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1.
Med Image Anal ; 59: 101568, 2020 Jan.
Artigo em Inglês | MEDLINE | ID: mdl-31622838

RESUMO

Accurate and simultaneous segmentation and full quantification (all indices are required in a clinical assessment) of the myocardial infarction (MI) area are crucial for early diagnosis and surgical planning. Current clinical methods remain subject to potential high-risk, nonreproducibility and time-consumption issues. In this study, a deep spatiotemporal adversarial network (DSTGAN) is proposed as a contrast-free, stable and automatic clinical tool to simultaneously segment and quantify MIs directly from the cine MR image. The DSTGAN is implemented using a conditional generative model, which conditions the distributions of the objective cine MR image to directly optimize the generalized error of the mapping between the input and the output. The method consists of the following: (1) A multi-level and multi-scale spatiotemporal variation encoder learns a coarse to fine hierarchical feature to effectively encode the MI-specific morphological and kinematic abnormality structures, which vary for different spatial locations and time periods. (2) The top-down and cross-task generators learn the shared representations between segmentation and quantification to use the commonalities and differences between the two related tasks and enhance the generator preference. (3) Three inter-/intra-tasks to label the relatedness discriminators are iteratively imposed on the encoder and generator to detect and correct the inconsistencies in the label relatedness between and within tasks via adversarial learning. Our proposed method yields a pixel classification accuracy of 96.98%, and the mean absolute error of the MI centroid is 0.96 mm from 165 clinical subjects. These results indicate the potential of our proposed method in aiding standardized MI assessments.

2.
Med Image Anal ; 59: 101591, 2020 Jan.
Artigo em Inglês | MEDLINE | ID: mdl-31704452

RESUMO

Accurate and automated cardiac bi-ventricle quantification based on cardiac magnetic resonance (CMR) image is a very crucial procedure for clinical cardiac disease diagnosis. Two traditional and commensal tasks, i.e., bi-ventricle segmentation and direct ventricle function index estimation, are always independently devoting to address ventricle quantification problem. However, because of inherent difficulties from the variable CMR imaging conditions, these two tasks are still open challenging. In this paper, we proposed a unified bi-ventricle quantification framework based on commensal correlation between the bi-ventricle segmentation and direct area estimation. Firstly, we proposed the area commensal correlation between the two traditional cardiac quantification tasks for the first time, and designed a novel deep commensal network (DCN) to join these two commensal tasks into a unified framework based on the proposed commensal correlation loss. Secondly, we proposed an differentiable area operator to model the proposed area commensal correlation and made the proposed model continuously differentiable. Thirdly, we proposed a high-efficiency and novel uncertainty estimation method through one-time inference based on cross-task output variability. And finally DCN achieved end-to-end optimization and fast convergence as well as uncertainty estimation with one-time inference. Experiments on the four open accessible short-axis CMR benchmark datasets (i.e., Sunnybrook, STACOM 2011, RVSC, and ACDC) showed that the proposed method achieves best bi-ventricle quantification accuracy and optimization performance. Hence, the proposed method has big potential to be extended to other medical image analysis tasks and has clinical application value.

3.
Sci Adv ; 5(11): eaay0418, 2019 Nov.
Artigo em Inglês | MEDLINE | ID: mdl-31701008

RESUMO

Traditionally, electronics have been designed with static form factors to serve designated purposes. This approach has been an optimal direction for maintaining the overall device performance and reliability for targeted applications. However, electronics capable of changing their shape, flexibility, and stretchability will enable versatile and accommodating systems for more diverse applications. Here, we report design concepts, materials, physics, and manufacturing strategies that enable these reconfigurable electronic systems based on temperature-triggered tuning of mechanical characteristics of device platforms. We applied this technology to create personal electronics with variable stiffness and stretchability, a pressure sensor with tunable bandwidth and sensitivity, and a neural probe that softens upon integration with brain tissue. Together, these types of transformative electronics will substantially broaden the use of electronics for wearable and implantable applications.

4.
Int Immunopharmacol ; : 105969, 2019 Nov 01.
Artigo em Inglês | MEDLINE | ID: mdl-31685436

RESUMO

Macrophages play a critical role in the immune response against pathogen invasion and injury. However, under pathological stress, macrophages could have aberrant roles and contribute to the pathogenesis of inflammatory associated diseases. Exenatide is a glucagon-like peptide 1(GLP-1) agonist, which belongs to the family of synthetic exendin-based incretin mimetic. Exendin related compounds reduce glucose levels in type 2 diabetes patients. The purpose of this study was to examine the anti-inflammatory effects of exendin-4 in LPS-induced activation of macrophages. We show that exendin-4 inhibits LPS-induced expression of inflammatory mediators (iNOS, COX-2, PGE2 and NO) and pro-inflammatory cytokines (TNF-α, IL-1ß, and IL-6) in RAW264.7 macrophages. Exendin-4 pretreatment mitigates LPS induced cellular ROS production. Mechanistically, Exendin-4 suppresses the LPS-induced activation of the JNK and AP-1 pathway. Furthermore, exendin-4 suppresses both nuclear p65 accumulation and transfected NF-κB promoter activity, indicating it inhibits the activation of the NF-κB pathway. Our study demonstrates that the GLP-1 agonist exendin-4 has a potent anti-inflammatory effect independent on its glucose reducing ability, and exendin-4 has the potential implication to treat inflammatory associated diseases.

5.
Chin Med J (Engl) ; 2019 Nov 22.
Artigo em Inglês | MEDLINE | ID: mdl-31764182

RESUMO

BACKGROUND: Artificial intelligence-assisted image recognition technology is currently able to detect the target area of an image and fetch information to make classifications according to target features. This study aimed to use deep neural networks for computed tomography (CT) diagnosis of perigastric metastatic lymph nodes (PGMLNs) to simulate the recognition of lymph nodes by radiologists, and to acquire more accurate identification results. METHODS: A total of 1371 images of suspected lymph node metastasis from enhanced abdominal CT scans were identified and labeled by radiologists and were used with 18,780 original images for faster region-based convolutional neural networks (FR-CNN) deep learning. The identification results of 6000 random CT images from 100 gastric cancer patients by the FR-CNN were compared with results obtained from radiologists in terms of their identification accuracy. Similarly, 1004 CT images with metastatic lymph nodes that had been post-operatively confirmed by pathological examination and 11,340 original images were used in the identification and learning processes described above. The same 6000 gastric cancer CT images were used for the verification, according to which the diagnosis results were analyzed. RESULTS: In the initial group, precision-recall curves were generated based on the precision rates, the recall rates of nodule classes of the training set and the validation set; the mean average precision (mAP) value was 0.5019. To verify the results of the initial learning group, the receiver operating characteristic curves was generated, and the corresponding area under the curve (AUC) value was calculated as 0.8995. After the second phase of precise learning, all the indicators were improved, and the mAP and AUC values were 0.7801 and 0.9541, respectively. CONCLUSION: Through deep learning, FR-CNN achieved high judgment effectiveness and recognition accuracy for CT diagnosis of PGMLNs. TRIAL REGISTRATION: Chinese Clinical Trial Registry, No. ChiCTR1800016787; http://www.chictr.org.cn/showproj.aspx?proj=28515.

6.
Chin Med J (Engl) ; 2019 Nov 22.
Artigo em Inglês | MEDLINE | ID: mdl-31764186

RESUMO

BACKGROUND: Early diagnosis and accurate staging are important to improve the cure rate and prognosis for pancreatic cancer. This study was performed to develop an automatic and accurate imaging processing technique system, allowing this system to read computed tomography (CT) images correctly and make diagnosis of pancreatic cancer faster. METHODS: The establishment of the artificial intelligence (AI) system for pancreatic cancer diagnosis based on sequential contrast-enhanced CT images were composed of two processes: training and verification. During training process, our study used all 4385 CT images from 238 pancreatic cancer patients in the database as the training data set. Additionally, we used VGG16, which was pre-trained in ImageNet and contained 13 convolutional layers and three fully connected layers, to initialize the feature extraction network. In the verification experiment, we used sequential clinical CT images from 238 pancreatic cancer patients as our experimental data and input these data into the faster region-based convolution network (Faster R-CNN) model that had completed training. Totally, 1699 images from 100 pancreatic cancer patients were included for clinical verification. RESULTS: A total of 338 patients with pancreatic cancer were included in the study. The clinical characteristics (sex, age, tumor location, differentiation grade, and tumor-node-metastasis stage) between the two training and verification groups were insignificant. The mean average precision was 0.7664, indicating a good training effect of the Faster R-CNN. Sequential contrast-enhanced CT images of 100 pancreatic cancer patients were used for clinical verification. The area under the receiver operating characteristic curve calculated according to the trapezoidal rule was 0.9632. It took approximately 0.2 s for the Faster R-CNN AI to automatically process one CT image, which is much faster than the time required for diagnosis by an imaging specialist. CONCLUSIONS: Faster R-CNN AI is an effective and objective method with high accuracy for the diagnosis of pancreatic cancer. TRIAL REGISTRATION: ChiCTR1800017542; http://www.chictr.org.cn.

7.
Med Image Anal ; 60: 101593, 2019 Oct 31.
Artigo em Inglês | MEDLINE | ID: mdl-31731092

RESUMO

Multi-indices quantification of optic nerve head (ONH), measuring ONH appearance with multiple types of indices simultaneously from fundus images, is the most clinically significant tasks for accurate ONH assessment and ophthalmic disease diagnosis. However, no attempt has been reported due to its challenges of the large variation of fundus appearance across patients, heavy overlap and extremely weak contrast between optic nerve head areas. In this paper, we propose a multitask collaborative learning framework (MCL-Net) for multi-indices ONH quantification. The proposed MCL-Net, a two-branch neural network, first obtains expressive shared and task-specific representations with the backbone network and its two branches; then models the feature exchanges and aggregations between two branches with a well-designed feature interaction module (FIM) to promote each other collaboratively. After that, it estimates multiple types of ONH indices under a multitask ensemble module (MEM) that is capable of learning aggregation of multiple outputs automatically. Therefore, the proposed MCL-Net is consisted of the feature representation, inter-task feature interaction, dual-branch task-specific prediction, and multitask quantification ensemble, which establish an effective framework which takes full advantages of segmentation and estimation tasks for multi-indices ONH quantification. Rather than the low-level feature sharing and individual prediction, the proposed MCL-Net collaboratively learns an optimal combination of shared and task-specific representation, as well as the aggregated prediction, therefore leads to accurate quantification of ONH with multiple types of indices. Experimental results on the dataset of 650 fundus images show that MCL-Net successfully delivers accurate quantification of all the three types of ONH indices, with average mean absolute error of 0.98 ±â€¯0.20, 0.97 ±â€¯0.16, 1.19 ±â€¯0.18, as well as average correlation coefficient of 0.699, 0.708 and 0.691, for diameters, whole areas and regional areas, respectively. In addition, the experiments demonstrate that quantitative indices obtained by our method provide more effective glaucoma diagnosis with AUC of 0.8698. This endows our proposed MCL-Net a great potential in clinical assessment from focal to global for ophthalmic disease diagnosis.

8.
Artigo em Inglês | MEDLINE | ID: mdl-31765307

RESUMO

The integration of segmentation and direct quantification on the left ventricle (LV) from the paired apical views(i.e., apical 4-chamber and 2-chamber together) echo sequence clinically achieves the comprehensive cardiac assessment: multiview segmentation for anatomical morphology, and multidimensional quantification for contractile function. Direct quantification of LV, i.e., to automatically quantify multiple LV indices directly from the image via task-aware feature representation and regression, avoids accumulative error from the inter-step target. This integration sequentially makes a stereoscopical reflection of cardiac activity jointly from the paired orthogonal cross views sequences, overcoming limited observation with a single plane. We propose a K-shaped Unified Network (K-Net), the first end-to-end framework to simultaneously segment LV from apical 4-chamber and 2-chamber views, and directly quantify LV from major-and minor-axis dimensions (1D), area (2D), and volume (3D), in sequence. It works via four components: 1) the K-Net architecture with the Attention Junction enables heterogeneous tasks learning of segmentation task of pixel-wise classification, and direct quantification task of image-wise regression, by interactively introducing the information from segmentation to jointly promote spatial attention map to guide quantification focusing on LV-related region, and transferring quantification feedback to make global constraint on segmentation; 2) the Bi-ResLSTMs distributed in K-Net layer-by-layer hierarchically extract spatial-temporal information in echo sequence, with bidirectional recurrent and short-cut connection to model spatial-temporal information among all frames; 3) the Information Valve tailing the Bi-ResLSTMs selectively exchanges information among multiple views, by stimulating complementary information and suppressing redundant information to make the efficient cross-flow for each view; 4) the Evolution Loss comprehensively guides sequential data learning, with static constraint for frame values, and dynamic constraint for inter-frame value changes. The experiments show that our K-Net gains high performance with a Dice coefficient up to 91.44% and a mean absolute error of the major-axis dimension down to 2.74mm, which reveal its clinical potential.

9.
Artigo em Inglês | MEDLINE | ID: mdl-31740399

RESUMO

Apoptosis plays important roles in regulation of the immune response and has a direct impact on disease resistance in teleost. Death associated protein kinase (DAPK)-related Serine/Threonine kinase 17A (STK17A) is a positive apoptosis regulator. However, the expression and function of STK17A in fish still remains uninvestigated. In this study, we identified and characterized a STK17A gene (termed PoSTK17A) from Japanese flounder Paralichthys olivaceus. We also investigated the pro-apoptotic role of PoSTK17A in fish. Real-time quantitative PCR analysis revealed that PoSTK17A is widely present in various Japanese flounder tissues, and dominantly expressed in liver. Immune challenge experiments showed that PoSTK17A expression was upregulated by inflammatory challenge, Edwardsiella tarda infection and DNA-damaging agent cisplatin treatment as well. Immunofluorescence microscopy revealed that the recombinant PoSTK17A proteins are mainly located in the nucleus of Japanese flounder FG-9307 cells, and human Hela and MCF7 cells. However, PoSTK17A was translocated from the nucleus to cytoplasm following cisplatin treatment. Overexpression of PoSTK17A significantly increased the apoptosis in human MCF7 cells through both cisplatin-dependent and independent manners. Importantly, PoSTK17A also promotes the ATP-gated P2X7 receptor-mediated apoptosis in Japanese flounder FG-9307 cells. Collectively, we characterized an inducible STK17A gene (PoSTK17A) that may play a conserved pro-apoptotic role in fish.

10.
Genomics ; 2019 Nov 22.
Artigo em Inglês | MEDLINE | ID: mdl-31765823

RESUMO

The small brown planthopper (SBPH), Laodelphax striatellus is one of the major insect pests of rice, but little is known about the molecular-level means by which it locates its hosts. SBPH host-seeking behavior heavily relies on chemosensory receptors (CRs). In this study, we utilized genome analysis of the SBPH to identify 169 CRs, including: 133 odorant receptors (ORs), 13 gustatory receptors (GRs) and 23 ionotropic receptors (IRs). The phylogenetic relationships of OR genes from three rice planthoppers and other insect species revealed that the odorant co-receptor (Orco) clade is the most conserved group. Among the candidate GRs, two sugar receptors and five fructose receptors have been identified but no carbon dioxide receptors investigated. Furthermore, we identified homologs of the three highly conserved IR co-receptors. The obtained results will provide us with precious information needed to better understand the interaction between insect pests and crop plants required for effective crop protection.

11.
World J Surg Oncol ; 17(1): 189, 2019 Nov 11.
Artigo em Inglês | MEDLINE | ID: mdl-31711515

RESUMO

BACKGROUND: The rate of breast-conserving surgery (BCS) is low in China. Many patients choose mastectomy even when informed that there is no difference in the overall survival rate compared with that of BCS plus radiotherapy. This study aimed to investigate the factors that influenced the surgical choice in patients eligible for BCS. METHODS: Female patients with breast carcinoma were enrolled in a single center from March 2016 to January 2017. They made their own decision regarding the surgical approach. Univariate analysis was employed to determine the factors associated with the different breast surgical approaches. Significant factors (defined as P < 0.05) were then incorporated into multivariate logistic regression models to determine the factors that independently influenced patients' decision. RESULTS: Of the 271 patients included, 149 were eligible for BCS; 65 chose BCS and 84 chose mastectomy. On the basis of univariate analysis, patients with younger age, higher income and education, shorter admission to surgery interval, and shorter confirmed diagnosis to surgery interval were more likely to choose BCS than mastectomy (P < 0.05). Meanwhile, patients who resided in rural regions, did not have general medicare insurance, and were diagnosed with breast cancer preoperatively were more inclined to choose mastectomy than BCS (P < 0.05). The multivariate model revealed three independent influencing factors: age at diagnosis (P = 0.009), insurance status (P = 0.035), and confirmed diagnosis to surgery interval (P = 0.037). In addition, patients receiving neoadjuvant chemotherapy (NCT) were more inclined to choose mastectomy. CONCLUSION: Surgical choice of patients eligible for BCS was affected by several factors, and age at diagnosis, confirmed diagnosis to surgery interval, and insurance status were independent factors.

12.
Artigo em Inglês | MEDLINE | ID: mdl-31699706

RESUMO

Breast cancers evolve in a multistage process that can span decades after a carcinogenic exposure. It follows that long-lived precursor breast lesions persist in a subclinical state prior to completing malignant transformation, yet widely-used breast cancer models lack an experimental framework for targeting premalignant disease. Inspired by classic multistage skin carcinogenesis protocols, we combined chemical carcinogenesis with transgenic mouse modeling to resolve mouse mammary carcinogenesis into discrete initiation and progression stages. At the initiation stage, exposure to the carcinogen 7,12-dimethylbenzanthracene (DMBA) generated "initiated mammary epithelial cells" (iMECs) by introducing a stereotyped HrasQ61L driver mutation. Whether DMBA exposure occurred during puberty or adulthood, mice efficiently acquired iMEC clones that eluded detection by conventional histology, yet were long-lived, persisting in a clinically silent state for months in the absence of a cooperating event. At the progression stage, inducible activation of oncogenic Wnt signaling drove rapid and synchronous transformation of latent iMECs into overt mammary carcinomas, while Wnt activation in neighboring normal mammary epithelium yielded only benign hyperplasia over this same time period. Although early parity (completion of a full-term pregnancy) reduces breast cancer risk in some contexts, standard parity-induced protection schemes failed to eliminate iMECs in our multistage model, suggesting Wnt-responsive iMECs are maintained by hormone-independent mechanisms. Variations on our multistage modeling strategy may help to identify and validate cellular and molecular targets for breast cancer chemoprevention.

13.
Artigo em Inglês | MEDLINE | ID: mdl-31715563

RESUMO

Intracoronary imaging is a crucial imaging technology in coronary disease diagnosis as it visualizes the internal tissue morphologies of coronary arteries. Vessel border detection in intracoronary images (VBDI) is desired because it can help the succeeding procedures of computer-aided disease diagnosis. However, existing VDBI methods suffer from the challenge of vessel-environment variability (i.e. high intra-and inter-subject diversity of vessels and their surrounding tissues appeared in images). This challenge leads to the ineffectiveness in the vessel region representation for hand-crafted features, in the receptive field extraction for deeply-represented features, as well as performance suppression derived from clinical data limitation. To solve this challenge, we propose a novel privileged modality distillation (PMD) framework for VBDI. PMD transforms the single-input-single-task (SIST) learning problem in the single-mode VBDI to a multiple-input-multiple-task (MIMT) problem by using the privileged image modality to help the learning model in the target modality. This learns the enriched high-level knowledge with similar semantics and generalizes PMD on diversity-increased low-level image features for improving the model adaptation to diverse vessel environments. Moreover, PMD refines MIMT to SIST by distilling the learned knowledge from multiple to one modality. This eliminates the reliance on privileged modality in the test phase, and thus enables the applicability to each of different intracoronary modalities. A structure-deformable neural network is proposed as an elaborately-designed implementation of PMD. It expands a conventional SIST network structure to the MIMT structure, and then recovers it to the final SIST structure. The PMD is validated on intravascular ultrasound imaging and optical coherence tomography imaging. One modality is the target, and the other one can be considered as the privileged modality owing to their semantic relatedness. The experiments show that our PMD is effective in VBDI (e.g. the Dice index is larger than 0.95), as well as superior to six state-of-the-art VBDI methods.

14.
Viruses ; 11(11)2019 Nov 08.
Artigo em Inglês | MEDLINE | ID: mdl-31717393

RESUMO

The prevalence and variation of the H9N2 avian influenza virus (AIV) pose a threat to public health. A total of eight viruses isolated from farmed poultry in South China during 2017-2018 were selected as representative strains for further systematic study. Phylogenetic analyses indicated that these prevalent viruses belong to the Y280-like lineage and that the internal genes are highly similar to those of recently circulating human H7N9 viruses. The receptor-binding assay showed that most of the H9N2 isolates preferentially bound to the human-like receptor, increasing the risk of them crossing the species barrier and causing human infection. Our in vitro, multi-step growth curve results indicate these viruses can effectively replicate in mammalian cells. Infection in mice showed that three viruses effectively replicated in the lung of mice. Infection in swine revealed that the viruses readily replicated in the upper respiratory tract of pig and effectively induced viral shedding. Our findings suggested that the H9N2 AIVs circulating in poultry recently acquired an enhanced ability to transmit from avian to mammalians, including humans. Based on our findings, we propose that it is essential to strengthen the efforts to surveil and test the pathogenicity of H9N2 AIVs.

15.
Phys Chem Chem Phys ; 21(46): 25802-25808, 2019 Dec 14.
Artigo em Inglês | MEDLINE | ID: mdl-31728461

RESUMO

MXenes are 2D transition metal carbides with high potential for overcoming limitations of conventional two-dimensional electronics. In this context, various MXenes have shown magnetic properties suitable for applications in spintronics, yet the number of MXenes reported so far is far smaller than their parental MAX phases. Therefore, we have studied the structural, electronic and magnetic properties of bimetallic and vacancy-ordered MXenes derived from a new (V2/3Zr1/3)2AlC MAX phase to assess whether MXene exfoliation would return stable magnetic materials. In particular, we have investigated the properties of pristine and surface-functionalized (V2/3Zr1/3)2CX2 bimetallic and (V2/3□1/3)2CX2 (where □ denotes the vacancies) vacancy-ordered MXenes (X = O, F and OH). Our density functional theory (DFT) calculations showed that modifying the MXene stoichiometry and/or MXene surface functionalization changes MXene properties. After testing all possible combinations of metallic motifs and functionalization, we identified (V2/3Zr1/3)2CX2, (V2/3□1/3)2CF2 and (V2/3□1/3)2C(OH)2 as stable structures. Among them, (V2/3Zr1/3)2CO2 MXene is predicted to be an FM intrinsic half-semiconductor with a remarkably high Curie temperature (TC) of 270 K. The (V2/3Zr1/3)2C(OH)2 MXene exhibits a rather low work function (WF) (1.37 eV) and is thus a promising candidate for ultra-low work function electron emitters. Conversely, the (V2/3□1/3)2CF2 MXene has a rather high WF and hence can be used as a hole injector for Schottky-barrier-free contact applications. Overall, our proof-of-concept study shows that theoretical predictions of MXene exfoliation and properties support further experimental research towards developing spintronics devices.

16.
J Recept Signal Transduct Res ; : 1-5, 2019 Nov 27.
Artigo em Inglês | MEDLINE | ID: mdl-31774019

RESUMO

Although ecotropic viral integration site 2 A (EVI2A) plays key roles in several cancers, the expression and function of EVI2A in osteosarcoma (OS) have not been investigated. Hence, we explored the expression of EVI2A and its clinical significance of EVI2A of OS. Firstly, we investigated the expression of EVI2A in OS tissues. The relationship of EVI2A expression and survival time was analyzed using Kaplan-Meier plotter. Then, we used quantitative reverse transcription PCR (qRT-PCR) to confirm the expression level of EVI2A in OS cell lines. Cell proliferation, and wound-healing experiments were used to identify the biological function of EVI2A. Moreover, EVI2A-mediated MEK/ERK signaling pathway was evaluated using western blotting. Data suggested that EVI2A was highly expressed in OS tissues, and high-expression of EVI2A was associated with worse overall survival in OS patients. Moreover, the up-regulation of it was observed in OS cell lines (Saos2, and MG63). Knockdown of EVI2A suppressed cell proliferation and migration of OS. Western blotting revealed that the inactivation of MEK/ERK pathway was found in OS cells after EVI2A knockdown. Our data implicated the crucial role of EVI2A in the progression of OS, demonstrating that expression of EVI2A may offer an attractive novel prognostic signature for OS.

17.
World J Gastroenterol ; 25(41): 6248-6257, 2019 Nov 07.
Artigo em Inglês | MEDLINE | ID: mdl-31749595

RESUMO

BACKGROUND: Platelets have been reported to participate in tumor cell growth, extravasation, epithelial-mesenchymal transition, metastasis, and drug resistance. However, the importance of platelets in pancreatic neuroendocrine tumor (pNET) lacks adequate literature support. The predictive value of tumor-infiltrating platelets (TIPs) in pNET remains unclear. AIM: To investigate the relationship between TIPs and the prognosis of patients with pNET following radical resection. METHODS: In total, 113 patients who had undergone radical surgical resection with a pathologic diagnosis of pNET were enrolled in this study. Immunohistochemical analysis of cluster of differentiation 42b (CD42b) expression in the tumor specimens was performed to determine the presence of TIPs. Univariate and multivariate analyses were used to analyze the prognostic value of TIPs. RESULTS: TIPs were observed in intratumoral areas in 54 patients. Neither basic characteristics nor preoperative platelet-associated indicators showed a significant relationship with the presence of TIPs (all P > 0.05). Patients with positive intratumoral CD42b expression had worse overall survival (P = 0.005) and recurrence-free survival (P < 0.001) than those with negative intratumoral CD42b expression. Multivariate analysis demonstrated that TIPs were independent prognostic factors for overall survival (P = 0.049) and recurrence-free survival (P = 0.003). Nevertheless, platelet count, mean platelet volume, and platelet-to-lymphocyte ratio were not associated with postoperative survival or recurrence in pNET patients (all P > 0.05). CONCLUSION: TIPs are a useful prognostic biomarker for patients with resectable pNET, and their detection represents a promising tool for pNET treatment strategy decisions.

18.
Exp Cell Res ; : 111745, 2019 Nov 22.
Artigo em Inglês | MEDLINE | ID: mdl-31765611

RESUMO

Orthodontic tooth movement (OTM) is initiated by mechanical force and featured as alveolar bone remodeling. Periodontal ligament cells (PDLCs) are one of the major cell components in periodontium and responsible for the signal transduction during OTM. Up to now, the mechanical stress-induced genetic alteration and mechanotransduction mechanisms in PDLCs still remain not fully understood. In this study, we identified a novel compressive force responsive gene-Growth differentiation factor 15 (GDF15), whose expression transcriptionally increased in human periodontal ligament cells (PDLCs) after exposure to the static compressive force in vitro. Functional analyses proved that GDF15 could promote osteoclast differentiation of the murine macrophage cell line RAW264.7 cells. Molecular investigation uncovered that GDF15 could promote the expression of several pro-inflammatory cytokines and RANKL/OPG ratio in PDLCs, while knockdown of GDF15 impaired their upregulation induced by compressive force. Additionally, administration of recombinant GDF15 protein stimulated the M1-like polarization of RAW264.7 cells and THP-1 induced macrophages. Mechanistically, siRNA-mediated suppression of GDF15 significantly disrupted the nuclear translocation of NF-κB and ERK phosphorylation in response to compressive force. Finally, Yes-associated protein (YAP) was demonstrated to be the upstream regulator of GDF15 in human PDLCs, implying a force-induced YAP-GDF15 regulation mechanism. Overall, these data suggested important roles of GDF15 in the functional modulation of both PDLCs and osteoclast progenitors in response to compressive force, providing novel insights into the molecular mechanism of mechanotransduction during OTM process.

19.
Chemphyschem ; 2019 Nov 25.
Artigo em Inglês | MEDLINE | ID: mdl-31769199

RESUMO

Organic semiconductor (OSC) crystals have great potential to be applied in many fields, as they can be flexibly designed according to the demands and show an outstanding device performance. However, OSCs with the capacity of solid state crystallization (SSC) are developing too slowly to meet demands in productions and applications, due to their difficulties in molecular design and synthesis, unclear mechanism and high dependence on experimental conditions. In this work, in order to solve the problems, we synthesized an organic semiconductor capable of SSC at room temperature by adjusting the relationship between conjugated groups and functional groups. The thermodynamic and kinetic properties have been studied to discover the model of film SSC. Moreover, it can be purposefully controlled to prepare the high-quality crystals, and their corresponding organic electronic devices were further fabricated and discussed.

20.
Arch Med Res ; 50(6): 350-361, 2019 Aug.
Artigo em Inglês | MEDLINE | ID: mdl-31677540

RESUMO

BACKGROUND: Previous studies have reported vitamin D receptor (VDR) polymorphisms in multiple sclerosis (MS); however, the results remain contradictory. This study aimed to investigate the association between VDR polymorphisms and the risk of MS. METHODS: PubMed and Embase databases were searched to obtain eligible studies. Data were calculated by odds ratios (OR) with 95% confidence intervals (CI). RESULTS: Twenty seven case-control studies with 4879 MS patients and 5402 controls were included. There was no significant association between ApaI polymorphisms and MS in the overall population. In Asians, no association was found between ApaI polymorphism and MS in the recessive, dominant, Codominant (OR1), Codominant (OR2), Codominant (OR3) models and allele contrast. Similar results were obtained between BsmI polymorphisms and MS. The association between TaqI polymorphism and MS showed significance in the recessive, homozygous, codominant (OR3) models in the overall population and Caucasians. The dominant model showed no association of Taq I polymorphism with MS risk in HLA-DRB1*15-positive and HLA-DRB1*15-negative groups. FokI polymorphism with MS was found in Codominant (OR3) model in the overall population. In Asians, FokI polymorphism showed association with MS in recessive, dominant, Codominant (OR1), Codominant (OR3) models and allele contrast. Subgroup analysis of sex showed no associations between TaqI or FokI polymorphism and MS risk in males or females in all models or allele contrast. CONCLUSIONS: The VDR TaqI polymorphisms showed association with MS risk, especially in Caucasians. In Asians, ApaI and FokI polymorphisms correlated with MS risk, while BsmI polymorphisms showed no association with MS.

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