AIMC Topic: Reactive Oxygen Species

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Clinical evaluation of deep learning-based clinical target volume three-channel auto-segmentation algorithm for adaptive radiotherapy in cervical cancer.

BMC medical imaging
OBJECTIVES: Accurate contouring of the clinical target volume (CTV) is a key element of radiotherapy in cervical cancer. We validated a novel deep learning (DL)-based auto-segmentation algorithm for CTVs in cervical cancer called the three-channel ad...

Group Emotion Detection Based on Social Robot Perception.

Sensors (Basel, Switzerland)
Social robotics is an emerging area that is becoming present in social spaces, by introducing autonomous social robots. Social robots offer services, perform tasks, and interact with people in such social environments, demanding more efficient and co...

Robot Operating System 2: Design, architecture, and uses in the wild.

Science robotics
The next chapter of the robotics revolution is well underway with the deployment of robots for a broad range of commercial use cases. Even in a myriad of applications and environments, there exists a common vocabulary of components that robots share-...

Machine Learning Identifies Pan-Cancer Landscape of Nrf2 Oxidative Stress Response Pathway-Related Genes.

Oxidative medicine and cellular longevity
BACKGROUND: Oxidative stress produced a large amount of reactive oxygen species (ROS), which played a pivotal role in balanced ability and determining cell fate. The activated Nrf2 signaling pathway that responds to the excessive ROS regulated the ex...

Cytocompatible manganese dioxide-based hydrogel nanoreactors for MRI imaging.

Biomaterials advances
The application of nanoparticles in magnetic resonance imaging (MRI) has been greatly increasing, due to their advantageous properties such as nanoscale dimension and tuneability. In this context, manganese (Mn)-based nanoparticles have been greatly ...

Establishment of a 13 genes-based molecular prediction score model to discriminate the neurotoxic potential of food relevant-chemicals.

Toxicology letters
Although many neurotoxicity prediction studies of food additives have been developed, they are applicable in a qualitative way. We aimed to develop a novel prediction score that is described quantitatively and precisely. We examined cell viability, r...

Biodegradable Small-Scale Swimmers for Biomedical Applications.

Advanced materials (Deerfield Beach, Fla.)
Most forms of biomatter are ephemeral, which means they transform or deteriorate after a certain time. From this perspective, implantable healthcare devices designed for temporary treatments should exhibit the ability to degrade and either blend in w...

Predicting Proteolysis in Complex Proteomes Using Deep Learning.

International journal of molecular sciences
Both protease- and reactive oxygen species (ROS)-mediated proteolysis are thought to be key effectors of tissue remodeling. We have previously shown that comparison of amino acid composition can predict the differential susceptibilities of proteins t...

Towards a new model and classification of mood disorders based on risk resilience, neuro-affective toxicity, staging, and phenome features using the nomothetic network psychiatry approach.

Metabolic brain disease
Current diagnoses of mood disorders are not cross validated. The aim of the current paper is to explain how machine learning techniques can be used to a) construct a model which ensembles risk/resilience (R/R), adverse outcome pathways (AOPs), stagin...

Chestnut shells (Italian cultivar "Marrone di Roccadaspide" PGI): Antioxidant activity and chemical investigation with in depth LC-HRMS/MS rationalization of tannins.

Food research international (Ottawa, Ont.)
In Italy a particularly valuable chestnut is "Marrone di Roccadaspide", a protected geographical indication (PGI) product, deriving from a Castanea sativa cultivar, typical of Salerno province in Campania region. As chestnut industrial processes yiel...