Search

As the most common cancer disease in the world, breast cancer is the main cause of death of female cancer patients. The number of women in China is far greater than that in other countries. Therefore, the absolute death toll is often high. Even a small increase in incidence rate will lead to a severe increase in deaths. Therefore, accurate preoperative diagnosis of benign and malignant breast cancer and the status prediction of various clinical indicators are urgently needed in clinical practice. Deep learning based on neural network has been widely used in diagnosis. Therefore, this paper attempts to explore the influence of deep learning on the auxiliary diagnosis technology of small tumor in mammography. In this paper, 200 cases of breast disease patients in a hospital of our city were taken as the research object, and the artificial neural network model was established. Through the experimental simulation, the results showed that the diagnostic sensitivity, specificity and overall accuracy of BP neural network for test set samples were 95.3%, 96.7 and 96.2%, respectively. The experimental results confirmed its generalization ability. In this paper, the core idea of multi feature kernel hash, combined with a variety of features and deep kernel hash network framework, constructs a new multi feature based deep learning network, which can effectively express the image features of breast tumor, and complete the task of breast micro tumor detection with good performance.

The coating of nanoparticles (NPs) with biodegradable ligands has been considered an efficient way to improve the biocompatibility of NPs and to decrease their biopersistence. However, the role of ligand biodegradation in reshaping the core material and the resulting change in toxicity have not been fully explored. In this study, magnetite (Fe3O4) NPs coated with a high or low loading of hyaluronic acid (termed Fe3O4–HAHand Fe3O4–HAL) were synthesized. Fe3O4–HARwas obtained after the enzymatic degradation of Fe3O4–HAHby a hyaluronidase, which had a coating weight similar to that of Fe3O4–HAL, as verified by thermogravimetric analysis. Interestingly, among the three NPs, Fe3O4–HARinduced the highest rate of cellular damage. In particular, 2 times more hydroxyl radicals were detected in cells stressed by Fe3O4–HARthan in cells stressed by Fe3O4–HAH, despite the highest cellular uptake being observed for Fe3O4–HAHbecause of the ligand–receptor interactions between hyaluronic acid and membrane receptors. The structural characterization results revealed that ligand degradation induced notable surface reconstruction of the Fe3O4core, showing a characteristic Fe3O4@Fe2O3structure with surface-bound ferrous ions. This unique structure endowed Fe3O4–HARwith superior competency in initiating the Fenton reaction and accelerating the Fe(iii)/Fe(ii) cycle. Our results emphasize the importance of tracing the in vivobiotransformation of NPs from all of the different architectural parts, particularly deciphering the interplay among the core, shell, surface ligands, and surrounding ions.

Agrocybe aegeritais widely popular for its umami taste. This study utilized five enzymes to hydrolyze the non-volatile taste active compounds extracted from A. aegerita, including inorganic ions, organic acids, soluble sugars, free amino acids, 5′-nucleotides, and small peptides. The taste activity value (TAV) was used to measure the non-volatile taste active components, while the synergistic effects of umami were determined using equivalent umami concentration (EUC). The results showed that the protamex-treated hydrolysate had the highest umami sensory score (7.03) and EUC value (1039.475 ± 2.673) with the most low-molecular-weight peptides (<1 KDa) and soluble sugars, conferring the best overall flavor characteristics. Furthermore, a positive correlation was found between the EUC values and umami sensory scores and acceptability. Overall, the results showed that the protamex-treated A. aegeritahydrolysate had the highest umami taste and acceptability. Thus, this study provides more information for further studies on the umami compounds of A. aegeritaand a theoretical basis for the development and utilization of A. aegeritaas a condiment.

The environmental transformation of graphene oxide (GO) can significantly change its physicochemical properties, thus altering its toxicity. Here, we demonstrated how exposure to simulated sunlight or reduction with ferrous iron (Fe2+, an environmentally abundant and mild reductant) significantly impacts the cytotoxicity of GO. GOs were reduced under both sets of conditions, but the Fe2+-reduced GO showed dramatically lower cytotoxicity than did the light-reduced GO. A highly reactive graphene-based radical was generated when GO was exposed to light, and this radical significantly contributed to cell membrane oxidation. Moreover, light-induced reduction promoted breakage of the graphene sheet, decreasing the lateral size and increasing the ability of the material to disrupt the membrane, which consequently enhanced cellular uptake. Interestingly, we observed a loss of C–O–C/C–O groups but an increase in CO/O–CO groups during Fe2+reduction; these alterations improved the radical quenching capacity of the material due to the restored sp2structure and the increase in electron-shuttering groups. Reduction-induced aggregation significantly decreased cellular uptake relative to the internalization of the parent GO. These results emphasize that environmental transformation-induced property changes should be given adequate consideration in the risk assessment of GO.