Alzheimer's disease (AD) is a progressive neurodegenerative disease manifested by cognitive impairment. As a unique approach to open the blood-brain barrier (BBB) noninvasively and temporarily, a growing number of studies showed that low-intensity focused ultrasound in combination with microbubbles (FUS/MB), in the absence of therapeutic agents, is capable of ameliorating amyloid or tau pathology, concurrent with improving memory deficits of AD animal models. However, the effects of FUS/MB on both the two pathologies simultaneously, as well as the memory behaviors, have not been reported so far.

Paclitaxel liposomes (PTX-LIPO) are a clinically promising antineoplastic drug formulation for the treatment of various extracranial cancers, excluding glioblastoma. A main reason for this is the presence of the blood–brain barrier (BBB) or blood–tumor barrier (BTB), preventing liposomal drugs from crossing at a therapeutically meaningful level. Focused ultrasound (FUS) in conjunction with microbubbles (MBs) has been suggested in many studies to be an effective approach to increase the BBB or BTB permeability. In this study, we investigated the feasibility of enhancing the delivery of PTX-LIPO in intracranial glioblastoma-bearing nude mice using pulsed low-intensity FUS exposure in the presence of MBs. Our results showed that the delivery efficiency of PTX-LIPO could be effectively improved in terms of the penetration of both the BBB in vitro and BTB in vivo by pulsed FUS sonication with a 10 ms pulse length and 1 Hz pulse repetition frequency at 0.64 MPa peak-rarefactional pressure in the presence of MBs. Quantitative analysis showed that a 2-fold higher drug concentration had accumulated in the glioblastoma 3 h after FUS treatment, with 7.20±1.18 µg PTX per g glioma tissue. Longitudinal magnetic resonance imaging analysis illustrated that the intracranial glioblastoma progression in nude mice treated with PTX-LIPO delivered via FUS with MBs was suppressed consistently for 4 weeks compared to the untreated group. The medium survival time of these tumor-bearing nude mice was significantly prolonged by 20.8%, compared to the untreated nude mice. Immunohistochemical analysis further confirmed the antiproliferation effect and cell apoptosis induction. Our study demonstrated that noninvasive low-intensity FUS with MBs can be used as an effective approach to deliver PTX-LIPO in order to improve their chemotherapy efficacy toward glioblastoma.

In this study we simultaneously collected ultrasound images, EMG, MMG from the rectus femoris (RF) muscle and torque signal from the leg extensor muscle group of nine male subjects (mean±SD, age=30.7±.4.9 years; body weight=67.0±8.4kg; height=170.4±6.9cm) during step, ramp increasing, and decreasing at three different rates (50%, 25% and 17% MVC/s). The muscle architectural parameters extracted from ultrasound imaging, which reflect muscle contractions, were defined as sonomyography (SMG) in this study. The cross-sectional area (CSA) and aspect ratio between muscle width and thickness (width/thickness) were extracted from ultrasound images. The results showed that the CSA of RF muscles decreased by 7.25±4.07% when muscle torque output changed from 0% to 90% MVC, and the aspect ratio decreased by 41.66±7.96%. The muscle contraction level and SMG data were strongly correlated (R(2)=0.961, P=0.003, for CSA and R(2)=0.999, P<0.001, for width/thickness ratio). The data indicated a significant difference (P<0.05) in percentage changes for CSA and aspect ratio among step, ramp increasing, and decreasing contractions. The normalized EMG RMS in ramp increasing was 8.25±4.00% higher than step (P=0.002). The normalized MMG RMS of step contraction was significantly lower than ramp increasing and decreasing, with averaged differences of 12.22±3.37% (P=0.001) and 12.06±3.37% (P=0.001), respectively. The results of this study demonstrated that the CSA and aspect ratio, i.e., SMG signals, can provide useful information about muscle contractions. They may therefore complement EMG and MMG for studying muscle activation strategies under different conditions.

Introduction: The pathological grading of pancreatic neuroendocrine neoplasms (pNENs) is an independent predictor of survival and indicator for treatment. Deep learning (DL) with a convolutional neural network (CNN) may improve the preoperative prediction of pNEN grading. Methods: Ninety-three pNEN patients with preoperative contrast-enhanced computed tomography (CECT) from Hospital I were retrospectively enrolled. A CNN-based DL algorithm was applied to the CECT images to obtain 3 models (arterial, venous, and arterial/venous models), the performances of which were evaluated via an eightfold cross-validation technique. The CECT images of the optimal phase were used for comparing the DL and traditional machine learning (TML) models in predicting the pathological grading of pNENs. The performance of radiologists by using qualitative and quantitative computed tomography findings was also evaluated. The best DL model from the eightfold cross-validation was evaluated on an independent testing set of 19 patients from Hospital II who were scanned on a different scanner. The Kaplan-Meier (KM) analysis was employed for survival analysis. Results: The area under the curve (AUC; 0.81) of arterial phase in validation set was significantly higher than those of venous (AUC 0.57, p = 0.03) and arterial/venous phase (AUC 0.70, p = 0.03) in predicting the pathological grading of pNENs. Compared with the TML models, the DL model gave a higher (although insignificantly) AUC. The highest OR was achieved for the p ratio <0.9, the AUC and accuracy for diagnosing G3 pNENs were 0.80 and 79.1% respectively. The DL algorithm achieved an AUC of 0.82 and an accuracy of 88.1% for the independent testing set. The KM analysis showed a statistical significant difference between the predicted G1/2 and G3 groups in the progression-free survival (p = 0.001) and overall survival (p < 0.001). Conclusion: The CNN-based DL method showed a relatively robust performance in predicting pathological grading of pNENs from CECT images.

Recently, emerging evidence has demonstrated that cavitation actually creates important bidirectional channels on biological barriers for both intratumoral drug delivery and extratumoral biomarker release. To promote the barrier-breaking effects of cavitation for both therapy and diagnosis, we first reviewed recent technical advances of ultrasound and its contrast agents (microbubbles, nanodroplets, and gas-stabilizing nanoparticles) and then reported the newly-revealed cavitation physical details. In particular, we summarized five types of cellular responses of cavitation in breaking the plasma membrane (membrane retraction, sonoporation, endocytosis/exocytosis, blebbing and apoptosis) and compared the vascular cavitation effects of three different types of ultrasound contrast agents in breaking the blood-tumor barrier and tumor microenvironment. Moreover, we highlighted the current achievements of the barrier-breaking effects of cavitation in mediating drug delivery and biomarker release. We emphasized that the precise induction of a specific cavitation effect for barrier-breaking was still challenged by the complex combination of multiple acoustic and non-acoustic cavitation parameters. Therefore, we provided the cutting-edge in-situ cavitation imaging and feedback control methods and suggested the development of an international cavitation quantification standard for the clinical guidance of cavitation-mediated barrier-breaking effects.