Pyruvate: immunonutritional effects on neutrophil intracellular amino or alpha-keto acid profiles and reactive oxygen species production

For the first time the immunonutritional role of pyruvate on neutrophils (PMN), free α-keto and amino acid profiles, important reactive oxygen species (ROS) produced [superoxide anion (O2−), hydrogen peroxide (H2O2)] as well as released myeloperoxidase (MPO) acitivity has been investigated. Exogenous pyruvate significantly increased PMN pyruvate, α-ketoglutarate, asparagine, glutamine, aspartate, glutamate, arginine, citrulline, alanine, glycine and serine in a dose as well as duration of exposure dependent manner. Moreover, increases in O2− formation, H2O2-generation and MPO acitivity in parallel with intracellular pyruvate changes have also been detected. Regarding the interesting findings presented here we believe, that pyruvate fulfils considerably the criteria for a potent immunonutritional molecule in the regulation of the PMN dynamic α-keto and amino acid pools. Moreover it also plays an important role in parallel modulation of the granulocyte-dependent innate immune regulation. Although further research is necessary to clarify pyruvate’s sole therapeutical role in critically ill patients’ immunonutrition, the first scientific successes seem to be very promising

Blood Pressure During Endovascular Treatment Under Conscious Sedation or Local Anesthesia

OBJECTIVE: To evaluate the role of blood pressure (BP) as mediator of the effect of conscious sedation (CS) compared to local anesthesia (LA) on functional outcome after endovascular treatment (EVT). METHODS: Patients treated in the Multicenter Randomized Clinical Trial of Endovascular Treatment for Acute Ischemic Stroke in the Netherlands (MR CLEAN) Registry centers with CS or LA as preferred anesthetic approach during EVT for ischemic stroke were analyzed. First, we evaluated the effect of CS on area under the threshold (AUT), relative difference between baseline and lowest procedural mean arterial pressure (∆LMAP), and procedural BP trend, compared to LA. Second, we assessed the association between BP and functional outcome (modified Rankin Scale [mRS]) with multivariable regression. Lastly, we evaluated whether BP explained the effect of CS on mRS. RESULTS: In 440 patients with available BP data, patients treated under CS (n = 262) had larger AUTs (median 228 vs 23 mm Hg*min), larger ∆LMAP (median 16% vs 6%), and a more negative BP trend (-0.22 vs -0.08 mm Hg/min) compared to LA (n = 178). Larger ∆LMAP and AUTs were associated with worse mRS (adjusted common odds ratio [acOR] per 10% drop 0.87, 95% confidence interval [CI] 0.78-0.97, and acOR per 300 mm Hg*min 0.89, 95% CI 0.82-0.97). Patients treated under CS had worse mRS compared to LA (acOR 0.59, 95% CI 0.40-0.87) and this association remained when adjusting for ∆LMAP and AUT (acOR 0.62, 95% CI 0.42-0.92). CONCLUSIONS: Large BP drops are associated with worse functional outcome. However, BP drops do not explain the worse outcomes in the CS group

Fast Cloud Segmentation Using Convolutional Neural Networks

Information about clouds is important for observing and predicting weather and climate as well as for generating and distributing solar power. Most existing approaches extract cloud information from satellite data by classifying individual pixels instead of using closely integrated spatial information, ignoring the fact that clouds are highly dynamic, spatially continuous entities. This paper proposes a novel cloud classification method based on deep learning. Relying on a Convolutional Neural Network (CNN) architecture for image segmentation, the presented Cloud Segmentation CNN (CS-CNN), classifies all pixels of a scene simultaneously rather than individually. We show that CS-CNN can successfully process multispectral satellite data to classify continuous phenomena such as highly dynamic clouds. The proposed approach produces excellent results on Meteosat Second Generation (MSG) satellite data in terms of quality, robustness, and runtime compared to other machine learning methods such as random forests. In particular, comparing CS-CNN with the CLAAS-2 cloud mask derived from MSG data shows high accuracy (0.94) and Heidke Skill Score (0.90) values. In contrast to a random forest, CS-CNN produces robust results and is insensitive to challenges created by coast lines and bright (sand) surface areas. Using GPU acceleration, CS-CNN requires only 25 ms of computation time for classification of images of Europe with 508 × 508 pixels

Programmes for the management of preoperative anaemia: audit in ten European hospitals within the PaBloE (Patient Blood Management in Europe) working group

Background and objectives Preoperative anaemia is an independent risk factor for a higher morbidity and mortality, a longer hospitalization and increased perioperative transfusion rates. Managing preoperative anaemia is the first of three pillars of Patient Blood Management (PBM), a multidisciplinary concept to improve patient safety. While various studies provide medical information on (successful) anaemia treatment pathways, knowledge of organizational details of diagnosis and management of preoperative anaemia across Europe is scarce. Materials and methods To gain information on various aspects of preoperative anaemia management including organization, financing, diagnostics and treatment, we conducted a survey (74 questions) in ten hospitals from seven European nations within the PaBloE (Patient Blood Management in Europe) working group covering the year 2016. Results Organization and activity in the field of preoperative anaemia management were heterogeneous in the participating hospitals. Almost all hospitals had pathways for managing preoperative anaemia in place, however, only two nations had national guidelines. In six of the ten participating hospitals, preoperative anaemia management was organized by anaesthetists. Diagnostics and treatment focused on iron deficiency anaemia which, in most hospitals, was corrected with intravenous iron. Conclusion Implementation and approaches of preoperative anaemia management vary across Europe with a primary focus on treating iron deficiency anaemia. Findings of this survey motivated the hospitals involved to critically evaluate their practice and may also help other hospitals interested in PBM to develop action plans for diagnosis and management of preoperative anaemia

Ketamine inhibits transcription factors activator protein 1 and nuclear factor-kappaB, interleukin-8 production, as well as CD11b and CD16 expression: studies in human leukocytes and leukocytic cell lines.

Item does not contain fulltextBACKGROUND: Recent data indicate that ketamine exerts antiinflammatory actions. However, little is known about the signaling mechanisms involved in ketamine-induced immune modulation. In this study, we investigated the effects of ketamine on lipopolysaccharide-induced activation of transcription factors activator protein 1 (AP-1) and nuclear factor-kappaB (NF-kappaB) in human leukocyte-like cell lines and in human blood neutrophils. METHODS: Electric mobility shift assays were used to investigate ketamine's effects on nuclear binding activity of both transcription factors in U937 cells, and a whole blood flow cytometric technique was used for AP-1 and NF-kappaB determination in leukocytes. Cell lines with different expression patterns of opioid and N-methyl-D-aspartate receptors were used for reverse transcription-polymerase chain reaction to investigate receptors involved in ketamine signaling. Ketamine's effect on interleukin-8 production was assessed in a whole blood assay. RESULTS: Ketamine inhibited both transcription factors in a concentration-dependent manner. These effects did not depend on opiate or N-methyl-D-aspartate receptors. Ketamine also reduced interleukin-8 production in whole blood and expression of CD11b and CD16 on neutrophils. CONCLUSION: The immunoinhibitory effects of ketamine are at least in part caused by inhibition of transcription factors NF-kappaB and AP-1, which regulate production of proinflammatory mediators. However, signaling mechanisms different from those present in the central nervous system are responsible for ketamine-mediated immunomodulation

Blood Pressure During Endovascular Treatment Under Conscious Sedation or Local Anesthesia

OBJECTIVE: To evaluate the role of blood pressure as mediator of the effect of conscious sedation (CS) compared to local anesthesia (LA) on functional outcome after EVT. METHODS: Patients treated in MR CLEAN Registry centers with CS or LA as preferred anesthetic approach during EVT for ischemic stroke were analyzed. First, we evaluated the effect of CS on area under the threshold (AUT), relative difference between baseline and lowest procedural mean arterial pressure (∆LMAP) and procedural blood pressure trend, compared to LA. Second, we assessed the association between blood pressure and functional outcome (modified Rankin Scale, mRS) with multivariable regression. Lastly, we evaluated whether blood pressure explained the effect of CS on mRS. RESULTS: In 440 patients with available blood pressure data, patients treated under CS (n = 262) had larger AUTs (median 228 vs 23 mm Hg*min), larger ∆LMAP (median 16% vs 6%) and a more negative blood pressure trend (-0.22 vs -0.08 mm Hg/min) compared to LA (n = 178). Larger ∆LMAP and AUTs were associated with worse mRS (adjusted common OR (acOR) per 10%-drop 0.87, 95%CI 0.78-0.97, and acOR per 300 mm Hg*min 0.89, 95%CI 0.82-0.97). Patients treated under CS had worse mRS compared to LA (acOR 0.59, 95%CI 0.40-0.87) and this association remained when adjusting for ∆LMAP and AUT (acOR 0.62, 95%CI0.42-0.92). CONCLUSIONS: Large blood pressure drops are associated with worse functional outcome. However, blood pressure drops do not explain the worse outcomes in the CS group

Nature 4.0: A networked sensor system for integrated biodiversity monitoring

Ecosystem functions and services are severely threatened by unprecedented global loss in biodiversity. To counteract these trends, it is essential to develop systems to monitor changes in biodiversity for planning, evaluating, and implementing conservation and mitigation actions. However, the implementation of monitoring systems suffers from a trade‐off between grain (i.e., the level of detail), extent (i.e., the number of study sites), and temporal repetition. Here, we present an applied and realized networked sensor system for integrated biodiversity monitoring in the Nature 4.0 project as a solution to these challenges, which considers plants and animals not only as targets of investigation, but also as parts of the modular sensor network by carrying sensors. Our networked sensor system consists of three main closely interlinked components with a modular structure: sensors, data transmission, and data storage, which are integrated into pipelines for automated biodiversity monitoring. We present our own real‐world examples of applications, share our experiences in operating them, and provide our collected open data. Our flexible, low‐cost, and open‐source solutions can be applied for monitoring individual and multiple terrestrial plants and animals as well as their interactions. Ultimately, our system can also be applied to area‐wide ecosystem mapping tasks, thereby providing an exemplary cost‐efficient and powerful solution for biodiversity monitoring. Building upon our experiences in the Nature 4.0 project, we identified ten key challenges that need to be addressed to better understand and counteract the ongoing loss of biodiversity using networked sensor systems. To tackle these challenges, interdisciplinary collaboration, additional research, and practical solutions are necessary to enhance the capability and applicability of networked sensor systems for researchers and practitioners, ultimately further helping to ensure the sustainable management of ecosystems and the provision of ecosystem services

Nature 4.0: A networked sensor system for integrated biodiversity monitoring

Zeuss D, Bald L, Gottwald J, et al. Nature 4.0: A networked sensor system for integrated biodiversity monitoring. Global Change Biology. 2024;30(1): e17056.**Abstract** Ecosystem functions and services are severely threatened by unprecedented global loss in biodiversity. To counteract these trends, it is essential to develop systems to monitor changes in biodiversity for planning, evaluating, and implementing conservation and mitigation actions. However, the implementation of monitoring systems suffers from a trade‐off between grain (i.e., the level of detail), extent (i.e., the number of study sites), and temporal repetition. Here, we present an applied and realized networked sensor system for integrated biodiversity monitoring in the Nature 4.0 project as a solution to these challenges, which considers plants and animals not only as targets of investigation, but also as parts of the modular sensor network by carrying sensors. Our networked sensor system consists of three main closely interlinked components with a modular structure: sensors, data transmission, and data storage, which are integrated into pipelines for automated biodiversity monitoring. We present our own real‐world examples of applications, share our experiences in operating them, and provide our collected open data. Our flexible, low‐cost, and open‐source solutions can be applied for monitoring individual and multiple terrestrial plants and animals as well as their interactions. Ultimately, our system can also be applied to area‐wide ecosystem mapping tasks, thereby providing an exemplary cost‐efficient and powerful solution for biodiversity monitoring. Building upon our experiences in the Nature 4.0 project, we identified ten key challenges that need to be addressed to better understand and counteract the ongoing loss of biodiversity using networked sensor systems. To tackle these challenges, interdisciplinary collaboration, additional research, and practical solutions are necessary to enhance the capability and applicability of networked sensor systems for researchers and practitioners, ultimately further helping to ensure the sustainable management of ecosystems and the provision of ecosystem services