Identification and validation of root length QTLs for water stress resistance in hexaploid wheat (<Emphasis Type="Italic">Titicum aestivum</Emphasis> L.)

Thorough understanding of the genetic mechanisms governing drought adaptive traits can facilitate drought resistance improvement. This study was conducted to identify chromosome regions harbouring QTLs contributing for water stress resistance in wheat. A RIL mapping population derived from a cross between W7984 (Synthetic) and Opata 85 was phenotyped for root length and root dry weight under water stress and non-stress growing conditions. ANOVA showed highly significant (p ≤ 0.01) variation among the RILs for both traits. Root length and root dry weight showed positive and significant (p ≤ 0.01) phenotypic correlation. Broad sense heritability was 86% for root length under stress and 65% for root dry weight under non-stress conditions. A total of eight root length and five root dry weight QTLs were identified under both water conditions. Root length QTLs Qrln.uwa.1BL, Qrln.uwa.2DS, Qrln.uwa.5AL and Qrln.uwa.6AL combined explained 43% of phenotypic variation under non-stress condition. Opata was the source of favourable alleles for root length QTLs under non-stress condition except for Qrln.uwa.6AL. Four stress specific root length QTLs, Qrls.uwa.1AS, Qrls.uwa.3AL, Qrls.uwa.7BL.1 and Qrls.uwa.7BL.2 jointly explained 47% of phenotypic variation. Synthetic wheat contributed favourable alleles for Qrls.uwa.1AS and Qrls.uwa.3AL. Two stable root dry weight QTLs on chromosomes 4AL and 5AL were consistently found in both water conditions. Three validation populations were developed by crossing cultivars Lang, Yitpi, and Chara with Synthetic W7984 to transfer two of the QTLs identified under stress condition. The F_2.3 and F_3.4 validation lines were phenotyped under the same level of water stress as RILs to examine the effect of these QTLs. There were 13.5 and 14.5% increases in average root length due to the inheritance of Qrls.uwa.1AS and Qrls.uwa.3AL, respectively. The result indicated that closely linked SSR markers Xbarc148 (Qrls.uwa.1AS) and Xgwm391 (Qrls.uwa.3AL) can be incorporated into MAS for water stress improvement in wheat.     

Impact of time lags on diurnal estimates of canopy transpiration and canopy conductance from sap-flow measurements of <Emphasis Type="Italic">Populus cathayana</Emphasis> in the Qinghai–Tibetan Plateau

Recently, canopy transpiration (E_c) has been often estimated by xylem sap-flow measurements. However, there is a significant time lag between sap flow measured at the base of the stem and canopy transpiration due to the capacitive exchange between the transpiration stream and stem water storage. Significant errors will be introduced in canopy conductance (g_c) and canopy transpiration estimation if the time lag is neglected. In this study, a cross-correlation analysis was used to quantify the time lag, and the sap flow-based transpiration was measured to parameterize Jarvis-type models of g_c and thus to simulate E_c of Populus cathayana using the Penman–Monteith equation. The results indicate that solar radiation (R_s) and vapor pressure deficit (VPD) are not fully coincident with sap flow and have an obvious lag effect; the sap flow lags behind R_s and precedes VPD, and there is a 1-h time shift between E_c and sap flow in the 30-min interval data set. A parameterized Jarvis-type g_c model is suitable to predict P. cathayana transpiration and explains more than 80% of the variation observed in g_c, and the relative error was less than 25%, which shows a preferable simulation effect. The root mean square error (RMSEs) between the predicted and measured E_c were 1.91 × 10^?3 (with the time lag) and 3.12 × 10^?3 cm h^?1 (without the time lag). More importantly, E_c simulation precision that incorporates time lag is improved by 6% compared to the results without the time lag, with the mean relative error (MRE) of only 8.32% and the mean absolute error (MAE) of 1.48 × 10^?3 cm h^?1.     

Stem cell factor supports migration in canine mesenchymal stem cells

Adult Mesenchymal Stem Cells (MSC) are cells that can be defined as multipotent cells able to differentiate into diverse lineages, under appropriate conditions. These cells have been widely used in regenerative medicine, both in preclinical and clinical settings. Initially discovered in bone marrow, MSC can now be isolated from a wide spectrum of adult and foetal tissues. Studies to evaluate the therapeutic potential of these cells are based on their ability to arrive to damaged tissues. In this paper we have done a comparative study analyzing proliferation, surface markers and OCT4, SOX9, RUNX2, PPARG genes expression in MSC cells from Bone marrow (BMMSC) and Adipose tissue (ASC). We also analyzed the role of Stem Cell Factor (SCF) on MSC proliferation and on ASCs metalloproteinases MMP-2, MMP-9 secretion. Healthy dogs were used as BMMSC donors, and ASC were collected from omentum during elective ovariohysterectomy surgery. Both cell types were cultured in IMDM medium with or without SCF, 10% Dog Serum (DS), and incubated at 38 °C with 5% CO2. Growth of BMMSCs and ASCs was exponential until 25–30 days. Flow citometry of MSCs revealed positive results for CD90 and negative for CD34, CD45 and MCH-II. Genes were evaluated by RT-PCR and metalloproteinases by zymografy. Our findings indicate morphological and immunological similarities as well as expression of genes from both origins on analyzed cells. Furthermore, SCF did not affect proliferation of MSCs, however it up-regulated MMP-2 and MMP-9 secretion in ASCs. These results suggest that metalloproteinases are possibly essential molecules pivoting migration.     

Effects of a probiotic bacterial <Emphasis Type="Italic">Lactobacillus rhamnosus</Emphasis> dietary supplement on the crowding stress response of juvenile Nile tilapia <Emphasis Type="Italic">Oreochromis niloticus</Emphasis>

To test the effects of probiotic bacteria against crowding stress, juvenile Nile tilapia Oreochromis niloticus were fed commercial feed supplemented with 1 × 10¹⁰ cfu/g pellets of Lactobacillus rhamnosus for 3 weeks. The fish were confined and subjected to crowding for 7 and 14 days after which their physiological condition was investigated. The administration of probiotic prophylaxis improved growth performance even in the stressed fish. After 7 days of stress exposure, fish receiving probiotic-supplemented feed showed proactive behavior and coping responses to the stressor, as evidenced by elevated plasma glucose levels and osmolality, stabilized plasma electrolytes, and a higher RNA:DNA ratio. Fish stressed for 7 days and fed normal commercial diet showed impairment of plasma electrolytes; after 14 days, the plasma osmolality, electrolytes, glucose, and RNA:DNA ratio decreased, indicating physiological maladaptation to the stressor. The growth rate was also found to be reduced, suggesting that energy demand exceeded the energy available from metabolism and dietary uptake. This latter effect was not observed in fish fed the probiotic-supplemented diet. The results suggest that probiotic bacteria prophylaxis may increase energy availability for metabolic support of the crowding stress response and improve the stress coping capacity of fish.     

Living with disease? Biosecurity and avian influenza in ostriches

This paper is about an avian influenza outbreak in South Africa’s commercial ostrich industry. The outbreak was managed according to international best practice and led to the destruction of 30,000 ostriches in two of South Africa’s provinces. However, the industry has a long history of managing low pathogenic avian influenza outbreaks in a different way. We use the 2004 outbreak and earlier approaches to managing disease to shed light on recent debates on how we might live differently with livestock diseases. The paper is based on in-depth interviews with farmers, veterinarians, scientists and agriculture officials.     

Prediction of multinomial probability of land use change using a bisection decomposition and logistic regression

Land use change is an important research area in landscape ecology and urban development. Prediction of land use change (urban development) provides critical information for making the right policies and management plans in order to maintain and improve ecosystem and city functions. Logistic regression is a widely used method to predict binomial probabilities of land use change when just two responses (change and no-change) are considered. However, in practice, more than two types of change are encountered and multinomial probabilities are therefore needed. The existing methods for predicting multinomial probabilities have limits in building multinomial probability models and are often based on improper assumptions. This is due to the lack of proper methodology and inadequate software. In this study, a procedure has been developed for building models to predict the multinomial probabilities of land use change and urban development. The foundation of this procedure consists of a special bisection decomposition system for the decomposition of multiple-class systems to bi-class systems, conditional probability inference, and logistic regression for binomial probability models. A case study of urban development has been conducted to evaluate this procedure. The evaluation results demonstrated that different samples and bisection decomposition systems led to very similar quality and performance in the developed multinomial probability models, which indicates the high stability of the proposed procedure for this case study.