Search Results (192)

Heading date (HD) is a key adaptive trait determining wheat regional suitability, yield stability, and resilience to environmental stresses. We dissected the genetic architecture of heading date (HD) by phenotyping a doubled haploid (DH) population (178 lines, CASL7AS × ZNL12) across five environments and constructing a high-density genetic map with the wheat 55K SNP array. A total of 38 QTLs associated with HD were identified on 12 chromosomes, among which 10 were consistently detected across multiple environments. Two major stable loci, QHD.ZAFU.2B and QHD.ZAFU.4A, explained substantial phenotypic variation and were considered key regulators of heading time. Candidate gene analysis revealed Ppd-B1 (TraesCSU02G196100) as the causal gene for QHD.ZAFU.2B. Within QHD.ZAFU.4A, a zinc finger RNA-binding protein gene (TraesCS4A02G394400) exhibiting strong flag-leaf expression at the heading stage was identified as the most promising candidate. Notably, most favorable alleles were derived from ZNL12, highlighting its potential for breeding applications aimed at manipulating heading time. These results provide valuable genomic resources and molecular targets for marker-assisted selection aimed at optimizing flowering time and improving wheat adaptation. Full article

This study examines the high-temperature degradation of Hastelloy C276, a corrosion-resistant nickel-based alloy, during exposure to combustion products generated by methane and 99% cracked ammonia. Using a high-pressure optical combustor (HPOC) at 4 bar and exhaust temperatures of 815–860 °C, standard tensile specimens were exposed for five hours to fully developed post-flame exhaust gases, simulating real industrial turbine or burner conditions. The surfaces and subsurface regions of the samples were analysed using scanning electron microscopy (SEM; Zeiss Sigma HD FEG-SEM, Carl Zeiss, Oberkochen, Germany) and energy-dispersive X-ray spectroscopy (EDX; Oxford Instruments X-MaxN detectors, Oxford Instruments, Abingdon, United Kingdom), while mechanical properties were evaluated by tensile testing, and the gas-phase compositions were tracked in detail for each fuel blend. Results show that exposure to methane causes moderate oxidation and some grain boundary carburisation, with localised carbon enrichment detected by high-resolution EDX mapping. In contrast, 99% cracked ammonia resulted in much more aggressive selective oxidation, as evidenced by extensive surface roughening, significant chromium depletion, and higher oxygen incorporation, correlating with increased NO_x in the exhaust gas. Tensile testing reveals that methane exposure causes severe embrittlement (yield strength +41%, elongation −53%) through grain boundary carbide precipitation, while cracked ammonia exposure results in moderate degradation (yield strength +4%, elongation −24%) with fully preserved ultimate tensile strength (870 MPa), despite more aggressive surface oxidation. These counterintuitive findings demonstrate that grain boundary integrity is more critical than surface condition for mechanical reliability. These findings underscore the importance of evaluating material compatibility in low-carbon and hydrogen/ammonia-fuelled combustion systems and establish critical microstructural benchmarks for the anticipated mechanical testing in future work. Full article

Reliable traffic-signal information delivery is critical for safe navigation through signalized intersections, particularly for low-cost autonomous vehicles that rely on Vehicle-to-Network (V2N) communication rather than on-board HD maps or expensive perception sensors. Ensuring this selective delivery requires accurate infrastructure-side map-matching, which becomes challenging when vehicles operate with only Standard Definition (SD) maps and noisy GNSS measurements. This study comparatively evaluates five infrastructure-side map-matching algorithms under varying GNSS errors and road-network densities using real trajectories from Jeju Island with controlled Gaussian perturbations. The framework includes geometric matching, Extended Kalman Filtering (EKF), route-constrained filtering, grid-based spatial indexing, and a hybrid route–EKF fallback mechanism, executed in real time on a cloud-hosted Kafka pipeline. The hybrid route–EKF algorithm exhibited consistently high and stable link-matching accuracy (0.99308–0.96546 across GPS error groups; 0.9887–0.9777 across density groups) together with strong signal-matching accuracy (0.99394–0.96950; 0.9865–0.9790). Route-constrained and Kalman-based approaches also performed well, while heading-based matching showed clear limitations. These results indicate that infrastructure-side map-matching provides a scalable foundation for cloud-assisted traffic-signal information services and supports the feasibility of delivering reliable traffic-signal information to low-cost autonomous platforms. Full article

Background: Optical coherence tomography (OCT) can quantify the morphology and dimensions of a macular hole for diagnosis and treatment planning. Objective: The aim of this study was to perform automatic segmentation of macular holes (MHs) and cysts from OCT macular volumes using a deep learning-based model and to quantitatively evaluate decision reliability using the model’s focus regions and GradientSHAP-based explainability. Methods: In this study, we automatically segmented MHs and cysts in OCT images from the open-access OIMHS dataset. The dataset comprises 125 eyes from 119 patients and 3859 OCT B-scans. OCT B-scan slices were input to a UNet-48-based model with a 2.5D stacking strategy. Performance was evaluated using Dice and intersection-over-union (IoU), boundary accuracy was evaluated using the 95th-percentile Hausdorff distance (HD95), and calibration was evaluated using the expected calibration error (ECE). Explainability was quantified from GradientSHAP maps using lesion coverage and spatial focus metrics: Attribution Precision in Lesion (APILτ), which is the proportion of attributions (SHAP contributions) falling inside the lesion; Attribution Recall in Lesion (ARILτ), which is the proportion of the true lesion covered by the attributions; and leakage (Leakτ = 1 − APILτ), which is the proportion of attributions falling outside the lesion. Spatial focus was monitored using the center-of-mass distance (COM-dist), which is the Euclidean distance between the attribution center and the segmentation center. All metrics were calculated using the top τ% of the pixels with the highest SHAP values. SHAP features were clustered using PCA and k-means. Explanations were calculated using the clinical mask in ground truth (GT) mode and the model segmentation in prediction (Pred) mode. Results: The Dice/IoU values for holes and cysts were 0.94/0.91 and 0.87/0.81, respectively. Across lesion classes, HD95 = 6 px and ECE = 0.008, indicating good boundary accuracy and calibration. In GT mode (τ = 20), three regimes were observed: (i) retina-dominant: high ARIL (hole: 0.659; cyst: 0.654), high Leak (hole: 0.983; cyst: 0.988), and low COM-dist (hole: 7.84 px; cyst: 6.91 px), with the focus lying within the retina and largely confined to the retinal tissue; (ii) peri-lesional: highest ARIL (hole: 0.684; cyst: 0.719), relatively lower Leak (hole: 0.917; cyst: 0.940), and medium/high COM-dist (hole: 16.22 px; cyst: 10.17 px), with the focus located around the lesion; (iii) narrow-coverage: primarily seen for cysts in GT mode (ARIL: 0.494; Leak: 1.000; COM-dist: 52.02 px), with markedly reduced coverage. In Pred mode, the ARIL20 for holes increased in the retina-dominant cluster (0.758) and COM-dist decreased (6.24 px), indicating better agreement with the model segmentation. Conclusions: The model exhibited high accuracy and good calibration for MH and cyst segmentation in OCT images. Quantitative characterization of SHAP validated the model results. In the clinic, peri-lesion and narrow-coverage conditions are the key situations that require careful interpretation. Full article

Background: Influenza poses a significant health threat to children under nine, who are at high risk of severe complications. Influenza vaccination is a key prevention strategy, but pediatric trials use heterogeneous safety and immunogenicity outcomes, follow-up windows, and dosing strata that hinder meaningful cross-trial comparison. Objective: To map how safety and immunogenicity outcomes are defined, collected, stratified, and reported across clinical trials of seasonal influenza vaccines in healthy children aged 6 months to 8 years, and to identify reporting patterns and gaps that limit cross-trial comparability. Methods: Studies were identified through a structured PubMed/MEDLINE search first conducted 20 April 2025 and last conducted June 2025, following JBI and PRISMA 2020 guidelines. We included clinical trials reporting at least one safety outcome in healthy children 6 months to 8 years old. Heterogeneity in outcome definitions, follow-up windows, and dose strata precluded meta-analysis; we conducted a narrative and per-study synthesis. Risk of bias was evaluated with RoB 2 for randomized trials and ROBINS-I (V2) for non-randomized studies following Cochrane guidance. Descriptive and visual syntheses were utilized. Results: Of 293 records, 20 studies comprising approximately [n = 12,267] pediatric participants met the inclusion criteria. All included studies evaluated inactivated, egg-based seasonal influenza intramuscular vaccines. Reporting windows and dose handling varied widely. Vaccine-related serious adverse events (SAEs) were rare (only four events, with reported SAEs happening in children 6–35 months old immunized with quadrivalent formulations; all SAEs resolved and did not result in participant withdrawal from the study). No SAEs were reported in children 3–8 years old. Immunogenicity outcomes are presented as reported by each trial, with baseline and post-vaccination sampling days reproduced; no cross-trial synthesis was performed. Conclusions: Seasonal, inactivated intramuscular influenza vaccines show a favorable safety and immunogenicity profile in healthy children 6 months to 8 years old. However, heterogeneous outcome definitions, variable safety follow-up windows, limited dose- and priming-specific reporting, and inconsistent immunogenicity schedules substantially constrain cross-trial comparability. Funding and Registration: Primary funding was provided by the Eunice Kennedy Shriver National Institute of Child Health and Human Development (Grant HD109732). This review was registered in PROSPERO (registration number: CRD420251237499). Full article

Background/Objective: Despite available SARS-CoV-2 vaccines, coverage gaps persist due to unequal distribution and limited access. Microarray patches offer a promising solution to address these challenges, providing a safer and easier-to-use alternative. We present a randomised, double-blind Phase I clinical trial evaluating the SARS-CoV-2 spike protein subunit vaccine, HexaPro, delivered via a high-density microarray patch (HD-MAP). Methods: Forty-four healthy adults aged 18–50 years were assigned to receive either 0 µg, 15 µg, or 45 µg of HexaPro via the HD-MAP, with the primary objective of assessing safety and tolerability. Results: The HD-MAP HexaPro vaccine was found to be safe and well tolerated, with only mild adverse events reported. Following vaccination significant increases in spike-specific IgG titers were observed by 7 days and remained stable through day 90. This IgG response effectively neutralised multiple SARS-CoV-2 variants. Additionally, the HexaPro HD-MAP was stable for up to 12 months at 40 °C. Conclusions: These findings support the continued clinical development of HD-MAPs as an alternative vaccination strategy. Full article

The large scale and shape variation in breast lesions make their segmentation extremely challenging. A breast ultrasound image segmentation model integrating Mamba-CNN and feature interaction is proposed for breast ultrasound images with a large amount of speckle noise and multiple artifacts. The model first uses the visual state space model (VSS) as an encoder for feature extraction to better capture its long-range dependencies. Second, a hybrid attention enhancement mechanism (HAEM) is designed at the bottleneck between the encoder and the decoder to provide fine-grained control of the feature map in both the channel and spatial dimensions, so that the network captures key features and regions more comprehensively. The decoder uses transposed convolution to upsample the feature map, gradually increasing the resolution and recovering its spatial information. Finally, the cross-fusion module (CFM) is constructed to simultaneously focus on the spatial information of the shallow feature map as well as the deep semantic information, which effectively reduces the interference of noise and artifacts. Experiments are carried out on BUSI and UDIAT datasets, and the Dice similarity coefficient and HD₉₅ indexes reach 76.04% and 20.28 mm, respectively, which show that the algorithm can effectively solve the problems of noise and artifacts in ultrasound image segmentation, and the segmentation performance is improved compared with the existing algorithms. Full article

Background/Objectives: Constructing a comprehensive spatiotemporal map of tumor heterogeneity is essential for understanding tumor evolution, with copy number variation (CNV) being a significant feature. Existing studies often rely on tools originally developed for single-cell data, which fail to utilize spatial information, often leading to an incomplete map of clonal architecture. Our study aims to develop a model that fully leverages spatial omics data to elucidate spatio-temporal changes in tumor evolution. Methods: Here, we introduce SCOIGET (Spatial COpy number Inference by Graph on Evolution of Tumor), a novel framework using graph neural networks with graph attention layers to learn spatial neighborhood features of gene expression and infer copy number variations. This approach integrates spatial multi-omics features to create a comprehensive spatial map of tumor heterogeneity. Results: Notably, SCOIGET achieves a substantial reduction in error metrics (e.g., mean squared error, cosine similarity, and distance measures) and produces superior clustering performance, as indicated by higher Silhouette Scores compared to existing methods, validated by both simulated data with spot-level ground truth and patient cohorts. Our model significantly enhances the accuracy of tumor evolution depiction, capturing detailed spatial and temporal changes within the tumor microenvironment. It is versatile and applicable to various downstream tasks, demonstrating strong generalizability across different spatial omics platforms, including 10× Visium and Visium HD and various cancer types, including colorectal cancer and prostate cancer. This robust performance improves research efficiency and provides valuable insights into tumor progression. Conclusions: SCOIGET offers an innovative solution by integrating multiple features and advanced algorithms, providing a detailed and accurate representation of tumor heterogeneity and evolution, aiding in the development of personalized cancer treatment strategies. Full article

Potato is globally recognized as the fourth most crucial staple food crop, trailing behind wheat, rice, and maize. Cadmium (Cd), a predominant heavy-metal pollutant in agricultural soils, demonstrates high biological toxicity and mobility. Therefore, exploring the genetic and molecular mechanisms underpinning cadmium tolerance in potato is of substantial theoretical and practical significance. In this research, an F₂ population composed of 170 families was established through the cross-breeding of homozygous diploid potato lines HD-5 (highly cadmium-tolerant) and M9 (cadmium-sensitive). Employing hydroponic cultivation, six traits, namely plant height (PH), root length (RL), shoot fresh weight (SFW), root fresh weight (RFW), chlorophyll content (SPAD), and nitrogen content (LNC), were measured in potato seedlings following a 9-day treatment with 40 mg·L⁻¹ CdCl₂. By utilizing the high-density genetic map of this population for QTL mapping, a total of 35 genetic loci associated with cadmium tolerance in potato seedlings were identified. Notably, loci21 and loci22 on chromosome 9, loci29 on chromosome 10, and loci31 and loci33 on chromosome 12 were consistently detected across multiple environmental conditions. This reproducibility across environments suggests the phenotypic stability of these five loci, which are thus considered reliable and robust genetic determinants. In addition, transcriptome sequencing analysis of roots from parental lines HD-5 and M9 after cadmium treatment revealed that significantly differentially expressed genes between the two parents were associated with glutathione metabolism and photosynthesis. By integrating QTL mapping, transcriptome analysis, and gene annotation, we screened four candidate genes involved in cadmium tolerance regulation: DM8C09G01000 (GST), DM8C09G01060 (GST), DM8C09G02130 (OXP1), and DM8C06G22960 (PsaH). These findings provide molecular targets and a genetic basis for molecular breeding of cadmium-tolerant potato varieties. Full article

Plant tissues exhibit a layered architecture that makes spatial context decisive for interpreting transcriptional changes. This review explains why the location of gene expression is as important as its magnitude and synthesizes advances uniting single-cell/nucleus RNA-seq with spatial transcriptomics in plants. Surveyed topics include platform selection and material preparation; plant-specific sample processing and quality control; integration with epigenomic assays such as single-nucleus Assay for Transposase-Accessible Chromatin using sequencing (ATAC) and Multiome; and computational workflows for label transfer, deconvolution, spatial embedding, and neighborhood-aware cell–cell communication. Protoplast-based single-cell RNA sequencing (scRNA-seq) enables high-resolution profiling but introduces dissociation artifacts and cell-type biases, whereas ingle-nucleus RNA sequencing (snRNA-seq) improves the representation of recalcitrant lineages and reduces stress signatures while remaining compatible with multiomics profiling. Practical guidance is provided for mitigating ambient RNA, interpreting organellar and intronic metrics, identifying doublets, and harmonizing batches across chemistries and studies. Spatial platforms (Visium HD, Stereo-seq, bead arrays) and targeted imaging (Single-molecule fluorescence in situ hybridization (smFISH), Hairpin-chain-reaction FISH (HCR-FISH), Multiplexed Error-Robust Fluorescence In Situ Hybridization (MERFISH)) are contrasted with plant-specific adaptations and integration pipelines that anchor dissociated profiles in anatomical coordinates. Recent atlases in Arabidopsis, soybean, and maize illustrate how cell identities, chromatin accessibility, and spatial niches reveal developmental trajectories and stress responses jointly. A roadmap is outlined for moving from atlases to interventions by deriving gene regulatory networks, prioritizing cis-regulatory targets, and validating perturbations with spatial readouts in crops. Together, these principles support a transition from descriptive maps to mechanism-informed, low-pleiotropy engineering of agronomic traits. Full article

High-definition (HD) maps, with their accurate and detailed road information, have become a core component of autonomous vehicles. These maps help vehicles with environment perception, precise localization, and path planning. However, outdated maps can compromise vehicle safety, making map updates a key research area in intelligent driving technology. Traditional surveying methods are accurate but expensive, making them unsuitable for large-scale and frequent updates. Most existing crowdsourced map update methods focus on matching perception data with map features. However, they lack sufficient analysis of the reliability and uncertainty of perception results, making it difficult to ensure the accuracy of map updates. To address this, this paper proposes an HD map change detection method that considers the uncertainty of single-source perception results. This method extracts road feature information using onboard camera and Global Navigation Satellite System (GNSS) data and improves matching accuracy by combining geometric proximity and consistency. Additionally, a probability-based change detection method is introduced, which evaluates the reliability of map changes by integrating observations from multi-source vehicles. To validate the effectiveness of the proposed method, experiments were conducted on both simulation data and real-world road data, and the detection results of single-source data were compared with those of multi-source fused data. The experimental results indicate that the probabilistic estimation method proposed in this study effectively identifies the three typical scenarios of addition, deletion, and modification in HD map change detection. Additionally, the method achieves more than a 10% improvement in both precision and recall compared to single-source data. Full article

Background and Objectives: Interdialytic blood pressure (BP) better reflects volume status and cardiovascular risk in hemodialysis (HD) patients than peridialytic readings. High-efficiency dialysis techniques—online hemodiafiltration (HDF) in pre-, post-, and mixed-dilution modes, and expanded hemodialysis (HDx) with medium cut-off membranes—aim to improve solute clearance and hemodynamic stability. Their comparative impact on interdialytic BP control remains unclear. This randomized cross-over study compared interdialytic BP profiles across these modalities under standardized treatment conditions. Materials and Methods: Sixteen clinically stable adults with end-stage kidney disease sequentially underwent high-flux HD, HDx, and HDF in pre-, post-, and mixed-dilution configurations, each for one month. Dialysis prescriptions, dry weight, and antihypertensive therapy remained constant. Home BP was measured twice daily on non-dialysis days, yielding ~3600 observations. Systolic (SBP), diastolic (DBP), and mean arterial pressure (MAP) were analyzed by repeated-measures ANOVA with Bonferroni correction. Results: Significant differences were found among modalities for SBP (p = 0.009), DBP (p = 0.004), and MAP (p < 0.001). HDx achieved the lowest mean BP values—SBP 129 (95% CI 127–131) mmHg; DBP 74 (95% CI 73–75) mmHg; MAP 93 (95% CI 91–94) mmHg—significantly lower than high-flux HD and post-dilution HDF (p < 0.05). Differences versus pre- and mixed-HDF did not reach significance. Conclusions: HDx provided modest but consistent reductions in interdialytic BP compared with diffusive and convective high-efficiency modalities. Trial Registration: Ethics Committee of the Medical University of Gdańsk (NKBBN/479-759/2022). Full article

As automated driving technologies become more mature, there is an increasing reliance on digital maps to support safe and efficient driving. Sensors like cameras and radars can be limited by occlusions, lighting conditions, or weather, and often fall short. High-definition (HD) maps offer excellent accuracy, but they are expensive to produce. These limitations make these techniques impractical for large-scale deployment. What makes our approach particularly attractive is its hardware simplicity: the entire process requires only a precise GNSS receiver and a commonly available lane detection camera, eliminating the need for expensive sensors like LiDAR or complex multi-vehicle fleets. We rigorously evaluated our method in a highway environment, where a vehicle equipped with our generated maps successfully executed autonomous lane following and adapted its speed based on detected speed limit signs. The positional deviation of the resulting maps was consistently under 5 cm. Full article

Stropharia rugosoannulata is a widely cultivated edible fungus with high economic and nutritional value. It is a tetrapolar heterothallic basidiomycete. The development of single nucleotide polymorphism (SNP) markers for mating-type identification holds considerable promise for enhancing breeding efficiency. In our study, one group of test crosses and three-round mating experiments from one parental strain were conducted in order to ascertain the mating type in this species. Segregation distortion in mating types was observed after single-spore isolation, which was deviated from Mendelian inheritance. The monokaryotic strain Q25 was derived from the dikaryotic mycelium S1 of S. rugosoannulata. The genome map of strain Q25 with 48.27 Mb and 14 chromosomes was constructed using genomic, transcriptomic, and high-throughput chromosome conformation capture (Hi-C) sequencing technologies. The locations of mating-type loci were identified using genomic annotation. The mating-type A locus is located in chromosome 1, with the gene sequence of β-fg, HD2, HD1, and MIP. The mating-type B locus is located in chromosome 12. It contains five pheromone receptors and five pheromone precursor genes. Two pairs of highly specific and stable primers were designed based on SNP loci in A and B mating types. A1, A2, B1, and B2 alleles were precisely distinguished with these primers, which were subsequently applied in cultivation experiments. This study lays a foundation for the precise breeding of S. rugosoannulata. Full article

Background: Pneumothorax (PTX) requires rapid recognition in emergency and critical care. Lung ultrasound (LUS) offers a fast, radiation-free alternative to computed tomography (CT), but its accuracy is limited by operator dependence. Artificial intelligence (AI) may standardize interpretation and improve performance. Methods: This retrospective single-center study included 46 patients (23 with CT-confirmed PTX and 23 controls). Sixty B-mode and M-mode frames per patient were extracted using a Clarius C3 HD3 wireless device, yielding 2760 images. CT served as the diagnostic reference. Experimental studies were conducted within the framework of three scenarios. Transformer-based models, Vision Transformer (ViT) and DINOv2, were trained and tested under two scenarios: random frame split and patient-level split. Also, Random Forest (RF) and eXtreme Gradient Boosting (XGBoost) classifiers were trained on the feature maps extracted by using Video Vision Transformer (ViViT) for ultrasound video sequences in Scenario 3. Model performance was evaluated using accuracy, sensitivity, specificity, F1-score, and area under the ROC curve (AUC). Results: Both transformers achieved high diagnostic accuracy, with B-mode images outperforming M-mode inputs in the first two scenarios. In Scenario 1, ViT reached 99.1% accuracy, while DINOv2 achieved 97.3%. In Scenario 2, which avoided data leakage, DINOv2 performed best in the B-mode region (90% accuracy, 80% sensitivity, 100% specificity, F1-score 88.9%). ROC analysis confirmed strong discriminative ability, with AUC values of 0.973 for DINOv2 and 0.964 for ViT on B-mode images. Also, both RF and XGBoost classifiers trained on the ViViT feature maps reached 90% accuracy on the video sequences. Conclusions: AI-assisted LUS substantially improves PTX detection, with transformers—particularly DINOv2—achieving near-expert accuracy. Larger multicenter datasets are required for validation and clinical integration. Full article