Revealing the Interlayer Interaction Forces in 2D Graphene Materials by Graphene-Wrapped Nanoprobe.

Understanding the interlayer interaction between 2D layered structures is critical for the construction of various micro- and nanoscale functional devices. However, both the normal and the tangential interlayer interactions between 2D layered materials have rarely been studied simultaneously. In this work, an immersion and lift-up method is proposed to wrap a layer of graphene flakes onto a plasma-pretreated atomic force microscopy (AFM) nanoprobe for the measurements of interaction forces by AFM. The normal interactions (adhesion force and adhesion energy) and tangential interactions (friction force) between two different probes (Pt-coated probe and graphene-wrapped probe) and two different 2D graphene materials [graphene and graphene oxide (GO)] were systematically measured, respectively. The adhesion energies of Pt-GO, Pt-graphene, graphene-GO, and graphene-graphene were measured to be 0.72 ± 0.05, 0.41 ± 0.03, 0.19 ± 0.02, and 0.10 ± 0.02 J m-2, respectively. The graphene-graphene contact pair showed the lowest adhesion force (5.57 ± 1.03 nN) and adhesion energy (0.10 ± 0.02 J m-2), which was attributed to the strong covalent bonds and charge density distribution. The friction coefficients of Pt-GO, graphene-GO, Pt-graphene, and graphene-graphene were determined to be 0.38, 0.14, 0.054, and 0.013. The graphene-graphene tribo-pair exhibited a superlow friction state for a long time, which was attributed to incommensurate contact and weak van der Waals interactions. These findings provide a technical route to reveal the interlayer interactions of various 2D layered materials, which can be widely applied in microelectromechanical systems.

A Nanoparticle-Based Artificial Ear for Personalized Classification of Emotions in the Human Voice Using Deep Learning.

Artificial intelligence and human-computer interaction advances demand bioinspired sensing modalities capable of comprehending human affective states and speech. However, endowing skin-like interfaces with such intricate perception abilities remains challenging. Here, we have developed a flexible piezoresistive artificial ear (AE) sensor based on gold nanoparticles, which can convert sound signals into electrical signals through changes in resistance. By testing the sensor's performance at both frequency and sound pressure level (SPL), the AE has a frequency response range of 20 Hz to 12 kHz and can sense sound signals from up to 5 m away at a frequency of 1 kHz and an SPL of 126 dB. Furthermore, through deep learning, the device achieves up to 96.9% and 95.0% accuracy in classification and recognition applications for seven emotional and eight urban environmental noises, respectively. Hence, on one hand, our device can monitor the patient's emotional state by their speech, such as sudden yelling and screaming, which can help healthcare workers understand patients' condition in time. On the other hand, the device could also be used for real-time monitoring of noise levels in aircraft, ships, factories, and other high-decibel equipment and environments.

Directly Characterizing the Capture Radius of Tethered Double-Stranded DNA by Single-Molecule Nanopipette Manipulation.

The tethered molecule exhibits characteristics of both free and fixed states, with the electrodynamics involved in its diffusion, electrophoresis, and stretching processes still not fully understood. We developed a Single-Molecule Manipulation, Identification, and Length Examination (SMILE) system by integrating piezoelectric devices with nanopipettes. This system enabled successful capture and stretching of tethered double-stranded DNA within the nanopore. Our research unveiled distinct capture (rcapture) and stretch radii (rstretch) surrounding the DNA's anchor point. Notably, consistent ratios of capture radius for DNA of varying lengths (2k, 4k, and 6k base pairs) were observed across different capturing voltages, approximately 1:1.4:1.83, showing a resemblance to their gyration radius ratios. However, the ratios of stretch radius are consistent to their contour length (L0), with the stretching ratio (rstretch/L0) increasing from 70 to 90% as the voltage rose from 100 to 1000 mV. Additionally, through numerical simulations, we identified the origin of capture and stretch radii, determined by the entropic elasticity-induced capture barrier and the electric field-dominant escape barrier. This research introduces an innovative methodology and outlines research perspectives for a comprehensive exploration of the conformational, electrical, and diffusion characteristics of tethered molecules.

Multidepth quantitative analysis of liver cell viscoelastic properties: Fusion of nanoindentation and finite element modeling techniques.

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.

Cytotoxic and Antitumor Agents from Genus Rubia.

Genus Rubia is widely distributed in almost all regions of the world, with 36 species and 2 varieties in China. Rubia species, such as Rubia cordifolia, have been used in traditional Chinese medicine for the treatment of diseases since ancient times. In recent years, the study of anticancer effects in traditional Chinese medicine has become a popular topic, and some studies have shown that several Rubia species extracts have cytotoxic and antitumor effects, and some of them have been shown to contain specific antitumor agents. Therefore, this review focuses on the cytotoxic and antitumor effects of the chemical constituents contained in Genus Rubia. Summarized 71 types of chemical substances in 5 categories with the effect of cytotoxicity and antitumor, as well as their structures, targets and mechanisms of action.

Research Progress on Saccharide Molecule Detection Based on Nanopores.

Saccharides, being one of the fundamental molecules of life, play essential roles in the physiological and pathological functions of cells. However, their intricate structures pose challenges for detection. Nanopore technology, with its high sensitivity and capability for single-molecule-level analysis, has revolutionized the identification and structural analysis of saccharide molecules. This review focuses on recent advancements in nanopore technology for carbohydrate detection, presenting an array of methods that leverage the molecular complexity of saccharides. Biological nanopore techniques utilize specific protein binding or pore modifications to trigger typical resistive pulses, enabling the high-sensitivity detection of monosaccharides and oligosaccharides. In solid-state nanopore sensing, boronic acid modification and pH gating mechanisms are employed for the specific recognition and quantitative analysis of polysaccharides. The integration of artificial intelligence algorithms can further enhance the accuracy and reliability of analyses. Serving as a crucial tool in carbohydrate detection, we foresee significant potential in the application of nanopore technology for the detection of carbohydrate molecules in disease diagnosis, drug screening, and biosensing, fostering innovative progress in related research domains.

Concanavalin-conjugated zinc-metal-organic framework drug for pH-controlled and targeted therapy of wound bacterial infection.

Wounds are prone to infection which may be fatal to the life of the patient. The use of antibiotics is essential for managing bacterial infections in wounds, but the long-term use of high doses of antibiotics may lead to bacterial drug resistance and even to creation of superbacteria. Therefore, the development of targeted antimicrobial treatment strategies and the reduction in antibiotic usage are of utmost urgency. In this study, a multifunctional nanodrug delivery system (Cef-rhEGF@ZIF-8@ConA) for the treatment of bacteriostatic infection was synthesized through self-assembly of Zn2+, cefradine (Cef) and recombinant human epidermal growth factor (rhEGF), then conjugated with concanavalin (ConA), which undergoes pH-responsive degradation to release the drugs. First, ConA can specifically combine with bacteria and inhibit the rapid release of Zn2+ ions, thus achieving a long-acting antibacterial effect. Cef exerts its antibacterial effect by inhibiting the synthesis of bacterial membrane proteins. Finally, Zn2+ ions released from the Zn-metal-organic framework (MOF) demonstrate bacteriostatic properties by enhancing the permeability of the bacterial cell membrane. Furthermore, rhEGF upregulates angiogenesis-associated genes, thereby promoting angiogenesis, re-epithelialization and wound healing processes. The results showed that Cef-rhEGF@ZIF-8@ConA has good biocompatibility, with antibacterial efficacy against Staphylococcus aureus and Escherichia coli of 99.61 % and 99.75 %, respectively. These nanomaterials can inhibit the release of inflammatory cytokines and promote the release of anti-inflammatory cytokines, while also stimulating the proliferation of fibroblasts to facilitate wound healing. Taken together, the Cef-rhEGF@ZIF-8@ConA nanosystem is an excellent candidate in clinical therapeutics for bacteriostatic infection and wound healing.

Laser Interference Additive Manufacturing: Mask Bundle Shape Bionic Shark Skin Structure.

Here, we explored a new manufacturing strategy that uses the mask laser interference additive manufacturing (MLIAM) technique, which combines the respective strengths of laser interference lithography and mask lithography to efficiently fabricate across-scales three-dimensional bionic shark skin structures with superhydrophobicity and adhesive reduction. The phenomena and mechanisms of the MLIAM curing process were revealed and analyzed, showing the feasibility and flexibility. In terms of structural performance, the adhesive force on the surface can be tuned based on the growth direction of the bionic shark skin structures, where the maximum rate of the adhesive reduction reaches about 65%. Furthermore, the evolution of the directional diffusion for the water droplet, which is based on the change of the contact angle, was clearly observed, and the mechanism was also discussed by the models. Moreover, no-loss transportations were achieved successfully using the gradient adhesive force and superhydrophobicity on the surface by tuning the growth direction and modifying by fluorinated silane. Finally, this work gives a strategy for fabricating across-scale structures on micro- and nanometers, which have potential application in bioengineering, diversional targeting, and condenser surface.

Probing action potentials of single beating cardiomyocytes using atomic force microscopy.

This paper presents a method for using atomic force microscopy to probe action potentials of single beating cardiomyocytes at the nanoscale. In this work, the conductive tip of an atomic force microscope (AFM) was used as a nanoelectrode to record the action potentials of self-beating cardiomyocytes in both the non-constant force contact mode and the constant force contact mode. An electrical model of a tip-cell interface was developed and the indentation force effect on the seal of an AFM conductive tip-cell membrane was theoretically analyzed. The force feedback of AFM allowed for the precise control of tip-cell contact, and enabled reliable measurements. The feasibility of simultaneously recording the action potentials and force information during the contraction of the same beating cardiomyocyte was studied. Furthermore, the AFM tip electrode was used to probe the differences of action potentials using different drugs. This method provides a way at the nanoscale for electrophysiological studies on single beating cardiomyocytes, neurons, and ion channels embedded within the cell membrane in relation to disease states, pharmaceutical drug testing and screening.

pH-induced changes in IgE molecules measured by atomic force microscopy.

The environment surrounding proteins is tightly linked to its dynamics, which can significantly influence the conformation of proteins. This study focused on the effect of pH conditions on the ultrastructure of Immunoglobulin E (IgE) molecules. Herein, the morphology, height, and area of IgE molecules incubated at different pH were imaged by atomic force microscopy (AFM), and the law of IgE changes induced by pH value was explored. The experiment results indicated that the morphology, height and area of IgE molecules are pH dependent and highly sensitive. In particular, IgE molecules were more likely to present small-sized ellipsoids under acidic conditions, while IgE molecules tend to aggregate into large-sized flower-like structures under alkaline conditions. In addition, it was found that the height of IgE first decreased and then increased with the increase of pH, while the area of IgE increased with the increase of pH. This work provides valuable information for further study of IgE, and the methodological approach used in this study is expected to developed into AFM to investigate the changes of IgE molecules mediated by other physical and chemical factors. RESEARCH HIGHLIGHTS: The ultrastructure of IgE molecules is pH dependent and highly sensitive. IgE molecules were tend to present small-sized ellipsoids under acidic pH. Alkaline pH drives IgE self-assembly into flower-like aggregates.

Cell recognition based on features extracted by AFM and parameter optimization classifiers.

Intelligent technology can assist in the diagnosis and treatment of disease, which would pave the way towards precision medicine in the coming decade. As a key focus of medical research, the diagnosis and prognosis of cancer play an important role in the future survival of patients. In this work, a diagnostic method based on nano-resolution imaging was proposed to meet the demand for precise detection methods in medicine and scientific research. The cell images scanned by AFM were recognized by cell feature engineering and machine learning classifiers. A feature ranking method based on the importance of features to responses was used to screen features closely related to categorization and optimization of feature combinations, which helps to understand the feature differences between cell types at the micro level. The results showed that the Bayesian optimized back propagation neural network has accuracy rates of 90.37% and 92.68% on two cell datasets (HL-7702 & SMMC-7721 and GES-1 & SGC-7901), respectively. This provides an automatic analysis method for identifying cancer cells or abnormal cells, which can help to reduce the burden of medical or scientific research, decrease misjudgment and promote precise medical care for the whole society.

High-quality AFM image acquisition of living cells by modified residual encoder-decoder network.

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.

Refractory dissolved organic matters in sludge leachate trigger the combination of anammox and denitratation for advanced nitrogen removal.

The cost-effective treatment of sludge leachate (SL) with high nitrogen content and refractory dissolved organic matter (rDOM) has drawn increasing attention. This study employed, for the first time, a rDOM triggered denitratation-anammox continuous-flow process to treat landfill SL. Moreover, the mechanisms of exploiting rDOM from SL as an inner carbon source for denitratation were systematically analyzed. The results demonstrated outstanding nitrogen and rDOM removal performance without any external carbon source supplement. In this study, effluent concentrations of 4.27 ± 0.45 mgTIN/L and 5.58 ± 1.64 mgTN/L were achieved, coupled with an impressive COD removal rate of 65.17 % ± 1.71 %. The abundance of bacteria belonging to the Anaerolineaceae genus, which were identified as rDOM degradation bacteria, increased from 18.23 % to 35.62 %. As a result, various types of rDOM were utilized to different extents, with proteins being the most notable, except for lignins. Metagenomic analysis revealed a preference for directing electrons towards NO3--N reductase rather than NO2--N reductase, indicating the coupling of denitratation bacteria and anammox bacteria (Candidatus Brocadia). Overall, this study introduced a novel synergy platform for advanced nitrogen removal in treating SL using its inner carbon source. This approach is characterized by low energy consumption and operational costs, coupled with commendable efficiency.

Gas permeable membrane electrode assembly with in situ utilization of authigenic acid and base for transmembrane electro-chemisorption to enhance ammonia recovery from wastewater.

Ammonia recovery from wastewater is of great significance for aquatic ecology safety, human health and carbon emissions reduction. Electrochemical methods have gained increasing attention since the authigenic base and acid of electrochemical systems can be used as stripper and absorbent for transmembrane chemisorption of ammonia, respectively. However, the separation of electrodes and gas permeable membrane (GPM) significantly restricts the ammonia transfer-transformation process and the authigenic acid-base utilization. To break the restrictions, this study developed a gas permeable membrane electrode assembly (GPMEA), which innovatively integrated anode and cathode on each side of GPM through easy phase inversion of polyvinylidene fluoride binder, respectively. With the GPMEA assembled in a stacked transmembrane electro-chemisorption (sTMECS) system, in situ utilization of authigenic acid and base for transmembrane electro-chemisorption of ammonia was achieved to enhance the ammonia recovery from wastewater. At current density of 60 A/m2, the transmembrane ammonia flux of the GPMEA was 693.0 ± 15.0 g N/(m2·d), which was 86 % and 28 % higher than those of separate GPM and membrane cathode, respectively. The specific energy consumption of the GPMEA was 9.7∼16.1 kWh/kg N, which were about 50 % and 25 % lower than that of separate GPM and membrane cathode, respectively. Moreover, the application of GPMEA in the ammonia recovery from wastewater is easy to scale up in the sTMECS system. Accordingly, with the features of excellent performance, energy saving and easy scale-up, the GPMEA showed good prospects in electrochemical ammonia recovery from wastewater.

A stacked transmembrane electro-chemisorption system connected by hydrophobic gas permeable membranes for on-site utilization of authigenic acid and base to enhance ammonia recovery from wastewater.

The ammonia recovery from wastewater via electrochemical technologies represents a promising way for wastewater treatment, resource recovery, and carbon emissions reduction. However, chemicals consumption and reactors scalability of the existing electrochemical systems have become the key challenges for their development and application. In this study, a stacked transmembrane electro-chemisorption (sTMECS) system was developed to utilize authigenic acid and base on site for enhancing ammonia recovery from wastewater. The easily scaled up system was achieved via innovatively connecting the cathode chamber in a unit with the anode chamber in the adjacent unit by a hydrophobic gas permeable membrane (GPM). Thus, authigenic base at cathodes and authigenic acid at anodes could be utilized as stripper and absorbent on site to enhance the transmembrane chemisorption of ammonia. Continuous power supply, reducing the distances of electrodes to GPM and moderate aeration of the catholyte could promote ammonia recovery. Applied to the ammonia recovery from the simulated urine, the sTMECS under the current density 62.5 A/cm2 with a catholyte aeration rate of 3.2 L/(L⋅min) for operation time 4 h showed the transmembrane ammonia flux of 26.00 g N/(m2·h) and the system energy consumption of 10.5 kWh/kg N. Accordingly, the developed sTMECS system with chemicals saving, easy scale-up and excellent performance shows good prospects in recovering ammonia from wastewater.

Optimizing broadband antireflection with Au micropatterns: a combined FDTD simulation and two-beam LIL approach.

Broadband antireflection (AR) is highly significant in a wide range of optical applications, and using a gold (Au) micropattern presents a viable method for controlling the behavior of light propagation. This study investigates a novel, to the best of our knowledge, methodology to achieve broadband AR properties in Au micropatterns. It employed the three-dimensional finite-difference time-domain (FDTD) method to simulate and optimize the design of micropatterns. In contrast, the fabrication of Au micropatterns was carried out using two-beam laser interference lithography (LIL). The fabricated Au micropatterns were characterized by a scanning electron microscope (SEM) and spectroscope to validate their antireflection and transmission properties and evaluate their performance at various wavelengths. The optimized Au micropatterns had a high transmittance rating of 96.2%. In addition, the device exhibits a broad-spectrum antireflective property, covering wavelengths ranging from 400 to 1100 nm. The simulation data and experimentally derived results show comparable patterns. These structures can potentially be employed in many optical devices, such as solar cells and photodetectors, whereby achieving optimal device performance reduced reflection and enhanced light absorption.

AI-Enabled Soft Sensing Array for Simultaneous Detection of Muscle Deformation and Mechanomyography for Metaverse Somatosensory Interaction.

Motion recognition (MR)-based somatosensory interaction technology, which interprets user movements as input instructions, presents a natural approach for promoting human-computer interaction, a critical element for advancing metaverse applications. Herein, this work introduces a non-intrusive muscle-sensing wearable device, that in conjunction with machine learning, enables motion-control-based somatosensory interaction with metaverse avatars. To facilitate MR, the proposed device simultaneously detects muscle mechanical activities, including dynamic muscle shape changes and vibrational mechanomyogram signals, utilizing a flexible 16-channel pressure sensor array (weighing ≈0.38 g). Leveraging the rich information from multiple channels, a recognition accuracy of ≈96.06% is achieved by classifying ten lower-limb motions executed by ten human subjects. In addition, this work demonstrates the practical application of muscle-sensing-based somatosensory interaction, using the proposed wearable device, for enabling the real-time control of avatars in a virtual space. This study provides an alternative approach to traditional rigid inertial measurement units and electromyography-based methods for achieving accurate human motion capture, which can further broaden the applications of motion-interactive wearable devices for the coming metaverse age.

Determining the degree of chromosomal instability in breast cancer cells by atomic force microscopy.

Chromosomal instability (CIN) is a source of genetic variation and is highly linked to the malignance of cancer. Determining the degree of CIN is necessary for understanding the role that it plays in tumor development. There is currently a lack of research on high-resolution characterization of CIN and the relationship between CIN and cell mechanics. Here, a method to determine CIN of breast cancer cells by high resolution imaging with atomic force microscopy (AFM) is explored. The numerical and structural changes of chromosomes in human breast cells (MCF-10A), moderately malignant breast cells (MCF-7) and highly malignant breast cells (MDA-MB-231) were observed and analyzed by AFM. Meanwhile, the nuclei, cytoskeleton and cell mechanics of the three kinds of cells were also investigated. The results showed the differences in CIN between the benign and cancer cells. Also, the degree of structural CIN increased with enhanced malignancy of cancer cells. This was also demonstrated by calculating the probability of micronucleus formation in these three kinds of cells. Meanwhile, we found that the area of the nucleus was related to the number of chromosomes in the nucleus. In addition, reduced or even aggregated actin fibers led to decreased elasticities in MCF-7 and MDA-MB-231 cells. It was found that the rearrangement of actin fibers would affect the nucleus, and then lead to wrong mitosis and CIN. Using AFM to detect chromosomal changes in cells with different malignancy degrees provides a new detection method for the study of cell carcinogenesis with a perspective for targeted therapy of cancer.

Multi-scale characterization and analysis of cellular viscoelastic mechanical phenotypes by atomic force microscopy.

The viscoelasticity of cells serves as a biomarker that reveals changes induced by malignant transformation, which aids the cytological examinations. However, differences in the measurement methods and parameters have prevented the consistent and effective characterization of the viscoelastic phenotype of cells. To address this issue, nanomechanical indentation experiments were conducted using an atomic force microscope (AFM). Multiple indentation methods were applied, and the indentation parameters were gradually varied to measure the viscoelasticity of normal liver cells and cancerous liver cells to create a database. This database was employed to train machine-learning algorithms in order to analyze the differences in the viscoelasticity of different types of cells and as well as to identify the optimal measurement methods and parameters. These findings indicated that the measurement speed significantly influenced viscoelasticity and that the classification difference between the two cell types was most evident at 5 µm/s. In addition, the precision and the area under the receiver operating characteristic curve were comparatively analyzed for various widely employed machine-learning algorithms. Unlike previous studies, this research validated the effectiveness of measurement parameters and methods with the assistance of machine-learning algorithms. Furthermore, the results confirmed that the viscoelasticity obtained from the multiparameter indentation measurement could be effectively used for cell classification. RESEARCH HIGHLIGHTS: This study aimed to analyze the viscoelasticity of liver cancer cells and liver cells. Different nano-indentation methods and parameters were used to measure the viscoelasticity of the two kinds of cells. The neural network algorithm was used to reverse analyze the dataset, and the methods and parameters for accurate classification and identification of cells are successfully found.

Effect of curcumin on malignant hepatocytes and mitochondria studied using atomic force microscopy.

Mitochondria are emerging as potential targets for the cancer treatment. In this study, the effects of curcumin on the activity, migration, and mitochondrial membrane potential (MMP) of malignant hepatocytes (SMMC-7721 cells) were determined using cell viability, migration, and MMP assays. Changes in the morphology and biomechanics of SMMC-7721 cells and their mitochondria were studied using both optical microscopy and atomic force microscopy (AFM). The cell survival rate, migration and MMP depended on the concentration of curcumin. Optical microscopy studies showed that curcumin altered the cell morphology. AFM studies showed that the changes in the morphology and nanomechanics of SMMC-7721 cells and their mitochondria, were induced by curcumin. As the concentration of curcumin increased, the cell length, width, and adhesion decreased, but the height, roughness and Young's modulus increased. In contrast, the mitochondrial length, width, height and roughness increased, but the adhesion and Young's modulus decreased. There was a close relationship between mitochondria and cells in terms of function, morphology and biomechanics. This study shows the effects of curcumin on SMMC-7721 cells and their mitochondria from biology and biophysics perspectives. The findings aid in comprehensively understanding the interactions between mitochondria and malignant hepatocytes.