Improving multivariate Horner schemes with Monte Carlo tree search

Optimizing the cost of evaluating a polynomial is a classic problem in computer science. For polynomials in one variable, Horner's method provides a scheme for producing a computationally efficient form. For multivariate polynomials it is possible to generalize Horner's method, but this leaves freedom in the order of the variables. Traditionally, greedy schemes like most-occurring variable first are used. This simple textbook algorithm has given remarkably efficient results. Finding better algorithms has proved difficult. In trying to improve upon the greedy scheme we have implemented Monte Carlo tree search, a recent search method from the field of artificial intelligence. This results in better Horner schemes and reduces the cost of evaluating polynomials, sometimes by factors up to two.Comment: 5 page

Cost-effectiveness and Cost-utility of the Adherence Improving Self-management Strategy in Human Immunodeficiency Virus Care : A Trial-based Economic Evaluation

This study was funded by ZonMw (the Netherlands), program Doelmatigheidsonderzoek (grant number 171002208). This funding source had no role in study design, data collection, analysis, interpretation, or writing of the report. All authors declare that they have no competing interests. We thank the HIV-nurses and physicians from the seven HIV-clinics who were involved in the AIMSstudy (Academic Medical Center, Amsterdam; Slotervaart Hospital, Amsterdam; St. Lucas-Andreas Hospital, Amsterdam; the Leiden University Medical Center, Leiden; Haga Teaching Hospital, Den Haag; Erasmus Medical Center, Rotterdam; Isala Clinics, Zwolle) for their input and collaboration. We also would like to express our gratitude to the study participants. Written informed consent was obtained from each patient. The study has been approved by the ethics committee of each participating center.Peer reviewedPostprin

Enlarged striatal volume in adults with ADHD carrying the 9-6 haplotype of the dopamine transporter gene DAT1

The dopamine transporter gene, DAT1 (SLC6A3), has been studied extensively as a candidate gene for attention-deficit/hyperactivity disorder (ADHD). Different alleles of variable number of tandem repeats (VNTRs) in this gene have been associated with childhood ADHD (10/10 genotype and haplotype 10-6) and adult ADHD (haplotype 9-6). This suggests a differential association depending on age, and a role of DAT1 in modulating the ADHD phenotype over the lifespan. The DAT1 gene may mediate susceptibility to ADHD through effects on striatal volumes, where it is most highly expressed. In an attempt to clarify its mode of action, we examined the effect of three DAT1 alleles (10/10 genotype, and the haplotypes 10-6 and 9-6) on bilateral striatal volumes (nucleus accumbens, caudate nucleus, and putamen) derived from structural magnetic resonance imaging scans using automated tissue segmentation. Analyses were performed separately in three cohorts with cross-sectional MRI data, a childhood/adolescent sample (NeuroIMAGE, 301 patients with ADHD and 186 healthy participants) and two adult samples (IMpACT, 118 patients with ADHD and 111 healthy participants; BIG, 1718 healthy participants). Regression analyses revealed that in the IMpACT cohort, and not in the other cohorts, carriers of the DAT1 adult ADHD risk haplotype 9-6 had 5.9 % larger striatum volume relative to participants not carrying this haplotype. This effect varied by diagnostic status, with the risk haplotype affecting striatal volumes only in patients with ADHD. An explorative analysis in the cohorts combined (N = 2434) showed a significant gene-by-diagnosis-by-age interaction suggesting that carriership of the 9-6 haplotype predisposes to a slower age-related decay of striatal volume specific to the patient group. This study emphasizes the need of a lifespan approach in genetic studies of ADHD

Nesfatin-1/NUCB2 as a Potential New Element of Sleep Regulation in Rats.

STUDY OBJECTIVES: Millions suffer from sleep disorders that often accompany severe illnesses such as major depression; a leading psychiatric disorder characterized by appetite and rapid eye movement sleep (REMS) abnormalities. Melanin-concentrating hormone (MCH) and nesfatin-1/NUCB2 (nesfatin) are strongly co - expressed in the hypothalamus and are involved both in food intake regulation and depression. Since MCH was recognized earlier as a hypnogenic factor, we analyzed the potential role of nesfatin on vigilance. DESIGN: We subjected rats to a 72 h-long REMS deprivation using the classic flower pot method, followed by a 3 h-long 'rebound sleep'. Nesfatin mRNA and protein expressions as well as neuronal activity (Fos) were measured by quantitative in situ hybridization technique, ELISA and immunohistochemistry, respectively, in 'deprived' and 'rebound' groups, relative to controls sacrificed at the same time. We also analyzed electroencephalogram of rats treated by intracerebroventricularly administered nesfatin-1, or saline. RESULTS: REMS deprivation downregulated the expression of nesfatin (mRNA and protein), however, enhanced REMS during 'rebound' reversed this to control levels. Additionally, increased transcriptional activity (Fos) was demonstrated in nesfatin neurons during 'rebound'. Centrally administered nesfatin-1 at light on reduced REMS and intermediate stage of sleep, while increased passive wake for several hours and also caused a short-term increase in light slow wave sleep. CONCLUSIONS: The data designate nesfatin as a potential new factor in sleep regulation, which fact can also be relevant in the better understanding of the role of nesfatin in the pathomechanism of depression

Gender differences in the use of cardiovascular interventions in HIV-positive persons; the D:A:D Study

Peer reviewe

Exploration of Shared Genetic Architecture Between Subcortical Brain Volumes and Anorexia Nervosa

In MRI scans of patients with anorexia nervosa (AN), reductions in brain volume are often apparent. However, it is unknown whether such brain abnormalities are influenced by genetic determinants that partially overlap with those underlying AN. Here, we used a battery of methods (LD score regression, genetic risk scores, sign test, SNP effect concordance analysis, and Mendelian randomization) to investigate the genetic covariation between subcortical brain volumes and risk for AN based on summary measures retrieved from genome-wide association studies of regional brain volumes (ENIGMA consortium, n = 13,170) and genetic risk for AN (PGC-ED consortium, n = 14,477). Genetic correlations ranged from − 0.10 to 0.23 (all p > 0.05). There were some signs of an inverse concordance between greater thalamus volume and risk for AN (permuted p = 0.009, 95% CI: [0.005, 0.017]). A genetic variant in the vicinity of ZW10, a gene involved in cell division, and neurotransmitter and immune system relevant genes, in particular DRD2, was significantly associated with AN only after conditioning on its association with caudate volume (pFDR = 0.025). Another genetic variant linked to LRRC4C, important in axonal and synaptic development, reached significance after conditioning on hippocampal volume (pFDR = 0.021). In this comprehensive set of analyses and based on the largest available sample sizes to date, there was weak evidence for associations between risk for AN and risk for abnormal subcortical brain volumes at a global level (that is, common variant genetic architecture), but suggestive evidence for effects of single genetic markers. Highly powered multimodal brain- and disorder-related genome-wide studies are needed to further dissect the shared genetic influences on brain structure and risk for AN

Genetic influences on schizophrenia and subcortical brain volumes: large-scale proof-of-concept and roadmap for future studies

Schizophrenia is a devastating psychiatric illness with high heritability. Brain structure and function differ, on average, between schizophrenia cases and healthy individuals. As common genetic associations are emerging for both schizophrenia and brain imaging phenotypes, we can now use genome-wide data to investigate genetic overlap. Here we integrated results from common variant studies of schizophrenia (33,636 cases, 43,008 controls) and volumes of several (mainly subcortical) brain structures (11,840 subjects). We did not find evidence of genetic overlap between schizophrenia risk and subcortical volume measures either at the level of common variant genetic architecture or for single genetic markers. The current study provides proof-of-concept (albeit based on a limited set of structural brain measures), and defines a roadmap for future studies investigating the genetic covariance between structural/functional brain phenotypes and risk for psychiatric disorders