A comparative assessment of morphological and molecular characterization among three Ziziphus species

Genetic variability of 84 accessions of three Ziziphus species including Z. spina-christi, Z. nummularia and Z. mauritiana were analyzed using a combination of morphological traits and translation initiation codon (ATG) polymorphism. Both morphological and molecular data revealed a high level of inter and intra specific variations among the accessions. Accordingly, 90.49% of amplified fragments were polymorphic among the accessions with the mean values of 0.37 for polymorphic information content (PIC), 3.31 for resolving power (RP), and 1.95 for marker index (MI). The phylogenetic clustering clearly delineated the entire germplasm into three well supported distinct clusters according to the species sources. According to the Nei''s genetic identity, Z. spina-christi and Z. nummularia were the most similar species and had high differentiation with Z. mauritiana. Moreover, the highest values for Shannon’s information index (I = 0.505) and gene diversity (h = 0.347) were recorded in Z. spina-christi indicating there is higher genetic diversity compared with two other species. Four private alleles were identified in two species which could be beneficial for accessions authentication in argumentative situations. Moreover, results of the Mantel test showed there were moderate correlation between molecular and morphological matrices. In addition, estimation of bivariate correlations revealed there were significant positive and negative correlations between different variables, which offer a practical application of this information during phenotype based selection in ber improvement programs. The results of this investigation highlight the efficiency of translation initiation codon polymorphism for genetic characterization and accurate authentication of Ziziphus accessions as well as detecting and tagging morphologically important traits in this genus that would be helpful for implementation of effective conservation strategies and even broaden current genetic diversity.Supplementary InformationThe online version contains supplementary material available at 10.1007/s12298-021-01000-7.     

A combination of urinary biomarker panel and PancRISK score for earlier detection of pancreatic cancer: A case–control study

BackgroundPancreatic ductal adenocarcinoma (PDAC) is one of the deadliest cancers, with around 9% of patients surviving >5 years. Asymptomatic in its initial stages, PDAC is mostly diagnosed late, when already a locally advanced or metastatic disease, as there are no useful biomarkers for detection in its early stages, when surgery can be curative. We have previously described a promising biomarker panel (LYVE1, REG1A, and TFF1) for earlier detection of PDAC in urine. Here, we aimed to establish the accuracy of an improved panel, including REG1B instead of REG1A, and an algorithm for data interpretation, the PancRISK score, in additional retrospectively collected urine specimens. We also assessed the complementarity of this panel with CA19-9 and explored the daily variation and stability of the biomarkers and their performance in common urinary tract cancers.Methods and findingsClinical specimens were obtained from multiple centres: Barts Pancreas Tissue Bank, University College London, University of Liverpool, Spanish National Cancer Research Center, Cambridge University Hospital, and University of Belgrade. The biomarker panel was assayed on 590 urine specimens: 183 control samples, 208 benign hepatobiliary disease samples (of which 119 were chronic pancreatitis), and 199 PDAC samples (102 stage I–II and 97 stage III–IV); 50.7% were from female individuals. PDAC samples were collected from patients before treatment. The samples were assayed using commercially available ELISAs. Statistical analyses were performed using non-parametric Kruskal–Wallis tests adjusted for multiple comparisons, and multiple logistic regression. Training and validation datasets for controls and PDAC samples were obtained after random division of the whole available dataset in a 1:1 ratio. The substitution of REG1A with REG1B enhanced the performance of the panel to detect resectable PDAC. In a comparison of controls and PDAC stage I–II samples, the areas under the receiver operating characteristic curve (AUCs) increased from 0.900 (95% CI 0.843–0.957) and 0.926 (95% CI 0.843–1.000) in the training (50% of the dataset) and validation sets, respectively, to 0.936 in both the training (95% CI 0.903–0.969) and the validation (95% CI 0.888–0.984) datasets for the new panel including REG1B. This improved panel showed both sensitivity (SN) and specificity (SP) to be >85%. Plasma CA19-9 enhanced the performance of this panel in discriminating PDAC I–II patients from controls, with AUC = 0.992 (95% CI 0.983–1.000), SN = 0.963 (95% CI 0.913–1.000), and SP = 0.967 (95% CI 0.924–1.000). We demonstrate that the biomarkers do not show significant daily variation, and that they are stable for up to 5 days at room temperature. The main limitation of our study is the low number of stage I–IIA PDAC samples (n = 27) and lack of samples from individuals with hereditary predisposition to PDAC, for which specimens collected from control individuals were used as a proxy.ConclusionsWe have successfully validated our urinary biomarker panel, which was improved by substituting REG1A with REG1B. At a pre-selected cutoff of >80% SN and SP for the affiliated PancRISK score, we demonstrate a clinically applicable risk stratification tool with a binary output for risk of developing PDAC (‘elevated’ or ‘normal’). PancRISK provides a step towards precision surveillance for PDAC patients, which we will test in a prospective clinical study, UroPanc.

Silvana Debernardi and colleagues establish a clinical risk score and a biomarker panel for early detection of pancreatic cancer.     

Integration of data-independent acquisition (DIA) with co-fractionation mass spectrometry (CF-MS) to enhance interactome mapping capabilities

Proteomics technologies are continually advancing, providing opportunities to develop stronger and more robust protein interaction networks (PINs). In part, this is due to the ever-growing number of high-throughput proteomics methods that are available. This review discusses how data-independent acquisition (DIA) and co-fractionation mass spectrometry (CF-MS) can be integrated to enhance interactome mapping abilities. Furthermore, integrating these two techniques can improve data quality and network generation through extended protein coverage, less missing data, and reduced noise. CF-DIA-MS shows promise in expanding our knowledge of interactomes, notably for non-model organisms (NMOs). CF-MS is a valuable technique on its own, but upon the integration of DIA, the potential to develop robust PINs increases, offering a unique approach for researchers to gain an in-depth understanding into the dynamics of numerous biological processes.     

Identification of genetic defects underlying FVII deficiency in 10 patients belonging to eight unrelated families of the North provinces from Tunisia

ABSTRACT: Inherited factor VII (FVII) deficiency is a rare disorder characterized by a bleeding phenotype varying from mild to severe. To date, more than 200 mutations have been described along the F7 gene encoding for FVII. The aim of this study was the identification of genetic defects underlying FVII deficiency in 10 patients belonging to eight unrelated families of the North provinces from Tunisia. Mutation detection was performed by sequencing the whole F7 gene coding region, exon-intron boundaries and about 400 bp of the promoter region. We identified 5 mutations in five unrelated families; the novel p.F328Y mutation and the reported mutations: p.R304Q, p.M298I, IVS1aG > A and nt1005C > T. For the remaining 5 patients we didn't identified any mutations using PCR/Sequencing protocol. In conclusion, this study represents the first comprehensive molecular series of FVII deficiency affected patients in Tunisia from the North. We will try in the future to continue the molecular study for Tunisian patients from Center and South provinces in order to have a complete idea about the FVII deficiency mutational profile in our country. Virtual slides The virtual slide(s) for this article can be found here: http://www.diagnosticpathology.diagnomx.eu/vs/1288044089753085.     

Fabrication Friendly Plasmonic Metasurface Sensing and Switching Configuration Based on Plasmonic Induced Absorption: Analytical and Numerical Evaluation

Plasmonics - Optical sensing and switching characteristic for a novel plasmonic metasurface structure are verified based on numerical and analytical evaluations for the proposed structure formed by...     

Influence of zinc on soluble carbohydrate and free amino acid levels in rapeseed plants regenerated in vitro in the presence of zinc

To gain more insight into the impact of zinc on the primary metabolites in rapeseed, plants were regenerated in vitro in the presence of zinc (0.1–1 mM), acclimatized, transferred to a greenhouse, and treated with 2 mM ZnSO₄. The main metabolites, including soluble carbohydrates and free amino acids, were analyzed by nuclear magnetic resonance spectroscopy, and further confirmed by spectrophotometry and enzymatic analyses. Exposure of these greenhouse-grown plants to ZnSO₄ led to both a significant rise of the total amino acid level and an increase of proline accumulation in the different tissues. Moreover, the control plants, regenerated without zinc stress, exhibited a significant reduction of soluble carbohydrate levels, whereas the plants derived from Zn-treated regenerants exhibited significantly higher levels of both glucose and sucrose. These levels increased proportionally with the Zn concentration in the regeneration step.