Search results for: disease cluster

Authors: A. K. Putri, A.Fitri, C. A. Batubara

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Diabetes Mellitus (DM) is a chronic disease that could cause complications. The complication can be Peripheral Arterial Disease (PAD) or Diabetic Neuropathy (DN). Peripheral Arterial Disease is checked by Ankle Brachial Index (ABI), DN is checked by Diabetic Neuropathy Examination (DNE) score. To determine the association of ABI and DNE score in DM type 2. This study uses a cross-sectional design. The subjects were DM patients at the neurology and endocrinology polyclinic at Haji Adam Malik Hospital Medan and its network hospital and this study subjects were examined for ABI and DNE scores. The data were analysed using the Fisher Exact statistics test. Demographics characteristic showed most of subject are female (51,6%), age range ≥ 60 (45.2% ; average 57,6 ± 9,8 years ), and history of DM 5-10 years (45,2%). The most patient ABI characteristics were mild PAD (42%) and moderate PAD (29%). The most patient DNE Score characteristics were≥ 3 (51,6%). There’s a significant relationship between ABI and DNE score in DM type 2 (p =0.016). Conclusion: There is a significant association between ABI and DNE scores in DM type 2 patients

Keywords: diabetic neuropathy, diabetes mellitus, ankle-brachial index, diabetic neuropathy examination

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Authors: Abobaker Mohammed Qasem Farhan, Shangming Yang, Mohammed Al-Nehari

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Pneumonia is a kind of lung disease that creates congestion in the chest. Such pneumonic conditions lead to loss of life of the severity of high congestion. Pneumonic lung disease is caused by viral pneumonia, bacterial pneumonia, or Covidi-19 induced pneumonia. The early prediction and classification of such lung diseases help to reduce the mortality rate. We propose the automatic Computer-Aided Diagnosis (CAD) system in this paper using the deep learning approach. The proposed CAD system takes input from raw computerized tomography (CT) scans of the patient's chest and automatically predicts disease classification. We designed the Hybrid Deep Learning Algorithm (HDLA) to improve accuracy and reduce processing requirements. The raw CT scans have pre-processed first to enhance their quality for further analysis. We then applied a hybrid model that consists of automatic feature extraction and classification. We propose the robust 2D Convolutional Neural Network (CNN) model to extract the automatic features from the pre-processed CT image. This CNN model assures feature learning with extremely effective 1D feature extraction for each input CT image. The outcome of the 2D CNN model is then normalized using the Min-Max technique. The second step of the proposed hybrid model is related to training and classification using different classifiers. The simulation outcomes using the publically available dataset prove the robustness and efficiency of the proposed model compared to state-of-art algorithms.

Keywords: CT scan, Covid-19, deep learning, image processing, lung disease classification

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Authors: Forrest Kaatz, Adhemar Bultheel

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We use an informational statistical mechanics approach to study the catalytic thermodynamics of platinum and palladium cuboctahedral nanoclusters. Nanoclusters and their adatoms are viewed as chemical graphs with a nearest neighbor adjacency matrix. We use the Morse potential to determine bond energies between cluster atoms in a coordination type calculation. We use adsorbate energies calculated from density functional theory (DFT) to study the adatom effects on the thermodynamic quantities, which are derived from a Hamiltonian. Oxygen radical and molecular adsorbates are studied on platinum clusters and hydrogen on palladium clusters. We calculate the entropy, free energy, and total energy as the coverage of adsorbates increases from bridge and hollow sites on the surface. Thermodynamic behavior versus adatom coverage is related to the structural distribution of adatoms on the nanocluster surfaces. The thermodynamic functions are characterized using a simple adsorption model, with linear trends as the coverage of adatoms increases. The data exhibits size effects for the measured thermodynamic properties with cluster diameters between 2 and 5 nm. Entropy and enthalpy calculations of Pt-O2 compare well with previous theoretical data for Pt(111)-O2, and our Pd-H results show similar trends as experimental measurements for Pd-H2 nanoclusters. Our methods are general and may be applied to wide variety of nanocluster adsorbate systems.

Keywords: catalytic thermodynamics, palladium nanocluster absorbates, platinum nanocluster absorbates, statistical mechanics

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Authors: M. Klimova, O. Semyachkina-Glushkovskaya, J. Kurts, E. Zinchenko, N. Navolokin, A. Shirokov, A. Dubrovsky, A. Abdurashitov, A. Terskov, A. Mamedova, I. Agranovich, T. Antonova, I. Blokhina

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The direction for research of Alzheimer's disease is to find an effective non-invasive and non-pharmacological way of treatment. Here we tested our hypothesis that the opening of the blood-brain barrier (BBB) induces activation of lymphatic drainage and clearing functions that can be used as a method for non-invasive stimulation of clearance of beta-amyloid and therapy of Alzheimer’s disease (AD). To test our hypothesis, in this study on healthy male mice we analyzed the interaction between BBB opening by repeated loud music (100-10000 Hz, 100 dB, duration 2 h: 60 sec – sound; 60 sec - pause) and functional changes in the meningeal lymphatic vessels (MLVs). We demonstrate clearance of dextran 70 kDa (i.v. injection), fluorescent beta-amyloid (intrahippocampal injection) and gold nanorods (intracortical injection) via MLV that significantly increased after the opening of BBB. Our studies also demonstrate that the BBB opening was associated with the improvement of neurocognitive status in mice with AD. Thus, we uncover therapeutic effects of BBB opening by loud music, such as non-invasive stimulation of lymphatic clearance of beta-amyloid in mice with AD, accompanied by improvement of their neurocognitive status. Our data are consistent with other results suggesting the therapeutic effect of BBB opening by focused ultrasound without drugs for patients with AD. This research was supported by a grant from RSF 18-75-10033

Keywords: Alzheimer's disease, beta-amyloid, blood-brain barrier, meningeal lymphatic vessels, repeated loud music

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Authors: Hushyar Azari

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Aim and background: Deep brain stimulation (DBS) is regarded as an important therapeutic choice for Parkinson's disease (PD). The two most common targets for DBS are the subthalamic nucleus (STN) and globus pallidus (GPi). This review was conducted to compare the clinical effectiveness of these two targets. Methods: A systematic literature search in electronic databases: Embase, Cochrane Library and PubMed were restricted to English language publications 2010 to 2021. Specified MeSH terms were searched in all databases. Studies which evaluated the Unified Parkinson's Disease Rating Scale (UPDRS) III were selected by meeting the following criteria: (1) compared both GPi and STN DBS; (2) had at least three months follow-up period; (3)at least five participants in each group; (4)conducted after 2010. Study quality assessment was performed using the Modified Jadad Scale. Results: 3577 potentially relevant articles were identified, of these, 3569 were excluded based on title and abstract, duplicate and unsuitable article removal. Eight articles satisfied the inclusion criteria and were scrutinized (458 PD patients). According to Modified Jadad Scale, the majority of included studies had low evidence quality which was a limitation of this review. 5 studies reported no statistically significant between-group difference for improvements in UPDRS ш scores. At the same time, there were some results in terms of pain, action tremor, rigidity, and urinary symptoms, which indicated that STN DBS might be a better choice. Regarding the adverse effects, GPi was superior. Conclusion: It is clear that other larger randomized clinical trials with longer follow-up periods and control groups are needed to decide which target is more efficient for deep brain stimulation in Parkinson’s disease and imposes fewer adverse effects on the patients. Meanwhile, STN seems more reasonable according to the results of this systematic review.

Keywords: brain stimulation, globus pallidus, Parkinson's disease, subthalamic nucleus

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Authors: Mohammad Al-Mousawi

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This academic article explores the indispensable role of critical thinking in the process of diagnosing diseases. Employing a multidisciplinary approach, we delve into the cognitive skills and analytical mindset that clinicians, researchers, and healthcare professionals must employ to navigate the complexities of disease identification. By examining the integration of critical thinking within the realms of medical education, diagnostic decision-making, and technological advancements, this article aims to underscore the significance of cultivating and applying critical thinking skills in the ever-evolving landscape of healthcare.

Keywords: critical thinking, medical education, diagnostic decision-making, fostering critical thinking

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Authors: Debit Datta, Jeffrey J. Coleman, Scott A. Enebak, Lori G. Eckhardt

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Loblolly pine (Pinus taeda) is a leading productive timber species in the southeastern USA. Over the past three years, an emerging threat is expressed by successive needle defoliation followed by stunted growth and tree mortality in loblolly pine plantations. Considering economic significance, it has now become a rising concern among landowners, forest managers, and forest health state cooperators. However, the symptoms of the disease were perplexed somewhat with root disease(s) and recurrently attributed to invasive Phytophthora species due to the similarity of disease nature and devastation. Therefore, the study investigated the potential causal agent of this disease and characterized the fungi associated with loblolly pine needle defoliation in the southeastern USA. Besides, 70 trees were selected at seven long-term monitoring plots at Chatom, Alabama, to monitor and record the annual disease incidence and severity. Based on colony morphology and ITS-rDNA sequence data, a total of 28 species of fungi representing 17 families have been recovered from diseased loblolly pine needles. The native brown-spot pathogen, Lecanosticta acicola, was the species most frequently recovered from unhealthy loblolly pine needles in combination with some other common needle cast and rust pathogen(s). Identification was confirmed using morphological similarity and amplification of translation elongation factor 1-alpha gene region of interest. Tagged trees were consistently found chlorotic and defoliated from 2019 to 2020. The current emergence of the brown-spot pathogen causing loblolly pine mortality necessitates the investigation of the role of changing climatic conditions, which might be associated with increased pathogen pressure to loblolly pines in the southeastern USA.

Keywords: brown-spot needle blight, loblolly pine, needle defoliation, plantation forestry

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Authors: Jakub Młoźniak, Adam Szymański, Gabriela Stondzik, Dagny Krankowska, Tomasz Mikuła

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Nontuberculous mycobacteria (NTM) are bacterial species that cause diversely manifesting diseases mainly in immunocompromised patients. In people with HIV, NTM infection is an AIDS-defining disease and usually appears when the lymphocyte T CD4 count is below 50 cells/μl. The usage of antiretroviral therapy has decreased the prevalence of NTM among people with HIV, but the disease can still be observed especially among patients with late HIV diagnosis. Common presence in environment, human colonization, clinical similarity with tuberculosis and slow growth on culture makes NTM especially hard to diagnose. The study aimed to analyze the epidemiology and clinical course of NTM among patients with HIV. This study included patients with NTM and HIV admitted to our department between 2017 and 2023. Medical records of patients were analyzed and data on age, sex, median time from HIV diagnosis to identification of NTM infection, median CD4 count at NTM diagnosis, methods of determining NTM infection, type of species of mycobacteria identified, clinical symptoms and treatment course were gathered. Twenty-four patients (20 men, 4 women) with identified NTM were included in this study. Among them, 20 were HIV late presenters. The patients' median age was 40. The main symptoms which patients presented were fever, weight loss and cough. Pulmonary disease confirmed with positive cultures from sputum/bronchoalveolar lavage was present in 18 patients. M. avium was the most common species identified. M. marinum caused disseminated skin lesions in 1 patient. Out of all, 5 people were not treated for NTM caused by lack of symptoms and suspicion of colonization with mycobacterium. Concomitant tuberculosis was present in 6 patients. The median diagnostic time from HIV to NTM infections was 3.5 months. The median CD4 count at NTM identification was 69.5 cells/μl. Median NTM treatment time was 16 months but 7 patients haven’t finished their treatment yet. The most commonly used medications were ethambutol and clarithromycin. Among analyzed patients, 4 of them have died. NTM infections are still an important disease among patients who are HIV late presenters. This disease should be taken into consideration during the differential diagnosis of fever, weight loss and cough in people with HIV with lymphocyte T CD4 count <100 cells/μl. Presence of tuberculosis does not exclude nontuberculous mycobacterium coinfection.

Keywords: mycobacteriosis, HIV, late presenter, epidemiology

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Authors: Vaishali Patil, Neeraj Masand

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In older people, Alzheimer’s disease (AD) is turning out to be a lethal disease. According to the amyloid hypothesis, aggregation of the amyloid β–protein (Aβ), particularly its 42-residue variant (Aβ42), plays direct role in the pathogenesis of AD. Aβ is generated through sequential cleavage of amyloid precursor protein (APP) by β–secretase (BACE) and γ–secretase (GS). Thus in the treatment of AD, γ-secretase modulators (GSMs) are potential disease-modifying as they selectively lower pathogenic Aβ42 levels by shifting the enzyme cleavage sites without inhibiting γ–secretase activity. This possibly avoids known adverse effects observed with complete inhibition of the enzyme complex. Virtual screening, via drug-like ADMET filter, QSAR and molecular docking analyses, has been utilized to identify novel γ–secretase modulators with sulphonamide nucleus. Based on QSAR analyses and docking score, some novel analogs have been synthesized. The results obtained by in silico studies have been validated by performing in vivo analysis. In the first step, behavioral assessment has been carried out using Scopolamine induced amnesia methodology. Later the same series has been evaluated for neuroprotective potential against the oxidative stress induced by Scopolamine. Biochemical estimation was performed to evaluate the changes in biochemical markers of Alzheimer’s disease such as lipid peroxidation (LPO), Glutathione reductase (GSH), and Catalase. The Scopolamine induced amnesia model has shown increased Acetylcholinesterase (AChE) levels and the inhibitory effect of test compounds in the brain AChE levels have been evaluated. In all the studies Donapezil (Dose: 50µg/kg) has been used as reference drug. The reduced AChE activity is shown by compounds 3f, 3c, and 3e. In the later stage, the most potent compounds have been evaluated for Aβ42 inhibitory profile. It can be hypothesized that this series of alkyl-aryl sulphonamides exhibit anti-AD activity by inhibition of Acetylcholinesterase (AChE) enzyme as well as inhibition of plaque formation on prolong dosage along with neuroprotection from oxidative stress.

Keywords: gamma-secretase inhibitors, Alzzheimer's disease, sulphonamides, QSAR

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Authors: Faheema Khan

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In order to investigate the influence of genetic background on salt tolerance in Soybean (Glycine max) ten soybean genotypes released/notified in India were selected. (Pusa-20, Pusa-40, Pusa-37, Pusa-16, Pusa-24, Pusa-22, BRAGG, PK-416, PK-1042, and DS-9712). The 10-day-old seedlings were subjected to 0, 25, 50, 75, 100, 125, and 150 mM NaCl for 15 days. Plant growth, leaf osmotic adjustment, and RAPD analysis were studied. In comparison to control plants, the plant growth in all genotypes was decreased by salt stress, respectively. Salt stress decreased leaf osmotic potential in all genotypes however the maximum reduction was observed in genotype Pusa-24 followed by PK-416 and Pusa-20. The difference in osmotic adjustment between all the genotypes was correlated with the concentrations of ion examined such as Na+ and the leaf proline concentration. These results suggest that the genotypic variation for salt tolerance can be partially accounted for by plant physiological measures. The genetic polymorphisms between soybean genotypes differing in response to salt stress were characterized using 25 RAPD primers. These primers generated a total of 1640 amplification products, among which 1615 were found to be polymorphic. A very high degree of polymorphism (98.30%) was observed. UPGMA cluster analysis of genetic similarity indices grouped all the genotypes into two major clusters. Intra-clustering within the two clusters precisely grouped the 10 genotypes in sub-cluster as expected from their physiological findings. Our results show that RAPD technique is a sensitive, precise and efficient tool for genomic analysis in soybean genotypes.

Keywords: glycine max, NaCl, RAPD, proteomics

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Authors: Adamu Garba, Saidu Idi

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This study was conducted to determine the prevalence of Dermatophilosis in cattle in Bauchi State and suggest possible control measures. Data were obtained from the State Ministry of Agriculture and Natural Resources, Veterinary Division and monthly reports from Local Government Area Veterinary Offices for a period of three years ranging from 1996-1998. The result revealed that the disease is more prevalent in the rainy season which coincides with preponderance of the predisposing factors. Of the total 17,252 infected cattle in the State, Western zone had the highest cases with 8,298 (50.0%), followed by Central zone with 5,211 (30.0%) and the least was in the Northern zone with 3,753 (20.0%) cases. Rainfall pattern within the zones could be responsible for the variation in the prevalence rate. Analysis of variance revealed that there is no significant difference in the prevalence of Dermatophilosis between the years (P<0.212) while there is significant difference within the zones (P<0.012). Correlation analysis carried out showed that there is positive relationship between rainfall and Dermatophilosis (r<0.909). Since the disease is more prevalent during the rainy season, efforts should be exerted on thorough preventive measures during the period to control the disease in the State, particularly in the Western zone.

Keywords: incidence, dermatophilosis, cattle, Bauchi State

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Authors: Geeta Sharma, Suma Chandra

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Sugarcane is one of the major commercial crop playing roles in agriculture and industrial economy of India. Globally sugarcane is affected by approximately 240 diseases caused by various plant pathogenic organisms. Among them, red rot disease caused by the fungus Colletotrichum falcatum, is one of the most important diseases. In the present investigation, one fungal bioagent of Trichoderma harzianum, Pant Bioagent 1 and one bacterial bioagent Pseudomonas fluorescence, Pant Bioagent 2 (PBAT 1 and PBAT 2, respectively) were tested by dual culture method against the pathogen under laboratory conditions. The effectiveness of biocontrol agents was observed against four isolates of C. falcatum. In the case of PBAT1 maximum percent inhibition of pathogen was recorded in isolated Cf 0238 (61.05%), followed by Cf 09 (60.62%) whereas, minimum percent inhibition was recorded in Cf 3220 (48.55%) and in case of PBAT2 maximum mycelial growth inhibition percent was recorded in Cf 767 (50.50%) followed by Cf 088230(48.83%), whereas minimum percent inhibition was recorded in Cf 08 (40.16%) followed by Cf 0238 (41.83%). The present study showed that these biocontrol agents have the potential of controlling the pathogen and can further be used for the management of red rot disease in field.

Keywords: biocontrol agents, Colletotrichum falcatum, isolates, sugarcane

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Authors: A. Khan, I. Khan, M. Younus, S. E. Haque, U. Waheed, H. Neubauer, A. A. Anjum, S. A. Muhammad, A. Idrees T. Abbas, S. Raza, M. A. Ali, M. Farooq, M. Mahmood, A. Hussain, H. Danish, U. Tayyab, M. Zafar, M. Aslam.

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Brucellosis is one of the major problems of milk producing animals in our country which deteriorate the health of livestock. It is a disease of zoonotic significance which is capable of producing disease in humans leading to infertility, orchitis, abortions, and synovitis. In this particular study, milk and serum samples of cattle and buffalo (n=402) were collected from different districts of Punjab including Narowal, Gujranwala and Gujrat. Milk samples were analyzed by Milk Ring Test (MRT), while serum samples were tested through Rose Bengal Plate agglutination Test (RBPT) and Indirect Enzyme Linked Immunosorbant Assay (i-ELISA). The sample tested with MRT were 9.5% positive, including cattle 9.6% and buffalo 9.3%. While using the RBPT test for the detection of serum samples and for screening purpose it was observed that 16.4% animals were seropositive, cattle were 18.8% and buffalo were 13.9% seropositive. The higher prevalence of brucellosis indicates the danger of the disease to human population. The serum samples positive by RBPT were further confirmed by the use of most specific and sensitive serological test known as i-ELISA. 11.4% animals were confirmed as seropositive by i-ELISA including cattle 13.5% seropositive and buffalo 9.3%. The results indicated high seroprevalence of brucellosis in cattle as compared to buffalos. Different risk factors were also studied to know the association between disease and their spread. Advanced age, larger herds, history of abortion and pregnancy of the animals is considered to be the important factors for the prevalence and spread of the hazardous zoonotic disease. It is a core issue of developing countries like Pakistan and has major public health impact.

Keywords: humans, bovines, infertility, orchitis, abortions, seroprevalence, brucellosis

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Authors: Asma Naseer Cheema, Attya Bhatti, Jabar Ali, John Peter

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Background: High cholesterol levels, endothelial dysfunction, inefficient coagulation cascade and hyper inflammatory response all are the basis of coronary artery disease (CAD). Several studies are carried out to see the genetic influence of these factors on disease outcome. Objective: The objective of our study was to see the association of 10 putative loci with coronary artery disease in our population. Materials & Methods: We screened our population for 10 putative loci of CAD showing significant association (p < 5x10-8) with candidate genes (regulating the cholesterol metabolism, endothelial function, coagulation cascade and inflammatory response of body). Hardy-Weinberg equilibrium and linkage disequilibrium in cases and controls s were estimated separately. Approximately 5-10 ng of dried DNA in 384 well plate format was used to genotype each sample on the Sequenom iPLEX assay at University of Pittsburgh Genomics and Proteomics Core Laboratories. It was built on single-base primer extension with the MALDI-TOF MS detection possessing high sensitivity and specificity. The SNPs were genotyped through Taqman assay. Hardy Weinberg test was applied. The 10 SNPs were selected as genetic markers for this study (rs579459, rs1561198, rs2954029, rs1122608, rs17114036, rs9515203, rs10947789, rs7173743, rs2895811, rs2075650). Results: Mean age of the patient was 52 ± 11 years. Blood pressure and positive family history was found a significant risk factor for CAD. None of the selected SNPs showed significant association with coronary artery disease in our population (p>0.05). Conclusion: rs579459, rs1561198, rs2954029, rs1122608, rs17114036, rs9515203, rs10947789, rs7173743, rs2895811, rs2075650 are not significant genetic markers for CAD in our population.

Keywords: CAD, genetic markers, loci, risk factors

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Authors: Dina A. Amu, Fifi N. Afifah, Catur Rosidati, Tirton Nefianto

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Indonesia was shaken up by the avian influenza cases that had caused the country suffered losses of millions of dollars. The avian influenza case had even been suspected as a bioterrorism attack since it was an uncommon case in epidemiology. Furthermore, this avian influenza virus is a high pathogenic one and Indonesia has the highest case of fatality rate in the world. Bioterrorism threats or epidemic potential disease outbreaks currently does not exist in Tanjung Priok port yet. However, the surveillance system enhancement on epidemic potential diseases should be taken as a prevention, especially because Indonesia is currently facing the ASEAN Economic Society (AES). Therefore, this research evaluates the health surveillance system which is organized by Control, Quarantine and Surveillance Department, Health Office of Tanjung Priok Port. This study uses qualitative-evaluative method which utilizes Urgency Seriousness Growth (USG) method to determine priority issues and Root Cause analysis to determine the cause of prior problem. The result of this research shows that the implementation of epidemic potential disease surveillance in Tanjung Priok port has not done in the best possible way. It is because the lack of time allocation and the succinctness of the check list of ship's environmental health inspection. Therefore, Health Ministry of Indonesia should recruit more employees at the health office of Tanjung Priok port, hold a simulation of ship's inspection and simplify the list for ship's environmental health inspection.

Keywords: surveillance, epidemic potential disease, port health, bioterrorism

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Authors: İsmail Kavdır, M. Burak Büyükcan, Ferhat Kurtulmuş

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Table olive is a valuable product especially in Mediterranean countries. It is usually consumed after some fermentation process. Defects happened naturally or as a result of an impact while olives are still fresh may become more distinct after processing period. Defected olives are not desired both in table olive and olive oil industries as it will affect the final product quality and reduce market prices considerably. Therefore it is critical to sort table olives before processing or even after processing according to their quality and surface defects. However, doing manual sorting has many drawbacks such as high expenses, subjectivity, tediousness and inconsistency. Quality criterions for green olives were accepted as color and free of mechanical defects, wrinkling, surface blemishes and rotting. In this study, it was aimed to classify fresh table olives using different classifiers and NIR spectroscopy readings and also to compare the classifiers. For this purpose, green (Ayvalik variety) olives were classified based on their surface feature properties such as defect-free, with bruised defect and with fly defect using FT-NIR spectroscopy and classification algorithms such as artificial neural networks, ident and cluster. Bruker multi-purpose analyzer (MPA) FT-NIR spectrometer (Bruker Optik, GmbH, Ettlingen Germany) was used for spectral measurements. The spectrometer was equipped with InGaAs detectors (TE-InGaAs internal for reflectance and RT-InGaAs external for transmittance) and a 20-watt high intensity tungsten–halogen NIR light source. Reflectance measurements were performed with a fiber optic probe (type IN 261) which covered the wavelengths between 780–2500 nm, while transmittance measurements were performed between 800 and 1725 nm. Thirty-two scans were acquired for each reflectance spectrum in about 15.32 s while 128 scans were obtained for transmittance in about 62 s. Resolution was 8 cm⁻¹ for both spectral measurement modes. Instrument control was done using OPUS software (Bruker Optik, GmbH, Ettlingen Germany). Classification applications were performed using three classifiers; Backpropagation Neural Networks, ident and cluster classification algorithms. For these classification applications, Neural Network tool box in Matlab, ident and cluster modules in OPUS software were used. Classifications were performed considering different scenarios; two quality conditions at once (good vs bruised, good vs fly defect) and three quality conditions at once (good, bruised and fly defect). Two spectrometer readings were used in classification applications; reflectance and transmittance. Classification results obtained using artificial neural networks algorithm in discriminating good olives from bruised olives, from olives with fly defect and from the olive group including both bruised and fly defected olives with success rates respectively changing between 97 and 99%, 61 and 94% and between 58.67 and 92%. On the other hand, classification results obtained for discriminating good olives from bruised ones and also for discriminating good olives from fly defected olives using the ident method ranged between 75-97.5% and 32.5-57.5%, respectfully; results obtained for the same classification applications using the cluster method ranged between 52.5-97.5% and between 22.5-57.5%.

Keywords: artificial neural networks, statistical classifiers, NIR spectroscopy, reflectance, transmittance

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Authors: Kristian Bautista, Ruben A. Idoy

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A bio-inspired metaheuristic algorithm inspired by the theory of collective animal behavior (CAB) was integrated to density-based clustering modeled as multimodal optimization problem. The algorithm was tested on synthetic, Iris, Glass, Pima and Thyroid data sets in order to measure its effectiveness relative to CDE-based Clustering algorithm. Upon preliminary testing, it was found out that one of the parameter settings used was ineffective in performing clustering when applied to the algorithm prompting the researcher to do an investigation. It was revealed that fine tuning distance δ3 that determines the extent to which a given data point will be clustered helped improve the quality of cluster output. Even though the modification of distance δ3 significantly improved the solution quality and cluster output of the algorithm, results suggest that there is no difference between the population mean of the solutions obtained using the original and modified parameter setting for all data sets. This implies that using either the original or modified parameter setting will not have any effect towards obtaining the best global and local animal positions. Results also suggest that CDE-based clustering algorithm is better than CAB-density clustering algorithm for all data sets. Nevertheless, CAB-density clustering algorithm is still a good clustering algorithm because it has correctly identified the number of classes of some data sets more frequently in a thirty trial run with a much smaller standard deviation, a potential in clustering high dimensional data sets. Thus, the researcher recommends further investigation in the post-processing stage of the algorithm.

Keywords: clustering, metaheuristics, collective animal behavior algorithm, density-based clustering, multimodal optimization

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Authors: Sree Sanyal

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Research in ageing often highlights the age-related health dimension more than the psycho-social characteristics of the elderly, which also influences and challenges the health outcomes. Multimorbidity is defined as the person having more than one chronic non-communicable diseases and their prevalence increases with ageing. The study aims to evaluate the influence of social ties on self-reported prevalence of multimorbidity (selected chronic non-communicable diseases) among the selected states of elderly population in India. The data is accessed from Building Knowledge Base on Population Ageing in India (BKPAI), collected in 2011 covering the self-reported chronic non-communicable diseases like arthritis, heart disease, diabetes, lung disease with asthma, hypertension, cataract, depression, dementia, Alzheimer’s disease, and cancer. The data of the above diseases were taken together and categorized as: ‘no disease’, ‘one disease’ and ‘multimorbidity’. The predicted variables were demographic, socio-economic, residential types, and the variable of social ties includes social support, social engagement, perceived support, connectedness, and importance of the elderly. Predicted probability for multiple logistic regression was used to determine the background characteristics of the old in association with chronic morbidities showing multimorbidity. The finding suggests that 24.35% of the elderly are suffering from multimorbidity. Research shows that with reference to ‘no disease’, according to the socio-economic characteristics of the old, the female oldest old (80+) from others in caste and religion, widowed, never had any formal education, ever worked in their life, coming from the second wealth quintile standard, from rural Maharashtra are more prone with ‘one disease’. From the social ties background, the elderly who perceives they are important to the family, after getting older their decision-making status has been changed, prefer to stay with son and spouse only, satisfied with the communication from their children are more likely to have less single morbidity and the results are significant. Again, with respect to ‘no disease’, the female oldest old (80+), who are others in caste, Christian in religion, widowed, having less than 5 years of education completed, ever worked, from highest wealth quintile, residing in urban Kerala are more associated with multimorbidity. The elderly population who are more socially connected through family visits, public gatherings, gets support in decision making, who prefers to spend their later years with son and spouse only but stays alone shows lesser prevalence of multimorbidity. In conclusion, received and perceived social integration and support from associated neighborhood in the older days, knowing about their own needs in life facilitates better health and wellbeing of the elderly population in selected states of India.

Keywords: morbidity, multi-morbidity, prevalence, social ties

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Authors: Enrique Barbieri

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The basic disease-spread model described by three states denoting the susceptible (S), infectious (I), and removed (recovered and deceased) (R) sub-groups of the total population N, or SIR model, has been considered. Heuristic mitigating action profiles of the pharmaceutical and non-pharmaceutical types may be developed in a control design setting for the purpose of reducing the transmission rate or improving the recovery rate parameters in the model. Even though the transmission and recovery rates are not control inputs in the traditional sense, a linear observer and feedback controller can be tuned to generate an asymptotic estimate of the transmission rate for a linearized, discrete-time version of the SIR model. Then, a set of mitigating actions is suggested to steer the basic reproduction number toward unity, in which case the disease does not spread, and the infected population state does not suffer from multiple waves. The special case of piecewise constant transmission rate is described and applied to a seventh-order SEIQRDP model, which segments the population into four additional states. The offline simulations in discrete time may be used to produce heuristic policies implemented by public health and government organizations.

Keywords: control of SIR, observer, SEIQRDP, disease spread

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Authors: Ayda Youssef, Mohammed Ali Khalaf, Tarek Rafaat

Abstract:

Background: Langerhans cell histiocytosis (LCH) is a rare multi-systemic disease that shows an abnormal proliferation of these kinds of cells associated with a granular infiltration that affects different structures of the human body, including the lung, liver, spleen, lymph nodes, brain, mucocutaneous, soft tissue (head and neck), and salivary glands. Evaluation of the extent of disease is one of the major predictors of patient outcome. Objectives: To recognize the pathogenesis of Langerhans cell histiocytosis (LCH), describe the radiologic criteria that are suggestive of LCH in different organs rather than the bones and to illustrate the appropriate differential diagnoses for LCH in each of the common extra-osseous sites. Material and methods: A retrospective study was done on 150 biopsy-proven LCH patients from 2007 to 2012. All patients underwent imaging studies, mostly US, CT, and MRI. These patients were reviewed to assess the extra-skeletal manifestations of LCH. Results: In 150 patients with biopsy-proven LCH, There were 33 patients with liver affection, 5 patients with splenic lesions, 55 patients with enlarged lymph nodes, 9 patient with CNS disease and 11 patients with lung involvement. Conclusions: Because of the frequent LCH children and evaluation of the extent of disease is one of the major predictors of patient outcome. Radiologist need to be familiar with its presentation in different organs and regions of body outside the commonest site of affection (bones). A high-index suspicion should be raised a biopsy is recommended in the presence of radiological suspicion. Chemotherapy is the preferred therapeutic modality.

Keywords: langerhans cell histiocytosis, extra-skeletal, pediatrics, radiology

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Authors: M. Samsami, A. Hekmatdoost, N. Ebrahimi Daryani, P. Rezanejad Asl

Abstract:

Ulcerative colitis (UC) is an inflammatory bowel disease in which immune and inflammatory factors are thought to be effective in this disease. Resveratrol is an antioxidant and anti-inflammatory compound. This study determined the effects of resveratrol compound on inflammatory factors in patients with ulcerative colitis. This study was a double-blind randomized clinical trial conducted on 50 patients with UC. Subjects received one capsule daily for 6 wk of either resveratrol (500 mg) or a placebo. Inflammatory factors, anthropometric measures, and IBDQ-9 (Inflammatory Bowel Disease Questionnaire-9) scores were assessed at baseline and at the end of the study. STATA12 software was used for data analysis. No significant differences were found in the background variables between the two groups at baseline. The results indicated that resveratrol supplementation for 6 week significantly decreased plasma levels of TNF-a and hs-CRP and the activity of NF-κB over the placebo group (p<0.001). Significant differences remained after adjustment for vitamin C (p<0.0001). The IBDQ-9 scores increased significantly in the resveratrol group over the placebo group (p<0.001). The findings of this study showed that resveratrol supplementation can be useful in patients with ulcerative colitis.

Keywords: IBD, inflammation, resveratrol, ulcerative colitis

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Authors: Angelis P. Barlampas

Abstract:

Purpose of Learning Objective: This case depicts the need for cooperation between the emergency department and the radiologist to achieve the best diagnostic result for the patient. The clinical picture must correlate well with the radiology report and when it does not, this is not necessarily someone’s fault. Careful interpretation and good knowledge of the limitations, advantages and disadvantages of each imaging procedure are essential for the final diagnostic goal. Methods or Background: A patient was brought to the emergency department by their relatives. He was suddenly confused and his mental status was altered. He hadn't any history of mental illness and was otherwise healthy. A computing tomography scan without contrast was done, but it was unremarkable. Because of high clinical suspicion of probable neurologic disease, he was admitted to the hospital. Results or Findings: Another T was done after 48 hours. It showed a hypodense region in both thalamic areas. Taking into account that the first CT was normal, but the initial clinical picture of the patient was alerting of something wrong, the repetitive CT exam is highly suggestive of a probable diagnosis of bilateral thalamic infractions. Differential diagnosis: Primary bilateral thalamic glioma, Wernicke encephalopathy, osmotic myelinolysis, Fabry disease, Wilson disease, Leigh disease, West Nile encephalitis, Greutzfeldt Jacob disease, top of the basilar syndrome, deep venous thrombosis, mild to moderate cerebral hypotension, posterior reversible encephalopathy syndrome, Neurofibromatosis type 1. Conclusion: As is the case of limitations for any imaging procedure, the same applies to CT. The acute ischemic attack can not depict on CT. A period of 24 to 48 hours has to elapse before any abnormality can be seen. So, despite the fact that there are no obvious findings of an ischemic episode, like paresis or imiparesis, one must be careful not to attribute the patient’s clinical signs to other conditions, such as toxic effects, metabolic disorders, psychiatric symptoms, etc. Further investigation with MRI or at least a repeated CT must be done.

Keywords: CNS, CT, thalamus, emergency department

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Authors: Salah Hadjout, Mohamed Zouidi

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In Algeria, several works carried out in recent years have shown the importance of fusarium head blight in durum wheat. Indeed, this disease is caused by a complex of Fusarium genus pathogens. The research carried out reports that F. culmorum is the main species infecting cereals. These informations motivated our interest in the field evaluation of the behavior of some durum wheat genotypes (parental varieties and lines) with regard to fusarium head blight, mainly caused by four F. culmorum isolates. Our research work focused on following the evolution of symptom development throughout the grain filling, after artificial inoculation of ears by Fusarium isolates in order to establish a first image on the differences in genotype behavior to fusarium haed blight. Field disease assessment criteria are: disease assessment using a grading scale, thousand grain weight measurement and AUDPC. The results obtained revealed that the varieties and lines resulting from crosses had a quite different level of sensitivity to F. culmorum species and no genotype showed complete resistance in our culture conditions. Among the material tested, some lines showed higher resistance than their parents. The results also show a slight behavioral variability also linked to the aggressiveness of the Fusarium species studied in this work. Our results open very important research perspectives on fusarium head blight, in particular the search for toxins produced by Fusarium species.

Keywords: fusarium head blight, durum wheat, Fusarium culmorum, field disease assessment criteria, Algeria

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Authors: Deokho Kim, Wonwoo Lee, Jaewoong Lee, Teresa Ng, Gun-Ill Lee, Jiwon Jeong

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This paper presents a method for improving object search accuracy using a deep learning model. A major limitation to provide accurate similarity with deep learning is the requirement of huge amount of data for training pairwise similarity scores (metrics), which is impractical to collect. Thus, similarity scores are usually trained with a relatively small dataset, which comes from a different domain, causing limited accuracy on measuring similarity. For this reason, this paper proposes a deep learning model that can be trained with a significantly small amount of data, a clustered data which of each cluster contains a set of visually similar images. In order to measure similarity distance with the proposed method, visual features of two images are extracted from intermediate layers of a convolutional neural network with various pooling methods, and the network is trained with pairwise similarity scores which is defined zero for images in identical cluster. The proposed method outperforms the state-of-the-art object similarity scoring techniques on evaluation for finding exact items. The proposed method achieves 86.5% of accuracy compared to the accuracy of the state-of-the-art technique, which is 59.9%. That is, an exact item can be found among four retrieved images with an accuracy of 86.5%, and the rest can possibly be similar products more than the accuracy. Therefore, the proposed method can greatly reduce the amount of training data with an order of magnitude as well as providing a reliable similarity metric.

Keywords: visual search, deep learning, convolutional neural network, machine learning

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Authors: Ali Saeed Alghamdi, Basel Mazen Alsolami, Basel Saeed Alghamdi, Muhanad Saleh Alzahrani Alamri, Salman Anwar Thabet, Abdulhalim J. Kinsara

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Objectives: This study measures the knowledge of the cardiovascular disease among the general population in western regions of Saudi Arabia, and it aimed to increase the level of awareness about cardiovascular diseases among the general population by providing an awareness lecture that included information about the risk factors, major symptoms, and prevention of cardiovascular diseases. The lecture has been attached at the end of the questionnaire. Setting: This study was conducted through an online questionnaire that included our aim and main objectives that targeted the general population in the Western regions of Saudi Arabia (Makkah and Madinah regions). Participants: This study participants were 460 collected through an online questionnaire. Methods: All Saudi citizens and residents who live in the western region of Saudi Arabia aged 18 years and above will be invited to participate voluntarily. A pre-structured questionnaire was designed to collect data on age, gender, marital status, education level, occupation, lifestyle habits, and history of heart diseases, with cardiac symptoms and risk factors sections. Results: The majority of respondents were females (74.8%) and Saudis. The knowledge about cardiovascular disease risk factors was weak. Only (18.5%) scores an excellent response regarding risk factors awareness. Lack of exercise, stress, and obesity were the most known risk factors. Regarding cardiovascular disease symptoms, chest pain scores the highest symptom (87.6%) among other symptoms like dyspnea, syncope, and excessive sweating. Participants revealed a poor awareness regarding cardiovascular disease symptoms also (0.9%). However, preventable factors for cardiovascular diseases were more knowledgeable than others categories in this study (60% fall into excellent knowledge). Smoking cessation, normal cholesterol level, and normal blood pressure score the highest preventable methods (92.2%), (88.6%), and (78.7%) respectively. 83.7% of the participant have attended the awareness lecture, and 99 of the attendees reported that the lecture increased their knowledge about cardiovascular disease. Conclusion: This study discussed the level of community awareness of cardiovascular disease in terms of symptoms, risk factors, and protective factors. We found a huge lack of the participant's level of knowledge about the disease and how to prevent it. Moreover, we measure the prevalence of the comorbidities among our participants (diabetes, hypertension, hypercholesterolemia/ hypertriglyceridemia) and their extent of adherence to their medication. In conclusion, this study not only demonstrates awareness of cardiovascular disease risk factors, symptoms, management, and the association between each domain but also provides educational material. Further educational material and campaigns are required to increase awareness and knowledge about cardiovascular diseases.

Keywords: awareness, cardiovascular diseases, education, prevention, risk factors

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Authors: Md. Minhazul Islam, Shah Ashisul Abed Nipun, Majharul Islam, Md. Abdur Rakib Rahat, Jonayet Miah, Salsavil Kayyum, Anwar Shadaab, Faiz Al Faisal

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The target of this research is to predict Myocardial Infarction using unsupervised Machine Learning algorithms. Myocardial Infarction Prediction related to heart disease is a challenging factor faced by doctors & hospitals. In this prediction, accuracy of the heart disease plays a vital role. From this concern, the authors have analyzed on a myocardial dataset to predict myocardial infarction using some popular Machine Learning algorithms K-Means and Hierarchical Clustering. This research includes a collection of data and the classification of data using Machine Learning Algorithms. The authors collected 345 instances along with 26 attributes from different hospitals in Bangladesh. This data have been collected from patients suffering from myocardial infarction along with other symptoms. This model would be able to find and mine hidden facts from historical Myocardial Infarction cases. The aim of this study is to analyze the accuracy level to predict Myocardial Infarction by using Machine Learning techniques.

Keywords: Machine Learning, K-means, Hierarchical Clustering, Myocardial Infarction, Heart Disease

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Authors: Amarachukwu B. Isiaka, Vivian N. Anakwenze, Chinyere C. Ezemba, Chiamaka R. Ilodinso, Chikodili G. Anaukwu, Chukwuebuka M. Ezeokoli, Ugonna H. Uzoka

Abstract:

Infectious diseases continue to pose significant threats to global public health, necessitating advanced and timely detection methods for effective outbreak management. This study explores the integration of artificial intelligence (AI) in the early detection and management of infectious disease outbreaks. Leveraging vast datasets from diverse sources, including electronic health records, social media, and environmental monitoring, AI-driven algorithms are employed to analyze patterns and anomalies indicative of potential outbreaks. Machine learning models, trained on historical data and continuously updated with real-time information, contribute to the identification of emerging threats. The implementation of AI extends beyond detection, encompassing predictive analytics for disease spread and severity assessment. Furthermore, the paper discusses the role of AI in predictive modeling, enabling public health officials to anticipate the spread of infectious diseases and allocate resources proactively. Machine learning algorithms can analyze historical data, climatic conditions, and human mobility patterns to predict potential hotspots and optimize intervention strategies. The study evaluates the current landscape of AI applications in infectious disease surveillance and proposes a comprehensive framework for their integration into existing public health infrastructures. The implementation of an AI-driven early detection system requires collaboration between public health agencies, healthcare providers, and technology experts. Ethical considerations, privacy protection, and data security are paramount in developing a framework that balances the benefits of AI with the protection of individual rights. The synergistic collaboration between AI technologies and traditional epidemiological methods is emphasized, highlighting the potential to enhance a nation's ability to detect, respond to, and manage infectious disease outbreaks in a proactive and data-driven manner. The findings of this research underscore the transformative impact of harnessing AI for early detection and management, offering a promising avenue for strengthening the resilience of public health systems in the face of evolving infectious disease challenges. This paper advocates for the integration of artificial intelligence into the existing public health infrastructure for early detection and management of infectious disease outbreaks. The proposed AI-driven system has the potential to revolutionize the way we approach infectious disease surveillance, providing a more proactive and effective response to safeguard public health.

Keywords: artificial intelligence, early detection, disease surveillance, infectious diseases, outbreak management

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Authors: Arash Osmani, Ian Robertson, Ihab Habib, Ahmad Aslami

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Foot and Mouth Disease (FMD) is endemic in Afghanistan. A retrospective study of data collected through passive surveillance of outbreaks of FMD from 1995 to 2016 was undertaken. A total of 1471 outbreaks were reported between 1995 and 2008. Of 7776 samples originating from 34 provinces tested between 2009 and 2016 4845 (62.3%) tested positive. The prevalence varied significantly between years (2009 and 2016) (P < 0.001); however, the number of outbreaks did not differ significantly (P = 0.24) between 1995 and 2008. During this period, there was a strong correlation between the number of outbreaks reported and the number of districts with infected animals (r = 0.74, P = 0.002). Serotype O was the predominant serotype detected, although serotypes A and Asia1 were also detected. Cattle were involved in all outbreaks reported. Herat province in the north-west (bordering Iran), Nangarhar province in the east (bordering Pakistan) and Kabul province in the centre of the country had infections detected in all years of the study. The findings from this study provide valuable direction for further research to understand the epidemiology of FMD in Afghanistan.

Keywords: foot and mouth disease, retrospective, epidemiology, Afghanistan

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Authors: Hediyeh Talebi, Shokoofeh Ghiam, Changiz Eslahchi

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Traditionally, Alzheimer’s disease research has focused on genes with significant fold changes, potentially neglecting subtle but biologically important alterations. Our study introduces an integrative approach that highlights genes crucial to underlying biological processes, regardless of their fold change magnitude. Alzheimer's Single-cell RNA-seq data related to the peripheral blood mononuclear cells (PBMC) was extracted from the Gene Expression Omnibus (GEO). After quality control, normalization, scaling, batch effect correction, and clustering, differentially expressed genes (DEGs) were identified with adjusted p-values less than 0.05. These DEGs were categorized based on cell-type, resulting in four datasets, each corresponding to a distinct cell type. To distinguish between cells from healthy individuals and those with Alzheimer's, an adversarial autoencoder with a classifier was employed. This allowed for the separation of healthy and diseased samples. To identify the most influential genes in this classification, the weight matrices in the network, which includes the encoder and classifier components, were multiplied, and focused on the top 20 genes. The analysis revealed that while some of these genes exhibit a high fold change, others do not. These genes, which may be overlooked by previous methods due to their low fold change, were shown to be significant in our study. The findings highlight the critical role of genes with subtle alterations in diagnosing Alzheimer's disease, a facet frequently overlooked by conventional methods. These genes demonstrate remarkable discriminatory power, underscoring the need to integrate biological relevance with statistical measures in gene prioritization. This integrative approach enhances our understanding of the molecular mechanisms in Alzheimer’s disease and provides a promising direction for identifying potential therapeutic targets.

Keywords: alzheimer's disease, single-cell RNA-seq, neural networks, blood biomarkers

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Authors: N. Balaban, A. Buernstein, F. Gelman, Z. Ronen

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Brominated flame retardants are widespread pollutants, and are known to be toxic, carcinogenic, endocrinic disrupting as well as recalcitrant. The industrial complex Neot Hovav, in the Northern Negev, Israel, is situated above a fractured chalk aquitard, which is polluted by a wide variety of halogenated organic compounds. Two of the abundant pollutants found in the site are Dibromoneopentyl-glycol (DBNPG) and tribromoneopentyl-alcohol (TBNPA). Due to the elusive nature of the groundwater flow, it is difficult to connect between the spatial changes in contaminant concentrations to degradation. In this study, we attempt to determine whether these compounds are biodegraded in the groundwater, and to gain a better understanding concerning the bacterial community in the groundwater. This was achieved through the application of compound-specific isotope analysis (CSIA) of carbon (13^C/12^C) and bromine (81^Br/79^Br), and new-generation MiSeq pyrosequencing. The sampled boreholes were distributed among three main areas of the industrial complex: around the production plant of TBNPA and DBNPG; along the Hovav Wadi (small ephemeral stream) which crosses and drains the industrial complex; and downstream to the industrial area. TBNPA and DBNPG are found in all three areas, with no clear connection to the proximity of the borehole to the production plant. Initial isotopic data of TBNPA from boreholes in the area surrounding the production plant, reveal no changes in the carbon and bromine isotopic values. When observing the microbial groundwater community, the dominant phylum is Proteobacteria. Known anaerobic dehalogenating bacteria such as Dehalococcoides from the Chloroflexi phylum have also been detected. A statistical comparison of the groundwater microbial diversity using a multi-variant ordination of non-metric multidimensional scaling (NMDS) reveals three main clusters in accordance to spatial location in the industrial complex: all the boreholes sampled adjacent to the production plant cluster together and separately from the Wadi Hovav boreholes cluster and the downstream to the industrial area borehole cluster. This work provides the basis for the development and implication of an isotopic fractionation based tool for assessing the biodegradation of brominated organic compounds in contaminated environments, and a novel attempt to characterize the spatial microbial diversity in the contaminated site.

Keywords: biodegradation, brominated flame retardants, groundwater, isotopic fractionation, microbial diversity

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