Radiotherapy-sensitized cancer immunotherapy via cGAS-STING immune pathway by activatable nanocascade reaction.

Radiotherapy-induced immune activation holds great promise for optimizing cancer treatment efficacy. Here, we describe a clinically used radiosensitizer hafnium oxide (HfO2) that was core coated with a MnO2 shell followed by a glucose oxidase (GOx) doping nanoplatform (HfO2@MnO2@GOx, HMG) to trigger ferroptosis adjuvant effects by glutathione depletion and reactive oxygen species production. This ferroptosis cascade potentiation further sensitized radiotherapy by enhancing DNA damage in 4T1 breast cancer tumor cells. The combination of HMG nanoparticles and radiotherapy effectively activated the damaged DNA and Mn2+-mediated cGAS-STING immune pathway in vitro and in vivo. This process had significant inhibitory effects on cancer progression and initiating an anticancer systemic immune response to prevent distant tumor recurrence and achieve long-lasting tumor suppression of both primary and distant tumors. Furthermore, the as-prepared HMG nanoparticles "turned on" spectral computed tomography (CT)/magnetic resonance dual-modality imaging signals, and demonstrated favorable contrast enhancement capabilities activated by under the GSH tumor microenvironment. This result highlighted the potential of nanoparticles as a theranostic nanoplatform for achieving molecular imaging guided tumor radiotherapy sensitization induced by synergistic immunotherapy.

Improved transcranial plane-wave imaging with Learned Speed-of-Sound Maps.

Although transcranial ultrasound plane-wave imaging (PWI) has promising clinical application prospects, studies have shown that variable speed-of-sound (SoS) would seriously damage the quality of ultrasound images. The mismatch between the conventional constant velocity assumption and the actual SoS distribution leads to the general blurring of ultrasound images. The optimization scheme for reconstructing transcranial ultrasound image is often solved using iterative methods like full-waveform inversion. These iterative methods are computationally expensive and based on prior magnetic resonance imaging (MRI) or computed tomography (CT) information. In contrast, the multi-stencils fast marching (MSFM) method can produce accurate time travel maps for the skull with heterogeneous acoustic speed. In this study, we first propose a convolutional neural network (CNN) to predict SoS maps of the skull from PWI channel data. Then, use these maps to correct the travel time to reduce transcranial aberration. To validate the performance of the proposed method, numerical and phantom studies were conducted using a linear array transducer (L11-5v, 128 elements, pitch = 0.3 mm). Numerical simulations demonstrate that for point targets, the lateral resolution of MSFM-restored images increased by 65%, and the center position shift decreased by 89%. For the cyst targets, the eccentricity of the fitting ellipse decreased by 75%, and the center position shift decreased by 58%. In the phantom study, the lateral resolution of MSFM-restored images was increased by 49%, and the position shift was reduced by 1.72 mm. This pipeline, termed AutoSoS, thus shows the potential to correct distortions in real-time transcranial ultrasound imaging.

Sensing and Controlling Strategy for Upper Extremity Prosthetics Based on Piezoelectric Micromachined Ultrasound Transducer.

Surface electromyography (sEMG) is currently the primary method for user control of prosthetic manipulation. Its inherent limitations of low signal-to-noise ratio, limited specificity and susceptibility to noise, however, hinder successful implementation. Ultrasound provides a possible alternative, but current systems with medical probes are expense, bulky and non-wearable. This work proposes an innovative prosthetic control strategy based on a piezoelectric micromachined ultrasound transducer (PMUT) hardware system. Two PMUT-based probes were developed, comprising a 23×26 PMUT array and encapsulated in Ecoflex material. These compact and wearable probes represent a significant improvement over traditional ultrasound probes as they weigh only 1.8 grams and eliminate the need for ultrasound gel. A preliminary test of the probes was performed in non-disabled subjects performing 12 different hand gestures. The two probes were placed perpendicular to the flexor digitorum superficialis and brachioradialis muscles, respectively, to transmit/receive pulse-echo signals reflecting muscle activities. Hand gesture was correctly predicted 96% of the time with only these two probes. The adoption of the PMUT-based strategy greatly reduced the required number of channels, amount of processing circuit and subsequent analysis. The probes show promise for making prosthesis control more practical and economical.

Transcranial Acoustic Metamaterial Parameters Inverse Designed by Neural Networks.

Objective: The objective of this work is to investigate the mapping relationship between transcranial ultrasound image quality and transcranial acoustic metamaterial parameters using inverse design methods. Impact Statement: Our study provides insights into inverse design methods and opens the route to guide the preparation of transcranial acoustic metamaterials. Introduction: The development of acoustic metamaterials has enabled the exploration of cranial ultrasound, and it has been found that the influence of the skull distortion layer on acoustic waves can be effectively eliminated by adjusting the parameters of the acoustic metamaterial. However, the interaction mechanism between transcranial ultrasound images and transcranial acoustic metamaterial parameters is unknown. Methods: In this study, 1,456 transcranial ultrasound image datasets were used to explore the mapping relationship between the quality of transcranial ultrasound images and the parameters of transcranial acoustic metamaterials. Results: The multioutput parameter prediction model of transcranial metamaterials based on deep back-propagation neural network was built, and metamaterial parameters under transcranial image evaluation indices are predicted using the prediction model. Conclusion: This inverse big data design approach paves the way for guiding the preparation of transcranial metamaterials.

Integrative analysis of a novel super-enhancer-associated lncRNA prognostic signature and identifying LINC00945 in aggravating glioma progression.

BACKGROUND: Super-enhancers (SEs), driving high-level expression of genes with tumor-promoting functions, have been investigated recently. However, the roles of super-enhancer-associated lncRNAs (SE-lncRNAs) in tumors remain undetermined, especially in gliomas. We here established a SE-lncRNAs expression-based prognostic signature to choose the effective treatment of glioma and identify a novel therapeutic target. METHODS: Combined analysis of RNA sequencing (RNA-seq) data and ChIP sequencing (ChIP-seq) data of glioma patient-derived glioma stem cells (GSCs) screened SE-lncRNAs. Chinese Glioma Genome Atlas (CGGA) and The Cancer Genome Atlas (TCGA) datasets served to construct and validate SE-lncRNA prognostic signature. The immune profiles and potential immuno- and chemotherapies response prediction value of the signature were also explored. Moreover, we verified the epigenetic activation mechanism of LINC00945 via the ChIP assay, and its effect on glioma was determined by performing the functional assay and a mouse xenograft model. RESULTS: 6 SE-lncRNAs were obtained and identified three subgroups of glioma patients with different prognostic and clinical features. A risk signature was further constructed and demonstrated to be an independent prognostic factor. The high-risk group exhibited an immunosuppressive microenvironment and was higher enrichment of M2 macrophage, regulatory T cells (Tregs), and Cancer-associated fibroblasts (CAFs). Patients in the high-risk group were better candidates for immunotherapy and chemotherapeutics. The SE of LINC00945 was further verified via ChIP assay. Mechanistically, BRD4 may mediate epigenetic activation of LINC00945. Additionally, overexpression of LINC00945 promoted glioma cell proliferation, EMT, migration, and invasion in vitro and xenograft tumor formation in vivo. CONCLUSION: Our study constructed the first prognostic SE-lncRNA signature with the ability to optimize the choice of patients receiving immuno- and chemotherapies and provided a potential therapeutic target for glioma.

Integrative analysis of a novel 5 methylated snoRNA genes prognostic signature in patients with glioma.

Aim: To explore the prognostic value of methylated snoRNA genes in glioma and construct a prognostic risk signature. Materials & methods: We retrieved clinical information and 450K methylation data from The Cancer Genome Atlas and obtained five methylated snoRNA genes. Then we established a risk signature and verified the effect of SNORA71B on glioma cells with functional assays. Results: A risk signature containing five methylated snoRNA genes was constructed and demonstrated to be an independent predictor of glioma prognosis. Silencing SNORA71B restrained the proliferation, migration and invasion of glioma cells and reduced the expression of mesenchymal and cell cycle marker proteins. Conclusion: This study constructed a methylated snoRNA gene risk signature, which may provide a reference for glioma patients' prognosis assessment.

A Novel Defined Endoplasmic Reticulum Stress-Related lncRNA Signature for Prognosis Prediction and Immune Therapy in Glioma.

Gliomas are a group of the most aggressive primary central nervous system tumors with limited treatment options. The abnormal expression of long non-coding RNA (lncRNA) is related to the prognosis of glioma. However, the role of endoplasmic reticulum (ER) stress-associated lncRNAs in glioma prognosis has not been reported. In this paper, we obtained ER stress-related lncRNAs by co-expression analysis, and then a risk signature composed of 6 ER stress-related lncRNAs was constructed using Cox regression analysis. Glioma samples in The Cancer Genome Atlas (TCGA) were separated into high- and low-risk groups based on the median risk score. Compared with the low-risk group, patients in the high-risk group had shorter survival times. Additionally, we verified the predictive ability of these candidate lncRNAs in the testing set. Three glioma patient subgroups (cluster 1/2/3) were identified by consensus clustering. We further analysed the abundance of immune-infiltrating cells and the expression levels of immune checkpoint molecules in both three subgroups and two risk groups, respectively. Immunotherapy and anticancer drug response prediction showed that ER stress-related lncRNA risk signature positively correlates with responding to immune checkpoints and chemosensitivity. Functional analysis showed that these gene sets are enriched in the malignant process of tumors. Finally, LINC00519 was chosen for functional experiments. The silence of LINC00519 restrained the migration and invasion of glioma cells. Hence, those results indicated that ER stress-related lncRNA risk signature could be a potential treatment target and a prognosis biomarker for glioma patients.

Optimized acoustic streaming generated at oblique incident angles to improve ultrasound thrombolysis effect.

BACKGROUND: Combined with thrombolytic drugs and/or microbubbles, ultrasound (US) has been regarded as a useful tool for thrombolysis treatment by taking its advantages of noninvasive, non-ionization, low cost, and accurate targeting of tissues deep in body. Recently, low-intensity pulsed US, which can cause fewer complications by stable cavitation and acoustic streaming other than more violent effects, has attracted broad attention. PURPOSE: However, the thrombolysis effect in practice might not achieve expectation because there is not an ideal parallel multilayered structure between the skin and the targeted vessel. Therefore, the current work aims to better elucidate the influence of US incident angle on the generation of acoustic streaming and thrombolysis effect. METHODS: Systemic numerical and experimental studies, namely, finite element modeling (FEM), particle image velocimetry (PIV), and in vitro thrombolysis measurements, were performed to estimate the acoustical/streaming field pattern, maximum flow velocity, and shear stress on the surface of thrombus, as well as the lysis rate generated at different conditions. These methods aim at verifying the hypothesis that streaming-induced vortices can further accelerate the dissolution of the thrombus and optimized thrombolysis effected can be achieved by adjusting US incident angles. RESULTS: The pool data results showed that the variation trends of the flow velocity and shear stress obtained from FEM simulation and PIV experiments are qualitatively consistent with each other. There exists an optimal incident angle that can maximize the flow velocity and shear stress on the surface of thrombus, so that superior stirring and mixing effect can be generated. Furthermore, as the flow velocity and shear stress on thrombus surface are both highly correlated with the thrombolysis effect (the correlation coefficient R1 = 0.988, R2 = 0.958, respectively), the peak value of lysis rate (increase by at least 5.02%) also occurred at 10°. CONCLUSIONS: The current results demonstrated that, with appropriately determined incident angle, higher thrombolysis rate could be achieved without increasing the driving pressure. It may shed the light on future US thrombolysis planning strategy that, if combined with other advanced technologies (e.g., machine-learning-based image analysis and image-guided adaptive US emission modulation), more efficient thrombolytic effect could be realized while minimizing undesired side-effects caused by excessively high pressure.

Identification of an endoplasmic reticulum stress-related signature associated with clinical prognosis and immune therapy in glioma.

BACKGROUND: Glioma is the most common brain tumor in adults and is characterized by a short survival time and high resistance to chemotherapy. It is imperative to determine the prognosis and therapy-related targets for glioma. Endoplasmic reticulum stress (ERS), as an adaptive protective mechanism, indicates the unfolded protein response (UPR) to determine cell survival and affects chemotherapy sensitivity, which is related to the prognosis of glioma. METHODS: Our research used the TCGA database as the training group and the CGGA database as the testing group. Lasso regression and Cox analysis were performed to construct an ERS signature-based risk score model in glioma. Three methods (time-dependent receiver operating characteristic analysis and multivariate and univariate Cox regression analysis) were applied to assess the independent prognostic effect of texture parameters. Consensus clustering was used to classify the two clusters. In addition, functional and immune analyses were performed to assess the malignant process and immune microenvironment. Immunotherapy and anticancer drug response prediction were adopted to evaluate immune checkpoint and chemotherapy sensitivity. RESULTS: The results revealed that the 7-gene signature strongly predicts glioma prognosis. The two clusters have markedly distinct molecular and prognostic features. The validation group result revealed that the signature has exceptional repeatability and certainty. Functional analysis showed that the ERS-related gene signature was closely associated with the malignant process and prognosis of tumors. Immune analysis indicated that the ERS-related gene signature is strongly related to immune infiltration. Immunotherapy and anticancer drug response prediction indicated that the ERS-related gene signature is positively correlated with immune checkpoint and chemotherapy sensitivity. CONCLUSIONS: Collectively, the ERS-related risk model can provide a novel signature to predict glioma prognosis and treatment.

Ultrasonic Methods for Brain Imaging: Techniques and Implications.

Brain imaging technology is widely used in the diagnosis of brain diseases. Computed tomography and magnetic resonance imaging are the most common imaging modalities used for clinical brain imaging, whereas ultrasound is rarely used because the skull substantially reduces the incident energy of ultrasonic waves to levels too low for imaging. However, remarkable developments of novel technologies in ultrasound brain imaging have been achieved recently, including Doppler-based imaging, contrast agent imaging, ultrasound elastography, and phase compensation imaging. Doppler-based imaging, including ultrafast Doppler imaging and functional ultrasound, is able to obtain reliable cerebral blood volume changes and has the best penetration depth and a better spatiotemporal resolution. Contrast agent brain imaging, including ultrasound localization microscopy, can obtain super spatial resolution vasculature maps over a large region within a few minutes of acquisition and reconstruction time. Ultrasound elastography reflects the stiffness of brain tissues. Phase correction imaging, such as time reversal mirror and spatiotemporal inverse filter, aims at focusing smoothly in the skull. These methods have been widely performed on animal models, newborn children, and adults in preclinical studies, with results demonstrating great potential in the diagnosis and treatment of brain diseases. This review discusses the ultrasound methods developed in recent years for brain imaging and highlights the promising future they hold.

A Novel Defined Pyroptosis-Related Gene Signature for Predicting Prognosis and Treatment of Glioma.

Pyroptosis, a form of programmed cell death, that plays a significant role in the occurrence and progression of tumors, has been frequently investigated recently. However, the prognostic significance and therapeutic value of pyroptosis in glioma remain undetermined. In this research, we revealed the relationship of pyroptosis-related genes to glioma by analyzing whole transcriptome data from The Cancer Genome Atlas (TCGA) dataset serving as the training set and the Chinese Glioma Genome Atlas (CGGA) dataset serving as the validation set. We identified two subgroups of glioma patients with disparate prognostic and clinical features by performing consensus clustering analysis on nineteen pyroptosis-related genes that were differentially expressed between glioma and normal brain tissues. We further derived a risk signature, using eleven pyroptosis-related genes, that was demonstrated to be an independent prognostic factor for glioma. Furthermore, we used Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) to implement functional analysis of our gene set, and the results were closely related to immune and inflammatory responses in accordance with the characteristics of pyroptosis. Moreover, Gene Set Enrichment Analysis (GSEA) results showed that that the high-risk group exhibited enriched characteristics of malignant tumors in accordance with its poor prognosis. Next, we analyzed different immune cell infiltration between the two risk groups using ssGSEA. Finally, CASP1 was identified as a core gene, so we subsequently selected an inhibitor targeting CASP1 and simulated molecular docking. In addition, the inhibitory effect of belnacasan on glioma was verified at the cellular level. In conclusion, pyroptosis-related genes are of great significance for performing prognostic stratification and developing treatment strategies for glioma.

Cavitation-facilitated transmembrane permeability enhancement induced by acoustically vaporized nanodroplets.

Ultrasound-facilitated transmembrane permeability enhancement has attracted broad attention in the treatment of central nervous system (CNS) diseases, by delivering gene/drugs into the deep site of brain tissues with a safer and more effective way. Although the feasibility of using acoustically vaporized nanodroplets to open the blood-brain-barrier (BBB) has previously been reported, the relevant physical mechanisms and impact factors are not well known. In the current study, a nitrocellulose (NC) membrane was used to mimic the multi-layered pore structure of BBB. The cavitation activity and the penetration ability of phase-changed nanodroplets were systemically evaluated at different concentration levels, and compared with the results obtained for SonoVue microbubbles. Passive cavitation detection showed that less intensified but more sustained inertial cavitation (IC) activity would be generated by vaporized nanodroplets than microbubbles. As the results, with a sufficiently high concentration (∼5 × 108/mL), phase-changed nanodroplets were more effective than microbubbles in enabling a fluorescent tracer agent (FITC, 150 kDa) to penetrate deeper and more homogeneously through the NC membrane, and a positive correlation was observed between accumulated IC dose and the amount of penetrated FITC. In vivo studies further confirmed acoustically vaporized nanodroplets performed better than microbubbles by opening the BBB in rats' brains. These results indicated that phase-changed nanodroplets can be used as a safe, efficient and durable agent to achieve satisfactory cavitation-mediated permeability enhancement effect in biomedical applications.

A fully hydrophobic ionogel enables highly efficient wearable underwater sensors and communicators.

Underwater sensing has extraordinary significance in ocean exploration (e.g., marine resources development, marine biology research, and marine environment reconnaissance), but the great difference between the marine environment and the land environment seriously prevents current traditional sensors from being applied in underwater sensing. Herein, we reported a fully hydrophobic ionogel with long-term underwater adhesion and stability as a highly efficient wearable underwater sensor that displays an excellent sensing performance, including high sensitivity, rapid responsiveness and superior durability. Of greater significance, the ionogel sensor showed tremendous potential in underwater sensing applications for communication, posture monitoring and marine biological research.

High-Sensitivity Ultrasonic Guided Wave Monitoring of Pipe Defects Using Adaptive Principal Component Analysis.

Ultrasonic guided wave monitoring is regularly used for monitoring the structural health of industrial pipes, but small defects are difficult to identify owing to the influence of the environment and pipe structure on the guided wave signal. In this paper, a high-sensitivity monitoring algorithm based on adaptive principal component analysis (APCA) for defects of pipes is proposed, which calculates the sensitivity index of the signals and optimizes the process of selecting principal components in principal component analysis (PCA). Furthermore, we established a comprehensive damage index (K) by extracting the subspace features of signals to display the existence of defects intuitively. The damage monitoring algorithm was tested by the dataset collected from several pipe types, and the experimental results show that the APCA method can monitor the hole defect of 0.075% cross section loss ratio (SLR) on the straight pipe, 0.15% SLR on the spiral pipe, and 0.18% SLR on the bent pipe, which is superior to conventional methods such as optimal baseline subtraction (OBS) and average Euclidean distance (AED). The results of the damage index curve obtained by the algorithm clearly showed the change trend of defects; moreover, the contribution rate of the K index roughly showed the location of the defects.

Development and Validation of an Mesenchymal-Related Long Non-Coding RNA Prognostic Model in Glioma.

Glioma is well known as the most aggressive and prevalent primary malignant tumor in the central nervous system. Molecular subtypes and prognosis biomarkers remain a promising research area of gliomas. Notably, the aberrant expression of mesenchymal (MES) subtype related long non-coding RNAs (lncRNAs) is significantly associated with the prognosis of glioma patients. In this study, MES-related genes were obtained from The Cancer Genome Atlas (TCGA) and the Ivy Glioblastoma Atlas Project (Ivy GAP) data sets of glioma, and MES-related lncRNAs were acquired by performing co-expression analysis of these genes. Next, Cox regression analysis was used to establish a prognostic model, that integrated ten MES-related lncRNAs. Glioma patients in TCGA were divided into high-risk and low-risk groups based on the median risk score; compared with the low-risk groups, patients in the high-risk group had shorter survival times. Additionally, we measured the specificity and sensitivity of our model with the ROC curve. Univariate and multivariate Cox analyses showed that the prognostic model was an independent prognostic factor for glioma. To verify the predictive power of these candidate lncRNAs, the corresponding RNA-seq data were downloaded from the Chinese Glioma Genome Atlas (CGGA), and similar results were obtained. Next, we performed the immune cell infiltration profile of patients between two risk groups, and gene set enrichment analysis (GSEA) was performed to detect functional annotation. Finally, the protective factors DGCR10 and HAR1B, and risk factor SNHG18 were selected for functional verification. Knockdown of DGCR10 and HAR1B promoted, whereas knockdown of SNHG18 inhibited the migration and invasion of gliomas. Collectively, we successfully constructed a prognostic model based on a ten MES-related lncRNAs signature, which provides a novel target for predicting the prognosis for glioma patients.

Effect of X-ray irradiation on hepatocarcinoma cells and erythrocytes in salvaged blood.

The broad clinical acceptance of intraoperative blood salvage and its applications in cancer surgery remain controversial. Until now, a method that can safely eliminate cancer cells while preserving erythrocytes does not exist. Here, we investigated whether X-ray generated from linear accelerator irradiation at a certain dose can kill hepatocarcinoma cells while preserving erythrocytes. HepG2, SK-Hep1 or Huh7 cells were mixed into the aliquots of erythrocytes obtained from healthy volunteers. After the mixed cells were exposed to 30 Gy and 50 Gy X-rays irradiation, the viability, clonogenicity, DNA synthesis and tumorigenicity of the tumor cells were determined by the MTT assay, plate colony formation, 5-ethynyl-2'-deoxyuridine incorporation, and subcutaneous xenograft implantation into immunocompromised mice. The ATP, 2,3-DPG, free Hb, osmotic fragility, blood gas variables in erythrocytes and morphology of erythrocytes at 0 h, 12 h, 24 h, 48 h, 72 h after irradiation were analyzed. X-ray irradiation at 30 Gy effectively inhibited the viability, proliferation, and tumorigenicity of HepG2, SK-Hep1 and Huh7 cells without noticeably damaging the ability of oxygen-carrying, membrane integrity and morphology of erythrocytes. Theses results suggest that X-ray at 30 Gy irradiation might be safe to eliminate hepatocarcinoma cells while preserving erythrocytes in salvaged blood.

Ultrasound image edge detection based on a novel multiplicative gradient and Canny operator.

To achieve the fast and accurate segmentation of ultrasound image, a novel edge detection method for speckle noised ultrasound images was proposed, which was based on the traditional Canny and a novel multiplicative gradient operator. The proposed technique combines a new multiplicative gradient operator of non-Newtonian type with the traditional Canny operator to generate the initial edge map, which is subsequently optimized by the following edge tracing step. To verify the proposed method, we compared it with several other edge detection methods that had good robustness to noise, with experiments on the simulated and in vivo medical ultrasound image. Experimental results showed that the proposed algorithm has higher speed for real-time processing, and the edge detection accuracy could be 75% or more. Thus, the proposed method is very suitable for fast and accurate edge detection of medical ultrasound images.

[Self-adaptive beamforming method based on plane wave ultrasound imaging].

In order to improve the resolution, contrast and frame rate of ultrasound imaging, it is necessary to design an adaptive beamforming method for plane wave ultrasound imaging. An optimized minimum variance algorithm that suits plane wave ultrasound imaging was proposed, based on the traditional minimum variance algorithm that combines with the subband beamforming as well as the forward-backward spatial smoothing method in the frequency domain. To verify the effectiveness of the improved algorithm, the matlab software was used. Simulation results showed that full width at half maximum and peak side-lobe level of Optimized MV, Conventional MV, DAS boxcar, and Linear scan methods were 0.08, 0.36, 0.92, 1.42 dB, and -41.1, - 37.3, -16.9, - 34.1 dB, respectively. The improved algorithm can significantly improve the image resolution and contrast, particularly applicable to plane wave ultrasound imaging, compared with the conventional minimum variance algorithm and traditional delay-and-sum method.