Tumors have posed a serious threat to human life and health. Researchers can determine whether or not cells are cancerous, whether the cancer cells are invasive or metastatic, and what the effects of drugs are on cancer cells by the physical properties such as hardness, adhesion, and Young's modulus. The atomic force microscope (AFM) has emerged as a key important tool for biomechanics research on tumor cells due to its ability to image and collect force spectroscopy information of biological samples with nano-level spatial resolution and under near-physiological conditions. This article reviews the existing results of the study of cancer cells with AFM. The main foci are the operating principle of AFM and research advances in mechanical property measurement, ultra-microtopography, and molecular recognition of tumor cells, which allows us to outline what we do know it in a systematic way and to summarize and to discuss future directions.

Indium (In) and other low melting point metals are used as interconnects in a variety of hybridized circuits and a full understanding of the metallurgy of these interconnects is important to the reliability and performance of the devices. This paper shows that room temperature focused ion beam (FIB) preparation of cross-sections, using Ga+ or Xe+ can result in artifacts that obscure the true In microbump structure. The use of modified milling strategies to minimize the increased local sample temperature are shown to produce cross-sections that are representative of the In bump microstructure in some sample configurations. Furthermore, cooling of the sample to cryogenic temperatures is shown to reliably eliminate artifacts in FIB prepared cross-sections of In bumps allowing the true bump microstructure to be observed.

The integrated differential phase contrast (IDPC) method is useful for generating the potential map of a thin sample. We evaluate theoretically the potential of IDPC imaging for thick samples by varying the focus at different sample thicknesses. Our calculations show that high defocus values result in enhanced anisotropy of the contrast transfer function (CTF) and uninterpretable images, if a quadrant detector is applied. We further show that applying a multi-sector detector can result in an almost isotropic CTF. By sector number-dependent calculations for both Cc/C3-corrected and C3-corrected scanning transmission electron microscopy (STEM), we show that the increase of detector sectors not only removes the anisotropy of the CTF, but also improves image contrast and resolution. For a proof-of-principle IDPC-STEM (uncorrected) experiment, we realize the functionality of a 12-sector detector from a physical quadrant detector and demonstrate the improvement in contrast and resolution on the example of InGaN/GaN quantum well structure.

Accurate geometrical calibration between the scan coordinates and the camera coordinates is critical in four-dimensional scanning transmission electron microscopy (4D-STEM) for both quantitative imaging and ptychographic reconstructions. For atomic-resolved, in-focus 4D-STEM datasets, we propose a hybrid method incorporating two sub-routines, namely a J-matrix method and a Fourier method, which can calibrate the uniform affine transformation between the scan-camera coordinates using raw data, without a priori knowledge of the crystal structure of the specimen. The hybrid method is found robust against scan distortions and residual probe aberrations. It is also effective even when defects are present in the specimen, or the specimen becomes relatively thick. We will demonstrate that a successful geometrical calibration with the hybrid method will lead to a more reliable recovery of both the specimen and the electron probe in a ptychographic reconstruction. We will also show that, although the elimination of local scan position errors still requires an iterative approach, the rate of convergence can be improved, and the residual errors can be further reduced if the hybrid method can be firstly applied for initial calibration. The code is made available as a simple-to-use tool to correct affine transformations of the scan-camera coordinates in 4D-STEM experiments.

The characterization of the three-dimensional arrangement of dislocations is important for many analyses in materials science. Dislocation tomography in transmission electron microscopy is conventionally accomplished through intensity-based reconstruction algorithms. Although such methods work successfully, a disadvantage is that they require many images to be collected over a large tilt range. Here, we present an alternative, semi-automated object-based approach that reduces the data collection requirements by drawing on the prior knowledge that dislocations are line objects. Our approach consists of three steps: (1) initial extraction of dislocation line objects from the individual frames, (2) alignment and matching of these objects across the frames in the tilt series, and (3) tomographic reconstruction to determine the full three-dimensional configuration of the dislocations. Drawing on innovations in graph theory, we employ a node-line segment representation for the dislocation lines and a novel arc-length mapping scheme to relate the dislocations to each other across the images in the tilt series. We demonstrate the method for a dataset collected from a dislocation network imaged by diffraction-contrast scanning transmission electron microscopy. Based on these results and a detailed uncertainty analysis for the algorithm, we discuss opportunities for optimizing data collection and further automating the method.

A direct comparison between electron transparent transmission electron microscope (TEM) samples prepared with gallium (Ga) and xenon (Xe) focused ion beams (FIBs) is performed to determine if equivalent quality samples can be prepared with both ion species. We prepared samples using Ga FIB and Xe plasma focused ion beam (PFIB) while altering a variety of different deposition and milling parameters. The samples’ final thicknesses were evaluated using STEM-EELS t/λ data. Using the Ga FIB sample as a standard, we compared the Xe PFIB samples to the standard and to each other. We show that although the Xe PFIB sample preparation technique is quite different from the Ga FIB technique, it is possible to produce high-quality, large area TEM samples with Xe PFIB. We also describe best practices for a Xe PFIB TEM sample preparation workflow to enable consistent success for any thoughtful FIB operator. For Xe PFIB, we show that a decision must be made between the ultimate sample thickness and the size of the electron transparent region.

Energy-filtering transmission electron microscopy (TEM) and bright-field TEM can be used to extract local sample thickness $t$ and to generate two-dimensional sample thickness maps. Electron tomography can be used to accurately verify the local $t$. The relations of log-ratio of zero-loss filtered energy-filtering TEM beam intensity ($I_{{\rm ZLP}}$) and unfiltered beam intensity ($I_{\rm u}$) versus sample thickness $t$ were measured for five values of collection angle in a microscope equipped with an energy filter. Furthermore, log-ratio of the incident (primary) beam intensity ($I_{\rm p}$) and the transmitted beam $I_{{\rm tr}}$ versus $t$ in bright-field TEM was measured utilizing a camera before the energy filter. The measurements were performed on a multilayer sample containing eight materials and thickness $t$ up to 800 nm. Local thickness $t$ was verified by electron tomography. The following results are reported:

• The maximum thickness $t_{{\rm max}}$ yielding a linear relation of log-ratio, $\ln ( {I_{\rm u}}/{I_{{\rm ZLP}}})$ and $\ln ( {I_{\rm p}}/{I_{{\rm tr}}} )$, versus $t$.

• Inelastic mean free path ($\lambda _{{\rm in}}$) for five values of collection angle.

• Total mean free path ($\lambda _{{\rm total}}$) of electrons excluded by an angle-limiting aperture.

• $\lambda _{{\rm in}}$ and $\lambda _{{\rm total}}$ are evaluated for the eight materials with atomic number from $\approx$10 to 79.

The results can be utilized as a guide for upper limit of $t$ evaluation in energy-filtering TEM and bright-field TEM and for optimizing electron tomography experiments.

Since it is now possible to record vibrational spectra at nanometer scales in the electron microscope, it is of interest to explore whether extended defects in crystals such as dislocations or grain boundaries will result in measurable changes of the phonon densities of states (dos) that are reflected in the spectra. Phonon densities of states were calculated for a set of high angle grain boundaries in silicon. The boundaries are modeled by supercells with up to 160 atoms, and the vibrational densities of states were calculated by taking the Fourier transform of the velocity–velocity autocorrelation function from molecular dynamics simulations with larger supercells doubled in all three directions. In selected cases, the results were checked on the original supercells by comparison with the densities of states obtained by diagonalizing the dynamical matrix calculated using density functional theory. Near the core of the grain boundary, the height of the optic phonon peak in the dos at 60 meV was suppressed relative to features due to acoustic phonons that are largely unchanged relative to their bulk values. This can be attributed to the variation in the strength of bonds in grain boundary core regions where there is a range of bond lengths.

The occurrence of multi-hit events and the separation distance between multi-hit ion pairs field evaporated from III-nitride semiconductors can potentially provide insights on neighboring chemistry, crystal structure, and field conditions. In this work, we quantify the range of variation in major III-N and III-III ion-pair separation to establish correlations with bulk composition, growth method, and ion-pair chemistry. The analysis of ion-pair separation along the AlGaN/GaN heterostructure system allows for comparison of Ga-N and Ga-Ga ion-pair separation between events evaporated from pure GaN and Al0.3Ga0.7N. From this, we aim to define a relative measure for the bond length of ion pairs within an AlGaN/GaN heterostructure. The distributions of pair separation revealed a distinct bimodal behavior that is unique to Al-N2+ ion pairs, suggesting the occurrence of both co-evaporation and molecular dissociation. Finally, we demonstrated that the two modes of ion-pair events align with the known variation in the surface electric field of the AlGaN(0001) structure. These findings demonstrate the utility of atom probe tomography in studying the crystallographic nature of nitride semiconductors.

Three independent analysis methods were developed to investigate the distribution of solid mass in foams analyzed by X-ray tomography with effective pixel sizes larger than the thickness of the solid network (sub-pixel conditions). Validation of the methods was achieved by a comparison with the results obtained employing high-resolution tomography for the same set of foams. The foams showed different solid mass distribution, which varied from being preferentially located on the edges, with a fraction of mass in the struts nearing 0.6, to materials in which the fraction of mass in the struts was low, under 0.15. In all cases, the accuracy of the proposed approaches was greater for materials with a higher fraction of mass in the struts. The method based on deconvolution of the attenuation probability density function yielded the closest results to the high-resolution characterizations. In contrast, analysis of the solid matrix thickness distribution after watershed segmentation, and binarization of high thickness regions (struts segmentation) required normalization through macroscopic measurements and revealed higher deviations with respect to the high-resolution results. However, segmentation-based methods allowed investigation of the heterogeneity of the fraction of mass in the struts along the sample.

It is known that 2D materials can exhibit a nonflat topography, which gives rise to an inherent strain. Since local curvature and strain influence mechanical, optical, and electrical properties, but are often difficult to distinguish from each other, a robust measurement technique is needed. In this study, a novel method is introduced, which is capable of obtaining quantitative strain and topography information of 2D materials with nanometer resolution. Relying on scanning nanobeam electron diffraction (NBED), it is possible to disentangle strain from the local sample slope. Using the positions of the diffraction spots of a specimen at two different tilts to reconstruct the locations and orientations of the reciprocal lattice rods, the local strain and slope can be simultaneously retrieved. We demonstrate the differences to strain measurements from a single NBED map in theory, simulation, and experiment. MoS2 monolayers with different shapes are used as simulation test structures. The slope and height information are recovered, as well as tensile and angular strain which have an absolute difference of less than 0.2% and 0.2° from the theoretical values. An experimental proof of concept using a freely suspended WSe2 monolayer together with a discussion of the accuracy of the method is provided.

The crystallographic analysis of nanoscale phases with dimensions well below the spatial probing volume of electron backscatter diffraction (EBSD) traditionally rely on electron microscopy in transmission (either in SEM or TEM), because EBSD patterns are invariably dominated by the matrix phase contribution and present seemingly no trace from such nanoscale phases. Yet, this study shows that such nanoscale features generate a very faint but valuable secondary diffraction signal which can be retrieved. A diffraction pattern postprocessing method is presented which focuses on the detection of such secondary signal emitted by nanoscale minority phases in overlapped patterns dominated by a dominant matrix signal. The predominant, majority phase contribution in EBSD patterns is removed by a close-neighbor pattern subtraction routine, after which both the conventional Hough indexing method as well as pattern matching methods can be used to reveal the crystallography, spatial distribution, morphology, and orientation of nanoscale minority phases initially absent from EBSD maps. Nanolamellar pearlitic steel, which has long been out of reach for EBSD, has been chosen as an application example.

Analytical studies of nanoparticles (NPs) are frequently based on huge datasets derived from hyperspectral images acquired using scanning transmission electron microscopy. These large datasets require machine learning computational tools to reduce dimensionality and extract relevant information. Principal component analysis (PCA) is a commonly used procedure to reconstruct information and generate a denoised dataset; however, several open questions remain regarding the accuracy and precision of reconstructions. Here, we use experiments and simulations to test the effect of PCA processing on data obtained from AuAg alloy NPs a few nanometers wide with different compositions. This study aims to address the reliability of chemical quantification after PCA processing. Our results show that the PCA treatment mitigates the contribution of Poisson noise and leads to better quantification, indicating that denoised results may be reliable from the point of view of both uncertainty and accuracy for properly planned experiments. However, the initial data need to be of sufficient quality: these results can only be obtained if the signal-to-noise ratio of input data exceeds a minimal value to avoid the occurrence of random noise bias in the PCA reconstructions.

Vaginitis is a prevalent gynecologic disease that threatens millions of women’s health. Although microscopic examination of vaginal discharge is an effective method to identify vaginal infections, manual analysis of microscopic leucorrhea images is extremely time-consuming and labor-intensive. To automate the detection and identification of visible components in microscopic leucorrhea images for early-stage diagnosis of vaginitis, we propose a novel end-to-end deep learning-based cells detection framework using attention-based detection with transformers (DETR) architecture. The transfer learning was applied to speed up the network convergence while maintaining the lowest annotation cost. To address the issue of detection performance degradation caused by class imbalance, the weighted sampler with on-the-fly data augmentation module was integrated into the detection pipeline. Additionally, the multi-head attention mechanism and the bipartite matching loss system of the DETR model perform well in identifying partially overlapping cells in real-time. With our proposed method, the pipeline achieved a mean average precision (mAP) of 86.00% and the average precision (AP) of epithelium, leukocyte, pyocyte, mildew, and erythrocyte was 96.76, 83.50, 74.20, 89.66, and 88.80%, respectively. The average test time for a microscopic leucorrhea image is approximately 72.3 ms. Currently, this cell detection method represents state-of-the-art performance.

The objective of this work was to characterize the ontogenesis of Protium spruceanum secretory ducts, to evaluate the effects of seasonality on that process, and to characterize the chemical nature of the resin. Morphometric, anatomical, micromorphometric, histochemical, and ultrastructural evaluations of shoot apexes and chemical analyses of the resin were performed. The ducts of schizolysigenous origin are distributed in the primary and secondary phloem. The subsecretory tissue is meristematic and can restore the secretory epithelium. Secretory epithelial cells have wall thickening resembling that of the Casparian strip that regulates secretion reflux. The main resin compounds are pentacyclic triterpenoids, α- and β-amyrins, and α- and β-amyrenones, which are reported here for the first time for this species. The presence of electron-dense and electron-opaque structures, in the secretory epithelial cells, are compatible with the triterpenes and mucilage identified in the resin. Rising temperatures, rainfall, and increasing day length induce the formation of ducts in the vascular cambium throughout Spring/Summer. The abundant production of resin rich in pentacyclic triterpenes indicates the potential use of the species for medicinal and cosmetic purposes. The understanding that secretory processes are concentrated during the Spring/Summer seasons will contribute to the definition of resin extraction management strategies.

The present study was designed to compare the ultrastructure of early endothelial progenitor cells (EPCs) derived from rabbit peripheral blood (PB-EPCs) and bone marrow (BM-EPCs). After the cells had been isolated and cultivated up to passage 3, microphotographs obtained from transmission electron microscope were evaluated from qualitative and quantitative (unbiased stereological approaches) points of view. Our results revealed that both cell populations displayed almost identical ultrastructural characteristics represented by abundant cellular organelles dispersed in the cytoplasm. Moreover, the presence of very occasionally occurring mature endothelial-specific Weibel–Palade bodies (WPBs) confirmed their endothelial lineage origin. The more advanced stage of their differentiation was also demonstrated by the relatively low nucleus/cytoplasm (N/C) ratios (0.41 ± 0.19 in PB-EPCs; 0.37 ± 0.25 in BM-EPCs). Between PB-EPCs and BM-EPCs, no differences in proportions of cells occupied by nucleus (28.13 ± 8.97 versus 25.10 ± 11.48%), mitochondria (3.71 ± 1.33 versus 4.23 ± 1.00%), and lipid droplets (0.65 ± 1.01 versus 0.36 ± 0.40%), as well as in estimations of the organelles surface densities were found. The data provide the first quantitative evaluation of the organelles of interest in PB-EPCs and BM-EPCs, and they can serve as a research framework for understanding cellular function.

Polyalthia longifolia is known for its anti-oxidative properties, which might contribute to the antiaging action. Hence, the current research was conducted to evaluate the antiaging activity of P. longifolia leaf methanolic extract (PLME) in a yeast model based on morphology using microscopic approaches. Saccharomyces cerevisiae BY611 strain yeast cells were treated with 1.00 mg/mL of PLME. The antiaging activity was assessed by determining the replicative lifespan, total lifespan, vacuole morphology by light microscopy, extra-morphology by scanning (SEM), and intra-morphology by transmission (TEM) electron microscopy. The findings demonstrated that PLME treatment significantly accelerated the replicative and total lifespan of the yeast cells. PLME treatment also delays the formation of large apoptotic-like type 3 yeast cell vacuoles. The untreated yeast cells demonstrated aging morphology via SEM analysis, such as shrinking, regional invaginations, and wrinkled cell surface. The TEM analysis revealed the quintessential aging intracellular morphology such as swollen, wrinkled, or damaged vacuole formation of the circular endoplasmic reticulum, a rupture in the nuclear membrane, fragmentation of the nucleus, and complete damaged cytoplasm. Decisively, the present study revealed the vital role of PLME in the induction of antiaging activity in a yeast model using three microscopic approaches—SEM, TEM, and bright-field light microscope.

Cryo-electron microscopy, widely used for high-resolution protein structure determination, does not require staining. Yet negative staining with heavy metal salts such as uranyl acetate has been in persistent demand since the 1950s due to its image contrasting capabilities at room temperature with a common electron microscope. However, uranium compounds are nuclear fuel materials and are tightly controlled worldwide. Acetates of each lanthanoid series elements except promethium are prepared at the same concentration (2%(w/v)) and used as a model on horse spleen ferritin for electron microscopic analysis to systematically evaluate their effectiveness as electron staining reagents for the protein. Analysis shows that the triacetates of samarium and europium, followed by gadolinium and erbium, and then lanthanum and neodymium could function as electron staining reagents. Thulium-triacetate precipitates thin plate-like crystals and may be used for selecting better imaging fields. Of the 14 lanthanoid-triacetates examined, about half are viable alternatives to uranyl acetate as an electron staining reagent for ferritin, and there appears an optimal range in ionic sizes for promising lanthanoids. This is the first systematic investigation of lanthanoid transition heavy metal triacetates from the viewpoint of lanthanoid contraction, using density distribution histograms of electron micrographs as an indicator for comparison with uranyl acetate.

Hibernation is a biological status during which hibernating animals acclimatize themselves to reduced energy consumption through extreme but governed decline in self-metabolism. The role of mitochondria (Mt) in metabolic suppression during hibernation has already been elaborated in different organs and species. Nonetheless, the concretely changing process of mitochondrial architecture and the mechanism underlying this transformation during hibernation remains unclear. Herein, the present study was aimed at clarifying the detailed alteration of mitochondrial morphology and its potential role in the Chinese soft-shelled turtle (Pelodiscus sinensis) during different stages of hibernation. Compared with the nonhibernation period, the mitochondrial architecture was changing from round to crescent, and lipid droplet (LD)/Mt interaction was enhanced during hibernation, as observed by transmission electron microscopy (TEM). Further ultrastructural analysis uncovered that mitochondrial fusion was promptly accelerated in the early stage of hibernation, followed by mitochondrial fission in the middle stage, and mitophagy was boosted in the late stage. Moreover, gene and protein expression related to mitochondrial fusion, fission, and mitophagy accorded closely with the mitochondrial ultrastructural changes in different stages of hibernation. Taken together, our results clarified that the transformation of mitochondrial architecture and mitochondrial dynamics are of vital importance in maintaining internal environment homeostasis of Pelodiscus sinensis.

In vivo transparent vessel segmentation is important to life science research. However, this task remains very challenging because of the fuzzy edges and the barely noticeable tubular characteristics of vessels under a light microscope. In this paper, we present a new machine learning method based on blood flow characteristics to segment the global vascular structure in vivo. Specifically, the videos of blood flow in transparent vessels are used as input. We use the machine learning classifier to classify the vessel pixels through the motion features extracted from moving red blood cells and achieve vessel segmentation based on a region-growing algorithm. Moreover, we utilize the moving characteristics of blood flow to distinguish between the types of vessels, including arteries, veins, and capillaries. In the experiments, we evaluate the performance of our method on videos of zebrafish embryos. The experimental results indicate the high accuracy of vessel segmentation, with an average accuracy of 97.98%, which is much more superior than other segmentation or motion-detection algorithms. Our method has good robustness when applied to input videos with various time resolutions, with a minimum of 3.125 fps.