Design of experiments for the optimization of SOFI super-resolution microscopy imaging

3D super-resolution optical fluctuation imaging with temporal focusing two-photon excitation

3D super-resolution fluorescence microscopy typically requires sophisticated setups, sample preparation, or long measurements. A notable exception, SOFI, only requires recording a sequence of frames and no hardware modifications whatsoever but being a wide-field method, it faces problems in thick, dense samples. We combine SOFI with temporal focusing two-photon excitation - the wide-field method that is capable of exciting a thin slice in 3D volume. Temporal focusing is simple to implement whenever the excitation path of the microscope can be accessed. The implementation of SOFI is straightforward. By merging these two methods, we obtain super-resolved 3D images of neurons stained with quantum dots. Our approach offers reduced bleaching of out-of-focus fluorescent probes and an improved signal-to-background ratio that can be used when robust resolution improvement is required in thick, dense samples.

Ionic-resolution protoacoustic microscopy: A feasibility study

Visualizing micro- and nano-scale biological entities requires high-resolution imaging and is conventionally achieved via optical microscopic techniques. Optical diffraction limits their resolution to ∼200 nm. This limit can be overcome by using ions with ∼1 MeV energy. Such ions penetrate through several micrometers in tissues, and their much shorter de Broglie wavelengths indicate that these ion beams can be focused to much shorter scales and hence can potentially facilitate higher resolution as compared to the optical techniques. Proton microscopy with ∼1 MeV protons has been shown to have reasonable inherent contrast between sub-cellular organelles. However, being a transmission-based modality, it is unsuitable for in vivo studies and cannot facilitate three-dimensional imaging from a single raster scan. Here, we propose proton-induced acoustic microscopy (PrAM), a technique based on pulsed proton irradiation and proton-induced acoustic signal collection. This technique is capable of label-free, super-resolution, 3D imaging with a single raster scan. Converting radiation energy into ultrasound enables PrAM with reflection mode detection, making it suitable for in vivo imaging and probing deeper than proton scanning transmission ion microscopy (STIM). Using a proton STIM image of HeLa cells, a coupled Monte Carlo+k-wave simulations-based feasibility study has been performed to demonstrate the capabilities of PrAM. We demonstrate that sub-50 nm lateral (depending upon the beam size and energy) and sub-micron axial resolution (based on acoustic detection bandwidth and proton beam pulse width) can be obtained using the proposed modality. By enabling visualization of biological phenomena at cellular and subcellular levels, this high-resolution microscopic technique enhances understanding of intricate cellular processes.

PySOFI: an open source Python package for SOFI

Super-resolution optical fluctuation imaging (SOFI) is a highly democratizable technique that provides optical super-resolution without requirement of sophisticated imaging instruments. Easy-to-use open-source packages for SOFI are important to support the utilization and community adoption of the SOFI method, they also encourage the participation and further development of SOFI by new investigators. In this work, we developed PySOFI, an open-source Python package for SOFI analysis that offers the flexibility to inspect, test, modify, improve, and extend the algorithm. We provide complete documentation for the package and a collection of Jupyter Notebooks to demonstrate the usage of the package. We discuss the architecture of PySOFI and illustrate how to use each functional module. A demonstration on how to extend the PySOFI package with additional modules is also included in the PySOFI package. We expect PySOFI to facilitate efficient adoption, testing, modification, dissemination, and prototyping of new SOFI-relevant algorithms.

Application of Color Doppler Ultrasound in Microscopic Imaging Diagnosis of Adenomyosis

In order to explore the value of color Doppler ultrasonography (TVCDS) in the diagnosis and differential diagnosis of adenomyosis. A total of 150 patients with adenomyosis admitted to a hospital from January 2020 to December 2021 were selected, taking transvaginal three-dimensional color Doppler ultrasound and abdominal ultrasound for examination, all results were compared with patient pathology or surgical results, in order to compare the accuracy of the two inspection methods. The positive predictive value of three-dimensional color Doppler ultrasonography was higher than that of abdominal ultrasonography, and the difference was statistically significant (P < 0.05). The coincidence rate, sensitivity, and specificity of three-dimensional color Doppler ultrasonography were higher than those of abdominal ultrasonography, while the misdiagnosis rate was lower than that of abdominal ultrasonography, and the differences were statistically significant (all P < 0.05). The imaging features of vaginal three-dimensional color Doppler ultrasound in patients with adenomyosis are mainly enlarged uterus, slightly stronger echoes in the myometrium with enhanced echogenic spots, and short or short branch blood flow signals in the lesions. After statistical analysis, there was a significant difference in the blood flow changes between benign and malignant endometrial echoes and abnormal echoes in the uterine cavity, P < 0.05. Normal endometrium and benign intrauterine lesions mainly showed no blood flow signal, while malignant lesions in the uterine cavity mostly showed changes in blood flow signal. Compared with abdominal examination, transvaginal color Doppler ultrasonography has obvious advantages in the diagnosis of adenomyosis. According to the characteristics of ultrasound images, blood flow distribution, frequency spectrum, etc., it can provide a more accurate basis for clinical timely, provide the identification points of uterine fibroids, and provide help for clinicians to choose a treatment plan.

Technological advances in super-resolution microscopy to study cellular processes

Since its initial demonstration in 2000, far-field super-resolution light microscopy has undergone tremendous technological developments. In parallel, these developments have opened a new window into visualizing the inner life of cells at unprecedented levels of detail. Here, we review the technical details behind the most common implementations of super-resolution microscopy and highlight some of the recent, promising advances in this field.

Development of a New Approach for Low-Laser-Power Super-Resolution Fluorescence Imaging

The development of super-resolution fluorescence microscopy over the past decade has drastically improved the resolution of light microscopy to ∼10 nm. Stochastic optical reconstruction microscopy (STORM) can be used to achieve subdiffraction-limit resolution by sequentially imaging and localizing individual fluorophores. In principle, the super-resolution of STORM can be obtained by high-accuracy localization of photoswitchable fluorophores, which require fast photoswitching and bright fluorescence intensity from a single emitter. It is known that the switching rate of photoswitchable fluorophores depends on the laser power─a high laser power being required for the enhancement of imaging resolution. However, high laser power is usually harmful to biological specimens and limits the imaging time because of its photobleaching effects and high phototoxicity. In this study, we attempted to overcome this problem by improving the STORM resolution at a lower laser power. Through the quantitative analysis of the photoswitching behavior of single fluorophores under different laser power conditions, we developed a new approach to achieve super-resolution fluorescence images at a laser power 10 times lower than had previously been reported. This approach is expected to play an increasingly significant role in super-resolution imaging of power-sensitive samples.