scholarly journals Self-Similar Functional Circuit Models of Arteries and Deterministic Fractal Operators: Theoretical Revelation for Biomimetic Materials

2021 ◽  
Vol 22 (23) ◽  
pp. 12897
Author(s):  
Gang Peng ◽  
Jianqiao Guo ◽  
Yajun Yin
Keyword(s):  
Blood Flow ◽  
Circuit Model ◽  
The Self ◽  
Regulation Mechanism ◽  
Biomimetic Materials ◽  
Proposed Model ◽  
Theoretical Mechanism ◽  
Self Similar ◽  
Electrical Components

In this paper, the self-similar functional circuit models of arteries are proposed for bioinspired hemodynamic materials design. Based on the mechanical-electrical analogous method, the circuit model can be utilized to mimic the blood flow of arteries. The theoretical mechanism to quantitatively simulate realistic blood flow is developed by establishing a fractal circuit network with an infinite number of electrical components. We have found that the fractal admittance operator obtained from the minimum repeating unit of the fractal circuit can simply and directly determine the blood-flow regulation mechanism. Furthermore, according to the operator algebra, the fractal admittance operator on the aorta can be represented by Gaussian-type convolution kernel function. Similarly, the arteriolar operator can be described by Bessel-type function. Moreover, by the self-similar assembly pattern of the proposed model, biomimetic materials which contain self-similar circuits can be designed to mimic physiological or pathological states of blood flow. Studies show that the self-similar functional circuit model can efficiently describe the blood flow and provide an available and convenient structural theoretical revelation for the preparation of in vitro hemodynamic bionic materials.

Improved Face Recognition With Fractal-Based Texture Analysis

2021 ◽  
Vol 11 (3) ◽  
pp. 41-53
Author(s):  
Rajalaxmi Padhy ◽  
Aishwarya Dash ◽  
Sanjit Kumar Dash ◽  
Jibitesh Mishra
Keyword(s):  
The Self ◽  
Human Vision ◽  
Svm Classifier ◽  
Human Face ◽  
Facial Image ◽  
Processing Stage ◽  
Proposed Model ◽  
The Face ◽  
System Maps ◽  
Self Similar

Fractals are useful to uniquely represent texture in the human face, which serves as an equivalent of human vision. FaceNet, calculating face descriptors of a person, has been observed to perform with setbacks when several factors of occlusion are present. This paper proposes a new methodology that exploits the self-similar patterns in a person's face to highlight and enhance regions of high texture in a facial image. The system maps the original image into a representation in the pre-processing stage of computer vision. This representation when fed as an input to the FaceNet CNN optimizes the face embedding generated. An SVM classifier separates the hard positive examples from the hard negative examples during classification. The model is trained using YouTube Faces DB as primary dataset and for validation; a custom dataset is designed to verify a person's identity despite the presence of secondary factors such as expressions and forgery. The proposed model attained an overall accuracy of 96.73% with the YouTube Faces DB, and a notable reduction in the false positive rates is observed.

Effect of caffeine on theophyliine on cerebral blood flow response to brain activation: In vitro and in vivo studies

2005 ◽  
Vol 25 (1_suppl) ◽  
pp. S198-S198
Author(s):  
Joseph R Meno ◽  
Thien-son K Nguyen ◽  
Elise M Jensen ◽  
G Alexander West ◽  
Leonid Groysman ◽  
...  
Keyword(s):  
Blood Flow ◽  
Cerebral Blood Flow ◽  
Brain Activation ◽  
In Vivo Studies ◽  
Blood Flow Response ◽  
Flow Response

The Mesothelial Cell as a Non-Thrombogenic Surface

1984 ◽  
Vol 52 (02) ◽  
pp. 102-104 ◽  
Author(s):  
L J Nicholson ◽  
J M F Clarke ◽  
R M Pittilo ◽  
S J Machin ◽  
N Woolf
Keyword(s):  
Electron Microscopy ◽  
Scanning Electron Microscopy ◽  
Blood Flow ◽  
Cell Surface ◽  
Mesothelial Cell ◽  
Mesothelial Cells ◽  
Plastic Film ◽  
In Vitro System ◽  
Scanning Electron

SummaryA technique for harvesting mesothelial cells is described. This entails collagenase digestion of omentum after which the cells can be cultured. The technique has been developed using the rat, but has also been successfully applied to human tissue. Cultured rat mesothelial cells obtained in this way have been examined by scanning electron microscopy. Rat mesothelial cells grown on plastic film have been exposed to blood in an in vitro system using a Baumgartner chamber and have been demonstrated to support blood flow. No adhering platelets were observed on the mesothelial cell surface. Fibroblasts similarily exposed to blood as a control were washed off the plastic.

Role of 4-O Galloylchlorogenic Acid in Lung Cancer- An Insilico Approach

2017 ◽  
Vol 9 (5) ◽  
Author(s):  
Jaynthy C. ◽  
N. Premjanu ◽  
Abhinav Srivastava
Keyword(s):  
Lung Cancer ◽  
Cell Proliferation ◽  
In Silico ◽  
Computational Study ◽  
Regulation Mechanism ◽  
Down Regulation ◽  
Fruit Extract ◽  
In Vitro Techniques ◽  
Discovery Studio

Cancer is a major disease with millions of patients diagnosed each year with high mortality around the world. Various studies are still going on to study the further mechanisms and pathways of the cancer cell proliferation. Fucosylation is one of the most important oligosaccharide modifications involved in cancer and inflammation. In cancer development increased core fucosylation by FUT8 play an important role in cell proliferation. Down regulation of FUT8 expression may help cure lung cancer. Therefore the computational study based on the down regulation mechanism of FUT8 was mechanised. Sapota fruit extract, containing 4-Ogalloylchlorogenic acid was used as the inhibitor against FUT-8 as target and docking was performed using in-silico tool, Accelrys Discovery Studio. There were several conformations of the docked result, and conformation 1 showed 80% dock score between the ligand and the target. Further the amino acids of the inhibitor involved in docking were studied using another tool, Ligplot. Thus, in-silico analysis based on drug designing parameters shows that the fruit extract can be studied further using in-vitro techniques to know its pharmacokinetics.

iTSP-PseAAC: Identify Tumor Suppressor Proteins by Using Fully Connected Neural Network and PseAAC

2021 ◽  
Vol 15 ◽  
Author(s):  
Muhammad Awais ◽  
Waqar Hussain ◽  
Nouman Rasool ◽  
Yaser Daanial Khan
Keyword(s):  
Tumor Suppressor ◽  
Cross Validation ◽  
Control Cell ◽  
Normal Function ◽  
In Vivo Studies ◽  
Tumor Suppressor Proteins ◽  
Proposed Model ◽  
Self Consistency

Background: The uncontrolled growth due to accumulation of genetic and epigenetic changes as a result of loss or reduction in the normal function of Tumor Suppressor Genes (TSGs) and Pro-oncogenes is known as cancer. TSGs control cell division and growth by repairing of DNA mistakes during replication and restrict the unwanted proliferation of a cell or activities, those are the part of tumor production. Objectives: This study aims to propose a novel, accurate, user-friendly model to predict tumor suppressor proteins, which would be freely available to experimental molecular biologists to assist them using in vitro and in vivo studies. Methods: The predictor model has used the input feature vector (IFV) calculated from the physicochemical properties of proteins based on FCNN to compute the accuracy, sensitivity, specificity, and MCC. The proposed model was validated against different exhaustive validation techniques i.e. self-consistency and cross-validation. Results: Using self-consistency, the accuracy is 99%, for cross-validation and independent testing has 99.80% and 100% accuracy respectively. The overall accuracy of the proposed model is 99%, sensitivity value 98% and specificity 99% and F1-score was 0.99. Conclusion: It concludes, the proposed model for prediction of the tumor suppressor proteins can predict the tumor suppressor proteins efficiently, but it still has space for improvements in computational ways as the protein sequences may rapidly increase, day by day.

scholarly journals Aberrantly high activation of a FoxM1–STMN1 axis contributes to progression and tumorigenesis in FoxM1-driven cancers

2021 ◽  
Vol 6 (1) ◽  
Author(s):  
Jun Liu ◽  
Jipeng Li ◽  
Ke Wang ◽  
Haiming Liu ◽  
Jianyong Sun ◽  
...  
Keyword(s):  
Cell Proliferation ◽  
Poor Prognosis ◽  
Soft Agar ◽  
Transcriptional Level ◽  
Regulation Mechanism ◽  
Strong Positive Correlation ◽  
Cell Viability Assay ◽  
High Level

AbstractFork-head box protein M1 (FoxM1) is a transcriptional factor which plays critical roles in cancer development and progression. However, the general regulatory mechanism of FoxM1 is still limited. STMN1 is a microtubule-binding protein which can inhibit the assembly of microtubule dimer or promote depolymerization of microtubules. It was reported as a major responsive factor of paclitaxel resistance for clinical chemotherapy of tumor patients. But the function of abnormally high level of STMN1 and its regulation mechanism in cancer cells remain unclear. In this study, we used public database and tissue microarrays to analyze the expression pattern of FoxM1 and STMN1 and found a strong positive correlation between FoxM1 and STMN1 in multiple types of cancer. Lentivirus-mediated FoxM1/STMN1-knockdown cell lines were established to study the function of FoxM1/STMN1 by performing cell viability assay, plate clone formation assay, soft agar assay in vitro and xenograft mouse model in vivo. Our results showed that FoxM1 promotes cell proliferation by upregulating STMN1. Further ChIP assay showed that FoxM1 upregulates STMN1 in a transcriptional level. Prognostic analysis showed that a high level of FoxM1 and STMN1 is related to poor prognosis in solid tumors. Moreover, a high co-expression of FoxM1 and STMN1 has a more significant correlation with poor prognosis. Our findings suggest that a general FoxM1-STMN1 axis contributes to cell proliferation and tumorigenesis in hepatocellular carcinoma, gastric cancer and colorectal cancer. The combination of FoxM1 and STMN1 can be a more precise biomarker for prognostic prediction.

scholarly journals Impairing flow-mediated endothelial remodeling reduces extravasation of tumor cells

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Gautier Follain ◽  
Naël Osmani ◽  
Valentin Gensbittel ◽  
Nandini Asokan ◽  
Annabel Larnicol ◽  
...  
Keyword(s):  
Blood Flow ◽  
Tumor Cells ◽  
Molecular Mechanisms ◽  
Metastatic Progression ◽  
Metastatic Dissemination ◽  
Secondary Tumors ◽  
Flow Profiles ◽  
Endothelial Response ◽  
Life Threatening

AbstractTumor progression and metastatic dissemination are driven by cell-intrinsic and biomechanical cues that favor the growth of life-threatening secondary tumors. We recently identified pro-metastatic vascular regions with blood flow profiles that are permissive for the arrest of circulating tumor cells. We have further established that such flow profiles also control endothelial remodeling, which favors extravasation of arrested CTCs. Yet, how shear forces control endothelial remodeling is unknown. In the present work, we aimed at dissecting the cellular and molecular mechanisms driving blood flow-dependent endothelial remodeling. Transcriptomic analysis of endothelial cells revealed that blood flow enhanced VEGFR signaling, among others. Using a combination of in vitro microfluidics and intravital imaging in zebrafish embryos, we now demonstrate that the early flow-driven endothelial response can be prevented upon specific inhibition of VEGFR tyrosine kinase and subsequent signaling. Inhibitory targeting of VEGFRs reduced endothelial remodeling and subsequent metastatic extravasation. These results confirm the importance of VEGFR-dependent endothelial remodeling as a driving force of CTC extravasation and metastatic dissemination. Furthermore, the present work suggests that therapies targeting endothelial remodeling might be a relevant clinical strategy in order to impede metastatic progression.

scholarly journals Hausdorff measure and Assouad dimension of generic self-conformal IFS on the line

2020 ◽  
pp. 1-31
Author(s):  
Balázs Bárány ◽  
Károly Simon ◽  
István Kolossváry ◽  
Michał Rams
Keyword(s):  
Hausdorff Measure ◽  
Similar Case ◽  
Iterated Function Systems ◽  
The Self ◽  
Dimensional Hausdorff Measure ◽  
Assouad Dimension ◽  
Iterated Function ◽  
Self Similar ◽  
Weak Separation ◽  
Topological Sense

This paper considers self-conformal iterated function systems (IFSs) on the real line whose first level cylinders overlap. In the space of self-conformal IFSs, we show that generically (in topological sense) if the attractor of such a system has Hausdorff dimension less than 1 then it has zero appropriate dimensional Hausdorff measure and its Assouad dimension is equal to 1. Our main contribution is in showing that if the cylinders intersect then the IFS generically does not satisfy the weak separation property and hence, we may apply a recent result of Angelevska, Käenmäki and Troscheit. This phenomenon holds for transversal families (in particular for the translation family) typically, in the self-similar case, in both topological and in measure theoretical sense, and in the more general self-conformal case in the topological sense.

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