AIMC Topic: Iron

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Identification of biomarkers related to iron death in diabetic kidney disease based on machine learning algorithms.

Annals of human biology
BACKGROUND: While ferroptosis has been recognised for its key role in tumour development, its involvement in DKD is not well understood. Identifying differentially expressed ferroptosis-related genes (DEIRGs) could help improve early diagnosis and tr...

Beetle-inspired responsive photonic microgel assemblies for multi-sensing enhanced by machine learning.

Biosensors & bioelectronics
Bioinspired photonic hydrogels hold promise as sensors; however, their use in triple-analyte sensing optical devices has been minimally explored. Temperature, serum Fe levels, and X-ray doses are critical factors for predicting and monitoring medical...

A negative combined effect of exposure to maternal Mn-Cu-Rb-Fe metal mixtures on gestational anemia, and the mediating role of creatinine in the Guangxi Birth Cohort Study (GBCS): Twelve machine learning algorithms.

Ecotoxicology and environmental safety
The link between individual metals and gestational anemia has been established, but the impact of metal mixtures and the mediating role of renal function on gestational anemia remain inconclusive. The concentrations of 20 blood essential trace and no...

Machine-learning models to predict iron recovery after blood donation: a model development and external validation study.

The Lancet. Haematology
BACKGROUND: Machine-learning models directly predicting iron biomarkers after blood donation could help to manage donation-associated iron deficiency and avoid low haemoglobin deferrals. No such models have been externally validated internationally. ...

Application of machine learning for the analysis of peripheral blood biomarkers in oral mucosal diseases: a cross-sectional study.

BMC oral health
BACKGROUND: Oral mucosal lesions are widespread globally, have a high prevalence in clinical practice, and significantly impact patients' quality of life. However, their pathogenesis remains unclear. Recent evidences suggested that hematological para...

Traditional and deep learning-oriented medical and biological image analysis.

Bratislavske lekarske listy
We investigated various methods for image segmentation and image processing for the segmentation of MRI of human medical data, as well as bioinformatics for the segmentation of brain cell details, in this work. The goal is to demonstrate and bring va...

Degradation of textile dyes Remazol Yellow Gold and reactive Turquoise: optimization, toxicity and modeling by artificial neural networks.

Water science and technology : a journal of the International Association on Water Pollution Research
In this work, the degradation of Remazol Yellow Gold RNL-150% and Reactive Turquoise Q-G125 were investigated using AOP: photolysis, UV/HO, Fenton and photo-Fenton. It was found that the photo-Fenton process employing sunlight radiation was the most ...

Dilemma: Correlation Between Serum Level of Hepcidin and IL-6 in Anemic Myeloma Patients.

Medical archives (Sarajevo, Bosnia and Herzegovina)
INTRODUCTION: Anemia occurs in 60% to 80 % of patients with newly diagnosed myeloma multiplex (MM). The cause of anemia in MM is probably multi factorial and involved among the others hepcidin and some cytokines, especially interleukine-6. Anemia in ...

[Evaluation of Basic Performance of "Point Strip ferritin-3000" for Simple and Rapid Quantification of Serum Ferritin].

Rinsho byori. The Japanese journal of clinical pathology
Serum ferritin is an excellent marker for total iron content in the body and is essential for the diagnosis of iron deficiency or iron overload. Recently, a simple and rapid method, which utilizes immunochromatography for the quantification of serum ...