A Metabolite Specific 3D Stack-of-Spiral bSSFP Sequence for Improved Lactate Imaging in Hyperpolarized [1-13^{13}C]Pyruvate Studies on a 3T Clinical Scanner

Purpose: The balanced steady-state free precession sequence has been previously explored to improve the efficient use of non-recoverable hyperpolarized $^{13}$C magnetization, but suffers from poor spectral selectivity and long acquisition time. The purpose of this study was to develop a novel metabolite-specific 3D bSSFP ("MS-3DSSFP") sequence with stack-of-spiral readouts for improved lactate imaging in hyperpolarized [1-$^{13}$C]pyruvate studies on a clinical 3T scanner. Methods: Simulations were performed to evaluate the spectral response of the MS-3DSSFP sequence. Thermal $^{13}$C phantom experiments were performed to validate the MS-3DSSFP sequence. In vivo hyperpolarized [1-$^{13}$C]pyruvate studies were performed to compare the MS-3DSSFP sequence with metabolite specific gradient echo ("MS-GRE") sequences for lactate imaging. Results: Simulations, phantom and in vivo studies demonstrate that the MS-3DSSFP sequence achieved spectrally selective excitation on lactate while minimally perturbing other metabolites. Compared with MS-GRE sequences, the MS-3DSSFP sequence showed approximately a 2.5-fold SNR improvement for lactate imaging in rat kidneys, prostate tumors in a mouse model and human kidneys. Conclusions: Improved lactate imaging using the MS-3DSSFP sequence in hyperpolarized [1-$^{13}$C]pyruvate studies was demonstrated in animals and humans. The MS-3DSSFP sequence could be applied for other clinical applications such as in the brain or adapted for imaging other metabolites such as pyruvate and bicarbonate

Effect of anticholinergic medication on positive and negative symptoms in medication-free schizophrenic patients

It is generally assumed that anticholinergic drugs have no effects on schizophrenic symptomatology. A few studies, however, indicate that anticholinergic agents aggravate psychotic symptoms and antagonize therapeutic effects of neuroleptics in schizophrenic patients; more recently, some investigators have observed that these agents appear to benefit negative symptoms. In an effort to resolve this issue, we studied the effects of 2 days of treatment with biperiden on positive and negative symptoms in 15 medication-free schizophrenic patients. Positive symptoms increased significantly, while there was a trend toward a decrease in negative symptoms. The implications of these findings for the role of the cholinergic system in schizophrenia are discussed.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/28707/1/0000527.pd

Machine learning uncovers the most robust self-report predictors of relationship quality across 43 longitudinal couples studies

Given the powerful implications of relationship quality for health and well-being, a central mission of relationship science is explaining why some romantic relationships thrive more than others. This large-scale project used machine learning (i.e., Random Forests) to 1) quantify the extent to which relationship quality is predictable and 2) identify which constructs reliably predict relationship quality. Across 43 dyadic longitudinal datasets from 29 laboratories, the top relationship-specific predictors of relationship quality were perceived-partner commitment, appreciation, sexual satisfaction, perceived-partner satisfaction, and conflict. The top individual-difference predictors were life satisfaction, negative affect, depression, attachment avoidance, and attachment anxiety. Overall, relationship-specific variables predicted up to 45% of variance at baseline, and up to 18% of variance at the end of each study. Individual differences also performed well (21% and 12%, respectively). Actor-reported variables (i.e., own relationship-specific and individual-difference variables) predicted two to four times more variance than partner-reported variables (i.e., the partner’s ratings on those variables). Importantly, individual differences and partner reports had no predictive effects beyond actor-reported relationship-specific variables alone. These findings imply that the sum of all individual differences and partner experiences exert their influence on relationship quality via a person’s own relationship-specific experiences, and effects due to moderation by individual differences and moderation by partner-reports may be quite small. Finally, relationship-quality change (i.e., increases or decreases in relationship quality over the course of a study) was largely unpredictable from any combination of self-report variables. This collective effort should guide future models of relationships