Formulation and Development of Flurbiprofen Colon-Specific Eudragit Coated Matrix Tablets: Use of a Novel Crude Banana Peel Powder as a Time-Dependent Polymer.

The rationale for the current investigation is to study the crude banana peel (CBP) powder efficiency as a novel natural time-dependent polymer along with a pH-sensitive polymer to develop flurbiprofen colon-specific tablets. The direct compression method is utilized to prepare the flurbiprofen-CBP matrix tablets using 9 mm punches on the rotary tableting machine and subsequently coated with Eudragit® S 100 by a dip coating method. The tablets were evaluated for various tableting properties and in vitro drug release studies. From the results of dissolution studies, the F6 formulation showed negligible drug release (5.76% in 5 h) in the upper gastrointestinal tract and progressive release in the colon (99.08% in 24 h). Mean dissolution time, T10%, and T80% were found to be 13.33 h, 5.8 h, and 20.7 h, respectively, which explains the efficiency of the present combination of polymers for colon-specific drug release. From the dissolution studies results of stability studies, the similarity index was calculated and found to be 74.75. In conclusion, utilizing CBP as a natural, time-dependent polymer in conjunction with Eudragit® S 100 to develop the flurbiprofen tablets seems like a promising approach for delivering drugs specifically to the colon.

Evaluation of multiple satellite precipitation products for rainfed maize production systems over Vietnam.

High-resolution reliable rainfall datasets are vital for agricultural, hydrological, and weather-related applications. The accuracy of satellite estimates has a significant effect on simulation models in particular crop simulation models, which are highly sensitive to rainfall amounts, distribution, and intensity. In this study, we evaluated five widely used operational satellite rainfall estimates: CHIRP, CHIRPS, CPC, CMORPH, and GSMaP. These products are evaluated by comparing with the latest improved Vietnam-gridded rainfall data to determine their suitability for use in impact assessment models. CHIRP/S products are significantly better than CMORPH, CPC, and GsMAP with higher skill, low bias, showing a high correlation coefficient with observed data, and low mean absolute error and root mean square error. The rainfall detection ability of these products shows that CHIRP outperforms the other products with a high probability of detection (POD) scores. The performance of the different rainfall datasets in simulating maize yields across Vietnam shows that VnGP and CHIRP/S were capable of producing good estimates of average maize yields with RMSE ranging from 536 kg/ha (VnGP), 715 kg/ha (CHIRPS), 737 kg/ha (CHIRP), 759 kg/ha (GsMAP), 878 kg/ha (CMORPH) to 949 kg/ha (CPC). We illustrated that there is a potential for use of satellite rainfall estimates to overcome the issues of data scarcity in regions with sparse rain gauges.

Simulating adaptation strategies to offset potential impacts of climate variability and change on maize yields in Embu County, Kenya.

In this study, we assessed the possible impacts of climate variability and change on growth and performance of maize using multi-climate, multi-crop model approaches built on Agricultural Model Intercomparison and Improvement Project (AgMIP) protocols in five different agro-ecological zones (AEZs) of Embu County in Kenya and under different management systems. Adaptation strategies were developed that are locally relevant by identifying a set of technologies that help to offset potential impacts of climate change on maize yields. Impacts and adaptation options were evaluated using projections by 20 Coupled Model Intercomparison Project-Phase 5 (CMIP5) climate models under two representative concentration pathways (RCPs) 4.5 and 8.5. Two widely used crop simulation models, Agricultural Production Systems Simulator (APSIM) and Decision Support System for Agrotechnology Transfer (DSSAT) was used to simulate the potential impacts of climate change on maize. Results showed that 20 CMIP5 models are consistent in their projections of increased surface temperatures with different magnitude. Projections by HadGEM2-CC, HadGEM2-ES, and MIROC-ESM tend to be higher than the rest of 17 CMIP5 climate models under both emission scenarios. The projected increase in minimum temperature (Tmin) which ranged between 2.7 and 5.8°C is higher than the increase in maximum temperature (Tmax) that varied between 2.2 and 4.8°C by end century under RCP 8.5. Future projections in rainfall are less certain with high variability projections by GFDL-ESM2G, MIROC5, and NorESM1-M suggest 8 to 25% decline in rainfall, while CanESM2, IPSL-CM5A-MR and BNU-ESM suggested more than 85% increase in rainfall under RCP 8.5 by end of 21st century. Impacts of current and future climatic conditions on maize yields varied depending on the AEZs, soil type, crop management and climate change scenario. Impacts are largely negative in the low potential AEZs such as Lower Midlands (LM4 and LM5) compared with the high potential AEZs Upper Midlands (UM2 and UM3). However, impacts of climate change are largely positive across all AEZs and management conditions when CO2 fertilization is included. Using the differential impacts of climate change, a strategy to adapt maize cultivation to climate change in all the five AEZs was identified by consolidating those practices that contributed to increased yields under climate change. We consider this approach as more appropriate to identify operational adaptation strategies using readily available technologies that contribute positively under both current and future climatic conditions. This approach when adopted in strategic manner will also contribute to further strengthen the development of adaptation strategies at national and local levels. The methods and tools validated and applied in this assessment allowed estimating possible impacts of climate change and adaptation strategies which can provide valuable insights and guidance for adaptation planning.

Neuroprotective effects of 1`δ-1`-acetoxyeugenol acetate on Aß(25-35) induced cognitive dysfunction in mice.

The progressive accumulation of amyloid beta (Aß) peptide is neurotoxic and leads to Alzheimer's type dementia. Accumulation of Aß has been associated with dysfunction of hypothalamic-pituitary-adrenal (HPA) axis and elevated pro-inflammatory cytokines. In this study, we investigated the effect of 1`δ-1`-acetoxyeugenol acetate (DAEA), isolated from Alpinia galanga (L.), on Aß(25-35) induced neurodegeneration in mice. Mice were treated with three different doses of DAEA (12.5 mg/kg, 25 mg/kg and 50 mg/kg) for 28 days. Aß(25-35) was injected by intracerebroventricular (i.c.v.) injection on the 15th day of 28 days. Open field, water maze and step-down inhibitory tests were performed on the 27th day to determine the habituation memory, spatial learning, and short- and long-term memory, respectively. Acetylcholinesterase (AChE), Corticosterone, biogenic amines (serotonin and dopamine), tumour necrosis factor-α (TNF-α), and antioxidant parameters such as superoxide dismutase, catalase, glutathione peroxidase and vitamin C were evaluated in brain homogenates after behavioural tests to ascertain the cognitive improvement through neuro-immune-endocrine modulation. The DAEA treatment with 25 mg/kg and 50 mg/kg resulted in significant (p < 0.001) improvement of habituation memory and step-down inhibitory avoidance task. In spatial learning, the cognitive improvement was significantly improved (p < 0.001) by reduction in escape latency. In the biochemical study, the significant (p < 0.001) reduction of AChE indicates the preeminent neuroprotection. Corticosterone and TNF-α were significantly (p < 0.01) reduced and biogenic amines were increased with antioxidant markers, which signify the potential influence of DAEA on neuroprotection. Our investigation revealed that the drug DAEA attenuates stress mediated through the HPA axis and regulates the neuroendocrine and neuroimmune function to improve the cognition. DAEA could be a potential lead candidate for the treatment of neurodegeneration.

Minor pregnanes from Caralluma adscendens var. gracilis and Caralluma pauciflora.

Phytochemical investigation of Caralluma adscendens var. gracilis and Caralluma pauciflora (Asclepiadaceae) whole plant extracts allowed to isolate one pregnane glycoside and two pregnanes characterized as 12ß,20-O-dibenzoyl-5α,6-dihydrosarcostin ß-oleandropyranosyl-(1→4)-ß-cymaropyranosyl-(1→4)-ß-digitoxypyranosyl-(1→4)-ß-cymaropyranosyl-(1→4)-ß-cymaropyranoside (1), 12ß-O-benzoyl-3ß,11α,14ß,20R-pentahydroxy-pregn-5-ene (2), and 11α-O-benzoyl-3ß,12ß,14ß,20R-pentahydroxy-pregn-5-ene (3), respectively. Their structural characterization was obtained on the basis of extensive NMR spectral studies. Three known pregnane glycosides along with lupeol and ß-sitosterol were also isolated and characterized.

Pregnane glycosides from Caralluma adscendens var. fimbriata.

Eleven novel pregnane glycosides, 2-7 and 9-13, of which four, i.e., 10-13, comprised a new pregnane-type genin exhibiting a hydroxymethylene instead of a Me group at C(19), and the known pregnane glycoside stalagmoside V (8) were isolated from whole plants of Caralluma adscendens var. fimbriata, a native Indian succulent plant. Their structures were elucidated by extensive 2D-NMR spectroscopic studies.