Search results for: cardiovascular diseases

Authors: Zain Ul Abdin, Mirza Aizaz Asim, Rao Sohail Ahmad Khan, Luqman Amrao, Fiaz Hussain, Hasooba Hira, Saqi Kosar Abbas

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The success of Integrated vector management programmes mainly depends on the correct identification of insect vector species involved in vector borne diseases. Based on molecular data the most important insect species involved as vectors for Zoonotic diseases in Pakistan were identified. The precise and accurate identification of such type of organism is only possible through molecular based techniques like “DNA barcoding”. Morphological species identification in insects at any life stage, is very challenging, therefore, DNA barcoding was used as a tool for rapid and accurate species identification in a wide variety of taxa across the globe and parallel studies revealed that DNA barcoding data can be effectively used in resolving taxonomic ambiguities, detection of cryptic diversity, invasion biology, description of new species etc. A comprehensive survey was carried out for the collection of insects (both adult and immature stages) in district Faisalabad, Pakistan and their DNA was extracted and mitochondrial cytochrome oxidase subunit I (COI-59) barcode sequences was used for molecular identification of immature and adult life stage.This preliminary research work opens new frontiers for developing sustainable insect vectors management programmes for saving lives of mankind from fatal diseases.

Keywords: zoonotic diseases, cytochrome oxidase, and insect vectors, CO1

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Authors: Mahdi Rahaie

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MicroRNAs are a novel class of small RNAs which regulate gene expression by translational repression or degradation of messenger RNAs. To produce sensitive, simple and cost-effective assays for microRNAs, detection is in urgent demand due to important role of these biomolecules in progression of human disease such as Alzheimer’s, Multiple sclerosis, and some other neurodegenerative diseases. Herein, we report several novel, sensitive and specific microRNA nanobiosensors which were designed based on colorimetric and fluorescence detection of nanoparticles and hybridization chain reaction amplification as an enzyme-free amplification. These new strategies eliminate the need for enzymatic reactions, chemical changes, separation processes and sophisticated equipment whereas less limit of detection with most specify are acceptable. The important features of these methods are high sensitivity and specificity to differentiate between perfectly matched, mismatched and non-complementary target microRNAs and also decent response in the real sample analysis with blood plasma. These nanobiosensors can clinically be used not only for the early detection of neuro diseases but also for every sickness related to miRNAs by direct detection of the plasma microRNAs in real clinical samples, without a need for sample preparation, RNA extraction and/or amplification.

Keywords: hybridization chain reaction, microRNA, nanobiosensor, neurodegenerative diseases

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Authors: Arsalan Ghaderi

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Introduction: Inactivity is one of the most important risk factors for cardiovascular disease. According to the study prevalence of inactivity in Iran, about 67.5% and in the staff, and especially nurses, are similar. The inflammatory index (HS-CRP) is highly predictive of the progression of these diseases. Physical activity education is very important in preventing these diseases. One of the modern educational methods is web-based theory-based education. Methods: This is a semi-experimental interventional study which was conducted in Isfahan and Kurdistan universities of medical sciences in two stages. A cross-sectional study was done to determine the status of physical activity and its predictive factors. Then, intervention was performed, and six months later the data were retrieved. The data was collected using a demographic questionnaire, an integrative model of behavior prediction constructs, a standard physical activity questionnaire and (HS-CRP) test. Data were analyzed by SPSS software. Results: Physical activity was low in 66.6% of nurses, 25.4% were moderate and 8% severe. According to Pearson correlation matrix, the highest correlation was found between behavioral intention and skill structures (0.553**), subjective norms (0.222**) and self-efficacy (0.198**). The relationship between age and physical activity in the first study was reverse and significant. After intervention, there was a significant change in attitudes, self-efficacy, skill and behavioral intention in the intervention group. This change was significant in attitudes, self-efficacy and environmental conditions of the control group. HS-CRP index decreased significantly after intervention in both groups, but there was not a significant relationship between inflammatory index and physical activity score. The change in physical activity level was significant only in the control group. Conclusion: Despite the effect of educational intervention on attitude, self-efficacy, skill, and behavioral intention, the results showed that if factors such as environmental factors are not corrected, training and changing structures cannot lead to physical activity behavior. On the other hand, no correlation between physical activity and HS-CRP showed that this index can be influenced by other factors, and this should be considered in any intervention to reduce the HS-CRP index.

Keywords: HS-CRP, integrative model of behavior prediction, physical activity, nurses, web-based education

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Authors: Saylav Ejder Bora, Arife Erdogan, Mumin Alper Erdogan, Oytun Erbas, Ismet Parlak

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Objective: The aim of this study was to evaluate histological, electrical and biochemical effects of metoprolol, lipid emulsion and magnesium sulphate as an alternative method to be used in preventing long QT emergence, that is among the lethal consequences of amitryptiline toxicity. Methods: Thirty Sprague- Dawley male rats were included. Rats were randomly separated into 5 groups. First group was administered saline only while the rest had received amitryptiline 100 mg/kg + saline, 5 mg/kg metoprolol, 20 ml/kg lipid emulsion and 75 mg/kg magnesium sulphate (MgSO4) intraperitoneally. ECG at DI lead, biochemical tests following euthanasia were performed in all groups after 1 hour of administration. Cardiac tissues were removed, sections were prepared and examined. Results: QTc values were significantly shorter in the rest when compared to amitryptiline+ saline group. While lipid emulsion did not affect proBNP and troponin values biochemically as compared to that of the control group, histologically, it was with reduced caspase 3 expression. Though statistically insignificant in the context of biochemical changes, pro-BNP and urea levels were lower in the metoprolol group when compared to controls. Similarly, metoprolol had no statistically significant effect on histological caspase 3 expression in the group that was treated with amitryptiline+metoprolol. On the other hand, there was a statistically significant decrease in Troponin, pro-BNP and urea levels as well as significant decline in histological caspase 3 expression within the MgSO4 group when compared to controls. Conclusion: As still a frequent cause of mortality in emergency units, administration of MgSO4, lipid emulsion and metoprolol might be beneficial in alternative treatment of cardiovascular toxicity caused by tricyclic antidepressant overdose, whether intake would be intentional or accidental.

Keywords: amitryptiline, cardiovascular toxicity, long QT, Rat Model

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Authors: Linda Saili, Amel Hanini, Chiraz Smirani, Iness Azzouz, Amina Azzouz, Hafedh Abdemelek, Zihad Bouslama

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Electrocardiogram and arterial pressure measurements were studied under acute exposures to WIFI (2.45 GHz) during one hour in adult male rabbits. Antennas of WIFI were placed at 25 cm at the right side near the heart. Acute exposure of rabbits to WIFI increased heart frequency (+ 22%) and arterial blood pressure (+14%). Moreover, analysis of ECG revealed that WIFI induced a combined increase of PR and QT intervals. By contrast, the same exposure failed to alter the maximum amplitude and P waves. After intravenously injection of dopamine (0.50 ml/kg) and epinephrine (0.50ml/kg) under acute exposure to RF we found that WIFI alter catecholamines(dopamine, epinephrine) action on heart variability and blood pressure compared to control. These results suggest for the first time, as far as we know, that exposure to WIFI affect heart rhythm, blood pressure, and catecholamines efficacy on cardiovascular system; indicating that radio frequency can act directly and/or indirectly on the cardiovascular system.

Keywords: heart rate (HR), arterial pressure (PA), electrocardiogram (ECG), the efficacy of catecholamines, dopamine, epinephrine

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Authors: Megha Gupta, Nupur Prakash

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Identification of plant diseases has been performed using machine learning and deep learning models on the datasets containing images of healthy and diseased plant leaves. The current study carries out an evaluation of some of the deep learning models based on convolutional neural network (CNN) architectures for identification of plant diseases. For this purpose, the publicly available New Plant Diseases Dataset, an augmented version of PlantVillage dataset, available on Kaggle platform, containing 87,900 images has been used. The dataset contained images of 26 diseases of 14 different plants and images of 12 healthy plants. The CNN models selected for the study presented in this paper are AlexNet, ZFNet, VGGNet (four models), GoogLeNet, and ResNet (three models). The selected models are trained using PyTorch, an open-source machine learning library, on Google Colaboratory. A comparative study has been carried out to analyze the high degree of accuracy achieved using these models. The highest test accuracy and F1-score of 99.59% and 0.996, respectively, were achieved by using GoogLeNet with Mini-batch momentum based gradient descent learning algorithm.

Keywords: comparative analysis, convolutional neural networks, deep learning, plant disease identification

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Authors: Hassan Shahmiri Barzoki

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Background: Posttraumatic stress disorder (PTSD) is an abnormal physiologic and psychological reaction in person with severe traumatic history. In recent studies, the relationship between PTSD and some other disease apparently unrelated to psychological situations, such as cardiovascular diseases, diabetes, and metabolic syndrome, has been revealed. Thus, the aim of this study was to survey the prevalence of metabolic syndrome and mental health in PTSD patients. Methods: The research design was retrospective cohort study. Subjects were consisted of 142 Iran-Iraq war veterans with PTSD (age: 40-60 years), and the control group was consisted of 153 veterans without PTSD. Data was collected using questionnaires, physical exams and laboratory tests. Results: Prevalence of metabolic syndrome was 45.1%in PTSD group and 17% in control group. In addition, blood pressure, triglyceride and fasting blood sugar in PTSD group were significantly higher than control group (p<0.05). Also, PTSD patients had significant high rates of psychiatric disorders. Conclusion: PTSD patients are more prone to metabolic syndrome and psychiatric disorders than control group.

Keywords: mental health, metabolic syndrome, post traumatic stress disorder, patient

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Authors: Kajori Banerjee, Laxmi Kant Dwivedi

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India is a part of the ongoing globalization, contemporary convergence, industrialization and technical advancement that is taking place world-wide. Some of the manifestations of this evolution is rapid demographic, socio-economic, epidemiological and health transition. There has been a considerable increase in non-communicable diseases due to change in lifestyle. This study aims to assess the direction of burden of disease and compare the pressure of infectious diseases against cardio-vascular, endocrine, metabolic and nutritional diseases. The change in prevalence in a ten-year period (2004-2014) is further decomposed to determine the net contribution of various socio-economic and demographic covariates. The present study uses the recent 71st (2014) and 60th (2004) rounds of National Sample Survey. The pressure of infectious diseases against cardio-vascular (CVD), endocrine, metabolic and nutritional (EMN) diseases during 2004-2014 is calculated by Prevalence Rates (PR), Hospitalization Rates (HR) and Case Fatality Rates (CFR). The prevalence of non-communicable diseases are further used as a dependent variable in a logit regression to find the effect of various social, economic and demographic factors on the chances of suffering from the particular disease. Multivariate decomposition technique further assists in determining the net contribution of socio-economic and demographic covariates. This paper upholds evidences of stagnation of the burden of communicable diseases (CD) and rapid increase in the burden of non-communicable diseases (NCD) uniformly for all population sub-groups in India. CFR for CVD has increased drastically in 2004-2014. Logit regression indicates the chances of suffering from CVD and EMN is significantly higher among the urban residents, older ages, females, widowed/ divorced and separated individuals. Decomposition displays ample proof that improvement in quality of life markers like education, urbanization, longevity of life has positively contributed in increasing the NCD prevalence rate. In India’s current epidemiological phase, compression theory of morbidity is in action as a significant rise in the probability of contracting the NCDs over the time period among older ages is observed. Age is found to play a vital contributor in increasing the probability of having CVD and EMN over the study decade 2004-2014 in the nationally representative sample of National Sample Survey.

Keywords: cardio-vascular disease, case-fatality rate, communicable diseases, hospitalization rate, multivariate decomposition, non-communicable diseases, prevalence rate

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Authors: Scott Cavinder

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Surgical site infections (SSI) are a known complication to any surgical procedure and are one of the most common nosocomial infections. Globally it is estimated 300 million surgical procedures take place annually, with an incidence of SSI’s estimated to be 11 of 100 surgical patients developing an infection within 30 days after surgery. The specific purpose of the project is to address the PICOT (Problem, Intervention, Comparison, Outcome, Time) question: In patients who have undergone cardiothoracic or vascular surgery (P), does implementation of a post-operative care bundle based on current EBP (I) as compared to current clinical agency practice standards (C) result in a decrease of SSI (O) over a 12-week period (T)? Synthesis of Supporting Evidence: A literature search of five databases, including citation chasing, was performed, which yielded fourteen pieces of evidence ranging from high to good quality. Four common themes were identified for the prevention of SSI’s including use and removal of surgical dressings; use of topical antibiotics and antiseptics; implementation of evidence-based care bundles, and implementation of surveillance through auditing and feedback. The Iowa Model was selected as the framework to help guide this project as it is a multiphase change process which encourages clinicians to recognize opportunities for improvement in healthcare practice. Practice/Implementation: The process for this project will include recruiting postsurgical participants who have undergone cardiovascular or thoracic surgery prior to discharge at a Northwest Indiana Hospital. The patients will receive education, verbal instruction, and return demonstration. The patients will be followed for 12 weeks, and wounds assessed utilizing the National Healthcare Safety Network//Centers for Disease Control (NHSN/CDC) assessment tool and compared to the SSI rate of 2021. Key stakeholders will include two cardiovascular surgeons, four physician assistants, two advance practice nurses, medical assistant and patients. Method of Evaluation: Chi Square analysis will be utilized to establish statistical significance and similarities between the two groups. Main Results/Outcomes: The proposed outcome is the prevention of SSIs in the post-op cardiothoracic and vascular patient. Implication/Recommendation(s): Implementation of standardized post operative care bundles in the prevention of SSI in cardiovascular and thoracic surgical patients.

Keywords: cardiovascular, evidence based practice, infection, post-operative, prevention, thoracic, surgery

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Authors: Amira Ben Rabeh, Faouzi Benzarti, Hamid Amiri, Mouna Bouaziz

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Alzheimer is a disease that affects the brain. It causes degeneration of nerve cells (neurons) and in particular cells involved in memory and intellectual functions. Early diagnosis of Alzheimer Diseases (AD) raises ethical questions, since there is, at present, no cure to offer to patients and medicines from therapeutic trials appear to slow the progression of the disease as moderate, accompanying side effects sometimes severe. In this context, analysis of medical images became, for clinical applications, an essential tool because it provides effective assistance both at diagnosis therapeutic follow-up. Computer Assisted Diagnostic systems (CAD) is one of the possible solutions to efficiently manage these images. In our work; we proposed an application to detect Alzheimer’s diseases. For detecting the disease in early stage we used the three sections: frontal to extract the Hippocampus (H), Sagittal to analysis the Corpus Callosum (CC) and axial to work with the variation features of the Cortex(C). Our method of classification is based on Support Vector Machine (SVM). The proposed system yields a 90.66% accuracy in the early diagnosis of the AD.

Keywords: Alzheimer Diseases (AD), Computer Assisted Diagnostic(CAD), hippocampus, Corpus Callosum (CC), cortex, Support Vector Machine (SVM)

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Authors: M. A. Munteanu, A. M. Lungu, A. I. Chivescu, V. Teodorescu, E. Tufanoiu, C. Nicolae, T. I. Nanea

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Introduction: Sodium-glucose co-transporter 2 inhibitors (SGLT2i), which were first developed as antidiabetic medications, have demonstrated numerous positive benefits on the cardiovascular system, especially in the prevention of heart failure (HF). HF is a challenging, multifaceted disease that needs all-encompassing therapy. It should not be viewed as a limited form of heart illness but rather as a systemic disease that leads to multiple organ failure and death. SGLT2i is an extremely effective tool for treating HF by using its pleiotropic effects. In addition to its use in patients with diabetes mellitus who are at high cardiovascular risk or who have already experienced a cardiovascular event, SGLT2i administration has been shown to have positive effects on a variety of HF manifestations and stages, regardless of the patient's presence of diabetes mellitus. Material and Methods: According to the guide, 110 patients (83 males and 27 females) with heart failure with mildly reduced ejection fraction (HFmrEF), with T2D and neoplasia, were enrolled in the prospective study. The structural and functional state of the left ventricle myocardium and ejection fraction was assessed through echocardiography. Patients were randomized to receive once-daily dapagliflozin 10 mg. Results: Patients with HFmrEF were divided into 3 subgroups according to age. 7% (8) patients aged < 45 years, 35% (28) patients aged between 46-59 years, and 58% (74) patients aged> 60 years. The most prevalent comorbidities were hypertension (43.1%), coronary heart disease (40%), and obesity (33.2%). Study drug discontinuation and serious adverse events were not frequent in the subgroups, in either men or women, until now. Conclusions: SGLT-2 inhibitors are a novel class of antidiabetic agents that have demonstrated positive efficacy and safety outcomes in the setting of HFmrEF. Until now, in our study, dapagliflozin was safe and well-tolerated irrespective of sex.

Keywords: diabetes mellitus type 2, Sodium-glucose co-transporters-2 inhibitors, heart failure, neoplasia

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Authors: Kobus-Cisowska Joanna, Flaczyk Ewa, Gramza-Michalowska Anna, Kmiecik Dominik, Przeor Monika, Marcinkowska Agata, Korczak Józef

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Cereal products, including mainly bread is a staple food known from the beginning of history throughout the world. It is now believed that there is no replacement of the basic food. Bread, due to the high content of starch is the energy source for the proper functioning of our body. It also contains proteins, fats, vitamins, especially of the B group and vitamin E, a number of minerals, and fiber. The aim of the study was to evaluate the antioxidant activity of new developed bread premixes with mulberry fruits for people with anemia, diabetes, obesity and cardiovascular disease. From the finished product-bread, aqueous and methanol extracts was prepared, which in next step were analyzed to assess the activity of the radical DPPH test, ABTS, chelating activity, the ability to reduce metals. Extracts were prepared from bread were acquired with premixes directly after production and stored for three months. The resulting trial breads effect by different mechanisms of antioxidant. They showed the ability to scavenge radicals ABTS and DPPH and chelating activity. Methanol extracts showed significantly greater antioxidant activity in comparison with aqueous extracts, and the largest effect was estimated for sample of bread for anemia, diabetes and cardiovascular disease. The greatest ability to scavenging ABTS radicals showed breads for anemia, diabetes and cardiovascular disease, while smaller for anemia and control sample. It was shown that the methanol extracts of the breads samples showed no ability to chelate iron (II). These properties are observed only in the aqueous extracts. The greatest ability attempt had anemia while the lowest control sample. Financial supported by the UE Project no POIG 01.01.02-00-061/09.

Keywords: morus alba, antioxidant activity, free radicals, polyphenols

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Authors: I. L. Ibrahim, A. Mann, B. M. Abdullahi

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Infectious diseases are prevalent in developing countries and plant extracts are known to contained bioactive compounds that can be used in the management of these diseases. The entire plant of Chrysanthellum indicum (Linn) was air-dried and pulverized into fine powder and then percolated to give ethanol and aqueous extracts. These extracts were phytochemically screened for metabolites and evaluated antibacterial activity against some pathogenic organisms Klebsilla, pneumonia, Bacillus subtilis, and Pseudomonas aeruginosa using agar dilution method. It was found that crude extracts of C. indicum revealed the presence of saponins, tannins, alkaloids, steroidal nucleus, cardiac glycosides, and coumarin while flavonoids and anthraquinones were absent. The Minimum Inhibitory Concentration (MIC) and Minimum Bactericidal Concentration (MBC) of the active extract of C. indicum shows that the extract could be a potential source of antibacterial agents.

Keywords: antibacterial activity, Chrysanthellum indicum, infectious diseases, phytochemical screening

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Authors: Mahdi Farajzadeh Ajirlou

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Prior evidence of normal cardiac anatomy is desirable to relieve the anxiety of cases with a family history of congenital heart disease or to offer the option of early gestation termination or close follow-up should a cardiac anomaly be proved. Fetal heart discovery plays an important part in the opinion of the fetus, and it can reflect the fetal heart function of the fetus, which is regulated by the central nervous system. Acquisition of ventricular volume and inflow data would be useful to quantify more valve regurgitation and ventricular function to determine the degree of cardiovascular concession in fetal conditions at threat for hydrops fetalis. This study discusses imaging the fetal heart with transvaginal ultrasound, Doppler ultrasound, three-dimensional ultrasound (3DUS) and four-dimensional (4D) ultrasound, spatiotemporal image correlation (STIC), glamorous resonance imaging and cardiac catheterization. Doppler ultrasound (DUS) image is a kind of real- time image with a better imaging effect on blood vessels and soft tissues. DUS imaging can observe the shape of the fetus, but it cannot show whether the fetus is hypoxic or distressed. Spatiotemporal image correlation (STIC) enables the acquisition of a volume of data concomitant with the beating heart. The automated volume accession is made possible by the array in the transducer performing a slow single reach, recording a single 3D data set conforming to numerous 2D frames one behind the other. The volume accession can be done in a stationary 3D, either online 4D (direct volume scan, live 3D ultrasound or a so-called 4D (3D/ 4D)), or either spatiotemporal image correlation-STIC (off-line 4D, which is a circular volume check-up). Fetal cardiovascular MRI would appear to be an ideal approach to the noninvasive disquisition of the impact of abnormal cardiovascular hemodynamics on antenatal brain growth and development. Still, there are practical limitations to the use of conventional MRI for fetal cardiovascular assessment, including the small size and high heart rate of the mortal fetus, the lack of conventional cardiac gating styles to attend data accession, and the implicit corruption of MRI data due to motherly respiration and unpredictable fetal movements. Fetal cardiac MRI has the implicit to complement ultrasound in detecting cardiovascular deformations and extracardiac lesions. Fetal cardiac intervention (FCI), minimally invasive catheter interventions, is a new and evolving fashion that allows for in-utero treatment of a subset of severe forms of congenital heart deficiency. In special cases, it may be possible to modify the natural history of congenital heart disorders. It's entirely possible that future generations will ‘repair’ congenital heart deficiency in utero using nanotechnologies or remote computer-guided micro-robots that work in the cellular layer.

Keywords: fetal, cardiac MRI, ultrasound, 3D, 4D, heart disease, invasive, noninvasive, catheter

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Authors: A. P. Pashkov

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The number of environmental factors that adversely affect children's health is growing every year; their combination in each territory is different. The contribution of socio-economic factors to the health status of the younger generation is increasing. It is the child’s body that is most sensitive to changes in environmental conditions, responding to this with a deterioration in health. Over the past years, scientists have determined the influence of environmental factors and the incidence of children. Currently, there is a tendency to study regional characteristics of the interaction of a combination of environmental factors with the child's body. The aim of the work was to identify trends in the primary non-infectious morbidity of the children of the Altai Territory as a unique region that combines territories with different levels of environmental quality indicators, as well as to assess the effect of atmospheric air, drinking water and socio-economic indicators on the incidence of children in the region. An unfavorable tendency has been revealed in the region for incidence of such nosological groups as neoplasms, including malignant ones, diseases of the endocrine system, including obesity and thyroid disease, diseases of the circulatory system, digestive diseases, diseases of the genitourinary system, congenital anomalies, and respiratory diseases. Between some groups of diseases revealed a pattern of geographical distribution during mapping and a significant correlation. Some nosologies have a relationship with socio-economic indicators for an integrated assessment: circulatory system diseases, respiratory diseases (direct connection), endocrine system diseases, eating disorders, and metabolic disorders (feedback). The analysis of associations of the incidence of children with average annual concentrations of substances that pollute the air and drinking water showed the existence of reliable correlation in areas of critical and intense degree of environmental quality. This fact confirms that the population living in contaminated areas is subject to the negative influence of environmental factors, which immediately affects the health status of children. The results obtained indicate the need for a detailed assessment of the influence of environmental factors on the incidence of children in the regional aspect, the formation of a database, and the development of automated programs that can predict the incidence in each specific territory. This will increase the effectiveness, including economic of preventive measures.

Keywords: incidence of children, regional features, socio-economic factors, environmental factors

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Authors: Himanshu Sharma, Karthik Kumar, Harish Kumar

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The major problem in crop cultivation is the occurrence of multiple crop diseases. During the growth stage, timely identification of crop diseases is paramount to ensure the high yield of crops, lower production costs, and minimize pesticide usage. In most cases, crop diseases produce observable characteristics and symptoms. The Surveyors usually diagnose crop diseases when they walk through the fields. However, surveyor inspections tend to be biased and error-prone due to the nature of the monotonous task and the subjectivity of individuals. In addition, visual inspection of each leaf or plant is costly, time-consuming, and labour-intensive. Furthermore, the plant pathologists and experts who can often identify the disease within the plant according to their symptoms in early stages are not readily available in remote regions. Therefore, this study specifically addressed early detection of leaf scald, red rot, and eyespot types of diseases within sugarcane plants. The study proposes a computer vision-based approach using a convolutional neural network (CNN) for automatic identification of crop diseases. To facilitate this, firstly, images of sugarcane diseases were taken from google without modifying the scene, background, or controlling the illumination to build the training dataset. Then, the testing dataset was developed based on the real-time collected images from the sugarcane field from India. Then, the image dataset is pre-processed for feature extraction and selection. Finally, the CNN-based Visual Geometry Group (VGG) model was deployed on the training and testing dataset to classify the images into diseased and healthy sugarcane plants and measure the model's performance using various parameters, i.e., accuracy, sensitivity, specificity, and F1-score. The promising result of the proposed model lays the groundwork for the automatic early detection of sugarcane disease. The proposed research directly sustains an increase in crop yield.

Keywords: automatic classification, computer vision, convolutional neural network, image processing, sugarcane disease, visual geometry group

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Authors: Praveen S. Muthukumarana, Achala C. Aponso

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A large percentage of global crop harvest is lost due to crop diseases. Timely identification and treatment of crop diseases is difficult in many developing nations due to insufficient trained professionals in the field of agriculture. Many crop diseases can be accurately diagnosed by visual symptoms. In the past decade, deep learning has been successfully utilized in domains such as healthcare but adoption in agriculture for plant disease detection is rare. The literature shows that models trained with popular datasets such as PlantVillage does not generalize well on real world images. This paper attempts to find out how to make plant disease identification models that generalize well with real world images.

Keywords: agriculture, convolutional neural network, deep learning, plant disease classification, plant disease detection, plant disease diagnosis

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Authors: Obinna Afamefuna Echi

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Background: The global increase in the elderly population is anticipated to reach significant levels by 2050, presenting extensive economic, social, and healthcare challenges. Age-related cognitive decline, alterations in brain anatomy, and systemic inflammation are profound concerns that diminish the quality of life and increase susceptibility to diseases like Alzheimer's and cardiovascular diseases. Resistance training is presently studied for its potential neuroprotective and anti-inflammatory benefits in older adults. Objectives: This study aimed to explore the effects of different resistance training modalities on neurotrophic factors, inflammatory markers, and cognitive functions in the elderly. Methods: A controlled trial was conducted with 60 male participants aged 60-75, assigned to either 12 weeks of high-intensity blood flow restriction training (BFRT), muscle damaging resistance training (MDRT), or a non-exercising control group. Cognitive function, neurotrophic factors such as BDNF, and inflammatory markers including IL-6 and TNF were measured before and after the intervention period. Setting: Participants were recruited from Kaunas, Lithuania, with sessions facilitated at the Lithuanian Sports University and health assessments conducted at the Lithuanian University of Health Sciences. Results: Preliminary data suggested did not show significant improvements in BDNF levels and cognitive functions in the BFRT and MDRT groups compared to controls. However, there was a notable reduction in inflammatory markers, indicating potential health benefits beyond cognitive enhancement. Conclusion: The incorporation of resistance training can be a strategic intervention to mitigate age-associated cognitive decline and systemic inflammation, thereby enhancing overall health and quality of life in older adults. The results advocate for wider adoption and further study of resistance training as a preventive measure in ageing populations. Funding: The Lithuanian Sports University, the Research Council of Lithuania and the Lithuanian University of Health Sciences.

Keywords: ageing, resistance training, BDNF, cognitive function

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Authors: Oya Bulut, Oguzhan Avci, Zafer Bulut, Atilla Simsek

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Livestock breeders have focused on the improvement of production traits with little or no attention for improvement of disease resistance traits. In order to determine the association between the genetic structure of the individual gene loci with possibility of the occurrence and the development of diseases, MHC (major histocompatibility complex) are frequently used. Because of their importance in the immune system, MHC locus is considered as candidate genes for resistance/susceptibility against to different diseases. Major histocompatibility complex (MHC) molecules play a critical role in both innate and adaptive immunity and have been considered candidate molecular markers of an association between polymorphisms and resistance/susceptibility to diseases. The purpose of this study is to give some information about MHC genes become an important area of study in recent years in terms of animal husbandry and determine the relation between MHC genes and resistance/susceptibility to disease.

Keywords: MHC, polymorphism, disease, resistance

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Authors: D. Motlhanka, M. Mine, T. Bagaketse, T. Ngakane

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There is a plethora of evidence from numerous sources that highlights the triumph of naturally derived medicinal plant metabolites with antioxidant capability for repurposed therapeutics. As post-COVID-19 syndromes and non-communicable diseases are on the rise, there is an urgent need to come up with new therapeutic strategies to address the problem. Non-communicable diseases and Post COVID-19 syndromes are classified as socio-economic diseases and are ranked high among threats to health security due to the economic burden they pose to any government budget commitment. Research has shown a strong link between accumulation of free radicals and oxidative stress critical for pathogenesis of non-communicable diseases and COVID-19 syndromes. Botswana has embarked on a robust programme derived from ethno-pharmacognosy and drug repurposing to address these threats to health security. In the current approach, a number of medicinally active plant-derived polyphenolics are repurposed and combined into new medicinal tools to target diabetes, Hypertension, Prostate Cancer and oxidative stress induced Post COVID 19 syndromes such as “brain fog”. All four formulants demonstrated Free Radical scavenging capacities above 95% at 200µg/ml using the diphenylpicryalhydrazyl free radical scavenging assay and the total phenolic contents between 6899-15000GAE(g/L) using the folin-ciocalteau assay respectively. These repurposed medicinal tools offer new hope and potential in the fight against emerging health threats driven by hyper-inflammation and free radical-induced oxidative stress.

Keywords: drug repurposed plant polyphenolics, free radical damage, non-communicable diseases, post COVID 19 syndromes

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Authors: Soumaya Mrabet, Taieb Ach, Imen Akkari, Amira Atig, Neirouz Ghannouchi, Koussay Ach, Elhem Ben Jazia

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Introduction: Celiac disease (CD) is an immune-mediated small intestinal disorder that occurs in genetically susceptible people. It is significantly associated with other autoimmune disorders represented mainly by type 1 diabetes and autoimmune dysthyroidism. The aim of our study is to determine the prevalence and the type of the various autoimmune diseases associated with CD in adult patients. Material and methods: This is a retrospective study including patients diagnosed with CD, explored in Internal Medicine, Gastroenterology and Endocrinology and Diabetology Departments of the Farhat Hached University Hospital, between January 2005 and January 2016. The diagnosis of CD was confirmed by serological tests and duodenal biopsy. The screening of autoimmune diseases was based on physical examination, biological and serological tests. Results: Sixty five patients with a female predominance were included, 48women (73.8%) and 17 men (26.2%). The mean age was 31.8 years (17-75). A family history of CD or other autoimmune diseases was present in 5 and 10 patients respectively. Clinical presentation of CD was made by recurrent abdominal pain in 49 cases, diarrhea in 29 cases, bloating in 17 cases, constipation in 25 cases and vomiting in 8 cases. Autoimmune diseases associated with CD were found in 30 cases (46.1%): type 1 diabetes in 15 patients attested by the positivity of anti-GAD antibodies in 11 cases and anti-IA2 in 4 cases, Hashimoto thyroiditis in 8 cases confirmed by the positivity of anti-TPO antibodies, Addison's disease in 2 patients, Anemia of Biermer in 2 patients, autoimmune hepatitis, Systemic erythematosus lupus, Gougerot Sjögren syndrome, rheumatoid arthritis, Vitiligo and antiphospholipid syndrome in one patient each. CD was associated with more than one autoimmune disease defining multiple autoimmune syndrome in 2 female patients. The first patient had Basedow disease, Addison disease and type 1 diabetes. The second patient had systemic erythematosus lupus and Gougerot Sjögren syndrome. Conclusion: In our study autoimmune diseases were associated with CD in 46.1% of cases and were dominated by diabetes and dysthroidism. After establishing the diagnosis of CD the search of associated autoimmune diseases is necessary in order to avoid any therapeutic delay which can alter the prognosis of the patient.

Keywords: association, autoimmune thyroiditis, celiac disease, diabetes

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Authors: Mohamed Z. Sayed-Ahmed, Ahmed M. Ahdy, Emad E. Younis, Sabry A. El-Khodary

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Little research information is available on the prevalence of diseases of donkeys in Egypt. Across sectional study was undertaken between March 2009 and February 2010 to verify the prevalence of skin affection of donkeys. A total of 1134 donkeys in northern Egypt were investigated. A questionnaire was constructed to verify the number of infected contact animals as well as the associated factors. Physical examination was carried out, and the distribution of skin lesions was recorded. Skin scraping and biopsy were obtained to perform bacteriological, mycological, and histopathological examinations. Thirty-five (3.09%) out of 1134 noticed donkeys had skin affections including mange (18/35), dermatophytosis (6/35), bacterial dermatitis (6/35) urticaria (2/35) and allergic dermatitis (3/35). The present results indicate that mange and dermatophytosis are the prevalent skin diseases in donkeys. Contact with other animal species of contaminated environment may contribute to the occurrence of the diseases.

Keywords: donkeys, Egypt, prevalence, skin affection

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Authors: Daudi S. Simbeye, Mbazingwa E. Mkiramweni

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Plant diseases have the potential to drastically diminish the quantity and quality of agricultural products. Guava (Psidium guajava), sometimes known as the apple of the tropics, is one of the most widely cultivated fruits in tropical regions. Monitoring plant health and diagnosing illnesses is an essential matter for sustainable agriculture, requiring the inspection of visually evident patterns on plant leaves and fruits. Due to minor variations in the symptoms of various guava illnesses, a professional opinion is required for disease diagnosis. Due to improper pesticide application by farmers, erroneous diagnoses may result in economic losses. This study proposes a method that uses artificial intelligence (AI) to detect and classify the most widespread guava plant by comparing images of its leaves and fruits to datasets. ESP32 CAM is responsible for data collection, which includes images of guava leaves and fruits. By comparing the datasets, these image formats are used as datasets to help in the diagnosis of plant diseases through the leaves and fruits, which is vital for the development of an effective automated agricultural system. The system test yielded the most accurate identification findings (99 percent accuracy in differentiating four guava fruit diseases (Canker, Mummification, Dot, and Rust) from healthy fruit). The proposed model has been interfaced with a mobile application to be used by smartphones to make a quick and responsible judgment, which can help the farmers instantly detect and prevent future production losses by enabling them to take precautions beforehand.

Keywords: early identification, guava plants, fruit diseases, deep learning

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Authors: Juan Francisco Morales Arteaga, Simon Gluhar, Anela Kaurin, Domen Lestan

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Contaminated soils are recognized as one of the most pressing global environmental problems. As is one of the most hazardous elements: chronic exposure to arsenic has devastating effects on health, cardiovascular diseases, cancer, and eventually death. Pb, Zn and Cd are very highly toxic metals that affect almost every organ in the body. With this in mind, new technologies for soil remediation processes are urgently needed. Calcareous artificially contaminated soil containing 231 mg kg-1 As and historically contaminated with Pb, Zn and Cd was washed with a 1:1.5 solid-liquid ratio of 90 mM EDTA, 100 mM oxalic acid, and 50 mM sodium dithionite to remove 59, 75, 29, and 53% of As, Pb, Zn, and Cd, respectively. To reduce emissions of residual EDTA and chelated metals from the remediated soil, zero valent iron (ZVI) was added (1% w/w) to the slurry of the washed soil immediately prior to rinsing. Experimental controls were conducted without the addition of ZVI after remediation. The use of ZVI reduced metal leachability and minimized toxic emissions 21 days after remediation. After this time, NH4NO3 extraction was performed to determine the mobility of toxic elements in the soil. In addition, Unified Human BioaccessibilityMethod (UBM) was performed to quantify the bioaccessibility levels of metals in stimulated human gastric and gastrointestinal phases.

Keywords: soil remediation, soil science, soil washing, toxic metals removal

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Authors: Albert P. Ekanem, Austin I. Obiekezie, Elizabeth X. Ntia

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Introduction: Some African plants and bile from animals have shown efficacies in the treatment and control of diseases in farmed fish. The background of the study is based on the fact the African rain forest is blessed with abundance of medicinal plants that should be investigated for their use in the treatment of diseases. The significance of the study is informed by the fact that chemical-based substances accumulates in the tissues of food fish, thereby reducing the food values of such products and moreover, the continuous use of chemotherapeutants in the aquatic environments tends to degrades the affected environment. Methodology: Plants and animal products were extracted, purified and applied under in vitro and in vivo conditions to the affected organisms. Effective plants and biles were analyzed for active biological substances responsible for the activities by both qualitative and HPLC methods. Results: Extracts of Carica papaya and Mucuna pruriens were effective in the treatment of Ichthyophthiriasis in goldfish (Carassius auratus auratus) with high host tolerance. Similarly, ectoparasitic monogeneans were effectively dislodged from the gills and skin of goldfish by the application of extracts of Piper guineense at therapeutic concentrations. Artemesia annua with known antimalarial activities in human was also effective against fish monogenean parasites of Clarias gariepinus in a concentration related manner without detriments to the host. Effective antibacterial activities against Aeromonas and Pseudomonas diseases of the African catfish (Heterobranchus longifilis) were demonstrated in some plants such as Phylanthus amarus, Allium sativum, A. annua, and Citrus lemon. Bile from some animals (fish, goat, chicken, cow, and pig) showed great antibacterial activities against some gastrointestinal bacterial pathogens of fish. Conclusions: African plants and some animal bile have shown potential promise in the treatment of diseases in fish and other aquatic animals. The use of chemical-based substances for control of diseases in the aquatic environments should be restricted.

Keywords: control, diseases, fish, natural products, treatment

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Authors: Jacqueline Rose T. Alipo-on, Francesca Isabelle F. Escobar, Myles Joshua T. Tan, Hezerul Abdul Karim, Nouar Al Dahoul

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Electrocardiogram (ECG) signal analysis and processing are crucial in the diagnosis of cardiovascular diseases, which are considered one of the leading causes of mortality worldwide. However, the traditional rule-based analysis of large volumes of ECG data is time-consuming, labor-intensive, and prone to human errors. With the advancement of the programming paradigm, algorithms such as machine learning have been increasingly used to perform an analysis of ECG signals. In this paper, various deep learning algorithms were adapted to classify five classes of heartbeat types. The dataset used in this work is the synthetic MIT-BIH Arrhythmia dataset produced from generative adversarial networks (GANs). Various deep learning models such as ResNet-50 convolutional neural network (CNN), 1-D CNN, and long short-term memory (LSTM) were evaluated and compared. ResNet-50 was found to outperform other models in terms of recall and F1 score using a five-fold average score of 98.88% and 98.87%, respectively. 1-D CNN, on the other hand, was found to have the highest average precision of 98.93%.

Keywords: heartbeat classification, convolutional neural network, electrocardiogram signals, generative adversarial networks, long short-term memory, ResNet-50

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Authors: Pedro Llanos, Diego García

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Spaceflight is considered the last frontier in terms of science, technology, and engineering. But it is also the next frontier in terms of human physiology and performance. After more than 200,000 years humans have evolved under earth’s gravity and atmospheric conditions, spaceflight poses environmental stresses for which human physiology is not adapted. Hypoxia, accelerations, and radiation are among such stressors, our research involves suborbital flights aiming to develop effective countermeasures in order to assure sustainable human space presence. The physiologic baseline of spaceflight participants is subject to great variability driven by age, gender, fitness, and metabolic reserve. The objective of the present study is to characterize different physiologic variables in a population of STEM practitioners during an aerobatic flight. Cardiovascular and pulmonary responses were determined in Science Astronaut Candidates (SACs) during unusual attitude aerobatic flight indoctrination. Physiologic data recordings from 20 subjects participating in high-G flight training were analyzed. These recordings were registered by wearable sensor-vest that monitored electrocardiographic tracings (ECGs), signs of dysrhythmias or other electric disturbances during all the flight. The same cardiovascular parameters were also collected approximately 10 min pre-flight, during each high-G/unusual attitude maneuver and 10 min after the flights. The ratio (pre-flight/in-flight/post-flight) of the cardiovascular responses was calculated for comparison of inter-individual differences. The resulting tracings depicting the cardiovascular responses of the subjects were compared against the G-loads (Gs) during the aerobatic flights to analyze cardiovascular variability aspects and fluid/pressure shifts due to the high Gs. In-flight ECG revealed cardiac variability patterns associated with rapid Gs onset in terms of reduced heart rate (HR) and some scattered dysrhythmic patterns (15% premature ventricular contractions-type) that were considered as triggered physiological responses to high-G/unusual attitude training and some were considered as instrument artifact. Variation events were observed in subjects during the +Gz and –Gz maneuvers and these may be due to preload and afterload, sudden shift. Our data reveal that aerobatic flight influenced the breathing rate of the subject, due in part by the various levels of energy expenditure due to the increased use of muscle work during these aerobatic maneuvers. Noteworthy was the high heterogeneity in the different physiological responses among a relatively small group of SACs exposed to similar aerobatic flights with similar Gs exposures. The cardiovascular responses clearly demonstrated that SACs were subjected to significant flight stress. Routine ECG monitoring during high-G/unusual attitude flight training is recommended to capture pathology underlying dangerous dysrhythmias in suborbital flight safety. More research is currently being conducted to further facilitate the development of robust medical screening, medical risk assessment approaches, and suborbital flight training in the context of the evolving commercial human suborbital spaceflight industry. A more mature and integrative medical assessment method is required to understand the physiology state and response variability among highly diverse populations of prospective suborbital flight participants.

Keywords: g force, aerobatic maneuvers, suborbital flight, hypoxia, commercial astronauts

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Authors: Yong Zhao, Jian He, Cheng Zhang

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Cardiovascular diseases caused by hypertension are extremely threatening to human health, and early diagnosis of hypertension can save a large number of lives. Traditional hypertension detection methods require special equipment and are difficult to detect continuous blood pressure changes. In this regard, this paper first analyzes the principle of heart rate variability (HRV) and introduces sliding window and power spectral density (PSD) to analyze the time domain features and frequency domain features of HRV, and secondly, designs an HRV-based hypertension prediction network by combining Resnet, attention mechanism, and multilayer perceptron, which extracts the frequency domain through the improved ResNet18 features through a modified ResNet18, its fusion with time-domain features through an attention mechanism, and the auxiliary prediction of hypertension through a multilayer perceptron. Finally, the network was trained and tested using the publicly available SHAREE dataset on PhysioNet, and the test results showed that this network achieved 92.06% prediction accuracy for hypertension and outperformed K Near Neighbor(KNN), Bayes, Logistic, and traditional Convolutional Neural Network(CNN) models in prediction performance.

Keywords: feature extraction, heart rate variability, hypertension, residual networks

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Authors: A. Badran, M. Hollocks, H. Markus

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Background: Common risk factors for cardiovascular disease are associated with age-related cognitive decline. There has been much interest in treating modifiable cardiovascular risk factors in the hope of reducing cognitive decline. However, there is currently no validated neuropsychological test to assess the subclinical cognitive effects of vascular risk. The Brief Memory and Executive Test (BMET) is a clinical screening tool, which was originally designed to be sensitive and specific to Vascular Cognitive Impairment (VCI), an impairment characterised by decline in frontally-mediated cognitive functions (e.g. Executive Function and Processing Speed). Objective: To cross-sectionally assess the validity of the BMET as a measure of the subclinical effects of vascular risk on cognition, in an otherwise healthy elderly cohort. Methods: Data from 346 participants (57 ± 10 years) without major neurological or psychiatric disorders were included in this study, gathered as part of a previous multicentre validation study for the BMET. Framingham Vascular Age was used as a surrogate measure of vascular risk, incorporating several established risk factors. Principal Components Analysis of the subtests was used to produce common constructs: an index for Memory and another for Executive Function/Processing Speed. Univariate General Linear models were used to relate Vascular Age to performance on Executive Function/Processing Speed and Memory subtests of the BMET, adjusting for Age, Premorbid Intelligence and Ethnicity. Results: Adverse vascular risk was associated with poorer performance on both the Memory and Executive Function/Processing Speed indices, adjusted for Age, Premorbid Intelligence and Ethnicity (p=0.011 and p<0.001, respectively). Conclusions: Performance on the BMET reflects the subclinical effects of vascular risk on cognition, in age-related cognitive decline. Vascular risk is associated with decline in both Executive Function/Processing Speed and Memory groups of subtests. Future studies are needed to explore whether treating vascular risk factors can effectively reduce age-related cognitive decline.

Keywords: age-related cognitive decline, vascular cognitive impairment, subclinical cerebrovascular disease, cognitive aging

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Authors: Deepak Jugran

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The last century has witnessed rapid scientific growth, and social policies mainly targeted to increase the “life expectancy” of the people. As a result of these developments, the aging as well as ailing population, is increasing by every day. Despite an increase in “life expectancy”, we have not recorded compression in morbidity numbers as the age of onset of the majority of health issues has not increased substantially. In recent years, the prevalence of chronic diseases along with the improved treatment has also resulted in the increase of people living with chronic diseases. The last decade has also focused on social policies to increase the life expectancy in the population; however, in recent decades, social policies and biomedical research are gradually shifting on the potential of increasing healthy life or healthspan. In this article, we review the existing framework of lifespan and healthspan and wish to ignite a discussion among social scientists and public health experts to propose a wholistic framework to balance the trade-offs on social policies for “lifespan” and “healthspan”.

Keywords: lifespan, healthspan, chronic diseases, social policies

Procedia PDF Downloads 107