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.     

Colonization and nitrogenase activity of Triticum aestivum (cv. Baccross and Mahdavi) to the dual inoculation with Azospirillum brasilense and Rhizobium meliloti plus 2,4-D

The potential enhancement of root colonization and nitrogenase activity of wheat cultivars (Baccross and Mahdavi) was studied with application of two Azospirillum brasilense strains (native and Sp7) co-inoculated with two Rhizobium meliloti strains (native and DSMZ 30135). The results indicated that the colonization was different due to the strains and cultivars of wheat were used. Native A. brasilense colonized wheat root better than Sp7 strain. However, Baccross cv. reacted better with native Azospirillum compared to Mahdavi cv. which reacted better with Sp7. When plants inoculated with dual inoculants (SP7 with standard Rhizobium), the colonization of Azospirillum were increased significantly (from 1.67 x 10(5) to 22 x 10(5) cfu g(-1) FW for Baccras cv. and 3.67 x 10(5) to 26 x 10(5) cfu g(-1) FW for Mahdavi cultivar). When the standard Rhizobium as co-inoculants changed to the native Rhizobium, the colonization of Azospirillum was higher when compared to the single inoculants but was almost the same when compared to the standard Rhizobium. When the standard or native strains of Rhizobium used as single inoculation of wheat roots, the number of Rhizobium in the wheat roots were not changed significantly. However, when plants co-inoculated with Rhizobium and Azospirillum, the colonization of Rhizobium was increased. Co-inoculation of standard strain of R. melilot with A. brasilense Sp7 showed that the colonization of Rhizobium were increased from 0.67 x 10(5) to 21 x 10(5) cfu g(-1) FW for Baccross cv. and 0.33 x 10(5) to 18 x 10(5) cfu g(-1) FW for Mahdavi cv. This behavior was the same when inoculation of Rhizobium was happened with the native one. In dual inoculation, the highest nitrogenase activity was measured in combination of the local strains (native A. brasilense with the native R. meliloti) and the lower one belongs to the combination of standard strains (Sp7 with standard R. meliloti). The difference in nirtogenase activity for different cultivars of wheat with Sp7 and standard Rhizobium is not significant but the difference for Sp7 strain plus native Rhizobium is significant (p > 0.05). However, the differences were not significant (p < 0.05) for nitrogenase activity in bacterial tubes, the difference for nitrogenase activity of co-inoculated plants with combination of Sp7 and Rhizobium either standard or native were significantly different.     

Comparison of three models describing bromide transport affected by different soil structure types

This study was conducted to investigate the effects of soil structure on bromide (Br) transport through three soils with granular, prismatic, and single-grain structures. The breakthrough curve (BTC) of the single-grain structure was sigmoidal, symmetrical and similar to a piston flow, showing the dominance of mass flow. In contrast, the BTCs of the granular and prismatic structures were initially steep, becoming more gradual at high pore volumes (PVs). The stable structure and preferential pathways caused the early breakthrough of Br in the leachate of these columns. The convection–dispersion equation (CDE), mobile–immobile water (MIM), and dual-permeability (DP) models were fitted to observed data using the program HYDRUS-1D. The equilibrium transport model (CDE) was not as successful as non-equilibrium (MIM and DP) models in describing the Br transport in prismatic and granular soil columns, although it was able to describe the Br transport in single-grain column well. Overall, the results demonstrated the importance of soil structure in pollutant transport through soils.     

Growth curve analyses in selected duck lines.

1. Growth patterns of male ducks from 4 lines (lines A, B, C and D) selected for market weight were analysed and compared to growth patterns of ducks in the respective line 7 generations earlier. Growth curves were analysed using procedures derived from the Weibull sigmoidal function and the linear-linear relative growth rate model and simple allometry. 2. The ducks were fed ad libitum under 24-h lighting throughout the experiment. At weekly intervals from the time of hatch through 70 d of age, 16 ducks from each line were killed to determine body, carcase, breast-muscle, leg and thigh-muscle, and abdominal fat weights. 3. Line A was the heaviest line, followed by line B, line C and line D. However, body weight, carcase weight and breast-muscle weight at 49 d of age were not significantly different between lines A and B. After 7 generations of selection, the breast-muscle yield was increased to >19% and the abdominal fat percent was reduced to <1.4% in all lines. 4. The Weibull growth curve analysis of body weight showed an increase in the asymptotes during selection, while the age of the inflection point remained constant in all lines (21.3 to 26.0 d). For breast-muscle growth, ducks reached the inflection point 12.8 to 14.3 d later than for body weight. Between line A and line B, asymptotes for body weight, asymptotes for breast-muscle weight and allometric growth coefficients of breast muscle and leg and thigh muscles from 14 to 49 d were not significantly different. 5. The relative growth rate model discriminated body and breast-muscle growth patterns of line A and line B. The initial decline in the relative body growth rate was less and the time to reach the transition was longer in line A than line B. On the other hand, the initial decline in the relative breast-muscle growth rate was greater in line A than line B.     

Comparison of distribution of virulence determinants in clinical and environmental isolates of Vibrio cholera

Background: The virulence of a pathogenic Vibrio cholerae is dependent on a discrete set of genetic determinants. In this study, we determined the distribution of virulence determinants among the clinical and environmental isolates of V. cholerae. Methods: The antibiotic resistance profiles of the isolates were determined using standard disk diffusion assay. PCR assay was performed to analyze the presence of toxin genes of ctx, zot and ace. The composition of cholera toxin encoding element (CTX) region flanking of the V. cholerae isolates was also analyzed. Results: All of the clinical isolates (100%) showed a complete set of virulence genes and also the attachment site of the filamentous bacteriophage CTXphi. None of the environmental isolates contained the virulence genes and the attachment site of the CTXphi. Analysis of the flanking regions including the toxin-linked cryptic element and repeat in toxin genes revealed their integrity in the clinical isolates while in the environmental isolates they were absent or contained incomplete sequences. Comparison of the antibiotic resistance assay of the environmental and clinical isolates showed a significant difference in the resistance profiles of the isolates obtained from the two sites. High rates of resistance to co-trimoxosol, streptomycin and chloramphenicol were found with clinical isolates. Conclusion: The absence of all virulence determinants in the environmental strains may suggest that certain ecological features must be present for V. cholerae to acquire a complete set of virulence determinants and to turn them into pathogenic strains.     

Effect of Metasystox-R on marine Nitrosomonas sp. as a nitrification inhibitor

Metasystox-R is a systemic soluble liquid insecticide for the control of aphids on brassica vegetable crops, cotton and lupins and it is possible enter to the marine environment and may be have a hazard effects for the marine organisms and nitrification processes. Effect of Metasystox-R on ammonia oxidizing activity by marine Nitrosomonas sp. was investigated by determining nitrification inhibitor assay in the cell suspension. Results showed that 8 microg mL(-1) of Metasystox-R with PI50 = 4.48 significantly inhibited nitrite production by marine Nitrosomonas sp. These results suggested marine Nitrosomonas sp. may be one of the target bacteria which was inhibitor and decreasing nitrification in the marine environment.     

Computer simulation of the interactions of glyphosate with metal ions in phloem

Essential nutrients such as trace metal ions, amino acids, and sugars are transported in the phloem from leaves to other parts of the plant. The major chelating agents in phloem include nicotianamine, histidine, cysteine, glutamic acid, and citrate. A computer model for the speciation of metal ions in phloem has been used to assess the degree to which the widely used herbicide glyphosate binds to Fe(3+), Fe(2+), Cu(2+), Zn(2+), Mn(2+), Ca(2+), and Mg(2+) in this fluid over the pH range of 8 to 6.5. The calculations show that glyphosate is largely unable to compete effectively with the biological chelating agents in phloem. At a typical phloem pH of 8, 1.5 mM glyphosate binds 8.4% of the total Fe(3+), 3.4% of the total Mn(2+), and 2.3% of the total Mg(2+) but has almost no effect on the speciation of Ca(2+), Cu(2+), Zn(2+), and Fe(2+). As the pH decreases to 6.5, there are some major shifts of the metal ions among the biological chelators, but only modest increases in glyphosate binding to 6% for Fe(2+) and 2% for Zn(2+). The calculations also indicate that over 90% of the glyphosate in phloem is not bound to any metal ion and that none of the metal-glyphosate complexes exceed their solubility limits.     

新疆鼓藻属植物（Cosmarium Cord.）新记录种

乌鲁木齐达坂城地区是新疆湿地分布比较集中的地区之一,包括河流、沼泽、湖泊和池塘等。2010年7-8月,先后2次在该地区采集藻类标本,在对标本鉴定过程中,发现新疆鼓藻属新记录有6种,分别为双眼鼓藻（Cosmarium bioculatum）、扁鼓藻（C.depressum）、丘凸鼓藻（C.ochthodes）、厚皮鼓藻（C.pachydermum）、斑点鼓藻（C.punctulatum）和直角鼓藻（C. rectangulare）,并描述了其形态学特征。这些新记录的发现,丰富了新疆鼓藻属植物的研究资料。     

Modeling of maximum dry density and optimum moisture content of stabilized soil using artificial neural networks

This study considers the use of artificial neural networks (ANNs) to predict the maximum dry density (MDD) and optimum moisture content (OMC) of soil‐stabilizer mix. Multilayer perceptron (MLP), one of the most widely used ANN architectures in the literature, is utilized to construct comprehensive and accurate models relating the MDD and OMC of stabilized soil to the properties of natural soil such as particle‐size distribution, plasticity, linear shrinkage, and the type and quantity of stabilizing additives. Five ANN models are constructed using different combinations of the input parameters. Two separate sets of ANN prediction models, one for MDD and the other for OMC, and also a combined ANN model for multiple outputs are developed using the potentially influential input parameters. Relative‐importance values of various inputs of the models are calculated to determine the significance of each of the predictor variables to MDD and OMC. Inferring the most relevant input parameters based on Garson's algorithm, modified ANN models are separately developed for MDD and OMC. The modified ANN models are utilized to introduce explicit formulations of MDD and OMC. A parametric study is also conducted to evaluate the sensitivity of MDD and OMC due to the variation of the most influencing input parameters. A comprehensive set of data including a wide range of soil types obtained from the previously published stabilization test results is used for training and testing the prediction models. The performance of ANN‐based models is subsequently analyzed and compared in detail. The results demonstrate that the accuracy of the proposed models is satisfactory as compared to the experimental results.