COVID-19 Vaccine Hesitancy Among Pregnant Women.

Background COVID-19 has struck the world severely and caused much damage, losses, and a massive impact on different aspects of life. It is an airborne disease that spreads rapidly among populations and can cause severe illness or death. The rapid nature of its spread led to significant challenges to control it. With the introduction of vaccines, strategies need to be developed to prioritize high-risk populations to lower complication rates, hospitalization, and death. Pregnant women are considered a group of high-risk populations. Misinformation about the vaccination efficacy or side effects contributed to general hesitancy, especially among pregnant women. Purpose This study aims to describe the drivers of COVID-19 vaccine hesitancy among pregnant women in Saudi Arabia. Methodology This is a cross-sectional study among pregnant women in the OB/Gyn clinic in King Abdulaziz Medical City, Riyadh, Ministry of National Guard Health Affairs (MNG-HA), using an online survey. Descriptive statistics (univariate analysis) was used to examine the population characteristics. The Chi-square test was used for categorical variables, and t-test for continuous variables. Further, we used the logistics regression model (multivariate analysis), adjusted for potential confounders, to examine factors associated with women's hesitancy to take the COVID-19 vaccine. All statistical tests were two-sided, and findings were considered statistically significant at p < 0.05. All analyses were conducted using SAS statistical software version 9.4 (SAS Institute Inc., Cary, NC). Result The study included 303 pregnant women. Nearly half of the respondents had their vaccine during their pregnancy (42.24%), believing that the current vaccines' effectiveness for the coronavirus is good (41.25%). More than 73% of participants have received their COVID-19 vaccine before pregnancy. The mean hesitancy and anxiety score was 2 (agree), which concluded that the respondents were hesitant and anxious to receive the COVID-19 vaccine. Conclusion The study showed a significant correlation between pregnant women's worries and the intention to take the vaccine. The concerns were mainly about the impact of the vaccine on themselves, their babies, and the pregnancy.

Spatio-temporal analysis of nanoparticles in live tumor spheroids impacted by cell origin and density.

Nanoparticles hold great preclinical promise in cancer therapy but continue to suffer attrition through clinical trials. Advanced, three dimensional (3D) cellular models such as tumor spheroids can recapitulate elements of the tumor environment and are considered the superior model to evaluate nanoparticle designs. However, there is an important need to better understand nanoparticle penetration kinetics and determine how different cell characteristics may influence this nanoparticle uptake. A key challenge with current approaches for measuring nanoparticle accumulation in spheroids is that they are often static, losing spatial and temporal information which may be necessary for effective nanoparticle evaluation in 3D cell models. To overcome this challenge, we developed an analysis platform, termed the Determination of Nanoparticle Uptake in Tumor Spheroids (DONUTS), which retains spatial and temporal information during quantification, enabling evaluation of nanoparticle uptake in 3D tumor spheroids. Outperforming linear profiling methods, DONUTS was able to measure silica nanoparticle uptake to 10 µm accuracy in both isotropic and irregularly shaped cancer cell spheroids. This was then extended to determine penetration kinetics, first by a forward-in-time, center-in-space model, and then by mathematical modelling, which enabled the direct evaluation of nanoparticle penetration kinetics in different spheroid models. Nanoparticle uptake was shown to inversely relate to particle size and varied depending on the cell type, cell stiffness and density of the spheroid model. The automated analysis method we have developed can be applied to live spheroids in situ, for the advanced evaluation of nanoparticles as delivery agents in cancer therapy.

Nanoscape, a data-driven 3D real-time interactive virtual cell environment.

Our understanding of cellular and structural biology has reached unprecedented levels of detail, and computer visualisation techniques can be used to create three-dimensional (3D) representations of cells and their environment that are useful in both teaching and research. However, extracting and integrating the relevant scientific data, and then presenting them in an effective way, can pose substantial computational and aesthetic challenges. Here we report how computer artists, experts in computer graphics and cell biologists have collaborated to produce a tool called Nanoscape that allows users to explore and interact with 3D representations of cells and their environment that are both scientifically accurate and visually appealing. We believe that using Nanoscape as an immersive learning application will lead to an improved understanding of the complexities of cellular scales, densities and interactions compared with traditional learning modalities.

Analogies in 3D molecular visualisations: development of a cell biology animation 'How cells move - a new interpretation of old data'.

Cell biology and imaging technology have vastly improved over the past decades, enabling scientists to dissect the inner workings of a cell. In addition to technical limits on spatial and temporal resolution, which obscure the picture at the molecular level, the sheer density and complexity of information impede clear understanding. 3D molecular visualisation has therefore blossomed as a way to translate molecular data in a more tangible form. Whilst the molecular machinery involved in cell locomotion has been extensively studied, existing narratives describing how cells generate the forces that drive movement remain unclear. Polymerisation of a protein called actin is clearly essential. The general belief in the cell migration field is that actin polymerisation's main role is to push the leading edge of the cell forwards, while the rest of the cell follows passively. The cell migration & chemotaxis group at the CRUK Beatson Institute propose an alternative hypothesis, in which actin filaments constitute cables. Motor proteins pull on these cables, causing them to behave like the treads of a tank and drive cell movement. This article describes the development of a 3D animation that uses analogical reasoning to contrast the 'tank' hypothesis for cell locomotion with the current dogma.

The Role of Personalized Virtual Reality in Education for Patients Post Stroke-A Qualitative Case Series.

BACKGROUND: Education is essential to promote prevention of recurrent stroke and maximize rehabilitation; however, current techniques are limited and many patients remain dissatisfied. Virtual reality (VR) may provide an alternative way of conveying complex information through a more universal language. AIM: To develop and conduct preliminary assessments on the use of a guided and personalized 3D visualization education session via VR, for stroke survivors and primary caregivers. METHODS: Four poststroke patients and their 4 primary caregivers completed the 3D visualization education session as well as pre- and postintervention interviews. Each patient had a different stroke etiology (i.e., ischemic thrombotic stroke, ischemic embolic stroke, hemorrhagic stroke, and transient ischemic attack followed by ischemic stroke, respectively). This new approach uses preintervention interview responses, patient MRI and CT datasets, VR head mounted displays, 3D computer modeling, and game development software to develop the visualization. Pre- and postintervention interview responses were analyzed using a qualitative phenomenological methodology approach. RESULTS: All participants safely completed the study and were highly satisfied with the education session. In this subset of participants, prior formal stroke education provision was limited. All participants demonstrated varied improvements in knowledge areas including brain anatomy and physiology, brain damage and repair, and stroke-specific information such as individual stroke risk factors and acute treatment benefits. These improvements were accompanied by feelings of closure, acceptance, and a greater motivation to manage their stroke risk. CONCLUSIONS: Preliminary results suggest this approach provides a safe and promising educational tool to promote understanding of individualized stroke experiences.

Rehabilitation doxa and practitioner judgment. An analysis of symbolic violence on health care provision in the Scottish prison system.

This paper presents an analysis of the symbolic conditions which govern health care provision in the Scottish prison system. The paper considers the wider context of Scottish prisons, where health care provision follows a similar structure both in juvenile and adult prisons. Our intention is to provoke a debate about the doxa (Bourdieu, 1977), which underlies decision making in respect of health care in prison, in a political environment where pragmatism, allied to the 'pathologisation' of social policies, health and criminal justice has been a hegemonic force.

Rehabilitation doxa and practitioner judgment. An analysis of symbolic violence on health care provision in the Scottish prison system / Doxa da rehabilitação e o julgamento professional. Uma análise da violência simbólica na provisão de cuidados em saúde no sistema prisional escocês

Abstract This paper presents an analysis of the symbolic conditions which govern health care provision in the Scottish prison system. The paper considers the wider context of Scottish prisons, where health care provision follows a similar structure both in juvenile and adult prisons. Our intention is to provoke a debate about the doxa (Bourdieu, 1977), which underlies decision making in respect of health care in prison, in a political environment where pragmatism, allied to the 'pathologisation' of social policies, health and criminal justice has been a hegemonic force.

Resumo Este artigo apresenta uma análise das condições simbólicas que governam a provisão de saúde nos sistemas prisional escocês. O artigo considera o contexto ampliado do sistema prisonal escocês, onde a provisão de saúde segue uma estrutura similar tanto nas unidades juvenis quanto nas de adultos. Nossa intenção é provocar um debate sobre a doxa (Bourdieu, 1977) que sustenta as tomadas de decisão sobre provisão de saúde nas prisões, onde o contexto político marcado pelo pragmatismo, aliado à 'patologização' das políticas sociais, de saúde e de justiça criminal, tem sido uma força hegemônica.

Journey to the centre of the cell: Virtual reality immersion into scientific data.

Visualization of scientific data is crucial not only for scientific discovery but also to communicate science and medicine to both experts and a general audience. Until recently, we have been limited to visualizing the three-dimensional (3D) world of biology in 2 dimensions. Renderings of 3D cells are still traditionally displayed using two-dimensional (2D) media, such as on a computer screen or paper. However, the advent of consumer grade virtual reality (VR) headsets such as Oculus Rift and HTC Vive means it is now possible to visualize and interact with scientific data in a 3D virtual world. In addition, new microscopic methods provide an unprecedented opportunity to obtain new 3D data sets. In this perspective article, we highlight how we have used cutting edge imaging techniques to build a 3D virtual model of a cell from serial block-face scanning electron microscope (SBEM) imaging data. This model allows scientists, students and members of the public to explore and interact with a "real" cell. Early testing of this immersive environment indicates a significant improvement in students' understanding of cellular processes and points to a new future of learning and public engagement. In addition, we speculate that VR can become a new tool for researchers studying cellular architecture and processes by populating VR models with molecular data.

A benchmarking method to evaluate the accuracy of a commercial proton monte carlo pencil beam scanning treatment planning system.

AcurosPT is a Monte Carlo algorithm in the Eclipse 13.7 treatment planning system, which is designed to provide rapid and accurate dose calculations for proton therapy. Computational run-time in minimized by simplifying or eliminating less significant physics processes. In this article, the accuracy of AcurosPT was benchmarked against both measurement and an independent MC calculation, TOPAS. Such a method can be applied to any new MC calculation for the detection of potential inaccuracies. To validate multiple Coulomb scattering (MCS) which affects primary beam broadening, single spot profiles in a Solidwater® phantom were compared for beams of five selected proton energies between AcurosPT, measurement and TOPAS. The spot Gaussian sigma in AcurosPT was found to increase faster with depth than both measurement and TOPAS, suggesting that the MCS algorithm in AcurosPT overestimates the scattering effect. To validate AcurosPT modeling of the halo component beyond primary beam broadening, field size factors (FSF) were compared for multi-spot profiles measured in a water phantom. The FSF for small field sizes were found to disagree with measurement, with the disagreement increasing with depth. Conversely, TOPAS simulations of the same FSF consistently agreed with measurement to within 1.5%. The disagreement in absolute dose between AcurosPT and measurement was smaller than 2% at the mid-range depth of multi-energy beams. While AcurosPT calculates acceptable dose distributions for typical clinical beams, users are cautioned of potentially larger errors at distal depths due to overestimated MCS and halo implementation.

A theory-informed approach to developing visually mediated interventions to change behaviour using an asthma and physical activity intervention exemplar.

BACKGROUND: Visualisation techniques are used in a range of healthcare interventions. However, these frequently lack a coherent rationale or clear theoretical basis. This lack of definition and explicit targeting of the underlying mechanisms may impede the success of and evaluation of the intervention. We describe the theoretical development, deployment, and pilot evaluation, of a complex visually mediated behavioural intervention. The exemplar intervention focused on increasing physical activity among young people with asthma. We employed an explicit five-stage development model, which was actively supported by a consultative user group. The developmental stages involved establishing the theoretical basis, establishing a narrative structure, visual rendering, checking interpretation, and pilot testing. We conducted in-depth interviews and focus groups during early development and checking, followed by an online experiment for pilot testing. A total of 91 individuals, including young people with asthma, parents, teachers, and health professionals, were involved in development and testing. RESULTS: Our final intervention consisted of two components: (1) an interactive 3D computer animation to create intentions and (2) an action plan and volitional help sheet to promote the translation of intentions to behaviour. Theory was mediated throughout by visual and audio forms. The intervention was regarded as highly acceptable, engaging, and meaningful by all stakeholders. The perceived impact on asthma understanding and intentions was reported positively, with most individuals saying that the 3D computer animation had either clarified a range of issues or made them more real. Our five-stage model underpinned by extensive consultation worked well and is presented as a framework to support explicit decision-making for others developing theory informed visually mediated interventions. CONCLUSIONS: We have demonstrated the ability to develop theory-based visually mediated behavioural interventions. However, attention needs to be paid to the potential ambiguity associated with images and thus the concept of visual literacy among patients. Our revised model may be helpful as a guide to aid development, acceptability, and ultimately effectiveness.

Validation of a new grid-based Boltzmann equation solver for dose calculation in radiotherapy with photon beams.

A new grid-based Boltzmann equation solver, Acuros, was developed specifically for performing accurate and rapid radiotherapy dose calculations. In this study we benchmarked its performance against Monte Carlo for 6 and 18 MV photon beams in heterogeneous media. Acuros solves the coupled Boltzmann transport equations for neutral and charged particles on a locally adaptive Cartesian grid. The Acuros solver is an optimized rewrite of the general purpose Attila software, and for comparable accuracy levels, it is roughly an order of magnitude faster than Attila. Comparisons were made between Monte Carlo (EGSnrc) and Acuros for 6 and 18 MV photon beams impinging on a slab phantom comprising tissue, bone and lung materials. To provide an accurate reference solution, Monte Carlo simulations were run to a tight statistical uncertainty (sigma approximately 0.1%) and fine resolution (1-2 mm). Acuros results were output on a 2 mm cubic voxel grid encompassing the entire phantom. Comparisons were also made for a breast treatment plan on an anthropomorphic phantom. For the slab phantom in regions where the dose exceeded 10% of the maximum dose, agreement between Acuros and Monte Carlo was within 2% of the local dose or 1 mm distance to agreement. For the breast case, agreement was within 2% of local dose or 2 mm distance to agreement in 99.9% of voxels where the dose exceeded 10% of the prescription dose. Elsewhere, in low dose regions, agreement for all cases was within 1% of the maximum dose. Since all Acuros calculations required less than 5 min on a dual-core two-processor workstation, it is efficient enough for routine clinical use. Additionally, since Acuros calculation times are only weakly dependent on the number of beams, Acuros may ideally be suited to arc therapies, where current clinical algorithms may incur long calculation times.

3-D visualization and animation technologies in anatomical imaging.

This paper explores a 3-D computer artist's approach to the creation of three-dimensional computer-generated imagery (CGI) derived from clinical scan data. Interpretation of scientific imagery, such as magnetic resonance imaging (MRI), is restricted to the eye of the trained medical practitioner in a clinical or scientific context. In the research work described here, MRI data are visualized and interpreted by a 3-D computer artist using the tools of the digital animator to navigate image complexity and widen interaction. In this process, the artefact moves across disciplines; it is no longer tethered to its diagnostic origins. It becomes an object that has visual attributes such as light, texture and composition, and a visual aesthetic of its own. The introduction of these visual attributes provides a platform for improved accessibility by a lay audience. The paper argues that this more artisan approach to clinical data visualization has a potential real-world application as a communicative tool for clinicians and patients during consultation.

Feasibility of a multigroup deterministic solution method for three-dimensional radiotherapy dose calculations.

PURPOSE: To investigate the potential of a novel deterministic solver, Attila, for external photon beam radiotherapy dose calculations. METHODS AND MATERIALS: Two hypothetical cases for prostate and head-and-neck cancer photon beam treatment plans were calculated using Attila and EGSnrc Monte Carlo simulations. Open beams were modeled as isotropic photon point sources collimated to specified field sizes. The sources had a realistic energy spectrum calculated by Monte Carlo for a Varian Clinac 2100 operated in a 6-MV photon mode. The Attila computational grids consisted of 106,000 elements, or 424,000 spatial degrees of freedom, for the prostate case, and 123,000 tetrahedral elements, or 492,000 spatial degrees of freedom, for the head-and-neck cases. RESULTS: For both cases, results demonstrate excellent agreement between Attila and EGSnrc in all areas, including the build-up regions, near heterogeneities, and at the beam penumbra. Dose agreement for 99% of the voxels was within the 3% (relative point-wise difference) or 3-mm distance-to-agreement criterion. Localized differences between the Attila and EGSnrc results were observed at bone and soft-tissue interfaces and are attributable to the effect of voxel material homogenization in calculating dose-to-medium in EGSnrc. For both cases, Attila calculation times were <20 central processing unit minutes on a single 2.2-GHz AMD Opteron processor. CONCLUSIONS: The methods in Attila have the potential to be the basis for an efficient dose engine for patient-specific treatment planning, providing accuracy similar to that obtained by Monte Carlo.

Radiative transport-based frequency-domain fluorescence tomography.

We report the development of radiative transport model-based fluorescence optical tomography from frequency-domain boundary measurements. The coupled radiative transport model for describing NIR fluorescence propagation in tissue is solved by a novel software based on the established Attila particle transport simulation platform. The proposed scheme enables the prediction of fluorescence measurements with non-contact sources and detectors at a minimal computational cost. An adjoint transport solution-based fluorescence tomography algorithm is implemented on dual grids to efficiently assemble the measurement sensitivity Jacobian matrix. Finally, we demonstrate fluorescence tomography on a realistic computational mouse model to locate nM to microM fluorophore concentration distributions in simulated mouse organs.

Radiative transport in fluorescence-enhanced frequency domain photon migration.

Small animal optical tomography has significant, but potential application for streamlining drug discovery and pre-clinical investigation of drug candidates. However, accurate modeling of photon propagation in small animal volumes is critical to quantitatively obtain accurate tomographic images. Herein we present solutions from a robust fluorescence-enhanced, frequency domain radiative transport equation (RTE) solver with unique attributes that facilitate its deployment within tomographic algorithms. Specifically, the coupled equations describing time-dependent excitation and emission light transport are solved using discrete ordinates (SN) angular differencing along with linear discontinuous finite-element spatial differencing on unstructured tetrahedral grids. Source iteration in conjunction with diffusion synthetic acceleration is used to iteratively solve the resulting system of equations. This RTE solver can accurately and efficiently predict ballistic as well as diffusion limited transport regimes which could simultaneously exist in small animals. Furthermore, the solver provides accurate solutions on unstructured, tetrahedral grids with relatively large element sizes as compared to commonly employed solvers that use step differencing. The predictions of the solver are validated by a series of frequency-domain, phantom measurements with optical properties ranging from diffusion limited to transport limited propagation. Our results demonstrate that the RTE solution consistently matches measurements made under both diffusion and transport-limited conditions. This work demonstrates the use of an appropriate RTE solver for deployment in small animal optical tomography.