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  Subjects -> SCIENCES: COMPREHENSIVE WORKS (Total: 374 journals)
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Proceedings of the Indian National Science Academy
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ISSN (Print) 0370-0046 - ISSN (Online) 2454-9983
Published by Springer-Verlag Homepage  [2469 journals]
  • Hepatogenic differentiation of adipose-derived mesenchymal stem cells
           directed by topographical cues: a proof of concept study

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      Abstract: Abstract Topography and roughness are key features that can direct the behavior of cells. Here, we have developed a surface pattern comparable to the features and roughness present in the native liver tissue by virtue of the liver extracellular matrix. This study used polydimethylsiloxane to get an imprint of the topographical pattern of the native liver and used this imprint as a template to guide the differentiation of adipose-derived mesenchymal stem cells. The results showed a similar gene and protein expression profile to that of hepatocytes, showing potential in the field of scaffold development for tissue engineering applications.
      PubDate: 2022-08-08
       
  • Electrochemical sensor for picric acid by using molecularly imprinted
           polymer and reduced graphene oxide modified pencil graphite electrode

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      Abstract: Abstract Here we report an electrochemical sensor for the determination of picric acid (PA) based on molecularly imprinted polymer (MIP) on reduced graphene oxide (rGO) coated pencil graphite electrode (PGE). Pyrrole (Py) was electropolymerized on the surface of rGO modified PGE, where PA was used as the template. After the extraction of PA molecules from the polymer matrix, MIP rGO PGE was obtained. Computational studies were carried out to predict the possible molecular interactions between template and polymer. The electrode modifications were characterized by various electrochemical and surface imaging techniques. The MIP rGO PGE shows linear response over PA concentration on differential pulse voltammetric (DPV) analysis with good reproducibility. MIP rGO PGE has significant mechanical stability with detection limits of 1.4 μM. The proposed sensor was applied to quantify the PA level present in the soil and water as real analytical samples successfully.
      PubDate: 2022-08-04
       
  • RNA nucleoprotein complexes in biological systems

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      Abstract: Abstract RNA-nucleoprotein (RNP) complexes are pivotal to the regulation of gene expression. These multiprotein, multifunctional complexes act as scaffolds, as molecular platforms, as hubs of interaction between the RNA and the proteins. The past decade has seen an exponential increase in the methodologies to identify and functionally characterize these complexes. In this review, we provide an overview of the recent advances in methodologies and the knowledge gained by characterizing these important complexes. This information has provided clues to the role of sequence, and structural determinants for RNA–Protein interaction networks in physiology and pathophysiology. With the recent studies implicating the role of RNA in the formation of biomolecular condensates, their role in health and disease warrants detailed sequence, structure and functional investigations.
      PubDate: 2022-08-03
       
  • Dehydration stress influences the expression of brevis radix gene family
           members in sorghum (Sorghum bicolor)

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      Abstract: Abstract Brevis radix (BRX) constitutes a small gene family in angiosperms. It was first identified in Arabidopsis thaliana where it contributed to cell proliferation and root elongation. New roles of BRX family members in plant developmental processes and abiotic stress tolerance are getting revealed lately. In this study, we have identified six members belonging to the BRX gene family from Sorghum bicolor. Based on similarity analysis, two each of these members were found to be belonging to BRXL1 (Sobic.007G151500, Sobic.002G218600) and BRXL2 (Sobic.006G203200, Sobic.004G270100) classes and one was of BRXL4 (Sobic.001G008400) class. The sixth member (Sobic.006G117900) with a partial amino acid sequence was a pseudogene. All members except Sobic.006G117900 and Sobic.006G203200 had three conserved BRX domains. The number of exons of the members ranged from 3 to 6 and protein length from 313 to 469aa. All proteins had nuclear localization signals in them. Drought stress imposed on M35-1 genotype of sorghum for a duration of 7 days and 14 days brought about observable changes in root morphology. Mean root length per seedling significantly increased in the drought stressed seedlings. Expression analysis of sorghum BRX members using quantitative PCR showed enhanced expression of all members in drought stressed leaf as well as root tissues. While in leaves the expression of all BRX genes were up-regulated as duration of drought stress increased, only Sobic.007G151500 and Sobic.002G218600 showed enhanced expression in 14-day drought in the roots. Members of BRX gene family may be involved in drought tolerance in sorghum.
      PubDate: 2022-08-03
       
  • Spectroscopic characterization, molecular structure, NBO analysis,
           dielectric studies and biological activities of 4-(3-aminophenyl)
           benzonitrile

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      Abstract: Abstract The molecular structure of 4-(3-aminophenyl)benzonitrile (AP-PhCN) were studied with Density Functional Theory. The calculated wavenumbers can be well supported by the experimental analysis of the vibrational modes of 4-(3-aminophenyl)benzonitrile. The complete assignments of AP-PhCN have been performed on the basis of experimental data and potential energy distribution (PED) of the vibrational modes. Through natural bond orbital (NBO) analysis, the charge delocalization within the molecule has been studied.The molecular electrostatic potential (MEP) map shows various active regions of the charge distribution on the chemical structure. In addition, dielectric quantities like dielectric constant at microwave frequency, optical frequency, relaxation time and static dielectric constant have also been determined. The results indicate the heterointeraction arises owing to the hydrogen bonding made between the C≡N of AP-PhCN and –OH group. Further, thermodynamic properties such as enthalphy and entropy have also been investigated. The molecular docking studies are also performed to explore the interaction between the AP-PhCN and Influenza endonuclease inhibitor.
      PubDate: 2022-08-02
       
  • MALDI-TOF MS: application in diagnosis, dereplication, biomolecule
           profiling and microbial ecology

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      Abstract: Abstract Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) has revolutionized scientific research over the past few decades and has provided a unique platform in ongoing technological developments. Undoubtedly, there has been a bloom chiefly in the field of biological sciences with this emerging technology, and has enabled researchers to generate critical data in the field of disease diagnoses, drug development, dereplication. It has received well acceptance in the field of microbial identification even at strain level, as well as diversified field like biomolecule profiling (proteomics and lipidomics) has evolved tremendously. Additionally, this approach has received a lot more attention over conventional technologies due to its high throughput, speed, and cost effectiveness. This review aims to provide a detailed insight regarding the application of MALDI-TOF MS in the context of medicine, biomolecule profiling, dereplication, and microbial ecology. In general, the expansion in the application of this technology and new advancements it has made in the field of science and technology has been highlighted.
      PubDate: 2022-08-01
       
  • Colorectal cancer: risk factors and potential of dietary probiotics in its
           prevention

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      Abstract: Abstract Cancer is the leading cause of human death worldwide. In spite of medical advancements, cancer cases are rising globally where Colorectal Cancer (CRC) frequency is third in position in males and second in females. Colorectal cancer (CRC) is a disease where abnormal growth of cells occurs in the colon and rectal area of the alimentary canal. Factors like food habits, smoking, alcohol consumption, obesity, gut dysbiosis, etc. increase CRC risk. The CRC patients suffer not only from painful surgical treatments but also bear the side effects of palliative radiotherapy, chemotherapy, and therapeutic drugs used for the same. Dietary probiotics have great potential in the prevention and management of CRC due to their anticancer properties. The present review discusses the various risk factors of colorectal cancer and important role of probiotic supplements to prevent it. It highlights some of the proposed mechanisms of probiotics for their protective role against CRC. The prevention through modifiable risk factors and probiotic dietary supplements can save the patients from the trauma of the disease. Probiotics regulate gut dysbiosis and prevent CRC through different mechanisms, so more research work and clinical trials in humans with respect to it are expected in the future.
      PubDate: 2022-07-07
       
  • Belousov–Zhabotinsky reaction: an open-source approach

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      Abstract: Abstract The time-dependent change in concentration of reactants in the oscillatory Belousov–Zhabotinsky reaction defined by non-linear ordinary coupled differential equations has been derived by applying normalized non-dimensional computational methods and presented graphically. The accurate normalisation procedure eschews complex mathematical steps; however, choosing the appropriate references to define the dimensionless variables necessitates a deep physical understanding of the problem. The dimensionless groups are then derived to provide the functional dependences of the unknowns of interest. Finally, to cross-check all the mentioned dependences, a computational simulation has been carried out using domain-specific to general-purpose programming languages. Although there are countless programming languages present to carry out computer simulations, a flexible, portable, and open-source language like python proves fruitful.
      PubDate: 2022-06-27
       
  • Communication between immune system and mycobiota impacts health and
           disease

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      Abstract: Abstract Fungi are the organisms present universally in the environment from ancient times. Being regarded as an essential part of human mycobiome either as commensals or as opportunistic pathogens they hold a spectacular place in our lives. Mycobiome is growing as a field of interest, but some questions still remain lurking like how fungi exactly modulate health and disease. Most of the studies focus on the interactions of the immune system with the bacterial and viral community rather than highlighting the communication with mycobiota. Crosstalk between the immune system and mycobiota have been found to be highly necessary for maintaining homeostasis, preventing susceptibility towards diseases, inducing immune tolerance, modulating microbial communities and generating signal responses by interacting with fungal molecular patterns. We are highlighting the latest advancement regarding the relationship of innate and adaptive branches of immunity with mycobiota, their role ranging from simple commensals to opportunistic pathogens and more importantly therapies designed to overcome fungal infections in this review.
      PubDate: 2022-06-23
       
  • Analysis of support vector machine and maximum likelihood classifiers in
           land cover classification using Sentinel-2 images

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      Abstract: Abstract Remote sensing data has been widely applied to classify the land cover more frequently and on a near real-time basis for updating as it is more economic, less time consuming compared to ground based survey. Accurate classification of the land use/cover classes such as water body, cropland, built-up area, scrub land, fallow land, forest etc., is one of the biggest challenges in natural resource inventory, management and monitoring. As accuracy of remote sensing data classification is affected by many parameters which include type of data, presence of heterogeneous landscapes in study area, classification approaches etc., as satellite imagery is complex in nature. Many classifiers have been developed and tested on remotely sensed data for better classification. Classification of remote sensing data is mainly divided into two categories such as supervised and unsupervised. In supervised classification, the decision boundaries in feature space are determined by training the samples. Two supervised classifiers namely maximum likelihood (ML) classifier, which is a parametric classifier that assumes data to be normally distributed, and support vector machine classifier (SVM) which is a non-parametric classifier are used in classification. In the present study, the accuracy of these two classifiers is studied on five different data sets of Sentinel-2 satellite image of different years and sessions to accommodate intra and inter annual variations of the datasets. Sentinel-2 satellite images covering part of Nagpur, located in Maharashtra, India were used for the classification. Classifier accuracy has been calculated using overall accuracy and kappa statistics based on ground truth information. The result obtained were carefully examined by comparing classification accuracies and then by visual analysis. The result shows that SVM classifiers gives better overall accuracy and kappa coefficients and its average value for intra and inter annual classification outputs were 91.78% and 0.89 in that order which is far better than ML classifier which gave 87.07% and 0.83 respectively. The experimental results obtained from the present study, it is clear that SVM classifier produced better accuracy than ML classifier in classifying Sentinel-2 optical image and have significant potential in classifying various land cover classes in the heterogeneous land use/land cover conditions of the tropical regime.
      PubDate: 2022-06-10
       
  • Research on monitoring overground carbon stock of forest vegetation
           communities based on remote sensing technology

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      Abstract: Abstract The monitoring of forest carbon stocks provides a better understanding of the carbon sequestration capacity of forests. This paper took forest vegetation communities in Henan as an example and extracted waveband information, texture features and vegetation features from Landsat8 remote sensing image data as modeling factors to establish a multiple regression model and a back-propagation neural network (BPNN) model for overground carbon stock. It was found that the BPNN model had a \({R}^{2}\) value value 0.678, a relative error of − 1.89%, and a root-mean-square error value of 13.21 t/hm2, indicating higher accuracy and more accurate estimation of overground carbon stock. The results verify the reliability of the remote sensing technology and the BPNN model in monitoring overground carbon stock, providing some theoretical bases for research on the carbon fixation capability of forest vegetation communities.
      PubDate: 2022-06-09
       
  • Deep neural network based fruit identification and grading system for
           precision agriculture

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      Abstract: Abstract Precision agriculture is a systematic scientific way of farming with an aim to increase yield in terms of quality and quantity, ensure profitability, sustainability, and protection of the environment through optimum use of resources. Fruit quality is associated with several factors such as freshness level, vitamin content, nutritional content, etc. Grading of fruits is an important process as it ensures exact characteristics and helps in regulating price as per quality. With an increased demand for quality fruits, automated fruit grading systems are required to support the farmers and to maintain a sound pricing scheme in the market. This paper presents an automated fruit grading scheme based on deep neural networks. A convolutional neural network structure is proposed and compared with transfer learning-based models for grading the fruit images in the ‘Kaggle’ dataset. Remarkable results are achieved with the proposed as well as with the 4 pre-trained models, i.e., ResNet-50, VGG-16 & 19, and Inception-ResNet V2. Further the results are also compared with that obtained from the support vector machine classifier. For comparison of all these models, the input data is same i.e., intensities of the pixels in the input image. A user interface demonstration module is generated to demonstrate how it can be useful to the farmers for sorting their products.
      PubDate: 2022-05-10
      DOI: 10.1007/s43538-022-00079-0
       
  • An update on medicinal plants traditionally used to treat diabetes in
           southeast Sikkim, India

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      Abstract: Abstract Sikkim, a Himalayan state of India, is known for its rich flora and fauna, and is one of the biodiversity hot spots in the Eastern Himalayas. Local people of Sikkim are largely dependent on plant-based medicines for the treatment of diabetes. This study documents traditional knowledge on plants with hypoglycemic effects from a field survey in 23 villages of East and South districts of Sikkim. In total 50 species of medicinal plants belonging to 36 families were found to be used by the traditional healers and local people to control diabetes. This updated survey revealed plant names which were not found in earlier surveys from this region for example, Smallanthus sonchifolius, Nyctanthes arbor-tristis, Abelmoschus esculentus etc. Further, antidiabetic potential of these plants was assessed from the lab-based findings documented in literature. It was found that 75% of the plants had anti-diabetic potential. The plants could be further validated for new drug molecules for diabetes from natural origin. For approximately 25% of the plants, however, laboratory-based data for their antidiabetic property were not found. This offers opportunity to experimentally assess their antidiabetic property and to characterize their active compounds.
      PubDate: 2022-05-04
      DOI: 10.1007/s43538-022-00074-5
       
  • What makes the beans (Phaseolus vulgaris L.) soft: insights into the
           delayed cooking and hard to cook trait

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      Abstract: Abstract Cooking quality has recently piqued the interest of bean researchers due to its implications for energy, nutrition, and gender equity and carbon footprints. Cooking imparts unique sensory characteristics, improves digestibility, reduces anti-nutritional factors, and boosts nutritional and biological value in beans. Delayed and hard to cook (HTC) traits result in extended cooking time to confer desired texture. Cooking has a complex mechanistic basis ranging from water imbibition to complex micro and macro structural (impermeable seed coat) and biochemical mechanisms (pectin-cations, lignification, phenols, starch and protein alterations, lipid polymerization, non-starch polysaccharides) that result in hard to cook trait. The mechanistic events leading to water uptake and seed softening may be a useful high throughput assay for genotypic screening for delayed cooking and HTC trait. Cooking time is largely under additive genetic control with high heritability and fast cooking is dominant over slow cooking trait. Use of molecular and genomics approaches has led to identification of various genomic regions on chromosome 1, 2, 3, 5, 6, 7 and 9 associated with cooking time, coding for various cooking related genes such as cystatin/monellin superfamily protein, tonoplast dicarboxylate transporter, acyl-CoA sterol acyl transferase and polygalacturonase. This review discusses, mechanistic insights, genetics and genomics information about delayed cooking and hard to cook trait, that will help breeders to improve cooking quality in beans using effective surrogate traits based on seed physical, biochemical, water absorption and microstructural parameters.
      PubDate: 2022-05-02
      DOI: 10.1007/s43538-022-00075-4
       
  • Climate change and its impact on biodiversity and human welfare

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      Abstract: Abstract Climate change refers to the long-term changes in temperature and weather due to human activities. Increase in average global temperature and extreme and unpredictable weather are the most common manifestations of climate change. In recent years, it has acquired the importance of global emergency and affecting not only the wellbeing of humans but also the sustainability of other lifeforms. Enormous increase in the emission of greenhouse gases (CO2, methane and nitrous oxide) in recent decades largely due to burning of coal and fossil fuels, and deforestation are the main drivers of climate change. Marked increase in the frequency and intensity of natural disasters, rise in sea level, decrease in crop productivity and loss of biodiversity are the main consequences of climate change. Obvious mitigation measures include significant reduction in the emission of greenhouse gases and increase in the forest cover of the landmass. Conference of Parties (COP 21), held in Paris in 2015 adapted, as a legally binding treaty, to limit global warming to well below 2 °C, preferably to 1.5 °C by 2100, compared to pre-industrial levels. However, under the present emission scenario, the world is heading for a 3–4 °C warming by the end of the century. This was discussed further in COP 26 held in Glasgow in November 2021; many countries pledged to reach net zero carbon emission by 2050 and to end deforestation, essential requirements to keep 1.5 °C target. However, even with implementation of these pledges, the rise is expected to be around 2.4 °C. Additional measures are urgently needed to realize the goal of limiting temperature rise to 1.5 °C and to sustain biodiversity and human welfare.
      PubDate: 2022-05-02
      DOI: 10.1007/s43538-022-00073-6
       
  • Comparative multifractal analysis of methane gas concentration time series
           in India and regions within India

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      Abstract: Abstract In the present study GOSAT CH4 has been used to analyze the methane gas concentration in India over the eight years from 2010 to 2017. The data have been analyzed using the multifractal detrended fluctuation analysis technique. Two different geographical regions within India have been selected and CH4 data for those regions are also analyzed. The generalized Hurst exponents for India and the two regions are 1.27, 0.74 and 0.91, which are significantly high from their shuffled data counterparts i.e. 0.50, 0.51 and 0.51 respectively. This finding reveals that methane gas concentration over time show multifractal nature which in turn establishes the presence of long-range temporal correlations in the data. The width of the Multifractal spectrum for India and the two regions are found to be 0.76, 1.38 and 1.01 respectively. This result shows that strength of correlation is different for the two regions selected, which we suggest may be due to the different methane emission process of the considered regions. Comparison of the results with that of shuffled data signify that the correlation is purely due to the methane production dynamics and not a result of mere statistics.
      PubDate: 2022-05-02
      DOI: 10.1007/s43538-022-00076-3
       
  • Digital soil mapping of PAU-Regional Research Station, Kapurthala, Punjab,
           India

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      Abstract: Abstract Digital soil mapping is an invention that uses modern technologies to express geographical soil information. Across the country, there has been a transition of digital soil mapping from the research phase to the operational phase, but no comprehensive research has been conducted at the Regional Research Station in Kapurthala. Instead of dealing with the whole field as a single unit, dealing with small units per spatial soil properties is the first step towards sustainable agriculture. However, all soil's spatial variations could not be corrected with one blanket recommendation. Considering this in mind, the current investigation carried out the research station with 84.4 ha of agricultural land comprising eight blocks, with an objective of delineating the spatial variation in soil properties viz. soil organic carbon (%), electrical conductivity, pH, available Phosphorus, potash, zinc, iron, manganese, and copper (mg kg−1), respectively on to the soil maps prepared using geo-statistics. Finally, digital soil mapping (DSM) was prepared for dealing with such spatial soil variation after preparing the base maps using GPS-60 (GARMIN). For this purpose, 40 representative spatial soil samples were collected from all the blocks. DSM delineated that most spots are low in SOC at the farm while available P, K, and Cu are sufficiently available. Further, the micronutrients DTPA-Zn, Fe, and Mn, were reported with spatial deficiencies in different blocks. Therefore, these recommendations help in the more sustainable and judicious use of the fertilizers on one side while also helping in controlling micronutrient deficiencies before their symptoms appear. Henceforth, DSM must be prepared and is a prerequisite to achieving sustainability in any soil–plant interphase despite any agro-climatic zone and soil textural class to improve soil health and practice sustainable agriculture at the farm.
      PubDate: 2022-04-28
      DOI: 10.1007/s43538-022-00077-2
       
  • Fluoride occurrence, health issues, and removal using adsorption process

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      Abstract: Abstract Safe drinking water is a key ingredient to a sustainable life for mankind. Fluoride is considered a micronutrient required in a minute quantity for the proper functioning of bones and teeth in humans. However, its higher concentration could lead to toxic effects on skeletal and dental health. The amount of fluoride required can be easily achieved through the consumption of vegetables, cereals, and drinking water (within desirable limits). Fluoride beyond the limits in groundwater has become a major issue in most of the states of India while Rajasthan has been considered as most severely affected with fluorosis where all the districts were reported with a high concentration of fluoride in groundwater. Adsorption technique was recently developed as a low-cost method that can potentially remove excess fluoride from groundwater. Numerous adsorbent developed so far has been discussed in this review to explore their potential for defluoridation. The ability of this method greatly depends on the development of adsorptive materials. It was found after the literature survey that several types of adsorbent using chemicals as well as vegetative waste have been developed and studied to quantify the removal capacity of fluoride from water. However, their utility on the water is still needed to be studied to explore these adsorbents for commercial use leading to the improvement in water quality.
      PubDate: 2022-04-19
      DOI: 10.1007/s43538-022-00071-8
       
  • Possible catalytic activity of N,N-coordinated mono-cationic copper bound
           Pyrazol-1-yl(1H-pyrrol-2-yl)methanone complex: a computational study

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      Abstract: Abstract Organic ligand-based transition metal coordinated complexes have been of paramount importance. They have found a lot of utilities in catalysis, bond activation, dye-sensitized solar cells, etc. Focusing on the so-called noble metal or coinage metal and keeping in mind the inexpensive single metal atom based catalyst, copper bound complexes are considered for adsorption of gas molecules and bond activation therein. Here, we have studied the interaction between a [Cu–NN] complex (N,N-coordinated mono-cationic copper bound Pyrazol-1-yl(1H-pyrrol-2-yl)methanone) and different gas molecules as ligands, such as L = H2, N2, CO, H2O, C2H4 and C2H2, which are industrially and environmentally important. Our computational investigation infers that these ligands are effective in electronic interactions and optical properties of the complex. The stability, geometry and the bonding nature in L bound [Cu–NN] complexes are studied to check their viability at room temperature. The [Cu–NN] complex can bind small gas molecules as ligands, viz., H2, N2, CO, H2O, C2H4 and C2H2, in a thermodynamically favorable way and the complexation induces bond activation within the ligands in the bound state as compared to their free state. All the [L–Cu–NN] complexes along with the bare complex show broadband optical absorption in the ultraviolet–visible (UV–Vis) domains. Furthermore, selective ligand binding has modulated the Fermi energy level resulting in an enhanced chemical reactivity of the [Cu–NN] complex.
      PubDate: 2022-04-14
      DOI: 10.1007/s43538-022-00072-7
       
  • The influence of COVID-19 pandemic on biomedical waste management, the
           impact beyond infection

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      Abstract: Abstract Excessive population outbursts and associated xenobiotic interventions contribute overproduction of waste materials across the world. Among these waste materials biomedical wastes (BMW) make a significant contribution. The huge accumulation of BMW is not only meant for successive environmental pollution but increases health hazards by cross-contamination and reoccurrence of different fatal infections. The management of BMW gaining continuous attention to the scientific communities for their intriguing potentiality towards public health concerns. Although, world health organization (WHO) and other public health and environmental societies formulate different guidelines for the disposal machinery of BMW but the proper implementation of those rules in public sectors in developing countries is very difficult. In this situation, the sudden prevalence of pandemic like, COVID-19 further worsen such conditions. Huge disposition of medical wastes during COVID-19 detection, treatment, and precautionary measures not only increases the risk of reoccurrence of infection but puts us also in front of a huge challenge of efficient management of these BMW. In this respect, the present review focus on an overview of BMW, existing BMW management, probable consequences of COVID-19 pandemic on the waste management system, and future perspectives.
      PubDate: 2022-03-10
      DOI: 10.1007/s43538-022-00070-9
       
 
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