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

The frequency analysis of auditory perceptions takes place in the cochlea of the inner ear. The cochlea’s task is to transform the entrance vibrations of the oval window into individual frequency components of the acoustic signal entering the outer ear. This frequency analysis is provided by a coupling between the overall acoustic wave in the perilymph and the vibrations of the basilar membrane. 

With regard to the analyzed transformation of signals, the scala vestibuli, scale tympani, basilar membrane and organ of Corti are of the highest importance, the latter of which transforms deformations of the basilar membrane into tension pulses that are further conveyed to the relevant part of the brain. The cavities of the scala vestibuli and scale tympani are filled with the same liquid-perilymph. They are interconnected with a narrow opening called the helicotrema.

Understanding Dive Computers

Modern digital dive computers date to the early 80s, though analog devices simulating tissue gas uptake and elimination through porous membranes date back to the 70s. Analog devices were limited to nonstop diving and had a short shelf life. 

Digital dive computers proved highly successful and very useful right from the start, progressing from just table emulators to full up algorithmic staging devices across mixed gas, open circuit (OC), re breather (RB), nonstop, decompression, deep, and shallow diving. Dive computers are moderately expensive items these days, and high end units range beyond $1500. Basically, a decompression computer is a microprocessor consisting of a power source, pressure transducer, analog to digital signal converter, internal clock, chip with RAM (random access memory) and ROM (read only memory), and pixel display screen.

A Multi-Layer Non-Newtonian Model of Cardiovascular Inflammation

We found that such locations are correlated to the vulnerable plaque phenotype, which is prone to rupture. Our results demonstrate that at locations of high particle concentration, blood particles change the shear stress distribution and magnitude. Therefore, the non-Newtonian blood flow assumption provides new insights in the characterization of plaque built up. 

These results are combined to in-vitro experiments that suggest the influence of blood particles in the activity of cytokines. An unbalance in pro and anti-inflammatory cytokines has been associated to an increase in inflammation and, consequently, in the volume of plaques forming. We anticipate our work to be a starting point for a more sophisticated multi-scale model, which combines experimental findings and computational modelling to characterize arterial segments affected by atherosclerosis. Such model includes a coupling between the distending arterial wall and the non-Newtonian blood flow.

Human-Organoid Models: Accomplishments to Salvage Test-Animals

Late stage attritions in drug discovery are costly and consuming. Improbable response of test molecules acquired in non-human systems is attributed to be the major cause of clinical failures. While conventional in vitro methods of drug discovery do not truly represent the human system, the animal models used for in vivo validation are also genetically and phenotypically distant from humans. However, recent developments in organoid culture are motivating and elevate hopes for replacing test animals with artificial human tissue models. 

Possibility of creating functional tissue ex vivo has a potential to revolutionize the way human therapeutics is perceived. Not only will it bridge the gap between drug development and its clinical efficacy but also help strategizing regenerative medicine. Successful human-tissue surrogates would liberate test animals or at least minimize their use for research purposes. Potential drug candidates tested on human-tissue equivalents are expected to generate clinically much more relevant data. Here we deliberate upon the options and possibilities of accomplishing human organoid models for in vitro testing and their significance in therapeutics.

Human-Organoid Models: Accomplishments to Salvage Test-Animals

Late stage attritions in drug discovery are costly and consuming. Improbable response of test molecules acquired in non-human systems is attributed to be the major cause of clinical failures. While conventional in vitro methods of drug discovery do not truly represent the human system, the animal models used for in vivo validation are also genetically and phenotypically distant from humans. However, recent developments in organoid culture are motivating and elevate hopes for replacing test animals with artificial human tissue models. 

Possibility of creating functional tissue ex vivo has a potential to revolutionize the way human therapeutics is perceived. Not only will it bridge the gap between drug development and its clinical efficacy but also help strategizing regenerative medicine. Successful human-tissue surrogates would liberate test animals or at least minimize their use for research purposes. Potential drug candidates tested on human-tissue equivalents are expected to generate clinically much more relevant data. Here we deliberate upon the options and possibilities of accomplishing human organoid models for in vitro testing and their significance in therapeutics.

Bioinformatics enables biotechnology and cancer research

Genomics and molecular biology has been a source of inspiration for biology and biotechnology research worldwide. Scientists and the researchers are unable to analyze this huge data manually so that innovative theraputical solutions have emerged for the data analysis. Bioinformatics come to the rescue of the scientists and researchers in digging the information efficiently. Bioinformatics is particularly capable of developing the next generation cancer research from the data and can come with innovative solutions to cure cancer.

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Human-Organoid Models: Accomplishments to Salvage Test-Animals

Late stage attritions in drug discovery are costly and consuming. Improbable response of test molecules acquired in non-human systems is attributed to be the major cause of clinical failures. While conventional in vitro methods of drug discovery do not truly represent the human system, the animal models used for in vivo validation are also genetically and phenotypically distant from humans. However, recent developments in organoid culture are motivating and elevate hopes for replacing test animals with artificial human tissue models. 

Possibility of creating functional tissue ex vivo has a potential to revolutionize the way human therapeutics is perceived. Not only will it bridge the gap between drug development and its clinical efficacy but also help strategizing regenerative medicine. Successful human-tissue surrogates would liberate test animals or at least minimize their use for research purposes. 

Evaluating the Impact of Different Factors on Voxel-Based Classification Methods of ADNI Structural MRI Brain Images

In this work we introduce the use of penalized logistic regression (PLR) to the problem of classification of MRI images and automatic detection of Alzheimer’s disease. Classification of sMRI is approached as a large scale regularization problem which uses voxels as input features. We evaluate how differences in sMRI pre-processing steps such as smoothing, normalization, and template selection affect the performance of high dimensional classification methods. 

In addition, we compared the relative performance of PLR to a different approach based on support vector machines. To study these questions we used data from the Alzheimer Disease Neuro imaging Initiative (ADNI). The ADNI project follows a protocol consisting of acquisition of two images in each session, image correction steps and further evaluation by experts to obtain the optimized images. We evaluated here the impact of this optimization process on the performance of high-dimensional machine learning techniques.

Likelihood Ratio Test of Hardy-Weinberg Equilibrium Using Uncertain Genotypes for Sibship Data

Testing for Hardy-Weinberg equilibrium of genotype frequencies is a crucial first step in the study of population genetics. In this paper, we develop an Expectation-Maximization algorithm to estimate the genotype frequencies for sibship data with genotype uncertainty. 

We also develop a likelihood ratio test of Hardy-Weinberg equilibrium for sibships with no parental genotypes available and with possible genotyping errors. Simulations show that our likelihood ratio test maintains valid control of the type I error rate and good statistical power. Finally, the likelihood ratio test is extended across strata when a sample is stratified by multiple ethnic populations with different genotype frequencies.

DNA/RNA Fragmentation and Cytolysis in Human Cancer Cells Treated with Diphthamide Nano Particles Derivatives

Molecular structure activity studies for some Diphthamide Nano particles derivatives indicate that the conformational characteristics along with the nature and position of the substituents on the Diphthamide Nano particles derivatives ring play an important role in their biological and biochemical activities. Therefore, we have calculated the optimized molecular geometries of some Diphthamide Nano particles derivatives. 

Calculations are carried out on the structures of these medical, medicinal and pharmaceutical Nano drugs using Hartree–Fock calculations and also Density Functional Theory (DFT) by performing HF, PM3, MM2, MM3, AM1, MP2, MP3, MP4, CCSD, CCSD(T), LDA, BVWN, BLYP and B3LYP levels of theory using the standard 31G, 6–31G*, 6–31+G*, 6–31G(3df, 3pd), 6–311G, 6–311G* and 6–311+G* basis sets of the Gaussian 09. The comparative heats of formation and Natural Bond Orbital (NBO) charges are calculated for these Diphthamide Nano particles derivatives. We have finally obtained some conformational rules in terms of the natures and positions of the substituents on the Diphthamide Nano particles derivatives ring.

Data Inventory for Cancer Patients Receiving Radiotherapy for Outcome Analysis and Modeling

Data collection for cancer patients is recognized as an important task in the USA, where the National Program of Cancer Registries (NPCR) administered by the Centers for Disease Control and Prevention collects data on the occurrence, type, extent, and location of the cancer, and the type of initial treatment. The International Consortium for Health Outcomes Measurements (ICHOM) aims at providing a global resource of in-use outcome measures and risk adjustment factors by medical condition and creating a global standard for measuring results. 

These initiatives will enable public health professionals to understand and address the cancer burden more effectively. We have recently proposed to use the pre-treatment, planning, and treatment outcomes data for cancer patients undergoing radiation therapy to provide guidelines for optimal choice of both radiation modality and planning for new patients. It is important to determine the most influential patient features (or their combinations) that has the strongest correlation with the outcomes. We propose an Overlap Volume Histogram as a valuable representation of size and shape for tumor and organs at risk important for planning.

A new sensitive and rapid assaying technique

Inspite of their low sensitivity compared to chemiluminescenceand fluorescence methods, Immunochromato graphic(IC) and Lateral flow (LF) test strips are widely used for the rapid detection of drugs, clinical factors, food safety etc. Recently American scientists developed adaptable rapid quantitation and multiplex detection sensitive assay for assaying clinical drugs,biomarkers, etc.

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A Similarity Retrieval Tool for Functional Magnetic Resonance Imaging Statistical Maps

We propose a method for retrieving similar functional magnetic resonance imaging (fMRI) statistical images given a query fMRI statistical image. Our method thresholds the voxels within those images and extracts spatially distinct regions from the voxels that remain. Each region is defined by a feature vector that contains the region centroid, the region area, the average activation value for all the voxels within that region, the variance of those activation values, the average distance of each voxel within that region to the region’s centroid, and the variance of the voxel’s distance to the region’s centroid. 

The similarity between two images is obtained by the summed minimum distance (SMD) of their constituent feature vectors. Results and conclusion. Our method is sensitive to similarities in brain activation patterns from members of the same data set. Using a subset of the features such as the centroid location and the average activation value (individually or in combination), maximized the sensitivity of our method. We also identified the similarity structure of the entire data set using those two features and the SMD.

Analytical formulas in designing protocols using linear theory of Bunsen Roscoe

Recent studies have shown the requirement of a nonlinear revision for linear theory of Bunsen Roscoe law to establish optimal concentration and UV dose for maximum stiffness increasing. Even the analytic formulas can provide useful guidance in designing protocols and in optimizing corneal cross linking.

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

Over the years there has been an increase in machine learning (ML) techniques, such as Random Forrest (RF), Boosting (ADA), Logistic (GLM), Decision Trees (RPART), Support Vector Machines(SVM), and Artificial Neural Networks (ANN) applied to many medical fields. A significant reason this has become the case is the capacity for human beings to act as diagnostic tools over time. Stress, fatigue, inefficiencies, and lack of knowledge all become barriers to high- quality outcomes.

There have been studies regarding applications of data mining in different fields, namely: biochemistry, genetics, oncology, neurology and However, literature suggests that there are few comparisons of machine learning algorithms and techniques in medical and biological areas. Of these ML algorithms, the most common approach to develop nonparametric and nonlinear classifications is based on ANNs.

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. 

A Review on New Horizons of Bioinformatics in Next Generation Sequencing, Viral and Cancer Genomics

Genomics and molecular biology has always been a constant source of inspiration and motivational research for worldwide researchers in field of biology and biotechnology. These two fields have always generated a huge amount of data and in order to compile and analyse those, bioinformatics came into action during last decade. Implementation of bioinformatics has a clear intention of doing all these analysis of data in efficient and fast manner in order to cut down the expensive laboratory equipment, chemicals and most precious time.

Mostly genomic data is composed of sequencing results at a higher scale and that is why manual curating and handling of these data is quite difficult. Supreme aim of this review is to make awareness about bioinformatics options in cancer genomics and viral genomics apart from next generation sequencing. Next generation sequencing or high throughput sequencing has helped a lot to replace old conventional method of sequencing and with the help of recent advances in technologies. 

Check this man made wonder device for treating Intractable Brain Disorders

Many neurological and psychiatric disorders with predominantly cerebral cortical pathology, including most severe strokes, traumatic brain injuries, malignant brain tumors, intractable focal epilepsies and dementias such as Alzheimer’s disease are currently difficult, if not impossible, to treat. This causes suffering in almost 100 million people worldwide. 

We propose that bioengineered cranial bones with multiple intelligent functions, including site specific Tran’s meningeal drug delivery and neurotoxin drainage with EEG feedback, can provide effective treatment of these brain disorders by drug combinations that act on both synapses and genes with concomitant selective drainage of harmful extracellular molecules. 

Drug delivery potential of hydrogels having α-amino acid residues

Stimuli-Responsive Hydrogels such as Vinyl hydrogels bearing α-amino acid residues are  Potential vehicles for the drug delivery systems especially cisplatin, pilocarpine, doxorubicin, citalopram, trazodone, paroxetine etc. These gels not only transport the drug to the target site but also preserve the structure and function of drug.

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Selenoergothionein as a Potential Inhibitor against Amyloid β-Protein (Aβ): Docking and Molecular Dynamics Studies

Alzheimer‘s disease (AD) is a progressive neurodegenerative disorder, encircling the deterioration of cognitive functions and behavioral changes, characterized by the aggregation of amyloid β-protein (Aβ) into fibrillar amyloid plaques in elected areas of the brain with the lipid-carrier protein apolipoprotein E (apoE), the microtubule associated protein tau, and the presynaptic protein α-synuclein. 

High levels of fibrillary Aβ, the main constituent of senile plaques, are deposited in the AD brain that outcome in the thrashing of synapses, neurons and destruction of neuronal role. Aβ is derived from the amyloid precursor protein through sequential protein cleavage by as partylprotease, β-secretase and presenilin-dependent β-secretase triggering a spill of events such as oxidative damage, neurotoxicity, and inflammation that contributes to the progression of AD. Therefore the Aβ protein may be a target for anti-Alzheimer drugs. Aβ proteinwas retrieved from the Protein data bankand energy minimized and subjectedto molecular dynamic simulations using NAMD 2.9 software with CHARMM27 force field in water. 

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A Review on New Horizons of Bioinformatics in Next Generation Sequencing, Viral and Cancer Genomics

Genomics and molecular biology has always been a constant source of inspiration and motivational research for worldwide researchers in field of biology and biotechnology. These two fields have always generated a huge amount of data and in order to compile and analyze those, bioinformatics came into action during last decade. 

Implementation of bioinformatics has a clear intention of doing all these analysis of data in efficient and fast manner in order to cut down the expensive laboratory equipment, chemicals and most precious time. Mostly genomic data is composed of sequencing results at a higher scale and that is why manual curating and handling of these data is quite difficult. Supreme aim of this review is to make awareness about bioinformatics options in cancer genomics and viral genomics apart from next generation sequencing. 

DNA/RNA Fragmentation and Cytolysis in Human Cancer Cells Treated with Diphthamide Nano Particles Derivatives

Molecular structure activity studies for some Diphthamide Nano particles derivatives indicate that the conformational characteristics along with the nature and position of the substituents on the Diphthamide Nano particles derivatives ring play an important role in their biological and biochemical activities (Figure 1). Therefore, we have calculated the optimized molecular geometries of some Diphthamide Nano particles derivatives. 

Calculations are carried out on the structures of these medical, medicinal and pharmaceutical Nano drugs using Hartree–Fock calculations and also Density Functional Theory (DFT) by performing HF, PM3, MM2, MM3, AM1, MP2, MP3, MP4, CCSD, CCSD(T), LDA, BVWN, BLYP and B3LYP levels of theory using the standard 31G, 6–31G*, 6–31+G*, 6–31G(3df, 3pd), 6–311G, 6–311G* and 6–311+G* basis sets of the Gaussian 09. The comparative heats of formation and Natural Bond Orbital(NBO) charges are calculated for these Diphthamide Nano particles derivatives. We have finally obtained some conformational rules in terms of the natures and positions of the substituents on the Diphthamide Nano particles derivatives ring.

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 beadequately 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. Here, we provided a briefly overview of current meta-analytic approaches together with the basic critical issues in performing meta-analysis of genomic data, with the aim of helping researchers to evaluate the quality of existing, published data and obtain more detailed information on what will be the best strategy to adopt to execute a good meta-analysis.

Human Organoid models may boost the drug discovery & Development

Drug discovery is an expensive affair that involves millions of dollars. Despite intensified researches, only one out of 10,000 drugs enters the market after successfully completing series of regulatory measures.

The main reasons for the low rate of success in the drug discovery include our inability produce the human tissue for research.  Test models like flat surface cell-culture, virtual computational methods and small animals are unable to replace the human culture. Recent developments and advancements in the drug research in the form of Organoid culture is offering new hopes for the drug discovery as there is scope for using artificial human tissue models in the place of animal models. There are proposals to create human Organoid models for in vitro testing, which are expected to add significance to the drug research.

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Application of software tools in the development of novel drug for Breast Cancer

The DNA methylation, in human cells regulates tumor growth and it also indicates the breast cancer susceptibility. In a research they pinpointed the genes that are involved invariations that occur in methylationof the breast cancer epigenome. The DNA methylation(CG sites)sequences from 7-normal individuals and 8-breast cancer patients were compared by using Statistical software package R and by Upperone-tailed chi-square tests. Consensus Path Database is used to map selected CG sites to study the biological relations between healthy individuals with patients affected by tumour. Based on the data collected from PubMed and Gene Card, 26 potential biomarker genes were discovered. All these data helps in the development of novel treatments for breast cancers.

Bioengineering method to identify and cure psychiatric disorders

Many neurological and psychiatric disorders are currently difficult or even impossible to treat; nearly 100 million people are suffering worldwide. Recently research proposed the bioengineered cranial bones with multiple intelligent functions that include neurotoxin drainage with EEG feedback, site specific trans meningeal drug delivery and it can also provide effective treatment for brain disorders by drug combinations that act on both synapses and genes. Finally after demonstrating the safety and anticonvulsant efficacy of this complex procedure on nonhuman primates, they confirmed that bioengineered cranial bones with multiple intelligent functions have realistic medical/therapeutic potential.

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Enhancing Visual Evoked Potentials Detection with Use of Computational Intelligence Tools

The analysis of evoked potentials (EPs) in the electroencephalogram (EEG) is usually inspected visually and demands subjective interpretation of the results. This paper aims at combiningan statistical criterion based on the magnitude square multiple coherence(MSMC) estimate with computational intelligence methods in order to estimate the EPs detection rate (DR) using only portions of the frequency spectrum. 

Thus, networks were used to predict the DR in EEG signals of 15 normal subjects during stroboscopic stimulation. The algorithms were designed to receive thespectral information of two, four or six EEG derivations as the input and DR asthe output. Our best result shows that the artificial neural networks can estimate DR with correlation coefficient of 0.97 compared with MSMC, even when a reduced amount of spectral information from the data is available.

Therapeutic role for Emodin against Alzheimer’s and Cancer

Rhubarb is a herb, used widely in conventional treatments; also this plant is the first source of Emodin. This Emodin is a potential anti-inflammatory and anti-canceragent; it successfully induces- down regulation of cancer inducing genes and apoptosis. Modification of Emodin and its derivatives successfully increase various cellular pathways like NF κβ, ROS, MAPK signalling pathway. These derivatives are also used in Alzheimer’s disease by inhibiting proteases and microtubule – associated proteins. The properties of Emodin proved to be a promising solution for many health complications in human.

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Editorial for International Journal of biomedical Data Mining

This issue of the International Journal of Biomedical Data Mining presents two contributed articles. The first article, entitled Data Inventory for CancerPatients Receiving Radiotherapy for Outcome Analysis and Modeling, authored by Jason Vickress, Rob Barnett and Slav Yartsev, describes a database created for storing and analyzing patient specific data related to pre-treatment condition, treatment planning, and treatment outcomes, for patients receiving radiotherapy based cancer treatment. 

The proposed database can perform automated analysis regarding quality assurance, dose accumulation for multiple treatments on different machines and can assist physicians in choosing the optimal radiation therapy for new patients. The second article, entitled Likelihood Ratio Test ofHardy-Weinberg Equilibrium Using Uncertain Genotypes for Sibship Data, authoredby Qiong Li, Helene Massam and Xin Gao, is concerned with the problem of testing for Hardy-Weinberg equilibrium of genotype frequencies in the area of population genetics. 

Sequence Features and Subset Selection Technique for the Prediction of Protein Trafficking Phenomenon in Eukaryotic Non Membrane Proteins

Eukaryotic cells are organized into several membrane bound compartments. In order toperform the function; newly formed proteins get sorted and are delivered to various compartments in the non-membrane and trans-membrane pathways. 

This protein sorting process in the pathway is very complex and still not clearly understood. But the most important principle of protein trafficking is that each protein has the information on its final localization site as a part of its amino acid sequence. In 1983, Nishikawa, Kubota and 0oi had conductedinvestigations into predicting subcellular locations based on amino acidcompositions. They had reported that the amino acid compositions have the discriminating ability to classify subcellular locations.

Bioinformatics tools in Viral and Cancer biology

Molecular biology and genomic tools are advanced techniques widely used in research fields. These tools can generate huge amount of data atthe same time they can compile and analyse. Bioinformatics tools such as Fast QC and htSeq tools are used for analysing quality of short reads, correlation between mutant, genes and pathway can be done by tool MuSiC etc.. Next generation sequencing tool helps to get information in low cost, time and labour. Application of such type of tools in virology and cancer biology provides advanced information and sequencing data for further research.

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Data Inventory for Cancer Patients Receiving Radiotherapy for Outcome Analysis and Modeling

Data collection for cancer patients is recognized as an important task in the USA, where the National Program of Cancer Registries (NPCR) administered by the Centers for Disease Control and Prevention collects data on the occurrence, type, extent, and location of the cancer, and the type of initial treatment. 

The International Consortium for Health Outcomes Measurements (ICHOM) aims at providing a global resource of in-use outcome measures and risk adjustment factors by medical condition and creating a global standard for measuring results. These initiatives will enable public healthprofessionals to understand and address the cancer burden more effectively. We have recently proposed to use the pre-treatment, planning, and treatment outcomes data for cancer patients undergoing radiation therapy to provide guidelines for optimal choice of both radiation modality and planning for new patients. 

It is important to determine the most influential patient features (or their combinations) that has the strongest correlation with the outcomes. We propose an Overlap Volume Histogram as a valuable representation of size andshape for tumor and organs at risk important for planning.

Understanding Dive Computers

Modern digital dive computers date to the early 80s, though analog devices simulating tissue gas uptake and elimination through porous membranes date back to the 70s. Analog devices were limited to nonstop divingand had a short shelf life. 

Digital dive computers proved highly successful and very useful right from the start, progressing from just table emulators to full up algorithmic staging devices across mixed gas, open circuit (OC), rebreather (RB), nonstop, decompression, deep, and shallow diving. Dive computers aremoderately expensive items these days, and high end units range beyond $1500.Basically, a decompression computer is a microprocessor consisting of a powersource, pressure transducer, analog to digital signal converter, internal clock, chip with RAM (random access memory) and ROM (read only memory), and pixel display screen. Pressure readings from the transducer are converted to digital format by the converter, and sent to memory with the elapsed clock time for model calculations, somewhere in 3-10 second intervals.

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 hemangioperycitoma 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 Iwould 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.

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Solid-phase Immuno Radio Metric Assay (IRMA) of 25-hydroxy Vitamin

Vitamin D is a steroid hormone involved in the active intestinal absorption of calcium and regulation of calcium homeostasis. It is essential for the formation and maintenance of strong, healthy bones. Vitamin Dhas other roles in the body, including modulation of cell growth, neuromuscularand immune function, and reduction of inflammation. Vitamin D has two isomers: vitamin D2 (ergocalciferol) and vitamin D3 (cholecalciferol). Vitamin D2 is obtained from dairy product whereas Vitamin D3 is produced in the skin after exposure to ultraviolet light. In the liver Vitamin D is hydroxylated at its carbon 25 to form 25(OH) D. This metabolite is the predominant circulating form of vitamin D and is considered to be an accurate indicator of the general Vitamin D status on an individual.

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Sequence Features and Subset Selection Technique for the Prediction of Protein Trafficking Phenomenon

Protein trafficking or protein sorting is the mechanism by which a cell transports proteins to the appropriate position in the cell or outside of it. This targeting is based on the information contained in theprotein. Many methods predict the subcellular location of proteins in eukaryotes from the sequence information. However, most of these methods use a flat structure to perform prediction.

In this work, we introduce ensemble methods to predict locations in the eukaryotic protein-sorting non membrane pathway hierarchically. We used features that were extracted exclusively fromfull length protein sequences with feature subset selection for classification. Sequence driven features, sequence mapped features and sequence autocorrelation features were tested with ensemble learners and classifier performances were compared with and without feature subset selection technique. 

Old Wine in a New Bottle: Harnessing the Therapeutic Properties of Emodin Derivatives

Studies involving mechanism of emodin, an herbal extract, has revealed its potential as anti-inflammatory, antioxidant and anti-cancer agent. Emodin has been shown to successfully induce apoptosis, down-regulate cancerinducing genes, proving it to be a therapeutically significant pharmacophore. Modification of emodin and synthesis of various derivatives have successfully increased efficacy of the molecule in regulating various cellular pathway like MAPK signaling pathway, NF-κβ signaling pathway, ROS mediated pathways and apoptotic pathways. 

With the advent of various, anti-bacterial properties of emodin may come in rescue to combat emerging drug resistant microbial and parasitic strains. Different emodin derivatives, including the recentlyreported haloemodin, which inhibits bacterial topoisomerases, can be designed to generate future drugs against resistant pathogens. Emodin derivatives can also inhibit proteases and microtubule-associated proteins, which play an important role in Alzheimer’s disease. Properly designed drug delivery systems like liposomes and nanoparticles have been reported as efficient emodin carriers and to enhance emodin activity in cancer cell inhibition. 

Cytotoxic Effects of Aflatoxin B1 Standard in Relation to Aflatoxin Extracts

Aflatoxins [AFs] are a group of mycotoxins produced as secondary metabolites notably by Aspergilliusflavus and A. parasiticus. Otherspecies such as A.nomius, A. bombycis, A. ochraceoroseus, A. pseudotamarii, A.tamarii, and A. australis are also recognized producers. 

There are four main types of aflatoxins; aflatoxin B1(AFB1), AFB2, AFG1 and AFG2, owing to their colour [blue and green, denoted by the letters] and retardation factor (RF) when viewed under UV light. The most important of these four toxins in terms ofprevalence and abundance is AFB1. Aflatoxin B1 is also the most potent of all AFs and has been classified as a Class 1 carcinogen by the International Agency for Research on Cancer, IARC. This natural toxin is commonly reported to induce various health effects in humans and animal species; which could be hepatotoxic, mutagenic, genotoxic or carcinogenic. Chronic exposure to low levels of AF may well be a risk factor involved in the etiology of hepatocellular carcinoma and immune system suppression/dysfunction.