Search results for: rare disease

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: Mahmoud Eldeeb, Yousri Mohamed

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Background: May-Thurner Syndrome (MTS) is a rare vascular condition caused by the compression of the left common iliac vein by the overlying right common iliac artery, leading to venous stasis and an increased risk of deep vein thrombosis (DVT). While MTS typically presents in young adults, its diagnosis is often delayed due to its nonspecific presentation, which can lead to catastrophic complications like massive pulmonary embolism (PE). Early recognition and intervention are paramount to prevent fatal outcomes. Objectives: Highlight the importance of early recognition and management of critically ill patients presenting with life- and limb-threatening conditions. Raise awareness of May-Thurner Syndrome as a rare but significant cause of extensive DVT in young adults. Emphasize the necessity of a multidisciplinary approach to managing complex vascular emergencies. Methodology: A 21-year-old female presented with a 7-day history of progressive left leg swelling, pain, and skin discoloration following immobilization due to gastroenteritis. Clinical suspicion for massive DVT and compartment syndrome prompted immediate initiation of a heparin bolus and referrals to vascular and orthopedic surgery teams. Bedside Doppler ultrasound confirmed extensive DVT, and subsequent CT venography revealed thrombi extending to the inferior vena cava, consistent with MTS. Despite anticoagulation therapy, angioplasty and stenting were required to restore venous patency. Tragically, the patient experienced a massive PE during the procedure, requiring cardiopulmonary resuscitation (CPR) and transfer to a tertiary center for cardiothoracic intervention. Results: The case highlights the aggressive and life-threatening progression of MTS. The patient’s presentation was characterized by massive DVT with severe pain and discoloration, rapidly culminating in a PE during intervention. The combination of bedside imaging and CT venography facilitated an accurate diagnosis. Despite timely management, the patient’s course underscores the high mortality risk associated with MTS-related thromboembolism. Conclusion: May-Thurner Syndrome, though rare, can lead to devastating complications in young adults if not promptly recognized and treated. This case emphasizes the need for a high index of suspicion in patients presenting with unexplained extensive DVT, especially in the context of limited mobility or other precipitating factors. Multidisciplinary collaboration, including vascular imaging, anticoagulation, and interventional procedures, is critical to optimize outcomes. Urgent recognition and treatment of MTS are vital to prevent progression to massive PE and death.

Keywords: may-thurner syndrome, deep venous thrombosis, pulmonary embolism, vascular emergency, iliac vein compression syndrome

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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: Adel H.El-Afandy, Abd Alrahman Embaby, Mona A. El Harairey

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Abu Marw area is located in the southeastern part of the Eastern Desert, about 150km south east of Aswan. Abu Marw area is mainly covered by late Proterozoic igneous and metamorphic rocks. These basement rocks are nonconformably overlain by late Cretaceous Nubian sandstones in the western and northern parts of the areas. Abu Marw granitoid batholiths comprises a co-magmatic calc alkaline I type peraluminous suite of rocks ranging in composition from tonalite, granodiorite, monzogranite, syenogranite to alkali feldspar granite. The studied tonalite and granodiorite samples have ΣREE lower than the average REE values (250ppm) of granitic rocks, while the monzogranite, syenogranite and alkali feldspar granite samples have ΣREE above the average REE values of granitic rocks. Chondrite-normalized REE patterns of the considered granites display a gull-wing shape, characterized by large to moderately fractionated patterns and high LREE relative to the MREE and HREE contents. Furthermore, the studied rocks have a steadily decreasing Eu/Eu* values from the tonalite to the alkali feldspar granite with simultaneous increase in the ΣREE contents. The average U contents in different granitic rocks.

Keywords: granite, rare earth element, radioactivity, Abu Marw, south eastern desert

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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: F. Ece Cetin, H. Nezih Ozdemir, Emre Kumral

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Ischemic stroke of the precuneal cortex (PC) alone is extremely rare. This study aims to evaluate the clinical, neurocognitive, and behavioural characteristics of isolated PC infarcts. We assessed neuropsychological and behavioral findings in 12 patients with isolated PC infarct among 3800 patients with ischemic stroke. To determine the most frequently affected brain locus in patients, we first overlapped the ischemic area of patients with specific cognitive disorders and patients without specific cognitive disorders. Secondly, we compared both overlap maps using the 'subtraction plot' function of MRIcroGL. Patients showed various types of cognitive disorders. All patients experienced more than one category of cognitive disorder, except for two patients with only one cognitive disorder. Lesion topographical analysis showed that damage within the anterior precuneal region might lead to consciousness disorders (25%), self-processing impairment (42%), visuospatial disorders (58%), and lesions in the posterior precuneal region caused episodic and semantic memory impairment (33%). The whole precuneus is involved in at least one body awareness disorder. The cause of the stroke was cardioembolism in 5 patients (42%), large artery disease in 3 (25%), and unknown in 4 (33%). This study showed a wide variety of neuropsychological and behavioural disorders in patients with precuneal infarct. Future studies are needed to achieve a proper definition of the function of the precuneus in relation to the extended cortical areas. Precuneal cortex region infarcts have been found to predict a source of embolism from the large arteries or heart.

Keywords: cognition, pericallosal artery, precuneal cortex, ischemic stroke

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Authors: Kiran Abdullah, Yanli Chen

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An amphiphilic mixed (phthalocyaninato) (porphyrinato) europium triple-decker complex Eu₂(Pc)₂(TPyP) has been synthesized and characterized. Introducing electron-withdrawing pyridyl substituents onto the meso-position of porphyrin ring in the triple-decker to ensure the sufficient hydrophilicity and suitable HOMO and LUMO energy levels and thus successfully realize amphiphilic ambipolar organic semiconductor. Importantly, high sensitive, reproducible p-type and n-type responses towards NH₃ andNO₂ respectively, based on the self-assembled film of the Eu₂(Pc)₂(TPyP) fabricated by a simple solution-based Quasi–Langmuir–Shäfer (QLS) method, have been first revealed. The good conductivity and crystallinity for the QLS film of Eu₂(Pc)₂(TPyP) render it excellent sensing property. This complex is sensitive to both electron-donating NH₃ gas in 5–30 ppm range and electron-accepting NO₂ gas 400–900 ppb range. Due to uniform nano particles there exist effective intermolecular interaction between triple decker molecules. This is the best result of Phthalocyanine–based chemical sensors at room temperature. Furthermore, the responses of the QLS film are all linearly correlated to both NH₃ and NO₂ with excellent sensitivity of 0.04% ppm⁻¹ and 31.9 % ppm⁻¹, respectively, indicating the great potential of semiconducting tetrapyrrole rare earth triple-decker compounds in the field of chemical sensors.

Keywords: ambipolar semiconductor, gas sensing, mixed (phthalocyaninato) (porphyrinato) rare earth complex, Self-assemblies

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Authors: Karthika Chandran, Pulkit Prakash, Amitabh Das, Santhosh P. N.

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Rare earth orthoferrites (RFeO₃) exhibit interesting and useful magnetic properties like multiferroicity, magnetodielectric coupling, spin reorientation (SR) and exchange bias. B site doped RFeO₃ are attracting attention due to the complex and tuneable magnetic transitions. In this work, 45% Mn-doped HoFeO₃ polycrystalline sample (HoFe₀.₅₅Mn₀.₄₅O₃) was synthesized by a solid-state reaction method. The magnetic structure and transitions were studied by magnetization measurements and neutron powder diffraction methods. The neutron diffraction patterns were taken at 13 different temperatures from 7°K to 300°K (7°K and 25°K to 300°K in 25°K intervals). The Rietveld refinement was carried out by using a FULLPROF suite. The magnetic space groups and the irreducible representations were obtained by SARAh module. The room temperature neutron diffraction refinement results indicate that the sample crystallizes in an orthorhombic perovskite structure with Pnma space group with lattice parameters a = 5.6626(3) Ǻ, b = 7.5241(3) Ǻ and c = 5.2704(2) Ǻ. The temperature dependent magnetization (M-T) studies indicate the presence of two magnetic transitions in the system ( TN Fe/Mn~330°K and TSR Fe/Mn ~290°K). The inverse susceptibility vs. temperature curve shows a linear behavior above 330°K. The Curie-Weiss fit in this region gives negative Curie constant (-34.9°K) indicating the antiferromagnetic nature of the transition. The neutron diffraction refinement results indicate the presence of mixed magnetic phases Γ₄(AₓFᵧG

Keywords: neutron powder diffraction, rare earth orthoferrites, Rietveld analysis, spin reorientation

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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: Gomes C. C. Izabel, Lanzotti B. Rafaela, Orlandi S. Fabiana

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Chronic Kidney Disease is considered a serious public health problem. The exploitation of resilience has been guided by studies conducted in various contexts, especially in hemodialysis, since the impact of diagnosis and restrictions produced during the treatment process because, despite advances in treatment, remains the stigma of the disease and the feeling of pain, hopelessness, low self-esteem and disability. The objective was to evaluate the level of resilience of patients in chronic renal dialysis. This is a descriptive, correlational, cross and quantitative research. The sample consisted of 100 patients from a Renal Replacement Therapy Unit in the countryside of São Paulo. For data collection were used the characterization instrument of Participants and the Resilience Scale. There was a predominance of males (70.0%) were Caucasian (45.0%) and had completed elementary education (34.0%). The average score obtained through the Resilience Scale was 131.3 (± 20.06) points. The resiliency level submitted may be considered satisfactory. It is expected that this study will assist in the preparation of programs and actions in order to avoid possible situations of crises faced by chronic renal patients.

Keywords: hemodialysis units, renal dialysis, renal insufficiency chronic, resilience psychological

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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: 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

Abstract:

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: 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

Abstract:

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

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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

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Authors: Rachel Shukrun, Szilvia Baron, Victoria Fidel, Anna Shusterman, Osnat Sher, Netanya Kollender, Dror Levin, Yair Peled, Yair Gortzak, Yoav Ben-Shahar, Revital Caspi, Sagi Gordon, Michal Manisterski, Ronit Elhasid

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Ewing sarcoma (EWS) is a highly aggressive cancer with a survival rate of 70–80% for patients with localized disease and under 30% for those with metastatic disease. Tumor-infiltrating neutrophils (TIN) can generate extracellular net-like DNA structures known as neutrophil extracellular traps (NETs). However, little is known about the presence and prognostic significance of tumor-infiltrating NETs in EWS. Herein, we investigated 46 patients diagnosed with EWS and treated in the Tel Aviv Medical Center between 2010 and 2021. TINs and NETs were identified in diagnostic biopsies of EWS by immunofluorescent. In addition, NETs were investigated in neutrophils isolated from peripheral blood samples of EWS patients at diagnosis and following neoadjuvant chemotherapy. The relationships between the presence of TINs and NETs, pathological and clinical features, and outcomes were analyzed. Our results demonstrate that TIN and NETs at diagnosis were higher in EWS patients with metastatic disease compared to those with local disease. High NETs formation at diagnosis predicted poor response to neo-adjuvant chemotherapy, relapse, and death from disease (P < .05). NETs formation in peripheral blood samples at diagnosis was significantly elevated among patients with EWS compared to pediatric controls and decreased significantly following neoadjuvant chemotherapy. In conclusion, NETs formation seems to have a role in the EWS immune microenvironment. Their presence can refine risk stratification, predict chemotherapy resistance and survival, and serve as a therapeutic target in patients with EWS.

Keywords: Ewing sarcoma, tumor microenvironment, neutrophil, neutrophil extracellular traps (NETs), prognosis

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Authors: Anukriti Verma, Bhawna Rathi, Shivani Sharda

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Reactive Arthritis (ReA) is a disorder that causes inflammation in joints due to certain infections at distant sites in the body. ReA begins with stiffness, pain, and inflammation in these areas especially the ankles, knees, and hips. It gradually causes several complications such as conjunctivitis in the eyes, skin lesions in hand, feet and nails and ulcers in the mouth. Nowadays the diagnosis of ReA is based upon a differential diagnosis pattern. The parameters for differentiating ReA from other similar disorders include physical examination, history of the patient and a high index of suspicion. There are no standard lab tests or markers available for ReA hence the early diagnosis of ReA becomes difficult and the chronicity of disease increases with time. It is reported that enteric disorders such as Inflammatory Bowel Disease (IBD) that is inflammation in gastrointestinal tract namely Crohn’s Disease (CD) and Ulcerative Colitis (UC) are reported to be linked with ReA. Several microorganisms are found such as Campylobacter, Salmonella, Shigella and Yersinia causing IBD leading to ReA. The aim of our study was to perform the in-silico analysis in order to find interactions between microorganisms and human host causing IBD leading to ReA. A systems biology approach for metabolic network reconstruction and simulation was used to find the essential genes of the reported microorganisms. Interactomics study was used to find the interactions between the pathogen genes and human host. Genes such as nhaA (pathogen), dpyD (human), nagK (human) and kynU (human) were obtained that were analysed further using the functional, pathway and network analysis. These genes can be used as putative drug targets and biomarkers in future for early diagnosis, prevention, and treatment of IBD leading to ReA.

Keywords: drug targets, inflammatory bowel disease, reactive arthritis, systems biology

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Authors: Uma Maheshwari V., Rajanikanth Aluvalu, Kumar Gautam

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The COVID-19 disease is a highly contagious viral infection with major worldwide health implications. The global economy suffers as a result of COVID. The spread of this pandemic disease can be slowed if positive patients are found early. COVID-19 disease prediction is beneficial for identifying patients' health problems that are at risk for COVID. Deep learning and machine learning algorithms for COVID prediction using X-rays have the potential to be extremely useful in solving the scarcity of doctors and clinicians in remote places. In this paper, a convolutional neural network (CNN) with deep layers is presented for recognizing COVID-19 patients using real-world datasets. We gathered around 6000 X-ray scan images from various sources and split them into two categories: normal and COVID-impacted. Our model examines chest X-ray images to recognize such patients. Because X-rays are commonly available and affordable, our findings show that X-ray analysis is effective in COVID diagnosis. The predictions performed well, with an average accuracy of 99% on training photographs and 88% on X-ray test images.

Keywords: deep CNN, COVID–19 analysis, feature extraction, feature map, accuracy

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Authors: Laura Gantley, Vanessa M. Conn, Stuart Webb, Kirsty Kirk, Marta Gabryelska, Duncan Holds, Brett W. Stringer, Simon J. Conn

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Trinucleotide repeat disorders comprise ~20 severe, inherited human neuromuscular and neurodegenerative disorders, which are a result of an abnormal expansion of repetitive sequences in the DNA. The most common of these, Huntington’s disease, results from the expansion of the CAG repeat region in exon 1 of the HTT gene via an unknown mechanism. Non-coding RNAs have been implicated in the initiation and progression of many diseases; thus, we focus on one circular RNA (circRNA) molecule arising from non-canonical splicing (back splicing) of HTT pre-mRNA. This circRNA and its mouse orthologue were transgenically overexpressed in human cells (SHSY-5Y and HEK293T) and mouse cells (Mb1), respectively. High-content imaging and flow cytometry demonstrated the overexpression of this circRNA reduces cell proliferation, reduces nuclear size independent of cellular size, and alters cell cycle progression. Analysis of protein by western blot and immunofluorescence demonstrated no change to HTT protein levels but altered nuclear-cytoplasmic distribution without impacting the expansion of the HTT repeat region. As these phenotypic and genotypic changes are found in Huntington’s disease patients, these results may suggest that this circRNA may play a functional role in the progression of Huntington’s disease.

Keywords: cell biology, circular RNAs, Huntington’s disease, molecular biology, neurodegenerative disorders

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Authors: Huamin Xu, Wenting Jia, Hong Jiang, Junxia Xie

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Rosmarinic acid (RA) is a natural acid that is found in a variety of herbs, such as rosemary and has multiple biological activities such as antioxidative, anti-inflammatory and antiviral activities. In this study, we investigated the neuroprotective effects of RA on dopaminergic system in 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP) induced mouse model of Parkinson’s disease (PD). The mice received oral administration of RA before MPTP injection. Results showed that the tyrosine hydroxylase expression in SN reduced and the levels of dopamine and its metabolites in the striatum decreased in MPTP intoxicated PD mice. Pretreatment with RA significantly inhibited these changes. Further studies demonstrated that MPTP treatment increased the iron content, which was counteracted by pre-treatment with RA. In addition, RA could restore the decrease of superoxide dismutase (SOD) induced by MPTP. This study provides evidence that RA could suppress MPTP-induced degeneration of the nigrostriatal dopaminergic system by regulating iron content and the expression of SOD. Thus, RA might be clinically evaluated for the prevention of neurodegenerative diseases.

Keywords: rosmarinic acid, Parkinson's disease, MPTP, dopaminergic system

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Authors: Preeti Virkar, V. P. Uniyal, Vinod Kumar Bhatt

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With 50% decline in managed honey bee hives in the continents of Europe and America, farmers and landscape managers are turning to native wild bees for their essential ecosystem services of pollination. Wild bees population are too under danger due to the rapid land use changes from anthropogenic activities. With an escalating population reaching 9.0 billion by 2050, human-induced land use changes are predicted to further deteriorate the habitats of numerous species by the turn of this century. The status of bees are uncertain, especially in the tropical regions of the world, which also questions the crisis of global pollinator decline and their essential services to wild and managed flora. Our investigation collectively compares wild native bee diversity and their status in forests and agroecosystems in Doon Valley landscape, situated at the foothills of Himalayan ranges, Uttarakhand, India. We seek to ask whether (1) natural habitat are refuge to richer and rarer bees communities than the agroecosystems, (2) Are agroecosystems closer to natural habitats similar to them than agroecosystems farther away; hence support richer bee communities and hence, (3) Do polyculture farms support richer bee communities than monoculture. The data was collected using observation and pantrap sampling form February to May, 2012 to 2014. We recorded 43 species of bees in Doon Valley. They belonged to 5 families; Megachilidae, Apidae, Andrenidae, Halictidae and Collitidae. A multinomial model approach was used to classify the bees into 2 habitats, in which forests demonstrated to support greater number of specialist (26%, n= 11) species than agroecosystems (7%, n= 3). The valley had many species categorized as the rare (58%, n= 25) and very few generalists (9%, n=4). A linear regression model run on our data demonstrated higher bee diversity in agro-ecosystems in close proximity to forests (H’ for < 200 m = 1.60) compared to those further away (H’ for > 600 m = 0.56) (R2=0.782, SE=0.148, p value=0.004). Organic agriculture supported significantly greater species richness in comparison to conventional farms (Mann-Whitney U test, n1 = 33, n2 = 35; P = 0.001). Forests ecosystems are refuge to rare specialist groups and support bee communities in nearby agroecosystems. The findings of our investigation demonstrate the importance of natural habitats as a potential refuge for rare native wild bee pollinators. Polyculture in the valley behaves similar to natural habitats and supports diverse bee communities in comparison to conventional monocultures. Our study suggests that the farming communities adopt diverse organic agriculture systems to attract wild pollinators beneficial for better crop production. Forests are sanctuaries for bees to nest, forage, and breed. Therefore, our outcome also suggests landscape managers not only preserve protected areas but also enhance the floral diversity in semi-natural and urban areas.

Keywords: native bees, pollinators, polyculture, agroecosystem, natural habitat, diversity, monoculture, specialists, generalists

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