An official website of the United States government
Summary Reversible transitions between epithelial and mesenchymal cell states are a crucial form of epithelial plasticity for development and disease progression. Recent experimental data and mechanistic models showed multiple intermediate epithelial–mesenchymal transition (EMT) states as well as trajectories of EMT underpinned by complex gene regulatory networks. In this review, we summarize recent progress in quantifying EMT and characterizing EMT paths with computational methods and quantitative experiments including omics‐level measurements. We provide perspectives on how these studies can help relating fundamental cell biology to physiological and pathological outcomes of EMT.
more »
« less
This content will become publicly available on April 24, 2026
Exploring reaction dynamics involving post-transition state bifurcations based on quantum mechanical ambimodal transition states
Abstract Computational methods for predicting product ratios in dynamically controlled reactions with shallow intermediates or bifurcating pathways after an ambimodal transition state are reviewed and benchmarked. The range of methods includes molecular dynamics simulations, machine learning-based models and recent advancements in correlational methods, all of which rely on quantum mechanical computations. Together, these approaches form a computational toolbox that enhances the efficiency and effectiveness of exploring reaction selectivity influenced by dynamic effects.
more »
« less
- Award ID(s):
- 2153972
- PAR ID:
- 10628058
- Publisher / Repository:
- De Gruyter Brill
- Date Published:
- Journal Name:
- Pure and Applied Chemistry
- ISSN:
- 0033-4545
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
-
Abstract Transition metal dichalcogenides (TMDs), especially in two-dimensional (2D) form, exhibit many properties desirable for device applications. However, device performance can be hindered by the presence of defects. Here, we combine state of the art experimental and computational approaches to determine formation energies and charge transition levels of defects in bulk and 2D MX2(M = Mo or W; X = S, Se, or Te). We perform deep level transient spectroscopy (DLTS) measurements of bulk TMDs. Simultaneously, we calculate formation energies and defect levels of all native point defects, which enable identification of levels observed in DLTS and extend our calculations to vacancies in 2D TMDs, for which DLTS is challenging. We find that reduction of dimensionality of TMDs to 2D has a significant impact on defect properties. This finding may explain differences in optical properties of 2D TMDs synthesized with different methods and lays foundation for future developments of more efficient TMD-based devices.more » « less
-
Abstract ObjectivesWe estimate adult age frequencies from Unar 1 and Unar 2, two late Umm an‐Nar (2400–2100 BCE) tombs in the modern‐day Emirate of Ras al‐Khaimah, United Arab Emirates. These collective tombs each contained hundreds of skeletons in commingled, fragmented, and variably cremated states. Previous studies placed the vast majority of this mortuary community in a generalized “adult” category, as have most analyses of similar tombs from this period. We sought to test how adult age estimation methods compare in identifying young, middle, and old‐age individuals in commingled assemblages. Materials and MethodsWe employed Transition Analysis 3 (TA3) and traditional age estimation methods to generate adult age frequencies for each tomb. We compared these frequencies between tomb contexts as well as by method. ResultsUnar 1 and Unar 2 had similar adult age frequencies within each method, but TA3 age frequencies included significantly more middle and older adult individuals than those generated by traditional methods. DiscussionThese results support findings of earlier iterations of transition analysis in regard to sensitivity in old adult age estimation, compared with traditional methods. Our findings indicate a potential use of TA3 in reconstructing age frequencies and mortality profiles in commingled skeletal assemblages. Increasing our understanding of everyday life in the distant past necessitates better understandings of adult age, and here, we illustrate how age estimation method choice significantly changes bioarchaeological interpretations of aging in Bronze Age Arabia. Research HighlightsAdult age estimation using TA3 revealed significantly more middle and older adults than traditional methods in two commingled tombs.Similar mean maximum likelihood point estimates by side and across skeletal elements were found between tombs.more » « less
-
Predicting rare DNA conformations via dynamical graphical models: a case study of the B→A transitionAbstract DNA exhibits local conformational preferences that affect its ability to adopt biologically relevant conformations, such as those required for binding proteins. Traditional methods, like Markov state models and molecular dynamics (MD) simulations, have advanced our understanding but often struggle to capture these rare conformational states due to high computational demands. Here, we introduce a novel AI framework based on dynamical graphical models (DGMs), a generative machine learning approach trained on equilibrium MD data, to predict DNA conformational transitions that are never seen in the MD ensembles. By leveraging local DNA interactions, DGMs generate a comprehensive transition matrix that captures both thermodynamic and kinetic properties of unsampled states, enabling accurate predictions of rare global conformations without the need for extensive sampling. Applying this model to the B→A transition, we demonstrate that DGMs can efficiently predict sequence-dependent A-DNA preferences, achieving results that align closely with replica exchange umbrella sampling simulations. DGMs provide new insights into DNA sequence–structure relationships, paving the way for applications in DNA sequence design and optimization.more » « less
-
Methods for computing core-level ionization energies using self-consistent field (SCF) calculations are evaluated and benchmarked. These include a “full core hole” (or “ΔSCF”) approach that fully accounts for orbital relaxation upon ionization, but also methods based on Slater’s transition concept in which the binding energy is estimated from an orbital energy level that is obtained from a fractional-occupancy SCF calculation. A generalization that uses two different fractional-occupancy SCF calculations is also considered. The best of the Slater-type methods afford mean errors of 0.3–0.4 eV with respect to experiment for a dataset of K-shell ionization energies, a level of accuracy that is competitive with more expensive many-body techniques. An empirical shifting procedure with one adjustable parameter reduces the average error below 0.2 eV. This shifted Slater transition method is a simple and practical way to compute core-level binding energies using only initial-state Kohn–Sham eigenvalues. It requires no more computational effort than ΔSCF and may be especially useful for simulating transient x-ray experiments where core-level spectroscopy is used to probe an excited electronic state, for which the ΔSCF approach requires a tedious state-by-state calculation of the spectrum. As an example, we use Slater-type methods to model x-ray emission spectroscopy.more » « less
