Efficacy of biogenic silver nanoparticles against clinical isolates of fungi causing mycotic keratitis in humans

Mycotic keratitis is mainly responsible for vision loss caused by various fungi. Sometimes, proper treatment of such infection is not possible due to unavailability of effective antifungal agents and development of resistance of such fungi to antimycotic drugs. Hence, it is necessary to search for potential antifungal agents, which can effectively eradicate fungal infection of eyes. Nanoparticles‐based antifungal drugs overcome this problem by increasing permeability and properties of drug molecules. In the present study, silver nanoparticles were synthesised by using Helminthosporium sp. and Chaetomium sp. following sequential reduction technique. The synthesised silver nanoparticles were detected primarily by UV‐visible spectrophotometer showing absorption spectra at 424 and 433 nm, respectively. Nanoparticles tracking analysis confirmed the mean particle size of silver nanoparticles as 45 and 55 nm. The synthesised AgNPs showed significant antifungal activity against fungi causing mycotic keratitis, when used alone and in combination with ketoconazole and amphotericin B in the range of 30–70 microgram per millilitre of minimum inhibitory concentration. Thus, the synthesised AgNPs can be used to enhance the activities of ketoconazole and amphotericin B.Inspec keywords: silver, nanoparticles, nanomedicine, antibacterial activity, diseases, permeability, ultraviolet spectra, visible spectra, particle sizeOther keywords: biogenic silver nanoparticles, fungi, mycotitic keratitis, vision loss, infection, antifungal agents, antimycotic drugs, antifungal drugs, permeability, Helminthosporium sp, Chaetomium sp, sequential reduction technique, UV‐visible spectrophotometer, mean particle size, ketoconazole, amphotericin B, wavelength 424 nm, wavelength 433 nm, size 45 nm, size 55 nm, Ag     

Machine Learning-Informed Predictive Design and Analysis of Electrohydrodynamic Printing Systems

Electrohydrodynamic (EHD) processes are promising techniques for manufacturing nanoscopic products with different shapes (such as thin films, nanofibers, 2D/3D nanostructures, and nanoparticles) and materials at a low cost using simple equipment. A key challenge in their adoption by nonexperts is the requirement of enormous time and resources in identifying the optimum design/process parameters for the underlying material and EHD system. Machine learning (ML) has made exciting advancements in predictive modeling of different processes, provided it is trained on high-quality datasets at appropriate volumes. This article extends the suitability of such ML-enabled approaches to a new technological domain of EHD spraying and drop-on-demand printing. Different ML models like ridge regression, random forest regression, support vector regression, gradient boosting regression, and multilayer perceptron are trained and their performance using evaluation metrics like RMSE and R2_score is examined. Tree-based algorithms like gradient boosting regression are found to be the most suitable technique for modeling EHD processes. The trained ML models show substantially higher accuracy (average error < 5%) in replicating these nonlinear processes as compared to previously reported scaling laws (average error ≈ 42%) and are well suited for predictive modeling/analysis of the underlying EHD system and process.     

Inhibition of neuronal calcium channels by a novel peptide spider toxin, DW13.3

Peptide toxins have proved to be useful agents, both in discriminating between different components of native calcium channel currents and in the molecular isolation and designation of their cloned channel counterparts. Here, we describe the isolation and characterization of the biochemical and physiological properties of a novel 74-amino acid peptide toxin (DW13.3) extracted from the venom of the spider Filistata hibernalis. The subtype specificity of DW13.3 was investigated using calcium channel currents recorded from two separate expression systems and several different cultured mammalian cell preparations. Overall, DW13.3 potently blocked all native calcium channel currents studied, with the exception of T-type currents recorded from GH3 cells. Examination of transiently expressed calcium channels in oocytes showed that DW13.3 had the highest affinity for alpha1A, followed by alpha1B > alpha1C > alpha1E. The affinity of DW13.3 for alpha1B N-type currents varied by 10-fold between expressed channels and native currents. Although block occurred in a similar 1:1 manner for all subtypes, DW13.3 produced a partial block of both alpha1A currents and P-type currents in cerebellar Purkinje cells. Selective occlusion of the P/Q-type channel ligand omega-conotoxin MVIIC (but not omega-agatoxin IVA) from its binding site in Purkinje neurons suggests that DW13.3 binds to a site close to the pore of the channel. The inhibition of different subtypes of calcium channels by DW13.3 reflects a common "macro" binding site present on all calcium channels except T-type.     

Does India need to harmonize the law of patent exhaustion and parallel imports?

The amendment of patent law of India in 2005 to fulfill her international obligation under the TRIPS Agreement (World Trade Organization Agreement on Trade Related Intellectual Property Rights) was an outcome of an attempt to balance the competing interests of several stakeholders, including indigenous pharmaceutical companies, multi-national pharmaceutical companies, non-governmental organizations and civil society groups concerned with access to affordable drugs. The adverse consequence of this delicate balancing is introduction of some provisions in the Act whose compatibility with the TRIPS Agreement is questionable, and which therefore are prone to litigations. Section 107A(b) of the amended patent law dealing with parallel imports is one such provision, which, if interpreted word for word could have significant connotations for the rights of a patent owner. This article aims to examine the inconsistencies intrinsic in Section 107A(b) and discusses the divergences in the Indian patent law associated with the doctrine of exhaustion and parallel imports. This article also proposes legal amendments with a view to eliminate inconsistencies intrinsic in the section and enlarge the ambit of the exhaustion principle conceptualized therein, while concurrently remaining compliant with the TRIPS Agreement.     

Proteome of human endometrium: Identification of differentially expressed proteins in proliferative and secretory phase endometrium

Purpose: To exploit the potential of proteomics to identify and study additional yet‐unidentified important proteins present in human endometrium. Experimental design: The proteome of human endometrium would be established using 2‐DE and MALDI and the data analyzed to identify differential protein expression in the proliferative and secretory phase of the menstrual cycle using PDQuest software and MALDI. Results: In the present work, 2‐DE of human endometrium protein led to the resolution of over 200 spots. Subsequent MALDI analysis of 215 spots allowed the identification of 194 proteins. A total of 57 out of the 215 spots were found to be differentially expressed, out of which 49 could be identified using MALDI. These differentially expressed proteins included structural proteins, molecular chaperones, signaling proteins, metabolic proteins, proteins related to immunity, RNA biogenesis, protein biosynthesis and others. The differential expressions of seven representative proteins in secretory and proliferative phase endometrium tissue were confirmed by immunoblot analysis. Conclusion and clinical relevance: This study establishes the 2‐D proteome of human endometrium represented by 194 identified protein spots. The present data provides an important clue towards determining the function of these proteins with respect to endometrium related diseases.     

Characterising and exploiting workloads of highly interactive video-on-demand

This paper presents a detailed characterisation of user behaviour for a series of interactive video experiments over a 12 month period, in which we served popular sporting and musical content. In addition to generic VCR-like features, our custom-built video-on-demand application provides advanced interactivity features such as bookmarking. The dramatic impact of such functionality on how users consume content is studied and analysed. We discuss in detail how this user behaviour can be exploited by content distributors to improve user experience. Specifically, we study how simple dynamic bookmark placement and interactivity-aware content pre-fetching and replication can reduce the impact of highly interactive media on CDN performance.     

SVM based robust watermarking for enhanced medical image security

Medical images are more typical than any other ordinary images, since it stores patient’s information for diagnosis purpose. Such images need more security and confidentiality as total diagnosis depends on it. In telemedicine applications, transmission of medical image via open channel, demands strong security and copyright protection. In our proposed robust watermarking model, a double layer security is introduced to ensure the robustness of embedded data. The embedded data is scrambled using a unique key and then a transform domain based hybrid watermarking technique is used to embed the scrambled data into the transform coefficients of the host image. The data embedding in medical images involves more attention, so that the diagnosis part must not be affected by any modification. Therefore, Support Vector Machine (SVM) is used as a classifier, which classify a medical image into two regions i.e. Non Region of Interest (NROI) and Region of Interest (ROI) to embed watermark data into the NROI part of the medical image, using the proposed embedding algorithm. The objective of the proposed model is to avoid any quality degradation to the medical image. The simulation is performed to measure the Peak Signal to Noise Ratio (PSNR) for imperceptibility and Structural Similarity Index (SSIM) to test the robustness. The experimented result shows, robustness and imperceptibility with SSIM of more than 0.50 and PSNR of more than 35 dB for proposed watermarking model.

     

Microhardness studies of SnI2 and SnI4 single crystals

The variation in the microhardness of tin-di-iodide (SnI₂) and tin-tetra-iodide (SnI₄) crystals has been determined using Vicker’s microhardness indentor. It is observed that the microhardness of the crystals depends on the applied load and is independent of the duration of loading. Vickers Hardness Numerals (vhn) for SnI₂ is found to be greater than that of SnI₄ crystals. Mayer’s equation and implications have been discussed.