Acute and long-term renal effects after iodine contrast media-enhanced computerised tomography in the critically ill-a retrospective bi-centre cohort study.

OBJECTIVES: To determine if current clinical use of iodine contrast media (ICM) for computerised tomography (CT) increases the risk of acute kidney injury (AKI) and long-term decline in renal function in patients treated in intensive care. METHODS: A retrospective bi-centre cohort study was performed with critically ill subjects undergoing either ICM-enhanced or unenhanced CT. AKI was defined and staged based on the Kidney Disease Improve Global Outcome AKI criteria, using both creatinine and urine output criteria. Follow-up plasma creatinine was recorded three to six months after CT to assess any long-term effects of ICM on renal function. RESULTS: In total, 611 patients were included in the final analysis, median age was 65.0 years (48.0-73.0, quartile 1-quartile 3 (IQR)) and 62.5% were male. Renal replacement therapy was used post-CT in 12.9% and 180-day mortality was 31.2%. Plasma creatinine level on day of CT was 100.0 µmol/L (66.0-166.5, IQR) for non-ICM group and 77.0 µmol/L (59.0-109.0, IQR) for the ICM group. The adjusted odds ratio for developing AKI if the patient received ICM was 1.03 (95% confidence interval 0.64-1.66, p = 0.90). No significant association between ICM and increase in plasma creatinine at long-term follow-up was found, with an adjusted effect size of 2.92 (95% confidence interval - 6.52-12.36, p = 0.543). CONCLUSIONS: The results of this study do not indicate an increased risk of AKI or long-term decline in renal function when ICM is used for enhanced CT in patients treated at intensive care units. CLINICAL RELEVANCE STATEMENT: Patients treated in intensive care units had no increased risk of acute kidney injury or persistent decline in renal function after contrast-enhanced CT. This information underlines the need for a proper risk-reward assessment before denying patients a contrast-enhanced CT. KEY POINTS: • Iodine contrast media is considered a risk factor for the development of acute kidney injury. • Patients receiving iodine contrast media did not have an increased incidence of acute kidney injury or persistent decline in renal function. • A more clearly defined risk of iodine contrast media helps guide clinical decisions whether to perform contrast-enhanced CTs or not.

An Eye into the Aorta: The Role of Extracellular Matrix Regulatory Genes ZNF469 and PRDM5, from Their Previous Association with Brittle Cornea Syndrome to Their Novel Association with Aortic and Arterial Aneurysmal Diseases.

The extracellular matrix is a complex network of proteins and other molecules that are essential for the support, integrity, and structure of cells and tissues within the human body. The genes ZNF469 and PRDM5 each produce extracellular-matrix-related proteins that, when mutated, have been shown to result in the development of brittle cornea syndrome. This dysfunction results from aberrant protein function resulting in extracellular matrix disruption. Our group recently identified and published the first known associations between variants in these genes and aortic/arterial aneurysms and dissection diseases. This paper delineates the proposed effects of mutated ZNF469 and PRDM5 on various essential extracellular matrix components, including various collagens, TGF-B, clusterin, thrombospondin, and HAPLN-1, and reviews our recent reports associating single-nucleotide variants to these genes' development of aneurysmal and dissection diseases.

Improved net carbon budgets in the US Midwest through direct measured impacts of enhanced weathering.

Terrestrial enhanced weathering (EW) through the application of Mg- or Ca-rich rock dust to soil is a negative emission technology with the potential to address impacts of climate change. The effectiveness of EW was tested over 4 years by spreading ground basalt (50 t ha-1 year-1 ) on maize/soybean and miscanthus cropping systems in the Midwest US. The major elements of the carbon budget were quantified through measurements of eddy covariance, soil carbon flux, and biomass. The movement of Mg and Ca to deep soil, released by weathering, balanced by a corresponding alkalinity flux, was used to measure the drawdown of CO2 , where the release of cations from basalt was measured as the ratio of rare earth elements to base cations in the applied rock dust and in the surface soil. Basalt application stimulated peak biomass and net primary production in both cropping systems and caused a small but significant stimulation of soil respiration. Net ecosystem carbon balance (NECB) was strongly negative for maize/soybean (-199 to -453 g C m-2 year-1 ) indicating this system was losing carbon to the atmosphere. Average EW (102 g C m-2 year-1 ) offset carbon loss in the maize/soybean by 23%-42%. NECB of miscanthus was positive (63-129 g C m-2 year-1 ), indicating carbon gain in the system, and EW greatly increased inorganic carbon storage by an additional 234 g C m-2 year-1 . Our analysis indicates a co-deployment of a perennial biofuel crop (miscanthus) with EW leads to major wins-increased harvested yields of 29%-42% with additional carbon dioxide removal (CDR) of 8.6 t CO2 ha-1 year-1 . EW applied to maize/soybean drives a CDR of 3.7 t CO2 ha-1 year-1 , which partially offsets well-established carbon losses from soil from this crop rotation. EW applied in the US Midwest creates measurable improvements to the carbon budgets perennial bioenergy crops and conventional row crops.

Global patterns of drought recovery.

Drought, a recurring phenomenon with major impacts on both human and natural systems, is the most widespread climatic extreme that negatively affects the land carbon sink. Although twentieth-century trends in drought regimes are ambiguous, across many regions more frequent and severe droughts are expected in the twenty-first century. Recovery time-how long an ecosystem requires to revert to its pre-drought functional state-is a critical metric of drought impact. Yet the factors influencing drought recovery and its spatiotemporal patterns at the global scale are largely unknown. Here we analyse three independent datasets of gross primary productivity and show that, across diverse ecosystems, drought recovery times are strongly associated with climate and carbon cycle dynamics, with biodiversity and CO2 fertilization as secondary factors. Our analysis also provides two key insights into the spatiotemporal patterns of drought recovery time: first, that recovery is longest in the tropics and high northern latitudes (both vulnerable areas of Earth's climate system) and second, that drought impacts (assessed using the area of ecosystems actively recovering and time to recovery) have increased over the twentieth century. If droughts become more frequent, as expected, the time between droughts may become shorter than drought recovery time, leading to permanently damaged ecosystems and widespread degradation of the land carbon sink.

Optimal stomatal behavior with competition for water and risk of hydraulic impairment.

For over 40 y the dominant theory of stomatal behavior has been that plants should open stomates until the carbon gained by an infinitesimal additional opening balances the additional water lost times a water price that is constant at least over short periods. This theory has persisted because of its remarkable success in explaining strongly supported simple empirical models of stomatal conductance, even though we have also known for over 40 y that the theory is not consistent with competition among plants for water. We develop an alternative theory in which plants maximize carbon gain without pricing water loss and also add two features to both this and the classical theory, which are strongly supported by empirical evidence: (i) water flow through xylem that is progressively impaired as xylem water potential drops and (ii) fitness or carbon costs associated with low water potentials caused by a variety of mechanisms, including xylem damage repair. We show that our alternative carbon-maximization optimization is consistent with plant competition because it yields an evolutionary stable strategy (ESS)-species with the ESS stomatal behavior that will outcompete all others. We further show that, like the classical theory, the alternative theory also explains the functional forms of empirical stomatal models. We derive ways to test between the alternative optimization criteria by introducing a metric-the marginal xylem tension efficiency, which quantifies the amount of photosynthesis a plant will forego from opening stomatal an infinitesimal amount more to avoid a drop in water potential.

Global nutrient transport in a world of giants.

The past was a world of giants, with abundant whales in the sea and large animals roaming the land. However, that world came to an end following massive late-Quaternary megafauna extinctions on land and widespread population reductions in great whale populations over the past few centuries. These losses are likely to have had important consequences for broad-scale nutrient cycling, because recent literature suggests that large animals disproportionately drive nutrient movement. We estimate that the capacity of animals to move nutrients away from concentration patches has decreased to about 8% of the preextinction value on land and about 5% of historic values in oceans. For phosphorus (P), a key nutrient, upward movement in the ocean by marine mammals is about 23% of its former capacity (previously about 340 million kg of P per year). Movements by seabirds and anadromous fish provide important transfer of nutrients from the sea to land, totalling ∼150 million kg of P per year globally in the past, a transfer that has declined to less than 4% of this value as a result of the decimation of seabird colonies and anadromous fish populations. We propose that in the past, marine mammals, seabirds, anadromous fish, and terrestrial animals likely formed an interlinked system recycling nutrients from the ocean depths to the continental interiors, with marine mammals moving nutrients from the deep sea to surface waters, seabirds and anadromous fish moving nutrients from the ocean to land, and large animals moving nutrients away from hotspots into the continental interior.

Woody plants optimise stomatal behaviour relative to hydraulic risk.

Stomatal response to environmental conditions forms the backbone of all ecosystem and carbon cycle models, but is largely based on empirical relationships. Evolutionary theories of stomatal behaviour are critical for guarding against prediction errors of empirical models under future climates. Longstanding theory holds that stomata maximise fitness by acting to maintain constant marginal water use efficiency over a given time horizon, but a recent evolutionary theory proposes that stomata instead maximise carbon gain minus carbon costs/risk of hydraulic damage. Using data from 34 species that span global forest biomes, we find that the recent carbon-maximisation optimisation theory is widely supported, revealing that the evolution of stomatal regulation has not been primarily driven by attainment of constant marginal water use efficiency. Optimal control of stomata to manage hydraulic risk is likely to have significant consequences for ecosystem fluxes during drought, which is critical given projected intensification of the global hydrological cycle.

A large-area, spatially continuous assessment of land cover map error and its impact on downstream analyses.

Land cover maps increasingly underlie research into socioeconomic and environmental patterns and processes, including global change. It is known that map errors impact our understanding of these phenomena, but quantifying these impacts is difficult because many areas lack adequate reference data. We used a highly accurate, high-resolution map of South African cropland to assess (1) the magnitude of error in several current generation land cover maps, and (2) how these errors propagate in downstream studies. We first quantified pixel-wise errors in the cropland classes of four widely used land cover maps at resolutions ranging from 1 to 100 km, and then calculated errors in several representative "downstream" (map-based) analyses, including assessments of vegetative carbon stocks, evapotranspiration, crop production, and household food security. We also evaluated maps' spatial accuracy based on how precisely they could be used to locate specific landscape features. We found that cropland maps can have substantial biases and poor accuracy at all resolutions (e.g., at 1 km resolution, up to ∼45% underestimates of cropland (bias) and nearly 50% mean absolute error (MAE, describing accuracy); at 100 km, up to 15% underestimates and nearly 20% MAE). National-scale maps derived from higher-resolution imagery were most accurate, followed by multi-map fusion products. Constraining mapped values to match survey statistics may be effective at minimizing bias (provided the statistics are accurate). Errors in downstream analyses could be substantially amplified or muted, depending on the values ascribed to cropland-adjacent covers (e.g., with forest as adjacent cover, carbon map error was 200%-500% greater than in input cropland maps, but ∼40% less for sparse cover types). The average locational error was 6 km (600%). These findings provide deeper insight into the causes and potential consequences of land cover map error, and suggest several recommendations for land cover map users.

Improved removal of volatile organic compounds for laser-based spectroscopy of water isotopes.

RATIONALE: Volatile organic compounds (VOCs) such as methanol and ethanol in water extracted from plants cause spectral interference in isotope ratio infrared spectroscopy (IRIS). This contamination degrades the accuracy of measurements, limiting the use of IRIS. In response, this study presents a new decontamination method of VOCs for enhanced IRIS measurements. METHODS: The isotopic compositions of water from laboratory-made and field-collected plant samples pre- and post-treatment were analyzed using IRIS. Traditional treatment methods of activated charcoal and commercial pre-combustion systems (MCM) were compared with our new treatment method that implements solid-phase extraction (SPE). The absolute concentrations of contaminants pre- and post-treatment were determined using (1)H and (13)C nuclear magnetic resonance to assess the effectiveness of the different treatments. RESULTS: SPE removes an average of 86.7% and 78.8% ethanol and methanol, respectively, significantly reducing spectral interference. SPE reduces errors to within instrumental noise for both ethanol and methanol at concentrations found in nature (<3.0% and 0.08%, respectively). Activated charcoal minimally affected alcohol concentrations. MCM significantly worsened ethanol-contaminated water isotope measurements by producing primary alcohol oxidation products such as formic acid, another compound that interferes with IRIS absorption. CONCLUSIONS: SPE is an effective, low-cost method for eliminating errors in ethanol-contaminated samples. For samples where methanol is prevalent, combining SPE and MCM is more effective than the use of SPE alone. Hence, SPE treatment alone or in conjunction with MCM is recommended as an effective pre-analysis purification method for water extracted from plants.

The Association of Novel Single-Nucleotide Variants in the Collagen Matrix-Encoding Gene PRDM5 with Aortic Aneurysmal Disease.

Thoracic aortic aneurysms are clinical conditions that are associated with severe clinical endpoints including dissection and rupture, potentially leading to sudden death. Contrary to their abdominal counterparts, thoracic aortic aneurysms are well-recognized to have a genetic basis underlying their development. Among all patients with aneurysmal disease who underwent clinical genetic screening in our program (N = 145), two patients were found to have variants of uncertain significance (VUS) in the PRDM5 gene. This gene is responsible for multiple regulatory functions in extracellular matrix development, and this is the first report, to our knowledge, to associate this gene with aortopathy.

Towards robotic laboratory automation Plug & play: Survey and concept proposal on teaching-free robot integration with the lapp digital twin.

The Laboratory Automation Plug & Play (LAPP) framework is an over-arching reference architecture concept for the integration of robots in life science laboratories. The plug & play nature lies in the fact that manual configuration is not required, including the teaching of the robots. In this paper a digital twin (DT) based concept is proposed that outlines the types of information that must be provided for each relevant component of the system. In particular, for the devices interfacing with the robot, the robot positions must be defined beforehand in a device-attached coordinate system (CS) by the vendor. This CS must be detectable by the vision system of the robot by means of optical markers placed on the front side of the device. With that, the robot is capable of tending the machine by performing the pick-and-place type transportation of standard sample carriers. This basic use case is the primary scope of the LAPP-DT framework. The hardware scope is limited to simple benchtop and mobile manipulators with parallel grippers at this stage. This paper first provides an overview of relevant literature and state-of-the-art solutions, after which it outlines the framework on the conceptual level, followed by the specification of the relevant DT parameters for the robot, for the devices and for the facility. Finally, appropriate technologies and strategies are identified for the implementation.

Ability of single anesthesia for combined robotic-assisted bronchoscopy and surgical lobectomy to reduce time between detection and treatment in stage I non-small cell lung cancer.

Background: Background: Early identification, diagnosis, and treatment of lung cancer is associated with improved clinical outcomes. Robotic-assisted bronchoscopy improves the ability to diagnose early stage lung malignancies and, when combined with robotic-assisted lobectomy under single anesthesia, could reduce time from identification to intervention in early stage lung cancer in a select patient population. Methods: Methods: A retrospective case-control single-center study compared patients with radiographic stage I non-small cell carcinoma (NSCCA) undergoing robotic navigational bronchoscopy and surgical resection (N = 22) with historical controls (N = 63). The primary outcome was time from initial radiographic identification of a pulmonary nodule to therapeutic intervention. Secondary outcomes included times between identification to biopsy, biopsy to surgery, and procedural complications. Results: Results: Patients with suspected stage I NSCCA who received single anesthesia for diagnosis and intervention with robotic-assisted bronchoscopy and robotic-assisted lobectomy had shorter times between identification of a pulmonary nodule and intervention compared to controls (65 vs 116 days, P = 0.005). Cases had lower rates of complications (0% vs 5%) and shorter hospitalizations after surgery (3.6 vs 6.2 days, P = 0.017). Conclusion: Conclusion: Our findings support that implementing a multidisciplinary thoracic oncology team and single-anesthesia biopsy-to-surgery approach in management of stage I NSCCA significantly reduced times from identification to intervention, biopsy to intervention, and length of hospital stays in management of lung cancer.

Therapeutic considerations for prevention and treatment of thrombotic events in COVID-19.

Thrombosis is a known complication of SARS-CoV-2 infection, particularly within a severely symptomatic subset of patients with COVID-19 disease, in whom an aggressive host immune response leads to cytokine storm syndrome (CSS). The incidence of thrombotic events coinciding with CSS may contribute to the severe morbidity and mortality observed in association with COVID-19. This review provides an overview of pharmacologic approaches based upon an emerging understanding of the mechanisms responsible for thrombosis across a spectrum of COVID-19 disease involving an interplay between immunologic and pro-thrombotic events, including endothelial injury, platelet activation, altered coagulation pathways, and impaired fibrinolysis.

Towards robotic laboratory automation Plug & Play: The "LAPP" framework.

Increasing the level of automation in pharmaceutical laboratories and production facilities plays a crucial role in delivering medicine to patients. However, the particular requirements of this field make it challenging to adapt cutting-edge technologies present in other industries. This article provides an overview of relevant approaches and how they can be utilized in the pharmaceutical industry, especially in development laboratories. Recent advancements include the application of flexible mobile manipulators capable of handling complex tasks. However, integrating devices from many different vendors into an end-to-end automation system is complicated due to the diversity of interfaces. Therefore, various approaches for standardization are considered in this article, and a concept is proposed for taking them a step further. This concept enables a mobile manipulator with a vision system to "learn" the pose of each device and - utilizing a barcode - fetch interface information from a universal cloud database. This information includes control and communication protocol definitions and a representation of robot actions needed to operate the device. In order to define the movements in relation to the device, devices have to feature - besides the barcode - a fiducial marker as standard. The concept will be elaborated following appropriate research activities in follow-up papers.

The mechanistic basis linking cytokine storm to thrombosis in COVID-19.

It is now well established that infection with SARS-CoV-2 resulting in COVID-19 disease includes a severely symptomatic subset of patients in whom an aggressive and/or dysregulated host immune response leads to cytokine storm syndrome (CSS) that may be further complicated by thrombotic events, contributing to the severe morbidity and mortality observed in COVID-19. This review provides a brief overview of cytokine storm in COVID-19, and then presents a mechanistic discussion of how cytokine storm affects integrated pathways in thrombosis involving the endothelium, platelets, the coagulation cascade, eicosanoids, auto-antibody mediated thrombosis, and the fibrinolytic system.

Evolutionarily stable strategy carbon allocation to foliage, wood, and fine roots in trees competing for light and nitrogen: an analytically tractable, individual-based model and quantitative comparisons to data.

We present a model that scales from the physiological and structural traits of individual trees competing for light and nitrogen across a gradient of soil nitrogen to their community-level consequences. The model predicts the most competitive (i.e., the evolutionarily stable strategy [ESS]) allocations to foliage, wood, and fine roots for canopy and understory stages of trees growing in old-growth forests. The ESS allocations, revealed as analytical functions of commonly measured physiological parameters, depend not on simple root-shoot relations but rather on diminishing returns of carbon investment that ensure any alternate strategy will underperform an ESS in monoculture because of the competitive environment that the ESS creates. As such, ESS allocations do not maximize nitrogen-limited growth rates in monoculture, highlighting the underappreciated idea that the most competitive strategy is not necessarily the "best," but rather that which creates conditions in which all others are "worse." Data from 152 stands support the model's surprising prediction that the dominant structural trade-off is between fine roots and wood, not foliage, suggesting the "root-shoot" trade-off is more precisely a "root-stem" trade-off for long-lived trees. Assuming other resources are abundant, the model predicts that forests are limited by both nitrogen and light, or nearly so.

Allometric growth and allocation in forests: a perspective from FLUXNET.

To develop a scheme for partitioning the products of photosynthesis toward different biomass components in land-surface models, a database on component mass and net primary productivity (NPP), collected from FLUXNET sites, was examined to determine allometric patterns of allocation. We found that NPP per individual of foliage (Gfol), stem and branches (Gstem), coarse roots (Gcroot) and fine roots (Gfroot) in individual trees is largely explained (r2 = 67-91%) by the magnitude of total NPP per individual (G). Gfol scales with G isometrically, meaning it is a fixed fraction of G ( 25%). Root-shoot trade-offs were manifest as a slow decline in Gfroot, as a fraction of G, from 50% to 25% as stands increased in biomass, with Gstem and Gcroot increasing as a consequence. These results indicate that a functional trade-off between aboveground and belowground allocation is essentially captured by variations in G, which itself is largely governed by stand biomass and only secondarily by site-specific resource availability. We argue that forests are characterized by strong competition for light, observed as a race for individual trees to ascend by increasing partitioning toward wood, rather than by growing more leaves, and that this competition stronglyconstrains the allocational plasticity that trees may be capable of. The residual variation in partitioning was not related to climatic or edaphic factors, nor did plots with nutrient or water additions show a pattern of partitioning distinct from that predicted by G alone. These findings leverage short-term process studies of the terrestrial carbon cycle to improve decade-scale predictions of biomass accumulation in forests. An algorithm for calculating partitioning in land-surface models is presented.

Simulating greenhouse gas budgets of four California cropping systems under conventional and alternative management.

Despite the importance of agriculture in California's Central Valley, the potential of alternative management practices to reduce soil greenhouse gas (GHG) emissions has been poorly studied in California. This study aims at (1) calibrating and validating DAYCENT, an ecosystem model, for conventional and alternative cropping systems in California's Central Valley, (2) estimating CO2, N2O, and CH4 soil fluxes from these systems, and (3) quantifying the uncertainty around model predictions induced by variability in the input data. The alternative practices considered were cover cropping, organic practices, and conservation tillage. These practices were compared with conventional agricultural management. The crops considered were beans, corn, cotton, safflower, sunflower, tomato, and wheat. Four field sites, for which at least five years of measured data were available, were used to calibrate and validate the DAYCENT model. The model was able to predict 86-94% of the measured variation in crop yields and 69-87% of the measured variation in soil organic carbon (SOC) contents. A Monte Carlo analysis showed that the predicted variability of SOC contents, crop yields, and N2O fluxes was generally smaller than the measured variability of these parameters, in particular for N2O fluxes. Conservation tillage had the smallest potential to reduce GHG emissions among the alternative practices evaluated, with a significant reduction of the net soil GHG fluxes in two of the three sites of 336 +/- 47 and 550 +/- 123 kg CO2-eq x ha(-1) x yr(-1) (mean +/- SE). Cover cropping had a larger potential, with net soil GHG flux reductions of 752 +/- 10, 1072 +/- 272, and 2201 +/- 82 kg CO2-eq x ha(-1) x yr(-1). Organic practices had the greatest potential for soil GHG flux reduction, with 4577 +/- 272 kg CO2-eq x ha(-1) x yr(-1). Annual differences in weather or management conditions contributed more to the variance in annual GHG emissions than soil variability did. We concluded that the DAYCENT model was successful at predicting GHG emissions of different alternative management systems in California, but that a sound error analysis must accompany the predictions to understand the risks and potentials of GHG mitigation through adoption of alternative practices.

The Cancer Imaging Phenomics Toolkit (CaPTk): Technical Overview.

The purpose of this manuscript is to provide an overview of the technical specifications and architecture of the Cancer imaging Phenomics Toolkit (CaPTk www.cbica.upenn.edu/captk), a cross-platform, open-source, easy-to-use, and extensible software platform for analyzing 2D and 3D images, currently focusing on radiographic scans of brain, breast, and lung cancer. The primary aim of this platform is to enable swift and efficient translation of cutting-edge academic research into clinically useful tools relating to clinical quantification, analysis, predictive modeling, decision-making, and reporting workflow. CaPTk builds upon established open-source software toolkits, such as the Insight Toolkit (ITK) and OpenCV, to bring together advanced computational functionality. This functionality describes specialized, as well as general-purpose, image analysis algorithms developed during active multi-disciplinary collaborative research studies to address real clinical requirements. The target audience of CaPTk consists of both computational scientists and clinical experts. For the former it provides i) an efficient image viewer offering the ability of integrating new algorithms, and ii) a library of readily-available clinically-relevant algorithms, allowing batch-processing of multiple subjects. For the latter it facilitates the use of complex algorithms for clinically-relevant studies through a user-friendly interface, eliminating the prerequisite of a substantial computational background. CaPTk's long-term goal is to provide widely-used technology to make use of advanced quantitative imaging analytics in cancer prediction, diagnosis and prognosis, leading toward a better understanding of the biological mechanisms of cancer development.