Abstract: Bay leaves have been shown to improve insulin
function in vitro but the effects on people have not been determined.
The objective of this study was to determine if bay leaves may be
important in the prevention and/or alleviation of type 1 diabetes.
Methods: Fifty five people with type 1 diabetes were divided into
two groups, 45 given capsules containing 3 g of bay leaves per day
for 30 days and 10 given a placebo capsules. Results All the patients
consumed bay leaves shows reduced serum glucose with significant
decreases 27% after 30 d. Total cholesterol decreased, 21 %, after 30
days with larger decreases in low density lipoprotein (LDL) 24%.
High density lipoprotein (HDL) increased 20% and Triglycerides
also decreased 26%. There were no significant changes in the
placebo group. Conclusion, this study demonstrates that consumption
of bay leaves, 3 g/d for 30 days, decreases risk factors for diabetes
and cardiovascular diseases and suggests that bay leaves may be
beneficial for people with type 1 diabetes.
Abstract: Until recently, researchers have developed various
tools and methodologies for effective clinical decision-making.
Among those decisions, chest pain diseases have been one of
important diagnostic issues especially in an emergency department. To
improve the ability of physicians in diagnosis, many researchers have
developed diagnosis intelligence by using machine learning and data
mining. However, most of the conventional methodologies have been
generally based on a single classifier for disease classification and
prediction, which shows moderate performance. This study utilizes an
ensemble strategy to combine multiple different classifiers to help
physicians diagnose chest pain diseases more accurately than ever.
Specifically the ensemble strategy is applied by using the integration
of decision trees, neural networks, and support vector machines. The
ensemble models are applied to real-world emergency data. This study
shows that the performance of the ensemble models is superior to each
of single classifiers.
Abstract: Mitochondria are dynamic organelles, capable to
interact with each other. While the number of mitochondria in a cell
varies, their quality and functionality depends on the operation of
fusion, fission, motility and mitophagy. Nowadays, several
researches declare as an important factor in neurogenerative diseases
the disruptions in the regulation of mitochondrial dynamics. In this
paper a stochastic model in BioAmbients calculus is presented,
concerning mitochondrial fusion and its distribution in the renewal of
mitochondrial population in a cell. This model describes the
successive and dependent stages of protein synthesis, protein-s
activation and merging of two independent mitochondria.
Abstract: The amount and heterogeneity of data in biomedical research, notably in interdisciplinary research, requires new methods for the collection, presentation and analysis of information. Important data from laboratory experiments as well as patient trials are available but come out of distributed resources. The Charite Medical School in Berlin has established together with the German Research Foundation (DFG) a new information service center for kidney diseases and transplantation (Open European Nephrology Science Centre - OpEN.SC). The system is based on a service-oriented architecture (SOA) with main and auxiliary modules arranged in four layers. To improve the reuse and efficient arrangement of the services the functionalities are described as business processes using the standardised Business Process Execution Language (BPEL).
Abstract: DNA microarray technology is widely used by
geneticists to diagnose or treat diseases through gene expression.
This technology is based on the hybridization of a tissue-s DNA
sequence into a substrate and the further analysis of the image
formed by the thousands of genes in the DNA as green, red or yellow
spots. The process of DNA microarray image analysis involves
finding the location of the spots and the quantification of the
expression level of these. In this paper, a tool to perform DNA
microarray image analysis is presented, including a spot addressing
method based on the image projections, the spot segmentation
through contour based segmentation and the extraction of relevant
information due to gene expression.
Abstract: The human knee joint has a three dimensional
geometry with multiple body articulations that produce complex
mechanical responses under loads that occur in everyday life and
sports activities. To produce the necessary joint compliance and
stability for optimal daily function various menisci and ligaments are
present while muscle forces are used to this effect. Therefore,
knowledge of the complex mechanical interactions of these load
bearing structures is necessary when treatment of relevant diseases is
evaluated and assisting devices are designed.
Numerical tools such as finite element analysis are suitable for
modeling such joints in order to understand their physics. They have
been used in the current study to develop an accurate human knee
joint and model its mechanical behavior. To evaluate the efficacy of
this articulated model, static load cases were used for comparison
purposes with previous experimentally verified modeling works
drawn from literature.
Abstract: This paper describes about the process of recognition and classification of brain images such as normal and abnormal based on PSO-SVM. Image Classification is becoming more important for medical diagnosis process. In medical area especially for diagnosis the abnormality of the patient is classified, which plays a great role for the doctors to diagnosis the patient according to the severeness of the diseases. In case of DICOM images it is very tough for optimal recognition and early detection of diseases. Our work focuses on recognition and classification of DICOM image based on collective approach of digital image processing. For optimal recognition and classification Particle Swarm Optimization (PSO), Genetic Algorithm (GA) and Support Vector Machine (SVM) are used. The collective approach by using PSO-SVM gives high approximation capability and much faster convergence.
Abstract: Application of Expert System in the area of agriculture would take the form of Integrated Crop Management decision aids and would encompass water management, fertilizer management, crop protection systems and identification of implements. In order to remain competitive, the modern farmer often relies on agricultural specialists and advisors to provide information for decision-making. An expert system normally composed of a knowledge base (information, heuristics, etc.), inference engine (analyzes knowledge base), and end user interface (accepting inputs, generating outputs). Software named 'CROP-9-DSS' incorporating all modern features like, graphics, photos, video clippings etc. has been developed. This package will aid as a decision support system for identification of pest and diseases with control measures, fertilizer recommendation system, water management system and identification of farm implements for leading crops of Kerala (India) namely Coconut, Rice, Cashew, Pepper, Banana, four vegetables like Amaranthus, Bhindi, Brinjal and Cucurbits. 'CROP-9-DSS' will act as an expert system to agricultural officers, scientists in the field of agriculture and extension workers for decision-making and help them in suggesting suitable recommendations.
Abstract: Diagnostic and detection of the arterial stiffness is
very important; which gives indication of the associated increased risk of cardiovascular diseases. To make a cheap and easy method for general screening technique to avoid the future cardiovascular
complexes , due to the rising of the arterial stiffness ; a proposed algorithm depending on photoplethysmogram to be used. The
photoplethysmograph signals would be processed in MATLAB. The
signal will be filtered, baseline wandering removed, peaks and
valleys detected and normalization of the signals should be achieved
.The area under the catacrotic phase of the photoplethysmogram
pulse curve is calculated using trapezoidal algorithm ; then will used
in cooperation with other parameters such as age, height, blood
pressure in neural network for arterial stiffness detection. The Neural
network were implemented with sensitivity of 80%, accuracy 85%
and specificity of 90% were got from the patients data. It is
concluded that neural network can detect the arterial STIFFNESS
depending on risk factor parameters.
Abstract: Thyroid dysfunction is one of the most frequently
reported complications of chronic blood transfusion therapy in patients with beta-thalassemia major (BTM). However, the occurrence of thyroid dysfunction and its possible association with
iron overload in BTM patients is still under debate. Therefore, this
study aimed to investigate the status of thyroid functions and iron overload in adolescent and young adult patients with BTM in Jordan population. Thirty six BTM patients aged 12-28 years and matched controls were included in this study. All patients have been receiving frequent blood transfusion to maintain pretransfusion hemoglobin
concentration above 10 g dl-1 and deferoxamine at a dose of 45 mg kg-1 day-1 (8 h, 5-7 days/week) by subcutaneous infusion. Blood
samples were drawn from patients and controls. The status of thyroid functions and iron overload was evaluated by measurements of serum
free thyroxine (FT4), triiodothyronine (FT3), thyrotropin (TSH) and
serum ferritin level. A number of some hematological and
biochemical parameters were also measured. It was found that hematocrit, serum ferritin, hemoglobin, FT3 and zinc, copper mean values were significantly higher in the patients than in the controls (P< 0.05). On other hand, leukocyte, FT4 and TSH mean values were
similar to that of the controls. In addition, our data also indicated that
all of the above examined parameters were not significantly affected
by the patient-s age and gender. Deferoxamine approach for removing excess iron from our BTM patient did not normalize the
values of serum ferritin, copper and zinc, suggesting poor compliance
with deferoxamine chelation therapy. Thus, we recommend the use
of a combination of deferoxamine and deferiprone to reduce the risk
of excess of iron in our patients. Furthermore, thyroid dysfunction
appears to be a rare complication, because our patients showed
normal mean levels for serum TSH and FT4. However, high mean
levels of serum ferritin, zinc, copper might be seen as potential risk
factors for initiation and development of thyroid dysfunctions and
other diseases. Therefore, further studies must be carried out at
yearly intervals with large sample number, to detect subclinical
thyroid dysfunction cases.
Abstract: Nowadays the construction industry is growing specially among developing counties. Iran also has a critical role in these industries in terms of workers disorders. Work-related musculoskeletal disorders (WMSDs) assign 7% of the whole diseases in the society, which make some limitations. One of the main factors, which are ended to WMSDs, is awkward posture. Steel bar bending is considered as one of the prominent performance among construction workers. In this case study we conducted to find the major tasks of bar benders and the most important related risk factors. This study was carried out among twenty workers (18-45 years) as our volunteer samples in some construction sites with less than 6 floors in two regions of Tehran municipality. The data was gathered through in depth observation, interview and questionnaire. Also postural analysis was done by OWAS. In another part of study we used NMQ for gathering some data about psychosocial effects of work related disorders. Our findings show that 64% of workers were not aware of work risks, also about 59% of workers had troubles in their wrists, hands, and especially among workers who worked in steel bar bending. In 46% cases low back pain were prevalence. Considering with gathered data and results, awkward postures and long term tasks and its duration are known as the main risk factors in WMSDs among construction workers, so work-rest schedule and also tools design should be considered to make an ergonomic condition for the mentioned workers.
Abstract: With increasing data in medical databases, medical
data retrieval is growing in popularity. Some of this analysis
including inducing propositional rules from databases using many
soft techniques, and then using these rules in an expert system.
Diagnostic rules and information on features are extracted from
clinical databases on diseases of congenital anomaly. This paper
explain the latest soft computing techniques and some of the
adaptive techniques encompasses an extensive group of methods
that have been applied in the medical domain and that are used for
the discovery of data dependencies, importance of features,
patterns in sample data, and feature space dimensionality
reduction. These approaches pave the way for new and interesting
avenues of research in medical imaging and represent an important
challenge for researchers.
Abstract: Evidence-based medicine is a new direction in modern healthcare. Its task is to prevent, diagnose and medicate diseases using medical evidence. Medical data about a large patient population is analyzed to perform healthcare management and medical research. In order to obtain the best evidence for a given disease, external clinical expertise as well as internal clinical experience must be available to the healthcare practitioners at right time and in the right manner. External evidence-based knowledge can not be applied directly to the patient without adjusting it to the patient-s health condition. We propose a data warehouse based approach as a suitable solution for the integration of external evidence-based data sources into the existing clinical information system and data mining techniques for finding appropriate therapy for a given patient and a given disease. Through integration of data warehousing, OLAP and data mining techniques in the healthcare area, an easy to use decision support platform, which supports decision making process of care givers and clinical managers, is built. We present three case studies, which show, that a clinical data warehouse that facilitates evidence-based medicine is a reliable, powerful and user-friendly platform for strategic decision making, which has a great relevance for the practice and acceptance of evidence-based medicine.
Abstract: Medical applications are among the most impactful
areas of microrobotics. The ultimate goal of medical microrobots is
to reach currently inaccessible areas of the human body and carry out
a host of complex operations such as minimally invasive surgery
(MIS), highly localized drug delivery, and screening for diseases at
their very early stages. Miniature, safe and efficient propulsion
systems hold the key to maturing this technology but they pose
significant challenges. A new type of propulsion developed recently,
uses multi-flagella architecture inspired by the motility mechanism of
prokaryotic microorganisms. There is a lack of efficient methods for
designing this type of propulsion system. The goal of this paper is to
overcome the lack and this way, a numerical strategy is proposed to
design multi-flagella propulsion systems. The strategy is based on the
implementation of the regularized stokeslet and rotlet theory, RFT
theory and new approach of “local corrected velocity". The effects of
shape parameters and angular velocities of each flagellum on overall
flow field and on the robot net forces and moments are considered.
Then a multi-layer perceptron artificial neural network is designed
and employed to adjust the angular velocities of the motors for
propulsion control. The proposed method applied successfully on a
sample configuration and useful demonstrative results is obtained.
Abstract: The performances of small and medium enterprises
have stagnated in the last two decades. This has mainly been due to
the emergence of HIV / Aids. The disease has had a detrimental
effect on the general economy of the country leading to morbidity
and mortality of the Kenyan workforce in their primary age. The
present study sought to establish the economic impact of HIV / Aids
on the micro-enterprise development in Obunga slum – Kisumu, in
terms of production loss, increasing labor related cost and to establish
possible strategies to address the impact of HIV / Aids on microenterprises.
The study was necessitated by the observation that most
micro-enterprises in the slum are facing severe economic and social
crisis due to the impact of HIV / Aids, they get depleted and close
down within a short time due to death of skilled and experience
workforce. The study was carried out between June 2008 and June
2009 in Obunga slum. Data was subjected to computer aided
statistical analysis that included descriptive statistic, chi-squared and
ANOVA techniques. Chi-squared analysis on the micro-enterprise
owners opinion on the impact of HIV / Aids on depletion of microenterprise
compared to other diseases indicated high levels of the
negative effects of the disease at significance levels of P
Abstract: Pleurotus ostreatus is a common edible mushroom with a number of properties that can help to solve the nutritional and economical problems of people in Chiapas, Mexico. The objective of this project was to produce the mushroom under a sustainable management in which only regional products were allowed as a way to promote the cultivation and consumption of Pleurotus ostreatus; 5 different substrates were tested as well as 2 sanitation methods. The obtained results showed that the highest yields were obtained using corn husk and a thermal sanitation method. Pests and diseases were not a problem during the project but they appeared more in the substrates sanitized with calcium hydroxide.
Abstract: In this paper, we propose disease diagnosis hardware
architecture by using Hypernetworks technique. It can be used to
diagnose 3 different diseases (SPECT Heart, Leukemia, Prostate
cancer). Generally, the disparate diseases require specified diagnosis
hardware model for each disease. Using similarities of three diseases
diagnosis processor, we design diagnosis processor that can diagnose
three different diseases. Our proposed architecture that is combining
three processors to one processor can reduce hardware size without
decrease of the accuracy.
Abstract: The plant world is the source of many medicines.
Recently, researchers have estimated that there are approximately
400,000 plant species worldwide, of which about a quarter or a third
have been used by societies for medicinal purposes. The human uses
of plants for thousands of years to treat various ailments, in many
developing countries, much of the population trust in traditional
doctors and their collections of medicinal plants to treat them.
Essential oils have many therapeutic properties. In herbal medicine,
they are used for their antiseptic properties against infectious
diseases of fungal origin, against dermatophytes, those of bacterial
origin. The aim of our study is to determine the antimicrobial effect
of essential oils of the plant Trigonella focnum greacum on some
pathogenic bacteria, it is a medicinal plant used in traditional
therapy. The test adopted is based on the diffusion method on solid
medium (Antibiogram), this method determines the sensitivity or
resistance of a microorganism vis-à-vis the extract studied. Our study
reveals that the essential oil of the plant Trigonella focnum greacum
has a different effect on the resistance of germs. For staphiloccocus
Pseudomonnas aeroginosa and Krebsilla, are moderately sensitive
strains, also Escherichia coli and Candida albicans represents a high
sensitivity. By against Proteus is a strain that represents a weak
sensitivity.
Abstract: Human genome is not only the evolutionary
summation of all advantageous events, but also houses lesions of
deleterious foot prints. A single gene mutation sometimes may
express multiple consequences in numerous tissues and a linear
relationship of the genotype and the phenotype may often be obscure.
ß Thalassemia minor, a transfusion independent mild anaemia,
coupled with environment among other factors may articulate into
phenotypic pleotropy with Hypocholesterolemia, Vitamin D
deficiency, Tissue hypoxia, Hyper-parathyroidism and Psychological
alterations. Occurrence of Pancreatic insufficiency, resultant
steatorrhoea, Vitamin-D (25-OH) deficiency (13.86 ngm/ml) with
Hypocholesterolemia (85mg/dl) in a 30 years old male ß Thal-minor
patient (Hemoglobin 11mg/dl with Fetal Hemoglobin 2.10%, Hb A2
4.60% and Hb Adult 84.80% and altered Hemogram) with increased
Para thyroid hormone (62 pg/ml) & moderate Serum Ca+2
(9.5mg/ml) indicate towards a cascade of phenotypic pleotropy
where the ß Thalassemia mutation ,be it in the 5’ cap site of the
mRNA , differential splicing etc in heterozygous state is effecting
several metabolic pathways. Compensatory extramedulary
hematopoiesis may not coped up well with the stressful life style of
the young individual and increased erythropoietic stress with high
demand for cholesterol for RBC membrane synthesis may have
resulted in Hypocholesterolemia.Oxidative stress and tissue hypoxia
may have caused the pancreatic insufficiency, leading to Vitamin D
deficiency. This may in turn have caused the secondary
hyperparathyroidism to sustain serum Calcium level. Irritability and
stress intolerance of the patient was a cumulative effect of the vicious
cycle of metabolic compromises. From these findings we propose
that the metabolic deficiencies in the ß Thalassemia mutations may
be considered as the phenotypic display of the pleotropy to explain
the genetic epidemiology.
According to the recommendations from the NIH Workshop on
Gene-Environment Interplay in Common Complex Diseases: Forging
an Integrative Model, study design of observations should be
informed by gene-environment hypotheses and results of a study
(genetic diseases) should be published to inform future hypotheses.
Variety of approaches is needed to capture data on all possible
aspects, each of which is likely to contribute to the etiology of
disease. Speakers also agreed that there is a need for development of
new statistical methods and measurement tools to appraise
information that may be missed out by conventional method where
large sample size is needed to segregate considerable effect.
A meta analytic cohort study in future may bring about significant
insight on to the title comment.
Abstract: Principally, plants grown in soilless culture may be
attacked by the same pests and diseases as cultivated traditionally in
soil. The most destructive phytopathogens are fungi, such as
Phythium, Phytophthora and Fusarium, followed by viruses, bacteria
and nematodes. We investigated effect of carbon nanotube filters on
disease management of soilless culture. Tomato seedlings transplant
in plastic pots filled with a soilless media of vermiculite. The crop
irrigated and fertilized using a hydroponic nutrient solution. We used
carbon nanotube filters for nutrient solution disinfection. Our results
show that carbon nanotube filtration significantly reduces pathogens
on tomato plants. Fungal elimination (Fusarium oxysporum and
Pythium spp.) was usually successful at about 96 to 99.9% all over
the cultural season. It is seem that in tomato soilless culture,
nanofiltration constitutes a reliable method that allows control of the
development of diseases caused by pathogenic fungi