Computer Simulation of Bioprocess

Bioprocess optimization is important in order to make the bioproduction process more efficient and economic. The conventional optimization methods are costly and less efficient. On the other hand, modeling and computer simulation can reveal the mechanisms behind the phenomenon to some extent, to assist the deep analysis and efficient optimization of bioprocesses. In this chapter, modeling and computer simulation of microbial growth and metabolism kinetics, bioreactor dynamics, bioreactor feedback control will be made to show the application methods and the usefulness of modeling and computer simulation methods in optimization of the bioprocess technology

Analysis of batch and repeated fedbatch productions of Candida utilis cell mass using mathematical modeling method

Background: Candida utilis is widely used in bioindustry, and its cell mass needs to be produced in a cost effective way. Process optimization based on the experimental results is the major way to reduce the production cost. However, this process is expensive, time consuming and labor intensive. Mathematical modeling is a useful tool for process analysis and optimization. Furthermore, sufficient information can be obtained with fewer experiments by using the mathematical modeling, and some results can be predicted even without doing experiments. Results: In the present study, we performed the mathematical modeling and simulation for the cell mass production of Candida utilis based on limited batch and repeated fedbatch experiments. The model parameters were optimized using genetic algorithm (GA), and the processes were analyzed. Conclusions: Taken together, this newly developed method is efficient, labor saving and cost effective

Cyberspace and gay rights in a digital China: queer documentary filmmaking under state censorship

Owing to China’s austere censorship regulations on film media, directors of films and documentaries engaging with lesbian, gay, bisexual and transgender themes have struggled to bring their work to domestic attention. Working outside of the state-funded Chinese film industry has become necessary for these directors to commit their narratives to film, but without approval of China’s State Administration of Press, Publication, Radio, Film and Television, these artists have had little chance of achieving widespread domestic distribution of their work. However, advancements in new media technology and Web 2.0, ranging from digital video formats to Internet-based distribution via social media networks and video-hosting platforms, provide opportunities for Chinese audiences to access films and documentaries dealing with LGBT themes. This empirical study assesses how production, promotion and consumption of queer documentary films are influenced by the development of social media within Chinese cyberspace. Through close readings of microblogs from Sina Weibo this study combines analysis of contemporary research with digital social rights activism to illustrate contemporary discourse regarding film-based LGBT representation in China. Finally, the study comments on the role that documentary filmmaking plays in China’s gay rights movement, and discusses the rewards (and challenges) associated with increased levels of visibility within society

Pore Structure Characteristics and Influencing Factors of Tight Reservoirs Controlled by Different Provenance Systems: A Case Study of the Chang 7 Members in Heshui and Xin’anbian of the Ordos Basin

The evaluation of pore structure is critical in understanding reservoir characteristics. This study aims to analyze the microscopic pore structure characteristics of tight reservoirs from various provenances through physical property analysis, casting thin sections, scanning electron microscopy (SEM), and constant−rate mercury injection. The pore throat parameters of the Chang 7 reservoir were analyzed and compared to those of the Xin’anbian and the Heshui areas. The results show that intergranular pores dominate the pore type of the Chang 7 reservoir in the Xin’anbian area, followed by feldspathic dissolution pores, with high-necked and tubular throat content caused by weak compaction and dissolution, respectively. On the other hand, feldspar dissolution pores dominate the pore type of the Chang 7 reservoir in the Heshui area, followed by intergranular pores, with a high content of tube−bundle throats caused by dissolution and flake−bent flake throats caused by compaction. The difference in pore parameters between the two blocks is minimal, but the difference in throat parameters is significant. Under the same permeability conditions, the throat radius distribution range of the Chang 7 reservoir samples in the Heshui area is narrower than that in the Xin’anbian area, with tiny throats contributing significantly to reservoir permeability. Sedimentary hydrodynamic conditions and diagenesis are the primary reasons for the differences in the pores, throats, and pore structure parameters of the Chang 7 tight reservoirs

Potential Regulatory Roles of MicroRNAs and Long Noncoding RNAs in Anticancer Therapies

MicroRNAs and long noncoding RNAs have long been investigated due to their roles as diagnostic and prognostic biomarkers of cancers and regulators of tumorigenesis, and the potential regulatory roles of these molecules in anticancer therapies are attracting increasing interest as more in-depth studies are performed. The major clinical therapies for cancer include chemotherapy, immunotherapy, and targeted molecular therapy. MicroRNAs and long noncoding RNAs function through various mechanisms in these approaches, and the mechanisms involve direct targeting of immune checkpoints, cooperation with exosomes in the tumor microenvironment, and alteration of drug resistance through regulation of different signaling pathways. Herein we review the regulatory functions and significance of microRNAs and long noncoding RNAs in three anticancer therapies, especially in targeted molecular therapy, and their mechanisms. Keywords: microRNAs, long noncoding RNAs, targeted therapy, chemoresistance, immune checkpoin

A pan-cancer analysis of SLC1A5 in human cancers

Background: The alanine-serine-cysteine transporter 2, ASCT2 (solute carrier family 1 member 5, SLC1A5), is a major transporter of the amino acid, glutamine. Although SLC1A5 has been reported to be associated with some types of cancer, less pan-cancer analysis, which would give a comprehensive understanding of SLC1A5 across human cancers, has been carried out. Methods: We used the TCGA and GEO databases to investigate the oncogenic role of SLC1A5. We examined gene and protein expression, survival, genetic mutations, protein phosphorylation, immunocyte infiltration and the related genes correlated pathways. In HCT116 cells, SLC1A5 was silenced by siRNAs and the mRNA and protein was checked by Q-PCR and WB, respectively and the cellular function was assessed by CCK8, cell cycle and apoptosis. Results: We found that SLC1A5 was over-expressed in multiple types of cancer and that elevated expression of SLC1A5 was associated with poor survival in many cancers. The missense mutation of R330 H/C was associated with poor survival, especially in uterine carcinosarcoma. Furthermore, we found enhanced phosphorylation of S503 in uterine corpus endometrial carcinoma and lung adenocarcinoma. In addition, elevated SLC1A5 expression was associated with immune cell infiltration in many cancers. KEGG and GO analysis showed that SLC1A5 and its related genes were involved in central carbon metabolism in cancer, due to their amino acid transport activity. The cellular function indicated that SLC1A5 may influence the cell proliferation by affecting DNA synthesis. Conclusions: Our findings highlighted the important role of SLC1A5 in tumorigenesis and provided insights into potential cancer treatment strategies

Feature selection and embedding based cross project framework for identifying crashing fault residence

Context: The automatically produced crash reports are able to analyze the root of fault causing the crash (crashing fault for short) which is a critical activity for software quality assurance. Objective: Correctly predicting the existence of crashing fault residence in stack traces of crash report can speed up program debugging process and optimize debugging efforts. Existing work focused on the collected label information from bug-fixing logs, and the extracted features of crash instances from stack traces and source code for Identification of Crashing Fault Residence (ICFR) of newly-submitted crashes. This work develops a novel cross project ICFR framework to address the data scarcity problem by using labeled crash data of other project for the ICFR task of the project at hand. This framework removes irrelevant features, reduces distribution differences, and eases the class imbalance issue of cross project data since these factors may negatively impact the ICFR performance. Method: The proposed framework, called FSE, combines Feature Selection and feature Embedding techniques. The FSE framework first uses an information gain ratio based feature ranking method to select a relevant feature subset for cross project data, and then employs a state-of-the-art Weighted Balanced Distribution Adaptation (WBDA) method to map features of cross project data into a common space. WBDA considers both marginal and conditional distributions as well as their weights to reduce data distribution discrepancies. Besides, WBDA balances the class proportion of each project data to alleviate the class imbalance issue. Results: We conduct experiments on 7 projects to evaluate the performance of our FSE framework. The results show that FSE outperforms 25 methods under comparison. Conclusion: This work proposes a cross project learning framework for ICFR, which uses feature selection and embedding to remove irrelevant features and reduce distribution differences, respectively. The results illustrate the performance superiority of our FSE framework