Ultrasound-driven exercise training ameliorates degeneration of ultrasonic responses in Caenorhabditis elegans.

The inevitability of age-related degeneration makes research on degradation mitigation attractive to humans, while exercise is considered an effective means due to its powerful impact on life and health. Caenorhabditis elegans is a model animal with a short life cycle and is widely used in health and aging studies. In this work, ultrasonic stimuli in the form of surface acoustic waves (SAWs) were used to induce behavioral activities in worms. As the worms grew, ultrasound-elicited behavioral responses started to decrease in the early adulthood stage. However, this situation was significantly ameliorated when ultrasonic training sessions at an effective acoustic pressure of 1.1 MPa were performed four times per day for 5 or 7 days, while ultrasonic responses in trained nematodes were stronger than those in untrained ones. These results suggest that long-term ultrasonic training might positively intervene in aging-related degeneration. Besides, it was found that exercise driven by long-term ultrasonic training had insignificant effects on the lifespan of worms. A preliminary exploration of the neural mechanisms underlying the sensation of SAWs was also conducted. The results show that, apart from touch receptor neurons (TRNs), polymodal nociceptors FLP and PVD neurons may also be involved in the perception of ultrasound in C. elegans. The results of this study may inspire related studies on other animals or humans.

C. elegans: Sensing the low-frequency profile of amplitude-modulated ultrasound.

Several research groups have demonstrated that C. elegans can respond to pulsed ultrasound stimuli, and elucidating the underlying mechanisms is necessary to develop ultrasound neuromodulation. Here, amplitude-modulated (AM) ultrasound is applied to C. elegans, and its behavioral responses are investigated in detail. By loading surface acoustic waves (SAWs) onto free-moving worms on an agar surface, a carrier wave with a frequency of 8.80 MHz is selected. The signal is modulated by a rectangular or sinusoidal profile. It is demonstrated that sinusoidal modulation can produce similar responses in worms to rectangular modulation, with the strongest responses occurring at modulation frequencies of around 1.00 kHz. Meanwhile, the behavioral response is relatively weak when the ultrasonic signal is unmodulated, that is, when only the carrier wave is applied. At modulation frequencies other than 100.00 Hz to 10.00 kHz, the worms respond weakly, but when a second modulation frequency of 1.00 kHz is introduced, an improvement in response can be observed. These results suggest that C. elegans may sense the low-frequency envelope and respond to amplitude-modulated ultrasonic stimuli like an amplitude demodulator. MEC-4, an ion channel for touch sensing, is involved in the behavioral response of C. elegans to ultrasound in the present setup.

Modelling of SAW-PDMS acoustofluidics: physical fields and particle motions influenced by different descriptions of the PDMS domain.

In modelling acoustofluidic chips actuated by surface acoustic waves (SAWs) and using polydimethylsilane (PDMS) as a channel material, reduced models are often adopted to describe the acoustic behaviors of PDMS. Here, based on a standing SAW (SSAW) acoustophoresis chip, we compared three different descriptions of a PDMS chamber and looked into in-chamber physical fields and ensuing particle motion processes through finite element (FE) simulations. Specifically, the PDMS domain was considered as an elastic solid material, a non-flow fluid, and a lossy wall, respectively. The major findings include: (a) the shear waves that propagated in a solid PDMS wall did not influence the in-chamber pressure and ARF fields severely, but induced an observable difference in the acoustic streaming (AS) patterns, and distinctly changed the trajectories of polystyrene particles, especially those whose radii were below 1.5 µm; and (b) the equivalent damping coefficients were linearly dependent on the SAW frequency, characterized by a fixed loss per wavelength, indicating the wave leakage at the interface being the main source of the transmission loss of SAWs. Meanwhile, the acoustic radiation force (ARF) can be overestimated when describing PDMS as a lossy wall, especially at the bottom corners of the chamber, which could cause inaccurate predictions of the motion of big particles. Based on the damping mechanism, a rough protocol is provided for scaling of pressure fields between different models. Some suggestions for device designs and operations are also given based on the obtained findings.

Prediction of suspicious thyroid nodule using artificial neural network based on radiofrequency ultrasound and conventional ultrasound: A preliminary study.

This study explored the use of backscattered radiofrequency ultrasound signals combined with artificial neural network (ANN) technology to differentiate benign and malignant thyroid nodules, in comparison with conventional ultrasound techniques. The proposed method uses the gray level co-occurrence matrix algorithm and principal component analysis to identify principal characteristics for use as inputs in the ANN. The dataset consisted of 131 ultrasound images, of which 59 were benign and 72 were malignant, as determined by subsequent surgeries. The nodules were divided randomly into training, validation, and testing groups. Receiver operating characteristic curves (ROC) were drawn to compare the diagnostic efficiency of the ANN when applied to radiofrequency and conventional ultrasound images. The sensitivity, specificity, and accuracy of the ANN in predicting malignancy from the radiofrequency ultrasound images were 100, 91.5, and 96.2%, respectively; from conventional ultrasound, the corresponding values were 94.4, 93.2, and 93.9%, respectively. The area under the receiver operating characteristic curve (AUC) was also higher for radiofrequency than conventional ultrasound (AUC = 0.945 vs. 0.917, 95% confidence interval = 0.901-0.998 vs. 0.854-0.979, using a P-value of 0.26). We then classified each nodule into new risk categories according to the output of each sample generated by the proposed method. The malignancy risks in the proposed Categories 3, 4, and 5 were 0, 18.8, and 94.5%, respectively, compared with 0, 55.1, and 88.2% using the American College of Radiology's Thyroid Imaging Reporting and Data System. Thus, this preliminary study initially indicated that the proposed method of using radiofrequency ultrasound and the ANN was more accurate at predicting malignancy and stratifying thyroid nodules than conventional ultrasound methods, thus offering significant potential to reduce the number of unnecessary thyroid biopsies.