458 research outputs found

    Generation of marker- and/or backbone-free transgenic wheat plants via Agrobacterium-mediated transformation

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    Horizontal transfer of antibiotic resistance genes to animals and vertical transfer of herbicide resistance genes to the weedy relatives are perceived as major biosafety concerns in genetically modified (GM) crops. In this study, five novel vectors which used gusA and bar as a reporter gene and a selection marker gene, respectively, were constructed based on the pCLEAN dual binary vector system. Among these vectors, 1G7B and 5G7B carried two T-DNAs located on two respective plasmids with 5G7B possessing an additional virGwt gene. 5LBTG154 and 5TGTB154 carried two T-DNAs in the target plasmid with either one or double right borders, and 5BTG154 carried the selectable marker gene on the backbone outside of the T-DNA left border in the target plasmid. In addition, 5BTG154, 5LBTG154, and 5TGTB154 used pAL154 as a helper plasmid which contains Komari fragment to facilitate transformation. These five dual binary vector combinations were transformed into Agrobacterium strain AGL1 and used to transform durum wheat cv Stewart 63. Evaluation of the co-transformation efficiencies, the frequencies of marker-free transgenic plants, and integration of backbone sequences in the obtained transgenic lines indicated that two vectors (5G7B and 5TGTB154) were more efficient in generating marker-free transgenic wheat plants with no or minimal integration of backbone sequences in the wheat genome. The vector series developed in this study for generation of marker- and/or backbone-free transgenic wheat plants via Agrobacterium-mediated transformation will be useful to facilitate the creation of “clean” GM wheat containing only the foreign genes of agronomic importance

    Validation of 58 autosomal individual identification SNPs in three Chinese populations

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    Aim To genotype and evaluate a panel of single-nucleotide polymorphisms for individual identification (IISNPs) in three Chinese populations: Chinese Han, Uyghur, and Tibetan. Methods Two previously identified panels of IISNPs, 86 unlinked IISNPs and SNPforID 52-plex markers, were pooled and analyzed. Four SNPs were included in both panels. In total, 132 SNPs were typed on Sequenom MassARRAY® platform in 330 individuals from Han Chinese, Uyghur, and Tibetan populations. Population genetic indices and forensic parameters were determined for all studied markers. Results No significant deviation from Hardy-Weinberg equilibrium was observed for any of the SNPs in 3 populations. Expected heterozygosity (He) ranged from 0.144 to 0.500 in Han Chinese, from 0.197 to 0.500 in Uyghur, and from 0.018 to 0.500 in Tibetan population. Wright’s Fst values ranged from 0.0001 to 0.1613. Pairwise linkage disequilibrium (LD) calculations for all 132 SNPs showed no significant LD across the populations (r2<0.147). A subset of 58 unlinked IISNPs (r20.450 and Fst values from 0.0002 to 0.0536 gave match probabilities of 10−25 and a cumulative probability of exclusion of 0.999992. Conclusion The 58 unlinked IISNPs with high heterozygosity have low allele frequency variation among 3 Chinese populations, which makes them excellent candidates for the development of multiplex assays for individual identification and paternity testing

    GPX8 regulates pan-apoptosis in gliomas to promote microglial migration and mediate immunotherapy responses

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    IntroductionGliomas have emerged as the predominant brain tumor type in recent decades, yet the exploration of non-apoptotic cell death regulated by the pan-optosome complex, known as pan-apoptosis, remains largely unexplored in this context. This study aims to illuminate the molecular properties of pan-apoptosis-related genes in glioma patients, classifying them and developing a signature using machine learning techniques.MethodsThe prognostic significance, mutation features, immunological characteristics, and pharmaceutical prediction performance of this signature were comprehensively investigated. Furthermore, GPX8, a gene of interest, was extensively examined for its prognostic value, immunological characteristics, medication prediction performance, and immunotherapy prediction potential. ResultsExperimental techniques such as CCK-8, Transwell, and EdU investigations revealed that GPX8 acts as a tumor accelerator in gliomas. At the single-cell RNA sequencing level, GPX8 appeared to facilitate cell contact between tumor cells and macrophages, potentially enhancing microglial migration. ConclusionsThe incorporation of pan-apoptosis-related features shows promising potential for clinical applications in predicting tumor progression and advancing immunotherapeutic strategies. However, further in vitro and in vivo investigations are necessary to validate the tumorigenic and immunogenic processes associated with GPX8 in gliomas

    The CDEX-1 1 kg Point-Contact Germanium Detector for Low Mass Dark Matter Searches

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    The CDEX Collaboration has been established for direct detection of light dark matter particles, using ultra-low energy threshold p-type point-contact germanium detectors, in China JinPing underground Laboratory (CJPL). The first 1 kg point-contact germanium detector with a sub-keV energy threshold has been tested in a passive shielding system located in CJPL. The outputs from both the point-contact p+ electrode and the outside n+ electrode make it possible to scan the lower energy range of less than 1 keV and at the same time to detect the higher energy range up to 3 MeV. The outputs from both p+ and n+ electrode may also provide a more powerful method for signal discrimination for dark matter experiment. Some key parameters, including energy resolution, dead time, decay times of internal X-rays, and system stability, have been tested and measured. The results show that the 1 kg point-contact germanium detector, together with its shielding system and electronics, can run smoothly with good performances. This detector system will be deployed for dark matter search experiments.Comment: 6 pages, 8 figure

    Development and efficacy evaluation of remodeled canine parvovirus-like particles displaying major antigenic epitopes of a giant panda derived canine distemper virus

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    Canine parvovirus (CPV) and Canine distemper virus (CDV) can cause fatal diseases in giant panda (Ailuropoda melanoleuca). The main capsid protein of CPV VP2 can be self-assembled to form virus-like particles (VLPs) in vitro, which is of great significance for potential vaccine development. In the present study, we remodeled the VP2 protein of a giant panda-derived CPV, where the major CDV F and N epitopes were incorporated in the N-terminal and loop2 region in two combinations to form chimeric VLPs. The reactivity ability and morphology of the recombinant proteins were confirmed by Western blot, hemagglutination (HA) test and electron microscopy. Subsequently, the immunogenicity of the VLPs was examined in vivo. Antigen-specific antibodies and neutralizing activity were measured by ELISA, hemagglutination inhibition (HI) test and serum neutralization test (SNT), respectively. In addition, antigen specific T cell activation were determined in splenic lymphocytes. The results indicated that the VLPs displayed good reaction with CDV/CPV antibodies, and the heterologous epitopes do not hamper solubility or activity. The VLPs showed decent HA activity, and resembled round-shaped particles with a diameter of 22–26 nm, which is identical to natural virions. VLPs could induce high levels of specific antibodies to CPV and CDV, shown by the indication of neutralizing antibodies in both VP2N and VP2L VLPs group. In addition, splenic lymphocytes of mice immunized with VLPs could proliferate rapidly after stimulation by specific antigen. Taken together, the CPV VP2 VLPs or chimeric VLPs are highly immunogenic, and henceforth could function as CPV/CDV vaccine candidates for giant pandas

    A Regression Model to Predict Augmented Renal Clearance in Critically Ill Obstetric Patients and Effects on Vancomycin Treatment

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    Background: Augmented renal clearance (ARC) risk factors and effects on vancomycin (VCM) of obstetric patients were possibly different from other populations based on pathophysiological characteristics. Our study was to establish a regression model for prediction of ARC and analyze the effects of ARC on VCM treatment in critically ill obstetric patients.Methods: We retrospectively included 427 patients, grouped into ARC and non-ARC patients. Logistic regression analysis was used to analyze the factors related to ARC. Receiver operating characteristic (ROC) curve was drawn to evaluate the predictive value of the model for ARC. Patients who received VCM therapy were collected. The published VCM population pharmacokinetic (PPK) model was used to calculate pharmacokinetic parameters. A linear regression analysis was made between the predicted and measured concentrations.Results: Of the 427 patients, ARC was present in 201 patients (47.1%). The independent risk factors of ARC were heavier, greater gestational age, higher albumin level, fewer caesarean section, severe preeclampsia and vasoactive drug; more infection, hypertriglyceridemia and acute pancreatitis. We established the above nine-variable prediction regression model and calculated the predicted probability. ROC curve showed that the predicted probability of combined weight, albumin and gestational age had better sensitivity (70.0%) and specificity (89.8%) as well as the maximal area under the curve (AUC, AUC = 0.863). 41 cases received VCM; 21 cases (51.2%) had ARC. The initial trough concentration in ARC patients was lower than in non-ARC patients (7.9 ± 3.2 mg/L vs 9.5 ± 3.3 mg/L; p = 0.033). Comparing the predicted trough concentration of two published VCM PPK models with the measured trough concentration, correlation coefficients (r) were all more than 0.8 in the ARC group and non-ARC group. AUC was significantly decreased in the ARC group (p = 0.003; p = 0.013), and clearance (CL) increased in the ARC group (p &lt; 0.001; p = 0.008) when compared with the non-ARC group.Conclusion: ARC is a common state in critically ill obstetric patients. The regression model of nine variables had high predictive value for predicting ARC. The published VCM PPK models had good predictive performance for predicting trough concentrations of obstetric patients. Pharmacokinetic parameters of VCM are different in ARC obstetric patients, which results in enhanced VCM clearance and decreased trough concentration
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