Baseline Total Metabolic Tumor Volume and Total Lesion Glycolysis Measured on 18F-FDG PET-CT Predict Outcomes in T-Cell Lymphoblastic Lymphoma

Xiaoyan Feng,Xin Wen,Ling Li,Zhenchang Sun,Xin Li,Lei Zhang,Jingjing Wu,Xiaorui Fu,Xinhua Wang,Hui Yu,Xinran Ma,Xudong Zhang,Xinli Xie,Xingmin Han,Mingzhi Zhang 대한암학회 2021 Cancer Research and Treatment Vol.53 No.3

Purpose There is no optimal prognostic model for T-cell lymphoblastic lymphoma (T-LBL). Here, we discussed the predictive value of total metabolic tumor volume (TMTV) and total lesion glycolysis (TLG) measured on 18F-fluorodeoxyglucose positron emission tomography–computed tomography (PET-CT) in T-LBL.Materials and Methods Thirty-seven treatment naïve T-LBL patients with PET-CT scans were enrolled. TMTV was obtained using the 41% maximum standardized uptake value (SUVmax) threshold method, and TLG was measured as metabolic tumor volume multiplied by the mean SUV. Progression-free survival (PFS) and overall survival (OS) were analyzed by Kaplan-Meier curves and compared by the log-rank test.Results The optimal cutoff values for SUVmax, TMTV, and TLG were 12.7, 302 cm3, and 890, respectively. A high SUVmax, TMTV, and TLG indicated a shorten PFS and OS. On multivariable analysis, TMTV ≥ 302 cm3, and central nervous system (CNS) involvement predicted inferior PFS, while high SUVmax, TLG and CNS involvement were associated with worse OS. Subsequently, we generated a risk model comprising high SUVmax, TMTV or TLG and CNS involvement, which stratified the population into three risk groups, which had significantly different median PFS of not reached, 14 months, and 7 months for low-risk group, mediate-risk group, and high-risk group, respectively (p < 0.001). Median OS were not reached, 27 months, and 13 months, respectively (p < 0.001).Conclusion Baseline SUVmax, TMTV, and TLG measured on PET-CT are strong predictors of worse outcome in T-LBL. A risk model integrating these three parameters with CNS involvement identifies patients at high risk of disease progression.

A CRISPR/Cas9 Cleavage System for Capturing Fungal Secondary Metabolite Gene Clusters

( Xinran Xu ),( Jin Feng ),( Peng Zhang ),( Jie Fan ),( Wen-bing Yin ) 한국미생물생명공학회(구 한국산업미생물학회) 2021 Journal of microbiology and biotechnology Vol.31 No.1

More and more available fungal genome sequence data reveal a large amount of secondary metabolite (SM) biosynthetic ‘dark matter’ to be discovered. Heterogeneous expression is one of the most effective approaches to exploit these novel natural products, but it is limited by having to clone entire biosynthetic gene clusters (BGCs) without errors. So far, few effective technologies have been developed to manipulate the specific large DNA fragments in filamentous fungi. Here, we developed a fungal BGC-capturing system based on CRISPR/Cas9 cleavage in vitro. In our system, Cas9 protein was purified and CRISPR guide sequences in combination with in vivo yeast assembly were rationally designed. Using targeted cleavages of plasmid DNAs with linear (8.5 kb) or circular (8.5 kb and 28 kb) states, we were able to cleave the plasmids precisely, demonstrating the high efficiency of this system. Furthermore, we successfully captured the entire Nrc gene cluster from the genomic DNA of Neosartorya fischeri. Our results provide an easy and efficient approach to manipulate fungal genomic DNA based on the in vitro application of Cas9 endonuclease. Our methodology will lay a foundation for capturing entire groups of BGCs in filamentous fungi and accelerate fungal SMs mining.

Distributed smoothed rank regression with heterogeneous errors for massive data

Yuan Xiaohui,Zhang Xinran,Wang Yue,Wang Chunjie 한국통계학회 2023 Journal of the Korean Statistical Society Vol.52 No.4

Rank estimation methods are robust and highly efficient for estimating linear regression model. This paper investigates the rank regression estimation for massive data. To deal with the situation that the data are distributed heterogeneously in different blocks, we propose a weighted distributed rank-based estimator for massive data, which can improve the efficiency of the standard divide and conquer estimator. Under mild conditions, the asymptotic distributions of the weighted distributed rank-based estimator is derived. To achieve sparsity with high-dimensional covariates, the variable selection procedure is also proposed. Both simulations and data analysis are included to illustrate the finite sample performance of the proposed methods.

Bavachin Suppresses Alpha-Hemolysin Expression and Protects Mice from Pneumonia Infection by Staphylococcus aureus

( Ye Tao ),( Dazhong Sun ),( Xinran Ren ),( Yicheng Zhao ),( Hengjian Zhang ),( Tao Jiang ),( Jiyu Guan ),( Yong Tang ),( Wu Song ),( Shuqiang Li ),( Li Wang ) 한국미생물생명공학회 2022 Journal of microbiology and biotechnology Vol.32 No.10

Staphylococcus aureus (S. aureus) infection causes dramatic harm to human health as well as to livestock development. As an important virulence factor, alpha-hemolysin (hla) is critical in the process of S. aureus infection. In this report, we found that bavachin, a natural flavonoid, not only efficiently inhibited the hemolytic activity of hla, but was also capable of inhibiting it on transcriptional and translational levels. Moreover, further data revealed that bavachin had no neutralizing activity on hla, which did not affect the formation of hla heptamers and exhibited no effects on the hla thermal stability. In vitro assays showed that bavachin was able to reduce the S. aureus-induced damage of A549 cells. Thus, bavachin repressed the lethality of pneumonia infection, lung bacterial load and lung tissue inflammation in mice, providing potent protection to mice models in vivo. Our results indicated that bavachin has the potential for development as a candidate hla inhibitor against S. aureus.

Multimode participation of traditional Chinese medicine in the treatment of COVID-19

Tieying Dai,Leyin Zhang,Xinyang Dai,Xinran Zhang,Beibei Lu,Yuxi Zheng,Deyi Shen,Yici Yan,Congqi Ji,Jieru Yu,Leitao Sun 한국한의학연구원 2021 Integrative Medicine Research Vol.10 No.-

Background The outbreak of COVID-19 has swiftly spread across China and all over the world, resulting in severe contagious pneumonia. However, no specific anti-COVID-19 drugs or methods are available for the treatment of this acute and fatal disease. In recent years, as the efficacy and safety of traditional Chinese medicine (TCM) have been universally acknowledged, it has been brought to a crucial status domestically and overseas for the treatment of COVID-19. Methods We searched relevant literature, electronic databases, and official statements, diagnoses and protocols to retrieve studies and applications related to traditional Chinese medicine for COVID-19 in terms of regulations and policies, clinical evidence, preclinical rationale and big data analysis and then summarized the discovery and development of potential drugs and their targets. Results Clinicians, researchers, governments, the public, colleges, institutes and companies collected and classified associated policies, regulations and actual contributions, searched clinical trials and preclinical experimental outcomes from databases, studied potential TCM drugs with possible mechanisms, retrieved numerous big data analysis method and gathered pooled results of compounds along with their effective targets to make traditional Chinese medicine vital to cover all stages of patients in the treatment and control of COVID-19. Conclusion Traditional Chinese medicine provides new evidence to support the clinical value of TCM for COVID-19. Background The outbreak of COVID-19 has swiftly spread across China and all over the world, resulting in severe contagious pneumonia. However, no specific anti-COVID-19 drugs or methods are available for the treatment of this acute and fatal disease. In recent years, as the efficacy and safety of traditional Chinese medicine (TCM) have been universally acknowledged, it has been brought to a crucial status domestically and overseas for the treatment of COVID-19. Methods We searched relevant literature, electronic databases, and official statements, diagnoses and protocols to retrieve studies and applications related to traditional Chinese medicine for COVID-19 in terms of regulations and policies, clinical evidence, preclinical rationale and big data analysis and then summarized the discovery and development of potential drugs and their targets. Results Clinicians, researchers, governments, the public, colleges, institutes and companies collected and classified associated policies, regulations and actual contributions, searched clinical trials and preclinical experimental outcomes from databases, studied potential TCM drugs with possible mechanisms, retrieved numerous big data analysis method and gathered pooled results of compounds along with their effective targets to make traditional Chinese medicine vital to cover all stages of patients in the treatment and control of COVID-19. Conclusion Traditional Chinese medicine provides new evidence to support the clinical value of TCM for COVID-19.