Stochastic optimization models always assume known probability distributions about uncertain parameters. However, it is unrealistic to know the true distributions. In the era of big data, with the knowledge of informative features related to uncertain parameters, this study aims to estimate the conditional distributions of uncertain parameters directly and solve the resulting contextual stochastic optimization problem by using a set of realizations drawn from estimated distributions, which is called the contextual distribution estimation method. We use an energy scheduling problem as the case study and conduct numerical experiments with real-world data. The results demonstrate that the proposed contextual distribution estimation method offers specific benefits in particular scenarios, resulting in improved decisions. This study contributes to the literature on contextual stochastic optimization problems by introducing the contextual distribution estimation method, which holds practical significance for addressing data-driven uncertain decision problems. Full article

Accurate measurement of systemic financial risk is crucial for maintaining the stability of financial markets. Taking China as the subject of investigation, the Chinese Financial Stress Index (CFSI) indicator system was constructed by integrating six dimensions and employing Gray Relation Analysis (GRA) to reduce the dimensionality of the indicators. The CFSI was derived using the Attribute Hierarchy Model (AHM) method with the Criteria Importance Through the Intercriteria Correlation (CRITIC) method, and an Improved Gravitational Search Algorithm (IGSA)-optimized Radial Basis Function Neural Network (RBFNN) was proposed for out-of-sample prediction of CFSI trends from 2024 to 2026. By analyzing the trends in financial pressure indicators, the intricate relationship between financial pressure and economic activity can be effectively discerned. The research findings indicate that (1) the CFSI is capable of accurately reflecting the current financial stress situation in China, and (2) the IGSA-RBFNN demonstrates strong robustness and generalization capabilities, predicting that the CFSI index will reach a peak value of 0.543 by the end of 2024, and there exists a regular pattern of stress rebound towards the end of each year. The novel methodology enables policymakers and regulatory authorities to proactively identify potential risks and vulnerabilities, facilitating the formulation of preventive measures. Full article

This paper develops a methodology to accommodate uncertainty in a GARCH model with the goal of improving portfolio decisions via Bayesian learning. Given the abundant evidence of uncertainty in estimating expected returns, we focus our analyses on the single parameter driving expected returns. After deriving an Uncertainty-Implied GARCH (UI-GARCH) model, we investigate how learning about uncertainty affects investments in a dynamic portfolio optimization problem. We consider an investor with constant relative risk aversion (CRRA) utility who wants to maximize her expected utility from terminal wealth under an Affine GARCH(1,1) model. The corresponding stock evolution, and therefore, the wealth process, is treated as a Bayesian information model that learns about the expected return with each period. We explore the one- and two-period cases, demonstrating a significant impact of uncertainty on optimal allocation and wealth-equivalent losses, particularly in the case of a small sample size or large standard errors in the parameter estimation. These analyses are conducted under well-documented parametric choices. The methodology can be adapted to other GARCH models and applications beyond portfolio optimization. Full article

Servicification in global value chains (GVCs) in emerging and developing Asian economies has become a trend recently. However, there have been no scientific studies to elucidate the mechanism of servicification in GVCs. To fill this gap, this study aims to investigate the involvement of service sectors in GVCs in Asian economies in terms of the quantitative interactions between service inputs and manufacturing exports and inputs and between service inputs and service exports. For this purpose, a panel vector-autoregressive model and the Trade in Value Added database of the Organization for Economic Cooperation and Development (OECD) were used for the empirical analysis during 1995–2018. The estimation results find that, first, there exist reciprocal interactions between the business services and manufacturing sectors; foreign business service inputs are induced by manufacturing exports, whereas manufacturing inputs are induced by business service exports. Second, foreign manufacturing inputs facilitate foreign business service inputs. Third, business service inputs are promoted by business service exports. These trends in the involvement of business services’ involvement in GVCs have accelerated since the mid-2000s. To enhance the role of services in GVCs, Asian economies should facilitate the removal of explicit restrictions in service trade and address regulatory divergence across countries. Full article

This article explores novel in-orbit drag-free technology that can be utilized for deep space detection scientific missions. In this study, we considered a two-test-mass drag-free method and analyzed the design of the drag-free and attitude control system for the TianQin mission. The entire control system was comprehensively designed, including an actuator allocation design and controllers for two test masses and one spacecraft, with a total of 18 degrees of freedom. Furthermore, stability analysis was conducted. Based on our design, numerical analysis and simulations were performed assuming geocentric orbit conditions in the TianQin mission, confirming the feasibility of this aerospace engineering concept. The versatility of the design allows for its application to scientific observations across various disciplines by modifying the structure of the simulation environment, and consequently, the approach discussed in this study holds significant practical implications for effectively accomplishing deep space observation tasks. Full article

This review’s objective is to examine the findings from various studies on oral signs and symptoms related to vitamin deficiency. In October 2023, two electronic databases (Scopus and PubMed) were searched for published scientific articles following PRISMA principles. Articles eligible for inclusion in this review had to be published in English between 2017 and 2023, be original studies, and involve human subjects. Fifteen studies were included in this review: three examining oral symptoms of vitamin B12 deficiency; one assessing vitamin B complex and vitamin E for recurrent oral ulcers; one investigating serum vitamin D levels in recurrent aphthous stomatitis patients; three exploring hypovitaminosis effects on dental caries; two measuring blood serum vitamin D levels; one evaluating vitamin B12 hypovitaminosis; three investigating hypovitaminosis as indicative of gingival disease; one focusing on vitamin deficiencies and enamel developmental abnormalities; one assessing vitamin deficiencies in oral cancer patients; one examining vitamin K as an oral anticoagulant and its role in perioperative hemorrhage; and one evaluating vitamin effects on burning mouth syndrome. Despite some limitations, evidence suggests a correlation between vitamin deficiencies and oral symptoms. This systematic review was registered in the International Platform of Registered Systematic Review and Meta-analysis Protocols (INPLASY) database (202430039). Full article

Loss of hand functions, often manifesting in the form of weakness or spasticity from conditions like stroke or multiple sclerosis, poses challenges in performing activities of daily living (ADLs). The broad area of rehabilitation robotics provides the tools and knowledge necessary for implementing efficient restorative therapies. These therapies aim to improve hand functionality with minimal therapist intervention. However, the human hand evolved for various precision and power gripping tasks, with its intricate anatomy featuring a large number of degrees of freedom—up to 31—which hinder its modeling in many rehabilitation scenarios. In the process of designing prosthetic devices, instrumented gloves, and rehabilitation devices, there is a clear need to obtain simplified rehabilitation-oriented hand models without compromising their representativeness across the population. This is where the concept of kinematic reduction, focusing on specific grasps, becomes essential. Thus, the objective of this study is to uncover the intra-finger dependencies during finger flexion/extension by analyzing a comprehensive database containing recorded trajectories for 23 different functional movements related to ADLs, involving 77 test subjects. The initial phase involves data wrangling, followed by correlation analysis aimed at selecting 116 dependency-movement relationships across all grasps. A regularized generalized linear model is then applied to select uncorrelated predictors, while a linear mixed-effect model, with reductions based on both predictor significance and effect size, is used for modeling the dependencies. As a final step, agglomerative clustering of models is performed to further facilitate flexibility in tradeoffs in hand model accuracy/reduction, allowing the modeling of finger flexion extensions using 5–15 degrees of freedom only. Full article

Pedestrian trajectory prediction is a key technical prerequisite for autonomous vehicle trajectory planning. However, a pedestrian is a changeable individual, and their intentions exhibit certain degrees of randomness and uncertainty, which leads to the issue that modeling only past trajectories does not enable the effective description of the random intentions and future trajectory directions of the pedestrian. Therefore, this paper proposes a flexible and embeddable stochastic intention vector construction strategy for modeling sudden pedestrian intention changes in real scenes and for better fitting the stochastic properties of pedestrian behaviors. First, we dynamically fuse historical trajectory information with random factors and construct an intention change probability based on the historical trajectory fitting errors of pedestrians, aiming to explicitly model the associated direction and velocity changes caused by random pedestrian intentions. Second, a new intention loss function is designed to guide the model to adaptively learn the probability of intention changes, which is used to dynamically describe pedestrian intention changes. Our proposed method is generalizable and can be applied as an embeddable module to any baseline pedestrian trajectory prediction method. The experimental results obtained on multiple large-scale public pedestrian trajectory prediction datasets demonstrate that our strategy achieves consistent performance improvements over different baselines. Full article

In the process of fabric production, various types of defects affect the quality of a fabric. However, due to the wide variety of fabric defects, the complexity of fabric textures, and the concealment of small target defects, current fabric defect detection algorithms suffer from issues such as having a slow detection speed, low detection accuracy, and a low recognition rate of small target defects. Therefore, developing an efficient and accurate fabric defect detection system has become an urgent problem that needs to be addressed in the textile industry. Addressing the aforementioned issues, this paper proposes an improved YOLOv8n-LAW algorithm based on the YOLOv8n algorithm. First, LSKNet attention mechanisms are added to both ends of the C2f module in the backbone network to provide a broader context area, enhancing the algorithm’s feature extraction capability. Next, the PAN-FPN structure of the backbone network is replaced by the AFPN structure, so that the different levels of features of the defects are closer to the semantic information in the progressive fusion. Finally, the CIoU loss is replaced with the WIoU v3 loss, allowing the model to dynamically adjust gradient gains based on the features of fabric defects, effectively focusing on distinguishing between defective and non-defective regions. The experimental results show that the improved YOLOv8n-LAW algorithm achieved an accuracy of 97.4% and a detection speed of 46 frames per second, while effectively increasing the recognition rate of small target defects. Full article

Flooding and drought are the two most devastating natural hazards limiting maize production. Exogenous glycinebetaine (GB), an osmotic adjustment agent, has been extensively used but there is limited research on its role in mitigating the negative effects of different abiotic stresses. This study aims to identify the different roles of GB in regulating the diverse defense regulation of maize against drought and flooding. Hybrids of Yindieyu 9 and Heyu 397 grown in pots in a ventilated greenhouse were subjected to flooding (2–3 cm standing layer) and drought (40–45% field capacity) at the three-leaf stage for 8 d. The effects of different concentrations of foliar GB (0, 0.5, 1.0, 5.0, and 10.0 mM) on the physiochemical attributes and growth of maize were tested. Greater drought than flooding tolerance in both varieties to combat oxidative stress was associated with higher antioxidant activities and proline content. While flooding decreased superoxide dismutase and guaiacol peroxidase (POD) activities and proline content compared to normal water, they all declined with stress duration, leading to a larger reactive oxygen species compared to drought. It was POD under drought stress and ascorbate peroxidase under flooding stress that played crucial roles in tolerating water stress. Foliar GB further enhanced antioxidant ability and contributed more effects to POD to eliminate more hydrogen peroxide than the superoxide anion, promoting growth, especially for leaves under water stress. Furthermore, exogenous GB made a greater increment in Heyu 397 than Yindieyu 9, as well as flooding compared to drought. Overall, a GB concentration of 5.0 mM, with a non-toxic effect on well-watered maize, was determined to be optimal for the effective mitigation of water-stress damage to the physiochemical characteristics and growth of maize. Full article

Measurements of temperature, salinity, and currents in the Amazon River plume over a section in the open ocean of the western tropical North Atlantic (38°48′ W) are considered. The measurements were carried out using an AML Base X CTD probe in the upper layer and a flow-through system that measures salinity, turbidity, and chlorophyll-a content in seawater while a vessel is on the way. The measurements were supplemented by velocity profiling using shipborne SADCP. Additionally, archived oceanographic data from the World Ocean Database (WOD18), data on satellite altimetry measurements (AVISO), and satellite salinity data from Aquarius and SMOS were used. It is shown that the width of the Amazon River plume is about 170–400 km and the depth of desalination is from 50 to 100 m. Surface salinity decreases compared to the background (36.1) by 0.25 in February and by more than 3.0 in September during the period of maximum development of the plume, which was determined from satellite measurements of surface salinity. Lagrangian modeling of the back-in-time advection of passive markers simulating freshwater particles was carried out. It was shown that the source of freshwater in the measurement area is discharge from the Amazon River. Amazon River freshwater covered a distance of 3300 km in 60–80 days. The estimate of freshwater transport in the plume was 0.02 Sv, which is one order of magnitude smaller than the mean river discharge. Full article

The segmentation of floating algae is a hot topic in the field of marine environmental research. Given the vastness of coastal areas and complex environments, algae detection models must have both higher performance and lower deployment costs. However, relying solely on a single Convolutional Neural Network (CNN) or transformer structure fails to achieve this objective. In this paper, a novel real-time floating algae segmentation method using a distillation network (ADNet) is proposed, based on the RGB images. ADNet can effectively transfer the performance of the transformer-based teacher network to the CNN-based student model while preserving its lightweight design. Faced with complex marine environments, we introduce a novel Channel Purification Module (CPM) to simultaneously strengthen algae features and purify interference responses. Importantly, the CPM achieves this operation without increasing any learnable parameters. Moreover, considering the huge scale differences among algae targets in surveillance RGB images, we propose a lightweight multi-scale feature fusion network (L-MsFFN) to improve the student’s modeling ability across various scales. Additionally, to mitigate interference from low-level noises on higher-level semantics, a novel position purification module (PPM) is proposed. The PPM can achieve more accurate weight attention calculation between different pyramid levels, thereby enhancing the effectiveness of fusion. Compared to CNNs and transformers, our ADNet strikes an optimal balance between performance and speed. Extensive experimental results demonstrate that our ADNet achieves higher application performance in the field of floating algae monitoring tasks. Full article

The farmers’ deep participation in the classification of domestic waste plays a crucial role in reducing the amount of waste out of the village from the source, lowering the cost of waste treatment, and realizing the sustainable development of rural waste resocialization, reduction, and harmlessness. This paper aims to identify the key factors and logical structure that influence the farmers’ behavior in classifying domestic waste and provide recommendations for improving it. Based on the Participants’ Intellectual Decision (PID) Model, we constructed a theoretical analysis framework for farmers’ decision-making on domestic waste classification, and the PID model was further extended by combining with the practice of rural domestic waste management in China and proposing the research hypothesis that factors, such as community attributes, rules of operation, the status of the participants, and the situation of external actions, have a significant impact on the farmers’ behavior in classifying domestic waste. Empirical analyses were carried out with the help of the ordered logistic model and the DEMATEL-ISM using 939 research data of farmers in Jiangsu and Gansu provinces of China. The results show the following: (1) classification of domestic waste by farmers in the sample area was predominantly unclassified (34.40%) and two-classified (40.58%); (2) 17 factors, including regional disparity, Party affiliation, organizational support perception, environmental emotions, conscious governance attitudes, trust in village cadres, social reference norms, and expected outcomes, have a significant impact on the farmers’ behavior in classifying domestic waste; (3) trust in village cadres, organizational support perception, and environmental emotion are superficial direct factors; incentive measures, fee level, waste transport situation, difficulty perception, self-consciousness perception, social reference norms, and expected outcomes are middle indirect factors; whether or not it is a demonstration village, Party membership and regional disparity are deep root factors affecting farmers to classify their domestic waste. Full article

Background/Objectives: The anxiolytic effect of transcutaneous electrical nerve stimulation (TENS) is associated with the activation of endogenous inhibitory mechanisms in the central nervous system. Both low-frequency, high-amplitude TENS (LF-TENS) and high-frequency, low-amplitude TENS (HF-TENS) are capable of activating opioid, GABA, serotonin, muscarinic, and cannabinoid receptors. However, there has been no comparative analysis of the effectiveness of HF-TENS and LF-TENS in the treatment of GAD. The purpose of our research was to study the effectiveness of direct HF-TENS and LF-TENS of the right median nerve in the treatment of patients with GAD compared with sham TENS. Methods: The effectiveness of direct HF-TENS and LF-TENS of the right median nerve in the treatment of GAD was studied using Generalized Anxiety Disorder 7-item scale (GAD-7) and the Hamilton Anxiety Rating Scale (HAM-A). 40 patients underwent sham TENS, 40 patients passed HF-TENS (50 Hz—50 μs—sensory response) and 41 patients completed LF –TENS (1 Hz—200 μs—motor response) for 30 days daily. After completion of treatment, half of the patients received weekly maintenance therapy for 6 months. Electroencephalography was performed before and after treatment. Results: Our study showed that a significant reduction in the clinical symptoms of GAD as assessed by GAD-7 and HAM-A was observed after HF-TENS and LF-TENS by an average of 42.4%, and after sham stimulation only by 13.5% for at least 2 months after the end of treatment. However, LF-TENS turned out to be superior in effectiveness to HF-TENS by 51% and only on electroencephalography leads to an increase in PSD for the alpha rhythm in the occipital regions by 24% and a decrease in PSD for the beta I rhythm in the temporal and frontal regions by 28%. The prolonged effect of HF-TENS and LF-TENS was maintained without negative dynamics when TENS treatment was continued weekly throughout the entire six-month observation period. Conclusions: A prolonged anxiolytic effect of direct TENS of the right median nerve has been proven with greater regression of clinical and neurophysiological manifestations of GAD after LF-TENS compared to HF-TENS. Minimal side effects, low cost, safety, and simplicity of TENS procedures are appropriate as a home treatment modality. Full article

Background: We aimed to study anxiety, depression and quality of life in smokers after stroke by sex. Methods: A longitudinal prospective study with a 24-month follow-up of acute stroke patients who were previously active smokers. Anxiety and depression were evaluated with the Hospital Anxiety and Depression scale, and quality of life was evaluated with the EQ-5D questionnaire. Results: One hundred and eighty patients participated (79.4% men); their mean age was 57.6 years. Anxiety was most prevalent at 3 months (18.9% in men and 40.5% in women) and depression at 12 months (17.9% in men and 27% in women). The worst perceived health occurred at 24 months (EQ-VAS 67.5 in men and 65.1 in women), which was associated with depression (p < 0.001) and Rankin Scale was worse in men (p < 0.001) and depression in women (p < 0.001). Continued tobacco use was associated with worse perceived health at 3 months in men (p = 0.034) and at 12 months in both sexes. Predictor variables of worse perceived health at 24 months remaining at 3 and 12 months were tobacco use in men and neurological damage in women. Conclusion: Differences by sex are observed in the prevalence of anxiety and depression and associated factors and in the predictive factors of perceived health. Full article

The role of the extracellular matrix (ECM) in Parkinson’s disease (PD) is not well understood, even though it is critical for neuronal structure and signaling. This systematic review identified the top deregulated ECM-related pathways in studies that used gene set enrichment analyses (GSEA) to document transcriptomic, proteomic, or genomic alterations in PD. PubMed and Google scholar were searched for transcriptomics, proteomics, or genomics studies that employed GSEA on data from PD tissues or cells and reported ECM-related pathways among the top-10 most enriched versus controls. Twenty-seven studies were included, two of which used multiple omics analyses. Transcriptomics and proteomics studies were conducted on a variety of tissue and cell types. Of the 17 transcriptomics studies (16 data sets), 13 identified one or more adhesion pathways in the top-10 deregulated gene sets or pathways, primarily related to cell adhesion and focal adhesion. Among the 8 proteomics studies, 5 identified altered overarching ECM gene sets or pathways among the top 10. Among the 4 genomics studies, 3 identified focal adhesion pathways among the top 10. The findings summarized here suggest that ECM organization/structure and cell adhesion (particularly focal adhesion) are altered in PD and should be the focus of future studies. Full article

The parameters of gravity dams and foundation materials objectively exhibit spatial variability due to environmental and load influences, which significantly affect the safety status of dam structures. Therefore, a safety risk analysis method for a gravity dam–foundation system based on random field theory is proposed in this paper. Spatial variabilities in materials are particularly considered by using the finite element method. Then, composite response surface equations for the performance function (PF) of strength and stability failure are established, and then, the system failure risk is obtained using the Monte Carlo method. The proposed method solves the problem wherein the effect of spatial variability on failure risk cannot be reflected accurately by the performance function of multi-element sliding paths, and the difficulties in solving the failure risk of the series–parallel system due to multiple failure paths and their complex correlations. The application of a gravity dam shows that the developed method overcomes the disadvantages of the traditional method, such as the homogenization of the spatially random characteristics of parameters and the overestimation of failure risk in the system due to large variance estimation. Full article

Damping reduction factors (DRFs) play a vital role in the seismic design of structures. DRFs have been widely studied due to their primary importance to the lateral resistance of structures subjected to earthquakes. On the other hand, devastating earthquakes have occurred all over the world, and recently, the Kahramanmaraş earthquakes in Turkey revealed the import of the vertical component of earthquakes and their impact on structures and infrastructures. Considering the importance of this parameter, this paper aims to develop new damping reduction factor (DRF) equations for the acceleration (DRFa), velocity (DRFv), and displacement spectra (DRFd) of the vertical components of earthquakes. For this purpose, 775 real ground motion records were selected from the Pacific Earthquake Engineering Research (PEER) strong motion database, and the vertical elastic response spectra of selected records were computed according to linear dynamic analysis. Taking the 5%-damped vertical response spectra as the target, the vertical spectral damping reduction factors (DRFa, DRFv, and DRFd) were computed for 1%, 3%, 10%, 15%, 20%, 30%, and 40% damping ratios. The effect of the earthquake magnitude, distance, and soil types on the DRFs was investigated. The results indicated that magnitude, distance, and soil type had no particular effect on the trend in the DRFs. Based on the evaluations, extensive statistical analyses were carried out, and new prediction equations were developed according to the nonlinear regression method. The developed equations were then compared to those found in the literature and seismic design codes. The comparisons proved that the proposed DRFa, DRFd, and DRFv models are strongly compatible with real DRFs and show strong robustness compared to existing models. Full article

In the context of the technological era, the smart tourism construct serves as a bridge between human and the artificial worlds, combining social sciences and neurosciences. This study aims to explore smart tourism through neuroscientific methods in order to shape the future of tourism destinations, using a hybrid methodology combining bibliometric techniques and content analysis. The findings reveal the integration of diverse scientific domains, highlighting a transdisciplinary approach. They offer clear evidence that neuroscientific methods in smart tourism integrate multiple areas of scientific knowledge, surpassing disciplinary boundaries. “Destination” stands out alongside “emotion”, “visual attention” and eye tracking (ET). The collaboration network reveals the emergence of a new school, called neurotourism in the 21st century, formed mainly by actors and organizations from the Global North, evoking the need to include the Global South in the research scenario. The predominant methods include ET, heart rate (HR), and electroencephalography (EEG), suggesting triangulation with traditional methods for robust results. Virtual reality emerges as the primary immersive technology, promising insights when integrated with neurosciences. This study’s practical and theoretical contributions guide smart tourism strategies and enhance destination experiences through neuroscientific methods, addressing a gap in the scientific literature while advancing ontological and epistemological understanding. Full article

The problem of reading comprehension at the university level has not been sufficiently explored in the field of education research. Understanding written texts is an essential prerequisite for academic success during university. Consequently, reading comprehension challenges can influence the dropout rate at the university level. On the other hand, research has been conducted from a cognitive perspective, without considering affective variables such as reading motivation and its relationship with linguistic and psychological variables. In this study, five questionnaires were administered to a sample of 65 teaching students from different disciplines. The questionnaires dealt with linguistic dimensions such as reading comprehension, at lexical, textual, and discursive levels; psychological aspects such as reading motivation; and cognitive aspects such as working memory. The results obtained through bivariate and mediation analyses show the mediating role of vocabulary in reading comprehension and other cognitive and affective variables. In this context, working memory has a positive indirect effect on more explicit processing tasks in reading comprehension of long texts associated with discourse comprehension. Finally, intrinsic motivation has a positive indirect effect on reading fluency and also on the comprehension of short texts. It also correlates positively with vocabulary tasks. These results are relevant in order to establish a reading profile of university students who have reading comprehension problems, as found in this study. Full article

Urticaria, independent of or associated with allergies, is commonly seen in horses and often shows a high reoccurrence rate. Managing these horses is discouraging, and efficient treatment options are lacking. Due to an incidental finding in a study on horses affected by insect bite hypersensitivity using the eosinophil-targeting eIL-5-CuMV-TT vaccine, we observed the prevention of reoccurring seasonal urticaria in four subsequent years with re-vaccination. In an exploratory case series of horses affected with non-seasonal urticaria, we aimed to investigate the role of eosinophils in urticaria. Skin punch biopsies for histology and qPCR of eosinophil associated genes were performed. Further, two severe, non-seasonal, recurrent urticaria-affected horses were vaccinated using eIL-5-CuMV-TT, and urticaria flare-up was followed up with re-vaccination for several years. Eotaxin-2, eotaxin-3, IL-5, CCR5, and CXCL10 showed high sensitivity and specificity for urticarial lesions, while eosinophils were present in 50% of histological tissue sections. The eIL-5-CuMV-TT vaccine reduced eosinophil counts in blood, cleared clinical signs of urticaria, and even prevented new episodes of urticaria in horses with non-seasonal recurrent urticaria. This indicates that eosinophils play a leading role in urticaria in horses, and targeting eosinophils offers an attractive new treatment option, replacing the use of corticosteroids. Full article

Aquaporins are membrane pores regulating the transport of water, glycerol, and other small molecules across membranes. Among 13 human aquaporins, six have been shown to transport H₂O₂ and are therefore called peroxiporins. Peroxiporins are implicated in cancer development and progression, partly due to their involvement in H₂O₂ transport. Oxidative stress is linked to breast cancer development but is also a mechanism of action for conventional chemotherapy. The aim of this study is to investigate the effects of prolonged oxidative stress on Aquaporin 3 (AQP3), Aquaporin 5 (AQP5), and signaling pathways in breast cancer cell lines of different malignancies alongside a non-tumorigenic breast cell line. The prolonged oxidative stress caused responses in viability only in the cancer cell lines, while it affected cell migration in the MCF7 cell line. Changes in the localization of NRF2, a transcription factor involved in oxidative stress response, were observed only in the cancer cell lines, and no effects were recorded on its downstream target proteins. Moreover, the prolonged oxidative stress caused changes in AQP3 and AQP5 expression only in the cancer cell lines, in contrast to their non-malignant counterparts. These results suggest peroxiporins are potential therapeutic targets in cancer treatment. However, further research is needed to elucidate their role in the modulation of therapy response, highlighting the importance of research on this topic. Full article