and valley filling effects.
Vulnerability analysis of power grid structure based on complex network theory
Authors: Yang Zhichun , Min Huaidong , Zhao Jie , Dong Xuzhu , Yang Fan , Wang Chenhao , Zhang Nan 
Published: January 2025

IntroductionThe key nodes of an intelligent distribution network significantly impact the reliability and stability of the distribution network’s operation. The failure of these key nodes can severely affect the safe operation of the distribution network. Therefore, vulnerability analysis of key nodes is particularly important.MethodsThis article proposes a comprehensive weighting method for evaluating indicators,combining the analytic hierarchy process (AHP) and entropy weighting method, while considering the structure and operational status of the power system grid. Key node structural evaluation indicators, such as node degree, node shrinkage centrality, and electric mediator, are established considering “significance” and “destructiveness.” State indicators are established based on the degree of impact of current, voltage, and load changes on the grid, as well as the uniformity of their distribution, including the improved current distribution entropy, voltage terre entropy, and three-phase state indicators of lost load. Subsequently, based on the AHP and entropy weighting method, a comprehensive weighting method is proposed to assign subjective and objective weights to the comprehensive evaluation indicators, obtaining the comprehensive weights of the indicators. Finally, the gray correlation degree is introduced to improve the ideal solution of the multi-objective decision making method, obtaining the criticality of the grid nodes and then identifying the critical nodes.Results and DiscussionThe example analysis presented in this article shows that the identified critical nodes of the power grid have a high degree of overlap with the identification results of different methods, can better identify edge nodes, and validate the effectiveness of the proposed evaluation indicators and key node identification methods.
The impact of green finance on carbon emission intensity in China: mediating and spatial effects
Authors: Liu Xiaonan , Lu Jinglei , Zhou Bin 
Published: January 2025

IntroductionInvestigating the relationship between green finance and carbon emission intensity is essential for understanding its role in China’s carbon reduction strategy.MethodsThis study employs the entropy weight method to measure the green finance development index across 30 Chinese provinces.Using double fixed-effects, mediation effect, and Spatial Durbin Models (SDM), the analysis reveals three key findings.ResultsFirstly, green finance directly reduces carbon emission intensity and indirectly does so by fostering technological innovation and optimizing energy structures, with more pronounced effects in western regions, highlighting regional disparities. Secondly, green finance shows a significant spatial spillover effect, reducing carbon emission intensity in neighboring provinces, beyond the impact on economically and geographically similar regions. Lastly, environmental regulation intensity positively influences carbon emission intensity in all models.DiscussionThese findings deepen our understanding of green finance’s role in China’s carbon reduction efforts and provide strong theoretical support for policy formulation, demonstrating its critical role in environmental governance and sustainable development.
Can the industrial transformation and upgrading demonstration zones policy improve urban green technology innovation? An empirical test based on old industrial cities and resource-based cities in China
Authors: Guo Bingnan , Hu Junjie , Guo Xinyan 
Published: January 2025

IntroductionWith industrial transformation and upgrading being essential to attaining sustainable growth, the pursuit of green development has grown in importance on a global scale.MethodsThis study employs a sample dataset from 2011 to 2021, utilizing the national Industrial Transformation and Upgrading Zones (ITUZ) policy interventions of 2017 and 2019 as a quasi-natural experiment. Employing a difference-in-differences approach, this paper investigates the impact and underlying mechanisms of these policies on green technology innovation, as well as their heterogeneity across different urban contexts.ResultsThe results indicate that the ITUZ policy substantially improves green technology innovation in the designated cities, a conclusion that persists across multiple robustness assessments. Subsequent mechanistic research reveals that financial development and the enhancement of industrial structures are essential avenues for the realization of green technology innovation. The heterogeneity study highlights the policy’s significant impact on green technology innovation in eastern cities, uniform demonstration zones, and old industrial cities.DiscussionThis study finishes with practical implications for policy design, indicating that it is essential to extract and share the beneficial experiences from pilot cities during the establishment of demonstration zones. It underscores the importance of synchronizing urban development policies with local characteristics to investigate varied and successful approaches for advancing green technology innovation. This research offers critical insights for policymakers and urban planners in guiding the transition of older industrial and resource-based cities toward a more sustainable and environmentally friendly future.
Characteristics of water distribution and preferential flow processes and nutrient response on dolomite slopes in the southwestern karst region
Authors: Duan Xiaoqian , Fu Zhiyong , Deng Yusong , Chen Hongsong 
Published: January 2025

Understanding the characteristics of the soil water content and preferential flow is critical for a thorough comprehension of soil nutrient loss in Karst slopes/ecosystems. We monitored the soil water content and soil temperature at 0–20, 20–40, and 40–60 cm depths on a typical Karst dolomite slope at a high frequency to determine the water distribution characteristics and confirm the occurrence of preferential flow from 2018 to 2021. The soil properties and nutrients in different soil layers during the rainy and dry seasons were determined along the slope (from upper to lower slope positions, with a total of 9 sampling sites). The results revealed that the saturated hydraulic conductivity of the soil at the upper slope position was significantly (p &lt; 0.05) greater than that at the middle and lower slope positions. The soil water content at the down slope position was greater than that at the middle and upper slope positions, further more, coupling monitoring of the soil water content and temperature revealed obvious preferential flow in the Karst dolomite slope. In addition to the spatial variability in the water content, the soil nutrients exhibited regular spatial variations. The dissolved organic carbon (DOC), dissolved organic nitrogen (DON), total nitrogen (TN), total phosphorus (TP) and total potassium (TK) contents were the lowest at the upper slope position and the highest at the down slope position, whereas the difference in nutrients between the rainy and dry seasons was the greatest at the upper slope position. Our results demonstrated that the patterns of the soil water content and surface nutrient loss are consistent along the Karst dolomite slope and are related to the occurrence of preferential flow. Furthermore, the results suggested that, compared with those in previous studies, which focused only on soil properties in the Karst regions of Southwest China, the variation in the soil water content and occurrence of preferential flow may be more important than previously assumed.