Newcastle disease virus activates diverse signaling pathways via Src to facilitate virus entry into host macrophages.

As an intrinsic cellular mechanism responsible for the internalization of extracellular ligands and membrane components, caveolae-mediated endocytosis (CavME) is also exploited by certain pathogens for endocytic entry [e.g., Newcastle disease virus (NDV) of paramyxovirus]. However, the molecular mechanisms of NDV-induced CavME remain poorly understood. Herein, we demonstrate that sialic acid-containing gangliosides, rather than glycoproteins, were utilized by NDV as receptors to initiate the endocytic entry of NDV into HD11 cells. The binding of NDV to gangliosides induced the activation of a non-receptor tyrosine kinase, Src, leading to the phosphorylation of caveolin-1 (Cav1) and dynamin-2 (Dyn2), which contributed to the endocytic entry of NDV. Moreover, an inoculation of cells with NDV-induced actin cytoskeletal rearrangement through Src to facilitate NDV entry via endocytosis and direct fusion with the plasma membrane. Subsequently, unique members of the Rho GTPases family, RhoA and Cdc42, were activated by NDV in a Src-dependent manner. Further analyses revealed that RhoA and Cdc42 regulated the activities of specific effectors, cofilin and myosin regulatory light chain 2, responsible for actin cytoskeleton rearrangement, through diverse intracellular signaling cascades. Taken together, our results suggest that an inoculation of NDV-induced Src-mediated cellular activation by binding to ganglioside receptors. This process orchestrated NDV endocytic entry by modulating the activities of caveolae-associated Cav1 and Dyn2, as well as specific Rho GTPases and downstream effectors. IMPORTANCE: In general, it is known that the paramyxovirus gains access to host cells through direct penetration at the plasma membrane; however, emerging evidence suggests more complex entry mechanisms for paramyxoviruses. The endocytic entry of Newcastle disease virus (NDV), a representative member of the paramyxovirus family, into multiple types of cells has been recently reported. Herein, we demonstrate the binding of NDV to induce ganglioside-activated Src signaling, which is responsible for the endocytic entry of NDV through caveolae-mediated endocytosis. This process involved Src-dependent activation of the caveolae-associated Cav1 and Dyn2, as well as specific Rho GTPase and downstream effectors, thereby orchestrating the endocytic entry process of NDV. Our findings uncover a novel molecular mechanism of endocytic entry of NDV into host cells and provide novel insight into paramyxovirus mechanisms of entry.

An Investigation into the Application of Acceleration Responses' Trendline for Bridge Damage Detection Using Quadratic Regression.

It has been proven that structural damage can be successfully identified using trendlines of structural acceleration responses. In previous numerical and experimental studies, the Savitzky-Golay filter and moving average filter were adjusted to determine suitable trendlines and locate structural damage in a simply supported bridge. In this study, the quadratic regression technique was studied and employed to calculate the trendlines of the bridge acceleration responses. The normalized energies of the resulting trendlines were then used as a damage index to identify the location and severity of the structural bridge damage. An ABAQUS model of a 25 m simply supported bridge under a truckload with different velocities was used to verify the accuracy of the proposed method. The structural damage was numerically modeled as cracks at the bottom of the bridge, so the stiffness at the damage positions was decreased accordingly. Four different velocities from 1 m/s to 8 m/s were used. The proposed method can identify structural damage in noisy environments without monitoring the dynamic modal parameters. Moreover, the accuracy of the newly proposed trendline-based method was increased compared to the previous method. For velocities up to 4 m/s, the damage in all single- and multiple-damage scenarios was successfully identified. For the velocity of 8 m/s, the damage in some scenarios was not located accurately. Additionally, it should be noted that the proposed method can be categorized as an online, quick, and baseline-free structural damage-detection method.

Surveillance of Class I Newcastle Disease Virus at Live Bird Markets in China and Identification of Variants with Increased Virulence and Replication Capacity.

In this study, 232 class I Newcastle disease viruses (NDVs) were identified from multiple bird species at nationwide live bird markets (LBMs) from 2017 to 2019 in China. Phylogenetic analysis indicated that all 232 isolates were clustered into genotype 1.1.2 of class I on the basis of the fusion (F) gene sequences, which were distinct from the genotypes identified in other countries. Most of the isolates (212/232) were shown to have the typical F gene molecular characteristics of class I NDVs, while a few (20/232) contained mutations at the site of the conventional start codon of the F gene, which resulted in open reading frames (ORFs) altered in length. The isolates with ACG, CTA, and ATA mutations showed different levels of increased virulence and replication capacity, suggesting that these viruses may be transitional types during the evolution of class I NDVs from avirulent to virulent. Further evaluation of biological characteristics with recombinant viruses obtained by reverse genetics demonstrated that the ATG located at genomic positions 4523 to 4525 was the authentic start codon in the F gene of class I NDV, and the specific ATA mutations which contributed to the expression of F protein on the surface of infected cells were the key determinants of increased replication capacity and virulence. Interestingly, the mutation at the corresponding site of genotype II LaSota of class II had no effects on the virulence and replication capacity in chickens. Our results suggest that the alteration of virulence and replication capacity caused by specific mutations in the F gene could be a specific characteristic of class I NDVs and indicate the possibility of the emergence of virulent NDVs due to the persistent circulation of class I NDVs. IMPORTANCE The available information on the distribution, genetic diversity, evolution, and biological characteristics of class I Newcastle disease viruses (NDVs) in domestic poultry is currently very limited. Here, identification of class I NDVs at nationwide live bird markets (LBMs) in China was performed and representative isolates were characterized. A widespread distribution of genotype 1.1.2 of class I NDVs was found in multiple bird species at LBMs in China. Though most isolates demonstrated typical molecular characteristics of class I NDVs, a few that contained specific mutations at the site of the conventional start codon of the fusion gene with increased virulence and replication capacity were identified for the first time. Our findings indicate that the virulence of class I NDVs could have evolved, and the widespread transmission and circulation of class I NDVs may represent a potential threat for disease outbreaks in poultry.

A dual ultra-broadband switchable high-performance terahertz absorber based on hybrid graphene and vanadium dioxide.

A tunable dual broadband switchable terahertz absorber based on vanadium dioxide and graphene is proposed. The tunability of graphene and the phase transition properties of vanadium dioxide are used to switch broadband absorption between low-frequency and high-frequency, as well as the absorption rate tuning function. The simulation results indicate that when vanadium dioxide is in the insulating phase and the graphene Fermi energy is 0.7 eV, the absorber achieves low-frequency broadband absorption within the range of 2.6-4.2 THz with an absorptance greater than 90%; when vanadium dioxide is in the metallic phase and the graphene Fermi energy is 0 eV, the absorber achieves high-frequency broadband absorption within the range of 4.9-10 THz with an absorptance greater than 90%. Furthermore, the absorptance can be tuned by adjusting the conductivity of vanadium dioxide or the Fermi energy of graphene. Due to the central symmetry of the proposed structure, the absorber is completely insensitive to polarization. For TE and TM polarized waves, both low and high-frequency broadband absorption are maintained over a range of incident angles from 0° to 50°. The simple structure, tunable absorption rate, insensitivity to polarization angle and incident angle properties are advantages of our proposed absorber. It has broad application prospects in adjustable filters and electromagnetic shielding.

Nanostructured perovskites for nonvolatile memory devices.

Perovskite materials have driven tremendous advances in constructing electronic devices owing to their low cost, facile synthesis, outstanding electric and optoelectronic properties, flexible dimensionality engineering, and so on. Particularly, emerging nonvolatile memory devices (eNVMs) based on perovskites give birth to numerous traditional paradigm terminators in the fields of storage and computation. Despite significant exploration efforts being devoted to perovskite-based high-density storage and neuromorphic electronic devices, research studies on materials' dimensionality that has dominant effects on perovskite electronics' performances are paid little attention; therefore, a review from the point of view of structural morphologies of perovskites is essential for constructing perovskite-based devices. Here, recent advances of perovskite-based eNVMs (memristors and field-effect-transistors) are reviewed in terms of the dimensionality of perovskite materials and their potentialities in storage or neuromorphic computing. The corresponding material preparation methods, device structures, working mechanisms, and unique features are showcased and evaluated in detail. Furthermore, a broad spectrum of advanced technologies (e.g., hardware-based neural networks, in-sensor computing, logic operation, physical unclonable functions, and true random number generator), which are successfully achieved for perovskite-based electronics, are investigated. It is obvious that this review will provide benchmarks for designing high-quality perovskite-based electronics for application in storage, neuromorphic computing, artificial intelligence, information security, etc.

Phase unwrapping algorithm based on phase edge tracking for dynamic measurement.

Phase unwrapping is an essential procedure for fringe projection profilometry (FPP). To improve measurement efficiency and reduce phase unwrapping errors (PUEs) in dynamic measurement, a phase unwrapping algorithm based on phase edge tracking is proposed, which unwraps the current wrapped phase map with the aid of the previously unwrapped one. The phase edges are accurately tracked and their trajectories are used to divide the phase map into several regions, each of which is unwrapped either temporally or spatially according to its properties. It doesn't require extra patterns for phase unwrapping once the initial unwrapped phase map is obtained, thus significantly increasing the frame rate of the 3D result. Meanwhile, it greatly reduces the PUEs caused by noise amplification and motion-induced misalignment of phase edges. Experiments prove that it is capable of retrieving the absolute phase maps of complex dynamic scenes with high unwrapping accuracy and efficiency.

Tunable wideband-narrowband switchable absorber based on vanadium dioxide and graphene.

A functionally tunable and absorption-tunable terahertz (THz) metamaterial absorber based on vanadium dioxide (VO2) and graphene is proposed and verified numerically. Based on phase transition properties of VO2 and tunability of graphene, the switching performance between ultra-broadband and narrow-band near-perfect absorption can be achieved. We simulate and analyze the characteristics of the constructed model by finite element analysis. Theoretical calculations show that when VO2 is in the metallic state and the graphene Fermi energy is 0 eV, the designed absorber can perform ultra-broadband absorption. The absorber achieves greater than 95% absorption in the 2.85 - 10THz range. When VO2 is in the insulating state and the graphene Fermi energy is 0.7 eV, more than 99.5% absorption can be achieved at 2.3 THz. The absorption rate can be tuned by changing the conductivity of VO2 and the Fermi energy of graphene. Moreover, the proposed absorber displays good polarization insensitivity and wide incident angle stability. The design may have potential applications in terahertz imaging, sensing, electromagnetic shielding and so on.

Dynamic 3D measurement based on orthogonal fringe projection and geometric constraints.

Geometric constraint algorithms can solve phase ambiguity for fringe projection profilometry (FPP). However, they either require multiple cameras or suffer from a small measurement depth range. To overcome these limitations, this Letter proposes an algorithm combining orthogonal fringe projection and geometric constraints. A novel, to the best of our knowledge, scheme is developed to assess the reliabilities of the potential homologous points, which works with depth segmentation to determine the final HPs. With full consideration of lens distortions, the algorithm reconstructs two 3D results from every set of patterns. Experimental results verify that it can effectively and robustly measure discontinuous objects with complex motion over a large depth range.

Study on the Classification of Metal Objects by a Fluxgate Magnetometer Cube Structure.

After wars, some unexploded bombs remained underground, and these faulty bombs seriously threaten the safety of people. The ability to accurately identify targets is crucial for subsequent mining work. A deep learning algorithm is used to recognize targets, which significantly improves recognition accuracy compared with the traditional recognition algorithm for measuring the magnetic moment of the target and the included geomagnetism angle. In this paper, a ResNet-18-based recognition system is presented for classifying metallic object types. First, a fluxgate magnetometer cube arrangement structure (FMCAS) magnetic field feature collector is constructed, utilizing an eight-fluxgate magnetometer sensor array structure that provides a 400 mm separation between each sensitive unit. Magnetic field data are acquired, along an east-west survey line on the northern side of the measured target using the FMCAS. Next, the location and type of targets are modified to create a database of magnetic target models, increasing the diversity of the training dataset. The experimental dataset is constructed by constructing the magnetic flux density tensor matrix. Finally, the enhanced ResNet-18 is used to train the data for the classification recognition recognizer. According to the test findings of 107 validation set groups, this method's recognition accuracy is 84.1 percent. With a recognition accuracy rate of 96.3 percent, a recall rate of 96.4 percent, and a precision rate of 96.4 percent, the target with the largest magnetic moment has the best recognition impact. Experimental findings demonstrate that our enhanced RestNet-18 network can efficiently classify metallic items. This provides a new idea for underground metal target identification and classification.

Flat Photonic Crystal Fiber Plasmonic Sensor for Simultaneous Measurement of Temperature and Refractive Index with High Sensitivity.

A compact temperature-refractive index (RI) flat photonic crystal fiber (PCF) sensor based on surface plasmon resonance (SPR) is presented in this paper. Sensing of temperature and RI takes place in the x- and y- polarization, respectively, to avoid the sensing crossover, eliminating the need for matrix calculation. Simultaneous detection of dual parameters can be implemented by monitoring the loss spectrum of core modes in two polarizations. Compared with the reported multi-function sensors, the designed PCF sensor provides higher sensitivities for both RI and temperature detection. A maximum wavelength sensitivity of -5 nm/°C is achieved in the temperature range of -30-40 °C. An excellent optimal wavelength sensitivity of 17,000 nm/RIU is accomplished in the RI range of 1.32-1.41. The best amplitude sensitivity of RI is up to 354.39 RIU-1. The resolution of RI and temperature sensing is 5.88 × 10-6 RIU and 0.02 °C, respectively. The highest value of the figure of merit (FOM) is 216.74 RIU-1. In addition, the flat polishing area of the gold layer reduces the manufacturing difficulty. The proposed sensor has the characteristics of high sensitivity, simple structure, good fabrication repeatability, and flexible operation. It has potential in medical diagnosis, chemical inspection, and many other fields.

Micro-Nano Processing of Active Layers in Flexible Tactile Sensors via Template Methods: A Review.

Template methods are regarded as an important method for micro-nano processing in the active layer of flexible tactile sensors. These template methods use physical/chemical processes to introduce micro-nano structures on the active layer, which improves many properties including sensitivity, response/recovery time, and detection limit. However, since the processing process and applicable conditions of the template method have not yet formed a perfect system, the development and commercialization of flexible tactile sensors based on the template method are still at a relatively slow stage. Despite the above obstacles, advances in microelectronics, materials science, nanoscience, and other disciplines have laid the foundation for various template methods, enabling the continuous development of flexible tactile sensors. Therefore, a comprehensive and systematic review of flexible tactile sensors based on the template method is needed to further promote progress in this field. Here, the unique advantages and shortcomings of various template methods are summarized in detail and discuss the research progress and challenges in this field. It is believed that this review will have a significant impact on many fields of flexible electronics, which is beneficial to promote the cross-integration of multiple fields and accelerate the development of flexible electronic devices.

Direct Use of the Savitzky-Golay Filter to Develop an Output-Only Trend Line-Based Damage Detection Method.

The Savitzky-Golay filter (SGF) is a time-domain technique that determines a trend line for a signal. The direct application of SGF for damage localization and quantification is investigated in this paper. Therefore, a single-stage trend line-based damage detection method employing SGF is proposed in which the damage is located and quantified at the bridge under moving load. A simply supported beam under moving sprung mass is numerically simulated to verify the proposed method. Four different velocities and five different single- and multi-damage scenarios are considered. The acceleration data along the beam are obtained, manually polluted with noise and their trend lines are then determined using SGF. The results show that the proposed method can accurately locate and quantify the damage using these trend lines. It is proved that the proposed method is insensitive to the noise and velocity variation in which having a constant velocity is a hard task before and after damage. Additionally, defining a normalization factor and fitting a Gaussian curve to this factor provide an estimation for the baseline and therefore, it categorizes the proposed method as baseline-free method.

Structural Damage Localization and Quantification Based on a CEEMDAN Hilbert Transform Neural Network Approach: A Model Steel Truss Bridge Case Study.

Vibrations of complex structures such as bridges mostly present nonlinear and non-stationary behaviors. Recently, one of the most common techniques to analyze the nonlinear and non-stationary structural response is Hilbert-Huang Transform (HHT). This paper aims to evaluate the performance of HHT based on complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) technique using an Artificial Neural Network (ANN) as a proposed damage detection methodology. The performance of the proposed method is investigated for damage detection of a scaled steel-truss bridge model which was experimentally established as the case study subjected to white noise excitations. To this end, four key features of the intrinsic mode function (IMF), including energy, instantaneous amplitude (IA), unwrapped phase, and instantaneous frequency (IF), are extracted to assess the presence, severity, and location of the damage. By analyzing the experimental results through different damage indices defined based on the extracted features, the capabilities of the CEEMDAN-HT-ANN model in detecting, addressing the location and classifying the severity of damage are efficiently concluded. In addition, the energy-based damage index demonstrates a more effective approach in detecting the damage compared to those based on IA and unwrapped phase parameters.

Reusable, Non-Invasive, and Ultrafast Radio Frequency Biosensor Based on Optimized Integrated Passive Device Fabrication Process for Quantitative Detection of Glucose Levels.

The increase in the number of people suffering diabetes has been the driving force behind the development of glucose sensors to overcome the current testing shortcomings. In this work, a reusable, non-invasive and ultrafast radio frequency biosensor based on optimized integrated passive device fabrication process for quantitative detection of glucose level was developed. With the aid of the novel biosensor design with hammer-shaped capacitors for carrying out detection, both the resonance frequency and magnitude of reflection coefficient can be applied to map the different glucose levels. Meanwhile, the corresponding fabrication process was developed, providing an approach for achieving quantitative detection and a structure without metal-insulator-metal type capacitor that realizes low cost and high reliability. To enhance the sensitivity of biosensor, a 3-min dry etching treatment based on chlorine/argon-based plasma was implemented for realizing hydrophilicity of capacitor surface to ensure that the biosensor can be touched rapidly with glucose. Based on above implementation, a non-invasive biosensor having an ultrafast response time of superior to 0.85 s, ultralow LOD of 8.01 mg/dL and excellent reusability verified through five sets of measurements are realized. The proposed approaches are not limited the development of a stable and accurate platform for the detection of glucose levels but also presents a scheme toward the detection of glucose levels in human serum.

Dielectric metasurfaces based on a rectangular lattice of a-Si:H nanodisks for color pixels with high saturation and stability.

Silicon dielectric metasurfaces based on a square lattice of nanoparticles have been extensively utilized to create transmissive structural colors. Yet it is a huge challenge to obtain stable yellow color with high saturation due to the relatively large absorption of silicon in the short wavelength regime and the applied square lattice. In this study, we propose a new design strategy of independently altering the mutually perpendicular periods of a hydrogenated amorphous silicon nanodisk array-enabled metasurface to meticulously modulate the transmission spectra for the realization of high-saturation and stable cyan, magenta and yellow (CMY) color pixels. By introducing rectangular lattice, the yellow pixel can provide a narrowband transmission spectrum with a highly suppressed dip at 455 nm. The high suppression in transmission contributes to give rise to high-saturation yellow color. The attained narrowband spectrum that enables low spectral cross-talk is attributed to the overlap between magnetic dipole resonance excited by individual nanodisks and lattice resonance arising from the dipole coupling between the nanodisks. Compared with the square lattice, the proposed pixels exhibit fairly stable output color responses for a large period range. Meanwhile, the proposed CMY pixels are capable of both the relaxed angular tolerance and low dependence on the incident polarization states. It is anticipated that the proposed color pixels pave the way for extensive applications in compact color displays.

Three-dimensional measurement based on optimized circular fringe projection technique.

Circular fringe projection profilometry (CFPP) is a recently proposed optical three-dimensional (3D) measurement technique. Theoretically, its optimal measurement accuracy should precede that of the conventional fringe projection profilometry. In practice, the measurement accuracy is impacted by many factors, and much research remains to be done in order to make CFPP reach its optimal precision. One of the dominant factors is the zero-phase point. For the usage of the cotangent function, error near the zero-phase point will be significantly amplified. This makes the overall measurement accuracy very low for CFPP with coaxial layout. To address this critical issue, CFPP with off-axis layout (called OCFPP for simplicity) is presented in this paper. The core theory of OCFPP is briefly introduced. The zero-phase point detection problem coming with OCFPP is explained. Then, two methods, one based on a two-dimensional ruler and the other based on plane constraint, are proposed to solve this additional problem. Simulation and experiments validate the effectiveness of the proposed zero-phase point detection methods, and convince the advantage of OCFPP. This paper contributes to distinctly improving the 3D measurement capability of CFPP, and lays an indispensible foundation for its practical application.

Beam Damage Detection Under a Moving Load Using Random Decrement Technique and Savitzky- Golay Filter.

In this paper, a two-stage time-domain output-only damage detection method is proposed with a new energy-based damage index. In the first stage, the random decrement technique (RDT) is employed to calculate the random decrement signatures (RDSs) from the acceleration responses of a simply supported beam subjected to a moving load. The RDSs are then filtered using the Savitzky-Golay filter (SGF) in the second stage. Next, the filtered RDSs are processed by the proposed energy-based damage index to locate and quantify the intensity of the possible damage. Finally, by fitting a Gaussian curve to the damage index resulted from the non-damage conditions, the whole process is systematically implemented as a baseline-free method. The proposed method is numerically verified using a simply supported beam under moving sprung mass with different velocities and damage scenarios. The results show that the proposed method can accurately estimate the damage location/quantification from the acceleration data without any prior knowledge of either input load or damage characteristics. Additionally, the proposed method is neither sensitive to noise nor velocity variation, which makes it ideal when obtaining a constant velocity is difficult.

Looseness Monitoring of Bolted Spherical Joint Connection Using Electro-Mechanical Impedance Technique and BP Neural Networks.

The bolted spherical joint (BSJ) has wide applications in various space grid structures. The bar and the bolted sphere are connected by the high-strength bolt inside the joint. High-strength bolt is invisible outside the joint, which causes the difficulty in monitoring the bolt looseness. Moreover, the bolt looseness leads to the reduction of the local stiffness and bearing capacity for the structure. In this regard, this study used the electro-mechanical impedance (EMI) technique and back propagation neural networks (BPNNs) to monitor the bolt looseness inside the BSJ. Therefore, a space grid specimen having bolted spherical joints and tubular bars was considered for experimental evaluation. Different torques levels were applied on the sleeve to represent different looseness degrees of joint connection. As the torque levels increased, the looseness degrees of joint connection increased correspondingly. The lead zirconate titanate (PZT) patch was used and integrated with the tubular bar due to its strong piezoelectric effect. The root-mean-square deviation (RMSD) of the conductance signatures for the PZT patch were used as the looseness-monitoring indexes. Taking RMSD values of sub-frequency bands and the looseness degrees as inputs and outputs respectively, the BPNNs were trained and tested in twenty repeated experiments. The experimental results show that the formation of the bolt looseness can be detected according to the changes of looseness-monitoring indexes, and the degree of bolt looseness by the trained BPNNs. Overall, this research demonstrates that the proposed structural health monitoring (SHM) technique is feasible for monitoring the looseness of bolted spherical connection in space grid structures.

The Strain Transfer Mechanism of Fiber Bragg Grating Sensor for Extra Large Strain Monitoring.

This research focuses on a desensitization method to develop a wide-range FBG sensor for extra-large strain monitoring, which is an essential requirement in large scale infrastructures or for some special occasions. Under appropriate hypotheses, the strain transfer distribution of wide-range FBG sensor based on the shear-lag theory is conducted to improve the accuracy of extra-large strain measurements. It is also discussed how the elastic modulus of adhesive layer affects the strain transfer rate. Two prototypes in different monitoring ranges are designed and fabricated by two layers of steel pipe encapsulation. The presented theoretical model is verified by experimental results. Moreover, it is demonstrated that experimentation in regards to the calibration of the wide-range FBG sensor, improved the amplification coefficient up to 2.08 times and 3.88 times, respectively. The static errors are both calculated and analyzed in this experiment. The wide-range FBG strain sensor shows favourable linearity and stability, which is an excellent property of sensors for extra-large strain monitoring.

Does vitamin E prevent asthma or wheeze in children: A systematic review and meta-analysis.

Asthma is a heterogeneous disease with multiple phenotypes. Epidemiologic studies suggest a close relationship between vitamin E and the occurrence of asthma, wheezing and atopic conditions during childhood. Previous results on its effects have been conflicting. The aim of this meta-analysis was to critically examine the current evidence on the association of vitamin E with childhood asthma and wheezing. We searched electronic databases for observational studies in English-language journals published from 2000 to 2016. The initial search found 420 titles; nineteen studies were eligible according to the abstracts and details, which included reporting asthma or wheeze as an outcome. None of the articles included in this meta-analysis reported side effects of vitamin E supplementation during pregnancy. This meta-analysis found that vitamin E supplementation during pregnancy influenced the risk of asthma. To better understand the effectiveness and safety of vitamin E in children with asthma, large-scale, well-designed and randomized controlled trials are needed.