Combinatorial Therapeutic Approaches with Nanomaterial-Based Photodynamic Cancer Therapy

Photodynamic therapy (PDT), in which a light source is used in combination with a photosensitizer to induce local cell death, has shown great promise in therapeutically targeting primary tumors with negligible toxicity and minimal invasiveness. However, numerous studies have shown that noninvasive PDT alone is not sufficient to completely ablate tumors in deep tissues, due to its inherent shortcomings. Therefore, depending on the characteristics and type of tumor, PDT can be combined with surgery, radiotherapy, immunomodulators, chemotherapy, and/or targeted therapy, preferably in a patient-tailored manner. Nanoparticles are attractive delivery vehicles that can overcome the shortcomings of traditional photosensitizers, as well as enable the codelivery of multiple therapeutic drugs in a spatiotemporally controlled manner. Nanotechnology-based combination strategies have provided inspiration to improve the anticancer effects of PDT. Here, we briefly introduce the mechanism of PDT and summarize the photosensitizers that have been tested preclinically for various cancer types and clinically approved for cancer treatment. Moreover, we discuss the current challenges facing the combination of PDT and multiple cancer treatment options, and we highlight the opportunities of nanoparticle-based PDT in cancer therapies.

Modelling of Coupled Mass and Thermal Balances in Hall-Heroult Cells During Anode Change

As the most routine work practice in an aluminium reduction cell, anode change introduces substantial perturbations that adversely affect the mass and heat balance of the cell which may lead to loss of process efficiency and increased energy consumption. The literature lacks a dynamic mathematical model that describes the interactions among cell variables (e.g., electrolyte temperature and flow, anode current distribution, and cell heat loss) during and following this operation, which could otherwise be used to understand the process in greater depth and to develop changes that improve process operations and control. This paper presents a spatially-discretised dynamic model for anode replacement that integrates mass balance, thermal balance and cell voltage to describe and predict local cell variables. It was experimentally validated with an industrial cell undergoing an anode change procedure. This generic model can be applied to different cell design or process conditions by using appropriate parameters (e.g., heat transfer coefficients, conductivities, and flow patterns). The model can be used to improve existing process operations or control strategies for higher process efficiency, lower energy consumption, and lower emissions.

A mechanical G2 checkpoint controls epithelial cell division through E-cadherin-mediated regulation of Wee1-Cdk1

Epithelial cell divisions must be tightly coordinated with cell loss to preserve epithelial integrity. However, it is not well understood how the rate of epithelial cell division adapts to changes in cell number, for instance during homeostatic turnover or upon wounding of epithelia. Here, we show epithelial cells sense local cell density through mechanosensitive E-cadherin adhesions to control G2/M cell cycle progression. We demonstrate that tensile forces on E-cadherin adhesions are reduced as local cell density increases, which prompts the accumulation of the G2 checkpoint kinase Wee1. This elevated abundance of Wee1 results in inhibitory phoshorylation of Cdk1, and thereby establishes a pool of cells that is temporarily halted in G2-phase. Importantly, these cells are readily triggered to divide upon epithelial wounding, due to the consequent increase in intercellular forces and resulting degradation of Wee1. Our data thus demonstrate that epithelial cell division is controlled by a mechanical G2 checkpoint, which is regulated by cell density-dependent intercellular forces sensed and transduced by E-cadherin adhesions.

Intraocular dendritic cells characterize HLA-B27-associated acute anterior uveitis

Uveitis describes a heterogeneous group of inflammatory eye diseases characterized by infiltration of leukocytes into the uveal tissues. Uveitis associated with the HLA haplotype B27 (HLA-B27) is a common subtype of uveitis and a prototypical ocular immune-mediated disease. Local immune mechanisms driving human uveitis are poorly characterized mainly due to the limited available biomaterial and subsequent technical limitations. Here, we provide the first high-resolution characterization of intraocular leukocytes in HLA-B27-positive (n = 4) and -negative (n = 2) anterior uveitis and an infectious endophthalmitis control (n = 1) by combining single-cell RNA-sequencing with flow cytometry and protein analysis. Ocular cell infiltrates consisted primarily of lymphocytes in both subtypes of uveitis and of myeloid cells in infectious endophthalmitis. HLA-B27-positive uveitis exclusively featured a plasmacytoid and classical dendritic cell (cDC) infiltrate. Moreover, cDCs were central in predicted local cell-cell communication. This suggests a unique pattern of ocular leukocyte infiltration in HLA-B27-positive uveitis with relevance to DCs.

Cancer Growth Inhibition Using Predictive Mathematical Models of Signaling Pathways

Cancer cells develop several hallmark changes over the progress of the tumor process. Cell assistance in multicellular organisms is regulated by the division of cell coordination by aggressive growth modulation. In this perspective, the use of molecular indicators triggering cell division is a mystery, because a cancer cell can manipulate any molecule that induces and helps growth, disturbing cellular assistance. An effective alteration proceeding to tumors must develop to be competitive, allowing a cancer cell to pass a signal resulting in better selection chances. The subjective simulation of physiological systems has become increasingly valuable in recent years, and there is now a wide range of mathematical models of signalling pathways that have contributed to some groundbreaking discoveries and hypotheses as to how this system works. Here we discuss various modeling methods and their application to the physiology of medical systems, focusing on the identification of parameters in ordinary differential equation models and their significance for forecasting cellular decisions in network modeling. In situations of global and local cell-to-cell rivalry, we quantify how this mechanism impacts a mutated cell's fixing chance of producing such a signal, and consider that this process will play a vital role in reducing cancer.

Clarifying intercellular signalling in yeast: Saccharomyces cerevisiae does not undergo a quorum sensing-dependent switch to filamentous growth

Saccharomyces cerevisiae can alter its morphology to a filamentous form associated with unipolar budding in response to environmental stressors. Induction of filamentous growth is suggested under nitrogen deficiency in response to alcoholic signalling molecules through a quorum sensing mechanism. To investigate this claim, we analysed the budding pattern of S. cerevisiae cells over time under low nitrogen while concurrently measuring cell density and extracellular metabolite concentration. We found that the proportion of cells displaying unipolar budding increased between local cell densities of 4.8x106 and 5.3x107 cells/ml within 10 to 20 hours of growth. However, the observed increase in unipolar budding could not be reproduced when cells were prepared at the critical cell density and in conditioned media. Removing the nutrient restriction by growth in high nitrogen conditions also resulted in an increase in unipolar budding between local cell densities of 5.2x106 and 8.2x107 cells/ml within 10 to 20 hours of growth, but there were differences in metabolite concentration compared to the low nitrogen conditions. This suggests that neither cell density, metabolite concentration, nor nitrogen deficiency were necessary or sufficient to increase the proportion of unipolar budding cells. It is therefore unlikely that quorum sensing is the mechanism controlling the switch to filamentous growth in S. cerevisiae. Only a high concentration of the putative signalling molecule, 2-phenylethanol resulted in an increase in unipolar budding, but this concentration was not physiologically relevant. We suggest that the compound 2-phenylethanol acts through a toxicity mechanism, rather than quorum sensing, to induce filamentous growth.

Simulations reveal that different responses to cell crowding determine the expansion of p53 and Notch mutant clones in squamous epithelia

During ageing, normal epithelial tissues progressively accumulate clones carrying mutations that increase mutant cell fitness above that of wild-type cells. Such mutants spread widely through the tissues, yet despite this cellular homeostasis and functional integrity of the epithelia are maintained. Two of the genes most commonly mutated in human skin and oesophagus are p53 and Notch1 , both of which are also recurrently mutated in cancers of these tissues. From observations taken in human and mouse epithelia, we find that clones carrying p53 and Notch pathway mutations have different clone dynamics which can be explained by their different responses to local cell crowding. p53 mutant clone growth in mouse epidermis approximates a logistic curve, but feedbacks responding to local crowding are required to maintain tissue homeostasis. We go on to show that the observed ability of Notch pathway mutant cells to displace the wild-type population in the mouse oesophageal epithelium reflects a local density feedback that affects both mutant and wild-type cells equally. We then show how these distinct feedbacks are consistent with the distribution of mutations observed in human datasets and are suggestive of a putative mechanism to constrain these cancer-associated mutants.

A SOLUTION TO STEFAN PROBLEM USING EULERIAN TWO FLUID VOF MODEL

A novel approach for the solution of Stefan problem within the framework of the multi fluid model supplemented with Volume of Fluid (VOF) method, i.e. two-fluid VOF, is presented in this paper. The governing equation set is comprised of mass, momentum and energy conservation equations, written on a per phase basis and supplemented with closure models via the source terms. In our method, the heat and mass transfer is calculated from the heat transfer coefficient, which has a fictitious function and depends on the local cell size and the thermal conductivity, and the implementation is straightforward because of the usage of the local value instead of a global parameter. The interface sharpness is ensured by the application of the geometrical reconstruction scheme implemented in VOF. The model is verified for three types of computational meshes including triangular cells, and good agreement was obtained for the interface position and the temperature field. Although the developed method was validated only for Stefan problem, the application of the method to engineering problems is considered to be straightforward since it is implemented to a commercial CFD code only using a local value; especially in the field of naval hydrodynamics wherein the reduction of ship resistance using boiling flow can be computed efficiently since the method handles phase change processes using low resolution meshes.