Two Distinct Modes of Hypoosmotic Medium-Induced Release of Excitatory Amino Acids and Taurine in the Rat Brain In Vivo

A variety of physiological and pathological factors induce cellular swelling in the brain. Changes in cell volume activate several types of ion channels, which mediate the release of inorganic and organic osmolytes and allow for compensatory cell volume decrease. Volume-regulated anion channels (VRAC) are thought to be responsible for the release of some of organic osmolytes, including the excitatory neurotransmitters glutamate and aspartate. In the present study, we compared the in vivo properties of the swelling-activated release of glutamate, aspartate, and another major brain osmolyte taurine. Cell swelling was induced by perfusion of hypoosmotic (low [NaCl]) medium via a microdialysis probe placed in the rat cortex. The hypoosmotic medium produced several-fold increases in the extracellular levels of glutamate, aspartate and taurine. However, the release of the excitatory amino acids differed from the release of taurine in several respects including: (i) kinetic properties, (ii) sensitivity to isoosmotic changes in [NaCl], and (iii) sensitivity to hydrogen peroxide, which is known to modulate VRAC. Consistent with the involvement of VRAC, hypoosmotic medium-induced release of the excitatory amino acids was inhibited by the anion channel blocker DNDS, but not by the glutamate transporter inhibitor TBOA or Cd2+, which inhibits exocytosis. In order to elucidate the mechanisms contributing to taurine release, we studied its release properties in cultured astrocytes and cortical synaptosomes. Similarities between the results obtained in vivo and in synaptosomes suggest that the swelling-activated release of taurine in vivo may be of neuronal origin. Taken together, our findings indicate that different transport mechanisms and/or distinct cellular sources mediate hypoosmotic medium-induced release of the excitatory amino acids and taurine in vivo

Changes in snow cover dynamics over the Indus Basin: evidences from 2008 to 2018 MODIS NDSI trends analysis

The frozen water reserves on the Earth are not only very dynamic in their nature, but also have significant effects on hydrological response of complex and dynamic river basins. The Indus basin is one of the most complex river basins in the world and receives most of its share from the Asian Water Tower (Himalayas). In such a huge river basin with high-altitude mountains, the regular quantification of snow cover is a great challenge to researchers for the management of downstream ecosystems. In this study, Moderate Resolution Imaging Spectroradiometer (MODIS) daily (MOD09GA) and 8-day (MOD09A1) products were used for the spatiotemporal quantification of snow cover over the Indus basin and the western rivers’ catchments from 2008 to 2018. The high-resolution Landsat Enhanced Thematic Mapper Plus (ETM+) was used as a standard product with a minimum Normalized Difference Snow Index (NDSI) threshold (0.4) to delineate the snow cover for 120 scenes over the Indus basin on different days. All types of errors of commission/omission were masked out using water, sand, cloud, and forest masks at different spatiotemporal resolutions. The snow cover comparison of MODIS products with Landsat ETM+, in situ snow data and Google Earth imagery indicated that the minimum NDSI threshold of 0.34 fits well compared to the globally accepted threshold of 0.4 due to the coarser resolution of MODIS products. The intercomparison of the time series snow cover area of MODIS products indicated R2 values of 0.96, 0.95, 0.97, 0.96 and 0.98, for the Chenab, Jhelum, Indus and eastern rivers’ catchments and Indus basin, respectively. A linear least squares regression analysis of the snow cover area of the Indus basin indicated a declining trend of about 3358 and 2459 km2 per year for MOD09A1 and MOD09GA products, respectively. The results also revealed a decrease in snow cover area over all the parts of the Indus basin and its sub-catchments. Our results suggest that MODIS time series NDSI analysis is a useful technique to estimate snow cover over the mountainous areas of complex river basins

Flood Mitigation in the Transboundary Chenab River Basin: A Basin-Wise Approach from Flood Forecasting to Management

Rapid and reliable flood information is crucial for minimizing post-event catastrophes in the complex river basins of the world. The Chenab River basin is one of the complex river basins of the world, facing adverse hydrometeorological conditions with unpredictable hydrologic response. Resultantly, many vicinities along the river undergo destructive inundation, resulting in huge life and economic losses. In this study, Hydrologic Engineering Centre–Hydrologic Modeling System (HEC-HMS) and HEC–River Analysis System (HEC-RAS) models were used for flood forecasting and inundation modeling of the Chenab River basin. The HEC-HMS model was used for peak flow simulation of 2014 flood event using Global Precipitation Mission (GMP) Integrated Multisatellite Retrievals-Final (IMERG-F), Tropical Rainfall Measuring Mission_Real Time (TRMM_3B42RT), and Global Satellite Mapping of Precipitation_Near Real Time (GSMaP_NRT) precipitation products. The calibration and validation of the HEC-RAS model were carried out for flood events of 1992 and 2014, respectively. The comparison of observed and simulated flow at the outlet indicated that IMERG-F has good peak flow simulation results. The simulated inundation extent revealed an overall accuracy of more than 90% when compared with satellite imagery. The HEC-RAS model performed well at Manning’s n of 0.06 for the river and the floodplain. From the results, it can be concluded that remote sensing integrated with HEC-HMS and HEC-RAS models could be one of the workable solutions for flood forecasting, inundation modeling, and early warning. The concept of integrated flood management (IFM) has also been translated into practical implementation for joint Indo-Pak management for flood mitigation in the transboundary Chenab River basin

Mechanism and Predictors of Failed Transradial Approach for Percutaneous Coronary Interventions

ObjectivesThe study aimed to determine the mechanism and predictors of procedural failure in patients undergoing percutaneous coronary intervention (PCI) from the transradial approach (TR).BackgroundTransradial approach PCI reduces vascular complications compared with a transfemoral approach (TF). However, the mechanism and predictors of TR-PCI failure have not been well-characterized.MethodsThe study population consisted of patients undergoing TR-PCI by low-to-intermediate volume operators with traditional TF guide catheters. Baseline characteristics, procedure details, and clinical outcomes were prospectively collected. Univariate and multivariate analyses were performed to determine independent predictors of TR-PCI failure.ResultsA total of 2,100 patients underwent TR-PCI and represented 38% of PCI volume. Mean age was 64 ± 12 years, and 17% were female. Vascular complications occurred in 22 (1%), and TR-PCI failure was observed in 98 (4.7%) patients. The mechanism of TR-PCI failure included inability to advance guide catheter to ascending aorta in 50 (51%), inadequate guide catheter support in 35 (36%), and unsuccessful radial artery puncture in 13 (13%) patients. The PCI was successful in 94 (96%) patients with TR-PCI failure by switching to TF. On multivariate analysis, age >75 years (odds ratio [OR]: 3.86; 95% confidence interval [CI]: 2.33 to 6.40, p = 0.0006), prior coronary artery bypass graft surgery (OR: 7.47; 95% CI: 3.45 to 16.19, p = 0.0002), and height (OR: 0.97; 95% CI: 0.95 to 0.99, p = 0.02) were independent predictors of TR-PCI failure.ConclusionsTransradial approach PCI can be performed by low-to-intermediate volume operators with standard equipment with a low failure rate. Age >75 years, prior coronary artery bypass graft surgery, and short stature are independent predictors of TR-PCI failure. Appropriate patient selection and careful risk assessment are needed to maximize benefits offered by TR-PCI

Estimation of Potential Soil Erosion and Sediment Yield: A Case Study of the Transboundary Chenab River Catchment

Near real-time estimation of soil loss from river catchments is crucial for minimizing environmental degradation of complex river basins. The Chenab river is one of the most complex river basins of the world and is facing severe soil loss due to extreme hydrometeorological conditions, unpredictable hydrologic response, and complex orography. Resultantly, huge soil erosion and sediment yield (SY) not only cause irreversible environmental degradation in the Chenab river catchment but also deteriorate the downstream water resources. In this study, potential soil erosion (PSE) is estimated from the transboundary Chenab river catchment using the Revised Universal Soil Loss Equation (RUSLE), coupled with remote sensing (RS) and geographic information system (GIS). Land Use of the European Space Agency (ESA), Climate Hazards Group InfraRed Precipitation with Station (CHIRPS) data, and world soil map of Food and Agriculture Organization (FAO)/The United Nations Educational, Scientific and Cultural Organization were incorporated into the study. The SY was estimated on monthly, quarterly, seasonal, and annual time-scales using sediment delivery ratio (SDR) estimated through the area, slope, and curve number (CN)-based approaches. The 30-year average PSE from the Chenab river catchment was estimated as 177.8, 61.5, 310.3, 39.5, 26.9, 47.1, and 99.1 tons/ha for annual, rabi, kharif, fall, winter, spring, and summer time scales, respectively. The 30-year average annual SY from the Chenab river catchment was estimated as 4.086, 6.163, and 7.502 million tons based on area, slope, and CN approaches. The time series trends analysis of SY indicated an increase of 0.0895, 0.1387, and 0.1698 million tons per year for area, slope, and CN-based approaches, respectively. It is recommended that the areas, except for slight erosion intensity, should be focused on framing strategies for control and mitigation of soil erosion in the Chenab river catchment.Water Resource