Rapid elimination of scattering in three-dimensional fluorescence spectra via deep learning.

Three-dimensional fluorescence spectra are often affected by scattering effects, traditional scattering elimination methods rely excessively on parameter settings and cannot automatically eliminate scattering in batches, thereby limiting the application of fluorescence spectroscopy technology in rapid online monitoring and analysis of samples. In this study, we have developed a model based on a deep learning CycleGAN to rapidly eliminate scattering from three-dimensional fluorescence spectra. The proposed model efficiently eliminates scattering by simply inputting single or batches of contaminated fluorescent spectra. By training the CycleGAN using a large dataset of simulated three-dimensional fluorescence spectra and employing data augmentation, to the model can transform fluorescence spectra with scattering into ones without scattering. To validate the effectiveness of the proposed methed, we confirmed its generalization and reliability by eliminating scattering from two sets of previously unseen real experimental three-dimensional fluorescence spectra. We evaluated the effectiveness of scattering elimination across various noise levels and scattering widths, using metrics such as the mean absolute error, peak signal-to-noise ratio, structural similarity and cosine similarity. Furthermore, we conducted a component analysis using PARAFAC on the spectra post-scattering elimination, yielding correlation coefficients of >0.97 when compared to that in case of actual components. Finally, we compared the proposed model with traditional mathematical methods, such as blank subtraction and Delaunay triangulation. Results showed that the proposed model can automatically and efficiently eliminate scattering from fluorescence spectra in batches, substantially improving the efficiency of scattering elimination.

Electronic Properties of CrB/Co2CO2 Superlattices by Multiple Descriptor-Based Machine Learning Combined with First-Principles.

In recent times, newly unveiled 2D materials exhibiting exceptional characteristics, such as MBenes and MXenes, have gained widespread application across diverse domains, encompassing electronic devices, catalysis, energy storage, sensors, and various others. Nonetheless, numerous technical bottlenecks persist in the development of high-performance, structurally flexible, and adjustable electronic device materials. Research investigations have demonstrated that 2D van der Waals superlattices (vdW SLs) structures comprising materials exhibit exceptional electrical, mechanical, and optical properties. In this work, the advantages of both materials are combined and compose the vdW SLs structure of MBenes and MXenes, thus obtaining materials with excellent electronic properties. Furthermore, it integrates machine learning (ML) with first-principles methods to forecast the electrical properties of MBene/MXene superlattice materials. Initially, various configurations of MBene/MXene superlattice materials are explored, revealing that distinct stacking methods exert significant influence on the electronic structure of MBene/MXene materials. Specifically, the BABA-type stacking of CrB (layer A) and Co2CO2 MXene (layer B) is most stable configureation. Subsequently, multiple descriptors of the structure are constructed to predict the density of states  of vdW SLs through the employment of ML techniques. The best model achieves a mean absolute error (MAE) as low as 0.147 eV.

MiR-138-5p Inhibits Thyroid Cancer Cell Growth and Stemness by Targeting TRPC5/Wnt/ß-Catenin Pathway.

MicroRNAs play a key role in the pathogenesis of many types of cancer, including thyroid cancer (TC). MiR-138-5p has been confirmed to be abnormally expressed in TC tissues. However, the role of miR-138-5p in TC progression and its potential molecular mechanism need to be further explored. In this study, quantitative real-time PCR was used to examine miR-138-5p and TRPC5 expression, and western blot analysis was performed to examine the protein levels of TRPC5, stemness-related markers, and Wnt pathway-related markers. Dual-luciferase reporter assay was used to assess the interaction between miR-138-5p and TRPC5. Cell proliferation, stemness, and apoptosis were examined using colony formation assay, sphere formation assay, and flow cytometry. Our data showed that miR-138-5p could target TRPC5 and its expression was negatively correlated with TRPC5 expression in TC tumor tissues. MiR-138-5p decreased proliferation, stemness, and promoted gemcitabine-induced apoptosis in TC cells, and this effect could be reversed by TRPC5 overexpression. Moreover, TRPC5 overexpression abolished the inhibitory effect of miR-138-5p on the activity of Wnt/ß-catenin pathway. In conclusion, our data showed that miR-138-5p suppressed TC cell growth and stemness via the regulation of TRPC5/Wnt/ß-catenin pathway, which provided some guidance for studying the potential function of miR-138-5p in TC progression.

How do self-exempt beliefs affect intentions to quit smoking? An exploration of the mediating role of threat appraisal and coping appraisal.

Introduction: Numerous smokers are cognizant of the detrimental effects associated with this habit yet exhibit a persistent reluctance to cease their tobacco consumption. Self-exempt beliefs serve as an obstacle to the cessation of this addictive behavior. This research explored the impact of self-exempt beliefs on the readiness to quit smoking based on the Protection Motivation Theory (PMT) model and the mediating roles of threat appraisal and coping appraisal. Methods: Self-exempt beliefs, PMT constructs, and the intention to quit smoking constituted the theoretical model. The questionnaires were collected from 488 Chinese adult male smokers based on snowball sampling. Exploratory Factor Analysis (EFA) was used to examine the underlying factor structure of the pre-designed self-exempt beliefs scale. The reliability, validity, path coefficients, and explanatory power of the model were calculated using Partial Least Squares Structural Equation Modeling (PLS-SEM). Results and discussion: The results showed that : (1) three common factors (skeptic beliefs, bulletproof beliefs, and "worth it" beliefs) with a total of 11 items were retained after EFA; (2) skeptic beliefs and "worth it" beliefs had a significantly negative effect on both threat appraisal and coping appraisal, while bulletproof beliefs did not; (3) bulletproof beliefs had a significantly positive direct impact on intention to quit, "worth it" beliefs had a significantly negative direct impact on intention, while skeptic beliefs had no significantly direct impact on intention; (4) threat appraisal and coping appraisal positively and significantly predicted cessation intention; and (5) threat appraisal and coping appraisal, as two main cognitive processes, acted as full mediations between skeptic beliefs and the intention to quit, as complementary partial mediations between "worth it" beliefs and the intention, and as non-mediation between bulletproof beliefs and the intention. Our findings suggest that efforts to undermine or "prevent" these self-exempt beliefs, particularly "worth it" and skeptic beliefs, may be an effective tactic for health communication interventions for quitting smoking.

Establishment and application of multiplex droplet digital polymerase chain reaction assay for bovine enterovirus, bovine coronavirus, and bovine rotavirus.

Bovine enterovirus (BEV), bovine coronavirus (BCoV), and bovine rotavirus (BRV) are still the major worldwide concerns in the health care of cattle, causing serious economic losses in the livestock industry. It is urgent to establish specific and sensitive methods to detect viruses for the early control of diseases. Droplet digital PCR (ddPCR) has been proposed to effectively detect viral particles, and it does not involve Ct values or standard curves. In this study, we designed specific primers and probes, based on conserved regions of viral genomes, to optimize protocols for a dual ddPCR assay for detecting BCoV and BRV and a multiplex ddPCR assay for BEV, BCoV, and BRV. Sensitivity assays revealed that the lower limit of detection for qPCR was 1,000 copies/µL and for ddPCR for BEV, BCoV, and BRV, 2.7 copies/µL, 1 copy/µL and 2.4 copies/µL, respectively. Studying 82 samples collected from diarrheal calves on a farm, our dual ddPCR method detected BCoV, BRV, and co-infection at rates of 18.29%, 14.63%, and 6.1%, respectively. In contrast, conventional qPCR methods detected BCoV, BRV, and co-infection at rates of 10.98%, 12.2%, and 3.66%, respectively. On the other hand, studying 68 samples from another farm, qPCR detected BCoV, BRV, BEV, and co-infection of BCoV and BEV at rates of 14.49%, 1.45%, 5.80%, and 1.45%, respectively. Our multiplex ddPCR method detected BCoV, BRV, BEV, co-infection of BCoV and BEV, and co-infection of BRV and BEV. at rates of 14.49%, 2.9%, 8.7%, 2.9%, and 1.45%, respectively. Studying 93 samples from another farm, qPCR detected BCoV, BRV, BEV, and co-infection of BCoV and BEV was detected at rates of 5.38%, 1.08%, 18.28%, and 1.08%, respectively. Co-infection of BCoV, BRV, BEV, BCoV, and BEV, and co-infection of BRV and BEV, were detected by multiplex ddPCR methods at rates of 5.38%, 2.15%, 20.45%, 1.08%, and 1.08%, respectively. These results indicated that our optimized dual and multiplex ddPCR methods were more effective than conventional qPCR assays to detect these viral infections.

QTL Mapping and Candidate Gene Identifying for N, P, and K Use Efficiency at the Maturity Stages in Wheat.

Nitrogen (N), phosphorus (P), and potassium (K) are the three most important mineral nutrients for crop growth and development. We previously constructed a genetic map of unigenes (UG-Map) based on their physical positions using a RIL population derived from the cross of "TN18 × LM6" (TL-RILs). In this study, a total of 18 traits related to mineral use efficiency (MUE) of N/P/K were investigated under three growing seasons using TL-RILs. A total of 54 stable QTLs were detected, distributed across 19 chromosomes except for 3A and 5B. There were 50 QTLs associated with only one trait, and the other four QTLs were associated with two traits. A total of 73 candidate genes for stable QTLs were identified. Of these, 50 candidate genes were annotated in Chinese Spring (CS) RefSeq v1.1. The average number of candidate genes per QTL was 1.35, with 45 QTLs containing only one candidate gene and nine QTLs containing two or more candidate genes. The candidate gene TraesCS6D02G132100 (TaPTR gene) for QGnc-6D-3306 belongs to the NPF (NRT1/PTR) gene family. We speculate that the TaPTR gene should regulate the GNC trait.

Metabolomics-based study on the changes of endogenous metabolites during adventitious bud formation from leaf margin of Bryophyllum pinnatum (Lam.) Oken.

Bryophyllum pinnatum (Lam.) Oken is an ornamental and ethno-medicine plant, which can grow a circle of adventitious bud around the leaf margin. The dynamic change of metabolites during the development of B. pinnatum remains poorly understood. Here, leaves from B. pinnatum at four developmental stages were sampled based on morphological characteristics. A non-targeted metabolomics approach was used to evaluate the changes of endogenous metabolites during adventitious bud formation in B. pinnatum. The results showed that differential metabolites were mainly enriched in sphingolipid metabolism, flavone and flavonol biosynthesis, phenylalanine metabolism, and tricarboxylic acid cycle pathway. The metabolites assigned to amino acids, flavonoids, sphingolipids, and the plant hormone jasmonic acid decreased from period Ⅰ to Ⅱ, and then increased from period Ⅲ to Ⅳ with the emergence of adventitious bud (period Ⅲ). While the metabolites related to the tricarboxylic acid cycle showed a trend of first increasing and then decreasing during the four observation periods. Depending on the metabolite changes, leaves may provide conditions similar to in vitro culture for adventitious bud to occur, thus enabling adventitious bud to grow at the leaf edge. Our results provide a basis for illustrating the regulatory mechanisms of adventitious bud in B. pinnatum.

Retinol-binding protein-hijacking nanopolyplex delivering siRNA to cytoplasm of hepatic stellate cell for liver fibrosis alleviation.

Activated hepatic stellate cell (aHSC) is mainly responsible for deposition of extracellular collagen matrix that causes liver fibrosis. Although several siRNAs adequately inhibited HSC activation in vitro, they were demonstrated poor RNAi efficiency in vivo. Developing HSC-targeting and cytoplasmic delivery nanocarrier is highly essential to acquire a desirable siRNA therapeutic index for anti-liver fibrosis. Here, we developed a unique crosslinking nanopolyplex (called T-C-siRNA) modified by vitamin A (VA) with the well-designed natures, including the negative charge, retinol-binding protein (RBP) hijacking, and cytoplasmic siRNA release in response to ROS and cis diol molecules. The nanopolyplex was given a yolk-shell-like shape, camouflage ability in blood, and HSC-targeting capability by hijacking the endogenous ligand RBP via surface VA. PDGFR-ß siRNA (siPDGFR-ß) supplied via T-C-siPDGFR-ß nanopolyplex dramatically reduced HSC activation and its production of pro-fibrogenic proteins in vitro and in vivo. Furthermore, T-C-siPDGFR-ß nanopolyplex effectively alleviated CCl4-induced liver injury, decreased hepatic collagen sediment, and recovered liver function in mice. This study provides a sophisticated method for HSC-targeting cytoplasmic RNA delivery using endogenous ligand hijacking and dual sensitivity of ROS and cis diol compounds.

Insight into the Electronic Properties of Semiconductor Heterostructure Based on Machine Learning and First-Principles.

A first-principles approach is a powerful means of gaining insight into the intrinsic structure and properties of materials. However, with the implementation of material genetic engineering, it is still a challenging road to discover materials with high satisfaction. One alternative is to employ machine-learning techniques to mine data and predict performance. In this present contribution, the method is taken to predict the band gap opening value of graphene in a heterostructure. First, the data of 2076 binary compounds in the Materials Project library are used to achieve visual dimensionality reduction of the data set through a t-distributed stochastic neighbor embedding (t-SNE) algorithm in unsupervised learning. Then, a series of semiconductor components are screened out and form heterostructures with graphene. Second, by means of the ensemble learning EXtreme Gradient Boost (XGBoost) algorithm and support vector machine (SVM) technology, two prediction frameworks are built to predict the band gap opening value of the graphene in the system. Finally, density functional theory (DFT) is used to calculate the energy band and density of states for comparison. Analysis shows that the prediction model has an accuracy rate of 88.3%, and there is little difference between prediction results and calculation results. We anticipate that this framework model would have fascinating applications in predicting the electronic properties of various multiphase materials.

Series fusion of scatter correction techniques coupled with deep convolution neural network as a promising approach for NIR modeling.

Deep convolution neural network (CNN) with one-dimensional (1D) convolution structure is a potential and effective nonlinear method for near infrared (NIR) spectroscopy analysis. However, it is also a challenge to build a reliable CNN calibration model since industrial NIR data present serious scattering effect which will seriously interfere with important information. Thus, this paper proposed a promising approach, namely series fusion of scatter correction technologies (SCSF), where CNN built on the series splicing data of normalized raw spectra, standard normal variable (SNV) spectra and first derivative (1d) spectra. Two real NIR cases (one is the identification of alcohols/diesel blends and the other is the prediction of methanol and ethanol content in alcohols/diesel blends) were introduced to explore the feasibility and effectiveness of the presented model. Through the comparative analysis with CNN based on raw spectra, SNV spectra and 1d spectra, as well as common support vector machine (SVM) and BP neural network, the proposed SCSF coupled with CNN cannot only achieve 97.73 % recognition rate for three types of diesel, but also significantly improve the prediction accuracy of methanol and ethanol. Satisfactory results show that SCSF approach can be regarded as series boosting of multiple scatter correction technologies to improve overall performance without mastering data prior information and professional knowledge. Further, the proposed SCSF applied to CNN deep learning is simple and efficient, and can be recommended for actual implementation in industrial NIR applications.

Fine-Tuned Polymer Nanoassembly for Codelivery of Chemotherapeutic Drug and siRNA.

Successful clinical application of siRNA to liver-associated diseases reinvigorates the RNAi therapeutics and delivery vectors, especially for anticancer combination therapy. Fine tuning of copolymer-based assembly configuration is highly important for a desirable synergistic cancer cell-killing effect via the codelivery of chemotherapeutic drug and siRNA. Herein, an amphiphilic triblock copolymer methoxyl poly(ethylene glycol)-block-poly(L-lysine)-block-poly(2-(diisopropyl amino)ethyl methacrylate) (abbreviated as mPEG-PLys-PDPA or PLD) consisting of a hydrophilic diblock mPEG-PLys and a hydrophobic block PDPA is synthesized. Three distinct assemblies (i.e., nanosized micelle, nanosized polymersome, and microparticle) are acquired, along with the increase in PDPA block length. Furthermore, the as-obtained polymersome can efficiently codeliver doxorubicin hydrochloride (DOX) as a hydrophilic chemotherapeutic model and siRNA against ADP-ribosylation factor 6 (siArf6) as an siRNA model into cancer cell via lysosomal pH-triggered payload release. PC-3 prostate cell is synergistically killed by the DOX- and siArf6-coloading polymersome (namely PLD@DOX/siArf6). PLD@DOX/siArf6 may serve as a robust nanomedicine for anticancer therapy.

Characterization of Two Wheat-Thinopyrum ponticum Introgression Lines With Pyramiding Resistance to Powdery Mildew.

Powdery mildew is one of the most devastating foliar diseases in wheat production. The wild relative Thinopyrum ponticum (2n = 10x = 70) has been widely used in wheat genetic improvement due to its superior resistance to both biotic and abiotic stresses. In the present study, two wheat-Th. ponticum introgression lines named SN0293-2 and SN0293-7 were developed from the progenies of a cross between the octoploid Trititrigia SNTE20 and common wheat, including the elite cultivar Jimai 22. They had a novel powdery mildew resistance gene (temporarily named PmSN0293) putatively from Th. ponticum pyramided with Pm2 and Pm52, exhibiting excellent Pm resistance at both the seedling and adult stages. Sequential GISH-FISH detected no signal of Th. ponticum in these two lines but a pair of T1BL·1RS in SN0293-2. Chromosomal structural variations were also observed obviously in SN0293-2 and SN0293-7. Through the Wheat 660K SNP array, 157 SNPs, 134 of which were on 6A, were found to be specific to Th. ponticum. Based on the data combined with DNA re-sequencing, seven specific markers, including one CAPS marker on 2B and six CAPS and Indel markers on 6A, were developed, confirming their wheat-Th. ponticum introgression nature. Furthermore, the two lines displayed positive plant height and produced more kernels and higher 1,000-grain weight. Excellent resistance with desirable agronomic traits makes them valuable in wheat breeding programs.

Genome-wide analysis of the Tritipyrum WRKY gene family and the response of TtWRKY256 in salt-tolerance.

Introduction: The transcription factor WRKY is widespread in the plant kingdom and plays a crucial role in diverse abiotic stress responses in plant species. Tritipyrum, an octoploid derived from an intergeneric cross between Triticum aestivum (AABBDD) and Thinopyrum elongatum (EE), is a valuable germplasm resource for introducing superior traits of Th. elongatum into T. aestivum. The recent release of the complete genome sequences of T. aestivum and Th. elongatum enabled us to investigate the organization and expression profiling of Tritipyrum WRKY genes across the entire genome. Results: In this study, 346 WRKY genes, from TtWRKY1 to TtWRKY346, were identified in Tritipyrum. The phylogenetic analysis grouped these genes into three subfamilies (I-III), and members of the same subfamilies shared a conserved motif composition. The 346 TtWRKY genes were dispersed unevenly across 28 chromosomes, with 218 duplicates. Analysis of synteny suggests that the WRKY gene family may have a common ancestor. Expression profiles derived from transcriptome data and qPCR demonstrated that 54 TtWRKY genes exhibited relatively high levels of expression across various salt stresses and recovery treatments. Tel1E01T143800 (TtWRKY256) is extremely sensitive to salt stress and is on the same evolutionary branch as the salt-tolerant A. thaliana genes AtWRKY25 and AtWRKY33. From 'Y1805', the novel AtWRKY25 was cloned. The Pearson correlation analysis identified 181 genes that were positively correlated (R>0.9) with the expression of TtWRKY256, and these genes were mainly enriched in metabolic processes, cellular processes, response to stimulus, biological regulation, and regulation of biological. Subcellular localization and qRT-PCR analysis revealed that TtWRKY256 was located in the nucleus and was highly expressed in roots, stems, and leaves under salt stress. Discussion: The above results suggest that TtWRKY256 may be associated with salt stress tolerance in plants and may be a valuable alien gene for improving salt tolerance in wheat.

A polymer­calcium phosphate nanocapsule for RNAi-induced oxidative stress and cascaded chemotherapy.

As most of intracellular reactive oxygen species (ROS) is produced in the mitochondria, mitochondrial modulation of cancer cell is a promising strategy for maximizing the in situ-activable combination therapy of oxidative catastrophe and cascaded chemotherapy. Herein, a serum-stable polymer­calcium phosphate (CaP) hybrid nanocapsule carrying siRNA against ADP-ribosylation factor 6 (Arf6) overexpressed in cancer cells and parent drug camptothecin (CPT), designated as PTkCPT/siRNA, was developed for the RNAi-induced oxidative catastrophe and cascaded chemotherapy. A copolymer of mPEG-P(Asp-co-TkCPT), covalently tethered with chemotherapeutic CPT via a ROS-labile dithioketal (Tk) linker, was synthesized and self-assembled into a PTkCPT micelle as a nanotemplate for the CaP mineralization. The as-prepared PTkCPT/siRNA nanoparticle showed a core-shell-distinct nanocapsule which was consisted of a spherical polymeric core enclosed within a CaP shell capable of releasing siRNA in response to lysosomal acidity. Blocking Arf6 signal pathway of cancer cells led to their mitochondrial aggregation and subsequently induced a burst of ROS for oxidative catastrophe, which further triggered the cascaded CPT chemotherapy via the breakage of ROS-labile dithioketal linker. This strategy of RNAi-induced oxidative catastrophe and cascaded chemotherapy resulted in a significant combination effect on cancer cell killing and tumor growth inhibition in mice with low side effects, and provided a promising paradigm for precise cancer therapy.

Correction: Recent development of gene therapy for pancreatic cancer using non-viral nanovectors.

Correction for 'Recent development of gene therapy for pancreatic cancer using non-viral nanovectors' by Yu Liu et al., Biomater. Sci., 2021, DOI: 10.1039/d1bm00748c.

Recent development of gene therapy for pancreatic cancer using non-viral nanovectors.

Pancreatic cancer (PC), characterized by its dense desmoplastic stroma and hypovascularity, is one of the most lethal cancers with a poor prognosis in the world. Traditional treatments such as chemotherapy, radiotherapy, and targeted therapy show little benefit in the survival rate in patients with advanced PC due to the poor penetration and resistance of drugs, low radiosensitivity, or severe side effects. Gene therapy can modify the morbific and drug-resistant genes as well as insert the tumor-suppressing genes, which has been shown to have great potential in PC treatment. The development of safe non-viral vectors for the highly efficient delivery of nucleic acids is essential for effective gene therapy, and has been attracting much attention. In this review, we first summarized the PC-promoting genes and gene therapies using plasmid DNA, mRNA, miRNA/siRNA-based RNA interference technology, and genome editing technology. Second, the commonly used non-viral nanovector and theranostic gene delivery nanosystem, especially the tumor microenvironment-sensitive delivery nanosystem and the cell/tumor-penetrating delivery nanosystem, were introduced. Third, a combination of non-viral nanovector-based gene therapy and other therapies, such as immunotherapy, chemotherapy, photothermal therapy (PTT), and photodynamic therapy (PDT), for PDAC treatment was discussed. Finally, a number of clinical trials have demonstrated the proof-of-principle that gene therapy or the combination of gene therapy and chemotherapy using non-viral vectors can inhibit the progression of PC. Although most of the non-viral vector-based gene therapies and their combination therapy are still under preclinical research, the development of genetics, molecular biology, and novel vectors would promote the clinical transformation of gene therapy.

UPLC-MS-Based Non-targeted Analysis of Endogenous Metabolite Changes in the Leaves of Scabiosa tschiliensis Grüning Induced by 6-Benzylaminopurine and Kinetin.

In vitro propagation technology with plant growth regulators (PGRs) is generally applied in the cultivation of Scabiosa tschiliensis, which can solve collection difficulties and limited resources of S. tschiliensis. Nevertheless, comprehensive metabolomic evaluation on S. tschiliensis with PGR effects is still lacking. In this work, a non-targeted metabolomics approach, coupled with statistical and pathway enrichment analysis, was used to assess the regulatory influences of 6-benzylaminopurine (6-BA) and kinetin (KT) applied in S. tschiliensis. The results showed that the PGRs affect metabolism differentially, and the addition of 6-BA and KT can increase different secondary metabolites. In the two PGR groups, some primary metabolites such as L-phenylalanine, L-tyrosine, L-arginine, L-asparagine, and D-proline were significantly reduced. We suspect that under the action of PGRs, these decreased amino acids are derived into secondary metabolites such as umbelliferone, chlorogenic acid, and glutathione. Additionally, some of those secondary metabolites have a biological activity and can also promote the plant growth. Our results provide a basis for the targeted cultivation and utilization of S. tschiliensis, especially the expression of metabolites related to PGR application.

Retracted: Allopregnanolone restores the tyrosine hydroxylase-positive neurons and motor performance in a 6-OHDA-injected mouse model.

AIMS: It has been reported that allopregnanolone (APα) promotes the neurogenesis of the neural progenitor cells (NPCs) in the subventricular zone (SVZ) and prevents the decrease of dopaminergic neurons in 6-hydroxydopamine (6-OHDA)-treated mice by binding to γ-aminobutyric acid A receptor (GABAAR) and then opening voltage-gated L-type Ca2+ channel, but the underlying mechanisms remain elusive. The aim of this study was to explore the possible involvement of GABAAR and calcium/calmodulin-dependent protein kinase II delta 3 (CaMKIIδ3) in this process. METHODS: 6-OHDA-treated mice and primary cultured midbrain cells were administrated with APα and GABAAR antagonist bicuculline (Bic), and the proliferation and differentiation of NPCs, the tyrosine hydroxylase (TH)-positive neurons and their fibers, the expression levels of CaMKIIδ3 and brain-derived neurotrophic factor (BDNF), and motor functions were measured using ELISA, immunohistochemical staining, real-time RT-PCR, Western blot, and behavioral test. RESULTS: Allopregnanolone significantly promoted the phosphorylation of cytoplasmic CaMKIIδ3 and its nuclear translocation by binding to GABAAR, which, in turn, increased the expression levels of BDNF. This may account for the findings that the exogenous APα enhanced the proliferation and differentiation of NPCs, and ameliorated the nigrostriatal system and behavioral performance in 6-OHDA-treated mice. CONCLUSIONS: Allopregnanolone may directly activate GABAAR, which, in turn, enhance the proliferation and differentiation of NPCs via upregulating the expression levels of CaMKIIδ3, and finally contribute to the restoration of dopaminergic neurons in 6-OHDA-treated mice.

A signal cascade amplification strategy based on RT-PCR triggering of a G-quadruplex DNAzyme for a novel electrochemical detection of viable Cronobacter sakazakii.

Cronobacter sakazakii is an important opportunistic food-borne pathogen, and it can cause severe diseases with main symptoms including neonatal meningitis, necrotizing enterocolitis, and sepsis. For the achievement of practical and convenient detection of viable C. sakazakii, a simple and robust strategy based on the cascade signal amplification of RT-PCR triggered G-quadruplex DNAzyme catalyzed reaction was firstly used to develop an effective and sensitive DNAzyme electrochemical assay. Without viable C. sakazakii in the samples there are no RT-PCR and DNAzyme products, which can cause a weak electrochemical response. Once viable C. sakazakii exists in the samples, an obvious enhancement of the electrochemical response can be achieved after the target signal is amplified by RT-PCR and the resulting DNAzyme, which catalyze the oxidation of 3,3',5,5'-tetramethylbenzidine (TMB) by H2O2 with the assistance of the cofactor hemin. Our novel assay can be performed in a range of 2.4 × 107 CFU mL-1 to 3.84 × 104 CFU mL-1 (R2 = 0.9863), with a detection limit of 5.01 × 102 CFU mL-1. Through the assay of 15 real samples, electrochemical detection assay provided the same results as conventional detection methods. Therefore, detection of viable C. sakazakii based on G-quadruplex DNAzyme electrochemical assay with RT-PCR demonstrates the significant advantages of high sensitivity, low cost and simple manipulation over existing approaches and offers an opportunity for potential application in pathogen detection.