Prey fractionation in the Archaeocyatha and its implication for the ecology of the first animal reef systems

<jats:title>Abstract</jats:title><jats:p>Archaeocyaths are the most abundant sponges from the Cambrian period, having formed the first animal reef communities more than 500 million years ago. The Archaeocyatha are index fossils for correlating rocks of similar ages globally because of their abundance, extensive geographic distribution, detailed anatomy, and well-established taxonomy. Their ecological significance remains incompletely explored, yet they are known to have strongly competitively interacted, unlike modern sponges. This study examines the feeding ecology of the fossil remains of Siberian archaeocyath assemblages. As suspension feeders, archaeocyaths filtered plankton from the water column through pores in their outer wall. Here we outline a new method to estimate the limit on the upper size of plankton that could be consumed by an archaeocyath during life. The archaeocyaths examined were predominantly feeding on nanoplankton and microplankton such as phytoplankton and protozooplankton. Size-frequency distributions of pore sizes from six different Siberian archaeocyath assemblages, ranging from Tommotian to Botoman in age, reveal significantly different upper limits to the prey consumed at each locality. Some of the assemblages contain specimens that could have fed on larger organisms extending into the mesoplankton, including micro-invertebrates as a possible food resource. These results show that during the establishment of the first animal reef systems, prey partitioning was established as a way of reducing competition. This method has applicability for understanding the construction and the functioning of the first reef systems, as well as helping to understand modern reef systems and their development though time and space.</jats:p&gt

Metabolic signatures of pneumonia in critical care: a paradigm shift in diagnosis and therapeutic monitoring

Pneumonia and ventilator associated pneumonia (VAP) are a frequent cause for admission to Intensive Care and complication of ventilation respectively. VAP occurs in 10-40% of patients requiring mechanical ventilation and is associated with increased mortality, morbidity and healthcare costs. Diagnosis can be difficult due to poor predictive value of clinical features and low specificity of radiological changes. Bronchoscopic techniques are often invasive, may not be suitable for all patients and are not without complications. New tests are required to improve the diagnosis of these conditions allowing early, appropriate antibiotic treatment. In this study several techniques were used to explore the value of profiling of a range of biofluids obtained from ventilated patients as an aid to diagnosis of pneumonia. Patients were recruited from Intensive Care with either a diagnosis of pneumonia or brain injury. Those with brain injuries were tracked to identify patients who developed VAP. Serum, urine and exhaled breath condensate (EBC) were collected from all patients. Metabonomics, an approach that identifies changes in metabolic profiles associated with disease, was applied using proton nuclear magnetic resonance spectroscopy to both blood and urine and with mass spectrometry (MS) to exhaled breath condensate. Following from the metabonomic work a panel of inflammatory mediators, including cytokines and eicosanoids were measured in serum using MS and flow cytometry to explore the inflammatory changes in these patients. Overall metabolic and inflammatory profiling of serum showed potential as an adjunct to clinical diagnosis especially when combined with clinical data. Analysis of urine and EBC proved more challenging due the number of drug metabolites and low concentration of metabolites they respectively contained. In summary this study has added to the field by demonstrating the potential for profiling techniques of serum from critically ill patients to assist in the diagnosis of both pneumonia and VAP.Open Acces

Early fossil record of Euarthropoda and the Cambrian Explosion

Euarthropoda is one of the best-preserved fossil animal groups and has been the most diverse animal phylum for over 500 million years. Fossil Konservat-Lagerstätten, such as Burgess Shale-type deposits (BSTs), show the evolution of the euarthropod stem lineage during the Cambrian from 518 million years ago (Ma). The stem lineage includes nonbiomineralized groups, such as Radiodonta (e.g., Anomalocaris) that provide insight into the step-by-step construction of euarthropod morphology, including the exoskeleton, biramous limbs, segmentation, and cephalic structures. Trilobites are crown group euarthropods that appear in the fossil record at 521 Ma, before the stem lineage fossils, implying a ghost lineage that needs to be constrained. These constraints come from the trace fossil record, which show the first evidence for total group Euarthropoda (e.g., Cruziana, Rusophycus) at around 537 Ma. A deep Precambrian root to the euarthropod evolutionary lineage is disproven by a comparison of Ediacaran and Cambrian lagerstätten. BSTs from the latest Ediacaran Period (e.g., Miaohe biota, 550 Ma) are abundantly fossiliferous with algae but completely lack animals, which are also missing from other Ediacaran windows, such as phosphate deposits (e.g., Doushantuo, 560 Ma). This constrains the appearance of the euarthropod stem lineage to no older than 550 Ma. While each of the major types of fossil evidence (BSTs, trace fossils, and biomineralized preservation) have their limitations and are incomplete in different ways, when taken together they allow a coherent picture to emerge of the origin and subsequent radiation of total group Euarthropoda during the Cambrian

Changing the picture of Earth's earliest fossils (3.5-1.9 Ga) with new approaches and new discoveries

New analytical approaches and discoveries are demanding fresh thinking about the early fossil record. The 1.88-Ga Gunflint chert provides an important benchmark for the analysis of early fossil preservation. High-resolution analysis of Gunflintia shows that microtaphonomy can help to resolve long-standing paleobiological questions. Novel 3D nanoscale reconstructions of the most ancient complex fossil Eosphaera reveal features hitherto unmatched in any crown-group microbe. While Eosphaera may preserve a symbiotic consortium, a stronger conclusion is that multicellular morphospace was differently occupied in the Paleoproterozoic. The 3.46-Ga Apex chert provides a test bed for claims of biogenicity of cell-like structures. Mapping plus focused ion beam milling combined with transmission electron microscopy data demonstrate that microfossil-like taxa, including species of Archaeoscillatoriopsis and Primaevifilum, are pseudofossils formed from vermiform phyllosilicate grains during hydrothermal alteration events. The 3.43-Ga Strelley Pool Formation shows that plausible early fossil candidates are turning up in unexpected environmental settings. Our data reveal how cellular clusters of unexpectedly large coccoids and tubular sheath-like envelopes were trapped between sand grains and entombed within coatings of dripstone beach-rock silica cement. These fossils come from Earth’s earliest known intertidal to supratidal shoreline deposit, accumulated under aerated but oxygen poor conditions

Large-area CCD imagers for spacecraft applications

Backside illuminated CCD imagers with 100 x 160 resolution elements have been fabricated using double level metal technology. Detailed study of the optical performance of such arrays has been performed between 24 C and -40 C using data rates from 10 kHz to 1 MHz. A 400 x 400 array is presently being fabricated

Novel Techniques for Gas Demand Modeling and Forecasting

The ability to provide accurate forecasts of future gas demand has a major impact on several business processes for Gas Regions in the UK and elsewhere in the world. Long term forecasts provide the guidance for major structural needs, while short term forecasts guide the operations management on requirements of supply purchase, supply storage and delivery. Accurate forecasts guarantee optimum and safe gas supply at the lowest cost. Currently there is no single technique that produces the perfect forecast, this research will attempt to improve on current methods by applying Non-Linear techniques. The technique to be tested is defined as ”Non-Linear Autoregressive Moving Average with eXogeneous Inputs, polynomials, and a Forward Regression with Orthogonal Least Squares estimation procedure”. The goal of the research is is to produce a Mean Average Percentage Error of between 4-6% or better, which was proposed by DNV GL (supplier of software for the Gas Industry), as a valid level of error to make any new methodology of value

Sepsis biomarkers and diagnostic tools with a focus on machine learning.

Over the last years, there have been advances in the use of data-driven techniques to improve the definition, early recognition, subtypes characterisation, prognostication and treatment personalisation of sepsis. Some of those involve the discovery or evaluation of biomarkers or digital signatures of sepsis or sepsis sub-phenotypes. It is hoped that their identification may improve timeliness and accuracy of diagnosis, suggest physiological pathways and therapeutic targets, inform targeted recruitment into clinical trials, and optimise clinical management. Given the complexities of the sepsis response, panels of biomarkers or models combining biomarkers and clinical data are necessary, as well as specific data analysis methods, which broadly fall under the scope of machine learning. This narrative review gives a brief overview of the main machine learning techniques (mainly in the realms of supervised and unsupervised methods) and published applications that have been used to create sepsis diagnostic tools and identify biomarkers

Profiling inflammatory markers in patients with pneumonia on intensive care

Clinical investigations lack predictive value when diagnosing pneumonia, especially when patients are ventilated and develop ventilator associated pneumonia (VAP). New tools to aid diagnosis are important to improve outcomes. This pilot study examines the potential for a panel of inflammatory mediators to aid in the diagnosis. Forty-four ventilated patients, 17 with pneumonia and 27 with brain injuries, eight of whom developed VAP, were recruited. 51 inflammatory mediators, including cytokines and oxylipins, were measured in patients’ serum using flow cytometry and mass spectrometry. The mediators could separate patients admitted to ICU with pneumonia compared to brain injury with an area under the receiver operating characteristic curve (AUROC) 0.75 (0.61–0.90). Changes in inflammatory mediators were similar in both groups over the course of ICU stay with 5,6-dihydroxyeicosatrienoic and 8,9-dihydroxyeicosatrienoic acids increasing over time and interleukin-6 decreasing. However, brain injured patients who developed VAP maintained inflammatory profiles similar to those at admission. A multivariate model containing 5,6-dihydroxyeicosatrienoic acid, 8,9-dihydroxyeicosatrienoic acid, intercellular adhesion molecule-1, interleukin-6, and interleukin-8, could differentiate patients with VAP from brain injured patients without infection (AUROC 0.94 (0.80–1.00)). The use of a selected group of markers showed promise to aid the diagnosis of VAP especially when combined with clinical data