Preparation and Application of High Internal Phase Pickering Emulsion Gels Stabilized by Starch Nanocrystal/Tannic Acid Complex Particles.

Herein, the starch nanocrystal/tannic acid (ST) complex particles, which were prepared based on the hydrogen bond between starch nanocrystal (SNC) and tannic acid (TA), were successfully used to stabilize the HIPPE gels. The optimal TA concentration of the ST complex particles resulted in better water dispersibility, surface wettability, and interfacial activity as compared to SNC. The hydrogen bond responsible for the formation of ST complex particles and subsequent stable emulsions was demonstrated by varying the pH and ionic strength of the aqueous phase. Notably, the HIPPE gels stabilized via the ST complex particles can maintain long-term stability for up to three months. The HIPPEs stabilized via the ST complex particles all displayed gel-like features and had smaller droplets and denser droplet networks than the SNC-stabilized HIPPEs. The rheological behavior of HIPPE gels stabilized via the ST complex particles can be readily changed by tuning the mass ratio of SNC and TA as well as pH. Finally, the prepared HIPPE gels used to effectively protect encapsulated ß-carotene against high temperatures and ultraviolet radiation and its controllable release at room temperature were demonstrated. It is anticipated that the aforementioned findings will provide new perspectives on the preparation of Pickering emulsion for delivery systems.

Symbiotic combination of Akkermansia muciniphila and inosine alleviates alcohol-induced liver injury by modulating gut dysbiosis and immune responses.

Background: Alcoholic liver disease (ALD) is exacerbated by disruptions in intestinal microecology and immune imbalances within the gut-liver axis. The present study assesses the therapeutic potential of combining Akkermansia muciniphila (A. muciniphila) with inosine in alleviating alcohol-induced liver injury. Methods: Male C57BL/6 mice, subjected to a Lieber-DeCarli diet with 5% alcohol for 4 weeks, served as the alcoholic liver injury model. Various analyzes, including quantitative reverse transcription polymerase chain reaction (qRT-PCR), ELISA, immunochemistry, 16S rRNA gene sequencing, and flow cytometry, were employed to evaluate liver injury parameters, intestinal barrier function, microbiota composition, and immune responses. Results: Compared to the model group, the A. muciniphila and inosine groups exhibited significantly decreased alanine aminotransferase, aspartate aminotransferase, and lipopolysaccharide (LPS) levels, reduced hepatic fat deposition and neutrophil infiltration, alleviated oxidative stress and inflammation, and increased expression of intestinal tight junction proteins (Claudin-1, Occludin, and ZO-1). These effects were further pronounced in the A. muciniphila and inosine combination group compared to individual treatments. While alcohol feeding induced intestinal dysbiosis and gut barrier disruption, the combined treatment reduced the abundance of harmful bacteria (Oscillibacter, Escherichia/Shigella, and Alistipes) induced by alcohol consumption, promoting the growth of butyrate-producing bacteria (Akkermansia, Lactobacillus, and Clostridium IV). Flow cytometry revealed that alcohol consumption reduced T regulatory (Treg) populations while increasing those of T-helper (Th) 1 and Th17, which were restored by A. muciniphila combined with inosine treatment. Moreover, A. muciniphila and inosine combination increased the expression levels of intestinal CD39, CD73, and adenosine A2A receptor (A2AR) along with enhanced proportions of CD4+CD39+Treg and CD4+CD73+Treg cells in the liver and spleen. The A2AR antagonist KW6002, blocked the beneficial effects of the A. muciniphila and inosine combination on liver injury in ALD mice. Conclusion: This study reveals that the combination of A. muciniphila and inosine holds promise for ameliorating ALD by enhancing the gut ecosystem, improving intestinal barrier function, upregulating A2AR, CD73, and CD39 expression, modulating Treg cells functionality, and regulating the imbalance of Treg/Th17/Th1 cells, and these beneficial effects are partly A2AR-dependent.

Potential Mechanism of Tibetan Medicine Liuwei Muxiang Pills against Colorectal Cancer: Network Pharmacology and Bioinformatics Analyses.

This study aimed to explore the mechanism through which Tibetan medicine Liuwei Muxiang (LWMX) pills acts against colorectal cancer (CRC). We firstly retrieved the active ingredients and the correlated targets of LWMX pills from public databases. The CRC-related targets were determined through bioinformatic analysis of a public CRC dataset. By computing the intersection of the drug-specific and disease-related targets, LWMX pill-CRC interaction networks were constructed using the protein-protein interaction (PPI) method and functional enrichment analysis. Subsequently, we determined the hub genes using machine learning tools and further verified their critical roles in CRC treatment via immune infiltration analysis and molecular docking studies. We identified 81 active ingredients in LWMX pills with 614 correlated targets, 1877 differentially expressed genes, and 9534 coexpression module genes related to CRC. A total of 5 target hub genes were identified among the 108 intersecting genes using machine learning algorithms. The immune infiltration analysis results suggested that LWMX pills could affect the CRC immune infiltration microenvironment by regulating the expression of the target hub genes. Finally, the molecular docking outcomes revealed stable binding affinity between all target hub proteins and the primary active ingredients of LWMX pills. Our findings illustrate the anti-CRC potential and the mechanism of action of LWMX pills and provide novel insights into multitarget medication for CRC treatment.

Coded Excitation for Ultrasonic Testing: A Review.

Originating in the early 20th century, ultrasonic testing has found increasingly extensive applications in medicine, industry, and materials science. Achieving both a high signal-to-noise ratio and high efficiency is crucial in ultrasonic testing. The former means an increase in imaging clarity as well as the detection depth, while the latter facilitates a faster refresh of the image. It is difficult to balance these two indicators with a conventional short pulse to excite the probe, so in general handling methods, these two factors have a trade-off. To solve the above problems, coded excitation (CE) can increase the pulse duration and offers great potential to improve the signal-to-noise ratio with equivalent or even higher efficiency. In this paper, we first review the fundamentals of CE, including signal modulation, signal transmission, signal reception, pulse compression, and optimization methods. Then, we introduce the application of CE in different areas of ultrasonic testing, with a focus on industrial bulk wave single-probe detection, industrial guided wave detection, industrial bulk wave phased array detection, and medical phased array imaging. Finally, we point out the advantages as well as a few future directions of CE.

Bioinspired handheld time-share driven robot with expandable DoFs.

Handheld robots offer accessible solutions with a short learning curve to enhance operator capabilities. However, their controllable degree-of-freedoms are limited due to scarce space for actuators. Inspired by muscle movements stimulated by nerves, we report a handheld time-share driven robot. It comprises several motion modules, all powered by a single motor. Shape memory alloy (SMA) wires, acting as "nerves", connect to motion modules, enabling the selection of the activated module. The robot contains a 202-gram motor base and a 0.8 cm diameter manipulator comprised of sequentially linked bending modules (BM). The manipulator can be tailored in length and integrated with various instruments in situ, facilitating non-invasive access and high-dexterous operation at remote surgical sites. The applicability was demonstrated in clinical scenarios, where a surgeon held the robot to conduct transluminal experiments on a human stomach model and an ex vivo porcine stomach. The time-share driven mechanism offers a pragmatic approach to build a multi-degree-of-freedom robot for broader applications.

Exploring the risk factors of early sepsis after liver transplantation: development of a novel predictive model.

Background: Sepsis is a severe and common complication of liver transplantation (LT) with a high risk of mortality. However, effective tools for evaluating its risk factors are lacking. Therefore, this study identified the risk factors of early post-liver transplantation sepsis and established a nomogram. Methods: We analyzed the risk factors of post-liver transplantation sepsis in 195 patients. Patients with infection and a systemic inflammatory response syndrome (SIRS) score ≥ 2 were diagnosed with sepsis. The predictive indicators were screened with the least absolute shrinkage and selection operator (LASSO) and collinearity analyses to develop a nomogram. The prediction performance of the new nomogram model, Sequential Organ Failure Assessment (SOFA) score, and Modified Early Warning Score (MEWS) was compared through assessment of the area under the curve (AUC), decision curve analysis (DCA), net reclassification index (NRI), and integrated discrimination improvement (IDI). Results: The nomogram was based on postoperative heart rate, creatinine concentration, PaO2/FiO2 ratio < 400 mmHg, blood glucose concentration, and international normalized ratio. The AUC of the nomogram, the SOFA score, and MEWS were 0.782 (95% confidence interval CI: 0.716-0.847), 0.649 (95% CI: 0.571-0.727), and 0.541 (95% CI: 0.469-0.614), respectively. The DCA curves showed that the net benefit rate of the nomogram was higher than that of the SOFA score and MEWS. The NRI and IDI tests revealed better predictive performance for the nomogram than SOFA score and MEWS. Conclusion: Heart rate, creatinine concentration, PaO2/FiO2, glucose concentration, and international normalized ratio should be monitored postoperatively for patients at risk of post-liver transplantation sepsis. The nomogram based on the aforementioned risk factors had a better predictive performance than SOFA score and MEWS.

A Novel Lipid Metabolism and Endoplasmic Reticulum Stress-Related Risk Model for Predicting Immune Infiltration and Prognosis in Colorectal Cancer.

Lipid metabolism and endoplasmic reticulum stress exhibit crosstalk in various cancer types, which are closely associated with the progression of colorectal cancer (CRC). This study constructs a prognostic signature based on lipid metabolism and endoplasmic reticulum stress-related genes (LERGs) for CRC patients, aiming to predict the prognosis and immune response. RNA sequencing and clinical data from the TCGA and GEO databases were analyzed to identify differentially expressed LERGs with prognostic relevance using univariate Cox regression. Subsequently, a risk model was developed using the LASSO regression. CRC patients were stratified into low-risk and high-risk groups based on risk scores, with the high-risk cohort demonstrating a poorer clinical prognosis in multiple databases. The risk model showed robust correlations with clinical features, gene mutations, and treatment sensitivity. Significant differences in immune cell infiltration and the expression of immune-related factors were also detected between risk groups, and elevated scores of cytokines and failure factors were detected in single-cell RNA sequencing analysis. This research indicates that lipid metabolism and endoplasmic reticulum stress in CRC are correlated with tumor progression, an immunosuppressive landscape, and alterations of drug sensitivity. The developed risk model can serve as a powerful prognostic tool, offering critical insights for refining clinical management and optimizing treatment in CRC patients.

Lipid metabolic reprogramming in tumor microenvironment: from mechanisms to therapeutics.

Lipid metabolic reprogramming is an emerging hallmark of cancer. In order to sustain uncontrolled proliferation and survive in unfavorable environments that lack oxygen and nutrients, tumor cells undergo metabolic transformations to exploit various ways of acquiring lipid and increasing lipid oxidation. In addition, stromal cells and immune cells in the tumor microenvironment also undergo lipid metabolic reprogramming, which further affects tumor functional phenotypes and immune responses. Given that lipid metabolism plays a critical role in supporting cancer progression and remodeling the tumor microenvironment, targeting the lipid metabolism pathway could provide a novel approach to cancer treatment. This review seeks to: (1) clarify the overall landscape and mechanisms of lipid metabolic reprogramming in cancer, (2) summarize the lipid metabolic landscapes within stromal cells and immune cells in the tumor microenvironment, and clarify their roles in tumor progression, and (3) summarize potential therapeutic targets for lipid metabolism, and highlight the potential for combining such approaches with other anti-tumor therapies to provide new therapeutic opportunities for cancer patients.

A flexible optoacoustic blood 'stethoscope' for noninvasive multiparametric cardiovascular monitoring.

Quantitative and multiparametric blood analysis is of great clinical importance in cardiovascular disease diagnosis. Although there are various methods to extract blood information, they often require invasive procedures, lack continuity, involve bulky instruments, or have complicated testing procedures. Flexible sensors can realize on-skin assessment of several vital signals, but generally exhibit limited function to monitor blood characteristics. Here, we report a flexible optoacoustic blood 'stethoscope' for noninvasive, multiparametric, and continuous cardiovascular monitoring, without requiring complicated procedures. The optoacoustic blood 'stethoscope' features the light delivery elements to illuminate blood and the piezoelectric acoustic elements to capture light-induced acoustic waves. We show that the optoacoustic blood 'stethoscope' can adhere to the skin for continuous and non-invasive in-situ monitoring of multiple cardiovascular biomarkers, including hypoxia, intravascular exogenous agent concentration decay, and hemodynamics, which can be further visualized with a tailored 3D algorithm. Demonstrations on both in-vivo animal trials and human subjects highlight the optoacoustic blood 'stethoscope''s potential for cardiovascular disease diagnosis and prediction.

Adaptive enhancement of acoustic resolution photoacoustic microscopy imaging via deep CNN prior.

Acoustic resolution photoacoustic microscopy (AR-PAM) is a promising medical imaging modality that can be employed for deep bio-tissue imaging. However, its relatively low imaging resolution has greatly hindered its wide applications. Previous model-based or learning-based PAM enhancement algorithms either require design of complex handcrafted prior to achieve good performance or lack the interpretability and flexibility that can adapt to different degradation models. However, the degradation model of AR-PAM imaging is subject to both imaging depth and center frequency of ultrasound transducer, which varies in different imaging conditions and cannot be handled by a single neural network model. To address this limitation, an algorithm integrating both learning-based and model-based method is proposed here so that a single framework can deal with various distortion functions adaptively. The vasculature image statistics is implicitly learned by a deep convolutional neural network, which served as plug and play (PnP) prior. The trained network can be directly plugged into the model-based optimization framework for iterative AR-PAM image enhancement, which fitted for different degradation mechanisms. Based on physical model, the point spread function (PSF) kernels for various AR-PAM imaging situations are derived and used for the enhancement of simulation and in vivo AR-PAM images, which collectively proved the effectiveness of proposed method. Quantitatively, the PSNR and SSIM values have all achieve best performance with the proposed algorithm in all three simulation scenarios; The SNR and CNR values have also significantly raised from 6.34 and 5.79 to 35.37 and 29.66 respectively in an in vivo testing result with the proposed algorithm.

A universal interface for plug-and-play assembly of stretchable devices.

Stretchable hybrid devices have enabled high-fidelity implantable1-3 and on-skin4-6 monitoring of physiological signals. These devices typically contain soft modules that match the mechanical requirements in humans7,8 and soft robots9,10, rigid modules containing Si-based microelectronics11,12 and protective encapsulation modules13,14. To make such a system mechanically compliant, the interconnects between the modules need to tolerate stress concentration that may limit their stretching and ultimately cause debonding failure15-17. Here, we report a universal interface that can reliably connect soft, rigid and encapsulation modules together to form robust and highly stretchable devices in a plug-and-play manner. The interface, consisting of interpenetrating polymer and metal nanostructures, connects modules by simply pressing without using pastes. Its formation is depicted by a biphasic network growth model. Soft-soft modules joined by this interface achieved 600% and 180% mechanical and electrical stretchability, respectively. Soft and rigid modules can also be electrically connected using the above interface. Encapsulation on soft modules with this interface is strongly adhesive with an interfacial toughness of 0.24 N mm-1. As a proof of concept, we use this interface to assemble stretchable devices for in vivo neuromodulation and on-skin electromyography, with high signal quality and mechanical resistance. We expect such a plug-and-play interface to simplify and accelerate the development of on-skin and implantable stretchable devices.

Ultrasonic imaging through reverberation media.

Thin layered media like thermal barrier and corrosion resistant coating layers, are important components to protect and strengthen the base materials. Nevertheless, the non-destructive testing (NDT) of base materials under thin layer media are still strongly demanded. However, surface and reverberation waves propagating in the top thin layer deteriorate the ultrasonic imaging results of base materials. Particularly, they overwhelm the reflection waves of defects, making ultrasonic NDT of base materials a challenge. These waves are determined by the structural of testing objects and called structural noises. Here, a pre-process of ultrasonic total focusing method is proposed to remove the structural noises. The pre-process utilizes the different similarity characteristics of structural noises and defect signals in diagonal matrices to suppress the noises by principal component analysis. The experimental results show that it can effectively improve the SNR about 5-8 dB and reduce array performance indicators about 30-40%.

Burden and Trends of IBD in 5 Asian Countries From 1990 to 2019: A Comparison With the United States and the United Kingdom.

BACKGROUND: IBD is becoming a global health challenge, with substantial variations in incidence and death rates between Eastern and Western countries. OBJECTIVE: This study aimed to investigate the burden and trends of IBD in 5 Asian countries, the United States, and the United Kingdom. DESIGN: This was a cross-sectional study. SETTING: Data were obtained from Global Burden of Disease 2019 Study. PATIENTS: Patients with IBD were included. MAIN OUTCOME MEASURES: Incidence, death, and age-standardized rates of IBD were measured. RESULTS: The age-standardized incidence and rates of death from IBD gradually decreased worldwide from 1990 to 2019. The age-standardized incidence rate in the United States decreased from 1990 to 2000 and then increased gradually from 2000 to 2019; the age-standardized incidence rates in the United Kingdom, Mongolia, and China increased gradually from 1990 to 2019, whereas in the Democratic People's Republic of Korea, it decreased from 1990 to 1995 and increased gradually from 1995 to 2019. The age-standardized death rate in the Republic of Korea exhibited a rising trend until 1995, fell significantly up to 2015, and then stabilized from 2015 to 2019. The age-standardized death rate in the United States showed a rising trend until 2007, and then decreased gradually from 2007 to 2019, whereas the rate in the United Kingdom showed a rising trend until 2010 and decreased from 2010 to 2019. The age-standardized death rates in China, Mongolia, the Democratic People's Republic of Korea, and Japan decreased gradually from 1990 to 2019. The age-standardized incidence and death rates in the United States and United Kingdom in recent decades were higher than those in the 5 Asian countries. The peak age-standardized incidence rates in the 7 countries were among people of 20 to 60 years of age. The age-standardized death rates in all 7 countries exhibited rising trends with increasing age, with older individuals, particularly those aged ≥70 years, accounting for the most deaths. LIMITATIONS: Limitations of this study include data from different countries with different quality and accuracy. CONCLUSIONS: There have been large variations in the burdens and trends of IBD between 5 Asian countries, the United States, and the United Kingdom during the past 3 decades. These findings may help policymakers to make better public decisions and allocate appropriate resources. See Video Abstract at http://links.lww.com/DCR/B996 . CARGA Y TENDENCIAS DE LA ENFERMEDAD INFLAMATORIA INTESTINAL EN CINCO PASES ASITICOS DESDE HASTA UNA COMPARACIN CON LOS ESTADOS UNIDOS Y EL REINO UNIDO: ANTECEDENTES:La enfermedad inflamatoria intestinal se está convirtiendo en un desafío en la salud mundial, con variaciones sustanciales en las tasas de incidencia y mortalidad entre los países orientales y occidentales.OBJETIVO:Investigar la carga y las tendencias de la enfermedad inflamatoria intestinal en cinco países asiáticos, EE. UU. y el Reino Unido.DISEÑO:Estudio transversal.ESCENARIO:Estudio de carga global de morbilidad 2019.PACIENTES:Enfermedad inflamatoria intestinal.PRINCIPALES MEDIDAS DE RESULTADO:Incidencia, muerte y tasas estandarizadas por edad de enfermedad inflamatoria intestinal.RESULTADOS:Las tasas de incidencia y muerte estandarizadas por edad de la enfermedad inflamatoria intestinal disminuyeron gradualmente en todo el mundo desde 1990 hasta 2019. La tasa de incidencia estandarizada por edad en los EE. UU. disminuyó de 1990 a 2000 y luego aumentó gradualmente de 2000 a 2019, las tasas en el Reino Unido, Mongolia y China aumentaron gradualmente de 1990 a 2019, mientras que la tasa en la República Popular Democrática de Corea disminuyó de 1990 a 1995 y aumentó gradualmente de 1990 a 2019. La tasa de mortalidad estandarizada por edad en la República de Corea exhibió un tendencia ascendente hasta 1995, cayó significativamente hasta 2015 y luego se estabilizó de 2015 a 2019. La tasa de mortalidad estandarizada por edad en los EE. UU. mostró una tendencia ascendente hasta 2007 y luego disminuyó gradualmente de 2007 a 2019, mientras que la tasa en el Reino Unido mostró una tendencia ascendente hasta 2010 y disminuyó de 2010 a 2019. Las tasas de mortalidad estandarizadas por edad en China, Mongolia, la República Popular Democrática de Corea y Japón disminuyeron gradualmente de 1990 a 2019. La tasa de incidencia estandarizada por edad y mortalidad en los EE. UU. y el Reino Unido en la última década fueron más altas que las de los cinco países asiáticos. Las tasas máximas de incidencia estandarizadas por edad en los siete países se dieron entre personas de 20 a 60 años. Las tasas de mortalidad estandarizadas por edad en los siete países exhibieron tendencias crecientes con el aumento de la edad, y las personas mayores, en particular las de ≥70 años, representaron la mayoría de las muertes.LIMITACIONES:Datos de diferentes países con diferente calidad y precisión.CONCLUSIONES:Ha habido grandes variaciones en las cargas y tendencias de la enfermedad inflamatoria intestinal entre cinco países asiáticos, EE. UU. y el Reino Unido durante las últimas tres décadas. Estos hallazgos pueden ayudar a los formuladores de políticas a tomar mejores decisiones públicas y asignar los recursos apropiados. Consulte Video Resumen en http://links.lww.com/DCR/B996 . (Traducción- Dr. Francisco M. Abarca-Rendon ).

Prognostic Significance of mRNA Expression RBBP8 or Its Methylation in Gliomas.

Retinoblastoma-binding protein 8 (RBBP8) affects the prognosis of patients with malignancies through various mechanisms. However, its function in gliomas is unknown. Our study explored the effects of RBBP8 on the prognosis of glioma patients, as well as its regulatory role in the glioma immune microenvironment. We used various bioinformatics methods to analyze the transcriptional profiles and methylation data of RBBP8 in gliomas from multiple databases. Our results showed that the mRNA and protein expression of RBBP8 in gliomas was higher than that in normal tissues and positively correlated with malignant clinical features such as age and WHO grade. A Kaplan-Meier analysis showed that patients with high RBBP8 expression had a poor prognosis. Cox regression demonstrated that RBBP8 was an independent risk indicator and had good diagnostic value for the poor prognosis of glioma. Importantly, RBBP8 was positively correlated with many well-known immune checkpoints (e.g., CTLA4 and PDL-1). Finally, a gene set enrichment analysis revealed that RBBP8 was remarkably enriched in cancer-related pathways such as cell cycle, DNA replication and so on. In conclusion, this study is the first to elaborate on the value of RBBP8 in the pathological process of glioma for anti-tumor immunotherapy. In addition, the expression of RBBP8 and its methylation site, cg05513509, may provide potential targets for glioma therapy.

A Review of Emerging Electromagnetic-Acoustic Sensing Techniques for Healthcare Monitoring.

Conventional electromagnetic (EM) sensing techniques such as radar and LiDAR are widely used for remote sensing, vehicle applications, weather monitoring, and clinical monitoring. Acoustic techniques such as sonar and ultrasound sensors are also used for consumer applications, such as ranging and in vivo medical/healthcare applications. It has been of long-term interest to doctors and clinical practitioners to realize continuous healthcare monitoring in hospitals and/or homes. Physiological and biopotential signals in real-time serve as important health indicators to predict and prevent serious illness. Emerging electromagnetic-acoustic (EMA) sensing techniques synergistically combine the merits of EM sensing with acoustic imaging to achieve comprehensive detection of physiological and biopotential signals. Further, EMA enables complementary fusion sensing for challenging healthcare settings, such as real-world long-term monitoring of treatment effects at home or in remote environments. This article reviews various examples of EMA sensing instruments, including implementation, performance, and application from the perspectives of circuits to systems. The novel and significant applications to healthcare are discussed. Three types of EMA sensors are presented: (1) Chip-based radar sensors for health status monitoring, (2) Thermo-acoustic sensing instruments for biomedical applications, and (3) Photoacoustic (PA) sensing and imaging systems, including dedicated reconstruction algorithms were reviewed from time-domain, frequency-domain, time-reversal, and model-based solutions. The future of EMA techniques for continuous healthcare with enhanced accuracy supported by artificial intelligence (AI) is also presented.

Construction of TiO2(B)/Anatase Heterophase Junctions via a Water-Induced Phase Transformation Strategy for Enhanced Photocatalytic Hydrogen Production.

The development of facile and green solution-phase routes toward the fabrication of TiO2-based heterophase junctions with a delicate control of phase and structure is a challenging task. Herein, we report a simple and convenient method to controllably fabricate TiO2(B)/anatase heterophase junctions, which was successfully realized by utilizing the ideal great solvent of water to treat the presynthesized TiO2(B) nanosheet precursor at a low temperature of 80 °C. On the basis of phase structure transformation and morphology evolution data, the formation of these TiO2(B)/anatase heterophase junctions was reasonably explained by a novel water-induced TiO2(B) → anatase phase transformation mechanism. Benefiting from the desirable structural and photoelectronic advantages of more exposed active sites, enhanced light absorbance, and promoted separation of photogenerated electron-hole pairs, the thus-transformed TiO2(B)/anatase heterophase junctions exhibit fascinating photocatalytic performance in water splitting. Specifically, with the help of Pt as a cocatalyst and methanol as a sacrificial agent, the H2 production rate of optimized TiO2(B)/anatase heterophase junction reaches 6.92 mmol·g-1·h-1, which is almost 7.1 and 2.1 times higher than those of the pristine TiO2(B) nanosheets and the final anatase nanocrystals. More interestingly, the TiO2(B)/anatase heterophase junction also delivers prominent activity toward pure water splitting to simultaneously produce H2 and H2O2, with evolution rates of up to 1.10 and 0.55 mmol·g-1·h-1, respectively. Our work may advance the facile green solvent-mediated synthesis of metal oxide-based heterophase junctions for applications in energy- and environmental-related areas.

Deep and Domain Transfer Learning Aided Photoacoustic Microscopy: Acoustic Resolution to Optical Resolution.

Acoustic resolution photoacoustic micros- copy (AR-PAM) can achieve deeper imaging depth in biological tissue, with the sacrifice of imaging resolution compared with optical resolution photoacoustic microscopy (OR-PAM). Here we aim to enhance the AR-PAM image quality towards OR-PAM image, which specifically includes the enhancement of imaging resolution, restoration of micro-vasculatures, and reduction of artifacts. To address this issue, a network (MultiResU-Net) is first trained as generative model with simulated AR-OR image pairs, which are synthesized with physical transducer model. Moderate enhancement results can already be obtained when applying this model to in vivo AR imaging data. Nevertheless, the perceptual quality is unsatisfactory due to domain shift. Further, domain transfer learning technique under generative adversarial network (GAN) framework is proposed to drive the enhanced image's manifold towards that of real OR image. In this way, perceptually convincing AR to OR enhancement result is obtained, which can also be supported by quantitative analysis. Peak Signal to Noise Ratio (PSNR) and Structural Similarity Index (SSIM) values are significantly increased from 14.74 dB to 19.01 dB and from 0.1974 to 0.2937, respectively, validating the improvement of reconstruction correctness and overall perceptual quality. The proposed algorithm has also been validated across different imaging depths with experiments conducted in both shallow and deep tissue. The above AR to OR domain transfer learning with GAN (AODTL-GAN) framework has enabled the enhancement target with limited amount of matched in vivo AR-OR imaging data.

Ultrasonic autofocus imaging of internal voids in multilayer polymer composite structures.

Multilayer polymer composite structures have been playing important roles in various fields, but the voids inside are not allowed in most scenarios. Ultrasonic technology has been widely used to inspect voids in concrete and metal structures. However, the application of ultrasonic imaging in polymer composite structures is severely blocked by the coating and lamination structures and unstable manufacturing induced sound speed variations. In this paper, a method to autofocus imaging of internal voids in multilayer polymer composite structures with ultrasonic phased array is firstly proposed. The method processes the full matrix capture (FMC) and focuses all voids in the multilayer structure automatically without the prior information of the speed of sound (SOS). The method utilizes the focus criterions to evaluate the focusing quality and then estimates the SOS with differential evolution layer by layer from surface to deep, which improves the robustness and computational efficiency. The method was examined with simulation data from three multilayer structures and well-focused all voids with position error less than 0.6 mm and SOS error less than 6 %. Moreover, the method was verified with the experimental data and focused voids with position error less than 1 mm.

3-D ultrasonic image reconstruction in frequency domain using a virtual transducer model.

In ultrasonic non-destructive testing, image reconstruction is essential to restore the diffracted ultrasound signals to improve the lateral resolution of images. Some reconstruction methods, like DAS-based synthetic aperture imaging, are inefficient, especially for reconstructing three-dimensional (3-D) images. Other methods do not provide high-resolution results, because they neglect the distortion effect introduced by transducer geometry. To overcome these disadvantages, we propose a 3-D ultrasonic image reconstruction method based on synthetic aperture wavenumber algorithm. It considers wave diffraction and transducer geometry effects, and can refocus the reflectors even in non-focal zone, which suits for large depth range imaging. This method builds a virtual transducer model in frequency domain by treating the focused transducer as a virtual planar transducer on its focal plane. In addition, the method uses non-uniform fast Fourier transform and deconvolution operation to achieve the 3-D image reconstruction, which has remarkably improved the efficiency and accuracy. According to the experimental results, the lateral resolution of an image reconstructed by the proposed method can reach 290.2 µm, exceeding the lateral resolution limitation of the 15 MHz focused transducer (523.24 µm). Furthermore, the proposed method only takes 0.744 s to reconstruct a 3-D image with 1000×100×100 pixels, while the time domain SAFT takes about 1163.8 s. It shows the potential for real-time 3-D imaging under advanced hardware.

Visual geometry Group-UNet: Deep learning ultrasonic image reconstruction for curved parts.

Detecting small defects in curved parts through classical monostatic pulse-echo ultrasonic imaging is known to be a challenge. Hence, a robot-assisted ultrasonic testing system with the track-scan imaging method is studied to improve the detecting coverage and contrast of ultrasonic images. To further improve the image resolution, we propose a visual geometry group-UNet (VGG-UNet) deep learning network to optimize the ultrasonic images reconstructed by the track-scan imaging method. The VGG-UNet uses VGG to extract advanced information from ultrasonic images and takes advantage of UNet for small dataset segmentation. A comparison of the reconstructed images on the simulation dataset with ground truth reveals that the peak signal-to-noise ratio (PSNR) and structural similarity index measure (SSIM) can reach 39 dB and 0.99, respectively. Meanwhile, the trained network is also robust against the noise and environmental factors according to experimental results. The experiments indicate that the PSNR and SSIM can reach 32 dB and 0.99, respectively. The resolution of ultrasonic images reconstructed by track-scan imaging method is increased approximately 10 times. All the results verify that the proposed method can improve the resolution of reconstructed ultrasonic images with high computation efficiency.