Neuropeptide-Gated Perception of Appetitive Olfactory Inputs in Drosophila Larvae

SummaryUnderstanding how smell or taste translates into behavior remains challenging. We have developed a behavioral paradigm in Drosophila larvae to investigate reception and processing of appetitive olfactory inputs in higher-order olfactory centers. We found that the brief presentation of appetitive odors caused fed larvae to display impulsive feeding of sugar-rich food. Deficiencies in the signaling of neuropeptide F (NPF), the fly counterpart of neuropeptide Y (NPY), blocked appetitive odor-induced feeding by disrupting dopamine (DA)-mediated higher-order olfactory processing. We have identified a small number of appetitive odor-responsive dopaminergic neurons (DL2) whose activation mimics the behavioral effect of appetitive odor stimulation. Both NPF and DL2 neurons project to the secondary olfactory processing center; NPF and its receptor NPFR1 mediate a gating mechanism for reception of olfactory inputs in DL2 neurons. Our findings suggest that eating for reward value is an ancient behavior and that fly larvae are useful for studying neurobiology and the evolution of olfactory reward-driven behavior

MiR-206-mediated dynamic mechanism of the mammalian circadian clock

<p>Abstract</p> <p>Background</p> <p>As a group of highly conserved small non-coding RNAs with a length of 21~23 nucleotides, microRNAs (miRNAs) regulate the gene expression post-transcriptionally by base pairing with the partial or full complementary sequences in target mRNAs, thus resulting in the repression of mRNA translation and the acceleration of mRNA degradation. Recent work has revealed that miRNAs are essential for the development and functioning of the skeletal muscles where they are. In particular, miR-206 has not only been identified as the only miRNA expressed in skeletal muscles, but also exhibited crucial roles in regulation of the muscle development. Although miRNAs are known to regulate various biological processes ranging from development to cancer, much less is known about their role in the dynamic regulation of the mammalian circadian clock.</p> <p>Results</p> <p>A detailed dynamic model of miR-206-mediated mammalian circadian clock system was developed presently by using Hill-type terms, Michaelis-Menten type and mass action kinetics. Based on a system-theoretic approach, the model accurately predicts both the periodicity and the entrainment of the circadian clock. It also explores the dynamics properties of the oscillations mediated by miR-206 by means of sensitivity analysis and alterations of parameters. Our results show that miR-206 is an important regulator of the circadian clock in skeletal muscle, and thus by study of miR-206 the main features of its mediation on the clock may be captured. Simulations of these processes display that the amplitude and frequency of the oscillation can be significantly altered through the miR-206-mediated control.</p> <p>Conclusions</p> <p>MiR-206 has a profound effect on the dynamic mechanism of the mammalian circadian clock, both by control of the amplitude and control or alteration of the frequency to affect the level of the gene expression and to interfere with the temporal sequence of the gene production or delivery. This undoubtedly uncovers a new mechanism for regulation of the circadian clock at a post-transcriptional level and provides important insights into the normal development as well as the pathological conditions of skeletal muscles, such as the aging, chronic disease and cancer.</p

Immobilized Talaromyces thermophilus lipase as an efficient catalyst for the production of LML-type structured lipids

LML-type structured lipids are one type of medium- and long-chain triacylglycerols. LML was synthesized using immobilized Talaromyces thermophilus lipase (TTL)-catalyzed interesterification of tricaprylin and ethyl linoleate. The resin AB-8 was chosen, and the lipase/support ratio was determined to be 60 mg/g. Subsequently, the immobilized TTL with strict sn-1,3 regiospecificity was applied to synthesize LML. Under the optimized conditions (60 °C, reaction time 6 h, enzyme loading of 6% of the total weight of substrates, substrate of molar ratio of ethyl linoleate to tricaprylin of 6:1), Triacylglycerols with two long- and one medium-chain FAs (DL-TAG) content as high as 52.86 mol% was obtained. Scale-up reaction further verified the industrial potential of the established process. The final product contained 85.24 mol% DL-TAG of which 97 mol% was LML after purification. The final product obtained with the high LML content would have substantial potential to be used as functional oils

Decelerating Airy pulse propagation in highly non-instantaneous cubic media

The propagation of decelerating Airy pulses in non-instantaneous cubic medium is investigated both theoretically and numerically. In a Debye model, at variance with the case of accelerating Airy and Gaussian pulses, a decelerating Airy pulse evolves into a single soliton for weak and general non- instantaneous response. Airy pulses can hence be used to control soliton generation by temporal shaping. The effect is critically dependent on the response time, and could be used as a way to measure the Debye type response function. For highly non- instantaneous response, we theoretically find a decelerating Airy pulse is still transformed into Airy wave packet with deceleration. The theoretical predictions are confirmed by numerical simulations

International Telecommunication Union-Radiocommunication Sector (ITU-R) P.837-6 and P.837-7 performance to estimate Indonesian rainfall

The cognitive radio technology can improve the efficiency of spectrum utilization byproviding dynamic spectrum access to unoccupied frequency bands. Spectrum sensing is one of the key technologies of cognitive radio networks. The spectrum sensing performance of cognitive radio networks will be greatly reduced in the low SNR environment, especially when using energy detection. Because the stochastic resonance system can improve the energy detection system output SNR .To improve the spectrum sensing performance of cognitive radio networks in the low SNR environment, the stochastic resonance of the single-mode nonlinear optical system is applied to spectrum sensing based on the energy detection method in this paper. The simulation results show that in the low SNR environment, the energy detection based on stochastic resonance of the single-mode nonlinear optical system has better performance than traditional energy detection

Spectrum Sensing Based on Monostable Stochastic Resonance in Cognitive Radio Networks

The cognitive radio technology can provide dynamic spectrum access and improve the efficiency of spectrum utilization. Spectrum sensing is one of the key technologies of cognitive radio networks. The spectrum sensing performance of cognitive radio networks will be greatly reduced in the low SNR environment, especially when using energy detection. Due to the monostable stochastic resonance system can improve the energy detection system output SNR, a monostable stochastic resonanceis applied to spectrum sensing based on the energy detection method of cognitive radio networks in this paper. The simulation results show that in the low SNR environment, when the false alarm probability is constant, the proposed spectrum sensing based on monostable stochastic resonance has better performance than traditional energy detection

Show, Recall, and Tell: Image Captioning with Recall Mechanism

Generating natural and accurate descriptions in image cap-tioning has always been a challenge. In this paper, we pro-pose a novel recall mechanism to imitate the way human con-duct captioning. There are three parts in our recall mecha-nism : recall unit, semantic guide (SG) and recalled-wordslot (RWS). Recall unit is a text-retrieval module designedto retrieve recalled words for images. SG and RWS are de-signed for the best use of recalled words. SG branch cangenerate a recalled context, which can guide the process ofgenerating caption. RWS branch is responsible for copyingrecalled words to the caption. Inspired by pointing mecha-nism in text summarization, we adopt a soft switch to balancethe generated-word probabilities between SG and RWS. Inthe CIDEr optimization step, we also introduce an individualrecalled-word reward (WR) to boost training. Our proposedmethods (SG+RWS+WR) achieve BLEU-4 / CIDEr / SPICEscores of 36.6 / 116.9 / 21.3 with cross-entropy loss and 38.7 /129.1 / 22.4 with CIDEr optimization on MSCOCO Karpathytest split, which surpass the results of other state-of-the-artmethods.Comment: Published in AAAI 202