Aptamer-free upconversion nanoparticle/silk biosensor system for low-cost and highly sensitive detection of antibiotic residues

From molecular mechanisms to clinical translation: Silk fibroin-based biomaterials for next-generation wound healing

Silk fibroin (SF) is a natural polymeric material that has attracted intense research attention in the field of wound healing due to its exceptional mechanical properties, tunable biodegradability, and multifunctional bioactivity. This review systematically summarizes the preparation strategies, functional modifications, and multidimensional application mechanisms of SF and its composite materials in wound healing. The innovative applications of SF in intelligent dressing design, immunometabolic regulation, controlled drug release, stem-cell function modulation, and bioelectrical-activity-mediated microenvironment remodeling is further explored, while analyzing the therapeutic efficacy and cost-effectiveness of SF through clinical translation cases. Distinct from previous reviews, this work not only integrates the latest advances in SF molecular mechanisms and material design but also emphasizes its potential in precision medicine, such as the development of genetically engineered SF for customized immunoregulatory networks. Finally, the article highlights the current challenges in the development of SF materials, including mechanical stability, degradation controllability, and standardization of large-scale production, and envisions future research directions driven by 3D bioprinting and synthetic biology technologies. This review provides a theoretical foundation and technical reference information for the development of efficient, multifunctional, and clinically translatable SF-based materials for application in wound healing.

Deep eutectic solvent induced silver-gel as a flexible SERS substrate for sensitive detection of antibiotics under low temperature conditions

Antibiotic residues pose a significant threat to global health. Traditional detection methods for antibiotics are cumbersome, time-consuming and often incapable of achieving non-destructive detection at low temperatures. This research introduces a groundbreaking innovation in antibiotic detection: a flexible Surface-Enhanced Raman Scattering substrate based on a silver composite deep eutectic solvent (DES) gel, specifically engineered for low-temperature antibiotic detection. To address the challenge of low SERS response for antibiotics, we utilize R6G (Rhodamine 6 G) to effectively label them. This unique SERS substrate exhibits exceptional mechanical robustness, stability, and frost-resistance. Remarkably, it enables the direct and sensitive detection of six types of labeled antibiotics across four categories in frozen chicken wings at -25 °C, with a limit of detection (LOD) below 1.3 × 10-9 mol/L. Additionally, the substrate demonstrates outstanding homogeneity (relative standard deviation (RSD< 6.4 %), reproducibility (RSD < 6.2 %), and long-term stability over 30 days, ensuring highly sensitive and quantitative antibiotic detection. Theoretical insights reveal that the labeled antibiotics exhibit higher binding energy with silver, further enhancing detection sensitivity. This novel, flexible substrate holds immense potential for quantifying antibiotics in frozen foods and heralds a new era of expanded detection capabilities for a broader spectrum of antibiotics at low temperatures.

Tracing antibiotics in sewers: Concentrations, measurement techniques, and mathematical approaches

Antibiotic contamination in sewer networks has significant environmental and health concerns worldwide, primarily due to its role in promoting bacterial resistance. In this literature review, antibiotic concentrations reported in urban sewers and hospital effluents, techniques for antimicrobial compound detection and quantification, and current modeling strategies are analyzed and discussed based on 91 papers published between 2014 and 2024. One-hundred and nine antibiotic compounds were reported across 80 studies, with sulfonamides, fluoroquinolones, and macrolides being the most frequently detected classes, while amphenicols and aminocyclitols were the least monitored. Advanced analytical techniques such as liquid chromatography and mass spectrometry are the most common approaches used for antibiotic quantification. Modeling efforts remain limited, with kinetic models, Risk Quotient (RQ) assessments, and Wastewater-Based Epidemiology (WBE) representing the main approaches identified. This review compiles 992 reports into a comprehensive dataset intended to support future research, especially for global monitoring, the development of predictive models, and the formulation of regulatory frameworks for managing antibiotic pollution in sewer systems.

Graphene FET biochip on PCB reinforced by machine learning for ultrasensitive parallel detection of multiple antibiotics in water

Antibiotics like Ciprofloxacin (Cfx), tetracycline (Tet) and Tobramycin (Tob) are commonly used against a broad-spectrum of bacterial infection. Recent surge in their uptake through the presence of their residues in environmental water has been linked to increased antibiotic resistance. Conventional methods for antibiotic monitoring by gold standards like LC-MS though sensitive and reliable, are expensive, requires dedicated equipment and complex sample processing steps. In this context, nanoscale field-effect transistors (FETs) present significant advantages of rapid measurement and ultra-high sensitivity but the device-device variations in the transfer characteristics originating from the inherent fluctuations in fabrication protocol of 2D materials, lead to stochasticity in bioreceptor orientation and binding densities which limits their potential for ultrasensitive and reliable detection of multiple antibiotics in river water. Here, we introduce a distinctive approach for few femtomolar detection of Cfx, Tet and Tob simultaneously in river water by developing thermally reduced graphene oxide (TRGO) FET array on printed circuit board utilizing copper plated electrodes where multiple features extracted from sensor transfer characteristics are processed by machine learning models, trained with moderate calibration dataset. The demonstrated methodology detects 1 fM concentration of Cfx, Tet and Tob with satisfactory accuracy within 20 min, using XGBoost model. The achieved detection limit is three and two orders of magnitude lower than previous reports of multiple and single antibiotic detection respectively. The TRGO FET sensor array interfaced with an electronic readout imparts capability to track the concentration of antibiotic contaminants in various water sources and adopt necessary measures for safe drinking water.

Oriented Cortical-Bone-Like Silk Protein Lamellae Effectively Repair Large Segmental Bone Defects in Pigs

Assembling natural proteins into large, strong, bone-mimetic scaffolds for repairing bone defects in large-animal load-bearing sites remain elusive. Here this challenge is tackled by assembling pure silk fibroin (SF) into 3D scaffolds with cortical-bone-like lamellae, superior strength, and biodegradability through freeze-casting. The unique lamellae promote the attachment, migration, and proliferation of tissue-regenerative cells (e.g., mesenchymal stem cells [MSCs] and human umbilical vein endothelial cells) around them, and are capable of developing in vitro into cortical-bone organoids with a high number of MSC-derived osteoblasts. High-SF-content lamellar scaffolds, regardless of MSC inoculation, regenerated more bone than non-lamellar or low-SF-content lamellar scaffolds. They accelerated neovascularization by transforming macrophages from M1 to M2 phenotype, promoting bone regeneration to repair large segmental bone defects (LSBD) in minipigs within three months, even without growth factor supplements. The bone regeneration can be further enhanced by controlling the orientation of the lamella to be parallel to the long axis of bone during implantation. This work demonstrates the power of oriented lamellar bone-like protein scaffolds in repairing LSBD in large animal models.

Injectable platelet-mimicking silk protein-peptide conjugate microspheres for hemostasis modulation and targeted treatment of internal bleeding

Uncontrolled deep bleeding, commonly encountered in surgical procedures, combat injuries, and trauma, poses a significant threat to patient survival and recovery. The development of effective hemostatic agents capable of precisely targeting trauma sites in deep tissues and rapidly halt bleeding remains a considerable challenge. Drawing inspiration from the natural hemostatic cascade, we present platelet-like microspheres composed of silk fibroin (SF) and thrombus-targeting peptides, engineered to mimic natural platelets for rapid hemostasis in vivo. These peptide/SF hemostatic microspheres, formulated using a freezing self-assembly technology, closely resemble natural platelets in terms of size, shape, and zeta potential. Moreover, they exhibit favorable cytocompatibility, hemocompatibility, and anti-cell adhesion. Assessment of fibrin polymerization revealed that these hemostatic microspheres possessed enzymatic physiological functions, similar to activated platelets, facilitating platelet adhesion, fibrin binding, and wound-triggered hemostasis. Notably, these hemostatic microspheres rapidly target the bleeding site in vivo within 5 min, with minimal dispersion elsewhere, persisting after blood clot formation. Furthermore, these microspheres exhibit favorable metabolic kinetics, with 71% degradation occurring within one-day post-subcutaneous injection. Histological assessment revealed well-preserved organ structures and minimal inflammatory responses at 14 d post-injection, supporting their long-term biocompatibility. Importantly, they can be injected and targeted into damaged blood vessels, selectively binding to fibrin and forming blood clots within 2 min, resulting in a 74% reduction in bleeding volume compared to SF microspheres alone. Therefore, these injectable SF-based hemostatic microspheres emerge as promising candidates for future rapid hemostasis in tissue injuries.

Bioengineered Silk Protein-Based 3D In Vitro Models for Tissue Engineering and Drug Development: From Silk Matrix Properties to Biomedical Applications

3D in vitro model has emerged as a valuable tool for studying tissue development, drug screening, and disease modeling. 3D systems can accurately replicate tissue microstructures and physiological features, mirroring the in vivo microenvironment departing from conventional 2D cell cultures. Various 3D in vitro models utilizing biomacromolecules like collagen and synthetic polymers have been developed to meet diverse research needs and address the complex challenges of contemporary research. Silk proteins, bearing structural and functional similarities to collagen, have been increasingly employed to construct advanced 3D in vitro systems, surpassing the limitations of 2D cultures. This review examines silk proteins' composition, structure, properties, and functions, elucidating their role in 3D in vitro models. Furthermore, recent advances in biomedical applications involving silk-based organoid models are discussed. In particular, the unique physiological attributes of silk matrix constituents in in vitro tissue constructs are highlighted, providing a meticulous evaluation of their importance. Additionally, it outlines the current research hurdles and complexities while contemplating future avenues, thereby paving the way for developing complex and biomimetic silk protein-based microtissues.

Fluorescence Visualization Quantitative Detection of Tetracycline and Nitrofurantoin in Food and Natural Water by Zn2+@Eu-bpdc Composite

Quantitative detection of tetracycline (TC) and nitrofurantoin (NFT) in food and water is of importance for food safety and environmental protection. Herein, Zn2+ was introduced into a europium metal-organic framework Eu-bpdc (H2bpdc = 2,2'-bipyridyl-5,5'-dicarboxylic acid) to prepare a composite of Zn2+@Eu-bpdc, which was developed as a fluorescence sensor for TC and NFT. The fluorescence mechanism concerns with bpdc2- ligand-to-Eu(III) charge transfer, and the detection mechanism is the inner filter effect. Zn2+@Eu-bpdc is a ratiometric fluorescence sensor for TC with the linear fitting equation of I520/I618 = 1.94 × 104 M-1CTC, whose limit of detection (LOD) is 0.148 μmol·L-1 (μM); it is also a fluorescence "turn-off" sensor for NFT with the fitting equation of (I0-I)/I = 3.62 × 104 M-1CNFT and LOD = 0.0792 μM. Zn2+@Eu-bpdc can detect TC or NFT in lake water, honey, and milk with high accuracy. The emission color changes of paper-based Zn2+@Eu-bpdc depending on CTC or CNFT reveal the visualization detections of TC and NFT. With the red and green values as input signals, smartphone-assisted on-site detection is utilized to recognize the antibiotic residuals of TC and NFT by a self-programmed APP. Zn2+@Eu-bpdc is promising in a smartphone-assisted intelligent platform for on-site detection of TC and NFT.

Lanthanide-doped upconversion nanoparticles as nanoprobes for bioimaging

Upconversion nanoparticles (UCNPs) are a class of nanomaterials composed of lanthanide ions with great potential for paraclinical applications, especially in laboratory and imaging sciences. UCNPs have tunable optical properties and the ability to convert long-wavelength (low energy) excitation light into short-wavelength (high energy) emission in the ultraviolet (UV)-visible and near-infrared (NIR) spectral regions. The core-shell structure of UCNPs can be customized through chemical synthesis to meet the needs of different applications. The surface of UCNPs can also be tailored by conjugating small molecules and/or targeting ligands to achieve high specificity and selectivity, which are indispensable elements in biomedical applications. Specifically, coatings can enhance the water dispersion, biocompatibility, and efficiency of UCNPs, thereby optimizing their functionality and boosting their performance. In this context, multimodal imaging can provide more accurate in vivo information when combined with nuclear imaging. This article intends to provide a comprehensive review of the core structure, structure optimization, surface modification, and various recent applications of UCNPs in biomolecular detection, cell imaging, tumor diagnosis, and deep tissue imaging. We also present and discuss some of their critical challenges, limitations, and potential future directions.