Minor physical anomalies including palatal rugae pattern and palatal dimensions in children with sickle cell disease: A cross-sectional analytical study.

Background: Sickle cell disease (SCD) is the most common hereditary hemoglobinopathy, which delays growth leading to an altered skeleton and craniofacial pattern. Palatal rugae patterning has been considered the regulator of the development of the palate. The purpose of the research work was to study the morphology of the palate, rugae pattern, and its dimensions in SCD children and compare them with healthy normal children, and to evaluate its role as minor physical anomalies (MPAs). Methods: A cross-sectional case-control study was designed as per STROBE guidelines. The sample comprised 50 children diagnosed with sickle cell disease (Group SCD) and 50 normal healthy children as control (Group C) belonging to the same age group (10-18 years). Dental impressions were made, followed by the pouring of dental casts. The length of the palatal rugae was measured and categorized into primary (>5 mm), secondary (3 mm-5 mm), and fragmentary rugae (<3 mm). The shape of each primary palatal rugae was identified and categorized as curved, wavy, straight, circular and non-specific. Linear and angular measurements of the palatal rugae patterns and palatal dimensions (width, height, area) were measured and recorded. Results: The total number of palatal rugae and fragmentary rugae was lesser in Group SCD than in Group C (p < 0.05). The depth of the palate was significantly increased, whereas the area of the palate significantly decreased in Group SCD. Conclusions: The children with SCD showed distinctive palatal rugae patterns and dimensions when compared with normal healthy children that can be attributed as potential MPAs for sickle cell disease. Children with SCD had an under-developed palatal rugae pattern with a deep, narrow and small palate when compared to healthy children.The dimensions of the palatal rugae pattern in SCD showed reduced distance between the incisive papilla and the first and last rugae, indicating a further decrease in the anteroposterior dimensions of the palate. These findings may aid in the early diagnosis and prevention of malocclusion in children with SCD by appropriate interceptive orthodontic treatment.

Identification of therapeutic targets for inflammation in sickle cell disease (SCD) among Indian patients using gene expression data analysis.

Sickle cell disease (SCD) is life-threatening hemoglobinopathy prevalent in India, Sub-Saharan Africa and Middle East. Inflammation plays a pivotal role in disease process and involves intricate interaction among leukocytes, platelets, sickle erythrocytes and vascular endothelium. Available disease modifying therapies are hydroxyl-urea and blood transfusion. Therefore, it is of interest to develop improved pharmacological agents for SCD. We report up-regulated genes in steady state and vaso-occlusive crisis using analysis of gene expression data obtained by microarray experiment for SCD as potential targets. The association of these targets with inflammation in pathway analysis is also documented.

Compound Heterozygosity of ß-Thalassemia and the Sickle Cell Hemoglobin in Various Populations of Chhattisgarh State, India.

Hemoglobinopathies evolved as a protective mechanism against malaria, which exhibit selective advantage in the heterozygous state. However, in a homozygous recessive condition, it poses a serious socioeconomic burden. Sickle cell anemia is an autosomal recessive hemoglobinopathy associated with erythrocytes sickling, vaso-occlusive crisis (VOC), as well as multi-organ failure and death. The coinheritance of other hemoglobinopathies is known to substantially modulate the clinical manifestation of sickle cell anemia. In the present study, we aimed to analyze the coinheritance of ß-thalassemia (ß-thal) in Hb S (HBB: c.20A>T) patients. The study includes 918 sickle cell anemia patients from 10 ethnic populations of Chhattisgarh State, India. Complete blood counts (CBCs) and hemoglobin (Hb) high performance liquid chromatography (HPLC) fractionation data were collected from patient record books. We observed Hb S-ß-thal in all the analyzed populations. Interestingly, high frequencies of Hb S-ß-thal have been observed in Satnami (53.8%), Rawat (47.1%), Gond (35.1%) and Panika (30.6%) populations. Inter-population comparison of hematological parameters [Hb F (p < 0.001), Hb A2 (p < 0.001), Hb (p = 0.03) and red blood cell distribution width (RDW) (p < 0.001)] revealed significant differences. We also observed that mean Hb F levels were significantly higher in Hb S compared to Hb S-ß-thal patients in the respective populations. Our study highlights the higher prevalence of ß-thal as well as the compound heterozygosity for Hb S and ß-thal in various populations of Chhattisgarh State, India.

Implementation of Indigenous Electronic Medical Record System to Facilitate Care of Sickle Cell Disease Patients in Chhattisgarh.

INTRODUCTION: Sickle cell disease (SCD) is prevalent in central India including Chhattisgarh. Screening for SCD is being carried out by Government of Chhattisgarh. Electronic Medical Record (EMR) system was developed and implemented in two phases. AIM: Aim was to use informatics techniques and indigenously develop EMR system to improve the care of SCD patients in Chhattisgarh. EMR systems had to be developed to store and manage: i) huge data generated through state wide screening for SCD; ii) clinical data for SCD patients attending the outpatient department (OPD) of institute. MATERIALS AND METHODS: 'State Wide Screening Data Interface' (SWSDI) was designed and implemented for storing and managing data generated through screening program. Further, 'Sickle Cell Patients Temporal Data Management System' (SCPTDMS) was developed and implemented for storing, managing and analysing sickle cell disease patients' data at OPD. Both systems were developed using VB.Net and MS SQL Server 2012. RESULTS: Till April 2015, SWSDI has data of 1294558 persons, out of which 121819 and 4087 persons are carriers and patients of sickle cell disease respectively. Similarly till June 2015, SCPTDMS has data of 3760 persons, of which 923 are sickle cell disease patients (SS) and 1355 are sickle cell carriers (AS). CONCLUSION: Both systems are proving to be useful in efficient storage, management and analysis of data for clinical and research purposes. The systems are an example of beneficial usage of medical informatics solutions for managing large data at community level.

An ANN-GA model based promoter prediction in Arabidopsis thaliana using tilling microarray data.

Identification of promoter region is an important part of gene annotation. Identification of promoters in eukaryotes is important as promoters modulate various metabolic functions and cellular stress responses. In this work, a novel approach utilizing intensity values of tilling microarray data for a model eukaryotic plant Arabidopsis thaliana, was used to specify promoter region from non-promoter region. A feed-forward back propagation neural network model supported by genetic algorithm was employed to predict the class of data with a window size of 41. A dataset comprising of 2992 data vectors representing both promoter and non-promoter regions, chosen randomly from probe intensity vectors for whole genome of Arabidopsis thaliana generated through tilling microarray technique was used. The classifier model shows prediction accuracy of 69.73% and 65.36% on training and validation sets, respectively. Further, a concept of distance based class membership was used to validate reliability of classifier, which showed promising results. The study shows the usability of micro-array probe intensities to predict the promoter regions in eukaryotic genomes.

Neurocognitive derivation of protein surface property from protein aggregate parameters.

Current work targeted to predicate parametric relationship between aggregate and individual property of a protein. In this approach, we considered individual property of a protein as its Surface Roughness Index (SRI) which was shown to have potential to classify SCOP protein families. The bulk property was however considered as Intensity Level based Multi-fractal Dimension (ILMFD) of ordinary microscopic images of heat denatured protein aggregates which was known to have potential to serve as protein marker. The protocol used multiple ILMFD inputs obtained for a protein to produce a set of mapped outputs as possible SRI candidates. The outputs were further clustered and largest cluster centre after normalization was found to be a close approximation of expected SRI that was calculated from known PDB structure. The outcome showed that faster derivation of individual protein's surface property might be possible using its bulk form, heat denatured aggregates.

Exploring geometric properties of gold nanoparticles using TEM images to explain their chaperone like activity for citrate synthase.

Study on geometric properties of nanoparticles and their relation with biomolecular activities, especially protein is quite a new field to explore. This work was carried out towards this direction where images of gold nanoparticles obtained from transmission electron microscopy were processed to extract their size and area profile at different experimental conditions including and excluding a protein, citrate synthase. Since the images were ill-posed, texture of a context-window for each pixel was used as input to a back-propagation network architecture to obtain decision on its membership as nanoparticle. The segmented images were further analysed by k-means clustering to derive geometric properties of individual nanoparticles even from their assembled form. The extracted geometric information was found to be crucial to give a model featuring porous cage like configuration of nanoparticle assembly using which the chaperone like activity of gold nanoparticles can be explained.

A comparative study on the molecular descriptors for predicting drug-likeness of small molecules.

Screening of " drug-like" molecule from the molecular database produced through high throughput techniques and their large repositories requires robust classification. In our work, a set of heuristically chosen nine molecular descriptors including four from Lipinski's rule, were used as classification parameter for screening "drug-like" molecules. The robustness of classification was compared with four fundamental descriptors of Lipinski. Back propagation neural network based classifier was applied on a database of 60000 molecules for classification of, " drug-like" and "non drug-like" molecules. Classification result using nine descriptors showed high classification accuracy of 96.1% in comparison to that using four Lipinski's descriptors which yielded an accuracy of 82.48%. Also a significant decrease of false positives resulted while using nine descriptors causing a sharp 18% increase of specificity of classification. From this study it appeared that Lipinski's descriptors which mainly deal with pharmacokinetic properties of molecules form the basis for identification of "drug-like" molecules that can be substantially improved by adding more descriptors representing pharmaco-dynamics properties of molecules.

Surface characterization of proteins using multi-fractal property of heat-denatured aggregates.

Multi-fractal property of heat-denatured protein aggregates (HDPA) is characteristic of its individual form. The visual similarity between digitally generated microscopic images of HDPA with that of surface-image of its individual X-ray structures in protein databank (PDB) displayed using Visual Molecular Dynamics (VMD) viewer is the basis of the study. We deigned experiments to view the fractal nature of proteins at different aggregate scales. Intensity based multi-fractal dimensions (ILMFD) extracted from various planes of digital microscopic images of protein aggregates were used to characterize HDPA into different classes. Moreover, the ILMFD parameters extracted from aggregates show similar classification pattern to digital images of protein surface displayed by VMD viewer using PDB entry. We discuss the use of irregular patterns of heat-denatured aggregate proteins to understand various surface properties in native proteins.