Atomic force microscopy (AFM) cantilevers are essential components that function both as force sensors and nanoscale interaction tools that play a critical role in AFM capabilities, sensitivity, and precision. Conventional fabrication techniques for probes, that rely on silicon or silicon nitride bulk micro-machining, generally requires complex fabrication processes associated to low throughput and limited geometric flexibility. Here the development of innovative AFM cantilevers made of silica glass through a novel approach based on selective laser etching is explored, which offers cantilever and tip design flexibility, condense the process into three steps, and reduces the fabrication time and cost while minimizing reliance on complex equipment and clean room facilities. The fabrication and characterization of functional glass cantilevers with thicknesses ranging from 1 to 50 µm and spring constants spanning from 0.02 to 80 N m-1 is demonstrated. The fabricated glass probes show excellent performance in both AFM imaging and force spectroscopy applications. The simple and fast fabrication approach, highlights the potential of selective laser etching to produce innovative versatile silica-based probes for AFM.

BACKGROUND AND OBJECTIVE:Cell mechanics, elasticity and viscoelasticity, are key markers of biological states like cancer. Atomic force microscopy (AFM) is ideal for such studies, but its low throughput limits large-scale use. Two solutions exist: automation for higher throughput, or high-density measurements for richer data. The latter enables machine learning (ML)-based classification, with viscoelastic parameters offering unique insights beyond static measures like Young's modulus. METHODS:This study used dynamic mechanical analysis (DMA) to classify cells, focusing on viscoelastic descriptors (storage/loss moduli) across frequencies. Normal (RWPE-1) and grade IV cancerous (PC3-GFP) prostate cells were probed at 1-200Hz, generating 304 features per cell. The fuzzy logic-based LAMDA algorithm, trained on 19 selected features, classified cells using 40 samples per line. RESULTS:PC3-GFP cells showed higher deformability and heterogeneity, behaving more like viscous fluids at low frequencies. The model achieved 79% classification accuracy. Adding features improved performance, suggesting fewer training samples may suffice with rich datasets. A sensitivity-optimized threshold reduced false negatives in cancer detection. CONCLUSIONS:Combining viscoelastic analysis with ML effectively discriminates normal and malignant cells. Future work could refine training and integrate new features, though acquisition time remains a challenge. This approach offers a promising framework for mechanome-based diagnostics, with applications in cancer and stem cell research.

In this Comment, we direct attention to initial efforts to establish a high-quality databank of atomic force microscopy (AFM) data: bioAFM-DB. We outline the state of this endeavor, its challenges, and potential courses of action.

Cell mechanics is essential in many biological phenomena such as cell division and migration. Further, cell mechanobiological measurements can distinguish between healthy and diseased cells; thus, investigations of cell mechanics have led to the development of tools to study the elasticity and the viscosity of cells. Cell mechanics can be affected by factors such as cell morphology, cytoskeletal remodelling, and cell intrinsic factors, and these are important in understanding disease progression. Here, we use an atomic force microscopy (AFM)-microrheology with a colloidal probe for a dynamic mechanical analysis of host cell elasticity and viscosity at 6 frequencies ranging from 1 to 200 Hz. Epithelial cells exhibit a more "liquid-like" behavior as the frequency increases, whereas cancerous cells transition into this viscous, fluid-like state at lower frequencies (48 and 63 Hz) compared to normal cells (92 Hz). Cell mechanical measurements inherently exhibit heterogeneity due to physical factors, such as cell shape and the position of the probe on the cell surface. In addition to this physical variability, biological parameters─notably the cell cycle phases─also contribute to mechanical heterogeneity. In this study, we specifically investigated the influence of cell cycle phases on the cell mechanical properties. Using chemically synchronized normal and cancerous cells in different phases of the cell cycle shows that the actin cytoskeleton undergoes rapid reorganization as the cell cycle progresses. Results show that as actin becomes disorganized, the elastic moduli decreases and the loss tangent is larger coupled with a lower phase shift frequency. Cells in the G1 and S phase had the lowest elastic moduli (G') meaning they were softer than cells in the G2/M phase. During disease onset, the pathogen adheres and invades the host, a process that leads to cytoskeleton arrangement and thus changes in cell elasticity, and thus, to understand the impact of the cell cycle on host invasion, we probed the interaction of Candida albicans with HeLa, HCT 116, and HaCaT cells using AFM in the single-cell force spectroscopy mode. There was a significant increase in force of interaction during the S phase which could be attributed to the disorganized cytoskeleton. This shows the importance of cytoskeletal organization and cell cycle phase in cell mechanical properties and pathogen-host interaction.

Atomic force microscopy (AFM) has reached a significant level of maturity in biology, demonstrated by the diversity of modes for obtaining not only topographical images but also insightful mechanical and adhesion data by performing force measurements on delicate samples with a controlled environment (e.g., liquid, temperature, pH). Numerous studies have applied AFM to describe biological phenomena at the molecular and cellular scales, and even on tissues. Despite these advances, AFM is not established as a diagnostic tool in the biomedical field. This article describes the reasons for this gap, focusing on one of the main weaknesses of bio-AFM: its low data throughput. We review current efforts to improve the automation of AFM measurements in particular on living cells, as well as the developments in automating data analysis. For the latter, artificial intelligence (AI) is progressively employed to classify data to distinguish healthy and diseased cells or tissues. Finally, we propose a roadmap to foster the application of bio-AFM into medical diagnostics.

Aims: Doxorubicin (DOX) is a highly effective chemotherapeutic agent whose clinical use is limited by cumulative cardiotoxicity. The subcellular origins of early cardiac injury remain unclear but cardiomyocyte (CM) mitochondrial dysfunction is implicated. However, vulnerability of specific CM mitochondrial subpopulations is unknown. Building on our previous work linking the postnatal maturation of crest-associated subsarcolemmal mitochondria (SSM) at the CM surface to diastolic function, we investigated the spatial and temporal susceptibility of SSM during DOX exposure and their contribution to early diastolic dysfunction. Methods and results: Adult male mice received chronic DOX treatment (5 mg/kg/week for 5 weeks) to mimic cumulative clinical exposure. Cardiac function was monitored longitudinally, during treatment and after protocol completion, using echocardiography-Doppler imaging, and global longitudinal strain (GLS). Subcellular mitochondrial remodeling was assessed using atomic force microscopy (AFM) and transmission electron microscopy (TEM). A tamoxifen-inducible, CM-specific Ephrin-B1 knockout model was used to probe the functional role of SSM in DOX-induced injury. DOX induced a progressive and selective loss of crest/SSM at the CM surface very early within 3 days of exposure, while the architecture of interfibrillar mitochondria IFM remained preserved. This early SSM depletion paralleled impaired myocardial relaxation reflected by a prolonged isovolumic relaxation time, along with reduced GLS, all preceding changes in left ventricular ejection fraction or detectable IFM abnormalities. Notably, in mice lacking Ephrin-B1, and therefore mature crest/SSM, DOX exposure triggered an unusually rapid onset of systolic dysfunction, highlighting the cardioprotective role of these surface mitochondrial populations. Conclusions: Crest/SSM at the CM surface are the earliest selective mitochondrial targets of DOX, and their loss precedes IFM remodeling. This spatial-temporal hierarchy reveals a compartment-specific functional distinction, with SSM supporting diastolic performance and IFM sustaining systolic contraction. Hence, preserving SSM emerges as a promising early target to prevent progression of anthracycline cardiotoxicity toward systolic failure. Clinically, our findings also support early diastolic monitoring as a sensitive approach for detecting anthracycline cardiotoxicity. ### Competing Interest Statement The authors have declared no competing interest.

Abstract Nanobiomechanical data have an interest in biomedical research, but the capability of deep learning (DL) based on convolutional neural networks (CNN) has not been explored to classify such data. We propose to use these strategies to treat nanobiomechanical data acquired by atomic force microscopy (AFM) on Candida albicans living cells, an opportunistic pathogenic micro-organism of medical interest. Data, acquired by force spectroscopy, allowed us to generate force vs. distance curves (FD curves) which its profile is linked to nanobiomechanical properties of C. albicans. DL was applied to classify FD curves, considered as images, into 3 groups: adhesive nanodomains, non-adhesive domains or in between domains. We achieved a real multiclass classification with a validation accuracy, macro-average of F1, and the weighted average of 92%, without the need to perform the usual dropout or weight regularisation methods. Transfer learning with a pre-trained (PT) VGG16 architecture with and without fine tuning (FT) permitted us to verify that our model is less computationally complex and better fitted. The generalisation was done by classifying on other C. albicans cells with more that 99% of confidence, to finally predict 16,384 FD curves in less than 90 seconds. This model could be employed by a non-machine learning specialist as the trained model can be downloaded to predict the adhesiveness, within seconds, on C. albicans cells characterized by AFM.

In this work, starch-based porous cryogels with controlled mechanical and electrical properties were prepared for tissue engineering applications. The starch cryogels were formulated using kappa-carrageenan, poly(vinyl alcohol) (PVA), and styrylpyridinium-substituted PVA (SbQ) into the composite. A conductive cryogel was polymerized by chemical oxidation of 3,4-ethylenedioxythiophene (EDOT) using iron(III) p-toluenesulfonate as a strategy to control the electrical properties. The physical, thermal, and mechanical properties were evaluated for the obtained composites. Macro- and nanoscale results confirmed the capability of tuning the mechanical properties of the material by the addition of biopolymers in different contents. The presence of kappa-carrageenan significantly increased the storage modulus and decreased the damping effect in the formulations. The presence of PVA showed a plasticizing effect in the formulations, confirmed by the buffering effect and an increase in storage modulus. PVA-SBQ improved the mechanical properties by cross-linking. The addition of PEDOT increased the mechanical and electrical properties of the obtained materials.

We demonstrate that after anchoring at the surface of silicone, carbon nanomaterials exhibit antibacterial activity against Gram+ or Gram− bacteria depending on their surface chemistry.

Microalgae, such as Parachlorella kessleri, have significant potential for environmental remediation, especially in removing heavy metals like zinc from water. This study investigates how P. kessleri, isolated from a polluted river in Argentina, can remediate zinc. Using atomic force microscopy (AFM), the research examined the interactions between Zn particles and cells grown with different nitrogen sources-nitrate or ammonium. The results showed that cells grown with nitrate produced extracellular polymeric substances (EPS), while those grown with ammonium did not. Raman spectroscopy revealed distinct metabolic responses based on the nitrogen source, with nitrate-grown cells showing altered profiles after zinc exposure. Zinc exposure also changed the surface roughness and nanomechanical properties of the cells, particularly in those producing EPS. AFM force spectroscopy experiments then confirmed strong Zn binding to EPS in nitrate-grown cells, while interactions were weaker in ammonium-grown cells that lacked EPS. Overall, our results elucidate the critical role of EPS in Zn removal by P. kessleri cells and show that Zn remediation is mediated by EPS adsorption. This study underscores the significance of regulating nitrogen sources to stimulate EPS production, offering insights that are essential for subsequent bioremediation applications.

Low-energy electron beams (LEEB) are a safe and practical sterilization solution for in-line industrial applications, such as sterilizing medical products. However, their low dose rate induces product degradation, and the limited maximal energy prohibits high-throughput applications. To address this, we developed a low-energy 'pulsed' electron beam generator (LEPEB) and evaluated its efficacy and mechanism of action. Bacillus pumilus vegetative cells and spores were irradiated with a 250 keV LEPEB system at a 100 Hz pulse repetition frequency and a pulse duration of only 10 ns. This produced highly efficient bacterial inactivation at a rate of >6 log10, the level required for sterilization in industrial applications, with only two pulses for vegetative bacteria (20 ms) and eight pulses for spores (80 ms). LEPEB induced no morphological or structural defects, but decreased cell wall hydrophobicity in vegetative cells, which may inhibit biofilm formation. Single- and double-strand DNA breaks and pyrimidine dimer formation were also observed, likely causing cell death. Together, the unique combination of high dose rate and nanosecond delivery of LEPEB enable effective and high-throughput bacterial eradication for direct integration into production lines in a wide range of industrial applications.

ABSTRACT Biofilm is a dynamic structure from which individual bacteria and micro-aggregates are released to subsequently colonize new niches by either detachment or dispersal. Screening of a transposon mutant library identified genes associated with the alteration of Klebsiella pneumoniae biofilm including fabR , which encodes a transcriptional regulator involved in membrane lipid homeostasis. An isogenic ∆ fabR mutant formed more biofilm than the wild-type (WT) strain and its trans-complemented strain. The thick and round aggregates observed with ∆ fabR were resistant to extensive washes, unlike those of the WT strain. Confocal microscopy and BioFlux microfluidic observations showed that fabR deletion was associated with biofilm robustness and impaired erosion over time. The genes fabB and yqfA associated with fatty acid metabolism were significantly overexpressed in the ∆ fabR strain, in both planktonic and biofilm conditions. Two monounsaturated fatty acids, palmitoleic acid (C16:1) and oleic acid (C18:1), were found in higher proportion in biofilm cells than in planktonic forms, whereas heptadecenoic acid (C17:1) and octadecanoic acid, 11-methoxy (C18:0-OCH3) were found in higher proportion in the planktonic lifestyle. The fabR mutation induced variations in the fatty acid composition, with no clear differences in the amounts of saturated fatty acids (SFA) and unsaturated fatty acids for the planktonic lifestyle but lower SFA in the biofilm form. Atomic force microscopy showed that deletion of fabR is associated with decreased K. pneumoniae cell rigidity in the biofilm lifestyle, as well as a softer, more elastic biofilm with increased cell cohesion compared to the wild-type strain. IMPORTANCE Klebsiella pneumoniae is an opportunistic pathogen responsible for a wide range of nosocomial infections. The success of this pathogen is due to its high resistance to antibiotics and its ability to form biofilms. The molecular mechanisms involved in biofilm formation have been largely described but the dispersal process that releases individual and aggregate cells from mature biofilm is less well documented while it is associated with the colonization of new environments and thus new threats. Using a multidisciplinary approach, we show that modifications of bacterial membrane fatty acid composition lead to variations in the biofilm robustness, and subsequent bacterial detachment and biofilm erosion over time. These results enhance our understanding of the genetic requirements for biofilm formation in K. pneumoniae that affect the time course of biofilm development and the embrittlement step preceding its dispersal that will make it possible to control K. pneumoniae infections.

Mechanobiological measurements have the potential to discriminate healthy cells from pathological cells. However, a technology frequently used to measure these properties, i.e., atomic force microscopy (AFM), suffers from its low output and lack of standardization. In this work, we have optimized AFM mechanical measurement on cell populations and developed a technology combining cell patterning and AFM automation that has the potential to record data on hundreds of cells (956 cells measured for publication). On each cell, 16 force curves (FCs) and seven features/FC, constituting the mechanome, were calculated. All of the FCs were then classified using machine learning tools with a statistical approach based on a fuzzy logic algorithm, trained to discriminate between nonmalignant and cancerous cells (training base, up to 120 cells/cell line). The proof of concept was first made on prostate nonmalignant (RWPE-1) and cancerous cell lines (PC3-GFP), then on nonmalignant (Hs 895.Sk) and cancerous (Hs 895.T) skin fibroblast cell lines, and demonstrated the ability of our method to classify correctly 73% of the cells (194 cells in the database/cell line) despite the very high degree of similarity of the whole set of measurements (79-100% similarity).

Candida is one of the most common opportunistic fungal pathogens in humans. Its adhesion to the host cell is required in parasitic states and is important for pathogenesis. Many studies have shown that there is an increased risk of developing candidiasis when normal tissue barriers are weakened or when immune defenses are compromised, for example, during cancer treatment that induces immunosuppression. The mechanical properties of malignant cells, such as adhesiveness and viscoelasticity, which contribute to cellular invasion and migration are different from those of noncancerous cells. To understand host invasion and its relationship with host cell health, we probed the interaction of Candida spp. with cancerous and noncancerous human cell lines using atomic force microscopy in the single-cell force spectroscopy mode. There was significant adhesion between Candida and human cells, with more adhesion to cancerous versus noncancerous cell lines. This increase in adhesion is related to the mechanobiological properties of cancer cells, which have a disorganized cytoskeleton and lower rigidity. Altered geometry and cytoskeletal disruption of the human cells impacted adhesion parameters, underscoring the role of cytoskeletal organization in Candida-human cell adhesion and implicating the manipulation of cell properties as a potential future therapeutic strategy.

The models used to calculate Young's moduli from atomic force microscopy (AFM) force curves consider the shape of the indentation. It is then assumed that the geometry of the indentation is identical to the geometry of the indenter, which has been verified for hard materials (E > 1 MPa). Based on this assumption, the force curves calculated by these models, for the same object with a given Young's modulus, are different if the indenter geometry is different. On the contrary, we observe experimentally that the force curves recorded on soft living cells, with pyramidal, spherical, or tipless indenters, are almost similar. This indicates that this basic assumption on the indentation geometry does not work for soft materials (E of the order of 5 kPa or less). This means that, in this case, the shape of the indentation is therefore different from the shape of the indenter. Indentation of living cells by AFM is not what we thought!

Immobilization of living micro-organisms on pre-defined areas of substrates is a major prerequisite of their characterizations by Atomic Force Microscopy (AFM) in culture media. It remains challenging since micro-organisms should not be denatured but attached strongly enough to be scanned with an AFM tip in liquid. Here, we propose a novel approach where biological objects of interest are electrostatically assembled on 2 nm thick Polyethylenimine (PEI) patterns fabricated by nanoxerography. This nanoxerography process consists in electrostatic trapping of PEI chains on negatively charged patterns written on electret thin films by AFM or electrical micro-contact printing. The great potentialities of this approach were demonstrated using a common biological system, Pseudomonas aeruginosa bacteria. Such bacteria, negatively charged, were selectively assembled on large scale arrays of PEI patterns. The number of bacteria grafted on each pattern was finely controlled either by tuning the surface potential or the lateral size of charge patterns. Contrary to uncontroled PEI films commonly used for cell anchoring, these ultra-thin PEI patterns strongly grafted on the surface are shown to not denature assembled Pseudomonas aeruginosa bacteria. AFM characterizations in culture media of large populations of individual living bacteria can thus easily be performed using this approach, offering the opportunity of representative statistical data analysis. These opportunities can be opened up to any micro-organism negatively charged in solution.

G protein-coupled receptors (GPCRs) form the largest family of cell surface receptors. Despite considerable insights into their pharmacology, the GPCR architecture at the cell surface still remains largely unexplored. Herein, we present the specific unfolding of different GPCRs at the surface of living mammalian cells by atomic force microscopy-based single molecule force spectroscopy (AFM-SMFS). Mathematical analysis of the GPCR unfolding distances at resting state revealed the presence of different receptor populations relying on distinct oligomeric states which are receptor-specific and receptor expression-dependent. Moreover, we show that the oligomer size dictates the receptor spatial organization with nanoclusters of high-order oligomers while lower-order complexes spread over the whole cell surface. Finally, the receptor activity reshapes both the oligomeric populations and their spatial arrangement. These results add an additional level of complexity to the GPCR pharmacology until now considered to arise from a single receptor population at the cell surface.

The recently developed One-Step Poly(amidoamine) (OS-PAMAM) dendrimers stand out for their characteristics as the high drug-load capacity and cell-delivery improvement of therapeutic agents. The OS-PAMAM dendrimers have proven to be useful in the biomedical field as nanocarrier or nanosystems for therapy. In the present research it was encouraging to determine their physicochemical characteristics which were compared with commercial PAMAM generation-6 (G6). The spectroscopic measurement of amides, nanoparticle size (10-30 nm), polydispersity index and zeta potential measurements correlates with the commercial product. The OS PAMAM has cavities detected by AFM, and the force analysis showed the same adhesion force and different elasticity than PAMAM-G6. The molecular weight (MW) was 10 times lower than the commercial one for both techniques employed, resembling the MW of a PAMAM generation-3 (G3). OS-PAMAM/PAMAM-G6 MS-MS mirror plots demonstrate chemical equivalency amongst herein analyzed dendrimers, with the advantage that OS-PAMAM is produced with a faster and low-cost synthetic protocol, which allows them to be applied for both research and industry in the biomedical field.

Correlative microscopy with atomic force quantitative imaging and laser scanning confocal (AFM-QI-LSCM) of live cells has refined our understanding of yeast biology. Correlative AFM-QI-LSCM generates high content data by simultaneously measuring the ultrastructural surface topography and nanomechanical properties with nanometer and picoNewton resolution (via AFM-QI) while tracking internal biochemical changes through fluorescent labelled markers in live yeast. This chapter outlines sample preparation and imaging protocols for AFM-QI and correlative AFM-QI-LSCM, and imaging of fixed and live Candida albicans and Saccharomyces cerevisiae. We describe sample immobilisation tools, including polydimethylsiloxane (PDMS stamps) and Cell-Tak, that are crucial for yeast cells to withstand the lateral AFM tip forces during live cell scanning. Finally, we describe methods for real-time AFM-QI-LSCM monitoring of cell surface remodelling, viscoelasticity, adhesion and intracellular signals in actively dividing C. albicans.