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Abstract Objective The single‐center retrospective cohort study investigated underlying pathogenic mechanisms and clinical significance of patients with temporal lobe epilepsy and hippocampal sclerosis (TLE‐HS), in the presence/absence of gray–white matter abnormalities (usually called “blurring”; GMB) in ipsilateral temporopolar region (TPR) on MRI. Methods The study involved 105 patients with unilateral TLE‐HS (60 GMB+ and 45 GMB−) who underwent standard anterior temporal lobectomy, along with 61 healthy controls. Resected specimens were examined under light microscope. With combined T1‐weighted and DTI data, we quantitatively compared large‐scale morphometric features and exacted diffusion parameters of ipsilateral TPR‐related superficial and deep white matter (WM) by atlas‐based segmentation. Along‐tract analysis was added to detect heterogeneous microstructural alterations at various points along deep WM tracts, which were categorized into inferior longitudinal fasciculus (ILF), uncinate fasciculus (UF), and temporal cingulum. Results Comparable seizure semiology and postoperative seizure outcome were found, while the GMB+ group had significantly higher rate of HS Type 1 and history of febrile seizures, contrasting with significantly lower proportion of interictal contralateral epileptiform discharges, HS Type 2, and increased wasteosomes in hippocampal specimens. Similar morphometric features but greater WM atrophy with more diffusion abnormalities of superficial WM was observed adjacent to ipsilateral TPR in the GMB+ group. Moreover, microstructural alterations resulting from temporopolar GMB were more localized in temporal cingulum while evenly and widely distributed along ILF and UF. Interpretation Temporopolar GMB could signify more severe and widespread microstructural damage of white matter rather than a focal cortical lesion in TLE‐HS, affecting selection of surgical procedures.

Objective(s): Neuroinflammation is considered an important step in the progression of secondary brain injury (SBI) induced by cerebral hemorrhage (ICH). The nucleotide-binding and oligomerization structural domain-like receptor family of pyridine structural domain-containing 3 (NLRP3) inflammasomes play an important role in the immune pathophysiology of SBI. Febuxostat (Feb) is a xanthine oxidase inhibitor that is approved for the treatment of gout and has been found to have potent anti-inflammatory effects. However, it has been less studied after ICH and we aimed to explore its protective role in ICH.Materials and Methods: We established an autologous blood-brain hemorrhage model in C57BL/6 mice. Functions of co-expressed genes were analyzed by trend analysis and bioinformatics analysis. Enzyme-linked immunosorbent assay were used to assess the inflammatory factor levels. Fluoro-Jade B histochemistry and TUNEL staining were used to detect neuronal apoptosis. Immunofluorescence staining and western blotting were used to detect the expression of NLRP3 inflammasomes.Results: Pretreatment with Feb reduced neuronal cell death and degeneration and alleviated neurobehavioral disorders in vivo. Feb was found to modulate inflammation-related pathways by trend analysis and bioinformatics analysis. In addition, Feb inhibited microglia activation and elevated cytokine levels after ICH. Furthermore, double immunofluorescence staining showed that co-localization of NLRP3 with Iba1 positive cells was reduced after treatment with Feb. Finally, we found that Feb inhibited the activation of the NLRP3/ASC/caspase-1 pathway after ICH. Conclusion: By inhibiting the NLRP3 inflammasome, preconditioning Feb attenuates inflammatory injury after ICH. Our findings may provide new insights into the role of Feb in neuroprotection.

Abstract Artificial intelligence provides an opportunity to try to redefine disease subtypes based on similar pathobiology. Using a machine-learning algorithm (Subtype and Stage Inference) with cross-sectional MRI from 296 individuals with focal epilepsy originating from the temporal lobe (TLE) and 91 healthy controls, we show phenotypic heterogeneity in the pathophysiological progression of TLE. This study was registered in the Chinese Clinical Trials Registry (number: ChiCTR2200062562). We identify two hippocampus-predominant phenotypes, characterized by atrophy beginning in the left or right hippocampus; a third cortex-predominant phenotype, characterized by hippocampus atrophy after the neocortex; and a fourth phenotype without atrophy but amygdala enlargement. These four subtypes are replicated in the independent validation cohort (109 individuals). These subtypes show differences in neuroanatomical signature, disease progression and epilepsy characteristics. Five-year follow-up observations of these individuals reveal differential seizure outcomes among subtypes, indicating that specific subtypes may benefit from temporal surgery or pharmacological treatment. These findings suggest a diverse pathobiological basis underlying focal epilepsy that potentially yields to stratification and prognostication – a necessary step for precise medicine.

BackgroundHippocampal sclerosis (HS) is the most common pathological type of temporal lobe epilepsy (TLE) and one of the important surgical markers. Currently, HS is mainly diagnosed manually by radiologists based on visual inspection of MRI, which greatly relies on MRI quality and physician experience. In clinical practice, non-thin MRI scans are often used due to the time and efficiency needed for the acquisition. However, these scans can be difficult for junior physicians to interpret accurately. Thus, the rapid and accurate diagnosis of HS using real-world MRI images in clinical settings is a challenging task.ObjectiveOur aim was to explore the feasibility of using computer vision methods to diagnose HS on real-world clinical MRI images and to provide a reference for future clinical applications of artificial intelligence methods to aid in detecting HS.MethodsWe proposed a deep learning algorithm called “HS-Net” to discriminate HS using real-world clinical MRI images. First, we delineated and segmented a region of interest (ROI) around the hippocampus. Then, we utilized the fractional differential (FD) method to enhance the textures of the ROIs. Finally, we used a small-sample image classification method based on transfer learning to fine-tune the feature extraction part of a pretrained model and added two fully connected layers and an output layer. In the study, 96 TLE patients with HS confirmed by postoperative pathology and 89 healthy controls were retrospectively enrolled. All subjects were cross-validated, and models were evaluated for performance, robustness, and clinical utility.ResultsThe HS-Net model achieved an area under the curve (AUC) of 0.894, an accuracy of 82.88%, an F1-score of 84.08% in the test cohort based on real, routine, clinical T2-weighted fluid attenuated inversion recovery (FLAIR) sequence MRI images. Additionally, the AUC, accuracy and F1 scores of our model all increased by around 3 percentage points when the inputs were augmented with the ROIs of the textures enhanced using the FD method.ConclusionsOur computational model has the potential to be used for the diagnosis of HS in real clinical MRI images, which could assist physicians, particularly junior physicians, in improving the accuracy of discrimination.

Objectives: To investigate the effect of aligner displacement on tooth movement and periodontal health to improve the efficiency of aligner treatment and explore the mechanism in vivo. Methods: A two-tooth site was established by a finite element (FE) model to virtually evaluate aligner staging. A randomized controlled experiment was conducted when the tooth sites in beagles were treated with fixed or aligner appliances with different movement and force, and tooth movement and internal structure were recorded during the alignment. After sacrificing five dogs, bone-periodontal ligament (PDL)-tooth specimens were removed and processed to conduct uniaxial compression and tensile tests as well as micro-CT imaging and histological analysis. Results: Three displacements of 0.25, 0.35 and 0.45 mm were obtained from FE analysis and applied in beagles. In general, aligners had poorer performance on movement compared to fixed systems in vivo, but the aligner with a staging of 0.35 mm had the highest accuracy (67.46%) (P

The γ-aminobutyric acid type A receptors (GABAAR) have been reported to contribute to the pathogenesis of epilepsy and the recurrence of chronic seizures. Genetic polymorphisms in GABRA1 and GABRA6 may confer a high risk of epilepsy and multiple drug resistance, but with conflicting results. We aimed to assess the association of GABRA1 rs2279020 and GABRA6 rs3219151 with epilepsy risk using a meta-analysis. The databases of Pubmed, Ovid, Web of Science, and China National Knowledge Infrastructure were searched. Summary odds ratios (ORs) and 95% confidence intervals (CIs) were computed to evaluate the association between the polymorphisms and epilepsy risk using a fixed- or random-effect model. Trial sequential analysis (TSA) was performed to assess the results of the meta-analysis. No significant association between the GABRA1 rs2279020 and GABRA6 rs3219151 and the risk of epilepsy was found in the Asian and Arabic populations. The negative results were also observed when comparing the GABRA1 rs2279020 and GABRA6 rs3219151 polymorphism to antiepileptic drug responsiveness. The trial sequential analysis confirmed the results of the meta-analysis. This meta-analysis suggests that GABRA1 rs2279020 and GABRA6 rs3219151 are not risk factors for the etiology of epilepsy and antiepileptic drug responsiveness in the Asian and Arabic populations.

Several lines of evidence indicate that inflammatory processes play a key role in the happening and development of intracranial aneurysm (IA). Recently, polymorphisms in the TP53 gene were shown to be associated with inflammation and inflammatory disease. The aim of this study was to investigate the interactions of miR-34b/c and TP53 Arg72-Pro polymorphisms on the risk of IA in a Chinese population. A total of 590 individuals (including 164 patients with IA and 426 controls) were involved in this study. The polymorphisms (i.e., miR-34b/c rs4938723 and TP53 Arg72-Pro) were genotyped by polymerase chain reaction-restriction fragment length polymorphism assay and DNA sequencing. We found that the CC genotype of miR-34b/c rs4938723 was significantly associated with a decreased risk of IA compared with the TT genotype. Moreover, a significant gene interaction of the carriers with the combined genotypes of miR-34b/c rs4938723CC and TP53 Arg72Pro CG/CC/GG had a decreased risk of IA, compared with those carrying miR-34b/c rs4938723CT/TT+TP53 Arg72Pro GG/CG/CC combined genotypes. These findings suggest that the miR-34b/c rs4938723CC and TP53 Arg72-Pro polymorphisms may be involved in the susceptibility to IA.

β-amyloid precursor protein (β-AFF), also known as Ap peptide, has a key role in the pathogenesis of Alzheimer's disease, and is also likely to be involved in the development of refractory epilepsy. The mechanism behind the association between β-AFF and refractory epilepsy remains to be elucidated. The aim of the present study was to examine the levels of APP mRNA and β-AFF protein in patients with refractory epilepsy. Tissue samples were obtained from patients with chronic pharmacoresistant epilepsy who underwent surgery. Levels of APP mRNA and β-AFF protein in epileptic temporal lobe and hippocampal tissue were assessed using quantitative polymerase chain reaction, immunohistochemistry and immunofluorescence. The expression levels of protein significantly increased in the temporal cortex and the hippocampus of the patients with epilepsy. β-AFF may thus contribute to the pathogenesis of refractory epilepsy. [ABSTRACT FROM AUTHOR]

Objective: Growing evidence indicates that vascular inflammation is a common phenomenon in the pathogenesis of intracranial aneurysms (IAs). Nuclear factor kappa B is a key molecule that is involved in the vascular inflammation of IA. We hypothesized that an insertion/deletion (ins/del) ATTG polymorphism located between two putative key promoter regulatory elements in the NFKB1 gene may be related to the risk of IA. Methods: We performed a case-control study, including 164 patients with IA and 525 healthy controls in a Chinese population using a polymerase chain reaction-polyacrylamide gel electrophoresis assay. Results: A significantly decreased risk of IA was observed in the ATTG1/ATTG2 and ATTG2/ATTG2 genotypes compared with the ATTG1/ ATTG1 genotype (ATTG1/ATTG2 vs. ATTG1/ATTG1: odds ratio [OR] = 0.58, 95% confidence interval [95% CI] = 0.39-0.87, p = 0.007; ATTG2/ATTG2 vs. ATTG1/ATTG1: OR= 0.12, 95% CI = 0.06-0.23, p < 0.001), and also the ATTG2 allele (ATTG2 vs. ATTG1: OR= 0.41, 95% CI = 0.32-0.54, p < 0.001). Conclusion: These findings suggest that the NFKB1 - 94ins/del ATTG polymorphism may contribute to the risk of IA. [ABSTRACT FROM AUTHOR]