TMEM16A regulates satellite cell-mediated skeletal muscle regeneration by ensuring a moderate level of caspase 3 activity.

It has been documented that caspase 3 activity is necessary for skeletal muscle regeneration, but how its activity is regulated is largely unknown. Our previous report shows that intracellular TMEM16A, a calcium activated chloride channel, significantly regulates caspase 3 activity in myoblasts during skeletal muscle development. By using a mouse line with satellite cell (SC)-specific deletion of TMEM16A, we examined the role of TMEM16A in regulating caspase 3 activity in SC (or SC-derived myoblast) as well as skeletal muscle regeneration. The mutant animals displayed apparently impaired regeneration capacity in adult muscle along with enhanced ER stress and elevated caspase 3 activity in Tmem16a-/- SC derived myoblasts. Blockade of either excessive ER stress or caspase 3 activity by small molecules significantly restored the inhibited myogenic differentiation of Tmem16a-/- SCs, indicating that excessive caspase 3 activity resulted from TMEM16A deletion contributes to the impaired muscle regeneration and the upstream regulator of caspase 3 was ER stress. Our results revealed an essential role of TMEM16A in satellite cell-mediated skeletal muscle regeneration by ensuring a moderate level of caspase 3 activity.

Tetrandrine Inhibits Skeletal Muscle Differentiation by Blocking Autophagic Flux.

Tetrandrine is well known to act as a calcium channel blocker. It is a potential candidate for a tumor chemotherapy drug without toxicity. Tetrandrine inhibits cancer cell proliferation and induces cell death through apoptosis and autophagy. As cancer patients usually experience complications with sarcopenia or muscle injury, we thus assessed the effects of tetrandrine on skeletal muscle cells. We report in this study that a low dose of tetrandrine (less than 5 µM) does not affect the proliferation of C2C12 myoblasts, but significantly inhibits myogenic differentiation. Consistently, tetrandrine inhibited muscle regeneration after BaCl2-induced injury. Mechanistic experiments showed that tetrandrine decreased the p-mTOR level and increased the levels of LC3 and SQSTM1/p62 during differentiation. Ad-mRFP-GFP-LC3B transfection experiments revealed that the lysosomal quenching of GFP signals was suppressed by tetrandrine. Furthermore, the levels of DNM1L/Drp1, PPARGA1 and cytochrome C (Cyto C), as well as caspase 3 activation and ROS production, were decreased following tetrandrine administration, indicating that the mitochondrial network signaling was inhibited. Our results indicate that tetrandrine has dual effects on autophagic flux in myoblasts during differentiation, activation in the early stage and blockade in the late stage. The ultimate blocking of autophagic flux by tetrandrine led to the disruption of mitochondria remodeling and inhibition of myogenic differentiation. The inhibitory effects of tetrandrine on skeletal muscle differentiation may limit its application in advanced cancer patients. Thus, great attention should be paid to the clinical use of tetrandrine for cancer therapy.

Direct femtosecond laser inscription of an IR fluorotellurite fiber Bragg grating.

This study proposes a novel, to the best of our knowledge, development of fluorotellurite glass fiber Bragg gratings (FBGs). Shell-like morphology was achieved using a single femtosecond laser pulse illuminated through the fiber's polymer coating. Different FBG fabrication methods and parameters were systematically studied to optimize performance. The fluorotellurite FBG exhibited a high sensitivity to writing laser power and reflectivity saturation effect in repetitive writing. A low-insertion-loss fluorotellurite FBG with a reflectivity of over 99% and bandwidth of less than 1 nm was successfully inscribed. The flexible inscription methods can write an FBG at any wavelength in the fluorotellurite glass transparent window, and are applicable to infrared fiber lasers or sensors.

Terahertz signatures and quantitative analysis of glucose anhydrate and monohydrate mixture.

Glucose, as the main energy carrier and significant source of nutrition, generally comes in two available forms of anhydrate and monohydrate in commercial production. Considering their respective application occasions, proper identification of glucose in single composition or binary-mixture and quantification of the mixture are crucial in industry monitoring to guarantee merchandise quality. Simultaneously, public confusions of glucose are rather ubiquitous partly due to anhydrate and monohydrate with identical white crystalline appearance. In this paper, utilizing the molecular fingerprints of terahertz (THz) technology that are corresponding to structural characteristics of anhydrous and hydrated form, THz signatures of glucose anhydrate, monohydrate and their mixture, as well as THz spectral transformation from monohydrate to anhydrate with the dehydrating process are systematically studied. Some visible peaks of monohydrate were noted at 1.82 and 1.99 THz signifying the presence of hydrated structure. However, with the dehydrating process, the peaks related to the hydrated structure are not very apparent when the peaks at 1.44 and 2.08 THz appear due to changes in the molecular structure of anhydrate, which provide clear indication for hydrogen-bond network reconstruction at the micro level. Furthermore, characteristic peaks at 1.44 and 1.82 THz can be specified as the main quantitative indicators for quantitative detection. The linear relationships between the amplitudes of characteristic peaks and the percentage compositions of anhydrate and monohydrate are revealed. Three commercially available brands of edible glucose powder A, B, C were effectively identified by THz signatures. While powder C was recognized as binary-mixture and the proportion of anhydrate and monohydrate was further quantified. THz spectroscopy technology has advantages of direct recognition, simple quantitative model based on THz absorption peaks, and no need for complicated chemical treatment. It may be potentially shed light on industrial monitoring of glucose production and other related mixture in the future.

SPICE-ML Algorithm for Direction-of-Arrival Estimation.

Sparse iterative covariance-based estimation, an iterative direction-of-arrival approach based on covariance fitting criterion, can simultaneously estimate the angle and power of incident signal. However, the signal power estimated by sparse iterative covariance-based estimation approach is inaccurate, and the estimation performance is limited to direction grid. To solve the problem above, an algorithm combing the sparse iterative covariance-based estimation approach and maximum likelihood estimation is proposed. The signal power estimated by sparse iterative covariance-based estimation approach is corrected by a new iterative process based on the asymptotically minimum variance criterion. In addition, a refinement procedure is derived by minimizing a maximum likelihood function to overcome the estimation accuracy limitation imposed by direction grid. Simulation results verify the effectiveness of the proposed algorithm. Compared with sparse iterative covariance-based estimation approach, the proposed algorithm can achieve more accurate signal power and improved estimation performance.

A Low-Complexity DOA and Polarization Method of Polarization-Sensitive Array.

This paper proposes a low-complexity method to estimate the direction of arrival and polarization based on the polarization sensitive array (PSA) which is composed of cross-dipoles. We built a half-quaternions model through the Cayley-Dickson form to remove the redundant information. Then, the directions of arrival (DOAs) were estimated via the root-MUSIC algorithm. Finally, the polarizations were estimated by generalized eigenvalue method. Unlike some existing searching algorithms, such as multiple signal classification (MUSIC), this method can avoid the peak searching and maintains high estimation accuracy. Moreover, we use the oblique projection operators to filter out the interference signals which are decoys of the target signal. Simulation results demonstrate the effectiveness and favorable performance of the proposed method.

LPI Radar Waveform Recognition Based on Time-Frequency Distribution.

In this paper, an automatic radar waveform recognition system in a high noise environment is proposed. Signal waveform recognition techniques are widely applied in the field of cognitive radio, spectrum management and radar applications, etc. We devise a system to classify the modulating signals widely used in low probability of intercept (LPI) radar detection systems. The radar signals are divided into eight types of classifications, including linear frequency modulation (LFM), BPSK (Barker code modulation), Costas codes and polyphase codes (comprising Frank, P1, P2, P3 and P4). The classifier is Elman neural network (ENN), and it is a supervised classification based on features extracted from the system. Through the techniques of image filtering, image opening operation, skeleton extraction, principal component analysis (PCA), image binarization algorithm and Pseudo-Zernike moments, etc., the features are extracted from the Choi-Williams time-frequency distribution (CWD) image of the received data. In order to reduce the redundant features and simplify calculation, the features selection algorithm based on mutual information between classes and features vectors are applied. The superiority of the proposed classification system is demonstrated by the simulations and analysis. Simulation results show that the overall ratio of successful recognition (RSR) is 94.7% at signal-to-noise ratio (SNR) of -2 dB.

A Modified Rife Algorithm for Off-Grid DOA Estimation Based on Sparse Representations.

In this paper we address the problem of off-grid direction of arrival (DOA) estimation based on sparse representations in the situation of multiple measurement vectors (MMV). A novel sparse DOA estimation method which changes MMV problem to SMV is proposed. This method uses sparse representations based on weighted eigenvectors (SRBWEV) to deal with the MMV problem. MMV problem can be changed to single measurement vector (SMV) problem by using the linear combination of eigenvectors of array covariance matrix in signal subspace as a new SMV for sparse solution calculation. So the complexity of this proposed algorithm is smaller than other DOA estimation algorithms of MMV. Meanwhile, it can overcome the limitation of the conventional sparsity-based DOA estimation approaches that the unknown directions belong to a predefined discrete angular grid, so it can further improve the DOA estimation accuracy. The modified Rife algorithm for DOA estimation (MRife-DOA) is simulated based on SRBWEV algorithm. In this proposed algorithm, the largest and sub-largest inner products between the measurement vector or its residual and the atoms in the dictionary are utilized to further modify DOA estimation according to the principle of Rife algorithm and the basic idea of coarse-to-fine estimation. Finally, simulation experiments show that the proposed algorithm is effective and can reduce the DOA estimation error caused by grid effect with lower complexity.

Augmented lagrange based on modified covariance matching criterion method for DOA estimation in compressed sensing.

A novel direction of arrival (DOA) estimation method in compressed sensing (CS) is presented, in which DOA estimation is considered as the joint sparse recovery from multiple measurement vectors (MMV). The proposed method is obtained by minimizing the modified-based covariance matching criterion, which is acquired by adding penalties according to the regularization method. This minimization problem is shown to be a semidefinite program (SDP) and transformed into a constrained quadratic programming problem for reducing computational complexity which can be solved by the augmented Lagrange method. The proposed method can significantly improve the performance especially in the scenarios with low signal to noise ratio (SNR), small number of snapshots, and closely spaced correlated sources. In addition, the Cramér-Rao bound (CRB) of the proposed method is developed and the performance guarantee is given according to a version of the restricted isometry property (RIP). The effectiveness and satisfactory performance of the proposed method are illustrated by simulation results.

Joint estimation of 2D-DOA and frequency based on space-time matrix and conformal array.

Each element in the conformal array has a different pattern, which leads to the performance deterioration of the conventional high resolution direction-of-arrival (DOA) algorithms. In this paper, a joint frequency and two-dimension DOA (2D-DOA) estimation algorithm for conformal array are proposed. The delay correlation function is used to suppress noise. Both spatial and time sampling are utilized to construct the spatial-time matrix. The frequency and 2D-DOA estimation are accomplished based on parallel factor (PARAFAC) analysis without spectral peak searching and parameter pairing. The proposed algorithm needs only four guiding elements with precise positions to estimate frequency and 2D-DOA. Other instrumental elements can be arranged flexibly on the surface of the carrier. Simulation results demonstrate the effectiveness of the proposed algorithm.

Beamforming of joint polarization-space matched filtering for conformal array.

Due to the polarization mismatch of the antenna, the received signal suffers from energy loss. The conventional beamforming algorithms could not be applied to the conformal array because of the varying curvature. In order to overcome the energy loss of the received signal, a novel joint polarization-space matched filtering algorithm for cylindrical conformal array is proposed. First, the snapshot data model of the conformal polarization sensitive array is analyzed. Second, the analytical expression of polarization sensitive array beamforming is derived. Linearly constrained minimum variance (LCMV) beamforming technique is facilitated for the cylindrical conformal array. Third, the idea of joint polarization-space matched filtering is presented, and the principle of joint polarization-space matched filtering is discussed in detail. Theoretical analysis and computer simulation results verify that the conformal polarization sensitive array is more robust than the ordinary conformal array. The proposed algorithm can improve the performance when signal and interference are too close. It can enhance the signal-to-noise ratio (SNR) by adjusting the polarization of the elements of the conformal array, which matches the polarization of the incident signal.