bluuebunny/crossref_metadata_2025 huggingface dataset:
Exploring the influence of the home literacy environment on early literacy and vocabulary skills in Korean–English bilingual children
Authors: Kim Wi-Jiwoon , Yim Dongsun
Published: March 2024

Studies have emphasized the significance of maintaining a heritage language for various reasons such as the establishment of linguistic and cultural identity, as well as socio-emotional development. Despite the crucial role that literacy development in a heritage language plays in language preservation, there is a scant research that explores the impact of home literacy environment and literacy development in children with a heritage language. This study aimed to examine the home literacy environment and literacy-related skills in 4-to 5-year-old Korean–English bilingual children living in an English-speaking country, Australia, whose heritage language is Korean, and to investigate the relationships among the home literacy environment factors and the child-internal literacy-related skills. The study employed parental questionnaires and video analyses of parent–child shared book reading sessions to assess the Korean and English home literacy environment. Children’s early literacy skills in Korean and English, along with their Korean, English, and conceptual vocabulary skills, were measured as literacy-related skills. The findings indicated that parents utilized an indirect approach for Korean literacy practices, in contrast to a more direct and explicit method for English literacy practices. However, active and direct literacy practices were found to be essential for Korean early literacy development, while indirect methods are sufficient for English early literacy skills. Moreover, the availability of abundant Korean literacy resources at home had a positive impact on the development of Korean and English, as well as conceptual vocabulary skills. In conclusion, this study underscores the importance of providing a robust literacy environment in a heritage language in bilingual families to promote language proficiency in both the heritage language and the dominant social language, while also supporting the development of conceptual language skills.
Multilevel perceptions of the virtual delivery of the University of California Diabetes Prevention Program on RE-AIM domains due to COVID-19 mandates
Authors: Loeb Tamra Burns , Gholami Maryam , Ramm Kate , Shedd Kelly , Soetenga Samantha , Jackson Nicholas J. , Chung Un Young Rebecca , Duru O. Kenrik , Mangione Carol M. , Hamilton Alison B. , Moin Tannaz
Published: March 2024

Background

The University of California’s Diabetes Prevention Program (UC DPP) Initiative was implemented across all 10 UC campuses in 2018. The COVID-19 pandemic and accompanying mandates required swift changes to program delivery, including pivoting from in-person to virtual delivery (i.e., Zoom). Our goal was to assess multilevel constituent perceptions of the use of a virtual platform to deliver UC DPP due to COVID-19 mandates.

Methods

We conducted qualitative interviews with 68 UC DPP participants, coordinators, and leaders to examine the use of virtual platform delivery on the reach, effectiveness, adoption, implementation, and maintenance (RE-AIM) of UC DPP. Transcripts were analyzed using rapid qualitative analysis and emergent themes were categorized using domains corresponding to RE-AIM framework.

Results

Among UC DPP participants (n = 42), virtual delivery primarily impacted perceptions of UC DPP effectiveness and implementation. Some participants perceived program effectiveness to be negatively impacted, given their preference for in-person sessions, which they felt provided more engagement, peer support, and accountability. Implementation challenges included problems with virtual format (e.g., “Zoom fatigue”); however, several benefits were also noted (e.g., increased flexibility, maintenance of DPP connections during campus closures). UC DPP coordinators (n = 18) perceived virtual delivery as positively impacting UC DPP reach, since virtual platforms provided access for some who could not participate in-person, and negatively impacting effectiveness due to reduced engagement and lower peer support. UC leaders (n = 8) perceived that use of the virtual format had a positive impact on reach (e.g., increased availability, accessibility) and negatively impacted effectiveness (e.g., less intensive interactions on a virtual platform). Across constituent levels, the use of a virtual platform had little to no impact on perceptions of adoption and maintenance of UC DPP.

Conclusion

Perceptions of the reach, effectiveness, and implementation of UC DPP using a virtual platform varied across constituents, although all groups noted a potential negative impact on overall program effectiveness. Unanticipated program adaptations, including virtual delivery, present potential benefits as well as perceived drawbacks, primarily across the effectiveness domain. Understanding differential constituent perceptions of the impact of virtual delivery can help maximize RE-AIM and inform future UC DPP delivery strategies.
Humans in XAI: increased reliance in decision-making under uncertainty by using explanation strategies
Authors: Lammert Olesja , Richter Birte , Schütze Christian , Thommes Kirsten , Wrede Britta
Published: March 2024

Introduction

Although decision support systems (DSS) that rely on artificial intelligence (AI) increasingly provide explanations to computer and data scientists about opaque features of the decision process, especially when it involves uncertainty, there is still only limited attention to making the process transparent to end users.

Methods

This paper compares four distinct explanation strategies employed by a DSS, represented by the social agent Floka, designed to assist end users in making decisions under uncertainty. Using an economic experiment with 742 participants who make lottery choices according to the Holt and Laury paradigm, we contrast two explanation strategies offering accurate information (transparent vs. guided) with two strategies prioritizing human-centered explanations (emotional vs. authoritarian) and a baseline (no explanation).

Results and discussion

Our findings indicate that a guided explanation strategy results in higher user reliance than a transparent strategy. Furthermore, our results suggest that user reliance is contingent on the chosen explanation strategy, and, in some instances, the absence of an explanation can also lead to increased user reliance.
Role of pattern recognition receptors and microbiota-derived ligands in obesity
Authors: Rolland Alice , Douard Véronique , Lapaque Nicolas
Published: March 2024

Obesity is associated with activation of low-grade inflammation in tissues metabolically relevant for the regulation glucose homeostasis. The gut microbiota has been extensively linked to the inflammatory responses observed during obesity emphasizing the interconnection between host immunity and metabolism during obesity. Gut microbiota together with alteration of the gut barrier functions provide a myriad of circulating ligands for the pattern recognition receptors (PRRs) expressed in innate immune cells and nonimmune cells. PRR-dependent signalling drives the expression of a wide range of genes beyond the inflammatory response depending on the specific functions of the targeted cells and on the physiological context. PRRs activation can have opposite effects on host metabolic inflammation. Nucleotide-binding oligomerization domain 1 (NOD1) or NOD-like Receptor pyrin domain containing 3 (NLRP3) activation promote metabolic inflammation and insulin resistance while NOD2 activation improves insulin sensitivity and glucose homeostasis during obesity. Toll-like receptors (TLRs) 2, 4 and 5 also display specific effects on metabolic tissues. TLR5 deficient mice are prone to obesity and inflammation in response to high fat diet, while injection of TLR5 ligand, flagellin, has a protective effect toward diet-induced obesity. To the opposite TLR2 and 4 activations are associated with deleterious metabolic outcome during obesity. TLR4 activation enhances metabolic inflammation and insulin resistance and TLR2 via its activation by molecules derived from the gut microbiota favours the onset of obesity. It is now clear that activation of PRRs by bacterial derived molecules plays a key role in the host metabolic regulation. PRRs are expressed in various cell types complicating the understanding of the mechanisms underlying the relationship between PRRs activation/silencing and metabolic inflammation in obesity context. This review presents an overview of the current understanding of the interrelationship between the gut microbiota and PRRs, with a focus on its consequences for obesity and related metabolic diseases.
Element abundance and the physics of solar energetic particles
Authors: Reames Donald V.
Published: March 2024

The acceleration and transport of solar energetic particles (SEPs) cause their abundance, measured at a constant velocity, to be enhanced or suppressed as a function of the magnetic rigidity of each ion, and hence, of its atomic mass-to-charge ratio of A/Q. Ion charges, in turn, depend upon the source electron temperature. In small “impulsive” SEP events, arising from solar jets, acceleration during magnetic reconnection causes steep power-law abundance enhancements. These impulsive SEP events can have 1,000-fold enhancements of heavy elements from sources at ∼2.5 MK and similar enhancements of 3He/4He and of streaming electrons that drive type-III radio bursts. Gamma-ray lines show that solar flares also accelerate 3He-rich ions, but their electrons and ions remain trapped in magnetic loops, so they dissipate their energy as X-rays, γ-rays, heat, and light. “Gradual” SEPs accelerated at shock waves, driven by fast coronal mass ejections (CMEs), can show power-law abundance enhancements or depressions, even with seed ions from the ambient solar corona. In addition, shocks can reaccelerate seed particles from residual impulsive SEPs with their pre-existing signature heavy-ion enhancements. Different patterns of abundance often show that heavy elements are dominated by a source different from that of H and He. Nevertheless, the SEP abundance, averaged over many large events, defines the abundance of the corona itself, which differs from the solar photosphere as a function of the first ionization potential (FIP) since ions, with FIP <10 eV, are driven upward by forces of electromagnetic waves, which neutral atoms, with FIP >10 eV, cannot feel. Thus, SEPs provide a measurement of element abundance in the solar corona, distinct from solar wind, and may even better define the photosphere for some elements.
Integrating inverse reinforcement learning into data-driven mechanistic computational models: a novel paradigm to decode cancer cell heterogeneity
Authors: Kinnunen Patrick C. , Ho Kenneth K. Y. , Srivastava Siddhartha , Huang Chengyang , Shen Wanggang , Garikipati Krishna , Luker Gary D. , Banovic Nikola , Huan Xun , Linderman Jennifer J. , Luker Kathryn E.
Published: March 2024

Cellular heterogeneity is a ubiquitous aspect of biology and a major obstacle to successful cancer treatment. Several techniques have emerged to quantify heterogeneity in live cells along axes including cellular migration, morphology, growth, and signaling. Crucially, these studies reveal that cellular heterogeneity is not a result of randomness or a failure in cellular control systems, but instead is a predictable aspect of multicellular systems. We hypothesize that individual cells in complex tissues can behave as reward-maximizing agents and that differences in reward perception can explain heterogeneity. In this perspective, we introduce inverse reinforcement learning as a novel approach for analyzing cellular heterogeneity. We briefly detail experimental approaches for measuring cellular heterogeneity over time and how these experiments can generate datasets consisting of cellular states and actions. Next, we show how inverse reinforcement learning can be applied to these datasets to infer how individual cells choose different actions based on heterogeneous states. Finally, we introduce potential applications of inverse reinforcement learning to three cell biology problems. Overall, we expect inverse reinforcement learning to reveal why cells behave heterogeneously and enable identification of novel treatments based on this new understanding.
Tailoring Sexual Health Research Practices to Meet the Needs of Adolescent Girls in Low- and Middle-Income Countries: Findings from Mexico
Authors: Servin Argentina E. , Macklin Ruth , Wilkerson Sara , Rocha-Jiménez Teresita , Rangel Gudelia M. , O’Bryan Sophie E. , Fisher Celia B.
Published: March 2024

Sexual and reproductive health (SRH) research is essential for the development of population-tailored evidence-based policies and programs that support sexual health among adolescent girls. However, ethical challenges create barriers to girls’ participation in low- and middle-income countries (LMICs). From February to September 2019, girls aged 16–20 (n = 30) who participated in the Jovenes Sanos study in Tijuana, Baja California (ClinicalTrials: NCT03660514) responded to in-depth interviews (IDs) on the perceived risks and benefits of participating in studies which address gender-based violence, unintended pregnancy, and STIs. Emergent themes indicated the need to ensure that consent and incentive procedures are tailored to the developmental level of participants, while highlighting the importance of researcher–participant relationships, and demonstrating how research can serve as an opportunity to empower girls to express their sexual health medical needs. Understanding adolescent girls’ voices is a critical step in ensuring that consent to participate SRH research is tailored to the developmental needs of participants, is culturally competent, and has a participant-centered approach.
A Comprehensive Assessment of the Morphological Development of Inflorescence, Yield Potential, and Growth Attributes of Summer-Grown, Greenhouse Cherry Tomatoes
Authors: Jerca Ionuț Ovidiu , Cîmpeanu Sorin Mihai , Teodorescu Răzvan Ionuț , Drăghici Elena Maria , Nițu Oana Alina , Sannan Sigurd , Arshad Adnan
Published: March 2024

Understanding how cherry tomatoes respond to variations in greenhouse microclimate is crucial for optimizing tomato production in a controlled environment. The present study delves into the intricate relationship between summer-grown cherry tomatoes (Cheramy F1) and greenhouse conditions, exploring the influence of these conditions on growth attributes, inflorescence development, and yield potential. The aim of the study was to characterize the chronology of reproductive events, specifically flowering and fruit stages, in correlation with the prevailing greenhouse climate during the development of the first ten inflorescences on the plant. The performance of each inflorescence has been ranked based on available data, which involve a comparative analysis of both the time duration (number of days) and the frequency of yield-contributing traits, specifically the total number of flowers at the anthesis stage. The duration of each stage required for completion was recorded and presented as a productivity rate factor. Greenhouse conditions exhibited variations during the vegetative and reproductive stages, respectively, as follows: temperature - 25.1 °C and 21.33 °C, CO2 levels - 484.85 ppm and 458.85 ppm, light intensity - 367.94 W/m2 and 349.52 W/m2, and humidity - 73.23% and 89.73%. The collected data conclusively demonstrated a substantial impact of greenhouse microclimate on plant growth, productivity, and inflorescence development. The development of flowers and fruit has been categorized into five stages: the fruit bud stage (FB), the anthesis stage (AS), the fruit setting stage (FS), the fruit maturation stage (FM), and the fruit ripening stage (FR). An irregular productivity and development response was noted across the first (close to roots) to the tenth inflorescence. Inflorescence 5 demonstrated the highest overall performance, followed by inflorescence numbers 4 and 6. The study findings provide valuable insights for enhancing greenhouse operations, emphasizing the improvement of both the yield and growth of cherry tomatoes while promoting environmental sustainability. A statistical analysis of variance was used to rigorously examine the presented results, conducted at a confidence level of p < 0.05.
An Analysis of the Rice-Cultivation Dynamics in the Lower Utcubamba River Basin Using SAR and Optical Imagery in Google Earth Engine (GEE)
Authors: Medina Medina Angel James , Salas López Rolando , Zabaleta Santisteban Jhon Antony , Tuesta Trauco Katerin Meliza , Turpo Cayo Efrain Yury , Huaman Haro Nixon , Oliva Cruz Manuel , Gómez Fernández Darwin
Published: March 2024

One of the world’s major agricultural crops is rice (Oryza sativa), a staple food for more than half of the global population. In this research, synthetic aperture radar (SAR) and optical images are used to analyze the monthly dynamics of this crop in the lower Utcubamba river basin, Peru. In addition, this study addresses the need to obtain accurate and timely information on the areas under cultivation in order to calculate their agricultural production. To achieve this, SAR sensor and Sentinel-2 optical remote sensing images were integrated using computer technology, and the monthly dynamics of the rice crops were analyzed through mapping and geometric calculation of the surveyed areas. An algorithm was developed on the Google Earth Engine (GEE) virtual platform for the classification of the Sentinel-1 and Sentinel-2 images and a combination of both, the result of which was improved in ArcGIS Pro software version 3.0.1 using a spatial filter to reduce the “salt and pepper” effect. A total of 168 SAR images and 96 optical images were obtained, corrected, and classified using machine learning algorithms, achieving a monthly average accuracy of 96.4% and 0.951 with respect to the overall accuracy (OA) and Kappa Index (KI), respectively, in the year 2019. For the year 2020, the monthly averages were 94.4% for the OA and 0.922 for the KI. Thus, optical and SAR data offer excellent integration to address the information gaps between them, are of great importance to obtaining more robust products, and can be applied to improving agricultural production planning and management.
Validation of the Portuguese Version of the Short-Form Glasgow Composite Measure Pain Scale (CMPS-SF) According to COSMIN and GRADE Guidelines
Authors: de Lima Mayara T. , Trindade Pedro H. E. , Pinho Renata H. , Oliveira Alice R. , Gil Juliana Cannavan , Almeida Thayná R. , Outeda Nadia C. , Luna Stelio P. L.
Published: March 2024

We aimed to validate the CMPS-SF according to COSMIN and GRADE guidelines. Four trained evaluators assessed 208 videos (pre-operative-M1, peak of pain-M2, 1 h after the peak of pain and analgesia (rescue)-M3, and 24 h post-extubation-M4) of 52 dogs, divided into negative controls (n = 10), soft tissue surgeries (n = 22), and orthopedic surgeries (n = 20). The videos were randomized and blinded as to when they were filmed, and were evaluated in two stages, 21 days apart. According to confirmatory analysis, the CMPS-SF is a unidimensional scale. Intra-observer reliability was between 0.80 and 0.99 and inter-observer reliability between 0.73 and 0.86. Criterion validity was confirmed by the correlation between the CMPS-SF and other unidimensional scales (≥0.7). The differences between the scores were M2 ≥ M3 > M4 > M1 (responsiveness), and the scale presented construct validity (higher postoperative pain scores in dogs undergoing surgery versus control). Internal consistency was 0.7 (Cronbach’s α) and 0.77 (McDonald’s ω), and the item-total correlation was between 0.3 and 0.7, except for “A(ii)—Attention to wound”. Specificity and sensitivity were 78–87% and 74–83%, respectively. The cut-off point for rescue analgesia was ≥5 or ≥4 excluding item B(iii) mobility, and the GRADE classification was high, confirming the validity of the scale.
Monocytes Count, NLR, MLR and PLR in Canine Inflammatory Bowel Disease
Authors: Marchesi Maria Chiara , Maggi Giulia , Cremonini Valentina , Miglio Arianna , Contiero Barbara , Guglielmini Carlo , Antognoni Maria Teresa
Published: March 2024

This is an observational retrospective study on 85 client-owned dogs, 60 with IBD and 25 clinically healthy dogs. This study aims to assess the clinical relevance of some easy to obtain and cost-effective hematological parameters including red blood cell distribution width (RDW), neutrophil-to-lymphocyte ratio (NLR), monocyte-to-lymphocyte ratio (MLR), and platelet-to-lymphocyte ratio (PLR) in dogs with IBD. Comparison of clinical and laboratory parameters between dogs with IBD and control dogs was carried out and the ability to distinguish between these two groups of dogs was evaluated by calculating the area under the receiver-operating characteristic curve (AUCROC). Univariate and multivariable logistic regression analysis estimated the odds ratio (OR) of developing IBD with a 95% confidence interval (CI). MLR and monocytes count had the highest accuracy in facilitating the discrimination of dogs with IBD from control dogs with an AUCROC of 0.839 and 0.787 at the cut-off of >0.14% and >3.7 cells*102/µL, respectively. According to two multivariable models, monocytes count (OR = 1.29; p = 0.016), NLR (OR = 1.80; p = 0.016), and MLR > 0.14 (OR = 8.07; p < 0.001) and PLR > 131.6 (OR = 4.35; p = 0.024) were significant and independent predictors of IBD for models one and two, respectively. Monocytes count and the hematological ratios MLR, NLR, and PLR can be useful in the diagnostic work-up of dogs with IBD.
Effects of Nutritional Factors on Fat Content, Fatty Acid Composition, and Sensorial Properties of Meat and Milk from Domesticated Ruminants: An Overview
Authors: Ponnampalam Eric , Priyashantha Hasitha , Vidanarachchi Janak , Kiani Ali , Holman Benjamin
Published: March 2024

The meat and milk products from domesticated ruminants are important foods within a balanced diet, offering a rich source of energy, protein, fats, minerals, and vitamins. The sensorial properties of meat and milk are mainly linked to their fat content and fatty acid composition, which are influenced by the feeding background or nutrient composition of diets. While several studies have investigated the nutritional effects on the fat content and fatty acid profile of ruminant meat and milk, as well as their relationship with sensorial properties, a comprehensive overview of these effects is lacking. This paper summarises current literature and discusses changes to fatty acid composition (including ω-3 concentrations), fattiness, and associated quality traits of sheep, goat, beef cattle, alpaca, and llama meat that can be achieved by using different forages or feeds in a total mixed ration. Additionally, it presents the shelf life and nutritional value of meat, milk, and cheeses from the milk of dairy cattle, buffalo, goats, and sheep as influenced by a ruminant diet. Further advancement in these areas will promote the sustainability of ruminant production and its associated feeding systems in achieving premium quality animal-derived foods.
8-OxoG-Dependent Regulation of Global Protein Responses Leads to Mutagenesis and Stress Survival in Bacillus subtilis
Authors: Martínez Lissett E. , Gómez Gerardo , Ramírez Norma , Franco Bernardo , Robleto Eduardo A. , Pedraza-Reyes Mario
Published: March 2024

The guanine oxidized (GO) system of Bacillus subtilis, composed of the YtkD (MutT), MutM and MutY proteins, counteracts the cytotoxic and genotoxic effects of the oxidized nucleobase 8-OxoG. Here, we report that in growing B. subtilis cells, the genetic inactivation of GO system potentiated mutagenesis (HPM), and subsequent hyperresistance, contributes to the damaging effects of hydrogen peroxide (H2O2) (HPHR). The mechanism(s) that connect the accumulation of the mutagenic lesion 8-OxoG with the ability of B. subtilis to evolve and survive the noxious effects of oxidative stress were dissected. Genetic and biochemical evidence indicated that the synthesis of KatA was exacerbated, in a PerR-independent manner, and the transcriptional coupling repair factor, Mfd, contributed to HPHR and HPM of the ΔGO strain. Moreover, these phenotypes are associated with wider pleiotropic effects, as revealed by a global proteome analysis. The inactivation of the GO system results in the upregulated production of KatA, and it reprograms the synthesis of the proteins involved in distinct types of cellular stress; this has a direct impact on (i) cysteine catabolism, (ii) the synthesis of iron–sulfur clusters, (iii) the reorganization of cell wall architecture, (iv) the activation of AhpC/AhpF-independent organic peroxide resistance, and (v) increased resistance to transcription-acting antibiotics. Therefore, to contend with the cytotoxic and genotoxic effects derived from the accumulation of 8-OxoG, B. subtilis activates the synthesis of proteins belonging to transcriptional regulons that respond to a wide, diverse range of cell stressors.
Evolving Strategies and Materials for Scaffold Development in Regenerative Dentistry
Authors: Gašparovič Michal , Jungová Petra , Tomášik Juraj , Mriňáková Bela , Hirjak Dušan , Timková Silvia , Danišovič Ľuboš , Janek Marián , Bača Ľuboš , Peciar Peter , Thurzo Andrej
Published: March 2024

Regenerative dentistry has experienced remarkable advancement in recent years. The interdisciplinary discoveries in stem cell applications and scaffold design and fabrication, including novel techniques and biomaterials, have demonstrated immense potential in the field of tissue engineering and regenerative therapy. Scaffolds play a pivotal role in regenerative dentistry by facilitating tissue regeneration and restoring damaged or missing dental structures. These biocompatible and biomimetic structures serve as a temporary framework for cells to adhere, proliferate, and differentiate into functional tissues. This review provides a concise overview of the evolution of scaffold strategies in regenerative dentistry, along with a novel analysis (Bard v2.0 based on the Gemini neural network architecture) of the most commonly employed materials used for scaffold fabrication during the last 10 years. Additionally, it delves into bioprinting, stem cell colonization techniques and procedures, and outlines the prospects of regenerating a whole tooth in the future. Moreover, it discusses the optimal conditions for maximizing mesenchymal stem cell utilization and optimizing scaffold design and personalization through precise 3D bioprinting. This review highlights the recent advancements in scaffold development, particularly with the advent of 3D bioprinting technologies, and is based on a comprehensive literature search of the most influential recent publications in this field.
End-to-End Light Field Image Compression with Multi-Domain Feature Learning
Authors: Ye Kangsheng , Li Yi , Li Ge , Jin Dengchao , Zhao Bo
Published: March 2024

Recently, end-to-end light field image compression methods have been explored to improve compression efficiency. However, these methods have difficulty in efficiently utilizing multi-domain features and their correlation, resulting in limited improvement in compression performance. To address this problem, a novel multi-domain feature learning-based light field image compression network (MFLFIC-Net) is proposed to improve compression efficiency. Specifically, an EPI-based angle completion module (E-ACM) is developed to obtain a complete angle feature by fully exploring the angle information with a large disparity contained in the epipolar plane image (EPI) domain. Furthermore, in order to effectively reduce redundant information in the light field image, a spatial-angle joint transform module (SAJTM) is proposed to reduce redundancy by modeling the intrinsic correlation between spatial and angle features. Experimental results demonstrate that MFLFIC-Net achieves superior performance on MS-SSIM and PSNR metrics compared to public state-of-the-art methods.
Review of Manufacturing Processes and Vibro-Acoustic Assessments of Composite and Alternative Materials for Musical Instruments
Authors: Brezas Spyros , Katsipis Markos , Kaleris Konstantinos , Papadaki Helen , Katerelos Dionysios T. G. , Papadogiannis Nektarios A. , Bakarezos Makis , Dimitriou Vasilis , Kaselouris Evaggelos
Published: March 2024

The evolution of musical instrument manufacturing has prompted a quest for innovative materials beyond traditional wood. This review explores the utilization of composite materials, 3D-printed materials, and metamaterials as favorable alternatives. The investigation is driven by challenges such as the scarcity of high-quality tonewoods, variations in wood properties, and environmental concerns. Carbon fiber, graphite fiber, ceramic polymers, and nanocomposites present promising alternatives, offering advantages in durability, weight reduction, and customizable acoustics. The integration of 3D printing technology introduces a cutting-edge dimension, enabling intricate, precisely engineered components, optimizing instrument structure, and allowing unprecedented customization. Additionally, this article explores metamaterials, leveraging unique mechanical properties from structural design rather than constituent materials. Metamaterials offer unprecedented capabilities for tailoring instrument vibrational characteristics by providing unparalleled control over sound production. The review provides a thorough analysis, including manufacturing methods for composite materials, metamaterials, and 3D printing in musical instruments. Comprehensive examinations of vibrational and acoustical analyses related to composite materials, 3D-printed materials, and metamaterials, for the evaluation of musical instruments, are presented. This overview, supported by experimental and numerical simulation methods, offers valuable insights for the future development of musical instruments.
Biostimulant Effect of Commercial Rhizobacteria Formulation on the Growth of Vitis vinifera L.: Case of Optimal and Water Deficit Conditions
Authors: Papantzikos Vasileios , Papanikou Areti , Stournaras Vasileios , Mpeza Paraskevi , Mantzoukas Spiridon , Patakioutas Georgios
Published: March 2024

As climate change is an imminent threat to the environment and agriculture, there is an increasing need to find immediate solutions capable of compensating for water deficits even in semi-arid conditions. This study is focused on the evaluation of the vegetative growth of grapevine plants Vitis vinifera L., of the Greek variety “Debina” in a water deficit environment, with the application of two bacterial-based formulations: one with Bacillus amyloliquefaciens (strain QST 713) and one with Sinorhizobium meliloti (strain cepa B2352). The two formulations were tested under rational irrigation (100% of Available Water) and deficit irrigation (57% of AW). After 140 days, plant growth parameters, such as total plant growth length, leaf area, roots, shoots, and leaves dry biomass showed better performance on treatments with plant growth-promoting rhizobacteria (PGPR) formulations under either rational or deficit irrigation conditions. In addition, the metabolic response of the grapevine plants to the deficit irrigation stress, such as the total chlorophyll, leaf relative water, total phenolic, and proline content, proved to be enriched on the treatments with PGPR formulations during this experiment. The two formulations, in conditions of abiotic stress, achieved to almost compensate for the irrigation deficit, boosting the plant metabolism. This study reveals the need for further research on PGPR biostimulants, as this first trial of these formulations on grapevine could be significant in the case of water scarcity and climate change.
Molecular Cloning, Characterization, and Expression of a Receptor for Activated Protein Kinase C1 (RACK1) Gene in Exopalaemon carinicauda Zoea Larvae under Aroclor 1254 Stress
Authors: Cai Yuefeng , Hu Jie , Guo Yepeng , Shen Xin
Published: March 2024

The receptor for activated protein kinase C1 (RACK1) belongs to the typical WD repeat family, which is extremely conservative and important in multiple signal transduction pathways related to growth and development that coordinate the intracellular role of various life activities. As a novel protein with versatile functions, it was found in a variety of organisms. In a previous study, we identified the RACK1 sequence of white shrimp from transcriptome data. In this study, we employed specialized bioinformatics software to conduct an in-depth analysis of EcRACK1 and compare its amino acid sequence homology with other crustaceans. Furthermore, we investigated the expression patterns of RACK1 at different developmental stages and tissues, as well as at various time points after exposure to Aroclor 1245, aiming to elucidate its function and potential response towards Aroclor 1245 exposure. The length of EcRACK1 is 957 nucleotides, which encodes 318 amino acids. Moreover, there were seven typical WD repeats in EcRACK1, which have more than a 96% sequence identity with the RACK1 proteins of Penaeus. The results of tissue expression and spatiotemporal expression showed that it was significantly increased in the II and IV stages, but had a significant tissue specificity in the hepatopancreas, spermary, and muscle tissues of E. carinicauda, adult stage. Compared to the control, EcRACK1 was significantly induced in E. carinicauda zoea larvae exposed to Aroclor 1254 for 6, 10, 20, and 30 d (p < 0.05). These results suggested that EcRACK1 may play an important role in the larval development and environmental defense of E. carinicauda.
An Engineered Laccase from Fomitiporia mediterranea Accelerates Lignocellulose Degradation
Authors: Pham Le Thanh Mai , Deng Kai , Choudhary Hemant , Northen Trent R. , Singer Steven W. , Adams Paul D. , Simmons Blake A. , Sale Kenneth L.
Published: March 2024

Laccases from white-rot fungi catalyze lignin depolymerization, a critical first step to upgrading lignin to valuable biodiesel fuels and chemicals. In this study, a wildtype laccase from the basidiomycete Fomitiporia mediterranea (Fom_lac) and a variant engineered to have a carbohydrate-binding module (Fom_CBM) were studied for their ability to catalyze cleavage of β-O-4′ ether and C–C bonds in phenolic and non-phenolic lignin dimers using a nanostructure-initiator mass spectrometry-based assay. Fom_lac and Fom_CBM catalyze β-O-4′ ether and C–C bond breaking, with higher activity under acidic conditions (pH < 6). The potential of Fom_lac and Fom_CBM to enhance saccharification yields from untreated and ionic liquid pretreated pine was also investigated. Adding Fom_CBM to mixtures of cellulases and hemicellulases improved sugar yields by 140% on untreated pine and 32% on cholinium lysinate pretreated pine when compared to the inclusion of Fom_lac to the same mixtures. Adding either Fom_lac or Fom_CBM to mixtures of cellulases and hemicellulases effectively accelerates enzymatic hydrolysis, demonstrating its potential applications for lignocellulose valorization. We postulate that additional increases in sugar yields for the Fom_CBM enzyme mixtures were due to Fom_CBM being brought more proximal to lignin through binding to either cellulose or lignin itself.
The Impact of Microbiota–Immunity–Hormone Interactions on Autoimmune Diseases and Infection
Authors: Martinelli Serena , Nannini Giulia , Cianchi Fabio , Coratti Francesco , Amedei Amedeo
Published: March 2024

Autoimmune diseases are complex multifactorial disorders, and a mixture of genetic and environmental factors play a role in their onset. In recent years, the microbiota has gained attention as it helps to maintain host health and immune homeostasis and is a relevant player in the interaction between our body and the outside world. Alterations (dysbiosis) in its composition or function have been linked to different pathologies, including autoimmune diseases. Among the different microbiota functions, there is the activation/modulation of immune cells that can protect against infections. However, if dysbiosis occurs, it can compromise the host’s ability to protect against pathogens, contributing to the development and progression of autoimmune diseases. In some cases, infections can trigger autoimmune diseases by several mechanisms, including the alteration of gut permeability and the activation of innate immune cells to produce pro-inflammatory cytokines that recruit autoreactive T and B cells. In this complex scenario, we cannot neglect critical hormones’ roles in regulating immune responses. Different hormones, especially estrogens, have been shown to influence the development and progression of autoimmune diseases by modulating the activity and function of the immune system in different ways. In this review, we summarized the main mechanisms of connection between infections, microbiota, immunity, and hormones in autoimmune diseases’ onset and progression given the influence of some infections and hormone levels on their pathogenesis. In detail, we focused on rheumatoid arthritis, multiple sclerosis, and systemic lupus erythematosus.
Pediatric and Adolescent Seizure Detection: A Machine Learning Approach Exploring the Influence of Age and Sex in Electroencephalogram Analysis
Authors: Wei Lan , Mooney Catherine
Published: March 2024

Background: Epilepsy, a prevalent neurological disorder characterized by recurrent seizures affecting an estimated 70 million people worldwide, poses a significant diagnostic challenge. EEG serves as an important tool in identifying these seizures, but the manual examination of EEGs by experts is time-consuming. To expedite this process, automated seizure detection methods have emerged as powerful aids for expert EEG analysis. It is worth noting that while such methods are well-established for adult EEGs, they have been underdeveloped for pediatric and adolescent EEGs. This study sought to address this gap by devising an automatic seizure detection system tailored for pediatric and adolescent EEG data. Methods: Leveraging publicly available datasets, the TUH pediatric and adolescent EEG and CHB-MIT EEG datasets, the machine learning-based models were constructed. The TUH pediatric and adolescent EEG dataset was divided into training (n = 118), validation (n = 19), and testing (n = 37) subsets, with special attention to ensure a clear demarcation between the individuals in the training and test sets to preserve the test set’s independence. The CHB-MIT EEG dataset was used as an external test set. Age and sex were incorporated as features in the models to investigate their potential influence on seizure detection. Results: By leveraging 20 features extracted from both time and frequency domains, along with age as an additional feature, the method achieved an accuracy of 98.95% on the TUH test set and 64.82% on the CHB-MIT external test set. Our investigation revealed that age is a crucial factor for accurate seizure detection in pediatric and adolescent EEGs. Conclusion: The outcomes of this study hold substantial promise in supporting researchers and clinicians engaged in the automated analysis of seizures in pediatric and adolescent EEGs.
Genetic Optimization in Uncovering Biologically Meaningful Gene Biomarkers for Glioblastoma Subtypes
Authors: Paplomatas Petros , Douroumi Ioanna-Efstathia , Vlamos Panagiotis , Vrahatis Aristidis
Published: March 2024

Background: Glioblastoma multiforme (GBM) is a highly aggressive brain cancer known for its challenging survival rates; it is characterized by distinct subtypes, such as the proneural and mesenchymal states. The development of targeted therapies is critically dependent on a thorough understanding of these subtypes. Advances in single-cell RNA-sequencing (scRNA-seq) have opened new avenues for identifying subtype-specific gene biomarkers, which are essential for innovative treatments. Methods: This study introduces a genetic optimization algorithm designed to select a precise set of genes that clearly differentiate between the proneural and mesenchymal GBM subtypes. By integrating differential gene expression analysis with gene variability assessments, our dual-criterion strategy ensures the selection of genes that are not only differentially expressed between subtypes but also exhibit consistent variability patterns. This approach enhances the biological relevance of identified biomarkers. We applied this algorithm to scRNA-seq data from GBM samples, focusing on the discovery of subtype-specific gene biomarkers. Results: The application of our genetic optimization algorithm to scRNA-seq data successfully identified significant genes that are closely associated with the fundamental characteristics of GBM. These genes show a strong potential to distinguish between the proneural and mesenchymal subtypes, offering insights into the molecular underpinnings of GBM heterogeneity. Conclusions: This study introduces a novel approach for biomarker discovery in GBM that is potentially applicable to other complex diseases. By leveraging scRNA-seq data, our method contributes to the development of targeted therapies, highlighting the importance of precise biomarker identification in personalized medicine.
Spatial Modelling of Urban Wind Characteristics: Review of Contributions to Sustainable Urban Development
Authors: Liu Yi-Song , Yigitcanlar Tan , Guaralda Mirko , Degirmenci Kenan , Liu Aaron
Published: March 2024

Wind, a renewable resource with growing importance in the contemporary world, is considered a capable tool for addressing some of the problems linked with rapid urbanization, unsustainable development, and climate change. As such, understanding modelling approaches to wind characteristics in cities becomes crucial. While prior reviews delve into the advancements in reduced-scale models and computational fluid dynamics simulations, there is scant literature evaluating large-scale spatial modelling of urban wind environments. This paper aims to consolidate the understanding of spatial modelling approaches to wind characteristics in cities by conducting a systematic literature review with the PRISMA protocol to capture the contributions to sustainable urban development. The reviewed articles are categorized under two distinctive approaches: (a) studies adopting the wind morphometric approach, encompassing theoretical foundations, input factors, and computation methods and (b) studies adopting the urban climate mapping approach, centering on the amalgamation of wind with urban microclimate analysis. The findings suggest that wind morphometric methodologies hold considerable promise due to their straightforward calculations and interpretability. Nonetheless, issues related to data precision and accuracy challenge the validity of these models. This review also probes into the implications of these two distinctive approaches for urban planning and policymaking, advocating for more sustainable urban development.
Border Control: The Role of the Microbiome in Regulating Epithelial Barrier Function
Authors: Schreiber Fernanda , Balas Iulia , Robinson Matthew J. , Bakdash Ghaith
Published: March 2024

The gut mucosal epithelium is one of the largest organs in the body and plays a critical role in regulating the crosstalk between the resident microbiome and the host. To this effect, the tight control of what is permitted through this barrier is of high importance. There should be restricted passage of harmful microorganisms and antigens while at the same time allowing the absorption of nutrients and water. An increased gut permeability, or “leaky gut”, has been associated with a variety of diseases ranging from infections, metabolic diseases, and inflammatory and autoimmune diseases to neurological conditions. Several factors can affect gut permeability, including cytokines, dietary components, and the gut microbiome. Here, we discuss how the gut microbiome impacts the permeability of the gut epithelial barrier and how this can be harnessed for therapeutic purposes.
Ammonium Removal in Wastewater Treatments by Adsorbent Geopolymer Material with Granite Wastes: Full-Scale Validation
Authors: Otero M. , Freire L. , Gómez-Cuervo S. , Ávila C.
Published: March 2024

Elevated ammonium (NH4+) concentrations in untreated waterways contribute to eutrophication and dissolved oxygen depletion. Geopolymer (GP) materials are introduced as sustainable, straightforward operation and low-cost option for pollutant adsorption through ion exchange mechanism. In the present study, a porous metakaolin-based geopolymer with granite waste additions was synthetized, characterised and validated as adsorbent material for NH4+ pollution in water. At this point, treatments to reduce GP alkalis leaching were also considered to comply with the water discharge regulations. The adsorption mechanism was analysed by Redlich-Peterson isotherm model concluding that NH4+ was disposed on the GP surface as a monolayer with strong physical-chemical attraction between molecules. Kinetics of the process followed the Weber-Morris rate equation being the intraparticle diffusion the limiting process. Continuous experiments at lab-scale suggested a maximum removal of 97% during the first hours and an adsorption capacity (q) of 25.24 mg/g. Additionally, as a main novelty of the work, the GP was validated in a full-scale pilot plant monitoring pH, electrical conductivity and NH4+ concentration. The obtained data revealed that the GP is high selective in a real wastewater stream and removed 81% of NH4+, higher adsorption values than those reported for natural and some synthetic zeolites.
What Cities Want to Measure: Bottom-Up Selection of Indicators for Systemic Change toward Climate Neutrality Aligned with Sustainable Development Goals (SDGs) in 40 European Cities
Authors: Mondal Rohit , Bresciani Sabrina , Rizzo Francesca
Published: March 2024

Cities are taking action to respond to climate change by designing and implementing sustainable solutions which provide benefits and challenges to citizens. Measuring the progress and effects of such actions at the urban level, beyond mere greenhouse gas (GHG) emissions quantification, is still an emerging research area. Based on data from the 40 European cities belonging to 20 pilot city programmes within the EU-funded NetZeroCities (NZC) project, cities’ selections and preferences for indicators for assessing their climate actions are analysed in relation to the Sustainable Development Goals (SDGs). This study provides bottom-up evidence of cities’ selection of non-GHG indicators through different levers of change, including participatory governance and social innovation, for assessing progress and the co-benefits of actions toward climate neutrality taken at the urban level. The resulting list of indicators, classified according to the SDGs, provides evidence of cities’ priorities and can be utilised by cities’ climate transition teams and also by researchers, as it highlights gaps and opportunities compared to extant literature.