bluuebunny/crossref_metadata_2025 huggingface dataset:
Sources of negative emotions and tactics of self-emotion regulation among college students during COVID-19 school closure in China
Authors: Fu Hai , Pan Mingfeng , Lai Mingdong
Published: March 2024

Background

This study investigated the level of anxiety and depression in Chinese college students since the COVID-19 pandemic and explored the sources of their negative emotions and students' self-emotion regulation strategies.

Methods

A stratified cluster sampling questionnaire was used to survey college students during the pandemic via the Anxiety Depression, Self-made Negative Emotion Source, and Negative Emotion Regulation Strategy Scales.

Results

The prevalence of anxiety and depression was 23.3 and 20.1%, respectively. These levels were higher in women than in men. Furthermore, senior students reported higher levels than freshmen. Anxiety and depression mainly came from the pressure to grow and the narrowed scope of social activities. Proper relaxation via entertainment and communication with family and friends were popular ways of regulating their negative emotions.

Conclusion

College students should confront their negative emotions and understand their source, use psychological methods to regulate their anxiety and depression or seek professional help, improve their psychological resilience, and adopt positive coping measures.
A cost-effective, machine learning-driven approach for screening arterial functional aging in a large-scale Chinese population
Authors: Miao Rujia , Dong Qian , Liu Xuelian , Chen Yingying , Wang Jiangang , Chen Jianwen
Published: March 2024

Introduction

An easily accessible and cost-free machine learning model based on prior probabilities of vascular aging enables an application to pinpoint high-risk populations before physical checks and optimize healthcare investment.

Methods

A dataset containing questionnaire responses and physical measurement parameters from 77,134 adults was extracted from the electronic records of the Health Management Center at the Third Xiangya Hospital. The least absolute shrinkage and selection operator and recursive feature elimination-Lightweight Gradient Elevator were employed to select features from a pool of potential covariates. The participants were randomly divided into training (70%) and test cohorts (30%). Four machine learning algorithms were applied to build the screening models for elevated arterial stiffness (EAS), and the performance of models was evaluated by calculating the area under the receiver operating characteristic curve (AUC), sensitivity, specificity, and accuracy.

Results

Fourteen easily accessible features were selected to construct the model, including “systolic blood pressure” (SBP), “age,” “waist circumference,” “history of hypertension,” “sex,” “exercise,” “awareness of normal blood pressure,” “eat fruit,” “work intensity,” “drink milk,” “eat bean products,” “smoking,” “alcohol consumption,” and “Irritableness.” The extreme gradient boosting (XGBoost) model outperformed the other three models, achieving AUC values of 0.8722 and 0.8710 in the training and test sets, respectively. The most important five features are SBP, age, waist, history of hypertension, and sex.

Conclusion

The XGBoost model ideally assesses the prior probability of the current EAS in the general population. The integration of the model into primary care facilities has the potential to lower medical expenses and enhance the management of arterial aging.
Changes and interruptions during COVID-19: caregivers of people with brain health challenges—A qualitative analysis
Authors: Kennedy Polly , Rogan Carol , Higgins Dawn , Chen Yao , Grycuk Emilia , Leroi Iracema , Wormald Andrew , Galvin Miriam
Published: March 2024

Background

The social and economic challenges of the COVID-19 pandemic greatly impacted people's physical and mental health. The majority of care for individuals with brain health challenges, including dementia and mental illness, is provided by informal family caregivers. The “Coping with Loneliness, Isolation and COVID-19” (CLIC) Global Caregiver Survey 2020 received responses from over 5,000 caregivers across 50 countries of people living with enduring brain and/or physical health conditions.

Aim

This study examined English-speaking caregivers of people with brain health challenges (dementia and mental health conditions) descriptions of changes and interruptions in their ability to provide care in the context of the COVID-19 pandemic.

Materials and methods

Quantitative and qualitative data were collected as part of the large-scale CLIC Global Caregiver Survey. Data from over 900 English language respondents were analyzed using descriptive statistics and thematic content analysis. A multidisciplinary team of clinicians and health policy practitioners participated in team-based qualitative analyses.

Results

The majority of respondents were from the United States (71% USA), female (83%) and care providers to people living with dementia (81%). Respondents reported concerns about their loved one's physical and mental health, the limited access to other caregiving sources and the limited opportunities to maintain personal wellbeing. Practical, social, psychological and emotional impacts affected their ability to offer care. There was clear evidence that the disruption to health and social care services—institutions, day care and home services impacted the ability to offer care.

Discussion

The pandemic may be seen as a catastrophic “event” that negatively impacted lives and livelihoods. A number of the social determinants of health were negatively impacted for the caregivers surveyed during this prolonged period. Caring for caregivers and supportive health and social care interventions are required to maintain the wellbeing of this informal workforce. This study represents the largest, cross-country survey on the impact of the COVID-19 pandemic on caregivers of people with brain health challenges to date; serving as an important resource for support agencies and to inform policy.
Development of a multidimensional military readiness assessment
Authors: Sheehan Riley C. , Vernon Michael
Published: March 2024

There is a need to be able to accurately evaluate whether an injured service member is able to return to duty. An effective assessment would challenge and measures physical and cognitive performance in a military-relevant context. Current assessments are lacking in one or more of these aspects. The simulation and data capture abilities of virtual reality systems are promising for use as the basis of multidimensional assessments. The team has previously developed a military-specific assessment in the Computer Assisted Rehabilitation Environment (CAREN) called the Readiness Evaluation During simulated Dismounted Operations (REDOp). Due to notable limitations in the original assessment, we have developed the next iteration, REDOp2. The assessment is able to challenge and measure a broader range of physical and cognitive performance domains in a more streamlined fashion. While limited to facilities with a CAREN, REDOp2 has the potential to provide an effective tool for highly trained and experienced wounded service members that require thorough assessment prior to returning to duty to ensure the safety of the team and mission. This methods paper describes the specific limitations in REDOp, how they were addressed in REDOp2, and suggested next steps to prepare the assessment for implementation.
Mind Wandering Can Be a Good Thing
Authors: Dubois Michael , Finn Amy S.
Published: March 2024

Staying focused is important for nearly every human activity, yet we often struggle to do it. When we are unable to focus our thoughts, we say that we are mind wandering. Mind wandering is very common and occurs in every healthy mind. In fact, mind wandering may even reflect the regular way of thinking, unless people make special efforts to prevent it. But is all mind wandering the same? Why does the mind wander, and when? What effect does mind wandering have in our lives? In answering these questions, we will show how mind wandering can even be helpful for things like creativity and learning.
Transient Characteristics of Fluidic Pintle Nozzle in a Solid Rocket Motor
Authors: Yan Dongfeng , Zhao Zehang , Song Anchen , Li Fengming , Ye Lu , Zhao Ganchao , Ma Shan
Published: March 2024

The fluidic pintle nozzle, a new method to control the thrust of a solid rocket motor, has been proposed in recent years by combining the pintle with the aerodynamic throat (fluidic throat). The study of static characteristics has proved that it has a remarkable effect on thrust control. To study the transient characteristics of the fluidic pintle nozzle, 2D transient simulations of a fluidic pintle nozzle propulsion system were conducted, employing dynamic meshing techniques. The Reynolds-averaged Navier–Stokes equations were meticulously solved, implementing a k–ω SST turbulence model. The thrust control principle of the fluid pintle nozzle was studied, and the wave structure was summarized. The transient characteristics of the secondary flow opening, secondary flow closing, pintle moving forward (pressure rise), and pintle moving backward (pressure drop) were obtained, and the effects of the injection angle and injection port position were studied. The response process after injection can be roughly divided into three stages: pressure propagation, pressure oscillation, and equilibrium stability, with time distributions of 0.4%, 5.39%, and 94.21%, respectively. In the process of the pintle moving forward, the rate of combustion chamber pressure increases and thrust decreases gradually because of the arc wall of the nozzle throat upstream, and the process of throats moving backward is just the opposite. Compared with the condition with a maximum throat opening and no secondary flow, the thrust of the condition with a minimum throat opening and a 0.3-flow-ratio secondary flow is increased by 80.95%. Under conditions of constrained flow ratio, the injection angle of the secondary flow ostensibly exerts negligible influence on the dynamic modulation of thrust. Nevertheless, it remains evident that a reduction in throat opening accentuates the impact of reverse injection. Furthermore, the proximity of the injection port to the head of the pintle is directly proportional to the efficacy of thrust control.
Advances in Respiratory Medicine—Aims and Scopes Update
Authors: Kuziemski Krzysztof , Franczuk Monika , Majewski Sebastian , Zielonka Tadeusz M. , Barczyk Adam
Published: March 2024

Advances in Respiratory Medicine, which has been published by MDPI since 2022, serves as a platform for hosting pneumological studies [...]
The Biomechanical Analysis of Tibial Implants Using Meshless Methods: Stress and Bone Tissue Remodeling Analysis
Authors: Pais Ana , Moreira Catarina , Belinha Jorge
Published: March 2024

Total knee arthroplasty (TKA) stands out as one of the most widely employed surgical procedures, establishing itself as the preferred method for addressing advanced osteoarthritis of the knee. However, current knee prostheses require refined design solutions. This research work focuses on a computational analysis of both the mechanical behavior of a knee joint implant and the bone remodeling process in the tibia following implantation. This research study delves into how specific design parameters, particularly the stem geometry, impact the prosthesis’s performance. Utilizing a computed tomography scan of a tibia, various TKA configurations were simulated to conduct analyses employing advanced discretization techniques, such as the finite element method (FEM) and the radial point interpolation method (RPIM). The findings reveal that the introduction of the implant leads to a marginal increase in the stress values within the tibia, accompanied by a reduction in the displacement field values. The insertion of the longest tested implant increased the maximum stress from 5.0705 MPa to 6.1584 MPa, leading to a displacement reduction from 0.016 mm to 0.0142 mm. Finally, by combining the FEM with a bone remodeling algorithm, the bone remodeling process of the tibia due to an implant insertion was simulated.
Harmonized Skies: A Survey on Drone Acceptance across Europe
Authors: Stolz Maria , Papenfuß Anne , Dunkel Franziska , Linhuber Eva
Published: March 2024

This study investigated the public acceptance of drones in six European countries. For this purpose, an online questionnaire was created, which was completed by 2998 participants. The general attitude towards drones, concerns, approval for different use cases, minimum tolerable flight altitude, acceptable flight areas, and the impact of personal and demographic attributes on drone acceptance were analyzed. Overall, attitudes towards drones were quite positive in the entire sample and even improved slightly in a second measurement at the end of the questionnaire. However, the results also show that acceptance strongly depends on the use case. Drones for civil and public applications are more widely accepted than those for private and commercial applications. Moreover, the population still has high concerns about privacy and safety. Knowledge about drones, interest in technologies, and age proved essential to predicting acceptance. Thus, tailored communication strategies, for example, through social media, can enhance public awareness and acceptance.
Global Navigation Satellite Systems Signal Vulnerabilities in Unmanned Aerial Vehicle Operations: Impact of Affordable Software-Defined Radio
Authors: Novák Andrej , Kováčiková Kristína , Kandera Branislav , Sedláčková Alena Novák
Published: March 2024

Spoofing, alongside jamming of the Global Navigation Satellite System signal, remains a significant hazard during general aviation or Unmanned Aerial Vehicle operations. As aircraft utilize various support systems for navigation, such as INS, an insufficient Global Navigation Satellite System signal renders Unmanned Aerial Vehicles nearly uncontrollable, thereby posing increased danger to operations within airspace and to individuals on the ground. This paper primarily focuses on assessing the impact of the budget friendly Software-Defined Radio, HackRF One 1.0, on the safety of Unmanned Aerial Vehicles operations. Considering the widespread use of Software-Defined Radio devices today, with some being reasonably inexpensive, understanding their influence on Unmanned Aerial Vehicles safety is crucial. The generation of artificial interference capable of posing a potential threat in expanding Unmanned Aerial Vehicles airspace is deemed unacceptable.
Educational Approach: Application of SWOT Analysis for Assessing Entrepreneurial Goals in Senior Dental Students
Authors: Antoniadou Maria , Kanellopoulou Antonia
Published: March 2024

The SWOT (strengths, weaknesses, opportunities, and threats) analysis is a framework used to evaluate a company’s competitive position and to develop strategic planning. In the competitive dental sector, it can aid dentists in identifying and analyzing internal strengths and weaknesses, as well as external opportunities and threats. This study focuses on senior dental students of the Department of Dentistry at the National and Kapodistrian University of Athens, Greece, aiming to scrutinize their use of SWOT analysis and assess its application as a tool for evaluating entrepreneurial goals and making career decisions in dental entrepreneurship. The research sample comprises 116 senior dental students (N1) in the final undergraduate year of their dental education, with data collection accomplished through the administration of an e-questionnaire during the obligatory course of “Organization and management of dental practices” in December 2023. The data extracted from the SWOT analysis encompass internal and external factors, gender distinctions, and outcomes derived from Stepwise Binary Logistic Regression concerning predictor markers. The results from the SWOT analysis of 114 valid questionnaires (N2), revealed that participants identified communication skills (50%) and organization skills (49.10%) as their primary strengths, followed by favorable personal traits contributing to goal success (36%). Weaknesses predominantly centered around emotional and personal traits like anxiety (41.20%) and other characteristics, alongside practical challenges such as lack of initial capital (24.60%). Main opportunities included collaboration with experienced dentists (33.30%) and access to training programs (27.20%), while economic instability in Greece (77.20%) and the saturated dentist profession (26.30%) were perceived as significant threats. Gender differences were notable, with female dentists more likely to report organization skills as a strength and anxiety as a weakness. Values such as industriousness, persistence, and ethics were commonly shared, with actions focusing on training programs (57.9%) and gaining experience with experienced dentists (29.8%). Cluster analysis identified two subgroups, with one emphasizing utilizing all available options (n = 49) and the other prioritizing on gaining professional skills and experience (n = 65). Logistic regression indicated that participants valuing industriousness were less likely to explore all available options, while those recognizing personal traits were more likely to do so. The study’s outcomes highlight key predictor factors linked to a proactive orientation in career decision-making among senior dental students. These insights offer valuable implications for educational institutions and career counselors.
A Method of Diagnosing Analog Circuit Soft Faults Using Boruta Features and LightGBM
Authors: Chen Hongyang , Hu Chunyan , Han Bo , Miao Keqiang
Published: March 2024

Modern electronic power systems rely heavily on analog circuits. The accurate detection of analog circuit faults, especially soft faults, is of great significance for the maintenance and inspection of electronic systems. This paper proposes the application of the Boruta feature selection method to the field of the soft fault diagnosis of analog circuits to screen out low-dimensional and efficient feature components from the high-dimensional time-domain statistical features and frequency-domain features of circuit responses. Then, the feature components are used as the input to train the LightGBM classification model, and the Bayesian optimization method is introduced to optimize the model’s hyperparameters. Finally, the trained fault diagnosis model is verified in two typical experimental circuits, and satisfactory accuracy is obtained.
Review of Research on the Impact of Changes Resulting from the Hard Coal Mining Sector in Poland on the GDP Value
Authors: Pepłowska Monika , Olczak Piotr
Published: March 2024

Energy transition is one of the main objectives of the European Union. Significant changes will mainly affect countries in which significant modifications will have to be made to their energy sources. The process will involve high investment in infrastructure and additional costs of the transformation, such as reduced production (which may affect the GDP value) in the economic sectors involved in the process. The aim of this article is to provide the energy transition community, namely the national economy in general and those involved in planning for structural change in particular, with the key lessons and challenges in researching the impact of production changes in the mining sector. This article also shows the relevance of the mining sector in the economy. Within this area, particular attention is given to the following issues: the impact of economic sectors on the country’s GDP (gross domestic product); the identification of key sectors of the economy using the input–output method; the contribution of coal mining and the mining industry to Poland’s GDP; an analysis of changes in the structure of Poland’s economy using the input–output method; and the use of the input–output method in the context of changing/reducing the supply of economic sectors.
Review of the Integration of Hybrid Electric Turbochargers for Mass-Produced Road Vehicles
Authors: Suciu Cosmin Constantin , Igret Sorin Vlad , Vetres Ion , Ionel Ioana
Published: March 2024

This study presents the findings of a comprehensive SWOT analysis on the integration of hybrid electric turbochargers (HETs) in mass-produced road vehicles. Through a synthesis of multiple research findings, this study compared the performance of HETs on thermal engines versus traditional turbochargers and HETs on thermal engines versus HETs on hybrid engines. The analysis highlights key strengths, weaknesses, opportunities, and threats associated with the adoption of HET technology in the automotive industry. The results of the SWOT analysis provide valuable insights for both manufacturers and consumers regarding the feasibility and benefits of adopting HET technology in modern vehicles. By elucidating the fundamental mechanics of turbochargers and demonstrating the potential of hybrid electric turbocharging, this study contributes to a deeper understanding of the role of HETs in shaping the future of automotive engineering. In conclusion, this study underscores the potential of HETs to substantially mitigate the environmental impact of the transportation sector by reducing emissions and conserving energy. The novelty of this study is reflected in its comprehensive synthesis of multiple research findings, offering insights into the feasibility and benefits of adopting HET technology in modern vehicles, thereby contributing to a deeper understanding of the role of HETs in shaping the future of automotive engineering and highlighting their continued significance, as evidenced by the systematic SWOT analysis presented. Their ability to optimize fuel efficiency and power output, coupled with the feasibility of downsized engines, positions HETs as an attractive option for sustainable mobility solutions. Further research is warranted to comprehensively understand the environmental and economic implications of widespread HET adoption.
Adaptation of Microinverter Reference Design for Integration with Battery Energy Storage Systems in Microgrids
Authors: Jolevski Danijel , Jakus Damir , Vasilj Josip , Novaković Joško
Published: March 2024

The paper presents an adaptation of the microinverter platform from Texas Instruments to incorporate a battery energy storage system (BESS) alongside the development of the BESS system itself. Initially designed for unidirectional power flow between PV panels and an electric grid, the platform required modifications to accommodate bidirectional energy transfer for BESS integration. These modifications encompass software adjustments and hardware enhancements, which are all detailed within the paper. The electrical configuration includes selecting and deploying components such as DCDC power converters, microcontrollers, measured signals, and actuating signals to facilitate battery connection to the platform’s DC bus. Furthermore, a supervisory control and data acquisition (SCADA) system is devised for supervisory control and monitoring, with its implementation outlined. Control software tailored for the chosen microcontroller of the DCDC converters is described in terms of structure and functionality. A hardware-in-the-loop (HIL) methodology is employed to validate the proposed modifications and microgrid configuration. Utilizing the real-time simulator OPAL-RT, the paper presents experimental results and their analysis within the considered microgrid environment.
Techniques for Theoretical Prediction of Immunogenic Peptides
Authors: Friedman Robert
Published: March 2024

Small peptides are an important component of the vertebrate immune system. They are important molecules for distinguishing proteins that originate in the host from proteins derived from a pathogenic organism, such as a virus or bacterium. Consequently, these peptides are central for the vertebrate host response to intracellular and extracellular pathogens. Computational models for prediction of these peptides have been based on a narrow sample of data with an emphasis on the position and chemical properties of the amino acids. In past literature, this approach has resulted in higher predictability than models that rely on the geometrical arrangement of atoms. However, protein structure data from experiment and theory are a source for building models at scale, and, therefore, knowledge on the role of small peptides and their immunogenicity in the vertebrate immune system. The following sections introduce procedures that contribute to theoretical prediction of peptides and their role in immunogenicity. Lastly, deep learning is discussed as it applies to immunogenetics and the acceleration of knowledge by a capability for modeling the complexity of natural phenomena.
Numerical Study of Rarefied Gas Flow in Diverging Channels of Finite Length at Various Pressure Ratios
Authors: Tantos Christos , Litovoli Foteini , Teichmann Tim , Sarris Ioannis , Day Christian
Published: March 2024

In the present work, the gas flows through diverging channels driven by small, moderate, and large pressure drops are studied, considering a wide range of the gas rarefaction from free molecular limit through transition flow regime up to early slip regime. The analysis is performed using the Shakhov kinetic model, and applying the deterministic DVM method. The complete 4D flow problem is considered by including the upstream and downstream reservoirs. A strong effect of the channel geometry on the flow pattern is shown, with the distributions of the macroscopic quantities differing qualitatively and quantitatively from the straight channel flows. The mass flow rate data set from the complete solution is compared with the corresponding set obtained from the approximate kinetic methodology, which is based on the fully developed mass flow rate data available in the literature. In addition, the use of the end-effect approach significantly improves the applicability range of the approximate kinetic methodology. The influence of the wall temperature on the flow characteristics is also studied and is found to be strong in less-rarefied cases, with the mass flow rate in these cases being a decreasing function of the temperature wall. Overall, the present analysis is expected to be useful in the development and optimization of technological devices in vacuum and aerospace technologies.
Using Online Videos to Improve Attitudes toward Shared Autonomous Vehicles: Age and Video Type Differences
Authors: Baringer Kathryn , Lopez Jeremy , Souders Dustin J.
Published: March 2024

Future adoption of shared automated vehicles (SAVs) should lead to several societal benefits, but both automated vehicles (AVs) and ridesharing must overcome their barriers to acceptance. Previous research has investigated age differences in ridesharing usage and factors influencing the acceptability and acceptance of AVs. Further complicating our understanding of SAV acceptance, much of the public lack accurate knowledge and/or actual experience regarding AVs. In this study, we employed a 3 (age group) × 4 (video condition) longitudinal mixed experimental design to investigate age differences in anticipated SAV acceptance after viewing different types of introductory videos related to AVs (educational, experiential, or both) or currently available ridesharing provided by transportation network companies (control). Younger, middle-aged, and older adults were randomly assigned to watch (1) an educational video about SAV technologies and potential benefits, (2) an experiential video showing an SAV navigating traffic, (3) both the experiential and educational videos or (4) a control video explaining how current ridesharing services work. Attitudes toward SAVs (intent to use, trust/reliability, perceived usefulness, perceived ease of use, safety, desire for control, cost, authority, media, and social influence) were measured before and after viewing the video(s). Significant differences in how SAV attitudes changed were found between the educational and experiential video conditions relative to the control video and between different age groups. Findings suggest that educational and/or experiential videos delivered in an online format can have modest but significant improvements to their viewers’ attitudes toward SAVs—particularly those of older adults.
Exploring the Potentials of Artificial Intelligence Image Generators for Educating the History of Architecture
Authors: Fareed Mohamed W. , Bou Nassif Ali , Nofal Eslam
Published: March 2024

The rapid integration of Artificial Intelligence (AI) tools, specifically text-to-image generators, across various domains has had a profound impact on numerous fields. Despite this, the potential applications of AI image generators in architectural education, particularly in teaching the history of architecture, remain underexplored. This research aims to uncover the possibilities of utilizing AI image generators, with a specific focus on the capabilities of Leonardo AI, to enhance communication and engagement. This study employed an experimental methodology to investigate how the integration of AI image generators in education on the subject of “History of Architecture” promises to elevate the learning experience, offering new perspectives, visualizations, and interactive tools. Two workshops were conducted with university students to explore AI image generators’ potential applications in architectural history education. The first workshop utilized an iterative approach, while the second aimed to assess students’ analytical skills. The ultimate objective was to determine the capabilities of this tool and stimulate discussions regarding its potential future implementations. Following the workshops, online questionnaires were administered to students, and interviews were conducted with educators. The findings of this research underscore the need for validating AI-generated images, establishing guidelines to prevent misuse, and designing tailored AI tools for History of Architecture courses, thereby paving the way for further advancements in architectural history education.
Investigating the Degradation of Mycenaean Glass Artifacts Using Scientific Methods
Authors: Kaparou Maria , Oikonomou Artemios , Karydas Andreas Germanos
Published: March 2024

Mycenaean vitreous artifacts, such as beads and relief plaques, are highly susceptible to degradation, which can significantly alter their visual characteristics and pose challenges to their taxonomy. The visual manifestation of corrosion on vitreous artifacts, especially glass and faience, has often led to their misclassification, which, in turn, has a significant impact on their interpretation by researchers, often resulting in misleading notions. The present paper constitutes part of an overall study, implemented within the framework of the project, Myc-MVP: Mycenaean Vitreous Production, A Novel Interdisciplinary Approach Towards Resolving Critical Taxonomy Issues, which has employed a combination of established, state-of-the-art scientific methods to analyze and identify the specific compositional changes occurring at different spatial dimensions within surface layers, with the overarching aim of contributing to our understanding of the degradation mechanisms of vitreous artifacts and the relevant implications for the archaeological record. Importantly, these findings will yield useful data in devising strategies for the proper classification, management, and preservation of vitreous artifacts in the future. The present study focuses on investigating the relationship between the compositional changes in a subset of 12 (of the overall 126 objects entailed in the project) corroded vitreous artifacts from Mycenaean contexts in the Aegean and the way these are manifested visually, with the application of X-ray fluorescence and LED microscopy. We aim to decipher the nature of corroded objects with the aid of focused analysis. This study delves into degradation processes in glass artifacts, highlighting preservation variations and environmental influences like burial. Coloration, attributed to copper and cobalt oxide, shows some correlation with preservation quality. These chromophore agents potentially induce thermal stresses and corrosion. The complex interplay between chemical composition, environmental conditions, and preservation status underscores the need for comprehensive research. Analyzing the full artifact set using complementary techniques promises deeper insights for secure material classification and cultural heritage preservation.
Gene Expression and Prognostic Value of NADPH Oxidase Enzymes in Breast Cancer
Authors: de Vasconcelos e Souza Andressa , de Faria Caroline Coelho , Pereira Leonardo Matta , Ferreira Andrea Claudia Freitas , Torres Pedro Henrique Monteiro , Fortunato Rodrigo Soares
Published: March 2024

NADPH oxidase enzymes (NOX) are involved in all stages of carcinogenesis, but their expression levels and prognostic value in breast cancer (BC) remain unclear. Thus, we aimed to assess the expression and prognostic value of NOX enzymes in BC samples using online databases. For this, mRNA expression from 290 normal breast tissue samples and 1904 BC samples obtained from studies on cBioPortal, Kaplan–Meier Plotter, and The Human Protein Atlas were analyzed. We found higher levels of NOX2, NOX4, and Dual oxidase 1 (DUOX1) in normal breast tissue. NOX1, NOX2, and NOX4 exhibited higher expression in BC, except for the basal subtype, where NOX4 expression was lower. DUOX1 mRNA levels were lower in all BC subtypes. NOX2, NOX4, and NOX5 mRNA levels increased with tumor progression stages, while NOX1 and DUOX1 expression decreased in more advanced stages. Moreover, patients with low expression of NOX1, NOX4, and DUOX1 had lower survival rates than those with high expression of these enzymes. In conclusion, our data suggest an overexpression of NOX enzymes in breast cancer, with certain isoforms showing a positive correlation with tumor progression.
Plasma Levels of Pentraxin 3: A Potential Prognostic Biomarker in Urinary Bladder Cancer Patients
Authors: Vikerfors Anders , Davidsson Sabina , Carlsson Jessica , Jerlström Tomas
Published: March 2024

Urinary bladder cancer (BC) represents a major health issue, and identifying novel biomarkers for early disease detection and outcome prediction is paramount. It has already been established that the immune system plays a role in tumour initiation and progression in which the inflammatory marker pentraxin 3 (PTX3) might be involved, presenting a variety of functions in different cancers. The aim of this study was to investigate whether plasma levels of PTX3 could be used as a biomarker for patients with BC. Plasma levels of PTX3 were determined in 118 BC patients and 50 controls by ELISA. Patients with BC had significantly higher PTX3 levels compared to controls. The value as a diagnostic biomarker is probably limited, however, since no significant difference in PTX3 levels was seen between patients with non-muscle-invasive BC and controls; they were seen only between patients with muscle-invasive disease and controls. However, the potential value of PTX3 as a prognostic biomarker was indicated by significantly higher PTX3 levels in patients who developed metastatic disease during follow-up compared to patients who did not develop metastatic disease. The conclusions from this study are that plasma levels of PTX3 have limited value as a diagnostic biomarker, although they have potential as a prognostic biomarker for patients with BC.
Rapid Nucleic Acid Detection of Listeria monocytogenes Based on RAA-CRISPR Cas12a System
Authors: Yang Yujuan , Kong Xiangxiang , Yang Jielin , Xue Junxin , Niu Bing , Chen Qin
Published: March 2024

Listeria monocytogenes (L. monocytogenes) is a food-borne pathogenic bacteria that frequently contaminates animal-derived food and low-temperature preserved food. Listeriosis caused by its infection has a high mortality rate and poses a serious threat to human health. Therefore, it is crucial to establish a sensitive, rapid and easy-to-operate technique. In this study, a Recombinase Aided Amplification (RAA) assisted CRISPR/Cas12a (RAA-CRISPR/Cas12a) fluorescence platform was established for highly sensitive nucleic acid detection of L. monocytogenes. The established RAA-CRISPR/Cas12a showed high sensitivity and high specificity, with the sensitivity of 350 CFU/mL and 5.4 × 10−3 ng/μL for pure bacterial solution and genomic DNA, and good specificity for 5 strains of Listeria spp. and 14 strains of other common pathogenic bacteria. L. monocytogenes could be detected at an initial concentration of 2.3 CFU/25g within 2 h of enriching the beef in the food matrix, and this method could be applied to food samples that were easily contaminated with L. monocytogenes The results of RAA-CRISPR/Cas12a could be observed in 5 min, while the amplification was completed in 20–30 min. The speed and sensitivity of RAA-CRISPR/Cas12a were significantly higher than that of the national standard method. In conclusion, the RAA-CRISPR/Cas12a system established in this study has new application potential in the diagnosis of food-borne pathogens.
Anaerobutyricum soehngenii Reduces Hepatic Lipogenic Pathways and Increases Intestinal Gluconeogenic Gene Expression in Metabolic-Dysfunction-Associated Steatotic Liver Disease (MASLD) Mice
Authors: Mak Anne Linde , Augustijn Quinten J. J. , Heymann Clément J. F. , Havik Stefan , Verdoes Xanthe , Rios-Morales Melany , Bosmans Laura A. , Verheij Joanne , Meijnikman Abraham S. , de Jonge Patrick A. , Herrema Hilde , de Vos Willem M. , Nieuwdorp Max , Grefhorst Aldo , Holleboom Adriaan G.
Published: March 2024

Metabolic-dysfunction-associated steatotic liver disease (MASLD) is a growing health problem for which no therapy exists to date. The modulation of the gut microbiome may have treatment potential for MASLD. Here, we investigated Anaerobutyricum soehngenii, a butyrate-producing anaerobic bacterium with beneficial effects in metabolic syndrome, in a diet-induced MASLD mouse model. Male C57BL/6J mice received a Western-type high-fat diet and water with 15% fructose (WDF) to induce MASLD and were gavaged with A. soehngenii (108 or 109 colony-forming units (CFU) 3 times per week) or a placebo for 6 weeks. The A. soehngenii gavage increased the cecal butyrate concentrations. Although there was no effect on histological MASLD scores, A. soehngenii improved the glycemic response to insulin. In the liver, the WDF-associated altered expression of three genes relevant to the MASLD pathophysiology was reversed upon treatment with A. soehngenii: Lipin-1 (Lpin1), insulin-like growth factor binding protein 1 (Igfbp1) and Interleukin 1 Receptor Type 1 (Il1r1). A. soehngenii administration also increased the intestinal expression of gluconeogenesis and fructolysis genes. Although these effects did not translate into significant histological improvements in MASLD, these results provide a basis for combined gut microbial approaches to induce histological improvements in MASLD.
Investigating Vα7.2+/CD161− T Cell and MAIT Cell Profiles Using Flow Cytometry in Healthy Subjects and Subjects with Atopic Dermatitis
Authors: Singh Parvind , Gaspar Krisztian , Szegedi Andrea , Sajtos Laszlo , Barath Sandor , Hevessy Zsuzsanna
Published: March 2024

This study investigates the roles of mucosal-associated invariant T (MAIT) cells and Vα7.2+/CD161− T cells in skin diseases, focusing on atopic dermatitis. MAIT cells, crucial for bridging innate and adaptive immunity, were analyzed alongside Vα7.2+/CD161− T cells in peripheral blood samples from 14 atopic dermatitis patients and 10 healthy controls. Flow cytometry and machine learning algorithms were employed for a comprehensive analysis. The results indicate a significant decrease in MAIT cells and CD69 subsets in atopic dermatitis, coupled with elevated CD38 and polyfunctional MAIT cells producing TNFα and Granzyme B (TNFα+/GzB+). Vα7.2+/CD161− T cells in atopic dermatitis exhibited a decrease in CD8 and IFNγ-producing subsets but an increase in CD38 activated and IL-22-producing subsets. These results highlight the distinctive features of MAIT cells and Vα7.2+/CD161− T cells and their different roles in the pathogenesis of atopic dermatitis and provide insights into their potential roles in immune-mediated skin diseases.
Differential Expression of CKLF-like MARVEL Transmembrane Domain-Containing Protein 6 and Programmed Cell Death Ligand 1 as Prognostic Biomarkers in Upper Tract Urothelial Carcinoma
Authors: Kdimati Said , Christoph Clemens , Glass Änne , Engel Nadja , Dräger Desiree-Louise , Maletzki Claudia , Becker Anne-Sophie , Zimpfer Annette
Published: March 2024

Upper tract urothelial carcinoma (UTUC) accounts for 5–10% of all UCs. Immune checkpoint inhibitors (ICIs) have been established for UCs. The prognostic and predictive potential of programmed cell death ligand 1 (PD-L1) expression to stratify patients benefiting from ICIs is not fully understood, and additional markers influencing the impact of PD-L1-mediated ICI response are needed. Previously, the chemokine-like MARVEL transmembrane domain-containing protein 6 (CMTM6) was identified as a positive regulator of PD-L1. Our aim was to investigate the expression profiles and impact of PD-L1 and CMTM6 protein status on the prognostic parameters and survival of UTUC patients. In this retrospective study, the combined positive score (CPS), tumor proportion score (TPS), and immune cell score (ICS) for PD-L1 and CMTM6 were determined. High PD-L1 CPS, ICS, and TPS were found in 77.4%, 58.3%, and 45.2% of cases, and high CMTM6 CPS, ICS, and TPS were seen in 52.5%, 51.5%, and 55.5% of cases, respectively. The scores of both markers had a significant positive correlation. High PD-L1 and CMTM6 expression was coupled with higher pT status, WHO grade, necrosis, and metastasis (p < 0.05, respectively). In the univariate survival analysis, patients with a PD-L1 ICS high and higher degree of intratumoral inflammation showed significantly longer overall survival. Compared to other studies on UC, our study shows a substantially higher rate of PD-L1-positive tumors. CMTM6 was associated with more aggressive tumors.
CgNis1’s Impact on Virulence and Stress Response in Colletotrichum gloeosporioides
Authors: Guo Sheng , Sun Qianlong , Liu Sizhen , Wu Fei , Li Chenggang , Zhang Xin , OuYang Chao , Chen Yue , Tan Xinqiu
Published: March 2024

Pepper anthracnose caused by Colletotrichum gloeosporioides infection is an important fungal disease and represents a serious threat to pepper yield and quality. At present, the pathogenic molecular mechanism of C. gloeosporioides is not very clear. In our study, we characterized the function of C. gloeosporioides CgNis1, a homolog of Magnaporthe oryzae MoNis1. We found that the ∆Cgnis1 mutant reduced the growth rate and was defective in conidiation. Although the rate of appressorium formation was unaffected, the germ tube was found to be abnormal. CgNis1 was shown to be involved in the H2O2 stress response and maintaining cell membrane permeability. The pathogenicity assays performed in this study indicated that the deletion of CgNIS1 is associated with virulence. Our results indicate that CgNis1 is necessary for the growth, development, and pathogenicity of the fungus. This work provides an in-depth analysis of the Nis1 protein, helps to enhance studies on pathogen-related molecular mechanisms, and provides a theoretical basis for the prevention and control of C. gloeosporioides in peppers.
Fine-Tuning of DADA2 Parameters for Multiregional Metabarcoding Analysis of 16S rRNA Genes from Activated Sludge and Comparison of Taxonomy Classification Power and Taxonomy Databases
Authors: Babis Wiktor , Jastrzebski Jan P. , Ciesielski Slawomir
Published: March 2024

Taxonomic classification using metabarcoding is a commonly used method in microbiological studies of environmental samples and during monitoring of biotechnological processes. However, it is difficult to compare results from different laboratories, due to the variety of bioinformatics tools that have been developed and used for data analysis. This problem is compounded by different choices regarding which variable region of the 16S rRNA gene and which database is used for taxonomic identification. Therefore, this study employed the DADA2 algorithm to optimize the preprocessing of raw data obtained from the sequencing of activated sludge samples, using simultaneous analysis of three frequently used regions of 16S rRNA (V1–V3, V3–V4, V4–V5). Additionally, the study evaluated which variable region and which of the frequently used microbial databases for taxonomic classification (Greengenes2, Silva, RefSeq) more accurately classify OTUs into taxa. Adjusting the values of selected parameters of the DADA2 algorithm, we obtained the highest possible numbers of OTUs for each region. Regarding biodiversity within regions, the V3–V4 region had the highest Simpson and Shannon indexes, and the Chao1 index was similar to that of the V1–V3 region. Beta-biodiversity analysis revealed statistically significant differences between regions. When comparing databases for each of the regions studied, the highest numbers of taxonomic groups were obtained using the SILVA database. These results suggest that standardization of metabarcoding of short amplicons may be possible.
Special Issue “Aquaporins in Brain Disease”
Authors: Echevarría Miriam , García-Miranda Pablo
Published: March 2024

Water is an abundant and important component of the human brain, the homeostasis of which is rigorously controlled [...]
Mlp4green: A Binary Classification Approach Specifically for Green Odor
Authors: Yang Jiuliang , Qian Zhiming , He Yi , Liu Minghao , Li Wannan , Han Weiwei
Published: March 2024

Fresh green leaves give off a smell known as “green odor.” It has antibacterial qualities and can be used to attract or repel insects. However, a common method for evaluating green odor molecules has never existed. Machine learning techniques are widely used in research to forecast molecular attributes for binary classification. In this work, the green odor molecules were first trained and learned using machine learning methods, and then clustering analysis and molecular docking were performed to further explore their molecular characteristics and mechanisms of action. For comparison, four algorithmic models were employed, MLP performed the best in all metrics, including Accuracy, Precision, Average Precision, Matthews coefficient, and Area under curve. We determined by difference analysis that, in comparison to non-green odor molecules, green odor molecules have a lower molecular mass and fewer electrons. Based on the MLP algorithm, we constructed a binary classification prediction website for green odors. The first application of deep learning techniques to the study of green odor molecules can be seen as a signal of a new era in which green odor research has advanced into intelligence and standardization.
Human–Fungal Pathogen Interactions from the Perspective of Immunoproteomics Analyses
Authors: Wangsanut Tanaporn , Pongpom Monsicha
Published: March 2024

Antibody immunity is now known to play a critical role in combating mycotic infections. The identification of molecules that can elicit an antibody response against fungal pathogens is the first step in developing antibody-based therapeutic strategies. Antigenic proteins are molecules recognized by the immune system that can stimulate antibody production and, therefore, can be a direct target for studying human–fungal pathogen interactions. Advances in recent immunoproteomic approaches have substantially aided in determining the key antigenic proteins on a large scale. In this review, we present a collection of antigenic proteins identified in yeast, dimorphic, and filamentous fungal pathogens to date. The general features of antigenic proteins are summarized and reveal that the proteins could commonly function in antistress responses, protein synthesis, and metabolism. The antigenic proteins listed here could serve as starting materials for developing species-specific or broad-spectrum diagnostic tests, therapeutic antibodies, and even vaccines against fungal infections.