Cardiac vagal activity changes moderated the association of cognitive and cerebral hemodynamic variations in the prefrontal cortex.

Phasic cardiac vagal activity (CVA), reflecting ongoing, moment-to-moment psychophysiological adaptations to environmental changes, can serve as a predictor of individual difference in executive function, particularly executive performance. However, the relationship between phasic CVA and executive function demands requires further validation because of previous inconsistent findings. Moreover, it remains unclear what types of phasic changes of CVA may be adaptive in response to heightened executive demands. This study used the standard N-back task to induce different levels of working memory (WM) load and combined functional Near-Infrared Spectroscopy (fNIRS) with a multipurpose polygraph to investigate the variations of CVA and its interactions with cognitive and prefrontal responses as executive demands increased in fifty-two healthy young subjects. Our results showed phasic decreases in CVA as WM load increased (t (51) = -3.758, p < 0.001, Cohen's d = 0.526). Furthermore, phasic changes of CVA elicited by increased executive demands moderated the association of cognitive and cerebral hemodynamic variations in the prefrontal cortex (B = 0.038, SE = 0.014, p < 0.05). Specifically, as executive demands increased, individuals with larger phasic CVA withdrawal showed a positive relationship between cognitive and hemodynamic variations in the prefrontal cortex (ß = 0.281, p = 0.031). No such significant relationship was observed in individuals with smaller phasic CVA withdrawal. The current findings demonstrate a decrease in CVA with increasing executive demands and provide empirical support for the notion that a larger phasic CVA withdrawal can be considered adaptive in situations requiring high executive function demands.

Unraveling how the adolescent brain deals with criticism using dynamic causal modeling.

Sensitivity to criticism, which can be defined as a negative evaluation that a person receives from someone else, is considered a risk factor for the development of psychiatric disorders in adolescents. They may be more vulnerable to social evaluation than adults and exhibit more inadequate emotion regulation strategies such as rumination. The neural network involved in dealing with criticism in adolescents may serve as a biomarker for vulnerability to depression. However, the directions of the functional interactions between the brain regions within this neural network in adolescents are still unclear. In this study, 64 healthy adolescents (aged 14 to 17 years) were asked to listen to a series of self-referential auditory segments, which included negative (critical), positive (praising), and neutral conditions, during fMRI scanning. Dynamic Causal Modeling (DCM) with Parametric Empirical Bayesian (PEB) analysis was performed to map the interactions within the neural network that was engaged during the processing of these segments. Three regions were identified to form the interaction network: the left pregenual anterior cingulate cortex (pgACC), the left dorsolateral prefrontal cortex (DLPFC), and the right precuneus (preCUN). We quantified the modulatory effects of exposure to criticism and praise on the effective connectivity between these brain regions. Being criticized was found to significantly inhibit the effective connectivity from the preCUN to the DLPFC. Adolescents who scored high on the Perceived Criticism Measure (PCM) showed less inhibition of the preCUN-to-DLPFC connectivity when being criticized, which may indicate that they required more engagement of the Central Executive Network (which includes the DLPFC) to sufficiently disengage from negative self-referential processing. Furthermore, the inhibitory connectivity from the DLPFC to the pgACC was strengthened by exposure to praise as well as criticism, suggesting a recruitment of cognitive control over emotional responses when dealing with positive and negative evaluative feedback. Our novel findings contribute to a more profound understanding of how criticism affects the adolescent brain and can help to identify potential biomarkers for vulnerability to develop mood disorders before or during adulthood.

Lateralized subgenual ACC metabolic connectivity patterns in refractory melancholic depression: does it matter?

Although treatment resistance to antidepressant pharmacotherapy is quite common, the phenomenon of refractory major depressive disorder (rMDD) is not well understood. Nevertheless, the metabolic activity of the subgenual anterior cingulate cortex (sgACC) has been put forward as a possible metabolic biomarker of clinical prediction and response, albeit sgACC lateralization differences in functional connectivity have not yet been extensively examined. Also not in the refractory depressed state. To examine sgACC lateralization differences in metabolic connectivity, we recruited 43 right-handed antidepressant-free unipolar melancholic rMDD patients and 32 right-handed healthy controls to participate in this 18FDG PET study and developed a searchlight-based interregional covariance connectivity approach. Compared to non-depressed individuals, sgACC covariance analysis showed stronger metabolic connections with frontolimbic brain regions known to be affected in the depressed state. Furthermore, whereas the left sgACC showed stronger metabolic connections with ventromedial prefrontal cortical regions, implicated in anhedonia, suicidal ideation, and self-referential processes, the right sgACC showed significantly stronger metabolic connections with posterior hippocampal and cerebellar regions, respectively specialized in memory and social processing. Overall, our results substantiate earlier research that the sgACC is a metabolic key player when clinically depressed and that distinct lateralized sgACC metabolic connectivity patterns are present.

Spatiotemporal topological correspondence between blood oxygenation and glucose metabolism revealed by simultaneous fPET-fMRI in brain's white matter.

White matter (WM) makes up half of the human brain. Compelling functional MRI evidence indicates that white matter exhibits neural activation and synchronization via a hemodynamic window. However, the neurometabolic underpinnings of white matter temporal synchronization and spatial topology remain unknown. By leveraging concurrent [18F]FDG-fPET and blood-oxygenation-level-dependent-fMRI, we demonstrated the temporal and spatial correspondences between blood oxygenation and glucose metabolism in the human brain white matter. In the temporal scale, we found that blood-oxygenation-level-dependent signals shared mutual information with FDG signals in the default-mode, visual, and sensorimotor-auditory networks. For spatial distribution, the blood-oxygenation-level-dependent functional networks in white matter were accompanied by substantial correspondence of FDG functional connectivity at different topological scales, including degree centrality and global gradients. Furthermore, the content of blood-oxygenation-level-dependent fluctuations in the white matter default-mode network was aligned and liberal with the FDG graph, suggesting the freedom of default-mode network neuro-dynamics, but the constraint by metabolic dynamics. Moreover, the dissociation of the functional gradient between blood-oxygenation-level-dependent and FDG connectivity specific to the white matter default-mode network revealed functional heterogeneities. Together, the results showed that brain energy metabolism was closely coupled with blood oxygenation in white matter. Comprehensive and complementary information from fMRI and fPET might therefore help decode brain white matter functions.

Solid-State Nanopore Distinguishes Ferritin and Apo-Ferritin with Identical Exteriors through Amplified Flexibility at Single-Molecule Level.

Protein identification and discrimination at the single-molecule level are big challenges. Solid-state nanopores as a sensitive biosensor have been used for protein analysis, although it is difficult to discriminate proteins with similar structures in the traditional discrimination method based on the current blockage fraction. Here, we select ferritin and apo-ferritin as the model proteins that exhibit identical exterior and different interior structures and verify the practicability of their discrimination with flexibility features by the strategy of gradually decreasing the nanopore size. We show that the larger nanopore (relative to the protein size) has no obvious effect on discriminating two proteins. Then, the comparable-sized nanopore plays a key role in discriminating two proteins based on the dwell time and fraction distribution, and the conformational changes of both proteins are also studied with this nanopore. Finally, in the smaller nanopore, the protein molecules are trapped rather than translocated, where two proteins are obviously discriminated through the current fluctuation caused by the vibration of proteins. This strategy has potential in the discrimination of other important similar proteins.

Precision targeting in prediction for rTMS clinical outcome in depression: what about sgACC lateralization, metabolic connectivity, and the potential role of the cerebellum?

Predicting clinical response to repetitive transcranial magnetic stimulation (rTMS) in medication-resistant depression (MRD) has gained great importance in recent years. Mainly, the right subgenual anterior cingulate cortex (sgACC) functional connectivity has been put forward as biomarker in relation to rTMS clinical outcome. Even though the left and right sgACC may have different neurobiological functions, little is known about the possible lateralized predictive role of the sgACC in rTMS clinical outcome. In 43 right-handed antidepressant-free MRD patients, we applied a searchlight-based interregional covariance connectivity approach using the baseline 18FDG-PET scan-collected from two previous high-frequency (HF)-rTMS treatment studies delivering stimulation to the left dorsolateral prefrontal cortex (DLPFC)-and investigated whether unilateral or bilateral sgACC glucose metabolism at baseline would result in different predictive metabolic connectivity patterns. Regardless of sgACC lateralization, the weaker the sgACC seed-based baseline metabolic functional connections with the (left anterior) cerebellar areas, the significantly better the clinical outcome. However, the seed diameter seems to be crucial. Similar significant findings on sgACC metabolic connectivity with the left anterior cerebellum, also unrelated to sgACC lateralization, in relation to clinical outcome were observed when using the HCPex atlas. Although we could not substantiate that specifically right sgACC metabolic connectivity would predict HF-rTMS clinical outcome, our findings suggest considering the entire sgACC in functional connectivity predictions. Given that the interregional covariance connectivity results were significant only when using the Beck Depression Inventory (BDI-II) and not with the Hamilton Depression Rating Scale (HDRS), our sgACC metabolic connectivity observations also suggest the possible involvement of the (left) anterior cerebellum involved in higher-order cognitive processing as part of this predictive value.

The moderating effect of resting heart rate variability on the relationship between internet addiction tendency and brain morphology.

Previous neuroimaging studies have investigated brain morphology associated with internet addiction tendency (IAT) in healthy subjects. However, whether resting vagally-mediated heart rate variability (HRV) exerting influences on the association of IAT and brain morphology remains unclear. This study used voxel-based morphometry (VBM) and multiple regression analyses to assess the interaction effect of IAT and resting vagally-mediated HRV on regional grey matter volumes in 82 healthy subjects. To further illustrate the observed interaction effect, the moderated hierarchical regression analysis was performed. The results showed that resting vagally-mediated HRV moderated the relationship between IAT scores and grey matter volume (GMV) in the precuneus and cerebellum. Specifically, individuals with higher resting vagally-mediated HRV showed a significant positive relationship between IAT scores and GMV in the precuneus, whereas individuals with lower resting vagally-mediated HRV showed a significant negative relationship between IAT scores and GMV in the precuneus. In addition, IAT scores were negatively correlated with GMV in the cerebellum among individuals with lower resting vagally-mediated HRV, but not among individuals with higher resting vagally-mediated HRV. These findings have demonstrated a moderating role of resting vagally-mediated HRV on the association of IAT and brain morphology.

Brainstem glucose metabolism predicts reward dependence scores in treatment-resistant major depression.

BACKGROUND: It has been suggested that individual differences in temperament could be involved in the (non-)response to antidepressant (AD) treatment. However, how neurobiological processes such as brain glucose metabolism may relate to personality features in the treatment-resistant depressed (TRD) state remains largely unclear. METHODS: To examine how brainstem metabolism in the TRD state may predict Cloninger's temperament dimensions Harm Avoidance (HA), Novelty Seeking (NS), and Reward Dependence (RD), we collected 18fluorodeoxyglucose positron emission tomography (18FDG PET) scans in 40 AD-free TRD patients. All participants were assessed with the Temperament and Character Inventory (TCI). We applied a multiple kernel learning (MKL) regression to predict the HA, NS, and RD from brainstem metabolic activity, the origin of respectively serotonergic, dopaminergic, and noradrenergic neurotransmitter (NT) systems. RESULTS: The MKL model was able to significantly predict RD but not HA and NS from the brainstem metabolic activity. The MKL pattern regression model identified increased metabolic activity in the pontine nuclei and locus coeruleus, the medial reticular formation, the dorsal/median raphe, and the ventral tegmental area that contributed to the predictions of RD. CONCLUSIONS: The MKL algorithm identified a likely metabolic marker in the brainstem for RD in major depression. Although 18FDG PET does not investigate specific NT systems, the predictive value of brainstem glucose metabolism on RD scores however indicates that this temperament dimension in the TRD state could be mediated by different monoaminergic systems, all involved in higher order reward-related behavior.

rsHRF: A toolbox for resting-state HRF estimation and deconvolution.

The hemodynamic response function (HRF) greatly influences the intra- and inter-subject variability of brain activation and connectivity, and might confound the estimation of temporal precedence in connectivity analyses, making its estimation necessary for a correct interpretation of neuroimaging studies. Additionally, the HRF shape itself is a useful local measure. However, most algorithms for HRF estimation are specific for task-related fMRI data, and only a few can be directly applied to resting-state protocols. Here we introduce rsHRF, a Matlab and Python toolbox that implements HRF estimation and deconvolution from the resting-state BOLD signal. We first provide an overview of the main algorithm, practical implementations, and then demonstrate the feasibility and usefulness of rsHRF by validation experiments with a publicly available resting-state fMRI dataset. We also provide tools for statistical analyses and visualization. We believe that this toolbox may significantly contribute to a better analysis and understanding of the components and variability of BOLD signals.

Dynamic brain connectome and high risk of mental problem in clinical nurses.

With the growing population and rapid change in the social environment, nurses in China are suffering from high rates of stress; however, the neural mechanism underlying this occupation related stress is largely unknown. In this study, mental status was determined for 81 nurses and 61 controls using the Symptom Checklist 90 (SCL-90) scale. A subgroup (n = 57) was further scanned by resting-state functional MRI with two sessions. Based on the SCL-90 scale, "somatic complaints" and "diet/sleeping" exhibited the most prominent difference between nurses and controls. This mental health change in nurses was further supported by the spatial independent component analysis on functional MRI data. First, dynamic functional connectome analysis identified two discrete connectivity configurations (States I and II). Controls had more time in the State I than II, while the nurses had more time in the State II than I. Second, nurses showed a similar static network topology as controls, but altered dynamic properties. Third, the symptom-imaging correlation analysis suggested the functional alterations in nurses as potential imaging biomarkers indicating a high risk for "diet/sleeping" problems. In summary, this study emphasized the high risk of mental deficits in nurses and explored the underlying neural mechanism using dynamic brain connectome, which provided valuable information for future psychological intervention.

Hostility in medication-resistant major depression and comorbid generalized anxiety disorder is related to increased hippocampal-amygdala 5-HT2A receptor density.

Major depressive disorder (MDD) and generalized anxiety disorder (GAD) are severe and difficult-to-treat psychiatric illnesses with high rates of comorbidity. Although both disorders are treated with serotonergic based psychotropic agents, little is known on the influence of the serotonergic neurotransmitter system on the occurrence of comorbid GAD when clinically depressed. To investigate this poorly understood clinical question, we examined the involvement of frontolimbic post-synaptic 5-HT2A receptors in 20 medication-resistant depressed (MRD) patients with half of them diagnosed with comorbid GAD with 123I-5-I-R91150 SPECT. To explore whether 5-HT2A receptor-binding indices (BI) associated with comorbid GAD could be related to distinct psychopathological symptoms, all were assessed with the symptom Checklist-90-Revised (SCL-90-R). MRD patients with comorbid GAD displayed significantly higher 5-HT2A receptor BI in the hippocampal-amygdala complex, compared to MRD patients without GAD. Correlation analyses revealed that the 5-HT2A receptor BI in these areas were significantly related to the SCL-90-R subscale hostility (HOS), especially for those MRD patients with comorbid GAD. Comorbid MRD-GAD may be characterized with increased hippocampal-amygdala 5-HT2A receptor BI which could represent enhanced levels in hostility in such kinds of patients. Adapted psychotherapeutic interventions may be warranted.

Baseline functional connectivity may predict placebo responses to accelerated rTMS treatment in major depression.

Although in theory sham repetitive transcranial magnetic stimulation (rTMS) has no inherent therapeutic value, nonetheless, such placebo stimulations may have relevant therapeutic effects in clinically depressed patients. On the other hand, antidepressant responses to sham rTMS are quite heterogeneous across individuals and its neural underpinnings have not been explored yet. The current brain imaging study aims to detect baseline neural fingerprints resulting in clinically beneficial placebo rTMS treatment responses. We collected resting-state functional magnetic resonance imaging data prior to a registered randomized clinical trial of accelerated placebo stimulation protocol in patients documented with treatment-resistant depression (http://clinicaltrials.gov/show/NCT01832805). In addition to global brain connectivity and rostral anterior cingulate cortex (rACC) seed-based functional connectivity (FC), elastic-net regression and cross-validation procedures were used to identify baseline intrinsic brain connectivity biomarkers for sham-rTMS responses. Placebo responses to accelerated sham rTMS were correlated with baseline global brain connectivity in the rACC/ventral medial prefrontal cortex (vmPFC). Concerning the rACC seed-based FC analysis, the placebo response was associated positively with the precuneus/posterior cingulate (PCun/PCC) cortex and negatively with the middle frontal gyrus. Our findings provide first brain imaging evidence for placebo responses to sham stimulation being predictable from rACC rsFC profiles, especially in brain areas implicated in (re)appraisal and self-focus processes.

Modulation of the spontaneous hemodynamic response function across levels of consciousness.

Functional imaging research has already contributed with several results to the study of neural correlates of consciousness. Apart from task-related activation derived in fMRI, PET based glucose metabolism rate or cerebral blood flow account for a considerable proportion of the study of brain activity under different levels of consciousness. Resting state functional connectivity MRI is playing a crucial role to explore the consciousness related functional integration, successfully complementing PET, another widely used neuroimaging technique. Here, spontaneous hemodynamic response is introduced to characterize resting state brain activity giving information on the local metabolism (neurovascular coupling), and useful to improve the time-resolved activity and connectivity measures based on BOLD fMRI. This voxel-wise measure is then used to investigate the loss of consciousness under Propofol anesthesia and unresponsive wakefulness syndrome. Changes in the hemodynamic response in precuneus and posterior cingulate are found to be a common principle underlying loss of consciousness in both conditions. The thalamus appears to be less obviously modulated by Propofol, compared with frontoparietal regions. However, a significant increase in spontaneous thalamic hemodynamic response was found in patients in unresponsive wakefulness syndrome compared with healthy controls. Our results ultimately show that anesthesia- or pathology-induced neurovascular coupling could be tracked by modulated spontaneous hemodynamic response derived from resting state fMRI.

Ultralow-Content Iron-Decorated Ni-MOF-74 Fabricated by a Metal-Organic Framework Surface Reaction for Efficient Electrocatalytic Water Oxidation.

Transition-metal-organic frameworks (MOFs) have been regarded as one of the most intriguing electrocatalysts because of its low cost and diversity in functional organic groups and metal centers. Different from the common strategies of tuning the ratio of metal centers in multivariate MOFs, here, ultralow-content Fe2O3 is decorated on the surface of monometallic Ni-MOF-74 based on the fast "phenol-iron (Fe)" surface reaction between Fe2+ and the surface hydroxyl group in Ni-MOF-74. Benefiting from this flexible method, the Fe loading can be finely modulated and thus a series of Fe-decorated Ni-MOF-74 with different Fe contents are prepared. The optimized 0.6 wt % Fe2O3@Ni-MOF-74 with the Fe loading of 0.6 wt % only needs the overpotential of 264 mV to deliver 10 mA cm-2, which obviously outperforms Fe-free Ni-MOF-74 (323 mV) and other Fe2O3@Ni-MOF-74 and is even superior to the commercial IrO2 benchmark (300 mV). X-ray photoelectron spectroscopy results disclose that Fe decoration can obviously modulate the electronic structure of Ni center in Ni-MOF-74, thereby resulting in enhanced oxygen evolution reaction activity. This work opens up a new avenue to fabricate excellent MOF-based electrocatalysts for direct utilization in an electrocatalytic process.

Grey Matter Volumes in the Executive Attention System Predict Individual Differences in Effortful Control in Young Adults.

Effortful control (EC), considered as one component of temperament, describes an individual's capacity for self-regulation. Previous neuroimaging studies have provided convergent evidence that individual differences in EC are determined by the functioning of neural systems subserving executive attention, primarily comprising the anterior cingulate cortex (ACC) and the lateral prefrontal cortex (PFC). Notwithstanding, as previous neuroimaging findings highlighted the structural neural bases of EC in adolescence, during which the PFC is prominently remodeled, the underlying neuroanatomical substrates of EC remain uncertain in young adults. In this study, we included 246 healthy young adults and used voxel-based morphometry analysis to investigate the relationship between EC and grey matter (GM) volumes. Additionally, permutation testing and cross-validation were applied to determine whether GM volumes in the detected regions could predict individual differences in EC. Our results revealed that EC was associated with GM volumes in the dorsal anterior cingulate cortex (dACC) and the pre-supplementary motor area (pre-SMA), demonstrating that these two regions may play a crucial role in EC. Furthermore, the identified regional GM volumes reliably contribute to the prediction of EC confirmed by cross-validation. Overall, these findings provide further evidence for the involvement of the executive attention system in EC, and shed more light on the neuroanatomical substrates of EC in young adulthood.

One MRI-compatible tDCS session attenuates ventromedial cortical perfusion when exposed to verbal criticism: The role of perceived criticism.

Transcranial direct current stimulation (tDCS) is a potential treatment strategy for mood and anxiety disorders, but how this application may influence emotional processes, and whether this is related to individual characteristics, is not well understood. It has been proposed that perceived criticism (PC) may represent a vulnerability factor for the development of such mental illnesses. To decipher whether neural mechanisms of action of tDCS potentially differ depending on PC status (low vs. high), we evaluated mood and brain perfusion before and after applying MRI-compatible tDCS, and after participants were exposed to verbal criticism in the scanner. Experimental design 30 healthy nondepressed females were included in a sham-controlled crossover MRI-compatible tDCS study. Brain perfusion was measured by means of arterial spin labeling (ASL) before and after tDCS applied to the left dorsolateral prefrontal cortex (DLPFC), and after hearing criticism. Before the experiment, all participants provided a rating of PC in their closest environment. Principal observations at the behavioral level, criticism made participants angrier. This was unrelated to the active or sham stimulation. After being criticized, females scoring high on PC had significantly decreased brain perfusion in the pregenual anterior cingulate cortex (pgACC) and medioprefrontal cortex (mPFC), after active tDCS but not sham. The decrease in pgACC/mPFC perfusion points to a significant impact of tDCS in brain areas related to stress responses and self-referential processes, especially in females scoring high on PC, which has been shown to be related to vulnerability for mood and anxiety disorders.

Hemodynamic response function (HRF) variability confounds resting-state fMRI functional connectivity.

PURPOSE: fMRI is the convolution of the hemodynamic response function (HRF) and unmeasured neural activity. HRF variability (HRFv) across the brain could, in principle, alter functional connectivity (FC) estimates from resting-state fMRI (rs-fMRI). Given that HRFv is driven by both neural and non-neural factors, it is problematic when it confounds FC. However, this aspect has remained largely unexplored even though FC studies have grown exponentially. We hypothesized that HRFv confounds FC estimates in the brain's default-mode-network. METHODS: We tested this hypothesis using both simulations (where the ground truth is known and modulated) as well as rs-fMRI data obtained in a 7T MRI scanner (N = 47, healthy). FC was obtained using 2 pipelines: data with hemodynamic deconvolution (DC) to estimate the HRF and minimize HRFv, and data with no deconvolution (NDC, HRFv-ignored). DC and NDC FC networks were compared, along with regional HRF differences, revealing potential false connectivities that resulted from HRFv. RESULTS: We found evidence supporting our hypothesis using both simulations and experimental data. With simulations, we found that HRFv could cause a change of up to 50% in FC. With rs-fMRI, several potential false connectivities attributable to HRFv, with majority connections being between different lobes, were identified. We found a double exponential relationship between the magnitude of HRFv and its impact on FC, with a mean/median error of 30.5/11.5% caused in FC by HRF confounds. CONCLUSION: HRFv, if ignored, could cause identification of false FC. FC findings from HRFv-ignored data should be interpreted cautiously. We suggest deconvolution to minimize HRFv.

Point-Process Deconvolution of fMRI BOLD Signal Reveals Effective Connectivity Alterations in Chronic Pain Patients.

It is now recognized that important information can be extracted from the brain spontaneous activity, as exposed by recent analysis using a repertoire of computational methods. In this context a novel method, based on a blind deconvolution technique, is used to analyze potential changes due to chronic pain in the brain pain matrix's effective connectivity. The approach is able to deconvolve the hemodynamic response function from spontaneous neural events, i.e., in the absence of explicit onset timings, and to evaluate information transfer between two regions as a joint probability of the occurrence of such spontaneous events. The method revealed that the chronic pain patients exhibit important changes in the insula's effective connectivity which can be relevant to understand the overall impact of chronic pain on brain function.

Long-term clinical outcomes of statin use for chronic heart failure: a meta-analysis of 15 prospective studies.

BACKGROUND: The effect of statin treatment on the long-term prognosis in patients with chronic heart failure (CHF) remains uncertain. This study aimed to answer the question by a meta-analysis. METHODS: The Cochrane databases, MEDLINE and EMBASE, were systematically searched. The eligibility of prospective studies that assigned CHF patients to receive statin treatment and a control (no statin treatment), had defined prognostic outcomes as primary endpoint, and had a minimal follow-up of 12 months was determined. RESULTS: Fifteen studies involving 45,110 patients were included in the analysis. Additional statin treatment was associated with reduced all-cause mortality (risk ratios [RR] = 0.71, 95% confidence intervals [CI] 0.61-0.83) and reduced rehospitalisation rate for heart failure (RR = 0.84, 95% CI 0.74-0.96). Statin treatment, however, had little impact on pump failure mortality, cardiovascular mortality, and sudden cardiac death. Atorvastatin treatment appeared to facilitate to reduce all-cause mortality (lnRR = 0.61, p = 0.05) and rehospitalisation for heart failure (lnRR = 0.44, p = 0.04) compared with non-atorvastatin therapy. CONCLUSIONS: Based on the available data, statins persistently decreased all-cause mortality and the incidence of rehospitalisation for heart failure in CHF patients, and the benefits might be partially associated with use of specific statin.

Shared and distinctive brain networks underlying trait and state rumination.

Although trait and state rumination play a central role in the exacerbation of negative affect, evidence suggests that they are weakly correlated and exert distinct influences on emotional reactivity to stressors. Whether trait and state rumination share a common or exhibit distinct neural substrate remains unclear. In this study, we utilized functional near-infrared spectroscopy (fNIRS) combined with connectome-based predictive modeling (CPM) to identify neural fingerprints associated with trait and state rumination. CPM identified distinctive functional connectivity (FC) profiles that contribute to the prediction of trait rumination, primarily involving FC within the default mode network (DMN) and the dorsal attention network (DAN) as well as FC between the DMN, control network (CN), DAN, and salience network (SN). Conversely, state rumination was predominantly associated with FC between the DMN and CN. Furthermore, the predictive features of trait rumination can be robustly generalized to predict state rumination, and vice versa. In conclusion, this study illuminates the importance of both DMN and non-DMN systems in the emergence and persistence of rumination. While trait rumination was associated with stronger and broader FC than state rumination, the generalizability of the predictive features underscores the presence of shared neural mechanisms between the two forms of rumination. These identified connectivity fingerprints may hold promise as targets for innovative therapeutic interventions aimed at mitigating rumination-related negative affect.