Simple Microscope Research Articles

Multi-stage and multi-colour liquid crystal reflections using a chiral triptycene photoswitchable dopant.

The photomodulation of the helical pitch of cholesteric liquid crystals results in dynamic and coloured canvases that can potentially be used in applications ranging from energy-efficient displays to colour filters, anti-counterfeiting tags and liquid crystal (LC) lasers. Here we report on the analysis of a series of photoswitchable chiral dopants that combine the large geometrical change and bistability of hydrazone switches with the efficient helical pitch induction of the chiral motif, triptycene. We elucidate the effects that conformational flexibility, dispersion forces and π-π interactions have on the chirality transfer ability of the dopant. We then use the irradiation time with visible light (442 nm) combined with a simple digital light processing microscope projection set-up to draw numerous stable multi-coloured images on an LC canvas, showcasing the fine control this dopant yields over the LC assembly.

Designing a Simple Microscope as an Alternative Learning Media with SolidWorks Software

Microscopes are essential as media or teaching aids for prospective educators to achieve learning goals. However, there are still obstacles in their application in the form of quite expensive costs. Often, educational aids have a sizeable nominal value for a school. Teaching aids are costly and prone to damage or loss if students use them frequently, and it is difficult and expensive to find replacements if they are damaged, so teachers are afraid to use them. To overcome this problem, this study provides another alternative design, namely the design of teaching aids that are still useful and function well for learning through the design of microscope teaching aids. The research method used is a model research design using Solidworks software. The development of learning tools compiled in this study refers to the type of 4-D development (Four-D model), which consists of 4 stages: the define stage, the design stage, the development stage, and the dissemination. The research carried out three stages, namely the definition stage (Define), the design stage (Design), and the development stage (Develop). In the results of the design draft, questions were asked of the informants; it was concluded that a proper microscope was a microscope that worked according to its specifications, namely being able to see tiny or micro-objects. The clarity of the lens and the maximum magnification are also factors in the feasibility of the microscope. This research can be concluded as a simple microscope design using the Solidworks application, which is suitable for use as an alternative learning media. If the design of this tool is to be made, then the selection of materials and mechanisms needs further research and trials.

Wide-field, high-resolution reconstruction in computational multi-aperture miniscope using a Fourier neural network

Traditional fluorescence microscopy is constrained by inherent trade-offs among resolution, field of view, and system complexity. To navigate these challenges, we introduce a simple and low-cost computational multi-aperture miniature microscope, utilizing a microlens array for single-shot wide-field, high-resolution imaging. Addressing the challenges posed by extensive view multiplexing and non-local, shift-variant aberrations in this device, we present SV-FourierNet, a multi-channel Fourier neural network. SV-FourierNet facilitates high-resolution image reconstruction across the entire imaging field through its learned global receptive field. We establish a close relationship between the physical spatially varying point-spread functions and the network’s learned effective receptive field. This ensures that SV-FourierNet has effectively encapsulated the spatially varying aberrations in our system and learned a physically meaningful function for image reconstruction. Training of SV-FourierNet is conducted entirely on a physics-based simulator. We showcase wide-field, high-resolution video reconstructions on colonies of freely moving C. elegans and imaging of a mouse brain section. Our computational multi-aperture miniature microscope, augmented with SV-FourierNet, represents a major advancement in computational microscopy and may find broad applications in biomedical research and other fields requiring compact microscopy solutions.

Multimodal analysis of traction forces and the temperature dynamics of living cells with a diamond-embedded substrate.

Cells and tissues are constantly exposed to chemical and physical signals that regulate physiological and pathological processes. This study explores the integration of two biophysical methods: traction force microscopy (TFM) and optically detected magnetic resonance (ODMR) to concurrently assess cellular traction forces and the local relative temperature. We present a novel elastic substrate with embedded nitrogen-vacancy microdiamonds that facilitate ODMR-TFM measurements. Optimization efforts focused on minimizing sample illumination and experiment duration to mitigate biological perturbations. Our hybrid ODMR-TFM technique yields TFM maps and achieves approximately 1 K precision in relative temperature measurements. Our setup employs a simple wide-field fluorescence microscope with standard components, demonstrating the feasibility of the proposed technique in life science laboratories. By elucidating the physical aspects of cellular behavior beyond the existing methods, this approach opens avenues for a deeper understanding of cellular processes and may inspire the development of diverse biomedical applications.

Radially polarized light in single particle optical extinction microscopy identifies silver nanoplates

Quantifying the optical extinction cross section of a single plasmonic nanoparticle (NP) has recently emerged as a powerful method to characterize the NP morphometry, i.e., size and shape, with a precision comparable to electron microscopy while using a simple optical microscope. Here, we enhance the capabilities of extinction microscopy by introducing a high numerical aperture annular illumination coupled with a radial polarizer to generate a strong axial polarization component. This enables us to probe the NP response to axial polarized light, and, in turn, to distinguish flat-lying nanoplates from other geometries. Polarization-resolved optical extinction cross sections were acquired on 219 individual colloidal silver NPs of a nominally triangular nanoplate shape but, in practice, exhibiting heterogeneous morphometries, including decahedrons and non-plate spheroids. An unsupervised machine learning cluster analysis algorithm was developed, which allowed us to separate NPs into different groups, owing to the measured differences in cross sections. Comparison of the measurements with a computational model of the absorption and scattering cross section accounting for nanoplates of varying geometries beyond simple triangles provided insight into the NP shape of each group. The results provide a significant improvement of polarization-resolved optical extinction microscopy to reconstruct NP shapes, further boosting the utility of the method as an alternative to electron microscopy analysis.

FlɛX: a computer vision program to evaluate strain in flexible crystals.

The program FlɛX (flexural ɛ for xtals) has been developed for a quick, easy and accurate evaluation of the maximum deformation reached in flexible crystals from a simple optical microscope picture. The program takes advantage of computer vision libraries to find the contours of a bent crystal and fit these to semicircles. It can then calculate the theoretical maximum deformation along its long axis using equations from the Euler-Bernoulli beam theory.

Early Predicting Osteogenic Differentiation of Mesenchymal Stem Cells Based on Deep Learning Within One Day.

Osteogenic differentiation of mesenchymal stem cells (MSCs) is proposed to be critical for bone tissue engineering and regenerative medicine. However, the current approach for evaluating osteogenic differentiation mainly involves immunohistochemical staining of specific markers which often can be detected at day 5-7 of osteogenic inducing. Deep learning (DL) is a significant technology for realizing artificial intelligence (AI). Computer vision, a branch of AI, has been proved to achieve high-precision image recognition using convolutional neural networks (CNNs). Our goal was to train CNNs to quantitatively measure the osteogenic differentiation of MSCs. To this end, bright-field images of MSCs during early osteogenic differentiation (day 0, 1, 3, 5, and 7) were captured using a simple optical phase contrast microscope to train CNNs. The results showed that the CNNs could be trained to recognize undifferentiated cells and differentiating cells with an accuracy of 0.961 on the independent test set. In addition, we found that CNNs successfully distinguished differentiated cells at a very early stage (only 1day). Further analysis showed that overall morphological features of MSCs were the main basis for the CNN classification. In conclusion, MSCs differentiation detection can be achieved early and accurately through simple bright-field images and DL networks, which may also provide a potential and novel method for the field of cell detection in the near future.

Comparative examination of a rapid immunocytochemical test for the detection of highly pathogenic avian influenza virus in domestic birds in field outbreaks

ABSTRACT The quantitative real-time reverse polymerase chain reaction (RRT-PCR) is the preferred test method for the diagnosis of avian influenza (AI), but can be performed only in specialized laboratories. Different antigen detection methods for the diagnosis of AI were previously reported to be specific and sensitive in field outbreaks. These tests can be performed in basic countryside labs. Brain smears of domestic birds (n = 105) collected during AI field outbreaks were examined with immunocytochemistry (IC). The results were statistically analysed by comparing IC to brain histology (BH), and immunohistochemistry (IHC), to gross pathological examination (GP) (n = 105), and RRT-PCR (n = 91). AI was diagnosed with RRT-PCR in 66 cases. IC and IHC were positive in 59/66 (90%) and 60/66 (91%) cases, respectively. Lesions suspicious for AI were detected with GP and HP in 66/66 (100%) and 61/66 (92%) cases, respectively. An almost perfect agreement was found between RRT-PCR, IC, IHC, and HP. Substantial agreement was found between IC and GP, between IHC and GP, between HP and GP, and between RRT-PCR and GP. The chromogen-based IC test presented in this study produces durable staining, which can be evaluated using a simple brightfield microscope. The test is rapid (can be completed in 2 h), sensitive (90%), specific (100%), and cost-effective, which makes the method suitable for routine diagnostic tests in AI epidemics. RESEARCH HIGHLIGHTS Avian influenza virus (AIV) antigen detection was examined in field outbreaks. Bird brain smears were tested using immunocytochemistry (IC). IC results strongly correlated with real-time RT-PCR results. The IC method was rapid, specific, sensitive, and cost-effective in AIV field outbreaks.

Metal-enhanced fluorescence biosensor integrated in capillary flow-driven microfluidic cartridge for highly sensitive immunoassays

Point-of-care testing (POCT) for low-concentration protein biomarkers remains challenging due to limitations in biosensor sensitivity and platform integration. This study addresses this gap by presenting a novel approach that integrates a metal-enhanced fluorescence (MEF) biosensor within a capillary flow-driven microfluidic cartridge (CFMC) for the ultrasensitive detection of the Parkinson's disease biomarker, aminoacyl-tRNA synthetase complex interacting multi-functional protein 2 (AIMP-2). Crucial point to this approach is the orientation-controlled immobilization of capture antibody on a nanodimple-structured MEF substrate within the CFMC. This strategy significantly enhances fluorescence signals without quenching, enabling accurate quantification of low-concentration AIMP-2 using a simple digital fluorescence microscope with a light-emitting diode excitation source and a digital camera. The resulting platform exhibits exceptional sensitivity, achieving a limit of detection in the pg/mL range for AIMP-2 in human serum. Additionally, the CFMC design incorporates a capillary-driven passive sample transport mechanism, eliminating the need for external pumps and further simplifying the detection process. Overall, this work demonstrates the successful integration of MEF biosensing with capillary microfluidics for point-of-care applications.

A simple coordinate transformation method for quickly locating the features of interest in TEM samples.

We developed a simple coordinate transformation method for quickly locating features of interest (FOIs) of samples in transmission electron microscope (TEM). The method is well suited for conducting sample searches in aberration-corrected scanning/transmission electron microscopes (S/TEM), where the survey can be very time-consuming because of the limited field of view imposed by the highly excited objective lens after fine-tuning the aberration correctors. For implementation, a digital image of the sample and the TEM holder was captured using a simple stereo-optical microscope. Naturally presented geometric patterns on the holder were referenced to construct a projective transformation between the electron and optical coordinate systems. The test results demonstrated that the method was accurate and required no electron microscope or specimen holder modifications. Additionally, it eliminated the need to mount the sample onto specific patterned TEM grids or deposit markers, resulting in universal applications for most TEM samples, holders and electron microscopes for fast FOI identification. Furthermore, we implemented the method into a Gatan script for graphical-user-interface-based step-by-step instructions. Through online communication, the script enabled real-time navigation and tracking of the motion of samples in TEM on enlarged optical images with a panoramic view.

Development of Optical Equipment Learning Media with the Utilization of Used Goods in Elementary School Science Subjects

The problem that often occurs in the science learning process is the lack of involvement of students in using learning media, this is due to the lack of learning media available in schools. This study aims to test the feasibility of optical instrument learning media products with the use of used goods in elementary school science subjects. This type of research uses the R&D (Research and Development) model ADDIE (Analysis, Design, Development, Implementation, and Evaluation). The subjects used were 9 grade IV students of SDN Sumberasri 04 Blitar. Data collection in the form of interview results, expert validation sheets, student response questionnaires, and observation sheets. Data analysis in the form of qualitative data analysis and quantitative data analysis. The questionnaire used is in the form of Likert scale. The results showed validation carried out by media experts on simple microscope products 91.66%, simple magnifying glasses 95.85%, and simple periscopes 95.85%, and the response of students obtained an average score of 3.55. The results stated that media products are classified as very suitable for use in elementary school science learning

Continuous microfluidic platform combining cell lysis and protein extraction for screening overall process conditions

AbstractBACKGROUNDMicrofluidic devices have been increasingly used as tools to accelerate the development of new biomanufacturing methods, given their ability to test a large set of variables in a short amount of time with minimal reagent consumption. However, while being able to expedite a bioprocess design, the modular aspect of these devices has not been systematically explored, with most applications focusing on single unitary operations. This paper explores the modular design of these devices through the development of an integrated microfluidic chip.RESULTSTwo separate unitary operations were included into a single device for continuous operation: product release by chemical cell lysis and product concentration by aqueous two‐phase system. In this way, it is possible to screen multiple conditions for each operation and evaluate their combined effect on the final product, making this a great tool in the development and optimization of a process. A recombinant Escherichia coli (E. coli) strain producing green fluorescent protein (GFP) was used as model system, which allows for lysis efficiency and partition coefficient to be evaluated by fluorescence microscopy. A chemical lysis solutions was used in the lysis step, presenting lysis efficiencies of about 100%, while a polyethylene glycol (PEG)/phosphate system was screened for the separation stage, presenting partition coefficients of about 4.CONCLUSIONSThe integrated device allowed for the continuous screening of multiple combinations of operation conditions, highlighting, for example, conditions where improvements on the lysis efficiency subsequently impaired the separation, decreasing the partition of the target product, thus demonstrating the need for the evaluation of a process in its entirety. In this way, the microfluidic device delivered a rapid process screening and optimization, with very low reagent consumption, and using a simple fluorescence microscope for data collection. © 2023 Society of Chemical Industry (SCI).

Machine learning based local recurrence prediction in colorectal cancer using polarized light imaging.

Current treatment for stage III colorectal cancer (CRC) patients involves surgery that may not be sufficient in many cases, requiring additional adjuvant systemic therapy. Identification of this latter cohort that is likely to recur following surgery is key to better personalized therapy selection, but there is a lack of proper quantitative assessment tools for potential clinical adoption. The purpose of this study is to employ Mueller matrix (MM) polarized light microscopy in combination with supervised machine learning (ML) to quantitatively analyze the prognostic value of peri-tumoral collagen in CRC in relation to 5-year local recurrence (LR). A simple MM microscope setup was used to image surgical resection samples acquired from stage III CRC patients. Various potential biomarkers of LR were derived from MM elements via decomposition and transformation operations. These were used as features by different supervised ML models to distinguish samples from patients that locally recurred 5 years later from those that did not. Using the top five most prognostic polarimetric biomarkers ranked by their relevant feature importances, the best-performing XGBoost model achieved a patient-level accuracy of 86%. When the patient pool was further stratified, 96% accuracy was achieved within a tumor-stage-III sub-cohort. ML-aided polarimetric analysis of collagenous stroma may provide prognostic value toward improving the clinical management of CRC patients.

Electroluminescence hyperspectral imaging of light-emitting diodes using a liquid crystal tunable filter

We demonstrate the use of a low-cost liquid-crystal-based wavelength-tunable filter and CMOS video camera to add hyperspectral imaging capabilities to a probe station equipped with a simple optical microscope. The resultant setup is used to rapidly resolve the spectral and spatial variations in electroluminescence typically observed for InxGa1−xN/GaN light-emitting diodes. Applying standard statistical analyses of variation within the multivariate datasets, such as moments and principal components, we observe inhomogeneities on a spectral scale significantly smaller than the bandwidth of the tunable filter. The resultant tool offers an alternative to scanning beam luminescence techniques for high-throughput hyperspectral analysis of optoelectronic devices.

A Mechanical Assay for the Quantification of Anti-RBD IgG Levels in Finger-Prick Whole Blood.

A large portion of the global population has been vaccinated with various vaccines or infected with SARS-CoV-2, the virus that causes COVID-19. The resulting IgG antibodies that target the receptor binding domain (RBD) of SARS-CoV-2 play a vital role in reducing infection rates and severe disease outcomes. Different immune histories result in the production of anti-RBD IgG antibodies with different binding affinities to RBDs of different variants, and the levels of these antibodies decrease over time. Therefore, it is important to have a low-cost, rapid method for quantifying the levels of anti-RBD IgG in decentralized testing for large populations. In this study, we describe a 30 min assay that allows for the quantification of anti-RBD IgG levels in a single drop of finger-prick whole blood. This assay uses force-dependent dissociation of nonspecifically absorbed RBD-coated superparamagnetic microbeads to determine the density of specifically linked microbeads to a protein A-coated transparent surface through anti-RBD IgGs, which can be measured using a simple light microscope and a low-magnification lens. The titer of serially diluted anti-RBD IgGs can be determined without any additional sample processing steps. The limit of detection for this assay is 0.7 ± 0.1 ng/mL referenced to the CR3022 anti-RBD IgG. The limits of the technology and its potential to be further developed to meet the need for point-of-care monitoring of immune protection status are discussed.

Fungal and Parasitic Diseases Seen in Tissue Biopsies at a Tertiary Health Center in Southwest Nigeria in a Five-Year Period

Aim: To describe the clinical and pathological features of the various fungal and parasitic diseases seen at our hospital over a five-year period.
 Study Design: This is a retrospective study of records of fungal and parasitic diseases.
 Place and Duration of Study: The study was done at the Department of Morbid Anatomy and Forensic Medicine of Obafemi Awolowo University Teaching Hospitals Complex, Ile-Ife from January 2018 to December 2022.
 Methods: The tissue sections of each case went through routine processing in the histopathology laboratory. The slides of the sections were viewed using a simple binocular microscope. The slides were scanned using APERIO CS2 digital slide scanner.
 Results: Eight cases of fungal infections and eleven cases of parasitic infections were noted during the study period. Aspergillosis accounted for five of the fungal infections, while mucormycosis accounted for two nasal infections. Schistosomiasis accounted for six cases of parasitic infections.
 Conclusion: Aspergillosis was the most diagnosed fungal infection while Schistosomiasis was the commonest parasitic infection. Digital stain separation could be an added tool in identification of fungal and parasitic stages in histological tissue sections.

Surface topography characterization using a simple optical device and artificial neural networks

State-of-the-art methods for quantifying wear in cylinder liners of large internal combustion engines for stationary power generation require disassembly and cutting of the examined liner. This is followed by laboratory-based high-resolution microscopic surface depth measurement that quantitatively evaluates wear based on bearing load curves (also known as Abbott-Firestone curves). Such reference methods are destructive, time-consuming and costly. The goal of the research presented here is to develop nondestructive yet reliable methods for quantifying the surface topography. A novel machine learning framework is proposed that allows prediction of the bearing load curves representing the depth profiles from reflection RGB images of the liner surface. These images can be collected with a simple handheld microscope. A joint deep learning approach involving two neural network modules optimizes the prediction quality of surface roughness parameters as well. The network stack is trained using a custom-built database containing 422 perfectly aligned depth profile and reflection image pairs of liner surfaces of large gas engines. The observed success of the method suggests its great potential for on-site wear assessment of engines during service.

A low-cost confocal microscope for the undergraduate lab

We demonstrate a simple and cost-efficient scanning confocal microscope setup for use in advanced instructional physics laboratories. The setup is constructed from readily available commercial products, and the implementation of a 3D-printed flexure stage allows for further cost reduction and pedagogical opportunity. Experiments exploring the thickness of a microscope slide and the surface of solid objects with height variation are presented as foundational components of undergraduate laboratory projects and demonstrate the capabilities of a confocal microscope. This system allows observation of key components of a confocal microscope, including depth perception and data acquisition via transverse scanning, making it an excellent pedagogical resource.

Fluholoscopy—Compact and Simple Platform Combining Fluorescence and Holographic Microscopy

The combination of different imaging modalities into single imaging platforms has a strong potential in biomedical sciences as it permits the analysis of complementary properties of the target sample. Here, we report on an extremely simple, cost-effective, and compact microscope platform for achieving simultaneous fluorescence and quantitative phase imaging modes with the capability of working in a single snapshot. It is based on the use of a single illumination wavelength to both excite the sample's fluorescence and provide coherent illumination for phase imaging. After passing the microscope layout, the two imaging paths are separated using a bandpass filter, and the two imaging modes are simultaneously obtained using two digital cameras. We first present calibration and analysis of both fluorescence and phase imaging modalities working independently and, later on, experimental validation for the proposed common-path dual-mode imaging platform considering static (resolution test targets, fluorescent micro-beads, and water-suspended lab-made cultures) as well as dynamic (flowing fluorescent beads, human sperm cells, and live specimens from lab-made cultures) samples.

An In-depth Guide to the Ultrastructural Expansion Microscopy (U-ExM) of Chlamydomonas reinhardtii.

Expansion microscopy is an innovative method that enables super-resolution imaging of biological materials using a simple confocal microscope. The principle of this method relies on the physical isotropic expansion of a biological specimen cross-linked to a swellable polymer, stained with antibodies, and imaged. Since its first development, several improved versions of expansion microscopy and adaptations for different types of samples have been produced. Here, we show the application of ultrastructure expansion microscopy (U-ExM) to investigate the 3D organization of the green algae Chlamydomonas reinhardtii cellular ultrastructure, with a particular emphasis on the different types of sample fixation that can be used, as well as compatible staining procedures including membranes. Graphical overview.