Eyetracking metrics reveal impaired spatial anticipation in behavioural variant frontotemporal dementia.

Eyetracking technology has had limited application in the dementia field to date, with most studies attempting to discriminate syndrome subgroups on the basis of basic oculomotor functions rather than higher-order cognitive abilities. Eyetracking-based tasks may also offer opportunities to reduce or ameliorate problems associated with standard paper-and-pencil cognitive tests such as the complexity and linguistic demands of verbal test instructions, and the problems of tiredness and attention associated with lengthy tasks that generate few data points at a slow rate. In the present paper we adapted the Brixton spatial anticipation test to a computerized instruction-less version where oculomotor metrics, rather than overt verbal responses, were taken into account as indicators of high level cognitive functions. Twelve bvFTD (in whom spatial anticipation deficits were expected), six SD patients (in whom deficits were predicted to be less frequent) and 38 healthy controls were presented with a 10×7 matrix of white circles. During each trial (N=24) a black dot moved across seven positions on the screen, following 12 different patterns. Participants' eye movements were recorded. Frequentist statistical analysis of standard eye movement metrics were complemented by a Bayesian machine learning (ML) approach in which raw eyetracking time series datasets were examined to explore the ability to discriminate diagnostic group performance not only on the overall performance but also on individual trials. The original pen and paper Brixton test identified a spatial anticipation deficit in 7/12 (58%) of bvFTD and in 2/6 (33%) of SD patients. The eyetracking frequentist approach reported the deficit in 11/12 (92%) of bvFTD and in none (0%) of the SD patients. The machine learning approach had the main advantage of identifying significant differences from controls in 24/24 individual trials for bvFTD patients and in only 12/24 for SD patients. Results indicate that the fine grained rich datasets obtained from eyetacking metrics can inform us about high level cognitive functions in dementia, such as spatial anticipation. The ML approach can help identify conditions where subtle deficits are present and, potentially, contribute to test optimisation and the reduction of testing times. The absence of instructions also favoured a better distinction between different clinical groups of patients and can help provide valuable disease-specific markers

Burnout and psychiatric morbidity among medical students entering clinical training: a three year prospective questionnaire and interview-based study

BACKGROUND: Mental distress among medical students is often reported. Burnout has not been studied frequently and studies using interviewer-rated diagnoses as outcomes are rarely employed. The objective of this prospective study of medical students was to examine clinically significant psychiatric morbidity and burnout at 3(rd )year of medical school, considering personality and study conditions measured at 1(st )year. METHODS: Questionnaires were sent to 127 first year medical students who were then followed-up at 3(rd )year of medical school. Eighty-one of 3(rd )year respondents participated in a diagnostic interview. Personality (HP5-i) and Performance-based self-esteem (PBSE-scale) were assessed at first year, Study conditions (HESI), Burnout (OLBI), Depression (MDI) at 1(st )and 3(rd )years. Diagnostic interviews (MINI) were used at 3(rd )year to assess psychiatric morbidity. High and low burnout at 3(rd )year was defined by cluster analysis. Logistic regressions were used to identify predictors of high burnout and psychiatric morbidity, controlling for gender. RESULTS: 98 (77%) responded on both occasions, 80 (63%) of these were interviewed. High burnout was predicted by Impulsivity trait, Depressive symptoms at 1(st )year and Financial concerns at 1(st )year. When controlling for 3(rd )year study conditions, Impulsivity and concurrent Workload remained. Of the interviewed sample 21 (27%) had a psychiatric diagnosis, 6 of whom had sought help. Unadjusted analyses showed that psychiatric morbidity was predicted by high Performance-based self-esteem, Disengagement and Depression at 1(st )year, only the later remained significant in the adjusted analysis. CONCLUSION: Psychiatric morbidity is common in medical students but few seek help. Burnout has individual as well as environmental explanations and to avoid it, organisational as well as individual interventions may be needed. Early signs of depressive symptoms in medical students may be important to address. Students should be encouraged to seek help and adequate facilities should be available

The discovery of potent, selective, and reversible inhibitors of the house dust mite peptidase allergen Der p 1: an innovative approach to the treatment of allergic asthma.

Blocking the bioactivity of allergens is conceptually attractive as a small-molecule therapy for allergic diseases but has not been attempted previously. Group 1 allergens of house dust mites (HDM) are meaningful targets in this quest because they are globally prevalent and clinically important triggers of allergic asthma. Group 1 HDM allergens are cysteine peptidases whose proteolytic activity triggers essential steps in the allergy cascade. Using the HDM allergen Der p 1 as an archetype for structure-based drug discovery, we have identified a series of novel, reversible inhibitors. Potency and selectivity were manipulated by optimizing drug interactions with enzyme binding pockets, while variation of terminal groups conferred the physicochemical and pharmacokinetic attributes required for inhaled delivery. Studies in animals challenged with the gamut of HDM allergens showed an attenuation of allergic responses by targeting just a single component, namely, Der p 1. Our findings suggest that these inhibitors may be used as novel therapies for allergic asthma

Overview of mathematical approaches used to model bacterial chemotaxis II: bacterial populations

We review the application of mathematical modeling to understanding the behavior of populations of chemotactic bacteria. The application of continuum mathematical models, in particular generalized Keller–Segel models, is discussed along with attempts to incorporate the microscale (individual) behavior on the macroscale, modeling the interaction between different species of bacteria, the interaction of bacteria with their environment, and methods used to obtain experimentally verified parameter values. We allude briefly to the role of modeling pattern formation in understanding collective behavior within bacterial populations. Various aspects of each model are discussed and areas for possible future research are postulated

The Role of Practice Research Networks (PRN) in the Development and Implementation of Evidence: The Northern Improving Access to Psychological Therapies PRN Case Study

Practice research networks (PRNs) can support the implementation of evidence based practice in routine services and generate practice based evidence. This paper describes the structure, processes and learning from a new PRN in the Improving Access to Psychological Therapies programme in England, in relation to an implementation framework and using one study as a case example. Challenges related to: ethics and governance processes; communications with multiple stakeholders; competing time pressures and linking outcome data. Enablers included: early tangible outputs and impact; a collaborative approach; engaging with local research leads; clarity of processes; effective dissemination; and committed leadership

IP-10 Levels as an Accurate Screening Tool to Detect Acute HIV Infection in Resource-Limited Settings.

Acute HIV infection (AHI) is the period prior to seroconversion characterized by high viral replication, hyper-transmission potential and commonly, non-specific febrile illness. AHI detection requires HIV-RNA viral load (VL) determination, which has very limited access in low-income countries due to restrictive costs and implementation constraints. We sought to identify a biomarker that could enable AHI diagnosis in scarce-resource settings, and to evaluate the feasibility of its implementation. HIV-seronegative adults presenting at the Manhiça District Hospital, Mozambique, with reported-fever were tested for VL. Plasma levels of 49 inflammatory biomarkers from AHI (n = 61) and non-HIV infected outpatients (n = 65) were determined by Luminex and ELISA. IP-10 demonstrated the best predictive power for AHI detection (AUC = 0.88 [95%CI 0.80-0.96]). A cut-off value of IP-10 ≥ 161.6 pg/mL provided a sensitivity of 95.5% (95%CI 85.5-99.5) and a specificity of 76.5% (95%CI 62.5-87.2). The implementation of an IP-10 screening test could avert from 21 to 84 new infections and save from US$176,609 to US$533,467 to the health system per 1,000 tested patients. We conclude that IP-10 is an accurate biomarker to screen febrile HIV-seronegative individuals for subsequent AHI diagnosis with VL. Such an algorithm is a cost-effective strategy to prevent disease progression and a substantial number of further HIV infections

The Role of Practitioner Resilience and Mindfulness in Effective Practice: A Practice-Based Feasibility Study.

A growing body of literature attests to the existence of therapist effects with little explanation of this phenomenon. This study therefore investigated the role of resilience and mindfulness as factors related to practitioner wellbeing and associated effective practice. Data comprised practitioners (n = 37) and their patient outcome data (n = 4980) conducted within a stepped care model of service delivery. Analyses employed benchmarking and multilevel modeling to identify more and less effective practitioners via yoking of therapist factors and nested patient outcomes. A therapist effect of 6.7 % was identified based on patient depression (PHQ-9) outcome scores. More effective practitioners compared to less effective practitioners displayed significantly higher levels of mindfulness as well as resilience and mindfulness combined. Implications for policy, research and practice are discussed

Identifying the physical features of marina infrastructure associated with the presence of non-native species in the UK

Marine invasive non-native species (NNS) are one of the greatest threats to global marine biodiversity, causing significant economic and social impacts. Marinas are increasingly recognised as key reservoirs for invasive NNS. They provide submersed artificial habitat that unintentionally supports the establishment of NNS introduced from visiting recreational vessels. While ballast water and shipping vectors have been well documented, the role of recreational vessels in spreading NNS has been relatively poorly studied. Identification of the main physical features found within marinas, which relate to the presence of NNS, is important to inform the development of effective biosecurity measures and prevent further spread. Towards this aim, physical features that could influence the presence of NNS were assessed for marinas throughout the UK in July 2013. Thirty-three marine and brackish NNS have been recorded in UK marinas, and of the 88 marinas studied in detail, 83 contained between 1 and 13 NNS. Significant differences in freshwater input, marina entrance width and seawall length were associated with the presence of NNS. Additionally, questionnaires were distributed to marina managers and recreational vessel owners to understand current biosecurity practices and attitudes to recreational vessel biosecurity. The main barriers to biosecurity compliance were cited as cost and time. Further work identifying easily distinguished features of marinas could be used as a proxy to assess risk of invasion. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s00227-016-2941-8) contains supplementary material, which is available to authorized users

A kilonova as the electromagnetic counterpart to a gravitational-wave source

Gravitational waves were discovered with the detection of binary black-hole mergers1 and they should also be detectable from lower-mass neutron-star mergers. These are predicted to eject material rich in heavy radioactive isotopes that can power an electromagnetic signal. This signal is luminous at optical and infrared wavelengths and is called a kilonova2,3,4,5. The gravitational-wave source GW170817 arose from a binary neutron-star merger in the nearby Universe with a relatively well confined sky position and distance estimate6. Here we report observations and physical modelling of a rapidly fading electromagnetic transient in the galaxy NGC 4993, which is spatially coincident with GW170817 and with a weak, short γ-ray burst7,8. The transient has physical parameters that broadly match the theoretical predictions of blue kilonovae from neutron-star mergers. The emitted electromagnetic radiation can be explained with an ejected mass of 0.04 ± 0.01 solar masses, with an opacity of less than 0.5 square centimetres per gram, at a velocity of 0.2 ± 0.1 times light speed. The power source is constrained to have a power-law slope of −1.2 ± 0.3, consistent with radioactive powering from r-process nuclides. (The r-process is a series of neutron capture reactions that synthesise many of the elements heavier than iron.) We identify line features in the spectra that are consistent with light r-process elements (atomic masses of 90–140). As it fades, the transient rapidly becomes red, and a higher-opacity, lanthanide-rich ejecta component may contribute to the emission. This indicates that neutron-star mergers produce gravitational waves and radioactively powered kilonovae, and are a nucleosynthetic source of the r-process element