Integrin αvß3-targeted self-assembled polypeptide nanomicelles for efficacious sonodynamic therapy against breast cancer.

Sonodynamic therapy (SDT) is an advanced non-invasive cancer treatment strategy with moderate tissue penetration, less invasiveness and a reliable curative effect. However, due to the low stability, potential bio-toxicity and lack of tumor targeting capability of most sonosensitizers, the vast clinical application of SDT has been challenging and limited. Therefore, it is desirable to develop a novel approach to implement sonosensitizers to SDT for cancer treatments. In this study, an amphiphilic polypeptide was designed to effectively encapsulate rose bengal (RB) as a model sonosensitizer to form peptido-nanomicelles (REPNs). The as-fabricated REPNs demonstrated satisfactory tumor targeting and fluorescence performances, which made them superb imaging tracers in vivo. In the meantime, they generated considerable amounts of reactive oxygen species (ROS) to promote tumor cell apoptosis under ultrasound irradiation and showed excellent anti-tumor performance without obvious side effects. These engineered nanomicelles in combination with medical ultrasound may be used to achieve integrin αvß3-targeted sonodynamic therapy against breast cancer, and it is also a promising non-invasive cancer treatment strategy for clinical translations.

Improved phase-to-height mapping method combine with device attitude.

Phase-to-height mapping is one of the important processes in three dimensional phase measurement profilometry. But, in traditional phase-to-height mapping method, the measurement accuracy is affected by device attitude, so it needs saving a large amount of mapping equations to achieve high-quality phase-to-height mapping. In order to improve that, this paper proposes an improved phase-to-height mapping method combine with device attitude. Firstly, we get the unwrapped phase of the target. Then, using generalized regression neural network is used to reduce the offset of phase information at the same height due to the randomness of device attitude. Last, the phase-to-height mapping is completed by substituting the unwrapped phase (the difference between having detected object and no detected object) of eliminate the offset into improved phase-to-height mapping method. Experimental results show that the proposed method could achieve high-quality phase-to-height mapping with less mapping equation and less memory space. Compared with the nonlinear phase-to-height mapping method (probabilistic neural network to eliminate phase offset), its accuracy is improved by 44.30%. Compared with the nonlinear phase-to-height mapping method (radial basis function neural network to eliminate phase offset), the accuracy is improved by 39.58%.

Visualization of Engineered M13 Phages Bound to Bacterial Targets by Transmission Electron Microscopy.

The filamentous phage M13 is one of the most well-studied and characterized phages, particularly since it was introduced as a scaffold for phage display, a technique to express and evolve fusion proteins on the M13 phage's coat to study protein or peptide binding interactions. Since phages can be engineered or evolved to specifically bind to a variety of targets, engineered M13 phages have been explored for applications such as drug delivery, biosensing, and cancer therapy, among others. Specifically, with the rising challenge of antimicrobial resistance among bacteria, chimeric M13 phages have been explored both as detection and therapeutic agents due to the flexibility in tuning target specificity. Transmission electron microscopy (TEM) is a powerful tool enabling researchers to directly visualize and characterize binding of phages to bacterial surfaces. However, the filamentous phage structure poses a challenge for this technique, as the phages have similar morphology to bacterial structures such as pili. In order to differentiate between bacterial structures and the filamentous phages, here we describe a protocol to prepare TEM samples of engineered M13 phages bound to bacterial cells, in which the phage virions have been specifically labeled by decoration of the major capsid proteins with gold nanoparticles. This protocol enables clear visualization and unambiguous identification of attached filamentous phages within the context of bacterial cells expressing numerous pili.

External stimuli-triggered photodynamic and sonodynamic therapies in combination with hybrid nanomicelles of ICG@PEP@HA: laser vs. ultrasound.

The concept of combining external medical stimuli with internal functional biomaterials to achieve cancer-oriented treatments is being emergingly developed. Optical and acoustical activations have shown particular promise as non-invasive regulation modalities in cancer treatment and intervention. It is always challenging to leverage the contributions of optical and acoustical stimuli and find appropriate biomaterials to optimally match them. Herein, a type of hybrid nanomicelle (ICG@PEP@HA) containing ICG as a photo/sonosensitizer, an amphiphilic peptide for membrane penetration and hyaluronic acid for cluster determinant 44 (CD44) targeting was fabricated. Triggered by the external stimuli of laser and US irradiation, their photo/sonothermal performance, in vitro reactive oxygen species (ROS) production capability and tumor-targeting efficiency have been systematically evaluated. It was interestingly found that the external stimulus of laser irradiation induced a greater quantity of ROS, which resulted in significant cell apoptosis and tumor growth inhibition in the presence of ICG@PEP@HA. The individual analyses and corresponding rationales have been investigated. Meanwhile, these hybrid nanomicelles were administered into MDA-MB-231 tumor-bearing nude mice for PDT and SDT therapies and their biocompatibility assessment, and a prevailing PDT efficacy and reliable bio-safety have been evidenced based on the hematological analysis and histochemical staining. In summary, this study has validated a novel pathway to utilize these hybrid nanomicelles for laser/US-triggered localized tumor treatment, and the treatment efficiency may be leveraged by different external stimuli sources. It is also expected to give rise to full accessibility to clinical translations for human cancer treatments by means of the as-reported laser/US-nanomicelle combination strategy.

A multilevel recovery diagnosis model for rolling bearing faults from imbalanced and partially missing monitoring data.

As an indispensable part of large Computer Numerical Control machine tool, rolling bearing faults diagnosis is particularly important. However, due to the imbalanced distribution and partially missing of collected monitoring data, such diagnostic issue generally emerging in manufacturing industry is still hardly to be solved. Thus, a multilevel recovery diagnosis model for rolling bearing faults from imbalanced and partially missing monitoring data is formulated in this paper. Firstly, a regulable resampling plan is designed to handle the imbalanced distribution of data. Secondly, a multilevel recovery scheme is formed to deal with partially missing. Thirdly, an improved sparse autoencoder based multilevel recovery diagnosis model is built to identify the health status of rolling bearings. Finally, the diagnostic performance of the designed model is verified by artificial faults and practical faults tests, respectively.

Saturation-induced phase error correction method in 3-D measurement based on inverted fringes.

Saturation-induced phase error in three-dimensional (3-D) measurement is a challenge in fringe projection profilometry. This paper proposed a new, to the best of our knowledge, high dynamic range 3-D measurement method based on inverted fringes. For an efficient phase extraction method based on the 3f H+2f M+2f L algorithm, we just need to project a set of inverted fringes. Saturated pixels in the original fringes are replaced with unsaturated pixels in the inverted fringes. We analyzed 72 fringe replacement cases for the 3f H+2f M+2f L algorithm and gave the corresponding wrapped phase calculation. Experiments verify the validity of the proposed method. Since the proposed method does not require extensive exposure adjustments and complex projection intensity adjustment, the implementation is simple and convenient.

Identifying peripheral arterial disease in the elderly patients using machine-learning algorithms.

BACKGROUND: Peripheral artery disease (PAD) is a common syndrome in elderly people. Recently, artificial intelligence (AI) algorithms, in particular machine-learning algorithms, have been increasingly used in disease diagnosis. AIM: In this study, we designed an effective diagnostic model of PAD in the elderly patients using artificial intelligence. METHODS: The study was performed with 539 participants, all over 80 years in age, who underwent the measurements of Doppler ultrasonography and ankle-brachial pressure index (ABI). Blood samples were collected. ABI and two machine-learning algorithms (MLAs)-logistic regression and a random forest (RF) model-were established to diagnose PAD. The sensitivity and specificity of the models were analyzed. An additional RF model was designed based on the most significant features of the original RF model and a prospective study was conducted to demonstrate its external validity. RESULTS: Thirteen of the 28 features introduced to the MLAs differed significantly between PAD and non-PAD participants. The respective sensitivities and specificities of logistic regression, RF, and ABI were as follows: logistic regression (81.5%, 83.8%), RF (89.3%, 91.6%) and ABI (85.1%, 84.5%). In the prospective study, the newly designed RF model based on the most significant seven features exhibited an acceptable performance rate for the diagnosis of PAD with 100.0% sensitivity and 90.3% specificity. CONCLUSIONS: An RF model was a more effective method than the logistic regression and ABI for the diagnosis of PAD in an elderly cohort.

3-D shape reconstruction of non-uniform reflectance surface based on pixel intensity, pixel color and camera exposure time adaptive adjustment.

High dynamic range 3-D shape measurement is a challenge. In this work, we propose a novel method to solve the 3-D shape reconstruction of high-reflection and colored surfaces. First, we propose a method to establish a fast pixel-level mapping between the projected image and the captured image. Secondly, we propose a color texture extraction method using a black-and-white (B/W) camera and a pixel-level projection color adjustment method. Third, we give an optimal projection fringe modulation/background intensity ratio. Fourth, we propose a method for estimating the reflectivity of the object surface and ambient light interference, and a method for adjusting the projection intensity at the pixel level and a method for estimating the optimal exposure time. Experiments show that, compared with the existing methods, the proposed method not only can obtain high-quality captured images, but also has higher measurement efficiency and wider application range.

3D shape measurement method for high-reflection surface based on fringe projection.

3D measurement methods based on fringe projection have attracted extensive research. However, it is a challenge to deal with overshooting on a high-reflection or specular surface. To eliminate the saturated pixels caused by overshooting, we propose a projection intensity adaptive adjustment method. First, we project three uniform gray-level images and estimate the projection intensity of the measured surface through the captured uniform gray-level images. Then we can obtain the optimal projection fringes in the camera coordinate system. Second, a set of horizontal and vertical gray-coded patterns are used to establish a coordinate matching relationship between the projected image and the captured image. To check the decoding result of the gray-coded patterns, a set of horizontal and vertical sinusoidal fringes are used to calculate the high-reflection mapping area (HRMA) in the projector coordinate system. Through the distribution of HRMA, we can check whether the decoding is reliable or not. Finally, we project the optimal intensity fringes and obtain the measurement results. We develop a measurement system to verify the validity of the proposed method. Experimental results show that the proposed method can effectively avoid overshooting and obtain measurement results with a minimum rms error.

Rapid 3D measurement technique for colorful objects employing RGB color light projection.

Three-dimensional (3D) measurement of colorful objects is challenging. As different colors can absorb different wavelengths of projected light, the brightness and contrast of the captured fringe are not uniform when employing single-color light projection, which will lead to measurement error. In this paper, we present a rapid 3D measurement technique for colorful objects employing red, green, and blue (RGB) light projection. According to the research in this paper, for common colors, the pixel with the largest brightness and contrast can be extracted from the three fringes projected by RGB light. Furthermore, we introduce the selection method of exposure time, and then combine the high-speed projection technique with the optimal pixel-extraction algorithm to get the optimal set of fringes for phase calculation. Experiments show that the proposed method improves the measurement accuracy and efficiency.

Comparison of design methods for negative pressure gradient rotary bodies: A CFD study.

Computational fluid dynamics (CFD) simulation is used to test two body design methods which use negative pressure gradient to suppress laminar flow separation and drag reduction. The steady-state model of the Transition SST model is used to calculate the pressure distribution, wall shear stress, and drag coefficient under zero angle of attack at different velocities. Four bodies designed by two different methods are considered. Our results show the first method is superior to the body of Hansen in drag reduction and the body designed by the first method is more likely to obtain the characteristics of suppressing or eliminating separation, which can effectively improve laminar flow coverage to achieve drag reduction under higher Reynolds number conditions. The results show that the negative pressure gradient method can suppress separation and drag reduction better than the second method. This successful design method is expected to open a promising prospect for its application in the design of small drag, small noise subsonic hydrodynamic hull and underwater weapons.

A KLVFFAE-Derived Peptide Probe for Detection of Alpha-Synuclein Fibrils.

Aggregation of an amyloid protein, α-synuclein (αS), is a critical step in the neurodegenerative pathway of Parkinson's diseases (PD). Specific detection of amyloid conformers (i.e., monomers, oligomers, and fibrils) produced during αS aggregation is critical in better understanding a molecular basis of PD and developing a diagnostic tool. While various molecular probes are available for detection of αS fibrils, which may serve as a reservoir of toxic αS aggregate forms, these probes suffer from limited conformer-specificity and operational flexibility. In the present study, we explored the potential of non-self-aggregating peptides derived from the highly aggregation-prone KLVFFAE region of an amyloid protein, ß-amyloid, as molecular probes for αS aggregates. We show that of the four peptides tested (KLVFWAK, ELVFWAE, and their C-terminal capping variants, all of which were attached with fluorescein isothiocyanate at their respective N-termini), KLVFWAK with C-terminal capping was selectively bound to αS fibrils over monomers and oligomers and readily used for monitoring αS fibrilization. Our analyses suggest that binding of the peptide to αS fibrils is mediated by both electrostatic and hydrophobic interactions. We anticipate that our peptide can readily be optimized for conformer-specificity and operational flexibility. Overall, this study presents the creation of a KLVFFAE-based molecular probe for αS fibrils and demonstrates fine-tuning of its conformer-specificity by terminal mutations and capping.

Deep model integrated with data correlation analysis for multiple intermittent faults diagnosis.

Currently, single fault diagnosis has received mass concern, and the related research achievements are remarkable. However, because of the mutual interaction of subsystems and the coupling of faults characteristics, the diagnosis of multiple intermittent faults commonly existing in industrial systems is still an intractable problem. In order to solve the problem, an improved Constrained Sparse Autoencoder integrated with Correlation Analysis (CA-CSAE) is proposed, further, a diagnosis scheme for multiple intermittent faults is formulated in this paper. The main strategies are as follows. (1) An adaptive loss function and a constraint for initial weight are designed to improve the diversity and accuracy of SAE feature learning. (2) A relational constraint term is constructed to mitigate the effect of data correlation. (3) The evaluation criterion of data correlation degree is put forward to quantify the scope of the method. (4) In order to improve the diagnostic efficiency, ReLU is introduced as the activation function of hidden layer, and L-BFGS algorithm is employed to obtain the optimal solution. (5) Softmax classifier is employed as the output layer to identify fault mode and ensure the reliability of diagnosis results. Finally, comparison experiments and results analysis are conducted to verify the effectiveness and practicability of the proposed method.

High-speed three-dimensional measurement technique for object surface with a large range of reflectivity variations.

It is a challenge for any optical method to measure object surfaces with a large range of reflectivity variations. Dark or saturated regions on fringe images may lead to phase and measurement errors. At present, the main defect of the existing methods is the low measurement efficiency. This paper presents a high-speed three-dimensional (3D) measurement for object surfaces with a large range of reflectivity variations. First, we set the intensity of the projected fringes to the maximum, which ensures a better signal-to-noise ratio (SNR) of fringe images compared to the traditional methods. Second, in order to achieve high-speed projection, we transform 12 fringes with 256 gray-value cosine variations to binary fringes and defocus the digital light procession to filter out the higher harmonics. Third, since manually adjusting the camera lens or exposure time is much more time-consuming and not conducive to improving the SNR, we use the color light projection of the projector itself to get multiple groups of fringe sequences with different brightnesses. Finally, the final group of fringe images, used for 3D reconstruction, are formed by choosing the brightest but unsaturated corresponding pixels from multiple groups of fringe images. Experiments verified that the proposed method has the advantages of high-speed measurement, low cost in hardware, high measurement accuracy, a simple algorithm, and ease of extending to several applications.

Amyloid Aggregation of Bacillus circulans Xylanase under Native Conditions and its Modulation by ß-Amyloid-Derived Peptide Fragments.

The aggregation of intrinsically disordered proteins into fibrils is implicated in many neurodegenerative diseases. Amyloid aggregation is a generic property of proteins as evidenced by globular proteins that often form amyloid aggregates under partially denaturing conditions. Recently, multiple lines of evidence have suggested that the amyloid aggregation of globular proteins can also occur under native conditions. Unfortunately, amyloid aggregation under native conditions has been demonstrated in only a handful of cases. Engineering a globular protein's amyloid aggregation might benefit from its fusion to an amyloid-derived fragment with reduced aggregation propensity. Unfortunately, the impacts of such fragments on the amyloid aggregation under native conditions have yet to be examined. In this study, we show that a globular protein, Bacillus circulans xylanase (BCX), can aggregate to form amyloid fibrils under native conditions. When BCX was mixed with or fused to the non-self-aggregating fragments, KLVFWAK and ELVFWAE-which were derived from ß-amyloid (Aß)-they modulated the BCX amyloid aggregation to differing extents. This study also provides insight into a correlation between the kinetic stability and amyloid aggregation of BCX, and supports a view that Aß-derived fragments can be useful for the modulating amyloid aggregation of some, though not all, proteins.

An efficient phase error self-compensation algorithm for nonsinusoidal gating fringes in phase-shifting profilometry.

The phase-shifting method is widely used in fringe projection profilometry. Since both the digital light projector and camera used in a grating projection measurement system are nonlinear pieces of equipment, the grating fringes captured by using the camera do not have a good sinusoidal property, which leads to a three-dimensional measurement error. Although the double-step phase-shifting method has proved that the phase error can be reduced to a large extent, the number of grating fringes is doubled, which affects the measurement efficiency. In this paper, we present an efficient phase error self-compensation algorithm. It transforms the initial wrapped phase into a second wrapped phase and integrates the initial and second wrapped phases to reduce the phase error. The advantage is that the measurement accuracy is close to that of the double-step phase-shifting method without increasing the number of projection fringes; at the same time, the measurement time is shortened, and the measurement efficiency is improved. We have elaborated the proposed algorithm in detail and compared it with the traditional single-step phase-shifting method and the double-step phase-shifting method. Finally, we utilize the proposed algorithm to measure different objects. The results prove its effectiveness.