Mechanobiology in Medicine最新文献

Given the tremendous increase in the risks of cartilage defects in the sports and aging population, current treatments are limited, and new repair strategies are needed. Cartilage tissue engineering (CTE) is a promising approach to handle this burden and several fabrication technologies and biomaterials have been developed these years. The extracellular matrix (ECM) of cartilage consists of a tissue-specific 3D microenvironment with excellent biomechanical and biochemical properties, which regulates cell proliferation, adhesion, migration, and differentiation, thus attracting a great deal of attention to the rapid development of CTE based on ECM components. New generations of biomaterials are being developed rapidly for use as scaffolds to mimic the natural ECM environment. In this review, we discuss such CTE scaffolds based on ECM-derived biomaterials by reviewing the biomaterials for CTE, the applications in different scaffolds and their processing approaches, as well as the current clinical applications of those ECM-based CTE scaffolds.

ChatGPT has garnered significant attention for its impressive capabilities across various domains, including medicine and mechanobiology. In order to facilitate the integration of ChatGPT into research, this paper explores the applications of ChatGPT in these domains, focusing on its usage in (1) reading and writing, (2) retrieval and knowledge management, and (3) computation, simulation, and visualization. Meanwhile, this study acknowledges the limitations and challenges associated with ChatGPT's usage. We investigate the interaction between ChatGPT and external tools in these applications and advocate for the integration of more powerful tools in these research areas into ChatGPT to further expand its potential applications in medicine and mechanobiology.

The use of mechanical biology and biomechanical signal transduction is a novel approach to attenuate biological tissue degeneration, whereas the understanding of specific cellular responses is critical to delineate the underlying mechanism. Dynamic mechanical signals with optimized loading signals, i.e., intensity and frequency, have been shown to have the potential to regulate adaptation and regeneration. Mechanotransduction pathways are of great interest in elucidating how mechanical signals produce such observed effects, including reduced tissue mass loss, increased healing and formation, and cell differentiation. While mechanobiology in the adaptation of cells and tissues is observed and recorded in the literature, its application in disease mechanism and treatment is under development. We would congratulate the opening of the Mechanobiology in Medicine journal, which provides an effective platform for advanced research in basic mechanotransduction and its translation in disease diagnosis, therapeutics, and beyond. This review aims to develop a cellular and molecular understanding of the mechanotransduction processes in tissue regeneration, which may provide new insights into disease mechanisms and the promotion of healing. Particular attention is allotted to the responses of mechanical loading, including potential cellular and molecular pathways, such as mechanotransduction associated with mechanotransduction pathways (e.g., Piezo ion channels and Wnt signaling), immune-response, neuron development, tissue adaptation and repair, and stem cell differentiation. Altogether, these discussed data highlight the complex yet highly coordinated mechanotransduction process in tissue regeneration.

Tumor progression is accompanied by complex structural changes in the extracellular matrix (ECM), which decrease the effective exposure of tumors to drugs. Breast cancer are highly heterogeneous with a typically high degree of ECM remodeling and stiffening. Therefore, it is especially important to explore the influence of ECM stiffness on breast cancer chemotherapy. Here, we fabricated 3D Methacrylate Gelatin (GelMA) hydrogels with varying stiffness by photo-crosslinking to simulate the change of tissue stiffness during the development of breast cancer. These 3D hydrogels were used to evaluate how MDA-MB-231 cells responded to the chemotherapy drug doxorubicin (DOX), the mechanical regulatory mechanism involved has also been investigated. The findings demonstrated that 15% GelMA hydrogel (9 ​kPa) increased the activity of EGFR to block the Hippo signaling pathway and activate Yes-associated protein (YAP). Activated YAP allowed cytosolic EGFR transport into the nucleus via binding with it, up-regulated the expression of their respective transcriptional targets, and thus generates drug resistance. Altogether, our study implicates that stiffness-dependent EGFR activation plays an important role in breast cancer drug resistance, indicating that targeting of both YAP and EGFR signals may present a promising therapeutic strategy for ECM stiffness-induced drug resistance.

Tumor models in vitro are conventional methods for developing anti-cancer drugs, evaluating drug delivery, or calculating drug efficacy. However, traditional cell line-derived tumor models are unable to capture the tumor heterogeneity in patients or mimic the interaction between tumors and their surroundings. Recently emerging patient-derived preclinical cancer models, including of patient-derived xenograft (PDX) model, circulating tumor cell (CTC)-derived model, and tumor organoids-on-chips, are promising in personalized drug therapy by recapitulating the complexities and personalities of tumors and surroundings. These patient-derived models have demonstrated potential advantages in satisfying the rigorous demands of specificity, accuracy, and efficiency necessary for personalized drug therapy. However, the selection of suitable models is depending on the specific therapeutic requirements dictated by cancer types, progressions, or the assay scale. As an example, PDX models show remarkable advantages to reconstruct solid tumors in vitro to understand drug delivery and metabolism. Similarly, CTC-derived models provide a sensitive platform for drug testing in advanced-stage patients, while also facilitating the development of drugs aimed at suppressing tumor metastasis. Meanwhile, the demand for large-scale testing has promoted the development of tumor organoids-on-chips, which serves as an optimal tool for high-throughput drug screening. This review summarizes the establishment and development of PDX, CTC-derived models, and tumor organoids-on-chips and addresses their distinctive advantages in drug discovery, sensitive testing, and screening, which demonstrate the potential to aid in the selection of suitable models for fundamental cancer research and clinical trials, and further developing the personalized drug therapy.

Coronavirus disease-19 (COVID-19) is the ongoing pandemic affecting millions of people worldwide. Several vaccine candidates have been designed and developed for the causative virus, SARS-CoV-2. However high mutation rate in the viral genome and the emergence of new variants have challenged the effectiveness of these vaccines developed for previous strains. Hence, screening and identification of anti-SARS-CoV-2 agents having multi-target potency would be more impactful in the prevention of the disease. Epicatechin gallate (ECG) is a green tea polyphenol having various medicinal properties, including anti-oxidative and anti-inflammatory effects. However its role as anti-SARS-CoV-2 agent is not clear. Hence the present in silico study aims to investigate the binding potential of ECG with several proteins which are critical to SARS-CoV-2 entry and replication within the host cell. Molecular docking analyses have revealed that ECG could potentially block several amino acid residues of entry factors in host cells, spike protein, and many non-structural proteins through Hydrogen bonds and hydrophobic interactions. Such interactions with vital proteins could inhibit SARS-CoV-2 entry and its subsequent replication into the host. Therefore, ECG could be a potential therapeutic agent for the prevention of COVID-19. However, the findings of the present study demand further validation in animal models.

Cell migration is an important biological process regulated by mechanical stimulation, which leads to intracellular calcium response. Cell migration are dependent on the distribution and dynamic changes of intracellular calcium concentration. However, the temporal relation among mechanical stimulation, cell migration, and intracellular calcium distribution remains unclear. In this study, unidirectional flow and oscillatory flow were applied on osteoclast precursor RAW264.7 cells. The parameters of cell migration under fluid flow and intracellular calcium distribution along the migration or flow direction were calculated. Experimental results suggest the cells to adjust the [Ca²⁺]_i distribution in the migration direction is independent of flow application or the reverse of flow direction, but the [Ca²⁺]_i distribution in the flow direction is determined by the [Ca²⁺]_i distribution-adjusting ability of cells and flow stimulation. Blocking calcium signaling pathways, namely, mechanosensitive cation-selective channels, phospholipase C, and endoplasmic reticulum, and removing extracellular calcium inhibited cell migration along the flow direction and the gradient distribution of intracellular calcium. This study provided insights into the mechanism of flow-induced cell migration and quantitative data for the recruitment of osteoclast precursors targeting the location of bone resorption.

Increased matrix stiffness is a common phenomenon in solid tumor tissue and is regulated by both tumor and mesenchymal cells. The increase in collagen and lysyl oxidase family proteins in the extracellular matrix leads to deposition, contraction, and crosslinking of the stroma, promoting increased matrix stiffness in tumors. Matrix stiffness is critical to the progression of various solid tumors. As a mechanical factor in the tumor microenvironment, matrix stiffness is involved in tumor progression, promoting biological processes such as tumor cell proliferation, invasion, metastasis, angiogenesis, drug resistance, and immune escape. Reducing tissue stiffness can slow down tumor progression. Therefore targeting matrix stiffness is a potential option for tumor therapy. This article reviews the detailed mechanisms of matrix stiffness in different malignant tumor phenotypes and potential tumor therapies targeting matrix stiffness. Understanding the role and mechanisms of matrix stiffness in tumors could provide theoretical insights into the treatment of tumors and assist in the clinical development of new drug therapies.

Tumor state transitions between the excited (high-concentration) and nonexcited (low-concentration) basins under the Gaussian white noise and non-Gaussian colored noise are investigated via the most probable steady states (MPSS) and the first escape probability (FEP)-based stochastic basin of attraction (SBA), respectively. Reducing the non-Gaussian colored noise and then utilizing the unified colored noise approximation (UCNA), the Markov system is derived. The extremal controlling equation of stationary probability density function (SPDF) is derived to analyze the impacts of noise on transitions in terms of MPSS. The existence of the ‘color’ of the non-Gaussian colored noise induces the reappearance of the uncorrelated additive white noise parameter that had vanished from the extremal controlling equation, completely reversing the inability of the uncorrelated additive Gaussian white noise to operate on transitions. The FEP-dependent SBA characterizing the excited basin stability is performed to further analyze the role of noise on the likelihood of escaping to the nonexcited state. Results show that the cross-correlated noises play a dual role in regulating SBA. The increased SBA indicating more difficulty to escape to the nonexcited state reflects a worse therapeutic effect. Therefore, enhancing the negatively correlated noise intensities and augmenting the non-Gaussian noise correlation time is essential for destabilizing the excited basin and achieving optimal therapeutic efficacy.