Estimating nephron number in the developing kidney using the physical disector/fractionator combination

Over the last decade the development of new molecular biology tools, advanced microscopy, live imaging and systems biology approaches have revolutionized our conception of how embryonic development proceeds. One fundamental aspect of development biology is the concept of morphogenesis: understanding how a group of multipotent cells organize and differentiate into a complex organ. In Kidney Development: Methods and Protocols, expert researchers in the field detail different approaches to tackle kidney development. These approaches include culture and live imaging aspects of kidney development, analyzing the 3-dimensional aspects of branching morphogenesis as well as nephrogenesis, manipulation of the gene/protein expression during kidney development as well as in the adult kidney, and how to assess kidney malformation and disease. Written in the highly successful Methods in Molecular Biology series format, chapters include introductions to their respective topics, lists of the necessary materials and reagents, step-by-step, readily reproducible laboratory protocols, and key tips on troubleshooting and avoiding known pitfalls. Authoritative and practical, Kidney Development: Methods and Protocols seeks to aid scientists in the further study of the process of morphogenesis which is fundamental important not only for studying developmental biology but also for regenerative medicine.

Do leatherback turtles Dermochelys coriacea forage during the breeding season? A combination of data-logging devices provide new insights

Animals which undertake migrations from foraging grounds to suitable breeding areas must adopt strategies in these new conditions in order to minimise the rate at which body condition deteriorates (which will occur due to oogenesis or provisioning for young). For some animals this involves continuing foraging, whereas for others the optimal strategy is to fast during the breeding season. The leatherback turtle undertakes long-distance migrations from temperate zones to tropical breeding areas, and in some of these areas it has been shown to exhibit diving behaviour indicative of foraging. We used conventional time–depth recorders and a single novel mouth-opening sensor to investigate the foraging behaviour of leatherback turtles in the southern Caribbean. Diving behaviour suggested attempted foraging on vertically migrating prey with significantly more diving to a more consistent depth occurring during the night. No obvious prey manipulation was detected by the mouth sensor, but rhythmic mouth opening did occur during specific phases of dives, suggesting that the turtle was relying on gustatory cues to sense its immediate environment. Patterns of diving in conjunction with these mouth-opening activities imply that leatherbacks are attempting to forage during the breeding season and that gustatory cues are important to leatherbacks.

Detection of fingertips based on the combination of color information and circle detection

Fingertips of human hand play an important role in hand-based interaction with computers. Therefore, identification of fingertips' positions on hand image is vital for developing a human computer interaction system. All most all of the research works for fingertips detection, initially isolate hand image from the background image. Most of these techniques develop color based segmentation methods because human skin color possess an exceptional characterises that can be used to isolate hand from the rest of the image quite easily. Sometimes color image segmentation becomes difficult due to illumination and background variations. To make it simple and reliable, this paper proposes a robust method for detecting fingertips of a hand image based on the combination of color segmentation and circle detection. Due to the characteristics of circularity of fingertips regions of hand boundary, any existing circle detection algorithms can be applied to detect circles at fingertips region. It is difficult to detect fingertips solely based on the circle detection method. For this reason, initially the proposed method detects all the circular regions on the image applying Circle Hough Transformation (CHT) then the fingertips are selected based on the color characteristics of the fingertips regions. Experimental results show that the proposed approach is promising.

Synergistic antibacterial effects of theaflavin in combination with ampicillin against hospital isolates of Stenotrophomonas Maltophilia

Stenotrophomonas maltophilia is an important opportunistic nosocomial pathogen that shows intrinsic resistance to many antibiotics. This often limits treatment options and can cause lengthy hospital stays. Combination treatments are often used to combat resistance and using natural compounds such as polyphenols could give increased treatment options and even the reuse of antibiotics to which high levels of resistance have been observed. A checkerboard assay was used to determine if any synergy exists between ampicillin and the polyphenol theaflavin against 9 clinical isolates and one control isolate (NCTC 13014) of S. maltophilia. It was discovered that significant synergy (P  0.05) does exist between theaflavin and ampicillin, reducing the mean MIC of ampicillin from 12.5-22.9 µg/mL, in liquid culture, to 3.125-6.25 µg/mL. The FIC index was calculated to be 0.22-0.35 confirming synergy. From these results, significant potential for medical applications can be seen and further investigation is recommended.

An adjunctive antidepressant nutraceutical combination in treating major depression: study protocol and clinical considerations

Current treatment for major depressive disorder (MDD), a prevalent and disabling mental illness, is inadequate, with two-thirds of people treated with first-line antidepressants not achieving remission. MDD is for many a chronic condition, often requiring multiple treatment attempts, thus development of additional interventions is urgently required. An emerging approach to improve non-response to antidepressants is the use of adjunctive nutraceuticals. The pathophysiology of MDD is considered to involve a range of abnormalities (monoamine impairment, neuro-endocrinological changes, reduced brain-derived neurotrophic factor, and cytokine alterations). By targeting an array of these key neurobiological pathways via specific nutraceuticals (S-adenosyl methionine; [SAMe], 5-HTP [active tryptophan], folinic acid [active folic acid], omega-3 fatty acids, and zinc), there is the potential to provide a more comprehensive therapeutic biological approach to treat depression. We are currently conducting a National Health and Medical Research Council funded study in Australia (APP1048222). The clinical trial is phase II/III, multi-site, 3-arm, 8-week, randomised, double-blind, placebo-controlled study using SAMe + folinic acid versus a combination nutraceutical (SAMe, 5-HTP, folinic acid, omega-3, and zinc) or matching placebo in 300 currently depressed participants with diagnosed MDD who are non-responsive to current antidepressants (ANZCTR, protocol number: 12613001300763). The results may provide evidence for a novel adjunctive neurobiological approach for treating depression.

Application of air quality combination forecasting to Bogota

The bulk of existing work on the statistical forecasting of air quality is based on either neural networks or linear regressions, which are both subject to important drawbacks. In particular, while neural networks are complicated and prone to in-sample overfitting, linear regressions are highly dependent on the specification of the regression function. The present paper shows how combining linear regression forecasts can be used to circumvent all of these problems. The usefulness of the proposed combination approach is verified using both Monte Carlo simulation and an extensive application to air quality in Bogota, one of the largest and most polluted cities in Latin America. © 2014 Elsevier Ltd.

Microencapsulation of coupled folate and chitosan nanoparticles for targeted delivery of combination drugs to colon

Folate-chitosan nanoparticles, co-loaded with 5-fluourouacil (5-FU) and leucovorin (LV) and prepared by ionic gelation technology were physically microencapsulated by enteric polymer using a solvent evaporation method. Average particle size of the microencapsulated particles was in the range of 15 to 35 µm. High drug encapsulation efficiency was obtained for both 5-FU and LV in the microencapsulated particles. Both drugs were in amorphous state in the microencapsulated particles. By enteric coating, excellent pH-dependent release profile was achieved and no drug release was observed in simulated gastric and intestinal fluids. However, when the pH value reached the soluble threshold of Eudragit S-100, a constant and slow drug release was observed. The results indicated that these microencapsulated particles are a promising vehicle for selectively targeting drugs to colon in the chemotherapy of colon cancer.

Progesterone and testosterone in combination act in the hypothalamus of castrated rams to regulate the secretion of LH

We tested the hypotheses that progesterone enhances the negative feedback actions of testosterone in rams and that this occurs through actions at the hypothalamus. In the first part of this study, blood samples were collected every 10 min for 12 h before and after 7 days of treatment (i.m.) of castrated Romney Marsh rams (n=5 per group) with vehicle, progesterone (4 mg/12 h), testosterone (4 mg/12 h) or a combination of progesterone (4 mg/12 h) and testosterone (4 mg/12 h). In the second part of this study the brains of four gonad-intact Romney Marsh rams were collected, the hypothalamus was sectioned and in situ hybridisation of mRNA for progesterone receptors conducted. After 7 days of treatment with vehicle or progesterone or testosterone alone, there were no changes in the secretion of LH. In contrast, treatment with a combination of progesterone and testosterone resulted in a significant (P<0.01, repeated measures ANOVA) decrease in mean plasma concentrations of LH, the number of LH pulses per hour and the pre-LH pulse nadir and a significant (P<0.01) increase in the inter-LH pulse interval. We found cells containing mRNA for progesterone receptors throughout the hypothalamus, including the preoptic area (where most GnRH neurons are located in sheep), the periventricular, ventromedial and arcuate nuclei and the bed nucleus of the stria terminalis. This study shows that progesterone is capable of acting centrally with testosterone to suppress the secretion of LH in castrated rams and that cells containing mRNA for progesterone receptors are located in the hypothalamus of rams in the vicinity of GnRH neurons.

Hybrid controller with the combination of FLC and neural network-based IMC for nonlinear processes

This work presents a hybrid controller based on the combination of fuzzy logic control (FLC) mechanism and internal model-based control (IMC). Neural network-based inverse and forward models are developed for IMC. After designing the FLC and IMC independently, they are combined in parallel to produce a single control signal. Mean averaging mechanism is used to combine the prediction of both controllers. Finally, performance of the proposed hybrid controller is studied for a nonlinear numerical plant model (NNPM). Simulation result shows the proposed hybrid controller outperforms both FLC and IMC.

Combination of calcium and magnesium ions prevents substrate inhibition and promotes biomass and lipid production in thraustochytrids under higher glycerol concentration

Effect of calcium and magnesium ions was studied in detail in batch mode in shake flask cultures of two fast growing strains of thraustochytrids (Aurantiochytrium sp. DBTIOC-18 and Schizochytrium sp. DBTIOC-1) for biomass and lipid production. These strains were previously isolated from Indian marine biodiversity. Screening of these two strains on different carbon and nitrogen sources revealed the suitability of glycerol over glucose and sodium nitrate over yeast extract for the cultivation of these strains. The presence of higher concentration of glycerol in the medium inhibited the glycerol utilization by the cell thus resulting in lower biomass and lipid production in both the strains. Supplementing media with calcium and magnesium ions promoted glycerol utilization thus resulted in a substantial rise in volumetric production of biomass (55.12 g L-1, 48.12 g L-1), fatty acid for biodiesel (27.14 g L-1, 22.15 g L-1) and docosahexaenoic acid (14.57 g L-1, 10.12 g L-1) with both strains Aurantiochytrium sp. DBTIOC-18 and Schizochytrium sp. DBTIOC-1, respectively. Growth profile study of these two strains showed further improvement in production of biomass, fatty acid for biodiesel and docosahexaenoic acid when cultures were extended up to 7 days. Finding of this work underlines the importance of calcium and magnesium salts in designing new fermentation strategies to prevent substrate inhibition and achieve high cell density culture under high nutrient concentration especially carbon sources.

Real-Time Control Of Floods Along The Demer River, Belgium, By Means Of MPC In Combination With GA And A Fast Conceptual River Model

Climate model projections show that climate change will further increase the risk of flooding in many regions of the world. There is a need for climate adaptation, but building new infrastructure or additional retention basins has its limits, especially in densely populated areas where open spaces are limited. Another solution is the more efficient use of the existing infrastructure. This research investigates a method for real-time flood control by means of existing gated weirs and retention basins. The method was tested for the specific study area of the Demer basin in Belgium but is generally applicable. Today, retention basins along the Demer River are controlled by means of adjustable gated weirs based on fixed logic rules. However, because of the high complexity of the system, only suboptimal results are achieved by these rules. By making use of precipitation forecasts and combined hydrological-hydraulic river models, the state of the river network can be predicted. To fasten the calculation speed, a conceptual river model was used. The conceptual model was combined with a Model Predictive Control (MPC) algorithm and a Genetic Algorithm (GA). The MPC algorithm predicts the state of the river network depending on the positions of the adjustable weirs in the basin. The GA generates these positions in a semi-random way. Cost functions, based on water levels, were introduced to evaluate the efficiency of each generation, based on flood damage minimization. In the final phase of this research the influence of the most important MPC and GA parameters was investigated by means of a sensitivity study. The results show that the MPC-GA algorithm manages to reduce the total flood volume during the historical event of September 1998 by 46% in comparison with the current regulation. Based on the MPC-GA results, some recommendations could be formulated to improve the logic rules.

Improvement on the sales forecast accuracy for a fast growing company by the best combination of historical data usage and clients segmentation

Industrial companies in developing countries are facing rapid growths, and this requires having in place the best organizational processes to cope with the market demand. Sales forecasting, as a tool aligned with the general strategy of the company, needs to be as much accurate as possible, in order to achieve the sales targets by making available the right information for purchasing, planning and control of production areas, and finally attending in time and form the demand generated. The present dissertation uses a single case study from the subsidiary of an international explosives company based in Brazil, Maxam, experiencing high growth in sales, and therefore facing the challenge to adequate its structure and processes properly for the rapid growth expected. Diverse sales forecast techniques have been analyzed to compare the actual monthly sales forecast, based on the sales force representatives’ market knowledge, with forecasts based on the analysis of historical sales data. The dissertation findings show how the combination of both qualitative and quantitative forecasts, by the creation of a combined forecast that considers both client´s demand knowledge from the sales workforce with time series analysis, leads to the improvement on the accuracy of the company´s sales forecast.

The combination of neural estimates in prediction and decision problems

In this dissertation, different ways of combining neural predictive models or neural-based forecasts are discussed. The proposed approaches consider mostly Gaussian radial basis function networks, which can be efficiently identified and estimated through recursive/adaptive methods. Two different ways of combining are explored to get a final estimate – model mixing and model synthesis –, with the aim of obtaining improvements both in terms of efficiency and effectiveness. In the context of model mixing, the usual framework for linearly combining estimates from different models is extended, to deal with the case where the forecast errors from those models are correlated. In the context of model synthesis, and to address the problems raised by heavily nonstationary time series, we propose hybrid dynamic models for more advanced time series forecasting, composed of a dynamic trend regressive model (or, even, a dynamic harmonic regressive model), and a Gaussian radial basis function network. Additionally, using the model mixing procedure, two approaches for decision-making from forecasting models are discussed and compared: either inferring decisions from combined predictive estimates, or combining prescriptive solutions derived from different forecasting models. Finally, the application of some of the models and methods proposed previously is illustrated with two case studies, based on time series from finance and from tourism.