Here is your first look at the editorial content for the upcoming March/April issue of BioPhotonics.
Second Harmonic Generation Microscopy
This feature examines the crucial role of machine learning (ML) in advancing second harmonic generation (SHG) microscopy, focusing on how ML algorithms transform acquisition and analysis. Techniques such as ESRGAN for upscaling and CARE 2D and N2V 2D for denoising significantly enhance image quality and extract valuable data from low-resolution or noisy images. These innovations reduce the acquisition times for polarization-resolved SHG and standard SHG, allowing rapid whole-sample imaging while maintaining the image analysis accuracy. They also enable the use of lower laser power, reducing sample damage and potentially cutting equipment costs. ML further automates and improves SHG image classification, distinguishes between healthy and pathological tissues, and enables the quantitative analysis of collagen structures and fiber alignment essential for understanding tissue microenvironments and remodeling. By addressing the challenges in speed, quality, and analytical depth, ML broadens the utility of SHG microscopy in biomedical research. This feature also discusses the implementation, strengths, and future potential of each method.
Key Technologies: Machine learning, SHG microscopy
Dynamic Light Scattering
"Historically, dynamic light scattering has been used to predict the development of cataracts in rabbits, the development of cataract formation and diabetes mellitus in humans, the effectiveness of treatment for wet age-related macular degeneration6, and the success of retinal stem cell surgery.
The results have demonstrated the utility of DLS to noninvasively quantitate subtle changes at the molecular level. DLS captures molecular changes indicative of a particular disease or treatment earlier than they could be captured by imaging methods which detect late changes in structure.
A proof-of-concept instrument for making retinal measurements has been developed. The detector is interfaced with a standard clinical fundus camera. Scattered light is analyzed by a digital autocorrelator with an extended delay option for baseline determination. The intensity fluctuations are averaged over 5 s, and the cumulant analysis method is used to analyze the light-scattering data as a function of the sample time."
Key Technologies: dynamic light scattering, optical coherence tomography, fundus camera, spectroscopy
Raman Spectroscopy
Raman spectroscopy has blossomed into a pivotal analytical technique, transforming fields from medical diagnostics to environmental surveillance. The emergence of compact transmission-based Raman spectrometers heralds a new era of analytical excellence, characterized by unmatched portability, efficiency, and stability. These devices facilitate rapid, non-invasive molecular analysis, rendering them indispensable in applications such as early-stage disease detection, environmental pollutant monitoring, and stringent quality control in the food and pharmaceutical sectors. This article delves into the technological advancements and pragmatic applications of compact transmission-based Raman spectrometers, showcasing their profound impact and potential to spearhead future innovations. By integrating advanced techniques and combining Raman with Laser-Induced Breakdown Spectroscopy (LIBS) or Fluorescence Spectroscopy, these spectrometers are poised to redefine analytical paradigms. These synergistic approaches enhance the detection capabilities, providing comprehensive elemental and molecular information and paving the way for groundbreaking discoveries in planetary research and beyond.
Key Technologies: Raman spectroscopy, laser-induced breakdown spectroscopy, fluorescence spectroscopy
Flow Cytometry
Multiplexing assays in flow cytometry identify cell types from mixed cell populations using antibodies conjugated to fluorophores. Often, panels are relatively small requiring eight or fewer antibodies to answer the biological question. By selecting optimal fluorophore combinations with minimal spectral overlap, you can create no or low compensation panels of this size tailored to the flow cytometer. This simplifies analysis by omitting the compensation step and improves data quality by reducing data spread. Using specialty dyes allows the design of such panels, enabling quick and reliable data generation. The design and successful use of these panels will be further discussed.
Key Technologies: Flow cytometry
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