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	1. Screening of strains from reconstituted tobacco sheet making high-yield enzymes and aroma
	Yang Chunxue,Deng Zhang,Liao xiang ru,Guan Zhengbing
	Biology 01 March 2023
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	Abstract:Reconstituted tobacco sheet (RTS) is critical to reduce the harm of cigarettes and considered as a comprehensive utilization approach for tobacco wastes in the tobacco industries. The aim of this study was to screen out bacteria from RTS materials capable of producing a high total amount of enzymes and aroma. A total of 21 strains with unique morphologies were obtained. Based on the results of enzymes and aroma producing capacities of the strains, one strain was screened. This strain, which was named B-NS-7, was capable of producing a total amount of 696.3 U/mL protease activity, 238.4 U/mL amylase activity, 64.3 U/mL pectinase activity and 100.0 μg/mL aroma. Combined with the results of the 16S rDNA sequencing, physiological and biochemical characteristics B-NS-7 was identified as Bacillus subtilis. Through a series of single factor experiences, the results showed that under the conditions of inoculation concentration of 1%, fermentation temperature of 37 C and time of 24 h, the highest aroma content of concentrated solutions were 116.3 μg/mL. Neophytadiene was responsible for the majority of the fragrance enhancement, and B-NS-7 was identified as an aldehydic and alkene-flavoured strain. The sensory quality of tobacco concentration solutions was superior under optimal conditions. This strain has been deposited at the China General Microbiological Culture Collection Center (CGMCC No. 23716). By way of this study, B. subtilis B-NS-7 was intended to be used in the manufacturing of RTS through microbial fermentation to improve the quality and providing suggestions for the microbial development of the RTS industry.
	TO cite this article:Yang Chunxue,Deng Zhang,Liao xiang ru, et al. Screening of strains from reconstituted tobacco sheet making high-yield enzymes and aroma[OL].[ 1 March 2023] http://en.paper.edu.cn/en_releasepaper/content/4759360


	2. Personalized prognostic signature for lung cancer based on 15 transcription-related gene pairs
	Liao Zili,Ren Zhihao,Zhang Boxiang,Zhu Ruiyu
	Biology 15 February 2023
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	Abstract:Lung cancer is the most aggressive malignancy and the leading cause of cancer deaths worldwide. Currently, reliable biomarkers are lacking in the diagnosis, prognosis and treatment of lung cancer. Given the significant role of transcription factors in tumorigenesis and progression, we aimed to establish a signature based on transcription-related gene pairs for the first time to predict the prognosis of lung cancer patients. The gene expression data and clinical information of 1568 lung cancer patients were obtained from The Cancer Genome Atlas data portal (TCGA) and Gene Expression Omnibus (GEO) as a training cohort and validation cohort, respectively. Through univariate Cox analysis and Least Absolute Shrinkage and Selection Operator (LASSO) analysis, we screened 15 transcription-related gene pairs to construct the transcription-related prognostic signature. Based on this signature, the samples were classified into high-risk group and low-risk group. Kaplan-Meier analysis and independent prognostic analysis showed that transcription-related prognostic signature predicted overall survival in lung cancer patients (p < 0.001). Compared with multiple clinical and pathological factors, the results of multivariate Cox regression analysis indicated that the signature was an independent prognostic factor in patients with lung cancer. Further analysis revealed the cellular pathways associated with this signature and the relationship between this signature and immune cell content. In conclusion, we established for the first time the signature of transcription-related genes on prognosis as an indicator to assess the overall survival in lung cancer patients. Our study provides new ideas for developing cancer prognostic signature and discovering new drug targets.
	TO cite this article:Liao Zili,Ren Zhihao,Zhang Boxiang, et al. Personalized prognostic signature for lung cancer based on 15 transcription-related gene pairs[OL].[15 February 2023] http://en.paper.edu.cn/en_releasepaper/content/4759077


	3. Characterization and comparison of lipids in ker-nels of two Camellia oleifera cultivars based on LC-MS/MS
	GuoPeng,FenglinChen,ZhaotongHe,YunyunDing,ShuaiJiang,ShucanLiu,XinhongGUO
	Biology 16 November 2022
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	Abstract:Camellia oleifera Abel. is an evergreen oil-bearing tree and widely cultivated in China. Camellia oleifera oil is considered to be a healthiest edible oil. However, the lipid profile are not well studied and ultilized. In the current study, we used non-targeted LC-MS/MS method to describe the lipid profiles of two C. oleifera cultivars. Stringent criteria was used to screen significantly different lipids metabolites (SDLs). By comparing CL3 with CL5, 79 SDLs in CL3 were found to be significantly up-regulated, and 61 SDLs were found to be significantly down-regulated. Correlation analysis indicated that intra-category and inter-category correlation of glycerolipids and glycerophospholipids were strong in CL3 and CL53 cultivars. Through pathway enrichment analysis, we found that the most influential pathway in two cultivars was the glycerophospholipid metabolism pathway. The present results provide essential insights into lipid composition and a basis to make better ultilization of the lipids
	TO cite this article:GuoPeng,FenglinChen,ZhaotongHe, et al. Characterization and comparison of lipids in ker-nels of two Camellia oleifera cultivars based on LC-MS/MS[OL].[16 November 2022] http://en.paper.edu.cn/en_releasepaper/content/4758414


	4. Recombinant expression, fermentation and characterization of a type Ⅲ human like collagen
	XIANG Zhixiang,GONG Jingsong,XU Zhenghong,SHI Jingsong
	Biology 12 May 2022
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