Flow cytometric assessment of DNA double-strand break and repair kinetics in prediction of intrinsic radiosensitivity.

Objectives: To enhance the efficiency of radiotherapy (RT), implementation of individual-based treatment is essential. In this way, determining individual intrinsic radiosensitivity (IRS) can be useful to achieve minimal adverse effects of RT. The present study aimed to identify IRS of breast cancer (BC) patients through determination of radiation-induced DNA double-strand breaks (DSBs), repair kinetics, and acute normal tissue complications induced by RT. Materials and Methods: DSBs induction and its repair kinetics in 50 BC patients' lymphocytes were analyzed by flow cytometric analysis of H2AX Ser-139 phosphorylation at 30 min, 3 and 24 hr after in vitro irradiation. In vivo skin dosimetry was done by GAFChromic films and acute skin toxicity was scored by radiation oncologists according to the criteria of Radiation Therapy and Oncology Group (RTOG) in all patients with similar prescribed treatment. Results: The average surface dose for patients ranged from 0.92 to 1.9 Gy and correlation analysis showed no significant relationship with weekly acute skin reactions. Formation of γH2AX after 30 min, slope of dose-response curve and repair kinetics of DSBs after 3 and 24 hr (intrinsic radiosensitivity) were significantly correlated with the RTOG scores following irradiation (clinical radiosensitivity) (r=0.48 and P-value<0.0001, r=0.72 and P-value<0.0001, r=0.48 and P-value<0.001, and finally r=0.53 and P-value<0.001, respectively; (using Pearson's correlation test). Conclusion: Flow cytometric analysis of DNA DSBs by γH2AX measurement has the potential to be developed into a clinical predictor for identifying the overreactor patients prior to RT. Our result suggests that the slope-related quantity based on the linear pattern of the dose-response curve has the merit to predict overreactor patients with a sensitivity of 89% and a specificity of 94%.

Comparative assessment of proliferation and immunomodulatory potential of Hypericum perforatum plant and callus extracts on mesenchymal stem cells derived adipose tissue from multiple sclerosis patients.

BACKGROUND: Mesenchymal stem cells-derived adipose tissue (AT-MSCs) are recognized for the treatment of inflammatory diseases including multiple sclerosis (MS). Hypericum perforatum (HP) is an anti-inflammatory pharmaceutical plant with bioactive compounds. Plant tissue culture is a technique to improve desired pharmacological potential. The aim of this study was to compare the anti-inflammatory and proliferative effects of callus with field-growing plant extracts of HP on AT-MSCs derived from MS patients. MATERIALS AND METHODS: AT-MSCs were isolated and characterized. HP callus was prepared and exposure to light spectrum (blue, red, blue-red, and control). Total phenols, flavonoids, and hypericin of HP callus and plant extracts were measured. The effects of HP extracts concentrations on proliferation were evaluated by MTT assay. Co-culture of AT-MSCs: PBMCs were challenged by HP plant and callus extracts, and Tregs percentage was assessed by flow cytometry. RESULTS: Identification of MSCs was performed. Data showed that blue light could stimulate total phenols, flavonoids, and hypericin. MTT test demonstrated that plant extract in concentrations (0.03, 1.2, 2.5 and 10 µg/ml) and HP callus extract in 10 µg/ml significantly increased. Both HP extracts lead to an increase in Tregs percentage in all concentrations. In particular, a comparison between HP plant and callus extracts revealed that Tregs enhanced 3-fold more than control groups in the concentration of 10 µg/ml callus. CONCLUSIONS: High concentrations of HP extracts showed effectiveness on AT-MSCs proliferation and immunomodulatory properties with a certain consequence in callus extract. HP extracts may be considered as supplementary treatments for the patients who receiving MSCs transplantation.

Comparative assessment of immunomodulatory, proliferative, and antioxidant activities of crocin and crocetin on mesenchymal stem cells.

Saffron (Crocus sativus L) is a well-known spice with active pharmacologic components including crocin, crocetin, safranal, and picrocrocin. Similar to crocin/crocetin, mesenchymal stem cells (MSCs) have been shown to display immunomodulatory and antioxidant properties, which could be beneficial in treatment of various diseases. In the current study, we have evaluated the effects of crocin and crocetin on the functions of MSCs. We used the 3-(4,5-dimethyl-2-thiazolyl)-2,5-diphenyl-2H-tetrazolium bromide assay to evaluate MSCs proliferation, and flow cytometry assay to measure the percentage of apoptotic MSCs and Tregs populations. Furthermore, we used the real-time polymerase chain reaction method to quantify messenger RNA (mRNA) expression of inflammatory and anti-inflammatory cytokines. Antioxidant assay was employed to quantify antioxidant parameters including nitric oxide and malondialdehyde levels besides superoxide dismutase activity. Our findings indicated that both crocin and crocetin at low concentrations (2.5 and 5 µM) exhibited significant effects on increasing MSCs viability and on protecting them against apoptosis-induced death. Furthermore, crocin and crocetin at low concentrations (2.5 and 5 µM) displayed a better antioxidant function. Moreover, increased Treg population was observed at lower doses. In addition, crocin/crocetin at low concentrations caused an elevation in mRNA expression of anti-inflammatory cytokines (transforming growth factor-ß, interleukin-10 [IL-10], and IL-4), while at higher doses (25 and 50 µM) they led to lowering inflammatory cytokines (IL-1ß, IL-6, IL-17, and interferon gamma). Altogether, both crocin and crocetin at lower concentrations exhibited more efficacies on MSCs with a better effect toward crocin. It seems that crocin and crocetin may be considered as complementary treatments for the patients who undergo MSCs transplantation.

Assessment of 1,25-dihydroxyvitamin D3 effects on Treg cells in a mouse model of systemic lupus erythematosus.

CONTEXT: Systemic lupus erythematosus (SLE) is a chronic autoimmune disease which is characterized by the presence of auto-reactive T cell and anti-ds DNA antibodies. Treg cells are crucial for maintaining immunologic self-tolerance and are shown to be reduced in SLE patients. 1,25-Dihydroxyvitamin D3 has immunomedulatory effects on the immune system and has recently received substantial attention. OBJECTIVE: In this study we evaluated the effects of 1,25-dihydroxyvitamin D3 on Treg cells and related cytokines in lupus-like induced mice model. MATERIALS AND METHODS: Female Balb/c mice were divided into four groups: Group one: injected with PBS and Freund's adjuvant; Group two: injected with non-activated chromatin; Group three: Lupus-like disease was induced with activated chromatin; Group four: Mice were initially treated for two weeks with 1,25-dihydroxyvitamin D3 and then lupus-like disease was induced. Group five: Four mice from group one were treated with 1,25-dihydroxyvitamin D3 for two weeks after disease establishment. Ten weeks after the last injection the mice were killed and spleens were studied for Treg percentages and expression of cytokine genes. RESULTS: We found that treatment with 1,25-dihydroxyvitamin D3 reduces IL-6 and IL-10 mRNA expression and increases TGF-ß and Foxp3 mRNA expression levels, and also enhances spleen Treg percentage. CONCLUSIONS: The remarkable reduction of IL-6 and IL-10 gene expressions, significant enhancement of TGF-ß and Foxp3 gene expressions, along with an increase in Treg cell population after oral 1,25-dihydroxyvitamin D3 administration suggest a possible role for this vitamin as a prophylactic supplement in SLE.

Comparison of two data mining techniques in labeling diagnosis to Iranian pharmacy claim dataset: artificial neural network (ANN) versus decision tree model.

BACKGROUND: This study aimed to evaluate and compare the prediction accuracy of two data mining techniques, including decision tree and neural network models in labeling diagnosis to gastrointestinal prescriptions in Iran. METHODS: This study was conducted in three phases: data preparation, training phase, and testing phase. A sample from a database consisting of 23 million pharmacy insurance claim records, from 2004 to 2011 was used, in which a total of 330 prescriptions were assessed and used to train and test the models simultaneously. In the training phase, the selected prescriptions were assessed by both a physician and a pharmacist separately and assigned a diagnosis. To test the performance of each model, a k-fold stratified cross validation was conducted in addition to measuring their sensitivity and specificity. RESULT: Generally, two methods had very similar accuracies. Considering the weighted average of true positive rate (sensitivity) and true negative rate (specificity), the decision tree had slightly higher accuracy in its ability for correct classification (83.3% and 96% versus 80.3% and 95.1%, respectively). However, when the weighted average of ROC area (AUC between each class and all other classes) was measured, the ANN displayed higher accuracies in predicting the diagnosis (93.8% compared with 90.6%). CONCLUSION: According to the result of this study, artificial neural network and decision tree model represent similar accuracy in labeling diagnosis to GI prescription.

Assessment of gastric cancer survival: using an artificial hierarchical neural network.

This study is designed to assess the application of neural networks in comparison to the Kaplan-Meier and Cox proportional hazards model in the survival analysis. Three hundred thirty gastric cancer patients admitted to and surgically treated were assessed and their post-surgical survival was determined. The observed baseline survival was determined with the three methods of Kaplan-Meier product limit estimator, Cox and the neural network and results were compared. Then the binary independent variables were entered into the model. Data were randomly divided into two groups of 165 each to test the models and assess the reproducibility. The Chi-square test and the multiple logistic model were used to ensure the groups were similar and the data was divided randomly. To compare subgroups, we used the log-rank test. In the next step, the probability of survival in different periods was computed based on the training group data using the Cox proportional hazards and a neural network and estimating Cox coefficient values and neural network weights (with 3 nodes in hidden layer). Results were used for predictions in the test group data and these predictions were compared using the Kaplan-Meier product limit estimator as the gold standard. Friedman and Kruskal-Wallis tests were used for comparisons as well. All statistical analyses were performed using SPSS version 11.5, Matlab version 7.2, Statistica version 6.0 and S_PLUS 2000. The significance level was considered 5% (alpha = 0.05). The three methods used showed no significance difference in base survival probabilities. Overall, there was no significant difference among the survival probabilities or the trend of changes in survival probabilities calculated with the three methods, but the 4 year (48th month) and 4.5 year (54th month) survival rates were significantly different with Cox compared to standard and estimated probabilities in the neural network (p < 0.05). Kaplan-Meier and Cox showed almost similar results for the baseline survival probabilities, but results with the neural network were different: higher probabilities up to the 4th year, then comparable with the other two methods. Estimates from Cox proportional hazards and the neural network with three nodes in hidden layer were compared with the estimate from the Kaplan-Meier estimator as the gold standard. Neither comparison showed statistically significant differences. The standard error ratio of the two estimate groups by Cox and the neural network to Kaplan-Meier were no significant differences, it indicated that the neural network was more accurate. Although we do not suggest neural network methods to estimate the baseline survival probability, it seems these models is more accurately estimated as compared with the Cox proportional hazards, especially with today's advanced computer sciences that allow complex calculations. These methods are preferable because they lack the limitations of conventional models and obviate the need for unnecessary assumptions including those related to the proportionality of hazards and linearity.

Report: The assessment of hospital waste management:a case study in Tehran.

Hospital waste management is an important process that must be dealt with diligently. The management of hazardous waste material requires specific knowledge and regulations and it must be carried out by specialists in the field. In this cross-sectional study, we assessed the main stages of hospital waste management including separation, containment, removal and disposal of waste materials in public hospitals affiliated with Tehran University of Medical Sciences (TUMS). We selected 108 units of six hospitals (three general hospitals and three subspecialty hospitals) from those hospitals supervised by TUMS using the cluster sampling method. The measurement was conducted through a questionnaire and direct observation by researchers. Association analysis was done by statistical tests; Fisher exact test and chi-squared using SPSS software. According to the results obtained by the questionnaire, most of the studied wards scored moderately in terms of quality of their performance in all stages of waste management. About one-fifth of the wards were suffering from poor management of their medical waste and only a minority of wards obtained good scores for managing their waste materials. The findings also revealed significant associations between temporary waste storage and collection and the level of education of the managers (P = 0.040, P = 0.050, respectively). In summary, the study indicated a moderate management in all processes of separation, collection, containment, removal and disposal of waste materials in hospitals with several observed problems in the process.

Assessment of the immune system activity in Iranian patients with Major Depression Disorder (MDD).

BACKGROUND: Major Depression Disorder (MDD) is a common disorder with prevalence of 15% among men and up to 25% among women. In recent years the association of immune system alterations and MDD has been investigated. Assessments of immunologic and inflammatory responses in these patients enhance our knowledge of the etiology and pathogenesis of this disease. OBJECTIVE: To investigate the changes in immunoglobulin and cytokine serum levels and lymphocyte subsets in patients with MDD. METHODS: We studied 37 adult patients with MDD, diagnosed based on DSM-IV diagnostic criteria, and 15 healthy controls matched with the patients. Plasma concentration of interleukin-4 (IL-4), IL-10, TNF alpha, and IFN gamma were measured by ELISA and serum immunoglobulins by SRID. Total number of NK cells (CD16 and CD56), B cells (CD19), and T cells (CD8, CD4, and CD3) were determined by flow cytometry. RESULTS: We found no significant differences in plasma concentration of IL-4, IL-10, TNF-alpha, IFN-gamma, and immunoglobulins as well as total number of NK cells, B cells, and T cells between major depressed patients and healthy control subjects. CONCLUSION: We conclude that in our patients, there were no significant differences in immune system activity between MDD patients and controls.