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Bacteriocins are bacterially synthesized ribosomal antimicrobial peptides which hinder the growth of closely related or unrelated bacterial species. They are often compared to antibiotics due to their significant bactericidal properties. Reports suggest that almost all bacteria synthesize bacteriocins as a part of their innate immunity. Bacteriocin production is dependent on a number of process variables such as aeration, pH, temperature and the type of carbon and nitrogen source used. Bacteriocin applications are primarily focused on food preservation. However, resistance to conventional antimicrobial agents offers novel prospects for bacteriocin applications. Several recent studies have purified bacteriocins for food preservation, infection control, cancer therapy, peptic ulcers etc. This study summarises the classification of bacteriocins, their mechanism of action, factors affecting bacteriocin production and the applications of bacteriocins as antimicrobial agents.

Quantum dots (QDs) are semiconductor nanocrystals possessing unique optoelectrical properties in that they can emit light energy of specific tunable wavelengths when excited by photons. They are gaining attention nowadays owing to their all-around ability to allow high-quality bio-imaging along with targeted drug delivery. The most lethal central nervous system (CNS) disorders are brain cancers or malignant brain tumors. CNS is guarded by the blood-brain barrier which poses a selective blockade toward drug delivery into the brain. QDs have displayed strong potential to deliver therapeutic agents into the brain successfully. Their bio-imaging capability due to photoluminescence and specific targeting ability through the attachment of ligand biomolecules make them preferable clinical tools for coming times. Biocompatible QDs are emerging as nanotheranostic tools to identify/diagnose and selectively kill cancer cells. The current review focuses on QDs and associated nanoformulations as potential futuristic clinical aids in the continuous battle against brain cancer.

The mechanism that produces fast radio burst (FRB) emission is poorly understood. Targeted monitoring of repeating FRB sources provides the opportunity to fully characterize the emission properties in a manner impossible with one-off bursts. Here, we report observations of the source of FRB 20201124A, with the Australian Square Kilometre Array Pathfinder (ASKAP) and the ultra-wideband low (UWL) receiver at the Parkes 64-m radio telescope (Murriyang). The source entered a period of emitting bright bursts during early 2021 April. We have detected 16 bursts from this source. One of the bursts detected with ASKAP is the brightest burst ever observed from a repeating FRB source with an inferred fluence of $640\pm70$ Jy ms. Of the five bursts detected with the Parkes UWL, none display any emission in the range 1.1--4 GHz. All UWL bursts are highly polarized, with their Faraday rotation measures (RMs) showing apparent variations. We obtain an average RM of $-614$ rad m$^{-2}$ for this FRB source with a standard deviation of $16$ rad m$^{-2}$ in the UWL bursts. In one of the UWL bursts, we see evidence of significant circularly polarized emission with a fractional extent of $47\pm1$ per cent. Such a high degree of circular polarization has never been seen before in bursts from repeating FRB sources. We also see evidence for significant variation in the linear polarization position angle in the pulse profile of this UWL repeat burst. Models for repeat burst emission will need to account for the increasing diversity in the burst polarization properties., 14 pages, 8 figures; accepted for publication in MNRAS

Sirtuins, a class III histone/protein deacetylase, is a central regulator of metabolic function and cellular stress response. This plays a pivotal role in the pathogenesis and progression of diseases such as cancer, neurodegeneration, metabolic syndromes, and cardiovascular disease. Sirtuins regulate biological and cellular processes, for instance, mitochondrial biogenesis, lipid and fatty acid oxidation, oxidative stress, gene transcriptional activity, apoptosis, inflammatory response, DNA repair mechanism, and autophagic cell degradation, which are known components for the progression of the neurodegenerative diseases (NDDs). Emerging evidence suggests that sirtuins are the useful molecular targets against NDDs like, Alzheimer's Disease (AD), Parkinson's Disease (PD), Huntington's Disease (HD), and Amyotrophic Lateral Sclerosis (ALS). However, the exact mechanism of neuroprotection mediated through sirtuins remains unsettled. The manipulation of sirtuins activity with its modulators, calorie restriction (CR), and micro RNAs (miR) is a novel therapeutic approach for the treatment of NDDs. Herein, we reviewed the current putative therapeutic role of sirtuins in regulating synaptic plasticity and cognitive functions, which are mediated through the different molecular phenomenon to prevent neurodegeneration. We also explained the implications of sirtuin modulators, and miR based therapies for the treatment of life-threatening NDDs.

Reduction of fossil fuels and increasing technology made importance of wind generation as renewable energy sources. With increasing number of wind farms fed to grid increases grid fault issues due to various wind systems disconnected from grid during grid faults. To get better grid operation, wind farms are probable to be carried during disturbance related to grid faults extensively known as fault ride through capability. In proposed system a fault ride through method in wind farm management system connected to grid is investigated in term of critical clearing time. This paper examines the use of dynamic voltage restorer on the enhancement of fixed-speed wind generator systems. The controller capability performance, drive performance, and cost factor are considered. Simulation is performed using MATLAB Simulink for constant speed wind generators with closed-loop controller-based DVR are tested. The constant speed drive called synchronous generator-based wind system feed to an infinite bus system. Simulation results show the wind system with DVR has better fault ride-through capability other compensated voltages and is more efficient in minimizing voltage fluctuations called sag/swell and wind generator’s speed. Additionally, DVR aids wind generators to maintain voltage sag/swell with the grid limits requirements with economical as compared to other voltage compensating systems.

Graphical abstract The etiology of the majority of human cancers is associated with a myriad of environmental causes, including physical, chemical, and biological factors. DNA damage induced by such mutagens is the initial step in the process of carcinogenesis resulting in the accumulation of mutations. Mutational events are considered the major triggers for introducing genetic and epigenetic insults such as DNA crosslinks, single- and double-strand DNA breaks, formation of DNA adducts, mismatched bases, modification in histones, DNA methylation, and microRNA alterations. However, DNA repair mechanisms are devoted to protect the DNA to ensure genetic stability, any aberrations in these calibrated mechanisms provoke cancer occurrence. Comprehensive knowledge of the type of mutagens and carcinogens and the influence of these agents in DNA damage and cancer induction is crucial to develop rational anticancer strategies. This review delineated the molecular mechanism of DNA damage and the repair pathways to provide a deep understanding of the molecular basis of mutagenicity and carcinogenicity. A relationship between DNA adduct formation and cancer incidence has also been summarized. The mechanistic basis of inflammatory response and oxidative damage triggered by mutagens in tumorigenesis has also been highlighted. We elucidated the interesting interplay between DNA damage response and immune system mechanisms. We addressed the current understanding of DNA repair targeted therapies and DNA damaging chemotherapeutic agents for cancer treatment and discussed how antiviral agents, anti-inflammatory drugs, and immunotherapeutic agents combined with traditional approaches lay the foundations for future cancer therapies.

We present the discovery of as-of-yet non-repeating Fast Radio Burst (FRB), FRB 20210117A, with the Australian Square Kilometer Array Pathfinder (ASKAP) as a part of the Commensal Real-time ASKAP Fast Transients (CRAFT) Survey. The sub-arcsecond localization of the burst led to the identification of its host galaxy at a $z=0.214(1)$. This redshift is much lower than what would be expected for a source dispersion measure (DM) of 729 pc cm$^{-3}$, given typical contributions from the intergalactic medium and the host galaxy. Optical observations reveal the host to be a dwarf galaxy with little on-going star formation, very different to the dwarf host galaxies of known repeating FRBs 20121102A, and 20190520B. We find an excess DM contribution from the host and attribute it to the FRB's local environment. We do not find any radio emission from the FRB site or host galaxy. The low magnetized environment and lack of a persistent radio source (PRS) indicate that the FRB source is older than those found in other dwarf host galaxies, and establish the diversity of FRB sources in dwarf galaxy environments. We find our observations to be fully consistent with the hypernebula model, where the FRB is powered by accretion-jet from a hyper-accreting black hole. Finally, our high-time resolution analysis reveals burst characteristics similar to those seen in repeating FRBs. We encourage follow-up observations of FRB 20210117A to establish any repeating nature., 15 pages, 9 figures, 2 Tables

Aim: To screen the zinc database for structurally similar molecules to compound 23 that targets DJ1 for use as a neuroprotective agent for Parkinson’s disease. Background: Parkinson’s disease (PD) is the second most common chronic neurodegenerative disorder characterized by progressive loss of dopaminergic neurons of the substantia nigra. To date, several proteins account for the recessive familial PD-forms, namely, Parkin, PINK-1, DJ-1, SNCA, PARK2, and LRRK2 Genes. DJ1 is one of the important central points that may be targeted for PD therapy. Recently, Compound 23 has been observed to exert the neuroprotective effect against neurodegeneration in a PD model, but due to its toxic substructure, the hunt for better nontoxic compounds continues. Objective: The overall objective of our work is to apply in silico approaches to screen structure similar compounds that interact potentially with DJ1 and may serve as a good therapeutic molecule for PD. Methods: Initial data mining was done from the zinc database and then screened compounds were additionally screened with toxicity checker, carcinopred, ADMET analysis and docking analysis. Results: The basic screening of database for structurally similar chemicals to compound 23 resulted in 50 compounds, which were further screened to twenty-three and finally seven compounds have been screened based on the toxicity and carcinopred test. Later, the seven compounds were docked and analysed for docking efficiency with DJ1. Our result of molecular docking and molecular simulation analysis highlights Molecule 42(SS2) to exhibit best binding affinity against DJ-1 protein target and can be proposed to be used as a therapeutic agent to modulate neurodegenerative proteins. Conclusion: Therefore, we conclude the discovery of novel, non-toxic, non-carcinogenic, ADMET investigated, capable of crossing BB barrier but structurally similar compounds to Compound-23, specifically molecule 42(SS2) and potentially molecule 34(SS1) to be used as neuroprotective agents for Parkinson’s disease.

The integration of artificial intelligence in precision medicine has revolutionized healthcare delivery. Precision medicine identifies the phenotype of particular patients with less-common responses to treatment. Recent studies have demonstrated that translational research exploring the convergence between artificial intelligence and precision medicine will help solve the most difficult challenges facing precision medicine. Here, we discuss different aspects of artificial intelligence in precision medicine that improve healthcare delivery. First, we discuss how artificial intelligence changes the landscape of precision medicine and the evolution of artificial intelligence in precision medicine. Second, we highlight the synergies between artificial intelligence and precision medicine and promises of artificial intelligence and precision medicine in healthcare delivery. Third, we briefly explain the promise of big data analytics and the integration of nanomaterials in precision medicine. Last, we highlight the challenges and opportunities of artificial intelligence in precision medicine.

Graphic abstract Drug designing and development is an important area of research for pharmaceutical companies and chemical scientists. However, low efficacy, off-target delivery, time consumption, and high cost impose a hurdle and challenges that impact drug design and discovery. Further, complex and big data from genomics, proteomics, microarray data, and clinical trials also impose an obstacle in the drug discovery pipeline. Artificial intelligence and machine learning technology play a crucial role in drug discovery and development. In other words, artificial neural networks and deep learning algorithms have modernized the area. Machine learning and deep learning algorithms have been implemented in several drug discovery processes such as peptide synthesis, structure-based virtual screening, ligand-based virtual screening, toxicity prediction, drug monitoring and release, pharmacophore modeling, quantitative structure–activity relationship, drug repositioning, polypharmacology, and physiochemical activity. Evidence from the past strengthens the implementation of artificial intelligence and deep learning in this field. Moreover, novel data mining, curation, and management techniques provided critical support to recently developed modeling algorithms. In summary, artificial intelligence and deep learning advancements provide an excellent opportunity for rational drug design and discovery process, which will eventually impact mankind. The primary concern associated with drug design and development is time consumption and production cost. Further, inefficiency, inaccurate target delivery, and inappropriate dosage are other hurdles that inhibit the process of drug delivery and development. With advancements in technology, computer-aided drug design integrating artificial intelligence algorithms can eliminate the challenges and hurdles of traditional drug design and development. Artificial intelligence is referred to as superset comprising machine learning, whereas machine learning comprises supervised learning, unsupervised learning, and reinforcement learning. Further, deep learning, a subset of machine learning, has been extensively implemented in drug design and development. The artificial neural network, deep neural network, support vector machines, classification and regression, generative adversarial networks, symbolic learning, and meta-learning are examples of the algorithms applied to the drug design and discovery process. Artificial intelligence has been applied to different areas of drug design and development process, such as from peptide synthesis to molecule design, virtual screening to molecular docking, quantitative structure–activity relationship to drug repositioning, protein misfolding to protein–protein interactions, and molecular pathway identification to polypharmacology. Artificial intelligence principles have been applied to the classification of active and inactive, monitoring drug release, pre-clinical and clinical development, primary and secondary drug screening, biomarker development, pharmaceutical manufacturing, bioactivity identification and physiochemical properties, prediction of toxicity, and identification of mode of action.

The incidence and prevalence of sleep disorders continue to increase in the elderly populace, particularly those suffering from neurodegenerative and neuropsychiatric disorders. This not only affects the quality of life but also accelerates the progression of the disease. There are many reasons behind sleep disturbances in such patients, for instance, medication use, nocturia, obesity, environmental factors, nocturnal motor disturbances and depressive symptoms. This review focuses on the mechanism and effects of sleep dysfunction in neurodegenerative and neuropsychiatric disorders. Wherein we discuss disturbed circadian rhythm, signaling cascade and regulation of genes during sleep deprivation. Moreover, we explain the perturbation in brainwaves during disturbed sleep and the ocular perspective of neurodegenerative and neuropsychiatric manifestations in sleep disorders. Further, as the pharmacological approach is often futile and carries side effects, therefore, the non-pharmacological approach opens newer possibilities to treat these disorders and widens the landscape of treatment options for patients.

Graphene and its derivatives, due to their extraordinary mechanical, thermal, and tribological properties, are extensively used to fabricate bulk graphene-based nanocomposites. On the other hand, m...

The high expression of the translocator protein (TSPO) makes it an ideal target for imaging and therapy. The present study is aimed at optimizing acetamidobenzoxazolone-based TSPO ligands by structural modification to overcome the limitations of TSPO ligands of the first two generations such as nonspecificity and polymorphism. Three different TSPO proteins, 2MGY, 4RYQ, and 4UC1, in the native and mutated form were chosen. Acetamidobenzoxazolones modified with phenylalanine methyl ester (methyl 2-(2-(5-bromo/chloro-2-oxobenzooxazol-3(2H)-yl)acetamido)-3-phenylpropanoate, ABPO-Br, ABPO-Cl) through better or comparable docking scores than the known TSPO ligands such as MBMP, FEBMP, FPBMP, and PK11195 are identified as potential TSPO ligands. ABPO-Cl and ABPO-Br were synthesized using phenylalanine methyl ester as a moiety for incorporation of the desired pharmacophoric feature. All the intermediates and final compounds were purified using column chromatography and analytical HPLC (purity > 97%). The purified compounds were characterized by 1H, 13C NMR and mass spectroscopy. Drug likeliness and comparative bioactivity analysis were performed using QikProp through prediction of various properties. Both analogs follow all the five Lipinski rules and three Jogersen’s rules predicting their drug likeliness. The other important aspects related to TSPO ligands such as blood-brain barrier penetration and better contrast have been predicted through lipophilicity (QP log P = 2.76 and 2.74 for ABPO-Br and ABPO-Cl, respectively) and serum binding (QP log Khsa = −0.18 and −0.25 for ABPO-Br and ABPO-Cl, respectively). The selectivity and distribution of these TSPO ligands were confirmed by 99mTc-ABPO-Br dynamic image in New Zealand rabbit. These results have shown that the ABPO analogs have the potential to act as better ligands as compared to known acetamidobenzoxazolone derivatives and would be of interest as a promising starting point for designing compounds for TSPO targeting.

Neurotransmitters are considered as a fundamental regulator in the process of neuronal growth, differentiation and survival. Parkinson's Disease (PD) occurs due to extensive damage of dopamine-producing neurons; this causes dopamine deficits in the midbrain, followed by the alternation of various other neurotransmitters (glutamate, GABA, serotonin, etc.). It has been observed that fluctuation of neurotransmission in the basal ganglia exhibits a great impact on the pathophysiology of PD. Dopamine replacement therapy, such as the use of L-DOPA, can increase the dopamine level, but it majorly ameliorates the motor symptoms and is also associated with long-term complications (for e.g., LID). While the non-dopaminergic system can efficiently target non-motor symptoms, for instance, the noradrenergic system regulates the synthesis of BDNF via the MAPK pathway, which is important in learning and memory. Herein, we briefly discuss the role of different neurotransmitters, implementation of neurotransmitter receptors in PD. We also illustrate the recent advances of neurotransmitter-based drugs, which are currently under in vivo and clinical studies. Reinstating normal neurotransmitter levels has been believed to be advantageous in the treatment of PD. Thus, there is an increasing demand for drugs that can specifically target the neurotransmission system and reinstate the normal levels of neurotransmitters, which might prevent or delay neurodegeneration in PD.

Epidemiological studies indicate a higher occurrence of breast cancer (BRCA) in patients with Parkinson's disease. However, the exact molecular mechanism is still not precise. Herein, we tested the hypothesis that this inverse comorbidity result from shared genetic and molecular processes. We conducted an integrated omics analysis to identify the common gene signatures associated with PD and BRCA. Secondly, several dysregulated biological processes in both indications were analyzed by functional enrichment methods, and significant overlapping processes were identified. To establish common regulatory mechanisms, information about transcription factors and miRNAs associated with both the disorders was extracted. Finally, disease-specific gene expression signatures were compared through LINCS L1000 analysis to identify potential repurposing drugs for PD. The potential repurposed drug candidates were then correlated with PD-specific gene signatures by Cmap analysis. In conclusion, this study highlights the shared genes, biological pathways and regulatory signatures associated with PD and BRCA with an improved understanding of crosstalk involved. Additionally, the role of therapeutics was investigated in context with their comorbid associations. These findings could help to explain the complex molecular patterns of associations between PD and BRCA.

Field experiment on the seed treatment for the management of termite infestation in wheat were conducted at Crop Research Farm of C.S. Azad University of Agriculture & Technology, Kanpur during Rabi 2016-17 and 2017-18 under rainfed condition. Eight treatments including untreated check were tested on wheat cultivar Maghar (K 8027). Seven insecticidal treatmens viz; thiamethoxam 25 WG @ 3.2 g, acephate 50% + imidachloprid 1.8 % @ 4.0 g , fipronil 5 SC @ 10 ml, imidacloprid 600 FS (48%) @ 4.0 ml, clothianidin 50 WDG @ 1.5 g, fipronil 40% + imidacloprid 40 WG @ 3.0 g and chlorntranil pride @ 3.0 ml were applied at the rate of one kg of seed before sowing. Non significant differences in germinatbility of wheat were observed between all the treatments. The order of effectiveness of insecticides on termite damage was , fipronil 40% + imidacloprid 40 WG > fipronil 5 SC>imidacloprid 600 FS (48%)> clothianidin 50 WDG> thiamethoxam 25 WG> in both the year chlorntranil pride s. Significant highest seed yield being 21.0 q/ha was recorded in seed treated with fipronil 40% + imidacloprid 40 WG which was at par with fipronil 5 SC (20.92 q/ha) and imidacloprid 600 FS (48%) (20.50 q/ha) in the year 2016-17. In the year 2017-18 fipronil 40%+imidacloprid 40 WG gave maximum yield of 20.46 q/ha followed by fipronil 5 SC (20.38 q/ha) and imidacloprid 600 FS (19.17 q/ha).