Adaptive cell wall thickening in Enterococcus faecalis is associated with decreased vancomycin susceptibility

OBJECTIVES

Enterococcus faecalis can adopt both a commensal and a nosocomial lifestyle, resisting numerous antibiotics. In this study, we aim to investigate the relationship between the cell wall (CW) thickness and decreased susceptibility to vancomycin (VD) in van-gene negative clinical isolates of E. faecalis (nMIC 8 = 2, nMIC 4 = 3, ST30, ST40, and ST59).

METHODS

The CW thickness was assessed in VD strains and compared with vancomycin susceptible isolates of the same sequence type (ST) (Vancomycin susceptible [VS]; nMIC 2 = 5). The VD and VS strains were subjected to serial passage (evolved [ev]) with and without vancomycin selection. Subsequent measurements of CW thickness and vancomycin MICs were performed.

RESULTS

The VD strains exhibited increased CW thickness when compared with ST-related VS strains (ΔCW thickness VD vs. VS ST30 25 nm, ST59 15 nm, and ST40 1 nm). Serial passages without vancomycin selection led to a decrease in CW thickness and vancomycin MIC in VD strains (ΔCW thickness VD vs. evVD ST30 22 nm, ST59 3 nm, and ST40 2 nm). Serial passages with vancomycin selection caused an increase in CW thickness and vancomycin MIC in ST-related VS strains (ΔCW thickness VS vs. evVS ST30 22 nm, ST59 16 nm, and ST40 1 nm).

DISCUSSION

Adaptive changes in CW thickness were observed in response to vancomycin exposure. Increased CW thickness correlated with decreased vancomycin susceptibility, whereas decreased CW thickness correlated with increased vancomycin susceptibility. Core single nucleotide polymorphisms in the evolved mutants were mostly found in genes encoding proteins associated with the cytoplasm or the cytoplasmic membrane. The potential relevance of these adaptive changes is underlined by the observed phenotypes in clinical isolates. Our findings emphasize the importance of monitoring adaptive changes, as vancomycin-resistant enterococci infections are a growing concern.

Performance domains of bio-inspired and triangular lattice patterns to optimize the structures' stiffness

Mass reduction of mechanical systems is a recurrent objective in engineering, which is often reached by removing material from its mechanical parts. However, this material removal leads to a decrease of mechanical performances for the parts, which must be minimized and controlled to avoid a potential system failure. To find a middle-ground between material removing and mechanical performances), material must be kept only in areas where it is necessary, for example using stress-driven material removal methods. These methods use the stress field to define the local material removal based on two local parameters: the local volume fraction v f and the structural anisotropy orientation β . These methods may be based on different types of cellular structure patterns: lattice-based or bio-inspired. The long-term objective of this study is to improve the performance of stress-driven methods by using the most efficient pattern. For this purpose, this study investigates the influence of v f and β on the mechanical stiffness of three planar cellular structures called Periodic Stress-Driven Material Removal (PSDMR) structures. The first, taken from the literature, is bio-inspired from bone and based on a square pattern. The second, developed in this study, is also bio-inspired from bone but based on a rectangular pattern. The third is a strut-based lattice pattern well documented in the literature for its isotropic behavior. These three patterns are compared in this study in terms of relative longitudinal stiffness, obtained through linear elastic compressive tests by finite element analysis. It is highlighted that each PSDMR pattern has a specific domain in which it performs better than the two others. In future works, these domains could be used in stress-driven material removal methods to select the most adequate pattern or a mix of them to improve the performances of parts.

Interactive mode of biochar-based silicon and iron nanoparticles mitigated Cd-toxicity in maize

Cadmium contamination poses severe environmental and health threats, necessitating effective mitigation strategies. Rice husk biochar (BC) and nanoparticle (NP) treatments are emerging strategies with limited research on their synergistic benefits. This study assesses BC, silicon NPs (nSi), and iron NPs (nFe) modifications (B-nSi, B-nFe, and B-nSi-nFe) to reduce Cd-bioavailability in soil and its toxicity in maize, not reported before. Characterization of amendments validated, nSi and nFe attachment to BC, forming new mineral crystals to adsorb Cd. We found that B-nSi-nFe induced Cd-immobilization in soil by the formation of Cd-ligand complexes with the effective retention of NPs within microporous structure of BC. B-nSi-nFe increased soil pH by 0.76 units while reducing bioavailable Cd by 49 %, than Ck-Cd. Resultantly, B-nSi-nFe reduced Cd concentrations in roots and shoots by 51 % and 75 %, respectively. Moreover, the application of B-nSi-nFe significantly enhanced plant biomass, antioxidant activities, and upregulated the expression of antioxidant genes [ZmAPX (3.28 FC), ZmCAT (3.20 FC), ZmPOD (2.58 FC), ZmSOD (3.08 FC), ZmGSH (3.17 FC), and ZmMDHAR (3.80 FC)] while downregulating Cd transporter genes [ZmNramp5 (3.65 FC), ZmHMA2 (2.92 FC), and ZmHMA3 (3.40 FC)] compared to Ck-Cd. Additionally, confocal microscopy confirmed the efficacy of B-nSi-nFe in maintaining cell integrity due to reduced oxidative stress. SEM and TEM observations revealed alleviation of Cd toxicity to stomata, guard cells, and ultracellular structures with B-nSi-nFe treatment. Overall, this study demonstrated the potential of B-nSi-nFe for reducing Cd mobility in soil-plant system, mitigating Cd-toxicity in plants and improving enzymatic activities in soil.

The power of super-resolution microscopy in modern biomedical science

Super-resolution microscopy (SRM) technology that breaks the diffraction limit has revolutionized the field of cell biology since its appearance, which enables researchers to visualize cellular structures with nanometric resolution, multiple colors and single-molecule sensitivity. With the flourishing development of hardware and the availability of novel fluorescent probes, the impact of SRM has already gone beyond cell biology and extended to nanomedicine, material science and nanotechnology, and remarkably boosted important breakthroughs in these fields. In this review, we will mainly highlight the power of SRM in modern biomedical science, discussing how these SRM techniques revolutionize the way we understand cell structures, biomaterials assembly and how assembled biomaterials interact with cellular organelles, and finally their promotion to the clinical pre-diagnosis. Moreover, we also provide an outlook on the current technical challenges and future improvement direction of SRM. We hope this review can provide useful information, inspire new ideas and propel the development both from the perspective of SRM techniques and from the perspective of SRM's applications.

Optimisation of the additive manufacturing parameters of polylactic acid (PLA) cellular structures for biomedical applications

Fused deposition modelling (FDM) is an additive manufacturing technology used to create functional and complex geometries directly from computer-generated models. This technique can be utilised to generate cellular structures with controllable pore size, pore shape, and porosity. Cellular structures are fundamental in orthopaedics scaffolds because of its low elastic modulus, high compressive strength, and adequate cell accommodation spaces. This paper aims at investigating and optimising the FDM additive manufacturing process parameters of polylactic Acid (PLA) for two lattice structures namely Schoen Gyroid and Schwarz Primitive. The effect of additive manufacturing critical process parameters including layer height, flow rate, and print speed on the geometrical accuracy and compressive strength of the specimens were analysed. In addition, other parameters that have minimal effect on the geometrical accuracy of the printed parts were discussed. A Full Factorial Analysis (FFA) using Minitab software was undertaken to identify the perfect combination of printing parameters to provide the most geometrically accurate structure. In this study, samples of the Schoen Gyroid and the Schwarz Primitive lattices and a solid control cylinder were 3D printed using the ideal printing combination to assess the manufacturability, the geometrical accuracy, and the mechanical behaviour of both designs. It was found that the optimised FDM process parameters for the studied cellular structures were a layer height of 0.16 mm, a printing speed of 50 mm/s and a flow rate of 90%. As a result of using these parameters, the solid, Schoen Gyroid and Schwarz Primitive specimens demonstrated elastic moduli values of 951 MPa, 264 MPa, and 221 MPa, respectively. In addition, the Schoen Gyroid and the Schwarz Primitive have reached their stress limits at around 8.68 MPa and 7.06 MPa, respectively. It was noticed that the Schoen Gyroid structure exhibited ∼ 18% higher compressive strength and ∼ 16% higher elastic modulus compared to the Schwarz Primitive structure for the same volume fraction of porosity, overall dimensions, and the manufacturing process parameters. Although both structures revealed mechanical properties that fall within the range of the human trabecular bone, but Schoen Gyroid exhibited improved structural integrity performance that is evident by its post-yield behaviour.

Label2label: Training a neural network to selectively restore cellular structures in fluorescence microscopy

Immunofluorescence microscopy is routinely used to visualise the spatial distribution of proteins that dictates their cellular function. However, unspecific antibody binding often results in high cytosolic background signals, decreasing the image contrast of a target structure. Recently, convolutional neural networks (CNNs) were successfully employed for image restoration in immunofluorescence microscopy, but current methods cannot correct for those background signals. We report a new method that trains a CNN to reduce unspecific signals in immunofluorescence images; we name this method label2label (L2L). In L2L, a CNN is trained with image pairs of two non-identical labels that target the same cellular structure. We show that after L2L training a network predicts images with significantly increased contrast of a target structure, which is further improved after implementing a multiscale structural similarity loss function. Here, our results suggest that sample differences in the training data decrease hallucination effects that are observed with other methods. We further assess the performance of a cycle generative adversarial network, and show that a CNN can be trained to separate structures in superposed immunofluorescence images of two targets.

Summary: Label2label is a new deep learning-based image restoration method that reduces cytosolic background signals in immunofluorescence images of cellular structures.

Selective Laser Melting of Ti6Al4V sub-millimetric cellular structures: Prediction of dimensional deviations and mechanical performance

Ti6Al4V sub-millimetric cellular structures arise as promising solutions concerning the progress of conventional orthopedic implants due to its ability to address a combination of mechanical, physical and topological properties. Such ability can improve the interaction between implant materials and surrounding bone leading to long-term successful orthopedic implants. Selective Laser Melting (SLM) capability to produce high quality Ti6Al4V porous implants is in great demand towards orthopedic biomaterials. In this study, Ti6Al4V cellular structures were designed, modeled, SLM produced and characterized targeting orthopedic implants. For that purpose, a set of tools is proposed to overcome SLM limited accuracy to produce porous biomaterials with desired dimensions and mechanical properties. Morphological analyses were performed to evaluate the dimensional deviations noticed between the model CAD and the SLM produced structures. Tensile tests were carried out to estimate the elastic modulus of the Ti6Al4V cellular structures. The present work proposes a design methodology showing the linear correlations found for the dimensions, the porosity and the elastic modulus when comparing the model CAD designs with Ti6Al4V structures by SLM.

Localization of nickel in the hyperaccumulator plant Breynia cernua (Poir.) Mull.Arg. discovered in the nickeliferous laterites of Zambales, the Philippines

A newly discovered nickel (Ni) hyperaccumulator plant, Breynia cernua (Phyllanthaceae) from the nickeliferous laterites of Acoje, Zambales, has elevated Ni concentrations. Its computed bioaccumulation factor is 1.7 and the translocation factor is 4.6. Leaf tissues which contain the highest Ni concentrations were analyzed using optical microscopy and Scanning Electron Microscopy with Energy-Dispersive X-ray (SEM/EDX). The results indicated that most of the Ni are stored in the epidermal cells of the leaves, followed by the mesophyll cells then the vascular bundles. The accumulation of Ni found in the subcellular locations, probably in the vacuoles, may prevent phytotoxicity that could affect the normal function of other cellular structures. A possible resistance mechanism through strain avoidance towards Ni accumulation makes B. cernua capable of tolerating elevated Ni concentrations in its tissues. The tolerance of B. cernua to Ni phytotoxicity suggests possible applications of this hyperaccumulator plant in phytoextraction technology.