Search results for: depression diagnosis

Authors: Ekaterina Zvorykina

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Nowadays, Arctic and Antarctic regions are distinguished to be one of the most important strategic resources for global development. Nonetheless, living conditions in Arctic regions still demand certain improvements. As soon as the region is rarely populated, one of the main points of interest is health accommodation of the people, who migrate to Arctic region for permanent and shift work. At Arctic and Antarctic latitudes, personnel face polar day and polar night conditions during the time of the year. It means that they are deprived of natural sunlight in winter season and have continuous daylight in summer. Firstly, the change in light intensity during 24-hours period due to migration affects circadian rhythms. Moreover, the controlled artificial light in winter is also an issue. The results of the recent studies on night shift medical professionals, who were exposed to permanent artificial light, have already demonstrated higher risks in cancer, depression, Alzheimer disease. Moreover, people exposed to frequent time zones change are also subjected to higher risks of heart attack and cancer. Thus, our main goals are to understand how high latitude work and living conditions can affect human health and how it can be prevented. In our study, we analyze molecular and cellular factors, which play important role in circadian rhythm change and distinguish main risk groups in people, migrating to high latitudes. The main well-studied index of circadian timing is melatonin or its metabolite 6-sulfatoxymelatonin. In low light intensity melatonin synthesis is disturbed and as a result human organism requires more time for sleep, which is still disregarded when it comes to working time organization. Lack of melatonin also causes shortage in serotonin production, which leads to higher depression risk. Melatonin is also known to inhibit oncogenes and increase apoptosis level in cells, the main factors for tumor growth, as well as circadian clock genes (for example Per2). Thus, people who work in high latitudes can be distinguished as a risk group for cancer diseases and demand more attention. Clock/Clock genes, known to be one of the main circadian clock regulators, decrease sensitivity of hypothalamus to estrogen and decrease glucose sensibility, which leads to premature aging and oestrous cycle disruption. Permanent light exposure also leads to accumulation superoxide dismutase and oxidative stress, which is one of the main factors for early dementia and Alzheimer disease. We propose a new screening system adjusted for people, migrating from middle to high latitudes and accommodation therapy. Screening is focused on melatonin and estrogen levels, sleep deprivation and neural disorders, depression level, cancer risks and heart and vascular disorders. Accommodation therapy includes different types artificial light exposure, additional melatonin and neuroprotectors. Preventive procedures can lead to increase of migration intensity to high latitudes and, as a result, the prosperity of Arctic region.

Keywords: circadian rhythm, high latitudes, melatonin, neuroprotectors

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Authors: Rajvir Kaur, Jeewani Anupama Ginige

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With recent trends in Big Data and advancements in Information and Communication Technologies, the healthcare industry is at the stage of its transition from clinician oriented to technology oriented. Many people around the world die of cancer because the diagnosis of disease was not done at an early stage. Nowadays, the computational methods in the form of Machine Learning (ML) are used to develop automated decision support systems that can diagnose cancer with high confidence in a timely manner. This paper aims to carry out the comparative evaluation of a selected set of ML classifiers on two existing datasets: breast cancer and cervical cancer. The ML classifiers compared in this study are Decision Tree (DT), Support Vector Machine (SVM), k-Nearest Neighbor (k-NN), Logistic Regression, Ensemble (Bagged Tree) and Artificial Neural Networks (ANN). The evaluation is carried out based on standard evaluation metrics Precision (P), Recall (R), F1-score and Accuracy. The experimental results based on the evaluation metrics show that ANN showed the highest-level accuracy (99.4%) when tested with breast cancer dataset. On the other hand, when these ML classifiers are tested with the cervical cancer dataset, Ensemble (Bagged Tree) technique gave better accuracy (93.1%) in comparison to other classifiers.

Keywords: artificial neural networks, breast cancer, classifiers, cervical cancer, f-score, machine learning, precision, recall

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Authors: Ligia Florio, João Mauricio Castaldelli-Maia

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Background: Food addiction (FA) emerged in the 1990s as a possible contributor to the increasing prevalence of obesity and overweight, in conjunction with changing food environments and mental health conditions. However, FA is not yet listed as one of the disorders in the DSM-5 and/or the ICD-11. Although there are controversies and debates in the literature about the classification and construct of FA, the most common approach to access it is the use of a research tool - the Yale Food Addiction Scale (YFAS) - which approximates the concept of FA to the concept diagnosis of dependence on psychoactive substances. There is a need to explore the dimensional phenotypes accessed by YFAS in different population groups for a better understanding and scientific support of FA diagnoses. Methods: The primary objective of this project was to investigate the construct validity of the FA concept by mYFAS 2.0 in individuals who underwent bariatric surgery (n = 100) at the Hospital Estadual Mário Covas since 2011. Statistical analyzes were conducted using the STATA software. In this sense, structural or factor validity was the type of construct validity investigated using exploratory factor analysis (EFA) and item response theory (IRT) techniques. Results: EFA showed that the one-dimensional model was the most parsimonious. The IRT showed that all criteria contributed to the latent structure, presenting discrimination values greater than 0.5, with most presenting values greater than 2. Conclusion: This study reinforces a FA dimension in patients who underwent bariatric surgery. Within this dimension, we identified the most severe and discriminating criteria for the diagnosis of FA.

Keywords: obesity, food addiction, bariatric surgery, regain

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Authors: Hyunsik Park

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As the rate of cerebrovascular disease increases in old populations, the prevalence rate of vascular dementia would be expected. Therefore, authors designed this study to find out the possibility of somatosensory evoked potentials(SSEP) as a parameter for early diagnosis and prognosis prediction of vascular dementia in cortical vascular dementia patients. 21 patients who met the criteria for vascular dementia according to DSM-IV,ICD-10and NINDS-AIREN with the history of recent cognitive impairment, fluctuation progression, and neurologic deficit. We subdivided these patients into two groups; a mild dementia and a severe dementia groups by MMSE and CDR score; and analysed comparison between normal control group and patient control group who have been cerebrovascular attack(CVA) history without dementia by using N20 latency and amplitude of median nerve. In this study, mild dementia group showed significant differences on latency and amplitude with normal control group(p-value<0.05) except patient control group(p-value>0.05). Severe dementia group showed significant differences both normal control group and patient control group.(p-value<0.05, <001). Since no significant difference has founded between mild dementia group and patient control group, SSEP has limitation to use for early diagnosis test. However, the comparison between severe dementia group and others showed significant results which indicate SSEP can predict the prognosis of vascular dementia in cortical vascular dementia patients.

Keywords: SSEP, cortical vascular dementia, N20 latency, N20 amplitude

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Authors: David Bakker, Nikki Rickard

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Smartphone apps hold immense potential as mental health and wellbeing tools. Support can be made easily accessible and can be used in real-time while users are experiencing distress. Furthermore, data can be collected to enable machine learning and automated tailoring of support to users. While many apps have been developed for mental health purposes, few have adhered to evidence-based recommendations and even fewer have pursued experimental validation. This paper details the development and experimental evaluation of an app, MoodMission, that aims to provide support for low moods and anxiety, help prevent clinical depression and anxiety disorders, and serve as an adjunct to professional clinical supports. MoodMission was designed to deliver cognitive behavioural therapy for specifically reported problems in real-time, momentary interactions. Users report their low moods or anxious feelings to the app along with a subjective units of distress scale (SUDS) rating. MoodMission then provides a choice of 5-10 short, evidence-based mental health strategies called Missions. Users choose a Mission, complete it, and report their distress again. Automated tailoring, gamification, and in-built data collection for analysis of effectiveness was also included in the app’s design. The development process involved construction of an evidence-based behavioural plan, designing of the app, building and testing procedures, feedback-informed changes, and a public launch. A randomized controlled trial (RCT) was conducted comparing MoodMission to two other apps and a waitlist control condition. Participants completed measures of anxiety, depression, well-being, emotional self-awareness, coping self-efficacy and mental health literacy at the start of their app use and 30 days later. At the time of submission (November 2016) over 300 participants have participated in the RCT. Data analysis will begin in January 2017. At the time of this submission, MoodMission has over 4000 users. A repeated-measures ANOVA of 1390 completed Missions reveals that SUDS (0-10) ratings were significantly reduced between pre-Mission ratings (M=6.20, SD=2.39) and post-Mission ratings (M=4.93, SD=2.25), F(1,1389)=585.86, p < .001, np2=.30. This effect was consistent across both low moods and anxiety. Preliminary analyses of the data from the outcome measures surveys reveal improvements across mental health and wellbeing measures as a result of using the app over 30 days. This includes a significant increase in coping self-efficacy, F(1,22)=5.91, p=.024, np2=.21. Complete results from the RCT in which MoodMission was evaluated will be presented. Results will also be presented from the continuous outcome data being recorded by MoodMission. MoodMission was successfully developed and launched, and preliminary analysis suggest that it is an effective mental health and wellbeing tool. In addition to the clinical applications of MoodMission, the app holds promise as a research tool to conduct component analysis of psychological therapies and overcome restraints of laboratory based studies. The support provided by the app is discrete, tailored, evidence-based, and transcends barriers of stigma, geographic isolation, financial limitations, and low health literacy.

Keywords: anxiety, app, CBT, cognitive behavioural therapy, depression, eHealth, mission, mobile, mood, MoodMission

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Authors: Lee Rui, Rajeev Ramachandran

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The approach to recurrent fevers in the paediatric or adolescent age group is not a straightforward one. Causes range from infectious diseases to rheumatological conditions to endocrinopathies, and are usually accompanied by weight loss rather than weight gain. We present an interesting case of a 16-year-old girl brought by her mother to the General Pediatrics Clinic for concerns of recurrent fever paired with significant weight gain over 1.5 years, with no identifiable cause found despite extensive work-up by specialists ranging from Rheumatologists to Oncologists. This case provides a learning opportunity on the approach to weight gain paired with persistent fevers in a paediatric population, one which is not commonly encountered and prompts further evaluation and consideration of less common diagnoses. In a span of 2 years, the girl’s weight had increased from 55 kg at 13 years old (75th centile) to 73.9 kg at 16 years old (>97th centile). About 1 year into her rapid weight gain, she started developing recurrent fevers of documented temperatures > 37.5 – 38.6 every 2-3 days, resulting in school absenteeism when she was sent home after temperature-taking in school found her to be febrile. The rapid onset of weight gain paired with unexplained fevers prompted the treating physician to consider the diagnosis of ROHHAD syndrome. Rapid onset obesity with hypoventilation, hypothalamic dysfunction and autonomic dysregulation (ROHHAD) syndrome is a rare disorder first described in 2007. It is characterized by dysfunction of the autonomic and endocrine system, characterized by hyperphagia and rapid-onset weight gain. This rapid weight gain is classically followed by hypothalamic manifestations with neuroendocrine deficiencies, hypo-ventilatory breathing abnormalities, and autonomic dysregulation. ROHHAD is challenging to diagnose with and diagnosis is made based mostly on clinical judgement. However if truly diagnosed, the condition is characterized by high morbidity and mortality rates. Early recognition of sleep disorders breathing and targeted therapeutic interventions helps limit morbidity and mortality associated with ROHHAD syndrome. This case poses an interesting diagnostic challenge and a diagnosis of ROHHAD has to be considered, given the serious complications that can come with disease progression while conditions such as Munchausen’s or drug fever remain as diagnoses of exclusion until we have exhausted all other possible conditions.

Keywords: pediatrics, endocrine, weight gain, recurrent fever, adolescent

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Authors: Saad Chahba, Rabia Sehab, Ahmad Akrad, Cristina Morel

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Nowadays, the electric machines used in urban electric vehicles are, in most cases, three-phase electric machines with or without a magnet in the rotor. Permanent Magnet Synchronous Machine (PMSM) and Induction Machine (IM) are the main components of drive trains of electric and hybrid vehicles. These machines have very good performance in healthy operation mode, but they are not redundant to ensure safety in faulty operation mode. Faced with the continued growth in the demand for electric vehicles in the automotive market, improving the reliability of electric vehicles is necessary over the lifecycle of the electric vehicle. Multiphase electric machines respond well to this constraint because, on the one hand, they have better robustness in the event of a breakdown (opening of a phase, opening of an arm of the power stage, intern-turn short circuit) and, on the other hand, better power density. In this work, a diagnosis approach using a neural network for an open circuit fault or more of a five-phase induction machine is developed. Validation on the simulator of the vehicle drivetrain, at reduced power, is carried out, creating one and more open circuit stator phases showing the efficiency and the reliability of the new approach to detect and to locate on-line one or more open phases of a five-induction machine.

Keywords: electric vehicle drivetrain, multiphase drives, induction machine, control, open circuit (OC) fault diagnosis, artificial neural network

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Authors: Abu Salim Mustafa

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The comparisons of mycobacterial genomes have identified several Mycobacterium tuberculosis-specific genomic regions that are absent in other mycobacteria and are known as regions of differences. Due to M. tuberculosis-specificity, the peptides encoded by these regions could be useful in the specific diagnosis of tuberculosis. To explore this possibility, overlapping synthetic peptides corresponding to 39 proteins predicted to be encoded by genes present in regions of differences were tested for antibody-reactivity with sera from tuberculosis patients and healthy subjects. The results identified four immunodominant peptides corresponding to four different proteins, with three of the peptides showing significantly stronger antibody reactivity and rate of positivity with sera from tuberculosis patients than healthy subjects. The fourth peptide was recognized equally well by the sera of tuberculosis patients as well as healthy subjects. Predication of antibody epitopes by bioinformatics analyses using ABCpred server predicted multiple linear epitopes in each peptide. Furthermore, peptide sequence analysis for sequence identity using BLAST suggested M. tuberculosis-specificity for the three peptides that had preferential reactivity with sera from tuberculosis patients, but the peptide with equal reactivity with sera of TB patients and healthy subjects showed significant identity with sequences present in nob-tuberculous mycobacteria. The three identified M. tuberculosis-specific immunodominant peptides may be useful in the serological diagnosis of tuberculosis.

Keywords: genomic regions of differences, Mycobacterium tuberculossis, peptides, serodiagnosis

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Authors: Morteza Rahbar Taramsari, Arya Mahdavi Baramchi, Mercedeh Enshaei, Ghazaleh Keshavarzi Baramchi

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Introduction: Malingering is one of the most challenging issues in the forensic psychology and imposes a heavy financial burden on health care and legal systems. It seems that some mental and personality abnormalities might have a crucial role in developing this condition. Materials and Methods: In this cross-sectional study, we aimed to assess 100 malingering clients of Gilan province general office of forensic medicine, all filled the related questionnaires. The data about some psychometric characteristics were collected through the 71-items version- short form- of Minnesota Multiphasic Personality Inventory (MMPI) questionnaire and the personality traits were assessed by NEO Personality Inventory-Revised (NEO PI-R) - including 240 items- as a reliable and accurate measure of the five domains of personality. Results: The 100 malingering clients (55 males and 45 females) ranged from 23 to 45 (32+/- 5.6) years old. Regarding marital status, 36% were single, 57% were married and 7% were divorced. Almost two-thirds of the participants (64%) were unemployed, 21% were self-employed and the rest of them were employed. The data of MMPI clinical scales revealed that the mean (SD) T score of Hypochondrias (Hs) was 67(9.2), Depression (D) was 87(7.9), Hysteria (Hy) was 74(5.8), Psychopathic Deviate (Pd) was 62(8.5), Masculinity-Feminity (MF) was 76(8.4), Paranoia (Pa) was 62(4.5), Psychasthenia (Pt) was 80(7.9), Schizophrenia (Sc) was 69(6.8), Hypomania (Ma) was 64(5.9)and Social Introversion (Si) was 58(4.3). NEO PI-R test showed five domains of personality. The mean (SD) T score of Neuroticism was 65(9.2), Extraversion was 51(7.9), Openness was 43(5.8), Agreeableness was 35(3.4) and Conscientiousness was 42(4.9). Conclusion: According to MMPI test in our malingering clients, Hypochondriasis (Hs), depression (D), Hysteria (Hy), Muscularity-Feminity (MF), Psychasthenia (Pt) and Schizophrenia (Sc) had high scores (T >= 65) which means pathological range and psychological significance. Based on NEO PI-R test Neuroticism was in high range, on the other hand, Openness, Agreeableness, and Conscientiousness were in low range. Extroversion was in average range. So it seems that malingerers require basic evaluations of different psychological fields. Additional research in this area is needed to provide stronger evidence of the possible positive effects of the mentioned factors on malingering.

Keywords: malingerers, mental profile, MMPI, NEO PI-R, personality profile

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Authors: Rubina Ghani, Sehrish Zia, Afifa Fatima Rafique, Shaista Emad

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Background: Cancer is a leading cause of death worldwide, with breast cancer being the most common cancer in women. Pakistan has the highest rate of breast cancer cases among Asian countries. Early and accurate diagnosis is crucial for treatment outcomes and quality of life. Method: It is a case-control study with a sample size of 150. There were 100 suspected cancer cases, 25 healthy controls, and 25 diagnosed cancer cases. To analyze SSAT-1 mRNA expression in whole blood, Zymo Research Quick-RNA Miniprep and Innu SCRIPT—One Step RT-PCR Syber Green kits were used. Patients were divided into three groups: 100 suspected cancer cases, 25 controls, and 25 confirmed breast cancer cases. Result: The total mRNA was isolated, and the expression of SSAT-1 was measured using RT-qPCR. The threshold cycle (Ct) values were used to determine the amount of each mRNA. Ct values were then calculated by taking the difference between the CtSSAT-1 and Ct GAPDH, and further Ct values were calculated with the median absolute deviation for all the samples within the same experimental group. Samples that did not correlate with the results were taken as outliers and excluded from the analysis. The relative fold change is shown as 2^-Ct values. Suspected cases showed a maximum fold change of 32.24, with a control fold change of 1.31. Conclusion: The study reveals an overexpression of SSAT-1 in breast cancer. Furthermore, we can use SSAT-1 as a diagnostic, prognostic, and therapeutic marker for early diagnosis of cancer.

Keywords: breast cancer, spermidine/spermine, qPCR, mRNA

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Authors: Viacheslav Sushko, Viktor Sushko

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Pre-cancerous breast diseases are pathological changes that precede the appearance of adenocarcinoma. The most common benign breast disease is mastopathy. We examined the life and disease history of 114 women aged 58-69 who were diagnosed with adenocarcinoma of the breast at different stages of development. They filled out the Reeder Scale to determine the level of stress. The results of the study revealed that 62 of them had mastopathy at the age of 30-45 years old. These women refused surgical treatment for mastopathy. Five to six years before their diagnosis of adenocarcinoma of the mammary gland, 84 women had experienced severe stress (death of a beloved close relative, torture accompanied by rape, prolonged stay in extreme conditions (under bombardment and bombardment). In the assessment of data from completed Reeder scales, 114 women had a high level of mental stress, with a score from 1-1.72. The 84 women who suffered from severe stress showed overeating or a significant decrease in food intake, insomnia, apathy, increased irritability and restlessness, loss of interest in sexual relationships, forgetfulness, difficulty in performing routine work, prolonged uncontrollable headaches, unexplained fatigue, heart pain, reduced capacity for work. In conclusion, it is important to provide psychotherapy for breast cancer patients as the diagnosis, and the different stages of treatment are very stressful. It is also advisable to see a psychiatrist at an early stage and prevent distress and treat precancerous breast disease.

Keywords: breast cancer, distress, mastopathy, severe stress

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Authors: L. I. Izhar, T. Stathaki, K. Howell

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Analyzing and interpreting of thermograms have been increasingly employed in the diagnosis and monitoring of diseases thanks to its non-invasive, non-harmful nature and low cost. In this paper, a novel system is proposed to improve diagnosis and monitoring of morphoea skin disorder based on integration with the published lines of Blaschko. In the proposed system, image registration based on global and local registration methods are found inevitable. This paper presents a modified normalized gradient cross-correlation (NGC) method to reduce large geometrical differences between two multimodal images that are represented by smooth gray edge maps is proposed for the global registration approach. This method is improved further by incorporating an iterative-based normalized cross-correlation coefficient (NCC) method. It is found that by replacing the final registration part of the NGC method where translational differences are solved in the spatial Fourier domain with the NCC method performed in the spatial domain, the performance and robustness of the NGC method can be greatly improved. It is shown in this paper that the hybrid NGC method not only outperforms phase correlation (PC) method but also improved misregistration due to translation, suffered by the modified NGC method alone for thermograms with ill-defined jawline. This also demonstrates that by using the gradients of the gray edge maps and a hybrid technique, the performance of the PC based image registration method can be greatly improved.

Keywords: Blaschko’s lines, image registration, morphoea, thermal imaging

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Authors: Arabi Abderrazak, Bourouba Nacerdine, Ayad Mouloud, Belaout Abdeslam

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In this paper, a new test technique of analog circuits using time mode simulation is proposed for the single catastrophic faults detection in analog circuits. This test process is performed to overcome the problem of catastrophic faults being escaped in a DC mode test applied to the inverter amplifier in previous research works. The circuit under test is a second-order low pass filter constructed around this type of amplifier but performing a function that differs from that of the previous test. The test approach performed in this work is based on two key- elements where the first one concerns the unique square pulse signal selected as an input vector test signal to stimulate the fault effect at the circuit output response. The second element is the filter response conversion to a square pulses sequence obtained from an analog comparator. This signal conversion is achieved through a fixed reference threshold voltage of this comparison circuit. The measurement of the three first response signal pulses durations is regarded as fault effect detection parameter on one hand, and as a fault signature helping to hence fully establish an analog circuit fault diagnosis on another hand. The results obtained so far are very promising since the approach has lifted up the fault coverage ratio in both modes to over 90% and has revealed the harmful side of faults that has been masked in a DC mode test.

Keywords: analog circuits, analog faults diagnosis, catastrophic faults, fault detection

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Authors: Hamidreza Akbari

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In this paper, for detection of inclined eccentricity in an induction motor, time–frequency analysis of the stator startup current is carried out. For this purpose, the discrete wavelet transform is used. Data are obtained from simulations, using winding function approach. The results show the validity of the approach for detecting the fault and discriminating with respect to other faults.

Keywords: induction machine, fault, DWT, electric

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Authors: Mbonigaba Swale

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Malaria is an infection or disease caused by parasites (Plasmodium Falciparum — causes severe Malaria, plasmodium Vivax, Plasmodium Ovale, and Plasmodium Malariae), transmitted by bites of infected anopheles (female) mosquitoes to humans. These vectors comprise of two types in Africa, particularly in Uganda, i.e. anopheles fenestus and Anopheles gambaie (‘example Anopheles arabiensis,,); feeds on man inside the house mainly at dusk, mid-night and dawn and rests indoors and makes them effective transmitters (vectors) of the disease. People in both urban and rural areas have consistently become prone to repetitive attacks of malaria, causing a lot of deaths and significantly increasing the poverty levels of the rural poor. Malaria is a national problem; it causes a lot of maternal pre-natal and antenatal disorders, anemia in pregnant mothers, low birth weights for the newly born, convulsions and epilepsy among the infants. Cumulatively, it kills about one million children every year in sub-Saharan Africa. It has been estimated to account for 25-35% of all outpatient visits, 20-45% of acute hospital admissions and 15-35% of hospital deaths. Uganda is the leading victim country, for which Rakai and Masaka districts are the most affected. So, it is not clear whether these abhorrent situations and episodes of recurrences and failure to cure from the disease are a result of poor diagnosis, prescription and dosing, treatment habits and compliance of the patients to the drugs or the ethical domain of the stake holders in relation to the main stream methodology of malaria management. The research is aimed at offering an alternative approach to manage and deal absolutely with problem by using a knowledge based software model of Artificial Intelligence (Al) that is capable of performing common-sense and cognitive reasoning so as to take decisions like the human brain would do to provide instantaneous expert solutions so as to avoid speculative simulation of the problem during differential diagnosis in the most accurate and literal inferential aspect. This system will assist physicians in many kinds of medical diagnosis, prescribing treatments and doses, and in monitoring patient responses, basing on the body weight and age group of the patient, it will be able to provide instantaneous and timely information options, alternative ways and approaches to influence decision making during case analysis. The computerized system approach, a new model in Uganda termed as “Software Aided Treatment” (SAT) will try to change the moral and ethical approach and influence conduct so as to improve the skills, experience and values (social and ethical) in the administration and management of the disease and drugs (combination therapy and generics) by both the patient and the health worker.

Keywords: knowledge based software, management, treatment, diagnosis

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Authors: Chandu Rathnayake, Isuri Anuradha

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Early detection and accurate diagnosis of lung diseases play a crucial role in improving patient prognosis. However, conventional diagnostic methods heavily rely on subjective symptom assessments and medical imaging, often causing delays in diagnosis and treatment. To overcome this challenge, we propose a novel lung disease prediction system that integrates patient symptoms and X-ray images to provide a comprehensive and reliable diagnosis.In this project, develop a mobile application specifically designed for detecting lung diseases. Our application leverages both patient symptoms and X-ray images to facilitate diagnosis. By combining these two sources of information, our application delivers a more accurate and comprehensive assessment of the patient's condition, minimizing the risk of misdiagnosis. Our primary aim is to create a user-friendly and accessible tool, particularly important given the current circumstances where many patients face limitations in visiting healthcare facilities. To achieve this, we employ several state-of-the-art algorithms. Firstly, the Decision Tree algorithm is utilized for efficient symptom-based classification. It analyzes patient symptoms and creates a tree-like model to predict the presence of specific lung diseases. Secondly, we employ the Random Forest algorithm, which enhances predictive power by aggregating multiple decision trees. This ensemble technique improves the accuracy and robustness of the diagnosis. Furthermore, we incorporate a deep learning model using Convolutional Neural Network (CNN) with the RestNet50 pre-trained model. CNNs are well-suited for image analysis and feature extraction. By training CNN on a large dataset of X-ray images, it learns to identify patterns and features indicative of lung diseases. The RestNet50 architecture, known for its excellent performance in image recognition tasks, enhances the efficiency and accuracy of our deep learning model. By combining the outputs of the decision tree-based algorithms and the deep learning model, our mobile application generates a comprehensive lung disease prediction. The application provides users with an intuitive interface to input their symptoms and upload X-ray images for analysis. The prediction generated by the system offers valuable insights into the likelihood of various lung diseases, enabling individuals to take appropriate actions and seek timely medical attention. Our proposed mobile application has significant potential to address the rising prevalence of lung diseases, particularly among young individuals with smoking addictions. By providing a quick and user-friendly approach to assessing lung health, our application empowers individuals to monitor their well-being conveniently. This solution also offers immense value in the context of limited access to healthcare facilities, enabling timely detection and intervention. In conclusion, our research presents a comprehensive lung disease prediction system that combines patient symptoms and X-ray images using advanced algorithms. By developing a mobile application, we provide an accessible tool for individuals to assess their lung health conveniently. This solution has the potential to make a significant impact on the early detection and management of lung diseases, benefiting both patients and healthcare providers.

Keywords: CNN, random forest, decision tree, machine learning, deep learning

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Authors: Aulanni’am Aulanni’am

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Incidence of Diabetes Mellitus (DM) progressively increasing it became a serious problem in Indonesia and it is a disease that government is priority to be addressed. The longer a person is suffering from diabetes the more likely to develop complications particularly diabetic patients who are not well maintained. Therefore, Incidence of Diabetes Mellitus needs to be done in the early diagnosis of pre-phase of the disease. In this pre-phase disease, already happening destruction of pancreatic beta cells and declining in beta cell function and the sign autoimmunity reactions associated with beta cell destruction. Type 1 DM is a multifactorial disease triggered by genetic and environmental factors, which leads to the destruction of pancreatic beta cells. Early marker of "beta cell autoreactivity" is the synthesis of autoantibodies against 65-kDa protein, which can be a molecule that can be detected early in the disease pathomechanism. The importance of early diagnosis of diabetic patients held in the phase of pre-disease is to determine the progression towards the onset of pancreatic beta cell destruction and take precautions. However, the price for this examination is very expensive ($ 150/ test), the anti-GAD65 abs examination cannot be carried out routinely in most or even in all laboratories in Indonesia. Therefore, production-based Rapid Test Recombinant Human Protein GAD65 with "Reverse Flow Immunchromatography Technique" in Indonesia is believed to reduce costs and improve the quality of care of patients with diabetes in Indonesia. Rapid Test Product innovation is very simple and suitable for screening and routine inspection of GAD65 autoantibodies. In the blood serum of patients with diabetes caused by autoimmunity, autoantibody-GAD65 is a major serologic marker to detect autoimmune reaction because their concentration level of stability.GAD65 autoantibodies can be found 10 years before clinical symptoms of diabetes. Early diagnosis is more focused to detect the presence autontibodi-GAD65 given specification and high sensitivity. Autoantibodies- GAD65 that circulates in the blood is a major indicator of the destruction of the islet cells of the pancreas. Results of research in collaboration with Biofarma has produced GAD65 autoantibodies based Rapid Test had conducted the soft launch of products and has been tested with the results of a sensitivity of 100 percent and a specificity between 90 and 96% compared with the gold standard (import product) which worked based on ELISA method.

Keywords: diabetes mellitus, GAD65 autoantibodies, rapid test, sensitivity, specificity

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Authors: Gadiri Sabiha

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Introduction: Current allergy diagnostic tools using Multiplex technology have made it possible to increase the efficiency of the search for specific IgE. This opportunity is provided by the newly developed “Alex Biochip”, consisting of a panel of 282 allergens in native and molecular form, a CCD inhibitor, and the potential for detecting cross-reactive allergens. We evaluated the performance of this technology in detecting cross-reactivity in previously explored patients. Material/Method: The sera of 39 patients presenting sensitization and polysensitization profiles were explored. The search for specific IgE is carried out by the Alex ® IgE Biochip, and the results are analyzed by nature and by molecular family of allergens using specific software. Results/Discussion: The analysis gave a particular profile of cross-reactivity allergens: 33% for the Ole e1 family, 31% for NPC2, 26% for storage proteins, 20% for Tropomyosin, 10% for LTPs, 10% for Arginine Kinase and 10% for Uteroglobin CCDs were absent in all patients. The “Ole e1” allergen is responsible for a pollen-pollen cross allergy. The storage proteins found and LTP are not species-specific, causing cross-pollen-food allergy. The nDer p2 of the NPC2 family is responsible for cross-reactivity between mite species. Conclusion: The cross-reactivities responsible for mixed syndromes at diagnosis in our patients were dominated by pollen-pollen and pollen-food syndromes. They allow the identification of severity factors linked to the prognosis and the best-adapted immunotherapy.

Keywords: specific IgE, allergy, cross reactivity, molecular allergens

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Authors: Isabel Cristina Ortiz Trujillo, Lina Maria Martinez Sanchez, Felipe Hernández Restrepo, Daniel Gallego Gonzalez, Natalia Vargas Grisales, Camilo Andrés Agudelo Vélez

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Chorioamnionitis, is a pregnancy infection, causes different fetal and maternal symptoms. Streptococcus agalactiae present in the normal vaginal microflora of some women, favouring its abnormal multiplication during pregnancy, causing perinatal morbidity and mortality. Objective. Describe the clinical and epidemiological profile of the patients with diagnosis of clinical chorioanmionitis. Methodology. Descriptive, cross-sectional study. The population was patients with diagnosis of clinical chorioanmionitis. The information was taken from the medical records. The research was approved by the Ethics Committee. We used the program SPSS ® version 17.0 (SPSS Inc; Chicago, Illinois, USA) for the information analysis, descriptive statistics were used. Results. 78 patients in total with clinical chorioamnionitis, with a mean age of 26.3 ±5, 8 years old, the 69.2% primigravid women. 2.6% of women had positive culture for Streptococcus agalactiae in urine sample during current pregnancy and 30.7% had received some kind of antibiotics during current pregnancy. The 57.7% had 37 to 40 weeks of gestation in the current pregnancy it was calculated more frequently by ultrasound (66.7% in first quarter, 11.5% in the second and 1.9% in the third). In a 60.3% way of termination of pregnancy was vaginal and a 35.9 percent were caesarean section. Among the women in the study, a 30.8% had premature rupture of membranes. Conclusion. The chorioamnionitis continues to be an important cause of antibiotic use during pregnancy or labour and the decision to do a caesarean, with highest percentage in pregnancies-preterm and preterm premature rupture of membranes.

Keywords: chorioamnionitis, Streptococcus agalactiae, pregnancy complications, infectious

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Authors: Mehwish Asghar

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Breast Cancer (BC) is a common type of cancer among women. Its screening is usually performed using different imaging modalities such as magnetic resonance imaging, mammogram, X-ray, CT, etc. Among these modalities’ mammogram is considered a powerful tool for diagnosis and screening of breast cancer. Sophisticated machine learning approaches have shown promising results in complementing human diagnosis. Generally, machine learning methods can be divided into two major classes: one is Radiomics analysis (RA), where image features are extracted manually; and the other one is the concept of convolutional neural networks (CNN), in which the computer learns to recognize image features on its own. This research aims to improve the incidence of early detection, thus reducing the mortality rate caused by breast cancer through the latest advancements in computer science, in general, and machine learning, in particular. It has also been aimed to ease the burden of doctors by improving and automating the process of breast cancer detection. This research is related to a relative analysis of different techniques for the implementation of different models for detecting and classifying breast cancer. The main goal of this research is to provide a detailed view of results and performances between different techniques. The purpose of this paper is to explore the potential of a convolutional neural network (CNN) w.r.t feature extractor and as a classifier. Also, in this research, it has been aimed to add the module of Radiomics for comparison of its results with deep learning techniques.

Keywords: breast cancer (BC), machine learning (ML), convolutional neural network (CNN), radionics, magnetic resonance imaging, artificial intelligence

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Authors: Santhani M. Selveindran

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Background: Natural disasters are traumatic global events that are becoming increasing more common, with significant psychosocial impact on survivors. This impact results not only in psychosocial distress but, for many, can lead to psychosocial disorders and chronic psychopathology. While there are currently available interventions that seek to prevent and treat these psychosocial sequelae, their effectiveness is uncertain. The evidence-base is emerging with more primary studies evaluating the effectiveness of various psychosocial interventions for survivors of natural disasters, which remains to be synthesized. Aim of Review: To identify, critically appraise and synthesize the current evidence-base on the effectiveness of psychosocial interventions in preventing or treating Post-Traumatic Stress Disorder (PTSD), Major Depressive Disorder (MDD) and/or Generalized Anxiety Disorder (GAD) in adults and children who are survivors of natural disasters. Methods: A protocol was developed as a guide to carry out this review. A systematic search was conducted in eight international electronic databases, three grey literature databases, one dissertation and thesis repository, websites of six humanitarian and non-governmental organizations renowned for their work on natural disasters, as well as bibliographic and citation searching for eligible articles. Papers meeting the specific inclusion criteria underwent quality assessment using the Downs and Black checklist. Data were extracted from the included papers and analysed by way of narrative synthesis. Results: Database and website searching returned 3777 papers where 31 met the criteria for inclusion. Additional 2 papers were obtained through bibliographic and citation searching. Methodological quality of most papers was fair. Twenty-five studies evaluated psychological interventions, five, social interventions whereas three studies evaluated ‘mixed’ psychological and social interventions. All studies, irrespective of methodological quality, reported post-intervention reductions in symptom scores for PTSD, depression and/or anxiety and where assessed, reduced diagnosis of PTSD and MDD, and produced improvements in self-efficacy and quality of life. Statistically significant results were seen in 27 studies. However, three studies demonstrated that the evaluated interventions may not have been very beneficial. Conclusions: The overall positive results suggest that any psychosocial interventions are favourable and should be delivered to all natural disaster survivors, irrespective of age, country, and phase of disaster. Yet, heterogeneity and methodological shortcomings of the current evidence-base makes it difficult to draw definite conclusions needed to formulate categorical guidance or frameworks. Further, rigorously conducted research is needed in this area, although the feasibility of such, given the context and nature of the problem, is also recognized.

Keywords: psychosocial interventions, natural disasters, survivors, effectiveness

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Authors: S. Zith Dey Babu, S. Kour, S. Verma, C. Verma, V. Pathania, A. Agrawal, V. Chaudhary, A. Manoj Puthur, R. Goyal, A. Pal, T. Danti Dey, A. Kumar, K. Wadhwa, O. Ved

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Background: Skin cancer is now is the buzzing button in the field of medical science. The cyst's pandemic is drastically calibrating the body and well-being of the global village. Methods: The extracted image of the skin tumor cannot be used in one way for diagnosis. The stored image contains anarchies like the center. This approach will locate the forepart of an extracted appearance of skin. Partitioning image models has been presented to sort out the disturbance in the picture. Results: After completing partitioning, feature extraction has been formed by using genetic algorithm and finally, classification can be performed between the trained and test data to evaluate a large scale of an image that helps the doctors for the right prediction. To bring the improvisation of the existing system, we have set our objectives with an analysis. The efficiency of the natural selection process and the enriching histogram is essential in that respect. To reduce the false-positive rate or output, GA is performed with its accuracy. Conclusions: The objective of this task is to bring improvisation of effectiveness. GA is accomplishing its task with perfection to bring down the invalid-positive rate or outcome. The paper's mergeable portion conflicts with the composition of deep learning and medical image processing, which provides superior accuracy. Proportional types of handling create the reusability without any errors.

Keywords: computer-aided system, detection, image segmentation, morphology

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Authors: Tomoko Fukuyama, Osamu Senbu

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Prestressed concrete is used a lot in infrastructures such as roads or bridges. However, poor grout filling and PC steel corrosion are currently major issues of prestressed concrete structures. One of the problems with nondestructive corrosion detection of PC steel is a plastic pipe which covers PC steel. The insulative property of pipe makes a nondestructive diagnosis difficult; therefore a practical technology to detect these defects is necessary for the maintenance of infrastructures. The goal of the research is a development of an electrochemical technique which enables to detect internal defects from the surface of prestressed concrete nondestructively. Ideally, the measurements should be conducted from the surface of structural members to diagnose non-destructively. In the present experiment, a prestressed concrete member is simplified as a layered specimen to simulate a current path between an input and an output electrode on a member surface. The specimens which are layered by mortar and the prestressed concrete constitution materials (steel, polyethylene, stainless steel, or galvanized steel plates) were provided to the alternating current impedance measurement. The magnitude of an applied electric field was 0.01-volt or 1-volt, and the frequency range was from 106 Hz to 10-2 Hz. The frequency spectrums of impedance, which relate to charge reactions activated by an electric field, were measured to clarify the effects of the material configurations or the properties. In the civil engineering field, the Nyquist diagram is popular to analyze impedance and it is a good way to grasp electric relaxation using a shape of the plot. However, it is slightly not suitable to figure out an influence of a measurement frequency which is reciprocal of reaction time. Hence, Bode diagram is also applied to describe charge reactions in the present paper. From the experiment results, the alternating current impedance method looks to be applicable to the insulative material measurement and eventually prestressed concrete diagnosis. At the same time, the frequency spectrums of impedance show the difference of the material configuration. This is because the charge mobility reflects the variety of substances and also the measuring frequency of the electric field determines migration length of charges which are under the influence of the electric field. However, it could not distinguish the differences of the material thickness and is inferred the difficulties of prestressed concrete diagnosis to identify the amount of an air void or a layer of corrosion product by the technique.

Keywords: capacitance, conductance, prestressed concrete, susceptance

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Authors: Olga Blagova, Yuliya Osipova, Evgeniya Kogan, Alexander Nedostup

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Purpose: to quantify the value of various clinical, laboratory and instrumental signs in the diagnosis of myocarditis in comparison with morphological studies of the myocardium. Methods: in 100 patients (65 men, 44.7±12.5 years) with «idiopathic» arrhythmias (n = 20) and dilated cardiomyopathy (DCM, n = 80) were performed 71 endomyocardial biopsy (EMB), 13 intraoperative biopsy, 5 study of explanted hearts, 11 autopsy with virus investigation (real-time PCR) of the blood and myocardium. Anti-heart antibodies (AHA) were also measured as well as cardiac CT (n = 45), MRI (n = 25), coronary angiography (n = 47). The comparison group included of 50 patients (25 men, 53.7±11.7 years) with non-inflammatory heart diseases who underwent open heart surgery. Results. Active/borderline myocarditis was diagnosed in 76.0% of the study group and in 21.6% of patients of the comparison group (p < 0.001). The myocardial viral genome was observed more frequently in patients of comparison group than in study group (group (65.0% and 40.2%; p < 0.01. Evaluated the diagnostic value of noninvasive markers of myocarditis. The panel of anti-heart antibodies had the greatest importance to identify myocarditis: sensitivity was 81.5%, positive and negative predictive value was 75.0 and 60.5%. It is defined diagnostic value of non-invasive markers of myocarditis and diagnostic algorithm providing an individual assessment of the likelihood of myocarditis is developed. Conclusion. The greatest significance in the diagnosis of latent myocarditis in patients with 'idiopathic' arrhythmias and DCM have AHA. The use of complex of noninvasive criteria allows estimate the probability of myocarditis and determine the indications for EMB.

Keywords: myocarditis, "idiopathic" arrhythmias, dilated cardiomyopathy, endomyocardial biopsy, viral genome, anti-heart antibodies

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Authors: A. Erragh, K. Amanzoui, M. Elharit, H. Salem, M. Ababneh, K. Elfakhr, S. Kalouch, A. Chlilek

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Guillain-Barre syndrome (GBS) is the most common form of acute polyradiculoneuritis (PRNA). It is a medical emergency in pediatrics that requires rapid diagnosis and immediate assessment of the severity criteria for the implementation of appropriate treatment. Retrospective, descriptive study in 24 patients under the age of 18 who presented with GBS between September 2017 and July 2021 and were hospitalized in the multipurpose pediatric intensive care unit of the Abderrahim EL Harouchi children's hospital in Casablanca. The average age was 7.91 years, with extremes ranging from 18 months and 14 years and a male predominance of 75%. After a prodromal event, most often infectious (80%) and a free interval of 12 days on average, 2 types of motor disorders begin either hypo or arereflectic flaccid paralysis of the lower limbs (45.8%) or flaccid quadriplegia hypo or arereflectic (54.2%). During GBS, the most formidable complication is respiratory distress, which can occur at any time. In our study, respiratory impairment was observed in 70.8% of cases. In addition, other signs of severity, such as swallowing disorders (75%) and dysautonomic disorders (8.33%), were also observed, which justified care in the intensive care unit for all of our patients. The use of invasive ventilation was necessary in 76.5% of cases, and specific treatments based on immunoglobulins were administered in all our patients. Despite everything, the death rate remains high (25%) and is mainly due to complications related to hospitalization. Guillain Barré syndrome is, therefore, a pediatric emergency that requires rapid diagnosis and immediate assessment of severity criteria for the implementation of appropriate treatment.

Keywords: guillain barre syndrome, emergency, children, medical

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Authors: Zainab Elazab, Azhar Aziz

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Background: Spontaneous Splenic artery pseudoaneurysm rupture is a rare condition which is potentially life threatening, if not detected and managed early. We report a case of abdominal pain with intraperitoneal free fluid, which turned out to be spontaneous rupture of a splenic artery pseudoaneurysm, and was treated with arterial embolization. Case presentation: A 28-year old, previously healthy male presented to the ED with a history of sudden onset upper abdominal pain and fainting attack. The patient denied any history of trauma or prior similar attacks. On examination, the patient had tachycardia and a low-normal BP (HR 110, BP 106/66) but his other vital signs were normal (Temp. 37.2, RR 18 and SpO2 100%). His abdomen was initially soft with mild tenderness in the upper region. Blood tests showed leukocytosis of 12.3 X109/L, Hb of 12.6 g/dl and lactic acid of 5.9 mmol/L. Ultrasound showed trace of free fluid in the perihepatic and perisplenic areas, and a splenic hypoechoic lesion. The patient remained stable; however, his abdomen became increasingly tender with guarding. We made a provisional diagnosis of a perforated viscus and the patient was started on IV fluids and IV antibiotics. An erect abdominal x-ray did not show any free air under the diaphragm so a CT abdomen was requested. Meanwhile, bedside ultrasound was repeated which showed increased amount of free fluid, suggesting intra-abdominal bleeding as the most probable etiology for the condition. His CT abdomen revealed a splenic injury with multiple lacerations, a focal intrasplenic enhancing area on venous phase scan (suggesting a pseudoaneurysm with associated splenic intraparenchymal, sub capsular and perisplenic hematomas). Free fluid in the subhepatic and intraperitoneal regions along the small bowel was also detected. Angiogram was done which confirmed a diagnosis of pseudoaneurysm of intrasplenic arterial branch, and angio-embolization was done to control the bleeding. The patient was later discharged in good condition with a surgery follow-up. Conclusion: Splenic artery pseudoaneurysm rupture is a rare cause of abdominal pain which should be considered in any case of abdominal pain with intraperitoneal bleeding. Early management is crucial as it carries a high mortality. Bedside ultrasound is a useful tool to help for early diagnosis of such cases.

Keywords: abdominal pain, pseudo aneurysm, rupture, splenic artery

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Authors: Hady Atef Labib

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Pediatric cardiac rehabilitation has the potential to benefit many children with congenital heart defects (CHD). Instead of excellent surgical results most of children usually present with a depression of physical condition so early rehabilitation program is recommended to avoid that decline in physical tolerance and prevent any post surgical complications. Unfortunately, the limited experience with and availability of these programs has caused the benefits of cardiac rehabilitation to be unavailable to most children with CHD. Therefore, it is recommended to study that field in more detail and apply it on wider scale.

Keywords: pediatric cardiac rehabilitation, congenital heart disease, quality of life, pediatric

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Authors: Abdollah Sobhani, Hossein Vaseghi-Dodaran

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Proteomics is defined as the study of the component of a cell, tissue and biological fluid. This technique has the potential to identify protein biomarkers of a disease states. In this study which was performed on bovine ovarian follicular cysts (BOFC), eight proteins are over expressed in BOFC that these proteins could be useful biomarkers for BOFC. The difference between serum proteome pattern cows affected by postpartum endometritis with healthy cows revealed that concentrations orosomucoid was decreased in endometritis. The comparison proteome of brucella abortus between laboratory adapted strains and clinical isolates could be useful to better understand this disease and vaccine development. Proteomics experiments identified new proteins and pathways that may be important in future hypothesis-driven studies of glucocorticoid-induced immunosuppression. Understanding the molecular mechanisms of effective parameters on male fertility is essential for obtaining high reproductive efficiency by decreasing cost and time. The investigations on proteome of high fertility spermatozoa indicated that expression of some proteins such as casein kinase 2 (CKII) prime poly peptide and tyrosine kinase in high fertility spermatozoa was higher compared to low fertility spermatozoa. Also, some evidence has indicated that variation in protein types and amounts in seminal fluid regulates fertility indexes in dairy bull. In conclusion, proteomics is a useful technique for discovering drugs, vaccine development, and diagnosis disease by biomarkers and improvement of reproduction efficiency.

Keywords: proteomics, reproduction, biomarker, immunity

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Authors: Divya Kanchibhotla, Shashank Kulkarni, Shweta Singh

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Chronic stress and sleep quality reduces mental health and increases the risk of developing depression and anxiety as well. There is increasing evidence for the utility of meditation as an adjunct clinical intervention for conditions like depression and anxiety. The present study is an attempt to explore the impact of Sahaj Samadhi Meditation (SSM), a category of Automatic Self Transcending Meditation (ASTM), on perceived stress and sleep quality in adults. The study design was a single group pre-post assessment. Perceived Stress Scale (PSS) and the Pittsburgh Sleep Quality Index (PSQI) were used in this study. Fifty-two participants filled PSS, and 60 participants filled PSQI at the beginning of the program (day 0), after two weeks (day 16) and at two months (day 60). Significant pre-post differences for the perceived stress level on Day 0 - Day 16 (p < 0.01; Cohen's d = 0.46) and Day 0 - Day 60 (p < 0.01; Cohen's d = 0.76) clearly demonstrated that by practicing SSM, participants experienced reduction in the perceived stress. The effect size of the intervention observed on the 16th day of assessment was small to medium, but on the 60th day, a medium to large effect size of the intervention was observed. In addition to this, significant pre-post differences for the sleep quality on Day 0 - Day 16 and Day 0 - Day 60 (p < 0.05) clearly demonstrated that by practicing SSM, participants experienced improvement in the sleep quality. Compared with Day 0 assessment, participants demonstrated significant improvement in the quality of sleep on Day 16 and Day 60. The effect size of the intervention observed on the 16th day of assessment was small, but on the 60th day, a small to medium effect size of the intervention was observed. In the current study we found out that after practicing SSM for two months, participants reported a reduction in the perceived stress, they felt that they are more confident about their ability to handle personal problems, were able to cope with all the things that they had to do, felt that they were on top of the things, and felt less angered. Participants also reported that their overall sleep quality improved; they took less time to fall asleep; they had less disturbances in sleep and less daytime dysfunction due to sleep deprivation. The present study provides clear evidence of the efficacy and safety of non-pharmacological interventions such as SSM in reducing stress and improving sleep quality. Thus, ASTM may be considered a useful intervention to reduce psychological distress in healthy, non-clinical populations, and it can be an alternative remedy for treating poor sleep among individuals and decreasing the use of harmful sedatives.

Keywords: automatic self transcending meditation, Sahaj Samadhi meditation, sleep, stress

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Authors: L. José, S. Vieira, E. Melo, A. R. Pinheiro

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Objectives: This study aims to characterize the stroke profile and the health care provided for people with a stroke in Luanda, Angola. Methods: A prospective longitudinal study was conducted at two Health centers, from March to November 2023, enrolling stroke patients. Data was gathered using a survey created by the researchers and validated by a health panel of experts from Angola. The analysis focused on demographic and stroke characteristics, as well as the care provided. Ethical approval and informed consent were obtained. Results: Preliminary results of a total of 186 patients are described, 122 from a Central Acute Care Hospital, with a mean age of 51.3±14.35 years old, a BMI of 26.7±4.15 kg/m2, 41% male, and 64 patients from a Rehabilitation Center, with 55.6±11.55 years old, a BMI of 27.0±3.8 kg/m2, 53% male. Ischemic stroke was reported as the most representative type in both centers (71.3% and 70.3%, respectively), though 100% of patients had no imaging diagnosis confirmation, neither data about the subtype was given. For patients admitted to the Hospital, discharge occurred before rehabilitation, and no follow-up was possible. No rehabilitation care was delivered in the first 7 days after the stroke. In the Rehabilitation Center, patient’s rehabilitation started in the late subacute phase, after a mean of 171.8±11.5 days. Conclusions: Stroke diagnosis lacks imaging confirmation, which is decisive for proper treatment, and rehabilitation starts during the late subacute phase, which is too late considering the international guidelines and the best window of opportunity for neuroplasticity and recovery. These results highlight the urgent need for the definition of Stroke-directed Health Care Policies in Angola.

Keywords: stroke, personalized health care, functional recovery, quality of life, health policies

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