Information geometric bound on general chemical reaction networks.

We investigate the convergence of chemical reaction networks (CRNs), aiming to establish an upper bound on their reaction rates. The nonlinear characteristics and discrete composition of CRNs pose significant challenges in this endeavor. To circumvent these complexities, we adopt an information geometric perspective, utilizing the natural gradient to formulate a nonlinear system. This system effectively determines an upper bound for the dynamics of CRNs. We corroborate our methodology through numerical simulations, which reveal that our constructed system converges more rapidly than CRNs within a particular class of reactions. This class is defined by the count of chemicals, the highest stoichiometric coefficients in the reactions, and the total number of reactions involved. Further, we juxtapose our approach with traditional methods, illustrating that the latter falls short in providing an upper bound for CRN reaction rates. Although our investigation centers on CRNs, the widespread presence of hypergraphs across various disciplines, ranging from natural sciences to engineering, indicates potential wider applications of our method, including in the realm of information science.

BayesAge: A maximum likelihood algorithm to predict epigenetic age.

Introduction: DNA methylation, specifically the formation of 5-methylcytosine at the C5 position of cytosine, undergoes reproducible changes as organisms age, establishing it as a significant biomarker in aging studies. Epigenetic clocks, which integrate methylation patterns to predict age, often employ linear models based on penalized regression, yet they encounter challenges in handling missing data, count-based bisulfite sequence data, and interpretation. Methods: To address these limitations, we introduce BayesAge, an extension of the scAge methodology originally designed for single-cell DNA methylation analysis. BayesAge employs maximum likelihood estimation (MLE) for age inference, models count data using binomial distributions, and incorporates LOWESS smoothing to capture non-linear methylation-age dynamics. This approach is tailored for bulk bisulfite sequencing datasets. Results: BayesAge demonstrates superior performance compared to scAge. Notably, its age residuals exhibit no age association, offering a less biased representation of epigenetic age variation across populations. Furthermore, BayesAge facilitates the estimation of error bounds on age inference. When applied to down-sampled data, BayesAge achieves a higher coefficient of determination between predicted and actual ages compared to both scAge and penalized regression. Discussion: BayesAge presents a promising advancement in epigenetic age prediction, addressing key challenges encountered by existing models. By integrating robust statistical techniques and tailored methodologies for count-based data, BayesAge offers improved accuracy and interpretability in predicting age from bulk bisulfite sequencing datasets. Its ability to estimate error bounds enhances the reliability of age inference, thereby contributing to a more comprehensive understanding of epigenetic aging processes.

Harnessing Biomaterials to Amplify Immunity in Aged Mice through T Memory Stem Cells.

The durability of a protective immune response generated by a vaccine depends on its ability to induce long-term T cell immunity, which tends to decline in aging populations. The longest protection appears to arise from T memory stem cells (TMSCs) that confer high expandability and effector functions when challenged. Here we engineered artificial antigen presenting cells (aAPC) with optimized size, stiffness and activation signals to induce human and mouse CD8+ TMSCs in vitro. This platform was optimized as a vaccine booster of TMSCs (Vax-T) with prolonged release of small-molecule blockade of the glycogen synthase kinase-3ß together with target antigens. By using SARS-CoV-2 antigen as a model, we show that a single injection of Vax-T induces durable antigen-specific CD8+ TMSCs in young and aged mice, and generates humoral responses at a level stronger than or similar to soluble vaccines. This Vax-T approach can boost long-term immunity to fight infectious diseases, cancer, and other diseases.

Dual-Signal Chemical Exchange Saturation Transfer (Dusi-CEST): An Efficient Strategy for Visualizing Drug Delivery Monitoring in Living Cells.

We report a dual-signal chemical exchange saturation transfer (Dusi-CEST) strategy for drug delivery and detection in living cells. The two signals can be detected by operators in complex environments. This strategy is demonstrated on a cucurbit[6]uril (CB[6]) nanoparticle probe, as an example. The CB[6] probe is equipped with two kinds of hydrophobic cavities: one is found inside CB[6] itself, whereas the other exists inside the nanoparticle. When the probe is dispersed in aqueous solution as part of a hyperpolarized 129Xe NMR experiment, two signals appear at two different chemical shifts (100 and 200 ppm). These two resonances correspond to the NMR signals of 129Xe in the two different cavities. Upon loading with hydrophobic drugs, such as paclitaxel, for intracellular drug delivery, the two resonances undergo significant changes upon drug loading and cargo release, giving rise to a metric enabling the assessment of drug delivery success. The simultaneous change of Dusi-CEST likes a mobile phone that can receive both LTE and Wi-Fi signals, which can help reduce the occurrence of false positives and false negatives in complex biological environments and help improve the accuracy and sensitivity of single-shot detection.

Nuclear induction line shape: Non-Markovian diffusion with boundaries.

The dynamics of viscoelastic fluids are governed by a memory function, essential yet challenging to compute, especially when diffusion faces boundary restrictions. We propose a computational method that captures memory effects by analyzing the time-correlation function of the pressure tensor, a viscosity indicator, through the Stokes-Einstein equation's analytic continuation into the Laplace domain. We integrate this equation with molecular dynamics simulations to derive necessary parameters. Our approach computes nuclear magnetic resonance (NMR) line shapes using a generalized diffusion coefficient, accounting for temperature and confinement geometry. This method directly links the memory function with thermal transport parameters, facilitating accurate NMR signal computation for non-Markovian fluids in confined geometries.

Nuclear induction lineshape modeling via hybrid SDE and MD approach.

The temperature dependence of the nuclear free induction decay in the presence of a magnetic-field gradient was found to exhibit motional narrowing in gases upon heating, a behavior that is opposite to that observed in liquids. This has led to the revision of the theoretical framework to include a more detailed description of particle trajectories since decoherence mechanisms depend on histories. In the case of free diffusion and single components, the new model yields the correct temperature trends. The inclusion of boundaries in the current formalism is not straightforward. We present a hybrid SDE-MD (stochastic differential equation - molecular dynamics) approach whereby MD is used to compute an effective viscosity and the latter is fed to the SDE to predict the line shape. The theory is in agreement with the experiments. This two-scale approach, which bridges the gap between short (molecular collisions) and long (nuclear induction) timescales, paves the way for the modeling of complex environments with boundaries, mixtures of chemical species, and intermolecular potentials.

Conducting polymer-based scaffolds for neuronal tissue engineering.

Neuronal tissue engineering has immense potential for treating neurological disorders and facilitating nerve regeneration. Conducting polymers (CPs) have emerged as a promising class of materials owing to their unique electrical conductivity and biocompatibility. CPs, such as poly(3,4-ethylenedioxythiophene) (PEDOT), poly(3-hexylthiophene) (P3HT), polypyrrole (PPy), and polyaniline (PANi), have been extensively explored for their ability to provide electrical cues to neural cells. These polymers are widely used in various forms, including porous scaffolds, hydrogels, and nanofibers, and offer an ideal platform for promoting cell adhesion, differentiation, and axonal outgrowth. CP-based scaffolds can also serve as drug delivery systems, enabling localized and controlled release of neurotrophic factors and therapeutic agents to enhance neural regeneration and repair. CP-based scaffolds have demonstrated improved neural regeneration, both in vitro and in vivo, for treating spinal cord and peripheral nerve injuries. In this review, we discuss synthesis and scaffold processing methods for CPs and their applications in neuronal tissue regeneration. We focused on a detailed literature review of the central and peripheral nervous systems.

Systemic enhancement of antitumour immunity by peritumourally implanted immunomodulatory macroporous scaffolds.

A tumour microenvironment abundant in regulatory T (Treg) cells aids solid tumours to evade clearance by effector T cells. Systemic strategies to suppress Treg cells or to augment immunity can elicit autoimmune side effects, cytokine storms and other toxicities. Here we report the design, fabrication and therapeutic performance of a biodegradable macroporous scaffold, implanted peritumourally, that releases a small-molecule inhibitor of transforming growth factor ß to suppress Treg cells, chemokines to attract effector T cells and antibodies to stimulate them. In two mouse models of aggressive tumours, the implant boosted the recruitment and activation of effector T cells into the tumour and depleted it of Treg cells, which resulted in an 'immunological abscopal effect' on distant metastases and in the establishment of long-term memory that impeded tumour recurrence. We also show that the scaffold can be used to deliver tumour-antigen-specific T cells into the tumour. Peritumourally implanted immunomodulatory scaffolds may represent a general strategy to enhance T-cell immunity and avoid the toxicities of systemic therapies.

Intramyocardial hemorrhage drives fatty degeneration of infarcted myocardium.

Sudden blockage of arteries supplying the heart muscle contributes to millions of heart attacks (myocardial infarction, MI) around the world. Although re-opening these arteries (reperfusion) saves MI patients from immediate death, approximately 50% of these patients go on to develop chronic heart failure (CHF) and die within a 5-year period; however, why some patients accelerate towards CHF while others do not remains unclear. Here we show, using large animal models of reperfused MI, that intramyocardial hemorrhage - the most damaging form of reperfusion injury (evident in nearly 40% of reperfused ST-elevation MI patients) - drives delayed infarct healing and is centrally responsible for continuous fatty degeneration of the infarcted myocardium contributing to adverse remodeling of the heart. Specifically, we show that the fatty degeneration of the hemorrhagic MI zone stems from iron-induced macrophage activation, lipid peroxidation, foam cell formation, ceroid production, foam cell apoptosis and iron recycling. We also demonstrate that timely reduction of iron within the hemorrhagic MI zone reduces fatty infiltration and directs the heart towards favorable remodeling. Collectively, our findings elucidate why some, but not all, MIs are destined to CHF and help define a potential therapeutic strategy to mitigate post-MI CHF independent of MI size.

In Science Journals.

Highlights from the Science family of journals.

Ultrasensitive molecular building block for biothiol NMR detection at picomolar concentrations.

Magnetic resonance imaging (MRI) provides structural and functional information, but it did not probe chemistry. Chemical information could help improve specificity of detection. Herein, we introduce a general method based on a modular design to construct a molecular building block Xe probe to help image intracellular biothiols (glutathione (GSH), cysteine (Cys) and homocysteine (Hcy)), the abnormal content of which is related to various diseases. This molecular building block possesses a high signal-to-noise ratio and no background signal effects. Its detection threshold was 100 pM, which enabled detection of intracellular biothiols in live cells. The construction strategy can be easily extended to the detection of any other biomolecule or biomarker. This modular design strategy promotes efficiency of development of low-cost multifunctional probes that can be combined with other readout parameters, such as optical readouts, to complement 129Xe MRI to usher in new capabilities for molecular imaging.

Mapping Cell Viability Quantitatively and Independently From Cell Density in 3D Gels Noninvasively.

OBJECTIVE: In biomanufacturing there is a need for quantitative methods to map cell viability and density inside 3D bioreactors to assess health and proliferation over time. Recently, noninvasive MRI readouts of cell density have been achieved. However, the ratio of live to dead cells was not varied. Herein we present an approach for measuring the viability of cells embedded in a hydrogel independently from cell density to map cell number and health. METHODS: Independent quantification of cell viability and density was achieved by calibrating the 1H magnetization transfer- (MT) and diffusion-weighted NMR signals to samples of known cell density and viability using a multivariate approach. Maps of cell viability and density were generated by weighting NMR images by these parameters post-calibration. RESULTS: Using this method, the limits of detection (LODs) of total cell density and viable cell density were found to be 3.88 ×108 cells · mL -1· Hz -1/2 and 2.36 ×109 viable cells · mL -1· Hz -1/2 respectively. CONCLUSION: This mapping technique provides a noninvasive means of visualizing cell viability and number density within optically opaque bioreactors. SIGNIFICANCE: We anticipate that such nondestructive readouts will provide valuable feedback for monitoring and controlling cell populations in bioreactors.

Damaged lung gas exchange function of discharged COVID-19 patients detected by hyperpolarized 129Xe MRI.

The recovery process of COVID-19 patients is unclear. Some recovered patients complain of continued shortness of breath. Vasculopathy has been reported in COVID-19, stressing the importance of probing pulmonary microstructure and function at the alveolar-capillary interface. While computed tomography (CT) detects structural abnormalities, little is known about the impact of disease on lung function. 129Xe magnetic resonance imaging (MRI) is a technique uniquely capable of assessing ventilation, microstructure, and gas exchange. Using 129Xe MRI, we found that COVID-19 patients show a higher rate of ventilation defects (5.9% versus 3.7%), unchanged microstructure, and longer gas-blood exchange time (43.5 ms versus 32.5 ms) compared with healthy individuals. These findings suggest that regional ventilation and alveolar airspace dimensions are relatively normal around the time of discharge, while gas-blood exchange function is diminished. This study establishes the feasibility of localized lung function measurements in COVID-19 patients and their potential usefulness as a supplement to structural imaging.

Augmenting T-cell responses to tumors by in situ nanomanufacturing.

Recent innovations in immunoregulatory treatments have demonstrated both the impressive potential and vital role of T cells in fighting cancer. These treatments come at a cost, with systemic side effects including life-threatening autoimmunity and immune dysregulation the norm. Here, we developed an approach to locally synthesize immune therapies and in this way, avoid systemic toxicity. Rather than just encapsulating cytokines, we endowed our nanoparticles with transcriptional and translational machinery to make cytokines locally, in situ, and on demand (activated by light). We demonstrated the capabilities of these particles in vitro and in vivo, in a mouse model of melanoma, and showed that tumor-infiltrating T cells were more highly activated in the context of these "microfactory" particles that make the synthetic cytokine.

T-cell activation is modulated by the 3D mechanical microenvironment.

T cells recognize mechanical forces through a variety of cellular pathways, including mechanical triggering of both the T-cell receptor (TCR) and integrin LFA-1. Here we show that T cells can recognize forces arising from the mechanical rigidity of the microenvironment. We fabricated 3D scaffold matrices with mechanical stiffness tuned to the range 4-40 kPa and engineered them to be microporous, independently of stiffness. We cultured T cells and antigen presenting cells within the matrices and studied T-cell activation by flow cytometry and live-cell imaging. We found that there was an augmentation of T-cell activation, proliferation, and migration speed in the context of mechanically stiffer 3D matrices as compared to softer materials. These results show that T cells can sense their 3D mechanical environment and alter both their potential for activation and their effector responses in different mechanical environments. A 3D scaffold of tunable stiffness and consistent microporosity offers a biomaterial advancement for both translational applications and reductionist studies on the impact of tissue microenvironmental factors on cellular behavior.

A Small Molecular Multifunctional Tool for pH Detection, Fluorescence Imaging, and Photodynamic Therapy.

A smart multitool platform for theranostics would be useful for monitoring the administration of therapies in vivo. However, the integration of multiple functions into a single small-molecule platform remains a challenge. In this study, we developed a multifunctional probe based on a small-molecule platform. The properties of this probe were investigated via hyperpolarized 129Xe NMR/MRI, fluorescence imaging in cells and in vivo, and photodynamic therapy (PDT) in tumor mouse models. This multifunctional probe shows good pH response across a broad range of pH values. It also exhibits excellent fluorescence in vivo for mapping its biodistribution. Additionally, it produces enough 1O2 radicals for in vivo PDT. The combination of these functionalities into a single small-molecule platform, rather than a bulky nanoconstruct, offers unique possibilities for molecular imaging and therapy.

Augmentation of T-Cell Activation by Oscillatory Forces and Engineered Antigen-Presenting Cells.

Activation of T cells by antigen presenting cells (APCs) initiates their proliferation, cytokine production, and killing of infected or cancerous cells. We and others have shown that T-cell receptors require mechanical forces for triggering, and these forces arise during the interaction of T cells with APCs. Efficient activation of T cells in vitro is necessary for clinical applications. In this paper, we studied the impact of combining mechanical, oscillatory movements provided by an orbital shaker with soft, biocompatible, artificial APCs (aAPCs) of various sizes and amounts of antigen. We showed that these aAPCs allow for testing the strength of signal delivered to T cells, and enabled us to confirm that that absolute amounts of antigen engaged by the T cell are more important for activation than the density of antigen. We also found that when our aAPCs interact with T cells in the context of an oscillatory mechanoenvironment, they roughly double antigenic signal strength, compared to conventional, static culture. Combining these effects, our aAPCs significantly outperformed the commonly used Dynabeads. We finally demonstrated that tuning the signal strength down to a submaximal "sweet spot" allows for robust expansion of induced regulatory T cells. In conclusion, augmenting engineered aAPCs with mechanical forces offers a novel approach for tuning of T-cell activation and differentiation.

Hyperpolarization of Amino Acids in Water Utilizing Parahydrogen on a Rhodium Nanocatalyst.

NMR offers many possibilities in chemical analysis, structural investigations, and medical diagnostics. Although it is broadly used, one of NMR spectroscopies main drawbacks is low sensitivity. Hyperpolarization techniques enhance NMR signals by more than four orders of magnitude allowing the design of new contrast agents. Parahydrogen induced polarization that utilizes the para-hydrogen's singlet state to create enhanced signals is of particular interest since it allows to produce molecular imaging agents within seconds. Herein, we present a strategy for signal enhancement of the carbonyl 13 C in amino acids by using parahydrogen, as demonstrated for glycine and alanine. Importantly, the hyperpolarization step is carried out in water and chemically unmodified canonical amino acids are obtained. Our approach thus offers a high degree of biocompatibility, which is crucial for further application. The rapid sample hyperpolarization (within seconds) may enable the continuous production of biologically useful probes, such as metabolic contrast agents or probes for structural biology.

Nuclear Spin Singlet States in Photoactive Molecules: From Fluorescence/NMR Bimodality to a Bimolecular Switch for Spin Singlet States.

Nuclear spin singlet states are silent states in nuclear magnetic resonance (NMR). However, they can be probed indirectly and offer great potential for the development of contrast agents for magnetic resonance imaging (MRI). Introduced here are two novel concepts: Firstly, the bimodal NMR/fluorescence properties of 13 C2 -tetraphenylethylene. It possesses a long-lived singlet state in organic solvents, and it shortens upon the addition of water. This simultaneously increases the aggregation-induced emission (AIE) of the molecule, resulting in a substantial enhancement of fluorescence. Secondly, introduced is a bimolecular switch for singlet states based on 3-2 H-coumarin containing an isolated proton. Upon UV-light exposure, a dimer forms, leading to a coupling between two previously isolated protons. A nuclear spin singlet state can now be populated. Excitation with a wavelength of 254 nm results in partial ring cleavage of the molecule back to its monomer.

Noninvasive Quantification of Cell Density in Three-Dimensional Gels by MRI.

OBJECTIVE: For tissue engineering, there is a need for quantitative methods to map cell density inside three-dimensional (3-D) bioreactors to assess tissue growth over time. The current cell mapping methods in 2-D cultures are based on optical microscopy. However, optical methods fail in 3-D due to increased opacity of the tissue. We present an approach for measuring the density of cells embedded in a hydrogel to generate quantitative maps of cell density in a living, 3-D tissue culture sample. METHODS: Quantification of cell density was obtained by calibrating the 1H T2, magnetization transfer (MT) and diffusion-weighted nuclear magnetic resonance (NMR) signals to samples of known cell density. Maps of cell density were generated by weighting NMR images by these parameters post-calibration. RESULTS: The highest sensitivity weighting arose from MT experiments, which yielded a limit of detection (LOD) of [Formula: see text] cells/mL/ √{Hz} in a 400 MHz (9.4 T) magnet. CONCLUSION: This mapping technique provides a noninvasive means of visualizing cell growth within optically opaque bioreactors. SIGNIFICANCE: We anticipate that such readouts of tissue culture growth will provide valuable feedback for controlled cell growth in bioreactors.