Ribonuclease inhibitor 1 emerges as a potential biomarker and modulates inflammation and iron homeostasis in sepsis.

Sepsis, marked by organ dysfunction, necessitates reliable biomarkers. Ribonuclease inhibitor 1 (RNH1), a ribonuclease (RNase) inhibitor, emerged as a potential biomarker for acute kidney injury and mortality in thoracoabdominal aortic aneurysm patients. Our study investigates RNH1 dynamics in sepsis, its links to mortality and organ dysfunction, and the interplay with RNase 1 and RNase 5. Furthermore, we explore RNH1 as a therapeutic target in sepsis-related processes like inflammation, non-canonical inflammasome activation, and iron homeostasis. We showed that RNH1 levels are significantly higher in deceased patients compared to sepsis survivors and correlate with creatine kinase, aspartate and alanine transaminase, bilirubin, serum creatinine and RNase 5, but not RNase 1. RNH1 mitigated LPS-induced TNFα and RNase 5 secretion, and relative mRNA expression of ferroptosis-associated genes HMOX1, FTH1 and HAMP in PBMCs. Monocytes were identified as the predominant type of LPS-positive PBMCs. Exogenous RNH1 attenuated LPS-induced CASP5 expression, while increasing IL-1ß secretion in PBMCs and THP-1 macrophages. As RNH1 has contradictory effects on inflammation and non-canonical inflammasome activation, its use as a therapeutic agent is limited. However, RNH1 levels may play a central role in iron homeostasis during sepsis, supporting our clinical observations. Hence, RNH1 shows promise as biomarkers for renal and hepatic dysfunction and hepatocyte injury, and may be useful in predicting the outcome of septic patients.

The Impact of Implant Abutment Angle and Height on Peri-implant Tissue Health: Retrospective Analyses from a Randomized Controlled Clinical Trial.

PURPOSE: To examine the influence of abutment emergence angle and abutment height on marginal peri-implant bone stability in patients not considered susceptible to peri-implantitis. Furthermore, it was analyzed whether titanium-base (Ti-base) abutments lead to wider abutment emergence angles compared to one-piece abutments. MATERIALS AND METHODS: A total of 48 abutments (ie, 24 Ti-base and 24 one-piece abutments in 24 patients) were evaluated at abutment installation, after 1 year, and thereafter on a yearly basis for up to 5 years. Clinical and radiographic outcome variables were assessed. RESULTS: With regard to peri-implant marginal bone stability, only moderately negative, albeit significant, correlations were found on the mesial sides of the one-piece abutments after 4 and 5 years for an abutment emergence angle > 30 degrees. No statistically significant negative correlations were found for distances of ≤ 1.5 mm between the restoration margin and the crestal peri-implant bone level for either Ti-base or for one-piece abutments. Furthermore, abutments bonded to Ti-bases were not associated with larger emergence angles than one-piece abutments. CONCLUSIONS: For patients at low risk of developing peri-implantitis, it can be concluded that neither a larger abutment emergence angle (> 30 degrees) nor a distance of ≤ 1.5 mm between the restoration margin and the crestal peri-implant bone level are associated with marginal peri-implant bone loss. Furthermore, abutments bonded to Ti-bases are not associated with wider emergence angles than one-piece abutments.

Plasma proteome signature of canine acute haemorrhagic diarrhoea syndrome (AHDS).

Acute haemorrhagic diarrhoea is a common complaint in dogs. In addition to causes like intestinal parasites, dietary indiscretion, intestinal foreign bodies, canine parvovirus infection, or hypoadrenocorticism, acute haemorrhagic diarrhoea syndrome (AHDS) is an important and sometimes life-threatening differential diagnosis. There is some evidence supporting the link between Clostridium perfringens toxins and AHDS. These toxins may be partially responsible for the epithelial cell injury, but the pathogenesis of AHDS is still not fully understood. Recent studies have suggested that severe damage to the intestinal mucosa and associated barrier dysfunction can trigger chronic gastrointestinal illnesses. Besides bloodwork and classical markers for AHDS such as protein loss and intestinal bacterial dysbiosis, we focused mainly on the plasma-proteome to identify systemic pathological alterations during this disease and searched for potential biomarkers to improve the diagnosis. To accomplish the goals, we used liquid chromatography-mass spectrometry. We compared the proteomic profiles of 20 dogs with AHDS to 20 age-, breed-, and sex-matched control dogs. All dogs were examined, and several blood work parameters were determined and compared, including plasma biochemistry and cell counts. We identified and quantified (relative quantification) 207 plasmatic proteins, from which dozens showed significantly altered levels in AHDS. Serpina3, Lipopolysaccharide-binding protein, several Ig-like domain-containing proteins, Glyceraldehyde-3-phosphate dehydrogenase and Serum amyloid A were more abundant in plasma from AHDS affected dogs. In contrast, other proteins such as Paraoxonase, Selenoprotein, Amine oxidases, and Apolipoprotein C-IV were significantly less abundant. Many of the identified and quantified proteins are known to be associated with inflammation. Other proteins like Serpina3 and RPLP1 have a relevant role in oncogenesis. Some proteins and their roles have not yet been described in dogs with diarrhoea. Our study opens new avenues that could contribute to the understanding of the aetiology and pathophysiology of AHDS.

Standardized Comparison of Voice-Based Information and Documentation Systems to Established Systems in Intensive Care: Crossover Study.

BACKGROUND: The medical teams in intensive care units (ICUs) spend increasing amounts of time at computer systems for data processing, input, and interpretation purposes. As each patient creates about 1000 data points per hour, the available information is abundant, making the interpretation difficult and time-consuming. This data flood leads to a decrease in time for evidence-based, patient-centered care. Information systems, such as patient data management systems (PDMSs), are increasingly used at ICUs. However, they often create new challenges arising from the increasing documentation burden. OBJECTIVE: New concepts, such as artificial intelligence (AI)-based assistant systems, are hence introduced to the workflow to cope with these challenges. However, there is a lack of standardized, published metrics in order to compare the various data input and management systems in the ICU setting. The objective of this study is to compare established documentation and retrieval processes with newer methods, such as PDMSs and voice information and documentation systems (VIDSs). METHODS: In this crossover study, we compare traditional, paper-based documentation systems with PDMSs and newer AI-based VIDSs in terms of performance (required time), accuracy, mental workload, and user experience in an intensive care setting. Performance is assessed on a set of 6 standardized, typical ICU tasks, ranging from documentation to medical interpretation. RESULTS: A total of 60 ICU-experienced medical professionals participated in the study. The VIDS showed a statistically significant advantage compared to the other 2 systems. The tasks were completed significantly faster with the VIDS than with the PDMS (1-tailed t59=12.48; Cohen d=1.61; P<.001) or paper documentation (t59=20.41; Cohen d=2.63; P<.001). Significantly fewer errors were made with VIDS than with the PDMS (t59=3.45; Cohen d=0.45; P=.03) and paper-based documentation (t59=11.2; Cohen d=1.45; P<.001). The analysis of the mental workload of VIDS and PDMS showed no statistically significant difference (P=.06). However, the analysis of subjective user perception showed a statistically significant perceived benefit of the VIDS compared to the PDMS (P<.001) and paper documentation (P<.001). CONCLUSIONS: The results of this study show that the VIDS reduced error rate, documentation time, and mental workload regarding the set of 6 standardized typical ICU tasks. In conclusion, this indicates that AI-based systems such as the VIDS tested in this study have the potential to reduce this workload and improve evidence-based and safe patient care.

A Potential Association between Ribonuclease 1 Dynamics in the Blood and the Outcome in COVID-19 Patients.

The COVID-19 pandemic caused by the new SARS-CoV-2 coronavirus is the most recent and well-known outbreak of a coronavirus. RNase 1 is a small endogenous antimicrobial polypeptide that possesses antiviral activity against viral diseases. In this study, we investigated a potential association between ribonuclease 1 and the outcome in COVID-19 patients and the impact of increased and decreased RNase 1 levels serum during the course of the disease. Therefore, two patient populations, Cohort A (n = 35) and B (n = 80), were subclassified into two groups, in which the RNase 1 concentration increased or decreased from time point one to time point two. We show that the RNase 1 serum levels significantly increased in the increasing group of both cohorts (p = 0.0171; p < 0.0001). We detect that patients in the increasing group who died had significantly higher RNase 1 serum levels at both time points in Cohort A (p = 0.0170; p = 0.0393) and Cohort B (p = 0.0253; p = 0.0034) than patients who survived. Additionally, we measured a significant correlation of RNase 1 serum levels with serum creatinine as well as creatinine clearance in the increasing and decreasing group at both time points of Cohort A. Based on these results, there is now good evidence that RNase 1 may play a role in renal dysfunction associated with ICU COVID-19 patients and that increasing RNase 1 serum level may be a potential biomarker to predict outcome in COVID-19 patients.

The impact of implant abutment angle and height on peri-implant tissue health: Retrospective analyses from a randomized, controlled, clinical trial.

PURPOSE: Implant abutment design may influence the predisposition of peri-implant sites to develop peri-implant inflammation, especially peri-implantitis. Therefore, the objectives of the current study were to examine the influence of (1) abutment emergence angle and, (2) abutment height on marginal periimplant bone stability in patients not considered susceptible to peri-implantitis. Furthermore, it was analyzed (3) whether Ti-Base abutments lead to wider abutment emergence angles as compared to onepiece abutments. MATERIALS AND METHODS: 48 abutments (i.e., 24 Ti-base- and 24 one-piece abutments in 24 patients) have been at abutment installation, after one year, and thereafter on a yearly basis for up to five years. Clinical and radiographic outcome variables were assessed. RESULTS: With regard to peri-implant marginal bone stability, (1) only moderately negative, albeit significant, correlations were found on the mesial sides of the one-piece abutments after 4 and 5 years for an abutment emergence angle >30° and no statistically significant negative correlations were found between a distance of less than or equal to versus more than 1.5 mm between the restoration margin and the crestal peri-implant bone level, neither for Ti-Base nor for one-piece abutments. Furthermore, (3) abutments bonded to Ti-bases are not associated with larger emergence angles than one-piece abutments. CONCLUSION: For patients at low risk of developing peri-implantitis it can be concluded, that neither (1) a larger abutment emergence angle (>30°) nor (2) a distance of less than or equal to 1.5 mm between the restoration margin and the crestal peri-implant bone level are per se associated with marginal periimplant bone loss. Furthermore, (3) abutments bonded to Ti-bases are not as such associated with wider emergence angles than one-piece abutments. Int J Prosthodont 2023. doi: 10.11607/ijp.8138.

Two-stage visual speech recognition for intensive care patients.

In this work, we propose a framework to enhance the communication abilities of speech-impaired patients in an intensive care setting via reading lips. Medical procedure, such as a tracheotomy, causes the patient to lose the ability to utter speech with little to no impact on the habitual lip movement. Consequently, we developed a framework to predict the silently spoken text by performing visual speech recognition, i.e., lip-reading. In a two-stage architecture, frames of the patient's face are used to infer audio features as an intermediate prediction target, which are then used to predict the uttered text. To the best of our knowledge, this is the first approach to bring visual speech recognition into an intensive care setting. For this purpose, we recorded an audio-visual dataset in the University Hospital of Aachen's intensive care unit (ICU) with a language corpus hand-picked by experienced clinicians to be representative of their day-to-day routine. With a word error rate of 6.3%, the trained system reaches a sufficient overall performance to significantly increase the quality of communication between patient and clinician or relatives.

Systemic thrombolytic and ultrasound-assisted catheter-directed thrombolysis for treatment of acute pulmonary embolism: a 7-year, multicenter experience.

Treatment of acute pulmonary embolism (PE) varies based upon risk stratification and ranges from outpatient oral anticoagulation to emergency surgical embolectomy. Patients with high-risk PE can be considered for systemic thrombolytic (ST) based upon guideline recommendations, but intermediate-risk PE does not currently have strong evidence to guide primary reperfusion strategies via thrombolytic administration. Ultrasound-assisted catheter-directed thrombolysis (USAT) is an alternative reperfusion option to ST but is not currently recommended as first line in any key guidelines due to limited available evidence. This retrospective, multicenter, observational study compares 210 patients treated with USAT (n = 105) or ST (n = 105) for acute high- or intermediate-risk PE in three hospitals. Baseline characteristics were significant in that severity of illness was higher in those that received ST, which limited comparisons of outcomes. The primary outcome of major bleeding in patients receiving USAT was 15.2% and 22.9% in those that received ST. Efficacy of reperfusion strategy was observed to be 86.7% of patients in USAT group and 65.7% in ST group. Reperfusion strategies had no difference in in-hospital death, intensive care length of stay, or hospital length of stay. Predefined subgroup analysis found that high-risk PE had higher mortality (14.7%) than intermediate-risk PE (0%) regardless of reperfusion strategy. Upon multivariate analysis, high-risk PE was the only independent risk factor for major bleeding while USAT therapy and intermediate-risk PE were independent predictors of efficacy. Due to the difference in baseline severity of illness, direct comparisons in primary outcomes to each group was not performed. We have described real world usage of both USAT and ST and which patients were likely to receive each therapy at these institutions.

DAMPs Released from Proinflammatory Macrophages Induce Inflammation in Cardiomyocytes via Activation of TLR4 and TNFR.

Cardiac dysfunction is a life-threatening complication in sepsis. Upon infection and cardiac stress, the cardiac macrophage population expands. Recruited macrophages exhibit a predominantly proinflammatory phenotype and release danger-associated molecular patterns (DAMPs) that contribute to cardiac dysfunction. However, the underlying pathomechanisms are highly complex and not fully understood. Here, we utilized an indirect macrophage-cardiomyocyte co-culture model to study the effects of proinflammatory macrophages on the activation of different cardiac receptors (TLR3, TLR4, and TNFR) and their role in cardiac inflammation and caspase-3/7 activation. The stimulation of cardiomyocytes with conditioned medium of LPS-stimulated macrophages resulted in elevated IL-6 protein concentrations and relative IL-6 and TNFα mRNA levels. Conditioned medium from LPS-stimulated macrophages also induced NFκB translocation and increased caspase-3/7 activation in cardiomyocytes. Analyzing the role of different cardiac receptors, we found that TLR4 and TNFR inhibition reduces cardiac inflammation and that the inhibition of TNFR prevents NFκB translocation into the nuclei of cardiomyocytes, induced by exposure to conditioned medium of proinflammatory macrophages. Moreover, we demonstrated that TLR3 inhibition reduces macrophage-mediated caspase-3/7 activation. Our results suggest that the immune response of macrophages under inflammatory conditions leads to the release of DAMPs, such as eRNA and cytokines, which in turn induce cardiomyocyte dysfunction. Thus, the data obtained in this study contribute to a better understanding of the pathophysiological mechanisms of cardiac dysfunction.

Development and Implementation of the Data Science Learning Platform for Research Physician.

Data analysis and their application are the unavoidable factors in the activities analyses in health care. Unfortunately, the acquisition of data from large available medical databases is a complex process and requires deep knowledge of computer science and especially knowledge of tools for data management. According to the European General Data Protection Regulation, the problem becomes much more complex. Recognizing these problems and difficulties, we have developed a Data Science Learning Platform (DSLP) that primarily targets practitioners and researchers but also the computer science students. Using our proposed tool chain together with the developed graphical user interface, data scientists and research physicians will be able to use available medical databases, apply and analyze different anonymization methods, analyze data according to the patient's risk and quickly formulate new studies to target a disease in a complex data model. This article presents a clinical research discovery toolbox that implements and demonstrates tools for data anonymization, patient data visualization, NLP-tools for guideline search and data science learning tools.

A Visualization and Benchmarking Simulator for Clinical Data.

The availability of Big Data has increased significantly in many areas in recent years. Insights from these data sets lead to optimized processes in many industries, which is why understanding as well as gaining knowledge through analyses of these data sets is becoming increasingly relevant. In the medical field, especially in intensive care units, fast and appropriate treatment is crucial due to the usually critical condition of patients. The patient data recorded here is often very heterogeneous and the resulting database models are very complex, so that accessing and thus using this data requires technical background knowledge. We have focused on the development of a web application that is primarily aimed at clinical staff and researchers. It is an easily accessible visualization and benchmarking tool that provides a graphical interface for the MIMIC-III database. The anonymized datasets contained in MIMIC-III include general information about patients as well as characteristics such as vital signs and laboratory measurements. These datasets are of great interest because they can be used to improve digital decision support systems and clinical processes. Therefore, in addition to visualization, the application can be used by researchers to validate anomaly detection algorithms and by clinical staff to assess disease progression. For this purpose, patient data can be individualized through modifications such as increasing and decreasing vital signs and laboratory parameters so that disease progression can be simulated and subsequently analyzed according to the user's specific needs.

The Potential Impact of Heparanase Activity and Endothelial Damage in COVID-19 Disease.

SARS-CoV-2 was first detected in 2019 in Wuhan, China. It has been found to be the most pathogenic virus among coronaviruses and is associated with endothelial damage resulting in respiratory failure. Determine whether heparanase and heparan sulfate fragments, biomarkers of endothelial function, can assist in the risk stratification and clinical management of critically ill COVID-19 patients admitted to the intensive care unit. We investigated 53 critically ill patients with severe COVID-19 admitted between March and April 2020 to the University Hospital RWTH Aachen. Heparanase activity and serum levels of both heparanase and heparan sulfate were measured on day one (day of diagnosis) and day three in patients with COVID-19. The patients were classified into four groups according to the severity of ARDS. When compared to baseline data (day one), heparanase activity increased and the heparan sulfate serum levels decreased with increasing severity of ARDS. The heparanase activity significantly correlated with the lactate concentration on day one (r = 0.34, p = 0.024) and on day three (r = 0.43, p = 0.006). Heparanase activity and heparan sulfate levels correlate with COVID-19 disease severity and outcome. Both biomarkers might be helpful in predicting clinical course and outcomes in COVID-19 patients.

Predicting Abnormalities in Laboratory Values of Patients in the Intensive Care Unit Using Different Deep Learning Models: Comparative Study.

BACKGROUND: In recent years, the volume of medical knowledge and health data has increased rapidly. For example, the increased availability of electronic health records (EHRs) provides accurate, up-to-date, and complete information about patients at the point of care and enables medical staff to have quick access to patient records for more coordinated and efficient care. With this increase in knowledge, the complexity of accurate, evidence-based medicine tends to grow all the time. Health care workers must deal with an increasing amount of data and documentation. Meanwhile, relevant patient data are frequently overshadowed by a layer of less relevant data, causing medical staff to often miss important values or abnormal trends and their importance to the progression of the patient's case. OBJECTIVE: The goal of this work is to analyze the current laboratory results for patients in the intensive care unit (ICU) and classify which of these lab values could be abnormal the next time the test is done. Detecting near-future abnormalities can be useful to support clinicians in their decision-making process in the ICU by drawing their attention to the important values and focus on future lab testing, saving them both time and money. Additionally, it will give doctors more time to spend with patients, rather than skimming through a long list of lab values. METHODS: We used Structured Query Language to extract 25 lab values for mechanically ventilated patients in the ICU from the MIMIC-III and eICU data sets. Additionally, we applied time-windowed sampling and holding, and a support vector machine to fill in the missing values in the sparse time series, as well as the Tukey range to detect and delete anomalies. Then, we used the data to train 4 deep learning models for time series classification, as well as a gradient boosting-based algorithm and compared their performance on both data sets. RESULTS: The models tested in this work (deep neural networks and gradient boosting), combined with the preprocessing pipeline, achieved an accuracy of at least 80% on the multilabel classification task. Moreover, the model based on the multiple convolutional neural network outperformed the other algorithms on both data sets, with the accuracy exceeding 89%. CONCLUSIONS: In this work, we show that using machine learning and deep neural networks to predict near-future abnormalities in lab values can achieve satisfactory results. Our system was trained, validated, and tested on 2 well-known data sets to ensure that our system bridged the reality gap as much as possible. Finally, the model can be used in combination with our preprocessing pipeline on real-life EHRs to improve patients' diagnosis and treatment.

Inhibition of Macrophage Migration Inhibitory Factor Activity Attenuates Haemorrhagic Shock-Induced Multiple Organ Dysfunction in Rats.

Objective: The aim of this study was to investigate (a) macrophage migration inhibitory factor (MIF) levels in polytrauma patients and rats after haemorrhagic shock (HS), (b) the potential of the MIF inhibitor ISO-1 to reduce multiple organ dysfunction syndrome (MODS) in acute (short-term and long-term follow-up) HS rat models and (c) whether treatment with ISO-1 attenuates NF-κB and NLRP3 activation in HS. Background: The MODS caused by an excessive systemic inflammatory response following trauma is associated with a high morbidity and mortality. MIF is a pleiotropic cytokine which can modulate the inflammatory response, however, its role in trauma is unknown. Methods: The MIF levels in plasma of polytrauma patients and serum of rats with HS were measured by ELISA. Acute HS rat models were performed to determine the influence of ISO-1 on MODS. The activation of NF-κB and NLRP3 pathways were analysed by western blot in the kidney and liver. Results: We demonstrated that (a) MIF levels are increased in polytrauma patients on arrival to the emergency room and in rats after HS, (b) HS caused organ injury and/or dysfunction and hypotension (post-resuscitation) in rats, while (c) treatment of HS-rats with ISO-1 attenuated the organ injury and dysfunction in acute HS models and (d) reduced the activation of NF-κB and NLRP3 pathways in the kidney and liver. Conclusion: Our results point to a role of MIF in the pathophysiology of trauma-induced organ injury and dysfunction and indicate that MIF inhibitors may be used as a potential therapeutic approach for MODS after trauma and/or haemorrhage.

Theranostic Trigger-Responsive Carbon Monoxide-Generating Microbubbles.

Carbon monoxide (CO) is a gaseous signaling molecule that modulates inflammation, cell survival, and recovery after myocardial infarction. However, handling and dosing of CO as a compressed gas are difficult. Here, light-triggerable and magnetic resonance imaging (MRI)-detectable CO release from dimanganese decacarbonyl (CORM-1) are demonstrated, and the development of CORM-1-loaded polymeric microbubbles (COMB) is described as an ultrasound (US)- and MRI-imageable drug delivery platform for triggerable and targeted CO therapy. COMB are synthesized via a straightforward one-step loading protocol, present a narrow size distribution peaking at 2 µm, and show excellent performance as a CORM-1 carrier and US contrast agent. Light irradiation of COMB induces local production and release of CO, as well as enhanced longitudinal and transversal relaxation rates, enabling MRI monitoring of CO delivery. Proof-of-concept studies for COMB-enabled light-triggered CO release show saturation of hemoglobin with CO in human blood, anti-inflammatory differentiation of macrophages, reduction of hypoxia-induced reactive oxygen species (ROS) production, and inhibition of ischemia-induced apoptosis in endothelial cells and cardiomyocytes. These findings indicate that CO-generating MB are interesting theranostic tools for attenuating hypoxia-associated and ROS-mediated cell and tissue damage in cardiovascular disease.

[Artificial Intelligence: Challenges and Applications in Intensive Care Medicine]. / Künstliche Intelligenz: Herausforderungen und Nutzen in der Intensivmedizin.

The high workload in intensive care medicine arises from the exponential growth of medical knowledge, the flood of data generated by the permanent and intensive monitoring of intensive care patients, and the documentation burden. Artificial intelligence (AI) is predicted to have a great impact on ICU work in the near future as it will be applicable in many areas of critical care medicine. These applications include documentation through speech recognition, predictions for decision support, algorithms for parameter optimisation and the development of personalised intensive care medicine. AI-based decision support systems can augment human therapy decisions. Primarily through machine learning, a sub-discipline of AI, self-adaptive algorithms can learn to recognise patterns and make predictions. For actual use in clinical settings, the explainability of such systems is a prerequisite. Intensive care staff spends a large amount of their working hours on documentation, which has increased up to 50% of work time with the introduction of PDMS. Speech recognition has the potential to reduce this documentation burden. It is not yet precise enough to be usable in the clinic. The application of AI in medicine, with the help of large data sets, promises to identify diagnoses more quickly, develop individualised, precise treatments, support therapeutic decisions, use resources with maximum effectiveness and thus optimise the patient experience in the near future.

Co-infection with Babesia canis and Babesia gibsoni in a dog.

A four-year-old intact male Boxer, that had a history of travelling to Serbia, was referred for lethargy and anaemia. Shortly before the dog was referred, it was diagnosed twice with an infection with Babesia canis and was treated with imidocarb both times. A blood smear evaluation was indicative of the presence of intraerythrocytic piroplasms. After receiving inconclusive results regarding the type of piroplasm, the dog was diagnosed with simultaneous infections with B. canis and Babesia gibsoni via real-time polymerase chain reaction (rt-PCR) testing. The dog was treated with imidocarb, atovaquone and azithromycin, and in a follow-up examination, the PCR results were negative for B. canis and B. gibsoni. Several weeks later, the dog was presented again, and a PCR was positive for B. gibsoni. After atovaquone and azithromycin failed to eliminate the parasites, a therapy attempt using metronidazole, clindamycin and doxycycline was initiated. Six months after diagnosis, the treatment appeared successful in eliminating B. gibsoni. This case report describes the clinical findings of the co-infection and the initiated diagnostic and therapeutic approaches.

A Synthetic Peptide Designed to Neutralize Lipopolysaccharides Attenuates Metaflammation and Diet-Induced Metabolic Derangements in Mice.

Metabolic endotoxemia has been suggested to play a role in the pathophysiology of metaflammation, insulin-resistance and ultimately type-2 diabetes mellitus (T2DM). The role of endogenous antimicrobial peptides (AMPs), such as the cathelicidin LL-37, in T2DM is unknown. We report here for the first time that patients with T2DM compared to healthy volunteers have elevated plasma levels of LL-37. In a reverse-translational approach, we have investigated the effects of the AMP, peptide 19-2.5, in a murine model of high-fat diet (HFD)-induced insulin-resistance, steatohepatitis and T2DM. HFD-fed mice for 12 weeks caused obesity, an impairment in glycemic regulations, hypercholesterolemia, microalbuminuria and steatohepatitis, all of which were attenuated by Peptide 19-2.5. The liver steatosis caused by feeding mice a HFD resulted in the activation of nuclear factor kappa light chain enhancer of activated B cells (NF-ĸB) (phosphorylation of inhibitor of kappa beta kinase (IKK)α/ß, IκBα, translocation of p65 to the nucleus), expression of NF-ĸB-dependent protein inducible nitric oxide synthase (iNOS) and activation of the NOD-, LRR- and pyrin domain-containing protein 3 (NLRP3) inflammasome, all of which were reduced by Peptide 19-2.5. Feeding mice, a HFD also resulted in an enhanced expression of the lipid scavenger receptor cluster of differentiation 36 (CD36) secondary to activation of extracellular signal-regulated kinases (ERK)1/2, both of which were abolished by Peptide 19-2.5. Taken together, these results demonstrate that the AMP, Peptide 19-2.5 reduces insulin-resistance, steatohepatitis and proteinuria. These effects are, at least in part, due to prevention of the expression of CD36 and may provide further evidence for a role of metabolic endotoxemia in the pathogenesis of metaflammation and ultimately T2DM. The observed increase in the levels of the endogenous AMP LL-37 in patients with T2DM may serve to limit the severity of the disease.

Prognostic Value of Bioactive Adrenomedullin in Critically Ill Patients with COVID-19 in Germany: An Observational Cohort Study.

The coronavirus disease 2019 (COVID-19) pandemic has placed a significant burden on hospitals worldwide. Objective biomarkers for early risk stratification and clinical management are still lacking. The aim of this work was to determine whether bioactive adrenomedullin can assist in the risk stratification and clinical management of critically ill COVID-19 patients. Fifty-three patients with confirmed COVID-19 were included in this prospective observational cohort study between March and April 2020. Bioactive adrenomedullin (bio-ADM) plasma concentration was measured daily for seven days after admission. The prognostic value and clinical significance of bio-ADM plasma levels were evaluated for the severity of respiratory failure, the need for extracorporeal organ support and outcome (28-day mortality). Bio-ADM levels increased with the severity of acute respiratory distress syndrome (ARDS; p < 0.001) and were significantly elevated in invasively ventilated patients (p = 0.006) and patients in need of extracorporeal membrane oxygenation (p = 0.040) or renal replacement therapy (RRT; p < 0.001) compared to patients without these conditions. Non-survivors showed significantly higher bio-ADM levels than survivors (p = 0.010). Bio-ADM levels predicted 28-day mortality (C-index 0.72, 95% confidence interval 0.56-0.87, p < 0.001). Bio-ADM plasma levels correlate with disease severity, the need for extracorporeal organ assistance, and outcome, and highlight the promising value of bio-ADM in the early risk stratification and management of patients with COVID-19.