239 research outputs found
Nutrigenomics and nutrigenetics
The nutrients are able to interact with molecular mechanisms and modulate the physiological functions in the body. The Nutritional Genomics focuses on the interaction between bioactive food components and the genome, which includes Nutrigenetics and Nutrigenomics. The influence of nutrients on f genes expression is called Nutrigenomics, while the heterogeneous response of gene variants to nutrients, dietary components and developing nutraceticals is called Nutrigenetics. Genetic variation is known to affect food tolerances among human subpopulations and may also influence dietary requirements and raising the possibility of individualizing nutritional intake for optimal health and disease prevention on the basis of an individual's genome. Nutrigenomics provides a genetic understanding for how common dietary components affect the balance between health and disease by altering the expression and/or structure of an individual's genetic makeup. Nutrigenetics describes that the genetic profile have impact on the response of body to bioactive food components by influencing their absorption, metabolism, and site of action. In this way, considering different aspects of gene-nutrient interaction and designing appropriate diet for every specific genotype that optimize individual health, diagnosis and nutritional treatment of genome instability, we could prevent and control conversion of healthy phenotype to diseases
Transient Flow and Pigging Operation in Gas-Liquid Two Phase Pipelines
For simulation of transient gas-liquid two phase flow, the continuity, momentum and energy equations for two fluids should be solved, which requires complex calculations. In oil and gas pipelines, it is possible to perform some simplifications on continuity and momentum equations. This will be done by using quasi steady state assumption for gas continuity equation and also local equilibrium momentum balance for both phases in some flow patterns such as stratified, annular, slug and bubbly flows. In this paper, simplified transient simulation with assumption of isothermal flow was utilized together with flow patterns transition criterion and tested against experimental data for verification of the results. For this purpose, a computer code was written and implemented as transient flow simulator. In this code, the one dimensional differential equations were discretized by semi- implicit finite difference method and solved by an iterative manner. Also, a model for pigging operation was developed to analyze the flow parameters in pipeline during and after pigging. The numerical results were compared with the experimental data and it is observed that agreement with experimental data is satisfactory from practical engineering stand point
Residual stress evaluation in friction stir welding of aluminum plates by means of acoustic emission and ultrasonic waves
© Faculty of Mechanical Engineering, Belgrade. The residual stress assessment in structures is essential for optimization of the structures' design. The attention of this paper is focused on how acoustic emission signals caused by tensile loading of the friction stir welded aluminum plates are expected to vary depending upon the residual stress. To this aim, the distribution of residual stresses in two friction stir welded aluminum specimens was firstly evaluated by ultrasonic stress measurement. AE signals were then produced during tensile tests and captured using AE sensors. The obtained AE signals were analyzed using statistical features including crest factor, cumulative crest factor and sentry function. It was found that the crest factor could be used to identify the presence of the residual stresses and that the trends of sentry function are in good agreement with the results of crest factor and cumulative crest factor
Association between TNF-α promoter G-308A and G-238A polymorphisms and obesity
Tumor necrosis factor-α (TNF-α), an adipokine, is produced in adipocytes, and the elevation of its levels has been linked to obesity and insulin resistance in some population. In this study the relationship between TNF-α promoter gene polymorphism and obesity in an Iranian population has been studied. Subjects were randomly selected from Tehran Cohort Lipid and Glucose Study. Adult participants placed in three groups according to their body mass index (BMI): BMI < 25, 25 ≤ BMI < 30, BMI ≥ 30 and under-18 subjects placed in two groups, under 85th percentile BMI and above 85th percentile. Finally, 244 persons were selected for G-308A and G-238A polymorphisms analysis. The FBS, high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), triglyceride, cholesterol levels and blood pressure and HOMA of all subjects were measured. The polymorphism −308 and −238 were revealed by restriction fragment length polymorphism (RFLP; NCOI and MSPI) after the promoter site was amplified by PCR. The allele frequency of TNF-α polymorphism was in the Hardy–Weinberg equilibrium. There was no relation between BMI and the frequency of this allele. The fact that there is no association between G-308A and G-238A TNF-α promoter polymorphisms and obesity probably shows that it is not an important risk factor for obesity and consequently for cardiovascular disease
PULSAR: Graph based Positive Unlabeled Learning with Multi Stream Adaptive Convolutions for Parkinson's Disease Recognition
Parkinson's disease (PD) is a neuro-degenerative disorder that affects
movement, speech, and coordination. Timely diagnosis and treatment can improve
the quality of life for PD patients. However, access to clinical diagnosis is
limited in low and middle income countries (LMICs). Therefore, development of
automated screening tools for PD can have a huge social impact, particularly in
the public health sector. In this paper, we present PULSAR, a novel method to
screen for PD from webcam-recorded videos of the finger-tapping task from the
Movement Disorder Society - Unified Parkinson's Disease Rating Scale
(MDS-UPDRS). PULSAR is trained and evaluated on data collected from 382
participants (183 self-reported as PD patients). We used an adaptive graph
convolutional neural network to dynamically learn the spatio temporal graph
edges specific to the finger-tapping task. We enhanced this idea with a multi
stream adaptive convolution model to learn features from different modalities
of data critical to detect PD, such as relative location of the finger joints,
velocity and acceleration of tapping. As the labels of the videos are
self-reported, there could be cases of undiagnosed PD in the non-PD labeled
samples. We leveraged the idea of Positive Unlabeled (PU) Learning that does
not need labeled negative data. Our experiments show clear benefit of modeling
the problem in this way. PULSAR achieved 80.95% accuracy in validation set and
a mean accuracy of 71.29% (2.49% standard deviation) in independent test,
despite being trained with limited amount of data. This is specially promising
as labeled data is scarce in health care sector. We hope PULSAR will make PD
screening more accessible to everyone. The proposed techniques could be
extended for assessment of other movement disorders, such as ataxia, and
Huntington's disease
Designing an adaptive fuzzy control for robot manipulators using PSO
This paper presents designing an optimal adaptive controller for tracking control of robot manipulators based on particle swarm optimization (PSO) algorithm. PSO algorithm has been employed to optimize parameters of the controller and hence to minimize the integral square of errors (ISE) as a performance criteria. In this paper, an improved PSO using logic is proposed to increase the convergence speed. In this case, the performance of PSO algorithms such as an improved PSO (IPSO), an improved PSO using fuzzy logic (F-PSO), a linearly decreasing inertia weight of PSO (LWD-PSO) and a nonlinearly decreasing inertia weight of PSO (NDW-PSO) are compared in terms of parameter accuracy and convergence speed. As a result, the simulation results show that the F-PSO approach presents a better performance in the tracking control of robot manipulators than other algorithms
Nutritional status and quality of life in patients with acute leukemia prior to and after induction chemotherapy in three hospitals in Tehran, Iran: a prospective study
BACKGROUND: The primary objective of the present study was to assess changes in the nutritional status and quality of life in acute leukaemia patients, aged ≥15 years, who had undergone induction chemotherapy.
METHODS: A preliminary and post-induction chemotherapy assessment of patients' nutritional status, quality of life, sociodemographic status and medical characteristics was conducted using the Patient Generated Subjective Global Assessment (PG-SGA) and the European Organization for Research and Treatment of Cancer quality of life (QOL-C30, version 3) questionnaires. The PG-SGA is a clinical nutrition assessment tool used to evaluate oncology patients. Patients with newly-diagnosed acute leukaemia, aged ≥15 years, at three hospitals in Tehran (from May 2009 to March 2010), were recruited for the present study.
RESULTS: Sixty-three acute leukaemia patients [65% men and 35% women with a mean (SD) age of 33 (15.4) years] participated in the present study. A total of 19.4% were found to be malnourished prior to chemotherapy. After chemotherapy, 76.1% of patients were considered moderately malnourished, whereas 6.3% were severely malnourished. After induction chemotherapy, both the nutritional status and quality of life deteriorated in the majority of patients, as demonstrated by a paired t-test.
CONCLUSIONS: A deteriorated nutritional status and quality of life was the result of the side effects posed by induction chemotherapy in the patients investigated in the present study. These findings highlight the need for an appropriate nutritional support programme to improve the nutritional status and quality of life in patients with leukaemia undergoing chemotherapy
An indirect adaptive neuro-fuzzy speed control of induction motors
This paper presents an indirect adaptive system based on neuro-fuzzy approximators for the speed control of induction motors. The uncertainty including parametric variations, the external load disturbance and unmodeled dynamics is estimated and compensated by designing neuro-fuzzy systems. The contribution of this paper is presenting a stability analysis for neuro-fuzzy speed control of induction motors. The online training of the neuro-fuzzy systems is based on the Lyapunov stability analysis and the reconstruction errors of the neuro-fuzzy systems are compensated in order to guarantee the asymptotic convergence of the speed tracking error. Moreover, to improve the control system performance and reduce the chattering, a PI structure is used to produce the input of the neuro-fuzzy systems. Finally, simulation results verify high performance characteristics and robustness of the proposed control system against plant parameter variation, external load and input voltage disturbance
Effect of dietary omega-3 fatty acids on castrate-resistant prostate cancer and tumor-associated macrophages.
BackgroundM2-like macrophages are associated with the pathogenesis of castrate-resistant prostate cancer (CRPC). We sought to determine if dietary omega-3 fatty acids (ω-3 FAs) delay the development and progression of CRPC and inhibit tumor-associated M2-like macrophages.MethodsMycCap cells were grown subcutaneously in immunocompetent FVB mice. Mice were castrated when tumors reached 300 mm2. To study effects of dietary ω-3 FAs on development of CRPC, ω-3 or ω-6 diets were started 2 days after castration and mice sacrificed after early regrowth of tumors. To study ω-3 FA effects on progression of CRPC, tumors were allowed to regrow after castration before starting the diets. M2 (CD206+) macrophages were isolated from allografts to examine ω-3 FA effects on macrophage function. Omega-3 fatty acid effects on androgen-deprived RAW264.7 M2 macrophages were studied by RT-qPCR and a migration/ invasion assay.ResultsThe ω-3 diet combined with castration lead to greater MycCap tumor regression (tumor volume reduction: 182.2 ± 33.6 mm3) than the ω-6 diet (tumor volume reduction: 148.3 ± 35.2; p = 0.003) and significantly delayed the time to CRPC (p = 0.006). Likewise, the ω-3 diet significantly delayed progression of established castrate-resistant MycCaP tumors (p = 0.003). The ω-3 diet (as compared to the ω-6 diet) significantly reduced tumor-associated M2-like macrophage expression of CSF-1R in the CRPC development model, and matrix metallopeptidase-9 (MMP-9) and vascular endothelial growth factor (VEGF) in the CRPC progression model. Migration of androgen-depleted RAW264.7 M2 macrophages towards MycCaP cells was reversed by addition of docosahexaenoic acid (ω-3).ConclusionsDietary omega-3 FAs (as compared to omega-6 FAs) decreased the development and progression of CRPC in an immunocompetent mouse model, and had inhibitory effects on M2-like macrophage function. Clinical trials are warranted evaluating if a fish oil-based diet can delay the time to castration resistance in men on androgen deprivation therapy, whereas further preclinical studies are warranted evaluating fish oil for more advanced CRPC
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