Duration-dependent impact of cardiometabolic diseases and multimorbidity on all-cause and cause-specific mortality: a prospective cohort study of 0.5 million participants

Background The association of incident cardiometabolic multimorbidity (CMM) with mortality risk is rarely studied, and neither are the durations of cardiometabolic diseases (CMDs). Whether the association patterns of CMD durations with mortality change as individuals progress from one CMD to CMM is unclear. Methods Data from China Kadoorie Biobank of 512,720 participants aged 30–79 was used. CMM was defined as the simultaneous presence of two or more CMDs of interest, including diabetes, ischemic heart disease, and stroke. Cox regression was used to estimate the hazard ratios (HRs) and 95% confidence intervals (CIs) for the duration-dependent associations of CMDs and CMM with all-cause and cause-specific mortality. All information on exposures of interest was updated during follow-up. Results During a median follow-up of 12.1 years, 99,770 participants experienced at least one incident CMD, and 56,549 deaths were documented. Among 463,178 participants free of three CMDs at baseline, compared with no CMD during follow-up, the adjusted HRs (95% CIs) between CMM and all-cause mortality, mortality from circulatory system diseases, respiratory system diseases, cancer, and other causes were 2.93 (2.80–3.07), 5.05 (4.74–5.37), 2.72 (2.35–3.14), 1.30 (1.16–1.45), and 2.30 (2.02–2.61), respectively. All CMDs exhibited a high mortality risk in the first year of diagnosis. Subsequently, with prolonged disease duration, mortality risk increased for diabetes, decreased for IHD, and sustained at a high level for stroke. With the presence of CMM, the above association estimates inflated, but the pattern of which remained. Conclusion Among Chinese adults, mortality risk increased with the number of the CMDs and changed with prolonged disease duration, the patterns of which varied among the three CMDs

Exposure to the taste of alcohol elicits activation of the mesocorticolimbic neurocircuitry

A growing number of imaging studies suggest that alcohol cues, mainly visual, elicit activation in mesocorticolimbic structures. Such findings are consistent with the growing recognition that these structures play an important role in the attribution of incentive salience and the pathophysiology of addiction. The present study investigated whether the presentation of alcohol taste cues can activate brain regions putatively involved in the acquisition and expression of incentive salience. Using functional magnetic resonance imaging, we recorded BOLD activity while delivering alcoholic tastes to 37 heavy drinking but otherwise healthy volunteers. The results yielded a pattern of BOLD activity in mesocorticolimbic structures (ie prefrontal cortex, striatum, ventral tegmental area/substantia nigra) relative to an appetitive control. Further analyses suggested strong connectivity between these structures during cue-elicited urge and demonstrated significant positive correlations with a measure of alcohol use problems (ie the Alcohol Use Disorders Identification Test). Thus, repeated exposure to the taste alcohol in the scanner elicits activation in mesocorticolimbic structures, and this activation is related to measures of urge and severity of alcohol problems

Reduced neural tracking of prediction error in substance-dependent individuals

Objective: Substance-dependent individuals make poor decisions on the Iowa Gambling Task, a reward-related decisionmaking task that involves risk and uncertainty. Task performance depends on several factors, including how sensitive individuals are to feedback and how well they learn based on such feedback. A physiological signal that guides decision making based on feedback is prediction error. The authors investigated whether disruptions in the neural systems underlying prediction error processing in substance-dependent individuals could account for decision-making performance on a modified Iowa Gambling Task. Methods: Thirty-two substance-dependent individuals and 30 healthy comparison subjects played a modified version of the Iowa Gambling Task during MR scanning. Trial-totrial behavior and functional MRI (fMRI) blood-oxygen-level-dependent (BOLD) signal were analyzed using a computational model of prediction error based on internal expectancies. The authors investigated how well BOLD signal tracked prediction error in the striatum and the orbitofrontal cortex as well as over the whole brain in patients relative to comparison subjects

Relative importance of climatic variables, soil properties and plant traits to spatial variability in net CO2 exchange across global forests and grasslands

Compared to the well-known drivers of spatial variability in gross primary productivity (GPP), the relative importance of climatic variables, soil properties and plant traits to the spatial variability in net ecosystem exchange of CO2 between terrestrial ecosystem and atmosphere (NEE) is poorly understood. We used principal component regression to analyze data from 147 eddy flux sites to disentangle effects of climatic variables, soil properties and plant traits on the spatial variation in annual NEE and its components (GPP and ecosystem respiration (RE)) across global forests and grasslands. Our results showed that the largest unique contribution (proportion of variance only explained by one class of variables) to NEE variance came from climatic variables for forests (24%-30%) and soil properties for grasslands (41%-54%). Specifically, mean annual precipitation and potential evapotranspiration were the most important climatic variables driving forest NEE, whereas available soil water capacity, clay content and cation exchange capacity mainly influenced grassland NEE. Plant traits showed a small unique contribution to NEE in both forests and grasslands. However, leaf phosphorus content strongly interacted with soil total nitrogen density and clay content, and these combined factors represented a major contribution for grassland NEE. For GPP and RE, the majority of spatial variance was attributed to the common contribution of climate, soil and plant traits (50% - 62%, proportion of variance explained by more than one class of variables), rather than their unique contributions. Interestingly, those factors with only minor influences on GPP and RE variability (e.g., soil properties) have significant contributions to the spatial variability in NEE. Such emerging factors and the interactions between climatic variables, soil properties and plant traits are not well represented in current terrestrial biosphere models, which should be considered in future model improvement to accurately predict the spatial pattern of carbon cycling across forests and grasslands globally.Peer reviewe

Risky Decisions and Their Consequences: Neural Processing by Boys with Antisocial Substance Disorder

Adolescents with conduct and substance problems ("Antisocial Substance Disorder" (ASD)) repeatedly engage in risky antisocial and drug-using behaviors. We hypothesized that, during processing of risky decisions and resulting rewards and punishments, brain activation would differ between abstinent ASD boys and comparison boys.We compared 20 abstinent adolescent male patients in treatment for ASD with 20 community controls, examining rapid event-related blood-oxygen-level-dependent (BOLD) responses during functional magnetic resonance imaging. In 90 decision trials participants chose to make either a cautious response that earned one cent, or a risky response that would either gain 5 cents or lose 10 cents; odds of losing increased as the game progressed. We also examined those times when subjects experienced wins, or separately losses, from their risky choices. We contrasted decision trials against very similar comparison trials requiring no decisions, using whole-brain BOLD-response analyses of group differences, corrected for multiple comparisons. During decision-making ASD boys showed hypoactivation in numerous brain regions robustly activated by controls, including orbitofrontal and dorsolateral prefrontal cortices, anterior cingulate, basal ganglia, insula, amygdala, hippocampus, and cerebellum. While experiencing wins, ASD boys had significantly less activity than controls in anterior cingulate, temporal regions, and cerebellum, with more activity nowhere. During losses ASD boys had significantly more activity than controls in orbitofrontal cortex, dorsolateral prefrontal cortex, brain stem, and cerebellum, with less activity nowhere.Adolescent boys with ASD had extensive neural hypoactivity during risky decision-making, coupled with decreased activity during reward and increased activity during loss. These neural patterns may underlie the dangerous, excessive, sustained risk-taking of such boys. The findings suggest that the dysphoria, reward insensitivity, and suppressed neural activity observed among older addicted persons also characterize youths early in the development of substance use disorders

Enhancing the Detection of BOLD Signal in fMRI by Reducing the Partial Volume Effect

Purpose. To investigate the advantages of reducing the partial volume effect (PVE) to enhance the detection of the BOLD signal in fMRI. Methods. A linear phase term was added in k-space to obtain half-voxel shifting of 64 × 64 T2*-weighted echo-planar images. Three sets of image data shifted in the x, y, and diagonal direction, respectively, are combined with the original 64 × 64 data to form the 128 × 128 voxel-shifted interpolated data. Results. A simulation of a synthetic fMRI dataset shows that the voxel-shifted interpolation (VSI) can increase the t-score up to 50% in single-voxel activations. An fMRI study (n=7) demonstrates that 20.4% of the interpolated voxels have higher t-scores than their nearest neighboring voxels in the original maps. The average increase of the t-score in these interpolated voxels is 13.3%. Conclusion. VSI yields increased sensitivity in detecting voxel-size BOLD activations, improved spatial accuracy of activated regions, and improved detection of the peak BOLD signal of an activated region. VSI can potentially be used as an alternative to the high-resolution fMRI studies in which reduction in SNR and increase in imaging time become prohibitive

Reduction of Scan Time and Echo Time in 3D Time-of-Flight (TOF) MR Angiography, Using Reverse Elliptical Centric Dual-Echo Acquisition

In the conventional single-echo three dimension (3D) time-of-flight (TOF) magnetic resonance angiography (MRA), it always takes long scan time to obtain the good images. In addition, high-resolution MRA with flow compensation requires long echo time (TE). Here, a reverse elliptical centric dual-echo 3D TOF MRA pulse sequence was developed to reduce the scan time and minimize the effective TE. Dual-echo and reverse elliptical centric acquisition in the phase encoding and slice phase encoding direction were used to reduce the scan time by 61%. Furthermore, the effective echo time (TE) was also minimized from 4.8ms to 4.1ms. The developed pulse sequence was tested on clinical MRI systems and the contrast to noise ratio (CNR) was measured to evaluate the results. The results show that the CNR only decrease by 2.5% with the scan time reduced to 39% when compared with the conventional single-echo 3D TOF. Compared with the conventional dual-echo 3D TOF acquisition, the developed pulse sequence brings advantages in three aspects: (1) reduce scan time by 22%; (2) increase CNR by 10%; (3) reduce the artifacts induced by dual-echo effects. In addition, while keeping the similar scan time as the conventional single-echo 3D TOF acquisition, the results show that reverse elliptical centric dual-echo 3D TOF acquisition increase CNR by 54.3%

Background-Suppressed MR Venography of the Brain Using Magnitude Data: A High-Pass Filtering Approach

Conventional susceptibility-weighted imaging (SWI) uses both phase and magnitude data for the enhancement of venous vasculature and, thus, is subject to signal loss in regions with severe field inhomogeneity and in the peripheral regions of the brain in the minimum-intensity projection. The purpose of this study is to enhance the visibility of the venous vasculature and reduce the artifacts in the venography by suppressing the background signal in postprocessing. A high-pass filter with an inverted Hamming window or an inverted Fermi window was applied to the Fourier domain of the magnitude images to enhance the visibility of the venous vasculature in the brain after data acquisition. The high-pass filtering approach has the advantages of enhancing the visibility of small veins, diminishing the off-resonance artifact, reducing signal loss in the peripheral regions of the brain in projection, and nearly completely suppressing the background signal. The proposed postprocessing technique is effective for the visualization of small venous vasculature using the magnitude data alone

Application of SVD-based sparsity in compressed sensing susceptibility weighted imaging

Long scan time has hampered susceptibility weighted imaging (SWI) in routine clinical application to diagnose brain diseases related to venous vasculature. Compressed sensing (CS) was demonstrated to significantly reduce scan time of SWI by exploiting signal sparsity in wavelet domain. However the reconstruction time of CS based on wavelet sparsity is usually time consuming. In this study, the feasibility of applying CS in SWI with singular value decomposition (SVD)-based sparsity basis was investigated. It was found that CS reconstruction based on SVD sparsity basis can achieve reasonably high computing speed than that of wavelet-based sparsity basis, while still achieving accurate image reconstruction