Exploring gene network and protein interaction analysis of neurotrophin signaling pathway in ameloblastoma.

Ameloblastoma is a non-cancerous but aggressive oral tumor emerging from odontogenic epithelial tissue involved during odontogenesis. Since there is lack in unravelling the complete molecular pathogenesis of ameloblastoma, chemotherapy is less attempted and a lot of disagreement over the optimal treatment option. Hence, till date, wide surgical resection is considered to be the reliable treatment for ameloblastoma. The Neurotrophin Signaling pathway plays an important role in neuron signaling and it is closely related with the MAPK pathway, which on the other hand regulated cell differentiation, apoptosis, proliferation, plasticity and survival. Protein- Protein Interaction analysis was analysed with STRING tool using WNL value, identified that CTNNB1, HRAS, NGFR, NGFR, and SORT1 having high interacting with BDNF, NT4, p75NTR, NGF, and NT3. The results of ontology analysis revealed that Neurotrophin signaling pathway is associated with Cell surface receptor signaling pathway, regulation of cell differentiation, regulation of development process, EGFR tyrosine kinase inhibitor resistance, MAPK signaling pathway, PI3K-Akt signaling pathway and Ras signaling pathway leading to pathogenesis involving genes. Further, clustering coefficient values of proteins BDNF, NT4, p75NTR, NGF & NT3 were identified as 0.627, 0.708, 0.367, 0.644 & 0.415. The results of molecular docking studies revealed among the selected ligands Methyl-É£-oresellinate, N-(4-Hydroxy-phenyl)-2-phenyl-N-phenylacetyl-acetamide, Atranorin and Oresellinate exhibited high binding affinity with selected protein. The key genes involved in Neurotrophin signaling pathway leading to ameloblastoma pathogenesis is revealed, which are closely associated with cell differentiation, cell proliferation, pro-apoptosis, and pro-survival regulations. Further it can be concluded that Neurotrophin signaling pathway could be one of the promising pathway to tailor the targeted drug therapy for Ameloblastoma treatment. Supplementary Information: The online version contains supplementary material available at 10.1007/s40203-024-00223-2.

Bacterial diversity and functional analysis of severe early childhood caries and recurrence in India.

Dental caries is the most prevalent oral disease affecting nearly 70% of children in India and elsewhere. Micro-ecological niche based acidification due to dysbiosis in oral microbiome are crucial for caries onset and progression. Here we report the tooth bacteriome diversity compared in Indian children with caries free (CF), severe early childhood caries (SC) and recurrent caries (RC). High quality V3-V4 amplicon sequencing revealed that SC exhibited high bacterial diversity with unique combination and interrelationship. Gracillibacteria_GN02 and TM7 were unique in CF and SC respectively, while Bacteroidetes, Fusobacteria were significantly high in RC. Interestingly, we found Streptococcus oralis subsp. tigurinus clade 071 in all groups with significant abundance in SC and RC. Positive correlation between low and high abundant bacteria as well as with TCS, PTS and ABC transporters were seen from co-occurrence network analysis. This could lead to persistence of SC niche resulting in RC. Comparative in vitro assessment of biofilm formation showed that the standard culture of S. oralis and its phylogenetically similar clinical isolates showed profound biofilm formation and augmented the growth and enhanced biofilm formation in S. mutans in both dual and multispecies cultures.

Correction to: Radical scavenging and antiproliferative effect of novel phenolic derivatives isolated from Nerium indicum against human breast cancer cell line (MCF-7)-an in silico and in vitro approach.

The correct presentation of the Author names are shown in this paper.

Radical scavenging and antiproliferative effect of novel phenolic derivatives isolated from Nerium indicum against human breast cancer cell line (MCF-7)-an in silico and in vitro approach.

Multiple drug resistance and increased side effects due to allopathic drugs has warned scientific community with a global alarm to identify molecules from natural sources to combat diseases with minimum or no side effects. The present investigation was aimed to identify and isolate secondary metabolites from traditionally used Nerium indicum using conventional column chromatography which led to the isolation of two compounds, C-I (fractions NB4f1) and C-II (fractions NC13b1). Further characterized, it is elucidated using spectral data and identified as N-(4-hydroxy-phenyl)-2-methoxy-2-phenyl-acetamide, molecular formula C15H15NO3, and molecular weight 257.3 (C-I) and N-(4-hydroxy-phenyl)-2-phenyl-N-phenylacetyl-acetamide, molecular formula C22H19NO3, and molecular weight 345.4 (C-II). Further, the isolated compounds were investigated using in silico approach by Autodock tool with four different proteins specific for cancer and in vitro assessed cell proliferation, and apoptosis against human breast cancer MCF 7 cell line. The results of the in silico model demonstrated potent binding affinity of both compounds with the proteins representing that the isolated molecules could be a drug of choice for cancer. Further, the isolated compounds revealed significant inhibition of cell proliferation (IC50 values 21 µg/mL for C-I, 19 µg/mL for C-II) with induced apoptosis with nuclear condensation effect on the MCF 7 cells in in vitro condition even at very low concentration. Compound treatment to MCF-7 cell line represented bright fetches indicating condensed chromatins and higher level of nuclear fragmentation with DAPI staining, indicating higher cell death due to induced apoptosis and confirmed using flow cytometry analysis representing inhibition of cell proliferation at S phase. Graphical abstract.

A critical analysis of state-of-the-art metagenomics OTU clustering algorithms.

Taxonomic profiling, using hyper-variable regions of 16S rRNA, is one of the important goals in metagenomics analysis. Operational taxonomic unit (OTU) clustering algorithms are the important tools to perform taxonomic profiling by grouping 16S rRNA sequence reads into OTU clusters. Presently various OTU clustering algorithms are available within different pipelines, even some pipelines have implemented more than one clustering algorithms, but there is less literature available for the relative performance and features of these algorithms. This makes the choice of using these methods unclear. In this study five current state-of-the-art OTU clustering algorithms (CDHIT, Mothur's Average Neighbour, SUMACLUST, Swarm, and UCLUST) have been comprehensively evaluated on the metagenomics sequencing data. It was found that in all the datasets, Mothur's average neighbour and Swarm created more number of OTU clusters. Based on normalized mutual information (NMI) and normalized information difference (NID), Swarm and Mothur's average neighbour showed better clustering qualities than others. But in terms of time complexity the greedy algorithms (SUMACLUST, CDHIT, and UCLUST) performed well. So there is a trade-off between quality and time, and it is necessary while analysing large size of 16S rRNA gene sequencing data.