Tag: #NanoWorldProbes

The Capacities of the Probiotic Strains L. helveticus MIMLh5 and L. acidophilus NCFM to Induce Th1-Stimulating Cytokines in Dendritic Cells Are Inversely Correlated with the Thickness of Their S-Layers

The surface layer (S-layer) of probiotic bacteria plays an important role in their interaction with the host immune system. In this article, Valentina Taverniti , Paolo D’Incecco , Stefano Farris , Peter Riber Jonsen , Helene Skovsted Eld , Juliane Sørensen, Laura Brunelli, Giacomo Mantegazza, Stefania Arioli and Hanne Frøkiær, investigated how the thickness of the S-layer influences the ability of Lactobacillus helveticus MIMLh5 and Lactobacillus acidophilus NCFM to stimulate Th1-related cytokine production in dendritic cells.

The results revealed an inverse correlation between S-layer thickness and the induction of interleukin-12, indicating that thinner S-layers are associated with a stronger immune-stimulating response. These findings provide new insights into the structure–function relationship of bacterial surface layers and their role in probiotic–host interactions.

Atomic force microscopy (AFM) was used for nanomechanical and morphological characterization of bacterial cells. Measurements were performed using a commercially available AFM instrument operated in contact resonance amplitude imaging (CRAI) mode. An Nanoworld Arrow-FMR force modulation AFM probe was used. This silicon AFM probe features a rectangular beam with a triangular free end and a tetrahedral tip (tip radius ~10 nm, tip height 10–15 μm), a spring constant of 2.8 N/m and a resonance frequency of 75 kHz. Images of 10 × 10 μm² and force–distance curves were recorded at multiple locations on the bacterial surface. Nanomechanical properties, including the elastic (Young’s) modulus, were determined by fitting approach curves to the Hertzian model with an indentation depth set to 2 nm.

figure S1: Schematic representation of the 4-step procedure for the AFM analysis of the bacteria surface

Figure S1: Schematic representation of the 4-step procedure for the AFM analysis of the bacteria surface: scanning of the surface in contact resonance amplitude (CRAI) mode (a); creation of the 10-point map of the nanomechanical test (b); generation of the force-distance curves (c); and fitting procedure for the extrapolation of the elastic modulus (d).     

 

Taverniti, V.; D’Incecco, P.; Farris, S.; Jonsen, P. R.; Eld, H. S.; Sørensen, J.; Brunelli, L.; Mantegazza, G.; Arioli, S.; Mora, D.; Guglielmetti, S.; Frøkiær, H.
The Capacities of the Probiotic Strains L. helveticus MIMLh5 and L. acidophilus NCFM to Induce Th1-Stimulating Cytokines in Dendritic Cells Are Inversely Correlated with the Thickness of Their S-Layers.
Biomolecules 2025, 15(7), 1012.
https://doi.org/10.3390/biom15071012

The article: The Capacities of the Probiotic Strains L. helveticus MIMLh5 and L. acidophilus NCFM to Induce Th1-Stimulating Cytokines in Dendritic Cells Are Inversely Correlated with the Thickness of Their S-Layers, is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

All-ferroelectric implementation of reservoir computing

In the article “All-ferroelectric implementation of reservoir computing”, published in Nature Communications, Zhiwei Chen, Wenjie Li, Shuai Dong, Z. Hugh Fan, Yihong Chen, Xubing Lu, Min Zeng, Minghui Qin, Guofu Zhou, Xingsen Gao, and Jun-Ming Liu report a novel approach for implementing reservoir computing (RC) using a monolithic, fully ferroelectric hardware platform. This work is a result of multidisciplinary collaboration among experts in ferroelectric materials, neuromorphic device engineering, and condensed matter physics.
Reservoir computing is a recurrent neural network model that excels at processing spatiotemporal data, typically requiring complex and heterogeneous hardware. In this study, the authors demonstrate that a single material system—epitaxially grown Pt/BiFeO₃/SrRuO₃ ferroelectric thin films—can simultaneously implement both volatile and nonvolatile functionalities required for RC. This is achieved through precise imprint field (E_imp) engineering, which modifies the polarization dynamics within the ferroelectric layer.
Two types of ferroelectric diodes (FDs) are fabricated from the same stack:
• Volatile FDs, grown at a oxygen pressure of 19 Pa, possess a nonzero imprint field, resulting in spontaneous polarization back-switching after the removal of input pulses. This gives rise to short-term memory and fading dynamics, which are ideal for temporal feature transformation in the reservoir layer.
• Nonvolatile FDs, grown at a oxygen pressure of 15 Pa, with minimal imprint field, exhibit stable long-term potentiation/depression (LTP/LTD), making them well-suited for synaptic weight storage in the readout layer.
The all-ferroelectric RC system was benchmarked on several temporal processing tasks:
• Chaotic Hénon map prediction with a normalized root-mean-square error (NRMSE) of 0.017,
• Waveform classification (NRMSE ≈ 0.13),
• Noisy handwritten digit recognition (up to 91.7% accuracy), and
• Curvature discrimination (100% accuracy).
The devices showed remarkable endurance (>10⁶ cycles), retention (>30 days), low variability (~8% cycle-to-cycle), and extremely low power consumption (~11.8 µW for volatile, ~140 nW for nonvolatile). These results affirm the potential of ferroelectric devices for ultralow-power, scalable neuromorphic computing.
To support these findings, the study employed high-resolution scanning probe microscopy techniques. Specifically, NanoWorld Arrow™ EFM conductive AFM probes were used for piezoresponse force microscopy (PFM). These measurements were critical in confirming that volatility and nonvolatility were governed by tunable imprint fields within the BiFeO₃ layer.
The exceptional electrostatic sensitivity, sharp tip radius, and stable mechanical properties of NanoWorld Arrow™ EFM probes were indispensable in characterizing the field-induced polarization behavior and validating the dual-mode operational framework of the ferroelectric diodes.
This work presents a significant advance in neuromorphic hardware, showing that imprint-field engineering in ferroelectric systems enables the unification of dynamic and static memory functions within a single material system. The integration of volatile and nonvolatile functions into a coherent architecture—combined with robust nanoscale characterization—offers a promising path toward compact, energy-efficient RC platforms based entirely on functional oxides.
Citation:
Chen, Z., Li, W., Dong, S., Fan, Z. H., Chen, Y., Lu, X., Zeng, M., Qin, M., Zhou, G., Gao, X., & Liu, J.-M. (2023). All-ferroelectric implementation of reservoir computing. Nature Communications, 14, 3851. https://doi.org/10.1038/s41467-023-39371-y Read full article here

Figure S3
Figure S3 from the original publication – licensed under CC BY 4.0
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