bluuebunny/crossref_metadata_2025 huggingface dataset:
Impact of Modern Lifestyle on Circadian Health and Its Contribution to Adipogenesis and Cancer Risk
Authors: Dobrovinskaya Oxana , Alamilla Javier , Olivas-Aguirre Miguel
Published: November 2024

Background: Recent research underscores a crucial connection between circadian rhythm disruption and cancer promotion, highlighting an urgent need for attention. Objectives: Explore the molecular mechanisms by which modern lifestyle factors—such as artificial light exposure, shift work, and dietary patterns—affect cortisol/melatonin regulation and cancer risk. Methods: Employing a narrative review approach, we synthesized findings from Scopus, Google Scholar, and PubMed to analyze lifestyle impacts on circadian health, focusing on cortisol and melatonin chronobiology as molecular markers. We included studies that documented quantitative changes in these markers due to modern lifestyle habits, excluding those lacking quantitative data or presenting inconclusive results. Subsequent sections focused solely on articles that quantified the effects of circadian disruption on adipogenesis and tumor microenvironment modifications. Results: This review shows how modern habits lead to molecular changes in cortisol and melatonin, creating adipose microenvironments that support cancer development. These disruptions facilitate immune evasion, chemotherapy resistance, and tumor growth, highlighting the critical roles of cortisol dysregulation and melatonin imbalance. Conclusions: Through the presented findings, we establish a causal link between circadian rhythm dysregulation and the promotion of certain cancer types. By elucidating this relationship, the study emphasizes the importance of addressing lifestyle factors that contribute to circadian misalignment, suggesting that targeted interventions could play a crucial role in mitigating cancer risk and improving overall health outcomes.
The Role of Bladder-Washing Cytology as an Adjunctive Method to Cystoscopy During Follow-Up for Low-Grade TaT1 Non-Muscle-Invasive Bladder Cancer
Authors: Carbonell Enric , Mercader Clàudia , Alfambra Héctor , Narvaez Paulette , Villalba Eric , Pagès Rita , Asiain Ignacio , Costa Meritxell , Franco Agustín , Alcaraz Antonio , Ribal María José , Vilaseca Antoni
Published: November 2024

Background and Objective: The role of urine cytology during follow-up for low-grade (LG) non-muscle-invasive bladder cancer (NMIBC) is not well established, although cytology has low sensitivity in detecting LG recurrences. Our study aims to evaluate the impact of urine cytology as a complementary method to cystoscopy during follow-up for LG NMIBC. Methods: Patients diagnosed with primary LG TaT1 bladder cancer (BC) between 2010 and 2020 were included. Patients were stratified according to the EAU NMIBC scoring model. Urine cytology was performed during follow-up cystoscopy. The outcomes of the study were BC recurrence and upgrading to high-grade (HG). Cytology utility was established by assessing whether its result led to management change. Results: We included 337 patients with LG TaT1 BC. EAU risk group distribution was low in 262 (77.7%), intermediate in 57 (16.9%), and high-risk in 18 (5.3%) cases. With a median follow-up of 5 years, 166 (49.3%) patients experienced recurrence. Cystoscopy was positive in 154 (92.8%) and suspicious in 12 (7.2%) cases. Urine cytology was positive in 33 (19.9%) cases but only changed management in 3 (0.89%), all with suspicious cystoscopy. Positive cytology at first recurrence was associated with higher risk of upgrading during follow-up (HR 2.781, p = 0.006) and lower upgrading-free survival (p = 0.001). Conclusions: The role of urine cytology to detect first recurrences during follow-up for primary LG TaT1 NMIBC might be limited to patients with non-conclusive lesions in the cystoscopy. A positive cytology at first recurrence is associated with a higher risk of upgrading to HG BC during follow-up.
Analysis of Solid Formulates Using UV-Visible Diffused Reflectance Spectroscopy with Multivariate Data Processing Based on Net Analyte Signal and Standard Additions Method
Authors: Kassouf Nicholas , Zappi Alessandro , Monticelli Michela , Melucci Dora
Published: November 2024

Quality control in pharmaceutical manufacturing necessitates rigorous testing and approval, adhering to Current Good Manufacturing Practices before commercialization. The production of solid drugs presents significant industrial challenges regarding uniformity, homogeneity, and consistency. Traditional quality guidelines rely on classical analytical methods such as liquid chromatography coupled with mass spectrometry. However, the emergence of Process Analytical Technology introduced non-destructive, rapid, and cost-effective methods like UV-Visible Diffuse Reflectance Spectroscopy. The present study aimed to develop a chemometric method for quantifying Active Pharmaceutical Ingredients (APIs) in Neo Nisidine®, a solid mixture drug, using spectrophotometric data. The Net Analyte Signal (NAS) method, combined with standard additions, allowed the creation of a pseudo-univariate standard addition model, overcoming some challenges in solid-phase analysis. Successful quantifications of APIs in ideal laboratory samples and real pharmaceutical tablets were obtained. NAS-based chemometric models showed high precision and reliability, whose results were validated by comparisons with HPLC ones. The study revealed that solid-phase spectrophotometric analyses can be considered a valid alternative to API analyses. Solid-phase analysis offers non-destructive, cost-effective, and environmentally friendly benefits, enabling its integration into pharmaceutical production to improve quality control.
Assessing Data Fusion in Sensory Devices for Enhanced Prostate Cancer Detection Accuracy
Authors: Gómez Jeniffer Katerine Carrillo , Vásquez Carlos Alberto Cuastumal , Acevedo Cristhian Manuel Durán , Llecha Jesús Brezmes
Published: November 2024

The combination of an electronic nose and an electronic tongue represents a significant advance in the pursuit of effective detection methods for prostate cancer, a widespread form of cancer affecting men across the globe. These cutting-edge devices, collectively called “E-Senses”, use data fusion to identify distinct chemical compounds in exhaled breath and urine samples, potentially improving existing diagnostic techniques. This study combined the information from two sensory perception devices to detect prostate cancer in biological samples (breath and urine). To achieve this, data from patients diagnosed with the disease and from control individuals were collected using a gas sensor array and chemical electrodes. The signals were subjected to data preprocessing algorithms to prepare them for analysis. Following this, the datasets for each device were individually analyzed and subsequently merged to enhance the classification results. The data fusion was assessed and it successfully improved the accuracy of detecting prostate-related conditions and distinguishing healthy patients, achieving the highest success rate possible (100%) in classification through machine learning methods, outperforming the results obtained from individual electronic devices.
Robust Goal Programming as a Novelty Asset Liability Management Modeling in Non-Financial Companies: A Systematic Literature Review
Authors: Wijayanti Hagni , Supian Sudradjat , Chaerani Diah , Shuib Adibah
Published: November 2024

In addressing asset-liability management (ALM) problems, goal programming (GP) has been widely applied to integrate multiple objectives. However, it is inadequate in handling data changes in ALM caused by interest rate fluctuations. Therefore, a more robust and improved ALM optimization method is needed to manage fluctuations in financial ratios in ALM. This study introduces a novel approach by combining a systematic literature review (SLR) with the preference reporting items for systematic reviews and meta-analysis (PRISMA) method and bibliometric analysis to investigate the application of robust goal programming (RGP) models in ALM. The methodology involved planning, search and selection, analysis, and result interpretation as part of the SLR process. Using PRISMA, seven relevant publications were identified. The results of this SLR present a new strategy to combine goal programming and robust optimization to enhance ALM. Model development steps include constructing weighted goal programming (WGP) or lexicographic goal programming (LGP) models, using factor analysis for financial ratios, applying the best-worst method or simple additive weighting (SAW) for prioritization, and modeling financial ratio uncertainty with robust counterparts. This research provides a foundation for further studies and offers guidance to non-financial companies on adopting RGP for strategic ALM decisions and optimizing ALM under uncertainty.
Visibility Graph Investigation of the Shallow Seismicity of Lai Chau Area (Vietnam)
Authors: Telesca Luciano , Thai Anh Tuan , Cao Dinh Trong , Dang Thanh Hai
Published: November 2024

In this study, the topological properties of the shallow seismicity occurring in the area around the Lai Chau hydropower plant (Vietnam) are investigated by using visibility graph (VG) analysis, a well-known method to convert time series into networks or graphs. The relationship between the seismicity and reservoir water level was analyzed using Interlayer Mutual Information (IMI) and the Frobenius norm, both applied to the corresponding VG networks. IMI was used to assess the correlation between the two variables, while the Frobenius norm was employed to estimate the time delay between them. The total seismicity, which resulted in an M≥0.8 with a b-value of 0.86, is characterized by a k−M slope of ≈9.1. Analyzing the variation of the seismological and topological parameters of the seismicity relative to the distance from the center of the Lai Chau reservoir revealed the following features: (1) the b-value fluctuates around a mean value of 1.21 at distances of up to 10–11 km, while, for distances larger than 25–30 km, it tends to the value of 0.86; (2) the maximum IMI between the monthly number of earthquakes and the monthly mean water level occurs at a distance of 9–11 km, showing a distance evolution similar to that of the b-value; (3) at these distances from the center of the reservoir, the time lag between the earthquake monthly counts and the monthly water level mean is 9–10 months; (4) the relationship between the b-value and the k−M slope suggests that the k−M slope depends on the number of earthquakes within a 22 km radius from the center of the dam. Our study’s findings offer new insights into the complex dynamics of seismicity occurring around reservoirs.
Synergistic Integration of Local and Global Information for Critical Edge Identification
Authors: Zhao Na , Luo Ting , Wang Hao , Yang Shuang-Ping , Xiong Ni-Fei , Jing Ming , Wang Jian
Published: November 2024

Identifying critical edges in complex networks is a fundamental challenge in the study of complex networks. Traditional approaches tend to rely solely on either global information or local information. However, this dependence on a single information source fails to capture the multi-layered complexity of critical edges, often resulting in incomplete or inaccurate identification. Therefore, it is essential to develop a method that integrates multiple sources of information to enhance critical edge identification and provide a deeper understanding and optimization of the structure and function of complex networks. In this paper, we introduce a Global–Local Hybrid Centrality method which integrates a second-order neighborhood index, a first-order neighborhood index, and an edge betweenness index, thus combining both local and global perspectives. We further employ the edge percolation process to evaluate the significance of edges in maintaining network connectivity. Experimental results on various real-world complex network datasets demonstrate that the proposed method significantly improves the accuracy of critical edge identification, providing theoretical and methodological support for the analysis and optimization of complex networks.
An Offset Parameter Optimization Algorithm for Denoising in Photon Counting Lidar
Authors: Tan Zhuangbin , Zhang Yan , Sun Ziwen , Chen Jintao , Huang Kun , Qi Yuanjie , Ma Feifan , Xu Zheyu , Zhang Renli , Jiao Zhongxing
Published: November 2024

In the case of a weak signal from a photon counting lidar and strong noise from the solar background, the signal is completely submerged by noise, potentially resulting in the appearance of multiple peaks in the denoising algorithm of photon counting entropy. Consequently, a clear distinction between the signal and noise may become challenging, leading to significant fluctuation in the ranging error. To solve this problem, this paper proposes an improved offset parameter optimization algorithm under the framework of photon counting entropy, aiming to effectively eliminate peak interference caused by noise and enhancing ranging accuracy. The algorithm includes two aspects. First, we introduce the solar irradiance prediction of an MLP network and least squares linear conversion to accurately estimate the noise rate of the solar background noise. Then, we propose the offset parameter optimization method to effectively mitigate the interference caused by noise. In simulation and experimental analyses, the ranging error of our proposed method is within 5 and 30 cm, respectively. Compared with the denoising method of photon counting entropy, the average ranging error is increased by 81.99% and 73.76%. Furthermore, compared to other anti-noise methods, it exhibits superior ranging capability.
A Construction of Optimal One-Coincidence Frequency-Hopping Sequences via Generalized Cyclotomy
Authors: Shao Minfeng , Miao Ying
Published: November 2024

Frequency-hopping sequences (FHSs) with low Hamming correlation are essential for synchronization and multiple-access communication systems. In this paper, we propose a novel construction of FHSs using generalized cyclotomy. Our results reveal that the constructed FHSs exhibit a one-coincidence property, meaning that the smallest correlation between different FHSs, aside from the trivial case, is minimized. Additionally, the new sets of FHSs achieve an optimal size in relation to a known theoretical bound.
Study on Coal Seam Roof Failure Based on Optical Fiber Acoustic Sensing and the Parallel Electrical Method
Authors: She Zilong , Wang Bo , Zhang Yan , Zeng Linfeng , Xie Liujun , Shen Sihongren
Published: November 2024

As China enters the stage of deep coal mining, the accidents caused by roof failure pose increasingly serious threats. Current research on roof failure zones often use single methods, but single geophysical data may result in multisolution issues during interpretation. This paper employed similar simulation experiments, exploring the strain failure characteristics and the changes in apparent resistivity caused by stress variations, taking the 11-3106 working face of a mining area as the research object. Through optical fiber strain and apparent resistivity, the locations and degrees of fracture in postmining rock strata were identified. The feasibility of using distributed optical fiber sensing and the parallel electrical method for qualitative and quantitative analysis of mining-induced fractures was verified. The results showed that optical fiber strain increased significantly at the location of rock fracture, with apparent resistivity anomalies rising correspondingly. The peak strain region corresponded well with the region of apparent resistivity anomalies. In a similar simulation with a geometric ratio of 1:100, the height of the caving zone was measured to be 31.65 cm, with a caving-to-mining ratio of 6.33. In the field working face, the caving zone height was 29.47 m, with a caving-to-mining ratio of 6.01, consistent with the actual conditions of the 11-3106 working face.
Leading Edge Erosion Classification in Offshore Wind Turbines Using Feature Extraction and Classical Machine Learning
Authors: Best Oscar , Khan Asiya , Sharma Sanjay , Collins Keri , Gianni Mario
Published: November 2024

Leading edge (LE) erosion is a type of damage that inhibits the aerodynamic performance of a wind turbine, resulting in high operation and maintenance (O&M) costs. This paper makes use of a small dataset consisting of 50 images of LE erosion and healthy blades for feature extraction and the training of four types of classifiers, namely, support vector machine (SVM), random forest, K-nearest neighbour (KNN), and multi-layer perceptron (MLP). Six feature extraction methods were used with these classifiers to train 24 models. The dataset has also been used to train a convolutional neural network (CNN) model developed using Keras. The purpose of this work is to determine whether classical machine learning (ML) classifiers trained with extracted features can produce higher-accuracy results, train faster, and classify faster than deep learning (DL) models for the application of LE damage detection of wind turbine blades. The oriented fast and rotated brief (ORB)-trained SVM achieved an accuracy of 90% ± 0.01, took 80.4 s to train, and achieved inference speeds of 63 frames per second (FPS), compared to the CNN model, which achieved an accuracy of 79.4% ± 2.07, took 4667.4 s to train, and achieved an inference speed of 1.3 FPS. These results suggest that classical ML models can be more accurate and efficient than DL models if the appropriate feature extraction method is used.
A Neuroadaptive Position-Sensorless Robust Control for Permanent Magnet Synchronous Motor Drive System with Uncertain Disturbance
Authors: Aguilar-Mejia Omar , Valderrabano-Gonzalez Antonio , Hernández-Romero Norberto , Seck-Tuoh-Mora Juan Carlos , Hernandez-Ochoa Julio Cesar , Minor-Popocatl Hertwin
Published: November 2024

The Permanent Magnet Synchronous Motor (PMSM) drive system is extensively utilized in high-precision positioning applications that demand superior dynamic performance across various operating conditions. Given the non-linear characteristics of the PMSM, a neuroadaptive sensorless controller based on B-spline neural networks is proposed to determine the control signals necessary for achieving the desired performance. The proposed control technique considers the system’s non-linearities and can be adapted to varying operating conditions, all while maintaining a low computational cost suitable for real-time operation. The introduced neuroadaptive controller is evaluated under conditions of uncertainty, and its performance is compared to that of a conventional PI controller optimized using the Whale Optimization Algorithm (WOA). The results demonstrate the viability of the proposed approach.
Using Time-Series Databases for Energy Data Infrastructures
Authors: Hadjichristofi Christos , Diochnos Spyridon , Andresakis Kyriakos , Vescoukis Vassilios
Published: November 2024

The management of energy market data, such as load, production, forecasts, and prices, is critical for energy market participants, who develop in-house energy data infrastructure services to aggregate data from many sources to support their business operations. Energy data management frequently involves time sensitive operations, including rapid data ingestion, real-time querying, filling in gaps from missing or delayed data, and updating large volumes of timestamped and loosely structured data, all of which demand high processing power. Traditional relational database management systems (RDBMSs) often struggle with these operations, whereas time series databases (TSDBs) appear to be a more efficient solution, providing enhanced scalability, reliability, real-time data availability and superior performance. This paper examines the advantages of TSDBs over RDBMS for energy data management, demonstrating that TSDBs can either replace or complement RDBMSs. We present quantitative improvements in digestion, integration, architecture, and performance, demonstrating that operations such as importing and querying time-series energy data, along with the overall system’s efficiency, can be significantly improved, achieving up to 100 times faster operations compared to relational databases, all without requiring extensive modifications to the existing information system’s architecture.
Biomass-Driven Polygeneration Coupled to Power-to-X: An Energy and Economic Comparison Between On-Site Electric Vehicle Charging and Hydrogen Production
Authors: Fraia Simona Di , Figaj Rafał , Shah Musannif , Vanoli Laura
Published: November 2024

The power-to-X strategy for passenger car applications offers a viable solution for using the surplus electrical power from renewable energy sources instead of exporting it to the grid. The innovative system proposed in this study allocates surplus electrical power from a building-integrated biomass-based Combined Cooling Heating and Power (CCHP) system to on-site applications and evaluates the energetic and economic benefits. The system comprises two key components: a 50 kW electric vehicle (EV) charging station for EVs and a 50 kW alkaline electrolyzer system for on-site hydrogen production, which is later dispensed to fuel cell electric vehicles (FCEVs). The primary goal is to decrease the surplus of electricity exports while simultaneously encouraging sustainable transportation. The system’s economic viability is assessed through two scenarios of fuel (e.g., biomass) supply costs (e.g., with and without fuel market costs) and compared to the conventional approach of exporting the excess power. The key findings of this work include a substantial reduction in surplus electricity exports, with only 3.7% allocated for EV charging and 31.5% for hydrogen production. The simple payback period (SPB) is notably reduced, enhancing economic viability. Sensitivity analysis identifies the optimal hydrogen system, featuring a 120 kW electrolyzer and a 37 kg daily hydrogen demand. The results underscore the importance of prioritizing self-consumed energy over exports to the national grid, thereby supporting integrated renewable energy solutions that enhance local energy utilization and promote sustainable transportation initiatives.
Use of International Adaptive Thermal Comfort Models as a Strategy for Adjusting the Museum Environments of the Mudejar Pavilion, Seville
Authors: Gallego-Maya Inmaculada , Rubio-Bellido Carlos
Published: November 2024

Adaptive thermal comfort models are increasingly utilized to condition thermal environments by considering occupants’ adaptability. The most widely recognized models internationally are the ASHRAE 55-2020 and UNE-EN 16798-1:2020 standards, primarily applied in residential and office buildings. However, their use in heritage buildings such as museums has been very limited. These environments present unique challenges that complicate the implementation of conventional energy-saving methodologies due to restrictions on interventions in the buildings to safeguard their historical value. Therefore, it is essential to develop research that evaluates the applicability of these standards as an alternative strategy to the specific conditions of museums in heritage buildings in Spain. This study aims to explore the application of the international adaptive thermal comfort models of the ASHRAE 55-2020 and UNE-EN 16798-1:2020 standards in parallel with the preventive conservation conditions of the collections established by the UNE-EN 15757:2011 standard. The aim is to evaluate new strategies for environmental reconditioning to improve visitor comfort while ensuring the conservation of the collections in the exhibition spaces of the Museum of Popular Arts and Customs, housed in a 1914 building known as the Mudejar Pavilion in Seville. Field monitoring was conducted to assess the thermal environment and visitor comfort. The results revealed that the monitored environmental conditions of the exhibition spaces of the Mudejar Pavilion, in accordance with ASHRAE 55-2020 standards, showed high effectiveness in ensuring thermal comfort for visitors, achieving comfort 99% of the time annually, with an acceptability of 80%. High suitability for the conservation of collections was also observed, with optimal conditions achieved 87% of the time. However, under the standards of UNE-EN 15757:2011 for a Category III expectation level, comfort was only achieved 70% of the year, while stability of conservation conditions was achieved 88% of the time. Finally, the implementation of specific correction guidelines is proposed to achieve the acceptability limits of greater energy efficiency.
Recent Developments on the Incentives for Users’ to Participate in Vehicle-to-Grid Services
Authors: Astolfi Davide , Vasile Antony , Iuliano Silvia , Pasetti Marco
Published: November 2024

The transportation is the sector of human activities which contributes the most to greenhouse gas emissions by far [...]
Biomethane Production and Methanogenic Microbiota Restoration After a pH Failure in an Anaerobic Sequencing Batch Reactor (A-SBR) Treating Tequila Vinasse
Authors: Serrano-Meza Adriana , Moreno-Andrade Iván , Estrada-Arriaga Edson B. , Díaz-Barajas Sergio A. , García-Sánchez Liliana , Garzón-Zúñiga Marco A.
Published: November 2024

Precise control of operational parameters in anaerobic digestion reactors is crucial to avoid imbalances that could affect biomethane production and alterations in the microbiota. Restoring the methanogenic microbiota after a failure is essential for recovering methane production, yet no published strategies exist for this recovery. In this study, we restored the methanogenic microbiota in an anaerobic SBR reactor that operates with both biofilm and suspended biomass simultaneously, aiming to treat tequila vinasses. Four strategies were evaluated for restoring the methanogenic microbiota: reducing the initial vinasse concentration, increasing the reaction time (RT), adjusting the carbon/nitrogen (C/N) ratio, and progressively increasing the initial vinasse concentration. Among these, adjusting the C/N ratio emerged as a critical parameter for restoring organic matter removal efficiency and reestablishing methanogenic microbiota. The operational conditions under which the methanogenic activity and microbiota were restored were as follows: Operating the A-SBR with an initial vinasse concentration of 60%, an RT of 168 h, a pH of 6.9 ± 0.2, a temperature of 35 ± 2 °C, and a C/N ratio adjusted to 100/1.9 resulted in stable COD removal efficiency of 93 ± 3% over a year and a high percentage of methanogenic microorganisms in both the suspended microbiota (69%) and biofilm (52%). The normalized methane production (0.332 NL CH4/g CODr) approached the theoretical maximum value (0.35 L CH4/g CODr) after restoring the population and methanogenic activity within the reactor.
Bio-Composite Nanogels Based on Chitosan and Hyaluronic Acid for the Treatment of Lung Infections
Authors: Della Sala Francesca , Barretta Marco , di Gennaro Mario , Paradiso Rubina , Borriello Giorgia , Borzacchiello Assunta
Published: November 2024

Pathogen infections constitute a serious problem in the field of lung diseases, especially in severe conditions such as chronic obstructive pulmonary disease (COPD) and acute respiratory distress syndrome (ARDS). Exacerbations of COPD and ARDS can be significantly influenced by bacterial infections from Pseudomonas aeruginosa and Staphylococcus aureus, which can hasten the decline of lung function. Moreover, the abuse of high-dose antibiotics used to treat obstinate infections is contributing to the growing issue of multidrug resistance (MDR) by microorganisms. Currently, new therapeutic strategies capable of surprising and fighting pathogens with new modalities are missing. In this framework, bio-composite nanogels (NGs) based on natural polymers with intrinsic antimicrobial properties such as chitosan (CS) and hyaluronic acid (HA) have been developed for the treatment of lung infections. The DLS and TEM results showed that NGs have a spherical shape with a size smaller than 100 nm, making it possible for them to potentially reach the lung site and evade the clearance of alveolar macrophages. FTIR spectra demonstrated that only electrostatic interactions, not chemical reactions, occur between NG precursors. Rheological analysis highlighted NGs’ injectability and mucoadhesive capacity. Moreover, an MTT assay on human lung fibroblast cells for biocompatibility evaluation showed good viability up to 48 h. Finally, an antimicrobial test on P. aeruginosa and S. aureus showed an increase in antimicrobial activity as the NG concentration increases, with a reduction in bacterial growth of around 60% at 375 μg/mL.
Autonomous Genealogies and Indigenous Reclamations: Decolonial (and Anti-Colonial) Interventions to Genealogy
Authors: Lopesi Lana , MacDonald Liana
Published: November 2024

Indigenous communities the world over have their own concepts of genealogy, many of which consider the living and non-living beings that we share time and space with, spanning the earth beneath us to the heavens above [...]
Determining Optimal Mutation Induction of Philodendron billietiae Using Gamma Radiation and In Vitro Tissue Culture Techniques
Authors: Khamrit Rattana , Jongrungklang Nakorn
Published: November 2024

The Philodendron billietiae is a popular ornamental plant, with mutated varieties in high demand and commanding premium prices. This research aims to identify the optimal medium for propagating Philodendron billietiae and to use gamma radiation to induce mutations. Shoot tips of Philodendron billietiae were cultured on Murashige and Skoog (MS) medium supplemented with various concentrations of 6-benzyladenine (BA), both alone and in combination with naphthalene acetic acid (NAA), to induce shoot formation. Different concentrations of NAA were then tested for root induction. Additionally, mutation induction was investigated using gamma radiation from cesium-137 as the primary radioactive source, with doses of 0, 10, 20, 30, 40, and 50 Gray. MS medium supplemented with 1.5 mg L−1 BA achieved the highest shoot induction, resulting in more shoots and leaves per shoot. The optimal medium for root induction was MS medium supplemented with 0.5 mg L−1 NAA. In the mutation induction experiment, increasing radiation doses resulted in decreased survival rates, fewer new shoots, and reduced leaf width and length. Gamma radiation at doses between 20 and 40 Gray induced morphological changes in the leaves of Philodendron billietiae. These findings provide valuable guidelines for the genetic improvement of Philodendron billietiae to enhance its commercial value.
Characteristics of Children with an Undesirable Motor Competence Development During the Transition from Early to Middle Childhood: Results of a 2-Year Longitudinal Study
Authors: Koolwijk Pim , de Jonge Ester , Mombarg Remo , Remmers Teun , Van Kann Dave , van Aart Ingrid , Savelsbergh Geert , de Vries Sanne
Published: November 2024

Objective: Motor competence development from early to middle childhood is accompanied by great variance. This course can be influenced by many factors in the ecosystem. The objective of this study was to examine which individual characteristics are associated with an undesirable motor competence development during the transition from early to middle childhood. Methods: A longitudinal study was conducted between February 2020 and May 2022. Actual and perceived motor competence and the potential determinants physical activity enjoyment, weight status, and organized sports participation of children (49% boys) aged 4–6 years old at T0 (N = 721) were measured at two points in time, separated by a two-year interval. Associations between potential determinants and AMC, including interactions with time, were analyzed using linear mixed-effect regression models with continuous motor quotient scores as outcome variables. Results: Overweight, obesity, and lack of organized sports participation were associated with lower motor quotient scores over time. Multivariate analyses showed that associations of weight status (overweight and obesity) and sports participation with motor quotient scores remained significant after adjustment for variations in perceived motor competence and physical activity enjoyment. Conclusions: Excessive body weight and lack of sports participation from early childhood are associated with an increased risk of an undesirable motor competence development over time.
Self-Reported Difficulty with and Assistance Needed by People with Spinal Cord Injury to Prepare Meals at Home
Authors: Froehlich-Grobe Katherine
Published: November 2024

Individuals with spinal cord injury (SCI) experience an increased risk for obesity and cardiometabolic disease. Recommendations to prevent and treat obesity for those with SCI follow those of the US Department of Agriculture to adopt a healthy eating pattern that includes eating a variety of fruits, vegetables, grains, dairy, and protein, plus limiting added sugars, saturated fats, and sodium. Yet, people with SCI eat too many calories, fat, and carbohydrates and too few fruits, vegetables, and whole grains. The study is based on secondary analyses of SCI participants (n = 122) who enrolled in a weight loss study to determine how SCI may impact their ability to prepare food at home. We hypothesize those with higher-level spinal injuries (specifically, those with cervical versus those with thoracic or lumbar/sacral injuries) experience significantly greater difficulty and are more likely to rely on others’ assistance to perform meal preparation tasks. Physiologic (weight, BMI, blood pressure, hemoglobin A1c) and self-reported data (demographic plus responses to the Life Habits Short Survey and meal prep items) were collected at baseline and qualitative data were obtained from a subsample after the intervention during phone interviews. Participants’ average age was 50 ± 14.7 years old, they lived with SCI for an average of 13.0 ± 13.1 years, and their average BMI was 32.0 ± 6.5. Participants were predominantly white (76.1%) men (54.1%) who had some college education (76.3%), though only 28.8% worked. A substantial proportion of respondents (30% to 68%) reported difficulty across the 13 tasks related to purchasing and preparing meals, with a proxy reported as the most common assistance type used across all tasks (17% to 42%). Forty-nine percent reported difficulty preparing simple meals, with 29% reporting a proxy does the task. More than half reported difficulty using the oven and stove, though between 60% to 70% reported no difficulty using other kitchen appliances (e.g., coffee machine, food processor, can opener), the refrigerator, or microwave. There was a significant difference in kitchen function by injury level. Those living with cervical-level injuries had significantly greater limitations than those with thoracic-level injuries. Spouses, other family members, and caregivers were most likely to serve as proxies and these individuals exerted both positive and negative influences on respondents’ dietary intake, based on qualitative data obtained during interviews. The results suggest that many people living with SCI experience functional and environmental barriers that impact their ability to prepare food and use kitchen appliances. Future research should examine how SCI-related functional limitations, transportation access, accessibility of the kitchen, ability to use appliances, availability of financial resources, and assistance by others to prepare foods impact people’s ability to follow a healthy eating pattern.
Supraspinatus Muscle Regeneration Following Rotator Cuff Tear: A Study of the Biomarkers Pax7, MyoD, and Myogenin
Authors: Hejbøl Eva Kildall , Andkjær Stephanie Wej , Dybdal Julie , Klindt Marie , Möller Sören , Lambertsen Kate Lykke , Schrøder Henrik Daa , Frich Lars Henrik
Published: November 2024

The success of rotator cuff tendon repair relies on both tendon healing and muscle recovery. The objective of this descriptive study was to investigate the regenerative potential of the supraspinatus muscle in rotator cuff tear conditions by quantifying the expression of Pax7, MyoD, and myogenin, basic factors that regulate myogenesis. Muscle biopsies were collected from thirty-three patients aged 34 to 73 years who underwent surgery for a rotator cuff tear affecting the supraspinatus muscle. Among these patients, twenty-seven percent were women, and the age of the lesions ranged from 2 to 72 months post-initial trauma. Biopsies were harvested from the supraspinatus muscle at the end closest to the tendon, and control biopsies were harvested from the ipsilateral deltoid muscle. The densities of immunohistochemically stained Pax7+, MyoD+, and myogenin+ nuclei/mm2 were used to estimate the myogenic potential of the muscle. Adjustments were made for patient age and lesion age. We found increased density of MyoD+ and myogenin+ cells in supraspinatus muscles compared to deltoid muscles (p < 0.001 and p = 0.003, respectively). Regression analyses that combined the density of positive nuclei with patient age showed a continuous increase in Pax7 with age but also a reduction of MyoD and myogenin in older patients. When combined with lesion age, there was a decline in the density of all myogenic markers after an initial rise. Pax7 density continued to be higher in supraspinatus compared to the deltoid muscle, but the density of MyoD and myogenin terminally dropped to a density lower than in the deltoid. Our findings suggest that the supraspinatus muscle in tear conditions showed signs of initial activation of muscle regeneration. When compared to the unaffected deltoid muscle, an apparent reduction in capacity to progress to full muscle fiber maturity was also demonstrated. This pattern of inhibited myogenesis seemed to increase with both patient age and lesion age. Our results on muscle regenerative capacity indicate that younger patients with rotator cuff tears have better chances of muscle recovery and may benefit from early surgical reconstruction.
Correction: Guarnera et al. KMT2A Rearrangements in Leukemias: Molecular Aspects and Therapeutic Perspectives. Int. J. Mol. Sci. 2024, 25, 9023
Authors: Guarnera Luca , D’Addona Matteo , Bravo-Perez Carlos , Visconte Valeria
Published: November 2024

There was an error in the original publication [...]
DeepDualEnhancer: A Dual-Feature Input DNABert Based Deep Learning Method for Enhancer Recognition
Authors: Song Tao , Song Haonan , Pan Zhiyi , Gao Yuan , Dai Huanhuan , Wang Xun
Published: November 2024

Enhancers are cis-regulatory DNA sequences that are widely distributed throughout the genome. They can precisely regulate the expression of target genes. Since the features of enhancer segments are difficult to detect, we propose DeepDualEnhancer, a DNABert-based method using a multi-scale convolutional neural network, BiLSTM, for enhancer identification. We first designed the DeepDualEnhancer method based only on the DNA sequence input. It mainly consists of a multi-scale Convolutional Neural Network, and BiLSTM to extract features by DNABert and embedding, respectively. Meanwhile, we collected new datasets from the enhancer–promoter interaction field and designed the method DeepDualEnhancer-genomic for inputting DNA sequences and genomic signals, which consists of the transformer sequence attention. Extensive comparisons of our method with 20 other excellent methods through 5-fold cross validation, ablation experiments, and an independent test demonstrated that DeepDualEnhancer achieves the best performance. It is also found that the inclusion of genomic signals helps the enhancer recognition task to be performed better.
Melatonin Maintains Postharvest Quality in Fresh Gastrodia elata Tuber by Regulating Antioxidant Ability and Phenylpropanoid and Energy Metabolism During Storage
Authors: Dong Boyu , Kuang Chengyue , Chen Yulong , Da Fangfang , Yao Qiuping , Zhu Dequan , Ding Xiaochun
Published: November 2024

Melatonin treatment has been reported to effectively preserve and improve the postharvest quality of fruits and vegetables during storage. This research focused on examining the significance of melatonin on maintaining the quality of fresh Gastrodia elata tubers throughout the storage period. The findings demonstrated that melatonin application effectively reduced the deterioration rate and inhibited the rise in respiratory rate, malondialdehyde content, and weight loss, while slowing down the decline in soluble solid content. Melatonin treatment led to a decrease in hydrogen peroxide production and a rise in non-enzymatic antioxidant concentrations, including ascorbic acid. Furthermore, it boosted both the activity and expression of indispensable antioxidant enzymes, like superoxide dismutase, catalase, and ascorbate peroxidase. Additionally, melatonin treatment promoted the accumulation of total phenols, flavonoids, and lignin in fresh G. elata, while enhancing both the activity and expression of critical enzymes in the phenylpropanoid pathway, including phenylalanine ammonia-lyase, cinnamate-4-hydroxylase, and 4-coumarate-CoA ligase. Moreover, melatonin treatment boosted the activity and expression of energy-associated enzymes including H+-ATPase, succinate dehydrogenase, Ca2+-ATPase, and cytochrome C oxidase, contributing to the improvement of energy levels in fresh G. elata. In summary, melatonin enhances the antioxidant potential and reduces oxidative damage in fresh G. elata by activating reactive oxygen species, phenylpropanoid metabolism, and energy metabolism, thereby maintaining its postharvest quality.
Identifying the HIV-Resistance-Related Factors and Regulatory Network via Multi-Omics Analyses
Authors: Long Xueyan , Liu Gexin , Liu Xinyi , Zhang Chunlin , Shi Lei , Zhu Zhenglin
Published: November 2024

For research on HIV/AIDS, it is important to elucidate the complex viral–host interaction, host dependency factors (HDFs), and restriction factors. However, the regulatory network of HIV-resistance-related factors remains not well understood. Therefore, we integrated four publicly available HIV-related transcriptome datasets, along with three datasets on HIV-infection-related DNA methylation, miRNA, and ChIP-seq, to predict the factors influencing HIV resistance and infection. Our approach involved differential analysis, functional annotation, and protein–protein interaction network analysis. Through comprehensive analyses, we identified 25 potential HIV-resistance-related genes (including shared EGF) and 24 HIV-infection-related hub genes (including shared JUN). Additionally, we pinpointed five key differentially methylated genes, five crucial differentially expressed microRNAs, and five significant pathways associated with HIV resistance. We mapped the potential regulatory pathways involving these HIV-resistance-related factors. Among the predicted factors, RHOA, RAD51, GATA1, IRF4, and CXCL8 have been validated as HDFs or restriction factors. The identified factors, such as JUN, EGF, and PLEK, are potential HDFs or restriction factors. This study uncovers the gene signatures and regulatory networks associated with HIV-1 resistance, suggesting potential targets for the development of new therapies against HIV/AIDS.
Structural Features of DNA in tRNA Genes and Their Upstream Sequences
Authors: Savina Ekaterina A. , Shumilina Tatiana G. , Porolo Viktoria A. , Lebedev Georgy S. , Orlov Yury L. , Anashkina Anastasia A. , Il’icheva Irina A.
Published: November 2024

RNA polymerase III (Pol III) transcribes tRNA genes using type II promoters. The internal control regions contain a Box A and a Box B, which are recognized by TFIIIC. The 5′-flanking regions of tRNA genes clearly play a role in the regulation of transcription, but consensus sequences in it have been found only in some plants and S. pombe; although, the TATA binding protein (TBP) is a component of the TFIIIB complex in all eukaryotes. Archaea utilize an ortholog of the TBP. The goal of this work is the detection of the positions of intragenic and extragenic promoters of Pol III, which regulate the transcription of tRNA genes in eukaryotes and archaea. For this purpose, we analyzed textual and some structural, mechanical, and physicochemical properties of the DNA in the 5′-flanking regions of tRNA genes, as well as in 30 bp at the beginning of genes and 60 bp at the end of genes in organisms possessing the TBP or its analog (eukaryotes, archaea) and organisms not possessing the TBP (bacteria). Representative tRNA gene sets of 11 organisms were taken from the GtRNAdb database. We found that the consensuses of A- and B-boxes in organisms from all three domains are identical; although, they differ in the conservativism of some positions. Their location relative to the ends of tRNA genes is also identical. In contrast, the structural and mechanical properties of DNA in the 5′-flanking regions of tRNA genes differ not only between organisms from different domains, but also between organisms from the same domain. Well-expressed TBP binding positions are found only in S. pombe and A. thaliana. We discuss possible reasons for the variability of the 5′-flanking regions of tRNA genes.
T Regulatory Cell Subsets Do Not Restore for One Year After Acute COVID-19
Authors: Aquino Arthur , Zaikova Ekaterina , Kalinina Olga , Karonova Tatiana L. , Rubinstein Artem , Mikhaylova Arina A. , Kudryavtsev Igor , Golovkin Alexey S.
Published: November 2024

COVID-19, caused by SARS-CoV-2, triggers a complex immune response, with T regulatory cells (Tregs) playing a crucial role in maintaining immune homeostasis and preventing excessive inflammation. The current study investigates the function of T regulatory cells during COVID-19 infection and the subsequent recovery period, emphasizing their impact on immune regulation and inflammation control. We conducted a comprehensive analysis of Treg subpopulations in peripheral blood samples from COVID-19 patients at different stages: acute infection, early convalescence, and long-term recovery. Flow cytometry was employed to quantify Tregs including “naïve”, central memory (CM), effector memory (EM), and terminally differentiated CD45RA+ effector cells (TEMRA). Additionally, the functional state of the Tregs was assessed by the expression of purinergic signaling molecules (CD39, CD73). Cytokine profiles were assessed through multiplex analysis. Our findings indicate a significant decrease in the number of Tregs during the acute phase of COVID-19, which correlates with heightened inflammatory markers and increased disease severity. Specifically, we found a decrease in the relative numbers of “naïve” and an increase in EM Tregs, as well as a decrease in the absolute numbers of “naïve” and CM Tregs. During the early convalescent period, the absolute counts of all Treg populations tended to increase, accompanied by a reduction in pro-inflammatory cytokines. Despite this, one year after recovery, the decreased subpopulations of regulatory T cells had not yet reached the levels observed in healthy donors. Finally, we observed the re-establishment of CD39 expression in all Treg subsets; however, there was no change in CD73 expression among Tregs. Understanding these immunological changes across different T regulatory subsets and adenosine signaling pathways offers important insights into the disease’s pathogenesis and provides a broader view of immune system dynamics during recovery.