Alkali stress is an important agricultural problem that affects plant metabolism, specifically root physiology. In this study, using two rice cultivars differing in alkali resistance, we investigated the physiological and molecular responses of rice plants to alkali stress. Compared to the alkali-sensitive cultivar (SC), the alkali-tolerant cultivar (TC) maintained higher photosynthesis and root system activity under alkali stress. Correspondingly, the Na+ content in its shoots was much lower, and the contents of mineral ions (e.g., K+, NO3-, and H2PO4-) in its roots was higher than those of the SC. These data showed that the metabolic regulation of roots might play a central role in rice alkali tolerance. Gene expression differences between the cultivars were much greater in roots than in shoots. In roots, 46.5% (20 of 43) of selected genes indicated over fivefold expression differences between cultivars under alkali stress. The TC had higher root system activity that might protect shoots from Na+ injury and maintain normal metabolic processes. During adaptation of TC to alkali stress, OsSOS1 (salt overly sensitive protein 1) may mediate Na+ exclusion from shoots or roots. Under alkali stress, SC could accumulate Na+ up to toxic concentrations due to relatively low expression of OsSOS1 in shoots. It possibly harmed chloroplasts and influenced photorespiration processes, thus reducing NH4+ production from photorespiration. Under alkali stress, TC was able to maintain normal nitrogen metabolism, which might be important for resisting alkali stress., H. Wang, X. Lin, S. Cao, Z. Wu., and Obsahuje bibliografii
In the present work neonatal male and female Wistar rats were treated intraperitoneally with monosodium glutamate (MSG 2 mg/kg b.w.) or saline (controls) daily for 4 day after birth. At the age of 30 and 80 days, the alkaline phosphatase activity (AP) in the brush border of individual enterocytes, the body fat content and Lee´s index of obesity were analyzed. Microdensitometrical quantification of AP was significantly increased on day 30 in males (P<0.01) and on day 80 in MSG-treated male and female rats (P<0.001) as compared to the controls. MSG administration also increased the body fat weight and the obesity index significantly (P<0.001) in 80-day-old animals, but was without any significant effect on their food intake. Our results showed that a) neonatal MSG-treatment may significantly change the intestinal function and b) the investigation of the intestinal enzyme activities may be important in further studies on MSG-induced and other forms of obesity., Š. Mozeš, Ľ. Lenhardt, A. Martinková., and Obsahuje bibliografii
The polymorphisms of the tumor suppressor gene p53 in exon 4 (p53 BstUI) and in intron 6 (p53 MspI) have been suggested to be associated with the genetically determined susceptibility in diverse types of human cancer. In our hospital-based case-control study, we examined the allele and genotype incidence of these polymorphisms as well as their haplotype combinations in 60 brain tumor patients (27 males and 33 females) and 183 controls without malignancies. The genotype characteristics were determined by the PCR-based RFLP method using DNA extracted from peripheral blood. In this study we show that the p53 BstUI and the p53 MspI polymorphisms are not associated with increased risk of brain tumors. Thus, we conclude that the p53 BstUI and the p53 MspI polymorphic sites within the tumor suppressor gene p53 do not represent genetic determinants of susceptibility to brain tumors., E. Biroš, I. Kalina, A. Kohút, E. Bogyiová, J. Šalagovič, I. Šulla., and Obsahuje bibliografii
Leaf area estimation is an important biometrical observation recorded for evaluating plant growth in field and pot experiments. In this study, conducted in 2009, a leaf area estimation model was developed for aromatic crop clary sage (Salvia sclarea L.), using linear measurements of leaf length (L) and maximum width (W). Leaves from four genotypes of clary sage, collected at different stages, were used to develop the model. The actual leaf area (LA) and leaf dimensions were measured with a Laser Area meter. Different combinations of prediction equations were obtained from L, W, product of LW and dry mass of leaves (DM) to create linear (y = a + bx), quadratic (y = a + bx + cx2), exponential (y = aebx), logarithmic (y = a + bLnx), and power models (y = axb) for each genotype. Data for all four genotypes were pooled and compared with earlier models by graphical procedures and statistical measures viz. Mean Square Error (MSE) and Prediction Sum of Squares (PRESS). A linear model having LW as the independent variables (y = -3.4444 + 0.729 LW) provided the most accurate estimate (R 2 = 0.99, MSE = 50.05, PRESS = 12.51) of clary sage leaf area. Validation of the regression model using the data from another experiment showed that the correlation between measured and predicted values was very high (R 2 = 0.98) with low MSE (107.74) and PRESS (26.96). and R. Kumar, S. Sharma.
The accurate and nondestructive determination of individual leaf area (LA) of plants, by using leaf length (L) and width (W) measurement or combinations of them, is important for many experimental comparisons. Here, we propose reliable and simple regressions for estimating LA across different leaf-age groups of eight common evergreen broadleaved trees in a subtropical forest in Gutianshan Natural Reserve, eastern China. During July 2007, the L, W, and LA of 2,923 leaves (202 to 476 leaves for each species) were measured for model construction and the respective measurements on 1,299 leaves were used for model validation. Mean L, W, LA and leaf shape (L:W ratio) differed significantly between current and older leaves in four out of the eight species. The coefficients of one-dimension LA models were affected by leaf age for most species while those incorporating both leaf dimensions (L and W) were independent of leaf age for all the species. Therefore, the regressions encompassing both L and W (LA = a L W + b), which were independent of leaf age and also allowed reliable LA estimations, were developed. Comparison between observed and predicted LA using these equations in another dataset, conducted for model validation, exhibited a high degree of correlation (R 2 = 0.96-0.99). Accordingly, these models can accurately estimate the LA of different age groups for the eight evergreen tree species without using instruments. and L. Zhang, L. Pan.