Your browser doesn't support javascript.
loading
Mostrar: 20 | 50 | 100
Resultados 1 - 20 de 130
Filtrar
1.
Cell Mol Neurobiol ; 2021 Feb 23.
Artigo em Inglês | MEDLINE | ID: mdl-33620674

RESUMO

Brain ischemia reperfusion injury (BIRI) is defined as a series of brain injury accompanied by inflammation and oxidative stress. Astrocyte-derived extracellular vesicles (EVs) are importantly participated in BIRI with involvement of microRNAs (miRs). Our study aimed to discuss the functions of miR-29a from astrocyte-derived EVs in BIRI treatment. Thus, astrocyte-derived EVs were extracted. Oxygen and glucose deprivation (OGD) cell models and BIR rat models were established. Then, cell and rat activities and pyroptosis-related protein levels in these two kinds of models were detected. Functional assays were performed to verify inflammation and oxidative stress. miR-29a expression in OGD cells and BIR rats was measured, and target relation between miR-29a and tumor protein 53-induced nuclear protein 1 (TP53INP1) was certified. Rat neural function was tested. Astrocyte-derived EVs improved miR-29a expression in N9 microglia and rat brains. Astrocyte-derived EVs inhibited OGD-induced injury and inflammation in vitro, reduced brain infarction, and improved BIR rat neural functions in vivo. miR-29a in EVs protected OGD-treated cells and targeted TP53INP1, whose overexpression suppressed the protective function of EVs on OGD-treated cells. miR-29a alleviated OGD and BIRI via downregulating TP53INP1 and the NF-κB/NLRP3 pathway. Briefly, our study demonstrated that miR-29a in astrocyte-derived EVs inhibits BIRI by downregulating TP53INP1 and the NF-κB/NLRP3 axis.

2.
Drug Deliv ; 28(1): 454-462, 2021 Dec.
Artigo em Inglês | MEDLINE | ID: mdl-33620010

RESUMO

This study aimed to construct a transdermal iontophoresis delivery system for terazosin hydrochloride (IDDS-TEH), which included a positive and negative electrode hydrogel prescription. Intact guinea pig skin was used as a model for the skin barrier function, and the current intensity, terazosin hydrochloride (TEH) concentration, pH, competitive salt, and transdermal enhancer properties were studied. The blood drug concentration was determined in Sprague-Dawley (SD) rats using HPLC, and the antihypertensive effects of IDDS-TEH were evaluated in spontaneously hypertensive rats (SHRs). The results showed that the steady-state penetration rate of TEH increased (from 80.36 µg·cm-2·h-1 to 304.93 µg·cm-2·h-1), followed by an increase in the current intensity (from 0.10 mA·cm-2 to 0.49 mA·cm-2). The pH values also had a significant influence on percutaneous penetration. The blood concentration of IDDS-TEH was significantly higher (p < .05) than with passive diffusion, which could not be detected. The main pharmacokinetic parameters of the high current group (0.17 mA·cm-2) and the low current group (0.09 mA·cm-2) were AUC0-t: 5873.0 ng·mL-1·h and 2493.7 ng·mL-1·h, respectively. Meanwhile, the pharmacodynamic results showed that IDDS-TEH significantly decreased the blood pressure of SHRs compared with the TEH hydrogel without loading current. Therefore, TEH could be successfully delivered by the transdermal iontophoresis system in vitro and in vivo, and further clinical studies should be explored to develop a therapeutically useful protocol.

3.
Nano Lett ; 2021 Feb 17.
Artigo em Inglês | MEDLINE | ID: mdl-33596656

RESUMO

Efficient endosomal escape is the most essential but challenging issue for siRNA drug development. Herein, a series of quaternary ammonium-based amphiphilic triblock polymers harnessing an elaborately tailored pH-sensitive hydrophobic core were synthesized and screened. Upon incubating in an endosomal pH environment (pH 6.5-6.8), mPEG45-P(DPA50-co-DMAEMA56)-PT53 (PDDT, the optimized polymer) nanomicelles (PDDT-Ms) and PDDT-Ms/siRNA polyplexes rapidly disassembled, leading to promoted cytosolic release of internalized siRNA and enhanced silencing activity evident from comprehensive analysis of the colocalization and gene silencing using a lysosomotropic agent (chloroquine) and an endosomal trafficking inhibitor (bafilomycin A1). In addition, PDDT-Ms/siPLK1 dramatically repressed tumor growth in both HepG2-xenograft and highly malignant patient-derived xenograft models. PDDT-Ms-armed siPD-L1 efficiently blocked the interaction of PD-L1 and PD-1 and restored immunological surveillance in CT-26-xenograft murine model. PDDT-Ms/siRNA exhibited ideal safety profiles in these assays. This study provides guidelines for rational design and optimization of block polymers for efficient endosomal escape of internalized siRNA and cancer therapy.

4.
IEEE Trans Cybern ; PP2021 Feb 02.
Artigo em Inglês | MEDLINE | ID: mdl-33531319

RESUMO

Being able to learn discriminative features from low-quality images has raised much attention recently due to their wide applications ranging from autonomous driving to safety surveillance. However, this task is difficult due to high variations across images, such as scale, rotation, illumination, and viewpoint, and distortions in images, such as blur, low contrast, and noise. Image preprocessing could improve the quality of the images, but it often requires human intervention and domain knowledge. Genetic programming (GP) with a flexible representation can automatically perform image preprocessing and feature extraction without human intervention. Therefore, this study proposes a new evolutionary learning approach using GP (EFLGP) to learn discriminative features from images with blur, low contrast, and noise for classification. In the proposed approach, we develop a new program structure (individual representation), a new function set, and a new terminal set. With these new designs, EFLGP can detect small regions from a large input low-quality image, select image operators to process the regions or detect features from the small regions, and output a flexible number of discriminative features. A set of commonly used image preprocessing operators is employed as functions in EFLGP to allow it to search for solutions that can effectively handle low-quality image data. The performance of EFLGP is comprehensively investigated on eight datasets of varying difficulty under the original (clean), blur, low contrast, and noise scenarios, and compared with a large number of benchmark methods using handcrafted features and deep features. The experimental results show that EFLGP achieves significantly better or similar results in most comparisons. The results also reveal that EFLGP is more invariant than the benchmark methods to blur, low contrast, and noise.

5.
IEEE Trans Cybern ; PP2021 Feb 02.
Artigo em Inglês | MEDLINE | ID: mdl-33531323

RESUMO

Dynamic flexible job shop scheduling (JSS) has received widespread attention from academia and industry due to its practical application value. It requires complex routing and sequencing decisions under unpredicted dynamic events. Genetic programming (GP), as a hyperheuristic approach, has been successfully applied to evolve scheduling heuristics for JSS due to its flexible representation. However, the simulation-based evaluation is computationally expensive since there are many calculations based on individuals for making decisions in the simulation. To improve training efficiency, this article proposes a novel multifidelity-based surrogate-assisted GP. Specifically, multifidelity-based surrogate models are first designed by simplifying the problem expected to be solved. In addition, this article proposes an effective collaboration mechanism with knowledge transfer for utilizing the advantages of multifidelity-based surrogate models to solve the desired problems. This article examines the proposed algorithm in six different scenarios. The results show that the proposed algorithm can dramatically reduce the computational cost of GP without sacrificing the performance in all scenarios. With the same training time, the proposed algorithm can achieve significantly better performance than its counterparts in most scenarios while no worse in others.

6.
Artigo em Inglês | MEDLINE | ID: mdl-33556026

RESUMO

Deep convolutional neural networks (CNNs) have demonstrated promising performance on image classification tasks, but the manual design process becomes more and more complex due to the fast depth growth and the increasingly complex topologies of CNNs. As a result, neural architecture search (NAS) has emerged to automatically design CNNs that outperform handcrafted counterparts. However, the computational cost is immense, e.g., 22,400 GPU-days and 2000 GPU-days for two outstanding NAS works named NAS and NASNet, respectively, which motivates this work. A new effective and efficient surrogate-assisted particle swarm optimization (PSO) algorithm is proposed to automatically evolve CNNs. This is achieved by proposing a novel surrogate model, a new method of creating a surrogate data set, and a new encoding strategy to encode variable-length blocks of CNNs, all of which are integrated into a PSO algorithm to form the proposed method. The proposed method shows its effectiveness by achieving the competitive error rates of 3.49% on the CIFAR-10 data set, 18.49% on the CIFAR-100 data set, and 1.82% on the SVHN data set. The CNN blocks are efficiently learned by the proposed method from CIFAR-10 within 3 GPU-days due to the acceleration achieved by the surrogate model and the surrogate data set to avoid the training of 80.1% of CNN blocks represented by the particles. Without any further search, the evolved blocks from CIFAR-10 can be successfully transferred to CIFAR-100, SVHN, and ImageNet, which exhibits the transferability of the block learned by the proposed method.

7.
Cancer Cell Int ; 21(1): 71, 2021 Jan 22.
Artigo em Inglês | MEDLINE | ID: mdl-33482821

RESUMO

BACKGROUND: Recent studies have established the roles of microRNAs (miRNAs) in cancer progression. The aberrant expression of miR-335-5p has been reported in many cancers, including gastric cancer (GC). In this study, the precise roles of miR-335-5p in GC as well as the molecular mechanisms underlying its effects, including the role of its target MAPK10, were evaluated. METHODS: Quantitative real-time PCR was used to evaluate miR-335-5p levels in GC cell lines and tissues. MTT and colony formation assays were used to detect cell proliferation, and Transwell and wound-healing assays were used to evaluate the invasion and migration of GC cells. The correlation between levels of miR-335-5p and the cell cycle-related target gene mitogen-activated protein kinase 10 (MAPK10) in GC was analyzed. In addition, the candidate target was evaluated by a luciferase reporter assay, qRT-PCR, and western blotting. RESULTS: The levels of miR-335-5p were downregulated in GC tissues and cell lines. Furthermore, miR-335-5p inhibited the proliferation and migration of GC cells and induced apoptosis. Additionally, miR-335-5p arrested the cell cycle at the G1/S phase in GC cells in vitro. Levels of miR-335-5p and the cell cycle-related target gene MAPK10 in GC were correlated, and MAPK10 was directly targeted by miR-335-5p. CONCLUSIONS: These data suggest that miR-335-5p is a tumor suppressor and acts via MAPK10 to inhibit GC progression.

8.
IEEE Trans Cybern ; PP2021 Feb 04.
Artigo em Inglês | MEDLINE | ID: mdl-33382668

RESUMO

Feature selection (FS) is an important data preprocessing technique in data mining and machine learning, which aims to select a small subset of information features to increase the performance and reduce the dimensionality. Particle swarm optimization (PSO) has been successfully applied to FS due to being efficient and easy to implement. However, most of the existing PSO-based FS methods face the problems of trapping into local optima and computationally expensive high-dimensional data. Multifactorial optimization (MFO), as an effective evolutionary multitasking paradigm, has been widely used for solving complex problems through implicit knowledge transfer between related tasks. Inspired by MFO, this study proposes a novel PSO-based FS method to solve high-dimensional classification via information sharing between two related tasks generated from a dataset. To be specific, two related tasks about the target concept are established by evaluating the importance of features. A new crossover operator, called assortative mating, is applied to share information between these two related tasks. In addition, two mechanisms, which are variable-range strategy and subset updating mechanism, are also developed to reduce the search space and maintain the diversity of the population, respectively. The results show that the proposed FS method can achieve higher classification accuracy with a smaller feature subset in a reasonable time than the state-of-the-art FS methods on the examined high-dimensional classification problems.

9.
Chirality ; 2020 Dec 03.
Artigo em Inglês | MEDLINE | ID: mdl-33274501

RESUMO

Brivaracetam is a structural derivative of the chiral drug levetiracetam and has been approved for the adjuvant treatment of partial epilepsy. As a new antiepileptic drug, it is widely used in a variety of epilepsy models. In this study, a novel lipase M16 derived from Aspergillus oryzae WZ007 was cloned, expressed, and used for chiral resolution. Lipase M16 has a high enantioselectivity to the racemic substrate (R,S)-methyl 2-propylsuccinate 4-tert-butyl ester, and the intermediate (R)-2-propylsuccinic acid 4-tert-butyl ester of brivaracetam was obtained efficiently. Under optimal conditions, the enantiomeric excess of substrate was up to 99.26%, and the e.e.p was 96.23%. The conversion and apparent E value were 50.63% and 342.48, respectively. This study suggests a new biocatalytic resolution via lipase M16 for preparing the brivaracetam chiral intermediate and its potential application in the pharmaceutical industry.

10.
Aging (Albany NY) ; 12(22): 22564-22581, 2020 Nov 17.
Artigo em Inglês | MEDLINE | ID: mdl-33201838

RESUMO

Growth and differentiation factor 15 (GDF-15) has been studied as an important hallmark of cancer. However, the receptor of GDF-15 in pancreatic cancer cell remains unclear. Here, we investigated its biological effects in pancreatic ductal adenocarcinoma (PDAC). We found that aberrant GDF-15 expression positively correlated with poor survival of PDAC patients. GDF-15 protein enhanced tumor cell proliferation in two pancreatic cancer lines, AsPC-1 and BxPC-3. Knockdown GDF-15 attenuated its biological function in vitro and reduced PDAC cell tumorigenesis upon xenotransplantation into nude mice. Moreover, we identified that glial-derived neurotropic factor family receptor α-like (GFRAL) was upregulated in PDAC tissues and positively correlated with GDF-15 expression. High GFRAL expression was significantly associated with poor survival in PDAC patients. Furthermore, we identified that the biological effects of GDF-15 are mediated by its receptor GFRAL which is present in PDAC cells. After overexpression GFRAL in pancreatic cancer cells, the effect of GDF-15 was significantly enhanced. Overall, our findings demonstrated that the GDF-15 secreted by PDAC cells, binds to GFRAL, itself localized in PDAC cells, to promote cancer cell growth and metastasis through the GDF-15/GFRAL signaling pathway.

11.
Foods ; 9(11)2020 Oct 30.
Artigo em Inglês | MEDLINE | ID: mdl-33143312

RESUMO

Salmon is a highly perishable food due to temperature, pH, odor, and texture changes during cold storage. Intelligent monitoring and spoilage rapid detection are effective approaches to improve freshness. The aim of this work was an evaluation of IoT-enabled monitoring system (IoTMS) and electronic nose spoilage detection for quality parameters changes and freshness under cold storage conditions. The salmon samples were analyzed and divided into three groups in an incubator set at 0 °C, 4 °C, and 6 °C. The quality parameters, i.e., texture, color, sensory, and pH changes, were measured and evaluated at different temperatures after 0, 3, 6, 9, 12, and 14 days of cold storage. The principal component analysis (PCA) algorithm can be used to cluster electronic nose information. Furthermore, a Convolutional Neural Networks and Support Vector Machine (CNN-SVM) based algorithm is used to cluster the freshness level of salmon samples stored in a specific storage condition. In the tested samples, the results show that the training dataset of freshness is about 95.6%, and the accuracy rate of the test dataset is 93.8%. For the training dataset of corruption, the accuracy rate is about 91.4%, and the accuracy rate of the test dataset is 90.5%. The overall accuracy rate is more than 90%. This work could help to reduce quality loss during salmon cold storage.

12.
Evol Comput ; : 1-34, 2020 Nov 25.
Artigo em Inglês | MEDLINE | ID: mdl-33236924

RESUMO

The performance of image classification is highly dependent on the quality of the extracted features that are used to build a model. Designing such features usually requires prior knowledge of the domain and is often undertaken by a domain expert who, if available, is very costly to employ. Automating the process of designing such features can largely reduce the cost and efforts associated with this task. Image descriptors, such as local binary patterns, have emerged in computer vision, and aim at detecting keypoints, e.g., corners, line-segments and shapes, in an image and extracting features from those keypoints. In this paper, genetic programming (GP) is used to automatically evolve an image descriptor using only two instances per class by utilising a multi-tree program representation. The automatically evolved descriptor operates directly on the raw pixel values of an image and generates the corresponding feature vector. Seven well-known datasets were adapted to the few-shot setting and used to assess the performance of the proposed method and compared against six hand-crafted and one evolutionary computation-based image descriptor as well as three convolutional neural network (CNN) based methods. The experimental results show that the new method has significantly outperformed the competitor image descriptors and CNN-based methods. Furthermore, different patterns have been identified from analysing the evolved programs.

13.
IEEE Trans Cybern ; PP2020 Nov 25.
Artigo em Inglês | MEDLINE | ID: mdl-33237874

RESUMO

Feature extraction is an essential process in the intelligent fault diagnosis of rotating machinery. Although existing feature extraction methods can obtain representative features from the original signal, domain knowledge and expert experience are often required. In this article, a novel diagnosis approach based on evolutionary learning, namely, automatic feature extraction and construction using genetic programming (AFECGP), is proposed to automatically generate informative and discriminative features from original vibration signals for identifying different fault types of rotating machinery. To achieve this, a new program structure, a new function set, and a new terminal set are developed in AFECGP to allow it to detect important subband signals and extract and construct informative features, automatically and simultaneously. More important, AFECGP can produce a flexible number of features for classification. Having the generated features, k-Nearest Neighbors is employed to perform fault diagnosis. The performance of the AFECGP-based fault diagnosis approach is evaluated on four fault diagnosis datasets of varying difficulty and compared with 14 baseline methods. The results show that the proposed approach achieves better fault diagnosis accuracy on all the datasets than the competitive methods and can effectively identify different fault conditions of rolling bearing, gear, and rotor.

14.
IEEE Trans Cybern ; PP2020 Oct 29.
Artigo em Inglês | MEDLINE | ID: mdl-33119522

RESUMO

Cooperative co-evolutionary algorithms have addressed many large-scale problems successfully, but the nonseparable large-scale problems with overlapping subcomponents are still a serious difficulty that has not been conquered yet. First, the existence of shared variables makes the problem hard to be decomposed. Second, existing cooperative co-evolutionary frameworks usually cannot maintain the two crucial factors: high cooperation frequency and effective computing resource allocation, simultaneously when optimizing the overlapping subcomponents. Aiming at these two issues, this article proposes a new contribution-based cooperative co-evolutionary algorithm to decompose and optimize nonseparable large-scale problems with overlapping subcomponents effectively and efficiently: 1) a contribution-based decomposition method is proposed to assign the shared variables. Among all the subcomponents containing a shared variable, the one that contributes the most to the entire problem will include the shared variable and 2) to achieve the two crucial factors at the same time, a new contribution-based optimization framework is designed to award the important subcomponents based on the round-robin structure. Experimental studies show that the proposed algorithm performs significantly better than the state-of-the-art algorithms due to the effective grouping structure generated by the proposed decomposition method and the fast optimizing speed provided by the new optimization framework.

15.
IEEE Trans Cybern ; PP2020 Oct 20.
Artigo em Inglês | MEDLINE | ID: mdl-33079689

RESUMO

Dynamic flexible job-shop scheduling (DFJSS) is a challenging combinational optimization problem that takes the dynamic environment into account. Genetic programming hyperheuristics (GPHH) have been widely used to evolve scheduling heuristics for job-shop scheduling. A proper selection of the terminal set is a critical factor for the success of GPHH. However, there is a wide range of features that can capture different characteristics of the job-shop state. Moreover, the importance of a feature is unclear from one scenario to another. The irrelevant and redundant features may lead to performance limitations. Feature selection is an important task to select relevant and complementary features. However, little work has considered feature selection in GPHH for DFJSS. In this article, a novel two-stage GPHH framework with feature selection is designed to evolve scheduling heuristics only with the selected features for DFJSS automatically. Meanwhile, individual adaptation strategies are proposed to utilize the information of both the selected features and the investigated individuals during the feature selection process. The results show that the proposed algorithm can successfully achieve more interpretable scheduling heuristics with fewer unique features and smaller sizes. In addition, the proposed algorithm can reach comparable scheduling heuristic quality with much shorter training time.

16.
Bioprocess Biosyst Eng ; 43(12): 2131-2141, 2020 Dec.
Artigo em Inglês | MEDLINE | ID: mdl-32959146

RESUMO

Aspergillus oryzae lipase (AOL) is a potential biocatalyst for industrial application. In this study, a mutant lipase AOL-3F38N/V230R was screened through two rounds of directed evolution, resulting in a fourfold increase in lipase activity, and threefold in catalytic efficiency (kcat/Km), while maintaining its excellent stereoselectivity. AOL-3F38N/V230R enzyme activity was maximum at pH 7.5 and also at 40 °C. And compared with wild-type AOL-3, AOL-3F38N/V230R preferentially hydrolyzed the fatty acid ethyl ester carbon chain length from C4 to C6-C10. In the same catalytic reaction conditions, the conversion of (R,S)-ethyl-2-(4-hydroxyphenoxy) propanoate ((R,S)-EHPP) by AOL-3F38N/V230R can be increased 169.7% compared to the original enzyme. The e.e.s of (R,S)-EHPP achieved 99.4% and conversion about 50.2% with E value being 829.0. Therefore, AOL-3F38N/V230R was a potential biocatalyst for obtaining key chiral compounds for aryloxyphenoxy propionate (APP) herbicides.

17.
Brain Imaging Behav ; 2020 Sep 10.
Artigo em Inglês | MEDLINE | ID: mdl-32909105

RESUMO

The purpose of this study was to investigate cerebral blood flow (CBF) changes in hemodialysis patients with arterial spin labeling (ASL) and to correlate these changes with clinical risk factors and neurocognitive function. Thirty-two hemodialysis patients and 35 age-, sex-, and education-matched healthy controls (HCs) were recruited in this prospective study. The Mini-Mental State Examination (MMSE) was performed to evaluate neurocognitive function. Pulsed ASL was performed to measure CBF. Two independent sample t-test was used to explore the CBF difference between the patients and HCs. Multiple stepwise regression was used to investigate the risk factors for CBF in patients. Correlation analysis was used to explore the relationship between the MMSE scores and CBF changes with and without adjusting for anemia status. Compared to HCs, the hemodialysis patients showed significantly increased CBF in some neurocognition-related cerebral regions (all P < 0.001, Bonferroni corrected). Increased CBF in the right opercular and triangular part of the inferior frontal gyrus correlated with the poorer MMSE scores (r = -0.502, P = 0.004; r = -0.423, P = 0.018, FDR corrected) and these correlations still remained after adjusting for anemia status (r = -0.516, P = 0.005; r = -0.439, P = 0.019, FDR corrected). The increased dialysis duration, and decreased hemoglobin, hematocrit, and serum phosphorus were predictive risk factors for increased CBF (P < 0.05). In conclusion, long-term hemodialysis patients had increased CBF, which correlated with neurocognitive impairment, and after adjusting for the effect of anemia, the correlation still remained.

18.
Carbohydr Polym ; 247: 116743, 2020 Nov 01.
Artigo em Inglês | MEDLINE | ID: mdl-32829862

RESUMO

Tough and conductive hydrogels are promising materials for various applications. However, it remains a great challenge to develop an integrated hydrogel combining outstanding mechanical, conductive, and self-healing performances. Herein, we prepared a conductive, self-healing, and tough hydrogel by constructing synergistic multiple interaction among montmorillonite (MMT), Poly (acrylamide-co-acrylonitrile) (P(AAm-co-AN)), xanthan gum (XG) and ferric ion (Fe3+). The obtained xanthan gum/montmorillonite/Poly (acrylamide-co-acrylonitrile) (XG/MMT/PAAm) hydrogels showed high strain stress (0.48 MPa) and compressive stress (5.9 MPa) as well as good shape recovery after multiple loading-unloading cycle tests. Moreover, the XG/MMT/PAAm hydrogels have distinctive features such as remarkable resistance to fatigue and harsh environments, insensitivity to notch, conductive, biocompatible, pH-dependent swelling behaviors and self-healing. Therefore, the as-fabricated hydrogel delivers a new prospect for its applications in various fields, such as flexible conductive device and tissue engineering.

19.
Small ; 16(37): e2003290, 2020 Sep.
Artigo em Inglês | MEDLINE | ID: mdl-32794645

RESUMO

Bioimaging has revolutionized medicine by providing accurate information for disease diagnosis and treatment. Nanotechnology-based bioimaging is expected to further improve imaging sensitivity and specificity. In this context, supramolecular nanosystems based on self-assembly of amphiphilic dendrimers for single photon emission computed tomography (SPECT) bioimaging are developed. These dendrimers bear multiple In3+ radionuclides at their terminals as SPECT reporters. By replacing the macrocyclic 1,4,7,10-tetraazacyclododecane-1,4,7,10-tetraacetic acid cage with the smaller 1,4,7-triazacyclononane-1,4,7-triacetic acid scaffold as the In3+ chelator, the corresponding dendrimer exhibits neutral In3+ -complex terminals in place of negatively charged In3+ -complex terminals. This negative-to-neutral surface charge alteration completely reverses the zeta-potential of the nanosystems from negative to positive. As a consequence, the resulting SPECT nanoprobe generates a highly sought-after biodistribution profile accompanied by a drastically reduced uptake in liver, leading to significantly improved tumor imaging. This finding contrasts with current literature reporting that positively charged nanoparticles have preferential accumulation in the liver. As such, this study provides new perspectives for improving the biodistribution of positively charged nanosystems for biomedical applications.

20.
Heliyon ; 6(7): e04532, 2020 Jul.
Artigo em Inglês | MEDLINE | ID: mdl-32760833

RESUMO

Circular RNAs (circRNAs) are novel endogenous RNAs with vital roles in the pathology of various diseases. However, their role in sepsis-induced lung injury is unknown. In this study, high-throughput gene sequencing was used to analyze the expression profiles of circRNAs in lung specimens of mice grouped by acute lung injury induced by cecal ligation and puncture (CLP) and sham. To identify differentially expressed circRNAs, the left lungs of sham (n = 3) and CLP (n = 3) mice were used for high-throughput sequencing. A total of 919 circRNAs were identified. Of these, 38 circRNAs showed significantly different expression levels between the groups (P < 0.05, fold change ≥2). The levels of 20 circRNAs were up-regulated and those of 18 others were down-regulated. In bioinformatics analysis of the source genes of these circRNAs, the genes were closely associated with the inflammatory response (e.g., the TGF-ß, MAPK, Fc gamma R-mediated phagocytic, and VEGF pathways). Eight circRNAs with large intergroup differences, small intragroup differences, and high expression were selected for further validation by qRT-PCR. Two of the eight were significantly different. These two circRNAs were annotated with circRNA/miRNA interaction information downloaded from the TargetScan and miRanda databases and visualized. Our results provide novel insights into the roles of circRNAs in sepsis-induced acute lung injury.

SELEÇÃO DE REFERÊNCIAS
DETALHE DA PESQUISA