Analysing vagus nerve spontaneous activity using finite element modelling.

Objective.Finite element modelling has been widely used to understand the effect of stimulation on the nerve fibres. Yet the literature on analysis of spontaneous nerve activity is much scarcer. In this study, we introduce a method based on a finite element model, to analyse spontaneous nerve activity with a typical bipolar electrode recording setup, enabling the identification of spontaneously active fibres. We applied our method to the vagus nerve, which plays a key role in refractory epilepsy.Approach.We developed a 3D model including dynamic action potential (AP) propagation, based on the vagus nerve geometry. The impact of key recording parameters-inter-electrode distance and temperature-and uncontrolled parameters-fibre size and position in the nerve-on the ability to discriminate active fibres were quantified. A specific algorithm was implemented to detect and classify APs from recordings, and tested on six ratin-vivovagus nerve recordings.Main results.Fibre diameters can be discriminated if they are below 3µm and 7µm, respectively for inter-electrode distances of 2 mm and 4 mm. The impact of the position of the fibre inside the nerve on fibre diameter discrimination is limited. The range of active fibres identified by modelling in the vagus nerve of rats is in agreement with ranges found at histology.Significance.The nerve fibre diameter, directly proportional to the AP propagation velocity, is related to a specific physiological function. Estimating the source fibre diameter is thus essential to interpret neural recordings. Among many possible applications, the present method was developed in the context of a project to improve vagus nerve stimulation therapy for epilepsy.

Smartphone Motion Sensor-Based Complex Human Activity Identification Using Deep Stacked Autoencoder Algorithm for Enhanced Smart Healthcare System.

Human motion analysis using a smartphone-embedded accelerometer sensor provided important context for the identification of static, dynamic, and complex sequence of activities. Research in smartphone-based motion analysis are implemented for tasks, such as health status monitoring, fall detection and prevention, energy expenditure estimation, and emotion detection. However, current methods, in this regard, assume that the device is tightly attached to a pre-determined position and orientation, which might cause performance degradation in accelerometer data due to changing orientation. Therefore, it is challenging to accurately and automatically identify activity details as a result of the complexity and orientation inconsistencies of the smartphone. Furthermore, the current activity identification methods utilize conventional machine learning algorithms that are application dependent. Moreover, it is difficult to model the hierarchical and temporal dynamic nature of the current, complex, activity identification process. This paper aims to propose a deep stacked autoencoder algorithm, and orientation invariant features, for complex human activity identification. The proposed approach is made up of various stages. First, we computed the magnitude norm vector and rotation feature (pitch and roll angles) to augment the three-axis dimensions (3-D) of the accelerometer sensor. Second, we propose a deep stacked autoencoder based deep learning algorithm to automatically extract compact feature representation from the motion sensor data. The results show that the proposed integration of the deep learning algorithm, and orientation invariant features, can accurately recognize complex activity details using only smartphone accelerometer data. The proposed deep stacked autoencoder method achieved 97.13% identification accuracy compared to the conventional machine learning methods and the deep belief network algorithm. The results suggest the impact of the proposed method to improve a smartphone-based complex human activity identification framework.

[Optimization of expression conditions and activity identification of hepatocyte-targeting peptide-human endostatin].

To obtain sufficient purified and active fusion protein-hepatocyte-targeting peptide-human endostatin (HTP-rES), we studied the growth curve and the optimal induction timing of BL21/pET21b-HTP-rES. Different conditions of pH value, induction time, induction concentration and induction temperature were optimized by univariate analysis. After washing, refolding and purifying, the activity of fusion protein was identified by flow cytometry and 3-(4,5)-dimethylthiahiazo (-z-y1)-3,5-di-phenytetrazoliumromide (MTT). Results show that the logarithmic growth phase of BL21/pET21b-HTP-rES was from 1.5 h to 3.5 h, the optimum expression conditions were pH 8.0, 0.06 mmol/L IPTG, at 42 ℃ for 5 h. The purity of inclusion bodies was up to 60% after washing. The purity of target protein was more than 95% after refolding and purification. Our findings provide the foundation for further biological activity and drug development.

Optimization of expression conditions and activity identification of hepatocyte-targeting peptide-human endostatin / 生物工程学报

To obtain sufficient purified and active fusion protein-hepatocyte-targeting peptide-human endostatin (HTP-rES), we studied the growth curve and the optimal induction timing of BL21/pET21b-HTP-rES. Different conditions of pH value, induction time, induction concentration and induction temperature were optimized by univariate analysis. After washing, refolding and purifying, the activity of fusion protein was identified by flow cytometry and 3-(4,5)-dimethylthiahiazo (-z-y1)-3,5-di-phenytetrazoliumromide (MTT). Results show that the logarithmic growth phase of BL21/pET21b-HTP-rES was from 1.5 h to 3.5 h, the optimum expression conditions were pH 8.0, 0.06 mmol/L IPTG, at 42 ℃ for 5 h. The purity of inclusion bodies was up to 60% after washing. The purity of target protein was more than 95% after refolding and purification. Our findings provide the foundation for further biological activity and drug development.

Prokaryotic expression of Tir gene of enterohemorrhagic escherichia coli / 实用医学杂志

Objective To identify the immune activity of the recombinant protein Preli minarily after expressing Tir C-ter minal of enterohemorrhagic Escherichia coli(EHEC) in E.coli BL21/DE3 efficiently. Methods Tir C-ter minal (marked as Tir-C)was amplified by PCR considering the result of Bioinformatics analysis of Tir. The recombinant plasmid(designed as PET-30a(+)-Tir-C)was identified by PCR,sequencing and digested by restriction endonucleases. The positive recombinants were transformed into E.coli BL21/DE3 and induced by IPTG to express the Tir-C. The Tir-C protein was detected by SDS-PAGE and identify the antigenic of the recombinant protein Preli minarily by Western blot. Results The 675bp DNA was gained. The plasmid PET-30a (+)-Tir-C was built. Tir-C was expressed mainly in supernatant of lysis and was purified by Ni+affinity chromatograghy. Concentration of the purified protein is about 500 μg/mL and a unique band was detected with the relative molecular mass of approximately 24KDa by Western blot. Conclusion The recombinant Tir-C was expressed successfully and had immunoreactivity to some extent, which deserves the investigations for vaccine against EHEC.

The identification of recombinant human angiogenin / 中国免疫学杂志

Objective:To detect the biological activity of the recombinant human angiogenin Methods:Gel scanning was used to analyze the purity of the prepared rhANG ELISA and chicken CAM assay were used to detect specificity and biological activity The prepared rhANG was compared with the standard rhANG Results:The purity of the prepared rhANG is 96% and it could induce the angiogenesis The immunity of the prepared rhANG is better than that of the standard Conclusion:The prepared rhANG could be used for the further basic and clinical research

Isolation and Identification of Endophytic Bacteria H-6 with High Antifungal Activity from Huperzia serrata / 微生物学通报

In this study,nearly 200 endophytic bacteria were isolated from different part of Huperzia serrata, over 60 bacterium with clear antifungal activity were selected from those cultures.Among them,strain H-6 exhibited the highest antifungal activity which was strongly inhibits the growth of many plant pathogenic fungi such as Sclerotinia scleroliorum,Fusarium graminearumt,Sclerotinia libertiana,Phytophthora capsici Leonia and Sesame fusarium wilt.According to the characteristics of morphology,physiology and biochem- istry tests and the comparison of 16S rDNA sequence,the strain H-6 was similar to the Burkholderia.So strain H-6 was identified as Burkholderia sp.H-6.The results also showed that Burkholderia sp.H-6 was markedly different from Burkholderia cepacia that was applied widely in agriculture as antagonistic bacteria. The medium and culture conditions of the strain all were optimized by single factor and orthogonal experiments.In the investigation of the culture condition,growth was carried out in a basal medium(potato juice)and gradually supplemented with the various ingredients to be investigated.The major ingredients be- ing investigated included carbon sources and nitrogen sources.The optimal antifungal activity production condition is growth in a medium(potato juice with 2.5%mannitol and 0.1%NaNO3),initial pH 4.0 at 28℃.

Isolation,Identification and Bioactivity Screening of Streptomyces pseudogriseolus Associated with Marine Sponge Hymeniacidon perleve / 微生物学通报

An actinomycete B37 was isolated from an intertidal marine sponge Hymeniacidon perleve, which has strong activity against Gram positive bacteria and moderate activity against tumor cells. The mycelium and spore morphology, physiological properties and 16SrDNA sequence suggested that B37 is Streptomyces pseudogriseolus. The fermentation conditions of this strain were investigated for the biosynthesis of bioactive metabolites.