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Background Anatomy is a crucial part of medical education, and there have been attempts to improve this field by utilizing various methods. With the advancement of technology, three-dimensional (3D) materials have gained popularity and become a matter of debate about their effectiveness compared to two-dimensional (2D) sources. This research aims to analyze the effectiveness of 3D PDFs compared to 2D atlases. Methods This study is a randomized controlled trial involving 87 Year-1 and Year-2 medical students at Gazi University Faculty of Medicine, Turkey. The study was conducted in two steps. In Step-1, students were randomized to watch lecture videos on liver anatomy and male genitalia anatomy supplemented with either a 3D PDF (intervention group) or 2D atlas (control group) images. Following the video lectures, a test (immediate test) was administered. In Step-2, the same test (delayed test) was administered 10 days after the immediate test. The test scores were compared between the intervention and control groups. In addition to the descriptive analyses, Chi-square and Mann-Whitney U tests were performed. Results In the immediate test, while there was no significant difference between the groups for the liver test ( p  > 0.05), 3D PDF group’s scores (Median = 24.50) was significantly higher than the 2D atlas group’s in the genitalia test (Median = 21.00), ( p  = 0.017). The effect size (Cohen’s d) was 0.57. In the delayed test, there was no significant difference between the groups in the liver and genitalia tests ( p  > 0.05). However, the effect size in the immediate genitalia test was 0.40. Year-1 students’ immediate test of genitalia performances were significantly higher in the 3D PDF group (Median = 24.00) than the 2D atlas group (Median = 19.00), ( p  = 0.016). The effect size was 0.76. Also, Year-1 students’ 3D PDF group (Median = 20.50) presented with significantly higher performance than the 2D atlas group (Median = 12.00), ( p  = 0.044) in the delayed test of genitalia, with the 0.63 effect size. Conclusion 3D PDF is more effective than 2D atlases in teaching anatomy, especially to initial learners. It is particularly useful for teaching complex anatomical structures, such as male genitalia, compared to the liver. Hence, it may be a valuable tool for medical teachers to utilize during lectures.

Reference brains are indispensable tools in human brain mapping, enabling integration of multimodal data into an anatomically realistic standard space. Available reference brains, however, are restricted to the macroscopic scale and do not provide information on the functionally important microscopic dimension. We created an ultrahigh-resolution three-dimensional (3D) model of a human brain at nearly cellular resolution of 20 micrometers, based on the reconstruction of 7404 histological sections. \"BigBrain\" is a free, publicly available tool that provides considerable neuroanatomical insight into the human brain, thereby allowing the extraction of microscopic data for modeling and simulation. BigBrain enables testing of hypotheses on optimal path lengths between interconnected cortical regions or on spatial organization of genetic patterning, redefining the traditional neuroanatomy maps such as those of Brodmann and von Economo.

The brain lacks lymph vessels and must rely on other mechanisms for clearance of waste products, including amyloid β that may form pathological aggregates if not effectively cleared. It has been proposed that flow of interstitial fluid through the brain’s interstitial space provides a mechanism for waste clearance. Here we compute the permeability and simulate pressure-mediated bulk flow through 3D electron microscope (EM) reconstructions of interstitial space. The space was divided into sheets (i.e., space between two parallel membranes) and tunnels (where three or more membranes meet). Simulation results indicate that even for larger extracellular volume fractions than what is reported for sleep and for geometries with a high tunnel volume fraction, the permeability was too low to allow for any substantial bulk flow at physiological hydrostatic pressure gradients. For two different geometries with the same extracellular volume fraction the geometry with the most tunnel volume had 36% higher permeability, but the bulk flow was still insignificant. These simulation results suggest that even large molecule solutes would be more easily cleared from the brain interstitium by diffusion than by bulk flow. Thus, diffusion within the interstitial space combined with advection along vessels is likely to substitute for the lymphatic drainage system in other organs.

The developing vertebrate gut tube forms a reproducible looped pattern as it grows into the body cavity. Here we use developmental experiments to eliminate alternative models and show that gut looping morphogenesis is driven by the homogeneous and isotropic forces that arise from the relative growth between the gut tube and the anchoring dorsal mesenteric sheet, tissues that grow at different rates. A simple physical mimic, using a differentially strained composite of a pliable rubber tube and a soft latex sheet is consistent with this mechanism and produces similar patterns. We devise a mathematical theory and a computational model for the number, size and shape of intestinal loops based solely on the measurable geometry, elasticity and relative growth of the tissues. The predictions of our theory are quantitatively consistent with observations of intestinal loops at different stages of development in the chick embryo. Our model also accounts for the qualitative and quantitative variation in the distinct gut looping patterns seen in a variety of species including quail, finch and mouse, illuminating how the simple macroscopic mechanics of differential growth drives the morphology of the developing gut. The gut is twisted logically The human intestine, much longer overall than the human body, is tightly looped within the body cavity in a pattern that is very similar between individuals, and characteristic of species. A study of gut morphogenesis in the chick, combining cellular and developmental biology, biophysics and mathematical modelling, shows that the looping complex shape of the vertebrate gut is a simple consequence of mechanics. As a body grows, the gut inside grows faster. It is anchored at each end and suspended by a muscular sheet called the mesentery, so is forced into loops. The looping pattern is determined solely by the elasticity, geometry and relative rates of growth of mesentery and gut, but the various twists and turns and loops are very reproducible, occurring with the same number in the same location from individual to individual.

Insect wings are complex structures that deform dramatically in flight. We analyzed the aerodynamic consequences of wing deformation in locusts using a three-dimensional computational fluid dynamics simulation based on detailed wing kinematics. We validated the simulation against smoke visualizations and digital particle image velocimetry on real locusts. We then used the validated model to explore the effects of wing topography and deformation, first by removing camber while keeping the same time-varying twist distribution, and second by removing camber and spanwise twist. The full-fidelity model achieved greater power economy than the uncambered model, which performed better than the untwisted model, showing that the details of insect wing topography and deformation are important aerodynamically. Such details are likely to be important in engineering applications of flapping flight.

Over the past decade, multivariate “decoding analyses” have become a popular alternative to traditional mass-univariate analyses in neuroimaging research. However, a fundamental limitation of using decoding analyses is that it remains ambiguous which source of information drives decoding performance, which becomes problematic when the to-be-decoded variable is confounded by variables that are not of primary interest. In this study, we use a comprehensive set of simulations as well as analyses of empirical data to evaluate two methods that were previously proposed and used to control for confounding variables in decoding analyses: post hoc counterbalancing and confound regression. In our empirical analyses, we attempt to decode gender from structural MRI data while controlling for the confound “brain size”. We show that both methods introduce strong biases in decoding performance: post hoc counterbalancing leads to better performance than expected (i.e., positive bias), which we show in our simulations is due to the subsampling process that tends to remove samples that are hard to classify or would be wrongly classified; confound regression, on the other hand, leads to worse performance than expected (i.e., negative bias), even resulting in significant below chance performance in some realistic scenarios. In our simulations, we show that below chance accuracy can be predicted by the variance of the distribution of correlations between the features and the target. Importantly, we show that this negative bias disappears in both the empirical analyses and simulations when the confound regression procedure is performed in every fold of the cross-validation routine, yielding plausible (above chance) model performance. We conclude that, from the various methods tested, cross-validated confound regression is the only method that appears to appropriately control for confounds which thus can be used to gain more insight into the exact source(s) of information driving one's decoding analysis. •The interpretation of decoding models is ambiguous when dealing with confounds.•We evaluate several methods that aim to to control for confounds.•We find that most of the evaluated methods yield biased results.•Only cross-validated confound regression yields nearly unbiased results.

In the past years, many attempts have been made in order to model the process of bone remodeling. This process is complex, as it is governed by not yet completely understood biomechanical coupled phenomena. It is well known that bone tissue is able to self-adapt to different environmental demands of both mechanical and biological origin. The mechanical aspects are related to the functional purpose of the bone tissue, i.e., to provide support to the body and protection for the vitally important organs in response to the external loads. The many biological aspects include the process of oxygen and nutrients supply. To describe the biomechanical process of functional adaptation of bone tissue, the approach commonly adopted is to consider it as a ‘feedback’ control regulated by the bone cells, namely osteoblasts and osteoclasts. They are responsible for bone synthesis and resorption, respectively, while osteocytes are in charge of ‘sensing’ the mechanical status of the tissue. Within this framework, in Lekszycki and dell’Isola (ZAMM - Zeitschrift für Angewandte Mathematik und Mechanik 92(6):426–444, 2012), a model based on a system of integro-differential equations was introduced aiming to predict the evolution of the process of remodeling in surgically reconstructed bones. The main idea in the aforementioned model was to introduce a scalar field, describing the biological stimulus regulating the interaction among all kinds of bone cells at a macroscale. This biological field was assumed to depend locally on certain deformation measures of the (reconstructed) bone tissue. However, biological knowledge suggests that this stimulus, after having been produced, ‘diffuses’ in bone tissue, so controlling in a complex way its remodeling. This means that the cells which are target of the stimulus may not be located in the same place occupied by the cells producing it. In this paper, we propose a model which intends to explain the diffusive nature of the biological stimulus to encompass the time-dependent and space–time displaced effects involved in bone reconstruction process. Preliminary numerical simulations performed in typical cases are presented. These numerical case studies suggest that the ‘diffusive’ model of stimulus is promising: we plan to continue these kinds of studies in further investigations.

Epithelial folding transforms simple sheets of cells into complex three-dimensional tissues and organs during animal development. Epithelial folding has mainly been attributed to mechanical forces generated by an apically localized actomyosin network, however, contributions of forces generated at basal and lateral cell surfaces remain largely unknown. Here we show that a local decrease of basal tension and an increased lateral tension, but not apical constriction, drive the formation of two neighboring folds in developing Drosophila wing imaginal discs. Spatially defined reduction of extracellular matrix density results in local decrease of basal tension in the first fold; fluctuations in F-actin lead to increased lateral tension in the second fold. Simulations using a 3D vertex model show that the two distinct mechanisms can drive epithelial folding. Our combination of lateral and basal tension measurements with a mechanical tissue model reveals how simple modulations of surface and edge tension drive complex three-dimensional morphological changes. Epithelial folding has mainly been linked to forces acting in the apical actomyosin network of cells. Here, the authors show using live imaging that two distinct mechanisms, changes in basal surface tension and changes in lateral surface tension, drive the formation of two folds in the Drosophila wing disc.

Surgeons typically rely on their past training and experiences as well as visual aids from medical imaging techniques such as magnetic resonance imaging (MRI) or computed tomography (CT) for the planning of surgical processes. Often, due to the anatomical complexity of the surgery site, two dimensional or virtual images are not sufficient to successfully convey the structural details. For such scenarios, a 3D printed model of the patient’s anatomy enables personalized preoperative planning. This paper reviews critical aspects of 3D printing for preoperative planning and surgical training, starting with an overview of the process-flow and 3D printing techniques, followed by their applications spanning across multiple organ systems in the human body. State of the art in these technologies are described along with a discussion of current limitations and future opportunities.