Geranylgeranyl pyrophosphate amplifies Treg differentiation via increased IL-2 expression to ameliorate DSS-induced colitis

Blocking the mevalonate pathway for cholesterol reduction by using statin may have adverse effects including statin-induced colitis. Moreover, one of the predisposing factors for colitis is an imbalanced CD4⁺ T cell, which can be observed on the complete deletion of HMG-CoA reductase (HMGCR), a target of statins. In this study, we inquired geranylgeranyl pyrophosphate (GGPP) is responsible for maintaining the T-cell homeostasis. Following dextran sulfate sodium (DSS)-induced colitis, simvastatin increased the severity of disease, while cotreatment with GGPP, but not with cholesterol, reversed the disease magnitude. GGPP ameliorated DSS-induced colitis by increasing T_reg cells. GGPP amplified T_reg differentiation through increased IL-2/STAT 5 signaling. GGPP prenylated Ras protein, a prerequisite for extracellular signal-regulated kinase (ERK) pathway activation, leading to increased IL-2 production. Higher simvastatin dose increased the severity of colitis. GGPP ameliorated simvastatin-increased colitis by increasing T_reg cells. T_reg cells, which have the capacity to suppress inflammatory T cells and were generated through IL-2/STAT5 signaling, increased IL-2 production through prenylation and activation of the Ras/ERK pathway.     

Characterizing the Discussion of Antibiotics in the Twittersphere: What is the Bigger Picture?

Background

User content posted through Twitter has been used for biosurveillance, to characterize public perception of health-related topics, and as a means of distributing information to the general public. Most of the existing work surrounding Twitter and health care has shown Twitter to be an effective medium for these problems but more could be done to provide finer and more efficient access to all pertinent data. Given the diversity of user-generated content, small samples or summary presentations of the data arguably omit a large part of the virtual discussion taking place in the Twittersphere. Still, managing, processing, and querying large amounts of Twitter data is not a trivial task. This work describes tools and techniques capable of handling larger sets of Twitter data and demonstrates their use with the issue of antibiotics.

Objective

This work has two principle objectives: (1) to provide an open-source means to efficiently explore all collected tweets and query health-related topics on Twitter, specifically, questions such as what users are saying and how messages are spread, and (2) to characterize the larger discourse taking place on Twitter with respect to antibiotics.

Methods

Open-source software suites Hadoop, Flume, and Hive were used to collect and query a large number of Twitter posts. To classify tweets by topic, a deep network classifier was trained using a limited number of manually classified tweets. The particular machine learning approach used also allowed the use of a large number of unclassified tweets to increase performance.

Results

Query-based analysis of the collected tweets revealed that a large number of users contributed to the online discussion and that a frequent topic mentioned was resistance. A number of prominent events related to antibiotics led to a number of spikes in activity but these were short in duration. The category-based classifier developed was able to correctly classify 70% of manually labeled tweets (using a 10-fold cross validation procedure and 9 classes). The classifier also performed well when evaluated on a per category basis.

Conclusions

Using existing tools such as Hive, Flume, Hadoop, and machine learning techniques, it is possible to construct tools and workflows to collect and query large amounts of Twitter data to characterize the larger discussion taking place on Twitter with respect to a particular health-related topic. Furthermore, using newer machine learning techniques and a limited number of manually labeled tweets, an entire body of collected tweets can be classified to indicate what topics are driving the virtual, online discussion. The resulting classifier can also be used to efficiently explore collected tweets by category and search for messages of interest or exemplary content.     

Preliminary study on the protective effect of vitamin C on monosodium glutamate-induced hepatotoxicity in rats

Monosodium glutamate (MSG) is a food additive with a wide range of biological effects but its high dose and prolonged use can cause a toxic effect on the liver. Therefore, the present study was aimed at investigating the role of vitamin C in MSG-induced hepatotoxicity in rats. MSG was administered to rats (by gavage) at a dose of 6 mg/g body weight for 10 days to induce hepatotoxicity, and vitamin C at a dose of 500 mg/kg body weight was coadministered to evaluate its ameliorating effect by measuring alanine aminotransferase (ALT) and aspartate aminotransferase (AST) activities in serum; superoxide dismutase (SOD) and catalase activities in liver fraction; lipid peroxidation; and liver weight. It was found that MSG significantly (P?<?0.05) induced lipid peroxidation (LPO), increased liver weight, and increased activity of SOD and catalase in the liver of animals. The activity of ALT and AST was also increased in the serum on MSG administration. Vitamin C (500 mg/kg) coadministered with MSG significantly reduced LPO and liver weight and decreased the hepatic activity of catalase, but the activity of SOD was not reduced significantly. Also, a significant reduction in ALT and AST activity was observed. MSG induced oxidative stress and hepatic toxicity in the experimental animals at a dose of 6 mg/g body weight. Vitamin C significantly reduced the oxidative stress and hepatic toxicity induced by MSG, thereby providing a protective effect against the MSG-induced hepatotoxicity. The protective effect is associated with decreased LPO and liver weight and decreased activities of catalase, ALT, and AST.     

Development of a fused imidazo[1,2-a]pyridine based fluorescent probe for Fe3+ and Hg2+ in aqueous media and HeLa cells

A new fluorescent sensor 5 based on a fused imidazopyridine scaffold has been designed and synthesized via cascade cyclization. The reaction features the formation of three different C–N bonds in sequence. Imidazopyridine based fluorescent probe 5 exhibits highly sensitive and selective fluorescent sensing for Fe³⁺(‘turn-on’) and Hg²⁺(‘turn-off’). The excellent selectivity of imidazopyridine for Fe³⁺/Hg²⁺ was not hampered in the presence of any of the competing cations. The limit of detection (LOD) of 5 toward Fe³⁺ and Hg²⁺ has been estimated to be 4.0 ppb and 1.0 ppb, respectively, with a good linear relationship (R² = 0.99). Notably, 5 selectively detects Fe³⁺/Hg²⁺ through fluorescence enhancement signalling both in vitro and in HeLa cells.

A new fluorescent sensor 5 having fused imidazopyridine scaffold has been synthesized via cascade cyclization. It exhibits highly sensitive and selective detection of Fe³⁺ (‘turn-on’) and Hg²⁺ (‘turn-off’) in vitro and in HeLa cells.     

Recent progress in development of 2,3-diaminomaleonitrile (DAMN) based chemosensors for sensing of ionic and reactive oxygen species

2,3-Diaminomaleonitrile (DAMN) has proved to be a valuable organic π-conjugated molecule having many applications in the area of chemosensors for sensing of ionic and neutral species because of its ability to act as a building block for well-defined molecular architectures and scaffolds for preorganised arrays of functionality. In this article, we discussed the utilization of 2,3-diaminomaleonitrile (DAMN) for the design and development of chemosensor molecules and their application in the area of metal ion, anion and reactive oxygen species sensing. Along with these, we present different examples of DAMN based chemosensors for multiple ion sensing. We also discuss the ion sensing mechanism and potential uses in other related areas of research.

2,3-Diamniomaleonitrile (DAMN) is valuable π-conjugated organic scaffold molecule for designing of efficient chemosensors for sensing of ionic and Reactive Oxygen Species (ROS).     

Pandemic H1N1 influenza vaccine induces a recall response in humans that favors broadly cross-reactive memory B cells

We have previously shown that broadly neutralizing antibodies reactive to the conserved stem region of the influenza virus hemagglutinin (HA) were generated in people infected with the 2009 pandemic H1N1 strain. Such antibodies are rarely seen in humans following infection or vaccination with seasonal influenza virus strains. However, the important question remained whether the inactivated 2009 pandemic H1N1 vaccine, like the infection, could also induce these broadly neutralizing antibodies. To address this question, we analyzed B-cell responses in 24 healthy adults immunized with the pandemic vaccine in 2009. In all cases, we found a rapid, predominantly IgG-producing vaccine-specific plasmablast response. Strikingly, the majority (25 of 28) of HA-specific monoclonal antibodies generated from the vaccine-specific plasmablasts neutralized more than one influenza strain and exhibited high levels of somatic hypermutation, suggesting they were derived from recall of B-cell memory. Indeed, memory B cells that recognized the 2009 pandemic H1N1 HA were detectable before vaccination not only in this cohort but also in samples obtained before the emergence of the pandemic strain. Three antibodies demonstrated extremely broad cross-reactivity and were found to bind the HA stem. Furthermore, one stem-reactive antibody recognized not only H1 and H5, but also H3 influenza viruses. This exceptional cross-reactivity indicates that antibodies capable of neutralizing most influenza subtypes might indeed be elicited by vaccination. The challenge now is to improve upon this result and design influenza vaccines that can elicit these broadly cross-reactive antibodies at sufficiently high levels to provide heterosubtypic protection.     

Withania somnifera reverses Alzheimer's disease pathology by enhancing low-density lipoprotein receptor-related protein in liver

A 30-d course of oral administration of a semipurified extract of the root of Withania somnifera consisting predominantly of withanolides and withanosides reversed behavioral deficits, plaque pathology, accumulation of β-amyloid peptides (Aβ) and oligomers in the brains of middle-aged and old APP/PS1 Alzheimer's disease transgenic mice. It was similarly effective in reversing behavioral deficits and plaque load in APPSwInd mice (line J20). The temporal sequence involved an increase in plasma Aβ and a decrease in brain Aβ monomer after 7 d, indicating increased transport of Aβ from the brain to the periphery. Enhanced expression of low-density lipoprotein receptor-related protein (LRP) in brain microvessels and the Aβ-degrading protease neprilysin (NEP) occurred 14-21 d after a substantial decrease in brain Aβ levels. However, significant increase in liver LRP and NEP occurred much earlier, at 7 d, and were accompanied by a rise in plasma sLRP, a peripheral sink for brain Aβ. In WT mice, the extract induced liver, but not brain, LRP and NEP and decreased plasma and brain Aβ, indicating that increase in liver LRP and sLRP occurring independent of Aβ concentration could result in clearance of Aβ. Selective down-regulation of liver LRP, but not NEP, abrogated the therapeutic effects of the extract. The remarkable therapeutic effect of W. somnifera mediated through up-regulation of liver LRP indicates that targeting the periphery offers a unique mechanism for Aβ clearance and reverses the behavioral deficits and pathology seen in Alzheimer's disease models.