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Introduction: In the study of neurodegenerative diseases, the possibility to follow the fate of specific cells or molecules within the whole body would be a milestone to better understand the complex evolution of disease mechanisms and to monitor the effects of therapies. The techniques available today do not allow the visualization of disease-relevant cells within the whole tridimensional biological context at high spatial resolution.Methods: Here we show the results from the first validation steps of a novel approach: by combining the conjugate nanobodies anti-glial fibrillary acidic protein (GFAP) and metal-nanoparticles (i.e. 2 nm gold NP) with X-ray phase contrast tomography (XPCT) we would be able to obtain a tridimensional visualization and identification of cells of interest together with the surrounding tissue and the vascular and neuronal networks.Results: By exploiting the X-ray attenuation properties of metal nanoparticles and the specific targeting capabilities of nanobodies, we could give XPCT the specificity it presently lacks, making it no longer a pure morphological but a molecular and targeted imaging technique. In our case, we synthesized and characterized Gold-NP/GFAP nanobody to target the astrocytes of mouse brain.Discussion: The results of the first tests presented in this paper have provided us with information on the feasibility of the approach, encouraging us to carry out further experiments in order to achieve the ultimate goal of setting up this new imaging technique.

Adding supplementary texture and 2D image-based annotations to 3D surface models is a useful next step for domain specialists to make use of photorealistic products of laser scanning and photogrammetry. This requires a registration between the new camera imagery and the model geometry to be solved, which can be a time-consuming task without appropriate automation. The increasing availability of photorealistic models, coupled with the proliferation of mobile devices, gives users the possibility to complement their models in real time. Modern mobile devices deliver digital photographs of increasing quality, as well as on-board sensor data, which can be used as input for practical and automatic camera registration procedures. Their familiar user interface also improves manual registration procedures. This paper introduces a fully automatic pose estimation method using the on-board sensor data for initial exterior orientation, and feature matching between an acquired photograph and a synthesised rendering of the orientated 3D scene as input for fine alignment. The paper also introduces a user-friendly manual camera registration- and pose estimation interface for mobile devices, based on existing surface geometry and numerical optimisation methods. The article further assesses the automatic algorithm’s accuracy compared to traditional methods, and the impact of computational- and environmental parameters. Experiments using urban and geological case studies show a significant sensitivity of the automatic procedure to the quality of the initial mobile sensor values. Changing natural lighting conditions remain a challenge for automatic pose estimation techniques, although progress is presented here. Finally, the automatically-registered mobile images are used as the basis for adding user annotations to the input textured model.

Texture mapping is a common method for combining surface geometry with image data, with the resulting photorealistic 3D models being suitable not only for visualization purposes but also for interpretation and spatiameasurement, in many application fields, such as cultural heritage and the earth sciences. When acquiring images for creation of photorealistic models, it is usual to collect more data than is finally necessary for the texturing process. Images may be collected from multiple locations, sometimes with different cameras or lens configurations and large amounts of overlap may exist. Consequently, much redundancy may be present, requiring sorting to choose the most suitable images to texture the model triangles. This paper presents a framework for visualization and analysis of the geometric relations between triangles of the terrain model and covering image sets. The application provides decision support for selection of an image subset optimized for 3D model texturing purposes, for non-specialists. It aims to improve the communication of geometrical dependencies between model triangles and the available digital images, through the use of static and interactive information visualization methods. The tool was used for computer-aided selection of image subsets optimized for texturing of 3D geological outcrop models. The resulting textured models were of high quality and with a minimum of missing texture, and the time spent in time-consuming reprocessing was reduced. Anecdotal evidence indicated that an increased user confidence in the final textured model quality and completeness makes the framework highly beneficial.

Introduction: During the early stage of pregnancy trophoblast cells adapt to adverse uterine environments characterized by oxygen and nutrient deprivation. Autophagy is an intracellular degradation process that aims to promote cell survival in response to stressful conditions. Autophagy activation passes through the mechanistic target of rapamycin (mTOR), also known as a placental nutrient sensor. Here, we tested the hypothesis that ovine trophoblast cells may adapt to a suboptimal environment through an mTOR dependent regulation of cell survival with relevant implications for key placental functionality., Methods: Primary ovine trophoblast cells subjected to mTOR inhibitor and low-nutrient conditions were used to explore how autophagy affects cellular functionality and expression of solute carriers' genes (SLCs)., Results: Autophagy activation was confirmed both in rapamycin-treated and low-nutrient conditions, through the detection of specific autophagic markers. However, p-mTOR activation seems to be severely modified only following rapamycin treatment whereas 24h of starvation allowed p-mTOR reactivation. Starvation promoted migration compared to normal culture conditions whereas all trophoblast functional activities were decreased in rapamycin treatment. Interestingly in both conditions, the autophagy-activated environment did not affect the progesterone release. mRNA expression of amino acid transporters remains largely undisturbed except for SLC43A2 and SLC38A4 which are downregulated in starved and rapamycin-treated cells, respectively., Discussion: The study demonstrates that sheep trophoblast cells can adapt to adverse conditions in the early stage of placentation by balancing, in an mTOR dependent manner, nutrient recycling and transport with relevant effects for in vitro functional properties, which could potentially impact conceptus development and survival., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Introduction: The preservation of locally endangered breeds is essential for maintaining ecosystem services that benefit both society and the environment. Reproductive fitness becomes a crucial consideration in this context. MicroRNAs (miRNAs) are small non-coding RNA molecules that play a key role in post-transcriptional regulation. Typically, they function within the tissues where they are produced. However, when they are released into extracellular fluid, they are referred to as circulating miRNAs (c-miRNAs). C-miRNAs may serve as potential biomarkers, whose profile changes under different physiological states. The purpose of this study is to establish a connection between distinctive variations in the expression of c-miRNAs and specific estrus cycle phases in Frabosana-Roaschina sheep, an endangered Piedmontese breed., Methods: Two trials, each involving 20 ewes with different reproductive efficiencies (nulliparous in the first trial and pluriparous in the second trial), were sampled on alternate days after synchronization for blood, saliva, and feces. Ultrasound scans were performed during the induced estrus cycle. The animals' behaviors were assessed through video recordings., Results: In the first trial, play behaviors were detected without sexual behaviors, whereas in the second trial, sexual behaviors were observed without play behaviors. Based on plasma trends of 17β-estradiol and progesterone and ultrasound images, two moments were identified for miRNAs analyses: the beginning of the follicular phase (day 2) and the beginning of the luteal phase (day 11). C-miRNAs of six representative animals from the second trial were sequenced. Analyses of the sequencing data have identified 12 c-miRNAs that were differentially expressed (DE) when comparing day 11 with day 2: five miRNAs were found to be upregulated, whereas seven miRNAs were downregulated. An enrichment analysis, based on predicted targets, using the Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) databases was performed. Many of these genes regulate reproductive pathways with the possible involvement of miRNAs. Finally, qRT-PCR was conducted to validate the DE miRNAs in all ewes. Differences in gene expression between the two sampling points and the two trials were observed, in line with existing literature., Discussion: Investigating the role of these miRNAs in regulating estrus could improve the reproductive performance and welfare of Frabosana-Roaschina ewes., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Manenti, Ala, Macchi, Viola, Toschi, Accornero, Baratta, Miretti and Martignani.)

In Brief: Melatonin plays a crucial role in enhancing reproductive performance in small ruminants. This paper reveals the effects of exogenous melatonin on the placental and endometrial rearrangement in early pregnancy in sheep., Abstract: Early pregnancy losses cause 25% of pregnancy failures in small ruminants because of asynchrony between conceptus and uterine signals. In this context, melatonin plays a crucial role in sheep reproductive dynamics, but little is known about its effects during the peri-implantation period. We hypothesized that melatonin supports embryo implantation by modulating the uterine microenvironment. This study aimed to assess the effects of exogenous melatonin on the endometrial and early placental rearrangement. Ten multiparous ewes either did (MEL, n = 5) or did not (CTR, n = 5) receive a subcutaneous melatonin implant (18 mg) 50 days before a synchronized mating. On day 21 of pregnancy, the sheep were euthanized. MEL ewes exhibited a higher prolificity rate (2.8 vs 2.0 embryos/ewe) and plasma progesterone levels (3.84 vs 2.96 ng/mL, P < 0.05) than did CTR ewes. Groups did not differ significantly in embryo crown-rump length. MEL placentas had significantly (P < 0.001) more binucleated trophoblast cells in the chorion region, and ovine placental lactogen expression was significantly (P < 0.05) more strongly upregulated than in CTR. Exogenous melatonin increased significantly (P < 0.05) gene expression of angiogenic factors (VEGFA, VEGFR1, IGF1R), IFNAR2, and PR in the caruncular endometrium. Expression of the MT2 receptor in the endometrium and placenta was significantly (P < 0.05) higher in the MEL group. These results indicate that melatonin implants acted differentially on uterine and placental rearrangement. Melatonin increases differentiation in the placenta and induces changes that could promote vessel maturation in the endometrium, suggesting that it enhances the uterine microenvironment in the early stage of pregnancy in sheep.

We introduce DiffFit, a differentiable algorithm for fitting protein atomistic structures into an experimental reconstructed Cryo-Electron Microscopy (cryo-EM) volume map. In structural biology, this process is necessary to semi-automatically composite large mesoscale models of complex protein assemblies and complete cellular structures that are based on measured cryo-EM data. The current approaches require manual fitting in three dimensions to start, resulting in approximately aligned structures followed by an automated fine-tuning of the alignment. The DiffFit approach enables domain scientists to fit new structures automatically and visualize the results for inspection and interactive revision. The fitting begins with differentiable three-dimensional (3D) rigid transformations of the protein atom coordinates followed by sampling the density values at the atom coordinates from the target cryo-EM volume. To ensure a meaningful correlation between the sampled densities and the protein structure, we proposed a novel loss function based on a multi-resolution volume-array approach and the exploitation of the negative space. This loss function serves as a critical metric for assessing the fitting quality, ensuring the fitting accuracy and an improved visualization of the results. We assessed the placement quality of DiffFit with several large, realistic datasets and found it to be superior to that of previous methods. We further evaluated our method in two use cases: automating the integration of known composite structures into larger protein complexes and facilitating the fitting of predicted protein domains into volume densities to aid researchers in identifying unknown proteins. We implemented our algorithm as an open-source plugin (github.com/nanovis/DiffFit) in ChimeraX, a leading visualization software in the field. All supplemental materials are available at osf.io/5tx4q.

Objectives: This study described disease characteristics and long-term outcomes in patients diagnosed with very early onset inflammatory bowel disease (VEOIBD) (diagnosed before 6 years of age) and infantile-IBD (before 2 years)., Methods: Cases from 21 centers worldwide diagnosed with VEOIBD (2008-2018), with minimum 2 years of follow-up, were retrospectively reviewed., Results: The cohort included 243 patients (52% males, median follow-up of 5.8 [range 2-18] years, including 69 [28%]) with infantile-IBD. IBD subtypes included Crohn's disease (CD), ulcerative colitis (UC), or IBD-unclassified (IBDU) in 30%, 59%, and 11%, respectively. Among patients with CD, 94% had colonic involvement, and among patients with UC/IBDU, 75% had pancolitis. Patients with infantile-IBD presented with higher rates of IBDU, lower hemoglobin and albumin levels, and higher C-reactive protein, and had lower response rates to first-induction therapy and corticosteroids therapy (P < .05 for all). Colectomy and diversion surgeries were performed in 11% and 4%, respectively, with no significant differences between age groups. Corticosteroid-free remission rates were 74% and 78% after 3 and 5 years, respectively, and 86% at end of follow-up. Genetic testing was performed in 96 (40%) patients. Among tested population, 15 (16%) were identified with monogenic disease. This group demonstrated lower response rates to induction therapies, higher rates of surgical intervention, and higher rates of major infections (P < .05 for all)., Conclusions: Patients with VEOIBD, including infantile-IBD, exhibit low rate of complications and surgical interventions at the long term. Patients with monogenic IBD are at risk for more severe disease course., (Copyright © 2024 by the American Academy of Pediatrics.)

We report the detection of high energy electrons of some hundreds of MeV, crossing a methylammonium lead bromide single crystal device with sensitivity down to a single electron. In the device, the released energy is close to the energy released by minimum-ionizing particles. This is the first demonstration of a perovskite-based device that can be used for tracking and counting minimum-ionizing charged particles. The device reaches single particle sensitivity with a low bias voltage of 5 V. It also shows a good linearity of the response as a function of the number of electrons in a dynamic range of approximately 10 4 .

Electronic immunosensors are indispensable tools for diagnostics, particularly in scenarios demanding immediate results. Conventionally, these sensors rely on the chemical immobilization of antibodies onto electrodes. However, globular proteins tend to adsorb and unfold on these surfaces. Therefore, self-assembled monolayers (SAMs) of thiolated alkyl molecules are commonly used for indirect gold-antibody coupling. Here, a limitation associated with SAMs is revealed, wherein they curtail the longevity of protein sensors, particularly when integrated into the state-of-the-art transducer of organic bioelectronics-the organic electrochemical transistor. The SpyDirect method is introduced, generating an ultrahigh-density array of oriented nanobody receptors stably linked to the gold electrode without any SAMs. It is accomplished by directly coupling cysteine-terminated and orientation-optimized spyTag peptides, onto which nanobody-spyCatcher fusion proteins are autocatalytically attached, yielding a dense and uniform biorecognition layer. The structure-guided design optimizes the conformation and packing of flexibly tethered nanobodies. This biolayer enhances shelf-life and reduces background noise in various complex media. SpyDirect functionalization is faster and easier than SAM-based methods and does not necessitate organic solvents, rendering the sensors eco-friendly, accessible, and amenable to scalability. SpyDirect represents a broadly applicable biofunctionalization method for enhancing the cost-effectiveness, sustainability, and longevity of electronic biosensors, all without compromising sensitivity., (© 2023 The Authors. Advanced Science published by Wiley‐VCH GmbH.)

We present a novel framework for 3D tomographic reconstruction and visualization of tomograms from noisy electron microscopy tilt-series. Our technique takes as an input aligned tilt-series from cryogenic electron microscopy and creates denoised 3D tomograms using a proximal jointly-optimized approach that iteratively performs reconstruction and denoising, relieving the users of the need to select appropriate denoising algorithms in the pre-reconstruction or post-reconstruction steps. The whole process is accelerated by exploiting parallelism on modern GPUs, and the results can be visualized immediately after the reconstruction using volume rendering tools incorporated in the framework. We show that our technique can be used with multiple combinations of reconstruction algorithms and regularizers, thanks to the flexibility provided by proximal algorithms. Additionally, the reconstruction framework is open-source and can be easily extended with additional reconstruction and denoising methods. Furthermore, our approach enables visualization of reconstruction error throughout the iterative process within the reconstructed tomogram and on projection planes of the input tilt-series. We evaluate our approach in comparison with state-of-the-art approaches and additionally show how our error visualization can be used for reconstruction evaluation.

We present a novel method for the interactive construction and rendering of extremely large molecular scenes, capable of representing multiple biological cells in atomistic detail. Our method is tailored for scenes, which are procedurally constructed, based on a given set of building rules. Rendering of large scenes normally requires the entire scene available in-core, or alternatively, it requires out-of-core management to load data into the memory hierarchy as a part of the rendering loop. Instead of out-of-core memory management, we propose to procedurally generate the scene on-demand on the fly. The key idea is a positional- and view-dependent procedural scene-construction strategy, where only a fraction of the atomistic scene around the camera is available in the GPU memory at any given time. The atomistic detail is populated into a uniform-space partitioning using a grid that covers the entire scene. Most of the grid cells are not filled with geometry, only those are populated that are potentially seen by the camera. The atomistic detail is populated in a compute shader and its representation is connected with acceleration data structures for hardware ray-tracing of modern GPUs. Objects which are far away, where atomistic detail is not perceivable from a given viewpoint, are represented by a triangle mesh mapped with a seamless texture, generated from the rendering of geometry from atomistic detail. The algorithm consists of two pipelines, the construction-compute pipeline, and the rendering pipeline, which work together to render molecular scenes at an atomistic resolution far beyond the limit of the GPU memory containing trillions of atoms. We demonstrate our technique on multiple models of SARS-CoV-2 and the red blood cell.

The agricultural sector is amidst an industrial revolution driven by the integration of sensing, communication, and artificial intelligence (AI). Within this context, the internet of things (IoT) takes center stage, particularly in facilitating remote livestock monitoring. Challenges persist, particularly in effective field communication, adequate coverage, and long-range data transmission. This study focuses on employing LoRa communication for livestock monitoring in mountainous pastures in the north-western Alps in Italy. The empirical assessment tackles the complexity of predicting LoRa path loss attributed to diverse land-cover types, highlighting the subtle difficulty of gateway deployment to ensure reliable coverage in real-world scenarios. Moreover, the high expense of densely deploying end devices makes it difficult to fully analyze LoRa link behavior, hindering a complete understanding of networking coverage in mountainous environments. This study aims to elucidate the stability of LoRa link performance in spatial dimensions and ascertain the extent of reliable communication coverage achievable by gateways in mountainous environments. Additionally, an innovative deep learning approach was proposed to accurately estimate path loss across challenging terrains. Remote sensing contributes to land-cover recognition, while Bidirectional Long Short-Term Memory (Bi-LSTM) enhances the path loss model's precision. Through rigorous implementation and comprehensive evaluation using collected experimental data, this deep learning approach significantly curtails estimation errors, outperforming established models. Our results demonstrate that our prediction model outperforms established models with a reduction in estimation error to less than 5 dB, marking a 2X improvement over state-of-the-art models. Overall, this study signifies a substantial advancement in IoT-driven livestock monitoring, presenting robust communication and precise path loss prediction in rugged landscapes., Competing Interests: The authors declare no conflicts of interest. The funders had no role in the design of the study; in the collection, analysis, or interpretation of data; in the writing of the manuscript; or in the decision to publish the results.

The latest social VR technologies have enabled users to attend traditional media and arts performances together while being geographically removed, making such experiences accessible despite budget, distance, and other restrictions. In this work, we aim at improving the way remote performances are shared by designing and evaluating a VR theatre lobby which serves as a space for users to gather, interact, and relive the common experience of watching a virtual opera. We conducted an initial test with experts ($\mathrm{N}=10$, i.e., designers and opera enthusiasts) in pairs using our VR lobby prototype, developed based on the theoretical lobby design concept. A unique aspect of our experience is its highly realistic representation of users in the virtual space. The test results guided refinements to the VR lobby structure and implementation, aiming to improve the user experience and align it more closely with the social VR lobby's intended purpose. With the enhanced prototype, we ran a between-subject controlled study ($\mathrm{N}=40$) to compare the user experience in the social VR lobby between individuals and paired participants. To do so, we designed and validated a questionnaire to measure the user experience in the VR lobby. Results of our mixed-methods analysis, including interviews, questionnaire results, and user behavior, reveal the strength of our social VR lobby in connecting with other users, consuming the opera in a deeper manner, and exploring new possibilities beyond what is common in real life. All supplemental materials are available at https://github.com/cwi-dis/IEEEVR2024-VRLobby.

Membrane-based sensors (MePSs) exhibit remarkable precision and sensitivity in detecting pressure changes. MePSs are commonly used to monitor catalytic reactions in solution, generating gas products crucial for signal amplification in bioassays. They also allow for catalyst quantification by indirectly measuring the pressure generated by the gaseous products. This is particularly interesting for detecting enzymes in biofluids associated with disease onset. To enhance the performance of a MePS, various structural factors influence membrane flexibility and response time, ultimately dictating the device's pressure sensitivity. In this study, we fabricated MePSs using polydimethylsiloxane (PDMS) and investigated how structural modifications affect the Young's modulus ( E ) and residual stress ( σ 0 ) of the membranes. These modifications have a direct impact on the sensors' sensitivity to pressure variations, observed as a function of the volume of the chamber ( Σ ) or of the mechanical properties of the membrane itself ( S ). MePSs exhibiting the highest sensitivities were then employed to detect catalyst quantities inducing the dismutation of hydrogen peroxide, producing dioxygen as a gaseous product. As a result, a catalase enzyme was successfully detected using these optimized MePSs, achieving a remarkable sensitivity of (22.7 ± 1.2) µm/nM and a limit of detection (LoD) of 396 pM.

Optoelectronic and spinoptronic technologies benefit from flexible and tunable coherent light sources combining the best properties of nano- and material-engineering to achieve favorable properties such as chiral lasing and low threshold nonlinearities. In this work we demonstrate an electrically wavelength- and polarization-tunable room temperature polariton laser due to emerging photonic spin-orbit coupling. For this purpose, we design an optical cavity filled with both birefringent nematic liquid crystal and an inorganic perovskite. Our versatile growth method of single CsPbBr 3 inorganic perovskite crystals in polymer templates allows us to reach strong light-matter coupling and pump-induced condensation of exciton-polaritons resulting in coherent emission of light. The sensitivity of the liquid crystal to external voltage permits electrical tuning of the condensate energy across 7 nm; its threshold power, allowing us to electrically switch it on and off; and its state of polarization sweeping from linear to locally tilted circularly polarized emission., Competing Interests: Conflict of interest: Authors state no conflicts of interest., (© 2024 the author(s), published by De Gruyter, Berlin/Boston.)

Embryo development is dependent upon the exchange of oxygen and nutrients through the placenta, mainly composed of peculiar epithelioid cells, known as trophoblast cells. Normal trophoblast functionality plays a key role during the whole pregnancy, especially in the first stage of placentation. This chapter explains the techniques to obtain sheep primary trophoblast cells from the early placenta. Overall, procedures for cell isolation, culture, characterization, and cryopreservation are described., (© 2024. The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature.)

Dr. KID is an algorithm that uses isometric decomposition for the physicalization of potato-shaped organic models in a puzzle fashion. The algorithm begins with creating a simple, regular triangular surface mesh of organic shapes, followed by iterative K-means clustering and remeshing. For clustering, we need similarity between triangles (segments) which is defined as a distance function. The distance function maps each triangle's shape to a single point in the virtual 3D space. Thus, the distance between the triangles indicates their degree of dissimilarity. K-means clustering uses this distance and sorts segments into k classes. After this, remeshing is applied to minimize the distance between triangles within the same cluster by making their shapes identical. Clustering and remeshing are repeated until the distance between triangles in the same cluster reaches an acceptable threshold. We adopt a curvature-aware strategy to determine the surface thickness and finalize puzzle pieces for 3D printing. Identical hinges and holes are created for assembling the puzzle components. For smoother outcomes, we use triangle subdivision along with curvature-aware clustering, generating curved triangular patches for 3D printing. Our algorithm was evaluated using various models, and the 3D-printed results were analyzed. Findings indicate that our algorithm performs reliably on target organic shapes with minimal loss of input geometry.

Farm procedures have an impact on animal welfare by activating the hypothalamic-pituitary-adrenal axis that induces a wide array of physiological responses. This adaptive system guarantees that the animal copes with environmental variations and it induces metabolic and molecular changes that can be quantified. MicroRNAs (miRNAs) play a key role in the regulation of homeostasis and emerging evidence has identified circulating miRNAs as promising biomarkers of stress-related disorders in animals. Based on a clustering analysis of salivary cortisol trends and levels, 20 ewes were classified into two different clusters. The introduction of a ram in the flock was identified as a common farm practice and reference time point to collect saliva samples. Sixteen miRNAs related to the adaptation response were selected. Among them, miR-16b, miR-21, miR-24, miR-26a, miR-27a, miR-99a, and miR-223 were amplified in saliva samples. Cluster 1 was characterized by a lower expression of miR-16b and miR-21 compared with Cluster 2 ( p < 0.05). This study identified for the first time several miRNAs expressed in sheep saliva, pointing out significant differences in the expression patterns between the cortisol clusters. In addition, the trend analyses of these miRNAs resulted in clusters ( p = 0.017), suggesting the possible cooperation of miR-16b and -21 in the integrated stress responses, as already demonstrated in other species as well. Other research to define the role of these miRNAs is needed, but the evaluation of the salivary miRNAs could support the selection of ewes for different profiles of response to sources of stressors common in the farm scenario.

Cryo-electron tomography (cryo-ET) is a new 3D imaging technique with unprecedented potential for resolving submicron structural details. Existing volume visualization methods, however, are not able to reveal details of interest due to low signal-to-noise ratio. In order to design more powerful transfer functions, we propose leveraging soft segmentation as an explicit component of visualization for noisy volumes. Our technical realization is based on semi-supervised learning, where we combine the advantages of two segmentation algorithms. First, the weak segmentation algorithm provides good results for propagating sparse user-provided labels to other voxels in the same volume and is used to generate dense pseudo-labels. Second, the powerful deep-learning-based segmentation algorithm learns from these pseudo-labels to generalize the segmentation to other unseen volumes, a task that the weak segmentation algorithm fails at completely. The proposed volume visualization uses deep-learning-based segmentation as a component for segmentation-aware transfer function design. Appropriate ramp parameters can be suggested automatically through frequency distribution analysis. Furthermore, our visualization uses gradient-free ambient occlusion shading to further suppress the visual presence of noise, and to give structural detail the desired prominence. The cryo-ET data studied in our technical experiments are based on the highest-quality tilted series of intact SARS-CoV-2 virions. Our technique shows the high impact in target sciences for visual data analysis of very noisy volumes that cannot be visualized with existing techniques.

The present case-report empathizes the usefulness of post-mortem computed tomography (PMCT) in the detection of live birth signs in a baby found dead, comparing the results with standard autoptic, histologic and immunohistochemical examinations. The report describes the case of a new-born who was thrown out on the footpath from a window of the fifth floor according to the investigative police, whilst the mother has hidden herself immediately after childbirth. PMCT showed diffusely aerated lung parenchyma with signs of severe lung distress, air in the airways with no fluid inside, and air in the upper gastro-intestinal tract, in absence any resuscitation manoeuvres performed on the baby at delivery. PMCT underlined multiple fractures of the skull with degeneration of cerebral parenchyma. All these findings were confirmed by conventional autopsy and histological and immunohistochemical examinations, clinching the usefulness of PMCT in differentiating live births from stillbirths., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier B.V. All rights reserved.)

Immersive virtual reality environments are gaining popularity for studying and exploring crowded three-dimensional structures. When reaching very high structural densities, the natural depiction of the scene produces impenetrable clutter and requires visibility and occlusion management strategies for exploration and orientation. Strategies developed to address the crowdedness in desktop applications, however, inhibit the feeling of immersion. They result in nonimmersive, desktop-style outside-in viewing in virtual reality. This article proposes Nanotilus-a new visibility and guidance approach for very dense environments that generates an endoscopic inside-out experience instead of outside-in viewing, preserving the immersive aspect of virtual reality. The approach consists of two novel, tightly coupled mechanisms that control scene sparsification simultaneously with camera path planning. The sparsification strategy is localized around the camera and is realized as a multi-scale, multi-shell, variety-preserving technique. When Nanotilus dives into the structures to capture internal details residing on multiple scales, it guides the camera using depth-based path planning. In addition to sparsification and path planning, we complete the tour generation with an animation controller, textual annotation, and text-to-visualization conversion. We demonstrate the generated guided tours on mesoscopic biological models - SARS-CoV-2 and HIV. We evaluate the Nanotilus experience with a baseline outside-in sparsification and navigational technique in a formal user study with 29 participants. While users can maintain a better overview using the outside-in sparsification, the study confirms our hypothesis that Nanotilus leads to stronger engagement and immersion.

We present a method for producing documentary-style content using real-time scientific visualization. We introduce molecumentaries, i.e., molecular documentaries featuring structural models from molecular biology, created through adaptable methods instead of the rigid traditional production pipeline. Our work is motivated by the rapid evolution of scientific visualization and it potential in science dissemination. Without some form of explanation or guidance, however, novices and lay-persons often find it difficult to gain insights from the visualization itself. We integrate such knowledge using the verbal channel and provide it along an engaging visual presentation. To realize the synthesis of a molecumentary, we provide technical solutions along two major production steps: (1) preparing a story structure and (2) turning the story into a concrete narrative. In the first step, we compile information about the model from heterogeneous sources into a story graph. We combine local knowledge with external sources to complete the story graph and enrich the final result. In the second step, we synthesize a narrative, i.e., story elements presented in sequence, using the story graph. We then traverse the story graph and generate a virtual tour, using automated camera and visualization transitions. We turn texts written by domain experts into verbal representations using text-to-speech functionality and provide them as a commentary. Using the described framework, we synthesize fly-throughs with descriptions: automatic ones that mimic a manually authored documentary or semi-automatic ones which guide the documentary narrative solely through curated textual input.

Sperm motility is a prerequisite for male fertility. Enhancing the concentration of motile sperms in assisted reproductive technologies - for human and animal reproduction - is typically achieved through aggressive methods such as centrifugation. Here, we propose a passive technique for the amplification of motile sperm concentration, with no externally imposed forces or flows. The technique is based on the disparity between probability rates, for motile cells, of entering and escaping from complex structures. The effectiveness of the technique is demonstrated in microfluidic experiments with microstructured devices, comparing the trapping power in different geometries. In these micro-traps, we observe an enhancement of cells' concentration close to 10, with a contrast between motile and non-motile cells increased by a similar factor. Simulations of suitable interacting model sperms in realistic geometries reproduce quantitatively the experimental results, extend the range of observations and highlight the components that are key to the optimal trap design.

In Brief: Fibroblast growth factor-2 (FGF2) is essential for early placenta development in sheep. This study shows that the mechanistic target of rapamycin is the key modulator of trophoblast adaptive response under FGF2 modulation., Abstract: During the early stage of placentation in sheep, normal conceptus development is affected by trophoblast cell functionality, whose dysregulation results in early pregnancy loss. Trophoblast metabolism is supported mainly by histotrophic factors, including fibroblast growth factor-2 (FGF2), which are involved in cell differentiation and function through the modulation of specific cellular mechanisms. The mechanistic target of rapamycin (mTOR) is known as a cellular 'nutrient sensor', but its downstream regulation remains poorly understood. The hypothesis was that during trophoblast development, the FGF2 effect is mediated by mTOR signalling pathway modulation. Primary trophoblast cells from 21-day-old sheep placenta were characterised and subjected to FGF2 and rapamycin treatment to study the effects on cell functionality and gene and protein expression profiles. The model showed mainly mononuclear cells with epithelial cell-like growth and placental morphological properties, expressing typical trophoblast markers. FGF2 promoted cell proliferation and migration under normal culture conditions, whereas mTOR inhibition reversed this effect. When the mTOR signalling pathway was activated, FGF2 failed to influence invasion activity. mTOR inhibition significantly reduced cell motility, but FGF2 supplementation restored motility even when mTOR was inhibited. Interestingly, mTOR inhibition influenced endocrine trophoblast marker regulation. Although FGF2 supplementation did not affect ovine placenta lactogen expression, as observed in the control, interferon-tau was drastically reduced. This study provides new insights into the mechanism underlying mTOR inhibitory effects on trophoblast cell functionality. In addition, as mTOR is involved in the expression of hormonal trophoblast markers, it may play a crucial role in early placenta growth and fetal-maternal crosstalk.

Background: The diagnosis of neck lesions remains a medico-legal diagnostic challenge because of the complexity of the anatomical relationship of the neck's organs and their anthropometric morphological variability. We compared the multidisciplinary approach using autopsy and postmortem computed tomography (PMCT), postmortem fine preparation (PMFP), postmortem micro-computed tomography (micro-CT), and postmortem magnetic resonance (PMMR) with the performance of a single diagnostic method among them evaluating the significance of different results. The multidisciplinary approach significantly reduced the number of unidentified neck lesions. The analysis demonstrates the need to better define the scan protocols and compose forensic guidelines for radiological application. The results of this study point out the need to compare the different diagnostic approaches in deceased subjects to better define the radiological scan protocol based on a multidisciplinary approach, including autopsy and radiological methods and the radiological scan protocols., Methods: We performed a systematic electronic search of retrospective scientific articles in PubMed, the Scopus database, and the Cochrane Library. The following combinations of words were used: "hyoid fracture"; "comparison between PMCT AND autopsy"; "hyoid fracture PMCT AND autopsy"; "hyoid bone fracture AND forensic imaging"; "hyoid fracture AND PMCT"; "neck fracture PMCT AND autopsy"; "laryngohyoid lesions"; "postmortem CT AND autopsy in strangulation"; "postmortem AND strangulation Signs "; "strangulation virtopsy"; and "strangulation AND MRI". We selected 16 articles that were published between March 2003 and June 2020. We conducted a meta-analysis with R software to evaluate the rates. We obtained related confidence intervals and a forest plot., Results: Thyroid cartilage damages were significantly more common than hyoid bone fractures (61.7% vs 42.2%) in a sample of 128 subjects. The synergic uses of autopsy/PMCT, autopsy/PMFP, autopsy/microCT, and autopsy/PMMR revealed significantly higher rates than a single investigation. We analyzed the PMCT scan data. The scan parameters evaluated were as follows: row, scan sample, reconstruction, kernel, slice thickness, kVp, and mAs. A lack of uniformity in the application of the protocol was observed., Conclusion: Further studies are needed to better define the radiological scan protocols and to draw guidelines to identify the appropriate radiological methods in relation to the specific case.

Colormapping is an effective and popular visualization technique for analyzing patterns in scalar fields. Scientists usually adjust a default colormap to show hidden patterns by shifting the colors in a trial-and-error process. To improve efficiency, efforts have been made to automate the colormap adjustment process based on data properties (e.g., statistical data value or histogram distribution). However, as the data properties have no direct correlation to the spatial variations, previous methods may be insufficient to reveal the dynamic range of spatial variations hidden in the data. To address the above issues, we conduct a pilot analysis with domain experts and summarize three requirements for the colormap adjustment process. Based on the requirements, we formulate colormap adjustment as an objective function, composed of a boundary term and a fidelity term, which is flexible enough to support interactive functionalities. We compare our approach with alternative methods under a quantitative measure and a qualitative user study (25 participants), based on a set of data with broad distribution diversity. We further evaluate our approach via three case studies with six domain experts. Our method is not necessarily more optimal than alternative methods of revealing patterns, but rather is an additional color adjustment option for exploring data with a dynamic range of spatial variations.