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Biphenyl-capped phosphopeptides instruct cell aggregation into spheroids, with minimal effective concentrations below 10 μM. Key factors driving morphogenesis include the self-assembly ability and dynamic shapeshifting of the peptide assemblies. 

Conventional rendering techniques are primarily designed and optimized for single-frame rendering. In practical applications, such as scene editing and animation rendering, users frequently encounter scenes where only a small portion is modified between consecutive frames. In this paper, we develop a novel approach to incremental re-rendering of scenes with dynamic objects, where only a small part of a scene moves from one frame to the next. We formulate the difference (or residual) in the image between two frames as a (correlated) light-transport integral which we call the residual path integral. Efficient numerical solution of this integral then involves (1) devising importance sampling strategies to focus on paths with non-zero residual-transport contributions and (2) choosing appropriate mappings between the native path spaces of the two frames. We introduce a set of path importance sampling strategies that trace from the moving object(s) which are the sources of residual energy. We explore path mapping strategies that generalize those from gradient-domain path tracing to our importance sampling techniques specially for dynamic scenes. Additionally, our formulation can be applied to material editing as a simpler special case. We demonstrate speed-ups over previous correlated sampling of path differences and over rendering the new frame independently. Our formulation brings new insights into the re-rendering problem and paves the way for devising new types of sampling techniques and path mappings with different trade-offs. 

We propose a set of techniques to efficiently importance sample the derivatives of a wide range of Bidirectional Reflectance Distribution Function (BRDF) models. In differentiable rendering, BRDFs are replaced by their differential BRDF counterparts, which are real-valued and can have negative values. This leads to a new source of variance arising from their change in sign. Real-valued functions cannot be perfectly importance sampled by a positive-valued PDF, and the direct application of BRDF sampling leads to high variance. Previous attempts at antithetic sampling only addressed the derivative with the roughness parameter of isotropic microfacet BRDFs. Our work generalizes BRDF derivative sampling to anisotropic microfacet models, mixture BRDFs, Oren-Nayar, Hanrahan-Krueger, among other analytic BRDFs. Our method first decomposes the real-valued differential BRDF into a sum of single-signed functions, eliminating variance from a change in sign. Next, we importance sample each of the resulting single-signed functions separately. The first decomposition, positivization, partitions the real-valued function based on its sign, and is effective at variance reduction when applicable. However, it requires analytic knowledge of the roots of the differential BRDF, and for it to be analytically integrable too. Our key insight is that the single-signed functions can have overlapping support, which significantly broadens the ways we can decompose a real-valued function. Our product and mixture decompositions exploit this property, and they allow us to support several BRDF derivatives that positivization could not handle. For a wide variety of BRDF derivatives, our method significantly reduces the variance (up to 58× in some cases) at equal computation cost and enables better recovery of spatially varying textures through gradient-descent-based inverse rendering. 

Abstract Rapid cellular uptake of synthetic molecules remains a challenge, and the motif frequently employed to generate prodrugs, succinic ester, unfortunately lowers the efficacy of the desired drugs due to their slow ester hydrolysis and low cell entry. Here we show that succinic ester‐containing diglycine drastically boosts the cellular uptake of supramolecular assemblies or prodrugs. Specifically, autohydrolysis of the diglycine‐activated succinic esters turns the nanofibers of the conjugates of succinic ester and self‐assembling motif into nanoparticles for fast cellular uptake. The autohydrolysis of diglycine‐activated succinic esters and drug conjugates also restores the efficacy of the drugs. 2D nuclear magnetic resonance (NMR) suggests that a “U‐turn” of diglycine favors intramolecular hydrolysis of diglycine‐activated succinic esters to promote autohydrolysis. As an example of rapid autohydrolysis of diglycine‐activated succinic esters for instant cellular uptake, this work illustrates a nonenzymatic bond cleavage approach to develop effective therapeutics for intracellular targeting.