19 research outputs found
Geology and geochemistry of metabasalts of Shimoga schist belt, Dharwar Craton: implications for the late Archean basin development
Field, petrographic and geochemical characteristics of Sullya alkaline complex in the Cauvery Shear Zone (CSZ), southern India: Implications for petrogenesis
Significant, but volumetrically smaller, unmetamorphosed and largely undeformed alkaline magmatic suites have been reported from the Southern Granulite Terrain in southern India. These Neoproterozoic alkaline magmatic rocks occur as lenses, dykes and plugs that are mostly within, or proximal to, major shear zones or transcrustal faults. In this contribution, field, petrographic and whole-rock geochemical data of Sullya syenites and associated mafic granulites from the Mercara Shear Zone (MSZ), which separates low-grade (greenschist to upper amphibolite facies) Dharwar Craton and high-grade (granulite facies) Southern Granulite Terrain is presented. The isolated body of the Sullya syenite, similar to other alkaline plutons of the Southern Granulite Terrain, shows an intrusive relationship with the host hornblende-biotite gneisses and mafic granulites. The Sullya syenites lack macroscopic foliations and unlike, other plutons, they are not associated with carbonatites and ultrapotassic granites. Potash feldspar and plagioclase dominates the felsic phases in the Sullya syenite and there is negligible quartz. The studied syenites show evidence of melt supported deformation, but show no evidence of recrystallization. Geochemically, they most resemble the Angadimogar syenites (situated 3 km west of the Sullya syenites) with similar major oxide and trace element concentrations. The petrogenetic studies of the Sullya syenite have indicated that they were generated by mixing of two different sources derived from the partial melting of metasomatized continental mantle lithosphere and lower crustal mafic granulites. This melt source could have been emplaced in a rift-related tectonic setting. The emplacement is considered to be controlled by shears
Pre-clinical risk assessment and therapeutic potential of antitumor lipopeptide ‘Iturin A’ in an in vivo and in vitro model
Lipopeptides are versatile bio-active weapons having antifungal, antibacterial, antimycoplasma and anticancer properties. In this study, the therapeutic potential and safety assessment of a lipopeptide molecule ‘Iturin A’ were evaluated. Iturin A was found to inhibit in vivo tumor growth in a sarcoma 180 mouse xenograft model. The antitumor efficacy of Iturin A was correlated with increased DNA fragmentation and modulation of CD-31, Ki-67, P-Akt, P-MAPK, apoptotic and anti-apoptotic proteins. Further, safety assessment was carried out in Sprague Dawley rats by 28 days repeated dose (28 days) toxicity and a bio-distribution study. In the toxicity study, Iturin A (10, 20 and 50 mg per kg per day) was administered to the animals for 28 days. Another group was kept for another 14 days without drug exposure after 28 days of treatment to access the reversibility of the toxicity. At the end of the treatment, body weight, food and water intake, organ weight, motility, hematology, serum biochemistry and histopathology of the major organs were evaluated. The bio-distribution of Iturin A was also performed in plasma as well as in different major organs by a well-developed and validated administration of Iturin A radiolabeled with 99mTc. The in vitro cytotoxic effect of Iturin A was also evaluated in BRL-3A rat liver cells. In the treated groups, various toxicities were found in the liver and spleen. However, these adverse effects were transient and reversible after discontinuation of Iturin A treatment. In conclusion, this pre-clinical study offered a preliminary investigation regarding the efficacy and safety assessment of Iturin A
Automatic leukocyte nucleus segmentation by intuitionistic fuzzy divergence based thresholding
The paper proposes a robust approach to automatic segmentation of leukocyte‟s nucleus from microscopic blood smear images under normal as well as noisy environment by employing a new exponential intuitionistic fuzzy divergence based thresholding technique. The algorithm minimizes the divergence between the actual image and the ideally thresholded image to search for the final threshold. A new divergence formula based on exponential intuitionistic fuzzy entropy has been proposed. Further, to increase its noise handling capacity, a neighborhood-based membership function for the image pixels has been designed. The proposed scheme has been applied on 110 normal and 54 leukemia (chronic myelogenous leukemia) affected blood samples. The nucleus segmentation results have been validated by three expert haematologists. The algorithm achieves an average segmentation accuracy of 98.52% in noise-free environment. It beats the competitor algorithms in terms of several other metrics. The proposed scheme with neighborhood based membership function outperforms the competitor algorithms in terms of segmentation accuracy under noisy environment. It achieves 93.90% and 94.93% accuracies for Speckle and Gaussian noises respectively. The average area under the ROC curves comes out to be 0.9514 in noisy conditions, which proves the robustness of the proposed algorithm
The global, regional, and national burden of adult lip, oral, and pharyngeal cancer in 204 countries and territories:A systematic analysis for the Global Burden of Disease Study 2019
Importance Lip, oral, and pharyngeal cancers are important contributors to cancer burden worldwide, and a comprehensive evaluation of their burden globally, regionally, and nationally is crucial for effective policy planning.Objective To analyze the total and risk-attributable burden of lip and oral cavity cancer (LOC) and other pharyngeal cancer (OPC) for 204 countries and territories and by Socio-demographic Index (SDI) using 2019 Global Burden of Diseases, Injuries, and Risk Factors (GBD) Study estimates.Evidence Review The incidence, mortality, and disability-adjusted life years (DALYs) due to LOC and OPC from 1990 to 2019 were estimated using GBD 2019 methods. The GBD 2019 comparative risk assessment framework was used to estimate the proportion of deaths and DALYs for LOC and OPC attributable to smoking, tobacco, and alcohol consumption in 2019.Findings In 2019, 370 000 (95% uncertainty interval [UI], 338 000-401 000) cases and 199 000 (95% UI, 181 000-217 000) deaths for LOC and 167 000 (95% UI, 153 000-180 000) cases and 114 000 (95% UI, 103 000-126 000) deaths for OPC were estimated to occur globally, contributing 5.5 million (95% UI, 5.0-6.0 million) and 3.2 million (95% UI, 2.9-3.6 million) DALYs, respectively. From 1990 to 2019, low-middle and low SDI regions consistently showed the highest age-standardized mortality rates due to LOC and OPC, while the high SDI strata exhibited age-standardized incidence rates decreasing for LOC and increasing for OPC. Globally in 2019, smoking had the greatest contribution to risk-attributable OPC deaths for both sexes (55.8% [95% UI, 49.2%-62.0%] of all OPC deaths in male individuals and 17.4% [95% UI, 13.8%-21.2%] of all OPC deaths in female individuals). Smoking and alcohol both contributed to substantial LOC deaths globally among male individuals (42.3% [95% UI, 35.2%-48.6%] and 40.2% [95% UI, 33.3%-46.8%] of all risk-attributable cancer deaths, respectively), while chewing tobacco contributed to the greatest attributable LOC deaths among female individuals (27.6% [95% UI, 21.5%-33.8%]), driven by high risk-attributable burden in South and Southeast Asia.Conclusions and Relevance In this systematic analysis, disparities in LOC and OPC burden existed across the SDI spectrum, and a considerable percentage of burden was attributable to tobacco and alcohol use. These estimates can contribute to an understanding of the distribution and disparities in LOC and OPC burden globally and support cancer control planning efforts
Knowledge Gap and Safe Use of Pesticides by Vegetable Growers of Bihar, India
In this study, knowledge about pesticides and their safe use among vegetable growers of Purnea district was discussed. Data were collected from vegetable growers of Purnea district of Bihar. From the district, one block was purposively chosen. Three villages from one block, comprising of 50 respondents each were randomly chosen. The sample size was 150 vegetable growers. Frequency, percent, weighted mean and rank were used to analyze the data. It was found that majority of the respondents lack knowledge about banned pesticides and label on pesticide products. Finding discloses that there was lack of knowledge about proper disposal of pesticide and lack of knowledge about using protective clothing. Farmers’ age, educational level, experience has positive effects on safe use of pesticides in vegetable cultivation. Under such condition, there is need of extension agents in establishing rapport with farmers on regular basis can help in enhancing knowledge level about safe use of pesticides among vegetable growers
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Influence of mantra meditation on intensity mismatch negativity
Studies investigating the effects of focused attention (FA) meditation on mismatch negativity (MMN) have produced inconsistent and conflicting findings, highlighting the need for well-powered studies exploring different meditation styles to fully understand MMN modulation. Addressing methodological concerns from prior research, the current study specifically examines expertise in mantra meditation, a form of focused attention meditation, utilizing a sufficiently powered investigation with an intensity MMN paradigm. This paradigm incorporates both louder and quieter deviant stimuli to assess the impact of meditation expertise and to discern whether meditation-induced MMN effects reflect higher-order cognitive processes or result from sensory adaptation. While the results suggest a trend of higher MMN in novices compared to experts, statistical significance was not achieved. The modest effect observed is likely due to using novices as an active control group, benefiting from enhanced attention skills fostered by the repetitive speech and rhythmic nature inherent in mantra meditation. The consistent unidirectional polarity shift in event-related potential (ERP) responses to both types of deviant stimuli implies that intensity-related MMN effects may not solely depend on loudness-dependent modulation of sensory components but could signify higher-order deviance detection. Complementary findings from eLORETA source localization indicate consistent bilateral temporal and frontal cortex activity, with lower amplitudes observed in the expert mantra meditator group compared to novices
Automated Tissue Classification Framework for Reproducible Chronic Wound Assessment
The aim of this paper was to develop a computer assisted tissue classification (granulation, necrotic, and slough) scheme for chronic wound (CW) evaluation using medical image processing and statistical machine learning techniques. The red-green-blue (RGB) wound images grabbed by normal digital camera were first transformed into HSI (hue, saturation, and intensity) color space and subsequently the “S” component of HSI color channels was selected as it provided higher contrast. Wound areas from 6 different types of CW were segmented from whole images using fuzzy divergence based thresholding by minimizing edge ambiguity. A set of color and textural features describing granulation, necrotic, and slough tissues in the segmented wound area were extracted using various mathematical techniques. Finally, statistical learning algorithms, namely, Bayesian classification and support vector machine (SVM), were trained and tested for wound tissue classification in different CW images. The performance of the wound area segmentation protocol was further validated by ground truth images labeled by clinical experts. It was observed that SVM with 3rd order polynomial kernel provided the highest accuracies, that is, 86.94%, 90.47%, and 75.53%, for classifying granulation, slough, and necrotic tissues, respectively. The proposed automated tissue classification technique achieved the highest overall accuracy, that is, 87.61%, with highest kappa statistic value (0.793)