Preoperative assessment of meningioma aggressiveness by Thallium-201 brain SPECT

Introduction: Meningioma is usually a benign brain tumor, but sometimes with aggressive course. The aim of this study was to assess the ability of 201Tl Brain SPECT to differentiate the pathologic grade of meningioma preoperatively. Methods: Thirty lesions in 28 patients were evaluated in this study. Early (20 minutes) and late (3 hours) brain SPECT images were performed and early uptake ratio (EUR), late uptake ratio (LUR) and retention index (RI) were calculated. All patients were operated and pathologic grade of tumors were defined according to World Health Organization grading system. Results: SPECT results were compared in different pathologic groups. Data analysis clarified no significant difference of EUR in benign and aggressive meningioma (P=0.2). However LUR and RI were significantly higher in aggressive tumors (P=0.001 and P=0.02, respectively). Conclusion: According to our data Tl-201 Brain SPECT with early and late imaging has 80 sensitivity and specificity to differentiate malignant from benign meningioma

Expanding networks of RNA virus evolution

In a recent BMC Evolutionary Biology article, Huiquan Liu and colleagues report two new genomes of double-stranded RNA (dsRNA) viruses from fungi and use these as a springboard to perform an extensive phylogenomic analysis of dsRNA viruses. The results support the old scenario of polyphyletic origin of dsRNA viruses from different groups of positive-strand RNA viruses and additionally reveal extensive horizontal gene transfer between diverse viruses consistent with the network-like rather than tree-like mode of viral evolution. Together with the unexpected discoveries of the first putative archaeal RNA virus and a RNA-DNA virus hybrid, this work shows that RNA viral genomics has major surprises to deliver

Assessment of left ventricular mechanical dyssynchrony by phase analysis of gated-SPECT myocardial perfusion imaging and tissue Doppler imaging: Comparison between QGS and ECTb software packages

Background: Recently, the phase analysis of gated single-photon emission computed tomography (SPECT) myocardial perfusion imaging (MPI) has become feasible via several software packages for the evaluation of left ventricular mechanical dyssynchrony. We compared two quantitative software packages, quantitative gated SPECT (QGS) and Emory cardiac toolbox (ECTb), with tissue Doppler imaging (TDI) as the conventional method for the evaluation of left ventricular mechanical dyssynchrony. Methods and Results: Thirty-one patients with severe heart failure (ejection fraction ≤35%) and regular heart rhythm, who referred for gated-SPECT MPI, were enrolled. TDI was performed within 3 days after MPI. Dyssynchrony parameters derived from gated-SPECT MPI were analyzed by QGS and ECTb and were compared with the Yu index and septal-lateral wall delay measured by TDI. QGS and ECTb showed a good correlation for assessment of phase histogram bandwidth (PHB) and phase standard deviation (PSD) (r = 0.664 and r = 0.731, P < .001, respectively). However, the mean value of PHB and PSD by ECTb was significantly higher than that of QGS. No significant correlation was found between ECTb and QGS and the Yu index. Nevertheless, PHB, PSD, and entropy derived from QGS revealed a significant (r = 0.424, r = 0.478, r = 0.543, respectively; P < .02) correlation with septal-lateral wall delay. Conclusion: Despite a good correlation between QGS and ECTb software packages, different normal cut-off values of PSD and PHB should be defined for each software package. There was only a modest correlation between phase analysis of gated-SPECT MPI and TDI data, especially in the population of heart failure patients with both narrow and wide QRS complex. © 2014, American Society of Nuclear Cardiology

Metaheuristics for Transmission Network Expansion Planning

This chapter presents the characteristics of the metaheuristic algorithms used to solve the transmission network expansion planning (TNEP) problem. The algorithms used to handle single or multiple objectives are discussed on the basis of selected literature contributions. Besides the main objective given by the costs of the transmission system infrastructure, various other objectives are taken into account, representing generation, demand, reliability and environmental aspects. In the single-objective case, many metaheuristics have been proposed, in general without making strong comparisons with other solution methods and without providing superior results with respect to classical mathematical programming. In the multi-objective case, there is a better convenience of using metaheuristics able to handle conflicting objectives, in particular with a Pareto front-based approach. In all cases, improvements are still expected in the definition of benchmark functions, benchmark networks and robust comparison criteria

Molecular characterization of a novel ssRNA ourmia-like virus from the rice blast fungus Magnaporthe oryzae

In this study we characterize a novel positive and single stranded RNA (ssRNA) mycovirus isolated from the rice field isolate of Magnaporthe oryzae Guy11. The ssRNA contains a single open reading frame (ORF) of 2,373 nucleotides in length and encodes an RNA-dependent RNA polymerase (RdRp) closely related to ourmiaviruses (plant viruses) and ourmia-like mycoviruses. Accordingly, we name this virus Magnaporthe oryzae ourmia-like virus 1 (MOLV1). Although phylogenetic analysis suggests that MOLV1 is closely related to ourmia and ourmia-like viruses, it has some features never reported before within the Ourmiavirus genus. 3' RLM-RACE (RNA ligase-mediated rapid amplification of cDNA ends) and extension poly(A) tests (ePAT) suggest that the MOLV1 genome contains a poly(A) tail whereas the three cytosine and the three guanine residues present in 5' and 3' untranslated regions (UTRs) of ourmia viruses are not observed in the MOLV1 sequence. The discovery of this novel viral genome supports the hypothesis that plant pathogenic fungi may have acquired this type of viruses from their host plants

Molecular identification of Candidatus Phytoplasma spp. associated with Sophora yellow stunt in Iran

In the spring of 2012, sophora (Sophora alopecuroides L.) plants showing symptoms of leaf yellowing, little leaves and stunting were observed in Firooz-kuh (Tehran province), Sari (Mazandaran province) and Urmia (West Azerbaijan province) in Iran. Symptomatic plants from the three locations were subjected to nested polymerase chain reaction (PCR) to amplify 16SrRNA using primer pair P1/P7 followed by primer pair R16F2n/R16R2. Th e amplicons were purifi ed, sequenced and the nucleotide sequences were analyzed by virtual restriction fragment length polymorphism (RFLP). Th e phytoplasmas associated with the yellows disease were identifi ed as members of the 16SrIX group (Candidatus Phytoplasma phoenicium) and the 16SrXII group (Candidatus Phytoplasma solani). Th e two phytoplasmas were placed in 16SrIX-C and 16SrXII-A subgroups, respectively, in constructed phylogenetic trees. Th is is the fi rst report on sophora yellows associated with Candidatus Phytoplasma phoenicium

Estimating the soil water retention curve - comparison of multiple nonlinear regression approach and random forest data mining technique

This study evaluates the performance of the random forest (RF) method on the prediction of the soil water retention curve (SWRC) and compares its performance with those of nonlinear regression (NLR) and Rosetta-based pedotransfer functions (PTFs), which has not been reported so far. Fifteen RF and NLR-based PTFs were constructed using readily-available soil properties for 223 soil samples from Iran. The general performance of RF and NLR-based PTFs was quantified by the integral root mean square error (IRMSE), Akaike’s information criterion (AIC) and coefficient of determination (R2). The results showed that the accuracy of the RF-based PTFs was significantly (P<0.05) better than the NLR-based PTFs, and that the reliability of the NLR-based PTFs was significantly (P<0.01) better than the RF-based PTFs and all of the Rosetta-based PTFs. The average values of the IRMSE, AIC and R2 of the RF method were 0.041 cm3 cm-3, -16997.7, and 0.987, and 0.053 cm3 cm-3, -15547.5, and 0.981 for the training and testing steps of all PTFs, respectively, whereas the values for the NLR method were 0.046 cm3 cm-3, -16616.4, and 0.984, and 0.048 cm3 cm-3, -16355.6, and 0.983 for the training and testing steps, respectively. The PTF5 of the RF and NLR methods, with inputs of sand and clay contents, bulk density, and the water content at field capacity and permanent wilting point, had the greatest R2 values (0.987 and 0.989, respectively), and the lowest IRMSE values (0.039 and 0.032 cm3 cm-3, respectively) compared to other PTFs for the testing step. Overall, the RF method had less reliability for the prediction of the SWRC compared to the NLR method due to overprediction, uncertainty of determination of forest scale and instability in the testing step. These findings could provide the scientific basis for further research on the RF method

Estimating Soil Water Retention Curve by Extreme Learning Machine, Radial Basis Function, M5 Tree and Modified Group Method of Data Handling Approaches

This study was conducted to assess the applicability of novel types of neural network methods (extreme learning machine (ELM), radial basis function (RBF), modified group method of data handling (M-GMDH)) and M5 tree methods for the prediction of the soil water retention curve (SWRC) and compare their performance with that of derived methods and pedotransfer functions (PTFs) of other studies for soils in Iran. Then, 15 PTFs were developed. Predictions were evaluated by the integral root mean square error (IRMSE), integral mean error (IME), Akaike's information criterion (AIC), and coefficient of determination (R2). The RBF-based PTFs were better than the M5 tree, M-GMDH, and ELM-based PTFs in terms of the IRMSE criterion in the testing step. Also, PTFs and methods developed in the present study were more reliable than other derived PTFs and methods by different researchers. The values of the IRMSE and R2 in the best PTFs (with inputs of sand, clay, total porosity and the moisture content at field capacity and permanent wilting point) of the testing data set of the RBF method were 0.037 cm3 cm−3 and 0.988, respectively. For the testing data set, the average values of the IRMSE criterion for all the PTFs of the RBF, ELM, M-GMDH, and M5 tree methods were 0.051, 0.062, 0.055, and 0.054 cm3 cm−3, respectively. Therefore, the differences were considerable only between the ELM and other methods. The IRMSE criterion results of the testing data set showed the suitability of the RBF method in the development of PTFs for the prediction of the SWRC

Grazing management, slope aspect and canopy effects on the compression characteristic of soils of the Gonbad experimental watershed in Hamedan, Iran

Arid and semiarid environments are very sensitive to unsuitable land management practices like livestock overgrazing. Animal trampling and overgrazing can cause land degradation through soil compaction, and this can be controlled by slope aspect. Soil compaction changes soil structure, reduces soil water infiltration and root penetration and decreases vegetation cover and soil organic matter. Livestock overgrazing and the slope aspect can affect many soil properties, but their effects on the confined compression curve (CCC) of soils and other land degradation indices have not been investigated so far. We studied the effects of slope aspect, grazing intensity, and sampling position on the characteristics of the CCC in Gonbad experimental watershed, Hamedan, Iran. Undisturbed and disturbed soil samples were collected at the end of the grazing season in November. The soil CCC was measured, and the Gompertz model was fitted to the measured data. The smallest void ratios, compactability, and swelling indices occurred with a southern aspect due to the greater sand content and coarser texture. Free grazing increased the soil bulk density and decreased the void ratio to decrease all of the CCC characteristics and Gompertz model coefficients (except m). Soil on a northern aspect and with no grazing improved the compression and degradation indices, and would be the best management to prevent compression and consequent land degradation. Path analysis demonstrated that topography and grazing management changed the compression characteristics, which affected land degradation strongly, by affecting the cation exchange capacity, organic matter, and textural and structural properties. In consequence, compression of rangeland soils can be mitigated by selecting suitable grazing management systems by considering topography of the region

Prediction of soil hydraulic properties by Gaussian process regression algorithm in arid and semiarid zones in Iran

The soil water retention curve (SWRC) is one of the principal soil hydraulic properties that is needed as input data in modeling water and solute transport through unsaturated soils. Field or laboratory measurement of SWRC is labor-intensive, expensive and time-consuming. Pedotransfer functions (PTFs) have been developed as an indirect method to predict soil hydraulic properties (e.g. SWRC) from more easily measured soil data by data mining tools. The novelty of the present study is the application of Gaussian process regression (GPR) algorithm as a data mining technique, to predict the SWRC, and comparing its performance with that of the multiple linear regression (MLR) and Rosetta methods, which has not been conducted so far. In this study 15 GPR and MLRbased PTFs were developed to predict the parameters of the van Genuchten model from different combinations of readily available properties of 223 soil samples that were taken from six provinces of Iran. The k-fold (k = 20) cross validation approach was utilized to obtain training and testing data sets for each PTF. The predictions of the GPR and MLR-based PTFs were evaluated by different criteria. The GPR-based PTFs had greater accuracy and reliability than MLR method in predicting SWRC according to integral root mean square error (IRMSE) criterion. However, the differences were not significant (P 0.05) in the testing step, but the reliability of both methods were significantly (P < 0.05) better than Rosetta-based PTFs. The covariance functions of GPR method can be effectively fitted by kernels with different features for modeling complex relationships. The GPR method can be considered as a competitive alternative to develop parametric-PTFs