8,004 research outputs found

    Screening of chemically defined basal and feed media formulations for IgM production

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    Floral induction in a photoperiodically insensitive duckweed, Lemna paucicostata LP6

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    The effects of 20 amino acids and two amides were studied on the flowering of a photoperiodically insensitive duckweed, Lemna paucicostata LP6. Alanine, asparagine, aspartate, cystine, glutamate, glutamine, glycine, lysine, methionine, proline, serine, and threonine induced flowering under a photoperiodic regime of 16 hours light and 8 hours darkness. Among these, glutamate and aspartate were found to be the most effective for flower induction. These acids could initiate flowering even at 5×10-7 molar level, though maximal flowering (about 80%) was obtained at 10-5 molar. Change in the photoperiodic schedule or the pH of the nutrient medium did not influence glutamate- or aspartate-induced flowering. The low concentrations at which glutamate and aspartate are effective suggests that they may have a regulatory role rather than simply acting as metabolites

    Intramuscular oxytocin 10 units versus intravenous methylergometrine 0.2 mg in active management of third stage of labour for prevention of postpartum haemorrhage: a comparative study

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    Background: To compare the effectiveness of 10 IU of oxytocin IM with 0.2 mg methyl ergometrine IV in the prevention of post-partum hemorrhage when used as a part of active management of third stage of labour. This study aims to compare their influence on duration of the third stage of labour, the amount of blood loss during the third stage of labour and the immediate post-partum period and side effects of the drugs if any.Methods: The study was conducted in a tertiary care teaching hospital. 200 women, who underwent normal delivery with or without episiotomy, were enrolled and were randomly distributed into two groups. 100 women received 10 IU of intramuscular Oxytocin and 100 women received intravenous 0.2 mg of methyl ergometrine. Women of both the groups were given the medication after delivery of anterior shoulder of the baby. Comparison done between percentages fall in Hb from before delivery to 24 hours after delivery, need for additional uterotonic agents, need for blood transfusion, duration of third stage of labour and any side effects including retained placenta and need for manual removal of placenta.Results: Intravenous methylergometrine was observed to be equally effective as intramuscular oxytocin in prevention of post-partum hemorrhage. There was no difference in the duration of third stage of labour, amount of blood loss, need for additional uterotonic agents, and need for blood transfusion in both the groups. There was no significant side effect in both the groups.Conclusions: Intramuscular oxytocin is as efficacious as Intravenous methylergometrine in the prevention of postpartum hemorrhage with no side effects

    Deciphering the role of innate immune NF-ĸB pathway in pancreatic cancer

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    Pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal cancers with no effective treatment option. A predominant hallmark of PDAC is the intense fibro-inflammatory stroma which not only physically collapses vasculature but also functionally suppresses anti-tumor immunity. Constitutive and induced activation of the NF-κB transcription factors is a major mechanism that drives inflammation in PDAC. While targeting this pathway is widely supported as a promising therapeutic strategy, clinical success is elusive due to a lack of safe and effective anti-NF-κB pathway therapeutics. Furthermore, the cell type-specific contribution of this pathway, specifically in neoplastic cells, stromal fibroblasts, and immune cells, has not been critically appraised. In this article, we highlighted seminal and recent literature on molecular mechanisms that drive NF-κB activity in each of these major cell types in PDAC, focusing specifically on the innate immune Toll-like/IL-1 receptor pathway. We reviewed recent evidence on the signaling interplay between the NF-κB and oncogenic KRAS signaling pathways in PDAC cells and their collective contribution to cancer inflammation. Lastly, we reviewed clinical trials on agents that target the NF-κB pathway and novel therapeutic strategies that have been proposed in preclinical studies

    Environmental factors influencing aphid transmission of potato virus Y and potato leafroll virus

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    The effect of temperature, relative humidity (RH) and light on aphid transmission of potato virus Y (PVY) and potato leafroll virus (PLRV) was studied using as vectors Myzus persicae Sulz. and Aphis gossypii Glov. Host susceptibility was enhanced by 48 h pre-inoculation exposure at 25°C and by 48 h post-inoculation exposure to 30°C. High RH (80%) in both pre- or postinoculation phases enhanced host susceptibility. Continuous fluorescent light (4000 lux) did not alter the rate of transmission of either virus. High RH (80-90%) and high temperature (25-30°C), when combined, increased virus transmission by 30-35%. Transmission rates were reduced by nearly 50% if RH was maintained at 50% in either of the two phases even if the temperature was 25 or 30°C. Both viruses were acquired by aphids earlier (13-20 days after inoculation) when the source plants were incubated at 25 or 30°C. Most virus was transmitted from plants inoculated with PVY 13 to 16 days and with PLRV 15 to 20 days previously. Transmission rates of PVY were enumerated from symptom expression on test plants and by Enzyme Linked Immunosorbent Assay (ELISA) whereas those of PLRV were enumerated from symptom expression alone

    Modeling the Enceladus plume--plasma interaction

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    We investigate the chemical interaction between Saturn's corotating plasma and Enceladus' volcanic plumes. We evolve plasma as it passes through a prescribed H2O plume using a physical chemistry model adapted for water-group reactions. The flow field is assumed to be that of a plasma around an electrically-conducting obstacle centered on Enceladus and aligned with Saturn's magnetic field, consistent with Cassini magnetometer data. We explore the effects on the physical chemistry due to: (1) a small population of hot electrons; (2) a plasma flow decelerated in response to the pickup of fresh ions; (3) the source rate of neutral H2O. The model confirms that charge exchange dominates the local chemistry and that H3O+ dominates the water-group composition downstream of the Enceladus plumes. We also find that the amount of fresh pickup ions depends heavily on both the neutral source strength and on the presence of a persistent population of hot electrons.Comment: 10 pages, 1 table, 2 figure

    The far-ultraviolet main auroral emission at Jupiter - Part 1:dawn-dusk brightness asymmetries

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    The main auroral emission at Jupiter generally appears as a quasi-closed curtain centered around the magnetic pole. This auroral feature, which accounts for approximately half of the total power emitted by the aurorae in the ultraviolet range, is related to corotation enforcement currents in the middle magnetosphere. Early models for these currents assumed axisymmetry, but significant local time variability is obvious on any image of the Jovian aurorae. Here we use far-UV images from the Hubble Space Telescope to further characterize these variations on a statistical basis. We show that the dusk side sector is ~ 3 times brighter than the dawn side in the southern hemisphere and ~ 1.1 brighter in the northern hemisphere, where the magnetic anomaly complicates the interpretation of the measurements. We suggest that such an asymmetry between the dawn and the dusk sectors could be the result of a partial ring current in the nightside magnetosphere

    The far-ultraviolet main auroral emission at Jupiter – Part 2:vertical emission profile

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    The aurorae at Jupiter are made up of many different features associated with a variety of generation mechanisms. The main auroral emission, also known as the main oval, is the most prominent of them as it accounts for approximately half of the total power emitted by the aurorae in the ultraviolet range. The energy of the precipitating electrons is a crucial parameter to characterize the processes at play which give rise to these auroral emissions, and the altitude of the emissions directly depends on this energy. Here we make use of far-UV (FUV) images acquired with the Advanced Camera for Surveys on board the Hubble Space Telescope and spectra acquired with the Space Telescope Imaging Spectrograph to measure the vertical profile of the main emissions. The altitude of the brightness peak as seen above the limb is ~ 400 km, which is significantly higher than the 250 km measured in the post-dusk sector by Galileo in the visible domain. However, a detailed analysis of the effect of hydrocarbon absorption, including both simulations and FUV spectral observations, indicates that FUV apparent vertical profiles should be considered with caution, as these observations are not incompatible with an emission peak located at 250 km. The analysis also calls for spectral observations to be carried out with an optimized geometry in order to remove observational ambiguities

    AFMB-Net: DeepFake Detection Network Using Heart Rate Analysis

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    With advances in deepfake generating technology, it is getting increasingly difficult to detect deepfakes. Deepfakes can be used for many malpractices such as blackmail, politics, social media, etc. These can lead to widespread misinformation and can be harmful to an individual or an institution’s reputation. It has become important to be able to identify deepfakes effectively, while there exist many machine learning techniques to identify them, these methods are not able to cope up with the rapidly improving GAN technology which is used to generate deepfakes. Our project aims to identify deepfakes successfully using machine learning along with Heart Rate Analysis. The heart rate identified by our model is unique to each individual and cannot be spoofed or imitated by a GAN and is thus susceptible to improving GAN technology. To solve the deepfake detection problem we employ various machine learning models along with heart rate analysis to detect deepfakes
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