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BackgroundNucleated red blood cells (nRBC) are precursor cells of the erythropoiesis that are absent from the peripheral blood under physiological conditions. Their presence is associated with adverse outcomes in critically ill patients. This study aimed to evaluate the predictive value of nRBC on mortality in intensive care unit (ICU) patients with COVID-19 acute respiratory distress syndrome (ARDS).Material and methodsThis retrospective, observational cohort study analyzed data on 206 ICU patients diagnosed with COVID-19 ARDS between March 2020 and March 2022. The primary endpoint was ICU mortality, and secondary endpoints included ICU and hospital stay lengths, ventilation hours, and the time courses of disease severity scores and clinical and laboratory parameters.ResultsAmong the included patients, 68.9% tested positive for nRBC at least once during their ICU stay. A maximum nRBC of 105 µl-1 had the highest accuracy in predicting ICU mortality (area under the curve of the receiver operating characteristic [AUCROC] 0.780, p < 0.001, sensitivity 69.0%, specificity 75.5%). Mortality was significantly higher among patients with nRBC >105 µl-1 than ≤105 µl-1 (86.5% vs. 51.3%, p = 0.008). Compared to patients negative for nRBC in their peripheral blood, those positive for nRBC required longer mechanical ventilation (127 [44 - 289] h vs. 517 [255 - 950] h, p < 0.001), ICU stays (12 [8 – 19] vs. 27 [13 – 51] d, p < 0.001), and hospital stays (19 [12 - 29] d vs. 31 [16 - 58] d, p < 0.001). Peak Sepsis-related Organ Failure Assessment (SOFA), Simplified Acute Physiology Score, PaO2/FiO2, interleukin-6, and procalcitonin values were reached before the peak nRBC level. However, the predictive performance of the SOFA (AUCROC 0.842, p < 0.001) was considerably improved when a maximum SOFA score >8 and nRBC >105 µl-1 were combined.DiscussionnRBC predict ICU mortality and indicate disease severity among patients with COVID-19 ARDS, and they should be considered a clinical alarm signal for a worse outcome. nRBC are a late predictor of ICU mortality compared to other established clinical scoring systems and laboratory parameters but improve the prediction accuracy when combined with the SOFA score.

The Visayan Sea is one of the major traditional fishing grounds in the Philippines and is likewise considered as a top contributor to the country’s overall fisheries production. However, fisheries surveys conducted over the past couple of decades have documented changes in the abundance and composition of catches and stocks toward an increasing dominance of invertebrates and low trophic levels fish families. Assessments of the commercially-important pelagic and demersal stocks were used to estimate population parameters that already exceed the sustainable reference limits. These traditional assessments point exclusively to fishing as the likely cause of the observed status and trends, but they fail to incorporate the potential influence of trophic interactions and variable environmental conditions despite a nationally-legislated mandate to apply an ecosystem approach to assessing and managing the country’s fisheries. Thus, an ecosystem model (Ecopath with Ecosim) of the Visayan Sea was constructed to investigate the role and extent of the fishery, trophic interactions, and changing environmental conditions as drivers of stock abundance and ecosystem dynamics. The results suggest that fishing and its corresponding trophic effects are the major drivers of invertebrate and fish biomass and catches in the Visayan Sea over the past two decades, while the environmental trends provide explanations for patterns that cannot be explained by fishing alone. Incorporating sea surface temperature variations and primary productivity anomalies produced the best-fitting models for most of the observed biomass and catch trends. The catches of the small pelagics (i.e., sardines and mackerels) were likewise found to be particularly affected by rainfall, while the biomass and catch of the small demersal fishes also show a sensitivity to chlorophyll-a concentrations. The primary productivity anomalies further showed a significant correlation with the Pacific Decadal Oscillation (PDO), which suggests that bottom-up trophic controls in the system may be affected by long-term regional climatic changes. These findings validate the applicability and necessity of the ecosystem modeling approach in assessing exploited marine ecosystems to complement the analyses from typically single-species population assessments, especially in the face of increasing environmental variability and projected climate change scenarios.

Abstract Background COVID-19 can induce acute respiratory distress syndrome (ARDS). In patients with congenital heart disease, established treatment strategies are often limited due to their unique cardiovascular anatomy and passive pulmonary perfusion. Case presentation We report the first case of an adult with single-ventricle physiology and bidirectional cavopulmonary shunt who suffered from severe COVID-19 ARDS. Treatment strategies were successfully adopted, and pulmonary vascular resistance was reduced, both medically and through prone positioning, leading to a favorable outcome. Conclusion ARDS treatment strategies including ventilatory settings, prone positioning therapy and cannulation techniques for extracorporeal oxygenation must be adopted carefully considering the passive venous return in patients with single-ventricle physiology.

Abstract Introduction Treatment of high-risk pulmonary embolism (PE) in perioperative patients remains challenging. Systemic thrombolysis is associated with a high risk of major bleedings and intracranial haemorrhage. High mortality rates are reported for open pulmonary embolectomy. Therefore, postoperative surgical patients may benefit substantially from catheter-directed ultrasound-accelerated thrombolysis (USAT). Case presentation We report two cases of high-risk perioperative PE. Both patients developed severe haemodynamic instability leading to cardiac arrest. After the implantation of a veno-arterial extracorporeal membrane oxygenation (ECMO), they were both successfully treated with USAT. Adequate improvement of right ventricular function was achieved; thus, ECMO could be successfully weaned after 3 and 4 days, respectively. Both patients showed favourable outcomes and could be discharged to rehabilitation. Conclusion Current guidelines on treatment of PE offer no specific therapies for perioperative patients with high-risk PE. However, systemic thrombolysis is often excluded due to the perioperative setting and the risk of major bleeding. Catheter-directed thrombolysis was shown to utilise less thrombolytic agent while obtaining comparable thrombolytic effects. The risk for major bleeding (including intracranial haemorrhage) is also significantly lowered. Until further trials determining the value of adopted treatment strategies of high-risk PE in perioperative patients are available, USAT should be considered in similar cases.

The concept of intelligent agents is—roughly speaking—based on an architecture and a set of behavioral programs that primarily serve to solve problems autonomously. Increasing the degree of autonomy and improving cognitive performance, which can be assessed using cognitive and behavioral tests, are two important research trends. The degree of autonomy can be increased using higher-level psychological modules with which needs and motives are taken into account. In our approach we integrate these modules in architecture for an embodied, enactive multi-agent system, such that distributed problem solutions can be achieved. Furthermore, after uncovering some weaknesses in the cognitive performance of traditionally designed agents, we focus on two major aspects. On the one hand, the knowledge processing of cognitive agents is based on logical formalisms, which have deficiencies in the representation and processing of incomplete or uncertain knowledge. On the other hand, in order to fully understand the performance of cognitive agents, explanations at the symbolic and subsymbolic levels are required. Both aspects can be addressed by quantum-inspired cognitive agents. To investigate this approach, we consider two tasks in the sphere of Shannon's famous mouse-maze problem: namely classifying target objects and ontology inference. First, the classification of an unknown target object in the mouse-maze, such as cheese, water, and bacon, is based on sensory data that measure characteristics such as odor, color, shape, or nature. For an intelligent agent, we need a classifier with good prediction accuracy and explanatory power on a symbolic level. Boolean logic classifiers do work on a symbolic level but are not adequate for dealing with continuous data. Therefore, we demonstrate and evaluate a quantum-logic-inspired classifier in comparison to Boolean-logic-based classifiers. Second, ontology inference is iteratively achieved by a quantum-inspired agent through maze exploration. This requires the agent to be able to manipulate its own state by performing actions and by collecting sensory data during perception. We suggest an algebraic approach where both kinds of behaviors are uniquely described by quantum operators. The agent's state space is then iteratively constructed by carrying out unitary action operators, while Hermitian perception operators act as observables on quantum eigenstates. As a result, an ontology emerges as the simultaneous solution of the respective eigenvalue equations.

Softness is one of the essential properties of hygiene tissue products. Reliably measuring it is of utmost importance to ensure the balance between customer expectations and cost-effective tissue production. This study presents a method for assessing softness by analyzing acoustic emissions produced while tearing a tissue specimen. The aim was to train neural network models using the corrected results of human panel tests as the ground truth labels and to predict the tissue softness in two- and three-class recognition tasks. We also investigate the possibility of predicting some production parameters related to the softness property. The results proved that tissue softness and production parameters could be reliably estimated only by the tearing noise.

The coast of Peru lies within the tropics under the influence of the cold, nutrient-rich waters of the Humboldt Current and the interannual onslaught of the El Niño phenomenon. The Peruvian upwelling system is exceptionally productive and is comprised of subsystems at different scales along the coast. We aimed to understand the differences between two shallow coastal systems along a latitudinal gradient: Sechura Bay in the north (at the convergence of Humboldt and tropical waters) and Independencia Bay in the central-south (under typical upwelling conditions). We compared their biodiversity, trophic dynamics, community energetics, resource use and underlying abiotic conditions. Our analysis revealed that over the past two decades, Sechura has shown a warming trend, while Independencia has maintained its cold water conditions. Chlorophyll concentrations have risen significantly in both systems, higher values in Sechura suggesting there is an increase in local pressures that could lead to eutrophication. Trophic models of the La Niña 07/08 period revealed that both systems are bottom-up driven with high biomass and production at the lower trophic levels, though top-down controls were also shown, particularly in Sechura. While primary productivity was similar in both systems, differences were found in the structure and size of energy flows. More cycling and higher transfer efficiency were found in Independencia, where phytoplankton-based food chains played the main role in the overall dynamic. In contrast, the detritus food chain appears to be more relevant for energy flow in Sechura. Differences in biota and flow structure relate to the systems’ environmental conditions, i.e., more diverse warm-water species in the north and mostly cold water adapted species (mainly invertebrate filter-feeders and their predators) in the central-south. Catches in both systems were dominated by the diving fisheries and comprised mostly scallops (bottom-cultured), snails and fish in Sechura, and mussels, clams, crabs and fish in Independencia. Overall, system indicators suggest that Sechura is a comparatively less developed system. Independencia shall likely maintain its general highly productive system features, whereas Sechura will continue to be more frequently disturbed by El Niño and ongoing human-driven activities, reducing its overall stability and functionality. In the context of climate change, acknowledging these differences is essential for future adaptive management regimes.

Cognitive agents that act independently and solve problems in their environment on behalf of a user are referred to as autonomous. In order to increase the degree of autonomy, advanced cognitive architectures also contain higher-level psychological modules with which needs and motives of the agent are also taken into account and with which the behavior of the agent can be controlled. Regardless of the level of autonomy, successful behavior is based on interacting with the environment and being able to communicate with other agents or users. The agent can use these skills to learn a truthful knowledge model of the environment and thus predict the consequences of its own actions. For this purpose, the symbolic information received during the interaction and communication must be converted into representational data structures so that they can be stored in the knowledge model, processed logically and retrieved from there. Here, we firstly outline a grammar-based transformation mechanism that unifies the description of physical interaction and linguistic communication and on which the language acquisition is based. Specifically, we use minimalist grammar (MG) for this aim, which is a recent computational implementation of generative linguistics. In order to develop proper cognitive information and communication technologies, we are using utterance meaning transducers (UMT) that are based on semantic parsers and a mental lexicon, comprising syntactic and semantic features of the language under consideration. This lexicon must be acquired by a cognitive agent during interaction with its users. To this aim we outline a reinforcement learning algorithm for the acquisition of syntax and semantics of English utterances. English declarative sentences are presented to the agent by a teacher in form of utterance meaning pairs (UMP) where the meanings are encoded as formulas of predicate logic. Since MG codifies universal linguistic competence through inference rules, thereby separating innate linguistic knowledge from the contingently acquired lexicon, our approach unifies generative grammar and reinforcement learning, hence potentially resolving the still pending Chomsky-Skinner controversy.

Based on the fact that cogwheels are indispensable parts in manufacturing, we present the acoustic resonance testing (ART) of small data on sintered cogwheels for quality control in the context of non-destructive testing (NDT). Considering the lack of extensive studies on cogwheel data by means of ART in combination with machine learning (ML), we utilize time-frequency domain feature analysis and apply ML algorithms to the obtained feature sets in order to detect damaged samples in two ways: one-class and binary classification. In each case, despite small data, our approach delivers robust performance: All damaged test samples reflecting real-world scenarios are recognized in two one-class classifiers (also called detectors), and one intact test sample is misclassified in binary ones. This shows the usefulness of ML and time-frequency domain feature analysis in ART on a sintered cogwheel dataset.

Encouraging people’s pro-environmental behaviors is an objective of Education for Sustainable Development. In the context of small-scale fisheries, unsustainable fishing practices are compromising the integrity of coastal communities and ecosystems. Ecopath with Ecosim (EwE) is an ecosystem modeling software that presents interactions/changes in the food web as a result of fishing. Despite the multiple applications of EwE in fisheries management, it is unknown from a quantitative perspective whether the application of EwE trophic modeling in environmental education processes and management produces effects on norms and ecological beliefs, and if it alters behavioral intentions of the participants receiving ecosystem modeling information. We conducted a behavior change intervention with gillnet fishers in the Gulf of Nicoya, Costa Rica, to compare antecedents of pro-environmental behavior between participants who received an ecosystem-based intervention (lectures containing EwE models; treatment) and those who received lectures that didn’t involve EwE (control). Based on theories of environmental psychology, we used a pre–post survey design, to evaluate changes between control/treatment, and to assess the influence of psychometric constructs and fishing characteristics on the behavioral intentions to support sustainable fishing measures and owning a fishing license (revealed behavior). Personal norms and values were significant at explaining management measures’ support, along with some fishing characteristics (e.g., fishing site). Deliberating about possible future scenarios (via EwE-modeling) helped reduce uncertainties, increasing legitimacy and a perceived behavioral control (PBC) to support measures. Currently, licenses in the Gulf aren’t granted under defined ecological criteria, and although altruistic-biospheric values scored highly before the intervention began, due to mistrust and high illegal-unlicensed fishing, fishers may be underestimating how much others care about the environment. Value-oriented and ecosystem-based interventions may assist to effectively redesign the licensing system and encourage fishers to support sustainable measures. Our research indicates the importance of education interventions that teach about the impacts of fishing in the ecosystem while helping participants to perceive themselves as capable of implementing actions (PBC) and expressing biospheric-altruistic values to restore trust. Redirecting human behaviors to reconnect with ecosystem resilience can be a leverage point for sustainability and for the compliance of small-scale fisheries management measures.

The Gulf of Nicoya is a large tropical estuary located on the Pacific coast of Costa Rica and accounts for the country’s main fish production. It is increasingly impacted not only by its fisheries, but also by urbanization, tourism developments, the input of pollutants from urban centers and agriculture activities in the catchment areas of large rivers entering the gulf. Similar to other coastal ecosystems, the gulf is particularly sensitive to short- and long-term changes in the climate, such as the precipitation rate, Sea Surface Temperature, wind speed and current regimes. While the gulf has been studied for decades, until now no attempt has been made to combine the analysis of the impacts of fishing and environmental changes on the ecosystem. By following a holistic approach that uses fisheries and environmental time series data from collaborative research and simulation models, this study aims at identifying the main drivers of the observed changes in the Gulf of Nicoya ecosystem. While the model simulations indicate that variations in the catch of some target species (e.g., cephalopods and shrimps) are mainly driven by the fisheries’ exploitation rates, several other species (e.g., corvina, snook, small pelagics, and crabs) are also substantially affected by climate variations, particularly during El Niño periods of high Sea Surface Temperature extremes and increased precipitation. During these periods, phytoplankton productivity and zooplankton biomass deceases with bottom–up effects on the entire food chain. Indicators of the environmental state of the system thus have to be considered along with regulations of the fishing pressure to form the basis for the development of appropriate management strategies.

The early administration of fibrinogen has gained wide acceptance for the treatment of major hemorrhage, whereas the substitution of coagulation factor XIII (FXIII) is only supported by a low level of evidence. This study aimed to answer the question of whether a combined therapy of fibrinogen/FXIII substitution performs superiorly to sole fibrinogen administration in the treatment of dilutional coagulopathy. An in-vitro model of massive transfusion was used to compare the effect of combined fibrinogen/FXIII administration to that of sole fibrinogen therapy for the treatment of dilutional coagulopathy. For this purpose, the blood of red blood cell concentrates, fresh frozen plasma, and platelet concentrates were reconstituted in a ratio of 4:4:1, and then diluted with gelatin by 20% and 40%, respectively. Clot formation and stability were analyzed by thrombelastography. Both sole fibrinogen therapy (equivalent to 50 mg/kg) and the combined administration of fibrinogen (equivalent to 50 mg/kg) and FXIII (equivalent to 75 International Units (IU)/kg) increased fibrinogen-dependent mean clot firmness independently of the degree of dilution (20% dilution: 7 (6.3–7.8) mm; 20% dilution fibrinogen: 13.5 (13–17.3) mm; 20% dilution fibrinogen/FXIII: 16.5 (15.3–18.8) mm; 40% dilution: 3 (2–3.8) mm; 40% dilution fibrinogen: 8 (7–11.3) mm; 40% dilution fibrinogen/FXIII: 10 (8.3–11.8) mm; all p < 0.01). However, no differences were identified between the two treatment arms. Compared to fibrinogen therapy, no beneficial effect of the combined administration of fibrinogen and FXIII for the treatment of dilutional coagulopathy was detected in this in-vitro massive transfusion model. The result was independent of the degree of dilution.

Trophic models of the Ecopath with Ecosim (EwE) type and local ecological knowledge (LEK) have widely been applied to fisheries assessment and management. However, there are no specific methodologies describing how LEK from local fishers can be incorporated with the scientific data from the models in the context of ecosystem-based fisheries management. To our knowledge this is the first contribution exploring a systematic integration of LEK with EwE modeled output. An EwE food web model of the Nicoya Gulf ecosystem constructed 20 years ago and recently revisited by the authors and collaborators, was used in workshops to stimulate discussion among local stakeholders regarding changes in the marine ecosystem. For this study, 58 artisanal fishers were recruited to eight workshops. To assess the LEK, we documented the discussions, and the qualitative data were analyzed with quantitative frequency of responses to identify trends. Next, we systematically compared the changes in the fishery over time through an analysis of similar, complementary, and contradictory information across knowledge systems. In general, the analysis across systems reflected changes in species composition of the catches, paralleled by a harvest reduction in high-trophic-level species, as well as economic losses due to a shift in harvesting low-value species and due to an increase in operational costs. Particularly, we identified (1) similar pieces of information that delivered the same message, providing robust evidence of changes in the social–ecological system; (2) information complementary to each other, which together provided a broader picture (descriptors and attributes) of the changes of some fishing resources; and (3) conflicting pieces of information that indicated mismatches between sources of knowledge, which might suggest the cause of management problems. This study demonstrated how integrating knowledge systems can enhance our understanding of the state and changes in ecosystems, helping to improve fisheries management. We also found that an EwE model can be an effective communication tool to be used with fishers and to promote discussion and engagement. Our aspiration is to bring new and replicable tools to the policy interface in Latin-American fisheries, based on both stakeholder participation (including LEK) and the best scientific information available.

Small-scale fisheries (SSF) remain a largely under-assessed and overlooked sector by governments and researchers, despite contributing approximately 50% to global fish landings and providing food and income for millions of people. The multi-species, multi-gear and data-poor nature of SSF makes implementation of traditional single-species management approaches – like catch-quotas or size limits – particularly challenging and insufficient. A more holistic approach is thus required, which demands assessment of ecological impacts. Here we carried out an estimation of selected ecological indicators of the impact of fisheries (mean length, maximum body size, mean trophic level, trophic and spatial guilds, threatened species and landed by-catch) based on the nominal catch of different gears in three representative SSF along the Colombian Pacific using landings data collected in multiple years (2011–2017). Results showed that taxonomic, size-based, functional and conservation features of the nominal catch vary greatly with geographical location and gear type used. Overall, handlines and longlines tend to select larger sizes and higher trophic levels than nets, but they also catch a higher proportion of intrinsically vulnerable species and species of conservation concern. This challenges the idea that more selective gears have overall lower ecological impacts. In contrast, nets target a wider size range – although focusing on small or medium sized fish – and include a higher diversity of trophic and spatial guilds, which could arguably be considered a more “balanced harvest” type of fishing that retains ecosystem structure and functionality. Bottom trawls, though, exhibited a relatively high percentage of landed by-catch, an undesirable feature for any fisheries in terms of sustainability. We propose that the assessment of a suite of ecological indicators, like those implemented here, should be included as part of periodic evaluations of multi-gear and multi-species SSF in tropical coastal areas, as a practical step toward ecosystem-based fisheries management.