bluuebunny/crossref_metadata_2025 huggingface dataset:
The Impact of Mutant EDNRB on the Two-End Black Coat Color Phenotype in Chinese Local Pigs
Authors: Huang Min , Wen Zuohao , Huang Tao , Zhou Xiaolong , Wang Zhijun , Yang Songbai , Zhao Ayong
Published: February 2025

Endothelin Receptor Type B (EDNRB) is expressed in a variety of cells during embryonic stage, including melanocyte precursors cells. Our previous studies found that 11 bp deletion of EDNRB caused the two-end black (TEB) coat color in Chinese pigs. In this study, we aimed to explore the mutant EDNRB on the formation of TEB coat color in Chinese pigs. We constructed recombinant plasmid for wild and mutant EDNRB and EDN1, respectively, and transfected the recombinant plasmid into mouse B16 melanoma cells in groups. Real-time fluorescent quantitative PCR (RT-qPCR) was performed to detect expression of genes that participate in melanin pathway, including PLCγ, Raf, MITF. Comparing to the wild-type EDNRB cells, expression of the three genes in the cell line expressing mutant EDNRB cells was significantly reduced. We measured the melanin content produced by transfected recombinant granulocytes of wild and mutant EDNRB and found that the amount of melanin in mutant EDNRB cells was significantly lower than that of the wild. Wound-healing assay confirmed that the migration and mobility rate of mutant EDNRB cells were significantly lower than the wild. Co-immunoprecipitation further confirmed that mutant EDNRB could not interact with the EDN1 protein. In conclusion, this study revealed that the 11 bp deletion of EDNRB reduced the melanin production, which may be caused by inhibiting the expression of PLCγ, Raf, and MITF. The mutant EDNRB reduced melanocyte migration and could not interact with the EDN1 protein. We explored the effect of mutant EDNRB in Chinese pigs with TEB coat color, and the results provided a reference for exploring molecular mechanism of mutant EDNRB on the formation of TEB coat color pigs.
Physical, Compressive Strength, and Microstructural Characteristics of Alkali-Activated Engineered Composites Incorporating MgO, MWCNTs, and rGO
Authors: Hossain Mohammad Ali , Hossain Khandaker M. A.
Published: February 2025

Thirty-two ambient cured alkali-activated engineered composites (AAECs) were developed by incorporating MgO, multi-walled carbon nanotubes (MWCNTs), reduced graphene oxide (rGO), and polyvinyl alcohol (PVA) fiber with a one-part dry mix technique using powder-based activators/reagents. The effects of material variables, namely binary or ternary combination source materials (fly ash C or F and ground granulated blast furnace slag ‘GGBFS’), two types of reagents with varying chemical ratios and dosages of additives (from 0 to 5% MgO and from 0 to 6% MWCNT/rGO), on the physical (slump flow, flow time, flow velocity, and density), hardness (compressive strength from 0 to 180 days and 28-day ultrasonic pulse velocity ‘UPV’), and micro-structural (SEM/EDS, XRD and FTIR) properties were evaluated. All these variables, individually or combined, influenced the properties and microstructural aspects of AAECs. Problems associated with the dispersion and agglomeration of nanomaterials, which could disrupt the microstructure and weaken its mechanical/physical properties, were avoided through the use of defined ultra-sonication with a high-shear mixing protocol. All AAECs achieved a 28-day compressive strength ranging from 26.0 MPa to 48.5 MPa and a slump flow > 800 mm, satisfying the criteria for flowable structural concrete. The addition of 5% MgO and up to 0.3% MWCNT/rGO increased the compressive strength/UPV of AAECs with MgO-MWCNT or rGO combination provided an improved strength at a higher dosage of 0.6%. A linear correlation between compressive strength and UPV was derived. As per SEM/EDS and XRD analyses, besides common C-A-S-H/N-C-A-S-H or C-A-S-H/C-S-H gels, the addition of MgO led to the formation of magnesium-aluminum hydrotalcite (Ht) and M-S-H (demonstrating self-healing potential), while the incorporation of rGO produced zeolites which densified the matrix and increased the compressive strength/UPV of the AAECs. Fourier transform infrared spectrometer (FTIR) analysis also suggested the formation of an aluminosilicate network in the AAECs, indicating a more stable structure. The increased UPV of MWCNT/rGO-incorporated AAECs indicated their better conductivity and ability of self-sensing. The developed AAECs, incorporating carbon-nano materials and MgO additive, have satisfactory properties with self-healing/-sensing potentials.
Microbiological Control and Nutritional and Sensorial Characterization of Bottarga by Mugil cephalus Produced in Sardinia (Italy)
Authors: Sanna Manuela , Carta Silvia , Murgia Marco A. , Chessa Margherita , Nudda Anna , Mangia Nicoletta P.
Published: February 2025

Bottarga is a traditional Sardinian (Italy) food derived from several treatments of female mullet gonads (Mugil cephalus) that occur in specific humidity (53%) and temperature (25 °C) conditions. In this work, samples from the east (BEC) and west coasts (BWC) of Sardinia were evaluated for microbiological quality, physico-chemical composition, and sensorial features. Chemical analyses show a protein and fat content of about 39% and 18.6%, respectively, without any difference between the two areas. The bottarga also had a concentration of calcium equal to 455 and 413 mg/kg for BWC and BEC, respectively, as well as a sodium concentration of about 0.70% in both samples. The cholesterol found in the samples was 417 and 389 mg/100 g of the edible part of the bottarga from the west and east coasts, respectively. Overall, microbiological evaluation indicates appropriate hygiene and safety conditions. No significant differences were observed between BEC and BWC samples regarding color uniformity and texture attributes (greasiness, adhesiveness, and friability), while the global odor and sea odor were higher for BWC than BEC.
The Vibration Response Characteristics of Neighboring Tunnels Induced by Shield Construction
Authors: Wang You , Yu Siyuan , Wang Rui , Ding Bosong
Published: February 2025

With the increasing complexity of engineering environments in tunnel construction, the vibrations generated by shield tunneling in hard rock strata pose significant challenges to the operation and maintenance of adjacent tunnels. This study investigates the vibration characteristics induced by shield tunneling and provides an in-depth analysis of the propagation behavior of these vibrations within tunnel segments and surrounding soil layers. Through a combination of theoretical derivations, on-site monitoring, and numerical simulations, the research examines the distribution of vibration energy and its attenuation patterns with increasing propagation distance. The findings reveal that vibration energy is primarily concentrated in the low-frequency range (3–4 Hz) and follows an exponential decay trend as distance increases. Furthermore, the vibration response of neighboring tunnels is heavily influenced by the construction vibration source, with rapid energy attenuation observed over short distances. Numerical simulations conducted using PFC3D6.0 (Particle Flow Code) software validate the theoretical model and emphasize the critical roles of soil-damping properties and tunnel segment material characteristics in vibration attenuation. This study offers a robust theoretical framework and valuable data to support the control of tunnel vibrations and the optimization of construction practices.
DeepST-Net: Leveraging Spatiotemporal Data Refinement for Enhanced Travel Time Prediction
Authors: Benlecheb Amira , Chaouche Ahmed-Chawki , Benabderrahmane Brahim , Díaz Gregorio
Published: February 2025

Accurate travel time prediction is essential for optimizing transportation systems and alleviating congestion in urban environments. This study introduces a comprehensive framework that combines advanced spatiotemporal data refinement techniques with a deep learning model, DeepST-Net, to improve prediction accuracy. Using a dataset from the New York City Taxi and Limousine Commission (TLC), an ablation study is conducted to systematically assess the impact of various preprocessing strategies on model performance. Additionally, the DeepST-Net model is benchmarked against established models, including MURAT, ST-NN, XGB-IN, and JSTC. Our findings demonstrate that DeepST-Net, leveraging refined spatiotemporal features, achieves significant improvements in prediction accuracy, with a mean absolute error (MAE) of 59.27 s, a root mean square error (RMSE) of 89.63 s, and a mean absolute percentage error (MAPE) of 9.73%, outperforming all benchmark models. By bridging data refinement and predictive modeling, the proposed framework offers a scalable and effective solution for travel time prediction in complex urban contexts.
Computer Modelling of Heliostat Fields by Ray-Tracing Techniques: Simulating the Sun
Authors: Pereira José Carlos Garcia , Domingos Gonçalo , Rosa Luís Guerra
Published: February 2025

To computer-simulate solar-concentrating facilities, an accurate knowledge of the Sun’s position as a function of latitude, longitude, time and date is required. In this work, it is reported first a simplified description of a general algorithm, developed by the astronomy community to accomplish that. Our implementation of this algorithm (included in our Light Analysis Modelling package) has been successfully validated against well trusted astronomy data. The software was then used to produce a wide range of results for 2024, for two well-known research facilities, the most northern (Jülich, Germany) and the most southern (Protaras, Cyprus) heliostat fields listed in the official SFERA-III EU project. This includes altitude and azimuth data, sunrise and sunset data, analemma curves, angular speed data and geocentric Sun trajectories around the observer’s position. Other ray-tracing techniques are also reported to help simulate the Sun vectors reaching the solar devices. The truly inspiring results obtained show how important this type of software is, from the scientific and industrial point of view, to better understand our relationship with our neighbor star, the Sun.
Hybrid Renewable Energy Systems—A Review of Optimization Approaches and Future Challenges
Authors: Giedraityte Akvile , Rimkevicius Sigitas , Marciukaitis Mantas , Radziukynas Virginijus , Bakas Rimantas
Published: February 2025

The growing need for sustainable energy solutions has propelled the development of Hybrid Renewable Energy Systems (HRESs), which integrate diverse renewable sources like solar, wind, biomass, geothermal, hydropower and tidal. This review paper focuses on balancing economic, environmental, social and technical criteria to enhance system performance and resilience. Using comprehensive methodologies, the review examines state-of-the-art algorithms such as Multi-Objective Particle Swarm Optimization (MOPSO) and Non-Dominated Sorting Genetic Algorithm II (NSGA-II), alongside Crow Search Algorithm (CSA), Grey Wolf Optimizer (GWO), Levy Flight-Salp Swarm Algorithm (LF-SSA), Mixed-Integer Linear Programming (MILP) and tools like HOMER Pro 3.12–3.16 and MATLAB 9.1–9.13, which have been instrumental in optimizing HRESs. Key findings highlight the growing role of advanced, multi-energy storage technologies in stabilizing HRESs and addressing the intermittency of renewable sources. Moreover, the integration of metaheuristic algorithms with machine learning has enabled dynamic adaptability and predictive optimization, paving the way for real-time energy management. HRES configurations for cost-effectiveness, environmental sustainability, and operational reliability while also emphasizing the transformative potential of emerging technologies such as quantum computing are underscored. This review provides critical insights into the evolving landscape of HRES optimization, offering actionable recommendations for future research and practical applications in achieving global energy sustainability goals.
Solution for Active and Passive Earth Pressure on Rigid Retaining Walls with Narrow Backfill
Authors: Wang Xu , Dang Faning , Cao Xiaoshan , Zhang Le , Gao Jun , Xue Haibin
Published: February 2025

For a retaining wall adjacent to rock or rigid structures, existing model test results indicate that the slip soil in the limit state can be approximated as a trapezoidal slip wedge. Based on the static equilibrium condition of the slip wedge, a calculation method for active and passive earth pressures is proposed that considers the effect of backfill width through extreme value analysis. As the backfill width increases, the trapezoidal slip wedge transitions to a triangular slip wedge, introducing a critical width to distinguish between finite and semi-infinite soil conditions. For cohesionless soils, the proposed method converges to Coulomb theory at the critical width; when the backfill is clay, the critical width exceeds the width of Coulomb’s triangular slip wedge due to the stabilizing contribution of cohesion. Parameter analysis reveals that with increasing backfill width, the active earth pressure of cohesionless soil follows a non-linear upward trend, whereas the passive earth pressure decays exponentially. For clay, the active earth pressure initially increases with backfill width and then decreases, whereas the passive earth pressure first decays exponentially and then exhibits a slight increase. Variations in the friction angle significantly affect both active and passive earth pressures, while cohesion mainly influences active earth pressure, and wall-soil friction angle exerts a stronger impact on passive earth pressure. The effectiveness of the proposed method is verified by comparison with results from model tests and numerical simulations.
A Dual-Adaptive Perspective on PV Array Reconfiguration with Genetic Algorithms Under Partial Shading Conditions
Authors: Karaduman Özgür , Parlak Koray Şener
Published: February 2025

Photovoltaic systems are among the most popular renewable energy sources due to their ease of installation and low operating costs. However, they are characterized by low efficiency, non-linear electrical properties, and sensitivity to radiant intensity on the panels. To address these limitations, researchers have focused on improving the efficiency of these systems. The most effective method for enhancing the maximum power point of a PV array is reconfiguration, which involves rearranging the connection structures of the panels. This study presents a method for determining the reconfiguration of panels based on their radiant intensity using a genetic algorithm (GA). The method matches the rows of the PV array to achieve similar radiant intensities, thereby increasing power efficiency. An algorithm was developed to enable the adaptive panels to connect to any row of the fixed section in a PV array divided into dual-adaptive and fixed sections, controlling this connection structure. This GA-based algorithm utilizes short-circuit currents obtained from specific points of the PV array to identify the most suitable connection structure within the solution space and generates control signals for reconfiguration. Simulation results with various array structures and shading scenarios demonstrate that the proposed method increases array efficiency and achieves results within a practically applicable cycle time.
The Effects of High Hydrostatic Pressure Treatment on the Quality Characteristics and the Protein Structure of Vacuum-Packed Fresh Pork and Wild Boar Meats
Authors: Majzinger Koppány , Kovács-Bányász Bernadett , Horváth-Mezőfi Zsuzsanna , Pósa Enikő , Csehi Barbara , Hitka Géza , Alpár Boglárka , Nyulas-Zeke Ildikó Csilla
Published: February 2025

In this study, the effects of high hydrostatic pressure treatment on the quality characteristics and the protein structure of vacuum-packed fresh pork and wild boar meats were investigated. Based on the results, an optimal pressure value was determined that would not cause the sensory properties of the treated flesh to differ from that of the untreated fresh meats but would effectively contribute to the extension of shelf life. The conclusion was made that high hydrostatic pressure treatment performed at 200 MPa did not lead to the denaturation of meat proteins and had no significant effect on the pH value or the color parameters. However, the shelf life of the meat could be extended by a week due to the two-orders-of-magnitude germicidal effect of the treatment.
Emerging Applications of Machine Learning in 3D Printing
Authors: Rojek Izabela , Mikołajewski Dariusz , Kempiński Marcin , Galas Krzysztof , Piszcz Adrianna
Published: February 2025

Three-dimensional (3D) printing techniques already enable the precise deposition of many materials, becoming a promising approach for materials engineering, mechanical engineering, or biomedical engineering. Recent advances in 3D printing enable scientists and engineers to create models with precisely controlled and complex microarchitecture, shapes, and surface finishes, including multi-material printing. The incorporation of artificial intelligence (AI) at various stages of 3D printing has made it possible to reconstruct objects from images (including, for example, medical images), select and optimize materials and the printing process, and monitor the lifecycle of products. New emerging opportunities are provided by the ability of machine learning (ML) to analyze complex data sets and learn from previous (historical) experience and predictions to dynamically optimize and individuate products and processes. This includes the synergistic capabilities of 3D printing and ML for the development of personalized products.
Numerical Analysis of Friction Reduction of Grouting in Long-Distance Pipe Jacking
Authors: Wu Kai , Mu Linlong , Hu Longhao , Zhang Linni
Published: February 2025

During pipe jacking construction, in addition to overcoming the resistance at the front, there is also the need to overcome significant frictional resistance. Grouting technology is commonly used in engineering to reduce the frictional resistance exerted on the pipe’s external surface during the jacking process. This paper first reviews the commonly used grouting materials and processes, summarizes their mechanisms for friction reduction, and then establishes a numerical analysis model for grouting in pipe jacking, enhancing the common theoretical methods based on simulation results. The study employs different interface reduction coefficients to simulate the different effects of friction reduction by grouting, focuses on the impact of grouting on friction reduction during long pipe jacking, and compares the results with those calculated using common methods. The results show that the frictional resistance around the pipe is the main source of jacking force in long-distance pipe jacking, and the jacking force increases approximately linearly with the interface reduction coefficient.
Mechanical Behavior of Carbon Fiber-Reinforced Concrete Structures After Structural Failure
Authors: Prieto Tomas Gómez , Prieto María Isabel , Leal Alberto , Ferrández Daniel
Published: February 2025

The research presented below examines the use of carbon fiber-reinforced concrete specimens that have been previously tested under compression. For this study, two types of specimens were used: half without the addition of polypropylene fibers and the other half with the addition of 3 kg/m3 of polypropylene fibers. These specimens were tested in two stress groups, one above 15 N/mm2 and the other below this value. The confinement was carried out using four types of carbon fibers, two unidirectional and two bidirectional, analyzing their stress and maximum strain and comparing them with reference tests. The results indicate that confinement with carbon fibers is highly effective for stresses both above and below 15 N/mm2. In fact, the confinement increased the compressive strength compared to the original specimens, which had very low strengths, reaching values up to 15 N/mm2. Finally, the polypropylene fibers demonstrated a greater energy absorption capacity, achieving a non-explosive failure.
Study on the Evolution Mechanism of the Butterfly-Shaped Plastic Zone in Surrounding Rocks of an Underlying Roadway
Authors: Hu Yang , Meng Qingbin , Han Xu , Shan Yongjie , Wu Xueke
Published: February 2025

The mining of the working face has a pronounced influence on the floor roadway, resulting in the intensification of deformation of the surrounding rock of the roadway and posing a threat to production safety. To clarify the failure mechanism of the surrounding rock of the dynamic pressure roadway and to understand the development pattern of the plastic zone shape, in this paper, by integrating the stress distribution law of the floor during the mining process of the working face, a mechanical model of the surrounding rock of the floor dynamic pressure roadway is established. An analytical solution for the plastic zone shape of the surrounding rock of the dynamic pressure roadway is proposed and verified through a comparison between analytical calculations and numerical simulation (using FLAC3D 7.0 software). The results indicate the following: (1) when the horizontal distance between the working face and the roadway exceeds 35 m, no obvious changes are observed in the development pattern of the plastic zone of the surrounding rock of the roadway; (2) when the horizontal distance is less than 35 m, the rate of change in the maximum value of f increases from 0.02 MPa/m to 0.205 MPa/m as the vertical distance decreases, and the β value increases from 0.09°/m to 0.79°/m. The maximum development depth increases, the butterfly leaf of the plastic zone deflects towards the working face direction, and the shape gradually transforms from a “circular” shape to a “butterfly” shape. (3) The morphological characteristics of the plastic zone obtained by the analytical algorithm are highly consistent with those obtained by the numerical simulation method, suggesting that the analytical algorithm possesses certain validity. (4) There exist certain errors between the analytical method and the numerical simulation results, and they increase with the increase in the vertical distance (the error range is 19.4%~54.9%), but they can be disregarded within the requirements of engineering accuracy.
Correction: Oswald et al. High-Resolution Air Temperature Forecasts in Urban Areas: A Meteorological Perspective on Their Added Value. Atmosphere 2024, 15, 1544
Authors: Oswald Sandro M. , Schneider Stefan , Hahn Claudia , Žuvela-Aloise Maja , Schmederer Polly , Wastl Clemens , Hollosi Brigitta
Published: February 2025

In the original publication [...]
Artificial Intelligence in Biomedical Engineering and Its Influence on Healthcare Structure: Current and Future Prospects
Authors: Tripathi Divya , Hajra Kasturee , Mulukutla Aditya , Shreshtha Romi , Maity Dipak
Published: February 2025

Artificial intelligence (AI) is a growing area of computer science that combines technologies with data science to develop intelligent, highly computation-able systems. Its ability to automatically analyze and query huge sets of data has rendered it essential to many fields such as healthcare. This article introduces you to artificial intelligence, how it works, and what its central role in biomedical engineering is. It brings to light new developments in medical science, why it is being applied in biomedicine, key problems in computer vision and AI, medical applications, diagnostics, and live health monitoring. This paper starts with an introduction to artificial intelligence and its major subfields before moving into how AI is revolutionizing healthcare technology. There is a lot of emphasis on how it will transform biomedical engineering through the use of AI-based devices like biosensors. Not only can these machines detect abnormalities in a patient’s physiology, but they also allow for chronic health tracking. Further, this review also provides an overview of the trends of AI-enabled healthcare technologies and concludes that the adoption of artificial intelligence in healthcare will be very high. The most promising are in diagnostics, with highly accurate, non-invasive diagnostics such as advanced imaging and vocal biomarker analyzers leading medicine into the future.
Isolation of OsMetAP10, a Peptidase_M24 Superfamily Gene, Regulating Heading Date in Rice
Authors: Sun Quanyi , Zhao Jianhua , Wang Guangda , Wang Yu , Zhu Yuntao , Yan Yu , Chen Zihang , Chen Zongxiang , Feng Zhiming , Zuo Shimin
Published: February 2025

The heading date is one of the important traits in rice, which greatly affects grain yield and regional adaptability. Although the flowering pathways in rice have been extensively investigated, the genes involved in flowering remain largely unknown. Here, we report a rice lhd mutant, which showed late flowering under both long-day (LD) and short-day (SD) conditions. Through MutMap+ and linkage analysis, a deletion mutation in OsMetAP10 was inferred as the most likely candidate for lhd late flowering. OsMetAP10 encodes a methionine aminopeptidase that belongs to the peptidase_M24 subfamily III. The OsMetAP10 gene is constitutively expressed in rice and is induced by light, with a rhythmic expression pattern. OsMetAP10 knockout lines displayed late heading as the lhd mutation, while no alternations in morphology and heading were observed on OsMetAP10 overexpression lines, further confirming the mutation of OsMetAP10 as responsible for the late heading of lhd. Through RT-qPCR and transcriptome analysis, we revealed that the upregulated expression of the FT-like gene OsFLT4, a negatively flowering regulator, and the downregulation of flower development-related genes, OsMADS14, OsMADS15, and OsMADS34, played critical roles in determining the late flowering of the OsMetAP10 mutation. This study reports a new gene affecting flowering and provides a new insight into the role of OsMetAP10 in regulating rice heading.
Microbiota–Gut–Brain Axis: Mass-Spectrometry-Based Metabolomics in the Study of Microbiome Mediators—Stress Relationship
Authors: Interino Nicolò , Vitagliano Rosalba , D’Amico Federica , Lodi Raffaele , Porru Emanuele , Turroni Silvia , Fiori Jessica
Published: February 2025

The microbiota–gut–brain axis is a complex bidirectional communication system that involves multiple interactions between intestinal functions and the emotional and cognitive centers of the brain. These interactions are mediated by molecules (metabolites) produced in both areas, which are considered mediators. To shed light on this complex mechanism, which is still largely unknown, a reliable characterization of the mediators is essential. Here, we review the most studied metabolites in the microbiota–gut–brain axis, the metabolic pathways in which they are involved, and their functions. This review focuses mainly on the use of mass spectrometry for their determination, reporting on the latest analytical methods, their limitations, and future perspectives. The analytical strategy for the qualitative–quantitative characterization of mediators must be reliable in order to elucidate the molecular mechanisms underlying the influence of the above-mentioned axis on stress resilience or vulnerability.
Crumbling Pathogenesis and Biomarkers for Diabetic Peripheral Neuropathy
Authors: Chong Zhao Zhong , Souayah Nizar
Published: February 2025

Background: Diabetic sensorimotor polyneuropathy (DSP) is a common chronic diabetic complication. Traditionally, DSP was once considered irreversible with a typical loss of axon. However, the superimpose of acquired demyelination on axonal loss in DSP patients has been observed, implying that DSP may be preventable or reversible, particularly within a subgroup of patients exhibiting early-stage acquired demyelination, underscoring the critical importance of identifying early prognostic markers. Methods: We systemically review the literature on the roles of biomarkers in predicting DSP and monitoring the progress. The underlying mechanisms of biomarkers were also discussed. Results: The pathogenesis of DSP is multifaceted, with various pathological mechanisms contributing to its development. Key mechanisms include aberrant glucose metabolism and induction of oxidative stress and inflammation. Several pathological processes, such as disrupted glucose metabolism, nerve damage, impaired microcirculation, genetic variants, and microRNA dysregulation, lead to molecular and protein changes that may be detectable in blood and other biological compartments, thus serving as potential biomarkers for DSP progression. However, the utility of a biomarker depends on its predictive accuracy, practicality, and ease of measurement. Conclusions: Most biomarkers for predicting DSP have demonstrated suboptimal predictive value, and many lack established accuracy in forecasting DSP progression. Consequently, the diagnostic utility of any single biomarker remains limited. A comprehensive combination of biomarkers from various categories may hold incredible promise for accurate detection. As artificial intelligence (AI) techniques, especially machine learning, rapidly advance, these technologies may offer significant potential for developing diagnostic platforms to integrate and interpret complex biomarker data for DSP.
A Narrative Review of the Efficacy of Long COVID Interventions on Brain Fog, Processing Speed, and Other Related Cognitive Outcomes
Authors: Whitaker-Hardin Bryana , McGregor Keith M. , Uswatte Gitendra , Lokken Kristine
Published: February 2025

In the years following the global emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), or COVID-19, researchers have become acutely aware of long-term symptomology associated with this disease, often termed long COVID. Long COVID is associated with pervasive symptoms affecting multiple organ systems. Neurocognitive symptoms are reported by up to 40% of long COVID patients, with resultant effects of loss of daily functioning, employment issues, and enormous economic impact and high healthcare utilization. The literature on effective, safe, and non-invasive interventions for the remediation of the cognitive consequences of long COVID is scarce and poorly described. Of specific interest to this narrative review is the identification of potential interventions for long COVID-associated neurocognitive deficits. Articles were sourced from PubMed, EBSCO, Scopus, and Embase following Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Articles published between the dates of January 2020 and 30 June 2024 were included in the search. Twelve studies were included in the narrative review, including a feasibility study, a pilot study, a case series, a case study, and an observational study, in addition to three randomized clinical trials and four interventional studies. Overall, treatment interventions such as cognitive training, non-invasive brain stimulation therapy, exercise rehabilitation, targeted pharmacological intervention, and other related treatment paradigms show promise in reducing long COVID cognitive issues. This narrative review highlights the need for more rigorous experimental designs and future studies are needed to fully evaluate treatment interventions for persistent cognitive deficits associated with long COVID.
Application of Omics Analyses in Pediatric B-Cell Acute Lymphoblastic Leukemia
Authors: Vllahu Megi , Savarese Maria , Cantiello Immacolata , Munno Carmen , Sarcina Rosalba , Stellato Pio , Leone Ornella , Alfieri Mariaevelina
Published: February 2025

Acute lymphoblastic leukemia (ALL) is the most common pediatric cancer, comprising almost 25% of all malignancies diagnosed in children younger than 20 years, and its incidence is still increasing. ALL is a blood cancer arising from the unregulated proliferation of clonal lymphoid progenitor cells. To make a diagnosis of B-cell ALL, bone marrow morphology and immunophenotyping are needed; cerebrospinal fluid examination, and chromosomal analysis are currently used as stratification exams. Currently, almost 70% of children affected by B-cell ALL are characterized by well-known cytogenetic abnormalities. However, the integration of results with “omic” techniques (genomics, transcriptomics, proteomics, and metabolomics, both individually and integrated) able to analyze simultaneously thousands of molecules, has enabled a deeper definition of the molecular scenario of B-cell ALL and the identification of new genetic alterations. Studies based on omics have greatly deepened our knowledge of ALL, expanding the horizon from the traditional morphologic and cytogenetic point of view. In this review, we focus our attention on the “omic” approaches mainly used to improve the understanding and management of B-cell ALL, crucial for the diagnosis, prognosis, and treatment of the disease, offering a pathway toward more precise and personalized therapeutic interventions.
Gut–Brain Axis and Brain Microbiome Interactions from a Medical Perspective
Authors: Arneth Borros
Published: February 2025

Background: The gut microbiome directly impacts brain health and activity, meaning the two are closely associated. This relationship suggests a link between microbial imbalances and diseases such as Alzheimer’s, although multiple other contributing factors, such as genetics, also play a part. Additionally, recent studies discovered that cerebrospinal fluid has some microbial deoxyribonucleic acid (DNA), which can be interpreted to mean a microbiome exists in the brain too. The vagus nerve and the central nervous and immune systems are responsible for the connection between the brain and gut microbiome. Aims and Objectives: The main aim of this systematic review is to analyze existing research on the gut–brain axis and the brain microbiome to fill the current knowledge gap. Materials and Methods: A search was conducted on the PubMed database based on a set of predefined MeSH terms. Results: After the search, 2716 articles meeting the MeSH parameters were found in PubMed. This list was then downloaded and analyzed according to the inclusion/exclusion criteria, and 63 relevant papers were selected. Discussion: Bacteria in the gut microbiome produce some substances that are considered neuroactive. These compounds can directly or indirectly affect brain function through the gut–brain axis. However, various knowledge gaps on the mechanisms involved in this connection need to be addressed first.
From Veterinary Medicine to Illicit Drug Supply: Utilising Social Media to Explore the Rising Emergence of Veterinary Medicines in Human Health
Authors: Dunn Josie , Schifano Fabrizio , Dudley Ed , Arillotta Davide , Guirguis Amira
Published: February 2025

Background/Objectives: The misuse of veterinary drugs is a growing concern, with increasing evidence of their presence in illicit drug markets and their use as alternatives to traditional substances. Methods: This study explores Reddit discussions on the misuse of veterinary drugs on Reddit, focusing on xylazine, carfentanil, medetomidine, pentobarbital, phenylbutazone, and acepromazine. Reddit was utilised for its abundant real-time data on users’ thoughts and experiences with substance misuse. Through a combination of manual and Artificial Intelligence (AI)-driven thematic analysis, we examined posts and comments to explore patterns of misuse. Results: The themes analysed included adverse effects, polysubstance misuse, routes of administration, motivations for misuse, and methods of obtaining these drugs. Our findings revealed that xylazine, medetomidine, carfentanil, and pentobarbital exhibit significant potential for misuse, while phenylbutazone and acepromazine are not widely misused. Despite this, phenylbutazone and acepromazine have been identified as adulterants in the illicit drug supply in the United States. The most discussed themes included motivations for misuse, followed by public experiences and perceptions, as well as adverse effects. Conclusions: The dual-method approach of combining manual interpretation with AI analysis allowed for a comprehensive understanding of social media discussions. This research highlights the importance of monitoring online platforms for early indicators of emerging drug trends, offering valuable insights to inform public health policies and intervention strategies. Impact Statement: This research highlights the growing public health risk posed by veterinary drug misuse, underscoring the need for enhanced monitoring, regulatory frameworks, and education to address their diversion into illicit markets. By leveraging social media as an early detection tool for emerging drug trends, our findings can inform targeted interventions.
Exploring the Roles of Entrepreneurial Education, Proactive Personality and Creative Self-Efficacy in the Formation of Undergraduates’ New Venture Ideas in China
Authors: Hu Rui , Li Caiyun
Published: February 2025

A new venture idea is the prerequisite for discovering or building an entrepreneurial opportunity and also the foundation for undergraduates to start a new venture. Based on social cognitive theory, this paper explores the roles of entrepreneurial education, proactive personality, and creative self-efficacy in the formation of undergraduates’ new venture ideas. Using a sample of 650 undergraduates in China, we find that entrepreneurial education and proactive personality are both positively related to new venture idea formation, and proactive personalities also moderate the relationship between entrepreneurial education and new venture ideas. In addition, creative self-efficacy plays a mediating role in those direct effects mentioned above. That is, entrepreneurial education and a proactive personality can both promote the formation of undergraduates’ new venture ideas through creative self-efficacy. These results have practical significance for entrepreneurial education in universities, especially for fostering undergraduates’ creative self-efficacy.
Application of Pillared Clays for Water Recovery
Authors: Romero Rubi
Published: February 2025

In recent years, efforts have been made in developing new and more efficient water purification methods and the synthesis of catalysts with greater catalytic activity that are more stable and can be used in wide pH ranges. Pillared clays represent a viable alternative for removing organic contaminants. The clays, usually smectites, are modified by inserting inorganic pillars (Al, Zr, Cr, Fe, Ti, Ga, and Mn) between the layers of the clay, increasing its surface area, porosity, catalytic activity, and thermal stability. This review describes the importance of using pillared clays with different polyoxycations in Fenton, photo-Fenton, ozonation, wet catalytic oxidation of hydrogen peroxide, and photocatalysis processes. Pillared iron clays (Fe-PILCs) are promising catalysts capable of generating hydroxyl radicals that can oxidize organic contaminants, thus facilitating their removal. The current challenges of the PILC application at industrial scale are also discussed.
Withaferin A Attenuates Muscle Cachexia Induced by Angiotensin II Through Regulating Pathways Activated by Angiotensin II
Authors: Kakar Sham S. , Vemuri Vasa , Ratajczak Mariusz Z.
Published: February 2025

Cachexia is a multifactorial syndrome characterized by severe muscle wasting and is a debilitating condition frequently associated with cancer. Previous studies from our group revealed that withaferin A (WFA), a steroidal lactone, mitigated muscle cachexia induced by ovarian tumors in NSG mice. However, it remains unclear whether WFA’s protective effects are direct or secondary to its antitumor properties. We developed a cachectic model through continuous angiotensin II (Ang II) infusion in C57BL/6 mice to address this issue. Ang II infusion resulted in profound muscle atrophy, evidenced by significant reductions in grip strength and in the TA, GA, and GF muscle mass. Molecular analyses indicated elevated expression of inflammatory cytokines (TNFα, IL-6, MIP-2, IL-18, IL-1β), NLRP3 inflammasome, and genes associated with the UPS (MuRF1, MAFBx) and autophagy pathways (Bacl1, LC3B), along with suppression of anti-inflammatory heme oxygenase-1 (HO-1) and myogenic regulators (Pax7, Myod1). Strikingly, WFA treatment reversed these pathological changes, restoring muscle mass, strength, and molecular markers to near-normal levels. These findings demonstrate that WFA exerts direct anti-cachectic effects by targeting key inflammatory and atrophic pathways in skeletal muscle, highlighting its potential as a novel therapeutic agent for cachexia management.
Activation of the Coagulation Cascade as a Universal Danger Sign
Authors: Starikova Eleonora A. , Mammedova Jennet T. , Rubinstein Artem A. , Sokolov Alexey V. , Kudryavtsev Igor V.
Published: February 2025

Hemostasis is a mechanism that stops bleeding from an injured vessel, involves multiple interlinked steps, culminating in the formation of a “clot” sealing the damaged area. Moreover, it has long been recognized that inflammation also provokes the activation of the coagulation system. However, there has been an increasing amount of evidence revealing the immune function of the hemostasis system. This review collects and analyzes the results of the experimental studies and data from clinical observations confirming the inflammatory function of hemostasis. Here, we summarize the latest knowledge of the pathways in immune system activation under the influence of coagulation factors. The data analyzed allow us to consider the components of hemostasis as receptors recognizing «foreign» or damaged «self» or/and as «self» damage signals that initiate and reinforce inflammation and affect the direction of the adaptive immune response. To sum up, the findings collected in the review allow us to classify the coagulation factors, such as Damage-Associated Molecular Patterns that break down the conventional concepts of the coagulation system.
Diagnostic Approaches in Myeloid Sarcoma
Authors: Patkowska Elzbieta , Krzywdzinska Agnieszka , Solarska Iwona , Wojtas Magdalena , Prochorec-Sobieszek Monika
Published: February 2025

Myeloid sarcoma (MS), or extramedullary acute myeloid leukaemia tumour (eAML), is a rare hematopoietic neoplasm. Recognised as a distinct entity within acute myeloid leukaemia (AML), MS presents significant diagnostic challenges due to its rarity, clinical heterogeneity, and variable immunophenotypic and genetic characteristics. The mechanisms by which leukaemic stem cells (LSCs) migrate to form solid tumours in extramedullary (EM) sites remain unclear. MS can occur de novo, precede AML, and manifest alongside AML relapse. It can also develop with myelodysplastic syndromes (MDSs) or myeloproliferative neoplasms (MPNs). MS frequently presents in organs such as the skin, lymph nodes, gastrointestinal (GI) tract, and central nervous system (CNS), often resulting in diverse clinical manifestations. Diagnosis relies on a comprehensive approach, including tissue biopsy, bone marrow (BM) evaluation, and advanced imaging modalities. Accurate diagnosis is crucial for risk stratification and treatment selection. Prognosis is influenced by several factors: MS’s anatomical location, timing of MS diagnosis, genetic profile, and possible treatment. This review emphasises the need for comprehensive diagnostic methods to better define individual MS characteristics and prognosis. It explores the role of novel targeted therapies in improving patient outcomes and further highlights the critical need for future multicentre data collection to optimise diagnostic and therapeutic approaches.
Progress in Plastic Work–Heat Conversion of Metallic Crystals
Authors: Yue Peng-Fei , Yang Shao-Dan , Gao Yan , Shi Rong-Hao , Zhang Guo-Shang , Zhu Zhi-Yuan , Han Dong , Song Ke-Xing
Published: February 2025

The Taylor–Quinney coefficient (TQC) is a critical parameter quantifying the thermal conversion of plastic work during deformation in metallic crystals. This review provides a comprehensive summary of recent advances in TQC research, spanning experimental, theoretical, and computational perspectives. The fundamental principles of the TQC are introduced, emphasizing its thermodynamic background and dependence on microstructural features. Experimental studies demonstrate how the strain rate, temperature, and microstructure influence the TQC, with advanced techniques such as infrared thermography and high-speed imaging enabling precise measurements under dynamic conditions. Theoretical models, including internal variable frameworks and nonequilibrium thermodynamics, offer insights into the energy distribution mechanisms and provide predictive capabilities across diverse loading scenarios. Computational simulations, using methods like finite element analysis and molecular dynamics, reveal multiscale thermal conversion mechanisms and the role of dislocation motion and localized heat accumulation in governing TQC values. Challenges and opportunities for TQC research are highlighted, including the need for multiscale modeling, the exploration of complex stress states, and applications under extreme environments. Future directions should focus on integrating advanced experimental techniques and computational models to optimize material design and performance. This review aims to deepen the understanding of the TQC and its implications for energy dissipation and material reliability in high-performance applications.
A State-of-the-Art Review of Ophthalmological Indications for a Cesarean Section: Is There a Patient for Whom a Cesarean Section Is Really Indicated?
Authors: Quaresima Paola , Covello Giuseppe , Bitonti Giovanna , Di Carlo Costantino , Morelli Michele , Guido Maurizio
Published: February 2025

Purpose: Our purpose was to review the current literature regarding ophthalmologic indications for cesarean section (CS). Methods: A literature search was conducted using MEDLINE, Embase, and the Cochrane Library from inception through October 2024. The databases were searched using the following keywords: “Caesarean section” OR “Caesarean section” OR “delivery” OR “pregnancy” AND “eyes” OR “eye disorders” OR “ocular disease” OR “diabetic retinopathy” OR “myopia” OR “retinal detachment” OR “glaucoma” OR “keratoconus”. Studies were considered eligible if they described pregnancy management in women affected by an eye disorder, with insight into the mode of delivery. Results: A total of 8383 results were identified, including only 1 specific guideline and no randomized controlled trials. After a manual review, 38 manuscripts were selected for inclusion. Based on the available evidence, an elective CS may be considered on a case-by-case basis in the presence of specific ophthalmic conditions, such as high-grade myopia with subretinal neovascularization, proliferative diabetic retinopathy, advanced glaucoma, or advanced keratoconus. These conditions are rare among women of childbearing age. Conclusions: Currently, only a limited number of highly specific ophthalmic conditions may benefit from an elective CS. Considering the potential short- and long-term implications of a CS, and in line with the current World Health Organization recommendations, this surgical procedure should be reserved for cases with a clear indication. Given the paucity of data in the available literature, further prospective randomized controlled trials are necessary to enhance the quality of evidence.