Automatic reconstruction from serial sections

In many experiments in biological and medical research, serial sectioning of biological material is the only way to reveal the three dimensional (3D) structure and function. For a number of reasons other 3D imaging techniques, such as CT, MRI, and confocal microscopy, are not always adequate because they cannot provide the necessary resolution or contrast, or because the specimen is too large, or because the staining techniques require sectioning. Therefore for the foreseeable future reconstruction from serial sections will remain the only method for 3D investigations in many biomedical fields. Reconstruction is a difficult problem due to the loss of 3D alignment as the sections are cut and, more seriously, the systematic and random distortion caused by the sectioning and preparation processes.Many authors have reported how serial sections can be registered by means of fiducial markers or otherwise, but there have been only a few studies of automated correction of the sectioning distortions. In this thesis solutions to the registration problem are reviewed and discussed, and a solution to the warping problem, based on image pro¬ cessing techniques and the finite element method (FEM), is presented. The aim of this project was to develop a fully automatic method of reconstruction in order to provide a 3D atlas of mouse development as part of a gene expression database. For this purpose it is not necessary to warp the object so that it is identical to the original object, but to correct local distortions in the sections in order to produce a smooth representative mouse embryo. Furthermore the use of fiducial markers was not possible because the reconstructions were from already sectioned material.In this thesis we demonstrate a new method for warping serial sections. The sections are warped by applying forces to each section, where each section is modelled as a thin elastic plate. The deformation forces are determined from correspondences between sections which are calculated by combining match strengths and positional information. The equilibrium state which represents the reconstructed 3D image is calculated using the finite element method. Results of the application of these methods to paraffin wax and resin embedded sections of the mouse embryo are presented

Special Issue Health Care Law and the Rights of Individuals with Disabilities

People with disabilities are vulnerable. They carry high risk for poor health and health outcomes. As a group, they experience social disadvantages such as poverty, underemployment and unemployment, isolation, and discrimination at a higher rate than the general population. They also face multiple barriers to quality health care and report poorer health status than people without disabilities. This Special Issue will explore the key health disparities and barriers to health care experienced by people with disabilities, and explore the legal, ethical, and social issues they raise. It will investigate the legal requirements of the Americans with Disabilities and other antidiscrimination laws as they apply to health and health care, the implications of health care reform efforts affecting people with disabilities, and other uses of law and policy to promote health determinants, such as access to education and work opportunities, a life in a community, and full participation in society for people with disabilities

A new method for parsing student text to support computer-assisted assessment of free text answers

Due to current trends in staff-student ratios, the assessment burden on staff will increase unless either students are assessed less, or alternative approaches are used. Much research and effort has been aimed at automated assessment but to date the most reliable method is to use variations of multiple choice questions. However, it is hard and time consuming to design sets of questions that foster deep learning. Although methods for assessing free text answers have been proposed, these are not very reliable because they either involve pattern matching or the analysis of frequencies in a “bag of words”. The first step towards automatic marking of free text answers by comparing the meaning of student answers with a single model answer is to parse the student work. However, because not all students are good at writing grammatically correct English, it is vital that any parsing algorithm can handle ungrammatical text. In this paper, we present preliminary results of using a relatively new linguistic theory, Role and Reference Grammar, to parse student texts and show that ungrammatical sentences can be parsed

An investigation into the potential use of the histone deacetylase inhibitor, valproic acid for the prevention of gastric cancer in high-risk families

Hereditary diffuse gastric cancer (HDGC) is a cancer syndrome caused by germline mutation of the CDH1 gene that encodes the cell adhesion tumor suppressor protein E-cadherin. Mutation carriers have a lifetime risk higher than 70% of developing diffuse gastric cancer, along with an elevated risk of lobular breast cancer. Mutation carriers develop multi focal stage T1a signet ring cell carcinoma as early as 16-years. Development of these foci follow after somatic inactivation of the second CDH1 allele by mechanisms that include DNA promoter hypermethylation, followed by an indolent stage that can last years before further tumor progression. Valproic acid (VPA) and Decitabine (DAC) were to be used as an epigenetic therapy, they each have been identified in the literature for their anticancer properties. In this study a combination of VPA and DAC were used to test chemopreventive capabilities on three cell lines, non-malignant breast MCF10a cells, positive control non-small lung carcinoma NCI-H460 cells and a gastric adenocarcinoma AGS cells. Gene expression of CDH1 was analysed by real-time qPCR and western blotting. VPA was further characterised in MCF10a cells by analysing transcriptome sequence (RNA-Seq) and DNA methylation status changes (Illumina 450k Methyl-array). Both VPA and DAC increased E-cadherin expression in each of the cell lines, however E-cadherin up regulation was transient after VPA treatment withdrawal in MCF10a cells. No synergistic effects between VPA and DAC were detected in MCF10a cells, but a synergistic effect was observed in NCI-H460 cells. VPA treatment in MCF10a cells resulted in gene expression changes associated with cell proliferation and cell cycle. VPA had no measurable effect on DNA methylation levels in MCF10a cells. To further study VPA gene expression changes eleven migraine and epilepsy patients treated with VPA from the Dunedin hospital had buccal and whole blood samples taken before and after VPA treatment. No identifiable trends were detected by real-time qPCR either in the target gene, CDH1 or potential VPA surrogate genes identified from transcriptome data, TGM2 and ADAM23. Overall the characterised effects of VPA in MCF10a cells, were, down-regulation of genes associated with cell proliferation and cell cycle. Because of the transient increase in CDH1 expression in MCF10a cells and the inability to detect a change in expression in neurological patients after VPA treatment, VPA will require further evidence to support its use as a chemopreventive agent in the HDGC syndrome

Hippocampal Proteomic and Metabonomic Abnormalities in Neurotransmission, Oxidative Stress, and Apoptotic Pathways in a Chronic Phencyclidine Rat Model.

Schizophrenia is a neuropsychiatric disorder affecting 1% of the world's population. Due to both a broad range of symptoms and disease heterogeneity, current therapeutic approaches to treat schizophrenia fail to address all symptomatic manifestations of the disease. Therefore, disease models that reproduce core pathological features of schizophrenia are needed for the elucidation of pathological disease mechanisms. Here, we employ a comprehensive global label-free liquid chromatography-mass spectrometry proteomic (LC-MS(E)) and metabonomic (LC-MS) profiling analysis combined with the targeted proteomics (selected reaction monitoring and multiplex immunoassay) of serum and brain tissues to investigate a chronic phencyclidine (PCP) rat model in which glutamatergic hypofunction is induced through noncompetitive NMDAR-receptor antagonism. Using a multiplex immunoassay, we identified alterations in the levels of several cytokines (IL-5, IL-2, and IL-1β) and fibroblast growth factor-2. Extensive proteomic and metabonomic brain tissue profiling revealed a more prominent effect of chronic PCP treatment on both the hippocampal proteome and metabonome compared to the effect on the frontal cortex. Bioinformatic pathway analysis confirmed prominent abnormalities in NMDA-receptor-associated pathways in both brain regions, as well as alterations in other neurotransmitter systems such as kainate, AMPA, and GABAergic signaling in the hippocampus and in proteins associated with neurodegeneration. We further identified abundance changes in the level of the superoxide dismutase enzyme (SODC) in both the frontal cortex and hippocampus, which indicates alterations in oxidative stress and substantiates the apoptotic pathway alterations. The present study could lead to an increased understanding of how perturbed glutamate receptor signaling affects other relevant biological pathways in schizophrenia and, therefore, support drug discovery efforts for the improved treatment of patients suffering from this debilitating psychiatric disorder.This research was kindly supported by the Stanley Medical Research Institute (SMRI), the Innovative Medicines Initiative for Novel Methods leading to New Medications in Depression and Schizophrenia (IMI NEWMEDS), the Dutch Fund for Economic Structure Reinforcement ((#0908) the NeuroBasic PharmaPhenomics project. EJW acknowledges Waters Corporation for funding.This is the accepted manuscript. The final version is available at http://dx.doi.org/10.1021/acs.jproteome.5b00105

Biobehavioral effects of Tai Chi Qigong in men with prostate cancer: Study design of a three-arm randomized clinical trial.

Fatigue is often one of the most commonly reported symptoms in prostate cancer survivors, but it is also one of the least understood cancer-related symptoms. Fatigue is associated with psychological distress, disruptions in sleep quality, and impairments in health-related quality of life. Moreover, inflammatory processes and changes related to the hypothalamic-pituitary-adrenal (HPA) axis and/or autonomic nervous system may also play a role in cancer-related fatigue. Thus, effective treatments for fatigue in prostate cancer survivors represent a current unmet need. Prior research has shown that Tai Chi Qigong, a mind-body exercise intervention, can improve physical and emotional health. Herein, we describe the protocol of the ongoing 3-arm randomized controlled Health Empowerment & Recovery Outcomes (HERO) clincal trial. One hundred sixty-six prostate cancer survivors with fatigue are randomized to a modified Tai Chi Qigong intervention (TCQ), intensity-matched body training intervention (BT), or usual care (UC) condition. Guided by biopsychosocial and psychoneuroimmunology models, we propose that TCQ, as compared to BT or UC will: i) reduce fatigue (primary outcome) in prostate cancer survivors; ii) reduce inflammation; and iii) regulate the expression of genes from two major functional clusters: a) inflammation, vasodilation and metabolite sensing and b) energy and adrenergic activation. Assessments are conducted at baseline, the 6-week midpoint of the intervention, and 1 week, 3 months, and 12 months post-intervention. If our findings show that TCQ promotes recovery from prostate cancer and its treatment, this type of intervention can be integrated into survivorship care plans as the standard of care. The study's findings will also provide novel information about underlying biobehavioral mechanisms of cancer-related fatigue. Trial registration number:NCT03326713; clinicaltrials.gov

Psychosocial interventions for children and young people with visible differences resulting from appearance-altering conditions, injury, or treatment effects: An updated systematic review

AbstractObjectiveChildren and young people with visible differences can experience psychosocial difficulties, such as anxiety and teasing by others. Interventions targeting difficulties have previously been reviewed by Jenkinson et al. This review aimed to identify and critically assess recent studies evaluating the effectiveness of psychosocial interventions for children and young people with visible differences on psychosocial wellbeing, self-esteem, and social experiences and compare the findings with Jenkinson et al. using a replacement review process.MethodsInclusion criteria are as follows: studies with participants aged 0–18 years with visible differences; investigating a psychosocial intervention; including comparison with an alternative intervention, control group, or pre- and post-intervention; and including a quantitative measure assessed pre- and post-intervention. Exclusion criteria are as follows: participants with body dysmorphic disorder or appearance changes due to eating disorders or obesity and studies not written in English. MEDLINE, AMED, and PsycInfo were searched and grey literature was included. Results were reviewed against eligibility criteria, data were extracted, and studies were evaluated using the Cochrane Risk of Bias 2 tool.ResultsUsing Jenkinson et al. as one source of studies, 24 studies were included evaluating a range of interventions such as social interaction skills training, residential social camps, and cognitive behavioral therapy. Risk of bias was high in 20 studies and of some concern in four studies.ConclusionThere is some evidence of the effectiveness of hypnotherapy, a relaxation response resiliency program, integrative body-mind-spirit group, and therapeutic patient education, but more rigorous research is needed to confirm their impact on psychosocial outcomes

A Dataset for Learning Graph Representations to Predict Customer Returns in Fashion Retail

We present a novel dataset collected by ASOS (a major online fashion retailer) to address the challenge of predicting customer returns in a fashion retail ecosystem. With the release of this substantial dataset we hope to motivate further collaboration between research communities and the fashion industry. We first explore the structure of this dataset with a focus on the application of Graph Representation Learning in order to exploit the natural data structure and provide statistical insights into particular features within the data. In addition to this, we show examples of a return prediction classification task with a selection of baseline models (i.e. with no intermediate representation learning step) and a graph representation based model. We show that in a downstream return prediction classification task, an F1-score of 0.792 can be found using a Graph Neural Network (GNN), improving upon other models discussed in this work. Alongside this increased F1-score, we also present a lower cross-entropy loss by recasting the data into a graph structure, indicating more robust predictions from a GNN based solution. These results provide evidence that GNNs could provide more impactful and usable classifications than other baseline models on the presented dataset and with this motivation, we hope to encourage further research into graph-based approaches using the ASOS GraphReturns dataset.Comment: The ASOS GraphReturns dataset can be found at https://osf.io/c793h/. Accepted at FashionXRecSys 2022 workshop. Published Versio

System-based proteomic and metabonomic analysis of the Df(16)A+/- mouse identifies potential miR-185 targets and molecular pathway alterations

Deletions on chromosome 22q11.2 are a strong genetic risk factor for development of schizophrenia and cognitive dysfunction. We employed shotgun liquid chromatography-mass spectrometry (LC-MS) proteomic and metabonomic profiling approaches on prefrontal cortex (PFC) and hippocampal (HPC) tissue from Df(16)A +/- mice, a model of the 22q11.2 deletion syndrome. Proteomic results were compared with previous transcriptomic profiling studies of the same brain regions. The aim was to investigate how the combined effect of the 22q11.2 deletion and the corresponding miRNA dysregulation affects the cell biology at the systems level. The proteomic brain profiling analysis revealed PFC and HPC changes in various molecular pathways associated with chromatin remodelling and RNA transcription, indicative of an epigenetic component of the 22q11.2DS. Further, alterations in glycolysis/gluconeogenesis, mitochondrial function and lipid biosynthesis were identified. Metabonomic profiling substantiated the proteomic findings by identifying changes in 22q11.2 deletion syndrome (22q11.2DS)-related pathways, such as changes in ceramide phosphoethanolamines, sphingomyelin, carnitines, tyrosine derivates and panthothenic acid. The proteomic findings were confirmed using selected reaction monitoring mass spectrometry, validating decreased levels of several proteins encoded on 22q11.2, increased levels of the computationally predicted putative miR-185 targets UDP-N-acetylglucosamine-peptide N-acetylglucosaminyltransferase 110 kDa subunit (OGT1) and kinesin heavy chain isoform 5A and alterations in the non-miR-185 targets serine/threonine-protein phosphatase 2B catalytic subunit gamma isoform, neurofilament light chain and vesicular glutamate transporter 1. Furthermore, alterations in the proteins associated with mammalian target of rapamycin signalling were detected in the PFC and with glutamatergic signalling in the hippocampus. Based on the proteomic and metabonomic findings, we were able to develop a schematic model summarizing the most prominent molecular network findings in the Df(16)A +/- mouse. Interestingly, the implicated pathways can be linked to one of the most consistent and strongest proteomic candidates, (OGT1), which is a predicted miR-185 target. Our results provide novel insights into system-biological mechanisms associated with the 22q11DS, which may be linked to cognitive dysfunction and an increased risk to develop schizophrenia. Further investigation of these pathways could help to identify novel drug targets for the treatment of schizophrenia

What the World Happiness Report doesn’t see: The sociocultural contours of wellbeing in northern Tanzania

This paper presents a mixed methods approach to understanding wellbeing in the Kilimanjaro region of northern Tanzania—a country consistently ranked by the World Happiness Report as one of the least happy in the world.  A primary objective is to demonstrate how qualitative data offering bottom-up perspectives on wellbeing offer a necessary complement to quantitative self-report measures, allowing for more nuanced cultural understandings of lived experience and wellbeing that recognize diversity both globally and locally. The research contextualized responses to standardized life evaluations (including the Cantril ladder question used by the World Happiness Report) through observations and interviews along with culturally sensitive measures of emotional experience.  Findings show Kilimanjaro to have more positive life evaluations than Tanzania as a whole, and significant within-region demographic variation driven particularly by lower levels of wellbeing for nonprofessional women compared with nonprofessional men and professionals.  In part because such demographic groups were often unfamiliar with standardized self-report measures, it was only through interviews, case studies, and culturally sensitive reports of emotional experience that we were able to recognize the diverse and nuanced life circumstances which individuals and groups were navigating and how those circumstances interacted with wellbeing.  Drawing on the example of nonprofessional women for illustration, we describe how key sociocultural factors – particularly, family stability, parenting circumstances, social relationships, and meeting life course expectations -- intersect with economic realities to create varied experiences of wellbeing. The complex picture of locally understood wellbeing that emerged from this research presents an alternative picture to global perspectives reliant on survey self-reports. It serves as a reminder of the importance of methodological choices in global wellbeing research and urges the addition of local perspectives and paradigms to inform policy and practice