AIMC Topic: Mitochondria

Clear Filters Showing 71 to 80 of 116 articles

Robust blind spectral unmixing for fluorescence microscopy using unsupervised learning.

PloS one
Due to the overlapping emission spectra of fluorophores, fluorescence microscopy images often have bleed-through problems, leading to a false positive detection. This problem is almost unavoidable when the samples are labeled with three or more fluor...

Visual Correspondences for Unsupervised Domain Adaptation on Electron Microscopy Images.

IEEE transactions on medical imaging
We present an Unsupervised Domain Adaptation strategy to compensate for domain shifts on Electron Microscopy volumes. Our method aggregates visual correspondences-motifs that are visually similar across different acquisitions-to infer changes on the ...

Identification of Hürthle cell cancers: solving a clinical challenge with genomic sequencing and a trio of machine learning algorithms.

BMC systems biology
BACKGROUND: Identification of Hürthle cell cancers by non-operative fine-needle aspiration biopsy (FNAB) of thyroid nodules is challenging. Resultingly, non-cancerous Hürthle lesions were conventionally distinguished from Hürthle cell cancers by hist...

Automatic localization and identification of mitochondria in cellular electron cryo-tomography using faster-RCNN.

BMC bioinformatics
BACKGROUND: Cryo-electron tomography (cryo-ET) enables the 3D visualization of cellular organization in near-native state which plays important roles in the field of structural cell biology. However, due to the low signal-to-noise ratio (SNR), large ...

In vitro survival, growth, and maturation of sheep oocytes from secondary follicles cultured in serum-free conditions: impact of a constant or a sequential medium containing recombinant human FSH.

Domestic animal endocrinology
This study evaluated the in vitro development and maturation of ovine oocytes from secondary follicles cultured in serum-free medium containing fixed or sequential concentrations of recombinant human FSH (rhFSH). Follicles were cultured in α-MEM alon...

Deep Analysis of Mitochondria and Cell Health Using Machine Learning.

Scientific reports
There is a critical need for better analytical methods to study mitochondria in normal and diseased states. Mitochondrial image analysis is typically done on still images using slow manual methods or automated methods of limited types of features. Mi...

Analyzing complex single-molecule emission patterns with deep learning.

Nature methods
A fluorescent emitter simultaneously transmits its identity, location, and cellular context through its emission pattern. We developed smNet, a deep neural network for multiplexed single-molecule analysis to retrieve such information with high accura...

Milk from cows fed a diet with a high forage:concentrate ratio improves inflammatory state, oxidative stress, and mitochondrial function in rats.

Journal of dairy science
Excessive energy intake may evoke complex biochemical processes characterized by inflammation, oxidative stress, and impairment of mitochondrial function that represent the main factors underlying noncommunicable diseases. Because cow milk is widely ...

Activation of PPARα by Oral Clofibrate Increases Renal Fatty Acid Oxidation in Developing Pigs.

International journal of molecular sciences
The objective of this study was to evaluate the effects of peroxisome proliferator-activated receptor α (PPARα) activation by clofibrate on both mitochondrial and peroxisomal fatty acid oxidation in the developing kidney. Ten newborn pigs from 5 litt...