Development of multivariable models to predict change in Body Mass Index within a clinical trial population of psychotic individuals

Many antipsychotics promote weight gain, which can lead to non-compliance and relapse of psychosis. By developing models that accurately identify individuals at greater risk of weight gain, clinicians can make informed treatment decisions and target intervention measures. We examined clinical, genetic and expression data for 284 individuals with psychosis derived from a previously published randomised controlled trial (IMPACT). These data were used to develop regression and classification models predicting change in Body Mass Index (BMI) over one year. Clinical predictors included demographics, anthropometrics, cardiac and blood measures, diet and exercise, physical and mental health, medication and BMI outcome measures. We included genetic polygenic risk scores (PRS) for schizophrenia, bipolar disorder, BMI, waist-hip-ratio, insulin resistance and height, as well as gene co-expression modules generated by Weighted Gene Co-expression Network Analysis (WGCNA). The best performing predictive models for BMI and BMI gain after one year used clinical data only, which suggests expression and genetic data do not improve prediction in this cohort

Mouse models of breast cancer metastasis

Metastatic spread of cancer cells is the main cause of death of breast cancer patients, and elucidation of the molecular mechanisms underlying this process is a major focus in cancer research. The identification of appropriate therapeutic targets and proof-of-concept experimentation involves an increasing number of experimental mouse models, including spontaneous and chemically induced carcinogenesis, tumor transplantation, and transgenic and/or knockout mice. Here we give a progress report on how mouse models have contributed to our understanding of the molecular processes underlying breast cancer metastasis and on how such experimentation can open new avenues to the development of innovative cancer therapy

Increased throughput and ultra-high mass resolution in DESI FT-ICR MS imaging through new-generation external data acquisition system and advanced data processing approaches

Desorption electrospray ionisation-mass spectrometry imaging (DESI-MSI) is a powerful imaging technique for the analysis of complex surfaces. However, the often highly complex nature of biological samples is particularly challenging for MSI approaches, as options to appropriately address mass spectral complexity are limited. Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS) offers superior mass accuracy and mass resolving power, but its moderate throughput inhibits broader application. Here we demonstrate the dramatic gains in mass resolution and/or throughput of DESI-MSI on an FT-ICR MS by developing and implementing a sophisticated data acquisition and data processing pipeline. The presented pipeline integrates, for the first time, parallel ion accumulation and detection, post-processing absorption mode Fourier transform and pixel-by-pixel internal re-calibration. To achieve that, first, we developed and coupled an external high-performance data acquisition system to an FT-ICR MS instrument to record the time-domain signals (transients) in parallel with the instrument’s built-in electronics. The recorded transients were then processed by the in-house developed computationally-efficient data processing and data analysis software. Importantly, the described pipeline is shown to be applicable even to extremely large, up to 1 TB, imaging datasets. Overall, this approach provides improved analytical figures of merits such as: (i) enhanced mass resolution at no cost in experimental time; and (ii) up to 4-fold higher throughput while maintaining a constant mass resolution. Using this approach, we not only demonstrate the record 1 million mass resolution for lipid imaging from brain tissue, but explicitly demonstrate such mass resolution is required to resolve the complexity of the lipidome

Supporting shared decision making for older people with multiple health and social care needs: a realist synthesis

Background: Health care systems are increasingly moving towards more integrated approaches. Shared decision making (SDM) is central to these models but may be complicated by the need to negotiate and communicate decisions between multiple providers, as well as patients and their family carers; particularly for older people with complex needs. The aim of this review was to provide a context relevant understanding of how interventions to facilitate SDM might work for older people with multiple health and care needs, and how they might be applied in integrated care models. Methods: Iterative, stakeholder driven, realist synthesis following RAMESES publication standards. It involved: 1) scoping literature and stakeholder interviews (n-13) to develop initial programme theory/ies, 2) systematic searches for evidence to test and develop the theories, and 3) validation of programme theory/ies with stakeholders (n=11). We searched PubMed, The Cochrane Library, Scopus, Google, Google Scholar, and undertook lateral searches. All types of evidence were included. Results: We included 88 papers; 29 focused on older people or people with complex needs. We identified four context-mechanism-outcome configurations that together provide an account of what needs to be in place for SDM to work for older people with complex needs. This includes: understanding and assessing patient and carer values and capacity to access and use care, organising systems to support and prioritise SDM, supporting and preparing patients and family carers to engage in SDM and a person-centred culture of which SDM is a part. Programmes likely to be successful in promoting SDM are those that allow older people to feel that they are respected and understood, and that engender confidence to engage in SDM. Conclusions: To embed SDM in practice requires a radical shift from a biomedical focus to a more person-centred ethos. Service providers will need support to change their professional behaviour and to better organise and deliver services. Face to face interactions, permission and space to discuss options, and continuity of patient-professional relationships are key in supporting older people with complex needs to engage in SDM. Future research needs to focus on inter-professional approaches to SDM and how families and carers are involved

Roadmap on dynamics of molecules and clusters in the gas phase

This roadmap article highlights recent advances, challenges and future prospects in studies of the dynamics of molecules and clusters in the gas phase. It comprises nineteen contributions by scientists with leading expertise in complementary experimental and theoretical techniques to probe the dynamics on timescales spanning twenty order of magnitudes, from attoseconds to minutes and beyond, and for systems ranging in complexity from the smallest (diatomic) molecules to clusters and nanoparticles. Combining some of these techniques opens up new avenues to unravel hitherto unexplored reaction pathways and mechanisms, and to establish their significance in, e.g. radiotherapy and radiation damage on the nanoscale, astrophysics, astrochemistry and atmospheric science