132 research outputs found
Calcium regulates the PI3K-Akt pathway in stretched osteoblasts
AbstractMechanical loading plays a vital role in maintaining bone architecture. The process by which osteoblasts convert mechanical signals into biochemical responses leading to bone remodeling is not fully understood. The earliest cellular response detected in mechanically stimulated osteoblasts is an increase in intracellular calcium concentration ([Ca2+]i). In this study, we used the clonal mouse osteoblast cell line MC3T3-E1 to show that uniaxial cyclic stretch induces: (1) an immediate increase in [Ca2+]i, and (2) the phosphorylation of critical osteoblast proteins that are implicated in cell proliferation, gene regulation, and cell survival. Our data suggest that cyclic stretch activates the phosphoinositide 3-kinase (PI3K) pathway including: PI3K, Akt, FKHR, and AFX. Moreover, cyclic stretch also causes the phosphorylation of stress-activated protein kinase/c-Jun N-terminal kinase. Attenuation in the level of phosphorylation of these proteins was observed by stretching cells in Ca2+-free medium, using intra- (BAPTA-AM) and extracellular (BAPTA) calcium chelators, or gadolinium, suggesting that influx of extracellular calcium plays a significant role in the early response of osteoblasts to mechanical stimuli
Medida da concentração plasmática do fator de crescimento do endotélio vascular em pacientes com câncer prostático: relação com estado clinico, gleason score, volume prostático e PSA sérico
OBJETIVO: Analisar os nÃveis circulantes do fator de crescimento do endotélio vascular em pacientes com câncer prostático comparados com uma população de indivÃduos eutróficos. MÉTODOS: Vinte e seis indivÃduos eutróficos e oitenta pacientes com câncer de próstata foram analisados nesse estudo. A coleta sangüÃnea foi realizada da mesma maneira em todos os pacientes e o plasma foi extraÃdo para a determinação dos nÃveis do fator de crescimento do endotélio vascular, utilizando-se o método quantitativo ELISA (enzyme-linked immunosorbent assay). RESULTADOS: Os nÃveis de fator de crescimento do endotélio vascular plasmático encontraram-se significativamente elevados nos pacientes com doença metastática quando comparados com pacientes com doença localizada e com indivÃduos sadios. Pacientes com PSA sérico maior que 20 ng/ml apresentaram nÃveis maiores de fator de crescimento do endotélio vascular plasmático quando comparados com pacientes com PSA menor que 20 ng/ml. Houve uma tendência dos pacientes com escore de Gleason de 8 a 10 apresentarem nÃveis maiores do fator de crescimento do endotélio vascular plasmático em relação a pacientes com escores de Gleason menores que 8. Não houve relação entre fator de crescimento do endotélio vascular plasmático e estado clÃnico, ou entre fator de crescimento do endotélio vascular e volume prostático em pacientes com câncer de próstata localizado. CONCLUSÃO: Os dados indicam que pacientes com câncer de próstata metastático apresentam nÃveis significativamente mais elevados de fator de crescimento do endotélio vascular plasmático quando comparados com pacientes com câncer localizado e com indivÃduos normais.PURPOSE: This study focused on circulating levels of vascular endothelial growth factor in patients with prostate cancer compared to a normal population. METHODS: We analyzed 26 normal individuals and 80 patients with prostate cancer. Blood was drawn from all subjects, and plasma was extracted to determine the concentration of vascular endothelial growth factor using a quantitative immunoassay technique (ELISA-enzyme-linked immunosorbent assay). RESULTS: The median plasma level of vascular endothelial growth factor was significantly elevated in patients with metastatic disease compared to patients with localized disease and with healthy controls. Patients with serum prostate-specific antigen >; 20 ng/mL had significantly higher levels of plasma vascular endothelial growth factor than patients with serum prostate-specific antigen < 20 ng/mL. There was a trend for patients with a Gleason score of 8 to 10 to have higher levels of plasma vascular endothelial growth factor when compared to patients with lower Gleason scores. No relationship was found between plasma vascular endothelial growth factor and clinical staging, or between plasma vascular endothelial growth factor and prostate volume, in patients with localized prostate cancer. CONCLUSION: This study indicates that patients with metastatic prostate cancer have higher plasma vascular endothelial growth factor levels than patients with localized disease or in healthy controls
Machine Learning Made Easy (MLme): A Comprehensive Toolkit for Machine Learning-Driven Data Analysis.
BACKGROUND
Machine learning (ML) has emerged as a vital asset for researchers to analyze and extract valuable information from complex datasets. However, developing an effective and robust ML pipeline can present a real challenge, demanding considerable time and effort, thereby impeding research progress. Existing tools in this landscape require a profound understanding of ML principles and programming skills. Furthermore, users are required to engage in the comprehensive configuration of their ML pipeline to obtain optimal performance.
RESULTS
To address these challenges, we have developed a novel tool called Machine Learning Made Easy (MLme) that streamlines the use of ML in research, specifically focusing on classification problems at present. By integrating four essential functionalities, namely Data Exploration, AutoML, CustomML, and Visualization, MLme fulfills the diverse requirements of researchers while eliminating the need for extensive coding efforts. To demonstrate the applicability of MLme, we conducted rigorous testing on six distinct datasets, each presenting unique characteristics and challenges. Our results consistently showed promising performance across different datasets, reaffirming the versatility and effectiveness of the tool. Additionally, by utilizing MLme's feature selection functionality, we successfully identified significant markers for CD8+ naive (BACH2), CD16+ (CD16), and CD14+ (VCAN) cell populations.
CONCLUSION
MLme serves as a valuable resource for leveraging machine learning (ML) to facilitate insightful data analysis and enhance research outcomes, while alleviating concerns related to complex coding scripts. The source code and a detailed tutorial for MLme are available at https://github.com/FunctionalUrology/MLme
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JunB Mediates Basal- and TGFβ1-Induced Smooth Muscle Cell Contractility
Smooth muscle contraction is a dynamic process driven by acto-myosin interactions that are controlled by multiple regulatory proteins. Our studies have shown that members of the AP-1 transcription factor family control discrete behaviors of smooth muscle cells (SMC) such as growth, migration and fibrosis. However, the role of AP-1 in regulation of smooth muscle contractility is incompletely understood. In this study we show that the AP-1 family member JunB regulates contractility in visceral SMC by altering actin polymerization and myosin light chain phosphorylation. JunB levels are robustly upregulated downstream of transforming growth factor beta-1 (TGFβ1), a known inducer of SMC contractility. RNAi-mediated silencing of JunB in primary human bladder SMC (pBSMC) inhibited cell contractility under both basal and TGFβ1-stimulated conditions, as determined using gel contraction and traction force microscopy assays. JunB knockdown did not alter expression of the contractile proteins α-SMA, calponin or SM22α. However, JunB silencing decreased levels of Rho kinase (ROCK) and myosin light chain (MLC20). Moreover, JunB silencing attenuated phosphorylation of the MLC20 regulatory phosphatase subunit MYPT1 and the actin severing protein cofilin. Consistent with these changes, cells in which JunB was knocked down showed a reduction in the F:G actin ratio in response to TGFβ1. Together these findings demonstrate a novel function for JunB in regulating visceral smooth muscle cell contractility through effects on both myosin and the actin cytoskeleton
Acellular Bi-Layer Silk Fibroin Scaffolds Support Tissue Regeneration in a Rabbit Model of Onlay Urethroplasty
Acellular scaffolds derived from Bombyx mori silk fibroin were investigated for their ability to support functional tissue regeneration in a rabbit model of urethra repair. A bi-layer silk fibroin matrix was fabricated by a solvent-casting/salt leaching process in combination with silk fibroin film casting to generate porous foams buttressed by homogeneous silk fibroin films. Ventral onlay urethroplasty was performed with silk fibroin grafts (Group 1, N = 4) (Width×Length, 1×2 cm2) in adult male rabbits for 3 m of implantation. Parallel control groups consisted of animals receiving small intestinal submucosa (SIS) implants (Group 2, N = 4) or urethrotomy alone (Group 3, N = 3). Animals in all groups exhibited 100% survival prior to scheduled euthanasia and achieved voluntary voiding following 7 d of initial catheterization. Retrograde urethrography of each implant group at 3 m post-op revealed wide urethral calibers and preservation of organ continuity similar to pre-operative and urethrotomy controls with no evidence of contrast extravasation, strictures, fistulas, or stone formation. Histological (hematoxylin and eosin and Masson's trichrome), immunohistochemical, and histomorphometric analyses demonstrated that both silk fibroin and SIS scaffolds promoted similar extents of smooth muscle and epithelial tissue regeneration throughout the original defect sites with prominent contractile protein (α-smooth muscle actin and SM22α) and cytokeratin expression, respectively. De novo innervation and vascularization were also evident in all regenerated tissues indicated by synaptophysin-positive neuronal cells and vessels lined with CD31 expressing endothelial cells. Following 3 m post-op, minimal acute inflammatory reactions were elicited by silk fibroin scaffolds characterized by the presence of eosinophil granulocytes while SIS matrices promoted chronic inflammatory responses indicated by mobilization of mononuclear cell infiltrates. The results of this study demonstrate that bi-layer silk fibroin scaffolds represent promising biomaterials for onlay urethroplasty, capable of promoting similar degrees of tissue regeneration in comparison to conventional SIS scaffolds, but with reduced immunogenicity
SpheroScan: A User-Friendly Deep Learning Tool for Spheroid Image Analysis.
BACKGROUND
In recent years, three-dimensional (3D) spheroid models have become increasingly popular in scientific research as they provide a more physiologically relevant microenvironment that mimics in vivo conditions. The use of 3D spheroid assays has proven to be advantageous as it offers a better understanding of the cellular behavior, drug efficacy, and toxicity as compared to traditional two-dimensional cell culture methods. However, the use of 3D spheroid assays is impeded by the absence of automated and user-friendly tools for spheroid image analysis, which adversely affects the reproducibility and throughput of these assays.
RESULTS
To address these issues, we have developed a fully automated, web-based tool called SpheroScan, which uses the deep learning framework called Mask Regions with Convolutional Neural Networks (R-CNN) for image detection and segmentation. To develop a deep learning model that could be applied to spheroid images from a range of experimental conditions, we trained the model using spheroid images captured using IncuCyte Live-Cell Analysis System and a conventional microscope. Performance evaluation of the trained model using validation and test datasets shows promising results.
CONCLUSION
SpheroScan allows for easy analysis of large numbers of images and provides interactive visualization features for a more in-depth understanding of the data. Our tool represents a significant advancement in the analysis of spheroid images and will facilitate the widespread adoption of 3D spheroid models in scientific research. The source code and a detailed tutorial for SpheroScan are available at https://github.com/FunctionalUrology/SpheroScan
SpheroScan: a user-friendly deep learning tool for spheroid image analysis.
BACKGROUND
In recent years, 3-dimensional (3D) spheroid models have become increasingly popular in scientific research as they provide a more physiologically relevant microenvironment that mimics in vivo conditions. The use of 3D spheroid assays has proven to be advantageous as it offers a better understanding of the cellular behavior, drug efficacy, and toxicity as compared to traditional 2-dimensional cell culture methods. However, the use of 3D spheroid assays is impeded by the absence of automated and user-friendly tools for spheroid image analysis, which adversely affects the reproducibility and throughput of these assays.
RESULTS
To address these issues, we have developed a fully automated, web-based tool called SpheroScan, which uses the deep learning framework called Mask Regions with Convolutional Neural Networks (R-CNN) for image detection and segmentation. To develop a deep learning model that could be applied to spheroid images from a range of experimental conditions, we trained the model using spheroid images captured using IncuCyte Live-Cell Analysis System and a conventional microscope. Performance evaluation of the trained model using validation and test datasets shows promising results.
CONCLUSION
SpheroScan allows for easy analysis of large numbers of images and provides interactive visualization features for a more in-depth understanding of the data. Our tool represents a significant advancement in the analysis of spheroid images and will facilitate the widespread adoption of 3D spheroid models in scientific research. The source code and a detailed tutorial for SpheroScan are available at https://github.com/FunctionalUrology/SpheroScan
Global use of Haemophilus influenzae type b conjugate vaccine.
Haemophilus influenzae type b (Hib) conjugate vaccines have been underutilized globally. We report progress in global use of Hib vaccines included in national immunization schedules. The number of countries using Hib vaccine increased from 89/193 (46%) in 2004 to 158/193 (82%) by the end of 2009. The increase was greatest among low-income countries eligible for financial support from the GAVI Alliance [13/75 (17%) in 2004, 60/72 (83%) by the end of 2009], and can be attributed to various factors. Additional efforts are still needed to increase vaccine adoption in lower middle income countries [20/31 (65%) by the end of 2009]
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