The distribution of small biomolecules, particularly amino acids (AAs), differs between normal cells and cancer cells. Imaging this distribution is crucial for gaining a deeper understanding of their physiological and pathological significance. Matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI MSI) provides accurate in situ visualization information. However, the analysis of AAs remains challenging due to the background interference by conventional MALDI matrices. On tissue chemical derivatization (OTCD) MSI serves as an important approach to resolve this issue. We designed, synthesized, and tested a series of pyridinium salt probes and screened out the 1-(4-(((2,5-dioxopyrrolidin-1-yl)oxy)carbonyl)phenyl)-2,4,6-triphenylpyridin-1-ium (DCT) probe with the highest reaction efficiency and the most effective detection. Moreover, a quantum chemistry calculation was executed to address mechanistic insight into the chemical nature of the novel probes. DCT was found to map 20 common AAs in normal mouse tissues for the first time, which allowed differentiation of AA distribution in normal, normal interstitium, tumor, and tumor interstitium regions and provided potential mechanistic insights for cancer research and other biomedical studies.
Research on soil contamination has become increasingly important, but there is limited information about where to sample for pollutants. Thus, the use of three-dimensional (3D) spatial interpolation techniques has been promoted in this area of study. However, the application of traditional interpolation methods is limited in geography, especially in the expression of anisotropy, and it is not associated with geographical properties. To address this issue, we used a test site (a factory in Nanjing) to develop a new research method based on the geographical shading radial basis function (RBF) interpolation method, which considers 3D anisotropy and geographical attribute expression. Drilling and uniform sampling were used to sample the contaminated area at this test site. This approach included two steps: i) An ellipsoid with anisotropic properties was constructed. Thus, the first step was to determine the shape of the ellipsoid using principal component analysis (PCA) to determine the main orientations and construct a rotational and stretched matrix. The second step was determining the ellipsoid size by computing the range using the variogram method for orientations. ii) During field measurement, the geospatial direction influences soil attribute values, so a shadowing calculation method was derived for quadratic weight determination. Then, the weight of the attribute value of known points can be assigned to meet the field conditions. Lastly, the model was evaluated using the root mean square error (RMSE). For the 2D space, the RMSE values of Kriging, RBF, and the proposed method are 6.09, 7.12, and 5.02, respectively. The R 2 values of Kriging, RBF, and the proposed method are 0.871, 0.832, and 0.946, respectively. For the 3D space, the RMSE values of Kriging, RBF, and the proposed method are 2.65, 2.23, and 2.58, respectively. The R 2 values of Kriging, RBF, and the proposed method are 0.934, 0.912, and 0.953, respectively. The resulting fitted model was relatively smooth and met experimental needs. Thus, we believe that the interpolation method can be applied as a new method to predict the distribution of soil pollutants.
Objective:To optimize extraction process of Schisandra chinensis fruit by central composite design/response surface method.Method: Independent variables were ethanol concentration,extraction time and solvent ratio,dependent variable was extraction rate of total saponins in S.chinensis.Linear or no-linear mathematic models were used to estimate relationship between independent and dependent variables.Response surface methodology was used to optimize extraction process,prediction was carried out through comparing observed and predicted values.Result: Optimal conditions of extraction process were as following:extracted 3 times with 85% ethanol for 170 min each time.The bias between observed and predicted values was 0.19%.Regression coefficients of binomial fitting complex model was as high as 0.994 2.Conclusion: This extraction process of S.chinensis fruit by central composite design/response surface methodology was simple,high precision,good predictability.
Kallistatin (Kal) is a negative acute phase endogenous protein which can inhibit tumor angiogenesis, growth and metastasis effectively. To express and purify recombinant human kallistatin (rHKal), and characterize its biological activity, P. pastoris was transformed with pPIC9-Kal/GS115 (His4) to express rHKal. The fermentation was carried out in a 7.5 L bioreactor with high density cell culture. 1%-2% methanol was added to the medium to induce the expression of rHKal. The secretion was purified with phenyl sepharose, G-25 sepharose, heparin sepharose and Sephacryl S-100 chromatography. The biological activity of purified bulk rHKal on HUVEC was evaluated with MTT and tube formation assays. The final expression of rHKal in the supernatant reached 50 mg x L(-1), the purity of bulk rHKal after purification was above 98%. A dose-dependent inhibition of rHKal on HUVEC proliferation was observed, however, a U-shaped dose-response curve of rHKal on capillary formation of HUVEC was revealed. The described protocol provides an effective means for preparing rHKal that could be used for anti-angiogenesis therapy in the future.
Topic: 22. Stem cell transplantation - Clinical Background: Relapse is still the main cause of death for hematological neoplasm patients after allogeneic hematopoietic stem cell transplantation (allo-HSCT). Effective prediction of relapse risk after transplantation can help clinicians judge whether to give intervention measures and what kind of intervention measures to give. Second-generation sequencing (NGS) technology has been widely used in the risk stratification and prognosis judgment of hematological neoplasms. Whether the gene variation detected with NGS after transplantation can predict the recurrence after transplantation is worthy of further study. Aims: To evaluate the changes of gene variation in patients with hematological neoplasms at the time of diagnosis and after allo-HSCT, and the relationship between gene mutation and recurrence after transplantation. Methods: 76 patients with hematological neoplasms were analyzed retrospectively, including 55 AML, 16 ALL, 4 MDS, 1 MAL and 1 CML. The median age was 35 years, with 42 males and 34 females. Among 76 patients, 13 were MDS-HSCT, 12 were MUS-HSCT, and 51 were haplo-HSCT. All patients underwent NGS of hematological neoplasms variation genes at the time of diagnosis and 28 days after transplantation. Results: Primary and Secondary variations were detected in 70 of 76 patients during diagnosis. Common variations include CEBPA (14/76), NRAS (10/76), FLT3 (8/76), DNMT3A (8/76), TP53 (6/76), etc. After transplantation, only 25 patients had variations, including ABCB1 (27/76), CYP2C19 (10/76). The above NGS detection results suggest that the number of primary and Secondary variations after transplantation is significantly reduced (p=0.019), and ABCB1 (27/76) and CYP2C19 are the main variation forms. SNP variations were detected in 42 of 76 patients at diagnosis, and GATA2 (20/76) and TET2 (21/76) variations were the most common variation forms. SNP variations of GATA2 and TET2 increased significantly after transplantation, 48/76 and 52/76 respectively. The increase of GATA2/TET2 double variation was more significant after transplantation (15/76 vs. 41/76, P<0.001). The increased variation frequency of GATA2 and TET2 after transplantation may be related to the mixed chimerism at the early stage of transplantation, which needs to be observed for a long time. Eight of 76 patients recurred after transplantation. The single factor competitive risk model showed that the presence of primary and Secondary variations after transplantation was an independent risk factor for recurrence (P=0.017) (Figure 1). Among them, the variation of TET2 gene has a good predictive effect on the recurrence after transplantation (P<0.001). The primary and secondary variations before transplantation, SNP variations before and after transplantation had no effect on recurrence after transplantation. The schemes of transplantation in 25 patients with primary and secondary variations after transplantation were analyzed, including 9 cases of MSD-HSCT, 11 cases of haplo-HSCT, and 5 cases of MUD-HSCT. It suggests that relative donors are more likely to have primary and secondary variations related to diseases. We used Fisher’s Exact Test to analyze the relationship between ASXL1, TP53, GATA2, RUNX1 and other high-risk variations at the time of diagnosis/after transplantation and recurrence, and did not find that the presence of these gene variations would increase the risk of recurrence after transplantation. Summary/Conclusion: The NGS gene variation detection before and after transplantation can predict the recurrence after transplantation. Large samples and long-term monitoring are also needed to find a more accurate variation pattern to predict the recurrence of hematological neoplasms after transplantation.Keywords: HSCT
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