The development of therapeutic drugs and methods has been greatly facilitated by the emergence of tumor models. However, due to their inherent complexity, establishing a model that can fully replicate the tumor tissue situation remains extremely challenging. With the development of tissue engineering, the advancement of bioprinting technology has facilitated the upgrading of tumor models. This article focuses on the latest advancements in bioprinting, specifically highlighting the construction of 3D tumor models, and underscores the integration of these two technologies. Furthermore, it discusses the challenges and future directions of related techniques, while also emphasizing the effective recreation of the tumor microenvironment through the emergence of 3D tumor models that resemble in vitro organs, thereby accelerating the development of new anticancer therapies.

Plant-based meat analogs have increasingly attracted the attention of the food industry in recent years. However, the digestion behavior of this innovative solid food in human stomach is poorly understood. In this study, plant-based meat analogs with different internal structures were prepared with/without high-moisture extrusion technology and at different temperatures. A semi-dynamic gastric digestion system which involves the mimic processes of the secretion of gastric juice and the gastric emptying was applied. After extrusion treatment at high temperature (150 ℃), the EHT had the highest anisotropic index (H⊥/H∥=1.90) and an ideal meat-like structure. It was found that particle disintegration and swelling simultaneously occurred in the bolus of the EHT but not in the sample without extrusion treatment (the HLT) in the early stage of gastric digestion. This difference might be attributed to the compact and well-arranged anisotropic structure of the EHT resulting from the extrusion, and leads to difficult enzymatic hydrolyzation unless the particles swell and unfold the polymer chains. The difficulty in particle disintegration in the EHT during gastric digestion is the consequence of the relatively slow gastric emptying rate and the decrease of protein degradation. As a result, the EHT which underwent extrusion treatment at high temperature and possessed the best anisotropic fibrous structure exhibited the slowest gastric digestion. This novel solid food shows good potential as a desired nutritional food for people on diet.

Understanding the role of mechanical force on tissue nutrient transport is essential, as sustained force may affect nutrient levels within the disc and initiate disc degeneration. This study aims to evaluate the time-dependent effects of different compressive force amplitudes as well as tensile force on glucose concentration and cell viability within the disc. Based on the mechano-electrochemical mixture theory, a multiphasic finite element model of the lumbar intervertebral disc was developed. The minimum glucose concentration and minimum cell density in both normal and degenerated discs were predicted for different compressive force amplitudes, tensile force, and corresponding creep time. Under high compressive force, the minimum glucose concentration exhibited an increasing and then decreasing trend with creep time in the normal disc, whereas that of the degenerated disc increased, then decreased, and finally increased again. At steady state, a higher compressive force was accompanied by a lower glucose concentration distribution. In the degenerated disc, the minimum cell density was negatively correlated with creep time, with a greater range of affected tissue under a higher compressive force. For tensile force, the minimum glucose concentration of the degenerated disc raised over time. This study highlighted the importance of creep time, force magnitude, and force type in affecting nutrient concentration and cell viability. Sustained weight-bearing activities could deteriorate the nutrient environment of the degenerated disc, while tensile force might have a nonnegligible role in effectively improving nutrient levels within the degenerated disc.

The double-bag theory in modern anatomy suggests that structures with coatings are commonly found in human body at various length scales, such as osteocyte processes covered by pericellular matrix and bones covered by muscle tissue. To understand the mechanical behaviors and physiological responses of such biological structures, we develop an analytical model to quantify surface effects on the deformation of a coated cylindrical compressible liquid inclusion in an elastic matrix subjected to remote loading. Our analytical solution reveals that coating can either amplify or attenuate the volumetric strain of the inclusion, depending on the relative elastic moduli of inclusion, coating, and matrix. For illustration, we utilize this solution to explore amplification/attenuation of volumetric strain in musculoskeletal systems, nerve cells, and vascular tissues. We demonstrate that coating often plays a crucial role in mechanical regulation of the development and repair of human tissues and cells. Our model provides qualitative analysis of cross-scale mechanical response of coated liquid inclusions, helpful for constructing mechanical microenvironment of cells.

The entrapment of bacteria near boundary surfaces is of biological and practical importance, yet the underlying physics is not well understood. We demonstrate that it is crucial to include a commonly neglected thermodynamic effect related to the spatial variation of hydrodynamic interactions, through a model that provides analytic explanation of bacterial entrapment in two dimensionless parameters: α_{1} the ratio of thermal energy to self-propulsion, and α_{2} an intrinsic shape factor. For α_{1} and α_{2} that match an Escherichia coli at room temperature, our model quantitatively reproduces existing experimental observations, including two key features that have not been previously resolved: The bacterial \"nose-down\" configuration, and the anticorrelation between the pitch angle and the wobbling angle. Furthermore, our model analytically predicts the existence of an entrapment zone in the parameter space defined by {α_{1},α_{2}}.

Chirality plays a crucial role in biology, as it is highly conserved and fundamentally important in the developmental process. To better understand the relationship between the chirality of individual cells and that of tissues and organisms, we develop a generalized mechanics model of chiral polarized particles to investigate the swirling dynamics of cell populations on substrates. Our analysis reveals that cells with the same chirality can form distinct chiral patterns on ring-shaped or rectangular substrates. Interestingly, our studies indicate that an excessively strong or weak individual cellular chirality hinders the formation of such chiral patterns. Our studies also indicate that there exists the influence distance of substrate boundaries in chiral patterns. Smaller influence distances are observed when cell-cell interactions are weaker. Conversely, when cell-cell interactions are too strong, multiple cells tend to be stacked together, preventing the formation of chiral patterns on substrates in our analysis. Additionally, we demonstrate that the interaction between cells and substrate boundaries effectively controls the chiral distribution of cellular orientations on ring-shaped substrates. This research highlights the significance of coordinating boundary features, individual cellular chirality, and cell-cell interactions in governing the chiral movement of cell populations and provides valuable mechanics insights into comprehending the intricate connection between the chirality of single cells and that of tissues and organisms.

In this paper, we consider a stochastic two-species predator-prey system with modified Leslie-Gower. Meanwhile, we assume that hunting cooperation occurs in the predators. By using Itô formula and constructing a proper Lyapunov function, we first show that there is a unique global positive solution for any given positive initial value. Furthermore, based on Chebyshev inequality, the stochastic ultimate boundedness and stochastic permanence are discussed. Then, under some conditions, we prove the persistence in mean and extinction of system. Finally, we verify our results by numerical simulations.

Excessive hydrogen peroxide (H2O2) generated during retinal cell metabolic activity could lead to oxidative degeneration of retinal pigment epithelium (RPE) tissue, a specific pathological process implicated in various retinal diseases resulting in blindness, which can be mitigated by taking dietary antioxidants to prevent inflammation and impaired cellular dysfunction. This study tested the hypothesis that damages induced by oxidative stresses can be mitigated by lutein in a H2O2-challenged model, which was based on an ARPE-19 cell monolayer cultured on three-dimensional (3D)-printed fibrous scaffolds. Pretreating these models with lutein (0.5 μM) for 24 h can significantly lower the oxidative stress and maintain phagocytosis and barrier function. Moreover, lutein can modulate the NLRP3 inflammasome, leading to a ∼40% decrease in the pro-inflammatory cytokine (IL-1β and IL-18) levels. Collectively, this study suggests that the 3D RPE model is an effective tool to examine the capability of lutein to modulate cellular functionalities and regulate NLRP3 inflammation.

Time-series experiments are crucial for understanding the transient and dynamic nature of biological phenomena. These experiments, leveraging advanced classification and clustering algorithms, allow for a deep dive into the cellular processes. However, while these approaches effectively identify patterns and trends within data, they often need to improve in elucidating the causal mechanisms behind these changes. Building on this foundation, our study introduces a novel algorithm for temporal causal signaling modeling, integrating established knowledge networks with sequential gene expression data to elucidate signal transduction pathways over time. Focusing on Escherichia coli\'s (E. coli) aerobic to anaerobic transition (AAT), this research marks a significant leap in understanding the organism\'s metabolic shifts. By applying our algorithm to a comprehensive E. coli regulatory network and a time-series microarray dataset, we constructed the cross-time point core signaling and regulatory processes of E. coli\'s AAT. Through gene expression analysis, we validated the primary regulatory interactions governing this process. We identified a novel regulatory scheme wherein environmentally responsive genes, soxR and oxyR, activate fur, modulating the nitrogen metabolism regulators fnr and nac. This regulatory cascade controls the stress regulators ompR and lrhA, ultimately affecting the cell motility gene flhD, unveiling a novel regulatory axis that elucidates the complex regulatory dynamics during the AAT process. Our approach, merging empirical data with prior knowledge, represents a significant advance in modeling cellular signaling processes, offering a deeper understanding of microbial physiology and its applications in biotechnology.

In this paper, a multi-patch and multi-group vector-borne disease model is proposed to study the effects of host commuting (Lagrangian approach) and/or vector migration (Eulerian approach) on disease spread. We first define the basic reproduction number of the model, R 0 , which completely determines the global dynamics of the model system. Namely, if R 0 ≤ 1 , then the disease-free equilibrium is globally asymptotically stable, and if R 0 > 1 , then there exists a unique endemic equilibrium which is globally asymptotically stable. Then, we show that the basic reproduction number has lower and upper bounds which are independent of the host residence times matrix and the vector migration matrix. In particular, nonhomogeneous mixing of hosts and vectors in a homogeneous environment generally increases disease persistence and the basic reproduction number of the model attains its minimum when the distributions of hosts and vectors are proportional. Moreover, R 0 can also be estimated by the basic reproduction numbers of disconnected patches if the environment is homogeneous. The optimal vector control strategy is obtained for a special scenario. In the two-patch and two-group case, we numerically analyze the dependence of the basic reproduction number and the total number of infected people on the host residence times matrix and illustrate the optimal vector control strategy in homogeneous and heterogeneous environments.