Search

Abstract Recently, multi-modal vision-language foundation models have gained significant attention in the medical field. While these models offer great opportunities, they still face crucial challenges, such as the requirement for fine-grained knowledge understanding in computer-aided diagnosis and the capability of utilizing very limited or even no task-specific labeled data in real-world clinical applications. In this study, we present MaCo, a masked contrastive chest X-ray foundation model that tackles these challenges. MaCo explores masked contrastive learning to simultaneously achieve fine-grained image understanding and zero-shot learning for a variety of medical imaging tasks. It designs a correlation weighting mechanism to adjust the correlation between masked chest X-ray image patches and their corresponding reports, thereby enhancing the model’s representation learning capabilities. To evaluate the performance of MaCo, we conducted extensive experiments using 6 well-known open-source X-ray datasets. The experimental results demonstrate the superiority of MaCo over 10 state-of-the-art approaches across tasks such as classification, segmentation, detection, and phrase grounding. These findings highlight the significant potential of MaCo in advancing a wide range of medical image analysis tasks.

Abstract Photonic and plasmonic hybrid nanostructures are the key solution for integrated nanophotonic circuits with ultracompact size but relative low loss. However, the poor tunability and modulability of conventional waveguides makes them cumbersome for optical multiplexing. Here we make use of two‐dimensional molecular crystal, α‐Sb2O3 as a dielectric waveguide via total internal reflection, which shows polarization‐sensitive modulation of the propagating beams due to its large polarization mode dispersion. Both experiments and simulations are performed to verify such concept. These Sb2O3 nanoflakes can be coupled with plasmonic nanowires to form nanophotonic beam splitters and routers which can be easily modulated by changing the polarization of the incidence. It thus provides a robust, exploitable and tunable platform for on‐chip nanophotonics.

Abstract High performance X-ray detector with ultra-high spatial and temporal resolution are crucial for biomedical imaging. This study reports a dynamic direct-conversion CMOS X-ray detector assembled with screen-printed CsPbBr3, whose mobility-lifetime product is 5.2 × 10−4 cm2 V–1 and X-ray sensitivity is 1.6 × 104 µC Gyair –1 cm–2. Samples larger than 5 cm $$\times$$ × 10 cm can be rapidly imaged by scanning this detector at a speed of 300 frames per second along the vertical and horizontal directions. In comparison to traditional indirect-conversion CMOS X-ray detector, this perovskite CMOS detector offers high spatial resolution (5.0 lp mm−1) X-ray radiographic imaging capability at low radiation dose (260 nGy). Moreover, 3D tomographic images of a biological specimen are also successfully reconstructed. These results highlight the perovskite CMOS detector’s potential in high-resolution, large-area, low-dose dynamic biomedical X-ray and CT imaging, as well as in non-destructive X-ray testing and security scanning.

Abstract Objectives This study aims to decrease the scan time and enhance image quality in pediatric total-body PET imaging by utilizing multimodal artificial intelligence techniques. Methods A total of 270 pediatric patients who underwent total-body PET/CT scans with a uEXPLORER at the Sun Yat-sen University Cancer Center were retrospectively enrolled. 18F-fluorodeoxyglucose (18F-FDG) was administered at a dose of 3.7 MBq/kg with an acquisition time of 600 s. Short-term scan PET images (acquired within 6, 15, 30, 60 and 150 s) were obtained by truncating the list-mode data. A three-dimensional (3D) neural network was developed with a residual network as the basic structure, fusing low-dose CT images as prior information, which were fed to the network at different scales. The short-term PET images and low-dose CT images were processed by the multimodal 3D network to generate full-length, high-dose PET images. The nonlocal means method and the same 3D network without the fused CT information were used as reference methods. The performance of the network model was evaluated by quantitative and qualitative analyses. Results Multimodal artificial intelligence techniques can significantly improve PET image quality. When fused with prior CT information, the anatomical information of the images was enhanced, and 60 s of scan data produced images of quality comparable to that of the full-time data. Conclusion Multimodal artificial intelligence techniques can effectively improve the quality of pediatric total-body PET/CT images acquired using ultrashort scan times. This has the potential to decrease the use of sedation, enhance guardian confidence, and reduce the probability of motion artifacts.

Abstract Objectives Commercialized total-body PET scanners can provide high-quality images due to its ultra-high sensitivity. We compared the dynamic, regular static, and delayed 18F-fluorodeoxyglucose (FDG) scans to detect lesions in oncologic patients on a total-body PET/CT scanner. Materials & methods In all, 45 patients were scanned continuously for the first 60 min, followed by a delayed acquisition. FDG metabolic rate was calculated from dynamic data using full compartmental modeling, whereas regular static and delayed SUV images were obtained approximately 60- and 145-min post-injection, respectively. The retention index was computed from static and delayed measures for all lesions. Pearson’s correlation and Kruskal–Wallis tests were used to compare parameters. Results The number of lesions was largely identical between the three protocols, except MRFDG and delayed images on total-body PET only detected 4 and 2 more lesions, respectively (85 total). FDG metabolic rate (MRFDG) image-derived contrast-to-noise ratio and target-to-background ratio were significantly higher than those from static standardized uptake value (SUV) images (P 0.05). Dynamic protocol did not significantly differentiate between benign and malignant lesions just like regular SUV, delayed SUV, and retention index. Conclusion The potential quantitative advantages of dynamic imaging may not improve lesion detection and differential diagnosis significantly on a total-body PET/CT scanner. The same conclusion applied to delayed imaging. This suggested the added benefits of complex imaging protocols must be weighed against the complex implementation in the future. Clinical relevance Total-body PET/CT was known to significantly improve the PET image quality due to its ultra-high sensitivity. However, whether the dynamic and delay imaging on total-body scanner could show additional clinical benefits is largely unknown. Head-to-head comparison between two protocols is relevant to oncological management.

Patients with mild traumatic brain injury have a diverse clinical presentation, and the underlying pathophysiology remains poorly understood. Magnetic resonance imaging is a non-invasive technique that has been widely utilized to investigate neurobiological markers after mild traumatic brain injury. This approach has emerged as a promising tool for investigating the pathogenesis of mild traumatic brain injury. Graph theory is a quantitative method of analyzing complex networks that has been widely used to study changes in brain structure and function. However, most previous mild traumatic brain injury studies using graph theory have focused on specific populations, with limited exploration of simultaneous abnormalities in structural and functional connectivity. Given that mild traumatic brain injury is the most common type of traumatic brain injury encountered in clinical practice, further investigation of the patient characteristics and evolution of structural and functional connectivity is critical. In the present study, we explored whether abnormal structural and functional connectivity in the acute phase could serve as indicators of longitudinal changes in imaging data and cognitive function in patients with mild traumatic brain injury. In this longitudinal study, we enrolled 46 patients with mild traumatic brain injury who were assessed within 2 weeks of injury, as well as 36 healthy controls. Resting-state functional magnetic resonance imaging and diffusion-weighted imaging data were acquired for graph theoretical network analysis. In the acute phase, patients with mild traumatic brain injury demonstrated reduced structural connectivity in the dorsal attention network. More than 3 months of follow-up data revealed signs of recovery in structural and functional connectivity, as well as cognitive function, in 22 out of the 46 patients. Furthermore, better cognitive function was associated with more efficient networks. Finally, our data indicated that small-worldness in the acute stage could serve as a predictor of longitudinal changes in connectivity in patients with mild traumatic brain injury. These findings highlight the importance of integrating structural and functional connectivity in understanding the occurrence and evolution of mild traumatic brain injury. Additionally, exploratory analysis based on subnetworks could serve a predictive function in the prognosis of patients with mild traumatic brain injury.

Given the widespread occurrence of obesity, new strategies are urgently needed to prevent, halt and reverse this condition. We proposed a noninvasive neurostimulation tool, ultrasound deep brain stimulation (UDBS), which can specifically modulate the hypothalamus and effectively regulate food intake and body weight in mice. Fifteen-min UDBS of hypothalamus decreased 41.4% food intake within 2 hours. Prolonged 1-hour UDBS significantly decreased daily food intake lasting 4 days. UDBS also effectively restrained body weight gain in leptin-receptor knockout mice (Sham: 96.19%, UDBS: 58.61%). High-fat diet (HFD) mice treated with 4-week UDBS (15 min / 2 days) reduced 28.70% of the body weight compared to the Sham group. Meanwhile, UDBS significantly modulated glucose-lipid metabolism and decreased the body fat. The potential mechanism is that ultrasound actives pro-opiomelanocortin (POMC) neurons in the hypothalamus for reduction of food intake and body weight. These results provide a noninvasive tool for controlling food intake, enabling systematic treatment of obesity.

We present SOmicsFusion, a software toolbox for ’fusing’ spatial omics with classical biomedical imaging modalities, capitalizing on their inherent correspondences and complementarity when characterizing the same subject. By augmenting radiological and histological images with spatially resolved molecular profiling, this fusion offers a panoramic characterization of the biochemical perturbations underlying pathological conditions, thereby advancing our understanding of diseases like brain disorders and cancers. The cornerstone of SOmicsFusion is a coregistration tool that leverages an innovative two-stage machine learning pipeline to tackle the longstanding challenge of spatially aligning data from fundamentally different modalities, priming them for subsequent fusion analysis that often requires precise pixel-wise correspondence between the datasets. Specifically, the pipeline utilizes an original dimension reduction algorithm for representational domain alignment, followed by a Deep Learning-based method for spatial domain alignment. SOmicsFusion is demonstrated using mass spectrometry imaging (MSI)-mediated spatial metabolomics and four other modalities: magnetic resonance imaging (MRI), microscopy, brain atlas, and spatial transcriptomics. By reducing coregistration errors by 38–69% compared to existing pipelines, SOmicsFusion enhances the precision of associating molecule distribution with anatomy and pathology features, ultimately leading to more statistically robust findings. Furthermore, SOmicsFusion incorporates various downstream analysis tools, including overlay visualization, spatial correlation/co-expression analysis, pansharpening, and automated anatomy annotation. These tools facilitate the extraction of biological insights that would be unattainable through individual modalities alone. For instance, the coregistration and correlation between MSI and in vivo MRI datasets unveil that the spatial heterogeneity in metabolites stems from the temporal heterogeneity in the development of cerebral ischemia-reperfusion injury.

Abstract Current diagnosis of glioma types requires combining both histological features and molecular characteristics, which is an expensive and time-consuming procedure. Determining the tumor types directly from whole-slide images (WSIs) is of great value for glioma diagnosis. This study presents an integrated diagnosis model for automatic classification of diffuse gliomas from annotation-free standard WSIs. Our model is developed on a training cohort (n = 1362) and a validation cohort (n = 340), and tested on an internal testing cohort (n = 289) and two external cohorts (n = 305 and 328, respectively). The model can learn imaging features containing both pathological morphology and underlying biological clues to achieve the integrated diagnosis. Our model achieves high performance with area under receiver operator curve all above 0.90 in classifying major tumor types, in identifying tumor grades within type, and especially in distinguishing tumor genotypes with shared histological features. This integrated diagnosis model has the potential to be used in clinical scenarios for automated and unbiased classification of adult-type diffuse gliomas.

Abstract Cellulose, as a component of green plants, becomes attractive for fabricating biocompatible flexible functional devices but is plagued by hydrophilic properties, which make it easily break down in water by poor mechanical stability. Here we report a class of SiO2-nanoparticle-decorated bacteria-cellulose meta-skin with superior stability in water, excellent machining property, ultrathin thickness, and active bacteria-repairing capacity. We further develop functional ultrasonic metasurfaces based on meta-skin paper-cutting that can generate intricate patterns of ~10 μm precision. Benefited from the perfect ultrasound insulation of surface Cassie-Baxter states, we utilize meta-skin paper-cutting to design and fabricate ultrathin (~20 μm) and super-light (

Abstract Acoustic tweezers can control target movement through the momentum interaction between an acoustic wave and an object. This technology has advantages over optical tweezers for in-vivo cell manipulation due to its high tissue penetrability and strong acoustic radiation force. However, normal cells are difficult to acoustically manipulate because of their small size and the similarity between their acoustic impedance and that of the medium. In this study, we use the heterologous expression of gene clusters to generate genetically engineered bacteria that can produce numerous sub-micron gas vesicles in the bacterial cytoplasm. We show that the presence of the gas vesicles significantly enhances the acoustic sensitivity of the engineering bacteria, which can be manipulated by ultrasound. We find that by employing phased-array-based acoustic tweezers, the engineering bacteria can be trapped into clusters and manipulated in vitro and in vivo via electronically steered acoustic beams, enabling the counter flow or on-demand flow of these bacteria in the vasculature of live mice. Furthermore, we demonstrate that the aggregation efficiency of engineering bacteria in a tumour is improved by utilizing this technology. This study provides a platform for the in-vivo manipulation of live cells, which will promote the progress of cell-based biomedical applications.

Tumor subtyping based on its immune landscape may guide precision immunotherapy. The aims of this study were to identify immune subtypes of adult diffuse gliomas with RNA sequencing data, and to noninvasively predict this subtype using a biologically interpretable radiomic signature from MRI. A subtype discovery dataset (n = 210) from a public database and two radiogenomic datasets (n = 130 and 55, respectively) from two local hospitals were included. Brain tumor microenvironment‐specific signatures were constructed from RNA sequencing to identify the immune types. A radiomic signature was built from MRI to predict the identified immune subtypes. The pathways underlying the radiomic signature were identified to annotate their biological meanings. The reproducibility of the findings was verified externally in multicenter datasets. Three distinctive immune subtypes were identified, including an inflamed subtype marked by elevated hypoxia‐induced immunosuppression, a “cold” subtype that exhibited scarce immune infiltration with downregulated antigen presentation, and an intermediate subtype that showed medium immune infiltration. A 10‐feature radiomic signature was developed to predict immune subtypes, achieving an AUC of 0.924 in the validation dataset. The radiomic features correlated with biological functions underpinning immune suppression, which substantiated the hypothesis that molecular changes can be reflected by radiomic features. The immune subtypes, predictive radiomic signature, and radiomics‐correlated biological pathways were validated externally. Our data suggest that adult‐type diffuse gliomas harbor three distinctive immune subtypes that can be predicted by MRI radiomic features with clear biological significance. The immune subtypes, radiomic signature, and radiogenomic links can be replicated externally.

Abstract Background The total-body positron emission tomography (PET) scanner provides an unprecedented opportunity to scan the whole body simultaneously, thanks to its long axial field of view and ultrahigh temporal resolution. To fully utilize this potential in clinical settings, a dynamic scan would be necessary to obtain the desired kinetic information from scan data. However, in a long dynamic acquisition, patient movement can degrade image quality and quantification accuracy. Methods In this work, we demonstrated a motion correction framework and its importance in dynamic total-body FDG PET imaging. Dynamic FDG scans from 12 subjects acquired on a uEXPLORER PET/CT were included. In these subjects, 7 are healthy subjects and 5 are those with tumors in the thorax and abdomen. All scans were contaminated by motion to some degree, and for each the list-mode data were reconstructed into 1-min frames. The dynamic frames were aligned to a reference position by sequentially registering each frame to its previous neighboring frame. We parametrized the motion fields in-between frames as diffeomorphism, which can map the shape change of the object smoothly and continuously in time and space. Diffeomorphic representations of motion fields were derived by registering neighboring frames using large deformation diffeomorphic metric matching. When all pairwise registrations were completed, the motion field at each frame was obtained by concatenating the successive motion fields and transforming that frame into the reference position. The proposed correction method was labeled SyN-seq. The method that was performed similarly, but aligned each frame to a designated middle frame, was labeled as SyN-mid. Instead of SyN, the method that performed the sequential affine registration was labeled as Aff-seq. The original uncorrected images were labeled as NMC. Qualitative and quantitative analyses were performed to compare the performance of the proposed method with that of other correction methods and uncorrected images. Results The results indicated that visual improvement was achieved after correction of the SUV images for the motion present period, especially in the brain and abdomen. For subjects with tumors, the average improvement in tumor SUVmean was 5.35 ± 4.92% (P = 0.047), with a maximum improvement of 12.89%. An overall quality improvement in quantitative Ki images was also observed after correction; however, such improvement was less obvious in K1 images. Sampled time–activity curves in the cerebral and kidney cortex were less affected by the motion after applying the proposed correction. Mutual information and dice coefficient relative to the reference also demonstrated that SyN-seq improved the alignment between frames over non-corrected images (P = 0.003 and P = 0.011). Moreover, the proposed correction successfully reduced the inter-subject variability in Ki quantifications (11.8% lower in sampled organs). Subjective assessment by experienced radiologists demonstrated consistent results for both SUV images and Ki images. Conclusion To conclude, motion correction is important for image quality in dynamic total-body PET imaging. We demonstrated a correction framework that can effectively reduce the effect of random body movements on dynamic images and their associated quantification. The proposed correction framework can potentially benefit applications that require total-body assessment, such as imaging the brain-gut axis and systemic diseases.

Abstract Purpose Efforts have been made both to avoid invasive blood sampling and to shorten the scan duration for dynamic positron emission tomography (PET) imaging. A total-body scanner, such as the uEXPLORER PET/CT, can relieve these challenges through the following features: First, the whole-body coverage allows for noninvasive input function from the aortic arteries; second, with a dramatic increase in sensitivity, image quality can still be maintained at a high level even with a shorter scan duration than usual. We implemented a dual-time-window (DTW) protocol for a dynamic total-body 18F-FDG PET scan to obtain multiple kinetic parameters. The DTW protocol was then compared to several other simplified quantification methods for total-body FDG imaging that were proposed for conventional setup. Methods The research included 28 patient scans performed on an uEXPLORER PET/CT. By discarding the corresponding data in the middle of the existing full 60-min dynamic scan, the DTW protocol was simulated. Nonlinear fitting was used to estimate the missing data in the interval. The full input function was obtained from 15 subjects using a hybrid approach with a population-based image-derived input function. Quantification was carried out in three areas: the cerebral cortex, muscle, and tumor lesion. Micro- and macro-kinetic parameters for different scan durations were estimated by assuming an irreversible two-tissue compartment model. The visual performance of parametric images and region of interest-based quantification in several parameters were evaluated. Furthermore, simplified quantification methods (DTW, Patlak, fractional uptake ratio [FUR], and standardized uptake value [SUV]) were compared for similarity to the reference net influx rate K i . Results K i and K 1 derived from the DTW protocol showed overall good consistency (P

Acoustic tweezers, capable of complicated manipulation of bioparticles by acoustic radiation forces using a noninvasive and noncontact approach, are an innovative technology for patterning assemble organoids. Hence, acoustic tweezers exhibit considerable potential for forming programmable patterning of organoids with specific spatial structures. Furthermore, heterogeneous assembloids with complex arrangement patterns can be built through sequential assembling and culturing to explore polarized tissue development or disease metastasis in multiple organs. This study focuses on the structural assembly of organoids using an ultrasonic 2D matrix array to generate real‐time switching of different acoustic fields. In addition, a local renal injured assembloid is fabricated to study and verify its application in tissue engineering and disease modeling.

Abstract Radioimmunotherapy (RIT) is an advanced physical therapy used to kill primary cancer cells and inhibit the growth of distant metastatic cancer cells. However, challenges remain because RIT generally has low efficacy and serious side effects, and its effects are difficult to monitor in vivo. This work reports that Au/Ag nanorods (NRs) enhance the effectiveness of RIT against cancer while allowing the therapeutic response to be monitored using activatable photoacoustic (PA) imaging in the second near‐infrared region (NIR‐II, 1000–1700 nm). The Au/Ag NRs can be etched using high‐energy X‐ray to release silver ions (Ag+), which promotes dendritic cell (DC) maturation, enhances T‐cell activation and infiltration, and effectively inhibits primary and distant metastatic tumor growth. The survival time of metastatic tumor‐bearing mice treated with Au/Ag NR‐enhanced RIT is 39 days compared with 23 days in the PBS control group. Furthermore, the surface plasmon absorption intensity at 1040 nm increases fourfold after Ag+ are released from the Au/Ag NRs, allowing X‐ray activatable NIR‐II PA imaging to monitor the RIT response with a high signal‐to‐background ratio of 24.4. Au/Ag NR‐based RIT has minimal side effects and shows great promise for precise cancer RIT.

Peripheral focused ultrasound stimulation (pFUS) has gained increasing attention in the past few decades, because it can be delivered to peripheral nerves, neural endings, or sub-organs. With different stimulation parameters, ultrasound stimulation could induce different modulation effects. Depending on the transmission medium, pFUS can be classified as body-coupled US stimulation, commonly used for therapeutics or neuromodulation, or as an air-coupled contactless US haptic system, which provides sensory inputs and allows distinct human-computer interaction paradigms. Despite growing interest in pFUS, the underlying working mechanisms remain only partially understood, and many applications are still in their infancy. This review focused on existing applications, working mechanisms, the latest progress, and future directions of pFUS. In terms of therapeutics, large-sample randomized clinical trials in humans are needed to translate these state of art techniques into treatments for specific diseases. The airborne US for human-computer interaction is still in its preliminary stage, but further efforts in task-oriented US applications might provide a promising interaction tool soon.

The imbalance between oxidants and antioxidants in cancer cells would evoke oxidative stress-induced cell death, which has been demonstrated to be highly effective in treating malignant tumors. Sonodynamic therapy (SDT) adopts ultrasound (US) as the excitation source to induce the production of reactive oxygen species (ROS), which emerges as a noninvasive therapeutic strategy with deep tissue penetration depth and high clinical safety. Herein, we construct novel sonoactivated oxidative stress amplification nanoplatforms by coating MnO2 on Au nanoparticle-anchored black phosphorus nanosheets and decorating soybean phospholipid subsequently (Au/BP@MS). The Au/BP@MS exhibit increased ROS generation efficiency under US irradiation in tumor tissues due to Au/BP nanosensitizer-induced improvement of electron-hole separation as well as MnO2-mediated O2 generation and GSH depletion, thus leading to notable inhibition effect on tumor growth. Moreover, tumor microenvironment-responsive biodegradability of Au/BP@MS endows them with enhanced magnetic resonance imaging guidance and clinical potential for cancer theranostics.

Mechanosensitive channel of large conductance (MscL) is the most thoroughly studied mechanosensitive channel in prokaryotes. Owing to its small molecular weight, clear mechanical gating mechanism, and nanopore forming ability upon opening, accumulating studies are implemented in regulating cell function by activating mechanosensitive channel of large conductance in mammalian cells. This study aimed to investigate the potentials of mechanosensitive channel of large conductance as a nanomedicine and a mechano-inducer in non-small cell lung cancer (NSCLC) A549 cells from the view of molecular pathways and acoustics. The stable cytoplasmic vacuolization model about NSCLC A549 cells was established via the targeted expression of modified mechanosensitive channel of large conductance channels in different subcellular organelles. Subsequent morphological changes in cellular component and expression levels of cell death markers are analyzed by confocal imaging and western blots. The permeability of mitochondrial inner membrane (MIM) exhibited a vital role in cytoplasmic vacuolization formation. Furthermore, mechanosensitive channel of large conductance channel can be activated by low intensity focused ultrasound (LIFU) in A549 cells, and the suppression of A549 tumors in vivo was achieved by LIFU with sound pressure as low as 0.053 MPa. These findings provide insights into the mechanisms underlying non-apoptotic cell death, and validate the nanochannel-based non-invasive ultrasonic strategy for cancer therapy.

A noninvasive brain–computer interface is a central task in the comprehensive analysis and understanding of the brain and is an important challenge in international brain-science research. Current implanted brain–computer interfaces are cranial and invasive, which considerably limits their applications. The development of new noninvasive reading and writing technologies will advance substantial innovations and breakthroughs in the field of brain–computer interfaces. Here, we review the theory and development of the ultrasound brain functional imaging and its applications. Furthermore, we introduce latest advancements in ultrasound brain modulation and its applications in rodents, primates, and human; its mechanism and closed-loop ultrasound neuromodulation based on electroencephalograph are also presented. Finally, high-frequency acoustic noninvasive brain–computer interface is prospected based on ultrasound super-resolution imaging and acoustic tweezers.

Targeted therapy of Parkinson’s disease is an important challenge because of the blood–brain barrier limitation. Here, we propose a natural killer cell membrane biomimetic nanocomplex (named BLIPO-CUR) delivered via the meningeal lymphatic vessel (MLV) route to further the therapeutic efficacy of Parkinson’s disease. The membrane incorporation enables BLIPO-CUR to target the damaged neurons, thus improving their therapeutic efficacy through clearing reactive oxygen species, suppressing the aggregation of α-synuclein, and inhibiting the spread of excess α-synuclein species. Compared with the conventional intravenous injection, this MLV administration can enhance the delivered efficiency of curcumin into the brain by ~20 folds. The MLV route administration of BLIPO-CUR enhances the treatment efficacy of Parkinson’s disease in mouse models by improving their movement disorders and reversing neuron death. Our findings highlight the great potential of MLV route administration used as targeted delivery of drugs to the brain, holding a great promise for neurodegenerative disease therapy.

Abstract Background To explore the feasibility of corrected slack angle acquired from two-dimensional shear wave elastography (2D-SWE) for quantitating the spasticity of medial gastrocnemius (MG) in stroke patients. Methods Consecutive stroke patients with spastic MG and matched healthy controls were recruited. Intra- and interobserver reliability of 2D-SWE measurement were evaluated, and the correlation between corrected slack angle and modified Ashworth scale (MAS) score was examined. The corrected slack angle before and after botulinum toxin A (BoNT-A) injection was compared and its diagnostic performance in classifying the severity of spasticity were assessed with receiver operating characteristic (ROC) curve analysis. Results The intra- (0.791 95% CI 0.432–0.932) and interobserver (0.751 95% CI 0.382–0.916) reliability of slack angle acquired with 2D-SWE were good. Significant correlation was found between corrected slack angle and MAS score (R = − 0.849, p

MR guided focused ultrasound (MRgFUS) therapy has been a promising treatment modality for many neurological disorders. However, the lack of real-time image processing software platform sets barriers for relevant pre-clinical researches. This work intends to develop an integrated software for MRgFUS therapy. The software contains three functional modules: a communication module, an image post-processing module, and a visualization module. The communication module provides a data interface with an open-source MR image reconstruction platform (Gadgetron) to receive the reconstructed MR images in real-time. The post-processing module contains the algorithms of image coordinate registration, focus localization by MR acoustic radiation force imaging (MR-ARFI), temperature and thermal dose calculations, motion correction, and temperature feedback control. The visualization module displays monitoring information and provides a user-machine interface. The software was tested to be compatible with systems from two different vendors and validated in multiple scenarios for MRgFUS. The software was tested in many ex vivo and in vivo experiments to validate its functions. The in vivo transcranial focus localization experiments were carried out for targeting the focused ultrasound in neuromodulation.

The chemical composition and spectra of rubies heat-treated with high temperatures (above 1200 °C) from Madagascar, Mozambique and Tanzania were analyzed by electron microprobe, LA-ICP-MS, Fourier transform infrared spectroscopy, Raman spectroscopy and UV-VIS spectroscopy. Compared with untreated rubies, the red hue of treated ruby intensifies while its blue tint diminishes, leading to increased cracks. The infrared spectra exhibit a distinct absorption peak at 3738 cm−1, attributed to water because of thermal treatment. After heat treatment, the absorption intensity decreases. Ultraviolet radiation reveals an enhancement in the electron transition of Cr3+ and ion transition of Fe3+ and Fe2+, with a shift towards shorter wavelengths observed in the absorption bandwidth. These can be utilized to indicate the basis of ruby identification through heat treatment.

Existing high-performance deep learning methods typically rely on large training datasets with high-quality manual annotations, which are difficult to obtain in many clinical applications. Here, the authors introduce an open-source framework to handle imperfect training datasets.

MR quantitative T1ρ mapping has gained increasing attention due to its capability to study low-frequency motional processes and chemical exchange in biological tissues. At ultra-high fields, the chemical exchange and proton diffusion in biological tissues should be more prominent. In this study, for the first time, we aim to test the feasibility of brain T1ρ mapping at 5.0 T MR scanner and compare the T1ρ values estimated using 3.0 T and 5.0 T scanners. Preliminary experimental results show that 5.0 T achieves T1ρ-weighted images with a higher signal-to-noise ratio than those acquired at 3.0T. The SNR benefit at 5.0 T is more obvious in high-resolution imaging. The T1ρ quantifications at 5.0 T are: Corpus callosum (67.4 ± 1.9 ms), Corona radiate (71.5 ± 1.8 ms), Superior frontal gyrus (67.6 ± 2.5 ms), Putamen (58.9 ± 1.2 ms), Centrum semiovale (84.0 ± 6.3 ms). Statistical analysis results indicate that the T1ρ values at 5.0 T show no significant difference with those obtained at 3.0 T (all p > 0.05). The interfield agreements in terms of T1ρ values between 3.0 T and 5.0 T were substantial (all ICCs >0.7). The coefficients of variation for T1ρ measurements from 3.0 T to 5.0 T were all less than 6.50% (2.28%–6.32%).

BackgroundCardiovascular magnetic resonance (CMR) imaging at ultra-high fields (UHF) such as 7T has encountered many challenges such as faster T2* relaxation, stronger B0 and B1+ field inhomogeneities and additional safety concerns due to increased specific absorption rate (SAR) and peripheral nervous stimulation (PNS). Recently, a new line of 5T whole body MRI system has become available, and this study aims at evaluating the performance and benefits of this new UHF system for CMR imaging.MethodsGradient echo (GRE) CINE imaging was performed on healthy volunteers at both 5 and 3T, and was compared to balanced steady-state-free-procession (bSSFP) CINE imaging at 3T as reference. Higher spatial resolution GRE CINE scans were additionally performed at 5T. All scans at both fields were performed with ECG-gating and breath-holding. Image quality was blindly evaluated by two radiologists, and the cardiac functional parameters (e.g., EDV/ESV/mass/EF) of the left and right ventricles were measured for statistical analyses using the Wilcoxon signed-rank test and Bland-Altman analysis.ResultsCompared to 3T GRE CINE imaging, 5T GRE CINE imaging achieved comparable or improved image quality with significantly superior SNR and CNR, and it has also demonstrated excellent capability for high resolution (1.0 × 1.0 × 6.0 mm3) imaging. Functional assessments from 5T GRE CINE images were highly similar with the 3T bSSFP CINE reference.ConclusionsThis pilot study has presented the initial evaluation of CMR CINE imaging at 5T UHF, which yielded superior image quality and accurate functional quantification when compared to 3T counterparts. Along with reliable ECG gating, the new 5T UHF system has the potential to achieve well-balanced performance for CMR applications.

PurposeTo develop and evaluate an automatic segmentation method of arterial vessel walls and plaques, which is beneficial for facilitating the arterial morphological quantification in magnetic resonance vessel wall imaging (MRVWI).MethodsMRVWI images acquired from 124 patients with atherosclerotic plaques were included. A convolutional neural network-based deep learning model, namely VWISegNet, was used to extract the features from MRVWI images and calculate the category of each pixel to facilitate the segmentation of vessel wall. Two-dimensional (2D) cross-sectional slices reconstructed from all plaques and 7 main arterial segments of 115 patients were used to build and optimize the deep learning model. The model performance was evaluated on the remaining nine-patient test set using the Dice similarity coefficient (DSC) and average surface distance (ASD).ResultsThe proposed automatic segmentation method demonstrated satisfactory agreement with the manual method, with DSCs of 93.8% for lumen contours and 86.0% for outer wall contours, which were higher than those obtained from the traditional U-Net, Attention U-Net, and Inception U-Net on the same nine-subject test set. And all the ASD values were less than 0.198 mm. The Bland–Altman plots and scatter plots also showed that there was a good agreement between the methods. All intraclass correlation coefficient values between the automatic method and manual method were greater than 0.780, and greater than that between two manual reads.ConclusionThe proposed deep learning-based automatic segmentation method achieved good consistency with the manual methods in the segmentation of arterial vessel wall and plaque and is even more accurate than manual results, hence improved the convenience of arterial morphological quantification.

Introduction11C-labeled Pittsburgh compound B (11C-PiB) PET imaging can provide information for the diagnosis of Alzheimer's disease (AD) by quantifying the binding of PiB to β-amyloid deposition in the brain. Quantification index, such as standardized uptake value ratio (SUVR) and distribution volume ratio (DVR), has been exploited to effectively distinguish between healthy and subjects with AD. However, these measures require a long wait/scan time, as well as the selection of an optimal reference region. In this study, we propose an alternate measure named amyloid quantification index (AQI), which can be obtained with the first 30-min scan without the selection of the reference region.Methods11C-labeled Pittsburgh compound B PET scan data were obtained from the public dataset “OASIS-3”. A total of 60 mild subjects with AD and 60 healthy controls were included, with 50 used for training and 10 used for testing in each group. The proposed measure AQI combines information of clearance rate and mid-phase PIB retention in featured brain regions from the first 30-min scan. For each subject in the training set, AQI, SUVR, and DVR were calculated and used for classification by the logistic regression classifier. The receiver operating characteristic (ROC) analysis was performed to evaluate the performance of these measures. Accuracy, sensitivity, and specificity were reported. The Kruskal–Wallis test and effect size were also performed and evaluated for all measures. Then, the performance of three measures was further validated on the testing set using the same method. The correlations between these measures and clinical MMSE and CDR-SOB scores were analyzed.ResultsThe Kruskal–Wallis test suggested that AQI, SUVR, and DVR can all differentiate between the healthy and subjects with mild AD (p < 0.001). For the training set, ROC analysis showed that AQI achieved the best classification performance with an accuracy rate of 0.93, higher than 0.88 for SUVR and 0.89 for DVR. The effect size of AQI, SUVR, and DVR were 2.35, 2.12, and 2.06, respectively, indicating that AQI was the most effective among these measures. For the testing set, all three measures achieved less superior performance, while AQI still performed the best with the highest accuracy of 0.85. Some false-negative cases with below-threshold SUVR and DVR values were correctly identified using AQI. All three measures showed significant and comparable correlations with clinical scores (p < 0.01).ConclusionAmyloid quantification index combines early-phase kinetic information and a certain degree of β-amyloid deposition, and can provide a better differentiating performance using the data from the first 30-min dynamic scan. Moreover, it was shown that clinically indistinguishable AD cases regarding PiB retention potentially can be correctly identified.

The plasmonic photothermal effects of metal nanostructures have recently become a new priority of studies in the field of nano-optics. Controllable plasmonic nanostructures with a wide range of responses are crucial for effective photothermal effects and their applications. In this work, self-assembled aluminum nano-islands (Al NIs) with a thin alumina layer are designed as a plasmonic photothermal structure to achieve nanocrystal transformation via multi-wavelength excitation. The plasmonic photothermal effects can be controlled by the thickness of the Al2O3 and the intensity and wavelength of the laser illumination. In addition, Al NIs with an alumina layer have good photothermal conversion efficiency even in low temperature environments, and the efficiency will not decline significantly after storage in air for 3 months. Such an inexpensive Al/Al2O3 structure with a multi-wavelength response provides an efficient platform for rapid nanocrystal transformation and a potential application for the wide-band absorption of solar energy.

Rheumatoid arthritis (RA) is a common autoimmune disease characterized by chronic and progressive inflammation of the synovium. Focused ultrasound therapy is an increasingly attractive alternative for treating RA owing to its noninvasiveness; however, it remains unclear which immune subsets respond to ultrasound stimulation. In this study, we showed that spleen-targeted low-frequency pulsed focused ultrasound (LFPFU) effectively improved the severity of arthritis in an arthritis mouse model established in DBA/1J mice. Additionally, we performed in-depth immune profiling of spleen samples from RA mice, RA mice that underwent ultrasound therapy, and healthy controls using mass cytometry along with extensive antibody panels and identified the immune composition of 14 cell populations, including CD4+/CD8+ T cells, B cells, natural killer cells, and dendritic cells. Moreover, multidimensional analysis according to cell-surface markers and phenotypes helped in identifying 4 and 5 cell subpopulations among T and myeloid cells, respectively, with 6 T cell subsets and 3 myeloid cell subsets responsive to ultrasound therapy among the 3 groups. Of these cell subsets, CD8+ T cell subsets showed a unique response to ultrasound stimulation in RA mice. Specifically, CD8+ T cells show a noticeable correlation with the degree of arthritis progression and could serve as an indicator for spleen-focused ultrasound-based therapy. Furthermore, single-cell RNA sequencing of spleen cells revealed the importance of T, B, and myeloid cell populations in the anti-inflammatory pathway. These results elucidated the unique cell subsets and transcriptome of splenic cells responsive to LFPFU and demonstrated the potential of spleen-focused ultrasound stimulation in the treatment of inflammatory diseases.

Background68 Ga-prostate-specific membrane antigen (PSMA) PET/MRI has become an effective imaging method for prostate cancer. The purpose of this study was to use deep learning methods to perform low-dose image restoration on PSMA PET/MRI and to evaluate the effect of synthesis on the images and the medical diagnosis of patients at risk of prostate cancer.MethodsWe reviewed the 68 Ga-PSMA PET/MRI data of 41 patients. The low-dose PET (LDPET) images of these patients were restored to full-dose PET (FDPET) images through a deep learning method based on MRI priors. The synthesized images were evaluated according to quantitative scores from nuclear medicine doctors and multiple imaging indicators, such as peak-signal noise ratio (PSNR), structural similarity (SSIM), normalization mean square error (NMSE), and relative contrast-to-noise ratio (RCNR).ResultsThe clinical quantitative scores of the FDPET images synthesized from 25%- and 50%-dose images based on MRI priors were 3.84±0.36 and 4.03±0.17, respectively, which were higher than the scores of the target images. Correspondingly, the PSNR, SSIM, NMSE, and RCNR values of the FDPET images synthesized from 50%-dose PET images based on MRI priors were 39.88±3.83, 0.896±0.092, 0.012±0.007, and 0.996±0.080, respectively.ConclusionAccording to a combination of quantitative scores from nuclear medicine doctors and evaluations with multiple image indicators, the synthesis of FDPET images based on MRI priors using and 50%-dose PET images did not affect the clinical diagnosis of prostate cancer. Prostate cancer patients can undergo 68 Ga-PSMA prostate PET/MRI scans with radiation doses reduced by up to 50% through the use of deep learning methods to synthesize FDPET images.

Chemical exchange saturation transfer (CEST) MRI, versatile for detecting endogenous mobile proteins and tissue pH, has proved valuable in tumor imaging. However, CEST MRI scans are often performed under non-equilibrium conditions, which confound tissue characterization. This study proposed a quasi-steady-state (QUASS) CEST MRI algorithm to standardize fast and accurate tumor imaging at 3 T. The CEST signal evolution was modeled by longitudinal relaxation rate during relaxation delay (Td) and spinlock relaxation during RF saturation time (Ts), from which the QUASS CEST effect is derived. Numerical simulation and human MR imaging experiments (7 healthy volunteers and 19 tumor patients) were conducted at 3 T to compare the CEST measurements obtained under two representative experimental conditions. In addition, amide proton transfer (APT), combined magnetization transfer (MT) and nuclear overhauser enhancement (NOE) effects, and direct water saturation were isolated using a 3-pool Lorentzian fitting in white matter and gray matter of healthy volunteers and for patients in the contralateral normal-appearing white matter and tumor regions. Finally, the student's t-test was performed between conventional and QUASS CEST measurements. The routine APT and combined MT & NOE measures significantly varied with Ts and Td (P .05), indicating the accuracy and robustness of QUASS CEST MRI for tumor imaging. To summarize, the QUASS CEST reconstruction algorithm enables fast and accurate tumor CEST imaging at 3 T, promising to expedite and standardize clinical CEST MRI.

Abstract Background To obtain high-yield histological samples by targeted prostate cancer (PCa) biopsy is the current trend compared with transrectal ultrasound (TRUS)-guided systematic histological biopsy, which is regarded as the gold standard for prostate cancer (PCa) diagnosis. In this paper, we present a targeted PCa imaging strategy using a real-time molecular photoacoustic imaging system integrated with a handheld US probe (PAI/US) and synthesized an integrin α v β 3 targeted probe based on ICG (cRGD–ICG). Methods To prepare cRGD–ICG, ICG-NHS was linked to cRGD through carboxyl-co-reaction. In vitro PA imaging ability of cRGD–ICG was tested. Orthotopic PCa-bearing rats were used as animal models. After injected with either cRGD–ICG or non-targeted probe, rats were implemented with PA imaging to confirm the specific accumulation of cRGD–ICG at tumor region. Moreover, pathological frozen slices were made to observe distribution of the probe in prostate tissue ex vivo. Results A small molecular PAI probe was synthesized and exhibited excellent targeted imaging ability in vitro. In vivo photoacoustic imaging was carried out after intravenous injection of cRGD-ICG in orthotopic PCa-bearing rats under the facilitation of the PAI/US system. Maximum molecular photoacoustic signals were observed in the tumor area in vivo after the probe injection, which showed 3.8-fold higher signal enhancement than that in the control group (P

Summary: Ultrasound brain stimulation is a promising modality for probing brain function and treating brain disease non-invasively and with high spatiotemporal resolution. However, the mechanism underlying its effects remains unclear. Here, we examine the role that the mouse piezo-type mechanosensitive ion channel component 1 (Piezo1) plays in mediating the in vitro effects of ultrasound in mouse primary cortical neurons and a neuronal cell line. We show that ultrasound alone could activate heterologous and endogenous Piezo1, initiating calcium influx and increased nuclear c-Fos expression in primary neurons but not when pre-treated with a Piezo1 inhibitor. We also found that ultrasound significantly increased the expression of the important proteins phospho-CaMKII, phospho-CREB, and c-Fos in a neuronal cell line, but Piezo1 knockdown significantly reduced this effect. Our findings demonstrate that the activity of mechanosensitive ion channels such as Piezo1 stimulated by ultrasound is an important contributor to its ability to stimulate cells in vitro. : Neuroscience; Molecular Neuroscience; Cellular Neuroscience; Sensory Neuroscience Subject Areas: Neuroscience, Molecular Neuroscience, Cellular Neuroscience, Sensory Neuroscience

Lately, deep learning technology has been extensively investigated for accelerating dynamic magnetic resonance (MR) imaging, with encouraging progresses achieved. However, without fully sampled reference data for training, the current approaches may have limited abilities in recovering fine details or structures. To address this challenge, this paper proposes a self-supervised collaborative learning framework (SelfCoLearn) for accurate dynamic MR image reconstruction from undersampled k-space data directly. The proposed SelfCoLearn is equipped with three important components, namely, dual-network collaborative learning, reunderampling data augmentation and a special-designed co-training loss. The framework is flexible and can be integrated into various model-based iterative un-rolled networks. The proposed method has been evaluated on an in vivo dataset and was compared to four state-of-the-art methods. The results show that the proposed method possesses strong capabilities in capturing essential and inherent representations for direct reconstructions from the undersampled k-space data and thus enables high-quality and fast dynamic MR imaging.

Plasmonic nanostructures with sharp tips are widely used for optical signal enhancement because of their strong light-confining abilities. These structures have a wide range of potential applications, for example, in sensing, bioimaging, and surface-enhanced Raman scattering. Au nanoparticles, which are important plasmonic materials with high photothermal conversion efficiencies in the visible to near-infrared region, have contributed greatly to the development of photothermal catalysis. However, the existing methods for synthesizing nanostructures with tips need the assistance of poly(vinylpyrrolidone), thiols, or biomolecules. This greatly hinders signal detection because of stubborn residues. Here, we propose an efficient binary surfactant–mediated method for controlling nanotip growth on Au nanoparticle surfaces. This avoids the effects of surfactants and can be used with other Au nanostructures. The Au architecture tip growth process can be controlled well by adjusting the ratio of hexadecyltrimethylammonium bromide to hexadecyltrimethylammonium chloride. This is due to the different levels of attraction between Br−/Cl− and Au3+ ions. The surface-enhanced Raman scattering and catalytic abilities of the synthesized nanoparticles with tips were evaluated by electromagnetic simulation and photothermal catalysis experiments (with 4-nitrothiophenol). The results show good potential for use in surface-enhanced Raman scattering applications. This method provides a new strategy for designing plasmonic photothermal nanostructures for chemical and biological applications.

Oxide-supported Ag nanoparticles have been widely reported as a good approach to improve the stability and reduce the cost of photocatalysts. In this work, a Ag-nanoparticles-doped porous ZnO photocatalyst was prepared by using metal–organic frameworks as a sacrificial precursor and the catalytic activity over 4-nitrophenol was determined. The Ag-nanoparticles-doped porous ZnO heterostructure was evaluated by UV, XRD, and FETEM, and the catalytic rate constant was calculated by the change in absorbance value at 400 nm of 4-nitrophenol. The photocatalyst with a heterogeneous structure is visible, light-responsive, and beneficial to accelerating the catalytic rate. Under visible light irradiation, the heterostructure showed excellent catalytic activity over 4-nitrophenol due to the hot electrons induced by the localized surface plasmon resonance of Ag nanoparticles. Additionally, the catalytic rates of 4 nm/30 nm Ag nanoparticles and porous/nonporous ZnO were compared. We found that the as-prepared Ag-nanoparticles-doped porous ZnO heterostructure catalyst showed enhanced catalytic performance due to the synergetic effect of Ag nanoparticles and porous ZnO. This study provides a novel heterostructure photocatalyst with potential applications in solar energy and pollutant disposal.

Noble metal nanostructures can produce the surface plasmon resonance under appropriate photoexcitation, which can be used to promote or facilitate chemical reactions, as well as photocatalytic materials, due to their strong plasmon resonance in the visible light region. In the current work, Ag/Au nanoislands (NIs) and Ag NIs/Au film composite systems were designed, and their thermocatalysis performance was investigated using luminescence of Eu3+ as a probe. Compared with Ag NIs, the catalytic efficiency and stability of surface plasmons of Ag/Au NIs and Ag NIs/Au film composite systems were greatly improved. It was found that the metal NIs can also generate strong localized heat at low temperature environment, enabling the transition of NaYF4:Eu3+ to Y2O3: Eu3+, and anti-oxidation was realized by depositing gold on the surface of silver, resulting in the relative stability of the constructed complex.

BackgroundT2-weighted (T2w) intracranial vessel wall imaging (IVWI) provides good contrast to differentiate intracranial vasculopathies and discriminate various important plaque components. However, the strong cerebrospinal fluid (CSF) signal in T2w images interferes with depicting the intracranial vessel wall. In this study, we propose a T2-prepared sequence for whole-brain IVWI at 3T with CSF suppression.MethodsA preparation module that combines T2 preparation and inversion recovery (T2IR) was used to suppress the CSF signal and was incorporated into the commercial three-dimensional (3D) turbo spin echo sequence-Sampling Perfection with Application optimized Contrast using different flip angle Evolution (SPACE). This new technique (hereafter called T2IR-SPACE) was evaluated on nine healthy volunteers and compared with two other commonly used 3D T2-weighted sequences: T2w-SPACE and FLAIR-SPACE (FLAIR: fluid-attenuated inversion recovery). The signal-to-noise ratios (SNRs) of the vessel wall (VW) and CSF and contrast-to-noise ratios (CNRs) between them were measured and compared among these three T2-weighted sequences. Subjective wall visualization of the three T2-weighted sequences was scored blindly and independently by two radiologists using a four-point scale followed by inter-rater reproducibility analysis. A pilot study of four stroke patients was performed to preliminarily evaluate the diagnostic value of this new sequence, which was compared with two conventional T2-weighted sequences.ResultsT2IR-SPACE had the highest CNR (11.01 ± 6.75) compared with FLAIR-SPACE (4.49 ± 3.15; p < 0.001) and T2w-SPACE (−56.16 ± 18.58; p < 0.001). The subjective wall visualization score of T2IR-SPACE was higher than those of FLAIR-SPACE and T2w-SPACE (T2IR-SPACE: 2.35 ± 0.59; FLAIR-SPACE: 0.52 ± 0.54; T2w-SPACE: 1.67 ± 0.58); the two radiologists’ scores showed excellent agreement (ICC = 0.883).ConclusionThe T2IR preparation module markedly suppressed the CSF signal without much SNR loss of the other tissues (i.e., vessel wall, white matter, and gray matter) compared with the IR pulse. Our results suggest that T2IR-SPACE is a potential alternative T2-weighted sequence for assessing intracranial vascular diseases.

Here, the authors propose an ultrasonic meta-lens for generating super-oscillation wave packets with different spatial momenta and then superimposing them to a diffraction-limit-broken spot. They experimentally verify super-resolution ultrasound imaging of subwavelength objects.

Abstract Background Ultrasound computed tomography (USCT) is usually realized with a ring array. It can provide better imaging performance and more tissue information by emitting and receiving the ultrasound signal in different directions simultaneously. However, USCT imaging is usually applied with the synthetic aperture (SA) emission method, which leads to a long scanning time with a large number of elements on the ring array. The echo image can provide the structural information, and has a higher resolution than maps of other parameters in USCT. Hence, we proposed plane wave (PW) imaging for ring array to acquire the echo wave and reduce the scanning time considerably. Results In this paper, an emitting and receiving process was proposed to realize plane wave imaging with a ring array. With the proposed scanning method, the number of emission events can be reduced greatly. A beamforming method based on the eigenspace-based minimum variance (ESBMV) was also combined with the scanning method. With ESBMV beamformer, the resolution and contrast ratio of reconstruction result can be maintained or even improved under a fewer-emissions condition. We validated the method using both computer simulations with Field II and phantom experiments with a ring array of 512 elements. The Verasonics® system was used to transmit and receive the ultrasound signal in the phantom experiments. Conclusions According to the results of the experiments, the imaging results will have a better contrast ratio with a higher emitting energy. Additionally, the scanning time with the proposed method can be only one-tenth of that with the SA emission method, while the echo imaging performance still remains at a similar level or even better.

Echinococcosis is an important zoonotic infectious disease that seriously affects human health. Conventional diagnosis of echinococcosis relies on the application of large-scale imaging equipment, which is difficult to promote in remote areas. Meanwhile, surgery and chemotherapy for echinococcosis can cause serious trauma and side effects. Thus, the development of simple and effective treatment strategies is of great significance for the diagnosis and treatment of echinococcosis. Herein, we designed a phototheranostic system utilizing neutrophil-membrane-camouflaged indocyanine green liposomes (Lipo-ICG) for active targeting the near-infrared fluorescence diagnosis and photothermal therapy of echinococcosis. The biomimetic Lipo-ICG exhibits a remarkable photo-to-heat converting performance and desirable active-targeting features by the inflammatory chemotaxis of the neutrophil membrane. In-vitro and in-vivo studies reveal that biomimetic Lipo-ICG with high biocompatibility can achieve in-vivo near-infrared fluorescence imaging and phototherapy of echinococcosis in mouse models. Our research is the first to apply bionanomaterials to the phototherapy of echinococcosis, which provides a new standard for the convenient and noninvasive detection and treatment of zoonotic diseases.

Imaging tracking of the migration of cell-based drug delivery systems are needed for expanding their clinical application for glioma. Here they report inflammation activatable engineered neutrophils containing doxorubicin-loaded magnetic mesoporous silica nanoparticles to image and actively target brain tumors after resection.

Contributing to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) clinical treatment, a drug library encompassing approximately 3,142 clinical-stage or FDA-approved small molecules is profiled to identify the candidate therapeutic inhibitors targeting nucleocapsid protein (N) and spike protein (S) of SARS-CoV-2.16 screened candidates with higher binding affinity are evaluated via virtual screening. Comparing to those under trial/temporarily used antivirus drugs (i.e., umifenovir, lopinavir), ceftriaxone, cefotaxime, and cefuroxime show higher binding affinities to the N-terminal domain of N protein (N-NTD), C-terminal domain of N protein (N-CTD), and receptor-binding domain of S protein (S-RBD). Cefotaxime and cefuroxime have high binding affinities towards S-RBD with angiotensin-converting enzyme 2 (ACE2) complex via influence the critical interface sites at the interface of S-RBD (Arg403, Tyr453, Trp495, Gly496, Phe497, Asn501and Tyr505) and ACE2 (Asn33, His34, Glu37, Asp38, Lys353, Ala386, Ala387, Gln388, Pro389, Phe390 and Arg393) complex.

Evidence in animals suggests that deep brain stimulation or optogenetics can be used for recovery from disorders of consciousness (DOC). However, these treatments require invasive procedures. This report presents a noninvasive strategy to stimulate central nervous system neurons selectively for recovery from DOC in mice. Through the delivery of ultrasound energy to the ventral tegmental area, mice were aroused from an unconscious, anaesthetized state in this study, and this process was controlled by adjusting the ultrasound parameters. The mice in the sham group under isoflurane-induced, continuous, steady-state general anaesthesia did not regain their righting reflex. On insonation, the emergence time from inhaled isoflurane anaesthesia decreased (sham: 13.63±0.53 min, ultrasound: 1.5±0.19 min, p

Benefiting from treating diseases at the genetic level, gene therapy has been considered a new revolution in the biomedical field. However, the extracellular and intracellular barriers during gene transport such as enzymatic degradation and endo-/lysosomal sequestration significantly compromise the therapeutic efficacy. Though photochemical internalization (PCI) has emerged as a promising approach for causing endo-/lysosomal leakage with translocation of the internalized molecules into the cytosol, its effect is still unsatisfactory due to the insufficient light penetration depth. Here, we develop tumor microenvironment-specific enhanced gene delivery by means of ROS generated from the in situ cascaded catalytic reactions in tumors involving GOx-mediated redox reaction and Mn2+-mediated Fenton-like reaction. The efficient enzymatic protection and successful endo-/lysosomal escape of cargo gene complexes have been demonstrated. Moreover, anti-Twist siRNA-loaded G@MMSNs-P exhibit tumor-specific biodegradation, excellent T1-weighted MR imaging, and significant inhibitory effects against breast cancer growth and pulmonary metastasis.

Acoustic tweezers have great application prospects because they allow noncontact and noninvasive manipulation of microparticles in a wide range of media. However, the nontransparency and heterogeneity of media in practical applications complicate particle trapping and manipulation. In this study, we designed a 1.04 MHz 256-element 2D matrix array for 3D acoustic tweezers to guide and monitor the entire process using real-time 3D ultrasonic images, thereby enabling acoustic manipulation in nontransparent media. Furthermore, we successfully performed dynamic 3D manipulations on multiple microparticles using multifoci and vortex traps. We achieved 3D particle manipulation in heterogeneous media (through resin baffle and ex vivo macaque and human skulls) by introducing a method based on the time reversal principle to correct the phase and amplitude distortions of the acoustic waves. Our results suggest cutting-edge applications of acoustic tweezers such as acoustical drug delivery, controlled micromachine transfer, and precise treatment.

Cochlear implantation is the first-line treatment for severe and profound hearing loss in children and adults. However, deaf patients with cochlear malformations or with cochlear nerve deficiencies are ineligible for cochlear implants. Meanwhile, the limited spatial selectivity and high risk of invasive craniotomy restrict the wide application of auditory brainstem implants. A noninvasive alternative strategy for safe and effective neuronal stimulation is urgently needed to address this issue. Because of its advantage in neural modulation over electrical stimulation, low-intensity ultrasound (US) is considered a safe modality for eliciting neural activity in the central auditory system. Although the neural modulation ability of low-intensity US has been demonstrated in the human primary somatosensory cortex and primary visual cortex, whether low-intensity US can directly activate auditory cortical neurons is still a topic of debate. To clarify the direct effects on auditory neurons, in the present study, we employed low-intensity US to stimulate auditory cortical neurons in vitro. Our data show that both low-frequency (0.8 MHz) and high-frequency (>27 MHz) US stimulation can elicit the inward current and action potentials in cultured neurons. c-Fos staining results indicate that low-intensity US is efficient for stimulating most neurons. Our study suggests that low-intensity US can excite auditory cortical neurons directly, implying that US-induced neural modulation can be a potential approach for activating the auditory cortex of deaf patients.