Hierarchical patterning modes orchestrate hair follicle morphogenesis

Two theories address the origin of repeating patterns, such as hair follicles, limb digits, and intestinal villi, during development. The Turing reaction–diffusion system posits that interacting diffusible signals produced by static cells first define a prepattern that then induces cell rearrangements to produce an anatomical structure. The second theory, that of mesenchymal self-organisation, proposes that mobile cells can form periodic patterns of cell aggregates directly, without reference to any prepattern. Early hair follicle development is characterised by the rapid appearance of periodic arrangements of altered gene expression in the epidermis and prominent clustering of the adjacent dermal mesenchymal cells. We assess the contributions and interplay between reaction–diffusion and mesenchymal self-organisation processes in hair follicle patterning, identifying a network of fibroblast growth factor (FGF), wingless-related integration site (WNT), and bone morphogenetic protein (BMP) signalling interactions capable of spontaneously producing a periodic pattern. Using time-lapse imaging, we find that mesenchymal cell condensation at hair follicles is locally directed by an epidermal prepattern. However, imposing this prepattern’s condition of high FGF and low BMP activity across the entire skin reveals a latent dermal capacity to undergo spatially patterned self-organisation in the absence of epithelial direction. This mesenchymal self-organisation relies on restricted transforming growth factor (TGF) β signalling, which serves to drive chemotactic mesenchymal patterning when reaction–diffusion patterning is suppressed, but, in normal conditions, facilitates cell movement to locally prepatterned sources of FGF. This work illustrates a hierarchy of periodic patterning modes operating in organogenesis

Feather arrays are patterned by interacting signalling and cell density waves

Feathers are arranged in a precise pattern in avian skin. They first arise during development in a row along the dorsal midline, with rows of new feather buds added sequentially in a spreading wave. We show that the patterning of feathers relies on coupled fibroblast growth factor (FGF) and bone morphogenetic protein (BMP) signalling together with mesenchymal cell movement, acting in a coordinated reaction-diffusion-taxis system. This periodic patterning system is partly mechanochemical, with mechanical-chemical integration occurring through a positive feedback loop centred on FGF20, which induces cell aggregation, mechanically compressing the epidermis to rapidly intensify FGF20 expression. The travelling wave of feather formation is imposed by expanding expression of Ectodysplasin A (EDA), which initiates the expression of FGF20. The EDA wave spreads across a mesenchymal cell density gradient, triggering pattern formation by lowering the threshold of mesenchymal cells required to begin to form a feather bud. These waves, and the precise arrangement of feather primordia, are lost in the flightless emu and ostrich, though via different developmental routes. The ostrich retains the tract arrangement characteristic of birds in general but lays down feather primordia without a wave, akin to the process of hair follicle formation in mammalian embryos. The embryonic emu skin lacks sufficient cells to enact feather formation, causing failure of tract formation, and instead the entire skin gains feather primordia through a later process. This work shows that a reaction-diffusion-taxis system, integrated with mechanical processes, generates the feather array. In flighted birds, the key role of the EDA/Ectodysplasin A receptor (EDAR) pathway in vertebrate skin patterning has been recast to activate this process in a quasi-1-dimensional manner, imposing highly ordered pattern formation

Improved Constraints on Northern Extratropical CO2 Fluxes Obtained by Combining Surface-Based and Space-Based Atmospheric CO2 Measurements

© 2020. The Authors. Top-down estimates of CO2 fluxes are typically constrained by either surface-based or space-based CO2 observations. Both of these measurement types have spatial and temporal gaps in observational coverage that can lead to differences in inferred fluxes. Assimilating both surface-based and space-based measurements concurrently in a flux inversion framework improves observational coverage and reduces sampling related artifacts. This study examines the consistency of flux constraints provided by these different observations and the potential to combine them by performing a series of 6-year (2010–2015) CO2 flux inversions. Flux inversions are performed assimilating surface-based measurements from the in situ and flask network, measurements from the Total Carbon Column Observing Network (TCCON), and space-based measurements from the Greenhouse Gases Observing Satellite (GOSAT), or all three data sets combined. Combining the data sets results in more precise flux estimates for subcontinental regions relative to any of the data sets alone. Combining the data sets also improves the accuracy of the posterior fluxes, based on reduced root-mean-square differences between posterior flux-simulated CO2 and aircraft-based CO2 over midlatitude regions (0.33–0.56 ppm) in comparison to GOSAT (0.37–0.61 ppm), TCCON (0.50–0.68 ppm), or in situ and flask measurements (0.46–0.56 ppm) alone. These results suggest that surface-based and GOSAT measurements give complementary constraints on CO2 fluxes in the northern extratropics and can be combined in flux inversions to improve constraints on regional fluxes. This stands in contrast with many earlier attempts to combine these data sets and suggests that improvements in the NASA Atmospheric CO2 Observations from Space (ACOS) retrieval algorithm have significantly improved the consistency of space-based and surface-based flux constraints

Raman Spectroscopy and Regenerative Medicine: A Review

The field of regenerative medicine spans a wide area of the biomedical landscape—from single cell culture in laboratories to human whole-organ transplantation. To ensure that research is transferrable from bench to bedside, it is critical that we are able to assess regenerative processes in cells, tissues, organs and patients at a biochemical level. Regeneration relies on a large number of biological factors, which can be perturbed using conventional bioanalytical techniques. A versatile, non-invasive, non-destructive technique for biochemical analysis would be invaluable for the study of regeneration; and Raman spectroscopy is a potential solution. Raman spectroscopy is an analytical method by which chemical data are obtained through the inelastic scattering of light. Since its discovery in the 1920s, physicists and chemists have used Raman scattering to investigate the chemical composition of a vast range of both liquid and solid materials. However, only in the last two decades has this form of spectroscopy been employed in biomedical research. Particularly relevant to regenerative medicine are recent studies illustrating its ability to characterise and discriminate between healthy and disease states in cells, tissue biopsies and in patients. This review will briefly outline the principles behind Raman spectroscopy and its variants, describe key examples of its applications to biomedicine, and consider areas of regenerative medicine that would benefit from this non-invasive bioanalytical tool

Hydrographic and hydrochemical conditions in the Gotland Deep area between 1992 and 2003

The paper describes the hydrographic-hydrochemical development in the eastern Gotland Basin between the major saltwater inflows into the Baltic Sea in 1993 and 2003. This period is characterised by only low inflow activity. The most important hydrographic events were the effects of the very strong inflow in 1993 and the weak inflows in 1993/1994 and 1997. The 1993/1994 inflows led to deep-water renewal, a steep fall in deep-water temperatures, and increasing salinity. The effects of the inflow of very warm, saline and oxygen-rich water in autumn 1997 were observed in the deep water in 1998, resulting in temperatures rising to 7◦C. The recent renewal in spring 2003 is reflected in the decreasing temperature, higher salinity and improved ventilation of the bottom water. Changes in the redox conditions exert a considerable influence on the nutrient distribution. During stagnation periods, there is enrichment of phosphate and ammonium, while nitrate is absent. Thus, around 31 μmol l−1 ammonium and 7 μmol l−1 phosphate were measured prior to the water renewal in 2003. Deepwater ventilation results in lower phosphate concentrations of around 2 μmol l−1, the nitrification of ammonium and the occurrence of nitrate. For the observation period, an estimate of nutrients stored in the deep water was done for the eastern Gotland Basin. During the recent stagnation period, there was an increase of up to 150% in the phosphate pool below the halocline, whereas the pool of inorganic nitrogen compounds decreased to 80% compared with 1992 when the previous stagnation period had ended. Under specific circumstances, these unbalanced nutrients can be made available to the upper water layers and can induce large-scale blooms of algae, especially of cyanobacteria

Temporal and spatial evolution of the Baltic deep water renewal in spring 2003

In January 2003, a deep-water renewal process in the Baltic Sea commenced with an inflow of about 200 km3 of cold and well oxygenated water from the Kattegat, half of which was of salinity >17 PSU; it is considered to be the most important inflow since 1993. Related front propagation and the ventilation of anoxic waters between the western and the central Baltic were recorded by the Darss Sill measuring mast, the Arkona Basin buoy, a subsurface mooring in the Eastern Gotland Basin, and hydrographic research cruises conducted in January, February, March, May and August 2003. Already in May, the central Gotland Basin was reached by water with near-bottom oxygen concentrations among the highest ever recorded there. A comprehensive review of the observed spatial and temporal structures together with additional background data is presented. Estimates of the intensity of the present inflow are discussed

TCCON Philippines: First Measurement Results, Satellite Data and Model Comparisons in Southeast Asia

The Total Carbon Column Observing Network (TCCON) is a global network dedicated to the precise and accurate measurements of greenhouse gases (GHG) in the atmosphere. The TCCON station in Burgos, Ilocos Norte, Philippines was established with the primary purpose of validating the upcoming Greenhouse gases Observing SATellite-2 (GOSAT-2) mission and in general, to respond to the need for reliable ground-based validation data for satellite GHG observations in the region. Here, we present the first 4 months of data from the new TCCON site in Burgos, initial comparisons with satellite measurements of CO2 and model simulations of CO. A nearest sounding from Japan\u27s GOSAT as well as target mode observations from NASA\u27s Orbiting Carbon Observatory 2 (OCO-2) showed very good consistency in the retrieved column-averaged dry air mole fractions of CO2, yielding TCCON - satellite differences of 0.86 ± 1.06 ppm for GOSAT and 0.83 ± 1.22 ppm for OCO-2. We also show measurements of enhanced CO, probably from East Asia. GEOS-Chem model simulations were used to study the observed CO variability. However, despite the model capturing the pattern of the CO variability, there is an obvious underestimation in the CO magnitude in the model. We conclude that more measurements and modeling are necessary to adequately sample the variability over different seasons and to determine the suitability of current inventories

Comparisons of the Orbiting Carbon Observatory-2 (OCO-2) X\u3csub\u3eCO2\u3c/sub\u3e measurements with TCCON

NASA\u27s Orbiting Carbon Observatory-2 (OCO-2) has been measuring carbon dioxide column-averaged dry-air mole fraction, XCO2, in the Earth\u27s atmosphere for over 2 years. In this paper, we describe the comparisons between the first major release of the OCO-2 retrieval algorithm (B7r) and XCO2 from OCO-2\u27s primary ground-based validation network: the Total Carbon Column Observing Network (TCCON). The OCO-2 XCO2 retrievals, after filtering and bias correction, agree well when aggregated around and coincident with TCCON data in nadir, glint, and target observation modes, with absolute median differences less than 0.4 ppm and RMS differences less than 1.5 ppm. After bias correction, residual biases remain. These biases appear to depend on latitude, surface properties, and scattering by aerosols. It is thus crucial to continue measurement comparisons with TCCON to monitor and evaluate the OCO-2 XCO2 data quality throughout its mission