Stopping, rationalising or optimising antipsychotic drug treatment in people with intellectual disability and/or autism

Intellectual disability (ID; also known as learning disability) is characterised by significant impairment of both cognitive functioning and adaptive behaviours, and an onset in early childhood. People with ID experience a different pattern of morbidity to the general population and die considerably younger than their counterparts without ID. Autism is a neurodevelopmental disorder characterised by troubles with social interaction and communication, and by restricted and repetitive behaviour. In both conditions, complex mental and physical health problems, as well as social issues, are common and are associated with communication difficulties that can result in maladaptive behavioural patterns (often referred to as ‘behaviour that challenges’). Ideally, all people presenting with behaviour that challenges should be assessed by a specialist multidisciplinary team (comprising psychiatrists, psychologists, speech and language therapists, occupational therapists) to develop an understanding of the behaviour and an appropriate support plan with tailored treatment strategies and specialist follow-up. Non-pharmacological interventions for challenging behaviour, such as positive behavioural support or cognitive–behavioural therapy and manipulation of environmental triggers, are preferred to psychotropic medication. However, antipsychotic medication is often prescribed to adults with ID and/or autism to manage behaviour that challenges in the absence of severe mental illness, despite there being little research evidence that antipsychotics are effective in this context

Fast algorithm for calculating two-photon absorption spectra

We report a numerical calculation of the two-photon absorption coefficient of electrons in a binding potential using the real-time real-space higher-order difference method. By introducing random vector averaging for the intermediate state, the task of evaluating the two-dimensional time integral is reduced to calculating two one-dimensional integrals. This allows the reduction of the computation load down to the same order as that for the linear response function. The relative advantage of the method compared to the straightforward multi-dimensional time integration is greater for the calculation of non-linear response functions of higher order at higher energy resolution.Comment: 4 pages, 2 figures. It will be published in Phys. Rev. E on 1, March, 199

Towards a national trauma registry for the United Arab Emirates

<p>Abstract</p> <p>Background</p> <p>Trauma is a major health problem in the United Arab Emirates (UAE) as well as worldwide. Trauma registries provide large longitudinal databases for analysis and policy improvement. We aim in this paper to report on the development and evolution of a national trauma registry using a staged approach by developing a single-center registry, a two-center registry, and then a multi-center registry. The three registries were established by developing suitable data collection forms, databases, and interfaces to these databases. The first two registries collected data for a finite period of time and the third is underway. The steps taken to establish these registries depend on whether the registry is intended as a single-center or multi-center registry.</p> <p>Findings</p> <p>Several issues arose and were resolved during the development of these registries such as the relational design of the database, whether to use a standalone database management system or a web-based system, and the usability and security of the system. The inclusion of preventive medicine data elements is important in a trauma registry and the focus on road traffic collision data elements is essential in a country such as the UAE. The first two registries provided valuable data which has been analyzed and published.</p> <p>Conclusions</p> <p>The main factors leading to the successful establishment of a multi-center trauma registry are the development of a concise data entry form, development of a user-friendly secure web-based database system, the availability of a computer and Internet connection in each data collection center, funded data entry personnel well trained in extracting medical data from the medical record and entering it into the computer, and experienced personnel in trauma injuries and data analysis to continuously maintain and analyze the registry.</p

Plasma lipid biomarker signatures in squamous carcinoma and adenocarcinoma lung cancer patients

There is a clinical need for reliable biomarkers for lung cancer that permit early diagnosis of the disease and provide prediction of histological phenotype. A prospective study design was used with a study population of patients with suspected lung cancer. Blood samples were collected from 17 patients with histologically confirmed squamous cell lung carcinoma, 17 individuals with adenocarcinoma, and 17 control individuals who did not subsequently have a diagnosis of lung cancer or any other cancer. Blood plasma samples were analysed for their lipid profiles using liquid chromatography coupled with high resolution mass spectrometry. Data were analysed using multivariate statistical methods. There was good separation between histological subtypes and control groups and also between individuals with a subsequent diagnosis of adenocarcinoma and squamous cell carcinoma (sensitivity 80 %, specificity 83 %, Q2 = 0.70). Alterations in the levels of different classes of lipids including triglycerides (TGs), phosphatidylinositols (PIs), phosphatidylcholines (PCs), phosphatidylethanolamines (PEs), free fatty acids, lysophospholipids and sphingolipids were observed in squamous carcinoma and adenocarcinoma lung cancer patients when compared with control patients. In conclusion, this study has identified candidate lipid biomarkers of non-small cell lung cancer patients which may be helpful to indicate the tumour subtype and to differentiate them from patients who do not have lung cancer. Measuring these biomarkers has the potential to improve diagnosis in patients with suspected lung cancer and risk stratification in screening