An Optimal Likelihood Free Method for Biological Model Selection

Systems biology seeks to create math models of biological systems to reduce inherent biological complexity and provide predictions for applications such as therapeutic development. However, it remains a challenge to determine which math model is correct and how to arrive optimally at the answer. We present an algorithm for automated biological model selection using mathematical models of systems biology and likelihood free inference methods. Our algorithm shows improved performance in arriving at correct models without a priori information over conventional heuristics used in experimental biology and random search. This method shows promise to accelerate biological basic science and drug discovery.Comment: 2022 International Conference on Machine Learning Workshop on Computational Biolog

Stochastic Gradient Bayesian Optimal Experimental Designs for Simulation-based Inference

Simulation-based inference (SBI) methods tackle complex scientific models with challenging inverse problems. However, SBI models often face a significant hurdle due to their non-differentiable nature, which hampers the use of gradient-based optimization techniques. Bayesian Optimal Experimental Design (BOED) is a powerful approach that aims to make the most efficient use of experimental resources for improved inferences. While stochastic gradient BOED methods have shown promising results in high-dimensional design problems, they have mostly neglected the integration of BOED with SBI due to the difficult non-differentiable property of many SBI simulators. In this work, we establish a crucial connection between ratio-based SBI inference algorithms and stochastic gradient-based variational inference by leveraging mutual information bounds. This connection allows us to extend BOED to SBI applications, enabling the simultaneous optimization of experimental designs and amortized inference functions. We demonstrate our approach on a simple linear model and offer implementation details for practitioners.Comment: Presented at ICML 2023 workshop on Differentiable Everythin

Learnable Earth Parser: Discovering 3D Prototypes in Aerial Scans

We propose an unsupervised method for parsing large 3D scans of real-world scenes into interpretable parts. Our goal is to provide a practical tool for analyzing 3D scenes with unique characteristics in the context of aerial surveying and mapping, without relying on application-specific user annotations. Our approach is based on a probabilistic reconstruction model that decomposes an input 3D point cloud into a small set of learned prototypical shapes. Our model provides an interpretable reconstruction of complex scenes and leads to relevant instance and semantic segmentations. To demonstrate the usefulness of our results, we introduce a novel dataset of seven diverse aerial LiDAR scans. We show that our method outperforms state-of-the-art unsupervised methods in terms of decomposition accuracy while remaining visually interpretable. Our method offers significant advantage over existing approaches, as it does not require any manual annotations, making it a practical and efficient tool for 3D scene analysis. Our code and dataset are available at https://imagine.enpc.fr/~loiseaur/learnable-earth-parse

Hepatocellular carcinoma surveillance, early detection and survival in a privately insured US cohort

Background/AimsSemiannual hepatocellular carcinoma (HCC) surveillance is recommended in patients with cirrhosis; however, recent studies have raised questions over its utility. We investigated the impact of surveillance on early detection and survival in a nationally representative database.MethodsWe included patients with cirrhosis and HCC from the Optum database (2001‐2015) with >6 months of follow‐up between cirrhosis and HCC diagnoses. Surveillance adherence was defined as proportion of time covered (PTC), with each 6‐month period after abdominal imaging defined as ‘covered’. To determine the association between surveillance and mortality, we compared PTC between fatal and non‐fatal HCC.ResultsOf 1001 patients with cirrhosis and HCC, 256 died with median follow‐up 30 months. Median PTC by any imaging was greater in early‐stage vs late‐stage HCC (43.6% vs 37.4%, P = .003) and non‐fatal vs fatal HCC (40.8% vs 34.3%, P = .001). In multivariable analyses, each 10% increase in PTC was associated with increased early HCC detection (OR 1.07, 95% CI 1.01‐1.12) and decreased mortality (HR 0.95; 95% CI 0.90‐1.00). On subgroup analysis, PTC by CT/MRI was associated with early tumour detection and decreased mortality; however, PTC by ultrasound was only associated with early detection but not decreased mortality. These findings were robust across sensitivity analyses.ConclusionsIn a US cohort of privately insured HCC patients, PTC by any imaging modality was associated with increased early detection and decreased mortality. Continued evaluation of HCC surveillance strategies and effectiveness is warranted.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/154974/1/liv14379_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/154974/2/liv14379.pd

The self-organization of plant microtubules inside the cell volume yields their cortical localization, stable alignment, and sensitivity to external cues.

Many cell functions rely on the ability of microtubules to self-organize as complex networks. In plants, cortical microtubules are essential to determine cell shape as they guide the deposition of cellulose microfibrils, and thus control mechanical anisotropy of the cell wall. Here we analyze how, in turn, cell shape may influence microtubule behavior. Building upon previous models that confined microtubules to the cell surface, we introduce an agent model of microtubules enclosed in a three-dimensional volume. We show that the microtubule network has spontaneous aligned configurations that could explain many experimental observations without resorting to specific regulation. In particular, we find that the preferred cortical localization of microtubules emerges from directional persistence of the microtubules, and their interactions with each other and with the stiff wall. We also identify microtubule parameters that seem relatively insensitive to cell shape, such as length or number. In contrast, microtubule array anisotropy depends on local curvature of the cell surface and global orientation follows robustly the longest axis of the cell. Lastly, we find that geometric cues may be overcome, as the network is capable of reorienting toward weak external directional cues. Altogether our simulations show that the microtubule network is a good transducer of weak external polarity, while at the same time, easily reaching stable global configurations

The one-body and two-body density matrices of finite nuclei with an appropriate treatment of the center-of-mass motion

The one-body and two-body density matrices in coordinate space and their Fourier transforms in momentum space are studied for a nucleus (a nonrelativistic, self-bound finite system). Unlike the usual procedure, suitable for infinite or externally bound systems, they are determined as expectation values of appropriate intrinsic operators, dependent on the relative coordinates and momenta (Jacobi variables) and acting on intrinsic wavefunctions of nuclear states. Thus, translational invariance (TI) is respected. When handling such intrinsic quantities, we use an algebraic technique based upon the Cartesian representation, in which the coordinate and momentum operators are linear combinations of the creation and annihilation operators a^+ and a for oscillator quanta. Each of the relevant multiplicative operators can then be reduced to the form: one exponential of the set {a^+} times other exponential of the set {a}. In the course of such a normal-ordering procedure we offer a fresh look at the appearance of "Tassie-Barker" factors, and point out other model-independent results. The intrinsic wavefunction of the nucleus in its ground state is constructed from a nontranslationally-invariant (nTI) one via existing projection techniques. As an illustration, the one-body and two-body momentum distributions (MDs) for the 4He nucleus are calculated with the Slater determinant of the harmonic-oscillator model as the trial, nTI wavefunction. We find that the TI introduces important effects in the MDs.Comment: 13 pages, incl. 3 figures - to appear in Eur. Phys. J.

Applying refinement to the use of mice and rats in rheumatoid arthritis research

Rheumatoid arthritis (RA) is a painful, chronic disorder and there is currently an unmet need for effective therapies that will benefit a wide range of patients. The research and development process for therapies and treatments currently involves in vivo studies, which have the potential to cause discomfort, pain or distress. This Working Group report focuses on identifying causes of suffering within commonly used mouse and rat ‘models’ of RA, describing practical refinements to help reduce suffering and improve welfare without compromising the scientific objectives. The report also discusses other, relevant topics including identifying and minimising sources of variation within in vivo RA studies, the potential to provide pain relief including analgesia, welfare assessment, humane endpoints, reporting standards and the potential to replace animals in RA research

Carbene-Metal-Amide Polycrystalline Materials Feature Blueshifted Energy yet Unchanged Kinetics of Emission

The nature of carbene-metal-amide (CMA) photoluminescence in the solid state is explored through spectroscopic and quantum-chemical investigations on a representative Au-centered molecule. The crystalline phase offers well-defined coplanar geometries-enabling the link between molecular conformations and photophysical properties to be unravelled. We show that a combination of restricted torsional distortion and molecular electronic polarization blue shift the charge-transfer emission by around 400 meV in the crystalline versus the amorphous phase, through energetically raising the less-dipolar S1 state relative to S0. This blue shift brings the lowest charge-transfer states very close to the localized carbazole triplet state, whose structured emission is observable at low temperature in the polycrystalline phase. Moreover, we discover that the rate of intersystem crossing and emission kinetics are unaffected by the extent of torsional distortion. We conclude that more coplanar triplet equilibrium conformations control the photophysics of CMAs