Search results for: endoscopic diagnosis

Authors: S. Alireza Mirghasemi, Elly Trepman, Mohammad Saleh Sadeghi, Narges Rahimi Gabaran, Shervin Rashidinia

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Bone marrow edema syndrome (BMES) is an uncommon and self-limited syndrome characterized by atraumatic extremity pain with unknown of etiology. Symptom onset may include sudden or gradual swelling and pain at rest or during activity, usually at night. This syndrome mostly affects middle-aged men and younger women who have pain in the lower extremities. The most common sites involved with BMES, in decreasing order of frequency, are the bones about the hip, knee, ankle, and foot. The diagnosis of BMES is made with magnetic resonance imaging to exclude other causes of bone marrow edema. The correct diagnosis often is delayed because of the low prevalence and nonspecific signs in the foot and ankle. This delay may intensify bone pain and impair patient function and quality of life. The goal of BMES treatment is to relieve pain and shorten disease duration. Treatment options are limited and may include symptomatic treatment, pharmacologic treatment, and surgery.

Keywords: transient osteoporosis, bone marrow edema syndrome, iloprost, bisphosphonates

Procedia PDF Downloads 363

Authors: Maria L. G. Lourenco, Viviane Y. Hibaru, Keylla H. N. P. Pereira, Fabiana F. Souza, Joao C. P. Ferreira, Simone B. Chiacchio, Luiz H. A. Machado

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Neonatal conjunctivitis, or ophthalmia, is an infection of the conjunctiva or cornea before opening the eyelids. It is believed that immunodeficiency contributes to the development of the condition. This study aims at reporting a case of ophthalmia neonatorum in a dog, in addition to its diagnosis and treatment. A litter of five pug neonates was admitted to the Sao Paulo State University (UNESP) Veterinary Hospital, Botucatu, Sao Paulo, Brazil, with complaints of ocular secretion. The neonates were five days old. The clinical examination revealed that three newborns presented swelling in the ocular region and a purulent secretion in the medial corner of the eye that was exerting pressure on the ocular globes, which are compatible with the description of this disease. The diagnosis was made based on the clinical signs and bacterial culture of the secretion, which revealed the presence of bacteria belonging to the genus Staphylococcus sp. The laboratory assays did not reveal any alterations. The treatment was instituted gently, opening the eyelids early and cleaning the purulent ocular secretion with saline solution. An ophthalmic ointment with retinol, amino acids, methionine, and chloramphenicol (Epitezan®) was prescribed four times a day for seven days. Blood plasma (2 mL/100 g) was administered subcutaneously because bacterial infections in neonates may represent a failure in the transference of passive immunity. A more thorough cleaning of the environment was also recommended. Neonatal conjunctivitis has a simple diagnosis and treatment. If not treated early, it can evolve to adherence of the eyelids to the cornea, ulceration, and perforation of the cornea. Therefore, the prognosis is favorable as long as the condition is diagnosed early, and the treatment is instituted quickly.

Keywords: ophthalmia neonatorum, neonatal infection, puppy, newborn

Procedia PDF Downloads 140

Authors: Bandana Koirala, Shivalal Sharma

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Introduction: Gingival enlargements are quite common and may be either inflammatory, non-inflammatory or a combination of both. Idiopathic gingival enlargement is a rare condition with a proliferative fibrous lesion of the gingival tissue that causes esthetic and functional problems. It is of undetermined etiology. Case Description: This case report addresses the diagnosis and treatment of a case of idiopathic gingival enlargement in a 9-year-old male patient. The patient presented with a generalized diffuse gingival enlargement involving the entire maxillary and the mandibular arch with extension on occlusal, buccal, lingual, and palatal surfaces with just parts of occlusal surfaces of few upper and lower molars visible resulting in open mouth, difficulty in mastication and speech. Biopsy report confirmed the diagnosis of fibromatosis gingivae. Gingivectomy was carried out in all four quadrants by using external bevel incision. Conclusion: Though total esthetics could not be restored due to unusual bony enlargement, the general appearance improved satisfactorily. Treatment after complete excision however, improved the masticatory competence to a great extent.

Keywords: idiopathic gingival fibromatosis, gingival enlargement, gingivectomy, medical and health sciences

Procedia PDF Downloads 329

Authors: Maomao Cao

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Objective: To test the performance of ctDNA methylation for the detection of liver cancer. Methods: A total of 1233 individuals have been recruited in 2017. 15 male and 15 female samples (including 10 cases of liver cancer) were randomly selected in the present study. CfDNA was extracted by MagPure Circulating DNA Maxi Kit. The concentration of cfDNA was obtained by Qubit™ dsDNA HS Assay Kit. A pre-constructed predictive model was used to analyze methylation data and to give a predictive score for each cfDNA sample. Individuals with a predictive score greater than or equal to 80 were classified as having liver cancer. CT tests were considered the gold standard. Sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) for the diagnosis of liver cancer were calculated. Results: 9 patients were diagnosed with liver cancer according to the prediction model (with high sensitivity and threshold of 80 points), with scores of 99.2, 91.9, 96.6, 92.4, 91.3, 92.5, 96.8, 91.1, and 92.2, respectively. The sensitivity, specificity, positive predictive value, and negative predictive value of ctDNA methylation for the diagnosis of liver cancer were 0.70, 0.90, 0.78, and 0.86, respectively. Conclusions: ctDNA methylation could be an acceptable diagnostic modality for the detection of liver cancer.

Keywords: liver cancer, ctDNA methylation, detection, diagnostic performance

Procedia PDF Downloads 151

Authors: Shima Soltanzadeh, Mohammad Hosain Fazel Zarandi, Mojtaba Barzegar Astanjin

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Diagnosis of male infertility by the laboratory tests is expensive and, sometimes it is intolerable for patients. Filling out the questionnaire and then using classification method can be the first step in decision-making process, so only in the cases with a high probability of infertility we can use the laboratory tests. In this paper, we evaluated the performance of four classification methods including naive Bayesian, neural network, logistic regression and fuzzy c-means clustering as a classification, in the diagnosis of male infertility due to environmental factors. Since the data are unbalanced, the ROC curves are most suitable method for the comparison. In this paper, we also have selected the more important features using a filtering method and examined the impact of this feature reduction on the performance of each methods; generally, most of the methods had better performance after applying the filter. We have showed that using fuzzy c-means clustering as a classification has a good performance according to the ROC curves and its performance is comparable to other classification methods like logistic regression.

Keywords: classification, fuzzy c-means, logistic regression, Naive Bayesian, neural network, ROC curve

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Authors: Ana Ferraz, Martim Santos, M. Graça Pereira

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Distress among parents of children with acute lymphoblastic leukemia (ALL) is common during treatment and can persist several years post-diagnosis, impacting the adjustment of children and parents themselves. Current evidence is needed to examine the scope and nature of parental distress in childhood ALL. This review focused on associated variables, predictors, and outcomes of parental distress following their ALL diagnosis of their child. PubMed, Web of Science, and PsycINFO databases were searched for English and Spanish papers published from 1983 to 2021. PRISMA statement was followed, and papers were evaluated through a standardized methodological quality assessment tool (NHLBI). Of the 28 papers included, 16 were evaluated as fair, eight as good, and four as poor. Regarding results, 11 papers reported subgroup differences, and 15 found potential predictors of parental distress, including sociodemographic, psychosocial, psychological, family, health, and ALL-specific variables. Significant correlations were found between parental distress, social support, illness cognitions, and resilience, as well as contradictory results regarding the impact of sociodemographic variables on parental distress. Family cohesion and caregiver burden were associated with distress, and the use of healthy coping strategies was associated with less anxiety. Caregiver strain contributed to distress, and the overall impact of illness positively predicted anxiety in mothers and somatization in fathers. Differences in parental distress were found regarding group risk, time since diagnosis, and treatment phases. Thirteen papers explored the outcomes of parental distress on psychological, family, health, and social/education outcomes. Parental distress was the most important predictor of family strain. Significant correlations were found between parental distress at diagnosis and further psychological adjustment of parents themselves and their children. Most papers reported correlations between parental distress on children’s adjustment and quality of life, although few studies reported no association. Correlations between maternal depression and child participation in education and social life were also found. Longitudinal studies are needed to better understand parental distress and its consequences on health outcomes, in particular. Future interventions should focus mainly on parents on distress reduction and psychological adjustment, both in parents and children over time.

Keywords: childhood acute lymphoblastic leukemia, family, parental distress, psychological adjustment, quality of life

Procedia PDF Downloads 108

Authors: Angelis P. Barlampas

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Theoretical background Disorders of fixation and rotation of the large intestine, result in the existence of its parts in ectopic anatomical positions. In case of symptomatology, the clinical picture is complicated by the possible symptomatology of the neighboring anatomical structures and a differential diagnostic problem arises. Target The purpose of this work is to demonstrate the difficulty of revealing the real cause of abdominal pain, in cases of anatomical variants and the decisive contribution of imaging and especially that of computed tomography. Methods A patient came to the emergency room, because of acute pain in the right hypochondrium. Clinical examination revealed tenderness in the gallbladder area and a positive Murphy's sign. An ultrasound exam depicted a normal gallbladder and the patient was referred for a CT scan. Results Flexible, unfixed ascending colon and cecum, located in the anatomical region of the right mesentery. Opacities of the surrounding peritoneal fat and a small linear concentration of fluid can be seen. There was an appendix of normal anteroposterior diameter with the presence of air in its lumen and without clear signs of inflammation. There was an impression of possible inflammatory swelling at the base of the appendix, (DD phenomenon of partial volume; e.t.c.). Linear opacities of the peritoneal fat in the region of the second loop of the duodenum. Multiple diverticula throughout the colon. Differential Diagnosis The differential diagnosis includes the following: Inflammation of the base of the appendix, diverticulitis of the cecum-ascending colon, a rare case of second duodenal loop ulcer, tuberculosis, terminal ileitis, pancreatitis, torsion of unfixed cecum-ascending colon, embolism or thrombosis of a vascular intestinal branch. Final Diagnosis There is an unfixed cecum-ascending colon, which is exhibiting diverticulitis.

Keywords: unfixed cecum-ascending colon, abdominal pain, malrotation, abdominal CT, congenital anomalies

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Authors: Babina Aryal

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Background: The diagnosis of pancreatitis is generally based on clinical and laboratory findings; however, Computed Tomography (CT) is an imaging technique of choice specially Contrast Enhanced Computed Tomography (CECT) shows morphological characteristic findings that allow for establishing the diagnosis of pancreatitis and determining the extent of disease severity which is done along with the administration of appropriate contrast medium. The purpose of this study was to compare Computed Tomography Dose Index (CTDI), Dose Length Product (DLP) and Effective Dose (ED) among male and female patients from Contrast Enhanced Computed Tomography (CECT) Pancreatitis Protocol. Methods: This retrospective study involved data collection based on clinical/laboratory/ultrasonography diagnosis of Pancreatitis and has undergone CECT Abdomen pancreatitis protocol. data collection involved detailed information about a patient's Age and Gender, Clinical history, Individual Computed Tomography Dose Index and Dose Length Product and effective dose. Results: We have retrospectively collected dose data from 150 among which 127 were males and 23 were females. The values obtained from the display of the CT screen were measured, calculated and compared to determine whether the CTDI, DLP and ED values were similar or not. CTDI for females was more as compared to males. The differences in CTDI values for females and males were 32.2087 and 37.1609 respectively. DLP values and Effective dose for both the genders did not show significant differences. Conclusion: This study concluded that there were no more significant changes in the DLP and ED values among both the genders however we noticed that female patients had more CTDI than males.

Keywords: computed tomography, contrast enhanced computed tomography, computed tomography dose index, dose length product, effective dose

Procedia PDF Downloads 118

Authors: T. S. Sowmya Bhaskaran, Shekhar Seshadri

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This study aims to study the clinical features of with a history of Child Sexual Abuse (CSA). A chart review of 40 children (<16 years) with history of CSA evaluated at the Department of Child and Adolescent Psychiatry of NIMHANS during a two year period was performed. Results:The most common form of abuse was contact penetrative abuse (65%) followed by non-contact penetrative abuse (32.5%). 75% (N=30) had a psychiatric diagnosis at baseline. 50% of these children had one or more psychiatric comorbidities. Anxiety disorder was the most common diagnosis (27.5%) which included PTSD (11%) followed by Depressive disorder (25.2%). Children abused by multiple perpetrators were found to be more likely to have depression, to having a comorbid psychiatric disorder and more prone to exhibit sexualized behaviour. Children who also experienced physical violence at home were more likely to develop psychiatric illness following child sexual abuse. Psychiatric morbidity is high in clinic population of children with history of CSA. It is important to increase the awareness regarding the consequences of CSA in order to increase help seeking.

Keywords: child sexual abuse, India, tertiary care centre, clinical characteristics

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Authors: Haoqi Gao, Koichi Ogawara

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Retinal vascular segmentation of color fundus is the basis of ophthalmic computer-aided diagnosis and large-scale disease screening systems. Early screening of fundus diseases has great value for clinical medical diagnosis. The traditional methods depend on the experience of the doctor, which is time-consuming, labor-intensive, and inefficient. Furthermore, medical images are scarce and fraught with legal concerns regarding patient privacy. In this paper, we propose a new Generative Adversarial Network based on CycleGAN for retinal fundus images. This method can generate not only synthetic fundus images but also generate corresponding segmentation masks, which has certain application value and challenge in computer vision and computer graphics. In the results, we evaluate our proposed method from both quantitative and qualitative. For generated segmented images, our method achieves dice coefficient of 0.81 and PR of 0.89 on DRIVE dataset. For generated synthetic fundus images, we use ”Toy Experiment” to verify the state-of-the-art performance of our method.

Keywords: retinal vascular segmentations, generative ad-versarial network, cyclegan, fundus images

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Authors: Azadeh Bashiri

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Introduction: Lack of proper diagnosis and inadequate treatment of asthma leads to physical and financial complications. This study aimed to use data mining techniques and creating a neural network intelligent system for diagnosis of asthma. Methods: The study population is the patients who had visited one of the Lung Clinics in Tehran. Data were analyzed using the SPSS statistical tool and the chi-square Pearson's coefficient was the basis of decision making for data ranking. The considered neural network is trained using back propagation learning technique. Results: According to the analysis performed by means of SPSS to select the top factors, 13 effective factors were selected, in different performances, data was mixed in various forms, so the different models were made for training the data and testing networks and in all different modes, the network was able to predict correctly 100% of all cases. Conclusion: Using data mining methods before the design structure of system, aimed to reduce the data dimension and the optimum choice of the data, will lead to a more accurate system. Therefore, considering the data mining approaches due to the nature of medical data is necessary.

Keywords: asthma, data mining, Artificial Neural Network, intelligent system

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Authors: M. Naeimi, H. Aghazadeh, E. Afjei, A. Siadatan

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In this paper, a novel view of air gap magnetic field analysis of synchronous reluctance motor and permanent magnet assisted synchronous reluctance motor under static eccentricity to provide the precise fault diagnosis based on three-dimensional finite element method is presented. Analytical nature of this method makes it possible to simulate reliable and precise model by considering the end effects and axial fringing effects. The results of the three-dimensional finite element analysis of synchronous reluctance motor and permanent magnet synchronous reluctance motor such as flux linkage, flux density, and compression both of SynRM and PM-SynRM for various eccentric motor conditions are obtained and analyzed. These results present useful information regarding to the detection of static eccentricity.

Keywords: synchronous reluctance motor (SynRM), permanent magnet assisted synchronous reluctance motor (PMaSynRM), finite element method, static eccentricity, fault analysis

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Authors: Jaiden Xuan Schraut, Leon Liu, Yiqiao Yin

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Computer vision in medical diagnosis has achieved a high level of success in diagnosing diseases with high accuracy. However, conventional classifiers that produce an image to-label result provides insufficient information for medical professionals to judge and raise concerns over the trust and reliability of a model with results that cannot be explained. In order to gain local insight into cancerous regions, separate tasks such as imaging segmentation need to be implemented to aid the doctors in treating patients, which doubles the training time and costs which renders the diagnosis system inefficient and difficult to be accepted by the public. To tackle this issue and drive AI-first medical solutions further, this paper proposes a multi-output network that follows a U-Net architecture for image segmentation output and features an additional convolutional neural networks (CNN) module for auxiliary classification output. Class activation maps are a method of providing insight into a convolutional neural network’s feature maps that leads to its classification but in the case of lung diseases, the region of interest is enhanced by U-net-assisted Class Activation Map (CAM) visualization. Therefore, our proposed model combines image segmentation models and classifiers to crop out only the lung region of a chest X-ray’s class activation map to provide a visualization that improves the explainability and is able to generate classification results simultaneously which builds trust for AI-led diagnosis systems. The proposed U-Net model achieves 97.61% accuracy and a dice coefficient of 0.97 on testing data from the COVID-QU-Ex Dataset which includes both diseased and healthy lungs.

Keywords: multi-output network model, U-net, class activation map, image classification, medical imaging analysis

Procedia PDF Downloads 203

Authors: Yunwei Zhang, Qiaochu Tang, Yao Zhang, Jiabin Wang, Ulrich Stimming, Alpha Lee

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Forecasting the state of health and remaining useful life of Li-ion batteries is an unsolved challenge that limits technologies such as consumer electronics and electric vehicles. Here we build an accurate battery forecasting system by combining electrochemical impedance spectroscopy (EIS) -- a real-time, non-invasive and information-rich measurement that is hitherto underused in battery diagnosis -- with Gaussian process machine learning. We collect over 20,000 EIS spectra of commercial Li-ion batteries at different states of health, states of charge and temperatures -- the largest dataset to our knowledge of its kind. Our Gaussian process model takes the entire spectrum as input, without further feature engineering, and automatically determines which spectral features predict degradation. Our model accurately predicts the remaining useful life, even without complete knowledge of past operating conditions of the battery. Our results demonstrate the value of EIS signals in battery management systems.

Keywords: battery degradation, machine learning method, electrochemical impedance spectroscopy, battery diagnosis

Procedia PDF Downloads 148

Authors: Taha SamadSoltani, Peyman Rezaei Hachesu, Marjan GhaziSaeedi, Maryam Zolnoori

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Introduction: Data mining defined as a process to find patterns and relationships along data in the database to build predictive models. Application of data mining extended in vast sectors such as the healthcare services. Medical data mining aims to solve real-world problems in the diagnosis and treatment of diseases. This method applies various techniques and algorithms which have different accuracy and precision. The purpose of this study was to apply knowledge discovery and data mining techniques for the diagnosis of asthma based on patient symptoms and history. Method: Data mining includes several steps and decisions should be made by the user which starts by creation of an understanding of the scope and application of previous knowledge in this area and identifying KD process from the point of view of the stakeholders and finished by acting on discovered knowledge using knowledge conducting, integrating knowledge with other systems and knowledge documenting and reporting.in this study a stepwise methodology followed to achieve a logical outcome. Results: Sensitivity, Specifity and Accuracy of KNN, SVM, Naïve bayes, NN, Classification tree and CN2 algorithms and related similar studies was evaluated and ROC curves were plotted to show the performance of the system. Conclusion: The results show that we can accurately diagnose asthma, approximately ninety percent, based on the demographical and clinical data. The study also showed that the methods based on pattern discovery and data mining have a higher sensitivity compared to expert and knowledge-based systems. On the other hand, medical guidelines and evidence-based medicine should be base of diagnostics methods, therefore recommended to machine learning algorithms used in combination with knowledge-based algorithms.

Keywords: asthma, datamining, classification, machine learning

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Authors: M. Bilal Ishfaq, Adnan N. Qureshi

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COVID-19 is the most infectious disease these days, it was first reported in Wuhan, the capital city of Hubei in China then it spread rapidly throughout the whole world. Later on 11 March 2020, the World Health Organisation (WHO) declared it a pandemic. Since COVID-19 is highly contagious, it has affected approximately 219M people worldwide and caused 4.55M deaths. It has brought the importance of accurate diagnosis of respiratory diseases such as pneumonia and COVID-19 to the forefront. In this paper, we propose a hybrid approach for the automated detection of COVID-19 using medical imaging. We have presented the hybridization of manually extracted and convolutional features. Our approach combines Haralick texture features and convolutional features extracted from chest X-rays and CT scans. We also employ a minimum redundancy maximum relevance (MRMR) feature selection algorithm to reduce computational complexity and enhance classification performance. The proposed model is evaluated on four publicly available datasets, including Chest X-ray Pneumonia, COVID-19 Pneumonia, COVID-19 CTMaster, and VinBig data. The results demonstrate high accuracy and effectiveness, with 0.9925 on the Chest X-ray pneumonia dataset, 0.9895 on the COVID-19, Pneumonia and Normal Chest X-ray dataset, 0.9806 on the Covid CTMaster dataset, and 0.9398 on the VinBig dataset. We further evaluate the effectiveness of the proposed model using ROC curves, where the AUC for the best-performing model reaches 0.96. Our proposed model provides a promising tool for the early detection and accurate diagnosis of COVID-19, which can assist healthcare professionals in making informed treatment decisions and improving patient outcomes. The results of the proposed model are quite plausible and the system can be deployed in a clinical or research setting to assist in the diagnosis of COVID-19.

Keywords: COVID-19, feature engineering, artificial neural networks, radiology images

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Authors: T. Bensana, S. Mekhilef

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The methodology of vibration based condition monitoring technology has been developing at a rapid stage in the recent years suiting to the maintenance of sophisticated and complicated machines. The ability of wavelet analysis to efficiently detect non-stationary, non-periodic, transient features of the vibration signal makes it a demanding tool for condition monitoring. This paper presents a methodology for fault diagnosis of rolling element bearings based on wavelet envelope power spectrum technique is analysed in both the time and frequency domains. In the time domain the auto-correlation of the wavelet de-noised signal is applied to evaluate the period of the fault pulses. However, in the frequency domain the wavelet envelope power spectrum has been used to identify the fault frequencies with the single sided complex Laplace wavelet as the mother wavelet function. Results show the superiority of the proposed method and its effectiveness in extracting fault features from the raw vibration signal.

Keywords: preventive maintenance, fault diagnostics, rolling element bearings, wavelet de-noising

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Authors: Eda Jazexhiu-Postoli, Gladiola Hoxha, Ada Simeoni, Sonila Biba

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Background Neonatal hypotonia represents a commonly encountered issue in the Neonatal Intensive Care Unit and newborn nursery. The differential diagnosis is broad, encompassing chromosome abnormalities, primary muscular dystrophies, neuropathies and inborn errors of metabolism. Aim of study Our study describes some of the main clinical features of hypotonia in newborns and presents clinical cases of neonatal hypotonia we treated in our Neonatal unit in the last 3 years. Case reports Four neonates born in our hospital presented with hypotonia after birth, one preterm newborn 35-36 weeks of gestational age and three other term newborns (38-39 weeks of gestational age). Prenatal data revealed a decrease in fetal movements in both cases. Intrapartum meconium-stained amniotic fluid was found in 75% of our hypotonic newborns. Clinical features included inability to establish effective respiratory movements and need for resuscitation in the delivery room, respiratory distress syndrome, feeding difficulties and need for oro-gastric tube feeding, dysmorphic features, hoarse voice and moderate to severe muscular hypotonia. The genetic workup revealed the diagnosis of Autosomal Recessive Congenital Myasthenic Syndrome 1-B, Sotos Syndrome, Spinal Muscular Atrophy Type 1 and Transient Hypotonia of the Newborn. Two out of four hypotonic neonates were transferred to the Pediatric Intensive Care Unit and died at the age of three to five months old. Conclusion Hypotonia is a concerning finding in neonatal care and it is suggested by decreased intrauterine fetal movements, failure to establish first breaths, respiratory distress and feeding difficulties in the neonate. Prognosis is determined by its etiology and time of diagnosis and intervention.

Keywords: hypotonic neonate, respiratory distress, feeding difficulties, fetal movements

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Authors: Geir Kirkebøen

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Most patients with serious diagnoses want to know their prognosis, in particular their expected survival time. As part of the informed consent process, physicians are legally obligated to communicate such information to patients. However, there is no established (evidence based) ‘best practice’ for how to do this. The two questions explored in this study are: How do physicians communicate expected survival time to patients, and how should it be done? We explored the first, descriptive question in a study with Norwegian oncologists as participants. The study had a scenario and a survey part. In the scenario part, the doctors should imagine that a patient, recently diagnosed with a serious cancer diagnosis, has asked them: ‘How long can I expect to live with such a diagnosis? I want an honest answer from you!’ The doctors should assume that the diagnosis is certain, and that from an extensive recent study they had optimal statistical knowledge, described in detail as a right-skewed survival curve, about how long such patients with this kind of diagnosis could be expected to live. The main finding was that very few of the oncologists would explain to the patient the variation in survival time as described by the survival curve. The majority would not give the patient an answer at all. Of those who gave an answer, the typical answer was that survival time varies a lot, that it is hard to say in a specific case, that we will come back to it later etc. The survey part of the study clearly indicates that the main reason why the oncologists would not deliver the mortality prognosis was discomfort with its uncertainty. The scenario part of the study confirmed this finding. The majority of the oncologists explicitly used the uncertainty, the variation in survival time, as a reason to not give the patient an answer. Many studies show that patients want realistic information about their mortality prognosis, and that they should be given hope. The question then is how to communicate the uncertainty of the prognosis in a realistic and optimistic – hopeful – way. Based on psychological research, our hypothesis is that the best way to do this is by explicitly describing the variation in survival time, the (usually) right skewed survival curve of the prognosis, and emphasize to the patient the (small) possibility of being a ‘lucky outlier’. We tested this hypothesis in two scenario studies with lay people as participants. The data clearly show that people prefer to receive expected survival time as a median value together with explicit information about the survival curve’s right skewedness (e.g., concrete examples of ‘positive outliers’), and that communicating expected survival time this way not only provides people with hope, but also gives them a more realistic understanding compared with the typical way expected survival time is communicated. Our data indicate that it is not the existence of the uncertainty regarding the mortality prognosis that is the problem for patients, but how this uncertainty is, or is not, communicated and explained.

Keywords: cancer patients, decision psychology, doctor-patient communication, mortality prognosis

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Authors: Yassa Nacera, Badji Abderrezak, Saidoune Abdelmalek, Houassine Hamza

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Several kinds of faults can occur in a permanent magnet synchronous machine (PMSM) systems: bearing faults, electrically short/open faults, eccentricity faults, and demagnetization faults. Demagnetization fault means that the strengths of permanent magnets (PM) in PMSM decrease, and it causes low output torque, which is undesirable for EVs. The fault is caused by physical damage, high-temperature stress, inverse magnetic field, and aging. Motor current signature analysis (MCSA) is a conventional motor fault detection method based on the extraction of signal features from stator current. a simulation model of the PMSM under partial demagnetization and uniform demagnetization fault was established, and different degrees of demagnetization fault were simulated. The harmonic analyses using the Fast Fourier Transform (FFT) show that the fault diagnosis method based on the harmonic wave analysis is only suitable for partial demagnetization fault of the PMSM and does not apply to uniform demagnetization fault of the PMSM.

Keywords: permanent magnet, diagnosis, demagnetization, modelling

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Authors: Fahad Qureshi

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This paper provides detailed study on the diagnosis of intermittent high vibration spikes at exhaust bearing (Non-Drive End) of Mitsubishi H-25 gas turbine installed in a petrochemical plant in Pakistan. The diagnosis is followed by successful root cause analysis of the issue and recommendations for improving the reliability of machine. Engro Polymer and Chemicals (EPCL), a Chlor Vinyl complex, has a captive power plant consisting of one combined cycle power plant (CCPP), having two gas turbines each having 25 MW capacity (make: Hitachi) and one extraction condensing steam turbine having 15 MW capacity (make: HTC). Besides, one 6.75 MW SGT-200 1S gas turbine (make: Alstom) is also available. In 2018, the organization faced an issue of intermittent high vibration at exhaust bearing of one of H-25 units having tag GT-2101 A, which eventually led to tripping of machine at configured securities. Since the machine had surpassed 64,000 running hours and major inspection was also due, so bearings inspection was performed. Inspection revealed excessive coke deposition at labyrinth where evidence of rotor rub was also present. Bearing clearance was also at upper limit, and slight babbitt (soft metal) chip off was observed at one of its pads so it was preventively replaced. The unit was restated successfully and exhibited no abnormality until October 2020, when these spikes reoccurred, leading to machine trip. Recurrence of the issue within two years indicated that root cause was not properly addressed, so this paper furthers the discussion on in-depth analysis of findings and establishes successful root cause analysis, which captured significant learnings both in terms of machine design deficiencies and gaps in operation & maintenance (O & M) regime. Lastly, revised O& M regime along with set of recommendations are proposed to avoid recurrence.

Keywords: exhaust side bearing, Gas turbine, rubbing, vibration

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Authors: Houda Najeh, Stéphane Ploix, Mahendra Pratap Singh, Karim Chabir, Mohamed Naceur Abdelkrim

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Building systems are highly vulnerable to different kinds of faults and failures. In fact, various faults, failures and human behaviors could affect the building performance. This paper tackles the detection of unreliable sensors in buildings. Different literature surveys on diagnosis techniques for sensor grids in buildings have been published but all of them treat only bias and outliers. Occurences of data gaps have also not been given an adequate span of attention in the academia. The proposed methodology comprises the automatic thresholding for data gap detection for a set of heterogeneous sensors in instrumented buildings. Sensor measurements are considered to be regular time series. However, in reality, sensor values are not uniformly sampled. So, the issue to solve is from which delay each sensor become faulty? The use of time series is required for detection of abnormalities on the delays. The efficiency of the method is evaluated on measurements obtained from a real power plant: an office at Grenoble Institute of technology equipped by 30 sensors.

Keywords: building system, time series, diagnosis, outliers, delay, data gap

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Authors: Abbas Pourreza

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MicroRNAs (miRNAs) are small single-stranded non-coding RNAs. They are almost 18-25 nucleotides long and very conservative through evolution. They are involved in adjusting the expression of numerous genes due to the existence of a complementary region, generally in the 3' untranslated regions (UTR) of target genes, against particular mRNAs in the cell. Also, miRNAs have been proven to be involved in cell development, differentiation, proliferation, and apoptosis. More than 2000 miRNAs have been recognized in human cells, and these miRNAs adjust approximately one-third of all genes in human cells. Dysregulation of miRNA originated from abnormal DNA methylation patterns of the locus, cause to down-regulated or overexpression of miRNAs, and it may affect tumor formation or development of it. Breast cancer (BC) is the most commonly identified cancer, the most prevalent cancer (23%), and the second-leading (14%) mortality in all types of cancer in females. BC can be classified based on the status (+/−) of the hormone receptors, including estrogen receptor (ER), progesterone receptor (PR), and the Receptor tyrosine-protein kinase erbB-2 (ERBB2 or HER2). Currently, there are four main molecular subtypes of BC: luminal A, approximately 50–60 % of BCs; luminal B, 10–20 %; HER2 positive, 15–20 %, and 10–20 % considered Basal (triple-negative breast cancer (TNBC)) subtype. Aberrant expression of miR-145, miR-21, miR-10b, miR-125a, and miR-206 was detected by Stem-loop real-time RT-PCR in BC cases. Breast tumor formation and development may result from down-regulation of a tumor suppressor miRNA such as miR-145, miR-125a, and miR-206 and/or overexpression of an oncogenic miRNA such as miR-21 and miR-10b. MiR-125a, miR-206, miR-145, miR-21, and miR-10b are hugely predicted to be new tumor markers for the diagnosis and prognosis of BC. MiR-21 and miR-125a could play a part in the treatment of HER-2-positive breast cancer cells, while miR-145 and miR-206 could speed up the evolution of cure techniques for TNBC. To conclude, miRNAs will be presented as hopeful molecules to be used in the primary diagnosis, prognosis, and treatment of BC and battle as opposed to its developed drug resistance.

Keywords: breast cancer, HER2 positive, miRNA, TNBC

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Authors: Paula I. Buonfiglio, Carlos David Bruque, Lucia Salatino, Vanesa Lotersztein, Sebastián Menazzi, Paola Plazas, Ana Belén Elgoyhen, Viviana Dalamón

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Hearing loss (HL) is the most prevalent sensorineural disorder affecting about 10% of the global population, with more than half due to genetic causes. About 1 in 500-1000 newborns present congenital HL. Most of the patients are non-syndromic with an autosomal recessive mode of inheritance. To date, more than 100 genes are related to HL. Therefore, the Whole-exome sequencing (WES) technique has become a cost-effective alternative approach for molecular diagnosis. Nevertheless, new challenges arise from the detection of novel variants, in particular missense changes, which can lead to a spectrum of genotype-to-phenotype correlations, which is not always straightforward. In this work, we aimed to identify the genetic causes of HL in isolated and familial cases by designing a multistep approach to analyze target genes related to hearing impairment. Moreover, we performed in silico and in vivo analyses in order to further study the effect of some of the novel variants identified in the hair cell function using the zebrafish model. A total of 650 patients were studied by Sanger Sequencing and Gap-PCR in GJB2 and GJB6 genes, respectively, diagnosing 15.5% of sporadic cases and 36% of familial ones. Overall, 50 different sequence variants were detected. Fifty of the undiagnosed patients with moderate HL were tested for deletions in STRC gene by Multiplex ligation-dependent probe amplification technique (MLPA), leading to 6% of diagnosis. After this initial screening, 50 families were selected to be analyzed by WES, achieving diagnosis in 44% of them. Half of the identified variants were novel. A missense variant in MYO6 gene detected in a family with postlingual HL was selected to be further analyzed. A protein modeling with AlphaFold2 software was performed, proving its pathogenic effect. In order to functionally validate this novel variant, a knockdown phenotype rescue assay in zebrafish was carried out. Injection of wild-type MYO6 mRNA in embryos rescued the phenotype, whereas using the mutant MYO6 mRNA (carrying c.2782C>A variant) had no effect. These results strongly suggest the deleterious effect of this variant on the mobility of stereocilia in zebrafish neuromasts, and hence on the auditory system. In the present work, we demonstrated that our algorithm is suitable for the sequential multigenic approach to HL in our cohort. These results highlight the importance of a combined strategy in order to identify candidate variants as well as the in silico and in vivo studies to analyze and prove their pathogenicity and accomplish a better understanding of the mechanisms underlying the physiopathology of the hearing impairment.

Keywords: diagnosis, genetics, hearing loss, in silico analysis, in vivo analysis, WES, zebrafish

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Authors: Denise Ben-Porath, Tracy Masterson

Abstract:

In the past, individuals who struggled with and sought treatment for mental health difficulties were stigmatized. However, the current generation holds more open attitudes around mental health issues. Indeed, public figures such as Demi Lovato, Naomi Osaka, and Simone Biles have taken to social media to break the silence around mental health, discussing their own struggles and the benefits of treatment. Thus, there is considerable reason to believe that this generation would hold fewer stigmatizing attitudes toward mental health difficulties and treatment compared to previous ones. In this study, we explored possible changes in stigma on mental health diagnosis and treatment seeking behavior between two generations: Gen Z, the current generation, and Gen X, those born between 1965-1980. It was hypothesized that Gen Z would hold less stigmatizing views on mental illness than Gen X. To examine possible changes in stigma attitudes between these two generations, we conducted a cross-generational cohort design by using the same methodology employed 20 years ago from the Ben-Porath (2002) study. Thus, participants were randomly assigned to read one of the following four case vignettes employed in the Ben-Porath (2002) study: (a) “Tom” who has received psychotherapy due to depression (b) “Tom” who has been depressed but received no psychological help, (c) “Tom” who has received medical treatment due to a back pain, or (d) “Tom” who had a back pain but did not receive medical attention. After reading the vignette, participants rated “Tom” on various personality dimensions using the IFQ Questionnaire and answered questions about their frequency of social media use and willingness to seek mental health treatment on a scale from 1-10. Identical to the results 20 years prior, a significant main effect was found for diagnosis with “Tom” being viewed in more negative terms when he was described as having depression vs. a medical condition (back pain) [F (1, 376) = 126.53, p < .001]. However, in the study conducted 20 years earlier, a significant interaction was found between diagnosis and help-seeking behavior [F (1, 376) = 8.28, p < .005]. Specifically, “Tom” was viewed in the most negative terms when described as depressed and seeking treatment. Alternatively, the current study failed to find a significant interaction between depression and help seeking behavior. These findings suggest that while individuals who hold a mental health diagnosis may still be stigmatized as they were 20 years prior, seeking treatment for mental health issues may be less so. Findings are discussed in the context of social media use and its impact on destigmatization.

Keywords: stigma, mental illness, help-seeking, social media

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Authors: Atanu K Samanta, Asim Ali Khan

Abstract:

Due to the acquisition of huge amounts of brain tumor magnetic resonance images (MRI) in clinics, it is very difficult for radiologists to manually interpret and segment these images within a reasonable span of time. Computer-aided diagnosis (CAD) systems can enhance the diagnostic capabilities of radiologists and reduce the time required for accurate diagnosis. An intelligent computer-aided technique for automatic detection of a brain tumor through MRI is presented in this paper. The technique uses the following computational methods; the Level Set for segmentation of a brain tumor from other brain parts, extraction of features from this segmented tumor portion using gray level co-occurrence Matrix (GLCM), and the Artificial Neural Network (ANN) to classify brain tumor images according to their respective types. The entire work is carried out on 50 images having five types of brain tumor. The overall classification accuracy using this method is found to be 98% which is significantly good.

Keywords: brain tumor, computer-aided diagnostic (CAD) system, gray-level co-occurrence matrix (GLCM), tumor segmentation, level set method

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Authors: Eva Karaskova, Jana Volejnikova, Dusan Holub, Maria Velganova-Veghova, Michaela Spenerova, Dagmar Pospisilova

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Background: Hepcidin is the central regulator of iron metabolism. Its production is mainly affected by an iron deficiency and the presence of inflammatory activity in the body. The aim of this study was to compare serum hepcidin levels in paediatric patients with newly diagnosed inflammatory bowel disease and hepcidin levels during maintenance therapy, correlate changes of serum hepcidin levels with selected markers of iron metabolism and inflammation and type of provided treatment. Methods: Children with newly diagnosed Crohn's disease (CD) and ulcerative colitis (UC) were included in this prospective study. Blood and stool samples were collected before treatment (baseline). Serum hepcidin, hemoglobin levels, platelet counts, erythrocyte sedimentation rate (ESR), C-reactive protein (CRP), interleukin-6 (IL 6), ferritin, iron, soluble transferrin receptors, and fecal calprotectin were assessed. The same parameters were measured and compared with the baseline levels in the follow-up period, during maintenance therapy (average of 39 months after diagnosis). Results: Patients with CD (n=30) had higher serum hepcidin levels (expressed as a median and interquartile range) at diagnosis than subjects with UC (n=13). These levels significantly decreased during the follow-up (from 36.5 (11.5-79.6) ng/ml to 2.1 (0.9-6.7) ng/ml). Contrarily, no significant serum hepcidin level changes were observed in UC (from 5.4 (3.4-16.6) ng/ml to 4.8 (0.9-8.1) ng/ml). While in children with CD hepcidin level dynamics correlated with disease activity and inflammatory markers (ESR, CRP), an only correlation with serum iron levels was observed in patients with UC. Conclusion: Children with CD had higher serum hepcidin levels at diagnosis compared to subjects with UC. Decrease of serum hepcidin in the CD group during anti-inflammatory therapy has been observed, whereas low hepcidin levels in children with UC have remained unchanged. Acknowledgment: This study was supported by grant MH CZ–DRO (FNOl, 00098892).

Keywords: children, Crohn's disease, ulcerative colitis, anaemia, hepcidin

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Authors: Ben-Caleb Egbide, Omolehinwa O. Eddy, Adeyemi S. Keyinde, Eriabie Sylvester, Ojeka Stephen

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The national budget remains an integral part of the developmental plan of the economy of any country. The budget reflects the fundamental values underlying the government’s economic policies and objectives and whose execution is expected to realize national/public desires. In Nigeria, over three decades budget had failed to deliver the desired benefits, suggesting the existence of infractions, which are yet to be empirically ascertained. This paper attempts a diagnosis of the infractions peculiar to Nigeria budgetary system and their suggested panacea. Data were collected through the administration of questionnaire to a cross section of organizations/institutions representing government agencies and the general public. Mann-Whitney U test was employed to gauge the consistency in perception of the two groups. The result revealed that budget indiscipline, official corruption, allocative inefficiency and poor budget governance are the most influential infractions of budgeting in Nigeria. Consequently, it was suggested that budget transparency, target budgeting, zero tolerance on corruption and budget discipline are the most cogent therapies to the malfunctioning in Nigerian budgetary system.

Keywords: budgeting, budget maladies, budget therapies, Nigeria

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Authors: Jun-ya Nagase

Abstract:

Recently, the need of colonoscopy is increasing because of the rise of colonic disorder including cancer of the colon. However, current colonoscopy depends on doctor's skill strongly. Therefore, a large intestine endoscope that does not depend on the techniques of a doctor with high safety is required. In this research, we aim at development a novel large intestine endoscope that can realize safe insertion without specific techniques. A wheel movement type robot, a snake-like robot and an earthworm-like robot are all described in the relevant literature as endoscope robots that are currently studied. Among them, the tracked crawler robot can travel by traversing uneven ground flexibly with a crawler belt attached firmly to the ground surface. Although conventional crawler robots have high efficiency and/or high ground-covering ability, they require a comparatively large space to move. In this study, a small cylindrical crawler robot inspired by amoeba locomotion, which does not need large space to move and which has high ground-covering ability, is proposed. In addition, we developed a prototype of the large intestine endoscope using the proposed crawler mechanism. Experiments have demonstrated smooth operation and a forward movement of the robot by application of voltage to the motor. This paper reports the structure, drive mechanism, prototype, and experimental evaluation.

Keywords: tracked-crawler, endoscopic robot, narrow path, amoeba locomotion.

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Authors: Ioannis Panagiotopoulos, Efstathios Kastritis, Anastasia Katinioti, Georgios Efthymiadis, Argyrios Doumas, Maria Koutelou

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Introduction: Transthyretin amyloidosis (ATTR) is a rare but serious infiltrative disease. Myocardial scintigraphy with DPD has emerged as the most effective, non-invasive, highly sensitive, and highly specific diagnostic method for cardiac ATTR amyloidosis. However, there are cases in which additional laboratory investigations reveal AL amyloidosis or other diseases despite a positive DPD scintigraphy. We describe the experience from the Onassis Cardiac Surgery Center and the monitoring center for infiltrative myocardial diseases of the cardiology clinic at AHEPA. Materials and Methods: All patients with clinical suspicion of cardiac or extracardiac amyloidosis undergo a myocardial scintigraphy scan with Tc-99m DPD. In this way, over 500 patients have been examined. Further diagnostic approach based on clinical and imaging findings includes laboratory investigation and invasive techniques (e.g., biopsy). Results: Out of 76 patients in total with positive myocardial scintigraphy Grade 2 or 3 according to the Perugini scale, 8 were proven to suffer from AL Amyloidosis during the investigation of paraproteinemia. Among these patients, 3 showed Grade 3 uptake, while the rest were graded as Grade 2, or 2 to 3. Additionally, one patient presented diffuse and unusual radiopharmaceutical uptake in soft tissues throughout the body without cardiac involvement. These findings raised suspicions, leading to the analysis of κ and λ light chains in the serum, as well as immunostaining of proteins in the serum and urine of these specific patients. The final diagnosis was AL amyloidosis. Conclusion: The value of DPD scintigraphy in the diagnosis of cardiac amyloidosis from transthyretin is undisputed. However, positive myocardial scintigraphy with DPD should not automatically lead to the diagnosis of ATTR amyloidosis. Laboratory differentiation between ATTR and AL amyloidosis is crucial, as both prognosis and therapeutic strategy are dramatically altered. Laboratory exclusion of paraproteinemia is a necessary and essential step in the diagnostic algorithm of ATTR amyloidosis for all positive myocardial scintigraphy with diphosphonate tracers since >20% of patients with Grade 3 and 2 uptake may conceal AL amyloidosis.

Keywords: AL amyloidosis, amyloidosis, ATTR, myocardial scintigraphy, Tc-99m DPD

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