Assessment of Different Traits to Evaluate Genetic Divergence in Some Wheat (<i>Triticum aestivum</i>L.) Genotypes under Late Sowing Condition

The research work was undertaken to identify the extent of genetic diversity in different parameters of wheat related to heat tolerance mechanism. Performances of currently available 25 spring wheat genotypes were studied at the Regional Wheat Research Institute, Shyampur, Rajshahi during the winter season of 2016/2017. All these genotypes (25) were grouped into five clusters on the basis of non-hierarchical clustering parameters viz. cluster I (G2, G5, G6, G16, G20), II (G4, G7, G9, G11, G12, G17), III (G10, G24), IV (G1, G13, G19, G21) and V (G3, G8, G14, G15, G18, G22, G23, G25). These groups were arranged into five (5) pairs of clusters viz. cluster I and III;II and III;II and V;III and IV;IV and V considering their similar potentiality of different traits. Results revealed that the maximum number of genotypes (8) was found in cluster V while cluster III comprised minimum genotypes (2). The inter-cluster distance was higher than intra-cluster distances. The highest and second highest eigenvalues belonged to spike/m2 (25.23%) and spikelets/spike (20.18%) respectively, along with positive canonical values in both the vectors 1 and 2 for these two traits identified them as major traits by exposing their highest potential toward genetic divergence. Cluster III produced the highest spike/m2 (388.8), grain/spike (48.1), plant height (89.5 cm), SPAD (54.2), yield (2799 kg/ha) and biomass (7758.1 Kg/ha) with lowest heading days (64.7 days), maturity days (98.7 days), canopy temperature at vegetative stage (21.7°C) and canopy temperature at grain filling stage (22.4°C). In contrast, cluster V produced the lowest 1000-grain weight (30.4 g) and grain yield (2172 kg/ha) belonging to the highest canopy temperature at both stages (23.8°C and 24.7°C). However, results suggested that the genotypes G10 and G24 under the cluster III, and genotypes G01, G13, G19 and G21 under the cluster IV could be considered as parents for future hybridization program, as well as the five pairs of clusters viz. cluster I and III;II and III;II and V;III and IV;IV and V might be matched as considered for getting more heterotic F1. The results of the study would help to identify the divergent genotypes associate with heat tolerance and this might be helpful in designing future breeding program.

Outcome assessment of stroke convalescence using multiple scales based on different dimensions

BACKGROUND: Convalescence is an important stage of stroke treatment. A lot of patients have somatic and mental disorders at various degrees. The primary standard can only reflect partial conditions of somatic disorder; in addition, multiple dimensions of patients at the phase of stroke convalescence are further observed by using a lot of standards, such as signs and symptoms of traditional Chinese medicine, daily activity and psychological status. OBJECTIVE: To analyze the outcome assessments of the cases of stroke convalescence measured with different criteria consisting of various dimensions by a cross-sectional investigation of the condition of stroke convalescent patients. DESIGN: Scale evaluation. SETTING: Departments of Clinical Epidemiology Exploratory Development and Neurology, the Second Affiliated Hospital of Guangzhou University of Traditional Chinese Medicine; National Center for Training of Design, Measurement and Evaluation in Clinical Research,Guangzhou University of Traditional Chinese Medicine. PARTICIPANTS: A total of 194 stroke convalescent patients treated in the Second Affiliated Hospital of Guangzhou University of Traditional Chinese Medicine from July 26, 2000 to February 28, 2001 were taken as subjects of the study. There were 126 males and 68 females aged from 40 to 89 years, and the illness course ranged from 14 to 181 days. All patients met diagnosis-treatment criteria of stroke (the second version)[DTCS(V2.0)] and various kinds of diagnostic points of cerebrovascular diseases; moreover, all patients provided confirmed consents. METHODS: They were assessed by assessment methods including the following assessment instruments: DTCS(V2.0), self-designed scale of traditional Chinese medicine (TCM) symptoms (28 symptoms and physical signs were scored as 0, 1, 2 marks from none to severity), modified Edinburgh-Scandinavia stroke scale (a total of 45 marks, 0 to 15 marks as mild defect, 16 to 30 as moderate defect, 31 to 45 as severe defect), modified Barthel activities of daily life (ADL) index (a total of 100 marks, less than 60 marks as unable self-care), vitality and mental health (subscales derived from Health Survey Questionnaire, SF-36). The collected data from scales and inter-scale correlation were processed by the statistic methods mainly including descriptive analysis, Spearmen correlation analysis, factor analysis, etc. MAIN OUTCOME MEASURES: ① Average scores of scales and criteria; ② correlation between modified Edinburgh-Scandinavia stroke scale and other scales. RESULTS: All of the patients completed the assessment, and analyzed in the final analysis. ① The average scores of the scales and criteria: The average scores of DTCS(V2.0), self-designed scale of TCM symptoms, modified Edinburgh-Scandinavia stroke scale, modified Barthel ADL index, vitality and mental health scales were 6.51±6.29, 13.73±6.97, 7.56±7.35, 63.58±23.68, 52.79±23.32 and 62.83±22.75 respectively. ② Correlation between modified Edinburgh-Scandinavia stroke scale and other scales: The Spearman correlation coefficients (R ’) of modified Edinburgh-Scandinavia stroke scale with diagnosis-treatment criteria of stroke, scales of TCM symptoms, modified Barthel ADL index, vitality scale and mental health scale were 20.885, 0.302, -0.824, -0.294 and -0.258 respectively. CONCLUSION: The modified Edinburgh-Scandinavia stroke scale and DTCS(V2.0) shared the same assessment dimension, so they can be mutually alternated in some clinical practices. Discrepancy in measurements of health status was gained due to the diverse dimensions applied in outcome assessments. It is necessary to build up a multi-dimensional assessment criteria system, such as signs and symptoms, daily activities and psychological status, for assessing the stroke convalescent cases in a more comprehensive scope and reflecting the efficacy of TCM treatment scientifically.

Significance of adverse outcome pathways in biomarker-based environmental risk assessment in aquatic organisms

In environmental risk assessments（ERA）, biomarkers have been widely used as an early warning signal of environmental contamination. However, biomarker responses have limitation due to its low relevance to adverse outcomes（e.g., fluctuations in community structure, decreases in population size, and other similar ecobiologically relevant indicators of community structure and function）. To mitigate these limitations, the concept of adverse outcome pathways（AOPs） was developed. An AOP is an analytical, sequentially progressive pathway that links a molecular initiating event（MIE） to an adverse outcome. Recently, AOPs have been recognized as a potential informational tool by which the implications of molecular biomarkers in ERA can be better understood. To demonstrate the utility of AOPs in biomarker-based ERA, here we discuss a series of three different biological repercussions caused by exposure to benzo（a）pyrene（Ba P）, silver nanoparticles（Ag NPs）, and selenium（Se）. Using mainly aquatic invertebrates and selected vertebrates as model species, we focus on the development of the AOP concept. Aquatic organisms are suitable bioindicator species whose entire lifespans can be observed over a short period; moreover, these species can be studied on the molecular and population levels.Also, interspecific differences between aquatic organisms are important to consider in an AOP framework, since these differences are an integral part of the natural environment.The development of an environmental pollutant-mediated AOP may enable a better understanding of the effects of environmental pollutants in different scenarios in the diverse community of an ecosystem.