Intracranial electrophysiological and structural basis of BOLD functional connectivity in human brain white matter.

While functional MRI (fMRI) studies have mainly focused on gray matter, recent studies have consistently found that blood-oxygenation-level-dependent (BOLD) signals can be reliably detected in white matter, and functional connectivity (FC) has been organized into distributed networks in white matter. Nevertheless, it remains unclear whether this white matter FC reflects underlying electrophysiological synchronization. To address this question, we employ intracranial stereotactic-electroencephalography (SEEG) and resting-state fMRI data from a group of 16 patients with drug-resistant epilepsy. We find that BOLD FC is correlated with SEEG FC in white matter, and this result is consistent across a wide range of frequency bands for each participant. By including diffusion spectrum imaging data, we also find that white matter FC from both SEEG and fMRI are correlated with white matter structural connectivity, suggesting that anatomical fiber tracts underlie the functional synchronization in white matter. These results provide evidence for the electrophysiological and structural basis of white matter BOLD FC, which could be a potential biomarker for psychiatric and neurological disorders.

Functional connectivity dynamics as a function of the fluctuation of tension during film watching.

To advance the understanding of the dynamic relationship between brain activities and emotional experiences, we examined the neural patterns of tension, a unique emotion that highly depends on how an event unfolds. Specifically, the present study explored the temporal relationship between functional connectivity patterns within and between different brain functional modules and the fluctuation in tension during film watching. Due to the highly contextualized and time-varying nature of tension, we expected that multiple neural networks would be involved in the dynamic tension experience. Using the neuroimaging data of 546 participants, we conducted a dynamic brain analysis to identify the intra- and inter-module functional connectivity patterns that are significantly correlated with the fluctuation of tension over time. The results showed that the inter-module connectivity of cingulo-opercular network, fronto-parietal network, and default mode network is involved in the dynamic experience of tension. These findings demonstrate a close relationship between brain functional connectivity patterns and emotional dynamics, which supports the importance of functional connectivity dynamics in understanding our cognitive and emotional processes.

Gene expression associated with individual variability in intrinsic functional connectivity.

It has been revealed that intersubject variability (ISV) in intrinsic functional connectivity (FC) is associated with a wide variety of cognitive and behavioral performances. However, the underlying organizational principle of ISV in FC and its related gene transcriptional profiles remain unclear. Using resting-state fMRI data from the Human Connectome Project (299 adult participants) and microarray gene expression data from the Allen Human Brain Atlas, we conducted a transcription-neuroimaging association study to investigate the spatial configurations of ISV in intrinsic FC and their associations with spatial gene transcriptional profiles. We found that the multimodal association cortices showed the greatest ISV in FC, while the unimodal cortices and subcortical areas showed the least ISV. Importantly, partial least squares regression analysis revealed that the transcriptional profiles of genes associated with human accelerated regions (HARs) could explain 31.29% of the variation in the spatial distribution of ISV in FC. The top-related genes in the transcriptional profiles were enriched for the development of the central nervous system, neurogenesis and the cellular components of synapse. Moreover, we observed that the effect of gene expression profile on the heterogeneous distribution of ISV in FC was significantly mediated by the cerebral blood flow configuration. These findings highlighted the spatial arrangement of ISV in FC and their coupling with variations in transcriptional profiles and cerebral blood flow supply.

Integrated and segregated frequency architecture of the human brain network.

The frequency of brain activity modulates the relationship between the brain and human behavior. Insufficient understanding of frequency-specific features may thus lead to inconsistent explanations of human behavior. However, to date, the frequency-specific features of the human brain functional network at the whole-brain level remain poorly understood. Here, we used resting-state fMRI data and graph-theory analyses to investigate the frequency-specific characteristics of fMRI signals in 12 frequency bands (frequency range 0.01-0.7 Hz) in 75 healthy participants. We found that brain regions with higher level and more complex functions had a more variable functional connectivity pattern but engaged less in higher frequency ranges. Moreover, brain regions that engaged in fewer frequency bands played more integrated roles (i.e., higher network participation coefficient and lower within-module degree) in the functional network, whereas regions that engaged in broader frequency ranges exhibited more segregated functions (i.e., lower network participation coefficient and higher within-module degree). Finally, behavioral analyses revealed that regional frequency variability was associated with a spectrum of behavioral functions from sensorimotor functions to complex cognitive and social functions. Taken together, our results showed that segregated functions are executed in wide frequency ranges, whereas integrated functions are executed mainly in lower frequency ranges. These frequency-specific features of brain networks provided crucial insights into the frequency mechanism of fMRI signals, suggesting that signals in higher frequency ranges should be considered for their relation to cognitive functions.

Comparison of mono-exponential, bi-exponential, kurtosis, and fractional-order calculus models of diffusion-weighted imaging in characterizing prostate lesions in transition zone.

PURPOSE: To compare various models of diffusion-weighted imaging including mono-exponential, bi-exponential, diffusion kurtosis (DK) and fractional-order calculus (FROC) models in diagnosing prostate cancer (PCa) in transition zone (TZ) and distinguish the high-grade PCa [Gleason score (GS) ≥ 7] lesions from the total of low-grade PCa (GS ≤ 6) lesions and benign prostatic hyperplasia (BPH) in TZ. METHODS: 80 Patients with 103 lesions were included in this study. Nine metrics [including apparent diffusion coefficient (ADC) derived from mono-exponential model, slow diffusion coefficient (Ds), fast diffusion coefficient (Df),, and f (the fraction of fast diffusion) from bi-exponential model; mean diffusivity (MD) and mean kurtosis (MK) from DK model; diffusion coefficient (D), fractional-order derivative in space (ß), and spatial metric (µ) from FROC model] were calculated. Comparisons between BPH and PCa lesions as well as between clinically significant PCa (CsPCa) (GS ≥ 7, n = 31) and clinically insignificant lesions (Cins) (GS ≤ 6 and BPH, n = 72) of these metrics were conducted. Mann-Whitney U-test and receiver operating characteristic (ROC) analysis were used for statistical evaluations. RESULTS: The areas under the ROC curve (AUC) values of ß derived from FROC model were 0.778 and 0.853 in differentiating PCa from BPH and in differentiating CS (GS ≥ 7) from Cins (GS ≤ 6 and BPH), both were the highest compared to other metrics. The AUC value of ß was significantly higher than that of ADC (P = 0.009) in differentiating CS from Cins, while the differentiation between BPH and PCa did not reach the statistical significance when comparing with ADC (P = 0.089). CONCLUSION: Although no significant difference was found in distinguishing PCa from BPH, the metric ß derived from FROC model was superior to other diffusion metrics in differentiation between CS and Cins in TZ.

Predicting visual working memory with multimodal magnetic resonance imaging.

The indispensability of visual working memory (VWM) in human daily life suggests its importance in higher cognitive functions and neurological diseases. However, despite the extensive research efforts, most findings on the neural basis of VWM are limited to a unimodal context (either structure or function) and have low generalization. To address the above issues, this study proposed the usage of multimodal neuroimaging in combination with machine learning to reveal the neural mechanism of VWM across a large cohort (N = 547). Specifically, multimodal magnetic resonance imaging features extracted from voxel-wise amplitude of low-frequency fluctuations, gray matter volume, and fractional anisotropy were used to build an individual VWM capacity prediction model through a machine learning pipeline, including the steps of feature selection, relevance vector regression, cross-validation, and model fusion. The resulting model exhibited promising predictive performance on VWM (r = .402, p < .001), and identified features within the subcortical-cerebellum network, default mode network, motor network, corpus callosum, anterior corona radiata, and external capsule as significant predictors. The main results were then compared with those obtained on emotional regulation and fluid intelligence using the same pipeline, confirming the specificity of our findings. Moreover, the main results maintained well under different cross-validation regimes and preprocess strategies. These findings, while providing richer evidence for the importance of multimodality in understanding cognitive functions, offer a solid and general foundation for comprehensively understanding the VWM process from the top down.

Kinetics and mechanisms of mitotic inheritance of DNA methylation and their roles in aging-associated methylome deterioration.

Mitotic inheritance of the DNA methylome is a challenging task for the maintenance of cell identity. Whether DNA methylation pattern in different genomic contexts can all be faithfully maintained is an open question. A replication-coupled DNA methylation maintenance model was proposed decades ago, but some observations suggest that a replication-uncoupled maintenance mechanism exists. However, the capacity and the underlying molecular events of replication-uncoupled maintenance are unclear. By measuring maintenance kinetics at the single-molecule level and assessing mutant cells with perturbation of various mechanisms, we found that the kinetics of replication-coupled maintenance are governed by the UHRF1-Ligase 1 and PCNA-DNMT1 interactions, whereas nucleosome occupancy and the interaction between UHRF1 and methylated H3K9 specifically regulate replication-uncoupled maintenance. Surprisingly, replication-uncoupled maintenance is sufficiently robust to largely restore the methylome when replication-coupled maintenance is severely impaired. However, solo-WCGW sites and other CpG sites displaying aging- and cancer-associated hypomethylation exhibit low maintenance efficiency, suggesting that although quite robust, mitotic inheritance of methylation is imperfect and that this imperfection may contribute to selective hypomethylation during aging and tumorigenesis.

Brain activity mediates the relation between emotional but not instrumental support and trait loneliness.

Loneliness results from lacking satisfied social connections. However, little is known how trait loneliness, which is a stable personal characteristic, is influenced by different types of social support (i.e. emotional and instrumental support) through the brain activity associated with loneliness. To explore these questions, data of resting-state functional magnetic resonance imaging (R-fMRI) of 92 healthy participants were analyzed. We identified loneliness-related brain regions by correlating participants' loneliness scores with amplitudes of low-frequency fluctuation (ALFF) of R-fMRI data. We then conducted mediation analyses to test whether the negative relation between each type of social support and loneliness was explained via the neural activity in the loneliness-related brain regions. The results showed that loneliness was positively related to the mean ALFF value within right inferior temporal gyrus (ITG). In addition, the negative relation between emotional support and loneliness was explained by a decrease in the spontaneous neural activity within right ITG but this pattern was not observed for instrumental support. These results suggest the importance of social information processing on trait loneliness and highlight the need to differentiate the functions of different types of social support on mental health from a neural perspective.

Molecular cloning and characterization of secretory and membrane-bound IgM of turbot.

In recent years, increasing diseases especially bacterial diseases have brought a host of losses with the expansive cultivation of turbot (Scophthalmus maximus). In order to do more research about the immune system of turbot for better understanding the mechanism of resisting diseases, the immunoglobulin genes related to secretory and membrane-bound IgM (s-IgM and m-IgM) of turbot were cloned using homology sequences cloning and SMART RACE PCR method. The heavy chain of s-IgM cDNA is 1900 bp in length including a leader region, a variable region, four constant regions (CH1, CH2, CH3 and CH4) and a C-terminal while the cDNA of m-IgM is 1795 bp with the same leader region, variable region, three constant regions (CH1, CH2 and CH3) and two transmembrane regions (TM1 and TM2). The sequence of IgM gene was also obtained and the structure consisted of V-CH1-CH2-CH3-CH4-TM1-TM2 is similar to other fishes. The highest level of s-IgM expression was observed in spleen, followed by kidney, gills, eyes, skin of the healthy turbot whereas the same profile of m-IgM expression is found with low level. And s-IgM takes up dominant proportion of total IgM expression. Also the relative expressions of s-IgM and m-IgM were analyzed in turbot vaccinated with the live attenuated vaccine Vibrio anguillarum. Not only the transcriptions of both s-IgM and m-IgM in liver, spleen and kidney of turbot injected with V. anguillarum MVAV6203 were up-regulated but also the expressions of s-IgM and m-IgM in spleen, kidney, gut, skin and gills of bath-vaccinated turbot were increased. Comparing the ratio changes of relative expression of m-IgM and s-IgM in vaccinated turbot, we found that the proportion of m-IgM were increasing in both administration routes, which probably indicated that the increasing expression of m-IgM strengthen the phagocytic ability of B cells.