Hypoxia shifts activity of neuropeptide Y in Ewing sarcoma from growth-inhibitory to growth-promoting effects

Ewing sarcoma (ES) is an aggressive malignancy driven by an oncogenic fusion protein, EWS-FLI1. Neuropeptide Y (NPY), and two of its receptors, Y1R and Y5R are up-regulated by EWS-FLI1 and abundantly expressed in ES cells. Paradoxically, NPY acting via Y1R and Y5R stimulates ES cell death. Here, we demonstrate that these growth-inhibitory actions of NPY are counteracted by hypoxia, which converts the peptide to a growth-promoting factor. In ES cells, hypoxia induces another NPY receptor, Y2R, and increases expression of dipeptidyl peptidase IV (DPPIV), an enzyme that cleaves NPY to a shorter form, NPY3-36. This truncated peptide no longer binds to Y1R and, therefore, does not stimulate ES cell death. Instead, NPY3-36 acts as a selective Y2R/Y5R agonist. The hypoxia-induced increase in DPPIV activity is most evident in a population of ES cells with high aldehyde dehydrogenase (ALDH) activity, rich in cancer stem cells (CSCs). Consequently, NPY, acting via Y2R/Y5Rs, preferentially stimulates proliferation and migration of hypoxic ALDHhigh cells. Hypoxia also enhances the angiogenic potential of ES by inducing Y2Rs in endothelial cells and increasing the release of its ligand, NPY3-36, from ES cells. In summary, hypoxia acts as a molecular switch shifting NPY activity away from Y1R/Y5R-mediated cell death and activating the Y2R/Y5R/DPPIV/NPY3-36 axis, which stimulates ES CSCs and promotes angiogenesis. Hypoxia-driven actions of the peptide such as these may contribute to ES progression. Due to the receptor-specific and multifaceted nature of NPY actions, these findings may inform novel therapeutic approaches to ES.National Institutes of Health (U.S.) (Grant UL1TR000101

Enabling Energy-Efficient Inference for Self-Attention Mechanisms in Neural Networks

The study of specialized accelerators tailored for neural networks is becoming a promising topic in recent years. Such existing neural network accelerators are usually designed for convolutional neural networks (CNNs) or recurrent neural networks have been (RNNs), however, less attention has been paid to the attention mechanisms, which is an emerging neural network primitive with the ability to identify the relations within input entities. The self-attention-oriented models such as Transformer have achieved great performance on natural language processing, computer vision and machine translation. However, the self-attention mechanism has intrinsically expensive computational workloads, which increase quadratically with the number of input entities. Therefore, in this work, we propose an software-hardware co-design solution for energy-efficient self-attention inference. A prediction-based approximate self-attention mechanism is introduced to substantially reduce the runtime as well as power consumption, and then a specialized hardware architecture is designed to further increase the speedup. The design is implemented on a Xilinx XC7Z035 FPGA, and the results show that the energy efficiency is improved by 5.7x with less than 1% accuracy loss

Giant Enhancement of Magnonic Frequency Combs by Exceptional Points

With their incomparable time-frequency accuracy, frequency combs have significantly advanced precision spectroscopy, ultra-sensitive detection, and atomic clocks. Traditional methods to create photonic, phononic, and magnonic frequency combs hinge on material nonlinearities which are often weak, necessitating high power densities to surpass their initiation thresholds, which subsequently limits their applications. Here, we introduce a novel nonlinear process to efficiently generate magnonic frequency combs (MFCs) by exploiting exceptional points (EPs) in a coupled system comprising a pump-induced magnon mode and a Kittel mode. Even without any cavity, our method greatly improves the efficiency of nonlinear frequency conversion and achieves optimal MFCs at low pump power. Additionally, our novel nonlinear process enables excellent tunability of EPs using the polarization and power of the pump, simplifying MFC generation and manipulation. Our work establishes a synergistic relationship between non-Hermitian physics and MFCs, which is advantages for coherent/quantum information processing and ultra-sensitive detection.Comment: 7 pages, 4 figure

Striatopallidal dysfunction underlies repetitive behavior in Shank3-deficient model of autism

The postsynaptic scaffolding protein SH3 and multiple ankyrin repeat domains 3 (SHANK3) is critical for the development and function of glutamatergic synapses. Disruption of the SHANK3-encoding gene has been strongly implicated as a monogenic cause of autism, and Shank3 mutant mice show repetitive grooming and social interaction deficits. Although basal ganglia dysfunction has been proposed to underlie repetitive behaviors, few studies have provided direct evidence to support this notion and the exact cellular mechanisms remain largely unknown. Here, we utilized the Shank3B mutant mouse model of autism to investigate how Shank3 mutation may differentially affect striatonigral (direct pathway) and striatopallidal (indirect pathway) medium spiny neurons (MSNs) and its relevance to repetitive grooming behavior in Shank3B mutant mice. We found that Shank3 deletion preferentially affects synapses onto striatopallidal MSNs. Striatopallidal MSNs showed profound defects, including alterations in synaptic transmission, synaptic plasticity, and spine density. Importantly, the repetitive grooming behavior was rescued by selectively enhancing the striatopallidal MSN activity via a Gq-coupled human M3 muscarinic receptor (hM3Dq), a type of designer receptors exclusively activated by designer drugs (DREADD). Our findings directly demonstrate the existence of distinct changes between 2 striatal pathways in a mouse model of autism and indicate that the indirect striatal pathway disruption might play a causative role in repetitive behavior of Shank3B mutant mice.National Institute of Mental Health (U.S.) (Grant 5R01MH097104

Mice with Shank3 Mutations Associated with ASD and Schizophrenia Display Both Shared and Distinct Defects

Genetic studies have revealed significant overlaps of risk genes among psychiatric disorders. However, it is not clear how different mutations of the same gene contribute to different disorders. We characterized two lines of mutant mice with Shank3 mutations linked to ASD and schizophrenia. We found both shared and distinct synaptic and behavioral phenotypes. Mice with the ASD-linked InsG3680 mutatio n manifest striatal synaptic transmission defects before weaning age and impaired juvenile social interaction, coinciding with the early onset of ASD symptoms. On the other hand, adult mice carrying the schizophrenia-linked R1117X mutation show profound synaptic defects in prefrontal cortex and social dominance behavior. Furthermore, we found differential Shank3 mRNA stability and SHANK1/2 upregulation in these two lines. These data demonstrate that different alleles of the same gene may have distinct phenotypes at molecular, synaptic, and circuit levels in mice, which may inform exploration of these relationships in human patients.National Institute of Mental Health (U.S.) (Grant 5R01MH097104)National Institute of Mental Health (U.S.) (Grant 5DP1-MH100706)National Institutes of Health (U.S.) (Grant R01-NS 07312401

Determination Factors for the Spatial Distribution of Forest Cover: A Case Study of China’s Fujian Province

Understanding the determination factors of the spatial distribution of forest cover is crucial for global forest governance. This study contributed a nuanced case, focusing on the determination factors for the spatial distribution of forest cover in Fujian Province, China, in 2020. In order to achieve this, a high-resolution GIS-based data set was used, and spatial auto-correlation and geographic detector approaches were adopted. Three findings are presented in the results. First, the spatial distribution of forest cover is affected by natural conditions. In regions with more precipitation, higher altitude, or cooler temperatures, forest cover is higher. The relationship between the spatial distribution of forest cover and slope is an inverted-U shape. Second, socioeconomic factors have a greater explanatory capacity. In particular, regions with dense populations or roads have less forest cover. Third, there is an inverted-U-shaped relationship between the spatial distribution of forest cover and GDP per capita. With the growth of GDP per capita, forest cover is first positive, but subsequently negative. The results indicate that natural factors could shape the spatial distribution of forest cover, while socioeconomic factors could play a more significant role in the spatial distribution of forest cover

Determination Factors for the Spatial Distribution of Forest Cover : A Case Study of China’s Fujian Province

Understanding the determination factors of the spatial distribution of forest cover is crucial for global forest governance. This study contributed a nuanced case, focusing on the determination factors for the spatial distribution of forest cover in Fujian Province, China, in 2020. In order to achieve this, a high-resolution GIS-based data set was used, and spatial auto-correlation and geographic detector approaches were adopted. Three findings are presented in the results. First, the spatial distribution of forest cover is affected by natural conditions. In regions with more precipitation, higher altitude, or cooler temperatures, forest cover is higher. The relationship between the spatial distribution of forest cover and slope is an inverted-U shape. Second, socioeconomic factors have a greater explanatory capacity. In particular, regions with dense populations or roads have less forest cover. Third, there is an inverted-U-shaped relationship between the spatial distribution of forest cover and GDP per capita. With the growth of GDP per capita, forest cover is first positive, but subsequently negative. The results indicate that natural factors could shape the spatial distribution of forest cover, while socioeconomic factors could play a more significant role in the spatial distribution of forest cover

Effects of Ambient Temperature on Nanosecond Laser Micro-Drilling of Polydimethylsiloxane (PDMS)

In this research, effects of ambient temperature (−100 °C–200 °C) on nanosecond laser micro-drilling of polydimethylsiloxane (PDMS) was investigated by simulation and experiment. A thermo-mechanical coupled model was established, and it was indicated that the top and bottom diameter of the micro-hole decreased with the decrease of the ambient temperature, and the micro-hole taper increased with the decrease of the ambient temperature. The simulation results showed a good agreement with the experiment results in micro-hole geometry; the maximum prediction errors of the top micro-hole diameter, the bottom micro-hole diameter and micro-hole taper were 2.785%, 6.306% and 9.688%, respectively. The diameter of the heat-affected zone decreased with the decrease of the ambient temperature. The circumferential wrinkles were controlled by radial compressive stress. As the ambient temperature increased from 25 °C to 200 °C, the radial compressive stress gradually decreased, which led to the circumferential wrinkles gradually evolving in the radial direction. This work provides a new idea and method based on ambient temperature control for nanosecond laser processing of PDMS, which provides exciting possibilities for a wider range of engineering applications of PDMS