Comparative actions of gaba and acetylcholine on the Xenopus laevis lateral line

1. The effects of GABA, acetylcholine and carbachol on the spontaneous activity of afferent nerve fibers in the lateral line of Xenopus laevis are characterized.2. Atropine and bicuculline were also tested on drug- and water motion-evoked activity.3. GABA (0.019-1.25 mM) suppressed and both acetylcholine (1.25-80 [mu]M) and carbachol (1.25-40 [mu]M) increased spontaneous activity. These actions were blocked by bicuculline (100 [mu]M) and atropine (4 [mu]M) respectively.4. Atropine (20 [mu]M) and bicuculline (100 [mu]M) had no effect on water motion-evoked activity.5. The results characterize actions of GABA and acetylcholine not previously described and provide evidence that does not support the hypothesis that GABA or acetylcholine are the afferent transmitter.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/25886/1/0000449.pd

Design of small molecule-responsive microRNAs based on structural requirements for Drosha processing

MicroRNAs (miRNAs) are prevalent regulatory RNAs that mediate gene silencing and play key roles in diverse cellular processes. While synthetic RNA-based regulatory systems that integrate regulatory and sensing functions have been demonstrated, the lack of detail on miRNA structure–function relationships has limited the development of integrated control systems based on miRNA silencing. Using an elucidated relationship between Drosha processing and the single-stranded nature of the miRNA basal segments, we developed a strategy for designing ligand-responsive miRNAs. We demonstrate that ligand binding to an aptamer integrated into the miRNA basal segments inhibits Drosha processing, resulting in titratable control over gene silencing. The generality of this control strategy was shown for three aptamer–small molecule ligand pairs. The platform can be extended to the design of synthetic miRNAs clusters, cis-acting miRNAs and self-targeting miRNAs that act both in cis and trans, enabling fine-tuning of the regulatory strength and dynamics. The ability of our ligand-responsive miRNA platform to respond to user-defined inputs, undergo regulatory performance tuning and display scalable combinatorial control schemes will help advance applications in biological research and applied medicine

Expression of UV-Sensitive Parapinopsin in the Iguana Parietal Eyes and Its Implication in UV-Sensitivity in Vertebrate Pineal-Related Organs

The pineal-related organs of lower vertebrates have the ability to discriminate different wavelengths of light. This wavelength discrimination is achieved through antagonistic light responses to UV or blue and visible light. Previously, we demonstrated that parapinopsin underlies the UV reception in the lamprey pineal organ and identified parapinopsin genes in teleosts and frogs of which the pineal-related organs were reported to discriminate light. In this study, we report the first identification of parapinopsin in the reptile lineage and show its expression in the parietal eye of the green iguana. Spectroscopic analysis revealed that iguana parapinopsin is a UV-sensitive pigment, similar to lamprey parapinopsin. Interestingly, immunohistochemical analyses using antibodies specific to parapinopsin and parietopsin, a parietal eye green-sensitive pigment, revealed that parapinopsin and parietopsin are colocalized in the outer segments of the parietal eye photoreceptor cells in iguanas. These results strongly suggest that parapinopsin underlies the wavelength discrimination involving UV reception in the iguana parietal eye. The current findings support the idea that parapinopsin is a common photopigment underlying the UV-sensitivity in wavelength discrimination of the pineal-related organs found from lampreys to reptiles

Aptamers that recognize drug-resistant HIV-1 reverse transcriptase

Drug-resistant variants of HIV-1 reverse transcriptase (RT) are also known to be resistant to anti-RT RNA aptamers. In order to be able to develop diagnostics and therapies that can focus on otherwise drug-resistant viruses, we have isolated two aptamers against a well-known, drug-resistant HIV-1 RT, Mutant 3 (M3) from the multidrug-resistant HIV-1 RT panel. One aptamer, M302, bound M3 but showed no significant affinity for wild-type (WT) HIV-1 RT, while another aptamer, 12.01, bound to both M3 and WT HIV-1 RTs. In contrast to all previously selected anti-RT aptamers, neither of these aptamers showed observable inhibition of either polymerase or RNase H activities. Aptamers M302 and 12.01 competed with one another for binding to M3, but they did not compete with a pseudoknot aptamer for binding to the template/primer cleft of WT HIV-1 RT. These results represent the surprising identification of an additional RNA-binding epitope on the surface of HIV-1 RT. M3 and WT HIV-1 RTs could be distinguished using an aptamer-based microarray. By probing protein conformation as a correlate to drug resistance we introduce an additional and useful measure for determining HIV-1 drug resistance

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

Identification of Novel Therapeutic Targets in Microdissected Clear Cell Ovarian Cancers

Clear cell ovarian cancer is an epithelial ovarian cancer histotype that is less responsive to chemotherapy and carries poorer prognosis than serous and endometrioid histotypes. Despite this, patients with these tumors are treated in a similar fashion as all other ovarian cancers. Previous genomic analysis has suggested that clear cell cancers represent a unique tumor subtype. Here we generated the first whole genomic expression profiling using epithelial component of clear cell ovarian cancers and normal ovarian surface specimens isolated by laser capture microdissection. All the arrays were analyzed using BRB ArrayTools and PathwayStudio software to identify the signaling pathways. Identified pathways validated using serous, clear cell cancer cell lines and RNAi technology. In vivo validations carried out using an orthotopic mouse model and liposomal encapsulated siRNA. Patient-derived clear cell and serous ovarian tumors were grafted under the renal capsule of NOD-SCID mice to evaluate the therapeutic potential of the identified pathway. We identified major activated pathways in clear cells involving in hypoxic cell growth, angiogenesis, and glucose metabolism not seen in other histotypes. Knockdown of key genes in these pathways sensitized clear cell ovarian cancer cell lines to hypoxia/glucose deprivation. In vivo experiments using patient derived tumors demonstrate that clear cell tumors are exquisitely sensitive to antiangiogenesis therapy (i.e. sunitinib) compared with serous tumors. We generated a histotype specific, gene signature associated with clear cell ovarian cancer which identifies important activated pathways critical for their clinicopathologic characteristics. These results provide a rational basis for a radically different treatment for ovarian clear cell patients

State-Space Analysis of Time-Varying Higher-Order Spike Correlation for Multiple Neural Spike Train Data

Precise spike coordination between the spiking activities of multiple neurons is suggested as an indication of coordinated network activity in active cell assemblies. Spike correlation analysis aims to identify such cooperative network activity by detecting excess spike synchrony in simultaneously recorded multiple neural spike sequences. Cooperative activity is expected to organize dynamically during behavior and cognition; therefore currently available analysis techniques must be extended to enable the estimation of multiple time-varying spike interactions between neurons simultaneously. In particular, new methods must take advantage of the simultaneous observations of multiple neurons by addressing their higher-order dependencies, which cannot be revealed by pairwise analyses alone. In this paper, we develop a method for estimating time-varying spike interactions by means of a state-space analysis. Discretized parallel spike sequences are modeled as multi-variate binary processes using a log-linear model that provides a well-defined measure of higher-order spike correlation in an information geometry framework. We construct a recursive Bayesian filter/smoother for the extraction of spike interaction parameters. This method can simultaneously estimate the dynamic pairwise spike interactions of multiple single neurons, thereby extending the Ising/spin-glass model analysis of multiple neural spike train data to a nonstationary analysis. Furthermore, the method can estimate dynamic higher-order spike interactions. To validate the inclusion of the higher-order terms in the model, we construct an approximation method to assess the goodness-of-fit to spike data. In addition, we formulate a test method for the presence of higher-order spike correlation even in nonstationary spike data, e.g., data from awake behaving animals. The utility of the proposed methods is tested using simulated spike data with known underlying correlation dynamics. Finally, we apply the methods to neural spike data simultaneously recorded from the motor cortex of an awake monkey and demonstrate that the higher-order spike correlation organizes dynamically in relation to a behavioral demand

Aptamers for pharmaceuticals and their application in environmental analytics

Aptamers are single-stranded DNA or RNA oligonucleotides, which are able to bind with high affinity and specificity to their target. This property is used for a multitude of applications, for instance as molecular recognition elements in biosensors and other assays. Biosensor application of aptamers offers the possibility for fast and easy detection of environmental relevant substances. Pharmaceutical residues, deriving from human or animal medical treatment, are found in surface, ground, and drinking water. At least the whole range of frequently administered drugs can be detected in noticeable concentrations. Biosensors and assays based on aptamers as specific recognition elements are very convenient for this application because aptamer development is possible for toxic targets. Commonly used biological receptors for biosensors like enzymes or antibodies are mostly unavailable for the detection of pharmaceuticals. This review describes the research activities of aptamer and sensor developments for pharmaceutical detection, with focus on environmental applications