An Accelerometer-Based Wearable Patch for Robust Respiratory Rate and Wheeze Detection Using Deep Learning.

Wheezing is a critical indicator of various respiratory conditions, including asthma and chronic obstructive pulmonary disease (COPD). Current diagnosis relies on subjective lung auscultation by physicians. Enabling this capability via a low-profile, objective wearable device for remote patient monitoring (RPM) could offer pre-emptive, accurate respiratory data to patients. With this goal as our aim, we used a low-profile accelerometer-based wearable system that utilizes deep learning to objectively detect wheezing along with respiration rate using a single sensor. The miniature patch consists of a sensitive wideband MEMS accelerometer and low-noise CMOS interface electronics on a small board, which was then placed on nine conventional lung auscultation sites on the patient's chest walls to capture the pulmonary-induced vibrations (PIVs). A deep learning model was developed and compared with a deterministic time-frequency method to objectively detect wheezing in the PIV signals using data captured from 52 diverse patients with respiratory diseases. The wearable accelerometer patch, paired with the deep learning model, demonstrated high fidelity in capturing and detecting respiratory wheezes and patterns across diverse and pertinent settings. It achieved accuracy, sensitivity, and specificity of 95%, 96%, and 93%, respectively, with an AUC of 0.99 on the test set-outperforming the deterministic time-frequency approach. Furthermore, the accelerometer patch outperforms the digital stethoscopes in sound analysis while offering immunity to ambient sounds, which not only enhances data quality and performance for computational wheeze detection by a significant margin but also provides a robust sensor solution that can quantify respiration patterns simultaneously.

Diagnosis of Coexisting Valvular Heart Diseases Using Image-to-Sequence Translation of Contact Microphone Recordings.

OBJECTIVE: Development of a contact microphone-driven screening framework for the diagnosis of coexisting valvular heart diseases (VHDs). METHODS: A sensitive accelerometer contact microphone (ACM) is employed to capture heart-induced acoustic components on the chest wall. Inspired by the human auditory system, ACM recordings are initially transformed into Mel-frequency cepstral coefficients (MFCCs) and their first and second derivatives, resulting in 3-channel images. An image-to-sequence translation network based on the convolution-meets-transformer (CMT) architecture is then applied to each image to find local and global dependencies in images, and predict a 5-digit binary sequence, where each digit corresponds to the presence of a specific type of VHD. The performance of the proposed framework is evaluated on 58 VHD patients and 52 healthy individuals using a 10-fold leave-subject-out cross-validation (10-LSOCV) approach. RESULTS: Statistical analyses suggest an average sensitivity, specificity, accuracy, positive predictive value, and F1 score of 93.28%, 98.07%, 96.87%, 92.97%, and 92.4% respectively, for the detection of coexisting VHDs. Furthermore, areas under the curve (AUC) of 0.99 and 0.98 are respectively reported for the validation and test sets. CONCLUSION: The high performances achieved prove that local and global features of ACM recordings effectively characterize heart murmurs associated with valvular abnormalities. SIGNIFICANCE: Limited access of primary care physicians to echocardiography machines has resulted in a low sensitivity of 44% when using a stethoscope for the identification of heart murmurs. The proposed framework provides accurate decision-making on the presence of VHDs, thus reducing the number of undetected VHD patients in primary care settings.

Multi-coefficient eigenmode operation-breaking through 10°/h open-loop bias instability in wideband aluminum nitride piezoelectric BAW gyroscopes.

In this paper, a modification to the eigenmode operation of resonant gyroscopes is introduced. The multi-coefficient eigenmode operation can improve cross-mode isolation due to electrode misalignments and imperfections, which is one of the causes of residual quadrature errors in conventional eigenmode operations. A 1400 µm annulus aluminum nitride (AlN) on a silicon bulk acoustic wave (BAW) resonator with gyroscopic in-plane bending modes at 2.98 MHz achieves a nearly 60 dB cross-mode isolation when operated as a gyroscope using a multi-coefficient eigenmode architecture. The as-born frequency mismatches in multiple devices are compensated by physical laser trimming. The demonstrated AlN piezoelectric BAW gyroscope shows a large open-loop bandwidth of 150 Hz and a high scale factor of 9.5 nA/°/s on a test board with a vacuum chamber. The measured angle random walk is 0.145°/√h, and the bias instability is 8.6°/h, showing significant improvement compared to the previous eigenmode AlN BAW gyroscope. The results from this paper prove that with multi-coefficient eigenmode operations, piezoelectric AlN BAW gyroscopes can achieve a noise performance comparable to that of their capacitive counterpart while having the unique advantage of a large open-loop bandwidth and not requiring large DC polarization voltages.

Diagnosis of Peripheral Artery Disease Using Backflow Abnormalities in Proximal Recordings of Accelerometer Contact Microphone (ACM).

OBJECTIVE: The development of an accurate, non-invasive method for the diagnosis of peripheral artery disease (PAD) from accelerometer contact microphone (ACM) recordings of the cardiac system. METHODS: Mel frequency cepstral coefficients (MFCCs) are initially extracted from ACM recordings. The extracted MFCCs are then used to fine-tune a pre-trained ResNet50 network whose middle layers provide streams of high-level-of-abstraction coefficients (HLACs) which could provide information on blood pressure backflow caused by arterial obstructions in PAD patients. A vision transformer is finally integrated with the feature extraction layer to detect PAD, and stratify the severity level. This architecture is coined multi-stream-powered vision transformer (MSPViT). The performance of MSPViT is evaluated on 74 PAD and 21 healthy subjects. RESULTS: Sensitivity, specificity, F1 score, and area under the curve (AUC) of 99.45%, 98.21%, 99.37%, and 0.99, respectively, are reported for the binary classification which ensures accurate detection of PAD. Furthermore, MSPViT suggests average sensitivity, specificity, F1 score, and AUC of 96.66%, 97.34%, 96.29%, and 0.96, respectively, for the classification of subjects into healthy, mild-PAD, and severe-PAD classes. The silhouette score is calculated to assess the separability of clusters formed for classes in the penultimate layer of MSPViT. An average silhouette score of 0.66 and 0.81 demonstrate excellent cluster separability in PAD detection and severity classification, respectively. CONCLUSION: The achieved performance suggests that the proximal ACM-driven framework can replace state-of-the-art techniques for PAD detection. SIGNIFICANCE: This study presents a fundamental step towards prompt and accurate diagnosis of PAD and stratification of its severity level.

Detection of pathological mechano-acoustic signatures using precision accelerometer contact microphones in patients with pulmonary disorders.

Monitoring pathological mechano-acoustic signals emanating from the lungs is critical for timely and cost-effective healthcare delivery. Adventitious lung sounds including crackles, wheezes, rhonchi, bronchial breath sounds, stridor or pleural rub and abnormal breathing patterns function as essential clinical biomarkers for the early identification, accurate diagnosis and monitoring of pulmonary disorders. Here, we present a wearable sensor module comprising of a hermetically encapsulated, high precision accelerometer contact microphone (ACM) which enables both episodic and longitudinal assessment of lung sounds, breathing patterns and respiratory rates using a single integrated sensor. This enhanced ACM sensor leverages a nano-gap transduction mechanism to achieve high sensitivity to weak high frequency vibrations occurring on the surface of the skin due to underlying lung pathologies. The performance of the ACM sensor was compared to recordings from a state-of-art digital stethoscope, and the efficacy of the developed system is demonstrated by conducting an exploratory research study aimed at recording pathological mechano-acoustic signals from hospitalized patients with a chronic obstructive pulmonary disease (COPD) exacerbation, pneumonia, and acute decompensated heart failure. This unobtrusive wearable system can enable both episodic and longitudinal evaluation of lung sounds that allow for the early detection and/or ongoing monitoring of pulmonary disease.

Long noncoding RNA GAS5 interacts and suppresses androgen receptor activity in prostate cancer cells.

The androgen receptor (AR) plays an important role in the progression of prostate cancer and is the most important therapeutic target. However, androgen deprivation therapy will finally lead patients to progress to castration-resistant prostate cancer (CRPC). Here, we confirmed that GAS5, a long noncoding RNA, could interact and suppress AR transactivation in CRPC C4-2 cells. Knockdown GAS5 by short hairpin RNA would enhance the transcription of AR via promote AR recruitment to the promoter of its downstream target genes. Functionally, GAS5 overexpression inhibits cell proliferation partially through inhibiting AR transactivation in C4-2 cells. Moreover, knocking down GAS5 protects C4-2 cells from the docetaxel-induced cell apoptosis. In return, the suppressed AR was found to downregulate the GAS5 expression, which forms a feedback loop resulted in AR high transcription activity in CRPC. Collectively, our findings revealed the important role of GAS5 in AR axis activity regulation and CRPC progression. Targeting GAS5 to intervene the feedback loop might be a new potential therapeutic approach for the patients at CRPC stage.

HOTAIR expands the population of prostatic cancer stem-like cells and causes Docetaxel resistance via activating STAT3 signaling.

Prostatic cancer stem-like cells (PCSLCs) play an essential role in PCa development. Accumulating evidence suggests that androgen deprivation therapy (ADT) or chemotherapy using docetaxel could expand the population of PCSLCs. Therefore, understanding the underlying mechanisms responsible for PCSLCs expansion has broadly scientific interest. Here, our results revealed that lncRNA HOTAIR could increase PCSLCs population via activating STAT3 signaling. Mechanistically, HOTAIR functioned as miR-590-5p sponge and prevented it from targeting the 3'UTR of IL-10, one upstream molecule of STAT3 signaling, leading to IL-10 upregulation and STAT3 activation. We also found that HOTAIR was required and sufficient to cause Docetaxel resistance (DocR) in C4-2 PCa cells. Moreover, our in vivo animal study also confirmed that Du145-HOTAIR mice had a faster tumor growth rate and a poorer survival rate compared to control cohorts. Our data build compelling rationale to target HOTAIR for the depletion of PCSLCs and alleviation of Docetaxel resistance.

Low motional impedance distributed Lamé mode resonators for high frequency timing applications.

This paper presents a novel high-Q silicon distributed Lamé mode resonator (DLR) for VHF timing reference applications. The DLR employs the nature of shear wave propagation to enable a cascade of small square Lamé modes in beam or frame configurations with increased transduction area. Combined with high efficiency nano-gap capacitive transduction, it enables low motional impedances while scaling the frequency to VHF range. The DLR designs are robust against common process variations and demonstrate high manufacturability across different silicon substrates and process specifications. Fabricated DLRs in beam and frame configurations demonstrate high performance scalability with high Q-factors ranging from 50 to 250 k, motional impedances <1 kΩ, and high-temperature frequency turnover points >90 °C in the VHF range, and are fabricated using a wafer-level-packaged HARPSS process. Packaged devices show excellent robustness against temperature cycling, device thinning, and aging effects, which makes them a great candidate for stable high frequency references in size-sensitive and power-sensitive 5 G and other IoT applications.

Monocrystalline Silicon Carbide Disk Resonators on Phononic Crystals with Ultra-Low Dissipation Bulk Acoustic Wave Modes.

Micromechanical resonators with ultra-low energy dissipation are essential for a wide range of applications, such as navigation in GPS-denied environments. Routinely implemented in silicon (Si), their energy dissipation often reaches the quantum limits of Si, which can be surpassed by using materials with lower intrinsic loss. This paper explores dissipation limits in 4H monocrystalline silicon carbide-on-insulator (4H-SiCOI) mechanical resonators fabricated at wafer-level, and reports on ultra-high quality-factors (Q) in gyroscopic-mode disk resonators. The SiC disk resonators are anchored upon an acoustically-engineered Si substrate containing a phononic crystal which suppresses anchor loss and promises QANCHOR near 1 Billion by design. Operating deep in the adiabatic regime, the bulk acoustic wave (BAW) modes of solid SiC disks are mostly free of bulk thermoelastic damping. Capacitively-transduced SiC BAW disk resonators consistently display gyroscopic m = 3 modes with Q-factors above 2 Million (M) at 6.29 MHz, limited by surface TED due to microscale roughness along the disk sidewalls. The surface TED limit is revealed by optical measurements on a SiC disk, with nanoscale smooth sidewalls, exhibiting Q = 18 M at 5.3 MHz, corresponding to f · Q = 9 · 1013 Hz, a 5-fold improvement over the Akhiezer limit of Si. Our results pave the path for integrated SiC resonators and resonant gyroscopes with Q-factors beyond the reach of Si.

Loss of KMT2D induces prostate cancer ROS-mediated DNA damage by suppressing the enhancer activity and DNA binding of antioxidant transcription factor FOXO3.

Histone methyltransferase KMT2D has diverse functions and distinct mechanisms in different cancers. Although we have previously found KMT2D serves as an oncogene that promotes tumor growth and metastasis in prostate cancer (PCa), the functions and mechanisms of KMT2D are complicated and most remain undefined. Here, the function of KMT2D regarding DNA damage in PCa and the underlying mechanisms of KMT2D in epigenetic regulation were explored in a series of studies. Knockdown of KMT2D sensitized cells to DNA damage through the disturbance of antioxidative gene expression and increased levels of intracellular reactive oxygen species, which led to cell apoptosis and senescence. The loss of KMT2D reduced the abundance of enhancer activity markers H3K4me1 and H3K27ac, which blocked the DNA binding of FOXO3, a critical mediator of the cellular response to oxidative stress, and suppressed antioxidative gene transcription. Moreover, KMT2D deletion in PCa cells also increased their sensitivity to genotoxic anticancer drugs and a PARP inhibitor, which suggested that lower levels of KMT2D may mediate the response of PCa to particular treatments. These findings further highlighted the important role of KMT2D in PCa progression and suggested that targeting KMT2D might be therapeutically beneficial for advanced PCa treatment.

Resonant pitch and roll silicon gyroscopes with sub-micron-gap slanted electrodes: Breaking the barrier toward high-performance monolithic inertial measurement units.

This paper presents the design, fabrication, and characterization of a novel high quality factor (Q) resonant pitch/roll gyroscope implemented in a 40 µm (100) silicon-on-insulator (SOI) substrate without using the deep reactive-ion etching (DRIE) process. The featured silicon gyroscope has a mode-matched operating frequency of 200 kHz and is the first out-of-plane pitch/roll gyroscope with electrostatic quadrature tuning capability to fully compensate for fabrication non-idealities and variation in SOI thickness. The quadrature tuning is enabled by slanted electrodes with sub-micron capacitive gaps along the (111) plane created by an anisotropic wet etching. The quadrature cancellation enables a 20-fold improvement in the scale factor for a typical fabricated device. Noise measurement of quadrature-cancelled mode-matched devices shows an angle random walk (ARW) of 0.63° √h-1 and a bias instability of 37.7° h-1, partially limited by the noise of the interface electronics. The elimination of silicon DRIE in the anisotropically wet-etched gyroscope improves the gyroscope robustness against the process variation and reduces the fabrication costs. The use of a slanted electrode for quadrature tuning demonstrates an effective path to reach high-performance in future pitch and roll gyroscope designs for the implementation of single-chip high-precision inertial measurement units (IMUs).

Improving community detection in networks by targeted node removal.

How a network breaks up into subnetworks or communities is of wide interest. Here we show that vertices connected to many other vertices across a network can disturb the community structures of otherwise ordered networks, introducing noise. We investigate strategies to identify and remove noisy vertices ("violators") and develop a quantitative approach using statistical breakpoints to identify when the largest enhancement to a modularity measure is achieved. We show that removing nodes thus identified reduces noise in detected community structures for a range of different types of real networks in software systems and in biological systems.