AIMC Topic: Nerve Tissue Proteins

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Identification and validation of PANX1 as an inflammasome-related biomarker in gestational diabetes mellitus: insights from machine learning and experimental approaches.

Mammalian genome : official journal of the International Mammalian Genome Society
Gestational diabetes mellitus (GDM) is characterized by glucose intolerance during pregnancy, resulting from insulin resistance, and is associated with increased maternal and neonatal risks. Inflammasomes play a critical role in GDM pathophysiology b...

Contrastive learning-based drug screening model for GluN1/GluN3A inhibitors.

Acta pharmacologica Sinica
GluN3A-containing NMDA receptors have recently emerged as promising therapeutic targets for neurological disorders. However, discovering potent modulators remains a significant challenge, primarily due to the limitations of traditional high-throughpu...

An efficient deep learning-based strategy to screen inhibitors for GluN1/GluN3A receptor.

Acta pharmacologica Sinica
The GluN1/GluN3A receptor, a unique excitatory glycine receptor recently identified in the central nervous system, challenges traditional perspectives of N-methyl-D-aspartate (NMDA) receptor diversity and glycinergic signaling. Its role in emotional ...

Functional MRGPRX2 expression on peripheral blood-derived human mast cells increases at low seeding density and is suppressed by interleukin-9 and fetal bovine serum.

Frontiers in immunology
Primary human mast cells (MC) obtained through culturing of blood-derived MC progenitors are the preferred model for the study of MRGPRX2- IgE-mediated MC activation. In order to assess the impact of culture conditions on functional MRGPRX2 express...

Exploring a novel seven-gene marker and mitochondrial gene TMEM38A for predicting cervical cancer radiotherapy sensitivity using machine learning algorithms.

Frontiers in endocrinology
BACKGROUND: Radiotherapy plays a crucial role in the management of Cervical cancer (CC), as the development of resistance by cancer cells to radiotherapeutic interventions is a significant factor contributing to treatment failure in patients. However...

Simulating the restoration of normal gene expression from different thyroid cancer stages using deep learning.

BMC cancer
BACKGROUND: Thyroid cancer (THCA) is the most common endocrine malignancy and incidence is increasing. There is an urgent need to better understand the molecular differences between THCA tumors at different pathologic stages so appropriate diagnostic...

The Emerging Role of Long Non-Coding RNAs and MicroRNAs in Neurodegenerative Diseases: A Perspective of Machine Learning.

Biomolecules
Neurodegenerative diseases (NDs) are characterized by progressive neuronal dysfunction and death of brain cells population. As the early manifestations of NDs are similar, their symptoms are difficult to distinguish, making the timely detection and d...

Machine learning identifies candidates for drug repurposing in Alzheimer's disease.

Nature communications
Clinical trials of novel therapeutics for Alzheimer's Disease (AD) have consumed a large amount of time and resources with largely negative results. Repurposing drugs already approved by the Food and Drug Administration (FDA) for another indication i...

Identification of contributing genes of Huntington's disease by machine learning.

BMC medical genomics
BACKGROUND: Huntington's disease (HD) is an inherited disorder caused by the polyglutamine (poly-Q) mutations of the HTT gene results in neurodegeneration characterized by chorea, loss of coordination, cognitive decline. However, HD pathogenesis is s...