Status of Soil Fertility in a Community Forest of Nepal

Soil is a complex mixture of mineral nutrients, organic matter, water, air and living organisms. The primary nutrients for plant growth are organic matter, nitrogen, phosphorus and potassium. In order to find the status of pH, organic matter (C), total nitrogen (N), available phosphorus (P) and available potassium (K) in forest soil, the study was conducted in Ghwangkhola Sapaude Babiyabhir Community Forest in Putali Bazaar Municipality-8, Syangja, Nepal. Soil parameters are analyzed through different standard methods followed worldwide by many soil scientists. Soil pH of sample in all three strata was slightly acidic and varies from 5.7 to 7.18. The carbon percentage was high and varies from 0.65% to 2.39%. The total nitrogen in soil was medium and varies from 0.09% to 0.12%. The concentration of available phosphorus in soil was high and varies from 73.71 kg/ha-93.23 kg/ha. The concentration of available potassium on soil was quiet low and varies from 2.54 kg/ha-4.23 kg/ha. Higher organic matter in the forest land indicate low activities of nitrogen losing process, which is due to the closed nutrient cycling and minimal disturbance in the natural forest system. So, addition of fertilizer rich in potassium and increasing pH is recommended to maintain potassium fertility and neutral pH in the forest soil

Targeting the hedgehog transcription factors GLI1 and GLI2 restores sensitivity to vemurafenib-resistant human melanoma cells

BRAF inhibitor (BRAFi) therapy for melanoma patients harboring the V600E mutation is initially highly effective, but almost all patients relapse within a few months. Understanding the molecular mechanisms underpinning BRAFi-based therapy is therefore an important issue. Here we identified a previously unsuspected mechanism of BRAFi resistance driven by elevated Hedgehog (Hh) pathway activation that is observed in a cohort of melanoma patients after vemurafenib treatment. Specifically, we demonstrate that melanoma cell lines, with acquired in vitro-induced vemurafenib resistance, show increased levels of glioma-associated oncogene homolog 1 and 2 (GLI1/GLI2) compared with naive cells. We also observed these findings in clinical melanoma specimens. Moreover, the increased expression of the transcription factors GLI1/GLI2 was independent of canonical Hh signaling and was instead correlated with the noncanonical Hh pathway, involving TGF beta/SMAD (transforming growth factor-beta/Sma- and Mad-related family) signaling. Knockdown of GLI1 and GLI2 restored sensitivity to vemurafenib-resistant cells, an effect associated with both growth arrest and senescence. Treatment of vemurafenib-resistant cells with the GLI1/GLI2 inhibitor Gant61 led to decreased invasion of the melanoma cells in a three-dimensional skin reconstruct model and was associated with a decrease in metalloproteinase (MMP2/MMP9) expression and microphthalmia transcription factor upregulation. Gant61 monotherapy did not alter the drug sensitivity of naive cells, but could reverse the resistance of melanoma cells chronically treated with vemurafenib. We further noted that alternating dosing schedules of Gant61 and vemurafenib prevented the onset of BRAFi resistance, suggesting that this could be a potential therapeutic strategy for the prevention of therapeutic escape. Our results suggest that targeting the Hh pathway in BRAFi-resistant melanoma may represent a viable therapeutic strategy to restore vemurafenib sensitivity, reducing or even inhibiting the acquired chemoresistance in melanoma patients.Fapesp-grant number 2012/04194-1, 2013/05172-4, 2014/24400-0 and 2015/10821-7, CNPq-grant number 150447/2013-2 and 471512/2013-3 and PRODOC-grant no 3193-32/2010. Work in the lab of KS Smalley was supported by the National Institutes of Health grants R01 CA161107, R21 CA198550, and Skin SPORE grant P50 CA168536info:eu-repo/semantics/publishedVersio

Spatiotemporal Analysis of Land Cover and the Effects on Ecosystem Service Values in Rupandehi, Nepal from 2005 to 2020

Land cover (LC) is a crucial parameter for studying environmental phenomena. Cutting-edge technology such as remote sensing (RS) and cloud computing have made LC change mapping efficient. In this study, the LC of Rupandehi District of Nepal were mapped using Landsat imagery and Random Forest (RF) classifier from 2005 to 2020 using Google Earth Engine (GEE) platform. GEE eases the way in extracting, analyzing, and performing different operations for the earth’s observed data. Land cover classification, Centre of gravity (CoG), and their trajectories for all LC classes: agriculture, built-up, water, forest, and barren area were extracted with five-year intervals, along with their Ecosystem service values (ESV) to understand the load on the ecosystem. We also discussed the aspects and problems of the spatiotemporal analysis of developing regions. It was observed that the built-up areas had been increasing over the years and more centered in between the two major cities. Other agriculture, water, and forest classes had been subjected to fluctuations with barren land in the decreasing trend. This alteration in the area of the LC classes also resulted in varying ESVs for individual land cover and total values for the years. The accuracy for the RF classifier was under substantial agreement for such fragmented LCs. Using LC, CoG, and ESV, the paper discusses the need for spatiotemporal analysis studies in Nepal to overcome the current limitations and later expansion to other regions. Studies such as these help in implementing proper plans and strategies by district administration offices and local governmental bodies to stop the exploitation of resources