Shikimate Kinase of Yersinia pestis: A Sequence, Structural and Functional Analysis

Yersinia pestis, the causative organism of Plague, is widely recognized as a potential bioterrorism threat. Due to the absence of homologs in human, Shikimate Kinase (SK) is considered as an excellent drug target in several bacterial and protozoan parasites. Ample literature evidences confirm the suitability of this protein as a good target. Therefore, Shikimate Kinase of Shikimate pathway in Yersinia pestis represents an attractive drug target.

In the present study, a clustering approach was undertaken to select the proper representative for Shikimate Kinase sequences belonging to Yersinia pestis for structure determination. Three-dimensional models of the enzyme for KFB61218.1 (SK1), EFA47400.1 (SK2) and WP_016255950.1 (SK3) were generated using a comparative molecular modeling approach where structures were developed using the single specific template as well as multiple closely associated templates. The structures of Shikimate Kinase developed using comparative modeling were evaluated for stereochemical quality using various structural validation tools. Results from structural assessment tools indicated the reasonably good quality of models.

Preface, or the Truth Revealed

The truth revealed was when a young man, Nick Kostovic, made public his findings about the power of the Universe, the achieved knowledge he performs in the healing systems of our days. Doctors, patients, and common people thought of him as a magician who penetrated from the clouds to announce a new truth. And this is what it was-a new truth. The community of coastal Los Angeles became stunned when terminally sick people began to feel better, when invalids began to walk, when memories returned to Parkinson’s and Alzheimer’s-diseased patients. For the past thirty years, Kostovic has conducted research on the effects of neurological disorders on human beings and spent the last fifteen years working on several projects in connection with bioenergetic physical therapy.

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The Neural Networks with an Incremental Learning Algorithm Approach for Mass Classification in Breast Cancer

Breast cancer is a leading fatality cancer for woman. According to epidemiological data, breast cancer accounts for 20-25% of female malignant tumor, with is expected to increase. These facts have driven us to select this deadly cancer as our domain. Breast cancer has four early signs; micro-calcification, mass, architectural distortion and breast asymmetries. However, only data regarding mass will be used as a pilot project to test our system later on. Masses of 2 cm in diameter are palpable with regular breast self-examination while mammogram images can capture it from 5 mm in diameter.

However, these images were to be determined by an expert radiologist who is familiar with breast cancer. Generally, there are 2 types of breast cancer which are in situ and invasive. In situ starts in the milk duct and does not spread to other organs even if it grows. Invasive breast cancer on the contrary, is very aggressive and spreads to other nearby organs and destroys them as well. It is very important to detect the cancerous cell before it spreads to other organs, thus the survival rate for patient will increase to more than 97%. However, time taken from taking mammogram images to biopsy dangerous result varies between 2weeks to a month in average.

A Multi-Layer Non-Newtonian Model of Cardiovascular Inflammation

Cellular functions related to the maintenance of homoeostasis are regulated by shear forces sensed by endothelial cells. The endothelial cells sense local changes in shear stress. The resulting signals are either transduced into chemical responses or transmitted to the surroundings to regulate the cellular activity.

In the current literature, models of blood flow applied to the characterization of atherosclerotic plaques consider blood as a Newtonian fluid because of the characteristic length of the domain. At predilection sites for plaque deposition, the diameter of the blood particles is much smaller than the normal arterial diameter. However, under disease condition, the proportions can dramatically change due to a reduction greater than 80% in the arterial cross-section, in cases of severe stenosis. Here we show that in diseased arteries, the local particle concentration can peak at locations associated to high inflammation.

The Neural Networks with an Incremental Learning Algorithm Approach for Mass Classification in Breast Cancer

As breast cancer can be very aggressive, only early detection can prevent mortality. The proposed system is to eliminate the unnecessary waiting time as well as reducing human and technical errors in diagnosing breast cancer. The correct diagnosis of breast cancer is one of the major problems in the medical field. From the literature it has been found that different pattern recognition techniques can help them to improve in this domain.

This paper uses the neural networks with an incremental learning algorithm as a tool to classify a mass in the breast (benign and malignant) using selection of the most relevant risk factors and decision making of the breast cancer diagnosis To test the proposed algorithm we used the Wisconsin Breast Cancer Database (WBCD). ANN with an incremental learning algorithm performance is tested using classification accuracy, sensitivity and specificity analysis, and confusion matrix. The obtained classification accuracy of 99.95%, a very promising result compared with previous algorithms already applied and recent classification techniques applied to the same database.

The Standing Acoustic Wave Principle within the Frequency Analysis of Acoustic Signals in the Cochlea

The organ of hearing is responsible for the correct frequency analysis of auditory perceptions coming from the outer environment. The article deals with the principles of the analysis of auditory perceptions in the cochlea only, i.e., from the overall signal leaving the oval window to its decomposition realized by the basilar membrane. The paper presents two different methods with the function of the cochlea considered as a frequency analyzer of perceived acoustic signals.

First, there is an analysis of the principle that cochlear function involves acoustic waves travelling along the basilar membrane; this concept is one that prevails in the contemporary specialist literature. Then, a new principle with the working name “the principle of standing acoustic waves in the common cavity of the scala vestibuli and scala tympani” is presented and defined in depth. According to this principle, individual structural modes of the basilar membrane are excited by continuous standing waves of acoustic pressure in the scale tympani.

Meta-Analysis of Genomic Data: Between Strengths, Weaknesses and New Perspective

The rapid advances in high-throughput technologies, such as microarrays have revolutionizing the knowledge and understanding of biological systems and genetic signatures of human diseases. This has led to the generation and accumulation of a large amount of genomic data that need to be adequately integrated to obtain more reliable and valid results than those from individual experiments. Meta-analysis of microarray data is one of the most common statistical techniques used for combining multiple data sets. Despite its remarkable successes in discovering molecular subtypes, underlying pathways and biomarkers for the pathological process of interest, this method possesses several limitations.

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Dose Optimization Studies by Selecting Kilovoltage in Oncologic Chest CT

In this work we have studied the adequacy of dose levels of irradiation in oncologic chest CT obtained in our daily practice. The secondary objective was to evaluate the effect on radiation dose of individual adjustment of kilovoltage in thoracic multidetector row computed tomography (MDCT) images acquired with both single and dual-source technology. The impact of lowering the kilovoltage in the diagnostic quality of these studies was also evaluated. 161 patients were included in the study. CT examinations were performed using two different equipments: a conventional CT scanner and a dual-source computed tomography. The average values of dose length product (DLP) obtained in our daily practice meet the recommendations of the existing referral guidelines. Lower values can be achieved through individual adjustment of kilovoltage and with dual-source CT technology, maintaining the diagnostic quality of these studies.

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A Bayesian Analysis of Copy Number Variations in Array Comparative Genomic Hybridization Data

Array Comparative Genomic Hybridization (CGH) has been widely used for detecting genomic copy number variations (CNVs). The central goal of array CGH data analysis is to accurately detect homogeneous regions of log intensity ratios which represent relative changes in DNA copy number. Various methods have been proposed in recent years. Most methods, however, do not consider correlations of neighboring probe measurements, and are usually designed for analysis at single sample level rather than detecting common or recurrent CNVs among multiple samples. We propose a Bayesian segment-based approach for efficient analysis of array CGH data. The proposed method is based on simple assumptions but is general enough to accommodate various spatial correlations among probe measurements. It also allows for multiple samples with recurrent CNVs, therefore is able to borrow strength across samples.

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A Revolutionary Method of Treatment

A tumor without a supporting network of blood vessel formation is like a car without wheels-it’s not going anywhere! But the multiple hemangiopericytoma type of brain tumors I’ve been shackled with over the last fourteen years were multiplying rapidly in the cancer lane and were driving me one hundred and ten miles an hour to my grave!

That was until suddenly, in early March, 2003, when Providence unexpectedly whisked me away from my home in Burbank, CA and guided me directly to the one person, who was to change my life forever so that I would be free of any new or recurring tumors of any variety, have a quality life and even have it extended several years! He is Mr. Nick Kostovic, a pioneer and visionary in energetic medicine, and his health clinic, the Bio Technological Health Center, Inc., in San Pedro, California is where he not only killed my malignant brain tumors, but where this brilliant, caring therapist is helping heal my malignant brain tumors, but where this brilliant, caring therapist is helping heal many other patients by eradicating other treacherous life threatening diseases such as diabetes, cancer, Lou Gehrig's Disease (ALS), Parkinson’s, MS, strokes and more.

Visually Guided Horizontal Saccades under the Double-Step Paradigm

Visually goal-oriented saccades were recorded under the double-step paradigm. Data were analyzed to produce parameter estimates using the system identification technique for a 3rd-order linear horizontal saccadic eye movement model. Statistical analysis of a large human saccade data set provided reliable conclusions of the response properties. Saccade amplitude, latency and inter-saccade interval were discussed with time delay, indicating the parallel programming mechanism, which two saccades to different targets could be programmed simultaneously. The results of neural input estimations suggested that the double-step visual targets may affect the synchronous firing of the saccade responsible neurons in the superior colliculus.

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A Discriminative Feature Space for Detecting and Recognizing Pathologies of the Vertebral Column

Each year it has become more and more difficult for healthcare providers to determine if a patient has a pathology related to the vertebral column. There is great potential to become more efficient and effective in terms of quality of care provided to patients through the use of automated systems.

However, in many cases automated systems can allow for mis classification and force providers to have to review more causes than necessary. In this study, we analyzed methods to increase the True Positives and lower the False Positives while comparing them against state of- the-art techniques in the biomedical community. We found that by applying the studied techniques of a data-driven model, the benefits to healthcare providers are significant and align with the methodologies and techniques utilized in the current research community.

Linear Quadratic Tracking Control of Smooth Pursuit Eye Movements

Conventional feedback control models of the oculo motor system fail to account for the destabilizing effects of neural transmission delays. To address this shortcoming, a linear quadratic tracking algorithm used to control smoothly pursuing eye movements of various target trajectories is presented.

Based on the type of input to the system, it is shown that stability, in the presence of large motor feedback delays, can be maintained by modulating weighting factors intrinsic to the model. Conditions, such as the initial orientation of the eye relative to the location of where a target first becomes salient and the possible oscillatory nature that the reference trajectory may present, play important roles in determining the optimal cost to go motor control strategy at the onset of a tracking movement.

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ePhenotyping for Abdominal Aortic Aneurysm in the Electronic Medical Records and Genomics (eMERGE) Network: Algorithm Development and Konstanz Information Miner Workflow

Structured Query Language, was used to script the algorithm utilizing “Current Procedural Terminology” and “International Classification of Diseases” codes, with demographic and encounter data to classify individuals as case, control, or excluded. The algorithm was validated using blinded manual chart review at three eMERGE Network sites and one non-eMERGE Network site.

Validation comprised evaluation of an equal number of predicted cases and controls selected at random from the algorithm predictions. After validation at the three eMERGE Network sites, the remaining eMERGE Network sites performed verification only. Finally, the algorithm was implemented as a workflow in the Konstanz Information Miner, which represented the logic graphically while retaining intermediate data for inspection at each node. The algorithm was configured to be independent of specific access to data and was exportable (without data) to other sites.

Stimuli-Responsive Hydrogels Bearing αamino acid Residues: a Potential Platform for Future Therapies

Vinyl hydrogels bearing α-amino acid residues have been explored as platforms for the treatment of cancer, glaucoma and mood disorder therapies. Ionic/ionizable groups of the L-valine, L-phenylalanine and L-histidine residues are able to modify the swelling properties of the hydrogel on the basis of their thermodynamic characteristics.

Greater basicity constants of functional groups improve a greater loading of the drug and a longer sustained-release pattern. The pH and the temperature affect the swelling of the hydrogel and increase ‘on demand’ the drug availability. A further stimulus based on alternating magnetic fields can be applied on hydrogels containing embedded magnetic nanoparticles used for site-specific controlled drug delivery. The diffusion process for the in vitro release of the drug (cisplatin, doxorubicin, pilocarpine, trazodone, citalopram and paroxetine) from the drug loaded hydrogels is mainly controlled by the drug-polymer interaction, that in the meanwhile preserves its bioactivity. The different interaction strength between the drug and the polymer may be a strategy to develop suitable capsules for long-term therapies.

In silico Study of Bacillus brevis Xylanase - Structure Prediction and Comparative Analysis with Other Bacterial and Fungal Xylanase

The most important building block of hemicelluloses is xylan. It is broken down into xylose oligomer residues by Xylanase - an enzyme, produced by most organisms, to utilize xylose as primary source of carbon. The Xylanase produced are classified into families, viz 5, 8, 10, 11 and 43 - of Glycoside Hydrolases (GH).

Xylanase from family GH 11 are monospecific, they consist solely of Xylanase activity, exclusively active on D-xylose containing substrates.They are inactive on aryl cellobiosidase. The fungal Xylanase are produced in higher concentrations, as compared to bacterial Xylanase, but have limited use in pulp bleaching, as they affect the viscosity and strength of the product. In the present study, we have worked upon the Xylanase of Bacillus brevis, which is fulfilling all the required quality needed to be a commercial Xylanase, and thus is used by many industries. The enzyme, when studied after modelling, provided similar structural configuration with high stability. When compared with other bacterial and fungal Xylanase structures, it provided better potential to ‘activity enhancement’ and ‘in silico handling’.