In-situ transesterification of single-cell oil for biodiesel production: a review.

In recent years, biodiesel synthesis and production demands have increased because of its high degradability, cleaner emissions, non-toxicity, and an alternative to petroleum diesel. In this context, Single Cell Oil (SCO) has been identified as an alternative feedstock, having the advantage of accumulating high intracellular lipid. SCO/microbial lipids are potential alternatives for sustainable biodiesel production. The traditional technique for biodiesel production from the oils obtained from microbes generally requires two steps: lipid extraction and transesterification. In-situ transesterification is an innovative and renewable process for biodiesel production. It rules out the need to isolate and refine the feedstock lipid, as it directly uses biomass in a single step, i.e., the pretreated biomass will be subjected to in-situ transesterification in the presence of catalysts. Hence, the production cost can be reduced by eliminating the lipid extraction procedure. The current review focuses on the basic features and advantages of in-situ transesterification of SCO for biodiesel production with the aid of short-chain alcohols along with different acid, base, and enzyme catalysts. In addition, a comparative study was carried out to highlight the merits of in-situ transesterification over conventional transesterification.

Scalable feature subset selection for big data using parallel hybrid evolutionary algorithm based wrapper under apache spark environment.

Extant sequential wrapper-based feature subset selection (FSS) algorithms are not scalable and yield poor performance when applied to big datasets. Hence, to circumvent these challenges, we propose parallel and distributed hybrid evolutionary algorithms (EAs) based wrappers under Apache Spark. We propose two hybrid EAs based on the Binary Differential Evolution (BDE), and Binary Threshold Accepting (BTA), namely, (i) Parallel Binary Differential Evolution and Threshold Accepting (PB-DETA), where BDE and BTA work in tandem in every iteration, and (ii) its ablation variant, Parallel Binary Threshold Accepting and Differential Evolution (PB-TADE). Here, BTA is invoked to enhance the search capability and avoid premature convergence of BDE. For comparison purposes, we also parallelized two state-of-the-art algorithms: adaptive DE (ADE) and permutation based DE (DE-FSPM), and named them PB-ADE and P-DE-FSPM respectively. Throughout, logistic regression (LR) is employed to compute the fitness function, namely, area under the receiver operator characteristic curve (AUC). The effectiveness of the proposed algorithms is tested over the five big datasets of varying dimensions. It is noteworthy that the PB-TADE turned out to be statistically significant than the rest. All the algorithms have shown the repeatability property. The proposed parallel model attained a speedup of 2.2-2.9. We also reported feature subset with high AUC and least cardinality.

An Optimized HCC Recurrence Prediction Using APO Algorithm Multiple Time Series Clinical Liver Cancer Dataset.

The classification of recurrence and non recurrence of Hepato Cellular carcinoma (HCC) outcome after Radio Frequency Ablation therapy is a critical task. Multiple time series clinical liver cancer dataset is collected from different dataset and time interval. A merging algorithm is used to merge all attributes collected from different sources in multiple time periods. In order to preserve the originality of information, statistical measures of each attribute is calculated and considered them as additional attributes for accurate prediction. However the merged dataset is unbalanced, in which, the number of samples from HCC recurrence class is much smaller than from HCC non recurrence. The feature weighting scheme select optimal features and parameter of classifiers are sequentially obtained from multiple iterations which causes higher computation time. In this paper, an efficient sampling approach is proposed using Inverse Random under Sampling (IRUS) to overcome class imbalance issue. IRUS under sample the majority class which creates a number of distinct partitions with a boundary separated minority and majority class samples. Additionally an optimization approach is proposed using Artificial Plant Optimization (APO) algorithm to select optimal features and parameters of classifiers to improve the effectiveness and efficiency of classification. The optimization approach reduces the number of iteration and computation time for feature selection and parameter selection for classifiers which classify the recurrence and non recurrence of HCC. Classify patients with HCC and without HCC based on optimal features and parameters by Support Vector Machine (SVM) and Random Forest(RF) classifiers. Finally, the experimental results are conducted to prove the effectiveness of the proposed method over existing method in terms of accuracy, specificity, sensitivity and balanced accuracy.

Root caries among type 2 diabetes mellitus patients visiting a hospital.

The relationship between diabetes and root caries has not received much attention in the literature; therefore the objectives of the present study were to assess the root surface caries among type 2 diabetic patients and the factors affecting root surface caries. A hospital based cross-sectional study was done among type 2 diabetics visiting a medical hospital in Bangalore. Those who had been diagnosed from at least past 5 years and were above 35 years of age were included. Among the 400 study subjects, root caries were present among 42% of the subjects. There was a statistically significant association for the presence of root caries and age (p = 0.00023), presence of periodontal pockets (p = 0.0004) and presence of loss of attachment of more than 3 mm (p < 0.0001). These findings indicate that there is a need for implementation of caries preventive measures with increasing age, and among those with compromised periodontal status among those suffering from type 2 diabetes mellitus.

Study of prevalence of endocrine abnormalities in primary empty sella.

INTRODUCTION: Empty sella is usually an incidental finding. Empty sella is an anatomical condition characterized by the presence of cerebrospinal fluid within the sella with a small pituitary gland compressed above the pituitary floor causing endocrine abnormalities. AIM: The aim of this study is to evaluate hormonal abnormalities associated with empty sella in tertiary care center. MATERIALS AND METHODS: This ongoing study was carried out in patients attending to endocrine out-patient departments from August 2012 to July 2013. A detailed history and examination was done. Hormonal evaluation including free thyroid hormones, thyroid stimulating hormone, growth hormone (GH), follicular stimulating hormone, luteinizing hormone, cortisol and prolactin was done. RESULTS: A total of 16 patients diagnosed clinically and biochemically of hormonal abnormalities were found to have empty sella on magnetic resonance imaging. Hypocortisolemia in 62.5% of cases, hypothyroidism in 50% of cases, in 18.75% hypogonadism, hyper prolactinemia in 18.7.5%, GH deficiency in 12.5% of cases and in 12.5% cases posterior pituitary involvement is seen. CONCLUSION: The high incidence of endocrine abnormalities associated with empty sella necessitates the need for prompt evaluation and early replacement of hormones for better quality-of-life.

A rare case of short stature: Say Meyer syndrome.

INTRODUCTION: Say Meyer syndrome is rare X linked condition characterized by developmental delay, short stature and metopic suture synostosis. We are reporting a case of Say Meyer syndrome presented to our hospital for short stature and developmental delay at age 3½ years. CASE REPORT: A 3½-year-old boy presented to our hospital for decreased growth velocity from the age of 1 year. History revealed the boy had a birth weight of 2.3 kg, had an episode of seizures in the neonatal period. He was born to non-consanguineous marriage. He had global developmental delay and there was a lack of bowel and bladder control. History did not reveal any hearing or visual impairment. No history of any chronic systemic illnesses. Magnetic resonance imaging (MRI) brain revealed mild diffuse frontotemporal atrophy with multiple irregular gliotic areas in bilateral frontal lobes. Diffuse white matter volume loss in bilateral cerebral hemispheres. Diffuse thinning of corpus callosum. Diffuse periventricular hyper intensity on T2W and fluid attenuated inversion recovery sequences. CONCLUSION: Say Meyer syndrome is rare X linked condition characterized by developmental delay, short stature and metopic suture synostosis. Characteristic MRI brain findings include diffuse frontotemporal atrophy with multiple gliotic areas in frontal lobes. Diffuse white matter volume loss in bilateral cerebral hemispheres.

A study on metabolic variables and its association with high sensitive C-reactive protein in obese children and adolescents.

Obesity in children and adolescents predispose to the development of obesity in adulthood and subsequent cardiovascular disease. High-sensitivity C-reactive protein (hsCRP) is a marker of low grade inflammatory state, which characterizes an atherosclerotic process. The aim of this study was to assess the metabolic abnormalities and its association with hsCRP in obese children and adolescents. A total of 62 obese children and adolescents and 24 healthy children and adolescents with a normal weight were recruited. In all subjects, anthropometric and biochemical parameters were measured. Body mass index (BMI) and blood pressure were significantly higher in the obese children and adolescents than the control. Obese children had significantly higher hsCRP levels (P < 0.001), total cholesterol, triglyceride, low-density lipoprotein-cholesterol (LDL-C) and lower high-density lipoprotein-cholesterol than the control group. Furthermore, homeostatic model assessment-insulin resistance (HOMA-IR) was significantly higher in obese children compared with the normal weight children. Furthermore, hsCRP showed a positive correlation with BMI (r = 0.357; P = 0.028), total cholesterol (r = 0.367; P = 0.008) and LDL-C (r = 0.356; P = 0.01), insulin (r = 0.311; P = 0.026) and not with HOMA-IR (r = 0.244; P = 0.084)). In conclusion, obese children and adolescents have significantly increased hsCRP compared with a normal weight group. Early intervention and prevention of obesity in children and adolescents decreases cardiovascular disease in later life.

Seizure as a presenting manifestation of vitamin D dependent rickets type 1.

There are two types of vitamin D dependent rickets (VDDR) that cause rickets in children. VDDR type 1 (VDDR-I) is caused by an inborn error of vitamin D metabolism, which interferes with renal conversion of calcidiol (25OHD) to calcitriol (1,25(OH)2D) by the enzyme 1-α-hydroxylase. Patients with VDDR-I have mutations of chromosome 12 that affect the gene for the enzyme 1-α-hydroxylase, resulting in decreased levels of 1,25(OH) vitamin D. Clinical features include growth failure, hypotonia, weakness, rachitic rosary, convulsions, tetany, open fontanels and pathologic fractures. We report a case of VDDR-I in 14-month-old male child. Establishing an early diagnosis of these genetic forms of rickets is challenging, especially in developing countries where nutritional rickets is the most common variety of the disease where genetic diagnosis is not always possible because of financial constraints. A prompt diagnosis is necessary to initiate adequate treatment, resolve biochemical features and prevent complications, such as severe deformities that may require surgical intervention.