Search Results (3,180)

Background/Objectives: There remains a need for additional prognostic markers in classic follicular lymphoma (cFL) to identify aggressive disease. Immunohistochemical stains such as Ki-67, MYC, and p53 have shown variable associations with histologic grade and adverse outcomes. In this study, we aimed to assess intrafollicular Ki-67, MYC, and p53 expression in cFL via immunohistochemistry, quantified by both manual and digital methods, and evaluate their relation to histologic grade and clinical outcomes. Methods: We evaluated 37 cases of cFL from 2000 to 2019 and performed immunohistochemistry for Ki-67, MYC, and p53 on tumor microarray tissue. Stains were assessed within follicles by digital pathology means on QuPath software and via manual low-power estimates. Results:MYC expression was greater in FL3A compared to FL1–2 across all digital and manual scoring methods (all p < 0.05). Ki-67 and p53 expression did not differ by histologic grade group. No biomarker showed a significant association with adverse clinicopathologic features or outcomes, including FLIPI risk group, bulky disease, clinical stage, event-free survival, or overall survival. Manual and digital scores demonstrated strong correlations for all markers (ρ = 0.71–0.89, all p < 0.001). Conclusions: In our cohort, MYC expression was increased in FL3A compared to FL1–2, while no intrafollicular biomarker measurement was associated with adverse clinicopathologic features or clinical outcomes in exploratory analyses. These findings should be interpreted with caution in light of our limited cohort size. Strong concordance between manual and digital scoring supports the feasibility of digital IHC quantification in cFL. Full article

Peach (Prunus persica) fruit pigmentation is largely associated with anthocyanin accumulation, whereas colorless flavonols such as kaempferol glycosides may reflect alternative use of shared flavonoid precursors. To examine the relationship between anthocyanin and selected kaempferol glycoside accumulation, we analyzed 15 peach accessions classified by red, white, or yellow flesh pigmentation. Skin color was quantified using the a*/b* ratio, where a* represents redness/greenness and b* represents yellowness/blueness. Red-fleshed accessions showed higher skin a*/b* values and accumulated higher levels of total anthocyanins, particularly cyanidin-3-glucoside, than white and yellow accessions. In contrast, kaempferol-3-rhamnoside preferentially accumulated in white-fleshed accessions. Expression analysis of flavonoid pathway genes showed that dihydroflavonol 4-reductase (PpDFR) was more highly expressed in red accessions, whereas flavonol synthase (PpFLS) was more highly expressed in white accessions; chalcone synthase (PpCHS), flavanone 3-hydroxylase (PpF3H), flavonoid 3′-hydroxylase (PpF3′H), and anthocyanidin synthase (PpANS) showed no significant differences among color groups. Heterologous overexpression of PpF3′H in Arabidopsis thaliana, a well-characterized model plant for flavonoid biosynthesis, was associated with increased seed anthocyanin accumulation and a lower kaempferol-to-quercetin ratio, supporting its catalytic capacity to influence flavonoid composition in an exogenous system. Overall, these results indicate that differential anthocyanin and selected kaempferol glycoside accumulation in peach is associated with the relative expression patterns of branch-related flavonoid genes, particularly PpDFR and PpFLS. This study provides targeted metabolic and transcriptional evidence for understanding peach flesh and skin pigmentation and provides mechanistic insight into flavonoid branch competition linking gene expression patterns with metabolite allocation, and identifies candidate genes for improving fruit color and flavonoid-related nutritional quality. Full article

Greenhouse studies were conducted to assess the impact of reniform nematode (Rotylenchulus reniformis) isolates originating from nine states in the US cotton belt (TN, AL, MS, LA, TX, AR, FL, SC, and GA) on the development of cotton. Two cotton cultivars, DP 2141NR B3XF, marketed as reniform nematode resistant, and DP 2317 B3TXF, a susceptible control, were employed. Origin of the reniform nematode significantly influenced plant height, number of leaves, boll weight, chlorophyll content and plant vigor, but not photosynthesis and transpiration. While cotton plants inoculated with any of the isolates sustained negative developmental impacts in comparison with the uninoculated plants, the level of these impacts differed by the origin of the isolate. The isolates originating from the delta region (AR, MS and TN) had the most pronounced negative impacts on cotton. The development of plants inoculated with the FL, SC, TX, and LA isolates were moderately impacted while plants inoculated with the AL and the GA isolates showed the least amount of impact. Across all isolates and in comparison with the susceptible control, the resistant cultivar was taller, produced more leaves and bolls, and had superior vigor, chlorophyll content, photosynthesis and transpiration. As the ability of reniform nematode to impact cotton development can differ based on geography, results from this study implied a need for the development of niche-specific reniform nematode management methods in cotton. Full article

Introduction: The early stages of fish represent a critical phase for survival and recruitment, as they are highly vulnerable to both biotic and abiotic factors, as well as anthropogenic pressures. To enhance survival, many marine species use estuaries as nursery areas. However, these ecosystems are increasingly exposed to contaminants such as microplastics (MPs; plastic particles < 5 mm) that can cause several direct or indirect negative impacts on fish larvae, namely impairing their development or survival. Objective: This study aimed to quantify and compare temporal changes in the ratio of microplastics (MPs) to fish larvae (FL) (MP:FL) in the Douro estuary (NW Portugal), assessing how exposure to MPs varies across years and seasons. Methodology: Seasonal sampling campaigns were conducted in the Douro estuary during 2021/2022 and 2025. Multiple stations along the estuary were sampled using plankton tows with a 0.5 mm mesh size. In the laboratory, fish larvae were sorted and identified, and the remaining material was processed to isolate and quantify MPs. The recovered MPs were subsequently characterized according to type, size, and color. Results: Data from 2022 indicated that Clupeidae, Gobiidae, and Gadidae were the most abundant fish families, while colorless and blue fibers between 2 and 3 mm were the dominant MP types. Data from 2025 showed that Gobiidae, Labridae, and Atherinidae were the most abundant families, with similar MP types observed in water in 2022. The ratio of MPs:FL in summer and autumn of 2021/2022 was 36 and 65 MPs:1 FL, respectively, whereas in 2025 it was 0.26 and 3.80 MPs:1 FL, respectively. Conclusions: These preliminary results indicate a decreasing trend in the ratio of MP:fish larvae over time. Although further data analysis is ongoing, the observed interannual differences highlight the importance of long-term monitoring of estuarine nursery areas to better understand contamination dynamics and their potential effects on early fish life stages. Full article

Impaction of the mandibular third molar in proximity to the mandibular canal increases the risk of inferior alveolar nerve injury. Panoramic radiography is routinely used to assess this relationship. Automated classification of molar–canal overlap could support clinical triage and reduce unnecessary CBCT referrals, while Federated Learning (FL) enables multi-center collaboration without sharing patient data. We compared Local Learning (LL), FL, and Centralized Learning (CL) for binary overlap/no-overlap classification on cropped panoramic radiographs partitioned across eight independent labelers in a simulated heterogeneous multi-center setting. A pretrained ResNet-34 was trained under each paradigm and evaluated using per-client metrics with locally optimized thresholds and pooled test performance with a global threshold. Performance was assessed using area under the receiver operating characteristic curve (AUC) and threshold-based metrics, alongside training dynamics, Grad-CAM visualizations, and server-side aggregate monitoring signals. On the test set, CL achieved the highest performance (AUC 0.831; accuracy ≈ 0.782), FL showed intermediate performance (AUC 0.757; accuracy ≈ 0.703), and LL generalized poorly across clients (AUC range ≈ 0.619–0.734; mean ≈ 0.672). Training curves suggested overfitting, particularly in LL models, and Grad-CAM indicated more anatomically focused attention in CL and FL. Overall, centralized training provided the strongest performance, while FL offers a privacy-preserving alternative that outperforms LL. Full article

Objectives: This study aimed to evaluate the impact of thoracic endovascular aortic repair (TEVAR) on aortic remodeling using CT angiography-based morphometric measurements and to examine associated mid-term clinical outcomes in patients with acute Stanford type B aortic dissection. Methods: This retrospective, single-center observational cohort study included 33 consecutive patients who underwent TEVAR for acute Stanford type B aortic dissection between January 2020 and January 2025. Preoperative and postoperative true lumen (TL), false lumen (FL), and descending aorta (DA) diameters were compared using paired t-tests after Shapiro–Wilk normality testing. Endoleak, reintervention, FL thrombosis, and mortality were analyzed. Univariable analyses identified factors associated with endoleak and reintervention. Spearman’s correlation assessed factors associated with morphometric remodeling response. Results: All 33 patients had acute Stanford type B dissection (mean time to intervention: 2.73 ± 3.86 days). Among 33 patients (81.8% male; mean age 53.6 ± 12.1 years), mean follow-up was 4.08 ± 1.66 years. TEVAR induced a significant aortic remodeling response: TL diameter increased from 9.55 ± 5.91 mm to 28.30 ± 5.49 mm (+18.76 ± 8.83 mm; p < 0.001) and FL diameter decreased from 33.39 ± 6.76 mm to 11.48 ± 8.97 mm (−21.91 ± 9.53 mm; p < 0.001), while DA diameter remained stable (42.94 ± 6.90 vs. 42.03 ± 9.46 mm; p = 0.323). Complete FL thrombosis was achieved in 19 patients (57.6%). Endoleak occurred in nine patients (27.3%); Zone 2 landing was significantly associated with endoleak (54.5% vs. 13.6%, p = 0.033). Secondary intervention was required in 13 patients (39.4%). Overall mortality was 12.1%. Narrower preoperative TL was strongly associated with greater TL expansion (Spearman r = −0.724, p < 0.001); longer stent–graft coverage was associated with greater TL gain (r = +0.522, p = 0.002). Conclusions: TEVAR induced clinically meaningful aortic remodeling in acute Stanford type B dissection without progressive aortic enlargement. A narrower baseline TL and longer stent–graft coverage were associated with greater remodeling benefit. Zone 2 deployment was significantly associated with higher endoleak rates, underscoring the value of careful preprocedural planning and systematic long-term imaging surveillance. Full article

Background: Anthocyanin biosynthesis is tightly controlled by MYB transcription factors, yet the role of repressors, particularly those in the DIVARICATA-like (DIV) subfamily, remains poorly characterized. Methods: A genome-wide identification of MYB family members was performed in the mulberry (Morus atropurpurea) genome using a hidden Markov model and BLAST-based searches. Putative MYB genes were phylogenetically classified, and their expression profiles were analyzed across three fruit developmental stages. A DIV-like R2R3-MYB candidate, MaDIV, was functionally characterized via subcellular localization, quantitative real-time PCR, and heterologous overexpression in tobacco. Results: A total of 145 MaMYB genes were identified and classified into 31 distinct subfamilies. MaDIV expression showed a progressive decline during fruit ripening, which significantly correlated with increasing anthocyanin accumulation. Heterologous overexpression of MaDIV in tobacco led to a 42% reduction in floral anthocyanin content compared with wild-type plants. Concomitantly, the expression of the key anthocyanin biosynthetic gene NtDFR was strongly suppressed, whereas the flavonol synthase gene NtFLS1 was significantly upregulated. Conclusions: These findings point to a possible involvement of MaDIV in the regulation of anthocyanin biosynthesis and provide preliminary evidence for the functional diversification of the DIV-like MYB subfamily in plants. The results contribute to a better understanding of the transcriptional control of fruit pigmentation in mulberry and related species. Full article

Although the sharing of data is an important part of multicenter biomedical AI, direct data sharing is hindered by privacy laws, institutional data silos, and restrained trust and cooperation between institutions. While federated learning offers an opportunity for collaborative model training without centralizing patient data, many current methods rely on the same fixed levels of privacy protection on all clients, every layer of the model, each round, and each modality, resulting in suboptimal privacy–utility–latency trade-offs. In this study, we introduce Adaptive Trust-Aware Encrypted Federated Artificial Intelligence with Blockchain Auditability (ATEB-AI) for biomedical signal and medical image analysis. ATEB-AI is an adaptive CKKS encryption, trust-aware aggregation, and permissioned blockchain-based audit logging combination. The proposed framework was tested on four public benchmarks, namely, MIT-BIH, CHB-MIT, BraTS, and NIH ChestXray. ATEB-AI had the highest overall performance out of all compared federated methods and remained near the centralized training benchmark at up to 99.0% of the reference centralized training performance. It reduced membership-inference success from 0.71 to 0.24 (−66.2%), inversion leakage from 0.64 to 0.27 (−57.8%), and poisoning-related utility loss from 0.18 to 0.07 (−61.1%). Round latency was 1.90× FedAvg, compared with 2.85× for HE-FL (−33.3%) and 3.50× for BC-FL (−45.7%). The key contribution of this study is a single biomedical federated learning framework in which privacy, client trust, reliability, and auditability are unified, instead of being disjointed components. The results obtained with the proposed model prove the feasibility of co-optimizing confidentiality, robustness, efficiency, and governance in a single deployable multicenter medical AI pipeline. Full article

Metabolic dysfunction-associated steatotic liver disease (MASLD) is highly associated with the development of cardiovascular disease (CVD); however, the mechanisms responsible are currently unknown. We have developed a model of MASLD due to the loss of hepatocyte peroxisome proliferator-activated receptor α (PPARα^HEPKO). We found that plasma beta-hydroxybutyrate (BHOB) levels were significantly reduced in PPARα^HEPKO mice and aimed to investigate the therapeutic potential of restoring BHOB levels in the development of CVD in these mice. Thirty-week-old PPARα^HEPKO and control PPARα^FL/FL mice were randomized to receive 1,3 butanediol (1,3-BDO), a precursor of BHOB, in drinking water for 6 weeks. 1,3-BDO treatment resulted in a significant increase in plasma BHOB levels, a significant decrease in mean arterial blood pressure, improvement in systolic and diastolic function, a decrease in vascular stiffness, and improved exercise performance in PPARα^HEPKO mice. 1,3-BDO treatment did not alleviate hepatic steatosis in PPARα^HEPKO mice; however, it improved plasma cholesterol levels and decreased cardiac lipid accumulation, fibrosis, and apoptosis. 1,3-BDO treatment also resulted in a significant increase in cardiac AMP-activated protein kinase (AMPK) levels. Increasing plasma BHOB levels reverses CVD in our mouse model of MASLD. A similar approach could be an effective strategy for preventing the development of CVD in patients with human MASLD. Full article

This paper aims to analyse the contributions of studies that link financial literacy (FL) and behavioural finance (BF) in relation to saving and debt behaviours, considering both global and developing economy perspectives. This study employs a semi-systematic literature review (S-SLR) to examine 109 articles sourced from Scopus and Web of Science, published between 2011 and 2024. The evidence shows mixed results regarding the influence of FL and behavioural factors on saving and debt behaviours, with saving receiving greater attention. Most research is quantitative and concentrated in developed economies, although some developing Asian economies are also represented. The in-depth analysis of developing economies indicates that, while FL training and intervention-based approaches are relatively well established, studies integrating FL and BF remain scarce, limiting a comprehensive understanding of financing decisions. Future research should therefore prioritise the developing contexts, adopt more diverse methodologies, and incorporate psychological variables. This S-SLR offers an integrated perspective on FL and BF in relation to saving and debt behaviours as components of financing decisions, contrasting with existing literature reviews, which typically treat these fields separately, focus on investment decisions, and provide limited in-depth analysis of developing economy contexts, while also generating insights to support future research on this interconnection. Full article

Background: Breast cancer (BrC) and lung cancer (LuC) are two forms of aggressive cancer that affect both men and women worldwide. Recently, multitask learning (MTL) and federated learning (FL) techniques have proven to be efficient in increasing the robustness of deep learning (DL)-based models by performing multiple tasks simultaneously and preserving the confidentiality of medical data. Methods: This paper presents a survey of MTL and FL methods for BrC and LuC screening and diagnosis using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) methodology. Comprehensive tables were created to highlight the performances of both MTL models and FL environments. Results: The main challenges identified were the lack of hybrid MTL models that combine hard and soft sharing, heterogeneous imaging data, and edge FL systems. Conclusions: FL environments obtain competitive performance compared with centralized MTL models, highlighting their potential to preserve medical data confidentiality without compromising performance. Future research directions could include MTL-based models incorporated in FL environments, hybrid MTL models that combine both hard- and soft-sharing parameter methods, and the use of blockchain techniques to increase the security of FL environments. Full article

Benefiting from tunable emission from ultraviolet to near-infrared windows, long luminescence lifetimes, and exceptional photostability, rare earth (RE)-doped nanomaterials overcome the limitations of conventional dyes and quantum dots, enabling deep-tissue, high-resolution, and low-background imaging. As multifunctional fluorescent probes, RE-doped nanomaterials are driving the development of next-generation biomedical imaging. This review summarizes recent advances in the structural design of RE-doped nanomaterials, surface engineering for biocompatibility, and targeting strategies for improved performance, and highlights their integration into advanced imaging modalities, including NIR-I/II fluorescence, FLIM, PAI, super-resolution STED, multimodal FL/MRI/CT, X-ray-excited luminescence, and persistent luminescence. Meanwhile, mechanistic insights, material innovations, and comparative advantages are discussed. Furthermore, challenges related to quantum yield, scalable synthesis, imaging resolution, and clinical translation are considered, while future directions—centered on multifunctional probe design, NIR-II imaging, and AI-assisted data analysis—are proposed, offering a versatile platform for precise multimodal imaging with significant potential to advance early diagnosis, personalized therapy, and clinical applications. Full article

The Industrial Internet of Things (IIoT) increasingly relies on federated learning (FL) to enable collaborative model training without directly sharing raw traffic data across industrial sites. However, in practical IIoT deployments, clients may later request the removal of their data contributions from a trained federated model due to regulatory requirements, such as the General Data Protection Regulation (GDPR), ownership transfer, or internal data-governance policies. Such practical requirements create a strong demand for federated unlearning in IIoT applications. Furthermore, IIoT deployments often exhibit highly imbalanced client data distributions, resulting in substantially different contributions of individual clients to the global model. Nevertheless, most existing federated unlearning methods adopt a uniform unlearning strategy and fail to account for such client-level contribution gaps. To address this issue, we propose DynamicFU, a contribution-aware dynamic federated unlearning framework for IIoT deployments. The proposed method evaluates the target client from parameter-level, data-level, and performance-level perspectives and adaptively determines the unlearning strength by dynamically adjusting the number of unlearning rounds. Experimental results on public IIoT datasets show that DynamicFU substantially improves unlearning efficiency, achieving up to 22.89× speedup over Full Retrain while maintaining comparable effectiveness. Full article

Acute kidney injury (AKI) caused by ischemia–reperfusion injury (IRI) involves rapid activation of innate immune responses, in which myeloid-derived immune cells critically shape injury severity. Y-box binding protein 1 (YB-1) regulates pro-inflammatory gene expression intracellularly and can be secreted to function extracellularly, yet how these two compartments jointly influence early IRI pathology remains poorly understood. To dissect the roles of intracellular myeloid versus extracellular YB-1, we subjected myeloid-specific Ybx1 knockout, Ybx1^fl/fl × LysM^cre, mice and wild-type (WT) littermates to unilateral renal IRI following administration of either a neutralizing anti-YB-1 antibody or control IgG. Kidney injury, inflammation, immune cell recruitment, neutrophil extracellular trap (NET) formation, antibody localization, and Fcγ receptor expression were assessed by qRT-PCR, histology, immunostaining, Western blotting, and flow cytometry. Myeloid-specific knockout of Ybx1 markedly reduced renal inflammation, neutrophil infiltration, NET formation, and tubular injury. This protective phenotype was lost when extracellular YB-1 was simultaneously reduced: anti-YB-1 treatment in knockout mice restored pro-inflammatory cytokine expression, increased tubular damage markers such as NGAL and KIM-1, exacerbated neutrophil recruitment and NET formation, and led to luminar accumulation of YB-1/anti-YB-1 immune complexes in tubular cells. Mechanistically, Ybx1-deficient myeloid cells exhibited significantly reduced CD16 expression, pointing to impaired Fcγ receptor-mediated phagocytosis as the cause of defective immune complex clearance. In contrast, wild-type mice efficiently cleared extracellular YB-1 complexes and showed no injury aggravation upon antibody treatment. Our findings identify myeloid YB-1 as a central regulator of early inflammatory injury in renal IRI and reveal that its protective depletion becomes pathogenic when extracellular YB-1 is simultaneously neutralized, likely due to unmasked defects in immune complex clearance. Full article

Horse meat is a high-quality protein source. A total of 50 two-year-old male horses with similar body weights (300 ± 50 kg) were used: 30 for regional comparison (10 each from Bulgan province region of Mongolia (BPM), Tuv province region of Mongolia (TPM), and Inner Mongolia region of China (IMC)) and an additional 20 from the IMC region for muscle-site analysis. To elucidate the molecular mechanisms underlying regional and muscle-site differences in the meat quality of Mongolian horses, with particular emphasis on tenderness, this study analyzed chemical composition, minerals, fatty acids, and transcriptomes. Results showed that Mongolian horses from the Inner Mongolia region of China (IMC) had the highest contents of Se, C17:1, C18:2n6c, C18:3n3, ∑PUFA, PUFA/SFA, ∑n-3PUFA, ∑n-6PUFA (p < 0.05), and Fe (p < 0.01), and the lowest levels of C15:0 (p < 0.01) and C16:0 (p < 0.05). The Mongolian horses from the Tuv province region of Mongolia (TPM) had the highest Ca content (p < 0.05). The Mongolian horses from the Bulgan province region of Mongolia (BPM) had the highest ∑SFA (p < 0.01). The forelimb (FL) had the highest a*_45min, b*_45min (p < 0.01), Fe, Zn, and C17:1 (p < 0.05), and the lowest shear force and drip loss (p < 0.01). The HD had the highest pH_45min and cooking loss (p < 0.01). The hindlimb (HD) increased the L*_45min compared with the FL (p < 0.01). Transcriptomic analysis identified 513 differentially expressed genes (DEGs) between FL and HD, including SLC16A7, GPAM, FABP3, and TNNC1. KEGG enrichment analysis revealed that these DEGs were significantly enriched in the cGMP-PKG signaling pathway, glycerophospholipid metabolism, and PPAR signaling pathway. In summary, this study demonstrated that among Mongolian horses from three different regions, IMC horses exhibited superior meat quality and flavor characteristics, and the FL of IMC horses showed significantly better meat quality than other anatomical sites. Transcriptomic analysis identified a set of candidate genes related to meat quality and lipid metabolism, including SLC16A7, GPAM, FABP3, and TNNC1, providing a scientific basis for further understanding of muscle-specific molecular mechanisms in Mongolian horses. Furthermore, the observed differences in physicochemical and nutritional properties across regions and muscle sites established a systematic foundation for quality grading, targeted nutritional utilization, and processing optimization of Mongolian horse meat. Full article