Search Results (6,222)

Background/Objectives: Hutchinson–Gilford progeria syndrome (HGPS) is a rare and fatal genetic disease caused by a silent mutation in the LMNA gene, leading to the production of progerin, a defective prelamin A variant. Progerin accumulation disrupts nuclear integrity, alters chromatin organization, and drives systemic cellular dysfunction. While autophagy and inflammation are key dysregulated pathways in HGPS, the role of microRNAs (miRNAs) in these processes remains poorly understood. Methods: We performed an extensive literature review to identify miRNAs involved in autophagy and inflammation. Through stem-loop RT-qPCR in aging HGPS and control fibroblast strains, we identified significant miRNAs and focused on the most prominent one, miR-181a-5p, for in-depth analysis. We validated our in vitro findings with miRNA expression studies in skin biopsies from an HGPS mouse model and conducted functional assays in human fibroblasts, including immunofluorescence staining, β-Galactosidase assay, qPCR, and Western blot analysis. Transfection studies were performed using an miR-181a-5p mimic and its inhibitor. Results: We identified miR-181a-5p as a critical regulator of premature senescence in HGPS. miR-181a-5p was significantly upregulated in HGPS fibroblasts and an HGPS mouse model, correlating with Sirtuin 1 (SIRT1) suppression and induction of senescence. Additionally, we demonstrated that TGFβ1 induced miR-181a-5p expression, linking inflammation to miRNA-mediated senescence. Inhibiting miR-181a-5p restored SIRT1 levels, increased proliferation, and alleviated senescence in HGPS fibroblasts, supporting its functional relevance in disease progression. Conclusions: These findings highlight the important role of miR-181a-5p in premature aging and suggest its potential as a therapeutic target for modulating senescence in progeroid syndromes. Full article

Background: Autism spectrum disorder (ASD) represents a neurobiological disorder with a high prevalence in the children’s population. The aim of the present review was to assess the current evidence on the use of salivary biomarkers for the early diagnosis of ASD. Materials and methods: A search was conducted on the electronic databases PUBMED/Medline, Google Scholar and Scopus for the retrieval of articles concerning the study topic. Results: A total of 22 studies have been included in the present review considering 21 articles identified from databases and 1 article included using a manual search. A wide range of biomarkers have been proposed for early detection of ASD diseases including nonspecific inflammation markers like interleukin-1β (IL-1β), interleukin-6 (IL-6), interleukin-8 (IL-8), tumor necrosis factor α (TNFα), oxidative stress markers like superoxide dismutase and glutathione peroxidase, hormones such as cortisol and oxytocin, various microRNAs including miR-21, miR-132 and miR-137, and exosomes. The techniques used for biomarke detection may vary according to molecule type and concentration. Conclusions: salivary biomarkers could represent a potential useful tool for the primary detection of several systemic diseases including ASD, taking advantage of non-invasiveness and cost-effective capability compared to other biofluid-based diagnostic techniques. Full article

Amylose content significantly influences the technological, quality, and nutritional properties of starchy foods. This study developed a rapid, non-destructive method to quantify amylose content in starch using mid-infrared (MIR) spectroscopy combined with chemometric techniques. Manually prepared starch mixtures with varying amylose levels were scanned to obtain MIR spectra, which were preprocessed using smoothing and z-score normalization to reduce operational variability. Three variable selection methods, including bootstrap soft shrinkage (BOSS), competitive adaptive reweighted sampling (CARS), and uninformative variable elimination (UVE), were applied to select the useful spectra. A partial least square (PLS) model was then constructed to correlate selected spectral data with amylose content. The results revealed that the number and position of selected variables differed across different optimization methods, which influenced the model’s performance. It is worth noting that the optimized PLS model significantly reduced the root mean squared error of cross-validation (RMSECV) and improved prediction accuracy in 50 runs. In particular, the CARS-PLS model showed superior performance, achieving a correlation coefficient (R_p) of 0.964 and a root mean squared error of prediction (RMSEP) of 4.59, a 60% improvement over the original PLS model, which had an RMSEP of 11.56. These results highlight MIR spectroscopy’s potential, combined with optimized chemometric models, for accurate amylose quantification in food quality control. Full article

Gestational diabetes mellitus (GDM) and iron deficiency anemia (IDA) are the most common pregnancy-related conditions resulting in adverse maternal and fetal complications. MicroRNAs (miRNAs), particularly miR-182-3p and miR-24-3p, are promising biomarkers as they act as regulatory elements in various diseases; however, their roles in GDM and IDA are unclear. The present study aimed to analyze the expression and functional relevance of miR-182-3p and miR-24-3p in GDM and IDA. Experimental validation via RT-PCR revealed significant upregulation of both miRNAs in GDM and IDA samples. We identified common target genes and signaling pathways associated with these miRNAs, using a combination of data mining, bioinformatic tools (miRDB, TargetScan, miRTarBase, and miRWalk), and differentially expressed gene (DEGs) analysis using the GEO, OMIM, MalaCards, and GeneCards datasets. GO and KEGG pathway analyses revealed that the shared miRNA–mRNA in target genes were enriched in insulin signaling, apoptosis, and inflammatory pathways—key mechanisms implicated in GDM and IDA. Furthermore, hub genes such as IRS1, PIK3CA, CASP3, MAPK7, and PDGFRB were identified, supporting their central role in metabolic dysregulation during pregnancy. These findings demonstrate the potential of miR-182-3p and miR-24-3p as diagnostic biomarkers and therapeutic targets in managing GDM and IDA, offering new insights into the molecular interplay underlying pregnancy complications. Full article

Background/Objectives: Non-alcoholic fatty liver disease (NAFLD) is one of the most common chronic liver conditions globally. This study aimed to assess the long non-coding RNAs (lncRNAs) growth arrest-specific 5 (GAS5), miR-29a-3p, and neurogenic locus notch homolog protein 2 (NOTCH2) as biomarkers in patients with NAFLD and find out if they are related to any clinical factors. Subjects and Methods: Thirty-eight age-matched healthy persons and thirty-eight NAFLD patients were enrolled. Patients were split into the following three groups: non-alcoholic steatohepatitis (NASH) (n = 12), patients with NAFLD-related cirrhosis (n = 8), and patients with NAFLD-related simple steatosis (n = 18). Real-time PCR was utilized to examine the expression. Results: The lncRNA GAS5 and NOTCH2 were higher in NAFLD cases in comparison to controls. On the other hand, microRNA-29a-3p was underexpressed in NAFLD cases in comparison to controls. Regarding NAFLD diagnosis, lncRNA GAS5 was the best single marker with a sensitivity of 100% and a specificity of 94.7% at the cutoff values of ≥1.16-fold change. Regarding different stages of the disease, the highest level of lncRNA GAS5 was in cirrhosis. lncRNA GAS5 expression, among other studied parameters, is still a significant predictor of NAFLD (adjusted odds ratio of 162, C.I. = 5.7–4629) (p = 0.003). LncRNA GAS5 has a positive correlation with NOTCH2 and a negative correlation with miR-29a-3p. LncRNA GAS5, NOTCH2, and RNA-29a-3p were significantly different in NAFLD cases compared to controls. Conclusions: lncRNA GAS5 appears to be the most effective single marker for detecting NAFLD. LncRNA GAS5 expression is a significant independent predictor of NAFLD. LncRNA GAS5 can differentiate different NAFLD stages. Full article

MicroRNA-211 (miR-211) is a versatile regulatory molecule that plays critical roles in cellular homeostasis and disease progression through the post-transcriptional regulation of gene expression. This review comprehensively examines miR-211’s multifaceted functions across various biological systems, highlighting its context-dependent activity as both a tumor suppressor and oncogene. In physiological contexts, miR-211 regulates cell cycle progression, metabolism, and differentiation through the modulation of key signaling pathways, including TGF-β/SMAD and PI3K/AKT. miR-211 participates in retinal development, bone physiology, and protection against renal ischemia–reperfusion injury. In pathological conditions, miR-211 expression is altered in various diseases, particularly cancer, where it may be a useful diagnostic and prognostic biomarker. Its stability in serum and differential expression in various cancer types make it a promising candidate for non-invasive diagnostics. The review also explores miR-211’s therapeutic potential, discussing both challenges and opportunities in developing miRNA-based treatments. Understanding miR-211’s complex regulatory interactions and context-dependent functions is crucial for advancing its clinical applications for diagnosis, prognosis, and targeted therapy in multiple diseases. Full article

Wound healing is a complex and dynamic process involving several stages of tissue repair. This study has shown that extracellular vesicles (EVs) derived from the callus of Camellia japonica L. and their associated microRNAs (miRNAs) possess significant wound healing activities. In human fibroblasts, EVs from C. japonica L. stimulated wound healing and upregulated collagen gene expression. The EVs also decreased inflammation levels in human keratinocytes, supporting wound healing. Among the miRNAs identified, miR408, one of the abundant miRNAs in the EVs, also showed similar wound healing efficacy. These findings suggest that both EVs and miR408 from the callus of C. japonica L. play a pivotal role in promoting wound healing. Additionally, this study shows that the regulation of miRNAs between different kingdoms can be achieved and suggests a new direction for the utilization of plant-derived components. Full article

Background: Colorectal cancer (CRC) is strongly influenced by miRNAs as well as the circadian system. Methods: High-throughput sequencing of miRNAs expressed in the rat colon during 24 h light (L)/dark (D) cycle was performed to identify rhythmically expressed miRNAs. The role of miR-150-5p in CRC progression was analyzed in DLD1 cell line and human CRC tissues. Results: Nearly 10% of mature miRNAs showed a daily rhythm in expression. A peak of miRNAs’ levels was in most cases observed during the first half of the D phase of the LD cycle. The highest amplitude was detected in expression of miR-150-5p and miR-142-3p. In the L phase of the LD cycle, the maximum in miR-30d-5p expression was detected. Gene ontology enrichment analysis revealed that genes interfering with miRNAs with peak expression during the D phase influence apoptosis, angiogenesis, the immune system, and EGF and TGF-beta signaling. Rhythm in miR-150-5p, miR-142-3p, and miR-30d-5p expression was confirmed by real-time PCR. Oncogenes bcl2 and myb and clock gene cry1 were identified as miR-150-5p targets. miR-150-5p administration promoted camptothecin-induced apoptosis. Expression of myb showed a rhythmic profile in DLD1 cells with inverted acrophase with respect to miR-150-5p. miR-150-5p was decreased in cancer compared to adjacent tissue in CRC patients. Decrease in miR-150-5p was age dependent. Older patients with lower expression of miR-150-5p and higher expression of cry1 showed worse survival in comparison with younger patients. Conclusions: miRNA signaling differs between the L and D phases of the LD cycle. miR-150-5p, targeting myb, bcl2, and cry1, can influence CRC progression in a phase-dependent manner. Full article

Metasurfaces have drawn extensive research attention for their unique optical properties and vast application potential. Among the various resonant modes induced in metasurfaces, BIC and electric anapole modes stand out as particularly interesting due to their distinctive physical characteristics. In this work, we designed and investigated novel dimeric dumbbell-shaped metasurfaces incorporating two independently tunable asymmetric parameters. This structural innovation enables the simultaneous excitation of both electric anapole and QBIC modes under normally incident MIR illumination. More importantly, by adjusting these two asymmetric parameters, one can independently tune the resonance peaks of the two modes, thereby overcoming the performance limits of conventional single-peak modulation. This metasurface design demonstrates outstanding performance for dielectric environment-sensing applications. We conducted a comprehensive investigation of the sensing sensitivity for dumbbell-shaped metasurfaces of various geometries. Our simulation results show that the circular-shaped configuration achieved high sensitivity, reaching 20,930 GHz/RIU. This work offers a novel design paradigm for multi-mode control and functionalization of metasurface structures. Full article

Bone metastasis remains a significant cause of morbidity and diminished quality of life in patients with advanced breast, prostate, and lung cancers. Emerging research highlights the pivotal role of reversible epigenetic alterations, including DNA methylation, histone modifications, chromatin remodeling complex dysregulation, and non-coding RNA networks, in orchestrating each phase of skeletal colonization. Site-specific promoter hypermethylation of tumor suppressor genes such as HIN-1 and RASSF1A, alongside global DNA hypomethylation that activates metastasis-associated genes, contributes to cancer cell plasticity and facilitates epithelial-to-mesenchymal transition (EMT). Key histone modifiers, including KLF5, EZH2, and the demethylases KDM4/6, regulate osteoclastogenic signaling pathways and the transition between metastatic dormancy and reactivation. Simultaneously, SWI/SNF chromatin remodelers such as BRG1 and BRM reconfigure enhancer–promoter interactions that promote bone tropism. Non-coding RNAs, including miRNAs, lncRNAs, and circRNAs (e.g., miR-34a, NORAD, circIKBKB), circulate via exosomes to modulate the RANKL/OPG axis, thereby conditioning the bone microenvironment and fostering the formation of a pre-metastatic niche. These mechanistic insights have accelerated the development of epigenetic therapies. DNA methyltransferase inhibitors (e.g., decitabine, guadecitabine) have shown promise in attenuating osteoclast differentiation, while histone deacetylase inhibitors display context-dependent effects on tumor progression and bone remodeling. Inhibitors targeting EZH2, BET proteins, and KDM1A are now advancing through early-phase clinical trials, often in combination with bisphosphonates or immune checkpoint inhibitors. Moreover, novel approaches such as CRISPR/dCas9-based epigenome editing and RNA-targeted therapies offer locus-specific reprogramming potential. Together, these advances position epigenetic modulation as a promising axis in precision oncology aimed at interrupting the pathological crosstalk between tumor cells and the bone microenvironment. This review synthesizes current mechanistic understanding, evaluates the therapeutic landscape, and outlines the translational challenges ahead in leveraging epigenetic science to prevent and treat bone metastases. Full article

The somatic cell count (SCC) and differential somatic cell count (DSCC) are proxies for the udder health of dairy cattle, regarded as the criterion of mastitis identification with healthy, suspicious mastitis, mastitis, and chronic/persistent mastitis. However, SCC and DSCC are tested using flow cytometry, which is expensive and time-consuming, particularly for DSCC analysis. Mid-infrared spectroscopy (MIR) enables qualitative and quantitative analysis of milk constituents with great advantages, being cheap, non-destructive, fast, and high-throughput. The objective of this study is to develop a dairy cattle udder health status diagnostic model of MIR. Data on milk composition, SCC, DSCC, and MIR from 2288 milk samples collected in dairy farms were analyzed using the CombiFoss 7 DC instrument (FOSS, Hilleroed, Denmark). Three MIR spectral preprocessing methods, six modeling algorithms, and three different sets of MIR spectral data were employed in various combinations to develop several diagnostic models for mastitis of dairy cattle. The MIR diagnostic model of effectively identifying the healthy and mastitis cattle was developed using a spectral preprocessing method of difference (DIFF), a modeling algorithm of Random Forest (RF), and 1060 wavenumbers, abbreviated as “DIFF-RF-1060 wavenumbers”, and the AUC reached 1.00 in the training set and 0.80 in the test set. The other MIR diagnostic model of effectively distinguishing mastitis and chronic/persistent mastitis cows was “DIFF-SVM-274 wavenumbers”, with an AUC of 0.87 in the training set and 0.85 in the test set. For more effective use of the model on dairy farms, it is necessary and worthwhile to gather more representative and diverse samples to improve the diagnostic precision and versatility of these models. Full article

Background/Objectives: Different risk factors are involved in the initiation and progression of melanoma. In particular, genetic and epigenetic pathways are involved in all stages of melanoma and are exploited in therapeutic approaches. This study investigated the role of circular RNA circ_0001591 in melanoma cell migration. Methods: Three different melanoma cell lines were transfected with siRNA targeting circ_0001591 and with mimic or inhibitor molecules for miR-20a-3p and miR-34a-5p. Gene and protein expression levels were analyzed by RT-qPCR and Western blot, respectively. Dual luciferase reporter assays were performed to confirm the direct interaction of miR-20a-3p and miR-34a-5p with circ_0001591, as well as with the 3’UTRs of AXL (for both miRNAs) and FOSL1 (miR-34a-5p only). Wound healing assays were conducted to assess cell migration velocity. Results: The silencing of circ_0001591 significantly reduces the migration ability of melanoma cell lines. This downregulation was associated with an increased expression of miR-20a-3p and miR-34a-5p. Dual luciferase reporter assays confirmed the direct binding of both miRNAs to circ_0001591, supporting its role as a molecular sponge. The same assays also verified that miR-20a-3p directly targets the 3’UTR of AXL, while miR-34a-5p binds the 3’UTRs of both AXL and FOSL1. Western blot analysis showed that the modulation of this axis affects the expression levels of the AXL and FRA1 oncoproteins. Conclusions: Our findings demonstrate that circ_0001591 promotes melanoma migration by sponging miR-20a-3p and miR-34a-5p, thereby indirectly modulating the expression of AXL and FRA1 oncoprotein. Further investigations of this new regulatory network are needed to better understand its role in melanoma progression and to support the development of targeted therapies. Full article

Grains and their derivatives play a crucial role as staple foods for the global population. Identifying grains in the food chain that are free from mycotoxin contamination is essential. Researchers have explored various traditional detection methods to address this concern. However, as grain consumption becomes increasingly time-sensitive and dynamic, traditional approaches face growing limitations. In recent years, emerging techniques—particularly molecular-based vibrational spectroscopy methods such as visible–near-infrared (Vis–NIR), near-infrared (NIR), Raman, mid-infrared (MIR) spectroscopy, and hyperspectral imaging (HSI)—have been applied to assess fungal contamination in grains and their products. This review summarizes research advances and applications of vibrational spectroscopy in detecting mycotoxins in grains from 2019 to 2025. The fundamentals of their work, information acquisition characteristics and their applicability in food matrices were outlined. The findings indicate that vibrational spectroscopy techniques can serve as valuable tools for identifying fungal contamination risks during the production, transportation, and storage of grains and related products, with each technique suited to specific applications. Given the close link between grain-based foods and humans, future efforts should further enhance the practicality of vibrational spectroscopy by simultaneously optimizing spectral analysis strategies across multiple aspects, including chemometrics, model transfer, and data-driven artificial intelligence. Full article

Compiler optimization is a critical component for improving program performance. However, the Rustc optimization process may introduce vulnerabilities due to algorithmic flaws or issues arising from component interactions. Existing testing methods face several challenges, including high randomness in test cases, inadequate targeting of vulnerability-prone regions, and low-quality initial fuzzing seeds. This paper proposes a test case generation method based on large language models (LLMs), which utilizes prompt templates and optimization algorithms to generate a code relevant to specific optimization passes, especially for real-time control logic and safety-critical modules unique to the industrial control field. A vulnerability screening approach based on static analysis and rule matching is designed to locate potential risk points in the optimization regions of both the MIR and LLVM IR layers, as well as in unsafe code sections. Furthermore, the targeted fuzzing strategy is enhanced by designing seed queues and selection algorithms that consider the correlation between optimization areas. The implemented system, RustOptFuzz, has been evaluated on both custom datasets and real-world programs. Compared with state-of-the-art tools, RustOptFuzz improves vulnerability discovery capabilities by 16%–50% and significantly reduces vulnerability reproduction time, thereby enhancing the overall efficiency of detecting optimization-related vulnerabilities in Rustc, providing key technical support for the reliability of industrial control systems. Full article

Imaging techniques have revolutionized cultural heritage analysis, particularly for objects that cannot be sampled. This study investigated the utilization of spectral imaging for the identification of pigments in artifacts from the Arxiu Valencià del Disseny, in conjunction with other portable spectroscopy techniques such as XRF, Raman, FT-NIR, and FT-MIR. Four early 1930s watercolors were examined using point-wise elemental and molecular spectroscopic data for pigment classification. Initially, the data cubes obtained with the spectral camera were processed using various methods. The spectral behavior was analyzed pixel-point, and the reflectance curves were qualitatively compared with a set of standards. Subsequently, a computational approach was applied to the data cube to produce RGB, false-color infrared (IRFC), and principal component (PC) images. Algorithms, such as the Vector Angle (VA) mapper, were also employed to map the pigment spectra. Consequently, 19th-century pigments such as Prussian blue, chrome yellow, and alizarin red were distinguished according to their composition, combining the spatial and spectral dimensions of the data. Elemental analysis and infrared spectroscopy supported these findings. In this context, the use of reflectance imaging spectroscopy (RIS), despite its technical limitations, emerged as an essential tool for the documentation and conservation of design heritage. Full article