Measurements of neutrino oscillation parameters from the T2K experiment using 3.6×1021 protons on target

The T2K experiment presents new measurements of neutrino oscillation parameters using 19.7 ( 16.3 ) × 10 20 protons on target (POT) in (anti-)neutrino mode at the far detector (FD). Compared to the previous analysis, an additional 4.7 × 10 20 POT neutrino data was collected at the FD. Significant improvements were made to the analysis methodology, with the near-detector analysis introducing new selections and using more than double the data. Additionally, this is the first T2K oscillation analysis to use NA61/SHINE data on a replica of the T2K target to tune the neutrino flux model, and the neutrino interaction model was improved to include new nuclear effects and calculations. Frequentist and Bayesian analyses are presented, including results on sin 2 θ 13 and the impact of priors on the δ CP measurement. Both analyses prefer the normal mass ordering and upper octant of sin 2 θ 23 with a nearly maximally CP-violating phase. Assuming the normal ordering and using the constraint on sin 2 θ 13 from reactors, sin 2 θ 23 = 0 . 561 - 0.032 + 0.021 using Feldman-Cousins corrected intervals, and Δ m 32 2 = 2 . 494 - 0.058 + 0.041 × 10 - 3 eV 2 using constant Δ χ 2 intervals. The CP-violating phase is constrained to δ CP = - 1 . 97 - 0.70 + 0.97 using Feldman-Cousins corrected intervals, and δ CP = 0 , π is excluded at more than 90% confidence level. A Jarlskog invariant of zero is excluded at more than 2 σ credible level using a flat prior in δ CP , and just below 2 σ using a flat prior in sin δ CP . When the external constraint on sin 2 θ 13 is removed, sin 2 θ 13 = 28 . 0 - 6.5 + 2.8 × 10 - 3 , in agreement with measurements from reactor experiments. These results are consistent with previous T2K analyses.

Search for Electron Antineutrino Appearance in a Long-Baseline Muon Antineutrino Beam

Electron antineutrino appearance is measured by the T2K experiment in an accelerator-produced antineutrino beam, using additional neutrino beam operation to constrain parameters of the Pontecorvo-Maki-Nakagawa-Sakata (PMNS) mixing matrix. T2K observes 15 candidate electron antineutrino events with a background expectation of 9.3 events. Including information from the kinematic distribution of observed events, the hypothesis of no electron antineutrino appearance is disfavored with a significance of 2.40σ and no discrepancy between data and PMNS predictions is found. A complementary analysis that introduces an additional free parameter which allows non-PMNS values of electron neutrino and antineutrino appearance also finds no discrepancy between data and PMNS predictions.

Principal metabolic flux mode analysis

Motivation

In the analysis of metabolism, two distinct and complementary approaches are frequently used: Principal component analysis (PCA) and stoichiometric flux analysis. PCA is able to capture the main modes of variability in a set of experiments and does not make many prior assumptions about the data, but does not inherently take into account the flux mode structure of metabolism. Stoichiometric flux analysis methods, such as Flux Balance Analysis (FBA) and Elementary Mode Analysis, on the other hand, are able to capture the metabolic flux modes, however, they are primarily designed for the analysis of single samples at a time, and not best suited for exploratory analysis on a large sets of samples.

Results

We propose a new methodology for the analysis of metabolism, called Principal Metabolic Flux Mode Analysis (PMFA), which marries the PCA and stoichiometric flux analysis approaches in an elegant regularized optimization framework. In short, the method incorporates a variance maximization objective form PCA coupled with a stoichiometric regularizer, which penalizes projections that are far from any flux modes of the network. For interpretability, we also introduce a sparse variant of PMFA that favours flux modes that contain a small number of reactions. Our experiments demonstrate the versatility and capabilities of our methodology. The proposed method can be applied to genome-scale metabolic network in efficient way as PMFA does not enumerate elementary modes. In addition, the method is more robust on out-of-steady steady-state experimental data than competing flux mode analysis approaches.

Availability and implementation

Matlab software for PMFA and SPMFA and dataset used for experiments are available in https://github.com/aalto-ics-kepaco/PMFA.

Supplementary information

Supplementary data are available at Bioinformatics online.

Search for CP Violation in Neutrino and Antineutrino Oscillations by the T2K Experiment with 2.2×10^{21} Protons on Target

The T2K experiment measures muon neutrino disappearance and electron neutrino appearance in accelerator-produced neutrino and antineutrino beams. With an exposure of 14.7(7.6)×10^{20} protons on target in the neutrino (antineutrino) mode, 89 ν_{e} candidates and seven anti-ν_{e} candidates are observed, while 67.5 and 9.0 are expected for δ_{CP}=0 and normal mass ordering. The obtained 2σ confidence interval for the CP-violating phase, δ_{CP}, does not include the CP-conserving cases (δ_{CP}=0, π). The best-fit values of other parameters are sin^{2}θ_{23}=0.526_{-0.036}^{+0.032} and Δm_{32}^{2}=2.463_{-0.070}^{+0.071}×10^{-3}  eV^{2}/c^{4}.

Analysis of Fluxomic Experiments with Principal Metabolic Flux Mode Analysis

In the analysis of metabolism, two distinct and complementary approaches are frequently used: Principal component analysis (PCA) and stoichiometric flux analysis. PCA is able to capture the main modes of variability in a set of experiments and does not make many prior assumptions about the data, but does not inherently take into account the flux mode structure of metabolism. Stoichiometric flux analysis methods, such as Flux Balance Analysis (FBA) and Elementary Mode Analysis, on the other hand, are able to capture the metabolic flux modes, however, they are primarily designed for the analysis of single samples at a time, and assume the stoichiometric steady state of the metabolic network.We will discuss a new methodology for the analysis of metabolism, called Principal Metabolic Flux Mode Analysis (PMFA), which marries the PCA and stoichiometric flux analysis approaches in an elegant regularized optimization framework. In short, the method incorporates a variance maximization objective form PCA coupled with a stoichiometric regularizer, which penalizes projections that are far from any flux modes of the network. For interpretability, we also discuss a sparse variant of PMFA that favors flux modes that contain a small number of reactions. PMFA has several benefits: (1) it can be applied to large metabolic network in efficient way as PMFA does not enumerate elementary modes, (2) the method is more robust to the steady-state violations than competing approaches, and (3) can compactly capture the variation in the data by a few factors. This chapter will describe the detailed steps how to do the above task on experimental data from fluxomic and gene expression measurements.

Combined Analysis of Neutrino and Antineutrino Oscillations at T2K

T2K reports its first results in the search for CP violation in neutrino oscillations using appearance and disappearance channels for neutrino- and antineutrino-mode beams. The data include all runs from January 2010 to May 2016 and comprise 7.482×10^{20} protons on target in neutrino mode, which yielded in the far detector 32 e-like and 135  μ-like events, and 7.471×10^{20} protons on target in antineutrino mode, which yielded 4 e-like and 66  μ-like events. Reactor measurements of sin^{2}2θ_{13} have been used as an additional constraint. The one-dimensional confidence interval at 90% for the phase δ_{CP} spans the range (-3.13, -0.39) for normal mass ordering. The CP conservation hypothesis (δ_{CP}=0, π) is excluded at 90% C.L.

Measurement of Coherent π^{+} Production in Low Energy Neutrino-Carbon Scattering

We report the first measurement of the flux-averaged cross section for charged current coherent π^{+} production on carbon for neutrino energies less than 1.5 GeV, and with a restriction on the final state phase space volume in the T2K near detector, ND280. Comparisons are made with predictions from the Rein-Sehgal coherent production model and the model by Alvarez-Ruso et al., the latter representing the first implementation of an instance of the new class of microscopic coherent models in a neutrino interaction Monte Carlo event generator. We observe a clear event excess above background, disagreeing with the null results reported by K2K and SciBooNE in a similar neutrino energy region. The measured flux-averaged cross sections are below those predicted by both the Rein-Sehgal and Alvarez-Ruso et al.

Measurement of Muon Antineutrino Oscillations with an Accelerator-Produced Off-Axis Beam

T2K reports its first measurements of the parameters governing the disappearance of ν[over ¯]_{μ} in an off-axis beam due to flavor change induced by neutrino oscillations. The quasimonochromatic ν[over ¯]_{μ} beam, produced with a peak energy of 0.6 GeV at J-PARC, is observed at the far detector Super-Kamiokande, 295 km away, where the ν[over ¯]_{μ} survival probability is expected to be minimal. Using a data set corresponding to 4.01×10^{20} protons on target, 34 fully contained μ-like events were observed. The best-fit oscillation parameters are sin^{2}(θ[over ¯]_{23})=0.45 and |Δm[over ¯]_{32}^{2}|=2.51×10^{-3}  eV^{2} with 68% confidence intervals of 0.38-0.64 and 2.26-2.80×10^{-3}  eV^{2}, respectively. These results are in agreement with existing antineutrino parameter measurements and also with the ν_{μ} disappearance parameters measured by T2K.

Measurement of the inclusive electron neutrino charged current cross section on carbon with the T2K near detector

The T2K off-axis near detector ND280 is used to make the first differential cross-section measurements of electron neutrino charged current interactions at energies ∼1  GeV as a function of electron momentum, electron scattering angle, and four-momentum transfer of the interaction. The total flux-averaged ν(e) charged current cross section on carbon is measured to be ⟨σ⟩(ϕ)=1.11±0.10(stat)±0.18(syst)×10⁻³⁸ cm²/nucleon. The differential and total cross-section measurements agree with the predictions of two leading neutrino interaction generators, NEUT and GENIE. The NEUT prediction is 1.23×10⁻³⁸ cm²/nucleon and the GENIE prediction is 1.08×10⁻³⁸ cm²/nucleon. The total ν(e) charged current cross-section result is also in agreement with data from the Gargamelle experiment.

Precise measurement of the neutrino mixing parameter θ23 from muon neutrino disappearance in an off-axis beam

New data from the T2K neutrino oscillation experiment produce the most precise measurement of the neutrino mixing parameter θ23. Using an off-axis neutrino beam with a peak energy of 0.6 GeV and a data set corresponding to 6.57×10(20) protons on target, T2K has fit the energy-dependent νμ oscillation probability to determine oscillation parameters. The 68% confidence limit on sin(2)(θ23) is 0.514(-0.056)(+0.055) (0.511±0.055), assuming normal (inverted) mass hierarchy. The best-fit mass-squared splitting for normal hierarchy is Δm32(2)=(2.51±0.10)×10(-3)  eV(2)/c(4) (inverted hierarchy: Δm13(2)=(2.48±0.10)×10(-3)  eV(2)/c(4)). Adding a model of multinucleon interactions that affect neutrino energy reconstruction is found to produce only small biases in neutrino oscillation parameter extraction at current levels of statistical uncertainty.

Observation of electron neutrino appearance in a muon neutrino beam

The T2K experiment has observed electron neutrino appearance in a muon neutrino beam produced 295 km from the Super-Kamiokande detector with a peak energy of 0.6 GeV. A total of 28 electron neutrino events were detected with an energy distribution consistent with an appearance signal, corresponding to a significance of 7.3σ when compared to 4.92±0.55 expected background events. In the Pontecorvo-Maki-Nakagawa-Sakata mixing model, the electron neutrino appearance signal depends on several parameters including three mixing angles θ12, θ23, θ13, a mass difference Δm(32)(2) and a CP violating phase δ(CP). In this neutrino oscillation scenario, assuming |Δm(32)(2)|=2.4×10(-3)  eV(2), sin(2)θ(23)=0.5, and Δm322>0 (Δm(32)(2)<0), a best-fit value of sin(2)2θ(13)=0.140(-0.032)(+0.038) (0.170(-0.037)(+0.045)) is obtained at δ(CP)=0. When combining the result with the current best knowledge of oscillation parameters including the world average value of θ(13) from reactor experiments, some values of δ(CP) are disfavored at the 90% C.L.

Measurement of neutrino oscillation parameters from muon neutrino disappearance with an off-axis beam

The T2K Collaboration reports a precision measurement of muon neutrino disappearance with an off-axis neutrino beam with a peak energy of 0.6 GeV. Near detector measurements are used to constrain the neutrino flux and cross section parameters. The Super-Kamiokande far detector, which is 295 km downstream of the neutrino production target, collected data corresponding to 3.01×10(20) protons on target. In the absence of neutrino oscillations, 205±17 (syst) events are expected to be detected while only 58 muon neutrino event candidates are observed. A fit to the neutrino rate and energy spectrum, assuming three neutrino flavors and normal mass hierarchy yields a best-fit mixing angle sin2(θ23)=0.514±0.082 and mass splitting |Δm(32)(2)|=2.44(-0.15)(+0.17)×10(-3) eV2/c4. Our result corresponds to the maximal oscillation disappearance probability.

Indication of electron neutrino appearance from an accelerator-produced off-axis muon neutrino beam

The T2K experiment observes indications of ν(μ) → ν(e) appearance in data accumulated with 1.43×10(20) protons on target. Six events pass all selection criteria at the far detector. In a three-flavor neutrino oscillation scenario with |Δm(23)(2)| = 2.4×10(-3)  eV(2), sin(2)2θ(23) = 1 and sin(2)2θ(13) = 0, the expected number of such events is 1.5±0.3(syst). Under this hypothesis, the probability to observe six or more candidate events is 7×10(-3), equivalent to 2.5σ significance. At 90% C.L., the data are consistent with 0.03(0.04) < sin(2)2θ(13) < 0.28(0.34) for δ(CP) = 0 and a normal (inverted) hierarchy.

Acetylcholinesterase enzyme inhibitory potential of standardized extract of Trigonella foenum graecum L and its constituents

Ethno pharmacological approach has provided several leads to identify potential new drugs from plant sources, including those for memory disorders. Acetylcholinesterase inhibitors (AChEI) give a symptomatic relief to some of the clinical manifestations of the disease. The main objective of this study is to standardize the extract of Trigonella foenum graecum L with trigonelline by HPTLC method and determine the in vitro AChE inhibitory activity of Trigonella foenum graecum L and its constituents using galanthamine as a reference. Different concentrations of hydro alcoholic extract of Trigonella foenum graecum and trigonelline were subjected to HPTLC analysis using the mobile phase n propanol, methanol and water (4:1:2, v/v). The R(f) of trigonelline was found to be 0.43, and the correlation coefficient of 0.99 was indicative of good linear dependence of peak area on concentration. The concentration of trigonelline was found to be 13mgg(-1)w/w in the hydro alcoholic extract of Trigonella foenum graecum. The AChE inhibitory activity of crude fenugreek seed extracts, fractions and trigonelline was evaluated using Ellman's method in 96-well micro plate's assay and TLC bioassay detection. The ethyl acetate fraction of the alcohol extract (IC50 53.00 +/- 17.33microg/ml), and total alkaloid fraction (IC50 9.23+/-6.08microg/ml) showed potential AChE inhibition. Trigonelline showed IC50 233+/-0.12microM. Galanthamine was used as standard and it showed inhibition of acetyl cholinesterase with an IC50 value of 1.27+/-0.21microM.

Prediction of candidate primary immunodeficiency disease genes using a support vector machine learning approach

Screening and early identification of primary immunodeficiency disease (PID) genes is a major challenge for physicians. Many resources have catalogued molecular alterations in known PID genes along with their associated clinical and immunological phenotypes. However, these resources do not assist in identifying candidate PID genes. We have recently developed a platform designated Resource of Asian PDIs, which hosts information pertaining to molecular alterations, protein-protein interaction networks, mouse studies and microarray gene expression profiling of all known PID genes. Using this resource as a discovery tool, we describe the development of an algorithm for prediction of candidate PID genes. Using a support vector machine learning approach, we have predicted 1442 candidate PID genes using 69 binary features of 148 known PID genes and 3162 non-PID genes as a training data set. The power of this approach is illustrated by the fact that six of the predicted genes have recently been experimentally confirmed to be PID genes. The remaining genes in this predicted data set represent attractive candidates for testing in patients where the etiology cannot be ascribed to any of the known PID genes.

A linear programming approach for estimating the structure of a sparse linear genetic network from transcript profiling data

BACKGROUND

A genetic network can be represented as a directed graph in which a node corresponds to a gene and a directed edge specifies the direction of influence of one gene on another. The reconstruction of such networks from transcript profiling data remains an important yet challenging endeavor. A transcript profile specifies the abundances of many genes in a biological sample of interest. Prevailing strategies for learning the structure of a genetic network from high-dimensional transcript profiling data assume sparsity and linearity. Many methods consider relatively small directed graphs, inferring graphs with up to a few hundred nodes. This work examines large undirected graphs representations of genetic networks, graphs with many thousands of nodes where an undirected edge between two nodes does not indicate the direction of influence, and the problem of estimating the structure of such a sparse linear genetic network (SLGN) from transcript profiling data.

RESULTS

The structure learning task is cast as a sparse linear regression problem which is then posed as a LASSO (l1-constrained fitting) problem and solved finally by formulating a Linear Program (LP). A bound on the Generalization Error of this approach is given in terms of the Leave-One-Out Error. The accuracy and utility of LP-SLGNs is assessed quantitatively and qualitatively using simulated and real data. The Dialogue for Reverse Engineering Assessments and Methods (DREAM) initiative provides gold standard data sets and evaluation metrics that enable and facilitate the comparison of algorithms for deducing the structure of networks. The structures of LP-SLGNs estimated from the INSILICO1, INSILICO2 and INSILICO3 simulated DREAM2 data sets are comparable to those proposed by the first and/or second ranked teams in the DREAM2 competition. The structures of LP-SLGNs estimated from two published Saccharomyces cerevisae cell cycle transcript profiling data sets capture known regulatory associations. In each S. cerevisiae LP-SLGN, the number of nodes with a particular degree follows an approximate power law suggesting that its degree distributions is similar to that observed in real-world networks. Inspection of these LP-SLGNs suggests biological hypotheses amenable to experimental verification.

CONCLUSION

A statistically robust and computationally efficient LP-based method for estimating the topology of a large sparse undirected graph from high-dimensional data yields representations of genetic networks that are biologically plausible and useful abstractions of the structures of real genetic networks. Analysis of the statistical and topological properties of learned LP-SLGNs may have practical value; for example, genes with high random walk betweenness, a measure of the centrality of a node in a graph, are good candidates for intervention studies and hence integrated computational - experimental investigations designed to infer more realistic and sophisticated probabilistic directed graphical model representations of genetic networks. The LP-based solutions of the sparse linear regression problem described here may provide a method for learning the structure of transcription factor networks from transcript profiling and transcription factor binding motif data.

RAPID: Resource of Asian Primary Immunodeficiency Diseases

Availability of a freely accessible, dynamic and integrated database for primary immunodeficiency diseases (PID) is important both for researchers as well as clinicians. To build a PID informational platform and also as a part of action to initiate a network of PID research in Asia, we have constructed a web-based compendium of molecular alterations in PID, named Resource of Asian Primary Immunodeficiency Diseases (RAPID), which is available as a worldwide web resource at http://rapid.rcai.riken.jp/. It hosts information on sequence variations and expression at the mRNA and protein levels of all genes reported to be involved in PID patients. The main objective of this database is to provide detailed information pertaining to genes and proteins involved in primary immunodeficiency diseases along with other relevant information about protein–protein interactions, mouse studies and microarray gene-expression profiles in various organs and cells of the immune system. RAPID also hosts a tool, mutation viewer, to predict deleterious and novel mutations and also to obtain mutation-based 3D structures for PID genes. Thus, information contained in this database should help physicians and other biomedical investigators to further investigate the role of these molecules in PID.

Inclusive K(S);(0)K(S);(0) resonance production in ep collisions at HERA

Inclusive K_{S};{0}K_{S};{0} production in ep collisions at the DESY ep collider HERA was studied with the ZEUS detector using an integrated luminosity of 0.5 fb;{-1}. Enhancements in the mass spectrum were observed and are attributed to the production of f_{2}(1270)/a_{2};{0}(1320), f_{2};{'}(1525) and f_{0}(1710). Masses and widths were obtained using a fit which takes into account theoretical predictions based on SU(3) symmetry arguments, and are consistent with the Particle Data Group values. The f_{0}(1710) state, which has a mass consistent with a glueball candidate, was observed with a statistical significance of 5 standard deviations. However, if this state is the same as that seen in gammagamma-->K_{S};{0}K_{S};{0}, it is unlikely to be a pure glueball state.

Pharmacological validation of Kantha chendooram for antiulcer activity in modified pylorus ligated (shay) rat model

The use of metals and minerals is predominant in siddha system of medicine. As per siddha concept, peptic ulcer is known as Valigunmam, the basic abnormality appears to be the derangement of metabolism in the stomach and duodenum resulting in malfunctioning of the secretory process of gastric mucosa. Chendooram is a group of siddha drugs which is used for anemia, obesity, rheumatic diseases; abdominal tumours etc.During the present study standardized Kantha chendooram was selected and evaluated for its anti-ulcer activity, which could not be attempted by researchers earlier.

PEGylated Peptide Dendrimeric Carriers for the Delivery of Antimalarial Drug Chloroquine Phosphate

PURPOSE

The present study was aimed at developing and exploring the use of uncoated and chondroitin sulfate A (CSA) coated PEGylated poly-L-lysine-based dendrimers for controlled and sustained delivery of a blood schizonticide, chloroquine phosphate (CQ).

METHODS

The poly-L-lysine-based peptide dendrimers with PEG amine core prepared and coated with CSA were used to encapsulate the drug molecules by dialysis method. Effect of CSA coating on the surface characteristics, drug entrapment, drug release, stability, hemolytic toxicity, macrophageal interactions, and cytoadherence were determined and compared with those of uncoated systems.

RESULTS

The CSA coating of the carriers was found to increase size and drug loading capacity, and reduce drug release rate and hemolytic toxicity. Transmission electron microscopic study revealed the surface properties of the systems. Stability studies had shown increased stability of the formulations on CSA coating. There was a significant reduction in hemolytic toxicity and cytotoxicity of CQ by the present dendrimeric carriers, which became more prominent on further CSA conjugation of the equivalent drug-loaded dendrimeric carriers. There were also significant reduction in levels of ring and trophozoite stages of Plasmodium falciparum in liquid culture when treated with CSA coated dendrimers because of the expression of similar carbohydrate receptors as that by placental and cerebral barriers for infected red blood cells. The systems were also found suitable for prolonging and controlling the blood level of drug as indicated by blood level and organ distribution studies in albino rats on intravenous administration, precluding any significant hematological or toxicological manifestations.

CONCLUSION

Thus it can be said that CSA coating can improve drug-loading capacity, control and sustain the release of CQ from such carriers, and can suitably act as safer and effective carriers for intravenous CQ administration.

Glycodendrimeric nanoparticulate carriers of primaquine phosphate for liver targeting

In the present study it was intended to deliver primaquine phosphate (PP), a liver schizonticide directly to liver cells using polypropyleneimine (PPI) dendrimers-coated peripherally with galactose. PPI dendrimers were synthesized by consecutive Michael double addition reaction (using ethyelenediamine as core), followed by hydrogenation reaction. Galactose conjugation was carried out by ring opening reactions, followed by Schiff's reaction and reduction to secondary amine in sodium acetate buffer (pH 4.0). IR, NMR, MASS spectroscopy were used for the confirmation of synthesis of uncoated and coated dendrimers. The formulations were made by equilibrium dialysis of dendrimers with the solution of PP. Then the formulations were characterized by TEM for size and shape. Release rate, hemolytic toxicity; bio-distribution and blood level studies were also performed on lyophilized formulations. The results obtained indicated that galactose coating of PPI systems increases the drug entrapment efficiency by 5-15 times depending upon generations. Galactose coating prolonged release up to 5-6 days as compared to 1-2 days for uncoated PPI systems. The hemolytic toxicity, blood level and hematological studies proved these systems to be safer and suitable for sustained drug delivery. Blood level studies proved the suitability of the systems for the prolonged circulations and delivery of PP to liver. The galactose coating of PPI dendrimers can therefore make the PPI systems more effective and suitable for targeted delivery of Primaquine phosphate to liver.

Chitosan hydrochloride based microspheres of albendazole for colonic drug delivery

Microspheres of chitosan hydrochloride (CH) were prepared in order to deliver albendazole specifically into the colon. Microspheres were prepared by an emulsion method using different ratios of drug and CH (1:1 to 1:5), agitation speeds (500 to 1500 rpm) and concentrations of glutaraldehyde in toluene as the cross-linking agent (0.25 to 1.0% w/v). The effect of polymer concentration, stirring rate and concentration of cross-linking agent on the particle size and drug loading was studied. With an increase in CH concentration, the average particle size was increased. Increased agitation speed reduced the size of the microspheres but higher agitation speed resulted in irregularly shaped microspheres. Increasing the concentration of cross-linking agent produced more regularly shaped microspheres of smaller size. The drug loading was highest at a drug: CH ratio of 1:3, stirring speed 1000 rpm and 0.75% w/v concentration of cross-linking agent. The effect of CH concentration on in vitro drug release from the microspheres was evaluated in simulated g.i.t fluids. A comparative in vitro drug release study of the optimized formulation was carried out in simulated colonic fluid, with and without 2% rat caecal content. The drug release in 24 h was 48.9% in colonic fluid without rat caecal content, and 76.5% in colonic fluid with rat caecal contents.

A PEGylated dendritic nanoparticulate carrier of fluorouracil

The present study was aimed at developing and exploring the use of uncoated and PEGylated newer PAMAM dendrimers for delivery of anti-cancer drug 5-fluorouracil. For this study, successive Michael addition and exhaustive amidation reactions were used to synthesize 4.0 G PAMAM dendrimers, using ethylenediamine as core and methylmethacrylate as propagating agent. The dendrimer was PEGylated using N-hydroxysuccinimide-activated carboxymethyl MPEG-5000. IR and NMR data proved the synthesis. Various physicochemical parameters, SEM, TEM, lambda(max) values, hemolytic toxicity, drug entrapment, drug release and blood-level studies of both PEGylated and non-PEGylated systems were determined and compared. The PEGylation of the systems was found to have increased their drug-loading capacity, reduced their drug release rate and hemolytic toxicity. TEM study revealed surface properties of the systems. Stability studies had shown its stability at room temperature in dark. The systems were found suitable for prolonged delivery of an anti-cancer drug by in vitro and blood-level studies in albino rats, without producing any significant hematological disturbances. PEGylation has been found to be suitable for modification of PAMAM dendrimers for reduction of drug leakage and hemolytic toxicity. This, in turn, could improve drug-loading capacity and stabilize such systems in body. The study suggests use of such PEGylated dendrimeric systems as nanoparticulate depot type of system for drug administration.

Pegnology: a review of PEG-ylated systems

Polyethylene glycol conjugation or linking with the system is called PEGylation. Many novel drug systems are used for the delivery of drugs and bioactive substances to particular sites in a controlled or sustained manner, but various side effects or shortcomings restrict their use for the intended purpose. The shortcomings such as RES uptake, drug leakage, immunogenicity, stability, hemolytic toxicity etc. can generally be overcome by PEGylation of novel drug delivery systems such as liposomes, proteins, enzymes, drugs, nanoparticles etc. In this article the whole aspect of PEGylation starting from activation and derivatisation of poly (ethylene glycol) to the linking and designing of systems and their purification and characterization is discussed. The various properties of Pegylated systems are also discussed.