Search results for: tumor segmentation

Authors: S. T. Kumbhar, M. S. Bhatia, R. C. Khairate

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An effective nanodrug delivery system was developed by using chitosan for increased encapsulation efficiency and retarded release of curcumin. Potential ionotropic gelation method was used for the development of chitosan nanoparticles with TPP as cross-linker. The characterization was done for analysis of size, structure, surface morphology, and thermal behavior of synthesized chitosan nanoparticles. The encapsulation efficiency was more than 80%, with improved drug loading capacity. The in-vitro drug release study showed that curcumin release rate was decreased significantly. These chitosan nanoparticles could be a suitable platform for co-delivery of curcumin and anticancer agent for enhanced cytotoxic effect on tumor cells.

Keywords: Curcumin, chitosan, nanoparticles, anticancer activity

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Authors: Rajeswari Raguraman, Sowmya Parameswaran, Krishnakumar Subramanian, Jagat Kanwar, Rupinder Kanwar

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Background: Tumor microenvironment has been implicated in several cancers to regulate cell growth, invasion and metastasis culminating in outcome of therapy. Tumor stroma consists of multiple cell types that are in constant cross-talk with the tumor cells to favour a pro-tumorigenic environment. Not much is known about the existence of tumor microenvironment in the pediatric intraocular malignancy, Retinoblastoma (RB). In the present study, we aim to understand the multiple stromal cellular subtypes and tumor stromal interactions expressed in RB tumors. Materials and Methods: Immunohistochemistry for stromal cell markers CD31, CD68, alpha-smooth muscle (α-SMA), vimentin and glial fibrillary acidic protein (GFAP) was performed on formalin fixed paraffin embedded tissues sections of RB (n=12). The differential expression of stromal target molecules; fibroblast activation protein (FAP), tenascin-C (TNC), osteopontin (SPP1), bone marrow stromal antigen 2 (BST2), stromal derived factor 2 and 4 (SDF2 and SDF4) in primary RB tumors (n=20) and normal retina (n=5) was studied by quantitative reverse transcriptase polymerase chain reaction (qRT-PCR) and Western blotting. The differential expression was correlated with the histopathological features of RB. The interaction between RB cell lines (Weri-Rb-1, NCC-RbC-51) and Bone marrow stromal cells (BMSC) was also studied using direct co-culture and indirect co-culture methods. The functional effect of the co-culture methods on the RB cells was evaluated by invasion and proliferation assays. Global gene expression was studied by using Affymetrix 3’ IVT microarray. Pathway prediction was performed using KEGG and the key molecules were validated using qRT-PCR. Results: The immunohistochemistry revealed the presence of several stromal cell types such as endothelial cells (CD31+;Vim+/-); macrophages (CD68+;Vim+/-); Fibroblasts (Vim+; CD31-;CD68- );myofibroblasts (α-SMA+/ Vim+) and invading retinal astrocytes/ differentiated retinal glia (GFAP+; Vim+). A characteristic distribution of these stromal cell types was observed in the tumor microenvironment, with endothelial cells predominantly seen in blood vessels and macrophages near actively proliferating tumor or necrotic areas. Retinal astrocytes and glia were predominant near the optic nerve regions in invasive tumors with sparse distribution in tumor foci. Fibroblasts were widely distributed with rare evidence of myofibroblasts in the tumor. Both gene and protein expression revealed statistically significant (P<0.05) up-regulation of FAP, TNC and BST2 in primary RB tumors compared to the normal retina. Co-culture of BMSC with RB cells promoted invasion and proliferation of RB cells in direct and indirect contact methods respectively. Direct co-culture of RB cell lines with BMSC resulted in gene expression changes in ECM-receptor interaction, focal adhesion, IL-8 and TGF-β signaling pathways associated with cancer. In contrast, various metabolic pathways such a glucose, fructose and amino acid metabolism were significantly altered under the indirect co-culture condition. Conclusion: The study suggests that the close interaction between RB cells and the stroma might be involved in RB tumor invasion and progression which is likely to be mediated by ECM-receptor interactions and secretory factors. Targeting the tumor stroma would be an attractive option for redesigning treatment strategies for RB.

Keywords: gene expression profiles, retinoblastoma, stromal cells, tumor microenvironment

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Authors: Zahra Shokrolahi, Mohammad Reza Atashzar

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The goals of treating patients with breast cancer are to cure the disease, prolong survival, and improve quality of life. Immune cells in the tumor microenvironment have an important role in regulating tumor progression. The term of cellular immunotherapy refers to the administration of living cells to a patient; this type of immunotherapy can be active, such as a dendritic cell (DC) vaccine, in that the cells can stimulate an anti-tumour response in the patient, or the therapy can be passive, whereby the cells have intrinsic anti-tumour activity; this is known as adoptive cell transfer (ACT) and includes the use of autologous or allogeneic lymphocytes that may, or may not, be modified. The most important breast cancer cellular immunotherapies involving the use of T cells and natural killer (NK) cells in adoptive cell transfer, as well as dendritic cells vaccines. T cell-based therapies including tumour-infiltrating lymphocytes (TILs), engineered TCR-T cells, chimeric antigen receptor (CAR T cell), Gamma-delta (γδ) T cells, natural killer T (NKT) cells. NK cell-based therapies including lymphokine-activated killers (LAK), cytokine-induced killer (CIK) cells, CAR-NK cells. Adoptive cell therapy has some advantages and disadvantages some. TILs cell strictly directed against tumor-specific antigens but are inactive against tumor changes due to immunoediting. CIK cell have MHC-independent cytotoxic effect and also need concurrent high dose IL-2 administration. CAR T cell are MHC-independent; overcome tumor MHC molecule downregulation; potent in recognizing any cell surface antigen (protein, carbohydrate or glycolipid); applicable to a broad range of patients and T cell populations; production of large numbers of tumor-specific cells in a moderately short period of time. Meanwhile CAR T cells capable of targeting only cell surface antigens; lethal toxicity due to cytokine storm reported. Here we present the most popular cancer cellular immunotherapy approaches and discuss their clinical relevance referring to data acquired from clinical trials .To date, clinical experience and efficacy suggest that combining more than one immunotherapy interventions, in conjunction with other treatment options like chemotherapy, radiotherapy and targeted or epigenetic therapy, should guide the way to cancer cure.

Keywords: breast cancer , cell therapy , CAR T cell , CIK cells

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Authors: H. J. T. Kevin Mozes, Dyah Purnamasari

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Background: Lung cancer accounted for the fourth most common cancer in Indonesia. 85% of all lung cancer cases are the Non-Small Cell Lung Cancer (NSCLC). The indistinct signs and symptoms of NSCLC sometimes lead to misdiagnosis. The gold standard assessment for the diagnosis of NSCLC is the histopathological biopsy, which is invasive. Cyfra 21-1 is a tumor marker, which can be found in the intermediate protein structure in the epitel. The accuracy of Cyfra 21-1 in diagnosing NSCLC is not yet known, so this report is made to seek the answer for the question above. Methods: Literature searching is done using online databases. Proquest and Pubmed are online databases being used in this report. Then, literature selection is done by excluding and including based on inclusion criterias and exclusion criterias. The selected literature is then being appraised using the criteria of validity, importance, and validity. Results: From six journals appraised, five of them are valid. Sensitivity value acquired from all five literature is ranging from 50-84.5 %, meanwhile the specificity is 87.8 %-94.4 %. Likelihood the ratio of all appraised literature is ranging from 5.09 -10.54, which categorized to Intermediate High. Conclusion: Serum Cyfra 21-1 is a sensitive and very specific tumor marker for diagnosis of non-small cell lung cancer (NSCLC).

Keywords: cyfra 21-1, diagnosis, nonsmall cell lung cancer, NSCLC, tumor marker

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Authors: Ruth Goldschmidt, Vyacheslav Kalchenko, Lilah Agemy, Rachel Elmoalem, Avigdor Scherz

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Vascular Targeted Photodynamic therapy (VTP) is a new modality for selective cancer treatment that leads to the complete tumor ablation. A photosensitizer, a bacteriochlorophyll derivative in our case, is first administered to the patient and followed by the illumination of the tumor area, by a near-IR laser for its photoactivation. The photoactivated drug releases reactive oxygen species (ROS) in the circulation, which reacts with blood cells and the endothelium leading to the occlusion of the blood vasculature. If the blood vessels are only partially closed, the tumor may recover, and cancer cells could survive. On the other hand, excessive treatment may lead to toxicity of healthy tissues nearby. Simultaneous VTP monitoring and image processing independent of the photoexcitation laser has not yet been reported, to our knowledge. Here we present a method for blood flow monitoring, using a real-time laser speckle imaging (RTLSI) in the tumor during VTP. We have synthesized over the years a library of bacteriochlorophyll derivatives, among them WST11 and STL-6014. Both are water soluble derivatives that are retained in the blood vasculature through their partial binding to HSA. WST11 has been approved in Mexico for VTP treatment of prostate cancer at a certain drug dose, and time/intensity of illumination. Application to other bacteriochlorophyll derivatives or other cancers may require different treatment parameters (such as light/drug administration). VTP parameters for STL-6014 are still under study. This new derivative mainly differs from WST11 by its lack of the central Palladium, and its conjugation to an Arg-Gly-Asp (RGD) sequence. RGD is a tumor-specific ligand that is used for targeting the necrotic tumor domains through its affinity to αVβ3 integrin receptors. This enables the study of cell-targeted VTP. We developed a special RTLSI module, based on Labview software environment for data processing. The new module enables to acquire raw laser speckle images and calculate the values of the laser temporal statistics of time-integrated speckles in real time, without additional off-line processing. Using RTLSI, we could monitor the tumor’s blood flow following VTP in a CT26 colon carcinoma ear model. VTP with WST11 induced an immediate slow down of the blood flow within the tumor and a complete final flow arrest, after some sporadic reperfusions. If the irradiation continued further, the blood flow stopped also in the blood vessels of the surrounding healthy tissue. This emphasizes the significance of light dose control. Using our RTLSI system, we could prevent any additional healthy tissue damage by controlling the illumination time and restrict blood flow arrest within the tumor only. In addition, we found that VTP with STL-6014 was the most effective when the photoactivation was conducted 4h post-injection, in terms of tumor ablation success in-vivo and blood vessel flow arrest. In conclusion, RTSLI application should allow to optimize VTP efficacy vs. toxicity in both the preclinical and clinical arenas.

Keywords: blood vessel occlusion, cancer treatment, photodynamic therapy, real time imaging

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Authors: Beom-Seok Ko, Yoo-Seok Kim, Woo-Sung Lim, Ku-Sang Kim, Hyun-Ah Kim, Jin-Sun Lee, An-Bok Lee, Jin-Gu Bong, Tae-Hyun Kim, Sei-Hyun Ahn

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Background: Breast conserving surgery (BCS) followed by radiation therapy is today standard therapy for early breast cancer. It is safe therapeutic procedure in early breast cancers, because it provides the same level of overall survival as mastectomy. There are a number of different types of incisions used to BCS. Avoiding scars on the breast is women’s desire. Numerous minimal approaches have evolved due to this concern. Periareolar incision is often used when the small tumor relatively close to the nipple. But periareolar incision has a disadvantages include limited exposure of the surgical field. In plastic surgery, various methods such as zigzag incisions have been recommended to achieve satisfactory esthetic results. Periareolar zigzag incision has the advantage of not only good surgical field but also contributed to better surgical scars. The purpose of this study was to evaluate the oncological safety of procedures by studying the status of the surgical margins of the excised tumor specimen and reduces the need for further surgery. Methods: Between January 2016 and September 2016, 148 women with breast cancer underwent BCS or mastectomy by the same surgeon in ASAN medical center. Patients with exclusion criteria were excluded from this study if they had a bilateral breast cancer or underwent resection of the other tumors or taken axillary dissection or performed other incision methods. Periareolar zigzag incision was performed and excision margins of the specimen were identified frozen sections and paraffin-embedded or permanent sections in all patients in this study. We retrospectively analyzed tumor characteristics, the operative time, size of specimen, the distance from the tumor to nipple. Results: A total of 148 patients were reviewed, 72 included in the final analysis, 76 excluded. The mean age of the patients was 52.6 (range 25-19 years), median tumor size was 1.6 cm (range, 0.2-8.8), median tumor distance from the nipple was 4.0 cm (range, 1.0-9.0), median excised specimen sized was 5.1 cm (range, 2.8-15.0), median operation time was 70.0 minute (range, 39-138). All patients were discharged with no sign of infection or skin necrosis. Free resection margin was confirmed by frozen biopsy and permanent biopsy in all samples. There were no patients underwent reoperation. Conclusions: We suggest that periareolar zigzag incision can provide a good surgical field to remove a relatively large tumor and may provide cosmetically good outcomes.

Keywords: periareolar zigzag incision, breast conserving surgery, breast cancer, resection margin

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Authors: Deniz Guven, Wil Ward, Jinming Duan, Li Bai

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Over the past two decades or so, Optical Coherence Tomography (OCT) has been used to diagnose retina and optic nerve diseases. The retinal nerve fibre layer, for example, is a powerful diagnostic marker for detecting and staging glaucoma. With the advances in optical imaging hardware, the adoption of OCT is now commonplace in clinics. More and more OCT images are being generated, and for these OCT images to have clinical applicability, accurate automated OCT image segmentation software is needed. Oct image segmentation is still an active research area, as OCT images are inherently noisy, with the multiplicative speckling noise. Simple edge detection algorithms are unsuitable for detecting retinal layer boundaries in OCT images. Intensity fluctuation, motion artefact, and the presence of blood vessels also decrease further OCT image quality. In this paper, we introduce a new method for segmenting three-dimensional (3D) OCT images. This involves the use of a Kalman filter, which is commonly used in computer vision for object tracking. The Kalman filter is applied to the 3D OCT image volume to track the retinal layer boundaries through the slices within the volume and thus segmenting the 3D image. Specifically, after some pre-processing of the OCT images, points on the retinal layer boundaries in the first image are identified, and curve fitting is applied to them such that the layer boundaries can be represented by the coefficients of the curve equations. These coefficients then form the state space for the Kalman Filter. The filter then produces an optimal estimate of the current state of the system by updating its previous state using the measurements available in the form of a feedback control loop. The results show that the algorithm can be used to segment the retinal layers in OCT images. One of the limitations of the current algorithm is that the curve representation of the retinal layer boundary does not work well when the layer boundary is split into two, e.g., at the optic nerve, the layer boundary split into two. This maybe resolved by using a different approach to representing the boundaries, such as b-splines or level sets. The use of a Kalman filter shows promise to developing accurate and effective 3D OCT segmentation methods.

Keywords: optical coherence tomography, image segmentation, Kalman filter, object tracking

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Authors: Hyunjung Lim, Jeonghun Nam, Hyuk Choi

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High-throughput separation is an essential technique for cancer research and diagnosis. Here, we propose a viscoelastic microfluidic device for sheathless, high-throughput isolation of circulating tumor cells (CTCs) from white blood cells. Here, we demonstrate a viscoelastic method for separation and concentration of CTCs using closed-loop microfluidics. Our device is a rectangular straight channel with a low aspect ratio. Also, to achieve high-efficiency, high-throughput processing, we used a polymer solution with low viscosity. At the inlet, CTCs and white blood cells (WBCs) were randomly injected into the microchannel. Due to the viscoelasticity-induced lateral migration to the equilibrium positions, large CTCs could be collected from the side outlet while small WBCs were removed at the center outlet. By recirculating the collected CTCs from the side outlet back to the sample reservoir, continuous separation and concentration of CTCs could be achieved with high separation efficiency (~ 99%). We believe that our device has the potential to be applied in resource-limited clinical settings.

Keywords: circulating tumor cell, closed-loop microfluidics, concentration, separation, viscoelastic fluid

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Authors: Diea Gamal Abo El-Hassan, Salwa Ahmed Aly, Abdelrahman Mahmoud Abdelgwad

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The major conjugated linoleic acid (CLA) isomers have anticancer effect, especially breast cancer cells, inhibits cell growth and induces cell death. Also, CLA has several health benefits in vivo, including antiatherogenesis, antiobesity, and modulation of immune function. The present study aimed to assess the safety and anticancer effects of milk fat CLA against in vivo Ehrlich ascites carcinoma (EAC) in female Swiss albino mice. This was based on acute toxicity study, detection of the tumor growth, life span of EAC bearing hosts, and simultaneous alterations in the hematological, biochemical, and histopathological profiles. Materials and Methods: One hundred and fifty adult female mice were equally divided into five groups. Groups (1-2) were normal controls, and Groups (3-5) were tumor transplanted mice (TTM) inoculated intraperitoneally with EAC cells (2×106 /0.2 mL). Group (3) was (TTM positive control). Group (4) TTM fed orally on balanced diet supplemented with milk fat CLA (40 mg CLA/kg body weight). Group (5) TTM fed orally on balanced diet supplemented with the same level of CLA 28 days before tumor cells inoculation. Blood samples and specimens from liver and kidney were collected from each group. The effect of milk fat CLA on the growth of tumor, life span of TTM, and simultaneous alterations in the hematological, biochemical, and histopathological profiles were examined. Results: For CLA treated TTM, significant decrease in tumor weight, ascetic volume, viable Ehrlich cells accompanied with increase in life span were observed. Hematological and biochemical profiles reverted to more or less normal levels and histopathology showed minimal effects. Conclusion: The present study proved the safety and anticancer efficiency of milk fat CLA and provides a scientific basis for its medicinal use as anticancer attributable to the additive or synergistic effects of its isomers.

Keywords: anticancer activity, conjugated linoleic acid, Ehrlich ascites carcinoma, % increase in life span, mean survival time, tumor transplanted mice.

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Authors: Konstantinos C. Kartsakalis, Angeliki Skoura, Vasileios Megalooikonomou

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The fuzzy composition of objects depicted in images acquired through MR imaging or the use of bio-scanners has often been a point of controversy for field experts attempting to effectively delineate between the visualized objects. Modern approaches in medical image segmentation tend to consider fuzziness as a characteristic and inherent feature of the depicted object, instead of an undesirable trait. In this paper, a novel technique for efficient image retrieval in the context of images in which segmented objects are either crisp or fuzzily bounded is presented. Moreover, the proposed method is applied in the case of multiple, even conflicting, segmentations from field experts. Experimental results demonstrate the efficiency of the suggested method in retrieving similar objects from the aforementioned categories while taking into account the fuzzy nature of the depicted data.

Keywords: fuzzy object, fuzzy image segmentation, motion descriptors, MRI imaging, object-based image retrieval

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Authors: Aferdita Stroka Koka, Laver Stroka, Juna Musa, Samanda Celaj

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Non-melanoma skin cancers (NMSCs) are the most common human malignancies. About 5.4 million basal and squamous cell skin cancers are diagnosed each year in the US and new cases continue to grow. About eight out of ten of these are basal cell cancers. Squamous cell cancers occur less often. NMSC usually are treatable, but treatment is expensive and can leave scars. In 2019, 167 patients of both sexes suffering from NMSC were treated by traditional medicine. Patients who have been diagnosed with Basal Cell Carcinoma were 122 cases, Squamous Cell Carcinoma 32 cases and both of them 13 cases. Of these,122 cases were ulcerated lesions and 45 unulcerated lesions. All patients were treated with the herbal solution called NILS, which contains extracts of some Albanian plants such as Allium sativum, Jugulans regia and Laurus nobilis. The treatment is done locally, on the surface of the tumor, applying the solution until the tumor mass is destroyed and, after that, giving the necessary time to the wound to make the regeneration that coincides with the complete healing of the wound. We have prepared a collection of photos for each case. Since the first sessions, a shrinkage and reduction of the tumor mass were evident, up to the total disappearance of the lesion at the end of treatment. The normal period of treatment lasted 1 to 2 weeks, depending on the size of the tumor, then take care of it until the closure of the wound, taking the whole process from 1 to 3 months. In 7 patients, the lesion failed to be dominated by treatment and they underwent standard treatment with radiotherapy or surgery, while in 10 patients, the lesion recurred and was treated again. The aim of this survey was to put in evidence the good results obtained by treatment of NMSC with Albanian traditional medicine methods.

Keywords: local treatment, nils, NMSC, traditional medicine

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Authors: N. H. Harun, A. S. Abdul Nasir, M. Y. Mashor, R. Hassan

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Leukaemia is a blood cancer disease that contributes to the increment of mortality rate in Malaysia each year. There are two main categories for leukaemia, which are acute and chronic leukaemia. The production and development of acute leukaemia cells occurs rapidly and uncontrollable. Therefore, if the identification of acute leukaemia cells could be done fast and effectively, proper treatment and medicine could be delivered. Due to the requirement of prompt and accurate diagnosis of leukaemia, the current study has proposed unsupervised pixel segmentation based on clustering algorithm in order to obtain a fully segmented abnormal white blood cell (blast) in acute leukaemia image. In order to obtain the segmented blast, the current study proposed three clustering algorithms which are k-means, fuzzy c-means and moving k-means algorithms have been applied on the saturation component image. Then, median filter and seeded region growing area extraction algorithms have been applied, to smooth the region of segmented blast and to remove the large unwanted regions from the image, respectively. Comparisons among the three clustering algorithms are made in order to measure the performance of each clustering algorithm on segmenting the blast area. Based on the good sensitivity value that has been obtained, the results indicate that moving k-means clustering algorithm has successfully produced the fully segmented blast region in acute leukaemia image. Hence, indicating that the resultant images could be helpful to haematologists for further analysis of acute leukaemia.

Keywords: acute leukaemia images, clustering algorithms, image segmentation, moving k-means

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Authors: Chang Liang, Weizhi Gong, Yan Zhang

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Purpose: Hepatocellular carcinoma (HCC) is a malignant tumor with a high mortality rate and poor prognosis worldwide. Murine double minute 2 (MDM2) regulates the tumor suppressor p53, increasing cancer risk and accelerating tumor progression. Speckle-type POX virus and zinc finger protein (SPOP), a key of subunit of Cullin-Ring E3 ligase, inhibits tumor genesis and progression by the ubiquitination of its downstream substrates. This study aimed to clarify whether SPOP and MDM2 are mutually regulated in HCC and the correlation between SPOP and MDM2 and the prognosis of HCC patients. Methods: First, the expression of SPOP and MDM2 in HCC tissues were detected by TCGA database. Then, 53 paired samples of HCC tumor and adjacent tissues were collected to evaluate the expression of SPOP and MDM2 using immunohistochemistry. Chi-square test or Fisher’s exact test were used to analyze the relationship between clinicopathological features and the expression levels of SPOP and MDM2. In addition, Kaplan‒Meier curve analysis and log-rank test were used to investigate the effects of SPOP and MDM2 on the survival of HCC patients. Last, the Multivariate Cox proportional risk regression model analyzed whether the different expression levels of SPOP and MDM2 were independent risk factors for the prognosis of HCC patients. Results: Bioinformatics analysis revealed the low expression of SPOP and high expression of MDM2 were related to worse prognosis of HCC patients. The relationship between the expression of SPOP and MDM2 and tumor stem-like features showed an opposite trend. The immunohistochemistry showed the expression of SPOP protein was significantly downregulated while MDM2 protein significantly upregulated in HCC tissue compared to that in para-cancerous tissue. Tumors with low SPOP expression were related to worse T stage and Barcelona Clinic Liver Cancer (BCLC) stage, but tumors with high MDM2 expression were related to worse T stage, M stage, and BCLC stage. Kaplan–Meier curves showed HCC patients with high SPOP expression and low MDM2 expression had better survival than those with low SPOP expression and high MDM2 expression (P < 0.05). A multivariate Cox proportional risk regression model confirmed that a high MDM2 expression level was an independent risk factor for poor prognosis in HCC patients (P <0.05). Conclusion: The expression of SPOP protein was significantly downregulated, while the expression of MDM2 significantly upregulated in HCC. The low expression of SPOP and high expression. of MDM2 were associated with malignant progression and poor prognosis of HCC patients, indicating a potential therapeutic target for HCC patients.

Keywords: hepatocellular carcinoma, murine double minute 2, speckle-type POX virus and zinc finger protein, ubiquitination

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Authors: Lian Zeng

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Double-Spear 1-H2-1 (DS1-H2-1) is an oncolytic virus and an innovative biological drug candidate. The chemical composition of the drug product is a live attenuated West Nile virus (WNV) containing the human T cell costimulator (CD86) gene. After intratumoral injection, the virus can rapidly self-replicate in the injected site and lyse/kill the tumor by repeated infection among tumor cells. We also established xenograft tumor models in mice to evaluate the drug candidate's efficacy on those tumors. The results from preclinical studies on transplanted tumors in immunodeficient mice showed that DS1-H2-1 had significant oncolytic effects on human-origin cancers: it completely (100%) shrieked human glioma; limited human neuroblastoma growth reached as high as 95% growth inhibition rate (%TGITW). The safety data of preclinical animal experiments confirmed that DS1-H2-1 is safe as a biological drug for clinical use. In the preclinical drug efficacy experiment, virus-drug administration with different doses did not show abnormal signs and disease symptoms in more than 300 tested mice, and no side effects or death occurred through various administration routes. Intravenous administration did not cause acute infectious disease or other side effects. However, the replication capacity of the virus in tumor tissue via intravenous administration is only 1% of that of direct intratumoral administration. The direct intratumoral administration of DS1-H2-1 had a higher rate of viral replication. Therefore, choosing direct intratumoral injection can ensure both efficacy and safety.

Keywords: oncolytic virus, WNV-CD86, immunotherapy drugs, glioma, neuroblastoma

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Authors: Amil Suleimanov, Aigul Saduakassova, Denis Vinnikov

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Objective: To assess functional visceral fat (VAT) activity evaluated by ¹⁸F-fluorodeoxyglucose (¹⁸F-FDG) positron emission tomography/computed tomography (PET/CT) as a predictor of metastases in colorectal cancer (CRC). Materials and methods: We assessed 60 patients with histologically confirmed CRC who underwent 18F-FDG PET/CT after a surgical treatment and courses of chemotherapy. Age, histology, stage, and tumor grade were recorded. Functional VAT activity was measured by maximum standardized uptake value (SUVmax) using ¹⁸F-FDG PET/CT and tested as a predictor of later metastases in eight abdominal locations (RE – Epigastric Region, RLH – Left Hypochondriac Region, RRL – Right Lumbar Region, RU – Umbilical Region, RLL – Left Lumbar Region, RRI – Right Inguinal Region, RP – Hypogastric (Pubic) Region, RLI – Left Inguinal Region) and pelvic cavity (P) in the adjusted regression models. We also report the best areas under the curve (AUC) for SUVmax with the corresponding sensitivity (Se) and specificity (Sp). Results: In both adjusted for age regression models and ROC analysis, 18F-FDG accumulation in RLH (cutoff SUVmax 0.74; Se 75%; Sp 61%; AUC 0.668; p = 0.049), RU (cutoff SUVmax 0.78; Se 69%; Sp 61%; AUC 0.679; p = 0.035), RRL (cutoff SUVmax 1.05; Se 69%; Sp 77%; AUC 0.682; p = 0.032) and RRI (cutoff SUVmax 0.85; Se 63%; Sp 61%; AUC 0.672; p = 0.043) could predict later metastases in CRC patients, as opposed to age, sex, primary tumor location, tumor grade and histology. Conclusions: VAT SUVmax is significantly associated with later metastases in CRC patients and can be used as their predictor.

Keywords: ¹⁸F-FDG, PET/CT, colorectal cancer, predictive value

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Authors: Malika Ourabia

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A new and efficient method is presented for the analysis of arbitrarily shaped discontinuities. The discontinuities is characterized using a hybrid spectral/numerical technique. This structure presents an arbitrary number of ports, each one with different orientation and dimensions. This article presents a hybrid method based on multimode contour integral and mode matching techniques. The process is based on segmentation and dividing the structure into key building blocks. We use the multimode contour integral method to analyze the blocks including irregular shape discontinuities. Finally, the multimode scattering matrix of the whole structure can be found by cascading the blocks. Therefore, the new method is suitable for analysis of a wide range of waveguide problems. Therefore, the present approach can be applied easily to the analysis of any multiport junctions and cascade blocks. The accuracy of the method is validated comparing with results for several complex problems found in the literature. CPU times are also included to show the efficiency of the new method proposed.

Keywords: segmentation, s parameters, simulation, optimization

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Authors: Sushila Jaiswal, Awadhesh Kumar Jaiswal

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Background: Primary melanocytic tumors of the central nervous system (CNS) are uncommon lesions and arise from the melanocytes located within the leptomeninges. Aim and objective: The aim of the study was to evaluate the clinical details, histomorphology of the primary melanocytic tumor of CNS. Method: The study was performed by the retrospective review of the case records of the primary melanocytic tumors of CNS diagnosed in our department. The formalin-fixed, paraffin embedded tissue blocks and tissue sections were retrieved and reviewed. Results: Seven cases (6 males, 1 female; age range- 16-40 years; mean age- 27 years) of primary melanocytic tumors of CNS were retrieved over last seven years. The tumor was intracranial (n=5; frontal – 1 case, parietal – 1 case, cerebello-pontine angle- 1 case, occipital -1 case, foramen magnum-1 case) and intra spinal (n=2; cervical – 2 cases). All patients presented with the neurological deficits related to the location of the tumor. Four cases were malignant melanoma; two were melanocytoma of intermediate grade and remaining one was melanocytoma. On histopathology, melanocytoma and melanoma both displayed sheets of well-differentiated melanocytes having round to oval nuclei with finely dispersed chromatin, occasional single eosinophilic nucleoli and a moderate amount of cytoplasm with abundant granular melanin pigment. The absence of mitosis and macronucleoli was noticed in melanocytoma while melanoma showed frequent mitosis and macronucleoli. On immunohistochemistry, both showed diffuse strong HMB45 and S-100 immunopositivity. Conclusion: Primary melanocytic tumors of CNS are rare and predominantly seen in males. It is important to differentiate melanoma from melanocytoma as prognosis of later is good.

Keywords: melanocytoma, melanoma, brain tumor, melanin

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Authors: Mutaz Dwairy

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Solid tumors have high interstitial fluid pressure (IFP), high mechanical stress, and low oxygen levels. Solid stresses may induce apoptosis, stimulate the invasiveness and metastasis of cancer cells, and lower their proliferation rate, while oxygen concentration may affect the response of cancer cells to treatment. Although tumors grow in a nonhomogeneous environment, many existing theoretical models assume homogeneous growth and tissue has uniform mechanical properties. For example, the brain consists of three primary materials: white matter, gray matter, and cerebrospinal fluid (CSF). Therefore, tissue inhomogeneity should be considered in the analysis. This study established a physical model based on convection-diffusion equations and continuum mechanics principles. The model considers the geometrical inhomogeneity of the brain by including the three different matters in the analysis: white matter, gray matter, and CSF. The model also considers fluid-solid interaction and explicitly describes the effect of mechanical factors, e.g., solid stresses and IFP, chemical factors, e.g., oxygen concentration, and biological factors, e.g., cancer cell concentration, on growing tumors. In this article, we applied the model on a brain tumor positioned within the white matter, considering the brain inhomogeneity to estimate solid stresses, IFP, the cancer cell concentration, oxygen concentration, and the deformation of the tissues within the neoplasm and the surrounding. Tumor size was estimated at different time points. This model might be clinically crucial for cancer detection and treatment planning by measuring mechanical stresses, IFP, and oxygen levels in the tissue.

Keywords: biomechanical model, interstitial fluid pressure, solid stress, tumor microenvironment

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Authors: Aoxue Yang, Weili Tian, Yonghe Wu, Haikun Liu

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Brain tumor stem cells (BTSCs) are resistant to therapy and give rise to recurrent tumors. These rare and elusive cells are likely to disseminate during cancer progression, and some may enter dormancy, remaining viable but not increasing. The identification of dormant BTSCs is thus necessary to design effective therapies for glioblastoma (GBM) patients. Little progress has been made in therapeutic treatment of glioblastoma in the last decade despite rapid progress in molecular understanding of brain tumors1. Here we show that the stress hormone glucocorticoid is essential for the maintenance of brain tumor stem cells (BTSCs), which are resistant to conventional therapy. The glucocorticoid receptor (GR) regulates metabolic plasticity and chemoresistance of the dormant BTSC via controlling expression of GPD1 (glycerol-3-phosphate dehydrogenase 1), which is an essential regulator of lipid metabolism in BTSCs. Genomic, lipidomic and cellular analysis confirm that GR/GPD1 regulation is essential for BTSCs metabolic plasticity and survival. We further demonstrate that the GR agonist dexamethasone (DEXA), which is commonly used to control edema in glioblastoma, abolishes the effect of chemotherapy drug temozolomide (TMZ) by upregulating GPD1 and thus promoting tumor cell dormancy in vivo, this provides a mechanistic explanation and thus settle the long-standing debate of usage of steroid in brain tumor patient edema control. Pharmacological inhibition of GR/GPD1 pathway disrupts metabolic plasticity of BTSCs and prolong animal survival, which is superior to standard chemotherapy. Patient case study shows that GR antagonist mifepristone blocks tumor progression and leads to symptomatic improvement. This study identifies an important mechanism regulating cancer stem cell dormancy and provides a new opportunity for glioblastoma treatment.

Keywords: cancer stem cell, dormancy, glioblastoma, glycerol-3-phosphate dehydrogenase 1, glucocorticoid receptor, dexamethasone, RNA-sequencing, phosphoglycerides.

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Authors: Olfat Shaker, Miriam Wadie, Reham Ali, Ayman Yosry

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Colorectal cancer (CRC) is a major cause of mortality and morbidity and accounts for over 9% of cancer incidence worldwide. Silent information regulator 2 homolog 1 (SIRT1) gene is located in the nucleus and exert its effects via modulation of histone and non-histone targets. They function in the cell via histone deacetylase (HDAC) and/or adenosine diphosphate ribosyl transferase (ADPRT) enzymatic activity. The aim of this work was to study the relationship between SIRT1 polymorphism and its protein level in colorectal cancer patients in comparison to control cases. This study includes 2 groups: thirty healthy subjects (control group) & one hundred CRC patients. All subjects were subjected to: SIRT-1 serum level was measured by ELISA and gene polymorphisms of rs12778366, rs375891 and rs3740051 were detected by real time PCR. For CRC patients clinical data were collected (size, site of tumor as well as its grading, obesity) CRC patients showed high significant increase in the mean level of serum SIRT-1 compared to control group (P<0.001). Mean serum level of SIRT-1 showed high significant increase in patients with tumor size ≥5 compared to the size < 5 cm (P<0.05). In CRC patients, percentage of T allele of rs12778366 was significantly lower than controls, CC genotype and C allele C of rs 375891 were significantly higher than control group. In CRC patients, the CC genotype of rs12778366, was 75% in rectosigmoid and 25% in cecum & ascending colon. According to tumor size, the percentage of CC genotype was 87.5% in tumor size ≥5 cm. Conclusion: serum level of SIRT-1 and T allele, C allele of rs12778366 and rs 375891 respectively can be used as diagnostic markers for CRC patients.

Keywords: CRC, SIRT1, polymorphisms, ELISA

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Authors: A. F. Suleimanov, A. B. Saduakassova, V. S. Pokrovsky, D. V. Vinnikov

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Relevance: Epithelial ovarian cancer (EOC) is the most lethal gynecological malignancy, with relapse occurring in about 70% of advanced cases with poor prognoses. The aim of the study was to evaluate functional visceral fat activity (VAT) evaluated by ¹⁸F-fluorodeoxyglucose (¹⁸F-FDG) positron emission tomography/computed tomography (PET/CT) as a predictor of metastases in epithelial ovarian cancer (EOC). Materials and methods: We assessed 53 patients with histologically confirmed EOC who underwent ¹⁸F-FDG PET/CT after a surgical treatment and courses of chemotherapy. Age, histology, stage, and tumor grade were recorded. Functional VAT activity was measured by maximum standardized uptake value (SUVₘₐₓ) using ¹⁸F-FDG PET/CT and tested as a predictor of later metastases in eight abdominal locations (RE – Epigastric Region, RLH – Left Hypochondriac Region, RRL – Right Lumbar Region, RU – Umbilical Region, RLL – Left Lumbar Region, RRI – Right Inguinal Region, RP – Hypogastric (Pubic) Region, RLI – Left Inguinal Region) and pelvic cavity (P) in the adjusted regression models. We also identified the best areas under the curve (AUC) for SUVₘₐₓ with the corresponding sensitivity (Se) and specificity (Sp). Results: In both adjusted-for regression models and ROC analysis, ¹⁸F-FDG accumulation in RE (cut-off SUVₘₐₓ 1.18; Se 64%; Sp 64%; AUC 0.669; p = 0.035) could predict later metastases in EOC patients, as opposed to age, sex, primary tumor location, tumor grade, and histology. Conclusions: VAT SUVₘₐₓ is significantly associated with later metastases in EOC patients and can be used as their predictor.

Keywords: ¹⁸F-FDG, PET/CT, EOC, predictive value

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Authors: Norah Al Hokbany, Ibrahim Al Jammaz, Basem Al Otaibi, Yousif Al Malki, Subhani M. Okarvi

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Objective: The folate receptor is over-expressed in a wide variety of human tumors. Conjugates of folate have been shown to be selectively taken up by tumor cells via the folate receptor. In an attempt to develop new folate radiotracers with favorable biochemical properties for detecting folate receptor-positive cancers. Methods: we synthesized ⁶⁴Cu-NOTA- and ⁶⁴Cu-NOTAM-folate conjugates using a straightforward and simple one-step reaction. Radiochemical yields were greater than 95% (decay-corrected) with a total synthesis time of less than 20 min. Results: Radiochemical purities were always greater than 98% without high-performance liquid chromatography (HPLC) purification. These synthetic approaches hold considerable promise as a rapid and simple method for ⁶⁴Cu-folate conjugate preparation with high radiochemical yield in a short synthesis time. In vitro tests on the KB cell line showed that significant amounts of the radio conjugates were associated with cell fractions. Bio-distribution studies in nude mice bearing human KB xenografts demonstrated a significant tumor uptake and favorable bio-distribution profile for ⁶⁴Cu-NOTA- and ⁶⁴Cu-NOTAM-folate conjugate. The uptake in the tumors was blocked by the excess injection of folic acid, suggesting a receptor-mediated process. Conclusion: These results demonstrate that the ⁶⁴Cu-NOTAM-folate conjugate may be useful as a molecular probe for the detection and staging of folate receptor-positive cancers, such as ovarian cancer and their metastasis, as well as monitoring tumor response to treatment.

Keywords: folate, receptor, tumor imaging, ⁶⁴Cu-NOTA-folate, PET

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Authors: René A. Sørensen, Søren Skovsen, Peter Christiansen, Henrik Karstoft

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Autonomous agricultural machines act in stochastic surroundings and therefore, must be able to perceive the surroundings in real time. This perception can be achieved using image sensors combined with advanced machine learning, in particular Deep Learning. Deep convolutional neural networks excel in labeling and perceiving color images and since the cost of high-quality RGB-cameras is low, the hardware cost of good perception depends heavily on memory and computation power. This paper investigates the possibility of designing lightweight convolutional neural networks for semantic segmentation (pixel wise classification) with reduced hardware requirements, to allow for embedded usage in autonomous agricultural machines. Using compression techniques, a lightweight convolutional neural network is designed to perform real-time semantic segmentation on an embedded platform. The network is trained on two large datasets, ImageNet and Pascal Context, to recognize up to 400 individual classes. The 400 classes are remapped into agricultural superclasses (e.g. human, animal, sky, road, field, shelterbelt and obstacle) and the ability to provide accurate real-time perception of agricultural surroundings is studied. The network is applied to the case of autonomous grass mowing using the NVIDIA Tegra X1 embedded platform. Feeding case-specific images to the network results in a fully segmented map of the superclasses in the image. As the network is still being designed and optimized, only a qualitative analysis of the method is complete at the abstract submission deadline. Proceeding this deadline, the finalized design is quantitatively evaluated on 20 annotated grass mowing images. Lightweight convolutional neural networks for semantic segmentation can be implemented on an embedded platform and show competitive performance with regards to accuracy and speed. It is feasible to provide cost-efficient perceptive capabilities related to semantic segmentation for autonomous agricultural machines.

Keywords: autonomous agricultural machines, deep learning, safety, visual perception

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Authors: Kayode A. Olaniyi, Tola. M. Osifeko, Adeola A. Ogunleye

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Text line segmentation is an important step in document image processing. It represents a labeling process that assigns the same label using distance metric probability to spatially aligned units. Text line detection techniques have successfully been implemented mainly in printed documents. However, processing of the handwritten texts especially unconstrained documents has remained a key problem. This is because the unconstrained hand-written text lines are often not uniformly skewed. The spaces between text lines may not be obvious, complicated by the nature of handwriting and, overlapping ascenders and/or descenders of some characters. Hence, text lines detection and segmentation represents a leading challenge in handwritten document image processing. Text line detection methods that rely on the traditional global projection profile of the text document cannot efficiently confront with the problem of variable skew angles between different text lines. Hence, the formulation of a horizontal line as a separator is often not efficient. This paper presents a technique to segment a handwritten document into distinct lines of text. The proposed algorithm starts, by partitioning the initial text image into columns, across its width into chunks of about 5% each. At each vertical strip of 5%, the histogram of horizontal runs is projected. We have worked with the assumption that text appearing in a single strip is almost parallel to each other. The algorithm developed provides a sliding window through the first vertical strip on the left side of the page. It runs through to identify the new minimum corresponding to a valley in the projection profile. Each valley would represent the starting point of the orientation line and the ending point is the minimum point on the projection profile of the next vertical strip. The derived text-lines traverse around any obstructing handwritten vertical strips of connected component by associating it to either the line above or below. A decision of associating such connected component is made by the probability obtained from a distance metric decision. The technique outperforms the global projection profile for text line segmentation and it is robust to handle skewed documents and those with lines running into each other.

Keywords: connected-component, projection-profile, segmentation, text-line

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Authors: Mehrnoosh Omati, Mahmod Reza Sahebi

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The information on land use/land cover changing plays an essential role for environmental assessment, planning and management in regional development. Remotely sensed imagery is widely used for providing information in many change detection applications. Polarimetric Synthetic aperture radar (PolSAR) image, with the discrimination capability between different scattering mechanisms, is a powerful tool for environmental monitoring applications. This paper proposes a new boundary-based segmentation algorithm as a fundamental step for land cover change detection. In this method, first, two PolSAR images are segmented using integration of marker-controlled watershed algorithm and coupled Markov random field (MRF). Then, object-based classification is performed to determine changed/no changed image objects. Compared with pixel-based support vector machine (SVM) classifier, this novel segmentation algorithm significantly reduces the speckle effect in PolSAR images and improves the accuracy of binary classification in object-based level. The experimental results on Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR) polarimetric images show a 3% and 6% improvement in overall accuracy and kappa coefficient, respectively. Also, the proposed method can correctly distinguish homogeneous image parcels.

Keywords: coupled Markov random field (MRF), environment, object-based analysis, polarimetric SAR (PolSAR) images

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Authors: Hiroyuki Aoki

Abstract:

Molecular imaging has attracted much attention to visualize a tumor site in a living body on the basis of biological functions. A fluorescence in vivo imaging technique has been widely employed as a useful modality for small animals in pre-clinical researches. However, it is difficult to observe a site deep inside a body because of a short penetration depth of light. A photo-acoustic effect is a generation of a sound wave following light absorption. Because the sound wave is less susceptible to the absorption of tissues, an in vivo imaging method based on the photoacoustic effect can observe deep inside a living body. The current study developed an in vivo imaging agent for a photoacoustic imaging method. Nano-particles of poly(lactic acid) including indocyanine dye were developed as bio-compatible imaging agent with strong light absorption. A tumor site inside a mouse body was successfully observed in a photo-acoustic image. A photo-acoustic imaging with polymer nano-particle agent would be a powerful method to visualize a tumor.

Keywords: nano-particle, photo-acoustic effect, polymer, dye, in vivo imaging

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Authors: Yujie Yuan, Yiyang Fan, Hong Fan

Abstract:

Objective: The RNA methylation recognition protein Aly/REF export factor (ALYREF) is considered one type of “reader” protein acting as a recognition protein of m5C, has been reported involved in several biological progresses including cancer initiation and progression. 5-methylcytosine (m5C) is a conserved and prevalent RNA modification in all species, as accumulating evidence suggests its role in the promotion of tumorigenesis. It has been claimed that ALYREF mediates nuclear export of mRNA with m5C modification and regulates biological effects of cancer cells. However, the systematical regulatory pathways of ALYREF in cancer tissues have not been clarified, yet. Methods: The expression level of ALYREF in pan-cancer and their normal tissues was compared through the data acquired from The Cancer Genome Atlas (TCGA). The University of Alabama at Birmingham Cancer data analysis Portal UALCAN was used to analyze the relationship between ALYREF and clinical pathological features. The relationship between the expression level of ALYREF and prognosis of pan-cancer, and the correlation genes of ALYREF were figured out by using Gene Expression Correlation Analysis database GEPIA. Immune related genes were obtained from TISIDB (an integrated repository portal for tumor-immune system interactions). Immune-related research was conducted by using Estimation of STromal and Immune cells in MAlignant Tumor tissues using Expression data (ESTIMATE) and TIMER. Results: Based on the data acquired from TCGA, ALYREF has an obviously higher-level expression in various types of cancers compared with relevant normal tissues excluding thyroid carcinoma and kidney chromophobe. The immunohistochemical images on The Human Protein Atlas showed that ALYREF can be detected in cytoplasm, membrane, but mainly located in nuclear. In addition, a higher expression level of ALYREF in tumor tissue generates a poor prognosis in majority of cancers. According to the above results, cancers with a higher expression level of ALYREF compared with normal tissues and a significant correlation between ALYREF and prognosis were selected for further analysis. By using TISIDB, we found that portion of ALYREF co-expression genes (such as BIRC5, H2AFZ, CCDC137, TK1, and PPM1G) with high Pearson correlation coefficient (PCC) were involved in anti-tumor immunity or affect resistance or sensitivity to T cell-mediated killing. Furthermore, based on the results acquired from GEPIA, there was significant correlation between ALYREF and PD-L1. It was exposed that there is a negative correlation between the expression level of ALYREF and ESTIMATE score. Conclusion: The present study indicated that ALYREF plays a vital and universal role in cancer initiation and progression of pan-cancer through regulating mitotic progression, DNA synthesis and metabolic process, and RNA processing. The correlation between ALYREF and PD-L1 implied ALYREF may affect the therapeutic effect of immunotherapy of tumor. More evidence revealed that ALYREF may play an important role in tumor immunomodulation. The correlation between ALYREF and immune cell infiltration level indicated that ALYREF can be a potential therapeutic target. Exploring the regulatory mechanism of ALYREF in tumor tissues may expose the reason for poor efficacy of immunotherapy and offer more directions of tumor treatment.

Keywords: ALYREF, pan-cancer, immunotherapy, PD-L1

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Authors: Revoti Prasad Bora, Saurabh Yadav, Nikita Katyal

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In the context of educational data mining, the use case of extracting information from images containing both text and diagrams is of high importance. Hence, document analysis requires the extraction of diagrams from such images and processes the text and diagrams separately. To the author’s best knowledge, none among plenty of approaches for extracting tables, figures, etc., suffice the need for real-time processing with high accuracy as needed in multiple applications. In the education domain, diagrams can be of varied characteristics viz. line-based i.e. geometric diagrams, chemical bonds, mathematical formulas, etc. There are two broad categories of approaches that try to solve similar problems viz. traditional computer vision based approaches and deep learning approaches. The traditional computer vision based approaches mainly leverage connected components and distance transform based processing and hence perform well in very limited scenarios. The existing deep learning approaches either leverage YOLO or faster-RCNN architectures. These approaches suffer from a performance-accuracy tradeoff. This paper proposes a U-Net based architecture that formulates the diagram extraction as a segmentation problem. The proposed method provides similar accuracy with a much faster extraction time as compared to the mentioned state-of-the-art approaches. Further, the segmentation mask in this approach allows the extraction of diagrams of irregular shapes.

Keywords: computer vision, deep-learning, educational data mining, faster-RCNN, figure extraction, image segmentation, real-time document analysis, text extraction, U-Net, YOLO

Procedia PDF Downloads 109

Authors: Aditya Karade, Sharada Falane, Dhananjay Deshmukh, Vijaykumar Mantri

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Brain tumors pose a significant challenge in healthcare due to their complex nature and impact on patient outcomes. The application of deep learning (DL) algorithms in medical imaging have shown promise in accurate and efficient brain tumour detection. This paper explores the performance of various pre-trained DL models ResNet50, Xception, InceptionV3, EfficientNetB0, DenseNet121, NASNetMobile, VGG19, VGG16, and MobileNet on a brain tumour dataset sourced from Figshare. The dataset consists of MRI scans categorizing different types of brain tumours, including meningioma, pituitary, glioma, and no tumour. The study involves a comprehensive evaluation of these models’ accuracy and effectiveness in classifying brain tumour images. Data preprocessing, augmentation, and finetuning techniques are employed to optimize model performance. Among the evaluated deep learning models for brain tumour detection, ResNet50 emerges as the top performer with an accuracy of 98.86%. Following closely is Xception, exhibiting a strong accuracy of 97.33%. These models showcase robust capabilities in accurately classifying brain tumour images. On the other end of the spectrum, VGG16 trails with the lowest accuracy at 89.02%.

Keywords: brain tumour, MRI image, detecting and classifying tumour, pre-trained models, transfer learning, image segmentation, data augmentation

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Authors: Behnaz Sohani, Sahand Shahalinezhad, Amir Rahmani, Aliyu Aliyu

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Recently, medical imaging and specifically medical image processing is becoming one of the most dynamically developing areas of medical science. It has led to the emergence of new approaches in terms of the prevention, diagnosis, and treatment of various diseases. In the process of diagnosis of lung cancer, medical professionals rely on computed tomography (CT) scans, in which failure to correctly identify masses can lead to incorrect diagnosis or sampling of lung tissue. Identification and demarcation of masses in terms of detecting cancer within lung tissue are critical challenges in diagnosis. In this work, a segmentation system in image processing techniques has been applied for detection purposes. Particularly, the use and validation of a novel lung cancer detection algorithm have been presented through simulation. This has been performed employing CT images based on multilevel thresholding. The proposed technique consists of segmentation, feature extraction, and feature selection and classification. More in detail, the features with useful information are selected after featuring extraction. Eventually, the output image of lung cancer is obtained with 96.3% accuracy and 87.25%. The purpose of feature extraction applying the proposed approach is to transform the raw data into a more usable form for subsequent statistical processing. Future steps will involve employing the current feature extraction method to achieve more accurate resulting images, including further details available to machine vision systems to recognise objects in lung CT scan images.

Keywords: lung cancer detection, image segmentation, lung computed tomography (CT) images, medical image processing

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