Automated Screening for Three Inborn Metabolic Disorders: A Pilot Study

Background: Inborn metabolic disorders (IMDs) form a large group of rare, but often serious, metabolic disorders. Aims: Our objective was to construct a decision tree, based on classification algorithm for the data on three metabolic disorders, enabling us to take decisions on the screening and clinical diagnosis of a patient. Settings and Design: A non-incremental concept learning classification algorithm was applied to a set of patient data and the procedure followed to obtain a decision on a patient’s disorder. Materials and Methods: Initially a training set containing 13 cases was investigated for three inborn errors of metabolism. Results: A total of thirty test cases were investigated for the three inborn errors of metabolism. The program identified 10 cases with galactosemia, another 10 cases with fructosemia and the remaining 10 with propionic acidemia. The program successfully identified all the 30 cases. Conclusions: This kind of decision support systems can help the healthcare delivery personnel immensely for early screening of IMDs

Development and validation of RP HPLC method for determination of metformin and sitagliptin in bulk and pharmaceutical dosage form

A simple and rapid reversed phase-high performance liquid chromatographic method was developed for simultaneous determination of Metformin and Sitagliptin in Tablet Dosage form. The elution was done with a mobile phase of Water: Methanol (60:40) on Intersil-BDS C18 column (250 × 4.6 mm, 5 μm particle size). The wavelength detector was set at 258 nm. Retention times for Metformin and Sitagliptin were around 2.869 min, 3.942 min respectively. The reliability and analytical performance of the proposed HPLC procedure were statistically validated according to the respect of linearity, ranges, precision, accuracy, repeatability, reproducibility, detection and quantification limits. Linear ranges were established between 20-80 μg/mL for both the drug. The LOD and LOQ for Metformin were found to be 0.663, 1.92 and for Sitagliptin were found to be 0.405, 1.228 respectively. The described High Performance Liquid Chromatography method was successfully employed for the analysis of pharmaceutical formulations containing combined dosage for

Patronin-mediated minus end growth is required for dendritic microtubule polarity.

Microtubule minus ends are thought to be stable in cells. Surprisingly, in Drosophila and zebrafish neurons, we observed persistent minus end growth, with runs lasting over 10 min. In Drosophila, extended minus end growth depended on Patronin, and Patronin reduction disrupted dendritic minus-end-out polarity. In fly dendrites, microtubule nucleation sites localize at dendrite branch points. Therefore, we hypothesized minus end growth might be particularly important beyond branch points. Distal dendrites have mixed polarity, and reduction of Patronin lowered the number of minus-end-out microtubules. More strikingly, extra Patronin made terminal dendrites almost completely minus-end-out, indicating low Patronin normally limits minus-end-out microtubules. To determine whether minus end growth populated new dendrites with microtubules, we analyzed dendrite development and regeneration. Minus ends extended into growing dendrites in the presence of Patronin. In sum, our data suggest that Patronin facilitates sustained microtubule minus end growth, which is critical for populating dendrites with minus-end-out microtubules

Unscented Kalman Filters Integrated with Deep Learning Approaches for Active Sonar Based 2D Underwater Target Tracking

This manuscript proposes a new approach to track 2D targets using a combination of machine learning algorithms and the Unscented Kalman filter (UKF). The approach makes use of active sonar sensors to measure range and bearing, which are used to predict the target’s course and speed. So far in the literature of target tracking, researchers assumed covariance matrix of the noise in sonar measurements. In this manuscript, it is tried to estimate the same using deep learning algorithms. The Machine Learning algorithms, such as multilayer perceptron, convolutional neural network, long-short term memory, and gated recurrent unit, are employed to approximate the covariance of the noise in the input measurements. Simultaneously, the Unscented Kalman Filter (UKF) is utilised to mitigate the noise in the measurements and to estimate the position and speed of the target. The results are quantified through Monte Carlo simulations in a simulated underwater environment. The measurements are assumed to conform to a normal Gaussian distribution with a mean of zero. The findings indicate that LSTM has superior performance compared to the other models. Nevertheless, it is important to note that the results are constrained in their applicability due to the restricted set of variables employed for training the machine learning models

Degradable Nitric Oxide-Releasing Biomaterials via Post-Polymerization Functionalization of Cross-Linked Polyesters

The synthesis of diverse nitric oxide (NO)-releasing network polyesters is described. The melt phase condensation of polyols with a calculated excess of diacid followed by thermal curing generates crosslinked polyesters containing acid end groups. Varying the composition and curing temperatures of the polyesters resulted in materials with tunable thermal and degradation properties. Glass transition temperatures for the synthesized materials range from −25.5 °C to 3.2 °C, while complete degradation of these polyesters occurs within a minimum of nine weeks under physiological conditions (pH 7.4, 37 °C). Post-polymerization coupling of aminothiols to terminal carboxylic acids generate thiol-containing polyesters, with thermal and degradation characteristics similar to those of the parent polyesters. After nitrosation, these materials are capable of releasing up to 0.81 μmol NO cm−2 for up to 6 d. The utility of the polyesters as antibacterial biomaterials was indicated by an 80% reduction of Pseudomonas aeruginosa adhesion compared to unmodified controls

Bacterial Endo-Symbiont Inhabiting Tridax procumbens L. and Their Antimicrobial Potential

Bacterial symbionts inhabiting Tridax procumbens L. were screened for antimicrobial potential with the aim to isolate potent bacteria bearing significant activity against test pathogens. The selected isolate was subjected to large scale fermentation to extract antimicrobial metabolite. The organic phase was reduced under vacuum pressure and crude ethyl acetate extract (10 mg/mL) was evaluated for antimicrobial activity against panel of test pathogens. The antibacterial activity was measured as a zone of inhibition and compared with standard antibiotics, gentamicin and tetracycline. Similarly, antifungal activity was compared with miconazole and bavistin. Significant activity was conferred against Shigella flexneri (MTCC 731) with 27±1.5 mm zone across the disc. Partially, purification of antimicrobial metabolite with TLC-bioautography and HPLC resulted in active fraction bearing activity at Rf 0.65 and eluting between 4 and 5 retention times. The obtained results are promising enough for future purification and characterization of antimicrobial metabolite. Thus, the study attributes to the growing knowledge on endophytes as one of the rich sources of antimicrobial potentials

Influence of Scaffold Size on Bactericidal Activity of Nitric Oxide-Releasing Silica Nanoparticles

A reverse microemulsion synthesis was used to prepare amine functionalized silica nanoparticles of three distinct sizes (i.e., 50, 100, and 200 nm) with identical amine concentrations. The resulting hybrid nanoparticles, consisting of N-(6 aminohexyl) aminopropyltrimethoxysilane and tetraethoxysilane, were highly monodisperse in size. N-diazeniumdiolate nitric oxide (NO) donors were subsequently formed on secondary amines while controlling reaction conditions to keep the total amount of nitric oxide (NO) released constant for each particle size. The bactericidal efficacy of the NO releasing nanoparticles against Pseudomonas aeruginosa increased with decreasing particle size. Additionally, smaller diameter nanoparticles were found to associate with the bacteria at a faster rate and to a greater extent than larger particles. Neither control (non-NO-releasing) nor NO releasing particles exhibited toxicity towards L929 mouse fibroblasts at concentrations above their respective minimum bactericidal concentrations. This study represents the first investigation of the bactericidal efficacy of NO-releasing silica nanoparticles as a function of particle size

Metabolite Profiling for Six 'B' Vitamins Using LC-MS in Tomato Genotypes at Different Stages of Fruit Maturity

Vitamins are essential nutrients in food crucial for maintaining good health. Tomato, being a widely consumed vegetable, provides a good quantity of vitamins. Metabolite profiling of vitamins at different stages of fruit maturity in a crop helps identify the right stage for better quality. Based on preliminary screening for quality parameters, tomato lines rich in TSS, antioxidants, lycopene and beta-carotene were selected for the present study. Eight genotypes and a wild species were profiled for 'B' vitamins at three different stages of fruit maturity, viz., green, breaker and ripe stage. A simple and sensitive liquid chromatography-tandem mass spectrometric (LC-MS/MS) method for simultaneous determination of six 'B' vitamins was developed and validated by us. Among the genotypes studied, IIHR-249-1 recorded higher niacin, pantothenic acid and biotin content. Pyridoxine content was higher in the hybrid, Arka Rakshak. The wild species, LA-1777(Solanum habrochaites) was found to be rich in pantothenic acid, riboflavin and thiamine. Content of most of the vitamins increased with ripening of the fruit. IIHR-249-1 and LA-1777 were found to be rich in 'B' vitamins, earlier reported to be also rich in antioxidants and lycopene. These genotypes can be used for improving the nutritive value of tomato under crop improvement programmes, through conventional breeding or biotechnological approaches

Women’s’ empowerment in the fragile environment of Semi-Arid Tropics: focus on norms, agency and attitudes

Empowerment of women, in its simplest meaning refers to the process whereby women acquire an ability to make strategic life choices. Likewise, power is also thought of as an ability to make choices. This view of power focuses on structure or the social norms and forces that enable and or constrain thinking, action and behavior. Hence, there is now a focus and discussion on not just the power relations among actors and their agency (strengthening capabilities to act) but also on social structures, norms, and attitudes that enable (or constrain) the behavior of all actors – women, men, socially included and excluded (Hayward 2000).Taking cues from the work of Munoz-Boudet et.al (2012), this paper attempts to discuss that social norms, gender roles, individual capacities, assets, and the communities wherein the marginalized rural poor live, determine the opportunities available to women and men.Harnessing the rich VLS longitudinal panel data from 6 villages of India, the paper explains the dynamics of intra-household relationships gleaned from the longitudinal panel and highlights how gender differences and inequalities among sample households engaged in agriculture in these villages has changed over time. Q2 analysis is used to examine variation in gender norms and attitudes among communities/villages as well as discern distinguishing patterns and pathways towards women’s empowerment. The paper also appeals to analysis of the social network architecture, identifying existing formal and informal institutions that enable women’s agency, voice, claims and opportunities. Understanding women in their wider social setting - wider social contexts of gender, age, class and other identities that influence their relations with others, leads to a better appreciation of the change agents women can be in their households, communities and nation at large. Ultimately, to bring about socially transformative empowerment , the paper clearly points that it is imperative that individuals and groups develop the capacities to not only address the norms, attitudes and conditions that determine their life choices and aspirations but also challenge them to bring about this change

Giant cell tumor of the temporal bone – a case report

BACKGROUND: Giant cell tumor is a benign but locally aggressive bone neoplasm which uncommonly involves the skull. The petrous portion of the temporal bone forms a rare location for this tumor. CASE PRESENTATION: The authors report a case of a large giant cell tumor involving the petrous and squamous portions of the temporal bone in a 26 year old male patient. He presented with right side severe hearing loss and facial paresis. Radical excision of the tumor was achieved but facial palsy could not be avoided. CONCLUSION: Radical excision of skull base giant cell tumor may be hazardous but if achieved is the optimal treatment and may be curative