Advanced biology最新文献

Microphysiological Systems (MPS) represent an intriguing stepping stone in efforts to replicate human biology. The premise of MPS is clear—cells, tissues, and organoids are grown ex vivo in a physiologically and anatomically accurate manner. These systems can be used as human surrogates to model disease, test drugs, and explore many other aspects of homeostasis and biology. This joint special issue aims to curate a wide-ranging collection of works including tissue engineering, biomaterials, biofabrication, and the implementation of these advances into complex models of human pathophysiology. The issue, guest edited by Martin Trapecar, Ramana Sidhaye, and Deok-Ho Kim (founding members of the new Center for Microphysiological Systems at Johns Hopkins University), is being jointly published in Advanced Biology and Advanced Healthcare Materials.

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The studies and reviews in Advanced Biology highlight significant advancements in bioengineering, specifically in the development and application of microphysiological systems (MPS), hydrogel optimization, and stem cell-derived models for biomedical research. Collectively, these efforts underscore the potential of these technologies to transform various fields, including angiogenesis, cancer immunotherapy, diabetes treatment, drug development, respiratory health, and neurological research.

Lam et al. (article 202300094) developed and validated a high-throughput bioassay to assess the angiogenic bioactivity of mesenchymal stromal cells (MSCs). They identified hepatocyte growth factor (HGF) gene expression as a potential biomarker for MSC angiogenic activity. The novelty here lies in the C-Curio MPS as a tool for evaluating MSC potency and the identification of HGF as a surrogate marker. Peng and Lee (article 202300077) then review the use of MPS (e.g., organs-on-a-chip) in cancer immunotherapy research, emphasizing their advantages over traditional methods. The article highlights the application of MPS in analyzing immune cell interactions and the tumor microenvironment, with potential use in personalized medicine and immunotherapy. Quiroz et al. (article 202300502) focused on optimizing alginate hydrogels for cell encapsulation to improve viability and function for type 1 diabetes models and found conditions that enhance the function of encapsulated cells. This advance will improve cell graft viability and function in vitro. Tomlinson et al. (article 202300131) discuss the use of MPS in drug development, emphasizing the need for standardization and regulatory acceptance. They highlight the importance of defining the context of use, characterizing materials, and developing reference test items. Guo et al. (article 202300276) describe a protocol to differentiate neurons from human iPSCs and created an opioid overdose model to study respiratory inhibition by opioids. The neurons expressed the mu-opioid receptor and responded

The research proposes a novel strategy for categorizing electroencephalograms (EEG) in real-time brain-computer interfaces that have rehabilitation applications. The methodology utilizes Five Cross-Common Spatial Patterns (FCCSP) to develop a motor movement/imagery systemization model that extracts multi-domain characteristics with excellent performance. The goal is to eliminate the impact caused by EEG's nonstationarity. The article highlights the findings of a real-time technique that is incorporated into a comprehensive prediction system, and it offers an innovative method to boost accuracy in real-time Sensory-Motor cortex Rhythms (SMR). The accuracy increased from 57.14% using raw EEG to 85.71% after preprocessing, and from 58.08% to 97.94% in public domain SMR. The proposed Butterworth bandpass filter is optimized using the FCCSP to determine the ideal bandwidth that incorporates the whole EEG features in beta waves. The Hybrid Systemization of the Correlated Feature Removal classifier is then integrated with the FCCSP method to create improved predictive models. As a consequence, while applied to real-time and PhysioNet datasets, the outcome system achieved outstanding accuracy values of 85.71% and 97.94%, respectively. This demonstrates the robustness of the strategy to increase SMR prediction efficiency.

Embryoid bodies (EB) are sensitive to changes in the culture conditions. Recent studies show that the addition of PEG 300 to culture medium affects cell growth and differentiation; however, its effect on the embryoid body is unclear. This study aims to understand the role of PEG 300 in the process of EB formation and germ layer differentiation. EBs formed more efficiently and differentiated toward the mesoderm when cultured in a medium supplemented with appropriate concentrations of PEG 300. The expression of T/Bry, a marker of mesodermal differentiation, increases in EBs in the PEG group, and the expression of TUBB3 generally decreases, showing a quantitative relationship with PEG. Furthermore, further differentiation of PEG-pretreated EB into vascular smooth muscle cells (VSMCs) by directional induction shows that PEG 300-pretreated induced VSMCs have higher expression of phenotypic markers and greater secretory and contractile functions. This study highlights the role of PEG 300 in the culture medium during EB differentiation, which can significantly enhance mesodermal gene expression and the efficiency of subsequent differentiation into smooth muscle cells and other target cells.

Triple-negative breast cancer (TNBC) is the most invasive type of breast cancer with high risk of brain metastasis. To better understand interactions between breast tumors with the brain extracellular matrix (ECM), a 3D cell culture model is implemented using a thiolated hyaluronic acid (HA-SH) based hydrogel. The latter is used as HA represents a major component of brain ECM. Melt-electrowritten (MEW) scaffolds of box- and triangular-shaped polycaprolactone (PCL) micro-fibers for hydrogel reinforcement are utilized. Two different molecular weight HA-SH materials (230 and 420 kDa) are used with elastic moduli of 148 ± 34 Pa (soft) and 1274 ± 440 Pa (stiff). Both hydrogels demonstrate similar porosities. The different molecular weight of HA-SH, however, significantly changes mechanical properties, e.g., stiffness, nonlinearity, and hysteresis. The breast tumor cell line MDA-MB-231 forms mainly multicellular aggregates in both HA-SH hydrogels but sustains high viability (75%). Supplementation of HA-SH hydrogels with ECM components does not affect gene expression but improves cell viability and impacts cellular distribution and morphology. The presence of other brain cell types further support numerous cell–cell interactions with tumor cells. In summary, the present 3D cell culture model represents a novel tool establishing a disease cell culture model in a systematic way.

Identification of neoantigens, derived from somatic DNA alterations, emerges as a promising strategy for cancer immunotherapies. However, not all somatic mutations result in immunogenicity, hence, efficient tools to predict the immunogenicity of neoepitopes are needed. A pipeline is presented that provides a comprehensive solution for the identification of neoepitopes based on genomic sequencing data. The pipeline consists of a data pre-processing step and three machine learning predictive steps. The pre-processing step analyzes genomic data for different types of alterations, produces a list of all possible antigens, and determines the human leukocyte antigen (HLA) type and T-cell receptor (TCR) repertoire. The first predictive step performs a classification into antigens and neoantigens, selecting neoantigens for further consideration. The next step predicts the strength of binding between neoantigens and available major histocompatibility complexes of class I (MHC-I). The third step is engaged to predict the likelihood of inducing an immune response. Neoepitopes satisfying all three predictive stages are assumed to be potent candidates to ensure immunogenicity. The predictive pipeline is used in two regimes: selecting neoantigens from patients' sequencing data and generating novel neoantigen candidates. Two different techniques — Monte Carlo and Reinforcement Learning – are implemented to facilitate the generative regime.

The maintenance and expansion of human neural stem cells (hNSCs) in 3D tissue scaffolds is a promising strategy in producing cost-effective hNSCs with quality and quantity applicable for clinical applications. A few biopolymers have been extensively used to fabricate 3D scaffolds, including hyaluronic acid, collagen, alginate, and chitosan, due to their bioactive nature and availability. However, these polymers are usually applied in combination with other biomolecules, leading to their responses difficult to ascribe to. Here, scaffolds made of chitosan, alginate, hyaluronic acid, or collagen, are explored for hNSC expansion under xeno-free and chemically defined conditions and compared for hNSC multipotency maintenance. This study shows that the scaffolds made of pure chitosan support the highest adhesion and growth of hNSCs, yielding the most viable cells with NSC marker protein expression. In contrast, the presence of alginate, hyaluronic acid, or collagen induces differentiation toward immature neurons and astrocytes even in the maintenance medium and absence of differentiation factors. The cells in pure chitosan scaffolds preserve the level of transmembrane protein profile similar to that of standard culture. These findings point to the potential of using pure chitosan scaffolds as a base scaffolding material for hNSC expansion in 3D.

Myocardial infarction (MI) is a common type of cardiovascular disease. The incidence of ventricular remodeling dysplasia and heart failure increases significantly after MI. The objective of this study is to investigate whether erythropoietin hepatocellular receptor B2 (EPHB2) can regulate myocardial injury after MI and explore its regulatory pathways. EPHB2 is significantly overexpressed in the heart tissues of MI mice. The downregulation of EPHB2 alleviates the cardiac function damage after MI. Knockdown EPHB2 alleviates MI-induced myocardial tissue inflammation and apoptosis, and myocardial fibrosis in mice. EPHB2 knockdown significantly inhibits the activation of mitogen activated kinase-like protein (MAPK) pathway in MI mice. Moreover, EPHB2 overexpression significantly promotes the phosphorylation of MAPK pathway-related protein, which can be reversed by MAPK-IN-1 (an MAPK inhibitor) treatment. In conclusion, silencing EPHB2 can mitigate MI-induced myocardial injury by inhibiting MAPK signaling in mice, suggesting that targeting EPHB2 can be a promising therapeutic target for MI-induced myocardial injury.

Endomucin (MUC14), encoded by EMCN gene, is an O-glycosylated transmembrane mucin that is mainly found in venous endothelial cells (ECs) and highly expressed in type H vessels of bone tissue. Its main biological functions include promoting endothelial generation and migration through the vascular endothelial growth factor (VEGF) signaling pathway and inhibiting the adhesion of inflammatory cells to ECs. In addition, it induces angiogenesis and promotes bone formation. Due to the excellent functions of Endomucin in the above aspects, it provides a new research target for the treatment of vascular inflammatory-related diseases and bone diseases. Based on the current understanding of its function, the research of Endomucin mainly focuses on the above two diseases. As it is known, the progression of cancer is closely related to angiogenesis. Endomucin recently is found to be differentially expressed in a variety of tumors and correlated with survival rate. The biological role of Endomucin in cancer is opaque. This article introduces the research progress of Endomucin in vascular inflammatory-related diseases and bone diseases, discusses its application value and prospect in the treatment, and collects the latest research situation of Endomucin in tumors, to provide meaningful evidence for expanding the research field of Endomucin.

A spinal cord injury (SCI) compresses the spinal cord, killing neurons and glia at the injury site and resulting in prolonged inflammation and scarring that prevents regeneration. Astrocytes, the main glia in the spinal cord, become reactive following SCI and contribute to adverse outcomes. The anti-inflammatory cytokine transforming growth factor beta 3 (TGFβ3) has been shown to mitigate astrocyte reactivity; however, the effects of prolonged TGFβ3 exposure on reactive astrocyte phenotype have not yet been explored. This study investigates whether magnetic core-shell electrospun fibers can be used to alter the release rate of TGFβ3 using externally applied magnetic fields, with the eventual application of tailored drug delivery based on SCI severity. Magnetic core-shell fibers are fabricated by incorporating superparamagnetic iron oxide nanoparticles (SPIONs) into the shell and TGFβ3 into the core solution for coaxial electrospinning. Magnetic field stimulation increased the release rate of TGFβ3 from the fibers by 25% over 7 days and released TGFβ3 reduced gene expression of key astrocyte reactivity markers by at least twofold. This is the first study to magnetically deliver bioactive proteins from magnetic fibers and to assess the effect of sustained release of TGFβ3 on reactive astrocyte phenotype.

Population aging has increased the global prevalence of aging-related diseases, including cancer, sarcopenia, neurological disease, arthritis, and heart disease. Understanding aging, a fundamental biological process, has led to breakthroughs in several fields. Cellular senescence, evinced by flattened cell bodies, vacuole formation, and cytoplasmic granules, ubiquitously plays crucial roles in tissue remodeling, embryogenesis, and wound repair as well as in cancer therapy and aging. The lack of universal biomarkers for detecting and quantifying senescent cells, in vitro and in vivo, constitutes a major limitation. The applications and limitations of major senescence biomarkers, including senescence-associated β-galactosidase staining, telomere shortening, cell-cycle arrest, DNA methylation, and senescence-associated secreted phenotypes are discussed. Furthermore, explore senotherapeutic approaches for aging-associated diseases and cancer. In addition to the conventional biomarkers, this review highlighted the in vitro, in vivo, and disease models used for aging studies. Further, technologies from the current decade including multi-omics and computational methods used in the fields of senescence and aging are also discussed in this review. Understanding aging-associated biological processes by using cellular senescence biomarkers can enable therapeutic innovation and interventions to improve the quality of life of older adults.