Edge-wise analysis reveals white matter connectivity associated with focal to bilateral tonic-clonic seizures.

OBJECTIVE: Focal to bilateral tonic-clonic seizures (FBTCS) represent a challenging subtype of focal temporal lobe epilepsy (TLE) in terms of both severity and treatment response. Most studies have focused on regional brain analysis that is agnostic to the distribution of white matter (WM) pathways associated with a node. We implemented a more selective, edge-wise approach that allowed for identification of the individual connections unique to FBTCS. METHODS: T1-weighted and diffusion-weighted images were obtained from 22 patients with solely focal seizures (FS), 43 FBTCS patients, and 65 age/sex-matched healthy participants (HPs), yielding streamline (STR) connectome matrices. We used diffusion tensor-derived STRs in an edge-wise approach to determine specific structural connectivity changes associated with seizure generalization in FBTCS compared to matched FS and HPs. Graph theory metrics were computed on both node- and edge-based connectivity matrices. RESULTS: Edge-wise analyses demonstrated that all significantly abnormal cross-hemispheric connections belonged to the FBTCS group. Abnormal connections associated with FBTCS were mostly housed in the contralateral hemisphere, with graph metric values generally decreased compared to HPs. In FBTCS, the contralateral amygdala showed selective decreases in the structural connection pathways to the contralateral frontal lobe. Abnormal connections in TLE involved the amygdala, with the ipsilateral side showing increases and the contralateral decreases. All the FS findings indicated higher graph metrics for connections involving the ipsilateral amygdala. Data also showed that some FBTCS connectivity effects are moderated by aging, recent seizure frequency, and longer illness duration. SIGNIFICANCE: Data showed that not all STR pathways are equally affected by the seizure propagation of FBTCS. We demonstrated two key biases, one indicating a large role for the amygdala in the propagation of seizures, the other pointing to the prominent role of cross-hemispheric and contralateral hemisphere connections in FBTCS. We demonstrated topographic reorganization in FBTCS, pointing to the specific WM tracts involved.

Prediction of sulfate concentrations in groundwater in areas with complex hydrogeological conditions based on machine learning.

The persistent and increasing levels of sulfate due to a variety of human activities over the last decades present a widely concerning environmental issue. Understanding the controlling factors of groundwater sulfate and predicting sulfate concentration is critical for governments or managers to provide information on groundwater protection. In this study, the integration of self-organizing map (SOM) approach and machine learning (ML) modeling offers the potential to determine the factors and predict sulfate concentrations in the Huaibei Plain, where groundwater is enriched with sulfate and the areas have complex hydrogeological conditions. The SOM calculation was used to illustrate groundwater hydrochemistry and analyze the correlations among the hydrochemical parameters. Three ML algorithms including random forest (RF), support vector machine (SVM), and back propagation neural network (BPNN) were adopted to predict sulfate levels in groundwater by using 501 groundwater samples and 8 predictor variables. The prediction performance was evaluated through statistical metrics (R2, MSE and MAE). Mine drainage mainly facilitated increase in groundwater SO42- while gypsum dissolution and pyrite oxidation were found another two potential sources. The major water chemistry type was Ca-HCO3. The dominant cation was Na+ while the dominant anion was HCO3-. There was an intuitive correlation between groundwater sulfate and total dissolved solids (TDS), Cl-, and Na+. By using input variables identified by the SOM method, the evaluation results of ML algorithms showed that the R2, MSE and MAE of RF, SVM, BPNN were 0.43-0.70, 0.16-0.49 and 0.25-0.44. Overall, BPNN showed the best prediction performance and had higher R2 values and lower error indices. TDS and Na+ had a high contribution to the prediction accuracy. These findings are crucial for developing groundwater protection and remediation policies, enabling more sustainable management.

Larger aggregate formed by self-assembly process of the mixture surfactants enhance the dissolution and oxidative removal of non-aqueous phase liquid contaminants in aquifer.

Surfactants can transfer non-aqueous phase liquid (NAPL) contaminants to the aqueous phase, and enhance the removal of the latter in groundwater. However, the extensive use of surfactants causes secondary contamination and increases the non-target consumption of oxidants. It is pressing to develop a surfactant with high phase transfer efficiency and sound compatibility with oxidants to minimize the use of surfactants for groundwater remediation. The phase transfer capability of different surfactants and their binary mixtures, their enhanced KMnO4 oxidation performance for NAPL contaminants as well as influencing factors were investigated to solve the above-mentioned question. The results showed that Tween20, SDBS and BS-12 perform best in terms of phase transfer capability among nonionic, anionic and amphoteric surfactants respectively, and only SDBS and BS-12 produce a synergistic effect among the binary mixtures. The CMC of SDBS/BS-12 was lower than its ideal CMC value, and the self-assembly process of SDBS/BS-12 also formed larger aggregates, which improved the phase transfer performance. Compared to other single surfactants, the removal efficiency of petroleum hydrocarbons in the aquifer sediments was raised by 7.4-33.8 % using the mixed surfactant. The SDBS/BS-12 mixture was compatible with KMnO4 and boosted the reaction of NAPL contaminants with KMnO4 by transferring from the NAPL phase to the aqueous phase. As a result, the NAPL toluene and phenanthrene removal efficiency increased from 37 % and 29 % to 80 % and 86 % respectively. Natural organic matters inhibited the phase transfer efficiency of the SDBS/BS-12 mixture, whereas anions and monovalent cations enhanced the phase transfer capability of the mixture. High-valent cations led to precipitation in the SDBS/BS-12, which could be eliminated by adding Na2Si2O5. The SDBS/BS-12 mixture delivered the same phase transfer efficiency with the dosage of 1.73-23.07 % of other single surfactants, and its cost was equivalent to 0.25-41.7 % of the latter, thus embracing bright application prospects.

Tropism-shifted AAV-PHP.eB-mediated bFGF gene therapy promotes varied neurorestoration after ischemic stroke in mice.

ABSTRACT: AAV-PHP.eB is an artificial adeno-associated virus (AAV) that crosses the blood-brain barrier and targets neurons more efficiently than other AAVs when administered systematically. While AAV-PHP.eB has been used in various disease models, its cellular tropism in cerebrovascular diseases remains unclear. In the present study, we aimed to elucidate the tropism of AAV-PHP.eB for different cell types in the brain in a mouse model of ischemic stroke and evaluate its effectiveness in mediating basic fibroblast growth factor (bFGF) gene therapy. Mice were injected intravenously with AAV-PHP.eB either 14 days prior to (pre-stroke) or 1 day following (post-stroke) transient middle cerebral artery occlusion. Notably, we observed a shift in tropism from neurons to endothelial cells with post-stroke administration of AAV-PHP.eB-mNeonGreen (mNG). This endothelial cell tropism correlated strongly with expression of the endothelial membrane receptor lymphocyte antigen 6 family member A (Ly6A). Furthermore, AAV-PHP.eB-mediated overexpression of bFGF markedly improved neurobehavioral outcomes and promoted long-term neurogenesis and angiogenesis post-ischemic stroke. Our findings underscore the significance of considering potential tropism shifts when utilizing AAV-PHP.eB-mediated gene therapy in neurological diseases and suggest a promising new strategy for bFGF gene therapy in stroke treatment.

NeuroD1 Regulated Endothelial Gene Expression to Modulate Transduction of AAV-PHP.eB and Recovery Progress after Ischemic Stroke.

AAV-PHP.eB depends on endothelial cells to highly transduce the central nervous system (CNS) and is widely used for intravenous gene therapy. However, the transduction profile and therapeutic efficiency after endothelial cell injury such as ischemic stroke is largely unknown. In this study, we tested the transduction profiles of AAV-PHP.eB and developed intravenous NeuroD1 gene therapy to treat ischemic stroke in mice. We found that AAV-PHP.eB-GFP control virus crossed the BBB and infected brain cells efficiently in normal brain. However, after stroke, AAV-PHP.eB-GFP control virus was highly restricted in the blood vessels. Surprisingly, after switching to therapeutic vector AAV-PHP.eB-NeuroD1-GFP, the viral vector successfully crossed blood vessels and infected brain cells. Using Tie2-cre transgenic mice, we demonstrated that NeuroD1 regulated endothelial gene expression to modulate AAV-PHP.eB transduction. Following the changes of signaling pathways in endothelial cells, NeuroD1 effectively protected BBB integrity, attenuated neuroinflammation, inhibited neuron apoptosis and rescued motor deficits after ischemic stroke. Moreover, NeuroD1 over-expression in brain cells further promoted neural regeneration. These results indicate that intravenous gene therapy using AAV-PHP.eB for ischemic stroke differs from intracranial gene therapy and NeuroD1 intravenous delivery using AAV-PHP.eB efficiently rescue both vascular damage and neuronal loss, providing an advancing therapeutic treatment for stroke.