Comparison between digital superimposition and microcomputed tomography methods of fit assessment of removable partial denture frameworks

STATEMENT OF PROBLEM

The fit of removable partial denture frameworks should be assessed to optimize clinical adaptation. Potential discrepancies between framework and supporting structures are typically precisely measured with negative subtracts and high-resolution equipment. The growth of computer-aided engineering technology allows the development of new methods for the direct evaluation of discrepancies. However, how the methods compare is unclear.

PURPOSE

The purpose of this in vitro study was to compare 2 digital methods of fit assessment based on direct digital superimposition and microcomputed tomography indirect analysis.

MATERIAL AND METHODS

Twelve cobalt chromium removable partial denture frameworks were fabricated by conventional lost-wax casting or additive manufacturing techniques. The thickness of the gap between occlusal rests and respective definitive cast rest seats (n=34) was evaluated by using 2 different digital methods. Silicone elastomer impressions of the gaps were obtained, and microcomputed tomography measurements were used as controls for validation purposes. Digitization of the framework, the respective definitive cast, and the combination was followed by digital superimposition and direct measurements with the Geomagic Control X software program. Because normality and homogeneity of variance were not verified (Shapiro-Wilk and Levene tests, P<.05), the data were analyzed with Wilcoxon signed rank and Spearman correlation tests (α=.05).

RESULTS

The thicknesses measured by microcomputed tomography (median=242 μm) and digital superimposition (median=236 μm) did not reveal statistically significant differences (P=.180). A positive correlation (ρ=0.612) was detected between the 2 methods of assessing fit.

CONCLUSIONS

The frameworks presented median gap thicknesses under the limit of clinical acceptability without differences between the proposed methods. The digital superimposition method was determined to be as acceptable as the high-resolution microcomputed tomography method for assessing removable partial denture framework fit.

Nutrigonometry I: using right-angle triangles to quantify nutritional trade-offs in performance landscapes

AbstractAnimals regulate their food intake to maximize the expression of fitness traits but are forced to trade off the optimal expression of some fitness traits because of differences in the nutrient requirements of each trait ("nutritional trade-offs"). Nutritional trade-offs have been experimentally uncovered using the geometric framework for nutrition (GF). However, current analytical methods to measure such responses rely on either visual inspection or complex models of vector calculations applied to multidimensional performance landscapes, making these approaches subjective or conceptually difficult, computationally expensive, and, in some cases, inaccurate. Here, we present a simple trigonometric model to measure nutritional trade-offs in multidimensional landscapes (nutrigonometry) that relies on the trigonometric relationships of right-angle triangles and thus is both conceptually and computationally easier to understand and use than previous quantitative approaches. We applied nutrigonometry to a landmark GF data set for comparison of several standard statistical models to assess model performance in finding regions in the performance landscapes. This revealed that polynomial (Bayesian) regressions can be used for precise and accurate predictions of peaks and valleys in performance landscapes, irrespective of the underlying structure of the data (i.e., individual food intakes vs. fixed diet ratios). We then identified the known nutritional trade-off between life span and reproductive rate in terms of both nutrient balance and concentration for validation of the model. This showed that nutrigonometry enables a fast, reliable, and reproducible quantification of nutritional trade-offs in multidimensional performance landscapes, thereby broadening the potential for future developments in comparative research on the evolution of animal nutrition.

Nutrigonometry III: curvature, area and differences between performance landscapes

Nutrition is one of the underlying factors necessary for the expression of life-histories and fitness across the tree of life. In recent decades, the geometric framework (GF) has become a powerful framework to obtain biological insights through the construction of multidimensional performance landscapes. However, to date, many properties of these multidimensional landscapes have remained inaccessible due to our lack of mathematical and statistical frameworks for GF analysis. This has limited our ability to understand, describe and estimate parameters which may contain useful biological information from GF multidimensional performance landscapes. Here, we propose a new model to investigate the curvature of GF multidimensional landscapes by calculating the parameters from differential geometry known as Gaussian and mean curvatures. We also estimate the surface area of multidimensional performance landscapes as a way to measure landscape deviations from flat. We applied the models to a landmark dataset in the field, where we also validate the assumptions required for the calculations of curvature. In particular, we showed that linear models perform as well as other models used in GF data, enabling landscapes to be approximated by quadratic polynomials. We then introduced the Hausdorff distance as a metric to compare the similarity of multidimensional landscapes.

'Holey' niche! finding holes in niche hypervolumes using persistence homology

Living organisms are limited in the range of values of ecological factors they can explore. This defines where animals exist (or could exist) and forms an ecological fingerprint that explains species' distribution at global scales. Species' ecological fingerprints can be represented as a n-dimensional hypervolume - known as Hutchinson's niche hypervolume. This concept has enabled significant progress in our understanding of species' ecological needs and distributions across environmental gradients. Nevertheless, the properties of Hutchinson's n-dimensional hypervolumes can be challenging to calculate and several methods have been proposed to extract meaningful measurements of hypervolumes' properties. One key property of hypervolumes are holes, which provide important information about the ecological occupancy of species. However, to date, current methods rely on volume estimates and set operations to identify holes in hypervolumes. Yet, this approach can be problematic because in high-dimensions, the volume of region enclosing a hole tends to zero. We propose the use of persistence homology (PH) to identify holes in hypervolumes and in ecological datasets more generally. PH allows for the estimates of topological properties in n-dimensional niche hypervolumes independent of the volume estimates of the hypervolume. We demonstrate the application of PH to canonical datasets and to the identification of holes in the hypervolumes of five vertebrate species with diverse niches, highlighting the potential benefits of this approach to gain further insights into animal ecology. Overall, our approach enables the study of a yet unexplored property of Hutchinson's hypervolumes, and thus, have important implications to our understanding of animal ecology.

An application of neighbourhoods in digraphs to the classification of binary dynamics

A binary state on a graph means an assignment of binary values to its vertices. A time dependent sequence of binary states is referred to as binary dynamics. We describe a method for the classification of binary dynamics of digraphs, using particular choices of closed neighbourhoods. Our motivation and application comes from neuroscience, where a directed graph is an abstraction of neurons and their connections, and where the simplification of large amounts of data is key to any computation. We present a topological/graph theoretic method for extracting information out of binary dynamics on a graph, based on a selection of a relatively small number of vertices and their neighbourhoods. We consider existing and introduce new real-valued functions on closed neighbourhoods, comparing them by their ability to accurately classify different binary dynamics. We describe a classification algorithm that uses two parameters and sets up a machine learning pipeline. We demonstrate the effectiveness of the method on simulated activity on a digital reconstruction of cortical tissue of a rat, and on a non-biological random graph with similar density.

Electrochemical Sensing in 3D Cell Culture Models: New Tools for Developing Better Cancer Diagnostics and Treatments

Currently, conventional pre-clinical in vitro studies are primarily based on two-dimensional (2D) cell culture models, which are usually limited in mimicking the real three-dimensional (3D) physiological conditions, cell heterogeneity, cell to cell interaction, and extracellular matrix (ECM) present in living tissues. Traditionally, animal models are used to mimic the 3D environment of tissues and organs, but they suffer from high costs, are time consuming, bring up ethical concerns, and still present many differences when compared to the human body. The applications of microfluidic-based 3D cell culture models are advantageous and useful as they include 3D multicellular model systems (MCMS). These models have demonstrated potential to simulate the in vivo 3D microenvironment with relatively low cost and high throughput. The incorporation of monitoring capabilities in the MCMS has also been explored to evaluate in real time biophysical and chemical parameters of the system, for example temperature, oxygen, pH, and metabolites. Electrochemical sensing is considered as one of the most sensitive and commercially adapted technologies for bio-sensing applications. Amalgamation of electrochemical biosensing with cell culture in microfluidic devices with improved sensitivity and performance are the future of 3D systems. Particularly in cancer, such models with integrated sensing capabilities can be crucial to assess the multiple parameters involved in tumour formation, proliferation, and invasion. In this review, we are focusing on existing 3D cell culture systems with integrated electrochemical sensing for potential applications in cancer models to advance diagnosis and treatment. We discuss their design, sensing principle, and application in the biomedical area to understand the potential relevance of miniaturized electrochemical hybrid systems for the next generation of diagnostic platforms for precision medicine.

Zinner's syndrome: an up-to-date review of the literature based on a clinical case

The authors made an up-to-date review of the literature concerning the management of Zinner's syndrome and evaluated a young patient with Zinner's syndrome who had presented with urinary and ejaculatory complaints. Physical examination and transrectal ultra-sonography showed a 7.0 cm right seminal vesicle cyst. Magnetic resonance imaging (MRI) confirmed the diagnosis of Zinner's syndrome. Oligoasthenoteratozoospermia was present at the two seminal analyses. Symptomatic improvement was achieved with conservative measures. Actually, the patient is still on a follow-up programme. The diagnosis is usually established at the age of increased sexual activity. Patients may be asymptomatic or present pain, irritative urinary or ejaculatory symptoms and infertility. MRI has proved to be the best imaging examination. Treatment should be adapted to symptoms, surveillance being the best option in the absence of clinical manifestations. Surgical approach may be adequate when conservative measures prove ineffective. Zinner's syndrome should be suspected if a male young patient presents with unilateral renal agenesis and pelvic complaints and has a supraprostatic mass on digital rectal examination. The initial approach should be medical, but invasive procedures may be the only way to solve the patient's complaints. Nowadays, laparoscopic and robotic techniques must replace the open surgical approach.