COMPARATIVE ANALYSIS OF ANTI-INFLAMMATORY ACTIVITY OF AQUEOUS AND METHANOLIC EXTRACTS OF C. CASSIA AND C. ZEYLANICUM IN RAW264.7, SW1353 AND PRIMARY CHONDROCYTES

Objectives: The objective of this research was to compare the anti-inflammatory activity of aqueous and methanolic extracts of C. cassia (CC) and C. zeylanicum (CZ) in mouse macrophage (RAW264.7) and human chondrosarcoma (SW1353) cell lines as well as in human primary chondrocytes, to correlate their efficacy in management of osteoarthritis (OA) related pathophysiology.Methods: RAW264.7, SW1353 and human primary chondrocytes were pre-treated with aqueous extracts of C. cassia (CCW) and C. zeylanicum (CZW) and methanolic extracts of C. cassia (CCM) and C. zeylanicum (CZM) at various concentrations (0.1-100 µg/ml) for 1 h, followed by stimulation with LPS and IL-1β, respectively. The effect of CCM, CCW, CZM and CZW on the production of nitric oxide (NO) was evaluated by Griess reaction. Evaluation of prostaglandin E2 (PGE2) and leukotriene (LTB4) proteins was performed by EIA-Monoclonal based kits. The effect of these extracts on matrix metalloproteinase (MMPs-2, 9 and 13) levels was analyzed by SensoLyte® fluorimetric MMP assay kit.Results: The methanolic extracts (CCM, CZM) of both the varieties of cinnamon were found to be more effective than the aqueous extracts in terms of PGE2, LTB4 and MMP inhibition.We found that in RAW 264.7, CCM and CZM decreased NO and PGE2 production by45.40%±8.6; 65.63%±5.7 and 79.88%±1.2; 95.91%±0.3, respectively. Similarly, in SW1353 and chondrocytes, CCM decreased PGE2 production by 68.8%±6.4;36.1%±9.5, respectively whereas CZM reduced PGE2 production by 70.2%±2.3; 52.3%±5.4, respectively. Moreover, in SW1353 and chondrocytes CCM decreased LTB4 production by 85.47%±3.03; 99.6%±0.2, respectively whereas CZM reduced LTB4 production by 67.5%±5.6; 75.6%±1.2, respectively. In chondrocytes both CCM and CZM significantly reduced the levels of MMP-2(55.7%±5.2; 73.1%±7.1), MMP-9 (57.5%±4.7; 74.5%±5.2) and MMP-13 (90.1%±2.6; 71.2%±12.5), respectively. However, on comparing the two species of cinnamon, C. zeylanicumwas found to be more effective than C. cassia andthus could be considered for its potential therapeutic application in the management of inflammatory conditions associated with OA.Conclusion: The present study would help in choosing better of the two species of cinnamon for their possible therapeutic application in the management of inflammatory condition associated with OA.Â

Operational Probabilistic Fog Prediction Based on Ensemble Forecast System: A Decision Support System for Fog

One of the well-known challenges of fog forecasting is the high spatio-temporal variability of fog. An ensemble forecast aims to capture this variability by representing the uncertainty in the initial/lateral boundary conditions (ICs/BCs) and model physics. The present study highlights a new operational Ensemble Forecast System (EFS) developed by the Indian Institute of Tropical Meteorology (IITM), Pune, to predict the fog over the Indo-Gangetic Plain (IGP) region using the visibility (Vis) diagnostic algorithm. The EFS framework comprises the WRF model with a 4 km horizontal resolution, initialized by 21 ICs/BCs. The advantages of probabilistic fog forecasting have been demonstrated by comparing control (CNTL) and ensemble-based fog forecasts. The forecast is verified using fog observations from the Indira Gandhi International (IGI) airport during the winter months of 2020–2021 and 2021–2022. The results show that with a probability threshold of 50%, the ensemble forecasts perform better than the CNTL forecasts. The skill scores of EFS are relatively promising, with a Hit Rate of 0.95 and a Critical Success Index of 0.55; additionally, the False Alarm Rate and Missing Rate are low, with values of 0.43 and 0.04, respectively. The EFS could correctly predict more fog events (37 out of 39) compared with the CNTL forecast (31 out of 39) and shows the potential skill. Furthermore, EFS has a substantially reduced error in predicting fog onset and dissipation (mean onset and dissipation error of 1 h each) compared to the CNTL forecasts

Operational Probabilistic Fog Prediction Based on Ensemble Forecast System: A Decision Support System for Fog

One of the well-known challenges of fog forecasting is the high spatio-temporal variability of fog. An ensemble forecast aims to capture this variability by representing the uncertainty in the initial/lateral boundary conditions (ICs/BCs) and model physics. The present study highlights a new operational Ensemble Forecast System (EFS) developed by the Indian Institute of Tropical Meteorology (IITM), Pune, to predict the fog over the Indo-Gangetic Plain (IGP) region using the visibility (Vis) diagnostic algorithm. The EFS framework comprises the WRF model with a 4 km horizontal resolution, initialized by 21 ICs/BCs. The advantages of probabilistic fog forecasting have been demonstrated by comparing control (CNTL) and ensemble-based fog forecasts. The forecast is verified using fog observations from the Indira Gandhi International (IGI) airport during the winter months of 2020–2021 and 2021–2022. The results show that with a probability threshold of 50%, the ensemble forecasts perform better than the CNTL forecasts. The skill scores of EFS are relatively promising, with a Hit Rate of 0.95 and a Critical Success Index of 0.55; additionally, the False Alarm Rate and Missing Rate are low, with values of 0.43 and 0.04, respectively. The EFS could correctly predict more fog events (37 out of 39) compared with the CNTL forecast (31 out of 39) and shows the potential skill. Furthermore, EFS has a substantially reduced error in predicting fog onset and dissipation (mean onset and dissipation error of 1 h each) compared to the CNTL forecasts

An Environmentally Sustainable Mechanochemical Route to Hydroxamic Acid Derivatives

An operationally simple, and cost efficient conversion of carboxylic acids into hydroxamic acid derivatives via a high-energy mechanochemical activation is presented. This ball milling methodology was applied to a wide variety of carboxylic acids dramatically improving purification issues associated with this class of molecules, which still remain one of the main bottlenecks of classical methodologies. (Figure presented.)