Modeling the effect of imperfect staggering in product inflow using queuing theory: revisiting block stacking layout

Conventional approaches to layout design of block stacked warehouses assume perfect staggering of product inflow leading to perfect sharing of space among products. Since such an assumption is seldom true, we argue that warehouses designed using the conventional approach may result in choking situations with large quantities of inventory waiting outside the storage areas. On the other hand, liberal space allocation such as in dedicated policy might lead to under-utilization of space. In this paper, we take a fresh look at the block stacked layout problem, modeling the effect of imperfectly staggered product arrivals using queuing theory. Analytical expressions are derived for arrival time and processing time coefficients of variation using warehouse parameters and design variables. Further, we develop a bi-objective optimization model to minimize both the space cost and waiting time. Our approach provides design options over a total space cost-waiting time trade-off frontier as opposed to singular design points given by conventional approaches. Computational experiments are conducted to derive further insights into the design of block stacked warehouses.

     

In silico Platform for Prediction of N-, O- and C-Glycosites in Eukaryotic Protein Sequences

Glycosylation is one of the most abundant and an important post-translational modification of proteins. Glycosylated proteins (glycoproteins) are involved in various cellular biological functions like protein folding, cell-cell interactions, cell recognition and host-pathogen interactions. A large number of eukaryotic glycoproteins also have therapeutic and potential technology applications. Therefore, characterization and analysis of glycosites (glycosylated residues) in these proteins is of great interest to biologists. In order to cater these needs a number of in silico tools have been developed over the years, however, a need to get even better prediction tools remains. Therefore, in this study we have developed a new webserver GlycoEP for more accurate prediction of N-linked, O-linked and C-linked glycosites in eukaryotic glycoproteins using two larger datasets, namely, standard and advanced datasets. In case of standard datasets no two glycosylated proteins are more similar than 40%; advanced datasets are highly non-redundant where no two glycosites’ patterns (as defined in methods) have more than 60% similarity. Further, based on our results with several algorihtms developed using different machine-learning techniques, we found Support Vector Machine (SVM) as optimum tool to develop glycosite prediction models. Accordingly, using our more stringent and non-redundant advanced datasets, the SVM based models developed in this study achieved a prediction accuracy of 84.26%, 86.87% and 91.43% with corresponding MCC of 0.54, 0.20 and 0.78, for N-, O- and C-linked glycosites, respectively. The best performing models trained on advanced datasets were then implemented as a user-friendly web server GlycoEP (http://www.imtech.res.in/raghava/glycoep/). Additionally, this server provides prediction models developed on standard datasets and allows users to scan sequons in input protein sequences.     

Impaired Autophagy Flux is Associated with Proinflammatory Microglia Activation Following Japanese Encephalitis Virus Infection

Neurochemical Research - Role of autophagy in Japanese encephalitis viral (JEV) infection is not well known. In the present study, we reported the role of autophagy flux in microglia activation,...     

Baseline susceptibility of Asian corn borer (Ostrinia furnacalis (Guenée)) populations in Vietnam to Cry1Ab insecticidal protein

Susceptibility of Asian corn borer (ACB), Ostrinia furnacalis (Guenée) to Bacillus thuringiensis (Bt) Cry1Ab protein was studied between 2015 and 2016 with 11 ACB populations, collected from various geographical regions in Vietnam. A concentration range of Cry1Ab from 0.20 to 26.10 ng/cm² of diet was evaluated against F₁ ACB neonates using diet surface-overlay bioassays. Mortality data was recorded daily until seven days after infestation. Growth inhibition was recorded at the end of seven days. The median lethal concentration (LC₅₀) varied ≈3-fold among the different populations, ranging from 0.58 to 1.83 ng/cm² of diet with an overall mean of 0.86 ng/cm² of diet. Even the lowest concentration of 0.20 ng/cm² caused 73.53% growth inhibition. >90% growth inhibition was achieved at 0.82 ng/cm² or higher concentrations. The results reflect natural variation in Bt susceptibility among ACB populations rather than variation caused by prior exposure to selection pressures. LC₉₉ value (17.26 ng/cm²) was generated by pooling mortality data across different populations. The upper fiducial limit of LC₉₉ (24.38 ng/cm²) could be a potential diagnostic dose for future resistance monitoring programs. The findings from this study suggest that ACB populations in Vietnam are highly susceptible to Cry1Ab protein. This is the first report of Cry1Ab susceptibility of different ACB populations in Vietnam and will serve as a baseline for future resistance monitoring work.     

Potential hypotensive agents: synthesis and hypotensive activity of oxime ethers derived from 1-naphthoxepines and related compounds

The synthesis and pharmacological evaluation of substituted oximino-ethers 1 and 2 of naphth[1,2-b]- and naphth[2,1-b]-oxepin-5-ones (4 and 8) were carried out. The hypotensive activity of oximino-ethers 1 and 2 was evaluated on anaesthetized cats. The results indicated that 1c caused a fall of 80 mm/Hg for >100' at a dose of 5mg/kg iv in anaesthetized cats.     

Intrinsic contributions of polar amino acid residues toward thermal stability of an ABC-ATPase of mesophilic origin

The nucleotide-binding subunit of phosphate-specific transporter (PstB) from mesophilic bacterium, Mycobacterium tuberculosis, is a unique ATP-binding cassette (ABC) ATPase because of its unusual ability to hydrolyze ATP at high temperature. In an attempt to define the basis of thermostability, we took a theoretical approach and compared amino acid composition of this protein to that of other PstBs from available bacterial genomes. Interestingly, based on the content of polar amino acids, this protein clustered with the thermophiles.     

Drebrin Regulates Neuroblast Migration in the Postnatal Mammalian Brain

After birth, stem cells in the subventricular zone (SVZ) generate neuroblasts that migrate along the rostral migratory stream (RMS) to become interneurons in the olfactory bulb (OB). This migration is crucial for the proper integration of newborn neurons in a pre-existing synaptic network and is believed to play a key role in infant human brain development. Many regulators of neuroblast migration have been identified; however, still very little is known about the intracellular molecular mechanisms controlling this process. Here, we have investigated the function of drebrin, an actin-binding protein highly expressed in the RMS of the postnatal mammalian brain. Neuroblast migration was monitored both in culture and in brain slices obtained from electroporated mice by time-lapse spinning disk confocal microscopy. Depletion of drebrin using distinct RNAi approaches in early postnatal mice affects neuroblast morphology and impairs neuroblast migration and orientation in vitro and in vivo. Overexpression of drebrin also impairs migration along the RMS and affects the distribution of neuroblasts at their final destination, the OB. Drebrin phosphorylation on Ser142 by Cyclin-dependent kinase 5 (Cdk5) has been recently shown to regulate F-actin-microtubule coupling in neuronal growth cones. We also investigated the functional significance of this phosphorylation in RMS neuroblasts using in vivo postnatal electroporation of phosphomimetic (S142D) or non-phosphorylatable (S142A) drebrin in the SVZ of mouse pups. Preventing or mimicking phosphorylation of S142 in vivo caused similar effects on neuroblast dynamics, leading to aberrant neuroblast branching. We conclude that drebrin is necessary for efficient migration of SVZ-derived neuroblasts and propose that regulated phosphorylation of drebrin on S142 maintains leading process stability for polarized migration along the RMS, thus ensuring proper neurogenesis.     

Identification of conformational B-cell Epitopes in an antigen from its primary sequence

Background

One of the major challenges in the field of vaccine design is to predict conformational B-cell epitopes in an antigen. In the past, several methods have been developed for predicting conformational B-cell epitopes in an antigen from its tertiary structure. This is the first attempt in this area to predict conformational B-cell epitope in an antigen from its amino acid sequence.

Results

All Support vector machine (SVM) models were trained and tested on 187 non-redundant protein chains consisting of 2261 antibody interacting residues of B-cell epitopes. Models have been developed using binary profile of pattern (BPP) and physiochemical profile of patterns (PPP) and achieved a maximum MCC of 0.22 and 0.17 respectively. In this study, for the first time SVM model has been developed using composition profile of patterns (CPP) and achieved a maximum MCC of 0.73 with accuracy 86.59%. We compare our CPP based model with existing structure based methods and observed that our sequence based model is as good as structure based methods.

Conclusion

This study demonstrates that prediction of conformational B-cell epitope in an antigen is possible from is primary sequence. This study will be very useful in predicting conformational B-cell epitopes in antigens whose tertiary structures are not available. A web server CBTOPE has been developed for predicting B-cell epitope http://www.imtech.res.in/raghava/cbtope/.     

Support Vector Machine-based method for predicting subcellular localization of mycobacterial proteins using evolutionary information and motifs

Background

Annotations that describe the function of sequences are enormously important to researchers during laboratory investigations and when making computational inferences. However, there has been little investigation into the data quality of sequence function annotations. Here we have developed a new method of estimating the error rate of curated sequence annotations, and applied this to the Gene Ontology (GO) sequence database (GOSeqLite). This method involved artificially adding errors to sequence annotations at known rates, and used regression to model the impact on the precision of annotations based on BLAST matched sequences.

Results

We estimated the error rate of curated GO sequence annotations in the GOSeqLite database (March 2006) at between 28% and 30%. Annotations made without use of sequence similarity based methods (non-ISS) had an estimated error rate of between 13% and 18%. Annotations made with the use of sequence similarity methodology (ISS) had an estimated error rate of 49%.

Conclusion

While the overall error rate is reasonably low, it would be prudent to treat all ISS annotations with caution. Electronic annotators that use ISS annotations as the basis of predictions are likely to have higher false prediction rates, and for this reason designers of these systems should consider avoiding ISS annotations where possible. Electronic annotators that use ISS annotations to make predictions should be viewed sceptically. We recommend that curators thoroughly review ISS annotations before accepting them as valid. Overall, users of curated sequence annotations from the GO database should feel assured that they are using a comparatively high quality source of information.