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Introduction Supraglottic airway devices represent a less invasive method of airway management than tracheal intubation during general anaesthesia. Their continued development is focused mainly on improvements in the insertion success rate and minimalisation of perioperative and postoperative complications. The i-gel Plus is a novel, anatomically preshaped supraglottic airway device which achieves a perilaryngeal seal due to a non-inflatable cuff made of a soft thermoplastic elastomer. The purpose of this cohort study is to assess the success rate of the i-gel Plus use during elective procedures under general anaesthesia, its intraoperative performance, and the degree of postoperative complications.Methods and analysis This is a multicentre, prospective, interventional cohort study. The enrolment will take place in seven centres in four European countries. We plan to enrol 2000 adult patients in total, who are scheduled for elective surgery under general anaesthesia, and with an indication for use of a supraglottic airway device for management of their airway. The study is projected to run over a period of 18 months. The primary outcome of the study is the total success rate of the i-gel Plus insertion in terms of successful ventilation and oxygenation through the device. Secondary outcomes include perioperative parameters, such as insertion time, seal/leak pressures, number of insertion attempts and postoperative adverse events and complications. Postoperative follow-up will be performed at 1 hour, 24 hours in all patients, and for selected patients at 3 and 6 months.Ethics and dissemination The cohort study has received the following ethical approvals: General University Hospital Prague, University Hospital Olomouc, University Military Hospital Prague, University Hospital Barcelona, University Hospital Lodz, Antrim Area Hospital, Craigavon Area Hospital, Office for Research Ethics Committees Northern Ireland. The results will be published in peer-reviewed journals and presented at relevant anaesthesia conferences.Trial registration number ISRCTN86233693;Pre-results.

NKR-P1 is an inhibitory receptor on the surface of natural killer cells, and its engagement with the ligand LLT1 on activated monocytes and B cells triggers NK cell self-tolerance and other immunological processes. Here authors set up a comprehensive, structure-based model of NKR-P1-LLT1 interaction that involves NKR-P1 homodimer formation and subsequent bridging of two LLT1 molecules.

The experiment was conducted on Isa Brown laying hens to study the effects of sea buckthorn fruit residues on hen performance and quality of eggs. The total number of 1440 eighteen-week-old pullets Isa Brown was divided into two groups (720 each) including 24 subgroups (30 hens). The experimental group was fed diets in which 5% of the wheat was replaced by sea buckthorn fruit residues. The control group was fed diets without any colour additives. Egg production and intensity of laying hens were evaluated in seven periods, from 127 to 322 days of age. In our study, a significant effect (P ≤ .05) of sea buckthorn fruit residues on total number of laid eggs and egg yolk colour was detected. However, a non-significant effect of sea buckthorn was found on hen performance or egg quality including egg weight, yolk weight, eggshell strength, shape index of egg, eggshell thickness, Haugh units, eggshell colour and blood spot, albumen weight, proportion and Haugh units. Results of our study showed the beneficial effect of feeding sea buckthorn fruit residues on total number of laid eggs and egg yolk colour which is a great concern for egg consumers.

Targeted cancer immunotherapy is a promising tool for restoring immune surveillance and eradicating cancer cells. Hydrophilic polymers modified with coiled coil peptide tags can be used as universal carriers designed for cell-specific delivery of such biologically active proteins. Here, we describe the preparation of pHPMA-based copolymer conjugated with immunologically active protein B7-H6 via complementary coiled coil VAALEKE (peptide E) and VAALKEK (peptide K) sequences. Receptor B7-H6 was described as a binding partner of NKp30, and its expression has been proven for various tumor cell lines. The binding of B7-H6 to NKp30 activates NK cells and results in Fas ligand or granzyme-mediated apoptosis of target tumor cells. In this work, we optimized the expression of coiled coil tagged B7-H6, its ability to bind activating receptor NKp30 has been confirmed by isothermal titration calorimetry, and the binding stoichiometry of prepared chimeric biopolymer has been characterized by analytical ultracentrifugation. Furthermore, this coiled coil B7-H6-loaded polymer conjugate activates NK cells in vitro and, in combination with coiled coil scFv, enables their targeting towards a model tumor cell line. Prepared chimeric biopolymer represents a promising precursor for targeted cancer immunotherapy by activating the cytotoxic activity of natural killer cells.

Despite the advances in mobile robotics, the introduction of autonomous robots in human-populated environments is rather slow. One of the fundamental reasons is the acceptance of robots by people directly affected by a robot’s presence. Understanding human behavior and dynamics is essential for planning when and how robots should traverse busy environments without disrupting people’s natural motion and causing irritation. Research has exploited various techniques to build spatio-temporal representations of people’s presence and flows and compared their applicability to plan optimal paths in the future. Many comparisons of how dynamic map-building techniques show how one method compares on a dataset versus another, but without consistent datasets and high-quality comparison metrics, it is difficult to assess how these various methods compare as a whole and in specific tasks. This article proposes a methodology for creating high-quality criteria with interpretable results for comparing long-term spatio-temporal representations for human-aware path planning and human-aware navigation scheduling. Two criteria derived from the methodology are then applied to compare the representations built by the techniques found in the literature. The approaches are compared on a real-world, long-term dataset, and the conception is validated in a field experiment on a robotic platform deployed in a human-populated environment. Our results indicate that continuous spatio-temporal methods independently modeling spatial and temporal phenomena outperformed other modeling approaches. Our results provide a baseline for future work to compare a wide range of methods employed for long-term navigation and provide researchers with an understanding of how these various methods compare in various scenarios.

The performance of deep learning-based detection methods has made them an attractive option for robotic perception. However, their training typically requires large volumes of data containing all the various situations the robots may potentially encounter during their routine operation. Thus, the workforce required for data collection and annotation is a significant bottleneck when deploying robots in the real world. This applies especially to outdoor deployments, where robots have to face various adverse weather conditions. We present a method that allows an independent car tansporter to train its neural networks for vehicle detection without human supervision or annotation. We provide the robot with a hand-coded algorithm for detecting cars in LiDAR scans in favourable weather conditions and complement this algorithm with a tracking method and a weather simulator. As the robot traverses its environment, it can collect data samples, which can be subsequently processed into training samples for the neural networks. As the tracking method is applied offline, it can exploit the detections made both before the currently processed scan and any subsequent future detections of the current scene, meaning the quality of annotations is in excess of those of the raw detections. Along with the acquisition of the labels, the weather simulator is able to alter the raw sensory data, which are then fed into the neural network together with the labels. We show how this pipeline, being run in an offline fashion, can exploit off-the-shelf weather simulation for the auto-labelling training scheme in a simulator-in-the-loop manner. We show how such a framework produces an effective detector and how the weather simulator-in-the-loop is beneficial for the robustness of the detector. Thus, our automatic data annotation pipeline significantly reduces not only the data annotation but also the data collection effort. This allows the integration of deep learning algorithms into existing robotic systems without the need for tedious data annotation and collection in all possible situations. Moreover, the method provides annotated datasets that can be used to develop other methods. To promote the reproducibility of our research, we provide our datasets, codes and models online.

Aims: The purpose of this international survey was to describe the impact of current practices and techniques of caesarean section on the neonatal Apgar score in the Czech Republic (CZE) and Slovakia (SVK). Methods: All Czech and Slovak departments that provide obstetric anaesthesia were invited to participate in a one-month (November 2015) prospective study that monitored in details all peripartum anaesthetic practices, delivered by anaesthesiologists. Participating centers recorded all data on-line in the CLADE-IS database (Masaryk University, CZE). Results and Discussions. We collected data of 10119 women who delivered 10226 newborns. A caesarean section was recorded in 25.1% of deliveries (CZE 23.2%; SVK 30%). General anaesthesia was used for caesarean section in 37.5% of the cases (CZE 40%, SVK 33%). There was no statistically significant difference in the Apgar score lower than 7 in the 1, 5 or 10 min in groups of general and regional anaesthesia for caesarean section, when only elective sections of in-term babies with birth weight over 2500 g were analyzed. We found no statistically significant differences in the Apgar score in newborns of women intubated for caesarean section in rocuronium (n=21; 2.2%) and suxamethonium (n=889; 93%). Conclusion: We found no difference in neonatal outcomes in groups of general and regional anaesthesia for caesarean section when only out-of-risk newborns were analyzed. The risk factors were identified as follows: an acute caesarean section, preterm babies, birth weight less than 2 500 g, born in perinatological center and multiple pregnancy - second baby. Trial Registration: ClinicalTrials.gov (ID: NCT02380586) https://clinicaltrials.gov/ct2/show/NCT02380586

Visual teach and repeat navigation (VT&R) is popular in robotics thanks to its simplicity and versatility. It enables mobile robots equipped with a camera to traverse learned paths without the need to create globally consistent metric maps. Although teach and repeat frameworks have been reported to be relatively robust to changing environments, they still struggle with day-to-night and seasonal changes. This paper aims to find the horizontal displacement between prerecorded and currently perceived images required to steer a robot towards the previously traversed path. We employ a fully convolutional neural network to obtain dense representations of the images that are robust to changes in the environment and variations in illumination. The proposed model achieves state-of-the-art performance on multiple datasets with seasonal and day/night variations. In addition, our experiments show that it is possible to use the model to generate additional training examples that can be used to further improve the original model’s robustness. We also conducted a real-world experiment on a mobile robot to demonstrate the suitability of our method for VT&R.

The performance of deep neural networks and the low costs of computational hardware has made computer vision a popular choice in many robotic systems. An attractive feature of deep-learned methods is their ability to cope with appearance changes caused by day–night cycles and seasonal variations. However, deep learning of neural networks typically relies on large numbers of hand-annotated images, which requires significant effort for data collection and annotation. We present a method that allows autonomous, self-supervised training of a neural network in visual teach-and-repeat (VT&R) tasks, where a mobile robot has to traverse a previously taught path repeatedly. Our method is based on a fusion of two image registration schemes: one based on a Siamese neural network and another on point-feature matching. As the robot traverses the taught paths, it uses the results of feature-based matching to train the neural network, which, in turn, provides coarse registration estimates to the feature matcher. We show that as the neural network gets trained, the accuracy and robustness of the navigation increases, making the robot capable of dealing with significant changes in the environment. This method can significantly reduce the data annotation efforts when designing new robotic systems or introducing robots into new environments. Moreover, the method provides annotated datasets that can be deployed in other navigation systems. To promote the reproducibility of the research presented herein, we provide our datasets, codes and trained models online.

Videolaryngoscopes may improve intubating conditions in obese patients. A total of 110 patients with a body mass index > 35 kg∙m−2 were prospectively randomized to tracheal intubation using non-channeled Glidescope Titanium or channeled King Vision videolaryngoscope. The primary outcome was the time to tracheal intubation. Secondary outcomes included: total success rate, number of attempts, the quality of visualization, peri-procedural and post-proceduralcomplications. Time to the first effective breath was shorter with the King Vision (median; 95% CI)—36; 34–39 s vs. 42; 40–50 in the Glidescope group (p = 0.007). The total success rate was higher in the Glidescope group—100% vs. 89.1% (p = 0.03). There was a higher incidence of moderate and difficult laryngoscopy in the King Vision group. No difference was recorded in first attempt success rates, total number of attempts, use of additional maneuvers, intraoperative trauma, or any significant decrease in SpO2 during intubation. No serious complications were noted and the incidence of postoperative complaints was without difference. Although tracheal intubation with King Vision showed shorter time to the first breath, total success was higher in the Glidescope group, and all but one patients where intubation failed with the KingVision were subsequently intubated with the Glidescope.

Videolaryngoscopes may reduce cervical spine movement during tracheal intubation in patients with neck trauma. This manikin study aimed to compare the performance of disposable non-channeled and channeled blades of the King Vision™ videolaryngoscope in simulated cervical spine injury. Fifty-eight anesthesiologists in training intubated the TruMan manikin with the neck immobilized using each blade in a randomized order. The primary outcome was the time needed for tracheal intubation, secondary aims included total success rate, the time required for visualization of the larynx, number of attempts, view of the vocal cords, and subjective assessment of both methods. Intubation time with the channeled blade was shorter, with a median time of 13 s (IQR 9−19) vs. 23 s (14.5−37.5), p < 0.001, while times to visualization of the larynx were similar in both groups (p = 0.54). Success rates were similar in both groups, but intubation with the non-channeled blade required more attempts (1.52 vs. 1.05; p < 0.001). The participants scored the intubation features of the channeled blade significantly higher, while visualization features were scored similarly in both groups. Both blades of the King Vision™ videolaryngoscope are reliable intubation devices in a simulated cervical spine injury in a manikin model when inserted by non-experienced operators. The channeled blade allowed faster intubation of the trachea.

Minimally invasive techniques to access subcutaneous adipose tissue for glucose monitoring are successfully applied in type1 diabetic and critically ill patients. During critical illness, the addition of a lactate sensor might enhance prognosis and early intervention. Our objective was to evaluate SAT as a site for lactate measurement in critically ill patients. In 40 patients after major cardiac surgery, arterial blood and SAT microdialysis samples were taken in hourly intervals. Lactate concentrations from SAT were prospectively calibrated to arterial blood. Analysis was based on comparison of absolute lactate concentrations (arterial blood vs. SAT) and on a 6-hour lactate trend analysis, to test whether changes of arterial lactate can be described by SAT lactate. Correlation between lactate readings from arterial blood vs. SAT was highly significant (r2=0.71, P

Epidural analgesia (EPA) is the most effective method of intrapartum pain relief and is considered to be very safe. Recently, it has been used in up to 34% of parturients with EPA and is also associated with maternal temperature elevations during labor. The mechanism of this epidural-associated fever remains incompletely understood. The most likely etiology seems to be non-infectious inflammation caused by an epidural catheter. However, some authors deny this association. They theorize it is caused by selection bias only, as EPA is more often required by women with more painful and prolonged or more complicated labor, where temperature elevation is due to other causes. They point out that in some studies, fever was correlated to EPA only with concurrent placental inflammation. Maternal fever, despite the cause, either infectious or non-infectious origin, carries important clinical and public health implications. Further research that evaluates maternal epidural status and its influence on maternal or neonatal fever could improve sepsis evaluation and lead to worldwide decrease of unnecessary antibio-tic exposure.