Search results for: lung physiology
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 697

Search results for: lung physiology

517 Isolation of Cytotoxic Compound from Tectona grandis Stem to Be Used as Thai Medicinal Preparation for Cancer Treatment

Authors: Onmanee Prajuabjinda, Pakakrong Thondeeying, Jipisute Chunthorng-Orn, Bhanuz Dechayont, Arunporn Itharat

Abstract:

A Thai medicinal preparation has been used for cancer treatment more than ten years ago in Khampramong Temple. Tectona grandis stem is one ingredient of this Thai medicinal remedy. The ethanolic extract of Tectona grandis stem showed the highest cytotoxic activities against human breast adenocarcinoma (MCF-7), but was less cytotoxic against large cell lung carcinoma (COR-L23) (IC50 = 3.92 and 7.78 µg/ml, respectively). It was isolated by bioassay-guided isolation method. Tectoquinone, a anthraquinone compound was isolated from this plant. This compound showed high specific cytotoxicity against human breast adenocarcinoma (MCF-7), but was less cytotoxic against large cell lung carcinoma (COR-L23)(IC50 =16.15 and 47.56 µg/ml or 72.67 and 214.00 µM, respectively). However, it showed less cytotoxic activity than the crude extract. In conclusion, tectoquinone as a main compound, is not the best cytotoxic compound from Tectona grandis, so there are more active cytotoxic compounds in this extract which should be isolated in the future. Moreover, tectoquinone displayed specific cytotoxicity against only human breast adenocarcinoma (MCF-7) which is a good criterion for cancer treatment.

Keywords: Tectona grandis, SRB assay, cytotoxicity, tectoquinone

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516 A Human Centered Design of an Exoskeleton Using Multibody Simulation

Authors: Sebastian Kölbl, Thomas Reitmaier, Mathias Hartmann

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Trial and error approaches to adapt wearable support structures to human physiology are time consuming and elaborate. However, during preliminary design, the focus lies on understanding the interaction between exoskeleton and the human body in terms of forces and moments, namely body mechanics. For the study at hand, a multi-body simulation approach has been enhanced to evaluate actual forces and moments in a human dummy model with and without a digital mock-up of an active exoskeleton. Therefore, different motion data have been gathered and processed to perform a musculosceletal analysis. The motion data are ground reaction forces, electromyography data (EMG) and human motion data recorded with a marker-based motion capture system. Based on the experimental data, the response of the human dummy model has been calibrated. Subsequently, the scalable human dummy model, in conjunction with the motion data, is connected with the exoskeleton structure. The results of the human-machine interaction (HMI) simulation platform are in particular resulting contact forces and human joint forces to compare with admissible values with regard to the human physiology. Furthermore, it provides feedback for the sizing of the exoskeleton structure in terms of resulting interface forces (stress justification) and the effect of its compliance. A stepwise approach for the setup and validation of the modeling strategy is presented and the potential for a more time and cost-effective development of wearable support structures is outlined.

Keywords: assistive devices, ergonomic design, inverse dynamics, inverse kinematics, multibody simulation

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515 Effect of Brown Algae, Ecklonia arborea and Silvetia compressa, in Lipidemic and Hepatic Metabolism in Wistar Rats

Authors: Laura Acevedo-Pacheco, Janet Alejandra Gutierrez-Uribe, Lucia Elizabeth Cruz-Suarez, Segio Othon Serna-Saldivar

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Seaweeds can generate changes in the metabolism of lipids; as a consequence, this may diminish cholesterol and other lipids in the blood. However, the consumption of marine algae may also alter the functions of other organs. Therefore, the objective of this research was to study the effect of two different sorts of algae (Ecklonia arborea and Silvetia compressa) in the metabolism of lipids, as well as, in the physiology of the liver. Wistar male rats were fed for two months with independent diets composed of 20% of fat and 2.5% of E. arborea and S. compressa each. Blood parameters (cholesterol, lipoproteins, triglycerides, hepatic enzymes) and triglycerides in the liver were quantified, and also hepatic histology analyses were performed. While S. compressa reduced 18% total cholesterol compared to the positive control, E. arborea increased it 5.8%. Animals fed with S. compressa presented a decrement, compared to the positive control, not only in low density lipoproteins levels (53%) but also in triglycerides (67%). The presence of steatosis in the histologies and the high levels of triglycerides showed an evident lipid accumulation in hepatic tissues of rats fed with both algae. These results indicate that even though S. compressa showed a promising resource to decrease total cholesterol and low-density lipoproteins in blood, a detrimental effect was observed in liver physiology. Further investigations should be made to find out if toxic compounds associated with these seaweeds may cause liver damage especially in terms of heavy metals.

Keywords: brown algae, Eisenia arborea, hepatic metabolism, lipidemic metabolism, Pelvetia compressa, steatosis

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514 Generation of High-Quality Synthetic CT Images from Cone Beam CT Images Using A.I. Based Generative Networks

Authors: Heeba A. Gurku

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Introduction: Cone Beam CT(CBCT) images play an integral part in proper patient positioning in cancer patients undergoing radiation therapy treatment. But these images are low in quality. The purpose of this study is to generate high-quality synthetic CT images from CBCT using generative models. Material and Methods: This study utilized two datasets from The Cancer Imaging Archive (TCIA) 1) Lung cancer dataset of 20 patients (with full view CBCT images) and 2) Pancreatic cancer dataset of 40 patients (only 27 patients having limited view images were included in the study). Cycle Generative Adversarial Networks (GAN) and its variant Attention Guided Generative Adversarial Networks (AGGAN) models were used to generate the synthetic CTs. Models were evaluated by visual evaluation and on four metrics, Structural Similarity Index Measure (SSIM), Peak Signal Noise Ratio (PSNR) Mean Absolute Error (MAE) and Root Mean Square Error (RMSE), to compare the synthetic CT and original CT images. Results: For pancreatic dataset with limited view CBCT images, our study showed that in Cycle GAN model, MAE, RMSE, PSNR improved from 12.57to 8.49, 20.94 to 15.29 and 21.85 to 24.63, respectively but structural similarity only marginally increased from 0.78 to 0.79. Similar, results were achieved with AGGAN with no improvement over Cycle GAN. However, for lung dataset with full view CBCT images Cycle GAN was able to reduce MAE significantly from 89.44 to 15.11 and AGGAN was able to reduce it to 19.77. Similarly, RMSE was also decreased from 92.68 to 23.50 in Cycle GAN and to 29.02 in AGGAN. SSIM and PSNR also improved significantly from 0.17 to 0.59 and from 8.81 to 21.06 in Cycle GAN respectively while in AGGAN SSIM increased to 0.52 and PSNR increased to 19.31. In both datasets, GAN models were able to reduce artifacts, reduce noise, have better resolution, and better contrast enhancement. Conclusion and Recommendation: Both Cycle GAN and AGGAN were significantly able to reduce MAE, RMSE and PSNR in both datasets. However, full view lung dataset showed more improvement in SSIM and image quality than limited view pancreatic dataset.

Keywords: CT images, CBCT images, cycle GAN, AGGAN

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513 Detection of Elephant Endotheliotropic Herpes Virus in a Wild Asian Elephant Calf in Thailand by Using Real-Time PCR

Authors: Bopit Puyati, Anchittha Kaewchana, Nuntita Ruksachat

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In January 2018, a male wild elephant, approximately 2 years old, was found dead in Phu Luang Wildlife Sanctuary, Loei province. The elephant was likely to die around 2 weeks earlier. The carcass was decayed without any signs of attack or bullet. No organs were removed. A deadly viral disease was suspected. Different organs including lung, liver, intestine and tongue were collected and submitted to the veterinary research and development center, Surin province for viral detection. The samples were then examined with real-time PCR for detecting U41 Major DNA binding protein (MDBP) gene and with conventional PCR for the presence of specific polymerase gene. We used tumor necrosis factor (TNF) gene as the internal control. In our real-time PCR, elephant endotheliotropic herpesvirus (EEHV) was recovered from lung, liver, and tongue whereas only tongue provided a positive result in the conventional PCR. All samples were positive with TNF gene detection. To our knowledge, this is the first report of EEHV detection in wild elephant in Thailand. EEHV surveillance in this wild population is strongly suggested. Linkage between EEHV in wild and domestic elephants should be further explored.

Keywords: elephant endotheliotropic herpes virus, PCR, Thailand, wild Asian elephant

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512 LncRNA NEAT1 Promotes NSCLC Progression through Acting as a ceRNA of miR-377-3p

Authors: Chengcao Sun, Shujun Li, Cuili Yang, Yongyong Xi, Liang Wang, Feng Zhang, Dejia Li

Abstract:

Recently, the long non-coding RNA (lncRNA) NEAT1 has been identified as an oncogenic gene in multiple cancer types and elevated expression of NEAT1 was tightly linked to tumorigenesis and cancer progression. However, the molecular basis for this observation has not been characterized in progression of non-small cell lung cancer (NSCLC). In our studies, we identified NEAT1 was highly expressed in NSCLC patients and was a novel regulator of NSCLC progression. Patients whose tumors had high NEAT1 expression had a shorter overall survival than patients whose tumors had low NEAT1 expression. Further, NEAT1 significantly accelerates NSCLC cell growth and metastasis in vitro and tumor growth in vivo. Additionally, by using bioinformatics study and RNA pull down combined with luciferase reporter assays, we demonstrated that NEAT1 functioned as a competing endogenous RNA (ceRNA) for has-miR-377-3p, antagonized its functions and led to the de-repression of its endogenous targets E2F3, which was a core oncogene in promoting NSCLC progression. Taken together, these observations imply that the NEAT1 modulated the expression of E2F3 gene by acting as a competing endogenous RNA, which may build up the missing link between the regulatory miRNA network and NSCLC progression.

Keywords: long non-coding RNA NEAT1, hsa-miRNA-377-3p, E2F3, non-small cell lung cancer, tumorigenesis

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511 Metabolomics Profile Recognition for Cancer Diagnostics

Authors: Valentina L. Kouznetsova, Jonathan W. Wang, Igor F. Tsigelny

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Metabolomics has become a rising field of research for various diseases, particularly cancer. Increases or decreases in metabolite concentrations in the human body are indicative of various cancers. Further elucidation of metabolic pathways and their significance in cancer research may greatly spur medicinal discovery. We analyzed the metabolomics profiles of lung cancer. Thirty-three metabolites were selected as significant. These metabolites are involved in 37 metabolic pathways delivered by MetaboAnalyst software. The top pathways are glyoxylate and dicarboxylate pathway (its hubs are formic acid and glyoxylic acid) along with Citrate cycle pathway followed by Taurine and hypotaurine pathway (the hubs in the latter are taurine and sulfoacetaldehyde) and Glycine, serine, and threonine pathway (the hubs are glycine and L-serine). We studied interactions of the metabolites with the proteins involved in cancer-related signaling networks, and developed an approach to metabolomics biomarker use in cancer diagnostics. Our analysis showed that a significant part of lung-cancer-related metabolites interacts with main cancer-related signaling pathways present in this network: PI3K–mTOR–AKT pathway, RAS–RAF–ERK1/2 pathway, and NFKB pathway. These results can be employed for use of metabolomics profiles in elucidation of the related cancer proteins signaling networks.

Keywords: cancer, metabolites, metabolic pathway, signaling pathway

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510 Indoor Air Pollution: A Major Threat to Human Health

Authors: Pooja Rawat, Rakhi Tyagi

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Globally, almost 3 billion people rely on biomass (wood, charcoal, dung and crop residues) and coal as their primary source of domestic energy. Cooking and heating with solid fuels on open fire give rise to major pollutants. Women are primarily affected by these pollutants as they spend most of their time in the house. The WHO World Health Report 2002 estimates that indoor air pollution (IAP) is responsible for 2.7% of the loss of disability adjusted life years (DALYs) worldwide and 3.7% in high mortality developing countries. Indoor air pollution has the potential to not only impact health, but also impact the general economic well-being of the household. Exposure to high level of household pollution lead to acute and chronic respiratory conditions (e.g.: pneumonia, chronic obstructive pulmonary disease, lung cancer and cataract). There has been many strategies for reducing IAP like subsidize cleaner fuel technologies, for example use of kerosene rather than traditional biomass fuels. Another example is development, promotion of 'improved cooking stoves'. India, likely ranks second- distributing over 12 million improved stoves in the first seven years of a national program to develop. IAP should be reduced by understanding the welfare effects of reducing IAP within households and to understanding the most cost effective way to reduce it.

Keywords: open fire, indoor pollution, lung diseases, indoor air pollution

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509 Analysis of Anti-Tuberculosis Immune Response Induced in Lungs by Intranasal Immunization with Mycobacterium indicus pranii

Authors: Ananya Gupta, Sangeeta Bhaskar

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Mycobacterium indicus pranii (MIP) is a saprophytic mycobacterium. It is a predecessor of M. avium complex (MAC). Whole genome analysis and growth kinetics studies have placed MIP in between pathogenic and non-pathogenic species. It shares significant antigenic repertoire with M. tuberculosis and have unique immunomodulatory properties. MIP provides better protection than BCG against pulmonary tuberculosis in animal models. Immunization with MIP by aerosol route provides significantly higher protection as compared to immunization by subcutaneous (s.c.) route. However, mechanism behind differential protection has not been studied. In this study, using mice model we have evaluated and compared the M.tb specific immune response in lung compartments (airway lumen / lung interstitium) as well as spleen following MIP immunization via nasal (i.n.) and s.c. route. MIP i.n. vaccination resulted in increased seeding of memory T cells (CD4+ and CD8+ T-cells) in the airway lumen. Frequency of CD4+ T cells expressing Th1 migratory marker (CXCR3) and activation marker (CD69) were also high in airway lumen of MIP i.n. group. Significantly high ex vivo secretion of cytokines- IFN-, IL-12, IL-17 and TNF- from cells of airway luminal spaces provides evidence of antigen-specific lung immune response, besides generating systemic immunity comparable to MIP s.c. group. Analysis of T cell response on per cell basis revealed that antigen specific T-cells of MIP i.n. group were functionally superior as higher percentage of these cells simultaneously secreted IFN-gamma, IL-2 and TNF-alpha cytokines as compared to MIP s.c. group. T-cells secreting more than one of the cytokines simultaneously are believed to have robust effector response and crucial for protection, compared with single cytokine secreting T-cells. Adoptive transfer of airway luminal T-cells from MIP i.n. group into trachea of naive B6 mice revealed that MIP induced CD8 T-cells play crucial role in providing long term protection. Thus the study demonstrates that MIP intranasal vaccination induces M.tb specific memory T-cells in the airway lumen that results in an early and robust recall response against M.tb infection.

Keywords: airway lumen, Mycobacterium indicus pranii, Th1 migratory markers, vaccination

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508 Prone Positioning and Clinical Outcomes of Mechanically Ventilated Patients with Severe Acute Respiratory Distress Syndrome

Authors: Maha Salah Abdullah Ismail, Mahmoud M. Alsagheir, Mohammed Salah Abd Allah

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Acute respiratory distress syndrome (ARDS) is characterized by permeability pulmonary edema and refractory hypoxemia. Lung-protective ventilation is still the key of better outcome in ARDS. Prone position reduces the trans-pulmonary pressure gradient, recruiting collapsed regions of the lung without increasing airway pressure or hyperinflation. Prone ventilation showed improved oxygenation and improved outcomes in severe hypoxemic patients with ARDS. This study evaluates the effect of prone positioning on mechanically ventilated patients with ARDS. A quasi-experimental design was carried out at Critical Care Units, on 60 patients. Two tools were utilized to collect data; Socio demographic, medical and clinical outcomes data sheet. Results of the present study indicated that prone position improves oxygenation in patients with severe respiratory distress syndrome. The study recommended that use prone position in patients with severe ARDS, as early as possible and for long sessions. Also, replication of this study on larger probability sample at the different geographical location is highly recommended.

Keywords: acute respiratory distress syndrome, critical care, mechanical ventilation, prone position

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507 The Utilization of FSI Technique and Two-Way Particle Coupling System on Particle Dynamics in the Human Alveoli

Authors: Hassan Athari, Abdurrahim Bolukbasi, Dogan Ciloglu

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This study represented the respiratory alveoli system, and determined the trajectory of inhaled particles more accurately using the modified three-dimensional model with deformable walls of alveoli. The study also considered the tissue tension in the model to demonstrate the effect of lung. Tissue tensions are transferred by the lung parenchyma and produce the pressure gradient. This load expands the alveoli and establishes a sub-ambient (vacuum) pressure within the lungs. Thus, at the alveolar level, the flow field and movement of alveoli wall lead to an integrated effect. In this research, we assume that the three-dimensional alveolus has a visco-elastic tissue (walls). For accurate investigation of pulmonary tissue mechanical properties on particle transport and alveolar flow field, the actual relevance between tissue movement and airflow is solved by two-way FSI (Fluid Structure Interaction) simulation technique in the alveolus. Therefore, the essence of real simulation of pulmonary breathing mechanics can be achieved by developing a coupled FSI computational model. We, therefore conduct a series of FSI simulations over a range of tissue models and breathing rates. As a result, the fluid flows and streamlines have changed during present flexible model against the rigid models and also the two-way coupling particle trajectories have changed against the one-way particle coupling.

Keywords: FSI, two-way particle coupling, alveoli, CDF

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506 Ergosterol Regulated Functioning of Rubisco in Tomato

Authors: Prabir Kumar Paul, Joyeeta Mitra

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Ergosterol, is an important fungal metabolite on phylloplane which is not synthesised by plants. However, the functional requirement of ergosterol to the plants is still an enigma. Being ubiquitously present in all plants except algae needs an insight into its physiological implication. The present study aimed at understanding if and how ergosterol influences the physiology of chloroplast particularly the activity of RuBisCo and carbonic anhydrase. The concept of the study was based on one of our earlier observation of enhanced Hills reaction in plants treated with fungal metabolites which contained ergosterol. The fungal metabolite treated plants had a significantly high concentration of photosynthetic pigments. Eight-week-old tomato plants raised under aseptic conditions at 25 + 10 C, 75 % relative humidity and 12 hour L/D photoperiod. Metabolites of Aspergillus niger and Fusarium oxysporum were sprayed on plants either singly or in a 1: 1 combination. A separate group of plants was also treated with 0.5, 1.0, 3.0, 5.0. 7.0 mg ergosterol / ml of n- heptane. Control plants were treated with sterile distilled water only. Plants were sampled at 24, 48, 72 and 96 hours of treatment. RuBisCo and carbonic anhydrase was estimated from sampled leaves. RuBisCo was separated on 1D SDS-PAGE and subjected to MALDI – TOF- TOF – MS analysis. The presence of ergosterol in fungal metabolites was confirmed. Fungal metabolites significantly enhanced the concentration and activity of RuBisCo and carbonic anhydrase. The Vmax activity of the enzymes was significantly high in metabolite treated plants. 1:1 mix of metabolite was more effective than when applied individually. Insilico analysis revealed, RuBisCo subunits had a binding site for ergosterol and in its presence affinity of Co2 to the enzyme increased by several folds. Invivo activity of RuBisCo was significantly elicited by ergosterol. Results of the present study indicate that ergosterol from phylloplane microfungi probably regulates the binding of Co2 to RuBisCo along with activity of carbonic anhydrase thereby modulating the physiology of choloroplast.

Keywords: carbonic anhydrase, ergosterol, phylloplane, RuBisCo

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505 Numerical Simulation on Airflow Structure in the Human Upper Respiratory Tract Model

Authors: Xiuguo Zhao, Xudong Ren, Chen Su, Xinxi Xu, Fu Niu, Lingshuai Meng

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The respiratory diseases such as asthma, emphysema and bronchitis are connected with the air pollution and the number of these diseases tends to increase, which may attribute to the toxic aerosol deposition in human upper respiratory tract or in the bifurcation of human lung. The therapy of these diseases mostly uses pharmaceuticals in the form of aerosol delivered into the human upper respiratory tract or the lung. Understanding of airflow structures in human upper respiratory tract plays a very important role in the analysis of the “filtering” effect in the pharynx/larynx and for obtaining correct air-particle inlet conditions to the lung. However, numerical simulation based CFD (Computational Fluid Dynamics) technology has its own advantage on studying airflow structure in human upper respiratory tract. In this paper, a representative human upper respiratory tract is built and the CFD technology was used to investigate the air movement characteristic in the human upper respiratory tract. The airflow movement characteristic, the effect of the airflow movement on the shear stress distribution and the probability of the wall injury caused by the shear stress are discussed. Experimentally validated computational fluid-aerosol dynamics results showed the following: the phenomenon of airflow separation appears near the outer wall of the pharynx and the trachea. The high velocity zone is created near the inner wall of the trachea. The airflow splits at the divider and a new boundary layer is generated at the inner wall of the downstream from the bifurcation with the high velocity near the inner wall of the trachea. The maximum velocity appears at the exterior of the boundary layer. The secondary swirls and axial velocity distribution result in the high shear stress acting on the inner wall of the trachea and bifurcation, finally lead to the inner wall injury. The enhancement of breathing intensity enhances the intensity of the shear stress acting on the inner wall of the trachea and the bifurcation. If human keep the high breathing intensity for long time, not only the ability for the transportation and regulation of the gas through the trachea and the bifurcation fall, but also result in the increase of the probability of the wall strain and tissue injury.

Keywords: airflow structure, computational fluid dynamics, human upper respiratory tract, wall shear stress, numerical simulation

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504 Algorithm for Quantification of Pulmonary Fibrosis in Chest X-Ray Exams

Authors: Marcela de Oliveira, Guilherme Giacomini, Allan Felipe Fattori Alves, Ana Luiza Menegatti Pavan, Maria Eugenia Dela Rosa, Fernando Antonio Bacchim Neto, Diana Rodrigues de Pina

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It is estimated that each year one death every 10 seconds (about 2 million deaths) in the world is attributed to tuberculosis (TB). Even after effective treatment, TB leaves sequelae such as, for example, pulmonary fibrosis, compromising the quality of life of patients. Evaluations of the aforementioned sequel are usually performed subjectively by radiology specialists. Subjective evaluation may indicate variations inter and intra observers. The examination of x-rays is the diagnostic imaging method most accomplished in the monitoring of patients diagnosed with TB and of least cost to the institution. The application of computational algorithms is of utmost importance to make a more objective quantification of pulmonary impairment in individuals with tuberculosis. The purpose of this research is the use of computer algorithms to quantify the pulmonary impairment pre and post-treatment of patients with pulmonary TB. The x-ray images of 10 patients with TB diagnosis confirmed by examination of sputum smears were studied. Initially the segmentation of the total lung area was performed (posteroanterior and lateral views) then targeted to the compromised region by pulmonary sequel. Through morphological operators and the application of signal noise tool, it was possible to determine the compromised lung volume. The largest difference found pre- and post-treatment was 85.85% and the smallest was 54.08%.

Keywords: algorithm, radiology, tuberculosis, x-rays exam

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503 Indirect Genotoxicity of Diesel Engine Emission: An in vivo Study Under Controlled Conditions

Authors: Y. Landkocz, P. Gosset, A. Héliot, C. Corbière, C. Vendeville, V. Keravec, S. Billet, A. Verdin, C. Monteil, D. Préterre, J-P. Morin, F. Sichel, T. Douki, P. J. Martin

Abstract:

Air Pollution produced by automobile traffic is one of the main sources of pollutants in urban atmosphere and is largely due to exhausts of the diesel engine powered vehicles. The International Agency for Research on Cancer, which is part of the World Health Organization, classified in 2012 diesel engine exhaust as carcinogenic to humans (Group 1), based on sufficient evidence that exposure is associated with an increased risk for lung cancer. Amongst the strategies aimed at limiting exhausts in order to take into consideration the health impact of automobile pollution, filtration of the emissions and use of biofuels are developed, but their toxicological impact is largely unknown. Diesel exhausts are indeed complex mixtures of toxic substances difficult to study from a toxicological point of view, due to both the necessary characterization of the pollutants, sampling difficulties, potential synergy between the compounds and the wide variety of biological effects. Here, we studied the potential indirect genotoxicity of emission of Diesel engines through on-line exposure of rats in inhalation chambers to a subchronic high but realistic dose. Following exposure to standard gasoil +/- rapeseed methyl ester either upstream or downstream of a particle filter or control treatment, rats have been sacrificed and their lungs collected. The following indirect genotoxic parameters have been measured: (i) telomerase activity and telomeres length associated with rTERT and rTERC gene expression by RT-qPCR on frozen lungs, (ii) γH2AX quantification, representing double-strand DNA breaks, by immunohistochemistry on formalin fixed-paraffin embedded (FFPE) lung samples. These preliminary results will be then associated with global cellular response analyzed by pan-genomic microarrays, monitoring of oxidative stress and the quantification of primary DNA lesions in order to identify biological markers associated with a potential pro-carcinogenic response of diesel or biodiesel, with or without filters, in a relevant system of in vivo exposition.

Keywords: diesel exhaust exposed rats, γH2AX, indirect genotoxicity, lung carcinogenicity, telomerase activity, telomeres length

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502 The Outcome of Using Machine Learning in Medical Imaging

Authors: Adel Edwar Waheeb Louka

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Purpose AI-driven solutions are at the forefront of many pathology and medical imaging methods. Using algorithms designed to better the experience of medical professionals within their respective fields, the efficiency and accuracy of diagnosis can improve. In particular, X-rays are a fast and relatively inexpensive test that can diagnose diseases. In recent years, X-rays have not been widely used to detect and diagnose COVID-19. The under use of Xrays is mainly due to the low diagnostic accuracy and confounding with pneumonia, another respiratory disease. However, research in this field has expressed a possibility that artificial neural networks can successfully diagnose COVID-19 with high accuracy. Models and Data The dataset used is the COVID-19 Radiography Database. This dataset includes images and masks of chest X-rays under the labels of COVID-19, normal, and pneumonia. The classification model developed uses an autoencoder and a pre-trained convolutional neural network (DenseNet201) to provide transfer learning to the model. The model then uses a deep neural network to finalize the feature extraction and predict the diagnosis for the input image. This model was trained on 4035 images and validated on 807 separate images from the ones used for training. The images used to train the classification model include an important feature: the pictures are cropped beforehand to eliminate distractions when training the model. The image segmentation model uses an improved U-Net architecture. This model is used to extract the lung mask from the chest X-ray image. The model is trained on 8577 images and validated on a validation split of 20%. These models are calculated using the external dataset for validation. The models’ accuracy, precision, recall, f1-score, IOU, and loss are calculated. Results The classification model achieved an accuracy of 97.65% and a loss of 0.1234 when differentiating COVID19-infected, pneumonia-infected, and normal lung X-rays. The segmentation model achieved an accuracy of 97.31% and an IOU of 0.928. Conclusion The models proposed can detect COVID-19, pneumonia, and normal lungs with high accuracy and derive the lung mask from a chest X-ray with similarly high accuracy. The hope is for these models to elevate the experience of medical professionals and provide insight into the future of the methods used.

Keywords: artificial intelligence, convolutional neural networks, deeplearning, image processing, machine learningSarapin, intraarticular, chronic knee pain, osteoarthritisFNS, trauma, hip, neck femur fracture, minimally invasive surgery

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501 An Experimental Study on the Influence of Brain-Break in the Classroom on the Physical Health and Academic Performance of Fourth Grade Students

Authors: Qian Mao, Xiaozan Wang, Jiarong Zhong, Xiaolin Zou

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Introduction: As a result of the decline of students' physical health level and the increase of study pressure, students’ academic performance is not so good. Objective: This study aims to verify whether the Brain-Break intervention in the fourth-grade classroom of primary school can improve students' physical health and academic performance. Methods: According to the principle of no difference in pre-test data, students from two classes of grade four in Fuhai Road Primary School, Fushan district, Yantai city, Shandong province, were selected as experimental subjects, including 50 students in the experimental class (25 males and 25 females) and 50 students in the control class (24 males and 26 females). The content of the experiment was that the students were asked to perform a 4-minute Brain-Berak program designed by the researcher in the second class in the morning and the afternoon, and the intervention lasted for 12 weeks. In addition, the lung capacity, 50-meter run, sitting body forward bend, one-minute jumping rope and one-minute sit-ups stipulated in the national standards for physical fitness of students (revised in 2014) were selected as the indicators of physical health. The scores of Chinese, Mathematics, and English in the unified academic test of the municipal education bureau were selected as the indicators of academic performance. The independent-sample t-test was used to compare and analyze the data of each index between the two classes. The paired-sample t-test was used to compare and analyze the data of each index in the two classes. This paper presents only results with significant differences. Results: in terms of physical health, lung capacity (P=0.002, T= -2.254), one-minute rope skipping (P=0.000, T=3.043), and one-minute sit-ups (P=0.045, T=6.153) were significantly different between the experimental class and the control class. In terms of academic performance, there is a significant difference between the Chinese performance of the experimental class and the control class (P=0.009, T=4.833). Conclusion: Adding Brain-Berak intervention in the classroom can effectively improve the cardiorespiratory endurance (lung capacity), coordination (jumping rope), and abdominal strength (sit-ups) of fourth-grade students. At the same time, it can also effectively improve their Chinese performance. Therefore, it is suggested to promote micro-sports in the classroom of primary schools throughout the country so as to help students improve their physical health and academic performance.

Keywords: academic performance, brain break, fourth grade, physical health

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500 Oral Microbiota as a Novel Predictive Biomarker of Response To Immune Checkpoint Inhibitors in Advanced Non-small Cell Lung Cancer Patients

Authors: Francesco Pantano, Marta Fogolari, Michele Iuliani, Sonia Simonetti, Silvia Cavaliere, Marco Russano, Fabrizio Citarella, Bruno Vincenzi, Silvia Angeletti, Giuseppe Tonini

Abstract:

Background: Although immune checkpoint inhibitors (ICIs) have changed the treatment paradigm of non–small cell lung cancer (NSCLC), these drugs fail to elicit durable responses in the majority of NSCLC patients. The gut microbiota, able to regulate immune responsiveness, is emerging as a promising, modifiable target to improve ICIs response rates. Since the oral microbiome has been demonstrated to be the primary source of bacterial microbiota in the lungs, we investigated its composition as a potential predictive biomarker to identify and select patients who could benefit from immunotherapy. Methods: Thirty-five patients with stage IV squamous and non-squamous cell NSCLC eligible for an anti-PD-1/PD-L1 as monotherapy were enrolled. Saliva samples were collected from patients prior to the start of treatment, bacterial DNA was extracted using the QIAamp® DNA Microbiome Kit (QIAGEN) and the 16S rRNA gene was sequenced on a MiSeq sequencing instrument (Illumina). Results: NSCLC patients were dichotomized as “Responders” (partial or complete response) and “Non-Responders” (progressive disease), after 12 weeks of treatment, based on RECIST criteria. A prevalence of the phylum Candidatus Saccharibacteria was found in the 10 responders compared to non-responders (abundance 5% vs 1% respectively; p-value = 1.46 x 10-7; False Discovery Rate (FDR) = 1.02 x 10-6). Moreover, a higher prevalence of Saccharibacteria Genera Incertae Sedis genus (belonging to the Candidatus Saccharibacteria phylum) was observed in "responders" (p-value = 6.01 x 10-7 and FDR = 2.46 x 10-5). Finally, the patients who benefit from immunotherapy showed a significant abundance of TM7 Phylum Sp Oral Clone FR058 strain, member of Saccharibacteria Genera Incertae Sedis genus (p-value = 6.13 x 10-7 and FDR=7.66 x 10-5). Conclusions: These preliminary results showed a significant association between oral microbiota and ICIs response in NSCLC patients. In particular, the higher prevalence of Candidatus Saccharibacteria phylum and TM7 Phylum Sp Oral Clone FR058 strain in responders suggests their potential immunomodulatory role. The study is still ongoing and updated data will be presented at the congress.

Keywords: oral microbiota, immune checkpoint inhibitors, non-small cell lung cancer, predictive biomarker

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499 Extra Skeletal Manifestations of Histocytosis in Pediatrics

Authors: Ayda Youssef, Mohammed Ali Khalaf, Tarek Rafaat

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Background: Langerhans cell histiocytosis (LCH) is a rare multi-systemic disease that shows an abnormal proliferation of these kinds of cells associated with a granular infiltration that affects different structures of the human body, including the lung, liver, spleen, lymph nodes, brain, mucocutaneous, soft tissue (head and neck), and salivary glands. Evaluation of the extent of disease is one of the major predictors of patient outcome. Objectives: To recognize the pathogenesis of Langerhans cell histiocytosis (LCH), describe the radiologic criteria that are suggestive of LCH in different organs rather than the bones and to illustrate the appropriate differential diagnoses for LCH in each of the common extra-osseous sites. Material and methods: A retrospective study was done on 150 biopsy-proven LCH patients from 2007 to 2012. All patients underwent imaging studies, mostly US, CT, and MRI. These patients were reviewed to assess the extra-skeletal manifestations of LCH. Results: In 150 patients with biopsy-proven LCH, There were 33 patients with liver affection, 5 patients with splenic lesions, 55 patients with enlarged lymph nodes, 9 patient with CNS disease and 11 patients with lung involvement. Conclusions: Because of the frequent LCH children and evaluation of the extent of disease is one of the major predictors of patient outcome. Radiologist need to be familiar with its presentation in different organs and regions of body outside the commonest site of affection (bones). A high-index suspicion should be raised a biopsy is recommended in the presence of radiological suspicion. Chemotherapy is the preferred therapeutic modality.

Keywords: langerhans cell histiocytosis, extra-skeletal, pediatrics, radiology

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498 Effect of Crown Gall and Phylloxera Resistant Rootstocks on Grafted Vitis Vinifera CV. Sultana Grapevine

Authors: Hassan Mahmoudzadeh

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The bacterium of Agrobacterium vitis causes crown and root gall disease, an important disease of grapevine, Vitis vinifera L. Also, Phylloxera is one of the most important pests in viticulture. Grapevine rootstocks were developed to provide increased resistance to soil-borne pests and diseases, but rootstock effects on some traits remain unclear. The interaction between rootstock, scion and environment can induce different responses to the grapevine physiology. 'Sultsna' (Vitis vinifera L.) is one of the most valuable raisin grape cultivars in Iran. Thus, the aim of this study was to determine the rootstock effect on the growth characteristics and yield components and quality of 'Sultana' grapevine grown in the Urmia viticulture region. The experimental design was completely randomized blocks, with four treatments, four replicates and 10 vines per plot. The results show that all variables evaluated were significantly affected by the rootstock. The Sultana/110R and Sultana/Nazmieh were among other combinations influenced by the year and had a higher significant yield/vine (13.25 and 12.14, respectively). Indeed, they were higher than that of Sultana/5BB (10.56 kg/vine) and Sultana/Spota (10.25 kg/vine). The number of clusters per burst bud and per vine and the weight of clusters were affected by the rootstock as well. Pruning weight/vine, yield/pruning weight, leaf area/vine and leaf area index are variables related to the physiology of grapevine, which was also affected by the rootstocks. In general, rootstocks had adapted well to the environment where the experiment was carried out, giving vigor and high yield to Sultana grapevine, which means that they may be used by grape growers in this region. In sum, the study found the best rootstocks for 'Sultana' to be Nazmieh and 110R in terms of root and shoot growth. However, the choice of the right rootstock depends on various aspects, such as those related to soil characteristics, climate conditions, grape varieties, and even clones, and production purposes.

Keywords: grafting, vineyards, grapevine, succeptability

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497 Deep Learning in Chest Computed Tomography to Differentiate COVID-19 from Influenza

Authors: Hongmei Wang, Ziyun Xiang, Ying liu, Li Yu, Dongsheng Yue

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Intro: The COVID-19 (Corona Virus Disease 2019) has greatly changed the global economic, political and financial ecology. The mutation of the coronavirus in the UK in December 2020 has brought new panic to the world. Deep learning was performed on Chest Computed tomography (CT) of COVID-19 and Influenza and describes their characteristics. The predominant features of COVID-19 pneumonia was ground-glass opacification, followed by consolidation. Lesion density: most lesions appear as ground-glass shadows, and some lesions coexist with solid lesions. Lesion distribution: the focus is mainly on the dorsal side of the periphery of the lung, with the lower lobe of the lungs as the focus, and it is often close to the pleura. Other features it has are grid-like shadows in ground glass lesions, thickening signs of diseased vessels, air bronchi signs and halo signs. The severe disease involves whole bilateral lungs, showing white lung signs, air bronchograms can be seen, and there can be a small amount of pleural effusion in the bilateral chest cavity. At the same time, this year's flu season could be near its peak after surging throughout the United States for months. Chest CT for Influenza infection is characterized by focal ground glass shadows in the lungs, with or without patchy consolidation, and bronchiole air bronchograms are visible in the concentration. There are patchy ground-glass shadows, consolidation, air bronchus signs, mosaic lung perfusion, etc. The lesions are mostly fused, which is prominent near the hilar and two lungs. Grid-like shadows and small patchy ground-glass shadows are visible. Deep neural networks have great potential in image analysis and diagnosis that traditional machine learning algorithms do not. Method: Aiming at the two major infectious diseases COVID-19 and influenza, which are currently circulating in the world, the chest CT of patients with two infectious diseases is classified and diagnosed using deep learning algorithms. The residual network is proposed to solve the problem of network degradation when there are too many hidden layers in a deep neural network (DNN). The proposed deep residual system (ResNet) is a milestone in the history of the Convolutional neural network (CNN) images, which solves the problem of difficult training of deep CNN models. Many visual tasks can get excellent results through fine-tuning ResNet. The pre-trained convolutional neural network ResNet is introduced as a feature extractor, eliminating the need to design complex models and time-consuming training. Fastai is based on Pytorch, packaging best practices for in-depth learning strategies, and finding the best way to handle diagnoses issues. Based on the one-cycle approach of the Fastai algorithm, the classification diagnosis of lung CT for two infectious diseases is realized, and a higher recognition rate is obtained. Results: A deep learning model was developed to efficiently identify the differences between COVID-19 and influenza using chest CT.

Keywords: COVID-19, Fastai, influenza, transfer network

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496 Harnessing Nature's Fury: Hyptis Suaveolens Loaded Bioactive Liposome for Photothermal Therapy of Lung Cancer

Authors: Sajmina Khatun, Monika Pebam, Aravind Kumar Rengan

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Photothermal therapy, a subset of nanomedicine, takes advantage of light-absorbing agents to generate localized heat, selectively eradicating cancer cells. This innovative approach minimizes damage to healthy tissues and offers a promising avenue for targeted cancer treatment. Unlike conventional therapies, photothermal therapy harnesses the power of light to combat malignancies precisely and effectively, showcasing its potential to revolutionize cancer treatment paradigms. The combined strengths of nanomedicine and photothermal therapy signify a transformative shift toward more effective, targeted, and tolerable cancer treatments in the medical landscape. Utilizing natural products becomes instrumental in formulating diverse bioactive medications owing to their various pharmacological properties attributed to the existence of phenolic structures, triterpenoids, and similar compounds. Hyptis suaveolens, commonly known as pignut, stands as an aromatic herb within the Lamiaceae family and represents a valuable therapeutic plant. Flourishing in swamps and alongside tropical and subtropical roadsides, these noxious weeds impede the development of adjacent plants. Hyptis suaveolens ranks among the most globally distributed alien invasive species. The present investigation revealed that a versatile, biodegradable liposome nanosystem (HIL NPs), incorporating bioactive molecules from Hyptis suaveolens, exhibits effective bioavailability to cancer cells, enabling tumor ablation upon near-infrared (NIR) laser exposure. The components within the nanosystem, specifically the bioactive molecules from Hyptis, function as anticancer agents, aiding in the photothermal ablation of highly metastatic lung cancer cells. Despite being a prolific weed impeding neighboring plant growth, Hyptis suaveolens showcases therapeutic benefits through its bioactive compounds. The obtained HIL NPs, characterized as a photothermally active liposome nanosystem, demonstrate a pronounced fluorescence absorption peak in the NIR range and achieve a high photothermal conversion efficiency under NIR laser irradiation. Transmission electron microscopy (TEM) and particle size analysis reveal that HIL NPs possess a spherical shape with a size of 141 ± 30 nm. Moreover, in vitro assessments of HIL NPs against lung cancer cell lines (A549) indicate effective anticancer activity through a combined cytotoxic effect and hyperthermia. Tumor ablation is facilitated by apoptosis induced by the overexpression of ɣ-H2AX, arresting cancer cell proliferation. Consequently, the multifunctional and biodegradable nanosystem (HIL NPs), incorporating bioactive compounds from Hyptis, provides valuable perspectives for developing an innovative therapeutic strategy originating from a challenging weed. This approach holds promise for potential applications in both bioimaging and the combined use of phyto-photothermal therapy for cancer treatment.

Keywords: bioactive liposome, hyptis suaveolens, photothermal therapy, lung cancer

Procedia PDF Downloads 54
495 Anti-tuberculosis, Resistance Modulatory, Anti-pulmonary Fibrosis and Anti-silicosis Effects of Crinum Asiaticum Bulbs and Its Active Metabolite, Betulin

Authors: Theophilus Asante, Comfort Nyarko, Daniel Antwi

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Drug-resistant tuberculosis, together with the associated comorbidities like pulmonary fibrosis and silicosis, has been one of the most serious global public health threats that requires immediate action to curb or mitigate it. This prolongs hospital stays, increases the cost of medication, and increases the death toll recorded annually. Crinum asiaticum bulb (CAE) and betulin (BET) are known for their biological and pharmacological effects. Pharmacological effects reported on CAE include antimicrobial, anti-inflammatory, anti-pyretic, anti-analgesic, and anti-cancer effects. Betulin has exhibited a multitude of powerful pharmacological properties ranging from antitumor, anti-inflammatory, anti-parasitic, anti-microbial, and anti-viral activities. This work sought to investigate the anti-tuberculosis and resistant modulatory effects and also assess their effects on mitigating pulmonary fibrosis and silicosis. In the anti-tuberculosis and resistant modulatory effects, both CAE and BET showed strong antimicrobial activities (31.25 ≤ MIC ≤ 500) µg/ml against the studied microorganisms and also produced significant anti-efflux pump and biofilm inhibitory effects (ρ < 0.0001) as well as exhibiting resistance modulatory and synergistic effects when combined with standard antibiotics. Crinum asiaticum bulbs extract and betulin were shown to possess anti-pulmonary fibrosis effects. There was an increased survival rate in the CAE and BET treatment groups compared to the BLM-induced group. There was a marked decrease in the levels of hydroxyproline and collagen I and III in the CAE and BET treatment groups compared to the BLM-treated group. The treatment groups of CAE and BET significantly downregulated the levels of pro-fibrotic and pro-inflammatory cytokine concentrations such as TGF-β1, MMP9, IL-6, IL-1β and TNF-alpha compared to an increase in the BLM-treated groups. The histological findings of the lungs suggested the curative effects of CAE and BET following BLM-induced pulmonary fibrosis in mice. The study showed improved lung functions with a wide focal area of viable alveolar spaces and few collagen fibers deposition on the lungs of the treatment groups. In the anti-silicosis and pulmonoprotective effects of CAE and BET, the levels of NF-κB, TNF-α, IL-1β, IL-6 and hydroxyproline, collagen types I and III were significantly reduced by CAE and BET (ρ < 0.0001). Both CAE and BET significantly (ρ < 0.0001) inhibited the levels of hydroxyproline, collagen I and III when compared with the negative control group. On BALF biomarkers such as macrophages, lymphocytes, monocytes, and neutrophils, CAE and BET were able to reduce their levels significantly (ρ < 0.0001). The CAE and BET were examined for anti-oxidant activity and shown to raise the levels of catalase (CAT) and superoxide dismutase (SOD) while lowering the level of malondialdehyde (MDA). There was an improvement in lung function when lung tissues were examined histologically. Crinum asiaticum bulbs extract and betulin were discovered to exhibit anti-tubercular and resistance-modulatory properties, as well as the capacity to minimize TB comorbidities such as pulmonary fibrosis and silicosis. In addition, CAE and BET may act as protective mechanisms, facilitating the preservation of the lung's physiological integrity. The outcomes of this study might pave the way for the development of leads for producing single medications for the management of drug-resistant tuberculosis and its accompanying comorbidities.

Keywords: fibrosis, crinum, tuberculosis, antiinflammation, drug resistant

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494 MAGE-A3 and PRAME Gene Expression and EGFR Mutation Status in Non-Small-Cell Lung Cancer

Authors: Renata Checiches, Thierry Coche, Nicolas F. Delahaye, Albert Linder, Fernando Ulloa Montoya, Olivier Gruselle, Karen Langfeld, An de Creus, Bart Spiessens, Vincent G. Brichard, Jamila Louahed, Frédéric F. Lehmann

Abstract:

Background: The RNA-expression levels of cancer-testis antigens MAGE A3 and PRAME were determined in resected tissue from patients with primary non-small-cell lung cancer (NSCLC) and related to clinical outcome. EGFR, KRAS and BRAF mutation status was determined in a subset to investigate associations with MAGE A3 and PRAME expression. Methods: We conducted a single-centre, uncontrolled, retrospective study of 1260 tissue-bank samples from stage IA-III resected NSCLC. The prognostic value of antigen expression (qRT-PCR) was determined by hazard-ratio and Kaplan-Meier curves. Results: Thirty-seven percent (314/844) of tumours expressed MAGE-A3, 66% (723/1092) expressed PRAME and 31% (239/839) expressed both. Respective frequencies in squamous-cell tumours and adenocarcinomas were 43%/30% for MAGE A3 and 80%/44% for PRAME. No correlation with stage, tumour size or patient age was found. Overall, no prognostic value was identified for either antigen. A trend to poorer overall survival was associated with MAGE-A3 in stage IIIB and with PRAME in stage IB. EGFR and KRAS mutations were found in 10.1% (28/311) and 33.8% (97/311) of tumours, respectively. EGFR (but not KRAS) mutation status was negatively associated with PRAME expression. Conclusion: No clear prognostic value for either PRAME or MAGE A3 was observed in the overall population, although some observed trends may warrant further investigation.

Keywords: MAGE A3, PRAME, cancer-testis gene, NSCLC, survival, EGFR

Procedia PDF Downloads 351
493 COVID-19 Detection from Computed Tomography Images Using UNet Segmentation, Region Extraction, and Classification Pipeline

Authors: Kenan Morani, Esra Kaya Ayana

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This study aimed to develop a novel pipeline for COVID-19 detection using a large and rigorously annotated database of computed tomography (CT) images. The pipeline consists of UNet-based segmentation, lung extraction, and a classification part, with the addition of optional slice removal techniques following the segmentation part. In this work, a batch normalization was added to the original UNet model to produce lighter and better localization, which is then utilized to build a full pipeline for COVID-19 diagnosis. To evaluate the effectiveness of the proposed pipeline, various segmentation methods were compared in terms of their performance and complexity. The proposed segmentation method with batch normalization outperformed traditional methods and other alternatives, resulting in a higher dice score on a publicly available dataset. Moreover, at the slice level, the proposed pipeline demonstrated high validation accuracy, indicating the efficiency of predicting 2D slices. At the patient level, the full approach exhibited higher validation accuracy and macro F1 score compared to other alternatives, surpassing the baseline. The classification component of the proposed pipeline utilizes a convolutional neural network (CNN) to make final diagnosis decisions. The COV19-CT-DB dataset, which contains a large number of CT scans with various types of slices and rigorously annotated for COVID-19 detection, was utilized for classification. The proposed pipeline outperformed many other alternatives on the dataset.

Keywords: classification, computed tomography, lung extraction, macro F1 score, UNet segmentation

Procedia PDF Downloads 100
492 A Comparative Time-Series Analysis and Deep Learning Projection of Innate Radon Gas Risk in Canadian and Swedish Residential Buildings

Authors: Selim M. Khan, Dustin D. Pearson, Tryggve Rönnqvist, Markus E. Nielsen, Joshua M. Taron, Aaron A. Goodarzi

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Accumulation of radioactive radon gas in indoor air poses a serious risk to human health by increasing the lifetime risk of lung cancer and is classified by IARC as a category one carcinogen. Radon exposure risks are a function of geologic, geographic, design, and human behavioural variables and can change over time. Using time series and deep machine learning modelling, we analyzed long-term radon test outcomes as a function of building metrics from 25,489 Canadian and 38,596 Swedish residential properties constructed between 1945 to 2020. While Canadian and Swedish properties built between 1970 and 1980 are comparable (96–103 Bq/m³), innate radon risks subsequently diverge, rising in Canada and falling in Sweden such that 21st Century Canadian houses show 467% greater average radon (131 Bq/m³) relative to Swedish equivalents (28 Bq/m³). These trends are consistent across housing types and regions within each country. The introduction of energy efficiency measures within Canadian and Swedish building codes coincided with opposing radon level trajectories in each nation. Deep machine learning modelling predicts that, without intervention, average Canadian residential radon levels will increase to 176 Bq/m³ by 2050, emphasizing the importance and urgency of future building code intervention to achieve systemic radon reduction in Canada.

Keywords: radon health risk, time-series, deep machine learning, lung cancer, Canada, Sweden

Procedia PDF Downloads 53
491 Ex-vivo Bio-distribution Studies of a Potential Lung Perfusion Agent

Authors: Shabnam Sarwar, Franck Lacoeuille, Nadia Withofs, Roland Hustinx

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After the development of a potential surrogate of MAA, and its successful application for the diagnosis of pulmonary embolism in artificially embolized rats’ lungs, this microparticulate system were radiolabelled with gallium-68 to synthesize 68Ga-SBMP with high radiochemical purity >99%. As a prerequisite step of clinical trials, 68Ga- labelled starch based microparticles (SBMP) were analysed for their in-vivo behavior in small animals. The purpose of the presented work includes the ex-vivo biodistribution studies of 68Ga-SBMP in order to assess the activity uptake in target organs with respect to time, excretion pathways of the radiopharmaceutical, %ID/g in major organs, T/NT ratios, in-vivo stability of the radiotracer and subsequently the microparticles in the target organs. Radiolabelling of starch based microparticles was performed by incubating it with 68Ga generator eluate (430±26 MBq) at room temperature and pressure without using any harsh reaction condition. For Ex-vivo biodistribution studies healthy White Wistar rats weighing between 345-460 g were injected intravenously 68Ga-SBMP 20±8 MBq, containing about 2,00,000-6,00,000 SBMP particles in a volume of 700µL. The rats were euthanized at predefined time intervals (5min, 30min, 60min and 120min) and their organ parts were cut, washed, and put in the pre-weighed tubes and measured for radioactivity counts through automatic Gamma counter. The 68Ga-SBMP produced >99% RCP just after 10-20 min incubation through a simple and robust procedure. Biodistribution of 68Ga-SBMP showed that initially just after 5 min post injection major uptake was observed in the lungs following by blood, heart, liver, kidneys, bladder, urine, spleen, stomach, small intestine, colon, skin and skeleton, thymus and at last the smallest activity was found in brain. Radioactivity counts stayed stable in lungs with gradual decrease with the passage of time, and after 2h post injection, almost half of the activity were seen in lungs. This is a sufficient time to perform PET/CT lungs scanning in humans while activity in the liver, spleen, gut and urinary system decreased with time. The results showed that urinary system is the excretion pathways instead of hepatobiliary excretion. There was a high value of T/NT ratios which suggest fine tune images for PET/CT lung perfusion studies henceforth further pre-clinical studies and then clinical trials should be planned in order to utilize this potential lung perfusion agent.

Keywords: starch based microparticles, gallium-68, biodistribution, target organs, excretion pathways

Procedia PDF Downloads 143
490 Anticancer Lantadene Derivatives: Synthesis, Cytotoxic and Docking Studies

Authors: A. Monika, Manu Sharma, Hong Boo Lee, Richa Dhingra, Neelima Dhingra

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Nuclear factor-κappa B serve as a molecular lynchpin that links persistent infections and chronic inflammation to increased cancer risk. Inflammation has been recognized as a hallmark and cause of cancer. Natural products present a privileged source of inspiration for chemical probe and drug design. Herbal remedies were the first medicines used by humans due to the many pharmacologically active secondary metabolites produced by plants. Some of the metabolites like Lantadene (pentacyclic triterpenoids) from the weed Lantana camara has been known to inhibit cell division and showed anti-antitumor potential. The C-3 aromatic esters of lantadenes were synthesized, characterized and evaluated for cytotoxicity and inhibitory potential against Tumor necrosis factor alpha-induced activation of Nuclear factor-κappa B in lung cancer cell line A549. The 3-methoxybenzoyloxy substituted lead analogue inhibited kinase activity of the inhibitor of nuclear factor-kappa B kinase in a single-digit micromolar concentration. At the same time, the lead compound showed promising cytotoxicity against A549 lung cancer cells with IC50 ( half maximal inhibitory concentration) of 0.98l µM. Further, molecular docking of 3-methoxybenzoyloxy substituted analogue against Inhibitor of nuclear factor-kappa B kinase (Protein data bank ID: 3QA8) showed hydrogen bonding interaction involving oxygen atom of 3-methoxybenzoyloxy with the Arginine-31 and Glutamine-110. Encouraging results indicate the Lantadene’s potential to be developed as anticancer agents.

Keywords: anticancer, lantadenes, pentacyclic triterpenoids, weed

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489 Smart Oxygen Deprivation Mask: An Improved Design with Biometric Feedback

Authors: Kevin V. Bui, Richard A. Claytor, Elizabeth M. Priolo, Weihui Li

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Oxygen deprivation masks operate through the use of restricting valves as a means to reduce respiratory flow where flow is inversely proportional to the resistance applied. This produces the same effect as higher altitudes where lower pressure leads to reduced respiratory flow. Both increased resistance with restricting valves and reduce the pressure of higher altitudes make breathing difficultier and force breathing muscles (diaphragm and intercostal muscles) working harder. The process exercises these muscles, improves their strength and results in overall better breathing efficiency. Currently, these oxygen deprivation masks are purely mechanical devices without any electronic sensor to monitor the breathing condition, thus not be able to provide feedback on the breathing effort nor to evaluate the lung function. That is part of the reason that these masks are mainly used for high-level athletes to mimic training in higher altitude conditions, not suitable for patients or customers. The design aims to improve the current method of oxygen deprivation mask to include a larger scope of patients and customers while providing quantitative biometric data that the current design lacks. This will be accomplished by integrating sensors into the mask’s breathing valves along with data acquisition and Bluetooth modules for signal processing and transmission. Early stages of the sensor mask will measure breathing rate as a function of changing the air pressure in the mask, with later iterations providing feedback on flow rate. Data regarding breathing rate will be prudent in determining whether training or therapy is improving breathing function and quantify this improvement.

Keywords: oxygen deprivation mask, lung function, spirometer, Bluetooth

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488 Metastatic Esophageal Squamous Cell Carcinoma Presenting with COVID-19 Infection and Cardiac Tamponade

Authors: Sutinon Yuchomsuk, Satchachon Changthom, Pruet Areesawangvong, Monsiri Jinapen

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Background: Esophageal squamous cell carcinoma can be presented with many symptoms, such as dysphagia or weight loss. However, in some circumstances, rare presentations can be found, e.g., dyspnea, which is more common in pulmonary malignancy. And dyspnea is also one of the most common presentations of COVID-19 infection. So, in this case, we can learn from many points in patient symptoms and findings leading to the diagnosis of esophageal squamous cell carcinoma. Method: This research is a case-report study including one patient from Mahasarakham Hospital, Thailand. Data were collected during December 2021. Result: A 55-year-old Thai male patient with an unknown past medical history presented with dyspnea and shortness of breath for the duration of three days prior to admission. His symptom also included cough, fever, and sore throat. Laboratory results indicated that the patient had COVID-19 pneumonia. Further investigation showed that he had cardiac tamponade and suspected pulmonary/esophageal cancer. Lung biopsy and pericardiocentesis were done, which were positive for carcinoma from pericardial effusion but negative for malignancy from the lung biopsy. Later esophagogastroduodenoscopy was done with endoscopic tissue biopsy; the result was positive for squamous cell carcinoma of the esophagus. Conclusion: Most commonly, esophageal cancer is presented with dysphagia or weight loss. However, in some rare cases, patients can also be presented with dyspnea due to cardiac tamponade. And in recent years, COVID-19 has become a pandemic all over the world, sometimes masking symptoms of other diseases. Such as in this case, the patient didn’t improve after the pneumonia was resolved, which led to the final diagnosis of metastatic esophageal cancer.

Keywords: esophageal cancer, cardiac tamponade, metastatic squamous cell carcinoma, COVID-19 infection

Procedia PDF Downloads 93