ABSTRACT
Multiple cell death pathways are involved in neuronal death in ischemic stroke (IS). However, the role of different cell death pathways in different cell types has not been elucidated. By analyzing three single-nucleus RNA sequencing (snRNA-seq) data of IS, we first found that a variety of programmed cell death (PCD) -related genes were significantly changed in different cell types. Based on machine learning and virtual gene knockout, we found that ferroptosis related genes, ferritin heavy chain 1 (Fth1) and ferritin light chain (Ftl1), play a key role in IS. Ftl1 and Fth1 can promote microglia activation, as well as the production of inflammatory factors and chemokines. Cell communication analysis showed that activated microglia could enhance chemotactic peripheral leukocyte infiltration, such as macrophages and neutrophils, through Spp1-Cd44 and App-Cd74 signaling, thereby aggravating brain tissue damage. Furthermore, real-time quantitative polymerase chain reaction (RT-qPCR) showed that P2ry12 and Mef2c were significantly decreased in oxygen-glucose deprivation (OGD) group, while Ftl1, Fth1, Apoe, Ctsb, Cd44 and Cd74 were significantly increased in OGD group. Collectively, our findings suggested targeted therapy against microglia Ftl1 and Fth1 might improve the state of microglia, reduce the infiltration of peripheral immune cells and tissue inflammation, and then improve the ischemic brain injury in mouse.
ABSTRACT
The advantages of genetic modification and preferable physicochemical qualities make nanobody (Nb) easy to develop a sensitive and stable immunosensor platform. Herein, an indirect competitive chemiluminescence enzyme immunoassay (ic-CLEIA) based on biotinylated Nb was established for the quantification of diazinon (DAZ). The anti-DAZ Nb, named Nb-EQ1, with good sensitivity and specificity, was obtained from an immunized library via a phage display technique, where the molecular docking results indicated that the hydrogen bond and hydrophobic interactions between DAZ and complementarity-determining region 3 and framework region 2 in Nb-EQ1 played a critical role in the Nb-DAZ affinity processes. Subsequently, the Nb-EQ1 was further biotinylated to generate a bi-functional Nb-biotin, and then an ic-CLEIA was developed for DAZ determination via signal amplification of the biotin-streptavidin platform. The results showed that the proposed method based on Nb-biotin had a high specificity and sensitivity to DAZ, with a relative broader linear range of 0.12-25.96 ng/mL. After being 2-folds dilution of the vegetable samples matrix, the average recoveries were 85.7-113.9% with a coefficient of variation of 4.2-19.2%. Moreover, the results for the analysis of real samples by the developed ic-CLEIA correlated well with that obtained by reference method GC-MS (R2 ≥ 0.97). In summary, the ic-CLEIA based on biotinylated Nb-EQ1 and streptavidin recognition demonstrated itself to be a convenient tool for the quantification of DAZ in vegetables.
Subject(s)
Biosensing Techniques , Biotin , Streptavidin/chemistry , Biotin/chemistry , Diazinon , Luminescence , Biosensing Techniques/methods , Molecular Docking Simulation , Immunoassay/methods , Immunoenzyme Techniques , Enzyme-Linked Immunosorbent Assay/methodsABSTRACT
This paper deals with adaptive nonlinear identification and trajectory tracking problem for model free nonlinear systems via parametric neural network (PNN). Firstly, a more effective PNN identifier is developed to obtain the unknown system dynamics, where a parameter error driven updating law is synthesized to ensure good identification performance in terms of accuracy and rapidity. Then, an adaptive tracking controller consisting of a feedback control term to compensate the identified nonlinearity and a sliding model control term to deal with the modeling error is established. The Lyapunov approach is synthesized to ensure the convergence characteristics of the overall closed-loop system composed of the PNN identifier and the adaptive tracking controller. Simulation results for an AFS/DYC system are presented to confirm the validity of the proposed approach.
Subject(s)
Neural Networks, Computer , Nonlinear Dynamics , Computer Simulation , Feedback , Research DesignABSTRACT
Current immunoassays for herbicide detection are usually based on polyclonal or monoclonal antibodies (MAbs) raised in animals. The mammalian expression system allows the procurement of specific and highly sensitive antibodies, avoiding animal immunization. In this study, S-metolachlor-specific IgG vectors bearing either Thosea asigna virus 2A or internal ribosome entry site (S-T2A or S-IRES) and single-chain variable fragment (scFv) vectors were designed and expressed. The recombinant antibodies (RAbs) were characterized by indirect competitive enzyme-linked immunosorbent assays (icELISA). The results showed that full-length RAbs exhibited significantly better performance than scFv, and both bicistronic vectors expressed antibodies of correct size, while RAb S-T2A elicited a higher yield than RAb S-IRES. Further analyses showed that RAb S-T2A and RAb S-IRES exhibited comparable reactivities and specificities to the parental MAb, with IC50 values of 3.44, 3.89 and 3.37 ng/mL, respectively. Finally, MAb- and RAb-based icELISAs were established for the determination of S-metolachlor in environmental waters. The recoveries were in the range of 73.0-128.1%, and the coefficients of variation were mostly below 10%. This article describes the production of RAbs for S-metolachlor from mammalian cells for the first time and paves the way to develop RAb-based immunoassays for monitoring herbicide residues in the environment.