bluuebunny/crossref_metadata_2025 huggingface dataset:
Dynamics of Gill Responses to a Natural Infection with Neoparamoeba perurans in Farmed Tasmanian Atlantic Salmon
Authors: Vallarino Max Charles , Dagen Sarah L. , Costelloe Eoin , Oyenekan Shalom Inioluwa , Tinsley John , Valdenegro Victoria , Król Elżbieta , Noguera Patricia , Martin Samuel A. M.
Published: August 2024

Gill health has become a significant global challenge for Atlantic salmon (Salmo salar) aquaculture, particularly during the marine phase of farming. The increasing prevalence of gill pathologies has been linked to rising seawater temperatures, underscoring the need to evaluate existing tools for monitoring gill health and to develop novel approaches for early detection. In this study, we investigated the gill responses of commercially farmed Atlantic salmon to natural infection with Neoparamoeba perurans during an outbreak of amoebic gill disease (AGD) in Tasmania. Our focus spanned the low AGD prevalence, high AGD prevalence, and post-freshwater treatment stages of the outbreak. Evaluations of gill tissue included assessments of the gross AGD score, histopathological score, abundance of N. perurans (measured by 18S rRNA gene expression), and expression levels of inflammation-related transcripts. We demonstrated a strong correlation between different measures of AGD-related gill pathology and significant differences between distinct stages of the N. perurans outbreak. Post-treatment, fish exhibited considerable variability in their responses to the freshwater bath, highlighting the necessity for personalized management strategies that consider genetic, environmental, and health status factors. The expression patterns of angiogenin-1 (ANG1) and complement C1q tumour necrosis factor-related protein 3-like (C1QTNF3) emphasize their potential as biomarkers for early detection of gill damage in salmon aquaculture worldwide.
Improving Milk Yield, Milk Quality, and Follicular Functionality Behavior in Dairy Cows from the Implementation of Microencapsulated Chili Pepper Supplements in Their Diets
Authors: Madrigal-Valverde Mónica , Loiola Marcus Vinicius Galvão , Freitas Júnior José E. de , Santiago Murilo R. , Dantas Lara Lôbo , Menezes Artur Azevedo , de Matos Brandão Carneiro Isabella , Xavier Gleice Mendes , Araujo Endrigo Adonis Braga , Pereira Juliana Reolon , Bittencourt Rodrigo Freitas
Published: August 2024

The present study evaluates the effect of including microencapsulated hot chili pepper (MHCP) in the diet of crossbred dairy cows on the volume and quality of milk and on ovarian morphofunctionality. Twenty-four crossbred females in their lactating period were used. The cows were divided into two experimental groups, a control (CT) and an MHCP -supplemented group (CP) given 1 g a day per animal of microencapsulated hot chili in concentrate for 42 days. Over seven weeks of daily milk production was measured, and sample milk was collected weekly for composition analysis. Animals were subject to an ovulation synchronization protocol on day 0 (D0), and an intravaginal progesterone (P4) implant, estradiol benzoate, and prostaglandin (PGF2α) were administered. On D8, the P4 implant was removed and PGF2α, equine chorionic gonadotropin, and estradiol cypionate were administered to the animals. The ovarian dynamics were evaluated in B mode and color Doppler. There were significant differences (p < 0.05) in the group X time interaction, the volume of milk produced, and the amount in kg/day of milk components. There was a higher percentage of vascularization in the preovulatory follicle in the CP group (p ≥ 0.10). The findings show that the inclusion of MHCP in the diet of dairy cows does influence their milk production and reproduction.
A Functional 67-bp Duplication Locating at the Core Promoter Region within the Bovine ADIPOQ Gene Is Associated with Ovarian Traits and mRNA Expression
Authors: Li Yufu , Liu Tingting , Zhang Mengyang , Pan Chuanying , Liu Xu , Zhao Haiyu , Lan Xianyong
Published: August 2024

ADIPOQ plays a crucial role in regulating the reproductive system, but there are few reports on the effects of ADIPOQ on ovarian in dairy cows. Previous studies have verified the presence of a 67-bp mutation in the promoter region of the ADIPOQ gene. Hence, we employed ovarian tissues (n = 2111) and blood samples (n = 108) from Chinese Holstein cows as experimental samples to examine the association between ADIPOQ promoter variants and ovarian traits. We extracted DNA from these samples and conducted genetic typing identification on each sample using advanced techniques like PCR and agarose gel electrophoresis. Consequently, the DD, ID, and II genotypes were discovered. and it has been observed that the mutation frequency of this locus is low in the Chinese Holstein cow. Importantly, the correlational analysis unveiled a significant relationship (p < 0.05) between the weight of ovaries in late estrus and the width of ovaries during the estrus interval with the mutation. Result of the RT-PCR revealed that the ID genotype partially diminished the expression of the ADIPOQ gene. The results of this study suggest that the identified variable duplication could serve as a potential genetic marker for enhancing the ovarian traits of Chinese Holstein cows.
Comparative Proteomic Identification of Ram Sperm before and after In Vitro Capacitation
Authors: Chen Ya-Le , Li Chun-Yan , Wang Peng-Hui , Wang Ru , Zhuo Xian , Zhang Yan , Wang Shi-Jia , Sun Zhi-Peng , Chen Jia-Hong , Cheng Xiao , Zhang Zi-Jun , Ren Chun-Huan , Wang Qiang-Jun
Published: August 2024

Ram sperm undergo a sequence of physiological and biochemical changes collectively termed as capacitation to perform oocyte fertilization. However, the protein changes induced by capacitation remain in need of further exploration. Thus, the present study investigated the comparative proteomic profiling in ram spermatozoa under non-capacitating (NC) and capacitating (CAP) conditions in vitro using a liquid chromatography–tandem mass spectrometry combined with tandem mass tag labeling strategy. As a results, 2050 proteins were identified and quantified; 348 of them were differentially abundant, with 280 of the proteins upregulated and 68 of the proteins downregulated between the CAP and NC spermatozoa, respectively. Functional enrichment analysis indicated that the differentially abundant proteins Prune Exopolyphosphatase 1, Galactose-1-Phosphate Uridylyltransferase, and ATP Citrate Lyase were strictly related to energy production and conversion, and Phosphoglycolate phosphatase, Glucosamine-6-Phosphate Deaminase 1 and 2 were related to metabolism, RNA processing, and vesicular transport pathways. Furthermore, the networks of protein–protein interaction indicated a strong interaction among these differential proteins in annotated pathways such as ubiquitin and transport metabolism. Our findings indicate that capacitation progress might be regulated through different pathways, providing insights into mechanisms involved in ram sperm capacitation and fertility.
Full-Fat Soybean Meals as an Alternative Poultry Feed Ingredient—Feed Processing Methods and Utilization—Review and Perspective
Authors: Toomer Ondulla T. , Oviedo-Rondón Edgar Orlando , Ali Muhammad , Joseph Michael , Vu Thien , Fallen Ben , Mian Rouf
Published: August 2024

On a global scale, the poultry industry expands its wings in terms of meat and egg production to the masses. However, this industry itself requires a sustainable and permanent supply of different inputs, one of which is poultry feed and nutrition. Soybean is a versatile protein that is offered to poultry in different inclusion rates in commercial diets after being processed using various thermal and mechanical processing methods. Conventional commercial soybean meal is usually prepared by the extraction of oil from whole soybeans using solvents, producing a meal that has approximately 1% crude fat. Without oil extraction, full-fat soybean (FFSBM) is produced, and it is an excellent source of dietary energy and protein for poultry with a nutritional profile of 38–40% protein and 18–20% crude fat, on average. FFSBM has less crude protein (CP) than solvent-extracted soybean meal (SE SBM) but higher metabolizable energy due to higher fat content. Alternatively, extruded expeller processing produces defatted soybean meal containing approximately 6–7% crude fat. Studies have demonstrated that FFSBM can be used in poultry diets to improve poultry nutrition, performance, and quality of the poultry meat and eggs produced. This review aims to evaluate the nutrition and use of meals prepared from conventional and high-oleic soybeans using various feed processing methods.
The SOD1 Inhibitor, LCS-1, Oxidizes H2S to Reactive Sulfur Species, Directly and Indirectly, through Conversion of SOD1 to an Oxidase
Authors: Olson Kenneth R. , Takata Tsuyoshi , Clear Kasey J. , Gao Yan , Ma Zhilin , Pfaff Ella , Mouli Karthik , Kent Thomas A. , Jones Prentiss , Fukuto Jon , Wu Gang , Straub Karl D.
Published: August 2024

LCS-1, a putative selective inhibitor of SOD1, is a substituted pyridazinone with rudimentary similarity to quinones and naphthoquinones. As quinones catalytically oxidize H2S to biologically active reactive sulfur species (RSS), we hypothesized LCS-1 might have similar attributes. Here, we examine LCS-1 reactions with H2S and SOD1 using thiol-specific fluorophores, liquid chromatography–mass spectrometry, electron paramagnetic resonance (EPR), UV–vis spectrometry, and oxygen consumption. We show that LCS-1 catalytically oxidizes H2S in buffer solutions to form RSS, namely per- and polyhydrosulfides (H2Sn, n = 2–6). These reactions consume oxygen and produce hydrogen peroxide, but they do not have an EPR signature, nor do they affect the UV–vis spectrum. Surprisingly, LCS-1 synergizes with SOD1, but not SOD2, to oxidize H2S to H2S3-6. LCS-1 forms monothiol adducts with H2S, glutathione (GSH), and cysteine (Cys), but not with oxidized glutathione or cystine; both thiol adducts inhibit LCS-1-SOD1 synergism. We propose that LCS-1 forms an adduct with SOD1 that disrupts the intramolecular Cys57-Cys146 disulfide bond and transforms SOD1 from a dismutase to an oxidase. This would increase cellular ROS and polysulfides, the latter potentially affecting cellular signaling and/or cytoprotection.
From Waste to Wealth: Exploring the Bioactive Potential of Wine By-Products—A Review
Authors: Peña-Portillo Glenda-Caridad , Acuña-Nelson Sergio-Miguel , Bastías-Montes José-Miguel
Published: August 2024

The present paper explores the biological potential of bioactive compounds present in wine industry wastes, highlighting their valorization to promote sustainability and circular economy. Wine by-products, such as grape pomace and vine shoots, contain a high concentration of polyphenols, flavonoids, anthocyanins and other phytochemicals with antioxidant, anti-inflammatory and anticarcinogenic properties. Both conventional extraction methods, such as solid–liquid extraction, and emerging technologies, including enzyme-assisted extraction, ultrasound-assisted extraction, supercritical fluid extraction, microwave-assisted extraction, pressurized liquid extraction, high-hydrostatic-pressure extraction, and deep natural solvent-assisted extraction (NaDES), are discussed. In addition, the preservation of polyphenolic extracts by microencapsulation, a key technique to improve the stability and bioavailability of bioactive compounds, is addressed. The combination of advanced extraction methods and innovative preservation techniques offers a promising perspective for the valorization of bioactive compounds from wine residues, driving sustainability and innovation in the industry.
Prediction of PM2.5 Concentration on the Basis of Multitemporal Spatial Scale Fusion
Authors: Li Sihan , Sun Yu , Wang Pengying
Published: August 2024

While machine learning methods have been successful in predicting air pollution, current deep learning models usually focus only on the time-based connection of air quality monitoring stations or the complex link between PM2.5 levels and explanatory factors. Due to the lack of effective integration of spatial correlation, the prediction model shows poor performance in PM2.5 prediction tasks. Predicting air pollution levels accurately over a long period is difficult because of the changing levels of correlation between past pollution levels and the future. In order to address these challenges, the study introduces a Convolutional Long Short-Term Memory (ConvLSTM) network-based neural network model with multiple feature extraction for forecasting PM2.5 levels in air quality prediction. The technique is composed of three components. The model-building process of this article is as follows: Firstly, we create a complex network layout with multiple branches to capture various temporal features at different levels. Secondly, a convolutional module was introduced to enable the model to focus on identifying neighborhood units, extracting feature scales with high spatial correlation, and helping to improve the learning ability of ConvLSTM. Next, the module for spatiotemporal fusion prediction is utilized to make predictions of PM2.5 over time and space, generating fused prediction outcomes that combine characteristics from various scales. Comparative experiments were conducted. Experimental findings indicate that the proposed approach outperforms ConvLSTM in forecasting PM2.5 concentration for the following day, three days, and seven days, resulting in a lower root mean square error (RMSE). This approach excels in modeling spatiotemporal features and is well-suited for predicting PM2.5 levels in specific regions.
Computer-Aided Design and Additive Manufacturing for Automotive Prototypes: A Review
Authors: Vido Marcos , de Oliveira Neto Geraldo Cardoso , Lourenço Sergio Ricardo , Amorim Marlene , Rodrigues Mário Jorge Ferreira
Published: August 2024

This study investigated the integration of computer-aided design (CAD) and additive manufacturing (AM) in prototype production, particularly in the automotive industry. It explores how these technologies redefine prototyping practices, with a focus on design flexibility, material efficiency, and production speed. Adopting the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines, this study encompasses a systematic review of 28 scholarly articles. It undertakes a comprehensive analysis to identify key themes, trends, and gaps in the existing research on CAD and AM integration in automotive prototyping. This study revealed the significant advantages of CAD and AM in prototype manufacturing, including improved design capabilities, efficient material usage, and the creation of complex geometries. It also addresses ongoing challenges, such as technology integration costs, scalability, and sustainability. Furthermore, this study foresees future developments by focusing on enhancing CAD and AM technologies to meet evolving market demands and optimize performance. This study makes a unique contribution to the literature by providing a detailed overview of the integration of CAD and AM in the context of automotive prototyping. This study incorporates valuable insights into the current practices and challenges and future prospects, potentially leading to more advanced, sustainable, and customer-oriented prototyping methods in the automotive sector.
Experimental Verification of 1D-Simulation Method of Water Hammer Induced in Two Series-Connected Pipes of Different Diameters: Determination of the Pressure Wave Speed
Authors: Lewandowski Mariusz , Adamkowski Adam
Published: August 2024

This paper presents the results of laboratory tests of water hammer phenomenon induced in two series-connected copper pipes with different diameters (a diameter ratio of 1:1.25) by a quick-closing valve installed at the end of the simple upstream tank–pipeline–valve system. Test results were compared with calculations made with the use of various friction loss models incorporated in a one-dimensional model based on a method of characteristics. The calculation takes into consideration quasi-steady and unsteady friction models as well as a special discretization procedure of the solution domain that ensures the elimination of numerical diffusion in the numerical scheme. The main attention was paid to determining the value of the pressure wave speed in the pipes, which has a significant influence on the compliance between the calculations and the experimental results of the pressure amplitudes and wave frequencies. Two methods of determining the wave speed were proposed and evaluated based on the measurements. The results presented in this article indicate that the use of the proposed procedure instead of the classic formulas for determining the pressure wave speed gives the desired correspondence between the frequencies of the measured and calculated waves. Calculation examples made with the use of different friction models showed that application of the developed procedure for discretization of the solution domain and the method used for determining the wave speed opened the possibility of reliable verification of these models, free of numerical errors and frequency discrepancies between the computational and measured wave.
Multi-Agent Cross-Domain Collaborative Task Allocation Problem Based on Multi-Strategy Improved Dung Beetle Optimization Algorithm
Authors: Zhou Yuxiang , Lu Faxing , Xu Junfei , Wu Ling
Published: August 2024

Cross-domain cooperative task allocation is a complex and challenging issue in the field of multi-agent task allocation that requires urgent attention. This paper proposes a task allocation method based on the multi-strategy improved dung beetle optimization (MSIDBO) algorithm, aiming to solve the problem of fully distributed multi-agent cross-domain cooperative task allocation. This method integrates two key objective functions: target allocation and control allocation. We propose a target allocation model based on the optimal comprehensive efficiency, cluster load balancing, and economic benefit maximization, and a control allocation model leveraging the radar detection ability and control data link connectivity. To address the limitations of the original dung beetle optimization algorithm in solving such problems, four revolutionary strategies are introduced to improve its performance. The simulation results demonstrate that our proposed task allocation algorithm significantly improves the cross-domain collaboration efficiency and meets the real-time requirements for multi-agent task allocation on various scales. Specifically, our optimization performance was, on average, 32.5% higher compared to classical algorithms like the particle swarm optimization algorithm and the dung beetle optimization algorithm and its improved forms. Overall, our proposed scheme enhances system effectiveness and robustness while providing an innovative and practical solution for complex task allocation problems.
The Contribution of the Brain–Gut Axis to the Human Reward System
Authors: Karaivazoglou Katerina , Aggeletopoulou Ioanna , Triantos Christos
Published: August 2024

The human reward network consists of interconnected brain regions that process stimuli associated with satisfaction and modulate pleasure-seeking behaviors. Impairments in reward processing have been implicated in several medical and psychiatric conditions, and there is a growing interest in disentangling the underlying pathophysiological mechanisms. The brain–gut axis plays a regulatory role in several higher-order neurophysiological pathways, including reward processing. In this context, the aim of the current review was to critically appraise research findings on the contribution of the brain–gut axis to the human reward system. Enteric neuropeptides, which are implicated in the regulation of hunger and satiety, such as ghrelin, PYY3–36, and glucagon-like peptide 1 (GLP-1), have been associated with the processing of food-related, alcohol-related, and other non-food-related rewards, maintaining a delicate balance between the body’s homeostatic and hedonic needs. Furthermore, intestinal microbiota and their metabolites have been linked to differences in the architecture and activation of brain reward areas in obese patients and patients with attention deficit and hyperactivity disorder. Likewise, bariatric surgery reduces hedonic eating by altering the composition of gut microbiota. Although existing findings need further corroboration, they provide valuable information on the pathophysiology of reward-processing impairments and delineate a novel framework for potential therapeutic interventions.
CSA-SA-CRTNN: A Dual-Stream Adaptive Convolutional Cyclic Hybrid Network Combining Attention Mechanisms for EEG Emotion Recognition
Authors: Qian Ren , Xiong Xin , Zhou Jianhua , Yu Hongde , Sha Kaiwen
Published: August 2024

In recent years, EEG-based emotion recognition technology has made progress, but there are still problems of low model efficiency and loss of emotional information, and there is still room for improvement in recognition accuracy. To fully utilize EEG’s emotional information and improve recognition accuracy while reducing computational costs, this paper proposes a Convolutional-Recurrent Hybrid Network with a dual-stream adaptive approach and an attention mechanism (CSA-SA-CRTNN). Firstly, the model utilizes a CSAM module to assign corresponding weights to EEG channels. Then, an adaptive dual-stream convolutional-recurrent network (SA-CRNN and MHSA-CRNN) is applied to extract local spatial-temporal features. After that, the extracted local features are concatenated and fed into a temporal convolutional network with a multi-head self-attention mechanism (MHSA-TCN) to capture global information. Finally, the extracted EEG information is used for emotion classification. We conducted binary and ternary classification experiments on the DEAP dataset, achieving 99.26% and 99.15% accuracy for arousal and valence in binary classification and 97.69% and 98.05% in ternary classification, and on the SEED dataset, we achieved an accuracy of 98.63%, surpassing relevant algorithms. Additionally, the model’s efficiency is significantly higher than other models, achieving better accuracy with lower resource consumption.
The Association between Long Non-Coding RNAs and Alzheimer’s Disease
Authors: Black Carson M. , Braden Anneliesse A. , Nasim Samia , Tripathi Manish , Xiao Jianfeng , Khan Mohammad Moshahid
Published: August 2024

Neurodegeneration occurs naturally as humans age, but the presence of additional pathogenic mechanisms yields harmful and consequential effects on the brain. Alzheimer’s disease (AD), the most common form of dementia, is a composite of such factors. Despite extensive research to identify the exact causes of AD, therapeutic approaches for treating the disease continue to be ineffective, indicating important gaps in our understanding of disease mechanisms. Long non-coding RNAs (lncRNAs) are an endogenous class of regulatory RNA transcripts longer than 200 nucleotides, involved in various regulatory networks, whose dysregulation is evident in several neural and extraneural diseases. LncRNAs are ubiquitously expressed across all tissues with a wide range of functions, including controlling cell differentiation and development, responding to environmental stimuli, and other physiological processes. Several lncRNAs have been identified as potential contributors in worsening neurodegeneration due to altered regulation during abnormal pathological conditions. Within neurological disease, lncRNAs are prime candidates for use as biomarkers and pharmacological targets. Gender-associated lncRNA expression is altered in a gender-dependent manner for AD, suggesting more research needs to be focused on this relationship. Overall, research on lncRNAs and their connection to neurodegenerative disease is growing exponentially, as commercial enterprises are already designing and employing RNA therapeutics. In this review we offer a comprehensive overview of the current state of knowledge on the role of lncRNAs in AD and discuss the potential implications of lncRNA as potential therapeutic targets and diagnostic biomarkers in patients with Alzheimer’s disease.
Validation of an Instrument for Detecting Problematic Internet Use in Adolescents
Authors: Pérez-Wiesner Mateo , Bühler Kora-Mareen , López-Moreno Jose Antonio
Published: August 2024

Problematic internet use (PIU) has drawn attention due to its potentially negative consequences on individuals’ social and personal lives. At present, a consensus on diagnostic criteria for problematic internet use remains elusive, leaving uncertainty regarding its classification as a distinct mental disorder. Extensive research efforts are underway to investigate its underlying causes, risk factors, and correlated adverse consequences. Nonetheless, research on problematic internet use (PIU) frequently faces challenges due to the absence of consistent and dependable evaluation methods, with many existing assessment tools lacking a solid theoretical basis. This study introduces a novel instrument that incorporates positive emotional regulation along with negative emotional regulation, compulsive use, and cognitive preoccupation, all crucial aspects of PIU. The study involved 3054 adolescents from Madrid, Spain, and employed exploratory and confirmatory factor analyses to validate the instrument’s structure. The resulting four-factor model includes Positive Emotional Regulation, Negative Emotional Regulation, Compulsive Use, and Cognitive Preoccupation. The instrument demonstrates good internal consistency and an association with risk factors, as evidenced by correlations with time spent on various internet-related activities. This comprehensive tool enhances our understanding of PIU and its underlying cognitive and emotional processes and provides a valuable resource for assessing and addressing problematic internet use in adolescents.
Feature Selection-Based Method for Scaffolding Assembly Quality Inspection Using Point Cloud Data
Authors: Zhao Jie , Chen Junwei , Liang Yangze , Xu Zhao
Published: August 2024

The stability of scaffolding structures is crucial for quality management in construction. Currently, scaffolding assembly quality monitoring relies on visual inspections performed by designated on-site personnel, which are highly subjective, inaccurate, and inefficient, hindering the advancement of intelligent construction practices. This study proposes an automated method for scaffolding assembly quality inspection using point cloud data and feature selection algorithms. High-precision point cloud data of the scaffolding are captured by a Trimble X7 3D laser scanner. After registration with the forward design model, a 2D slicing comparison method is developed to measure geometric dimensions with an accuracy controlled within 0.1 mm. The collected data are used to build an SVM model for automated assembly quality inspection. To combat the curse of dimensionality associated with high-dimensional data, an optimized genetic algorithm is employed for the dimensionality reduction in the raw sample data, effectively eliminating data redundancy and significantly enhancing convergence speed and classification accuracy of the detection model. Case studies indicate that the proposed method can reduce feature dimensionality by 70% while simultaneously improving classification accuracy by 13.9%. The proposed method enables high-precision automated inspection of scaffolding assembly quality. By identifying the optimal feature subset, the method differentiates the priority of various structural parameters during inspection, providing insights for optimizing the quality inspection process.
Household Income Is Associated with Chronic Pain and High-Impact Chronic Pain among Cancer Survivors: A Cross-Sectional Study Using NHIS Data
Authors: Valvi Nimish , Tamargo Javier A. , Braithwaite Dejana , Fillingim Roger B. , Karanth Shama D.
Published: August 2024

Pain is a prevalent issue among cancer patients, yet its link with socioeconomic status has not been thoroughly examined. This study investigated chronic pain (lasting ≥3 months) and high-impact pain (chronic pain limiting activities) among cancer survivors based on household income relative to the federal poverty level (FPL), using data from the National Health Interview Survey (2019–2020). Of the 4585 participants with a history of solid cancers, 1649 (36.3%) reported chronic pain and 554 (12.6%) reported high-impact chronic pain. After adjustment, participants with incomes < 200% FPL had significantly higher odds of chronic pain (adjusted odds ratio [aOR]: 1.60, 95% CI: 1.25–2.05) and high-impact chronic pain (aOR: 1.73, 95% CI: 1.09–2.74) compared to those with incomes ≥ 400% FPL. Opioid use for chronic pain was most prevalent among those with incomes < 200% FPL (28.3%) compared to those with 200–399% (21.3%) and ≥400% (19.0%). Higher-income participants reported greater use of alternative pain management methods such as yoga (50.5%), chiropractic care (44.8%), and physical therapy (44.3%). This study highlights the association between household income and chronic pain outcomes among cancer survivors, emphasizing the necessity for targeted interventions to mitigate healthcare access disparities and improve pain management for all individuals affected by cancer.
Advancing Pancreatic Cancer Surgical Treatments and Proposal of New Approaches
Authors: Cortiana Viviana , Vallabhaneni Harshitha , Gambill Jade , Nadar Soumiya , Itodo Kennedy , Park Chandler H. , Leyfman Yan
Published: August 2024

Pancreatic cancer is a significant challenge in oncology due to its aggressive nature and complex management, leading to high mortality rates and a dismally low 5-year survival rate. Approximately 85% of cases manifest as adenocarcinoma, while endocrine tumors constitute less than 5%. Borderline resectable and locally advanced pancreatic cancers are particularly difficult to treat due to vascular involvement, which complicates complete resections and increases morbidity. Various therapeutic modalities aim to overcome these challenges and improve patient outcomes. Traditionally, upfront surgery was the standard for resectable tumors, with multimodal chemotherapy being central to treatment. Understanding surgical anatomy is pivotal in enhancing surgical outcomes and patient survival. Resectability challenges are several when seeking to achieve R0 resections, particularly for borderline resectable tumors. Various classification systems—the MD Anderson criteria, the NCCN criteria, the AHPA/SSAT/SSO consensus statement, and the Alliance definition—assess tumor involvement with major blood vessels, with the first of these systems being broadly accepted. Vascular staging integration is also important, with the Ishikawa staging system using preoperative imaging to assess venous involvement. Furthermore, neoadjuvant therapy enhances treatment effectiveness by addressing micro-metastatic disease early, increasing R0 resection chances, and downstaging tumors for optimal surgery. Insights from the Fox Chase Cancer Center’s neoadjuvant treatment approach highlight the importance of a multidisciplinary strategy when advancing therapy and improving patient prognosis. This commentary, inspired by Dr. Sanjay S. Reddy’s Keynote Conference during MedNews week, highlights current advancements and ongoing challenges in the treatment of pancreatic cancer, emphasizing the need for a comprehensive, multidisciplinary approach to improve outcomes.
Comparison of Short-Term Outcomes after Robotic Surgery for Gastric Cancer in Elderly and Younger Patients: A Retrospective Cohort Study
Authors: Fortuna Laura , Staderini Fabio , Coratti Francesco , Cianchi Fabio
Published: August 2024

Robot-assisted surgery has recently been introduced to overcome some drawbacks and technical limitations in performing laparoscopic gastrectomy. The aim of the present study was to evaluate the feasibility and safety of robotic gastrectomy in elderly patients. The study enrolled 143 patients who underwent robotic gastrectomy in a single high-volume centre. All patients were divided into two groups based on age: elderly group ≥ 75 years old (EG; n = 64) and non-elderly group < 75 years old (NEG; n = 79). Comorbidities were significantly more frequent in the EG (95.3%) than in the NEG (81%) (p = 0.011). Similarly, the percentage of ASA 3 patients was significantly higher in the EG than in the NEG (43.8% vs. 24.0%, respectively; p = 0.048). Nevertheless, the incidence of Clavien–Dindo grade III and IV complications did not differ significantly between the two groups (10.9% in the EG and 6.3% in the NEG; p = 0.852). Moreover, operative time, re-operation rate, mean number of harvested lymph nodes, 30-day mortality, and median hospital stay were similar within the two groups. Our study suggests that robotic gastrectomy can be performed safely for elderly patients. In particular, chronological age does not seem to affect either the clinical or oncological short-term outcomes after robotic gastrectomy.
Porous Nanostructured Catalysts Based on Silicates and Their Surface Functionality: Effects of Silica Source and Metal Added in Glycerol Valorization
Authors: Carmo José Vitor C. , Nogueira Joabson , Bertoldo Gabriela M. , Clemente Francisco E. , Oliveira Alcineia C. , Campos Adriana F. , Duarte Gian C. S. , Tehuacanero-Cuapa Samuel , Jiménez-Jiménez José , Rodríguez-Castellón Enrique
Published: August 2024

A series of nanospherical-shaped silicates containing heteroatoms (Al, Zr or Ti) were successfully synthesized using tetraethylorthosilicate (TEOS) or silica colloids as a silicon source. These metallosilicate nanospheres were used as silicon nutrients to obtain silicalite zeolites with micro-mesoporosity and improved textural properties. The results demonstrated that TEOS acted as a suitable silicon source to produce amorphous silicates and a spherical-type zeolite architecture with Zr and Ti heteroatoms included in their framework, with preferable particle size and crystallinity. The surface functionality of the mesostructured nanospheres and zeolite silicates provide active centers for the esterification of glycerol with acetic acid (EG) reaction. The dispersion of Cu entities on the surface of the zeolites achieved high glycerol conversions selectively producing triacetin in comparison with Fe counterparts.
Defective TiO2/MIL-88B(Fe) Photocatalyst for Tetracycline Degradation: Characterization and Augmented Photocatalytic Efficiency
Authors: Xiang Dongsheng , Wang Zhihao , Xu Jingwen , Shen Hongdan , Zhang Xiaodong , Liu Ning
Published: August 2024

Photocatalysts, such as TiO2, are widely used in photoreduction. However, drawbacks like their wide band gap and short carrier lifetime lead to lower efficiencies with their use. Introducing defects and forming heterostructures of TiO2 could extend the carrier’s light-harvesting range from UV to visible light and enhance its lifetime. Herein, an electron-beam irradiation-defected TiO2 was induced in MIL-88B(Fe). The structure of the material was characterized using XRD, FT-IR, TEM, HRTEM, and XPS techniques. Remarkably, TiO2 under 300 kGy electron-beam irradiation performed the best with a series of 0, 100, 300, and 500 kGy irradiation ratios. PL and UV–vis DRS were utilized to measure the material’s optical properties. The introduction of MIL-88B(Fe) expanded the light response range, reduced the optical band gap, and lengthened the carrier lifetime of the defective TiO2 composite photocatalysts, resulting in superior TC photoreduction capabilities of 88B5%300, which degraded 97% of tetracycline (10 mg/L) in water after 120 min.
Multiscale Modeling of Bistability in the Yeast Polarity Circuit
Authors: Hladyshau Siarhei , Guan Kaiyun , Nivedita Nivedita , Errede Beverly , Tsygankov Denis , Elston Timothy C.
Published: August 2024

Cell polarity refers to the asymmetric distribution of proteins and other molecules along a specified axis within a cell. Polarity establishment is the first step in many cellular processes. For example, directed growth or migration requires the formation of a cell front and back. In many cases, polarity occurs in the absence of spatial cues. That is, the cell undergoes symmetry breaking. Understanding the molecular mechanisms that allow cells to break symmetry and polarize requires computational models that span multiple spatial and temporal scales. Here, we apply a multiscale modeling approach to examine the polarity circuit of yeast. In addition to symmetry breaking, experiments revealed two key features of the yeast polarity circuit: bistability and rapid dismantling of the polarity site following a loss of signal. We used modeling based on ordinary differential equations (ODEs) to investigate mechanisms that generate these behaviors. Our analysis revealed that a model involving positive and negative feedback acting on different time scales captured both features. We then extend our ODE model into a coarse-grained reaction–diffusion equation (RDE) model to capture the spatial profiles of polarity factors. After establishing that the coarse-grained RDE model qualitatively captures key features of the polarity circuit, we expand it to more accurately capture the biochemical reactions involved in the system. We convert the expanded model to a particle-based model that resolves individual molecules and captures fluctuations that arise from the stochastic nature of biochemical reactions. Our models assume that negative regulation results from negative feedback. However, experimental observations do not rule out the possibility that negative regulation occurs through an incoherent feedforward loop. Therefore, we conclude by using our RDE model to suggest how negative feedback might be distinguished from incoherent feedforward regulation.
Analysis of Primary Graft Dysfunction (PGD) Risk Factors in Lung Transplantation (LuTx) Patients
Authors: Kubisa Michał Jan , Wojtyś Małgorzata Edyta , Lisowski Piotr , Kordykiewicz Dawid , Piotrowska Maria , Wójcik Janusz , Pieróg Jarosław , Safranow Krzysztof , Grodzki Tomasz , Kubisa Bartosz
Published: August 2024

Background: Primary graft dysfunction (PGD) is a form of acute lung injury (ALI) that occurs within 72 h after lung transplantation (LuTx) and is the most common early complication of the procedure. PGD is diagnosed and graded based on the ratio of the partial pressure of arterial oxygen to the fraction of inspired oxygen and chest X-ray results. PGD grade 3 increases recipient mortality and the chance of chronic lung allograft dysfunction (CLAD). Method: The aim of this retrospective study was to identify new PGD risk factors. The inclusion criteria were met by 59 patients, who all received transplants at the same center between 2010 and 2018. Donor data were taken from records provided by the Polish National Registry of Transplantation and analyzed in three variants: PGD 1–3 vs. PGD 0, PGD 3 vs. PGD 0 and PGD 3 vs. PGD 0–2. Results: A multiple-factor logistic regression model was used to identify decreasing recipient age; higher donor BMI and higher donor central venous pressure (CVP) for the PGD (of the 1–3 grade) risk factor. Conclusions: Longer cold ischemia time (CIT) and higher donor CVP proved to be independent risk factors of PGD 3.
An Innovative Wood Fire-Retardant Coating Based on Biocompatible Nanocellulose Surfactant and Expandable Graphite
Authors: Jurczyková Tereza , Kmeťová Elena , Kačík František , Lexa Martin , Ťoupal Jakub
Published: August 2024

Nanocellulose (CNC) seems to be a promising surfactant, which, together with expandable graphite (EG), forms the essence of an effective natural-based fire-retardant wood coating. In our research, the most suitable composition of the mixture was tested concerning good solubility, dispersion, and consistency. Favorable results were achieved with the formulation composed of a 4% CNC alkaline solution with 80 wt.% of the selected EG. Subsequently, six different types of EG were used to prepare these wood fire-retardant coatings. The effectiveness of treatments was verified using a test with a radiant heat source, where the test samples’ relative weight loss, relative burning rate, and surface temperature during 600 s were evaluated. All prepared formulations can be characterized as more or less equally effective. However, the best results were obtained with the EG of GG 200–100 N, where the mass loss of the sample was 8.10 ± 1.24%. Very good results were also achieved by graphite 25 E + 180 HPH (8.70 ± 0.89%), which is similar to the previous one, even according to the microscopic assessment of the coating as well as the expanded layer. The graphite type 25 K + 180 (8.86 ± 0.65%) shows the expanded layer’s best adhesion, coating uniformity, and ease of application. The results of this work confirmed that the CNC coating itself has significant retardation effects.
High-Temperature Rheological Behavior and Fatigue Performance of Montmorillonite-Modified Asphalt
Authors: Zhang Ming-Xin , Du Wei , Li Yong-Xu , Wang Yan-Min , Wang Xiao-Ning , Liu Xiao-Cun
Published: August 2024

In this research, the effects of modifiers on the high-temperature rheological and fatigue properties of asphalt were investigated by utilizing montmorillonite (MMT) and organic montmorillonite (OMMT) as modifiers for 70# and styrene butadiene styrene (SBS) asphalt, respectively. Temperature scanning tests and linear amplitude scanning (LAS) tests were performed using a dynamic shear rheometer (DSR) to evaluate the viscoelasticity, rutting resistance, and fatigue properties of the asphalt binder. The rheological properties under high-temperature and high-frequency conditions were also characterized by the Black curve and Cole–Cole transformation. Additionally, the elastic properties of the asphalt were examined using nanoindentation (NI). The results of the DSR tests indicate that the incorporation of MMT/OMMT into asphalt enhances its elastic properties and reduces its viscous properties, leading to improved resistance to shear deformation, rutting, and fatigue. Moreover, the NI tests show that the addition of MMT or OMMT improves the elastic properties of the asphalt, while also validating the effectiveness of nanoindentation in assessing the viscoelasticity of asphalt.
Spectral- and Image-Based Metrics for Evaluating Cleaning Tests on Unvarnished Painted Surfaces
Authors: Cutajar Jan Dariusz , Steindal Calin Constantin , Caruso Francesco , Joseph Edith , Frøysaker Tine
Published: August 2024

Despite advances in conservation–restoration treatments, most surface cleaning tests are subjectively evaluated. Scores according to qualitative criteria are employed to assess results, but these can vary by user and context. This paper presents a range of cleaning efficacy and homogeneity evaluation metrics for appraising cleaning trials, which minimise user bias by measuring quantifiable changes in the appearance and characteristic spectral properties of surfaces. The metrics are based on various imaging techniques (optical imaging by photography using visible light (VIS); spectral imaging in the visible-to-near-infrared (VNIR) and shortwave infrared (SWIR) ranges; chemical imaging by Fourier transform infrared (FTIR) spectral mapping in the mid-infrared (MIR) range; and scanning electron microscopy coupled with energy dispersive X-ray spectroscopy (SEM-EDX) element mapping). They are complemented by appearance measurements (glossimetry and colourimetry). As a case study showcasing the low-cost to high-end metrics, agar gel spray cleaning tests on exposed ground and unvarnished oil paint mock-ups are reported. The evaluation metrics indicated that spraying agar (prepared with citric acid in ammonium hydroxide) at a surface-tailored pH was as a safe candidate for efficacious and homogenous soiling removal on water-sensitive oil paint and protein-bound ground. Further research is required to identify a gel-based cleaning system for oil-bound grounds.
Achieving High Accuracy in Android Malware Detection through Genetic Programming Symbolic Classifier
Authors: Anđelić Nikola , Baressi Šegota Sandi
Published: August 2024

The detection of Android malware is of paramount importance for safeguarding users’ personal and financial data from theft and misuse. It plays a critical role in ensuring the security and privacy of sensitive information on mobile devices, thereby preventing unauthorized access and potential damage. Moreover, effective malware detection is essential for maintaining device performance and reliability by mitigating the risks posed by malicious software. This paper introduces a novel approach to Android malware detection, leveraging a publicly available dataset in conjunction with a Genetic Programming Symbolic Classifier (GPSC). The primary objective is to generate symbolic expressions (SEs) that can accurately identify malware with high precision. To address the challenge of imbalanced class distribution within the dataset, various oversampling techniques are employed. Optimal hyperparameter configurations for GPSC are determined through a random hyperparameter values search (RHVS) method developed in this research. The GPSC model is trained using a 10-fold cross-validation (10FCV) technique, producing a set of 10 SEs for each dataset variation. Subsequently, the most effective SEs are integrated into a threshold-based voting ensemble (TBVE) system, which is then evaluated on the original dataset. The proposed methodology achieves a maximum accuracy of 0.956, thereby demonstrating its effectiveness for Android malware detection.
A Deep Learning Approach for Early Detection of Facial Palsy in Video Using Convolutional Neural Networks: A Computational Study
Authors: Arora Anuja , Zaeem Jasir Mohammad , Garg Vibhor , Jayal Ambikesh , Akhtar Zahid
Published: August 2024

Facial palsy causes the face to droop due to sudden weakness in the muscles on one side of the face. Computer-added assistance systems for the automatic recognition of palsy faces present a promising solution to recognizing the paralysis of faces at an early stage. A few research studies have already been performed to handle this research issue using an automatic deep feature extraction by deep learning approach and handcrafted machine learning approach. This empirical research work designed a multi-model facial palsy framework which is a combination of two convolutional models—a multi-task cascaded convolutional network (MTCNN) for face and landmark detection and a hyperparameter tuned and parametric setting convolution neural network model for facial palsy classification. Using the proposed multi-model facial palsy framework, we presented results on a dataset of YouTube videos featuring patients with palsy. The results indicate that the proposed framework can detect facial palsy efficiently. Furthermore, the achieved accuracy, precision, recall, and F1-score values of the proposed framework for facial palsy detection are 97%, 94%, 90%, and 97%, respectively, for the training dataset. For the validation dataset, the accuracy achieved is 95%, precision is 90%, recall is 75.6%, and F-score is 76%. As a result, this framework can easily be used for facial palsy detection.