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Human serum albumin (HSA) is an important therapeutic used in clinical settings for restoration of blood volume and treatment of chemotherapy induced neutropenia. Currently sourced from human serum, it carries the risk of contamination with viruses. The production of stable extracellular recombinant (r)HSA was achieved at nearly 1 g/L at shake-flask level in Pichia pastoris (syn. Komagataella phaffii) containing a three-copy containing HSA expression cassette, prepared in vitro. The HSA specific transcripts were increased by 1.82- to 2.46-fold in the three-copy containing clones indicating increased transcript levels to result in enhanced production of extracellular rHSA. The purified rHSA displayed secondary structure, zeta potential, size distribution and biological efficacy that matched with that of the commercial HSA. Cultivation strategy was developed at bioreactor level for the single HSA expression cassette containing recombinant which led to productivity of 300 mg/L/d of rHSA with minimum proteolytic cleavage.

The orographic effects of Antarctica on the atmospheric circulation are investigated through idealized orographic reduction numerical experiments performed using the NCAR CAM5 model. The investigation shows that, in the absence of the orography over the continent, the troposphere becomes warmer and wetter, the sea level pressure reduces, and the precipitation is enhanced. Furthermore, over the continent, the height of the tropopause increases, the stationary waves become weaker, and the southern polar jet gets more energetic. The radiative budget also gets altered, with more outgoing longwave radiation over the continent, which drives circulation changes beneath. The mean atmospheric circulation is weakened with weakening and shrinking of the Polar cell and widening of the Ferrel cell in the Southern Hemisphere, which decreases the contribution by mean flow towards poleward energy transport. An increase in transient eddy due to an enhancement of baroclinicity over the region supports poleward energy transport and compensates for a higher outgoing longwave radiation over the Antarctic continent. These significant changes observed in idealized Antarctic orographic reduction demonstrate the importance of the present Antarctic orography and ice cover for the Southern Hemisphere. The impact of these changes provides valuable insights on the future role of Antarctic orography on the earth’s climate system from a fundamental point of view.

Equilibrium climate sensitivity (ECS) is defined as the change in the global mean surface air temperature due to the doubling or quadrupling of CO2 in a climate model simulation. This metric is used to determine the uncertainty in future climate projections, and therefore, the impact of model changes on ECS is of large interest to the climate modeling community. In this paper, we propose a new graphical method, which is an extension of Gregory's linear regression method, to represent the impact of model changes on ECS, climate forcing, and climate feedbacks in a single diagram. Using this visualization method, one can (a) quantify whether the model or process change amplifies, reduces, or has no impact on global warming, (b) evaluate the percentage changes in ECS, climate forcing, and climate feedbacks, and (c) quantify the ranges of the uncertainties in the estimated changes. We demonstrate this method using an example of climate sensitivity simulations with and without interactive chemistry. This method can be useful for multimodel assessments where the response of multiple models for the same model experiment (e.g., usage of interactive chemistry compared with the prescribed chemistry as shown here) can be assessed simultaneously, which is otherwise difficult to compare and comprehend. We also demonstrate how this method can be used to examine the spread in ECS, climate forcing, and climate feedbacks with respect to the multimodel mean (or one benchmark model) for multimodel frameworks such as Coupled Model Intercomparison Project Phase 5 or for different ensemble members in a large ensemble of simulations conducted using a single model., 平衡気候感度（ECS）は、気候モデルシミュレーションにおいてCO2の２倍または４倍増による全球平均地表気温の変化として定義される。この指標は気候予測の不確実性を示すのに用いられ、したがって、モデルチェンジのECSへの影響は気候モデル開発コミュニティにとって大きな興味対象である。本論文では、ECS、気候強制、および、フィードバックに対するモデルチェンジの影響を一つの図で示す、新たなグラフ手法を提案する。それはグレゴリーの線形回帰法に基づいている。この可視化手法を用いれば、（a）モデルチェンジや新モデル過程導入が地球温暖化を増幅させるか、減衰させるか、影響しないか、を定量化し、（b）ECS、気候強制、および、フィードバックが何％変化するか、を見積り、そして、（c）影響評価の不確実性の程度を定量化できる。ここでは、相互作用する大気化学過程を入れるか入れないかに関する気候感度実験を実例として、この手法の有効性を実証する。同じ実験（例えば、相互作用する大気化学過程か、定められた値の化学成分量を使うか、の比較実験）に対して、複数のモデルの応答を同時に評価するという複数モデル評価において、この手法は有効であり、モデルの相互比較と結果の理解が容易になる。また、第五次結合モデル相互比較プロジェクトのような多数モデル比較の枠組みで、多数モデル平均（または、ある１つのベンチマーク・モデル）に対して各モデルのECS、気候強制、および、フィードバックのばらつき度合いを調べることが、この手法により如何に容易になるかを例示する。さらに、一つのモデルを用いた多数アンサンブルシミュレーションにおいて、個々のアンサンブル・メンバーのばらつきを調べるのにもこの手法が有用である。

Using reanalysis data and observations, interannual variations and long-term trends in the Somali Jet (hereafter, the Jet) and Indian Summer Monsoon Rainfall (ISMR) are characterized for drought vs flood, El Nino vs La Nina, and positive vs negative Indian Ocean Dipole (IOD) summer monsoon seasons. In flood years, the Jet is stronger over the upstream sector (i.e., Arabian Sea) and weaker over the downstream (i.e., Bay of Bengal), resulting in additional convergence and enhanced moisture transport over India, whereas the reverse occurs during drought years. The Jet and ISMR characteristics for El Nino (La Nina) years are similar to drought (flood) years, despite only around half of dry (wet) years, being associated with El Nino (La Nina). In +IOD years, the Jet shifts northward and intensifies over central and northern India, bringing more moisture and rainfall to those regions, while the −IOD has an opposite but relatively weak impact on ISMR. Over the last century, the Jet has become weaker over peninsular India, with reductions in rainfall across east India. Future projections under the SSP585 scenario from the CMIP6 multi-model mean suggest that the Jet will progressively shift northward and strengthen over the Arabian Sea, with associated rainfall increases over entire Indian region. The long-term changes in the Jet over the twentieth century are of comparable magnitude to interannual variations; however, the absolute magnitude of projected future changes is smaller than interannual variations observed in the past.

Termitomyces sp. OE 147 is one of the active cellulose degraders in the ecosphere and produces large amount of cellobiose dehydrogenase (CDH) and β-glucosidases when cultivated on cellulose. In ord...

Using uncertainty quantification techniques, we carry out a sensitivity analysis of a large number (17) of parameters used in the NCAR CAM5 cloud parameterization schemes. The LLNL PSUADE software is used to identify the most sensitive parameters by performing sensitivity analysis. Using Morris One-At-a-Time (MOAT) method, we find that the simulations of global annual mean total precipitation, convective, large-scale precipitation, cloud fractions (total, low, mid, and high), shortwave cloud forcing, longwave cloud forcing, sensible heat flux, and latent heat flux are very sensitive to the threshold-relative-humidity-for-stratiform-low-clouds ($$rhminl)$$ r h m i n l ) and the auto-conversion-size-threshold-for-ice-to-snow $$\left( {dcs} \right).$$ dcs . The seasonal and regime specific dependence of some parameters in the simulation of precipitation is also found for the global monsoons and storm track regions. Through sensitivity analysis, we find that the Somali jet strength and the tropical easterly jet associated with the south Asian summer monsoon (SASM) show a systematic dependence on $$dcs$$ dcs and $$rhminl$$ rhminl . The timing of the withdrawal of SASM over India shows a monotonic increase (delayed withdrawal) with an increase in $$dcs$$ dcs . Overall, we find that $$rhminl$$ rhminl , $$dcs$$ dcs , $$ai,$$ a i , and $$as$$ as are the most sensitive cloud parameters and thus are of high priority in the model tuning process, in order to reduce uncertainty in the simulation of past, present, and future climate.

Here, we report the whole-genome sequence of Bacillus sp. strain IITD106. The bacterium has the unique ability to produce saponins. The complete nucleotide sequence will provide insights into the various genes and regulators involved in the biosynthesis of saponin.

This study reports, for the first time, morphological transition from yeast-like to filamentous form, normally associated with pathogenicity/increased protein secretion, in Pichia pastoris SMD1168 strain. The response was recorded in response to nutritional and environmental cues. The factors affecting this switch were extracellular pH (under nitrogen starvation conditions), carbon and nitrogen source under nitrogen- and carbon-limiting conditions respectively. Under nitrogen-limiting conditions, addition of fructose and sucrose in the culture medium induced filamentous morphology in a segregated form whereas addition of galactose led to a mixture of yeast and the filamentous form of the cells. Under carbon-limiting conditions, isoleucine and proline forced a filamentous form whereas glycine, valine, alanine and phenylalanine promoted yeast-like morphology. Similar dimorphic shift was also displayed by a recombinant methanol slow utilizing (Mut

The human granulocyte colony-stimulating factor (G-CSF) is one of the hematopoietic growth factors administered for chemotherapy induced neutropenia and is currently produced through recombinant route in Escherichia coli. The methylotrophic unicellular yeast Pichia pastoris (syn. Komagataella phaffii) makes a good host for production of human therapeutics as the proteins are low-mannose glycosylated, disulfide bonded and correctly folded on their way to the cell exterior. Given the low level of production of G-CSF in P. pastoris, the present study examined modification of the Saccharomyces cerevisiae derived α-mating type secretory signal sequence to enhance its production. The substitution of Glu, at the P1' position of the Kex2 cleavage site, by Val/Ala led to extracellular production of ~ 60 mg/L of G-CSF in the extracellular medium. Production was further increased to ~ 100 mg/L by putting these mutations against rarely occurring methanol slow utilization P. pastoris X-33 host. Analysis of the modelled structure of the signal peptide indicated exposed loop structures, created by presence of Val/Ala, that favour cleavage by the Kex2 peptidase thereby leading to enhanced production of G-CSF. The conformational changes, induced on account of binding between the signal sequence and the cargo protein (G-CSF), also appear to play an important role in the final yield of the extracellular protein.

Recently released NASA's Earth Exchange Global Daily Downscaled Projections (NEX-GDDP) data (surface air temperature and precipitation) are evaluated using the observations from the India Meteorological Department (IMD) and compared with CMIP5 and CORDEX data to show its advantage over the Indian subcontinent for the summer monsoon season. The multi-model mean of 21 NEX-GDDP models, 28 CMIP5 models, and 10 CORDEX models are analyzed for the period of 1975–2005. In general and over most parts of the subcontinent, the NEX-GDDP is found to be quite satisfactory and surpasses the CMIP5 and CORDEX data. The NEX-GDDP data captures the spatial patterns of seasonal mean temperatures and precipitation with highest accuracy (pattern correlation of ~0.8) and least errors (root mean square error of ~ 4.25 °C and ~2.48 mm day−1); the inter-annual variations in precipitation are closer to the observations (r = 0.66 and standard deviation = 0.36 mm day−1); bias in the annual cycle reduces; simulation of extremes is more realistic with less inter-model differences. Remarkable improvements in this data suggest its potential application for future projections and climate change impact studies at the regional scale.

The Himalaya–Tibetan Highland (HTH) is highly vulnerable to climate change for multiple reasons. In this work, we present past and future changes in HTH climate, using temperature and precipitation from APHRODITE, CMIP5 and NEX-GDDP. To assess observed climate change, we analysed APHRODITE and found significant warming (up to 3 °C) during all seasons but no significant change in precipitation. We validated CMIP5 and NEX-GDDP against APHRODITE and found the latter more accurate. Future climate projections under RCP8.5 using NEX-GDDP suggest widespread warming (~5–8 °C) and increase in monsoon and post-monsoon precipitation (up to ~50%) over HTH by the end of the twenty-first century.

Effects of increase in horizontal resolution (from 2°, to 1° and 0.5°) in simulating Indian summer monsoon (ISM) in Community Atmosphere Model version 5 (CAM5) are reported herein. Various parameters — temperature, rainfall, winds, surface evaporation, precipitable water, specific humidity, and clouds — of the model simulations are examined with respect to observations {India Meteorological Department (IMD) and Tropical Rainfall Measuring Mission (TRMM) data for precipitation and Modern-Era Retrospective analysis for Research and Applications (MERRA) products for rest of the variables}. With increase in horizontal resolution overall improvement in majority of surface driven parameters like surface air temperature, surface specific humidity, and low-level winds is observed that highlights the importance of better representation of orography. Over the Indian subcontinent and surrounding oceans, rainfall is overestimated due to the overestimation of the large-scale precipitation in the model, which significantly gets alleviated with increase in resolution. Overall, seasonal mean features of ISM show significant improvements, which are likely to further improve by representing finer spatial features with increase in resolution. However, some aspects of its temporal variations — seasonal, intraseasonal, and diurnal variations — of monsoon rainfall do not show much improvement with increase in resolution, suggesting that traditional physics parameterizations do not work well at high resolution and hence there is a need for improvement in model physics.

Model simulations are highly sensitive to the formulation of the atmospheric mixing process or entrainment in the deep convective parameterizations used in their atmospheric component. In this paper, we have implemented stochastic entrainment in the deep convection scheme of NCAR CAM5 and analyzed the improvements in model simulation, focusing on the South Asian Summer Monsoon (SASM), as compared to the deterministic entrainment formulation in the default version of the model. Simulations using stochastic entrainment (StochCAM5) outperformed default model simulations (DefCAM5), as inferred from multiple metrics associated with the SASM. StochCAM5 significantly alleviated some of the longstanding SASM biases seen in DefCAM5, such as precipitation pattern and magnitude over the Arabian Sea and western Equatorial Indian ocean, early monsoon withdrawal, and the overestimation (underestimation) in the frequency of light (large-to-extreme) precipitation. Related SASM dynamical and thermodynamical features, such as Somali Jet, low-level westerly winds, and meridional tropospheric temperature gradient (MTTG), are improved in StochCAM5. Further, the simulation of monsoon intra-seasonal oscillation (MISO), Madden Julian Oscillation (MJO), and equatorial Kelvin waves are improved in StochCAM5. Many essential climate variables, such as shortwave and longwave cloud forcing, cloud cover, relative and specific humidity, and precipitable water, show significant improvement in StochCAM5.

Laccases (EC 1.10.3.2) are multi-copper oxidases that can degrade several xenobiotics, including textile dyes. Present study investigated the nature of laccase isoforms induced by 2,6-dimethylaniline in Cyathus bulleri cultivated on basal salt medium. Two isoforms, LacI and LacII were identified and purified by a combination of ultrafiltration and ion-exchange chromatography. The MS spectrum of the two proteins displayed a number of non-identical and identical molecular peaks (m/z), and, the latter were mapped to protein originating from the previously reported Laccase (Lcc) 1 gene. The LacI isoform exhibited higher catalytic efficiency (Kcat/Km) towards 2,2'-azino-bis (3-ethylbenzothiazoline-6-sulfonic acid), 2,6-dimethoxyphenol, guaiacol and pyrogallol and was tolerant to high levels of chloride ions and resistant to EDTA. Higher decolorization of several dyes such as Direct Scarlet B (67%), Reactive Brilliant blue-R (96%), Direct Orange 34 (50%) and Reactive Red198 (95%) by the LacI isoform makes it a good candidate for degradation of synthetic dyes. The decolorization of Direct Orange 34 by laccases is being reported for the first time. Many of the properties exhibited by this isoform make it a good candidate for large scale production and applications for use in the dyeing industry.

The lowest portion of the planetary boundary layer (PBL), where the turbulent fluxes are assumed to be constant, is known as the atmospheric surface layer (ASL). Within the surface layer, the surface exchange processes play an important role in land-atmosphere interaction. Thus, a precise formulation of the surface fluxes is crucial to ensure an adequate atmospheric evolution by numerical models. The Monin–Obukhov Similarity Theory (MOST) is a widely used framework to estimate the surface turbulent fluxes within the surface layer. MOST uses similarity functions of momentum (φm) and heat (φh) for non-dimensional wind and temperature profiles. Over the years, various formulations for these similarity functions have been proposed by the researchers ranging from linear to non-linear forms. These formulations have limitations in the weak wind, stable, and unstable atmospheric conditions. In the surface layer scheme currently available in the Community Atmosphere Model version 5 (CAM5.0), the stable and unstable regimes are divided into four parts, and the corresponding similarity functions are the functions proposed by Kader and Yaglom (1990) for strong unstable stratification, by Businger et al. (1971) for weak unstable stratification, functions by Dyer (1974) for weak stable stratification, and for moderate to strongly stable stratification, the functions from Holtslag et al. (1990) have been utilized. The criteria used for this classification are somewhat ad-hoc, and there is an abrupt transition between different regimes encountered. In the present study, an effort has been made to implement the similarity functions proposed by Grachev et al. (2007) for stable conditions and Fairall et al. (1996) for unstable conditions in the surface layer scheme of Community Land Model (CLM) for CAM5.0. In the modified version, the similarity functions for unstable conditions are a combination of commonly used Paulson type expressions for near-neutral stratification and an expression proposed by Carl et al. (1973) that takes in to account highly convective conditions. Similarly, the formulation proposed by Grachev et al., for stable conditions, can cover a wider range of stable stratifications. The simulations with CAM5 model using the existing and modified version of surface layer scheme have been performed with 1° resolution for ten years, and the impact of modified functions on the simulation of various important near-surface variables over the tropical region is analyzed. It is found that the scheme with modified functions improving the simulation of surface variables as compared with the existing scheme over the tropical region. In addition, the limitations arbitrarily imposed on particular variables in the existing surface layer scheme can be eliminated or suppressed by using these modified functions. References:Fairall CW, Bradley EF, Rogers DP, Edson JB, Young GS (1996) Bulk parameterization of air-sea fluxes for tropical ocean global atmosphere coupled-ocean atmosphere response experiment. J Geophys Res 101(C2):3747–3764Grachev, A.A., Andreas, E.L., Fairall, C.W., Guest, P.S. and Persson, P.O.G. (2007a) SHEBA: flux–profile relationships in stable atmospheric boundary layer. Boundary-Layer Meteorology,124, 315–333.Keywords:Boundary layer, Turbulence, Climate Model, Surface Fluxes

India suffers from severe social-economic losses due to floods and droughts during boreal summer (June-September) and therefore there is a growing interest in the current risk of extreme monsoon rainfall. In this analysis, we estimate the risk of flood, drought and unprecedented (outside the range of present observational record) rainfall over India using UNprecedented Simulated Extremes using ENsembles (UNSEEN) method. The UNSEEN is a statistical framework under which the risk of unprecedented rainfall extremes can be estimated using a large ensemble of initialized climate simulations to sample a broad range of internal variability. This is the first application of the method to the hindcasts from multiple coupled atmosphere-ocean models. Under this method, we first test individual models against the observed rainfall record over India and select models that are statistically indistinguishable from observations. The risk of floods, droughts and unprecedented rainfall is then estimated using a large ensemble of summer precipitation simulated by the selected set of models. We note that in present climate the risk of drought is higher than the flood, with droughts being more frequent and intense than the floods. This asymmetry in rainfall extremes is found to be partly due to the asymmetry in El-Nino Southern Oscillation (ENSO) phase, with El Nino reaching higher magnitude more frequently than La Nina. The current risk of record breaking drought (>23% deficit w.r.t climatological mean) is 1.6% whereas the risk for record-breaking flood (>16% excess) is 2.6%. There is even a risk of 30% rainfall deficit that could occur around once in two centuries, which is not yet seen in observations and would have a catastrophic influence on India.

In this paper, the fidelity of 28 models under Coupled Model Inter-comparison Project Phase-5 is examined for the Indian summer monsoon for the historical period from 1975 to 2005. It is found that all models simulate the spatial distribution of the seasonal mean surface air temperatures (Tas) quite well (pattern correlation > 0.75), whereas the simulation of precipitation is found to be relatively poor (correlation 0.1–0.7). Most models underestimate the Tas with more bias during winter and less bias during summer. In regard to precipitation, most models fail to capture the observed contribution ratio of convective and large-scale precipitation (LSP) and simulate more convective precipitation as compared to the LSP. Extremely large wet (dry) biases are noted in convective (large-scale) precipitation. The total precipitation is also noted to have a large dry bias in most models, which is mainly due to the large dry bias in the LSP. Contrary to the notion that better simulation of the contribution ratio would lead to better simulation of total precipitation or vice-versa, our results show that both of these notions are not valid for most models. In observations, the LSP dominates the annual cycle of the total precipitation, whereas in models, the convective component dominates. In few models, the annual cycle in the individual precipitation component is either weak or completely missing. None of the models are found to simulate the observed trend in precipitation and temperature. The model with the highest resolution, MIROC-4h, simulates many of the observed features better than the other models, thereby emphasizing the usefulness of finer resolutions in better simulation of Indian monsoon. A comprehensive list of models has been prepared on the basis of their capability in simulating various features of Indian summer monsoon. The multimodel mean of the better models identified in this study is expected to produce more reliable projections of the Indian monsoon.

Considering the wide use of the multi-model mean (MMM) on the seasonal time scale, this work examines its fidelity in simulating some important characteristics of the Indian summer monsoon using Coupled Model Intercomparison Project Phase 5 (CMIP5) simulations. It is noted that the MMM captures the observed spatial pattern and annual cycle of surface air temperature to a great extent, but there are large biases in magnitude, particularly over north India. For precipitation, only the broad-scale features are captured and extreme large biases, of magnitude equal or higher than the seasonal mean precipitation, exist in the MMM. The simulation of trends in seasonal mean temperatures and precipitation is even less satisfactory than the climatological means. Several precipitation features, for example, low-to-moderate intensity precipitation events, orography-related rain bands, extreme events, are noted to improve with increasing resolution of the models, whereas, no such improvement is noted for temperatures. It is also noted that the improvement in CMIP5 MMM is marginal if compared with the best performing model from the group of models considered for analysis. There are several models that show similar skill as MMM, and therefore could be alternatively used for future projections. Moreover, using such individual models for Indian monsoon projections will also help us to understand the underlying mechanisms and processes by conducting targeted numerical experiments, which would otherwise be highly limited by approaches like MMM. Therefore, targeted efforts to improve some of these better models are required to gain more confidence in future projections of Indian monsoon. Averaging output from various climate models (the multi-model mean, MMM) fails to capture key characteristics of the Indian monsoon. The MMM—which reduces bias associated with individual models—has been used extensively to investigate observed and projected changes in monsoon rainfall, upon which millions of people rely for water resources. Saroj Mishra and colleagues from the Indian Institute of Technology Delhi use the CMIP5 ensemble to test whether the MMM is able to represent broad-scale monsoon features. Several biases exist in the simulation of both temperature and precipitation. In particular, the magnitude of MMM rainfall is incorrect, low-to-moderate precipitation events are overestimated, while extreme events are underestimated. Thus, care must be taken when using the MMM to interpret projected changes in monsoon variability, and in some instances, analysis of individual models may be preferable.

In this paper, the performance of 28 CMIP5 models in simulating the climate of the Himalaya-Tibetan Plateau (HTP) for the recent past (1975–2005) is evaluated using the observations from the Asian Precipitation Highly-Resolved Observational Data Integration Towards Evaluation (APHRODITE). Many models realistically simulate the spatial distribution of surface air temperature (Tas) and precipitation with pattern correlation as high as 0.8; however, they possess severe biases in their magnitude. The biases in Tas appear to be associated with the biases in the surface elevation. All the models capture the observed phase of the annual cycle of the Tas but underestimate the amplitude. For precipitation, the phase is captured by most models (except few), but the amplitude is overestimated in all models. In the mid-intensity precipitation range (10–80 mm day−1), most of the models overestimate the probability of occurrence and show large intermodel differences. Most of the models fail to simulate the spatial distribution of the trend in Tas and precipitation. As compared to many individual models, the biases are noted to reduce when using multimodel means (MMMs); however, the MMMs also failed to capture the observed trends in both Tas and precipitation. Many models still struggle to capture the large-scale phenomena, such as the location and intensity of upper-level Asian anticyclone and middle troposphere temperature maximum over the HTP, which have large implications on the HTP as well as the Indian summer monsoon. The results show that none of the models capture all features of the HTP monsoon, and hence, further improvement in the parameterization schemes and resolution is required to gain more confidence in the projection of HTP climate using these models.

As Himalaya-Tibet Highland (HTH), a spatially extensive and complex terrain, plays influential roles in the regional and global climate, its representation in climate models is a decisive factor in climate simulations. It is established that higher spatial resolution improves the simulation of several seasonal mean features over this region, but how much improvement comes from the better representation of surface topography and how much comes from the better modeling of the atmospheric and surface processes are still not clear. To understand this, three sets of 6-member ensemble simulations are conducted using the NCAR Community Atmosphere Model version 5.1 (CAM5.1) at: (1) 1.9° × 2.5° resolution (Coarse), (2) 0.47° × 0.63° resolution (Fine), and (3) topography is prescribed at the Coarse resolution and rest of the model processes are computed at the Fine resolution (Hybrid). The Coarse resolution overlooks most of the intricate features of the topography with a severe bias of ~ 1–2 km but Fine resolution does a much better job in their representations. Surface air temperatures are found to be strongly dependent on the resolution of topography and therefore it is desirable to resolve topography in models for the realistic simulation and projection of temperatures. Rest of the variables, viz. seasonal mean, seasonal cycle and probability distribution of precipitation; tropospheric temperature and moisture; Tibetan anticyclone, show remarkable improvements with the increase in resolution of the atmospheric and surface processes. Influence of the resolution of topography is found to be limited to the model levels adjacent to the surface, and for higher model levels, the resolution of the atmospheric and surface processes is noted to play a more crucial role.

Three artificial intelligence approaches - K-nearest neighbor (KNN), artificial neural network (ANN), and extreme learning machine (ELM) - are used for the seasonal forecasting of summer monsoon (June-September) and post-monsoon (October-December) rainfall from 2011 to 2016 for the Kerala state of India and performance of these techniques are evaluated against observations. All the aforesaid techniques have performed reasonably well and in comparison, ELM technique has shown better performance with minimal mean absolute percentage error scores for summer monsoon (3.075) and post-monsoon (3.149) respectively than KNN and ANN techniques. The prediction accuracy is highly influenced by the number of hidden nodes in the hidden layer and more accurate results are provided by the ELM architecture (8-15-1). This study reveals that the proposed artificial intelligence approaches have the potential of predicting both summer monsoon and post-monsoon of the Kerala state of India with minimal prediction error scores.

The influence of surface topography resolution in Indian summer monsoon simulation is investigated. Three sets of six-member ensemble simulations with climatological sea surface temperature are conducted with the Community Atmospheric Model, version 5.1 (CAM5.1): COARSE simulation at 1.9° × 2.5° latitude–longitude resolution, FINE simulation at 0.47° × 0.63° resolution, and HYBRID simulation, that is, using COARSE surface topography imposed on the FINE configuration. With regard to the representation of the surface topography, substantial differences occur at the regional scales between the simulations, especially over the foothills and steep flanks of the mountains. In the COARSE and HYBRID simulations, the orographic height of the foothills is overestimated whereas that of the steep flanks adjacent to the foothills is underestimated. The biases are severe (up to 1 km) over the Himalayas and Tibet and have detrimental effects on regional climate through barrier effects on the low-level flow, and the lapse rate and elevated heat source effects. Overall, the simulations show remarkable improvement with an increase in resolution, mainly because of the improved representation of atmospheric and surface processes. However, local climate—surface air temperature, sea level pressure, precipitable water, and wind—of the orographic regions, particularly where large orographic biases exist in COARSE, is found to benefit substantially from increased resolution of surface topography. Local precipitation and evaporation are exceptions, although, as they are negligibly sensitive to topographic resolution, showing strong dependence on the resolution of surface and atmospheric processes. Moreover, resolution of surface topography generally does not have notable remote impacts.

A new bias-corrected statistically downscaled product, namely, the NASA Earth Exchange Global Daily Downscaled Projections (NEX-GDDP), has recently been developed by NASA to help the scientific community in climate change impact studies at local to regional scale. In this work, the product is validated over India and its added value as compared to its CMIP5 counterpart for the NCAR CCSM4 model is analyzed, followed by climate change projections under the RCP8.5 global warming scenario using the two datasets for the variables daily maximum 2-m air temperature (Tmax), daily minimum 2-m air temperature (Tmin), and rainfall. It is found that, overall, the CCSM4-NEX-GDDP significantly reduces many of the biases in CCSM4-CMIP5 for the historical simulations; however, some biases such as the significant overestimation in the frequency of occurrence in the lower tail of the Tmax and Tmin still remain. In regard to rainfall, an important value addition in CCSM4-NEX-GDDP is the alleviation of the significant underestimation of rainfall extremes found in CCSM4-CMIP5. The projected Tmax from CCSM4-NEX-GDDP are in general higher than that projected by CCSM4-CMIP5, suggesting that the risks of heat waves and very hot days could be higher than that projected by the latter. CCSM4-NEX-GDDP projects the frequency of occurrence of the upper extreme values of historical Tmax to increase by a factor of 100 towards the end of century (as opposed to a factor of 10 increase projected by CCSM4-CMIP5). In regard to rainfall, both CCSM4-CMIP5 and CCSM4-NEX-GDDP project an increase in annual rainfall over India under the RCP8.5 global warming scenario progressively from the near term through the far term. However, CCSM4-NEX-GDDP consistently projects a higher magnitude of increase and over a larger area as compared to that projected by CCSM4-CMIP5. Projected daily rainfall distributions from CCSM4-CMIP5 and CCSM4-NEX-GDDP suggest the occurrence of events that have no historical precedents. Worth noting is that the extreme daily rainfall values projected by CCSM4-NEX-GDDP are two to three times larger than that projected by CCSM4-CMIP5.

Protein folding is an extremely complex and fast, yet perfectly defined process, involving interplay of many intra and inter-molecular forces. In vitro, these molecular interactions are reversible for many proteins e.g., smaller and monomeric, organized into single domains. However, refolding of larger multi-domain/multimeric proteins is much more complicated, proceeds in a hierarchal way and is often irreversible. In a comparative study on two large, multi-domain and multimeric isozymes, β-glucosidase I (BGLI) and β-glucosidase II (BGLII) from Pichia etchellsii, we studied spontaneous and assisted refolding under three denaturing conditions viz. GdnHCl, alkaline pH and heat. During refolding, higher refolding yields were obtained for BGLII in case of pH induced unfolding (13.89% ± 0.25) than BGLI (6% ± 0.85) while for GdnHCl induced unfolding, refolding was marginal (BGLI = 5% ± 0.5; BGLII = 6% ± 0.69). Thermal unfolding was irreversible while assisted refolding also showed little structural gain for both proteins. When the apparent free energies of unfolding (ΔGUapp) were calculated from GdnHCl unfolding data, their values were strikingly found to be lower (BGLI ΔGUapp = 3.02 kcal/mol; BGLII ΔGUapp = 2.99 kcal/mol) than reported for globular (ΔGU = 5–15 kcal/mol)/multimeric proteins (ΔGU = 23–29 kcal/mol) indicating marginal stability results in low refolding.

The influence of the height of the Antarctic Ice Sheet (AIS) on its climate is investigated through numerical modeling, using NCAR-CESM-CAM5, which is found to be one of the best performing models over the region. The investigation reveals that on the reduction of its height, the troposphere over Antarctica will become warmer and wetter, annual precipitation and snow accumulation would enhance, and there will be a net enhancement in southward energy transport towards the Antarctic from the lower latitudes. The response will be opposite if the height of the AIS increases. The effect is found to be driven by the radiation imbalance developed from the changes in the outgoing longwave radiation at the top of the atmosphere due to perturbations in the ice sheet's elevation. An increase (decrease) in precipitation will occur on reduction (enhancement) of the AIS, which will try to stabilize its height, but this will be accompanied by an increase (decrease) in the surface temperature, which would have an opposite effect. A significant influence of the AIS elevation was also felt on the surface winds, stationary waves, and the eddy-driven jet around the continent, highlighting the impact that changes in the height of AIS have on the surrounding atmospheric circulation.

This study reports extraction and characterization of carotenoid pigments from Microbacterium paraoxydans, a non-photosynthetic bacterium, cultivated in Luria–Bertani (LB) medium. The isolate was identified to be moderately halo- and osmo-tolerant capable of withstanding high (~ 6%) salt and sugar (30% w/v sucrose, 20% w/v glucose) concentrations after a brief period of adaptation. The pigments were characterized using a combination of UV–Vis spectral analysis with the λmax at 407, 436 and 466 nm and ESI–MS with an m/z value at 536.44. The absorption profile of the pigments and their nature was influenced by carbon, nitrogen source and presence of salt in the growth medium. Highest level of pigment (~ 16 g kg dry wt cells−1) was produced in NH4Cl supplemented LB medium. The pigment displayed free radical scavenging, anticancer activity, characteristic of the plant carotenoids. Based on the accumulation of pigments under different conditions, a biochemical pathway for synthesis of neurosporene was proposed.

Given the general notion that dynamical downscaling leads to added accuracy in both historical simulations as well as climate change projections, this paper investigates its validity over India using historical data (1975–2005) from the CORDEX models and their driving global climate models (GCMs) from Coupled Model Intercomparison Project Phase 5 (CMIP5), and comparing them against observed temperature and rainfall. We find that downscaling invariably leads to an improvement in the spatial pattern of surface air temperature, but compared to the driving GCMs, the errors in magnitude after downscaling are even worse in some cases. In regard to JJAS rainfall simulations, the CMIP5 driving GCMs are found to be superior to their dynamically downscaled counterparts both in terms of spatial patterns as well as magnitude of errors. Both CMIP5 driving GCMs as well as the CORDEX models underestimate rainfall during JJAS; however, negative bias in CORDEX models is worse. Unlike the driving CMIP5 GCMs, their dynamically downscaled counterparts simulate an early onset followed by a slow and late withdrawal of the Indian summer monsoon rainfall. The frequency of occurrence of rainfall intensities is simulated well by both sets of models in the lower intensity regime (0–20 mm/day); however, for higher intensities, the driving CMIP5 GCMs underestimate whereas the CORDEX models overestimate.

Protein fusion technology has emerged as one of the important strategies to increase the level of expression and half-life of therapeutic proteins in heterologous expression systems. Granulocyte colony-stimulating factor (G-CSF) is a hematopoietic growth factor and is clinically used against neutropenia. Enhanced expression and stability of G-CSF were achieved in Pichia pastoris by the way of constructing a fusion protein with human serum albumin (HSA). The strategy involved polymerase chain reaction (PCR) amplification of fragments corresponding to codon-optimized G-CSF and domain 3 of HSA. Overlapping PCR was used to obtain the full-length fused gene (1,184 bp) with a 15-bp linker sequence comprising of 4 Gly and 1 Ser residues. Extracellular expression was carried out downstream of α-factor secretion signal sequence under the control of alcohol oxidase 1 promoter using pPICZαB. Excreted protein in the range of 110–380 mg L−1 was observed among the transformants. Effect of aeration and temperature was investigated in one of the transformants (35) overexpressing fusion protein and levels of G-CSF enhanced by 1.8-fold and 2.3-fold, respectively. Assay of biological activity indicated the fusion protein to retain similar cell proliferation activity as the commercial G-CSF preparation.

In this study, the white-rot fungus Cyathus bulleri was cultivated on low-cost agro-residues, namely wheat bran (WB), wheat straw (WS), and domestic waste orange peel (OP) for production of ligninolytic enzymes. Of the three substrates, WB and OP served as good materials for the production of laccase with no requirement of additional carbon or nitrogen source. Specific laccase activity of 94.4 U mg−1 extracellular protein and 21.01 U mg−1 protein was obtained on WB and OP, respectively. Maximum decolorization rate of 13.6 μmol h−1 U−1 laccase for reactive black 5 and 22.68 μmol h−1 U−1 laccase for reactive orange 16 (RO) was obtained with the WB culture filtrate, and 11.7 μmol h−1 U−1 laccase for reactive violet 5 was observed with OP culture filtrate. Importantly, Kiton blue A (KB), reported not to be amenable to enzymatic degradation, was degraded by culture filtrate borne activities. Products of degradation of KB and RO were identified by mass spectrometry, and a pathway of degradation proposed. WB-grown culture filtrate decolorized and detoxified real and simulated textile effluents by about 40%. The study highlights the use of inexpensive materials for the production of enzymes effective on dyes and effluents.

Highlights • Use of culture filtrates of Termitomyces sp. OE147. • Decolourization and degradation of Reactive blue 21. • Cellobiose dehydrogenase and laccase as effective redox couple., This study evaluates culture filtrate, rich in cellobiose dehydrogenase and laccases, of Termitomyces sp. OE 147, in decolouration and degradation of Reactive blue (RB) 21. About 35% decolouration was achieved at low volumes of the culture supernatant without addition of external redox mediators. An optimized dye to culture fluid ratio (75 ppm: 0.1 ml) at a pH of 4–5 resulted in removal of colour by 60%. The degradation products of RB21 were analysed by Electron Spray Ionization-Mass Spectrometry and several small molecules (of m/z 106–199) were detected. These were concluded to be o-Xylene, 2,3-Dihydro-1H-isoindole, Isoindole-1,3-dione, 2,Benzenesulfonyl-ethanol, (4-Hydroxy-phenyl)-sulfamic acid, 2,3-Dihydro-1H-isoindole-5-sulfonic acid and proposed to result from joint action of cellobiose dehydrogenase, laccase, peroxidases and unidentified oxidoreductases present in the culture fluids. Based on the products formed and the known reactions of these enzymes, a degradation pathway was proposed for RB21. The culture fluid was also effective in decolouration (by about 50%) and detoxification (by ∼25%) of the combined effluent collected from a local mill indicating a treatment process that bypasses use of H2O2 and toxic mediators.