■原子力显微镜(AFM)是用于表征纳米级软生物样品和生物材料的机械性能的主要技术之一。尽管AFM社区努力推广开源数据分析工具,在需要通用分析程序的领域中,标准化仍然是一个重要的问题。基于AFM的机械测量涉及向样品施加受控的力并测量所谓的力-距离曲线中产生的变形。这些可以包括简单的方法和在各种频率下的缩回或振荡循环(微流变)。为了提取定量参数,如弹性模量,从这些测量中,使用数据分析软件处理AFM测量。尽管存在开放式工具并允许获得样品的机械性能,其中大多数只包括标准的弹性模型,不允许处理微流变数据。在这项工作中,我们开发了一个开源软件包(称为PyFMLab,从python力显微镜实验室开始),能够从常规的力-距离曲线和微流变测量中确定样品的粘弹性。
■PyFMLab是用Python编写的,它提供了可访问的语法和足够的计算效率。将软件功能划分为单独的,独立库,以增强代码组织和模块化,并提高可读性,可维护性,可测试性,和可重用性。要验证PyFMLab,两个AFM数据集,一个由简单的力曲线组成,另一个包括振荡测量,收集在HeLa细胞上。
使用PyFMLab分析的两个数据集上获得的粘弹性参数针对数据处理专有软件和在获得等效结果之前开发的验证MATLAB例程进行了验证。
■其开源性质和多功能性使PyFMLab成为开源解决方案,为从力-距离曲线和微流变测量中对生物样品进行标准化粘弹性表征铺平了道路。
就像我们可以通过触摸来测试水果的成熟度一样,我们可以用我们的手轻轻触摸物体,并确定它是软还是硬。医生使用这种技术,叫做触诊,探索我们的器官并检查疾病的迹象。我们可以考虑做类似的事情,但在一个更小的尺度——纳米尺度——这么小,你甚至不能用肉眼看到它。原子力显微镜(AFM)允许在纳米级应用触诊。AFM是一种强大的工具,可以让科学家检查难以置信的小物体,像单个细胞或分子。AFM使用超敏感的“手指”来触摸和探索太小而无法在常规显微镜下看到的东西。在欧洲项目Phys2BioMed期间,我们探讨了如何应用AFM诊断疾病使用纳米化。例如,触摸患者活检样本,并确定他们有多柔软或僵硬。这里的陷阱:没有一个单一的,标准化的方法或软件,可以有效地处理从AFM获得的所有数据。这有点像有很多不同的语言,但没有通用的翻译。就像秤或量杯是标准化的,科学家需要准确和一致地分析AFM数据。这对于确保不同研究人员在不同仪器上获得的结果之间的可靠比较至关重要,当结果用于诊断或预测目的时,这一点特别重要。为了帮助解决这个问题,我们开发了PyFMLab.该软件是一个可靠且易于使用的工具,可将AFM数据转换为有关正在研究的微小结构的见解。通过提供标准化的,开源,模块化和可访问的方式来分析AFM数据,PyFMLab使生物物理学领域的普及,为AFM的临床应用铺平了道路。
UNASSIGNED: Atomic force microscopy (AFM) is one of the main techniques used to characterize the mechanical properties of soft biological samples and biomaterials at the nanoscale. Despite efforts made by the AFM community to promote open-source data analysis tools, standardization continues to be a significant concern in a field that requires common analysis procedures. AFM-based mechanical measurements involve applying a controlled force to the sample and measure the resulting deformation in the so-called force-distance curves. These may include simple approach and retract or oscillatory cycles at various frequencies (microrheology). To extract quantitative parameters, such as the elastic modulus, from these measurements, AFM measurements are processed using data analysis software. Although open tools exist and allow obtaining the mechanical properties of the sample, most of them only include standard elastic models and do not allow the processing of microrheology data. In this work, we have developed an open-source software package (called PyFMLab, as of python force microscopy laboratory) capable of determining the viscoelastic properties of samples from both conventional force-distance curves and microrheology measurements.
UNASSIGNED: PyFMLab has been written in Python, which provides an accessible syntax and sufficient computational efficiency. The software features were divided into separate, self-contained libraries to enhance code organization and modularity and to improve readability, maintainability, testability, and reusability. To validate PyFMLab, two AFM datasets, one composed of simple force curves and another including oscillatory measurements, were collected on HeLa cells.
UNASSIGNED: The viscoelastic parameters obtained on the two datasets analysed using PyFMLab were validated against data processing proprietary software and against validated MATLAB routines developed before obtaining equivalent results.
UNASSIGNED: Its open-source nature and versatility makes PyFMLab an open-source solution that paves the way for standardized viscoelastic characterization of biological samples from both force-distance curves and microrheology measurements.
Just like we can test the ripeness of fruit by touching it, we can use our hands to gently touch an object and determine if it is soft or stiff. Doctors use this technique, called palpation, to explore our organs and check for signs of disease. We can think about doing something similar, but on a much smaller scale — the nanoscale — so small that you cannot even see it with your naked eye. Atomic force microscopy (AFM) allows to apply palpation at the nanoscale. AFM is a powerful tool that allows scientists to examine incredibly small objects, like individual cells or molecules. AFM uses super sensitive “fingers” to touch and explore things that are too small to be seen under a regular microscope. During the European project Phys2BioMed, we explored how to apply AFM to diagnose diseases using nanopalpation. For example, touching samples from biopsies of patients and determining how soft or stiff they are. Here\'s the catch: there is not a single, standardized method or software that can efficiently process all the data obtained from AFM. It\'s a bit like having a lot of different languages but no universal translator. Just like a scale or a measuring cup are standardized, scientists need to analyze AFM data accurately and consistently. This is crucial to ensure reliable comparisons between results obtained by different researchers on different instruments, something particularly important when the results are to be used for diagnostic or predictive purposes. To help tackle this problem, we have developed PyFMLab. This software is a reliable and easy-to-use tool that translates AFM data into insights about the tiny structures being studied. By providing a standardized, open-source, modular and accessible way to analyze AFM data, PyFMLab democratizes access to this field of Biophysics, paving the way for clinical applications of AFM.