Bio-Inorganic Studies on the Fe(II) Sparfloxacin Complex

The qualitative and quantitative analysis of an antibiotic drug, 5-amino-1 cyclopropyl-7 (cis-3, 5 dimethyl-1-piperazyl)-6,8- dihydro-1, 4 dihydro-4-oxo-3-quinoline carboxylic acid (Sparfloxacin, SFX) and its pharmaceutical formulation i.e.sparx-100 tablet, has been done using polarographic and amperometric methods. Complexation behavior of SFX with Fe(II), both in solid and liquid phases has been studied by elemental analysis, IR.-spectra and polarographic and amperometric methods. SFX produces a single cathodic reduction wave in 0.1 M ammonium tartrate (supporting electrolyte) at pH 6.0 ±0.1. The wave is diffusion controlled and wave height is proportional to the concentration of SFX. The complex is also reversibly reduced at the electrode surface with diffusion-controlled kinetics. The stoichiometry of the Fe(II)- SFX complex is 1:1. Antibacterial studies on the drug and its metal complex have been performed against different bacteria. The observed results revealed the complex to be more potent in its antibacterial activity as compared to the parent drug. On the basis of observed results it could be concluded that the prepared Fe(II)- SFX complex may be recommended to the therapeutic experts for its possible use as a more potent antibiotic drug

Fe(III)-Chloroquine Complex: A New Potent Compound in Wellness Industries of High Antimicrobial and Antimalarial Activities

Fe(III)- Chloroquine complex has been synthesized and screened for its physicochemical, microbial as well as pharmacological activity have been done in solid and aqueous phase. On the basis of elemental analysis, polarographic studies, amperometric titration and IR spectral studies the probable formula for the complex has been determined at 25±1OC and ionic strength of µ= 1.0[KCl]. Raper's paper disc method was used for microbial study against various pathogenic bacteria and fungi. In vivo syudy of Swiss mice [25-30gm] were used for antimalarial activity against Chloroquine and its complex on xyline-Alcoholic activity test Kidney, liver and serum of these rats were also studied. On the basis of observed result it could be concluded that Fe (III)-Chloroquine complex were found to be non-toxic and more potent than pure chloroquine drug

Functional classification of proteins based on projection of amino acid sequences: application for prediction of protein kinase substrates

<p>Abstract</p> <p>Background</p> <p>The knowledge about proteins with specific interaction capacity to the protein partners is very important for the modeling of cell signaling networks. However, the experimentally-derived data are sufficiently not complete for the reconstruction of signaling pathways. This problem can be solved by the network enrichment with predicted protein interactions. The previously published <it>in silico </it>method PAAS was applied for prediction of interactions between protein kinases and their substrates.</p> <p>Results</p> <p>We used the method for recognition of the protein classes defined by the interaction with the same protein partners. 1021 protein kinase substrates classified by 45 kinases were extracted from the Phospho.ELM database and used as a training set. The reasonable accuracy of prediction calculated by leave-one-out cross validation procedure was observed in the majority of kinase-specificity classes. The random multiple splitting of the studied set onto the test and training set had also led to satisfactory results. The kinase substrate specificity for 186 proteins extracted from TRANSPATH^®database was predicted by PAAS method. Several kinase-substrate interactions described in this database were correctly predicted. Using the previously developed ExPlain™ system for the reconstruction of signal transduction pathways, we showed that addition of the newly predicted interactions enabled us to find the possible path between signal trigger, TNF-alpha, and its target genes in the cell.</p> <p>Conclusions</p> <p>It was shown that the predictions of protein kinase substrates by PAAS were suitable for the enrichment of signaling pathway networks and identification of the novel signaling pathways. The on-line version of PAAS for prediction of protein kinase substrates is freely available at <url>http://www.ibmc.msk.ru/PAAS/</url>.</p

Optimization of sentinel lymph node biopsy in breast cancer using an operative gamma camera

<p>Abstract</p> <p>Background</p> <p>Sentinel lymph node (SLN) procedure is now a widely accepted method of LN staging in selected invasive breast cancers (unifocal, size ≤ 2 cm, clinically N0, without previous treatment). Complete axillary clearance is no longer needed if the SLN is negative. However, the oncological safety of this procedure remains to be addressed in randomized clinical trials. One main pitfall is the failure to visualize SLN, resulting in incorrect tumor staging, leading to suboptimal treatment or axillary recurrence. Operative gamma cameras have therefore been developed to optimize the SLN visualization and the quality control of surgery.</p> <p>Case presentation</p> <p>A 44-year-old female patient with a 14-mm infiltrative ductal carcinoma underwent the SLN procedure. An operative gamma camera was used during and after the surgery. The conventional lymphoscintigraphy showed only one SLN, which was also detected by the operative gamma camera, then removed and measured (9.6 kBq). It was analyzed by frozen sections, showing no cancer cells. During this analysis, the exploration of the axillary area with the operative gamma camera enabled the identification of a second SLN with low activity (0.5 kBq) that conventional lymphoscintigraphy, surgical probe and blue staining had failed to visualize. Histological examination revealed a macrometastasis. Axillary clearance was then performed, followed by a postoperative image proving that no SLN remained. Therefore, the use of the operative gamma camera prevented an under-estimation of staging which would have resulted in a suboptimal treatment for this patient.</p> <p>Conclusion</p> <p>This case report illustrates that an efficient operative gamma camera may be able to decrease the risk of false negative rate of the SLN procedure, and could be an additional tool to control the quality of the surgery.</p> <p>Trial Registration</p> <p>ClinicalTrials.gov Identifier: NCT00357487</p

Critical assessment of sequence-based protein-protein interaction prediction methods that do not require homologous protein sequences

<p>Abstract</p> <p>Background</p> <p>Protein-protein interactions underlie many important biological processes. Computational prediction methods can nicely complement experimental approaches for identifying protein-protein interactions. Recently, a unique category of sequence-based prediction methods has been put forward - unique in the sense that it does not require homologous protein sequences. This enables it to be universally applicable to all protein sequences unlike many of previous sequence-based prediction methods. If effective as claimed, these new sequence-based, universally applicable prediction methods would have far-reaching utilities in many areas of biology research.</p> <p>Results</p> <p>Upon close survey, I realized that many of these new methods were ill-tested. In addition, newer methods were often published without performance comparison with previous ones. Thus, it is not clear how good they are and whether there are significant performance differences among them. In this study, I have implemented and thoroughly tested 4 different methods on large-scale, non-redundant data sets. It reveals several important points. First, significant performance differences are noted among different methods. Second, data sets typically used for training prediction methods appear significantly biased, limiting the general applicability of prediction methods trained with them. Third, there is still ample room for further developments. In addition, my analysis illustrates the importance of complementary performance measures coupled with right-sized data sets for meaningful benchmark tests.</p> <p>Conclusions</p> <p>The current study reveals the potentials and limits of the new category of sequence-based protein-protein interaction prediction methods, which in turn provides a firm ground for future endeavours in this important area of contemporary bioinformatics.</p

Transformation formulas for double hypergeometric series related to 9-j coefficients and their basic analogs

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