93 research outputs found
Interface crack between dissimilar one-dimensional hexagonal quasicrystals with piezoelectric effect
T cell receptor reversed polarity recognition of a self-antigen major histocompatibility complex
Central to adaptive immunity is the interaction between the αβ T cell receptor (TCR) and peptide presented by the major histocompatibility complex (MHC) molecule. Presumably reflecting TCR-MHC bias and T cell signaling constraints, the TCR universally adopts a canonical polarity atop the MHC. We report the structures of two TCRs, derived from human induced T regulatory (iTreg) cells, complexed to an MHC class II molecule presenting a proinsulin-derived peptide. The ternary complexes revealed a 180° polarity reversal compared to all other TCR-peptide-MHC complex structures. Namely, the iTreg TCR α-chain and β-chain are overlaid with the α-chain and β-chain of MHC class II, respectively. Nevertheless, this TCR interaction elicited a peptide-reactive, MHC-restricted T cell signal. Thus TCRs are not 'hardwired' to interact with MHC molecules in a stereotypic manner to elicit a T cell signal, a finding that fundamentally challenges our understanding of TCR recognition
Using Functional Signatures to Identify Repositioned Drugs for Breast, Myelogenous Leukemia and Prostate Cancer
The cost and time to develop a drug continues to be a major barrier to widespread distribution of medication. Although the genomic revolution appears to have had little impact on this problem, and might even have exacerbated it because of the flood of additional and usually ineffective leads, the emergence of high throughput resources promises the possibility of rapid, reliable and systematic identification of approved drugs for originally unintended uses. In this paper we develop and apply a method for identifying such repositioned drug candidates against breast cancer, myelogenous leukemia and prostate cancer by looking for inverse correlations between the most perturbed gene expression levels in human cancer tissue and the most perturbed expression levels induced by bioactive compounds. The method uses variable gene signatures to identify bioactive compounds that modulate a given disease. This is in contrast to previous methods that use small and fixed signatures. This strategy is based on the observation that diseases stem from failed/modified cellular functions, irrespective of the particular genes that contribute to the function, i.e., this strategy targets the functional signatures for a given cancer. This function-based strategy broadens the search space for the effective drugs with an impressive hit rate. Among the 79, 94 and 88 candidate drugs for breast cancer, myelogenous leukemia and prostate cancer, 32%, 13% and 17% respectively are either FDA-approved/in-clinical-trial drugs, or drugs with suggestive literature evidences, with an FDR of 0.01. These findings indicate that the method presented here could lead to a substantial increase in efficiency in drug discovery and development, and has potential application for the personalized medicine
Long non-coding RNA AFAP1-AS1 facilitates tumor growth and promotes metastasis in colorectal cancer
A heterogeneous cohesive model for quasi-brittle materials considering spatially varying random fracture properties
Optimal control of multi-zone VAV air-conditioning system and fresh air flow rate
Department of Building Services EngineeringRefereed conference pape
Evaluation of energy performance and alternative control strategies of new buildings
Department of Building Services EngineeringRefereed conference pape
Development of an optimal control strategy for the centralized cooling water system in international commerce centre of Hong Kong
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