A study protocol to investigate the management of depression and challenging behaviors associated with dementia in aged care settings

Background:&nbsp;The high occurrence and under-treatment of clinical depression and behavioral and psychological symptoms of dementia (BPSD) within aged care settings is concerning, yet training programs aimed at improving the detection and management of these problems have generally been ineffective. This article presents a study protocol to evaluate a training intervention for facility managers/registered nurses working in aged care facilities that focuses on organisational processes and culture as well as knowledge, skills and self-efficacy. Methods. A Randomised Control Trial (RCT) will be implemented across 18 aged care facilities (divided into three conditions). Participants will be senior registered nurses and personal care attendants employed in the aged care facility. The first condition will receive the training program (Staff as Change Agents - Enhancing and Sustaining Mental Health in Aged Care), the second condition will receive the training program and clinical support, and the third condition will receive no intervention. Results: Pre-, post-, 6-month and 12-month follow-up measures of staff and residents will be used to demonstrate how upskilling clinical leaders using our transformational training approach, as well as the use of a structured screening, referral and monitoring protocol, can address the mental health needs of older people in residential care. Conclusions: The expected outcome of this study is the validation of an evidence-based training program to improve the management of depression and BPSD among older people in residential care settings by establishing routine practices related to mental health. This relatively brief but highly focussed training package will be readily rolled out to a larger number of residential care facilities at a relatively low cost.</div

A transient helix in the disordered region of dynein light intermediate chain links the motor to structurally diverse adaptors for cargo transport

All animal cells use the motor cytoplasmic dynein 1 (dynein) to transport diverse cargo toward microtubule minus ends and to organize and position microtubule arrays such as the mitotic spindle. Cargo-specific adaptors engage with dynein to recruit and activate the motor, but the molecular mechanisms remain incompletely understood. Here, we use structural and dynamic nuclear magnetic resonance (NMR) analysis to demonstrate that the C-terminal region of human dynein light intermediate chain 1 (LIC1) is intrinsically disordered and contains two short conserved segments with helical propensity. NMR titration experiments reveal that the first helical segment (helix 1) constitutes the main interaction site for the adaptors Spindly (SPDL1), bicaudal D homolog 2 (BICD2), and Hook homolog 3 (HOOK3). In vitro binding assays show that helix 1, but not helix 2, is essential in both LIC1 and LIC2 for binding to SPDL1, BICD2, HOOK3, RAB-interacting lysosomal protein (RILP), RAB11 family-interacting protein 3 (RAB11FIP3), ninein (NIN), and trafficking kinesin-bind-ing protein 1 (TRAK1). Helix 1 is sufficient to bind RILP, whereas other adaptors require additional segments preceding helix 1 for efficient binding. Point mutations in the C-terminal helix 1 of Caenorhabditis elegans LIC, introduced by genome editing, severely affect development, locomotion, and life span of the animal and disrupt the distribution and transport kinetics of membrane cargo in axons of mechanosensory neurons, identical to what is observed when the entire LIC C-terminal region is deleted. Deletion of the C-terminal helix 2 delays dynein-dependent spindle positioning in the one-cell embryo but overall does not significantly perturb dynein function. We conclude that helix 1 in the intrinsically disordered region of LIC provides a conserved link between dynein and structurally diverse cargo adaptor families that is critical for dynein function in vivo.This work was financed by the Fundo Europeu de Desenvolvimento Regional (FEDER) through the Norte Portugal Regional Operational Programme (NORTE 2020), Portugal 2020 (RG); by the Fundação para a Ciência e a Tecnologia (FCT)/Ministério da Ciência, Tecnologia e Ensino Superior in the framework of the project NORTE-01-0145-FEDER-030507 (RG); by FCT fellowships IF/01015/2013/CP1157/CT0006 (RG) and SFRH/ BPD/101898/2014 (DJB); by the European Research Council under the European Union’s Seventh Framework Programme, ERC grant agreement no. ERC-2013-StG-338410-DYNEINOME (RG), and by a start-up package of the University of Colorado (BV). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript

Classification of patients with knee osteoarthritis in clinical phenotypes: data from the osteoarthritis initiative

<div><p>Objectives</p><p>The existence of phenotypes has been hypothesized to explain the large heterogeneity characterizing the knee osteoarthritis. In a previous systematic review of the literature, six main phenotypes were identified: Minimal Joint Disease (MJD), Malaligned Biomechanical (MB), Chronic Pain (CP), Inflammatory (I), Metabolic Syndrome (MS) and Bone and Cartilage Metabolism (BCM). The purpose of this study was to classify a sample of individuals with knee osteoarthritis (KOA) into pre-defined groups characterized by specific variables that can be linked to different disease mechanisms, and compare these phenotypes for demographic and health outcomes.</p><p>Methods</p><p>599 patients were selected from the OAI database FNIH at 24 months’ time to conduct the study. For each phenotype, cut offs of key variables were identified matching the results from previous studies in the field and the data available for the sample. The selection process consisted of 3 steps. At the end of each step, the subjects classified were excluded from the further classification stages. Patients meeting the criteria for more than one phenotype were classified separately into a ‘complex KOA’ group.</p><p>Results</p><p>Phenotype allocation (including complex KOA) was successful for 84% of cases with an overlap of 20%. Disease duration was shorter in the MJD while the CP phenotype included a larger number of Women (81%). A significant effect of phenotypes on WOMAC pain (F = 16.736 p <0.001) and WOMAC physical function (F = 14.676, p < 0.001) was identified after controlling for disease duration.</p><p>Conclusion</p><p>This study signifies the feasibility of a classification of KOA subjects in distinct phenotypes based on subgroup-specific characteristics.</p></div

Misuse of "study drugs:" prevalence, consequences, and implications for policy

BACKGROUND: Non-medical/illegal use of prescription stimulants popularly have been referred to as "study drugs". This paper discusses the current prevalence and consequences of misuse of these drugs and implications of this information for drug policy. RESULTS: Study drugs are being misused annually by approximately 4% of older teens and emerging adults. Yet, there are numerous consequences of misuse of prescription stimulants including addiction, negative reactions to high dosages, and medical complications. Policy implications include continuing to limit access to study drugs, finding more safe prescription drug alternatives, interdiction, and public education. CONCLUSION: Much more work is needed on prescription stimulant misuse assessment, identifying the extent of the social and economic costs of misuse, monitoring and reducing access, and developing prevention and cessation education efforts

What happens if you single out? An experiment

We present an experiment investigating the effects of singling out an individual on trust and trustworthiness. We find that (a) trustworthiness falls if there is a singled out subject; (b) non-singled out subjects discriminate against the singled out subject when they are not responsible of the distinct status of this person; (c) under a negative frame, the singled out subject returns significantly less; (d) under a positive frame, the singled out subject behaves bimodally, either selecting very low or very high return rates. Overall, singling out induces a negligible effect on trust but is potentially disruptive for trustworthiness

A contemporaneous infrared flash from a long gamma-ray burst: an echo from the central engine

The explosion that results in a cosmic gamma-ray burst (GRB) is thought to produce emission from two physical processes -- the activity of the central engine gives rise to the high-energy emission of the burst through internal shocking and the subsequent interaction of the flow with the external environment produces long-wavelength afterglow. While afterglow observations continue to refine our understanding of GRB progenitors and relativistic shocks, gamma-ray observations alone have not yielded a clear picture of the origin of the prompt emission nor details of the central engine. Only one concurrent visible-light transient has been found and was associated with emission from an external shock. Here we report the discovery of infrared (IR) emission contemporaneous with a GRB, beginning 7.2 minutes after the onset of GRB 041219a. Our robotic telescope acquired 21 images during the active phase of the burst, yielding the earliest multi-colour observations of any long-wavelength emission associated with a GRB. Analysis of an initial IR pulse suggests an origin consistent with internal shocks. This opens a new possibility to study the central engine of GRBs with ground-based observations at long wavelengths.Comment: Accepted to Nature on March 1, 2005. 9 pages, 4 figures, nature12.cls and nature1.cls files included. This paper is under press embargo until print publicatio

Climate Dynamics: A Network-Based Approach for the Analysis of Global Precipitation

Precipitation is one of the most important meteorological variables for defining the climate dynamics, but the spatial patterns of precipitation have not been fully investigated yet. The complex network theory, which provides a robust tool to investigate the statistical interdependence of many interacting elements, is used here to analyze the spatial dynamics of annual precipitation over seventy years (1941-2010). The precipitation network is built associating a node to a geographical region, which has a temporal distribution of precipitation, and identifying possible links among nodes through the correlation function. The precipitation network reveals significant spatial variability with barely connected regions, as Eastern China and Japan, and highly connected regions, such as the African Sahel, Eastern Australia and, to a lesser extent, Northern Europe. Sahel and Eastern Australia are remarkably dry regions, where low amounts of rainfall are uniformly distributed on continental scales and small-scale extreme events are rare. As a consequence, the precipitation gradient is low, making these regions well connected on a large spatial scale. On the contrary, the Asiatic South-East is often reached by extreme events such as monsoons, tropical cyclones and heat waves, which can all contribute to reduce the correlation to the short-range scale only. Some patterns emerging between mid-latitude and tropical regions suggest a possible impact of the propagation of planetary waves on precipitation at a global scale. Other links can be qualitatively associated to the atmospheric and oceanic circulation. To analyze the sensitivity of the network to the physical closeness of the nodes, short-term connections are broken. The African Sahel, Eastern Australia and Northern Europe regions again appear as the supernodes of the network, confirming furthermore their long-range connection structure. Almost all North-American and Asian nodes vanish, revealing that extreme events can enhance high precipitation gradients, leading to a systematic absence of long-range patterns

Rescaling quality of life values from discrete choice experiments for use as QALYs: a cautionary tale

Background: Researchers are increasingly investigating the potential for ordinal tasks such as ranking and discrete choice experiments to estimate QALY health state values. However, the assumptions of random utility theory, which underpin the statistical models used to provide these estimates, have received insufficient attention. In particular, the assumptions made about the decisions between living states and the death state are not satisfied, at least for some people. Estimated values are likely to be incorrectly anchored with respect to death (zero) in such circumstances. Methods: Data from the Investigating Choice Experiments for the preferences of older people CAPability instrument (ICECAP) valuation exercise were analysed. The values (previously anchored to the worst possible state) were rescaled using an ordinal model proposed previously to estimate QALY-like values. Bootstrapping was conducted to vary artificially the proportion of people who conformed to the conventional random utility model underpinning the analyses. Results: Only 26% of respondents conformed unequivocally to the assumptions of conventional random utility theory. At least 14% of respondents unequivocally violated the assumptions. Varying the relative proportions of conforming respondents in sensitivity analyses led to large changes in the estimated QALY values, particularly for lower-valued states. As a result these values could be either positive (considered to be better than death) or negative (considered to be worse than death). Conclusion: Use of a statistical model such as conditional (multinomial) regression to anchor quality of life values from ordinal data to death is inappropriate in the presence of respondents who do not conform to the assumptions of conventional random utility theory. This is clearest when estimating values for that group of respondents observed in valuation samples who refuse to consider any living state to be worse than death: in such circumstances the model cannot be estimated. Only a valuation task requiring respondents to make choices in which both length and quality of life vary can produce estimates that properly reflect the preferences of all respondents

Exploring local knowledge and perceptions on zoonoses among pastoralists in northern and eastern Tanzania

Background: Zoonoses account for the most commonly reported emerging and re-emerging infectious diseases in Sub-Saharan Africa. However, there is limited knowledge on how pastoral communities perceive zoonoses in relation to their livelihoods, culture and their wider ecology. This study was carried out to explore local knowledge and perceptions on zoonoses among pastoralists in Tanzania. Methodology and principal findings: This study involved pastoralists in Ngorongoro district in northern Tanzania and Kibaha and Bagamoyo districts in eastern Tanzania. Qualitative methods of focus group discussions, participatory epidemiology and interviews were used. A total of 223 people were involved in the study. Among the pastoralists, there was no specific term in their local language that describes zoonosis. Pastoralists from northern Tanzania possessed a higher understanding on the existence of a number of zoonoses than their eastern districts' counterparts. Understanding of zoonoses could be categorized into two broad groups: a local syndromic framework, whereby specific symptoms of a particular illness in humans concurred with symptoms in animals, and the biomedical framework, where a case definition is supported by diagnostic tests. Some pastoralists understand the possibility of some infections that could cross over to humans from animals but harm from these are generally tolerated and are not considered as threats. A number of social and cultural practices aimed at maintaining specific cultural functions including social cohesion and rites of passage involve animal products, which present zoonotic risk. Conclusions: These findings show how zoonoses are locally understood, and how epidemiology and biomedicine are shaping pastoralists perceptions to zoonoses. Evidence is needed to understand better the true burden and impact of zoonoses in these communities. More studies are needed that seek to clarify the common understanding of zoonoses that could be used to guide effective and locally relevant interventions. Such studies should consider in their approaches the pastoralists' wider social, cultural and economic set up

Novel image analysis approach for quantifying expression of nuclear proteins assessed by immunohistochemistry: application to measurement of oestrogen and progesterone receptor levels in breast cancer

INTRODUCTION: Manual interpretation of immunohistochemistry (IHC) is a subjective, time-consuming and variable process, with an inherent intra-observer and inter-observer variability. Automated image analysis approaches offer the possibility of developing rapid, uniform indicators of IHC staining. In the present article we describe the development of a novel approach for automatically quantifying oestrogen receptor (ER) and progesterone receptor (PR) protein expression assessed by IHC in primary breast cancer. METHODS: Two cohorts of breast cancer patients (n = 743) were used in the study. Digital images of breast cancer tissue microarrays were captured using the Aperio ScanScope XT slide scanner (Aperio Technologies, Vista, CA, USA). Image analysis algorithms were developed using MatLab 7 (MathWorks, Apple Hill Drive, MA, USA). A fully automated nuclear algorithm was developed to discriminate tumour from normal tissue and to quantify ER and PR expression in both cohorts. Random forest clustering was employed to identify optimum thresholds for survival analysis. RESULTS: The accuracy of the nuclear algorithm was initially confirmed by a histopathologist, who validated the output in 18 representative images. In these 18 samples, an excellent correlation was evident between the results obtained by manual and automated analysis (Spearman\u27s rho = 0.9, P \u3c 0.001). Optimum thresholds for survival analysis were identified using random forest clustering. This revealed 7% positive tumour cells as the optimum threshold for the ER and 5% positive tumour cells for the PR. Moreover, a 7% cutoff level for the ER predicted a better response to tamoxifen than the currently used 10% threshold. Finally, linear regression was employed to demonstrate a more homogeneous pattern of expression for the ER (R = 0.860) than for the PR (R = 0.681). CONCLUSIONS: In summary, we present data on the automated quantification of the ER and the PR in 743 primary breast tumours using a novel unsupervised image analysis algorithm. This novel approach provides a useful tool for the quantification of biomarkers on tissue specimens, as well as for objective identification of appropriate cutoff thresholds for biomarker positivity. It also offers the potential to identify proteins with a homogeneous pattern of expression