Ultrasensitive detection of tyrosinase with click reaction-combined dark-field imaging platform.

Tyrosinase (TYR) is an essential oxidase that is responsible for the regulation of multiple physiological processes and diseases. Achieving the trace and reliable detection of TYR in complex biological samples is of great significance for the diagnosis of TYR-related diseases, but which faces a great challenge. In this study, we developed an ingenious and powerful method for the ultrasensitive detection of TYR by click reaction-combined dark-field microscopy. This method begins with the formation of cuprous ions (Cu+) based on the reduction of copper ions (Cu2+) by ascorbic acid (AA). Subsequently, the formed Cu+ can catalyze the crosslinking between azide- and alkyne-functionalized gold nanoparticles, causing a significant red-shift in the scattering spectrum. However, AA can chelate with TYR, which inhibits the generation of Cu+ and subsequent click reaction, thus achieving TYR-controlled scattering spectral shift. The proposed sensing platform shows a good linear detection range of 0.01-0.8 U/L with a low detection limit of 0.003 U/L, which is three orders of magnitude lower than the best performance of TYR sensing probes reported to date. Most importantly, the strategy has the ability to reliably and accurately detect TYR in serum sample, suggesting its potential clinical application in diagnosing TYR-related diseases. This visual sensing platform offers promising prospects for future research in enzymatic analysis and biomedical diagnostics.

Holistic Prediction of AuNP Aggregation in Diverse Aqueous Suspensions Based on Machine Vision and Dark-Field Scattering Imaging.

The localized surface-plasmon resonance of the AuNP in aqueous media is extremely sensitive to environmental changes. By measuring the signal of plasmon scattering light, the dark-field microscopic (DFM) imaging technique has been used to monitor the aggregation of AuNPs, which has attracted great attention because of its simplicity, low cost, high sensitivity, and universal applicability. However, it is still challenging to interpret DFM images of AuNP aggregation due to the heterogeneous characteristics of the isolated and discontinuous color distribution. Herein, we introduce machine vision algorithms for the training of DFM images of AuNPs in different saline aqueous media. A visual deep learning framework based on AlexNet is constructed for studying the aggregation patterns of AuNPs in aqueous suspensions, which allows for rapid and accurate identification of the aggregation extent of AuNPs, with a prediction accuracy higher than 0.96. With the aid of machine learning analysis, we further demonstrate the prediction ability of various aggregation phenomena induced by both cation species and the concentration of the external saline solution. Our results suggest the great potential of machine vision frameworks in the accurate recognition of subtle pattern changes in DFM images, which can help researchers build predictive analytics based on DFM imaging data.

Determination of mycobiota and aflatoxin contamination in commercial bee pollen from eight provinces and one autonomous region of China.

The co-occurrence of fungi and mycotoxins in various foods has been frequently reported in many countries, posing a serious threat to the health and safety of consumers. In this study, the mycobiota in five types of commercial bee pollen samples from China were first revealed by DNA metabarcoding. Meanwhile, the content of total aflatoxins in each sample was investigated by high-performance liquid chromatography with fluorescence detection. The results demonstrated that Cladosporium (0.16 %-89.29 %) was the most prevalent genus in bee pollen, followed by Metschnikowia (0-81.12 %), unclassified genus in the phylum Ascomycota (0-81.13 %), Kodamaea (0-73.57 %), and Penicillium (0-36.13 %). Meanwhile, none of the assayed aflatoxins were determined in the 18 batches of bee pollen samples. In addition, the fungal diversity, community composition, and trophic mode varied significantly among five groups. This study provides comprehensive information for better understanding the fungal communities and aflatoxin residues in bee pollen from different floral origins in China.

Enabling High-Performance All-Solid-State Batteries via Guest Wrench in Zeolite Strategy.

All-solid-state batteries with a high energy density and safety are desirable candidates for next-generation energy storage applications. However, conventional solid electrolytes for all-solid-state batteries encounter limitations such as poor ionic conduction, interfacial compatibility, instability, and high cost. Herein, taking advantage of the ingenious capability of zeolite to incorporate functional guests in its void space, we present an innovative ionic activation strategy based on the "guest wrench" mechanism, by introducing a pair of cation and anion of LiTFSI-based guest species (GS) into the supercage of the LiX zeolite, to fabricate a zeolite membrane (ZM)-based solid electrolyte (GS-ZM) with high Li ionic conduction and interfacial compatibility. The restriction of zeolite frameworks toward the framework-associated Li ions is significantly reduced through the dynamic coordination of Li ions with the "oxygen wrench" of TFSI- at room temperature as shown by experiments and Car-Parrinello molecular dynamics simulations. Consequently, the GS-ZM shows an ∼100% increase in ionic conductivity compared with ZM and an outstanding Li+ transference number of 0.97. Remarkably, leveraging the superior ionic conduction of GS-ZM with the favorable interface structure between GS-ZM and electrodes, the assembled all-solid-state Li-ion and Li-air batteries based on GS-ZM exhibit the best-level electrochemical performance much superior to batteries based on liquid electrolytes: a capacity retention of 99.3% after 800 cycles at 1 C for all-solid-state Li-ion batteries and a cycle life of 909 cycles at 500 mA g-1 for all-solid-state Li-air batteries. The mechanistic discovery of a "guest wrench" in zeolite will significantly enhance the adaptability of zeolite-based electrolytes in a variety of all-solid-state energy storage systems with high performance, high safety, and low cost.

Zearalenone Exposure Disrupts STAT-ISG15 in Rat Colon: A Potential Linkage between Zearalenone and Inflammatory Bowel Disease.

Zearalenone (ZEN), a prevalent mycotoxin contaminating food and known for its intestinal toxicity, has been suggested as a potential risk factor for inflammatory bowel disease (IBD), although the exact relationship between ZEN exposure and IBD remains unclear. In this study, we established a rat model of colon toxicity induced by ZEN exposure to investigate the key targets of ZEN-induced colon toxicity and explore the underlying connection between ZEN exposure and IBD. Histological staining of the rat colon revealed significant pathological changes resulting from ZEN exposure (p < 0.01). Furthermore, the proteomic analysis demonstrated a notable upregulation of protein expression levels, specifically STAT2 (0.12 ± 0.0186), STAT6 (0.36 ± 0.0475) and ISG15 (0.43 ± 0.0226) in the rat colon (p < 0.05). Utilizing bioinformatics analysis, we combined ZEN exposure and IBD clinical sample databases to reveal that ZEN exposure may increase the risk of IBD through activation of the STAT-ISG15 pathway. This study identified novel targets for ZEN-induced intestinal toxicity, providing the basis for further study of ZEN exposure to IBD.

Rapid screening of imidacloprid residue in grains and medicinal herbs: A newly designed hapten and monoclonal antibody.

Three different imidacloprid hapten structures were designed to conjugate with proteins (bovine serum albumin, BSA; ovalbumin, OVA; keyhole limpet hemocyanin, KLH) for screening the optimal immunogen and coating antigen. Among these, an unreported antigen (hapten 6-KLH) was selected as the optimal immunogen and coating antigen. In addition, an imidacloprid-specific and high titer monoclonal antibody (IMIB7C3) was obtained by using the above-selected immunogen. A sensitive ic-ELISA (indirect competitive enzyme-linked immunosorbent assay) with a half-maximal inhibitory concentration (IC50) of 1.3 ng mL-1 was established by using the IMIB7C3 antibody (only 1.2 ng per well) to detect the residues of imidacloprid in grains (wheat and maize) and different herbs (Notoginseng radix et rhizoma, Dioscoreae rhizoma, Lonicerae japonicae flos, Astragali radix, Jujubae fructus). The detection results of real samples by the developed immunoassay were confirmed by liquid chromatography-tandem mass spectrometry (LC-MS/MS), which proved the accuracy and reliability of the established ic-ELISA. These results indicate that the proposed ic-ELISA method is suitable for rapid and high-throughput detection of imidacloprid residues in agricultural products and medicinal herbs. Furthermore, a quantitative risk assessment was conducted for Lonicerae japonicae flos based on the detection results, which indicates an acceptable risk to human health after the intake of Lonicerae japonicae flos polluted by imidacloprid.