Ultrastructural localization of carbohydrates in Reichert's membrane of the mouse

In the present investigation, we examined the role of trophoblast and parietal endoderm cells in the synthesis of carbohydrate-containing components of Reichert's membrane. To eliminate the function of Reichert's membrane as a filter between maternal and embryonal tissues we carried out our examination under in vitro conditions. Parietal yolk sac from mouse embryos on day 9 post coitum (p.c.) were cultivated for 0 to 5 days. Because tannic acid enables a complex formation between carbohydrates and osmium we chose the fixation with this acid for the ultrastructural study. Electron microscopy showed that for assembly of Reichert's membrane, trophoblast cells produce and then release components that were detected as tannic acid-positive granules both in the Reichert's membrane and in the vacuoles of the trophoblast cells. To localize specific carbohydrates we used postembedding-gold-lectin histochemistry on LR-Gold^R-embedded tissues. Strong binding sites for the lectins WGA (Triticum vulgare), RCA I (Ricinus communis) and Con A (Canavalia ensiformis) were observed in Reichert's membrane and trophoblast cells but not in the parietal endoderm cells. The LTA (Lotus tetragonolobus)-binding pattern was positive in the membrane and its adjacent cells but that of the LFA (Limax flavus) was negative in the parietal endoderm cells and very weak in Reichert's membrane and trophoblast cells. Our results demonstrate that trophoblast cells are involved in the construction of Reichert's membrane through the production and release of specific glycoconjugates.     

Synthesis and anticonvulsant activity of new 2-substituted-5- [2-(2-fluorophenoxy)phenyl]-1,3,4-oxadiazoles and 1,2,4-triazoles

A series of new 2-substituted-5-[2-(2-fluorophenoxy)phenyl]-1,3,4-oxadiazoles has been synthesized and screened for their anticonvulsant activities. Compound 3 shows considerable anticonvulsant activity both in PTZ and MES models. It seems that this effect is mediated by benzodiazepine receptors and other unknown mechanism, respectively.     

Seed plant phylogeny: gnetophytes are derived conifers and a sister group to Pinaceae

The phylogenetic position of gnetophytes has long been controversial. We sequenced parts of the genes coding for the largest subunit of nuclear RNA polymerase I, II, and III and combined these sequences with those of four chloroplast genes, two mitochondrial genes, and 18S rRNA genes to address this issue. Both maximum likelihood and maximum parsimony analyses of the sites not affected by high substitution levels strongly support a phylogeny where gymnosperms and angiosperms are monophyletic, where cycads are at the base of gymnosperm tree and are followed by ginkgos, and where gnetophytes are grouped within conifers as the sister group of pines. The evolution of several morphological and molecular characters of gnetophytes and conifers will therefore need to be reinterpreted.     

Adaptive neuro-fuzzy inference system: Estimation of soil aggregates stability

In present study, the capabilities of multiple linear regression (MLR) and adaptive neuro-fuzzy inference system (ANFIS) in developing pedotransfer functions (PTFs) for estimating geometric mean diameter (GMD) and mean weight diameter (MWD), from routine soil properties and combination of routine soil properties and fractal dimension of aggregates were evaluated. For this reason 101 samples were collected form the Northwest of Iran and some their properties such as soil texture, pH, cation exchange capacity (CEC), and organic matter (OM), fractal dimension of aggregates between number-diameter (Dn), mass-diameter (Dmt), and bulk density-diameter (Dmy) were determined and used as an input variables for determining of mean weight diameter (MWD) and geometric mean diameter (GMD) by MLR and ANFIS PTFs. Results showed that the application of fractal dimension of aggregates as a predictor in two methods improved the accuracy of PTFs. As well as, results showed that ANFIS have greater potential for determination of the relationships between soil aggregate stability indices and other soil properties in compared with MLR. Therefore using of adaptive neuro-fuzzy inference system (ANFIS) in developing pedotransfer functions is recommended.     

Structure-activity study of phosphoramido acid esters as acetylcholinesterasf inhibitors

Phosphoramido acid esters (CH₃)₂NP(O)X(p-OC₆H₄-CH₃) (containing P-Cl (1), P-O (2), P-F (3), P-CN (5), and P-N (4,6) bonds, X for 2, 4 and 6 is OCH₃, (C₂H₅)₂N and morpholin) have been synthesized to investigate the structure-activity study of AChE enzyme inhibition, through the parameters logP, δ³¹P and IC₅₀. After their characterization by ³¹P, ³¹P{¹H}, ¹³C, ¹H NMR, IR and mass spectroscopy, the parameters logP and δ³¹P (³¹P chemical shift in NMR) were used to evaluated the lipophilicity and electronical properties. The ability of compounds to inhibit human AChE was predicted by PASS software (version 1.193), and experimentally evaluated by a modified Ellman's assay.     

Hemodynamics-driven mathematical model of first and second heart sound generation

We propose a novel, two-degree of freedom mathematical model of mechanical vibrations of the heart that generates heart sounds in CircAdapt, a complete real-time model of the cardiovascular system. Heart sounds during rest, exercise, biventricular (BiVHF), left ventricular (LVHF) and right ventricular heart failure (RVHF) were simulated to examine model functionality in various conditions. Simulated and experimental heart sound components showed both qualitative and quantitative agreements in terms of heart sound morphology, frequency, and timing. Rate of left ventricular pressure (LV dp/dt_max) and first heart sound (S1) amplitude were proportional with exercise level. The relation of the second heart sound (S2) amplitude with exercise level was less significant. BiVHF resulted in amplitude reduction of S1. LVHF resulted in reverse splitting of S2 and an amplitude reduction of only the left-sided heart sound components, whereas RVHF resulted in a prolonged splitting of S2 and only a mild amplitude reduction of the right-sided heart sound components. In conclusion, our hemodynamics-driven mathematical model provides fast and realistic simulations of heart sounds under various conditions and may be helpful to find new indicators for diagnosis and prognosis of cardiac diseases.New & noteworthyTo the best of our knowledge, this is the first hemodynamic-based heart sound generation model embedded in a complete real-time computational model of the cardiovascular system. Simulated heart sounds are similar to experimental and clinical measurements, both quantitatively and qualitatively. Our model can be used to investigate the relationships between heart sound acoustic features and hemodynamic factors/anatomical parameters.     

Improving ECG classification accuracy using an ensemble of neural network modules

This paper illustrates the use of a combined neural network model based on Stacked Generalization method for classification of electrocardiogram (ECG) beats. In conventional Stacked Generalization method, the combiner learns to map the base classifiers' outputs to the target data. We claim adding the input pattern to the base classifiers' outputs helps the combiner to obtain knowledge about the input space and as the result, performs better on the same task. Experimental results support our claim that the additional knowledge according to the input space, improves the performance of the proposed method which is called Modified Stacked Generalization. In particular, for classification of 14966 ECG beats that were not previously seen during training phase, the Modified Stacked Generalization method reduced the error rate for 12.41% in comparison with the best of ten popular classifier fusion methods including Max, Min, Average, Product, Majority Voting, Borda Count, Decision Templates, Weighted Averaging based on Particle Swarm Optimization and Stacked Generalization.