bluuebunny/crossref_metadata_2025 huggingface dataset:
A Case of Dedifferentiated Liposarcoma That Contributes to Accompanying Vessels of Various Size
Authors: Yamada Yosuke , Mizoguchi Kai , Shiba Eisuke , Mishima Honami , Otsuki Shinya , Hoki Masahito , Hirata Masahiro , Sakamoto Akio , Matsuda Shuichi , Marx Alexander , Hisaoka Masanori , Haga Hironori
Published: August 2024

Dedifferentiated liposarcoma (DDLPS) is a non-lipogenic sarcoma, generally arising from well-differentiated liposarcoma (WDLPS), although it can develop de novo. DDLPS tumors rarely trans-differentiate into non-adipose mesenchymal tissues; however, the latter lack notable variety and mostly show striated muscle or osteogenic/chondrogenic differentiation. Here, we report a case of DDLPS that contained numerous atypical vessels. A man in his sixties presented with a large tumor in his right thigh, and the tumor was surgically resected. Microscopically, most of the tumor was WDLPS, but a minor portion showed DDLPS, consisting of high-grade spindle cells. Remarkably, the DDLPS contained vessels of various sizes with atypical cytoarchitecture, including vessels with seemingly muscular layers. Immunohistochemically, the atypical cells within the vascular wall expressed aSMA, consistent with smooth muscle cells or pericytes, whereas surrounding high-grade spindle cells only focally expressed it, and these aSMA-positive cells within the vessels exhibited MDM2 amplification by immuno-fluorescence in situ hybridization. Our results demonstrate that DDLPS can trans-differentiate into smooth muscle cells of various-sized accompanying vessels, which may support their survival and proliferation.
Treating Aortic Valve Stenosis for Vitality Improvement: The TAVI Study
Authors: Tartaglione Donato , Prozzo Dario , Bianchi Renatomaria , Ciccarelli Giovanni , Cappelli Bigazzi Maurizio , Natale Francesco , Golino Paolo , Cimmino Giovanni
Published: August 2024

Background: Degenerative aortic valve stenosis (AS) is the most common valvular heart disease among the elderly. Once cardiac symptoms occur, current guidelines recommend aortic valve replacement. Progressive degeneration/calcification reduces leaflet mobility with gradual cardiac output (CO) impairment. Low CO might induce abnormal brain-aging with cognitive impairment and increased risk of dementia, such as Alzheimer’s disease or vascular dementia. On the contrary, cognitive improvement has been reported in patients in whom CO was restored. Transcatheter aortic valve implantation (TAVI) has proven to be a safe alternative to conventional surgery, with a similar mid-term survival and stroke risk even in low-risk patients. TAVI is associated with an immediate CO improvement, also effecting the cerebrovascular system, leading to an increased cerebral blood flow. The correlation between TAVI and cognitive improvement is still debated. The present study aims at evaluating this relationship in a cohort of AS patients where cognitive assessment before and after TAVI was available. Methods: a total of 47 patients were retrospectively selected. A transcranial Doppler ultrasound (TCD) before and after TAVI, a quality of life (QoL) score, as well as a mini-mental state examination (MMSE) at baseline and up to 36 months, were available. Results: TAVI was associated with immediate increase in mean cerebral flow at TCD. MMSE slowly increase at 36-months follow-up with improved QoL mainly for symptoms, emotions and social interactions. Conclusions: this proof-of-concept study indicates that TAVI might induce cognitive improvement in the long-term as a result of multiple factors, such as cerebral flow restoration and a better QoL.
Exploring the Exposome Spectrum: Unveiling Endogenous and Exogenous Factors in Non-Communicable Chronic Diseases
Authors: Di Renzo Laura , Gualtieri Paola , Frank Giulia , Cianci Rossella , Caldarelli Mario , Leggeri Giulia , Raffaelli Glauco , Pizzocaro Erica , Cirillo Michela , De Lorenzo Antonino
Published: August 2024

The exposome encompasses all endogenous and exogenous exposure individuals encounter throughout their lives, including biological, chemical, physical, psychological, relational, and socioeconomic factors. It examines the duration and intensity of these types of exposure and their complex interactions over time. This interdisciplinary approach involves various scientific disciplines, particularly toxicology, to understand the long-term effects of toxic exposure on health. Factors like air pollution, racial background, and socioeconomic status significantly contribute to diseases such as metabolic, cardiovascular, neurodegenerative diseases, infertility, and cancer. Advanced analytical methods measure contaminants in biofluids, food, air, water, and soil, but often overlook the cumulative risk of multiple chemicals. An exposome analysis necessitates sophisticated tools and methodologies to understand health interactions and integrate findings into precision medicine for better disease diagnosis and treatment. Chronic exposure to environmental and biological stimuli can lead to persistent low-grade inflammation, which is a key factor in chronic non-communicable diseases (NCDs), such as obesity, cardiometabolic disorders, cancer, respiratory diseases, autoimmune conditions, and depression. These NCDs are influenced by smoking, unhealthy diets, physical inactivity, and alcohol abuse, all shaped by genetic, environmental, and social factors. Dietary patterns, especially ultra-processed foods, can exacerbate inflammation and alter gut microbiota. This study investigates the exposome’s role in the prevention, development, and progression of NCDs, focusing on endogenous and exogenous factors.
Orbit Rendezvous Maneuvers in Cislunar Space via Nonlinear Hybrid Predictive Control
Authors: Sanna Dario , Madonna David Paolo , Pontani Mauro , Gasbarri Paolo
Published: August 2024

The NASA’s Artemis project intends to bring humans back to the Moon in the next decade. A key element of the project will be the Lunar Gateway, a space station placed in a peculiar, near rectilinear Halo orbit in the vicinity of a collinear libration point in the Earth–Moon system. This study focuses on the high-fidelity description of the relative orbit dynamics of a chaser spacecraft with respect to the Gateway, as well as on the design of a proper orbit control strategy for rendezvous maneuvers. A novel formulation of the Battin–Giorgi approach is introduced, in which the reference orbit is that traveled by the Gateway, i.e., it is a highly non-Keplerian, perturbed orbit. The modified Battin–Giorgi approach allows for the description of a relative orbit motion with no restrictive assumption, while including all the relevant orbit perturbations on both the chaser and the Gateway. Moreover, nonlinear hybrid predictive control is introduced as a feedback guidance strategy. This new technique is shown to outperform the classical, well-established feedback linearization in terms of success rate and accuracy on the final conditions. Moreover, a Monte Carlo analysis confirms that hybrid predictive control is also effective in the presence of the temporary unavailability of propulsion or thrust misalignment.
War-Related Stress among Israeli College Students Following 7 October 2023 Terror Attack in Israel
Authors: Dopelt Keren , Houminer-Klepar Nourit
Published: August 2024

Background: Warfare represents a significant source of stress in contemporary times, with enduring implications beyond the immediate casualties, fostering a pervasive atmosphere of danger and anxiety within affected populations. The Israel–Hamas war, marked by ongoing armed incursions and missile attacks, stands as a recent example of such turmoil, inflicting widespread trauma and disruption. Methods: This study, conducted among students at the Ashkelon Academic College in southern Israel, aimed to investigate the stress levels and associated factors amidst the ongoing conflict. Utilizing a cross-sectional survey design, data were collected from 625 participants between January and February 2024, approximately four months after the commencement of the initial attack. The survey encompassed demographic information, perceived stress levels, sleep quality, and social media usage. Results: The findings revealed moderate to high stress levels among participants, with significant differences observed based on gender, parental status, and residency in conflict zones. Moreover, poorer sleep quality was reported among students residing in conflict-affected areas. Regression analysis identified several predictors of elevated stress, including gender, parental status, sleep quality, residency in conflict zones, and social media usage. Conclusions: These findings underscore the profound impact of ongoing conflict on college students’ mental well-being, highlighting the need for tailored interventions and support services within higher education institutions. The limitations include the study’s focus on a specific college population and the timing of the data collection relative to the onset of the war. Nonetheless, this research contributes valuable insights concerning the stress dynamics within the unique context faced by Israeli students amidst ongoing warfare.
Mother–Child Attachment Relationship in Pregnancy, Postpartum, and Early Childhood: Current Status and New Research Perspectives
Authors: La Rosa Valentina Lucia , Commodari Elena
Published: August 2024

The mother–child attachment relationship is a cornerstone of human development, with profound implications for the well-being of both the mother and child [...]
Enhancing Autonomous Vehicle Perception in Adverse Weather: A Multi Objectives Model for Integrated Weather Classification and Object Detection
Authors: Aloufi Nasser , Alnori Abdulaziz , Basuhail Abdullah
Published: August 2024

Robust object detection and weather classification are essential for the safe operation of autonomous vehicles (AVs) in adverse weather conditions. While existing research often treats these tasks separately, this paper proposes a novel multi objectives model that treats weather classification and object detection as a single problem using only the AV camera sensing system. Our model offers enhanced efficiency and potential performance gains by integrating image quality assessment, Super-Resolution Generative Adversarial Network (SRGAN), and a modified version of You Only Look Once (YOLO) version 5. Additionally, by leveraging the challenging Detection in Adverse Weather Nature (DAWN) dataset, which includes four types of severe weather conditions, including the often-overlooked sandy weather, we have conducted several augmentation techniques, resulting in a significant expansion of the dataset from 1027 images to 2046 images. Furthermore, we optimize the YOLO architecture for robust detection of six object classes (car, cyclist, pedestrian, motorcycle, bus, truck) across adverse weather scenarios. Comprehensive experiments demonstrate the effectiveness of our approach, achieving a mean average precision (mAP) of 74.6%, underscoring the potential of this multi objectives model to significantly advance the perception capabilities of autonomous vehicles’ cameras in challenging environments.
MmWave Tx-Rx Self-Interference Suppression through a High Impedance Surface Stacked EBG
Authors: Oladeinde Adewale K. , Aryafar Ehsan , Pejcinovic Branimir
Published: August 2024

This paper proposes a full-duplex (FD) antenna design with passive self-interference (SI) suppression for the 28 GHz mmWave band. The reduction in SI is achieved through the design of a novel configuration of stacked Electromagnetic Band Gap structures (EBGs), which create a high impedance path to travelling electromagnetic waves between the transmit and receive antenna elements. The EBG is composed of stacked patches on layers 1 and 2 of a four-layer stack-up configuration. We present the design, optimization, and prototyping of unit antenna elements, stacked EBGs, and integration of stacked EBGs with antenna elements. We also evaluate the design through both HFSS (High Frequency Structure Simulator) and over-the-air measurements in an anechoic chamber. Through extensive evaluations, we show that (i) compared to an architecture that does not use EBGs, the proposed novel stacked EBG design provides an average of 25 dB of additional reduction in SI over 1 GHz of bandwidth, (ii) unit antenna element has over 1 GHz of bandwidth at −10 dB return loss, and (iii) HFSS simulations show close correlation with actual measurement results; however, measured results could still be several dB lower or higher than predicted simulation results. For example, the gap between simulated and measured antenna gains is less than 1 dB for 26–28 GHz and 28.5–30 GHz frequencies, but almost 3 dB for 28–28.5 GHz frequency band.
Learning to Improve Operational Efficiency from Pose Error Estimation in Robotic Pollination
Authors: Chen Jinlong , Xiao Jun , Yang Minghao , Pan Hang
Published: August 2024

Autonomous pollination robots have been widely discussed in recent years. However, the accurate estimation of flower poses in complex agricultural environments remains a challenge. To this end, this work proposes the implementation of a transformer-based architecture to learn the translational and rotational errors between the pollination robot’s end effector and the target object with the aim of enhancing robotic pollination efficiency in cross-breeding tasks. The contributions are as follows: (1) We have developed a transformer architecture model, equipped with two feedforward neural networks that directly regress the translational and rotational errors between the robot’s end effector and the pollination target. (2) Additionally, we have designed a regression loss function that is guided by the translational and rotational errors between the robot’s end effector and the pollination targets. This enables the robot arm to rapidly and accurately identify the pollination target from the current position. (3) Furthermore, we have designed a strategy to readily acquire a substantial number of training samples from eye-in-hand observation, which can be utilized as inputs for the model. Meanwhile, the translational and rotational errors identified in the end-manipulator Cartesian coordinate system are designated as loss targets simultaneously. This helps to optimize the training of the model. We conducted experiments on a realistic robotic pollination system. The results demonstrate that the proposed method outperforms the state-of-the-art method, in terms of both accuracy and efficiency.
Short-Circuit Current Calculation of Flexible Direct Current Transmission Lines Considering Line Distribution Parameters
Authors: Wang Zhuoya , Hao Liangliang , Wang Zemin
Published: August 2024

A fault on the DC side of a flexible HVDC system, along with the rise in short-circuit current, develops rapidly. With the gradual expansion of flexible HVDC technology to large capacities and long-distance transmission and offshore transmission scenarios, the problem of short-circuit current calculation considering the characteristics of line distribution parameters needs urgent attention. Therefore, in order to solve the problem of the inaccurate calculation of the short-circuit current on the DC side, the lumped parameter model is used in a flexible DC system for long-distance transmission. This study analyzes the transmission line structure on the basis of the general model of the MMC short-circuit current calculation on the DC side and establishes a mathematical model of a long-distance transmission line considering the characteristics of distributed parameters. Two impedance equivalent models for different length lines are proposed to facilitate the analytical calculation of the short-circuit current. A short-circuit current calculation method for a flexible HVDC system with long-distance transmission lines is proposed. Additionally, the correctness of the proposed method is verified through the comparison of the simulation values and calculation values. The results show that the error of the lumped parameter calculation is about 10%, and the error of the distributed parameter calculation is less than 2%.
Separation and Classification of Partial Discharge Sources in Substations
Authors: Melo João Victor Jales , Lira George Rossany Soares , Costa Edson Guedes , Vilar Pablo Bezerra , Andrade Filipe Lucena Medeiros , Marotti Ana Cristina Freitas , Costa Andre Irani , Leite Neto Antonio Francisco , Santos Júnior Almir Carlos dos
Published: August 2024

This work proposes a methodology for noise removal, separation, and classification of partial discharges in electrical system assets. Partial discharge analysis is an essential method for fault detection and evaluation of the operational conditions of high-voltage equipment. However, it faces several limitations in field measurements due to interference from radio signals, television transmissions, WiFi, corona signals, and multiple sources of partial discharges. To address these challenges, we propose the development of a clustering model to identify partial discharge sources and a classification model to identify the types of discharges. New features extracted from pulses are introduced to model the clustering and classification of discharge sources. The methodology is tested in the laboratory with controlled partial discharge sources, and field tests are conducted in substations to assess its practical applicability. The results of laboratory tests achieved an accuracy of 85% in classifying discharge sources. Field tests were performed in a substation of the Eletrobras group, allowing the identification of at least three potentially defective current transformers.
A Multiparadigm Approach for Generation Dispatch Optimization in a Regulated Electricity Market towards Clean Energy Transition
Authors: Isnandar Suroso , Simorangkir Jonathan F. , Banjar-Nahor Kevin M. , Paradongan Hendry Timotiyas , Hariyanto Nanang
Published: August 2024

In Indonesia, the power generation sector is the primary source of carbon emissions, largely due to the heavy reliance on coal-fired power plants, which account for 60% of electricity production. Reducing these emissions is essential to achieve national clean energy transition goals. However, achieving this initiative requires careful consideration, especially regarding the complex interactions among multiple stakeholders in the Indonesian electricity market. The electricity market in Indonesia is characterized by its non-competitive and heavily regulated structure. This market condition often requires the PLN, as the system operator, to address multi-objective and multi-constraint problems, necessitating optimization in the generation dispatch scheduling scheme to ensure a secure, economical, and low-carbon power system operation. This research introduces a multiparadigm approach for GS optimization in a regulated electricity market to support the transition to clean energy. The multiparadigm integrates multi-agent system and system dynamic paradigms to model, simulate, and quantitatively analyze the complex interactions among multiple stakeholders in the Indonesian regulated electricity market. The research was implemented on the Java–Madura–Bali power system using AnyLogic 8 University Researcher Software. The simulation results demonstrate that the carbon policy scheme reduces the system’s carbon emissions while increasing the system’s cost of electricity. A linear regression for sensitivity analysis was conducted to determine the relationship between carbon policies and the system’s cost of electricity. This research offers valuable insights for policymakers to develop an optimal, acceptable, and reasonable power system operation scheme for all stakeholders in the Indonesian electricity market.
Numerical Investigation and Simulation of Hydrogen Blending into Natural Gas Combustion
Authors: Jung Laura , Mages Alexander , Sauer Alexander
Published: August 2024

This study reviews existing simulation models and describes a selected model for analysing combustion dynamics in hydrogen and natural gas mixtures, specifically within non-ferrous melting furnaces. The primary objectives are to compare the combustion characteristics of these two energy carriers and assess the impact of hydrogen integration on furnace operation and efficiency. Using computational fluid dynamics (CFD) simulations, incorporating actual furnace geometries and a detailed combustion and NOx emission prediction model, this research aims to accurately quantify the effects of hydrogen blending. Experimental tests on furnaces using only natural gas confirmed the validity of these simulations. By providing precise predictions for temperature distribution and NOx emissions, this approach reduces the need for extensive laboratory testing, facilitates broader exploration of design modifications, accelerates the design process, and ultimately lowers product development costs.
The Concept of Statistical Evidence, Historical Roots and Current Developments
Authors: Evans Michael
Published: August 2024

One can argue that one of the main roles of the subject of statistics is to characterize what the evidence in the collected data says about questions of scientific interest. There are two broad questions that we will refer to as the estimation question and the hypothesis assessment question. For estimation, the evidence in the data should determine a particular value of an object of interest together with a measure of the accuracy of the estimate, while for the hypothesis assessment, the evidence in the data should provide evidence in favor of or against some hypothesized value of the object of interest together with a measure of the strength of the evidence. This will be referred to as the evidential approach to statistical reasoning, which can be contrasted with the behavioristic or decision-theoretic approach where the notion of loss is introduced, and the goal is to minimize expected losses. While the two approaches often lead to similar outcomes, this is not always the case, and it is commonly argued that the evidential approach is more suited to scientific applications. This paper traces the history of the evidential approach and summarizes current developments.
Impact of the September 2023 Storm Daniel and Subsequent Flooding in Thessaly (Greece) on the Natural and Built Environment and on Infectious Disease Emergence
Authors: Mavroulis Spyridon , Mavrouli Maria , Lekkas Efthymios , Tsakris Athanasios
Published: August 2024

The storm Daniel and subsequent floods hit the Region of Thessaly (Greece) in early September 2023, causing extensive damage to the built environment (buildings, networks, and infrastructure), the natural environment (water bodies and soil), and the population (fatalities, injured, homeless, and displaced people). Additionally, the conditions and factors favorable for indirect public health impact (infectious diseases) emerged in the flood-affected communities. The factors had to do with infectious diseases from rodents and vectors, injuries, respiratory infections, water contamination, flood waste and their disposal sites as well as structural damage to buildings and the failures of infrastructure. The conditions that evolved necessitated the mobilization of the Civil Protection and Public Health agencies not only to cope with the storm and subsequent floods but also to avoid and manage indirect public health impact. The instructions provided to affected residents, health experts, and Civil Protection staff were consistent with the best practices and lessons learned from previous disasters. The emphasis should be on training actions for competent agencies, as well as education and increasing the awareness of the general population. Non-structural and structural measures should be implemented for increasing the climate resilience of infrastructures including the health care systems within a One Health approach.
A Framework for Developing Tools to Predict PFAS Physical–Chemical Properties and Mass-Partitioning Parameters
Authors: Brusseau Mark L.
Published: August 2024

A framework for developing predictive models for PFAS physical–chemical properties and mass-partitioning parameters is presented. The framework is based on the objective of developing tools that are of sufficient simplicity to be used rapidly and routinely for initial site investigations and risk assessments. This is accomplished by the use of bespoke PFAS-specific QSPR models. The development of these models entails aggregation and curation of measured data sets for a target property or parameter, supplemented by estimates produced with quantum–chemical ab initio predictions. The application of bespoke QSPR models for PFAS is illustrated with several examples, including partitioning to different interfaces, uptake by several fish species, and partitioning to four different biological materials. Reasonable correlations to molar volume were observed for all systems. One notable observation is that the slopes of all of the regression functions are similar. This suggests that the partitioning processes in all of these systems are to some degree mediated by the same mechanism, namely hydrophobic interaction. Special factors and elements requiring consideration in the development of predictive models are discussed, including differences in bulk-phase versus interface partitioning processes.
A Potential Replacement to Phenol–Formaldehyde-Based Adhesives: A Study of Plywood Panels Manufactured with Bio-Based Wood Protein and Nanolignin Adhesives
Authors: Núñez-Decap Mario , Friz-Sánchez Catherine , Opazo-Carlsson Camila , Moya-Rojas Boris , Vidal-Vega Marcela
Published: August 2024

Plywood production relies on phenol–formaldehyde (PF), which is why bio-based wood adhesives (BBWAs) were developed as potential replacements, showing promising results in several tests performed. A control sample (PLY-C) with PF and two samples (PLY-1 and PLY-2) with BBWA were manufactured, on which physical and mechanical properties, adhesive bonding morphology, formaldehyde emissions, and accelerated UV aging were evaluated. The adhesive penetration results, into the wood cells, were according to the viscosity of each adhesive. About the mechanical properties, the sample PLY-2 presented the same MOE and tensile strength as the sample PLY-C and reached 87% of the sample PLY-C MOR in the parallel direction. On the other hand, the sample PLY-1 presented the same behavior in the Janka hardness test as the sample PLY-C. All the samples subjected to shear strength tests met the requirement, and the samples PLY-1 and PLY-2 reached 68% and 80% of the PLY-C sample, respectively. The samples manufactured with BBWA presented a decrease in formaldehyde emissions by 88% and they were less susceptible to color change than the control sample under UV aging. According to the results obtained, it is concluded that plywood manufactured with BBWA might be a considerable replacement for plywood manufactured with PF adhesives at a laboratory scale.
Land Use Evolution and Its Driving Factors over the Past 30 Years in Luochuan County
Authors: Xue Yuhang , Ma Wenbao , Liu Liangxu , Yang Yang
Published: August 2024

Understanding the evolution of land use change and its drivers is vital in keeping the fragile balance between human activities and nature. The present study employs remote sensing data from between 1990 and 2020 during the Grain-for-Green Project (GGP) in Luochuan county, Shaanxi Province, which offers 30 years of continuous data on precipitation, temperature, population, and GDP. Here, the combined method of supervised classification with manual visual interpretation was adopted for building a high-precision spatial distribution information database, in order to explore the links existing between the change features of land use, distribution, and spatial pattern, and the interference of local socio-economic development and natural factors before and after the GGP. According to the results, during the past three decades, Luochuan county has undergone large changes in land use types, displaying distinct features and regional disparities. Geographically, the north of Luochuan county is predominantly forest and grassland, while farmland is mostly in the south of Luochuan county. In 1990, farmland dominated this county; however, after 2000, forest and grassland areas expanded. Notably, the implementation of the GGP significantly influenced changes in grassland and forest areas. With the development of modernization, Luochuan county’s land use structure has gradually equilibrated, with increased uniformity in the distribution of various land use types. Obviously, the shift in land use from 1990 to 2020 primarily correlates with mean annual temperature, annual precipitation, total population, and GDP. Furthermore, regression analysis revealed that during the initial decade of the GGP, natural factors primarily drove land use changes. However, after the GGP, the conversion rate from farmland to forest and shrubland/grassland escalated, and population growth was the continual external force driving the expansion of forest and grassland. Despite substantial economic benefits from land development and utilization in Luochuan county during the past 30 years, certain human economic activities have posed significant pressure on regional agricultural development and sustainable land resource use. Overall, this study helps our government to enhance national land management and planning through a targeted method, also providing a reference for analyzing land use change processes within same areas.
The Demand of Forest Bathing in Northern Italy’s Regions: An Assessment of the Economic Value
Authors: Visintin Francesca , Bassi Ivana , Deotto Vanessa , Iseppi Luca
Published: August 2024

The study aims to evaluate the demand for forest bathing in northern Italy’s regions, underlining the willingness to pay and the potential tourists’ habits and flows on attending alpine contexts. Several studies have analyzed the psychophysical benefits of forest bathing, and there is a growing interest in assessing its economic value for tourism purposes. The sample’s answers have been analyzed employing a stratified sampling methodology considering three different macro areas (northwest regions, northeast regions, and the Friuli Venezia Giulia region). After analyzing the sample’s attitudes, the research approached the estimation section by calculating the flow as the number of potential forest bathing hikes per year and the willingness to pay through the contingent valuation method. The main results indicate that forest bathing activity in northern Italy has a considerable monetary value, and it is generally compared with positive feelings, particularly concerning well-being and fascination factors.
Nitrogen Application Promotes Drought Resistance of Toona sinensis Seedlings
Authors: Yu Xiaochi , He Runhua , Yi Fei , Liu Ying , Zhang Peng , Wang Junhui , Ma Wenjun
Published: August 2024

A factorial design consisting of four N treatments (no N fertilization, 0.70, 0.14, and 0.28 mol N·plant−1) combined with two water conditions, drought (D = 25 ± 5% soil moisture content) and well-watered (W = 65 ± 5% soil moisture content), was used. Overall, the gas exchange parameters, chlorophyll, and growth of T. sinensis seedlings were significantly inhibited under drought conditions, while all of them showed improvement with N fertilizer, particularly at 0.14~0.28 mol N·plant−1. Under drought conditions, the root length and root surface area of T. sinensis increased; N application positively influenced the above root morphological changes. The activities of antioxidant enzymes such as superoxide dismutase (SOD; EC1.15.1.1) and peroxidase (POD; EC1.11.1.7) and the contents of osmotic adjustment substances such as soluble sugar and proline increased upon drought stress, but decreased under N application conditions. Overall, T. sinensis responds to drought stress through the synergistic action of drought resistance and drought tolerance mechanisms. N application enhances photosynthesis and improves root morphology, compensating for the need for osmotic regulation and reactive oxygen species scavenging.
Machine Learning-Assisted Dynamic Proximity-Driven Sorting Algorithm for Supermarket Navigation Optimization: A Simulation-Based Validation
Authors: Abella Vincent , Initan Johnfil , Perez Jake Mark , Astillo Philip Virgil , Cañete Luis Gerardo , Choudhary Gaurav
Published: August 2024

In-store grocery shopping is still widely preferred by consumers despite the rising popularity of online grocery shopping. Moreover, hardware-based in-store navigation systems and shopping list applications such as Walmart’s Store Map, Kroger’s Kroger Edge, and Amazon Go have been developed by supermarkets to address the inefficiencies in shopping. But even so, the current systems’ cost-effectiveness, optimization capability, and scalability are still an issue. In order to address the existing problems, this study investigates the optimization of grocery shopping by proposing a proximity-driven dynamic sorting algorithm with the assistance of machine learning. This research method provides us with an analysis of the impact and effectiveness of the two machine learning models or ML-DProSA variants—agglomerative hierarchical and affinity propagation clustering algorithms—in different setups and configurations on the performance of the grocery shoppers in a simulation environment patterned from the actual supermarket. The unique shopping patterns of a grocery shopper and the proximity of items based on timestamps are utilized in sorting grocery items, consequently reducing the distance traveled. Our findings reveal that both algorithms reduce dwell times for grocery shoppers compared to having an unsorted grocery shopping list. Ultimately, this research with the ML-DProSA’s optimization capabilities aims to be the foundation in providing a mobile application for grocery shopping in any grocery stores.
Biopreservation and the Safety of Fish and Fish Products, the Case of Lactic Acid Bacteria: A Basic Perspective
Authors: Cortés-Sánchez Alejandro De Jesús , Jaramillo-Flores María Eugenia , Díaz-Ramírez Mayra , Espinosa-Chaurand Luis Daniel , Torres-Ochoa Erika
Published: August 2024

Through fishing and aquaculture activities, humans have access to fish, which are a basic food source in the diet due to their nutritional value. Fish are widely distributed and commercialized worldwide in different products (e.g., whole fresh, filleted, sliced, frozen, dried, smoked, salted, and canned fish, among others). Because of their composition and nutritional value, fish are highly susceptible to spoilage and contamination, mainly by microorganisms, compromising their safety, shelf life, and availability; therefore, consuming fish can become a risk to public health. Foodborne diseases are considered important global public health problems because of their incidence, consequences, mortality, and negative economic impact on the population. Among the foods commonly associated with foodborne diseases are fish and fish products contaminated by various agents that are harmful to health throughout the food chain. Because of the constant growth of the population and the demand for greater quantities of food, the search for and development of technologies for the generation and availability of fresh, safe food with nutritional and sensorial qualities has increased. This is how biopreservation emerges, which, through the application of lactic acid bacteria and/or metabolites, is positioned as a sustainable, economic, and simple alternative for obtaining fish and fish products and making them available for human and/or animal consumption. Therefore, this work focuses on providing a basic and general perspective and information through the search, collection, and analysis of information in various databases, such as Google Scholar, SciELO, Redalyc, ScienceDirect, and/or institutional repositories, regarding fish production, nutritional properties, foodborne diseases, causal agents, and their associations with fish and fish products. Additionally, this study describes the biopreservation process through the use of lactic acid bacteria and/or metabolites to extend shelf life and promote the safety and nutritional and sensory qualities of fish and fish products intended for human and/or animal consumption.
Staphylococcus spp. in Salad Vegetables: Biodiversity, Antimicrobial Resistance, and First Identification of Methicillin-Resistant Strains in the United Arab Emirates Food Supply
Authors: Habib Ihab , Lakshmi Glindya Bhagya , Mohamed Mohamed-Yousif Ibrahim , Ghazawi Akela , Khan Mushtaq , Al-Rifai Rami H. , Abdalla Afra , Anes Febin , Elbediwi Mohammed , Khalifa Hazim O. , Senok Abiola
Published: August 2024

Contamination of leafy greens with Staphylococcus spp. can occur at various supply chain stages, from farm to table. This study comprehensively analyzes the species diversity, antimicrobial resistance, and virulence factors of Staphylococci in salad vegetables from markets in the United Arab Emirates (UAE). A total of 343 salad items were sampled from three major cities in the UAE from May 2022 to February 2023 and tested for the presence of Staphylococcus spp. using standard culture-based methods. Species-level identification was achieved using matrix-assisted laser desorption ionization-time of flight mass spectrometry. Antimicrobial susceptibility testing was conducted using the VITEK-2 system with AST-P592 cards. Additionally, whole genome sequencing (WGS) of ten selected isolates was performed to characterize antimicrobial resistance determinants and toxin-related virulence factors. Nine Staphylococcus species were identified in 37.6% (129/343) of the tested salad items, with coagulase-negative staphylococci (CoNS) dominating (87.6% [113/129]) and S. xylosus being the most prevalent (89.4% [101/113]). S. aureus was found in 4.6% (14/343) of the salad samples, averaging 1.7 log10 CFU/g. One isolate was confirmed as methicillin-resistant S. aureus, harboring the mecA gene. It belonged to multi-locus sequence type ST-672 and spa type t384 and was isolated from imported fresh dill. Among the characterized S. xylosus (n = 45), 13.3% tested positive in the cefoxitin screen test, and 6.6% were non-susceptible to oxacillin. WGS analysis revealed that the cytolysin gene (cylR2) was the only toxin-associated factor found in S. xylosus, while a methicillin-sensitive S. aureus isolate harbored the Panton-Valentine Leukocidin (LukSF/PVL) gene. This research is the first to document the presence of methicillin-resistant S. aureus in the UAE food chain. Furthermore, S. xylosus (a coagulase-negative staphylococcus not commonly screened in food) has demonstrated phenotypic resistance to clinically relevant antimicrobials. This underscores the need for vigilant monitoring of antimicrobial resistance in bacterial contaminants, whether pathogenic or commensal, at the human-food interface.
3-Methyl Thiophene-Modified Boron-Doped Diamond (BDD) Electrodes as Efficient Catalysts for Phenol Detection—A Case Study for the Detection of Gallic Acid in Three Specific Tea Types
Authors: Abrahams Dhielnawaaz , Baker Priscilla G. L.
Published: August 2024

Polymer modification has been established as a cost-effective, simple, in situ method for overcoming some of the inherent disadvantages of boron-doped diamond (BDD) electrodes, and its application has been extended to reliable, low-cost environmental monitoring solutions. The present review focuses on modifying BDD electrodes with semi-conductive polymers acting as redox mediators. This article reports on the development of a 3-methyl thiophene-modified boron-doped diamond (BDD/P3MT) sensor for the electrochemical determination of total phenolic compounds (TPCs) in tea samples, using gallic acid (GA) as a marker. GA is a significant polyphenol with various biological activities, making its quantification crucial. Thus, a simple, fast, and sensitive GA sensor was fabricated using the electroanalytical square wave voltammetry (SWV) technique. The sensor utilizes a semi-conductive polymer, 3-methyl thiophene, as a redox mediator to enhance BDD’s sensitivity and selectivity. Electrochemical synthesis was used for polymer deposition, allowing for greater purity and avoiding solubility problems. The BDD/P3MT sensor exhibits good electrochemical properties, including rapid charge transfer and a large electrochemical area, enabling GA detection with a limit of detection of 11 mg/L. The sensor’s response was correlated with TPCs measured by the Folin–Ciocalteu method. Square wave voltammetry (SWV) showed a good linear relationship between peak currents and GA concentrations in a wide linear range of 3–71 mg/L under optimal conditions. The BDD/P3MT sensor accurately measured TPCs in green tea, rooibos tea, and black tea samples, with green tea exhibiting the highest TPC levels. The results demonstrate the potential of the modified BDD electrode for the rapid and accurate detection of phenolic compounds in tea, with implications for quality control and antioxidant activity assessments. The prolific publications of the past decade have established BDD electrodes as robust BDD sensors for quantifying polyphenols. Fruits, vegetables, nuts, plant-derived beverages such as tea and wine, traditional Eastern remedies and various herbal nutritional supplements contain phenolic chemicals. The safety concerns of contaminated food intake are significant health concerns worldwide, as there exists a critical nexus between food safety, nutrition, and food security. It has been well established that green tea polyphenol consumption promotes positive health effects. Despite their potential benefits, consuming high amounts of these polyphenols has sparked debate due to concerns over potential negative consequences.
Direct Determination of Glyphosate and Its Metabolites in Foods of Animal Origin by Liquid Chromatography–Tandem Mass Spectrometry
Authors: Denžić Lugomer Marija , Bilandžić Nina , Pavliček Damir , Novosel Tiana
Published: August 2024

Glyphosate is the most used herbicide in agriculture. Its major metabolite is AMPA (aminomethylphosphonic acid), but N-acetyl-AMPA and N-acetylglyphosate are also metabolites of interest. For risk assessment, a general residue definition was proposed as the sum of glyphosate, AMPA, N-acetyl-glyphosate and N-acetyl-AMPA, expressed as glyphosate. A confirmatory method for glyphosate in fat, liver and kidneys, as well as a confirmatory method for AMPA and N-acetyl-glyphosate in all matrices, are still missing. In this paper, we present a method for the quantitative determination of glyphosate residues and its metabolites AMPA, N-acetyl-AMPA and N-acetyl-glyphosate by liquid chromatography–mass spectrometry (LC-MS/MS) in adipose tissue, liver, eggs, milk and honey without derivatization. Different chromatographic columns were tested, with the Hypercarb column providing the best results. The analytes were eluted with mobile phases of acidified water with 1.2% formic acid and 0.5% formic acid in acetonitrile. Sample purification procedures were also optimized by varying the solvent extraction mixtures (water, methanol and mixture ψ (methanol, water) = 1:1, each with the addition of 1% formic acid (v/v)), using different sorbents in solid phase extraction (SPE) (polymeric cationic (PCX) and anionic (PAX)) and using dispersive solid phase extraction (dSPE) (C18 and PSA) by modifying the extraction procedures. Finally, the analytes were extracted from the samples with 1% formic acid in water (v/v). Milk and adipose tissue were purified by the addition of dichloromethane, while liver and egg samples were purified by SPE with a mixed cation exchange sorbent and ultrafiltration with cut-off filters. The proposed analytical procedures were validated according to SANTE/11312/2021 guidelines: linearity, limits of quantification, precision and accuracy were determined for all matrices. The limits of quantification (LOQs) ranged from 0.025 to 0.2 mg kg−1. Precision, expressed as relative standard deviation, was <20%, while accuracy, expressed as analytical recovery, ranged from 70% to 120%. During method validation, the measurement uncertainty was estimated to be <50% for all analytes. Good validation parameters according to the SANTE document were achieved for all analytes. Therefore, the method can be considered reliable and sensitive enough for routine monitoring of polar pesticides. The application of the accredited method in routine analysis will provide data that are useful for the re-evaluation of risk assessment studies in foods of animal origin.
Cardiac Phenotype and Gene Mutations in RASopathies
Authors: Faienza Maria Felicia , Meliota Giovanni , Mentino Donatella , Ficarella Romina , Gentile Mattia , Vairo Ugo , D’amato Gabriele
Published: August 2024

Cardiac involvement is a major feature of RASopathies, a group of phenotypically overlapping syndromes caused by germline mutations in genes encoding components of the RAS/MAPK (mitogen-activated protein kinase) signaling pathway. In particular, Noonan syndrome (NS) is associated with a wide spectrum of cardiac pathologies ranging from congenital heart disease (CHD), present in approximately 80% of patients, to hypertrophic cardiomyopathy (HCM), observed in approximately 20% of patients. Genotype–cardiac phenotype correlations are frequently described, and they are useful indicators in predicting the prognosis concerning cardiac disease over the lifetime. The aim of this review is to clarify the molecular mechanisms underlying the development of cardiac diseases associated particularly with NS, and to discuss the main morphological and clinical characteristics of the two most frequent cardiac disorders, namely pulmonary valve stenosis (PVS) and HCM. We will also report the genotype–phenotype correlation and its implications for prognosis and treatment. Knowing the molecular mechanisms responsible for the genotype–phenotype correlation is key to developing possible targeted therapies. We will briefly address the first experiences of targeted HCM treatment using RAS/MAPK pathway inhibitors.
Tracking Ovine Pulmonary Adenocarcinoma Development Using an Experimental Jaagsiekte Sheep Retrovirus Infection Model
Authors: Cousens Chris , Meehan James , Collie David , Wright Steven , Chang Ziyuan , Todd Helen , Moore Jo , Grant Lynn , Daniel Carola R. , Tennant Peter , Ritchie Adrian , Nixon James , Proudfoot Chris , Guido Stefano , Brown Helen , Gray Calum D. , MacGillivray Tom J. , Clutton R. Eddie , Greenhalgh Stephen N. , Gregson Rachael , Griffiths David J. , Spivey James , Storer Nicole , Eckert Chad E. , Gray Mark
Published: August 2024

Ovine pulmonary adenocarcinoma (OPA) is an infectious, neoplastic lung disease of sheep that causes significant animal welfare and economic issues throughout the world. Understanding OPA pathogenesis is key to developing tools to control its impact. Central to this need is the availability of model systems that can monitor and track events after Jaagsiekte sheep retrovirus (JSRV) infection. Here, we report the development of an experimentally induced OPA model intended for this purpose. Using three different viral dose groups (low, intermediate and high), localised OPA tumour development was induced by bronchoscopic JSRV instillation into the segmental bronchus of the right cardiac lung lobe. Pre-clinical OPA diagnosis and tumour progression were monitored by monthly computed tomography (CT) imaging and trans-thoracic ultrasound scanning. Post mortem examination and immunohistochemistry confirmed OPA development in 89% of the JSRV-instilled animals. All three viral doses produced a range of OPA lesion types, including microscopic disease and gross tumours; however, larger lesions were more frequently identified in the low and intermediate viral groups. Overall, 31% of JSRV-infected sheep developed localised advanced lesions. Of the sheep that developed localised advanced lesions, tumour volume doubling times (calculated using thoracic CT 3D reconstructions) were 14.8 ± 2.1 days. The ability of ultrasound to track tumour development was compared against CT; the results indicated a strong significant association between paired CT and ultrasound measurements at each time point (R2 = 0.799, p < 0.0001). We believe that the range of OPA lesion types induced by this model replicates aspects of naturally occurring disease and will improve OPA research by providing novel insights into JSRV infectivity and OPA disease progression.