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1. ADM mass for C 0 C^{0} metrics and distortion under Ricci–DeTurck flow

   https://doi.org/10.1515/crelle-2023-0085  

   Burkhardt-Guim, Paula (December 2023, Journal für die reine und angewandte Mathematik (Crelles Journal))

   Abstract We show that there exists a quantity, depending only on $C^0$C^{0}data of a Riemannian metric, that agrees with the usual ADM mass at infinity whenever the ADM mass exists, but has a well-defined limit at infinity for any continuous Riemannian metric that is asymptotically flat in the $C^0$C^{0}sense and has nonnegative scalar curvature in the sense of Ricci flow.Moreover, the $C^0$C^{0}mass at infinity is independent of choice of $C^0$C^{0}-asymptotically flat coordinate chart, and the $C^0$C^{0}local mass has controlled distortion under Ricci–DeTurck flow when coupled with a suitably evolving test function. 

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2. An Immobilized-Dirhodium Hollow-Fiber Flow Reactor for Scalable and Sustainable C−H Functionalization in Continuous Flow

   https://doi.org/10.1002/anie.201805528  

   Yoo, Chun-Jae; Rackl, Daniel; Liu, Wenbin; Hoyt, Caroline B.; Pimentel, Brian; Lively, Ryan P.; Davies, Huw M.; Jones, Christopher W. (August 2018, Angewandte Chemie International Edition)
3. π-Bond Dissociation Energies: C–C, C–N, and C–O

   https://doi.org/10.1021/acs.joc.4c01925  

   Kass, Steven R (October 2024, The Journal of Organic Chemistry)
4. HiCForecast: dynamic network optical flow estimation algorithm for spatiotemporal Hi-C data forecasting

   https://doi.org/10.1093/bioinformatics/btaf030  

   Pinchuk, Dmitry; Chowdhury, H_M_A_Mohit; Pandeya, Abhishek; Oluwadare, Oluwatosin; Alkan, ed., Can (January 2025, Bioinformatics)

   Abstract MotivationThe exploration of the 3D organization of DNA within the nucleus in relation to various stages of cellular development has led to experiments generating spatiotemporal Hi-C data. However, there is limited spatiotemporal Hi-C data for many organisms, impeding the study of 3D genome dynamics. To overcome this limitation and advance our understanding of genome organization, it is crucial to develop methods for forecasting Hi-C data at future time points from existing timeseries Hi-C data. ResultIn this work, we designed a novel framework named HiCForecast, adopting a dynamic voxel flow algorithm to forecast future spatiotemporal Hi-C data. We evaluated how well our method generalizes forecasting data across different species and systems, ensuring performance in homogeneous, heterogeneous, and general contexts. Using both computational and biological evaluation metrics, our results show that HiCForecast outperforms the current state-of-the-art algorithm, emerging as an efficient and powerful tool for forecasting future spatiotemporal Hi-C datasets. Availability and implementationHiCForecast is publicly available at https://github.com/OluwadareLab/HiCForecast. 

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5. Automated Iterative N─C and C─C Bond Formation

   https://doi.org/10.1002/anie.202509974  

   Tyrikos‐Ergas, Theodore; Agiakloglou, Sevasti; LaPorte, Antonio J; Wang, Wesley; Chan, Chieh‐Kai; Wells, Clare E; Rakowski, Christopher K; Hammond, Rachel I; Qiu, Jia; Raymond, Jonathan D; et al (August 2025, Angewandte Chemie International Edition)

   Small molecule solutions to many contemporary societal challenges await discovery, but the artisanal and manual process via which this class of chemical matter is typically accessed limits the discovery of new functions. Automated assembly of (N‐methyl iminodiacetic acid) MIDA or (tetramethyl N‐methyl iminodiacetic acid) TIDA boronate building blocks via iterative C─C bond formation, an approach we call “block chemistry”, alternatively enables generalized and automated preparation of many different types of small molecules in a modular fashion. But in its current form, this engine cannot also leverage nitrogen atoms as iteration handles. Here, we disclose a new iteration‐enabling group, CbzT (p‐TIDA boronate‐substituted carboxybenzyl), that reversibly attenuates the reactivity of nitrogen atoms and enables generalized catch‐and‐release purification. CbzT is leveraged to achieve the automated modular synthesis of Imatinib (Gleevec), an archetypical clinically approved kinase inhibitor, in which building blocks are iteratively linked by both N─C and C─C bonds. This work substantially expands the types of small molecules that can be iteratively assembled in an automated modular fashion. It also advances the concept of intentionally developing chemistry that machines can do. 

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