Validity and value of metabolic connectivity in mouse models of β-amyloid and tauopathy

Among functional imaging methods, metabolic connectivity (MC) is increasingly used for investigation of regional network changes to examine the pathophysiology of neurodegenerative diseases such as Alzheimer's disease (AD) or movement disorders. Hitherto, MC was mostly used in clinical studies, but only a few studies demonstrated the usefulness of MC in the rodent brain. The goal of the current work was to analyze and validate metabolic regional network alterations in three different mouse models of neurodegenerative diseases (β-amyloid and tau) by use of 2-deoxy-2-[18F]fluoro-d-glucose positron emission tomography (FDG-PET) imaging. We compared the results of FDG-µPET MC with conventional VOI-based analysis and behavioral assessment in the Morris water maze (MWM). The impact of awake versus anesthesia conditions on MC read-outs was studied and the robustness of MC data deriving from different scanners was tested. MC proved to be an accurate and robust indicator of functional connectivity loss when sample sizes ≥12 were considered. MC readouts were robust across scanners and in awake/ anesthesia conditions. MC loss was observed throughout all brain regions in tauopathy mice, whereas β-amyloid indicated MC loss mainly in spatial learning areas and subcortical networks. This study established a methodological basis for the utilization of MC in different β-amyloid and tau mouse models. MC has the potential to serve as a read-out of pathological changes within neuronal networks in these models.

Exploration and Gas Source Localization in Advection-Diffusion Processes with Potential-Field-Controlled Robotic Swarms

Mobile multi-robot systems are well suited for gas leak localization in challenging environments. They offer inherent advantages such as redundancy, scalability, and resilience to hazardous environments, all while enabling autonomous operation, which is key to efficient swarm exploration. To efficiently localize gas sources using concentration measurements, robots need to seek out informative sampling locations. For this, domain knowledge needs to be incorporated into their exploration strategy. We achieve this by means of partial differential equations incorporated into a probabilistic gas dispersion model that is used to generate a spatial uncertainty map of process parameters. Previously, we presented a potential-field-control approach for navigation based on this map. We build upon this work by considering a more realistic gas dispersion model, now taking into account the mechanism of advection, and dynamics of the gas concentration field. The proposed extension is evaluated through extensive simulations. We find that introducing fluctuations in the wind direction makes source localization a fundamentally harder problem to solve. Nevertheless, the proposed approach can recover the gas source distribution and compete with a systematic sampling strategy. The estimator we present in this work is able to robustly recover source candidates within only a few seconds. Larger swarms are able to reduce total uncertainty faster. Our findings emphasize the applicability and robustness of robotic swarm exploration in dynamic and challenging environments for tasks such as gas source localization.

Depletion and activation of microglia impact metabolic connectivity of the mouse brain

AIM

We aimed to investigate the impact of microglial activity and microglial FDG uptake on metabolic connectivity, since microglial activation states determine FDG-PET alterations. Metabolic connectivity refers to a concept of interacting metabolic brain regions and receives growing interest in approaching complex cerebral metabolic networks in neurodegenerative diseases. However, underlying sources of metabolic connectivity remain to be elucidated.

MATERIALS AND METHODS

We analyzed metabolic networks measured by interregional correlation coefficients (ICCs) of FDG-PET scans in WT mice and in mice with mutations in progranulin (Grn) or triggering receptor expressed on myeloid cells 2 (Trem2) knockouts (^-/-) as well as in double mutant Grn^-/-/Trem2^-/- mice. We selected those rodent models as they represent opposite microglial signatures with disease associated microglia in Grn^-/- mice and microglia locked in a homeostatic state in Trem2^-/- mice; however, both resulting in lower glucose uptake of the brain. The direct influence of microglia on metabolic networks was further determined by microglia depletion using a CSF1R inhibitor in WT mice at two different ages. Within maps of global mean scaled regional FDG uptake, 24 pre-established volumes of interest were applied and assigned to either cortical or subcortical networks. ICCs of all region pairs were calculated and z-transformed prior to group comparisons. FDG uptake of neurons, microglia, and astrocytes was determined in Grn^-/- and WT mice via assessment of single cell tracer uptake (scRadiotracing).

RESULTS

Microglia depletion by CSF1R inhibition resulted in a strong decrease of metabolic connectivity defined by decrease of mean cortical ICCs in WT mice at both ages studied (6-7 m; p = 0.0148, 9-10 m; p = 0.0191), when compared to vehicle-treated age-matched WT mice. Grn^-/-, Trem2^-/- and Grn^-/-/Trem2^-/- mice all displayed reduced FDG-PET signals when compared to WT mice. However, when analyzing metabolic networks, a distinct increase of ICCs was observed in Grn^-/- mice when compared to WT mice in cortical (p < 0.0001) and hippocampal (p < 0.0001) networks. In contrast, Trem2^-/- mice did not show significant alterations in metabolic connectivity when compared to WT. Furthermore, the increased metabolic connectivity in Grn^-/- mice was completely suppressed in Grn^-/-/Trem2^-/- mice. Grn^-/- mice exhibited a severe loss of neuronal FDG uptake (- 61%, p < 0.0001) which shifted allocation of cellular brain FDG uptake to microglia (42% in Grn^-/- vs. 22% in WT).

CONCLUSIONS

Presence, absence, and activation of microglia have a strong impact on metabolic connectivity of the mouse brain. Enhanced metabolic connectivity is associated with increased microglial FDG allocation.

Microglial activation states drive glucose uptake and FDG-PET alterations in neurodegenerative diseases

2-Deoxy-2-[18F]fluoro-d-glucose positron emission tomography (FDG-PET) is widely used to study cerebral glucose metabolism. Here, we investigated whether the FDG-PET signal is directly influenced by microglial glucose uptake in mouse models and patients with neurodegenerative diseases. Using a recently developed approach for cell sorting after FDG injection, we found that, at cellular resolution, microglia displayed higher glucose uptake than neurons and astrocytes. Alterations in microglial glucose uptake were responsible for both the FDG-PET signal decrease in Trem2-deficient mice and the FDG-PET signal increase in mouse models for amyloidosis. Thus, opposite microglial activation states determine the differential FDG uptake. Consistently, 12 patients with Alzheimer’s disease and 21 patients with four-repeat tauopathies also exhibited a positive association between glucose uptake and microglial activity as determined by 18F-GE-180 18-kDa translocator protein PET (TSPO-PET) in preserved brain regions, indicating that the cerebral glucose uptake in humans is also strongly influenced by microglial activity. Our findings suggest that microglia activation states are responsible for FDG-PET signal alterations in patients with neurodegenerative diseases and mouse models for amyloidosis. Microglial activation states should therefore be considered when performing FDG-PET.

Beehive-Inspired Information Gathering with a Swarm of Autonomous Drones

This paper presents a beehive-inspired multi-agent drone system for autonomous information collection to support the needs of first responders and emergency teams. The proposed system is designed to be simple, cost-efficient, yet robust and scalable at the same time. It includes several unmanned aerial vehicles (UAVs) that can be tasked with data collection, and a single control station that acts as a data accumulation and visualization unit. The system also provides a local communication access point for the UAVs to exchange information and coordinate the data collection routes. By avoiding peer-to-peer communication and using proactive collision avoidance and path-planning, the payload weight and per-drone costs can be significantly reduced; the whole concept can be implemented using inexpensive off-the-shelf components. Moreover, the proposed concept can be used with different sensors and types of UAVs. As such, it is suited for local-area operations, but also for large-scale information-gathering scenarios. The paper outlines the details of the system hardware and software design, and discusses experimental results for collecting image information with a set of 4 multirotor UAVs at a small experimental area. The obtained results validate the concept and demonstrate robustness and scalability of the system.

Multi-Domain Airflow Modeling and Ventilation Characterization Using Mobile Robots, Stationary Sensors and Machine Learning

Ventilation systems are critically important components of many public buildings and workspaces. Proper ventilation is often crucial for preventing accidents, such as explosions in mines and avoiding health issues, for example, through long-term exposure to harmful respirable matter. Validation and maintenance of ventilation systems is thus of key interest for plant operators and authorities. However, methods for ventilation characterization, which allow us to monitor whether the ventilation system in place works as desired, hardly exist. This article addresses the critical challenge of ventilation characterization—measuring and modelling air flow at micro-scales—that is, creating a high-resolution model of wind speed and direction from airflow measurements. Models of the near-surface micro-scale flow fields are not only useful for ventilation characterization, but they also provide critical information for planning energy-efficient paths for aerial robots and many applications in mobile robot olfaction. In this article we propose a heterogeneous measurement system composed of static, continuously sampling sensing nodes, complemented by localized measurements, collected during occasional sensing missions with a mobile robot. We introduce a novel, data-driven, multi-domain airflow modelling algorithm that estimates (1) fields of posterior distributions over wind direction and speed (“ventilation maps”, spatial domain); (2) sets of ventilation calendars that capture the evolution of important airflow characteristics at measurement positions (temporal domain); and (3) a frequency domain analysis that can reveal periodic changes of airflow in the environment. The ventilation map and the ventilation calendars make use of an improved estimation pipeline that incorporates a wind sensor model and a transition model to better filter out sporadic, noisy airflow changes. These sudden changes may originate from turbulence or irregular activity in the surveyed environment and can, therefore, disturb modelling of the relevant airflow patterns. We tested the proposed multi-domain airflow modelling approach with simulated data and with experiments in a semi-controlled environment and present results that verify the accuracy of our approach and its sensitivity to different turbulence levels and other disturbances. Finally, we deployed the proposed system in two different real-world industrial environments (foundry halls) with different ventilation regimes for three weeks during full operation. Since airflow ground truth cannot be obtained, we present a qualitative discussion of the generated airflow models with plant operators, who concluded that the computed models accurately depicted the expected airflow patterns and are useful to understand how pollutants spread in the work environment. This analysis may then provide the basis for decisions about corrective actions to avoid long-term exposure of workers to harmful respirable matter.

Analysis of Model Mismatch Effects for a Model-Based Gas Source Localization Strategy Incorporating Advection Knowledge

In disaster scenarios, where toxic material is leaking, gas source localization is a common but also dangerous task. To reduce threats for human operators, we propose an intelligent sampling strategy that enables a multi-robot system to autonomously localize unknown gas sources based on gas concentration measurements. This paper discusses a probabilistic, model-based approach for incorporating physical process knowledge into the sampling strategy. We model the spatial and temporal dynamics of the gas dispersion with a partial differential equation that accounts for diffusion and advection effects. We consider the exact number of sources as unknown, but assume that gas sources are sparsely distributed. To incorporate the sparsity assumption we make use of sparse Bayesian learning techniques. Probabilistic modeling can account for possible model mismatch effects that otherwise can undermine the performance of deterministic methods. In the paper we evaluate the proposed gas source localization strategy in simulations using synthetic data. Compared to real-world experiments, a simulated environment provides us with ground truth data and reproducibility necessary to get a deeper insight into the proposed strategy. The investigation shows that (i) the probabilistic model can compensate imperfect modeling; (ii) the sparsity assumption significantly accelerates the source localization; and (iii) a-priori advection knowledge is of advantage for source localization, however, it is only required to have a certain level of accuracy. These findings will help in the future to parameterize the proposed algorithm in real world applications.

On the Necessity of Systematically Planning Clinical Tumor Documentation

Tumor documentation is an important task for both clinical research and patient care. Documentation systems for these purposes have to be planned systematically and should be goal oriented. We applied the method of a so-called ‘standardized documentation protocol’ for systematically planning two documentation systems in oncology: one for the tumor center Heidelberg/Mannheim and the other for a nationwide project in the field of documentation and therapy planning in pediatric oncology. The method proved to be helpful in both cases even though the resulting documentation protocols are completely different and although they served different objectives. Therefore, the aim of the paper is to motivate and help medical informatics professionals to systematically plan other documentation systems using this method.

Object-oriented business process analysis of the cooperative soft tissue sarcoma trial of the german society for paediatric oncology and haematology (GPOH)

The German Society for Paediatric Oncology and Haematology (GPOH) runs nation-wide multicentre clinical trials to improve the treatment of children suffering from malignant diseases. We want to provide methods and tools to support the centres of these trials in developing trial specific modules for the computer-based DOcumentation System for Paediatric Oncology (DOSPO). For this we carried out an object-oriented business process analysis for the Cooperative Soft Tissue Sarcoma Trial at the Olgahospital Stuttgart for Child and Adolescent Medicine. The result is a comprehensive business process model consisting of UML-diagrams and use case specifications. We recommend the object-oriented business process analysis as a method for the definition of requirements in information processing projects in the field of clinical trials in general. For this our model can serve as basis because it slightly can be adjusted to each type of clinical trial.

On the necessity of systematically planning clinical tumor documentation

Tumor documentation is an important task for both clinical research and patient care. Documentation systems for these purposes have to be planned systematically and should be goal oriented. We applied the method of a so-called 'standardized documentation protocol' for systematically planning two documentation systems in oncology: one for the tumor center Heidelberg/Mannheim and the other for a nationwide project in the field of documentation and therapy planning in pediatric oncology. The method proved to be helpful in both cases even though the resulting documentation protocols are completely different and although they served different objectives. Therefore, the aim of the paper is to motivate and help medical informatics professionals to systematically plan other documentation systems using this method.

Requirements and design aspects of a data model for a data dictionary in paediatric oncology

German children suffering from cancer are mostly treated within the framework of multicentre clinical trials. An important task of conducting these trials is an extensive information and knowledge exchange, which has to be based on a standardised documentation. To support this effort, it is the aim of a nationwide project to define a standardised terminology that should be used by clinical trials for therapy documentation. In order to support terminology maintenance we are currently developing a data dictionary. In this paper we describe requirements and design aspects of the data model used for the data dictionary as first results of our research. We compare it with other terminology systems.

Integrating specialized application systems into hospital information systems--obstacles and factors for success

Hospital information systems are often huge and heterogeneous systems. To support physicians with their daily clinical work, application systems are developed which are dedicated to particular medical fields or tasks and which have to be integrated into the hospital information system. The integration process is quite complicated, because it makes the information system's infrastructure even more heterogeneous. We developed an application system for documentation and therapy planning in pediatric oncology (DOSPO) and we started to introduce it into the Department of Pediatric Oncology of Heidelberg University Hospital. The fact that DOSPO is developed as a universal system for nationwide use made the integration process more difficult. In any case, the introduction of specialized application systems has to be planned systematically in advance, regarding the prevailing information system's infrastructure, available resources and established processes. To simplify the integration process comprehensive electronic patient records for the future should be designed in a way that they can be enhanced easily by new clinical functions.

Recording clinical data--from a general set of record items to case report forms (CRF) for clinics

Standardising a documentary language makes only sense if we use it for documentation consequently. Using an example of Paediatric Oncology in Germany we have developed a procedure that generates CRFs from a documentary language. The introduced procedure has proved to be feasible in practice. With it we can support developers of documentation systems in creating their CRFs; through the guaranteed use of the documentation terminology we further achieve that information recorded with the created CRFs may be statistically analysed across different institutions.

Cox-2 and osteopontin in cocultured platelets and mesangial cells: role of glucocorticoids

BACKGROUND

Glomerular inflammation is characterized by a consecutive infiltration of immunoreactive cells. To mimic the early phase of glomerular injury, a coculture system of platelets and rat renal mesangial cells was established. As prototypes, the inflammation-related proteins cyclooxygenase-2 (Cox-2) and the chemotactic protein osteopontin (OPN) were investigated.

METHODS

The expression of OPN and Cox-2 mRNA and protein was determined by Northern and Western blot analyses.

RESULTS

Coincubation of platelets and mesangial cells led to a rapid, transient induction of Cox-2 mRNA, which peaked at two hours, whereas OPN and monocyte chemoattractant protein-1 (MCP-1) were induced at later time points. The induction of Cox-2 mRNA was concentration dependent and highly reproducible when platelets of different donors were investigated. Partial Cox-2 induction was observed when supernatants of preactivated platelets were incubated with mesangial cells. The inhibition of the signaling pathways of platelet-derived growth factor (PDGF) and epidermal growth factor (EGF) or interference with Gi-protein signaling partially inhibited platelet-induced Cox-2 expression. Down-regulation of protein kinase C (PKC), which is a common signaling module in many pathways leading to Cox-2 induction, almost completely abrogated platelet-induced Cox-2 expression. The time pattern of Cox-2 and OPN expression suggested that Cox-2 might play a role in OPN induction. The up-regulation of OPN was dependent on de novo protein synthesis and was induced by high levels of exogenous prostaglandin E2 (PGE2; 10 micromol/L). Endogenous PGE2, however, proved not to be essential for OPN mRNA expression, because inhibition of Cox activity did not change OPN mRNA levels. Dexamethasone inhibited Cox-2 mRNA induction but increased OPN mRNA and protein expression.

CONCLUSION

These data indicate that Cox-2 and OPN are independently up-regulated upon interaction of platelets and mesangial cells.

[Computer-assisted documentation and therapy planning in pediatric oncology--introduction of a nationwide solution]

In Pediatric Oncology in Germany, 90% of the patients are treated according to multicenter clinical trials, which means an enormous effort for documentation in the participating clinics. In order to enable multiple use of data for patient records as well as for clinical trials a computer-based documentation system for pediatric oncology (DOSPO) is being developed, which can be used nationwide. DOSPO currently comprises a minimum basic data set, which represents the common core of all multicenter trials and which has been approved by the German Society for Pediatric Oncology and Hematology (GPOH). It is intended to enhance the documentation by specific items of each clinical trial. Functions for computer-aided chemotherapy planning and medical report writing have already been implemented in the documentation system. Various centers in Germany are currently validating the system in routine use.

Computer-aided documentation and therapy planning in pediatric oncology

In the past 20 years considerable progress was made in pediatric oncology concerning the results of therapy in Germany. Nationwide multicentre trials provide protocols for the therapy of the children. The calculation of the chemotherapy according to the protocols is rather complex and the documentation efforts for the pediatricians are enormous. Thus, we developed as a first step an application system for Computer Aided Therapy Planning In Pediatric Oncology (CATIPO), that is in routine use in about 20 pediatric clinics in Germany. In order to support the physician comprehensively with the documentation that is necessary for the trials we currently develop a Documentation System for Pediatric Oncology (DOSPO) that comprises the functionality of chemotherapy planning according to the protocols released by the trial centres. Besides supporting the physician in clinical routine the major objective is to improve the quality of the documented data. To reach this aims DOSPO combines research aspects of decision support and clinical documentation: formal representation of general protocols, calculating of a particular therapy for a patient, data acquisition, communication interfaces for transferring the data to the trial centres. In order to support trial centres an authoring system and a central data dictionary will be developed. This will enable the trial centres to develop new modules for trial-specific data acquisition in the clinics.