Search for: All records

Workflow for developing anin vitrobiomimetic myotendinous junction (MTJ): tissue properties and SEM data are measured (left), informing 3D printing of microstructure and properties (middle). MTJ formation occurs naturally within 2 weeks (right). 

Abstract Controllable and long‐term release remains a great challenge in current drug delivery systems. Benefiting from their efficient drug loading and painless administration, microneedles (MNs) have emerged as a promising platform for transdermal drug delivery, while they often fail to achieve long‐term tissue adhesion and controllable extended drug release. Here, 3D printing of an innovative MN patch is presented with succulent‐inspired responsive microstructures and light‐controllable long‐term release capability. The MN exhibits a reversible shrink‐swell volume change behavior in response to surrounding humidity, which enables sufficient mechanical strength for skin penetration under the shrinkage conditions and efficient long‐term adhesion when swollen in skin tissues. Moreover, the MN patch introduces a controllable long‐term drug release system, achieved through the integration of thiolated heparin (Hep‐SH) for sustained growth factor release and graphene oxide (GO) nanosheets for controlled drug release via near infrared (NIR) laser irradiation. The MN patches with growth factor loading have good biocompatibility and can promote the proliferation, migration, and proangiogenesis of endothelial cells is further demonstrated. Thus, it is believed that such flexible MN patches can be promising candidates for controllable long‐term transdermal drug delivery as well as other related tissue engineering applications. 

Hematopoiesis has been studied via stem cell labeling using barcodes, viral integration sites (VISs), or in situ methods. Subsequent proliferation and differentiation preserve the tag identity, thus defining a clone of mature cells across multiple cell type or lineages. By tracking the population of clones, measured within samples taken at discrete time points, we infer physiological parameters associated with a hybrid stochastic-deterministic mathematical model of hematopoiesis. We analyze clone population data from Koelle et al. ( Koelle et al., 2017 ) and compare the states of clones (mean and variance of their abundances) and the state-space density of clones with the corresponding quantities predicted from our model. Comparing our model to the tagged granulocyte populations, we find parameters (stem cell carrying capacity, stem cell differentiation rates, and the proliferative potential of progenitor cells, and sample sizes) that provide reasonable fits in three out of four animals. Even though some observed features cannot be quantitatively reproduced by our model, our analyses provides insight into how model parameters influence the underlying mechanisms in hematopoiesis. We discuss additional mechanisms not incorporated in our model. 

Chemotaxis describes the movement of an organism, such as single or multi-cellular organisms and bacteria, in response to a chemical stimulus. Two widely used models to describe the phenomenon are the celebrated Keller–Segel equation and a chemotaxis kinetic equation. These two equations describe the organism’s movement at the macro- and mesoscopic level, respectively, and are asymptotically equivalent in the parabolic regime. The way in which the organism responds to a chemical stimulus is embedded in the diffusion/advection coefficients of the Keller–Segel equation or the turning kernel of the chemotaxis kinetic equation. Experiments are conducted to measure the time dynamics of the organisms’ population level movement when reacting to certain stimulation. From this, one infers the chemotaxis response, which constitutes an inverse problem. In this paper, we discuss the relation between both the macro- and mesoscopic inverse problems, each of which is associated with two different forward models. The discussion is presented in the Bayesian framework, where the posterior distribution of the turning kernel of the organism population is sought. We prove the asymptotic equivalence of the two posterior distributions. 

Abstract The pharmacology and toxicology of a broad variety of therapies and chemicals have significantly improved with the aid of the increasing in vitro models of complex human tissues. Offering versatile and precise control over the cell population, extracellular matrix (ECM) deposition, dynamic microenvironment, and sophisticated microarchitecture, which is desired for the in vitro modeling of complex tissues, 3D bio-printing is a rapidly growing technology to be employed in the field. In this review, we will discuss the recent advancement of printing techniques and bio-ink sources, which have been spurred on by the increasing demand for modeling tactics and have facilitated the development of the refined tissue models as well as the modeling strategies, followed by a state-of-the-art update on the specialized work on cancer, heart, muscle and liver. In the end, the toxicological modeling strategies, substantial challenges, and future perspectives for 3D printed tissue models were explored.