Lower Limb Motion Recognition with Improved SVM Based on Surface Electromyography.

During robot-assisted rehabilitation, failure to recognize lower limb movement may efficiently limit the development of exoskeleton robots, especially for individuals with knee pathology. A major challenge encountered with surface electromyography (sEMG) signals generated by lower limb movements is variability between subjects, such as motion patterns and muscle structure. To this end, this paper proposes an sEMG-based lower limb motion recognition using an improved support vector machine (SVM). Firstly, non-negative matrix factorization (NMF) is leveraged to analyze muscle synergy for multi-channel sEMG signals. Secondly, the multi-nonlinear sEMG features are extracted, which reflect the complexity of muscle status change during various lower limb movements. The Fisher discriminant function method is utilized to perform feature selection and reduce feature dimension. Then, a hybrid genetic algorithm-particle swarm optimization (GA-PSO) method is leveraged to determine the best parameters for SVM. Finally, the experiments are carried out to distinguish 11 healthy and 11 knee pathological subjects by performing three different lower limb movements. Results demonstrate the effectiveness and feasibility of the proposed approach in three different lower limb movements with an average accuracy of 96.03% in healthy subjects and 93.65% in knee pathological subjects, respectively.

A double-stranded RNA binding protein enhances drought resistance via protein phase separation in rice.

Drought stress significantly impacts global rice production, highlighting the critical need to understand the genetic basis of drought resistance in rice. Here, through a genome-wide association study, we reveal that natural variations in DROUGHT RESISTANCE GENE 9 (DRG9), encoding a double-stranded RNA (dsRNA) binding protein, contribute to drought resistance. Under drought stress, DRG9 condenses into stress granules (SGs) through liquid-liquid phase separation via a crucial α-helix. DRG9 recruits the mRNAs of OsNCED4, a key gene for the biosynthesis of abscisic acid, into SGs and protects them from degradation. In drought-resistant DRG9 allele, natural variations in the coding region, causing an amino acid substitution (G267F) within the zinc finger domain, increase DRG9's binding ability to OsNCED4 mRNA and enhance drought resistance. Introgression of the drought-resistant DRG9 allele into the elite rice Huanghuazhan significantly improves its drought resistance. Thus, our study underscores the role of a dsRNA-binding protein in drought resistance and its promising value in breeding drought-resistant rice.

Characteristics of flash droughts and their association with compound meteorological extremes in China: Observations and model simulations.

Flash droughts have gained considerable public attention due to the imminent threats they pose to food security, ecological safety, and human health. Currently, there has been little research exploring the projected changes in flash droughts and their association with compound meteorological extremes (CMEs). In this study, we applied the pentad-mean water deficit index to investigate the characteristics of flash droughts and their association with CMEs based on observational data and downscaled model simulations. Our analysis reveals an increasing trend in flash drought frequency in China based on historical observations and model simulations. Specifically, the proportion of flash drought frequency with a one-pentad onset time showed a consistent upward trend, with the southern parts of China experiencing a high average proportion during the historical period. Furthermore, the onset dates of the first (last) flash droughts during year are projected to shift earlier (later) in a warmer world. Flash droughts become significantly more frequent in the future, with a growth rate approximately 1.3 times higher in the high emission scenario than in the medium emission scenario. The frequency of flash droughts with a one-pentad onset time also exhibits a significant upward trend, indicating that flash droughts will occur more rapidly in the future. CMEs in southern regions of China were found to be more likely to trigger flash droughts in the historical period. The probability of CMEs triggering flash droughts is expected to increase with the magnitude of warming, particularly in the far-future under the high emissions scenario.

In Vivo Ultrasound Molecular Imaging in the Evaluation of Complex Ovarian Masses: A Practical Guide to Correlation with Ex Vivo Immunohistochemistry.

Ovarian cancer is the fifth leading cause of cancer-related deaths in women and the most lethal gynecologic cancer. It is curable when discovered at an early stage, but usually remains asymptomatic until advanced stages. It is crucial to diagnose the disease before it metastasizes to distant organs for optimal patient management. Conventional transvaginal ultrasound imaging offers limited sensitivity and specificity in the ovarian cancer detection. With molecularly targeted ligands addressing targets, such as kinase insert domain receptor (KDR), attached to contrast microbubbles, ultrasound molecular imaging (USMI) can be used to detect, characterize and monitor ovarian cancer at a molecular level. In this article, the authors propose a standardized protocol is proposed for the accurate correlation between in- vivo transvaginal KDR-targeted USMI and ex vivo histology and immunohistochemistry in clinical translational studies. The detailed procedures of in vivo USMI and ex vivo immunohistochemistry are described for four molecular markers, CD31 and KDR with a focus on how to enable the accurate correlation between in vivo imaging findings and ex vivo expression of the molecular markers, even if not the entire tumor could can be imaged by USMI, which is not an uncommon scenario in clinical translational studies. This work aims to enhance the workflow and the accuracy of characterization of ovarian masses on transvaginal USMI using histology and immunohistochemistry as reference standards, which involves sonographers, radiologists, surgeons, and pathologists in a highly collaborative research effort of USMI in cancer.

Serine protease NAL1 exerts pleiotropic functions through degradation of TOPLESS-related corepressor in rice.

NARROW LEAF 1 (NAL1) is a breeding-valuable pleiotropic gene that affects multiple agronomic traits in rice, although the molecular mechanism is largely unclear. Here, we report that NAL1 is a serine protease and displays a novel hexameric structure consisting of two ATP-mediated doughnut-shaped trimeric complexes. Moreover, we identified TOPLESS-related corepressor OsTPR2 involved in multiple growth and development processes as the substrate of NAL1. We found that NAL1 degraded OsTPR2, thus modulating the expression of downstream genes related to hormone signalling pathways, eventually achieving its pleiotropic physiological function. An elite allele, NAL1A, which may have originated from wild rice, could increase grain yield. Furthermore, the NAL1 homologues in different crops have a similar pleiotropic function to NAL1. Our study uncovers a NAL1-OsTPR2 regulatory module and provides gene resources for the design of high-yield crops.

Contrast Enhanced Ultrasound Molecular Imaging of Spontaneous Chronic Inflammatory Bowel Disease in an Interleukin-2 Receptor α-/- Transgenic Mouse Model Using Targeted Microbubbles.

Inflammatory bowel disease (IBD) is a lifelong inflammatory disorder with relapsing-remission cycles, which is currently diagnosed by clinical symptoms and signs, along with laboratory and imaging findings. However, such clinical findings are not parallel to the disease activity of IBD and are difficult to use in treatment monitoring. Therefore, non-invasive quantitative imaging tools are required for the multiple follow-up exams of IBD patients in order to monitor the disease activity and determine treatment regimens. In this study, we evaluated a dual P- and E-selectin-targeted microbubble (MBSelectin) in an interleukin-2 receptor α deficient (IL-2Rα-/-) spontaneous chronic IBD mouse model for assessing long-term anti-inflammatory effects with ultrasound molecular imaging (USMI). We used IL-2Rα-/- (male and female on a C57BL/6 genetic background; n = 39) and C57BL/6 wild-type (negative control; n = 6) mice for the study. USMI of the proximal, middle, and distal colon was performed with MBSelectin using a small animal scanner (Vevo 2100) up to six times in each IL-2Rα-/- mouse between 6-30 weeks of age. USMI signals were compared between IL-2Rα-/- vs. wild-type mice, and sexes in three colonic locations. Imaged colon segments were analyzed ex vivo for inflammatory changes on H&E-stained sections and for selectin expression by immunofluorescence staining. We successfully detected spontaneous chronic colitis in IL-2Rα-/- mice between 6-30 weeks (onset at 6-14 weeks) compared to wild-type mice. Both male and female IL-2Rα-/- mice were equally (p = 0.996) affected with the disease, and there was no significant (p > 0.05) difference in USMI signals of colitis between the proximal, middle, and distal colon. We observed the fluctuating USMI signals in IL-2Rα-/- mice between 6-30 weeks, which might suggest a resemblance of the remission-flare pattern of human IBD. The ex vivo H&E and immunostaining further confirmed the inflammatory changes, and the high expression of P- and E-selectin in the colon. The results of this study highlight the IL-2Rα-/- mice as a chronic colitis model and are suitable for the long-term assessment of treatment response using a dual P- and E-selectin-targeted USMI.

Ultrasound-Guided Microbubble-Mediated Locoregional Delivery of Multiple MicroRNAs Improves Chemotherapy in Hepatocellular Carcinoma.

Rationale: To assess treatment effects of 4 complementary miRNAs (miRNA-100/miRNA-122/antimiRNA-10b/antimiRNA-21) encapsulated in a biodegradable PLGA-PEG nanoparticle, administered by an ultrasound-guided microbubble-mediated targeted delivery (UGMMTD) approach in mouse models of hepatocellular carcinoma (HCC). Methods:In vitro apoptotic index was measured in HepG2 and Hepa1-6 HCC cells treated with various combinations of the 4 miRNAs with doxorubicin. Three promising combinations were further tested in vivo by using UGMMTD. 63 HepG2 xenografts in mice were randomized into: group 1, miRNA-122/antimiRNA-10b/antimiRNA-21/US/doxorubicin; group 2, miRNA-100/miRNA-122/antimiRNA-10b/antimiRNA-21/US/doxorubicin; group 3, miRNA-100/miRNA-122/antimiRNA-10b/US/doxorubicin; group 4, miRNA-122/anitmiRNA-10b/antimiRNA-21/doxorubicin; group 5, miRNA-100/miRNA-122/antimiRNA-10b/antimiRNA-21/doxorubicin; group 6, miRNA-100/miRNA-122/antimiRNA-10b/doxorubicin; group 7, doxorubicin only treatment; and group 8, without any treatment. Tumor volumes were measured through 18 days. H&E staining, TUNEL assay, and qRT-PCR quantification for delivered miRNAs were performed. Results:In vivo results showed that UGMMTD of miRNAs with doxorubicin in groups 1-3 significantly (P<0.05) delayed tumor growth compared to control without any treatment, and doxorubicin only from day 7 to 18. On qRT-PCR, levels of delivered miRNAs were significantly (P<0.05) higher in groups 1-3 upon UGMMTD treatment compared to controls. TUNEL assay showed that upon UGMMTD, significantly higher levels of apoptotic cell populations were observed in groups 1-3 compared to controls. Toxicity was not observed in various organs of different groups. Conclusions: UGMMTD of miRNA-100/miRNA-122/antimiRNA-10b/antimiRNA-21 combination improved therapeutic outcome of doxorubicin chemotherapy in mouse models of HCC by substantial inhibition of tumor growth and significant increase in apoptotic index.

Risk assessment of water resource shortages in the Aksu River basin of northwest China under climate change.

As most of the runoff resulting from snow-ice melt is related to climate change factors in the arid region of northwest China, the risk to water resource systems threatens the socio-economic and ecological environment and is becoming increasingly prevalent. Therefore, we explored the risks of water resource shortages for different periods (2010, 2020, and 2030) in the Aksu River basin (ARB) in the northwest arid region of China by reconstructing a risk model based on the framework proposed by the Intergovernmental Panel on Climate Change (IPCC) with an improved vulnerability (V) module and a more suitable hazard probability in the cost module. The major conclusions are as follows: (1) the simulation of the Community Land Model-Distributed Time Variant Gain Model (CLM-DTVGM) and the Vegetation Interface Processes model (VIP) was suitable for the eco-hydrological processes in the ARB under climate change (i.e., R2 ≥ 0.583; Nash coefficient ≥0.371; and relative mean standard ≤155.727 for CLM-DTVGM; R2 = 0.798 for VIP); (2) the vulnerability of the water resource system in the ARB was medium in 2010, and dropped to a medium-low to non-vulnerable level in 2020 before increasing in 2030 under different Representative Concentration Pathways (RCP) (RCP2.6, RCP4.5, and RCP8.5); and (3) there was a medium-low risk of water resource shortages in the ARB in 2010 (i.e., 0.246), and although the risk of water resource shortages decreased in 2020 due to the increasing water supply from mountainous areas, the risk predicted to increase significantly in 2030, to a medium-high risk level. This study is critical for accurately predicting and understanding the impact of climate change on water resource systems as well as on the drought risk in arid regions.

Local Sound Speed Estimation for Pulse-Echo Ultrasound in Layered Media.

Our previous methodology in local sound speed estimation utilized time delays measured by the cross correlation of delayed full-synthetic aperture channel data to estimate the average speed of sound. However, focal distortions in this methodology lead to biased estimates of the average speed of sound, which, in turn, leads to biased estimates of the local speed of sound. Here, we demonstrate the bias in the previous methodology and introduce a coherence-based average sound speed estimator that eliminates this bias and is computationally much cheaper in practice. Because this coherence-based approach estimates the average sound speed in the medium over an equally spaced grid in depth rather than time, we derive a refined model that relates the local and average speeds of sound as a function of depth in layered media. A fast, closed-form inversion of this model yields highly accurate local sound speed estimates. The root-mean-square (rms) error of local sound speed reconstruction in simulations of two-layer media is 4.6 and 2.5 m/s at 4 and 8 MHz, respectively. This work examines the impact of frequency, f -number, aberration, and reverberation on sound speed estimation. Phantom and in vivo experiments in rats further validate the coherence-based sound speed estimator.

Detection and Characterization of Sentinel Lymph Node by Ultrasound Molecular Imaging with B7-H3-Targeted Microbubbles in Orthotopic Breast Cancer Model in Mice.

PURPOSE: Accurate identification and assessment of sentinel lymph node (SLN) using noninvasive imaging methods can play a vital role in tumor staging, surgical planning, and prognostic evaluation. In this study, we assessed the efficacy of B7-H3-targeted molecular-ultrasound imaging for the early SLN detection, and characterization in a mouse model of orthotopic breast cancer. PROCEDURES: We established a mouse breast cancer model with lymph node metastasis by injecting MAD-MB 231 cells which were engineered to express firefly luciferase reporter gene into the fat pad of the right 4th mammary gland in female BALB/c nude mice. The sole lymph node (LN) close to the tumor was regarded as the SLN for imaging investigation, which included metastatic and non-metastatic SLNs. The LN in the right 4th mammary gland from normal mice was used as normal control (normal mice LN). The commercially available preclinical streptavidin-coated, perfluorocarbon-containing lipid-shelled microbubbles (VisualSonics, Toronto, Canada) were used to generate B7-H3-targeted microbubbles (MBB7-H3) and control microbubbles (MBControl). Then, ultrasound molecular imaging (USMI) was performed using a high-resolution transducer (MS250; center frequency, 21 MHz; Vevo 2100; VisualSonics, Toronto, Canada) after intravenous injection of microbubbles. RESULTS: The SLN was clearly detected and located under conventional (B-mode) and contrast-enhanced ultrasonography with microbubble injection. The metastatic SLNs showed a markedly higher signal from B7-H3-targeted microbubbles (MBB7-H3) compared to the non-metastatic SLNs and normal LNs. The metastatic SLN was further confirmed by ex vivo bioluminescence imaging and eventually verified by histological analysis. CONCLUSIONS: Our findings suggest the potential value of USMI using B7-H3 targeted microbubbles in breast cancer and establish an effective imaging method for the non-invasive detection and characterization of SLN.

VBNet: An end-to-end 3D neural network for vessel bifurcation point detection in mesoscopic brain images.

BACKGROUND AND OBJECTIVE: Accurate detection of vessel bifurcation points from mesoscopic whole-brain images plays an important role in reconstructing cerebrovascular networks and understanding the pathogenesis of brain diseases. Existing detection methods are either less accurate or inefficient. In this paper, we propose VBNet, an end-to-end, one-stage neural network to detect vessel bifurcation points in 3D images. METHODS: Firstly, we designed a 3D convolutional neural network (CNN), which input a 3D image and output the coordinates of bifurcation points in this image. The network contains a two-scale architecture to detect large bifurcation points and small bifurcation points, respectively, which takes into account the accuracy and efficiency of detection. Then, to solve the problem of low accuracy caused by the imbalance between the numbers of large bifurcations and small bifurcations, we designed a weighted loss function based on the radius distribution of blood vessels. Finally, we extended the method to detect bifurcation points in large-scale volumes. RESULTS: The proposed method was tested on two mouse cerebral vascular datasets and a synthetic dataset. In the synthetic dataset, the F1-score of the proposed method reached 96.37%. In two real datasets, the F1-score was 92.35% and 86.18%, respectively. The detection effect of the proposed method reached the state-of-the-art level. CONCLUSIONS: We proposed a novel method for detecting vessel bifurcation points in 3D images. It can be used to precisely locate vessel bifurcations from various cerebrovascular images. This method can be further used to reconstruct and analyze vascular networks, and also for researchers to design detection methods for other targets in 3D biomedical images.

Noninvasive estimation of local speed of sound by pulse-echo ultrasound in a rat model of nonalcoholic fatty liver.

Objective. Speed of sound has previously been demonstrated to correlate with fat concentration in the liver. However, estimating speed of sound in the liver noninvasively can be biased by the speed of sound of the tissue layers overlying the liver. Here, we demonstrate a noninvasive local speed of sound estimator, which is based on a layered media assumption, that can accurately capture the speed of sound in the liver. We validate the estimator using an obese Zucker rat model of non-alcoholic fatty liver disease and correlate the local speed of sound with liver steatosis.Approach.We estimated the local and global average speed of sound noninvasively in 4 lean Zucker rats fed a normal diet and 16 obese Zucker rats fed a high fat diet for up to 8 weeks. The ground truth speed of sound and fat concentration were measured from the excised liver using established techniques.Main Results. The noninvasive, local speed of sound estimates of the livers were similar in value to their corresponding 'ground truth' measurements, having a slope ± standard error of the regression of 0.82 ± 0.15 (R2= 0.74 andp< 0.001). Measurement of the noninvasive global average speed of sound did not reliably capture the 'ground truth' speed of sound in the liver, having a slope of 0.35 ± 0.07 (R2= 0.74 andp< 0.001). Decreasing local speed of sound was observed with increasing hepatic fat accumulation (approximately -1.7 m s-1per 1% increase in hepatic fat) and histopathology steatosis grading (approximately -10 to -13 m s-1per unit increase in steatosis grade). Local speed of sound estimates were highly correlated with steatosis grade, having Pearson and Spearman correlation coefficients both ranging from -0.87 to -0.78. In addition, a lobe-dependent speed of sound in the liver was observed by theex vivomeasurements, with speed of sound differences of up to 25 m s-1(p< 0.003) observed between lobes in the liver of the same animal.Significance.The findings of this study suggest that local speed of sound estimation has the potential to be used to predict or assist in the measurement of hepatic fat concentration and that the global average speed of sound should be avoided in hepatic fat estimation due to significant bias in the speed of sound estimate.

Therapeutic Ultrasound Parameter Optimization for Drug Delivery Applied to a Murine Model of Hepatocellular Carcinoma.

Ultrasound and microbubble (USMB)-mediated drug delivery is a valuable tool for increasing the efficiency of the delivery of therapeutic agents to cancer while maintaining low systemic toxicity. Typically, selection of USMB drug delivery parameters used in current research settings are either based on previous studies described in the literature or optimized using tissue-mimicking phantoms. However, phantoms rarely mimic in vivo tumor environments, and the selection of parameters should be based on the application or experiment. In the following study, we optimized the therapeutic parameters of the ultrasound drug delivery system to achieve the most efficient in vivo drug delivery using fluorescent semiconducting polymer nanoparticles as a model nanocarrier. We illustrate that voltage, pulse repetition frequency and treatment time (i.e., number of ultrasound pulses per therapy area) delivered to the tumor can successfully be optimized in vivo to ensure effective delivery of the semiconducting polymer nanoparticles to models of hepatocellular carcinoma. The optimal in vivo parameters for USMB drug delivery in this study were 70 V (peak negative pressure = 3.4 MPa, mechanical index = 1.22), 1-Hz pulse repetition frequency and 100-s therapy time. USMB-mediated drug delivery using in vivo optimized ultrasound parameters caused an up to 2.2-fold (p < 0.01) increase in drug delivery to solid tumors compared with that using phantom-optimized ultrasound parameters.

Spatial Characterization of Tumor Perfusion Properties from 3D DCE-US Perfusion Maps are Early Predictors of Cancer Treatment Response.

There is a need for noninvasive repeatable biomarkers to detect early cancer treatment response and spare non-responders unnecessary morbidities and costs. Here, we introduce three-dimensional (3D) dynamic contrast enhanced ultrasound (DCE-US) perfusion map characterization as inexpensive, bedside and longitudinal indicator of tumor perfusion for prediction of vascular changes and therapy response. More specifically, we developed computational tools to generate perfusion maps in 3D of tumor blood flow, and identified repeatable quantitative features to use in machine-learning models to capture subtle multi-parametric perfusion properties, including heterogeneity. Models were developed and trained in mice data and tested in a separate mouse cohort, as well as early validation clinical data consisting of patients receiving therapy for liver metastases. Models had excellent (ROC-AUC > 0.9) prediction of response in pre-clinical data, as well as proof-of-concept clinical data. Significant correlations with histological assessments of tumor vasculature were noted (Spearman R > 0.70) in pre-clinical data. Our approach can identify responders based on early perfusion changes, using perfusion properties correlated to gold-standard vascular properties.

A lamin-like protein OsNMCP1 regulates drought resistance and root growth through chromatin accessibility modulation by interacting with a chromatin remodeller OsSWI3C in rice.

Lamin proteins in animals are implicated in important nuclear functions, including chromatin organization, signalling transduction, gene regulation and cell differentiation. Nuclear Matrix Constituent Proteins (NMCPs) are lamin analogues in plants, but their regulatory functions remain largely unknown. We report that OsNMCP1 is localized at the nuclear periphery in rice (Oryza sativa) and induced by drought stress. OsNMCP1 overexpression resulted in a deeper and thicker root system, and enhanced drought resistance compared to the wild-type control. An assay for transposase accessible chromatin with sequencing (ATAC-seq) analysis revealed that OsNMCP1-overexpression altered chromatin accessibility in hundreds of genes related to drought resistance and root growth, including OsNAC10, OsERF48, OsSGL, SNAC1 and OsbZIP23. OsNMCP1 can interact with SWITCH/SUCROSE NONFERMENTING (SWI/SNF) chromatin remodelling complex subunit OsSWI3C. The reported drought resistance or root growth-related genes that were positively regulated by OsNMCP1 were negatively regulated by OsSWI3C under drought stress conditions, and OsSWI3C overexpression led to decreased drought resistance. We propose that the interaction between OsNMCP1 and OsSWI3C under drought stress conditions may lead to the release of OsSWI3C from the SWI/SNF gene silencing complex, thus changing chromatin accessibility in the genes related to root growth and drought resistance.

Assessment of Metastatic and Reactive Sentinel Lymph Nodes with B7-H3-Targeted Ultrasound Molecular Imaging: A Longitudinal Study in Mouse Models.

PURPOSE: To explore the potential of B7-H3-targeted ultrasound molecular imaging (USMI) for longitudinal assessment and differentiation of metastatic and reactive sentinel lymph nodes (SLNs) in mouse models. PROCEDURES: Metastatic and reactive SLN models were established by injection of 4T1 breast cancer cells and complete Freund's adjuvant (CFA) respectively to the 4th mammary fat pad of female BALB/c mice. At day 21, 28, and 35 after inoculation, USMI was performed following intravenous injection of B7-H3-targeted microbubbles (MBB7-H3) or IgG-control microbubbles (MBcontrol). All SLNs were histopathologically examined after the last imaging session. RESULTS: A total of 20 SLNs from tumor-bearing mice (T-SLNs) and five SLNs from CFA-injected mice (C-SLNs) were examined by USMI. Nine T-SLNs were histopathologically positive for metastasis (MT-SLNs). From day 21 to 35, T-SLNs showed a rising trend in MBB7-H3 signal with a steep increase in MT-SLNs at day 35 (213.5 ± 80.8 a.u.) as compared to day 28 (87.6 ± 77.2 a.u., P = 0.002) and day 21 (55.7 ± 35.5 a.u., P < 0.001). At day 35, MT-SLNs had significantly higher MBB7-H3 signal than non-metastatic T-SLNs (NMT-SLNs) (101.9 ± 48.0 a.u., P = 0.001) and C-SLNs (38.5 ± 34.0 a.u., P = 0.001); MBB7-H3 signal was significantly higher than MBcontrol in MT-SLNs (P = 0.001), but not in NMT-SLNs or C-SLNs (both P > 0.05). A significant correlation was detected between MBB7-H3 signal and volume fraction of metastasis in MT-SLNs (r = 0.76, P = 0.017). CONCLUSIONS: B7-H3-targeted USMI allows differentiation of MT-SLNs from NMT-SLNs and C-SLNs in mouse models and has great potential to evaluate tumor burden in SLNs of breast cancer.

Ultrasound-mediated delivery of miRNA-122 and anti-miRNA-21 therapeutically immunomodulates murine hepatocellular carcinoma in vivo.

Hepatocellular carcinoma (HCC) is the most common cause of cancer-related mortality, and patients with HCC show poor response to currently available treatments, which demands new therapies. We recently developed a synthetic microRNA-based molecularly targeted therapy for improving HCC response to chemotherapy by eliminating drug resistance. We used ultrasound-targeted microbubble destruction (UTMD) to locally deliver microRNA-loaded nanoparticles to HCC. Since the immune microenvironment plays a crucial role in HCC disease development and response to treatment, and UTMD and microRNAs have the potential to interfere with the immune system, in this study we analyzed the immunomodulatory effects of UTMD and miRNAs in HCC. We used an immunocompetent syngeneic HCC mouse model for the study. We conducted cytokine profiling in tumor, lymph nodes, and serum of animals within the first 24 h of treatment to analyze changes in the level of pro- and antitumoral cytokines. The results showed: (1) Hepa1-6 syngeneic tumors expressed HCC-related cytokines, (2) UTMD-microRNA combination therapy triggered transient cytokine storms, and (3) delivery of microRNA-122 and anti-microRNA-21 affected the immune microenvironment by decreasing the level of GM-CSF in tumors while modulating protumoral IL-1α, IL-1ß, IL-5, IL-6 and IL-17 and antitumoral IL-2 and IL-12 in tumor-proximal lymph nodes, and increasing IL-2 in the serum of tumor-bearing mice. Local delivery of targeted therapy by UTMD significantly reduced the concentration of IL-12 and IL-17 in lymph nodes of treated and contralateral tumors suggesting a systemic response. CONCLUSION: UTMD-mediated delivery of microRNA-122 and anti-microRNA-21 modulated the immune microenvironment of Hepa1-6 tumors at the level of cytokine expressions. Exploiting antitumoral immune effects could enhance the therapeutic efficacy of the proposed combination therapy for HCC.

webTDat: A Web-Based, Real-Time, 3D Visualization Framework for Mesoscopic Whole-Brain Images.

The popularity of mesoscopic whole-brain imaging techniques has increased dramatically, but these techniques generate teravoxel-sized volumetric image data. Visualizing or interacting with these massive data is both necessary and essential in the bioimage analysis pipeline; however, due to their size, researchers have difficulty using typical computers to process them. The existing solutions do not consider applying web visualization and three-dimensional (3D) volume rendering methods simultaneously to reduce the number of data copy operations and provide a better way to visualize 3D structures in bioimage data. Here, we propose webTDat, an open-source, web-based, real-time 3D visualization framework for mesoscopic-scale whole-brain imaging datasets. webTDat uses an advanced rendering visualization method designed with an innovative data storage format and parallel rendering algorithms. webTDat loads the primary information in the image first and then decides whether it needs to load the secondary information in the image. By performing validation on TB-scale whole-brain datasets, webTDat achieves real-time performance during web visualization. The webTDat framework also provides a rich interface for annotation, making it a useful tool for visualizing mesoscopic whole-brain imaging data.