Fan Fan

Real-time mechanical monitoring of liquid-to-solid phase transitions is essential in materials science and biomedical diagnostics, yet existing instruments face challenges in continuously and nondestructively tracking the complete phase transition process of small-volume samples. Here we present an instrument for monitoring small-volume liquid-to-solid phase transitions based on magnetically driven droplet resonance. By combining phase-sensitive optical coherence tomography (OCT) detection with magnetic excitation using embedded superparamagnetic nanoparticles, the instrument enables continuous measurement of the resonance frequency throughout the entire transition process of a single 30 μ l droplet. We designed a sidewall-free sample base to confine the sample geometry via surface tension, providing consistent vibrational boundary conditions for cross-phase-state measurements. To mitigate electromagnetic interference-induced mechanical noise in the optical detection path under alternating magnetic fields, a non-metallic optomechanical structure was designed, reducing the displacement noise spectral density to below 3 nm Hz − 1 . The instrument achieves frequency measurement stability of ± 0.4 Hz and ± 0.6 Hz (15 min, standard deviation) for liquid and solid standard samples, respectively. Monitoring of agar gelation and porcine whole blood coagulation demonstrates the instrument’s ability to distinguish distinct phase transition mechanisms. This instrument provides a continuous, non-destructive mechanical monitoring tool for small-volume liquid-to-solid transition research and coagulation function assessment.

Objective: Radial extracorporeal shock wave therapy (rESWT) has been widely used in the treatment of soft tissue disorders. However, the temperature variations induced in soft tissue during rESWT have not yet been systematically quantified. This study aims to quantitatively investigate the pressure and temperature changes within soft tissue during rESWT, thereby providing important information for understanding its potential therapeutic mechanisms. Methods: A finite element model of the rESWT device and soft tissue was established. A thermo-mechanical coupling approach was employed to calculate the pressure and temperature fields induced by shock waves in the soft tissue. Furthermore, the maximum and minimum pressure values, as well as the maximum temperature value in the soft tissue, were extracted and analyzed. Results: The negative peak pressure generated by the rESWT device was in the MPa range, which could induce cavitation. In contrast, the associated temperature changes were minimal, with the maximum temperature rise in the tissue remaining below 0.01 °C and the temperature change at a depth of 20 mm even less than 0.001 °C. Conclusion: rESWT primarily exerts its therapeutic effects through cavitation induced by the rapidly increasing pressure. Although a single shock produces only a minimal temperature change in the tissue, multiple shocks may lead to energy accumulation. The findings of this study provide important reference information for the evaluation of rESWT devices and the development of clinical treatment protocols.

Assessment of coagulation function is crucial for anticoagulant therapy, surgical procedures, and cardiovascular diseases. Changes in the mechanical properties during coagulation can directly reflect coagulation function. Here, we report a magneto-droplet resonance spectroscopy (MDRS) method to monitor the mechanical property changes of a single drop sample (30 μL) as it transitions from a liquid state to a clot. We utilized a series of low-mass-fraction agarose gel solutions to mimic blood samples with varying coagulation characteristics. We obtained the changes in the resonance frequency of the sample during coagulation and calculated Young's modulus of the coagulated sample using a multi-degree-of-freedom model. The results demonstrate that this method can monitor the whole coagulation process of a single drop sample and effectively distinguish samples with Young's moduli ranging from 0.36 to 2.00 kPa. The MDRS method has the potential to serve as a highly sensitive tool for monitoring the coagulation function of small-sized blood samples.

The loss of speech function following a laryngectomy usually leads to severe physiological and psychological distress for laryngectomees. In clinical practice, most laryngectomees retain intact upper tract articulatory organs, emphasizing the significance of speech rehabilitation that utilizes articulatory motion information to effectively restore speech. This study proposed a deep learning-based end-to-end method for speech reconstruction using ultrasound tongue images. Initially, ultrasound tongue images and speech data were collected simultaneously with a designed Mandarin corpus. Subsequently, a speech reconstruction model was built based on adversarial neural networks. The model includes a pretrained feature extractor to process ultrasound images, an upsampling block to generate speech, and discriminators to ensure the similarity and fidelity of the reconstructed speech. Finally, both objective and subjective evaluations were conducted for the reconstructed speech. The reconstructed speech demonstrated high intelligibility in both Mandarin phonemes and tones. The character error rate of phonemes in automatic speech recognition was 0.2544, and tone error rate obtained from dictation tests was 0.1784, respectively. Objective results showed high similarity between the reconstructed and ground truth speech. Subjective perception results also indicated an acceptable level of naturalness. The proposed method demonstrates its capability to reconstruct tonal Mandarin speech from ultrasound tongue images. However, future research should concentrate on specific conditions of laryngectomees, aiming to enhance and optimize model performance. This will be achieved by enlarging training datasets, investigating the impact of ultrasound tongue imaging parameters, and further refining this method.

Objective: Extracorporeal shock wave therapy (ESWT) has been widely used in clinical and rehabilitation fields. However, limited knowledge of shock wave sources constrains its therapeutic efficacy. This study aimed to simulate and analyze the characteristics of shock wave sources generated by the radial extracorporeal shock wave therapy (rESWT) device at different media interfaces. Methods: In this paper, a numerical calculation model including the front portion of the handpiece of an rESWT device and three different media (soft tissue, water, and air) was established using the finite element method, and the dynamic impact process was carried out according to the basic principle of the rESWT apparatus. The projectile speed was set to be 7.11, 12.46, 17.81 and 23.16m/s, respectively. In addition, the waveforms at the geometric center of the applicator surface were extracted, and the temporal and spectral characteristics of the shock wave source were disclosed. Results: The waveform of shock wave generated by the applicator of the rESWT device at soft tissue and water interface were similar at the same projectile speed, but both being different from the waveform at air interface. The absolute positive and negative pressure values at the air interface were three orders smaller than those observed at the soft tissue and water interfaces. The spectral characteristics of the waveforms at different media interfaces were similar, with modulation frequencies of soft tissue, water and air being 4.51 kHz, 3.97 kHz and 4.03 kHz, and carrier frequencies being 78.00 kHz, 76.90 kHz and 77.27 kHz, respectively. At different projectile speeds, there was no variation in the waveform shapes of the same medium, revealing that the projectile speed didn't affect the peak frequency of the shock wave waveform. The projectile speed only affected the amplitude of the shock wave waveform, indicating that the absolute positive and negative pressure at the medium interface increased linearly with the projectile speed. Conclusion: The shock waves produced at various media interfaces displayed changes in their temporal and spectral characteristics, and the results observed in biological soft tissues couldn't be directly substituted with those observed in air or water. The findings could offer crucial insights into the assessment of rESWT devices and the enhancement of clinical shock wave treatment protocols.

Extracorporeal shock wave therapy (ESWT), a non-invasive clinical approach, is widely used in sports rehabilitation, orthopaedics, and aesthetic medicine, whose treatment effects result from the interaction of mechanical impulsive waves with target tissues. Though generally accepted, the nature of waves generated by ESWT is not clearly disclosed when propagating through tissues, resulting in the limitation of the technique. In this work, propagation characteristics of shock waves within the tissue-mimicking phantom are revealed. Our approach involves employing a thin, flexible PVDF sensor embedded within the phantoms to capture dynamic wave pressure signals. These signals facilitate the extraction of pertinent features across various impact pressures and depths. Our results demonstrate that the impulsive wave's rise time approximates 5μs. It produces a positive pressure peak ranging from 0.5 to 8.2 MPa, and a negative pressure peak from -0.19 to -3.28 MPa. Notably, peak amplitudes decrease with increasing depth while maintaining a constant impact pressure. As driving pressure increased, maximum positive pressure increased linearly at the same depth. The implications of our findings are pivotal for the design of pertinent devices, formulation of treatment strategies, and assessment of treatment efficacy. Ultimately, a comprehensive understanding of shock wave propagation will enable more informed and effective applications of ESWT.

Fluid shear stress is an important mediator of vascular permeability, yet the molecular mechanisms underlying the effect of shear on the blood‐brain barrier (BBB) have yet to be clarified in cerebral vasculature despite its importance for brain homeostasis. The goal of this study is to probe components of shear mechanotransduction within the BBB to gain a better understanding of pathologies associated with changes in cerebral perfusion including ischemic stroke. Interrogating the effects of shear stress in vivo is complicated by the complexity of factors in the brain parenchyma and the difficulty associated with modulating blood flow regimes. The in vitro model used in this study is compatible with real‐time measurement of barrier function using a transendothelial electrical resistance as well as immunocytochemistry and dextran permeability assays. These experiments reveal that there is a threshold level of shear stress required for barrier formation and that the composition of the extracellular matrix, specifically the presence of high molecular weight hyaluronan, dictates the flow response. Gene editing to modulate the expression of CD44, a mechanosensitive receptor for hyaluronan, demonstrates that the receptor is required for the endothelial response to shear stress. Manipulation of small GTPase activity reveals CD44 activates Rac1 while inhibiting RhoA activation. Additionally, adducin‐γ localizes to tight junctions in response to shear stress and RhoA inhibition and is required to maintain the barrier. This study identifies specific components of the mechanosensing complex associated with the BBB response to fluid shear stress and, therefore, illuminates potential targets for barrier manipulation in vivo.

Resonant ultrasound spectroscopy (RUS) is an experimental method for measuring the full elastic tensor of a small solid sample from the free resonant frequencies. One important step of the method is to adjust the stiffness coefficients in a model to minimize the difference between computed and measured frequencies. This inverse problem is traditionally solved with the Levenberg-Marquardt (LM) minimization algorithm. The convergence rate and accuracy of the method depend on the initial guess of the elastic tensor that should be relatively close to the sought solution in order to reach the global minimum (as opposed to a local one). To overcome this limitation, we introduce in this paper the particle swarm optimization (PSO) algorithm for its potential in finding a global solution without the need for an accurate initial guess for the model parameters.