bluuebunny/crossref_metadata_2025 huggingface dataset:
3D-Printing of Artificial Aortic Heart Valve Using UV-Cured Silicone: Design and Performance Analysis
Authors: Ertas Atila , Farley-Talamantes Erik , Cuvalci Olkan , Gecgel Ozhan
Published: January 2025

The advancement of medical 3D printing technology includes several enhancements, such as decreasing the length of surgical procedures and minimizing anesthesia exposure, improving preoperative planning, creating personalized replicas of tissues and bones specific to individual patients, bioprinting, and providing alternatives to human organ transplants. The range of materials accessible for 3D printing within the healthcare industry is significantly narrower when compared with conventional manufacturing techniques. Liquid silicone rubber (LSR) is characterized by its remarkable stability, outstanding biocompatibility, and significant flexibility, thus presenting substantial opportunities for manufacturers of medical devices who are engaged in 3D printing. The main objective of this study is to develop, refine, and assess a 3D printer that can employ UV-cured silicone for the fabrication of aortic heart valves. Additionally, the research aims to produce a 3D-printed silicone aortic heart valve and evaluate the feasibility of the final product. A two-level ANOVA experimental design was utilized to investigate the impacts of print speed, nozzle temperature, and layer height on the print quality of the aortic heart valve. The findings demonstrated that the 3D-printed heart valve’s UV-cured silicone functioned efficiently, achieving the target flow rates of 5 L/min and 7 L/min. Two distinct leaflet thicknesses (LT) of the heart valve, namely 0.8 mm and 1.6 mm, were also analyzed to simulate calcium deposition on the leaflets.
Investigation and Identification of Fungal Diseases of Aloe barbadensis in China
Authors: Zhang Guohui , Wan Qingjia , Li Xiangyang , Deng Jie
Published: January 2025

The Aloe barbadensis industry plays an important role in the economic development of Yuanjiang county of Yuxi city in Yunnan province, China. In order to reduce the harm of diseases and ensure the quality of products, the occurrence of A. barbadensis was investigated. The pathogenic fungi of wild and cultivated species of A. barbadensis were isolated by a tissue separation method, and DNA sequencing was carried out by using the sequence analysis of the ribosomal rDNA-ITS region, and the pathogenic fungi were classified and identified by finally combining morphological observations. The results showed that the main fungal diseases were root rot and leaf rot disease caused by Fusarium oxysporum, leaf spot disease caused by Curvularia lunata, anthracnose caused by Colletotrichum boninense, and brown spot disease caused by Alternaria alternata on A. barbadensis.
Parameterization of the Differences in Neural Oscillations Recorded by Wearable Magnetoencephalography for Chinese Semantic Cognition
Authors: Liang Xiaoyu , Wu Huanqi , Ma Yuyu , Liu Changzeng , Ning Xiaolin
Published: January 2025

Neural oscillations observed during semantic processing embody the function of brain language processing. Precise parameterization of the differences in these oscillations across various semantics from a time–frequency perspective is pivotal for elucidating the mechanisms of brain language processing. The superlet transform and cluster depth test were used to compute the time–frequency representation of oscillatory difference (ODTFR) between neural activities recorded by optically pumped magnetometer-based magnetoencephalography (OPM-MEG) during processing congruent and incongruent Chinese semantics. Subsequently, ODTFR was parameterized based on the definition of local events. Finally, this study calculated the specific time–frequency values at which oscillation differences occurred in multiple auditory-language-processing regions. It was found that these oscillatory differences appeared in most regions and were mainly concentrated in the beta band. The average peak frequency of these oscillatory differences was 15.7 Hz, and the average peak time was 457 ms. These findings offer a fresh perspective on the neural mechanisms underlying the processing of distinct Chinese semantics and provide references and insights for analyzing language-related brain activities recorded by OPM-MEG.
Fetal Mammary Gland Development and Offspring’s Breast Cancer Risk in Adulthood
Authors: Mabasa Lawrence , Kotze Anri , Sangweni Nonhlakanipho F. , Willmer Tarryn , Gabuza Kwazikwakhe B. , Patel Oelfah , Omoruyi Sylvester Ifeanyi , Burns Anathi , Johnson Rabia
Published: January 2025

While advancements in early detection and improved access to care have significantly enhanced breast cancer survival rates, the disease remains a significant global malignancy, constituting approximately 12.5% of all new cancer cases and claiming nearly 700,000 lives in 2020. As a result, there is widespread consensus that the most sustainable solution lies in prevention. Indeed, preventive strategies, including lifestyle modifications and research into risk-reducing interventions, offer the potential to address the root causes of noncommunicable diseases such as breast cancer. While conventional wisdom has long attributed established risk factors for breast cancer to age, lifestyle, familial history, and reproductive factors, evidence highlights the maternal environment as a pivotal stage for fetal programming of disease risk, as elucidated in the developmental origins of health and disease (DOHaD) framework. Consequently, a growing body of research has been focused on elucidating epigenomic signatures that influence fetal development while shaping health outcomes and susceptibility to diseases later in life. This review aims to identify fetal mammary developmental genes that have been implicated in breast cancer etiology and the potential interplay of maternal environment in epigenetic programming of breast cancer risk in adulthood.
Correction: Hao et al. Enhanced Chemoprevention of Prostate Cancer by Combining Arctigenin with Green Tea and Quercetin in Prostate-Specific Phosphatase and Tensin Homolog Knockout Mice. Biomolecules 2024, 14, 105
Authors: Hao Qiongyu , Henning Susanne M. , Magyar Clara E. , Said Jonathan , Zhong Jin , Rettig Matthew B. , Vadgama Jaydutt V. , Wang Piwen
Published: January 2025

The authors would like to replace Figure 3B of the following published paper [...]
Risk Stratification in HPV-Associated Oropharyngeal Cancer: Limitations of Current Approaches and the Search for Better Solutions
Authors: Garb Bailey Fabiny , Mohebbi Elham , Lawas Maria , Xia Shaomiao , Maag Garett , Ahn Peter H. , D’Silva Nisha J. , Rozek Laura S. , Sartor Maureen A.
Published: January 2025

The rising incidence of human papillomavirus (HPV)-associated oropharyngeal squamous cell carcinoma (OPSCC) necessitates advancements in risk stratification to optimize treatment outcomes and improve the quality of life for patients. Despite its favorable prognosis compared to HPV-negative OPSCC, current clinical staging and biomarkers, such as p16 status, are limited in their ability to distinguish between high- and low-risk patients within HPV-associated OPSCC. This limitation results in the overtreatment of low-risk patients, exposing them to unnecessary toxicity, and the undertreatment of high-risk patients who require more aggressive interventions. This review critically evaluates current stratification methods, including clinical assessments, de-escalation trials, and candidate molecular biomarkers for risk stratification. Emerging approaches such as immune markers, viral genomic integration patterns, and other molecular markers offer promising avenues for enhanced prognostic accuracy. By integrating advanced risk stratification methods, tailored treatment approaches may one day be developed to balance oncologic efficacy with reduced treatment-related morbidity. This review underscores the need for continued research into predictive biomarkers and adaptive treatment strategies to better address the diverse risk profiles of HPV-associated OPSCC patients.
Circulating Tumor DNA Testing for Minimal Residual Disease and Its Application in Colorectal Cancer
Authors: Abidoye Oluseyi , Ahn Daniel H. , Borad Mitesh J. , Wu Christina , Bekaii-Saab Tanios , Chakrabarti Sakti , Sonbol Mohamad Bassam
Published: January 2025

Colorectal cancer (CRC) represents a heterogeneous group of diseases that imposes a considerable global and national health burden. Although most CRC patients are diagnosed at an early stage and undergo potentially curative treatment, a significant proportion experience recurrence. Currently, adjuvant chemotherapy decisions are primarily based on clinicopathological characteristics, which have well-recognized limitations in accurately identifying patients harboring minimal residual disease (MRD), often resulting in unnecessary chemotherapy exposure. Circulating tumor DNA (ctDNA) has emerged as a promising surrogate marker for MRD, offering a more precise approach to identifying patients at risk of recurrence after curative-intent surgery and refining adjuvant chemotherapy decisions. Growing evidence from multiple studies has demonstrated that ctDNA outperforms traditional clinicopathological factors as a marker for MRD. This review synthesizes key studies supporting the role of ctDNA in MRD detection for CRC patients and evaluates clinical trials investigating the application of ctDNA in guiding adjuvant therapy decisions. This emerging strategy holds the potential to transform the adjuvant treatment paradigm in colorectal cancer by optimizing therapeutic precision and minimizing unnecessary treatment.
Cellular Systems for Colorectal Stem Cancer Cell Research
Authors: Grigoreva Tatyana A. , Kindt Daria N. , Sagaidak Aleksandra V. , Novikova Daria S. , Tribulovich Vyacheslav G.
Published: January 2025

Oncological diseases consistently occupy leading positions among the most life-threatening diseases, including in highly developed countries. At the same time, the second most common cause of cancer death is colorectal cancer. The current level of research shows that the development of effective therapy, in this case, requires a new grade of understanding processes during the emergence and development of a tumor. In particular, the concept of cancer stem cells that ensure the survival of chemoresistant cells capable of giving rise to new tumors is becoming widespread. To provide adequate conditions that reproduce natural processes typical for tumor development, approaches based on increasingly complex cellular systems are being improved. This review discusses the main strategies that allow for the study of the properties of tumor cells with an emphasis on colorectal cancer stem cells. The features of working with tumor cells and the advantages and disadvantages of 2D and 3D culture systems are considered.
The Effect of Ti(C,N)-Based Coating Composition on Ni-Cr Alloys on the Initial Adhesion of E. coli Bacteria and C. albicans Fungi
Authors: Banaszek Katarzyna , Dąbrowska Katarzyna , Jakubowski Witold , Klimek Leszek , Kula Zofia
Published: January 2025

Under natural physiological conditions, the oral cavity is colonized by a diverse range of microorganisms, which inhabit its anatomical structures as well as prosthetic restorations and the supragingival surfaces of implants. The metabolic activity of these microorganisms can contribute to microbiological corrosion, leading to the degradation of metal prosthetic materials. No material used for prosthetic elements is entirely resistant to bacterial adhesion. However, the application of protective coatings, such as Ti(C,N) coatings, on prosthetic surfaces can significantly reduce microorganism adherence. This study aimed to evaluate the influence of carbon and nitrogen content in Ti(C,N) coatings on reducing microorganism adhesion. Tests were conducted on five groups of Ni-Cr alloy specimens, each coated with Ti(C,N) layers containing varying amounts of carbon and nitrogen. The adhesion of E. coli bacteria and C. albicans fungi was assessed under both stationary and dynamic flow conditions. Results demonstrated that all tested coatings significantly reduced microorganism adhesion compared to uncoated Ni-Cr alloy samples.
Thermal Decomposition of Calcium Carbonate at Multiple Heating Rates in Different Atmospheres Using the Techniques of TG, DTG, and DSC
Authors: Zhuang Dingxiang , Chen Zhengzheng , Sun Bin
Published: January 2025

To grasp the decomposition reaction rule of calcium carbonate in cement raw material, the thermogravimetric analyzer (TG), derivative thermogravimetric (DTG), and differential scanning calorimeter (DSC) were used for analysis. Calcium carbonate samples were heated linearly at multiple heating rates of 10, 20, 30, and 40 °C/min in the atmospheres of N2 and 70% N2 + 30% O2, respectively. The decomposition kinetics was investigated using a double extrapolation method. Kinetic parameters of the thermal decomposition and the most probable mechanism function were determined in two different atmospheres. The results show that TG, DTG, and DSC curves moved to a higher temperature with the increase in heating rate, and the addition of O2 in the reaction atmosphere had almost no effect on the change in the decomposition curve. Additionally, the activation energy of the initial state in the formation of the new nucleus obtained using the double extrapolation method was 232.13 kJ/mol in the N2 atmosphere, and the most probabilistic mechanistic function was G(α) = 1 − (1 − α)1/2. The chemical reaction process was consistent with the contracted cylinder mechanism model of phase boundary reaction. Moreover, the activation energy of the initial state in the formation of the new nucleus was 233.79 kJ/mol in the 70% N2 + 20% O2 atmosphere, and the chemical reaction process was consistent with that of the N2 atmosphere. Therefore, these results could determine the decomposition temperature and decomposition rate of calcium carbonate. This was important for understanding the thermal stability and processing temperature range of polymer materials, especially the application and potential in production and scientific research.
Probability via Expectation Measures
Authors: Harremoës Peter
Published: January 2025

Since the seminal work of Kolmogorov, probability theory has been based on measure theory, where the central components are so-called probability measures, defined as measures with total mass equal to 1. In Kolmogorov’s theory, a probability measure is used to model an experiment with a single outcome that will belong to exactly one out of several disjoint sets. In this paper, we present a different basic model where an experiment results in a multiset, i.e., for each of the disjoint sets we obtain the number of observations in the set. This new framework is consistent with Kolmogorov’s theory, but the theory focuses on expected values rather than probabilities. We present examples from testing goodness-of-fit, Bayesian statistics, and quantum theory, where the shifted focus gives new insight or better performance. We also provide several new theorems that address some problems related to the change in focus.
Smart Transparency: A User-Centered Approach to Improving Human–Machine Interaction in High-Risk Supervisory Control Tasks
Authors: Wang Keran , Hou Wenjun , Hong Leyi , Guo Jinyu
Published: January 2025

In supervisory control tasks, particularly in high-risk fields, operators need to collaborate with automated intelligent agents to manage dynamic, time-sensitive, and uncertain information. Effective human–agent collaboration relies on transparent interface communication to align with the operator’s cognition and enhance trust. This paper proposes a human-centered adaptive transparency information design framework (ATDF), which dynamically adjusts the display of transparency information based on the operator’s needs and the task type. This ensures that information is accurately conveyed at critical moments, thereby enhancing trust, task performance, and interface usability. Additionally, the paper introduces a novel user research method, Heu–Kano, to explore the prioritization of transparency needs and presents a model based on eye-tracking and machine learning to identify different types of human–agent interactions. This research provides new insights into human-centered explainability in supervisory control tasks.
Robust Co-Optimization of Medium- and Short-Term Electrical Energy and Flexibility in Electricity Clusters
Authors: Kaleta Mariusz
Published: January 2025

The increasing penetration of distributed renewable energy sources introduces challenges in maintaining balance within power systems. Civic energy initiatives offer a promising solution by decentralizing balancing responsibilities to local areas, with energy clusters serving as an example of such communities. This article proposes a novel mixed-integer linear programming (MILP) model for optimizing the energy mix within a cluster, addressing both planned balancing (day-ahead) and unplanned real-time adjustments. The proposed approach focuses on mid-term decision-making, including the integration of additional wind energy sources into the cluster and the procurement of new demand-side response (DSR) contracts, that allow for short-term planned and unplanned balancing. While increased wind energy enhances the system’s renewable capacity, it also raises operational stiffness, whereas DSR contracts provide the flexibility necessary for effective system balancing. The model incorporates risk aversion by employing Conditional Value at Risk (CVaR) as a risk measure, enabling a nuanced evaluation of trade-offs between cost and risk. The interactive framework allows decision-makers to tailor solutions by adjusting confidence levels and assigning weights to cost and risk metrics. A representative numerical example, based on a typical energy cluster in Poland, illustrates the model’s applicability. This case study demonstrates that the model responds intuitively to varying decision-maker preferences and can be efficiently solved for practical problem sizes.
Energy Conservation Strategy Driven by Optimizing Waste Heat Supply Chain
Authors: Yang Jing , He Juan , Zhang Zhiyong , Hong Ming , Xu Tao , Li Zhidong , Qin Fuyu
Published: January 2025

Subject to pressures from resource exhaustion and environmental pollution, many countries have aimed to replace fossil fuels with renewable energy as part of their decarbonization strategy. In the post-pandemic era, countries are making efforts to explore a sustainable mode of economic development that features low resource consumption and less environmental pollution. Consumers are increasingly concerned about the environmental friendliness of energy products. In this study, we formulated four solutions for energy-saving optimization and control of the waste heat supply chain to conserve energy and compared the impact of a profit-as-incentive energy efficiency strategy and an energy efficiency incentive strategy on energy efficiency in the waste heat supply chain. Government agencies and enterprises can adopt a suitable strategy with the best current social and economic benefits to manage waste heat recovery. The profit-as-incentive energy efficiency strategy is more favorable for enterprises in the early stage of development. Under dual pressures of social attention to green energy and environmental protection, government agencies may adjust energy conservation policy to encourage enterprises to choose an energy efficiency incentive strategy to increase energy conservation.
Improved YOLOv5: Efficient Object Detection for Fire Images
Authors: Yu Dongxing , Li Shuchao , Zhang Zhongze , Liu Xin , Ding Wei , Zhao Xinyi
Published: January 2025

Camera-based fire detection systems have been found to yield significantly superior results compared to their sensor-based counterparts, and are thus widely employed for this purpose across the globe. This study presents an effective and lightweight fire detection technique based on deep learning. A novel convolutional neural network has been created specifically for the purpose of identifying fire areas. This network utilizes the YOLOv5 algorithm. The default versions of the You Only Look Once (YOLO) technique demonstrate limited accuracy when applied to fire detection instances, even after undergoing training and testing. After training and testing in fire detection instances, the default versions of the YOLO technique exhibit a significantly low level of accuracy. We chose the YOLOv5 network to augment its capabilities and maximize its effectiveness in identifying fire disasters. The self-designed convolution module, also known as the improved convolution module, is implemented to substitute the regular convolution module in YOLOv5. By dividing the input features into two main portions, it helps to realize the lightweight of the network. Additionally, the network incorporates the attention mechanism. The testing findings clearly show that the proposed method is more effective than previous ways of identifying fire, with a precision of 91.22% and a recall of 93.78%.
Pressure Behavior in a Linear Porous Media for Partially Miscible Displacement of Oil by Gas
Authors: Sousa Luara K. S. , Barros Wagner Q. , Pires Adolfo P. , Peres Alvaro M. M.
Published: January 2025

Miscible gas flooding improves oil displacement through mass exchange between oil and gas phases. It is one of the most efficient enhanced oil recovery methods for intermediate density oil reservoirs. In this work, analytical solutions for saturation, concentration and pressure are derived for oil displacement by a partially miscible gas injection at a constant rate. The mathematical model considers two-phase, three-component fluid flow in a one-dimensional homogeneous reservoir initially saturated by a single oil phase. Phase saturations and component concentrations are described by a 2×2 hyperbolic system of partial differential equations, which is solved by the method of characteristics. Once this Goursat–Riemann problem is solved, the pressure drop between two points in the porous media is obtained by the integration of Darcy’s law. The solution of this problem may present three different fluid regions depending on the rock–fluid parameters: a single-phase gas region near the injection point, followed by a two-phase region where mass transfer takes place and a single-phase oil region. We considered the single-phase gas and the two-phase gas/oil regions as incompressible, while the single-phase oil region may be incompressible or slightly compressible. The solutions derived in this work are applied for a specific set of rock and fluid properties. For this data set, the two-phase region displays rarefaction waves, shock waves and constant states. The pressure behavior depends on the physical model (incompressible, compressible and finite or infinite porous media). In all cases, the injection pressure is the result of the sum of two terms: one represents the effect of the mobility contrast between phases and the other represents the single-phase oil solution. The solutions obtained in this work are compared to an equivalent immiscible solution, which shows that the miscible displacement is more efficient.
Comparative Study of Statistical Approaches and SNP Panels to Infer Distant Relationships in Forensic Genetics
Authors: Tillmar Andreas , Kling Daniel
Published: January 2025

Background/Objectives: Inferring genetic relationships based on genetic data has gained an increasing focus in the last years, in particular explained by the rise of forensic investigative genetic genealogy (FIGG) but also the introduction of expanded SNP panels in forensic genetics. A plethora of statistical methods are used throughout publications; in direct-to-consumer (DTC) testing, the shared segment approach is used, in screenings of relationships in medical genetic research, for instance, methods-of-moment estimators, e.g., estimation of the kinship coefficient, are used, and in forensic genetics, the likelihood and the likelihood ratio are commonly used to evaluate the genetic data under competing hypotheses. This current study aims to compare and contrast examples of the aforementioned statistical methods to infer relationships from genetic data. Methods/Results: This study includes some historical and some recently published panels of SNP markers to illustrate the strength and caveats of the statistical methods on different marker sets and a selection of pre-defined pairwise relationships, 1st through 7th degree. Extensive simulations are performed and subsequently subsetted based on the marker panels alluded to above. As has been shown in previous research, the likelihood ratio is most powerful, i.e., high correct classifications, when SNP data are sparse, say below 20,000 markers, whereas the windowed kinships and segment approaches are equally powerful when very dense SNP data are available, say >20,000 markers. In between lay approaches using method-of-moments estimators which perform well when the degree of relationship is below four but less so beyond, say, 4th degree relationships. The likelihood ratio is the only method that is easily adapted for non-pairwise tests and therefore has an additional depth not addressed in the current study. We furthermore perform a study of genotyping error rates and their impact on the different statistical methods employed to infer relationships, where the results show that error rates below 1% seem to have low impact across all methods, in particular for errors yielding false heterozygote genotypes.
Persisting Rock-Buffered Conditions in the Upper Triassic and Lower Jurassic Dolomites of the Central Apennines (Italy) During Diagenesis, Burial, and Thrusting
Authors: Lucca Alessio , Mittempergher Silvia , Balsamo Fabrizio , Cipriani Anna , Cilona Antonino , Storti Fabrizio
Published: January 2025

Basin-scale dolomitization of carbonate sequences occurs over long time spans and results from diagenesis, burial, and tectonically driven fluid fluxes. Depicting the different geological processes producing dolomitized carbonate sequences requires combining accurate field, petrographic, and geochemical analyses. Here, we investigate the dolomitization processes in carbonates of the Norian to Toarcian age exposed in the Gran Sasso Massif, Central Apennines of Italy, by integrating field observations, standard and CL petrography, carbon, oxygen, strontium and clumped isotopes, minor elements, and X-ray diffractometry. The carbonates show pervasive replacive dolomitization, and dolomite cements are observed in bed-parallel and thrust-related veins. Replacive dolomites show incomplete replacement from modified seawater in oxidizing conditions, with minimum temperatures of 40–65 °C and a 87Sr/86Sr lower than coeval seawater. The first dolomitization event started at shallow burial in the Late Triassic–Early Jurassic and was later affected by replacement at intermediate burial depths. Bedding-parallel dolomite veins crystallized due to fluid overpressures at deep burial depths in a rock-buffered system without variations in geochemistry. Fault-related dolomites cemented thrust-related fractures during compressional deformation in the Messinian–Early Pliocene from seawater modified by mixing with external fluids. Precipitation temperatures of replacive, bedding-parallel, and fault-related dolomite veins are similar. Despite the dolomite types being characterized by different textures and petrographic features, rock-buffered conditions resulted in insignificant variations of their geochemical properties.
Development of an Evidence-Based Cognitive Training Application for Elderly Individuals with Cognitive Dysfunction
Authors: Chae Hee-Jae , Kim Chan-Hee , Lee Seon-Heui
Published: January 2025

Background: Early cognitive training is important to prevent cognitive decline in patients with mild cognitive impairment (MCI) or dementia. Therefore, developing an application that can provide evidence-based cognitive training is necessary for patients with MCI or dementia. Method: This study aimed to develop and evaluate Smart Brain, an evidence-based application that provides comprehensive cognitive training tailored to this population. The application was developed using an ADDIE (analysis, design, development, implementation, and evaluation) model. A systematic review of databases, including Ovid-MEDLINE, Ovid-EMBASE, Cochrane Library, and CINAHL, was conducted up to April 15, 2021, to identify key content areas. Additionally, a survey of 100 participants highlighted the need for features such as cognitive games, health notes, social networking services, and goal achievement. Result: The application was developed with distinct user and administrator interfaces to support engagement and monitoring. Usability testing involved 7 experts and 11 elderly individuals with MCI or dementia from a daycare center. Based on usability feedback, features such as the time limits for cognitive games were refined. The final application integrates cognitive games, physical exercises, emotional support, and health management tools to address user needs comprehensively. Conclusion: Smart Brain holds significant potential to improve the quality of life and cognitive health of elderly individuals with MCI or dementia. Its usability and functionality make it a promising tool for community-based interventions.
Psychedelics: Safety and Efficacy
Authors: Miller Norman
Published: January 2025

Psychedelic research has experienced a renaissance in recent years, with many researchers exploring the possible therapeutic effects of these drugs. Medical institutions, universities, pharmaceutical companies, and governmental institutions alike have been showing an increase in support of this research, as shown through the recent establishment of various psychedelic research facilities across the United States. However, the safety and efficacy of psychedelic usage are not the focus of the existing research. Additionally, many of the studies on psychedelic use that have already been published lack the necessary scientific rigor required for studies of such medical importance. The current paper will discuss the issue of misleading information as well as poorly designed studies and what implications these have on the rescheduling of psychedelic drugs that are currently categorized as Schedule I. The current Schedule I status of psychedelics means that they are considered to have no legitimate medical value as well as a high potential for abuse. Furthermore, the current paper aims to discuss psychedelics while drawing awareness to the lack of the literature surrounding the safety and efficacy of psychedelics for medical use. This paper will also discuss the history of psychedelic use and abuse, the adverse effects of psychedelic use, and the role that personal and financial bias has within the psychedelic research field.
Integrative Single-Cell and Bulk RNA Sequencing Identifies a Macrophage-Related Prognostic Signature for Predicting Prognosis and Therapy Responses in Colorectal Cancer
Authors: Xie Shaozhuo , Hou Siyu , Chen Jiajia , Qi Xin
Published: January 2025

Colorectal cancer (CRC) is one of the most common malignant tumors, characterized by a high incidence and mortality rate. Macrophages, as a key immune cell type within the tumor microenvironment (TME), play a key role in tumor immune evasion and the progression of CRC. Therefore, identifying macrophage biomarkers is of great significance for predicting the prognosis of CRC patients. This study integrates scRNA-seq and bulk RNA-seq data to identify macrophage-related genes in CRC. By applying a comprehensive machine learning framework, the macrophage-related prognostic signature (MRPS) was constructed by 15 macrophage-related genes with prognostic values. The MRPS demonstrated strong predictive performance across multiple datasets, effectively stratifying high-risk and low-risk patients in terms of overall survival (OS) and disease-specific survival (DSS). Furthermore, immune analysis revealed significant differences between the high-risk and low-risk groups in immune cell infiltration levels and immune checkpoint gene expression patterns. Drug screening identified several small molecules, including Bortezomib and Mitoxantrone, as potential therapeutic options for high-risk patients. Pseudotime trajectory analysis further highlighted the potential role of genes comprising the MRPS in macrophage differentiation. This study provides a powerful tool for personalized prognosis prediction in CRC patients, offering new insights into macrophage-driven mechanisms in tumor progression and potential therapeutic strategies.
Proteomics Reveals the Response Mechanism of Embryonic Bovine Lung Cells to Mycoplasma bovis Infection
Authors: Wang Li , Wang Qing , Liu Yudong , Chen Yunxia , Bao Shijun , Zhang Xiaoli , Wang Chuan
Published: January 2025

Mycoplasma bovis (M. bovis) has caused huge economic losses to the cattle industry. The interaction between M. bovis and host cells is elucidated by screening and identifying the target protein of M. bovis adhesin on the surface of the host cell membrane. However, the response mechanism of embryonic bovine lung (EBL) cells to M. bovis infection is not yet fully understood. Additionally, it is necessary to further explore whether infection with M. bovis induces oxidative stress and mitochondrial damage in EBL cells. In this study, oxidation reaction, mitochondrial membrane potential, mitochondrial structure, and apoptosis ability of EBL cells infected with M. bovis were assessed at different times (12, 24, 48 h post-infection; hpi). Then, the differential proteomic analysis of M. bovis-infected EBL cells at 12 h and 24 h was performed with uninfected cells as the control. The results showed that M. bovis infection reduced the antioxidant capacity of EBL cells, increased ROS levels, and decreased mitochondrial membrane potential. The mitochondrial membrane of EBL cells was damaged, and the ridge arrangement was disordered after infection by transmission electron microscopy. With the increase in infection time, the mitochondrial matrix partially dissolved and spilled. The apoptosis rate of EBL cells increased with the increase in infection time of M. bovis. Furthermore, proteomic analysis identified 268 and 2061 differentially expressed proteins (DEPs) at 12 hpi and 24 hpi, respectively, compared with the uninfected cells. According to GO analysis, these DEPs were involved in the mitosis and negative regulation of cell growth. Additionally, the Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis indicated the following pathways were linked to mitochondrial damage or cell growth regulation, including glycolysis/gluconeogenesis, pentose phosphate pathway, oxidative phosphorylation, AMPK, cGMP-PKG, cAMP, calcium, Wnt, Phospholipase D, apoptosis, MAPK, cell cycle, Ras, PI3K-Akt, mTOR, HIF-1. PPI results indicated that YWHAZ, PIK3CA, HSP90AB1, RAP1A, TXN, RAF1, MAPK1, PKM, PGK1, and GAPDH might be involved in mitochondrial pathway apoptosis induced by M. bovis infection. This study offers helpful data toward understanding the response of mitochondria of EBL cells to M. bovis infection.
Data Augmentation in Earth Observation: A Diffusion Model Approach
Authors: Sousa Tiago , Ries Benoît , Guelfi Nicolas
Published: January 2025

High-quality Earth Observation (EO) imagery is essential for accurate analysis and informed decision making across sectors. However, data scarcity caused by atmospheric conditions, seasonal variations, and limited geographical coverage hinders the effective application of Artificial Intelligence (AI) in EO. Traditional data augmentation techniques, which rely on basic parameterized image transformations, often fail to introduce sufficient diversity across key semantic axes. These axes include natural changes such as snow and floods, human impacts like urbanization and roads, and disasters such as wildfires and storms, which limits the accuracy of AI models in EO applications. To address this, we propose a four-stage data augmentation approach that integrates diffusion models to enhance semantic diversity. Our method employs meta-prompts for instruction generation, vision–language models for rich captioning, EO-specific diffusion model fine-tuning, and iterative data augmentation. Extensive experiments using four augmentation techniques demonstrate that our approach consistently outperforms established methods, generating semantically diverse EO images and improving AI model performance.
Impact of Ultraviolet Radiation on Growth, Development and Antioxidant Enzymes of Tuta absoluta (Meyrick)
Authors: Zhou Junhui , Luo Wenfang , He Wei , Huang Xin , Song Suqin , Mao Liang , Peng Huan , Xu Jianjun
Published: January 2025

Ultraviolet radiation serves as a significant abiotic stressor for numerous organisms, particularly impacting insects in various ways. Tuta absoluta, a highly destructive pest infesting of the Solanaceae species, was investigated to elucidate its growth, development, and enzymatic defense mechanisms of insects in response to UV exposure. This study investigates the effects of three types of UV radiation on the lifespan, egg laying behavior, and antioxidant enzyme activities of T. absoluta. Our study revealed a significant reduction in the lifespan of T. absoluta upon exposure to both UV-A and UV-B radiation, whereas extended exposure to UV-C radiation for 120 min and 180 min resulted in a decline in its egg laying capacity. Exposure to all three types of radiation (UV-A, UV-B, and UV-C) led to an irreversible decrease in catalase (CAT) enzyme activity. Upon exposure to UV-A, there was a gradual increase in peroxidase (POD) enzyme activity; however, at 120 min post-exposure, a subsequent decrease was observed. A notable elevation in superoxide dismutase (SOD) activity was observed following exposures of both 60 min and 120 min durations under the rays of UV-A. These findings provide valuable insights into understanding the effects of UV exposure on T. absoluta as well as its potential application as a control measure, warranting further investigation.
An LDDoS Attack Detection Method Based on Behavioral Characteristics and Stacking Mechanism
Authors: Ye Junwei , Wang Zhixuan , Yang Jichen , Wang Chunan , Zhang Chunyu
Published: January 2025

Today, the development of the Internet of Things has grown, and the number of related IoT devices has reached the order of tens of billions. Most IoT devices are vulnerable to attacks, especially DdoS (Distributed Denial of Service attack) attacks. DDoS attacks can easily cause damage to IoT devices, and LDDoS is an attack launched against hardware resources through a small string of very slow traffic. Compared with traditional large-scale DDoS, their attacks require less bandwidth and generate traffic similar to that of normal users, making them difficult to distinguish when identifying them. This article uses the CICIoT2023 dataset combined with behavioral features and stacking mechanisms to extract information from the attack behavior of low-rate attacks as features and uses the stacking mechanism to improve the recognition effect. A method of behavioral characteristics and stacking mechanism is proposed to detect DDoS attacks. This method can accurately detect LDDoS. Experimental results show that the recognition rate of low-rate attacks of this scheme reaches 0.99, and other indicators such as accuracy, recall, and F1 score are all better than other LDDoS detection methods. Thus, the method model proposed in this paper can effectively detect LDDoS attacks. At present, DDoS attacks are relatively mature, and there are many related results, but there is less research on LDDoS detection alone. This paper focuses on the investigation and analysis of LDDoS attacks in DDoS attacks and deduces feasible LDDoS detection methods.
Androgens and Hirsutism in a Large Cohort of Portuguese Women
Authors: Pinto Joana , Cera Nicoletta , Camerino Claudia , Beires Jorge , Pignatelli Duarte
Published: January 2025

Background/Objectives: Hirsutism is excessive male-patterned hair in postpubertal women with multifactorial etiology and is an indicator of hyperandrogenism associated with polycystic ovary syndrome (PCOS). Indeed, it can be caused by the enhanced peripheral conversion of androgen precursors to testosterone, as in idiopathic hirsutism (IH). Moreover, hirsutism can be caused by hirsutism-related hyperandrogenic syndromes like non-classic congenital adrenal hyperplasia (NCAH) and idiopathic hyperandrogenism (IHA). Methods: In this study, we characterized a large cohort of Portuguese women referred for hirsutism and estimated the prevalence of PCOS, NCAH, IHA, and IH. The levels of androgens and gonadotropins and body mass index (BMI) were measured and compared with controls. The correlation between each variable was calculated. Results: In the cohort, we found a prevalence of PCOS of 56.2%, IH of 20.2%, IHA of 17.3%, and NCAH of 6.2%. Subjects with PCOS were the only ones showing a significant difference in BMI compared to the controls and had the lowest levels of sex hormone-binding globulin (SHBG). Those with NCAH were younger and more hirsute with higher levels of testosterone, among other androgens. Those with IH had lower luteinizing hormone (LH) and LH/follicle-stimulating hormone (FSH) ratios than those with PCOS. Those with IH had lower SHBG levels compared to the controls and a higher free androgen index (FAI). Those with IHA had higher androgens compared to those with IH, in particular, adrenal-derived androgens. Conclusions: The pathogenesis of hirsutism is complex, and the contributions of the pituitary gland, ovaries, adrenals, adipose tissue, and liver have to be ascertained to understand the clinical manifestations and delineate appropriate treatments. This study sheds new light on the fine hormonal regulation of these diseases.
Cerebrospinal Fluid Biomarkers and Neuropsychological Abnormalities in Dementia: A Monocentric Study of Consecutive Patients
Authors: Römer Martin , Lange-Asschenfeldt Christian , Müller-Schmitz Katharina , Seitz Rüdiger J.
Published: January 2025

Background: In search of indicators for dementia, this study investigated the association of cerebrospinal fluid (CSF) biomarkers and neuropsychological test results with disease stage in patients with early manifestations of dementia. Methods: In 190 consecutive patients with symptoms of dementia, the CSF parameters amyloid-β 1-42 (Aβ1-42), phosphorylated tau protein (pTau), total tau protein (tTau), neuron-specific enolase (NSE), protein S100B (S100B), and Aβ (1-42)/(1-40) ratio (Aβ ratio), as well as the results of the CERAD-Plus test battery supplemented by the Clock Drawing Test (CDT), were analysed. Patients were divided into two groups based on the median duration of reported symptom onset. Results: Most prominent in the early phase of the disease were the relationships between Aβ1-42 and neuropsychological memory subtests, which were absent in the later phase. Less pronounced relationships to memory function were detectable for Aβ ratio and pTau. Conclusions: The results substantiate the relevance of Aβ1-42 for memory deficits and support the amyloid cascade hypothesis for Alzheimer’s dementia (AD). Our data suggest other pathomechanisms for visuospatial impairments in AD.
Resting Body Temperature and Long-Term Survival in Older Adults at a Mental Health Center: Cross-Sectional and Longitudinal Data
Authors: Chmielewski Piotr Paweł , Strzelec Bartłomiej , Data Krzysztof , Chmielowiec Krzysztof , Mozdziak Paul , Kempisty Bartosz
Published: January 2025

Background/Objectives: Elevated body temperature is a well-established biomarker of infection, increased disease risk, and adverse health outcomes. However, the relationship between resting body temperature and long-term survival in older individuals is complex. Emerging evidence suggests that higher basal body temperature is associated with reduced survival and accelerated aging in non-obese older adults. This study aimed to compare body temperatures across different age groups in hospitalized older adults. Methods: Data were retrospectively collected from 367 physically healthy residents of a mental health center. Longitudinal data from 142 individuals (68 men and 74 women), aged 45 to 70 years and monitored continuously over 25 years, were compared with cross-sectional data from 225 individuals (113 men and 112 women) who underwent periodic clinical examinations with temperature measurements. The cross-sectional sample was stratified into four survival categories. Resting oral temperatures were measured under clinical conditions to ensure protocol consistency. Age-related changes in both sexes were evaluated using standard regression analysis, Student’s t-tests, ANOVA, and Generalized Linear Models. Results: Longitudinal analysis revealed an increase in body temperature with age among women, while cross-sectional analysis showed that long-lived residents generally had lower body temperatures compared to their shorter-lived counterparts. Conclusions: These findings support the hypothesis that lower lifetime steady-state body temperature is associated with greater longevity in physically healthy older adults. However, further research is needed to determine whether the lower body temperature observed in long-lived individuals is linked to specific health advantages, such as enhanced immune function, absence of detrimental factors or diseases, or a reduced metabolic rate potentially influenced by caloric restriction.
Early Surge Warning Using a Machine Learning System with Real-Time Surveillance Camera Images
Authors: Chen Yi-Wen , Yu Teng-To , Peng Wen-Fei
Published: January 2025

While extreme oceanic phenomena can often be accurately predicted, sudden abnormal waves along the shore (surge) are often difficult to foresee; therefore, an immediate sensing system was developed to monitor sudden and extreme events to take necessary actions to prevent further risks and damage. Real-time images from coastal surveillance video and meteorological data were used to construct a warning model for incoming waves using long short-term memory (LSTM) machine learning. This model can predict the wave magnitude that will strike the destination area seconds later and issue an alarm before the surge arrives. The warning model was trained and tested using 110 h of historical data to predict the wave magnitude in the destination area 6 s ahead of its arrival. If the forecasting wave magnitude exceeds the threshold value, a warning will be issued, indicating that a surge will strike in 6 s, alerting personnel to take the necessary actions. This configuration had an accuracy of 60% and 88% recall. The proposed prediction model could issue a surge alarm 5 s ahead with an accuracy of 90% and recall of 80%. For surge caused by a typhoon, this approach could offer 10 s of early waring with recall of 76% and an accuracy of 74%.