Medication and suicide risk in schizophrenia: A nested case-control study

Introduction: Patients with schizophrenia are at increased risk of suicide, but data from controlled studies of pharmacotherapy in relation to suicide risk is limited. Aim: To explore suicide risk in schizophrenia in relation to medication with antipsychotics, antidepressants, and lithium. Methods: Of all patients with a first clinical discharge diagnosis of schizophrenia or schizoaffective disorder in Stockholm County between 1984 and 2000 (n=4000), patients who died by suicide within five years from diagnosis were defined as cases (n=84; 54% male). Individually matched controls were identified from the same population. Information on prescribed medication was retrieved from psychiatric records in a blinded way. Adjusted odds ratios [OR] of the association between medication and suicide were calculated by conditional logistic regression. Results: Lower suicide risk was found in patients who had been prescribed a second generation antipsychotic (clozapine, olanzapine, risperidone, or ziprasidone; 12 cases and 20 controls): OR 0.29 (95% confidence interval [CI], 0.09-0.97). When the 6 cases and 8 controls who had been prescribed clozapine were excluded, the OR was 0.23 (95% CI 0.06-0.89). No significant association was observed between suicide and prescription of any antipsychotic, depot injection antipsychotics, antidepressants, SSRI, or lithium. Conclusions: Lower suicide risk for patients who had been prescribed second generation antipsychotics may be related to a pharmacological effect of these drugs, to differences in adherence, or to differences in other patient characteristics associated with lower suicide risk. © 2013 Elsevier B.V

STAR: predicting recombination sites from amino acid sequence

BACKGROUND: Designing novel proteins with site-directed recombination has enormous prospects. By locating effective recombination sites for swapping sequence parts, the probability that hybrid sequences have the desired properties is increased dramatically. The prohibitive requirements for applying current tools led us to investigate machine learning to assist in finding useful recombination sites from amino acid sequence alone. RESULTS: We present STAR, Site Targeted Amino acid Recombination predictor, which produces a score indicating the structural disruption caused by recombination, for each position in an amino acid sequence. Example predictions contrasted with those of alternative tools, illustrate STAR'S utility to assist in determining useful recombination sites. Overall, the correlation coefficient between the output of the experimentally validated protein design algorithm SCHEMA and the prediction of STAR is very high (0.89). CONCLUSION: STAR allows the user to explore useful recombination sites in amino acid sequences with unknown structure and unknown evolutionary origin. The predictor service is available from

Leaping and dancing with digitality : Exploring human-smartphone-entanglements in classrooms

This chapter explores digitality as part of young people’s everyday lives in the Arctic. It is based on two ethnographic studies situated in the political context of the “digital leap”, the governmental and curricular emphasis on digitality in education in Finland. With the more formal “digital leap”, informal engagements and attachments with digitality intertwine, in which students’ own smartphones play an increasingly significant role. The analyses use the notion of entanglement (Barad) to examine how primary school and upper secondary school students emerge in their situated and specific encounters with smartphones in school. The starting points of things, bodies, affect, time and space open up insights to connectivity between young people’s digital activities and global economic networks as well as to the multidirectionality between humans and technologies: while the students access their digital devices, the digitalities also access their users. We suggest that this wilder form of “digital leap” requires reconsidering materiality, affect, and instability of space and time.Peer reviewe

On the importance of sluggish state memory for learning long term dependency

The vanishing gradients problem inherent in Simple Recurrent Networks (SRN) trained with back-propagation, has led to a significant shift towards the use of Long Short-term Memory (LSTM) and Echo State Networks (ESN), which overcome this problem through either second order error-carousel schemes or different learning algorithms respectively. This paper re-opens the case for SRN-based approaches, by considering a variant, the Multi-recurrent Network (MRN). We show that memory units embedded within its architecture can ameliorate against the vanishing gradient problem, by providing variable sensitivity to recent and more historic information through layer- and self-recurrent links with varied weights, to form a so-called sluggish state-based memory. We demonstrate that an MRN, optimised with noise injection, is able to learn the long term dependency within a complex grammar induction task, significantly outperforming the SRN, NARX and ESN. Analysis of the internal representations of the networks, reveals that sluggish state-based representations of the MRN are best able to latch on to critical temporal dependencies spanning variable time delays, to maintain distinct and stable representations of all underlying grammar states. Surprisingly, the ESN was unable to fully learn the dependency problem, suggesting the major shift towards this class of models may be premature

The value of position-specific priors in motif discovery using MEME

<p>Abstract</p> <p>Background</p> <p>Position-specific priors have been shown to be a flexible and elegant way to extend the power of Gibbs sampler-based motif discovery algorithms. Information of many types–including sequence conservation, nucleosome positioning, and negative examples–can be converted into a prior over the location of motif sites, which then guides the sequence motif discovery algorithm. This approach has been shown to confer many of the benefits of conservation-based and discriminative motif discovery approaches on Gibbs sampler-based motif discovery methods, but has not previously been studied with methods based on expectation maximization (EM).</p> <p>Results</p> <p>We extend the popular EM-based MEME algorithm to utilize position-specific priors and demonstrate their effectiveness for discovering transcription factor (TF) motifs in yeast and mouse DNA sequences. Utilizing a discriminative, conservation-based prior dramatically improves MEME's ability to discover motifs in 156 yeast TF ChIP-chip datasets, more than doubling the number of datasets where it finds the correct motif. On these datasets, MEME using the prior has a higher success rate than eight other conservation-based motif discovery approaches. We also show that the same type of prior improves the accuracy of motifs discovered by MEME in mouse TF ChIP-seq data, and that the motifs tend to be of slightly higher quality those found by a Gibbs sampling algorithm using the same prior.</p> <p>Conclusions</p> <p>We conclude that using position-specific priors can substantially increase the power of EM-based motif discovery algorithms such as MEME algorithm.</p

Shotgun Phage Display - Selection for Bacterial Receptins or other Exported Proteins

Shotgun phage display cloning involves construction of libraries from randomly fragmented bacterial chromosomal DNA, cloned genes, or eukaryotic cDNAs, into a phagemid vector. The library obtained consists of phages expressing polypeptides corresponding to all genes encoded by the organism, or overlapping peptides derived from the cloned gene. From such a library, polypeptides with affinity for another molecule can be isolated by affinity selection, panning. The technique can be used to identify bacterial receptins and identification of their minimal binding domain, and but also to identify epitopes recognised by antibodies. In addition, after modification of the phagemid vector, the technique has also been used to identify bacterial extracytoplasmic proteins

Association of Mediterranean diet with survival after breast cancer diagnosis in women from nine European countries: results from the EPIC cohort study

BACKGROUND: The Mediterranean diet has been associated with lower risk of breast cancer (BC) but evidence from prospective studies on the role of Mediterranean diet on BC survival remains sparse and conflicting. We aimed to investigate whether adherence to Mediterranean diet prior to diagnosis is associated with overall and BC-specific mortality. METHODS: A total of 13,270 incident breast cancer cases were identified from an initial sample of 318,686 women in 9 countries from the European Prospective Investigation into Cancer and Nutrition (EPIC) study. Adherence to Mediterranean diet was estimated through the adapted relative Mediterranean diet (arMED), a 16-point score that includes 8 key components of the Mediterranean diet and excludes alcohol. The degree of adherence to arMED was classified as low (score 0-5), medium (score 6-8), and high (score 9-16). Multivariable Cox proportional hazards models were used to analyze the association between the arMED score and overall mortality, and Fine-Gray competing risks models were applied for BC-specific mortality. RESULTS: After a mean follow-up of 8.6 years from diagnosis, 2340 women died, including 1475 from breast cancer. Among all BC survivors, low compared to medium adherence to arMED score was associated with a 13% higher risk of all-cause mortality (HR 1.13, 95%CI 1.01-1.26). High compared to medium adherence to arMED showed a non-statistically significant association (HR 0.94; 95% CI 0.84-1.05). With no statistically significant departures from linearity, on a continuous scale, a 3-unit increase in the arMED score was associated with an 8% reduced risk of overall mortality (HR3-unit 0.92, 95% CI: 0.87-0.97). This result sustained when restricted to postmenopausal women and was stronger among metastatic BC cases (HR3-unit 0.81, 95% CI: 0.72-0.91). CONCLUSIONS: Consuming a Mediterranean diet before BC diagnosis may improve long-term prognosis, particularly after menopause and in cases of metastatic breast cancer. Well-designed dietary interventions are needed to confirm these findings and define specific dietary recommendations

Periprosthetic DXA after total hip arthroplasty with short vs. ultra-short custom-made femoral stems

Background and purpose Dual-energy X-ray absorptiometry (DXA) analysis of the 7 periprosthetic Gruen zones is the most commonly used protocol to evaluate bone remodeling after the implantation of conventional femoral stems. We assessed the value of DXA after cementless primary total hip arthroplasty (THA) by comparing the effect of progressive shortening of the stem of two femoral implants on periprosthetic bone remodeling using a specifically developed protocol of analysis with 5 periprosthetic regions of interest (ROIs)

Metabolic signatures of healthy lifestyle patterns and colorectal cancer risk in a European cohort

Background & Aims Colorectal cancer risk can be lowered by adherence to the World Cancer Research Fund/American Institute for Cancer Research (WCRF/AICR) guidelines. We derived metabolic signatures of adherence to these guidelines and tested their associations with colorectal cancer risk in the European Prospective Investigation into Cancer cohort. Methods Scores reflecting adherence to the WCRF/AICR recommendations (scale, 1–5) were calculated from participant data on weight maintenance, physical activity, diet, and alcohol among a discovery set of 5738 cancer-free European Prospective Investigation into Cancer participants with metabolomics data. Partial least-squares regression was used to derive fatty acid and endogenous metabolite signatures of the WCRF/AICR score in this group. In an independent set of 1608 colorectal cancer cases and matched controls, odds ratios (ORs) and 95% CIs were calculated for colorectal cancer risk per unit increase in WCRF/AICR score and per the corresponding change in metabolic signatures using multivariable conditional logistic regression. Results Higher WCRF/AICR scores were characterized by metabolic signatures of increased odd-chain fatty acids, serine, glycine, and specific phosphatidylcholines. Signatures were inversely associated more strongly with colorectal cancer risk (fatty acids: OR, 0.51 per unit increase; 95% CI, 0.29–0.90; endogenous metabolites: OR, 0.62 per unit change; 95% CI, 0.50–0.78) than the WCRF/AICR score (OR, 0.93 per unit change; 95% CI, 0.86–1.00) overall. Signature associations were stronger in male compared with female participants. Conclusions Metabolite profiles reflecting adherence to WCRF/AICR guidelines and additional lifestyle or biological risk factors were associated with colorectal cancer. Measuring a specific panel of metabolites representative of a healthy or unhealthy lifestyle may identify strata of the population at higher risk of colorectal cancer