Mitochondrial physiology

As the knowledge base and importance of mitochondrial physiology to evolution, health and disease expands, the necessity for harmonizing the terminology concerning mitochondrial respiratory states and rates has become increasingly apparent. The chemiosmotic theory establishes the mechanism of energy transformation and coupling in oxidative phosphorylation. The unifying concept of the protonmotive force provides the framework for developing a consistent theoretical foundation of mitochondrial physiology and bioenergetics. We follow the latest SI guidelines and those of the International Union of Pure and Applied Chemistry (IUPAC) on terminology in physical chemistry, extended by considerations of open systems and thermodynamics of irreversible processes. The concept-driven constructive terminology incorporates the meaning of each quantity and aligns concepts and symbols with the nomenclature of classical bioenergetics. We endeavour to provide a balanced view of mitochondrial respiratory control and a critical discussion on reporting data of mitochondrial respiration in terms of metabolic flows and fluxes. Uniform standards for evaluation of respiratory states and rates will ultimately contribute to reproducibility between laboratories and thus support the development of data repositories of mitochondrial respiratory function in species, tissues, and cells. Clarity of concept and consistency of nomenclature facilitate effective transdisciplinary communication, education, and ultimately further discovery

Mitochondrial physiology

As the knowledge base and importance of mitochondrial physiology to evolution, health and disease expands, the necessity for harmonizing the terminology concerning mitochondrial respiratory states and rates has become increasingly apparent. The chemiosmotic theory establishes the mechanism of energy transformation and coupling in oxidative phosphorylation. The unifying concept of the protonmotive force provides the framework for developing a consistent theoretical foundation of mitochondrial physiology and bioenergetics. We follow the latest SI guidelines and those of the International Union of Pure and Applied Chemistry (IUPAC) on terminology in physical chemistry, extended by considerations of open systems and thermodynamics of irreversible processes. The concept-driven constructive terminology incorporates the meaning of each quantity and aligns concepts and symbols with the nomenclature of classical bioenergetics. We endeavour to provide a balanced view of mitochondrial respiratory control and a critical discussion on reporting data of mitochondrial respiration in terms of metabolic flows and fluxes. Uniform standards for evaluation of respiratory states and rates will ultimately contribute to reproducibility between laboratories and thus support the development of data repositories of mitochondrial respiratory function in species, tissues, and cells. Clarity of concept and consistency of nomenclature facilitate effective transdisciplinary communication, education, and ultimately further discovery

Assessment of Component Selection Strategies in Hyperspectral Imagery

Hyperspectral imagery (HSI) integrates many continuous and narrow bands that cover different regions of the electromagnetic spectrum. However, the main challenge is the high dimensionality of HSI data due to the ’Hughes’ phenomenon. Thus, dimensionality reduction is necessary before applying classification algorithms to obtain accurate thematic maps. We focus the study on the following feature-extraction algorithms: Principal Component Analysis (PCA), Minimum Noise Fraction (MNF), and Independent Component Analysis (ICA). After a literature survey, we have observed a lack of a comparative study on these techniques as well as accurate strategies to determine the number of components. Hence, the first objective was to compare traditional dimensionality reduction techniques (PCA, MNF, and ICA) in HSI of the Compact Airborne Spectrographic Imager (CASI) sensor and to evaluate different strategies for selecting the most suitable number of components in the transformed space. The second objective was to determine a new dimensionality reduction approach by dividing the CASI HSI regarding the spectral regions covering the electromagnetic spectrum. The components selected from the transformed space of the different spectral regions were stacked. This stacked transformed space was evaluated to see if the proposed approach improves the final classification

Evaluation of Hyperspectral Classification Maps in Heterogeneous Ecosystem

International audienc

Adjustment of Sentinel-3 Spectral Bands With Sentinel-2 to Enhance the Quality of Spatio-Temporally Fused Images

Spatiotemporal fusion (STF) methods are a paramount solution for generating high spatial and temporal time series, overcoming the limitations of spatial and temporal resolution of satellite data. STF methods typically rely on band-by-band fusion, assuming spectral similarities. However, selecting the optimal band for fusion becomes challenging when multiple narrow bands overlap with the target band, often leading to the use of only one single band. Furthermore, sensor specifications and observation configurations can further compound this challenge, reducing spectral and spatial information. We introduce a new preprocessing step that maximizes the use of spectral information from narrow bands. It minimizes radiometric differences caused by sensor variations in the STF process by considering the spectral response function (SRF). Our method generates adjusted bands that closely match the target band's spectral characteristics, leveraging all available spectral information. We evaluated this strategy at two study sites employing Sentinel 2 and Sentinel 3 data by comparing fused images from adjusted bands and the original bands using three popular STF methods. The results obtained showed that the images fused with the adjusted bands were closer to the target images and achieved better performance, improving the fusion quality compared to the original bands (SAM by 37% and RMSE by 30%). The preprocessing step offers a feasible approach to generate spectral bands that would be captured by the sensors if they had the same spectral characteristics. Importantly, this preprocessing technique is applicable to any STF method

Assessment of Hyperspectral Sharpening Methods for the Monitoring of Natural Areas Using Multiplatform Remote Sensing Imagery

International audienc

Hyperspectral Classification Through Unmixing Abundance Maps Addressing Spectral Variability

International audienc

Classification Using Unmixing Models in Areas With Substantial Endmember Variability

International audienc

Extended Linear Mixing Model in an Ecosytem with High Spectral Variability

International audienc