bluuebunny/crossref_metadata_2025 huggingface dataset:
A Comprehensive Regional Approach to Eco-Efficiency in Spanish Agriculture over Time
Authors: Rodríguez-Fernández María Pilar , Hidalgo-González Cristina , Pérez-Neira David
Published: February 2025

Eco-efficiency, which integrates environmental and economic variables, is crucial for decision-making in agriculture, particularly within the framework of European environmental policy. The SBM-DEA tool has been applied in several studies, and facilitates the optimization of greenhouse gas (GHG) emissions in the agricultural sector. Despite the significance of the Spanish agricultural economy at both European and international levels, the analysis of its eco-efficiency is limited and fragmented, and does not consider the regional disparities within the country. The objective of this study is therefore to assess the eco-efficiency of the Spanish regional agricultural sector during the period from 2004 to 2022, considering its regional and productive differences. This has been achieved using data from the Farm Accounting Network and the non-oriented SBM-DEA method with constant returns to scale. The eco-efficiency of the Spanish regional agricultural sector as a whole was estimated to range from 0.644 to 0.837, with an average value of 0.772 for the period analyzed. Forty-seven percent of the regions exceeded the average eco-efficiency. The data indicate significant opportunities to improve eco-efficiency and reduce GHG emissions at both the national (65.6%) and regional (ranging from 7.4 to 86.5%) levels. This paper discusses the need to develop regionalized strategies to optimize resource allocation and reduce greenhouse gas emissions within the Common Agricultural Policy.
Behavioural Engagement of Holstein Friesian Dairy Cattle with Different Mounting Techniques for Salt Licks as Environmental Enrichment
Authors: McLaughlin Danielle Lauren , Blackie Nicola
Published: February 2025

With increasing numbers of dairy farms adopting zero-grazing systems, there is a growing need for indoor environmental enrichment methods. Enrichment is necessary to meet industry requirements and fulfil behavioural motivations, such as oral manipulation. This study evaluated the magnitude with which Holstein Freisen cows would interact with salt lick enrichment blocks based on the mounting design. Holstein Freisen dairy cows (n = 55) were recruited from a UK dairy farm and observed over a 4-week period (n = 20 days). Three different mounting designs were utilized, low non-moveable (LNM), low moveable (LM), and high moveable (HM), and the LNM setup was repeated on week 4. These mounting designs were each observed over a five-day period and then removed for two days in-between. Data were collected by in-person observation and included cow IDs, instances of interaction, and kilograms of salt lick used per setup. The data were analysed through IBM SPSS Statistics via a One-Way Repeated Measures ANOVA and Microsoft Excel to determine significant findings and habituation. The number of new interactions significantly decreased in the HM setup compared to the LM and LNM. The supporting data of kilograms of salt lick used and total percentage of the herd utilizing the blocks, also favoured the LM setups over LNM. The LNM setup was repeated on the final week to assess the level with which cows had habituated to the environmental enrichment. Despite a significant difference between week 1 and week 4, the trends of cow interactions showed individual variability in habituation and overall negligible herd-level habituation. These findings suggest that the use of mineral licks within a dairy herd serves as effective environmental enrichment, even over extended time periods, and when implemented they are best used at low heights with the ability to have free movement. When implemented on a farm, the LM mounting design should increase the herd-level uptake of enrichment leading to a reduction in stereotypies and fulfilment of oral motivation, which is beneficial for overall cow health and welfare.
The Pathological and Histopathological Findings in Cats with Clinically Recognised Hypertrophic Cardiomyopathy Are Related to the Severity of Clinical Signs and Disease Duration
Authors: Janus-Ziółkowska Izabela , Bubak Joanna , Ciaputa Rafał , Kandefer-Gola Małgorzata , Noszczyk-Nowak Agnieszka
Published: February 2025

Hypertrophic cardiomyopathy (HCM) is the most frequent type of cardiac disease in cats. Due to its high prevalence and risk of sudden and severe signs, the disease is an important topic of various research. Despite the focus on the clinical course of the disease, studies presenting the pathological and histopathological patterns are rare. The study was conducted as a retrospective analysis of feline patients subjected to postmortem examination in the Cardiopathology Unit due to a clinical diagnosis of hypertrophic cardiomyopathy based on echocardiographic examination and ACVIM guidelines. Thirty-four cats clinically diagnosed with HCM were enrolled in the study. During the postmortem examination, hearts were subjected to gross morphometric and histopathological evaluation. Our results show that the histopathological pattern in cats with clinically stated HCM is very diverse, affecting both ventricles and atria. The histopathological picture is more complex in animals diagnosed earlier and treated for a longer period. Moreover, it is generally unrelated to wall thickness, with only left ventricular fibrosis affecting the thickness of the left ventricular wall. In conclusion, further research combining clinical and pathological results is required to unambiguously determine the histopathological remodelling that takes place in the myocardium of cats with hypertrophic cardiomyopathy.
A Multiscale CNN-Based Intrinsic Permeability Prediction in Deformable Porous Media
Authors: Heider Yousef , Aldakheel Fadi , Ehlers Wolfgang
Published: February 2025

This work introduces a novel application for predicting the macroscopic intrinsic permeability tensor in deformable porous media, using a limited set of μ-CT images of real microgeometries. The primary goal is to develop an efficient, machine learning (ML)-based method that overcomes the limitations of traditional permeability estimation techniques, which often rely on time-consuming experiments or computationally expensive fluid dynamics simulations. The novelty of this work lies in leveraging convolutional neural networks (CNNs) to predict pore-fluid flow behavior under deformation and anisotropic flow conditions. The approach utilizes binarized CT images of porous microstructures to predict the permeability tensor, a crucial parameter in continuum porous media flow modeling. The methodology involves four steps: (1) constructing a dataset of CT images from Bentheim sandstone at varying volumetric strain levels; (2) conducting pore-scale flow simulations using the lattice Boltzmann method (LBM) to obtain permeability data; (3) training the CNN model with processed CT images as inputs and permeability tensors as outputs; and (4) employing techniques like data augmentation to enhance model generalization. Examples demonstrate the CNN’s ability to accurately predict the permeability tensor in connection with the deformation state through the porosity parameter. A source code has been made available as open access.
From a Spectrum to Diagnosis: The Integration of Raman Spectroscopy and Chemometrics into Hepatitis Diagnostics
Authors: Kashif Muhammad , Byrne Hugh J.
Published: February 2025

Hepatitis, most importantly hepatitis B and hepatitis C, is a significant global health concern, requiring an accurate and early diagnosis to prevent severe liver damage and ensure effective treatment. The currently employed diagnostic methods, while effective, are often limited in their sensitivity, specificity, and rapidity, and the quest for improved diagnostic tools is ongoing. This review explores the innovative application of Raman spectroscopy combined with a chemometric analysis as a powerful diagnostic tool for hepatitis. Raman spectroscopy offers a non-invasive, rapid, and detailed molecular fingerprint of biological samples, while chemometric techniques enhance the interpretation of complex spectral data, enabling precise differentiation between healthy and diseased states and moreover the severity/stage of disease. This review aims to provide a comprehensive overview of the current research, foster greater understanding, and stimulate further innovations in this burgeoning field. The Raman spectrum of blood plasma or serum provides fingerprints of biochemical changes in the blood profile and the occurrence of disease simultaneously, while Raman analyses of polymerase chain reaction/hybridization chain reaction (PCR/HCR)-amplified nucleic acids and extracted DNA/RNA as the test samples provide more accurate differentiation between healthy and diseased states. Chemometric tools enhance the diagnostic efficiency and allow for quantification of the viral loads, indicating the stage of disease. The incorporation of different methodologies like surface enhancement and centrifugal filtration using membranes provides the ability to target biochemical changes directly linked with the disease. Immunoassays and biosensors based on Raman spectroscopy offer accurate quantitative detection of viral antigens or the immune response in the body (antibodies). Microfluidic devices enhance the speed of detection through the continuous testing of flowing samples. Raman diagnostic studies with massive sample sizes of up to 1000 and multiple reports of achieving a greater than 90% differentiation accuracy, sensitivity, and specificity using advanced multivariate data analysis tools indicate that Raman spectroscopy is a promising tool for hepatitis detection. Its reproducibility and the identification of unique reference spectral features for each hepatic disease are still challenges in the translation of Raman spectroscopy as a clinical tool, however. The development of databases for automated comparison and the incorporation of automated chemometric processors into Raman diagnostic tools could pave the way for their clinical translation in the near future.
Analysis of Corrosion-Mechanical Properties of Electroplated and Hot-Dip Zinc Coatings on Mechanically Pre-Treated Steel Substrate
Authors: Lozrt Jaroslav , Votava Jiří , Kumbár Vojtěch , Polcar Adam
Published: February 2025

This study evaluates the effects of three mechanical pre-treatment methods on S235JRG2 steel sheets: blasting with a synthetic corundum (F40), blasting with steel shot (S170), and grinding with synthetic corundum (P40). Untreated samples served as a reference. The analysis of mechanical pre-treatments focused on surface integrity, including measurements of surface roughness parameters Ra and Rz (ISO 21920-2) and subsurface microhardness (ISO 6507-1). Zinc coatings were assessed through mechanical testing (cupping test, ISO 1520) and corrosion testing in a neutral salt spray environment (ISO 9227), with results evaluated using digital image analysis. Experimental findings indicate that electroplated zinc deposition rates are influenced by surface roughness, while subsurface microhardness has no significant effect. In contrast, for hot-dip galvanizing, both parameters impact the process. The mechanical properties of electroplated zinc coatings are further affected by steel surface integrity, whereas hot-dip zinc coatings are primarily governed by intermetallic phase formation, making the influence of steel surface integrity statistically negligible. Corrosion testing revealed that blasting with a synthetic corundum is particularly unsuitable, as it leads to numerous inhomogeneities in both coating types, accelerating corrosion degradation.
Scanning Electron Microscopy Techniques in the Analysis of Gunshot Residues: A Literature Review
Authors: Sacco Matteo Antonio , Gualtieri Saverio , Santos Agostinho , Mendes Bárbara , Raffaele Roberto , Tarallo Alessandro Pasquale , Verrina Maria Cristina , Ranno Francesco , Monterossi Maria Daniela , Ricci Pietrantonio , Aquila Isabella
Published: February 2025

The analysis of gunshot residues (GSRs) is a critical component of criminal investigations, linking suspects to firearms or shooting incidents. Among the various analytical techniques employed, scanning electron microscopy (SEM) has emerged as a valuable tool due to its ability to provide high-resolution imaging and detailed elemental composition analysis of GSR particles. Recent technological advancements have significantly enhanced the effectiveness of SEM in GSR analysis, incorporating improved detectors and software that facilitate the more accurate detection and characterization of GSR particles. To ensure the reliability of SEM-based GSR analysis, it is essential to adhere to established methodologies for sample collection and preparation, as well as to implement best practices in data interpretation within the forensic context. Through a narrative review, this paper aims to explore the application of SEM techniques for GSR analysis, elucidate the methodological approaches that underpin effective forensic investigations, and highlight the advantages and limitations of SEM, thereby addressing the ongoing challenges and opportunities in the field.
Comprehensive Evaluation of Conveyor Belt Impact Resistance Using Canonical Correlation Analysis
Authors: Andrejiova Miriam , Grincova Anna , Marasova Daniela
Published: February 2025

The aim of the research was to comprehensively evaluate the impact resistance of conveyor belts. Initially, variables were identified that describe the input conditions of the experiment (weight of impacting material, impact height, type and strength of conveyor belt) and subsequent dependent variables that describe the result of the experiment (impact force, increase in tension force, relative amount of absorbed energy, degree of damage). For each dependent variable, its dependence on input variables was monitored through multiple regression analysis. In the next step, through canonical correlation analysis, correlations were observed between the created dummy canonical variables that are a linear combination of the original variables. Based on the results, strong relationships between new canonical variables were demonstrated. A test of significance of canonical correlation using Wilk’s lambda showed that the first to third canonical correlations were statistically significant. It turns out that in the first pair of canonical variables, the strength and type of conveyor belt are strongly negatively correlated with the increase in tension force and the relative amount of energy absorbed. In the second pair, the impact height and weight of the landing material are strongly positively correlated with the impact force.
A Quasi-Explicit Method Applied to Missing Boundary Data Reconstruction for the Stokes System
Authors: Alharbi Abdulaziz H. , Jday Fadhel , Albidah Abdulrahman B. , Alhartomi Ali M.
Published: February 2025

In this paper, we study the data completion problem for the Cauchy–Stokes equation in a cylindrical domain, Ω. Neumann and Dirichlet boundary conditions are prescribed on part of the overdetermined boundary, Γ0, and the goal is to complete the data on the other part of the boundary, Γa. Here, Γ0 and Γa represent the side faces of the cylinder Ω. This problem is known to be ill-posed and is formulated as an optimal control problem with a regularized cost function. To directly approximate the missing data on Γa, we employ the method of factorization of elliptic boundary value problems. This technique allows the factorization of a boundary value problem into a product of parabolic problems. It is successfully applied to the optimality system in this work, yielding new and significant results.
On Topologies on Simple Graphs and Their Applications in Radar Chart Methods
Authors: Alzubaidi Husniyah , Kočinac Ljubiša D. R. , Othman Hakeem A.
Published: February 2025

This paper introduces a novel topology (upper approximated G-topology) on vertex sets of graphs using rough upper approximation neighborhoods, extending prior work on graph-induced topologies. Key results include characterizing discrete/indiscrete topologies for complete graphs, cycle graphs, and bipartite graphs (Theorems 1–3). The discrete topology for cycle graphs Cn, n>5, is particularly insightful. Exploring further, we delve into the continuity and isomorphism of graph mappings. Subsequently, we apply these findings to enhance radar chart graphical methods through the analysis of corresponding graph structures. These applications demonstrate practical relevance, linking graph structures to data visualization.
Synthesis and Electrochemical Characterization of Dissymmetric Tetrathiafulvalene Derivatives for Aqueous Rechargeable Batteries
Authors: Rodrigues João F. G. , Santos Isabel C. , Rabaça Sandra , Santos Diogo M. F.
Published: February 2025

Organic electroactive materials (OEMs) offer advantages such as cost-effectiveness, environmental sustainability, and simplified end-of-life processing compared to inorganic electrode materials. Aqueous electrolytes further enhance sustainability and safety relative to organic electrolytes. Investigating the electrochemical properties of OEMs in aqueous media provides valuable insights into their redox behavior and stability under such conditions. However, challenges remain, including low electronic conductivity and structural stability concerns, while aqueous rechargeable batteries (ARBs) face inherent energy density limitations. Tetrathiafulvalene (TTF) has been previously reported as an electrode material for ARBs, while its oligomers have been proposed for organic electrolyte batteries. This study focuses on the synthesis and characterization of two new dissymmetric TTF derivatives—cyanobenzene tetrathiafulvalene pyrazine (CNB-TTF-Pz) (1) and 4-cyanobenzene tetrathiafulvalene pyrazine (4-CNB-TTF) (2)—as well as one symmetric TTF derivative, dipyrazine tetrathiafulvalene ((Pz)2-TTF) (3). Their electrochemical behavior in aqueous lithium and potassium nitrate electrolytes was systematically characterized using cyclic voltammetry. The study provides insights into the redox properties and electroactivity of these compounds, highlighting challenges related to low electronic conductivity and redox potentials close to the water stability limits. These findings contribute to broadening our understanding of the electrochemical properties of TTF derivatives in aqueous electrolytes and offer a preliminary assessment of their potential application as electrodes for ARBs.
High-Volume Battery Recycling: Technical Review of Challenges and Future Directions
Authors: Rehman Sheikh , Al-Greer Maher , Burn Adam S. , Short Michael , Cui Xinjun
Published: February 2025

The growing demand for lithium-ion batteries (LIBs), driven by their use in portable electronics and electric vehicles (EVs), has led to an increasing volume of spent batteries. Effective end-of-life (EoL) management is crucial to mitigate environmental risks and prevent depletion of valuable raw materials like lithium (Li), cobalt (Co), nickel (Ni), and manganese (Mn). Sustainable, high-volume recycling and material recovery are key to establishing a circular economy in the battery industry. This paper investigates challenges and proposes innovative solutions for high-volume LIB recycling, focusing on automation for large-scale recycling. Key issues include managing variations in battery design, chemistry, and topology, as well as the availability of sustainable raw materials and low-carbon energy sources for the recycling process. The paper presents a comparative study of emerging recycling techniques, including EV battery sorting, dismantling, discharge, and material recovery. With the expected growth in battery volume by 2030 (1.4 million per year by 2040), automation will be essential for efficient waste processing. Understanding the underlying processes in battery recycling is crucial for enabling safe and effective recycling methods. Finally, the paper emphasizes the importance of sustainable LIB recycling in supporting the circular economy. Our proposals aim to overcome these challenges by advancing automation and improving material recovery techniques.
Triggering Pyroptosis in Cancer
Authors: Johnson Daniel E. , Cui Zhibin
Published: February 2025

Pyroptosis is an inflammatory programmed cell death recently identified as a crucial cellular process in various diseases, including cancers. Unlike other forms of cell death, canonical pyroptosis involves the specific cleavage of gasdermin by caspase-1, resulting in cell membrane damage and the release of the pro-inflammatory cytokines IL-1β and IL-18. Initially observed in innate immune cells responding to external pathogens or internal death signals, pyroptotic cell death has now been observed in numerous cell types. Recent studies have extensively explored different ways to trigger pyroptotic cell death in solid tumors, presenting a promising avenue for cancer treatment. This review outlines the mechanisms of both canonical and noncanonical pyroptosis pertinent to cancer and primarily focuses on various biomolecules that can induce pyroptosis in malignancies. This strategy aims not only to eliminate cancer cells but also to promote an improved tumor immune microenvironment. Furthermore, emerging research indicates that targeting pyroptotic pathways may improve the effectiveness of existing cancer treatments, making them more potent against resistant tumor types, offering new hope for overcoming treatment resistance in aggressive malignancies.
From Metabolic Syndrome to Cardio-Kidney-Metabolic Syndrome in the SIMETAP Study: Prevalence Rates of Metabolic Syndrome and Its Independent Associations with Cardio-Renal-Metabolic Disorders Other than Its Defining Criteria
Authors: Ruiz-García Antonio , Arranz-Martínez Ezequiel , Serrano-Cumplido Adalberto , Cinza-Sanjurjo Sergio , Escobar-Cervantes Carlos , Polo-García José , Pallarés-Carratalá Vicente
Published: February 2025

Background/Objectives: Metabolic syndrome (MetS) is a highly prevalent entity defined according to cardiometabolic criteria. Other disorders related to MetS could help assess the comprehensive risk of diabetes, cardiovascular disease, and chronic kidney disease (CKD). This study aimed to update the prevalence rates of MetS and to assess its relationship with other disorders and clinical conditions other than the criteria defining MetS. Methods: A cross-sectional observational study was conducted with a random population-based sample of 6588 study subjects between 18 and 102 years of age. Crude and sex- and age-adjusted prevalence rates of MetS were calculated, and their associations with comorbidities and clinical conditions other than their defining criteria were assessed by bivariate and multivariate analysis. Results: The adjusted prevalence rates were 36.0% for MetS (39.8% in men; 33.5% in women), 21.5% for premorbid Mets, and 14.5% for morbid MetS. Considering only clinical conditions other than the criteria defining MetS, the independent disorders associated with premorbid MetS were hypercholesterolemia, hypertension, high levels of lipid accumulation product, high triglyceride-glucose index (TyG), high visceral adiposity index, high fatty liver index, and high waist-to-height ratio (WtHR), highlighting excess adiposity (EA). The independent disorders associated with morbid MetS were hypercholesterolaemia, high-WtHR, EA, high-TyG index, heart failure, atrial fibrillation, CKD, and albuminuria, highlighting hypertension. Conclusions: One-fifth of the adult population has premorbid MetS, and almost one-sixth has morbid MetS. Almost two-fifths of people with MetS are at moderate, high, or very high risk of CKD, and four-fifths are at high or very high cardiovascular risk. In addition to the criteria defining MetS, other cardiovascular-renal-metabolic disorders show an independent association with MetS, highlighting EA for premorbid MetS and hypertension for morbid MetS.
Recent Advances in Electrochemical Biosensors for Neurodegenerative Disease Biomarkers
Authors: Bae Mingyu , Kim Nayoung , Cho Euni , Lee Taek , Lee Jin-Ho
Published: February 2025

Neurodegenerative diseases, such as Parkinson’s disease (PD) and Alzheimer’s disease (AD), represent a growing global health challenge with overlapping biomarkers. Key biomarkers, including α-synucleins, amyloid-β, and Tau proteins, are critical for accurate detection but are often assessed using conventional methods like enzyme-linked immunosorbent assay (ELISA) and polymerase chain reaction (PCR), which are invasive, costly, and time-intensive. Electrochemical biosensors have emerged as promising tools for biomarker detection due to their high sensitivity, rapid response, and potential for miniaturization. The integration of nanomaterials has further enhanced their performance, improving sensitivity, specificity, and practical application. To this end, this review provides a comprehensive overview of recent advances in electrochemical biosensors for detecting neurodegenerative disease biomarkers, highlighting their strengths, limitations, and future opportunities. By addressing the challenges of early diagnosis, this work aims to stimulate interdisciplinary innovation and improve clinical outcomes for neurodegenerative disease patients.
Correction: Oesch, N. Social Brain Perspectives on the Social and Evolutionary Neuroscience of Human Language. Brain Sci. 2024, 14, 166
Authors: Oesch Nathan
Published: February 2025

In the published publication [...]
Understanding Altered Dynamics in Cocaine Use Disorder Through State Transitions Mediated by Artificial Perturbations
Authors: Zheng Yi , Yang Yaqian , Zhen Yi , Wang Xin , Liu Longzhao , Zheng Hongwei , Tang Shaoting
Published: February 2025

Background/Objectives: Cocaine use disorder (CUD) poses a worldwide health challenge, with severe consequences for brain function. However, the phase dynamics underlying CUD and the transitions between CUD and health remain poorly understood. Methods: Here, we used resting-state functional magnetic resonance imaging (fMRI) data from 43 CUD patients and 45 healthy controls (HCT). We performed empirical analysis to identify phase-coherence states and compared their probabilities of occurrence between conditions. To further explore the underlying mechanism, we employed computational modeling to replicate the observed state probabilities for each condition. These generated whole-brain models enabled us to simulate external perturbations and identify optimal brain regions mediating transitions between HCT and CUD. Results: We found that CUD was associated with a reduced occurrence probability of the state dominated by the default mode network (DMN). Perturbing the nucleus accumbens, thalamus, and specific regions within the default mode, limbic and frontoparietal networks drives transitions from HCT to CUD, while perturbing the hippocampus and specific regions within the visual, dorsal attention, and DMN facilitates a return from CUD to HCT. Conclusions: This study revealed altered DMN-related dynamics in CUD from the phase perspective and provides potential regions critical for state transitions. The results contribute to understanding the pathogenesis of CUD and the development of therapeutic stimulation strategies.
AI as the Therapist: Student Insights on the Challenges of Using Generative AI for School Mental Health Frameworks
Authors: Chan Cecilia Ka Yuk
Published: February 2025

The integration of generative AI (GenAI) in school-based mental health services presents new opportunities and challenges. This study focuses on the challenges of using GenAI chatbots as therapeutic tools by exploring secondary school students’ perceptions of such applications. The data were collected from students who had both theoretical and practical experience with GenAI. Based on Grodniewicz and Hohol’s framework highlighting the “Problem of a Confused Therapist”, “Problem of a Non-human Therapist”, and “Problem of a Narrowly Intelligent Therapist”, qualitative data from student reflections were examined using thematic analysis. The findings revealed that while students acknowledged AI’s benefits, such as accessibility and non-judgemental feedback, they expressed significant concerns about a lack of empathy, trust, and adaptability. The implications underscore the need for AI chatbot use to be complemented by in-person counselling, emphasising the importance of human oversight in AI-augmented mental health care. This study contributes to a deeper understanding of how advanced AI can be ethically and effectively incorporated into school mental health frameworks, balancing technological potential with essential human interaction.
F3 Expression Drives Sensitivity to the Antibody-Drug Conjugate Tisotumab Vedotin in Glioblastoma
Authors: Sears Thomas K. , Wang Wenxia , Drumm Michael , Unruh Dusten , McCord Matthew , Horbinski Craig
Published: February 2025

Background/Objectives: The gene F3, encoding Tissue Factor (TF), is expressed in many cancers and contributes to their malignancy. Among adult-type diffuse gliomas, IDH1/2 wild-type (IDHwt) glioblastomas (GBM) express more TF than IDH1/2 mutant (IDHmut) gliomas. Tisotumab vedotin (TisVed), an anti-TF antibody conjugated to monomethyl auristatin E, is a therapeutic designed to target cells expressing TF. We therefore sought to determine the therapeutic potential of TisVed in IDHwt vs. IDHmut gliomas. Methods: We treated IDHwt and IDHmut patient-derived glioma cells with control IgG, unconjugated tisotumab (Tis), or TisVed in vitro, followed by cell viability assays and the assessment of TF signaling. We tested Tis and TisVed in mice intracranially engrafted with patient-derived IDHwt and IDHmut gliomas and mice flank engrafted with IDHwt GBM. Results: TisVed was more active against cultured IDHwt GBM cells than IDHmut glioma cells. This activity was increased by the daily washout of soluble TF secreted by IDHwt GBM cells. Unconjugated Tis had less effect than TisVed, and TF signaling was minimally inhibited. TisVed extended the survival of mice intracranially engrafted with IDHwt GBM (p = 0.006), but not mice with IDHmut glioma (p = 0.88). TisVed also reduced the growth of IDHwt GBM flank xenografts. Tis alone had no antitumor effect in either setting. Notably, both TisVed and Tis were associated with hemorrhage in flank tumors. Conclusions: TisVed targets high-TF-expressing IDHwt GBM, but not low-TF-expressing IDHmut glioma. This is predominately through the vedotin conjugate rather than inhibition of TF signaling. Though the effect size is modest, TisVed shows anticancer effects against IDHwt GBM. However, there could be complications related to hemostasis and hemorrhage.
Exploring the Role of Metabolic Hyperferritinaemia (MHF) in Steatotic Liver Disease (SLD) and Hepatocellular Carcinoma (HCC)
Authors: Anastasopoulos Nikolaos-Andreas , Barbouti Alexandra , Goussia Anna C. , Christodoulou Dimitrios K. , Glantzounis Georgios K.
Published: February 2025

The increasing prevalence of the spectrum of Steatotic Liver Disease (SLD), including Metabolic-Associated Steatotic Liver Disease (MASLD), Metabolic-Associated Steatohepatitis (MASH), and progression to Cirrhosis and Hepatocellular Carcinoma (HCC) has led to intense research in disease pathophysiology, with many studies focusing on the role of iron. Iron overload, which is often observed in patients with SLD as a part of metabolic hyperferritinaemia (MHF), particularly in the reticuloendothelial system (RES), can exacerbate steatosis. This imbalance in iron distribution, coupled with a high-fat diet, can further promote the progression of SLD by means of oxidative stress triggering inflammation and activating hepatic stellate cells (HSCs), therefore leading to fibrosis and progression of simple steatosis to the more severe MASH. The influence of iron overload in disease progression has also been shown by the complex role of ferroptosis, a type of cell death driven by iron-dependent lipid peroxidation. Ferroptosis depletes the liver’s antioxidant capacity, further contributing to the development of MASH, while its role in MASH-related HCC is potentially linked to alternations in the tumour microenvironment, as well as ferroptosis resistance. The iron-rich steatotic hepatic environment becomes prone to hepatocarcinogenesis by activation of several pro-carcinogenic mechanisms including epithelial-to-mesenchymal transition and deactivation of DNA damage repair. Biochemical markers of iron overload and deranged metabolism have been linked to all stages of SLD and its associated HCC in multiple patient cohorts of diverse genetic backgrounds, enhancing our daily clinical understanding of this interaction. Further understanding could lead to enhanced therapies for SLD management and prevention.
First-Principles Exploration of the Electronic Structure and Optical Properties of S-Doped Bi4O5Br2
Authors: Liu Gaihui , Shi Huihui , Dong Nan , Cao Xinrui , Gao Xuan , Xue Suqin , Zhang Fuchun
Published: February 2025

At present, many research studies have explored the modification of Bi4O5Br2, but relatively few have focused on non-metallic doping. In particular, the effect of S doping on its photocatalytic mechanism remains unclear. Hence, this study systematically investigates the modulation mechanism of the electronic structure and optical properties of Bi4O5Br2 by doped S using density functional theory (DFT) calculations. The calculated results indicate that the Br4Br1 model, in which S replaces Br at sites 4 and 1, is the most thermodynamically stable configuration. Comparing the models before and after doping, it is found that S doping significantly alters the lattice parameters of Bi4O5Br2, thus affecting its electronic structure. Furthermore, differential charge density calculations reveal that S doping improves the charge transfer capability and enhances the separation efficiency of photogenerated electron–hole pairs in Bi4O5Br2. Calculated absorption spectra demonstrate that S doping augments the light absorption of Bi4O5Br2 in the low- and medium-energy regions. Moreover, the dielectric function calculations further validate the effect of S doping on the optical properties of Bi4O5Br2. Specifically, there is an increase in polarization and energy loss in the low-energy region, with the opposite trend in the middle- and high-energy regions. Overall, S doping elevated the light absorption capacity and charge transfer efficiency of Bi4O5Br2 by altering its lattice parameter and electronic structure, which facilitated the enhancement of photocatalytic performance. This study provides new insights into the development of efficient photocatalytic materials and broadens the potential of Bi4O5Br2 for photocatalytic applications.
Controllable Synthesis of Ultrafine Ag NPs/Functionalized Graphene-Introduced TiO2 Mesoporous Hollow Nanofibers by Coaxial Electrospinning for Photocatalytic Oxidation of CO
Authors: Dou Tianwei , Zhu Yangyang , Chu Zhanyu , Li Zhijun , Sun Lei , Jing Liqiang
Published: February 2025

Solar-driven catalytic oxidation processes for the removal of toxic gaseous pollutants have attracted considerable scientific attention, and there is a strong desire to improve the mass transfer, photogenerated charge separation, and O2 activation by regulating the structure of the photocatalyst. Initially, functionalized graphene–TiO2 mesoporous hollow nanofibers have been controllably fabricated by a coaxial electrospinning technique, in which functionalized graphene is controllably prepared through a sequential diazonium functionalization and silane modification and ensures its uniform distribution among TiO2 nanoparticles (NPs). Subsequently, the ultrafine Ag NPs are primarily anchored onto the surface of graphene by an in situ frozen photodeposition strategy, producing Ag/functionalized graphene–TiO2 mesoporous hollow nanofibers (Ag/SiG-TO MPHNFs). The optimal Ag/SiG-TO MPHNFs exhibit 3.9-fold and 4.6-fold enhancements in CO photooxidation compared with TO MPHNFs and P25 TiO2, respectively. The enhanced photoactivity can be attributed to three factors: the creation of the mesoporous hollow structure accelerates mass transfer, the incorporation of graphene facilitates the transfer of photogenerated electrons from TiO2 to graphene, and the anchoring of Ag NPs improves O2 activation.
Recent Research on the Anti-Poisoning Catalysts in the Catalytic Oxidation of VOCs: A Review
Authors: Wang Longfei , Huang Chun , Gao Ziting , Cui Bing , Zhao Mingqin , Xiao Menglan , Yu Xiaolin
Published: February 2025

Volatile organic compounds (VOCs) from petrochemical, pharmaceutical, and other industries have serious damage to human health and the environment. Catalytic oxidation is a promising method to eliminate air pollution due to its high efficiency, wide application range, and environmental friendliness. However, in the actual industrial environment, the composition of industrial exhaust gases is complex, including VOCs, water vapour, chloride, sulfide and so on. The impurities would have competitive adsorption with reactants or react with the active sites, leading to the decline of catalytic activity, even the deactivation of catalysts. Therefore, this review summarises the recent research on the anti-poisoning ability of catalysts in the catalytic oxidation of VOCs, primarily focusing on the effect of water vapour, chloride, and sulfide. The catalytic oxidation mechanism manifested that the adsorption and activation of reactants are significant in VOCs degradation. On this basis, the mechanism of catalyst poisoning was analysed, and the inhibitory effect of impurities on the oxidation reaction was elucidated. According to the research status, three anti-poisoning strategies are proposed, including building a bimetallic system, modifying supports, and establishing the protected coating. This work provides a theoretical foundation and reference point for the rational construction of anti-poisoning catalysts in VOCs elimination.
Caki-1 Spheroids as a Renal Model for Studying Free Fatty Acid-Induced Lipotoxicity
Authors: Battle Dana , Qiu Xiangzhe , Alex Marilyn , Rivers London , Hamilton Jamie A. G. , Takayama Shuichi , Zhao Xueying
Published: February 2025

Lipotoxicity, resulting from the buildup of excess lipids in non-adipose tissues, is increasingly recognized as a major contributor to the progression of kidney disease, highlighting the need for alternative models to assess its effects on renal cells. The main aim of this study was to investigate the usefulness of Caki-1, a human proximal tubule (PT) and renal cell carcinoma (RCC) representative cell line, as a 3D model system for studying free fatty acid-induced PT lipotoxicity. Caki-1 spheroids were generated and maintained on ultra-low attachment plates and characterized regarding time-dependent morphology changes. In optimal 3D culture conditions, Caki-1 cells formed well-defined large compact spheroids with uniform morphology, good circularity, and increased diameter from days 4–12. Chronic exposure to saturated palmitate resulted in dose- and time-dependent spheroid disintegration and cell death, including dispersed and flattened spheroid morphology, with increased dead cells in the peripheral layers and decreased spheroid core. Moreover, palmitate-treated spheroids showed a significant increase in cleaved poly(ADP-ribose) polymerase (PARP) and active caspase-3. Palmitate-induced PARP cleavage, as well as endoplasmic reticulum (ER) stress and autophagy dysfunction, were blunted by triacsin C, an inhibitor of long-chain acyl-CoA synthetases. In addition, co-incubation with unsaturated oleate prevented palmitate-induced spheroid disintegration and apoptotic cell death in Caki-1 3D culture. While fatty acid overload upregulated lipid droplet protein perilipin 2 in Caki-1 cells, knockdown of perilipin 2 by siRNAs resulted in an exacerbation of palmitate-induced cell death. Together, these results indicate that the 3D Caki-1 spheroid model is a simple and reproducible in vitro system for studying renal lipotoxicity and lipid metabolism that gives useful readouts at the molecular, cellular, and multicellular levels.
Chronic Pain Induced by Social Defeat Stress in Juvenile Mice Depends on TLR4
Authors: Borges Paes Lemes Julia , Panichkina Alisa , Franco Malange Kaue , Morado-Urbina Carlos E. , Dochnal Sara Anna , Jadhav Saee , Dolmat Maksim , Pagliusi Jr. Marco , Navia-Pealez Juliana M. , Corr Maripat , Miller Yury I. , Yaksh Tony L.
Published: February 2025

A significant portion of adolescents suffer from mental illnesses and persistent pain due to repeated stress. The components of the nervous system that link stress and pain in early life remain unclear. Prior studies in adult mice implicated the innate immune system, specifically Toll-like receptors (TLRs), as critical for inducing long-term anxiety and pain-like behaviors in social defeat stress (SDS) models. In this work, we investigated the pain and anxiety behavioral phenotypes of wild-type and TLR4-deficient juvenile mice subjected to repeated SDS and evaluated the engagement of TLR4 by measuring dimerization in the spinal cord, dorsal root ganglia, and prefrontal cortex. Male juvenile (4-week-old) mice (C57BL/6J or Tlr4-/-) underwent six social defeat sessions with adult aggressor (CD1) mice. In WT mice, SDS promotes chronic mechanical allodynia and thermal hyperalgesia assessed via von Frey testing and the Hargreaves test, respectively. In parallel, the stressed WT mice exhibited transient anxiety-like behavior and long-lasting locomotor activity reduction in the open-field test. Tlr4-/--stressed animals were resistant to the induction of pain-like behavior but had a remnant of anxious behavior, spending less time in the center of the arena. In WT SDS, there were concordant robust increases in TLR4 dimerization in dorsal root ganglia macrophages and spinal cord microglia, indicating TLR4 activation. These results suggest that the chronic pain phenotype and locomotor impairment induced by SDS in juvenile mice depends on TLR4 engagement evidenced by dimerization in immune cells of the dorsal root ganglia and spinal cord.
Autophagy and Programmed Cell Death Modalities Interplay in HIV Pathogenesis
Authors: Lamsira Harpreet Kaur , Sabatini Andrea , Ciolfi Serena , Ciccosanti Fabiola , Sacchi Alessandra , Piacentini Mauro , Nardacci Roberta
Published: February 2025

Human immunodeficiency virus (HIV) infection continues to be a major global health challenge, affecting 38.4 million according to the Joint United Nations Program on HIV/AIDS (UNAIDS) at the end of 2021 with 1.5 million new infections. New HIV infections increased during the 2 years after the COVID-19 pandemic. Understanding the intricate cellular processes underlying HIV pathogenesis is crucial for developing effective therapeutic strategies. Among these processes, autophagy and programmed cell death modalities, including apoptosis, necroptosis, pyroptosis, and ferroptosis, play pivotal roles in the host–virus interaction dynamics. Autophagy, a highly conserved cellular mechanism, acts as a double-edged sword in HIV infection, influencing viral replication, immune response modulation, and the fate of infected cells. Conversely, apoptosis, a programmed cell death mechanism, is a critical defense mechanism against viral spread and contributes to the depletion of CD4+ T cells, a hallmark of HIV/AIDS progression. This review aims to dissect the complex interplay between autophagy and these programmed cell death modalities in HIV-induced pathogenesis. It highlights the molecular mechanisms involved, their roles in viral persistence and immune dysfunction, and the challenges posed by the viral reservoir and drug resistance, which continue to impede effective management of HIV pathology. Targeting these pathways holds promise for novel therapeutic strategies to mitigate immune depletion and chronic inflammation, ultimately improving outcomes for individuals living with HIV.
Flow Cytometric Detection of Waterborne Bacteria Metabolic Response to Anthropogenic Chemical Inputs to Aquatic Ecosystems
Authors: Jenkins Jill A. , Mize Scott V. , Johnson Darren , Brown Bonnie L.
Published: February 2025

Typical investigations into the biological consequences of suspected xenobiotics or nutrients introduced in watersheds include analytical chemistry screens of environmental samples—such as periphyton responses or studies of fish condition—which are all costly in terms of equipment, reagents, time, and human resources. An alternative is to assess pollutant effects on waterborne bacteria. A flow cytometric method was developed to yield rapid, same-day results that could be used to proactively screen for suspected chemical inputs into watersheds using water sampling methods that are identical to those in standard use. The analytical methods are microbe cultivation-independent, for use with waterborne bacteria that are typically viable but not culturable. The procedure is quick and inexpensive, generating measures of bacterial esterase that reflect metabolic activity and are sensitive and statistically robust. After phosphate-EDTA incubation to increase cell wall permeability, staining was performed with 5(6) carboxyfluorescein diacetate (enzyme activity) and propidium iodide (cell viability) with three bacterial species in exponential phase growth having been incubated with organic wastewater compounds (atrazine, pharmaceuticals [17α-ethynylestradiol and trenbolone], and antimicrobials [tylosin and butylparaben]). This method successfully detected metabolic changes in all bacterial species, with atrazine inducing the greatest change. Additional fluorescent stains can target specific microbial structures or functions of interest in a particular watershed. This biotechnology can inform analytical chemistry and study of biota at sites of interest and has the potential to be automated.
Automatic Movement Recognition for Evaluating the Gross Motor Development of Infants
Authors: Yang Yin-Zhang , Tsai Jia-An , Yu Ya-Lan , Ko Mary Hsin-Ju , Chiou Hung-Yi , Pai Tun-Wen , Chen Hui-Ju
Published: February 2025

Objective: The objective of this study was to early-detect gross motor abnormalities through video detection in Taiwanese infants aged 2–6 months. Background: The current diagnosis of infant developmental delays primarily relies on clinical examinations. However, during clinical visits, infants may show atypical behaviors due to unfamiliar environments, which might not truly reflect their true developmental status. Methods: This study utilized videos of infants recorded in their home environments. Two pediatric neurologists manually annotated these clips to identify whether an infant possessed the characteristics of gross motor delays through an assessment of his/her gross motor movements. Using transfer learning techniques, four pose recognition models, including ViTPose, HRNet, DARK, and UDP, were applied to the infant gross motor dataset. Four machine learning classification models, including random forest, support vector machine, logistic regression, and XGBoost, were used to predict the developmental status of infants. Results: The experimental results of pose estimation and tracking indicate that the ViTPose model provided the best performance for pose recognition. A total of 227 features related to kinematics, motions, and postures were extracted and calculated. A one-way ANOVA analysis revealed 106 significant features that were retained for constructing prediction models. The results show that a random forest model achieved the best performance with an average F1-score of 0.94, a weighted average AUC of 0.98, and an average accuracy of 94%.