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Pollution by end-of-life electronics is a rapid ever-increasing threat and is a universal concern with production of million metric tons of these wastes per annum. Electronic wastes (E-waste) are rejected electric or electronic equipment which have no other applications. The aggrandized unproper land filling of E-waste may generate hazardous effects on living organisms and ecosystem. At present, millions of tons of E-waste await the advancement of more efficient and worthwhile recycling techniques. Recovery of base and critical elements from electronic scraps will not only reduce the mining of these elements from natural resources but also reduces the contamination caused by the hazardous chemicals (mostly organic micropollutants) released from these wastes when unproperly disposed of. Bioleaching is reported to be the most eco-friendly process for metal recycling from spent electronic goods. A detailed investigation of microbial biodiversity and a molecular understanding of the metabolic pathways of bioleaching microorganisms will play a vital function in extraction of valuable minerals from the end-of-life scraps. Bioleaching technique as an economic and green technology costs around 7 USD per kg for effective reusing of E-waste as compared to other physical and chemical techniques. This review provides a summary of worldwide scenario of electronic pollutants; generation, composition and hazardous components of electronic waste; recycling of valuable elements through bioleaching; mechanism of bioleaching; microorganisms involved in base and critical element recovery from E-waste; commercial bioleaching operations; and upcoming aspects of this eco-friendly technique. [ABSTRACT FROM AUTHOR]

Mission-critical applications refer to the real-time applications, which require fast and secure service provisioning, such as defense sector and disaster management. This paper proposes a delay-aware and secure service provisioning model for such types of applications. As a use-case, we have considered the defense sector, which is a vital sector for a country's all-round well-being including security, safety, society, and economy. In the conventional sensor-cloud model, the sensor data is stored and processed in the cloud. However, the sensor nodes have small coverage and the use of the long distant cloud servers increases the delay. Therefore, the conventional sensor-cloud model may not be efficient for defense application. Moreover, data hiding for security purposes is another important aspect of this field. To address these challenges, this paper proposes a mobility-aware sensor-fog paradigm for mission-critical applications based on network coding and steganography, referred to as Mobi-Sense. In Mobi-Sense, steganography is used for hiding the data during transmission. The theoretical results demonstrate that Mobi-Sense outperforms the existing frameworks with respect to delay and power consumption by ∼ (40 - 80) %. The simulation results present that Mobi-Sense reduces the delay by ∼ (18 - 40) % than the conventional sensor-cloud framework for mission-critical applications. An optimal path finding algorithm based on deep learning has been deployed in the context of disaster scenario. The experimental analysis shows that the proposed optimal path finding method achieves precision and accuracy above 90%. This is observed that our proposed modules have outperformed existing baselines in terms of accuracy, delay, and power consumption. [ABSTRACT FROM AUTHOR]

Antibiotic resistance of Mycobacterium tuberculosis is exclusively a consequence of chromosomal mutations. Translesion synthesis (TLS) is a widely conserved mechanism of DNA damage tolerance and mutagenesis, executed by translesion polymerases such as DinBs. In mycobacteria, DnaE2 is the only known agent of TLS and the role of DinB polymerases is unknown. Here we demonstrate that, when overexpressed, DinB1 promotes missense mutations conferring resistance to rifampicin, with a mutational signature distinct from that of DnaE2, and abets insertion and deletion frameshift mutagenesis in homo-oligonucleotide runs. DinB1 is the primary mediator of spontaneous −1 frameshift mutations in homo-oligonucleotide runs whereas DnaE2 and DinBs are redundant in DNA damage-induced −1 frameshift mutagenesis. These results highlight DinB1 and DnaE2 as drivers of mycobacterial genome diversification with relevance to antimicrobial resistance and host adaptation. This manuscript elucidates new mechanisms of mutagenesis in mycobacteria by implicating two translesion DNA polymerases in genome diversification, including creating the mutations that underlie all antibiotic resistance in these global pathogens. [ABSTRACT FROM AUTHOR]

Automatic chronic pain assessment and pain intensity estimation has been attracting growing attention due to its widespread applications. One of the prevalent issues in automatic pain analysis is inadequate balanced expert-labelled data for pain estimation. This work proposes an anomaly detection based network addressing one of the existing limitations of automatic pain assessment. The evaluation of the network is performed on pain intensity estimation and protective behaviour estimation tasks from body movements in the EmoPain Challenge dataset. The EmoPain dataset consists of body part based sensor data for both the tasks. The proposed network, PLAAN (Pain Level Assessment with Anomaly-detection based Network), is a lightweight LSTM-DNN network which considers features based on sensor data as the input and predicts intensity level of pain and presence or absence of protective behaviour in chronic low back pain patients. Joint training considering body movement patterns, such as exercise type, corresponding to pain exhibition as a label improves the performance of the network. However, contrary to perception, protective behaviour rather exists sporadically alongside pain in the EmoPain dataset. This induces yet another complication in accurate estimation of protective behaviour. This problem is resolved by incorporating anomaly detection in the network. A detailed comparison of different networks with varied features is outlined in the paper, presenting a significant improvement with the final proposed anomaly detection based network. [ABSTRACT FROM AUTHOR]

There has been alarming depletion of manganese (Mn) reserves owing to the ongoing extensive mining operations for catering the massive industrial demand of this element. Moreover, the mining operations have been leading to the generation of Mn-rich waste, thereby contaminating both terrestrial and aquatic bodies. The current scenario necessitates the development of alternative processes for bioremediation as well as economic recovery of Mn from mining wastes. The present investigation aims to report the bioleaching of Mn by Lysinibacillus sp. from mining waste residues in the context of mine waste remediation. Results confirmed that the native isolate had a high Mn biosolubilization potential with a solubilizing efficiency of 84% at the end of a 21-day study under optimized conditions of pulp density 2% (< 150-μm particle size), pH 6.5, and temperature 30 °C. Fourier transform infrared spectroscopy (FTIR) studies followed by liquid chromatography mass spectrometry (LC-MS) analysis were used to ascertain the change in microbial protein conformation, configuration, and protein identification. The results revealed the expression of heat shock proteins (HSP) from the family HSP which is predominantly expressed in bacteria during stress conditions. This study represents the application of native bacterial strain in Mn biosolubilization. We foresee the utility of proteomics-based studies to provide a methodological framework to the underlying mechanism of metal solubilization, thereby facilitating the two-tier benefit of recovery of Mn from alternative sources as well as bioremediation of waste having high manganese content. [ABSTRACT FROM AUTHOR]

This paper proposes a mobile healthcare framework based on edge-fog-cloud collaborative network. It uses edge and fog devices for parameterized health monitoring, and cloud for further health data analysis in case of abnormal health status. The continuous location change of users is a critical issue, and the connection interruption and delay in delivering health related data may be fatal in case of emergency. In this direction, in the proposed framework, mobility information of the users is considered and the users' mobility pattern detection is performed inside the cloud for advising the user regarding nearby health centre. From the theoretical analysis, it is observed that the proposed framework reduces the delay and energy consumption of user device by ∼ 28 % and ∼ 27 % respectively than the cloud only health care model. The proposed healthcare framework has been implemented in the laboratory and health data of few student volunteers are analyzed to predict their health status. The experimental analysis also shows that the proposed mobility prediction model has better precision, recall value and time-efficiency than the existing models. [ABSTRACT FROM AUTHOR]

This paper presents a study of the response of FRET based DNA aptasensors in the intracellular environment. Herein, we extend previous studies of aptasensors functioning in the extracellular environment to detection of antigens in the intracellular environment. An essential step in this research is the use of a novel means of achieving the endocytosis of aptasensors. Specifically, it is demonstrated that functioning aptasensors are successfully endocytosed by functionalizing the aptasensors with endocytosis—inducing DSS peptides. [ABSTRACT FROM AUTHOR]

The global consumption of manganese is rising due to its growing industrial requirement while the natural reserves of manganese are diminishing at an alarming rate. Consequently, recovery of manganese from metal containing wastes has become highly crucial. Bioleaching of metal from wastes using microbes provides an adequate advantage over the traditional method of recovery. A molecular level understanding of microbial catalyzed manganese recovery is essential for the exploitation of novel microorganisms for similar applications. In current scenario, the application of bioleaching concentrates on cost effective and eco-friendly recovery of precious metals from mining and industrial wastes. This review encompasses the modern improvements in biomining, highlights the comprehensive factors that emphasize the selection of manganese recovery technique, shed insights into spectacular progress in developing molecular based technologies and also identifies the applicability of different models in metal bioremediation which will not only aid in pollution abatement but also in the prevention of occupational health disorder. [ABSTRACT FROM AUTHOR]

An amendment to this paper has been published and can be accessed via a link at the top of the paper. [ABSTRACT FROM AUTHOR]

S100A12 or Calgranulin C is a homodimeric antimicrobial protein of the S100 family of EF-hand calcium-modulated proteins. S100A12 is involved in many diseases such as inflammation, tumor invasion, cancer and neurological disorders such as Alzheimer’s disease. The binding of transition metal ions to the protein is important as the sequestering of the metal ion induces conformational changes in the protein, inhibiting the growth of various pathogenic microorganisms. In this work, we probe the Cu2+ binding properties of Calgranulin C. We demonstrate that the two Cu2+ binding sites in Calgranulin C show different coordination environments in solution. Continuous wave-electron spin resonance (CW-ESR) spectra of Cu2+-bound protein clearly show two distinct components at higher Cu2+:protein ratios, which is indicative of the two different binding environments for the Cu2+ ions. The g|| and A|| values are also different for the two components, indicating that the number of directly coordinated nitrogen in each site differs. Furthermore, we perform CW-ESR titrations to obtain the binding affinity of the Ca2+-loaded protein to Cu2+ ions. We observe a positive cooperativity in binding of the two Cu2+ ions. To further probe the Cu2+ coordination, we also perform electron spin echo envelope modulation (ESEEM) experiment. We perform ESEEM at two different fields where one Cu2+ binding site dominates the other. At both sites we see distinct signatures of Cu2+-histidine coordination. However, we clearly see that the ESEEM spectra corresponding to the two Cu2+ binding sites are significantly different. There is clear change in the intensity of the double quantum peak with respect to the nuclear quadrupole interaction peak at the two different fields. Furthermore, ESEEM along with hyperfine sublevel correlation show that only one of the two Cu2+ binding sites has backbone coordination, confirming our previous observation. Finally, we perform double electron-electron resonance spectroscopy to probe if the difference in binding environment is due to the Cu2+ binding to different sites in the protein. We obtain a distance distribution with a sharp peak at ~ 3 nm and a broad peak at ~ 4 nm. The shorter distance agrees with the Cu2+-Cu2+ distance expected for a dimer from the crystal structure. The longer distance is consistent with the Cu2+-Cu2+ distance when oligomerization occurs. [ABSTRACT FROM AUTHOR]

Spin labels attached to two residues of a protein chain have less conformational flexibility than those attached to a single residue and thus lead to a narrower spatial distribution of the unpaired electron. The case of Cu2+ labels based on the double-histidine (dHis) motif is of particular interest, as it combines the advantage of precise localization of the unpaired electron with a labelling scheme orthogonal to the more common cysteine-based labelling. Here, we introduce an approach for in silico spin labelling of a protein by dHis motifs and Cu2+ complexes of iminodiacetic acid or nitrilotriacetic acid. We discuss a computerized scan for native histidine pairs that might be prone to bind such Cu2+ complexes and spin-labelling site pair scans that can identify suitable double mutants for labelling. Predicted distance distributions between two Cu2+ labels are compared to experimental distance distributions. We also test the hypothesis that elastic network modelling of conformational transitions with Cu2+-dHis labels can provide more accurate structural models than with nitroxide labels. [ABSTRACT FROM AUTHOR]

Translation of genes is regulated by many factors including microRNAs (miRNAs). miRNA profiling of lesional and non-lesional epidermal RNA from 18 vitiligo patients revealed significant upregulation of 29 miRNAs in the lesional epidermis, of which 6 miRNAs were transfected in normal human epidermal keratinocytes (NHEKs) to study their downstream effects using quantitative proteomics. Many proteins involved in oxidative stress, Vesicle trafficking, Cellular apoptosis, Mitochondrial proteins and Keratins were regulated after miRNA transfections in the keratinocytes. However, tyrosinase related protein-1 (TRP1/TYRP1), a melanogenesis protein, was consistently downregulated in NHEKs by all the six miRNAs tested, which was quite intriguing. TRP1 was also downregulated in lesional epidermis compared with non-lesional epidermis. Since melanocytes synthesize and transfer melanosomes to the surrounding keratinocytes, we hypothesized that downregulation of TRP1 in NHEKs may have a role in melanosome transfer, which was confirmed by our co-culture experiments. Downregulation of TRP1 in keratinocytes negatively affected the melanosome transfer from melanocytes to keratinocytes resulting in melanin accumulation which may be leading to melanin induced cytotoxicity in melanocytes. Regulation of key processes involved in aetiopathogenesis of vitiligo along with TRP1 suggests that miRNAs act in an integrated manner which may be detrimental for the loss of melanocytes in vitiligo. [ABSTRACT FROM AUTHOR]