Dynamics of RNA Polymerase in E. Coli determined by Raster Image Correlation Spectroscopy and Number and Brightness Analysis

RNA Polymerase (RNAP) is fundamental in all living organisms, as it transcribes DNA into RNA molecules. Visualizing the molecular copy number and dynamics of RNAP in single living cells is difficult using conventional fluorescence microscopy. We use two techniques based on Fluorescence Correlation Spectroscopy (FCS) to determine the molecular copy number and mobility of RNAP in single living cells of Escheri coli. Raster Image Correlation Spectroscopy (RICS) is an image based FCS technique that measures the average molecular diffusion at every point in an image. This is useful in living cells for characterizing molecular diffusivity in addition to DNA, membrane or cytoskeletal binding(Digman et al. 2005; Digman & Gratton 2009). Number and Brightness Analysis (N&B) is an image based FCS technique which measures molecular concentration and molecular brightness at every point in an image. This is useful in living cells for characterizing expression level and oligomerization state (Digman et al. 2008). We found that RNAP is expressed in copy numbers of ~ 1000 molecules per cell and diffuses at approximately 1µm2/s. We have established the utility of RICS and N&B for monitoring RNAP in E. coli, and intend to measure RNA-protein interactions between RNAP and the sigma 70 subunit using RNA Mango labelling of sigma 70

Grain boundary network plasticity: reduced-order modeling of deformation-driven microstructure evolution

Microstructural evolution in structural materials is known to occur in response to mechanical loading and can often accommodate substantial plastic deformation through the coupled motion of grain boundaries (GBs). This can produce desirable behavior, such as increased ductility, or undesirable behavior such as mechanically-induced coarsening. In this work a novel, multiscale model is developed for capturing the combined effect of plasticity mediated by multiple GBs simultaneously. This model is referred to as "grain boundary network plasticity." The mathematical framework of graph theory is used to describe the microstructure connectedness, and the evolution of microstructure is represented as volume flow along the graph. By using the principle of minimum dissipation potential, which has previously been applied to grain boundary migration, a set of evolution equations are developed that transfer volume and eigendeformation along the graph edges in a physically consistent way. It is shown that higher-order geometric effects, such as the pinning effect of triple points, may be accounted for through the incorporation of a geometric hardening that causes geometry-induced GB stagnation. The result is a computationally efficient reduced order model that can be used to simulate the initial motion of grain boundaries in a polycrystal with parameters informed by atomistic simulations. The effectiveness of the model is demonstrated through comparison to multiple bicrystal atomistic simulations, as well as a select number of GB engineered and non-GB engineered data obtained from the literature. The effect of the network of shear-coupling grain boundaries is demonstrated through mechanical response tests and by examining the yield surfaces

Humanity's Last Exam

Benchmarks are important tools for tracking the rapid advancements in large language model (LLM) capabilities. However, benchmarks are not keeping pace in difficulty: LLMs now achieve over 90\% accuracy on popular benchmarks like MMLU, limiting informed measurement of state-of-the-art LLM capabilities. In response, we introduce Humanity's Last Exam (HLE), a multi-modal benchmark at the frontier of human knowledge, designed to be the final closed-ended academic benchmark of its kind with broad subject coverage. HLE consists of 3,000 questions across dozens of subjects, including mathematics, humanities, and the natural sciences. HLE is developed globally by subject-matter experts and consists of multiple-choice and short-answer questions suitable for automated grading. Each question has a known solution that is unambiguous and easily verifiable, but cannot be quickly answered via internet retrieval. State-of-the-art LLMs demonstrate low accuracy and calibration on HLE, highlighting a significant gap between current LLM capabilities and the expert human frontier on closed-ended academic questions. To inform research and policymaking upon a clear understanding of model capabilities, we publicly release HLE at https://lastexam.ai

Humanity's Last Exam

Benchmarks are important tools for tracking the rapid advancements in large language model (LLM) capabilities. However, benchmarks are not keeping pace in difficulty: LLMs now achieve over 90\% accuracy on popular benchmarks like MMLU, limiting informed measurement of state-of-the-art LLM capabilities. In response, we introduce Humanity's Last Exam (HLE), a multi-modal benchmark at the frontier of human knowledge, designed to be the final closed-ended academic benchmark of its kind with broad subject coverage. HLE consists of 3,000 questions across dozens of subjects, including mathematics, humanities, and the natural sciences. HLE is developed globally by subject-matter experts and consists of multiple-choice and short-answer questions suitable for automated grading. Each question has a known solution that is unambiguous and easily verifiable, but cannot be quickly answered via internet retrieval. State-of-the-art LLMs demonstrate low accuracy and calibration on HLE, highlighting a significant gap between current LLM capabilities and the expert human frontier on closed-ended academic questions. To inform research and policymaking upon a clear understanding of model capabilities, we publicly release HLE at https://lastexam.ai

Grain boundary network plasticity: reduced-order modeling of deformation-driven microstructure evolution

Microstructural evolution in structural materials is known to occur in response to mechanical loading and can often accommodate substantial plastic deformation through the coupled motion of grain boundaries (GBs). This can produce desirable behavior, such as increased ductility, or undesirable behavior such as mechanically-induced coarsening. In this work a novel, multiscale model is developed for capturing the combined effect of plasticity mediated by multiple GBs simultaneously. This model is referred to as "grain boundary network plasticity." The mathematical framework of graph theory is used to describe the microstructure connectedness, and the evolution of microstructure is represented as volume flow along the graph. By using the principle of minimum dissipation potential, which has previously been applied to grain boundary migration, a set of evolution equations are developed that transfer volume and eigendeformation along the graph edges in a physically consistent way. It is shown that higher-order geometric effects, such as the pinning effect of triple points, may be accounted for through the incorporation of a geometric hardening that causes geometry-induced GB stagnation. The result is a computationally efficient reduced order model that can be used to simulate the initial motion of grain boundaries in a polycrystal with parameters informed by atomistic simulations. The effectiveness of the model is demonstrated through comparison to multiple bicrystal atomistic simulations, as well as a select number of GB engineered and non-GB engineered data obtained from the literature. The effect of the network of shear-coupling grain boundaries is demonstrated through mechanical response tests and by examining the yield surfaces.This preprint is available as Bugas, Daniel, and Brandon Runnels. "Grain boundary network plasticity: reduced-order modeling of deformation-driven microstructure evolution." arXiv preprint arXiv:2306.01712 (2023). https://doi.org/10.48550/arXiv.2306.01712 Published as Bugas, Daniel, and Brandon Runnels. "Grain boundary network plasticity: Reduced-order modeling of deformation-driven shear-coupled microstructure evolution." Journal of the Mechanics and Physics of Solids 184 (2024): 105541. doi: https://doi.org/10.1016/j.jmps.2024.105541

Measuring the Viscoelasticity of the Extracellular Matrix by Fluorescence Correlation Spectroscopy and Orbital Tracking Microrheology

Mechanical properties of the extracellular matrix affect the growth of tissue, the integrity of blood vessels and cancer metastasis. There are currently very few methods that can measure mechanical properties of tissues at molecular length scales in living cells, tissues and organisms. We propose and evaluate two novel techniques based on Fluorescence Correlation Spectroscopy and 3D Orbital Tracking to measure the micromechanical properties of collagen gels, glycerol solutions and in living cells. We find that using simple models of entangled polymer gels and passive single point microrheology we can characterize the complex viscoelastic modulus of an entangled collagen gel. In the future we intend to apply this technique in living biomasses and the vasculature of the Sea Squirt, Botryllus Schlosseri

Humanity's Last Exam

International audienceBenchmarks are important tools for tracking the rapid advancements in large language model (LLM) capabilities. However, benchmarks are not keeping pace in difficulty: LLMs now achieve over 90% accuracy on popular benchmarks like MMLU, limiting informed measurement of state-of-the-art LLM capabilities. In response, we introduce Humanity's Last Exam (HLE), a multi-modal benchmark at the frontier of human knowledge, designed to be the final closed-ended academic benchmark of its kind with broad subject coverage. HLE consists of 3,000 questions across dozens of subjects, including mathematics, humanities, and the natural sciences. HLE is developed globally by subject-matter experts and consists of multiple-choice and short-answer questions suitable for automated grading. Each question has a known solution that is unambiguous and easily verifiable, but cannot be quickly answered via internet retrieval. State-of-the-art LLMs demonstrate low accuracy and calibration on HLE, highlighting a significant gap between current LLM capabilities and the expert human frontier on closed-ended academic questions. To inform research and policymaking upon a clear understanding of model capabilities, we publicly release HLE at https://lastexam.ai

Humanity's Last Exam

International audienceBenchmarks are important tools for tracking the rapid advancements in large language model (LLM) capabilities. However, benchmarks are not keeping pace in difficulty: LLMs now achieve over 90% accuracy on popular benchmarks like MMLU, limiting informed measurement of state-of-the-art LLM capabilities. In response, we introduce Humanity's Last Exam (HLE), a multi-modal benchmark at the frontier of human knowledge, designed to be the final closed-ended academic benchmark of its kind with broad subject coverage. HLE consists of 3,000 questions across dozens of subjects, including mathematics, humanities, and the natural sciences. HLE is developed globally by subject-matter experts and consists of multiple-choice and short-answer questions suitable for automated grading. Each question has a known solution that is unambiguous and easily verifiable, but cannot be quickly answered via internet retrieval. State-of-the-art LLMs demonstrate low accuracy and calibration on HLE, highlighting a significant gap between current LLM capabilities and the expert human frontier on closed-ended academic questions. To inform research and policymaking upon a clear understanding of model capabilities, we publicly release HLE at https://lastexam.ai