Search results for: diabetic kidney disease

Authors: Laura Cochrane

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The United States Centers for Disease Control and Prevention has established three categories of biological agents based on their ease of spread and the severity of the disease they cause. Category A biological agents are the highest priority because of their high degree of morbidity and mortality, ease of dissemination, the potential to cause social disruption and panic, special requirements for public health preparedness, and past use as a biological weapon. Despite the threat of Category A biological agents, opportunities for medical intervention exist. This work summarizes public information, consolidated and reviewed across the situational usefulness and disease awareness to offer discussion to three specific Category A agents: anthrax (Bacillus anthracis), botulism (Clostridium botulinum toxin), and smallpox (variola major), and provides an overview on the management of medical countermeasures available to treat these three (3) different types of pathogens. The medical countermeasures are discussed in the setting of pre-exposure prophylaxis, post-exposure prophylaxis, and therapeutic treatments to provide a framework for requirements in public health preparedness.

Keywords: anthrax, botulism, smallpox, medical countermeasures

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Authors: Sh. Khoshemehry, M. J. Pourvaghar, M. E. Bahram

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In modern life, daily physical activity is relatively reduced, which is why the incidence of some diseases associated with overweight and obesity, such as hypertension, diabetes and other chronic illnesses, even in young people are observed. Obesity and overweight is one of the most common metabolic disorders in industrialized countries and in developing countries. One consequence of pathological obesity is cardiovascular disease and metabolic syndrome. In the past, it was believed that adipose tissue was ineffective and served only for storing triglycerides. In this review article, it was tried to refer to the esteemed scientific sources about physical activity and responses of leptin.

Keywords: disease, leptin, obesity, physical activity

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Authors: Evgenia Papathanasiou, Georgios Kokkotis, Georgios Axiaris, Theodoros Argyropoulos, Nikos Viazis, Olga Giouleme, Konstantinos Gkoumas, Αnthia Gatopoulou, Αggelos Theodoulou, Georgios Theocharis, Αngeliki Theodoropoulou, Μaria Κalogirou, Pantelis Karatzas, Κonstantinos Κatsanos, Theodora Kafetzi, Κonstantinos Κarmiris, Αnastasia Κourikou, Ιoannis E Κoutroubakis, Christos Liatsos, Gerassimos J. Mantzaris, Νicoletta Μathou, Georgia Bellou, George Michalopoulos Αikaterini Μantaka, Penelope Nikolaou, Μichael Oikonomou, Dimitrios Polymeros, George Papatheodoridis, Εvdoxia Stergiou, Κonstantinos Soufleris, Εpameinondas Skouloudis, Μaria Tzouvala, Georgia Tsiolakidou, Εftychia Tsironi, Styliani Tsafaraki, Kalliopi Foteinogiannopoulou, Konstantina Chalakatevaki, Αngeliki Christidou, Dimitrios K. Christodoulou, Giorgos Bamias, Spyridon Michopoulos, Εvanthia Zampeli

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Background: Inflammatory bowel disease (IBD) commonly affects female patients of reproductive age, making the interaction between fertility, pregnancy and IBD an important issue in disease management. The effect of disease activity on the outcome of pregnancy and its impact on neonatal growth is a field of intense research. Close follow-up of pregnant IBD patients by a multidisciplinary team improves maternal and neonatal outcomes. Aim – Methods: Α national retrospective study of pregnancies in women with IBD between 2010-2020 was carried out in 22 IBD reference centers in Greece. Patient characteristics such as disease profile, type of treatment, and disease activity during gestation were analyzed in correlation to the method of delivery, pregnancy outcomes, as well as breastfeeding and offspring health. Results: Two-hundred and twenty-three pregnancies in 175 IBD patients were registered in the study. 122 with Crohn’s disease (CD). Median age during diagnosis was 25.6 years (12-44), with median disease duration of 7.4 years (0-23). One-hundred and twenty-nine patients (58%) were recorded during their first pregnancy. Early pregnancy termination was reported by 48 patients (22%). Pregnancy as a result of in vitro fertilization (IVF) occurred in 15 cases (6.7%). At the beginning of gestation, 165 patients (74%) were under treatment: 48 with anti-TNF agents (29%), 43 with azathioprine (26%), 101 with 5-aminosalicylic acid formulations (61%) and 12 with steroids (7%). We recorded 49 cases of IBD flares (22%) during pregnancy. Two-thirds of them (n=30) were in remission at the onset of the pregnancy. Almost half of them (n=22) required corticosteroid treatment. Patients with ulcerative colitis (UC) were in greater risk of disease flare during pregnancy (p<0.001). All but 3 pregnancies (99.1%) resulted in uncomplicated delivery. In 147 cases (67.1%), cesarean delivery was performed. Two late fetal deaths (0.9%) were reported, both in patients with continuously active disease since the beginning of pregnancy. After delivery, 75 patients (34%) presented with a disease flare, which was associated with active disease at the beginning of pregnancy (p <0.001). Conclusion: The majority of female, Greek IBD patients, had a favorable pregnancy outcome. Active inflammation during gestation and UC diagnosis were associated with a negative impact on pregnancy outcomes. The results of this study are in favor of the continuation of IBD treatment during pregnancy.

Keywords: pregnancy, ulcerative colitis, Crohn disease, flare

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Authors: Anida Causevic-Ramosevac, Sabina Semiz

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The aim of this study was to investigate the association of four single nucleotide polymorphisms (SNPs) - rs673548, rs693 in ApoB gene, rs1800775 in CETP gene and rs4846914 in GALNT2 gene with parameters of type 2 diabetes (T2D) and diabetic dyslipidemia in the population of Bosnia and Herzegovina (BH). Materials and methods: Our study involved 352 patients with T2D and 156 healthy subjects. Biochemical and anthropometric parameters were measured in all participants. DNA was extracted from the peripheral blood for the purpose of genetic testing. Polymorphisms in ApoB (rs673548, rs693), CETP (rs1800775) and GALNT2 (rs4846914) genes were analyzed by using Sequenom IPLEX platform. Results: Our results demonstrated significant associations for rs180075 polymorphism in CETP gene with levels of fasting insulin (p = 0.020; p = 0.027; p = 0.044), triglycerides (p = 0.046) and ALT (p = 0.031) activity in control group. In group of diabetic patients, results showed a significant association of rs673548 in ApoB gene with levels of fasting insulin (p = 0.008), HOMA-IR (p = 0.013), VLDL-C (p = 0.037) and CRP (p = 0.029) and rs693 in ApoB gene with BMI (p = 0.025), systolic blood pressure (p = 0.027), fasting insulin (p = 0.037) and HOMA-IR (p = 0.023) levels. Significant associations were also observed for rs1800775 in CETP gene with triglyceride (p = 0.023) levels and rs4846914 in GALNT2 gene with HbA1C (p = 0.013) and triglyceride (p = 0.043) levels. Conclusion: In conclusion, this is the first study that examined the impact of variations of candidate genes on a wide range of metabolic parameters in BH population. Our results suggest an association of variations of ApoB, CETP and GALNT2 genes with specific markers of T2D and dyslipidemia. Further studies would be needed in order to confirm these genetic effects in other ethnic groups as well.

Keywords: ApoB, CETP, dyslipidemia, GALNT2, type 2 diabetes

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Authors: Alice Huffman, Joseph Hartland, Sam Gibbs

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Dermatology is often a neglected specialty in low-resource settings, despite the high morbidity associated with skin disease. This becomes even more significant when associated with HIV infection, as dermatological conditions are more common and aggressive in HIV positive patients. African countries have the highest HIV infection rates and skin conditions are frequently misdiagnosed and mismanaged, because of a lack of dermatological training and educational material. The frequent lack of diagnostic tests in the African setting renders basic clinical skills all the more vital. This project aimed to improve diagnosis and treatment of skin disease in the HIV population in a district hospital in Malawi. A basic dermatological clinical tool was developed and produced in collaboration with local staff and based on available literature and data collected from clinics. The aim was to improve diagnostic accuracy and provide guidance for the treatment of skin disease in HIV positive patients. A literature search within Embase, Medline and Google scholar was performed and supplemented through data obtained from attending 5 Antiretroviral clinics. From the literature, conditions were selected for inclusion in the resource if they were described as specific, more prevalent, or extensive in the HIV population or have more adverse outcomes if they develop in HIV patients. Resource-appropriate treatment options were decided using Malawian Ministry of Health guidelines and textbooks specific to African dermatology. After the collection of data and discussion with local clinical and pharmacy staff a list of 15 skin conditions was included and a booklet created using the simple layout of a picture, a diagnostic description of the disease and treatment options. Clinical photographs were collected from local clinics (with full consent of the patient) or from the book ‘Common Skin Diseases in Africa’ (permission granted if fully acknowledged and used in a not-for-profit capacity). This tool was evaluated by the local staff, alongside an educational teaching session on skin disease. This project aimed to reduce uncertainty in diagnosis and provide guidance for appropriate treatment in HIV patients by gathering information into one practical and manageable resource. To further this project, we hope to review the effectiveness of the tool in practice.

Keywords: dermatology, HIV, Malawi, skin disease

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Authors: Ibtisam Al-Zaru

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Background: Worldwide, depression among coronary artery disease (CAD) patients is considered a serious problem that may cause many complications and negative consequences; particularly serious being increased mortality and morbidity rate. Studying depression among CAD patients in Jordan has not been investigated thoroughly and thus a need for further studies has been a priority. Aims: To assess depression in non-hospitalized Jordanian patients with CAD; to describe the relationship between socio-demographic data, health related factors, and depression; and to examine the best predictors of depression in non-hospitalized Jordanian patients with CAD. Method: A cross-sectional-descriptive design was used to collect data from 174 non-hospitalized Jordanian patients diagnosed with CAD in outpatients’ cardiac clinics, using a self- administered questionnaires and Cardiac Depression Scale. Results: 53.4% of CAD patients reported mild/moderate, and severe depressive symptoms. Significant relationships between depressive symptoms and some demo-clinical characteristics (i.e. being female gender; having of chronic disease and surgical history; being physically inactive, and perceived their sexual activity, physical and psychological as poor). The preceding factors are also found to be statistically significant predictors for depression among this patients’ group. Conclusion: Jordanian patients with CAD had various levels of severity regarding their depressive symptoms. Therefore, health care providers need to introduce depression assessment and treatment in cardiac rehabilitation to control depression and its impact on the patient. Consequently, such control will reduce co-morbidity, mortality, complications and health costs among CAD patients and enhance the quality of their lives.

Keywords: coronary artery disease, predictors, depression, prevalence

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Authors: Suhaida Salleh, Tee Yei Kheng

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Black pod is the most commonly destructive disease of cacao (Theobroma cacao) which cause major losses to global production of cocoa beans. The genus of Phytophthora is the important pathogen of this disease worldwide. The species of P. megakarya causes black pod disease in West Africa, whereas P. capsici and P. citrophthora cause the incident in Central and South America. In Malaysia, this disease is caused by P. palmivora which infect all stages of pod development including flower cushion, cherelle, immature and mature pods. This pathogen destroys up to 10% of trees yearly through stem cankers and causes 20 to 30% pod damages through black pod rot. Since P. palmivora has a high impact on cocoa yield, it is crucial to identify some of the abiotic factors that can constrain their growth. In an effort to evaluate the effect of different substrates and temperatures to the growth of P. palmivora, a laboratory study was done under a different range of temperatures. Different substrate for the growth of P. palmivora were used which are corn meal agar (CMA) media and detached pod of cocoa. An agar plug of seven days old of P. palmivora growth was transferred on both substrates and incubated at 24, 27, 30, 33 and 36ᵒC, respectively. The diameter of lesion on pod and the cultural growth of pathogen was recorded for 7 consecutive days. The optimum incubation temperature of P. palmivora on both substrates is at 27ᵒC. However, the growth tends to be inhibited as the temperature increases. No lesion developed on pod surface incubated at 36ᵒC and only a small lesion observed at 33ᵒC. The sporulation with the formation of white mycelial growth on pod surface was only visible at optimum temperature, 27ᵒC. On CMA, the pathogen grew over the entire range of temperatures tested. The study is, therefore, concluded that P. palmivora grow the best at temperature of 27ᵒC on both substrates and their growth begin to inhibit when the temperature rises to more than 27ᵒC. The growth pattern of this pathogen is similar on both pod surface and cultural media.

Keywords: cocoa, Phytophthora palmivora, substrate, temperature

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Authors: Yasinta Ratna Esti Wulandari, Vivitri Dewi Prasasty, Adrianus Rio, Cindy Geniola

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Mulberry is a plant that widely cultivated around the world, mostly for silk industry. In recent years, the study showed that the mulberry leaves have an anti-diabetic effect which mostly comes from the compound known as 1-deoxynojirimycin (DNJ). DNJ is a very potent α-glucosidase inhibitor. It will decrease the degradation rate of carbohydrates in digestive tract, leading to slower glucose absorption and reducing the post-prandial glucose level significantly. The mulberry leaves also known as the best source of DNJ. Since then, the DNJ in mulberry leaves had received a considerable attention, because of the increased number of diabetic patients and the raise of people awareness to find a more natural cure for diabetic. The DNJ content in mulberry leaves varied depend on the mulberry species, leaf’s age, and the plant’s growth environment. Few of the mulberry varieties that were cultivated in Indonesiaare Morus alba var. kanva-2, M. alba var. multicaulis, M. bombycis var. lembang, and M. cathayana. The lack of data concerning phytochemicals contained in the Indonesian mulberry leaves are restraining their use in the medicinal field. The aim of this study is to fully utilize the use of mulberry leaves cultivated in Indonesia as a medicinal herb in local, national, or global community, by determining the DNJ and other phytochemical contents in them. This study used eight leaf samples which are the young leaves and mature leaves of both Morus alba var. kanva-2, M. alba var. multicaulis, M. bombycis var. lembang, and M. cathayana. The DNJ content was analyzed using reverse phase high performance liquid chromatography (HPLC). The stationary phase was silica C18 column and the mobile phase was acetonitrile:acetic acid 0.1% 1:1 with elution rate 1 mL/min. Prior to HPLC analysis the samples were derivatized with FMOC to ensure the DNJ detectable by VWD detector at 254 nm. Results showed that the DNJ content in samples are ranging from 2.90-0.07 mg DNJ/ g leaves, with the highest content found in M. cathayana mature leaves (2.90 ± 0.57 mg DNJ/g leaves). All of the mature leaf samples also found to contain higher amount of DNJ from their respective young leaf samples. The phytochemicals in leaf samples was tested using qualitative test. Result showed that all of the eight leaf samples contain alkaloids, phenolics, flavonoids, tannins, and terpenes. The presence of this phytochemicals contribute to the therapeutic effect of mulberry leaves. The pyrolysis-gas chromatography-mass spectrometry (Py-GC-MS) analysis was also performed to the eight samples to quantitatively determine their phytochemicals content. The pyrolysis temperature was set at 400 °C, with capillary column Phase Rtx-5MS 60 × 0.25 mm ID stationary phase and helium gas mobile phase. Few of the terpenes found are known to have anticancer and antimicrobial properties. From all the results, all of four samples of mulberry leaves which are cultivated in Indonesia contain DNJ and various phytochemicals like alkaloids, phenolics, flavonoids, tannins, and terpenes which are beneficial to our health.

Keywords: Morus, 1-deoxynojirimycin, HPLC, Py-GC-MS

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Authors: J. K Adedeji, O. H Olowomofe, C. O Alo, S.T Ijatuyi

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The issue of high blood sugar level, the effects of which might end up as diabetes mellitus, is now becoming a rampant cardiovascular disorder in our community. In recent times, a lack of awareness among most people makes this disease a silent killer. The situation calls for urgency, hence the need to design a device that serves as a monitoring tool such as a wrist watch to give an alert of the danger a head of time to those living with high blood glucose, as well as to introduce a mechanism for checks and balances. The neural network architecture assumed 8-15-10 configuration with eight neurons at the input stage including a bias, 15 neurons at the hidden layer at the processing stage, and 10 neurons at the output stage indicating likely symptoms cases. The inputs are formed using the exclusive OR (XOR), with the expectation of getting an XOR output as the threshold value for diabetic symptom cases. The neural algorithm is coded in Java language with 1000 epoch runs to bring the errors into the barest minimum. The internal circuitry of the device comprises the compatible hardware requirement that matches the nature of each of the input neurons. The light emitting diodes (LED) of red, green, and yellow colors are used as the output for the neural network to show pattern recognition for severe cases, pre-hypertensive cases and normal without the traces of diabetes mellitus. The research concluded that neural network is an efficient Accu-Chek design tool for the proper monitoring of high glucose levels than the conventional methods of carrying out blood test.

Keywords: Accu-Check, diabetes, neural network, pattern recognition

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Authors: Nazmul Haque, Syeda Tasnuva Maria

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Sheehan's Syndrome (SS), also known as postpartum hypopituitarism, is a rare but potentially serious condition resulting from ischemic necrosis of the pituitary gland, often occurring during or after childbirth. This syndrome is characterized by hypopituitarism, leading to deficiencies in various hormones produced by the pituitary gland. The primary cause is typically severe postpartum hemorrhage, leading to inadequate blood supply and subsequent necrosis of the pituitary tissue. This chronic hypopituitarism sometimes plays the role of premature atherosclerosis, which may lead to cardiovascular disease. This abstract provides a comprehensive overview of Sheehan's Syndrome with ischaemic heart disease, encompassing its pathophysiology, clinical manifestations, and current management strategies. The disorder presents a wide spectrum of symptoms, including chest pain, fatigue, amenorrhea, lactation failure, hypothyroidism, and adrenal insufficiency. Timely diagnosis is crucial, as delayed recognition can lead to complications and long-term health consequences. We herein report a patient complaining of chronic fatigue symptoms, aggressiveness, chest pain, and breathlessness with repeated LOC that were diagnosed with SS with IHD. The patient was treated with antiplatelet, antianginal, steroids, and hormone replacement with marked improvement in his overall condition.

Keywords: ischaemic heart disease, Sheehan's syndrome, post-partum haemorrhage, pituitary gland

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Authors: Davies Obaromi, Qin Yongsong, James Ndege

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To interpolate scattered or regularly distributed data, there are imprecise or exact methods. However, there are some of these methods that could be used for interpolating data in a regular grid and others in an irregular grid. In spatial epidemiology, it is important to examine how a disease prevalence rates are distributed in space, and how they relate with each other within a defined distance and direction. In this study, for the geographic and graphic representation of the disease prevalence, linear and biharmonic spline methods were implemented in MATLAB, and used to identify, localize and compare for smoothing in the distribution patterns of tuberculosis (TB) in Eastern Cape Province. The aim of this study is to produce a more “smooth” graphical disease map for TB prevalence patterns by a 3-D curve fitting techniques, especially the biharmonic splines that can suppress noise easily, by seeking a least-squares fit rather than exact interpolation. The datasets are represented generally as a 3D or XYZ triplets, where X and Y are the spatial coordinates and Z is the variable of interest and in this case, TB counts in the province. This smoothing spline is a method of fitting a smooth curve to a set of noisy observations using a spline function, and it has also become the conventional method for its high precision, simplicity and flexibility. Surface and contour plots are produced for the TB prevalence at the provincial level for 2012 – 2015. From the results, the general outlook of all the fittings showed a systematic pattern in the distribution of TB cases in the province and this is consistent with some spatial statistical analyses carried out in the province. This new method is rarely used in disease mapping applications, but it has a superior advantage to be assessed at subjective locations rather than only on a rectangular grid as seen in most traditional GIS methods of geospatial analyses.

Keywords: linear, biharmonic splines, tuberculosis, South Africa

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Authors: Walid Moudani

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The healthcare environment is generally perceived as being information rich yet knowledge poor. However, there is a lack of effective analysis tools to discover hidden relationships and trends in data. In fact, valuable knowledge can be discovered from application of data mining techniques in healthcare system. In this study, a proficient methodology for the extraction of significant patterns from the coronary heart disease warehouses for heart attack prediction, which unfortunately continues to be a leading cause of mortality in the whole world, has been presented. For this purpose, we propose to enumerate dynamically the optimal subsets of the reduced features of high interest by using rough sets technique associated to dynamic programming. Therefore, we propose to validate the classification using Random Forest (RF) decision tree to identify the risky heart disease cases. This work is based on a large amount of data collected from several clinical institutions based on the medical profile of patient. Moreover, the experts’ knowledge in this field has been taken into consideration in order to define the disease, its risk factors, and to establish significant knowledge relationships among the medical factors. A computer-aided system is developed for this purpose based on a population of 525 adults. The performance of the proposed model is analyzed and evaluated based on set of benchmark techniques applied in this classification problem.

Keywords: multi-classifier decisions tree, features reduction, dynamic programming, rough sets

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Authors: Mahfoodha Al-Kitani, Dylan Thompson, Keith Stokes

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Sickle cell disease (SCD) and sickle cell trait (SCT) are the most common hematological diseases in Oman according to the national survey of genetic blood disorders. The aim of this study was to determine markers of physical fitness and anthropometrics indices in children with sickle cell disease and children with sickle cell trait and compare them with normal healthy children of the same age. One hundred and twenty male children participated in the present study divided to three groups: 40 with sickle disease (SCD; age, 13.3(.80), height, 131.9(3.5), mass, 29.2(3.1)); 40 with sickle cell trait (SCT; age, 12.2(.80), height, 141.0(9.9), mass, 38.0(4.4)); and 40 controls with normal hemoglobin (Con; age, 12.8(.80), height, 139.4(8.7), mass, 37.2(4.3)). All children completed a 5-min running exercise test on a treadmill at speed corresponding to 5 km/hr. Heart rate and was recorded during exercise and during 10-min of recovery. Blood lactate was measured before and 5 min after the completion of exercise. Children with SCD exhibited a higher mean value (P < 0.05) for percent body fat and fat mass than the normal healthy subjects and SCT subjects. Resting values of hemoglobin were similar in SCT (11.04(.78)) and control (10.8(94)) groups, and lower in SCD (8.89(.54); P < 0.05). There was a strong correlation between peak heart rate and resting hemoglobin levels for the three groups (r= -.472. n= 120, p < .0005).The SCD group (175.2(10.3)) exhibited higher mean heart rate during exercise than those observed in the SCT (143.7(9.5)) and normal control children (144.5(22.4); P < 0.05). Additionally, SCD children showed higher serum lactate values before and after treadmill exercise compared to the other groups (P < 0.05). Children with sickle cell trait demonstrate similar physical fitness level and similar exercise responses to treadmill stress test to normal children. In contrast, SCD children have lower body mass, higher fat mass and lower physical fitness than children with SCT and healthy controls.

Keywords: sickle cell disease, sickle cell trait, children, exercise

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Authors: Niki Hayatgheib, SéGolèNe Calvez, Catherine Fournel, Lionel Pineau, Herve Pouliquen, Emmanuelle Moreau

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Furunculosis caused by infection with Aeromonas salmonicida subsp. salmonicida has been a known disease found principally in salmonid aquaculture. Vaccination has been partly successful in preventing this disease, but outbreaks still occur. The application of functional feed additive found to be a promising yield to improve fish health against diseases. In this study, we tested the efficacy of prebiotics and plant essential oils-enriched diet on immune response and disease resistance in vaccinated and non-vaccinated rainbow trout (Oncorhynchus mykiss) against furunculosis. A total of 600 fish were fed with the basal diet or supplement. On 4th week of feeding, fish were vaccinated with an autovaccine. Following 8 weeks, fish were challenged with Aeromonas salmonicida subsp. salmonicida and mortalities were recorded for 3 weeks. Lysozyme activity and antibody titer in serum were measured in different groups. The results of this study showed that lysozyme and circulatory antibody titer in plasma elevated significantly in vaccinated fish fed with additive. The best growth rate and relative percentage survival (62%) were in fish fed with a supplement, while 15% in control fish. Overall, prebiotics and essential oils association can be considered as a potential component for enhancing vaccine efficacy against furunculosis by increasing the growth performance, immune responses and disease resistance in rainbow trout.

Keywords: aeromonas salmonicida subsp. salmonicida, aquaculture, disease resistance, fish, immune response, prebiotics-essential oils feed additive, rainbow trout, vaccination

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Authors: Jinan Fiaidhi, Sabah Mohammed, Petros Zezos

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Capsule endoscopy (CE) is an established noninvasive diagnostic modality in investigating small bowel disease. CE has a pivotal role in assessing patients with suspected bleeding or identifying evidence of active Crohn's disease in the small bowel. However, CE produces lengthy videos with at least eighty thousand frames, with a frequency rate of 2 frames per second. Gastroenterologists cannot dedicate 8 to 15 hours to reading the CE video frames to arrive at a diagnosis. This is why the issue of analyzing CE videos based on modern artificial intelligence techniques becomes a necessity. However, machine learning, including deep learning, has failed to report robust results because of the lack of large samples to train its neural nets. In this paper, we are describing a thick data approach that learns from a few anchor images. We are using sound datasets like KVASIR and CrohnIPI to filter candidate frames that include interesting anomalies in any CE video. We are identifying candidate frames based on feature extraction to provide representative measures of the anomaly, like the size of the anomaly and the color contrast compared to the image background, and later feed these features to a decision tree that can classify the candidate frames as having a condition like the Crohn's Disease. Our thick data approach reported accuracy of detecting Crohn's Disease based on the availability of ulcer areas at the candidate frames for KVASIR was 89.9% and for the CrohnIPI was 83.3%. We are continuing our research to fine-tune our approach by adding more thick data methods for enhancing diagnosis accuracy.

Keywords: thick data analytics, capsule endoscopy, Crohn’s disease, siamese neural network, decision tree

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Authors: Snigdha Sahai, Devaki Chikkavenkatappa Yellappa

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This study outlines approaches for testing and validating stochastic models used in epidemiology, focusing on the integration and functional testing of simulation code. It details methods for combining simple functions into comprehensive simulations, distinguishing between deterministic and stochastic components, and applying tests to ensure robustness. Techniques include isolating stochastic elements, utilizing large sample sizes for validation, and handling special cases. Practical examples are provided using R code to demonstrate integration testing, handling of incorrect inputs, and special cases. The study emphasizes the importance of both functional and defensive programming to enhance code reliability and user-friendliness.

Keywords: computational epidemiology, epidemiology, public health, infectious disease modeling, statistical analysis, health data analysis, disease transmission dynamics, predictive modeling in health, population health modeling, quantitative public health, random sampling simulations, randomized numerical analysis, simulation-based analysis, variance-based simulations, algorithmic disease simulation, computational public health strategies, epidemiological surveillance, disease pattern analysis, epidemic risk assessment, population-based health strategies, preventive healthcare models, infection dynamics in populations, contagion spread prediction models, survival analysis techniques, epidemiological data mining, host-pathogen interaction models, risk assessment algorithms for disease spread, decision-support systems in epidemiology, macro-level health impact simulations, socioeconomic determinants in disease spread, data-driven decision making in public health, quantitative impact assessment of health policies, biostatistical methods in population health, probability-driven health outcome predictions

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Authors: Soumaya Mrabet, Imen Akkari, Amira Atig, Elhem Ben Jazia

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Introduction: Primary biliary cirrhosis (PBC) is a cholestatic cholangitis of unknown etiology. It is frequently associated with autoimmune diseases, which explains their systematic screening. The aim of our study was to determine the prevalence and the type of autoimmune disorders associated with PBC and to assess their impact on the prognosis of the disease. Material and methods: It is a retrospective study over a period of 16 years (2000-2015) including all patients followed for PBC. In all these patients we have systematically researched: dysthyroidism (thyroid balance, antithyroid autoantibodies), type 1 diabetes, dry syndrome (ophthalmologic examination, Schirmer test and lip biopsy in case of Presence of suggestive clinical signs), celiac disease(celiac disease serology and duodenal biopsies) and dermatological involvement (clinical examination). Results: Fifty-one patients (50 women and one men) followed for PBC were collected. The Mean age was 54 years (37-77 years). Among these patients, 30 patients(58.8%) had at least one autoimmune disease associated with PBC. The discovery of these autoimmune diseases preceded the diagnosis of PBC in 8 cases (26.6%) and was concomitant, through systematic screening, in the remaining cases. Autoimmune hepatitis was found in 12 patients (40%), defining thus an overlap syndrome. Other diseases were Hashimoto's thyroiditis (n = 10), dry syndrome (n = 7), Gougerot Sjogren syndrome (n=6), celiac disease (n = 3), insulin-dependent diabetes (n = 1), scleroderma (n = 1), rheumatoid arthritis (n = 1), Biermer Anemia (n=1) and Systemic erythematosus lupus (n=1). The two groups of patients with PBC with or without associated autoimmune disorders were comparable for bilirubin levels, Child-Pugh score, and response to treatment. Conclusion: In our series, the prevalence of autoimmune diseases in PBC was 58.8%. These diseases were dominated by autoimmune hepatitis and Hashimoto's thyroiditis. Even if their association does not seem to alter the prognosis, screening should be systematic in order to institute an early and adequate management.

Keywords: autoimmune diseases, autoimmune hepatitis, primary biliary cirrhosis, prognosis

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Authors: Kayne Uriel K. Rodrigo, Jerriane Hillary Heart S. Marcial, Samuel C. Brillo

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Rice leaf diseases significantly impact yield production in rice-dependent countries, affecting their agricultural sectors. As part of precision agriculture, early and accurate detection of these diseases is crucial for effective mitigation practices and minimizing crop losses. Hence, this study proposes an enhancement to the Convolutional Neural Network (CNN), a widely-used method for Rice Leaf Disease Image Classification, by incorporating MobileViTV2—a recently advanced architecture that combines CNN and Vision Transformer models while maintaining fewer parameters, making it suitable for broader deployment on edge devices. Our methodology utilizes a publicly available rice disease image dataset from Kaggle, which was validated by a university structural biologist following the guidelines provided by the Philippine Rice Institute (PhilRice). Modifications to the dataset include renaming certain disease categories and augmenting the rice leaf image data through rotation, scaling, and flipping. The enhanced dataset was then used to train the MobileViTV2 model using the Timm library. The results of our approach are as follows: the model achieved notable performance, with 98% accuracy in both training and validation, 6% training and validation loss, and a Receiver Operating Characteristic (ROC) curve ranging from 95% to 100% for each label. Additionally, the F1 score was 97%. These metrics demonstrate a significant improvement compared to a conventional CNN-based approach, which, in a previous 2022 study, achieved only 78% accuracy after using 5 convolutional layers and 2 dense layers. Thus, it can be concluded that MobileViTV2, with its fewer parameters, outperforms traditional CNN models, particularly when applied to Rice Leaf Disease Image Identification. For future work, we recommend extending this model to include datasets validated by international rice experts and broadening the scope to accommodate biotic factors such as rice pest classification, as well as abiotic stressors such as climate, soil quality, and geographic information, which could improve the accuracy of disease prediction.

Keywords: convolutional neural network, MobileViTV2, rice leaf disease, precision agriculture, image classification, vision transformer

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Authors: Mohamed A. Morsy, Azza A. El-Sheikh, Abdulla Y. Al-Taher

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Resveratrol (RES) is a well-known polyphenol antioxidant. We have previously shown that testicular protective effect of RES against the anticancer drug methotrexate (MTX)-induced toxicity involves transporter-mediated mechanisms. Here, we investigated the effect of RES on MTX-induced nephrotoxicity. Rats were administered RES (10 mg/kg/day) for 8 days, with or without a single MTX dose (20 mg/kg i.p.) at day 4 of the experiment. MTX induced nephrotoxicity evident by significantly increase in serum blood urea nitrogen and creatinine compared to control, as well as distortion of kidney microscopic structure. MTX also significantly increased renal nitric oxide level, with induction of inducible nitric oxide synthase expression. MTX also significantly up-regulated fas ligand and caspase 3. Administering RES prior to MTX significantly improved kidney function and microscopic picture, as well as significantly decreased nitrosative and apoptotic markers compared to MTX alone. RES, but not MTX, caused significant increase in expression of breast cancer resistance protein (BCRP), an apical efflux renal transporter that participates in urinary elimination of both MTX and RES. Interestingly, concomitant MTX and RES caused further up-regulation of renal Bcrp compared to RES alone. Using Human BCRP ATPase assay, both RES and MTX exhibited dose-dependent increase in ATPase activity, with Km values of 0.52 ± 0.03 and 30.9 ± 4.2 µM, respectively. Furthermore, combined RES and MTX caused ATPase activity which was significantly less than maximum ATPase activity attained by the positive control; sulfasalazine (12.5 µM). In conclusion, RES exerted nephro-protection against MTX-induced toxicity through anti-nitrosative and anti-apoptotic effects, as well as via up-regulation of renal Bcrp.

Keywords: methotrexate, resveratrol, nephrotoxicity, breast cancer resistance protein

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Authors: Abeer A. Aljohani

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COVID-19 virus spread has been one of the extreme pandemics across the globe. It is also referred to as coronavirus, which is a contagious disease that continuously mutates into numerous variants. Currently, the B.1.1.529 variant labeled as omicron is detected in South Africa. The huge spread of COVID-19 disease has affected several lives and has surged exceptional pressure on the healthcare systems worldwide. Also, everyday life and the global economy have been at stake. This research aims to predict COVID-19 disease in its initial stage to reduce the death count. Machine learning (ML) is nowadays used in almost every area. Numerous COVID-19 cases have produced a huge burden on the hospitals as well as health workers. To reduce this burden, this paper predicts COVID-19 disease is based on the symptoms and medical history of the patient. This research presents a unique architecture for COVID-19 detection using ML techniques integrated with feature dimensionality reduction. This paper uses a standard UCI dataset for predicting COVID-19 disease. This dataset comprises symptoms of 5434 patients. This paper also compares several supervised ML techniques to the presented architecture. The architecture has also utilized 10-fold cross validation process for generalization and the principal component analysis (PCA) technique for feature reduction. Standard parameters are used to evaluate the proposed architecture including F1-Score, precision, accuracy, recall, receiver operating characteristic (ROC), and area under curve (AUC). The results depict that decision tree, random forest, and neural networks outperform all other state-of-the-art ML techniques. This achieved result can help effectively in identifying COVID-19 infection cases.

Keywords: supervised machine learning, COVID-19 prediction, healthcare analytics, random forest, neural network

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Authors: Aadil Khan, Yasser Chomayil, P. P. Venugopalan

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Background: Budd-Chiari syndrome is caused by thrombosis of the hepatic veins and/or the thrombosis of the intrahepatic or suprahepatic IVC. The etiology remains idiopathic in 16% -35% of cases. Malignancy, rheumatological disorder, myeloproliferative disease, inheritable coagulopathy, infection or hyperestrogen state can be identified in many cases. Methodology: Review of case records of the patient presented to Aster Medcity, Emergency Department, Cochin. Introduction:17 years old female was presented to ED with fever, jaundice and abdominal distention since 1 week. O/E: Pallor+, icterus+. Abdomen- gross distension+, shifting dullness+, generalized anasarca+. USG abdomen showed hepatomegaly with mild coarse echotexture and moderate to gross ascites. CT abdomen and chest showed hepatomegaly with thrombosis of all three hepatic vein and moderate ascites suggestive of Budd-Chiari syndrome. Patient was taken for catheter vein thrombolysis. Venogram done the next day revealed almost > 50% opening of the right hepatic vein. Concurrent doppler showed colour and doppler signals in middle hepatic veins. She gradually improved and was discharged home on anticoagulant and adviced regular follow up. Conclusion: Being a rare disease in this young population, high suspicion is required when evaluating young patients with abdominal pain and jaundice.

Keywords: Budd-Chiari syndrome, rare disease, abdominal pain, India

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Authors: Ethan James

Abstract:

Over one billion people worldwide suffer from some level of vision loss or blindness as a result of progressive retinal diseases. Many patients, particularly in developing areas, are incorrectly diagnosed or undiagnosed whatsoever due to unconventional diagnostic tools and screening methods. Artificial intelligence (AI) based on deep learning (DL) convolutional neural networks (CNN) have recently gained a high interest in ophthalmology for its computer-imaging diagnosis, disease prognosis, and risk assessment. Optical coherence tomography (OCT) is a popular imaging technique used to capture high-resolution cross-sections of retinas. In ophthalmology, DL has been applied to fundus photographs, optical coherence tomography, and visual fields, achieving robust classification performance in the detection of various retinal diseases including macular degeneration, diabetic retinopathy, and retinitis pigmentosa. However, there is no complete diagnostic model to analyze these retinal images that provide a diagnostic accuracy above 90%. Thus, the purpose of this project was to develop an AI model that utilizes machine learning techniques to automatically diagnose specific retinal diseases from OCT scans. The algorithm consists of neural network architecture that was trained from a dataset of over 20,000 real-world OCT images to train the robust model to utilize residual neural networks with cyclic pooling. This DL model can ultimately aid ophthalmologists in diagnosing patients with these retinal diseases more quickly and more accurately, therefore facilitating earlier treatment, which results in improved post-treatment outcomes.

Keywords: artificial intelligence, deep learning, imaging, medical devices, ophthalmic devices, ophthalmology, retina

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Authors: Cherrie Mae S. Sia, Noel J. Belonguel, Jarungchai Anton S. Vatanagul

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Background: Parkinson’s disease (PD) is a chronic progressive, neurodegenerative disorder known for its motor symptoms such as bradykinesia, resting tremor, muscle rigidity, and postural instability. Patients with PD also experience non-motor symptoms (NMS) such as depression, fatigue, and sleep disturbances that are most of the time unrecognized by clinicians. This may be due to the lack of spontaneous reports from the patients or partly because of the lack of systematic questioning from the healthcare professional. There is limited data with regards to these NMS especially that of Filipino patients with PD. Objectives: This study aims to determine the non-motor symptoms of Filipino patients with Parkinson’s disease. Materials and Methods: This is a prospective, cohort study involving thirty-four patients of Filipino-descent diagnosed with PD in three out-patient clinics in Cebu City from April to September 2014. Each patient was interviewed using the Non-Motor Symptom Scale (NMSS). A Cebuano version of the NMSS was also provided for the non-English speaking patients. Interview time was approximately ten to fifteen minutes for each respondent. Results: Of the thirty-four patients with Parkinson’s disease, majority was noted to be males (N=19) and the disease was noted to be more prevalent in patients with a mean age of 62 (SD±9) years old. Hypertension (59%) and diabetes mellitus (29%) were the common co-morbidities in the study population. All patients presented more than one NMS, with insomnia (41.2%), poor memory (23.5%) and depression (14.7%) being the first non-motor symptoms to occur. Symptoms involving mood/cognition (mean=2.21), and attention/memory (mean=2.05) were noted to be the most frequent and of moderate severity. Based on the NMSS, the symptoms that were noted to be mild and often to occur were those that involved the mood/cognition (score=3.84), attention/memory (score=3.50), and sleep/fatigue (score=3.00) domains. Levodopa-Carbidopa, Ropinirole, and Pramipexole were the most frequently used medications in the study population. Conclusion: Non-motor symptoms (NMS) are common in patients with Parkinson’s disease (PD). They appear at the time of diagnosis of PD or even before the motor symptoms manifest. The earliest non-motor symptoms to occur are insomnia, poor memory, and depression. Those pertaining to mood/cognition and attention/memory are the most frequent NMS and they are of moderate severity. Identifying these NMS by doing a questionnaire-guided interview such as the Non-Motor Symptom Scale (NMSS) before they can become more severe and affect the patient’s quality of life is a must for every clinician caring for a PD patient. Early treatment and control of these NMS can then be given, hence, improving the patient’s outcome and prognosis.

Keywords: non motor symptoms, Parkinson's Disease, insomnia, depression

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Authors: Ranveet Saggu, Saad Bin Ahmed

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Cardiovascular Disease (CVD) is the leading cause of death worldwide. One of its main manifestations, myocardial infarction (commonly known as a heart attack), occurs about 750,000 times a year, caused by insufficient blood flow to a portion of the heart muscle. A quick and accurate diagnosis of a heart attack or heart failure is crucial in the treatment of the patient. The aim of this research project is to improve the prediction of cardiovascular diseases by automating risk assessment using binary classifiers. The methodology includes Exploratory Data Analysis (EDA), which helps to obtain information about the dataset with the help of visualizations and metrics. Additionally, Feature Engineering techniques is employed to address missing values, outliers, feature extraction, and normalizing the dataset. Subsequently, various classification machine learning algorithms are trained, and their accuracy along with other metrics are evaluated to identify the most efficient model in terms of processing time and predictive performance.

Keywords: cardiovascular disease, machine learning, deci- sion trees, logistic regression, k-nearest neighbor, xgboost, random forest, gradient boosting

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Authors: Ruttayaporn Ngasaman, Saowakon Indouang, Usa Chethanond

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Leptospirosis is a public health concern zoonosis in Thailand. Human and animals are often infected by contact with contaminated water. The infected animals play an important role in leptospira infection for both human and other hosts via urine. In humans, it can cause a wide range of symptoms, some of which may present mild flu-like symptoms including fever, vomiting, and jaundice. Without treatment, Leptospirosis can lead to kidney damage, meningitis, liver failure, respiratory distress, and even death. The prevalence of leptospirosis in stray animals in Thailand is unknown. The aim of this study was to investigate leptospira infection in stray animals including dogs and cats in Songkhla province, Thailand. Total of 434 blood samples were collected from 370 stray dogs and 64 stray cats during the population control program from 2014 to 2018. Screening test using latex agglutination for the detection of antibodies against Leptospira interrogans in serum samples shows 29.26% (127/434) positive. There were 120 positive samples of stray dogs and 7 positive samples of stray cats. Detection by polymerase chain reaction specific to LipL32 gene of Leptospira interrogans showed 1.61% (7/434) positive. Stray cats (5/64) show higher prevalence than stray dogs (2/370). Although active infection was low detected, but seroprevalence was high. This result indicated that stray animals were not active infection during sample collection but they use to get infected or in a latent period of infection. They may act as a reservoir for domestic animals and human in which stay in the same environment. In order to prevent and reduce the risk of leptospira infection in a human, stray animals should be done health checking, vaccination, and disease treatment.

Keywords: leptospirosis, stray animals, risk reduction, Thailand

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Authors: Nino G. Vepkhvadze, Tea Enukidze

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Every year the number of countries around the world face the risk of the spread of infectious diseases that bring significant ecological and social-economic damage. Hence, the importance of food product safety is emphasized that is the issue of interest for many countries. To solve them, it’s necessary to conduct preventive measures against the diseases, have accurate diagnostic results, leadership, and management. The Peste des petits ruminants (PPR) disease is caused by a morbillivirus closely related to the rinderpest virus. PPR is a transboundary disease as it emerges and evolves, considered as one of the top most damaging animal diseases. The disease imposed a serious threat to sheep-breeding when the farms of sheep, goats are significantly growing within the country. In January 2016, PPR was detected in Georgia. Up to present the origin of the virus, the age relationship of affected ruminants and the distribution of PPRV in Georgia remains unclear. Due to the nature of PPR, and breeding practices in the country, reemerging of the disease in Georgia is highly likely. The purpose of the studies is to provide laboratories with efficient tools allowing the early detection of PPR emergence and re-emergences. This study is being accomplished under the Biological Threat Reduction Program project with the support of the Defense Threat Reduction Agency (DTRA). The purpose of the studies is to investigate the samples and identify areas at high risk of the disease. Georgia has a high density of small ruminant herds bred as free-ranging, close to international borders. Kakheti region, Eastern Georgia, will be considered as area of high priority for PPR surveillance. For this reason, in 2019, in Kakheti region investigated n=484 sheep and goat serum and blood samples from the same animals, utilized serology and molecular biology methods. All samples were negative by RT-PCR, and n=6 sheep samples were seropositive by ELISA-Ab. Future efforts will be concentrated in areas where the risk of PPR might be high such as international bordering regions of Georgia. For diagnostics, it is important to integrate the PPRV knowledge with epidemiological data. Based on these diagnostics, the relevant agencies will be able to control the disease surveillance.

Keywords: animal disease, especially dangerous pathogen, laboratory diagnostics, virus

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Authors: Sina Mahdavi

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Multiple sclerosis (MS) is a progressive inflammatory autoimmune disease of the CNS that affects the myelination process in the central nervous system (CNS). Complex interactions of various "environmental or infectious" factors may act as triggers in autoimmunity and disease progression. The association between viral infections, especially human immunodeficiency virus (HIV) and MS is one potential cause that is not well understood. This study aims to summarize the available data on human HIV infection in MS disease progression. In this study, the keywords "Multiple sclerosis", "Human immunodeficiency virus ", and "Central nervous system" in the databases PubMed, and Google Scholar between 2017 and 2022 were searched and 15 articles were chosen, studied, and analyzed. Revealed histologic signs of "MS-like illness" in the setting of HIV, which comprised widespread demyelination with reactive astrocytes, foamy macrophages, and perivascular infiltration with inflammatory cells, all of which are compatible with MS lesions. Human immunodeficiency virus causes dysfunction of the immune system, especially characterized by hypergammaglobulinemia and chronic activation of B cells. Activation of B cells leads to increased synthesis of immunoglobulin and finally to an excess of free light chains. Free light chains may be involved in autoimmune responses against neurons. There is a high expression of HIV during the course of MS, which indicates the relationship between HIV and MS, that this virus can play a role in the development of MS by creating an inflammatory state. Therefore, measures to modulate the expression of HIV may be effective in reducing inflammatory processes in demyelinated areas of MS patients.

Keywords: multiple sclerosis, human immunodeficiency virus, central nervous system, autoimmunity

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Authors: Marziye Hadian, Alireza Jabbari

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Background: Each year, tropical diseases affect large numbers of tropical or subtropical populations and give rise to irreparable financial and human damage. Among these diseases, some are known as Neglected Tropical Disease (NTD) that may cause unusual dangers; however, they have not been appropriately accounted for. Taking into account the priority of eradication of the disease, this study explored the causes of failure to eradicate neglected tropical diseases. Method: This study was a systematized review that was conducted in January 2021 on the articles related to neglected tropical diseases on databases of Web of Science, PubMed, Scopus, Science Direct, Ovid, Pro-Quest, and Google Scholar. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines as well as Critical Appraisal Skills Program (CASP) for articles and AACODS (Authority, Accuracy, Coverage, Objectivity, Date, Significance) for grey literature (provides five criteria for judging the quality of grey information) were integrated. Finding: The challenges in controlling and eradicating neglected tropical diseases in four general themes are as follows: shortcomings in disease management policies and programs, environmental challenges, executive challenges in policy disease and research field and 36 sub-themes. Conclusion: To achieve the goals of eradicating forgotten tropical diseases, it seems indispensable to free up financial, human and research resources, proper management of health infrastructure, attention to migrants and refugees, clear targeting, prioritization appropriate to local conditions and special attention to political and social developments. Reducing the number of diseases should free up resources for the management of neglected tropical diseases prone to epidemics as dengue, chikungunya and leishmaniasis. For the purpose of global support, targeting should be accurate.

Keywords: neglected tropical disease, NTD, preventive, eradication

Procedia PDF Downloads 135

Authors: Naveen Kumar B. T., Anuj Tyagi, Prabjeet Singh, Shanthanagouda A. H., Sumeet Rai

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Inland saline water resources are gaining the importance in expanding the aquaculture activities to mitigate the nutritional and food security issues of the world. For profitable and sustainable aquaculture practices, scientific farming, biosecurity measure, and best fish health management should be the integral part of developmental activities. Keeping in line with global awareness and trends, the Indian government has taken an innovative step to conduct disease surveillance and awareness programme for aquatic disease through network project. This ‘National Surveillance Programme for Aquatic Animal Diseases (NSPAAD)’ is being implemented in collaboration of national institutes and state agriculture universities with funding support from National Fisheries Development Board (NFDB), Govt. of India. Guru Angad Dev Veterinary and Animal Sciences University (GADVASU), Ludhiana, an NSPAAD collaborator, has been actively engaged in disease surveillance in the Indian state of Punjab. Shrimp farming in inland saline areas of Punjab is expanding at a tremendous pace under the guidance of GADVASU along with the support of State Fisheries Department. Under this national disease surveillance programme, we reported Enterocytozoon hepatopenaei (EHP) infection in the Litopenaeus vannamei cultured in the inland saline waters. Polymerase chain reaction (PCR) based diagnosis was carried out using the OIE (World Organisation for Animal Health) protocol. It was observed that out of 20 shrimp farms, two farms were 1st step PCR positive and two more farms were nested PCR positive. All the EHP positive ponds had shown the white faeces along with mortalities at very low rate. Therefore, implementation of biosecurity and continuous surveillance and monitoring program for finfish and shellfish aquaculture are in need of the hour to prevent and control the large-scale disease outbreaks and subsequent economic losses.

Keywords: disease, EHP, inland saline water, shrimp culture

Procedia PDF Downloads 264

Authors: Reham Algheshairy, Khaled Tayeb, Christopher Smith, Rebecca Gregg, Haruna Musa

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Background: Diabetes is a medical condition that refers to the pancreas’ inability to secrete sufficient insulin levels, a hormone responsible for controlling glucose levels in the body. Any surplus glucose in the blood stream is excreted through the urinary system. Insulin resistance in blood cells can also cause this condition despite the fact that the pancreas is producing the required amount of insulin A number of researchers claim that the prevalence of diabetes in Saudi Arabia has reached epidemic proportions, although one study did observe one positive in the rise in the awareness of diabetes, possibly indicative of Saudi Arabia’s improving healthcare system. While a number of factors can cause diabetes, the ever-increasing incidence of the disease in Saudi Arabia has been blamed primarily on low levels of physical activity and high levels of obesity. Objectives: The project has two aims. The first aim of the project is to investigate the regulatory effects of consumption of Nigella seeds and Ajwah dates on blood glucose levels in diabetic patients with type 2 diabetes. The second aim of the project is to investigate whether these dietary factors may have potentially beneficial effects in controlling the complications that associated with type 2 diabetes. Methods: This use a random-cross intervention trail of 75 Saudi male and female with type 2 diabetes in Al-Noor hospital in Makkah ( KSA) aged between 18 and 70 years were divided into 3 groups. Group 1 will consume 2g of Nigella Sativa seeds daily along with a modified diet for 12 weeks, group 2 will be given Ajwah dates daily with a modified diet for 12 weeks and group 3 will follow a modified diet for 12 weeks. Anthropometric measurements were taken at baseline, along with bloods for HbA1c, fasting blood sugar and at the end of 12 weeks. Results: This study found significant decrease in blood level (FBG & 2PPBG) and HbA1c in the groups with diet and Nigella seeds) compared to Ajwa date. However, there is no significant change were found in HbA1c, FBG and 2hrpp regarding Ajwa group. Conclusion: This study illustrated a significant improvement in some markers of glycaemia following 2 g of Ns and diet for 12 weeks. The dose of 2g/day of consumed Nigella seeds was found to be more effective in controlling BGL and HbA1c than control and Ajwa groups. This suggests that Nigella seeds and following a diet may have a potential effect (a role in controlling outcomes for type 2 diabetes and controlling the disease). Further research is needed on a large scale to determine the optimum dose and duration of Nigella and Ajwa in order to achieve the desired results.

Keywords: type 2 diabetes, Nigella seeds, Ajwa dates, fasting blood glucose, control

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