Search results for: lung parenchyma segmentation

Authors: Wiam El Kheir, Anais Dumais, Maude Beaudoin, Bernard Marcos, Nick Virgilio, Benoit Paquette, Nathalie Faucheux, Marc-Antoine Lauzon

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The high infiltrative pattern of glioblastoma multiforme cells (GBM) is the main cause responsible for the actual standard treatments failure. The tumor high heterogeneity, the interstitial fluid flow (IFF) and chemokines guides GBM cells migration in the brain parenchyma resulting in tumor recurrence. Drug delivery systems emerged as an alternative approach to develop effective treatments for the disease. Some recent studies have proposed to harness the effect CXC-lchemokine-ligand-12 to direct and control the cancer cell migration through delivery system. However, the dynamics of the brain environment on the delivery system remains poorly understood. Nanoparticles (NPs) and hydrogels are known as good carriers for the encapsulation of different agents and control their release. We studied the release of CXCL12 (free or loaded into NPs) from an alginate-based hydrogel under static and indirect perfusion (IP) conditions. Under static conditions, the main phenomena driving CXCL12 release from the hydrogel was diffusion with the presence of strong interactions between the positively charged CXCL12 and the negatively charge alginate. CXCL12 release profiles were independent from the initial mass loadings. Afterwards, we demonstrated that the release could tuned by loading CXCL12 into Alginate/Chitosan-Nanoparticles (Alg/Chit-NPs) and embedded them into alginate-hydrogel. The initial burst release was substantially attenuated and the overall cumulative release percentages of 21%, 16% and 7% were observed for initial mass loadings of 0.07, 0.13 and 0.26 µg, respectively, suggesting stronger electrostatic interactions. Results were mathematically modeled based on Fick’s second law of diffusion framework developed previously to estimate the effective diffusion coefficient (Deff) and the mass transfer coefficient. Embedding the CXCL12 into NPs decreased the Deff an order of magnitude, which was coherent with experimental data. Thereafter, we developed an in-vitro 3D model that takes into consideration the convective contribution of the brain IFF to study CXCL12 release in an in-vitro microenvironment that mimics as faithfully as possible the human brain. From is unique design, the model also allowed us to understand the effect of IP on CXCL12 release in respect to time and space. Four flow rates (0.5, 3, 6.5 and 10 µL/min) which may increase CXCL12 release in-vivo depending on the tumor location were assessed. Under IP, cumulative percentages varying between 4.5-7.3%, 23-58.5%, 77.8-92.5% and 89.2-95.9% were released for the three initial mass loadings of 0.08, 0.16 and 0.33 µg, respectively. As the flow rate increase, IP culture conditions resulted in a higher release of CXCL12 compared to static conditions as the convection contribution became the main driving mass transport phenomena. Further, depending on the flow rate, IP had a direct impact on CXCL12 distribution within the simulated brain tissue, which illustrates the importance of developing such 3D in-vitro models to assess the efficiency of a delivery system targeting the brain. In future work, using this very model, we aim to understand the impact of the different phenomenon occurring on GBM cell behaviors in response to the resulting chemokine gradient subjected to various flow while allowing them to express their invasive characteristics in an in-vitro microenvironment that mimics the in-vivo brain parenchyma.

Keywords: 3D culture system, chemokines gradient, glioblastoma multiforme, kinetic release, mathematical modeling

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Authors: Xiang Zhang, Daohong Yang, Ziyuan Wu, Lei Li, Wanting Zhou

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Visual Simultaneous Localization and Mapping (VSLAM) uses cameras to collect information in unknown environments to realize simultaneous localization and environment map construction, which has a wide range of applications in autonomous driving, virtual reality and other related fields. At present, the related research achievements about VSLAM can maintain high accuracy in static environment. But in dynamic environment, due to the presence of moving objects in the scene, the movement of these objects will reduce the stability of VSLAM system, resulting in inaccurate localization and mapping, or even failure. In this paper, a robust VSLAM method was proposed to effectively deal with the problem in dynamic environment. We proposed a dynamic region removal scheme based on semantic segmentation neural networks and geometric constraints. Firstly, semantic extraction neural network is used to extract prior active motion region, prior static region and prior passive motion region in the environment. Then, the light weight frame tracking module initializes the transform pose between the previous frame and the current frame on the prior static region. A motion consistency detection module based on multi-view geometry and scene flow is used to divide the environment into static region and dynamic region. Thus, the dynamic object region was successfully eliminated. Finally, only the static region is used for tracking thread. Our research is based on the ORBSLAM3 system, which is one of the most effective VSLAM systems available. We evaluated our method on the TUM RGB-D benchmark and the results demonstrate that the proposed VSLAM method improves the accuracy of the original ORBSLAM3 by 70%˜98.5% under high dynamic environment.

Keywords: dynamic scene, dynamic visual SLAM, semantic segmentation, scene flow, VSLAM

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Authors: Shivahari Revathi Venkateswaran

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Segmenting customers plays a significant role in churn prediction. It helps the marketing team with proactive and reactive customer retention. For the reactive retention, the retention team reaches out to customers who already showed intent to disconnect by giving some special offers. When coming to proactive retention, the marketing team uses churn prediction model, which ranks each customer from rank 1 to 100, where 1 being more risk to churn/disconnect (high ranks have high propensity to churn). The churn prediction model is built by using XGBoost model. However, with the churn rank, the marketing team can only reach out to the customers based on their individual ranks. To profile different groups of customers and to frame different marketing strategies for targeted groups of customers are not possible with the churn ranks. For this, the customers must be grouped in different segments based on their profiles, like demographics and other non-controllable attributes. This helps the marketing team to frame different offer groups for the targeted audience and prevent them from disconnecting (proactive retention). For segmentation, machine learning approaches like k-mean clustering will not form unique customer segments that have customers with same attributes. This paper finds an alternate approach to find all the combination of unique segments that can be formed from the user attributes and then finds the segments who have uplift (churn rate higher than the baseline churn rate). For this, search algorithms like fast search and recursive search are used. Further, for each segment, all customers can be targeted using individual churn ranks from the churn prediction model. Finally, a UI (User Interface) is developed for the marketing team to interactively search for the meaningful segments that are formed and target the right set of audience for future marketing campaigns and prevent them from disconnecting.

Keywords: churn prediction modeling, XGBoost model, uplift segments, proactive marketing, search algorithms, retention, k-mean clustering

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Authors: Shenlun Chen, Leonard Wee

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Tumor grading is an essential reference for colorectal cancer (CRC) staging and survival prognostication. The widely used World Health Organization (WHO) grading system defines histological grade of CRC adenocarcinoma based on the density of glandular formation on whole slide images (WSI). Tumors are classified as well-, moderately-, poorly- or un-differentiated depending on the percentage of the tumor that is gland forming; >95%, 50-95%, 5-50% and <5%, respectively. However, manually grading WSIs is a time-consuming process and can cause observer error due to subjective judgment and unnoticed regions. Furthermore, pathologists’ grading is usually coarse while a finer and continuous differentiation grade may help to stratifying CRC patients better. In this study, a deep learning based automatic differentiation grading algorithm was developed and evaluated by survival analysis. Firstly, a gland segmentation model was developed for segmenting gland structures. Gland regions of WSIs were delineated and used for differentiation annotating. Tumor regions were annotated by experienced pathologists into high-, medium-, low-differentiation and normal tissue, which correspond to tumor with clear-, unclear-, no-gland structure and non-tumor, respectively. Then a differentiation prediction model was developed on these human annotations. Finally, all enrolled WSIs were processed by gland segmentation model and differentiation prediction model. The differentiation grade can be calculated by deep learning models’ prediction of tumor regions and tumor differentiation status according to WHO’s defines. If multiple WSIs were possessed by a patient, the highest differentiation grade was chosen. Additionally, the differentiation grade was normalized into scale between 0 to 1. The Cancer Genome Atlas, project COAD (TCGA-COAD) project was enrolled into this study. For the gland segmentation model, receiver operating characteristic (ROC) reached 0.981 and accuracy reached 0.932 in validation set. For the differentiation prediction model, ROC reached 0.983, 0.963, 0.963, 0.981 and accuracy reached 0.880, 0.923, 0.668, 0.881 for groups of low-, medium-, high-differentiation and normal tissue in validation set. Four hundred and one patients were selected after removing WSIs without gland regions and patients without follow up data. The concordance index reached to 0.609. Optimized cut off point of 51% was found by “Maxstat” method which was almost the same as WHO system’s cut off point of 50%. Both WHO system’s cut off point and optimized cut off point performed impressively in Kaplan-Meier curves and both p value of logrank test were below 0.005. In this study, gland structure of WSIs and differentiation status of tumor regions were proven to be predictable through deep leaning method. A finer and continuous differentiation grade can also be automatically calculated through above models. The differentiation grade was proven to stratify CAC patients well in survival analysis, whose optimized cut off point was almost the same as WHO tumor grading system. The tool of automatically calculating differentiation grade may show potential in field of therapy decision making and personalized treatment.

Keywords: colorectal cancer, differentiation, survival analysis, tumor grading

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Authors: Anca Dinischiotu, Sorina Nicoleta Voicu

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Silica nanoparticles (SiO2-NPs) are widely used in consumer products such as paints, plastics, insulation materials, tires, concrete production, as well as in gene delivery systems and imaging procedures. Environmental human exposure to them occurs during utilization of these products, in a time-dependent manner, the uptake being by topic and inhalation route especially. SiO2-NPs enter cells and induce membrane damage, oxidative stress and inflammatory reactions in a concentration-dependent manner. In this study, MRC-5 cells (human fetal lung fibroblasts) were exposed to amorphous SiO2-NPs at a dose of 62.5 μg/ml for 24, 48 and 72 hours. The size distribution of NPs was a lognormal function, in the range 3-14 nm. A time-dependent decrease of total reduced glutathione concentration by 36%, 50%, and 78% and an increase of NO level by 62%, 32%, respectively 24% compared to control were noticed. An up-regulation of NF-kB expression by 20%, 50% respectively 10% and of Nrf-2 by 139%, 58%, and 16% compared to control after 24, 48 and 72 hours was noticed also. The expression of IL-1β, IL-6, IL-8, and COX-2 was up-regulated in a time-dependent manner. Also, the expression of MMP-2 and MMP-9 were down-regulated after 48 and 72 hours, whereas their activities raised in a time-dependent manner. Exposure of cells to NPs up-regulated the expression of inducible NO synthase, as previously was shown, and probably this is the reason for the increased level of NO, that can react with the thiol groups of reduced glutathione molecules, diminishing its concentration Nrf2 is a transcription factor translocated in nucleus, under oxidative stress, where downstream gene expression activates in order to modulate the adaptive intracellular response against oxidative stress. The cross-talk between Nrf2 and NF-kB activities regulates the inflammatory processes. The activation of NF-kB could activate up-regulation of IL-1β, IL-6, and IL-8. The increase of COX-2 expression could be correlated with IL-1β one. Also, probably in response to the pro-inflammatory cytokines, MMP-2 and MMP-9 were induced and activated. In conclusion, the exposure of MRC-5 cells to SiO2-NPs generated inflammation in a time-dependent manner.

Keywords: inflammation, MRC-5 cells, oxidative stress, silica nanoparticles

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Authors: Mohammed Abu Shquier

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This paper introduces a word segmentation method using the novel BP-LSTM-CRF architecture for processing semantic output training. The objective of web morphological analysis tools is to link a formal morpho-syntactic description to a lemma, along with morpho-syntactic information, a vocalized form, a vocalized analysis with morpho-syntactic information, and a list of paradigms. A key objective is to continuously enhance the proposed system through an inductive learning approach that considers semantic influences. The system is currently under construction and development based on data-driven learning. To evaluate the tool, an experiment on homograph analysis was conducted. The tool also encompasses the assumption of deep binary segmentation hypotheses, the arbitrary choice of trigram or n-gram continuation probabilities, language limitations, and morphology for both Modern Standard Arabic (MSA) and Dialectal Arabic (DA), which provide justification for updating this system. Most Arabic word analysis systems are based on the phonotactic morpho-syntactic analysis of a word transmitted using lexical rules, which are mainly used in MENA language technology tools, without taking into account contextual or semantic morphological implications. Therefore, it is necessary to have an automatic analysis tool taking into account the word sense and not only the morpho-syntactic category. Moreover, they are also based on statistical/stochastic models. These stochastic models, such as HMMs, have shown their effectiveness in different NLP applications: part-of-speech tagging, machine translation, speech recognition, etc. As an extension, we focus on language modeling using Recurrent Neural Network (RNN); given that morphological analysis coverage was very low in dialectal Arabic, it is significantly important to investigate deeply how the dialect data influence the accuracy of these approaches by developing dialectal morphological processing tools to show that dialectal variability can support to improve analysis.

Keywords: NLP, DL, ML, analyser, MSA, RNN, CNN

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Authors: Shantanu Arya, Sachin Sakhuja, Gunjan Mehta, Sanjay Munjal

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Stuttering may be defined as a speech disorder affecting the fluency domain of speech and characterized by covert features like word substitution, omittance and circumlocution and overt features like prolongation of sound, syllables and blocks etc. Many etiologies have been postulated to explain stuttering based on various experiments and research. Moreover, Breathlessness has also been reported by many individuals with stuttering for which breathing exercises are generally advised. However, no studies reporting objective evaluation of the pulmonary capacity and further objective assessment of the efficacy of breathing exercises have been conducted. Pulmonary Function Test which evaluates parameters like Forced Vital Capacity, Peak Expiratory Flow Rate, Forced expiratory flow Rate can be used to study the pulmonary behavior of individuals with stuttering. The study aimed: a) To identify speech motor & physiologic behaviours associated with stuttering by administering PFT. b) To recognize possible reasons for an association between speech motor behaviour & stuttering severity. In this regard, PFT tests were administered on individuals who reported signs and symptoms of stuttering and showed abnormal scores on Stuttering Severity Index. Parameters like Forced Vital Capacity, Forced Expiratory Volume, Peak Expiratory Flow Rate (L/min), Forced Expiratory Flow Rate (L/min) were evaluated and correlated with scores of Stuttering Severity Index. Results showed significant decrease in the parameters (lower than normal scores) in individuals with established stuttering. Strong correlation was also found between degree of stuttering and the degree of decrease in the pulmonary volumes. Thus, it is evident that fluent speech requires strong support of lung pressure and requisite volumes. Further research in demonstrating the efficacy of abdominal breathing exercises in this regard is needed.

Keywords: forced expiratory flow rate, forced expiratory volume, forced vital capacity, peak expiratory flow rate, stuttering

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Authors: Dipti Chand, Riya Saboo

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OBJECTIVES: Early and correct diagnosis may present a significant clinical challenge in diagnosis of patients presenting to Emergency Department with Acute Dyspnoea. The common cause of acute dyspnoea and respiratory distress in Emergency Department are Decompensated Heart Failure (HF), Chronic Obstructive Pulmonary Disease (COPD), Asthma, Pneumonia, Acute Respiratory Distress Syndrome (ARDS), Pulmonary Embolism (PE), and other causes like anaemia. The aim of the study was to measure NT-pro Brain Natriuretic Peptide (BNP) and exhaled End-Tidal Carbon dioxide (ETCO2) in patients presenting with dyspnoea. MATERIAL AND METHODS: This prospective, cross-sectional and observational study was performed at the Government Medical College and Hospital, Nagpur, between October 2019 and October 2021 in patients admitted to the Medicine Intensive Care Unit. Three groups of patients were compared: (1) HFrelated acute dyspnoea group (n = 52), (2) pulmonary (COPD/PE)-related acute dyspnoea group (n = 31) and (3) sepsis with ARDS-related dyspnoea group (n = 13). All patients underwent initial clinical examination with a recording of initial vital parameters along with on-admission ETCO2 measurement, NT-proBNP testing, arterial blood gas analysis, lung ultrasound examination, 2D echocardiography, chest X-rays, and other relevant diagnostic laboratory testing. RESULTS: 96 patients were included in the study. Median NT-proBNP was found to be high for the Heart Failure group (11,480 pg/ml), followed by the sepsis group (780 pg/ml), and pulmonary group had an Nt ProBNP of 231 pg/ml. The mean ETCO2 value was maximum in the pulmonary group (48.610 mmHg) followed by Heart Failure (31.51 mmHg) and the sepsis group (19.46 mmHg). The results were found to be statistically significant (P < 0.05). CONCLUSION: NT-proBNP has high diagnostic accuracy in differentiating acute HF-related dyspnoea from pulmonary (COPD and ARDS)-related acute dyspnoea. The higher levels of ETCO2 help in diagnosing patients with COPD.

Keywords: NT PRO BNP, ETCO2, dyspnoea, lung USG

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Authors: Sweta Agrawal, Sachin Chaugule, Gargi Rane, Shashank More, Madhavi Indap

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Angiogenesis and metastasis are two of the most important hallmarks of cancer. Hence, most of the cancer therapies nowadays are multi-targeted so as to reduce resistance and have better efficacy. As synthetic molecules arise with a burden of their toxicities and side-effects, more and more research is being focussed on exploiting the vast natural resources of drugs, in the form of plants and animals. Although, the idea of using marine organisms as a source of pharmaceuticals is not new, the pace at which marine drugs are being discovered, has definitely up surged! In the present study, we have assessed the anti-angiogenic and in vitro anti-metastatic activity of aqueous fraction from the extract of marine gastropod Euchelus asper. The soft body of Euchelus Asper was extracted with methanol and named EAME. Partition chromatography of EAME gave three fractions EAME I, II and III. Biochemical analysis revealed the presence of proteins in EAME III. Preliminary analysis had revealed the anti-angiogenic activity was exhibited by EAME III out of the three fractions. Hereafter, EAME III (concentration 25µg/ml-400µg/ml) was tested on chick chorioallantoic membrane (CAM) model for the detailed analysis of its potential anti-angiogenic effect. In vitro testing of the fraction (concentration 0.25µg/ml - 1µg/ml), involved cytotoxicity by SRB assay, cell cycle analysis by flow cytometry and anti-proliferative effect by scratch wound healing assay on A549 lung carcinoma cells. Apart from this, a portion of treated CAM as well as conditioned medium from treated A549 were subjected to gelatin zymography for assessment of matrix metalloproteinases MMP-2 and MMP-9 levels. Our results revealed that EAME III exhibited significant anti-angiogenic activity on CAM which was also supported by histological observations. During histological studies of CAM, it was found that EAME III caused reduction in angiogenesis by altering the extracellular matrix of the CAM membrane. In vitro analysis disclosed that EAME III exhibited moderate cytotoxic effect on A549 cells and its effect was not dose-dependent. The results of flow cytometry confirmed that EAME III caused cell cycle arrest in A549 cell line as almost all of the treated cells were found in G1 phase. Further, the migration and proliferation of A549 was significantly reduced by EAME III as observed from the scratch wound assay. Moreover, Gelatin zymography analysis revealed that EAME III caused suppression of MMP-2 in CAM membrane and reduced MMP-9 and MMP-2 expression in A549 cells. This verified that the anti-angiogenic and anti-metastatic effects of EAME III were correlated with the suppression of MMP-2 and -9. To conclude, EAME III shows dual anti-tumour action by reducing angiogenesis and exerting anti-metastatic effect on lung cancer cells, thus it has the potential to be used as an anti-cancer agent against lung carcinoma.

Keywords: angiogenesis, anti-cancer, marine drugs, matrix metalloproteinases

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Authors: Öznur Saribaş, Si̇bel Kahraman Çeti̇ntaş

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It is aimed to compare target volume and critical organ doses by using CyberKnife (CK) in accelerated partial breast irradiation (APBI) in patients with early stage breast cancer. Three different virtual plans were made for Iris, fixed and multi-leaf collimator (MLC) for 5 patients who received radiotherapy in the CyberKnife system. CyberKnife virtual plans were created, with 6 Gy per day totaling 30 Gy. Dosimetric parameters for the three collimators were analyzed according to the restrictions in the NSABP-39/RTOG 0413 protocol. The plans ensured critical organs were protected and GTV received 95 % of the prescribed dose. The prescribed dose was defined by the isodose curve of a minimum of 80. Homogeneity index (HI), conformity index (CI), treatment time (min), monitor unit (MU) and doses taken by critical organs were compared. As a result of the comparison of the plans, a significant difference was found for the duration of treatment, MU. However, no significant difference was found for HI, CI. V30 and V15 values of the ipsi-lateral breast were found in the lowest MLC. There was no significant difference between Dmax values for lung and heart. However, the mean MU and duration of treatment were found in the lowest MLC. As a result, the target volume received the desired dose in each collimator. The contralateral breast and contralateral lung doses were the lowest in the Iris. Fixed collimator was found to be more suitable for cardiac doses. But these values did not make a significant difference. The use of fixed collimators may cause difficulties in clinical applications due to the long treatment time. The choice of collimator in breast SBRT applications with CyberKnife may vary depending on tumor size, proximity to critical organs and tumor localization.

Keywords: APBI, CyberKnife, early stage breast cancer, radiotherapy.

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Authors: P. V. Pramila , V. Mahesh

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Pulmonary Function Tests are important non-invasive diagnostic tests to assess respiratory impairments and provides quantifiable measures of lung function. Spirometry is the most frequently used measure of lung function and plays an essential role in the diagnosis and management of pulmonary diseases. However, the test requires considerable patient effort and cooperation, markedly related to the age of patients esulting in incomplete data sets. This paper presents, a nonlinear model built using Multivariate adaptive regression splines and Random forest regression model to predict the missing spirometric features. Random forest based feature selection is used to enhance both the generalization capability and the model interpretability. In the present study, flow-volume data are recorded for N= 198 subjects. The ranked order of feature importance index calculated by the random forests model shows that the spirometric features FVC, FEF 25, PEF,FEF 25-75, FEF50, and the demographic parameter height are the important descriptors. A comparison of performance assessment of both models prove that, the prediction ability of MARS with the `top two ranked features namely the FVC and FEF 25 is higher, yielding a model fit of R2= 0.96 and R2= 0.99 for normal and abnormal subjects. The Root Mean Square Error analysis of the RF model and the MARS model also shows that the latter is capable of predicting the missing values of FEV1 with a notably lower error value of 0.0191 (normal subjects) and 0.0106 (abnormal subjects). It is concluded that combining feature selection with a prediction model provides a minimum subset of predominant features to train the model, yielding better prediction performance. This analysis can assist clinicians with a intelligence support system in the medical diagnosis and improvement of clinical care.

Keywords: FEV, multivariate adaptive regression splines pulmonary function test, random forest

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Authors: Fiona Bei Na Tan, Glen Wen Kiat Ho, Ee Leen Liow, Li Yin Tan, Sean Wei Loong Ho

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Background: Shoulder arthroscopy is an increasingly common procedure. Pneumothorax post-shoulder arthroscopy is a rare complication. Objectives: Our aim is to highlight a case report of pneumothorax post shoulder arthroscopy and to conduct a literature review to evaluate the possible risk factors associated with developing a pneumothorax during or after shoulder arthroscopy. Case Report: We report the case of a 75-year-old male non-smoker who underwent left shoulder arthroscopy without regional anaesthesia and in the left lateral position. The general anaesthesia and surgery were uncomplicated. The patient was desaturated postoperatively and was found to have a pneumothorax on examination and chest X-ray. A chest tube drain was inserted promptly into the right chest. He had an uncomplicated postoperative course. Methods: PubMed Medline and Cochrane database search was carried out using the terms shoulder arthroplasty, pneumothorax, pneumomediastinum, and subcutaneous emphysema. We selected full-text articles written in English. Results: Thirty-two articles were identified and thoroughly reviewed. Based on our inclusion and exclusion criteria, 14 articles, which included 20 cases of pneumothorax during or after shoulder arthroscopy, were included. Eighty percent (16/20) of pneumothoraxes occurred postoperatively. In the articles that specify the side of pneumothorax, 91% (10/11) occur on the ipsilateral side of the arthroscopy. Eighty-eight percent (7/8) of pneumothoraxes occurred when subacromial decompression was performed. Fifty-six percent (9/16) occurred in patients placed in the lateral decubitus position. Only 30% (6/20) occurred in current or ex-smokers, and only 25% (5/20) had a pre-existing lung condition. Overall, of the articles that posit a mechanism, 75% (9/12) deem the pathogenesis to be multifactorial. Conclusion: The exact mechanism of pneumothorax is currently unknown. Awareness of this complication and timely recognition are important to prevent life-threatening sequelae. Surgeons should have a low threshold to obtain diagnostic plain radiographs in the event of clinical suspicion.

Keywords: rotator cuff repair, decompression, pressure, complication

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Authors: Shreeyam, Ranjan Kumar Sah, Shivangi

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Recognizing and solving handwritten mathematical expressions can be a challenging task, particularly when certain characters are segmented and classified. This project proposes a solution that uses Convolutional Neural Network (CNN) and image processing techniques to accurately solve various types of equations, including arithmetic, quadratic, and trigonometric equations, as well as logical operations like logical AND, OR, NOT, NAND, XOR, and NOR. The proposed solution also provides a graphical solution, allowing users to visualize equations and their solutions. In addition to equation solving, the platform, called CNNCalc, offers a comprehensive learning experience for students. It provides educational content, a quiz platform, and a coding platform for practicing programming skills in different languages like C, Python, and Java. This all-in-one solution makes the learning process engaging and enjoyable for students. The proposed methodology includes horizontal compact projection analysis and survey for segmentation and binarization, as well as connected component analysis and integrated connected component analysis for character classification. The compact projection algorithm compresses the horizontal projections to remove noise and obtain a clearer image, contributing to the accuracy of character segmentation. Experimental results demonstrate the effectiveness of the proposed solution in solving a wide range of mathematical equations. CNNCalc provides a powerful and user-friendly platform for solving equations, learning, and practicing programming skills. With its comprehensive features and accurate results, CNNCalc is poised to revolutionize the way students learn and solve mathematical equations. The platform utilizes a custom-designed Convolutional Neural Network (CNN) with image processing techniques to accurately recognize and classify symbols within handwritten equations. The compact projection algorithm effectively removes noise from horizontal projections, leading to clearer images and improved character segmentation. Experimental results demonstrate the accuracy and effectiveness of the proposed solution in solving a wide range of equations, including arithmetic, quadratic, trigonometric, and logical operations. CNNCalc features a user-friendly interface with a graphical representation of equations being solved, making it an interactive and engaging learning experience for users. The platform also includes tutorials, testing capabilities, and programming features in languages such as C, Python, and Java. Users can track their progress and work towards improving their skills. CNNCalc is poised to revolutionize the way students learn and solve mathematical equations with its comprehensive features and accurate results.

Keywords: AL, ML, hand written equation solver, maths, computer, CNNCalc, convolutional neural networks

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Authors: Olivier Delage, Thierry Portafaix, Hassan Bencherif, Guillaume Guimbretiere

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Most observation data sequences in geophysics can be interpreted as resulting from the interaction of several physical processes at several time and space scales. As a consequence, measurements time series in geophysics have often characteristics of non-linearity and non-stationarity and thereby exhibit strong fluctuations at all time-scales and require a time-frequency representation to analyze their variability. Empirical Mode Decomposition (EMD) is a relatively new technic as part of a more general signal processing method called the Hilbert-Huang transform. This analysis method turns out to be particularly suitable for non-linear and non-stationary signals and consists in decomposing a signal in an auto adaptive way into a sum of oscillating components named IMFs (Intrinsic Mode Functions), and thereby acts as a bank of bandpass filters. The advantages of the EMD technic are to be entirely data driven and to provide the principal variability modes of the dynamics represented by the original time series. However, the main limiting factor is the frequency resolution that may give rise to the mode mixing phenomenon where the spectral contents of some IMFs overlap each other. To overcome this problem, J. Gilles proposed an alternative entitled “Empirical Wavelet Transform” (EWT) which consists in building from the segmentation of the original signal Fourier spectrum, a bank of filters. The method used is based on the idea utilized in the construction of both Littlewood-Paley and Meyer’s wavelets. The heart of the method lies in the segmentation of the Fourier spectrum based on the local maxima detection in order to obtain a set of non-overlapping segments. Because linked to the Fourier spectrum, the frequency resolution provided by EWT is higher than that provided by EMD and therefore allows to overcome the mode-mixing problem. On the other hand, if the EWT technique is able to detect the frequencies involved in the original time series fluctuations, EWT does not allow to associate the detected frequencies to a specific mode of variability as in the EMD technic. Because EMD is closer to the observation of physical phenomena than EWT, we propose here a new technic called EAWD (Empirical Adaptive Wavelet Decomposition) based on the coupling of the EMD and EWT technics by using the IMFs density spectral content to optimize the segmentation of the Fourier spectrum required by EWT. In this study, EMD and EWT technics are described, then EAWD technic is presented. Comparison of results obtained respectively by EMD, EWT and EAWD technics on time series of ozone total columns recorded at Reunion island over [1978-2019] period is discussed. This study was carried out as part of the SOLSTYCE project dedicated to the characterization and modeling of the underlying dynamics of time series issued from complex systems in atmospheric sciences

Keywords: adaptive filtering, empirical mode decomposition, empirical wavelet transform, filter banks, mode-mixing, non-linear and non-stationary time series, wavelet

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Authors: Merfat Algethami, Anton Blencowe, Bryce Feltis, Stephen Best, Moshi Geso

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Nano-materials with high atomic number atoms have been demonstrated to enhance the effective radiation dose and thus potentially could improve therapeutic efficacy in radiotherapy. The optimal nanoparticulate agents require high X-ray absorption coefficients, low toxicity, and should be cost effective. The focus of our research is the development of a nanoparticle therapeutic agent that can be used in radiotherapy to provide optimal enhancement of the radiation effects on the target. In this study, we used bismuth (Bi) nanoparticles coated with starch and bismuth sulphide nanoparticles (Bi2S3) coated with polyvinylpyrrolidone (PVP). These NPs are of low toxicity and are one of the least expensive heavy metal-based nanoparticles. The aims of this study were to synthesise Bi2S3 and Bi NPs, and examine their cytotoxicity to human lung adenocarcinoma epithelial cells (A549). The dose enhancing effects of NPs on A549 cells were examined at both KV and MV energies. The preliminary results revealed that bismuth based nanoparticles show increased radio-sensitisation of cells, displaying dose enhancement with KV X-ray energies and to a lesser degree for the MV energies. We also observed that Bi NPs generated a greater dose enhancement effect than Bi2S3 NPs in irradiated A549 cells. The maximum Dose Enhancement Factor (DEF) was obtained at lower energy KV range when cells treated with Bi NPs (1.5) compared to the DEF of 1.2 when cells treated with Bi2S3NPs. Less radiation dose enhancement was observed when using high energy MV beam with higher DEF value of Bi NPs treatment (1.26) as compared to 1.06 DEF value with Bi2S3 NPs. The greater dose enhancement was achieved at KV energy range, due the effect of the photoelectric effect which is the dominant process of interaction of X-ray. The cytotoxic effect of Bi NPs on enhancing the X-ray dose was higher due to the higher amount of elemental Bismuth present in Bi NPs compared to Bi2S3 NPs. The results suggest that Bismuth based NPs can be considered as valuable dose enhancing agents when used in clinical applications.

Keywords: A549 lung cancer cells, Bi2S3 nanoparticles, dose enhancement effect, radio-sensitising agents

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Authors: R. Fardid, R. Coppes

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Introduction: In mediastinal radiotherapy and to a lesser extend also in total-body irradiation (TBI) radiation exposure may lead to development of cardiac diseases. Radiation-induced heart disease is dose-dependent and it is characterized by a loss of cardiac function, associated with progressive heart cells degeneration. We aimed to determine the in-vivo radiation effects on fibronectin, ColaA1, ColaA2, galectin and TGFb1 gene expression levels in left ventricle heart tissues of rats after irradiation. Material and method: Four non-treatment adult Wistar rats as control group (group A) were selected. In group B, 4 adult Wistar rats irradiated to 20 Gy single dose of 150 Mev proton beam locally in heart only. In heart plus lung irradiate group (group C) 4 adult rats was irradiated by 50% of lung laterally plus heart radiation that mentioned in before group. At 8 weeks after radiation animals sacrificed and left ventricle heart dropped in liquid nitrogen for RNA extraction by Absolutely RNA® Miniprep Kit (Stratagen, Cat no. 400800). cDNA was synthesized using M-MLV reverse transcriptase (Life Technologies, Cat no. 28025-013). We used Bio-Rad machine (Bio Rad iQ5 Real Time PCR) for QPCR testing by relative standard curve method. Results: We found that gene expression of fibronectin in group C significantly increased compared to control group, but it was not showed significant change in group B compared to group A. The levels of gene expressions of Cola1 and Cola2 in mRNA did not show any significant changes between normal and radiation groups. Changes of expression of galectin target significantly increased only in group C compared to group A. TGFb1 expressions in group C more than group B showed significant enhancement compared to group A. Conclusion: In summary we can say that 20 Gy of proton exposure of heart tissue may lead to detectable damages in heart cells and may distribute function of them as a component of heart tissue structure in molecular level.

Keywords: gene expression, heart damage, proton irradiation, radiotherapy

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Authors: Clara Franch de la Cal, Christopher J Morris, Michael McArthur

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Cystic fibrosis (CF) is an autosomal recessive genetic disorder characterized by abnormal transport of chloride and sodium across the lung epithelium, leading to thick and viscous secretions. Within which CF patients suffer from repeated bacterial pulmonary infections, with Pseudomonas aeru-ginosa (PA) eliciting the greatest inflammatory response, causing an irreversible loss of lung func-tion that determines morbidity and mortality. The cell wall of PA is a permeability barrier to many antibacterials and the rise of Mutli-Drug Resistant strains (MDR) is eroding the efficacy of the few remaining clinical options. In addition when PA infection becomes established it forms an antibi-otic-resistant biofilm, embedded in which are slow growing cells that are refractive to drug treat-ment. Making the development of new antibacterials a major challenge. This work describes the development of new type of nanoparticulate oligonucleotide antibacterial capable of tackling PA infections, including MDR strains. It is being developed to both block growth and prevent biofilm formation. These oligonucleotide therapeutics, Transcription Factor Decoys (TFD), act on novel genomic targets by capturing key regulatory proteins to block essential bacterial genes and defeat infection. They have been successfully transfected into a wide range of pathogenic bacteria, both in vitro and in vivo, using a proprietary delivery technology. The surfactant used self-assembles with TFD to form a nanoparticle stable in biological fluids, which protects the TFD from degradation and preferentially transfects prokaryotic membranes. Key challenges are to adapt the nanoparticle so it is active against PA in the context of biofilms and to formulate it for administration by inhalation. This would allow the drug to be delivered to the respiratory tract, thereby achieving drug concentrations sufficient to eradicate the pathogenic organisms at the site of infection.

Keywords: antibacterials, transcriptional factor decoys (TFDs), pseudomonas aeruginosa

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Authors: Kim Kennedy, Daren Gibson, Stephanie Flukes, Chandra Diwakarla, Lisa Spalding, Leanne Pilkington, Andrew Redfern

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Introduction: The mortality gap in Aboriginal Head and Neck Cancer is well known, but the reasons for poorer survival are not well established. Aim: We aimed to evaluate the locoregional and metastatic involvement, and stage at diagnosis, in Aboriginal compared with non-Aboriginal patients. Methods: We performed a retrospective cohort analysis of 320 HNC patients from a single centre in Western Australia, identifying 80 Aboriginal patients and 240 non-Aboriginal patients matched on a 1:3 ratio by sites, histology, rurality, and age. We collected data on the patient characteristics, tumour features, regions involved, stage at diagnosis, treatment history, and survival and relapse patterns, including sites of metastatic and locoregional involvement. Results: Aboriginal patients had a significantly higher incidence of lung metastases (26.3% versus 13.7%, p=0.009). Aboriginal patients also had a numerically but non-statistically significant higher incidence of thoracic nodal involvement (10% vs 5.8%) and malignant pleural effusions (3.8% vs 2.5%). Aboriginal patients also had a numerically but not statistically significantly higher incidence of adrenal and bony involvement. Interestingly, non-Aboriginal patients had an increased rate of cutaneous (2.1% vs 0%) and liver metastases (4.6% vs 2.5%) compared with Aboriginal patients. In terms of locoregional involvement, Aboriginal patients were more than twice as likely to have contralateral neck involvement (58.8% vs 24.2%, p<0.00001), and 30% more likely to have ipsilateral neck lymph node involvement (78.8% vs 60%, p=0.002) than non-Aboriginal patients. Aboriginal patients had significantly more advanced disease at diagnosis (p=0.008). Aboriginal compared with non-Aboriginal patients were less likely to present with stage I (7.5% vs 22.5%), stage II (11.3% vs 13.8%), or stage III disease (13.8% vs 17.1%), and more likely to present with more advanced stage IVA (42.5% vs 34.6%), stage IVB (15% vs 7.1%), or stage IVC (10% vs 5%) disease (p=0.008). Number of regions of disease involvement was higher in Aboriginal patients (median 3, mean 3.64, range 1-10) compared with non-Aboriginal patients (median 2, mean 2.80, range 1-12). Conclusion: Aboriginal patients had a significantly higher incidence of lung metastases, and significantly more frequent involvement of ipsilateral and contralateral neck lymph nodes. Aboriginal patients also had significantly more advanced disease at presentation with a higher stage at diagnosis. We are performing further analyses to investigate explanations for these findings.

Keywords: head and neck cancer, Aboriginal, metastases, locoregional, pattern of relapse, sites of disease

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Authors: Thomas Louis, Irina Primac, Florent Morfoisse, Tania Durre, Silvia Blacher, Agnes Noel

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In vitro and in vivo lymphangiogenesis assays are essential for the identification of potential lymphangiogenic agents and the screening of pharmacological inhibitors. In the present study, we analyse three biological models: in vitro lymphatic endothelial cell spheroids, in vivo ear sponge assay, and in vivo lymph node colonisation by tumour cells. These assays provide suitable 3D models to test pro- and anti-lymphangiogenic factors or drugs. 3D images were acquired by confocal laser scanning and light sheet fluorescence microscopy. Virtual scan microscopy followed by 3D reconstruction by image aligning methods was also used to obtain 3D images of whole large sponge and ganglion samples. 3D reconstruction, image segmentation, skeletonisation, and other image processing algorithms are described. Fixed and time-lapse imaging techniques are used to analyse lymphatic endothelial cell spheroids behaviour. The study of cell spatial distribution in spheroid models enables to detect interactions between cells and to identify invasion hierarchy and guidance patterns. Global measurements such as volume, length, and density of lymphatic vessels are measured in both in vivo models. Branching density and tortuosity evaluation are also proposed to determine structure complexity. Those properties combined with vessel spatial distribution are evaluated in order to determine lymphangiogenesis extent. Lymphatic endothelial cell invasion and lymphangiogenesis were evaluated under various experimental conditions. The comparison of these conditions enables to identify lymphangiogenic agents and to better comprehend their roles in the lymphangiogenesis process. The proposed methodology is validated by its application on the three presented models.

Keywords: 3D image segmentation, 3D image skeletonisation, cell invasion, confocal microscopy, ear sponges, light sheet microscopy, lymph nodes, lymphangiogenesis, spheroids

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Authors: Yih-Chien Chen, Tse-Lung Lin

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The microwave characteristics of NdTi₍₀.₅₋ₓ₎GeₓMo₀.₅O₄ are studied to determine the feasibility of their use in the liquid sensor. The microwave characteristics of NdTi₍₀.₅₋ₓ₎GeₓMo₀.₅O₄ are determined using X-ray diffraction (XRD) patterns. The permittivity (𝜀r) of NdTi₍₀.₄₉₎Ge₀.₀₁Mo₀.₅O₄ that is sintered at 1425 ℃ for 4 h is 17.6, the unloaded quality factor (Qu×f) is 33,400 GHz, and it has a temperature coefficient at the resonance frequency (TCF) of -30.7 ppm/℃. The proposed liquid sensor is at the 5G FR1 bands.

Keywords: NdTi₍₀.₅₋ₓ₎GeₓMo₀.₅O₄, X-ray diffraction pattern, permittivity, Unloaded quality factor

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Authors: Ahcene Boucied

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In this paper, a case study is conducted to analyze the effectiveness of web pages designed in Barbados for the tourism and hospitality industry. The assessment is made from two perspectives: to understand how the Barbados’ tourism industry is using the web, and to identify the effect of information technology on economic issues. In return, this is used: (a) to provide interested parties with accurate information and marketing insight necessary for decision making for electronic commerce/e-commerce, and (b) to demonstrate pragmatic difficulties in searching and designing web pages.

Keywords: segmentation, tourism stakeholders, destination marketing, case study

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Authors: Esther Friedlander, Philip Friedlander

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The use of immunotherapy that inhibits programmed death-1 (PD-1) or its ligand PD-L1 confers survival benefits in patients with non-small cell lung cancer (NSCLC). However, approximately 45% of patients experience primary treatment resistance, necessitating the development of strategies to improve efficacy. While the renin-angiotensin system (RAS) has systemic hemodynamic effects, tissue-specific regulation exists along with modulation of immune activity in part through regulation of myeloid cell activity, leading to the hypothesis that RAS inhibition may improve anti-PD-1/L-1 efficacy. A retrospective analysis was conducted that included 173 advanced solid tumor cancer patients treated at Valley Hospital, a community Hospital in New Jersey, USA, who were treated with a PD-1/L-1 inhibitor in a defined time period showing a statistically significant relationship between RAS pathway inhibition (RASi through concomitant treatment with an ACE inhibitor or angiotensin receptor blocker) and positive efficacy to the immunotherapy that was independent of age, gender and cancer type. Subset analysis revealed strong numerical benefit for efficacy in both patients with squamous and nonsquamous NSCLC as determined by documented clinician assessment of efficacy and by duration of therapy. A PUBMED literature search was now conducted to identify studies assessing the effect of RAS pathway inhibition on anti-PD-1/L1 efficacy in advanced solid tumor patients and compare these findings to those seen in the Valley Hospital retrospective study with a focus on NSCLC specifically. A total of 11 articles were identified assessing the effects of RAS pathway inhibition on the efficacy of checkpoint inhibitor immunotherapy in advanced cancer patients. Of the 11 studies, 10 assessed the effect on survival of RASi in the context of treatment with anti-PD-1/PD-L1, while one assessed the effect on CTLA-4 inhibition. Eight of the studies included patients with NSCLC, while the remaining 2 were specific to genitourinary malignancies. Of the 8 studies, two were specific to NSCLC patients, with the remaining 6 studies including a range of cancer types, of which NSCLC was one. Of these 6 studies, only 2 reported specific survival data for the NSCLC subpopulation. Patient characteristics, multivariate analysis data and efficacy data seen in the 2 NSLCLC specific studies and in the 2 basket studies, which provided data on the NSCLC subpopulation, were compared to that seen in the Valley Hospital retrospective study supporting a broader effect of RASi on anti-PD-1/L1 efficacy in advanced NSLCLC with the majority of studies showing statistically significant benefit or strong statistical trends but with one study demonstrating worsened outcomes. This comparison of studies extends published findings to the community hospital setting and supports prospective assessment through randomized clinical trials of efficacy in NSCLC patients with pharmacodynamic components to determine the effect on immune cell activity in tumors and on the composition of the tumor microenvironment.

Keywords: immunotherapy, cancer, angiotensin, efficacy, PD-1, lung cancer, NSCLC

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Authors: S. B. R. Slagmulder

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Monitoring inspiratory effort and dynamic lung stress in patients on pressure support ventilation in the ICU is important for protecting against self inflicted lung injury (P-SILI) and diaphragm dysfunction. Strategies to address the detrimental effects of respiratory drive and effort can lead to improved patient outcomes. Two non-invasive estimation methods, occlusion pressure (Pocc) and P0.1, have been proposed for achieving lung and diaphragm protective ventilation. However, their relationship and interpretation in neuro ICU patients is not well understood. P0.1 is the airway pressure measured during a 100-millisecond occlusion of the inspiratory port. It reflects the neural drive from the respiratory centers to the diaphragm and respiratory muscles, indicating the patient's respiratory drive during the initiation of each breath. Occlusion pressure, measured during a brief inspiratory pause against a closed airway, provides information about the inspiratory muscles' strength and the system's total resistance and compliance. Research Objective: Understanding the relationship between Pocc and P0.1 in brain-injured patients can provide insights into the interpretation of these values in pressure support ventilation. This knowledge can contribute to determining extubation readiness and optimizing ventilation strategies to improve patient outcomes. The central goal is to asses a study protocol for determining the relationship between Pocc and P0.1 in brain-injured patients on pressure support ventilation and their ability to predict successful extubation. Additionally, comparing these values between brain-damaged and non-brain-damaged patients may provide valuable insights. Key Areas of Inquiry: 1. How do Pocc and P0.1 values correlate within brain injury patients undergoing pressure support ventilation? 2. To what extent can Pocc and P0.1 values serve as predictive indicators for successful extubation in patients with brain injuries? 3. What differentiates the Pocc and P0.1 values between patients with brain injuries and those without? Methodology: P0.1 and occlusion pressures are standard measurements for pressure support ventilation patients, taken by attending doctors as per protocol. We utilize electronic patient records for existing data. Unpaired T-test will be conducted to compare P0.1 and Pocc values between both study groups. Associations between P0.1 and Pocc and other study variables, such as extubation, will be explored with simple regression and correlation analysis. Depending on how the data evolve, subgroup analysis will be performed for patients with and without extubation failure. Results: While it is anticipated that neuro patients may exhibit high respiratory drive, the linkage between such elevation, quantified by P0.1, and successful extubation remains unknown The analysis will focus on determining the ability of these values to predict successful extubation and their potential impact on ventilation strategies. Conclusion: Further research is pending to fully understand the potential of these indices and their impact on mechanical ventilation in different patient populations and clinical scenarios. Understanding these relationships can aid in determining extubation readiness and tailoring ventilation strategies to improve patient outcomes in this specific patient population. Additionally, it is vital to account for the influence of sedatives, neurological scores, and BMI on respiratory drive and occlusion pressures to ensure a comprehensive analysis.

Keywords: brain damage, diaphragm dysfunction, occlusion pressure, p0.1, respiratory drive

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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: Rossella Resi

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This paper describes a project carried out in an Italian school with English learning pupils combining three didactic tools which are attested to be relevant for the success of young learner’s language curriculum: the use of technology, the intralingual and interlingual mediation (according to CEFR) and the cultural dimension. Aim of this project was to test a technological hands-on translation activity like subtitling in a formal teaching context and to exploit its potential as motivational tool for developing listening and writing, translation and cross-cultural skills among language learners. The activities proposed involved the use of professional subtitling software called Aegisub and culture-specific films. The workshop was optional so motivation was entirely based on the pleasure of engaging in the use of a realistic subtitling program and on the challenge of meeting the constraints that a real life/work situation might involve. Twelve pupils in the age between 16 and 18 have attended the afternoon workshop. The workshop was organized in three parts: (i) An introduction where the learners were opened up to the concept and constraints of subtitling and provided with few basic rules on spotting and segmentation. During this session learners had also the time to familiarize with the main software features. (ii) The second part involved three subtitling activities in plenum or in groups. In the first activity the learners experienced the technical dimensions of subtitling. They were provided with a short video segment together with its transcription to be segmented and time-spotted. The second activity involved also oral comprehension. Learners had to understand and transcribe a video segment before subtitling it. The third activity embedded a translation activity of a provided transcription including segmentation and spotting of subtitles. (iii) The workshop ended with a small final project. At this point learners were able to master a short subtitling assignment (transcription, translation, segmenting and spotting) on their own with a similar video interview. The results of these assignments were above expectations since the learners were highly motivated by the authentic and original nature of the assignment. The subtitled videos were evaluated and watched in the regular classroom together with other students who did not take part to the workshop.

Keywords: ICT, L2, language learning, language mediation, subtitling

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Authors: M. Yadegari

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The thyroid gland is the largest classic endocrine organ that effects many organs of the body and plays a significant role in the process of Metabolism in animals. The aim of this study was to investigate the prevalence of thyroid disorders diagnosed by ultrasound and microscopic Lesions of the thyroid during the slaughter of apparently healthy One Humped Camels (Camelus dromedarius) in Iran. Randomly, 520 male camels (With an age range of 4 to 8 years), were studied in 2012 to 2013. The Camels’ thyroid glands were evaluated by sonographic examination. In both longitudinal and transverse view and then tissue sections were provide and stained with H & E and finally examined by light microscopy. The results obtained indicated the following: hyperplastic goiter (21%), degenerative changes (12%), follicular cysts (8%), follicular atrophy (4%), nodular hyperplasia (3%), adenoma (1%), carcinoma (1%) and simple goiter colloid (1%). Ultrasound evaluation of thyroid gland in adenoma and carcinoma showed enlargement and irregular of the gland, decreased echogenicity, and the heterogeneous thyroid parenchyma. Also, in follicular cysts were observed in the enlarged gland with no echo structures of different sizes and decreased echogenicity as a local or general. In nodular hyperplasia, increase echogenicity and heterogeneous parenchymal were seen. These findings suggest the use of Ultrasound as a screening test in the diagnosis of complications of thyroid disorders. Pathology also to be used for the diagnosis of thyroid problems and other side effects.

Keywords: thyroid gland, one humped camel, sonography, pathology

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Authors: Behcet Al, Mustafa Bogan, Mehmet Murat Oktay, Suat Zengin, Hasan Bayram

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Objective: In the last two decades there is a strong scientific interest regarding the role of aerosols for the Earth’s climate and associated changes. Aerosol particles are very important to the Earth-atmosphere climate system playing a crucial role in cloud and precipitation processes, air quality and climate. Here, we evaluated the association between saharran dust and emergency department admission, hospitalization, and mortality. Method: The records of admission to emergency department of Gaziantep University and the dust stroms of 31 months were studied. Patients admitted to ED at dust strom with chronic obstructive lung disease (COLD), asthma bronchiale (AB), serebrovascular events (SVE), acute myocardial infarction (AMI), stabile and unstabile angina pectoris (SAAP andUSAP); and the days with and without dust stroms were included. The study was realized from March 2010 to October 2012. The admission of three days before strom (group 1), during strom days (group 2) and three days after strom (group 3) were determined. The mean level of dust PM10 particulate was calculated, and the results were compared. Results: 5864 patients with chronic obstructive lung disease, asthma bronchiale, serebrovascular events, acute myocardial infarction, stabile and unstabile angyina pectoris admitted during the days with and without dust stroms. 28 dust stroms ocurred during 31 months. The totaliy of stroms continiued 78 days. Of admissions, 35.5% (n=2075) were in group1, 29.8% (n=1746) in group 2, and 34.8% (n=2043) were in group 3. The mean of PM10 for groups (group 1, 2 and 3) were 78.53 mg/m3 (range 19–276) particulate, 108.7 mg/m3 (range 34–631) particulate, and 60.9 mg/m3 (range 17–160) particulate respectively. The mean admission per a day for groups were 24.86, 22.55, and 24.50 respectively. The mortality was 12 in group 1, 12 in group 2, and 17 in grou 3. The hospitalization ratio for groups were 0.24, 0.27, and 0.27 respectively. Conclusion: However, the mean level of PM10 particulate for groups 2 (in dust strom days) is significantly higher (p=0.001) than the days before (group 1) and after (group 3) dust stroms, the mean admissions/day, hostilalization and mortality related to deseases (COLD, AB, SVE, AMI, SAAP andUSA) for group 2 is lower than the group 1 and group 3.

Keywords: Saharran dust, PM10 particulate, emergency department admission, mortality

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Authors: Kara J. Coffman-Rea, Karen E. Samonds

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Microplastic pollution is an urgent global threat to our planet and human health. Microplastic particles have been detected within our food, water, and atmosphere, and found within the human stool, placenta, and lung tissue. However, most spectrometric microplastic detection methods require chemical digestion which can alter or destroy microplastic particles and makes it impossible to acquire information about their in-situ distribution. MALDI TOF MS (Matrix-assisted laser desorption ionization-time of flight mass spectrometry) is an analytical method using a soft ionization technique that can be used for polymer analysis. This method provides a valuable opportunity to both acquire information regarding the in-situ distribution of microplastics and also minimizes the destructive element of chemical digestion. In addition, MALDI TOF MS allows for expanded analysis of the microplastics including detection of specific additives that may be present within them. MALDI TOF MS is particularly sensitive to sample preparation and has not yet been used to analyze environmental microplastics within their specific location (e.g., biological tissues, sediment, water). In this study, microplastics were created using polyethylene gloves, polystyrene micro-foam, and polyethylene terephthalate cable sleeving. Plastics were frozen using liquid nitrogen and ground to obtain small fragments. An artificial tissue was created using a cellulose sponge as scaffolding coated with a MaxGel Extracellular Matrix to simulate human lung tissue. Optimal preparation techniques (e.g., matrix, cationization reagent, solvent, mixing ratio, laser intensity) were first established for each specific polymer type. The artificial tissue sample was subsequently spiked with microplastics, and specific polymers were detected using MALDI-TOF-MS. This study presents a novel method for the detection of environmental polyethylene, polyethylene terephthalate, and polystyrene microplastics within a complex sample. Results of this study provide an effective method that can be used in future microplastics research and can aid in determining the potential threats to environmental and human health that they pose.

Keywords: environmental plastic pollution, MALDI-TOF MS, microplastics, polymer identification

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Authors: Mohamed Alsafy, Samir El-Gendy, Ashraf Karkoura, Doha Shokry

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The purpose of the current study was to investigate the development of the chicken ovary. One hundred fertilized egg of Alexandria breed of chicken used. The whole embryo has undergone the light microscopic examination at HH20 (E.3), HH21 (E.3.5), HH23 (E.4), HH29 (E.6) and HH34 (E.8). The ovary has undergone the light microscopic examination at HH38 (E.12) and HH42 (E.16), SEM at HH26 (E.5), HH29 (E.6), HH36 (E.10), HH38 (E.12), HH39 (E.13) and HH42 (E.16), TEM at HH38 (E.12) and HH42 (E.16). The genital ridge appeared by a thickening of the coelomic epithelium medioventral surface of the developing mesonephroi at HH20 (E.3). The boundaries of the undifferentiating gonads defined clearly separated from the mesonephroi. The undifferentiated gonads bulged as a distinct organ in the coelomic cavity at HH23 (E.4). At the initial stages of the gonadogenesis, the germinal epithelium was stratified squamous epithelium. The PGCs appeared at the genital ridge at HH21 (E.3.5). The PGCs observed at the dorsal mesentery with few microvilli and showed positive PAS reaction due to the glycogen content in their cytoplasm. The left-right gonadal asymmetry firstly detected by the number of PGCs migrating toward the left gonadal ridge more than the right at HH20 (E.3) and the macroscopic examination of gonadal asymmetry began at HH34 (E.8). The left ovary appeared a smooth rod-shape, its stroma showed lipid droplets, and its parenchyma showed an extensive arrangement of interstitial cords at HH42 (E.16).

Keywords: ovary, Alexandria chicken, light microscopy, SEM, TEM

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Authors: Janani Selvaraj, M. Prashanthi Devi, P. B. Harathi

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Epidemiologic studies conducted over several decades have provided evidence to suggest that long-term exposure to elevated ambient levels of particulate air pollution is associated with increased mortality. Air quality risk management is significant in developing countries and it highlights the need to understand the role of ecologic covariates in the association between air pollution and mortality. Several new methods show promise in exploring the geographical distribution of disease and the identification of high risk areas using epidemiological maps. However, the addition of the temporal attribute would further give us an in depth idea of the disease burden with respect to forecasting measures. In recent years, new methods developed in the reanalysis were useful for exploring the spatial structure of the data and the impact of spatial autocorrelation on estimates of risk associated with exposure to air pollution. Based on this, our present study aims to explore the spatial and temporal distribution of the lung cancer cases in the Coimbatore district of Tamil Nadu in relation to air pollution risk areas. A spatio temporal moving average method was computed using the CrimeStat software and visualized in ArcGIS 10.1 to document the spatio temporal movement of the disease in the study region. The random walk analysis performed showed the progress of the peak cancer incidences in the intersection regions of the Coimbatore North and South taluks that include major commercial and residential regions like Gandhipuram, Peelamedu, Ganapathy, etc. Our study shows evidence that daily exposure to high air pollutant concentration zones may lead to the risk of lung cancer. The observations from the present study will be useful in delineating high risk zones of environmental exposure that contribute to the increase of cancer among daily commuters. Through our study we suggest that spatially resolved exposure models in relevant time frames will produce higher risks zones rather than solely on statistical theory about the impact of measurement error and the empirical findings.

Keywords: air pollution, cancer, spatio-temporal analysis, India

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