Correction to: Linear relation between leaf xylem water potential and transpiration in pearl millet during soil drying

Plant and Soil - In the original version of this article, equations 4 and 9 unfortunately contained errors     

Association between serum cell adhesion molecules with hs-CRP,uric acid and VEGF genetic polymorphisms in subjects with metabolic syndrome

Molecular Biology Reports - Metabolic syndrome (MetS) is associated with a pro-inflammatory state and endothelial dysfunction that places subjects with MetS at a higher risk of atherosclerosis....     

Biochemical study on modifying role of variants of leptin gene and its receptor on serum leptin levels in breast cancer

Molecular Biology Reports - The leptin is discharged from breast adipose tissue and is overexpressed in breast cancer (BC). Conflicting relation of leptin with BC was reported. We investigated this...     

Synthetic biology in various cellular and molecular fields: applications,limitations, and perspective

Molecular Biology Reports - Synthetic biology breakthroughs have facilitated genetic circuit engineering to program cells through novel biological functions, dynamic gene expressions, as well as...     

Expression of the Arcelin 1 gene from Phaseolus vulgaris L. in cowpea seeds (Vigna unguiculata L.) confers bruchid resistance

Persistent decrease in the productivity of cowpea (Vigna unguiculata L.) has been partly due to attack by bruchids including Zabrotes subfasciatus and Callosobruchus maculatus. Resistance to these insects in Phaseolus vulgaris L. has been shown to be associated with arcelins, a family of seed proteins encoded by a multigenic family of lectins on the APA locus. In this work, we report the construction of an expression vector containing Arc1 gene isolated from P. vulgaris and introduced into cowpea as a strategy to confer resistance to insect attack. Following transformation and selection, feeding experiments in which C. maculatus and Z. subfasciatus were fed with transgenic (L3 and L5) and non-transgenic (control) grains showed that introduced gene protected the transgenic line. Significant differences (p < .05 and p < .01) were found in the number of eggs laid, the number of emerging insects and the loss of grain mass in L3, compared with control, for both insects. Similar observations were made in L5 with the exception of the number of laid eggs. The strategy here described may form the basis for the development of a cowpea variety tolerant to bruchids in a crop cultivated by farmers throughout Latin America and Africa.     

Joint analysis of single-cell and bulk tissue sequencing data to infer intratumor heterogeneity

Many computational methods have been developed to discern intratumor heterogeneity (ITH) using DNA sequence data from bulk tumor samples. These methods share an assumption that two mutations arise from the same subclone if they have similar mutant allele-frequencies (MAFs), and thus it is difficult or impossible to distinguish two subclones with similar MAFs. Single-cell DNA sequencing (scDNA-seq) data can be very informative for ITH inference. However, due to the difficulty of DNA amplification, scDNA-seq data are often very noisy. A promising new study design is to collect both bulk and single-cell DNA-seq data and jointly analyze them to mitigate the limitations of each data type. To address the analytic challenges of this new study design, we propose a computational method named BaSiC (B ulk tumor a nd Si ngle C ell), to discern ITH by jointly analyzing DNA-seq data from bulk tumor and single cells. We demonstrate that BaSiC has comparable or better performance than the methods using either data type. We further evaluate BaSiC using bulk tumor and single-cell DNA-seq data from a breast cancer patient and several leukemia patients.     

Bayesian design of biosimilars clinical programs involving multiple therapeutic indications

In this paper, we propose a Bayesian design framework for a biosimilars clinical program that entails conducting concurrent trials in multiple therapeutic indications to establish equivalent efficacy for a proposed biologic compared to a reference biologic in each indication to support approval of the proposed biologic as a biosimilar. Our method facilitates information borrowing across indications through the use of a multivariate normal correlated parameter prior (CPP), which is constructed from easily interpretable hyperparameters that represent direct statements about the equivalence hypotheses to be tested. The CPP accommodates different endpoints and data types across indications (eg, binary and continuous) and can, therefore, be used in a wide context of models without having to modify the data (eg, rescaling) to provide reasonable information-borrowing properties. We illustrate how one can evaluate the design using Bayesian versions of the type I error rate and power with the objective of determining the sample size required for each indication such that the design has high power to demonstrate equivalent efficacy in each indication, reasonably high power to demonstrate equivalent efficacy simultaneously in all indications (ie, globally), and reasonable type I error control from a Bayesian perspective. We illustrate the method with several examples, including designing biosimilars trials for follicular lymphoma and rheumatoid arthritis using binary and continuous endpoints, respectively.     

Partial least squares for functional joint models with applications to the Alzheimer's disease neuroimaging initiative study

Many biomedical studies have identified important imaging biomarkers that are associated with both repeated clinical measures and a survival outcome. The functional joint model (FJM) framework, proposed by Li and Luo in 2017, investigates the association between repeated clinical measures and survival data, while adjusting for both high-dimensional images and low-dimensional covariates based on the functional principal component analysis (FPCA). In this paper, we propose a novel algorithm for the estimation of FJM based on the functional partial least squares (FPLS). Our numerical studies demonstrate that, compared to FPCA, the proposed FPLS algorithm can yield more accurate and robust estimation and prediction performance in many important scenarios. We apply the proposed FPLS algorithm to a neuroimaging study. Data used in preparation of this article were obtained from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database.     

Use of some emulsified plant seed oils as a safe alternative for the management of Meloidogyne incognita infecting tomato

Abstract

The aim of the present study was to formulate six different plant seed oils namely canola, cotton, flax, olive, sesame and soybean as emulsifiable concentrates. The composition of the formulation comprises at least one organic solvent, one surfactant and one plant oil. Physico-chemical properties of the formulated oils (emulsion stability test, cold stability and heat stability tests) were measured. The successfully emulsified oils were evaluated for nematicidal activity against Meloidogyne incognita infecting tomato plants under greenhouse conditions. Emulsified canola oil proved to be the most effective oil as a protectant against M. incognita infection to tomatoes followed by soybean, cotton, flax and sesame oil. In addition, employing a high rate of the tested emulsified oils gave higher activity in suppressing nematodes both in the soil and in tomato roots than using a low rate. Moreover, all tested formulated oils at both rates of application had no adverse effect on the growth of tomato plants except sesame oil which significantly decreased the shoot length when compared to the control. The prepared plant oils might be used as potential sources for sustainable eco-friendly botanical nematicides to protect plants from nematode attack.