Liver cells are the basic functional unit of the liver. However, repeated or sustained injury leads to structural disorders of liver lobules, proliferation of fibrous tissue and changes in structure, thus increasing scar tissue. Cellular fibrosis affects tissue stiffness, shear force, and other cellular mechanical forces. Mechanical force characteristics can serve as important indicators of cell damage and cirrhosis. Atomic force microscopy (AFM) has been widely used to study cell surface mechanics. However, characterization of the deep mechanical properties inside liver cells remains an underdeveloped field. In this work, cell nanoindentation was combined with finite element analysis to simulate and analyze the mechanical responses of liver cells at different depths in vitro and their internal responses and stress diffusion distributions after being subjected to normal stress. The sensitivities of the visco-hyperelastic parameters of the finite element model to the effects of the peak force and equilibrium force were compared. The force curves of alcohol-damaged liver cells at different depths were measured and compared with those of undamaged liver cells. The inverse analysis method was used to simulate the finite element model in vitro. Changes in the parameters of the cell model after injury were explored and analyzed, and their potential for characterizing hepatocellular injury and related treatments was evaluated. RESEARCH HIGHLIGHTS: This study aims to establish an in vitro hyperelastic model of liver cells and analyze the mechanical changes of cells in vitro. An analysis method combining finite element analysis model and nanoindentation was used to obtain the key parameters of the model. The multi-depth mechanical differences and internal structural changes of injured liver cells were analyzed.

OBJECTIVE: To compare the mechanical properties of human annulus fibrosus obtained by forceps versus bistoury and observe whether the measurement could be affected by forceps sampling method.
METHODS: In this study, the mechanical properties of the the extracellular matrix (ECM) of human annulus fibrosus, including elastic modulus and stiffness, were investigated using atomic force microscope (AFM). Tissue was obtained from patients during operation using a bistoury or nucleus pulposus forceps. Tissues obtained with the nucleus pulposus forceps were considered as the forceps group and those obtained with a bistoury were considered as the bistoury group.
RESULTS: There was no significant difference observed between the forceps and bistoury group according to histological staining. The elastic modulus of the forceps group was 0.41 ± 0.08 MPa, and that of bistoury group was 0.53 ± 0.13 MPa, and the difference between the two groups was statistically significant (p < 0.05). The stiffness of the forceps group was 0.024 ± 0.003 N/m, and that of the bistoury group was 0.037 ± 0.003 N/m, and the difference between the two groups was statistically significant (p < 0.05).
CONCLUSIONS: The results indicate that the forceps sampling method has a substantial negative effect on the micromechanical properties of the ECM of the annulus fibrosus. Bistoury sampling method is recommended as the experimental subject for exploring the micromechanics mechanisms of cervical degenerative disease.

Introduction Canal preparation is a critical step in endodontic therapy. Introducing nickel-titanium (NiTi) rotary instruments has significantly reduced the likelihood of errors in curved canals. However, due to their price, these instruments are often reused following autoclaving. The aim of this study is to compare and evaluate the surface characteristics of two designs of rotary NiTi files used in curved canals and subjected to multiple autoclaving cycles, utilizing an atomic force microscope for detailed analysis. Methods A total sample size of 24 files was taken, 12 files of Hyflex EDM (Coltene/Whaledent, Germany) files and WaveOne Gold (Dentsply Sirona, USA) files were then divided into four groups (n=6) as follows: Group I: Hyflex EDM control group; Group II: WaveOne Gold control group; Group III: Hyflex EDM experimental group; Group IV: WaveOne Gold experimental group. Sterilization using an autoclave was performed thrice for Groups I and II files. The files in Groups III and IV were used in simulated curved canals three times and autoclaved after each use. Atomic force microscopy was used to assess the surface roughness of the files after the first and third autoclave cycles. Results The results showed that, without statistical significance, Hyflex EDM exhibited the highest surface roughness after the first usage among the two file systems. Conclusion It can be concluded that both Hyflex EDM and WaveOne Gold files produced similar levels of surface changes when subjected to multiple usage and autoclaving cycles.

BACKGROUND: Lichen planopilaris (LPP) is a chronic lymphocytic skin disease manifested by progressive scarring alopecia. The diagnosis of LPP is made based on histopathological examination, although it is not always definite. The current study evaluates the effectiveness of non-invasive atomic force microscopy (AFM) hair examination in detecting morphological differences between healthy and diseased hair.
METHODS: Here, three to five hairs from lesional skin of 10 LPP patients were collected and examined at nine locations using AFM. At least four images were taken at each of the nine sites. Metric measurements were taken and metric (length, width, and scale step height) and morphological features (striated and smooth surface of scales, the presence of endocuticle and cortex, shape of scales edges, scratches, pitting, cracks, globules, and wavy edge) were compared with hair from healthy controls. In addition, areas on diseased hair where the process of pathological, unnatural delamination of the hair fiber occurs are described.
RESULTS: There was a statistically significant difference in the number of scratches in the initial sections of the LPP hair, in the intensity of wavy edges along the entire length of the tested hair, and in the number of scales with pitting in the middle section of the hair. In addition, a statistically significant higher number of scales with striated surface was found in LPP group starting at 3.5 cm from the root continuing towards the free end of the hair. Other morphological changes such as presence of cortex, globules, oval indentations, and rod-like macrofibrillar elements were also assessed, however, detailed results are not presented, as the differences shown in the number of these morphological changes were not significantly different.
CONCLUSIONS: This publication outlines the differences between virgin, healthy Caucasian hair, and the hair of LPP patients. The results of this study can be used for further research and work related to LPP. This is the first attempt to characterize the hair of LPP patients using AFM.

As the world moves toward a green economy and sustainable agriculture, bacterial viruses or bacteriophages (phages) become attractive biocontrol agents for controlling crop diseases. Effective utilization of phages in farms requires integrated knowledge of crops, pathogens, phages, and surroundings. Phages must encounter environmental fluctuations, including temperature, and must remain infectious for successful bacteria lysis. This work studied a soilborne RSJ2 phage discovered in Thailand, which can eliminate Ralstonia solanacearum, causing bacterial wilt disease in chili. We investigated how phage infectivity and nanomechanics responded to thermal changes. The plaque-based assay showed that the infectivity of the RSJ2 phage was stable within 24-40 °C, an average temperature fluctuation in tropical regions. The structural examination also showed that the phage remained intact. The nanomechanical property of the phage was inspected by the atomic force microscopy-based nanoindentation. The result revealed that the phage stiffness within 24-40 °C was statistically similar (0.05-0.06 N/m). Upon heating at 40 °C for 1, 5, and 10 h and resting at 25 °C, the stiffness of the phage particles increased to 0.09-0.11 N/m (54-83% increase). The stiffness results suggest structural adaptation of the protein subunits as a response to thermal alteration. The study exhibits that the phage structure is highly dynamic and can nanomechanically respond to varying temperatures. The phage stiffness may reveal insight into phage adaptation to environmental factors. Equipped with the knowledge of phage infectivity, structure, and nanomechanics, we can design practical guidelines for effective phage usage in farming and propelling green and safe agriculture.

To control three-dimensional (3D) cell spheroid formation, it is well-known the surface physicochemical and mechanical properties of cell culture materials are important; however, the formation and function of 3D cells are still unclear. This study demonstrated the precise control of the formation of 3D cells and 3D cell functions using diblock copolymers containing different ratios of a zwitterionic trimethylamine N-oxide group. The diblock copolymers were composed of poly(n-butyl methacrylate) (PBMA) as the hydrophobic unit for surface coating on a cell culture dish and stabilization in water, and poly(2-(dimethylamino)ethyl methacrylate) (PDMAEMA) as the precursor of N-oxide. The zwitterionic N-oxide converted from 0 to 100% using PDMAEMA. The wettability and surface zeta potential varied with different ratios of N-oxide diblock copolymer-coated surfaces, and the amount of protein adsorbed in the cell culture medium decreased monotonically with increasing N-oxide ratio. 3D cell spheroid formations were observed by seeding human umbilical cord mesenchymal stem cells (hUC-MSCs) in diblock copolymer-coated flat-bottom well plates, and the N-oxide ratio was over 40%. The cells proliferated in two-dimensions (2D) and did not form spheroids when the N-oxide ratio was less than 20%. Interestingly, the expression of undifferentiated markers of hUC-MSCs was higher on surfaces that adsorbed proteins to some extent and formed 50-150 μm spheroids in the range of 40-70% of N-oxide ratio. We revealed that a moderately protein-adsorbed surface allows precise control of spheroid formation and undifferentiated 3D cells and has potential applications for high-quality spheroids in regenerative medicine and drug screening.

Atomic force microscope enables ultra-precision imaging of living cells. However, atomic force microscope imaging is a complex and time-consuming process. The obtained images of living cells usually have low resolution and are easily influenced by noise leading to unsatisfactory imaging quality, obstructing the research and analysis based on cell images. Herein, an adaptive attention image reconstruction network based on residual encoder-decoder was proposed, through the combination of deep learning technology and atomic force microscope imaging supporting high-quality cell image acquisition. Compared with other learning-based methods, the proposed network showed higher peak signal-to-noise ratio, higher structural similarity and better image reconstruction performances. In addition, the cell images reconstructed by each method were used for cell recognition, and the cell images reconstructed by the proposed network had the highest cell recognition rate. The proposed network has brought insights into the atomic force microscope-based imaging of living cells and cell image reconstruction, which is of great significance in biological and medical research.

The surface micromorphology and roughening of the thermal evaporation-coated FTO/ZnS bilayer thin films annealed at 300, 400, 500, and 550 ∘ C for 1 h have been studied. AFM images of the prepared samples were analysed by the MountainsMap software, and the effects of the annealing temperature on the surface texture of the FTO/ZnS thin film\'s surface were investigated. Stereometric and advanced fractal analyses showed that the sample annealed at 500 ∘ C exhibited greater surface roughness and greater skewness and kurtosis. This film also has the most isotropic surface and exhibits the highest degree of heterogeneity. Also, despite the decrease in surface roughness with increasing temperature from 500 to 550 ∘ C , the fractal dimension tends to increase. The static water contact angle measurements indicate that the film annealed at 500 ∘ C exhibits higher hydrophobicity, which can be attributed to its greater topographic roughness. Our research indicates that the surface morphology of FTO/ZnS bilayer thin films is influenced by the annealing temperature. Changing factors such as roughness, fractality, and wettability parameters to help improve surface performance make the FTO/ZnS bilayer suitable for application in electronic and solar systems.

Achieving high-temperature superlubricity is essential for modern extreme tribosystems. Solid lubrication is the sole viable alternative due to the degradation of liquid ones but currently suffers from notable wear, instability, and high friction coefficient. Here, we report robust superlubricity in MoS2/graphene van der Waals heterostructures at high temperatures up to ∼850 K, achieved through localized heating to enable reliable friction testing. The ultralow friction of the MoS2/graphene heterostructure is found to be notably further reduced at elevated temperature and dominantly contributed by the MoS2 edge. The observation can be well described by a multi-contact model, wherein the thermally activated rupture of edge-contacts facilitates the sliding. Our results should be applicable to other van der Waals heterostructures and shed light on their applications for superlubricity at elevated temperature.

Artificial intelligence-based methods such as chemometrics, machine learning, and deep learning are promising tools that lead to a clearer and better understanding of data. Only with these tools, data can be used to its full extent, and the gained knowledge on processes, interactions, and characteristics of the sample is maximized. Therefore, scientists are developing data science tools mentioned above to automatically and accurately extract information from data and increase the application possibilities of the respective data in various fields. Accordingly, AI-based techniques were utilized for chemical data since the 1970s and this review paper focuses on the recent trends of chemometrics, machine learning, and deep learning for chemical and spectroscopic data in 2020. In this regard, inverse modeling, preprocessing methods, and data modeling applied to spectra and image data for various measurement techniques are discussed.