184 research outputs found
Formulation, Characterization and Antihelminthic Activity Testing of Nitazoxanide Superporous Hydrogel Tablets
In the pharmaceutical field controlled release products have the ability to maintain desired medicament concentration or a longer period of time. Certain drugs are relatively insoluble in water and have high dose requirements that render unsuitable formulation difficulties in sustained release formulations. Nitazoxanide which is a high dose water insoluble antiprotozoal drug was formulated with the aim. To modulate gastro-retentive dosage form based on the superporous hydrogel composites. Foaming technique was used in the preparation of SPH composites. The superporous hydrogels were extremely sensitive to pH of swelling media and good porosity. Superporous hydrogels tablets of nitazoxanide showed good pre-compressional and post-compressional properties. Formulation X is the best formulation containing chitosan, polyvinyl alcohol, formaldehyde, exhibited good swelling ratio. The compatibility studies were performed by Fourier Transform Infrared (FT-IR) Spectroscopic Studies, Differential Scanning Calorimetry Studies (DSC). All formulations were evaluated for stability, drug content, and kinetic drug release & in-vitro drug release profile. It was concluded that the proposed gastro-retention drug delivery provides a different supply of nitazoxanide directly to the stomach.
Keywords: Nitazoxanide, Anti protozoal, foaming technique, Chitosa
FORMULATION AND EVALUATION OF EXTENDED RELEASE PELLETS OF PIOGLITAZONE HYDROCHLORIDE USING NATURAL AND SYNTHETIC POLYMERS BY FLUIDIZED BED COATING TECHNIQUE
Objective: The objective of the current work was to develop Pioglitazone hydrochloride (HCl) pellets coated with natural polymer extracted from peas gum and also to compare the drug release profile with coatings containing semi-synthetic and synthetic polymers.
Methods: Fluidized bed coating technique was used to develop pellets. A 22 factorial design was employed to study the effect of independent variables (inlet air temperature and spray rate), on dependent variables (percentage entrapment efficiency, percentage friability, and average particle size). Optimization was done by fitting experimental data to the software program. Obtained pellets were subjected to different evaluation parameters which are critical in the development of the dosage form. An in vitro lag phase study was carried out for all batches in simulated gastric fluid (0.1N HCl) for 5 h and in vitro drug release study was carried out for optimized batch (E-2 and P-3) in simulated intestinal fluid (pH 7.4 phosphate buffer).
Results: The optimized batches E-2 and P-3 showed satisfactory percentage entrapment efficiency of 92.66±1.52, percentage friability of 0.57±0.03, and average particle size of 1424±16 μm. All batches maintained lag phase for 5 h in 0.1N HCl. An optimized batch of two different sizes exhibited a burst release within 30 min in a simulated intestinal fluid with no significant difference in release rate constant (*p>0.05) and followed first-order kinetics.
Conclusion: Thus, Pioglitazone HCl pulsatile pellets were successfully developed for treating diabetes mellitus by fluidized bed coating technique employing factorial design
Development Of Al-B-C Master Alloy Under External Fields
This study investigates the application of external fields in the development of an Al-B-C alloy, with the aim of synthesizing in situ Al3BC particles. A combination of ultrasonic cavitation and distributive mixing was applied for uniform dispersion of insoluble graphite particles in the Al melt, improving their wettability and its subsequent incorporation into the Al matrix. Lower operating temperatures facilitated the reduction in the amount of large clusters of reaction phases, with Al3BC being identified as the main phase in XRD analysis. The distribution of Al3BC particles was quantitatively evaluated. Grain refinement experiments reveal that Al-B-C alloy can act as a master alloy for Al-4Cu and AZ91D alloys, with average grain size reduction around 50% each at 1wt%Al-1.5B-2C additions
Disease Ontology: a backbone for disease semantic integration
The Disease Ontology (DO) database (http://disease-ontology.org) represents a comprehensive knowledge base of 8043 inherited, developmental and acquired human diseases (DO version 3, revision 2510). The DO web browser has been designed for speed, efficiency and robustness through the use of a graph database. Full-text contextual searching functionality using Lucene allows the querying of name, synonym, definition, DOID and cross-reference (xrefs) with complex Boolean search strings. The DO semantically integrates disease and medical vocabularies through extensive cross mapping and integration of MeSH, ICD, NCI's thesaurus, SNOMED CT and OMIM disease-specific terms and identifiers. The DO is utilized for disease annotation by major biomedical databases (e.g. Array Express, NIF, IEDB), as a standard representation of human disease in biomedical ontologies (e.g. IDO, Cell line ontology, NIFSTD ontology, Experimental Factor Ontology, Influenza Ontology), and as an ontological cross mappings resource between DO, MeSH and OMIM (e.g. GeneWiki). The DO project (http://diseaseontology.sf.net) has been incorporated into open source tools (e.g. Gene Answers, FunDO) to connect gene and disease biomedical data through the lens of human disease. The next iteration of the DO web browser will integrate DO's extended relations and logical definition representation along with these biomedical resource cross-mappings
Social learning against data falsification in sensor networks
Sensor networks generate large amounts of geographically-distributed data. The conventional approach to exploit this data is to first gather it in a special node that then performs processing and inference. However, what happens if this node is destroyed, or even worst, if it is hijacked? To explore this problem, in this work we consider a smart attacker who can take control of critical nodes within the network and use them to inject false information. In order to face this critical security thread, we propose a novel scheme that enables data aggregation and decision-making over networks based on social learning, where the sensor nodes act resembling how agents make decisions in social networks. Our results suggest that social learning enables high network resilience, even when a significant portion of the nodes have been compromised by the attacker
Measurement of the diffractive structure function in deep inelastic scattering at HERA
This paper presents an analysis of the inclusive properties of diffractive
deep inelastic scattering events produced in interactions at HERA. The
events are characterised by a rapidity gap between the outgoing proton system
and the remaining hadronic system. Inclusive distributions are presented and
compared with Monte Carlo models for diffractive processes. The data are
consistent with models where the pomeron structure function has a hard and a
soft contribution. The diffractive structure function is measured as a function
of \xpom, the momentum fraction lost by the proton, of , the momentum
fraction of the struck quark with respect to \xpom, and of . The \xpom
dependence is consistent with the form \xpoma where
in all bins of and
. In the measured range, the diffractive structure function
approximately scales with at fixed . In an Ingelman-Schlein type
model, where commonly used pomeron flux factor normalisations are assumed, it
is found that the quarks within the pomeron do not saturate the momentum sum
rule.Comment: 36 pages, latex, 11 figures appended as uuencoded fil
Observation of hard scattering in photoproduction events with a large rapidity gap at HERA
Events with a large rapidity gap and total transverse energy greater than 5
GeV have been observed in quasi-real photoproduction at HERA with the ZEUS
detector. The distribution of these events as a function of the
centre of mass energy is consistent with diffractive scattering. For total
transverse energies above 12 GeV, the hadronic final states show predominantly
a two-jet structure with each jet having a transverse energy greater than 4
GeV. For the two-jet events, little energy flow is found outside the jets. This
observation is consistent with the hard scattering of a quasi-real photon with
a colourless object in the proton.Comment: 19 pages, latex, 4 figures appended as uuencoded fil
GLI1 Confers Profound Phenotypic Changes upon LNCaP Prostate Cancer Cells That Include the Acquisition of a Hormone Independent State
The GLI (GLI1/GLI2) transcription factors have been implicated in the development
and progression of prostate cancer although our understanding of how they
actually contribute to the biology of these common tumours is limited. We
observed that GLI reporter activity was higher in normal (PNT-2) and
tumourigenic (DU145 and PC-3) androgen-independent cells compared to
androgen-dependent LNCaP prostate cancer cells and, accordingly, GLI mRNA levels
were also elevated. Ectopic expression of GLI1 or the constitutively active
ΔNGLI2 mutant induced a distinct cobblestone-like morphology in LNCaP cells
that, regarding the former, correlated with increased GLI2 as well as expression
of the basal/stem-like markers CD44, β1-integrin, ΔNp63 and BMI1, and
decreased expression of the luminal marker AR (androgen receptor). LNCaP-GLI1
cells were viable in the presence of the AR inhibitor bicalutamide and gene
expression profiling revealed that the transcriptome of LNCaP-GLI1 cells was
significantly closer to DU145 and PC-3 cells than to control LNCaP-pBP (empty
vector) cells, as well as identifying LCN2/NGAL as a highly induced transcript
which is associated with hormone independence in breast and prostate cancer.
Functionally, LNCaP-GLI1 cells displayed greater clonal growth and were more
invasive than control cells but they did not form colonies in soft agar or
prostaspheres in suspension suggesting that they do not possess inherent stem
cell properties. Moreover, targeted suppression of GLI1 or GLI2 with siRNA did
not reverse the transformed phenotype of LNCaP-GLI1 cells nor did double
GLI1/GLI2 knockdowns activate AR expression in DU145 or PC-3 cells. As such,
early targeting of the GLI oncoproteins may hinder progression to a hormone
independent state but a more detailed understanding of the mechanisms that
maintain this phenotype is required to determine if their inhibition will
enhance the efficacy of anti-hormonal therapy through the induction of a luminal
phenotype and increased dependency upon AR function
The Gene Ontology knowledgebase in 2023
The Gene Ontology (GO) knowledgebase (http://geneontology.org) is a comprehensive resource concerning the functions of genes and gene products (proteins and noncoding RNAs). GO annotations cover genes from organisms across the tree of life as well as viruses, though most gene function knowledge currently derives from experiments carried out in a relatively small number of model organisms. Here, we provide an updated overview of the GO knowledgebase, as well as the efforts of the broad, international consortium of scientists that develops, maintains, and updates the GO knowledgebase. The GO knowledgebase consists of three components: (1) the GO-a computational knowledge structure describing the functional characteristics of genes; (2) GO annotations-evidence-supported statements asserting that a specific gene product has a particular functional characteristic; and (3) GO Causal Activity Models (GO-CAMs)-mechanistic models of molecular "pathways" (GO biological processes) created by linking multiple GO annotations using defined relations. Each of these components is continually expanded, revised, and updated in response to newly published discoveries and receives extensive QA checks, reviews, and user feedback. For each of these components, we provide a description of the current contents, recent developments to keep the knowledgebase up to date with new discoveries, and guidance on how users can best make use of the data that we provide. We conclude with future directions for the project
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