Development of a double-antibody sandwich ELISA targeting the receptor binding domain of TcdB toxin of ST11 type Clostridium difficile of porcine origin / 生物工程学报

Clostridium difficile is an important zoonotic intestinal pathogen, which is widely present in humans and a variety of animals. The ST11 type C. difficile is one of the most widespread and harmful subtypes in the world. As a large country in pig farming, China lacks efficient methods for detecting C. difficile of porcine origin, leaving hidden dangers for the prevention and control of C. difficile. The aim of this study was to develop a specific and sensitive double-antibody sandwich ELISA for the epidemiological investigation of ST11 type C. difficile of porcine origin. Firstly, a 97 kDa receptor binding domain (RBD) was expressed in a prokaryotic host and purified. A hybridoma cell line AE2D3 capable of stably secreting monoclonal antibody targeting the RBD was screened, and the antibody subtype was determined to be IgG2b (κ). Secondly, a double antibody sandwich ELISA method was developed, where the monoclonal antibody targeting the RBD was used as a detection antibody, and the rabbit polyclonal antibody was used as a capture antibody. The chessboard method was used to determine the matching concentration of the capture antibody and the detection antibody, the antigen coating conditions, the blocking conditions, the incubation conditions for detection antibody and samples to be tested, as well as the reaction conditions of HRP-conjugated and reaction conditions of TMB chromogenic solution. The negative cutoff OD450 was 0.152, and no cross-reaction with 13 strains of non-ST11 type C. difficile was found. The minimum detection concentration of RBD was 8.83 ng/mL. This specific and sensitive double-antibody sandwich ELISA provides a reliable serological detection method for epidemiological investigation of the ST11 type C. difficile in pig industry.

Diffusional kurtosis imaging value for assessment of liver cancer and tumoral cell invasion of peritumoral zone / 中华放射学杂志

Objective Study the apply of diffusional kurtosis imaging(DKI) value to assess liver cancer and tumoral cell invasion of peritumoral liver zone. Methods This research belonging to prospective study which included 24 patients with liver cancer and confirmed by clinical history and imaging features(liver cancer group), 10 healthy volunteers as control group. The liver cancer group underwent MRI plain and contrast enhanced scan, and DKI examination, while control group underwent MRI plain scan and DKI scan. The signal features of liver parenchyma and liver cancer lesion could be observed from the routine MRI and DKI. Fractional anisotropy (FA), mean diffusion (MD), axial diffusivity (Da), radial diffusivity (Dr), fractional anisotropy kurtosis (Fak), mean kurtosis (MK), kurtosis anisotropy (Ka) and radial kurtosis (Kr) value of four groups, the distant liver parenchyma(far away from the tumor>2 cm), peritumoral liver parenchyma(the distance≤2 cm around the tumor) and liver cancer were recorded. The differences of DKI parameters were evaluated using one-way analysis of variance (ANOVA). Results The signal of liver cancer in MR plain scan showed mild long T1 and mild long T2 signal, fast in and fast out enhanced feature of the neoplasms could be observed from the enhanced MRI and signal of liver cancer would not lower in DKI with b value up to top. The difference of DKI parameters including FA, MD, Da, Dr and Ka value had statistical significance in these four groups excepted for MK and Kr value. MD, Da and Dr value of normal parenchyma were higher than that of peritumoral parenchyma and liver cancer,while the Ka value was reverse. The differences of MD, Da, Dr and Ka value only had no statistical significance between the distant liver parenchyma and peritumoral liver parenchyma(P>0.05),and the differences of them had statistical significance among the rest group(P<0.05). Conclusion The DKI quantitative parameters can reflect the differences of different tissue, meaning that they can provide molecular imaging information for evaluating liver cancer and peritumoral zone.