Wheat peroxidases 1 (WP1) is the major cationic peroxidase of wheat (Triticum aestivum) grain, which is involved in the development of seeds and an important factor to affect the final processing quality of flour. We constructed a prokaryotic expression vector pET28a-WP1, and transformed it into E. coli host strain T7 Expression. His-tag fused WP1 existed as inclusion body, and the recombinant protein was purified by Ni-NTA resin affinity chromatography under denatured condition. The purity of target protein reached 98%. The recombinant WP1 was refolded by gradient urea dialysis, then used as antigen to immune rabbit to prepare polyclonal antibody. The result of ELISA showed that the titer of rabbit anti-WP1 antiserum was higher than 1:625 000. The result of Western blotting demonstrated that the prepared WP1 polyclonal antibody could be used to detect WP1 with high specificity.
Animals ; Antibodies ; immunology ; metabolism ; Escherichia coli ; genetics ; metabolism ; Genetic Vectors ; Peroxidases ; biosynthesis ; genetics ; Rabbits ; Recombinant Proteins ; biosynthesis ; genetics ; immunology

Objective:To investigate the predictive value of dynamic platelet and hemagglutination-related parameters in patients with acute pancreatitis (AP).Methods:The patients admitted to the Department of Emergency Surgery in the First Affiliated Hospital of Zhengzhou University from January 2020 to December 2020 were analyzed. According to the inclusion criteria and exclusion criteria, patients with AP were retrospectively enrolled. According to the Chinese Guidelines for the Diagnosis and Treatment of Acute Pancreatitis (Shenyang, 2019), the patients were divided into two groups: severe acute pancreatitis (SAP group) and non-severe acute pancreatitis (non-SAP group) [including mild acute pancreatitis (MAP) and moderate severe acute pancreatitis (MSAP)]. A normal distribution of the maximum and mean aggregation rates of dynamic platelets (arachiidonic acid), plateletcrit (PCT) and bedside index for severity in acute pancreatitis (BISAP) scores and other measurement data were tested by t test, while measurement data of prothrombin time (PT), fibrinogen (FIB) and D-dimer that did not conform to normal distribution were tested by Mann-Whitney U test. χ 2 test was used for the counting data such as sex, age and etiology of patients in the two groups. The prognostic value of statistically significant indicators for non-SAP group and SAP group was further analyzed by receiver operating characteristic (ROC) curve. Results:A total of 146 patients with AP were enrolled, including 50 patients in SAP group and 96 in non-SAP group. The maximum and average aggregation rates of dynamic platelet (aracidonic acid) in the SAP group were (71.76±17.62) % and (67.91±18.10) %, PT (12.02±1.33) s, FIB (4.76±2.08) g/L, D-dimer (3.75±6.04) μg/L, PCT (0.23±0.08) %, and BISAP scores (1.42±1.18), which were all significantly higher than those in the non-SAP group [the maximum and average aggregation rates of dynamic platelet (arachiidonic acid) (46.65±20.11) % and (42.50±20.71) %, PT (11.50±1.51) s and FIB (3.91±1.48) g/L, D-dimer (1.00±1.37) μg/L, PCT (0.19±0.06) %, BISAP scores (0.45±0.66)] (all P<0.05). According to area under the ROC curve, the maximum and average aggregation rates of dynamic platelets (arachiidonic acid) in serum of patients with SAP were 0.83 and 0.82, respectively, and the sensitivities were 0.56 and 0.68, respectively. The specificity was 0.99 and 0.81, respectively, which was better than PT, FIB, D-dimer, PCT and BISAP scores in predicting the severity of AP. Conclusions:The maximum and average aggregation rates of dynamic platelets (arachidonic acid), PT, FIB, D-dimer, PCT and BISAP scores can be used as predictors of the severity of acute pancreatitis. The maximum and average aggregation rates of dynamic platelets (arachiidonic acid) were the best in predicting the severity of AP.

Objective:To analyze the prognostic risk factors of patients with traumatic pancreatitis (TP) and establish an early combined prediction of multiple indicators model for TP.Methods:Patients admitted to the ICU of the First Affiliated Hospital of Zhengzhou University from June 2017 to June 2022 were collected retrospectively. Based on their prognosis, the patients were divided into two groups: the good prognosis group and the poor prognosis group. The general data such as sex, age, underlying diseases, Glasgow Coma Scale (GCS), acute physiology and chronic health evaluationⅡ (APACHEⅡ), injury severity score (ISS), bedside index for severity in acute pancreatitis (BISAP), and clinical test indices such as blood routine, blood coagulation, blood gas analysis, and liver and kidney function at admission were compared between the two groups. Univariate analysis and multivariate logistic regression analysis were used to screen the early independent predictors of poor prognosis of TP, and the prediction model of TP was established by combining all of the independent indicators. The receiver operating characteristic (ROC) curve of each independent predictor and prediction model was drawn, and the area under the curve (AUC), sensitivity, specificity, and optimal cut-off value were calculated to examine the diagnostic impact of each independent predictor and the combined prediction model.Results:There were statistically significant differences in the complication rate of mental disorders, GCS, APACHE II, combined craniocerebral injury, combined chest injury, activated partial thromboplastin time, fibrin(pro)degradation products, lactate, aspartate aminotransferase, glomerular filtration rate, amylase, lipase, NT-proBNP, myoglobin, procalcitonin, ISS, and BISAP between the good and poor prognosis groups (all P<0.05). Multivariate logistic regression analysis showed that lactate ( OR=1.636, 95% CI: 1.046-2.559), lipase ( OR=1.005, 95% CI: 1.001-1.008), and ISS ( OR=1.161, 95% CI: 1.064-1.266) were independent risk factors influencing the prognosis of patients with TP. Based on the risk factors listed above, a prediction model was created: Logit P=-9.260+0.492×lactate+0.005×lipase+0.149×ISS, and the ROC curve was plotted. The AUC curve of the prediction model was 0.96 (95% CI: 0.91-1.00). Conclusions:Lactate, lipase, and ISS are early independent risk factors associated with the prognosis of TP. Their combined multi-indicator prediction model has an excellent clinical prediction effect, which can provide a clinical reference for early prediction and treatment of TP.

Objective:To investigate the protective effect of overexpressed tripartite motif containing (TRIM27) on severe acute pancreatitis (SAP) in mice and its possible mechanism.Methods:Twenty-four mice were randomly divided into the sham operation + control virus group (AAV-GFP group), sham operation + overexpression of TRIM27 group (AAV-TRIM27 group), SAP + control virus group (SAP+AAV-GFP group), SAP + overexpression of TRIM27 group (SAP + AAV-TRIM27 group), with 6 mice in each group. SAP model of mice was established by intraperitoneal injection of L-arginine (4 mg/kg). The sham operation group was injected with equal volume of normal saline, and the virus group was injected with control or TRIM27 overexpression adeno-associated virus (2×10 11 μg/ per mice). The serum and pancreatic tissue samples were collected 72 h after modeling. The levels of serum amylase, lipase, tumor necrosis factor α (TNF-α), interleukin-1b (IL-1b), IL-6, macrophage chemoattractant protein-1 (MCP-1) and the expression of malondialdehyde (MDA), superoxide dismutase (SOD) and glutathione (GSH) in pancreatic tissue were detected by enzyme-linked immunosorbent assay. Hematoxylin eosin staining was used to observe the pathological damage of pancreatic tissue. The expressions of myeloperoxidase (MPO) and Ly6g positive inflammatory cells in mouse pancreas were observed by immunohistochemistry. The expression of p-p65, p65, p-ASK1, ASK1, p-JNK, JNK, p-p38 and p38 in pancreatic tissue were detected by Western blot. Results:The expression of TRIM27 in pancreatic of mice was significantly down regulated after SAP ( P<0.05); after overexpression of TRIM27 by adeno-associated virus, the expression of TRIM27 in mouse pancreas was significantly up-regulated ( P<0.05). There was no significant difference in the indexes of mice between the AAV-GFP group and AAV-TRIM27 group ( P>0.05). Compared with the SAP + AAV-GFP group, the levels of serum amylase, lipase, TNF-α, IL-1b, IL-6 and MCP-1 in mice of the SAP + AAV-TRIM27 group were significantly decreased, MDA in pancreatic tissue was decreased, SOD and GSH were increased, MPO and Ly6g inflammatory cells were significantly decreased, and p-p65, p-ASK1, p-JNK, and p-p38 protein expression were down regulated. Conclusions:Overexpression of TRIM27 alleviates SAP in mice by inhibiting inflammatory response and oxidative stress, and its mechanism may be through inhibiting NFκB/MAPK signaling pathway.

The importance of structural variants(SVs)for human phenotypes and diseases is now recognized.Although a variety of SV detection platforms and strategies that vary in sensitivity and specificity have been developed,few benchmarking procedures are available to confidently assess their performances in biological and clinical research.To facilitate the validation and application of these SV detection approaches,we established an Asian reference material by characterizing the genome of an Epstein-Barr virus(EBV)-immortalized B lymphocyte line along with identified benchmark regions and high-confidence SV calls.We established a high-confidence SV callset with 8938 SVs by integrating four alignment-based SV callers,including 109x Pacific Biosciences(PacBio)continuous long reads(CLRs),22 x PacBio circular consensus sequencing(CCS)reads,104x Oxford Nanopore Technologies(ONT)long reads,and 114×Bionano optical mapping plat-form,and one de novo assembly-based SV caller using CCS reads.A total of 544 randomly selected SVs were validated by PCR amplification and Sanger sequencing,demonstrating the robustness of our SV calls.Combining trio-binning-based haplotype assemblies,we established an SV benchmark for identifying false negatives and false positives by constructing the continuous high-confidence regions(CHCRs),which covered 1.46 gigabase pairs(Gb)and 6882 SVs supported by at least one diploid haplotype assembly.Establishing high-confidence SV calls for a benchmark sample that has been characterized by multiple technologies provides a valuable resource for investigating SVs in human biology,disease,and clinical research.