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Optical microscopy has emerged as a key driver of fundamental research since it provides the ability to probe into imperceptible structures in the biomedical world. For the detailed investigation of samples, a high-resolution image with enhanced contrast and minimal damage is preferred. To achieve this, an automated image analysis method is preferable over manual analysis in terms of both speed of acquisition and reduced error accumulation. In this regard, deep learning (DL)-based image processing can be highly beneficial. The review summarises and critiques the use of DL in image processing for the data collected using various optical microscopic techniques. In tandem with optical microscopy, DL has already found applications in various problems related to image classification and segmentation. It has also performed well in enhancing image resolution in smartphone-based microscopy, which in turn enablse crucial medical assistance in remote places. Graphical abstract

Exosomes are the smallest extracellular vesicles present in most of the biological fluids. They are found to play an important role in cell signaling, immune response, tumor metastasis, etc. Studies have shown that these vesicles also have diagnostic and therapeutic roles for which their accurate detection and quantification is essential. Due to the complexity in size and structure of exosomes, even the gold standard methods face challenges. This comprehensive review discusses the various standard methods such as ultracentrifugation, ultrafiltration, size-exclusion chromatography, precipitation, immunoaffinity, and microfluidic technologies for the isolation of exosomes. The principle of isolation of each method is described, as well as their specific advantages and disadvantages. Quantification of exosomes by nanoparticle tracking analysis, flow cytometry, tunable resistive pulse sensing, electron microscopy, dynamic light scattering, and microfluidic devices are also described, along with the applications of exosomes in various biomedical domains.

Cancer is a life-threatening disease that has claimed the lives of many people worldwide. With the current diagnostic methods, it is hard to determine cancer at an early stage, due to its versatile nature and lack of genomic biomarkers. The rapid development of biophotonics has emerged as a potential tool in cancer detection and diagnosis. Using the fluorescence, scattering, and absorption characteristics of cells and tissues, it is possible to detect cancer at an early stage. The diagnostic techniques addressed in this review are highly sensitive to the chemical and morphological changes in the cell and tissue during disease progression. These changes alter the fluorescence signal of the cell/tissue and are detected using spectroscopy and microscopy techniques including confocal and two-photon fluorescence (TPF). Further, second harmonic generation (SHG) microscopy reveals the morphological changes that occurred in non-centrosymmetric structures in the tissue, such as collagen. Again, Raman spectroscopy is a non-destructive method that provides a fingerprinting technique to differentiate benign and malignant tissue based on Raman signal. Photoacoustic microscopy and spectroscopy of tissue allow molecule-specific detection with high spatial resolution and penetration depth. In addition, terahertz spectroscopic studies reveal the variation of tissue water content during disease progression. In this review, we address the applications of spectroscopic and microscopic techniques for cancer detection based on the optical properties of the tissue. The discussed state-of-the-art techniques successfully determines malignancy to its rapid diagnosis.

Severe Acute Respiratory Syndrome Coronaviruses (SARS‐CoVs), causative of major outbreaks in the past two decades, has claimed many lives all over the world. The virus effectively spreads through saliva aerosols or nasal discharge from an infected person. Currently, no specific vaccines or treatments exist for coronavirus; however, several attempts are being made to develop possible treatments. Hence, it is important to study the viral structure and life cycle to understand its functionality, activity, and infectious nature. Further, such studies can aid in the development of vaccinations against this virus. Microscopy plays an important role in examining the structure and topology of the virus as well as pathogenesis in infected host cells. This review deals with different microscopy techniques including electron microscopy, atomic force microscopy, fluorescence microscopy as well as computational methods to elucidate various prospects of this life‐threatening virus., Highlights Structural analysis of SARS‐CoVs aids in understanding its nature, activity, and pathophysiologyRevealing the surface morphology of SARS‐CoVs using scanning electron microscope and atomic force microscopyComputational methods help to understand the structure of SARS‐CoVs and their interactions with various inhibitors

Over recent decades, three-dimensional (3D) bioprinting has been studied, improved, and extensively applied to various areas such as medicine, healthcare, food technology, etc. Although several applications have been identified, the field still requires extensive study to enhance and broaden the application sensitivity. The review provides a comprehensive overview of different principles and methods employed for 3D bioprinting. The literature focuses mainly on the applications in tissue engineering and regenerative medicine, 3D organ printing and its transplantation, high-throughput screening, drug and toxicology screening, drug printing, and clinical research. It also provides ample foundation for future research as it gathers the latest and ongoing research that scientists could utilize.