140 research outputs found
Body randomization reduces the sim-to-real gap for compliant quadruped locomotion
Designing controllers for compliant, underactuated robots is challenging and usually requires a learning procedure. Learning robotic control in simulated environments can speed up the process whilst lowering risk of physical damage. Since perfect simulations are unfeasible, several techniques are used to improve transfer to the real world. Here, we investigate the impact of randomizing body parameters during learning of CPG controllers in simulation. The controllers are evaluated on our physical quadruped robot. We find that body randomization in simulation increases chances of finding gaits that function well on the real robot
PyTorch-Hebbian : facilitating local learning in a deep learning framework
Recently, unsupervised local learning, based on Hebb's idea that change in
synaptic efficacy depends on the activity of the pre- and postsynaptic neuron
only, has shown potential as an alternative training mechanism to
backpropagation. Unfortunately, Hebbian learning remains experimental and
rarely makes it way into standard deep learning frameworks. In this work, we
investigate the potential of Hebbian learning in the context of standard deep
learning workflows. To this end, a framework for thorough and systematic
evaluation of local learning rules in existing deep learning pipelines is
proposed. Using this framework, the potential of Hebbian learned feature
extractors for image classification is illustrated. In particular, the
framework is used to expand the Krotov-Hopfield learning rule to standard
convolutional neural networks without sacrificing accuracy compared to
end-to-end backpropagation. The source code is available at
https://github.com/Joxis/pytorch-hebbian.Comment: Presented as a poster at the NeurIPS 2020 Beyond Backpropagation
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Populations of spiking neurons for reservoir computing : closed loop control of a compliant quadruped
Compliant robots can be more versatile than traditional robots, but their
control is more complex. The dynamics of compliant bodies can however
be turned into an advantage using the physical reservoir computing frame-
work. By feeding sensor signals to the reservoir and extracting motor signals
from the reservoir, closed loop robot control is possible. Here, we present
a novel framework for implementing central pattern generators with spik-
ing neural networks to obtain closed loop robot control. Using the FORCE
learning paradigm, we train a reservoir of spiking neuron populations to act
as a central pattern generator. We demonstrate the learning of predefined
gait patterns, speed control and gait transition on a simulated model of a
compliant quadrupedal robot
Deep sequencing reveals differential expression of microRNAs in favorable versus unfavorable neuroblastoma
Small non-coding RNAs, in particular microRNAs(miRNAs), regulate fine-tuning of gene expression and can act as oncogenes or tumor suppressor genes. Differential miRNA expression has been reported to be of functional relevance for tumor biology. Using next-generation sequencing, the unbiased and absolute quantification of the small RNA transcriptome is now feasible. Neuroblastoma(NB) is an embryonal tumor with highly variable clinical course. We analyzed the small RNA transcriptomes of five favorable and five unfavorable NBs using SOLiD next-generation sequencing, generating a total of >188 000 000 reads. MiRNA expression profiles obtained by deep sequencing correlated well with real-time PCR data. Cluster analysis differentiated between favorable and unfavorable NBs, and the miRNA transcriptomes of these two groups were significantly different. Oncogenic miRNAs of the miR17-92 cluster and the miR-181 family were overexpressed in unfavorable NBs. In contrast, the putative tumor suppressive microRNAs, miR-542-5p and miR-628, were expressed in favorable NBs and virtually absent in unfavorable NBs. In-depth sequence analysis revealed extensive post-transcriptional miRNA editing. Of 13 identified novel miRNAs, three were further analyzed, and expression could be confirmed in a cohort of 70 NBs
Human fetal neuroblast and neuroblastoma transcriptome analysis confirms neuroblast origin and highlights neuroblastoma candidate genes
BACKGROUND: Neuroblastoma tumor cells are assumed to originate from primitive neuroblasts giving rise to the sympathetic nervous system. Because these precursor cells are not detectable in postnatal life, their transcription profile has remained inaccessible for comparative data mining strategies in neuroblastoma. This study provides the first genome-wide mRNA expression profile of these human fetal sympathetic neuroblasts. To this purpose, small islets of normal neuroblasts were isolated by laser microdissection from human fetal adrenal glands. RESULTS: Expression of catecholamine metabolism genes, and neuronal and neuroendocrine markers in the neuroblasts indicated that the proper cells were microdissected. The similarities in expression profile between normal neuroblasts and malignant neuroblastomas provided strong evidence for the neuroblast origin hypothesis of neuroblastoma. Next, supervised feature selection was used to identify the genes that are differentially expressed in normal neuroblasts versus neuroblastoma tumors. This approach efficiently sifted out genes previously reported in neuroblastoma expression profiling studies; most importantly, it also highlighted a series of genes and pathways previously not mentioned in neuroblastoma biology but that were assumed to be involved in neuroblastoma pathogenesis. CONCLUSION: This unique dataset adds power to ongoing and future gene expression studies in neuroblastoma and will facilitate the identification of molecular targets for novel therapies. In addition, this neuroblast transcriptome resource could prove useful for the further study of human sympathoadrenal biogenesis
CADM1 is a strong neuroblastoma candidate gene that maps within a 3.72 Mb critical region of loss on 11q23
<p>Abstract</p> <p>Background</p> <p>Recurrent loss of part of the long arm of chromosome 11 is a well established hallmark of a subtype of aggressive neuroblastomas. Despite intensive mapping efforts to localize the culprit 11q tumour suppressor gene, this search has been unsuccessful thus far as no sufficiently small critical region could be delineated for selection of candidate genes.</p> <p>Methods</p> <p>To refine the critical region of 11q loss, the chromosome 11 status of 100 primary neuroblastoma tumours and 29 cell lines was analyzed using a BAC array containing a chromosome 11 tiling path. For the genes mapping within our refined region of loss, meta-analysis on published neuroblastoma mRNA gene expression datasets was performed for candidate gene selection. The DNA methylation status of the resulting candidate gene was determined using re-expression experiments by treatment of neuroblastoma cells with the demethylating agent 5-aza-2'-deoxycytidine and bisulphite sequencing.</p> <p>Results</p> <p>Two small critical regions of loss within 11q23 at chromosomal band 11q23.1-q23.2 (1.79 Mb) and 11q23.2-q23.3 (3.72 Mb) were identified. In a first step towards further selection of candidate neuroblastoma tumour suppressor genes, we performed a meta-analysis on published expression profiles of 692 neuroblastoma tumours. Integration of the resulting candidate gene list with expression data of neuroblastoma progenitor cells pinpointed <it>CADM1 </it>as a compelling candidate gene. Meta-analysis indicated that <it>CADM1 </it>expression has prognostic significance and differential expression for the gene was noted in unfavourable neuroblastoma versus normal neuroblasts. Methylation analysis provided no evidence for a two-hit mechanism in 11q deleted cell lines.</p> <p>Conclusion</p> <p>Our study puts <it>CADM1 </it>forward as a strong candidate neuroblastoma suppressor gene. Further functional studies are warranted to elucidate the role of <it>CADM1 </it>in neuroblastoma development and to investigate the possibility of <it>CADM1 </it>haploinsufficiency in neuroblastoma.</p
Focal DNA copy number changes in neuroblastoma target MYCN regulated genes
Neuroblastoma is an embryonic tumor arising from immature sympathetic nervous system cells. Recurrent genomic alterations include MYCN and ALK amplification as well as recurrent patterns of gains and losses of whole or large partial chromosome segments. A recent whole genome sequencing effort yielded no frequently recurring mutations in genes other than those affecting ALK. However, the study further stresses the importance of DNA copy number alterations in this disease, in particular for genes implicated in neuritogenesis. Here we provide additional evidence for the importance of focal DNA copy number gains and losses, which are predominantly observed in MYCN amplified tumors. A focal 5 kb gain encompassing the MYCN regulated miR-17,92 cluster as sole gene was detected in a neuroblastoma cell line and further analyses of the array CGH data set demonstrated enrichment for other MYCN target genes in focal gains and amplifications. Next we applied an integrated genomics analysis to prioritize MYCN down regulated genes mediated by MYCN driven miRNAs within regions of focal heterozygous or homozygous deletion. We identified RGS5, a negative regulator of G-protein signaling implicated in vascular normalization, invasion and metastasis, targeted by a focal homozygous deletion, as a new MYCN target gene, down regulated through MYCN activated miRNAs. In addition, we expand the miR-17,92 regulatory network controlling TGFß signaling in neuroblastoma with the ring finger protein 11 encoding gene RNF11, which was previously shown to be targeted by the miR-17,92 member miR-19b. Taken together, our data indicate that focal DNA copy number imbalances in neuroblastoma (1) target genes that are implicated in MYCN signaling, possibly selected to reinforce MYCN oncogene addiction and (2) serve as a resource for identifying new molecular targets for treatment
Botrydial and botcinins produced by Botrytis cinerea regulate the expression of Trichoderma arundinaceum genes involved in trichothecene biosynthesis
Trichoderma arundinaceum IBT 40837 (Ta37) and Botrytis cinerea produce the sesquiterpenes harzianum A (HA) and botrydial (BOT), respectively, and also the polyketides aspinolides and botcinins (Botcs), respectively. We analysed the role of BOT and Botcs in the Ta37–B. cinerea interaction, including the transcriptomic changes in the genes involved in HA (tri) and ergosterol biosynthesis, as well as changes in the level of HA and squaleneergosterol.
We found that, when confronted with B. cinerea, the tri biosynthetic genes were up-regulated in all dual cultures analysed, but at higher levels when Ta37 was confronted with the BOT non-producer mutant bcbot2D. The production of HA was also higher in the interaction area with this mutant. In Ta37– bcbot2D confrontation experiments, the expression of the hmgR gene, encoding the 3-hydroxy-3-methylglutaryl coenzyme A reductase, which is the first enzyme of the terpene biosynthetic pathway, was also up-regulated, resulting in an increase in squalene production compared with the confrontation with B. cinerea B05.10. Botcs had an up-regulatory effect on the tri biosynthetic
genes, with BotcA having a stronger effect than BotcB. The results indicate that the interaction between Ta37 and B. cinerea exerts a stimulatory effect on the expression of the tri biosynthetic genes, which, in the interaction zone, can be attenuated by BOT produced by B. cinerea B05.10. The present work provides evidence for a metabolic dialogue between T. arundinaceum and B. cinerea that is mediated by sesquiterpenes and polyketides, and that affects the outcome of the interaction of these fungi with each other and their environment
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