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1. Computational analysis of photophysical changes of oligomeric P-phenylene ethynylene sensors upon binding to amyloid-β aggregates

   https://doi.org/10.1016/j.bpj.2023.11.3314  

   Fetrow, Benjamin P; Whitten, David G; Bricker, William P; Chi, Eva Y (February 2024, Biophysical Journal)

   Alzheimer's disease (AD) is an uncurable progressive neurodegenerative disease and is the most common cause of dementia. As current understanding of the disease suggests damage begins accumulating a decade before diagnosable symptoms, preventative treatment strategies will require screenings during the asymptomatic state. The high cost of PET and MRI scans make them challenging for the throughput necessary to screen the large population of 65+ individuals most at risk of developing AD. An alternative is near-IR fluorescence imaging, which is less costly and less invasive. We have reported a small-molecule fluorescent sensor able to selectively detect and oxidize the amyloid-β oligomers and fibrils implicated as pathogenic agents in the early development of AD. In this study, we use computational modeling to gain insights into what changes in sensor-protein binding lead to both turn-on fluorescence and turn-on singlet oxygen generation. We utilize molecular dynamics to model sensor behavior in multiple environments, including sensor complexation and protein binding. Both density functional theory (DFT) and time-dependent DFT ab initio calculations are used to monitor intra- and inter-molecular photophysical properties of the molecule. Results show that the structural dynamics of the sensor depends on its binding environment and that the structural changes upon binding are correlated with changes in sensor photophysical characteristics. This investigation contributes to a better understanding of how molecular design gives rise to desirable properties for molecular sensing, leading to improved ability to rationally design near-IR fluorescent sensors for AD. 

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2. Probing atomic physics at ultrahigh pressure using laser-driven implosions

   https://doi.org/10.1038/s41467-022-34618-6  

   Hu, S. X.; Bishel, David T.; Chin, David A.; Nilson, Philip M.; Karasiev, Valentin V.; Golovkin, Igor E.; Gu, Ming; Hansen, Stephanie B.; Mihaylov, Deyan I.; Shaffer, Nathaniel R.; et al (December 2022, Nature Communications)

   Abstract Spectroscopic measurements of dense plasmas at billions of atmospheres provide tests to our fundamental understanding of how matter behaves at extreme conditions. Developing reliable atomic physics models at these conditions, benchmarked by experimental data, is crucial to an improved understanding of radiation transport in both stars and inertial fusion targets. However, detailed spectroscopic measurements at these conditions are rare, and traditional collisional-radiative equilibrium models, based on isolated-atom calculations and ad hoc continuum lowering models, have proved questionable at and beyond solid density. Here we report time-integrated and time-resolved x-ray spectroscopy measurements at several billion atmospheres using laser-driven implosions of Cu-doped targets. We use the imploding shell and its hot core at stagnation to probe the spectral changes of Cu-doped witness layer. These measurements indicate the necessity and viability of modeling dense plasmas with self-consistent methods like density-functional theory, which impact the accuracy of radiation transport simulations used to describe stellar evolution and the design of inertial fusion targets. 

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3. Pitfalls in the n-mode representation of vibrational potentials

   https://doi.org/10.1063/5.0176612  

   Yang, Emily L; Talbot, Justin J; Spencer, Ryan J; Steele, Ryan P (November 2023, The Journal of Chemical Physics)

   Simulations of anharmonic vibrational motion rely on computationally expedient representations of the governing potential energy surface. The n-mode representation (n-MR)—effectively a many-body expansion in the space of molecular vibrations—is a general and efficient approach that is often used for this purpose in vibrational self-consistent field (VSCF) calculations and correlated analogues thereof. In the present analysis, a lack of convergence in many VSCF calculations is shown to originate from negative and unbound potentials at truncated orders of the n-MR expansion. For cases of strong anharmonic coupling between modes, the n-MR can both dip below the true global minimum of the potential surface and lead to effective single-mode potentials in VSCF that do not correspond to bound vibrational problems, even for bound total potentials. The present analysis serves mainly as a pathology report of this issue. Furthermore, this insight into the origin of VSCF non-convergence provides a simple, albeit ad hoc, route to correct the problem by “painting in” the full representation of groups of modes that exhibit these negative potentials at little additional computational cost. Somewhat surprisingly, this approach also reasonably approximates the results of the next-higher n-MR order and identifies groups of modes with particularly strong coupling. The method is shown to identify and correct problematic triples of modes—and restore SCF convergence—in two-mode representations of challenging test systems, including the water dimer and trimer, as well as protonated tropine. 

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4. PyCDFT : A Python package for constrained density functional theory

   https://doi.org/10.1002/jcc.26354  

   Ma, He; Wang, Wennie; Kim, Siyoung; Cheng, Man‐Hin; Govoni, Marco; Galli, Giulia (June 2020, Journal of Computational Chemistry)

   Abstract We present PyCDFT, a Python package to compute diabatic states using constrained density functional theory (CDFT). PyCDFT provides an object‐oriented, customizable implementation of CDFT, and allows for both single‐point self‐consistent‐field calculations and geometry optimizations. PyCDFT is designed to interface with existing density functional theory (DFT) codes to perform CDFT calculations where constraint potentials are added to the Kohn–Sham Hamiltonian. Here, we demonstrate the use of PyCDFT by performing calculations with a massively parallel first‐principles molecular dynamics code, Qbox, and we benchmark its accuracy by computing the electronic coupling between diabatic states for a set of organic molecules. We show that PyCDFT yields results in agreement with existing implementations and is a robust and flexible package for performing CDFT calculations. The program is available athttps://dx.doi.org/10.5281/zenodo.3821097. 

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5. Divisible E-Cash for Billing in Private Ad Retargeting

   https://doi.org/10.56553/popets-2024-0104  

   Liao, Kevin; Corrigan-Gibbs, Henry; Boneh, Dan (October 2024, Proceedings on Privacy Enhancing Technologies)

   This paper presents new techniques for private billing in systems for privacy-preserving online advertising. In particular, we show how an ad exchange can use an e-cash scheme to bill advertisers for ad impressions without learning which client saw which ad: The exchange issues electronic coins to advertisers, advertisers pay publishers (via clients) for ad impressions, and publishers unlinkably redeem coins with the exchange. To implement this proposal, we design a new divisible e-cash scheme that uses modern zero-knowledge proofs to reduce the ad exchange's computational costs by roughly 250x compared to the previous state-of-the-art. With our new e-cash scheme, our private-billing infrastructure adds little overhead to existing private ad-retargeting systems: less than 63 ms of latency, negligible client computation, less than 3.2 KB of client communication, and a combined server operating cost (advertisers, publishers, and exchange) of less than 1% of ad spend, an over 5x savings compared to the previous state-of-the-art. 

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