Search Results (11,455)

The Body Mass Index (BMI), integrating body weight and length, is a widely used metric for obesity assessment in humans. As pigs serve as crucial biomedical models, the application of BMI in swine and its genetic basis remain poorly explored. This study aimed to investigate the genetic architecture of pig BMI and compare two carcass-based BMI metrics (BMI-S and BMI-O) for breeding applicability. A total of 439 Landrace × Yorkshire crossbred pigs were genotyped with a 50 K SNP chip; heritability was estimated via a mixed linear model, and genome-wide association study (GWAS) was performed using the BLINK model. BMI-S and BMI-O exhibited moderate-to-high heritability of 0.55 and 0.47, respectively, with 17 genome-wide significant SNPs detected—including the top associated SNP rs81382440 on chromosome 4 and rs80898583 on chromosome 7. Key candidate genes (GPHN, ADAM33, KCNH8, PDCD4) and 5 SNP-trait associations validated in PigQTLdb were linked to lipid/energy metabolism and muscle development. Carcass-based BMI improved phenotypic accuracy, and our findings provide core genetic markers and a theoretical basis for molecular breeding of pig body conformation and lipid deposition traits. Full article

Background/Objectives: Chemical methods for quantifying resistant starch (RS) in rice are labor-intensive, costly, and lack high repeatability, creating a bottleneck in breeding. This study aimed to develop specific, codominant molecular markers for the Wx gene to enable rapid and accurate genotype screening for RS content, thereby accelerating the development of high-RS rice varieties. Methods: Based on sequence alignment of the Wx gene in rice varieties with divergent RS content, a key single-nucleotide polymorphism was targeted. Two sets of tetra-primer amplification refractory mutation system polymerase chain reaction (ARMS-PCR) markers, T-Wx9-RS1 and T-Wx9-RS2, were designed. These markers were used to genotype diverse rice varieties and F₄ segregating populations, with results validated against standard chemical assays. Results: Sequence analysis identified a critical T → C base mutation at position 202 of the ninth exon in high-RS varieties. The developed ARMS-PCR markers successfully and consistently distinguished all three possible genotypes (homozygous mutant, homozygous wild-type, and heterozygous). The genotyping results showed complete concordance with the phenotypes determined by chemical methods. Conclusions: The developed molecular markers, T-Wx9-RS1 and T-Wx9-RS2, provide a rapid, reliable, and cost-effective tool for marker-assisted selection of high resistant starch content in rice. Their implementation can significantly enhance screening efficiency and expedite the breeding pipeline for novel, nutritionally improved rice cultivars. Full article

Background/Objectives: Post-COVID-19 pulmonary fibrosis (PCPF) and idiopathic pulmonary fibrosis (IPF) exhibit significant clinical and pathophysiological overlap, suggesting convergent molecular pathways driving fibrosis. This prospective longitudinal study investigates the sustained dysregulation of matrix metalloproteinases (MMP)-2 and MMP-9 and its relationship with evolving systemic inflammation and endothelial dysfunction in convalescent COVID-19 patients, with comparative analysis to IPF. Methods: We conducted a prospective observational study of 86 patients at 6 and 12 months post-SARS-CoV-2 infection, stratified by high-resolution CT evidence of PCPF (FB+ group, n = 32) or absence of fibrosis (FB− group, n = 54). Gene expression of MMP-2 and MMP-9 in peripheral blood leukocytes and circulating levels of MMP-2, MMP-9, pro-inflammatory cytokines (TNF-α, IL-6), and endothelial dysfunction markers (Endothelin-1 [ET-1], adhesion molecules) were quantified via qRT-PCR and ELISA. A pre-pandemic healthy control group (HD, n = 20) and an IPF patient group (n = 10) served as comparators. Results: A significant, sustained elevation of MMP-2 and MMP-9 was observed in all post-COVID-19 patients versus HDs, most pronounced in the FB+ group and qualitatively similar to IPF. A critical divergence emerged: FB− patients showed resolution of systemic inflammation (reduced TNF-α, IL-6), whereas FB+ patients exhibited persistent cytokine elevation. Critically, a delayed, severe endothelial dysfunction, characterized by a profound surge in ET-1 and elevated adhesion molecules, manifested exclusively in the FB+ cohort at 12 months. Positive correlations linked plasma MMP-2/9 levels with ET-1 (r_s = 0.65, p = 0.004; r_s = 0.49, p = 0.009) and ET-1 with sICAM-1 (r_s = 0.68, p = 0.01). Conclusions: The development of PCPF is associated with a distinct pathogenic triad: sustained MMP dysregulation, failure to resolve inflammation, and severe late-phase endothelial dysfunction. The correlative links between these components suggest a self-reinforcing loop. This systemic signature mirrors patterns in IPF, underscoring shared final pathways in fibrotic lung disease and identifying the MMP–inflammation–endothelial axis as a promising target for biomarker development and therapeutic intervention. Full article

Few-shot object detection (FSOD) in high-resolution remote sensing (RS) imagery remains challenging due to scarce annotations, large intra-class variability, and high visual similarity between categories, which together limit the generalization ability of convolutional neural network (CNN)-based detectors. To address this issue, we explore leveraging large vision-language models (LVLMs) for FSOD in RS. We propose a two-stage, parameter-efficient fine-tuning framework with hierarchical prompting that adapts Qwen3-VL for object detection. In the first stage, low-rank adaptation (LoRA) modules are inserted into the vision and text encoders and trained jointly with a Detection Transformer (DETR)-style detection head on fully annotated base classes under three-level hierarchical prompts. In the second stage, the vision LoRA parameters are frozen, the text encoder is updated using $K$-shot novel-class samples, and the detection head is partially frozen, with selected components refined using the same three-level hierarchical prompting scheme. To preserve base-class performance and reduce class confusion, we further introduce knowledge distillation and semantic consistency losses. Experiments on the DIOR and NWPU VHR-10.v2 datasets show that the proposed method consistently improves novel-class performance while maintaining competitive base-class accuracy and surpasses existing baselines, demonstrating the effectiveness of integrating hierarchical semantic reasoning into LVLM-based FSOD for RS imagery. Full article

Background and Clinical Significance: Focal hemorrhagic severity associated with posterior convexity pial brain arteriovenous malformation (AVM) cases can be exacerbated by hemodynamic stress focusing on focal areas of architectural weakness and by superficial venous outflow being restricted by non-redundant superficial venous drainage. This clinical case report exemplifies how bedside neurologic localization and angioarchitectural characteristics can inform the selection of microsurgical approaches for the treatment of ruptured AVMs that are directed at reducing hemorrhage recurrence risk through corridors based on rupture location. Case Presentation: An otherwise healthy young adult male (modified Rankin scale [mRS] pre-morbid = 0) initially presented with a thunderclap headache, emesis, photophobia, decreased level of consciousness (admitted Glasgow Coma Score [GCS] = 11; E3V3M5), and subsequent deficits including left-sided pyramidal weakness, visual field loss, and visuo-spatial neglect. A non-contrast computed tomogram (CT) confirmed an intraparenchymal hemorrhage (ICH) located within the right hemisphere’s posterior lobe. Angiographic evaluation of this AVM with catheter injection and three-dimensional reconstruction revealed a compact right occipital posterior convexity pial AVM (nidus 8 × 3 mm) supplied by distal cortical branches of the right middle cerebral artery (MCA); all blood draining from the nidus was directed to a single cortical vein which then drained into the superior sagittal sinus; there were two additional intranidal saccular aneurysms (approximately 3 × 2 mm and 3 × 3 mm). Because of the acute worsening secondary to ICH and because all venous drainage was superficial-only, a single-stage approach was selected given the urgency: decompressive evacuation of the hematoma via a corridor to the site of the AVM, followed by microsurgical removal of the AVM. The removal of the AVM was accomplished in a feeder-first, vein-last sequence, and en-passage arteries and parasagittal bridging veins were preserved throughout the procedure. Additionally, the two intranidal aneurysms identified as potential weak points during progressive devascularization of the AVM were specifically treated during the removal procedure. Following the successful removal of the AVM, the patient experienced a rapid recovery and returned to a nearly premorbid state of functioning, excepting a persistent small area of quadrantanopia. Conclusions: Rupture of posterior convexity AVMs may result in increased hemorrhagic severity due to localized architectural weaknesses in addition to the overall size of the AVM nidus. By correlating neurological findings, the topography of the hemorrhage, and angioarchitectural features early after rupture, emergency decisions regarding management can be better informed. The application of a hematoma-corridor, feeder-first/vein-last microsurgical approach for the treatment of such AVMs can achieve definitive curative results while minimizing damage to posterior cortical regions. Full article

Background: Non-syndromic cleft lip/palate (NCL/P) is a prevalent congenital anomaly. Despite an unclear epidemiological link between orofacial clefts and dental caries, genetic studies suggest that polymorphisms in taste receptor genes may influence caries risk. Objectives: This study had two primary objectives: (1) to compare SNPs in NCL/P-associated genes (IRF6, FOXE1) between Kuwaiti NCL/P cases and controls, and (2) to explore whether variants in caries-associated (KLK4, DSPP) and taste receptor (TAS1R2, TAS2R38) genes are associated with dental caries susceptibility in individuals with NCL/P, independent of overall caries prevalence. Methods: A case–control design was employed, with 25 NCL/P cases and 25 unaffected controls recruited from a Dental Craniofacial Clinic in Kuwait. Genomic DNA was extracted from buccal swabs, and SNP genotyping was performed using real-time PCR for genes related to NCL/P, dental caries, and taste perception. Caries status was assessed using the dmft/DMFT scoring system. The genotyped genes included NCL/P-related (IRF6, FOXE1), caries-related (KLK4, DSPP), and taste receptor genes (TAS1R2, TAS2R38). Results: At nominal significance, KLK4, DSPP, and TAS1R2 showed associations with NCL/P status, while IRF6 and FOXE1 did not. After applying Benjamini–Hochberg FDR correction across 10 SNPs, no allele- or genotype-level association remained significant (q < 0.05). The strongest signal was KLK4 rs2235091 (allele-level p = 0.016; q = 0.159). An exploratory age- and sex-adjusted logistic model for KLK4 suggested a possible effect (aOR 0.40; 95% CI 0.18–0.87; p = 0.021). Within-group analyses of caries burden revealed no associations that survived FDR control (lowest q = 0.056 for FOXE1 in controls). Conclusions: After controlling for multiple testing, no SNP showed a statistically significant association with NCL/P or caries burden. Nominal signals for KLK4, DSPP, and TAS1R2 did not survive FDR correction; an exploratory adjusted model suggested a possible KLK4 effect, but this requires cautious interpretation. The small sample size is a key limitation, and the findings highlight the need for larger, well-powered studies to clarify genetic contributions to NCL/P and caries risk. Full article

Chimeric antigen receptor (CAR)-T-cell therapy is a revolutionary approach in immunotherapy that has shown remarkable success in the treatment of blood cancers. Many preclinical studies are currently underway worldwide to extend the CAR-T-cell therapy benefits to a broad spectrum of cancers, using rodent models. Alternative in vivo platforms are essential for overcoming the drawbacks associated with rodent models, including immunodeficiency in humanized models, ethical concerns, extended time requirements, and cost. In this work, we used the chicken chorioallantoic membrane (CAM) assay to evaluate the in vivo efficacy of cluster-of-differentiation 19 (CD19)-targeting CAR-T cells expressing a second-generation CAR construct against human lymphoma derived from the Raji cell line. Our results confirm the efficacy of selected CAR-T cells on tumor growth, metastasis, and angiogenesis. Further, the chicken embryo has an intrinsic active immune system. Therefore, the dialog between CAR-T cells and endogenous immune cells, as well as their participation in the tumor challenge, has also been studied. In conclusion, our study demonstrates that the chicken CAM assay provides a relevant in vivo, 3Rs (Replacement, Reduction and Refinement)-compliant new approach methodology (NAM), which is well-suited for the current needs of preclinical research on CAR-T-cell therapy. Full article

Background/Objectives. Atrial fibrillation (AF) is the most common sustained cardiac arrhythmia and represents a major public health problem. Genetic factors contribute to AF susceptibility, including variants associated with atrial remodeling. Methods. This case–control study investigated the rs3903239 polymorphism of the PRRX1 gene in a Kazakh population. The main group included patients with AF (n = 75), the control group consisted of 2 subgroups: subgroup 1 (control group 1) included conditionally healthy patients (n = 73), subgroup 2 (control group 2) consisted of patients with arterial hypertension (AH) and coronary heart disease (CHD) without diagnosed AF at the time of inclusion in the study (n = 50). Genotype and allele frequencies were compared between patients with AF and two control groups. The frequency of the rs3903239 polymorphism genotypes of the PRRX1 gene in the main group and in the control groups was in the Hardy–Weinberg equilibrium. Results. The frequency of the rare G allele (AG + GG genotypes) was higher in patients with AF compared with conditionally healthy controls; however, this difference did not reach statistical significance (OR 1.357; 95% CI 0.845–2.178). Conclusions. The observed differences represent a non-significant trend and do not demonstrate a statistically confirmed association between the rs3903239 polymorphism of the PRRX1 gene and AF in the Kazakh population. Full article

Polyunsaturated fatty acids (PUFAs), particularly omega-3 derivatives such as docosahexaenoic acid (DHA), are precursors of specialized pro-resolving mediators (SPMs) that actively orchestrate the resolution of inflammation. Among these, maresins (MaRs) have gathered increasing attention due to their potent immunomodulatory and tissue-regenerative properties. This review provides a comprehensive synthesis of the current knowledge on the biosynthesis, structural diversity, and biological functions of MaRs, with a focus on MaR1. We discuss the enzymatic pathways involved in the generation of MaR1, MaR2, MaRs conjugates in tissue regeneration (MCTRs), and maresin-like lipid mediators (MaR-Ls), highlighting their roles in modulating inflammatory responses, promoting phagocytosis, and restoring tissue homeostasis. Preclinical evidence from in vitro and in vivo models demonstrates that MaRs exert protective effects in a wide range of pathological contexts, including neuroinflammation, liver injury, cardiovascular dysfunction, pulmonary diseases, and metabolic disorders. Although their therapeutic promise is well-supported, key gaps remain in the understanding of MaRs biosynthesis, receptor specificity, and translational applicability. This review emphasizes the importance of advancing mechanistic and clinical research to fully harness MaRs as part of next-generation therapeutics in inflammation-driven diseases. Full article

Maintaining adequate root-zone temperature in solar greenhouses during extreme cold is crucial for crop production. This study investigated the optimization of an auxiliary biomass heating system in a solar greenhouse. The heating performance was evaluated using an integrated methodology that combined orthogonal experimental design, Computational Fluid Dynamics (CFD) simulation, and Machine Learning (ML) surrogate modeling. First, a reliable CFD model, validated against experimental data (Index of Agreement, IA = 0.954), was used to generate high-fidelity temperature field data for nine layout schemes. Parameter sensitivity analysis revealed that the burning cave Diameter is the dominant factor (R = 6.01), followed by burial Depth (R = 2.00), with inter-pool Spacing having the least impact (R = 0.89). Subsequently, six ML algorithms were compared for use as a predictive surrogate model, with Lasso Regression demonstrating superior performance (R² = 0.934). Comprehensive optimization focused on maximizing the Suitable Area Ratio (R_s) in the critical 0.2 m depth root zone. The analysis conclusively identified the 2.5 m diameter group as optimal, achieving a maximum R_s of 90% and the lowest temperature standard deviation. The final recommended optimal design (2.5 m diameter, 0.7 m depth, 10 m spacing) significantly improves heating uniformity and efficiency. This integrated CFD-ML approach provides a scientific basis and a rapid assessment tool for the design and structural optimization of similar underground thermal systems in cold-climate agriculture. Full article

Forest resources are among the most important ecosystems on the earth. The semantic segmentation and accurate positioning of ground objects in forest remote sensing (RS) imagery are crucial to the emergency treatment of forest natural disasters, especially forest fires. Currently, most existing methods for image semantic segmentation are built upon convolutional neural networks (CNNs). Nevertheless, these techniques face difficulties in directly accessing global contextual information and accurately detecting geometric transformations within the image’s target regions. This limitation stems from the inherent locality of convolution operations, which are restricted to processing data structured in Euclidean space and confined to square-shaped regions. Inspired by the graph convolution network (GCN) with robust capabilities in processing irregular and complex targets, as well as Swin Transformers renowned for exceptional global context modeling, we present a hybrid semantic segmentation framework for forest RS imagery termed GSwin–Unet. This framework embeds the GCN model into Swin–Unet architecture to address the issue of low semantic segmentation accuracy of RS imagery in forest scenarios, which is caused by the complex texture features, diverse shapes, and unclear boundaries of land objects. GSwin–Unet features a parallel dual-encoder architecture of GCN and Swin Transformer. First, we integrate the Zero-DCE (Zero-Reference Deep Curve Estimation) algorithm into GSwin–Unet to enhance forest RS image feature representation. Second, a feature aggregation module (FAM) is proposed to bridge the dual encoders by fusing GCN-derived local aggregated features with Swin Transformer-extracted features. Our study demonstrates that, compared with the baseline models TransUnet, Swin–Unet, Unet, and DeepLab V3+, the GSwin–Unet achieves improvements of 7.07%, 5.12%, 8.94%, and 2.69% in the mean Intersection over Union (MIoU) and 3.19%, 1.72%, 4.3%, and 3.69% in the average F1 score (Ave.F1), respectively, on the RGB forest RS dataset. On the NIRGB forest RS dataset, the improvements in MIoU are 5.75%, 3.38%, 6.79%, and 2.44%, and the improvements in Ave.F1 are 4.02%, 2.38%, 4.72%, and 1.67%, respectively. Meanwhile, GSwin–Unet shows excellent adaptability on the selected GID dataset with high forest coverage, where the MIoU and Ave.F1 reach 72.92% and 84.3%, respectively. Full article

Early detection of small-scale fires is crucial for minimizing damage and enabling rapid emergency response. While recent deep learning-based fire detection systems have achieved high accuracy, they still face three key challenges: (1) limited deployability in resource-constrained edge environments due to high computational costs, (2) performance degradation caused by feature interference when jointly learning flame and smoke features in a single backbone, and (3) low sensitivity to small flames and thin smoke in the initial stages. To address these issues, we propose a lightweight dual-stream fire detection architecture based on YOLOv5n, which learns flame and smoke features separately to improve both accuracy and efficiency under strict edge constraints. The proposed method integrates two specialized attention modules: ESCFM++, which enhances spatial and channel discrimination for sharp boundaries and local flame structures (flame), and ESCFM-RS, which captures low-contrast, diffuse smoke patterns through depthwise convolutions and residual scaling (smoke). On the D-Fire dataset, the flame detector achieved 74.5% mAP@50 with only 1.89 M parameters, while the smoke detector achieved 89.2% mAP@50. When deployed on an NVIDIA Jetson Xavier NX(NVIDIA Corporation, Santa Clara, CA, USA)., the system achieved 59.7 FPS (single-stream) and 28.3 FPS (dual-tream) with GPU utilization below 90% and power consumption under 17 W. Under identical on-device conditions, it outperforms YOLOv9t and YOLOv12n by 36–62% in FPS and 0.7–2.0% in detection accuracy. We further validate deployment via outdoor day/night long-range live-stream tests on Jetson using our flame detector , showing reliable capture of small, distant flames that appear as tiny cues on the screen, particularly in challenging daytime scenes. These results demonstrate overall that modality-specific stream specialization and ESCFM attention reduce feature interference while improving detection accuracy and computational efficiency for real-time edge-device fire monitoring. Full article

To address the lack of accurate strength evaluation methods of the TMS concrete, this study focused on establishing a multi-age correlation model between the RS and CS of the TMS concrete. Sixteen groups of the TMS concrete with differentiated mix proportions were designed, and XRF/XRD techniques were used to characterize the chemical and mineral compositions of the TMS. RS and CS tests were conducted on standard cubic specimens at 3 d, 7 d, and 28 d ages, and linear, quadratic polynomial, and exponential functions were adopted for fitting analysis. The optimal model for each age was screened using the coefficient of determination, F-test, Akaike information criterion, and Bayesian information criterion. To verify the model and eliminate size effect interference, a large-scale plate specimen was fabricated for tests. Results showed that the correlation between RS and CS of the TMS concrete varied with age. Linear function was optimal for 3 d, quadratic polynomial function for 7 d, and exponential function for 28 d. All models passed the F-test. The relative errors of the piecewise model in large-scale specimen verification were stably controlled within 5.0%, meeting engineering-allowable error requirements. Crucially, the validation confirmed that the size effect is negligible for TMS concrete components within the investigated mix proportion range, eliminating the need for size correction factors. Consequently, this model can be directly applied to the non-destructive strength testing of TMS concrete prepared with P.O 42.5 Portland cement at 3 d, 7 d, and 28 d ages without the need for parameter adjustment regarding component dimensions. Full article

Background/Objectives: Advanced 3D cell culture techniques enhance the physiological relevance of in vitro models, while supporting the 3Rs principles (Reduction, Refinement, and Replacement) of animal experimentation. In this context, 3D collagen-based systems mimic key extracellular matrix properties, enabling more accurate cellular organization and phenotype. However, changes in culture dimensionality can affect RT-qPCR reference gene stability, underscoring the need for careful validation when combining 2D and 3D systems. Methods: AML12 cells were cultured for 7 days under different 2D and collagen-based 3D conditions. The expression stability of nine candidate housekeeping genes was systematically evaluated using established algorithms (BestKeeper, NormFinder, geNorm, RefFinder, and ΔCt method), followed by inter-group statistical and correlation analyses of raw Ct values. Albumin gene expression was used as a target gene. Results: Although all candidate genes initially met acceptable variability thresholds, a stepwise, exclusion-based analysis revealed distinct performance differences. Hprt, Ppia, and Actb emerged as the most stable, showing no intra-group variability or interaction with Albumin expression. Nevertheless, Ywhaz and Rplp0, despite their high stability, were compromised by significant correlation with Albumin. Furthermore, Ywhaz showed significant downregulation under 3D culture conditions. B2M, Gapdh, 18S, and Hmbs exhibited increased variability, likely reflecting metabolic and microenvironmental heterogeneity associated with prolonged 2D cultivation of AML12 cells. Conclusions: Overall, this study highlights the importance of context-dependent, exclusion-based reference gene validation when comparing 2D and 3D models, and demonstrates a new approach for reliable gene expression normalization in complex in vitro culture systems. Full article

Systemic Lupus Erythematosus (SLE) and primary Sjögren’s Disease (SjD) are autoimmune diseases characterized by the presence of autoantibodies that lead to damage in healthy tissues. The production of autoantibodies requires the activation and differentiation of B-lymphocytes into plasma cells. To achieve this effect, BAFF (B-lymphocyte activating factor), APRIL (A proliferation-inducing ligand), and their receptors are key factors. BAFF is a cytokine recognized by BAFF-R (BAFF receptor), which is increased and related to disease activity in both SLE and SjD patients. The H159Y mutation (rs61756766) in the gene encoding the BAFF-R, TNFRSF13C (Tumor Necrosis Factor Receptor Superfamily) has been shown in vitro to cause receptor hyperactivation via the NF-κB2 pathway. This study evaluated the frequency of this variant in a western Mexican population and its association with the risk of developing SLE and SjD. Genotypes of the TNFRSF13C H159Y (rs61756766) variant were determined by PCR-RFLP assay. sBAFF levels were measured by ELISA. The study included 300 SLE patients, 110 SjD patients, and 300 healthy subjects (HS). HS were in Hardy–Weinberg equilibrium. The data distribution was assessed using the Kolmogorov–Smirnov test. Group comparisons were conducted using the Chi-square test, Fisher’s exact test, or the Mann–Whitney U test, as appropriate. A p-value of <0.05 was considered statistically significant. In the Mexican population, allelic and genotypic distribution frequencies of the H159Y variant (rs61756766) were similar between SLE patients and HSs, while the variant was not found in SjD patients. SLE patients carrying the heterozygous CT genotype showed a trend toward higher soluble BAFF (sBAFF) levels than wild-type genotype patients. This variant does not confer risk to SLE or SjD in the Mexican population. However, the heterozygous genotype may be associated with high levels of sBAFF in SLE patients. Full article