Understanding and predicting antidepressant response : using animal models to move toward precision psychiatry

There are two important gaps of knowledge in depression treatment, namely the lack of biomarkers predicting response to antidepressants and the limited knowledge of the molecular mechanisms underlying clinical improvement. However, individually tailored treatment strategies and individualized prescription are greatly needed given the huge socio-economic burden of depression, the latency until clinical improvement can be observed and the response variability to a particular compound. Still, individual patient-level antidepressant treatment outcomes are highly unpredictable. In contrast to other therapeutic areas and despite tremendous efforts during the past years, the genomics era so far has failed to provide biological or genetic predictors of clinical utility for routine use in depression treatment. Specifically, we suggest to 1) shift the focus from the group patterns to individual outcomes, 2) use dimensional classifications such as Research Domain Criteria, 3) envision better planning and improved connections between pre-clinical and clinical studies within translational research units. In contrast to studies in patients, animal models enable both searches for peripheral biosignatures predicting treatment response and in depth analyses of the neurobiological pathways shaping individual antidepressant response in the brain. While there is a considerable number of animal models available aiming at mimicking disease-like conditions such as those seen in depressive disorder, only a limited number of preclinical or truly translational investigations is dedicated to the issue of heterogeneity seen in response to antidepressant treatment. In this mini-review, we provide an overview on the current state of knowledge and propose a framework for successful translational studies into antidepressant treatment response

Brane Tilings and Exceptional Collections

Both brane tilings and exceptional collections are useful tools for describing the low energy gauge theory on a stack of D3-branes probing a Calabi-Yau singularity. We provide a dictionary that translates between these two heretofore unconnected languages. Given a brane tiling, we compute an exceptional collection of line bundles associated to the base of the non-compact Calabi-Yau threefold. Given an exceptional collection, we derive the periodic quiver of the gauge theory which is the graph theoretic dual of the brane tiling. Our results give new insight to the construction of quiver theories and their relation to geometry.Comment: 46 pages, 37 figures, JHEP3; v2: reference added, figure 13 correcte

The effects of anorexia nervosa on bone metabolism in female adolescents

Osteopenia is a frequent, often persistent, complication of anorexia nervosa (AN) in adolescent girls and occurs during a critical time in bone development. Little is known about bone metabolism in this patient population. Therefore, we measured bone density (BMD) and body composition by dual energy x-ray absorptiometry, nutritional status, bone turnover, calcium, and hormonal status in 19 adolescent girls with AN (mean +/- SEM, 16.0+/-0.4 yr) and 19 bone age-matched controls. The mean duration of AN was 19+/-5 months. Spinal (L1-L4) osteopenia was common in AN. Lumbar anterioposterior BMD was more than 1 SD below the mean in 42% of patients, and lateral spine BMD was more than 1 SD below in 63% of patients compared with controls. Lean body mass significantly predicted lumbar bone mineral content (r = 0.75; P \u3c 0.0001) in controls only. In AN, duration of illness was the most significant predictor of spinal BMD (lumbar: r = -0.44; P = 0.06; lateral: r = -0.59; P = 0.008). AN adolescents with mature BA (15 yr and greater) were hypogonadal [estradiol, 16.2+/-1.9 vs. 23.3+/-1.6 pg/mL (P = 0.01); free testosterone, 0.70+/-0.17 vs. 1.36+/-0.14 pg/mL (P = 0.01)] although dehydroepiandrosterone sulfate and urinary free cortisol levels did not differ. Leptin levels were reduced in AN (2.9+/-2.1 vs. 16.5+/-1.8 ng/mL; P \u3c 0.0001). Insulin-like growth factor I (IGF-I) was reduced in AN to 50% of control levels (219+/-41 vs. 511+/-35 ng/mL; P \u3c 0.0001) and correlated with all measures of nutritional status, particularly leptin (r = 0.80; P \u3c 0.0001). Surrogate markers of bone formation, serum osteocalcin (OC) and bone-specific alkaline phosphatase (BSAP), were significantly (P = 0.02) reduced in AN vs. controls (OC, 39.1+/-6.4 vs. 59.2+/-5.2 ng/mL; BSAP, 27.9+/-4.0 vs. 40.6+/-3.4 U/L). The majority of the variation in bone formation in AN was due to IGF-I levels (OC: r2 = 0.72; P = 0.002; BSAP: r2 = 0.53; P = 0.01) in stepwise regression analyses. Bone resorption was comparable in patients and controls. These data demonstrate that bone formation is reduced and uncoupled to bone resorption in mature adolescents with AN in association with low bone density. Lean body mass was a significant predictor of BMD in controls, but not AN patients. The major correlate of bone formation in AN was the nutritionally dependent bone trophic factor, IGF-I. Reduced IGF-I during the critical period of bone mineral accumulation may be an important factor in the development of osteopenia in adolescents with AN

Quivers, Tilings, Branes and Rhombi

We describe a simple algorithm that computes the recently discovered brane tilings for a given generic toric singular Calabi-Yau threefold. This therefore gives AdS/CFT dual quiver gauge theories for D3-branes probing the given non-compact manifold. The algorithm solves a longstanding problem by computing superpotentials for these theories directly from the toric diagram of the singularity. We study the parameter space of a-maximization; this study is made possible by identifying the R-charges of bifundamental fields as angles in the brane tiling. We also study Seiberg duality from a new perspective.Comment: 36 pages, 40 figures, JHEP

Understanding and Predicting Antidepressant Response: Using Animal Models to Move Toward Precision Psychiatry

There are two important gaps of knowledge in depression treatment, namely the lack of biomarkers predicting response to antidepressants and the limited knowledge of the molecular mechanisms underlying clinical improvement. However, individually tailored treatment strategies and individualized prescription are greatly needed given the huge socio-economic burden of depression, the latency until clinical improvement can be observed and the response variability to a particular compound. Still, individual patient-level antidepressant treatment outcomes are highly unpredictable. In contrast to other therapeutic areas and despite tremendous efforts during the past years, the genomics era so far has failed to provide biological or genetic predictors of clinical utility for routine use in depression treatment. Specifically, we suggest to (1) shift the focus from the group patterns to individual outcomes, (2) use dimensional classifications such as Research Domain Criteria, and (3) envision better planning and improved connections between pre-clinical and clinical studies within translational research units. In contrast to studies in patients, animal models enable both searches for peripheral biosignatures predicting treatment response and in depth-analyses of the neurobiological pathways shaping individual antidepressant response in the brain. While there is a considerable number of animal models available aiming at mimicking disease-like conditions such as those seen in depressive disorder, only a limited number of preclinical or truly translational investigations is dedicated to the issue of heterogeneity seen in response to antidepressant treatment. In this mini-review, we provide an overview on the current state of knowledge and propose a framework for successful translational studies into antidepressant treatment response

Hail formation triggers rapid ash aggregation in volcanic plumes.

During explosive eruptions, airborne particles collide and stick together, accelerating the fallout of volcanic ash and climate-forcing aerosols. This aggregation process remains a major source of uncertainty both in ash dispersal forecasting and interpretation of eruptions from the geological record. Here we illuminate the mechanisms and timescales of particle aggregation from a well-characterized 'wet' eruption. The 2009 eruption of Redoubt Volcano, Alaska, incorporated water from the surface (in this case, a glacier), which is a common occurrence during explosive volcanism worldwide. Observations from C-band weather radar, fall deposits and numerical modelling demonstrate that hail-forming processes in the eruption plume triggered aggregation of ∼95% of the fine ash and stripped much of the erupted mass out of the atmosphere within 30 min. Based on these findings, we propose a mechanism of hail-like ash aggregation that contributes to the anomalously rapid fallout of fine ash and occurrence of concentrically layered aggregates in volcanic deposits.AVE acknowledges NSF Postdoctoral Fellowship EAR1250029 and a seed grant from NASA Ames Supercomputing Center. Integrated Data Viewer (IDV) software from UCAR/Unidata was used in the analysis and visualization of the large-eddy simulation. ASTER GDEM is a product of NASA and METI. NCAR Reanalysis data provided by the NOAA/OAR/ESRL Physical Sciences Division, Boulder, Colorado, USA. We acknowledge Victoria University of Wellington, New Zealand, for access to the laser particle size analyzer, and Matt Rogers at University of Alaska, Anchorage for use of the freeze dryer. Rick Hoblitt is thanked for discussions and comments on the manuscript.This is the final version of the article. It first appeared from NPG via http://dx.doi.org/10.1038/ncomms886

Supersymmetry Breaking from a Calabi-Yau Singularity

We conjecture a geometric criterion for determining whether supersymmetry is spontaneously broken in certain string backgrounds. These backgrounds contain wrapped branes at Calabi-Yau singularites with obstructions to deformation of the complex structure. We motivate our conjecture with a particular example: the $Y^{2,1}$ quiver gauge theory corresponding to a cone over the first del Pezzo surface, $dP_1$. This setup can be analyzed using ordinary supersymmetric field theory methods, where we find that gaugino condensation drives a deformation of the chiral ring which has no solutions. We expect this breaking to be a general feature of any theory of branes at a singularity with a smaller number of possible deformations than independent anomaly-free fractional branes.Comment: 32 pages, 6 figures, latex, v2: minor changes, refs adde

Serum osteoprotegerin in adolescent girls with anorexia nervosa

Low bone mineral density (BMD) in adolescents with anorexia nervosa (AN) is associated with a low bone turnover state. Osteoprotegerin (OPG), a cytokine that acts as a decoy receptor for receptor activator of nuclear factor-kappaB ligand, decreases bone resorption by inhibiting differentiation of osteoclast precursors and activation of mature osteoclasts, and by stimulating osteoclast apoptosis. We compared OPG levels in 43 adolescent girls with AN with 38 controls and examined bone density, bone turnover, and hormonal parameters. Girls with AN had lower fat mass, lean body mass, lumbar BMD z-scores, and lumbar bone mineral apparent density than controls. OPG levels were higher in girls with AN than in controls (44.5 +/- 22.5 pg/ml vs. 34.5 +/- 12.7 pg/ml, P = 0.02). Osteocalcin, deoxypyridinoline, estradiol, free testosterone, IGF-I, and leptin were lower in AN than in healthy adolescents. OPG values correlated negatively with body mass index (r = -0.27, P = 0.02), percent fat mass (r = -0.35, P = 0.0002), leptin (r = -0.28, P = 0.02), lumbar BMD z-scores (r = -0.25, P = 0.03), and lumbar bone mineral apparent density (r = -0.26, P = 0.03). In conclusion, adolescent girls with AN have higher serum OPG values than controls. OPG values correlate negatively with markers of nutritional status and lumbar bone density z-scores and may be a compensatory response to the bone loss seen in this population

Detection statistics in the micromaser

We present a general method for the derivation of various statistical quantities describing the detection of a beam of atoms emerging from a micromaser. The user of non-normalized conditioned density operators and a linear master equation for the dynamics between detection events is discussed as are the counting statistics, sequence statistics, and waiting time statistics. In particular, we derive expressions for the mean number of successive detections of atoms in one of any two orthogonal states of the two-level atom. We also derive expressions for the mean waiting times between detections. We show that the mean waiting times between de- tections of atoms in like states are equivalent to the mean waiting times calculated from the uncorrelated steady state detection rates, though like atoms are indeed correlated. The mean waiting times between detections of atoms in unlike states exhibit correlations. We evaluate the expressions for various detector efficiencies using numerical integration, reporting re- sults for the standard micromaser arrangement in which the cavity is pumped by excited atoms and the excitation levels of the emerging atoms are measured. In addition, the atomic inversion and the Fano-Mandel function for the detection of de-excited atoms is calculated for compari- son to the recent experimental results of Weidinger et al. [1], which reports the first observation of trapping states.Comment: 26 pages, 11 figure