Multivariate wind power curve modeling using multivariate adaptive regression splines and regression trees.

Wind turbine power curve (WTPC) serves as an important tool for wind turbine condition monitoring and wind power forecasting. Due to complex environmental factors and technical issues of the wind turbines, there are many outliers and inconsistencies present in the recorded data, which cannot be removed through any pre-processing technique. However, the current WTPC models have limited ability to understand such complex relation between wind speed and wind power and have limited non-linear fitting ability, which limit their modelling accuracy. In this paper, the accuracy of the WTPC models is improved in two ways: first is by developing multivariate models and second is by proposing MARS as WTPC modeling technique. MARS is a regression-based flexible modeling technique that automatically models complex the nonlinearities in the data using spline functions. Experimental results show that by incorporating additional inputs the accuracy of the power curve estimation is significantly improved. Also by studying the error distribution it is proved that multivariate models successfully mitigate the adverse effect of hidden outliers, as their distribution has higher peaks and lesser standard deviation, which proves that the errors, are more converged to zero compared to the univariate models. Additionally, MARS with its superior non-linear fitting ability outperforms the compared methods in terms of the error metrics and ranks higher than regression trees and several other popular parametric and non-parametric methods. Finally, an outlier detection method is developed to remove the hidden outliers from the data using the error distribution of the modeled power curves.

Deciphering the Structural Enigma of HLA Class-II Binding Peptides for Enhanced Immunoinformatics-based Prediction of Vaccine Epitopes.

Vaccines remain the most efficacious means to avoid and eliminate morbid diseases associated with high morbidity and mortality. Clinical trials indicate the gaining impetus of peptide vaccines against diseases for which an effective treatment still remains obscure. CD4 T-cell-based peptide vaccines involve immunization with antigenic determinants from pathogens or neoplastic cells that possess the ability to elicit a robust T helper cell response, which subsequently activates other arms of the immune system. The available in silico predictors of human leukocyte antigen II (HLA-II) binding peptides are sequence-based techniques, which ostensibly have balanced sensitivity and specificity. Structural analysis and understanding of the cognate peptide and HLA-II interactions are essential to empirically derive a successful peptide vaccine. However, the availability of structure-based epitope prediction algorithms is inadequate compared with sequence-based prediction methods. The present study is an attempt to understand the structural aspects of HLA-II binders by analyzing the Protein Data Bank (PDB) complexes of pHLA-II. Furthermore, we mimic the peptide exchange mechanism and demonstrate the structural implication of an acidic environment on HLA-II binders. Finally, we discuss a structure-guided approach to decipher potential HLA-II binders within an antigenic protein. This strategy may accurately predict the peptide epitopes and thus aid in designing successful peptide vaccines.

Mutation in the Squalene Epoxidase Gene of Trichophyton interdigitale and Trichophyton rubrum Associated with Allylamine Resistance.

Dermatophytosis, the commonest superficial fungal infection, has gained recent attention due to its change of epidemiology and treatment failures. Despite the availability of several agents effective against dermatophytes, the incidences of chronic infection, reinfection, and treatment failures are on the rise. Trichophyton rubrum and Trichophyton interdigitale are the two species most frequently identified among clinical isolates in India. Consecutive patients (n = 195) with suspected dermatophytosis during the second half of 2014 were included in this study. Patients were categorized into relapse and new cases according to standard definitions. Antifungal susceptibility testing of the isolated Trichophyton species (n = 127) was carried out with 12 antifungal agents: fluconazole, voriconazole, itraconazole, ketoconazole, sertaconazole, clotrimazole, terbinafine, naftifine, amorolfine, ciclopirox olamine, griseofulvin, and luliconazole. The squalene epoxidase gene was evaluated for mutation (if any) in 15 T. interdigitale and 5 T. rubrum isolates exhibiting high MICs for terbinafine. A T1189C mutation was observed in four T. interdigitale and two T. rubrum isolates. This transition leads to the change of phenylalanine to leucine in the 397th position of the squalene epoxidase enzyme. In homology modeling the mutant residue was smaller than the wild type and positioned in the dominant site of squalene epoxidase during drug interaction, which may lead to a failure to block the ergosterol biosynthesis pathway by the antifungal drug.

T-cell exhaustion in tuberculosis: pitfalls and prospects.

T-cells play an important role in immunity but when these cells are overexposed to specific antigens, their function may decline. This state is usually referred to as exhaustion and the T-cells show reduced proliferation and functions such as cytokine release. T-cell exhaustion has been observed in several cancers as well as in chronic infections such as tuberculosis (TB). In chronic Mycobacterium tuberculosis (Mtb) infection, T-cells may express the exhaustion phenotype and show a progressive loss of secretion of IL-2, IFN-γ and TNF-α. In some cancers and chronic infection models, blocking the exhaustion phenotype can be achieved with the so-called checkpoint inhibitors. This results in tumor control and more effective immunity. However, in the case of TB, the T-cell exhaustion results are quite ambiguous. Hence, there is a need to investigate and explain the contribution of checkpoint at a molecular level to the outcome of events in chronic TB. Such information could help to guide the success of new therapies against chronic TB. This review highlights the mechanism through which T-cells undergo exhaustion and the approaches that can avert such events. This will help to design immunotherapies that can reinvigorate T-cell potency to protect patients from TB.

Rv2031c of Mycobacterium tuberculosis: a master regulator of Rv2028-Rv2031 (HspX) operon.

Genes belonging to the same operon are transcribed as a single mRNA molecule in all prokaryotes. The genes of the same operon are presumed to be involved in similar metabolic and physiological processes. Hence, computational analysis of constituent proteins could provide important clues to the functional relationships within the operonic genes. This tends to be more fruitful in the case of Mycobacterium tuberculosis (Mtb), considering the number of hypothetical genes with unknown functions and interacting partners. Dramatic advances in the past decade have increased our knowledge of the mechanisms that tubercle bacilli employ to survive within the host. But the phenomenon of Mtb latency continues to baffle all. Rv2031c belonging to dormancy regulon of Mtb is predominantly expressed during latency, with myriad immunological roles. Thus we attempted to analyze the operon comprising Rv2031c protein to gain insights into its role during latency. In the current study, we have carried out computational analysis of proteins encoded by genes known to be a part of this operon. Our study includes phylogenetic analysis, modeling of protein 3D structures, and protein interaction network analysis. We describe the mechanistic role in the establishment of latency and regulation of DevS-DevR component system. Additionally, we have identified the probable role of these proteins in carbohydrate metabolism, erythromycin tolerance, and nucleotide synthesis. Hence, these proteins can modulate the metabolism of Mtb inside the host cells and can be important for its survival in latency. The functional characterization and interactome of this important operon can give insight into its role during latency along with the exploitation of constituent proteins as drug targets and vaccine candidates.

Challenges and solutions for a rational vaccine design for TB-endemic regions.

Vaccines have been successful for global eradication or control of dreaded diseases such as smallpox, diphtheria, tetanus, yellow fever, whooping cough, polio, and measles. Unfortunately, this success has not been achieved for controlling tuberculosis (TB) worldwide. Bacillus Calmette Guérin (BCG) is the only available vaccine against TB. Paradoxically, BCG has deciphered success in the Western world but has failed in TB-endemic areas. In this article, we highlight and discuss the aspects of immunity responsible for controlling Mycobacterium tuberculosis infection and factors responsible for the failure of BCG in TB-endemic countries. In addition, we also suggest strategies that contribute toward the development of successful vaccine in protecting populations where BCG has failed.

Decision-making critical amino acids: role in designing peptide vaccines for eliciting Th1 and Th2 immune response.

CD4 T cells play a cardinal role in orchestrating immune system. Differentiation of CD4 T cells to Th1 and Th2 effector subsets depends on multiple factors such as relative intensity of interactions between T cell receptor with peptide-major histocompatibility complex, cytokine milieu, antigen dose, and costimulatory molecules. Literature supports the critical role of peptide's binding affinity to Human Leukocyte Antigens (HLAs) and in the differentiation of naïve CD4 T cells to Th1 and Th2 subsets. However, there exists no definite report addressing very precisely the correlation between physicochemical properties (hydrophobicity, hydrophilicity), pattern, position of amino acids in peptide and their role in skewing immune response towards Th1 and Th2 cells. This may play a significant role in designing peptide vaccines. Hence in the present study, we have evaluated the relationship between amino acid pattern and their influence in differentiation of Th1 and Th2 cells. We have used a data set of 320 peptides, whose role has been already established experimentally in the generation of either Th1 or Th2 immune response. Further, characterization was done based on binding affinity, promiscuity, amino acid pattern and binding conformation of peptides. We have observed that distinct amino acids in peptides elicit either Th1 or Th2 immunity. Consequently, this study signifies that alteration in the sequence and type of selected amino acids in the HLA class II binding peptides can modulate the differentiation of Th1 and Th2 cells. Therefore, this study may have an important implication in providing a platform for designing peptide-based vaccine candidates that can trigger desired Th1 or Th2 response.