Improving LADCP velocity with external heading, pitch, and roll

Data collected with acoustic Doppler current profilers installed on CTD rosettes and lowered through the water column [lowered ADCP (LADCP) systems] are routinely used to derive full-depth profiles of ocean velocity. In addition to the uncertainties arising from random noise in the along-beam velocity measurements, LADCP-derived velocities are commonly contaminated by bias errors due to imperfectly measured instrument attitude (heading, pitch, and roll). Of particular concern are the heading measurements, because it is not usually feasible to calibrate the internal ADCP compasses with the instruments installed on a CTD rosette, away from the magnetic disturbances of the ship. Heading data from dual-headed LADCP systems, which consist of upward- and downward-pointing ADCPs installed on the same rosette, commonly indicate heading-dependent compass errors with amplitudes exceeding 10°. In an attempt to reduce LADCP velocity errors, several dozen profiles of simultaneous LADCP and magnetometer/accelerometer data were collected in the Gulf of Mexico. Agreement between the LADCP profiles and simultaneous shipboard velocity measurements improves significantly when the former are processed with external attitude measurements. Another set of LADCP profiles with external attitude data was collected in a region of the Arctic Ocean where the horizontal geomagnetic field is too weak for the ADCP compasses to work reliably. Good agreement between shipboard velocity measurements and Arctic LADCP profiles collected at magnetic dip angles exceeding and processed with external attitude measurements indicate that high-quality velocity profiles can be obtained close to the magnetic poles

Mechanisms driving variability in the ocean forcing of Pine Island Glacier

Pine Island Glacier (PIG) terminates in a rapidly melting ice shelf, and ocean circulation and temperature are implicated in the retreat and growing contribution to sea level rise of PIG and nearby glaciers. However, the variability of the ocean forcing of PIG has been poorly constrained due to a lack of multi-year observations. Here we show, using a unique record close to the Pine Island Ice Shelf (PIIS), that there is considerable oceanic variability at seasonal and interannual timescales, including a pronounced cold period from October 2011 to May 2013. This variability can be largely explained by two processes: cumulative ocean surface heat fluxes and sea ice formation close to PIIS; and interannual reversals in ocean currents and associated heat transport within Pine Island Bay, driven by a combination of local and remote forcing. Local atmospheric forcing therefore plays an important role in driving oceanic variability close to PIIS

Vigorous lateral export of the meltwater outflow from beneath an Antarctic ice shelf

The instability and accelerated melting of the Antarctic Ice Sheet are among the foremost elements of contemporary global climate change1, 2. The increased freshwater output from Antarctica is important in determining sea level rise1, the fate of Antarctic sea ice and its effect on the Earth’s albedo4, 5, ongoing changes in global deep-ocean ventilation6, and the evolution of Southern Ocean ecosystems and carbon cycling7, 8. A key uncertainty in assessing and predicting the impacts of Antarctic Ice Sheet melting concerns the vertical distribution of the exported meltwater. This is usually represented by climate-scale models3–5, 9 as a near-surface freshwater input to the ocean, yet measurements around Antarctica reveal the meltwater to be concentrated at deeper levels10, 11, 12, 13, 14. Here we use observations of the turbulent properties of the meltwater outflows from beneath a rapidly melting Antarctic ice shelf to identify the mechanism responsible for the depth of the meltwater. We show that the initial ascent of the meltwater outflow from the ice shelf cavity triggers a centrifugal overturning instability that grows by extracting kinetic energy from the lateral shear of the background oceanic flow. The instability promotes vigorous lateral export, rapid dilution by turbulent mixing, and finally settling of meltwater at depth. We use an idealized ocean circulation model to show that this mechanism is relevant to a broad spectrum of Antarctic ice shelves. Our findings demonstrate that the mechanism producing meltwater at depth is a dynamically robust feature of Antarctic melting that should be incorporated into climate-scale models

Aberrant crypt foci in colorectal carcinogenesis. Cell and crypt dynamics

Aberrant crypt foci (ACF) have been identified on the colonic mucosal surface of rodents treated with colon carcinogens and of humans after methylene-blue staining and observation under a light microscope. Several lines of evidence strongly suggest that ACF with certain morphological, histological, cell kinetics, and genetic features are precursor lesions of colon cancer both in rodents and in humans. Thus, ACF represent the earliest step in colorectal carcinogenesis. This paper has the main purpose of reviewing the evidence supporting this view, with particular emphasis on cell and crypt dynamics in ACF. ACF have been used as intermediate biomarkers of cancer development in animal studies aimed at the identification of colon carcinogens and chemopreventive agents. Recently, evidence has also shown that ACF can be effectively employed in chemopreventive studies also in humans

Exploring the coupled ocean and atmosphere system with a data science approach applied to observations from the Antarctic Circumnavigation Expedition

The Southern Ocean is a critical component of Earth’s climate system, but its remoteness makes it challenging to develop a holistic understanding of its processes from the small scale to the large scale. As a result, our knowledge of this vast region remains largely incomplete. The Antarctic Circumnavigation Expedi�tion (ACE, austral summer 2016/2017) surveyed a large number of variables describing the state of the ocean and the atmosphere, the freshwater cycle, atmospheric chemistry, and ocean biogeochemistry and microbiology. This circumpolar cruise included visits to 12 remote islands, the marginal ice zone, and the Antarctic coast. Here, we use 111 of the observed variables to study the latitudinal gradients, seasonality, shorter-term variations, geographic setting of environmental processes, and interactions between them over the duration of 90 d. To re�duce the dimensionality and complexity of the dataset and make the relations between variables interpretable we applied an unsupervised machine learning method, the sparse principal component analysis (sPCA), which describes environmental processes through 14 latent variables. To derive a robust statistical perspective on these processes and to estimate the uncertainty in the sPCA decomposition, we have developed a bootstrap approach. Our results provide a proof of concept that sPCA with uncertainty analysis is able to identify temporal patterns from diurnal to seasonal cycles, as well as geographical gradients and “hotspots” of interaction between envi�ronmental compartments. While confirming many well known processes, our analysis provides novel insights into the Southern Ocean water cycle (freshwater fluxes), trace gases (interplay between seasonality, sources, and sinks), and microbial communities (nutrient limitation and island mass effects at the largest scale ever reported). More specifically, we identify the important role of the oceanic circulations, frontal zones, and islands in shap�ing the nutrient availability that controls biological community composition and productivity; the fact that sea ice controls sea water salinity, dampens the wave field, and is associated with increased phytoplankton growth and net community productivity possibly due to iron fertilisation and reduced light limitation; and the clear regional patterns of aerosol characteristics that have emerged, stressing the role of the sea state, atmospheric chemical processing, and source processes near hotspots for the availability of cloud condensation nuclei and hence cloud formation. A set of key variables and their combinations, such as the difference between the air and sea surface temperature, atmospheric pressure, sea surface height, geostrophic currents, upper-ocean layer light intensity, surface wind speed and relative humidity played an important role in our analysis, highlighting the necessity for Earth system models to represent them adequately. In conclusion, our study highlights the use of sPCA to identify key ocean–atmosphere interactions across physical, chemical, and biological processes and their associated spatio-temporal scales. It thereby fills an important gap between simple correlation analyses and complex Earth system models. The sPCA processing code is available as open-access from the following link: https://renkulab.io/gitlab/ACE-ASAID/spca-decomposition (last access: 29 March 2021). As we show here, it can be used for an exploration of environmental data that is less prone to cognitive biases (and confirmation biases in particular) compared to traditional regression analysis that might be affected by the underlying research question

Myelin Proteomics: Molecular Anatomy of an Insulating Sheath

Fast-transmitting vertebrate axons are electrically insulated with multiple layers of nonconductive plasma membrane of glial cell origin, termed myelin. The myelin membrane is dominated by lipids, and its protein composition has historically been viewed to be of very low complexity. In this review, we discuss an updated reference compendium of 342 proteins associated with central nervous system myelin that represents a valuable resource for analyzing myelin biogenesis and white matter homeostasis. Cataloging the myelin proteome has been made possible by technical advances in the separation and mass spectrometric detection of proteins, also referred to as proteomics. This led to the identification of a large number of novel myelin-associated proteins, many of which represent low abundant components involved in catalytic activities, the cytoskeleton, vesicular trafficking, or cell adhesion. By mass spectrometry-based quantification, proteolipid protein and myelin basic protein constitute 17% and 8% of total myelin protein, respectively, suggesting that their abundance was previously overestimated. As the biochemical profile of myelin-associated proteins is highly reproducible, differential proteome analyses can be applied to material isolated from patients or animal models of myelin-related diseases such as multiple sclerosis and leukodystrophies