Search Results (1,630)

Vermicomposting is a sustainable biotechnological process that transforms organic waste through the synergistic activity of earthworms, such as Eisenia fetida, and their associated microbiota. This study evaluated bacterial and physicochemical dynamics during the vermicomposting of bovine manure by analyzing the microbial composition of the substrate and the gut of E. fetida at three time points (weeks 0, 6, and 12). The V3–V4 region of the 16S rRNA gene was sequenced, and microbial diversity was characterized using QIIME2. Significant differences in alpha diversity (observed features, Shannon index, and phylogenetic diversity) and beta diversity indicated active microbial succession. Proteobacteria, Bacteroidota, and Actinobacteriota were the dominant phyla, with abundances varying across habitats and over time. A significant enrichment of Proteobacteria, Bacteroidota, and the genera Chryseolinea, Flavobacterium, and Sphingomonas was observed in the manure treatments. In contrast, Actinobacteriota, Firmicutes, and the genera Methylobacter, Brevibacillus, Enhygromyxa, and Bacillus, among others, were distinctive of the gut samples and contributed to their dissimilarity from the manure treatments. Simultaneously, the physicochemical parameters indicated progressive substrate stabilization and nutrient enrichment. Notably, the organic matter and total organic carbon contents decreased (from 79.47% to 47.80% and from 46.10% to 27.73%, respectively), whereas the total nitrogen content increased (from 1.70% to 2.23%); these effects reduced the C/N ratio, which is a recognized indicator of maturity, from 27.13 to 12.40. The macronutrient contents also increased, with final values of 1.41% for phosphorus, 1.50% for potassium, 0.89% for magnesium, and 2.81% for calcium. These results demonstrate that vermicomposting modifies microbial communities and enhances substrate quality, supporting its use as a biofertilizer for sustainable agriculture, soil restoration, and agrochemical reduction. Full article

Temperature fluctuations caused by climate change and global warming pose a threat to fish. The burbot (lota lota) population is particularly sensitive to increased water temperature, but the systematic impacts of high-temperature exposure on their liver and intestinal health remain unclear. In January of 2025, we collected wild adult burbot individuals from the Ussuri River (water temperature: about 2 °C), China. The burbot were exposed to 2 °C, 7 °C, 12 °C, 17 °C, and 22 °C environments for 96 h; then, the liver and intestinal contents were subsequently collected for histopathology observation, immunohistochemistry, biochemical index assessment, and transcriptome/16S rDNA sequencing analysis. There was obvious liver damage including hepatocyte necrosis, fat vacuoles, and cellular peripheral nuclei. Superoxide dismutase (SOD), catalase (CAT), and glutathione peroxidase (GSH-Px) activities were elevated and subsequently decreased. Additionally, the malondialdehyde (MDA) level significantly increased with increasing temperature. These results indicate that 7 °C (heat stress temperature), 12 °C (tipping point for normal physiological metabolism status), 17 °C (tipping point for individual deaths), and 22 °C (thermal limit) are critical temperatures in terms of the physiological response of burbot during their breeding period. In the hepatic transcriptome profiling, 6538 differentially expressed genes (DEGs) were identified, while KEGG enrichment analysis showed that high-temperature stress could affect normal liver function by regulating energy metabolism, immune, and apoptosis-related pathways. Microbiomics also revealed that acute heat stress could change the intestinal microbe community structure. Additionally, correlation analysis suggested potential regulatory relationships between intestinal microbe taxa and immune/apoptosis-related DEGs in the liver. This study revealed the potential impact of environmental water temperature changes in cold habitats in winter on the physiological adaptability of burbot during the breeding period and provides new insights for the ecological protection of burbot in the context of global climate change and habitat warming. Full article

This study presents the structural and compositional characterisation of a newly developed Ti55Al27Mo13 alloy synthesised via aluminothermic reaction. The alloy was designed to overcome the limitations of conventional processing routes for high–melting–point elements such as Ti and Mo, enabling the formation of a complex, multi–phase microstructure in a single high–temperature step. The aim was to develop and characterise a material with microstructural features expected to enhance wear resistance, oxidation behaviour, and thermal stability in future applications. The alloy is intended as a precursor for composite nanopowders and surface coatings applied to aluminium–, magnesium–, and iron–based substrates subjected to mechanical and thermal loading. Elemental analysis (XRF, EDS) confirmed the presence of Ti, Al, Mo, and minor elements such as Si, Fe, and C. Microstructural investigations using laser confocal and scanning electron microscopy revealed a heterogeneous structure comprising solid solutions, eutectic regions, and dispersed oxide and carbide phases. Notably, the alloy exhibits high hardness values, reaching >2400 HV in Al₂O₃ regions and ~1300 HV in Mo– and Si–enriched solid solutions. These results suggest the material’s substantial potential for protective surface engineering. Further tribological, thermal, and corrosion testing, conducted with meticulous attention to detail, will follow to validate its functional performance in target applications. Full article

Barley leaf stripe, caused by Pyrenophora graminea (Pg), significantly reduces yields across various regions globally. Understanding the resistance mechanisms of barley to Pg is crucial for advancing disease resistance breeding efforts. In this study, two barley genotypes—highly susceptible Alexis and immune Ganpi2—were inoculated with the highly pathogenic Pg isolate QWC for 7, 14, and 18 days. The number of differentially expressed genes (DEGs) in Alexis was 1350, 1898, and 2055 at 7, 14, and 18 days, respectively, while Ganpi2 exhibited 1195, 1682, and 2225 DEGs at the same time points. Gene expression pattern analysis revealed that Alexis responded more slowly to Pg infection compared to Ganpi2. A comparative analysis identified 457 DEGs associated with Ganpi2’s immunity to Pg. Functional enrichment of these DEGs highlighted the involvement of genes related to plant-pathogen interactions and kinase activity in Pg immunity. Additionally, 20 resistance genes and 24 transcription factor genes were predicted from the 457 DEGs. Twelve candidate genes were selected for qRT-PCR verification, and the results showed that the transcriptomic data was reliable. We conducted cloning of the candidate Pg resistance gene HvLRR_8-1 by the barley cultivar Ganpi2, and the sequence analysis confirmed that the HvLRR_8-1 gene contains seven leucine-rich repeat (LRR) domains and an S_TKc domain. Subcellular localization in tobacco indicates that the HvLRR_8-1 is localized on the cell membrane. Through the functional analysis using virus-induced gene silencing, it was demonstrated that HvLRR_8-1 plays a critical role in regulating barley resistance to Pg. This study represents the first comparative transcriptome analysis of barley varieties with differing responses to Pg infection, providing that HvLRR_8-1 represents a promising candidate gene for improving durable resistance against Pg in cultivated barley. Full article

Accurate organ-level segmentation is essential for achieving high-throughput, non-destructive, and automated plant phenotyping. To address the challenge of intelligent acquisition of phenotypic parameters in tomato plants, we propose TSINet, an end-to-end dual-task segmentation network designed for effective and precise semantic labeling and instance recognition of tomato point clouds, based on the Pheno4D dataset. TSINet adopts an encoder–decoder architecture, where a shared encoder incorporates four Geometry-Aware Adaptive Feature Extraction Blocks (GAFEBs) to effectively capture local structures and geometric relationships in raw point clouds. Two parallel decoder branches are employed to independently decode shared high-level features for the respective segmentation tasks. Additionally, a Dual Attention-Based Feature Enhancement Module (DAFEM) is introduced to further enrich feature representations. The experimental results demonstrate that TSINet achieves superior performance in both semantic and instance segmentation, particularly excelling in challenging categories such as stems and large-scale instances. Specifically, TSINet achieves 97.00% mean precision, 96.17% recall, 96.57% F1-score, and 93.43% IoU in semantic segmentation and 81.54% mPrec, 81.69% mRec, 81.60% mCov, and 86.40% mWCov in instance segmentation. Compared with state-of-the-art methods, TSINet achieves balanced improvements across all metrics, significantly reducing false positives and false negatives while enhancing spatial completeness and segmentation accuracy. Furthermore, we conducted ablation studies and generalization tests to systematically validate the effectiveness of each TSINet component and the overall robustness of the model. This study provides an effective technological approach for high-throughput automated phenotyping of tomato plants, contributing to the advancement of intelligent agricultural management. Full article

High-temperature stress has become an important factor that has restricted the aquaculture industry. Huso dauricus is a high-economic-value fish that has faced the threat of thermal stress. Based on this point, our investigation aimed to explore the detailed mechanism of the negative impacts of heat stress on the liver metabolism functions in Huso dauricus. In this study, we set one control group (19 °C) and four high-temperature treatment groups (22 °C, 25 °C, 28 °C, 31 °C) with 40 fish in each group for continuous 53-day heat exposure. Histological analysis, biochemical detection, and transcriptome technology were used to explore the effects of heat stress on the liver structure and functions of juvenile Huso dauricus. It suggested heat-stress-induced obvious liver injury and reactive oxygen species accumulation in Huso dauricus with a time/temperature-dependent manner. Serum total protein, transaminase, and alkaline phosphatase activities showed significant changes under heat stress (p < 0.05). In addition, 6433 differentially expressed genes (DEGs) were identified based on the RNA-seq project. Gene Ontology enrichment analysis showed that various DEGs could be mapped to the lipid-metabolism-related terms. KEGG enrichment and immunohistochemistry analysis showed that ferroptosis and FoxO signaling pathways were significantly enriched (p < 0.05). These results demonstrated that thermal stress induced oxidative stress damage in the liver of juvenile Huso dauricus, which triggered lipid metabolism disorder and hepatocyte ferroptosis to disrupt normal liver functions. In conclusion, chronic thermal stress can cause antioxidant capacity imbalance in the liver of Huso dauricus to mediate the ferroptosis process, which would finally disturb the lipid metabolism homeostasis. In further research, it will be necessary to verify the detailed cellular signaling pathways that are involved in the heat-stress-induced liver function disorder response based on the in vitro experiment, while the multi-organ crosswalk mode under the thermal stress status is also essential for understanding the comprehensive mechanism of heat-stress-mediated negative effects on fish species. Full article

Background/Objectives: Sweet potato is a tropical and subtropical crop and its growth and yield are susceptible to low-temperature stress. However, the molecular mechanisms underlying the low temperature stress of sweetpotato are unknown. Methods: In this work, combined transcriptome and metabolism analysis was employed to investigate the low-temperature responses of two sweet potato cultivars, namely, the low-temperature-resistant cultivar “X33” and the low-temperature-sensitive cultivar “W7”. Results: The differentially expressed metabolites (DEMs) of X33 at different time stages clustered in five profiles, while they clustered in four profiles of W7 with significant differences. Differentially expressed genes (DEGs) in X33 and W7 at different time points clustered in five profiles. More DEGs exhibited continuous or persistent positive responses to low-temperature stress in X33 than in W7. There were 1918 continuously upregulated genes and 6410 persistent upregulated genes in X33, whereas 1781 and 5804 were found in W7, respectively. Core genes involved in Ca²⁺ signaling, MAPK cascades, the reactive oxygen species (ROS) signaling pathway, and transcription factor families (including bHLH, NAC, and WRKY) may play significant roles in response to low temperature in sweet potato. Thirty-one common differentially expressed metabolites (DEMs) were identified in the two cultivars in response to low temperature. The KEGG analysis of these common DEMs mainly belonged to isoquinoline alkaloid biosynthesis, phosphonate and phosphinate metabolism, flavonoid biosynthesis, cysteine and methionine metabolism, glycine, serine, and threonine metabolism, ABC transporters, and glycerophospholipid metabolism. Five DEMs with identified Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways were selected for correlation analysis. KEGG enrichment analysis showed that the carbohydrate metabolism, phenylpropanoid metabolism, and glutathione metabolism pathways were significantly enriched and played vital roles in low-temperature resistance in sweet potato. Conclusions: These findings contribute to a deeper understanding of the molecular mechanisms underlying plant cold tolerance and offer targets for molecular breeding efforts to enhance low-temperature resistance. Full article

Some studies performed in our laboratory on pyrrole and its derivatives pointed towards the enrichment of the evaluations of these promising chemical structures for the potential treatment of neurodegenerative conditions in general and Parkinson’s disease in particular. A classical Paal-Knorr cyclization approach is applied to synthesize the basic hydrazine used for the formation of the designed series of hydrazones (15a–15g). The potential neurotoxic and neuroprotective effects of the newly synthesized derivatives were investigated in vitro using different models of induced oxidative stress at three subcellular levels (rat brain synaptosomes, mitochondria, and microsomes). The results identified as the least neurotoxic molecules, 15a, 15d, and 15f applied at a concentration of 100 µM to the isolated fractions. In addition, the highest statistically significant neuroprotection was observed for 15a and 15d at a concentration of 100 µM using three different injury models on subcellular fractions, including 6-hydroxydopamine in rat brain synaptosomes, tert-butyl hydroperoxide in brain mitochondria, and non-enzyme-induced lipid peroxidation in brain microsomes. The hMAOA/MAOB inhibitory activity of the new compounds was studied at a concentration of 1 µM. The lack of a statistically significant hMAOA inhibitory effect was observed for all tested compounds, except for 15f, which showed 40% inhibitory activity. The most prominent statistically significant hMAOB inhibitory effect was determined for 15a, 15d, and 15f, comparable to that of selegiline. The corresponding selectivity index defined 15f as a non-selective MAO inhibitor and all other new hydrazones as selective hMAOB inhibitors, with 15d indicating the highest selectivity index of >471. The most active and least toxic representative (15d) was evaluated in vivo on Rotenone based model of Parkinson’s disease. The results revealed no microscopically visible alterations in the ganglion and glial cells in the animals treated with rotenone in combination with 15d. Full article

Although age-related changes in the gut microbiome of pigs have been extensively studied, the dynamic patterns of fecal microbiota and SCFAs during the gestation-to-weaning period in sows remain poorly characterized. We aim to characterize the changes in fecal microbiota and SCFAs from pregnancy to weaning, and to investigate their associations with maternal weight gain during gestation. We systematically collected 100 fecal samples at four time points (day 30 of pregnancy (T1), 1–2 days before delivery (T2), day 10 after delivery (T3), and day 21 of weaning stage (T3)), and measured the body weight of sows at T1 (132 kg ± 10.8) and T2 (205 kg ± 12.1). The primary nutrient components of the diets during the gestation and lactation periods are summarized. All fecal samples were subjected to 16S rRNA gene sequencing. We found that a high proportion of crude fiber (bran) is a key feature of the gestation diet, which may affect enterotype shifts and gut microbial composition. Sows fed a high-fiber diet showed significant enrichment of gut microbiota, including genera such as Prevotellaceae_UCG-003, Prevotellaceae_NK3B31_group, and Prevotella_9 during the gestational period (LDA score > 2). Moreover, Eubacterium_coprostanoligenes_group (average relative abundance: 5.5%) and Lachnospiraceae_NK4A136_group (average relative abundance: 2.5%) were the dominant bacteria during the lactation stage. Fecal propionate and butyrate levels were lowest in late gestation, and propionate negatively and acetate positively correlated with body weight change (p < 0.05). Additionally, certain Prevotella taxa were associated with arachidonic acid metabolism and acetate production (p < 0.05). Our study identified key microbial communities across four stages from gestation to weaning and revealed that dietary patterns can shape the sow gut microbiota. Furthermore, we observed significant correlations between SCFAs and body weight change during pregnancy. These findings provide a scientific basis and theoretical support for future strategies aimed at modulating gut microbiota and targeting SCFAs to improve maternal health and productivity throughout the gestation-to-weaning period. Full article

During the automated picking of table grapes, the automatic recognition and segmentation of grape pedicels, along with the positioning of picking points, are vital components for all the following operations of the harvesting robot. In the actual scene of a grape plantation, however, it is extremely difficult to accurately and efficiently identify and segment grape pedicels and then reliably locate the picking points. This is attributable to the low distinguishability between grape pedicels and the surrounding environment such as branches, as well as the impacts of other conditions like weather, lighting, and occlusion, which are coupled with the requirements for model deployment on edge devices with limited computing resources. To address these issues, this study proposes a novel picking point localization method for table grapes based on an instance segmentation network called Progressive Global-Local Structure-Sensitive Segmentation (PGSS-YOLOv11s) and a simple combination strategy of morphological operators. More specifically, the network PGSS-YOLOv11s is composed of an original backbone of the YOLOv11s-seg, a spatial feature aggregation module (SFAM), an adaptive feature fusion module (AFFM), and a detail-enhanced convolutional shared detection head (DE-SCSH). And the PGSS-YOLOv11s have been trained with a new grape segmentation dataset called Grape-⊥, which includes 4455 grape pixel-level instances with the annotation of ⊥-shaped regions. After the PGSS-YOLOv11s segments the ⊥-shaped regions of grapes, some morphological operations such as erosion, dilation, and skeletonization are combined to effectively extract grape pedicels and locate picking points. Finally, several experiments have been conducted to confirm the validity, effectiveness, and superiority of the proposed method. Compared with the other state-of-the-art models, the main metrics $F1$ score and mask mAP@0.5 of the PGSS-YOLOv11s reached 94.6% and 95.2% on the Grape-⊥ dataset, as well as 85.4% and 90.0% on the Winegrape dataset. Multi-scenario tests indicated that the success rate of positioning the picking points reached up to 89.44%. In orchards, real-time tests on the edge device demonstrated the practical performance of our method. Nevertheless, for grapes with short pedicels or occluded pedicels, the designed morphological algorithm exhibited the loss of picking point calculations. In future work, we will enrich the grape dataset by collecting images under different lighting conditions, from various shooting angles, and including more grape varieties to improve the method’s generalization performance. Full article

This paper applies a multi-level social network analysis to examine Aragón’s innovation ecosystem, focusing on a decade of competitive public projects (2014–2023) aligned with the region’s Smart Specialisation Strategy (S3) 2021–2027. By mapping and weighting the participation of regional entities across regional, national, and European calls, the study uncovers how all types of local actors organise themselves around key specialisation areas. Moreover, a comparative benchmark is introduced by analysing more than 33,000 Horizon 2020 and Horizon Europe initiatives without Aragonese partners, revealing how to fill structural gaps and enrich the regional ecosystem through international collaboration. Results show strong funding concentration in four fields—Energy, Health, Agri-Food, and Advanced Technologies—while other historically strategic areas like Hydrogen and Water remain underrepresented. Although leading institutions (UNIZAR, CIRCE, ITA, AITIIP) play central roles in connecting academia and industry, direct collaboration among them is limited, pointing to missed synergies. Expanding previous SNA-based assessments, this study introduces a diagnostic tool to guide policy, proposing targeted actions such as challenge-driven calls, dedicated support programs, and cross-border consortia with top EU partners. Applied to two contrasting specialisation areas, the method offers sector-specific recommendations, helping policymakers align Aragón’s innovation capabilities with EU priorities and strengthen its position in both established and emerging domains. Full article

Virtual reality (VR) can enrich neuropsychological testing, yet the ergonomic trade-offs of its input modes remain under-examined. Seventy-seven healthy volunteers—young (19–29 y) and middle-aged (35–56 y)—completed a VR Trail Making Test with three pointing methods: eye-tracking, head-gaze, and a six-degree-of-freedom hand controller. Completion time, spatial accuracy, and error counts for the simple (Trail A) and alternating (Trail B) sequences were analysed in 3 × 2 × 2 mixed-model ANOVAs; post-trial scales captured usability (SUS), user experience (UEQ-S), and acceptability. Age dominated behaviour: younger adults were reliably faster, more precise, and less error-prone. Against this backdrop, input modality mattered. Eye-tracking yielded the best spatial accuracy and shortened Trail A time relative to manual control; head-gaze matched eye-tracking on Trail A speed and became the quickest, least error-prone option on Trail B. Controllers lagged on every metric. Subjective ratings were high across the board, with only a small usability dip in middle-aged low-gamers. Overall, gaze-based ray-casting clearly outperformed manual pointing, but optimal choice depended on task demands: eye-tracking maximised spatial precision, whereas head-gaze offered calibration-free enhanced speed and error-avoidance under heavier cognitive load. TMT-VR appears to be accurate, engaging, and ergonomically adaptable assessment, yet it requires age-specific–stratified norms. Full article

Tungsten and tungsten alloys are widely used in important industrial fields due to their high density, hardness, melting point, and corrosion resistance. However, machining often leaves processing marks on their surface, significantly affecting the surface quality of precision components in industrial applications. Electrolytic polishing offers high efficiency, low workpiece wear, and simple processing. In this study, an electrolytic polishing method is adopted and a novel trisodium phosphate–sodium hydroxide electrolytic polishing electrolyte is developed to study the effects of temperature, voltage, polishing time, and solution composition on the surface roughness of a tungsten–nickel–iron alloy. The optimal voltage, temperature, and polishing time are determined to be 15 V, 55 °C, and 35 s, respectively, when the concentrations of trisodium phosphate and sodium hydroxide are 100 g·L⁻¹ and 6 g·L⁻¹. In addition, glycerol is introduced into the electrolyte as an additive. The calculated LUMO value of glycerol is −5.90 eV and the HOMO value is 0.40 eV. Moreover, electron enrichment in the hydroxyl region of glycerol can form an adsorption layer on the surface of the tungsten alloy, inhibit the formation of micro-pits, balance ion diffusion, and thus promote the formation of a smooth surface. At 100 mL·L⁻¹ of glycerol, the roughness of the tungsten–nickel–iron alloy decreases significantly from 1.134 μm to 0.582 μm. The electrochemical polishing mechanism of the tungsten alloy in a trisodium phosphate electrolyte is further investigated and explained according to viscous film theory. This study demonstrates that the trisodium phosphate–sodium hydroxide–glycerol electrolyte is suitable for electropolishing tungsten–nickel–iron alloys. Overall, the results support the application of tungsten–nickel–iron alloy in the electronics, medical, and atomic energy industries. Full article

Background: Sternal wound infections (SWIs) remain a significant complication following cardiac surgery. Inflammatory and nutritional status are increasingly recognized as key contributors to their development. This study aimed to investigate the predictive utility of immunonutritional biomarkers and to evaluate the protective effect of combining sternal irrigation with an antibiotic-impregnated membrane. Methods: This retrospective cohort study included 480 patients undergoing off-pump coronary artery bypass grafting. Patients were categorized based on sternal management strategy (standard closure or local prophylaxis using gentamicin-enriched irrigation combined with an antibiotic-impregnated fascia lata membrane) and according to the severity of SWIs, classified as superficial or deep. Inflammatory and nutritional markers—including C-reactive protein (CRP), neutrophils, lymphocytes, albumin, neutrophil-to-lymphocyte ratio (NLR), C-reactive protein-to-albumin ratio (CAR), and prognostic nutritional index (PNI)—were assessed at three time points: preoperatively, on postoperative day 3, and after week 1. Results: SWIs were observed in 93 patients, including 75 superficial and 18 deep infections. The combined prophylactic approach was associated with a nearly 1.8-fold reduction in deep SWIs (OR: 0.55; 95% CI: 0.15–0.87) and a modest reduction in superficial infections (OR: 0.89; 95% CI: 0.5–1.3; p = 0.061). Threshold values of 3.75 for preoperative NLR, 9.8 for ΔNLR, and 16.7 for ΔCAR demonstrated strong predictive capacity for identifying patients at increased risk of developing deep SWIs. Patients receiving local prophylaxis exhibited significantly lower CRP, NLR, and CAR values and higher PNI levels at all time points. Conclusions: The combination of sternal irrigation and local antibiotic prophylaxis appears to confer protection against SWIs, potentially by mitigating postoperative inflammation. Immunonutritional biomarkers offer a promising means for early risk stratification. To confirm their clinical utility and broader applicability, these results should be validated in prospective, multicenter studies encompassing a wider range of cardiac surgical procedures. Full article

The enterovirus Coxsackievirus B3 causes a range of serious health problems, including aseptic meningitis, myocarditis, and pancreatitis. Currently, Coxsackievirus B3 has no targeted antiviral treatments or vaccines, leaving supportive care as the primary management option. Understanding how Coxsackievirus B3 interacts with and alters the blood–brain barrier may help identify new therapies to combat this often-devastating infection. We reanalyzed a previously published RNA sequencing dataset for Coxsackievirus B3-infected human-induced pluripotent stem-cell-derived brain endothelial cells (iBECs) to examine how Coxsackievirus B3 altered mRNA expression. By integrating GSEA, EnrichR, and iLINCs-based perturbagen analysis, we present a novel, systems-level approach to uncover potential drug repurposing candidates for CVB3 infection. We found dynamic changes in host transcriptomic response to Coxsackievirus B3 infection at 2- and 5-day infection time points. Downregulated pathways included ribosomal biogenesis and protein synthesis, while upregulated pathways included a defense response to viruses, and interferon production. Using iLINCs transcriptomic analysis, MEK, PDGFR, and VEGF inhibitors were identified as possible novel antiviral therapeutics. Our findings further elucidate Coxsackievirus B3-associated pathways in (iBECs) and highlight potential drug repurposing candidates, including pelitinib and neratinib, which may disrupt Coxsackievirus B3 pathology at the blood–brain barrier (BBB). Full article