Market research study proposal for an assessment of market opportunities for application of 3D pattern analysis to single-molecule localization microscopy (SMLM)

超分辨率显微镜打破了光学衍射障碍，使生物学家能够在接近电子显微镜的分辨率下观察分子结构。使用单分子定位显微镜（SMLM）获得最佳分辨率（XY:<20nm; Z: <50nm），基于离散荧光团的重复激活（闪烁），其精确定位是使用点扩散函数（PSF）的高斯拟合确定的。通过将三维单分子定位数据集建模为一个点云，我们建立了分析方法来定义完整细胞中大分子复合物的结构。对~100 nm小泡的关键结构成分caveolin-1进行了无监督聚类分析和多阈值模块化分析，确定了小泡外壳结构的模块化性质，并表明较小的非小泡Cav1支架相互作用形成较大的支架和小泡。我们已经开始与Quorum技术公司讨论，以改进我们的软件，提供全面的文档和清晰的用户界面，以开发用于任何SMLM显微镜系统的独立软件包。该申请将通过AdventusResearch + Consulting Inc （Guelph, Ontario）进行市场评估，以评估该技术的商业可行性，包括验证该技术的潜在市场规模，验证最终用户的需求和购买意愿/能力。计算成像、网络建模和基于机器学习的3D模式分析工具在SMLM中的应用代表了一种高度创新和强大的方法来定义亚细胞结构中的分子结构和分子相互作用，这将导致HQP在这个新兴领域的多学科培训。

Super-resolution microscopy has broken the optical diffraction barrier, enabling biologists to visualizemolecular structures at resolutions approaching that of an electron microscope. The best resolution (XY:<20nm; Z: <50nm) is obtained using single molecule localization microscope (SMLM), based on the repeatedactivation (blinking) of discrete fluorophores whose precise localization is determined using a Gaussian fit ofthe point-spread function (PSF). By modeling 3D single-molecule localization data sets as a point cloud, awell-established representation used in 3D visual computing, we established analytical approaches to define thestructure of macromolecular complexes in intact cells. Unsupervised clustering analysis and multi-thresholdmodularity analysis of caveolin-1, a key structural component of ~100 nm caveolae, has defined the modularnature of the caveolae coat structure and shows that smaller non-caveolar Cav1 scaffolds interact to form largerscaffolds and caveolae. We have initiated discussion with Quorum Technologies Inc to refine our software,providing comprehensive documentation and a clear user interface, to develop a stand-alone package for usewith any SMLM microscope system. This application is to support a market assessment through AdventusResearch + Consulting Inc (Guelph, Ontario) to assess the commercial viability of this technology includingvalidation of the potential market size for the technology, validation of the end-user need andwillingness/ability to purchase. Application of computational imaging, network modelling, and machinelearning based 3D pattern analysis tools to SMLM represents a highly innovative and powerful approach todefine molecular structure and molecular interactions in subcellular structures that will lead to themultidisciplinary training of HQP in this burgeoning field.