Indian Coal Mines in Hundred Years Old Fiction and Now: A Geographical Analysis

This study attempts to construe the first-ever coalmine-oriented Bengali fiction from a social, historical, and geographic perspective. Sailjananda Mukhopadhyay wrote Koylakuthi (the coal miners’ office) in 1922, representing Bengal’s coal mines. This study aims to reconstruct the miners’ society from the early 20th Century with narratives from this story and examine the societal challenges and changes a hundred years apart. A comparative study of the mining geo-cultural landscape of the 1920s Bengal and its contemporary counterpart is carried out. Changed geography, technology, and community are observed. And it reveals that areal expansion of the coalfields has increased production, and technological advancement has increased the safety and security of the miner class. However, the labour structure, class and caste hierarchy, and patriarchal mindset have hardly changed

EFFECT OF BOILING AND MICROWAVE ASSISTED PROCESSING ON THE ANTIMICROBIAL EFFICACY OF VITAMIN–C IN EMBLICA OFFICINALIS

Objective: The present work aimed to expand the awareness of restoring vitamin-C in its active form on different heat exposures. The effect of microwave-assisted processing and boiling of the aqueous crude extract of citrus fruit Emblica officinalis (amla) has been correlated with its antimicrobial efficacy against E. coli. Methods: The aqueous crude extract of dried amla pulp exposed to microwave radiation(600W,5 min) and boiling (5 min) were titrimetrically estimated for vitamin-C content by DCPIP-(2,6, Dinitrophenol indophenol) method and compared the same with the untreated sample. These three samples were studied for their effect on the growth pattern of E. coli turbidimetrically. The antimicrobial susceptibility test by agar cup well diffusion method was further followed to measure the zone of inhibitions (ZOI) for these three test extracts against E. coli. Results: The total estimated vitamin-C content was 26.76 mg/100g, 25.35 mg/100g and 21.12 mg/100g in the untreated extract (UTE), microwaved extract (MWE) and boiled extract (BE) respectively. At a higher concentration (0.8 mg/ml), the UTE showed a greater ZOI of 20 mm and a comparable ZOI of 18 mm for the MWE against E. coli. In addition, a reduced ZOI of 10 mm was recorded in case of the BE. At a lowest concentration (0.05 mg/ml), the UTE inhibited the growth with a least ZOI of 7 mm, whereas no inhibition zones were detected for MWE and BE at this concentration. Conclusion: The present investigation demonstrated the effect of boiling and microwave-assisted processing on the content of bioactive vitamin-C and its antimicrobial activity. The DCPIP method calculated a more vitamin-C retention in the MWE than the BE. As the boiling method destroyed the vitamin more rapidly, a higher growth rate of E. coli was measured in the presence of BE than the UTE and MWE. In addition, the antimicrobial assay also showed a least inhibitory effect against E. coli in the presence of the BE. A moderate inhibitory effect for MWE was also detected. Thus the present investigation proved that the boiling process destroys vitamin-C present in a food sample to a higher extent than the microwave-assisted processing

Cytoplasmic chromatin triggers inflammation in senescence and cancer

Chromatin is traditionally viewed as a nuclear entity that regulates gene expression and silencing. However, we recently discovered the presence of cytoplasmic chromatin fragments that pinch off from intact nuclei of primary cells during senescence, a form of terminal cell-cycle arrest associated with pro-inflammatory responses. The functional significance of chromatin in the cytoplasm is unclear. Here we show that cytoplasmic chromatin activates the innate immunity cytosolic DNA-sensing cGAS-STING (cyclic GMP-AMP synthase linked to stimulator of interferon genes) pathway, leading both to short-term inflammation to restrain activated oncogenes and to chronic inflammation that associates with tissue destruction and cancer. The cytoplasmic chromatin-cGAS-STING pathway promotes the senescence-associated secretory phenotype in primary human cells and in mice. Mice deficient in STING show impaired immuno-surveillance of oncogenic RAS and reduced tissue inflammation upon ionizing radiation. Furthermore, this pathway is activated in cancer cells, and correlates with pro-inflammatory gene expression in human cancers. Overall, our findings indicate that genomic DNA serves as a reservoir to initiate a pro-inflammatory pathway in the cytoplasm in senescence and cancer. Targeting the cytoplasmic chromatin-mediated pathway may hold promise in treating inflammation-related disorders

A new, highly conserved domain in Swi2/Snf2 is required for SWI/SNF remodeling

SWI/SNF is an ATP-dependent remodeler that mobilizes nucleosomes and has important roles in gene regulation. The catalytic subunit of SWI/SNF has an ATP-dependent DNA translocase domain that is essential for remodeling. Besides the DNA translocase domain there are other domains in the catalytic subunit of SWI/SNF that have important roles in mobilizing nucleosomes. One of these domains, termed SnAC (Snf2 ATP Coupling), is conserved in all eukaryotic SWI/SNF complexes and is located between the ATPase and A-T hook domains. Here, we show that the SnAC domain is essential for SWI/SNF activity. The SnAC domain is not required for SWI/SNF complex integrity, efficient nucleosome binding, or recruitment by acidic transcription activators. The SnAC domain is however required in vivo for transcription regulation by SWI/SNF as seen by alternative carbon source growth assays, northern analysis, and genome-wide expression profiling. The ATPase and nucleosome mobilizing activities of SWI/SNF are severely affected when the SnAC domain is removed or mutated. The SnAC domain positively regulates the catalytic activity of the ATPase domain of SWI/SNF to hydrolyze ATP without significantly affecting its affinity for ATP

Studies in some Aspects of Anti-Tubercular Drug Design Utilizing Theoretical Molecular Descriptors

Rational drug designing adopts an integrated approach to study and understand the structures of potential agents (particularly, the analogs of an existing drug or lead compound), elucidate how they might interact with target protein structures and predict their activity profiles in-silico. Identification of such potential agents from a large number of analogous structures makes computational modeling approach a useful tool for drug discovery studies. Availability of various experimental data against different leads and their derivatives, and sometimes, the structural knowledge of their target proteins facilitate the structure-activity modeling studies and make modern day approach to drug design “rational”, compared to the protocols pursued in the past. Quantitative structureactivity relationship (QSAR) can be derived for a series of structurally similar type of derivatives, and efficient QSAR models can predict the activity profiles for any structurally known molecule in that series, whether real or virtual. Prediction of such important properties for a large number of analogous structures definitely would be a “blessing” for drug discovery process and will reduce the cost and time of the entire drug development process. Synthetic chemists can utilize these models as a decision support tool in synthesis planning and do the initial screening in a fraction of time. Molecular docking, another important chemometric technique, has the potential to address several important issues that arise in drug discovery such as interaction between the ligand (chemical compound) and the target (generally, protein structure). The thesis enlists various QSAR models in conjunction with molecular docking studies for mainly three types of chemical structures having potential anti-tubercular activity, viz., derivatives of fluoroquinolone, quinoxaline and nitrofuranyl amide and describes the usefulness of different statistical as well as neural network approaches to improve the predictability of these models. Insights gained from these studies may be applied in anti-tubercular drug design with additional chemical structures. Mycobacterium tuberculosis (Mtb), the principal causative agent of tuberculosis in humans, is estimated to cause two million deaths every year. The existing drugs viz., isoniazid, rifampicin, ethambutol, pyrazinamide etc., although of immense value in controlling the disease to some extent, have several shortcomings, the most important of them being the emergence of drug resistance rendering even the front-line drugs inactive. So, there is an urgent need to develop novel agents having high anti-tubercular activity values, which may shorten the treatment period of tuberculosis disease, thus preventing the emergence of drug resistance.The thesis is mainly concerned with the development of novel computational approaches that could be useful in the early stages of drug discovery for elucidating the potency of promising anti-tubercular agents belonging to several different families of anti-tuberculosis leads. The thesis begins with a focus on the fluoroquinolone derivatives, which are used in case of first line drug resistance. To examine specific structure activity relationships of quinolone antibacterials against mycobacterial activity, an attempt has been made to establish a quantitative structure activity relationship modeling for a series of quinolone compounds against Mycobacterium fortuitum and Mycobacterium smegmatis. Due to lack of sufficient physicochemical data for the anti-mycobacterial compounds, it becomes very difficult to develop predictive methods based on experimental data. QSARs were generated from the standpoint of physicochemical, constitutional, geometrical, electrostatic and topological indices, which have been calculated solely from the chemical structure of N-1, C-7 and 8 substituted quinolone compounds and ridge regression models have been developed for a better understanding of structure-activity relationships. Consideration of an intermolecular similarity analysis approach based on atom-pair method led to data sub-grouping of the considered analog structures depending on their similarity to a drug or lead molecule, and the influence of various molecular descriptors in different data subsets were compared. It is suggested that topological descriptors play an important role in the design of QSAR models for fluoroquinolone derivatives. In continuation of the work with fluoroquinolone derivatives, the applicability and scope of descriptor based QSAR models have been improved by introducing feature selection method along with the modeling techniques. Virtual screening using molecular docking approach have also been applied in course of this work to identify potential molecules targeting DNA gyrase A from Mycobacterium tuberculosis, an effective and validated mycobacterial target. Initially QSAR models have been developed against M.fortuitum and M. smegmatis using series of structurally related fluoroquinolone derivatives as DNA gyrase inhibitors. The statistically significant models have been then validated by a test set of compounds and y-randomization scheme. To aid the creation of novel antitubercular compounds, combinatorial library has been developed on fluoroquinolone template whose activity values have been measured by the above models. Highly active compounds predicted from the models were then subjected to molecular docking study to investigate the mechanism of drug binding with the DNA gyrase A protein of M. tuberculosis and the compounds showing similar type of binding patterns with that of the existing drug molecules viz., sparfloxacin, have been reported. Observations suggest that hydrophobic characteristics of the small molecular structure together with few hydrogen bond interactions are playing an essential role in anti-tubercular activity for the fluoroquinolone derivatives. A representative set of seven compounds with highly predicted MIC values were identified in the analysis. An endeavor towards development of QSAR models for quinoxaline compounds having excellent anti-tubercular activities constitute another integral part of the investigation. Since, there is a dearth of anti-mycobacterial activity studies involving an adequate number of quinoxaline molecules, an effort was made to merge multiple quinoxaline data sets after verifying that their constituents share the same chemical space.Such a merged data set was utilized to develop robust QSAR models that were validated statistically by leave-one-out and leave-many-out methods. Both 2D and 3D-QSAR models have been developed for the quinoxaline derivatives. In addition, genetic algorithm (GA) and simulated annealing (SA) have been applied as variable selection methods for the selection of a preferred set of molecular descriptors that can signify the chemico–biological interaction. 2D-QSAR modeling using GA or SA based partial least squares (GA-PLS and SA-PLS) methods identified some important topological and electrostatic descriptors as vital factors for tubercular activity. Kohonen network and counter propagation neural network (CP-NN) considering GA and SA based feature selection methods have also been applied in an attempt to capture inherent non-linearity in the structure-function relationships of quinoxaline compounds. In addition, 3D-QSAR models obtained by GA-PLS and SA-PLS methods identify the influences of steric and electrostatic field effects that can give a direction for the synthesis of new quinoxaline derivatives with potent anti-tubercular activity. A series of nitrofuranyl amides were also subjected to quantitative structureactivity relationship (QSAR) analysis using various feature selection methods. Genetic algorithm (GA), simulated annealing (SA) and stepwise regression have been applied as variable selection methods for an effective comparison and subsequently, models were generated for these compounds. Both 2D and 3D QSAR analyses of such derivatives provide important structural insights for designing potent anti-tuberculosis drugs.Summarising, the thesis presents a comprehensive in silico analysis of structureactivity relationships of three important classes of drugs and their derivatives having antitubercular activity. Although the principal focus of the thesis has been the discovery of potent anti-tubercular compounds, the methodologies described are highly generic in nature, lending themselves to the application in drug discovery programmes targeted against other diseases

Medical Image Segmentation Using a Genetic Algorithm

Advances in medical imaging technology have led to the acquisition of large number of images in different modalities. On some of these images the boundaries of key organs need to be accurately identified for treatment planning and diagnosis. This is typically performed manually by a physician who uses prior knowledge of organ shapes and locations to demarcate the boundaries of organs. Such manual segmentation is subjective, time consuming and prone to inconsistency. Automating this task has been found to be very challenging due to poor tissue contrast and ill-defined organ/tissue boundaries. This dissertation presents a genetic algorithm for combining representations of learned information such as known shapes, regional properties and relative location of objects into a single framework in order to perform automated segmentation. The algorithm has been tested on two different datasets: for segmenting hands on thermographic images and for prostate segmentation on pelvic computed tomography (CT) and magnetic resonance (MR) images. In this dissertation we report the results of segmentation in two dimensions (2D) for thermographic images; and two as well as three dimensions (3D) for pelvic images. We show that combining multiple features for segmentation improves segmentation accuracy as compared with segmentation using single features such as texture or shape alone

Development of a Process for Clarification and Concentration of Jamun (Syzygium cuminii) Juice using Membrane Filtration

Traditional processing of fruit juice is labour, energy and time intensive. It involves heat treatment at various stages of processing. The heat treatment causes losses in natural nutrients, colour and aroma. It also results in typical cooked flavour in the juice. There is a need to develop and adopt non-thermal processing protocols. Enzymatic extraction of juice followed by clarification and concentration through membrane filtration could be a suitable alternative for juice processing. Feasibility of the above-hypothesized process was verified using Jamun (Syzygium cuminii L) as the raw material. Jamun is an underutilised minor fruit grown in plenty. It has several nutritional and therapeutic values. Jamun is an excellent source of antioxidants and anthocyanin that makes it a prospective fruit for value addition and further commercialisation. Various physico-chemical, mechanical and nutritional properties of Jamun fruit were measured which were used in designing and developing the protocol. The Jamun juice was purple in colour (b* value: -0.9) with significant amount of polyphenol (203.76±9.84 mg GAE/g), tannin (94.52±9.19 mg/100g) and anthocyanin (195.58±6.15 mg/100g). Process parameters for enzymatic extraction of Jamun juice were optimised for different variety of Pectinase and Tannase. Pectinase from Aspergillus aculeatus strain gave best results in terms of quality of the juice at 44 oC with an incubation time and enzyme concentration of 80 minute and 0.05% (w/w) respectively. Juice yield could be achieved up to 79% with acceptable turbidity (32.21 NTU), clarity (74.39 %T), polyphenol content (115.31 mg GAE/g), and protein content (102.43 mg/g). The juice so obtained was clarified and concentrated using micro-filtration, ultra-filtration and nano-filtration. Primary clarification of juice by micro-filtration with a pressure of 137.89 kPa and membrane pore size of 0.45 μm had better results in terms of clarity, turbidity, colour and protein concentration, than centrifugation at 7000 rpm and 40 min. There was decline in permeate flux after 130 min of micro-filtration due to the presence of macromolecules and fibre particles in the juice. Fouling of the membrane was also observed due to cake layer resistance (65%). Membranes could be reuse up to 82% after CIP treatment. Secondary clarification of the juice was done by ultra-filtration with optimised membrane pore size (50 kDa) and pressure (137.89 kPa). Juice recovery after ultra-filtration was 60.46% with acceptable turbidity (0.03 NTU), clarity (96.33 %T), polyphenol content (125.74 mg GAE/g) and protein content (109.43 mg/g). Storage stability and quality of the ultra-filtered juice were compared with the juices obtained from enzymatic extraction, centrifugation, and micro-filtration. Ultra-filtered juice had prolonged shelf life (8 weeks) with acceptable qualities. The juice thus obtained from ultra-filtration was further concentrated for bioactive molecules by nanofiltration with a membrane pore size of 300 Da and pressure 2.5 mPa. Protein, polyphenol and antioxidants of the concentrated Jamun juice were quantified by UV-Spectrophotometer. Particle size distribution was measured by zeta-sizer. Anthocyanidins (5.9 mg/10 mg of cyanidine chloride, 20.8 mg/10mg of malvidin chloride and 3.6 mg/10mg of delphinidin chloride) content was determined by RP-HPLC-PDA. Rejection rate of protein, polyphenol and antioxidant for ultra-filtered and nano-filtered permeates were 48%, 22.3%, 51% and 63%, 74%, 40% respectively. The particle size distribution curves for ultra-filtered and nano-filtered juice were parabolic confirming proper membrane filtration. Enzymatic extraction by Pectinase from Aspergillus aculeatus strain (44 oC, 80 min and 0.05%) followed by clarification with micro-filtration (137.89 kPa and 0.45 μm) and ultra-filtration (137.89 kPa and 50 kDa), and concentration through nano-filtration (2.5 mPa and 300 Da) could recover commercial grade clarified Jamun juice (604.6 ml/kg of pulp) and anthocynidins. Total cost for processing Rs. 173.18 /litre. The above processing protocol could be an alternative non-thermal method for fruit juice to concentrate natural colour pigment and bioactive molecules in beverage and pharmaceutical industries