Search Results (1,022)

While stamen-focused research has predominantly examined flowering ornamental species, the tissue-specific regulatory mechanisms governing anthocyanin biosynthesis in potato stamens remain poorly understood. To characterize the tissue-specific regulatory mechanisms controlling anthocyanin biosynthesis in potato reproductive and storage organs, this investigation employed the red stamen mutant line ‘BF1811-8’ and the commercial cultivar ‘Atlantic’ as experimental models. Anthocyanin composition and quantification were determined using high-performance liquid chromatography (HPLC), while RNA-sequencing coupled with quantitative real-time PCR validation enabled comprehensive analysis of differential gene expression patterns within the anthocyanin biosynthetic pathway. Biochemical analysis revealed complete absence of anthocyanins across all examined tissues in ‘Atlantic’, whereas ‘BF1811-8’ exhibited tissue-specific anthocyanin profiles: stamens accumulated delphinidin and pelargonidin, while tuber skin and flesh primarily contained pelargonidin and peonidin. Gene ontology and KEGG pathway enrichment analysis of differentially expressed genes identified significant representation within secondary metabolism, flavonoid biosynthesis, and pigmentation processes. The transcription factors StMYB4 and StMYBA1 demonstrated positive regulatory roles in anthocyanin biosynthesis within tuber flesh and skin, respectively, while exhibiting coordinated expression with structural genes including CHS, DFR, ANS, and GST. Notably, StbHLH94 showed stamen-specific regulatory activity and demonstrated transcriptional co-regulation with 3GT. These findings provide crucial insights into the tissue-specific regulatory architecture governing potato anthocyanin biosynthesis, establishing a foundation for elucidating molecular mechanisms underlying tissue-specific pigmentation and advancing functional cultivar development. Full article

Background/Objectives: This study aimed to characterize the expression patterns of B7 homolog 3 (B7-H3) and cluster of differentiation 155 (CD155), two immune-related transmembrane glycoproteins, in resectable gastric adenocarcinoma and to elucidate their clinicopathological, prognostic, and molecular implications. Methods: The study included 112 patients who underwent gastrectomy for gastric adenocarcinoma between 2020 and 2025, along with 30 samples of normal gastric tissue obtained from sleeve gastrectomy specimens. Histological subtype, grade of differentiation, TNM stage, and invasion parameters were re-evaluated. Immunohistochemical expression of B7-H3 and CD155 was quantified for membranous, stromal and membranous/cytoplasmic staining patterns. Quantitative reverse transcription polymerase chain reaction (RT-PCR) was performed on 29 tumor and 25 normal samples to confirm mRNA expression levels, with fold change ≥2 considered biologically significant upregulation and ≤0.5 considered downregulation. Machine learning models were developed to predict metastasis and mortality based on clinical and immunohistochemical features. Results: 78.5% of tumors were at an advanced stage (T3–T4), and metastasis was present in 22.3% of patients. Perineural invasion (PNI) and lymphovascular invasion (LVI) were observed in 67.9% and 88.4% of cases, respectively. Increased B7-H3 and CD155 expression were significantly associated with advanced tumor stage, metastasis, and the presence of PNI and LVI (all p < 0.05). In metastatic tumors, median membranous B7-H3, stromal B7-H3, and CD155 scores were 60, 130, and 190, respectively, compared with 20, 90, and 120 in non-metastatic tumors. A significant positive correlation was found between stromal B7-H3 and CD155 expression (r = 0.384, p < 0.001), indicating parallel upregulation. Quantitative RT-PCR confirmed significant overexpression of both genes in tumor tissues relative to normal controls. B7-H3 was upregulated in 75.9% and CD155 in 58.6% of samples, with co-upregulation in 55.2%. Fold-change levels were markedly higher in metastatic versus non-metastatic cases (B7-H3: 7.69-fold vs. 3.04-fold; CD155: 7.44-fold vs. 1.79-fold). ML analysis using the XGBoost model achieved 91.1% accuracy for metastasis prediction (F1-score 0.800). Key variables included pathological T4b stage, perineural invasion, N3b status, T4a stage, and CD155 score. The mortality model yielded 86.7% accuracy (F1-score 0.864), with metastasis, differentiation status, nodal involvement, age, lymph node ratio, and perineural invasion emerging as principal predictors. Conclusions: Combined evaluation of B7-H3 and CD155, supported by immunohistochemical staining and RT-PCR quantification of B7-H3 and CD155 mRNA expression levels, provides meaningful prognostic insights and supports their potential as dual molecular biomarkers for aggressive gastric adenocarcinoma phenotypes. Full article

Flavonoids, a ubiquitous class of plant secondary metabolites, are increasingly pivotal as chemical markers for ensuring the quality, safety, and efficacy of herbal medicines (HMs). Their broad distribution, biological activities, and detectability make them ideal for this role. This comprehensive review critically examines current trends and analytical perspectives regarding flavonoids in HM quality control. We first explore advanced quality control strategies that move beyond single-compound quantification, including chemical fingerprinting, metabolomics, network pharmacology, and the innovative concept of Q-markers. The review then provides an in-depth analysis of the analytical techniques central to flavonoid analysis, from the routine use of HPTLC and HPLC-UV to advanced hyphenated systems like UHPLC-QTOF-MS, highlighting their applications in authentication, standardization, and adulteration detection. Furthermore, we emphasize the growing importance of modern data analysis workflows, particularly the integration of chemometrics and molecular networking, for interpreting complex datasets and identifying robust, bioactivity-relevant markers. By synthesizing recent research (2017–2024), this work underscores a paradigm shift towards holistic, multi-marker approaches and data-driven methodologies. It concludes that the synergistic application of advanced analytical techniques with sophisticated data modeling is essential for the future of HM quality control, ensuring reliable and standardized herbal products for global consumers. Full article

Bacterial extracellular vesicles (BEVs) are nanoscale membrane-bound structures secreted by prokaryotic cells and have recently gained considerable attention in environmental pollution research. By encapsulating virulence factors and antibiotic resistance genes (ARGs), BEVs can persist in aquatic, soil, and sedimentary environments, facilitating interspecies gene transfer, aggravating microbial contamination, and ultimately posing risks to ecosystem stability and human health. This review provides a comprehensive overview of BEVs’ formation mechanisms, structural composition, and spatial distribution. Particular attention is given to the environmental implications of BEVs, including their roles in mediating horizontal ARG transfer, delivering virulence genes and amplifying pathogenicity, and their emerging potential as environmental bioindicators, despite current analytical limitations in complex matrices. Nevertheless, three major research gaps remain: (i) the molecular mechanisms underlying BEV interactions with heavy metals and microplastics are poorly understood; (ii) field-based quantification and distribution data are still limited; and (iii) effective, targeted strategies for BEV removal or inactivation are lacking. Addressing these challenges will not only enhance our understanding of BEV-mediated environmental risks but also inform the development of advanced detection methods and remediation approaches for BEV-associated pollution. Full article

Indocalamus tessellatus (Munro) P. C. Keng is a bamboo species with significant economic and ecological value, and exhibits considerable resistance to abiotic stresses. However, systematic evaluation of reference genes for gene expression analysis in this species is lacking. Analysis of multi-tissue transcriptomes yielded 3801 relatively stable genes; from these, we selected eleven new candidates along with nine widely adopted reference genes. We then evaluated these candidates under four conditions: drought (15% PEG-6000), salt (200 mM NaCl), waterlogging (root submergence in water), and a multi-tissue panel (leaf, leaf sheath, culm, shoot, and root). Under stress, early and sustained time points were sampled to capture dynamic transcriptional responses. Expression stability was assessed using geNorm, NormFinder, BestKeeper, and ΔCt, and results were integrated with RefFinder to generate comprehensive stability rankings for each condition. The most stable reference genes were condition-dependent: MD10B and PP2A under drought, eIF1A and Ite23725 under salt stress, PP2A and eIF4A under waterlogging, and 60S and UBP1 across different tissues. Notably, commonly used genes such as UBI and Actin7 were less stable. Peroxidase (POD) was used as a validation marker because it is a known stress-responsive gene, providing a sensitive readout of normalization accuracy. Validation confirmed that selecting suitable reference genes is essential for dependable expression quantification. These findings provide a robust set of reference genes for qRT-PCR studies in I. tessellatus, supporting future molecular and functional research in bamboo. Full article

Nondestructive quality detection of characteristic fruits is essential for ensuring nutritional value, economic viability, and consumer safety in global supply chains, yet traditional destructive methods compromise sample integrity and scalability. Visible and near-infrared (Vis/NIR) spectroscopy offers a transformative solution by enabling rapid, non-invasive multi-attribute quantification through molecular overtone vibrations. This review examines recent advancements in Vis/NIR-based fruit quality detection, encompassing fundamental principles, system configurations, and detection strategies calibrated to fruit biophysical properties. Firstly, optical mechanisms and system architectures (portable, online, vehicle-mounted) are compared, emphasizing their compatibility with fruit structural complexity. Then, critical challenges arising from fruit-specific characteristics—such as rind thickness, pit interference, and spatial heterogeneity—are analyzed, highlighting their impact on spectral accuracy. Applications across diverse fruit categories (pitted, thin-rinded, and thick-rinded) are systematically reviewed, with case studies demonstrating the robust prediction of key quality indices. Subsequently, considerations in model development and validation are presented. Finally, persistent limitations in model transferability and environmental adaptability are discussed, proposing future research directions centered on integrating hyperspectral imaging, AI-driven calibration transfer, standardized spectral databases, and miniaturized, field-deployable sensors. Collectively, these methodological breakthroughs will pave the way for autonomous, next-generation quality assessment platforms, revolutionizing postharvest management for characteristic fruits. Full article

Over the past five decades, the emergence and re-emergence of multiple flaviviruses have triggered significant global outbreaks, posing serious threats to public health. Among them, West Nile virus (WNV) is a major cause of mosquito-borne illness, typically presenting as an acute systemic febrile disease and, in some cases, progressing to the central nervous system involvement. No specific antiviral therapies or effective vaccines are available for WNV infections. In this context, antimicrobial peptides (AMPs) with antiviral properties—known as antiviral peptides (AVPs)—have gained attention as potential therapeutic agents due to their ability to interfere with various stages of the viral life cycle. Two frog-derived melittin-like peptides, AR-23 and RV-23, were synthesized and purified, and their hemolytic activity was assessed on human erythrocytes. Antiviral activity against WNV was evaluated in Vero cells using cytopathic effect reduction assays and real-time PCR quantification of viral RNA. Time-of-addition experiments were conducted to explore the stage of viral inhibition. In silico molecular docking studies were performed to examine interactions between the peptides and the viral E glycoprotein. Both peptides displayed strong antiviral effects during the early phases of infection, likely through direct interaction with viral particles and disruption of virus–host interactions. Compared with melittin, AR-23 and RV-23 showed greater efficacy and lower cytotoxicity, highlighting their potential as promising therapeutic candidates for flavivirus infections. Full article

Antioxidant properties of inorganic nanoparticles in aqueous media are attracting growing interest due to their high surface reactivity. Materials such as cerium oxide, iron oxide, silver, and gold exhibit distinct radical-scavenging behaviors at the nanoscale, but reliable quantification remains challenging. Conventional assays developed for molecular antioxidants cannot be directly applied because probes such as 2,2-diphenyl-1-picrylhydrazyl (DPPH) require methanol–water mixtures and are unstable in aqueous nanoparticle suspensions, while other assays are affected by nanoparticle-induced absorption or fluorescence changes. Here we demonstrate strategies to correct these interferences by independently measuring nanoparticle optical properties after oxidation and customizing assay conditions to account for the dilute, per-particle concentrations of nanomaterials. Using a high-throughput 96-well format, four adapted assays revealed that silver, ceria, and iron oxide nanoparticles possess substantially higher antioxidant capacities than Trolox, while gold showed negligible activity. This optimized approach enables reproducible comparison of nanoparticle antioxidants and provides a platform for tailoring nanostructures with enhanced radical-scavenging properties. Full article

Collagen is a family of large, fibrous biomacromolecules common in animals, distinguished by unique molecular, structural, and functional properties. Despite the relatively low complexity of their sequences and the repetitive conformation of the triple helix, which is the defining feature of this family, unraveling sequence–stability and structure–function relationships in this group of proteins remains a challenging task. Considering the importance of the structural aspects in collagen chain recognition and selection, we reviewed our current knowledge of the heterotrimeric structures of non-collagenous (NC) regions that lack the triple helix sequence motif, Gly-X-Y, and are crucial for the correct folding of the functional states of these proteins. This study was conducted by simultaneously surveying the current literature, mining the structural database, and making predictions of the three-dimensional structure of these domains using highly reliable approaches based on machine learning techniques, such as AlphaFold. The combination of experimental structural data and predictive analyses offers some interesting clues about the structural features of heterotrimers formed by collagen NC regions. Structural studies carried out in the last decade show that for fibrillar collagens (types I, V, XI, and mixed V/XI), key factors include the formation of specific disulfide bridges and electrostatic interaction patterns. In the subgroup of collagens whose heterotrimers create supramolecular networks (types IV and VIII), available structural information provides a solid ground for the definition of the basis of the molecular and supramolecular organization. Very recent AlphaFold predictions and structural analyses of type VI collagen offer strong evidence of the specific domains in the NC region of the protein that are involved in chain selection and their staggering. Insightful crystallographic studies have also revealed some fundamental elements of the chain selection process in type IX collagen. Collectively, the data reported here indicate that, although some aspects (particularly the quantification of the relative contribution of the NC and triple helix regions to correct collagen folding) are yet to be fully understood, the available structural information provides a solid foundation for future studies aimed at precisely defining sequence–structure–function relationships in collagens. Full article

Human granulocyte colony-stimulating factor (hG-CSF) is primarily used to treat neutropenia induced by cancer chemotherapy and bone marrow transplantation. The current identification test for hG-CSF relies on Western blot (WB), a labor-intensive and technically demanding method. This study aimed to screen and prepare an anti-hG-CSF nanobody to identify and quantify hG-CSF, with the ultimate goal of developing colloidal gold-labeled nanobody test strips for rapid identification. An alpaca was immunized with hG-CSF, and the VHH gene sequence encoding the anti-hG-CSF nanobody was obtained through sequencing following phage display library construction and multiple rounds of biopanning. The nanobody C68, obtained from screening, was expressed by E. coli, and its physicochemical properties such as molecular weight, isoelectric point, and affinity were characterized after purification. WB analysis demonstrated excellent performance of the nanobody in identification tests in terms of specificity, limit of detection (LOD), applicability with products from various manufacturers, and thermal stability. Additionally, we established an ELISA method for hG-CSF quantification utilizing the nanobody C68 and conducted methodological validation. Finally, colloidal gold-based test strips were constructed using the nanobody C68, with a LOD of 30 μg/mL, achieving rapid identification for hG-CSF. This study represents a novel application of nanobodies in pharmaceutical testing and offers valuable insights for developing identification tests for other recombinant protein drugs. Full article

Anthocyanins, key flavonoid-derived secondary metabolites, not only confer diverse pigmentation but also function in photoprotection, antioxidative defense, and cold acclimation. In woody species, bark anthocyanin turnover is tightly linked to environmental adaptation, stress resilience, and ornamental traits, yet its molecular regulation remains largely unresolved. Here, we investigated Salix alba L. bark by integrating anthocyanin quantification, transcriptome profiling, and weighted gene co-expression network analysis (WGCNA) to dissect the temporal dynamics and regulatory architecture of anthocyanin degradation. Anthocyanin content peaked at D2 (late December 2024), declined through D3 (mid-January 2025) and D4 (mid-February 2025), and partially rebounded at D5 (early March 2025), coinciding with peak expression of structural genes LAC1/2, POD1/2, and BGLU10. These enzymes co-expressed with multiple transcription factors, including MYB, bHLH, and WRKY families, forming putative core modules. Functional enrichment indicated that differentially expressed genes were enriched in redox processes, glycoside hydrolysis, flavonoid metabolism, and hormone signaling, suggesting a degradation mechanism mediated by reactive oxygen species, glycosidic cleavage, and hormone–transcription factor interplay. This study provides the first comprehensive framework of bark anthocyanin degradation in white willow, advancing the understanding of pigment dynamics, gene–environment crosstalk, and breeding strategies for ornamental woody plants. Full article

Although bovine respiratory syncytial virus (BRSV) is a key contributor to bovine respiratory disease (BRD) worldwide, there are few detailed reports of BRSV-related outbreaks in Brazil. This study describes the clinical, pathological, immunohistochemical (IHC), and molecular findings from a BRD outbreak in adult dairy cows from Southern Brazil. The affected cattle had dyspnea, nasal discharge, and coughing. One cow died, and samples were collected for diagnosis. Histopathology revealed interstitial pneumonia with multinucleated giant cells. IHC identified BRSV antigens in pulmonary tissue. A multiplex real-time PCR identified BRSV, Histophilus somni, and Pasteurella multocida in nasal and oral swabs, while only BRSV and H. somni were detected in the tissues of the cow that died. All animals had co-infections involving BRSV. The average cycle threshold (Cq) values for BRSV were 27.43 (nasal) and 32.68 (oral), with significant differences (p = 0.016), indicating higher nasal shedding. This qPCR assay was effective for detecting BRD pathogens, the quantification of viral and bacterial loads in animals with BRD and can be used for the rapid detection of respiratory pathogens. The elevated BRSV detection in oral samples suggests that this route may be an alternative for the collection of samples in cattle with profuse nasal discharge. Full article

Non-alcoholic fatty liver disease (NAFLD) is a prevalent chronic liver disorder and a major global health challenge, yet effective pharmacological therapies are lacking. Empagliflozin, a sodium–glucose cotransporter-2 (SGLT2) inhibitor, has shown systemic metabolic and anti-inflammatory benefits, but its liver-specific molecular mechanisms remain incompletely understood. In this study, we evaluated the therapeutic effects of empagliflozin in a diet-induced mouse model of NAFLD, supported by Mendelian randomization analysis. Histological examination, serum biochemistry, and hepatic triglyceride quantification demonstrated that empagliflozin markedly attenuated hepatic steatosis and improved liver injury indices. At the molecular level, empagliflozin suppressed NF-κB-mediated inflammatory signaling and significantly downregulated fibrotic markers including α-SMA and COL1A1, while modulating TIMP-1 and MMP-9 expression. Collectively, these findings reveal that empagliflozin ameliorates NAFLD by inhibiting inflammatory and fibrotic molecular pathways, highlighting its potential as a mechanism-based therapeutic option for NAFLD. Full article

Background: Haemoglobinopathies are among the most common monogenic disorders worldwide. Early identification of asymptomatic carriers through reliable screening and molecular diagnostics is crucial for prevention programmes, especially in high-prevalence regions such as Southern Italy. Methods: A total of 5243 individuals were analysed between 2013 and 2024 using both biochemical and genetic parameters. First-level screening included full blood count, iron status, and high-performance liquid chromatography (HPLC) for haemoglobin variant quantification. Molecular analyses were performed using next-generation sequencing (NGS) for the HBA1, HBA2, and HBB genes. Results: We identified 267 individuals (11.2%) as carriers of α-thalassaemia and 473 individuals (16.7%) as carriers of β-thalassaemia. Among them, 5 were compound heterozygotes and 3 homozygous for the α-3.7 deletion. A rare case of HbG Philadelphia in association with a triplicated α-gene was also observed. The most common β-globin mutations included c.118C>T (β⁰39, 44%), IVS-I-110 (17.7%), IVS-I-6 (12.7%), and IVS-I-1 (12.3%). Among α-globin mutations, the most prevalent were -α^3.7 (48%), α2 IVS1 -5nt (15.4%), -20.5 Kb (14.2%), and triplicated α (11%). In total, 18.7% of individuals were found to carry either α- or β-thalassaemia traits. Conclusion: Our findings highlight the limitations of traditional diagnostic methods—such as the osmotic fragility test—and the importance of integrating haematological, biochemical, and molecular data to accurately identify thalassaemia carriers. The variability of genotype–phenotype correlations, especially in the context of immigration and genetic diversity, underscores the need for comprehensive molecular analysis. We propose a three-step diagnostic algorithm combining first-level screening, iron status assessment, and NGS-based sequencing for inconclusive cases. Full article

Quercetin, a key flavonoid in Anoectochilus roxburghii (Wall.) Lindl., plays an important role in determining the pharmacological value of this medicinal herb. However, traditional methods for quercetin quantification are destructive and time-consuming, limiting their application in real-time quality monitoring. This study investigates the hyperspectral response characteristics of quercetin using near-infrared hyperspectral imaging and establishes a feature-based model to explore its detectability in A. roxburghii leaves. We scanned standard quercetin solutions of known concentration under the same imaging conditions as the leaves to produce a dilution series. Feature-selection methods used included the successive projections algorithm (SPA), Pearson correlation, and competitive adaptive reweighted sampling (CARS). A 1D convolutional neural network (1D-CNN) trained on SPA-selected wavelengths yielded the best prediction performance. These key wavelengths—particularly the 923 nm band—showed strong theoretical and statistical relevance to quercetin’s molecular absorption. When applied to plant leaf spectra, the standard-trained model produced continuous predicted quercetin values that effectively distinguished cultivars with varying flavonoid contents. PCA visualization and ROC-based classification confirmed spectral transferability and potential for functional evaluation. This study demonstrates a non-destructive, spatially resolved, and biochemically interpretable strategy for identifying bioactive markers in plant tissues, offering a methodological basis for future hyperspectral inversion studies and intelligent quality assessment in herbal medicine. Full article