A study on the effect of phthalate esters and their metabolites on idiopathic infertile males.

Phthalate plasticisers in medical, cosmetic and consumer products might pose serious health implications in humans including infertility. We sought to investigate the correlation, if any, between the phthalates and their metabolites and sperm quality parameters, and male infertility. Phthalate esters (15) and their metabolites (5) were estimated in the blood serum and urine samples from the age-matched 152 infertile and 75 fertile males using gas chromatography (GC) and high-performance liquid chromatography (HPLC). Finally, the data were analysed to correlate phthalate exposure and semen quality parameters in the infertility group. The estimated levels of DEHP, DBP, DIBP, BEHIP, BPBG, DPP, DIOP, DIHP, DMP, DINP, BIOP, DMOP and DICHP were significantly higher in the infertile males compared to the fertile males (p < .05 or p < .01). However, these were not found to be associated with the semen quality parameters (sperm count, motility and sperm morphology). Similarly, HPLC data revealed that the associations between semen parameters (sperm count, sperm motility and sperm morphology) and phthalate metabolite (MEHP and MBP) concentrations in urine samples from the infertile males were mostly unremarkable or statistically nonsignificant. Conclusively, environmental exposure to phthalates and their impacts on male infertility were statistically insignificant in our study groups.

Up-regulation of fibroblast growth factor receptor 1 due to prenatal tobacco exposure can lead to developmental defects in new born.

Introduction: Tobacco-smoking is one of the most important risk factor for preterm delivery, pregnancy loss, low birth weight, and fetal growth restriction. It is estimated that approximately 30% of growth-restricted neonates could be independently associated with maternal smoking.Methods: In this study, gene expression profile, GSE11798, was chosen from GEO database with an aim to perceive change in gene expression signature in new born due to maternal smoking. Enrichment analysis was performed to annotate differentially expressed genes (DEGs) through gene ontology and pathway analysis using DAVID. Protein-protein interactions and module detection of these DEGs were carried out using cytoscape v3.6.0. Thirty umbilical cord tissue samples from 15 smokers and 15 non-smokers pregnant women were included in this analysis.Results: Twenty-six differentially expressed genes (DEGs) between two groups were selected using GEO2R tool. The DEGs were observed to be participating in biological processes/pathways related to growth releasing hormone, angiogenesis, embryonic skeletal, and cardiac development. Fibroblast growth factor receptor-1 (FGFR1) was identified to be the hub node with 348 interacting partners, which regulates transcription, cell growth, differentiation, and apoptosis. The up-regulation of FGFR1 in umbilical cord tissue may lead to reproductive and developmental complications such as encephalocraniocutaneous lipomatosis, osteoglophonic dysplasia, and Pfeiffer syndrome in new-borns.Conclusion: The findings manifests the possibility of overcoming these adverse health effects in new born through FGFR1 modulating treatments during pregnancy.

Analysis of interleukin 23 and 7G10 interactions for computational design of lead antibodies against immune-mediated inflammatory diseases.

Wealth of structural data on theurapeutic targets in complex with monoclonal antibodies (mAbs) and advances in molecular modeling algorithms present exciting opportunities in the field of novel biologic design. Interleukin 23 (IL23), a well-known drug target for autoimmune diseases, in complex with mAb 7G10 offers prospect to design potent lead antibodies by traversing the complete epitope-paratope interface. Herein, key interactions aiding antibody-based neutralization in IL23-7G10 complex are resolute through PyMOL, LigPlot+, Antibody i-Patch, DiscoTope and FoldX. Six amino acids Ser31, Val33, Asn55, Lys59 in heavy chain and His34, Ser93 in light chain are subjected to in silico mutagenesis with residues Met, Trp, Ile, Leu and Arg. A set of 431 mutant macromolecules are outlined. Binding affinities of these molecules with IL23 are estimated through protein-protein docking by employing ZDOCK, ClusPro and RosettaDock. Subsequently, the macromolecules revealed comparable result with 7G10 are cross validated through binding free-energy calculations by applying Molecular Mechanics/Poisson Boltzman Surface Area method in CHARMM. Thirty nine designed theoretical antibodies showed improved outcome in all evaluations; from these, top 10 molecules showed at least nine unit better binding affinity compared to the known mAb. These molecules have the potential to act as lead antibodies. Subsequent molecular dynamics simulations too favored prospective of best ranked molecule to have therapeutic implications in autoimmune and inflammatory diseases. Abbreviations: IL23: interleukin 23; IL17: interleukin17; Ab: antibody; Ag: antigen; mAbs: monoclonal antibodies; STAT3: signal transducer and activator of transcription 3; STAT4: signal transducer and activator of transcription 4; PDB: protein databank; MM/PBSA: molecular mechanics Poisson-Boltzmann surface area; Ag-Ab: antigen- antibody complex; SPC/E: extended simple point charge; SD: steepest descents; PME: particle mesh ewald; dG: binding free energies; Fv: variable fragment.