Portrayal of psychiatric genetics in Australian print news media, 1996-2009

Objective: To investigate how Australian print news media portray psychiatric genetics. Design and setting: Content and framing analysis of a structured sample of print news items about psychiatric genetics published in Australian newspapers between 1996 and 2009. Main outcome measures: Identify dominant discourses about aetiology of mental illness, and perceived clinical outcomes and implications of psychiatric genetics research. Results: We analysed 406 eligible items about the genetics of psychiatric disorders. News coverage of psychiatric genetics has steadily increased since 1996. Items attributing the aetiology of psychiatric disorders to gene-environment interactions (51%) outnumbered items attributing only genetic (30%) or only environmental factors (20%). Of items that referred to heritability of mental illness, frames of genetic determinism (78%) occurred more frequently than probabilistic frames (22%). Of frames related to genetic prophesy, genetic optimism frames (78%) were used more frequently than frames of genetic pessimism (22%). Psychosocial and ethical implications of psychiatric genetics received comparatively relatively little coverage (23%). The analysis identified 22 predictions about psychiatric genetic discoveries and the availability of molecular-based interventions in psychiatry, most of which (20/ 22, 91%) failed to manifest by the predicted year. Conclusions: Excessive optimism about the power of genetic technology in psychiatric health care, perceived clinical benefits, and largely unfulfilled predictions about availability of these benefits could encourage unrealistic expectations about future molecular-based treatment options for mental health

Psychosocial Care after Cancer Diagnosis: Recent Advances and Challenges

Psychosocial oncology is coming of age [...]</jats:p

Seizures as an early symptom of autosomal dominant Alzheimer's disease

Our objective was to assess the reported history of seizures in cognitively asymptomatic mutation carriers for autosomal dominant Alzheimer's disease (ADAD) and the predictive value of seizures for mutation carrier status in cognitively asymptomatic first-degree relatives of ADAD patients. Seizure occurrence in the Dominantly Inherited Alzheimer Network observational study was correlated with mutation carrier status in cognitively asymptomatic subjects. Of 276 cognitively asymptomatic individuals, 11 (4%) had experienced seizures, and nine of these carried an ADAD mutation. Thus, in the Dominantly Inherited Alzheimer Network population, seizure frequency in mutation carriers was significantly higher than in noncarriers (p = 0.04), and the positive predictive value of seizures for the presence of a pathogenic mutation was 81.8%. Among cognitively asymptomatic ADAD family members, the occurrence of seizures increases the a priori risk of 50% mutation-positive status to about 80%. This finding suggests that ADAD mutations increase the risk of seizures

Predicting sporadic Alzheimer's disease progression via inherited Alzheimer's disease‐informed machine‐learning

Introduction Developing cross‐validated multi‐biomarker models for the prediction of the rate of cognitive decline in Alzheimer's disease (AD) is a critical yet unmet clinical challenge. Methods We applied support vector regression to AD biomarkers derived from cerebrospinal fluid, structural magnetic resonance imaging (MRI), amyloid‐PET and fluorodeoxyglucose positron‐emission tomography (FDG‐PET) to predict rates of cognitive decline. Prediction models were trained in autosomal‐dominant Alzheimer's disease (ADAD, n = 121) and subsequently cross‐validated in sporadic prodromal AD (n = 216). The sample size needed to detect treatment effects when using model‐based risk enrichment was estimated. Results A model combining all biomarker modalities and established in ADAD predicted the 4‐year rate of decline in global cognition (R2 = 24%) and memory (R2 = 25%) in sporadic AD. Model‐based risk‐enrichment reduced the sample size required for detecting simulated intervention effects by 50%–75%. Discussion Our independently validated machine‐learning model predicted cognitive decline in sporadic prodromal AD and may substantially reduce sample size needed in clinical trials in AD

Two-electron spin correlations in precision placed donors in silicon

Substitutional donor atoms in silicon are promising qubits for quantum computation with extremely long relaxation and dephasing times demonstrated. One of the critical challenges of scaling these systems is determining inter-donor distances to achieve controllable wavefunction overlap while at the same time performing high fidelity spin readout on each qubit. Here we achieve such a device by means of scanning tunnelling microscopy lithography. We measure anti-correlated spin states between two donor-based spin qubits in silicon separated by 16 ± 1 nm. By utilising an asymmetric system with two phosphorus donors at one qubit site and one on the other (2P−1P), we demonstrate that the exchange interaction can be turned on and off via electrical control of two in-plane phosphorus doped detuning gates. We determine the tunnel coupling between the 2P−1P system to be 200 MHz and provide a roadmap for the observation of two-electron coherent exchange oscillations

Search for Gravitational Waves from Primordial Black Hole Binary Coalescences in the Galactic Halo

We use data from the second science run of the LIGO gravitational-wave detectors to search for the gravitational waves from primordial black hole (PBH) binary coalescence with component masses in the range 0.2--$1.0 M_\odot$. The analysis requires a signal to be found in the data from both LIGO observatories, according to a set of coincidence criteria. No inspiral signals were found. Assuming a spherical halo with core radius 5 kpc extending to 50 kpc containing non-spinning black holes with masses in the range 0.2--$1.0 M_\odot$, we place an observational upper limit on the rate of PBH coalescence of 63 per year per Milky Way halo (MWH) with 90% confidence.Comment: 7 pages, 4 figures, to be submitted to Phys. Rev.