Effects of NaCl and iso-osmotic PEG stress on growth,osmolytes accumulation and antioxidant defense in cultured sugarcane cells

In order to discriminate between the ionic and osmotic components of salt stress, sugarcane (Saccharum officinarum L. cv. Co 86032) calli were cultured on media containing NaCl or polyethylene glycol (PEG) 8000 that exerted the same osmotic pressure (−0.7 MPa). PEG stress exposure for 15 days led to significant growth reduction and loss in water content than salt stressed and control tissues. Osmotic adjustment (OA) was observed in callus tissues grown on salt, but was not evident in callus grown on PEG. Oxidative damage to membranes, estimated in terms of accumulation of thiobarbituric acid reactive substances-TBARS and electrolytic leakage was significantly higher in both the stressed calli than the control however, the extent of damage was more in the PEG stressed calli. The stressed callus tissues showed inhibition of ascorbate peroxidase activity, while catalase activity was increased. These results indicate sensitivity of cells to PEG-mediated stress than salt stress and differences in their OA to these two stress conditions. The sensitivity to the osmotic stress indicate that expression of the stress tolerance response requires the coordinated action of different tissues in a plant and hence was not expressed at the cellular level.     

Probing binding mechanism of interleukin-6 and olokizumab: in silico design of potential lead antibodies for autoimmune and inflammatory diseases

Computer-aided antibody engineering has been successful in the design of new biologics for disease diagnosis and therapeutic interventions. Interleukin-6 (IL-6), a well-recognized drug target for various autoimmune and inflammatory diseases such as rheumatoid arthritis, multiple sclerosis, and psoriasis, was investigated in silico to design potential lead antibodies. Here, crystal structure of IL-6 along with monoclonal antibody olokizumab was explored to predict antigen–antibody (Ag???Ab)-interacting residues using DiscoTope, Paratome, and PyMOL. Tyr56, Tyr103 in heavy chain and Gly30, Ile31 in light chain of olokizumab were mutated with residues Ser, Thr, Tyr, Trp, and Phe. A set of 899 mutant macromolecules were designed, and binding affinity of these macromolecules to IL-6 was evaluated through Ag???Ab docking (ZDOCK, ClusPro, and Rosetta server), binding free-energy calculations using Molecular Mechanics/Poisson Boltzman Surface Area (MM/PBSA) method, and interaction energy estimation. In comparison to olokizumab, eight newly designed theoretical antibodies demonstrated better result in all assessments. Therefore, these newly designed macromolecules were proposed as potential lead antibodies to serve as a therapeutics option for IL-6-mediated diseases.     

Occurrence of Horizontal Gene Transfer of PIB-type ATPase Genes among Bacteria Isolated from the Uranium Rich Deposit of Domiasiat in North East India

Uranium (U) tolerant aerobic heterotrophs were isolated from the subsurface soils of one of the pre-mined U-rich deposits at Domiasiat located in the north-eastern part of India. On screening of genomic DNA from 62 isolates exhibiting superior U and heavy metal tolerance, 32 isolates were found to be positive for P_IB-type ATPase genes. Phylogenetic incongruence and anomalous DNA base compositions revealed the acquisition of P_IB-type ATPase genes by six isolates through horizontal gene transfer (HGT). Three of these instances of HGT appeared to have occurred at inter-phylum level and the other three instances indicated to have taken place at intra-phylum level. This study provides an insight into one of the possible survival strategies that bacteria might employ to adapt to environments rich in uranium and heavy metals.     

Linked Cross Sectional Schemes for Estimating Growth of Children

For estimation of growth, the efficiency of linked cross sectional scheme has been compared with pure longitudinal and cross sectional schemes. The relevant estimation theory has been developed and the expressions for the optimum estimators alongwith their variances have been derived. It has been observed that for estimation of growth, the linked cross-sectional scheme has been observed to be less efficient as compared to pure longitudinal scheme but more efficient than pure cross-sectional scheme.     

Tree ring imprints of long-term changes in climate in western Himalaya,India

Tree-ring analyses from semi-arid to arid regions in western Himalaya show immense potential for developing millennia long climate records. Millennium and longer ring-width chronologies of Himalayan pencil juniper (Juniperus polycarpos), Himalayan pencil cedar (Cedrus deodara) and Chilgoza pine (Pinus gerardiana) have been developed from different sites in western Himalaya. Studies conducted so far on various conifer species indicate strong precipitation signatures in ring-width measurement series. The paucity of weather records from stations close to tree-ring sampling sites poses difficulty in calibrating tree-ring data against climate data especially precipitation for its strong spatial variability in mountain regions. However, for the existence of strong coherence in temperature, even in data from distant stations, more robust temperature reconstructions representing regional and hemispheric signatures have been developed. Tree-ring records from the region indicate multi-century warm and cool anomalies consistent with the Medieval Warm Period and Little Ice Age anomalies. Significant relationships noted between mean premonsoon temperature over the western Himalaya and ENSO features endorse utility of climate records from western Himalayan region in understanding long-term climate variability and attribution of anthropogenic impact.     

Handling class imbalance problem in miRNA dataset associated with cancer

MiRNAs are small (~22nt long) non-coding RNA sequences; binds to the complementarity target sites in 3'' Untranslated Region (UTR) of mRNA sequences but not restricted to other mRNA regions viz., 5'' UTR and Coding sequences (CDS). Complementarity binding of miRNA to mRNA target sites either results in complete degradation of the mRNA itself or it may regulate the mRNA as an oncogene or as a tumor suppressor gene. However, the exact mechanism involved in identifying a miRNA to be associated with cancer is still unclear. Further, with the outburst in the number of miRNAs sequences recorded every year in miRBase, the gap is still widening mainly due to the laborious and economically unfavorable experimental procedures associated with the functional annotation. Motivated by the fact, we constructed a two-step support vector machine-based predictive model - miRSEQ and miRINT. However, the major pitfall during the construction of the model is the class imbalance problem. Hence, in order to overcome class imbalance problem, in the present study we empirically compare the effectiveness of two different methods viz., Synthetic Minority Oversampling Technique (SMOTE) and cost-senstive learning method. Performance measures were evaluated in terms of Precision and Recall. Based on our result, it was observed that for miRNA dataset with high class imbalance utilized for predicting association of cancer, cost-sensitive method outperformed the oversampling method.