Cellular and molecular bioengineering最新文献

Introduction

Kinesin-3 motor, which is in the monomeric and inactive form in solution, after cargo-induced dimerization can step on microtubules towards the plus end with a high velocity and a supperprocessivity, which is responsible for transporting the cargo in axons and dendrites. The kinesin-3 motor has a large initial landing rate to microtubules and spends the majority of its stepping cycle in a one-head-bound state. Under the load the kinesin-3 motor can dissociate more readily than the kinesin-1 motor.

Methods

To understand the physical origin of the peculiar features for the kinesin-3 motor, a model is presented here for its chemomechanical coupling. Based on the model the dynamics of the motor under no load, under the ramping load and under the constant load is studied analytically.

Results

The theoretical results explain well the available experimental data under no load and under the ramping load. For comparison, the corresponding available experimental data for the kinesin-1 motor under the ramping load are also explained. The predicted results of the velocity, dissociation rate and run length versus the constant load for the kinesin-3 motor are provided.

Conclusions

The study has strong implications for the chemomechanical coupling mechanism of the kinesin-3 dimer. The origin of the kinesin-3 dimer in the predominant one-head-bound state is due to the fact that the rate of ATP transition to ADP in the trailing head is much larger than that of ADP release from the MT-bound head. The study shows that the kinesin-3 ADP-head has an evidently longer interaction distance with microtubule than the kinesin-1 ADP-head, explaining why in the initial ADP state the kinesin-3 motor has the much larger landing rate than the kinesin-1 motor and why under the load the kinesin-3 motor can dissociate more readily than the kinesin-1 motor.

Abstract

Abstract

The remarkable capabilities of generative artificial intelligence and large language models (LLMs) such as ChatGPT have delighted users around the world. Educators have regarded these tools as either a cause for great concern, an opportunity to educate students on cutting-edge technology, or often some combination of the two. Throughout the Fall 2023 semester, we explored the use of ChatGPT (and Bard, among other LLMs) in a graduate level numerical and statistical methods course for PhD-level bioengineers. In this article we share examples of this ChatGPT content, our observations on what worked best in our course, and speculate on how bioengineering students may be best served by this technology in the future.

Introduction

Breast tumors often display an astonishing degree of spatial and temporal heterogeneity, which are associated with cancer progression, drug resistance, and relapse. Triple-negative breast cancer (TNBC) is a particularly aggressive and heterogeneous subtype for which targeted therapies are scarce. Consequently, patients with TNBC have a poorer overall prognosis compared to other breast cancer patients. Within heterogeneous tumors, individual clonal subpopulations may exhibit differences in their rates of growth and degrees of invasiveness. We hypothesized that such phenotypic heterogeneity at the single-cell level may accelerate tumor progression by enhancing the overall growth and invasion of the entire tumor.

Methods

To test this hypothesis, we isolated and characterized clonal subpopulations with distinct morphologies and biomarker expression from the inherently heterogeneous 4T1 mouse mammary carcinoma cell line. We then leveraged a 3D microfluidic tumor model to reverse-engineer intratumoral heterogeneity and thus investigate how interactions between phenotypically distinct subpopulations affect tumor growth and invasion.

Results

We found that the growth and invasion of multiclonal tumors were largely dictated by the presence of cells with epithelial and mesenchymal traits, respectively. The latter accelerated overall tumor invasion, even when these cells comprised less than 1% of the initial population. Consistently, tumor progression was delayed by selectively targeting the mesenchymal subpopulation.

Discussion

This work reveals that highly invasive cells can dominate tumor phenotype and that specifically targeting these cells can slow the progression of heterogeneous tumors, which may help inform therapeutic approaches.

Purpose

Individuals with Down syndrome (DS) are 2000 times more likely to develop a congenital heart defect (CHD) than the typical population Freeman et al. in Am J Med Genet 80:213–217 (1998). The majority of CHDs in individuals with DS characteristically involve the atrioventricular (AV) canal, including the valves and the atrial or ventricular septum. Type VI collagen (COLVI) is the primary structural component in the developing septa and endocardial cushions, with two of the three genes encoding for COLVI located on human chromosome 21 and upregulated in Down syndrome (von Kaisenberg et al. in Obstet Gynecol 91:319–323, 1998; Gittenberger-De Groot et al. in Anatom Rec Part A 275:1109–1116, 2023).

Methods

To investigate the effect of COLVI dosage on cardiomyocytes with trisomy 21, induced pluripotent stem cells (iPSC) from individuals with DS and age- and sex-matched controls were differentiated into cardiomyocytes (iPSC-CM) and plated on varying concentrations of COLVI.

Results

Real time quantitative PCR showed decreased expression of cardiac-specific genes of DS iPSC-CM lines compared to control iPSC-CM. As expected, DS iPSC-CM had increased expression of genes on chromosome 21, including COL6A1, COL6A2, as well as genes not located on chromosome 21, namely COL6A3, HAS2 and HYAL2. We found that higher concentrations of COLVI result in decreased proliferation and migration of DS iPSC-CM, but not control iPSC-CM.

Conclusions

These results suggest that the increased expression of COLVI in DS may result in lower migration-driven elongation of endocardial cushions stemming from lower cell proliferation and migration, possibly contributing to the high incidence of CHD in the DS population.

Background

Current research on the biophysics of circulating tumor cells often overlooks the heterogeneity of cell populations, focusing instead on average cellular properties. This study aims to address the gap by considering the diversity of cell biophysical characteristics and their implications on cancer spread.

Methods

We utilized computer simulations to assess the influence of variations in cell size and membrane elasticity on the behavior of cells within fluid environments. The study controlled cell and fluid properties to systematically investigate the transport of tumor cells through a simulated network of branching channels.

Results

The simulations revealed that even minor differences in cellular properties, such as slight changes in cell radius or shear elastic modulus, lead to significant changes in the fluid conditions that cells experience, including velocity and wall shear stress (p < 0.001).

Conclusion

The findings underscore the importance of considering cell heterogeneity in biophysical studies and suggest that small variations in cellular characteristics can profoundly impact the dynamics of tumor cell circulation. This has potential implications for understanding the mechanisms of cancer metastasis and the development of therapeutic strategies.

Introduction

Several functional gastrointestinal disorders (FGIDs) have been associated with the degradation or remodeling of the network of interstitial cells of Cajal (ICC). Introducing fractal analysis to the field of gastroenterology as a promising data analytics approach to extract key structural characteristics that may provide insightful features for machine learning applications in disease diagnostics. Fractal geometry has advantages over several physically based parameters (or classical metrics) for analysis of intricate and complex microstructures that could be applied to ICC networks.

Methods

In this study, three fractal structural parameters: Fractal Dimension, Lacunarity, and Succolarity were employed to characterize scale-invariant complexity, heterogeneity, and anisotropy; respectively of three types of gastric ICC network structures from a flat-mount transgenic mouse stomach.

Results

The Fractal Dimension of ICC in the longitudinal muscle layer was found to be significantly lower than ICC in the myenteric plexus and circumferential muscle in the proximal, and distal antrum, respectively (both p < 0.0001). Conversely, the Lacunarity parameters for ICC-LM and ICC-CM were found to be significantly higher than ICC-MP in the proximal and in the distal antrum, respectively (both p < 0.0001). The Succolarity measures of ICC-LM network in the aboral direction were found to be consistently higher in the proximal than in the distal antrum (p < 0.05).

Conclusions

The fractal parameters presented here could go beyond the limitation of classical metrics to provide better understanding of the structural-functional relationship between ICC networks and the conduction of gastric bioelectrical slow waves.