Tree rings of Rhododendron arboreum portray signal of monsoon precipitation in the Himalayan region

The Himalayas has a significant impact not just on the Indian subcontinent’s monsoon patterns but also on the global climate. Monsoon failure causing drought has become more common in recent years. As a result, it poses a major threat to ecosystem sustainability. We reported for the first time, a climatic-sensitive tree ring chronology of a broadleaf tree, Rhododendron arboreum, spanning 1732–2017 CE from the Himalayan region. We discovered that the climate during the monsoon season limits the growth of this tree in this region. The correlation analysis between tree ring chronology and climate revealed a significant positive relationship with precipitation (r = 0.63, p < 0.001) and a negative relationship with temperature (r = −0.48, p < 0.01) during the months of June–August (JJA). This strong relationship allowed us to reconstruct monsoon precipitation spanning 1780 to 2017 CE which explained 40% of the variance of the observed climate data for the calibration period. The reconstructed data are validated by the existence of a significant association with the gridded JJA precipitation data of the Climate Research Unit (CRU) of this region. The monsoon rainfall record captured extremely wet years during 1793, 1950, 2011, 2013, and 2017 and extremely dry years during 1812, 1833, 1996, 2002, 2004, and 2005. The extremely dry and wet years well coincided with major catastrophic historical and instrumental droughts and floods in the region. Furthermore, the reconstructed data are also validated by the significant positive correlation (r = 0.36, p < 0.001, n = 163) with the all Indian summer monsoon rainfall series. Such data will be useful to predict the incidence of future droughts, which can help to assess the vulnerability of the forest ecosystem to extreme events

Flood challenges and disaster risk reduction in the Indian Himalayan region

University of Cumbria Associate Professor Rich Johnson delivered a keynote presentation to the Royal Commonwealth Society (RCS), Bath & District Branch. Alongside placement graduates, he shared insights into the research team's expedition to the Indian Himalayan state of Uttarakhand earlier this year (2023). With Turing Scheme and RCS funding, and the partnership of the GB Pant National Institute of Himalayan Environment (GBP-NIHE), the research team explored flood history in the high-altitude Dhualiganga catchment (headwaters of the Ganges) in the Chamoli District, using documentary records and local community knowledge sources. This builds on over a decade of research, teaching, and placement activity in the Indian Himalaya

Virtual screening of anti-HIV1 compounds against SARS-CoV-2: machine learning modeling, chemoinformatics and molecular dynamics simulation based analysis

COVID-19 caused by the SARS-CoV-2 is a current global challenge and urgent discovery of potential drugs to combat this pandemic is a need of the hour. 3-chymotrypsin-like cysteine protease (3CLpro) enzyme is the vital molecular target against the SARS-CoV-2. Therefore, in the present study, 1528 anti-HIV1compounds were screened by sequence alignment between 3CLpro of SARS-CoV-2 and avian infectious bronchitis virus (avian coronavirus) followed by machine learning predictive model, drug-likeness screening and molecular docking, which resulted in 41 screened compounds. These 41 compounds were re-screened by deep learning model constructed considering the IC50 values of known inhibitors which resulted in 22 hit compounds. Further, screening was done by structural activity relationship mapping which resulted in two structural clefts. Thereafter, functional group analysis was also done, where cluster 2 showed the presence of several essential functional groups having pharmacological importance. In the final stage, Cluster 2 compounds were re-docked with four different PDB structures of 3CLpro, and their depth interaction profile was analyzed followed by molecular dynamics simulation at 100 ns. Conclusively, 2 out of 1528 compounds were screened as potential hits against 3CLpro which could be further treated as an excellent drug against SARS-CoV-2

Understanding the role of natural and anthropogenic forcings in structuring the periphytic algal assemblages in a regulated river ecosystem

Abstract Periphytic algal assemblages in the River Sindh of Kashmir Himalaya were studied in relation to environmental factors and anthropogenic alterations like flow regulation for Run-of-River hydropower plants to understand their ecology in a regulated river ecosystem. Sites were sampled from unregulated, regulated, and downstream reaches along the river on a seasonal basis from the year 2017 to 2019. A total of 48 species were identified, spread over 31 genera. Non-metric multidimensional analysis showed clear distinction in periphytic algal assemblage samples based on sites and potentially some more minor distinction based on seasons rendering the sites into two distinct groups (G1 and G2). The ADONIS test showed that the groups (G1 and G2 sites) do not significantly differ in terms of how communities differ from one another, but there is a difference in species compositions based on seasons. However, the betadisper test indicated that groups (G1 and G2 sites) and seasons present homogeneity among group dispersions (compositions vary similarly) while having significantly different compositions. Geo-physical factors (discharge and altitude) accounted for most variations, while the scraper community played a minor role. This study provides scientific insights related to the ecology of a regulated Himalayan river and may provide information relevant to managing the River Sindh sustainably

Impacts of Aerosol Loading in the Hindu Kush Himalayan Region Based on MERRA-2 Reanalysis Data

The impacts of climate change have severely affected geosphere, biosphere and cryosphere ecosystems in the Hindu Kush Himalayan (HKH) region. The impact has been accelerating further during the last few decades due to rapid increase in anthropogenic activities such as modernization, industrialization and urbanization, along with energy demands. In view of this, the present work attempts to examine aerosol optical depth (AOD) over the HKH region using the long-term homogeneous MERRA-2 reanalysis data from January, 1980 to December, 2020. The AOD trends are examined statistically with student’s t-test (t). Due to a vast landmass, fragile topography and harsh climatic conditions, we categorized the HKH region into three sub-regions, namely, the northwestern and Karakoram (HKH1), the Central (HKH2) and the southeastern Himalaya and Tibetan Plateau (HKH3). Among the sub-regions, the significant enhancement of AOD is observed at several potential sites in the HKH2 region, namely, Pokhara, Nainital, Shimla and Dehradun by 55.75 × 10−4 ± 3.76 × 10−4, 53.15 × 10−4 ± 3.94 × 10−4, 51.53 × 10−4 ± 4.99 × 10−4 and 39.16 × 10−4 ± 4.08 × 10−4 AOD year−1 (550 nm), respectively, with correlation coefficients (Rs) of 0.86 to 0.93. However, at a sub-regional scale, HKH1, HKH2 and HKH3 exhibit 23.33 × 10−4 ± 2.28 × 10−4, 32.20 × 10−4 ± 2.58 × 10−4 and 9.48 × 10−4 ± 1.21 × 10−4 AOD year−1, respectively. The estimated trends are statistically significant (t > 7.0) with R from 0.81 to 0.91. Seasonally, the present study also shows strong positive AOD trends at several potential sites located in the HKH2 region, such as Pokhara, Nainital, Shimla and Dehradun, with minimum 19.81 × 10−4 ± 3.38 × 10−4 to maximum 72.95 × 10−4 ± 4.89 × 10−4 AOD year−1 with statistical significance. In addition, there are also increasing AOD trends at all the high-altitude background sites in all seasons

Efficacy of a novel sequential enzymatic hydrolysis of lignocellulosic biomass and inhibition characteristics of monosugars

Efficient production of sugar monomers from lignocellulose is often hampered by serious bottle-necks in biomass hydrolysis. The present study reveals that ultra-sonication assisted pretreatment following autoclaving, termed as combined pretreatment, can lead to more efficient delignification of lignocellulosic biomass and an open, deformed polysaccharide matrix, found favorable for subsequent enzymatic hydrolysis, is formed. The pattern of inhibition for the enzymatic hydrolysis reaction on combined-pretreated saw dust is identified. Two main inhibition models (competitive and noncompetitive) are proposed and a better fit of experimental values with the theoretical values for the competitive inhibition model validates the proposition that in the present experiment, glucose inhibits the enzymes competitively. Additionally, accuracy of the inhibitory kinetics based models is estimated over a series of enzyme and substrate concentrations.acceptedVersio

Studies on delignification and inhibitory enzyme kinetics of alkaline peroxide pre-treated pine and deodar saw dust

Delignification of lignocellulosic biomass by alkaline peroxide pre-treatment is a preliminary important step for an overall biomass fractionation process. In the present work, saw dusts are pre-treated by aqueous alkaline peroxide solution under different temperatures over a predetermined time. It is seen that Combined Pre-treatment (CP) removes a substantially higher quantity of lignin from biomass under a particular temperature. At elevated temperatures, the extent of delignification is observed much better. The % removal is: [PR: 19.35%(30 °C):25.26%(50 °C):33.30%(100 °C)]; [CD:14.64%(30 °C):23.64%(50 °C): 28.83%(100 °C)]. Batch kinetics is investigated with certain models and corresponding parameters are estimated. As pre-treatment severity is strongly correlated to the pre-treatment temperature, increased value of “potential degree of delignification” is observed at escalated temperatures. Kinetics of enzymatic hydrolysis of delignified biomass shows decreased product inhibition with increased substrate concentration under a particular enzyme loading. Starting with a combination of 50 g/L substrate concentration with an enzyme loading of 13.23 g/L, an optimum concentration of 17.2 g/L and 21.19 g/L of glucose are produced from Pinus roxburghii and Cedrus deodara respectively. Experimental data fit quite well with the competitive inhibition kinetics based theoretical models with r2 ≥0.95. It is inferred that enzymes are competitively inhibited by glucose

Potent multi-target natural inhibitors against SARS-CoV-2 from medicinal plants of the Himalaya: a discovery from hybrid machine learning, chemoinformatics, and simulation assisted screening

The emergence and immune evasion ability of SARS-CoV-2 Omicron strains, mainly BA.5.2 and BF.7 and other variants of concern have raised global apprehensions. With this context, the discovery of multitarget inhibitors may be proven more comprehensive paradigm than its one-drug-to-one target counterpart. In the current study, a library of 271 phytochemicals from 25 medicinal plants from the Indian Himalayan Region has been virtually screened against SARS-CoV-2 by targeting nine virus proteins, viz., papain-like protease, main protease, nsp12, helicase, nsp14, nsp15, nsp16, envelope, and nucleocapsid for screening of a multi-target inhibitor against the viral replication. Initially, 94 phytochemicals were screened by a hybrid machine learning model constructed by combining 6 confirmatory bioassays against SARS-CoV-2 replication using an instance-based learner lazy k-nearest neighbour classifier. Further, 25 screened compounds with excellent drug-like properties were subjected to molecular docking. The phytochemical Cepharadione A from the plant Piper longum showed binding potential against four proteins with the highest binding energy of −10.90 kcal/mol. The compound has acceptable absorption, distribution, metabolism, excretion, and toxicity properties and exhibits stable binding behaviour in terms of root mean square deviation (0.068 ± 0.05 nm), root-mean-square fluctuation, hydrogen bonds, solvent accessible surface area (83.88–161.89 nm2), and molecular mechanics Poisson-Boltzmann surface area during molecular dynamics simulation of 200 ns with selected target proteins. Concerning the utility of natural compounds in the therapeutics formulation, Cepharadione A could be further investigated as a remarkable lead candidate for the development of therapeutic drugs against SARS-CoV-2. Communicated by Ramaswamy H. Sarma</p

Aerosol Characteristics and Their Impact on the Himalayan Energy Budget

The extensive work on the increasing burden of aerosols and resultant climate implications shows a matter of great concern. In this study, we investigate the aerosol optical depth (AOD) variations in the Indian Himalayan Region (IHR) between its plains and alpine regions and the corresponding consequences on the energy balance on the Himalayan glaciers. For this purpose, AOD data from Moderate Resolution Imaging Spectroradiometer (MODIS, MOD-L3), Aerosol Robotic Network (AERONET), India, and Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) were analyzed. Aerosol radiative forcing (ARF) was assessed using the atmospheric radiation transfer model (RTM) integrated into AERONET inversion code based on the Discrete Ordinate Radiative Transfer (DISORT) module. Further, air mass trajectory over the entire IHR was analyzed using a hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model. We estimated that between 2001 and 2015, the monthly average ARF at the surface (ARFSFC), top of the atmosphere (ARFTOA), and atmosphere (ARFATM) were &minus;89.6 &plusmn; 18.6 Wm&minus;2, &minus;25.2 &plusmn; 6.8 Wm&minus;2, and +64.4 &plusmn; 16.5 Wm&minus;2, respectively. We observed that during dust aerosol transport days, the ARFSFC and TOA changed by &minus;112.2 and &minus;40.7 Wm&minus;2, respectively, compared with low aerosol loading days, thereby accounting for the decrease in the solar radiation by 207% reaching the surface. This substantial decrease in the solar radiation reaching the Earth&rsquo;s surface increases the heating rate in the atmosphere by 3.1-fold, thereby acting as an additional forcing factor for accelerated melting of the snow and glacier resources of the IHR