Silver staining is an excellent technique for detecting proteins that are separated by sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE). Protein silver staining technology has higher sensitivity and is suitable for the detection of low-concentration proteins compared to other staining techniques including the Coomassie brilliant blue detection method. The present study was conducted to enhance the detection ability of the protein staining method. Herein, we modified the recipe of silver staining, a very reproducible method, by adding AMP, PVP, Tween-80, and xylene to enhance the detection ability of protein staining. Furthermore, the particle size and potentiometer were used to detect the particle size and potential difference of the silver ions in the prepared dyeing materials, and then, the morphology, transparency, and size of the dyed silver particles in different dyeing solutions were studied using a transmission electron microscopy (TEM). The obtained results revealed that the use of 0.5% of AMP, PVP, Tween-80, and xylene improved the staining ability of protein silver staining, compared with the original method. Furthermore, 0.5% AMP, 0.5% PVP, 0.5% Tween-80 reagents significantly influenced the morphology, size, potential, and dispersion of silver ions. These results suggested a new idea for further improving the detection ability of protein silver staining.
The artificial intelligence (AI) system has achieved expert-level performance in electrocardiogram (ECG) signal analysis. However, in underdeveloped countries or regions where the healthcare information system is imperfect, only paper ECGs can be provided. Analysis of real-world ECG images (photos or scans of paper ECGs) remains challenging due to complex environments or interference. In this study, we present an AI system developed to detect and screen cardiac abnormalities (CAs) from real-world ECG images. The system was evaluated on a large dataset of 52,357 patients from multiple regions and populations across the world. On the detection task, the AI system obtained area under the receiver operating curve (AUC) of 0.996 (hold-out test), 0.994 (external test 1), 0.984 (external test 2), and 0.979 (external test 3), respectively. Meanwhile, the detection results of AI system showed a strong correlation with the diagnosis of cardiologists (cardiologist 1 (R=0.794, p<1e-3), cardiologist 2 (R=0.812, p<1e-3)). On the screening task, the AI system achieved AUCs of 0.894 (hold-out test) and 0.850 (external test). The screening performance of the AI system was better than that of the cardiologists (AI system (0.846) vs. cardiologist 1 (0.520) vs. cardiologist 2 (0.480)). Our study demonstrates the feasibility of an accurate, objective, easy-to-use, fast, and low-cost AI system for CA detection and screening. The system has the potential to be used by healthcare professionals, caregivers, and general users to assess CAs based on real-world ECG images.
African swine fever virus (ASFV) is the causative agent of African swine fever (ASF), a severe hemorrhagic disease with a mortality rate reaching 100%. Despite extensive research on ASFV mechanisms, no safe and effective vaccines or antiviral treatments have been developed. Live attenuated vaccines generated via gene deletion are considered to be highly promising. We developed a novel recombinant ASFV strain by deleting MGF360-10L and MGF505-7R, significantly reducing virulence in pigs. In the inoculation experiment, pigs were infected with 104 50% hemadsorption doses (HAD50) of the mutant strain. All the animals survived the observation period without showing ASF-related clinical signs. Importantly, no significant viral infections were detected in the cohabitating pigs. In the virus challenge experiment, all pigs succumbed after being challenged with the parent strain. RNA-seq analysis showed that the recombinant virus induced slightly higher expression of natural immune factors than the parent ASFV; however, this level was insufficient to provide immune protection. In conclusion, our study demonstrates that deleting MGF360-10L and MGF505-7R from ASFV CN/GS/2018 significantly reduces virulence but fails to provide protection against the parent strain.
Collagen is the most abundant protein in animals, which is widely distributed in all kinds of animals, and its composition and evolution is very complex. In this study, SDS-PAGE protein electrophoresis was used to determine the changes of electrophoretic bands of collagen extracted by enzymatic hydrolysis from pigs, cattle, fish and rats, and the results of electrophoretic hydrolysis are summarized below. Hydrolysis from pigs, cattle, fish and rats, and the results of electrophoretic bands were classified and sorted out. Using the different characteristics and proportion data of collagen electrophoretic bands of four kinds of animals, the characteristic bands were analyzed, and the Using the different characteristics and proportion data of collagen electrophoretic bands of four kinds of animals, the characteristic bands were analyzed, and the functional region analysis and prediction tool of SMART protein was used. The relevant research results provide a reference for clarifying the characteristics of collagen evolved in different animals and for the establishment of its determination methodology, and for the determination of collagen in different animals. The relevant research results provide a reference for clarifying the characteristics of collagen evolved in different animals and for the establishment of its determination methodology, and provide experimental data and scientific basis for the development of different types of collagen medical products.
In this study, we fed the larval of Bombyx mori silkworms with nanodroplets of liquid metal (LM) coated with microgels of marine polysaccharides to obtain stretchable silk. Alginate-coated liquid metal nanodroplets (LM@NaAlg) were prepared with significant chemical stability and biocompatibility. This study demonstrates how the fed LM@NaAlg acts on the as-spun silk fiber. We also conducted a series of characterizations and steered molecular dynamics simulations, which showed that the LM@NaAlg additions impede the conformation transition of silk fibroins from the random coil and α-helix to the β-sheet by the formation of hydrogen bonds between LM@NaAlg and the silk fibroins, thus enhancing the elongation at the breakpoints in addition to the tensile properties. The intrinsically highly stretchable silk showed outstanding mechanical properties compared with regular silk due to its 814 MPa breaking strength and a breaking elongation of up to 70%-the highest reported performance so far. We expect that the proposed method can expand the fabrication of multi-functional silks.
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