Boronic acid‐containing molecules are substantially popularized in chemical biology and medicinal chemistry due to the broad spectrum of covalent conjugations as well as interaction modules offered ...by the versatile boron atom. Apparently, the WGA peptide (wheat germ agglutinin, 62–73), which shows a considerably low binding affinity to sialic acid, turned into a selective and >5 folds potent binder with the aid of a suitable boronic acid probe installed chemoselectively. In silico studies prompted us to install BA probes on the cysteine residue, supposedly located in close proximity to the bound sialic acid. In vitro studies revealed that the tailored boronopeptides show enhanced binding ability due to the synergistic recognition governed by selective non‐covalent interactions and cis‐diol boronic acid conjugation. The intense binding is observed even in 10 % serum, thus enabling profiling of sialyl‐glycan on cancer cells, as compared with the widely used lectin, Sambucus nigra. The synergistic binding mode between the best boronopeptide (P3) binder and sialic acid was analyzed via 1H and 11B NMR.
This investigation demonstrates that the appropriate positioning of a customized boronic acid probe into a sialic acid binding epitope leverages a selective and potent binder of sialyl‐glycan. Such synergistic peptide probe is promising in clinical oncology for diagnosis.
Boron was misconstrued as a toxic element for animals, which retarded the growth of boron-containing drug discovery in the last century. Nevertheless, modern applications of boronic acid derivatives ...are attractive in biomedical applications after the declaration that boron is a 'probable essential element' for humans by the WHO. Additionally, the approval of five boronic acid-containing drugs by the FDA has vastly impacted the use of boron in medicinal chemistry, chemical biology, drug delivery, biomaterial exploration, pharmacological improvements, and nutrition. This review article focuses on the chemistries attributed to boronic acids at physiological pH, enticing chemists to multidisciplinary applications. Prospective uses of boronic acid in pharma and chemical biology, along with prospects and challenges, are also part of the deliberation. Understanding these fundamental chemistries and interactions of boronic acid in biological systems will enable solving future challenges in drug discovery and executing space-age applications.
▸ A stable, label-free, bacteriophage-based detection of E. coli using ultra sensitive long-period gratings is demonstrated. ▸ E. coli binding by covalently immobilized bacteriophage T4 is ...investigated using the spectral interrogation mechanism. ▸ No moving part or metallization is required in our sensor, making it extremely accurate, very compact and cost effective. ▸ The detection mechanism is capable of reliable detection of E. coli concentrations as low as 103cfu/ml with an experimental accuracy > 99%. ▸ We present the SEM images to confirm a reliable binding of E. coli bacteria to the optical fiber surface.
In this paper we report a stable, label-free, bacteriophage-based detection of Escherichia coli (E. coli) using ultra sensitive long-period fiber gratings (LPFGs). Bacteriophage T4 was covalently immobilized on optical fiber surface and the E. coli binding was investigated using the highly accurate spectral interrogation mechanism. In contrast to the widely used surface plasmon resonance (SPR) based sensors, no moving part or metal deposition is required in our sensor, making the present sensor extremely accurate, very compact and cost effective. We demonstrated that our detection mechanism is capable of reliable detection of E. coli concentrations as low as 103cfu/ml with an experimental accuracy greater than 99%.
Unnao has a large number of tanneries and huge amount of waste water is generated and there effluents contain Chromium, which infiltrates and percolates below the ground and contaminate the surface ...and subsurface water, thereby creating a possibility of becoming a potent carcinogenic. Chromium is present in different forms, trivalent and hexavalent being the prevalent ones. Cr(III) has low solubility whereas Cr(VI) has high solubility and can easily move through the groundwater and get mixed with it. Present paper is based upon the collection of 47 samples from Unnao district of Uttar Pradesh (India), which were tested for pH, Electrical Conductivity, hexavalent Chromium and total Chromium. The concentration of Cr(VI) for one of the sites (Dharamkata) was found to be 2070 µg/l; which has a high efficacy to contaminate the unlined channels, thereby causing contamination of surface and groundwater. In order to remediate the problem, different bio-waste materials were used for the removal of Cr(VI). The concentration of Cr(VI) and total Chromium were determined by Diphenylcarbazide method and ICP-OES. Hexavalent Chromium is highly oxidizing in nature and requires electron donor materials for reduction. The research utilized bio-wastes like coir pith, sawdust, rice husk and vermiculite (natural mineral) to reduce Chromium. An effluent sample having Chromium concentration, 184.8 mg/l was passed through columns having different bio-absorbent medium, out of which bio-absorbents and vermiculite combination was found to be more capable of reducing hexavalent Chromium from the sample. An outstanding decrease in concentration of total Chromium (184.8–4.48 mg/l) is accomplished by the combination of vermiculite and coir pith. This shows that natural wastes are very likely the absorbents of Cr(VI), which can be used to decrease the concentrations of Chromium from the contaminated water.
We present an updated model of light and charge yields from nuclear recoils in liquid xenon with a simultaneously constrained parameter set. A global analysis is performed using measurements of ...electron and photon yields compiled from all available historical data, as well as measurements of the ratio of the two. These data sweep over energies from 1 - 300 keV and external applied electric fields from 0 - 4060 V/cm. The model is constrained by constructing global cost functions and using a simulated annealing algorithm and a Markov Chain Monte Carlo approach to optimize and find confidence intervals on all free parameters in the model. This analysis contrasts with previous work in that we do not unnecessarily exclude data sets nor impose artificially conservative assumptions, do not use spline functions, and reduce the number of parameters used in NEST v0.98. We report our results and the calculated best-fit charge and light yields. These quantities are crucial to understanding the response of liquid xenon detectors in the energy regime important for rare event searches such as the direct detection of dark matter particles.
This edited book is intended to serve as a resource for engineers, researchers, scientists and experts wishing to become familiar with energy conversion technologies. This edited volume contains ...thirteen selected chapters that deal with cutting-edge studies on energy conversion and storage technologies. A comprehensive collection of relevant topics on the subject area has been produced in this edited book. Readers are expected to find all the chapters inspiring and very useful while doing their research in the subject area.
Abstract
A vote gives a citizen of a democratic country the power to elect a representative which forms a government which is of the people, by the people, and for the people. Voting forms one of the ...fundamental pillars of modern democracy. Conducting a transparent, verifiable, and unbiased election is a challenging task for the election commission. Earlier ballot papers were used for conducting elections but it has to face many issues like booth capturing or damaging of ballot papers of the booths where there were fewer chances of winning for a candidate. Currently, EVMs are used for conducting the election in India but there are many reports that EVMs are not fully tamperproof. EVM is not a universal acceptance across the world. Blockchain is a distributed tamperproof technology which can help in conducting election transparent and tamperproof. Here in this paper, an approach for voting using blockchain and Paillier encryption is proposed. It implies the tamperproof property of blockchain and additive homomorphic property of Paillier encryption to build a voting architecture that will make the election process trans-parent and tamperproof. Next, algorithms for registration, voting, and result declaration has been mentioned along with the results of Paillier encryption for voting.
In this paper, we discuss the inference for the competing risks model when the failure times follow Chen distribution. With assumption of two causes of failures, which are partially observed, are ...considered as independent. The existence and uniqueness of maximum likelihood estimates for model parameters are obtained under generalized progressive hybrid censoring. Also, we discussed the classical and Bayesian inferences of the model parameters under the assumption of restricted and nonrestricted parameters. Performance of classical point and interval estimators are compared with Bayesian point and interval estimators by conducting extensive simulation study. In addition to that, for illustration purpose, a real life example is discussed. Finally, some concluding remarks, regarding the presented model, are made.
Environmental Sound Classification (ESC) is one of the most challenging tasks in signal processing, digital forensic and machine learning. Numerous methods have been proposed to perform ESC. The ...conventional models’ training depends on an enormous amount of annotated data, specifically while training the deep models. This paper presents a self-supervised learning (SSL)-based deep classifier for ESC, which is an under-explored method in the field of ESC. SSL mechanism directs the model to effectively learn prototypical features from the data itself by solving a pretext task. The model proposed in this paper takes spectrogram images as input. A pretext or an auxiliary task is defined as identification of the type of data augmentation applied to the signal. The model learned by solving the pretext task is further fine-tuned for developing the deep model for ESC. The model’s performance is evaluated on two benchmark sound classification datasets, i.e. ESC-10 and DCASE 2019 Task-1(A) datasets. The experiments and results show that the SSL model attains an improvement of 12.59% and 11.17% in accuracy compared to the baseline models of the DCASE 2019 Task-1(A) and ESC-10 datasets respectively. Moreover, the model also shows competitive performance to state-of-the-art methods.
PDF
