S100B is increased in mood disorders and may be reduced by antidepressive treatment

Previous studies have reported alterations of glial cells and particularly astrocytes in mood disorders. Therefore, serum concentration of the astrocytic marker S100B was ascertained with an immunoluminometric assay in 20 patients with mood disorder and 12 healthy age-matched controls. Serum S100B was elevated in major depression (median after admission 410 ng/l, at discharge < 100 ng/l) and mania (130, 160 ng/l), when compared with controls (< 100 ng/l; rho< 0.01). Antidepressive treatment reduced S100B in conjunction with severity of depressive symptoms ( rho< 0.01). The severity of depression (Hamilton Depression Rating Scale) was positively correlated with S100B (r(s) = 0.51, rho< 0.005). Elevated serum S100B during depressive and manic episodes of mood disorders may indicate alterations of astrocytes, which are reversed by antidepressive treatment

Serum S100B is increased during early treatment with antipsychotics and in deficit schizophrenia

Previous studies reported controversial results concerning alterations of astrocytes in schizophrenia. Because S100B may be regarded as a marker for astrocytes, the objective of this study was to examine S100B serum concentrations in 30 patients with schizophrenia with a monoclonal two-site immunoluminometric assay that specifically detects S100B. An ANOVA revealed medication (p0.05). Patients with deficit (250.6±154.9 ng/l) had higher S100B levels than patients with nondeficit schizophrenia (146.7±107.2 ng/l, p<0.05) or controls (p<0.005). S100B was positively correlated with the subscore ‘thought disturbance’ of the Brief Psychiatric Rating Scale (p<0.05). In summary, increased serum levels of S100B may indicate alterations of astrocytes during early treatment with antipsychotics and in deficit schizophrenia. Whether S100B is elevated due to injured astrocytes and a disrupted blood–brain barrier, or by active secretion of S100B by astrocytes, has to be clarified by further studies

Calomplification — the power of generative calorimeter models

Motivated by the high computational costs of classical simulations, machine-learned generative models can be extremely useful in particle physics and elsewhere. They become especially attractive when surrogate models can efficiently learn the underlying distribution, such that a generated sample outperforms a training sample of limited size. This kind of GANplification has been observed for simple Gaussian models. We show the same effect for a physics simulation, specifically photon showers in an electromagnetic calorimeter

Somatization among ethnic minorities and immigrants: Why does it matter to Consultation Liaison Psychiatry?

The article describes the reasons why psychiatrists working in the field of consultation-liaison should be trained and aware of the relevance of culture in their everyday work. Moreover, the article aims at advertising the special-interest group on cultural CLP, a network of clinicians and researchers within the European Association of Psychosomatic Medicine that share their interest and activities in this subject

Requirement for Interaction of PI3-Kinase p110α with RAS in Lung Tumor Maintenance

SummaryRAS proteins directly activate PI3-kinases. Mice bearing a germline mutation in the RAS binding domain of the p110α subunit of PI3-kinse are resistant to the development of RAS-driven tumors. However, it is unknown whether interaction of RAS with PI3-kinase is required in established tumors. The need for RAS interaction with p110α in the maintenance of mutant Kras-driven lung tumors was explored using an inducible mouse model. In established tumors, removal of the ability of p110α to interact with RAS causes long-term tumor stasis and partial regression. This is a tumor cell-autonomous effect, which is improved significantly by combination with MEK inhibition. Total removal of p110α expression or activity has comparable effects, albeit with greater toxicities

Developing a collaborative agenda for humanities and social scientific research on laboratory animal science and welfare.

Improving laboratory animal science and welfare requires both new scientific research and insights from enquiry in the humanities and social sciences. Whilst scientific research provides evidence to replace, reduce and refine procedures involving laboratory animals (the ‘3Rs’), work in the humanities and social sciences can help understand the social, economic and cultural processes that enhance or impede humane ways of knowing and working with laboratory animals. However, communication across these disciplinary perspectives is currently limited, and they frame questions, generate results, engage users, and seek to influence policy in different ways. To facilitate dialogue and future research at this interface, we convened an interdisciplinary group of 45 life scientists, social scientists, humanities scholars, non-governmental organisations and policy-makers to generate a collaborative research agenda. This drew on other agenda-setting exercises in science policy, using a collaborative and deliberative approach for the identification of research priorities. Participants were recruited from across the community, invited to submit research questions and vote on their priorities. They then met at an interactive workshop in the UK, discussed all 136 questions submitted, and collectively defined the 30 most important issues for the group. The output is a collaborative future agenda for research in the humanities and social sciences on laboratory animal science and welfare. The questions indicate a demand for new research in the humanities and social sciences to inform emerging discussions and priorities on the governance and practice of laboratory animal research, including around: international harmonisation, openness and public engagement, ‘cultures of care’, harm-benefit analysis and the future of the 3Rs. The process underlines the value of interdisciplinary exchange for improving mutual understanding of different research cultures and identifies ways of enhancing the effectiveness of future research at the interface between the humanities, social sciences, science and science policy

A programme theory for liaison mental health services in England

Background: Mechanisms by which liaison mental health services (LMHS) may bring about improved patient and organisational outcomes are poorly understood. A small number of logic models have been developed, but they fail to capture the complexity of clinical practice. Method: We synthesised data from a variety of sources including a large national survey, 73 in-depth interviews with acute and liaison staff working in hospitals with different types of liaison mental health services, and relevant local, national and international literature. We generated logic models for two common performance indicators used to assess organisational outcomes for LMHS: response times in the emergency department and hospital length of stay for people with mental health problems. Results: We identified 8 areas of complexity that influence performance, and 6 trade-offs which drove the models in different directions depending upon the balance of the trade-off. The logic models we developed could only be captured by consideration of more than one pass through the system, the complexity in which they operated, and the trade-offs that occurred. Conclusions: Our findings are important for commissioners of liaison services. Reliance on simple target setting may result in services that are unbalanced and not patient-centred. Targets need to be reviewed on a regular basis, together with other data that reflect the wider impact of the service, and any external changes in the system that affect the performance of LMHS, which are beyond their control