Analysis of vibrational dynamics in cell-substrate interactions using nanopipette electrochemical sensors.

Cell-substrate interaction plays a critical role in determining the mechanical status of living cell membrane. Changes of substrate surface properties can significantly alter the cell mechanical microenvironment, leading to mechanical changes of cell membrane. However, it is still difficult to accurately quantify the influence of the substrate surface properties on the mechanical status of living cell membrane without damage. This study addresses the challenge by using an electrochemical sensor made from an ultrasmall quartz nanopipette. With the tip diameter less than 100 nm, the nanopipette-based sensor achieves highly sensitive, noninvasive and label-free monitoring of the mechanical status of single living cells by collecting stable cyclic membrane oscillatory signals from continuous current versus time traces. The electrochemical signals collected from PC12 cells cultured on three different substrates (bare ITO (indium tin oxides) glass, hydroxyl modified ITO glass, amino modified ITO glass) indicate that the microenvironment more favorable for cell adhesion can increase the membrane stiffness. This work provides a label-free electrochemical approach to accurately quantify the mechanical status of single living cells in real-time, which may help to better understand the relationship between the cell membrane and the extra cellular matrix.

Construction of yield loss indicators for cold vortex, light-temperature-water combined stress during the flowering period of rice in Northeast China.

The construction of a yield loss evaluation index for the cold vortex type light-temperature-water composite adversity during rice flowering period in Northeast China is important for elucidating the impacts of cold vortex type composite disasters on rice yield loss in middle and high latitude areas. Moreover, it can provide meteorological support to ensure safe production of high-quality japonica rice in China and contribute to regional disaster reduction and efficiency improvement. By combining growth period data, meteorological data, and yield data, we delineated and constructed the composite stress occurrence index of cold vortex type light-temperature-water at the flowering stage of japonica. We analyzed the relationship between factors causing disasters and yield structure, as well as the relationship between different yield structures and yield by employing BP neural network method. We further dissected the processes involved in the causation of combined disasters. Based on the K-means clustering method and historical typical disaster years, we quantified the critical thresholds and disaster grades, and established an evaluation index and model for assessing yield loss caused by combined stress from cold vortex type light-temperature-water. Finally, we examined the spatial and temporal variations of low temperature, abundant rainfall, and reduced sunlight during the flowering period in the three provinces of Northeast China. Results showed that the critical thresholds for light, temperature, and water stress index during the flowering stage of mild, moderate, and severe cold vortex types were [0, 0.21), [0.21, 0.32), and [0.32, 0.64], respectively. The rates of yield loss were [0, 0.03), [0.03, 0.08), and [0.08, 0.096], respectively. Based on the verification results of a total of 751 samples in 11 random years from 1961 to 2020, the percentage of stations for which the production reduction grade, as calculated by the composite index developed in this study, aligning with the actual production reduction grade was 63.7%, consistently exceeding 58.0% annually. Moreover, the proportion of sites with a similarity or difference level of 1 stood at 88.3%, surpassing 85.0% in each year. The index could effectively assess the extent of rice yield loss caused by cold vortex disasters in Northeast China.