Microscale to Manufacturing Scale-up of Cell-Free Cytokine Production—A New Approach for Shortening Protein Production Development Timelines

Engineering robust protein production and purification of correctly folded biotherapeutic proteins in cell-based systems is often challenging due to the requirements for maintaining complex cellular networks for cell viability and the need to develop associated downstream processes that reproducibly yield biopharmaceutical products with high product quality. Here, we present an alternative Escherichia coli-based open cell-free synthesis (OCFS) system that is optimized for predictable high-yield protein synthesis and folding at any scale with straightforward downstream purification processes. We describe how the linear scalability of OCFS allows rapid process optimization of parameters affecting extract activation, gene sequence optimization, and redox folding conditions for disulfide bond formation at microliter scales. Efficient and predictable high-level protein production can then be achieved using batch processes in standard bioreactors. We show how a fully bioactive protein produced by OCFS from optimized frozen extract can be purified directly using a streamlined purification process that yields a biologically active cytokine, human granulocyte-macrophage colony-stimulating factor, produced at titers of 700 mg/L in 10 h. These results represent a milestone for in vitro protein synthesis, with potential for the cGMP production of disulfide-bonded biotherapeutic proteins. Biotechnol. Bioeng. 2011; 108:1570–1578. © 2011 Wiley Periodicals, Inc

Ethyl methanesulfonate mutant library construction in Neopyropia yezoensis to provide germplasm resources for next-generation genome-selection breeding

With the development of the laver industry, germplasm depression has become a serious issue, and current cultivars cannot adapt to different aquaculture regions. In order to increasing the genetic diversity and developing more germplasm sources, it is urgent and reasonable to construct a mutant library with more new germplasms. In this research, a mutant library was constructed by ethyl methanesulfonate (EMS)-mutagenized archeospores, and the most optimal treatment procedure was determined by performing different mutagen concentrations (2.25%) and treatment times (30 min). A total of 1860 haploid thalli were produced as the M1 mutant population and further cultured into conchocelis clones for the reservation of germplasm resources. Among these, 667 individual thalli were evaluated for their phenotypic traits, including thallus length, thallus width, length/width, thallus shape, photosynthesis ability, thallus color, thallus margin, and specific growth speed. The mutation frequency of the length/width ratio was 17.39%, Fv/Fm and NPQ were 21.84% and 29.35%, respectively, and SGR was 13.59%. The mutation frequency of thallus color was 0.91%. This work may not only provide a basic practical reference guide for EMS-based mutant library construction for other seaweeds but, more importantly, also serve as a valuable resource for functional genomics research and laver breeding

HECT, UBA and WWE domain containing 1 represses cholesterol efflux during CD4+ T cell activation in Sjögren’s syndrome

Introduction: Sjögren’s syndrome (SS) is a chronic autoimmune disorder characterized by exocrine gland dysfunction, leading to loss of salivary function. Histological analysis of salivary glands from SS patients reveals a high infiltration of immune cells, particularly activated CD4+ T cells. Thus, interventions targeting abnormal activation of CD4+ T cells may provide promising therapeutic strategies for SS. Here, we demonstrate that Hect, uba, and wwe domain containing 1 (HUWE1), a member of the eukaryotic Hect E3 ubiquitin ligase family, plays a critical role in CD4+ T-cell activation and SS pathophysiology.Methods: In the context of HUWE1 inhibition, we investigated the impact of the HUWE1 inhibitor BI8626 and sh-Huwe1 on CD4+ T cells in mice, focusing on the assessment of activation levels, proliferation capacity, and cholesterol abundance. Furthermore, we examined the therapeutic potential of BI8626 in NOD/ShiLtj mice and evaluated its efficacy as a treatment strategy.Results: Inhibition of HUWE1 reduces ABCA1 ubiquitination and promotes cholesterol efflux, decreasing intracellular cholesterol and reducing the expression of phosphorylated ZAP-70, CD25, and other activation markers, culminating in the suppressed proliferation of CD4+ T cells. Moreover, pharmacological inhibition of HUWE1 significantly reduces CD4+ T-cell infiltration in the submandibular glands and improves salivary flow rate in NOD/ShiLtj mice.Conclusion: These findings suggest that HUWE1 may regulate CD4+ T-cell activation and SS development by modulating ABCA1-mediated cholesterol efflux and presents a promising target for SS treatment

An Adaptive Sampling Framework for Life Cycle Degradation Monitoring

Data redundancy and data loss are relevant issues in condition monitoring. Sampling strategies for segment intervals can address these at the source, but do not receive the attention they deserve. Currently, the sampling methods in relevant research lack sufficient adaptability to the condition. In this paper, an adaptive sampling framework of segment intervals is proposed, based on the summary and improvement of existing problems. The framework is implemented to monitor mechanical degradation, and experiments are implemented on simulation data and real datasets. Subsequently, the distributions of the samples collected by different sampling strategies are visually presented through a color map, and five metrics are designed to assess the sampling results. The intuitive and numerical results show the superiority of the proposed method in comparison to existing methods, and the results are closely related to data status and degradation indicators. The smaller the data fluctuation and the more stable the degradation trend, the better the result. Furthermore, the results of the objective physical indicators are obviously better than those of the feature indicators. By addressing existing problems, the proposed framework opens up a new idea of predictive sampling, which significantly improves the degradation monitoring

A three-dimensional vibration data compression method for rolling bearing condition monitoring

In condition monitoring for rolling bearings, it has achieved good diagnostic performance and clear mechanistic interpretation based on vibration data. The high sampling frequency of data collection preserves fault characteristics but brings the problem of big data. An effective way to reduce this problem is to apply data compression. However, in order not to affect the diagnostic performance of data, it is difficult to improve the compression ratio further. Inspired by the binarization method, the compression dimension of the bit cost of a single sample point is first introduced into the fault-mechanism-based method in this article. On this basis, a three-dimensional data compression method is proposed, and it is subsequently validated with two real-bearing datasets. Two performance metrics, including a newly defined one, are utilized to compare the proposed method with the five existing methods. The comparison results show that the proposed method significantly improves the compression ratio of data but maintains good diagnostic performance.This work was supported in part by the National Key Research and Development Program of China under Grant 2018YFB1702400, in part by the Key Research and Development Program of Sichuan Province under Grant 23ZDYF0212, and in part by the China Scholarship Council with a Scholarship under Grant 202106070089

Real-time fall detection system based on deep learning and infrared array sensors

In this paper, a novel fall detection algorithm based infrared image is proposed. Firstly, the RetinexNet algorithm is adopted for the infrared image pre-processing and enhancement, then the YOLOv3 algorithm is improved by adding three bounding boxes to achieve the task of falling posture detection and recognition, finally a fall data set collected by ourselves is utilized to train and test the algorithm. The experimental results shows that our proposed algorithm achieves excellent fall detection accuracy result and outperforms the traditional YOLOv3 algorithm, the average accuracy of our proposed algorithm is more than 90.86%, which meets the requirements of the fall detection task quite well

Scenario simulation of land use change and carbon storage response in Henan Province, China: 1990–2050

The carbon storage service of terrestrial ecosystems has an veritable impact on the global carbon cycle and, in turn, on global climate change. Hence, both assessing and predicting the impact of land use changes on carbon storage are necessary to reduce carbon emissions and mitigate climate change. Therefore, using integrated valuation of ecosystem services and tradeoffs (InVEST) model with remote sensing data, this study systematically analyzes the land use/cover change (LUCC) and the carbon storage response characteristics of land types in Henan Province, China in the 1990–2020 period. The study also uses patch-generating land use simulation (PLUS) model to predict the LUCC and carbon storage in Henan Province from 2023 to 2050 under different scenarios, including Business as Usual (BAU), Ecological Conservation (EC), and Urban Development (UD) scenarios. The following results are noted: (1) The LUCC mainly comprises the conversion of farmland to construction land. Presently, Henan Province’s carbon storage is found to have decreased by 339.72 Tg due to LUCC, which is characterized as “high in the west and low in the east.” (2) Regarding the three aforementioned scenarios, the province’s construction land is predicted to increase to its greatest extent under the UD scenario. Under the EC scenario, its woodland and farmland areas will be effectively protected. Therefore, the highest level of carbon reserves will likely be found in the EC scenario, followed by that in the BAU scenario, while the lowest level of carbon reserves should be seen in the UD scenario. The carbon reserves of Henan Province in 2050 will be 312.07 Tg, 233.43 Tg, and 394.49 Tg lower than that in 2020 under the BAU, EC, and UD scenarios, respectively. In sum, this study provides the scientific basis of the decisions aimed at the facilitation of low-carbon development, the optimal utilization of land spaces, and the development of an ecological civilization in Henan Province