Improving the expression of recombinant pullulanase by increasing mRNA stability in Escherichia coli

Background: Pullulanase production in both wild-type strains and recombinantly engineered strains remains low. The Shine-Dalgarno (SD) sequence and stem-loop structure in the 5\u2032 or 3\u2032 untranslated region (UTR) are well-known determinants of mRNA stability. This study investigated the effect of mRNA stability on pullulanase heterologous expression. Results: We constructed four DNA fragments, pulA, SD-pulA, pulA-3t, and SD-pulA-3t,whichwere cloned into the expression vector pHT43 to generate four pullulanase expression plasmids. The DNA fragment pulA was the coding sequence (CDS) of pulA in Klebsiella variicola Z-13. SD-pulA was constructed by the addition of the 5\u2032 SD sequence at the 5\u2032 UTR of pulA. pulA-3t was constructed by the addition of a 3\u2032 stem-loop structure at the 3\u2032 UTR of pulA. SD-pulA-3t was constructed by the addition of the 5\u2032 SD sequence at the 5\u2032 UTR and a 3\u2032 stem-loop structure at the 3\u2032 UTR of pulA. The four vectors were transformed into Escherichia coli BL21(DE3). The pulA mRNA transcription of the transformant harboring pHT43-SD-pulA-3t was 338.6%, 34.9%, and 79.9% higher than that of the other three transformants, whereas the fermentation enzyme activities in culture broth and intracellularly were 107.0 and 584.1 times, 1.2 and 2.0 times, and 62.0 and 531.5 times the amount of the other three transformants (pulA, SD-pulA, and pulA-3 t), respectively. Conclusion: The addition of the 5\u2032 SD sequence at the 5\u2032 UTR and a 3\u2032 stem-loop structure at the 3\u2032 UTR of the pulA gene is an effective approach to increase pulA gene expression and fermentation enzyme activity

Non-Data Aided Rician Parameters Estimation in Temporal Fading Channel With 3 DoFs Gaussian Mixture Model

Rician distribution has been widely utilized to describe wireless fading channel. In the non-stationary temporal fading channel like industrial scenarios, both the specular and scattered components of the multi-path fading channel will be time varying. As a result, the online estimation of Rician parameters is necessary to provide stable wireless service. The traditional estimation approaches of Rician parameters are designed for channel measurement usage and therefore have to work in the data-aided mode for online estimation with modulated I/Q samples. To solve this problem, some non-data-aided algorithms have been proposed in recent years, but only valid in specific scenarios. In this paper, we formulate the estimation of Rician parameters from modulated I/Q samples as a two-dimensional Gaussian mixture model to provide a general non-data-aided Rician parameter estimation method. By involving a priori information of modulation scheme and the motivation of optimized gradient searching, the independent parameters in the maximum likelihood estimation can be significantly decreased to three, which leads to fast convergence of the modified expectation-maximization algorithm with high accuracy. The combination of these modifications has been finally formulated as a Rician mixture model. The numerical results and field measurements illustrate the feasibility of this methodology

Image_3_Orange-derived and dexamethasone-encapsulated extracellular vesicles reduced proteinuria and alleviated pathological lesions in IgA nephropathy by targeting intestinal lymphocytes.tif

Current evidence highlights the critical role of the gut-kidney axis in the pathogenesis of IgA nephropathy (IgAN). However, few attempts have been made to explore targeted intestinal immunity therapy. This research aims to develop an oral intestine targeting medication based on extracellular vesicles (EVs) and investigate its therapeutic efficacy in IgAN. EVs were isolated from orange juice and electroporated with dexamethasone sodium phosphate (DexP). After oral administration, EVs-DexP was picked up by lymphocytes in the submucosal area of ileocecum. EVs-DexP outperformed DexP not only in suppressing lymphocyte stimulation in vitro but also in alleviating renal pathological lesions in the IgAN mouse model. Clinical improvement was accompanied by a reducing IgA secreted by the intestine and a decreasing IgA + B220 + lymphocytes in Peyer’s patches. The present study develops a cost-effective, biofriendly EVs-based glucocorticoid strategy for IgAN.</p

Image_1_Orange-derived and dexamethasone-encapsulated extracellular vesicles reduced proteinuria and alleviated pathological lesions in IgA nephropathy by targeting intestinal lymphocytes.tif

Current evidence highlights the critical role of the gut-kidney axis in the pathogenesis of IgA nephropathy (IgAN). However, few attempts have been made to explore targeted intestinal immunity therapy. This research aims to develop an oral intestine targeting medication based on extracellular vesicles (EVs) and investigate its therapeutic efficacy in IgAN. EVs were isolated from orange juice and electroporated with dexamethasone sodium phosphate (DexP). After oral administration, EVs-DexP was picked up by lymphocytes in the submucosal area of ileocecum. EVs-DexP outperformed DexP not only in suppressing lymphocyte stimulation in vitro but also in alleviating renal pathological lesions in the IgAN mouse model. Clinical improvement was accompanied by a reducing IgA secreted by the intestine and a decreasing IgA + B220 + lymphocytes in Peyer’s patches. The present study develops a cost-effective, biofriendly EVs-based glucocorticoid strategy for IgAN.</p

Anatomically-aided PET reconstruction using the kernel method

This paper extends the kernel method that was proposed previously for dynamic PET reconstruction, to incorporate anatomical side information into the PET reconstruction model. In contrast to existing methods that incorporate anatomical information using a penalized likelihood framework, the proposed method incorporates this information in the simpler maximum likelihood (ML) formulation and is amenable to ordered subsets. The new method also does not require any segmentation of the anatomical image to obtain edge information. We compare the kernel method with the Bowsher method for anatomically-aided PET image reconstruction through a simulated data set. Computer simulations demonstrate that the kernel method offers advantages over the Bowsher method in region of interest (ROI) quantification. Additionally the kernel method is applied to a 3D patient data set. The kernel method results in reduced noise at a matched contrast level compared with the conventional ML expectation maximization (EM) algorithm