Publications by authors named "Pablo J"

IFNλ4 has posed a conundrum in human immunology since its discovery in 2013, with its expression linked to complications with viral clearance. While genetic and cellular studies revealed the detrimental effects of IFNλ4 expression, extensive structural and functional characterization has been limited by the inability to express and purify the protein, complicating explanations of its paradoxical behavior. In this work, we report a method for robust production of IFNλ4.

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Exposure to saturated fatty acids (SFAs), such as palmitic acid, can lead to cellular metabolic dysfunction known as lipotoxicity. Although canonical adaptive metabolic processes like lipid storage or desaturation are known cellular responses to saturated fat exposure, the link between SFA metabolism and organellar biology remains an area of active inquiry. We performed a genome-wide CRISPR knockout screen in human epithelial cells to identify modulators of SFA toxicity.

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Article Synopsis
  • A multiscale modeling framework is developed to predict the nonlinear shear rheology of entangled polymer melts, starting from an all-atom model and transitioning to coarser models through a detailed parametrization process.
  • The study focuses on atactic polystyrene melts, where the steady shear viscosity is accurately calculated across various shear rates, matching experimental data without needing adjustable parameters.
  • The analysis reveals a transition from power-law behavior at high shear rates to a plateau regime at lower rates, influenced by molecular weight, allowing for comprehensive viscosity predictions over a wide range of conditions.
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Machine learning interatomic potentials (MLIPs) are rapidly gaining interest for molecular modeling, as they provide a balance between quantum-mechanical level descriptions of atomic interactions and reasonable computational efficiency. However, questions remain regarding the stability of simulations using these potentials, as well as the extent to which the learned potential energy function can be extrapolated safely. Past studies have encountered challenges when MLIPs are applied to classical benchmark systems.

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We theoretically investigate how the intranuclear environment influences the charge of a nucleosome core particle (NCP)-the fundamental unit of chromatin consisting of DNA wrapped around a core of histone proteins. The molecular-based theory explicitly considers the size, shape, conformation, charge, and chemical state of all molecular species-thereby linking the structural state with the chemical/charged state of the system. We investigate how variations in monovalent and divalent salt concentrations, as well as pH, affect the charge distribution across different regions of an NCP and quantify the impact of charge regulation.

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The trafficking dynamics of uromodulin (UMOD), the most abundant protein in human urine, play a critical role in the pathogenesis of kidney disease. Monoallelic mutations in the UMOD gene cause autosomal dominant tubulointerstitial kidney disease (ADTKD-UMOD), an incurable genetic disorder that leads to kidney failure. The disease is caused by the intracellular entrapment of mutant UMOD in kidney epithelial cells, but the precise mechanisms mediating disrupted UMOD trafficking remain elusive.

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We theoretically investigate how the intranuclear environment influences the charge of a nucleosome core particle (NCP) - the fundamental unit of chromatin consisting of DNA wrapped around a core of histone proteins. The molecular-based theory explicitly considers the size, shape, conformations, charges, and chemical states of all molecular species - thereby linking the structural state with the chemical/charged state of the system. We investigate how variations in monovalent and divalent salt concentrations, as well as pH, affect the charge distribution across different regions of an NCP and quantify the impact of charge regulation.

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Cholesteric liquid crystals (CLCs) are compelling responsive materials with applications in next-generation sensing, imaging, and display technologies. While electric fields and surface treatments have been used to manipulate the molecular organization and, subsequently, the optical properties of CLCs, their response to controlled fluid flow has remained largely unexplored. Here, we investigate the influence of microfluidic flow on the structure of thermotropic CLCs that can exhibit structural coloration.

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The rapid growth of population and the effects of climate change have placed unprecedented pressure on urban water supplies and pollution control. Consequently, it is essential to explore new local water resources in water-strained areas. To this end, this work focuses on evaluating pollutant removal effectiveness of decentralized treatment systems for groundwater reclamation.

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We study the rheology of bidisperse non-Brownian suspensions using particle-based simulation, mapping the viscosity as a function of the size ratio of the species, their relative abundance, and the overall solid content. The variation of the viscosity with applied stress exhibits shear-thickening phenomenology irrespective of composition, though the stress-dependent limiting solids fraction governing the viscosity and its divergence point are nonmonotonic in the mixing ratio. Contact force data demonstrate an asymmetric exchange in the dominant stress contribution from large-large to small-small particle contacts as the mixing ratio of the species evolves.

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Intracellular accumulation of misfolded proteins causes serious human proteinopathies. The transmembrane emp24 domain 9 (TMED9) cargo receptor promotes a general mechanism of cytotoxicity by entrapping misfolded protein cargos in the early secretory pathway. However, the molecular basis for this TMED9-mediated cargo retention remains elusive.

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A combination of machine learned interatomic potentials (MLIPs) and enhanced sampling simulations is used to investigate the activation of methane on a Ni(111) surface. The work entails the development and iterative refinement of MLIPs, initially trained on a data set constructed via molecular dynamics simulations, supplemented by adaptive biasing forces, to enrich the sampling of catalytically relevant configurations. Our results reveal that upon incorporation of collective variables that capture the behavior of the reactant molecule, as well as additional frames that describe the dynamic response of the catalytic surface, it is possible to enhance considerably the accuracy of predicted energies and forces.

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Polymer electrolytes are of interest for applications in energy storage. Molecular simulations of ion transport in polymer electrolytes have been widely used to study the conductivity in these materials. Such simulations have generally relied on classical force fields.

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Article Synopsis
  • Researchers are focusing on improving syphilis diagnostic tests due to a rise in cases, aiming to enhance the effectiveness of treponemal tests through high-throughput profiling of immune responses to specific proteins during infections.
  • A pan-proteome array was developed using complete proteomes of syphilis strains to analyze the immune response in infected rabbits, including those who were treated and re-infected.
  • The study identified specific antigens that may lead to better early diagnosis and could also aid in selecting vaccine candidates for more effective protection against reinfection.
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Children with hemoglobin AC or AS have decreased susceptibility to clinical malaria. Parasite variant surface antigen (VSA) presentation on the surface of infected erythrocytes is altered in erythrocytes with hemoglobin C (Hb AC) or sickle trait (Hb AS) mutations in vitro. The protective role of incomplete or altered VSA presentation against clinical malaria in individuals with Hb AC or AS is unclear.

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Solid-state electrolytes, particularly polymer/ceramic composite electrolytes, are emerging as promising candidates for lithium-ion batteries due to their high ionic conductivity and mechanical flexibility. The interfaces that arise between the inorganic and organic materials in these composites play a crucial role in ion transport mechanisms. While lithium ions are proposed to diffuse across or parallel to the interface, few studies have directly examined the quantitative impact of these pathways on ion transport and little is known about how they affect the overall conductivity.

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Multidimensional solitons are prevalent in numerous research fields. In orientationally ordered soft matter system, three-dimensional director solitons exemplify the localized distortion of molecular orientation. However, their precise manipulation remains challenging due to unpredictable and uncontrolled generation.

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Machine learned force fields offer the potential for faster execution times while retaining the accuracy of traditional DFT calculations, making them promising candidates for molecular simulations in cases where reliable classical force fields are not available. Some of the challenges associated with machine learned force fields include simulation stability over extended periods of time and ensuring that the statistical and dynamical properties of the underlying simulated systems are correctly captured. In this work, we propose a systematic training pipeline for such force fields that leads to improved model quality, compared to that achieved by traditional data generation and training approaches.

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Article Synopsis
  • - This study compares human milk antibodies to various pathogens in women from five different countries (Bangladesh, Finland, Peru, Pakistan, and the U.S.) using advanced protein microarrays, analyzing samples from 695 women.
  • - Results reveal that antibody levels, specifically IgA and IgG, vary significantly by region and are influenced by factors like maternal BMI and number of children, with the highest antibody coverage found in Bangladeshi and Pakistani mothers.
  • - The findings suggest that certain human milk antibodies may provide protective benefits against infections in infants, which could inform strategies to reduce infant illness and mortality globally.
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Nonequilibrium states in soft condensed matter require a systematic approach to characterize and model materials, enhancing predictability and applications. Among the tools, X-ray photon correlation spectroscopy (XPCS) provides exceptional temporal and spatial resolution to extract dynamic insight into the properties of the material. However, existing models might overlook intricate details.

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Redox-active polymers serving as the active materials in solid-state electrodes offer a promising path toward realizing all-organic batteries. While both cathodic and anodic redox-active polymers are needed, the diversity of the available anodic materials is limited. Here, we predict solid-state structural, ionic, and electronic properties of anodic, phthalimide-containing polymers using a multiscale approach that combines atomistic molecular dynamics, electronic structure calculations, and machine learning surrogate models.

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  • This study assesses the diagnostic value of bone marrow aspiration (BMA) in patients suspected of having immune thrombocytopaenia (ITP) over a 27-year period.
  • It analyzes data from 243 ITP patients, revealing a significant decrease in the number of unnecessary BMAs performed as adherence to guidelines improved.
  • Although BMA did not change initial diagnoses significantly, it did help confirm acquired aplastic anaemia in two cases after diagnosis.
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In this paper, we investigate how the dielectric constant, ϵ, of an electrolyte solvent influences the current rectification characteristics of bipolar nanopores. It is well recognized that bipolar nanopores with two oppositely charged regions rectify current when exposed to an alternating electric potential difference. Here, we consider dilute electrolytes with NaCl only and with a mixture of NaCl and charged nanoparticles.

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