Abstract   Researchers at UNC have created a panel of cell lines originating from the human airway epithelium using improved primary cell culture methods and a new lentiviral vector to introduce human telomerase reverse transcriptase (hTERT) and the mouse Bmi1 gene in a single vector. The novel lentiviral vector was introduced into three non-cystic fibrosis and three ?F508 homozygous CF primary bronchial cell preparations. The resulting cell lines have extended growth capacity but retain the ability to differentiate along the normal muco-ciliary pathway.   Market Application   Ideal for studying Cystic Fibrosis Pathogenesis and Development and Testing of CF Therapeutics. Publications   Fulcher ML, Gabriel SE, Olsen JC, Tatreau JR, Gentzsch M, Livanos E, Saavedra MT, Salmon P, Randell SH. Novel human bronchial epithelial cell lines for cystic fibrosis research. Am J Physiol Lung Cell Mol Physiol. 2009 Jan;296(1):L82-91. doi: 10.1152/ajplung.90314.2008. Epub 2008 Oct 31. PMID: 18978040; PMCID: PMC2636952. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2636952/ Categories Research Tools         Cell Lines Therapeutics by Clinical Indication         Pulmonology

Abstract   A suite of of stable lentiviral vector packaging cell lines which facilitate the production of integration defective lentiviral vectors pseudotyped with the VSV-G envelope. These IDLV packaging stable cell lines are tetracycline-inducible and produce high-titer IDLV lentiviral particles and are suitable for packaging a variety of gene products.   Market Application   Ideal for generating lentiviral-packaged gene products for research, cell therapy, and gene therapy applications. Publications   Hu et al Molecular Therapy — Methods & Clinical Development (2015) 2, 15025; doi:10.1038/mtm.2015.25. Entitled: 'Generation of a stable packaging cell line producing high-titer PPT-deleted integration-deficient lentiviral vectors" https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4510976/ Categories Life Sciences        Cellular Therapeutics        Industrial Biotechnology - Life Sciences Research Tools        Cell Lines

We created inducible cell lines expressing human MRGPRX2 and MRGPRX4 receptors. These cell lines can be used to identify and study selective agonists for these receptors. If you are an academic institution or nonprofit organization interested in this research tool for noncommercial purposes, please contact the researcher directly to inquire about availability.

The p53 preclinical models developed in our laboratory originally in collaboration with Daniel Medina have been characterized in collaboration with Dr. Charles Perou at the Lineberger Comprehensive Cancer at the University of North Carolina at Chapel Hill as described in a previous disclosure and originally published in Herschkowitz et al. PNAS USA 2021. PMID 21633010. The cell lines were derived from the tumor bank. Additional PMID 35442423. 

This is a growth enhanced cell line derived from primary epithelial cells originally obtained from the explanted lungs of a donor with cystic fibrosis, in accordance with an IRB-approved protocol, that underwent lung transplantation. The CFTR genotype is G542X homozygous, enabling this cell line to be used to study the biology and potential therapies for diseases created by premature termination codon mutations. The primary cells were growth enhanced by lentiviral delivery of two oncogenes, Bmi-1 and hTERT. Cells that are growth enhanced in this manner typically remain diploid and, when expanded and cultured appropriately, retain the ability to form resistive epithelial sheets suitable for testing on ion transport properties.

Abstract   Researchers at UNC have created a panel of cell lines originating from the human airway epithelium using improved primary cell culture methods and a new lentiviral vector to introduce human telomerase reverse transcriptase (hTERT) and the mouse Bmi1 gene in a single vector. The novel lentiviral vector was introduced into three non-cystic fibrosis and three ?F508 homozygous CF primary bronchial cell preparations. The resulting cell lines have extended growth capacity but retain the ability to differentiate along the normal muco-ciliary pathway.   Market Application   Ideal for studying Cystic Fibrosis Pathogenesis and Development and Testing of CF Therapeutics. Publications   Fulcher ML, Gabriel SE, Olsen JC, Tatreau JR, Gentzsch M, Livanos E, Saavedra MT, Salmon P, Randell SH. Novel human bronchial epithelial cell lines for cystic fibrosis research. Am J Physiol Lung Cell Mol Physiol. 2009 Jan;296(1):L82-91. doi: 10.1152/ajplung.90314.2008. Epub 2008 Oct 31. PMID: 18978040; PMCID: PMC2636952. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2636952/ Categories Research Tools         Cell Lines Therapeutics by Clinical Indication         Pulmonology

We have generated a novel GEM (Genetically Engineered Murine) Model of luminal bladder cancer, called UPPL, by knocking out Pten and Trp53 in Upk3a expressing cells (Upk3a-CreERT2). Once bladder tumors formed, cell lines were generated that can be passaged in vitro as well as form tumors in immunocompetent B6 mice

 Mucin secretion is regulated by purigenic agonists and inflammatory mediators. The SPOC1 cell line was derived from spontaneously immortalized rat tracheal epithelial secondary cultures. SPOC1 cells secrete mucin under the control of a P2u purinoceptor. SPOC1 cells are a valuable tool for the study of airway epithelial secretory cell differentiation, function and neoplastic progression, as well as the key molecular events underlying mucous production. This cell line is available for distribution from Applied Biological Materials and can be found at https://www.abmgood.com/immortalized-rat-tracheal-epithelial-cells-spoc-1.html  

A repository of terms extracted from the biomedical literature, named ChemoText, has been developed. ChemoText is designed specifically to be used in drug research and discovery, including predicting new uses for existing drugs or drug reprofiling. The repository is constructed by pulling the Medline annotations behind each PubMed record and extracting annotations that identify chemicals and indicate what biological activity and effects the chemicals have. The database can be seen as a network of relationships between chemicals, proteins, disease, and biological effects. Advantages:•  Useful in drug research and discovery applications •  Designed to capture relationships between diseases, therapeutics and biology

Deep Learning for Hemorrhage Segmentation of Computed Tomography Scans Automated 3D deep neural network accurately segments intracerebral hemorrhages, optimizing clinical trial workflows and improving outcomes Background Patients with intracerebral hemorrhage (ICH) are at risk of significant morbidity and mortality. The volume and location of the hematoma, as well as the presence and volume of intraventricular hemorrhage (IVH) are well established predictors of outcome. Therapeutic clinical trials to treat ICH and IVH historically rely on linear estimators and semi-quantitative scales, such as ABC/2, the modified Graeb score (mGS), or the IVH score for timely volumetric estimation. However, there are limitations for the accuracy of these methods, such as the ABC/2 formula lacking accuracy in estimating the volume of complex hemorrhages or those with a volume greater than 30ml, and mGS does not have a conversion for IVH volume to ml. This necessitates automated, accurate tools for clinical use.    Technology Overview To address the need for methods with improved accuracy, clinicians in the Department of Neurology at UNC with collaborators at Johns Hopkins, have developed a fully-automated deep neural network (DNN) model to accurately segment ICH and IVH, as well as estimate the volumes for each. The DNN model has been trained using diagnostic CT data from two separate clinical trials. Validation of the DNN model against the current gold-standard, semi-automated planimetry segmentations estimates, was conducted over the course of two separate clinical trials as well. The DNN model can be used to accurately segment ICH and IVH patients to aid clinicians in the proper diagnosis and treatment. Proper segmentation can also aid in enrolling patients in clinical trials as well as to monitor the interventions under investigation in clinical trials.  Further Details: Mansour A, et al. Post-Trial Enhanced Deployment and Technical Performance with the MISTIE Procedure per Lessons Learned. J Stroke Cerebrovasc Dis. 2021 Sep;30(9):105996. https://pubmed.ncbi.nlm.nih.gov/34303090/ Sharrock MF, et al. 3D Deep Neural Network Segmentation of Intracerebral Hemorrhage: Development and Validation for Clinical Trials. Neuroinformatics. 2021 Jul;19(3):403-415. https://pubmed.ncbi.nlm.nih.gov/32980970/ Sharrock MF, Mould WA, Hildreth M, Ryu EP, Walborn N, Awad IA, Hanley DF, Muschelli J. Bayesian deep learning outperforms clinical trial estimators of intracerebral and intraventricular hemorrhage volume. J Neuroimaging. 2022 Apr 17. https://pubmed.ncbi.nlm.nih.gov/35434846/ Benefits Aids in diagnosis and treatment of patients. Use in clinical trials evaluating therapeutic or surgical interventions. Accurately segment intracerebral hemorrhage and intraventricular hemorrhage. Trained using patient data from two separate clinical trials.