A mathematical insight in the epithelial-mesenchymal-like transition in cancer cells and its effect in the invasion of the extracellular matrix

Current biological knowledge supports the existence of a secondary group of cancer cells within the body of the tumour that exhibits stem cell-like properties. These cells are termed cancer stem cells, and as opposed to themore usual differentiated cancer cells, they exhibit highermotility, they are more resilient to therapy, and are able to metastasize to secondary locations within the organism and produce new tumours. The origin of the cancer stem cells is not completely clear; they seem to stem from the differentiated cancer cells via a transition process related to the epithelial-mesenchymal transition that can also be found in normal tissue. In the current work we model and numerically study the transition between these two types of cancer cells, and the resulting “ensemble” invasion of the extracellular matrix. This leads to the derivation and numerical simulation of two systems: an algebraic-elliptic system for the transition and an advection-reaction-diffusion system of Keller-Segel taxis type for the invasion.     

Peptide Conjugated Dihydroazulene/Vinylheptafulvene Photoswitches in Aqueous Environment

Light-responsive molecules have seen a major advance in modulating biological functions in recent years. Especially photoswitches are highly attractive building blocks due to the reversible nature of their light-mediated reactivity. They are frequently used to affect both the properties of small bioactive compounds and biomacromolecules if incorporated suitably. Despite their success in a plethora of applications, only a limited set of photochromic core structures is routinely employed and a large number of photochromic couples are under-investigated in biological context. Broadening the toolbox of photoswitches available to modulate biological activity would open new avenues and unlock the full potential of photoswitchable molecules for biological studies. In this work, we explore the photochemical and thermal properties of the dihydroazulene/vinylheptafulvene photochromic couple as peptide conjugates in aqueous environment.     

Continuous glucose monitoring in interstitial fluid using glucose oxidase-based sensor compared to established blood glucose measurement in rats

Glucose monitoring is of importance for success of complex therapeutic interventions in diabetic patients. Its impact on treatment and glycemic control is demonstrated in large clinical trials. Up to eight blood glucose measurements per day are recommended. Notwithstanding, a substantial number of diabetic patients cannot or will not monitor their blood glucose appropriately. Considerable progress in control of disturbed metabolism in diabetic patients can be expected by continuous glucose monitoring. The aim of the study was to evaluate the performance of a new amperometric glucose oxidase-based glucose sensor in vitro and in vivo after subcutaneous implantation into rats.For in vitro testing current output of sensors was measured by exposure to increasing and decreasing glucose concentrations up to 472 mg dL⁻¹ over a time period of 7 days. After subcutaneous implantation of sensors into interscapular region of male rats glucose in interstitial fluid was evaluated and compared to glucose in arterial blood up to 7 days. Hyper- and hypoglycaemia were induced by intravenous application of glucose and insulin, respectively. Current of each implanted sensor was converted into glucose concentration using the first blood glucose measurement only.A change of current with glucose of 0.35 nA mg⁻¹ dL⁻¹ indicates high sensitivity of the sensor in vitro. The response time (90% of steady state) was calculated by approximately 60 s. Test strips for blood glucose measurement as reference for sensor readings was found as an appropriate and rapidly available method in rats by comparison with established hexokinase method in an automated lab analyzer with limits of agreement of +32.8 and −25.7 mg dL⁻¹ in Bland-Altman analysis. In normo- and hypoglycaemic range sensor readings in interstitial fluid correlated well with blood glucose measurements whereas hyperglycaemia was not reflected by the sensor completely when blood glucose was changing rapidly.The data given characterize a sensor with high sensitivity, long term stability and short response time. A single calibration of the sensor is required only in measurement periods up to 7 days. The findings demonstrate that the sensor is a highly promising candidate for assessment in humans.     

Barium isotope fractionation during experimental formation of the double carbonate BaMn[CO3]2 at ambient temperature

In this study, we present the first experimental results for stable barium (Ba) isotope (¹³⁷Ba/¹³⁴Ba) fractionation during low-temperature formation of the anhydrous double carbonate BaMn[CO₃]₂. This investigation is part of an ongoing work on Ba fractionation in the natural barium cycle. Precipitation at a temperature of 21±1°C leads to an enrichment of the lighter Ba isotope described by an enrichment factor of?0.11±0.06‰ in the double carbonate than in an aqueous barium-manganese(II) chloride/sodium bicarbonate solution, which is within the range of previous reports for synthetic pure BaCO ₃ (witherite) formation.     

Supercritical CO2-Brine Relative Permeability Experiments in Reservoir Rocks��Literature Review and Recommendations

The relative permeability of carbon dioxide (CO₂) to brine influences the injectivity and plume migration when CO₂ is injected in a reservoir for CO₂ storage or enhanced oil recovery (EOR) purposes. It is common practice to determine the relative permeability of a fluid by means of laboratory measurements. Two principal approaches are used to obtain a relative permeability data: steady state and unsteady state. Although CO₂ has been employed in enhanced oil recovery, not much data can be found in the open literature. The few studies available report wide ranges for CO₂ relative permeability in typical sedimentary rocks such as Berea sandstone, dolomite, and others. The experimental setups vary for each study, employing steady and unsteady state approaches, different experimental parameters such as temperature, pressure, rock type, etc. and various interpretation methods. Hence, it is inherently difficult to compare the data and determine the origin of differences. It is evident that more experiments are needed to close this knowledge gap on relative permeability. This article concludes that standards for lab measurements need to be defined a. to establish a reliable CO₂-brine relative permeability measurement method that can be repeated under the same conditions in any lab and b. to enable comparison of the data to accurately predict the well injection and fluid migration behavior in the reservoir.     

Non-linear model parameter estimation–estimating a feasible parameter set with respect to model use

This article deals with non-linear model parameter estimation from experimental data. As for non-linear models a rigorous identifiability analysis is difficult to perform, parameter estimation is performed in such a way that uncertainty in the estimated parameter values is represented by the range of model use results when the model is used for a certain purpose. Using this approach, the article presents a simulation study where the objective is to discover whether the estimation of model parameters can be improved, so that a small enough range of model use results is obtained. The results of the study indicate that from plant measurements available for the estimation of model parameters, it is possible to extract data that are important for the estimation of model parameters relative to a certain model use. If these data are improved by a proper measurement campaign (e.g. proper choice of measured variables, better accuracy, higher measurement frequency) it is to be expected that a valid model for a certain model use will be obtained. The simulation study is performed for an activated sludge model from wastewater treatment, while the estimation of model parameters is done by Monte Carlo simulation.     

Barium isotope fractionation during the experimental transformation of aragonite to witherite and of gypsum to barite,and the effect of ion (de)solvation

In this study, we present the experimental results for stable barium (Ba) isotope fractionation (¹³⁷Ba/¹³⁴Ba) during the transformation of aragonite (CaCO₃) and gypsum (CaSO₄·2H₂O) in Ba-bearing aqueous solution to witherite (BaCO₃) and barite (BaSO₄), respectively. The process was studied at three temperatures between 4 and 60?°C. In all cases, the transformation leads to a relative enrichment of the lighter ¹³⁴Ba isotope in the solid compared to the aqueous solution, with ^137/134Ba enrichment factors between –0.11 and ?0.17?‰ for BaCO₃, and –0.21 and –0.26?‰ for BaSO₄. The corresponding mass-dependent ^138/134Ba enrichment factors are ?0.15 to –0.23?‰ for BaCO₃, and –0.28 to –0.35?‰ for BaSO₄. The magnitude of isotope fractionation is within the range of recent reports for witherite and barite formation, as well as trace Ba incorporation into orthorhombic aragonite, and no substantial impact of temperature can be found between 4 and 80?°C. In previous studies, ion (de)solvation has been suggested to impact both the crystallization process of Ba-bearing solids and associated Ba isotope fractionation. Precipitation experiments of BaSO₄ and BaCO₃ using an methanol-containing aqueous solution indicate only a minor effect of ion and crystal surface (de)solvation on the overall Ba isotope fractionation process.     

Maximizing Complementary Quantities by Projective Measurements

In this work, we study the so-called quantitative complementarity quantities. We focus in the following physical situation: two qubits (q _A and q _B ) are initially in a maximally entangled state. One of them (q _B ) interacts with a N-qubit system (R). After the interaction, projective measurements are performed on each of the qubits of R, in a basis that is chosen after independent optimization procedures: maximization of the visibility, the concurrence, and the predictability. For a specific maximization procedure, we study in detail how each of the complementary quantities behave, conditioned on the intensity of the coupling between q _B and the N qubits. We show that, if the coupling is sufficiently “strong,” independent of the maximization procedure, the concurrence tends to decay quickly. Interestingly enough, the behavior of the concurrence in this model is similar to the entanglement dynamics of a two qubit system subjected to a thermal reservoir, despite that we consider finite N. However, the visibility shows a different behavior: its maximization is more efficient for stronger coupling constants. Moreover, we investigate how the distinguishability, or the information stored in different parts of the system, is distributed for different couplings.     

Quantum Chemical Investigation of the Initial Steps of the Yttrium‐Mediated Polymerization of Ethene and Propene

The mechanistic details of the initial steps of the polymerization brought about by a dicyclopentadienyl yttriumhydrid catalyst have been computationally investigated using approximate density functional theory. In accord with the experimental information, the overall reaction sequence Cp₂YH + C₂H₄ → Cp₂Y–C₂H₅ and Cp₂YH + C₃H₆ → Cp₂Y–C₃H₇ is computed to be exothermic by ca. 22.2 and 20.8 kcal mol^–1, respectively. The reaction mechanism predicted by our calculations is in harmony with the available experimental information but provides additional information into the various elementary steps of this reaction, which could not be obtained by experimental means.     

Using Background Knowledge from Preceding Studies for Building a Random Forest Prediction Model: A Plasmode Simulation Study

There is an increasing interest in machine learning (ML) algorithms for predicting patient outcomes, as these methods are designed to automatically discover complex data patterns. For example, the random forest (RF) algorithm is designed to identify relevant predictor variables out of a large set of candidates. In addition, researchers may also use external information for variable selection to improve model interpretability and variable selection accuracy, thereby prediction quality. However, it is unclear to which extent, if at all, RF and ML methods may benefit from external information. In this paper, we examine the usefulness of external information from prior variable selection studies that used traditional statistical modeling approaches such as the Lasso, or suboptimal methods such as univariate selection. We conducted a plasmode simulation study based on subsampling a data set from a pharmacoepidemiologic study with nearly 200,000 individuals, two binary outcomes and 1152 candidate predictor (mainly sparse binary) variables. When the scope of candidate predictors was reduced based on external knowledge RF models achieved better calibration, that is, better agreement of predictions and observed outcome rates. However, prediction quality measured by cross-entropy, AUROC or the Brier score did not improve. We recommend appraising the methodological quality of studies that serve as an external information source for future prediction model development.