J. Jefferson

Bio: J. Jefferson is an academic researcher from University of California, Riverside. The author has contributed to research in topics: Protein aggregation & Congenital cataracts. The author has an hindex of 1, co-authored 1 publications receiving 268 citations.

Lanosterol reverses protein aggregation in cataracts

Abstract: The human lens is comprised largely of crystallin proteins assembled into a highly ordered, interactive macro-structure essential for lens transparency and refractive index. Any disruption of intra- or inter-protein interactions will alter this delicate structure, exposing hydrophobic surfaces, with consequent protein aggregation and cataract formation. Cataracts are the most common cause of blindness worldwide, affecting tens of millions of people1, and currently the only treatment is surgical removal of cataractous lenses. The precise mechanisms by which lens proteins both prevent aggregation and maintain lens transparency are largely unknown. Lanosterol is an amphipathic molecule enriched in the lens. It is synthesized by lanosterol synthase (LSS) in a key cyclization reaction of a cholesterol synthesis pathway. Here we identify two distinct homozygous LSS missense mutations (W581R and G588S) in two families with extensive congenital cataracts. Both of these mutations affect highly conserved amino acid residues and impair key catalytic functions of LSS. Engineered expression of wild-type, but not mutant, LSS prevents intracellular protein aggregation of various cataract-causing mutant crystallins. Treatment by lanosterol, but not cholesterol, significantly decreased preformed protein aggregates both in vitro and in cell-transfection experiments. We further show that lanosterol treatment could reduce cataract severity and increase transparency in dissected rabbit cataractous lenses in vitro and cataract severity in vivo in dogs. Our study identifies lanosterol as a key molecule in the prevention of lens protein aggregation and points to a novel strategy for cataract prevention and treatment.

An artificial intelligence platform for the multihospital collaborative management of congenital cataracts

Abstract: Using artificial intelligence (AI) to prevent and treat diseases is an ultimate goal in computational medicine. Although AI has been developed for screening and assisted decision-making in disease prevention and management, it has not yet been validated for systematic application in the clinic. In the context of rare diseases, the main strategy has been to build specialized care centres; however, these centres are scattered and their coverage is insufficient, which leaves a large proportion of rare-disease patients with inadequate care. Here, we show that an AI agent using deep learning, and involving convolutional neural networks for diagnostics, risk stratification and treatment suggestions, accurately diagnoses and provides treatment decisions for congenital cataracts in an in silico test, in a website-based study, in a ‘finding a needle in a haystack’ test and in a multihospital clinical trial. We also show that the AI agent and individual ophthalmologists perform equally well. Moreover, we have integrated the AI agent with a cloud-based platform for multihospital collaboration, designed to improve disease management for the benefit of patients with rare diseases. An artificial intelligence agent integrated with a cloud-based platform for multihospital collaboration performs equally as well as ophthalmologists in the diagnosis of congenital cataracts in a series of online tests and a multihospital clinical trial.

Pharmacological chaperone for α-crystallin partially restores transparency in cataract models

Abstract: Cataracts reduce vision in 50% of individuals over 70 years of age and are a common form of blindness worldwide. Cataracts are caused when damage to the major lens crystallin proteins causes their misfolding and aggregation into insoluble amyloids. Using a thermal stability assay, we identified a class of molecules that bind α-crystallins (cryAA and cryAB) and reversed their aggregation in vitro. The most promising compound improved lens transparency in the R49C cryAA and R120G cryAB mouse models of hereditary cataract. It also partially restored protein solubility in the lenses of aged mice in vivo and in human lenses ex vivo. These findings suggest an approach to treating cataracts by stabilizing α-crystallins.

Self-renewing Monolayer of Primary Colonic or Rectal Epithelial Cells

Abstract: Background & aims Three-dimensional organoid culture has fundamentally changed the in vitro study of intestinal biology enabling novel assays; however, its use is limited because of an inaccessible luminal compartment and challenges to data gathering in a three-dimensional hydrogel matrix. Long-lived, self-renewing 2-dimensional (2-D) tissue cultured from primary colon cells has not been accomplished. Methods The surface matrix and chemical factors that sustain 2-D mouse colonic and human rectal epithelial cell monolayers with cell repertoires comparable to that in vivo were identified. Results The monolayers formed organoids or colonoids when placed in standard Matrigel culture. As with the colonoids, the monolayers exhibited compartmentalization of proliferative and differentiated cells, with proliferative cells located near the peripheral edges of growing monolayers and differentiated cells predominated in the central regions. Screening of 77 dietary compounds and metabolites revealed altered proliferation or differentiation of the murine colonic epithelium. When exposed to a subset of the compound library, murine organoids exhibited similar responses to that of the monolayer but with differences that were likely attributable to the inaccessible organoid lumen. The response of the human primary epithelium to a compound subset was distinct from that of both the murine primary epithelium and human tumor cells. Conclusions This study demonstrates that a self-renewing 2-D murine and human monolayer derived from primary cells can serve as a physiologically relevant assay system for study of stem cell renewal and differentiation and for compound screening. The platform holds transformative potential for personalized and precision medicine and can be applied to emerging areas of disease modeling and microbiome studies.