DETERMINATION OF 10-GINGEROL IN INDIAN GINGER BY VALIDATED HPTLC METHOD OF SAMPLES COLLECTED ACROSS SUBCONTINENT OF INDIA

Objective: A simple, sensitive, precise, and accurate stability indicating HPTLC (high-performance thin-layer chromatography) method for analysis of 10-gingerol in ginger has been developed and validated as perICH guidelines.Methods: The separation was achieved on TLC (thin layer chromatography) aluminum plates pre-coated with silica gel 60F254 using n-hexane: ethyl acetate 55:45 (%, v/v) as a mobile phase. Densitometric analysis was performed at 569 nm.Results: This system was found to have a compact spot of 10-gingerol at RF value of 0.57±0.03. For the proposed procedure, linearity (r2 = 0.998±0.02), limit of detection (18ng/spot), limit of quantification (42 ng/spot), recovery (ranging from 98.35%–100.68%), were found to be satisfactory.Conclusion: Statistical analysis reveals that the content of 10-gingerol in different geographical region varied significantly. The highest and lowest concentration of 10-gingerol in ginger was found to be present in a sample of Patna, Lucknow and Surat respectively which inferred that the variety of ginger found in Patna, Lucknow are much superior to other regions of India

GENETIC DIVERSITY IN ACCESSIONS OF INDIAN TURMERIC (CURCUMA LONGA L.) USING RAPD MARKERS

Objective: The present investigation was undertaken for identification and assessment of eight accessions of Curcuma longa collected from all ecological zones in India by random amplification of polymorphic DNA (RAPD) markers.Methods: DNA was isolated using modified cetyl trimethyl ammonium bromide (CTAB) method. Polymerase chain reaction (PCR) was performed according to the method based on Williams et al. and data analysis was done using Alpha Imager EC software.Results: Eleven out of twenty primers screened were informative and produced 150 amplification products among which 132 products (88%) were found to be polymorphic. The percentage polymorphism of all 08 accessions ranged from 44.44% to 100%. A total of 150 amplification products were scored with an average frequency of 13.63 bands per primer. Most of the RAPD markers studied showed a different level of genetic polymorphism. The data of 150 RAPD bands were used to generate Jaccard's similarity coefficients and to construct a dendrogram by means of UPGMA.Conclusion: Results shows that C. longa undergoes genetic variation due to a wide range of ecological conditions within distribution area of its population in India. This investigation as an understanding of the level and partitioning of genetic variation within the accessions and would provide an important input into determining efficient management strategies and will help to breeders for turmeric improvement program

An Empirical Analysis of the Linder

This paper presents empirical evidence in support of the Linder theory of international trade for three of the South Asian countries, Bangladesh, India, and Pakistan. This finding implies that these countries trade more intensively with countries of other regions, which may have similar per capita income levels, as predicted by Linder in his hypothesis. The contribution of this research is threefold: first, there is new information on the Linder hypothesis by focusing on South Asian countries; second, this is one of very few analyses to capture both time-series and cross-section elements of the trade relationship by employing a panel data set; third, the empirical methodology used in this analysis corrects a major shortcoming in the existing literature by using a censored dependent variable in estimation.

Analyzing the Parameters of Multidimensional Poverty in Taluka Naushahro Feroze: A Case Study

This research paper tackles the multidimensional poverty applying Foster and Alkire methods of Taluka Naushahro Feroze’s 14 Union councils on the basic figures. No any single navigator gives clear value for deprivation as naturally it is multidimensional. Three dimensions are selected having unequal weights in health, education, and living standard. These areas have been extra distributed in ten indicators, two for education, two for health while six for living standards. The out-put shows that Union Council Waggan has the most multidimensional poverty while least multidimensional poverty was found in Union Councils of Cheeho Taluka Naushahro Feroze. It further suggests an indicator which has highest contributions for multidimensional poverty such as life expectancy, child school attendance, school quality, child mortality, year of schooling, walls, cooking fuel, overcrowding and which contribute lowest is electricity and improved drinking water. Percentage of people for those who are MPI poor of Taluka Naushahro is 47.95 % (incidence of poverty), while average deprivation of people is 55.75 % furthermore, multidimensional poverty index (MPI) is 26.73 % in Naushahro Feroze. Keywords: Multidimensional poverty, incidence of poverty, Average deprivation DOI: 10.7176/JPID/53-06 Publication date: March 31st 202

SOLID PHASE MICROBIAL FERMENTATION OF ANABOLIC STEROID, DIHYDROTESTOSTERONE WITH ASCOMYCETE FUNGUS FUSARIUM OXYSPORUM

Objective: Microbial catalysis is used in the commercial production of many bioactive steroids. Solid phase microbial fermentation of anabolic steroid, dihydrotestosterone (DHT, 1), was carried out with ascomycete fungal strain Fusarium oxysporum (NRRL-1392).Methods: Sabouraud-4% glucose-agar was used to cultivate the fungal cultures as solid phase medium. Substrate 1 was incubated with Fusarium oxysporum (NRRL-1392) for 8 days. Microbial transformed metabolites were purified by using column chromatographic technique. Results: Ascomycete fungal strain Fusarium oxysporum (NRRL-1392), transformed dihydrotestosterone (1) to four oxidative metabolites 2-5  using solid phase microbial transformation metod. During biotransformation process the hydroxy group was incorporated in inactivated methine carbon atoms at C-7 and C-11 positions. Their structures were elucidated by means of a homo and heteronuclear 2D NMR and by HREI-MS techniques as 17b-hydroxyandrosta-1, 4-dien-3-one 2, androsta-1, 4-diene-3, 17-dione 3, 7a, 17b-dihydroxyandrosta-1, 4-dien-3-one (4), and 11a-hydroxyandrosta-1, 4-diene-3, 17-dione 5. The relative stereochemistry of newly incorporated hydroxy groups were deduced by 2D NOESY experiment.Conclusion: In conclusion, microbial biocatalysis is an attractive alternative tool for the preparation of new bioactive steroids, which might be difficult to prepare by conventional chemical routes. Furthermore, microbial-catalyzed biotransformations can produce commercially valuable steroidal pharmaceuticals for the pharmaceutical industry.Â

SOLID PHASE MICROBIAL REACTIONS OF SEX HORMONE, TRANS-ANDROSTERONE WITH FILAMENTOUS FUNGI

Objective: A microbial biotransformation study was performed on trans-androsterone (1) using solid phase medium. In the present context, trans-androsterone (1), a sex hormone was fermented with two filamentous fungi, Rhizopus stolonifer (black bread mold) and Fusarium lini.Methods: Sabouraud-4% glucose-agar were used to cultivate the fungal cultures as solid phase medium. Substrate 1 was incubated with R. stolonifer (ATCC 10404) and F. lini (NRRL 68751) for 8 days. Microbial transformed metabolites were purified by using column chromatographic technique. Results: The metabolism study of 1 revealed that various metabolites were detected when incubated with filamentous fungi. A total of 3 transformed products were obtained. The reactions occurred that exhibited diversity; including selective hydroxylation at C-6 and C-7 along with oxidation occurs at C-3 positions. Their structure and identified on the basis of extensive spectroscopic data (NMR, HREIMS, IR and UV) as 3b,7b-dihydroxy-5a-androstan-17-one 2 in a good yield (58%), 6b-hydroxy-5a-androstan-3,17-dione 3, and 3b,6b-dihydroxy-5a-androstan-17-one 4.Conclusion: Solid phase microbial transformation method can successfully be used for the development of new steroidal drugs. The modified steroidal molecules could favor when compared to their natural counterparts due to several medicinal advantages.Â

MICROBIAL OXIDATION OF FINASTERIDE WITH MACROPHOMINA PHASEOLINA(KUCC 730)

Objectives: New  microbial oxidative derivatives of Finasteride [17β-(N-tert-butylcarbamoyl)-4-aza-5α-androst-1-en-3-one] (1) has been investigated with Macrophomina phaseolina (ATCC730).Methods: Fermented media of  Macrophomina phaseolina (ATCC730) was prepared to cultivate the fungal cultures . Substrate 1 was incubated in liquid media for 16 days. After sixteen days, filtration and extraction of the fermented media was carried out with 9 L DCM in three portions. Resulting organic extract was dried using anhydrous (Na2SO4), and evaporated to afford a brown gum (950 mg). This on chromatographic purification with MeOH in CH2Cl2 afforded the metabolites 2-4 . Results: Three oxidised metabolites of finasteride (1) which were identified as 15-oxo-finasteride (2), 11a-hydroxyfinasteride (3), and 15β-hydroxyfinasteride (4). Metabolite 2 was found to be new. The structure of the oxidised metabolites were elucidated by 1-D (1H, 13C) and 2-D NMR (COSY, HMBC, HMQC, NOESY) techniques and MS analyses.Conclusion: As a result of these study, oxidation at C-7, C-11 and C-15 positions were found. Metabolite 2 was identified as a new metabolite

An Empirical Analysis of the Linder Theory of International Trade for South Asian Countries.

This paper presents empirical evidence in support of the Linder theory of international trade for three of the South Asian countries, Bangladesh, India, and Pakistan. This finding implies that these countries trade more intensively with countries of other regions, which may have similar per capita income levels, as predicted by Linder in his hypothesis. The contribution of this research is threefold: first, there is new information on the Linder hypothesis by focusing on South Asian countries; second, this is one of very few analyses to capture both time-series and cross-section elements of the trade relationship by employing a panel data set; third, the empirical methodology used in this analysis corrects a major shortcoming in the existing literature by using a censored dependent variable in estimation

Flexible and scalable software defined radio based testbed for large scale body movement

Human activity (HA) sensing is becoming one of the key component in future healthcare system. The prevailing detection techniques for IHA uses ambient sensors, cameras and wearable devices that primarily require strenuous deployment overheads and raise privacy concerns as well. This paper proposes a novel, non-invasive, easily-deployable, flexible and scalable test-bed for identifying large-scale body movements based on Software Defined Radios (SDRs). Two Universal Software Radio Peripheral (USRP) models, working as SDR based transceivers, are used to extract the Channel State Information (CSI) from continuous stream of multiple frequency subcarriers. The variances of amplitude information obtained from CSI data stream are used to infer daily life activities. Different machine learning algorithms namely K-Nearest Neighbour, Decision Tree, Discriminant Analysis and Naïve Bayes are used to evaluate the overall performance of the test-bed. The training, validation and testing processes are performed by considering the time-domain statistical features obtained from CSI data. The K-nearest neighbour outperformed all aforementioned classifiers, providing an accuracy of 89.73%. This preliminary non-invasive work will open a new direction for design of scalable framework for future healthcare systems

An Intelligent Non-Invasive Real-Time Human Activity Recognition System for Next-Generation Healthcare

Human motion detection is getting considerable attention in the field of Artificial Intelligence (AI) driven healthcare systems. Human motion can be used to provide remote healthcare solutions for vulnerable people by identifying particular movements such as falls, gait and breathing disorders. This can allow people to live more independent lifestyles and still have the safety of being monitored if more direct care is needed. At present wearable devices can provide real-time monitoring by deploying equipment on a person’s body. However, putting devices on a person’s body all the time makes it uncomfortable and the elderly tend to forget to wear them, in addition to the insecurity of being tracked all the time. This paper demonstrates how human motions can be detected in a quasi-real-time scenario using a non-invasive method. Patterns in the wireless signals present particular human body motions as each movement induces a unique change in the wireless medium. These changes can be used to identify particular body motions. This work produces a dataset that contains patterns of radio wave signals obtained using software-defined radios (SDRs) to establish if a subject is standing up or sitting down as a test case. The dataset was used to create a machine learning model, which was used in a developed application to provide a quasi-real-time classification of standing or sitting state. The machine-learning model was able to achieve 96.70% accuracy using the Random Forest algorithm using 10 fold cross-validation. A benchmark dataset of wearable devices was compared to the proposed dataset and results showed the proposed dataset to have similar accuracy of nearly 90%. The machine-learning models developed in this paper are tested for two activities but the developed system is designed and applicable for detecting and differentiating x number of activities