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Cellular Reprogramming

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Metabolic reprogramming and macrophage expansion define ACPA-negative rheumatoid arthritis: insights from single-cell RNA sequencing.

Frontiers in immunology
BACKGROUND: Anti-citrullinated peptide antibodies (ACPA)-negative (ACPA-) rheumatoid arthritis (RA) presents significant diagnostic and therapeutic challenges due to the absence of specific biomarkers, underscoring the need to elucidate its distincti...

Basic fibroblast growth factor is critical to reprogramming buffalo (Bubalus bubalis) primordial germ cells into embryonic germ stem cell-like cells.

Theriogenology
Primordial germ cells (PGCs) are destined to form gametes in vivo, and they can be reprogrammed into pluripotent embryonic germ (EG) cells in vitro. Buffalo PGC have been reported to be reprogrammed into EG-like cells, but the identities of the major...

A Machine Learning Assisted, Label-free, Non-invasive Approach for Somatic Reprogramming in Induced Pluripotent Stem Cell Colony Formation Detection and Prediction.

Scientific reports
During cellular reprogramming, the mesenchymal-to-epithelial transition is accompanied by changes in morphology, which occur prior to iPSC colony formation. The current approach for detecting morphological changes associated with reprogramming purely...

DeepNEU: cellular reprogramming comes of age - a machine learning platform with application to rare diseases research.

Orphanet journal of rare diseases
BACKGROUND: Conversion of human somatic cells into induced pluripotent stem cells (iPSCs) is often an inefficient, time consuming and expensive process. Also, the tendency of iPSCs to revert to their original somatic cell type over time continues to ...

Human Induced Pluripotent Stem Cell Reprogramming Prediction in Microscopy Images using LSTM based RNN.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
We present a LSTM (Long Short-Term Memory) based RNN (recurrent neural network) method for predicting human induced Pluripotent Stem (hiPS) cells in the reprogramming process. The method uses a trained LSTM network by time-lapse microscopy images to ...

A novel machine learning based approach for iPS progenitor cell identification.

PLoS computational biology
Identification of induced pluripotent stem (iPS) progenitor cells, the iPS forming cells in early stage of reprogramming, could provide valuable information for studying the origin and underlying mechanism of iPS cells. However, it is very difficult ...

Neuronal differentiation strategies: insights from single-cell sequencing and machine learning.

Development (Cambridge, England)
Neuronal replacement therapies rely on the differentiation of specific cell types from embryonic or induced pluripotent stem cells, or on the direct reprogramming of differentiated adult cells via the expression of transcription factors or signaling...

AI in cellular engineering and reprogramming.

Biophysical journal
During the last decade, artificial intelligence (AI) has increasingly been applied in biophysics and related fields, including cellular engineering and reprogramming, offering novel approaches to understand, manipulate, and control cellular function....