Crowded Environment Research Articles

Kinetic Study of the Esterase-like Activity of Albumin following Condensation by Macromolecular Crowding.

The ability of bovine serum albumin (BSA) to form condensates in crowded environments has been discovered only recently. Effects of this condensed state on the secondary structure of the protein have already been unraveled as some aging aspects, but the pseudo-enzymatic behavior of condensed BSA has never been reported yet. This article investigates the kinetic profile of para-nitrophenol acetate hydrolysis by BSA in its condensed state with poly(ethylene) glycol (PEG) as the crowding agent. Furthermore, the initial BSA concentration was varied between 0.25 and 1 mM which allowed us to modify the size distribution, the volume fraction, and the partition coefficient (varying from 136 to 180). Hence, the amount of BSA originally added was a simple way to modulate the size and density of the condensates. Compared with dilute BSA, the initial velocity (vi) with condensates was dramatically reduced. From the Michaelis-Menten fits, the extracted Michaelis constant Km and the maximum velocity Vmax decreased in control samples without condensates when the BSA concentration increased, which was attributed to BSA self-oligomerization. In samples containing condensates, the observed vi was interpreted as an effect of diluted BSA remaining in the supernatants and from the condensates. In supernatants, the crowding effect of PEG increased the kcat and catalytic efficiency. Last, Vmax was proportional to the volume fraction of the condensates, which could be controlled by varying its initial concentration. Hence, the major significance of this article is the control of the size and volume fraction of albumin condensates, along with their kinetic profile using liquid-liquid phase separation.

Global-Position Tracking Control for Multi-Domain Bipedal Walking with Underactuation

Abstract Accurate control of a humanoid robot's global position (i.e., its three-dimensional position in the world) is critical to the reliable execution of high-risk tasks such as avoiding collision with pedestrians in a crowded environment. This paper introduces a time-based nonlinear control method that achieves accurate global-position tracking (GPT) for multi-domain bipedal walking. Deriving a tracking controller for bipedal robots is challenging due to the highly complex robot dynamics that are time-varying and hybrid, especially for multi-domain walking that involves multiple phases/domains of full actuation, over actuation, and underactuation. To tackle this challenge, we introduce a continuous-phase GPT control law for multi-domain walking, which provably ensures the exponential convergence of the entire error state within the full and over actuation domains and that of the directly regulated error state within the underactuation domain. We then construct sufficient multiple-Lyapunov stability conditions for the hybrid multi-domain tracking error system under the proposed GPT control law. We illustrate the proposed controller design through both three-domain walking with all motors activated and two-domain gait with inactive ankle motors. Simulations of a ROBOTIS OP3 bipedal humanoid robot demonstrate the satisfactory accuracy and convergence rate of the proposed control approach under two different cases of multi-domain walking as well as various walking speeds and desired paths.

Size Sensitivity of Metabolite Diffusion in Macromolecular Crowds.

Metabolites play crucial roles in cellular processes, yet their diffusion in the densely packed interiors of cells remains poorly understood, compounded by conflicting reports in existing studies. Here, we employ pulsed-gradient stimulated-echo NMR and Brownian/Stokesian dynamics simulations to elucidate the behavior of nano- and subnanometer-sized tracers in crowded environments. Using Ficoll as a crowder, we observe a linear decrease in tracer diffusivity with increasing occupied volume fraction, persisting─somewhat surprisingly─up to volume fractions of 30-40%. While simulations suggest a linear correlation between diffusivity slowdown and particle size, experimental findings hint at a more intricate relationship, possibly influenced by Ficoll's porosity. Simulations and numerical calculations of tracer diffusivity in the E. coli cytoplasm show a nonlinear yet monotonic diffusion slowdown with particle size. We discuss our results in the context of nanoviscosity and discrepancies with existing studies.

Polyethylene Glycol Impacts Conformation and Dynamics of Escherichia coli Prolyl-tRNA Synthetase Via Crowding and Confinement Effects.

Polyethylene glycol (PEG) is a flexible, nontoxic polymer commonly used in biological and medical research, and it is generally regarded as biologically inert. PEG molecules of variable sizes are also used as crowding agents to mimic intracellular environments. A recent study with PEG crowders revealed decreased catalytic activity of Escherichia coli prolyl-tRNA synthetase (Ec ProRS), where the smaller molecular weight PEGs had the maximum impact. The molecular mechanism of the crowding effects of PEGs is not clearly understood. PEG may impact protein conformation and dynamics, thus its function. In the present study, the effects of PEG molecules of various molecular weights and concentrations on the conformation and dynamics of Ec ProRS were investigated using a combined experimental and computational approach including intrinsic tryptophan fluorescence spectroscopy, atomic force microscopy, and atomistic molecular dynamic simulations. Results of the present study suggest that lower molecular weight PEGs in the dilute regime have modest effects on the conformational dynamics of Ec ProRS but impact the catalytic function primarily via the excluded volume effect; they form large clusters blocking the active site pocket. In contrast, the larger molecular weight PEGs in dilute to semidilute regimes have a significant impact on the protein's conformational dynamics; they wrap on the protein surface through noncovalent interactions. Thus, lower-molecular-weight PEG molecules impact protein dynamics and function via crowding effects, whereas larger PEGs induce confinement effects. These results have implications for the development of inhibitors for protein targets in a crowded cellular environment.

Enabling High Activation of Glucose-6-Phosphate Dehydrogenase Activity Through Liquid Condensate Formation and Compression.

Droplet formation via liquid-liquid phase separation is thought to be involved in the regulation of various biological processes, including enzymatic reactions. We investigated a glycolytic enzymatic reaction, the conversion of glucose-6-phosphate to 6-phospho-D-glucono-1,5-lactone with concomitant reduction of NADP+ to NADPH both in the absence and presence of dynamically controlled liquid droplet formation. Here, the nucleotide serves as substrate as well as the scaffold required for the formation of liquid droplets. To further expand the process parameter space, temperature and pressure dependent measurements were performed. Incorporation of the reactants in the liquid droplet phase led to a boost in enzymatic activity, which was most pronounced at medium-high pressures. The crowded environment of the droplet phase induced a marked increase of the affinity of the enzyme and substrate. An increase in turnover number in the droplet phase at high pressure contributed to a further strong increase in catalytic efficiency. Enzyme systems that are dynamically coupled to liquid condensate formation may be the key to deciphering many biochemical reactions. Expanding the process parameter space by adjusting temperature and pressure conditions can be a means to further increase the efficiency of industrial enzyme utilization and help uncover regulatory mechanisms adopted by extremophiles.

The Design of the External Space of a Neigh Bour Hood Commercial Complex Based on Urban Sharing

As urbanization accelerates and the scale and density of urban population grows rapidly, there is a contradiction between the increasing shortage of urban land resources and the significant reduction in the area of public space per capita in cities, and the increasing demand for a high quality of life and public interaction. Therefore, in an increasingly crowded urban environment, the creation of a commercial external space that is shared with the city and has the attributes of an urban public space becomes the key to this study. Through a comprehensive survey of the current situation of commercial complexes in Shenzhen, four different typical cases of spatial organization, namely Shenzhen Wan Xiang tian di, Shenzhen One Square City, Shenzhen COCO park and Shenzhen Happy Coast (East), are selected as the main objects of this study, and three major design principles (the principle of integration, the principle of compounding and the principle of sharing) are summarized for the external space of a neighborhood-based commercial complex based on urban sharing, and four (interaction and continuity of urban space, integration and optimization of urban texture, three-dimensional connection to urban traffic, and continuity and echo of urban culture) and three design strategies for the use of external space (openness to the city at all times, enhancement of spatial accessibility, and accommodation of various urban activities). The study concludes that the external space of a neighborhood commercial complex should become part of the public space of the city and take on the two-way function of urban and architectural space to achieve the integration and interpenetration of urban and architectural space in order to realize the maximum value of the external space.

Multi-robot navigation based on velocity obstacle prediction in dynamic crowded environments

PurposeThe purpose of this paper is to propose a new velocity prediction navigation algorithm to develop a conflict-free path for robots in dynamic crowded environments. The algorithm BP-prediction and reciprocal velocity obstacle (PRVO) combines the BP neural network for velocity PRVO to accomplish dynamic collision avoidance.Design/methodology/approachThis presented method exhibits innovation by anticipating ahead velocities using BP neural networks to reconstruct the velocity obstacle region; determining the optimized velocity corresponding to the robot’s scalable radius range from the error generated by the non-holonomic robot tracking the desired trajectory; and considering acceleration constraints, determining the set of multi-step reachable velocities of non-holonomic robot in the space of velocity variations.FindingsThe method is validated using three commonly used metrics of collision rate, travel time and average distance in a comparison between simulation experiments including multiple differential drive robots and physical experiments using the Turtkebot3 robot. The experimental results show that our method outperforms other RVO extension methods on the three metrics.Originality/valueIn this paper, the authors propose navigation algorithms capable of adaptively selecting the optimal speed for a multi-robot system to avoid robot collisions during dynamic crowded interactions.

Perspectives on AI-based recommendations for mask-wearing and COVID-19 vaccination for transplant recipients in the post-COVID-19 era

In the aftermath of the COVID-19 pandemic, the ongoing necessity for preventive measures such as mask-wearing and vaccination remains particularly critical for organ transplant recipients, a group highly susceptible to infections due to immunosuppressive therapy. Given that many individuals nowadays increasingly utilize Artificial Intelligence (AI), understanding AI perspectives is important. Thus, this study utilizes AI, specifically ChatGPT 4.0, to assess its perspectives in offering precise health recommendations for mask-wearing and COVID-19 vaccination tailored to this vulnerable population. Through a series of scenarios reflecting diverse environmental settings and health statuses in December 2023, we evaluated the AI’s responses to gauge its precision, adaptability, and potential biases in advising high-risk patient groups. Our findings reveal that ChatGPT 4.0 consistently recommends mask-wearing in crowded and indoor environments for transplant recipients, underscoring their elevated risk. In contrast, for settings with fewer transmission risks, such as outdoor areas where social distancing is possible, the AI suggests that mask-wearing might be less imperative. Regarding vaccination guidance, the AI strongly advocates for the COVID-19 vaccine across most scenarios for kidney transplant recipients. However, it recommends a personalized consultation with healthcare providers in cases where patients express concerns about vaccine-related side effects, demonstrating an ability to adapt recommendations based on individual health considerations. While this study provides valuable insights into the current AI perspective on these important topics, it is crucial to note that the findings do not directly reflect or influence health policy. Nevertheless, given the increasing utilization of AI in various domains, understanding AI’s viewpoints on such critical matters is essential for informed decision-making and future research.

Concentration-Dependent Diffusion of Monoclonal Antibodies: Underlying Mechanisms of Anomalous Diffusion.

The development, storage, transport, and subcutaneous delivery of highly concentrated monoclonal antibody formulations pose significant challenges due to the high solution viscosity and low diffusion of the antibody molecules in crowded environments. These issues often stem from the self-associating behavior of the antibody molecules, potentially leading to aggregation. In this work, we used a dissipative particle dynamics-based coarse-grained model to investigate the diffusion behavior of IgG1 antibody molecules in aqueous solutions with 15 and 32 mM NaCl and antibody concentrations ranging from 10 to 400 mg/mL. We determined the coarse-grained interaction parameters by matching the calculated structure factor with the computational and experimental data from the literature. Our results indicate Fickian diffusion for antibody concentrations of 10 and 25 mg/mL and anomalous diffusion for concentrations exceeding 50 mg/mL. The anomalous diffusion was observed for ∼0.33 to 0.4 μs, followed by Fickian diffusion for all antibody concentrations. We observed a strong linear correlation between the diffusion behavior of the antibody molecules (diffusion coefficient D and anomalous diffusion exponent α) and the amount of aggregates present in the solution and between the amount of aggregates and the Coulomb interaction energy. The investigation of underlying mechanisms for anomalous diffusion revealed that in crowded environments at high antibody concentrations, the attractive interaction between electrostatically complementary regions of the antibody molecules could further bring the neighboring molecules closer to one another, ultimately resulting in aggregate formation. Further, the Coulomb attraction can continue to draw more molecules together, forming larger aggregates.

Nanozyme catalysis in a crowded environment: the impact of diffusion and surface shielding

Nanozyme catalysis in a crowded environment: the impact of diffusion and surface shielding

Contribution of different macromolecules to the diffusion of a 40 nm particle in Escherichia coli

Due to the high concentration of proteins, nucleic acids, and other macromolecules, the bacterial cytoplasm is typically described as a crowded environment. However, the extent to which each of these macromolecules individually affects the mobility of macromolecular complexes, and how this depends on growth conditions, is presently unclear. In this study, we sought to quantify the crowding experienced by an exogenous 40 nm fluorescent particle in the cytoplasm of E. coli under different growth conditions. By performing single-particle tracking measurements in cells selectively depleted of DNA and/or mRNA, we determined the contribution to crowding of mRNA, DNA, and remaining cellular components, i.e., mostly proteins and ribosomes. To estimate this contribution to crowding, we quantified the difference of the particle’s diffusion coefficient in conditions with and without those macromolecules. We found that the contributions of the three classes of components were of comparable magnitude, being largest in the case of proteins and ribosomes. We further found that the contributions of mRNA and DNA to crowding were significantly larger than expected based on their volumetric fractions alone. Finally, we found that the crowding contributions change only slightly with the growth conditions. These results reveal how various cellular components partake in crowding of the cytoplasm and the consequences this has for the mobility of large macromolecular complexes.

Computational Approaches to Predict Protein-Protein Interactions in Crowded Cellular Environments.

Investigating protein-protein interactions is crucial for understanding cellular biological processes because proteins often function within molecular complexes rather than in isolation. While experimental and computational methods have provided valuable insights into these interactions, they often overlook a critical factor: the crowded cellular environment. This environment significantly impacts protein behavior, including structural stability, diffusion, and ultimately the nature of binding. In this review, we discuss theoretical and computational approaches that allow the modeling of biological systems to guide and complement experiments and can thus significantly advance the investigation, and possibly the predictions, of protein-protein interactions in the crowded environment of cell cytoplasm. We explore topics such as statistical mechanics for lattice simulations, hydrodynamic interactions, diffusion processes in high-viscosity environments, and several methods based on molecular dynamics simulations. By synergistically leveraging methods from biophysics and computational biology, we review the state of the art of computational methods to study the impact of molecular crowding on protein-protein interactions and discuss its potential revolutionizing effects on the characterization of the human interactome.

The effect of konjac glucomannan on enzyme kinetics and fluorescence spectrometry of digestive enzymes: An in vitro research from the perspective of macromolecule crowding

Konjac glucomannan (KGM) can significantly prolong gastrointestinal digestion. However, it is still worth investigating whether the macromolecular crowding (MMC) induced by KGM is correlated with digestion. In this paper, the MMC effect was quantified by fluorescence resonance energy transfer and microrheology, and the digests of starch, protein, and oil were determined. The digestive enzymes were analyzed by enzyme reaction kinetic and fluorescence quenching. The results showed that higher molecular weight (604.85 ∼ 1002.21 kDa) KGM created a larger MMC (>0.8), and influenced the digestion of macronutrients; the digests of starch, protein, and oil all decreased significantly. MMC induced by KGM decreased the Michaelis-Menten constants (Km and Vmax) of pancreatic α-amylase (PPA), pepsin (PEP), and pancreatic lipase (PPL). The larger MMC (>0.8) induced by KGM resulted in the decrease of fluorescence quenching constants (Ksv) in PPA and PPL, and the increase of Ksv in PEP. Therefore, varying degrees of MMC induced by KGM could play a role in regulating digestion and the inhibitory effect on digestion was more significant in a relatively more crowded environment induced by KGM. This study provides theoretical support for the strategies of nutrient digestion regulation from the perspective of MMC caused by dietary fiber.

Potential gap in understanding cyanoHABs: Light-dependent morphological variations in colonial cyanobacterium Microcystis

Colony formation is a crucial characteristic of Microcystis, a cyanobacterium known for causing cyanobacterial harmful algal blooms (cyanoHABs). It has been observed that as Microcystis colonies grow larger, they often become less densely packed, which correlates with a decrease in light penetration. The objective of this study was to investigate the effects of light limitation on the morphological variations in Microcystis, particularly in relation to the crowded cellular environment. The results indicated that when there was sufficient light (transmittance = 100 %) to support a growth rate of 0.11±0.01 day−1, a significant increase in colony size was found, from 466±15 μm to 1030±111 μm. However, under light limitation (transmittance = 50 % – 1 %) where the growth rate was lower than 0, there was no significant improvement in colony size. Microcystis in the light limitation groups exhibited a loose cell arrangement and even the presence of holes or pores within the colony, confirming the negative correlation between colony size and cell arrangement. This pattern is driven by regional differences in growth within the colony, as internal cells have a significantly lower frequency of division compared to peripheral cells, due to intra-colony self-shading (ICSS). The research demonstrates that Microcystis can adjust its cell arrangement to avoid excessive self-shading, which has implications for predicting and controlling cyanoHABs. These findings also contribute to the understanding of cyanobacterial variations and can potentially inform future research on the diverse phycosphere.

Collision avoidance behaviours of luggage-laden pedestrians

Understanding how pedestrians move and avoid collisions is essential for ensuring safety in crowded environments. In this study, we conducted detailed experiments, focusing on variables such as movement type (walking and running), encounter angles (90 and 180 degrees), and pedestrian characteristics. We analyzed a total of 168 trajectories to gain insights into the collision avoidance strategies employed by luggage-laden pedestrians. Our study highlights the significant impact of luggage on the minimum avoidance distance in vertical encounters, while head-on approaches show limited influence. We use the minimum predicted distance to evaluate time avoidance time, with particular focus on the presence of luggage as a pivotal determinant. Furthermore, we conduct a comprehensive categorization on pedestrian behaviors when carrying luggage, taking into account their speed and trajectory. Our findings reveal distinct strategies adopted by luggage-laden pedestrians when avoiding from the left and right sides. Interestingly, pedestrians employ more efficient conflict mitigation tactics when interacting with luggage-laden individuals approaching from the left compared to the right side. These insights are valuable for optimizing crowd management strategies, particularly in transportation hubs with luggage-laden crowds.

Molecular Crowding: The History and Development of a Scientific Paradigm.

It is now generally accepted that macromolecules do not act in isolation but "live" in a crowded environment, that is, an environment populated by numerous different molecules. The field of molecular crowding has its origins in the far 80s but became accepted only by the end of the 90s. In the present issue, we discuss various aspects that are influenced by crowding and need to consider its effects. This Review is meant as an introduction to the theme and an analysis of the evolution of the crowding concept through time from colloidal and polymer physics to a more biological perspective. We introduce themes that will be more thoroughly treated in other Reviews of the present issue. In our intentions, each Review may stand by itself, but the complete collection has the aspiration to provide different but complementary perspectives to propose a more holistic view of molecular crowding.

Application of Machine Learning in the Quantitative Analysis of the Surface Characteristics of Highly Abundant Cytoplasmic Proteins: Toward AI-Based Biomimetics.

Proteins in the crowded environment of human cells have often been studied regarding nonspecific interactions, misfolding, and aggregation, which may cause cellular malfunction and disease. Specifically, proteins with high abundance are more susceptible to these issues due to the law of mass action. Therefore, the surfaces of highly abundant cytoplasmic (HAC) proteins directly exposed to the environment can exhibit specific physicochemical, structural, and geometrical characteristics that reduce nonspecific interactions and adapt to the environment. However, the quantitative relationships between the overall surface descriptors still need clarification. Here, we used machine learning to identify HAC proteins using hydrophobicity, charge, roughness, secondary structures, and B-factor from the protein surfaces and quantified the contribution of each descriptor. First, several supervised learning algorithms were compared to solve binary classification problems for the surfaces of HAC and extracellular proteins. Then, logistic regression was used for the feature importance analysis of descriptors considering model performance (80.2% accuracy and 87.6% AUC) and interpretability. The HAC proteins showed positive correlations with negatively and positively charged areas but negative correlations with hydrophobicity, the B-factor, the proportion of beta structures, roughness, and the proportion of disordered regions. Finally, the details of each descriptor could be explained concerning adaptative surface strategies of HAC proteins to regulate nonspecific interactions, protein folding, flexibility, stability, and adsorption. This study presented a novel approach using various surface descriptors to identify HAC proteins and provided quantitative design rules for the surfaces well-suited to human cellular crowded environments.

Crowding induced switching of polymer translocation by the amalgamation of entropy and osmotic pressure

The translocation of polymers is omnipresent in inherently crowded biological systems. We investigate the dynamics of polymer translocation through a pore in free and crowded environments using Langevin dynamics simulation. We observed a location-dependent translocation rate of monomers showcasing counterintuitive behavior in stark contrast to the bead velocity along the polymer backbone. The free energy calculation of asymmetrically placed polymers indicates a critical number of segments to direct receiver-side translocation. For one-sided crowding, we have identified a critical crowding size revealing a nonzero probability of translocation toward the crowded-side. Moreover, we have observed that shifting the polymer toward the crowded-side compensates for one-sided crowding, yielding an equal probability akin to a crowder-free system. In two-sided crowding, a slight variation in crowder size and packing fraction induces a polymer to switch its translocation direction. These conspicuous yet counter-intuitive phenomena are rationalized by minimalistic theoretical arguments based on osmotic pressure and radial entropic forces.

Safe and socially compliant robot navigation in crowds with fast-moving pedestrians via deep reinforcement learning

AbstractSafe and socially compliant navigation in a crowded environment is essential for social robots. Numerous research efforts have shown the advantages of deep reinforcement learning techniques in training efficient policies, while most of them ignore fast-moving pedestrians in the crowd. In this paper, we present a novel design of safety measure, named Risk-Area, considering collision theory and motion characteristics of different robots and humans. The geometry of Risk-Area is formed based on the real-time relative positions and velocities of the agents in the environment. Our approach perceives risk in the environment and encourages the robot to take safe and socially compliant navigation behaviors. The proposed method is verified with three existing well-known deep reinforcement learning models in densely populated environments. Experiment results demonstrate that our approach combined with the reinforcement learning techniques can efficiently perceive risk in the environment and navigate the robot with high safety in the crowds with fast-moving pedestrians.

Congested C(sp3)-rich architectures enabled by iron-catalysed conjunctive alkylation.

Catalytic cross-coupling by transition metals has revolutionized the formation of C-C bonds in organic synthesis. However, the challenge of forming multiple alkyl-alkyl bonds in crowded environments remains largely unresolved. Here, we report the regioselective functionalization of olefins with sp3-hybridized organohalides and organozinc reagents using a simple (terpyridine)iron catalyst. Aliphatic groups of various sizes are successfully installed on either olefinic carbon, furnishing a diverse array of products with congested cores featuring C- or heteroatom-substituted stereocenters. The method enables access to valuable but synthetically challenging C(sp3)-rich molecules, including alicyclic compounds bearing multiple contiguous stereocenters through annulation cascades. Mechanistic and theoretical studies suggest a stepwise iron-mediated radical carbometallation pathway followed by outer-sphere C-C bond formation, which potentially opens the door to a broader scope of transformations and new chemical space.