Introduction: Arterial and venous thromboses contribute to significant morbidity and mortality rate, thus an anti- thrombotic agent is needed for prevention and treatment of thrombosis. Ajwa dates (Phoenix dactylifera L.) report- edly contain a high level of salicylic acid which is a compound responsible for anticoagulation via antagonism of vitamin K. The present study was designed to assess coagulation activities in human plasma treated with Ajwa date extracts in vitro. Methods: Platelet-poor plasma samples from 27 donors were treated with ethanol crude date extract (ET) or aqueous crude date extract (AQ) of Ajwa dates at different concentrations to generate the following seven test groups from each donor: control (normal saline), ET-I (0.1 g/mL), ET-II (0.5 g/mL), ET-III (1.0 g/mL), AQ-I (0.1 g/ mL), AQ-II (0.5 g/mL) and AQ-III (1.0 g/mL). In vitro coagulation activities of Ajwa dates were assessed based on prothrombin time (PT, an assessment of extrinsic coagulation pathway), activated partial thromboplastin time (APTT, an assessment of the intrinsic coagulation pathway), and thrombin time (TT, an evaluation of level and function of fibrinogen). Results: A very significant prolongation of PT, APTT and TT were observed for the ET-II and ET-III groups and very significant prolongation of PT and TT was observed for the AQ-II and AQ-III groups. Significant prolonga- tion of TT was observed in the AQ-I group. Conclusion: In conclusion, Ajwa date extracts had an anticoagulation effect on human plasma.
Visible and near infrared spectroscopy is a non-destructive, green, and rapid technology that can be utilized to estimate the components of interest without conditioning it, as compared with classical analytical methods. The objective of this paper is to compare the performance of artificial neural network (ANN) (a nonlinear model) and principal component regression (PCR) (a linear model) based on visible and shortwave near infrared (VIS-SWNIR) (400-1000 nm) spectra in the non-destructive soluble solids content measurement of an apple. First, we used multiplicative scattering correction to pre-process the spectral data. Second, PCR was applied to estimate the optimal number of input variables. Third, the input variables with an optimal amount were used as the inputs of both multiple linear regression and ANN models. The initial weights and the number of hidden neurons were adjusted to optimize the performance of ANN. Findings suggest that the predictive performance of ANN with two hidden neurons outperforms that of PCR.
Rice (Oryza sativa L.) blast disease is one of the most destructive rice diseases in the world. The fungal pathogen, Magnaporthe oryzae, is the causal agent of rice blast disease. Development of resistant cultivars is the most preferred method to achieve sustainable rice production. However, the effectiveness of resistant cultivars is hindered by the genetic plasticity of the pathogen genome. Therefore, information on genetic resistance and virulence stability are vital to increase our understanding of the molecular basis of blast disease resistance. The present study set out to elucidate the resistance pattern and identify potential simple sequence repeat markers linked with rice blast disease. A backcross population (BC2F1), derived from crossing MR264 and Pongsu Seribu 2 (PS2), was developed using marker-assisted backcross breeding. Twelve microsatellite markers carrying the blast resistance gene clearly demonstrated a polymorphic pattern between both parental lines. Among these, two markers, RM206 and RM5961, located on chromosome 11 exhibited the expected 1:1 testcross ratio in the BC2F1 population. The 195 BC2F1 plants inoculated against M. oryzae pathotype P7.2 showed a significantly different distribution in the backcrossed generation and followed Mendelian segregation based on a single-gene model. This indicates that blast resistance in PS2 is governed by a single dominant gene, which is linked to RM206 and RM5961 on chromosome 11. The findings presented in this study could be useful for future blast resistance studies in rice breeding programs.
Among 120 simple sequence repeat (SSR) markers, 23 polymorphic markers were used to identify the segregation ratio in 320 individuals of an F(2) rice population derived from Pongsu Seribu 2, a resistant variety, and Mahsuri, a susceptible rice cultivar. For phenotypic study, the most virulent blast (Magnaporthe oryzae) pathotype, P7.2, was used in screening of F(2) population in order to understand the inheritance of blast resistance as well as linkage with SSR markers. Only 11 markers showed a good fit to the expected segregation ratio (1:2:1) for the single gene model (d.f. = 1.0, P < 0.05) in chi-square (χ(2)) analyses. In the phenotypic data analysis, the F(2) population segregated in a 3:1 (R:S) ratio for resistant and susceptible plants, respectively. Therefore, resistance to blast pathotype P7.2 in Pongsu Seribu 2 is most likely controlled by a single nuclear gene. The plants from F(2) lines that showed resistance to blast pathotype P7.2 were linked to six alleles of SSR markers, RM168 (116 bp), RM8225 (221 bp), RM1233 (175 bp), RM6836 (240 bp), RM5961 (129 bp), and RM413 (79 bp). These diagnostic markers could be used in marker assisted selection programs to develop a durable blast resistant variety.
Blast caused by the fungus Magnaporthe oryzae is a significant disease threat to rice across the world and is especially prevalent in Malaysia. An elite, early-maturing, high-yielding Malaysian rice variety, MR263, is susceptible to blast and was used as the recurrent parent in this study. To improve MR263 disease resistance, the Pongsu Seribu 1 rice variety was used as donor of the blast resistance Pi-7(t), Pi-d(t)1 and Pir2-3(t) genes and qLN2 quantitative trait locus (QTL). The objective was to introgress these blast resistance genes into the background of MR263 using marker-assisted backcrossing with both foreground and background selection.