Age-dependent memory impairment is known to occur in several organisms, including Drosophila, mouse and human. However, the fundamental cellular mechanisms that underlie these impairments are still poorly understood, effectively hampering the development of pharmacological strategies to treat the condition. Polyamines are among the substances found to decrease with age in the human brain. We found that levels of polyamines (spermidine, putrescine) decreased in aging fruit flies, concomitant with declining memory abilities. Simple spermidine feeding not only restored juvenile polyamine levels, but also suppressed age-induced memory impairment. Ornithine decarboxylase-1, the rate-limiting enzyme for de novo polyamine synthesis, also protected olfactory memories in aged flies when expressed specifically in Kenyon cells, which are crucial for olfactory memory formation. Spermidine-fed flies showed enhanced autophagy (a form of cellular self-digestion), and genetic deficits in the autophagic machinery prevented spermidine-mediated rescue of memory impairments. Our findings indicate that autophagy is critical for suppression of memory impairments by spermidine and that polyamines, which are endogenously present, are candidates for pharmacological intervention.

Efficient energy use has constrained the evolution of nervous systems. However, it is unresolved whether energy metabolism may resultantly regulate major brain functions. Our observation that Drosophila flies double their sucrose intake at an early stage of long-term memory formation initiated the investigation of how energy metabolism intervenes in this process. Cellular-resolution imaging of energy metabolism reveals a concurrent elevation of energy consumption in neurons of the mushroom body, the fly's major memory centre. Strikingly, upregulation of mushroom body energy flux is both necessary and sufficient to drive long-term memory formation. This effect is triggered by a specific pair of dopaminergic neurons afferent to the mushroom bodies, via the D5-like DAMB dopamine receptor. Hence, dopamine signalling mediates an energy switch in the mushroom body that controls long-term memory encoding. Our data thus point to an instructional role for energy flux in the execution of demanding higher brain functions.

Understanding how the various memory components are encoded and how they interact to guide behavior requires knowledge of the underlying neural circuits. Currently, aversive olfactory memory in Drosophila is behaviorally subdivided into four discrete phases. Among these, short- and long-term memories rely, respectively, on the γ and α/β Kenyon cells (KCs), two distinct subsets of the ∼2,000 neurons in the mushroom body (MB). Whereas V2 efferent neurons retrieve memory from α/β KCs, the neurons that retrieve short-term memory are unknown. We identified a specific pair of MB efferent neurons, named M6, that retrieve memory from γ KCs. Moreover, our network analysis revealed that six discrete memory phases actually exist, three of which have been conflated in the past. At each time point, two distinct memory components separately recruit either V2 or M6 output pathways. Memory retrieval thus features a dramatic convergence from KCs to MB efferent neurons.

No abstract

SummaryA key function of the brain is to filter essential information and store it in the form of stable, long-term memory (LTM). We demonstrate here that the Dunce (Dnc) phosphodiesterase, an important enzyme that degrades cAMP, acts as a molecular switch that controls LTM formation in Drosophila. We show that, during LTM formation, Dnc is inhibited in the SPN, a pair of newly characterized serotonergic neurons, which stimulates the cAMP/PKA pathway. As a consequence, the SPN activates downstream dopaminergic neurons, opening the gate for LTM formation in the olfactory memory center, the mushroom body. Strikingly, transient inhibition of Dnc in the SPN by RNAi was sufficient to induce LTM formation with a training protocol that normally generates only short-lived memory. Thus, Dnc activity in the SPN acts as a memory checkpoint to guarantee that only the most relevant learned experiences are consolidated into stable memory.

The microstructure of dual-phase steels consisting of a ferrite matrix with embedded martensite inclusions is the main contributor to the mechanical properties such as high ultimate tensile strength, high work hardening rate, and good ductility. Due to the composite structure and the wide field of applications of this steel type, a wide interest exists in corresponding virtual computational experiments. For a reliable modeling, the microstructure should be included. For that reason, in this paper we follow a computational strategy based on the definition of a representative volume element (RVE). These RVEs will be constructed by a set of tomographic measurements and mechanical tests. In order to arrive at more efficient numerical schemes, we also construct statistically similar RVEs, which are characterized by a lower complexity compared with the real microstructure but which represent the overall material behavior accurately. In addition to the morphology of the microstructure, the austenite-martensite transformation during the steel production has a relevant influence on the mechanical properties and is considered in this contribution. This transformation induces a volume expansion of the martensite phase. A further effect is determined in nanoindentation test, where it turns out that the hardness in the ferrite phase increases exponentially when approaching the martensitic inclusion. To capture these gradient properties in the computational model, the volumetric expansion is applied to the martensite phase, and the arising equivalent plastic strain distribution in the ferrite phase serves as basis for a locally graded modification of the ferritic yield curve. Good accordance of the model considering the gradient yield behavior in the ferrite phase is observed in the numerical simulations with experimental data.Keywords Reconstruction of microstructure · Dual-phase steel · RVE · Microheterogeneous materials · EBSD-FIB · SSRVE · Volume expansion of martensite · Multiscale simulations

Can mating influence cognitive functions such as learning and memory in a permanent way? We have addressed this question using a combined behavioral and in vivo imaging approach, finding that aversive long-term memory performance strongly increases in Drosophila females in response to sperm transfer following mating. A peptide in the male sperm, the sex peptide, is known to cause marked changes in female reproductive behavior, as well as other behaviors such as dietary preference. Here, we demonstrate that this sex peptide enhances memory by acting on a single pair of serotonergic brain neurons, in which activation of the sex peptide receptor stimulates the cyclic adenosine monophosphate/protein kinase A pathway. We thus reveal a strong effect of mating on memory via the neuromodulatory action of a sperm peptide on the female brain.

No abstract