Designing stem cell niches for differentiation and self-renewal

Mesenchymal stem cells, characterized by their ability to differentiate into skeletal tissues and self-renew, hold great promise for both regenerative medicine and novel therapeutic discovery. However, their regenerative capacity is retained only when in contact with their specialized microenvironment, termed the stem cell niche. Niches provide structural and functional cues that are both biochemical and biophysical, stem cells integrate this complex array of signals with intrinsic regulatory networks to meet physiological demands. Although, some of these regulatory mechanisms remain poorly understood or difficult to harness with traditional culture systems. Biomaterial strategies are being developed that aim to recapitulate stem cell niches, by engineering microenvironments with physiological-like niche properties that aim to elucidate stem cell-regulatory mechanisms, and to harness their regenerative capacity in vitro. In the future, engineered niches will prove important tools for both regenerative medicine and therapeutic discoveries

Current approaches for modulation of the nanoscale interface in the regulation of cell behavior

Regulation of cell behavior in response to nanoscale features has been the focus of much research in recent years and the successful generation of nanoscale features capable of mimicking the natural nanoscale interface has been of great interest in the field of biomaterials research. In this review, we discuss relevant nanofabrication techniques and how they are combined with bioengineering applications to mimic the natural extracellular matrix (ECM) and create valuable nanoscale interfaces

Optimal Trading with Differing Trade Signals

We consider the problem of maximizing portfolio value when an agent has a subjective view on asset value which differs from the traded market price. The agent's trades will have a price impact which affect the price at which the asset is traded. In addition to the agent's trades affecting the market price, the agent may change his view on the asset's value if its difference from the market price persists. We also consider a situation of several agents interacting and trading simultaneously when they have a subjective view on the asset value. Two cases of the subjective views of agents are considered, one in which they all share the same information, and one in which they all have an individual signal correlated with price innovations. To study the large agent problem we take a mean-field game approach which remains tractable. After classifying the mean-field equilibrium we compute the cross-sectional distribution of agents' inventories and the dependence of price distribution on the amount of shared information among the agents

Benchmarking Small-Dataset Structure-Activity-Relationship Models for Prediction of Wnt Signaling Inhibition

Quantitative structure-activity relationship (QSAR) models based on machine learning algorithms are powerful tools to expedite drug discovery processes and therapeutics development. Given the cost in acquiring large-sized training datasets, it is useful to examine if QSAR analysis can reasonably predict drug activity with only a small-sized dataset (size \u3c; 100) and benchmark these small-dataset QSAR models in application-specific studies. To this end, here we present a systematic benchmarking study on small-dataset QSAR models built for prediction of effective Wnt signaling inhibitors, which are essential to therapeutics development in prevalent human diseases (e.g., cancer). Specifically, we examined a total of 72 two-dimensional (2D) QSAR models based on 4 best-performing algorithms, 6 commonly used molecular fingerprints, and 3 typical fingerprint lengths. We trained these models using a training dataset (56 compounds), benchmarked their performance on 4 figures-of-merit (FOMs), and examined their prediction accuracy using an external validation dataset (14 compounds). Our data show that the model performance is maximized when: 1) molecular fingerprints are selected to provide sufficient, unique, and not overly detailed representations of the chemical structures of drug compounds; 2) algorithms are selected to reduce the number of false predictions due to class imbalance in the dataset; and 3) models are selected to reach balanced performance on all 4 FOMs. These results may provide general guidelines in developing high-performance small-dataset QSAR models for drug activity prediction

Variability in the lower circumpolar deep water and the Lazarev Sea

Furthering our understanding of the Southern Ocean as a critical component of the global climate system and its variability in both space and time is the focus of many investigations. This thesis aims to add to that effort by addressing two important questions. The first chapter will set the role of the Southern Ocean into greater context, clarifying the framework and background for its examination. The second chapter will examine a simple 1-dimensional model of the modification of the Lower Circumpolar Deep Water as it moves southwards across the ACC and into the Weddell Gyre. This leads into the third chapter which will address the first question of how variable are the characteristics of the Lower Circumpolar Deep Water? The variability of the salinity maximum associated with the Lower Circumpolar Deep Water is examined in order to address its spatial variability – from entry via the South Atlantic, through its circumpolar transit, ending with a terminal repository in the Weddell Gyre – by making use of freely available hydrographic data. It also examines temporal variability where repeat data allows, and provides new estimates of deep ocean mixing rates. The fourth chapter will seek to address the second question of how variable was the volume transport during the Lazarev Sea Krill Study (LaKriS) cruises? The LaKriS cruises provide a rare set of semi-repeat grids of hydrographic measurements near the Greenwich Meridian. This provides the opportunity to attempt to assess seasonal and inter-annual variability by making use of an inverse modelling technique. The fifth and final chapter will set the knowledge gained from addressing these two questions against the wider knowledge of the Southern Ocean system and consider the implications for future oceanic sampling and research

Programming Idioms for Transactional Events

Transactional events (TE) are an extension of Concurrent ML (CML), a programming model for synchronous message-passing. Prior work has focused on TE's formal semantics and its implementation. This paper considers programming idioms, particularly those that vary unexpectedly from the corresponding CML idioms. First, we solve a subtle problem with client-server protocols in TE. Second, we argue that CML's wrap and guard primitives do not translate well to TE, and we suggest useful workarounds. Finally, we discuss how to rewrite CML protocols that use abort actions

The influence of nanotopography on cell behaviour through interactions with the extracellular matrix - A review

[EN] Nanotopography presents an effective physical approach for biomaterial cell manipulation mediated through material-extracellular matrix interactions. The extracellular matrix that exists in the cellular microenvironment is crucial for guiding cell behaviours, such as determination of integrin ligation and interaction with growth factors. These interactions with the extracellular matrix regulate downstream mechanotransductive pathways, such as rearrangements in the cytoskeleton and activation of signal cascades. Protein adsorption onto nanotopography strongly influences the conformation and distribution density of extracellular matrix and, therefore, subsequent cell responses. In this review, we first discuss the interactive mechanisms of protein physical adsorption on nanotopography. Secondly, we summarise advances in creating nanotopographical features to instruct desired cell behaviours. Lastly, we focus on the cellular mechanotransductive pathways initiated by nanotopography. This review provides an overview of the current state-of-the-art designs of nanotopography aiming to provide better biomedical materials for the future.We acknowledge support from the Leverhulme Trust through gran t RPG-2019-252 and the Engineering and Physical Sciences Research Council (EPSRC) grant EP/P001114/1.Luo, J.; Walker, M.; Xiao, Y.; Donnelly, H.; Dalby, MJ.; Salmerón Sánchez, M. (2022). The influence of nanotopography on cell behaviour through interactions with the extracellular matrix - A review. Bioactive materials. 15:145-159. https://doi.org/10.1016/j.bioactmat.2021.11.0241451591

Building empathy through a design thinking project : a case study with middle secondary schoolboys

Adolescents' empathy is an essential socio-emotional concept that helps mediate friendships and family relationships. Year 10 boys, aged 14-15 years, were invited to participate in a five-day experiential education program (Design Week) based on a social equity challenge using a Design Thinking concept. Students worked in small groups, mentored by experts. Student groups developed innovative solutions to support women who experienced domestic and family violence. As a key outcome, students' empathy measured by the Comprehensive State Empathy Scale increased significantly from a baseline of 63% to 75% at post-test, representing a large effect size (d= 1.06). Six empathy subscale factors were also significantly increased (p= <0.05). The program was feasible and was rated by teachers and students as engaging, relevant to learning, and learning about complex social issues. This paper presents a case study of the Design Week program, shown to be worthy of further testing with secondary school adolescents. © 2021, Western Australian Institute for Educational Research Inc. All rights reserved

The plot thickens: the emerging role of matrix viscosity in cell mechanotransduction

Cell mechanotransduction is an area of intense research focus. Until now, very limited tools have existed to study how cells respond to changes in the extracellular matrix beyond, for example, mechanical deformation studies and twisting cytometry. However, emerging are a range of elastic, viscoelastic and even purely viscous materials that deform and dissipate on cellular length and timescales. This article reviews developments in these materials, typically translating from 2D model surfaces to 3D microenvironments and explores how cells interact with them. Specifically, it focuses on emerging concepts such as the molecular clutch model, how different extracellular matrix proteins engage the clutch under viscoelastic‐stress relaxation conditions, and how mechanotransduction can drive transcriptional control through regulators such as YAP/TAZ

3-Dimensional Tuning of an Atomically Defined Silicon Tunnel Junction

A requirement for quantum information processors is the in-situ tunability of the tunnel rates and the exchange interaction energy within the device. The large energy level separation for atom qubits in silicon is well suited for qubit operation but limits device tunability using in-plane gate architectures, requiring vertically separated top-gates to control tunnelling within the device. In this paper we address control of the simplest tunnelling device in Si:P, the tunnel junction. Here we demonstrate that we can tune its conductance by using a vertically separated top-gate aligned with +-5nm precision to the junction. We show that a monolithic 3D epitaxial top-gate increases the capacitive coupling by a factor of 3 compared to in-plane gates, resulting in a tunnel barrier height tunability of 0-186meV. By combining multiple gated junctions in series we extend our monolithic 3D gating technology to implement nanoscale logic circuits including AND and OR gates