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Hydrogels cross-linked by dynamic covalent chemistry (DCC) are stiff and remodelable, making them ideal biomimetics for tissue engineering applications. Due to the reversibility of DCC cross-links, the opportunity exists to transiently control hydrogel network formation through the use of small molecule competitors. Specifically, we incorporate low molecular weight competitors that reversibly disrupt the formation of hydrazone cross-links as they diffuse through a recombinant hydrogel. Using complementary experimental, computational, and theoretical polymer physics approaches, we present a family of competitors that predictably alter hydrogel gelation time and mechanics. By changing the competitor chemistry, we connect key reaction parameters (forward and reverse reactions rates and thermodynamic equilibrium constants) to the delayed onset of a percolated network, increased hydrogel gelation time, and transient control of hydrogel stiffness. Using human intestinal organoids as a model system, we demonstrate the ability to tune gelation kinetics of a recombinant hydrogel for uniform encapsulation of individual, patient-derived stem cells and their proliferation into three-dimensional structures. Taken together, our data establish a validated framework to relate molecular-level parameters of transient competitors to predicted macromolecular-network properties. As interest in biomimetic, DCC-cross-linked hydrogels continues to grow, these results will enable the rationale design of bespoke, dynamic biomaterials for tissue engineering. 

This work probed the thermal “switchability” from ethylene coordination/insertion to controlled radical polymerization of methyl acrylate (MA) for Brookhart-type α-diimine PdII catalysts. The investigation focused on the extremely bulky 2,6-bis(3,5-dimethylphenyl)-4-methylphenyl (Xyl4Ph) α-diimine N-substituents to probe reversible PdII–C bond activation in the MA-quenched Pd-capped PE intermediate and reversible trapping during radical MA polymerization. The substituent steric effect on the relative stability of various [PE–MA–PdII(ArN═CMeCMe═NAr)]+ chain-end structures and on the bond dissociation-free energy (BDFE) for the homolytic PdII–C bond cleavage has been assessed by DFT calculations at the full quantum mechanics (QM) and QM/molecular mechanics (QM/MM) methods. The structures comprise ester-chelated forms with the Pd atom bonded to the α, β, and γ C atoms as a result of 2,1 MA insertion into the PE–Pd bond and of subsequent chain walking, as well as related monodentate (ring-opened) forms resulting from the addition of MA or acetonitrile. The opened Cα-bonded form is electronically favored for smaller N-substituents, including 2,6-diisopropylphenyl (Dipp), particularly when MeCN is added, but the open Cγ-bonded form is preferred for the extremely bulky system with Ar = Xyl4Ph. The Pdα–C bond is the weakest one to cleave, with the BDFE decreasing as the Ar steric bulk is increased (31.8, 25.8, and 12.6 kcal mol–1 for Ph, Dipp, and Xyl4Ph, respectively). However, experimental investigations on the [PE–MA–PdII(ArN═CMeCMe═NAr)]+ (Ar = Xyl4Ph) macroinitiator do not show any evidence of radical formation under thermal activation conditions, while photolytic activation produces both TEMPO-trapped (TEMPO = 2,2,6,6-tetramethylpiperidinyloxy) and unsaturated MA-containing PE chains. The DFT investigation has highlighted a low-energy pathway for termination of the PE–MA• radicals by disproportionation, promoted by β-H elimination/dissociation and H-atom abstraction from the PdII–H intermediate by a second radical. This phenomenon appears to be the main reason for the failure of this PdII system to control the radical polymerization of MA by the OMRP (OMRP = organometallic-mediated radical polymerization) mechanism. 

Regression test selection (RTS) speeds up regression testing by only re-running tests that might be affected by code changes. Ideal RTS safely selects all affected tests and precisely selects only affected tests. But, aiming for this ideal is often slower than re-running all tests. So, recent RTS techniques use program analysis to trade precision for speed, i.e., lower regression testing time, or even use machine learning to trade safety for speed. We seek to make recent analysis-based RTS techniques more precise, to further speed up regression testing. Independent studies suggest that these techniques reached a “performance wall” in the speed-ups that they provide. We manually inspect code changes to discover those that do not require re-running tests that are only affected by such changes. We categorize 29 kinds of changes that we found from five projects into 13 findings, 11 of which are semantics-modifying. We enhance two RTS techniques—Ekstazi and STARTS—to reason about our findings. Using 1,150 versions of 23 projects, we evaluate the impact on safety and precision of leveraging such changes. We also evaluate if our findings from a few projects can speed up regression testing in other projects. The results show that our enhancements are effective and they can generalize. On average, they result in selecting 41.7% and 31.8% fewer tests, and take 33.7% and 28.7% less time than Ekstazi and STARTS, respectively, with no loss in safety. 

We recently proposed inline tests for validating individual program statements; they allow developers to provide test inputs, expected outputs, and test oracles immediately after a target statement. But, existing code can have many target statements. So, automatic generation of inline tests is an important next step towards increasing their adoption. We propose ExLi, the first technique for automatically generating inline tests. ExLi extracts inline tests from unit tests; it first records all variable values at a target statement while executing unit tests. Then, ExLi uses those values as test inputs and test oracles in an initial set of generated inline tests. Target statements that are executed many times could have redundant initial inline tests. So, ExLi uses a novel coverage-then-mutants based reduction process to remove redundant inline tests. We implement ExLi for Java and use it to generate inline tests for 718 target statements in 31 open-source programs. ExLi reduces 17,273 initially generated inline tests to 905 inline tests. The final set of generated inline tests kills up to 25.1% more mutants on target statements than developer written and automatically generated unit tests. That is, ExLi generates inline tests that can improve the fault-detection capability of the test suites from which they are extracted.