Search Results (574)

Mitral valve prolapse (MVP) is generally associated with excellent long-term outcomes when MR is absent or mild. Nonetheless, a small proportion of patients exhibit a distinct arrhythmogenic susceptibility, characterized by complex ventricular ectopy, sustained ventricular arrhythmias (VAs), and in rare instances, sudden cardiac death (SCD). This subgroup—collectively referred to as arrhythmic MVP (AMVP)—has prompted renewed attention in identifying individuals at elevated risk. Among the structural alterations associated with MVP, mitral annular disjunction (MAD) has gained recognition as a major contributor to arrhythmic vulnerability, arising from the pathological separation of the posterior annulus from the adjacent ventricular muscle. Advances in multimodality imaging, including trans-thoracic echocardiography (TTE), cardiac magnetic resonance (CMR), and cardiac computed tomography (cCT), have significantly improved delineation of MAD and clarified its relationship to the broader MVP spectrum. Current evidence suggests that MVP, MAD, and AMVP should not be regarded as isolated conditions but as intersecting phenotypes within a shared pathological framework. In certain patients, especially those without established myocardial fibrosis, abnormal annular dynamics appear to constitute the primary arrhythmogenic driver and may diminish after surgical intervention. In others, persistent arrhythmias despite optimal repair reflect a fibrosis-based substrate. This review synthesizes contemporary insights into the anatomical, biomechanical, and electrophysiological interplay linking MVP, MAD, and ventricular arrhythmogenesis, emphasizing implications for imaging-based risk assessment and individualized surgical management strategies. Full article

Trypsin is one of the most extensively studied enzymes in biochemistry. However, little information is available on the role of the disulfide bonds to establish the correct conformation and enzyme activity during molecular evolution. To obtain this information, two additional disulfide bonds corresponding to those found in human trypsin were individually or simultaneously introduced into the trypsin-like protease cocoonase (Bombyx mori), which contains three consensus disulfide bonds, and structural effects were analyzed. Enzyme assays of the mutant proteins revealed that, during molecular evolution, the Cys19–Cys154 bond contributed to improving substrate recognition (K_m), whereas the Cys134–Cys199 bond contributed to enhancing catalytic turnover (k_cat). In addition, the Cys134–Cys199 disulfide bond significantly increased the structural stability, whereas the Cys19–Cys154 disulfide bond promoted a more compact folded ensemble. Interestingly, when both disulfide bridges were introduced together, their effects acted synergistically, yielding the highest catalytic activity toward the substrate BAEE (k_cat/K_m). Taken together, these findings suggest that trypsin-like proteases evolved through a two-step adaptive process: an initial phase in which the catalytic efficiency (k_cat) and structural stability were enhanced, followed by a second phase in which the fold became more compact, thereby improving the overall enzymatic activity. Full article

Microparticle detection technology uses materials that can specifically recognize complex biostructures, such as antibodies and aptamers, as trapping agents. The development of antibody production technology and simplification of sensing signal output methods have facilitated commercialization of disposable biosensors, making rapid diagnosis possible. Although this contributed to the early resolution of pandemics, traditional biosensors face issues with sensitivity, durability, and rapid response times. We aimed to fabricate microspaces using metallic materials to further enhance durability of mold fabrication technologies, such as molecular imprinting. Low-damage metal deposition was performed on target protozoa and Norovirus-like particles (NoV-LPs) to produce thin metallic films that adhere to the material. The procedure for fitting the object into the bio structured space formed on the thin metal film took less than a minute, and sensitivity was 10 fg/mL for NoV-LPs. Furthermore, because it was a metal film, no decrease in reactivity was observed even when the same substrate was stored at room temperature and reused repeatedly after fabrication. These findings underscore the potential of integrating stable metallic structures with bio-recognition elements to significantly enhance robustness and reliability of environmental monitoring. This contributes to public health strategies aimed at early detection and containment of infectious diseases. Full article

Coconut coir, a key substrate in soilless cultivation, presents challenges for accurate moisture detection because of its complex internal structure, which limits the understanding of water infiltration and redistribution. This study employed RGB image recognition techniques combined with machine learning algorithms to systematically investigate the effects of initial moisture content (10%, 20%, and 30%), coarse-to-fine coir volume ratio (1:0, 1:1, and 0:1), and emitter discharge rate (1.0, 1.5, and 2.0 L h⁻¹) on wetting front morphology, water transport dynamics, and moisture variation within coir substrates. Morphological features of the wetting front were extracted from images and incorporated into three machine learning models—Support Vector Regression (SVR), Random Forest (RF), and Polynomial Regression—to construct a predictive framework for coir moisture estimation. The results showed that the SVR model achieved the best predictive performance in coarse coir substrates (R² = 0.89, RMSE = 3.37%), whereas Polynomial Regression performed best in mixed substrates (R² = 0.861, RMSE = 4.34%). All models exhibited lower accuracy in fine coir, particularly at high moisture levels. Under the same irrigation volume, increasing the initial moisture content enhanced both the water transport rate and the wetting front extent, with the aspect ratio (AR) decreasing from approximately 2.0 to 1.3, indicating a morphological transition of the wetting front from a “thumb-shaped” to a “hemispherical” pattern. Coarse particles facilitated vertical infiltration, while fine particles exhibited stronger water retention. By integrating RGB image recognition with machine learning approaches, this study achieved reliable prediction of coir moisture content and proposed an optimal management strategy using mixed substrates with an initial moisture content of 20–30% to balance infiltration efficiency and water-holding capacity while minimizing percolation risk. These findings provide a robust technical pathway for precise water management in coir-based cultivation systems. Full article

Metal–organic framework (MOF)-based surface-enhanced Raman scattering (SERS) sensors have emerged as a versatile platform for high-sensitivity and selective detection in agricultural, environmental, and biomedical applications. By integrating plasmonic nanostructures with tunable MOF architectures, these hybrid systems combine ultrahigh signal enhancement with molecular recognition, analyte preconcentration, and controlled hotspot distribution. This review provides a comprehensive overview of the fundamental principles underpinning MOF–SERS performance, including EM and chemical enhancement mechanisms, and highlights strategies for substrate design, such as metal–MOF composites, plasmon-free frameworks, ligand functionalization, and hierarchical or core–shell architectures. We further examine their applications in environmental monitoring, pesticide and contaminant detection, pathogen identification, biomarker analysis, and theranostics, emphasizing real-sample performance, molecular selectivity, and emerging integration with portable Raman devices and AI-assisted data analysis. Despite notable advances, challenges remain in reproducibility, quantitative reliability, matrix interference, scalability, and biocompatibility. Future developments are likely to focus on rational MOF design, sustainable fabrication, intelligent spectral interpretation, and multifunctional integration to enable robust, field-deployable sensors. Overall, MOF-based SERS platforms represent a promising next-generation analytical tool poised to bridge laboratory innovation and practical, real-world applications. Full article

Human carboxylesterases (CES) are enzymes that play a central role in the metabolism and biotransformation of diverse endogenous substances and xenobiotics. The two most relevant isoforms, CES1 and CES2, are crucial in clinical pharmacotherapy as they catalyze the hydrolysis of numerous approved drugs and prodrugs. Elucidating the structural basis of CES isoform substrate specificity is essential not only for understanding and anticipating the biological fate of administered drugs, but also for designing prodrugs with optimized site-specific bioactivation. Additionally, this knowledge is also important for the design of biomedically useful molecules such as subtype-targeted CES inhibitors and fluorescent probes. In this context, both experimental and computational methodologies have been used to explore the mechanistic and thermodynamic properties of CES-mediated catalysis. Experimental designs commonly employ recombinant CES or human tissue microsomes as enzyme sources, utilizing quantification methods such as spectrophotometry (UV and fluorescence) and mass spectrometry. Computational approaches fall into two categories: (1) modeling substrate: CES recognition and affinity (molecular docking, molecular dynamics simulation, and free-energy binding calculations), and (2) modeling substrate: CES reaction coordinates (hybrid QM/MM simulations). While experimental and theoretical approaches are highly synergistic in studying the catalytic properties of CES subtypes, they represent distinct technical and scientific fields. This review aims to provide an integrated discussion of the key concepts and the interplay between the most commonly used wet-lab and dry-lab strategies for investigating CES catalytic activity. We hope this report will serve as a concise resource for researchers exploring CES isoform specificity, enabling them to effectively utilize both experimental and computational methods. Full article

Swida wilsoniana is an important oil-producing tree species whose fruits are rich in unsaturated fatty acids with high nutritional and medicinal value. Lipases are involved not only in lipid mobilization but also potentially in the regulation of fatty acid composition and oil accumulation in plants. In this study, the fatty acid composition of S. wilsoniana fruits was analyzed using gas chromatography–flame ionization detection (GC-FID), and the three most abundant fatty acids were selected as molecular docking ligands. Based on overall multi-ligand docking performance (including mean affinity across the three ligands), three key lipases—SwL5, SwL8, and SwL12—were identified as having the strongest interactions with these fatty acids. Phylogenetic analysis revealed that SwL5 and SwL12 belong to lipase family II, while SwL8 is classified into family VI. Molecular dynamics simulations were further performed to evaluate the binding stability and to characterize the structural basis of substrate recognition, including key interacting residues. This study provides theoretical insights into the molecular regulation of fatty acid composition in S. wilsoniana, and offers potential gene targets for the genetic improvement of oil quality traits. Full article

Ene reductases, belonging to the Old Yellow Enzyme (OYE) family, are widely used for biocatalysis. The OYE from Thermus scotoductus SA-01 (TsOYE) gained great attention due to its broad substrate scope, high stereoselectivity, thermostability, and catalytic versatility. Recently, the otherwise noncovalently bound flavin cofactor (FMN) was covalently anchored in several TsOYE mutants using the “flavin-fixing” method. However, the biochemical properties of these mutants remained unexplored. A detailed comparative study of wild-type (WT) TsOYE and the flavin-fixing variant F1 (F1 TsOYE) revealed that F1 TsOYE has a lower stability and poorer catalytic activity. Interestingly, both WT and F1 TsOYE have comparable redox potential values. These results suggest that the decrease in activity and stability is primarily caused by changes in structure and structural dynamics induced by the mutations and the covalent flavin-protein linkage. Replacing residues in the flavinylation recognition site did not result in significant repair of enzyme activity. Our findings highlight the sensitivity of TsOYE activity to covalent FMN incorporation and its associated mutations and underscore the necessity of structural insights for further rational design. This study also provides critical groundwork for optimizing the flavin-fixing strategy. Full article

Since 2014, a model of the individual response to ionizing radiation (IR), based on the radiation-induced nucleoshuttling of the ATM protein kinase (RIANS), has been developed by our lab: after irradiation, ATM dimers monomerize in cytoplasm and diffuse into the nucleus to trigger both recognition and repair of DNA double-strand breaks (DSB), the key-damage of IR response. Moderate radiosensitivity is generally caused by heterozygous mutations of ATM substrates (called X-proteins) that are over-expressed in cytoplasm and form complexes with ATM monomers, which reduces and/or delays the RIANS and DSB recognition. Here, we asked whether molecules, rather than X-proteins, can also influence RIANS. Caffeine was chosen as a potential “X-molecule” candidate. After incubation of cells with caffeine, cutaneous fibroblasts from an apparently healthy radioresistant donor, a patient suffering from Alzheimer’s disease (AD) and another suffering from neurofibromatosis type 1 (NF1) were exposed to X-rays. The functionality of ATM-dependent DSB repair and signaling was evaluated. We report here that caffeine molecule interaction with ATM leads to the inhibition of DSB recognition. This effect is significant in radioresistant cells. Conversely, in the AD and NF1 cells, the DSB recognition is already so low that caffeine does not provide any additional molecular effect. Full article

The recognition of trauma-induced coagulopathy (TIC) as an endogenous response to traumatic injuries rather than a consequence of therapeutic interventions has shifted the clinical approach toward an early and physiologically based hemostatic resuscitation. Prompt identification and correction of fibrinolysis and fibrinogen level derangements, dysregulated thrombin generation, and platelet dysfunction represent the cornerstones of the treatment strategies. Currently available viscoelastic hemostatic assays (VHAs) are point-of-care devices able to rapidly assess the phases of clot initiation, propagation, stabilization, and degradation, as well as isolate the contribution of specific elements—e.g., fibrinogen—to the coagulation process in fully automated analyses by multi-channel single-use cartridges. As a result, in the last decade, VHAs have been widely investigated as tools to implement individualized protocols of hemostatic resuscitation. Current guidelines support their use to optimize transfusion load in a goal-directed strategy. Nevertheless, contrasting evidence has emerged regarding the improvement in main clinical outcomes induced by the VHA-based algorithm of hemostatic resuscitation compared with those guided by conventional coagulation tests, and their place in the management of this peculiar population is still a matter of debate. We propose a narrative review ranging from TIC physiopathology as a proper substrate for viscoelastic diagnostic technique, through the strengths and weaknesses of VHAs, to their application in clinical practice. Full article

This study addresses the challenges associated with transmission electron microscopy (TEM) image analysis of supported nanoparticles, including low signal-to-noise ratio, poor contrast, and interference from complex substrate backgrounds. This study proposes an automated segmentation and particle size analysis method based on a large-scale deep learning model, namely segment anything model (SAM). Using Ru/TiO₂ and related materials as representative systems, the pretrained SAM is employed for zero-shot segmentation of nanoparticles, which is further integrated with a custom image processing pipeline, including optical character recognition (OCR) module, morphological optimization, and connected component analysis to achieve high-precision particle size quantification. Experimental results demonstrate that the method retains robust performance under challenging imaging conditions, with a size estimation error between 3% and 5% and a per-image processing time under 1 min, significantly outperforming traditional manual annotation and threshold-based segmentation approaches. This framework provides an efficient and reliable analytical tool for morphological characterization and structure–performance correlation studies in supported nanocatalysts. Full article

Kombucha is gaining global recognition for its potential health benefits. While traditionally made from sweetened tea, researchers are increasingly exploring local ingredients and agricultural byproducts as alternative substrates for SCOBY fermentation. As a functional beverage that embodies the concept of metabiotics—encompassing live or non-viable probiotics and their bioactive metabolites. This review highlights the holistic health benefits and sustainability aspects of kombucha. Both the fermented beverage, rich in bioactive compounds, and the cellulose-based zoogleal mat can be utilized in various applications, including medical and industrial uses. Moreover, the increasing use of local ingredients and agricultural byproducts as alternative substrates for kombucha production may further improve its sustainability and expand the range of its functional properties. Kombucha has shown promising antioxidant, anti-inflammatory, antimicrobial, anticancer, and antidiabetic properties in pre-clinical studies, positioning it as an emerging functional food. However, further clinical trials and stronger regulatory frameworks are essential to validate its health claims and ensure consumer safety. Full article

KY₃F₁₀:Yb³⁺, Tm³⁺ upconversion microparticles (UCMPs) with varying Mn²⁺ doping concentrations were synthesized via a hydrothermal method. Under 980 nm laser excitation, the sample with 3 mol% Mn²⁺ doping demonstrated markedly enhanced luminescence performance, exhibiting a significant intensity increase compared to undoped samples. The as-synthesized UCMPs were successfully incorporated into an anti-counterfeiting ink. Target information was encrypted using a hash function to generate a QR code, which was then screen-printed onto substrate materials. Under 980 nm laser irradiation, the printed QR code exhibited visible blue fluorescence with high stability, confirming its anti-counterfeiting capability. Furthermore, an image recognition system for anti-counterfeiting, based on a hybrid Convolutional Neural Network-Bidirectional Long Short-Term Memory (CNN-BiLSTM) architecture, was developed on the Matlab platform. The system achieved 100% recognition accuracy for the luminescent QR code patterns, providing valuable insights for the development of deep learning-based image anti-counterfeiting technologies. Full article

Docosahexaenoic acid (DHA), the dominant polyunsaturated fatty acid in photoreceptors, neurons, and synapses, is usually described as a passive structural membrane constituent. We propose a different view: DHA is a quantum-electronically active molecule whose methylene interrupted double-bond system creates an electron-rich matrix that couples with proteins to form quantum “clouds” and high-speed signaling central to recognition, recall, and cognition. Integrating evidence from molecular evolution, biophysics, and neuroscience, we argue that, as the original chromophore, DHA’s unique properties enabled the emergence of the nervous system and continue to provide the electronic substrate for cognition. By suggesting that cognition depends not only on protein-based mechanisms but on DHA-mediated electron dynamics at the membrane–protein interface, this perspective reframes DHA as an active, conserved determinant of brain evolution and function. Full article

The vein and ligament of Marshall (VOM and LOM) are embryological remnants that have gained increasing recognition due to their anatomical complexity, arrhythmogenic potential, and relevance during catheter ablation and structural heart interventions. This review summarizes current evidence on their embryology, morphology, anatomical variability, imaging characteristics, and clinical implications. A structured literature search across PubMed, Embase, and Scopus identified anatomical, histological, electrophysiological, and interventional studies. The VOM is present in most hearts, but its topographic variants and ostial positions show substantial interindividual diversity. The LOM displays a segmental architecture with distinct muscular and fibrotic components that interface with the atrial myocardium and the coronary sinus, providing a substrate for atrial fibrillation. Advances in cardiac imaging have improved delineation of the VOM–LOM region, enhancing pre-procedural assessment and guidance for ethanol infusion and ablation strategies. Recognition of the variability and functional significance of these structures is essential for optimizing procedural outcomes and avoiding complications. Taken together, the VOM and LOM represent key atrial venous remnants whose detailed characterization contributes to a deeper understanding of atrial arrhythmogenesis and contemporary interventional electrophysiology. Full article