Abstract: In both developed and developing countries, obesity among women is increasing, but in different patterns and at very different speeds. It may have a negative effect on health, leading to reduced life expectancy and/or increased health problems. This research studied the age distribution among obese women, the types of overweight and obesity, and the extent of the problem of overweight/obesity and the obesity etiological factors among women in Hillah city in central Iraq. A total of 322 overweight and obese women were included in the study, those women were randomly selected. The Body Mass Index was used as indicator for overweight/ obesity. The incidence of overweight/obesity among age groups were estimated, the etiology factors included genetic, environmental, genetic/environmental and endocrine disease. The overweight and obese women were screened for incidence of infection and/or diseases. The study found that the prevalence of 322 overweight and obese women in Hillah city in central Iraq was 19.25% and 80.78%, respectively. The obese women types were recorded based on BMI and WHO classification as class-1 obesity (29.81%), class-2 obesity (24.22%) and class-3 obesity (26.70%), the result was discrepancy non-significant, P value < 0.05. The incidence of overweight in women was high among those aged 20-29 years (90.32%), 6.45% aged 30-39 years old and 3.22% among ≥ 60 years old, while the incidence of obesity was 20.38% for those in the age group 20-29 years, 17.30% were 30-39 years, 23.84% were 40-49 years, 16.92% were 50-59 years group and 21.53% were ≥ 60 years age group. These results confirm that the age can be considered as a significant factor for obesity types (P value < 0.0001). The result also showed that the both genetic factors and environmental factors were responsible for incidents of overweight or obesity (84.78%) p value < 0.0001. The results also recorded cases of different repeated infections (skin infection, recurrent UTI and influenza), cancer, gallstones, high blood pressure, type 2 diabetes, and infertility. Weight stigma and bias generally refers to negative attitudes; Obesity can affect quality of life, and the results of this study recorded depression among overweight or obese women. This can lead to sexual problems, shame and guilt, social isolation and reduced work performance. Overweight and Obesity are real problems among women of all age groups and is associated with the risk of diseases and infection and negatively affects quality of life. This result warrants further studies into the prevalence of obesity among women in Hillah City in central Iraq and the immune response of obese women.
Abstract: Retinoblastoma is a rare type of childhood genetic cancer that affects children worldwide. The diagnosis is often missed due to lack of education and difficulty in presentation of the tumor. Frequently, the tumor on the retina is noticed by photography when the red-eye flash, commonly seen in normal eyes, is not produced. Instead, a yellow or white colored patch is seen or the child has a noticeable strabismus. Early detection can be life-saving though often results in removal of the affected eye. Remaining functioning in the healthy eye when the child is young has resulted in super-vision and high or above-average intelligence. Technological advancement of cameras has helped in early detection. Brain imaging has also made possible early detection of neurological diseases and, together with the monitoring of cortisol levels and yawning frequency, promises to be the next new early diagnostic tool for the detection of neurological diseases where cortisol insufficiency is particularly salient, such as multiple sclerosis and Cushing’s disease.
Abstract: This research paper presents a framework for classifying Magnetic Resonance Imaging (MRI) images for Dementia. Dementia, an age-related cognitive decline is indicated by degeneration of cortical and sub-cortical structures. Characterizing morphological changes helps understand disease development and contributes to early prediction and prevention of the disease. Modelling, that captures the brain’s structural variability and which is valid in disease classification and interpretation is very challenging. Features are extracted using Gabor filter with 0, 30, 60, 90 orientations and Gray Level Co-occurrence Matrix (GLCM). It is proposed to normalize and fuse the features. Independent Component Analysis (ICA) selects features. Support Vector Machine (SVM) classifier with different kernels is evaluated, for efficiency to classify dementia. This study evaluates the presented framework using MRI images from OASIS dataset for identifying dementia. Results showed that the proposed feature fusion classifier achieves higher classification accuracy.
Abstract: In recent years, there has been an explosion in the rate of using technology that help discovering the diseases. For example, DNA microarrays allow us for the first time to obtain a "global" view of the cell. It has great potential to provide accurate medical diagnosis, to help in finding the right treatment and cure for many diseases. Various classification algorithms can be applied on such micro-array datasets to devise methods that can predict the occurrence of Leukemia disease. In this study, we compared the classification accuracy and response time among eleven decision tree methods and six rule classifier methods using five performance criteria. The experiment results show that the performance of Random Tree is producing better result. Also it takes lowest time to build model in tree classifier. The classification rules algorithms such as nearest- neighbor-like algorithm (NNge) is the best algorithm due to the high accuracy and it takes lowest time to build model in classification.
Abstract: HIV and Tuberculosis (TB) infections each speed the other's progress. HIV-infection increases the risk of TB disease. At the same time, TB infection is associated with clinical progression of HIV-infection. HIV+TB co-infected patients are also at higher risk of acquiring new opportunistic infections. An important feature of disease progression and clinical outcome is the innate and acquired immune responses. HIV and TB, however, have a spectrum of dysfunctions of the immune response. As cytokines play a crucial role in the immunopathology of both infections, it is important to study immune interactions in patients with dual infection HIV+TB. Plasma levels of proinflammatory cytokines IL-2, IFN-γ and immunoregulating cytokines IL-4, IL-10 were evaluated in 75 patients with dual infection HIV+TB, 58 patients with HIV monoinfection and 50 patients with TB monoinfection who were previously naïve for HAART. The decreased levels of IL-2, IFN-γ, IL-4 and IL-10 were observed in patients with dual infection HIV+TB in comparison with patients who had only HIV or TB which means the profound suppression of Th1 and Th2 cytokine secretion. Thus, those cytokines could possibly serve as immunological markers of progression of HIV-infection in patients with TB.
Abstract: Oil palm or Elaeis guineensis is considered as the golden crop in Malaysia. But oil palm industry in this country is now facing with the most devastating disease called as Ganoderma Basal Stem Rot disease. The objective of this paper is to analyze the economic loss due to this disease. There were three commercial oil palm sites selected for collecting the required data for economic analysis. Yield parameter used to measure the loss was the total weight of fresh fruit bunch in six months. The predictors include disease severity, change in disease severity, number of infected neighbor palms, age of palm, planting generation, topography, and first order interaction variables. The estimation model of yield loss was identified by using backward elimination based regression method. Diagnostic checking was conducted on the residual of the best yield loss model. The value of mean absolute percentage error (MAPE) was used to measure the forecast performance of the model. The best yield loss model was then used to estimate the economic loss by using the current monthly price of fresh fruit bunch at mill gate.
Abstract: Dietary cholesterol has elicited the most public
interest as it relates with coronary heart disease. Thus, humans have
been paying more attention to health, thereby reducing consumption
of cholesterol enriched food. Egg is considered as one of the major
sources of human dietary cholesterol. However, an alternative way to
reduce the potential cholesterolemic effect of eggs is to modify the
fatty acid composition of the yolk. The effect of palm oil (PO),
soybean oil (SO), sesame seed oil (SSO) and fish oil (FO)
supplementation in the diets of layers on egg yolk fatty acid,
cholesterol, egg production and egg quality parameters were
evaluated in a 42-day feeding trial. One hundred and five Isa Brown
laying hens of 34 weeks of age were randomly distributed into seven
groups of five replicates and three birds per replicate in a completely
randomized design. Seven corn-soybean basal diets (BD) were
formulated: BD+No oil (T1), BD+1.5% PO (T2), BD+1.5% SO (T3),
BD+1.5% SSO (T4), BD+1.5% FO (T5), BD+0.75% SO+0.75% FO
(T6) and BD+0.75% SSO+0.75% FO (T7). Five eggs were randomly
sampled at day 42 from each replicate to assay for the cholesterol,
fatty acid profile of egg yolk and egg quality assessment. Results
showed that there were no significant (P>0.05) differences observed
in production performance, egg cholesterol and egg quality
parameters except for yolk height, albumen height, yolk index, egg
shape index, haugh unit, and yolk colour. There were no significant
differences (P>0.05) observed in total cholesterol, high density
lipoprotein and low density lipoprotein levels of egg yolk across the
treatments. However, diets had effect (P
Abstract: Segmentation of left ventricle (LV) from cardiac
ultrasound images provides a quantitative functional analysis of the
heart to diagnose disease. Active Shape Model (ASM) is widely used
for LV segmentation, but it suffers from the drawback that
initialization of the shape model is not sufficiently close to the target,
especially when dealing with abnormal shapes in disease. In this work,
a two-step framework is improved to achieve a fast and efficient LV
segmentation. First, a robust and efficient detection based on Hough
forest localizes cardiac feature points. Such feature points are used to
predict the initial fitting of the LV shape model. Second, ASM is
applied to further fit the LV shape model to the cardiac ultrasound
image. With the robust initialization, ASM is able to achieve more
accurate segmentation. The performance of the proposed method is
evaluated on a dataset of 810 cardiac ultrasound images that are mostly
abnormal shapes. This proposed method is compared with several
combinations of ASM and existing initialization methods. Our
experiment results demonstrate that accuracy of the proposed method
for feature point detection for initialization was 40% higher than the
existing methods. Moreover, the proposed method significantly
reduces the number of necessary ASM fitting loops and thus speeds up
the whole segmentation process. Therefore, the proposed method is
able to achieve more accurate and efficient segmentation results and is
applicable to unusual shapes of heart with cardiac diseases, such as left
atrial enlargement.
Abstract: The nutritional composition and hypoglycaemic effect
of crackers produced from blend of sprouted pigeon pea, unripe
plantain and brewers’ spent grain and fed to Alloxan induced diabetic
rat was investigated. Crackers were produced from different blends of
sprouted pigeon pea, unripe plantain and brewers’ spent grain. The
crackers were evaluated for proximate composition, amino acid
profile and antinutritional factors. Blood glucose levels of normal and
diabetic rats fed with the control sample and different formulations of
cracker were measured. The protein content of the samples were
significantly different (p
Abstract: Leishmaniasis is the collective name for a number of
diseases caused by protozoan flagellates of the genus Leishmania,
which is transmitted by Phlebotomine sandfly, the disease has diverse
clinical manifestations and found in many areas of the world,
particularly in Africa, Latin America, South and Central Asia, the
Mediterranean basin and the Middle East. This study was done to
assess primary health care physicians’ knowledge (PHP) and attitude
about leishmaniasis and to assess awareness of local inhabitants
about the disease and its vector in four areas in west Alexandria,
Egypt. It is a cross sectional survey that was conducted in four PHC
units in west Alexandria. All physicians currently working in these
units during the study period were invited to participate in the study;
only 20 PHP completed the questionnaire. 60 local inhabitants were
selected randomly from the four areas of the study, 15 from each
area; Data was collected through two different specially designed
questionnaires. Results showed that 11 (55%) percent of the
physicians had satisfactory knowledge; they answered more than 9
(60%) questions out of a total 14 questions about leishmaniasis and
sandfly. On the other hand when attitude of the primary health care
physicians about leishmaniasis was measured, results showed that 17
(85%) had good attitude and 3 (15%) had poor attitude. The second
questionnaire showed that the awareness of local inhabitants about
leishmaniasis and sandfly as a vector of the disease is poor and needs
to be corrected. (90%) of the interviewed inhabitants had not heard
about leishmaniasis, Only 3 (5%) of them said they know sandfly and
its role in transmission of leishmaniasis. Thus we conclude that
knowledge and attitudes of physicians are acceptable. However, there
is, room for improvement and could be done through formal training
courses and distribution of guidelines. In addition to raising the
awareness of primary health care physicians about the importance of
early detection and notification of cases of leishmaniasis, health
education for raising awareness of the public regarding the vector and
the disease is necessary because related studies have demonstrated
that for inhabitants to take enough protective measures against the
vector, they should perceive that it is responsible for causing a
disease.
Abstract: Phonocardiography is important in appraisal of
congenital heart disease and pulmonary hypertension as it reflects the
duration of right ventricular systoles. The systolic murmur in patients
with intra-cardiac shunt decreases as pulmonary hypertension
develops and may eventually disappear completely as the pulmonary
pressure reaches systemic level. Phonocardiography and auscultation
are non-invasive, low-cost, and accurate methods to assess heart
disease. In this work an objective signal processing tool to extract
information from phonocardiography signal using Wavelet is
proposed to classify the murmur as normal or abnormal. Since the
feature vector is large, a Binary Particle Swarm Optimization (PSO)
with mutation for feature selection is proposed. The extracted
features improve the classification accuracy and were tested across
various classifiers including Naïve Bayes, kNN, C4.5, and SVM.
Abstract: The goal of this paper is to present the diagnostic
contribution that the screening instrument, Mini-Mental State
Examination-2: Expanded Version (MMSE-2:EV), brings in
detecting the cognitive impairment or in monitoring the progress of
degenerative disorders. The diagnostic signification is underlined by
the interpretation of the MMSE-2:EV scores, resulted from the test
application to patients with mild and major neurocognitive disorders.
The cases were selected from current practice, in order to cover vast
and significant neurocognitive pathology: mild cognitive impairment,
Alzheimer’s disease, vascular dementia, mixed dementia, Parkinson’s
disease, conversion of the mild cognitive impairment into
Alzheimer’s disease. The MMSE-2:EV version was used: it was
applied one month after the initial assessment, three months after the
first reevaluation and then every six months, alternating the blue and
red forms. Correlated with age and educational level, the raw scores
were converted in T scores and then, with the mean and the standard
deviation, the z scores were calculated. The differences of raw scores
between the evaluations were analyzed from the point of view of
statistic signification, in order to establish the progression in time of
the disease. The results indicated that the psycho-diagnostic approach
for the evaluation of the cognitive impairment with MMSE-2:EV is
safe and the application interval is optimal. In clinical settings with a
large flux of patients, the application of the MMSE-2:EV is a safe
and fast psychodiagnostic solution. The clinicians can draw objective
decisions and for the patients: it does not take too much time and
energy, it does not bother them and it doesn’t force them to travel
frequently.
Abstract: In addition to environmental parameters like rain,
temperature diseases on crop is a major factor which affects
production quality & quantity of crop yield. Hence disease
management is a key issue in agriculture. For the management of
disease, it needs to be detected at early stage. So, treat it properly &
control spread of the disease. Now a day, it is possible to use the
images of diseased leaf to detect the type of disease by using image
processing techniques. This can be achieved by extracting features
from the images which can be further used with classification
algorithms or content based image retrieval systems. In this paper,
color image is used to extract the features such as mean and standard
deviation after the process of region cropping. The selected features
are taken from the cropped image with different image size samples.
Then, the extracted features are taken in to the account for
classification using Fuzzy Inference System (FIS).
Abstract: Availability of different genetic tests after completion
of Human Genome Project increases the physicians’ responsibility to
keep themselves update on the potential implementation of these
genetic tests in their daily practice. However, due to numbers of
barriers, still many of physicians are not either aware of these tests or
are not willing to offer or refer their patients for genetic tests. This
study was conducted an anonymous, cross-sectional, mailed-based
survey to develop a primary data of Malaysian physicians’ level of
knowledge and perception of gene profiling. Questionnaire had 29
questions. Total scores on selected questions were used to assess the
level of knowledge. The highest possible score was 11. Descriptive
statistics, one way ANOVA and chi-squared test was used for
statistical analysis. Sixty three completed questionnaires were
returned by 27 general practitioners (GPs) and 36 medical specialists.
Responders’ age ranges from 24 to 55 years old (mean 30.2 ± 6.4).
About 40% of the participants rated themselves as having poor level
of knowledge in genetics in general whilst 60% believed that they
have fair level of knowledge; however, almost half (46%) of the
respondents felt that they were not knowledgeable about available
genetic tests. A majority (94%) of the responders were not aware of
any lab or company which is offering gene profiling services in
Malaysia. Only 4% of participants were aware of using gene profiling
for detection of dosage of some drugs. Respondents perceived greater
utility of gene profiling for breast cancer (38%) compared to the
colorectal familial cancer (3%). The score of knowledge ranged from
2 to 8 (mean 4.38 ± 1.67). Non- significant differences between score
of knowledge of GPs and specialists were observed, with score of
4.19 and 4.58 respectively. There was no significant association
between any demographic factors and level of knowledge. However,
those who graduated between years 2001 to 2005 had higher level of
knowledge. Overall, 83% of participants showed relatively high level
of perception on value of gene profiling to detect patient’s risk of
disease. However, low perception was observed for both statements
of using gene profiling for general population in order to alter their
lifestyle (25%) as well as having the full sequence of a patient
genome for the purpose of determining a patient’s best match for
treatment (18%). The lack of clinical guidelines, limited provider
knowledge and awareness, lack of time and resources to educate
patients, lack of evidence-based clinical information and cost of tests
were the most barriers of ordering gene profiling mentioned by
physicians. In conclusion Malaysian physicians who participate in
this study had mediocre level of knowledge and awareness in gene
profiling. The low exposure to the genetic questions and problems
might be a key predictor of lack of awareness and knowledge on
available genetic tests. Educational and training workshop might be useful in helping Malaysian physicians incorporate genetic profiling
into practice for eligible patients.
Abstract: In medical investigations, uncertainty is a major
challenging problem in making decision for doctors/experts to
identify the diseases with a common set of symptoms and also has
been extensively increasing in medical diagnosis problems. The
theory of cross entropy for intuitionistic fuzzy sets (IFS) is an
effective approach in coping uncertainty in decision making for
medical diagnosis problem. The main focus of this paper is to
propose a new intuitionistic fuzzy cross entropy measure (IFCEM),
which aid in reducing the uncertainty and doctors/experts will take
their decision easily in context of patient’s disease. It is shown that
the proposed measure has some elegant properties, which
demonstrates its potency. Further, it is also exemplified in detail the
efficiency and utility of the proposed measure by using a real life
case study of diagnosis the disease in medical science.
Abstract: In this paper, we used data mining to extract
biomedical knowledge. In general, complex biomedical data
collected in studies of populations are treated by statistical methods,
although they are robust, they are not sufficient in themselves to
harness the potential wealth of data. For that you used in step two
learning algorithms: the Decision Trees and Support Vector Machine
(SVM). These supervised classification methods are used to make the
diagnosis of thyroid disease. In this context, we propose to promote
the study and use of symbolic data mining techniques.
Abstract: This paper proposes a rotational invariant texture
feature based on the roughness property of the image for psoriasis
image analysis. In this work, we have applied this feature for image
classification and segmentation. The fuzzy concept is employed to
overcome the imprecision of roughness. Since the psoriasis lesion is
modeled by a rough surface, the feature is extended for calculating
the Psoriasis Area Severity Index value. For classification and
segmentation, the Nearest Neighbor algorithm is applied. We have
obtained promising results for identifying affected lesions by using
the roughness index and severity level estimation.
Abstract: Analyzing DNA microarray data sets is a great
challenge, which faces the bioinformaticians due to the complication
of using statistical and machine learning techniques. The challenge
will be doubled if the microarray data sets contain missing data,
which happens regularly because these techniques cannot deal with
missing data. One of the most important data analysis process on
the microarray data set is feature selection. This process finds the
most important genes that affect certain disease. In this paper, we
introduce a technique for imputing the missing data in microarray
data sets while performing feature selection.
Abstract: The Roma (Gypsies) is a transnational minority with a
high degree of consanguineous marriages. Similar to other
genetically isolated founder populations, the Roma harbor a number
of unique or rare genetic disorders. This paper discusses about a rare
form of Charcot-Marie-Tooth disease – type 4G (CMT4G), also
called Hereditary Motor and Sensory Neuropathy type Russe, an
autosomal recessive disease caused by mutation private to Roma
characterized by abnormally increased density of non-myelinated
axons. CMT4G was originally found in Bulgarian Roma and in 2009
two putative causative mutations in the HK1 gene were identified.
Since then, several cases were reported in Roma families mainly
from Bulgaria and Spain. Here we present a Slovak Roma family in
which CMT4G was diagnosed on the basis of clinical examination
and genetic testing. This case is a further proof of the role of the HK1
gene in pathogenesis of the disease. It confirms that mutation in the
HK1 gene is a common cause of autosomal recessive CMT disease in
Roma and should be considered as a common part of a diagnostic
procedure.
Abstract: The inhibition of SH2 domain regulated protein-protein interactions is an attractive target for developing an effective chemotherapeutic approach in the treatment of disease. Molecular simulation is a useful tool for developing new drugs and for studying molecular recognition. In this study, we searched potential drug compounds for the inhibition of SH2 domain by performing structural similarity search in PubChem Compound Database. A total of 37 compounds were screened from the database, and then we used the LibDock docking program to evaluate the inhibition effect. The best three compounds (AP22408, CID 71463546 and CID 9917321) were chosen for MD simulations after the LibDock docking. Our results show that the compound CID 9917321 can produce a more stable protein-ligand complex compared to other two currently known inhibitors of Src SH2 domain. The compound CID 9917321 may be useful for the inhibition of SH2 domain based on these computational results. Subsequently experiments are needed to verify the effect of compound CID 9917321 on the SH2 domain in the future studies.