Yann Sakref

All Publications

• Empowering surgeons with integrated synthetic data: solutions for mastering complex clinical scenarios. NPJ digital medicine Sakref, Y., Seenivasan, L., Ding, H., Iyer, R., Venkatesh, D. K., Speidel, S., Unberath, M., Jopling, J. K., Knowlton, L. M. 2026

  Abstract

  Synthetic data generation across domains can bridge gaps between visual training, skill development, and personalized surgical planning, ultimately transforming how surgeons and artificial intelligence (AI) systems prepare for the complexities of the operating room. In this Perspective, we explore applications of synthetic data to advance surgical education and AI across three key areas: visual data synthesis for training surgeons and AI systems, surgical simulation for skill development and robotics, and digital twins for patient-specific surgical planning and guidance. These domains have largely remained siloed, but their integration has the potential to transform surgical training and AI development across the entire surgical workflow. To fully realize this potential, synthetic data must extend beyond routine surgical events to model atypical anatomy and intraoperative complications-the high-stakes clinical scenarios where enhanced training and AI support are most critical.

  View details for DOI 10.1038/s41746-026-02660-z

  View details for PubMedID 42062460

• Design principles, growth laws, and competition of minimal autocatalysts COMMUNICATIONS CHEMISTRY Sakref, Y., Rivoire, O. 2024; 7 (1): 239

  Abstract

  The difficulty of designing simple autocatalysts that grow exponentially in the absence of enzymes, external drives or ingenious internal mechanisms severely constrains scenarios for the emergence of evolution by natural selection in chemical and physical systems. Here, we systematically analyze these difficulties in the simplest and most generic autocatalyst: a dimeric molecule that duplicates by templated ligation. We show that despite its simplicity, such an autocatalyst can achieve exponential growth autonomously. We also show, however, that it is possible to design as simple sub-exponential autocatalysts that have an advantage over exponential autocatalysts when competing for a common resource. We reach these conclusions by developing a theoretical framework based on kinetic barrier diagrams. Besides challenging commonly accepted assumptions in the field of the origin of life, our results provide a blueprint for the experimental realization of elementary autocatalysts exhibiting a form of natural selection, whether on a molecular or colloidal scale.

  View details for DOI 10.1038/s42004-024-01250-y

  View details for Web of Science ID 001339927100001

  View details for PubMedID 39433950

  View details for PubMedCentralID PMC11494078

• On the exclusion of exponential autocatalysts by sub-exponential autocatalysts JOURNAL OF THEORETICAL BIOLOGY Sakref, Y., Rivoire, O. 2024; 579: 111714

  Abstract

  Selection among autocatalytic species fundamentally depends on their growth law: exponential species, whose number of copies grows exponentially, are mutually exclusive, while sub-exponential ones, whose number of copies grows polynomially, can coexist. Here we consider competitions between autocatalytic species with different growth laws and make the simple yet counterintuitive observation that sub-exponential species can exclude exponential ones while the reverse is, in principle, impossible. This observation has implications for scenarios pertaining to the emergence of natural selection.

  View details for DOI 10.1016/j.jtbi.2023.111714

  View details for Web of Science ID 001142698700001

  View details for PubMedID 38128753

• On Kinetic Constraints That Catalysis Imposes on Elementary Processes JOURNAL OF PHYSICAL CHEMISTRY B Sakref, Y., Munoz-Basagoitii, M., Zeravcic, Z., Rivoire, O. 2023; 127 (51): 10950-10959

  Abstract

  Catalysis, the acceleration of product formation by a substance that is left unchanged, typically results from multiple elementary processes, including diffusion of the reactants toward the catalyst, chemical steps, and release of the products. While efforts to design catalysts are often focused on accelerating the chemical reaction on the catalyst, catalysis is a global property of the catalytic cycle that involves all processes. These are controlled by both intrinsic parameters such as the composition and shape of the catalyst and extrinsic parameters such as the concentration of the chemical species at play. We examine here the conditions that catalysis imposes on the different steps of a reaction cycle and the respective role of intrinsic and extrinsic parameters of the system on the emergence of catalysis by using an approach based on first-passage times. We illustrate this approach for various decompositions of a catalytic cycle into elementary steps, including non-Markovian decompositions, which are useful when the presence and nature of intermediate states are a priori unknown. Our examples cover different types of reactions and clarify the constraints on elementary steps and the impact of species concentrations on catalysis.

  View details for DOI 10.1021/acs.jpcb.3c04627

  View details for Web of Science ID 001134068000001

  View details for PubMedID 38091487