Measuring Psychological Inflexibility of Suicidal Thoughts: The Acceptance and Action Questionnaire for Suicidal Ideation (AAQ-SI)

Cognitive Therapy and Research - Despite interest in psychological inflexibility as a marker of suicide risk, no measure of psychological inflexibility specific to SI exists. The present study...     

The theory of Rational Addiction

The Theory of Rational Addictions, by Gary Becker & Kevin Murphy (1988), was a rational choice model that became a standard tool for economists modeling addictive behavior. The approach differs from other theories of addiction by modeling addictive behavior as the gradual implementation of a rational, forward‐looking plan, where consumption at any point in time is partly motivated by the immediate payoff of consumption and partly by the effects this consumption has on the individual in the future. This makes addictive behavior a subset of rational behavior, requiring no more specific government policies or attention than any other consumption choice. Later work by economists extended the theory in different ways, allowing it to match an increasing number of consumption patterns, and searched for ways to test the forward‐looking assumption in different types of market data. While the work was successful as a contribution to rational choice theory, with possible statistical applications, there are several reasons to dismiss its usefulness as an explanation of real‐world addictive behavior and its ability to assess the welfare effects of addictions.     

Secretion,blood levels and cutaneous expression of TL1A in psoriasis patients

TL1A is a TNF‐like cytokine which has been shown to co‐stimulate TH1 and TH17 responses during chronic inflammation. The expression of this novel cytokine has been investigated in inflammatory disorders like rheumatoid arthritis and inflammatory bowel disease, but little is known about expression and induction in psoriasis. Indeed, the pathogenesis in psoriasis is still not fully understood and it is speculated that cytokines other than TNF‐α are important in subsets of patients. Also, for patients with severe disease that are treated with systemic anti‐TNF‐α blockade, novel candidates to be used as disease and response biomarkers are of high interest. Here, we demonstrate TL1A expression in biopsies from psoriatic lesions. Also, we investigated spontaneous and induced TL1A secretion from PBMCs and blood levels from a cohort of psoriasis patients. Here, increased spontaneous secretion from PBMCs was observed as compared to healthy controls and a small subset of patients had highly elevated TL1A in the blood. Interestingly, activation of PBMCs with various cytokines showed a decreased sensitivity for TL1A activation in psoriasis patients compared to healthy controls.TL1A levels in blood and biopsies could not be correlated with disease activity with this patient cohort. Thus, additional large‐scale studies are warranted to investigate TL1A as a biomarker.     

Reoperation rates and risk factors for revision 4 years after dynamic stabilization of the lumbar spine

Background Context

The concept of dynamic stabilization (DS) of the lumbar spine for treatment of degenerative instability has been introduced almost two decades ago. Dynamic stabilization follows the principle of controlling movement in the coronal plane by providing load transfer of the spinal segment without fusion and, at the same time, reducing side effects such as adjacent segment disease (ASD). So far, only little is known about revision rates after DS due to ASD and screw loosening (SL).

Patterns in metabolite profile are associated with risk of more aggressive prostate cancer: A prospective study of 3,057 matched case–control sets from EPIC

Metabolomics may reveal novel insights into the etiology of prostate cancer, for which few risk factors are established. We investigated the association between patterns in baseline plasma metabolite profile and subsequent prostate cancer risk, using data from 3,057 matched case–control sets from the European Prospective Investigation into Cancer and Nutrition (EPIC). We measured 119 metabolite concentrations in plasma samples, collected on average 9.4 years before diagnosis, by mass spectrometry (AbsoluteIDQ p180 Kit, Biocrates Life Sciences AG). Metabolite patterns were identified using treelet transform, a statistical method for identification of groups of correlated metabolites. Associations of metabolite patterns with prostate cancer risk (OR_1SD) were estimated by conditional logistic regression. Supplementary analyses were conducted for metabolite patterns derived using principal component analysis and for individual metabolites. Men with metabolite profiles characterized by higher concentrations of either phosphatidylcholines or hydroxysphingomyelins (OR_1SD = 0.77, 95% confidence interval 0.66–0.89), acylcarnitines C18:1 and C18:2, glutamate, ornithine and taurine (OR_1SD = 0.72, 0.57–0.90), or lysophosphatidylcholines (OR_1SD = 0.81, 0.69–0.95) had lower risk of advanced stage prostate cancer at diagnosis, with no evidence of heterogeneity by follow-up time. Similar associations were observed for the two former patterns with aggressive disease risk (the more aggressive subset of advanced stage), while the latter pattern was inversely related to risk of prostate cancer death (OR_1SD = 0.77, 0.61–0.96). No associations were observed for prostate cancer overall or less aggressive tumor subtypes. In conclusion, metabolite patterns may be related to lower risk of more aggressive prostate tumors and prostate cancer death, and might be relevant to etiology of advanced stage prostate cancer.