Porous Matrix Stiffness Modulates Response to Targeted Therapy in Breast Carcinoma.

Porous matrix stiffness modulates response to targeted therapy. Poroelastic behavior within porous matrix may modulate the molecule events in cell-matrix and cell-cell interaction like the complex formation of human epidermal growth factor receptor-2 (HER2)-Src-α6ß4 integrin, influencing the targeted therapy with lapatinib.

Artificial Intelligence-Assisted Bone Age Assessment to Improve the Accuracy and Consistency of Physicians With Different Levels of Experience.

Background: The accuracy and consistency of bone age assessments (BAA) using standard methods can vary with physicians' level of experience. Methods: To assess the impact of information from an artificial intelligence (AI) deep learning convolutional neural network (CNN) model on BAA, specialists with different levels of experience (junior, mid-level, and senior) assessed radiographs from 316 children aged 4-18 years that had been randomly divided into two equal sets-group A and group B. Bone age (BA) was assessed independently by each specialist without additional information (group A) and with information from the model (group B). With the mean assessment of four experts as the reference standard, mean absolute error (MAE), and intraclass correlation coefficient (ICC) were calculated to evaluate accuracy and consistency. Individual assessments of 13 bones (radius, ulna, and short bones) were also compared between group A and group B with the rank-sum test. Results: The accuracies of senior, mid-level, and junior physicians were significantly better (all P < 0.001) with AI assistance (MAEs 0.325, 0.344, and 0.370, respectively) than without AI assistance (MAEs 0.403, 0.469, and 0.755, respectively). Moreover, for senior, mid-level, and junior physicians, consistency was significantly higher (all P < 0.001) with AI assistance (ICCs 0.996, 0.996, and 0.992, respectively) than without AI assistance (ICCs 0.987, 0.989, and 0.941, respectively). For all levels of experience, accuracy with AI assistance was significantly better than accuracy without AI assistance for assessments of the first and fifth proximal phalanges. Conclusions: Information from an AI model improves both the accuracy and the consistency of bone age assessments for physicians of all levels of experience. The first and fifth proximal phalanges are difficult to assess, and they should be paid more attention.

Knowledge transfer between brain lesion segmentation tasks with increased model capacity.

Convolutional neural networks (CNNs) have become an increasingly popular tool for brain lesion segmentation in recent years due to its accuracy and efficiency. However, CNN-based brain lesion segmentation generally requires a large amount of annotated training data, which can be costly for medical imaging. In many scenarios, only a few annotations of brain lesions are available. One common strategy to address the issue of limited annotated data is to transfer knowledge from a different yet relevant source task, where training data is abundant, to the target task of interest. Typically, a model can be pretrained for the source task, and then fine-tuned with the scarce training data associated with the target task. However, classic fine-tuning tends to make small modifications to the pretrained model, which could hinder its adaptation to the target task. Fine-tuning with increased model capacity has been shown to alleviate this negative impact in image classification problems. In this work, we extend the strategy of fine-tuning with increased model capacity to the problem of brain lesion segmentation, and then develop an advanced version that is better suitable for segmentation problems. First, we propose a vanilla strategy of increasing the capacity, where, like in the classification problem, the width of the network is augmented during fine-tuning. Second, because unlike image classification, in segmentation problems each voxel is associated with a labeling result, we further develop a spatially adaptive augmentation strategy during fine-tuning. Specifically, in addition to the vanilla width augmentation, we incorporate a module that computes a spatial map of the contribution of the information given by width augmentation in the final segmentation. For demonstration, the proposed method was applied to ischemic stroke lesion segmentation, where a model pretrained for brain tumor segmentation was fine-tuned, and the experimental results indicate the benefit of our method.

Multifunctional "smart" particles engineered from live immunocytes: toward capture and release of cancer cells.

Multifunctional "smart" particles with magnetic, topographic, cell-targeting, and stimulus-responsive properties are obtained using a "live template" strategy. These particles exhibit improved efficiency in capture of target cancer cells by introducing synergistic topographic interactions, and enable the release of captured cells with high viability via reduction of disulfide bonds. Diverse multifunctional particles can be designed using the "live template" strategy.

Rapid fibroblast activation in mammalian cells induced by silicon nanowire arrays.

Activated tumor-associated fibroblasts (TAFs) with abundant fibroblast activation protein (FAP) expression attract tremendous attention in tumor progression studies. In this work, we report a rapid 24 h FAP activation method for fibroblasts using silicon nanowires (SiNWs) as culture substrates instead of growth factors or chemokines. In contrast with cells cultured on flat silicon which rarely express FAP, SiNW cultivated cells exhibit FAP levels similar to those found in cancerous tissue. We demonstrated that activated cells grown on SiNWs maintain their viability and proliferation in a time-dependent manner. Moreover, environmental scanning electron microscopy (ESEM) and focused ion beam and scanning electron microscopy (FIB-SEM) analysis clearly revealed that activated cells on SiNWs adapt to the structure of their substrates by filling inter-wire cavities via filopodia in contrast to cells cultured on flat silicon which spread freely. We further illustrated that the expression of FAP was rarely detected in activated cells after being re-cultured in Petri dishes, suggesting that the unique structure of SiNWs may have a certain influence on FAP activation.