bluuebunny/crossref_metadata_2025 huggingface dataset:
Multimodal Analgesia Strategies for Cardiac Surgery: A Literature Review
Authors: Fernandes Rostand Moreira , Pontes João Paulo Jordão , Rezende Borges Celso Eduardo , de Brito Neto Demócrito Ribeiro , Pereira Anastácio de Jesus , Carvalho Vergílio Pereira , Gomes Lucas Gonçalves , Prado Silva Fernando Cássio
Published: August 2024

In cardiac surgery, post-sternotomy pain is a significant issue, peaking within 48 hours and requiring proper analgesia for both acute relief and to avoid chronicization. Opioids are commonly used for pain management post-surgery but pose risks like adverse effects and dependency. Post-cardiac surgery pain can stem from various sources - somatic, visceral, and neuropathic, making opioid reliance a concern. Multimodal analgesia, combining different medications and regional anesthesia techniques, is increasingly recommended to decrease opioid use and its related problems. Strategies include acetaminophen, gabapentinoids, NMDA antagonists, alpha-2 agonists, intravenous lidocaine, anti-inflammatory drugs, and regional anesthesia. Implementing these approaches can enhance pain control, lessen opioid reliance, and improve cardiac surgery outcomes. The ERAS® Cardiac Society strongly advocates for an opioid-sparing multimodal approach to benefit patient recovery by reducing complications and enhancing satisfaction. This review aims to consolidate current evidence to assist healthcare providers in customizing pain management for patients post-cardiac surgery, emphasizing reduced opioid use and optimizing the recovery process.
Enhancement of Sustainable Maintenance in Hydrogen Compressor Monitoring by the Utilization of Fractional Factorial Experiments to Optimize the Hyperparameters of a Self-Attention-Based Neural Network
Authors: Pérez Salvador , González-Gaya Cristina , Sebastián Miguel A.
Published: August 2024

Making sustainable business models, especially in manufacturing, is a key approach for organizations to adopt in order to create more sustainable processes. New technologies are needed to implement new policies that can minimize the economic, environmental, and social consequences of industrial activity. Sustainable maintenance is decisive to guarantee the availability, reliability, and safety of assets, surpassing traditional maintenance policies and embracing the principles of the circular economy. The main objective of Maintenance 4.0 is to increase the lifespan and availability of the equipment by preventing unplanned downtime, reducing planned shutdowns, and improving safety. This research focuses on the integration of advanced Industry 4.0 tools with conventional monitoring and control techniques in process industries. The article suggests that while complex neural networks might provide good predictions, simpler solutions can generalize well and have lower prediction errors because they can capture the underlying relationships between variables in a specific asset better. The combination of maintenance function, Industry 4.0 tools, and advanced statistical solutions to obtain sustainable processes can facilitate organizational change and aid decision-making in equipment management. These solutions seek to reduce interruptions and expenses through the unnecessary utilization of labor and spare parts. All these considerations improve communication and data processing, resulting in improved maintenance of a hydrogen compressor in the petrochemical industry.
Defensive Adaptations and Paleoecology of Ankylosaurus: Insights into the Armor and Lifestyle of a Cretaceous Armored Dinosaur
Authors: Hu Tyler
Published: August 2024

Ankylosaurus stands as a quintessential example of Cretaceous armored dinosaurs, renowned for its formidable defensive adaptations. This study explores the defensive mechanisms and paleoecology of Ankylosaurus, focusing on its unique armor and lifestyle. Through detailed morphological analysis of fossil specimens, we examine the structure and function of the robust osteoderms and the prominent tail club, evaluating their roles in defense against predators. The distribution and arrangement of these defensive features suggest a sophisticated strategy to deter and survive attacks from contemporary theropods. Additionally, we investigate the paleoenvironmental context of Ankylosaurus, assessing how its habitat and ecological interactions influenced its evolutionary adaptations. Comparative analysis with other ankylosaurids and contemporaneous species provides insights into the evolutionary pressures shaping its armor. Our findings highlight the balance between offensive and defensive strategies in the Late Cretaceous ecosystem, underscoring the role of Ankylosaurus as both a well-protected herbivore and a critical component of its ecological niche. This study contributes to a deeper understanding of the evolutionary dynamics of armored dinosaurs and their interaction with their environment, offering a comprehensive perspective on the adaptations that defined Ankylosaurus' survival strategy.
First-Order Comprehensive Adjoint Sensitivity Analysis Methodology for Neural Ordinary Differential Equations: Mathematical Framework and Illustrative Application to the Nordheim-Fuchs Reactor Safety Model
Authors: Cacuci Dan Gabriel
Published: August 2024

This work introduces the mathematical framework of the novel “First-Order Comprehensive Adjoint Sensitivity Analysis Methodology for Neural Ordinary Differential Equations (1st-CASAM-NODE)” which yields exact expressions for the first-order sensitivities of NODE decoder-responses to the NODE parameters, including encoder initial conditions, while enabling the most efficient computation of these sensitivities. The application of the 1st-CASAM-NODE is illustrated by using the Nordheim-Fuchs reactor dynamics/safety phenomenological model, which is representative of physical systems that would be modeled by NODE while admitting exact analytical solutions for all quantities of interest (hidden states, decoder outputs, sensitivities with respect to all parameters and initial conditions, etc.). This work also lays the foundation for the ongoing work on conceiving the “Second-Order Comprehensive Adjoint Sensitivity Analysis Methodology for Neural Ordinary Differential Equations (2nd-CASAM-NODE)” which aims at yielding exact expressions for the second-order sensitivities of NODE decoder-responses to the NODE parameters and initial conditions while enabling the most efficient computation of these sensitivities.
Olfactory Selection Preferences of Pagiophloeus tsushimanus Adults toward Lauraceae Plants
Authors: Chen Cong , Li Shou Yin , Lin Zhao Yan , Ji Qian Hua , Hao De Jun
Published: August 2024

Pagiophloeus tsushimanus, a new record of wood-boring pest first reported in China in 2014, has significantly infested Cinnamomum camphora across various administrative districts in Shanghai. And it shows a concerning trend of spread. The larval stage of the insect, being concealed within the trunks of C. camphora, exhibits characteristics such as hidden activity, strong destructiveness, and difficulty in control. This severely affects the normal growth of the host trees. While the primary host plant for P. tsushimanus is the C. camphora, preliminary observations have shown that the pest can also complete its life cycle on Cinnamomum chekiangensis and Phoebe chekiangensis. Both of them are significant species for urban greening. To explore the host selection preference of this beetle, this study investigates the olfactory selection behavior of adult P. tsushimanus towards C. camphora, C. chekiangensis, and P. chekiangensis. Results from choice tests, no-choice tests, and "Y"-shaped olfactometer experiments indicated that both male and female adults exhibited a feeding preference for C. camphora branches, with females showing a preference for laying eggs on C. camphora branches as well. Behavioral responses demonstrated a positive chemotaxis towards volatiles from C. camphora and a negative chemotaxis towards volatiles from C. chekiangensis and P. chekiangensis. Overall, the findings suggest that both male and female adults have a selective preference for volatiles emitted by C. camphora. These provides a theoretical basis for monitoring and controlling host shift occurrences in P. tsushimanus.
Antimicrobial Activity of Gallium(III) Compounds: Pathogen-Dependent Targeting of Multiple Iron/Heme-Dependent Biological Processes
Authors: Choi Seoung-ryoung , Hassan Mohammed A , Britigan Bradley E , Narayanasamy Prabagaran
Published: August 2024

Metals play vital roles in biological systems, with iron/heme being essential for cellular and metabolic functions necessary for survival and/or virulence in many bacterial pathogens. Given the rise of bacterial resistance to current antibiotics, there is an urgent need for the development of non-toxic and novel antibiotics that do not contribute to resistance to other antibiotics. Gallium, which mimics iron, has emerged as a promising antimicrobial agent, offering a novel approach to combat bacterial infections. Gallium does not have any known functions in biological systems. Gallium exerts its effects primarily by replacing iron in redox enzymes, effectively inhibiting bacterial growth by targeting multiple iron/heme-dependent biological processes and suppressing the development of drug resistance. The aim of this review is to highlight recent findings on the mechanisms of action of gallium and provide further insights into the development of gallium-based compounds. Understanding the mechanisms underlying gallium’s biological activities will enhance its therapeutic application across various medical fields, offering promising avenues for the treatment of infectious diseases, cancer, and inflammatory conditions.
Bioactive Polysaccharides from Gracilaria lemaneiformis: Preparation, Structures, and Therapeutic Insights
Authors: Wang Min , Zhu Zhen , Wu Xiaocheng , Cheong Kit-Leong , Li Xiaohua , Yu Wanli , Yao Yinlin , Wu Jiang , Cao Zhanhui
Published: August 2024

Gracilaria lamaneiformis, a red seaweed, is an abundant source of bioactive polysaccharides with significant health-promoting properties. Nevertheless, the broad application of G. lamaneiformis in the nutraceutical and pharmaceutical sectors remains constrained due to the absence of comprehensive data. This review provides a detailed examination of the preparation methods, structural characteristics, and biological activities of G. lamaneiformis polysaccharides (GLP). We explore both conventional and advanced extraction techniques, highlighting the efficiency and yield improvements achieved through methods such as microwave-, ultrasonic-, and enzyme-assisted extraction. The structural elucidation of GLP using modern analytical techniques, including high-performance liquid chromatography, gas chromatography, and nuclear magnetic resonance spectroscopy, is discussed, providing comprehensive insights into their molecular composition and configuration. Furthermore, we critically evaluate the diverse biological activities of GLP, including their antioxidant, anti-inflammatory, antitumor, and gut microbiota modulation properties. This review underscores the therapeutic potential of GLP and suggests future research directions to fully harness their health benefits.
A Focus on the Metabolic Dysfunction of Proximal Tubule Cells in Dent Disease Type 1
Authors: de Combiens Elise , Sakhi Imene Bouchra , Lourdel Stéphane
Published: August 2024

Dent disease type 1 is a rare inherited renal disorder affecting mainly young males, generally leading to end-stage renal failure and for which there is no cure. It is caused by inactivating mutations in the gene encoding ClC-5, a 2Cl-/H+ exchanger found on endosomes in the renal proximal tubule. This transporter participates in reabsorbing all filtered plasma proteins which justifies why proteinuria is commonly observed when ClC-5 is defective. In the context of Dent disease type 1, a proximal tubule dedifferentiation was shown to be accompanied by a dysfunctional cell metabolism. However, the exact mechanisms linking such alterations to chronic kidney disease are still unclear. In this review, we gather knowledge from several Dent disease type 1 models to summarize the current hypotheses generated to understand the progression of this disorder. We also highlight some urinary biomarkers for Dent disease type 1 suggested in different studies.
Innovations in Polymer Additive Manufacturing: Research Advancements in Polymer Materials for Additive Manufacturing
Authors: Egon Axel , Bell Chris , Shad Ralph
Published: August 2024

The field of polymer additive manufacturing (AM) has experienced rapid evolution, marked by significant advancements in materials science and technology. This paper reviews recent innovations in polymer materials tailored for additive manufacturing processes, focusing on enhancements in mechanical properties, functionalization, and processability. Key developments include the introduction of high-performance thermoplastics, composite materials incorporating fibers or nanoparticles, and novel photocurable resins. These materials offer improved strength, durability, and versatility compared to traditional polymers. Furthermore, research into bio-based and recyclable polymers highlights a growing trend towards sustainable manufacturing practices. Advances in material formulations, including self-healing and shape-memory polymers, are also examined for their potential to transform applications across various industries. This review synthesizes current research trends and provides a comprehensive overview of the state-of-the-art in polymer AM materials, emphasizing the impact of these innovations on the future of manufacturing technologies.
Eis Behavior of Polyethylene+graphite Composite Considered as an Approximation to an Ensemble of Microelectrodes
Authors: Navarro-Laboulais Javier , Agrisuelas Jerónimo , García-Jareño José Juan , Vicente Francisco
Published: August 2024

The electrical percolation of alternating current through two-phase polyethylene/graphite composite electrodes with different contents of graphite microparticles immersed in aqueous KCl solutions has been studied. Above the graphite content of the first percolation threshold, the electrochemical impedance response of this electrode is associated with an equivalent circuit of resistance Ru in series with a constant phase element CPE. An insulator material+conductive filler model is proposed in which the electroactive surface is considered as the intersection of the percolation cluster through the solid and the cluster associated with the interfacial region. CPE is analyzed assuming a distribution of micro-capacitors of the graphite particles in contact with the dielectric solution and inside the dielectric polymeric phase.
Positive Selection Drives the Evolution of the Structural Maintenance of Chromosomes (SMC) Complex
Authors: Forni Diego , Mozzi Alessandra , Sironi Manuela , Cagliani Rachele
Published: August 2024

Structural Maintenance of Chromosomes (SMC) complexes are an evolutionary conserved protein family. In most eukaryotes, three SMC complexes have been characterized: cohesin, condensin, and SMC5-6 complexes. These complexes are involved in a plethora of functions and defects in SMC genes can lead to increased risk of chromosomal abnormalities, infertility, and cancer. To investigate th evolution of SMC complex genes in mammals, we analyzed their selective patterns in an extended phylogeny. Signals of positive selection were identified for condensin NCAPG, for two SMC5/6 complex genes (SMC5 and NSMCE4A) and for all cohesin genes with almost exclusive meiotic expression (RAD21L1, REC8, SMC1B, and STAG3). For the latter, evolutionary rates correlate with expression during female meiosis and most positively selected sites fall in intrinsically disordered regions (IDRs). Our results support growing evidence that IDRs are fast evolving and that most likely contribute to adaptation through modulation of phase separation. We suggest that the natural selection signals identified in SMC complexes may be the result of different selective pressures: a host-pathogen arms race in the condensin and SMC5/6 complexes, and an intragenomic conflict similar to that described for centromeres and telomeres for meiotic cohesin genes.
The Role of Catalysts in LCA Applied to Biogas Reforming
Authors: Nogales-Delgado Sergio , González González Juan Félix
Published: August 2024

The real implementation of biogas reforming at industrial scale to obtain interesting products, like hydrogen or syngas, is a developing research field where multidisciplinary teams are continuously adding improvements and innovative technologies. Thus, these works can contribute to the proliferation of green technologies where circular economy and sustainability are present. To assess the sustainability of these processes, there are different tools like life cycle assessment (LCA), which implies a complete procedure where even small details count to consider a certain technology sustainable or not. The aim of this work was to review works where LCA is applied to different aspects of biogas reforming, especially focusing on the role of catalysts, which are essential to improve the efficiency of a certain process, but also present a strong influence on its environmental impact. As a conclusion, catalysts have an influence on LCA through the improvement on the catalytic performance and the impact of their production, whereas other aspects related to biogas or methane reforming could equally influence on their durability or reusability, with the subsequent effect on LCA. Further research about this subject is required in a continuously changing technology with plenty of possibilities.
Open-source Hardware Design of Modular Solar DC Nanogrid
Authors: Rahman Md Motakabbir , Khan Sara , Pearce Joshua M.
Published: August 2024

The technical feasibility of solar photovoltaic (PV) direct current (DC) nanogrids are well-established, but the components of nanogrids are primarily commercially focused on alternating current (AC)-based systems. Thus, DC converter-based designs at the system level require personnel with high degree of technical knowledge and this results in high costs. To enable a democratization of the technology by reducing the costs this study provides a novel modular plug-and-play open source DC nanogrid. The system can be customized according to consumer requirements, enabling the supply of various voltage levels to accommodate different device voltage needs. The step-by-step design process of the converter, controller, data logger, and assembly of the complete system is provided. A time-domain simulation and stability analysis of the designed system were conducted in MATLAB/Simulink as well as experimental validation. The results show transforming the nanogrid from a distribution network to a device makes it suitable for various user-specific applications, such as remotely supplying power to campsites, emergency vehicles like ambulances, and small houses lacking grid electricity. The modular DC nanogrid includes all the features available in a DC distribution network as well as data logging, which enhances the user experience and promotes the use of solar-powered DC grid systems.
Clinical and Technical Validation of OncoIndx® Assay – A Comprehensive Genome Profiling Assay for Pan-Cancer Investigations
Authors: Ramesh Aarthi , Bharde Atul , D'Souza Alain , Jadhav Bhagwat , Prajapati Sangeeta , Hariramani Kanchan , Basavalingegowda Madhura , Iyer Sandhya , Halder Sumit , Deochake Mahesh , Kothavade Hrishita , Vasudevan Aravindan , Uttarwar Mohan , Khandare Jayant , Shafi Gowhar
Published: August 2024

Comprehensive next-generation sequencing (NGS) assays enable identification of clinically relevant mutations, enhancing the capability for targeted therapeutic interventions. In addition, genomic alterations driving the oncogenic roadmap and lead to resistance mechanisms are reshaping precision oncology. We report, workflow, informatics validation of OncoIndx NGS platform – a comprehensive genomic profiling (CGP)-base assay for pan-cancer investigation. We evaluated the concordance between the OncoIndx® test findings and clinically established hotspot findings using SeraSeq reference standards. OncoIndx is a hybridization capture-based NGS assay for targeted deep sequencing of all exons and selected introns of 1080 cancer related genes. We show the outcome in the form of -tier I and tier II single nucleotide variants (SNVs), copy number alterations (CNAs), and specific gene rearrangements (fusion). OncoIndx® also enables tumor mutational burden (TMB), microsatellite instability (MSI), homologous recombination deficiency (HRD), and genomic loss of heterozygosity (gLOH). We show maximum clinical sensitivity of 98% and a positive predictive value (PPV) of 100% for the clinically actionable genomic variants detected by the assay. In addition, we demonstrate analytical validation with performance of the assay, limit of detection (LoD), precision, and orthogonal concordance for various types of SVs, CNAs, genomic rearrangements, and complex biomarkers like TMB, MSI, and HRD. The assay offers reliable genomic predictions with high precision detection of actionable variants, validated by established reference standards.
Strategic Transformation and Sustainability: Unveiling the EFQM Model 2025
Authors: Martusewicz Joanna , Wierzbic Arkadiusz , Łukaszewicz Marcin
Published: August 2024

The EFQM Model, established in 1991, serves as a framework for organizational excellence, helping achieve sustainable success through an integrated management system. The model's evo-lution is driven by the need to adapt to global trends, threats, and technological innovations such as: digital transformation, employee engagement and well-being, remote work, agile performance management, diversity, equity and inclusion (DEI), sustainability, AI, and big data. The new EFQM Model 2025, presented in Istanbul in June 2024, introduces significant changes, emphasiz-ing sustainability, innovation, and technology. These changes are analyzed based on the logic of three questions: Why, How, and What.
Why: There is a necessity for better alignment of organizations with contemporary challenges through flexibility, risk resilience, and innovation capabilities in a dynamic business environ-ment, including alignment with the UN Sustainable Development Goals (SDGs).
How: The model introduces an integrated approach to performance management and transfor-mation, incorporating advanced technologies such as AI and data analytics.
What: Implementing the EFQM Model 2025 enhances organizational adaptability, innovation, and flexibility, improving financial, operational, and strategic outcomes.
Better alignment with sustainability goals leads to long-term value and social responsibility. Improved stakeholder engagement methods enhance understanding and satisfaction. The use of advanced technologies supports innovation and operational efficiency, while better strategic and operational performance and risk management ensures greater stability and the ability to anticipate future challenges.
Advancements in Query-Based Tabular Data Retrieval: Detecting Image Data Tables and Extracting Text using Convolutional Neural Networks
Authors: Tufail Hina , Naseer Asma , Tamoor Maria , Ali Abbas Raza
Published: August 2024

The detection and recognition of tables in image-based documents is a challenging and essential task for automated data extraction and anal- ysis. This paper introduces a methodology that utilizes Convolutional Neural Networks (CNNs) to address this problem. By harnessing the ro- bust visual recognition abilities of CNNs, the proposed method effectively detects and extracts tables from image-based documents. Additionally, an Encoder-Dual Decoder (EDD) architecture is employed to extract the textual content from table cells, enabling the transformation of visual data into structured, machine-readable formats. This structured data is then further processed using a Vector Space Model (VSM)-based language modeling technique for query-based table retrieval. The methodology’s accuracy is assessed by analyzing the spatial relationships between the extracted cells and comparing them against a pre-defined table structure. The results provide an evidence to the effectiveness of the proposed ap- proach, with an impressive 85% accuracy rate and a corresponding error rate of 15%. This accurate extraction and recognition of tables from image-based documents can significantly enhance applications in data analysis, information retrieval, and knowledge extraction.
Predictors of Hospitalization in Breakthrough COVID-19 among Fully Vaccinated Individuals with Immune-Mediated Rheumatic Diseases: Data from Safer-Study
Authors: Calderaro Debora Cerqueira , Valim Valéria , Oliveira Gilda Ferreira , Machado Ketty Lysie Libardi Lira , Ribeiro Priscila Dias Cardoso , Ribeiro Sandra Lúcia Euzébio , Sartori Natália Sarzi , Rezende Rodrigo Poubel Vieira , Melo Ana Karla Guedes , Cruz Vitor , Vieira Adah Sophia Rodrigues , Kakehasi Adriana Maria , Landa Aline Teixeira , Burian Ana Paula Neves , Peixoto Flávia Maria Matos Melo Campos , Telles Camila Maria Paiva França , do Espírito Santo Rafaela Cavalheiro , Baptista Katia Lino , Oliveira Yasmin Gurtler Pinheiro , Magalhães Vanessa de Oliveira , Lima Raquel Lima , Biegelmeyer Erika , Lorencini Pietra Zava , Teixeira-Carvalho Andréa , Reis-Neto Edgard Torres , Sato Emilia Inoue , Pinheiro Marcelo Medeiros , Monticielo Odirlei André André , de Souza Viviane Angellina , Xavier Ricardo Machado , Pileggi Gecilmara Salviato
Published: August 2024

Breakthrough COVID-19 (occurring in fully vaccinated people) has been described. Data on its characteristics among immune mediated rheumatic disesases (IMRD) patients are scarce. This study describes breakthrough COVID-19 among IMRD patients participating of SAFER-study, a Brazilian multicentric cohort evaluating safety, effectiveness and immunogenicity of SARS-Cov-2 vaccines in autoimmune diseases. Descriptive analysis and a binary logistic regression model, to evaluate predictors of COVID-19-related hospitalization, were performed. P-value < 0.05 was significant. The included 160 patients were predominantly females (83.1%), with mean (SD) age 40.23 (13.19) years. Patients received 2 (19%), 3 (70%) or 4 (11%) vaccine doses. The initial two-dose series was mainly with ChAdOx1 (Oxford/AstraZeneca) (58%) or BBIBP-CorV (Sinopharm-Beijing) (34%). The first booster (n=150) was with BNT162b2 (BioNtech/Fosun Pharma/Pfizer) (63%) or ChAdOx1 (29%). The second booster (n=112) was with BNT162b2 (40%) or ChAdOx1 (26%). COVID-19 hospitalization rate was 17.5%. IMRD moderate/high activity (OR: 5.84, CI: 1.9-18.5, p=0.002) and treatment with corticosteroids (OR: 2.94, CI: 1.02-8.49, p=0.0043) associated with higher odds of hospitalization, while the increasing number of vaccine doses was protective (OR: 0.37, CI: 0.15-0.9, p=0.032). These findings, along with previous reassuring results about the safety of the COVID-19 vaccines, argue in favour of booster vaccination in IMRD patients.
The Symmetry Group of the Grand Antiprism
Authors: Monson Barry
Published: August 2024

The grand antiprism A is an outlier among the uniform 4-polytopes, since it is not obtainable from Wythoff’s construction. Its symmetry group G(A) has been incorrectly described as [[10,2+,10]] or even as an `ionic diminished Coxeter group’. In fact, G(A) is another group of order 400, namely the group ±[D10×D10]·2, in the notation of Conway and Smith.
Fetal Growth Following Electronic Cigarette Use in Pregnancy
Authors: Bailey Beth A. , Azar Michelle , Nadolski Katherine , Dodge Phoebe A
Published: August 2024

Electronic cigarette (ecig) use in pregnancy is common, but potential effects on fetal development are largely unknown. The study goal was to examine the association between ecig exposure and fetal growth. Data were extracted from medical charts in this single site retrospective study. The sample, excluding those with known tobacco, alcohol, illicit drug, opioid, and benzodiazepine use, contained women who used ecigs throughout pregnancy and non-ecig user controls. Fetal size measurements from second and third trimester ultrasounds and at birth were expressed as percentiles for gestational age. Following adjustment for confounding factors, in the second trimester, only femur length was significant, with an adjusted deficit of 11.5 percentile points for ecig exposed compared to controls. By the third trimester, femur length difference was 28.5 points, with fetal weight difference also significant (17.2 points). At birth, all three size parameter differences between groups were significant. Significant size deficits were predicted by prenatal ecig exposure, becoming larger and impacting more parameters with increasing gestation. While additional study is warranted to confirm and expand upon these findings, this study adds to emerging data pointing to specific harms following ecig exposure in pregnancy, and suggests that ecigs may not be a “safer” alternative to combustible cigarette smoking in pregnancy.
Advances in Ultrasound-Guided Surgery and Artificial Intelligence Applications in Musculoskeletal Diseases
Authors: Hattori Soichi , Saggar Rachit , Heidinger Eva M , Qi Andrew , Mullen Joseph , Fee Brianna , Brown Cortez L , Canton Stephen P , Scott Devon , Hogan MaCalus Vinson
Published: August 2024

Ultrasound imaging is a vital imaging tool in musculoskeletal medicine, with the number of publications on ultrasound-guided surgery increasing in recent years. However, ultrasound imaging has drawbacks, such as operator dependency and image obscurity. Artificial Intelligence (AI) and Deep Learning (DL), a subset of AI, can address these issues. DL methods, including segmentation, detection, and localization of target tissues and medical instruments, potentially allow physicians and surgeons to perform ultrasound-guided procedures more accurately and efficiently. This review summarizes recent advances in ultrasound-guided procedures for musculoskeletal diseases and provides a comprehensive overview of the utilization of AI/DL in ultrasound for musculoskeletal medicine, particularly focusing on ultrasound-guided surgery.
Polyphenols Investigation, Antioxidant and Anticholinesterase Activity of Rosmarinus officinalis L. Species from Southwest Romania Flora
Authors: Bejenaru Ludovic Everard , Biţă Andrei , Mogoşanu George Dan , Segneanu Adina-Elena , Radu Antonia , Ciocîlteu Maria Viorica , Bejenaru Cornelia
Published: August 2024

Rosemary is one of the most important medicinal plants for natural therapy due to its multiple pharmacological properties, such as antioxidant, anti-inflammatory, neuroprotective, antiproliferative, antitumor, hepato- and nephroprotective, hypolipidemic, hypocholesterolemic, antihypertensive, anti-ischemic, hypoglycemic, radioprotective, antimicrobial, antiviral, antiallergic, wound healing. Our study reports for the first time, over a 12-month period, the identification and quantification of polyphenols and the investigation of the antioxidant and acetylcholinesterase (AChE) inhibitory activity of the Rosmarinus officinalis L. species harvested at flowering from the flora of southwestern Romania (Oltenia Region). Identification and quantification of polyphenolic acids was made by ultra-high-performance liquid chromatography/mass spectrometry (UHPLC/MS). Total phenolic content was determined using the spectrophotometric method. In situ antioxidant and anticholinesterase activity was evaluated using 2,2-diphenyl-1-picrylhydrazyl (DPPH) and AChE inhibitory assay, respectively, on high-performance thin-layer chromatography (HPTLC) plates. DPPH radical scavenging activity was also assessed spectrophotometrically. The results revealed significant correlations between specific polyphenolic compounds and the measured biological activities, understanding the role of seasonal variations and providing insights into the optimal harvesting times and medicinal benefits of rosemary. Our research brings new information on the phytochemical profile of R. officinalis, as a natural source of polyphenols with antioxidant and AChE inhibitory properties.
Retinal Hemoperfusion and Vascular Endothelial Function after Pancreatic Transplantation
Authors: Bulava Evgeniy , Vorobyeva Irina V. , Dmitriev Ilya V. , Balkarov Aslan G.
Published: August 2024

Introduction: ophthalmological assessment of the retinal circulation and the level of VEGF-A is currently considered a non-invasive and safe diagnostic tool to assess the peripheral microcircu-lation
Objective: to study retinal hemodynamics and VEGF-A levels in patients with type 1 diabetes mellitus after pancreas transplantation
Settings and Design:
A prospective, single-stage, single-center, non-randomized clinical trial
Methods: 79 patients (158 eyes) with type 1 diabetes mellitus and end-stage diabetic nephropathy participated in the study. Patients were divided into 3 groups: group 1, potential recipients of pancreas and kidney transplant from the waiting list; group 2, patients after kidney transplanta-tion; and group 3, patients after simultaneous pancreas and kidney transplantation. Ophthalmo-logical examination included measuring the macular hemoperfusion density. The level of VEGF-A was examined in the patients' tear by enzyme immunoassay.
Results: retinal hemoperfusion density and VEGF-A concentration were expected to correlate with the severity of diabetic changes in the fundus of patients. A lower index of retinal hemoperfusion density and a high level of VEGF-A were noted in patients with proliferative ret-inopathy and macular oedema. Group 3 showed the lowest frequency of the active phase of the proliferative retinopathy and retinal macular oedema, characterized by a higher retinal hemoperfusion density in the foveal and the parafoveal zone of the macular region, and low VEGF-A concentration in tear.
Conclusion: measurement of retinal hemoperfusion density and determination of tear VEGF-A concentration are informative objective methods for diagnosing the severity of diabetic changes of the fundus.
Unconventional Luminaire Layout Design by Genetic Algorithms
Authors: Panska Zuzana , Balsky Marek , Bayer Rudolf , Brejcha Michal
Published: August 2024

The dominant part of energy performance of a building consists of consumption of heating and lighting. Both heating and lighting systems of buildings work at their designed efficiency for most of the buildings’ lifetimes. Interference with existing systems is costly considering replacements and construction adjustments. Therefore, considerable effort must be put into the design of these systems during the building design phase. The article is focused on luminaire layout design strategy, which affects the number of luminaires in a building and therefore their power consumption and the sustainability of the building. A genetic algorithm with radiosity implemented has been used to find suitable placements of luminaires of a single type in a model room to decrease the number of luminaires as much as possible. Three outcomes of optimal luminaire layout design are presented in this paper, including design strategy conclusions. Results of calculation outcomes are verified by software DIALux, that is commonly used for designing lighting systems.
Effects of Icon Grouping based on Familiartity on Search Times and Eye Movements
Authors: Ha Yujeong , Hong Seung-Kweon
Published: August 2024

This study investigated the effects of icon familiarity on visual search performance. An equal number of familiar and unfamiliar icons were selected as background icons. These background icons were randomly arranged, and a visual search experiment was conducted to locate the target icon. The results showed no significant difference in the time required to find the target icon, regardless of whether the target icon was familiar or unfamiliar. This finding contrasts with previous studies that have suggested a positive effect of target icon familiarity on visual search performance, indicating that the influence of target icon familiarity may not always be consistent and could depend on the characteristics of the background icons. However, when background icons were grouped based on their familiarity, the time taken to locate the target icon was significantly reduced compared to when the icons were randomly arranged. To understand the underlying mechanism of this effect, participants' gaze fixation times were observed. The results revealed that participants spent more time fixating on areas where the target icon was located, rather than on areas without the target icon, suggesting a more efficient visual search process. Moreover, the shorter the visual search time, the higher the proportion of time spent fixating on the area containing the target icon. Additionally, this study examined the contrast ratio between the color of the background space and the dominant color of the target icon, comparing it with the visual search time. The findings indicated that as the contrast ratio increased, the visual search time decreased.
Evaluation of Evidence-Based Practice Competency among Greek Undergraduate Nursing Students
Authors: Miliara Eleni , Kalokairinou Athena , Schetaki Stefania , Patelarou Evridiki , Patelarou Athina
Published: August 2024

Several years now, the global scientific community has accepted and recognized the importance of Evidence-based practice (EBP) for Nursing science. The main factor for the implementation of EBP is the competence of undergraduate Nursing students towards EBP, so that they as active nurses be ready for its application in their clinical practice, in order to provide better care for their patients. The aim of the present study is to examine the level of evidence-based practice competency evaluated with the self-reported EBP-COQ questionnaire. A quantitative study based on cross-sectional design was conducted from February to June 2022 in a convenience sample of Greek undergraduate nursing students. The Evidence-Based Practice Competence Questionnaire (EBP-COQ) and a questionnaire on undergraduate students’ gender, age, academic year, and training in the field of research were used. The SPSS 26.0 program was used to perform descriptive, bivariate and multivariate analyses. A total of 175 undergraduate students participated at the Hellenic University Nursing (Greece), specifically from the 2nd and 3rd academic year. The mean score of EBP-COQ for nursing undergraduate students was 3.03 ± 0.26, indicating moderate EBP. Among the EBP-COQ dimensions, the mean scores were obtained 3.03 ± 0.32 for Attitude toward EBP, 3.01 ± 0.49 for Skills in EBP, and 3.03 ± 0.49 for Knowledge in EBP. They were not found significant differences among participants’ mean EBP-COQ scores regarding gender (p = 0.766), age (p = 0.400), academic year (p = 0.153), and training in the field of Research Methodology (p = 0.538). It appears that the level of readiness towards EBP is mediocre between undergraduate nursing students at a university in Greece. Therefore, it is necessary to carry out new studies in the future, so that there is a correct approach of all the elements that contribute to the readiness of Nursing undergraduate students regarding EBP.
Redundancy in Innate Immune Pathways that Promote CD8+ T cell Responses in AAV Muscle Gene Transfer
Authors: Li Ning , Kumar Sandeep R.P. , Cao Di , Munoz-Melero Maite , Arisa Sreevani , Brian Bridget A. , Greenwood Calista M. , Yamada Kentaro , Duan Dongsheng , Herzog Roland W.
Published: August 2024

While adeno-associated viral (AAV) vectors are successfully used in a variety of in vivo gene therapy applications, they continue to be hampered by the immune system. Here, we sought to identify innate and cytokine signaling pathways that promote CD8+ T cell responses against the transgene product upon vector administration to murine skeletal muscle. Eliminating just one of several pathways (including DNA sensing via TLR9, IL-1 receptor signaling, and possibly endosomal sensing of double-stranded RNA) substantially reduced the CD8+ T cell response at lower vector doses but was surprisingly ineffective at higher doses. Using genetic, antibody-mediated, and vector engineering approaches, we show that blockade of at least two innate pathways is required to achieve an effect at higher vector doses. Concurrent blockade of IL-1R1>MyD88 and TLR9>MyD88>IFN I>IFNaR pathways was often but not always synergistic and had limited utility in preventing antibody formation against the transgene product. We further provide evidence that CpG depletion of vector genomes and inclusion of TLR9 inhibitory sequences can have a synergistic effect. However, even low-frequency CD8+ T cell responses could eliminate transgene expression. Thus, innate immune avoidance/blockade strategies, albeit helpful, may not be sufficient to prevent destructive cellular responses in muscle gene transfer because of redundancy of immune activating pathways.
Elucidating the Causal Link Between Hearing and Chronic Kidney Disease Through Mendelian Randomization and Development of Predictive Machine Learning Models Based on NHANES Data
Authors: Yang Yanting , Li Yuqing , Huang Zhongquan , Lin Rongrong , Chen Zhuoni , Zhang Ning , Zheng Nan , Xu Jiean , Zhou Yaqi
Published: August 2024

Chronic kidney disease (CKD) is a growing public health issue with significant morbidity and mortality rates. Traditional diagnostics, with about 70% accuracy, often delay CKD detection, highlighting the need for more efficient methods. Recent studies indicate a potential link between CKD and auditory health, yet this relationship remains underexplored due to methodological challenges and the complexity of establishing causality. Our research utilizes data spanning from 2000 to 2020 from the National Health and Nutrition Examination Survey (NHANES), covering 12,392 participants, including 2,060 diagnosed with CKD. Through meticulous analysis employing logistic regression and Mendelian randomization, we have unearthed novel insights into the bi-directional associations between hearing impairment and CKD. Furthermore, we developed and validated a machine learning model that surpasses traditional diagnostic approaches in terms of accuracy and predictive power. These findings highlight the innovative integration of auditory examinations with demographic data to enhance CKD detection. Our approach demonstrates the potential of machine learning in transforming diagnostic methodologies, thus offering a significant advancement in the field of nephrology and public health.
From Voxel to Gene: A Scoping Reviews on MRI Radiogenomics Artificial Intelligence Predictions in Adult Gliomas and Glioblastomas - the Promise of Virtual Biopsy?
Authors: LE GUILLOU HORN Xavier
Published: August 2024

Background: Gliomas, including the most severe form known as glioblastomas, are primary brain tumors arising from glial cells, with significant impact on adults, particularly men aged 45 to 70. Recent advancements in the WHO classification now correlate genetic markers with glioma phenotypes, enhancing diagnostic precision and therapeutic strategies. Aims and Methods: This scoping review aims to evaluate the current state of deep learning (DL) applications in the genetic characterization of adult gliomas, addressing the potential of these technologies for a reliable virtual biopsy. Results: We reviewed 17 studies, analyzing the evolution of DL algorithms from fully convolutional networks to more advanced architectures (ResNet and DenseNet). The methods involved various validation techniques, including k-fold cross-validation and external dataset validation. Conclusions: Our findings highlight significant variability in reported performance, largely due to small, homogeneous datasets and inconsistent validation methods. Despite promising results, particularly in predicting individual genetic traits, the lack of robust external validation limits the generalizability of these models. Future efforts should focus on developing larger, more diverse datasets and integrating multidisciplinary collaboration to enhance model reliability. This review underscores the potential of DL in advancing glioma characterization, paving the way for more precise, non-invasive diagnostic tools.
The Influence of Various Modifications of Hazelnut Shell Flour as Potential Filler in Plywood Technology
Authors: Wronka Marta , Wojnicz Damian , Kowaluk Grzegorz
Published: August 2024

This study investigates the potential of utilizing hazelnut shells (HS) as an innovative filler in three-layer plywood technology, addressing the growing need for sustainable, high-performance materials. Traditional plywood production relies on adhesives enhanced with various fillers to improve physical, mechanical, and operational characteristics. This research explores using native, chemically modified, and activated carbon derived from hazelnut shells as fillers in urea-formaldehyde (UF) resin. The mechanical properties, water absorption, and formaldehyde emissions of the produced plywood were thoroughly analyzed. Key findings demonstrate that incorporating 10 part by weight (pbw) native hazelnut shell flour significantly enhances the modulus of rupture (MOR) and modulus of elasticity (MOE). Chemically modified hazelnut shell flour achieves optimal results at 5 pbw, while activated carbon from hazelnut shells, even at 1 pbw, markedly improves bonding strength and thermal properties. Notably, activated carbon effectively reduces formaldehyde emissions and improves water resistance, indicating better further dimensional stability and lower environmental impact. The study also shows that excessive filler content negatively affects strength parameters, confirming the importance of optimizing filler concentration. These results highlight the potential of hazelnut shells as an eco-friendly alternative filler in plywood production, contributing to waste valorization and environmental sustainability. This study supports the practical application of hazelnut shell fillers, promoting a circular economy and reducing reliance on traditional, less sustainable materials, thus providing a valuable solution for the wood composite industry.
Evaluating Diabetes Risk: Bayesian Hierarchical Models and Machine Learning Integration
Authors: Muhammad Khan Noor , Rahman Md. Mizanoor , Chowdhury Mashfiqul Huq
Published: August 2024

Type 2 diabetes mellitus (T2DM) is a global health concern driven by factors such as obesity, sedentary behavior, and poor diet. This study uses data from the 2017-18 Bangladesh Demographic and Health Survey (BDHS) to analyze regional and individual predictors of diabetes and predi-abetes. Employing a Bayesian multinomial mixed-effects model, we account for regional varia-bility and individual factors like age, gender, BMI, residence, wealth, education, employment, and hypertension. Our results indicate significant regional differences and associations between de-mographic and health-related factors with diabetes risk. Younger individuals and those with higher BMI are more likely to be diabetic, while hypertension significantly increases diabetes risk. We applied machine learning (ML) models, including logistic regression, decision trees, k-nearest neighbor, linear discriminant analysis, and random forest, to classify diabetic status using these predictors, assessing their accuracy through 10-fold cross-validation. Logistic regression and linear discriminant analysis demonstrated robust performance across various response distributions. Simulation studies further examined the impact of different response distributions on model performance, revealing significant differences in classification accuracies. This approach of esti-mating parameters with a Bayesian model, applying ML for prediction, and conducting simulation studies to explore various scenarios highlights the importance of integrating these methodologies for effective diabetes prediction, providing insights for public health strategies to mitigate T2DM's impact.