The protein cloud-point temperature (T_Cloud) is a known representative of protein–protein interaction strength and provides valuable information during the development and characterization of protein-based products, such as biopharmaceutics. A high-throughput low volume T_Cloud detection method was introduced in preceding work, where it was concluded that the extracted value is an apparent T_Cloud (T_Cloud,app). As an understanding of the apparent nature is imperative to facilitate inter-study data comparability, the current work was performed to systematically evaluate the influence of 3 image analysis strategies and 2 experimental parameters (sample volume and cooling rate) on T_Cloud,app detection of lysozyme. Different image analysis strategies showed that T_Cloud,app is detectable by means of total pixel intensity difference and the total number of white pixels, but the latter is also able to extract the ice nucleation temperature. Experimental parameter variation showed a T_Cloud,app depression for increasing cooling rates (0.1–0.5 °C/min), and larger sample volumes (5–24 μL). Exploratory thermographic data indicated this resulted from a temperature discrepancy between the measured temperature by the cryogenic device and the actual sample temperature. Literature validation confirmed that the discrepancy does not affect the relative inter-study comparability of the samples, regardless of the image analysis strategy or experimental parameters. Additionally, high measurement precision was demonstrated, as T_Cloud,app changes were detectable down to a sample volume of only 5 μL and for 0.1 °C/min cooling rate increments. This work explains the apparent nature of the T_Cloud detection method, showcases its detection precision, and broadens the applicability of the experimental setup.

蛋白质浊点温度 ( T _Cloud ) 是蛋白质-蛋白质相互作用强度的已知代表，在生物制药等蛋白质产品的开发和表征过程中提供有价值的信息。前面的工作中介绍了一种高通量低容量T_云检测方法，得出的结论是提取的值是表观T_云（ T _Cloud，app ）。由于了解表观性质对于促进研究间数据可比性至关重要，因此当前的工作是系统评估 3 种图像分析策略和 2 个实验参数（样品体积和冷却速率）对T _{Cloud 的影响，应用程序}检测溶菌酶。不同的图像分析策略表明， T _Cloud,app可以通过总像素强度差和白色像素总数来检测，但后者也能够提取冰核温度。实验参数变化显示，随着冷却速率 (0.1–0.5 °C/min) 的增加和样品体积 (5–24 μL) 的增加， T _Cloud,app会降低。探索性热成像数据表明这是由于低温装置测量的温度与实际样品温度之间的温度差异造成的。文献验证证实，无论图像分析策略或实验参数如何，这种差异不会影响样本的相对研究间可比性。 此外，还证明了高测量精度，因为T _{Cloud,app 的}变化可检测到仅 5 μL 的样品体积和 0.1 °C/min 的冷却速率增量。这项工作解释了T _Cloud检测方法的明显本质，展示了其检测精度，并拓宽了实验装置的适用性。