Generative Models from the perspective of Continual Learning

Which generative model is the most suitablefor Continual Learning? This paper aims at evaluating andcomparing generative models on disjoint sequential imagegeneration tasks. We investigate how several models learn andforget, considering various strategies: rehearsal, regularization,generative replay and fine-tuning. We used two quantitativemetrics to estimate the generation quality and memory ability.We experiment with sequential tasks on three commonly usedbenchmarks for Continual Learning (MNIST, Fashion MNISTand CIFAR10). We found that among all models, the originalGAN performs best and among Continual Learning strategies,generative replay outperforms all other methods. Even ifwe found satisfactory combinations on MNIST and FashionMNIST, training generative models sequentially on CIFAR10is particularly instable, and remains a challenge. Our code isavailable online

Reciprocal Changes in Factor XIII and Retinal Transglutaminase Expressions in the Fish Retina During Optic Nerve Regeneration

[email protected] mammals, fish retinal ganglion cells have the capacity to repair their axons even after optic nerve transection. In the process of fish optic nerve regeneration, a large number of genes have been described as regeneration-associated molecules. Using molecular cloning techniques, we identified two types of cDNA clones belonging to the transglutaminase (TG) family which were upregulation genes; one is cellular factor XIII (cFXIII) and the other is a tissue type TG named retinal transglutaminase (TGR). cFXIII mRNA started to increase in the retinal ganglion cells at 1-2 days, peaked at 5-7 days, and returned to the control level by 20 days post optic nerve injury. In contrast, TGR mRNA started to increase at day 5-10, peaked at day 20, and then gradually decreased by day 40 after nerve injury. To elucidate the molecular involvement of these TGs in optic nerve regeneration, we studied the effects of recombinant TGR protein or overexpression of cFXIII using a retinal explant culture system. cFXIII effectively induced neurite outgrowth only from naïve (intact) retinas. In contrast, the TGR protein significantly enhanced neurite outgrowth only from primed retinas, in which the optic nerve had been crushed 5-7 days previously. These reciprocal expressions of cFXIII and TGR suggest that these two types of TGs are important for the neurite sprouting and axonal elongation processes, respectively, during optic nerve regeneration processes

Deterministic approach to microscopic three-phase traffic theory

Two different deterministic microscopic traffic flow models, which are in the context of the Kerner's there-phase traffic theory, are introduced. In an acceleration time delay model (ATD-model), different time delays in driver acceleration associated with driver behaviour in various local driving situations are explicitly incorporated into the model. Vehicle acceleration depends on local traffic situation, i.e., whether a driver is within the free flow, or synchronized flow, or else wide moving jam traffic phase. In a speed adaptation model (SA-model), vehicle speed adaptation occurs in synchronized flow depending on driving conditions. It is found that the ATD- and SA-models show spatiotemporal congested traffic patterns that are adequate with empirical results. In the ATD- and SA-models, the onset of congestion in free flow at a freeway bottleneck is associated with a first-order phase transition from free flow to synchronized flow; moving jams emerge spontaneously in synchronized flow only. Differences between the ATD- and SA-models are studied. A comparison of the ATD- and SA-models with stochastic models in the context of three phase traffic theory is made. A critical discussion of earlier traffic flow theories and models based on the fundamental diagram approach is presented.Comment: 40 pages, 14 figure

14-3-3theta Protects against Neurotoxicity in a Cellular Parkinson's Disease Model through Inhibition of the Apoptotic Factor Bax

Disruption of 14-3-3 function by alpha-synuclein has been implicated in Parkinson's disease. As 14-3-3s are important regulators of cell death pathways, disruption of 14-3-3s could result in the release of pro-apoptotic factors, such as Bax. We have previously shown that overexpression of 14-3-3θ reduces cell loss in response to rotenone and MPP+ in dopaminergic cell culture and reduces cell loss in transgenic C. elegans that overexpress alpha-synuclein. In this study, we investigate the mechanism for 14-3-3θ's neuroprotection against rotenone toxicity. While 14-3-3s can inhibit many pro-apoptotic factors, we demonstrate that inhibition of one factor in particular, Bax, is important to 14-3-3s' protection against rotenone toxicity in dopaminergic cells. We found that 14-3-3θ overexpression reduced Bax activation and downstream signaling events, including cytochrome C release and caspase 3 activation. Pharmacological inhibition or shRNA knockdown of Bax provided protection against rotenone, comparable to 14-3-3θ's neuroprotective effects. A 14-3-3θ mutant incapable of binding Bax failed to protect against rotenone. These data suggest that 14-3-3θ's neuroprotective effects against rotenone are at least partially mediated by Bax inhibition and point to a potential therapeutic role of 14-3-3s in Parkinson's disease

Accessible Cultural Heritage through Explainable Artificial Intelligence

International audienceEthics Guidelines for Trustworthy AI advocate for AI technology that is, among other things, more inclusive. Explainable AI (XAI) aims at making state of the art opaque models more transparent, and defends AI-based outcomes endorsed with a rationale explanation, i.e., an explanation that has as target the non-technical users. XAI and Responsible AI principles defend the fact that the audience expertise should be included in the evaluation of explainable AI systems. However, AI has not yet reached all public and audiences , some of which may need it the most. One example of domain where accessibility has not much been influenced by the latest AI advances is cultural heritage. We propose including minorities as special user and evaluator of the latest XAI techniques. In order to define catalytic scenarios for collaboration and improved user experience, we pose some challenges and research questions yet to address by the latest AI models likely to be involved in such synergy

Brain injury-associated biomarkers of TGF-beta1, S100B, GFAP, NF-L, tTG, AbetaPP, and tau were concomitantly enhanced and the UPS was impaired during acute brain injury caused by Toxocara canis in mice

BACKGROUND: Because the outcomes and sequelae after different types of brain injury (BI) are variable and difficult to predict, investigations on whether enhanced expressions of BI-associated biomarkers (BIABs), including transforming growth factor beta1 (TGF-beta1), S100B, glial fibrillary acidic protein (GFAP), neurofilament light chain( NF-L), tissue transglutaminases (tTGs), beta-amyloid precursor proteins (AbetaPP), and tau are present as well as whether impairment of the ubiquitin-proteasome system (UPS) is present have been widely used to help delineate pathophysiological mechanisms in various BIs. Larvae of Toxocara canis can invade the brain and cause BI in humans and mice, leading to cerebral toxocariasis (CT). Because the parasitic burden is light in CT, it may be too cryptic to be detected in humans, making it difficult to clearly understand the pathogenesis of subtle BI in CT. Since the pathogenesis of murine toxocariasis is very similar to that in humans, it appears appropriate to use a murine model to investigate the pathogenesis of CT. METHODS: BIAB expressions and UPS function in the brains of mice inoculated with a single dose of 250 T. canis embryonated eggs was investigated from 3 days (dpi) to 8 weeks post- infection (wpi) by Western blotting and RT-PCR. RESULTS: Results revealed that at 4 and 8 wpi, T. canis larvae were found to have invaded areas around the choroid plexus but without eliciting leukocyte infiltration in brains of infected mice; nevertheless, astrogliosis, an indicator of BI, with 78.9~142.0-fold increases in GFAP expression was present. Meanwhile, markedly increased levels of other BIAB proteins including TGF-beta1, S100B, NF-L, tTG, AbetaPP, and tau, with increases ranging 2.0~12.0-fold were found, although their corresponding mRNA expressions were not found to be present at 8 wpi. Concomitantly, UPS impairment was evidenced by the overexpression of conjugated ubiquitin and ubiquitin in the brain. CONCLUSION: Further studies are needed to determine whether there is an increased risk of CT progression into neurodegenerative disease because neurodegeneration-associated AbetaPP and phosphorylated tau emerged in the brain. DOI: 10.1186/1471-2334-8-8

Transglutaminase 6: a protein associated with central nervous system development and motor function.

Transglutaminases (TG) form a family of enzymes that catalyse various post-translational modifications of glutamine residues in proteins and peptides including intra- and intermolecular isopeptide bond formation, esterification and deamidation. We have characterized a novel member of the mammalian TG family, TG6, which is expressed in a human carcinoma cell line with neuronal characteristics and in mouse brain. Besides full-length protein, alternative splicing results in a short variant lacking the second β-barrel domain in man and a variant with truncated β-sandwich domain in mouse. Biochemical data show that TG6 is allosterically regulated by Ca(2+) and guanine nucleotides. Molecular modelling indicates that TG6 could have Ca(2+) and GDP-binding sites related to those of TG3 and TG2, respectively. Localization of mRNA and protein in the mouse identified abundant expression of TG6 in the central nervous system. Analysis of its temporal and spatial pattern of induction in mouse development indicates an association with neurogenesis. Neuronal expression of TG6 was confirmed by double-labelling of mouse forebrain cells with cell type-specific markers. Induction of differentiation in mouse Neuro 2a cells with NGF or dibutyryl cAMP is associated with an upregulation of TG6 expression. Familial ataxia has recently been linked to mutations in the TGM6 gene. Autoantibodies to TG6 were identified in immune-mediated ataxia in patients with gluten sensitivity. These findings suggest a critical role for TG6 in cortical and cerebellar neurons

Significant Association of Estrogen Receptor Binding Site Variation with Bipolar Disorder in Females

Major depression is nearly twice as prevalent in women compared to men. In bipolar disorder, depressive episodes have been reported to be more common amongst female patients. Furthermore, periods of depression often correlate with periods of hormonal fluctuations. A link between hormone signaling and these mood disorders has, therefore, been suggested to exist in many studies. Estrogen, one of the primary female sex hormones, mediates its effect mostly by binding to estrogen receptors (ERs). Nuclear ERs function as transcription factors and regulate gene transcription by binding to specific DNA sequences. A nucleotide change in the binding sequence might alter the binding efficiency, which could affect transcription levels of nearby genes. In order to investigate if variation in ER DNA-binding sequences may be involved in mood disorders, we conducted a genome-wide study of ER DNA-binding in patients diagnosed with major depression or bipolar disorder. Association studies were performed within each gender separately and the results were corrected for multiple testing by the Bonferroni method. In the female bipolar disorder material a significant association result was found for rs6023059 (corrected p-value = 0.023; odds ratio (OR) 0.681, 95% confidence interval (CI) 0.570–0.814), a single nucleotide polymorphism (SNP) placed downstream of the gene coding for transglutaminase 2 (TGM2). Thus, females with a specific genotype at this SNP may be more vulnerable to fluctuating estrogen levels, which may then act as a triggering factor for bipolar disorder

Multifaceted roles of GSK-3 and Wnt/β-catenin in hematopoiesis and leukemogenesis: opportunities for therapeutic intervention

Glycogen synthase kinase-3 (GSK-3) is well documented to participate in a complex array of critical cellular processes. It was initially identified in rat skeletal muscle as a serine/threonine kinase that phosphorylated and inactivated glycogen synthase. This versatile protein is involved in numerous signaling pathways that influence metabolism, embryogenesis, differentiation, migration, cell cycle progression and survival. Recently, GSK-3 has been implicated in leukemia stem cell pathophysiology and may be an appropriate target for its eradication. In this review, we will discuss the roles that GSK-3 plays in hematopoiesis and leukemogenesis as how this pivotal kinase can interact with multiple signaling pathways such as: Wnt/β-catenin, phosphoinositide 3-kinase (PI3K)/phosphatase and tensin homolog (PTEN)/Akt/mammalian target of rapamycin (mTOR), Ras/Raf/MEK/extracellular signal-regulated kinase (ERK), Notch and others. Moreover, we will discuss how targeting GSK-3 and these other pathways can improve leukemia therapy and may overcome therapeutic resistance. In summary, GSK-3 is a crucial regulatory kinase interacting with multiple pathways to control various physiological processes, as well as leukemia stem cells, leukemia progression and therapeutic resistance. GSK-3 and Wnt are clearly intriguing therapeutic targets

Continual learning for robotics: Definition, framework, learning strategies, opportunities and challenges

Continual learning (CL) is a particular machine learning paradigm where the data distribution and learning objective change through time, or where all the training data and objective criteria are never available at once. The evolution of the learning process is modeled by a sequence of learning experiences where the goal is to be able to learn new skills all along the sequence without forgetting what has been previously learned. CL can be seen as an online learning where knowledge fusion needs to take place in order to learn from streams of data presented sequentially in time. Continual learning also aims at the same time at optimizing the memory, the computation power and the speed during the learning process. An important challenge for machine learning is not necessarily finding solutions that work in the real world but rather finding stable algorithms that can learn in real world. Hence, the ideal approach would be tackling the real world in a embodied platform: an autonomous agent. Continual learning would then be effective in an autonomous agent or robot, which would learn autonomously through time about the external world, and incrementally develop a set of complex skills and knowledge.Robotic agents have to learn to adapt and interact with their environment using a continuous stream of observations. Some recent approaches aim at tackling continual learning for robotics, but most recent papers on continual learning only experiment approaches in simulation or with static datasets. Unfortunately, the evaluation of those algorithms does not provide insights on whether their solutions may help continual learning in the context of robotics. This paper aims at reviewing the existing state of the art of continual learning, summarizing existing benchmarks and metrics, and proposing a framework for presenting and evaluating both robotics and non robotics approaches in a way that makes transfer between both fields easier. We put light on continual learning in the context of robotics to create connections between fields and normalize approaches