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.

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.

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.

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.

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.

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.

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.

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.