Conflicts of interest

the Euclidean distance between data matrices was defined as performed (scalar values). We summarized the images close in distance as one larger cluster, and we then calculated the distance between the newly grouped individual clusters. By repeating this process, clustering

Figure 7. An example of HCA analysis. Distribution of hemoglobin subunit alpha peptide signal (m/z = 1529) is shown.

Figure 6. Examples of DM. The component (m/z)l@xij in the matrix signifies the lth m/z values (1 ≤ l ≤ k) for the pixels at the coordinate of xij (1 ≤ i ≤ m, 1 ≤ j ≤ n) on the sample issue. This DM is the platform of the ROI analysis and other static analyses. The bottom illustration represents the coordinate on the cardiac tissue (indicated by orange circles). First, we measured the intensity values for m/z = (m/z)1 of each pixel in the image and arranged the value as a column vector. Similarly, another value m/z = (m/z)2 was measured, and the value was arranged as the next column vector. Further measurements of all detected intensity values of m/z (1, 2,…l, …) are arranged in the row direction. Row and column

vectors yielded a DM for a single whole dataset of a tissue.

130 Histology

The authors have declared no conflicts of interest.
