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Energy management strategies (EMSs) are one of the key technologies for the development of plug-in hybrid electric buses (PHEBs). This paper addresses the issue of optimal energy distribution for PHEBs under significant variations in passenger load at different bus stations, which cannot be solved by a single equivalent factor equivalent fuel consumption minimization energy management strategy (ECMS). An adaptive equivalent factor equivalent fuel consumption minimization energy management strategy (A-ECMS) considering passenger load is proposed. First, the powertrain system of the PHEB is modeled, and the accuracy of the model is verified in a simulation environment. Then, the reference SOC descent trajectory of the battery is obtained using a dynamic programming (DP) algorithm, the recursive least squares (RLS) method is employed to identify the passenger load, and the influence of different loads on the state of charge (SOC) trajectory under a single equivalent factor is analyzed. Finally, a genetic algorithm (GA) is used to establish the correspondence between passenger load, bus station, and equivalent factor, enabling the actual SOC to follow the reference SOC descent trajectory, thereby achieving optimal energy distribution. Simulation results demonstrate that the A-ECMS reduces fuel consumption of the PHEB per 100 km by 2.59% and 10.10% compared to the ECMS and rule-based EMS, respectively, validating the effectiveness of the proposed strategy.

The field of computer vision has shown great potential for the identification of crops at large scales based on multispectral images. However, the challenge in designing crop identification networks lies in striking a balance between accuracy and a lightweight framework. Furthermore, there is a lack of accurate recognition methods for non-large-scale crops. In this paper, we propose an improved encoder-decoder framework based on DeepLab v3+ to accurately identify crops with different planting patterns. The network employs ShuffleNet v2 as the backbone to extract features at multiple levels. The decoder module integrates a convolutional block attention mechanism that combines both channel and spatial attention mechanisms to fuse attention features across the channel and spatial dimensions. We establish two datasets, DS1 and DS2, where DS1 is obtained from areas with large-scale crop planting, and DS2 is obtained from areas with scattered crop planting. On DS1, the improved network achieves a mean intersection over union (mIoU) of 0.972, overall accuracy (OA) of 0.981, and recall of 0.980, indicating a significant improvement of 7.0%, 5.0%, and 5.7%, respectively, compared to the original DeepLab v3+. On DS2, the improved network improves the mIoU, OA, and recall by 5.4%, 3.9%, and 4.4%, respectively. Notably, the number of parameters and giga floating-point operations (GFLOPs) required by the proposed Deep-agriNet is significantly smaller than that of DeepLab v3+ and other classic networks. Our findings demonstrate that Deep-agriNet performs better in identifying crops with different planting scales, and can serve as an effective tool for crop identification in various regions and countries.

Integrating multi-omics data for cancer subtype recognition is an important task in bioinformatics. Recently, deep learning has been applied to recognize the subtype of cancers. However, existing studies almost integrate the multi-omics data simply by concatenation as the single data and then learn a latent low-dimensional representation through a deep learning model, which did not consider the distribution differently of omics data. Moreover, these methods ignore the relationship of samples. To tackle these problems, we proposed SADLN: A self-attention based deep learning network of integrating multi-omics data for cancer subtype recognition. SADLN combined encoder, self-attention, decoder, and discriminator into a unified framework, which can not only integrate multi-omics data but also adaptively model the sample’s relationship for learning an accurately latent low-dimensional representation. With the integrated representation learned from the network, SADLN used Gaussian Mixture Model to identify cancer subtypes. Experiments on ten cancer datasets of TCGA demonstrated the advantages of SADLN compared to ten methods. The Self-Attention Based Deep Learning Network (SADLN) is an effective method of integrating multi-omics data for cancer subtype recognition.

Objectives: Investigate the biomechanical characteristics in tracheostomized patients with aspiration following acquired brain injury (ABI) and further explore the relationship between the biomechanical characteristics and aspiration. Methods: This is a single-center cross-sectional study. The tracheostomized patients with aspiration following ABI and age-matched healthy controls were recruited. The biomechanical characteristics, including velopharynx (VP) maximal pressure, tongue base (TB) maximal pressure, upper esophageal sphincter (UES) residual pressure, UES relaxation duration, and subglottic pressure, were examined by high-resolution manometry and computational fluid dynamics simulation analysis. The penetration–aspiration scale (PAS) score was evaluated by a videofluoroscopic swallowing study. Results: Fifteen healthy subjects and fifteen tracheostomized patients with aspiration following ABI were included. The decreased VP maximal pressure, increased UES residual pressure, and shortened UES relaxation duration were found in the patient group compared with the control group (p < 0.05). Furthermore, the subglottic pressure significantly decreased in patients (p < 0.05), while no significant difference was found in TB maximal pressure between groups (p > 0.05). In addition, in the patient group, VP maximal pressure (rs = −0.439; p = 0.015), UES relaxation duration (rs = −0.532; p = 0.002), and the subglottic pressure (rs = −0.775; p < 0.001) were negatively correlated with the PAS score, while UES residual pressure (rs = 0.807; p < 0.001) was positively correlated with the PAS score (p < 0.05), the correlation between TB maximal pressure and PAS score (rs = −0.315; p = 0.090) did not reach statistical significance. Conclusions: The biomechanical characteristics in tracheostomized patients with aspiration following ABI might manifest as decreased VP maximal pressure and subglottic pressure, increased UES residual pressure, and shortened UES relaxation duration, in which VP maximal pressure, UES relaxation duration, subglottic pressure, and UES residual pressure were correlated with aspiration.

In this paper, the Multi-Temporal Interferometric Synthetic Aperture Radar (MT-InSAR) technology is adopted to monitor the Line of Sight (LOS) displacement of Fushun West Opencast Coal Mine (FWOCM) and its surrounding areas in northeast China using Sentinel-1 Synthetic Aperture Radar (SAR) images acquired from 2018 to 2022. The spatial-temporal evolution of urban subsidence and the south-slope landslide are both analyzed in detail. Comparison with ground measurements and cross-correlation analysis via cross wavelet transform with monthly precipitation data are also conducted, to analyze the influence factors of displacements in FWOCM. The monitoring results show that a subsidence basin appeared in the urban area near the eastern part of the north slope in 2018, with settlement center located at the intersection of E3000 and fault F1. The Qian Tai Shan (QTS) landslide on the south slope, which experienced rapid sliding during 2014 to 2016, presents seasonal deceleration and acceleration with precipitation, with the maximum displacement in vicinity of the Liushan paleochannel. The results of this paper have fully taken in account for the complications of large topographic relief, geological conditions, spatial distribution and temporal evolution characteristics of surface displacements in opencast mining area. The wide range and long time series dynamic monitoring of opencast mine are of great significance to ensure mine safety production and geological disaster prevention in the investigated mining area. [ABSTRACT FROM AUTHOR]

As a decentralized system, blockchain has been widely used in numerous areas and has become a hot topic in both industry and academia. The increasing demand for blockchain causes heavy storage consumption which seriously affects the performance of blockchain, especially in the context of massive volumes of data. To solve these problems, many related systems like sharding and sidechain have been proposed to improve the efficiency and scalability of blockchain. However, in practical deployment scenarios, these systems still have problems, such as low read–write performance, and reorganization and synchronization of ledger data after storage expansion, which cause the storage system's expansion to become difficult and time-consuming in large-scale blockchain systems. Facing these problems, in this paper we propose ChainMaker Storage System (CMSS). CMSS is a blockchain storage system with high read-and-write performance and horizontal scaling support. It has been used as the storage system of the most popular permissioned blockchain ChainMaker. There are three contributions of our proposed CMSS: (i) a new block storage workflow to achieve high read–write performance; (ii) the Meta File System (MFS) to support the horizontal expansion of blockchain storage; and (iii) hot–cold separation to reduce the resource usage and economic costs. To evaluate the performance of CMSS, we compare CMSS with Hyperledger Fabric (HLF), the most popular permissioned blockchain platform. We select five well-known cloud service providers to calculate the storage cost in a real production environment. The results show that CMSS has better performance in read and write than HLF and advantages in storage capacity and price. [ABSTRACT FROM AUTHOR]

With the increasing demand for decentralized systems and the widespread usage of blockchain, low throughput and high latency have become the biggest stumbling blocks in the development of blockchain systems. This problem seriously hinders the expansion of blockchain and its application in production. Most existing smart contract scheduling solutions use static feature analysis to prevent contract conflicts during parallel execution. However, the conflicts between transactions are complex; static feature analysis is not accurate enough. In this paper, we first build the dependency between smart contracts by analyzing the features. After numerous experiments, we propose a conflict model to adjust the relationship between threads and conflict to achieve high throughput and low latency. Based on these works, we propose adaptive parallel scheduling for smart contracts on the blockchain. Our adaptive parallel scheduling can distinguish conflicts between smart contracts and dynamically adjust the execution strategy of smart contracts based on the conflict factors we define. We implement our scheme on ChainMaker, one of the most popular open-source permissioned blockchains, and build experiments to verify our solution. Regarding latency, our solution demonstrates remarkable efficiency compared with the fully parallel scheme, particularly in high-conflict transaction scenarios, where our solution achieves latency levels just one-twentieth of the fully parallel scheme. Regarding throughput, our solution significantly outperforms the fully parallel scheme, achieving 30 times higher throughput in high-conflict transaction scenarios. These results highlight the superior performance and effectiveness of our solution in addressing latency and throughput challenges, particularly in environments with high transaction conflicts. [ABSTRACT FROM AUTHOR]

Bronchopulmonary dysplasia (BPD) is a prevalent lung disease in neonates that is associated with numerous complications and high mortality. The promising approach to treat BPD is the use of mesenchymal stem cells (MSCs), However, the current treatment of MSCs presents safety concerns, including occlusion of blood vessels and tumorigenicity. In this study, relevant publications from the Web of Science Core Collection were downloaded in January 2023. The acquired data were analyzed and predicted for trends and hotspots in this field using CiteSpace software. Results revealed that in recent years, the focus of co-cited references has been primarily on the clinical studies of MSCs and the application of MSCs derivatives for treating BPD models. The keywords that have gained attention are extracellular vesicles and exosomes. The United States has emerged as the most influential co-authoring country in this field. Among the co-cited journals, the American Journal of Respiratory and Critical Care Medicine holds the highest influence. Thus, this study provides trends in publications, collaboration, research interests, and hotspots, and provides clues for novel ideas and strategies in to further MSCs treatments for BPD. [ABSTRACT FROM AUTHOR]

Stroke incidence is the most severe complication associated with atrial fibrillation (AF), and the most common site of thrombus formation in AF patients is the left atrial appendage (LAA). This study was developed to use two-dimensional speckle tracking imaging (2D-STI) to explore associations between LAA strain/strain rate and stroke incidence and to evaluate the value of utilizing LAA strain and strain rate values to support the stratification of nonvalvular AF (NVAF) patients based on stroke risk. A total of 486 AF patients who had undergone transesophageal echocardiography to exclude potential intracardiac thrombosis between March 2021 and November 2022 were consecutively enrolled. Patients meeting the inclusion criteria were separated into two groups according to their history of stroke/transient ischemic attack (TIA). LAA strain and strain rate values in these patients were measured via 2D-STI. Multivariable logistic regression analysis was employed to determine independent risk factors for the construction of a combined predictive model. Of the 333 analyzed patients (134 females, aged 65 (56,72) years), 39 (11.71%, 39/333) had a history of stroke at the time of evaluation. Multivariate logistic regression analysis demonstrated that nonparoxysmal AF, CHA2DS2VASc score, LAA thrombus/spontaneous echo contrast (SEC), LAA strain, and strain rate were all predictors of stroke incidence among NVAF patients. The combined predictive model demonstrated excellent discriminative ability, with an AUC of 0.91 (95%CI 0.87–0.95, P < 0.001), and a sensitivity and specificity of 79.49% and 89.46%, respectively. The Hosmer-Lemeshow test confirmed good calibration, yielding a value of 0.98. Comparative decision curve analysis showed that the model provided superior net benefits compared to the CHA2DS2VASc score. Furthermore, the model exhibited improved predictive performance and reclassification for stroke when compared to the CHA2DS2VASc score (AUC 0.91 vs. 0.88, Z = 2.32, P = 0.02), accompanied by a significant increase in the net reclassification index (+ 5.44%, P < 0.001) and integrated discrimination improvement (8.21%, P < 0.001). These data demonstrate that LAA strain and strain rate, as measured via 2D-STI, can offer value when assessing LAA function in AF patients, potentially providing further predictive value to extant clinical risk scoring strategies. [ABSTRACT FROM AUTHOR]

In the theory of traditional Chinese medicine, acupoints refer to special points and areas on the meridian line of the human body. Traditional Chinese medicine believes that the application of unique techniques such as pressing, kneading, rubbing, pushing, and patting to acupoints or massage with the help of specific tools has the effects of promoting blood circulation, dredging meridians, and eliminating fatigue. At present, most automatic massage devices are for large-area massage of the trunk, and few are specifically for acupoint massage of the limbs. First, this paper analyzes the characteristics of traditional Chinese medical acupoint massage and then obtains the design index of an automatic acupoint massage device. After that, based on the principle of a series elastic actuating mechanism, a flexible uni-acupoint massage device and control system, imitating the acupoint massage technique of traditional Chinese medicine, were designed. In order to analyze the massage force of the massage device, the man–machine contact dynamic model of the massage device was established, and the force of the massage device was simulated and analyzed. Finally, an experimental platform was built to verify the massage force and massage process of the massage device. The experimental results show that the massage device designed in this paper meets the indexes of traditional Chinese medical massage, in terms of the massage process and massage force, and verify the rationality of the design.

The field of computer vision has shown great potential for the identification of crops at large scales based on multispectral images. However, the challenge in designing crop identification networks lies in striking a balance between accuracy and a lightweight framework. Furthermore, there is a lack of accurate recognition methods for non-large-scale crops. In this paper, we propose an improved encoder-decoder framework based on DeepLab v3+ to accurately identify crops with different planting patterns. The network employs ShuffleNet v2 as the backbone to extract features at multiple levels. The decoder module integrates a convolutional block attention mechanism that combines both channel and spatial attention mechanisms to fuse attention features across the channel and spatial dimensions. We establish two datasets, DS1 and DS2, where DS1 is obtained from areas with large-scale crop planting, and DS2 is obtained from areas with scattered crop planting. On DS1, the improved network achieves a mean intersection over union (mIoU) of 0.972, overall accuracy (OA) of 0.981, and recall of 0.980, indicating a significant improvement of 7.0%, 5.0%, and 5.7%, respectively, compared to the original DeepLab v3+. On DS2, the improved network improves the mIoU, OA, and recall by 5.4%, 3.9%, and 4.4%, respectively. Notably, the number of parameters and giga floating-point operations (GFLOPs) required by the proposed Deep-agriNet is significantly smaller than that of DeepLab v3+ and other classic networks. Our findings demonstrate that DeepagriNet performs better in identifying crops with different planting scales, and can serve as an effective tool for crop identification in various regions and countries. [ABSTRACT FROM AUTHOR]

We aimed to study the regulatory roles and mechanism of circular nuclear factor IX (circNFIX) in cancer growth and stemness properties of ovarian cancer (OC). CircNFIX and SH3RF3 levels in OC tissues and cells were tested by quantitative real‐time PCR. RNase R treatment quantified circNFIX RNA stability. Molecular interaction among circNFIX, LIN28B, and SH3RF3 was predicted by bioinformatics software and validated through RNA immunoprecipitation (RIP) assay. The gain‐ or loss‐experiments of circNFIX on capabilities of metastasis and stemness in vitro were assessed using Cell Counting Kit‐8, Transwell, western blot, and sphere‐formation assays. CircNFIX and SH3RF3 were markedly elevated in OC tissues and OC cells. Knocking down circNFIX repressed the proliferation, migration, invasion, and stemness properties of A2780 and SKOV3 cells. The RIP assay verified the direct binding relationship between LIN28B, circNFIX, and SH3RF3. Additionally, overexpression of circNFIX elevated the SH3RF3 expression, while this effect was reversed by LIN28B silence. Rescue experiments demonstrated that the overexpression of SH3RF3 reversed the knockdown of circNFIX on OC cells' proliferation, metastasis, and stemness properties. CircNFIX improved the mRNA stability and translation of SH3RF3 via recruiting LIN28B, thus promoting the proliferation, invasion, and stemness properties of OC cells in vitro. [ABSTRACT FROM AUTHOR]

Southern California, USA, has been suffering severe surface deformation due to its active crustal movement under the north–south compression of the Pacific Plate and North American Plate. Meanwhile, affected by groundwater extraction and recharge, oil exploitation, surface subsidence, uplift, and seasonal deformation occur commonly in this region. In this paper, multi-path SAR datasets were collected to investigate and monitor surface deformation in Southern California. The unified simultaneous least squares (USLS) approach is applied to remove the deformation discontinuity between adjacent SAR image paths. Multiple deformation patterns of structural faults, groundwater withdrawal, and oil exploitation are observed with the interferometric synthetic aperture radar (InSAR) technique. The InSAR-derived results were validated with GPS monitoring data. The correlations between land deformation and groundwater withdrawal, faults, and precipitation were intensively analyzed, finding out and mastering the magnitude and characteristics of ground deformation in Southern California. [ABSTRACT FROM AUTHOR]

Ovarian cancer (OC) is a gynecological cancer with high mortality. OC‐derived exosomal circRNAs can regulate angiogenesis. This study aims to explore the role and mechanism of exosomal circRNA nuclear factor I X (CircNFIX) derived from OC cells in angiogenesis. Quantitative real‐time polymerase chain reaction was employed to evaluate the levels of circNFIX, miR‐518a‐3p, and tripartite motif protein 44 (TRIM44) in OC and adjacent tissues. Exosomes from the ovarian surface epithelial cell (HOSEpiC) and OC cells (SKOV3 or OVCAR3) were isolated by differential centrifugation. Exosomes were cocultured with the human umbilical vein endothelial cells (HUVECs). The angiogenesis capacity was analyzed by Tube formation assay. 3‐(4,5‐dimethyl‐2‐thiazolyl)‐2,5‐diphenyl‐2‐H‐tetrazolium bromide (MTT) and Transwell assays were used to determine the cell viability and migration ability. The dual‐luciferase report, RNA immunoprecipitation (RIP), and RNA pull‐down assays were applied to validate the gene's interaction. CircNFIX and TRIM44 expression were higher and miR‐518a‐3p was lower in OC tissues than in the adjacent tissues. Upregulated circNFIX and TRIM44 were significantly correlated with the tumor size and International Federation of Gynecology and Obstetrics (FIGO) stage of OC patients. HUVECs treated OC‐derived exosomes had higher proliferation, migration, and angiogenesis capacities than the control group. While OC‐derived exosomal circNFIX silencing restrained HUVECs' proliferation, migration, and angiogenesis, compared with the OC‐derived exosomes group. OC‐derived exosomal circNFIX positively regulated TRIM44 expression by targeting miR‐518a‐3p in HUVECs. OC‐derived exosomal circNFIX promoted angiogenesis by regulating the Janus‐activated kinase/signal transducer and activator of transcription 1 (JAK/STAT1) pathway via miR‐518a‐3p/TRIM44 axis in HUVECs. [ABSTRACT FROM AUTHOR]

When an electromagnetic wave passes through the atmosphere, due to variation of atmospheric parameters, its propagation path is usually altered and the propagation speed also changes. Therefore, errors will be induced in triangulation measurement with electronic surveying robots, delimiting the accuracy of trigonometric leveling. Targeting at improving the accuracy of trigonometric leveling, a correction model based on atmospheric refraction coefficients is proposed in this article. First, based on the meteorological parameters collected on-site and Rüeger equation, influence of the meteorological parameters (e.g., temperature, atmospheric pressure, humidity, and CO2) on the refractive index are analyzed. Furthermore, gradient models of temperature, humidity, and atmospheric pressure with reference to height are established. In order to build the atmospheric gradient models of the optical path, height difference between the optical path and the ground is estimated with a precise digital elevation model generated by laser scanning. On this basis, the vertical atmospheric refraction coefficient model is proposed and used to correct the trigonometric leveling data measured by surveying robots. By conducting experimental studies over two open-pit iron mines with large topographic relief and comparing with first-class leveling data, reliability of the proposed atmospheric refraction coefficient model is assessed. The outcome of this article has demonstrated that by adopting the proposed model, accuracy of trigonometric leveling can meet the requirements of second-class leveling. [ABSTRACT FROM AUTHOR]

"Zou Fan" is currently the largest "tree hole" on Weibo, where people having suicidal ideation often express their thoughts and use this channel to seek support. Therefore, early suicide monitoring and timely crisis intervention based on artificial intelligence technology are needed for this social media user group. This research was based on the knowledge graph technology, whereby "Tree Hole Intelligent Agent" (i.e., Artificial Intelligence Program) was used to identify "Zou Fan Tree Hole" users at high risk for suicide, and then, the "Tree Hole Action" carried out proactive suicide crisis intervention with them. The "Tree Hole Action" has temporarily prevented 3,629 potential suicides. The "Tree Hole Action" plays a significant role in suicide risk monitoring and crisis intervention for social media users and has been seen to have an important social impact. [ABSTRACT FROM AUTHOR]

BACKGROUND: In recent years, molecular imaging combined with medical imaging technology and targeted molecular probes have gradually become a research focus. The targeted tissues at the molecular level can be observed using molecular imaging, medical imaging technology, and targeted molecular probes in combination to realize non-invasive imaging of the occurrence and development of the diseases. OBJECTIVE: To develop the magnetic targeted nanoparticle probes, observe the ultrasound/CT/MRI imaging properties in vitro, and investigate their targeting ability to rat hepatic stellate cells in vitro. METHODS: Taking poly(lactic-co-glycolic acid) (PLGA) polymer as the shell, cyclic arginine-glycine-aspartic acid (eRGO) octapeptide as the ligand, targeted magnetic nanoparticles with superparamagnetic Fe3O4 embedded in the shell and perfluorooctyl bromide(PFOB) loaded in the core were prepared by double emulsion evaporation method. The physical and chemical properties of the nanoparticles were detected. The ultrasound/CT/MRI multi-modal imaging properties of the nanoparticles at different concentrations diluted with double-distilled water were tested in vitro. Cyclic RGD peptide immobilization on PLGA-Fe3O4-PFOB NPs was completed through the amide condensation reaction. The conjugation efficiency of the eRGO on PLGA-Fe3O4-PFOB NPs and targeting ability of targeted magnetic nanoparticles in vitro were verified. Cytotoxicity experiments were used to measure the toxic effects of nanoparticles at different concentrations on BRL-3A cells in each group. RESULTS AND CONCLUSION: The targeted magnetic nanoparticles with the average size of (221.5±60.3) nm were uniform in dispersion and size. The prepared individual nanoparticle was spherical with the superparamagnetic Fe3O4 scattered on the shell. The encapsulation rate of Fe3O4 was 38%. In vitro ultrasound imaging and CT imaging signal decreased gradually as the concentrations of the nanoparticle suspension decreased. The T2-weighted signal of MRI decreased gradually with the increase of the concentrations of magnetic particle Fe3O4. Flow cytometry results showed that 94.13% of the eRGD was bound to the nanoparticles. In vitro cell targeting experiments showed that compared to PLGA-Fe3O4-PFOB NPs, cRGD-PLGA-Fe3O4-PFOB NPs exhibited greater cell targeting and affinity efficiency to hepatic stellate cells. Cytotoxicity experiments results showed the nanoparticles had no significant influence on cell viability of the BRL-3A cells. These results suggest that targeted magnetic nanoprobe cannot only be used as a multi-modal imaging contrast agent for ultrasound/CT/MRI, but also exhibits a strong specific affinity to rat hepatic stellate cells in vitro. It has great potential for the early diagnosis of liver fibrosis. [ABSTRACT FROM AUTHOR]

SAR Interferometry (InSAR) is a powerful technique for mapping land surface deformation, but single one-dimensional (1D) InSAR line-of-sight (LOS) measurement limits its application in three-dimensional (3D) displacement retrieval. Traditional methods were developed for measuring large-scale deformation. In this paper, to retrieve the slow 3D deformation process in the Jiaju landslide, a surface-parallel flow model is applied, according to the existing geological data gained from this landslide. Nine ENVISAT ASAR images and 19 ALOS PALSAR images were collected to reconstruct the 3D deformation field. An iterative method for correcting the characteristic value (IMCCV) with maximum likelihood estimation (M-estimation) adaptively generates an accurate stochastic model. The 3D deformation measurements show that the northern part of the Jiaju landslide clearly had horizontal deformation with the largest deformation velocity exceeding 15 cm year−1, while the southern part was relatively stable. Similarly, large vertical deformation appeared in the northern part (−2 cm year−1) and little deformation occurred in the southern part (−0.5 cm year−1). Compared with GPS measurements, the standard deviation is 1.4 cm year−1 and 0.7 cm year−1 in horizontal and vertical directions, respectively. Therefore, the Jiaju landslide exhibited movements in the horizontal direction accompanied by slight settlement in the vertical direction. [ABSTRACT FROM AUTHOR]

Graphical abstract Abstract Breast cancer is a severe threat to the health and lives of women due to its difficult early diagnosis and the unsatisfactory therapeutic efficacy of breast cancer treatments. The development of theranostic strategies to combat breast cancer with high accuracy and effectiveness is therefore urgently needed. In this study, we describe a near-infrared (NIR) light-controllable, targeted and biocompatible drug delivery nanoplatform (PFH-PTX@PLGA/SPIO-Her) for photoacoustic (PA)/ultrasound (US) bimodal imaging-guided photothermal (PTT)/chemo synergistic cancer therapy of breast cancer. Carboxyl-modified PEGylated poly (lactic-co-glycolic acid) (PLGA-PEG-COOH) constituted the skeleton of the nanoplatform. Especially, the antibody Herceptin was modified onto the surface of nanoplatform for active HER2-targing to facilitate the tumor accumulation of the nanoplatform. The encapsulated superparamagnetic iron oxide (SPIO) nanoparticles could be employed as an excellent PA imaging agent to guide tumor therapy. When exposed to NIR light, the SPIO also could transform NIR light into thermal energy for photothermal ablation of tumor. The NIR-induced thermal effect subsequently triggered the optical droplet vaporization (ODV) of perfluorohexane (PFH) to generate PFH gas bubbles, which not only achieved the US imaging enhancement, but also contributed to the release of loaded paclitaxel (PTX) from the nanoplatform for significantly improving PTT therapeutic efficacy. Our results demonstrated that the targeted tumor accumulation, accurate real-time bimodal imaging, and the abundant drug release at the tumor site were all closely associated with the PTT therapeutic efficacy. Therefore, the theranostic nanoplatform is a very promising strategy for targeted imaging-guided photothermal/chemo synergistic tumor therapy with high therapeutic efficacy and minimized side effects. Statement of Significance Breast cancer is the most frequent cancer in women. Herein, we successfully developed a light-controllable and HER2 targeted theranostic nanoparticels (PFH-PTX@PLGA/SPIO-Her) as a specific drug delivery nanoplatform to overcome the low accuracy of tumor detection and the low specificity of traditional chemo-therapeutic protocols. The study demonstrated that PFH-PTX@PLGA/SPIO-Her could actively target to breast cancer cells with positive HER2 expression. The biocompatible PFH-PTX@PLGA/SPIO-Her nanoparticles as both photoacoustic/ultrasound bimodal imaging agents, photothermal-conversion nanomaterials (photothermal hyperthermia) and controllable drug delivery nanoagents (optical droplet vaporization) have completely eradicated the tumor without severe side effects. The theranostic strategy not only integrates strengthens of traditional imaging or therapeutic modalities, but also paves a new way for the efficient cancer treatment by taking the advantage of quickly-developing nanomedicine. [ABSTRACT FROM AUTHOR]

The purpose of this study was to develop a sonosensitizer-loaded multi-functional ultrasound (US) contrast agent for both tumour therapy and imaging. The hematoporphyrin (HP)-encapsulated poly(lactic-co-glycolic acid) microbubbles (HP-PLGA-MBs) were prepared and filled with perfluorocarbon gases. The enhancement of US imaging and its sonodynamically induced anti-tumour effect were evaluated by both in vitro and in vivo experiments. The HP-PLGA-MBs have a narrow size distribution and smooth surface with a mean diameter of 702.6 ± 56.8 nm and HP encapsulation efficiency of 63.50 ± 1.26% and drug-loading efficiency of 2.15 ± 0.13%. The HP-PLGA-MBs could well enhance the ultrasound imaging both in vitro and in vivo. A significant anti-tumour effect was obtained by HP-PLGA-MBs mediated sonodynamic therapy. The tumour growth rate and the tumour proliferation index were the lowest in the HP-PLGA-MBs plus sonication group. And the tumour cell apoptotic index was the biggest in the HP-PLGA-MBs plus sonication group. In conclusion, a sonosensitizer-loaded multi-functional contrast agent was constructed and the feasibility was demonstrated, which might provide a novel strategy for tumour imaging and therapy. [ABSTRACT FROM AUTHOR]

Objective: To prepare the Gd‐DTPA‐loaded poly (lactic‐co‐glycolic acid) (PLGA) microbubbles for both ultrasound imaging and MRI imaging. Methods: Biodegradable high‐molecular‐weight poly (lactic‐co‐glycolic acid) (PLGA) was used as an encapsulating vehicle to fabricate a contrast agent composed of gadolinium diethylenetriamine pentaacetic acid (Gd‐DTPA) and fluorocarbon‐filled microbubbles by using double emulsion method. The morphology, size, and Gd loading capacity of PLGA microparticles were assessed. The efficacy of the contrast agent for ultrasound and magnetic resonance (MR) imaging was evaluated by in vivo imaging of hepatic vessels and the liver parenchyma of rabbit following injection of the contrast agent. Additionally, the liver and kidney functions were examined before and at 7, 14, 30 days after injection. Results: Electron microscopy showed Gd loaded PLGA microbubbles were spherical in shape. The mean diameter were 1.47 ± 0.38 μm and the Gd loading was 25 ± 2 μg/mg. Right after the injection of the PLGA microbubbles, the ultrasound echo intensity of hepatic vessels and the liver parenchyma was significantly enhanced. Moreover, enhanced signal intensity of the liver parenchyma on MR images was observed for ∼30 min after injection of the contrast agent. Neither marked changes in the liver and kidney functions nor other severe complications were detected during the follow‐up period. Conclusion: Gd‐DTPA‐loaded PLGA microbubbles could enhance both ultrasound imaging and MRI imaging. © 2010 Wiley Periodicals, Inc. J Biomed Mater Res Part B: Appl Biomater, 2010. [ABSTRACT FROM AUTHOR]

Variations in flowering time and plant architecture have a crucial impact on crop biomass and yield, as well as the aesthetic value of ornamental plants. Aechmea fasciata, a member of the Bromeliaceae family, is a bromeliad variety that is commonly cultivated worldwide. Here, we report the characterization of AfSPL14, a squamosa promoter binding protein-like gene in A. fasciata. AfSPL14 was predominantly expressed in the young vegetative organs of adult plants. The expression of AfSPL14 could be upregulated within 1 h by exogenous ethephon treatment. The constitutive expression of AfSPL14 in Arabidopsis thaliana caused early flowering and variations in plant architecture, including smaller rosette leaves and thicker and increased numbers of main inflorescences. Our findings suggest that AfSPL14 may help facilitate the molecular breeding of A. fasciata, other ornamental and edible bromeliads (e.g., pineapple), and even cereal crops. [ABSTRACT FROM AUTHOR]

Nanoprobes are small enough to circulate within the vasculature and can reach tumour tissues through the endothelial gap, providing a new strategy for accurate tumour monitoring and imaging-guided antitumour therapy at the molecular level. Both photoacoustic and ultrasonic imaging are noninvasive tools for cancer detection via the application of nanoprobes. In this study, a polymeric multifunctional nanoparticle probe loaded with gold nanorods (Au-NRs) and liquid perfluorocarbon (perfluorinated hexane/PFH) and conjugated to a monoclonal antibody (MAGE-1 antibody) to melanoma-associated antigens (MAGE) targeting melanoma was successfully prepared by the double emulsion and carbodiimide methods as a targeted photoacoustic/ultrasound dual-mode imaging contrast agent (MAGE-Au-PFH-NPs). Cell-targeting experiments in vitro showed large amounts of MAGE-Au-PFH-NPs surrounding B16 melanoma cells in the targeted group. The photoacoustic signal in the targeted group was significantly increased, and the duration was longer than that in the untargeted group in vivo . The photoacoustic signal of the nanoprobes was enhanced with increased Au-NR concentration in the photoacoustic experiment in vitro . The enhanced signal was observed by ultrasound after 808-nm laser irradiation. A cytotoxicity and biocompatibility test showed that MAGE-Au-PFH-NPs exhibited good biological safety. The MAGE-Au-PFH-NPs can be used as a photoacoustic/ultrasound dual-mode contrast agent to lay the foundation for a promising new approach for the noninvasive targeting, monitoring and treatment of tumours. [ABSTRACT FROM AUTHOR]

Abstract: Objective: The purpose of this study was to explore the feasibility of using ultrasound-targeted microbubble destruction to treat liver fibrosis induced by hepatocyte growth factor (HGF). Methods: Forty Wistar rats were divided into five groups after the models of liver fibrosis were prepared: (1) HGF, ultrasound, and microbubbles (HGF+US/MB); (2) HGF and ultrasound (HGF+US); (3) HGF and microbubbles (HGF+MB); (4) HGF (HGF); and (5) model alone (MA). All rats were killed after being transfected for 14 days. Recovery of the liver was detect by diffusion-weighted imaging (DWI) and pathological methods. Collagen I expression was detected by immunohistochemistry. Hepatocyte growth factor expression in the liver was detect by western blotting. Results: The results of DWI and pathological examination showed the recovery of liver in HGF+US/MB group were better than those of other groups. In HGF+US/MB group, collagen I expression was less, and HGF protein was the highest among all the groups. Conclusions: Ultrasound-targeted microbubble destruction could deliver HGF into the fibrotic liver and produce an antifibrosis effect, which could provide a novel strategy for gene therapy of liver fibrosis. [Copyright &y& Elsevier]