The Effect of Various Root Characteristics on Root-pulling Resistance of 44 Inbred Lines of Corn

The purposes of this study were to determine (1) the range of root-pulling resistance that exists among inbred lines, (2) the repeatability of root-pulling measurements as well as other root characteristics in differing environmental conditions, and (3) the relationship between root pulling resistance and root characteristics such as root spread, root dry weight, root abundance, and root rot resistance

Generalized Fisher information matrix in nonextensive systems with spatial correlation

By using the $q$-Gaussian distribution derived by the maximum entropy method for spatially-correlated $N$-unit nonextensive systems, we have calculated the generalized Fisher information matrix of $g_{\theta_n \theta_m}$ for $(\theta_1, \theta_2, \theta_3) = (\mu_q, \sigma_q^2$, $s$), where $\mu_q$, $\sigma_q^2$ and $s$ denote the mean, variance and degree of spatial correlation, respectively, for a given entropic index $q$. It has been shown from the Cram\'{e}r-Rao theorem that (1) an accuracy of an unbiased estimate of $\mu_q$ is improved (degraded) by a negative (positive) correlation $s$, (2) that of $\sigma_q^2$ is worsen with increasing $s$, and (3) that of $s$ is much improved for $s \simeq -1/(N-1)$ or $s \simeq 1.0$ though it is worst at $s = (N-2)/2(N-1)$. Our calculation provides a clear insight to the long-standing controversy whether the spatial correlation is beneficial or detrimental to decoding in neuronal ensembles. We discuss also a calculation of the $q$-Gaussian distribution, applying the superstatistics to the Langevin model subjected to spatially-correlated inputs.Comment: 18 pages, 3 figures: revised version accepted in Phys. Rev.

Design principles for riboswitch function

Scientific and technological advances that enable the tuning of integrated regulatory components to match network and system requirements are critical to reliably control the function of biological systems. RNA provides a promising building block for the construction of tunable regulatory components based on its rich regulatory capacity and our current understanding of the sequence–function relationship. One prominent example of RNA-based regulatory components is riboswitches, genetic elements that mediate ligand control of gene expression through diverse regulatory mechanisms. While characterization of natural and synthetic riboswitches has revealed that riboswitch function can be modulated through sequence alteration, no quantitative frameworks exist to investigate or guide riboswitch tuning. Here, we combined mathematical modeling and experimental approaches to investigate the relationship between riboswitch function and performance. Model results demonstrated that the competition between reversible and irreversible rate constants dictates performance for different regulatory mechanisms. We also found that practical system restrictions, such as an upper limit on ligand concentration, can significantly alter the requirements for riboswitch performance, necessitating alternative tuning strategies. Previous experimental data for natural and synthetic riboswitches as well as experiments conducted in this work support model predictions. From our results, we developed a set of general design principles for synthetic riboswitches. Our results also provide a foundation from which to investigate how natural riboswitches are tuned to meet systems-level regulatory demands

Aptamer-based multiplexed proteomic technology for biomarker discovery

Interrogation of the human proteome in a highly multiplexed and efficient manner remains a coveted and challenging goal in biology. We present a new aptamer-based proteomic technology for biomarker discovery capable of simultaneously measuring thousands of proteins from small sample volumes (15 [mu]L of serum or plasma). Our current assay allows us to measure ~800 proteins with very low limits of detection (1 pM average), 7 logs of overall dynamic range, and 5% average coefficient of variation. This technology is enabled by a new generation of aptamers that contain chemically modified nucleotides, which greatly expand the physicochemical diversity of the large randomized nucleic acid libraries from which the aptamers are selected. Proteins in complex matrices such as plasma are measured with a process that transforms a signature of protein concentrations into a corresponding DNA aptamer concentration signature, which is then quantified with a DNA microarray. In essence, our assay takes advantage of the dual nature of aptamers as both folded binding entities with defined shapes and unique sequences recognizable by specific hybridization probes. To demonstrate the utility of our proteomics biomarker discovery technology, we applied it to a clinical study of chronic kidney disease (CKD). We identified two well known CKD biomarkers as well as an additional 58 potential CKD biomarkers. These results demonstrate the potential utility of our technology to discover unique protein signatures characteristic of various disease states. More generally, we describe a versatile and powerful tool that allows large-scale comparison of proteome profiles among discrete populations. This unbiased and highly multiplexed search engine will enable the discovery of novel biomarkers in a manner that is unencumbered by our incomplete knowledge of biology, thereby helping to advance the next generation of evidence-based medicine

The Temporal Winner-Take-All Readout

How can the central nervous system make accurate decisions about external stimuli at short times on the basis of the noisy responses of nerve cell populations? It has been suggested that spike time latency is the source of fast decisions. Here, we propose a simple and fast readout mechanism, the temporal Winner-Take-All (tWTA), and undertake a study of its accuracy. The tWTA is studied in the framework of a statistical model for the dynamic response of a nerve cell population to an external stimulus. Each cell is characterized by a preferred stimulus, a unique value of the external stimulus for which it responds fastest. The tWTA estimate for the stimulus is the preferred stimulus of the cell that fired the first spike in the entire population. We then pose the questions: How accurate is the tWTA readout? What are the parameters that govern this accuracy? What are the effects of noise correlations and baseline firing? We find that tWTA sensitivity to the stimulus grows algebraically fast with the number of cells in the population, N, in contrast to the logarithmic slow scaling of the conventional rate-WTA sensitivity with N. Noise correlations in first-spike times of different cells can limit the accuracy of the tWTA readout, even in the limit of large N, similar to the effect that has been observed in population coding theory. We show that baseline firing also has a detrimental effect on tWTA accuracy. We suggest a generalization of the tWTA, the n-tWTA, which estimates the stimulus by the identity of the group of cells firing the first n spikes and show how this simple generalization can overcome the detrimental effect of baseline firing. Thus, the tWTA can provide fast and accurate responses discriminating between a small number of alternatives. High accuracy in estimation of a continuous stimulus can be obtained using the n-tWTA

Retuning of Inferior Colliculus Neurons Following Spiral Ganglion Lesions: A Single-Neuron Model of Converging Inputs

Lesions of spiral ganglion cells, representing a restricted sector of the auditory nerve array, produce immediate changes in the frequency tuning of inferior colliculus (IC) neurons. There is a loss of excitation at the lesion frequencies, yet responses to adjacent frequencies remain intact and new regions of activity appear. This leads to immediate changes in tuning and in tonotopic progression. Similar effects are seen after different methods of peripheral damage and in auditory neurons in other nuclei. The mechanisms that underlie these postlesion changes are unknown, but the acute effects seen in IC strongly suggest the “unmasking” of latent inputs by the removal of inhibition. In this study, we explore computational models of single neurons with a convergence of excitatory and inhibitory inputs from a range of characteristic frequencies (CFs), which can simulate the narrow prelesion tuning of IC neurons, and account for the changes in CF tuning after a lesion. The models can reproduce the data if inputs are aligned relative to one another in a precise order along the dendrites of model IC neurons. Frequency tuning in these neurons approximates that seen physiologically. Removal of inputs representing a narrow range of frequencies leads to unmasking of previously subthreshold excitatory inputs, which causes changes in CF. Conversely, if all of the inputs converge at the same point on the cell body, receptive fields are broad and unmasking rarely results in CF changes. However, if the inhibition is tonic with no stimulus-driven component, then unmasking can still produce changes in CF

Screening and Initial Binding Assessment of Fumonisin B1 Aptamers

Fumonisins are mycotoxins produced by Fusarium verticillioides and F. proliferatum, fungi that are ubiquitous in corn (maize). Insect damage and some other environmental conditions result in the accumulation of fumonisins in corn-based products worldwide. Current methods of fumonisin detection rely on the use of immunoaffinity columns and high-performance liquid chromatography (HPLC). The use of aptamers offers a good alternative to the use of antibodies in fumonisin cleanup and detection due to lower costs and improved stability. Aptamers are single-stranded oligonucleotides that are selected using Systematic Evolution of Ligands by EXponential enrichment (SELEX) for their ability to bind to targets with high affinity and specificity. Sequences obtained after 18 rounds of SELEX were screened for their ability to bind to fumonisin B1. Six unique sequences were obtained, each showing improved binding to fumonisin B1 compared to controls. Sequence FB1 39 binds to fumonisin with a dissociation constant of 100 ± 30 nM and shows potential for use in fumonisin biosensors and solid phase extraction columns

Role of HPV Genotype, Multiple Infections, and Viral Load on the Risk of High-Grade Cervical Neoplasia

Background:HPV testing provides a much more sensitive method of detection for high-grade lesions than cytology, but specificity is low. Here we explore the extent to which full HPV genotyping, viral load and multiplicity of types can be used to improve specificity. Methods:A population-based sample of 47,120 women undergoing cervical screening were tested for 13 high-risk HPV genotypes. Positive predictive values (PPV) for CIN grade 2 or worse (CIN2+; N=3449) and CIN3 or worse (CIN3+; N=1475) over three years of follow-up were estimated for HPV genotype and viral load. Weighted multivariate logistic regression models were used to estimate the odds of CIN2+ or CIN3+ according to genotype, multiplicity of types and viral load. Results:High-risk HPV was detected in 15.4% of women. A hierarchy of HPV genotypes based on sequentially maximizing PPVs for CIN3+ found HPV16>33>31 to be the most predictive, followed sequentially by HPV18>35>58>45>52>59>51>39>56>68. After adjusting for higher ranked genotypes, multiple HPV infections added little to risk prediction. High viral loads for HPV18, 35, 52 and 58 carried more risk than low viral loads for HPV16, 31 and 33. High viral load for HPV16 was significantly more associated with CIN3+ than low viral load. Conclusions:HPV genotype and viral load, but not multiplicity of HPV infections, are important predictors of CIN2+ and CIN3+. Impact:The ability to identify women at higher risk of CIN2+ and CIN3+ based on both HPV genotype and viral load could be important for individualising triage plans, particularly as HPV becomes the primary screening test

Ligand-induced sequestering of branchpoint sequence allows conditional control of splicing

<p>Abstract</p> <p>Background</p> <p>Despite tremendous progress in understanding the mechanisms of constitutive and alternative splicing, an important and widespread step along the gene expression pathway, our ability to deliberately regulate gene expression at this step remains rudimentary. The present study was performed to investigate whether a theophylline-dependent "splice switch" that sequesters the branchpoint sequence (BPS) within RNA-theophylline complex can regulate alternative splicing.</p> <p>Results</p> <p>We constructed a series of pre-mRNAs in which the BPS was inserted within theophylline aptamer. We show that theophylline-induced sequestering of BPS inhibits pre-mRNA splicing both in vitro and in vivo in a dose-dependent manner. Several lines of evidence suggest that theophylline-dependent inhibition of splicing is highly specific, and thermodynamic stability of RNA-theophylline complex as well as the location of BPS within this complex affects the efficiency of splicing inhibition. Finally, we have constructed an alternative splicing model pre-mRNA substrate in which theophylline caused exon skipping both in vitro and in vivo, suggesting that a small molecule-RNA interaction can modulate alternative splicing.</p> <p>Conclusion</p> <p>These findings provide the ability to control splicing pattern at will and should have important implications for basic, biotechnological, and biomedical research.</p