Influence of scanning and reconstruction parameters on quality of three-dimensional surface models of the dental arches from cone beam computed tomography

The study aim is to investigate the influence of scan field, mouth opening, voxel size, and segmentation threshold selections on the quality of the three-dimensional (3D) surface models of the dental arches from cone beam computed tomography (CBCT). 3D models of 25 patients scanned with one image intensifier CBCT system (NewTom 3G, QR SLR, Verona, Italy) using three field sizes in open- and closed-mouth positions were created at different voxel size resolutions. Two observers assessed the quality of the models independently on a five-point scale using specified criteria. The results indicate that large-field selection reduced the visibility of the teeth and the interproximal space. Also, large voxel size reduced the visibility of the occlusal surfaces and bone in the anterior region in both maxilla and mandible. Segmentation threshold was more variable in the maxilla than in the mandible. Closed-mouth scan complicated separating the jaws and reduced teeth surfaces visibility. The preliminary results from this image-intensifier system indicate that the use of medium or small scan fields in an open-mouth position with a small voxel is recommended to optimize quality of the 3D surface model reconstructions of the dental arches from CBCT. More research is needed to validate the results with other flat-panel detector-based CBCT systems

Інтеграційні процеси в паливно-енергетичному комплексі як фактор забезпечення екологічної безпеки

Challenge tests stress homeostasis and may reveal deviations in health that remain masked under unchallenged conditions. Ideally, challenge tests are non-invasive and applicable in an early phase of an animal experiment. Oxygen restriction (OxR; based on ambient, mild normobaric hypoxia) is a non-invasive challenge test that measures the flexibility to adapt metabolism. Metabolic inflexibility is one of the hallmarks of the metabolic syndrome. To test whether OxR can be used to reveal early diet-induced health effects, we exposed mice to a low-fat (LF) or high-fat (HF) diet for only 5 days. The response to OxR was assessed by calorimetric measurements, followed by analysis of gene expression in liver and epididymal white adipose tissue (eWAT) and serum markers for e.g. protein glycation and oxidation. Although HF feeding increased body weight, HF and LF mice did not differ in indirect calorimetric values under normoxic conditions and in a fasting state. Exposure to OxR; however, increased oxygen consumption and lipid oxidation in HF mice versus LF mice. Furthermore, OxR induced gluconeogenesis and an antioxidant response in the liver of HF mice, whereas it induced de novo lipogenesis and an antioxidant response in eWAT of LF mice, indicating that HF and LF mice differed in their adaptation to OxR. OxR also increased serum markers of protein glycation and oxidation in HF mice, whereas these changes were absent in LF mice. Cumulatively, OxR is a promising new method to test food products on potential beneficial effects for human health

A Fluorescence Polarization Activity-Based Protein Profiling Assay in the Discovery of Potent, Selective Inhibitors for Human Nonlysosomal Glucosylceramidase

Human nonlysosomal glucosylceramidase (GBA2) is one of several enzymes that controls levels of glycolipids and whose activity is linked to several human disease states. There is a major need to design or discover selective GBA2 inhibitors both as chemical tools and as potential therapeutic agents. Here, we describe the development of a fluorescence polarization activity-based protein profiling (FluoPol-ABPP) assay for the rapid identification, from a 350+ library of iminosugars, of GBA2 inhibitors. A focused library is generated based on leads from the FluoPol-ABPP screen and assessed on GBA2 selectivity offset against the other glucosylceramide metabolizing enzymes, glucosylceramide synthase (GCS), lysosomal glucosylceramidase (GBA), and the cytosolic retaining β-glucosidase, GBA3. Our work, yielding potent and selective GBA2 inhibitors, also provides a roadmap for the development of high-throughput assays for identifying retaining glycosidase inhibitors by FluoPol-ABPP on cell extracts containing recombinant, overexpressed glycosidase as the easily accessible enzyme source

Abnormal P300 in people with high risk of developing psychosis

Background Individuals with an “at-risk mental state” (or “prodromal” symptoms) have a 20–40% chance of developing psychosis; however it is difficult to predict which of them will become ill on the basis of their clinical symptoms alone. We examined whether neurophysiological markers could help to identify those who are particularly vulnerable. Method 35 cases meeting PACE criteria for the at-risk mental state (ARMS) and 57 controls performed an auditory oddball task whilst their electroencephalogram was recorded. The latency and amplitude of the P300 and N100 waves were compared between groups using linear regression. Results The P300 amplitude was significantly reduced in the ARMS group [8.6 ± 6.4 microvolt] compared to controls [12.7 ± 5.8 microvolt] (p < 0.01). There were no group differences in P300 latency or in the amplitude and latency of the N100. Of the at-risk subjects that were followed up, seven (21%) developed psychosis. Conclusion Reduction in the amplitude of the P300 is associated with an increased vulnerability to psychosis. Neurophysiological and other biological markers may be of use to predict clinical outcomes in populations at high risk

Process intensification education contributes to sustainable development goals: Part 2

Achieving the United Nations sustainable development goals requires industry and society to develop tools and processes that work at all scales, enabling goods delivery, services, and technology to large conglomerates and remote regions. Process Intensification (PI) is a technological advance that promises to deliver means to reach these goals, but higher education has yet to totally embrace the program. Here, we present practical examples on how to better teach the principles of PI in the context of the Bloom's taxonomy and summarise the current industrial use and the future demands for PI, as a continuation of the topics discussed in Part 1. In the appendices, we provide details on the existing PI courses around the world, as well as teaching activities that are showcased during these courses to aid students’ lifelong learning. The increasing number of successful commercial cases of PI highlight the importance of PI education for both students in academia and industrial staff.We acknowledge the sponsors of the Lorentz’ workshop on“Educating in PI”: The MESA+Institute of the University of Twente,Sonics and Materials (USA) and the PIN-NL Dutch Process Intensi-fication Network. DFR acknowledges support by The Netherlands Centre for Mul-tiscale Catalytic Energy Conversion (MCEC), an NWO Gravitationprogramme funded by the Ministry of Education, Culture and Sci-ence of the government of The Netherlands. NA acknowledges the Deutsche Forschungsgemeinschaft (DFG)- TRR 63¨Integrierte Chemische Prozesse in flüssigen Mehrphasen-systemen¨(Teilprojekt A10) - 56091768. The participation by Robert Weber in the workshop and thisreport was supported by Laboratory Directed Research and Devel-opment funding at Pacific Northwest National Laboratory (PNNL).PNNL is a multiprogram national laboratory operated for theUS Department of Energy by Battelle under contract DE-AC05-76RL0183

Process intensification education contributes to sustainable development goals : part 1

In 2015 all the United Nations (UN) member states adopted 17 sustainable development goals (UN-SDG) as part of the 2030 Agenda, which is a 15-year plan to meet ambitious targets to eradicate poverty, protect the environment, and improve the quality of life around the world. Although the global community has progressed, the pace of implementation must accelerate to reach the UN-SDG time-line. For this to happen, professionals, institutions, companies, governments and the general public must become cognizant of the challenges that our world faces and the potential technological solutions at hand, including those provided by chemical engineering. Process intensification (PI) is a recent engineering approach with demonstrated potential to significantly improve process efficiency and safety while reducing cost. It offers opportunities for attaining the UN-SDG goals in a cost-effective and timely manner. However, the pedagogical tools to educate undergraduate, graduate students, and professionals active in the field of PI lack clarity and focus. This paper sets out the state-of-the-art, main discussion points and guidelines for enhanced PI teaching, deliberated by experts in PI with either an academic or industrial background, as well as representatives from government and specialists in pedagogy gathered at the Lorentz Center (Leiden, The Netherlands) in June 2019 with the aim of uniting the efforts on education in PI and produce guidelines. In this Part 1, we discuss the societal and industrial needs for an educational strategy in the framework of PI. The terminology and background information on PI, related to educational implementation in industry and academia, are provided as a preamble to Part 2, which presents practical examples that will help educating on Process Intensification

A Multi-Element Detector System for Intelligent Imaging: I-ImaS

I-ImaS is a European project aiming to produce new, intelligent x-ray imaging systems using novel APS sensors to create optimal diagnostic images. Initial systems concentrate on mammography and encephalography. Later development will yield systems for other types of radiography such as industrial QA and homeland security. The I-ImaS system intelligence, due to APS technology and FPGAs, allows real-time analysis of data during image acquisition, giving the capability to build a truly adaptive imaging system with the potential to create images with maximum diagnostic information within given dose constraints. A companion paper deals with the DAQ system and preliminary characterization. This paper considers the laboratory x-ray characterization of the detector elements of the I-ImaS system. The characterization of the sensors when tiled to form a strip detector will be discussed, along with the appropriate correction techniques formulated to take into account the misalignments between individual sensors within the array. Preliminary results show that the detectors have sufficient performance to be used successfully in the initial mammographic and encephalographic I-ImaS systems under construction and this paper will further discuss the testing of these systems and the iterative processes used for intelligence upgrade in order to obtain the optimal algorithms and setting

Nutritional and environmental effects on ammonia emissions from dairy cattle housing: A meta-analysis

Nitrogen (N) excreted in urine by dairy cows can be potentially transformed to ammonia (NH3) and emitted to the atmosphere. Dairy production contributes to NH3 emission, which can create human respiratory problems and odor issues, reduces manure quality, and is an indirect source of nitrous oxide (N2O). The objective of this study was to (i) investigate environmental factors and measurement method that influence NH3 from dairy housing, and (ii) identify key explanatory variables in the prediction of NH3 emissions from dairy barns using a meta-analytical approach. Data from 25 studies were used for the preliminary analysis and data from 10 studies reporting 87 treatment means were used for the meta-analysis. Season, flooring type, manure handling and housing type and system significantly affected NH3 emission rates as well as the measurement method used to quantify the NH3 emission. Ammonia emissions rates from open-lot and scrape systems were considerably greater and those from deep pit systems lower compared to U.S. Environmental Protection Agency (USEPA) estimates used in national inventory calculations. For nutritional effect analysis, the between-study variability (heterogeneity) of the mean emission was estimated using random-effect models and had a significant effect (P < 0.01). Therefore, random-effect models were extended to mixed-effect models to explain heterogeneity. Available dietary and animal variables were included as fixed effects in the mixed-effect models. The final mixed-effect model included dietary crude protein, milk yield and dry matter intake, explaining 45.5% of the heterogeneity in NH3 emissions. A unit increase in milk yield (kg/d) resulted in 4.9 g cow/d reduction in NH3 emissions, and a unit increase in diet crude protein content (%) and dry matter intake (kg/d) resulted in 10.2 and 16.3 g cow/d increase in NH3 emissions, respectively. Ammonia emissions from dairy barns are driven by several factors including housing system, season and diet. Crude protein content of the diet, dry matter intake and milk production are important animal related factors that significantly affect ammonia emission from dairy facilities