Ergodic Mean-Field Games of Singular Control with Regime-Switching (Extended Version)

This paper studies a class of stationary mean-field games of singular stochastic control with regime-switching. The representative agent adjusts the dynamics of a Markov-modulated It\^o-diffusion via a two-sided singular stochastic control and faces a long-time-average expected profit criterion. The mean-field interaction is of scalar type and it is given through the stationary distribution of the population. Via a constructive approach, we prove the existence and uniqueness of the stationary mean-field equilibrium. Furthermore, we show that this realizes a symmetric $\varepsilon_N$-Nash equilibrium for a suitable ergodic $N$-player game with singular controls. The proof hinges on the characterization of the optimal solution to the representative player's ergodic singular stochastic control problem with regime switching, which is of independent interest and appears here for the first time

A photoconversion model for full spectral programming and multiplexing of optogeneticﾠsystems

Optogenetics combines externally applied light signals and genetically engineered photoreceptors to control cellular processes with unmatched precision. Here, we develop a mathematical model of wavelength‐ and intensity‐dependent photoconversion, signaling, and output gene expression for our two previously engineered light‐sensing Escherichia coli two‐component systems. To parameterize the model, we develop a simple set of spectral and dynamical calibration experiments using our recent open‐source “Light Plate Apparatus” device. In principle, the parameterized model should predict the gene expression response to any time‐varying signal from any mixture of light sources with known spectra. We validate this capability experimentally using a suite of challenging light sources and signals very different from those used during the parameterization process. Furthermore, we use the model to compensate for significant spectral cross‐reactivity inherent to the two sensors in order to develop a new method for programming two simultaneous and independent gene expression signals within the same cell. Our optogenetic multiplexing method will enable powerful new interrogations of how metabolic, signaling, and decision‐making pathways integrate multiple input signals

Mesenchymal stem cell and gelatin microparticle encapsulation in thermally and chemically gelling injectable hydrogels for tissue engineering

In this work, we investigated the viability and osteogenic differentiation of mesenchymal stem cells encapsulated with gelatin microparticles (GMPs) in an injectable, chemically and thermally gelling hydrogel system combining poly(N-isopropylacrylamide)-based thermogelling macromers containing pendant epoxy rings with polyamidoamine-based hydrophilic and degradable diamine crosslinking macromers. Specifically, we studied how the parameters of GMP size and loading ratio affected the viability and differentiation of cells encapsulated within the hydrogel. We also examined the effects of cell and GMP co-encapsulation on hydrogel mineralization. Cells demonstrated long-term viability within the hydrogels, which was shown to depend on GMP size and loading ratio. In particular, increased interaction of cells and GMPs through greater available GMP surface area, use of an epoxy-based chemical gelation mechanism, and the tunable high water content of the thermogelled hydrogels led to favorable long-term cell viability. Compared with cellular hydrogels without GMPs, hydrogels co-encapsulating cells and GMPs demonstrated greater production of alkaline phosphatase by cells at all time-points and a transient early enhancement of hydrogel mineralization for larger GMPs at higher loading ratios. Such injectable, in situ forming hydrogels capable of delivering and maintaining populations of encapsulated mesenchymal stem cells and promoting mineralization in vitro offer promise as novel therapies for applications in tissue engineering and regenerative medicine

Single-cell RNA sequencing of liver fine-needle aspirates captures immune diversity in the blood and liver in chronic hepatitis B patients

Background and Aims: HBV infection is restricted to the liver, where it drives exhaustion of virus-specific T and B cells and pathogenesis through dysregulation of intrahepatic immunity. Our understanding of liver-specific events related to viral control and liver damage has relied almost solely on animal models, and we lack useable peripheral biomarkers to quantify intrahepatic immune activation beyond cytokine measurement. Our objective was to overcome the practical obstacles of liver sampling using fine-needle aspiration and develop an optimized workflow to comprehensively compare the blood and liver compartments within patients with chronic hepatitis B using single-cell RNA sequencing. Approach and Results: We developed a workflow that enabled multi-site international studies and centralized single-cell RNA sequencing. Blood and liver fine-needle aspirations were collected, and cellular and molecular captures were compared between the Seq-Well S3 picowell-based and the 10× Chromium reverse-emulsion droplet–based single-cell RNA sequencing technologies. Both technologies captured the cellular diversity of the liver, but Seq-Well S3 effectively captured neutrophils, which were absent in the 10× dataset. CD8 T cells and neutrophils displayed distinct transcriptional profiles between blood and liver. In addition, liver fine-needle aspirations captured a heterogeneous liver macrophage population. Comparison between untreated patients with chronic hepatitis B and patients treated with nucleoside analogs showed that myeloid cells were highly sensitive to environmental changes while lymphocytes displayed minimal differences. Conclusions: The ability to electively sample and intensively profile the immune landscape of the liver, and generate high-resolution data, will enable multi-site clinical studies to identify biomarkers for intrahepatic immune activity in HBV and beyond.</p

Synthesis and Characterization of Thermally and Chemically Gelling Injectable Hydrogels for Tissue Engineering

Novel, injectable hydrogels were developed that solidify through a dual-gelation, physical and chemical, mechanism upon preparation and elevation of temperature to 37°C. A thermogelling, poly(N-isopropylacrylamide)-based macromer with pendant epoxy rings and a hydrolyticallydegradable polyamidoamine-based diamine crosslinker were synthesized, characterized, and combined to produce in situ forming hydrogel constructs. Network formation through the epoxyamine reaction was shown to be rapid and facile, and the progressive incorporation of the hydrophilic polyamidoamine crosslinker into the hydrogel was shown to mitigate the often problematic tendency of thermogelling materials to undergo significant post-formation gel syneresis. The results suggest that this novel class of injectable hydrogels may be attractive substrates for tissue engineering applications due to the synthetic versatility of the component materials and beneficial hydrogel gelation kinetics and stability

SARS-CoV-2 Receptor ACE2 Is an Interferon-Stimulated Gene in Human Airway Epithelial Cells and Is Detected in Specific Cell Subsets across Tissues.

There is pressing urgency to understand the pathogenesis of the severe acute respiratory syndrome coronavirus clade 2 (SARS-CoV-2), which causes the disease COVID-19. SARS-CoV-2 spike (S) protein binds angiotensin-converting enzyme 2 (ACE2), and in concert with host proteases, principally transmembrane serine protease 2 (TMPRSS2), promotes cellular entry. The cell subsets targeted by SARS-CoV-2 in host tissues and the factors that regulate ACE2 expression remain unknown. Here, we leverage human, non-human primate, and mouse single-cell RNA-sequencing (scRNA-seq) datasets across health and disease to uncover putative targets of SARS-CoV-2 among tissue-resident cell subsets. We identify ACE2 and TMPRSS2 co-expressing cells within lung type II pneumocytes, ileal absorptive enterocytes, and nasal goblet secretory cells. Strikingly, we discovered that ACE2 is a human interferon-stimulated gene (ISG) in vitro using airway epithelial cells and extend our findings to in vivo viral infections. Our data suggest that SARS-CoV-2 could exploit species-specific interferon-driven upregulation of ACE2, a tissue-protective mediator during lung injury, to enhance infection

Ergodic Mean-Field Games of Singular Control with Regime-Switching (extended version)

Dianetti J, Ferrari G, Tzouanas I. Ergodic Mean-Field Games of Singular Control with Regime-Switching (extended version). Center for Mathematical Economics Working Papers. Vol 681. Bielefeld: Center for Mathematical Economics; 2023.This paper studies a class of stationary mean-field games of singular stochastic control with regime-switching. The representative agent adjusts the dynamics of a Markov-modulated Itô-diffusion via a two-sided singular stochastic control and faces a long-time-average expected profit criterion. The mean-field interaction is of scalar type and it is given through the stationary distribution of the population. Via a constructive approach, we prove the existence and uniqueness of the stationary mean-field equilibrium. Furthermore, we show that this realizes a symmetric $\varepsilon_N$-Nash equilibrium for a suitable ergodic $N$-player game with singular controls. The proof hinges on the characterization of the optimal solution to the representative player's ergodic singular stochastic control problem with regime switching, which is of independent interest and appears here for the first time.MSC subject classification: 49L20, 91A15, 91A16, 60G40, 35R35, 93C3

A photoconversion model for full spectral programming and multiplexing of optogenetic systems

Optogenetics combines externally applied light signals and genetically engineered photoreceptors to control cellular processes with unmatched precision. Here, we develop a mathematical model of wavelength‐ and intensity‐dependent photoconversion, signaling, and output gene expression for our two previously engineered light‐sensing Escherichia coli two‐component systems. To parameterize the model, we develop a simple set of spectral and dynamical calibration experiments using our recent open‐source “Light Plate Apparatus” device. In principle, the parameterized model should predict the gene expression response to any time‐varying signal from any mixture of light sources with known spectra. We validate this capability experimentally using a suite of challenging light sources and signals very different from those used during the parameterization process. Furthermore, we use the model to compensate for significant spectral cross‐reactivity inherent to the two sensors in order to develop a new method for programming two simultaneous and independent gene expression signals within the same cell. Our optogenetic multiplexing method will enable powerful new interrogations of how metabolic, signaling, and decision‐making pathways integrate multiple input signals