bluuebunny/crossref_metadata_2025 huggingface dataset:
School Leader Preparation in the U.S. State of Virginia: Exploring the Relationship between Data Use in Standards and Program Delivery
Authors: Meyers Coby V. , Abrams Lisa , Moon Tonya R. , Hock Michelle
Published: October 2024

National school leadership standards are now de facto curriculum for preparation programs. Data use is embedded throughout standards to guide school improvement and classroom instruction. Yet, across a number of areas, pre-service principals do not appear ready to lead once in the field. Principals are responsible for using various data to guide internal policies, school cultures, and capacity building, largely supporting teachers by establishing norms, expectations, and clear visions for data use in instructional decisions. In this study, we examined leadership preparation programs in one U.S. state to understand how data use is addressed in leader preparation. Our analysis of course description, syllabi, and program director interview data resulted in the following findings: (1) programs and courses seldom explicitly acknowledged data use as a topic; (2) when data use was acknowledged as a topic, it was infrequently tied to standards; (3) connections between data use and instructional change were limited; and (4) most programs relied on internships for leadership preparation programs to learn data use practices. There are opportunities for programs to make connections between standards, data use, and instructional improvement more explicit, as well as to clarify expectations for and increase oversight of field-based mentors.
Explaining a Logic Dendritic Neuron Model by Using the Morphology of Decision Trees
Authors: Chen Xingqian , Fan Honghui , Chen Wenhe , Zhang Yaoxin , Zhu Dingkun , Song Shuangbao
Published: October 2024

The development of explainable machine learning methods is attracting increasing attention. Dendritic neuron models have emerged as powerful machine learning methods in recent years. However, providing explainability to a dendritic neuron model has not been explored. In this study, we propose a logic dendritic neuron model (LDNM) and discuss its characteristics. Then, we use a tree-based model called the morphology of decision trees (MDT) to approximate LDNM to gain its explainability. Specifically, a trained LDNM is simplified by a proprietary structure pruning mechanism. Then, the pruned LDNM is further transformed into an MDT, which is easy to understand, to gain explainability. Finally, six benchmark classification problems are used to verify the effectiveness of the structure pruning and MDT transformation. The experimental results show that MDT can provide competitive classification accuracy compared with LDNM, and the concise structure of MDT can provide insight into how the classification results are concluded by LDNM. This paper provides a global surrogate explanation approach for LDNM.
Memoryless Multimodal Anomaly Detection via Student–Teacher Network and Signed Distance Learning
Authors: Sun Zhongbin , Li Xiaolong , Li Yiran , Ma Yue
Published: October 2024

Unsupervised anomaly detection is a challenging computer vision task, in which 2D-based anomaly detection methods have been extensively studied. However, multimodal anomaly detection based on RGB images and 3D point clouds requires further investigation. The existing methods are mainly inspired by memory bank-based methods commonly used in 2D-based anomaly detection, which may cost extra memory for storing multimodal features. In the present study, a novel memoryless method MDSS is proposed for multimodal anomaly detection, which employs a lightweight student–teacher network and a signed distance function to learn from RGB images and 3D point clouds, respectively, and complements the anomaly information from the two modalities. Specifically, a student–teacher network is trained with normal RGB images and masks generated from point clouds by a dynamic loss, and the anomaly score map could be obtained from the discrepancy between the output of student and teacher. Furthermore, the signed distance function learns from normal point clouds to predict the signed distances between points and surfaces, and the obtained signed distances are used to generate an anomaly score map. Subsequently, the anomaly score maps are aligned to generate the final anomaly score map for detection. The experimental results indicate that MDSS is comparable but more stable than SOTA methods and, furthermore, performs better than other baseline methods.
Adoption and Continuance in the Metaverse
Authors: Shin Donghyuk , Jo Hyeon
Published: October 2024

The burgeoning metaverse market, encompassing virtual and augmented reality, gaming, and manufacturing processes, presents a unique domain for studying user behavior. This study delineates a research framework to investigate the antecedents of behavioral intention, bifurcating users into inexperienced and experienced cohorts. Utilizing a cross-sectional survey, empirical data were amassed and analyzed using structural equation modeling, encompassing 372 responses from 131 inexperienced and 241 experienced users. For inexperienced users, the analysis underscored the significant impact of perceived usefulness on both satisfaction and adoption intention, while perceived enjoyment was found to bolster only satisfaction. Innovativeness and satisfaction do not drive adoption intention. Conversely, for experienced users, satisfaction was significantly influenced by perceived ease of use, perceived usefulness, and perceived enjoyment. Continuance intention was positively affected by perceived usefulness, perceived enjoyment, trust, innovativeness, and satisfaction. This research extends valuable insights for both theoretical advancements and practical implementations in the burgeoning metaverse landscape.
Robust Optimal Frequency Response Enhancement Using Energy Storage-Based Grid-Forming Converters
Authors: Rehimi Sharara , Bevrani Hassan , Tarimoradi Hadi , Urabe Chiyori T. , Kato Takeyoshi , Kato Toshiji
Published: October 2024

To enhance frequency and active power control performance, this research proposes a decentralized robust optimal tuning approach for power grid frequency regulation support using energy storage systems (ESSs) as the primary source of grid-forming (GFM) converters. The proposed approach employs the robust Kharitonov theory to find a family of stabilizing sets of a proportional-integral (PI)-based supplementary controller, which is used in the outer control layer of the GFM control system. A family of stabilizing parameter sets is found in the presence of system uncertainties and disturbances that are common in power grid operation. Then, using a developed Bayesian optimization algorithm, an optimal set of parameters is determined among the mentioned family member sets. The proposed sophisticated combination of a robust control theorem and an optimization algorithm provides a promising solution for the robust and optimal tuning of control system parameters in ESS-based GFM converters. The efficacy of the proposed method is demonstrated via simulation and laboratory real-time experiment results for a given detailed case study.
Analysis of the Measurements of the Radiated Emission from 9 kHz to 150 kHz from Electric Railways
Authors: Sadeghi Babak , Westerlund Per , Giri Manav , Bollen Math
Published: October 2024

The frequency domain measurement of radiated emissions from electric railways (from 9 kHz up to 150 kHz) has been omitted from the main part of the relevant standard (lack of repeatability and reproducibility of the results is mentioned as the reason). This paper describes the radiated emissions measured from three electric trains to emphasize the importance of the suitable time length selection (by comparing specific durations of the recorded data: 1 min and 5 min) and the influence of calculation methods of the resultant spectrum in frequency domain (RMS, mean, and Max of spectrum). The results revealed the requirement of unique definitions for pre-, during-, and post-measurement factors so that the repeatable and reproducible results could be achieved. The prerequisites for having less uncertain results are as follows: (1) pure background measurement (in energized and de-energized state of the catenary); (2) precoordinated operation mode, speed, and power of the train during the measurement; (3) precise details of the analysis step. A unique analysis method is required (to be clearly elaborated in the relevant standards) to obtain comparable results between different working groups engaged with the radiated-emission measurements from a train in a frequency range of 9 kHz to 150 kHz.
Estimation of Differential Capacity in Lithium-Ion Batteries Using Machine Learning Approaches
Authors: Odinsen Eirik , Amiri Mahshid N. , Burheim Odne S. , Lamb Jacob J.
Published: October 2024

Comprehending the electrochemical condition of a lithium-ion battery (LiB) is essential for guaranteeing its safe and effective operation. This insight is increasingly obtained through characterization tests such as a differential capacity analysis, a characterization test well suited for the electric transportation sector due to its dependency on the available voltage and current (E–I) data. However, a drawback of this technique is its time dependency, as it requires extensive time due to the need to conduct it at low charge rates, typically around C/20. This work seeks to forecast characterization data utilizing 1C cycle data at increased temperatures, thereby reducing the time required for testing. To achieve this, three neural network architectures were utilized as the following: a recurrent neural network (RNN), feed forward neural network (FNN), and long short-term memory neural network (LSTM). The LSTM demonstrated superior performance with evaluation scores of the mean squared error (MSE) of 0.49 and mean absolute error (MAE) of 4.38, compared to the FNN (MSE: 1.25, MAE: 7.37) and the RNN (MSE: 0.89, MAE: 6.05) in predicting differential capacity analysis, with all models completing their computations within a time range of 49 to 299 ms. The methodology utilized here offers a straightforward way of predicting LiB degradation modes without relying on polynomial fits or physics-based models. This work highlights the feasibility of forecasting differential capacity profiles using 1C data at various elevated temperatures. In conclusion, neural networks, particularly an LSTM, can effectively provide insights into electrochemical conditions based on 1C cycling data.
Avoid–Shift–Improve: Are Demand Reduction Strategies Under-Represented in Current Energy Policies?
Authors: Jarre Matteo , Noussan Michel , Campisi Edoardo
Published: October 2024

The Avoid–Shift–Improve framework has been used since its conception in the 1990s to help decision-makers prioritize action towards environmental sustainability in the transport sector. The core of the framework establishes a clear priority of action among the three main strategies that give it its name, thus highlighting the prominent role transport demand reduction should have within policy discussions. However, although its general formulation allows for a fruitful application to other sectors, the approach and its definitions have rarely been extended beyond transport. In particular, the energy sector could significantly benefit from an application of its methodology since the prioritization of energy demand reduction over energy efficiency would be in line with an optimized path towards decarbonization. This paper outlines a theoretical application of the A-S-I framework to the energy sector that allows the categorization of energy policies in terms of Avoid, Shift, or Improve strategies. Moreover, the paper presents an analysis of several energy policies databases to evaluate to what extent policies are addressing energy demand reduction, shift to less-carbon-intensive energy sources or energy efficiency. The results of the study show that most energy-related policies seem to support improving efficiency in current technology (18–33% of policies, depending on the database that is considered) and shifting towards low-carbon sources (28–48% of policies) more than reducing or altogether avoiding energy demand in the first place (6–22% of policies). Further research is recommended to strengthen the results, especially by evaluating the significance of each policy in terms of committed investment, as well as to understand the main factors that contribute to Avoid-type policies being under-represented in the energy sector.
Pectin Microwave Assisted Extraction from Pumpkin Peels: Process Optimization and Chemical-Physical and Rheological Characterization
Authors: Frosi Ilaria , Colombo Raffaella , Pugliese Raffaele , Milanese Chiara , Papetti Adele
Published: October 2024

Recently, pectin, a versatile polysaccharide with different industrial applications, has gained significant attention as an eco-friendly and functional ingredient. This study investigates pumpkin peels (Cucurbita maxima L., Mantua variety) as a novel source of pectin, using a microwave-assisted extraction method with citric acid-acidified water as solvent. The extraction conditions were optimized using a Design of Experiments approach, considering the solvent-to-solid ratio (SSR), pH, temperature, and extraction time. The optimized conditions (94.8 °C, 5 min, pH 1.5, and 46 mL/g SSR) resulted in a pectin yield of 18.05%. A comprehensive characterization of the extracted pectin was performed, including FT-IR spectroscopy, DSC, TGA, rheological properties, and techno-functional assessments such as water holding capacity and fat binding capacity. The results indicated a high degree of esterification (56.19 ± 0.87%), classifying the pumpkin peels (PP) extract as a high methoxyl pectin. PP pectin demonstrated potential as a stabilizer and emulsifying agent, although its high methoxyl content limits its use as a carrier for targeted bioactive delivery. The findings support the viability of using agricultural by-products to obtain valuable polysaccharides, contributing to waste valorization and sustainable industrial practices.
Fractal Analysis and Fractal Dimension in Materials Chemistry
Authors: Dobrescu Gianina , Papa Florica , State Razvan
Published: October 2024

Using fractal analysis and computing fractal dimension to understand materials chemistry and solve problems such as catalysis, chemical reactions, fuel storage, and material design is an important scientific research domain [...]
Fractional Reverse Inequalities Involving Generic Interval-Valued Convex Functions and Applications
Authors: Bin-Mohsin Bandar , Javed Muhammad Zakria , Awan Muhammad Uzair , Meftah Badreddine , Kashuri Artion
Published: October 2024

The relation between fractional calculus and convexity significantly impacts the development of the theory of integral inequalities. In this paper, we explore the reverse of Minkowski and Hölder’s inequality, unified Jensen’s inequality, and Hermite–Hadamard (H-H)-like inequalities using fractional calculus and a generic class of interval-valued convexity. We introduce the concept of I.V-(⋏,ℏ) generic class of convexity, which unifies several existing definitions of convexity. By utilizing Riemann–Liouville (R-L) fractional operators and I.V-(⋏,ℏ) convexity to derive new improvements of the H-H- and Fejer and Pachpatte-like inequalities. Our results are quite unified; by substituting the different values of parameters, we obtain a blend of new and existing inequalities. These results are fruitful for establishing bounds for I.V R-L integral operators. Furthermore, we discuss various implications of our findings, along with numerical examples and simulations to enhance the reliability of our results.
Genomic and Transcriptional Analysis of the Necroptosis Pathway Elements RIPK and MLKL in Sea Cucumber, Holothuria leucospilota
Authors: Chen Rong , Huang Qianying , Rao Yingzhu , Wang Junyan , Yu Ruiming , Peng Shuangxin , Huang Kaiyi , Huang Yihang , Zhu Xiangxing , Tang Dongsheng , Zhang Xiaoli , Lin Tiehao , Chen Ting , Yan Aifen
Published: October 2024

Background: Receptor-interacting protein kinases (RIPKs) and mixed-lineage kinase domain-like protein (MLKL) are crucial in regulating innate immune responses and cell death signaling (necroptosis and apoptosis), and are potential candidates for genetic improvement in breeding programs. Knowledge about the RIPK family and MLKL in sea cucumber remains limited. Methods: We searched the genomes of sea cucumber Holothuria leucospilota for genes encoding RIPKs and MLKL, performed phylogenetic tree, motif and functional domain analyses, and examined tissue distribution and embryonic development patterns using qPCR. Results: RIPK5 (Hl-RIPK5), RIPK7 (Hl-RIPK7) and MLKL (Hl-MLKL) were identified in sea cucumber H. leucospilota. Hl-RIPK5 and Hl-RIPK7 were mainly expressed in coelomocytes, suggesting that they play a role in innate immunity, whereas Hl-MLKL exhibited relatively low expression across tissues. During embryonic development, Hl-MLKL was highly expressed from the 2-cell stage to the morula stage, while Hl-RIPK5 and Hl-RIPK7 were primarily expressed after the morula stage, indicating different roles in embryonic development. In primary coelomocytes, Hl-RIPK5 transcriptional activity was significantly depressed by LPS, poly(I:C), or pathogen Vibrio harveyi. Hl-RIPK7 expression levels were unchanged following the same challenges. Hl-MLKL mRNA levels were significantly decreased with poly(I:C) or V. harveyi, but did not change with LPS. Conclusions: These findings provide valuable insights into the evolutionary tree and characterization of RIPK and MLKL genes in sea cucumber, contributing to the broader understanding of the RIPK gene family and MLKL in ancient echinoderms.
Metabolic Cinema: From Hollywood to Socialist China
Authors: Zhu Ping
Published: October 2024

Drawing on Karl Marx’s ecological concepts of the “metabolic rift” and the “emancipation of senses”, this paper explores an alternative ecocinema that integrates the ecological with the social and the economic. Early Hollywood films, such as Sunrise: A Song of Two Humans (1927) and The Good Earth (1937), represent the metabolic rift in human relationships as a byproduct of the metabolic rift with nature created in the process of urbanization; hence, they can be regarded as precursors to an alternative ecocinema, which I refer to as “metabolic cinema”. The Story of the Golden Bell (Jinling Zhuan), a comedy film produced during the Chinese Great Leap Forward in 1958, offers an intriguing case for socialist metabolic cinema as a multisensory medianature that participates in and facilitates the metabolic process between humans and nature, as well as the social metabolism among humans, despite the period’s notorious ecological record. The film not only consciously moves away from the visual-centric model associated with capitalist consumerism by using the aural to rectify the once-aberrant visual but also demonstrates how romantic love, as one of the human senses, must be emancipated along with other senses through denouncing utilitarianism and commercialism and, subsequently, returning to need-based labor as the universal condition for the metabolic interaction between humans and nature.
What Evidence Exists to Support Palliative Allied Health Practice in Aged Care: A Scoping Review
Authors: Farrer Olivia , Tieman Jennifer
Published: October 2024

Background: As our population ages, the demand for aged care services and palliative care is expected to increase. Allied health professionals have a diverse set of skills to offer in the management of older adults. This scoping review aimed to identify what evidence exists to support the best practice of allied health clinicians in palliative and aged care. Methods: Searches were conducted using broad keywords and MeSH headings with relevance to palliative, ageing and allied health care in the databases Ovid MEDLINE (R), CINAHL, EMCARE, INFORMIT, REHABDATA, PEDRO and SCOPUS, as well as the grey literature. Results: Only 15 studies met the inclusion criteria. A prominent finding was that regular exercise interventions delivered improved mobility, balance, sleep and quality of life outcomes when measured (n = 5). Broader allied health input and outcomes, such as nutrition, were not well described, other than to suggest an interprofessional approach contributed to health benefits where these were observed. Conclusions: The lack of research creates uncertainty about what excellent care looks like and how it can be measured, making it harder for allied health professionals to advocate for funded time in providing care at the end of life and leading to poorer outcomes for older adults.
Athlete Perspectives on Concussion Recognition and Management in Gaelic Games: A Qualitative Analysis
Authors: Daly Ed , Ryan Lisa
Published: October 2024

Background: The focus of this qualitative research was to interview current and retired Gaelic games athletes to ascertain how athletes viewed concussion recognition and management. Methods: A grounded theory methodology design was utilised to investigate concussion recognition and management experiences of a cohort of Gaelic games athletes (n = 22). Data for the study were collected using a semi-structured interview format. Results: Two major themes were identified: (1) an inconsistent identification of concussion as an injury and the absence of standardised procedures for removal from play, and (2) the impact of athlete-driven decision making on concussion management. Concussions were experienced by all the participants on multiple occasions while playing Gaelic games. However, concussion recognition and removal rarely occurred, as many athletes chose not to disclose their injuries or self-managed their concussions. Conclusions: The recognition and management of concussions in Gaelic games are currently inadequate, and they may be posing significant risks to athletes’ long-term health. This research highlights the need for more stringent protocols for concussion recognition and removal at pitch side. In addition, Gaelic games require a more objective injury management plan during acute and chronic concussion recovery.
Effects of Water-Deficit Stress on the Growth and Physiological Characteristics of Chloranthus spicatus Seedlings
Authors: Shang Yangjuan , Wan Zhibing , Zhao Changheng , Su Xing , Liu Xinyi
Published: October 2024

Chloranthus spicatus is one of the main scented tea varieties cultivated mainly in the Huangshan region, and dried flowers of these plants are mainly used for imparting a characteristic aroma to the tea. However, climatic variations in Huangshan limit its cultivation, with water deficit (WD) being the main limiting factor. The present study evaluated the effects of different WD intensities on the growth and physiological parameters of C. spicatus seedlings to determine the optimal soil moisture content for their large-scale cultivation. The experimental design comprised a control group (95–100%) and three treatment groups, namely mild WD (75–80%), moderate WD (55–60%), and severe WD (35–40%). Each treatment lasted 45 days and was given to 10 potted C. spicatus seedlings, with 3 replicates. Measurements were conducted for the shoot length and diameter; biomass; photosynthesis parameter; activities of antioxidant enzymes, namely superoxide dismutase (SOD), peroxidase (POD), and catalase (CAT); and soluble protein (SP) and malonylaldehyde (MDA) contents of the seedlings. The results indicated that mild and moderate WD positively affected C. spicatus seedlings in terms of shoot length, diameter, biomass, root/shoot ratio, photosynthesis rate, intercellular CO2 concentration, water use efficiency, and carboxylation efficiency. Moreover, the growth and photosynthesis were increased in the mild and moderate WD seedlings but decreased in the severe WD seedlings. Mild and moderate WD also led to a significant decrease in the antioxidant enzyme activities and the MDA content of seedlings (p < 0.05), all of which exhibited higher levels in severe WD seedlings. These results indicated that severe water stress restricted the growth of seedlings, while mild and moderate stress proved beneficial. SP content of the seedlings increased under mild and moderate WD but decreased under severe WD. We infer that the strong hydrophilicity of SPs in the seedlings results in the accumulation of water in plant cells, thus conferring resistance to drought stress. In conclusion, reducing the soil moisture content by 55–80% in the Huangshan region may be a promising strategy for boosting its cultivation.
Energy Efficiency of Glasshouses and Plant Factories for Sustainable Urban Farming in the Desert Southwest of the United States of America
Authors: Azad Md , Gruda Nazim , Naznin Most
Published: October 2024

The extreme heat and water scarcity of the desert southwest in the United States of America present significant challenges for growing food crops. However, controlled-environment agriculture offers a promising solution for plant production in these harsh conditions. Glasshouses and plant factories represent advanced but energy-intensive production methods among controlled-environment agriculture techniques. This review aims to comprehensively assess how controlled-environment agriculture can thrive and be sustained in the desert southwest by evaluating the energy efficiency of controlled glasshouses and building-integrated plant factories. The analysis focuses on the efficiency of these systems’ energy and water consumption, mainly using artificial lighting, heating, cooling, ventilation, and water management through various hydroponic techniques. Approximately 50% of operational energy costs in controlled glasshouses are dedicated to cooling, whereas 25–30% of energy expenses in building-integrated plant factories are allocated to artificial lighting. Building-integrated plant factories with aeroponic systems have demonstrated superior water use and energy efficiency compared to controlled glasshouses in desert environments. Integrating photovoltaic solar energy and glass rooftops in building-integrated plant factories can significantly reduce energy costs for urban farming in the desert southwest.
Characterization of AGAMOUS Ortholog and Promoter from the Ilex verticillata (Aquifoliaceae)
Authors: Li Jiayi , Su Yalan , Chen Xiangjian , Liu Zhixiong
Published: October 2024

Arabidopsis AGAMOUS (AG) plays a crucial role in specifying stamen and carpel identities, floral meristem identity determination, and repression of the A-function. Ilex verticillata (Aquifoliaceae) is a dioecious shrub, whereby an individual plant has either male or female flowers with vestigial organs of the opposite sex. The molecular mechanism of male and female organ development in I. verticillata remains unknown. In order to identify the possible roles of AG-like genes in regulating floral development in I. verticillata, AG ortholog (IlveAG) and its promoter (pIlveAG) from the male and female flowers of I. verticillata were separately isolated. IlveAG is highly expressed in stamens, pistils, and sepals of male and female flowers. Moreover, obvious GUS staining was observed in the inflorescence and sepals, stamens, and pistils of mature flowers in pIlveAG::GUS Arabidopsis. The 35S::IlveAG Arabidopsis showed obviously early flowering. Moreover, IlveAG could substitute for endogenous AG to rescue the stamen and pistil in the Arabidopsis ag-1 mutant. In addition, expression of IlveAG can inhibit the development of sepals and petals (two outer whorls of floral organs) in wild-type and ag-1 Arabidopsis. Our findings suggest that IlveAG has a conservative C-function and plays key roles in determination of reproductive floral organs (stamen and carpel) identity and meristem determinacy. Our results provide more details to understand the role of AG orthologs in the development of male and female flowers in woody plants.
Short-Term Drought Forecast across Two Different Climates Using Machine Learning Models
Authors: Piraei Reza , Niazkar Majid , Gangi Fabiola , Eryılmaz Türkkan Gökçen , Afzali Seied Hosein
Published: October 2024

This paper presents a comparative analysis of machine learning (ML) models for predicting drought conditions using the Standardized Precipitation Index (SPI) for two distinct stations, one in Shiraz, Iran and one in Tridolino, Italy. Four ML models, including Artificial Neural Network (ANN), Multiple Linear Regression, K-Nearest Neighbors, and XGBoost Regressor, were employed to forecast multi-scale SPI values (for 6-, 9-, 12-, and 24-month) considering various lag times. Results indicated that the ML model with the most robust performance varied depending on station and SPI duration. Furthermore, ANN demonstrated robust performance for SPI estimations at Shiraz station, whereas no single model consistently outperformed the others for Tridolino station. These findings were further validated through the confidence percentage analysis performed on all ML models in this study. Across all scenarios, longer SPI durations generally yielded better model performance. Additionally, for Shiraz station, optimal lag times varied by SPI duration: 6 months for the 6- and 9-month SPI, 4 months for the 12-month SPI, and 2 months for the 24-month SPI. For Tridolino station, on the other hand, no definitive optimal lag time was identified. These findings contribute to our understanding of predicting drought indicators and supporting effective water resource management and climate change adaptation efforts.
Why Is Caries Prevention in Children So Difficult? A Narrative Opinion
Authors: Twetman Svante
Published: October 2024

Caries is among the most common non-communicable diseases worldwide, yet it is commonly described as preventable. Caries prevention is, however, difficult and complex, since the disease has strong social, parental, behavioral, political, medical/genetic, and psychological elements, and the payment models are targeted at traditional conservative care. The aim of this paper is to discuss some key issues that make caries prevention in children be perceived as “difficult”: i) the communication gap between researchers and clinicians, creating unrealistic expectations of intervention efficacy; ii) the skewed distribution of caries and the problem of reaching children with the highest need; iii) limited access to care, which is a threat to oral health, in particular in low-socioeconomic-status, underserviced, and remote communities; and iv) the need to adopt behavior change models to affect the modifiable risk factors that are shared with other non-communicable diseases. Dentists cannot simply rely on fluoride exposure; proper education and training in caries risk assessment, behavior change models targeted at oral hygiene and sugar intake, and collaboration with primary healthcare and local school authorities are avenues that aid in caries prevention and reduce the uneven burden of the disease. Online education and mobile apps may help to promote oral health in areas with shortages of dental work force.
Contextual Enrichment of Crowds from Mobile Phone Data through Multimodal Geo-Social Media Analysis
Authors: Honzák Klára , Schmidt Sebastian , Resch Bernd , Ruthensteiner Philipp
Published: October 2024

The widespread use of mobile phones and social media platforms provides valuable information about users’ behavior and activities. Mobile phone data are rich on positional information, but lack semantic context. Conversely, geo-social media data reveal users’ opinions and activities, but are rather sparse in space and time. In the context of emergency management, both data types have been considered separately. To exploit their complementary nature and potential for emergency management, this paper introduces a novel methodology for improving situational awareness with the focus on urban events. For crowd detection, a spatial hot spot analysis of mobile phone data is used. The analysis of geo-social media data involves building spatio-temporal topic-sentiment clusters of posts. The results of the spatio-temporal contextual enrichment include unusual crowds associated with topics and sentiments derived from the analyzed geo-social media data. This methodology is demonstrated using the case study of the Vienna Pride. The results show how crowds change over time in terms of their location, size, topics discussed, and sentiments.
The Modulation of Septic Shock: A Proteomic Approach
Authors: Alves Patrícia Terra , de Souza Aline Gomes , Bastos Victor Alexandre F. , Miguel Eduarda L. , Ramos Augusto César S. , Cameron L. C. , Goulart Luiz Ricardo , Cunha Thúlio M.
Published: October 2024

Sepsis poses a significant challenge due its lethality, involving multiple organ dysfunction and impaired immune responses. Among several factors affecting sepsis, monocytes play a crucial role; however, their phenotype, proteomic profile, and function in septic shock remain unclear. Our aim was to fully characterize the subpopulations and proteomic profiles of monocytes seen in septic shock cases and discuss their possible impact on the disease. Peripheral blood monocyte subpopulations were phenotype based on CD14/CD16 expression by flow cytometry, and proteins were extracted from the monocytes of individuals with septic shock and healthy controls to identify changes in the global protein expression in these cells. Analysis using 2D-nanoUPLC-UDMSE identified 67 differentially expressed proteins in shock patients compared to controls, in which 44 were upregulated and 23 downregulated. These proteins are involved in monocyte reprogramming, immune dysfunction, severe hypotension, hypo-responsiveness to vasoconstrictors, vasodilation, endothelial dysfunction, vascular injury, and blood clotting, elucidating the disease severity and therapeutic challenges of septic shock. This study identified critical biological targets in monocytes that could serve as potential biomarkers for the diagnosis, prognosis, and treatment of septic shock, providing new insights into the pathophysiology of the disease.
Cordyceps militaris Grown on Germinated Rhynchosia nulubilis (GRC) Encapsulated in Chitosan Nanoparticle (GCN) Suppresses Particulate Matter (PM)-Induced Lung Inflammation in Mice
Authors: Park Byung-Jin , Dhong Kyu-Ree , Park Hye-Jin
Published: October 2024

Cordyceps militaris grown on germinated Rhynchosia nulubilis (GRC) exerts various biological effects, including anti-allergic, anti-inflammatory, and immune-regulatory effects. In this study, we investigated the anti-inflammatory effects of GRC encapsulated in chitosan nanoparticles (CN) against particulate matter (PM)-induced lung inflammation. Optimal CN (CN6) (CHI: TPP w/w ratio of 4:1; TPP pH 2) exhibited a zeta potential of +22.77 mV, suitable for GRC encapsulation. At different GRC concentrations, higher levels (60 and 120 mg/mL) led to increased negative zeta potential, enhancing stability. The optimal GRC concentration for maximum entrapment (31.4 ± 1.35%) and loading efficiency (7.6 ± 0.33%) of GRC encapsulated in CN (GCN) was 8 mg/mL with a diameter of 146.1 ± 54 nm and zeta potential of +30.68. In vivo studies revealed that administering 300 mg/kg of GCN significantly decreased the infiltration of macrophages and T cells in the lung tissues of PM-treated mice, as shown by immunohistochemical analysis of CD4 and F4/80 markers. Additionally, GCN ameliorated PM-induced lung tissue damage, inflammatory cell infiltration, and alveolar septal hypertrophy. GCN also decreased total cells and neutrophils, showing notable anti-inflammatory effects in the bronchoalveolar lavage fluid (BALF) from PM-exposed mice, compared to GRC. Next the anti-inflammatory properties of GCN were further explored in PM- and LPS-exposed RAW264.7 cells; it significantly reduced PM- and LPS-induced cell death, NO production, and levels of inflammatory cytokine mRNAs (IL-1β, IL-6, and COX-2). GCN also suppressed NF-κB/MAPK signaling pathways by reducing levels of p-NF-κB, p-ERK, and p-c-Jun proteins, indicating its potential in managing PM-related inflammatory lung disease. Furthermore, GCN significantly reduced PM- and LPS-induced ROS production. The enhanced bioavailability of GRC components was demonstrated by an increase in fluorescence intensity in the intestinal absorption study using FITC-GCN. Our data indicated that GCN exhibited enhanced bioavailability and potent anti-inflammatory and antioxidant effects in cells and in vivo, making it a promising candidate for mitigating PM-induced lung inflammation and oxidative stress.
Regulation of Bone Morphogenetic Protein Receptor Type II Expression by FMR1/Fragile X Mental Retardation Protein in Human Granulosa Cells in the Context of Poor Ovarian Response
Authors: Nguyen Xuan Phuoc , Vilkaite Adriana , Bender Ulrike , Dietrich Jens E. , Hinderhofer Katrin , Strowitzki Thomas , Rehnitz Julia
Published: October 2024

Fragile X mental retardation protein (FMRP) is a translational repressor encoded by FMR1. It targets bone morphogenetic protein receptor type II (BMPR2), which regulates granulosa cell (GC) function and follicle development. However, whether this interaction affects folliculogenesis remains unclear. Therefore, this study investigated the potential effect of FMRP-BMPR2 dysregulation in ovarian reserves and infertility. COV434 cells and patient-derived GCs were used to evaluate FMRP and BMPR2 expression. Similarly, FMR1, BMPR2, LIMK1, and SMAD expression were evaluated in GCs with normal (NOR) and poor (POR) ovarian responses. FMRP and BMPR2 were expressed in both cell types. They were co-localized to the nuclear membrane of COV434 cells and cytoplasm of primary GCs. FMR1 silencing increased the mRNA and protein levels of BMPR2. However, the mRNA levels of FMR1 and BMPR2 were significantly lower in the POR group. FMR1 and BMPR2 levels were strongly positively correlated in the NOR group but weakly correlated in the POR group. Additionally, SMAD9 expression was significantly reduced in the POR group. This study highlights the crucial role of FMR1/FMRP in the regulation of BMPR2 expression and its impact on ovarian function. These findings indicate that the disruption of FMRP-BMPR2 interactions may cause poor ovarian responses and infertility.
Exploring Lysophosphatidylcholine as a Biomarker in Ischemic Stroke: The Plasma–Brain Disjunction
Authors: Turpin Justin , Wadolowski Steven , Tambo Willians , Kim Daniel , Al Abed Yousef , Sciubba Daniel M. , Becker Lance B. , Ledoux David , Kim Junhwan , Powell Keren , Li Chunyan
Published: October 2024

Lipids and their bioactive metabolites, notably lysophosphatidylcholine (LPC), are increasingly important in ischemic stroke research. Reduced plasma LPC levels have been linked to stroke occurrence and poor outcomes, positioning LPC as a potential prognostic or diagnostic marker. Nonetheless, the connection between plasma LPC levels and stroke severity remains unclear. This study aimed to elucidate this relationship by examining plasma LPC levels in conjunction with brain LPC levels to provide a deeper understanding of the underlying mechanisms. Adult male Sprague–Dawley rats underwent transient middle cerebral artery occlusion and were randomly assigned to different groups (sham-operated, vehicle, LPC supplementation, or LPC inhibition). We measured multiple LPC species in the plasma and brain, alongside assessing sensorimotor dysfunction, cerebral perfusion, lesion volume, and markers of BBB damage, inflammation, apoptosis, and oxidative stress. Among five LPC species, plasma LPC(16:0) and LPC(18:1) showed strong correlations with sensorimotor dysfunction, lesion severity, and mechanistic biomarkers in the rat stroke model. Despite notable discrepancies between plasma and brain LPC levels, both were strongly linked to functional outcomes and mechanistic biomarkers, suggesting that LPC’s prognostic value is retained extracranially. This study advances the understanding of LPC as a blood marker in ischemic stroke and highlights directions for future research to further elucidate its association with stroke severity, particularly through investigations in more clinically representative models.
Effects of Zinc Phthalocyanine Photodynamic Therapy on Vital Structures and Processes in Hela Cells
Authors: Hosik Jakub , Hosikova Barbora , Binder Svatopluk , Lenobel Rene , Kolarikova Marketa , Malina Lukas , Dilenko Hanna , Langova Katerina , Bajgar Robert , Kolarova Hana
Published: October 2024

This work presents results on the efficiency of newly designed zinc phthalocyanine-mediated photodynamic therapy of both tumoral and nontumoral cell models using the MTT assay. Further detailed examinations of mechanistic and cell biological effects were focused on the HELA cervical cancer cell model. Here, ROS production, changes in the mitochondrial membrane potential, the determination of genotoxicity, and protein changes determined by capillary chromatography and tandem mass spectrometry with ESI were analyzed. The results showed that, in vitro, 5 Jcm−2 ZnPc PDT caused a significant increase in reactive oxygen species. Still, except for superoxide dismutase, the levels of proteins involved in cell response to oxidative stress did not increase significantly. Furthermore, this therapy damaged mitochondrial membranes, which was proven by a more than 70% voltage-dependent channel protein 1 level decrease and by a 65% mitochondrial membrane potential change 24 h post-therapy. DNA impairment was assessed by an increased level of DNA fragmentation, which might be related to the decreased level of DDB1 (decrease in levels of more than 20% 24 h post-therapy), a protein responsible for maintaining genomic integrity and triggering the DNA repair pathways. Considering these results and the low effective concentration (LC50 = 30 nM), the therapy used is a potentially very promising antitumoral treatment.
Neutrophil Diversity (Immature, Aged, and Low-Density Neutrophils) and Functional Plasticity: Possible Impacts of Iron Overload in β-Thalassemia
Authors: Sae-Khow Kritsanawan , Charoensappakit Awirut , Leelahavanichkul Asada
Published: October 2024

Neutrophil dysfunction is a form of immune suppression in patients with β-thalassemia (Beta-thal), although data on this are limited. In this study, blood from patients and healthy volunteers was analyzed. Flow cytometry analysis demonstrated an increase in immature neutrophils (CD16− CD62L+) and aged (senescent) neutrophils (CD16+ CD62L−) in Beta-thal patients compared to healthy volunteers. The Beta-thal neutrophils demonstrated less prominent chemotaxis and phagocytosis than healthy neutrophils at the baseline. With phorbol myristate acetate (PMA) or lipopolysaccharide (LPS) stimulations, some of the indicators, including the flow cytometry markers (CD11b, CD62L, CD66b, CD63, apoptosis, and reactive oxygen species) and neutrophil extracellular traps (NETs; detected by anti-citrullinated histone 3 immunofluorescence), were lower than the control. Additionally, low-density neutrophils (LDNs), which are found in the peripheral blood mononuclear cell (PBMC) fraction, were observed in Beta-thal patients but not in the control group. The expression of CD11b, CD66b, CD63, arginase I, and ROS in LDNs was higher than the regular normal-density neutrophils (NDNs). The proliferation rate of CD3+ T cells isolated from the PBMC fraction of healthy volunteers was higher than that of the cells from patients with Beta-thal. The incubation of red blood cell (RBC) lysate plus ferric ions with healthy NDNs transformed the NDNs into the aged neutrophils (decreased CD62L) and LDNs. In conclusion, iron overload induces neutrophil diversity along with some dysfunctions.
First-Trimester Preeclampsia-Induced Disturbance in Maternal Blood Serum Proteome: A Pilot Study
Authors: Starodubtseva Natalia , Tokareva Alisa , Kononikhin Alexey , Brzhozovskiy Alexander , Bugrova Anna , Kukaev Evgenii , Muminova Kamilla , Nakhabina Alina , Frankevich Vladimir E. , Nikolaev Evgeny , Sukhikh Gennady
Published: October 2024

Preeclampsia (PE) is a complex and multifaceted obstetric syndrome characterized by several distinct molecular subtypes. It complicates up to 5% of pregnancies and significantly contributes to maternal and newborn morbidity, thereby diminishing the long-term quality of life for affected women. Due to the widespread dissatisfaction with the effectiveness of existing approaches for assessing PE risk, there is a pressing need for ongoing research to identify newer, more accurate predictors. This study aimed to investigate early changes in the maternal serum proteome and associated signaling pathways. The levels of 125 maternal serum proteins at 11–13 weeks of gestation were quantified using liquid chromatography–multiple reaction monitoring mass spectrometry (LC-MRM MS) with the BAK-125 kit. Ten serum proteins emerged as potential early markers for PE: Apolipoprotein M (APOM), Complement C1q subcomponent subunit B (C1QB), Lysozyme (LYZ), Prothrombin (F2), Albumin (ALB), Zinc-alpha-2-glycoprotein (AZGP1), Tenascin-X (TNXB), Alpha-1-antitrypsin (SERPINA1), Attractin (ATRN), and Apolipoprotein A-IV (APOA4). Notably, nine of these proteins have previously been associated with PE in prior research, underscoring the consistency and reliability of our findings. These proteins play key roles in critical molecular processes, including complement and coagulation cascades, platelet activation, and insulin-like growth factor pathways. To improve the early prediction of PE, a highly effective Support Vector Machine (SVM) model was developed, analyzing 19 maternal serum proteins from the first trimester. This model achieved an area under the curve (AUC) of 0.91, with 87% sensitivity and 95% specificity, and a hazard ratio (HR) of 13.5 (4.6–40.8) with p < 0.001. These findings demonstrate that serum protein-based SVM models possess significantly higher predictive power compared to the routine first-trimester screening test, highlighting their superior utility in the early detection and risk stratification of PE.
Disease-Specific Alteration of Cardiac Lymphatics: A Review from Animal Disease Models to Clinics
Authors: Shimizu Yuuki , Luo Haihang , Murohara Toyoaki
Published: October 2024

For many years, the significance of cardiac lymphatic vessels was largely overlooked in clinical practice, with little consideration given to their role in the pathophysiology or treatment of cardiac diseases. However, recent research has brought renewed attention to these vessels, progressively illuminating their function and importance within the realm of cardiovascular science. Experimental studies, particularly those utilizing animal models of cardiac disease, have demonstrated a clear relationship between cardiac lymphatic vessels and both the pathogenesis and progression of these conditions. These findings have prompted a growing interest in potential therapeutic applications that specifically target the cardiac lymphatic system. Conversely, while clinical investigations into cardiac lymphatics remain limited, recent studies have begun to explore their identification through specific surface markers, as well as the expression dynamics of lymphangiogenic factors. These studies have increasingly highlighted associations of lymphatic dysfunction with inflammation and fibrosis, both of which negatively impact cardiac function and remodeling across various pathological states. Despite these advances, comprehensive reviews of the current knowledge regarding the cardiac lymphatic vasculature, particularly within specific disease contexts, remain scarce. This review aims to address this gap by providing a detailed synthesis of existing reports, encompassing both animal model research and studies on human clinical specimens, with a special focus on the role of cardiac lymphatic vessels in different disease states.