Altered gut microbiota in temporal lobe epilepsy with anxiety disorders

IntroductionPatients with epilepsy are particularly vulnerable to the negative effects of anxiety disorders. In particular, temporal lobe epilepsy with anxiety disorders (TLEA) has attracted more attention in epilepsy research. The link between intestinal dysbiosis and TLEA has not been established yet. To gain deeper insight into the link between gut microbiota dysbiosis and factors affecting TLEA, the composition of the gut microbiome, including bacteria and fungi, has been examined.MethodsThe gut microbiota from 51 temporal lobe epilepsy patients has been subjected to sequencing targeting 16S rDNA (Illumina MiSeq) and from 45 temporal lobe epilepsy patients targeting the ITS-1 region (through pyrosequencing). A differential analysis has been conducted on the gut microbiota from the phylum to the genus level.ResultsTLEA patients' gut bacteria and fungal microbiota exhibited distinct characteristics and diversity as evidenced by high-throughput sequencing (HTS). TLEA patients showed higher abundances of Escherichia-Shigella (genus), Enterobacterales (order), Enterobacteriaceae (family), Proteobacteria (phylum), Gammaproteobacteria (class), and lower abundances of Clostridia (class), Firmicutes, Lachnospiraceae (family), Lachnospirales (order), and Ruminococcus (genus). Among fungi, Saccharomycetales fam. incertae sedis (family), Saccharomycetales (order), Saccharomycetes (class), and Ascomycota (phylum) were significantly more abundant in TLEA patients than in patients with temporal lobe epilepsy but without anxiety. Adoption and perception of seizure control significantly affected TLEA bacterial community structure, while yearly hospitalization frequency affected fungal community structures in TLEA patients.ConclusionHere, our study validated the gut microbiota dysbiosis of TLEA. Moreover, the pioneering study of bacterial and fungal microbiota profiles will help in understanding the course of TLEA and drive us toward preventing TLEA gut microbiota dysbiosis

Highly sensitive Curcumin-conjugated nanotheranostic platform for detecting amyloid-beta plaques by magnetic resonance imaging and reversing cognitive deficits of Alzheimer's disease via NLRP3-inhibition

Abstract Background Alzheimer's disease (AD) is the most common neurodegenerative disorder without effective therapy and lack diagnosis strategy for preclinical AD patients. There is an urgent need for development of both early diagnosis and therapeutic intervention of AD. Results Herein, we developed a nanotheranostics platform consisting of Curcumin (Cur), an anti-inflammatory molecule, and superparamagnetic iron oxide (SPIO) nanoparticles encapsulated by diblock 1,2-dio-leoyl-sn-glycero-3-phosphoethanolamine-n-[poly(ethylene glycol)] (DSPE-PEG) that are modified with CRT and QSH peptides on its surface. Furthermore, we demonstrated that this multifunctional nanomaterial efficiently reduced β-amyloid plaque burden specifically in APP/PS1 transgenic mice, with the process noninvasively detected by magnetic resonance imaging (MRI) and the two-dimensional MRI images were computed into three-dimension (3D) plot. Our data demonstrated highly sensitive in vivo detection of β-amyloid plaques which more closely revealed real deposition of Aβ than previously reported and we quantified the volumes of plaques for the first time based on 3D plot. In addition, memory deficits of the mice were significantly rescued, probably related to inhibition of NLR Family Pyrin Domain Containing 3 (NLRP3) inflammasomes. Conclusions Gathered data demonstrated that this theranostic platform may have both early diagnostic and therapeutic potential in AD. Graphical Abstrac

Protection of Fecal Microbiota Transplantation in a Mouse Model of Multiple Sclerosis

Given the growing evidence of a link between gut microbiota (GM) dysbiosis and multiple sclerosis (MS), fecal microbiota transplantation (FMT), aimed at rebuilding GM, has been proposed as a new therapeutic approach to MS treatment. To evaluate the viability of FMT for MS treatment and its impact on MS pathology, we tested FMT in mice with experimental autoimmune encephalomyelitis (EAE), a mouse model of MS. We provide evidence that FMT can rectify altered GM to some extent with a therapeutic effect on EAE. We also found that FMT led to reduced activation of microglia and astrocytes and conferred protection on the blood-brain barrier (BBB), myelin, and axons in EAE. Taken together, our data suggest that FMT, as a GM-based therapy, has the potential to be an effective treatment for MS

An MRI-based strategy for differentiation of frontotemporal dementia and Alzheimer's disease.

BackgroundThe differential diagnosis of frontotemporal dementia (FTD) and Alzheimer's disease (AD) is difficult due to the overlaps of clinical symptoms. Structural magnetic resonance imaging (sMRI) presents distinct brain atrophy and potentially helps in their differentiation. In this study, we aim at deriving a novel integrated index by leveraging the volumetric measures in brain regions with significant difference between AD and FTD and developing an MRI-based strategy for the differentiation of FTD and AD.MethodsIn this study, the data were acquired from three different databases, including 47 subjects with FTD, 47 subjects with AD, and 47 normal controls in the NACC database; 50 subjects with AD in the ADNI database; and 50 subjects with FTD in the FTLDNI database. The MR images of all subjects were automatically segmented, and the brain atrophy, including the AD resemblance atrophy index (AD-RAI), was quantified using AccuBrain®. A novel MRI index, named the frontotemporal dementia index (FTDI), was derived as the ratio between the weighted sum of the volumetric indexes in "FTD dominant" structures over that obtained from "AD dominant" structures. The weights and the identification of "FTD/AD dominant" structures were acquired from the statistical analysis of NACC data. The differentiation performance of FTDI was validated using independent data from ADNI and FTLDNI databases.ResultsAD-RAI is a proven imaging biomarker to identify AD and FTD from NC with significantly higher values (p < 0.001 and AUC = 0.88) as we reported before, while no significant difference was found between AD and FTD (p = 0.647). FTDI showed excellent accuracy in identifying FTD from AD (AUC = 0.90; SEN = 89%, SPE = 75% with threshold value = 1.08). The validation using independent data from ADNI and FTLDNI datasets also confirmed the efficacy of FTDI (AUC = 0.93; SEN = 96%, SPE = 70% with threshold value = 1.08).ConclusionsBrain atrophy in AD, FTD, and normal elderly shows distinct patterns. In addition to AD-RAI that is designed to detect abnormal brain atrophy in dementia, a novel index specific to FTD is proposed and validated. By combining AD-RAI and FTDI, an MRI-based decision strategy was further proposed as a promising solution for the differential diagnosis of AD and FTD in clinical practice