In-silico molecular docking and molecular dynamic simulation of γ-elemene and caryophyllene identified from the essential oil of Kaempferia galanga L. against biofilm forming proteins, CrtM and SarA of Staphylococcus aureus.

Medicinal plants play an important role as antimicrobials by inhibiting various key targets of diverse microorganisms. A major antimicrobial component of plants is its essential oil, which are increasingly being studied for their antimicrobial properties as well as for their potential role in the inhibition of biofilm formation. In the present study, essential oil from Kaempferia galanga L was isolated resulting in the identification of eleven compounds. Of these, two of the compounds, γ-elemene and caryophyllene were found to dock with the target proteins, CrtM and SarA of Staphylococcus aureus, which are essential for the formation of biofilm. γ-elemene demonstrated the best binding affinity with CrtM with binding energy of -8.1 kcal/mol whereas caryophyllene and its derivative isocaryophyllene showed the best binding with SarA with binding energy -6.1 kcal/mol. ADMET study of the compounds also revealed that the compounds are non-toxic and can be used as probable compounds for inhibition of biofilms. Molecular dynamic simulation studies revealed high affinity of binding and stability of the molecules with their targets. PCA analysis helped in identifying the principal motions occurring within a trajectory that are essential in inducing conformational changes.Communicated by Ramaswamy H. Sarma.

An insight into microscopy and analytical techniques for morphological, structural, chemical, and thermal characterization of cellulose.

Cellulose obtained from plants is a bio-polysaccharide and the most abundant organic polymer on earth that has immense household and industrial applications. Hence, the characterization of cellulose is important for determining its appropriate applications. In this article, we review the characterization of cellulose morphology, surface topography using microscopic techniques including optical microscopy, transmission electron microscopy, scanning electron microscopy, and atomic force microscopy. Other physicochemical characteristics like crystallinity, chemical composition, and thermal properties are studied using techniques including X-ray diffraction, Fourier transform infrared, Raman spectroscopy, nuclear magnetic resonance, differential scanning calorimetry, and thermogravimetric analysis. This review may contribute to the development of using cellulose as a low-cost raw material with anticipated physicochemical properties. HIGHLIGHTS: Morphology and surface topography of cellulose structure is characterized using microscopy techniques including optical microscopy, transmission electron microscopy, scanning electron microscopy, and atomic force microscopy. Analytical techniques used for physicochemical characterization of cellulose include X-ray diffraction, Fourier transform infrared spectroscopy, Raman spectroscopy, nuclear magnetic resonance spectroscopy, differential scanning calorimetry, and thermogravimetric analysis.

Robust deep learning optical autofocus system applied to automated multiwell plate single molecule localization microscopy.

We presenta robust, long-range optical autofocus system for microscopy utilizing machine learning. This can be useful for experiments with long image data acquisition times that may be impacted by defocusing resulting from drift of components, for example due to changes in temperature or mechanical drift. It is also useful for automated slide scanning or multiwell plate imaging where the sample(s) to be imaged may not be in the same horizontal plane throughout the image data acquisition. To address the impact of (thermal or mechanical) fluctuations over time in the optical autofocus system itself, we utilize a convolutional neural network (CNN) that is trained over multiple days to account for such fluctuations. To address the trade-off between axial precision and range of the autofocus, we implement orthogonal optical readouts with separate CNN training data, thereby achieving an accuracy well within the 600 nm depth of field of our 1.3 numerical aperture objective lens over a defocus range of up to approximately +/-100 µm. We characterize the performance of this autofocus system and demonstrate its application to automated multiwell plate single molecule localization microscopy.

Many microscopy experiments involve extended imaging of samples over timescales from minutes to days, during which the microscope can 'drift' out of focus. When imaging at high magnification, the depth of field is of the order of one micron and so the imaging system should keep the sample in the focal plane of the microscope objective lens to this precision. Unfortunately, temperature changes in the laboratory can cause thermal expansion of microscope components that can move the focal plane by more than a micron and such changes can occur on a timescale of minutes. This is a particular issue for super-resolved microscopy experiments using single molecule localization microscopy (SMLM) techniques, for which 1000s of images are acquired, and for automated imaging of multiple samples in multiwell plates. It is possible to maintain the sample in the focal plane focus position by either automatically moving the sample or adjusting the imaging system, for example by moving the objective lens. This is called 'autofocus' and is frequently achieved by reflecting a light beam from the microscope coverslip and measuring its position of beam profile as a function of defocus of the microscope. The correcting adjustment is then usually calculated analytically but there is recent interest in using machine learning techniques to determine the required focussing adjustment. Here, we present a system that uses a neural network to determine the required defocus correcting adjustment from camera images of a laser beam that is reflected from the coverslip. Unfortunately, this approach will only work when the microscope is in the same condition as it was when the neural network was trained - and this can be compromised by the same drift of the optical system that causes the defocus needing to be corrected. We show, however, that by training a neural network over an extended period, for example 10 days, this approach can 'learn' about the optical system drifts and provide the required autofocus function. We also show that an optical system utilizing a rectangular slit can make two measurements of the defocus simultaneously, with one measurement being optimized for high accuracy over a limited range (±10 µm) near focus and the other providing lower accuracy but over a much longer range (±100 µm). This robust autofocus system is suitable for automated super-resolved microscopy of arrays of samples in a multiwell plate using SMLM, for which an experiment routinely lasts more than 5 h.

Single-shot phase contrast microscopy using polarisation-resolved differential phase contrast.

We present a robust, low-cost single-shot implementation of differential phase microscopy utilising a polarisation-sensitive camera to simultaneously acquire four images from which phase contrast images can be calculated. This polarisation-resolved differential phase contrast (pDPC) microscopy technique can be easily integrated with fluorescence microscopy.

Application of direct stochastic optical reconstruction microscopy (dSTORM) to the histological analysis of human glomerular disease.

Electron microscopy (EM) following immunofluorescence (IF) imaging is a vital tool for the diagnosis of human glomerular diseases, but the implementation of EM is limited to specialised institutions and it is not available in many countries. Recent progress in fluorescence microscopy now enables conventional widefield fluorescence microscopes to be adapted at modest cost to provide resolution below 50 nm in biological specimens. We show that stochastically switched single-molecule localisation microscopy can be applied to clinical histological sections stained with standard IF techniques and that such super-resolved IF may provide an alternative means to resolve ultrastructure to aid the diagnosis of kidney disease where EM is not available. We have implemented the direct stochastic optical reconstruction microscopy technique with human kidney biopsy frozen sections stained with clinically approved immunofluorescent probes for the basal laminae and immunoglobulin G deposits. Using cases of membranous glomerulonephritis, thin basement membrane lesion, and lupus nephritis, we compare this approach to clinical EM images and demonstrate enhanced imaging compared to conventional IF microscopy. With minor modifications in established IF protocols of clinical frozen renal biopsies, we believe the cost-effective adaptation of conventional widefield microscopes can be widely implemented to provide super-resolved image information to aid diagnosis of human glomerular disease.

A laser scanning microscope executing intraframe polarization switching of the illumination beam.

The polarization of the illumination beam in a beam scanning microscope such as the confocal microscope plays an important role in extracting the orientational information of the molecules in the specimen. In this paper, we present the development of a beam scanning microscope comprising a custom designed optical arrangement to obtain images of the same target with different polarizations of the illumination beam. The optical arrangement, based on a ferroelectric liquid crystal spatial light modulator (FELCSLM), can generate homogeneous as well as non-homogeneous user defined polarization profiles over the cross-sectional area of the illumination beam. Here, we employ a computer generated holography technique and exploit the programmability of the FELCSLM display to considerably reduce the time gap between two successive illuminations of each location of the specimen with two different polarizations. We demonstrate the working of the beam scanning microscope where the polarization profile of the illumination beam is switched at the end of every line scanned, in contrast to a conventional beam scanning microscope where the polarization can be switched at the end of every frame scanned. Preliminary experimental results obtained using a polarization sensitive target confirm the feasibility of the proposed scheme.

Experimental observation of the aberration effects on a radially polarized beam.

In the last couple of decades the radially polarized beam has been gaining a lot of importance in diverse areas owing to its unique properties, especially near the focus of a lens. For instance, when focused tightly, the radially polarized beam produces a strong axially polarized field on the optical axis near the focus. Some of the areas where the radially polarized beam is found to be useful are optical trapping, laser machining, optical data storage, optical superresolution, and so on. Considering the fact that there is not any optical system that can be treated as perfectly aberration free, the applications of the radially polarized beam can, in practice, more or less be affected by the presence of aberrations. Indeed, there have been studies to understand the properties of the radially polarized beam in the presence of various aberrations. However, most such studies have been purely theoretical without being complimented by experimental results. In this paper, we present a comprehensive experimental investigation on the effect of aberrations on a focused radially polarized beam. The accuracy of our experimental results is confirmed by comparing them with the equivalent numerical simulation results.

Experimental demonstration of a light beam with superior aberration resilience.

In this Letter, we present the experimental results of a focused light beam that exhibits superior resilience to various common monochromatic aberrations. The light beam, obtained by applying a helical phase mask on an azimuthally polarized beam, has an Airy pattern that is like a circularly symmetric focal spot. Our results show that the beam in the presence of aberrations has better performance in terms of the Strehl ratio and the effect on the radius of the encircled energy relative to a normal linearly polarized or circularly polarized beam. Our experimental results agree well with the corresponding theoretical results.

Extraction and characterization of microcrystalline cellulose from fodder grass; Setaria glauca (L) P. Beauv, and its potential as a drug delivery vehicle for isoniazid, a first line antituberculosis drug.

Microcrystalline cellulose (MCC) is generally produced through acid hydrolysis of woody plants and agro sources. MCC synthesized from a common wild grass Setaria glauca (L) P. Beauv was characterized to explore the possibility of application in pharmaceutical industry especially as a drug delivery vehicle. The SEM, TGA, XRD and FTIR investigations of the prepared MCC reveal that the 5-30µm long, non aggregated MCC rods have high crystallinity index of 80% and were stable at 286°C. The preliminary investigation of the MCC incorporated micro beads containing isoniazid, one of the first line drugs for treatment of tuberculosis was carried out in the simulated intestinal fluid (SIF). The MCC incorporated micro beads with isoniazid drug load showed sustained release upto 24h with release of 0.521µg of isoniazid equivalent drug in the SIF system. No cytotoxicity of the MCC was observed in the haemolytic assay. The MCC also showed good antioxidant activity. Thus, the study reveals that the MCC can be prepared from an inexpensive and abundant grass species. The MCC have properties advantageous for application in the pharmaceutical industry and may be explored further in drug delivery research.