Observation of intraseasonal oscillation of 64 day in the ionospheric sporadic E layers using Indian MST Radar, SABER / TIMED instrument and Ionosonde present at Gadanki(13.5 N,79.2 E)

15th MST Radar WorkshopSession M6: Middle atmosphere dynamics and structureMay 30 (Tue), Poster Sessio

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Global metabolic network indicating taxonomic representation of metabolic activities within the cow rumen dataset. Global metabolic network indicating taxonomic representation of metabolic activities within the cow rumen dataset. Pie charts indicate the relative proportion of each taxon, size of pie chart indicates relative expression (see key). Indicated are specific metabolic pathways. (PDF 1162 kb

Additional file 10: Figure S5. of Perilipin-2 modulates dietary fat-induced microbial global gene expression profiles in the mouse intestine

Diet-based comparisons of enzyme expression in pantothenate pathway. Two comparisons are shown: (A) Plin2-HF vs. Plin2-LF and (B) WT-HF vs. WT-LF. Circular nodes indicate enzymes, with size indicating relative difference in expression between sample types and color indicating direction of change (see inset key). Associated heatmaps indicate global changes in expression for each enzyme, in addition to taxon-specific changes in expression for each of the 17 defined taxa colored according to phylum. The following abbreviations are used: 5,6-dh-uracil (5,6-dihydro-uracil), N-cm-β-alanine (N-carbamoyl-β-alanine), N-pt-Cys (N-pantothenoyl-cysteine), and (R)-4′-P-pt-L-Cys ((R)-4′-phospho-pantothenoyl-l-cysteine. (PDF 1119 kb

Additional file 3: Figure S1. of Perilipin-2 modulates dietary fat-induced microbial global gene expression profiles in the mouse intestine

Principal component analysis for four data types (Taxa, Enzymes, Significant Differentially Expressed Transcripts and Metabolic Pathways). With each plot, p values (< 0.05) are provided indicating significant differences in clustering between each of the four pairwise comparisons. (PDF 912 kb

Additional file 8: Figure S3. of Perilipin-2 modulates dietary fat-induced microbial global gene expression profiles in the mouse intestine

Comparison of glycolysis pathway enzyme expression between sample types. Three comparisons are shown: (A) Plin2-LF vs. WT-LF; (B) Plin2-HF vs. Plin2-LF; (C) WT-HF vs. WT-LF. Circular nodes indicate enzymes, with size indicating relative difference in expression between sample types and color indicating direction of change (see inset key). Associated heatmaps indicate global changes in expression for each enzyme, in addition to taxon-specific changes in expression for each of the 17 defined taxa colored according to phylum. (PDF 1138 kb

Additional file 2: Table S2. of Perilipin-2 modulates dietary fat-induced microbial global gene expression profiles in the mouse intestine

Expression values (RPKM) for each of the 57,736 transcripts identified across all samples. (XLSX 35991 kb

Additional file 14: Figure S8. of Perilipin-2 modulates dietary fat-induced microbial global gene expression profiles in the mouse intestine

Rarefaction analysis of annotated mRNA reads. Recovery of species (A) and enzymes (B) with increasing numbers of annotated mRNA reads (reads mapped to known transcripts) indicate that sequencing depth for each sample was sufficient to recover the vast majority of species and enzymes present within each of the 16 samples. Rarefaction analysis was performed using R. (PDF 16825 kb

Identification of a Functional Connectome for Long-Term Fear Memory in Mice

<div><p>Long-term memories are thought to depend upon the coordinated activation of a broad network of cortical and subcortical brain regions. However, the distributed nature of this representation has made it challenging to define the neural elements of the memory trace, and lesion and electrophysiological approaches provide only a narrow window into what is appreciated a much more global network. Here we used a global mapping approach to identify networks of brain regions activated following recall of long-term fear memories in mice. Analysis of Fos expression across 84 brain regions allowed us to identify regions that were co-active following memory recall. These analyses revealed that the functional organization of long-term fear memories depends on memory age and is altered in mutant mice that exhibit premature forgetting. Most importantly, these analyses indicate that long-term memory recall engages a network that has a distinct thalamic-hippocampal-cortical signature. This network is concurrently integrated and segregated and therefore has small-world properties, and contains hub-like regions in the prefrontal cortex and thalamus that may play privileged roles in memory expression.</p> </div

Generation of long-term fear memory networks.

<p><b>A</b>. Matrices showing inter-regional correlations for Fos expression at the short (upper) and long (lower) retention delays. Axes are numbered, and correspond to brain regions listed in <b><a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1002853#pcbi.1002853.s016" target="_blank">Table S1</a></b>. Colors reflect correlation strength (scale, right). <b>B</b>. Network graphs were generated by considering only the strongest correlations (Pearson's r≥0.83). In these graphs, regions are grouped by major brain subdivision and node size is proportional to the number of connections (degree) while the weight of the connection is proportional to correlation strength.</p

Fos is induced by contextual fear memory recall.

<p><b>A.</b> Experimental design. Mice were trained, and fear memory was assessed either 1 (short delay) or 36 (long delay) days later. Ninety minutes following this test, brains were removed and expression of the activity-regulated gene, c-fos, was evaluated immunohistochemically. <b>B.</b> Percent freezing at the 1 day or 36 day retention test in trained (black bars) or control (open bars) mice. <b>C–D.</b> Task PLS analysis of Fos expression in trained vs. control mice tested 1 or 36 days following training. These analyses identified LVs (left graph) that strongly differentiated the trained vs. control conditions at both the (<b>C</b>) short and (<b>D</b>) long retention delays. Salience scores (right) identify regions that maximally differentiate between these conditions at both the (<b>C</b>) short and (<b>D</b>) long retention delays. The hatched line reflects a salience score of 3, above which the contribution of the regions is considered reliable. At the short delay, Fos expression in the hippocampus contributed strongly to this contrast, whereas at the longer retention delay, Fos expression in multiple brain regions contributed to the contrast.</p