Does the meld system provide equal access to liver transplantation for patients with different ABO blood groups?

This study investigates the relationship between blood group and waiting time until transplantation or death on the waiting list. All patients listed for liver transplantation in the Netherlands between 15 December 2006 and 31 December 2012, were included. Study variables were gender, age, year of listing, diagnosis, previous transplantations, blood group, urgency, and MELD score. Using a competing risks analysis, separate cumulative incidence curves were constructed for death on the waiting list and transplantation and used to evaluate outcomes.In 517 listings, the mean death rate per 100 patient‐years was 10.4. A total of 375 (72.5% of all listings) were transplanted. Of all transplantations, 352 (93.9%) were ABO‐identical and 23 (6.1%) ABO‐compatible. The 5‐year cumulative incidence of death was 11.2% (SE 1.4%), and of transplantation 72.5% (SE 2.0%). Patient blood group had no multivariate significant impact on the hazard of dying on the waiting list nor on transplantation. Age, MELD score, and urgency status were significantly related to the death on the waiting list and transplantation. More recent listing had higher probability of being transplanted. In the MELD era, patient blood group status does not have a significant impact on liver transplant waiting list mortality nor on waiting time for transplantation.     

Equilibrium point control cannot be refuted by experimental reconstruction of equilibrium point trajectories

In the literature, it has been hotly debated whether the brain uses internal models or equilibrium point (EP) control to generate arm movements. EP control involves specification of EP trajectories, time series of arm configurations in which internal forces and external forces are in equilibrium; if the arm is not in a specified EP, it is driven toward this EP by muscle forces arising due to central drive, reflexes, and muscle mechanics. EP control has been refuted by researchers claiming that EP trajectories underlying movements of subjects were complex. These researchers used an approach that involves applying force perturbations during movements of subjects and fitting a mass-spring-damper model to the kinematic responses, and then reconstructing the EP trajectory using the estimated stiffness, damping, and measured kinematics. In this study, we examined the validity of this approach using an EP-controlled musculoskeletal model of the arm. We used the latter model to simulate unperturbed and perturbed maximally fast movements and optimized the parameter values of a mass-spring-damper model to make it reproduce as best as possible the kinematic responses. It was shown that estimated stiffness not only depended on the "true" stiffness of the musculoskeletal model but on all of its dynamical parameters. Furthermore it was shown that reconstructed EP trajectories were in agreement with those presented in the literature but did not resemble the simple EP trajectories that had been used to generate the movement of the model. It was concluded that the refutation of EP control on the basis of results obtained with mass-spring-damper models was unjust.     

Nicotine improves probabilistic reward learning in wildtype but not alpha7 nAChR null mutants,yet alpha7 nAChR agonists do not improve probabilistic learning

Cognitive impairments, e.g., reward learning, are present in various psychiatric disorders and warrant treatment. Improving reward-related learning could synergistically enhance psychosocial treatments and cognition generally. A critical first step is to understand the mechanisms underlying reward learning. The dopamine system has been implicated in such learning, but less known is how indirect activation of this system may affect reward learning. We determined the role of alpha7 nicotinic acetylcholine receptors (nAChR) on a probabilistic reversal learning task (PRLT) in mice that includes reward and punishment. Male alpha7 knockout (KO), heterozygous (HT), and wildtype (WT) littermate mice (n?=?84) were treated with vehicle, 0.03, or 0.3?mg/kg nicotine. Two cohorts of C57BL/6NJ male mice were treated with various alpha7 nAChR ligands, including the full agonists PNU282877 and AR-R-17779, the positive allosteric modulator CCMI, the partial agonist SSR180711, and the antagonist methyllycaconitine. All mice were then tested in the PRLT. Nicotine (0.3?mg/kg) significantly improved initial reward learning in alpha7 WT and HT mice but did not improve learning in KO mice, suggesting an involvement of the alpha7 nAChR in the pro-learning effects of nicotine. Neither alpha7 nAChR treatments (PNU282987, AR-R-17779, CCMI, SSR180711, nor methyllycaconitine) affected mouse PRLT performance however. Nicotine improved reward learning via a mechanism that may include alpha7 nAChRs. This improvement unlikely relied solely on alpha7 nAChRs however, since no alpha7 nAChR ligand improved reward learning in normal mice. Future assessments of the effects of other nAChR subtypes on reward learning are needed.     

Do Surrogate Endpoints Better Correlate with Overall Survival in Studies That Did Not Allow for Crossover or Reported Balanced Postprogression Treatments? An Application in Advanced Non–Small Cell Lung Cancer

Background

In previous studies, correlation between overall survival (OS) and surrogate endpoints like objective response rate (ORR) or progression-free survival (PFS) in advanced non-small cell lung cancer (NSCLC) was poor. This can be biased by crossover and postprogression treatments.

Assessing Lung Cancer Screening Programs under Uncertainty in a Heterogeneous Population

Background

Lung cancer screening can reduce cancer mortality. Most implementation studies focus only on low-dose computed tomography (LDCT) and clinical attributes of screening and do not include preferences of potential participants. In this study we evaluated the perceived value of screening programs based on LDCT, breath analysis (BA), or blood biomarkers (BB) according to the perspective of the target population.

Identifying viable theoretical frameworks with essential parameters for real-time and real world alcohol craving research: a systematic review of craving models

Background: Substance use is known to be episodic, dynamic, complex, and highly influenced by the environment, therefore a situational and momentary focus to alcohol craving research is appropriate. Current advances in mobile and wearable technology provide novel opportunities for craving research. However, the lack of consensus within craving theory impedes the identification and prioritization of parameters to be monitored. The aim of this study is to critically review current craving models in order to determine viable theoretical frameworks of alcohol craving and its essential parameters.

Methods: Eighteen models of craving were reviewed by applying a literature search with a five-step strategy that accounted for the momentary nature of craving and included a snowballing search and a key term extraction algorithm. Based on this review, multiple decision criteria were defined upon which to evaluate the models.

Results: Six models for alcohol craving were supported by sufficient empirical research to be eligible. The inferences drawn on these six models resulted in three decision criteria: the model should (1) incorporate negative affect as a predictor of relapse; (2) explain that dependent drinkers have a higher attentional bias towards alcohol cues than nondependent drinkers; (3) incorporate increased risk of relapse with heightened stress levels.

Conclusions: The affective processing model of negative reinforcement, the cognitive processing model, the incentive sensitization theory of addiction and the theory of neural opponent motivation are classified as viable theoretical frameworks, resulting in negative affect and stress as relevant parameters to include in real-time craving monitoring research.