Disorders of gastrointestinal (GI) motility are associated with various symptoms such as nausea, vomiting, and constipation. However, the underlying causes of impaired GI motility remain unclear, which has led to variation in the efficacy of therapies to treat GI dysfunction. Optogenetics is a novel approach through which target cells can be precisely controlled by light and has shown great potential in GI motility research. Here, we summarized recent studies of GI motility patterns utilizing optogenetic devices and focused on the ability of opsins, which are genetically expressed in different types of cells in the gut, to regulate the excitability of target cells. We hope that our review of recent findings regarding optogenetic control of GI cells broadens the scope of application for optogenetics in GI motility studies.

Cancer cells dysregulate lipid metabolism to accelerate energy production and biomolecule synthesis for rapid growth. Lipid metabolism is highly dynamic and intrinsically heterogeneous at the single cell level. Although fluorescence microscopy has been commonly used for cancer research, bulky fluorescent probes can hardly label small lipid molecules without perturbing their biological activities. Such a challenge can be overcome by coherent Raman scattering (CRS) microscopy, which is capable of chemically selective, highly sensitive, submicron resolution and high-speed imaging of lipid molecules in single live cells without any labeling. Recently developed hyperspectral and multiplex CRS microscopy enables quantitative mapping of various lipid metabolites in situ. Further incorporation of CRS microscopy with Raman tags greatly increases molecular selectivity based on the distinct Raman peaks well separated from the endogenous cellular background. Owing to these unique advantages, CRS microscopy sheds new insights into the role of lipid metabolism in cancer development and progression. This review focuses on the latest applications of CRS microscopy in the study of lipid metabolism in cancer.

The algorithm used for reconstruction or resolution enhancement is one of the factors affecting the quality of super-resolution images obtained by fluorescence microscopy. Deep-learning-based algorithms have achieved state-of-the-art performance in super-resolution fluorescence microscopy and are becoming increasingly attractive. We firstly introduce commonly-used deep learning models, and then review the latest applications in terms of the network architectures, the training data and the loss functions. Additionally, we discuss the challenges and limits when using deep learning to analyze the fluorescence microscopic data, and suggest ways to improve the reliability and robustness of deep learning applications.

Microfluidic systems have been widely utilized in high-throughput biology analysis, but the difficulties in liquid manipulation and cell cultivation limit its application. This work has developed a new digital microfluidic (DMF) system for on-demand droplet control. By adopting an extending-depth-of-field (EDoF) phase modulator to the optical system, the entire depth of the microfluidic channel can be covered in one image without any refocusing process, ensuring that 95% of the particles in the droplet are captured within three shots together with shaking processes. With this system, suspension droplets are generated and droplets containing only one yeast cell can be recognized, then each single cell is cultured in the array of the chip. By observing their growth in cell numbers and the green fluorescence protein (GFP) production via fluorescence imaging, the single cell with the highest production can be identified. The results have proved the heterogeneity of yeast cells, and showed that the combined system can be applied for rapid single-cell sorting, cultivation, and analysis.

Fourier light-field microscopy (FLFM) uses a microlens array (MLA) to segment the Fourier plane of the microscopic objective lens to generate multiple two-dimensional perspective views, thereby reconstructing the three-dimensional (3D) structure of the sample using 3D deconvolution calculation without scanning. However, the resolution of FLFM is still limited by diffraction, and furthermore, it is dependent on the aperture division. In order to improve its resolution, a super-resolution optical fluctuation Fourier light-field microscopy (SOFFLFM) was proposed here, in which the super-resolution optical fluctuation imaging (SOFI) with the ability of super-resolution was introduced into FLFM. SOFFLFM uses higher-order cumulants statistical analysis on an image sequence collected by FLFM, and then carries out 3D deconvolution calculation to reconstruct the 3D structure of the sample. The theoretical basis of SOFFLFM on improving resolution was explained and then verified with the simulations. Simulation results demonstrated that SOFFLFM improved the lateral and axial resolution by more than 2 and 2 times in the second- and fourth-order accumulations, compared with that of FLFM.

As changes in hard or soft oral tissues normally have a microbiological component, it is important to develop diagnostic techniques that support clinical evaluation, without destroying microbiological formation. The optical coherence tomography (OCT) represents an alternative to analyze tissues and microorganisms without the need for processing. This imaging technique could be defined as a fast, real-time, in situ, and non-destructive method. Thus, this study proposed the use of the OCT to visualize biofilm by Candida albicans in reline resins for removable prostheses. Three reline resins (Silagum-Comfort, Coe-Comfort, and Soft-Confort), with distinct characteristics related to water sorption and fungal inhibition were used. A total of 30 samples (10 for each resin group) were subjected to OCT scanning before and 96 h after inoculation with Candida albicans (URM 6547). The biofilm analysis was carried out through a 2D optical Callisto SD-OCT (930 nm) operated in the spectral domain. Then, the images were preprocessed using a 3×3 Gaussian filter to remove the noise, and then Otsu binarization, allowing segmentation and pixel counting. The layer’s biofilm formed was clearly defined and, indeed, its visualization is modified by water sorption of each material. Silagum-Comfort and Soft-Confort showed some similarities in the scattering of light between the clean and inoculated samples, in which, the latter samples presented higher values of light signal intensity. Coe-Comfort samples were the only ones that showed no differences between the clean or inoculated images. Therefore, the results of this study suggest that OCT is a viable technique to visualize the biofilm in reline materials. Because findings in the literature are still scarcely using the OCT technique to visualize biofilm in reline resins, further studies are encouraged. It should not contain any references or displayed equations.

The skin is the largest organ in humans. It comprises about 16% of our body. Many diseases originate from the skin, including acne vulgaris, skin cancer, fungal skin disease, etc. As a common skin cancer in China, melanoma alone grows at year rate of nearly 4%. Therefore, it is crucial to develop an objective, reliable, accurate, non-invasive, and easy-to-use diagnostic method for skin diseases to support clinical decision-making. Raman spectroscopy is a highly specific imaging technique, which is sensitive, even to the single-cell level in skin diagnosis. Raman spectroscopy provides a pattern of signals with narrow bandwidths, making it a common and essential tool for researching individual characteristics of skin cells. Raman spectroscopy already has a number of clinical applications, including in thyroid, cervical and colorectal cancer. This review will introduce the advantages and recent developments in Raman spectroscopy, before focusing on the advances in skin diagnosis, including the advantages, methods, results, analysis, and notifications. Finally, we discuss the current limitations and future progress of Raman spectroscopy in the context of skin diagnosis.

The study of circulating cells in the blood stream is critical, as it covers many fields of biomedicine, including immunology, cell biology, oncology, and reproductive medicine. In-vivo flow cytometry (IVFC) is a new tool to monitor and count cells in real time for long durations in their native biological environment. This review describes two main categories of IVFC, i.e., labeled and label-free IVFC. It focuses on label-free IVFC and introduces its technological development and related biological applications. Because cell recognition is the basis of flow cytometry counting, this review also describes various methods for the classification of unlabeled cells, including the latest machine learning-based technologies.

As the largest internal organ of the human body, the liver has an extremely complex vascular network and multiple types of immune cells. It plays an important role in blood circulation, material metabolism, and immune response. Optical imaging is an effective tool for studying fine vascular structure and immunocyte distribution of the liver. Here, we provide an overview of the structure and composition of liver vessels, the three-dimensional (3D) imaging of the liver, and the spatial distribution and immune function of various cell components of the liver. Especially, we emphasize the 3D imaging methods for visualizing fine structure in the liver. Finally, we summarize and prospect the development of 3D imaging of liver vessels and immune cells.

The tumor microenvironment (TME) promotes pro-tumor and anti-inflammatory metabolisms and suppresses the host immune system. It prevents immune cells from fighting against cancer effectively, resulting in limited efficacy of many current cancer treatment modalities. Different therapies aim to overcome the immunosuppressive TME by combining various approaches to synergize their effects for enhanced anti-tumor activity and augmented stimulation of the immune system. Immunotherapy has become a major therapeutic strategy because it unleashes the power of the immune system by activating, enhancing, and directing immune responses to prevent, control, and eliminate cancer. Phototherapy uses light irradiation to induce tumor cell death through photothermal, photochemical, and photo-immunological interactions. Phototherapy induces tumor immunogenic cell death, which is a precursor and enhancer for anti-tumor immunity. However, phototherapy alone has limited effects on long-term and systemic anti-tumor immune responses. Phototherapy can be combined with immunotherapy to improve the tumoricidal effect by killing target tumor cells, enhancing immune cell infiltration in tumors, and rewiring pathways in the TME from anti-inflammatory to pro-inflammatory. Phototherapy-enhanced immunotherapy triggers effective cooperation between innate and adaptive immunities, specifically targeting the tumor cells, whether they are localized or distant.Herein, the successes and limitations of phototherapy combined with other cancer treatment modalities will be discussed. Specifically, we will review the synergistic effects of phototherapy combined with different cancer therapies on tumor elimination and remodeling of the immunosuppressive TME. Overall, phototherapy, in combination with other therapeutic modalities, can establish anti-tumor pro-inflammatory phenotypes in activated tumor-infiltrating T cells and B cells and activate systemic anti-tumor immune responses.