Network pharmacology and bioinformatics approach reveals the therapeutic mechanism of action of curcumin in Alzheimer disease.

Curcumin is a natural anti-inflammatory and antioxidant substance which plays a major role in reducing the amyloid plaques formation, which is the major cause of Alzheimer's disease (AD). Consequently, a methodical approach was used to select the potential protein targets of curcumin in AD through network pharmacology. In this study, through integrative methods, AD targets of curcumin through SwissTargetPrediction database, STITCH database, BindingDB, PharmMapper, Therapeutic Target Database (TTD), Online Mendelian Inheritance in Man (OMIM) database were predicted followed by gene enrichment analysis, network construction, network topology, and docking studies. Gene ontology analysis facilitated identification of a list of possible AD targets of curcumin (74 targets genes). The correlation of the obtained targets with AD was analysed by using gene ontology (GO) pathway enrichment analyses and Kyoto Encyclopaedia of Genes and Genomes (KEGG). We have incorporated the applied network pharmacological approach to identify key genes. Furthermore, we have performed molecular docking for analysing the mechanism of curcumin. In order to validate the temporospatial expression of key genes in human central nervous system (CNS), we searched the Human Brain Transcriptome (HBT) dataset. We identified top five key genes namely, PPARγ, MAPK1, STAT3, KDR and APP. Further validated the expression profiling of these key genes in publicly available brain data expression profile databases. In context to a valuable addition in the treatment of AD, this study is concluded with novel insights into the therapeutic mechanisms of curcumin, will ease the treatment of AD with the clinical application of curcumin.

Photoperiodically driven transcriptome-wide changes in the hypothalamus reveal transcriptional differences between physiologically contrasting seasonal life-history states in migratory songbirds.

We investigated time course of photoperiodically driven transcriptional responses in physiologically contrasting seasonal life-history states in migratory blackheaded buntings. Birds exhibiting unstimulated winter phenotype (photosensitive state; responsive to photostimulation) under 6-h short days, and regressed summer phenotype (photorefractory state; unresponsiveness to photostimulation) under 16-h long days, were released into an extended light period up to 22 h of the day. Increased tshß and dio2, and decreased dio3 mRNA levels in hypothalamus, and low prdx4 and high il1ß mRNA levels in blood confirmed photoperiodic induction by hour 18 in photosensitive birds. Further, at hours 10, 14, 18 and 22 of light exposure, the comparison of hypothalamus RNA-Seq results revealed transcriptional differences within and between states. Particularly, we found reduced expression at hour 14 of transthyretin and proopiomelanocortin receptor, and increased expression at hour 18 of apolipoprotein A1 and carbon metabolism related genes in the photosensitive state. Similarly, valine, leucine and isoleucine degradation pathway genes and superoxide dismutase 1 were upregulated, and cocaine- and amphetamine-regulated transcript and gastrin-releasing peptide were downregulated in the photosensitive state. These results show life-history-dependent activation of hypothalamic molecular pathways involved in initiation and maintenance of key biological processes as early as on the first long day.

Seasonal reproductive state determines gene expression in the hypothalamus of a latitudinal migratory songbird during the spring and autumn migration.

We investigated gonadal effects on hypothalamic transcription of genes in sham-operated and castrated redheaded buntings photostimulated into spring and autumn migratory states. RNA-Seq results showed testes-dependent differences between spring and autumn migratory states. In particular, differentially expressed genes enriched G-protein-coupled receptor and calcium-ion signaling pathways during spring and autumn states, respectively. qPCR assay showed attenuated gabra5, ttr, thra and thrb expressions, suggesting reduced GABA and thyroid hormone effects on photo-sexual response in spring. In spring castrates, reduced npy, tac1 and nrcam and increased ank3 expression suggested testicular effects on the appetite, prolactin release and neuronal functions, whereas in autumn castrates, reduced rasgrp1, grm5 and grin1, and increased mras expression suggested testicular effects on the ras, G-protein and glutamate signaling pathways. Castration-induced reciprocal switching of pomc and pdyn expressions suggested effects on the overall homeostasis in both seasons. These results demonstrate transcriptome-wide changes, with season-dependent roles of testes in songbird migration.

Hypothalamic and liver transcriptome from two crucial life-history stages in a migratory songbird.

NEW FINDINGS: What is the central question of this study? What are the molecular underpinnings of the seasonal adaptation in a latitudinal migratory songbird? What is the main finding and its importance? We found changes in mRNA levels after a photoperiod-induced alteration of seasonal state in a captive long-distance latitudinal avian migrant. The hypothalamus and liver transcriptomes revealed genes involved in the regulatory and functional pathways between non-migratory and migratory states. Our results provide insights into mechanisms underlying homeostasis during seasonal changes that are conserved across most species, including humans. ABSTRACT: Very little is understood about genetic mechanisms underlying the onset of spring migration in latitudinal avian migrants. To gain insight into the genetic architecture of the hypothalamus and liver tissues of a long-distance migrant, we examined and compared the transcriptome profile of captive night-migratory black-headed buntings (Emberiza melanocephala) between photoperiod-induced winter non-migratory (WnM) and spring migratory (SM) life-history states under short and long days, respectively. High-throughput 454 pyrosequenced transcripts were mapped initially with reference to the genome of two phylogenetically close species, Taeniopygia guttata and Ficedula albicollis. The F. albicollis genome gave higher annotation results and was used for further analysis. A total of 216 (78 in hypothalamus; 138 in liver) genes were found to be expressed differentially between the WnM and SM life-history states. These genes were enriched for physiological pathways that might be involved in the regulation of seasonal migrations in birds. For example, genes for the ATP binding pathway in the hypothalamus were expressed at a significantly higher level in SM than in the WnM life-history state. Likewise, upregulated genes associated with the myelin sheath and focal adhesion were enriched in the hypothalamus, and those with cell-to-cell junction, intracellular protein transport, calcium ion transport and small GTPase-mediated signal transduction were enriched in the liver. Many of these genes are a part of physiological pathways potentially involved in the regulation of seasonal migration in birds. These results show molecular changes at the regulatory and metabolic levels associated with seasonal transitions in a long-distance migrant and provide the basis for future studies aimed at unravelling the genetic control of migration in birds.

Podium: Ranking Data Using Mixed-Initiative Visual Analytics.

People often rank and order data points as a vital part of making decisions. Multi-attribute ranking systems are a common tool used to make these data-driven decisions. Such systems often take the form of a table-based visualization in which users assign weights to the attributes representing the quantifiable importance of each attribute to a decision, which the system then uses to compute a ranking of the data. However, these systems assume that users are able to quantify their conceptual understanding of how important particular attributes are to a decision. This is not always easy or even possible for users to do. Rather, people often have a more holistic understanding of the data. They form opinions that data point A is better than data point B but do not necessarily know which attributes are important. To address these challenges, we present a visual analytic application to help people rank multi-variate data points. We developed a prototype system, Podium, that allows users to drag rows in the table to rank order data points based on their perception of the relative value of the data. Podium then infers a weighting model using Ranking SVM that satisfies the user's data preferences as closely as possible. Whereas past systems help users understand the relationships between data points based on changes to attribute weights, our approach helps users to understand the attributes that might inform their understanding of the data. We present two usage scenarios to describe some of the potential uses of our proposed technique: (1) understanding which attributes contribute to a user's subjective preferences for data, and (2) deconstructing attributes of importance for existing rankings. Our proposed approach makes powerful machine learning techniques more usable to those who may not have expertise in these areas.