5D proteomic approach for the biomarker search in plasma: Acute myeloid leukaemia as a case study

Application of Encapsulated Bacillus licheniformis Supplemented with Chitosan Nanoparticles and Rice Starch for the Control of Sclerotium rolfsii in Capsicum annuum (L.) Seedlings

Rhizosphere encourages the survival and functioning of diverse microbial communities through the influence of plant roots. Likewise, the rhizobacterial functioning contribute to the growth and productivity of crop plants significantly. With the advancement of nanotechnology, the nanoparticles can expect to augment the performance of plant beneficial microorganisms including the rhizobacteria and hence have the promise to boost sustainable agricultural practices. In the present study, Bacillus licheniformis encapsulated in alginate-chitosan nanoparticles (CNPs) beads supplemented with rice starch (RS) has been evaluated for its plant growth enhancement and disease control properties. The encapsulated Bacillus licheniformis was initially characterized for indole-3-acetic acid (IAA) production, nitrogen fixing capacity, 1-aminocyclopropane-1-carboxylic acid (ACC) deaminase production and antifungal activity against Sclerotium rolfsii. In addition to this, the plant growth promoting and biocontrol properties of the encapsulated Bacillus licheniformis were also evaluated using Capsicum annuum (L.) (chilli) seedlings. From the results, the plants treated with encapsulated Bacillus licheniformis supplemented with CNPs were found to have maximum growth enhancement. At the same time, plants treated with encapsulated Bacillus licheniformis supplemented with CNPs and RS were found to have enhanced disease suppression. This revealed the application of encapsulated Bacillus licheniformis supplemented with CNPs and RS as a promising delivery system for agricultural applications.

Mass Spectrometry: A Powerful Method for Monitoring Various Type of Leukemia, Especially MALDI-TOF in Leukemia's Proteomics Studies Review

Recent success in studying the proteome, as a source of biomarkers, has completely changed our understanding of leukemia (blood cancer). The identification of differentially expressed proteins, such as relapse and drug resistance proteins involved in leukemia by using various ionization sources and mass analyzers of mass spectrometry techniques, has helped scientists find better diagnosis, prognosis, and treatment strategies. With the aid of this powerful analytical technique, we can investigate the qualification/quantification of proteins, protein-protein interactions, post-translational modifications, and find the correlation between proteins and their genes with the hope of finding the missing parts of the successful therapy puzzle. In this review, we followed different MS sources and analyzers which used for monitoring various type of leukemia, then focused on MALDI-TOF MS as a quick and reliable method for studying proteins. Due to several review published for other techniques, the present review is the first work in this field. Also, by classifying more than 400 proteins, we have found 42 proteins are involved in two or three different stages of leukemia. Finally, we have suggested six specific biomarkers for AML, one for ALL, three biomarkers with a role in the etiology of leukemia and 13 markers with the potential for further studies.

Influence of gene expression on survival of clear cell renal cell carcinoma

Approximately 10%‐20% of patients with clinically localized clear cell renal cell carcinoma (ccRCC) at time of surgery will subsequently experience metastatic progression. Although considerable progression was seen in the systemic treatment of metastatic ccRCC in last 20 years, once ccRCC spreads beyond the confines of the kidney, 5‐year survival is less than 10%. Therefore, significant clinical advances are urgently needed to improve overall survival and patient care to manage the growing number of patients with localized ccRCC. We comprehensively evaluated expression of 388 candidate genes related with survival of ccRCC by using TCGA RNAseq (n = 515), Total Cancer Care (TCC) expression array data (n = 298), and a well characterized Moffitt RCC cohort (n = 248). We initially evaluated all 388 genes for association with overall survival using TCGA and TCC data. Eighty‐one genes were selected for further analysis and tested on Moffitt RCC cohort using NanoString expression analysis. Expression of nine genes (AURKA, AURKB, BIRC5, CCNE1, MK167, MMP9, PLOD2, SAA1, and TOP2A) was validated as being associated with poor survival. Survival prognostic models showed that expression of the nine genes and clinical factors predicted the survival in ccRCC patients with AUC value: 0.776, 0.821 and 0.873 for TCGA, TCC and Moffitt data set, respectively. Some of these genes have not been previously implicated in ccRCC survival and thus potentially offer insight into novel therapeutic targets. Future studies are warranted to validate these identified genes, determine their biological mechanisms and evaluate their therapeutic potential in preclinical studies.