Award winning incentive in distance learning

Background: Our distance learning MSc and Diploma course in Clinical Neurology has traditionally had poor engagement from students with our monthly activities. These activities are set and marked by the clinical tutor, and whilst more formative than summative, are taken into account when awarding the final tutor score which makes 20% of the students final mark. Feedback has been strongly positive for these activities, but they do take some time to complete. Student participation for the five months after I joined as clinical tutor in 2017 was 44 out of 94 students (47%), comparable to levels before I joined. / Aim: We wished to improve participation, but avoid the draconian approach of heavily penalising students for not participating. Whilst monetary rewards can incentivise, work has suggested that non-monetary awards, especially in the form of a gift or presentation, can be very effective too / Methods: We announced to all students that a non-monetary award (a medal) would be awarded at the end of each academic year to the student with the best overall results. Participation with the monthly activities was assessed for the five months after this announcement and compared with the five months before. / Results: The number of eligible students was the same before and after the announcement (94). For the five months after the announcement 56 /94 (60%) of students participated, a significant increase compared to pre-medal announcement levels of 47% (Z test p=0.039). / Conclusions: We have shown that a non-monetary incentive in the form of a medal can significantly increase participation in a distance learning course which had not previously been demonstrated. The medal is still in the process of being designed so does not physically exist yet, raising the question of whether a ‘virtual’ medal might be as effective as a physical one for distance learning courses

Use of novel serum markers in clinical follow-up of Sertoli-Leydig cell turnours

Background: Sertoli-Leyclig cell tumours of the ovary account for only 0.2% of malignant ovarian tumours. Two-thirds of all patients become apparent due to the tumour's hormone production. Methods: A 41-year-old patient (gravida 4, para 4) presented with dyspnoea, enlarged abdominal girth and melaena. Diagnostic imaging was suspicious for an ovarian cancer. The standard tumour marker for ovarian cancer (CA 125) was elevated to 984 U/mL. Results: Surgical exploration of the abdomen revealed a mouldering tumour of both adnexes extending to the level of the navel. Frozen sections showed an undifferentiated carcinoma of unknown origin. Radical surgery was performed. The final histological report described a malignant sex-cord stroma tumour, a Sertoli-Leydig cell tumour, emanating from both ovaries. Analysis of preoperative blood serum showed elevated levels of CYFRA 21-1 (10.4 ng/mL), neuron-specific enolase (36.2 ng/mL), oestradiol (485 pg/mL) and CA-125 (984 U/mL). Adjuvant chemotherapy and regional hyperthermia were performed due to the malignant potential and incomplete resection of the tumour. Conclusions: Undifferentiated Sertoli-Leyclig cell tumours show a poor clinical course. As only two-thirds of patients with this rare disease present with elevated hormone levels, new markers deserve further investigation to offer more specific, individualised tumour monitoring

Subgrouping factors influencing migraine intensity in women: A semi-automatic methodology based on machine learning and information geometry

This is the peer reviewed version of the following article: Pérez-Benito, F.J., Conejero, J.A., Sáez, C., García-Gómez, J.M., Navarro-Pardo, E., Florencio, L.L. and Fernández-de-las-Peñas, C. (2020), Subgrouping Factors Influencing Migraine Intensity in Women: A Semi-automatic Methodology Based on Machine Learning and Information Geometry. Pain Pract, 20: 297-309, which has been published in final form at https://doi.org/10.1111/papr.12854. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Self-Archiving.[EN] Background Migraine is a heterogeneous condition with multiple clinical manifestations. Machine learning algorithms permit the identification of population groups, providing analytical advantages over other modeling techniques. Objective The aim of this study was to analyze critical features that permit the differentiation of subgroups of patients with migraine according to the intensity and frequency of attacks by using machine learning algorithms. Methods Sixty-seven women with migraine participated. Clinical features of migraine, related disability (Migraine Disability Assessment Scale), anxiety/depressive levels (Hospital Anxiety and Depression Scale), anxiety state/trait levels (State-Trait Anxiety Inventory), and pressure pain thresholds (PPTs) over the temporalis, neck, second metacarpal, and tibialis anterior were collected. Physical examination included the flexion-rotation test, cervical range of cervical motion, forward head position while sitting and standing, passive accessory intervertebral movements (PAIVMs) with headache reproduction, and joint positioning sense error. Subgrouping was based on machine learning algorithms by using the nearest neighbors algorithm, multisource variability assessment, and random forest model. Results For migraine intensity, group 2 (women with a regular migraine headache intensity score of 7 on an 11-point Numeric Pain Rating Scale [where 0 = no pain and 10 = maximum pain]) were younger and had lower joint positioning sense error in cervical rotation, greater cervical mobility in rotation and flexion, lower flexion-rotation test scores, positive PAIVMs reproducing migraine, normal PPTs over the tibialis anterior, shorter migraine history, and lower cranio-vertebral angles while standing than the remaining migraine intensity subgroups. The most discriminative variable was the flexion-rotation test score of the symptomatic side. For migraine frequency, no model was able to identify differences between groups (ie, patients with episodic or chronic migraine). Conclusions A subgroup of women with migraine who had common migraine intensity was identified with machine learning algorithms.Perez-Benito, FJ.; Conejero, JA.; Sáez Silvestre, C.; Garcia-Gomez, JM.; Navarro-Pardo, E.; Florencio, LL.; Fernández-De-Las-Peñas, C. (2020). Subgrouping factors influencing migraine intensity in women: A semi-automatic methodology based on machine learning and information geometry. Pain Practice. 20(3):297-309. https://doi.org/10.1111/papr.12854S29730920

Detection of TMPRSS2 : ERG fusion gene in circulating prostate cancer cells

Creative Commons Attribution-NonCommercial-Share Alike 3.0 license (CC BY-NC SA)Aim: To investigate the existence of TMPRSS2:ERG fusion gene in circulating tumor cells (CTC) from prostate cancer patients and its potential in monitoring tumor metastasis. Methods: We analyzed the frequency of TMPRSS2: ERG and TMPRSS2:ETV1 transcripts in 27 prostate cancer biopsies from prostatectomies, and TMPRSS2:ERG transcripts in CTC isolated from 15 patients with advanced androgen independent disease using reverse transcription polymerase chain reaction (RT-PCR). Fluorescence in situ hybridization (FISH) was applied to analyze the genomic truncation of ERG, which is the result of TMPRSS2:ERG fusion in 10 of the 15 CTC samples. Results: TMPRSS2: ERG transcripts were found in 44% of our samples, but we did not detect expression of TMPRSS2:ETV1. Using FISH analysis we detected chromosomal rearrangements affecting the ERG gene in 6 of 10 CTC samples, including 1 case with associated TMPRSS2:ERG fusion at the primary site. However, TMPRSS2:ERG transcripts were not detected in any of the 15 CTC samples, including the 10 cases analyzed by FISH. Conclusion: Although further study is required to address the association between TMPRSS2:ERG fusion and prostate cancer metastasis, detection of genomic truncation of the ERG gene by FISH analysis could be useful for monitoring the appearance of CTC and the potential for prostate cancer metastasis.Peer reviewedFinal Published versio

Study profile: the Durban Diabetes Study (DDS): a platform for chronic disease research.

The Durban Diabetes Study (DDS) is a population-based cross-sectional survey of an urban black population in the eThekwini Municipality (city of Durban) in South Africa. The survey combines health, lifestyle and socioeconomic questionnaire data with standardised biophysical measurements, biomarkers for non-communicable and infectious diseases, and genetic data. Data collection for the study is currently underway and the target sample size is 10 000 participants. The DDS has an established infrastructure for survey fieldwork, data collection and management, sample processing and storage, managed data sharing and consent for re-approaching participants, which can be utilised for further research studies. As such, the DDS represents a rich platform for investigating the distribution, interrelation and aetiology of chronic diseases and their risk factors, which is critical for developing health care policies for disease management and prevention. For data access enquiries please contact the African Partnership for Chronic Disease Research (APCDR) at [email protected] or the corresponding author.The study was supported by the Wellcome Trust (grant number 098051), the African Partnership for Chronic Disease Research (Medical Research Council UK partnership grant number MR/K013491/1), the National Institute for Health Research Cambridge Biomedical Research Centre (UK), the Gates Cambridge Scholarship programme (UK), Novo-Nordisk (South Africa), Sanofi-Aventis (South Africa), and MSD Pharmaceuticals (Pty) Ltd (Southern Africa).This is the final version of the article. It first appeared from Cambridge University Press via http://dx.doi.org/10.1017/gheg.2015.

Violent video games and morality: a meta-ethical approach

This paper considers what it is about violent video games that leads one reasonably minded person to declare "That is immoral" while another denies it. Three interpretations of video game content a re discussed: reductionist, narrow, and broad. It is argued that a broad interpretation is required for a moral objection to be justified. It is further argued that understanding the meaning of moral utterances – like "x is immoral" – is important to an understanding of why there is a lack of moral consensus when it comes to the content of violent video games. Constructive ecumenical expressivism is presented as a means of explaining what it is that we are doing when we make moral pronouncements and why, when it comes to video game content, differing moral attitudes abound. Constructive ecumenical expressivism is also presented as a means of illuminating what would be required for moral consensus to be achieved

The MROI fringe tracker: Laboratory tracking with ICONN

The loop is closed on ICONN, the Magdalena Ridge Observatory Interferometer fringe tracker. Results from laboratory experiments demonstrating ICONN's ability to track realistic, atmospheric-like path difference perturbations in real-time are shown. Characterizing and understanding the behavior and limits of ICONN in a controlled environment are key for reaching the goals of the MROI. The limiting factors in the experiments were found to be the light delivery system and temporary path length correction mechanism; not the on-sky components of ICONN. ICONN was capable of tracking fringes with a coherence loss below 5%; this will only improve in its final deployment.The Magdalena Ridge Observatory Interferometer is funded by the US Department of Transportation, the State of New Mexico, and New Mexico Tech with previous funding from the Navy Research Laboratory (NRL, agreement no. N00173-01-2-C902).This is the final version of the article, also available from SPIE at http://proceedings.spiedigitallibrary.org/proceeding.aspx?articleid=1891933. Copyright 2014 Society of Photo Optical Instrumentation Engineers. One print or electronic copy may be made for personal use only. Systematic reproduction and distribution, duplication of any material in this paper for a fee or for commercial purposes, or modification of the content of the paper are prohibited. http://dx.doi.org/10.1117/12.205560

Justice at Sea: Fishers’ politics and marine conservation in coastal Odisha, India

This is a paper about the politics of fishing rights in and around the Gahirmatha marine sanctuary in coastal Odisha, in eastern India. Claims to the resources of this sanctuary are politicised through the creation of a particularly damaging narrative by influential Odiya environmental actors about Bengalis, as illegal immigrants who have hurt the ecosystem through their fishing practices. Anchored within a theoretical framework of justice as recognition, the paper considers the making of a regional Odiya environmentalism that is, potentially, deeply exclusionary. It details how an argument about ‘illegal Bengalis’ depriving ‘indigenous Odiyas’ of their legitimate ‘traditional fishing rights’ derives from particular notions of indigeneity and territory. But the paper also shows that such environmentalism is tenuous, and fits uneasily with the everyday social landscape of fishing in coastal Odisha. It concludes that a wider class conflict between small fishers and the state over a sanctuary sets the context in which questions about legitimate resource rights are raised, sometimes with important effects, like when out at sea

The conceptualisation and measurement of DSM-5 Internet Gaming Disorder: the development of the IGD-20 Test

Background: Over the last decade, there has been growing concern about ‘gaming addiction’ and its widely documented detrimental impacts on a minority of individuals that play excessively. The latest (fifth) edition of the American Psychiatric Association’s Diagnostic and Statistical Manual of Mental Disorders (DSM-5) included nine criteria for the potential diagnosis of Internet Gaming Disorder (IGD) and noted that it was a condition that warranted further empirical study. Aim: The main aim of this study was to develop a valid and reliable standardised psychometrically robust tool in addition to providing empirically supported cut-off points. Methods: A sample of 1003 gamers (85.2% males; mean age 26 years) from 57 different countries were recruited via online gaming forums. Validity was assessed by confirmatory factor analysis (CFA), criterion-related validity, and concurrent validity. Latent profile analysis was also carried to distinguish disordered gamers from non-disordered gamers. Sensitivity and specificity analyses were performed to determine an empirical cut-off for the test. Results: The CFA confirmed the viability of IGD-20 Test with a six-factor structure (salience, mood modification, tolerance, withdrawal, conflict and relapse) for the assessment of IGD according to the nine criteria from DSM-5. The IGD-20 Test proved to be valid and reliable. According to the latent profile analysis, 5.3% of the total participants were classed as disordered gamers. Additionally, an optimal empirical cut-off of 71 points (out of 100) seemed to be adequate according to the sensitivity and specificity analyses carried