Parkinson’s disease (PD) is a neurodegenerative disease characterized by the death of dopaminergic neurons in the substantia nigra and the formation of Lewy bodies that are composed of aggregated α-synuclein (α-Syn). However, the factors that regulate α-Syn pathology and nigrostriatal dopaminergic degeneration remain poorly understood. Previous studies demonstrate cholesterol 24-hydroxylase (CYP46A1) increases the risk for PD. Moreover, 24-hydroxycholesterol (24-OHC), a brain-specific oxysterol that is catalyzed by CYP46A1, is elevated in the cerebrospinal fluid of PD patients. Herein, we show that the levels of CYP46A1 and 24-OHC are elevated in PD patients and increase with age in a mouse model. Overexpression of CYP46A1 intensifies α-Syn pathology, whereas genetic removal of CYP46A1 attenuates α-Syn neurotoxicity and nigrostriatal dopaminergic degeneration in the brain. Moreover, supplementation with exogenous 24-OHC exacerbates the mitochondrial dysfunction induced by α-Syn fibrils. Intracerebral injection of 24-OHC enhances the spread of α-Syn pathology and dopaminergic neurodegeneration via elevated X-box binding protein 1 (XBP1) and lymphocyte-activation gene 3 (LAG3) levels. Thus, elevated CYP46A1 and 24-OHC promote neurotoxicity and the spread of α-Syn via the XBP1–LAG3 axis. Strategies aimed at inhibiting the CYP46A1-24-OHC axis and LAG3 could hold promise as disease-modifying therapies for PD.
δ-secretase, also known as asparagine endopeptidase (AEP) or legumain, is a lysosomal cysteine protease that cleaves both amyloid precursor protein (APP) and tau, mediating the amyloid-β and tau pathology in Alzheimer's disease (AD). Here we report the therapeutic effect of an orally bioactive and brain permeable δ-secretase inhibitor in mouse models of AD. We performed a high-throughput screen and identified a non-toxic and selective δ-secretase inhibitor, termed compound 11, that specifically blocks δ-secretase but not other related cysteine proteases. Co-crystal structure analysis revealed a dual active site-directed and allosteric inhibition mode of this compound class. Chronic treatment of tau P301S and 5XFAD transgenic mice with this inhibitor reduces tau and APP cleavage, ameliorates synapse loss and augments long-term potentiation, resulting in protection of memory. Therefore, these findings demonstrate that this δ-secretase inhibitor may be an effective clinical therapeutic agent towards AD.
Supplementary Figure from Telaglenastat plus Everolimus in Advanced Renal Cell Carcinoma: A Randomized, Double-Blinded, Placebo-Controlled, Phase II ENTRATA Trial
Cucumber, Cucumis sativus L., is an economically important vegetable crop which is processed or consumed fresh worldwide. However, the narrow genetic base in cucumber makes it difficult for constructing high-density genetic maps. The development of massively parallel genotyping methods and next-generation sequencing (NGS) technologies provides an excellent opportunity for developing single nucleotide polymorphisms (SNPs) for linkage map construction and QTL analysis of horticultural traits. Specific-length amplified fragment sequencing (SLAF-seq) is a recent marker development technology that allows large-scale SNP discovery and genotyping at a reasonable cost. In this study, we constructed a high-density SNP map for cucumber using SLAF-seq and detected fruit-related QTLs.An F2 population of 148 individuals was developed from an intra-varietal cross between CC3 and NC76. Genomic DNAs extracted from two parents and 148 F2 individuals were subjected to high-throughput sequencing and SLAF library construction. A total of 10.76 Gb raw data and 75,024,043 pair-end reads were generated to develop 52,684 high-quality SLAFs, out of which 5,044 were polymorphic. 4,817 SLAFs were encoded and grouped into different segregation patterns. A high-resolution genetic map containing 1,800 SNPs was constructed for cucumber spanning 890.79 cM. The average distance between adjacent markers was 0.50 cM. 183 scaffolds were anchored to the SNP-based genetic map covering 46% (168.9 Mb) of the cucumber genome (367 Mb). Nine QTLs for fruit length and weight were detected, a QTL designated fl3.2 explained 44.60% of the phenotypic variance. Alignment of the SNP markers to draft genome scaffolds revealed two mis-assembled scaffolds that were validated by fluorescence in situ hybridization (FISH).We report herein the development of evenly dispersed SNPs across cucumber genome, and for the first time an SNP-based saturated linkage map. This 1,800-locus map would likely facilitate genetic mapping of complex QTL loci controlling fruit yield, and the orientation of draft genome scaffolds.
The molecular mechanisms mediating the aggregation and transmission of tau in AD remain unclear. Here, we show that the actin-binding protein cofilin is cleaved by a cysteine protease asparagine endopeptidase (AEP) at N138 in the brains of patients with AD. The AEP-generated cofilin 1-138 fragment interacts with tau and promotes its aggregation. The mixed fibrils consisting of cofilin 1-138 and tau are more pathogenic to cells than pure tau fibrils. Furthermore, overexpression of cofilin 1-138 in the brain facilitates the propagation of pathological tau aggregates and promotes AD-like cognitive impairments in tau P301S mice. However, mice infected with adeno-associated viruses (AAVs) encoding an AEP-uncleavable cofilin mutant show attenuated tau pathology and cognitive impairments compared with mice injected with AAVs encoding wild-type cofilin. Together, these observations support the role of the cofilin 1-138 fragment in the aggregation and transmission of tau pathology during the onset and progression of AD.
Solar cell model parameters are of great significance in the study of solar cell fault model, power prediction and the maximum power point tracking. Therefore, it is very necessary to study an fast and accurate algorithm for solar cell model parameters identification. Based on characteristics of solar cell model, a solar cell parameters identification method based on particle swarm optimization (PSO) with adaptive elite mutation (AEM) is studied. Traditional evolutionary computation methods have the disadvantage of premature convergence, which will affect the accuracy of identification. In order to accelerate the searching speed, we select elite particles to replace inferior particles in the process of evolution. Meanwhile, adaptive mutation strategy can avoid the risk that particle swarm will lose its diversity and fall into local optimal solution. Combining elite particle and adaptive mutation strategy, we overcome contradiction between exploration and development of the optimization algorithm. The experimental results show that the particle swarm optimization with adaptive elite mutation (PSO-AEM) has a good effect and processing speed for identification of solar cell model parameters.
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