Miracle-dz/UniFAR-FTUs huggingface dataset:
Application of "A3 thinking" to operational improvements in radiation oncology

The grand challenge for most healthcare organizations is to develop systems that deliver value to every patient. The purpose of our talk is to demonstrate how we have systematically been incorporating quality and safety improvement initiatives using Plan-Do-Study-Act (PDSA) thinking supported by Toyota’s "A3” tool into our academic radiation oncology clinic at the University of North Carolina (UNC). We herein quantify the impact of these A3 initiatives on prospectively collected, clinically meaningful, metrics. The data from key quality and safety improvement initiatives are presented. In summary, we show that improvement initiatives can be successfully implemented using A3 thinking approach in an academic radiation oncology department to yield measurable improvements in operations resulting in improvement in patient safety culture.
Utilizing Social Media Data for Psychoanalysis to Study Human Personality

Social media data, for instance from Twitter or Facebook, provide a new type of data that consist of a mixture of text, image and video information. From a scientific point of view, the capabilities of this type of data from such microblogs are not well explored and to date it is largely unknown what principal knowledge can be extracted thereof. In this paper, we present a discussion of the capabilities of data from microblogs for performing a psychoanalysis. This could allow an analysis of the human personality of individual users. Such prospects raises serious concerns regarding the privacy of users of social media platforms.
The Impact of Transcranial Direct Current Stimulation on Upper-Limb Motor Performance in Healthy Adults: A Systematic Review and Meta-Analysis

Background: Transcranial direct current stimulation (tDCS) has previously been reported to improve facets of upper limb motor performance such as accuracy and strength. However, the magnitude of motor performance improvement has not been reviewed by contemporaneous systematic review or meta-analysis of sham vs. active tDCS. Objective: To systematically review and meta-analyse the existing evidence regarding the benefits of tDCS on upper limb motor performance in healthy adults. Methods: A systematic search was conducted to obtain relevant articles from three databases (MEDLINE, EMBASE, and PsycINFO) yielding 3,200 abstracts. Following independent assessment by two reviewers, a total of 86 articles were included for review, of which 37 were deemed suitable for meta-analysis. Results: Meta-analyses were performed for four outcome measures, namely: reaction time (RT), execution time (ET), time to task failure (TTF), and force. Further qualitative review was performed for accuracy and error. Statistically significant improvements in RT (effect size −0.01; 95% CI −0.02 to 0.001, p = 0.03) and ET (effect size −0.03; 95% CI −0.05 to −0.01, p = 0.017) were demonstrated compared to sham. In exercise tasks, increased force (effect size 0.10; 95% CI 0.08 to 0.13, p < 0.001) and a trend towards improved TTF was also observed. Conclusions: This meta-analysis provides evidence attesting to the impact of tDCS on upper limb motor performance in healthy adults. Improved performance is demonstrable in reaction time, task completion time, elbow flexion tasks and accuracy. Considerable heterogeneity exists amongst the literature, further confirming the need for a standardised approach to reporting tDCS studies.
Three-dimensional Segmentation of Trees Through a Flexible Multi-Class Graph Cut Algorithm (MCGC)

Jonathan Williams holds a NERC studentship [NE/N008952/1] which is a CASE partnership with support from Royal Society for the Protection of Birds (RSPB). David Coomes was supported by an International Academic Fellowship from the Leverhulme Trust. Carola-Bibiane Schoenlieb was supported by the RISE projects CHiPS and NoMADS, the Cantab Capital Institute for the Mathematics of Information and the Alan Turing Institute. We gratefully acknowledge the support of NVIDIA Corporation with the donation of a Quadro P6000 GPU used for this research.
Étude de l’immunité antivaricelleuse chez l’enfant transplanté au moyen de moelle osseuse ou de sang de cordon ombilical

L’infection primaire au VZV et la reactivation du VZV latent sont frequemment observees a la suite d’une GMO ou d’une GSCO, ce qui cause de serieuses complications chez le patient. Pour prevenir ces infections, une prophylaxie antivirale est administree systematiquement chez tous les greffes de MO ou de SCO, alors qu’il n’existe aucun consensus sur la duree optimale d’une telle prophylaxie. Pour resoudre ce probleme, notre objectif est de developper et valider une methode ELISpot-VZV-IFN- qui permettra de suivre la reconstitution de l’immunite a mediation cellulaire anti-VZV chez les receveurs de GMO ou de GSCO et ainsi determiner le moment opportun pour reduire ou interrompe la prophylaxie chez les receveurs de greffes de CSH. Dans un premier temps, des valeurs-seuil de la reponse a mediation cellulaire anti-VZV chez la population pediatrique saine ont du etre generees. A la lumiere de nos resultats, un enfant avec un resultat ELISpot-VZV-IFN- > 190.0 SFU/106 PBMC devrait etre protege contre une possible infection a VZV. Pour valider cette etude, une etude prospective de la reconstitution immunitaire anti-VZV a ete effectuee chez 9 enfants greffes de MO ou de SCO. Nos resultats preliminaires ont montre qu’il n’y avait eu aucune reconstitution significative de l’immunite a mediation cellulaire anti-VZV dans les 18 premiers mois post-transplantation chez 8 de ces 9 enfants. Les resultats de ces experiences vont fournir d’importantes informations quant a la reconstitution de l’immunite anti-VZV a la suite d’une GMO ou d’une GSCO et pourraient permettre l’amelioration des soins apportes aux receveurs de GMO ou de GSCO.
Efficacy of lyophilized cell-free supernatant of Lactobacillus salivarius (Ls-BU2) on Escherichia coli and shelf life of ground beef

In the present study, the effect of different concentrations of cell-free supernatant (CFS; 10.00 and 35.00 mg g-1) of Lactobacillus salivarius (Ls-BU2) on chemical, microbial and sensorial specifications of ground beef stored under the refrigerated condition was investigated. The antibacterial activity of CFS on Escherichia coli was also assessed. According to agar-disk diffusion method, CFS of Ls-BU2 revealed a promising antibacterial activity against E. coli in culture media compared to CFS of a well-known probiotic (L. acidophilus LA-5). In meat, CFS of Ls-BU2 showed a minimal effective concentration (MEC) of 35.00 mg g-1 on E. coli, while CFS of L. acidophilus represented a MEC of 45.00 mg g-1. The CFS of Ls-BU2 at 35.00 mg g-1 concentration retained psychrophilic counts of meat at a lower value than maximum accepted level (7 log10 CFU g-1). In a similar trend, CFS of Ls-BU2 at 35.00 mg g-1 concentration was also displayed high sensorial scores compared to other CFS-treated samples. In conclusion, we demonstrated that CFS of Ls-BU2 and to some extent CFS of L. acidophilus could act as a safe food additive for the control of bacterial pathogens and to extend the shelf life of ground beef.
Poor Results of Flow Diversion as Salvage Treatment for Intracranial Aneurysm Rerupture After Surgical Clip Reconstruction

Rebleeding episodes after a ruptured intracranial aneurysm has been secured are considered a significant source of patient morbidity and mortality. Theoretically, acute treatment with a flow-diversion device may offer a reasonable treatment option to prevent future bleeding and to remodel the diseased vessel segment. The authors identified two patients who underwent emergent treatment with the placement of a Pipeline Embolization Device (PED) in the setting of an acute rebleeding of a ruptured intracranial aneurysm previously treated with clip reconstruction. The first patient was a 50-year-old woman who underwent clip reconstruction for a broad-based right anterior choroidal artery aneurysm measuring approximately 2×8 mm. Clip reconstruction was achieved with a single fenestrated clip. On day 14, the patient experienced a rebleeding episode. She underwent emergent treatment with a single PED but experienced another rebleeding and died. The second patient was a 53-year-old woman who presented with a ruptured dorsal variant blister aneurysm, which was treated with clip reconstruction. On day 22, she experienced a rebleeding episode and underwent emergent treatment using two PEDs in a duplicative fashion. After the procedure, she experienced another acute rebleeding episode and died. The treatment of reruptured intracranial aneurysms in a salvage fashion with emergent placement of PEDs in two patients resulted in good technical placement of the device covering the neck of the aneurysm, yet both patients experienced additional rebleeding and did not survive. Future generations of flow diverters may have more appropriate properties that would allow their use as salvage treatment in the setting of acutely ruptured aneurysms.
Entangled Ethnography: Towards a collective future understanding

In this work, we develop a vision for entangled ethnography, where constellations of people, artefacts, algorithms and data come together to collectively make sense of the relations between people and objects. This is grounded in New Materialism’s picture of a world understood through entanglement, through resonant constellations, through a multiplicity of unique individual viewpoints and their relationships. These perspectives are especially relevant for design ethnography, in particular for research around smart connected products, which collect data about their environment, the networks they are a part of, and the ways they are used. However, we are concerned about the current trend of many connected systems towards surveillance capitalism, as data is colonised, machinations are hidden, and a narrow definition of value is extracted. There is a key tension that while design, particularly of networked objects, attempts to go beyond human centeredness, the infrastructures that support it are moving towards a less than human perspective in their race to accumulate and dispossess. Our work tries to imagine the situations where participants in networked systems are richly engaged, rather than exploited. We hope for a future where human agency is central to a respectful and acceptable collaborative development of understanding.
Thitarodes shambalaensis sp. nov. (Lepidoptera, Hepialidae): a new host of the caterpillar fungus Ophiocordyceps sinensis supported by genome-wide SNP data

Abstract A new species of ghost moth, Thitarodes shambalaensissp. nov., is described from Yanzigou glacier, Mt. Gongga, Sichuan, China. The species is a host of the economically important caterpillar fungus Ophiocordyceps sinensis. Establishment of this new species is supported by morphology and genetic differentiation measured in a CO1 phylogeny and in genome-wide SNP coverage. A summary tree from 538 sequences of different genetic markers from Thitarodes (including sequences extracted from caterpillar fungus sclerotium samples) support the genus Thitarodes as a monophyletic group, and indicate that Thitarodes is the host genus for O. sinensis. Sampling efforts so far have centered on half of the known phylogenetic diversity of Thitarodes, with some species-level clusters (separated by < 2.5% genetic distance) containing 17 described species. Fifteen clusters are known from either a single “orphan taxon” or a single sequence from a caterpillar fungus sclerotium sample. We provide suggestions for building a more robust phylogeny of the genus Thitarodes and highlight some of the conservation threats that species from this genus face due to unprecedented habitat exploitation.
Classification of Hard Exudates in Fundus Images using Support Vector Machine Classifier.

Diabetic retinopathy (DR) is one of the potential complications of diabetes that may cause blindness in people worldwide. The purpose of computer-aided detection or diagnosis (CAD) technology has to serve as a second reader for the radiologists. This paper presents an algorithm based on Support Vector Machine for the computer-assisted detection of exudates in fundus images of human retina for the diagnosis of diabetic retinopathy. The disease is diagnosed by the presence of exudates in the macular region. The selected feature vectors are then classified using a Support Vector Machine classifier. The algorithm was implemented using a large image dataset consisting of 300 manually labeled retinal images, and could identify affected retinal images with 95.0% sensitivity and specificity of 92.3%.
Exploring Machine Learning Approaches for Classifying Mental Workload using fNIRS Data from HCI Tasks

Functional Near-Infrared Spectroscopy (fNIRS) has shown promise for being potentially more suitable (than e.g. EEG) for brain-based Human Computer Interaction (HCI). While some machine learning approaches have been used in prior HCI work, this paper explores different approaches and configurations for classifying Mental Workload (MWL) from a continuous HCI task, to identify and understand potential limitations and data processing decisions. In particular, we investigate three overall approaches: a logistic regression method, a supervised shallow method (SVM), and a supervised deep learning method (CNN). We examine personalised and generalised models, as well as consider different features and ways of labelling the data. Our initial explorations show that generalised models can perform as well as personalised ones and that deep learning can be a suitable approach for medium size datasets. To provide additional practical advice for future brain-computer interaction systems, we conclude by discussing the limitations and data-preparation needs of different machine learning approaches. We also make recommendations for avenues of future work that are most promising for the machine learning of fNIRS data.
Pilot Study of Pelvic Girdle Pain in Women with and Without Laparoscopically Diagnosed Endometriosis

Objective: Pelvic girdle pain is a well recognized cause of back pain in the pregnant and postpartum population. In this pilot study, we explore whether pelvic girdle pain is also involved in the etiology of back pain outside the pregnant/postpartum period, in women with or without laparoscopically diagnosed endometriosis. Methods: Retrospective review of new patients seen for pelvic pain from June – December 2012 at a tertiary referral centre. Patients self-rated back pain severity from 0-10. Pelvic girdle pain tests were sacroiliac dorsal ligament tenderness, right or left active straight leg raise, and right or left Faber tests. The examiner was blinded to the back pain severity. Pelvic girdle pain was tested for an association with the severity of back pain. Endometriosis was diagnosed on laparoscopy, and the presence or absence of endometriosis was also considered. Results: Sixty-three women with pelvic pain met the study criteria, with 82% having underlying endometriosis (32/39). Pelvic girdle pain (presence of at least one positive pelvic girdle pain test) was significantly associated with greater severity of back pain (5.6 +/2.9 vs. 3.5 +/- 2.9, Mann-Whitney test, p=0.009). Furthermore, the number of positive pelvic girdle pain tests was significantly associated with the severity of back pain (Spearman rho=0.30, p=0.016; linear regression b=0.53, p=0.031). Pelvic girdle pain was similarly present in women with or without endometriosis (63% (20/32) vs. 86% (6/7), Fisher Exact test, p=0.39). No other demographic variables, diagnoses, symptoms, or signs, were associated with severity of back pain. Conclusion: This pilot study provides initial evidence that pelvic girdle pain is involved in the etiology of back pain in the pelvic pain population, similar to the pregnant/postpartum population, in women with or without endometriosis at laparoscopy.
Prevalence, pattern and perceptions of self-medication in medical students.

Background: The use of self-medication is highly prevalent in the community more so amongst the medical students. Self-medication can be defined as the use of drugs to treat self-diagnosed disorders or symptoms, or the intermittent or continued use of a prescribed drug for chronic or recurrent disease or symptoms. Aims and Objectives: To study the prevalence and pattern of use of self-medication among medical students from first year to internship. Methods: This cross sectional study was carried out among under graduate medical students including interns of Smt. NHL Municipal Medical College, Ahmedabad during the period of March 2010 to May 2010. Results: Out of 747 students and interns enrolled, 685 responded (91.7%). Out of 685 respondents 564 (82.3%) reported self-medication within one year of recall period. Most common conditions/symptoms for self-medication in students were fever (72.7%), headache (69.1%), upper respiratory tract infections (64.1%) followed by others like body-ache, abdominal pain, diarrhoea etc. Over the counter drugs (84.2%) was the most common category of drugs used by all the students except first year students who used prescription only drugs more frequently (48.5%). Herbal and Ayurvedic drugs were also used as self-medication (17.8%); most frequently by the first year students (22.7%). Conclusion: The pattern of self-medication practice changes with time and advancement of knowledge.
OCCUPATIONAL MOBILITY AND CHRONIC ILLNESS IN LATE LIFE: A SYSTEMATIC REVIEW

Abstract Objectives: Occupational mobility at various stages in the life course may have a cumulative influence on health outcomes in later life. This study aims to (1) systematically review the association between occupational mobility and chronic illness in late life; and (2) identify potential mechanisms underlying this relationship. Methods: A systematic review of literature was carried out by searching two databases (PubMed and SocIndex) and reference lists. Eligible studies examined associations between occupational mobility and at least one measure of chronic illness among adults aged 50 years or above. Occupational disruptions (e.g., job loss) were reviewed as special cases of occupational mobility. Results: Downward occupational mobility and mid-life occupational disruptions have been consistently shown to predict higher risk of chronic illness in older adults. Several potential mechanisms were identified from the literature: (1) health behaviors, including dietary practices and alcohol consumption; (2) psychosocial factors, including stress, stigma, job control, job demands, and job satisfaction; (3) economic factors, including financial incentives or constraints; and (4) other individual characteristics, including personality traits and coping skills. There is also evidence that the timing of job mobility and the duration of (each) occupation modify the association between occupational mobility and health in late life. Discussion: These findings suggest that experiencing involuntary occupational mobility at various stages in the life course can increase the risk of chronic illness in late life. Health professionals and policymakers should target more resources to disadvantaged older adults who experience involuntary occupational transition.
Business Models for Open Digital Ecosystems of Trustable Assistants

Digital ecosystems (DEs) are self-organizing, robust and scalable environments where various stakeholders interact to solve complex problems. The idea of building digital ecosystems is not new. Thus, we can currently draw on an extensive body of literature on the topic. Although academics have addressed the technical and architectural challenges of building digital ecosystems as well as their desirability regarding innovativeness and privacy, research on how to ensure the economic viability and thus sustainability of such DEs remains scarce. In this study, we address this void in the literature and focus on the economic challenges of building open DE. We discuss this topic in the context of an open DE for trustable assistants in the Internet of Things (IoT) and vet the research question: “which are the business models an open DE must support to be economically viable? " Based on a structured research analysis we identify seven business models, which are most likely essential to the economic success of the analysed DE.
Prediction of Drug Permeability Using In Vitro Blood–Brain Barrier Models with Human Induced Pluripotent Stem Cell-Derived Brain Microvascular Endothelial Cells

Abstract The strong barrier function of the blood–brain barrier (BBB) protects the central nervous system (CNS) from xenobiotic substances, while the expression of selective transporters controls the transportation of nutrients between the blood and brain. As a result, the delivery of drugs to the CNS and prediction of the ability of specific drugs to penetrate the BBB can be difficult. Although in vivo pharmacokinetic analysis using rodents is a commonly used method for predicting human BBB permeability, novel in vitro BBB models, such as Transwell models, have been developed recently. Induced pluripotent stem cells (iPSCs) have the potential to differentiate into various types of cells, and protocols for the differentiation of iPSCs to generate brain microvascular endothelial cells (BMECs) have been reported. The use of iPSCs makes it easy to scale-up iPSC-derived BMECs (iBMECs) and enables production of BBB disease models by using iPSCs from multiple donors with disease, which are advantageous properties compared with models that utilize primary BMECs (pBMECs). There has been little research on the value of iBMECs for predicting BBB permeability. This study focused on the similarity of iBMECs to pBMECs and investigated the ability of iPSC-BBB models (monoculture and coculture) to predict in vivo human BBB permeability using iBMECs. iBMECs express BMEC markers (e.g., VE-cadherin and claudin-5) and influx/efflux transporters (e.g., Glut-1, SLC7A5, CD220, P-gp, ABCG2, and MRP-1) and exhibit high barrier function (transendothelial electrical resistance, >1000 Ω × cm2) as well as similar transporter expression profiles to pBMECs. We determined that the efflux activity using P-glycoprotein (P-gp) transporter is not sufficient in iBMECs, while in drug permeability tests, iPSC-derived BBB models showed a higher correlation with in vivo human BBB permeability compared with a rat BBB model and the Caco-2 model. In a comparison between monoculture and coculture models, the coculture BBB model showed higher efflux activity for compounds with low CNS permeability (e.g., verapamil and thioridazine). In conclusion, iPSC-BBB models make it possible to predict BBB permeability, and employing coculturing can improve iPSC-BBB function.