Cell Reports Physical Science

Living organisms achieve adaptive actuation through the seamless integration of neural motor control circuitry and proprioceptive feedback. While biohybrid robotics aims to replicate these capabilities by merging engineered muscle with synthetic scaffolds, the field remains limited by interfaces that lack the efficiency and closed-loop regulation of natural neuromuscular systems. Here, we introduce a biohybrid muscle actuator system featuring a bioelectronic interface based on soft poly(3,4-ethylenedioxythiophene) (PEDOT) fibers for stimulation and sensing. These fibers conformally couple to muscle tissues, eliciting robust contractions at voltages as low as 1 V--requiring ultra-low power (0.376 {+/-} 0.034 mW) and preserving long-term tissue viability. By leveraging the independent addressability of these fibers, we demonstrate selective actuation of individual muscle units to achieve precise spatiotemporal control of a two-muscle-powered walking biohybrid robot, reaching a locomotion speed of 5.43 {+/-} 0.79 mm/min. When configured as strain sensors, the fibers exhibit a high gauge factor of 155.45 {+/-} 6.59 and resolve contractile displacements within tens of micrometers. We demonstrate that this sensing modality can be integrated into a closed-loop controller to autonomously modulate stimulation based on real-time feedback, significantly mitigating muscle fatigue (p = 0.038) during continuous operation. This work establishes a versatile platform for efficient actuation and intrinsic feedback sensing, providing a blueprint for efficient, autonomous, and adaptive biohybrid machines. SummarySoft conductive fibers enable a bioelectronic interface for low-power actuation and closed-loop control in biohybrid robots.

Scaffolded DNA origami has become a valuable nanoscale tool for applications in biomedical and physical sciences. Critical to leveraging the modular and programmable properties of DNA origami nanodevices is access to the scaffold strand, a long single-stranded DNA (ssDNA) of precise length and sequence, which is folded into a compact shape via piecewise base-pairing with many staple strands, short ssDNA oligonucleotides. Current methods to produce and manipulate long ssDNA scaffolds can be costly, time-consuming, and cumbersome. In contrast, methods to produce and manipulate the sequence of double-stranded DNA (dsDNA) are efficient and scalable. Here, we present a method for the rapid isolation of target ssDNA sequences from a variety of dsDNA sources using oligonucleotides as blocking strands that bind continuously to the undesired strand, thereby releasing the target scaffold strand. We report successful ssDNA isolation from linear and supercoiled dsDNAs of various sequences and lengths, ranging from 769 to 15,101 nucleotides. In addition to isolating ssDNA, we demonstrated this approach enables folding of DNA origami directly from dsDNA templates using both blocking and staple strands in a single-pot thermally controlled reaction. Furthermore, we explore multi-scaffold and gene-encoding DNA origami structures, expanding the framework for application-based designs. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=82 SRC="FIGDIR/small/709872v1_ufig1.gif" ALT="Figure 1"> View larger version (30K): org.highwire.dtl.DTLVardef@1cc75dcorg.highwire.dtl.DTLVardef@4df8e2org.highwire.dtl.DTLVardef@10ed113org.highwire.dtl.DTLVardef@1c05bdd_HPS_FORMAT_FIGEXP M_FIG C_FIG

There has been a surge in antibiotic resistance in recent years, making traditional antibiotics less effective against key pathogens. RNA has recently emerged as a potential target for antibiotics due to its involvement in crucial microbial functions. It is possible to expand the range of therapeutic targets by using RNA-based therapies, but it remains necessary to improve the molecular-level understanding of interactions between RNA and known and potential binders. The SAM-I riboswitch, which controls the transcriptional termination of gene expression involved in sulfur metabolism in most bacteria, is an excellent ligand target. Thus, understanding its behavior with and without ligand complexes would be very helpful for drug design applications. In this manuscript, we studied the interactions between the SAM-I riboswitch and its natural ligand, SAM, which controls riboswitch function, and compared those interactions to its interactions with the very similar small molecular SAH, which does not control riboswitch function, and to its interactions with a potential binder JS4, identified via virtual screening. From our simulations, we gain a deeper understanding of small molecule interactions with the SAM-I riboswitch. The results reveal how differently the small molecules (SAM, SAH and JS4) bind to and potentially induce conformational changes in the riboswitch. Our findings offer valuable insight into the molecular mechanisms underlying riboswitch RNA-ligand interactions for the design of more effective RNA-targeting therapeutics.

The CRISPR-Cas9 system has revolutionized genome engineering, yet its full therapeutic potential remains constrained by challenges in precisely modulating its activity and specificity. Here we report a fully computational end-to-end pipeline for the de novo design of a single-domain VHH nanobody (NbSpCas9-v1) targeting a structurally conserved, non-catalytic epitope at the PAM-interacting (PI) and RuvC-III interface of Streptococcus pyogenes Cas9 (SpCas9; PDB: 4UN3). Nanobody sequences were generated using BoltzGen, a generative diffusion binder design framework, and co-folded with SpCas9 using Boltz-2 to evaluate structural confidence and binding affinity. The top-ranked model (SpCas9_4UN3_Bivalent_Hub_v1) achieved a complex pLDDT of 0.8406, an aggregate score of 0.8016, and an ipTM of >0.8, indicating high confidence in the nanobody-antigen interface. The designed 1,616-residue quaternary complex (SpCas9 + sgRNA + DNA + nanobody) was subjected to 10 ns of all-atom molecular dynamics (MD) simulation using the AMBER14SB force field within the GROMACS/OpenMM framework. The complex stabilized at RMSD [~]6 [A] with a radius of gyration of 39-44 [A], confirming thermodynamic stability under physiological conditions (310 K, 0.15 M NaCl). A conserved 96.3 [A] inter-molecular distance between the nanobody centroid and the HNH catalytic residue H840 establishes NbSpCas9-v1 as a distal, non-inhibitory binder -- ideally suited for a Bivalent Hub architecture recruiting secondary effectors to the Cas9 ribonucleoprotein (RNP). The nanobody-Cas9 interface is stabilized by 8 hydrogen bonds, 4 salt bridges, and [~]1,850 [A]2 of buried solvent-accessible surface area. These results provide a rigorous structural and dynamic foundation for experimental validation of VHH-based CRISPR-Cas9 enhancers and modulators. GRAPHICAL ABSTRACTThe computational workflow proceeds from SpCas9 crystal structure acquisition (PDB: 4UN3) through BoltzGen nanobody design, Boltz-2 structural co-folding, 10 ns explicit-solvent MD validation, and Bivalent Hub functional characterization. The PyMOL rendering below shows the full quaternary complex at atomistic resolution.

Rotavirus is a major cause of severe diarrheal disease in children under the age of five, with reduced vaccine effectiveness in low-resource settings causing substantial morbidity and mortality. In the absence of approved antiviral therapeutics, treatment is largely supportive, urging the need for targeted and precision-based interventions. VP4 protein plays an essential role in viral attachment, entry, and infectivity, making it a suitable target for targeted therapy. In this context, RNA interference is a specific method for inhibiting viral gene expression with its efficacy depending on sequence conservation, target accessibility, and compatibility with the RISC-loading machinery. In the present study, an integrative in silico approach was employed to design and evaluate siRNAs targeting conserved regions of the VP4 gene across six geographically diverse countries. Candidate siRNAs were screened using established design rules and regression-based scoring with off-target filtering. Three optimized siRNAs were further assessed through structural modeling, molecular docking, and molecular dynamics simulations to examine interactions with human Dicer, TRBP, and Argonaute-2. Comparative dynamic analyses identified one siRNA with enhanced structural compatibility, reduced conformational fluctuations, and stable interactions with RISC-loading proteins. These findings provide a rational computational basis for VP4-targeted siRNA development, facilitating experimental validation.

Bacteria can be engineered to express double-stranded RNA (dsRNA) that modulates eukaryotic host gene expression in a programmable manner via RNA interference (RNAi). This requires robust and systematic strategies for dsRNA circuit design and expression. Here, we developed modular genetic parts compatible with the CIDAR MoClo system for rapid assembly of dsRNA expression constructs in Escherichia coli HT115(DE3). We validated dsRNA production in vitro and assessed RNAi efficiency in Caenorhabditis elegans. A constitutive dsRNA circuit achieved rapid and near-complete gene knockdown, whereas a Ptac-driven circuit enabled tunable, partial silencing while minimizing the leakiness commonly observed in standard feeding RNAi systems. Together, this work expands the synthetic biology toolkit for dsRNA delivery, enabling precise control of RNAi outcomes from partial to complete gene silencing in nematodes.

Pigs and chickens are not only the most important livestock species for global food production but also serve as key model organisms in various research disciplines. The pig is widely used in translational research due to its anatomical and physiological similarity to humans, providing valuable insights into immunology, metabolism, and disease mechanisms. In contrast, the chicken has become an essential model for studies related to poultry health, animal welfare, and developmental biology. Its externally developing embryo offers exceptional accessibility for experimental manipulation. Recent advances in genome editing technologies, particularly CRISPR/Cas9, have further expanded the potential of these species for functional genomic studies, although the efficient delivery of such tools remains a major challenge. By using virus-like particles (VLPs), we have been able to overcome this limitation. Here, we evaluated VLPs as delivery vehicles for genome engineering tools in pigs and chickens, two key livestock species at the human-animal interface. VLP-mediated delivery enabled efficient Cre recombination and high CRISPR/Cas9 editing rates in porcine cells, organoids, and oocytes, particularly when multiplexed. In chickens, VLPs supported robust Cre recombination and Cas9-mediated editing in cell culture, tracheal organ cultures, and in ovo. Reporter VLPs and dCas9 VLPs further demonstrated the versatility of this platform across porcine and avian systems. Together, these findings establish VLPs as an efficient and time-saving strategy for gene editing in livestock, with relevance for animal health, agricultural productivity, and translational One Health research.

Antimicrobial peptides (AMPs) are emerging as promising alternatives to conventional antibiotics, and growing evidence indicates a fundamental link between antimicrobial activity and amyloid-like self-assembly. Many AMPs are known to form amyloid-like fibrils, while several amyloidogenic peptides exhibit intrinsic antimicrobial properties, suggesting shared underlying physicochemical determinants such as amphipathicity, {beta}-sheet propensity, and charge distribution. However, the rational design of peptides that simultaneously encode these dual functionalities remains a significant challenge. Here, we present amyAMP, a generative deep-learning framework based on a Wasserstein generative adversarial network with gradient penalty (WGAN-GP), designed to learn and generate peptides with integrated antimicrobial and amyloidogenic properties. Trained on curated datasets of antimicrobial and amyloid-forming peptides, amyAMP captures the latent sequence-property relationships governing dual functionality. Statistical and latent-space analyses demonstrate that the generated peptides closely overlap with biologically relevant peptide space while remaining distinct from random sequences, indicating successful learning of key biochemical features. To validate functional behavior, we performed extensive coarse-grained molecular dynamics simulations to probe membrane interaction, peptide self-assembly, and membrane disruption. The simulations reveal rapid membrane adsorption, stable amphipathic insertion, and strong peptide-peptide aggregation. Notably, cooperative clustering of peptides on membrane surfaces induces membrane thinning and curvature perturbations, highlighting a mechanistic coupling between aggregation and antimicrobial activity. Collectively, these results establish that amyAMP effectively captures the shared physicochemical principles underlying antimicrobial action and amyloid-like self-assembly. This work provides a generalizable framework for the AI-guided design of multifunctional peptides to advance the development of next-generation therapeutics targeting antimicrobial resistance.

Osmotic pressure has been known to play essential roles in living systems from single cells to complex tissues. However, direct in-situ measurements of osmotic pressures in biosystems have remained challenging, especially in complicated heterogeneous systems in which osmotic pressure gradients could exist and induce directed forces. Bacterial biofilms -- organized communities of bacteria encased in a self-produced extracellular matrix -- are a major mode of bacterial life. It has, however, remained unexplored how the osmotic pressure is distributed in the biofilm and how this distribution contributes to biofilm growth and activity. Here, liposomal nano-sensors are developed for the in-situ mapping of osmotic pressures at an unprecedented microscale resolution in real time using Escherichia coli. biofilm as a model system that develops at the surface of a hydrogel containing the nutrients. The measurements reveal osmotic pressure gradients with a radially increasing trend from the inner regions to the outer regions of the biofilm, which is associated with biofilm formation, morphology, and metabolism. The gradients likely contribute to mechanical properties, internal stresses, and nutrient transport. The sensor readouts also show that there is an osmotic pressure difference between the biofilm and the adjacent medium, which may promote biofilm expansion through matrix swelling and bacteria growth via water and nutrient uptake from the surroundings. Our novel approach based on in-situ osmotic pressure mapping in a growing biofilm reveals a sophisticated spatial regulation of physical forces, which may inspire new models and approaches in the field of mechanobiology.

Nanoplastics generated from plastic waste in our ecosystems are becoming increasingly prevalent as bulk plastics exposed to natural factors like water and sunlight fragment to the nanoscale over time. These incidental nanoplastics span a wide range of physicochemical properties, which makes studying nanoplastic interactions in biological systems difficult. Here, we characterized the behavior of incidental nanoplastics generated through mechanical abrasion within coacervate droplets to probe the surface properties of the nanoplastics. We used elastin-like polypeptides (ELPs) to create hydrophobic or charged coacervate microenvironments. Using optical microscopy and fluorescence quantification, we observed that nanoplastics made from polyethylene terephthalate (nPET), nylon 6 (nPA), and polystyrene (nPS) exhibited distinct partitioning behavior with more favorable interactions with hydrophobic droplets. This indicated that the hydrophobic polymer backbone was the predominate surface feature despite exposed functional groups of the incidental nanoplastics, in contrast to findings with model carboxylated latex nanospheres (nPS-COOH). Furthermore, the selective partitioning of incidental nanoplastics into the hydrophobic droplets was able to capture over 80% of nPET in solution, and after recovery of the protein droplet, was able to cumulatively capture over 75% of the nPET feedstock across multiple cycles. This work explores the nuanced surface characteristics of incidental nanoplastics, expands the application of coacervates as chemical probes, and demonstrates a biopolymer approach for effective nanoplastic removal.

G-quadruplexes (G4s) are critical nucleic acid secondary structures that play pivotal roles in regulating gene expression. In this study, we conducted a proteome-wide in silico analysis across multiple viruses causing hemorrhagic fevers to identify candidate proteins containing a conserved G4-binding motif. Four peptides belonging to Marburg, Ebola, Hantaan and Yellow fever viruses were shown to bind to G4 in vitro. We selected the NS3 protease domain of Yellow Fever virus for further validation. Biochemical assays demonstrated that the NS3 protease domain binds G4 structures with high specificity and affinity, particularly favoring the parallel conformation. Molecular docking and simulations further revealed that the NS3 protease domain interacts with the terminal G-tetrads and loop regions of G4 via key residues, including PHE40, adopting an insertion and stacking composite binding mode. These findings expand our understanding of virus - G4 interactions and offer novel potential targets for G4-based antiviral strategies. Bullet points- We screened viruses causing hemorrhagic fevers for potential G4-binding peptides. - Four peptides belonging to Marburg, Ebola, Hantaan and Yellow fever viruses were shown to bind to G4 in vitro. - Biochemical assays demonstrated that the NS3 protease domain of YFV binds G4 structures with high specificity and affinity.

Microneedle (MN) patches have emerged as a highly efficient platform for localized drug delivery, showing great promise in cancer therapy due to their ability to enable precise drug administration. However, conventional MN systems are limited by the low drug-loading capacity of their tips and primarily rely on biologically inert, non-therapeutic matrices for structural support, which restricts further gains in antitumor efficacy. Herein, we present a strategy turning toxicity into therapy by constructing palladium nanoparticle-loaded polyvinyl alcohol/polyethyleneimine (PVA/PEI@Pd) hydrogel microneedles (PPPd-MNs), which exploit the intrinsic cytotoxicity of PEI for synergistic melanoma therapy. The PPPd-MNs efficiently catalyze the deprotection of a doxorubicin prodrug (P-DOX), enabling in situ generation of active doxorubicin (DOX). Notably, the PEI matrix serves a dual function: acting as a robust ligand to stabilize Pd catalysts and functioning as a therapeutic agent that disrupts cancer cell membranes. Both in vitro and in vivo experiments demonstrate that the combination of Pd-mediated bioorthogonal activation of DOX and PEI-induced membrane damage achieves a remarkable synergistic therapeutic outcome in a murine melanoma model, resulting in a tumor inhibition rate of up to 98%. This work repurposes the inherent cytotoxicity of the carrier material as an active therapeutic component, offering a novel paradigm for the design of high-performance bioorthogonal catalytic systems.

We present a proof-of-concept platform in which amyloids are displayed on the surface of engineered Bacillus subtilis spores for bioengineered materials. Amyloids possess high tensile strength, elasticity, and tunable assembly, but their use is limited by inaccessible native sources and low-yield or toxic heterologous expression. Here, spores were engineered to display the native amyloid TasA and Humboldt squid suckerins 9 and 10 as fusions to the spore coat protein CotY. Amyloid production and fibril formation were confirmed by Western blot and X-34 staining, and quantitative analysis indicated mg/L-level yields. Atomic force microscopy revealed altered stiffness and surface ultrastructure, and incorporation of amyloid-displaying spores into resin-based 3D printing modified tensile strength. These findings highlight spore-based amyloid display as a scalable, modular platform for materials applications, leveraging established industrial spore production.

Microplastic (MP) pollution, which is present in the ecosystem in vast quantities, adversely affects human health and the environment, making it imperative to develop methods for its mitigation. The challenge of detecting or capturing MPs could potentially be addressed using plastic-binding peptides (PBPs). The ideal PBP for MP remediation would not only bind strongly to plastic, but also have other properties such as high solubility in water or great binding specificity to a certain plastic. However, the scarcity or absence of known PBPs for common plastics along with the lack of methods that can discover PBPs with all of the desired properties precludes the development of peptide-based MP remediation strategies. In this study, we discovered short linear PBPs with high predicted water solubility and binding specificity by employing an in-silico discovery pipeline that combines deep learning and biophysical modeling. First, a long short-term memory (LSTM) network was trained on biophysical modeling data to predict peptide affinity to plastic. High affinity peptides were generated by pairing the trained LSTM with a Monte Carlo tree search (MCTS) algorithm. Molecular dynamics (MD) simulations showed that the PBPs discovered for polyethylene, the most common plastic, had 15% lower binding free energy than PBPs obtained using biophysical modeling alone. PBPs with both high affinity and high predicted solubility in water were found by including the CamSol solubility score in the MCTS peptide scoring function, increasing the average solubility score from 0.2 to 0.9, while only minimally decreasing affinity for polyethylene. The framework also discovered peptides with high binding specificity between polystyrene and polyethylene, two major constituents of MP pollution, using a competitive MCTS approach that optimized the difference in affinity between the two plastics. MD simulations showed that competitive MCTS increased the binding specificity of PBPs for polystyrene and identified peptides with relatively great preference for either of the two plastics. The framework can readily be applied to design PBPs for other types of plastic. Overall, the high-affinity PBPs with desirable properties discovered by marrying artificial intelligence and biophysics can be valuable for remediating MP pollution and protecting the health of humans and the environment.

Angiogenesis, the process by which new blood vessels form from existing vasculature, is fundamental to tissue repair and regeneration but also underlies pathological conditions such as cancer progression. Targeting angiogenesis has thus become a promising approach for developing novel cancer therapeutics. While various phytochemicals have demonstrated anti-angiogenic effects, the role of 2-5(H)-Furanone, a naturally occurring lactone found in various plants and marine sources with diverse biological activities, remains insufficiently explored. In this study, we systematically evaluate the anti-angiogenic potential of 2-5(H)-Furanone using Human Umbilical Vein Endothelial Cells (HUVECs) as an in vitro model and zebrafish embryos as an in vivo model. Experimental findings demonstrated that treatment of HUVECs with increasing concentrations of 2-5(H)-Furanone led to significant, dose-dependent reductions in proliferation, invasion, migration, and tube formation. Analyses of gene expression revealed marked downregulation of key pro-angiogenic mediators, VEGF, and HIF-1. Complementing these in vitro results, in vivo studies in zebrafish embryos showed robust, dose-dependent inhibition of intersegmental vessel (ISV) formation, accompanied by suppression of critical angiogenesis-related genes. Molecular docking further supported these observations by indicating stable binding of 2-5(H)-Furanone to major angiogenic targets, including VEGFR2, MMP2, HIF-1, and PIK3CA. Collectively, our data demonstrate that 2-5(H)-Furanone potently inhibits angiogenesis, as evidenced in both HUVEC and zebrafish models, through functional and molecular mechanisms. These findings support the further development of 2-5(H)-Furanone as a promising anti-angiogenic therapy candidate.

The glucagon-like peptide-1 receptor (GLP-1R) plays a central role in metabolic regulation and is a major therapeutic target for obesity and diabetes. Peptide agonists, like semaglutide, targeting the GLP-1R remain among the most effective regulators of glucose metabolism and appetite. Nonetheless, recent reports about weight regain have limited the effectiveness of GLP1R peptide agonists, sustaining the interest in expanding the chemical diversity of GLP-1R ligands through drug discovery strategies. However, the structural complexity and conformational plasticity of class B1 GPCRs make conventional single-method virtual screening approaches prone to bias and limited chemotype recovery. Using an integrated ligand- and structure-based virtual screening pipeline, explicitly combining complementary ligand-based descriptors, multi-fingerprint similarity, electrostatic similarity, pharmacophore modeling, and multi-conformation docking under a consensus-driven selection strategy, we were able to identify three chemically distinct classes of GLP-1R agonist candidates: GQB47810, a non-peptidic molecule; neuromedin C, a peptide, and 2,5-Pen-enkephalin (DPDPE), a small peptide. From all of them, DPDPE showed the greatest effectiveness, reaching values similar to those of GLP-1, although with lower potency. Further in vitro characterization confirmed that pen-enkephalin behaved as a full agonist and exhibited dual GLP-1R/GIPR agonistic activity. These findings establish a consensus-driven and transferable computational framework for chemotype-diverse agonist discovery at conformationally flexible GPCR targets, and revealed a pentapeptide with GLP-1-like efficacy as a promising lead for next-generation small peptide therapeutics.

The scalable fabrication of stable colloidosomes with controlled permeability and defined multicompartmental architecture remains a critical challenge, limiting their broader use in molecular delivery and environmental remediation. Here, we develop a hybrid lipid-metal-organic framework (lipid-MOF) colloidosome assembled through an interfacial emulsification strategy that integrates the structural rigidity of ZIF-8 particles with lipid-mediated membrane stabilization. During assembly, ZIF-8 particles accumulate at the oil-water interface to form a shell, producing hollow micron-sized spherical colloidosomes. The resulting colloidosomes exhibit excellent colloidal stability in aqueous media for over 30 days with a zeta potential of approximately -50 mV. Nitrogen adsorption measurements reveal a surface area of 45 m2g-1 and an average pore width of 4 nm. Fluorescence imaging shows that hydrophobic Nile red preferentially partitions into the colloidosomal membrane, whereas hydrophilic fluorescein isothiocyanate (FITC) localize predominantly within the aqueous interior, enabling simultaneous encapsulation of molecules with contrasting polarity with loading efficiencies approaching 90%. Furthermore, the colloidosomes demonstrate rapid removal of model pollutants from water, achieving >90% removal of methylene blue and metal ions without stirring. Together, these results introduce lipid-MOF colloidosomes as a new class of hybrid platforms that unify structural stability, multicompartmental encapsulation, and efficient adsorption behavior, opening pathways toward sustainable platforms for drug delivery and environmental bioremediation.

Ubiquitin-like protein 3 (UBL3) is a post-translational modifier that sorts proteins into small extracellular vesicles and regulates the trafficking of disease-associated proteins such as -synuclein. The structural and dynamic features of the UBL domain that underlie these functions, however, remain poorly understood. Here we performed in silico structural dynamics analysis of the UBL3 UBL domain using an NMR structure ensemble combined with anisotropic network modeling (ANM) and perturbation response scanning (PRS). Principal component analysis and residue-wise fluctuation analysis consistently revealed high flexibility in the C-terminal region of UBL3. Comparative ANM analysis across 20 ubiquitin-like proteins (UBLs) further showed that C-terminal flexibility is a conserved yet variable property within the UBL family. PRS analysis demonstrated that residues forming the central -helix of the {beta}-grasp fold exert greater dynamic control over collective motions than {beta}-sheet residues. Notably, UBL3 displayed the highest helix/sheet PRS effectiveness ratio among all UBLs analyzed, highlighting the prominent dynamic contribution of helix residues in this domain. Together, these results provide a structural basis for understanding UBL3-dependent protein interactions and disease-related mechanisms, and suggest that helix-centered dynamic control in the UBL domain may represent a potential target for modulating UBL3 function.

Hydrogels are increasingly recognized as promising therapeutics for arthritic joints, extending their traditional role as mechanical lubricants to modulators of joint immunity. However, the rational design of these materials remains challenging, with progress largely driven by empirical experimentation. To address this, we curated a comprehensive database of 220 hydrogel formulations from 317 published studies and applied an interpretable machine learning (ML) framework to uncover the relationships between hydrogel design parameters and the arthritis severity score. Using a Random Forest algorithm, our model achieved an external validation accuracy of 0.67 in predicting effective hydrogel therapies for arthritis. Analysis revealed a clear hierarchy of design principles: the choice of functional agent, base polymer, and elastic modulus were the most influential predictors of therapeutic efficacy, with composite agents, protein-based polymers, and softer hydrogels most strongly associated with positive therapeutic outcomes. Mechanistic investigations further demonstrated that successful hydrogels promote an anti-inflammatory M2 macrophage phenotype. Benchmarking against classical statistical methods and a large language model framework showed that our ML approach provided more robust, nuanced insights into complex feature interactions. This data-driven framework offers a generalizable blueprint for the rational design of next-generation immunomodulatory hydrogels, paving the way for more effective arthritis therapies.

Single molecule methods have become prevalent tools in elucidating molecular processes across various life science fields over the past three decades, driving breakthroughs in understanding their underlying molecular mechanisms. In our study, we employed two single-molecule methods, Forster Resonance Energy Transfer (smFRET) and high-resolution optical tweezers, to investigate the transcription of Mycobacterium tuberculosis RNA polymerase (MtbRNAP) from initiation through to termination. We aim to provide a set of comprehensive biophysical tools to deepen our current understanding of MtbRNAP and its transcription factors. These experimental assays represent an important step towards unraveling the molecular dynamics and interactions that support transcription in Mycobacterium tuberculosis.