Topology, dynamics, and control of a muscle-architected soft arm.

Muscular hydrostats, such as octopus arms or elephant trunks, lack bones entirely, endowing them with exceptional dexterity and reconfigurability. Key to their unmatched ability to control nearly infinite degrees of freedom is the architecture into which muscle fibers are weaved. Their arrangement is, effectively, the instantiation of a sophisticated mechanical program that mediates, and likely facilitates, the control and realization of complex, dynamic morphological reconfigurations. Here, by combining medical imaging, biomechanical data, live behavioral experiments, and numerical simulations, an octopus-inspired arm made of [Formula: see text]200 continuous muscle groups is synthesized, exposing "mechanically intelligent" design and control principles broadly pertinent to dynamics and robotics. Such principles are mathematically understood in terms of storage, transport, and conversion of topological quantities, effected into complex 3D motions via simple muscle activation templates. These are in turn composed into higher-level control strategies that, compounded by the arm's compliance, are demonstrated across challenging manipulation tasks, revealing surprising simplicity and robustness.

Computational targeting of iron uptake proteins in Covid-19 induced mucormycosis to identify inhibitors via molecular dynamics, molecular mechanics and density function theory studies.

Mucormycosis is a concerning invasive fungal infection with difficult diagnosis, high mortality rates, and limited treatment options. Iron availability is crucial for fungal growth that causes this disease. This study aimed to computationally target iron uptake proteins in Rhizopus arrhizus, Lichtheimia corymbifera, and Mucor circinelloides to identify inhibitors, thereby halting fungal growth and intervening in mucormycosis pathogenesis. Seven important iron uptake proteins were identified, modeled, and validated using Ramachandran plots. An in-house antifungal library of ~ 15,401 compounds was screened in molecular docking studies with these proteins. The best small molecule-protein complexes were simulated at 100 ns using Maestro, Schrodinger. Toxicity predictions suggested all six molecules, identified as the best binding compounds to seven proteins, belonged to lower toxicity levels per GHS classification. A molecular mechanics GBSA study for all seven complexes indicated low standard deviations after calculating free binding energies every 10 ns of the 100 ns trajectory. Density functional theory via quantum mechanics approaches highlighted the HOMO, LUMO, and other properties of the six best-bound molecules, revealing their binding capabilities and behaviour. This study sheds light on the molecular mechanisms and protein-ligand interactions, providing a multi-dimensional view towards the use of FDBD01920, FDBD01923, and FDBD01848 as stable antifungal ligands. Supplementary Information: The online version contains supplementary material available at 10.1007/s40203-024-00264-7.

Competition between cross-linking and force-induced local conformational changes determines the structure and mechanics of labile protein networks.

Folded protein hydrogels are emerging as promising new materials for medicine and healthcare applications. Folded globular proteins can be modelled as colloids which exhibit site specific cross-linking for controlled network formation. However, folded proteins have inherent mechanical stability and unfolded in response to an applied force. It is not yet understood how colloidal network theory maps onto folded protein hydrogels and whether it models the impact of protein unfolding on network properties. To address this, we study a hybrid system which contains folded proteins (patchy colloids) and unfolded proteins (biopolymers). We use a model protein, bovine serum albumin (BSA), to explore network architecture and mechanics in folded protein hydrogels. We alter both the photo-chemical cross-linking reaction rate and the mechanical properties of the protein building block, via illumination intensity and redox removal of robust intra-protein covalent bonds, respectively. This dual approach, in conjunction with rheological and structural techniques, allows us to show that while reaction rate can 'fine-tune' the mechanical and structural properties of protein hydrogels, it is the force-lability of the protein which has the greatest impact on network architecture and rigidity. To understand these results, we consider a colloidal model which successfully describes the behaviour of the folded protein hydrogels but cannot account for the behaviour observed in force-labile hydrogels containing unfolded protein. Alternative models are needed which combine the properties of colloids (folded proteins) and biopolymers (unfolded proteins) in cross-linked networks. This work provides important insights into the accessible design space of folded protein hydrogels without the need for complex and costly protein engineering, aiding the development of protein-based biomaterials.

The Molecular Mechanism of Macrophages in Response to Mechanical Stress.

Macrophages, a type of functionally diversified immune cell involved in the progression of many physiologies and pathologies, could be mechanically activated. The physical properties of biomaterials including stiffness and topography have been recognized as exerting a considerable influence on macrophage behaviors, such as adhesion, migration, proliferation, and polarization. Recent articles and reviews on the physical and mechanical cues that regulate the macrophage's behavior are available; however, the underlying mechanism still deserves further investigation. Here, we summarized the molecular mechanism of macrophage behavior through three parts, as follows: (1) mechanosensing on the cell membrane, (2) mechanotransmission by the cytoskeleton, (3) mechanotransduction in the nucleus. Finally, the present challenges in understanding the mechanism were also noted. In this review, we clarified the associated mechanism of the macrophage mechanotransduction pathway which could provide mechanistic insights into the development of treatment for diseases like bone-related diseases as molecular targets become possible.

Modification of MM force fields around heme-Fe in the CYP-ligand complex and ab initio FMO calculations for the complex.

Cytochrome P450 (CYP) enzymes play essential roles in the synthesis and metabolic activation of physiologically active substances. CYP has a prosthetic heme (iron protoporphyrin IX) in its active center, where Fe ion (heme-Fe) is deeply involved in enzymatic reactions of CYP. To precisely describe the structure and electronic states around heme-Fe, we modified the force fields (FFs) around heme-Fe in molecular mechanics (MM) simulations and conducted ab initio fragment molecular orbital (FMO) calculations for the CYP-ligand complex. To describe the coordination bond between heme-Fe and its coordinated ligand (ketoconazole), we added FF between heme-Fe and the N atom of ketoconazole, and then the structure of the complex was optimized using the modified FF. Its adequacy was confirmed by comparing the MM-optimized structure with the X-ray crystal one of the CYP-ketoconazole complex. We also performed 100 ns molecular dynamics simulations and revealed that the coordination bonds around heme-Fe were maintained even at 310 K and that the CYP-ketoconazole structure was kept similar to the X-ray structure. Furthermore, we investigated the electronic states of the complex using the ab initio FMO method to identify the CYP residues and parts of ketoconazole that contribute to strong binding between CYP and ketoconazole. The present procedure of constructing FF between heme-Fe and ketoconazole can be applicable to other CYP-ligand complexes, and the modified FF can provide their accurate structures useful for predicting the specific interactions between CYP and its ligands.

Vitreous Tissue Cryopreservation Using a Blood Vessel Model and Cryomacroscopy for Scale-Up Studies: Observations and Mathematical Modeling.

Successful long term cryobanking of multicellular tissues and organs at deep subzero temperatures calls for the avoidance of ice cryoinjury by reliance upon ice-free cryopreservation techniques. However, the quality of the cryopreserved material is the direct result of its ability to survive a host of harmful mechanisms, chief among which is overcoming the trifecta effects of ice crystallization, toxicity, and mechanical stress. This study aims at exploring improved conditions to scale-up ice-free cryopreservation by combining DP6 as a base cryoprotective agent (CPA) solution with an array of synthetic ice modulators (SIMs). This study is conducted by integrating cryomacroscopy techniques, thermal modeling, solid mechanics analysis, and viability and contractility investigation to correlate physical effects, thermal outcomes, and cryobiology results. As an extension of previous work, this study aims at scale-up of established baseline blood vessel models, while comparing the relative toxicity and vitreous stability of 4ml and 10ml samples of DP6 containing either sucrose as a SIM, or the commercial synthetic ice blockers (X1000 and Z1000). Using that established protocol, the addition and removal of DP6+0.6M sucrose and DP6+1%X1000+1%Z1000 were both well tolerated in rabbit carotid and pig femoral artery models, when assessed for metabolic recovery and contractility. Using cryomacroscopy, it was demonstrated that DP6+0.6M sucrose provided a stable vitrification medium under marginal cooling and warming conditions that resulted in >50% survival rate. By contrast, DP6+1%X1000+1%Z1000 was subject to visible ice formation during cooling under the same thermal conditions, resulting in a significantly lower recovery of ∼20%. Thermal modeling is used in this study to verify the actual cooling and rewarming rates in the specimens, while thermo-mechanics analysis is used to explain why fractures were observed using cryomacroscopy when the specimens were contained in glass vials but not in plastic vials.

Multiscale Fiber Remodeling in the Infarcted Left Ventricle using a Stress-Based Reorientation Law.

The organization of myofibers and extra cellular matrix within the myocardium plays a significant role in defining cardiac function. When pathological events occur, such as myocardial infarction (MI), this organization can become disrupted, leading to degraded pumping performance. The current study proposes a multiscale finite element (FE) framework to determine realistic fiber distributions in the left ventricle (LV). This is achieved by implementing a stress-based fiber reorientation law, which seeks to align the fibers with local traction vectors, such that contractile force and load bearing capabilities are maximized. By utilizing the total stress (passive and active), both myofibers and collagen fibers are reoriented. Simulations are conducted to predict the baseline fiber configuration in a normal LV as well as the adverse fiber reorientation that occurs due to different size MIs. The baseline model successfully captures the transmural variation of helical fiber angles within the LV wall, as well as the transverse fiber angle variation from base to apex. In the models of MI, the patterns of fiber reorientation in the infarct, border zone, and remote regions closely align with previous experimental findings, with a significant increase in fibers oriented in a left-handed helical configuration and increased dispersion in the infarct region. Furthermore, the severity of fiber reorientation and impairment of pumping performance both showed a correlation with the size of the infarct. The proposed multiscale modeling framework allows for the effective prediction of adverse remodeling and offers the potential for assessing the effectiveness of therapeutic interventions in the future. STATEMENT OF SIGNIFICANCE: The organization of muscle and collagen fibers within the heart plays a significant role in defining cardiac function. This organization can become disrupted after a heart attack, leading to degraded pumping performance. In the current study, we implemented a stress-based fiber reorientation law into a computer model of the heart, which seeks to realign the fibers such that contractile force and load bearing capabilities are maximized. The primary goal was to evaluate the effects of different sized heart attacks. We observed substantial fiber remodeling in the heart, which matched experimental observations. The proposed computational framework allows for the effective prediction of adverse remodeling and offers the potential for assessing the effectiveness of therapeutic interventions in the future.

Improving predictions of rock tunnel squeezing with ensemble Q-learning and online Markov chain.

Predicting rock tunnel squeezing in underground projects is challenging due to its intricate and unpredictable nature. This study proposes an innovative approach to enhance the accuracy and reliability of tunnel squeezing prediction. The proposed method combines ensemble learning techniques with Q-learning and online Markov chain integration. A deep learning model is trained on a comprehensive database comprising tunnel parameters including diameter (D), burial depth (H), support stiffness (K), and tunneling quality index (Q). Multiple deep learning models are trained concurrently, leveraging ensemble learning to capture diverse patterns and improve prediction performance. Integration of the Q-learning-Online Markov Chain further refines predictions. The online Markov chain analyzes historical sequences of tunnel parameters and squeezing class transitions, establishing transition probabilities between different squeezing classes. The Q-learning algorithm optimizes decision-making by learning the optimal policy for transitioning between tunnel states. The proposed model is evaluated using a dataset from various tunnel construction projects, assessing performance through metrics like accuracy, precision, recall, and F1-score. Results demonstrate the efficiency of the ensemble deep learning model combined with Q-learning-Online Markov Chain in predicting surrounding rock tunnel squeezing. This approach offers insights into parameter interrelationships and dynamic squeezing characteristics, enabling proactive planning and support measures implementation to mitigate tunnel squeezing hazards and ensure underground structure safety. Experimental results show the model achieves a prediction accuracy of 98.11%, surpassing individual CNN and RNN models, with an AUC value of 0.98.

Expiratory flow limitation development index (ELDI): a novel method of assessing respiratory mechanics in COPD.

BACKGROUND: Expiratory flow limitation (EFL) can be detected using oscillometric reactance and is associated with a worse clinical presentation in chronic obstructive pulmonary disease (COPD). Reactance can show negative swings upon exhalation, which may develop at different rates between patients. We propose a new method to quantify the rate of EFL development; the EFL Development Index (ELDI). METHODS: A retrospective analysis of data from 124 COPD patients was performed. Data included lung function tests, Impulse Oscillometry (IOS), St Georges Respiratory Questionnaire (SGRQ), modified Medical Research Council (mMRC) scale and COPD Assessment Test (CAT) score. Fifty four patients had repeat data after 6 months. Twenty two patients had data recorded after 5 days of treatment with long acting bronchodilator therapy. EDLI was calculated as the mean expiratory reactance divided by the minimum expiratory reactance. RESULTS: The mean ELDI was used to categorise patients with rapid onset of EFL (> 0.63; n = 29) or gradual onset (≤ 0.63; n = 34). Those with rapid development had worse airflow obstruction, lower quality of life scores, and greater resting hyperinflation, compared to those with gradual development. In patients with EFL, ELDI correlated with symptoms scores, airflow obstruction, lung volumes and gas diffusion. Both EFL and ELDI were stable over 6 months. EFL and EDLI improved with bronchodilator treatment. CONCLUSIONS: COPD patients with rapid EFL development (determined by ELDI) had worse clinical characteristics than those with gradual EFL development. The rate of EFL development appears to be associated with clinical and physiological characteristics.

The Exploration of Ink Formulations in Binder Jet 3D Printing Drugs.

The application of binder jet 3D printing technology in the pharmaceutical field is developing rapidly. The properties of the ink are very important, affecting the stability of the ejection and the precision of the finished product, but there is a great lack of research on pharmaceutical inks. This study used solvents and excipients commonly used in pharmaceuticals to quantify the printability of inks using printability Z value theory, while using an ink-jet printing and observation platform to analyze the droplet ejection state of different composition inks from microscopic level. Studies have shown that compared to ethanol, the ejection effect of droplets was better when isopropanol was added to the ink, and the proportion added should not be greater than 40%; as the molecular weight of polyvinylpyrrolidone (PVP) increased, the concentration of PVP tolerated by the ink decreased; glycerin has a high ejection efficiency when the proportion is within 10%. In summary, a superior ink formulation of 40% aqueous isopropanol plus 0.1% PVP K30 and 4% glycerin was obtained. With this ink, levetiracetam dispersible tablets were prepared with a smooth printing process and the tablets had good appearance, good mechanical properties, and rapid release. This study provides a mutual validation of the Z value theory and the results of droplet ejection and tablet printing, while providing good ideas.