Drosophila TMEM63 and mouse TMEM63A are lysosomal mechanosensory ion channels.

Cells sense physical forces and convert them into electrical or chemical signals, a process known as mechanotransduction. Whereas extensive studies focus on mechanotransduction at the plasma membrane, little is known about whether and how intracellular organelles sense mechanical force and the physiological functions of organellar mechanosensing. Here we identify the Drosophila TMEM63 (DmTMEM63) ion channel as an intrinsic mechanosensor of the lysosome, a major degradative organelle. Endogenous DmTMEM63 proteins localize to lysosomes, mediate lysosomal mechanosensitivity and modulate lysosomal morphology and function. Tmem63 mutant flies exhibit impaired lysosomal degradation, synaptic loss, progressive motor deficits and early death, with some of these mutant phenotypes recapitulating symptoms of TMEM63-associated human diseases. Importantly, mouse TMEM63A mediates lysosomal mechanosensitivity in Neuro-2a cells, indicative of functional conservation in mammals. Our findings reveal DmTMEM63 channel function in lysosomes and its physiological roles in vivo and provide a molecular basis to explore the mechanosensitive process in subcellular organelles.

Single-cell transcriptomics reveals the brain evolution of web-building spiders.

Spiders are renowned for their efficient capture of flying insects using intricate aerial webs. How the spider nervous systems evolved to cope with this specialized hunting strategy and various environmental clues in an aerial space remains unknown. Here we report a brain-cell atlas of >30,000 single-cell transcriptomes from a web-building spider (Hylyphantes graminicola). Our analysis revealed the preservation of ancestral neuron types in spiders, including the potential coexistence of noradrenergic and octopaminergic neurons, and many peptidergic neuronal types that are lost in insects. By comparing the genome of two newly sequenced plesiomorphic burrowing spiders with three aerial web-building spiders, we found that the positively selected genes in the ancestral branch of web-building spiders were preferentially expressed (42%) in the brain, especially in the three mushroom body-like neuronal types. By gene enrichment analysis and RNAi experiments, these genes were suggested to be involved in the learning and memory pathway and may influence the spiders' web-building and hunting behaviour. Our results provide key sources for understanding the evolution of behaviour in spiders and reveal how molecular evolution drives neuron innovation and the diversification of associated complex behaviours.

Small Target Recognition and Tracking Based on UAV Platform.

Target recognition and tracking based on multi-rotor UAVs have the advantages of low cost and high flexibility. It can monitor low-altitude targets with high intensity. It has great application prospects in national defense, military, and civil fields. The existing algorithms for aerial small target recognition and tracking have the disadvantages of slow speed, low accuracy, poor robustness, and insufficient intelligence. Aiming at the problems of existing algorithms, this paper first makes a lightweight improvement for the YOLOv4 network recognition algorithm suitable for small target recognition and tests it on the VisDrone dataset. The accuracy of the improved algorithm is increased by 1.5% and the speed is increased by 3.3 times. Then, by analyzing the response value, the KCF tracking situation is judged, and the template update of the adaptive learning rate is realized. When the tracking fails, the target is re-searched and tracked based on the recognition results and the similarity judgment. Finally, experiments are carried out on the multi-rotor UAV, and the adaptive zoom tracking strategy is designed to track pedestrians, cars, and UAVs. The results show that the proposed algorithm can achieve stable tracking of long-distance small targets.

Selfee, self-supervised features extraction of animal behaviors.

Fast and accurately characterizing animal behaviors is crucial for neuroscience research. Deep learning models are efficiently used in laboratories for behavior analysis. However, it has not been achieved to use an end-to-end unsupervised neural network to extract comprehensive and discriminative features directly from social behavior video frames for annotation and analysis purposes. Here, we report a self-supervised feature extraction (Selfee) convolutional neural network with multiple downstream applications to process video frames of animal behavior in an end-to-end way. Visualization and classification of the extracted features (Meta-representations) validate that Selfee processes animal behaviors in a way similar to human perception. We demonstrate that Meta-representations can be efficiently used to detect anomalous behaviors that are indiscernible to human observation and hint in-depth analysis. Furthermore, time-series analyses of Meta-representations reveal the temporal dynamics of animal behaviors. In conclusion, we present a self-supervised learning approach to extract comprehensive and discriminative features directly from raw video recordings of animal behaviors and demonstrate its potential usage for various downstream applications.

Visceral Mechano-sensing Neurons Control Drosophila Feeding by Using Piezo as a Sensor.

Animal feeding is controlled by external sensory cues and internal metabolic states. Does it also depend on enteric neurons that sense mechanical cues to signal fullness of the digestive tract? Here, we identify a group of piezo-expressing neurons innervating the Drosophila crop (the fly equivalent of the stomach) that monitor crop volume to avoid food overconsumption. These neurons reside in the pars intercerebralis (PI), a neuro-secretory center in the brain involved in homeostatic control, and express insulin-like peptides with well-established roles in regulating food intake and metabolism. Piezo knockdown in these neurons of wild-type flies phenocopies the food overconsumption phenotype of piezo-null mutant flies. Conversely, expression of either fly Piezo or mammalian Piezo1 in these neurons of piezo-null mutants suppresses the overconsumption phenotype. Importantly, Piezo+ neurons at the PI are activated directly by crop distension, thus conveying a rapid satiety signal along the "brain-gut axis" to control feeding.

Truly Concomitant and Independently Expressed Short- and Long-Term Plasticity in a Bi2 O2 Se-Based Three-Terminal Memristor.

Concomitance of diverse synaptic plasticity across different timescales produces complex cognitive processes. To achieve comparable cognitive complexity in memristive neuromorphic systems, devices that are capable of emulating short-term (STP) and long-term plasticity (LTP) concomitantly are essential. In existing memristors, however, STP and LTP can only be induced selectively because of the inability to be decoupled using different loci and mechanisms. In this work, the first demonstration of truly concomitant STP and LTP is reported in a three-terminal memristor that uses independent physical phenomena to represent each form of plasticity. The emerging layered material Bi2 O2 Se is used for memristors for the first time, opening up the prospects for ultrathin, high-speed, and low-power neuromorphic devices. The concerted action of STP and LTP allows full-range modulation of the transient synaptic efficacy, from depression to facilitation, by stimulus frequency or intensity, providing a versatile device platform for neuromorphic function implementation. A heuristic recurrent neural circuitry model is developed to simulate the intricate "sleep-wake cycle autoregulation" process, in which the concomitance of STP and LTP is posited as a key factor in enabling this neural homeostasis. This work sheds new light on the development of generic memristor platforms for highly dynamic neuromorphic computing.

Proteome analysis and serological characterization of surface-exposed proteins of Rickettsia heilongjiangensis.

BACKGROUND: Rickettsia heilongjiangensis, the agent of Far-Eastern spotted fever (FESF), is an obligate intracellular bacterium. The surface-exposed proteins (SEPs) of rickettsiae are involved in rickettsial adherence to and invasion of host cells, intracellular bacterial growth, and/or interaction with immune cells. They are also potential molecular candidates for the development of diagnostic reagents and vaccines against rickettsiosis. METHODS: R. heilongjiangensis SEPs were identified by biotin-streptavidin affinity purification and 2D electrophoreses coupled with ESI-MS/MS. Recombinant SEPs were probed with various sera to analyze their serological characteristics using a protein microarray and an enzyme-linked immune sorbent assay (ELISA). RESULTS: Twenty-five SEPs were identified, most of which were predicted to reside on the surface of R. heilongjiangensis cells. Bioinformatics analysis suggests that these proteins could be involved in bacterial pathogenesis. Eleven of the 25 SEPs were recognized as major seroreactive antigens by sera from R. heilongjiangensis-infected mice and FESF patients. Among the major seroreactive SEPs, microarray assays and/or ELISAs revealed that GroEL, OmpA-2, OmpB-3, PrsA, RplY, RpsB, SurA and YbgF had modest sensitivity and specificity for recognizing R. heilongjiangensis infection and/or spotted fever. CONCLUSIONS: Many of the SEPs identified herein have potentially important roles in R. heilongjiangensis pathogenicity. Some of them have potential as serodiagnostic antigens or as subunit vaccine antigens against the disease.