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Summary: Pediatric-type high-grade gliomas frequently harbor gene fusions involving receptor tyrosine kinase genes, including neurotrophic tyrosine kinase receptor (NTRK) fusions. Clinically, these tumors show high initial response rates to tyrosine kinase inhibition but ultimately recur due to the accumulation of additional resistance-conferring mutations. Here, we develop a series of genetically engineered mouse models of treatment-naive and -experienced NTRK1/2/3 fusion-driven gliomas. All tested NTRK fusions are oncogenic in vivo. The NTRK variant, N-terminal fusion partners, and resistance-associated point mutations all influence tumor histology and aggressiveness. Additional tumor suppressor losses greatly enhance tumor aggressiveness. Treatment with TRK kinase inhibitors significantly extends the survival of NTRK fusion-driven glioma mice, but fails to fully eradicate tumors, leading to recurrence upon treatment discontinuation. Finally, we show that ERK activation promotes resistance to TRK kinase inhibition and identify MEK inhibition as a potential combination therapy. These models will be invaluable tools to study therapy resistance of NTRK fusion tumors.

Abstract Microplastic (MP) particles can be ejected into the air by jet drops when gas bubbles burst at water surfaces. For a qualitative and quantitative understanding of this transport mechanism from the hydrosphere to the atmosphere, we studied the transfer of MP due to bubble bursting at the air–water interface in laboratory experiments. Gas bubbles were produced with filtered air that was pushed through a stainless-steel frit at two different volume flow rates in a glass flask filled with polystyrene (PS) particles of six different diameters (0.35 µm, 0.5 µm, 0.75 µm, 1 µm, 1.5 µm, 2 µm) suspended in deionized water. Airborne PS particle concentrations were measured by an optical particle counter. Additionally, size and volume of the bursting bubbles and the resulting jet droplets were analyzed with a camera. Depending on the volume flow rates, bubble bursting rates from 688 s−1 to 1176 s−1 and mean diameters of the bursting bubbles from 0.76 mm to 0.81 mm were observed. The mean diameters of the top jet drops were estimated to be between 0.10 mm and 0.11 mm. The measured number of jet droplets ranged from 2092 s−1 to 2391 s−1. For particle diameters from 0.35 µm – 2.0 µm, the airborne MP particle concentrations ranged from 4.2 l−1 to 348 l−1. We determined size-dependent transfer factors for the water–air transfer and found a maximum for 1 µm particles. For MP particles up to 1 µm diameter, the particle concentration in the jet droplets was enhanced compared to the bulk water concentration, indicating an enrichment of MP particles at the water–air-interface of bubbles.

In this report, we describe the successful resuscitation of a 4-year-old child who suffered a traumatic cardiac arrest during a routine procedure in the operating room. The diagnosis of a sanguineous pericardial tamponade was made by emergency ultrasonography. Consecutive subxiphoid pericardiocentesis with an adult Shaldon catheter led to return of spontaneous circulation. Subsequent thoracotomy and surgical suturing definitively stopped the bleeding from the right ventricle. The combined expertise of all perioperative disciplines was decisive for the patient's survival.

BackgroundThe prevalence of neurodegenerative diseases is increasing as is life expectancy with Alzheimer’s disease accounting for two-thirds of dementia cases globally. Whether general anesthesia and surgery worsen cognitive decline is still a matter of debate and most likely depending on the interplay of various influencing factors. In order to account for this complexity, Alzheimer’s disease animal models have been developed. The Tg2576 model of Alzheimer’s disease is a well-established mouse model exhibiting amyloidopathy and age-dependent sex-specific differences in Alzheimer’s disease symptomology. Yet, data on anesthesia in this mouse model is scarce and a systematic comparison of vital parameters during anesthesia with wild-type animals is missing. In order to investigate the safety of general anesthesia and changes in vital parameters during general anesthesia in Tg2576 mice, we did a secondary analysis of vital parameters collected during general anesthesia in aged Tg2576 mice.MethodsAfter governmental approval (General Administration of the Free State of Bavaria, file number: 55.2-1-54-2532-149-11) 60 mice at 10-12 months of age were exposed to isoflurane (1.6 Vol%) for 120 min, data of 58 mice was analyzed. During general anesthesia, heart rate, respiratory rate, temperature, isoflurane concentration and fraction of inspired oxygen were monitored and collected. Data were analyzed using univariate and multivariate linear mixed regression models.ResultsDuring general anesthesia, heart rate decreased in a sex-specific manner. Respiratory rate decreased and body temperature increased dependent on genotype. However, the changes were limited and all vital parameters stayed within physiological limits.ConclusionIsoflurane anesthesia in the Tg2576 mouse model is safe and does not seem to influence experimental results by interacting with vital parameters. The present study provides information on appropriate anesthesia in order to advance research on anesthesia and AD and could contribute to improving laboratory animal welfare.

Abstract Background Prehospital care of psychiatric patients often relies on the medical experience of prehospital emergency physicians (PHEPs). The psychiatrists (PSs) involved in the further treatment of psychiatric patients also often rely on their experience. Furthermore, the interaction between PHEPs and PSs is characterized by interaction problems and different approaches in the prehospital care of the psychiatric emergency. Objectives To analyze the phenomenon of “medical experience” as a cause of possible interaction-related problems and assess its impact on the prehospital decision-making process between prehospital emergency physicians and psychiatrists. Methods The retrospective data analysis was conducted between November 2022 and March 2023. Medical experience was defined as follows, based on the demographic information collected in the questionnaires: For PHEPs, the period since obtaining the additional qualification in emergency medicine was defined as a surrogate marker of medical experience: (i) inexperienced: < 1 year, (ii) experienced: 1–5 years, (iii) very experienced: > 5 years. For PSs, age in years was used as a surrogate parameter of medical experience: (i) inexperienced: 25–35 years, (ii) experienced: 35–45 years, (iii) very experienced: > 45 years. Results Inexperienced PSs most frequently expressed anxiety about the psychiatric emergency referred by a PHEP (27.9%). Experienced PHEPs most frequently reported a lack of qualifications in handling the care of psychiatric emergencies (p = 0.002). Very experienced PHEPs were significantly more likely to have a referral refused by the acute psychiatric hospital if an inexperienced PS was on duty (p = 0.01). Experienced PHEPs apply an intravenous hypnotic significantly more often (almost 15%) than PSs of all experience levels (p = 0.001). In addition, very experienced PHEPs sought prehospital phone contact with acute psychiatry significantly more often (p = 0.01). Conclusion PHEPs should be aware that the PS on duty may be inexperienced and that treating emergency patients may cause him/her anxiety. On the other hand, PHEPs should be receptive to feedback from PS who have identified a qualification deficiency in them. Jointly developed, individualized emergency plans could lead to better prehospital care for psychiatric emergency patients. Further training in the prehospital management of psychiatric disorders is needed to minimize the existing skills gap among PHEPs in the management of psychiatric disorders.

Immature platelets are newly formed platelets with an increased prothrombotic potential. This study evaluates whether immature platelets are associated with relevant complications in neurosurgical patients. Data were obtained in the frame of a prospectively conducted observational study exploring the association between immature platelets and major cardiovascular events after surgery. Immature platelet fraction (IPF) and H-IPF (highly fluorescent immature platelet fraction) were measured preoperatively and postoperatively at the neurosurgical ward (24–72 hours after surgery). Therapy-relevant complications after surgery were stratified using the Clavien-Dindo Grade (CDG >2) as primary outcome. Data were analyzed in 391 neurosurgical patients. While preoperatively there were no differences in IPF or H-IPF, patients with higher therapy-complication grades had higher values post-op compared to patients with lower grade complications (≤2 CDG). Cut-off values identified by receiver operating characteristic curve analysis revealed that there were significantly more patients with H-IPF ≥0.95% in the group with serious complications (CDG >2) [odds ratio OR (95% confidence interval CI) = 2.06 (1.09–3.9), p = .025], whereas this association was not present for the IPF cutoff value. In a multivariate model, H-IPF≥0.95% was independently associated with serious complications after surgery [OR (95% CI) = 1.97 (1.03–3.78), p = .041]. These findings suggest that H-IPF is associated with surgical complications and may improve risk stratification of neurosurgical patients (clinicaltrials.gov: NCT02097602, registration date: 27/03/2014).

Objectives Postoperative monitoring outside intensive and post-anaesthesia care units is seldom, partly due to lack of suitable and approved systems. We therefore aim to validate the oxygen saturation (SpO 2 ) and pulse rate measurement of the in-ear sensor c-med° alpha with a reference pulse oximeter. Methods This prospective agreement study was conducted in 12 healthy (ASA 1) adult (18–50 years) volunteers according to the EN ISO 80601-2-61. The sitting volunteers were equipped with the finger pulse oximeter Rad-5 and two c-med° alpha sensors in each ear. The inspiratory oxygen content was reduced via a tight-fitting breathing mask to achieve five defined plateaus with stable SpO 2 between 99% and 70%. The deviation of the SpO 2 and pulse rate measurements of the c-med° alpha from those of the Rad-5 was calculated using the mean square error (A rms ). Bias and limits of agreement between both devices were calculated using the Bland-Altman technique. The precision was compared based on the repeatability coefficients. Results The c-med° alpha measured SpO 2 had an A rms = 1.9% relative to the Rad-5, a non-significant bias (−0.1% (-0.2% to 0.0%)), levels of agreement from −4.0% to 3.8%, and the same repeatability coefficient (0.8% vs. 0.8%). The c-med° alpha measured pulse rate did not deviate from the one measured with the certified finger pulse oximeter (bias: 0.1 min −1 (0 to 0.1 min −1 ), level of agreement: −3.6 to 3.7 min −1 , A rms : 1.8 min −1 ). Conclusions The c-med° alpha fulfils the EN ISO 80601-2-61 standard and is sufficiently accurate for measuring SpO 2 and pulse rate in healthy adults at rest. Trial registration EUDAMED No. CIV-21-03-036033

Human malignant brain tumors such as gliomas are devastating due to the induction of cerebral edema and neurodegeneration. A major contributor to glioma-induced neurodegeneration has been identified as glutamate. Glutamate promotes cell growth and proliferation in variety of tumor types. Intriguently, glutamate is also an excitatory neurotransmitter and evokes neuronal cell death at high concentrations. Even though glutamate signaling at the receptor and its downstream effectors has been extensively investigated at the molecular level, there has been little insight into how glutamate enters the tumor microenvironment and impacts on metabolic equilibration until recently. Surprisingly, the 12 transmembrane spanning tranporter xCT (SLC7A11) appeared to be a major player in this process, mediating glutamate secretion and ferroptosis. Also, PPARγ is associated with ferroptosis in neurodegeneration, thereby destroying neurons and causing brain swelling. Although these data are intriguing, tumor-associated edema has so far been quoted as of vasogenic origin. Hence, glutamate and PPARγ biology in the process of glioma-induced brain swelling is conceptually challenging. By inhibiting xCT transporter or AMPA receptors in vivo, brain swelling and peritumoral alterations can be mitigated. This review sheds light on the role of glutamate in brain tumors presenting the conceptual challenge that xCT disruption causes ferroptosis activation in malignant brain tumors. Thus, interfering with glutamate takes center stage in forming the basis of a metabolic equilibration approach.

Background and goal of studyCardiopulmonary resuscitation (CPR) in prehospital care is a major reason for emergency medical service (EMS) dispatches. CPR outcome depends on various factors, such as bystander CPR and initial heart rhythm. Our aim was to investigate whether short-term outcomes such as the return of spontaneous circulation (ROSC) and hospital admission with spontaneous circulation differ depending on the location of the out-of-hospital cardiac arrest (OHCA). In addition, we assessed further aspects of CPR performance.Materials and methodsIn this monocentric retrospective study, protocols of a prehospital physician-staffed EMS located in Munich, Germany, were evaluated using the Mann–Whitney U-test, chi-square test, and a multifactor logistic regression model.Results and discussionOf the 12,073 cases between 1 January 2014 and 31 December 2017, 723 EMS responses with OHCA were analyzed. In 393 of these cases, CPR was performed. The incidence of ROSC did not differ between public and non-public spaces (p = 0.4), but patients with OHCA in public spaces were more often admitted to the hospital with spontaneous circulation (p = 0.011). Shockable initial rhythm was not different between locations (p = 0.2), but defibrillation was performed significantly more often in public places (p

BackgroundPatients with Alzheimer’s disease show a sex-dependent decline of cognitive and behavioral performance. It is controversially discussed whether general anesthesia itself can aggravate or even cause this neurocognitive decline. Therefore, we investigated the effect of general anesthesia on neurocognitive and behavioral function and amyloidopathy in a mouse model of early-stage Alzheimer’s disease with respect to sex.MethodsAfter governmental approval 10 months old Tg2576 mice and wild type (total 85 mice) either underwent general anesthesia with 1.0 minimal alveolar concentration of isoflurane for 2 h or were not exposed to isoflurane (controls). Following cognitive and behavioral testing using the modified hole board test (mHBT), brains were investigated regarding amyloidopathy, inflammation, and apoptosis. Data were analyzed using repeated measure analysis of variance (ANOVA) and univariate analysis of variance (UNIANOVA).ResultsTg2576 mice showed a decline in memory function (p < 0.001), less anxiety (p = 0.022 and p = 0.024), increased locomotor activity (p = 0.025), and impaired fine motor skills (p < 0.001). Amyloid precursor protein (p < 0.001), soluble amyloid-beta (p < 0.001) and insoluble amyloid deposits (p < 0.001) were increased in Tg2576 animals. Neither sex nor exposure to isoflurane had an effect on cognitive or behavioral testing or expression of amyloid-related biomarkers.Discussion and conclusionWe found that 10 months old Tg2576 showed typical signs of early-stage Alzheimer’s disease and corresponding histopathological alterations. Relevant sex-specific differences or an effect of isoflurane anesthesia could not be detected at this early stage of the disease.

BackgroundPost-operative delirium is common in elderly patients and associated with increased morbidity and mortality. We evaluated in this pilot study whether a perioperative goal-directed hemodynamic optimization algorithm improves cerebral oxygenation and can reduce the incidence of delirium.Materials and MethodsPatients older than 70 years with high risk for post-operative delirium undergoing elective non-cardiac surgery were randomized to an intervention or control group. Patients in the intervention group received a perioperative hemodynamic optimization protocol based on uncalibrated pulse-contour analysis. Patients in the control group were managed according to usual standard of care. Incidence of delirium until day seven was assessed with confusion assessment method (CAM) and chart review. Cerebral oxygenation was measured with near-infrared spectroscopy.ResultsDelirium was present in 13 of 85 (15%) patients in the intervention group and 18 of 87 (21%) in the control group [risk difference −5.4%; 95% confidence interval, −16.8 to 6.1%; P = 0.47]. Intervention did not influence length of stay in hospital or in-hospital mortality. Amounts of fluids and vasopressors applied, mean arterial pressure, cardiac index, and near-infrared spectroscopy values were comparable between groups.ConclusionThe hemodynamic algorithm applied in high-risk non-cardiac surgery patients did not change hemodynamic interventions, did not improve patient hemodynamics, and failed to increase cerebral oxygenation. An effect on the incidence of post-operative delirium could not be observed.Clinical Trial Registration[Clinicaltrials.gov], identifier [NCT01827501].

Abstract Background Hypalbuminemia is associated with numerous postoperative complications, so a perioperative albumin substitution is often considered. The objective of SuperAdd is to investigate whether substitution of human albumin, aiming to maintain a serum concentration > 30 g/l, can reduce postoperative complications in normovolemic surgical patients in comparison with standard care. Methods/design SuperAdd is a single-center, prospective, randomized, outcome-assessor blinded, patient blinded controlled trial. The primary outcome is the frequency of postoperative complications identified using the Postoperative Morbidity Survey graded ≥ 2 according to the Clavien-Dindo Score. Adult patients at risk to develop hypalbuminemia, i.e., ASA III or IV or high-risk surgery, are recruited after written informed consent was obtained. The albumin concentration is assessed before the induction of anesthesia and every 3 h until admission to the postanesthesia care unit. If albumin concentrations drop below 30 g/l, patients are randomly allocated to the control or the treatment group. The study intervention is a goal-directed human albumin substitution aimed at a concentration > 30 g/l during surgery and postanesthesia care unit stay. The patients in the control group are treated according to standard clinical care. Postoperative visits are to be performed on days 1, 3, 5, 8, and 15, as well as by telephone 6 months after surgery. Discussion SuperAdd is the first clinical trial in a surgical population investigating the effect of a goal-directed albumin substitution aiming at a serum level > 30 g/l. The nonrestrictive selection of patients guarantees that the patients without albumin screening will most likely not develop hypalbuminemia, thus ensuring generalizability of the study results. Trial registration EudraCT 2016-001313-24. Registered on 5 September 2016. Clinical Trials NCT03167645. Registered on 18 October 2016 and has the Universal Trial Number (UTN) U1111-1181-2625.

Abstract Background Postoperative delirium may manifest in the immediate post-anaesthesia care period. Such episodes appear to be predictive of further episodes of inpatient delirium and associated adverse outcomes. Frontal electroencephalogram (EEG) findings of suppression patterns and low proprietary index values have been associated with postoperative delirium and poor outcomes. However, the efficacy of titrating anaesthesia to proprietary index targets for preventing delirium remains contentious. We aim to assess the efficacy of two strategies which we hypothesise could prevent post-anaesthesia care unit (PACU) delirium by maximising the alpha oscillation observed in frontal EEG channels during the maintenance and emergence phases of anaesthesia. Methods This is a 2 × 2 factorial, double-blind, stratified, randomised control trial of 600 patients. Eligible patients are those aged 60 years or over who are undergoing non-cardiac, non-intracranial, volatile-based anaesthesia of expected duration of more than 2 h. Patients will be stratified by pre-operative cognitive status, surgery type and site. For the maintenance phase of anaesthesia, patients will be randomised (1:1) to an alpha power-maximisation anaesthesia titration strategy versus standard care avoiding suppression patterns in the EEG. For the emergence phase of anaesthesia, patients will be randomised (1:1) to early cessation of volatile anaesthesia and emergence from an intravenous infusion of propofol versus standard emergence from volatile anaesthesia only. The primary study outcomes are the power of the frontal alpha oscillation during the maintenance and emergence phases of anaesthesia. Our main clinical outcome of interest is PACU delirium. Discussion This is a largely exploratory study; the extent to which EEG signatures can be modified by titration of pharmacological agents is not known. The underlying concept is maximisation of anaesthetic efficacy by individualised drug titration to a clearly defined EEG feature. The interventions are already clinically used strategies in anaesthetic practice, but have not been formally evaluated. The addition of propofol during the emergence phase of volatile-based general anaesthesia is known to reduce emergence delirium in children; however, the efficacy of this strategy in older patients is not known. Trial registration Australian and New Zealand Clinical Trial Registry, ID: 12617001354370. Registered on 27/09/2017.

BackgroundThe aim of this study was to assess different amyloid beta subspecies' effects on behaviour and cognition in mice and their interaction with isoflurane anaesthesia.MethodsAfter governmental approval, cannulas were implanted in the lateral cerebral ventricle. After 14 days the mice were randomly intracerebroventricularly injected with Aβ 1-40 (Aβ40), Aβ 1-42 (Aβ42), 3NTyr10-Aβ (Aβ nitro), AβpE3-42 (Aβ pyro), or phosphate buffered saline. Four days after the injection, 30 mice (6 animals per subgroup) underwent general anaesthesia with isoflurane. A "sham" anaesthetic procedure was performed in another 30 mice (6 animals per subgroup, 10 subgroups in total). During the next eight consecutive days a blinded assessor evaluated behavioural and cognitive performance using the modified hole-board test. Following the testing we investigated 2 brains per subgroup for insoluble amyloid deposits using methoxy staining. We used western blotting in 4 brains per subgroup for analysis of tumour-necrosis factor alpha, caspase 3, glutamate receptors NR2B, and mGlu5. Data were analysed using general linear modelling and analysis of variance.ResultsAβ pyro improved overall cognitive performance (p = 0.038). This cognitive improvement was reversed by isoflurane anaesthesia (p = 0.007), presumably mediated by decreased exploratory behaviour (p = 0.022 and p = 0.037). Injection of Aβ42 was associated with increased anxiety (p = 0.079). Explorative analysis on a limited number of brains did not reveal insoluble amyloid deposits or differences in the expression of tumour-necrosis factor alpha, NR2B, mGlu5, or caspase 3.ConclusionsTesting cognitive performance after intracerebroventricular injection of different amyloid beta subspecies revealed that Aβ pyro might be less harmful, which was reversed by isoflurane anaesthesia. There is minor evidence for Aβ42-mediated neurotoxicity. Preliminary molecular analysis of biomarkers did not clarify pathophysiological mechanisms.

The neuronal mechanisms how anesthetics lead to loss of consciousness are unclear. Thalamocortical interactions are crucially involved in conscious perception; hence the thalamocortical network might be a promising target for anesthetic modulation of neuronal information pertaining to arousal and waking behavior. General anesthetics affect the neurophysiology of the thalamus and the cortex but the exact mechanisms of how anesthetics interfere with processing thalamocortical information remain to be elucidated. Here we investigated the effect of the anesthetic agents sevoflurane and propofol on thalamocortical network activity in vitro. We used voltage-sensitive dye imaging techniques to analyze the cortical depolarization in response to stimulation of the thalamic ventrobasal nucleus in brain slices from mice. Exposure to sevoflurane globally decreased cortical depolarization in a dose-dependent manner. Sevoflurane reduced the intensity and extent of cortical depolarization and delayed thalamocortical signal propagation. In contrast, propofol neither affected area nor amplitude of cortical depolarization. However, propofol exposure resulted in regional changes in spatial distribution of maximum fluorescence intensity in deep regions of the cortex. In summary, our experiments revealed substance-specific effects on the thalamocortical network. Functional changes of the neuronal network are known to be pivotally involved in the anesthetic-induced loss of consciousness. Our findings provide further evidence that the mechanisms of anesthetic-mediated loss of consciousness are drug- and pathway-specific.

The aim of the study was to explore the possible role of Trefoil Factor Family peptide 3 (TFF3) for skeletal repair. The expression of TFF3 was analyzed in human joint tissues as well as in a murine bone fracture model. Serum levels of TFF3 following a defined skeletal trauma in humans were determined by ELISA. The mRNA expression of TFF3 was analyzed under normoxia and hypoxia. Expression analysis after stimulation of human mesenchymal progenitor cells (MPCs) with TFF3 was performed by RT2 Profiler PCR Array. The effect of recombinant human (rh)TFF3 on MPCs was analysed by different migration and chemotaxis assays. The effect on cell motility was also visualized by fluorescence staining of F-Actin. TFF3 was absent in human articular cartilage, but strongly expressed in the subchondral bone and periosteum of adult joints. Strong TFF3 immunoreactivity was also detected in murine fracture callus. Serum levels of TFF3 were significantly increased after skeletal trauma in humans. Expression analysis demonstrated that rhTFF3 significantly decreased mRNA of ROCK1. Wound healing assays showed increased cell migration of MPCs by rhTFF3. The F-Actin cytoskeleton was markedly influenced by rhTFF3. Cell proliferation was not increased by rhTFF3. The data demonstrate elevated expression of TFF3 after skeletal trauma. The stimulatory effects on cell motility and migration of MPCs suggest a role of TFF3 in skeletal repair.

Acute kidney injury (AKI) is common in critically ill patients. AKI requires renal replacement therapy (RRT) in up to 10% of patients. Particularly during connection and fluid removal, RRT frequently impairs haemodyamics which impedes recovery from AKI. Therefore, "acute" connection with prefilled tubing and prolonged periods of RRT including sustained low efficiency dialysis (SLED) has been suggested. Furthermore, advanced haemodynamic monitoring using trans-pulmonary thermodilution (TPTD) and pulse contour analysis (PCA) might help to define appropriate fluid removal goals.Since data on TPTD to guide RRT are scarce, we investigated the capabilities of TPTD- and PCA-derived parameters to predict feasibility of fluid removal in 51 SLED-sessions (Genius; Fresenius, Germany; blood-flow 150 mL/min) in 32 patients with PiCCO-monitoring (Pulsion Medical Systems, Germany). Furthermore, we sought to validate the reliability of TPTD during RRT and investigated the impact of "acute" connection and of disconnection with re-transfusion on haemodynamics. TPTDs were performed immediately before and after connection as well as disconnection.Comparison of cardiac index derived from TPTD (CItd) and PCA (CIpc) before, during and after RRT did not give hints for confounding of TPTD by ongoing RRT. Connection to RRT did not result in relevant changes in haemodynamic parameters including CItd. However, disconnection with re-transfusion of the tubing volume resulted in significant increases in CItd, CIpc, CVP, global end-diastolic volume index GEDVI and cardiac power index CPI. Feasibility of the pre-defined ultrafiltration goal without increasing catecholamines by >10% (primary endpoint) was significantly predicted by baseline CPI (ROC-AUC 0.712; p = 0.010) and CItd (ROC-AUC 0.662; p = 0.049).TPTD is feasible during SLED. "Acute" connection does not substantially impair haemodynamics. Disconnection with re-transfusion increases preload, CI and CPI. The extent of these changes might be used as a "post-RRT volume change" to guide fluid removal during subsequent RRTs. CPI is the most useful marker to guide fluid removal by SLED.

Previous studies have focused on postoperative anaesthetic visit as a tool for measuring postoperative recovery or patient's satisfaction. Whether it could also improve timely recognition of complications has not been studied yet. Aim of our study was to assess pathological findings in physical examination requiring further intervention during postoperative visit and to explore whether a self-administered version of the Quality of Recovery (QoR)-9 score, compared to a detailed medical history, can act as a screening tool for identification of patients who show a low risk to develop postoperative complications. This observational study included 918 patients recovering from various types of non-cardiac surgery and anaesthesia. The postoperative visit implied three steps: measuring the QoR-9 score, a structured medical history and a physical examination. QoR-9-score showed a comparable negative predictive value (0.93 vs. 0.92) and a higher sensitivity of finding at least one pathological examination than a detailed medical history (0.92 vs. 0.81 respectively). At least one postoperative pathological examination finding was observed in 23.7% of the patients. Our approach presents a strategy on screening postoperative patients in order to identify patients whose examination and consequent treatment should be intensified. In further studies the question could be addressed whether the postoperative visit may help to reduce complications and mortality after surgery.

Abstract While different stages of mutualism can be observed in natural communities, the dynamics and mechanisms underlying the gradual erosion of independence of the initially autonomous organisms are not yet fully understood. In this study, by conducting the laboratory evolution on an engineered microbial community, we reproduce and molecularly track the stepwise progression towards enhanced partner entanglement. We observe that the evolution of the community both strengthens the existing metabolic interactions and leads to the emergence of de novo interdependence between partners for nitrogen metabolism, which is a common feature of natural symbiotic interactions. Selection for enhanced metabolic entanglement during the community evolution repeatedly occurred indirectly, via pleiotropies and trade-offs within cellular regulatory networks, and with no evidence of group selection. The indirect positive selection of metabolic dependencies between microbial community members, which results from the direct selection of other coupled traits in the same regulatory network, may therefore be a common but underappreciated driving force guiding the evolution of natural mutualistic communities.

Abstract enviPath is a widely used database and prediction system for microbial biotransformation pathways of primarily xenobiotic compounds. Data and prediction system are freely available both via a web interface and a public REST API. Since its initial release in 2016, we extended the data available in enviPath and improved the performance of the prediction system and usability of the overall system. We now provide three diverse data sets, covering microbial biotransformation in different environments and under different experimental conditions. This also enabled developing a pathway prediction model that is applicable to a more diverse set of chemicals. In the prediction engine, we implemented a new evaluation tailored towards pathway prediction, which returns a more honest and holistic view on the performance. We also implemented a novel applicability domain algorithm, which allows the user to estimate how well the model will perform on their data. Finally, we improved the implementation to speed up the overall system and provide new functionality via a plugin system. Scientific contribution The main scientific contributions are the development of a pathway prediction model applicable to diverse chemicals, a specialized evaluation method for holistic performance assessment, and a novel applicability domain algorithm for user-specific performance estimation. The introduction of two new data sets, and the creation of links to EC classes make enviPath a unique resource in microbial biotransformation research.

While many digital technologies provide opportunities for creating business models that impact sustainability, some technologies, especially blockchain applications, are often criticized for harming the environment, e.g. due to high energy demand. In our study, we present a novel approach to identifying sustainability-focused blockchain companies and relate their level of engagement to location factors and entrepreneurial ecosystem embeddedness. For this, we use a large-scale web scraping approach to analyze the textual content and hyperlink networks of all US companies from their websites. Our results show that blockchain remains a niche technology, with its use communicated by about 0.6% of US companies. However, the proportion of blockchain companies that are committed to sustainability is significantly higher than in the overall firm population. Additionally, we find that such sustainability-engaged blockchain companies have, at least quantitatively, a more intensive embedding in entrepreneurial ecosystems, while infrastructural and socio-economic location factors hardly play a role.

This study presents a new approach for predicting forest aboveground biomass (AGB) from airborne laser scanning (ALS) data: AGB is predicted from sequences of images depicting vertical cross-sections through the ALS point clouds. A 3D version of the VGG16 convolutional neural network (CNN) with initial weights transferred from pre-training on the ImageNet dataset was used. The approach was tested on datasets from Canada, Poland, and the Czech Republic. To analyse the effect of training sample size on model performance, different-sized samples ranging from 10 to 375 ground plots were used. The CNNs were compared with random forest models (RFs) trained on point cloud metrics. At the maximum number of training samples, the difference in RMSE between observed and predicted AGB of CNNs and RFs ranged from −2 t/ha to 5 t/ha, and the difference in squared Pearson correlation coefficient ranged from −0.05 to 0.06. Additional pre-training on synthetic data derived from virtual laser scanning of simulated forest stands could only improve the prediction performance of the CNNs when only a few real training samples (10–40) were available. While 3D CNNs trained on cross-section images derived from real data showed promising results, RFs remain a competitive alternative.

Abstract Classifications of forest vegetation types and characterization of related species assemblages are important analytical tools for mapping and diversity monitoring of forest communities. The discrimination of forest communities is often based on β‐diversity, which can be quantified via numerous indices to derive compositional dissimilarity between samples. This study aims to evaluate the applicability of unsupervised classification for National Forest Inventory data from Georgia by comparing two cluster hierarchies. We calculated the mean basal area per hectare for each woody species across 1059 plot observations and quantified interspecies distances for all 87 species. Following an unspuervised cluster analysis, we compared the results derived from the species‐neutral dissimilarity (Bray‐Curtis) with those based on the Discriminating Avalanche dissimilarity, which incorporates interspecies phylogenetic variation. Incorporating genetic variation in the dissimilarity quantification resulted in a more nuanced discrimination of woody species assemblages and increased cluster coherence. Favorable statistics include the total number of clusters (23 vs. 20), mean distance within clusters (0.773 vs. 0.343), and within sum of squares (344.13 vs. 112.92). Clusters derived from dissimilarities that account for genetic variation showed a more robust alignment with biogeographical units, such as elevation and known habitats. We demonstrate that the applicability of unsupervised classification of species assemblages to large‐scale forest inventory data strongly depends on the underlying quantification of dissimilarity. Our results indicate that by incorporating phylogenetic variation, a more precise classification aligned with biogeographic units is attained. This supports the concept that the genetic signal of species assemblages reflects biogeographical patterns and facilitates more precise analyses for mapping, monitoring, and management of forest diversity.

Transportation tasks in nursing are common, often overlooked, and directly impact patient care time in the context of staff shortages and an aging society. Current studies lack a specific focus on transportation tasks, a gap our research aims to fill. By providing detailed data on transportation needs in nursing, our study establishes a crucial foundation for the development and integration of assistive robots in clinical settings. In July and September 2023, we conducted weekly observations of nurses to assess clinical transportation needs. We aim to understand the economic impact and the methods nurses use for transportation tasks. We conducted a participant observation using a standardized app-based form over a seven-day observation period in two rural clinics. N = 1830 transports were made by nurses and examined by descriptive analysis. Non-medical supplies account for 27.05% (n = 495) of all transports, followed by medical supplies at 17.32% (n = 317), pharmacotherapy at 14.10% (n = 258) and other other categories like meals or drinks contributing 12.68% (n = 232). Most transports had a factual transport time of under a minute, with patient transport and lab samples displaying more variability. In total, 77.15% of all transports were made by hand. Requirements to collect items or connect transports with patient care were included in 5% of all transports. Our economic evaluation highlighted meals as the most costly transport, with 9596.16 € per year in the observed clinics. Budget-friendly robots would amortize these costs over one year by transporting meals. We support understanding nurses’ transportation needs via further research on assistive robots to validate our findings and determine the feasibility of transport robots.

The widespread use of mobile phones and social media platforms provides valuable information about users’ behavior and activities. Mobile phone data are rich on positional information, but lack semantic context. Conversely, geo-social media data reveal users’ opinions and activities, but are rather sparse in space and time. In the context of emergency management, both data types have been considered separately. To exploit their complementary nature and potential for emergency management, this paper introduces a novel methodology for improving situational awareness with the focus on urban events. For crowd detection, a spatial hot spot analysis of mobile phone data is used. The analysis of geo-social media data involves building spatio-temporal topic-sentiment clusters of posts. The results of the spatio-temporal contextual enrichment include unusual crowds associated with topics and sentiments derived from the analyzed geo-social media data. This methodology is demonstrated using the case study of the Vienna Pride. The results show how crowds change over time in terms of their location, size, topics discussed, and sentiments.

A key pathological feature of Parkinson’s Disease (PD) is the progressive degeneration of dopaminergic neurons (DAns) in the substantia nigra pars compacta. Considering the major role of EN1 in the development and maintenance of these DAns and the implications from En1 mouse models, it is highly interesting to study the molecular and protective effect of EN1 also in a human cellular model. Therefore, we generated EN1 knock-out (ko) human induced pluripotent stem cell (hiPSCs) lines and analyzed these during neuronal differentiation. Although the EN1 ko didn’t interfere with neuronal differentiation and generation of tyrosine hydroxylase positive (TH+) neurons per se, the neurons exhibited shorter neurites. Furthermore, mitochondrial respiration, as well as mitochondrial complex I abundance was significantly reduced in fully differentiated neurons. To understand the implications of an EN1 ko during differentiation, we performed a transcriptome analysis of human neuronal precursor cells (hNPCs) which unveiled alterations in cilia-associated pathways. Further analysis of ciliary morphology revealed an elongation of primary cilia in EN1-deficient hNPCs. Besides, also Wnt signaling pathways were severely affected. Upon stimulating hNPCs with Wnt which drastically increased EN1 expression in WT lines, the phenotypes concerning mitochondrial function and cilia were exacerbated in EN1 ko hNPCs. They failed to enhance the expression of the complex I subunits NDUFS1 and 3, and now displayed a reduced mitochondrial respiration. Furthermore, Wnt stimulation decreased ciliogenesis in EN1 ko hNPCs but increased ciliary length even further. This further highlights the relevance of primary cilia next to mitochondria for the functionality and correct maintenance of human DAns and provides new possibilities to establish neuroprotective therapies for PD.

Abstract Sporadic Parkinson’s Disease (sPD) is a progressive neurodegenerative disorder caused by multiple genetic and environmental factors. Mitochondrial dysfunction is one contributing factor, but its role at different stages of disease progression is not fully understood. Here, we showed that neural precursor cells and dopaminergic neurons derived from induced pluripotent stem cells (hiPSCs) from sPD patients exhibited a hypometabolism. Further analysis based on transcriptomics, proteomics, and metabolomics identified the citric acid cycle, specifically the α-ketoglutarate dehydrogenase complex (OGDHC), as bottleneck in sPD metabolism. A follow-up study of the patients approximately 10 years after initial biopsy demonstrated a correlation between OGDHC activity in our cellular model and the disease progression. In addition, the alterations in cellular metabolism observed in our cellular model were restored by interfering with the enhanced SHH signal transduction in sPD. Thus, inhibiting overactive SHH signaling may have potential as neuroprotective therapy during early stages of sPD.

Abstract A fundamental operation in computational genomics is to reduce the input sequences to their constituent k-mers. For maximum performance of downstream applications it is important to store the k-mers in small space, while keeping the representation easy and efficient to use (i.e. without k-mer repetitions and in plain text). Recently, heuristics were presented to compute a near-minimum such representation. We present an algorithm to compute a minimum representation in optimal (linear) time and use it to evaluate the existing heuristics. Our algorithm first constructs the de Bruijn graph in linear time and then uses a Eulerian-cycle-based algorithm to compute the minimum representation, in time linear in the size of the output.

Abstract We propose a polynomial algorithm computing a minimum plain-text representation of k-mer sets, as well as an efficient near-minimum greedy heuristic. When compressing read sets of large model organisms or bacterial pangenomes, with only a minor runtime increase, we shrink the representation by up to 59% over unitigs and 26% over previous work. Additionally, the number of strings is decreased by up to 97% over unitigs and 90% over previous work. Finally, a small representation has advantages in downstream applications, as it speeds up SSHash-Lite queries by up to 4.26× over unitigs and 2.10× over previous work.

In the early stages of a disaster caused by a natural hazard (e.g., flood), the amount of available and useful information is low. To fill this informational gap, emergency responders are increasingly using data from geo-social media to gain insights from eyewitnesses to build a better understanding of the situation and design effective responses. However, filtering relevant content for this purpose poses a challenge. This work thus presents a comparison of different machine learning models (Naïve Bayes, Random Forest, Support Vector Machine, Convolutional Neural Networks, BERT) for semantic relevance classification of flood-related, German-language Tweets. For this, we relied on a four-category training data set created with the help of experts from human aid organisations. We identified fine-tuned BERT as the most suitable model, averaging a precision of 71% with most of the misclassifications occurring across similar classes. We thus demonstrate that our methodology helps in identifying relevant information for more efficient disaster management.

Summary: Background: Treatment with elexacaftor/tezacaftor/ivacaftor (ETI) improves multiple clinical outcomes in people with cystic fibrosis (pwCF) with at least one F508del allele. This study evaluated the real-world impact of ETI on lung function, nutritional status, pulmonary exacerbation frequency, and sweat chloride concentrations in a large group of pwCF. Methods: This observational cohort study used data from the German CF Registry for pwCF who received ETI therapy and were followed up for a period of 12 months. Findings: The study included 2645 pwCF from 67 centres in Germany (mean age 28.0 ± 11.5 years). Over the first year after ETI was initiated, percent predicted forced expiratory volume in 1 s (ppFEV1) increased by 11.3% (95% confidence interval [CI] 10.8–11.8, p

Abstract Background The disease burden of musculoskeletal disorders necessitates multidisciplinary and patient-centered models of care. Exercise therapy represents a first-line treatment strategy and a central component of medical rehabilitation. In order to realize the goals of long-term physical activity and participation as proposed by the ICF, exercise therapy can be supplemented by interventional techniques from the field of psychotherapy. Although psychotherapist feedback has been shown to improve therapeutic outcome and patient satisfaction, feedback use in exercise therapy is mostly limited to motor learning and exercise instruction. The present paper therefore describes the use of multidimensional exercise therapy feedback in medical rehabilitation. The aims of the trial presented in this study protocol are to evaluate the effects of this novel feedback approach on rehabilitation outcomes in comparison to usual care. Methods The study is designed as a prospective, mono-centric, randomized controlled, superiority trial (RCT) with two parallel groups and three measuring points: T0 = start of three-week inpatient rehabilitation, T1 = end of three-week inpatient rehabilitation, T2 = 12-week follow-up. In total, 132 patients suffering from chronic neck, shoulder and/or lumbar spine disorders will be recruited. The intervention involves multidimensional exercise therapy feedbacks during the initial and final physical therapist examination, as well as short exercise therapy feedbacks during the course units of the mandatory group-based exercise therapy program. Primary outcomes are the subjective treatment outcome, assessed by BPI and indication-specific questionnaires, as well as patient satisfaction, assessed by ZUF-8 and an intervention-specific questionnaire. The final data collection is expected by May 2023. Discussion This study may provide a valuable insight into the effectiveness of multidimensional exercise therapy feedback to improve treatment outcomes and patient satisfaction in medical rehabilitation. This could contribute to rehabilitation quality assurance and the long-term physical activity behavior of rehabilitation patients. Trial registration The trial has been registered with the German Clinical Trial Register (DRKS) under the Registration Number DRKS00027263.

Abstract Background Explainable artificial intelligence (XAI) methods have shown increasing applicability in chemistry. In this context, visualization techniques can highlight regions of a molecule to reveal their influence over a predicted property. For this purpose, some XAI techniques calculate attribution scores associated with tokens of SMILES strings or with atoms of a molecule. While an association of a score with an atom can be directly visually represented on a molecule diagram, scores computed for SMILES non-atom tokens cannot. For instance, a substring [N+] contains 3 non-atom tokens, i.e., [, $$+$$ + , and ], and their attributions, depending on the model, are not necessarily revealing an influence of the nitrogen atom over the predicted property; for that reason, it is not possible to represent the scores on a molecule diagram. Moreover, SMILES’s notation is complex, foregrounding the need for techniques to facilitate the analysis of explanations associated with their tokens. Results We propose XSMILES, an interactive visualization technique, to explore explainable artificial intelligence attributions scores and support the interpretation of SMILES. Users can input any type of score attributed to atom and non-atom tokens and visualize them on top of a 2D molecule diagram coordinated with a bar chart that represents a SMILES string. We demonstrate how attributions calculated for SMILES strings can be evaluated and better interpreted through interactivity with two use cases. Conclusions Data scientists can use XSMILES to understand their models’ behavior and compare multiple modeling approaches. The tool provides a set of parameters to adapt the visualization to users’ needs and it can be integrated into different platforms. We believe XSMILES can support data scientists to develop, improve, and communicate their models by making it easier to identify patterns and compare attributions through interactive exploratory visualization.

Climate change, and in particular the unprecedented rapid global warming, presents a major threat to corals, with warming rates potentially exceeding the adaptive capacities of most coral species. Assisted gene flow, the human facilitated introduction of temperature resilience alleles from warmer to threatened colder populations via the movement of individuals (assisted migration) or their gametes (selective breeding), has been suggested as a tool to transfer thermal adaptations among populations. Due to its strong latitudinal temperature gradient and extreme temperature conditions, the Red Sea constitutes an ideal location to investigate the potential of this strategy. Here, we relocated Porites lobata colonies from three reefs along the Saudi Arabian Red Sea with different mean sea surface temperature summer maxima (ranging from 30.9 °C in Duba, 32.5 °C in Thuwal, to 33.8 °C in Jazan) to a common garden experiment in the intermediate central location. Five colonies from each location were fragmented and deployed in situ in early summer of 2018 to investigate physiological differences in bleaching, survival, and growth. Results showed significantly higher bleaching in fragments from Duba, followed by 65% mortality. Even though no bleaching was observed in fragments from Jazan, mortality rates of around 20% indicated that other environmental parameters besides temperature might influence coral health and survival. These results suggest that assisted gene flow via translocation alone may be restricted in its success due to a lack of local adaptations to environmental conditions other than temperature. However, strategies like inter-populational breeding may overcome these limitations as they might allow producing offspring with both increased thermal tolerance and local adaptations.

In many rural East African areas, anti-malarial plants are commonly used as first-line treatment against malaria. However, spatially explicit information about the future availability of anti-malarial plant species and its relation to future suitable habitat for malaria vectors is limited. In this study we (1) model the distribution of anti-malarial plant and malaria vector species and assess the drivers of their distributions taking the example of the Samburu dryland in Kenya, (2) map the modeled overlap in this area, (3) assess the impact of future climate change on anti-malarial plant and malaria vector species and (4) report their future overlaps. Our results show that mean temperature of warmest quarter, precipitation of wettest quarter and mean temperature of coldest quarter were the most important environmental variables that affected the distribution of anti-malarial species. The effects of climate change will vary, with some areas characterized by huge losses in anti-malarial species habitat while others gained or remained stable under both SSP2-4.5 and SSP5-8.5 climate change scenarios by 2050s and 2070s. According to most of our scenarios, more than half of the anti-malarial species will become vulnerable or threatened by 2050s and 2070s. A comparison between distribution patterns of future anti-malarial species richness and malaria vector species suitable habitat suggests that the former will decrease considerably while the later will increase. Because the availability of anti-malarial species will decrease in the areas affected by malaria vectors, geographically targeted conservation strategies and further control measures against malaria vectors are all the more important.

Here, the authors reveal using single-cell RNA sequencing that Parkinson’s disease (PD) patient-derived neuronal cells show altered primary cilia morphology and signaling suggesting cilia dysfunction may underlie PD pathogenesis.

Abstract Background Chronic hip pain due to osteoarthritis or hip dysplasia has been shown to negatively affect many daily life aspects. One aspect, however, which persists underestimated is sexual health. The number of total hip arthroplasties (THA) are increasing, especially in young patients who have high functional expectations, not only to pain relief, but to an increase in hip mobility and quality of life as well as sexual activity. Aim (1) to report the demographic factors, (2) the sexual activity before and after THA, as well as the concerns related to sexual activity after THA and (3) the patient-reported outcome measurements (PROMs) in sexually active male patients. Methods We evaluated the results of patients between 18 and 65 years of age following primary cementless short femoral stem THA using a direct anterior approach (DAA) at a midterm follow-up of 4 years. A web-based questionnaire (via SurveyMonkey) was chosen to assess frequency, positions, complaints, fears, dealing with the questions and PROMs. Our patients sexual activity was via The Sexual Health Inventory for Men (SHIM) validated. Results Patients resumed their sexual activities after 6 weeks. The two main causes of difficulty in sexual activity before surgery were pain and limitation of the range of motion of the hip joint. Patients experienced less pain and an improvement in hip range of motion after THA. 89% of patients expressed a desire for more detailed and specific information on the subject. The patients foremost concern about muscle weakness, surgical scar or fear of dislocation. After 4 years follow-up our patients presented a significant improvement of the modified Harris Hip Score (mHHS) from 34.1 preoperative to 92.6 after THA. Conclusion THA improves the quality in sexual life, in relation to less pain and improvement in the range of motion, but not in the frequency of sexual activity. Men’s sexual positions required less mobility and could therefore be considered safer.

Imaging skeletal muscle function and metabolism, as reported by local hemodynamics and oxygen kinetics, can elucidate muscle performance, severity of an underlying disease or outcome of a treatment. Herein, we used multispectral optoacoustic tomography (MSOT) to image hemodynamics and oxygen kinetics within muscle during exercise. Four healthy volunteers underwent three different hand-grip exercise challenges (60s isometric, 120s intermittent isometric and 60s isotonic). During isometric contraction, MSOT showed a decrease of HbO2, Hb and total blood volume (TBV), followed by a prominent increase after the end of contraction. Corresponding hemodynamic behaviors were recorded during the intermittent isometric and isotonic exercises. A more detailed analysis of MSOT readouts revealed insights into arteriovenous oxygen differences and muscle oxygen consumption during all exercise schemes. These results demonstrate an excellent capability of visualizing both circulatory function and oxygen metabolism within skeletal muscle under exercise, with great potential implications for muscle research, including relevant disease diagnostics.

Purpose: Supervising roles within virtual collaborative learning (VCL) environments face many different challenges and are often having difficulties keeping an eye on everything and comprehending every participant’s or group’s workflow. To help supervisors with problems like that we developed a software prototype to support their daily workflow and overcome the mentioned challenges. Study design/methodology/approach: This study used a design science research approach to investigate how learning analytics might be able to support teaching staff in VCL settings. Previous studies demonstrated that this approach is very well suited to derive design guidelines for such software artifacts. Initially, a qualitative interview series with four experienced tutors was carried out to get an in-depth understanding of the challenges and tasks teaching staff typically faces in VCL environments. The interview material was systematically analysed to acquire the underlying software requirements. These were then combined with existing knowledge about support software of similar use cases to create a first prototype, primarily based on a supervised machine learning model that classifies online messages sent within the teams. Findings: The software tool we have developed has shown that machine learning processes can indeed be used to support teaching staff in VCL environments. The tool achieves satisfactory classification performance in categorizing chat messages. It could therefore be demonstrated that it is possible to classify chat messages using a software tool. The interviews conducted revealed a particular interest in the statistical evaluations of group activities in Microsoft Teams. This was said to save a lot of time in the subsequent evaluation of the groups. The interviewed eTutors also expressed an interest in receiving private information on the development of possible conflicts within groups. The interest of the interviewed supervisors was very high and additional interviews could lead to further possible feature ideas. In general, the evaluative interviews resulted in positive feedback regarding how our prototype supported eTutors during their work. Originality/value: In current times, spatially distributed and asynchronous education plays a bigger role than ever before. VCL environments are useful tools to overcome these challenges of time and space. However, unlike research on conversational agents or automated feedback systems, the focus of this work is not on the communication interface between software and users or the exclusively quantitative analysis of messages. The goal is to evaluate the content of sent messages within VCL environments using the six defined categories to gain a better qualitative understanding of the teams’ collaboration and its workflow.

The durability of prestressed concrete structures built between the 1950s and 1980s is becoming a growing problem. One reason is the sensitivity to stress corrosion cracking of the prestressing steel. Failure of prestressing wires can result in collapse of the entire structure without premature indication by transverse bending cracks or considerable deformation. The response of a structure to significant number of prestressing wire breaks was studied on a bridge in Brandenburg, Germany. Two thirds of the prestressing wires in concentrated tendons of two girders were cut before the bridge was demolished. Acoustic Emission Analysis was used to detect the wire breaks. Thus, the number of wire breaks was correlated with results of other measurement techniques, in particular strain measurements on the girders. In preparation of the measurements, the acoustic properties of the bridge were determined and the suitability of Schmidt hammer impacts as an acoustic reference source was validated.

Increasing tree mortality due to climate change has been observed globally. Remote sensing is a suitable means for detecting tree mortality and has been proven effective for the assessment of abrupt and large-scale stand-replacing disturbances, such as those caused by windthrow, clear-cut harvesting, or wildfire. Non-stand replacing tree mortality events (e.g., due to drought) are more difficult to detect with satellite data – especially across regions and forest types. A common limitation for this is the availability of spatially explicit reference data. To address this issue, we propose an automated generation of reference data using uncrewed aerial vehicles (UAV) and deep learning-based pattern recognition. In this study, we used convolutional neural networks (CNN) to semantically segment crowns of standing dead trees from 176 UAV-based very high-resolution (

IntroductionThe food-borne Gram-negative bacterial pathogen Campylobacter jejuni may cause the acute enterocolitis syndrome campylobacteriosis in infected humans. Given that human C. jejuni infections are rising globally which hold also true for resistance rates against antibiotic compounds such as macrolides and fluoroquinolones frequently prescribed for the treatment of severe infectious enteritis, novel antibiotics-independent therapeutic strategies are needed. Distinct organic acids are well known for their health-beneficial including anti-microbial and immunomodulatory properties. In our present study, we investigated potential pathogen-lowering and anti-inflammatory effects of benzoic acid, butyric acid, caprylic acid, and sorbic acid either alone or in combination during acute murine campylobacteriosis.MethodsTherefore, secondary abiotic IL-10–/– mice were perorally infected with C. jejuni strain 81–176 and subjected to a 4-day-course of respective organic acid treatment.Results and discussionOn day 6 post-infection, mice from the combination cohort displayed slightly lower pathogen loads in the duodenum, but neither in the stomach, ileum nor large intestine. Remarkably, the clinical outcome of C. jejuni induced acute enterocolitis was significantly improved after combined organic acid treatment when compared to the placebo control group. In support, the combinatory organic acid treatment dampened both, macroscopic and microscopic inflammatory sequelae of C. jejuni infection as indicated by less colonic shrinkage and less pronounced histopathological including apoptotic epithelial cell changes in the colon on day 6 post-infection. Furthermore, mice from the combination as compared to placebo cohort exhibited lower numbers of innate and adaptive immune cells such as neutrophilic granulocytes, macrophages, monocytes, and T lymphocytes in their colonic mucosa and lamina propria, respectively, which also held true for pro-inflammatory cytokine secretion in the large intestines and mesenteric lymph nodes. Notably, the anti-inflammatory effects were not restricted to the intestinal tract, but could also be observed systemically given pro-inflammatory mediator concentrations in C. jejuni infected mice from the combination organic acid treatment that were comparable to basal values. In conclusion, our in vivo study provides first evidence that an oral application of distinct organic acids in combination exhibits pronounced anti-inflammatory effects and hence, constitutes a promising novel antibiotics-independent therapeutic strategy in the combat of acute campylobacteriosis.

Abstract Background The coral-Symbiodiniaceae symbiosis is fundamental for the coral reef ecosystem. Corals provide various inorganic nutrients to their algal symbionts in exchange for the photosynthates to meet their metabolic demands. When becoming symbionts, Symbiodiniaceae cells show a reduced proliferation rate and a different life history. While it is generally believed that the animal hosts play critical roles in regulating these processes, far less is known about the molecular underpinnings that allow the corals to induce the changes in their symbionts. Results We tested symbiont cell proliferation and life stage changes in vitro in response to different nutrient-limiting conditions to determine the key nutrients and to compare the respective symbiont transcriptomic profiles to cells in hospite. We then examined the effects of nutrient repletion on symbiont proliferation in coral hosts and quantified life stage transitions in vitro using time-lapse confocal imaging. Here, we show that symbionts in hospite share gene expression and pathway activation profiles with free-living cells under nitrogen-limited conditions, strongly suggesting that symbiont proliferation in symbiosis is limited by nitrogen availability. Conclusions We demonstrate that nitrogen limitation not only suppresses cell proliferation but also life stage transition to maintain symbionts in the immobile coccoid stage. Nutrient repletion experiments in corals further confirmed that nitrogen availability is the major factor limiting symbiont density in hospite. Our study emphasizes the importance of nitrogen in coral-algae interactions and, more importantly, sheds light on the crucial role of nitrogen in symbiont life history regulation.

Abstract Background Pelvic fractures are often associated with spine injury in polytrauma patients. This study aimed to determine whether concomitant spine injury influence the surgical outcome of pelvic fracture. Methods We performed a retrospective analysis of data of patients registered in the German Pelvic Registry between January 2003 and December 2017. Clinical characteristics, surgical parameters, and outcomes were compared between patients with isolated pelvic fracture (group A) and patients with pelvic fracture plus spine injury (group B). We also compared apart patients with isolated acetabular fracture (group C) versus patients with acetabular fracture plus spine injury (group D). Results Surgery for pelvic fracture was significantly more common in group B than in group A (38.3% vs. 36.6%; p = 0.0002), as also emergency pelvic stabilizations (9.5% vs. 6.7%; p

For aerosol, cloud, land, and ocean remote sensing, the development of accurate cloud detection methods, or cloud masks, is extremely important. For airborne passive remotesensing, it is also important to identify when clouds are above the aircraft since their presence contaminates the measurements of nadir-viewing passive sensors. We describe the development of a camera-based approach to detecting clouds above the aircraft via a convolutional neural network called the cloud detection neural network (CDNN). We quantify the performance of this CDNN using human-labeled validation data where we report 96% accuracy in detecting clouds in testing datasets for both zenith viewing and forward-viewing models. We present results from the CDNN based on airborne imagery from the NASA Aerosol Cloud meteorology Interactions oVer the western Atlantic Experiment (ACTIVATE) and the Clouds, Aerosol, and Monsoon Processes Philippines Experiment (CAMP2Ex). We quantify the ability of the CDNN to identify the presence of clouds above the aircraft using a forward-looking camera mounted inside the aircraft cockpit compared to the use of an all-sky upward-looking camera that is mounted outside the fuselage on top of the aircraft. We assess our performance by comparing the flight-averaged cloud fraction of zenith and forward CDNN retrievals with that of the prototype hyperspectral total-diffuse Sunshine Pyranometer (SPN-S) instrument’s cloud optical depth data. A comparison of the CDNN with the SPN-S on time-specific intervals resulted in 93% accuracy for the zenith viewing CDNN and 84% for the forward-viewing CDNN. The comparison of the CDNNs with the SPN-S on flight-averaged cloud fraction resulted in an agreement of .15 for the forward CDNN and .07 for the zenith CDNN. For CAMP2Ex, 53% of flight dates had above-aircraft cloud fraction above 50%, while for ACTIVATE, 52% and 54% of flight dates observed above-aircraft cloud fraction above 50% for 2020 and 2021, respectively. The CDNN enables cost-effective detection of clouds above the aircraft using an inexpensive camera installed in the cockpit for airborne science research flights where there are no dedicated upward-looking instruments for cloud detection, the installation of which requires time-consuming and expensive aircraft modifications, in addition to added mission cost and complexity of operating additional instruments.

Since 1950, coral abundance has declined worldwide by an estimated 60%, and further dramatic declines are predicted. Although global reductions in carbon emissions are essential to prevent further loss, coral reef restoration has become imperative to maintain the ecosystem services that coral reefs provide to humans at local scales. Yet, currently coral restoration and gardening efforts are too expensive to scale up due to the labor-intensive nature of the methods and low success rates. Here, we present a suite of technologies that improve coral reef restoration and rehabilitation’s scalability, efficiency, and effectiveness. Our modular technologies are designed to streamline in and ex situ nursery workflows, reduce maintenance times, solve problems in transporting corals to outplanting sites, and enable rapid outplanting on natural and artificial substrates. These novel structures can act as coral seeding hubs, which placed strategically, can have the capacity to enhance coral reproduction and replenish degraded nearby reefs with larvae. They can be applied to coral restoration and reefscaping, complemented by unique eco-friendly, low-carbon-emission structures for the creation of architecturally and visually appealing habitats and underwater landscapes. Our technologies integrate novel monitoring approaches that support intelligent solutions to track genotypes, optimize and control stock management, apply assisted evolution approaches, and adaptive management through long-term monitoring.

Global warming and other anthropogenic impacts have driven coral reef degradation on a global scale to unprecedented levels of decline, with further dramatic deterioration predicted by the end of this century. Along with a drastic reduction in carbon emissions, we face an imperative to restore and maintain marine habitats to secure the ecosystem services they provide. While terrestrial systems have benefited from the agricultural revolution that provided industrial tools for effective habitat restoration, limited access to marine environments has inhibited similar levels of innovation resulting in a lack of cost-effective and scalable solutions. Commercial off-the-shelf technologies to cater to this growing industry are still absent. Here we conducted a systematic analysis of patent and scientific literature data as indicators of research and development (R&D) output in the field of coral restoration. We identify technology growth trends, key areas of technological development, and their geographical distribution. While the number of inventions filed for coral restoration is on the rise, similar to the published academic literature, the stakeholders leading both fields are unrelated. Academic research appears to lack translation into inventions for commercialization. Intellectual property protection further seems to be spearheaded by a few countries and is often limited in its application to national jurisdictions, with China dominating this sector. This does not mirror the distribution of current and need for coral restoration efforts globally. Here we discuss potential differences in cultural, socio-economic, and philosophical ideologies that drive these divergences and their impact as inhibitors or promoters of innovations targeting coral restoration solutions.

The Bioconcentration Factor (BCF) is an important parameter in the environmental risk assessment of chemicals, relevant for industrial and academic research as well as required in many regulatory contexts. It represents the potential of a substance to accumulate in organic tissues or whole animals and is most frequently measured in fish. However, animal welfare reasons, throughput limitations, and costs push the need for alternative methods that allow accurate and reliable estimations of BCF in silico. We present a new deep learning model to predict BCF values from chemical structures, that outperforms currently available models (R2 of 0.68 and RMSE of 0.59 log units on an external test set; R2 of 0.70 and RMSE of 0.74 log units in a demanding cluster split validation). The model is based on molecular representations encoded as CDDD descriptors and exploits a large in-house dataset with measured logD values as an auxiliary task.Additionally, we developed a post-hoc explainability method based on SMILES character substitutions to accompany our predictions with atom-level interpretations. These sensitivity scores highlight the most influential moieties in the molecule and can help to understand the predictions better and design new molecules.

Abstract The prediction of metabolism and biotransformation pathways of xenobiotics is a highly desired tool in environmental sciences, drug discovery, and (eco)toxicology. Several systems predict single transformation steps or complete pathways as series of parallel and subsequent steps. Their performance is commonly evaluated on the level of a single transformation step. Such an approach cannot account for some specific challenges that are caused by specific properties of biotransformation experiments. That is, missing transformation products in the reference data that occur only in low concentrations, e.g. transient intermediates or higher-generation metabolites. Furthermore, some rule-based prediction systems evaluate the performance only based on the defined set of transformation rules. Therefore, the performance of these models cannot be directly compared. In this paper, we introduce a new evaluation framework that extends the evaluation of biotransformation prediction from single transformations to whole pathways, taking into account multiple generations of metabolites. We introduce a procedure to address transient intermediates and propose a weighted scoring system that acknowledges the uncertainty of higher-generation metabolites. We implemented this framework in enviPath and demonstrate its strict performance metrics on predictions of in vitro biotransformation and degradation of xenobiotics in soil. Our approach is model-agnostic and can be transferred to other prediction systems. It is also capable of revealing knowledge gaps in terms of incompletely defined sets of transformation rules.

Abstract Plant functional traits (‘traits’) are essential for assessing biodiversity and ecosystem processes, but cumbersome to measure. To facilitate trait measurements, we test if traits can be predicted through visible morphological features by coupling heterogeneous photographs from citizen science (iNaturalist) with trait observations (TRY database) through Convolutional Neural Networks (CNN). Our results show that image features suffice to predict several traits representing the main axes of plant functioning. The accuracy is enhanced when using CNN ensembles and incorporating prior knowledge on trait plasticity and climate. Our results suggest that these models generalise across growth forms, taxa and biomes around the globe. We highlight the applicability of this approach by producing global trait maps that reflect known macroecological patterns. These findings demonstrate the potential of Big Data derived from professional and citizen science in concert with CNN as powerful tools for an efficient and automated assessment of Earth’s plant functional diversity.