Genotoxic effects of heavy metal cadmium on growth,biochemical, cyto-physiological parameters and detection of DNA polymorphism by RAPD in Capsicum annuum L. – An important spice crop of India

The present study was designed to investigate the effects of cadmium (Cd) on biochemical, physiological and cytological parameters of Capsicum annuum L. treated with five different concentrations (20, 40, 60, 80 and 100 ppm) of the metal. Shoot–root length, pigment and protein content showed a continuous decrease with increasing Cd concentrations and the maximal decline was observed at the higher concentration. Proline content was found to be increased upto 60 ppm while at higher concentrations it gradually decreased. MDA content and chromosomal aberrations increased as the concentration increased. Additionally Random amplified polymorphic DNA (RAPD) technique was used for the detection of genotoxicity induced by Cd. A total of 184 bands (62 polymorphic and 122 monomorphic) were generated in 5 different concentrations with 10 primers where primer OPA-02 generated the highest percentage of polymorphism (52.63%). Dendrogram showed that control, R1 and R2 showed similar cluster and R4 and R5 grouped with R3 into one cluster, which showed that plants from higher doses showed much difference than the plants selected at mild doses which resemble control at the DNA level. This investigation showed that RAPD marker is a useful tool for evaluation of genetic diversity and relationship among different metal concentrations.     

A utility approach to individualized optimal dose selection using biomarkers

In many settings, including oncology, increasing the dose of treatment results in both increased efficacy and toxicity. With the increasing availability of validated biomarkers and prediction models, there is the potential for individualized dosing based on patient specific factors. We consider the setting where there is an existing dataset of patients treated with heterogenous doses and including binary efficacy and toxicity outcomes and patient factors such as clinical features and biomarkers. The goal is to analyze the data to estimate an optimal dose for each (future) patient based on their clinical features and biomarkers. We propose an optimal individualized dose finding rule by maximizing utility functions for individual patients while limiting the rate of toxicity. The utility is defined as a weighted combination of efficacy and toxicity probabilities. This approach maximizes overall efficacy at a prespecified constraint on overall toxicity. We model the binary efficacy and toxicity outcomes using logistic regression with dose, biomarkers and dose–biomarker interactions. To incorporate the large number of potential parameters, we use the LASSO method. We additionally constrain the dose effect to be non-negative for both efficacy and toxicity for all patients. Simulation studies show that the utility approach combined with any of the modeling methods can improve efficacy without increasing toxicity relative to fixed dosing. The proposed methods are illustrated using a dataset of patients with lung cancer treated with radiation therapy.     

Bioinoculant with Vermicompost Augments Essential Oil Constituents and Antioxidants in Mentha arvensis L.

Journal of Plant Growth Regulation - Today’s demand has approached the sustainable agriculture with synergistic bioinoculants for improved crop production and soil rejuvenation. Furthermore,...     

Quantitative phosphoproteomic analysis reveals involvement of PD-1 in multiple T cell functions

Programmed cell death protein 1 (PD-1) is a critical inhibitory receptor that limits excessive T cell responses. Cancer cells have evolved to evade these immunoregulatory mechanisms by upregulating PD-1 ligands and preventing T cell–mediated anti-tumor responses. Consequently, therapeutic blockade of PD-1 enhances T cell–mediated anti-tumor immunity, but many patients do not respond and a significant proportion develop inflammatory toxicities. To improve anti-cancer therapy, it is critical to reveal the mechanisms by which PD-1 regulates T cell responses. We performed global quantitative phosphoproteomic interrogation of PD-1 signaling in T cells. By complementing our analysis with functional validation assays, we show that PD-1 targets tyrosine phosphosites that mediate proximal T cell receptor signaling, cytoskeletal organization, and immune synapse formation. PD-1 ligation also led to differential phosphorylation of serine and threonine sites within proteins regulating T cell activation, gene expression, and protein translation. In silico predictions revealed that kinase/substrate relationships engaged downstream of PD-1 ligation. These insights uncover the phosphoproteomic landscape of PD-1–triggered pathways and reveal novel PD-1 substrates that modulate diverse T cell functions and may serve as future therapeutic targets. These data are a useful resource in the design of future PD-1–targeting therapeutic approaches.     

Wake Up: it’s Time to Bloom

Russian Journal of Plant Physiology - The transition from vegetative to floral buds is a complex phenomenon regulated by many factors. The timing of floral transduction has a direct impact on the...