SWENet: A Physics-Informed Deep Neural Network (PINN) for Shear Wave Elastography.

Shear wave elastography (SWE) enables the measurement of elastic properties of soft materials in a non-invasive manner and finds broad applications in various disciplines. The state-of-the-art SWE methods rely on the measurement of local shear wave speeds to infer material parameters and suffer from wave diffraction when applied to soft materials with strong heterogeneity. In the present study, we overcome this challenge by proposing a physics-informed neural network (PINN)-based SWE (SWENet) method. The spatial variation of elastic properties of inhomogeneous materials has been introduced in the governing equations, which are encoded in SWENet as loss functions. Snapshots of wave motions have been used to train neural networks, and during this course, the elastic properties within a region of interest illuminated by shear waves are inferred simultaneously. We performed finite element simulations, tissue-mimicking phantom experiments, and ex vivo experiments to validate the method. Our results show that the shear moduli of soft composites consisting of matrix and inclusions of several millimeters in cross-section dimensions with either regular or irregular geometries can be identified with excellent accuracy. The advantages of the SWENet over conventional SWE methods consist of using more features of the wave motions and enabling seamless integration of multi-source data in the inverse analysis. Given the advantages of SWENet, it may find broad applications where full wave fields get involved to infer heterogeneous mechanical properties, such as identifying small solid tumors with ultrasound SWE, and differentiating gray and white matters of the brain with magnetic resonance elastography.

Versatile flexible SERS substrate for in situ detection of contaminants in water and fruits based on Ag NPs decorated wrinkled PDMS film.

Flexible surface-enhanced Raman spectroscopy (SERS) substrate has attracted great attention due to its convenient sampling and on-site monitoring capability. However, it is still challenging to fabricate a versatile flexible SERS substrate, which can be used for in situ detection of analytes either in water or on irregular solid surfaces. Here, we report a flexible and transparent SERS substrate based on a wrinkled polydimethylsiloxane (PDMS) film obtained by transferring corrugated structures on the aluminium/polystyrene bilayer film, onto which silver nanoparticles (Ag NPs) are deposited by thermal evaporation. The as-fabricated SERS substrate exhibits a high enhancement factor (∼1.19×105), good signal uniformity (RSD of 6.27%), and excellent batch-to-batch reproducibility (RSD of 7.3%) for rhodamine 6 G. In addition, the Ag NPs@W-PDMS film can maintain high detection sensitivity even after mechanical deformations of bending or torsion for 100 cycles. More importantly, being flexible, transparent, and light, the Ag NPs@W-PDMS film can both float on the water surface and conformally contact with the curved surface for in situ detection. The malachite green in aqueous environment and on apple peel can be easily detected down to 10-6 M with a portable Raman spectrometer. Therefore, it is expected that such a versatile flexible SERS substrate has great potential in on-site, in situ contaminant monitoring for realistic applications.

Shear wave imaging the active constitutive parameters of living muscles.

Shear wave elastography (SWE) of human skeletal muscles allows for measurement of muscle elastic properties in vivo and has important applications in sports medicine and for the diagnosis and treatment of muscle-related diseases. Existing methods of SWE for skeletal muscles rely on the passive constitutive theory and have so far been unable to provide constitutive parameters describing muscle active behavior. In the present paper, we overcome this limitation by proposing a SWE method for quantitative inference of active constitutive parameters of skeletal muscles in vivo. To this end, we investigate the wave motion in a skeletal muscle described by a constitutive model in which muscle active behavior has been defined by an active parameter. An analytical solution relating shear wave velocities to both passive and active material parameters of muscles is derived, based upon which an inverse approach has been developed to evaluate these parameters. To demonstrate the usefulness of the reported method, in vivo experiments were carried out on 10 volunteers to obtain constitutive parameters, particularly those describing active deformation behaviors of living muscles. The results reveal that the active material parameter of skeletal muscles varies with warm-up, fatigue and rest. STATEMENT OF SIGNIFICANCE: Existing shear wave elastography methods are limited to imaging the passive parameters of muscles. This limitation is addressed in the present paper by developing a method to image the active constitutive parameter of living muscles using shear waves. We derived an analytical solution demonstrating the relationship between constitutive parameters of living muscles and shear waves. Relying on the analytical solution, we proposed an inverse method to infer active parameter of skeletal muscles. We performed in vivo experiments to demonstrate the usefulness of the theory and method; the quantitative variation of the active parameter with muscle states such as warm-up, fatigue and rest has been reported for the first time.

Noninvasive measurement of local stress inside soft materials with programmed shear waves.

Mechanical stresses across different length scales play a fundamental role in understanding biological systems' functions and engineering soft machines and devices. However, it is challenging to noninvasively probe local mechanical stresses in situ, particularly when the mechanical properties are unknown. We propose an acoustoelastic imaging-based method to infer the local stresses in soft materials by measuring the speeds of shear waves induced by custom-programmed acoustic radiation force. Using an ultrasound transducer to excite and track the shear waves remotely, we demonstrate the application of the method by imaging uniaxial and bending stresses in an isotropic hydrogel and the passive uniaxial stress in a skeletal muscle. These measurements were all done without the knowledge of the constitutive parameters of the materials. The experiments indicate that our method will find broad applications, ranging from health monitoring of soft structures and machines to diagnosing diseases that alter stresses in soft tissues.

Decreased transthyretin predicts a poor prognosis in primary myelodysplastic syndrome.

Background: This study aims to investigate the prognostic significance of transthyretin in newly diagnosed myelodysplastic syndromes (MDS). Methods: The clinical, laboratory, and follow-up data of 280 newly diagnosed patients with MDS were collected. The relationship between serum transthyretin levels and overall survival (OS) and leukemia-free survival (LFS) were analyzed by Kaplan-Meier analysis and Cox Regression Model. Result: In the MDS cohort, there were 121 cases in the low transthyretin group and 159 cases in the normal transthyretin group. MDS patients with decreased transthyretin had a higher risk score on the Revised International Prognostic Scoring System (IPSS-R) (p = 0.004) and on the molecular IPSS (IPSS-M) (p = 0.005), a higher frequency of TP53 mutation (p < 0.0001), a shorter OS (p < 0.0001) and LFS (p < 0.0001). Multivariate analyses showed that higher IPSS-R and IPSS-M score were adverse factors for OS (p = 0.008 and p = 0.015, respectively) and LFS (p = 0.024 and p = 0.005, respectively). Mutations of TP53 and NRAS were also poor factors for LFS (p = 0.034 and p = 0.018, respectively). Notably, decreased transthyretin was an independent adverse predictor for OS (p = 0.009, HR = 0.097, 95%CI, 0.017-0.561) but not for LFS (p = 0.167) when IPSS-R was included in the Cox regression model and an independent poor one for OS (p = 0.033, HR = 0.267, 95%CI, 0.080-0.898) and LFS (p = 0.024, HR = 0.290, 95%CI, 0.099-0.848) while IPSS-M involved. Conclusion: The results indicate that decreased transthyretin could be an independent adverse prognostic factor in patients with MDS and may provide a supplement to IPSS-R and IPSS-M.

Towards a robust out-of-the-box neural network model for genomic data.

BACKGROUND: The accurate prediction of biological features from genomic data is paramount for precision medicine and sustainable agriculture. For decades, neural network models have been widely popular in fields like computer vision, astrophysics and targeted marketing given their prediction accuracy and their robust performance under big data settings. Yet neural network models have not made a successful transition into the medical and biological world due to the ubiquitous characteristics of biological data such as modest sample sizes, sparsity, and extreme heterogeneity. RESULTS: Here, we investigate the robustness, generalization potential and prediction accuracy of widely used convolutional neural network and natural language processing models with a variety of heterogeneous genomic datasets. Mainly, recurrent neural network models outperform convolutional neural network models in terms of prediction accuracy, overfitting and transferability across the datasets under study. CONCLUSIONS: While the perspective of a robust out-of-the-box neural network model is out of reach, we identify certain model characteristics that translate well across datasets and could serve as a baseline model for translational researchers.

Probing the Mechanical Properties of Large Arteries by Measuring Their Deformation In Vivo with Ultrasound.

Aging and cardiovascular diseases (CVDs) may alter the microstructures of arteries and hence their mechanical properties. Therefore, the measurement of intrinsic artery mechanical properties in vivo can provide valuable information in understanding aging and CVDs and is of clinical significance. The accuracy of advanced ultrasound imaging techniques in measuring the deformation of large arteries under blood pressure is good. However, the assessment of arterial stiffness in vivo remains a challenge. An inverse method to infer the constitutive parameters of arteries in vivo from the blood pressure-arterial radius relationship (P-r curve) is proposed here. The stability analysis reveals that a key constitutive parameter, bθ, which measures the circumferential hardening of an artery, can be reliably identified. An in vivo experiment was performed on the common carotid arteries of 41 healthy volunteers (age: 37 ± 17 y). The value of bθ varies significantly (from 0.55 ± 0.15 for the young group to 0.93 ± 0.29 for the older group, p < 0.01) and is positively correlated with age (r = 0.673, p < 0.01). Furthermore, our theoretical analysis and experimental study have revealed a strong correlation between the clinic-used stiffness index ß and bθ. This study shows that the arterial material parameter bθ can be measured in vivo, which makes it promising as a new biomarker in the diagnosis of CVDs.

Arterial Stiffness Probed by Dynamic Ultrasound Elastography Characterizes Waveform of Blood Pressure.

The clinical and economic burdens of cardiovascular diseases pose a global challenge. Growing evidence suggests an early assessment of arterial stiffness can provide insights into the pathogenesis of cardiovascular diseases. However, it remains difficult to quantitatively characterize local arterial stiffness in vivo. Here we utilize guided axial waves continuously excited and detected by ultrasound to probe local blood pressures and mechanical properties of common carotid arteries simultaneously. In a pilot study of 17 healthy volunteers, we observe a  âˆ¼ 20 % variation in the group velocities of the guided axial waves (5.16 ± 0.55 m/s in systole and 4.31 ± 0.49 m/s in diastole) induced by the variation of the blood pressures. A linear relationship between the square of group velocity and blood pressure is revealed by the experiments and finite element analysis, which enables us to measure the waveform of the blood pressures by the group velocities. Furthermore, we propose a wavelet analysis-based method to extract the dispersion relations of the guided axial waves. We then determined the shear modulus by fitting the dispersion relations in diastole with the leaky Lamb wave model. The average shear modulus of all the volunteers is 166.3 ± 32.8 kPa. No gender differences are found. This study shows the group velocity and dispersion relation of the guided axial waves can be utilized to probe blood pressure and arterial stiffness locally in a noninvasive manner and thus promising for early diagnosis of cardiovascular diseases.

Research Progress of Transparent Electrode Materials with Sandwich Structure.

The nonrenewable nature of fossil energy has led to a gradual decrease in reserves. Meanwhile, as society becomes increasingly aware of the severe pollution caused by fossil energy, the demand for clean energy, such as solar energy, is rising. Moreover, in recent years, electronic devices with screens, such as mobile phones and computers, have had increasingly higher requirements for light transmittance. Whether in solar cells or in the display elements of electronic devices, transparent conductive films directly affect the performance of these devices as a cover layer. In this context, the development of transparent electrodes with low sheet resistance and high light transmittance has become one of the most urgent issues in related fields. At the same time, conventional electrodes can no longer meet the needs of some of the current flexible devices. Because of the high sheet resistance, poor light transmittance, and poor bending stability of the conventional tin-doped indium tin oxide conductive film and fluorine-doped tin oxide transparent conductive glass, there is a need to find alternatives with better performance. In this article, the progress of research on transparent electrode materials with sandwich structures and their advantages is reviewed according to the classification of conductive materials to provide reference for research in related fields.

Mechanical characterization of functionally graded soft materials with ultrasound elastography.

Functionally graded soft materials (FGSMs) with microstructures and mechanical properties exhibiting gradients across a spatial volume to satisfy specific functions have received interests in recent years. How to characterize the mechanical properties of these FGSMs in vivo/in situ and/or in a non-destructive manner is a great challenge. This paper investigates the use of ultrasound elastography in the mechanical characterization of FGSMs. An efficient finite-element model was built to calculate the dispersion relation for surface waves in FGSMs. For FGSMs with large elastic gradients, the measured dispersion relation can be used to identify mechanical parameters. In the case where the elastic gradient is smaller than a certain critical value calculated here, our analysis on transient wave motion in FGSMs shows that the group velocities measured at different depths can infer the local mechanical properties. Experiments have been performed on polyvinyl alcohol (PVA) cryogel to demonstrate the usefulness of the method. Our analysis and the results may not only find broad applications in mechanical characterization of FGSMs but also facilitate the use of shear wave elastography in clinics because many diseases change the local elastic properties of soft tissues and lead to different material gradients. This article is part of the theme issue 'Rivlin's legacy in continuum mechanics and applied mathematics'.

Guided wave elastography of layered soft tissues.

In vivo mechanical characterization of soft biological tissues has broad applications ranging from disease diagnosis to tissue engineering. Shear wave elastography based on the bulk wave theory has been widely used to measure the mechanical properties of soft tissues. Given that most soft tissues basically have layered structures, the dispersive feature of elastic waves should be considered when the thickness of the interested layer is comparable to or smaller than the wavelength. Bearing this fundamental issue in mind, we propose an ultrasound-based guided wave elastography (GWE) method to characterize the mechanical properties of layered soft tissues. The dispersion relations of guided waves in layered structures were derived first, and its explicit expression was achieved. An inverse approach based on the dispersion relation to characterize the mechanical properties of layered soft tissues was then established. Both finite element analysis (FEA) and phantom experiments were carried out to validate the new method. In vivo experiments on forearm skin demonstrate the usefulness of the present method in characterizing layered soft tissues. STATEMENT OF SIGNIFICANCE: Layered soft tissues and artificial soft materials are ubiquitous in both nature and engineering. Imaging their in vivo/in situ mechanical properties finds important applications and remains a great challenge to date. Here, we propose an ultrasound-based guided wave elastography method to in vivo/in situ characterize the elastic properties of layered soft materials. We validate the method via finite element analysis and phantom experiments and further demonstrate its usefulness in practice by performing in vivo measurements on forearm skins. Given that the dispersive feature of elastic waves in layered soft media is considered in our method, it provides the opportunity to assess the intrinsic elastic properties of an individual layer in a non-destructive manner as shown in our experiments.

miR-503 is down-regulated in osteosarcoma and suppressed MG63 proliferation and invasion by targeting VEGFA/Rictor.

We analyzed the expression of miR-503 in osteosarcoma tissues (OS) and discussed the clinical significance of our findings. To provide a theoretical basis for clinical applications, prognosis prediction and treatment of osteosarcoma, we studied the biological function of miR-503 and its mechanism in MG63 osteosarcoma cells. Real-time polymerase chain reaction (PCR) was used to detect the expression of miR-503 in 45 OS tissues and 20 osteochondroma tumors, analyzing the relationship between clinical pathology and follow-up data. Cox multivariate analysis revealed the clinical and pathological features of the osteosarcoma index and the influence of miR-503 expression on OS prognosis. To observe the effect on cell proliferation and invasion, MG-63 cells were transfected with miR-503. The TargetScan and PicTar bioinformatics method was used to analyze the probable target gene of miR-503 and, combined with the function of the target genes, resulted in a final validation of related pathways. miR-503 was significantly down-regulated in primary OS samples (26/45, 57.8%). The median miR-503 expression level in osteosarcoma was two-fold lower than that in osteochondroma (median expression 6.4 and 13.09, respectively, P< 0.05). The less-expressed miR-503 was associated with Enneking stage (p= 0.004) and invasion (p= 0.015) of OC. Patients with low miR-503 expression had poorer overall survival time. In the multivariate analysis, miR-503 was a significant prognostic factor (P= 0.010). miR-503 can inhibit proliferation and invasion in the MG63 cell line. Using bioinformatics, VEGFA and Rictor were determined to be the likely downstream target genes of miR-503. VEGFA, Rictor, Akt and Erk1/2 were negatively regulated by the overexpression of miR-503. In conclusion, miR-503 has significant tumor-suppressor biological activity and is thus likely to become a new target for the treatment of osteosarcoma.

A Two-Dimensional Ruddlesden-Popper Perovskite Nanowire Laser Array based on Ultrafast Light-Harvesting Quantum Wells.

Miniaturized nanowire nanolasers of 3D perovskites feature a high gain coefficient; however, room-temperature optical gain and nanowire lasers from 2D layered perovskites have not been reported to date. A biomimetic approach is presented to construct an artificial ligh-harvesting system in mixed multiple quantum wells (QWs) of 2D-RPPs of (BA)2 (FA)n-1 Pbn Br3n+1 , achieving room-temperature ASE and nanowire (NW) lasing. Owing to the improvement of flexible and deformable characteristics provided by organic BA cation layers, high-density large-area NW laser arrays were fabricated with high photostability. Well-controlled dimensions and uniform geometries enabled 2D-RPPs NWs functioning as high-quality Fabry-Perot (FP) lasers with almost identical optical modes, high quality (Q) factor (ca. 1800), and similarly low lasing thresholds.

2D Ruddlesden-Popper Perovskites Microring Laser Array.

3D organic-inorganic hybrid perovskites have featured high gain coefficients through the electron-hole plasma stimulated emission mechanism, while their 2D counterparts of Ruddlesden-Popper perovskites (RPPs) exhibit strongly bound electron-hole pairs (excitons) at room temperature. High-performance solar cells and light-emitting diodes (LEDs) are reported based on 2D RPPs, whereas light-amplification devices remain largely unexplored. Here, it is demonstrated that ultrafast energy transfer along cascade quantum well (QW) structures in 2D RPPs concentrates photogenerated carriers on the lowest-bandgap QW state, at which population inversion can be readily established enabling room-temperature amplified spontaneous emission and lasing. Gain coefficients measured for 2D RPP thin-films (≈100 nm in thickness) are found about at least four times larger than those for their 3D counterparts. High-density large-area microring arrays of 2D RPPs are fabricated as whispering-gallery-mode lasers, which exhibit high quality factor (Q ≈ 2600), identical optical modes, and similarly low lasing thresholds, allowing them to be ignited simultaneously as a laser array. The findings reveal that 2D RPPs are excellent solution-processed gain materials potentially for achieving electrically driven lasers and ideally for on-chip integration of nanophotonics.

Synthetic green fluorescent protein chromophore analogues with a positive charge at the phenyl-like group.

Synthetic green fluorescent protein (GFP) chromophore analogues with a positive charge at the phenyl-like group have the highly electrophilic amidine carbon, smaller LUMO-HOMO energy gap, red-shifted electronic absorptions and fluorescent emissions, and accelerated E-Z thermoisomerization rates. They are water-labile and their hydrolysis results in ring-opening of the imidazolinone moiety with a half life around 25-37 h in D2O at 25 °C.

A novel molecularly imprinted electrochemical sensor based on graphene quantum dots coated on hollow nickel nanospheres with high sensitivity and selectivity for the rapid determination of bisphenol S.

In this paper, a novel molecularly imprinted electrochemical sensor (MIECS) based on a glassy carbon electrode (GCE) modified with graphene quantum dots (GQDs) coated on hollow nickel nanospheres (hNiNS) for the rapid determination of bisphenol S (BPS) was proposed for the first time. HNiNS and GQDs as electrode modifications were used to enlarge the active area and electron-transport ability for amplifying the sensor signal, while molecularly imprinted polymer (MIP) film was electropolymerized by using pyrrole as monomer and BPS as template to detect BPS via cyclic voltammetry (CV). Scanning electron microscope (SEM), energy-dispersive spectrometry (EDS), CV and differential pulse voltammetry (DPV) were employed to characterize the fabricated sensor. Experimental conditions, such as molar ratio of monomer to template, electropolymerization cycles, pH, incubation time and elution time were optimized. The DPV response of the MIECS to BPS was obtained in the linear range from 0.1 to 50µM with a low limit of detection (LOD) of 0.03µM (S/N = 3) under the optimized conditions. The MIECS exhibited excellent response towards BPS with high sensitivity, selectivity, good reproducibility, and stability. In addition, the proposed MIECS was also successfully applied for the determination of BPS in the plastic samples with simple sample pretreatment.

An "on-off-on" fluorescent probe for ascorbic acid based on Cu-ZnCdS quantum dots and α-MnO2 nanorods.

This work established a fluorescence approach for detecting ascorbic acid (AA) based on Cu-ZnCdS quantum dots (Cu-ZnCdS QDs) and α-MnO2 nanorods. Cu-ZnCdS QDs and α-MnO2 nanorods were characterized by high-resolution transmission electron microscopy (HRTEM), fluorescence spectroscopy, inductively coupled plasma optical emission spectroscopy (ICP-OES) and X-ray diffraction (XRD). In the presence of α-MnO2 nanorods, the fluorescence of Cu-ZnCdS QDs was greatly quenched through the inner filter effect (IFE). Subsequently, AA can trigger the decomposition of the α-MnO2 nanorods which can reduce α-MnO2 to Mn2+ and recover the fluorescence. Under optimal conditions, a linear relation was obtained over the range 5.02-401.77 µM with a 31.62 µM detection limit. Through applying the fluorescent sensing system for detecting AA, a satisfactory result is obtained with recoveries ranging from 89.23% to 110.99%.