Chromium is the most toxic pollutant that negatively affects a plant's metabolic activities and yield. It reduces plant growth by influencing the antioxidant defence system's activities. In the ...present study, a completely randomized block design experiment with three plants/pot in three replication was conducted on three varieties of sorghum viz. SSG 59-3, HJ 513 (multi-cut) and HJ 541 (single-cut) for amelioration of chromium toxicity (2 & 4 ppm) by exogenous application of GB (50 & 100 mM) with and without AMF in soil. The ameliorative effects were tested at two growth stages viz. vegetative (35 DAS) and grain filling (95 DAS), in terms of Cr uptake, grain yield, antioxidative defence system parameters (viz. enzymes - SOD, APX, CAT, GR, POX and metabolites - proline, glutathione, ascorbate, beta-carotene) and indices of oxidative stress parameters (viz. PPO, H.sub.2O.sub.2, and MDA). The results delineated that Cr uptake and indices of oxidative stress were increased with increasing concentration of Cr stress in all the varieties (HJ 541, HJ513 & SSG 59-3) at both the growth stages (35 & 95 DAS). At higher concentration (4 ppm), Cr stress decreased the grain yield (45-50%) as compared with controls. Polyphenoloxidase activity, MDA and H.sub.2O.sub.2 content increased at both growth stages in all the varieties. However, antioxidative enzymes and metabolite activities increased due to Cr stress but this increase was not sufficient to counteract with ROS generated under Cr stress which was enhanced on the application of AMF and GB either individually or in combination (spiked in soil). It decreased the indices of oxidative stress and ameliorated the Cr toxicity and increased grain yield (65-70%) in all the varieties. Both GB and AMF improved the antioxidative activities and stress tolerance capacity of the plant. Glycine betaine at both 50 and 100 mM level, significantly ameliorated Cr toxicity. However, AMF concomitantly with GB further boosts up the amelioration behaviour of the plant against Cr toxicity, at both growth stages in all the varieties. The combination of 100 mM GB with 10 g AMF was observed most effective among all the treatments. Among the varieties, SSG 59-3 had the lowest chromium uptake, indices of oxidative stress, and highest antioxidative system's activity as compared to HJ 513 followed by HJ 541 variety. Thus AMF and GB either individually or in combination may be used to maintain plant yield attributes under Cr toxicity.
Chromium toxicity is a major problem in agricultural soils that negatively affects a plant's metabolic activities. It reduces biochemical and antioxidant defence system's activities. In search of the ...solution to this problem a two-year pot experiment (completely randomized design with three replications), in three genetically different varieties of sorghum (SSG 59-3, HJ 513 and HJ 541) under Cr toxicity (2 and 4 ppm) was conducted to determine the effect of glycine betaine (50 and 100mM) and Arbuscular mycorrhizal fungi (AMF) on the antioxidant system (enzymes viz. superoxide dismutase, ascorbate peroxidase, catalase, glutathione reductase, peroxidase and metabolites viz. glutathione, ascorbate, proline, beta-carotene) along with Cr accumulation and indices of oxidative stress parameters (polyphenol oxidase, hydrogen peroxide and malondialdehyde) at two growth stages (vegetative and grain filling). According to results; Cr stress (2 & 4 ppm) increased its accumulation and indices of oxidative stresses significantly (pless than or equal to0.05) in all varieties of sorghum at both growth stages. However, soil application of glycine betaine (GB) and AMF decreased Cr accumulation and indices of oxidative stress by increasing antioxidant enzymes and metabolites activities at both growth stages in all varieties. The combination of 100mM GB with AMF was observed most significant (pless than or equal to0.05) in decreasing oxidative stress and improved the antioxidant system's activities. The SSG 59-3 cultivar showed the lowest Cr accumulation (1.60 and 8.61 ppm), indices of oxidative stress and highest antioxidant system's activity among these three cultivars at both growth stages. Thus, SSG 59-3 was found most tolerant cultivars followed by HJ 513 and then HJ 541. These findings suggest that both GB and AMF, either individually or combined can play a positive role to reduce oxidative stress and increased antioxidant attributes under Cr toxicity in sorghum.
•Cell-free therapy using MSC-CM can offer an exciting approach in regenerative medicine.•Therapeutic role of cytokine and growth factors present in MSC-CM in clinical studies.•Cell-free therapy ...offers a significant advantage over cells based therapy and other conventional pharmaceutics.
Mesenchymal Stem Cells (MSCs) have been shown to be a promising candidate for cell-based therapy. The therapeutic potential of MSCs, towards tissue repair and wound healing is essentially based on their paracrine effects. Numerous pre-clinical and clinical studies of MSCs have yielded encouraging results. Further, these cells have been shown to be relatively safe for clinical applications. MSCs harvested from numerous anatomical locations including the bone marrow, adipose tissue, Wharton’s jelly of the umbilical cord etc., display similar immunophenotypic profiles. However, there is a large body of evidence showing that MSCs secrete a variety of biologically active molecules such as growth factors, chemokines, and cytokines. Despite the similarity in their immunophenotype, the secretome of MSCs appears to vary significantly, depending on the age of the host and niches where the cells reside. Thus, by implication, proteomics-based profiling suggests that the therapeutic potential of the different MSC populations must also be different. Analysis of the secretome points to its influence on varied biological processes such as angiogenesis, neurogenesis, tissue repair, immunomodulation, wound healing, anti-fibrotic and anti-tumour for tissue maintenance and regeneration. Though MSC based therapy has been shown to be relatively safe, from a clinical standpoint, the use of cell-free infusions can altogether circumvent the administration of viable cells for therapy. Understanding the secretome of in vitro cultured MSC populations, by the analysis of the corresponding conditioned medium, will enable us to evaluate its utility as a new therapeutic option. This review will focus on the accumulating evidence that points to the therapeutic potential of the conditioned medium, both from pre-clinical and clinical studies. Finally, this review will emphasize the importance of profiling the conditioned medium for assessing its potential for cell-free therapy therapy.
Prediction problems broadly deal with ascertaining the fate of fluctuations or instabilities through the dynamical system being modeled. Predictability is a measure of our ability to provide ...knowledge about events that have not yet transpired or phenomena that may be hitherto unobserved or unrecognized. The challenges associated with these two problems, that is, forecasting a future event and identifying a novel phenomenon, are distinctly different. Whereas the prediction of novel phenomena seeks to explore all possible logical space of a model's behavioral response, the prediction of future events seeks to constrain the model response to a specific trajectory of the known history to achieve the least uncertainty for the forecast. Predictability challenges have been categorized as initial value, boundary value, and parameter estimation problems. Here I discuss two additional types of challenges arising from the dynamic changes in the spatial complexity driven by evolving connectivity patterns during an event and cross‐scale interactions in time and space. These latter two are critical elements in the context of human and climate‐driven changes in the hydrologic cycle as they lead to structural change–induced new connectivity and cross‐scale interaction patterns that have no historical precedence. To advance the science of prediction under environmental and human‐induced changes, the critical issues lie in developing models that address these challenges and that are supported by suitable observational systems and diagnostic tools to enable adequate detection and attribution of model errors.
Key Points
Prediction involves forecasting a future event and identifying novel phenomena
Connectivity and cross‐scale interactions lead to new predictability challenges
Prediction under change needs to consider the alteration of feedback dynamics
Due to digitization, a huge volume of data is being generated across several sectors such as healthcare, production, sales, IoT devices, Web, organizations. Machine learning algorithms are used to ...uncover patterns among the attributes of this data. Hence, they can be used to make predictions that can be used by medical practitioners and people at managerial level to make executive decisions. Not all the attributes in the datasets generated are important for training the machine learning algorithms. Some attributes might be irrelevant and some might not affect the outcome of the prediction. Ignoring or removing these irrelevant or less important attributes reduces the burden on machine learning algorithms. In this work two of the prominent dimensionality reduction techniques, Linear Discriminant Analysis (LDA) and Principal Component Analysis (PCA) are investigated on four popular Machine Learning (ML) algorithms, Decision Tree Induction, Support Vector Machine (SVM), Naive Bayes Classifier and Random Forest Classifier using publicly available Cardiotocography (CTG) dataset from University of California and Irvine Machine Learning Repository. The experimentation results prove that PCA outperforms LDA in all the measures. Also, the performance of the classifiers, Decision Tree, Random Forest examined is not affected much by using PCA and LDA.To further analyze the performance of PCA and LDA the eperimentation is carried out on Diabetic Retinopathy (DR) and Intrusion Detection System (IDS) datasets. Experimentation results prove that ML algorithms with PCA produce better results when dimensionality of the datasets is high. When dimensionality of datasets is low it is observed that the ML algorithms without dimensionality reduction yields better results.
•The survey of machine learning algorithms for WSNs from the period 2014 to March 2018.•Machine learning (ML) for WSNs with their advantages, features and limitations.•A statistical survey of ...ML-based algorithms for WSNs.•Reasons to choose a ML techniques to solve issues in WSNs.•The survey proposes a discussion on open issues.
Wireless sensor network (WSN) is one of the most promising technologies for some real-time applications because of its size, cost-effective and easily deployable nature. Due to some external or internal factors, WSN may change dynamically and therefore it requires depreciating dispensable redesign of the network. The traditional WSN approaches have been explicitly programmed which make the networks hard to respond dynamically. To overcome such scenarios, machine learning (ML) techniques can be applied to react accordingly. ML is the process of self-learning from the experiences and acts without human intervention or re-program. The survey of the ML techniques for WSNs is presented in 1, covering period of 2002–2013. In this survey, we present various ML-based algorithms for WSNs with their advantages, drawbacks, and parameters effecting the network lifetime, covering the period from 2014–March 2018. In addition, we also discuss ML algorithms for synchronization, congestion control, mobile sink scheduling and energy harvesting. Finally, we present a statistical analysis of the survey, the reasons for selection of a particular ML techniques to address an issue in WSNs followed by some discussion on the open issues.
Mesenchymal stem cells (MSCs) have immense potential for cell-based therapy of acute and chronic pathological conditions. MSC transplantation for cell-based therapy requires a substantial number of ...cells in the range of 0.5-2.5 × 10
cells/kg body weight of an individual. A prolific source of MSCs followed by in vitro propagation is therefore an absolute prerequisite for clinical applications. Umbilical cord tissue (UCT) is an abundantly available prolific source of MSC that are fetal in nature and have higher potential for ex-vivo expansion. However, the ex-vivo expansion of MSCs using a xenogeneic supplement such as fetal bovine serum (FBS) carries the risk of transmission of zoonotic infections and immunological reactions. We used platelet lysate (PL) as a xeno-free, allogeneic replacement for FBS and compared the biological and functional characteristics of MSC processed and expanded with PL and FBS by explant and enzymatic method. UCT-MSCs expanded using PL displayed typical immunophenotype, plasticity, immunomodulatory property and chromosomal stability. PL supplementation also showed 2-fold increase in MSC yield from explant culture with improved immunomodulatory activity as compared to enzymatically dissociated cultures. In conclusion, PL from expired platelets is a viable alternative to FBS for generating clinically relevant numbers of MSC from explant cultures over enzymatic method.
•Imposition of restriction on people movement plays a vital role in global air quality concentration levels.•The concentration of major air pollutants was measured during lockdown period and compared ...with previous years.•There is a significant reduction in Annual monthly average of air pollutants concentration due to impact of COVID-19.•The outbreak of COVID-19 around the globe was assessed.
It is well known that pandemics not only change people's social habits but have also changed most activities related to energy consumption, especially industry and transport. Over the past year, a plethora of case studies have been published mapping the environmental impacts in specific locations in terms of changes in wastewater composition, noise, solar radiation and more. However, policymakers are demanding a global perspective and are looking for a synthesis of all these reports that will indicate whether, or to what extent, these changes interact with global climate change. The most urgent question is whether artificially inducing such a pandemic could be justified, given the loss of human life and economic losses. Robust analysis on air pollutants such as PM2.5, PM10, NOx, SO2, CO, O3 and NH3 confirmed significant improvement in air quality indicators especially in India and China. The study indicates that key hypotheses can be confirmed or refuted, but further measurements are needed.
Plastic plays a major role in today’s human life; moreover, it becomes a part of our life, yet it is a most challenging threat for the freshwater ecosystems in the future. The present study ...identifies, characterizes, and quantifies the microplastics in groundwater samples around Perungudi and Kodungaiyur municipal solid waste dumpsites in South India. To evaluate and assess the microplastic abundance, characteristics (composite, size, colour, shape, and surface morphology), detection methods of plastic particles, and potential risk factors from the absorption of microplastic in groundwater. Further, the microplastic particle classification was performed using LB-340 Zoom Stereo Microscope with LED Illumination, ATR-FTIR fitted with SEM with EDX analyzer. The groundwater samples (n = 20) were found contaminated with microplastic particles in the range of 2–80 items/L with coloured particles, white (38%), black (27%), green (8%), red (18%), blue (6%), and yellow (2%). The polymer type was found to occur in the following order: nylon (70%), pellets (18%), foam (6%), fragments (3%), fibers/PVC (2%), and polythene (1%). In both sampling sites, 90% of microplastics are derived from the buried plastics and waste fragmentation which are predominantly of polypropylene (PP), polystyrene (PS). Micro and nano plastics abundance in groundwater is of paramount importance as it has a major impact on human health. This study throws light on the characteristics and quantification of the microplastics in groundwater that initiates further research by which microplastics enter into the environment.
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•Microplastics have found in groundwater samples around the solid waste landfills.•Microplastics abundance ranges from different sources 2 to 80 items/L.•The number of microplastics increased with the decreasing of particle size less than 500 μm.•The multi-analytical characteristics and assessing the potential risk of microplastic to human in groundwater developed.
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