Incorporating chemical signalling factors into cell-based models of growing epithelial tissues

In this paper we present a comprehensive computational framework within which the effects of chemical signalling factors on growing epithelial tissues can be studied. The method incorporates a vertex-based cell model, in conjunction with a solver for the governing chemical equations. The vertex model provides a natural mesh for the finite element method (FEM), with node movements determined by force laws. The arbitrary Lagrangian–Eulerian formulation is adopted to account for domain movement between iterations. The effects of cell proliferation and junctional rearrangements on the mesh are also examined. By implementing refinements of the mesh we show that the finite element (FE) approximation converges towards an accurate numerical solution. The potential utility of the system is demonstrated in the context of Decapentaplegic (Dpp), a morphogen which plays a crucial role in development of the Drosophila imaginal wing disc. Despite the presence of a Dpp gradient, growth is uniform across the wing disc. We make the growth rate of cells dependent on Dpp concentration and show that the number of proliferation events increases in regions of high concentration. This allows hypotheses regarding mechanisms of growth control to be rigorously tested. The method we describe may be adapted to a range of potential application areas, and to other cell-based models with designated node movements, to accurately probe the role of morphogens in epithelial tissues

Photo-elastic properties of the wing imaginal disc of Drosophila

In the study of developmental biology, the physical properties and constraints of the developing tissues are of great importance. In spite of this, not much is known about the elastic properties of biologically relevant tissues that are studied in biology labs. Here, we characterize properties of the wing imaginal disc of Drosophila, which is a precursor organ intensely studied in the framework of growth control and cell polarity. In order to determine the possibility of measuring mechanical stresses inside the tissue during development, we quantify the photo-elastic properties of the tissue by direct mechanical manipulation. We obtain a photo-elastic constant of [Formula: see text]

Coastal Subsistence, Maritime Trade, and the Colonization of Small Offshore Islands in Eastern African Prehistory

Recent archaeological research has firmly established eastern Africa's offshore islands as important localities for understanding the region's pre-Swahili maritime adaptations and early Indian Ocean trade connections. While the importance of the sea and small offshore islands to the development of urbanized and mercantile Swahili societies has long been recognized, the formative stages of island colonization—and in particular the processes by which migrating Iron Age groups essentially became “maritime”—are still relatively poorly understood. Here we present the results of recent archaeological fieldwork in the Mafia Archipelago, which aims to understand these early adaptations and situate them within a longer-term trajectory of island settlement and pre-Swahili cultural developments. We focus on the results of zooarchaeological, archaeobotanical, and material culture studies relating to early subsistence and trade on this island to explore the changing significance of marine resources to the local economy. We also discuss the implications of these maritime adaptations for the development of local and long-distance Indian Ocean trade networks

Comparison of Techniques for Bonding VCSELs Directly to Ics

This paper reports the successful bonding of 8 x 8 and 4 x 4 VCSEL arrays to Si CMOS and GaAs MESFET integrated circuits and to GaAs substrates. Three different bonding techniques are demonstrated and their electrical, optical and mechanical characteristics are compared. All three techniques remove the substrate from the VCSEL wafer, leaving individual VCSELs bonded directly to locations within the integrated circuit

A cross dialectal view of the Arabic dative alternation

This paper is concerned with the syntax of ditransitive verbs in Arabic.We concentrate on the vernaculars, focussing in particular on three geographically spread dialects: Egyptian Cairene Arabic, the dominant vernacular in Egypt, Hijazi Arabic, spoken in Western Saudi Arabia and Maltese, a mixed language with a Magrebi/Siculo-Arabic stratum. We show that all three exhibit an alternation (the dative alternation) between a ditransitive ('double object') construction and a corresponding prepositional dative construction, and outline a number of differences between these constructions in the different varieties of Arabic. We consider the distribution of verbs exhibiting the dative alternation in the light of Ryding's (2011) observations concerning Modern Standard Arabic

Study of a novel type of the optical modes in VCSELs

We study novel side-emitting modes in VCSEL microcavities. These modes correspond to π-shaped propagation along the mesa diameter, reflection from angled mesa walls and bottom Bragg reflector. We believe this study of π-modes is important for optimization of VCSEL design for improvement of efficiency

Mechanisms and mechanics of cell competition in epithelia

When fast-growing cells are confronted with slow-growing cells in a mosaic tissue, the slow-growing cells are often progressively eliminated by apoptosis through a process known as cell competition. The underlying signalling pathways remain unknown, but recent findings have shown that cell crowding within an epithelium leads to the eviction of cells from the epithelial sheet. This suggests that mechanical forces could contribute to cell elimination during cell competition

Stratification of hospitalized COVID-19 patients into clinical severity progression groups by immuno-phenotyping and machine learning

Quantitative or qualitative differences in immunity may drive clinical severity in COVID-19. Although longitudinal studies to record the course of immunological changes are ample, they do not necessarily predict clinical progression at the time of hospital admission. Here we show, by a machine learning approach using serum pro-inflammatory, anti-inflammatory and anti-viral cytokine and anti-SARS-CoV-2 antibody measurements as input data, that COVID-19 patients cluster into three distinct immune phenotype groups. These immune-types, determined by unsupervised hierarchical clustering that is agnostic to severity, predict clinical course. The identified immune-types do not associate with disease duration at hospital admittance, but rather reflect variations in the nature and kinetics of individual patient's immune response. Thus, our work provides an immune-type based scheme to stratify COVID-19 patients at hospital admittance into high and low risk clinical categories with distinct cytokine and antibody profiles that may guide personalized therapy. Developing predictive methods to identify patients with high risk of severe COVID-19 disease is of crucial importance. Authors show here that by measuring anti-SARS-CoV-2 antibody and cytokine levels at the time of hospital admission and integrating the data by unsupervised hierarchical clustering/machine learning, it is possible to predict unfavourable outcome