Search results for: hepatic lesion segmentation

Authors: Mi Ju Choi

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This study investigated the perception of gaming tourists toward Macau and developed a typology of gaming tourists. The 1,497 responses from tourists in Macau were collected through convenience sampling method. The dimensions of multi-culture, convenience, economy, gaming, and unsafety, were subsequently extracted as the factors of perception of gaming tourists in Macau. Cluster analysis was performed using the delineated factors (perception of tourists on Macau). Four heterogonous groups were generated, namely, gaming lovers (n = 467, 31.2%), exotic lovers (n = 509, 34.0%), reasonable budget seekers (n = 269, 18.0%), and convenience seekers (n = 252, 16.8%). Further analysis was performed to investigate any difference in gaming behavior and tourist activities. The findings are expected to contribute to the efforts of destination marketing organizations (DMOs) in establishing effective business strategies, provide a profile of gaming tourists in certain market segments, and assist DMOs and casino managers in establishing more effective marketing strategies for target markets.

Keywords: destination image, gaming tourists, Macau, segmentation

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Authors: Zine Kechrid, Samira Bouhalit

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Aim: We studied the effect of intraperitonial zinc treatment on nickel sulphate-induced hepatotoxicity and nephrotoxicity in Wistar strain male albino rats. Materials and Methods: Liver and kidney dysfunction parameters represented by aspartate transaminase (AST), alanine transaminase (ALT), alkaline phosphatase (ALP), blood glucose, serum total protein, serum urea, serum creatinine, and serum belurebin were estimated. Liver glutathione level, catalase and GPx activities were also determined in liver as indicators of oxidative damage. Result: Nickel treatment led to high serum glucose concentration and produced hepatotoxicity and nephrotoxicity characterized by increasing GPT, GOT and alkaline phosphatase activities, serum total protein, serum urea, serum creatinine and serum belurebin concentrations. In addition, liver glutathione level, catalase and GSH-Px activities diminished due to high lipid peroxidation. The simultaneous administration of zinc with nickel sulphate resulted in a remarkable improvement of the previous parameters compared with rats treated with nickel alone. Conclusion: In conclusion, nickel sulphate led to liver and kidney dysfunctions and hepatic lipid peroxidation in animals, but simultaneous treatment with zinc offers a relative protection against nickel induced hepatotoxicity, nephrotoxicity and lipid peroxidation.

Keywords: nickel, zinc, rats, GOT, GPT, nephrotoxicity, hepatotoxicity

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Authors: Renuka Mahadevan, Sharon Chang

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This exploratory study is based on potential cruisers’ monetary valuation of cruise attributes. Using choice experiment, monetary trade-offs between four different cruise attributes are examined with Australians as a case study. We found 50% of the sample valued variety of onboard cruise activities the least while 30% were willing to pay A$87 for cruise-organised activities per day, and the remaining 20% regarded an ocean view to be most valuable at A$125. Latent class modelling was then applied and results revealed that potential cruisers’ valuation of the attributes can be used to segment the market into adventurers, budget conscious and comfort lovers. Evidence showed that socio demographics are not as insightful as lifestyle preferences in developing cruise packages and pricing that would appeal to potential cruisers. Marketing also needs to counter the mindset of potential cruisers’ belief that cruises are often costly and that cruising can be done later in life.

Keywords: latent class modelling, choice experiment, potential cruisers, market segmentation, willingness to pay

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Authors: Shadrack Mambo, Karim Djouani, Yskandar Hamam, Barend van Wyk, Patrick Siarry

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This paper discusses the current trends in medical image registration techniques and addresses the need to provide a solid theoretical foundation for research endeavours. Methodological analysis and synthesis of quality literature was done, providing a platform for developing a good foundation for research study in this field which is crucial in understanding the existing levels of knowledge. Research on medical image registration techniques assists clinical and medical practitioners in diagnosis of tumours and lesion in anatomical organs, thereby enhancing fast and accurate curative treatment of patients. Literature review aims to provide a solid theoretical foundation for research endeavours in image registration techniques. Developing a solid foundation for a research study is possible through a methodological analysis and synthesis of existing contributions. Out of these considerations, the aim of this paper is to enhance the scientific community’s understanding of the current status of research in medical image registration techniques and also communicate to them, the contribution of this research in the field of image processing. The gaps identified in current techniques can be closed by use of artificial neural networks that form learning systems designed to minimise error function. The paper also suggests several areas of future research in the image registration.

Keywords: image registration techniques, medical images, neural networks, optimisaztion, transformation

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Authors: Don Buddika Oshadi Malaweera, Lora Harris, Bruce Rathgeber, Chibuike C. Udenigwe, Kirsti Rouvinen-Watt

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Fatty liver disease is among the three most severe health concerns for mink and believed to occur through the same mechanism as nursing sickness. In North America, nursing sickness affects about 45% of mink farms and in Canada, approximately 50,000 mink females is affected annually. Orotic acid (OA) plays a critical role in lipid metabolism and can increase hepatic lipids by enhancing Sterol regulatory element binding protein-1c expression and decreasing Carnitine palmitoyl transferase I activity. This study was conducted to identify particular pathways and regulatory control points involved in fatty liver development, and evaluate the effectiveness of arginine and bioactive peptides for prevention and treatment of fatty liver disease in mink. A total of 45 mink were used in 9 treatments. The experimental diets consisted of 1% OA, 2% L-arginine and 5% of whey protein hydrolysates. At the end of 10 days of experimental period, the mink were anaesthetized, sampled for blood and euthanized, samples were obtained for histological, biochemical and molecular assays. The blood samples will be analyzed for clinical chemistry and triacylglycerol. The liver samples will be analyzed for total lipid content and analyzed for 6 genes of interest involved in adipogenic transformation, ER stress, and liver inflammation.

Keywords: fatty liver, L-arginine, mink, orotic acid, whey protein hydrolysates

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Authors: Venkatalakshmi Ranganathan, Ong Hsin Ju, Tan Yinn Ming, Lim Kien Sin, Wong Man Ting, Venkata Srikanth Meka

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The mucoadhesive buccal tablet is an oral drug delivery system which attached to the buccal surface for direct drug absorption into the systemic circulation and the unidirectional drug release is ensured by formulating a hydrophobic backing layer. The objective of present study was to formulate mucoadhesive atenolol bilayer buccal tablets by using sodium alginate, hydroxyethyl cellulose, and xanthan gum as mucoadhesive polymer and the technique applied was direct compression method. Ethyl cellulose was used as backing layer of the tablet. FTIR and DSC analysis were carried out to identify the drug polymer interactions. The prepared tablets were evaluated for physicochemical parameters, ex vivo mucoadhesion time and in-vitro drug release. The formulated tablets showed the average surface pH 6-7 which is favourable for oral mucosa. The formulation containing sodium alginate showed more than 90 % of drug release at the end of the 7 hours in vitro dissolution studies. The formulation containing xanthan gum showed more than 8 hours of mucoadhesion time and all formulation exhibited non fickian release kinetics. The present study indicates enormous potential of erodible mucoadhesive buccal tablet containing atenolol for systemic delivery with an added advantage of circumventing the hepatic first pass metabolism.

Keywords: atenolol, mucoadhesion, in vitro drug release, direct compression, ethyl cellulose

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Authors: Suparman

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Piecewise linear regression models are very flexible models for modeling the data. If the piecewise linear regression models are matched against the data, then the parameters are generally not known. This paper studies the problem of parameter estimation of piecewise linear regression models. The method used to estimate the parameters of picewise linear regression models is Bayesian method. But the Bayes estimator can not be found analytically. To overcome these problems, the reversible jump MCMC algorithm is proposed. Reversible jump MCMC algorithm generates the Markov chain converges to the limit distribution of the posterior distribution of the parameters of picewise linear regression models. The resulting Markov chain is used to calculate the Bayes estimator for the parameters of picewise linear regression models.

Keywords: regression, piecewise, Bayesian, reversible Jump MCMC

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Authors: Amna Beshir Medani Ahmed, Samia Mohammed Ali El Badwi, Ahmed El Amin Mohammed

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This work has been managed to yield toxicity information on water treatment agents in the Sudan namely polyDADMAC, using New Zealand rabbits at multiple daily oral doses for a period of 10 weeks. Thirty-three heads of New Zealand rabbits were divided into 11 groups, each of three. Group 1 animals were the undosed controls. Test groups of either species were given polyDADMAC at similar dose rates of 0.5, 2.5, 4.5, 10, 15, 20, 25, 50, 100 and 150 mg/kg body weight respectively for groups 2,3,4,5,6,7,8,9,10 and 11. Clinical signs were closely observed with postmortem and histopathological examinations. Chemical investigations included enzymatic concentrations of ALP, GOT, CK, GPT and LDH together with hematological changes in Hb, PCV, RBCs and WBCs. Mortalities occurred to variable degrees irrespective of the dose level. On polyDADMAC challenge, the test species showed clinical signs of dullness, loss of weight, anorexia, diarrhea, difficulty in respiration, hind limb paralysis and recumbency. Notably oral dosing with polyDADMAC caused lung emphysema, hepatic and renal dysfunctions, irregularity in enzymatic activities and serum metabolites, sloughing of intestinal epithelium, decreased electrolytes in serum, and splenic haemosiderosis. On evaluation of the above results, polyDADMAC was considered toxic to New Zealand rabbits at all dose rates tried. Practical implications of the results were highlighted and suggestions for future work were put forward.

Keywords: polydiallyldiethylaluminiumchloride (polyDADMAC), nubian goats, toxicity of drinking water, treatment of drinking water using chemicals

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Authors: Zhongzhen Luo, Saeid Habibi, Martin v. Mohrenschildt

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Self-driving vehicle require a high level of situational awareness in order to maneuver safely when driving in real world condition. This paper presents a LiDAR based real time perception system that is able to process sensor raw data for multiple target detection and tracking in dynamic environment. The proposed algorithm is nonparametric and deterministic that is no assumptions and priori knowledge are needed from the input data and no initializations are required. Additionally, the proposed method is working on the three-dimensional data directly generated by LiDAR while not scarifying the rich information contained in the domain of 3D. Moreover, a fast and efficient for real time clustering algorithm is applied based on a radially bounded nearest neighbor (RBNN). Hungarian algorithm procedure and adaptive Kalman filtering are used for data association and tracking algorithm. The proposed algorithm is able to run in real time with average run time of 70ms per frame.

Keywords: lidar, segmentation, clustering, tracking

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Authors: Madushani Rodrigo, Banuka Athuraliya

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In today's world of medical diagnosis and prediction, machine learning stands out as a strong tool, transforming old ways of caring for health. This study analyzes the use of machine learning in the specialized domain of sports medicine, with a focus on the timely and accurate detection of bone fractures in cricket athletes. Failure to identify bone fractures in real time can result in malunion or non-union conditions. To ensure proper treatment and enhance the bone healing process, accurately identifying fracture locations and types is necessary. When interpreting X-ray images, it relies on the expertise and experience of medical professionals in the identification process. Sometimes, radiographic images are of low quality, leading to potential issues. Therefore, it is necessary to have a proper approach to accurately localize and classify fractures in real time. The research has revealed that the optimal approach needs to address the stated problem and employ appropriate radiographic image processing techniques and object detection algorithms. These algorithms should effectively localize and accurately classify all types of fractures with high precision and in a timely manner. In order to overcome the challenges of misidentifying fractures, a distinct model for fracture localization and classification has been implemented. The research also incorporates radiographic image enhancement and preprocessing techniques to overcome the limitations posed by low-quality images. A classification ensemble model has been implemented using ResNet18 and VGG16. In parallel, a fracture segmentation model has been implemented using the enhanced U-Net architecture. Combining the results of these two implemented models, the FracXpert system can accurately localize exact fracture locations along with fracture types from the available 12 different types of fracture patterns, which include avulsion, comminuted, compressed, dislocation, greenstick, hairline, impacted, intraarticular, longitudinal, oblique, pathological, and spiral. This system will generate a confidence score level indicating the degree of confidence in the predicted result. Using ResNet18 and VGG16 architectures, the implemented fracture segmentation model, based on the U-Net architecture, achieved a high accuracy level of 99.94%, demonstrating its precision in identifying fracture locations. Simultaneously, the classification ensemble model achieved an accuracy of 81.0%, showcasing its ability to categorize various fracture patterns, which is instrumental in the fracture treatment process. In conclusion, FracXpert has become a promising ML application in sports medicine, demonstrating its potential to revolutionize fracture detection processes. By leveraging the power of ML algorithms, this study contributes to the advancement of diagnostic capabilities in cricket athlete healthcare, ensuring timely and accurate identification of bone fractures for the best treatment outcomes.

Keywords: multiclass classification, object detection, ResNet18, U-Net, VGG16

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Authors: Marcos Bosques-Perez, Walter Izquierdo, Harold Martin, Liangdon Deng, Josue Rodriguez, Thony Yan, Mercedes Cabrerizo, Armando Barreto, Naphtali Rishe, Malek Adjouadi

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Aerial imagery is a powerful tool when it comes to analyzing temporal changes in ecosystems and extracting valuable information from the observed scene. It allows us to identify and assess various elements such as objects, structures, textures, waterways, and shadows. To extract meaningful information, multispectral cameras capture data across different wavelength bands of the electromagnetic spectrum. In this study, the collected multispectral aerial images were subjected to principal component analysis (PCA) to identify independent and uncorrelated components or features that extend beyond the visible spectrum captured in standard RGB images. The results demonstrate that these principal components contain unique characteristics specific to certain wavebands, enabling effective object identification and image segmentation.

Keywords: big data, image processing, multispectral, principal component analysis

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Authors: Samiah Alammari, Nassim Ammour

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When providing a massive number of tasks successively to a deep learning process, a good performance of the model requires preserving the previous tasks data to retrain the model for each upcoming classification. Otherwise, the model performs poorly due to the catastrophic forgetting phenomenon. To overcome this shortcoming, we developed a successful continual learning deep model for remote sensing hyperspectral image regions classification. The proposed neural network architecture encapsulates two trainable subnetworks. The first module adapts its weights by minimizing the discrimination error between the land-cover classes during the new task learning, and the second module tries to learn how to replicate the data of the previous tasks by discovering the latent data structure of the new task dataset. We conduct experiments on HSI dataset Indian Pines. The results confirm the capability of the proposed method.

Keywords: continual learning, data reconstruction, remote sensing, hyperspectral image segmentation

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Authors: Zahow Muoftah

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Traditional manual visual grading of fruits has been one of the agricultural industry’s major challenges due to its laborious nature as well as inconsistency in the inspection and classification process. The main requirements for computer vision and visual processing are some effective techniques for identifying defects and estimating defect areas. Automated defect detection using computer vision and machine learning has emerged as a promising area of research with a high and direct impact on the visual inspection domain. Grading, sorting, and disease detection are important factors in determining the quality of fruits after harvest. Many studies have used computer vision to evaluate the quality level of fruits during post-harvest. Many studies have used computer vision to evaluate the quality level of fruits during post-harvest. Many studies have been conducted to identify diseases and pests that affect the fruits of agricultural crops. However, most previous studies concentrated solely on the diagnosis of a lesion or disease. This study focused on a comprehensive study to identify pests and diseases of apple and banana fruits using detection and classification defects on Banana and Apples by Computer Vision. As a result, the current article includes research from these domains as well. Finally, various pattern recognition techniques for detecting apple and banana defects are discussed.

Keywords: computer vision, banana, apple, detection, classification

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Authors: Hasanpasha N. Sholapur, Basanagouda M.Patil

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Alcoholic extract of the bark of Moringa oleifera Lam. (MO), (Moringaceae), has been evaluated experimentally in the past for its insulin sensitizing potentials. In order to explore the possibility of the class of phytochemical(s) responsible for this experimental claim, the alcoholic extract was fractionated into non-polar [petroleum ether (PEF)], moderately non-polar [ethyl acetate (EAF)] and polar [aqueous (AQF)] fractions. All the fractions and pioglitazone (PIO) as standard (10mg/kg were p.o., once daily for 11 d) were investigated for their chronic effect on fasting plasma glucose, triglycerides, total cholesterol, insulin, oral glucose tolerance and acute effect on oral glucose tolerance in dexamethasone-induced (1 mg/kg s.c., once daily for 11 d) chronic model and acute model (1 mg/kg i.p., for 4 h) respectively for insulin resistance (IR) in rats. Among all the fractions tested, chronic treatment with EAF (140 mg/kg) and PIO (10 mg/kg) prevented dexamethasone-induced IR, indicated by prevention of hypertriglyceridemia, hyperinsulinemia and oral glucose intolerance, whereas treatment with AQF (95 mg/kg) prevented hepatic IR but not peripheral IR. In acute study single dose treatment with EAF (140 mg/kg) and PIO (10 mg/kg) prevented dexamethasone-induced oral glucose intolerance, fraction PEF did not show any effect on these parameters in both the models. The present study indicates that the triterpenoidal and the phenolic class of phytochemicals detected in EAF of alcoholic extract of MO bark may be responsible for the prevention of dexamethasone-induced insulin resistance in rats.

Keywords: Moringa oleifera, insulin resistance, dexamethasone, serum triglyceride, insulin, oral glucose tolerance test

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Authors: Bhuwan C. Joshi, Atish Prakash, Ajudhia N. Kalia

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Ethnopharmacological relevance: The plant Urtica dioica L. (Urticaceae) is used in various diseases including hepatic ailments. Traditionally, the leaves and roots of the plant are used in jaundice. Objective: The aim of the present work was to evaluate hepatoprotective potential of potent antioxidant from Urtica dioica L. against CCl4 induced hepatotoxicity in-vitro and in-vivo model. Materials and methods: Antioxidant activity of hydro alcoholic extract and its fractions petroleum ether fraction (PEF), ethyl acetate fraction (EAF), n-butanol fraction (NBF) and aqueous fraction (AF) were determined by DPPH radicals scavenging assay. Fractions were subjected to in-vitro cell line study. Further, the most potent fraction (EAF) was subjected to in-vivo study. The in-vivo hepatoprotective active fraction was chromatographed on silica column to isolate the bioactive constituent(s). Structure elucidation was done by using various spectrophotometric techniques like UV, IR, 1H NMR, 13C NMR and MS spectroscopy. Results and conclusion: The ethyl acetate fraction (EAF) of Urtica. dioica L. possessed the potent antioxidant activity viz. DPPH (IC50 78.99 ± 0.17 µg/ml). The in-vitro cell line study showed EAF prevented the cell damage. The EAF significantly attenuated the increased liver enzymes activities in serum and tissue. Column chromatography of most potent antioxidant fraction (EAF) leads to the isolation of 4-hydroxy-3-methoxy cinnamic acid which is responsible for its hepatoprotective potential. Hence, the present study suggests that EAF has significant antioxidant and hepatoprotective potential on CCl4 induced hepatotoxicity in-vitro and in-vivo.

Keywords: Urtica dioica L., antioxidant, HepG2 cell line, hepatoprotective

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Authors: Ali Dulla

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This paper introduces a new dataset (and the methodology used to generate it) based on a wide range of historical Arabic documents containing clean data simple and homogeneous-page layouts. The experiments are implemented on printed and handwritten documents obtained respectively from some important libraries such as Qatar Digital Library, the British Library and the Library of Congress. We have gathered and commented on 150 archival document images from different locations and time periods. It is based on different documents from the 17th-19th century. The dataset comprises differing page layouts and degradations that challenge text line segmentation methods. Ground truth is produced using the Aletheia tool by PRImA and stored in an XML representation, in the PAGE (Page Analysis and Ground truth Elements) format. The dataset presented will be easily available to researchers world-wide for research into the obstacles facing various historical Arabic documents such as geometric correction of historical Arabic documents.

Keywords: dataset production, ground truth production, historical documents, arbitrary warping, geometric correction

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Authors: Karthika Durairaj, Buvaneswari G., Gowdham M., Gilles M., Velmurugan G.

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Background: Hyperglycaemia is the primary cause of metabolic illness. Recently, researchers focused on the possibility that chemical exposure could promote metabolic disease. Hyperglycaemia causes a variety of metabolic diseases dependent on its etiologic conditions. According to animal and population-based research, individual chemical exposure causes health problems through alteration of endocrine function with the influence of microbial influence. We were intrigued by the function of gut microbiota variation in high fat and chemically induced hyperglycaemia. Methodology: C57/Bl6 mice were subjected to two different treatments to generate the etiologic-based diabetes model: I – a high-fat diet with a 45 kcal diet, and II - endocrine disrupting chemicals (EDCs) cocktail. The mice were monitored periodically for changes in body weight and fasting glucose. After 120 days of the experiment, blood anthropometry, faecal metagenomics and metabolomics were performed and analyzed through statistical analysis using one-way ANOVA and student’s t-test. Results: After 120 days of exposure, we found hyperglycaemic changes in both experimental models. The treatment groups also differed in terms of plasma lipid levels, creatinine, and hepatic markers. To determine the influence on glucose metabolism, microbial profiling and metabolite levels were significantly different between groups. The gene expression studies associated with glucose metabolism vary between hosts and their treatments. Conclusion: This research will result in the identification of biomarkers and molecular targets for better diabetes control and treatment.

Keywords: hyperglycaemia, endocrine-disrupting chemicals, gut microbiota, host metabolism

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Authors: Shaira L. Kee, Michael Aaron G. Sy, Myles Joshua T. Tan, Hezerul Abdul Karim, Nouar AlDahoul

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Skin diseases are considered the fourth most common disease, with melanoma and non-melanoma skin cancer as the most common type of cancer in Caucasians. The alarming increase in Skin Cancer cases shows an urgent need for further research to improve diagnostic methods, as early diagnosis can significantly improve the 5-year survival rate. Machine Learning algorithms for image pattern analysis in diagnosing skin lesions can dramatically increase the accuracy rate of detection and decrease possible human errors. Several studies have shown the diagnostic performance of computer algorithms outperformed dermatologists. However, existing methods still need improvements to reduce diagnostic errors and generate efficient and accurate results. Our paper proposes an ensemble method to classify dermoscopic images into benign and malignant skin lesions. The experiments were conducted using the International Skin Imaging Collaboration (ISIC) image samples. The dataset contains 3,297 dermoscopic images with benign and malignant categories. The results show improvement in performance with an accuracy of 88% and an F1 score of 87%, outperforming other existing models such as support vector machine (SVM), Residual network (ResNet50), EfficientNetB0, EfficientNetB4, and VGG16.

Keywords: deep learning - VGG16 - efficientNet - CNN – ensemble – dermoscopic images - melanoma

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Authors: Ioannis Boutas, Vasilios Pergialiotis, Nicolaos Salakos, George Agrogiannis, Panagiotis Konstantopoulos, Laskarina-Maria Korou, Theodoros Kalampokas, Odysseas Gregoriou, George Creatsas, Despina Perrea

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Introduction: The effect of third generation aromatase inhibitors in the lipid profile among women with breast cancer, present diversities. It has been also shown that low levels of estrogens affect liver metabolism in mice in numerous ways, such as lipid accumulation and hepatic steatosis. Materials and Methods: Forty-five female Wistar rats underwent surgical ovariectomy. The animals were anesthetized with a combination of ketamine (75 mg/kg) and xylazine (10 mg/kg) which were administered intraperitoneally. After the ovariectomy, the operated animals were randomized in three groups. The first group did not receive any drug regimen (ovariectomized control group). The second group received Anastrazole and the third group received Letrozole. Four months after the initiation of the study, the animals were euthanized and livers were dissected immediately for further histopathological analysis. The histological features were grouped into 4 broad categories: steatosis, ballooning, portal inflammation and lobular activity. A score from 0 (absence) to 3 (severe) was assigned to each parameter. Results: The liver pathology analysis revealed significant differences among groups with favored mild steatosis and ballooning among animals that received Anastrazole or Letrozole. Conclusion: The effect of Anastrazole and Letrozole on liver function have not yet been clarified. In our study mild histological liver alterations seem also to occur and these alterations should be taken in mind in future clinical studies

Keywords: anastrazole, letrozole, liver, rats

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Authors: Hye-Young Shin, Chan Kee Park

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Background: To compare the thinning patterns of the ganglion cell-inner plexiform layer (GCIPL) and peripapillary retinal nerve fiber layer (pRNFL) as measured using Cirrus high-definition optical coherence tomography (HD-OCT) in patients with visual field (VF) defects that respect the vertical meridian. Methods: Twenty eyes of eleven patients with VF defects that respect the vertical meridian were enrolled retrospectively. The thicknesses of the macular GCIPL and pRNFL were measured using Cirrus HD-OCT. The 5% and 1% thinning area index (TAI) was calculated as the proportion of abnormally thin sectors at the 5% and 1% probability level within the area corresponding to the affected VF. The 5% and 1% TAI were compared between the GCIPL and pRNFL measurements. Results: The color-coded GCIPL deviation map showed a characteristic vertical thinning pattern of the GCIPL, which is also seen in the VF of patients with brain lesions. The 5% and 1% TAI were significantly higher in the GCIPL measurements than in the pRNFL measurements (all P < 0.01). Conclusions: Macular GCIPL analysis clearly visualized a characteristic topographic pattern of retinal ganglion cell (RGC) loss in patients with VF defects that respect the vertical meridian, unlike pRNFL measurements. Macular GCIPL measurements provide more valuable information than pRNFL measurements for detecting the loss of RGCs in patients with retrograde degeneration of the optic nerve fibers.

Keywords: brain lesion, macular ganglion cell, inner plexiform layer, spectral-domain optical coherence tomography

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Authors: Niall Fennessy, Charlotte Yin, Vineet Gorolay, Michael Chan, Ilias Drivas

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Background: The aim of this study was to evaluate the effect of manual aspiration of air from the pleural cavity in mitigating the need for chest drain placement after a CT-guided lung biopsy. Method: This is a single institution retrospective review of CT-guided lung biopsies performed on 799 patients between September 2013 and May 2021 in a major tertiary hospital. Percutaneous manual aspiration of air was performed in 104/306 patients (34%) with pneumothoraxes as a preventative measure. Simple and multivariate analysis was performed to identify independent risk factors (modifiable and nonmodifiable) for the success of manual aspiration in mitigating the need for chest drain insertion. Results: The overall incidence of pneumothorax was 37% (295/799). Chest drains were inserted for 81/295 (27%) of the pneumothoraxes, representing 81/799 (10%) of all CT-guided lung biopsies. Of patients with pneumothoraces, 104 (36%) underwent percutaneous aspiration via either the coaxial guide needle or an 18 or 20G intravenous catheter attached to a three-way stopcock and syringe. Amongst this group, 13 patients (13%) subsequently required chest drain insertion. The success of percutaneous aspiration in avoiding subsequent pleural drain insertion decreased with aspiration volume >500mL, radial pneumothorax depth >3cm, increased subpleural depth of the lesion, and the presence of background emphysema.

Keywords: computed tomography, lung biopsy, pneumothorax, manual aspiration, chest drainage

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Authors: M. Bredice, M. B. Forleo, L. Quici

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Coastal tourism is currently facing huge challenges on how to balance environmental problems and tourist activities. Recent literature shows a growing interest in the issue of sustainable tourism from a so-called civilized tourists’ perspective by investigating opinions, perceptions, and behaviors. This study investigates the opinions of youth on what makes them responsible tourists and the ability of coastal marine areas to support tourism in future scenarios. A sample of 778 Italians attending the last year of high school was interviewed. Descriptive statistics, tests, and cluster analyses are applied to highlight the distribution of opinions among youth, detect significant differences based on demographic characteristics, and make segmentation of the different profiles based on students’ opinions and behaviors. Preliminary results show that students are largely convinced (62%) that by 2050 the quality of coastal environments could limit seaside tourism, while 10% of them believe that the problem can be solved simply by changing the tourist destination. Besides the cost of the holiday, the most relevant aspect respondents consider when choosing a marine destination is the presence of tourist attractions followed by the quality of the marine-coastal environment, the specificity of the local gastronomy and cultural traditions, and finally, the activities offered to guests such as sports and events. The reduction of waste and lower air emissions are considered the most important environmental areas in which marine-coastal tourism activities can contribute to preserving the quality of seas and coasts. Areas in which, as a tourist, they believe possible to give a personal contribution were (responses “very much” and “somewhat”); do not throw litter in the sea and on the beach (84%), do not buy single-use plastic products (66%), do not use soap or shampoo when showering in beaches (53%), do not have bonfires (47%), do not damage dunes (46%), and do not remove natural materials (e.g., sand, shells) from the beach (46%). About 6% of the sample stated that they were not interested in contributing to the aforementioned activities, while another 7% replied that they could not contribute at all. Finally, 80% of the sample has never participated in voluntary environmental initiatives or citizen science projects; moreover, about 64% of the students have never participated in events organized by environmental associations in marine or coastal areas. Regarding the test analysis -based on Kruskal-Wallis and Mann and Whitney tests - gender, region, and studying area of students reveals significance in terms of variables expressing knowledge and interest in sustainability topics and sustainable tourism behaviors. The classification of the education field is significant for a great number of variables, among which those related to several sustainable behaviors that respondents declare to be able to contribute as tourists. The ongoing cluster analysis will reveal different profiles in the sample and relevant variables. Based on preliminary results, implications are envisaged in the fields of education, policy, and business strategies for sustainable scenarios. Under these perspectives, the study has the potential to contribute to the conference debate about marine and coastal sustainable development and management.

Keywords: cluster analysis, education, knowledge, young people

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Authors: Chiung-Yun Chang, Po-Chou Chen, Jiun-Shiang Tzeng, Ka-Wai Mac, Chia-Chi Hsiao, Jo-Chi Jao

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This study aimed to measure R2* relaxation rates in the liver of New Zealand White (NZW) rabbits. R2* relaxation rate has been widely used in various hepatic diseases for iron overload by quantifying iron contents in liver. R2* relaxation rate is defined as the reciprocal of T2* relaxation time and mainly depends on the composition of tissue. Different tissues would have different R2* relaxation rates. The signal intensity decay in Magnetic resonance imaging (MRI) may be characterized by R2* relaxation rates. In this study, a 1.5T GE Signa HDxt whole body MR scanner equipped with an 8-channel high resolution knee coil was used to observe R2* values in NZW rabbit’s liver and muscle. Eight healthy NZW rabbits weighted 2 ~ 2.5 kg were recruited. After anesthesia using Zoletil 50 and Rompun 2% mixture, the abdomen of rabbit was landmarked at the center of knee coil to perform 3-plane localizer scan using fast spoiled gradient echo (FSPGR) pulse sequence. Afterward, multi-planar fast gradient echo (MFGR) scans were performed with 8 various echo times (TEs) (2/4/6/8/10/12/14/16 ms) to acquire images for R2* calculations. Regions of interest (ROIs) at liver and muscle were measured using Advantage workstation. Finally, the R2* was obtained by a linear regression of ln(SI) on TE. The results showed that the longer the echo time, the smaller the signal intensity. The R2* values of liver and muscle were 44.8  10.9 s-1 and 37.4  9.5 s-1, respectively. It implies that the iron concentration of liver is higher than that of muscle. In conclusion, R2* is correlated with iron contents in tissue. The correlations between R2* and iron content in NZW rabbit might be valuable for further exploration.

Keywords: liver, magnetic resonance imaging, muscle, R2* relaxation rate

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Authors: Vaibhav V. Dixit, Shubham Ajay Karwa

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Diabetic foot ulcers speak to a critical medical problem. Right now, clinicians and medical caretakers primarily construct their injury evaluation in light of visual examination of wound size and mending status, while the patients themselves rarely have a chance to play a dynamic part. Henceforth, love quantitative and practical examination technique that empowers the patients and their parental figures to take a more dynamic part in every day wound care possibly can quicken wound recuperating, spare travel cost and diminish human services costs. Considering the commonness of cell phones with a high-determination computerized camera, evaluating wounds by breaking down pictures of ceaseless foot ulcers is an alluring choice. In this paper, we propose a novel injury picture examination framework actualized using feature extraction and color segmentation. Here we are using the Normalized minimum distance classifier for classifying the output.

Keywords: diabetic, Gabor wavelet, normalized minimum distance classifier, quantiable parameters

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Authors: Maryam Fallahpoor, Biswajeet Pradhan

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Background: Artificial intelligence (AI) serves as a valuable tool in mitigating the scarcity of human resources required for the evaluation and categorization of vast quantities of medical imaging data. When AI operates with optimal precision, it minimizes the demand for human interpretations and, thereby, reduces the burden on radiologists. Among various AI approaches, deep learning (DL) stands out as it obviates the need for feature extraction, a process that can impede classification, especially with intricate datasets. The advent of DL models has ushered in a new era in medical imaging, particularly in the context of COVID-19 detection. Traditional 2D imaging techniques exhibit limitations when applied to volumetric data, such as Computed Tomography (CT) scans. Medical images predominantly exist in one of two formats: neuroimaging informatics technology initiative (NIfTI) and digital imaging and communications in medicine (DICOM). Purpose: This study aims to employ DL for the classification of COVID-19-infected pulmonary patients and normal cases based on 3D CT scans while investigating the impact of image format. Material and Methods: The dataset used for model training and testing consisted of 1245 patients from IranMehr Hospital. All scans shared a matrix size of 512 × 512, although they exhibited varying slice numbers. Consequently, after loading the DICOM CT scans, image resampling and interpolation were performed to standardize the slice count. All images underwent cropping and resampling, resulting in uniform dimensions of 128 × 128 × 60. Resolution uniformity was achieved through resampling to 1 mm × 1 mm × 1 mm, and image intensities were confined to the range of (−1000, 400) Hounsfield units (HU). For classification purposes, positive pulmonary COVID-19 involvement was designated as 1, while normal images were assigned a value of 0. Subsequently, a U-net-based lung segmentation module was applied to obtain 3D segmented lung regions. The pre-processing stage included normalization, zero-centering, and shuffling. Four distinct 3D CNN models (ResNet152, ResNet50, DensNet169, and DensNet201) were employed in this study. Results: The findings revealed that the segmentation technique yielded superior results for DICOM images, which could be attributed to the potential loss of information during the conversion of original DICOM images to NIFTI format. Notably, ResNet152 and ResNet50 exhibited the highest accuracy at 90.0%, and the same models achieved the best F1 score at 87%. ResNet152 also secured the highest Area under the Curve (AUC) at 0.932. Regarding sensitivity and specificity, DensNet201 achieved the highest values at 93% and 96%, respectively. Conclusion: This study underscores the capacity of deep learning to classify COVID-19 pulmonary involvement using real 3D hospital data. The results underscore the significance of employing DICOM format 3D CT images alongside appropriate pre-processing techniques when training DL models for COVID-19 detection. This approach enhances the accuracy and reliability of diagnostic systems for COVID-19 detection.

Keywords: deep learning, COVID-19 detection, NIFTI format, DICOM format

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Authors: Vahid Anari, Mina Bakhshi

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Visual search and identification of immunohistochemically stained tissue of meningioma was performed manually in pathologic laboratories to detect and diagnose the cancers type of meningioma. This task is very tedious and time-consuming. Moreover, because of cell's complex nature, it still remains a challenging task to segment cells from its background and analyze them automatically. In this paper, we develop and test a computerized scheme that can automatically identify cells in microscopic images of meningioma and classify them into positive (proliferative) and negative (normal) cells. Dataset including 150 images are used to test the scheme. The scheme uses Fuzzy C-means algorithm as a color clustering method based on perceptually uniform hue, saturation, value (HSV) color space. Since the cells are distinguishable by the human eye, the accuracy and stability of the algorithm are quantitatively compared through application to a wide variety of real images.

Keywords: positive cell, color segmentation, HSV color space, immunohistochemistry, meningioma, thresholding, fuzzy c-means

Procedia PDF Downloads 190

Authors: Marina Lazar Chandy, N. Kannan, Rajendra Patil, Vinod Mathew, Ajmal Mohamed, P. K. Sreeja, Renju Jose

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Introduction- Arecoline, a major constituent of arecanut has shown to have some effect on liver. The use of arecanut is found to be the most common etiological factor for the development of Oral Submucous fibrosis (O.S.M.F). The effect of arecanut usage on liver in patients with O.S.M.F needs to be assessed. Lipids play a role in structural maintenance of cell. Alterations of lipid profile were noted in cancer patients. O.S.M.F being a precancerous lesion can have some effect on the level of lipids in the body. Objectives: This study was done to assess the alterations in liver enzymes (Serum Glutamic Pyruvic Transaminase(S.G.P.T ,Serum Glutamic Oxaloacetic Transaminase(S.G.O.T)) and lipid metabolism (High Density Lipoprotien(H.D.L) and Apo Lipoprotien A1 (Apo A1)) in patients with O.S.M.F. Methods-130 patients were taken for the study,100 patients with O.S.M.F and 30 as control group without O.S.M.F. Fasting blood sugar levels were taken, centrifuged and analyzed for S.G.P.T,S.G.O.T, H.D.L and Apo A1 using semi automated spectrophotometer. Results: After statistical analysis, it was concluded that there is an elevation of levels of S.G.P.T, S.G.O.T, and decreased levels of H.D.L, Apo A1 for O.S.M.F group when compared with control group. With increased grade of O.S.M.F. and duration of habit, S.G.P.T. & S.G.O.T. increased whereas, H.D.L. & Apo A1 decreased. All the values were statistically significant at p<0.01.

Keywords: apolipoprotien A1, high density lipoprotien, oral submucous fibrosis, serum glutamic oxaloacetic transaminase

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Authors: Hasan Afarnegan, Ali Shahraki, Jafar Shahraki

Abstract:

Paraquat is widely used as a strong nitrogen-based herbicide for controlling of weeds in agriculture. This poison is extremely toxic for humans which induces several – organ failure by accumulation in cells and many instances of death occurred due to its poisoning. Paraquat metabolized primarily in the liver. The purpose of this study was to assess the effects of aquatic extract of levisticum officinale on oxidative status and biochemical factors in hepatocytes exposed to paraquat. Our results determined that hepatocytes destruction induced by paraquat is mediated by reactive oxygen species (ROS) production, lipid peroxidation and decrease of mitochondrial membrane potential were significantly (P<0.05) prevented by aquatic extract of Levisicum officinale (100, 200 and 300 µg/ml). These effects of paraquat also prevented via antioxidants and ROS scavengers (α-tocopherol, DMSO, manitol), mitochondrial permeability transition (MPT) pore sealing compound (carnitine).MPT pore sealing compound inhibited the hepatotoxicity, indicating that paraquat induced cell death via mithochondrial pathway. Pretreatment of hepatocytes with aquatic extracts of Levisticum officinale, antioxidants and ROS scavengers also blocked hepatic cell death caused by paraquat, suggesting that oxidative stress may be directly induced decline of mithochondrial membrane potential. In conclusion, paraquat hepatotoxicity can be attributed to oxidative stress and continued by mithochondrial membrane potential disruption. Levisticum officinale aquatic extract, presumably due to its strong antoxidant properties, could protect the destructive effects of paraquat on rat hepatocytes.

Keywords: hepatocyte protection, levisticum officinale, oxidative stress, paraquat

Procedia PDF Downloads 199

Authors: Tayyibah Shah Alam, Joe Thomas, Nayantara Shenoy

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Presenting a case that we would like to share, the answer is straight forward but the path taken to get to the diagnosis is where it gets interesting. A 31-year-old lady presented to the Rheumatology Outpatient department with left-sided chest pain associated with left-sided elbow joint pain intensifying over the last 2 days. She had been having a prolonged history of chest pain with minimal intensity since 2016. The pain is intermittent in nature. Aggravated while exerting, lifting heavy weights and lying down. Relieved while sitting. Her physical examination and laboratory tests were within normal limits. An electrocardiogram (ECG) showed normal sinus rhythm and a chest X-ray with no significant abnormality was noted. The primary suspicion was recurrent costochondritis. Cardiac blood inflammatory markers and Echo were normal, ruling out ACS. CT chest and MRI Thorax contrast showed small ill-defined STIR hyperintensity with thin peripheral enhancement in the anterior mediastinum in the left side posterior to the 5th costal cartilage and anterior to the pericardium suggestive of changes in the fat-focal panniculitis. Confirming the diagnosis as Epicardial fat necrosis. She was started on Colchicine and Nonsteroidal anti-inflammatory drugs for 2-3 weeks, following which a repeat CT showed resolution of the lesion and improvement in her. It is often under-recognized or misdiagnosed. CT scan was collectively used to establish the diagnosis. Making the correct diagnosis prospectively alleviates unnecessary testing in favor of conservative management.

Keywords: EFN, panniculitis, unknown etiology, recurrent chest pain

Procedia PDF Downloads 79

Authors: S. P. Gomes, D. C. Goncalves, E. Ribeiro, M. C. L. Seelaender

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Skin is susceptible to photo damage induced by exposure to sunlight, or ultraviolet (UV) radiation, which induces breakdown of extracellular matrix, DNA degradation, skin cell lesion and apoptosis, and development of cancer. Phytonutrients demonstrate protective effects against UV damage. The purpose of this study was evaluating the effect of an antioxidant juice (AJ) contaning Brazilian natural products upon skin damage. The juice was produced by Metabolics®. Male Wistar rats were divided in 4 groups: Animals receiving the antioxidant juice (AJ): orange, carrot, honey, tomato extract, avocado, ginger and camu-camu (Brazilian fruit, a major source of vitamin C) ad libitum for 21 days; or water (C), subdivided in groups exposed or not to UV radiation for 2 non consecutive days, during five hours each day, after 15 days of juice supplementation. On the 22nd day, rats were killed by decapitation and epithelium samples from the dorsal skin removed, fixed in bouin and embedded in paraffin. The sections were stained with hematoxylin and eosin or mallory and picrosirius red. Isolated DNA was submitted to electrophoresis (1.8% agarose gel, 0.5% ethidium bromide). UV radiation significantly induced sunburn of superficial epithelial cells of C, AJ treatment reduced this effect. Collagen changes were observed in UV groups, yet AJ treatment prevented collagen degradation. UV radiation induced significant DNA degradation, in C, which was prevented by AJ treatment. The antioxidant juice consumed chronically protected against acute skin damage.

Keywords: nutraceuticals, antioxidants, photoprotection, uv radiation

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