Project description:HPLC MS/MS confirmation of lipids found to be heterogeneously distributed between rested and sleep-deprived Drosophila melanogaster brain samples by MALDI MSI. Data belongs to publication "Kv Channels Integrate Sleep Pressure in a Voltage-Gated Lipid Peroxidation Memory"
Project description:Differential analysis of plasma transmembrane proteins between two human blood-brain barrier model cells, hCMEC/D3 and HBMEC/cib cells.
Project description:Tight homeostatic control of brain amino acids (AA) depends on transport via solute family carrier proteins expressed by the Blood-Brain Barrier (BBB) microvascular endothelial cells (BMEC). To characterize the mouse BMEC transcriptome and probe culture-induced changes microarray analyses of PECAM-1+ endothelial cells (ppMBMECs) were compared with primary MBMECs (pMBMEC) cultured in the presence or absence of glial cells, and with b.End5 endothelioma cell-line. Selected cell marker and AA transporter mRNA levels were further verified by real-time RT PCR. Regardless of glial co-culture expression of a large subset of genes was strongly altered by a brief culture step. This is consistent with the known dependence of BMECs on in vivo interactions to maintain physiological functions, e.g. tight barrier formation, and their consequent de-differentiation in culture. Seven (4F2hc, Lat1, Taut, Snat3, Snat5, Xpct, Cat1) of nine highly in vivo expressed AA transporter mRNAs were strongly down-regulated for all cultures and two (Snat2, Eaat3) were variably regulated. In contrast, five AA transporter mRNAs with low in vivo expression, including y+Lat2, xCT, and Snat1, were strongly up-regulated by culture. We hypothesized that the AA transporters highly expressed in ppMBMECs and strongly down-regulated in culture play a major in vivo role for BBB transendothelial transport. Keywords: culture vs non-cultured RNA was prepared from 4 sources of endothelial cells: 1) isolated mouse brain microvascular endothelial cells that were cultured in transwells with and 2) without non-contact co-culture with glial cultures or 3) further purified using anti-PECAM1 magnetic bead sorting and 4) the endothelioma b.End5 cell-line.
Project description:This model predicts the Blood-Brain Barrier (BBB) penetration potential of small molecules using as training data the curated MoleculeNet benchmark containing 2000 experimental data points. It has been trained using the GROVER transformer.
Model Type: Predicitive machine learning model.
Model Relevance: Predicts Probability that a molecule crosses the blood brain barrier.
Model Encoded by: Amna Ali (Ersilia)
Metadata Submitted in BioModels by: Zainab Ashimiyu-Abdusalam
Implementation of this model code by Ersilia is available here:
https://github.com/ersilia-os/eos1amr
