The Influence of Variable Rainfall Frequency on Germination and Early Growth of Shade-Tolerant Dipterocarp Seedlings in Borneo

Climate change induced alterations to rainfall patterns have the potential to affect the regeneration dynamics of plant species, especially in historically everwet tropical rainforest. Differential species response to infrequent rainfall may influence seed germination and seedling establishment in turn affecting species distributions. We tested the role of watering frequency intervals (from daily to six-day watering) on the germination and the early growth of Dipterocarpaceae seedlings in Borneo. We used seeds that ranged in size from 500 to 20,000 mg in order to test the role of seed mass in mediating the effects of infrequent watering. With frequent rainfall, germination and seedling development traits bore no relationship to seed mass, but all metrics of seedling growth increased with increasing seed mass. Cumulative germination declined by 39.4% on average for all species when plants were watered at six-day intervals, and days to germination increased by 76.5% on average for all species from daily to six-day intervals. Final height and biomass declined on average in the six-day interval by 16% and 30%, respectively, but the percentage decrease in final size was greater for large-seeded species. Rooting depth per leaf area also significantly declined with seed mass indicating large-seeded species allocate relatively more biomass for leaf production. This difference in allocation provided an establishment advantage to large-seeded species when water was non-limiting but inhibited their growth under infrequent rainfall. The observed reduction in the growth of large-seeded species under infrequent rainfall would likely restrict their establishment in drier microsites associated with coarse sandy soils and ridge tops. In total, these species differences in germination and initial seedling growth indicates a possible niche axis that may help explain both current species distributions and future responses to climate change.     

Influence of Vectors’ Risk-Spreading Strategies and Environmental Stochasticity on the Epidemiology and Evolution of Vector-Borne Diseases: The Example of Chagas’ Disease

Insects are known to display strategies that spread the risk of encountering unfavorable conditions, thereby decreasing the extinction probability of genetic lineages in unpredictable environments. To what extent these strategies influence the epidemiology and evolution of vector-borne diseases in stochastic environments is largely unknown. In triatomines, the vectors of the parasite Trypanosoma cruzi, the etiological agent of Chagas’ disease, juvenile development time varies between individuals and such variation most likely decreases the extinction risk of vector populations in stochastic environments. We developed a simplified multi-stage vector-borne SI epidemiological model to investigate how vector risk-spreading strategies and environmental stochasticity influence the prevalence and evolution of a parasite. This model is based on available knowledge on triatomine biodemography, but its conceptual outcomes apply, to a certain extent, to other vector-borne diseases. Model comparisons between deterministic and stochastic settings led to the conclusion that environmental stochasticity, vector risk-spreading strategies (in particular an increase in the length and variability of development time) and their interaction have drastic consequences on vector population dynamics, disease prevalence, and the relative short-term evolution of parasite virulence. Our work shows that stochastic environments and associated risk-spreading strategies can increase the prevalence of vector-borne diseases and favor the invasion of more virulent parasite strains on relatively short evolutionary timescales. This study raises new questions and challenges in a context of increasingly unpredictable environmental variations as a result of global climate change and human interventions such as habitat destruction or vector control.     

Neuromuscular Electrical Stimulation as a Method to Maximize the Beneficial Effects of Muscle Stem Cells Transplanted into Dystrophic Skeletal Muscle

Cellular therapy is a potential approach to improve the regenerative capacity of damaged or diseased skeletal muscle. However, its clinical use has often been limited by impaired donor cell survival, proliferation and differentiation following transplantation. Additionally, functional improvements after transplantation are all-too-often negligible. Because the host microenvironment plays an important role in the fate of transplanted cells, methods to modulate the microenvironment and guide donor cell behavior are warranted. The purpose of this study was to investigate whether the use of neuromuscular electrical stimulation (NMES) for 1 or 4 weeks following muscle-derived stem cell (MDSC) transplantation into dystrophic skeletal muscle can modulate the fate of donor cells and enhance their contribution to muscle regeneration and functional improvements. Animals submitted to 4 weeks of NMES after transplantation demonstrated a 2-fold increase in the number of dystrophin+ myofibers as compared to control transplanted muscles. These findings were concomitant with an increased vascularity in the MDSC+NMES group when compared to non-stimulated counterparts. Additionally, animals subjected to NMES (with or without MDSC transplantation) presented an increased maximal specific tetanic force when compared to controls. Although cell transplantation and/or the use of NMES resulted in no changes in fatigue resistance, the combination of both MDSC transplantation and NMES resulted in a faster recovery from fatigue, when compared to non-injected and non-stimulated counterparts. We conclude that NMES is a viable method to improve MDSC engraftment, enhance dystrophic muscle strength, and, in combination with MDSC transplantation, improve recovery from fatigue. These findings suggest that NMES may be a clinically-relevant adjunct approach for cell transplantation into skeletal muscle.     

Mapping the Genetic Variation of Regional Brain Volumes as Explained by All Common SNPs from the ADNI Study

Typically twin studies are used to investigate the aggregate effects of genetic and environmental influences on brain phenotypic measures. Although some phenotypic measures are highly heritable in twin studies, SNPs (single nucleotide polymorphisms) identified by genome-wide association studies (GWAS) account for only a small fraction of the heritability of these measures. We mapped the genetic variation (the proportion of phenotypic variance explained by variation among SNPs) of volumes of pre-defined regions across the whole brain, as explained by 512,905 SNPs genotyped on 747 adult participants from the Alzheimer''s Disease Neuroimaging Initiative (ADNI). We found that 85% of the variance of intracranial volume (ICV) (p = 0.04) was explained by considering all SNPs simultaneously, and after adjusting for ICV, total grey matter (GM) and white matter (WM) volumes had genetic variation estimates near zero (p = 0.5). We found varying estimates of genetic variation across 93 non-overlapping regions, with asymmetry in estimates between the left and right cerebral hemispheres. Several regions reported in previous studies to be related to Alzheimer''s disease progression were estimated to have a large proportion of volumetric variance explained by the SNPs.     

Leaves of the Arabidopsis?maltose exporter1?Mutant Exhibit a?Metabolic Profile with?Features of Cold Acclimation in the Warm

Background

Arabidopsis plants accumulate maltose from starch breakdown during cold acclimation. The Arabidopsis mutant, maltose excess1-1, accumulates large amounts of maltose in the plastid even in the warm, due to a deficient plastid envelope maltose transporter. We therefore investigated whether the elevated maltose level in mex1-1 in the warm could result in changes in metabolism and physiology typical of WT plants grown in the cold.

Principal Findings

Grown at 21 °C, mex1-1 plants were much smaller, with fewer leaves, and elevated carbohydrates and amino acids compared to WT. However, after transfer to 4 °C the total soluble sugar pool and amino acid concentration was in equal abundance in both genotypes, although the most abundant sugar in mex1-1 was still maltose whereas sucrose was in greatest abundance in WT. The chlorophyll a/b ratio in WT was much lower in the cold than in the warm, but in mex1-1 it was low in both warm and cold. After prolonged growth at 4 °C, the shoot biomass, rosette diameter and number of leaves at bolting were similar in mex1-1 and WT.

Conclusions

The mex1-1 mutation in warm-grown plants confers aspects of cold acclimation, including elevated levels of sugars and amino acids and low chlorophyll a/b ratio. This may in turn compromise growth of mex1-1 in the warm relative to WT. We suggest that elevated maltose in the plastid could be responsible for key aspects of cold acclimation.     

Tracking 20 Years of Compound-to-Target Output from Literature and Patents

The statistics of drug development output and declining yield of approved medicines has been the subject of many recent reviews. However, assessing research productivity that feeds development is more difficult. Here we utilise an extensive database of structure-activity relationships extracted from papers and patents. We have used this database to analyse published compounds cumulatively linked to nearly 4000 protein target identifiers from multiple species over the last 20 years. The compound output increases up to 2005 followed by a decline that parallels a fall in pharmaceutical patenting. Counts of protein targets have plateaued but not fallen. We extended these results by exploring compounds and targets for one large pharmaceutical company. In addition, we examined collective time course data for six individual protease targets, including average molecular weight of the compounds. We also tracked the PubMed profile of these targets to detect signals related to changes in compound output. Our results show that research compound output had decreased 35% by 2012. The major causative factor is likely to be a contraction in the global research base due to mergers and acquisitions across the pharmaceutical industry. However, this does not rule out an increasing stringency of compound quality filtration and/or patenting cost control. The number of proteins mapped to compounds on a yearly basis shows less decline, indicating the cumulative published target capacity of global research is being sustained in the region of 300 proteins for large companies. The tracking of six individual targets shows uniquely detailed patterns not discernible from cumulative snapshots. These are interpretable in terms of events related to validation and de-risking of targets that produce detectable follow-on surges in patenting. Further analysis of the type we present here can provide unique insights into the process of drug discovery based on the data it actually generates.     

Employing a Monte Carlo Algorithm in Newton-Type Methods for Restricted Maximum Likelihood Estimation of Genetic Parameters

Estimation of variance components by Monte Carlo (MC) expectation maximization (EM) restricted maximum likelihood (REML) is computationally efficient for large data sets and complex linear mixed effects models. However, efficiency may be lost due to the need for a large number of iterations of the EM algorithm. To decrease the computing time we explored the use of faster converging Newton-type algorithms within MC REML implementations. The implemented algorithms were: MC Newton-Raphson (NR), where the information matrix was generated via sampling; MC average information(AI), where the information was computed as an average of observed and expected information; and MC Broyden''s method, where the zero of the gradient was searched using a quasi-Newton-type algorithm. Performance of these algorithms was evaluated using simulated data. The final estimates were in good agreement with corresponding analytical ones. MC NR REML and MC AI REML enhanced convergence compared to MC EM REML and gave standard errors for the estimates as a by-product. MC NR REML required a larger number of MC samples, while each MC AI REML iteration demanded extra solving of mixed model equations by the number of parameters to be estimated. MC Broyden''s method required the largest number of MC samples with our small data and did not give standard errors for the parameters directly. We studied the performance of three different convergence criteria for the MC AI REML algorithm. Our results indicate the importance of defining a suitable convergence criterion and critical value in order to obtain an efficient Newton-type method utilizing a MC algorithm. Overall, use of a MC algorithm with Newton-type methods proved feasible and the results encourage testing of these methods with different kinds of large-scale problem settings.     

128-Slice Acceletated-Pitch Dual Energy CT Angiography of the Head and Neck: Comparison of Different Low Contrast Medium Volumes

Background

Our study aims to evaluate the image quality and feasibility of 128-slice dual-energy CTA (DE-CTA) for supra-aortic arteries using reduced amounts of contrast medium (CM).

Methods

A prospective study was performed in 54 patients receiving CTA of the head and neck with a 128-slice dual-source CT system. Patients were randomized into two groups with a volume of either 40 mL of CM (Group I) or 50 mL of CM (Group II). Arterial and venous enhancements were recorded for quantitative assessment. Qualitative assessments for images without bone removal (BR) were based on a) the visualization of the circle of Willis and b) streak artifacts due to residual CM in the subclavian or internal jugular veins ipsilateral to injection of CM. Qualitative assessment of dual-energy images using BR was based on the presence of bone remnants and vessel integrity. Quantitative data was compared using the Student t test. The χ² test was used for the qualitative measurements of streak artifacts in veins while the Mann-Whitney U test was used for the qualitative measurements of images with BR.

Results

Arterial and venous attenuation was significantly higher in Group II (P=0.000). Image quality regarding the circle of Willis was excellent in both groups (3.90±0.30 for Group I and 4.00±0 for Group II) . Imaging of the internal jugular veins was scored higher in Group I (1.87±0.72) compared with Group II (1.48±0.51) (P=0.021). Within Group I using BR, mean scores for bone remnants did not differ significantly (P>0.05) but mean scores of vessel integrity (P<0.05) did.

Conclusions

Contrast-enhanced head and neck CTA is feasible using a scan protocol with low amounts of contrast medium (40 mL) on a 128-slice dual-energy CTA. The 40-mL protocol provides satisfactory image quality before and after dual-energy bone-removal post-processing.