Nanospikes functionalization as a universal strategy to disperse hydrophilic particles in non-polar media.

Dispersion of hydrophilic particles in non-polar media has many important applications yet remains difficult. Surfactant or amphiphilic functionalization was conventionally applied to disperse particles but is highly dependent on the particle/solvent system and may induce unfavorable effects and impact particle hydrophilic nature. Recently 2 µm size polystyrene microbeads coated with ZnO nanospikes have been reported to display anomalous dispersity in phobic media without using surfactant or amphiphilic functionalization. However, due to the lack of understanding whether this phenomenon was applicable to a wider range of conditions, little application has been derived from it. Here the anomalous dispersity phenomenons of hydrophilic microparticles covered with nanospikes were systematically assessed at various conditions including different particle sizes, material compositions, particle morphologies, solvent hydrophobicities, and surface polar groups. Microparticles were functionalized with nanospikes through hydrothermal route, followed by dispersity test in hydrophobic media. The results suggest nanospikes consistently prevent particle aggregation in various particle or solvent conditions, indicating the universal applicability of the anomalous dispersion phenomenons. This work provides insight on the anomalous dispersity of hydrophilic particles in various systems and offers potential application to use this method for surfactant-free dispersions.

Exercise improves cardiac function and attenuates myocardial inflammation and apoptosis by regulating APJ/STAT3 in mice with stroke.

Stroke can induce cardiac dysfunction without a primary cardiac disease. Exercise can promote the overall rehabilitation of stroke patients and be beneficial for all kinds of heart diseases. However, the mechanisms underlying the protective effects of exercise in stroke-induced cardiac dysfunction are poorly understood. Hence, we aimed to distinguish the different effects of acute and long-term exercise and further study the mechanism of protection against cardiomyopathy caused by stroke. Mice underwent a single acute session or long-term exercise for 30 days, followed by middle cerebral artery occlusion surgery. The expression of apoptosis-related proteins and proinflammatory factors in the heart was evaluated. Then, overexpression of apelin peptide jejunum (APJ) transfected adeno-associated virus type 9 (AAV9) and inhibition of signal transducer and activator of transcription 3 (STAT3) by Stattic were used in stroke mice or hypoxic cardiomyocytes. ML221 were used to inhibit APJ activity in exercise mouse. Thereafter, changes in apoptotic and proinflammatory factors were evaluated. The results demonstrated that chronic exercise prevented myocardial inflammation, apoptosis and cardiac dysfunction after stroke. However, acute exercise did not have similar effects. Exercise maintained the levels of APJ expression and decreased phosphorylated-STAT3 (p-STAT3) activation to protect cardiomyocytes. Moreover, APJ overexpression promoted cardiomyocyte survival and reduced p-STAT3 levels. STAT3 inhibition also reduced apoptosis and proinflammatory factors in mice hearts. Conversely, the protective effect of exercise was eliminated by APJ inhibition. This study showed that exercise can maintain APJ expression and inhibit p-STAT3, thus, conferring protection against myocardial inflammation and apoptosis induced by stroke.

Index-Rotated Fast Ultrasound Imaging of Cortical Bone Based on Predicted Velocity Model.

Due to the significant acoustic impedance contrast at cortical boundaries, highly inside attenuation, and the unknown sound velocity distribution, accurate ultrasound cortical bone imaging remains a challenge, especially for the traditional pulse-echo modalities using unique sound velocity. Moreover, the large amounts of data recorded by multielement probe results in a relatively time-consuming reconstruction process. To overcome these limitations, this article proposed an index-rotated fast ultrasound imaging method based on predicted velocity model (IR-FUI-VP) for cortical cross section ultrasound tomography (UST) imaging, utilizing ray-tracing synthetic aperture (RTSA). In virtue of ring probe, the sound velocity model was predicted in advance using bent-ray inversion (BRI). With the predicted velocity model, index-rotated fast ultrasound imaging (IR-FUI) was further applied to image the cortical cross sections in the sectors corresponding to the dynamic apertures (DAs) and ring center. The final result was merged by all sector images. One cortical bone phantom and two ex vivo bovine femurs were utilized to demonstrate the performance of the proposed method. Compared to the conventional synthetic aperture (SA) imaging, the method can not only accurately image the outer cortical boundary but also precisely reconstruct the inner cortical surface. The mean relative errors of the predicted sound velocity in the region of interest (ROI) were all smaller than 7%, and the mean errors of cortical thickness are all less than 0.31 mm. The reconstructed images of bovine femurs were in good agreement with the reference images scanned by micro-computed tomography ( µ CT) with respect to the morphology and thickness. The speed of IR-FUI is about 3.73 times faster than the traditional SA. It is proved that the proposed IR-FUI-VP-based UST is an effective way for fast and accurate cortical bone imaging.

Meta-Learning Analysis of Ultrasonic Guided Waves for Coated Cortical Bone Characterization.

Due to its sensitivity to geometrical and mechanical properties of waveguides, ultrasonic guided waves (UGWs) propagating in cortical bones play an important role in the early diagnosis of osteoporosis. However, as impacts of overlaid soft tissues are complex, it remains challenging to retrieve bone properties accurately. Meta-learning, i.e., learning to learn, is capable of extracting transferable features from a few data and, thus, suitable to capture potential characteristics, leading to accurate bone assessment. In this study, we investigate the feasibility to apply the multichannel identification neural network (MCINN) to estimate the thickness and bulk velocities of coated cortical bone. It minimizes the effects of soft tissue by extracting specific features of UGW, which shares the same cortical properties, while the overlaid soft tissue varies. Distinguished from most reported methods, this work moves from the hand-design inversion scheme to data-driven assessment by automatically mapping features of UGW to the space of bone properties. The MCINN was trained and validated using simulated datasets produced by the finite-difference time-domain (FDTD) method and then applied to experimental data obtained from cortical bovine bone plates overlaid with soft tissue mimics. A good match was found between experimental trajectories and theoretical dispersion curves. The results demonstrated that the proposed method was feasible to assess the thickness of coated cortical bone plates.

Spectrogram decomposition of ultrasonic guided waves for cortical thickness assessment using basis learning.

Due to its multimode and dispersive nature, ultrasonic guided waves (UGWs) usually consist of overlapped wave packets, which challenge accurate bone characterization. To overcome this obstacle, a classic idea is to separate individual modes and to extract the corresponding dispersion curves. Reported single-channel mode separation algorithms mainly focused on offering a time-frequency representation (TFR) where the energy distributions of individual modes were apart from each other. However, such approaches are still limited to identifying the modes without significant overlapping in time-frequency domain. In this study, a spectrogram decomposition technique was developed based on a combination strategy of generalized separable nonnegative matrix factorization (GS-NMF) and adaptive basis learning, towards the automatic mode extraction under severe overlapping and low signal-to-noise ratio (SNR). The extracted modes were further used for cortical thickness estimation. The method was verified using broadband simulated and experimental datasets. Experiments were conducted on a bone-mimicking plate and bovine cortical bone plates. For simulated data, the relative errors between extracted and theoretical dispersion curves are 1.33% (SNR = ∞), 1.43% (SNR = 10 dB) and 0.88% (SNR = 5 dB). The root-mean-square errors of the estimated thickness for 3.10 mm-thick bone-mimicking plate, 3.83 mm- and 4.00 mm-thick bovine cortical bone plates are 0.039 mm, 0.049 mm, and 0.052 mm, respectively. It is demonstrated that the proposed method is capable of separating multimodal UGWs even under significantly overlapping and low SNR conditions, further facilitating the UGW-based cortical thickness assessment.

Fourier-Domain Ultrasonic Imaging of Cortical Bone Based on Velocity Distribution Inversion.

There is a significant acoustic impedance contrast between the cortical bone and the surrounding soft tissue, resulting in difficulty for ultrasound penetration into bone tissue with high frequency. It is challenging for the conventional pulse-echo modalities to give accurate cortical bone images using uniform sound velocity model. To overcome these limitations, an ultrasound imaging method called full-matrix Fourier-domain synthetic aperture based on velocity inversion (FM-FDSA-VI) was developed to provide accurate cortical bone images. The dual linear arrays were located on the upper and lower sides of the imaging region. After full-matrix acquisition with two identical linear array probes facing each other, travel-time inversion was used to estimate the velocity distribution in advance. Then, full-matrix Fourier-domain synthetic aperture (FM-FDSA) imaging based on the estimated velocity model was applied twice to image the cortical bone, utilizing the data acquired from top and bottom linear array, respectively. Finally, to further improve the image quality, the two images were merged to give the ultimate result. The performance of the method was verified by two simulated models and two bone phantoms (i.e., regular and irregular hollow bone phantom). The mean relative errors of estimated sound velocity in the region-of-interest (ROI) are all below 12%, and the mean errors of cortical section thickness are all less than 0.3 mm. Compared to the conventional synthetic aperture (SA) imaging, the FM-FDSA-VI method is able to accurately image cortical bone with respect to the structure. Moreover, the result of irregular bone phantom was close to the image scanned by microcomputed tomography ( µ CT) in terms of macro geometry and thickness. It is demonstrated that the proposed FM-FDSA-VI method is an efficient way for cortical bone ultrasonic imaging.

Comparisons of serum total IgE, IgG, and IgG1 levels in patients with and without echinococcosis-induced anaphylactic shock.

We investigated serum total immunoglobulin E (IgE), IgG, and IgG1 levels in patients with and without echinococcosis-induced anaphylactic shock. This was a case-control study of 11 patients with echinococcosis-induced anaphylactic shock and 22 echinococcosis patients with cyst rupture but without anaphylactic shock. Blood was collected before surgery (T0), at the time of cyst rupture (T1), and shock (Tx), 1 h (T2), 1 day (T3), and 1 week (T4) after cyst rupture. Serum IgE, IgG, and IgG1 were determined by enzyme-linked immunosorbent assay. Serum IgE, IgG, and IgG1 levels were significantly higher in patients who developed anaphylactic shock at all time points. Increased pre-surgical IgG and IgG1 levels were identified to be a significant risk factors for developing anaphylactic shock. The results showed that a serum IgG concentration of 312.25 µg/mL could be used as a cut-off point to predict whether an echinococcosis patient would develop anaphylactic shock.