Computation of Oxidation Potentials of Solvated Nucleobases by Static and Dynamic Multilayer Approaches

The determination of the redox properties of nucleobases is of paramount importance to get insight into the charge-transfer processes in which they are involved, as those occurring in DNA-inspired biosensors. Although many theoretical and experimental studies have been conducted, the value of the one-electron oxidation potentials of nucleobases is not well defined. Moreover, the most appropriate theoretical protocol to model the redox properties has not been established yet. In this work, we have implemented and evaluated different static and dynamic approaches to compute the one-electron oxidation potentials of solvated nucleobases. In the static framework, two thermodynamic cycles have been tested to assess their accuracy against the direct determination of oxidation potentials from the adiabatic ionization energies. Then, the introduction of vibrational sampling, the effect of implicit and explicit solvation models, and the application of the Marcus theory have been analyzed through dynamic methods. The results revealed that the static direct determination provides more accurate results than thermodynamic cycles. Moreover, the effect of sampling has not shown to be relevant, and the results are improved within the dynamic framework when the Marcus theory is applied, especially in explicit solvent, with respect to the direct approach. Finally, the presence of different tautomers in water does not affect significantly the one-electron oxidation potentials.

The Menstrual Cycle Modulates Whole-Brain Turbulent Dynamics

Brain dynamics have recently been shown to be modulated by rhythmic changes in female sex hormone concentrations across an entire menstrual cycle. However, many questions remain regarding the specific differences in information processing across spacetime between the two main follicular and luteal phases in the menstrual cycle. Using a novel turbulent dynamic framework, we studied whole-brain information processing across spacetime scales (i.e., across long and short distances in the brain) in two open-source, dense-sampled resting-state datasets. A healthy naturally cycling woman in her early twenties was scanned over 30 consecutive days during a naturally occurring menstrual cycle and under a hormonal contraceptive regime. Our results indicated that the luteal phase is characterized by significantly higher information transmission across spatial scales than the follicular phase. Furthermore, we found significant differences in turbulence levels between the two phases in brain regions belonging to the default mode, salience/ventral attention, somatomotor, control, and dorsal attention networks. Finally, we found that changes in estradiol and progesterone concentrations modulate whole-brain turbulent dynamics in long distances. In contrast, we reported no significant differences in information processing measures between the active and placebo phases in the hormonal contraceptive study. Overall, the results demonstrate that the turbulence framework is able to capture differences in whole-brain turbulent dynamics related to ovarian hormones and menstrual cycle stages.

Diachronic Cognitive Linguistics: Past, present and future

Diachronic studies have played an increasingly important role in recent Cognitive Linguistics. This introductory paper provides an overview of some major lines of research in this field, starting with the inherently panchronic approach that characterizes most flavors of usage-based theory from Cognitive Grammar to recent complex adaptive systems approaches. In particular, the “constructionist turn” and the “quantitative turn” in Diachronic Cognitive Linguistics are discussed in detail. Diachronic Cognitive Linguistics is introduced as a multi-faceted, dynamic framework that aims at providing a holistic and nuanced picture of the complex interplay between language, cognition, and cultural evolution. In addition, this paper introduces the contributions to the present volume in some detail and discusses their relation to current research trends and paradigms within the broader framework of Diachronic Cognitive Linguistics.

3D Cell Culture Systems: Tumor Application, Advantages, and Disadvantages

The traditional two-dimensional (2D) in vitro cell culture system (on a flat support) has long been used in cancer research. However, this system cannot be fully translated into clinical trials to ideally represent physiological conditions. This culture cannot mimic the natural tumor microenvironment due to the lack of cellular communication (cell-cell) and interaction (cell-cell and cell-matrix). To overcome these limitations, three-dimensional (3D) culture systems are increasingly developed in research and have become essential for tumor research, tissue engineering, and basic biology research. 3D culture has received much attention in the field of biomedicine due to its ability to mimic tissue structure and function. The 3D matrix presents a highly dynamic framework where its components are deposited, degraded, or modified to delineate functions and provide a platform where cells attach to perform their specific functions, including adhesion, proliferation, communication, and apoptosis. So far, various types of models belong to this culture: either the culture based on natural or synthetic adherent matrices used to design 3D scaffolds as biomaterials to form a 3D matrix or based on non-adherent and/or matrix-free matrices to form the spheroids. In this review, we first summarize a comparison between 2D and 3D cultures. Then, we focus on the different components of the natural extracellular matrix that can be used as supports in 3D culture. Then we detail different types of natural supports such as matrigel, hydrogels, hard supports, and different synthetic strategies of 3D matrices such as lyophilization, electrospiding, stereolithography, microfluid by citing the advantages and disadvantages of each of them. Finally, we summarize the different methods of generating normal and tumor spheroids, citing their respective advantages and disadvantages in order to obtain an ideal 3D model (matrix) that retains the following characteristics: better biocompatibility, good mechanical properties corresponding to the tumor tissue, degradability, controllable microstructure and chemical components like the tumor tissue, favorable nutrient exchange and easy separation of the cells from the matrix.

Diachronic Cognitive Linguistics

Diachronic studies have played an increasingly important role in recent Cognitive Linguistics. This introductory paper provides an overview of some major lines of research in this field, starting with the inherently panchronic approach that characterizes most flavors of usage-based theory from Cognitive Grammar to recent complex adaptive systems approaches. In particular, the “constructionist turn” and the “quantitative turn” in Diachronic Cognitive Linguistics are discussed in detail. Diachronic Cognitive Linguistics is introduced as a multi-faceted, dynamic framework that aims at providing a holistic and nuanced picture of the complex interplay between language, cognition, and cultural evolution. In addition, this paper introduces the contributions to the present volume in some detail and discusses their relation to current research trends and paradigms within the broader framework of Diachronic Cognitive Linguistics.

Measuring robustness: sustainable success factors affecting professional football clubs

PurposeMany factors influence success at a professional football club, as each club has an exclusive definition and interpretation of success. Using the Football Management Q-Score as a foundation, the authors set out to prove the framework's robustness in the industry's current environment.Design/methodology/approachTo determine the purpose, the authors conducted interviews with Bundesliga experts. Using the Gioia Method, the authors could condense interview feedback into aggregate themes reflecting the main findings of the analysis process.FindingsFrom 1,025 codes, three main contributions resulted – the concept of intercorrelation, a more balanced and dynamic framework, and four new key drivers.Originality/valueExpert feedback validated the framework as robust, and the further main contributions gave the framework a wider application to a larger range of clubs, allowing the users of the framework to infer a greater context. Interview results proved the inclusion of Kaplan and Norton's original framework with vision and strategy.

Social Participation as a Moderator for Caregivers’ Psychological Distress: a Dynamic Panel Data Model Analysis in Japan

The adverse impact of caregiving on caregivers’ mental health and the positive impact of social participation (SP) on health are both well understood. This study examined the moderating effect of SP on the association between family caregiving and caregivers’ psychological distress (PD). We used longitudinal data from 27,869 individuals born between 1946 and 1955 collected from a 14-wave nationwide survey, which was conducted from 2005 to 2018. We estimated dynamic panel data models, which could control for an individual’s time-invariant attributes in a dynamic framework, to examine how SP moderated the association between informal caregiving and a caregiver’s PD (defined by a Kessler score of 13 or higher). We observed that the onset of caregiving increased the probability of PD by 2.1% (95% confidence interval [CI]: 1.5%–2.6%) and 1.0% (95% CI: 0.5%–1.6%) for women and men, respectively, compared to 3.4% and 2.8% as the prevalence of PD for women and men, respectively. SP moderated the association between caregiving and a caregiver’s PD by 55.8% (95% CI: 31.9%–79.8%) and 73.5% (95% CI: 36.1%–110.9%) for women and men, respectively. In addition, the moderating effect of SP on a caregiver’s PD increased as the caregiver’s age advanced especially in women. These results suggest the need to keep family caregivers from being socially isolated, especially as they get older.