Altered Neurocircuitry in the Dopamine Transporter Knockout Mouse Brain

The plasma membrane transporters for the monoamine neurotransmitters dopamine, serotonin, and norepinephrine modulate the dynamics of these monoamine neurotransmitters. Thus, activity of these transporters has significant consequences for monoamine activity throughout the brain and for a number of neurological and psychiatric disorders. Gene knockout (KO) mice that reduce or eliminate expression of each of these monoamine transporters have provided a wealth of new information about the function of these proteins at molecular, physiological and behavioral levels. In the present work we use the unique properties of magnetic resonance imaging (MRI) to probe the effects of altered dopaminergic dynamics on meso-scale neuronal circuitry and overall brain morphology, since changes at these levels of organization might help to account for some of the extensive pharmacological and behavioral differences observed in dopamine transporter (DAT) KO mice. Despite the smaller size of these animals, voxel-wise statistical comparison of high resolution structural MR images indicated little morphological change as a consequence of DAT KO. Likewise, proton magnetic resonance spectra recorded in the striatum indicated no significant changes in detectable metabolite concentrations between DAT KO and wild-type (WT) mice. In contrast, alterations in the circuitry from the prefrontal cortex to the mesocortical limbic system, an important brain component intimately tied to function of mesolimbic/mesocortical dopamine reward pathways, were revealed by manganese-enhanced MRI (MEMRI). Analysis of co-registered MEMRI images taken over the 26 hours after introduction of Mn^(2+) into the prefrontal cortex indicated that DAT KO mice have a truncated Mn^(2+) distribution within this circuitry with little accumulation beyond the thalamus or contralateral to the injection site. By contrast, WT littermates exhibit Mn^(2+) transport into more posterior midbrain nuclei and contralateral mesolimbic structures at 26 hr post-injection. Thus, DAT KO mice appear, at this level of anatomic resolution, to have preserved cortico-striatal-thalamic connectivity but diminished robustness of reward-modulating circuitry distal to the thalamus. This is in contradistinction to the state of this circuitry in serotonin transporter KO mice where we observed more robust connectivity in more posterior brain regions using methods identical to those employed here

Kaposi's Sarcoma-Associated Herpesvirus ORF45 Interacts with Kinesin-2 Transporting Viral Capsid-Tegument Complexes along Microtubules

Open reading frame (ORF) 45 of Kaposi's sarcoma-associated herpesvirus (KSHV) is a tegument protein. A genetic analysis with a null mutant suggested a possible role for this protein in the events leading to viral egress. In this study, ORF45 was found to interact with KIF3A, a kinesin-2 motor protein that transports cargoes along microtubules to cell periphery in a yeast two-hybrid screen. The association was confirmed by both co-immunoprecipitation and immunoflorescence approaches in primary effusion lymphoma cells following virus reactivation. ORF45 principally mediated the docking of entire viral capsid-tegument complexes onto the cargo-binding domain of KIF3A. Microtubules served as the major highways for transportation of these complexes as evidenced by drastically reduced viral titers upon treatment of cells with a microtubule depolymerizer, nocodazole. Confocal microscopic images further revealed close association of viral particles with microtubules. Inhibition of KIF3A–ORF45 interaction either by the use of a headless dominant negative (DN) mutant of KIF3A or through shRNA-mediated silencing of endogenous KIF3A expression noticeably decreased KSHV egress reflecting as appreciable reductions in the release of extracellular virions. Both these approaches, however, failed to impact HSV-1 egress, demonstrating the specificity of KIF3A in KSHV transportation. This study thus reports on transportation of KSHV viral complexes on microtubules by KIF3A, a kinesin motor thus far not implicated in virus transportation. All these findings shed light on the understudied but significant events in the KSHV life cycle, delineating a crucial role of a KSHV tegument protein in cellular transport of viral particles

Synergistic Activity of Rhamnolipid Biosurfactant and Nanoparticles Synthesized Using Fungal Origin Chitosan Against Phytopathogens.

Phytopathogens pose severe implications in the quantity and quality of food production by instigating several diseases. Biocontrol strategies comprising the application of biomaterials have offered endless opportunities for sustainable agriculture. We explored multifarious potentials of rhamnolipid-BS (RH-BS: commercial), fungal chitosan (FCH), and FCH-derived nanoparticles (FCHNPs). The high-quality FCH was extracted from Cunninghamella echinulata NCIM 691 followed by the synthesis of FCHNPs. Both, FCH and FCHNPs were characterized by UV-visible spectroscopy, DLS, zeta potential, FTIR, SEM, and Nanoparticle Tracking Analysis (NTA). The commercial chitosan (CH) and synthesized chitosan nanoparticles (CHNPs) were used along with test compounds (FCH and FCHNPs). SEM analysis revealed the spherical shape of the nanomaterials (CHNPs and FCHNPs). NTA provided high-resolution visual validation of particle size distribution for CHNPs (256.33 ± 18.80 nm) and FCHNPs (144.33 ± 10.20 nm). The antibacterial and antifungal assays conducted for RH-BS, FCH, and FCHNPs were supportive to propose their efficacies against phytopathogens. The lower MIC of RH-BS (256 μg/ml) was observed than that of FCH and FCHNPs (>1,024 μg/ml) against Xanthomonas campestris NCIM 5028, whereas a combination study of RH-BS with FCHNPs showed a reduction in MIC up to 128 and 4 μg/ml, respectively, indicating their synergistic activity. The other combination of RH-BS with FCH resulted in an additive effect reducing MIC up to 128 and 256 μg/ml, respectively. Microdilution plate assay conducted for three test compounds demonstrated inhibition of fungi, FI: Fusarium moniliforme ITCC 191, FII: Fusarium moniliforme ITCC 4432, and FIII: Fusarium graminearum ITCC 5334 (at 0.015% and 0.020% concentration). Furthermore, potency of test compounds performed through the in vitro model (poisoned food technique) displayed dose-dependent (0.005%, 0.010%, 0.015%, and 0.020% w/v) antifungal activity. Moreover, RH-BS and FCHNPs inhibited spore germination (61–90%) of the same fungi. Our efforts toward utilizing the combination of RH-BS with FCHNPs are significant to develop eco-friendly, low cytotoxic formulations in future

Assessing the Effect of Salt Stress on Soybean [Glycine max (L.) Merrillis] Genotypes Using AMMI and GGE Biplot Analysis

Not AvailableThe genotype × environment interaction manipulates the selection criteria in a multipurpose crop like soybean. A total 108 soybean genotypes were evaluated at normal tap water (Control), field sodicity conditions (pH 9.0 and 9.3) and saline water (ECiw 5.0 and 8.0 dS m-1) at ICAR-CSSRI, Karnal from 2017-2020. Yield and associated data were analyzed using the AMMI and GGE biplot. The AMMI analysis of variance for seed yield detected significant effects for genotype, environment and genotype × environment interaction. The environment effect was responsible for the greatest part of the variation, followed by genotype and genotype × environment interaction effects. The ‘which-won-where’ feature of the GGE biplot identified wining genotypes SL-1226 and SL-1258 in the saline (up to ECiw 8 dS m-1) and sodic (up to pH 9.3) and SL-1242 in control conditions whereas, PS-1225 across the environment was the most ideal and these genotypes could be used as donor for breeding soybean for salt tolerance. This indicates that characterization of germplasm using GGE and AMMI model is important for determining visual comparisons, adaptability/stability focusing on overall performance to identify superior genotypes.Not Availabl

A Flexible Scalable Hardware Architecture for Radial Basis Function Neural Networks

Radial Basis Function Neural Networks (RBFNN) are used in variety of applications such as pattern recognition, control and time series prediction and nonlinear identification. RBFNN with Gaussian Function as the basis function is considered for classification purpose. Training is done offline using K-means clustering method for center learning and Pseudo inverse for weight adjustments. Offline training is done since the objective function with any fixed set of weights can be computed and we can see whether we make any progress in training. Moreover, minimum of the objective function can be computed to any desired precision, while with online training none of these can be done and it is more difficult and unreliable. In this paper we provide the comparison of RBFNN implementation on FPGAs using soft core processor based multi-processor system versus a network of HyperCells 8], 13]. Next we propose three different partitioning structures (Linear, Tree and Hybrid) for the implementation of RBFNN of large dimensions. Our results show that implementation of RBFNN on a network of HyperCells using Hybrid Structure, has on average 26x clock cycle reduction and 105X improvement in the performance over that of multiprocessor system on FPGAs