Assessing a New Clue to How Much Carbon Plants Take Up

Current climate models disagree on how much carbon dioxide land ecosystems take up for photosynthesis. Tracking the stronger carbonyl sulfide signal could help

Profiling tropospheric CO_2 using Aura TES and TCCON instruments

Monitoring the global distribution and long-term variations of CO_2 sources and sinks is required for characterizing the global carbon budget. Total column measurements are useful for estimating regional-scale fluxes; however, model transport remains a significant error source, particularly for quantifying local sources and sinks. To improve the capability of estimating regional fluxes, we estimate lower tropospheric CO_2 concentrations from ground-based near-infrared (NIR) measurements with space-based thermal infrared (TIR) measurements. The NIR measurements are obtained from the Total Carbon Column Observing Network (TCCON) of solar measurements, which provide an estimate of the total CO_2 column amount. Estimates of tropospheric CO_2 that are co-located with TCCON are obtained by assimilating Tropospheric Emission Spectrometer (TES) free tropospheric CO_2 estimates into the GEOS-Chem model. We find that quantifying lower tropospheric CO_2 by subtracting free tropospheric CO_2 estimates from total column estimates is a linear problem, because the calculated random uncertainties in total column and lower tropospheric estimates are consistent with actual uncertainties as compared to aircraft data. For the total column estimates, the random uncertainty is about 0.55 ppm with a bias of −5.66 ppm, consistent with previously published results. After accounting for the total column bias, the bias in the lower tropospheric CO_2 estimates is 0.26 ppm with a precision (one standard deviation) of 1.02 ppm. This precision is sufficient for capturing the winter to summer variability of approximately 12 ppm in the lower troposphere; double the variability of the total column. This work shows that a combination of NIR and TIR measurements can profile CO_2 with the precision and accuracy needed to quantify lower tropospheric CO_2 variability

Gradient microfluidics enables rapid bacterial growth inhibition testing

Bacterial growth inhibition tests have become a standard measure of the adverse effects of inhibitors for a wide range of applications, such as toxicity testing in the medical and environmental sciences. However, conventional well-plate formats for these tests are laborious and provide limited information (often being restricted to an end-point assay). In this study, we have developed a microfluidic system that enables fast quantification of the effect of an inhibitor on bacteria growth and survival, within a single experiment. This format offers a unique combination of advantages, including long-term continuous flow culture, generation of concentration gradients, and single cell morphology tracking. Using Escherichia coli and the inhibitor amoxicillin as one model system, we show excellent agreement between an on-chip single cell-based assay and conventional methods to obtain quantitative measures of antibiotic inhibition (for example, minimum inhibition concentration). Furthermore, we show that our methods can provide additional information, over and above that of the standard well-plate assay, including kinetic information on growth inhibition and measurements of bacterial morphological dynamics over a wide range of inhibitor concentrations. Finally, using a second model system, we show that this chip-based systems does not require the bacteria to be labeled and is well suited for the study of naturally occurring species. We illustrate this using Nitrosomonas europaea, an environmentally important bacteria, and show that the chip system can lead to a significant reduction in the period required for growth and inhibition measurements (<4 days, compared to weeks in a culture flask)

Cointegration strategy for damage assessment of offshore platforms subject to wind and wave forces

In structural engineering, offshore structures are undoubtedly among the most exposed to the effects of harsh environmental conditions. The external conditions of these semi -immersed systems involve complex combinations of wave and wind loads. The operating conditions are also unique because oil production platforms are subjected to repeated loading and unloading cycles of the extracted material, which continuously alter their mass. These characteristics make the definition of a structural health monitoring (SHM) protocol highly challenging but necessary to avoid environmental disasters. In this regard, this study discusses an SHM method that can be applied to offshore structures under realistic wave and wind loads. This approach combines anomaly detection, frequency domain decomposition, and a cointegration strategy. Two machine learning regression algorithms were tested to define a cointegration relationship: the support vector machine and the relevance vector machine. The effectiveness of the overall method was evaluated on time -domain signals generated from a finite -element model of a fixed steel platform, on which the Davenport and JONSWAP spectra were used to simulate wind and wave forces. The results show that this damage detection strategy is effective in supervising the health conditions in the analyzed scenario

Responses to Prescribed Fire at Big Thicket National Preserve, Texas, USA

US Federal land managers have utilized hand ignited prescribed fire at Big Thicket National Preserve in efforts to restore the structure and diversity of the longleaf pine (Pinus palustris) forest. A fire ecology study was initiated by Rice University in the early 1990’s and the National Park Service has continued monitoring the plots. Ordination was applied to species abundance data to examine changes in vegetation communities from a variety of prescribed fire treatments and controls. The vegetation data was separated by size class to include overstory, small tree, large sapling and seedling data. Across the size classes and treatments, the sandhill and wetland savanna vegetation types remained less effected by fire treatments and only the upland pine responded to changes in the overstory. Upon reviewing fire return interval histories, it became evident that prescribed fire alone was not changing vegetation communities. Most of the plots did not have longleaf pine trees or seedlings present and only two plots that were mechanical treated showed distinction among other treatment regimes. Restoration treatments including the mechanical and chemical application and seedling plantings are necessary to ensure restoration of the longleaf pine forest structure and diverse understory vegetation

Diversity Synthesis of Complex Pyridines Yields a Probe of a Neurotrophic Signaling Pathway

Recognizing the value of including complex pyridines in small-molecule screening collections, we developed a previously unexplored [2 + 2 + 2]-cycloaddition of silyl-tethered diynes with nitriles. The tether provides high regioselectivity, while the solvent THF allows catalytic CpCo(CO)2 to be used without exogenous irradiation. One of the resulting bicyclic and monocyclic (desilylated) pyridines was identified as an inhibitor of neuregulin-induced neurite outgrowth (EC50 = 0.30 µM) in a screen that probes a pathway likely to be involved in breast cancers and schizophrenia.Chemistry and Chemical Biolog

Knowledge-driven design of solid-electrolyte interphases on lithium metal via multiscale modelling

Due to its high energy density, lithium metal is a promising electrode for future energy storage. However, its practical capacity, cyclability and safety heavily depend on controlling its reactivity in contact with liquid electrolytes, which leads to the formation of a solid electrolyte interphase (SEI). In particular, there is a lack of fundamental mechanistic understanding of how the electrolyte composition impacts the SEI formation and its governing processes. Here, we present an in-depth model-based analysis of the initial SEI formation on lithium metal in a carbonate-based electrolyte. Thereby we reach for significantly larger length and time scales than comparable molecular dynamic studies. Our multiscale kinetic Monte Carlo/continuum model shows a layered, mostly inorganic SEI consisting of LiF on top of Li$_2$CO$_3$ and Li after 1 µs. Its formation is traced back to a complex interplay of various electrolyte and salt decomposition processes. We further reveal that low local Li$^+$ concentrations result in a more mosaic-like, partly organic SEI and that a faster passivation of the lithium metal surface can be achieved by increasing the salt concentration. Based on this we suggest design strategies for SEI on lithium metal and make an important step towards knowledge-driven SEI engineering

Low level constraints on dynamic contour path integration

Contour integration is a fundamental visual process. The constraints on integrating discrete contour elements and the associated neural mechanisms have typically been investigated using static contour paths. However, in our dynamic natural environment objects and scenes vary over space and time. With the aim of investigating the parameters affecting spatiotemporal contour path integration, we measured human contrast detection performance of a briefly presented foveal target embedded in dynamic collinear stimulus sequences (comprising five short 'predictor' bars appearing consecutively towards the fovea, followed by the 'target' bar) in four experiments. The data showed that participants' target detection performance was relatively unchanged when individual contour elements were separated by up to 2° spatial gap or 200ms temporal gap. Randomising the luminance contrast or colour of the predictors, on the other hand, had similar detrimental effect on grouping dynamic contour path and subsequent target detection performance. Randomising the orientation of the predictors reduced target detection performance greater than introducing misalignment relative to the contour path. The results suggest that the visual system integrates dynamic path elements to bias target detection even when the continuity of path is disrupted in terms of spatial (2°), temporal (200ms), colour (over 10 colours) and luminance (-25% to 25%) information. We discuss how the findings can be largely reconciled within the functioning of V1 horizontal connections

Robust Anti‐Tumor T Cell Response with Efficient Intratumoral Infiltration by Nanodisc Cancer Immunotherapy

Potent anti‐tumor T cell response and efficient intratumoral T cell infiltration are the major challenges for therapeutic cancer vaccines. To address these issues, a nanovaccine system is designed to promote anti‐tumor T cell responses, and intratumoral infiltration is examined in various murine tumor models. Subcutaneous vaccination with nanodiscs carrying human papillomavirus (HPV)‐16 E7 antigen elicits as high as ∼32% E7‐specific CD8α+ T cell responses in circulation, representing a 29‐fold improvement over the soluble peptide vaccination. Importantly, nanodisc vaccination also promotes robust intratumoral T cell infiltration and eliminates HPV16 E6/E7‐expressing TC‐1 tumors at mucosal sites, including lungs, inner lip, and intravaginal tissues. In a benchmark study with a live Listeria vaccine combined with anti‐PD‐1 IgG, nanodiscs plus anti‐PD‐1 immune checkpoint blockade elicits comparable levels of T cell responses with anti‐tumor efficacy. Furthermore, compared with Complete Freund’s Adjuvant combined with tetanus toxoid, nanodisc vaccination in HLA‐A02 mice generates >200‐fold stronger IFN‐γ+ T cell responses against a neoantigen from an HLA‐A02 melanoma patient. Overall, these results show that the nanodisc system is a promising cancer vaccine platform for inducing anti‐tumor T cell responses.Efficient infiltration of T cells in solid cancer is a major challenge for cancer immunotherapy. A nanoparticle vaccine system is developed to promote T cell infiltration into peripheral mucosal tissues and eliminate disseminated tumors. Nanodiscs are broadly applicable with a wide range of tumor antigens, thus providing a versatile and potent vaccine platform for eliciting T cell immunity.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/156420/3/adtp202000094.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/156420/2/adtp202000094-sup-0001-SuppMat.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/156420/1/adtp202000094_am.pd