Dataset related to article: FM19G11-LOADED NANOPARTICLES MODULATE ENERGETIC STATUS AND PRODUCTION OF REACTIVE OXYGEN SPECIES IN MYOBLASTS FROM ALS MICE

The database inlcudes the CT values obtained from the mrna analysis by realt time pcr.

in addition the database includes the data obtaiend by mina analysis. specifically,

MiNA plugin classifies each pixel of a skeleton image and, according to how the pixels are spatially related one to each other, mitochondria are classified as 1) individuals, characterized by rod, punctate or large/round morphology; 2) networks, which are a large continuous reticulum of multiple mitochondria. Each network contains at least one junction and more than one branch.

MiNA specifically computes the number of individuals, which is the number of objects that does not contain a junction pixel, and corresponds to the number of mitochondria that are not part of a network. Regarding the network analysis, MiNA accurately provides the: 1) number of networks, corresponding to the number of objects that contains at least one junction pixel; the number of networks is indicative of the balance between the fission and fusion processes, where the mitochondria divides into one or more independent structure (individuals), or are fused resulting in thin and elongated highly interconnected mitochondrial network; 2) mean length of network branches; 3) median length of network branches; 4) standard deviation of network branch lengths; 5) mean number of branches per network; 6) median number of branches per network; and 7) standard deviation of the number of branches per network.

These parameters quantify the extension of the mitochondrial networks and how statistically disperse they are. Finally, MiNA enables the mitochondrial footprint analysis, which calculates the total area or volume of the image consumed by the lengths of mitochondrial structure using a topological skeleton.