Multiscale modeling of tumor growth and angiogenesis: Evaluation of tumor-targeted therapy.

The dynamics of tumor growth and associated events cover multiple time and spatial scales, generally including extracellular, cellular and intracellular modifications. The main goal of this study is to model the biological and physical behavior of tumor evolution in presence of normal healthy tissue, considering a variety of events involved in the process. These include hyper and hypoactivation of signaling pathways during tumor growth, vessels' growth, intratumoral vascularization and competition of cancer cells with healthy host tissue. The work addresses two distinctive phases in tumor development-the avascular and vascular phases-and in each stage two cases are considered-with and without normal healthy cells. The tumor growth rate increases considerably as closed vessel loops (anastomoses) form around the tumor cells resulting from tumor induced vascularization. When taking into account the host tissue around the tumor, the results show that competition between normal cells and cancer cells leads to the formation of a hypoxic tumor core within a relatively short period of time. Moreover, a dense intratumoral vascular network is formed throughout the entire lesion as a sign of a high malignancy grade, which is consistent with reported experimental data for several types of solid carcinomas. In comparison with other mathematical models of tumor development, in this work we introduce a multiscale simulation that models the cellular interactions and cell behavior as a consequence of the activation of oncogenes and deactivation of gene signaling pathways within each cell. Simulating a therapy that blocks relevant signaling pathways results in the prevention of further tumor growth and leads to an expressive decrease in its size (82% in the simulation).

Analysis of Magneto-Hyperthermia Duration in Nano-sized Drug Delivery System to Solid Tumors Using Intravascular-Triggered Thermosensitive-Liposome.

Computational models have been developed as a potential platform to identify bio-interactions that cannot be properly understood by experimental models. In the present study, a mathematical model has been employed to investigate the therapeutic response of drug-loaded thermosensitive liposome (TSL) following intravascular release paradigm. Thermal field created by an alternating magnetic field is utilized to release the drug within microvessels. Determining the time required for the application of magneto-hyperthermia is the main purpose of this study. Results show that applying a long-term continuous or pulsed hyperthermia can affect the concentration level of drugs in the extracellular space. The peak value of free and bound drug concentrations in the extracellular space is equal for all hyperthermia programs. Additionally, the concentrations of free and bound drugs are retained at a higher level in pulsed mode compared to the continuous mode (i.e., area under curve (AUC) of pulsed case is slightly higher than continuous case). However, there is no significant difference in bioavailability time. Hence, onset time of tumor growth is similar for different conditions. This study shows that the appropriate time to apply hyperthermia is post-bolus injection until reaching the peak concentration profile in extracellular space. Therefore, in clinical applications similar to the present study's circumstances, continuous hyperthermia for 30 min can be a better choice. This study can be a useful guideline for experimental studies to reduce the number of in vivo tests as well as for clinical trials to make the right decision to provide optimal medication programs.

Deep neural networks for neuro-oncology: Towards patient individualized design of chemo-radiation therapy for Glioblastoma patients.

BACKGROUND AND OBJECTIVES: Glioblastoma multiforme (GBM) is the most common and deadly type of primary cancers of the brain and central nervous system in adults. Despite the importance of designing a personalized treatment regimen for the patient, clinical trials prescribe a set of conventional regimens for GBM patients. We propose a computerized framework for designing chemo-radiation therapy (CRT) regimen based on patient characteristics. METHODS: An intelligent agent, based on deep reinforcement learning, interacts with a virtual personalized GBM. The proposed deep Q network (DQN) uses a deep neural network to estimate the state - action value function. The algorithm stores agent experiences in a replay memory to be used for training of the deep neural network. Also, the proliferation-invasion model is used to simulate spatiotemporal dynamics of GBM growth and its response to therapeutic agents. RESULTS: Assuming tumor size at the end of the treatment course as a measure of the quality of the treatment regimen, experiments show that the proposed DQN is superior to the Q learning. Also, while the quality of the protocols obtained by the Q learning as well as its convergence speed decreases sharply with the increase in the dimensions of the state-action value function, the DQN is relatively robust against increasing the initial tumor size or lengthening the treatment period. CONCLUSION: Our results suggest that the optimal personalized treatment regimen may differ from the conventional regimens suggested by clinical trials. Given the scalability of the proposed DQN in designing treatment regimen for real size tumors, as well as its superiority over previous models, it is a suitable tool for designing personalized CRT regimen for GBM patients.

Computational modeling of PET tracer distribution in solid tumors integrating microvasculature.

BACKGROUND: We present computational modeling of positron emission tomography radiotracer uptake with consideration of blood flow and interstitial fluid flow, performing spatiotemporally-coupled modeling of uptake and integrating the microvasculature. In our mathematical modeling, the uptake of fluorodeoxyglucose F-18 (FDG) was simulated based on the Convection-Diffusion-Reaction equation given its high accuracy and reliability in modeling of transport phenomena. In the proposed model, blood flow and interstitial flow are solved simultaneously to calculate interstitial pressure and velocity distribution inside cancer and normal tissues. As a result, the spatiotemporal distribution of the FDG tracer is calculated based on velocity and pressure distributions in both kinds of tissues. RESULTS: Interstitial pressure has maximum value in the tumor region compared to surrounding tissue. In addition, interstitial fluid velocity is extremely low in the entire computational domain indicating that convection can be neglected without effecting results noticeably. Furthermore, our results illustrate that the total concentration of FDG in the tumor region is an order of magnitude larger than in surrounding normal tissue, due to lack of functional lymphatic drainage system and also highly-permeable microvessels in tumors. The magnitude of the free tracer and metabolized (phosphorylated) radiotracer concentrations followed very different trends over the entire time period, regardless of tissue type (tumor vs. normal). CONCLUSION: Our spatiotemporally-coupled modeling provides helpful tools towards improved understanding and quantification of in vivo preclinical and clinical studies.

A neuro evolutionary algorithm for patient calibrated prediction of survival in Glioblastoma patients.

BACKGROUND AND OBJECTIVES: Glioblastoma multiforme (GBM) is the most common and malignant type of primary brain tumors. Radiation therapy (RT) plus concomitant and adjuvant Temozolomide (TMZ) constitute standard treatment of GBM. Existing models for GBM growth do not consider the effect of different schedules on tumor growth and patient survival. However, clinical trials show that treatment schedule and drug dosage significantly affect patient survival. The goal is to provide a patient calibrated model for predicting survival according to the treatment schedule. METHODS: We propose a top-down method based on artificial neural networks (ANN) and genetic algorithm (GA) to predict survival of GBM patients. A feed forward undercomplete Autoencoder network is integrated with the neuro-evolutionary (NE) algorithm in order to extract a compressed representation of input clinical data. The proposed NE algorithm uses GA to obtain optimal architecture of a multi-layer perceptron (MLP). Taguchi L16 orthogonal design of experiments is used to tune parameters of the proposed NE algorithm. Finally, the optimal MLP is used to predict survival of GBM patients. RESULTS: Data from 8 related clinical trials have been collected and integrated to train the model. From 847 evaluable cases, 719 were used for train and validation and the remaining 128 cases were used to test the model. Mean absolute error of the predictions on the test data is 0.087 months which shows excellent performance of the proposed model in predicting survival of the patients. Also, the results show that the proposed NE algorithm is superior to other existing models in both the mean and variability of the prediction error.

Estimation of drug and tumor properties using novel hybrid meta-heuristic methods.

One of the major drawbacks in mathematical modeling of the drug delivery in living species is application of a common value for a specific property such as diffusion coefficient of drug in tissue, while this property is unique for each person or species. Therefore, knowledge on the species-specific values of these properties can improve the process of drug delivery and treatment. Inverse problem methods can achieve these unique properties for each specimen. Estimation of the individual-specific drug and tumor parameters requires the evaluation of the drug concentration (the concentration of medical images) within the tumor tissue. Accordingly, in this paper, first, the drug transport equation in tumor is determined. Then, the sensitivity analysis is conducted to determine the appropriate area for selecting the drug concentration to estimate the drug and tumor parameters. Finally, the parameters estimated by meta-heuristic and hybrid meta-heuristic methods are compared. To enhance the validity of the methods, two different drug transport models are examined. The results indicate that the hybrid methods gave rise to more precise estimations, especially the hybrid particle swarm optimization (PSO) method with whale optimization algorithm (WOA) which offer more appropriate responses in the parameters estimation of two models.

Probiotics, lactic acid bacteria and bacilli: interesting supplementation for aquaculture.

Probiotics administration in aquafeed is known to increase feed consumption and absorption due to their capacity to release a wide range of digestive enzymes and nutrients which can participate in digestion process and feed utilization, along with the absorption of diet components led to an increase in host's health and well-being. Furthermore, probiotics improve gut maturation, prevention of intestinal disorders, predigestion of antinutrient factors found in the feed ingredients, gut microbiota, disease resistance against pathogens and metabolism. The beneficial immune effects of probiotics are well established in finfish. However, in comparison, similar studies are less abundant in the shellfish. In this review, the discussions will mainly focus on studies reported the last 2 years. In recent studies, native probiotic bacteria were isolated and fed back to their hosts. Although beneficial effects were demonstrated, some studies showed adverse effects when treated with a high concentration. This adverse effect may be due to the imbalance of the gut microbiota caused by the replenished commensal probiotics. Probiotics revealed greatest effect on the shrimp digestive system particularly in the larval and early post-larval stages, and stimulate the production of endogenous enzymes in shrimp and contribute with improved the enzyme activities in the gut, as well as disease resistance.

Image-based spatio-temporal model of drug delivery in a heterogeneous vasculature of a solid tumor - Computational approach.

The solute transport distribution in a tumor is an important criterion in the evaluation of the cancer treatment efficacy. The fraction of killed cells after each treatment can quantify the therapeutic effect and plays as a helpful tool to evaluate the chemotherapy treatment schedules. In the present study, an image-based spatio-temporal computational model of a solid tumor is provided for calculation of interstitial fluid flow and solute transport. Current model incorporates heterogeneous microvasculature for angiogenesis instead of synthetic mathematical modeling. In this modeling process, a comprehensive model according to Convection-Diffusion-Reaction (CDR) equations is employed due to its high accuracy for simulating the binding and the uptake of the drug by tumor cells. Based on the velocity and the pressure distribution, transient distribution of the different drug concentrations (free, bound, and internalized) is calculated. Then, the fraction of killed cells is obtained according to the internalized concentration. Results indicate the dependence of the drug distribution on both time and space, as well as the microvasculature density. Free and bound drug concentration have the same trend over time, whereas, internalized and total drug concentration increases over time and reaches a constant value. The highest amount of concentration occurred in the tumor region due to the higher permeability of the blood vessels. Moreover, the fraction of killed cells is approximately 78.87% and 24.94% after treatment with doxorubicin for cancerous and normal tissues, respectively. In general, the presented methodology may be applied in the field of personalized medicine to optimize patient-specific treatments. Also, such image-based modeling of solid tumors can be used in laboratories that working on drug delivery and evaluating new drugs before using them for any in vivo or clinical studies.

The pivotal role of angiogenesis in a multi-scale modeling of tumor growth exhibiting the avascular and vascular phases.

The mechanisms involved in tumor growth mainly occur at the microenvironment, where the interactions between the intracellular, intercellular and extracellular scales mediate the dynamics of tumor. In this work, we present a multi-scale model of solid tumor dynamics to simulate the avascular and vascular growth as well as tumor-induced angiogenesis. The extracellular and intercellular scales are modeled using partial differential equations and cellular Potts model, respectively. Also, few biochemical and biophysical rules control the dynamics of intracellular level. On the other hand, the growth of melanoma tumors is modeled in an animal in-vivo study to evaluate the simulation. The simulation shows that the model successfully reproduces a completed image of processes involved in tumor growth such as avascular and vascular growth as well as angiogenesis. The model incorporates the phenotypes of cancerous cells including proliferating, quiescent and necrotic cells, as well as endothelial cells during angiogenesis. The results clearly demonstrate the pivotal effect of angiogenesis on the progression of cancerous cells. Also, the model exhibits important events in tumor-induced angiogenesis like anastomosis. Moreover, the computational trend of tumor growth closely follows the observations in the experimental study.

Modeling of FMISO [F18] nanoparticle PET tracer in normal-cancerous tissue based on real clinical image.

Hypoxia as one of the principal properties of tumor cells is a reaction to the deprivation of oxygen. The location of tumor cells could be identified by assessment of oxygen and nutrient level in human body. Positron emission tomography (PET) is a well-known non-invasive method that is able to measure hypoxia based on the FMISO (Fluoromisonidazole) tracer dynamic. This paper aims to study the PET tracer concentration through convection-diffusion-reaction equations in a real human capillary-like network. A non-uniform oxygen pressure along the capillary path and convection mechanism for FMISO transport are taken into account to accurately model the characteristics of the tracer. To this end, a multi-scale model consists of laminar blood flow through the capillary network, interstitial pressure, oxygen pressure, FMISO diffusion and FMISO convection transport in the extravascular region is developed. The present model considers both normal and tumor tissue regions in computational domain. The accuracy of numerical model is verified with the experimental results available in the literature. The convection and diffusion types of transport mechanism are employed in order to calculate the concentration of FMISO in the normal and tumor sub-domain. The influences of intravascular oxygen pressure, FMISO transport mechanisms, capillary density and different types of tissue on the FMISO concentration have been investigated. According to result (Table 4) the convection mechanism of FMISO molecules transportation is negligible, but it causes more accuracy of the proposed model. The approach of present study can be employed in order to investigate the effects of various parameters, such as tumor shape, on the dynamic behavior of different PET tracers, such as FDG, can be extended to different case study problems, such as drug delivery.

Nephroblastoma in bester sturgeon, a cultured hybrid of Huso huso × Acipenser ruthenus: Diagnostic imaging, clinical and histopathological study.

Abdominal distention occurred at an incidence of 1% (15 from 1500 fish) in the population of 1-year-old bester (Huso huso × Acipenser ruthenus). Computed tomography (CT) images and radiographs showed a soft tissue mass compressed the posterior part of the swim bladder. Ultrasonography showed that the masses had different patterns. Internal examination revealed the abdominal cavities to be filled with large masses which appeared to encompass most of the visceral organs, including the swim bladder. The masses originated from the posterior kidney. Histologically, the masses were composed of mixtures of embryonal epithelial (tubules and glomeruli), blastema and mesenchymal tissues. The tubules showed cystic, papillary and tubular patterns. Tubules and glomeruloid structures were surrounded by proliferating blastema cells. The primitive mesenchyme was composed of loose streams and whorls of spindle to stellate cells with elongate nuclei. Histological findings in the skeletal muscles, hypoderm and spleen confirmed the metastatic tumour from the kidney in two cases. Immunohistochemically, neoplastic cells of the tubules and glomeruloid structures were positive for cytokeratin AE1/AE3. Sections stained with Masson's trichrome showed blue staining of the stroma. The histopathologic findings were consistent with nephroblastoma.

Protective effects of the hydroalcoholic extract of Fumaria parviflora on testicular injury induced by torsion/detorsion in adult rats.

This study was designed to determine the effects of daily oral administration (250 mg/kg) of the hydroalcoholic extract of Fumaria parviflora (FP) for 14 days on the sperm parameters, oxidative stress parameters, serum testosterone levels, expression of Bax and Bcl-2 genes, and apoptosis index of germ cells after testicular torsion-detorsion (ischaemia-reperfusion, IR) injury model in rats. Twenty-eight adult male Wistar rats were divided randomly into four groups of seven each: sham operation, torsion-detorsion (TD), TD plus the hydroalcoholic extract FP (TDFP) and only FP without TD application (FP). Testicular torsion was created by rotating the left testis 720° in a counterclockwise direction; then, after 4 hr, detorsion was performed. The Johnson's score, mean seminiferous tubule diameter (MSTD) and height (thickness) of seminiferous tubule epithelium (HST) were significantly increased in TDFP and FP groups as compared to TD group. The gene expression of Bcl-2, level of serum testosterone hormone and antioxidant parameters-GPx and SOD-were significantly higher in TDFP and FP groups than TD group. The index of apoptosis, the gene expression of Bax and the level of MDA were significantly higher in TD group than TDFP and FP groups. Therefore, F. parviflora could decrease oxidative stress induced by testicular torsion-detorsion.

Comparison of single- and multi-strain probiotics effects on broiler breeder performance, egg production, egg quality and hatchability.

1. This study was conducted to investigate the effect of multi-strain probiotic (containing Lactobacillus acidophilus 2.5 × 107 cfu/g, Lactobacillus casei 2.5 × 107 cfu/g, Bifidobacterium thermophilum 2.5 × 107 cfu/g and Enterococcus faecium 2.5 × 107 cfu/g) and single-strain probiotic (Pediococcus acidilactici 1 × 1010 cfu/g) on broiler breeder performance and gastrointestinal health. 2. A completely randomised trial was conducted using 300 broiler breeder hens (Ross 308) aged 51 weeks old which were randomly allocated to 1 of 5 dietary treatments with 6 replicates per treatment in a 10 week trial. Treatments included (1) the basal diet a negative control, (2) basal diet supplemented with 0.1 g/kg multi-strain probiotic (MS), (3) basal diet supplemented with 0.1 g/kg single-strain probiotic (SS), (4) basal diet supplemented with 0.1 g/kg of both of probiotics (MS+ SS) and (5) positive control basal diet supplemented with 0.5 g/kg oxytetracycline antibiotic (OX). 3. Body weight, egg production, yolk weight, eggshell thickness and weight, Haugh unit, fertility and hatchability were determined. Results showed that dietary treatments had no significant effect on total hen house or total hatching egg production, egg weight, yolk colour index, shell weight, mortality, body weight, fertility, hatchability, oviduct and stroma weight or number of large and small yellow follicles (P > 0.05). None of the jejunum morphological parameters, apparent ileal digestibility of protein and ileal Lactobacillus population were influenced by supplemental probiotics (P > 0.05), although ileum Escherichia coli count was reduced by inclusion of dietary probiotics (P < 0.05). 4. It was concluded that although both probiotic treatments reduced coliforms, they did not improve broiler breeder performance or gastrointestinal tract (GIT) function.

Ultrasensitive micro-scale parity-time-symmetric ring laser gyroscope.

We propose a new scheme for ultrasensitive laser gyroscopes that utilizes the physics of exceptional points. By exploiting the properties of such non-Hermitian degeneracies, we show that the rotation-induced frequency splitting becomes proportional to the square root of the gyration speed (Ω), thus enhancing the sensitivity to low angular rotations by orders of magnitudes. In addition, at its maximum sensitivity limit, the measurable spectral splitting is independent of the radius of the rings involved. This Letter paves the way toward a new class of ultrasensitive miniature ring laser gyroscopes on chip.

Co-circulation of genetically distinct groups of avian paramyxovirus type 1 in pigeon Newcastle disease in Iran.

Pigeons are considered as one of the major natural reservoirs in the epidemiology of Newcastle disease (ND). In this study, the partial sequence of fusion protein gene of 17 pigeon-origin ND viruses (NDVs) isolated during 2012-2013 in Iran was analysed. Since the studied isolates showed F0 protein cleavage sites compatible with velogenic NDVs, all were considered as virulent NDVs. Two isolates carried 112RRQKRF117 as the cleavage site motif, whereas the rest demonstrated 112KRQKRF117 motif which just recently has been reported among Iranian virulent NDVs. Phylogenetic analysis divided all these diverse isolates in two distinct clusters within class II genotype VI. Based on the partial fusion protein gene sequence, 15 out of 17 isolates showed the highest genetic identity to subgenotype VIb/2 and the other two isolates were placed in a distinct genetic group of genotype VI. Based on recent findings, at least two different sublineages of genotype VI are causing the ND outbreaks in the pigeon population and are circulating simultaneously along with virulent NDVs of genotype VII in various species in Iran. The continuing circulation of a diverse group of virulent NDVs as an enzootic in widespread species such as pigeon can cause outbreaks in commercial poultry flocks and also failure in controlling programmes. Therefore, the constant monitoring and awareness of the virus characteristics should be considered in controlling programmes against ND in Iran.

Cell-free fetal DNA in amniotic fluid supernatant for prenatal diagnosis.

In widespread conviction, amniotic fluid is utilized for prenatal diagnosis. Amniotic fluid supernatant is usually discarded, notwithstanding being a good source of fetal DNA. The aim of the present study was to assess cell-free fetal DNA extracted from amniotic fluid supernatant for application in prenatal diagnosis such as gender determination and early diagnosis of ß-thalassemia. Samples of amniotic fluid of 70 pregnant women were collected and went through routine tests along with tests for cell-free fetal DNA from amniotic fluid supernatant. The DNA in the amniotic fluid supernatant was extracted and analyzed for gender determination by PCR and Real-time PCR. ARMS-PCR was applied to test early diagnosis of IVS II-I mutation (common ß-thalassemia mutation) and E7V mutation for sickle cell anemia using DNA extracted from the amniotic fluid supernatant. Using the cell-free fetal DNA extracted from the amniotic fluid supernatant, the sensitivity of PCR and Real-time PCR for gender detection was compared with the routine cytogenetic method. The fetus tested for sickle cell anemia and ß-thalassemia was observed to be healthy but heterozygous for IVS II-I mutation. The findings indicated that cell-free fetal DNA from amniotic fluid supernatant can be a good source of fetal DNA and be used in early prenatal diagnosis since because of its fast and accurate application. Therefore, it would be suggested that the amniotic fluid supernatant's disposal is prevented because if the tests needs to be repeated, cell-free fetal DNA extracted from the amniotic fluid supernatant can be used as an alternative source for prenatal diagnosis.

Changes in volatile composition and sensory properties of Iranian ultrafiltered white cheese as affected by blends of Rhizomucor miehei protease or camel chymosin.

The effect of using various combinations of Rhizomucor miehei protease and camel chymosin (100:0, 75:25, 50:50, 25:75, and 0:100, respectively) on volatile composition and sensory scores in Iranian ultrafiltered white cheese was studied during 90d of ripening. A solid-phase microextraction-gas chromatography-mass spectrometric method was used for determining the volatile compounds of the cheeses. Forty compounds including esters (12), acids (6), ketones (9), alcohols (3), and miscellaneous compounds (10) were identified. The main classes of volatile components in the cheeses are esters, miscellaneous compounds, and ketones. The type and concentration of the coagulants influenced both volatile composition and sensory scores of the cheeses. Principal component analysis separated the cheeses based on the use of 2 coagulants in various combinations and ripening time. The cheeses produced using higher concentrations of R. miehei were separately located on the plot compared with the cheeses produced using higher concentrations of camel chymosin. Sensory evaluation of the cheeses showed that, in general, the cheeses produced using higher concentrations of camel chymosin received higher body and texture and odor and flavor scores than the cheese produced using higher concentrations of R. miehei. In conclusion, 2 combinations of R. miehei and camel chymosin (75:25 and 25:75, respectively) can be successfully used for the production of Iranian ultrafiltered white cheese, considering the results of volatile composition and sensory analysis.

Nonspecific transcription factor binding can reduce noise in the expression of downstream proteins.

Transcription factors (TFs) interact with a multitude of binding sites on DNA and partner proteins inside cells. We investigate how nonspecific binding/unbinding to such decoy binding sites affects the magnitude and time-scale of random fluctuations in TF copy numbers arising from stochastic gene expression. A stochastic model of TF gene expression, together with decoy site interactions is formulated. Distributions for the total (bound and unbound) and free (unbound) TF levels are derived by analytically solving the chemical master equation under physiologically relevant assumptions. Our results show that increasing the number of decoy binding sides considerably reduces stochasticity in free TF copy numbers. The TF autocorrelation function reveals that decoy sites can either enhance or shorten the time-scale of TF fluctuations depending on model parameters. To understand how noise in TF abundances propagates downstream, a TF target gene is included in the model. Intriguingly, we find that noise in the expression of the target gene decreases with increasing decoy sites for linear TF-target protein dose-responses, even in regimes where decoy sites enhance TF autocorrelation times. Moreover, counterintuitive noise transmissions arise for nonlinear dose-responses. In summary, our study highlights the critical role of molecular sequestration by decoy binding sites in regulating the stochastic dynamics of TFs and target proteins at the single-cell level.

Numerical modeling of drug delivery in a dynamic solid tumor microvasculature.

The complicated capillary network induced by angiogenesis is one of the main reasons of unsuccessful cancer therapy. A multi-scale mathematical method which simulates drug transport to a solid tumor is used in this study to investigate how capillary network structure affects drug delivery. The mathematical method involves processes such as blood flow through vessels, solute and fluid diffusion, convective transport in extracellular matrix, and extravasation from blood vessels. The effect of heterogeneous dynamic network on interstitial fluid flow and drug delivery is investigated by this multi-scale method. The sprouting angiogenesis model is used for generating capillary network and then fluid flow governing equations are implemented to calculate blood flow through the tumor-induced capillary network and fluid flow in normal and tumor tissues. Finally, convection-diffusion equation is used to simulate drug delivery. Three approaches are used to simulate drug transport based on the developed mathematical method: without a vascular network, using a static vascular network, and a dynamic vascular network. The avascular approach predicts more uniform and higher drug concentration than vascular approaches since the simplified assumptions are implemented in this method. The dynamic network which uses more realistic assumptions predicts more irregular blood vessels, high interstitial pressure, and more heterogeneity in drug distribution than other two approaches.

Vitamin D replacement therapy in patients with cardiac syndrome X.

AIMS: The aim of present study was to assess whether vitamin D, with proven beneficial effects on the cardiovascular system, has any effect on angina and exercise-induced ischemia in patients with cardiac syndrome X and low serum vitamin D. METHODS: Patients with cardiac syndrome X and low serum vitamin D3 were studied before and after treatment with an intramuscular injection of vitamin D3 (300,000 units, every other week for 2 months). We determined the angina episode (per day) and several indices of exercise capacity. RESULTS: At the end of the treatment course (75±6 day), a significant increase of serum vitamin D3 occurred and was within the normal range (45±8 ng/ml) and the frequency of angina improved significantly (p=0.003). Exercise duration and maximal work capacity increased significantly (p<0.001). Maximal ST-segment depression (mm) decreased significantly (p=0.001). The calculated Duck treadmill score improved significantly (p=0.001). CONCLUSIONS: Our findings show that vitamin D replacement therapy in patients with cardiac syndrome X and vitamin D deficiency dramatically improves symptoms and signs of ischemia.