编辑丨王多鱼 排版丨水成文 在这项最新研究中，研究团队发现，与天然 突触后致密区 （ postsynaptic density，PSD） 类似，重构的 PSD 凝聚体形成了一种软玻璃材料，且没有不可逆淀 粉样结构的形成迹象。这种玻璃样 PSD 凝聚体的形成依赖于支架蛋白间特异性、多价相互作用介导的 PSD 蛋白网络渗流。破坏 Shank3 的 SAM 结构域介导的 寡聚化 （一种在Phelan-McDermid综合征患者中观察到的 SHANK3 基因突变，患者 临床为智力障碍、语言发育迟缓、自闭症和肌张力低下 ） ，会通过削弱网 络渗流，使 PSD 凝聚体变软 （由软玻璃样向近液态转变） ，进而损害突触传递和可塑性，并导致小鼠出现自闭症样行为。 该研究的核心发现： Shank3 的寡聚化使 PSD 凝聚物具有软玻璃样材料特性 蛋白质网络特性决定 PSD 凝聚物的物质特性； Shank3 寡聚化缺失使突触后致密区变软并损害突触可塑性； 物质特性对于生物凝聚体的功能至关重要。 细胞含有通过 相分离 形成的多种类型的 无膜细胞器 和 生物凝聚体 。这些细胞生物凝聚体具有广泛的物质特性，从牛顿流体到弹性固体。关于生物 ...

Core Insights - The research reveals a convergent mechanism of echolocation in different mammalian species, providing new perspectives on the evolutionary origins of this complex behavior [1][2] - The study highlights the significance of non-coding regulatory regions in the convergent evolution of behaviors, challenging the traditional focus on protein-coding genes [2] Group 1: Research Findings - The study identifies 222 shared open chromatin regions in the hippocampal area of echolocating species, significantly higher than random expectations, indicating a complex gene regulatory network [1] - Traditional auditory-related genes are found to be abnormally active in the hippocampal regulatory networks of echolocating mammals, suggesting their role in spatial localization functions [2] Group 2: Methodology and Implications - The research employs innovative techniques such as chromatin accessibility sequencing, transcriptome sequencing, and transmission electron microscopy to compare the hippocampal gene regulatory features of various species [1] - The establishment of the Daluoshan pig-tailed mouse as a new model organism offers a valuable platform for further exploration of the neural mechanisms underlying echolocation [2]

Core Viewpoint - Researchers from the National University of Singapore (NUS) have demonstrated that a single standard silicon transistor can mimic the behavior of biological neurons and synapses, bringing hardware-based artificial neural networks (ANN) closer to reality [1][3]. Group 1: Research Findings - The NUS research team, led by Professor Mario Lanza, provides a scalable and energy-efficient solution for hardware-based ANN, making neuromorphic computing more feasible [1][3]. - The study published in Nature on March 26, 2025, shows that a single silicon transistor can replicate neural firing and synaptic weight changes, which are fundamental mechanisms of biological neurons and synapses [3][4]. Group 2: Technical Innovations - The research achieved this by adjusting the resistance of the transistor to specific values, controlling two physical phenomena: impact ionization and charge trapping [4]. - The team developed a dual-transistor unit called "neuro-synaptic random access memory" (NS-RAM), which operates in neuron or synapse states [4]. Group 3: Advantages of the New Approach - The method utilizes commercial CMOS technology, ensuring scalability, reliability, and compatibility with existing semiconductor manufacturing processes [4]. - Experimental results show that NS-RAM units exhibit low power consumption, stable performance over multiple operational cycles, and consistent behavior across different devices, essential for building reliable ANN hardware [4].