Metabolic dysfunction occurs in many age-related neurodegenerative diseases, yet its role in disease etiology remains poorly understood. We recently discovered a potential causal link between the branched-chain amino acid transferase BCAT-1 and the neurodegenerative movement disorder Parkinson’s disease (PD). RNAi-mediated knockdown of Caenorhabditis elegans bcat-1 is known to recapitulate PD-like features, including progressive motor deficits and neurodegeneration with age, yet the underlying mechanisms have remained unknown. Using transcriptomic, metabolomic, and imaging approaches, we show here that bcat-1 knockdown increases mitochondrial respiration and induces oxidative damage in neurons through mammalian target of rapamycin-independent mechanisms. Increased mitochondrial respiration, or “mitochondrial hyperactivity,” is required for bcat-1(RNAi) neurotoxicity. Moreover, we show that post–disease-onset administration of the type 2 diabetes medication metformin reduces mitochondrial respiration to control levels and significantly improves both motor function and neuronal viability. Taken together, our findings suggest that mitochondrial hyperactivity may be an early event in the pathogenesis of PD, and that strategies aimed at reducing mitochondrial respiration may constitute a surprising new avenue for PD treatment.

A novel model is presented to study red blood cell (RBC) hemolysis at cellular level. Under high shear rates, pores form on RBC membranes through which hemoglobin (Hb) leaks out and increases free Hb content of plasma leading to hemolysis. By coupling lattice Boltzmann and spring connected network models through immersed boundary method, we estimate hemolysis of a single RBC under various shear rates. First, we use adaptive meshing to find local strain distribution and critical sites on RBC membranes, and then we apply underlying molecular dynamics simulations to evaluate damage. Our approach comprises three sub-models: defining criteria of pore formation, calculating pore size, and measuring Hb diffusive flux out of pores. Our damage model uses information of different scales to predict cellular level hemolysis. Results are compared with experimental studies and other models in literature. The developed cellular damage model can be used as a predictive tool for hydrodynamic and hematologic design optimization of blood-wetting medical devices.

Effective discovery of causal disease genes must overcome the statistical challenges of quantitative genetics studies and the practical limitations of human biology experiments. Here we developed diseaseQUEST, an integrative approach that combines data from human genome-wide disease studies with in silico network models of tissue-and cell-type-specific function in model organisms to prioritize candidates within functionally conserved processes and pathways. We used diseaseQUEST to predict candidate genes for 25 different diseases and traits, including cancer, longevity, and neurodegenerative diseases. Focusing on Parkinson's disease (PD), a diseaseQUEST-directed Caenhorhabditis elegans behavioral screen identified several candidate genes, which we experimentally verified and found to be associated with age-dependent motility defects mirroring PD clinical symptoms. Furthermore, knockdown of the top candidate gene, bcat-1, encoding a branched chain amino acid transferase, caused spasm-like 'curling' and neurodegeneration in C. elegans, paralleling decreased BCAT1 expression in PD patient brains. diseaseQUEST is modular and generalizable to other model organisms and human diseases of interest.

In this paper, we reported a new approach for particle assembly with acoustic tweezer during three-dimensional (3D) printing for the fabrication of embedded conductive wire with 3D structures. A hexagon shaped acoustic tweezer was incorporated with Digital Light Processing (DLP) based stereolithography (SLA) printer to pattern conductive lines via aligning and condensing conductive nanoparticles. The effect of filler content on electrical resistivity and pattern thickness were studied for copper, magnetite nanoparticles, and carbon nanofiber reinforced nanocomposite samples. The obtained data was later used to produce examples of conductive 3D microstructures and embedded electronic components by using the suggested method.

Abstract3D printing of composite materials offers an opportunity to combine desired properties of composite materials with flexibility of additive manufacturing in geometric shape and complexity. In this paper, shear-induced alignment of aluminum oxide nanowires during stereolithography printing was utilized to fabricate a nanowire reinforced polymer composite. To align the fibers, a lateral oscillation mechanism was implemented and combined with wall pattern printing technique to generate shear flow in both vertical and horizontal directions. A series of specimens were fabricated for testing the composite material's tensile strength. The results showed that mechanical properties of the composite were improved by reinforcement of nanofibers through shear induced alignment. The improvement of tensile strength was approximately ~28% by aligning the nanowires at 5wt% (~1.5% volume fraction) loading of aluminum oxide nanowires.