A lysosome-targetable fluorescent probe for the ratiometric detection of formaldehyde in living cells and in vivo.

Inspired by the synthetic method of benzoxazine derivatives and our previous research, a fluorescent probe (SWJT-6) was designed for formaldehyde (FA) detection based on the cyclization reaction. The synthetic SWJT-6 showed excellent colorimetric and ratiometric response to formaldehyde, and could be perfectly used as test strips to detect formaldehyde. It also showed a fast detection time (3 min), low detection limit (5.65 µM) and high selectivity for formaldehyde within various interfering analytes. In addition, SWJT-6 has been successfully applied in bioimaging of intracellular and lysosomal formaldehyde in both HeLa cells and zebrafish.

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.

Avalanche criticality in individuals, fluid intelligence, and working memory.

The critical brain hypothesis suggests that efficient neural computation can be achieved through critical brain dynamics. However, the relationship between human cognitive performance and scale-free brain dynamics remains unclear. In this study, we investigated the whole-brain avalanche activity and its individual variability in the human resting-state functional magnetic resonance imaging (fMRI) data. We showed that though the group-level analysis was inaccurate because of individual variability, the subject wise scale-free avalanche activity was significantly associated with maximal synchronization entropy of their brain activity. Meanwhile, the complexity of functional connectivity, as well as structure-function coupling, is maximized in subjects with maximal synchronization entropy. We also observed order-disorder phase transitions in resting-state brain dynamics and found that there were longer times spent in the subcritical regime. These results imply that large-scale brain dynamics favor the slightly subcritical regime of phase transition. Finally, we showed evidence that the neural dynamics of human participants with higher fluid intelligence and working memory scores are closer to criticality. We identified brain regions whose critical dynamics showed significant positive correlations with fluid intelligence performance and found that these regions were located in the prefrontal cortex and inferior parietal cortex, which were believed to be important nodes of brain networks underlying human intelligence. Our results reveal the possible role that avalanche criticality plays in cognitive performance and provide a simple method to identify the critical point and map cortical states on a spectrum of neural dynamics, ranging from subcriticality to supercriticality.

Convergent developmental principles between Caenorhabditis elegans and human connectomes.

A recent study by Witvliet et al. reconstructed the entire brain connectome for eight Caenorhabditis elegans spanning from birth to adulthood and described how synapse changes shape the connectome topology during development. Their data suggest some convergent developmental principles in connectome maturation between C. elegans and humans.

Faded Critical Dynamics in Adult Moyamoya Disease Revealed by EEG and fMRI.

Criticality is considered a dynamic signature of healthy brain activity that can be measured on the short-term timescale with neural avalanches and long-term timescale with long-range temporal correlation (LRTC). It is unclear how the brain dynamics change in adult moyamoya disease (MMD). We used BOLD-fMRI for LRTC analysis from 16 hemorrhagic (H MMD) and 34 ischemic (I MMD) patients and 25 healthy controls. Afterwards, they were examined by EEG recordings in the eyes-closed (EC), eyes-open (EO), and working memory (WM) states. The EEG data of 11 H MMD and 13 I MMD patients and 21 healthy controls were in good quality for analysis. Regarding the 4 metrics of neural avalanches (e.g., size (α), duration (ß), κ value, and branching parameter (σ)), both MMD subtypes exhibited subcritical states in the EC state. When switching to the WM state, H MMD remained inactive, while I MMD surpassed controls and became supercritical (p < 0.05). Regarding LRTC, the amplitude envelope in the EC state was more analogous to random noise in the MMD patients than in controls. During state transitions, LRTC decreased sharply in the controls but remained chaotic in the MMD individuals (p < 0.05). The spatial LRTC reduction distribution based on both EEG and fMRI in the EC state implied that, compared with controls, the two MMD subtypes might exhibit mutually independent but partially overlapping patterns. The regions showing decreased LRTC in both EEG and fMRI were the left supplemental motor area of H MMD and right pre-/postcentral gyrus and right inferior temporal gyrus of I MMD. This study not only sheds light on the decayed critical dynamics of MMD in both the resting and task states for the first time but also proposes several EEG and fMRI features to identify its two subtypes.