Search results for: artificial lung

Authors: Chiara Colarusso, Michela Terlizzi, Aldo Pinto, Rosalinda Sorrentino

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Cigarette smoking is the main cause and the most common risk factor for both COPD and lung cancer. In our previous studies, we proved that caspase-11 in mice and its human analogue, caspase-4, are involved in lung carcinogenesis and that AIM2 inflammasome might play a pro-cancerous role in lung cancer. Therefore, the aim of this study was to investigate potential crosstalk between COPD and lung cancer, focusing on AIM2 and caspase-11-dependent inflammasome signaling pathway. To mimic COPD, we took advantage of an experimental first-hand smoking mouse model and, to confirm what was observed in mice, we used human samples of lung adenocarcinoma patients stratified according to the smoking and COPD status. We demonstrated that smoke exposure led to emphysema-like features, bronchial tone impairment, and release of IL-1-like cytokines (IL-1α, IL-1β, IL-33, IL-18) in a caspase-1 independent manner in C57Bl/6N. Rather, a dysfunctional caspase-11 in smoke-exposed 129Sv mice was associated to lower bronchial inflammation, collagen deposition, and IL-1-like inflammation. In addition, for the first time, we found that AIM2 inflammasome is involved in lung inflammation in smoking and COPD, in that its expression was higher in smoke-exposed C57Bl/6N compared to 129Sv smoking mice, who instead did not show any alteration of AIM2 in both macrophages and dendritic cells. Moreover, we found that AIM2 expression in the cancerous tissue, albeit higher than non-cancerous tissue, was not statistically different according to the COPD and smoking status. Instead, the higher expression of AIM2 in non-cancerous tissue of smoker COPD patients than smokers who did not have COPD was correlated to a higher hazard ratio of poor survival rate than patients who presented lower levels of AIM2. In conclusion, our data highlight that caspase-11 in mice is associated to smoke-induced lung latent inflammation which could drive the establishment of lung cancer, and that AIM2 inflammasome plays a role at the crosstalk between smoking/COPD and lung adenocarcinoma in that its higher presence is correlated to lower survival rate of smoker COPD adenocarcinoma.

Keywords: COPD, inflammasome, lung cancer, lung inflammation, smoke

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Authors: Sonal Sethi, Mukesh Yadav, Abhimanyu Gupta

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The upcoming field of radiogenomics has the potential to upgrade the role of imaging in lung cancer management by noninvasive characterization of tumor histology and genetic microenvironment. Receptor positivity like epidermal growth factor receptor (EGFR) and anaplastic lymphoma kinase (ALK) genotyping are critical in lung adenocarcinoma for treatment. As conventional identification of receptor positivity is an invasive procedure, we analyzed the features on non-invasive computed tomography (CT), which predicts the receptor positivity in lung adenocarcinoma. Retrospectively, we did a comprehensive study from 77 proven lung adenocarcinoma patients with CT images, EGFR and ALK receptor genotyping, and clinical information. Total 22/77 patients were receptor-positive (15 had only EGFR mutation, 6 had ALK mutation, and 1 had both EGFR and ALK mutation). Various morphological characteristics and metastatic distribution on CT were analyzed along with the clinical information. Univariate and multivariable logistic regression analyses were used. On multivariable logistic regression analysis, we found spiculated margin, lymphangitic spread, air bronchogram, pleural effusion, and distant metastasis had a significant predictive value for receptor mutation status. On univariate analysis, air bronchogram and pleural effusion had significant individual predictive value. Conclusions: Receptor positive lung cancer has characteristic imaging features compared with nonreceptor positive lung adenocarcinoma. Since CT is routinely used in lung cancer diagnosis, we can predict the receptor positivity by a noninvasive technique and would follow a more aggressive algorithm for evaluation of distant metastases as well as for the treatment.

Keywords: lung cancer, multidisciplinary cancer care, oncologic imaging, radiobiology

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Authors: Ammar Amsyar Abdul Haddi, Mohd Hasni Jaafar

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Heavy metals are elements naturally presented in the environment that can cause adverse effect to health. But not much literature was found on effects toward lung function, where impairment of lung function may lead to various lung diseases. The objective of the study is to explore the lung function impairment, urinary heavy metal level, and its associated factors among the community in Klang valley, Malaysia. Sampling was done in Kuala Lumpur suburb public and housing areas during community events throughout March 2019 till October 2019. respondents who gave the consent were given a questionnaire to answer and was proceeded with a lung function test. Urine samples were obtained at the end of the session and sent for Inductively coupled plasma mass spectrometry (ICP-MS) analysis for heavy metal cadmium (Cd) and lead (Pb) concentration. A total of 200 samples were analysed, and of all, 52% of respondents were male, Age ranging from 18 years old to 74 years old with a mean age of 38.44. Urinary samples show that 12% of the respondent (n=22) has Cd level above than average, and 1.5 % of the respondent (n=3) has urinary Pb at an above normal level. Bivariate analysis show that there was a positive correlation between urinary Cd and urinary Pb (r= 0.309; p<0.001). Furthermore, there was a negative correlation between urinary Cd level and full vital capacity (FVC) (r=-0.202, p=0.004), Force expiratory volume at 1 second (FEV1) (r = -0.225, p=0.001), and also with Force expiratory flow between 25-75% FVC (FEF25%-75%) (r= -0.187, p=0.008). however, urinary Pb did not show any association with FVC, FEV1, FEV1/FVC, or FEF25%-75%. Multiple linear regression analysis shows that urinary Cd remained significant and negatively affect FVC% (p=0.025) and FEV1% (p=0.004) achieved from the predicted value. On top of that, other factors such as education level (p=0.013) and duration of smoking(p=0.003) may influencing both urinary Cd and performance in lung function as well, suggesting Cd as a potential mediating factor between smoking and impairment of lung function. however, there was no interaction detected between heavy metal or other influencing factor in this study. In short, there is a negative linear relationship detected between urinary Cd and lung function, and urinary Cd is likely to affects lung function in a restrictive pattern. Since smoking is also an influencing factor for urinary Cd and lung function impairment, it is highly suggested that smokers should be screened for lung function and urinary Cd level in the future for early disease prevention.

Keywords: lung function, heavy metals, community

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Authors: Ali Chitgar

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Respiratory infections including diseases in camels are important not only because of the threat of animal health but also to reduce their production. Since that deal with respiratory problems and their treatment requires adequate knowledge of the existing respiratory problems, unfortunately, there is limited information about the species of camels. This study aimed to identify lung lesions camels slaughtered in a slaughterhouse more important was performed using histopathology. Respiratory camels (n = 477) was examined after the killing fully and tissue samples were placed in 10% formalin. The samples and histological sections using hematoxylin and eosin staining and color were evaluated. In this study 79.6 % (236 of 477 samples) of the samples was at least a lung lesion. Rate acute interstitial pneumonia, chronic interstitial pneumonia, bronchopneumonia, bronchiolitis, an inflammation of the pleura and 52.8 % respectively atelectasis (236 of 477 samples), 5.4 % (24 of 477 samples), 7.8 % (35 of 477 samples), 6.7 % (30 of 477 samples), 3.4 % (15 of 477 samples) and 15.2% (68 of 477 samples). The lung lesions, acute interstitial pneumonia and bronchopneumonia in autumn winter rather than spring and summer (p <0/05) and as a result, this study showed that high rates of lung lesions in the camel population. Waste higher results in cold seasons (fall and winter) shows.

Keywords: camel, surgery, histopathology, breathing organ

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Authors: Y. Pilehvar-Soltanahmadi, F. Badrzadeh, N. Zarghami, S. Jalilzadeh-Tabrizi, R. Zamani

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Herbal compounds such as curcumin which decrease telomerase and gene expression have been considered as beneficial tools for lung cancer treatment. In this article, we compared the effects of pure curcumin and curcumin-loaded NIPAAm-MAA nanoparticles on telomerase and PinX1 gene expression in a lung cancer cell line. A tetrazolium-based assay was used for determination of cytotoxic effects of curcumin on the Calu-6 lung cancer cell line and telomerase and pinX1 gene expression was measured with real-time PCR. MTT assay showed that Curcumin-loaded NIPAAm-MAA inhibited the growth of the Calu-6 lung cancer cell line in a time and dose-dependent manner. Our q-PCR results showed that the expression of telomerase gene was effectively reduced as the concentration of curcumin-loaded NIPAAm-MAA increased while expression of the PinX1 gene became elevated. The results showed that curcumin loaded NIPAAm-MAA exerted cytotoxic effects on the Calu-6 cell line through down-regulation of telomerase and stimulation of pinX1 gene expression. NIPPAm-MAA could be the good carrier for such kinds of hydrophobic agent.

Keywords: curcumin, NIPAAm-MAA, PinX1, telomerase, lung cancer cells

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Authors: Sultan Ayoub Meo

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Environmental pollution is a highly challenging global concern of the 21st century and is a major cause of various communicable and non-communicable diseases. We investigate the impact of air pollution on "lung function, fractional exhaled nitric oxide, and cognitive function"in a group of one hundred young students studying in a traffic-polluted school. The students wereselected based on their age, gender, height, weight, and ethnicity. After the clinical history, one hundred students were recruited from the schoolnear and away from the polluted areas. The lung and cognitive functions were recorded. The results revealed that lung and cognitive function parameters were reduced in groups of students studying in a school located in a traffic-polluted area compared to thosestudying in a schoolsituated away from the traffic-polluted area. Environmental pollution impairs students' lung and cognitive functions studying in schools located within traffic-polluted areas. The health officials and policymakers establish strategies to minimize environmental pollution and its allied health hazards. Prof. Sultan Ayoub Meo, MD, Ph.D Professor, Department of Physiology, College of Medicine, King Saud University, Saudi Arabia Email. [email protected] / [email protected]

Keywords: environmental pOllution, lung physiology, cognitive functions, air pollution

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Authors: Abdurrahim Bolukbasi, Hassan Athari, Dogan Ciloglu

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The modeling lung respiratory system which has complex anatomy and biophysics presents several challenges including tissue-driven flow patterns and wall motion. Also, the lung pulmonary system because of that they stretch and recoil with each breath, has not static walls and structures. The direct relationship between air flow and tissue motion in the lung structures naturally prefers an FSI simulation technique. Therefore, in order to toward the realistic simulation of pulmonary breathing mechanics the development of a coupled FSI computational model is an important step. A simple but physiologically-relevant three dimensional deep long geometry is designed and fluid-structure interaction (FSI) coupling technique is utilized for simulating the deformation of the lung parenchyma tissue which produces airflow fields. The real understanding of respiratory tissue system as a complex phenomenon have been investigated with respect to respiratory patterns, fluid dynamics and tissue visco-elasticity and tidal breathing period.

Keywords: lung deformation and mechanics; Tissue mechanics; Viscoelasticity; Fluid-structure interactions; ANSYS

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Authors: Jonathan Gong

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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, deep learning, image processing, machine learning

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Authors: Moumita Chanda, Md. Fazlul Karim Patwary

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Smoking is one of the most popular recreational drug use behaviors, and it contributes to birth defects, COPD, heart attacks, and erectile dysfunction. To completely eradicate this disease, it is imperative that it be identified and treated. Numerous smoking cessation programs have been created, and they demonstrate how beneficial it may be to help someone stop smoking at the ideal time. A tomography meter is an effective smoking detector. Other wearables, such as RF-based proximity sensors worn on the collar and wrist to detect when the hand is close to the mouth, have been proposed in the past, but they are not impervious to deceptive variables. In this study, we create a machine that can discriminate between smokers and non-smokers in real-time with high sensitivity and specificity by watching and collecting the human lung and analyzing the X-ray data using machine learning. If it has the highest accuracy, this machine could be utilized in a hospital, in the selection of candidates for the army or police, or in university entrance.

Keywords: CNN, smoker detection, non-smoker detection, OpenCV, artificial Intelligence, X-ray Image detection

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Authors: Selim M. Khan

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Indoor air quality is strongly influenced by the presence of radioactive radon (222Rn) gas. Indeed, exposure to high 222Rn concentrations is unequivocally linked to DNA damage and lung cancer and is a worsening issue in North American and European built environments, having increased over time within newer housing stocks as a function of as yet unclear variables. Indoor air radon concentration can be influenced by a wide range of environmental, structural, and behavioral factors. As some of these factors are quantitative while others are qualitative, no single statistical model can determine indoor radon level precisely while simultaneously considering all these variables across a complex and highly diverse dataset. The ability of AI- machine (deep) learning to simultaneously analyze multiple quantitative and qualitative features makes it suitable to predict radon with a high degree of precision. Using Canadian and Swedish long-term indoor air radon exposure data, we are using artificial deep neural network models with random weights and polynomial statistical models in MATLAB to assess and predict radon health risk to human as a function of geospatial, human behavioral, and built environmental metrics. Our initial artificial neural network with random weights model run by sigmoid activation tested different combinations of variables and showed the highest prediction accuracy (>96%) within the reasonable iterations. Here, we present details of these emerging methods and discuss strengths and weaknesses compared to the traditional artificial neural network and statistical methods commonly used to predict indoor air quality in different countries. We propose an artificial deep neural network with random weights as a highly effective method for assessing and predicting indoor radon.

Keywords: radon, radiation protection, lung cancer, aI-machine deep learnng, risk assessment, risk prediction, Europe, North America

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Authors: Vishnu Varthan Vaithiyalingam Jagannathan, Lakshmi Karunanidhi Santhanalakshmi, Srividya Ammayappan Rajam

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Formononetin is the O-Methoxy Flavonol that has many pharmacological activities, which belongs to the flavonoid family. In the current study, activity of this molecule was evaluated in lung cancer cell lines. In general, flavonoids possess certain anticancer mechanism. Being a flavonoid subfamily, this molecule was subjected to evaluate cytotoxicity assay by MTT ((3-(4,5-Dimethylthiazol-2-yl)-2,5-Diphenyltetrazolium Bromide)) stain, mode of cell death assay stained by acridine orange and ethidium bromide and Evaluation of Apoptosis pathway (extrinsic or intrinsic) by Caspase 3/7 stain and Rhodamine-123 stain. From the results, we could able to confirm that the investigatory molecule formononetin has anticancer activity and in future, the study will propose to evaluate the formononetin action against genetic changes occurs during lung cancer progression.

Keywords: Caspase 3/7, formononetin, lung cancer, Rhodamine-123

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Authors: Zixuan Zhao, Lingbin Du, Le Wang, Youqing Wang, Yi Yang, Jingjun Chen, Hengjin Dong

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Objectives: Few results from public attitudes for lung cancer screening are available both in China and abroad. This study aimed to identify preferred lung cancer screening modalities in a Chinese population and predict uptake rates of different modalities. Materials and Methods: A discrete choice experiment questionnaire was administered to 392 Chinese individuals aged 50–74 years who were at high risk for lung cancer. Each choice set had two lung screening options and an option to opt-out, and respondents were asked to choose the most preferred one. Both mixed logit analysis and stepwise logistic analysis were conducted to explore whether preferences were related to respondent characteristics and identify which kinds of respondents were more likely to opt out of any screening. Results: On mixed logit analysis, attributes that were predictive of choice at 1% level of statistical significance included the screening interval, screening venue, and out-of-pocket costs. The preferred screening modality seemed to be screening by low-dose computed tomography (LDCT) + blood test once a year in a general hospital at a cost of RMB 50; this could increase the uptake rate by 0.40 compared to the baseline setting. On stepwise logistic regression, those with no endowment insurance were more likely to opt out; those who were older and housewives/househusbands, and those with a health check habit and with commercial endowment insurance were less likely to opt out from a screening programme. Conclusions: There was considerable variance between real risk and self-perceived risk of lung cancer among respondents, and further research is required in this area. Lung cancer screening uptake can be increased by offering various screening modalities, so as to help policymakers further design the screening modality.

Keywords: lung cancer, screening, China., discrete choice experiment

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Authors: Md Abdullah Al Mashud, M. Tariquzzaman, M. Jahangir Alam, Tapan Kumar Godder, M. Mahbubur Rahman

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This paper presents a Monte Carlo (MC) method-based dose distributions on lung tumor for 6 MV photon beam to improve the dosimetric accuracy for cancer treatment. The polystyrene which is tissue equivalent material to the lung tumor density is used in this research. In the empirical calculations, TRS-398 formalism of IAEA has been used, and the setup was made according to the ICRU recommendations. The research outcomes were compared with the state-of-the-art experimental results. From the experimental results, it is observed that the proposed based approach provides more accurate results and improves the accuracy than the existing approaches. The average %variation between measured and TPS simulated values was obtained 1.337±0.531, which shows a substantial improvement comparing with the state-of-the-art technology.

Keywords: lung tumour, Monte Carlo, polystyrene, Elekta synergy, Monaco planning system

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Authors: Melliti Rihab, Zaeid Sonia, Khechine Wiem, Daldoul Amira

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Introduction: Lung cancer is the leading cause of cancer death. Its incidence is increasing, and its prognosis remains pejorative. We present the clinical, pathological, and therapeutic characteristics of bronchopulmonary cancer (BPC) in Tunisia. Methods: Retrospective study including patients followed in the oncology department of the University Hospital of Monastir between April 2014 and December 2021 suffering from lung cancer. Results: These are 117 patients, including 86.3% men and 13.7% women (sex ratio 6.3). The average age was 64 years ± 9 (37-83), with 95.7% being over 50 years old. Patients were smokers in 82% of cases. The clinical signs were dominated by chest pain (27.5%) and dyspnea in 21.1% of cases. In 6 patients, an episode of COVID-19 infection revealed the diagnosis. Half of the patients had a PS between 0 and 1. Small cell lung cancer was present in 18 patients (15.4%). The majority of non small cell lung cancer was of the adenocarcinoma type (68.7%). The diagnosis was late (stage IV) in 62.4% of cases. BPC was metastatic to bone (52%), contralateral lung (25.9%), and brain (27.3%). Patients were oligometastatic in 26% of cases. Surgery and radiotherapy were performed respectively in 14.5% and 23.1% of cases. Three-quarters of the patients had had nutrition (75.2%). The ROS1 mutation was present in 1 patient. PDL-1 expression was >40% in 2 patients. Survival was mean eight months ± 7.4. Conclusion: Lung cancer is diagnosed at a late stage in Tunisia. The lack of molecular study for non-small cell PBC and the lack of marketing authorization for tyrosine kinase inhibitors in Tunisia make the management incomplete.

Keywords: SCLC, NCSLC, ROS1, PDL1

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Authors: Angelis P. Barlampas

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Learning Objectives: The purpose of this study is to inform briefly the reader about the applications of AI in chest radiology. Background: Currently, there are 190 FDA-approved radiology AI applications, with 42 (22%) pertaining specifically to thoracic radiology. Imaging findings OR Procedure details Aids of AI in chest radiology1: Detects and segments pulmonary nodules. Subtracts bone to provide an unobstructed view of the underlying lung parenchyma and provides further information on nodule characteristics, such as nodule location, nodule two-dimensional size or three dimensional (3D) volume, change in nodule size over time, attenuation data (i.e., mean, minimum, and/or maximum Hounsfield units [HU]), morphological assessments, or combinations of the above. Reclassifies indeterminate pulmonary nodules into low or high risk with higher accuracy than conventional risk models. Detects pleural effusion . Differentiates tension pneumothorax from nontension pneumothorax. Detects cardiomegaly, calcification, consolidation, mediastinal widening, atelectasis, fibrosis and pneumoperitoneum. Localises automatically vertebrae segments, labels ribs and detects rib fractures. Measures the distance from the tube tip to the carina and localizes both endotracheal tubes and central vascular lines. Detects consolidation and progression of parenchymal diseases such as pulmonary fibrosis or chronic obstructive pulmonary disease (COPD).Can evaluate lobar volumes. Identifies and labels pulmonary bronchi and vasculature and quantifies air-trapping. Offers emphysema evaluation. Provides functional respiratory imaging, whereby high-resolution CT images are post-processed to quantify airflow by lung region and may be used to quantify key biomarkers such as airway resistance, air-trapping, ventilation mapping, lung and lobar volume, and blood vessel and airway volume. Assesses the lung parenchyma by way of density evaluation. Provides percentages of tissues within defined attenuation (HU) ranges besides furnishing automated lung segmentation and lung volume information. Improves image quality for noisy images with built-in denoising function. Detects emphysema, a common condition seen in patients with history of smoking and hyperdense or opacified regions, thereby aiding in the diagnosis of certain pathologies, such as COVID-19 pneumonia. It aids in cardiac segmentation and calcium detection, aorta segmentation and diameter measurements, and vertebral body segmentation and density measurements. Conclusion: The future is yet to come, but AI already is a helpful tool for the daily practice in radiology. It is assumed, that the continuing progression of the computerized systems and the improvements in software algorithms , will redder AI into the second hand of the radiologist.

Keywords: artificial intelligence, chest imaging, nodule detection, automated diagnoses

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Authors: Michela Terlizzi, Chiara Colarusso, Aldo Pinto, Rosalinda Sorrentino

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Sphingosine-1-phosphate (S1P) is a membrane-derived bioactive phospholipid exerting a multitude of effects on respiratory cell physiology and pathology through five S1P receptors (S1PR1-5). Higher levels of S1P have been registered in a broad range of respiratory diseases, including inflammatory disorders and cancer, although its exact role is still elusive. Based on our previous study in which we found that S1P/S1PR3 is involved in an inflammatory pattern via the activation of Toll-like Receptor 9 (TLR9), highly expressed on lung cancer cells, the main goal of the current study was to better understand the involvement of S1P/S1PR3 pathway/signaling during lung carcinogenesis, taking advantage of a mouse model of first-hand smoke exposure and of carcinogen-induced lung cancer. We used human samples of Non-Small Cell Lung Cancer (NSCLC), a mouse model of first-hand smoking, and of Benzo(a)pyrene (BaP)-induced tumor-bearing mice and A549 lung adenocarcinoma cells. We found that the intranuclear, but not the membrane, localization of S1PR3 was associated to the proliferation of lung adenocarcinoma cells, the mechanism that was correlated to human and mouse samples of smoke-exposure and carcinogen-induced lung cancer, which were characterized by higher utilization of S1P. Indeed, the inhibition of the membrane S1PR3 did not alter tumor cell proliferation after TLR9 activation. Instead, according to the nuclear localization of sphingosine kinase (SPHK) II, the enzyme responsible for the catalysis of the S1P last step synthesis, the inhibition of the kinase completely blocked the endogenous S1P-induced tumor cell proliferation. These results prove that the endogenous TLR9-induced S1P can on one side favor pro-inflammatory mechanisms in the tumor microenvironment via the activation of cell surface receptors, but on the other tumor progression via the nuclear S1PR3/SPHK II axis, highlighting a novel molecular mechanism that identifies S1P as one of the crucial mediators for lung carcinogenesis-associated inflammatory processes and that could provide differential therapeutic approaches especially in non-responsive lung cancer patients.

Keywords: sphingosine-1-phosphate (S1P), S1P Receptor 3 (S1PR3), smoking-mice, lung inflammation, lung cancer

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Authors: B. S. Akhmetov, S. T. Akhmetova, A. I. Ivanov, T. S. Kartbayev, A. Y. Malygin

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The problem of training of a network of artificial neurons in biometric appendices is that this process has to be completely automatic, i.e. the person operator should not participate in it. Therefore, this article discusses the issues of training the network of artificial neurons and the description of the non-iterative learning algorithm of artificial neuron.

Keywords: artificial neuron, biometrics, biometrical applications, learning of neuron, non-iterative algorithm

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Authors: Parisa Mansour

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Introduction: Early diagnosis of coronavirus disease (COVID-19) is extremely important to isolate and treat patients in time, thus preventing the spread of the disease, improving prognosis and reducing mortality. High-resolution computed tomography (HRCT) chest imaging and artificial intelligence (AI)-based analysis of HRCT chest images can play a central role in the treatment of patients with COVID-19. Objective: To investigate different chest HRCT findings in different stages of COVID-19 pneumonia and to evaluate the potential role of artificial intelligence in the quantitative assessment of lung parenchymal involvement in COVID-19 pneumonia. Materials and Methods: This retrospective observational study was conducted between May 1, 2020 and August 13, 2020. The study included 2169 patients with COVID-19 who underwent chest HRCT. HRCT images showed the presence and distribution of lesions such as: ground glass opacity (GGO), compaction, and any special patterns such as septal thickening, inverted halo, mark, etc. HRCT findings of the breast at different stages of the disease (early: andlt) 5 days, intermediate: 6-10 days and late stage: >10 days). A CT severity score (CTSS) was calculated based on the extent of lung involvement on HRCT, which was then correlated with clinical disease severity. Use of artificial intelligence; Analysis of CT pneumonia and quot; An algorithm was used to quantify the extent of pulmonary involvement by calculating the percentage of pulmonary opacity (PO) and gross opacity (PHO). Depending on the type of variables, statistically significant tests such as chi-square, analysis of variance (ANOVA) and post hoc tests were applied when appropriate. Results: Radiological findings were observed in HRCT chest in 1438 patients. A typical pattern of COVID-19 pneumonia, i.e., bilateral peripheral GGO with or without consolidation, was observed in 846 patients. About 294 asymptomatic patients were radiologically positive. Chest HRCT in the early stages of the disease mostly showed GGO. The late stage was indicated by such features as retinal enlargement, thickening and the presence of fibrous bands. Approximately 91.3% of cases with a CTSS = 7 were asymptomatic or clinically mild, while 81.2% of cases with a score = 15 were clinically severe. Mean PO and PHO (30.1 ± 28.0 and 8.4 ± 10.4, respectively) were significantly higher in the clinically severe categories. Conclusion: Because COVID-19 pneumonia progresses rapidly, radiologists and physicians should become familiar with typical TC chest findings to treat patients early, ultimately improving prognosis and reducing mortality. Artificial intelligence can be a valuable tool in treating patients with COVID-19.

Keywords: chest, HRCT, covid-19, artificial intelligence, chest HRCT

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Authors: Sungsoo Na, Chanho Park

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Lung cancer is one of the most common severe diseases driving to the death of a human. Lung cancer can be divided into two cases of small-cell lung cancer (SCLC) and non-SCLC (NSCLC), and about 80% of lung cancers belong to the case of NSCLC. From several studies, the correlation between epidermal growth factor receptor (EGFR) and NSCLCs has been investigated. Therefore, EGFR inhibitor drugs such as gefitinib and erlotinib have been used as lung cancer treatments. However, the treatments result showed low response (10~20%) in clinical trials due to EGFR mutations that cause the drug resistance. Patients with resistance to EGFR inhibitor drugs usually are positive to KRAS mutation. Therefore, assessment of EGFR and KRAS mutation is essential for target therapies of NSCLC patient. In order to overcome the limitation of conventional therapies, overall EGFR and KRAS mutations have to be monitored. In this work, the only detection of EGFR will be presented. A variety of techniques has been presented for the detection of EGFR mutations. The standard detection method of EGFR mutation in ctDNA relies on real-time polymerase chain reaction (PCR). Real-time PCR method provides high sensitive detection performance. However, as the amplification step increases cost effect and complexity increase as well. Other types of technology such as BEAMing, next generation sequencing (NGS), an electrochemical sensor and silicon nanowire field-effect transistor have been presented. However, those technologies have limitations of low sensitivity, high cost and complexity of data analyzation. In this report, we propose a label-free and high-sensitive detection method of lung cancer using quartz crystal microbalance based platform. The proposed platform is able to sense lung cancer mutant DNA with a limit of detection of 1nM.

Keywords: cancer DNA, resonance frequency, quartz crystal microbalance, lung cancer

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Authors: Asghar Arif

Abstract:

Lung cancer has been recognized as one of the greatest common cancers, causing the annual mortality rate of about 1.2 million people in the world. Lung cancer is the most prevalent cancer in men and the third-most common cancer among women (after breast and digestive cancers).Recent evidences have shown the inflammatory process as one of the potential factors of cancer. Tuberculosis (TB), pneumonia, and chronic bronchitis are among the most important inflammation-inducing factors in the lungs, among which TB has a more profound role in the emergence of cancer.TB is one of the important mortality factors throughout the world, and 205,000 death cases are reported annually due to this disease. Chronic inflammation and fibrosis due to TB can induce genetic mutation and alternations. Parenchyma tissue of lung is involved in both diseases of TB and lung cancer, and continuous cough in lung cancer, morphological vascular variations, lymphocytosis processes, and generation of immune system mediators such as interleukins, are all among the factors leading to the hypothesis regarding the role of TB in lung cancer Some reports have shown that the induction of necrosis and apoptosis or TB reactivation, especially in patients with immune-deficiency, may result in increasing IL-17 and TNF_α, which will either decrease P53 activity or increase the expression of Bcl-2, decrease Bax-T, and cause the inhibition of caspase-3 expression due to decreasing the expression of mitochondria cytochrome oxidase. It has been also indicated that following the injection of BCG vaccine, the host immune system will be reinforced, and in particular, the rates of gamma interferon, nitric oxide, and interleukin-2 are increased. Therefore, CD4 + lymphocyte function will be improved, and the person will be immune against cancer.Numerous prospective studies have so far been conducted on the role of TB in lung cancer, and it seems that this disease is effective in that particular cancer.One of the main challenges of lung cancer is its correct and timely diagnosis. Unfortunately, clinical symptoms (such as continuous cough, hemoptysis, weight loss, fever, chest pain, dyspnea, and loss of appetite) and radiological images are similar in TB and lung cancer. Therefore, anti-TB drugs are routinely prescribed for the patients in the countries with high prevalence of TB, like Pakistan. Regarding the similarity in clinical symptoms and radiological findings of lung cancer, proper diagnosis is necessary for TB and respiratory infections due to nontuberculousmycobacteria (NTM). Some of the drug resistive TB cases are, in fact, lung cancer or NTM lung infections. Acid-fast staining and histological study of phlegm and bronchial washing, culturing and polymerase chain reaction TB are among the most important solutions for differential diagnosis of these diseases. Briefly, it is assumed that TB is one of the risk factors for cancer. Numerous studies have been conducted in this regard throughout the world, and it has been observed that there is a significant relationship between previous TB infection and lung cancer. However, to prove this hypothesis, further and more extensive studies are required. In addition, as the clinical symptoms and radiological findings of TB, lung cancer, and non-TB mycobacteria lung infections are similar, they can be misdiagnosed as TB.

Keywords: TB and lung cancer, TB people, TB servivers, TB and HIV aids

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Authors: Dujrudee Chinwong, Chanida Prompantakorn, Ubonphan Chaichana, Surarong Chinwong

Abstract:

Objective: Understanding the university students’ perceptions on smoking caused lung cancer based on the Health Belief Model should help health care providers in assisting them to quit smoking. Thus, this study aimed to investigate the University students’ health belief in smoking behaviors caused lung cancer, which based on the Health Belief Model. Methods: Data were collected from voluntary participants using a self-administered questionnaire. Participants were students studying at a University in northern Thailand who were current smokers; they were selected using snowball sampling. Results: Of 361 students, 84% were males; 78% smoked not more than 10 cigarettes a day; 68% intended to quit smoking. Our findings, based on the health belief model, showed that 1) perceived susceptibility: participants strongly believed that if they did not stop smoking, they were at high risk of lung cancer (88%); 2) perceived severity: they strongly believed that they had a high chance of death from lung cancer if they continued smoking (84%); 3) perceived benefits: they strongly believed that quitting smoking could reduce the chance of developing lung cancer; 4) perceived barriers of quitting smoking: they strongly believed in the difficulty of quitting smoking because it needed a high effort and strong intention (69%); 5) perceived self-efficacy: however, they strongly believed that they can quit smoking right away if they had a strong intention to quit smoking (70%); 6) cues to action: they strongly believed in the support of parents (85%) and lovers (78%) in helping them to quit smoking. Further, they believed that limitation on smoking area in the University and smoking cessation services provided by the University can assist them to quit smoking. Conclusion: The Health Belief Model helps us to understand students’ smoking behaviors caused lung cancer. This could lead to designing a smoking cessation program to assist students to quit smoking.

Keywords: health belief model, lung cancer, smoking, Thailand

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Authors: Aastha Agarwal, Veena Sharma

Abstract:

N-nitrosopyrollidine or NPYR is a tobacco-specific nitrosamine which upon intoxicated causes abnormal production of Reactive Oxygen Species disrupt the endogenous antioxidant system. The study was designed to evaluate the histological changes in lung tissue of Mus musculus in NPYR administered lungs and effect of isolated flavonoid 3,6-dihydroxy-(3’,4’,7’-trimethoxyphenyl)-chromen-4-one-7-glucoside (ITC) from experimental plant Indigofera tinctorial. Post treatment with isolated compound significantly restored the abnormal symptoms and changes in pulmonary tissue. Transverse section of mouse lung in control animals appeared as a thin lace. Histologically, most of the lung was arranged as alveoli which were thin walled structures made up of single layered squamous epithelial cells. In the transverse section of lung at 100 X will clearly show the component of alveoli, surround by a thin layer of connective tissue and blood vessels. Smaller bronchioles were lined by cuboidal epithelial cells while larger bronchioles were lined by ciliated columnar epithelium layer while in NPYR intoxicated lungs signs of vast pulmonary damages and carcinogenesis as alveolar damage, necrosis, DADs or defused alveolar damages hyperplasia, metaplasia, dysplasia and next stage of carcinogenesis were revealed. Treatment with ITC showed the significant positive changes in the lung tissue due to the side hydroxyl and methoxy groups in its structure which help in combating oxidative injuries and give protection from the free radicals generated during the metabolism of NPYR in body. Thus, histopathological analysis confirms the development of the cancerous conditions in the lung tissue in mice model and the protective effects of ITC.

Keywords: flavonoid, histopathology, Indigofera tinctoria, lung

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Authors: Mariana Panayotova-Pencheva, Anetka Trifonova, Vassilena Dakova

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790 lungs from brown hares (Lepus europeus L.) from different regions of Bulgaria were investigated during the period 2009-2017. The parasitological status and pathomorphological features in the lungs were recorded. The following parasite species were established: one nematode - Protostrongylus tauricus (7.59% prevalence), one tapeworm – larva of Taenia pisiformis – Cysticercus pisiformis (3.04% prevalence) and one arthropod – larva of Linguatula serrata – Pentastomum dentatum (0.89% prevalence). Macroscopic lesions in the lungs were different depending on the causative agents. The infections with C. pisiformis and P. dentatum were attended with small, mainly superficial changes in the lungs. Protostrongylid infections were connected with different in appearance and burden macroscopic changes. In 77.7%, they were nodular, and in the rest of cases, they diffuse. The consistency of the lesions was compact. In most of the cases, alterations were grey in colour, rarely were dark-red or marble-like. In 91.7% of these cases, they were spread on the apical parts of large lung lobes. In 36.7% middle parts of the large lung lobes, and, in 26.7% small lung lobes, were also affected. The small lung lobes were never independently infected.

Keywords: Cysticercus pisiformis, Lepus europeus, lung lesions, Pentastomum dentatum, Protostrongylus tauricus

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Authors: Chia-Chen Hsieh, Fei-Hsiu Hsiao

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Objective: To examine the effects of supportive care interventions on depressive symptoms in patients with lung cancer. Methods: The databases of Cochrane Central Register of Controlled Trials (CENTRAL), Ovid EMBASE, PubMed, and Chinese Electronic Periodical Services (CEPS) were searched from their inception until September 2015. We included the studies with randomized controlled trial design that compared standard care with supportive care interventions using psychotherapeutic or exercises approach. The standardized mean differences (SMD) (Cohen’s d) were calculated to estimate the treatment effects. The Cochrane Risk of Bias Tool was used for quality assessment and subgroup analysis was conducted to identify possible sources of heterogeneity. Results: A total of 1472 patients with lung cancer were identified. Compared with standard care, the overall effects of all supportive care interventions significantly reduced depressive symptoms (SMD = -0.74 with 95% CI = -1.07 to -0.41), and the effect was maintained at the 4th, 8th, and 12th weeks of follow-up. Either psychotherapy combined with psychoeducation or exercise alone produced significant improvements in depressive symptoms, while psychoeducation alone did not. The greater improvements in depressive symptoms occurred in lung cancer patients with severe depressive symptoms at baseline, total duration of interventions of less than ten weeks, and intervention provided through face-to-face delivery. Conclusions: Psychotherapy combined with psychoeducation can help patients manage the causes of depressive symptoms, including both symptom distress and psychological trauma due to lung cancer. Exercise can target the impaired respiratory function that is a cause of depressive symptoms in lung cancer patients.

Keywords: supportive care intervention, depressive symptoms, lung cancer, meta-analysis

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Authors: Yousif Mohamed Y. Abdallah

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This is an experimental study deals with detection, measurement and analysis of the periodic physiological organ motion during external beam radiotherapy; to improve the accuracy of the radiation field placement, and to reduce the exposure of healthy tissue during radiation treatments. The importance of this study is to detect the maximum path of the mobile structures during radiotherapy delivery, to define the planning target volume (PTV) and irradiated volume during both inspiration and expiration period and to verify the target volume. In addition to its role to highlight the importance of the application of Intense Guided Radiotherapy (IGRT) methods in the field of radiotherapy. The results showed (body contour was equally (3.17 + 0.23 mm), for left lung displacement reading (2.56 + 0.99 mm) and right lung is (2.42 + 0.77 mm) which the radiation oncologist to take suitable countermeasures in case of significant errors. In addition, the use of the image registration technique for automatic position control is predicted potential motion. The motion ranged between 2.13 mm and 12.2 mm (low and high). In conclusion, individualized assessment of tumor mobility can improve the accuracy of target areas definition in patients undergo Sterostatic RT for stage I, II and III lung cancer (NSCLC). Definition of the target volume based on a single CT scan with a margin of 10 mm is clearly inappropriate.

Keywords: respiratory motion, external beam radiotherapy, image processing, lung

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Authors: Mahya Naghipoor

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Purpose: Non-small cell lung cancer (NSCLC) is the most common lung cancer type. Epidermal growth factor receptor (EGFR) mutation is the main reason which causes NSCLC. Computed tomography (CT) is used for diagnosis and prognosis of lung cancers because of low price and little invasion. Semantic analyses of qualitative CT features are based on visual evaluation by radiologist. However, the naked eye ability may not assess all image features. On the other hand, radiomics provides the opportunity of quantitative analyses for CT images features. The aim of this review study was comparing accuracy of semantic and radiomics features in prognosis of EGFR mutation in NSCLC. Methods: For this purpose, the keywords including: non-small cell lung cancer, epidermal growth factor receptor mutation, semantic, radiomics, feature, receiver operating characteristics curve (ROC) and area under curve (AUC) were searched in PubMed and Google Scholar. Totally 29 papers were reviewed and the AUC of ROC analyses for semantic and radiomics features were compared. Results: The results showed that the reported AUC amounts for semantic features (ground glass opacity, shape, margins, lesion density and presence or absence of air bronchogram, emphysema and pleural effusion) were %41-%79. For radiomics features (kurtosis, skewness, entropy, texture, standard deviation (SD) and wavelet) the AUC values were found %50-%86. Conclusions: In conclusion, the accuracy of radiomics analysis is a little higher than semantic in prognosis of EGFR mutation in NSCLC.

Keywords: lung cancer, radiomics, computer tomography, mutation

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Authors: Mohamed Bakry Mohamed Ali, Mohamed Ehab El-Din Mustafa, Joseph Naiem Sabet Aziz, Sarah Mahmoud Ali Kaooh

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Background: Acute lung injury (ALI) is one of the major challenges in intensive care medicine. The most common extrapulmonary cause of ALI is sepsis, accounting more than 30% of the cases in humans. Lipopolysaccharide (LPS) has gained wide acceptance as a clinically relevant model of ALI. Lipopolysaccharide is a glycoprotein forming the major constituent of bacterial endotoxin. Losartan is angiotensin II type 1 (AT1) receptor antagonists. It is widely used for management of hypertension. It was recently suggested that losartan protects against septic ALI. It would thereby prevent LPS-induced ALI. Aim of the work and design of the experiment: This work investigated the injurious effect of lipopolysaccharide (LPS) and ALI on adult male albino rat at 24 hours and 14 days of LPS administration and the possible protective role of losartan pretreatment. LPS has deteriorated animal survival and behavior. It increased lung weight and induced lung histological damage. These changes could be much reduced by the losartan pretreatment. Conclusion: Administration of losartan before LPS could largely reduce these LPS/ ALI induced short and long term alterations. It could be recommended that patients susceptible to developing ALI, as in ICU, should receive a protective dose of angitensin II type 1 (AT1) receptor blocker as losartan.

Keywords: acute lung injury (ALI), lipopolysaccharide (LPS), losartan

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Authors: Meshandren Naidoo, Amy Gooden

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The concept of personhood extending from the moral status of an artificial intelligence system has been explored – but predominantly from a Western conception of personhood. African personhood, however, is distinctly different from Western personhood in that communitarianism is central rather than individualism. Given the decolonization projects happening in Africa, it’s paramount to consider these views. This research demonstrates that the African notion of personhood may extend for an artificial intelligent system where the pre-conditions are met.

Keywords: artificial intelligence, ethics, law, personhood, policy

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Authors: Mehrnoosh Abouzari

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Artificial intelligence has covered all areas of human life and has helped or replaced many jobs. One of the areas of application of artificial intelligence in the police is to detect crime, identify the accused or victim and prove the crime. It will play an effective role in implementing preventive justice and creating security in the community, and improving judicial decisions. This will help improve the performance of the police, increase the accuracy of criminal investigations, and play an effective role in preventing crime and high-risk behaviors in society. This article presents and analyzes the capabilities and capacities of artificial intelligence in police and similar examples used worldwide to prove the necessity of using artificial intelligence in the police. The main topics discussed include the performance of artificial intelligence in crime detection and prediction, the risk capacity of criminals and the ability to apply arbitray institutions, and the introduction of artificial intelligence programs implemented worldwide in the field of criminal investigation for police.

Keywords: police, artificial intelligence, forecasting, prevention, software

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Authors: Fakhrosadat Sajjadian

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The majority of deaths in cancer patients are caused by distant metastasis. Breast cancer shows a unique spread pattern, often affecting bone, liver, lung, and brain. Breast cancer can be categorized into various subtypes according to gene expression patterns, and these subtypes exhibit specific preferences for organs where metastasis occurs. Breast tumors with luminal characteristics have a preference for spreading to the bone, whereas basal-like breast cancer (BLBC) shows a tendency to metastasize to the lungs. Still, the mechanisms behind this particular pattern of metastasis in organs have yet to be fully understood. In this evaluation, we will outline the latest progress in molecular signaling pathways and treatment methods for breast cancer lung metastasis.

Keywords: lung cancer, liver cancer, diagnosis, BLBC, metastasis

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