Time-independent charge carrier mobility in a model polymer:fullerene organic solar cell

The technique of photo-CELIV (charge extraction by linearly increasing voltage) is one of the more straightforward and popular approaches to measure the faster carrier mobility in measurement geometries that are relevant for operational solar cells and other optoelectronic devices. It has been used to demonstrate a time-dependent photocarrier mobility in pristine polymers, attributed to energetic relaxation within the density of states. Conversely, in solar cell blends, the presence or absence of such energetic relaxation on transport timescales remains under debate. We developed a complete numerical model and performed photo-CELIV experiments on the model high efficiency organic solar cell blend poly[3,6-dithiophene-2-yl-2,5-di(2-octyldodecyl)-pyrrolo[3,4-c]pyrrole-1,4-dione-alt-naphthalene] (PDPP-TNT):[6,6]-phenyl-C71-butyric-acid-methyl-ester (PC70BM). In the studied solar cells a constant, time-independent mobility on the scale relevant to charge extraction was observed, where thermalisation of photocarriers occurs on time scales much shorter than the transit time. Therefore, photocarrier relaxation effects are insignificant for charge transport in these efficient photovoltaic devices.

Autologous human kidney proximal tubule epithelial cells (PTEC) modulate dendritic cell (DC), T cell and B cell responses

This is a comprehensive study of human kidney proximal tubular epithelial cells (PTEC) which are known to respond to and mediate the pathological process of a range of kidney diseases. It identifies various molecules expressed by PTEC and how these molecules participate in down-regulating the inflammatory process, thereby highlighting the clinical potential of these molecules to treat various kidney diseases. In the disease state, PTEC gain the ability to regulate the immune cell responses present within the interstitium. This down-regulation is a complex interaction of contact dependent/independent mechanisms involving various immuno-regulatory molecules including PD-L1, sHLA-G and IDO. The overall outcome of this down-regulation is suppressed DC maturation, decreased number of antibody producing B cells and low T cell responses. These manifestations within a clinical setting are expected to dampen the ongoing inflammation, preventing the damage caused to the kidney tissue.

Cross-scale biophysics modelling of F-actin cytoskeleton in cell

This thesis is a comparative study of the modelling of mechanical behaviours of F-actin cytoskeleton which is an important structural component in living cells. A new granular model was developed for F-actin cytoskeleton based on the concept of multiscale modelling. This framework overcomes difficulties encountered in physical modelling of cytoskeleton in conventional continuum mechanics modelling, and the computational challenges in all-atom molecular dynamics simulation. The thermostat algorithm was further modified to better predict the thermodynamic properties of F-actin cytoskeleton in modelling. This multiscale modelling framework was applied in explaining the physical mechanisms of cytoskeleton responses to external mechanical loads.

Double star chopper cell converter for battery electric vehicles with inter-module SoC balancing and fault tolerant control

A modularized battery system with Double Star Chopper Cell (DSCC) based modular multilevel converter is proposed for a battery operated electric vehicle (EV). A design concept for the modularized battery micro-packs for DSCC is described. Multidimensional pulse width modulation (MD-PWM) with integrated inter-module SoC balancing and fault tolerant control is proposed and explained. The DSCC can be operated either as an inverter to drive the EV motor or as a synchronous rectifier connected to external three phase power supply equipment for charging the battery micro-packs. The methods of operation as inverter and synchronous rectifier with integrated inter-module SoC balancing and fault tolerant control are discussed. The proposed system operation as inverter and synchronous rectifier are verified through simulations and the results are presented.

Quantifying uncertainty in parameter estimates for stochastic models of collective cell spreading using approximate Bayesian computation

Wound healing and tumour growth involve collective cell spreading, which is driven by individual motility and proliferation events within a population of cells. Mathematical models are often used to interpret experimental data and to estimate the parameters so that predictions can be made. Existing methods for parameter estimation typically assume that these parameters are constants and often ignore any uncertainty in the estimated values. We use approximate Bayesian computation (ABC) to estimate the cell diffusivity, D, and the cell proliferation rate, λ, from a discrete model of collective cell spreading, and we quantify the uncertainty associated with these estimates using Bayesian inference. We use a detailed experimental data set describing the collective cell spreading of 3T3 fibroblast cells. The ABC analysis is conducted for different combinations of initial cell densities and experimental times in two separate scenarios: (i) where collective cell spreading is driven by cell motility alone, and (ii) where collective cell spreading is driven by combined cell motility and cell proliferation. We find that D can be estimated precisely, with a small coefficient of variation (CV) of 2–6%. Our results indicate that D appears to depend on the experimental time, which is a feature that has been previously overlooked. Assuming that the values of D are the same in both experimental scenarios, we use the information about D from the first experimental scenario to obtain reasonably precise estimates of λ, with a CV between 4 and 12%. Our estimates of D and λ are consistent with previously reported values; however, our method is based on a straightforward measurement of the position of the leading edge whereas previous approaches have involved expensive cell counting techniques. Additional insights gained using a fully Bayesian approach justify the computational cost, especially since it allows us to accommodate information from different experiments in a principled way.

Cell type-dependent, infection-induced, aberrant DNA methylation in gastric cancer

Epigenetic changes correspond to heritable modifications of the chromatin structure, which do not involve any alteration of the DNA sequence but nonetheless affect gene expression. These mechanisms play an important role in cell differentiation, but aberrant occurrences are also associated with a number of diseases, including cancer and neural development disorders. In particular, aberrant DNA methylation induced by H. Pylori has been found to be a significant risk factor in gastric cancer. To investigate the sensitivity of different genes and cell types to this infection, a computational model of methylation in gastric crypts is developed. In this article, we review existing results from physical experiments and outline their limitations, before presenting the computational model and investigating the influence of its parameters.

Reduced intensity conditioning for allogeneic hematopoietic stem cell transplant determines the kinetics of acute Graft-Versus-Host Disease

Background Preparative myeloablative conditioning regimens for allogeneic hematopoietic stem-cell transplantation (HSCT) may control malignancy and facilitate engraftment but also contribute to transplant related mortality, cytokine release, and acute graft-versus-host disease (GVHD). Reduced intensity conditioning (RIC) regimens have decreased transplant related mortality but the incidence of acute GVHD, while delayed, remains unchanged. There are currently no in vivo allogeneic models of RIC HSCT, limiting studies into the mechanism behind RIC-associated GVHD. Methods We developed two RIC HSCT models that result in delayed onset GVHD (major histocompatibility complex mismatched (UBI-GFP/BL6 [H-2b]→BALB/c [H-2d]) and major histocompatibility complex matched, minor histocompatibility mismatched (UBI-GFP/BL6 [H-2b]→BALB.B [H-2b])) enabling the effect of RIC on chimerism, dendritic cell (DC) chimerism, and GVHD to be investigated. Results In contrast with myeloablative conditioning, we observed that RIC-associated delayed-onset GVHD is characterized by low production of tumor necrosis factor-α, maintenance of host DC, phenotypic DC activation, increased T-regulatory cell numbers, and a delayed emergence of activated donor DC. Furthermore, changes to the peritransplant milieu in the recipient after RIC lead to the altered activation of DC and the induction of T-regulatory responses. Reduced intensity conditioning recipients suffer less early damage to GVHD target organs. However, as donor cells engraft, activated donor DC and rising levels of tumor necrosis factor-α are associated with a later onset of severe GVHD. Conclusions Delineating the mechanisms underlying delayed onset GVHD in RIC HSCT recipients is vital to improve the prediction of disease onset and allow more targeted interventions for acute GVHD.

Developing a therapeutic anti-dendritic cell antibody to prevent graft versus host disease

Host and donor dendritic cells (DC) stimulate alloreactive donor T lymphocytes, and initiate GVHD. We have shown that polyclonal antibody to the DC surface activation marker human CD83 (anti hCD83), which depletes activated DC, can prevent human DC and T cell induced lethal xenogeneic GVHD in SCID mice without impairing T cell mediated anti-leukaemic and anti-viral (CMV and influenza) immunity (J Exp Med 2009; 206: 387). Therefore, we made and tested a polyclonal anti mouse CD83 (RAM83) antibody in murine HSCT models and developed a human mAb against hCD83 as a potential new therapeutic immunosuppressive agent.

A three dimensional virtual medical imaging computed tomography suite: Innovation in education

Aims: The Medical Imaging Training Immersive Environment(MITIE) Computed Tomography(CT) system is an innovative virtual reality (VR) platform that allows students to practice a range of CT techniques. The aim of this pilot study was to harvest user feedback about the educational value of teh application and inform future pedagogical development. This presentation explores the use of this technology for skills training. Background: MITIE CT is a 3D VR environment that allows students to position a patient,and set CT technical parameters including IV contrast dose and dose rate. As with VR initiatives in other health disciplines the software mimics clinical practice as much as possible and uses 3D technology to enhance immersion and realism. The software is new and was developed by the Medical Imaging Course Team at a provider University with funding from a Health Workforce Australia 'Simulated Learning Environments' grant Methods: Current third year medical imaging students were provided with additional 1 hour MITIE laboratory tutorials and studnet feedback was collated with regard to educational value and performance. Ethical approval for the project was provided by the university ethics panel Results: This presentation provides qualitative analysis of student perceptions relating to satisfaction, usability and educational value. Students reported high levels of satisfaction and both feedback and assessment results confirmed the application's significance as a pre-clinical tool. There was a clear emerging theme that MITIE could be a useful learning tool that students could access to consolidate their clinical learning, either on campus or during their clinical placement. Conclusion: Student feedback indicates that MITIE CT has a valuable role to play in the clinial skills training for medical imaging students both in the academic and clinical environment. Future work will establish a framework for an appropriate supprting pedagogy that can cross the boundary between the two environments

Drug accumulation into single drug-sensitive and drug-resistant prostate cancer cells conducted on the single cell bioanalyzer

Multidrug resistance (MDR) occurs in prostate cancer, and this happens when the cancer cells resist chemotherapeutic drugs by pumping them out of the cells. MDR inhibitors such as cyclosporin A (CsA) can stop the pumping and enhance the drugs accumulated in the cells. The cellular drug accumulation is monitored using a microfluidic chip mounted on a single cell bioanalyzer. This equipment has been developed to measure accumulation of drugs such as doxorubicin (DOX) and fluorescently labeled paclitaxel (PTX) in single prostate cancer cells. The inhibition of drug efflux on the same prostate cell was examined in drug-sensitive and drug-resistant cells. Accumulation of these drug molecules was not found in the MDR cells, PC-3 RX-DT2R cells. Enhanced drug accumulation was observed only after treating the MDR cell in the presence of 5 μM of CsA as the MDR inhibitor. We envision this monitoring of the accumulation of fluorescent molecules (drug or fluorescent molecules), if conducted on single patient cancer cells, can provide information for clinical monitoring of patients undergoing chemotherapy in the future.

Different correlation of Sphingosine-1-Phosphate receptor 1 with receptor activator of nuclear factor kappa B ligand and regulatory T cells in rat periapical lesions

Introduction Sphingosine-1-phosphate receptor 1 (S1P1) is crucial for regulation of immunity and bone metabolism. This study aimed to investigate the expression of S1P1 in rat periapical lesions and its relationship with receptor activator of nuclear factor kappa B ligand (RANKL) and regulatory T (Treg) cells. Methods Periapical lesions were induced by pulp exposure in the first lower molars of 55 Wistar rats. Thirty rats were killed on days 0, 7, 14, 21, 28, and 35, and their mandibles were harvested for x-ray imaging, micro–computed tomography scanning, histologic observation, immunohistochemistry, enzyme histochemistry, and double immunofluorescence analysis. The remaining 25 rats were killed on days 0, 14, 21, 28, and 35, and mandibles were harvested for flow cytometry. Results The volume and area of the periapical lesions increased from day 0 to day 21 and then remained comparably stable after day 28. S1P1-positive cells were observed in the inflammatory periapical regions; the number of S1P1-positive cells peaked at day 14 and then decreased from day 21 to day 35. The distribution of S1P1-positive cells was positively correlated with the dynamics of RANKL-positive cells but was negatively correlated with that of Treg cells. Conclusions S1P1 expression was differentially correlated with RANKL and Treg cell infiltration in the periapical lesions and is therefore a contributing factor to the pathogenesis of such lesions.

Numerical investigation of motion and deformation of a single red blood cell in a stenosed capillary

It is generally assumed that influence of the red blood cells (RBCs) is predominant in blood rheology. The healthy RBCs are highly deformable and can thus easily squeeze through the smallest capillaries having internal diameter less than their characteristic size. On the other hand, RBCs infected by malaria or other diseases are stiffer and so less deformable. Thus it is harder for them to flow through the smallest capillaries. Therefore, it is very important to critically and realistically investigate the mechanical behavior of both healthy and infected RBCs which is a current gap in knowledge. The motion and the steady state deformed shape of the RBCs depend on many factors, such as the geometrical parameters of the capillary through which blood flows, the membrane bending stiffness and the mean velocity of the blood flow. In this study, motion and deformation of a single two-dimensional RBC in a stenosed capillary is explored by using smoothed particle hydrodynamics (SPH) method. An elastic spring network is used to model the RBC membrane, while the RBC's inside fluid and outside fluid are treated as SPH particles. The effect of RBC's membrane stiffness (kb), inlet pressure (P) and geometrical parameters of the capillary on the motion and deformation of the RBC is studied. The deformation index, RBC's mean velocity and the cell membrane energy are analyzed when the cell passes through the stenosed capillary. The simulation results demonstrate that the kb, P and the geometrical parameters of the capillary have a significant impact on the RBCs' motion and deformation in the stenosed section.

Melanoma cell colony expansion parameters revealed by approximate Bayesian computation

In vitro studies and mathematical models are now being widely used to study the underlying mechanisms driving the expansion of cell colonies. This can improve our understanding of cancer formation and progression. Although much progress has been made in terms of developing and analysing mathematical models, far less progress has been made in terms of understanding how to estimate model parameters using experimental in vitro image-based data. To address this issue, a new approximate Bayesian computation (ABC) algorithm is proposed to estimate key parameters governing the expansion of melanoma cell (MM127) colonies, including cell diffusivity, D, cell proliferation rate, λ, and cell-to-cell adhesion, q, in two experimental scenarios, namely with and without a chemical treatment to suppress cell proliferation. Even when little prior biological knowledge about the parameters is assumed, all parameters are precisely inferred with a small posterior coefficient of variation, approximately 2–12%. The ABC analyses reveal that the posterior distributions of D and q depend on the experimental elapsed time, whereas the posterior distribution of λ does not. The posterior mean values of D and q are in the ranges 226–268 µm2h−1, 311–351 µm2h−1 and 0.23–0.39, 0.32–0.61 for the experimental periods of 0–24 h and 24–48 h, respectively. Furthermore, we found that the posterior distribution of q also depends on the initial cell density, whereas the posterior distributions of D and λ do not. The ABC approach also enables information from the two experiments to be combined, resulting in greater precision for all estimates of D and λ.

A cellular automata model to investigate immune cell–tumor cell interactions in growing tumors in two spatial dimensions

We develop a hybrid cellular automata model to describe the effect of the immune system and chemokines on a growing tumor. The hybrid cellular automata model consists of partial differential equations to model chemokine concentrations, and discrete cellular automata to model cell–cell interactions and changes. The computational implementation overlays these two components on the same spatial region. We present representative simulations of the model and show that increasing the number of immature dendritic cells (DCs) in the domain causes a decrease in the number of tumor cells. This result strongly supports the hypothesis that DCs can be used as a cancer treatment. Furthermore, we also use the hybrid cellular automata model to investigate the growth of a tumor in a number of computational “cancer patients.” Using these virtual patients, the model can explain that increasing the number of DCs in the domain causes longer “survival.” Not surprisingly, the model also reflects the fact that the parameter related to tumor division rate plays an important role in tumor metastasis.