bluuebunny/crossref_metadata_2025 huggingface dataset:
Deltoid Muscle Tension Alterations Post Reverse Shoulder Arthroplasty: An Investigation Using Shear Wave Elastography
Authors: Fenwick Annabel , Reichel Thomas , Eden Lars , Schmalzl Jonas , Meffert Rainer , Plumhoff Piet , Gilbert Fabian
Published: September 2023

Introduction: This study aimed to evaluate the utility of shear wave elastography (SWE) in assessing changes in deltoid muscle properties following reverse shoulder arthroplasty (RSA). Methods: Our cohort consisted of 18 patients who underwent RSA due to various conditions, including osteoarthritis, cuff arthropathy, and irreducible proximal humeral fractures. Pre- and postoperative muscle elasticity and stiffness were measured using SWE and were compared with functional outcomes and radiological parameters. Results: Our results showed significant changes in deltoid muscle elasticity after RSA, particularly in the anterior and middle portions. However, these alterations were not correlated with postoperative functional outcomes or specific radiological parameters. The study also underscored the potential of SWE for future applications, including the preoperative assessment of deltoid function, postoperative monitoring, and intraoperative use for optimal component positioning during RSA. Conclusion: Further research, involving larger, more homogeneous patient cohorts is needed to confirm these findings and to explore the potential influence of these changes on the biomechanical design of implants and prosthesis positioning in RSA.
A Systematic Review on Deep Learning with CNNs Applied to Surface Defect Detection
Authors: Cumbajin Esteban , Rodrigues Nuno , Costa Paulo , Miragaia Rolando , Frazão Luís , Costa Nuno , Fernández-Caballero Antonio , Carneiro Jorge , Buruberri Leire H. , Pereira António
Published: September 2023

Surface defect detection with machine learning has become an important tool in industries and a large field of study for researchers or workers in recent years. It is necessary to have a simplified source of information that helps us to better focus on one type of surface. In this systematic review, we present a classification for surface defect detection based on convolutional neural networks (CNNs) focused on surface types. Findings: Out of 253 records identified, 59 primary studies were eligible. Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, we analyzed the structures of each study and the concepts related to defects and their types on surfaces. The presented review is mainly focused on finding a classification for the types of surfaces most used in industry (metal, building, ceramic, wood, and special). We delve into the specifics of each surface category, offering illustrative examples of their applications within both industrial and laboratory settings. Furthermore, we propose a new taxonomy of machine learning based on the obtained results and collected information. We summarized the studies and extracted the main characteristics such as type of surface, problem types, timeline, type of network, techniques, and datasets. Among the most relevant results of our analysis, we found that the metallic surface is the most used, as it is the one found in 62.71% of the studies, and the most prevalent problem type is classification, accounting for 49.15% of the total. Furthermore, we observe that transfer learning was employed in 83.05% of the studies, while data augmentation was utilized in 59.32%. Our findings also provide insights into the cameras most frequently employed, along with the strategies adopted to address illumination challenges present in certain articles and the approach to creating datasets for real-world applications. The main results presented in this review allow for a quick and efficient search of information for researchers and professionals interested in improving the results of their defect detection projects. Finally, we analyzed the trends that could open new fields of study for future research in the area of surface defect detection.
Lignicolous Freshwater Fungi from Plateau Lakes in China (I): Morphological and Phylogenetic Analyses Reveal Eight Species of Lentitheciaceae, Including New Genus, New Species and New Records
Authors: Shen Hong-Wei , Bao Dan-Feng , Boonmee Saranyaphat , Su Xi-Jun , Tian Xing-Guo , Hyde Kevin D. , Luo Zong-Long
Published: September 2023

During the investigation of lignicolous freshwater fungi in plateau lakes in Yunnan Province, China, eight Lentitheciaceae species were collected from five lakes viz. Luguhu, Qiluhu, Xingyunhu, Cibihu, and Xihu lake. Based on morphological characters and phylogenetic analysis of combined ITS, LSU, SSU, and tef 1-α sequence data, a new genus Paralentithecium, two new species (Paralentithecium suae, and Setoseptoria suae), three new records (Halobyssothecium phragmitis, H. unicellulare, and Lentithecium yunnanensis) and three known species viz. Halobyssothecium aquifusiforme, Lentithecium pseudoclioninum, and Setoseptoria bambusae are reported.
Phase-Dependent Differential In Vitro and Ex Vivo Susceptibility of Aspergillus flavus and Fusarium keratoplasticum to Azole Antifungals
Authors: Roberts Darby , Salmon Jacklyn , Cubeta Marc A. , Gilger Brian C.
Published: September 2023

Fungal keratitis (FK) is an invasive infection of the cornea primarily associated with Aspergillus and Fusarium species. FK is treated empirically with a limited selection of topical antifungals with varying levels of success. Though clinical infections are typically characterized by a dense network of mature mycelium, traditional models used to test antifungal susceptibility of FK isolates exclusively evaluate susceptibility in fungal cultures derived from asexual spores known as conidia. The purpose of this study was to characterize differences in fungal response when topical antifungal treatment is initiated at progressive phases of fungal development. We compared the efficacy of voriconazole and luliconazole against in vitro cultures of A. flavus and F. keratoplasticum at 0, 24, and 48 h of fungal development. A porcine cadaver corneal model was used to compare antifungal efficacy of voriconazole and luliconazole in ex vivo tissue cultures of A. flavus and F. keratoplasticum at 0, 24, and 48 h of fungal development. Our results demonstrate phase-dependent susceptibility of both A. flavus and F. keratoplasticum to both azoles in vitro as well as ex vivo. We conclude that traditional antifungal susceptibility testing with conidial suspensions does not correlate with fungal susceptibility in cultures of a more advanced developmental phase. A revised method of antifungal susceptibility testing that evaluates hyphal susceptibility may better predict fungal response in the clinical setting where treatment is often delayed until days after the initial insult.
Receptor Tyrosine Kinase KIT: Mutation-Induced Conformational Shift Promotes Alternative Allosteric Pockets
Authors: Ledoux Julie , Botnari Marina , Tchertanov Luba
Published: September 2023

Receptor tyrosine kinase (RTK) KIT is key regulator of cellular signalling, and its deregulation contributes to the development and progression of many serious diseases. Several mutations lead to the constitutive activation of the cytoplasmic domain of KIT, causing the aberrant intracellular signalling observed in malignant tumours. Elucidating the molecular basis of mutation-induced effects at the atomistic level is absolutely required. We report the first dynamic 3D model (DYNASOME) of the full-length cytoplasmic domain of the oncogenic mutant KITD816V generated through unbiased long-timescale MD simulations under conditions mimicking the natural environment of KIT. The comparison of the structural and dynamical properties of multidomain KITD816V with those of wild type KIT (KITWT) allowed us to evaluate the impact of the D816V mutation on each protein domain, including multifunctional well-ordered and intrinsically disordered (ID) regions. The two proteins were compared in terms of free energy landscape and intramolecular coupling. The increased intrinsic disorder and gain of coupling within each domain and between distant domains in KITD816V demonstrate its inherent self-regulated constitutive activation. The search for pockets revealed novel allosteric pockets (POCKETOME) in each protein, KITD816V and KITWT. These pockets open an avenue for the development of new highly selective allosteric modulators specific to KITD816V.
Environmental and Social Benefits of Extensive Green Roofs Applied on Bus Shelters in Edinburgh
Authors: Koscikova Zuzana , Krivtsov Vladimir
Published: September 2023

The presence of green roofs in urban areas provides various ecosystem services that help mitigate climate change. They play an essential role in sustainable drainage systems, contribute to air quality and carbon sequestration, mitigate urban heat island, support biodiversity, and create green spaces supporting public well-being. Bus stops provide good opportunities for installing green roofs. Various cities worldwide have started installing green roofs on bus shelters, but often without thoroughly comparing expenses and the resulting benefits. This study quantifies the social and environmental benefits of installing green roofs on bus shelters in the City of Edinburgh. An assessment of the benefits and their monetary values was conducted using the B£ST analysis tool combined with manual calculations, which is easily transferable to other cities worldwide. It was compared to the current situation with no green roofs installed at bus stops. Installation of green roofs on all bus shelters in the City of Edinburgh may result in £12.9 million–£87.2 million in total benefit present value. The total cost was projected to be £15,994,000. By green roof installation, the City of Edinburgh can be closer to being carbon-neutral by 2030, a sustainable city as part of the City Plan 2030 and City Vision 2050.
Forest Inventory Data Provide Useful Information for Mapping Ecosystem Services Potential
Authors: Jūrmalis Edgars , Bārdule Arta , Donis Jānis , Gerra-Inohosa Linda , Lībiete Zane
Published: September 2023

The ecosystem services framework is a convenient approach for identifying and mapping nature’s contributions to people, and an accurate assessment of ecosystem services potential is the first step in the decision support process of well-informed land management planning. The approach we use for forest ecosystem services potential assessment in Latvia is based on the principles of the matrix model and biophysical data of the forest inventory database, and it is comparable to other assessments previously carried out in the Baltic Sea Region. The proposed approach supports spatial planning and may be integrated with assessments of other ecosystems based on the same methodological principles. The evaluation results reflect the high spatial heterogeneity of forest types in Latvia. Future work should include integrating ecosystem services flows and demand into the assessment, developing additional indicators for culturally important ecosystem services, and introducing socio-cultural valuation to account for a broader set of stakeholders and values.
The Role of Different Methods in Defining Cardiometabolic Risk and Metabolic Syndrome in Women with Polycystic Ovary Syndrome
Authors: Çakır Biçer Nihan , Ermiş Asime Aleyna , Baş Dilşat
Published: September 2023

Polycystic ovary syndrome (PCOS) is one of the most frequent endocrine illnesses, often accompanied by visceral adiposity and metabolic syndrome (MetS). Visceral adiposity is an accurate predictor of MetS and cardiometabolic risk. This study aims to evaluate different anthropometric indices that can be used in PCOS and MetS risk assessment. A total of 66 women with PCOS (50%) and 66 controls (50%) were included, and clinical and biochemical parameters were evaluated. The body mass index (BMI), body shape index (ABSI), body roundness index (BRI), dysfunctional adiposity index (DAI), lipid accumulation (LAP) index, and visceral adiposity index (VAI) were calculated. The means of all indices were higher in the PCOS group (p < 0.05). The marker with the lowest discriminatory ability for PCOS and MetS was ABSI (AUC = 0.762 and AUC = 0.714, respectively, p = 0.000). According to the multivariate logistic regression model, the VAI and WC are strong predictors of PCOS (AUC, 98%; accuracy, 92%; sensitivity, 92%; and specificity, 91%), and WC, LAP index, and BRI are strong predictors of MetS (AUC, 0.95%; accuracy, 86%; sensitivity, 83%; and specificity, 88%). The use of different anthropometric indices in the detection of PCOS and MetS may allow for early diagnosis and treatment, and are simple and cost-effective.
Colchicine-Induced Polyploidy in Leguminous Crops Enhances Morpho-Physiological Characteristics for Drought Stress Tolerance
Authors: Mangena Phetole , Mushadu Pirtunia Nyadzani
Published: September 2023

Legumes play a significant role in the alleviation of food insecurity, maintaining soil fertility, and achieving sustainable crop production under adverse environmental conditions. The increased demand in legume production contemplates that attention on the genetic improvement of these crops through various means such as genetic engineering and mutation breeding should take a centre stage in global agriculture. Therefore, this paper provides a succinct analysis of the currently available literature on morphological and physiological traits in polyploidised leguminous plants to counter the adverse effects of drought stress. The effects of colchicine on various morphological and physiological traits of polyploidised legumes compared to their diploid counterparts were examined. Numerous reports revealed variations in these traits, such as improved root and shoot growth, plant biomass, chloroplastidic content, protein, RNA, and DNA. The differences observed were also associated with the strong relationship between plant ploidy induction and colchicine application. Furthermore, the analysis indicated that polyploidisation remains dose-dependent and may be achievable within a shorter space of time as this antimitotic chemical interferes with chromosome separations in somatic plant cells. The efficiency of this process also depends on the advancement of treatment conditions (in vitro, in vivo, or ex vitro) and the successful regeneration of polyploidised plants for adaptation under drought stress conditions. As such, the improvement in metabolite profile and other essential growth characteristics serves as a clear indication that induced polyploidy needs to be further explored to confer resilience to environmental stress and improve crop yield under drought stress conditions in leguminous plants.
Research and Application Progress of Resin-Based Composite Materials in the Electrical Insulation Field
Authors: Yan Bingyue , Zhang Zhuo , Li Yin , Cui Huize , Zhang Chong , He Jianfei
Published: September 2023

The research and application progress of resin-based composite materials in the field of electrical insulation has attracted considerable attention and emerged as a current research hotspot. This review comprehensively summarized the research and application progress of resin-based composite materials in the field of electrical insulation, providing detailed insights into their concept, properties, and preparation methods. In addition, a comprehensive evaluation of the electrical insulation performance, mechanical properties, and thermal properties of resin-based composite materials was presented, along with an in-depth analysis of their current application status. Despite the immense potential and development opportunities of resin-based composite materials, they also face several challenges. This review serves as a valuable reference and resource for researchers in related fields and aimed to promote further research and application development of resin-based composite materials in the field of electrical insulation.
Analysis of the Mechanical Properties of a Stabilized Subgrade Type Soil under a Sustainable Approach for Construction
Authors: Gallego-Quintana Pedro , Ojeda-Farias Omar Farid , Alvarez-Rosario Alexander , Alvarez-Sánchez Ervin Jesús , Landa-Ruiz Laura , Terán-Torres Bernardo T. , Mendoza-Rangel José Manuel , Baltazar-Zamora Miguel Ángel
Published: September 2023

This article presents an experimental study to analyze the mechanical properties of a soil stabilized with ordinary Portland cement (OPC) under a sustainable approach consisting of a significant substitution of OPC for sugarcane bagasse ash (SCBA) to reduce the quantity of cement used in the stabilization, reaching the necessary mechanical requirements for its use as a subgrade layer. Soil specimens were elaborated with 3%, 5%, and 7% OPC as a stabilizing agent by weight of the soil. These mixtures were then partially substituted with 25%, 50%, and 75% SCBA, with these percentages being by weight of the stabilizer (OPC). Compaction, compressive strength, and California bearing ratio (CBR) tests were performed to evaluate the mechanical properties of the specimens. The results indicate that a 25% substitution of OPC by SCBA shows a similar performance to the mixture with only Portland cement, so a reduction in OPC use can be made. Further, with a substitution of 100% OPC by SCBA, the CBR of natural soil without stabilizers is improved.
Indoor Air Pollutant (Toluene) Reduction Based on Ultraviolet-A Irradiance and Changes in the Reactor Volume in a TiO2 Photocatalyst Reactor
Authors: Song Yong-Woo , Kim Seong-Eun , Yoo Min-Sang , Park Jin-Chul
Published: September 2023

This study experimentally confirmed the effect of TiO2 photocatalysts on the removal of indoor air pollutants. In the experiment, toluene, a representative indoor air pollutant, was removed using a coating agent containing TiO2 photocatalysts. Conditions proposed by the International Organization for Standardization (ISO) were applied mutatis mutandis, and a photoreactor for an experiment was manufactured. The experiment was divided into two categories. The first experiment was conducted under ISO conditions using the TiO2 photocatalyst coating agent. In the second experiment, the amount of ultraviolet-A (UV-A) light was varied depending on the lamp’s service life, and the volume of the reactor was varied depending on the number of contaminants. The results showed that the TiO2 photocatalytic coating agent reduced the effect of toluene. This reduction effect can be increased as a primary function depending on the changes in the amount of UV-A light and reactor volume. However, because toluene is decomposed in this study, additional organic pollutants such as benzene and butadiene can be produced. Because these pollutants are decomposed by the TiO2 photocatalysts, the overall reduction performance may change. Nonetheless, TiO2 photocatalysts can be used to examine the effect of indoor pollutant reduction in indoor ventilation systems and building materials.
Self-Discharge Processes in Symmetrical Supercapacitors with Activated Carbon Electrodes
Authors: Rychagov Alexey Yu. , Sosenkin Valentin E. , Izmailova Marianna Yu. , Kabachkov Evgeny N. , Shulga Yury M. , Volfkovich Yury M. , Gutsev Gennady L.
Published: September 2023

The self-discharge of an electric double-layer capacitor with composite activated carbon electrodes and aqueous electrolyte (1 M MgSO4) was studied in detail. Under a long-term potentiostatic charge (stabilization), a decrease in the discharge capacity was observed in the region of voltages exceeding 0.8 V. The self-discharge process consists of two phases. In the initial phase, the cell voltage drop is due to the charge redistribution inside electrodes. During the main phase, the charge transfer between the electrodes determines the voltage drop. The optimal stabilization time of the self-discharge was found to be 50 min at 1.4 V. Hydrophilization of the negative electrode occurred during long-term polarization due to the formation of epoxy functional groups.
Unraveling COVID-19 Dynamics via Machine Learning and XAI: Investigating Variant Influence and Prognostic Classification
Authors: Lohaj Oliver , Paralič Ján , Bednár Peter , Paraličová Zuzana , Huba Matúš
Published: September 2023

Machine learning (ML) has been used in different ways in the fight against COVID-19 disease. ML models have been developed, e.g., for diagnostic or prognostic purposes and using various modalities of data (e.g., textual, visual, or structured). Due to the many specific aspects of this disease and its evolution over time, there is still not enough understanding of all relevant factors influencing the course of COVID-19 in particular patients. In all aspects of our work, there was a strong involvement of a medical expert following the human-in-the-loop principle. This is a very important but usually neglected part of the ML and knowledge extraction (KE) process. Our research shows that explainable artificial intelligence (XAI) may significantly support this part of ML and KE. Our research focused on using ML for knowledge extraction in two specific scenarios. In the first scenario, we aimed to discover whether adding information about the predominant COVID-19 variant impacts the performance of the ML models. In the second scenario, we focused on prognostic classification models concerning the need for an intensive care unit for a given patient in connection with different explainability AI (XAI) methods. We have used nine ML algorithms, namely XGBoost, CatBoost, LightGBM, logistic regression, Naive Bayes, random forest, SGD, SVM-linear, and SVM-RBF. We measured the performance of the resulting models using precision, accuracy, and AUC metrics. Subsequently, we focused on knowledge extraction from the best-performing models using two different approaches as follows: (a) features extracted automatically by forward stepwise selection (FSS); (b) attributes and their interactions discovered by model explainability methods. Both were compared with the attributes selected by the medical experts in advance based on the domain expertise. Our experiments showed that adding information about the COVID-19 variant did not influence the performance of the resulting ML models. It also turned out that medical experts were much more precise in the identification of significant attributes than FSS. Explainability methods identified almost the same attributes as a medical expert and interesting interactions among them, which the expert discussed from a medical point of view. The results of our research and their consequences are discussed.
Brainstorming Will Never Be the Same Again—A Human Group Supported by Artificial Intelligence
Authors: Lavrič Franc , Škraba Andrej
Published: September 2023

A modification of the brainstorming process by the application of artificial intelligence (AI) was proposed. Here, we describe the design of the software system “kresilnik”, which enables hybrid work between a human group and AI. The proposed system integrates the Open AI-GPT-3.5–turbo model with the server side providing the results to clients. The proposed architecture provides the possibility to not only generate ideas but also categorize them and set priorities. With the developed prototype, 760 ideas were generated on the topic of the design of the Gorenjska region’s development plan with eight different temperatures with the OpenAI-GPT-3.5-turbo algorithm. For the set of generated ideas, the entropy was determined, as well as the time needed for their generation. The distributions of the entropy of the ideas generated by the human-generated and the AI-generated sets of ideas of the OpenAI-GPT-3.5–turbo algorithm at different temperatures are provided in the form of histograms. Ideas are presented as word clouds and histograms for the human group and the AI-generated sets. A comparison of the process of generating ideas between the human group and AI was conducted. The statistical Mann-Whitney U-test was performed, which confirmed the significant differences in the average entropy of the generated ideas. Correlations between the length of the generated ideas and the time needed were determined for the human group and AI. The distributions for the time needed and the length of the ideas were determined, which are possible indicators to distinguish between human and artificial processes of generating ideas.
An Extended Zeta Function with Applications in Model Building and Bayesian Analysis
Authors: Mathai Arak M.
Published: September 2023

In certain problems in model building and Bayesian analysis, the results end up in forms connected with generalized zeta functions. This necessitates the introduction of an extended form of the generalized zeta function. Such an extended form of the zeta function is introduced in this paper. In model building situations and in various types of applications in physical, biological and social sciences and engineering, a basic model taken is the Gaussian model in the univariate, multivariate and matrix-variate situations. A real scalar variable logistic model behaves like a Gaussian model but with a thicker tail. Hence, for many of industrial applications, a logistic model is preferred to a Gaussian model. When we study the properties of a logistic model in the multivariate and matrix-variate cases, in the real and complex domains, invariably the problem ends up in the extended zeta function defined in this paper. Several such extended logistic models are considered. It is also found that certain Bayesian considerations also end up in the extended zeta function introduced in this paper. Several such Bayesian models in the multivariate and matrix-variate cases in the real and complex domains are discussed. It is stated in a recent paper that “Quantum Mechanics is just the Bayesian theory generalized to the complex Hilbert space”. Hence, the models developed in this paper are expected to have applications in quantum mechanics, communication theory, physics, statistics and related areas.
Mutable Collagenous Tissue Isolated from Echinoderms Leads to the Production of a Dermal Template That Is Biocompatible and Effective for Wound Healing in Rats
Authors: Carolo Anna , Melotti Luca , Zivelonghi Giulia , Sacchetto Roberta , Akyürek Eylem Emek , Martinello Tiziana , Venerando Andrea , Iacopetti Ilaria , Sugni Michela , Martinelli Giordana , Roncoroni Margherita , Marzorati Stefania , Barbon Silvia , Contran Martina , Incendi Damiana , Perozzo Filippo , Porzionato Andrea , Vindigni Vincenzo , Patruno Marco
Published: September 2023

The mutable collagenous tissue (MCT) of echinoderms possesses biological peculiarities that facilitate native collagen extraction and employment for biomedical applications such as regenerative purposes for the treatment of skin wounds. Strategies for skin regeneration have been developed and dermal substitutes have been used to cover the lesion to facilitate cell proliferation, although very little is known about the application of novel matrix obtained from marine collagen. From food waste we isolated eco-friendly collagen, naturally enriched with glycosaminoglycans, to produce an innovative marine-derived biomaterial assembled as a novel bi-layered skin substitute (Marine Collagen Dermal Template or MCDT). The present work carried out a preliminary experimental in vivo comparative analysis between the MCDT and Integra, one of the most widely used dermal templates for wound management, in a rat model of full-thickness skin wounds. Clinical, histological, and molecular evaluations showed that the MCDT might be a valuable tool in promoting and supporting skin wound healing: it is biocompatible, as no adverse reactions were observed, along with stimulating angiogenesis and the deposition of mature collagen. Therefore, the two dermal templates used in this study displayed similar biocompatibility and outcome with focus on full-thickness skin wounds, although a peculiar cellular behavior involving the angiogenesis process was observed for the MCDT.
Artificial Intelligence and Neurosurgery: Tracking Antiplatelet Response Patterns for Endovascular Intervention
Authors: Saigal Khushi , Patel Anmol Bharat , Lucke-Wold Brandon
Published: September 2023

Platelets play a critical role in blood clotting and the development of arterial blockages. Antiplatelet therapy is vital for preventing recurring events in conditions like coronary artery disease and strokes. However, there is a lack of comprehensive guidelines for using antiplatelet agents in elective neurosurgery. Continuing therapy during surgery poses a bleeding risk, while discontinuing it before surgery increases the risk of thrombosis. Discontinuation is recommended in neurosurgical settings but carries an elevated risk of ischemic events. Conversely, maintaining antithrombotic therapy may increase bleeding and the need for transfusions, leading to a poor prognosis. Artificial intelligence (AI) holds promise in making difficult decisions regarding antiplatelet therapy. This paper discusses current clinical guidelines and supported regimens for antiplatelet therapy in neurosurgery. It also explores methodologies like P2Y12 reaction units (PRU) monitoring and thromboelastography (TEG) mapping for monitoring the use of antiplatelet regimens as well as their limitations. The paper explores the potential of AI to overcome such limitations associated with PRU monitoring and TEG mapping. It highlights various studies in the field of cardiovascular and neuroendovascular surgery which use AI prediction models to forecast adverse outcomes such as ischemia and bleeding, offering assistance in decision-making for antiplatelet therapy. In addition, the use of AI to improve patient adherence to antiplatelet regimens is also considered. Overall, this research aims to provide insights into the use of antiplatelet therapy and the role of AI in optimizing treatment plans in neurosurgical settings.
The Impact of Assisted Reproductive Technology on Umbilical Cord Insertion: Increased Risk of Velamentous Cord Insertion in Singleton Pregnancies Conceived through ICSI
Authors: Fukuda Eriko , Hamuro Akihiro , Kitada Kohei , Kurihara Yasushi , Tahara Mie , Misugi Takuya , Nakano Akemi , Tamaue Mami , Shinomiya Sae , Yoshida Hisako , Koyama Masayasu , Tachibana Daisuke
Published: September 2023

Background and Objectives: Vasa previa (VP) is a significant perinatal complication that can have serious consequences for the fetus/neonate. Velamentous cord insertion (VCI) is a crucial finding in prenatal placental morphology surveillance as it is indicative of comorbid VP. Assisted reproductive technology (ART) has been identified as a risk factor for VCI, so identifying risk factors for VCI in ART could improve VP recognition. This study aims to evaluate the displacement of umbilical cord insertion (CI) from the placental center and to examine the relationship between the modes of conception. Materials and Methods: We conducted a retrospective study at the Obstetrics Department of Osaka Metropolitan University Hospital in Japan between May 2020 and June 2022. The study included a total of 1102 patients who delivered after 22 weeks of gestation. They were divided into three groups: spontaneous pregnancy, conventional in vitro fertilization (cIVF), and in vitro fertilization/intracytoplasmic sperm injection (IVF/ICSI). We recorded patient background information, perinatal complications, perinatal outcomes, and a numerical “displacement score”, indicating the degree of separation between umbilical CI and the placental center. Results: The displacement score was significantly higher in the cIVF and IVF/ICSI groups compared with the spontaneous conception group. Additionally, the IVF/ICSI group showed a significantly higher displacement score than the cIVF group. Conclusions: Our study provides the first evidence that the methods of ART can affect the location of umbilical CI on the placental surface. Furthermore, we found that IVF/ICSI may contribute to greater displacement of CI from the placental center.
Applications of Lab on a Chip in Antimicrobial Susceptibility of Staphylococcus aureus: A Systematic Review
Authors: Ardila Carlos M. , Zuluaga-Gómez Mateo , Vivares-Builes Annie Marcela
Published: September 2023

Background and Objectives: Staphylococcus aureus is a prevalent bacterium capable of inducing various infections, including skin and soft tissue infections, bloodstream infections, pneumonia, and surgical site infections. The emergence of antimicrobial resistance in S. aureus, particularly methicillin-resistant S. aureus, has raised substantial concerns within global healthcare settings. Prior to antibiotic prescription, the ideal approach is antimicrobial susceptibility testing (AST); however, this is frequently perceived as excessively complex and time-intensive. Lab-on-a-chip (LOC) technology holds promise in addressing these challenges and advancing fundamental microbiological research while also aiding in the development of therapeutic strategies. This systematic review aims to evaluate the potential utility of LOC for AST of S. aureus. Materials and Methods: This study adhered to the PRISMA guidelines. Various databases, including SCOPUS, PubMed/MEDLINE, SCIELO, and LILACS, in addition to gray literature sources, were employed in the review process. Results: Sixteen studies were included in this systematic review. All these studies detailed the effectiveness, rapidity, and predictability of LOC systems for assessing S. aureus susceptibility to various antibiotics. When comparing the LOC approach to traditional manual methods, it was evident that LOC requires a minimal quantity of reagents. Furthermore, most studies reported that the entire LOC procedure took 10 min to 7 h, with results being equally accurate as those obtained through traditional AST protocols. Conclusions: The potential application of LOC for AST of S. aureus is emphasized by its ability to provide rapid access to minimum inhibitory concentration data, which can substantially aid in selecting the most suitable antibiotics and dosages for treating challenging infections caused by this microorganism. Moreover, the rapid AST facilitated by LOC holds promise for enhancing the appropriateness and efficacy of therapy in clinical settings.
Augmented Reality in Neurosurgery: A New Paradigm for Training
Authors: Hey Grace , Guyot Michael , Carter Ashley , Lucke-Wold Brandon
Published: September 2023

Augmented reality (AR) involves the overlay of computer-generated images onto the user’s real-world visual field to modify or enhance the user’s visual experience. With respect to neurosurgery, AR integrates preoperative and intraoperative imaging data to create an enriched surgical experience that has been shown to improve surgical planning, refine neuronavigation, and reduce operation time. In addition, AR has the potential to serve as a valuable training tool for neurosurgeons in a way that minimizes patient risk while facilitating comprehensive training opportunities. The increased use of AR in neurosurgery over the past decade has led to innovative research endeavors aiming to develop novel, more efficient AR systems while also improving and refining present ones. In this review, we provide a concise overview of AR, detail current and emerging uses of AR in neurosurgery and neurosurgical training, discuss the limitations of AR, and provide future research directions. Following the guidelines of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA), 386 articles were initially identified. Two independent reviewers (GH and AC) assessed article eligibility for inclusion, and 31 articles are included in this review. The literature search included original (retrospective and prospective) articles and case reports published in English between 2013 and 2023. AR assistance has shown promise within neuro-oncology, spinal neurosurgery, neurovascular surgery, skull-base surgery, and pediatric neurosurgery. Intraoperative use of AR was found to primarily assist with surgical planning and neuronavigation. Similarly, AR assistance for neurosurgical training focused primarily on surgical planning and neuronavigation. However, studies included in this review utilize small sample sizes and remain largely in the preliminary phase. Thus, future research must be conducted to further refine AR systems before widespread intraoperative and educational use.
Espresso: A Global Deep Learning Model to Estimate Precipitation from Satellite Observations
Authors: Berthomier Léa , Perier Laurent
Published: September 2023

Estimating precipitation is of critical importance to climate systems and decision-making processes. This paper presents Espresso, a deep learning model designed for estimating precipitation from satellite observations on a global scale. Conventional methods, like ground-based radars, are limited in terms of spatial coverage. Satellite observations, on the other hand, allow global coverage. Combined with deep learning methods, these observations offer the opportunity to address the challenge of estimating precipitation on a global scale. This research paper presents the development of a deep learning model using geostationary satellite data as input and generating instantaneous rainfall rates, calibrated using data from the Global Precipitation Measurement Core Observatory (GPMCO). The performance impact of various input data configurations on Espresso was investigated. These configurations include a sequence of four images from geostationary satellites and the optimal selection of channels. Additional descriptive features were explored to enhance the model’s robustness for global applications. When evaluated against the GPMCO test set, Espresso demonstrated highly accurate precipitation estimation, especially within equatorial regions. A comparison against six other operational products using multiple metrics indicated its competitive performance. The model’s superior storm localization and intensity estimation were further confirmed through visual comparisons in case studies. Espresso has been incorporated as an operational product at Météo-France, delivering high-quality, real-time global precipitation estimates every 30 min.
Glutathione Concentration in Dunaliella salina: A Growth-Phase-Dependent Study
Authors: Kurahashi Midori , Naka Angelica , Enokida Kazuhiko , Morita Yasuhiko
Published: September 2023

The microalga Dunaliella salina can produce antioxidants such as glutathione, which is an essential and powerful regulator of major cell functions. Changes in the glutathione concentration occur due to a microalga’s response to oxidative stress, which usually occurs when cells are exposed to environmental stressors or reach senescence. This study represents one of the few examples where changes in the glutathione concentration were tracked over the entire growth cycle of an alga. We found significant differences in the glutathione concentration depending on the growth stage. During the early lag growth phase, D. salina had relatively low levels of glutathione (190–280 µmol/1012 cell), which gradually increased as it entered the log phase (280–500 µmol/1012 cell) but then decreased as it entered the stationary phase (320–370 µmol/1012 cell). We also observed that the ratio between the reduced form of glutathione (GSH) and the oxidized form (GSSG) decreased with time, probably as a result of senescence or a lack of nutrients.
Rubble Mines in the Environs of Veszprém (Bakony Region, Hungary)
Authors: Veress Márton
Published: September 2023

In the Bakony Region, in the mines of dolomite (dolostone) surfaces between the settlements of Márkó and Pétfürdő (Várpalota), in rubble beds exposed by them and with the consideration of these, the process of rubble formation is studied here in order to interpret the characteristics of rubble beds (different thicknesses and vertical changes in grain size) in the studied area. The mines in the area (differentiated between old-school/traditional mining or mechanical mining) were classified with the consideration of mining methods. Rubble varieties were differentiated, the bedding of rubble beds was studied along profiles, and the elevation difference between mines of mechanical mining and Stream Séd was determined. The calcareous content and structure compactness of 124 samples originating from dolomite, rubble, and non-rubble in the Bakony Region were compared. The data prove that the rubble developed by dissolution. Dissolution might have been caused by both meteoric water and karstwater. The rubble of mines excavated by traditional mining mainly developed to the effect of the dissolution effect of meteoric water (the rubble beds are of coarser and coarser grain size downwards), while the mines excavated by mechanical mining were formed to the dissolution effect of karstwater (the rubble beds are coarser and coarser upwards). The formation of rubble by karstwater origin has not been mentioned in the literature yet. However, dissolution of meteoric water origin may also take place in the case of the latter, and dissolution of karstwater origin also plays a role in the development of mines excavated by traditional mining.
Unlocking the Therapeutic Potential of Stevia rebaudiana Bertoni: A Natural Antiglycating Agent and Non-Toxic Support for HDF Cell Health
Authors: Shahu Rinkey , Kumar Dinesh , Ali Ahmad , Tungare Kanchanlata , Al-Anazi Khalid Mashay , Farah Mohammad Abul , Jobby Renitta , Jha Pamela
Published: September 2023

Sugar carbonyl groups interact with protein amino groups, forming toxic components referred to as advanced glycation end products (AGEs). The glycation system (BSA, a model protein, and fructose) was incubated for five weeks at 37 °C in the presence and absence of Stevia leaf extract. The results indicated that the leaf extract (0.5 mg/mL) decreased the incidence of browning (70.84 ± 0.08%), fructosamine (67.27 ± 0.08%), and carbonyl content (64.04 ± 0.09%). Moreover, we observed an 81 ± 8.49% reduction in total AGEs. The inhibition of individual AGE (argpyrimidine, vesper lysine, and pentosidine) was ~80%. The decrease in the protein aggregation was observed with Congo red (46.88 ± 0.078%) and the Thioflavin T (31.25 ± 1.18%) methods in the presence of Stevia leaf extract. The repercussion of Stevia leaf extract on DNA glycation was examined using agarose gel electrophoresis, wherein the DNA damage was reversed in the presence of 1 mg/mL of leaf extract. When the HDF cell line was treated with 0.5 mg/mL of extract, the viability of cells decreased by only ~20% along with the same cytokine IL-10 production, and glucose uptake decreased by 28 ± 1.90% compared to the control. In conclusion, Stevia extract emerges as a promising natural agent for mitigating glycation-associated challenges, holding potential for novel therapeutic interventions and enhanced management of its related conditions.
Recent Advances in Functional Nanomaterials for Electrochemical Sensors and Biosensors
Authors: Luo Liqiang
Published: September 2023

Considering the unique advantages of the quantum size, volume, surface, and macroscopical quantum tunnel effects, nanomaterials have been paid increasing attention for various applications in environmental, medical, biological, and chemical analyses in recent decades [...]
Experimental and Computational Study on Inhibitory Effect and Adsorption Properties of N-Acetylcysteine Amino Acid in Acid Environment
Authors: Samide Adriana , Dobriţescu Aurelian , Tigae Cristian , Spînu Cezar Ionuţ , Oprea Bogdan
Published: September 2023

Potentiodynamic polarization (PDP) and electrochemical impedance spectroscopy (EIS) were applied to study the inhibitory effect of N-acetylcysteine (NAC) on corrosion inhibition of carbon steel in hydrochloric acid solution. N-acetylcysteine influenced the iron dissolution to a greater extent than the hydrogen evolution reaction acting as a mixed inhibitor, predominantly anodic. The charge transfer resistance (Rct) gradually increased with the inhibitor concentration. From both methods, the inhibition efficiency (IE) reached a value of 89 ± 1% and NAC adsorption followed the Temkin isotherm. The value of adsorption Gibbs energy (ΔGadso), around −35 kJ mol−1, indicated a spontaneous adsorption and mixed action mechanism, with NAC chemical adsorption prevailing over physical one. New data will be reported by the computational study, that was performed using the density functional theory (DFT) method in aqueous phase. Quantum chemical descriptors were determined by B3LYP theory level with 6–31G+(d) basis set. Metropolis Monte Carlo atomistic simulation was used to reveal the adsorption configuration and interactions between acetylcysteine molecules and the carbon steel surface. Theoretical results were consistent with the experimental data, showing that the inhibitor action mechanism consisted of mainly chemisorption of its molecules on the carbon steel surface accompanied by van der Waals forces and electrostatic interactions.
Coordination Complexes Built from a Ditopic Triazole-Pyrazole Ligand with Antibacterial and Antifungal Performances
Authors: Draoui Youssef , Radi Smaail , El Massaoudi Mohamed , Bahjou Yousra , Ouahhoud Sabir , Mamri Samira , Ferbinteanu Marilena , Benabbes Redouane , Wolff Mariusz , Robeyns Koen , Garcia Yann
Published: September 2023

Four mononuclear complexes (H3O){[NiL3](ClO4)3} (1), [CoL3](ClO4)2·2H2O (2), [CdL2Cl2] (3) and [CuL3](NO3)2 (4) have been prepared employing a newly synthesized 1,2,4-triazole ligand: 3-(3,5-dimethyl-1H-pyrazol-1-yl)-1H-1,2,4-triazole (L). The structures of the complexes, which crystallized in P63/m (1), P-1 (2), P1 (3), and P21/c (4), are reviewed within the context of the cooperative effect of the hydrogen bonding network and counter anions on the supramolecular formations. Moreover, within the framework of biological activity examination, these compounds showed favorable antibacterial performances compared to those of various species of bacteria, including both Gram-positive and Gram-negative strains. Significant antifungal inhibitory activity towards Fusarium oxysporum f. sp. albedinis fungi was recorded for 3 and 4 over the ligand L.
Uncertainty Evaluation for the Quantification of Urinary Amphetamine and 4-Hydroxyamphetamine Using Liquid Chromatography–Tandem Mass Spectrometry: Comparison of the Guide to the Expression of Uncertainty in Measurement Approach and the Monte Carlo Method with R
Authors: Kim Seon Yeong , Shin Dong Won , Hyun Jihye , Kwon Nam Hee , Cheong Jae Chul , Paeng Ki-Jung , Lee Jooyoung , Kim Jin Young
Published: September 2023

Estimating the measurement uncertainty (MU) is becoming increasingly mandatory in analytical toxicology. This study evaluates the uncertainty in the quantitative determination of urinary amphetamine (AP) and 4-hydroxyamphetamine (4HA) using a liquid chromatography–tandem mass spectrometry (LC–MS/MS) method based on the dilute-and-shoot approach. Urine sample dilution, preparation of calibrators, calibration curve, and method repeatability were identified as the sources of uncertainty. To evaluate the MU, the Guide to the Expression of Uncertainty in Measurement (GUM) approach and the Monte Carlo method (MCM) were compared using the R programming language. The MCM afforded a smaller coverage interval for both AP (94.83, 104.74) and 4HA (10.52, 12.14) than that produced by the GUM (AP (92.06, 107.41) and 4HA (10.21, 12.45)). The GUM approach offers an underestimated coverage interval for Type A evaluation, whereas the MCM provides an exact coverage interval under an abnormal probability distribution of the measurand. The MCM is useful in complex settings where the measurand is combined with numerous distributions because it is generated from the uncertainties of input quantities based on the propagation of the distribution. Therefore, the MCM is more practical than the GUM for evaluating the MU of urinary AP and 4HA concentrations using LC–MS/MS.