Sharif Digital Repository

Microfluidic cell culture platforms are ideal candidates for modeling the native tumor microenvironment because they can precisely reconstruct in vivo cellular behavior. Moreover, mathematical modeling of tumor growth can pave the way toward description and prediction of growth pattern as well as improving cancer treatment. In this study, a modified mathematical model based on concentration distribution is applied to tumor growth in both conventional static culture and dynamic microfluidic cell culture systems. Apoptosis and necrosis mechanisms are considered as the main inhibitory factors in the model, while tumor growth rate and nutrient consumption rate are modified in both quiescent and... 

Breast cancer is one of the most common fatal diseases in women. Early detection of malignant breast cancer could be a great help in treating this cancer. Many studies have been performed in order to detect the malignant of cancer tumor till now. It has been tried to contribute more in accurate diagnosis of breast cancer by Support Vector Machine, in this paper. LS and SMO methods have been utilized instead of conventional learning method of QP in SVM in this probe. The feasibility of 100 percent in sensitivity for LS-SVM, and 100 percent in specificity for SMO-SVM has been achieved in this assay by the proposed method, which this percentage has not been achieved so far in the previous... 

In order to plan precise treatment or accurate tumor removal surgery, brain tumor segmentation is critical for detecting all parts of tumor and its surrounding tissues. To visualize brain anatomy and detect its abnormalities, we use multi-modal Magnetic Resonance Imaging (MRI) as input. This paper introduces an efficient and automated algorithm based on the 3D bit-plane neighborhood concept for Brain Tumor segmentation using a rule-based learning algorithm. In the proposed approach, in addition to using intensity values in each slice, we consider sets of three consecutive slices to extract information from 3D neighborhood. We construct a Rule base using sequential covering algorithm. Through... 

In order to plan precise treatment or accurate tumor removal surgery, brain tumor segmentation is critical for detecting all parts of tumor and its surrounding tissues. To visualize brain anatomy and detect its abnormalities, we use multi-modal Magnetic Resonance Imaging (MRI) as input. This paper introduces an efficient and automated algorithm based on the 3D bit-plane neighborhood concept for Brain Tumor segmentation using a rule-based learning algorithm. In the proposed approach, in addition to using intensity values in each slice, we consider sets of three consecutive slices to extract information from 3D neighborhood. We construct a Rule base using sequential covering algorithm. Through... 

Local hyperthermia is one of the most common methods to treat cancerous tumors, near the skin surface or natural body orifices. In order to study the problem of temperature control during local hyperthermia, firstly the heat conduction process during this therapy is analytically modeled by a time-delayed fractional-order transfer function, parametrized with respect to the body temperature. Since the body temperature may vary under the influence of patient physiological reaction and heat source, a robustness criterion is proposed to achieve the phase margin invariance despite of the temperature variations. Afterwards, an analytical method is proposed to tune stabilizing FO-PI/PD controllers... 

Being the second cause of mortality across the globe, there is now a persistent effort to establish new cancer medication and therapies. Any accomplishment in treating cancers entails the existence of accurate identification systems empowering the early diagnosis. Recent studies indicate CTCs’ potential in cancer prognosis as well as therapy monitoring. The chief shortcoming with CTCs is that they are exceedingly rare cells in their clinically relevant concentration. Here, we simulated a microfluidic construct devised for immunomagnetic separation of the particles of interest from the background cells. This separation unit is integrated with a mixer subunit. The mixer is envisioned for... 

Interest in the design and manufacture of RNA and DNA aptamers as apta-biosensors for the early diagnosis of blood infections and other inflammatory conditions has increased considerably in recent years. The practical utility of these aptamers depends on the detailed knowledge about the putative interactions with their target proteins. Therefore, understanding the aptamer-protein interactions at the atomic scale can offer significant insights into the optimal apta-biosensor design. In this study, we consider one RNA and one DNA aptamer that were previously used as apta-biosensors for detecting the infection biomarker protein TNF-α, as an example of a novel computational workflow for... 

Cytotoxic T-lymphocyte-associated antigen 4 (CTLA-4) and programmed cell death protein 1 (PD-1), two clinically relevant targets for the immunotherapy of cancer, are negative regulators of T-cell activation and migration. Optimizing the therapeutic response to CTLA-4 and PD-1 blockade calls for a more comprehensive insight into the coordinated function of these immune regulators. Mathematical modeling can be used to elucidate nonlinear tumor–immune interactions and highlight the underlying mechanisms to tackle the problem. Here, we investigated and statistically characterized the dynamics of T-cell migration as a measure of the functional response to these pathways. We used a previously... 

Graphene oxide (GO) sheets functionalized by aminopropylsilyl groups (8.0 wt.%) were labeled by 198,199Au nanoparticle radioisotopes (obtained through reduction of HAuCl4 in sodium citrate solution followed by thermal neutron irradiation) for fast in vivo targeting and SPECT imaging (high purity germanium-spectrometry) of tumors. Using instant thin layer chromatography method, the physicochemical properties of the amino-functionalized GO sheets labeled by 198,199Au NPs (198,199Au@AF-GO) were found to be highly stable enough in organic phases, e.g. a human serum, to be reliably used in bioapplications. In vivo biodistribution of the 198,199Au@AF-GO composite was investigated in rats bearing... 

Reduced graphene oxide nanomesh (rGONM), as one of the recent structures of graphene with a surprisingly strong near-infrared (NIR) absorption, is used for achieving ultraefficient photothermal therapy. First, by using TiO2 nanoparticles, graphene oxide nanoplatelets (GONPs) are transformed into GONMs through photocatalytic degradation. Then rGONMs functionalized by polyethylene glycol (PEG), arginine-glycine-aspartic acid (RGD)-based peptide, and cyanine 7 (Cy7) are utilized for in vivo tumor targeting and fluorescence imaging of human glioblastoma U87MG tumors having ανβ3 integrin receptors, in mouse models. The rGONM-PEG suspension (1 μg mL -1) exhibits about 4.2- and 22.4-fold higher NIR... 

Tumor metastasis is responsible for the vast majority of cancer-associated morbidities and mortalities. Recent studies have disclosed the higher metastatic potential of circulating tumor cell (CTC) clusters than single CTCs. Despite long-term study on metastasis, the characterizations of its most potent cellular drivers, i.e., CTC clusters have only recently been investigated. The analysis of CTC clusters offers new intuitions into the mechanism of tumor metastasis and can lead to the development of cancer diagnosis and prognosis, drug screening, detection of gene mutations, and anti-metastatic therapeutics. In recent years, considerable attention has been dedicated to the development of... 

Identifying tumor cells from a pool of other cells has always been an appealing topic for different purposes. The objective of this study is to discriminate circulating tumor cells (CTCs) from blood cells for diagnostic purposes in a novel microfluidic device using two active methods: magnetophoresis and dielectrophoresis. The most specific feature of this device is the differentiation of CTCs without labeling them in order to achieve a more reliable and less complicated method. This device was analyzed and evaluated using finite element method. Four cell lines are separated in this device containing red blood cells, platelets, white blood cells, and CTCs. Primarily, red blood cells and... 

Tumor microenvironment (TME) is a multi-scale biological environment that can control tumor dynamics with many biomechanical and biochemical factors. Investigating the physiology of TME with a heterogeneous structure and abnormal functions not only can achieve a deeper understanding of tumor behavior but also can help develop more efficient anti-cancer strategies. In this work, we develop a hybrid multi-scale mathematical model of TME to simulate the progression of a three-dimensional tumor and elucidate its response to different chemotherapy approaches. The chemotherapy approaches include multiple low dose (MLD) of anti-cancer drug, maximum tolerated dose (MTD) of anti-cancer drug,...