Search Results (1,166)

All living organisms possess a DNA damage response (DDR) that is important for genetic evolution. Cells have developed comprehensive mechanisms for addressing DNA damage, collectively called the DNA damage response and repair. External environmental stress continuously disrupts genomic integrity and triggers various pathological changes. The failure of the DDR network often drives cell carcinogenesis, and its core components not only serve as biological markers for disease monitoring but also represent highly promising molecular targets for targeted therapy. Therefore, there is a high level of interest in exploring DDR-related biomarkers as cutting-edge therapeutic regimens and developing highly sensitive tools for DDR diagnosis. These methods should assess the rate of damage occurrence and distinguish when repair pathways are activated. These kinds of advances are key to preserving genetic stability and detecting and preventing diseases early. Here, we provide a broad summary of recent advances in DDR detection technologies, with a particular focus on the complementarity between different techniques. We have also summarized current technological bottlenecks, future research paradigms, and clinical translation pathways. The insights presented in this review will contribute to the development of multidisciplinary integrated DDR detection technologies, promote the establishment of DDR biomarker detection systems, and provide crucial methodological references for targeted drug development, efficacy evaluation, and resistance mechanism research targeting the DDR pathway. Full article

Pomegranate (Punica granatum L.) is a major fruit crop in tropical and subtropical regions, but changing climatic conditions—especially rising temperatures and intense solar radiation—are increasing physiological disorders. Sunburn, a key heat- and light-induced disorder, causes peel discoloration and tissue damage. This results in significant yield loss and reduced fruit quality. The objective of this study was to characterize sunburn-induced anatomical changes in the widely grown, highly sensitive Hicaznar cultivar in Türkiye, and to identify the optimal phenological stage for the application of sunburn-preventive practices. For this purpose, pomegranate fruit peels were fixed in FAA (Formalin–Acetic Acid–Alcohol) solution, embedded in paraffin blocks, and sectioned at a thickness of 5–7 µm. The sections were stained using the hematoxylin–eosin method and examined under a light microscope. The images captured with a digital camera wereanalyzed and revealed that sunburn damage in the pomegranate peel first appears in the cuticle layer, followed by disruption and fragmentation of the cutaneous and epidermal layers beneath it, and ultimately leads to damage of the parenchyma cells. Furthermore, Light microscopy showed that before visible discoloration, cells near the epidermis undergo phenolic accumulation, cell-wall thickening, and lignification, which are early indicators of sunburn. These microscopic changes provide early diagnostic features for detecting sunburn damage before external symptoms manifest. The study concluded that anatomical changes begin before the visible symptoms of sunburn appear on the fruit, and the most appropriate timing for applying preventive measures against sunburn has been identified. Light microscopy showed that before visible discoloration, cells near the epidermis undergo phenolic accumulation, cell-wall thickening, and lignification, which are early indicators of sunburn. Full article

Steels remain among the most widely used structural and engineering materials in modern infrastructure, energy systems, and industrial facilities. Their long-term reliability depends critically on the early detection of corrosion damage and microstructural degradation. This review surveys recent advances in two complementary families of non-destructive evaluation (NDE) methods: magnetic techniques, including magnetic Barkhausen noise (MBN), magnetic flux leakage (MFL), eddy current testing (ECT), and magnetic hysteresis analysis; and electrochemical methods including electrochemical impedance spectroscopy (EIS), linear polarization resistance (LPR), scanning vibrating electrode technique (SVET), and electrochemical noise (EN). Recent progress in sensor miniaturization, signal processing algorithms, and multi-technique integration is reviewed. Particular attention is given to the sensitivity of these methods to microstructural changes reported in the literature, including carbide dissolution, phase transformations, temper embrittlement, and sensitization in stainless steels, as well as to the conditions under which such sensitivity has been demonstrated. The potential synergy between magnetic and electrochemical monitoring is discussed as a possible pathway toward more robust, condition-based maintenance frameworks. Challenges related to field deployment, environmental interference, calibration, and data interpretation are identified, and future directions—including machine learning-assisted analysis and multi-physics sensor arrays—are outlined. Full article

Background: The combination of conventional drugs and inhibitors of signaling molecules is an effective strategy to increase cancer treatment efficacy and reduce drug doses to protect against their cytotoxic effects. Our research has shown the cisplatin concentration-dependent shift in the role of MAP kinase JNK from antiapoptotic to proapoptotic in non-small cell lung cancer A549 cells. Cell death/survival signaling molecules, tumor suppressor p53 and pro-survival protein kinase AKT were detected to be differently regulated by JNK inhibition at low vs. high cisplatin concentrations. Here, we further investigated the phenomenon and potential mechanisms of combined JNK inhibition and cisplatin treatment. Methods: Cell death in vitro was evaluated by MTT and Western blot assays after combined cisplatin and specific inhibitor treatment; two-way ANOVA was used for analysis. Results: JNK is differently involved in determining cellular sensitivity to different DNA-damaging drugs. There is no universal cell death induction mechanism originating from DNA damage through the involvement of JNK. The outcome of JNK inhibition also depends on the cell type. We found that there is an unusual reciprocal interaction between p53 and AKT in cisplatin-treated A549 cells, where p53 inhibits AKT, while AKT activates p53. In the case of cisplatin + JNK inhibitor SP600125, DNA damage and reactive oxygen species (ROS) contribute to cell death regulation in different ways. ROS exert opposite roles on cell fate-determining molecules p53 and AKT, and ROS act on p53 and AKT in opposite directions at low vs. high concentrations of cisplatin, combined or not with JNK inhibition. The differentially activated p53 in response to ROS (at low versus high concentrations of cisplatin, combined with JNK inhibitor) may be a molecular switch in the role of JNK from antiapoptotic to neutral/proapoptotic, and an executor of cell death. ROS is a possible threshold regulator that, together with an as-yet-unidentified factor, can differentially regulate p53. As a result, AKT phosphorylation and function are altered. The findings emphasize the importance of assessing the role of drug concentration when combining them with JNK inhibition when monitoring therapeutic efficacy and toxicity issues in personalized cancer treatment. Full article

Sirtuins are conserved proteins regulating oxidative stress and lifespan. While they enhance cellular adaptability, the long-term biological consequences of combining bioactive compounds with nanomaterials remain poorly understood. This study examined the effects of combined resveratrol and nanodiamonds (RV+NDs) in two Acheta domesticus strains: wild-type (H) and longevity-selected (D). The impact was assessed across developmental stages, focusing on survival, total sirtuin activity, specific isoforms (SIRT1, SIRT6), oxidative stress, antioxidant enzymes, and DNA damage markers. RV+NDs exposure did not result in consistent lifespan extension or sustained oxidative stress. Molecular responses were strongly dictated by genetic background and age, as reflected by significant survival differences between strains H and D (p < 0.001) Notably, a persistent increase in total sirtuin activity (~60% ↑ across developmental stages) occurred exclusively in the longevity-selected strain, though no stable activation of SIRT1 or SIRT6 was detected. While classical redox parameters showed only transient changes, DNA damage response markers emerged as the most sensitive indicators of RV+NDs exposure. Overall, the findings demonstrate that RV+NDs treatment induces context-dependent, adaptive molecular responses. This highlights the critical role of genetic background and age in shaping ageing-related pathways, suggesting that nanodelivery systems do not produce universal effects across different genotypes. Full article

Carbon fiber-reinforced polymer (CFRP) laminates are widely used in aircraft skins due to their advantages of high strength and lightweight properties. However, their laminate structure and energy-absorbing characteristics result in low-energy impact damage, such as delamination, that is often invisible but can lead to catastrophic failure. Consequently, early detection of delamination in CFRP laminates is necessary. Nonlinear ultrasonic guided waves exhibit high sensitivity to delamination, and second harmonics are widely employed. Compared to second harmonics, one-way mixing of ultrasonic guided waves can excite and receive signals simultaneously at the same location, thereby precisely localizing delamination. This capability has the potential for inspecting buried structures. However, existing literature has not yet fully addressed the generation mechanism of one-way mixing in CFRP laminates nor its interaction with delamination. Based on finite element simulation, this study investigates one-way mixing of A₀ modes and S₀ modes in CFRP laminates. Utilizing pulse-inversion techniques and two-dimensional fast Fourier transforms, the modes and propagation directions of difference-frequency components and sum-frequency components are determined. Furthermore, by utilizing the normalized acoustic nonlinearity parameter χ’ and adjusting the position of the mixing zone through different time delays, delamination in the CFRP laminate is successfully localized. Full article

Sensitive and on-site detection of pesticide residues remains a critical challenge for food safety, particularly in developing regions where rapid screening tools are urgently needed. Herein, we report a flexible surface-enhanced Raman scattering (SERS) platform based on triangular silver nanoplates (TSNPs) integrated onto a polydimethylsiloxane (PDMS) substrate, enabling sensitive and conformal detection of paraquat residues on agricultural surfaces. TSNPs were synthesized via a seed-mediated photochemical growth method and formulated into a TSNP ink, which was directly deposited onto oxygen-plasma-treated and thiol-functionalized PDMS substrates. Owing to the highly anisotropic geometry and sharp edges of TSNPs, the flexible SERS substrate exhibits strong localized surface plasmon resonance (LSPR) enhancement and mechanically stable electromagnetic hot spots. Systematic optimization of TSNP optical absorbance revealed that uniform nanoplate distribution and optimal hotspot density were achieved at an absorbance of 2.0. The SERS performance was evaluated using rhodamine 6G under front-side and back-side illumination configurations, demonstrating good signal reproducibility and a detection limit of approximately 10⁻⁵ M. Notably, back-side illumination through the PDMS layer provided superior SERS responses due to improved optical transmission and light–matter interaction. The practical applicability was further demonstrated through back-side SERS detection of paraquat on aluminum foil as a model surface, achieving a lowest detectable concentration of 5 × 10⁻⁶ M, followed by damage-free detection on Chinese pear peels. This work highlights a reliable and nondestructive flexible SERS platform for on-site pesticide residue monitoring. Full article

Structural damage detection using the finite element method is inherently formulated as an inverse problem, often suffering from ill-posedness and high sensitivity to measurement noise. This study introduces a novel damage detection methodology by applying low-rank adaptation (LoRA), originally developed for fine-tuning large language models, to inverse problems in structural mechanics for the first time. The proposed approach exploits the physically inherent low-rank nature of structural damage: damage is typically localized, and the contribution of each finite element to the stiffness matrix is limited by its degrees of freedom. Accordingly, the stiffness change matrix is factorized into two low-rank matrices, reducing the number of parameters and providing implicit regularization against full-rank measurement noise. Physical consistency is ensured through sparsity and symmetry constraints. Numerical experiments on cantilever beam and L-shaped plate structures across five damage scenarios demonstrated that the proposed method achieved superior noise robustness compared with baseline methods. At a signal-to-noise ratio of 20 dB, representative of practical field conditions, LoRA achieved stiffness errors below 2%, whereas the baseline methods failed to provide reliable results. The proposed framework achieved a 100% success rate in damage zone localization (Precision@n ≥ 80%) with over 60% parameter reduction, presenting a promising solution for practical structural health monitoring. Full article

Background/Objectives: Despite recent advances in breast cancer diagnostics, therapies and personalized medicine through genetic profiling, effective treatment of aggressive subtypes, particularly triple-negative breast cancer (TNBC), remains a considerable clinical challenge. MicroRNAs (miRNAs) are post-transcriptional regulators of gene expression that influence tumor progression and are detectable extracellularly in biofluids, where they are typically protected within extracellular vesicles (e.g., exosomes) or associated with RNA-binding proteins and lipoprotein complexes. This review integrates current evidence on oncogenic and tumor-suppressive extracellular miRNAs in breast cancer, with emphasis on subtype-specific functions and potential clinical relevance as liquid-biopsy biomarkers and therapeutic targets. Methods: A PubMed-based literature review (January 2000–February 2026) was conducted using search terms combining “breast cancer” with “miRNA/microRNA” and “circulating/plasma/serum/exosomal/extracellular vesicle.” Studies were prioritized if they provided validated targets/mechanisms and/or human clinical evidence for diagnostic, prognostic, or predictive utility; discrepant findings were evaluated in a subtype-aware framework. Findings were organized into functional categories (e.g., EMT/metastasis, cell-cycle/DNA damage, immune modulation, and hormone/growth factor signaling). Clinical and translational studies evaluating circulating miRNAs for diagnosis, prognosis, treatment response, and toxicity prediction were synthesized, together with key pre-analytical and analytical variables that affect reproducibility. Results: Across mechanistic and clinical studies, miR-21 and miR-155 recur as prominent oncogenic miRNAs, whereas miR-205 is frequently reported as a tumor-suppressive miRNA that is reduced in breast cancer and in circulation in several cohorts. Panels combining these miRNAs show promise for sensitive and specific breast cancer diagnostics. Additionally, several miRNAs show context- or subtype-dependent effects, with opposing activities reported between TNBC and estrogen receptor (ER)-positive disease (e.g., miR-17-92, miR-425, miR-181 family members, miR-31, and miR-24). Conclusions: Circulating miRNAs represent a promising class of minimally invasive biomarkers and potential therapeutic targets; however, translation is constrained by biological context dependence and by pre-analytical and analytical variability. Standardized protocols and rigorously validated, subtype-aware biomarker panels will be essential for clinical implementation and for enabling miRNA-informed precision oncology in breast cancer. Full article

Due to climate change, seedling damage caused by drought stress is expected to increase in both afforestation sites and nurseries. Therefore, to ensure stable seedling production under high-temperature conditions and to cultivate seedlings with enhanced drought tolerance through hardening treatments, the development of an effective irrigation system is required. Conventional physiological methods for non-destructive drought detection, such as chlorophyll fluorescence and leaf temperature measurements, require expensive and manual operation, thereby limiting their real-time applicability in forest nurseries. This study evaluated the applicability of using image-based leaf angle measurements for drought stress detection in Quercus acutissima Carruth. seedlings. One-year-old seedlings were grown under two water regimes—well-watered (CT: control) and unwatered (DT: drought)—through Day 8. Statistical analyses (RMANOVA) revealed that changes in the leaf angle parameter PMD–MD (the difference between the previous and current measurement days) showed treatment effects similar to those of the physiological responses ΦNO (quantum yield of non-regulated energy dissipation) and qL (fraction of open PSII reaction centers) to drought on Day 6. Leaf angle reflected drought stress but did not precede physiological changes, indicating its role as a complementary rather than an early indicator. Multiple regression models identified AT (air temperature), SM (soil moisture), Fm′ (maximum fluorescence in the light-adapted state), and VPD (vapor pressure deficit) as the main factors influencing leaf angle variation. Although leaf angle was affected by combined environmental stresses such as high temperature, it was less sensitive to heat stress than physiological responses based on RMANOVA results. These results indicate the potential of image-based leaf angle measurements for drought stress detection. To establish plant-based smart irrigation systems, future studies should validate and refine this approach using larger datasets. Full article

Diflubenzuron (DFB), a benzoylurea insecticide widely used in fruits, vegetables, cereals, and edible fungi, is increasingly detected in food. It has been linked to endocrine disruption, hematological effects, developmental toxicity, DNA damage, and ecological risks in aquatic organisms. These concerns, together with strict maximum residue limits, highlight the need for rapid, field-deployable detection methods. Herein, we developed a quantitative colloidal gold lateral-flow immunoassay for rapid DFB detection within 10 min. The optimized assay achieved a limit of detection (LOD) of 0.02 ng mL⁻¹, a limit of quantification (LOQ) of 0.067 ng mL⁻¹, and a linear range of 0.07–100 ng mL⁻¹ (R² = 0.9998), with high selectivity. Validation in eight food matrices (milk, chicken, mushrooms, pear, Chinese cabbage, rice, dried chili, and peanut) showed recoveries of 97.6–110.0% with RSDs of 2.1–4.9%. Results were consistent with LC-MS analysis, demonstrating that this assay provides a sensitive, practical, and rapid tool for screening DFB residues. Full article

Background and Objective: Axial spondyloarthritis (axSpA) is a group of chronic inflammatory diseases that primarily affect the sacroiliac joints. Early diagnosis is crucial for preventing irreversible structural damage. Magnetic Resonance Imaging (MRI) is the gold standard for detecting early inflammatory changes such as sacroiliitis. However, conventional MRI interpretation is inherently subjective and susceptible to both intra- and inter-observer variability. Therefore, artificial intelligence (AI)-driven diagnostic solutions are increasingly being explored. Among them, the Gated Attention Multiple Instance Learning (MIL) framework holds strong potential in modeling heterogeneous inflammatory distributions, thanks to its slice-level attention mechanism. This study aims to evaluate the diagnostic performance of a deep learning model based on Gated Attention MIL for automated sacroiliitis detection. Furthermore, its results are compared with a baseline deep learning architecture (standard ResNet-18), and its consistency with radiologist annotations is analyzed. Materials and Methods: The dataset included 554 subjects, comprising 276 patients diagnosed with axSpA and 278 healthy controls. All MRI data were derived from axial T2-weighted fat-suppressed (T2_TSE_TRA_FS) sequences. Patient-wise data splitting was employed to construct training, validation, and independent test sets. The proposed model architecture integrates ResNet-18-based feature extraction, a gated attention mechanism for instance-level weighting, and bag-level classification. Additionally, Test-Time Augmentation (TTA) was implemented to enhance robustness during inference. Results: On the independent test set, the model achieved an accuracy of 85.88%, sensitivity of 92.86%, specificity of 79.07%, and an F1-score of 86.67%. Attention heatmaps generated by the MIL module showed strong spatial overlap with bone marrow edema regions annotated by expert radiologists. Implementation of TTA led to an approximate 10% improvement in overall classification accuracy. Conclusions: The Gated Attention MIL framework demonstrated high diagnostic performance for sacroiliitis detection, indicating its value as a reliable decision support tool for early axSpA diagnosis. Validation on larger, multi-center datasets is warranted to ensure generalizability and to support clinical integration in routine radiology workflows. Full article

This study evaluates the tracking performance of structural damages in disaster environments by combining YOLOv8 detection with the BoT-SORT tracker. Cracks and exposed rebar, characterized by fine and irregular structures, showed high sensitivity to viewpoint changes, with camera motion compensation (CMC) improving $IoU$ by +19.63% and +20.23%. For exposed rebar, the joint use of CMC and re-identification (Re-ID) further increased $IDF1$ by +37.73%, emphasizing the effectiveness of appearance-based matching. In contrast, delamination and concrete debris, with stable morphology and clear boundaries, exhibited limited benefits from CMC, improving $IoU$ by +11.17% and +3.28%. Analysis of $MOTA$, $IDF1$, and $HOTA$ confirms that fine-grained damages require motion- and appearance-based strategies, while stable types maintain high performance through detection consistency. These results highlight the importance of tailored tracking strategies for enhancing disaster-response robots and structural monitoring systems. Full article

Drought stress induces the excessive accumulation of hydrogen peroxide (H₂O₂), leading to oxidative damage and reduced crop productivity. This study presents a dual-function nanotechnology-based strategy for monitoring and mitigating drought-induced oxidative stress in cereal crops. Hierarchical CuO nanostructures were grown directly on copper substrates by hydrothermal oxidation, and the influence of growth time on morphology and hydrogen peroxide sensing performance was systematically evaluated. An optimal growth time of 3 h produced CuO nanoflower architectures with high surface area, yielding superior electrocatalytic activity toward H₂O₂ detection, with a low detection limit of 1.9 µM and high sensitivity of 11.92 mA·mM⁻¹·cm⁻². The optimized sensor enabled reliable quantification of H₂O₂ in oat (Avena sativa) and rye (Secale cereale) under drought stress, revealing species-dependent oxidative responses. In parallel, magnesium oxide (MgO) nanoparticles effectively alleviated drought-induced oxidative damage, reducing H₂O₂ accumulation by up to 63% in oat and 61% in rye and significantly improving plant growth and chlorophyll content. The integration of CuO-based sensing with MgO nanoparticle-assisted stress mitigation provides a robust framework for plant stress diagnostics and intervention, highlighting the potential of nanotechnology-enabled strategies for crop stress diagnostics and precision agriculture. Full article

Line-field spectral-domain optical coherence tomography (LF-SD-OCT) offers high-speed parallel imaging, but lateral beam expansion limits the photon budget per spatial channel, compromising sensitivity. Here, we demonstrate a high-speed LF-SD-OCT system driven by a gain-managed nonlinear (GMN) all-fiber source operating at a central wavelength of 1063.2 nm. Delivering 269 mW of average power with a smooth 98 nm (3 dB) bandwidth, the GMN source effectively fulfills the stringent photon budget and stability requirements of parallel detection. The system achieves a 5.68 μm axial resolution and a ~1.2 mm effective imaging range. Ex vivo porcine myocardial tissue ablation experiments validate its capability for high-contrast cross-sectional visualization of ablation crater morphology, showing excellent agreement with optical microscopy. These results establish GMN-enabled LF-SD-OCT as a robust solution for the precise intraoperative monitoring of laser-induced tissue damage. Full article