Label-free biological cell imaging relies on rapid multimode phase imaging of biological samples in natural settings. To improve image contrast, phase is encoded into intensity information using the differential interference contrast (DIC) and Zernike phase contrast (ZPC) techniques. To enable multimode contrast-enhanced observation of unstained specimens, this paper proposes an improved multimode phase imaging method based on the transport of intensity equation (TIE), which combines conventional microscopy with computational imaging. The ZPC imaging module based on adaptive aperture adjustment is applied when the quantitative phase results of biological samples have been obtained by solving the TIE. Simultaneously, a rotationally symmetric shear-based technique is used that can yield isotropic DIC. In this paper, we describe numerical simulation and optical experiments carried out to validate the accuracy and viability of this technology. The calculated Michelson contrast of the ZPC image in the resolution plate experiment increased from 0.196 to 0.394.

Fourier ptychographic microscopy (FPM) enables quantitative phase imaging with a large field-of-view and high resolution by acquiring a series of low-resolution intensity images corresponding to different spatial frequencies stitched together in the Fourier domain. However, the presence of various aberrations in an imaging system can significantly degrade the quality of reconstruction results. The imaging performance and efficiency of the existing embedded optical pupil function recovery (EPRY-FPM) aberration correction algorithm are low due to the optimization strategy.
An aberration correction method (AA-P algorithm) based on an improved phase recovery strategy is proposed to improve the reconstruction image quality.
This algorithm uses adaptive modulation factors, which are added while updating iterations to optimize the spectral function and optical pupil function updates of the samples, respectively. The effectiveness of the proposed algorithm is verified through simulations and experiments using an open-source biological sample dataset.
Experimental results show that the proposed AA-P algorithm in an optical system with hybrid aberrations, recovered complex amplitude images with clearer contours and higher phase contrast. The image reconstruction quality was improved by 82.6% when compared with the EPRY-FPM algorithm.
The proposed AA-P algorithm can reconstruct better results with faster convergence, and the recovered optical pupil function can better characterize the aberration of the imaging system. Thus, our method is expected to reduce the strict requirements of wavefront aberration for the current FPM.

Surface and interface, with unique local characteristics different from bulk structure, are of great significance in various applications of metal-organic frameworks (MOFs), which should be studied by real-space imaging methods, such as electron microscopy. However, it is still challenging to atomically resolve these local structures in MOFs, because they are even more sensitive to electron irradiation. Here, we use integrated differential phase contrast scanning transmission electron microscopy (iDPC-STEM) to achieve the atomic imaging of both the metal nodes and organic linkers in UiO-66 (Zr) nanocrystals and their assembly. After adding acetic acid, we modulate the whole process of MOF assembly and observe the organic linkers at both the surfaces and twin interfaces in the chemically assembled UiO-66 (Zr) crystals by the iDPC-STEM. These results bring us a deeper understanding on the role of acid modulators that promote the MOF assembly by generating the missing-linker defects on the crystal surface.

The main aspects of material research: material synthesis, material structure, and material properties, are interrelated. Acquiring atomic structure information of electron beam sensitive materials by electron microscope, such as porous zeolites, organic-inorganic hybrid perovskites, metal-organic frameworks, is an important and challenging task. The difficulties in characterization of the structures will inevitably limit the optimization of their synthesis methods and further improve their performance. The emergence of integrated differential phase contrast scanning transmission electron microscopy (iDPC-STEM), a STEM characterization technique capable of obtaining images with high signal-to-noise ratio under lower doses, has made great breakthroughs in the atomic structure characterization of these materials. This article reviews the developments and applications of iDPC-STEM in electron beam sensitive materials, and provides an outlook on its capabilities and development.

The current classical blood smear technique to observe the morphology of single red blood cells (RBCs) for classification is a laborious and error-prone process. To objectively evaluate the morphology of blood cells, we established a method of computational imaging based on a programmable light emitting diode array. By using quantitative differential phase contrast (qDPC), we characterized the morphology of unlabeled RBCs as well as blood smears. By focusing on comparing the difference of imaging between unlabeled RBCs and stained RBCs under multimode microscopic imaging technology, we demonstrated that qDPC could clearly differentiate discocytes and spherocytes in both unlabeled RBCs and blood smears. The phase map provided by quantitative phase imaging further enhanced the classification accuracy. According to statistical analysis from morphological indexes, the qDPC imaging has a significantly improvement in non-circularity, texture inhomogeneity and equivalent diameters of cells. Thus, this method has a significant superiority in the capability to analyze the morphology of RBCs and could be applied to clinical assays for determining morphological, functional, and structural deterioration of RBCs.

Scanning transmission electron microscopy (STEM) is a powerful imaging technique and has been widely used in current material science research. The attempts of applying STEM (annual dark field (ADF)-STEM or annular bright field (ABF)-STEM) into biological research have been going on for decades while applications have still been limited because of the existing bottlenecks in dose efficiency and non-linearity in contrast. Recently, integrated differential phase contrast (iDPC) STEM technique emerged and achieved a linear phase contrast imaging condition, while resolving signals of light elements next to heavy ones even at low electron dose. This enables successful investigation of beam sensitive materials. Here, we investigate iDPC-STEM advantages in biology, in particular, chemically fixed and resin embedded biological tissues. By comparing results to the conventional TEM, we have found that iDPC-STEM not only shows better contrast but also resolves more structural details at molecular level, including conditions of extremely low dose and minimal heavy-atom staining. We also compare iDPC-STEM with ABF-STEM and found that contrast of iDPC-STEM is even further improved, moderately in lower frequency domains while highly with preserving high frequency biological structural details. For thick sample sections, iDPC-STEM is particularly advantageous. It avoids contrast inversion canceling effects, and by adjusting the depth of focus, fully preserves the contrast of structural details along with the sample. In addition, using depth-sectioning, iDPC-STEM enables resolving in-depth structural variation. Our results suggest that iDPC-STEM have the place and advantages within the future biological research.

BACKGROUND: The structural changes of gastric mucosa are considered as an important window of early gastric lesions. This article shows an imaging method of the stomach that does not use imaging agents. X-ray phase-contrast images of different stages of gastric development were taken using micrometer level X-ray in-line phase-contrast imaging (XILPCI) technique on synchrotron radiation facility. The aim of the study was to demonstrate that the imaging technique is an appropriate method for micron imaging of the gastric structures.
METHODS: The stomachs of 4-, 6- and 12-week-old rats were removed and cleaned. XILPCI has 1000 times greater soft tissue contrast than that of X-ray traditional absorption radiography. The projection images of the rats stomachs were recorded by an XILPCI charge coupled device (CCD) at 9-μm image resolution.
RESULTS: The X-ray in-line phase-contrast images of the different stages of rats\' gastric specimens clearly showed the gastric architectures and the details of the gastro-duodenal region. 3-dimensional (3D) stomach anatomical structure images were reconstruction.
CONCLUSIONS: The reconstructed gastric 3D images can clearly display the internal structure of the stomach. XILPCI may be a useful method for medical research in the future.

A prophage comprises a bacteriophage genome that has integrated into a host bacterium\'s DNA, which generally permits the cell to grow and divide normally. However, the prophage can be induced by various stresses, or induction can occur spontaneously. After prophage induction, viral replication and production of endolysins begin until the cell lyses and phage particles are released. However, the heterogeneity of prophage induction and lysis of individual cells in a population and the dynamics of a cell undergoing lysis by prophage induction have not been fully characterized. Here, we used Raman tweezers and live-cell phase-contrast microscopy to characterize the Raman spectral and cell length changes that occur during the lysis of individual Bacillus subtilis cells from spores that carry PBSX prophage during spores\' germination, outgrowth, and then vegetative growth. Major findings of this work are as follows: (i) After addition of xylose to trigger prophage induction, the intensities of Raman spectral bands associated with nucleic acids of single cells in induced cultures gradually fell to zero, in contrast to the much smaller changes in protein band intensities and no changes in nucleic acid bands in uninduced cultures; (ii) the nucleic acid band intensities from an individual induced cell exhibited a rapid decrease, following a long lag period; (iii) after the addition of nutrient-rich medium with xylose, single spores underwent a long period (228 ± 41.4 min) for germination, outgrowth, and vegetative growth, followed by a short period of cell burst in 1.5 ± 0.8 min at a cell length of 8.2 ± 5.5 μm; (iv) the latent time (Tlatent) between the addition of xylose and the start of cell burst was heterogeneous in cell populations; however, the period (ΔTburst) from the latent time to the completion of cell lysis was quite small; (v) in a poor medium with l-alanine alone, addition of xylose caused prophage induction following spore germination but with longer Tlatent and ΔTburst times and without cell elongation; (vi) spontaneous prophage induction and lysis of individual cells from spores in a minimal nutrient medium were observed without xylose addition, and cell length prior to cell lysis was ∼4.1 μm, but spontaneous prophage induction was not observed in a rich medium; (vii) in a rich medium, addition of xylose at a time well after spore germination and outgrowth significantly shortened the average Tlatent time. The results of this study provide new insights into the heterogeneity and dynamics of lysis of individual B. subtilis cells derived from spores upon prophage induction.

The use of models of stem cell differentiation to trophoblastic cells provides an effective perspective for understanding the early molecular events in the establishment and maintenance of human pregnancy. In combination with the newly developed deep learning technology, the automated identification of this process can greatly accelerate the contribution to relevant knowledge. Based on the transfer learning technique, we used a convolutional neural network to distinguish the microscopic images of Embryonic stem cells (ESCs) from differentiated trophoblast -like cells (TBL). To tackle the problem of insufficient training data, the strategies of data augmentation were used. The results showed that the convolutional neural network could successfully recognize trophoblast cells and stem cells automatically, but could not distinguish TBL from the immortalized trophoblast cell lines in vitro (JEG-3 and HTR8-SVneo). We compare the recognition effect of the commonly used convolutional neural network, including DenseNet, VGG16, VGG19, InceptionV3, and Xception. This study extends the deep learning technique to trophoblast cell phenotype classification and paves the way for automatic bright-field microscopic image analysis of trophoblast cells in the future.

Cryo-electron microscopy is an essential tool for high-resolution structural studies of biological systems. This method relies on the use of phase contrast imaging at high defocus to improve information transfer at low spatial frequencies at the expense of higher spatial frequencies. Here we demonstrate that electron ptychography can recover the phase of the specimen with continuous information transfer across a wide range of the spatial frequency spectrum, with improved transfer at lower spatial frequencies, and as such is more efficient for phase recovery than conventional phase contrast imaging. We further show that the method can be used to study frozen-hydrated specimens of rotavirus double-layered particles and HIV-1 virus-like particles under low-dose conditions (5.7 e/Å2) and heterogeneous objects in an Adenovirus-infected cell over large fields of view (1.14 × 1.14 μm), thus making it suitable for studies of many biologically important structures.