An assessment of representing land‐ocean heterogeneity via CAPE relaxation timescale in the Community Atmospheric Model 6 (CAM6)

The time needed by deep convection to bring the atmosphere back to equilibrium is called convective adjustment timescale or simply adjustment timescale, typically denoted by . In the Community Atmospheric Model|Community Atmosphere Model (CAM), is the convective available potential energy (CAPE) relaxation timescale and is 1 hr, worldwide. Observational evidence suggests that is generally longer than 1 hr. Further, continental and oceanic convection are different in terms of the vigor of updrafts and can have different longevities. So using hour worldwide in CAM has two potential caveats. A longer improves the simulation of the mean climate. However, it does not address the land‐ocean heterogeneity of atmospheric deep convection. We investigate the prescription of two different CAPE relaxation timescales for land ( hr) and ocean ( to 4 hr). It is arguably an extremely crude parameterization of boundary layer control on atmospheric convection. We contrast a suite of 5‐year‐long simulations with two different for land and ocean to having one globally. The choice of longer over ocean is guided by previous studies and inspired by observational pieces of evidence. Nonetheless, to complement our variable experiments, we perform a simulation with  hr and  hrs. Most importantly, our key findings are immune to the exact values of prescribed and . The CAM model, with two values , improves convective‐stratiform rainfall partitioning and the Madden–Julian oscillation propagation characteristics

A coarse-grained model for aqueous two-phase systems: Application to ferrofluids

Aqueous two-phase systems (ATPSs), phase-separating solutions of water soluble but mutually immiscible molecular species, offer fascinating prospects for selective partitioning, purification, and extraction. Here, we formulate a general Brownian dynamics based coarse-grained simulation model for an ATPS of two water soluble but mutually immiscible polymer species. Including additional solute species into the model is straightforward, which enables capturing the assembly and partitioning response of, e.g., nanoparticles (NPs), additional macromolecular species, or impurities in the ATPS. We demonstrate that the simulation model captures satisfactorily the phase separation, partitioning, and interfacial properties of an actual ATPS using a model ATPS in which a polymer mixture of dextran and polyethylene glycol (PEG) phase separates, and magnetic NPs selectively partition into one of the two polymeric phases. Phase separation and NP partitioning are characterized both via the computational model and experimentally, under different conditions. The simulation model captures the trends observed in the experimental system and quantitatively links the partitioning behavior to the component species interactions. Finally, the simulation model reveals that the ATPS interface fluctuations in systems with magnetic NPs as a partitioned species can be controlled by the magnetic field at length scales much smaller than those probed experimentally to date

ISTA Thesis

Immune responses depend on the coordinated and efficient migration of leukocytes. These cells, which are embedded and tightly confined within tissues, must navigate and traverse diverse and complex three-dimensional environments. Leukocytes adapt their locomotory behavior to the mechanical, geometrical, and biochemical characteristics of their surroundings. In low-density environments, where the pore size of the interstitial matrix allows free passage, these cells position the nucleus directly behind the lamellipodium, the protrusive actin structure that forms the leading front of the cell. In this configuration, they use the nucleus as a gauge to identify the path of least resistance. Here, we show that in high-density environments, where the pore size precludes free passage of the cell body, leukocytes reposition the microtubule-organizing center (MTOC) and associated organelles in front of the nucleus. In this configuration, they use actin structures protruding orthogonally to the direction of migration in order to open a path for the cell body. We identify two distinct actin populations that serve this purpose at different subcellular localizations. At the leading edge, local indentation of the plasma membrane leads to recruitment of the Wiskott-Aldrich syndrome protein (WASp), which, via Arp2/3, results in the formation of individual actin foci. At the cell body, actin polymerization is triggered by DOCK8, a Cdc42 exchange factor, resulting in the formation of a central actin pool. We demonstrate that the central and peripheral actin pools are functionally communicating and that depletion of the central actin pool leads to increased actin accumulation at the cell front, resulting in excessive extension of the leading edge

Magnetic excitations in Ndn+1Nin O3n+1 Ruddlesden-Popper nickelates observed via resonant inelastic x-ray scattering

Magnetic interactions are thought to play a key role in the properties of many unconventional superconductors, including cuprates, iron pnictides, and square-planar nickelates. Superconductivity was also recently observed in the bilayer and trilayer Ruddlesden-Popper nickelates, the electronic structure of which is expected to differ from that of cuprates and square-planar nickelates. Here we study how electronic structure and magnetic interactions evolve with the number of layers, , in thin film Ruddlesden-Popper nickelates Nd+1⁢Ni⁢O3⁢+1 with =1,3, and 5 using resonant inelastic x-ray scattering (RIXS). The RIXS spectra are consistent with a high-spin |3⁢8⁢ ̲⟩ electronic configuration, resembling that of La2−⁢Sr⁢NiO4 and the parent perovskite, NdNiO3. The magnetic excitations soften to lower energy in the structurally self-doped, higher- films. Our observations confirm that structural tuning is an effective route for altering electronic properties, such as magnetic superexchange, in this prominent family of materials

Bumps on the road: The way to clean relaxation dispersion magic-angle spinning NMR

Microsecond-to-millisecond motions are instrumental for many biomolecular functions, including enzymatic activity and ligand binding. Bloch-McConnell Relaxation Dispersion (BMRD) Nuclear Magnetic Resonance (NMR) spectroscopy is a key technique for studying these dynamic processes. While BMRD experiments are routinely used to probe protein motions in solution, the experiment is more demanding in the solid state, where dipolar couplings complicate the spin dynamics. It is believed that high deuteration levels are required and sufficient to obtain accurate and quantitative data. Here we show that even under fast magic-angle spinning and high levels of deuteration artifactual “bumps” in 15N R1ρ BMRD profiles are common. The origin of these artifacts is identified as a second-order three-spin Mixed Rotational and Rotary Resonance (MIRROR) recoupling condition. These artifacts are found to be a significant confounding factor for the accurate quantification of microsecond protein dynamics using BMRD in the solid state. We show that the application of low-power continuous wave (CW) decoupling simultaneously with the 15N spin-lock leads to the suppression of these conditions and enables quantitative measurements of microsecond exchange in the solid state. Remarkably, the application of decoupling allows the measurement of accurate BMRD even in fully protonated proteins at 100 kHz MAS, thus extending the scope of μs dynamics measurements in MAS NMR

A high fraction of close massive binary stars at low metallicity

At high metallicity, a majority of massive stars have at least one close stellar companion. The evolution of such binaries is subject to strong interaction processes, which heavily impact the characteristics of their life-ending supernova and compact remnants. For the low-metallicity environments of high-redshift galaxies, constraints on the multiplicity properties of massive stars over the separation range leading to binary interaction are crucially missing. Here we show that the presence of massive stars in close binaries is ubiquitous, even at low metallicity. Using the Very Large Telescope, we obtained multi-epoch radial velocity measurements of a representative sample of 139 massive O-type stars across the Small Magellanic Cloud, which has a metal content of about one-fifth of the solar value. We find that 45% of them show radial velocity variations that demonstrate that they are members of close binary systems, and predominantly have orbital periods shorter than 1 year. Correcting for observational biases indicates that at least 70+11−6 % of the O stars in our sample are in close binaries, and that at least 68+7 −8% of all O stars interact with a companion star during their lifetime. We found no evidence supporting a statistically significant trend of the multiplicity properties with metallicity. Our results indicate that multiplicity and binary interactions govern the evolution of massive stars and determine their cosmic feedback and explosive fates

Pairs of commuting integer matrices

We prove upper and lower bounds on the number of pairs of commuting n x n matrices with integer entries in [-T, T], as T -> . Our work uses Fourier analysis and leads to an analysis of exponential sums involving matrices over finite fields. These are bounded by combining a stratification result of Fouvry and Katz with a new result about the flatness of the commutator Lie bracket

Automatic feature selection and weighting in molecular systems using Differentiable Information Imbalance

Feature selection is essential in the analysis of molecular systems and many other fields, but several uncertainties remain: What is the optimal number of features for a simplified, interpretable model that retains essential information? How should features with different units be aligned, and how should their relative importance be weighted? Here, we introduce the Differentiable Information Imbalance (DII), an automated method to rank information content between sets of features. Using distances in a ground truth feature space, DII identifies a low-dimensional subset of features that best preserves these relationships. Each feature is scaled by a weight, which is optimized by minimizing the DII through gradient descent. This allows simultaneously performing unit alignment and relative importance scaling, while preserving interpretability. DII can also produce sparse solutions and determine the optimal size of the reduced feature space. We demonstrate the usefulness of this approach on two benchmark molecular problems: (1) identifying collective variables that describe conformations of a biomolecule, and (2) selecting features for training a machine-learning force field. These results show the potential of DII in addressing feature selection challenges and optimizing dimensionality in various applications. The method is available in the Python library DADApy

Microglia determine an immune-challenged environment and facilitate ibuprofen action in human retinal organoids

Prenatal immune challenges pose significant risks to human embryonic brain and eye development. However, our knowledge about the safe usage of anti-inflammatory drugs during pregnancy is still limited. While human induced pluripotent stem cells (hIPSC)-derived brain organoid models have started to explore functional consequences upon viral stimulation, these models commonly lack microglia, which are susceptible to and promote inflammation. Furthermore, microglia are actively involved in neuronal development. Here, we generate hIPSC-derived microglia precursor cells and assemble them into retinal organoids. Once the outer plexiform layer forms, these hIPSC-derived microglia (iMG) fully integrate into the retinal organoids. Since the ganglion cell survival declines by this time in 3D-retinal organoids, we adapted the model into 2D and identify that the improved ganglion cell number significantly decreases only with iMG presence. In parallel, we applied the immunostimulant POLY(I:C) to mimic a fetal viral infection. While POLY(I:C) exposure alters the iMG phenotype, it does not hinder their interaction with ganglion cells. Furthermore, iMG significantly enhance the supernatant’s inflammatory secretome and increase retinal cell proliferation. Simultaneous exposure with the non-steroidal anti-inflammatory drug (NSAID) ibuprofen dampens POLY(I:C)-mediated changes of the iMG phenotype and ameliorates cell proliferation. Remarkably, while POLY(I:C) disrupts neuronal calcium dynamics independent of iMG, ibuprofen rescues this effect only if iMG are present. Mechanistically, ibuprofen targets the enzymes cyclooxygenase 1 and 2 (COX1/PTGS1 and COX2/PTGS2) simultaneously, from which iMG mainly express COX1. Selective COX1 blockage fails to restore the calcium peak amplitude upon POLY(I:C) stimulation, suggesting ibuprofen’s beneficial effect depends on the presence and interplay of COX1 and COX2. These findings underscore the importance of microglia in the context of prenatal immune challenges and provide insight into the mechanisms by which ibuprofen exerts its protective effects during embryonic development