Turner Syndrome (TS) is a condition where several genes are affected but the molecular mechanism remains unknown. Identifying the genes that regulate the TS network is one of the main challenges in understanding its aetiology. Here, we studied the regulatory network from manually curated genes reported in the literature and identified essential proteins involved in TS. The power-law distribution analysis showed that TS network carries scale-free hierarchical fractal attributes. This organization of the network maintained the self-ruled constitution of nodes at various levels without having centrality–lethality control systems. Out of twenty-seven genes culminating into leading hubs in the network, we identified two key regulators (KRs) i.e. KDM6A and BDNF. These KRs serve as the backbone for all the network activities. Removal of KRs does not cause its breakdown, rather a change in the topological properties was observed. Since essential proteins are evolutionarily conserved, the orthologs of selected interacting proteins in C. elegans, cat and macaque monkey (lower to higher level organisms) were identified. We deciphered three important interologs i.e. KDM6A-WDR5, KDM6A-ASH2L and WDR5-ASH2L that form a triangular motif. In conclusion, these KRs and identified interologs are expected to regulate the TS network signifying their biological importance.

Alzheimer's disease (AD) is the leading cause of dementia, accounts for 60 to 80 percent cases. Two main factors called β-amyloid (Aβ) plaques and tangles are prime suspects in damaging and killing nerve cells. However, oxidative stress, the process which produces free radicals in cells, is believed to promote its progression to the extent that it may responsible for the cognitive and functional decline observed in AD. As of today there are few FDA approved drugs in the market for treatment, but their cholinergic adverse effect, potentially distressing toxicity and limited targets in AD pathology limits their use. Therefore, it is crucial to find an effective compounds to combat AD. We choose 45 plant-derived natural compounds that have antioxidant properties to slow down disease progression by quenching free redicals or promoting endogenous antioxidant capacity. However, we performed molecular docking studies to investigate the binding interactions between natural compounds and 13 various anti-Alzheimer drug targets. Three known Cholinesterase inhibitors (Donepezil, Galantamine and Rivastigmine) were taken as reference drugs over natural compounds for comparison and drug-likeness studies. Few of these compounds showed good inhibitory activity besides anti-oxidant activity. Most of these compounds followed pharmacokinetics properties that make them potentially promising drug candidates for the treatment of Alzheimer's disease. Graphical Abstract : Pharmacokinatics and Molecular docking studies of 45 natural antioxidant compounds with most known Alzheimer asscociated targets. Administration (FDA) have approved two medications-cholinesterase inhibitors and Memantine. Over the past decade, much of the research on Alzheimer disease (AD) has focused on oxidative stress mechanisms and its importance in disease pathogenesis. The net effect of oxygen radicals is damaging, such damage present in AD includes advanced glycation end products [2], nitration [3], lipid peroxidation adduction products [4-5] as well as carbonyl-modified neurofilament protein and free carbonyls [6-7]. Significantly, this damage involves all neurons at risk to death in AD, not just those containing neurofibrillary tangles.Nature has gifted us lots of natural remedies in the form of fruits, leaves, bark, vegetables and nuts, etc. The various ranges of bioactive nutrients present in these natural products play a vital role in prevention and cure of various neurodegenerative diseases, such as AD,Parkinson's disease and other neuronal dysfunctions. Previous studies suggested that the naturally occurring phytochemicals, such as polyphenolic antioxidants found in fruits, vegetables, herbs and nuts, may potentially hinder neurodegeneration, and improve memory and cognitive functions.

Cardiorenal syndromes constellate primary dysfunction of either heart or kidney whereby one organ dysfunction leads to the dysfunction of another. The role of several microRNAs (miRNAs) has been implicated in number of diseases, including hypertension, heart failure, and kidney diseases. Wide range of miRNAs has been identified as ideal candidate biomarkers due to their stable expression. Current study was aimed to identify crucial miRNAs and their target genes associated with cardiorenal syndrome and to explore their interaction analysis. Three differentially expressed microRNAs (DEMs), namely, hsa-miR-4476, hsa-miR-345-3p, and hsa-miR-371a-5p, were obtained from GSE89699 and GSE87885 microRNA data sets, using R/GEO2R tools. Furthermore, literature mining resulted in the retrieval of 15 miRNAs from scientific research and review articles. The miRNAs-gene networks were constructed using miRNet (a Web platform of miRNA-centric network visual analytics). CytoHubba (Cytoscape plugin) was adopted to identify the modules and the top-ranked nodes in the network based on Degree centrality, Closeness centrality, Betweenness centrality, and Stress centrality. The overlapped miRNAs were further used in pathway enrichment analysis. We found that hsa-miR-21-5p was common in 8 pathways out of the top 10. Based on the degree, 5 miRNAs, namely, hsa-mir-122-5p, hsa-mir-222-3p, hsa-mir-21-5p, hsa-mir-146a-5p, and hsa-mir-29b-3p, are considered as key influencing nodes in a network. We suggest that the identified miRNAs and their target genes may have pathological relevance in cardiorenal syndrome (CRS) and may emerge as potential diagnostic biomarkers.

Sarcoidosis is a multi-organ disorder where immunology, genetic and environmental factors play a key role in causing Sarcoidosis, but its molecular mechanism remains unclear. Identification of its genetics profiling that regulates the Sarcoidosis network will be one of the main challenges to understand its aetiology. We have identified differentially expressed genes (DEGs) by analyzing the gene expression profiling of Sarcoidosis and compared it with healthy control. Gene set enrichment analysis showed that these DEGs were mainly enriched in the inflammatory response, immune system, and pathways in cancer. Sarcoidosis protein interaction network was constructed by a total of 877 DEGs (up-down) and calculated its network topological properties, which follow hierarchical scale-free fractal nature up to six levels of the organization. We identified a large number of leading hubs that contain six key regulators (KRs) including ICOS, CTLA4, FLT3LG, CD33, GPR29 and ITGA4 are deeply rooted in the network from top to bottom, considering a backbone of the network. We identified the transcriptional factors (TFs) which are closely interacted with KRs. These genes and their TFs regulating the Sarcoidosis network are expected to be the main target for the therapeutic approaches and potential biomarkers. However, experimental validations of KRs needed to confirm their efficacy.