174 research outputs found

    DESIGN AND STATISTICAL OPTIMIZATION OF A BILAYERED TABLET OF METOPROLOL SUCCINATE SUSTAINED RELEASE AND ATORVASTATIN CALCIUM IMMEDIATE RELEASE: ONCE A DAY FORMULATION IN THE MANAGEMENT OF HYPERTENSION

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     Objective: The current study involves the fabrication of oral bilayer matrix designs of a combination of two drugs, metoprolol succinate and atorvastatin calcium, the optimization of their in vitro release and characterization using the design expert software. Metoprolol succinate, a β1- selective adrenergic receptor blocking agent, is used in the management of hypertension has a half-life of approximately 4–5 h; thus, there is the need to use extended-release formulation for prolonged action. Atorvastatin is a hydroxymethylglutaryl-coenzyme A reductase inhibitor, an antilipidemic, used to lower blood cholesterol. The rationale for this fixed-dose combination is to coadminister two drugs acting by different mechanisms of action together, reduce dosing frequency, and increase patient compliance.Methods: A 32 factorial design was selected to analyze the effect of critical factors, polymer concentration of Kollidon sustained release (SR), and Eudragit RS and their interaction on the in vitro release of the SR part containing metoprolol succinate. The drug release at 2 h (Q2), 8 h (Q8), and 20 h (Q20) was taken as responses. The blends of both layers were prepared, evaluated for precompression characteristics, and compressed by direct compression. The compressed bilayer tablets were evaluated for their hardness, weight variation, friability, content uniformity, diameter, and in vitro release.Result and Conclusion: The release profile indicates Higuchi's kinetics. Contour and surface response plots show significant interaction among the formulation variables. Formulation MS06 containing 70 mg Kollidon SR and 10 mg Eurdragit RS was found to be the optimized formulation, controlling the drug release for a 24 h period

    Do rats learn conditional independence?

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    If acquired associations are to accurately represent real relevance relations, there is motivation for the hypothesis that learning will, in some circumstances, be more appropriately modelled, not as direct dependence, but as conditional independence. In a serial compound conditioning experiment, two groups of rats were presented with a conditioned stimulus (CS1) that imperfectly (50%) predicted food, and was itself imperfectly predicted by a CS2. Groups differed in the proportion of CS2 presentations that were ultimately followed by food (25% versus 75%). Thus, the information presented regarding the relevance of CS2 to food was ambiguous between direct dependence and conditional independence (given CS1). If rats learnt that food was conditionally independent of CS2, given CS1, subjects of both groups should thereafter respond similarly to CS2 alone. Contrary to the conditionality hypothesis, subjects attended to the direct food predictability of CS2, suggesting that rats treat even distal stimuli in a CS sequence as immediately relevant to food, not conditional on an intermediate stimulus. These results urge caution in representing indirect associations as conditional associations, accentuate the theoretical weight of the Markov condition in graphical models, and challenge theories to articulate the conditions under which animals are expected to learn conditional associations, if ever.All funding for the project was internal, from Indiana University

    Small molecule inhibitor of Igf2bp1 represses Kras and a pro-oncogenic phenotype in cancer cells

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    Igf2bp1 is an oncofetal RNA binding protein whose expression in numerous types of cancers is associated with upregulation of key pro-oncogenic RNAs, poor prognosis, and reduced survival. Importantly, Igf2bp1 synergizes with mutations in Kras to enhance signalling and oncogenic activity, suggesting that molecules inhibiting Igf2bp1 could have therapeutic potential. Here, we isolate a small molecule that interacts with a hydrophobic surface at the boundary of Igf2bp1 KH3 and KH4 domains, and inhibits binding to Kras RNA. In cells, the compound reduces the level of Kras and other Igf2bp1 mRNA targets, lowers Kras protein, and inhibits downstream signalling, wound healing, and growth in soft agar, all in the absence of any toxicity. This work presents an avenue for improving the prognosis of Igf2bp1-expressing tumours in lung, and potentially other, cancer(s)

    Improving the performance of DomainDiscovery of protein domain boundary assignment using inter-domain linker index

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    BACKGROUND: Knowledge of protein domain boundaries is critical for the characterisation and understanding of protein function. The ability to identify domains without the knowledge of the structure – by using sequence information only – is an essential step in many types of protein analyses. In this present study, we demonstrate that the performance of DomainDiscovery is improved significantly by including the inter-domain linker index value for domain identification from sequence-based information. Improved DomainDiscovery uses a Support Vector Machine (SVM) approach and a unique training dataset built on the principle of consensus among experts in defining domains in protein structure. The SVM was trained using a PSSM (Position Specific Scoring Matrix), secondary structure, solvent accessibility information and inter-domain linker index to detect possible domain boundaries for a target sequence. RESULTS: Improved DomainDiscovery is compared with other methods by benchmarking against a structurally non-redundant dataset and also CASP5 targets. Improved DomainDiscovery achieves 70% accuracy for domain boundary identification in multi-domains proteins. CONCLUSION: Improved DomainDiscovery compares favourably to the performance of other methods and excels in the identification of domain boundaries for multi-domain proteins as a result of introducing support vector machine with benchmark_2 dataset

    The role of amputation as an outcome measure in cellular therapy for critical limb ischemia: implications for clinical trial design

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    <p>Abstract</p> <p>Background</p> <p>Autologous bone marrow-derived stem cells have been ascribed an important therapeutic role in No-Option Critical limb Ischemia (NO-CLI). One primary endpoint for evaluating NO-CLI therapy is major amputation (AMP), which is usually combined with mortality for AMP-free survival (AFS). Only a trial which is double blinded can eliminate physician and patient bias as to the timing and reason for AMP. We examined factors influencing AMP in a prospective double-blinded pilot RCT (2:1 therapy to control) of 48 patients treated with site of service obtained bone marrow cells (BMAC) as well as a systematic review of the literature.</p> <p>Methods</p> <p>Cells were injected intramuscularly in the CLI limbs as either BMAC or placebo (peripheral blood). Six month AMP rates were compared between the two arms. Both patient and treating team were blinded of the assignment in follow-up examinations. A search of the literature identified 9 NO-CLI trials, the control arms of which were used to determine 6 month AMP rates and the influence of tissue loss.</p> <p>Results</p> <p>Fifteen amputations occurred during the 6 month period, 86.7% of these during the first 4 months. One amputation occurred in a Rutherford 4 patient. The difference in amputation rate between patients with rest pain (5.6%) and those with tissue loss (46.7%), irrespective of treatment group, was significant (p = 0.0029). In patients with tissue loss, treatment with BMAC demonstrated a lower amputation rate than placebo (39.1% vs. 71.4%, p = 0.1337). The Kaplan-Meier time to amputation was longer in the BMAC group than in the placebo group (p = 0.067). Projecting these results to a pivotal trial, a bootstrap simulation model showed significant difference in AFS between BMAC and placebo with a power of 95% for a sample size of 210 patients. Meta-analysis of the literature confirmed a difference in amputation rate between patients with tissue loss and rest pain.</p> <p>Conclusions</p> <p>BMAC shows promise in improving AMP-free survival if the trends in this pilot study are validated in a larger pivotal trial. The difference in amp rate between Rutherford 4 & 5 patients suggests that these patients should be stratified in future RCTs.</p

    The Association Between Pre-pregnancy BMI and Preterm Delivery in a Diverse Southern California Population of Working Women

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    Whereas preterm birth has consistently been associated with low maternal pre-pregnancy weight, the relationship with high pre-pregnancy weight has been inconsistent. We quantified the pre-pregnancy BMI—preterm delivery (PTD) relationship using traditional BMI categories (underweight, normal weight, overweight and obese) as well as continuous BMI. Eligible women participated in California’s statewide prenatal screening program, worked during pregnancy, and delivered a live singleton birth in Southern California in 2002–2003. The final analytic sample included 354 cases delivering at <37 weeks, as identified by clinical estimate of gestational age from screening records, and 710 term normal-birthweight controls. Multivariable logistic regression models using categorical BMI levels and continuous BMI were compared. In categorical analyses, PTD was significantly associated with pre-pregnancy underweight only. Nonparametric local regression revealed a V-shaped relationship between continuous BMI and PTD, with minimum risk at the high end of normal, around 24 kg/m2. The odds ratio (OR) for PTD associated with low BMI within the normal range (19 kg/m2) was 2.84 (95%CI = 1.61–5.01); ORs for higher BMI in the overweight (29 kg/m2) and obese (34 kg/m2) ranges were 1.42 (95%CI = 1.10–1.84) and 2.01 (95% CI = 1.20–3.39) respectively, relative to 24 kg/m2). BMI categories obscured the preterm delivery risk associated with low-normal, overweight, and obese BMI. We found that higher BMI up to around 24 kg/m2 is increasingly protective of preterm delivery, beyond which a higher body mass index becomes detrimental. Current NHLBI/WHO BMI categories may be inadequate for identifying women at higher risk for PTD

    Influence of maternal and social factors as predictors of low birth weight in Italy

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    Abstract Background The purpose of this study is to provide insight into the determinants of low birth weight (LBW) in Italy. Methods The study was carried out in a non-teaching hospital in Catanzaro (Italy). All LBW and very LBW newborns (200) were included in the study and a random sample of 400 newborns weighing ≥ 2500 g was selected. Data were collected from the delivery certificates during one year. Smoking activity of mother and familiar and/or social support during pregnancy was gathered through telephone interviews. Results Overall annual LBW rate was 11.8%. Among LBW newborn there were 125 preterm and 75 term. Younger mothers, those who smoked during pregnancy, and had fewer prenatal care visits were more likely to deliver a LBW child; moreover, preterm newborns, delivered by caesarean section, and twin or multiple birth were significantly more likely to have a LBW. The comparison of very LBW ( Conclusion Several modifiable factors affect the risk of LBW, even when universal access to health care is freely available, but socio-economic status appears to correlate only to very LBW.</p

    Representing and comparing protein structures as paths in three-dimensional space

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    BACKGROUND: Most existing formulations of protein structure comparison are based on detailed atomic level descriptions of protein structures and bypass potential insights that arise from a higher-level abstraction. RESULTS: We propose a structure comparison approach based on a simplified representation of proteins that describes its three-dimensional path by local curvature along the generalized backbone of the polypeptide. We have implemented a dynamic programming procedure that aligns curvatures of proteins by optimizing a defined sum turning angle deviation measure. CONCLUSION: Although our procedure does not directly optimize global structural similarity as measured by RMSD, our benchmarking results indicate that it can surprisingly well recover the structural similarity defined by structure classification databases and traditional structure alignment programs. In addition, our program can recognize similarities between structures with extensive conformation changes that are beyond the ability of traditional structure alignment programs. We demonstrate the applications of procedure to several contexts of structure comparison. An implementation of our procedure, CURVE, is available as a public webserver
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