Measurement of ice thickness and quality to optimise and qualify robotic cryo-plunger

** Linkam的自动低温电子显微镜（cryo-EM）样品制备系统解决了低温电子显微镜工作流程中的不一致性和瓶颈问题**低温电子显微镜的发展为生物学研究和药物发现的研究人员提供了高分辨率的蛋白质和细胞成分结构信息。2017年，冷冻电镜技术获得了诺贝尔奖（[https://www.nobelprize.org/prizes/chemistry/2017/press-release/][0]）.Conventional]冷冻电镜技术依靠在玻璃化冰中快速冷冻样品（蛋白质颗粒或细胞成分），以保存分子水平的结构。这可以通过暴跌冻结来实现，然而，用于暴跌冻结的典型机器和过程大多是手动的，并使用传统的吸墨纸。这种依赖于用户的过程总是导致一致性差，并且被认为是整个低温电镜工作流程的瓶颈。新颖设计的Linkam CryoGenium机器人样品制备系统优化了cryo-EM的样品冷冻过程，采用Linkam专利设计，可自动调节样品膜厚度。CryoGenium提供了一个控制低温条件的单一平台，并消除了样品制备过程中任何不希望的用户依赖效应。当前的A4i项目打算使用一组确定的样品对玻璃化样品（冰）质量进行结构化调查。冰的厚度由能量过滤器测量和内置的低温电子显微镜成像系统确定。这组定量测量将更好地了解仪器设置与样品结果质量之间的关系。与传统的样品冷冻方法相比，基于统计参数的进一步系统优化将进一步提高重复性和样品均匀性。该项目的第二个目标是利用这次扩展试验的反馈来增强仪器和软件的用户友好性。总的来说，这种新设备可以帮助进一步建立冷冻电镜作为研究细胞和分子结构的常规工具，对理解疾病机制和药物设计具有重要意义。[0]: https://www.nobelprize.org/prizes/chemistry/2017/press-release/

**Automatic cryogenic electron microscopy (cryo-EM) sample preparation system from Linkam to tackle inconsistency and bottlenecks in cryo-EM workflow**The development of cryo-EM has made high resolution structural information of proteins and cellular components available to researchers in biological studies and drug discovery. A Nobel prize for cryo-EM was awarded in 2017 ([https://www.nobelprize.org/prizes/chemistry/2017/press-release/][0]).Conventional cryo-EM relies on the rapid freezing of samples (protein particles or cellular components) in vitrified ice to preserve structures down to molecular level. This can be achieved by plunge-freezing, however, the typical machines and processes used for the plunge freezing are mostly manual and use conventional blotting paper. This substantial user-dependent process always lead to poor consistency, and is considered as a bottleneck of the overall cryo-EM workflow.The novel design of the Linkam CryoGenium robotic sample preparation system has optimised the sample freezing process of cryo-EM using a Linkam - patented design for the adjustment of the sample film thickness automatically. CryoGenium provides a single platform for controlled cryogenic conditions and eliminates any undesirable user-dependent effects during the sample preparation process.This current A4i project intends to perform a structured investigation of vitrified sample (ice) quality using a defined set of samples. The ice thickness is determined by energy filter measurements and a built-in cryo-EM imaging system. The set of quantitative measurements will give better insights into the relationship between instrument settings and the quality of sample results. Further system optimisation based on statistical parameters will be achieved to further improve repeatability and sample uniformity compared to conventional sample freezing methods. A secondary goal of the project is to enhance the user-friendliness of the instrument and software with feedback from this extended trial.Overall this new device can help to further establish cryo-EM as a routine tool to study cellular and molecular structures with implications for the understanding disease mechanisms and the design of drugs.[0]: https://www.nobelprize.org/prizes/chemistry/2017/press-release/