Microsecond pulsed electric fields (PEF) have previously been used for various tumour therapies, such as gene therapy, electrochemotherapy and irreversible electroporation (IRE), due to its demonstrated ability. However, recently nanosecond pulsed electric fields (nsPEF) have also been used as a potential tumor therapy via inducing cell apoptosis or immunogenic cell death to prevent recurrence and metastasis by interacting with intracellular organelles. A large proportion of the existing in-vitro studies of nsPEF on cells also suggests cell necrosis and swelling/blebbing can be induced, but the replicability and potential for other effects on cells suggesting a complicated process which requires further investigation. Therefore, this study investigated the effects of pulse width and intensity of nsPEF on the murine melanoma cells (B16) and normal murine fibroblast cells (L929) through electromagnetic simulation and in-vitro experiments. Through examining the evolution patterns of potential difference and electric fields on the intracellular compartments, the simulation has shown a differential effect of nsPEF on normal and cancerous skin cells, which explains well the results observed in the reported experiments. In addition, the modelling has provided a clear evidence that a few hundreds of ns PEF may have caused a mixed mode of effects, i.e. a ‘cocktail effect’, including cell electroporation and IRE due to an over their threshold voltage induced on the plasma membrane, as well as cell apoptosis and other biological effects caused by its interaction with the intracellular compartments. The in-vitro experiments in the pulse range of the hundreds of nanoseconds showed a possible differential cytotoxicity threshold of electric field intensity between B16 cells and L929 cells.
The intricate anatomy of the eyelid, and the subspecialization trend in pathology made it more difficult for general surgical pathologists to maintain high accuracy across the entire range of diverse eyelid lesions. A lack of access to subspecialty expertise, and misalignment of diagnosis for eye pathology can slow diagnostic speed, resulting in intraorbital and intracranial extension and/or systemic spread which could threaten vision and life. Here, we developed a robust diagnostic deep learning system (DLS) to detect eyelid tumors using digital histopathological sections based on 473,037 pathological patches from 794 haematoxylin-eosin [H&E] stained whole slide images (WSIs) from two hospitals. This 9-class diagnosis task included top five benign and four malignant eyelid tumors. We first proposed a cascade-network instead of single network, to use the features from both histologic pattern and cellular atypia in a holistic pattern. Our model utilizing cascade-network design achieved 1.0 and 0.946 accuracy in the test and independent test set, respectively, for benign and malignant binary classification; without cascade-network design, accuracy was 0.957 and 0.887, respectively. For multiple classification of individual disease, the DLS with cascade-network design achieved 0.989 and 0.931 overall accuracy for WSI diagnosis in the test set (9-class) and independent test set (8-class) respectively, while without cascade design achieved 0.774 and 0.662. In conclusion, this DLS, using cascade-network design, can automatically detect malignancy in histopathologic slides of common eyelid tumors with a high degree of accuracy, which also has potential to augment histopathological diagnosis for a wide range of tumors.
Abslrad-with the integrated circuit (IC) trending toward deep sub-micron (DSM) technology, the crosstalk problem of interconnection has become the bottle-neck in the IC design. This paper presents a new time-efficient method for the estimation of crosstalk, which considers the effect of coupling capacitances and inductors completely. The results of experiment show that the average error is about 5% and the maximum error is less than 11%.Also, the method we proposed is more efficient compared with SPICE.
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