Metabolic sensing in AgRP neurons integrates homeostatic state with dopamine signalling in the striatum

Agouti-related peptide (AgRP) neurons increase motivation for food, however, whether metabolic sensing of homeostatic state in AgRP neurons potentiates motivation by interacting with dopamine reward systems is unexplored. As a model of impaired metabolic-sensing, we used the AgRP-specific deletion of carnitine acetyltransferase

Implementing Synthetic Aperture Radar Backprojection in Chisel – A Field Report

Chisel is an emerging hardware description language which is especially popular in the RISC-V community. In this report, we evaluate its application in the field of general digital hardware design. A dedicated hardware implementation of a Synthetic Aperture Radar (SAR) processing algorithm is used as an example case for a real-world application. It is targeting a modern high performance FPGA platform. We analyze the difference in code size compared to a VHDL implementation. In contrast to related publications, we classify the code lines into several categories, providing a more detailed view. Overall, the number of lines was reduced by 74% while the amount of boilerplate code was reduced by 83%. Additionally, we report on our experience using Chisel in this practical application. We found the generative concept and the flexibility introduced by modern software paradigms superior to traditional hardware description languages. This increased productivity, especially during timing closure. However, additional programming skills not associated with classic hardware design are required to fully leverage its advantages. We recommend Chisel as a language for all hardware design tasks and expect its popularity to increase in the future

Planning a future randomized clinical trial based on a network of relevant past trials

Background The important role of network meta-analysis of randomized clinical trials in health technology assessment and guideline development is increasingly recognized. This approach has the potential to obtain conclusive results earlier than with new standalone trials or conventional, pairwise meta-analyses. Methods Network meta-analyses can also be used to plan future trials. We introduce a four-step framework that aims to identify the optimal design for a new trial that will update the existing evidence while minimizing the required sample size. The new trial designed within this framework does not need to include all competing interventions and comparisons of interest and can contribute direct and indirect evidence to the updated network meta-analysis. We present the method by virtually planning a new trial to compare biologics in rheumatoid arthritis and a new trial to compare two drugs for relapsing-remitting multiple sclerosis. Results A trial design based on updating the evidence from a network meta-analysis of relevant previous trials may require a considerably smaller sample size to reach the same conclusion compared with a trial designed and analyzed in isolation. Challenges of the approach include the complexity of the methodology and the need for a coherent network meta-analysis of previous trials with little heterogeneity. Conclusions When used judiciously, conditional trial design could significantly reduce the required resources for a new study and prevent experimentation with an unnecessarily large number of participants

Unacylated-Ghrelin Impairs Hippocampal Neurogenesis and Memory in Mice and Is Altered in Parkinson’s Dementia in Humans

Blood-borne factors regulate adult hippocampal neurogenesis and cognition in mammals. We report that elevating circulating unacylated-ghrelin (UAG), using both pharmacological and genetic methods, reduced hippocampal neurogenesis and plasticity in mice. Spatial memory impairments observed in ghrelin-O-acyl transferase-null (GOAT/) mice that lack acyl-ghrelin (AG) but have high levels of UAG were rescued by acyl-ghrelin. Acyl-ghrelin-mediated neurogenesis in vitro was dependent on non-cell-autonomous BDNF signaling that was inhibited by UAG. These findings suggest that post-translational acylation of ghrelin is important to neurogenesis and memory in mice. To determine relevance in humans, we analyzed circulating AG:UAG in Parkinson disease (PD) patients diagnosed with dementia (PDD), cognitively intact PD patients, and controls. Notably, plasma AG:UAG was only reduced in PDD. Hippocampal ghrelin-receptor expression remained unchanged; however, GOAT+ cell number was reduced in PDD. We identify UAG as a regulator of hippocampal-dependent plasticity and spatial memory and AG:UAG as a putative circulating diagnostic biomarker of dementia

Metabolic sensing in AgRP neurons integrates homeostatic state with dopamine signalling in the striatum

Agouti-related peptide (AgRP) neurons increase motivation for food, however, whether metabolic sensing of homeostatic state in AgRP neurons potentiates motivation by interacting with dopamine reward systems is unexplored. As a model of impaired metabolic-sensing, we used the AgRP-specific deletion of carnitine acetyltransferase (Crat) in mice. We hypothesised that metabolic sensing in AgRP neurons is required to increase motivation for food reward by modulating accumbal or striatal dopamine release. Studies confirmed that Crat deletion in AgRP neurons (KO) impaired ex vivo glucose-sensing, as well as in vivo responses to peripheral glucose injection or repeated palatable food presentation and consumption. Impaired metabolic-sensing in AgPP neurons reduced acute dopamine release (seconds) to palatable food consumption and during operant responding, as assessed by GRAB-DA photometry in the nucleus accumbens, but not the dorsal striatum. Impaired metabolic-sensing in AgRP neurons suppressed radiolabelled 18F-fDOPA accumulation after ~30 min in the dorsal striatum but not the nucleus accumbens. Impaired metabolic sensing in AgRP neurons suppressed motivated operant responding for sucrose rewards during fasting. Thus, metabolic-sensing in AgRP neurons is required for the appropriate temporal integration and transmission of homeostatic hunger-sensing to dopamine signalling in the striatum

Short-term calorie restriction enhances adult hippocampal neurogenesis and remote fear memory in a Ghsr-dependent manner

The beneficial effects of calorie restriction (CR) have been described at both organismal and cellular levels in multiple organs. However, our understanding of the causal mediators of such hormesis is poorly understood, particularly in the context of higher brain function. Here, we show that the receptor for the orexigenic hormone acyl-ghrelin, the growth hormone secretagogue receptor (Ghsr), is enriched in the neurogenic niche of the hippocampal dentate gyrus (DG). Acute elevation of acyl-ghrelin levels by injection or by overnight CR, increased DG levels of the neurogenic transcription factor, Egr-1. Two weeks of CR increased the subsequent number of mature newborn neurons in the DG of adult wild-type but not Ghsr−/− mice. CR wild-type mice also showed improved remote contextual fear memory. Our findings suggest that Ghsr mediates the beneficial effects of CR on enhancing adult hippocampal neurogenesis and memory

Classification and Cluster Analysis of Complex Time-of-Flight Secondary Ion Mass Spectrometry for Biological Samples

Identifying and separating subtly different biological samples is one of the most critical tasks in biological analysis. Time-of-flight secondary ion mass spectrometry (ToF-SIMS) is becoming a popular and important technique in the analysis of biological samples, because it can detect molecular information and characterize chemical composition. ToF-SIMS spectra of biological samples are enormously complex with large mass ranges and many peaks. As a result the classification and cluster analysis are challenging. This study presents a new classification algorithm, the most similar neighbor with a probability-based spectrum similarity measure (MSN- PSSM), which uses all the information in the entire ToF- SIMS spectra. MSN-PSSM is applied to automatically classify bacterial samples which are major causal agents of urinary tract infections. Experimental results show that MSN-PSSM is an accurate classification algorithm. It outperforms traditional techniques such as decision trees, principal component analysis (PCA) with discriminant function analysis (DFA), and soft independent modeling of class analogy (SIMCA). This study also applies a modern clustering algorithm, normalized spectral clustering, to automatically cluster the bacterial samples at the species level. Experimental results demonstrate that normalized spectral clustering is able to show accurate quantitative separations. It outperforms traditional techniques such as hierarchical clustering analysis, k- means, and PCA with k-means