Validity and value of metabolic connectivity in mouse models of ß-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 (ß-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 ß-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 ß-amyloid and tau mouse models. MC has the potential to serve as a read-out of pathological changes within neuronal networks in these models.

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.

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.

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.

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 vehicle (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.

Control of Chain Walking by Weak Neighboring Group Interactions in Unsymmetrical Catalysts.

A combined theoretical and experimental study shows how weak attractive interactions of a neighboring group can strongly promote chain walking and chain transfer. This accounts for the previously observed very different microstructures obtained in ethylene polymerization by [κ2-N,O-{2,6-(3',5'-R2C6H3)2C6H3-N═C(H)-(3,5-X,Y-2-O-C6H2)}NiCH3(pyridine)], namely hyperbranched oligomers for remote substituents R = CH3 versus high-molecular-weight polyethylene for R = CF3. From a full mechanistic consideration, the alkyl olefin complex with the growing chain cis to the salicylaldiminato oxygen donor is identified as the key species. Alternative to ethylene chain growth by insertion in this species, decoordination of the monomer to form a cis ß-agostic complex provides an entry into branching and chain-transfer pathways. This release of monomer is promoted and made competitive by a weak η2-coordination of the distal aryl rings to the metal center, operative only for the case of sufficiently electron-rich aryls. This concept for controlling chain walking is underlined by catalysts with other weakly coordinating furan and thiophene motifs, which afford highly branched oligomers with >120 branches per 1000 carbon atoms.

Monofunctional hyperbranched ethylene oligomers.

The neutral κ(2)N,O-salicylaldiminato Ni(II) complexes [κ(2)N,O-{(2,6-(3',5'-R2C6H3)2C6H3-N═C(H)-(3,5-I2-2-O-C6H2)}]NiCH3(pyridine)] (1a-pyr, R = Me; 1b-pyr, R = Et; 1c-pyr, R = iPr) convert ethylene to hyperbranched low-molecular-weight oligomers (Mn ca. 1000 g mol(-1)) with high productivities. While all three catalysts are capable of generating hyperbranched structures, branching densities decrease significantly with the nature of the remote substituent along Me > Et > iPr and oligomer molecular weights increase. Consequently, only 1a-pyr forms hyperbranched structures over a wide range of reaction conditions (ethylene pressure 5-30 atm and 20-70 °C). An in situ catalyst system achieves similar activities and identical highly branched oligomer microstructures, eliminating the bottleneck given by the preparation and isolation of Ni-Me catalyst precursor species. Selective introduction of one primary carboxylic acid ester functional group per highly branched oligoethylene molecule was achieved by isomerizing ethoxycarbonylation and alternatively cross metathesis with ethyl acrylate followed by hydrogenation. The latter approach results in complete functionalization and no essential loss of branched oligomer material and molecular weight, as the reacting double bonds are close to a chain end. Reduction yielded a monoalcohol-functionalized oligomer. Introduction of one reactive epoxide group per branched oligomer occurs completely and selectively under mild conditions. All reaction steps involved in oligomerization and monofunctionalization are efficient and readily scalable.

Comparison of Zirconia Implant Surface Modifications for Optimal Osseointegration.

Zirconia ceramic implants are commercially available from a rapidly growing number of manufacturers. Macroscopic and microscopic surface design and characteristics are considered to be key determining factors in the success of the osseointegration process. It is, therefore, crucial to assess which surface modification promotes the most favorable biological response. The purpose of this study was to conduct a comparison of modern surface modifications that are featured in the most common commercially available zirconia ceramic implant systems. A review of the currently available literature on zirconia implant surface topography and the associated bio-physical factors was conducted, with a focus on the osseointegration of zirconia surfaces. After a review of the selected articles for this study, commercially available zirconia implant surfaces were all modified using subtractive protocols. Commercially available ceramic implant surfaces were modified or enhanced using sandblasting, acid etching, laser etching, or combinations of the aforementioned. From our literature review, laser-modified surfaces emerged as the ones with the highest surface roughness and bone-implant contact (BIC). It was also found that surface roughness could be controlled to achieve optimal roughness by modifying the laser output power during manufacturing. Furthermore, laser surface modification induced a very low amount of preload microcracks in the zirconia. Osteopontin (OPN), an early-late osteogenic differentiation marker, was significantly upregulated in laser-treated surfaces. Moreover, surface wettability was highest in laser-treated surfaces, indicating favorable hydrophilicity and thus promoting early bone forming, cell adhesion, and subsequent maturation. Sandblasting followed by laser modification and sandblasting followed by acid etching and post-milling heat treatment (SE-H) surfaces featured comparable results, with favorable biological responses around zirconia implants.

Clinical Dilemmas in the Differential Diagnosis of Peri-implantitis: Case Presentation and Literature Review.

Advancements in the field of implantology have made dental implants a mainstay treatment for both fully and partially edentulous patients. As a result, practitioners need to be able to identify clinical signs of peri-implant disease in its early stages and provide patients with reliable treatment options. The objective of this article is to provide a differential diagnosis of peri-implant lesions, outlining the clinical, radiographic, and histopathologic features of similar benign and malignant conditions. Additionally, two case studies are presented that showcase lesions that mimic peri-implantitis, providing practitioners with practical examples of how to apply the discussed features in a clinical setting. Lesions described in the differential diagnosis include physiologic bone loss, implant fracture, loosened abutments, pyogenic granuloma, peripheral giant cell granuloma, peripheral ossifying fibroma, squamous cell carcinoma, and metastasis extending to the oral cavity.

Graftless Implantology as a Forward-Looking Clinical Concept for Highly Atrophic Maxillary Arches.

For many decades the success of dental implants has been considered to be dependent predominantly on the quality and quantity of the patient's alveolar bone. Building on the high success rates of implants, bone grafting eventually was implemented, allowing patients with insufficient bone volume to obtain implant-supported prosthetic solutions for treatment of partial or complete edentulism. Extensive bone grafting procedures have been commonly used to rehabilitate severely atrophic arches but are associated with long treatment times, unpredictability, and donor site morbidity. More recently, nongrafting solutions that maximally utilize the residual highly atrophic alveolar or extra-alveolar bone for implant therapy have been reported to have success. The emergence of diagnostic imaging and 3D printing technology has allowed clinicians to provide individualized, subperiosteal implants that can adapt precisely to the patient's remaining alveolar bone. Furthermore, paranasal, pterygoid, and zygomatic implants that utilize the patient's extraoral facial bone outside the alveolar process can provide predictable and optimal results with no or minimal bone grafting with less treatment time. This article considers and evaluates the rationale for graftless solutions in implant therapy as well as the data supporting the use of various graftless protocols as alternatives to grafting and conventional dental implant therapy.

Esthetic Considerations In Minimally Invasive Orthognathic Surgery.

The success of dental implants has long been considered to be dependent primarily on the quality and quantity of alveolar bone. Bone grafting allows patients with insufficient bone volume to obtain implant-supported prosthetic solutions for treatment of edentulism. While extensive bone grafting procedures have been commonly used to rehabilitate severely atrophic arches, they can be associated with long treatment times, unpredictability, and donor site morbidity. Nongrafting solutions have more recently been employed that maximally utilize the residual highly atrophic alveolar or extra-alveolar bone for implant therapy. With the use of modern diagnostic imaging and 3D printing technology, clinicians are able to provide individualized, subperiosteal implants that fully adapt to the patient's remaining alveolar bone. Other "graftless" implants, including zygomatic implants, utilize the patient's extraoral facial bone outside the alveolar process and have been shown to provide predictable results. This article discusses the rationale for graftless solutions in implant therapy and the data supporting the use of various graftless protocols as alternatives to grafting and conventional dental implant therapy.

OsteoMacs and Their Role in Early Implant Failure and Osseointegration.

Dental implant failure cannot always be explained by clinical risk factors. Recent literature suggests that immune cells are pivotal players in the integration of biomaterials and have a co-relationship within a set of osteal macrophages known as "OsteoMacs." These cells have been known to polarize quickly between a M1 pro-inflammatory and a M2 wound healing state during implant osseointegration. OsteoMacs play a critical immune surveillance role in the osseointegration of dental implant healing and bone homeostasis. This review is intended to provide an overview of the current understanding of OsteoMacs and their role in early implant failure and osseointegration.

A Clinical Approach to Treatment of Retrograde Peri-Implantitis.

Retrograde peri-implantitis (RPI) is a primary microbial inflammatory condition that affects only the apical portion of an osseointegrated implant, which retains normal bone-to-implant contact in its coronal portion. Currently, no uniformly accepted definition or classification exists for RPI. This article reviews the etiopathological mechanisms, diagnostic pattern, and current treatment modalities for this type of periapical implant bone loss. The prevalence of RPI is reported to be relatively low, and along with a lack of an accepted classification system there is no widely accepted treatment algorithm. Therapeutic options include antibiotics, open-flap implant debridement, and apical resection eventually including apicoectomy of endodontically affected adjacent teeth, with or without bone grafting or removal of the affected implant. Implants with RPI usually remain osseointegrated. A diagnostic approach is proposed.

A Clinical Approach to Treatment of Retrograde Peri-Implantitis.

Retrograde peri-implantitis (RPI) is a primary microbial inflammatory condition that affects only the apical portion of an osseointegrated implant, which retains normal bone-to-implant contact in its coronal portion. Currently, no uniformly accepted definition or classification exists for RPI. This article reviews the etiopathological mechanisms, diagnostic pattern, and current treatment modalities for this type of periapical implant bone loss. The prevalence of RPI is reported to be relatively low, and along with a lack of an accepted classification system there is no widely accepted treatment algorithm. Therapeutic options include antibiotics, open-flap implant debridement, and apical resection eventually including apicoectomy of endodontically affected adjacent teeth, with or without bone grafting or removal of the affected implant. Implants with RPI usually remain osseointegrated. A diagnostic approach is proposed to establish the staging of the lesion and determine the best treatment option accordingly. When there is no loss of implant stability the most adequate treatment in the acute and chronic stage is apical resection of the implant with regeneration of the bone defect. If there is implant mobility, extraction of the implant is necessary.

Are Cannabis and Electronic Cigarettes Risks for Early Sinus Lift Failures?

To achieve restorative success for esthetic cases a process is needed that can be reproduced repeatedly. As with any process there are critical steps that must be followed to ensure accurate and precise results. This article outlines a verification process of provisional restorations in order to obtain appropriate esthetics, phonetics, and function. Additionally, the article discusses how newly created contours can be transferred intraorally to the laboratory benchtop and then to the final restorations. Through the process of verification, the clinician can establish restorative predictability to enhance the restorative success of any esthetic case.

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.

An Algorithmic Approach to Evaluation of an Ailing Implant.

With the incidence of failed and ailing dental implants increasing, the authors conducted research to evaluate and characterize all known criteria used in the assessment of implant health in the clinical setting. A review of articles found in electronic databases was performed. Once all parameters for implant assessment as supported by current literature were selected, implant assessment documents were created: a data acquisition form and a quantitative comprehensive evaluation. These documents provide the clinician an algorithm that yields a prognosis of survival for each implant. Diagnostic criteria were organized to offer a comprehensive assessment of risk factors related to implant health. Data acquisition prior to establishing the prognosis is necessary in accordance with the staging system developed. Parameters for diagnosis and staging include a thorough medical/social history of the patient, implant history, and clinical evaluation. The authors concluded that the establishment of parameters for comprehensive implant evaluation in the clinical setting is feasible. This assessment process enables an effective clinical approach to evaluate and treat ailing implants while facilitating a clinical diagnostic algorithm.