Search Results (761)

Biochemical detection is fundamental to various scientific disciplines, yet conventional methods still face inherent bottlenecks in achieving rapid, ultrasensitive, and simultaneous multi-target analysis. Terahertz (THz) waves, characterized by their unique spectral fingerprinting capabilities and non-destructive properties, have emerged as a compelling platform for advanced biochemical sensing. This review outlines the evolution of THz biochemical sensing over the past two decades, tracing its progression from passive identification toward intelligent perception. We structure this technological trajectory around four core themes: sensitivity enhancement, specific recognition, multi-target visualization, and system intelligence. We first evaluate the fundamental limitations of direct detection techniques, such as THz time-domain spectroscopy (THz-TDS). Building on this, we examine how metamaterial-assisted architectures utilize high-quality-factor resonances to achieve trace-level detection, pushing the limits of detection (LOD) down to the ng/mL or even pg/mL scale, and how surface chemical functionalization provides a molecular lock mechanism for selective targeting in complex samples. Furthermore, we highlight the paradigm shift from single-point spectral measurements to spatially resolved multi-target imaging using pixelated metasurfaces. Finally, the review addresses emerging directions, including dynamically tunable intelligent metasurfaces, multimodal on-chip integration platforms, and the growing integration of artificial intelligence (AI) in inverse design and data interpretation, which achieves classification accuracies exceeding 95% even in complex matrices. By synthesizing these developments, this review provides a comprehensive perspective on the future trajectory of THz sensing technologies. Full article

Soil contamination by heavy metals and organic pollutants presents significant challenges to the global environment and public health. However, a lack of micro-scale understanding of the pollution process hinders efforts to remediate and enhance soil quality. Synchrotron-based X-ray imaging and spectroscopy techniques are powerful tools in revealing complex interactions within heterogeneous soil systems. This review systematically explores recent advances in soil research that deepen our knowledge on the chemical states, spatial distribution, and dynamic interactions of heavy metals and organic contaminants via synchrotron-based techniques (e.g., micro-XRF imaging, FTIR, SR-μCT). It highlights the potential of these methods to characterize composition, aggregate structure, and microbial activity within soil matrices with high spatial and temporal resolution, in situ, and with element-specific analysis. Additionally, a forward-looking perspective outlines key research directions to leverage these advantages and develop more effective and sustainable soil restoration strategies. We hope this work emphasizes the role of synchrotron science in field-scale soil applications and inspires future, mechanism-driven, evidence-based soil remediation efforts. Full article

Rare-earth elements (REEs), which include the entire lanthanide series together with scandium and yttrium, have unique electronic configurations and coordination chemical properties that provide them with special magnetic, optical, and redox abilities. Generally used for diagnostic imaging and theranostic applications, increasing evidence emphasizes their potential as direct anticancer agents. This review aims to present a thorough investigation of the studies published in the last ten years that focus on the intrinsic anticancer properties of REE-based molecular complexes and nanostructures, without discussing their recognized imaging functions. Rare-earth compounds exhibit selective cytotoxicity against malignant cells via mechanisms that mainly include modulations in the generation of reactive oxygen species, mitochondrial dysfunctions, interaction with DNA molecules, apoptosis, and ferroptosis induction, as well as radiosensitization. Molecular complexes that are based on the trivalent coordination chemistry of REEs enable them to target biomolecules like DNA and serum albumin. Nanostructured systems, on the other hand, render tumors more responsive to treatment by improving the cellular uptake, enabling surface functionalization, and controlling ROS generation. Terbium, thulium, yttrium, scandium, ytterbium, cerium, erbium, dysprosium, and europium show different levels of anticancer activity in both in vitro and in vivo cancer models. They often exert more toxicity in tumor cells than in normal tissues, thus exhibiting selective anticancer effects. The findings collectively underscore the therapeutic potential of REE-based compounds as novel metal-based anticancer agents and advocate for additional mechanistic and translational research to enhance their clinical applicability. Full article

This study experimentally investigates the dynamics of air bubble plumes in water under varying thermal and hydrodynamic conditions using a two-dimensional Particle Image Velocimetry (PIV) system. The experimental setup consists of a transparent acrylic tank equipped with a bubble generator, a controlled heating system, and a synchronized PIV arrangement to capture both bubble motion and the induced liquid flow field. Experiments were conducted over a range of water temperatures (21–60 °C), air flow rates, and water depths (200–600 mm) to systematically quantify their coupled influence on bubble plume behavior. The results demonstrate that bubble rising velocity (defined here as the mean vertical, buoyancy-driven component of bubble motion measured in the fully developed plume region) increases with water temperature, gas flow rate, and water depth. For a fixed gas flow rate and water depth, increasing the water temperature from 40 °C to 60 °C resulted in an approximately twofold increase in bubble rising velocity, primarily due to reduced liquid viscosity and enhanced buoyancy forces. Bubble velocity also increased with gas flow rate and water depth, reflecting stronger momentum input and extended acceleration distances within taller water columns. PIV-resolved velocity fields further reveal that the surrounding fluid velocity increases proportionally with bubble rising velocity and temperature, confirming a strong coupling between bubble motion and plume-induced circulation. The surrounding liquid velocity reached approximately 30–60% of the corresponding bubble rising velocity, depending on operating conditions. These findings provide quantitative experimental insight into the coupled effects of thermal conditions, gas injection rate, and liquid depth on bubble–liquid interactions. The results contribute valuable validation data for multiphase flow modeling and offer practical relevance for thermal–hydraulic, chemical, and environmental engineering applications involving bubble-driven transport processes. Full article

Serotonin is a critical morphogen in early development, yet the mechanisms regulating its homeostasis in the preimplantation embryo remain unclear, particularly under conditions of maternal antidepressant exposure. Here, we investigated embryonic serotonergic autonomy using mouse models of pharmacological transport blockade (maternal fluoxetine treatment) and in vitro treatment with the monoamine oxidase inhibitor pargyline. We employed immunofluorescence, RT-qPCR, and live-cell imaging to assess metabolic flux, gene expression, and physiological health. We demonstrate that monoamine oxidase functions as a metabolic firewall, progressively maturing from zygote to blastocyst to degrade excess amines. Paradoxically, maternal serotonin transporter blockade triggered significant intracellular serotonin hyper-accumulation in blastocysts, associated with a trend toward a compensatory upregulation of the biosynthetic gene Ddc. While this serotonin overload did not compromise morphology, mitochondrial function, or pluripotency marker expression, it induced a robust epigenetic response. Excess serotonin promoted elevated H3Q5ser immunoreactivity in both nuclear and cytoplasmic compartments via a transglutaminase-dependent mechanism. These findings reveal that the preimplantation embryo possesses a resilient, autonomous serotonergic system capable of compensatory synthesis. However, environmental fluctuations are chemically recorded via transglutaminase-mediated serotonylation, representing an epigenetic mark that warrants further long-term study within the Developmental Origins of Health and Disease (DOHaD) framework. Full article

Numerous chemical and physical surface decontamination methods are used in clinical practice for implant surface decontamination, which constitutes the most critical step in the management of peri-implantitis. The aim of this study was to compare, in vitro, the efficacy of the electrolytic cleaning device GalvoSurge (GalvoSurge, GalvoSurge Dental AG, Widnau, Switzerland) with that of an air-abrasive AIRFLOW unit (AIRFLOW, Master PiezonVR, EMS Electro Medical Systems, Herrliberg, Switzerland). Thirty-two SLA-surfaced dental implants were allocated to two groups (n = 16) and contaminated with permanent ink, after which they were placed into jaw models representing two different defect configurations. After treatment, implants were photographed and, using ImageJ, the residual stain area/percentage within a 4 mm region apical to the implant neck was calculated. Surface topography was further evaluated by SEM and EDS. In the two-way analysis of variance, the effect of the decontamination method was statistically significant. The GalvoSurge group exhibited a lower residual stain percentage than AIRFLOW (overall 28.47 ± 10.13 vs. 37.14 ± 9.60; p = 0.019). This difference was independent of defect type (p > 0.05). These findings indicate that electrochemical cleaning via galvanic current may be more effective, under in vitro conditions, for stain removal and surface decontamination; however, they also demonstrate that residual contamination could not be completely eliminated irrespective of the method. Full article

Raman spectroscopy offers unique molecular fingerprinting capability for cancer diagnosis and monitoring, yet its biomedical application is fundamentally limited by weak intrinsic signals and complex biological backgrounds. Composite Raman probes, particularly surface-enhanced Raman scattering (SERS)—based systems, overcome these limitations through synergistic electromagnetic and chemical enhancement combined with functional integration. By engineering plasmonic nanostructures, interfacial electronic states, and molecular architectures, composite Raman probes achieve synergistic electromagnetic and chemical enhancement while incorporating biorecognition units, reporter molecules, and protective coatings to improve stability, specificity, and biocompatibility. In recent years, these probes have evolved from simple signal tags into multifunctional platforms capable of ultrasensitive tumor biomarker detection, high-contrast imaging, surgical guidance, therapy monitoring, and dynamic analysis of the tumor microenvironment (TME). This review systematically summarizes recent advances in composite Raman probes for oncological applications, with an emphasis on material design strategies, enhancement mechanisms, and stimulus-responsive regulation. Representative applications at both molecular and tissue levels are highlighted, including nucleic acid, protein, and exosome detection, as well as in vivo imaging and microenvironmental sensing. Finally, current challenges and future perspectives toward clinical translation are discussed, aiming to provide guidance for the rational design of next-generation Raman probes for precision oncology. Full article

This study addresses the automatic classification of sugar beet seeds according to their spraying levels using RGB images, aiming to enable a fast, practical, and non-destructive early warning system without chemical analysis. A dataset of 16,519 seed images acquired under controlled lighting conditions was used to evaluate YOLOv8-CLS and YOLO11-CLS architectures, including the n, s, m, l, and x scale variants within the Ultralytics framework. All experiments were conducted using a 10-fold cross-validation strategy, with models trained under different batch size and learning rate configurations. The results indicate that both architectures achieve reliable performance, with accuracy values ranging from approximately 78–83% for YOLOv8-CLS and 80–82% for YOLO11-CLS models. ROC-AUC scores consistently above 0.94 demonstrate strong inter-class discrimination. Misclassification analysis shows that errors mainly occur between visually similar intermediate treatment levels, particularly 25% and 50%. Despite this challenge, low log-loss values and balanced precision–recall profiles indicate stable decision behavior. Overall, the findings confirm that sugar beet seed treatment levels can be effectively distinguished using only RGB imagery, providing a potentially low-cost and scalable approach for early warning and quality control in seed treatment processes. Full article

This work presents a portable polarimetric multispectral imaging (PMSI) system operating in the visible to shortwave infrared range (VNIR–SWIR: 400–1700 nm) and its application to target detection, discrimination from aquatic backgrounds, and polymer identification. The instrument integrates two synchronized cameras with motorized bandpass filters and piezoelectric polarization control, enabling the acquisition of 48 wavelength–polarization measurements per capture. This configuration allows the extraction of both intensity-based and polarimetric features, including the degree of linear polarization (DoLP). A complete radiometric and polarimetric calibration framework is implemented, encompassing system response characterization, polarization-dependent gain correction, and reflectance normalization under variable illumination. Experiments conducted on a representative set of 16 polymer materials show that polarimetric information consistently improves class separability compared to intensity-only features, with a mean gain of 6.9 (95% CI: 6.35–8.47). Although the correlation between intensity- and DoLP-based separability is moderate (r = 0.44), the results indicate complementary identification capability. Material recoverability was further evaluated using spectral unmixing techniques (VCA, N-FINDR, and PPI), with VCA offering the best accuracy–complexity trade-off on the calibrated Stokes reflectance dataset. Despite these gains, identification among chemically similar polyethylene variants remains challenging due to limited spectral and polarimetric contrast. An underwater detectability study under natural illumination reveals strong wavelength-dependent constraints: SWIR penetration is limited to 4 cm, whereas VNIR bands (430–550 nm) preserve detectability up to 20 cm, with DoLP enhancing edge visibility. These results motivate future validation in more complex aquatic conditions and with increased spectral dimensionality. Full article

Authenticity verification for thangka artworks remains challenging in the market, as traditional physical authentication methods offer limited reliability, while modern spectroscopic and chemical testing technologies are costly and unsuitable for large-scale application. Although deep learning methods can achieve efficient authentication through image features, they rely on centralized databases to store feature information, making them susceptible to tampering risks and undermining the credibility of authentication results. To address these issues, this study proposes a digital authentication method for thangka paintings that integrates blockchain technology. This approach stores image features in the InterPlanetary File System (IPFS) and records their hash values on the blockchain, ensuring the immutability and verifiable evidence of feature data. Simultaneously, it employs convolutional neural networks for feature extraction and similarity analysis of thangka images, constructing an integrated platform system encompassing storage, authentication, and traceability. This enhances the reliability and automation of authentication outcomes. The platform further supports full-process traceability of thangka storage and authentication operations, providing a viable pathway for establishing a scientific and reliable digital authentication system for thangkas. Experimental evaluation on a dataset of 2847 thangka images demonstrates 99.2% authentication accuracy, with a precision of 98.7% and an F1-score of 99.1%, while end-to-end authentication latency averages 1247 ms, validating the system’s effectiveness for practical museum and market deployment scenarios. Full article

Three cerium-based metal–organic frameworks (MOFs), Ce-BDC, Ce-BDC-NH₂, and Ce-BTC, were used as catalysts for the hydroxylation of several organic compounds, including those not relevant to environmental or biological systems. Structural characteristics were validated by FT-IR spectroscopy, while SEM imaging demonstrated rod-like morphologies of 100–200 nm in width for Ce-BDC-NH₂ and 50–100 nm for Ce-BTC. The optical properties, ascertained using diffuse reflectance spectra and Tauc analysis, revealed bandgaps of 3.0 eV, 2.9 eV, and 3.6 eV for Ce-BDC, Ce-BDC-NH₂, and Ce-BTC, respectively. Catalytic investigations revealed that Ce-MOFs effectively convert phenol into 1,4-dihydroxybenzene with an efficiency of 86–99%, as confirmed by UV–Vis spectroscopy and HPLC analysis using an authentic hydroquinone (1,4-dihydroxybenzene) standard. The Ce-MOFs efficiently oxidize the dyes methylene blue (MB) and Congo red (CR) and also promote the hydroxylation of L-tyrosine, indicating their relevance to biologically significant substrates. The high catalytic performance of Ce-MOF highlights the potential of Ce-based materials for environmental remediation, chemical transformation, and sustainable wastewater treatment. Full article

Over the past two decades, numerous studies have examined the etiological significance of DNA fragmentation in human sperm using methods such as the comet assay (CA), the sperm chromatin structure assay, the sperm chromatin dispersion assay, and the TUNEL assay. We developed single-cell pulsed-field gel electrophoresis techniques, including one-dimensional (1D-SCPFGE) and angle-modulated two-dimensional (2D-SCPFGE), to detect early signs of naturally occurring DNA fragmentation. Comparative studies using purified human sperm with and without DNA fragmentation revealed some technical limitations in the conventional methods. This technical review outlines the procedures to ensure the quantitative performance of SCPFGE: (1) The mass of naked DNA was prepared through simultaneous in-gel swelling and proteolysis, which are highly sensitive to chemical and physical factors. Notably, these processes are vulnerable to reactive oxygen species (ROS). We developed the anti-ROS SCPFGE system to prevent artifactual cleavages. (2) 1D-SCPFGE discharges long-chain fibers from the origin, separating fibrous and granular segments beyond the tips of the fibers. (3) During continuous electrophoresis after 150° rotation (2D-SCPFGE-0-150), long-chain fibers unexpectedly extended diagonally backward from the origin, with long fibrous segments pulled out from a bundle that extended during the first electrophoresis, indicating some fibrous segments were embedded within the long-chain fibers. Even when SCPFGE was employed, one-directional current led to false negatives. (4) 2D-SCPFGE with angle rotation is currently the most sensitive imaging method for single-nuclear DNA fibers. However, without knowing the size of DNA fragments, it remains a semi-quantitative analysis. (5) To prevent artifactual DNA cleavage caused by ice crystals, low-temperature liquid storage is recommended. (6) The in-gel proteolyzed naked DNA is suitable as a substrate for chemical and enzymatic DNA cleavage analyses. Full article

Multicellular systems form diverse morphologies through chemical and physical interactions among cells. In this study, we propose a trainable multicellular phase-field model that incorporates a neural network. The phase-field model represents cell morphology and position as continuous fields and serves as the basis for learning intercellular dynamics. In the proposed model, the neural network takes the local state as input and predicts the subsequent state, adjusting the spatial evolution of the multicellular system to approach a target pattern defined by a loss function. Through simulation experiments, we confirmed that the trained neural network enables cells to aggregate into a cluster and reproduce the spatial pattern of a given image. Moreover, similar results were obtained in a larger simulation domain than that used during training, demonstrating the scalability of the model. Full article

Background: Successful root canal treatment depends on the synergy between mechanical instrumentation and chemical disinfection. The internal canal geometry, particularly taper configuration, critically influences irrigant flow and penetration. Conventional taper designs tend to displace irrigants coronally, creating stagnation zones and limiting cleaning efficacy. The MEA Inverse Taper^® technique introduces a reversed taper geometry designed to retain irrigant within the canal during shaping, forming a fluid reservoir termed the Radicular Tank (RT). This proof-of-concept study aimed to experimentally demonstrate the formation of the RT generated by the MEA Inverse Taper^® design and to compare its qualitative hydrodynamic and shaping behavior with a conventional rotary system (MTWO). Methods: Standardized transparent canal models were instrumented using either the MEA Inverse Taper^® or MTWO sequence. A 1% methylene blue dye served as a visual tracer to assess potential intracanal retention at successive shaping stages. Standardized photographic documentation and digital image superimposition were used to evaluate residual dye retention, canal morphology, and taper variation. Results: The MEA Inverse Taper^® sequence maintained residual dye in the coronal and middle thirds, confirming the formation of the RT. Compared with MTWO, it produced a more conservative taper, minimized coronal and apical displacement of dye, and preserved canal curvature, removing less coronal dentin. Conclusion: The MEA Inverse Taper^® technique creates a qualitative dye-retention phenomenon (Radicular Tank) that allows continuous instrumentation within a visually persistent dye environment. This novel concept may support disinfection efficiency, alongside preserving dentin structure and reducing mechanical stress on rotary instruments, representing a potential advancement in endodontic shaping and irrigation protocols. Full article

Optical microscopy is a fundamental tool in the physical, chemical, and life sciences, enabling direct investigation of structure, dynamics, and function across multiple spatial and temporal scales. Advances in optical design, detectors, and computational techniques have greatly enhanced performance, but have also increased the complexity of modern microscopes, which are now software-driven and embedded in data-intensive workflows. Artificial intelligence has become an important component of this landscape, particularly through task-specific machine learning approaches for image analysis, optimization, and limited instrument control. While effective, these solutions are often fragmented and lack the ability to integrate experimental intent, contextual knowledge, and multi-step reasoning. Recent progress in large language models (LLMs) offers a new paradigm for intelligent microscopy. As foundation models trained on large-scale text and code, LLMs exhibit emergent capabilities in reasoning, abstraction, and tool coordination, allowing them to act as natural interfaces between users and complex experimental systems. This perspective highlights how LLMs can function as cognitive and orchestration layers that connect experiment design, instrument control, data analysis, and knowledge integration. Emerging applications include conversational microscope control, workflow supervision, and scientific assistance for data exploration and hypothesis generation, alongside important technical, ethical, and governance challenges. Full article