Thursday, 27 October 2016

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.

Pathologies of the Vertebral Column
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.

Tuesday, 25 October 2016

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

Artificial neural networks
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. 

Monday, 24 October 2016

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.

Bioinformatics in Next Generation
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. 

Friday, 21 October 2016

Check this man made wonder device for treating Intractable Brain Disorders

Bioengineered Cranial Bones

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. 

Thursday, 20 October 2016

Drug delivery potential of hydrogels having α-amino acid residues

Stimuli-Responsive Hydrogels

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.

Monday, 17 October 2016

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. 

Amyloid β-Protein
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.