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Terrestrial laser scanning has become more and more popular in recent years. The according planning of the standpoint network is a crucial issue influencing the overhead and the resulting point cloud. Fully static approaches are both cost and time extensive, whereas fully kinematic approaches cannot produce the same data quality. Stop-and-go scanning, which combines the strengths of both strategies, represents a good alternative solution. In the scanning process, the standpoint planning is by now mostly a manual process based on expert knowledge and relying on the surveyor’s experience. This paper provides a method based on Mixed Integer Linear Programming (MILP) ensuring an optimal placement of scanner standpoints considering all scanner-related constraints (e.g. incidence angle), a full coverage of the scenery, a sufficient overlap for the subsequent registration and an optimal route planning solving a Traveling Salesperson Problem (TSP). This enables the fully automatic application of autonomous systems for providing a complete model while performing a stop-and-go laser scanning, e.g. with the Spot robot from Boston Dynamics. Our pre-computed solution, i.e. standpoints and trajectory, has been evaluated surveying a real-world environment using a 360° panoramic laser scanner and successfully compared with a precise LoD2 building model of the underlying scene. The performed ICP-based registration issued from our fully automatic pipeline turns out to be a very good and safe alternative of the otherwise laborious target-based registration.

Unmanned Aerial Vehicles (UAVs) are used for the inspection of areas which are otherwise difficult to access. Autonomous monitoring and navigation requires a background knowledge on the surroundings of the vehicle. Most mission planing systems assume collision-free pre-defined paths and do not tolerate a GPS signal outage. Our approach makes weaker assumptions. This paper introduces a mission planing platform allowing for the integration of environmental prior knowledge such as 3D building and terrain models. This prior knowledge is integrated to pre-compute an octomap for collision detection. The semantically rich building models are used to specify semantic user queries such as roof or facade inspection. A reasoning process paves the way for semantic mission planing of hidden and a-priori unknown objects. Subsequent scene interpretation is performed by an incremental parsing process.

Accurate and robust positioning of vehicles in urban environments is of high importance for many applications (e.g. autonomous driving or mobile mapping). In the case of mobile mapping systems, a simultaneous mapping of the environment using laser scanning and an accurate positioning using GNSS is targeted. This requirement is often not guaranteed in shadowed cities where GNSS signals are usually disturbed, weak or even unavailable. Both, the generated point clouds and the derived trajectory are consequently imprecise. We propose a novel approach which incorporates prior knowledge, i.e. 3D building model of the environment, and improves the point cloud and the trajectory. The key idea is to benefit from the complementarity of both GNSS and 3D building models. The point cloud is matched to the city model using a point-to-plane ICP. An informed sampling of appropriate matching points is enabled by a pre-classification step. Support vector machines (SVMs) are used to discriminate between facade and remaining points. Local inconsistencies are tackled by a segment-wise partitioning of the point cloud where an interpolation guarantees a seamless transition between the segments. The full processing chain is implemented from the detection of facades in the point clouds, the matching between them and the building models and the update of the trajectory estimate. The general applicability of the implemented method is demonstrated on an inner city data set recorded with a mobile mapping system.

Unmanned Aerial Vehicles (UAVs) are increasingly used, and open new opportunities, in agriculture and phenotyping because of the flexible data acquisition. In this study the potential of ultra-high spatially resolved UAV image data was investigated to quantify lodging percentage, lodging development and lodging severity of barley using Structure from Motion techniques. The term lodging is defined as the permanent displacement of a plant from the upright position. Traditionally lodging quantification is based on observations that need, and vary with observers in the field. An objective threshold approach was proposed in this study to improve the accuracy in lodging determination. Across breeding trials, manual reference measurements and UAV based lodging percentage showed a very high correlation (R2 = 0.96). In addition, the multi-temporal lodging percentage development was used to estimate the recovery rate and to determine the influence of different lodging events. Based on the parameter lodging percentage an approach was developed that allowed the assessment of lodging severity, an information that is important to estimate the yield impairment. Lodging severity can be used for insurance applications, precision farming and breeder research. This trait, together with differentiated recovery are novel traits next to lodging severity that will aid the selection for genetic lines.

In this paper, we investigate the usage of unmanned aerial vehicles (UAV) to assess the crop geometry with special focus on the crop height extraction. Crop height is classified as a reliable trait in crop phenotyping and recognized as a good indicator for biomass, expected yield, lodging or crop stress. The current industrial standard for crop height measurement is a manual procedure using a ruler, but this method is considered as time consuming, labour intensive and subjective. This study investigates methods for reliable and rapid deriving of the crop height from high spatial, spectral and time resolution UAV data considering the influences of the reference surface and the selected crop height generation method to the final calculation. To do this, we performed UAV missions during two winter wheat growing seasons and generate point clouds from areal images using photogrammetric methods. For the accuracy assessment we compare UAV based crop height with ruler based crop height as current industrial standard and terrestrial laser scanner (TLS) based crop height as a reliable validation method. The high correlation between UAV based and ruler based crop height and especially the correlation with TLS data shows that the UAV based crop height extraction method can provide reliable winter wheat height information in a non-invasive and rapid way. Along with crop height as a single value per area of interest, 3D UAV crop data should provide some additional information like lodging area, which can also be of interest in the plant breeding community.

For some years now, UAVs (unmanned aerial vehicles) are commonly used for different mobile mapping applications, such as in the fields of surveying, mining or archeology. To improve the efficiency of these applications an automation of the flight as well as the processing of the collected data is currently aimed at. One precondition for an automated mapping with UAVs is that the georeferencing is performed directly with cm-accuracies or better. Usually, a cm-accurate direct positioning of UAVs is based on an onboard multi-sensor system, which consists of an RTK-capable (real-time kinematic) GPS (global positioning system) receiver and additional sensors (e.g. inertial sensors). In this case, the absolute positioning accuracy essentially depends on the local GPS measurement conditions. Especially during mobile mapping applications in urban areas, these conditions can be very challenging, due to a satellite shadowing, non-line-of sight receptions, signal diffraction or multipath effects. In this paper, two straightforward and easy to implement strategies will be described and analyzed, which improve the direct positioning accuracies for UAV-based mapping and surveying applications under challenging GPS measurement conditions. Based on a 3D model of the surrounding buildings and vegetation in the area of interest, a GPS geometry map is determined, which can be integrated in the flight planning process, to avoid GPS challenging environments as far as possible. If these challenging environments cannot be avoided, the GPS positioning solution is improved by using obstruction adaptive elevation masks, to mitigate systematic GPS errors in the RTK-GPS positioning. Simulations and results of field tests demonstrate the profit of both strategies.

In recent years, unmanned aerial vehicles (UAVs) have increasingly been used in various application areas, such as in the remote sensing or surveying. For these applications the UAV has to be equipped with a mapping sensor, which is mostly a camera. Furthermore, a georeferencing of the UAV platform and/or the acquired mapping data is required. The most efficient way to realize this georeferencing is the direct georeferencing, which is based on an onboard multi-sensor system. In recent decades, direct georeferencing systems have been researched and used extensively in airborne, ship and land vehicle applications. However, these systems cannot easily be adapted to UAV platforms, which is mainly due to weight and size limitations. In this paper a direct georeferencing system for micro- and mini-sized UAVs is presented, which consists of a dual-frequency geodetic grade OEM GPS board, a low-cost single-frequency GPS chip, a tactical grade IMU and a magnetometer. To allow for cm-level position and sub-degree attitude accuracies, RTK GPS (real-time kinematic) and GPS attitude (GPS compass) determination algorithms are running on this system, as well as a GPS/IMU integration. Beside the direct georeferencing, also the precise time synchronization of the camera, which acts as the main sensor for mobile mapping applications, and the calibration of the lever arm between the camera reference point and the direct georeferencing reference point are explained in this paper. Especially the high accurate time synchronization of the camera is very important, to still allow for high surveying accuracies, when the images are taken during the motion of the UAV. Results of flight tests demonstrate that the developed system, the camera synchronization and the lever arm calibration make directly georeferenced UAV based single point measurements possible, which have cm-level accuracies on the ground.

In many unmanned aerial vehicle (UAV) applications a direct georeferencing is required. The reason can be that the UAV flies autonomous and must be navigated precisely, or that the UAV performs a remote sensing operation, where the position of the camera has to be known at the moment of the recording. In our application, a project called Mapping on Demand, we are motivated by both of these reasons. The goal of this project is to develop a lightweight autonomously flying UAV that is able to identify and measure inaccessible three-dimensional objects by use of visual information. Due to payload and space limitations, precise position and attitude determination of micro- and mini-sized UAVs is very challenging. The limitations do not only affect the onboard computing capacity, but they are also noticeable when choosing the georeferencing sensors. In this article, we will present a new developed onboard direct georeferencing system which is real-time capable, applicable for lightweight UAVs and provides very precise results (position accuracy σ < 5 cm and attitude accuracy σ < 0.5 deg). In this system GPS, inertial sensors, magnetic field sensors, a barometer as well as stereo video cameras are used as georeferencing sensors. We will describe the hardware development and will go into details of the implemented software. In this context especially the RTK-GPS software and the concept of the attitude determination by use of inertial sensors, magnetic field sensors as well as an onboard GPS baseline will be highlighted. Finally, results of first field tests as well as an outlook on further developments will conclude this contribution.

Background: This study addresses the importance of precise referencing in 3-dimensional (3D) plant phenotyping, which is crucial for advancing plant breeding and improving crop production. Traditionally, reference data in plant phenotyping rely on invasive methods. Recent advancements in 3D sensing technologies offer the possibility to collect parameters that cannot be referenced by manual measurements. This work focuses on evaluating a 3D printed sugar beet plant model as a referencing tool., Results: Fused deposition modeling has turned out to be a suitable 3D printing technique for creating reference objects in 3D plant phenotyping. Production deviations of the created reference model were in a low and acceptable range. We were able to achieve deviations ranging from -10 mm to +5 mm. In parallel, we demonstrated a high-dimensional stability of the reference model, reaching only ±4 mm deformation over the course of 1 year. Detailed print files, assembly descriptions, and benchmark parameters are provided, facilitating replication and benefiting the research community., Conclusion: Consumer-grade 3D printing was utilized to create a stable and reproducible 3D reference model of a sugar beet plant, addressing challenges in referencing morphological parameters in 3D plant phenotyping. The reference model is applicable in 3 demonstrated use cases: evaluating and comparing 3D sensor systems, investigating the potential accuracy of parameter extraction algorithms, and continuously monitoring these algorithms in practical experiments in greenhouse and field experiments. Using this approach, it is possible to monitor the extraction of a nonverifiable parameter and create reference data. The process serves as a model for developing reference models for other agricultural crops., (© The Author(s) 2024. Published by Oxford University Press GigaScience.)

Accurately characterizing vineyard parameters is crucial for precise vineyard management and breeding purposes. Various macroscopic vineyard parameters are required to make informed management decisions, such as pesticide application, defoliation strategies, and determining optimal sugar content in each berry by assessing biomass. In this paper, we present a novel approach that utilizes point cloud data to detect trunk positions and extract macroscopic vineyard characteristics, including plant height, canopy width, and canopy volume. Our approach relies solely on geometric features and is compatible with different training systems and data collected using various 3D sensors. To evaluate the effectiveness and robustness of our proposed approach, we conducted extensive experiments on multiple grapevine rows trained in two different systems. Our method provides more comprehensive canopy characteristics than traditional manual measurements, which are not representative throughout the row. The experimental results demonstrate the accuracy and efficiency of our method in extracting vital macroscopic vineyard characteristics, providing valuable insights for yield monitoring, grape quality optimization, and strategic interventions to enhance vineyard productivity and sustainability., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Cantürk, Zabawa, Pavlic, Dreier, Klingbeil and Kuhlmann.)

Background: To present a retrospective study on the outcomes of a modified version of suture suspension arthroplasty with trapeziectomy on patients with thumb basal joint arthritis and to evaluate the relationship between the degree of subsidence and functional outcome. Methods: We performed a chart review on 67 patients (75 thumbs) who were surgically treated for thumb carpometacarpal osteoarthritis with trapeziectomy and suture suspension arthroplasty from May 2010 to May 2016. Outcome measures included Disabilities of the Arm, Shoulder and Hand (DASH), grip strength, lateral/precision pinch strength, range of motion, and return to work/resumption of usual activities. Radiographic images were used to measure first metacarpal subsidence into the trapezial space. Results: Clinical outcomes were satisfactory, showing an initial postoperative DASH score of 45.94, which decreased to 27.93 at 6 months postoperatively and to 19.69 at 1 year postoperatively. Radiographic images revealed a mean first metacarpal subsidence of 39% compared with the preoperative images. Grip and pinch strengths showed steady improvement from initial postoperative to final follow-up visits, resulting in 90% recovery of gross grasp, 77% recovery of lateral pinch, and 79% recovery of precision pinch compared with the contralateral side. Conclusions: Our study has found that suture suspension arthroplasty with trapeziectomy is an effective treatment for thumb basal joint arthritis. Suture suspension arthroplasty allows for short immobilization time, avoids tendon sacrifice, avoids anchor use, and leaves a cosmetically appealing scar. Furthermore, a relationship of any significance between postoperative first metacarpal subsidence and functional outcomes does not appear.

Case: A Salter-Harris II fracture of the small finger middle phalanx with complete extrusion of the epiphyseal fragment in a 6-year-old boy is described. Closed reduction was unsuccessful. Open reduction was performed, the epiphysis was reduced, and a single Kirschner wire was placed obliquely across the fracture and joint., Conclusion: This is an extremely rare injury. Open reduction and pinning was successful in preserving functional range of motion. Despite eventual growth arrest, there was no clinically significant angular deformity, and the joint was preserved. Surgical technique and early hand therapy allowed the patient to return to high-level activity without pain or functional limitation thus far at the 27-month follow-up., Competing Interests: Disclosure: The Disclosure of Potential Conflicts of Interest forms are provided with the online version of the article (http://links.lww.com/JBJSCC/B687)., (Copyright © 2021 by The Journal of Bone and Joint Surgery, Incorporated.)

Understanding the growth and development of individual plants is of central importance in modern agriculture, crop breeding, and crop science. To this end, using 3D data for plant analysis has gained attention over the last years. High-resolution point clouds offer the potential to derive a variety of plant traits, such as plant height, biomass, as well as the number and size of relevant plant organs. Periodically scanning the plants even allows for performing spatio-temporal growth analysis. However, highly accurate 3D point clouds from plants recorded at different growth stages are rare, and acquiring this kind of data is costly. Besides, advanced plant analysis methods from machine learning require annotated training data and thus generate intense manual labor before being able to perform an analysis. To address these issues, we present with this dataset paper a multi-temporal dataset featuring high-resolution registered point clouds of maize and tomato plants, which we manually labeled for computer vision tasks, such as for instance segmentation and 3D reconstruction, providing approximately 260 million labeled 3D points. To highlight the usability of the data and to provide baselines for other researchers, we show a variety of applications ranging from point cloud segmentation to non-rigid registration and surface reconstruction. We believe that our dataset will help to develop new algorithms to advance the research for plant phenotyping, 3D reconstruction, non-rigid registration, and deep learning on raw point clouds. The dataset is freely accessible at https://www.ipb.uni-bonn.de/data/pheno4d/., Competing Interests: The authors have declared that no competing interests exist.

Immersed tunnel elements need to be exactly controlled during their immersion process. Position and attitude of the element should be determined quickly and accurately to navigate the element from the holding area to the final location in the tunnel trench. In this paper, a newly-developed positioning and attitude determination system, integrating a 3-antenna Global Navigation Satellite System (GNSS) system, an inclinometer and a range-measurement system, is presented. The system is designed to provide the absolute position of both ends of the element with sufficient accuracy in real time. Special attention in the accuracy analysis is paid to the influence of GNSS multipath error and sound speed profile. Simulations are conducted to illustrate the performance of the system in different scenarios. If both elements are very close, the accuracies of the system are higher than 0.02 m in the directions perpendicular to and along the tunnel axis., Competing Interests: The authors declare no conflict of interest.

Background: To ensure further genetic gain, genomic approaches in plant breeding rely on precise phenotypic data, describing plant structure, function and performance. A more precise characterization of the environment will allow a better dealing with genotype-by-environment-by-management interactions. Therefore, space and time dependencies of the crop production processes have to be considered. The use of novel sensor technologies has drastically increased the amount and diversity of phenotypic data from agronomic field trials. Existing data management systems either do not consider space and time, are not customizable to individual needs such as field trial handling, or have restricted availability. Hence, we propose an integrative data management and information system (DMIS) for handling of traditional and novel sensor-based phenotypic, environmental and management data. The DMIS must be customizable, applicable and scalable from individual users to organizations., Results: Key element of the system is a dynamic PostgreSQL database with GIS-extension, capable of importing, storing and managing all types of data including images. The database references every structural database object and measurement in a threefold approach with semantic, spatial and temporal reference. Timestamps and geo-coordinates allow automated linking of all data. Traits can be precisely defined individually or uploaded as predefined lists. Filtering and selection routines allow compilation of all data for visualization via tables, charts or maps and for export and external statistical analysis. New possibilities of environmental information-based planning of field trials, weather-guided phenotyping and data analysis for outlier or hot-spot detection are demonstrated., Conclusions: The DMIS supports users in handling experimental field trials with crop plants and modern phenotyping methods. It focuses on linking all space and time dependent processes of plant production. Weather, soil and management, as well as growth and yield formation of the plants can be depicted, thus allowing a more precise interpretation of the results in relation to environment and management. Breeders, extension specialists, official testing agencies and agricultural scientists are assisted in all steps of a typical workflow with planning, designing, conducting, controlling and analyzing field trials to generate new information for decision support in the crop improvement process., Competing Interests: Competing interestsThe authors declare that they have no competing interests., (© The Author(s) 2020.)

GNSS (Global Navigation Satellite Systems) multipath has been subject to scientific research for decades and although numerous methods and techniques have already been developed to mitigate this effect, it is still one of the accuracy-limiting factors in many GNSS applications. Since multipath is highly dependent on the individual antenna environment, there is still a need for new methods and further investigations to increase the understanding of this systematic effect. In this paper, the concept of Fresnel zones is applied to two different aspects of multipath. First, Fresnel zones are determined for the line-of-sight transmission between satellite and receiver. By comparing the boundary of the Fresnel zones to an obstruction adaptive elevation mask, potentially diffracted signals can be identified and excluded from the position estimation process. Both the percentage of epochs with fixed ambiguities and the positioning accuracy can be increased by the proposed method. Second, Fresnel zones are used to analyze the multipath induced by a horizontal and spatially-limited reflector. The comparison of simulated and real signal-to-noise (SNR) observations reveals a relationship between the percentage of the overlap of the Fresnel zone and reflector and the occurrence of multipath. It is found that an overlap of 50% is sufficient to induce multipath effects. This is of special interest, since this does not confirm theoretical assumptions of the multipath theory.

In grapevine research the acquisition of phenotypic data is largely restricted to the field due to its perennial nature and size. The methodologies used to assess morphological traits and phenology are mainly limited to visual scoring. Some measurements for biotic and abiotic stress, as well as for quality assessments, are done by invasive measures. The new evolving sensor technologies provide the opportunity to perform non-destructive evaluations of phenotypic traits using different field phenotyping platforms. One of the biggest technical challenges for field phenotyping of grapevines are the varying light conditions and the background. In the present study the Phenoliner is presented, which represents a novel type of a robust field phenotyping platform. The vehicle is based on a grape harvester following the concept of a moveable tunnel. The tunnel it is equipped with different sensor systems (RGB and NIR camera system, hyperspectral camera, RTK-GPS, orientation sensor) and an artificial broadband light source. It is independent from external light conditions and in combination with artificial background, the Phenoliner enables standardised acquisition of high-quality, geo-referenced sensor data., Competing Interests: The authors declare no conflict of interest.

Background: Changes in three-dimensional (3D) measurements of neuroblastoma are used to assess response. Linear measurements may not accurately characterize tumor size due to the infiltrative character of these tumors. The purpose of this study was to assess the accuracy of one-dimensional (1D), two-dimensional (2D), and 3D measurements in characterizing neuroblastoma response compared to a reference standard of tumor volume., Procedure: We retrospectively reviewed imaging for 34 patients with stage 3 or 4 neuroblastoma. Blinded readers contoured or made linear measurements of tumors. Correlation coefficients were used to compare linear measurements to volumetric and 3D measurements. Bland-Altman analyses were used to assess bias between measurements. Sensitivity and specificity for patient events and survival were calculated for each measurement technique., Results: Mean patient age was 2.9 ± 3.0 years (range 0-15 years). There was strong correlation between volumetric and 1D (r = 0.78, P < 0.0001), 2D (r = 0.86, P < 0.0001), and 3D (r = 0.88, P < 0.0001) measurements. Mean bias between volumetric measurements and 1D, 2D, and 3D measurements was 37.1% (95% limits: 6.2-67.9%), 16.1% (95% limits: -11.7-43.8%), and 7.7% (95% limits: -19.7-35.1%), respectively. 1D and 2D measurements undercategorized response versus volumetric change in 88.2% (30/34) and 29.4% (10/34) of cases. 3D measurements incorrectly characterized response in 16.7% (4/24) of cases versus volumetric change. 3D measurements were highly sensitive for patient events and survival, but all measurement techniques had poor specificity., Conclusions: 3D measurements most accurately quantify neuroblastoma size response versus volumetric change in patients with stage 3 and 4 neuroblastoma. 1D and 2D measurements underrepresent tumor response., (© 2016 Wiley Periodicals, Inc.)

In viticulture, phenotypic data are traditionally collected directly in the field via visual and manual means by an experienced person. This approach is time consuming, subjective and prone to human errors. In recent years, research therefore has focused strongly on developing automated and non-invasive sensor-based methods to increase data acquisition speed, enhance measurement accuracy and objectivity and to reduce labor costs. While many 2D methods based on image processing have been proposed for field phenotyping, only a few 3D solutions are found in the literature. A track-driven vehicle consisting of a camera system, a real-time-kinematic GPS system for positioning, as well as hardware for vehicle control, image storage and acquisition is used to visually capture a whole vine row canopy with georeferenced RGB images. In the first post-processing step, these images were used within a multi-view-stereo software to reconstruct a textured 3D point cloud of the whole grapevine row. A classification algorithm is then used in the second step to automatically classify the raw point cloud data into the semantic plant components, grape bunches and canopy. In the third step, phenotypic data for the semantic objects is gathered using the classification results obtaining the quantity of grape bunches, berries and the berry diameter., Competing Interests: The authors declare no conflict of interests.

Acute mesenteric ischemia is associated with high morbidity and mortality. In recent studies, we found that the intestine is an important source of matrix metalloproteinase (MMP)8 during intestinal injury. We hypothesized that genetic ablation or pharmacological inhibition of MMP8 would reduce intestinal injury in mice subjected to intestinal ischemia-reperfusion (I/R) injury. Male mice aged 8-12 wk were subjected to intestinal I/R injury by transient occlusion of the superior mesenteric artery for 30 min. MMP8 was inhibited by genetic and pharmacological approaches. In vivo study endpoints included several functional, histological, and biochemical assays. Intestinal sections were assessed for barrier function and expression of tight junction proteins. I/R injury led to increased intestinal and systemic expression of MMP8. This increase was associated with increased intestinal neutrophil infiltration, epithelial injury, and permeability. I/R injury was associated with increased systemic inflammation and weight loss. These parameters were ameliorated by inhibiting MMP8. I/R injury caused a loss of the tight junction protein claudin-3, which was ameliorated by genetic ablation of MMP8. MMP8 plays an important role in intestinal I/R injury through mechanisms involving increased inflammation and loss of claudin-3. Inhibition of MMP8 is a potential therapeutic strategy in this setting.-Daly, M. C., Atkinson, S. J., Varisco, B. M., Klingbeil L., Hake, P., Lahni, P., Piraino, G., Wu, D., Hogan, S. P., Zingarelli, B., Wong, H. R. Role of matrix metalloproteinase-8 as a mediator of injury in intestinal ischemia and reperfusion., (© FASEB.)

Genetic ablation or pharmacologic inhibition of matrix metalloproteinase-8 ( MMP8 ) improves survival in an adult murine sepsis model. Because developmental age influences the host inflammatory response, we hypothesized that developmental age influences the role of MMP8 in sepsis. First, we compared sepsis survival between wild type (WT, C57BL/6) and MMP8 null juvenile-aged mice (12-14 days) after intraperitoneal injection of a standardized cecal slurry. Second, peritoneal lavages collected at 6 and 18 hours after cecal slurry injection were analyzed for bacterial burden, leukocyte subsets, and inflammatory cytokines. Third, juvenile WT mice were pretreated with an MMP8 inhibitor prior to cecal slurry injection; analysis of their bacterial burden was compared to vehicle-injected animals. Fourth, the phagocytic capacity of WT and MMP8 null peritoneal macrophages was compared. Finally, peritoneal neutrophil extracellular traps (NETs) were compared using immunofluorescent imaging and quantitative image analysis. We found that juvenile MMP8 null mice had greater mortality and higher bacterial burden than WT mice. Leukocyte counts and cytokine concentrations in the peritoneal fluid were increased in the MMP8 null mice, relative to the wild type mice. Peritoneal macrophages from MMP8 null mice had reduced phagocytic capacity compared to WT macrophages. There was no quantitative difference in NET formation, but fewer bacteria were adherent to NETs from MMP8 null animals. In conclusion, in contrast to septic adult mice, genetic ablation of MMP8 increased mortality following bacterial peritonitis in juvenile mice. The increase in mortality in MMP8 null juvenile mice was associated with reduced bacterial clearance and reduced NET efficiency. We conclude that developmental age influences the role of MMP8 in sepsis.

Objective: Inhibition of matrix metalloproteinase-8 improves survival following cecal ligation and puncture in mice, making it a potential therapeutic target. In the current study, we expand our understanding of the role of matrix metalloproteinase-8 in sepsis by using an adoptive transfer approach and alternative sepsis models., Design: We used three different sepsis models: cecal ligation and puncture, cecal slurry, and intestinal implantation. In our first model, adoptive transfer experiments were followed by cecal ligation and puncture to test the hypothesis that matrix metalloproteinase-8-containing myeloid cells are a critical factor in sepsis following cecal ligation and puncture. Our second model, cecal slurry, used intraperitoneal injections of cecal contents to induce polymicrobial peritonitis without tissue compromise in the recipient. Our third model, intestinal implantation, involved ligating and puncturing a cecum from a donor, and then removing the cecum and placing it into the recipient's peritoneal cavity. Clinically, blood samples were drawn from pediatric patients within 24 hours of meeting criteria for septic shock., Setting: Basic science laboratory., Subjects: Wild type and genetically modified mice., Interventions: Experimental models of sepsis., Measurements and Main Results: In our adoptive transfer experiments, matrix metalloproteinase-8 null mice receiving wild-type marrow had a survival advantage when compared with wild-type mice receiving matrix metalloproteinase-8 null marrow, suggesting that matrix metalloproteinase-8-containing myeloid cells are not a critical factor in sepsis following cecal ligation and puncture. In our cecal slurry model, no survival advantage was seen among matrix metalloproteinase-8 null mice. Our third model, intestinal implantation, found that mice receiving matrix metalloproteinase-8 null intestine had a survival advantage when compared with mice receiving wild-type intestine, regardless of recipient genotype. Clinically, median matrix metalloproteinase-8 serum concentrations were higher in patients with sepsis and primary intestinal pathology than in septic patients without primary intestinal pathology., Conclusions: Intestine-derived matrix metalloproteinase-8 is a critical component of septic peritonitis secondary to intestinal compromise.

Background: Coronary artery bypass grafting with aortic valve replacement (AVR) or mitral valve replacement (MVR) is traditionally performed via sternotomy. Minimally invasive coronary surgery (MICS) and minimally invasive valve surgery have been successfully performed independently. Patients with critical right coronary artery (RCA) stenosis not amenable to percutaneous intervention are candidates for valve replacement and single vessel coronary artery bypass. We present our series of six patients who underwent a concomitant valve and single vessel intervention via right thoracotomy., Methods: Between January 2011 and June 2013, six patients underwent right thoracotomy with valve replacement and single vessel bypass. Four aortic and two mitral valves were replaced and all received single vessel RCA bypass using reversed saphenous vein graft. Thoracotomy was via right anterior approach for AVR and right lateral for MVR. The patients were assessed postoperatively for overall outcomes., Results: The average age was 74 years (range 69-81); two patients were elective (AVR-1; MVR-1) and four were urgent (AVR-3; MVR-1). For MICS AVR and MICS MVR, the average cardiopulmonary bypass time was 171 ± 30 and 169 ± 7 minutes and the average aortic cross-clamp time was 122 ± 36 and 112 ± 2 minutes, respectively. Three patients were discharged home, one patient to a nursing home, and two to rehab. No patients required conversion to sternotomy; one patient developed atrial fibrillation, and one sepsis., Conclusion: Concomitant valve replacement and single bypass grafting via right anterior mini-thoracotomy is a viable option for select patients, particularly in non-stentable RCA stenosis. In the appropriate patient population, combined coronary artery bypass grafting and valve surgery can be safely performed via right thoracotomy.

In this paper, a newly-developed direct georeferencing system for the guidance, navigation and control of lightweight unmanned aerial vehicles (UAVs), having a weight limit of 5 kg and a size limit of 1.5 m, and for UAV-based surveying and remote sensing applications is presented. The system is intended to provide highly accurate positions and attitudes (better than 5 cm and 0.5°) in real time, using lightweight components. The main focus of this paper is on the attitude determination with the system. This attitude determination is based on an onboard single-frequency GPS baseline, MEMS (micro-electro-mechanical systems) inertial sensor readings, magnetic field observations and a 3D position measurement. All of this information is integrated in a sixteen-state error space Kalman filter. Special attention in the algorithm development is paid to the carrier phase ambiguity resolution of the single-frequency GPS baseline observations. We aim at a reliable and instantaneous ambiguity resolution, since the system is used in urban areas, where frequent losses of the GPS signal lock occur and the GPS measurement conditions are challenging. Flight tests and a comparison to a navigation-grade inertial navigation system illustrate the performance of the developed system in dynamic situations. Evaluations show that the accuracies of the system are 0.05° for the roll and the pitch angle and 0.2° for the yaw angle. The ambiguities of the single-frequency GPS baseline can be resolved instantaneously in more than 90% of the cases.

RT-PCR and DNA microarrays were used to probe for Zn(II)-responsive genes in E. coli cells that were made Zn(II) deficient. Microarray data revealed 114 genes were significantly up-regulated and 146 genes were significantly down-regulated in Zn(II) deficient conditions. The three most up-regulated genes were (1) znuA, which encodes for a periplasmic protein known to be involved with Zn(II) import, (2) yodA, which encodes for a periplasmic protein with unknown function, and (3) ykgM, which encodes for a ribosomal protein that is thought to be a paralog of ribosomal protein L31. YodA was over-expressed and purified as a maltose binding protein (MBP) fusion protein and shown to tightly bind 4 equivalents of Zn(II). Metal analyses showed that MBP-YkgM does not bind Zn(II). On the other hand, MBP-L31 tightly binds 1 equivalent of Zn(II). EXAFS studies on MBP-L31 suggest a ligand field of 1 histidine, 1 cysteine, and 2 additional N/O scatterers. Site-directed mutagenesis studies suggest that Cys16 coordinates Zn(II) in MBP-L31 and that the other three cysteines do not bind metal. These results are discussed in light of Zn(II) starvation model that has been postulated for B. subtilis., (Copyright © 2011 Elsevier Inc. All rights reserved.)

The ability to rise from a chair is considered to be important to achieve functional independence and quality of life. This sit-to-stand task is also a good indicator to assess condition of patients with chronic diseases. We developed a wavelet based algorithm for detecting and calculating the durations of sit-to-stand and stand-to-sit transitions from the signal vector magnitude of the measured acceleration signal. The algorithm was tested on waist worn accelerometer data collected from young subjects as well as geriatric patients. The test demonstrates that both transitions can be detected by using wavelet transformation applied to signal magnitude vector. Wavelet analysis produces an estimate of the transition pattern that can be used to calculate the transition duration that further gives clinically significant information on the patients condition. The method can be applied in a real life ambulatory monitoring system for assessing the condition of a patient living at home.