Unraveling the Mechanisms of Valvular Heart Disease to Identify Medical Therapy Targets: A Scientific Statement From the American Heart Association.

Valvular heart disease is a common cause of morbidity and mortality worldwide and has no effective medical therapy. Severe disease is managed with valve replacement procedures, which entail high health care-related costs and postprocedural morbidity and mortality. Robust ongoing research programs have elucidated many important molecular pathways contributing to primary valvular heart disease. However, there remain several key challenges inherent in translating research on valvular heart disease to viable molecular targets that can progress through the clinical trials pathway and effectively prevent or modify the course of these common conditions. In this scientific statement, we review the basic cellular structures of the human heart valves and discuss how these structures change in primary valvular heart disease. We focus on the most common primary valvular heart diseases, including calcific aortic stenosis, bicuspid aortic valves, mitral valve prolapse, and rheumatic heart disease, and outline the fundamental molecular discoveries contributing to each. We further outline potential therapeutic molecular targets for primary valvular heart disease and discuss key knowledge gaps that might serve as future research priorities.

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.

Unravelling a diversity of cellular structures and aggregation dynamics during the early development of Myxococcus xanthus.

Aggregation underlies the collective dynamics of a diversity of organisms, enabling the formation of complex structures and emergent behaviours on interaction with the environment. Cellular aggregation constitutes one of the routes to collective motility and multicellular development. Myxococcus xanthus, a social bacterium, is a valuable model for studying the aggregative path to multicellularity, a major transition in the evolutionary history of life. While the collective developmental behaviour of M. xanthus has been largely studied in high cellular densities, there is a lack of understanding at low-density conditions that can be ecologically relevant. In this work, we study the early stages of emergent collective behaviour of M. xanthus under nutrient-poor and low-density conditions, uncovering the formation of diverse cellular structures with different shapes and sizes, ranging from individual cells to networks comprising thousands of cells. We study their motility patterns and their prevalence along development and discuss their cross-scale role on the population's exploratory dynamics. This work contributes to understanding key, yet largely understudied, aspects in the early stages of multicellular development in myxobacteria, shedding light on the dynamics underlying aggregative processes in this and other taxa and study systems.

Looking outside the box: a comparative cross-kingdom view on the cell biology of the three major lineages of eukaryotic multicellular life.

Many cell biological facts that can be found in dedicated scientific textbooks are based on findings originally made in humans and/or other mammals, including respective tissue culture systems. They are often presented as if they were universally valid, neglecting that many aspects differ-in part considerably-between the three major kingdoms of multicellular eukaryotic life, comprising animals, plants and fungi. Here, we provide a comparative cross-kingdom view on the basic cell biology across these lineages, highlighting in particular essential differences in cellular structures and processes between phyla. We focus on key dissimilarities in cellular organization, e.g. regarding cell size and shape, the composition of the extracellular matrix, the types of cell-cell junctions, the presence of specific membrane-bound organelles and the organization of the cytoskeleton. We further highlight essential disparities in important cellular processes such as signal transduction, intracellular transport, cell cycle regulation, apoptosis and cytokinesis. Our comprehensive cross-kingdom comparison emphasizes overlaps but also marked differences between the major lineages of the three kingdoms and, thus, adds to a more holistic view of multicellular eukaryotic cell biology.

Exploring the property space of periodic cellular structures based on crystal networks.

The properties of periodic cellular structures strongly depend on the regular spatial arrangement of their constituent base materials and can be controlled by changing the topology and geometry of the repeating unit cell. Recent advances in three-dimensional (3D) fabrication technologies more and more expand the limits of fabricable real-world architected materials and strengthen the need of novel microstructural topologies for applications across all length scales and fields in both fundamental science and engineering practice. Here, we systematically explore, interpret, and analyze publicly available crystallographic network topologies from a structural point of view and provide a ready-to-use unit cell catalog with more than 17,000 unique entries in total. We show that molecular crystal networks with atoms connected by chemical bonds can be interpreted as cellular structures with nodes connected by mechanical bars. By this, we identify new structures with extremal properties as well as known structures such as the octet-truss or the Kelvin cell and show how crystallographic symmetries are related to the mechanical properties of the structures. Our work provides inspiration for the discovery of novel cellular structures and paves the way for computational methods to explore and design microstructures with unprecedented properties, bridging the gap between microscopic crystal chemistry and macroscopic structural engineering.

A Novel Method for Estimating Chlorophyll and Carotenoid Concentrations in Leaves: A Two Hyperspectral Sensor Approach.

Leaf optical properties can be used to identify environmental conditions, the effect of light intensities, plant hormone levels, pigment concentrations, and cellular structures. However, the reflectance factors can affect the accuracy of predictions for chlorophyll and carotenoid concentrations. In this study, we tested the hypothesis that technology using two hyperspectral sensors for both reflectance and absorbance data would result in more accurate predictions of absorbance spectra. Our findings indicated that the green/yellow regions (500-600 nm) had a greater impact on photosynthetic pigment predictions, while the blue (440-485 nm) and red (626-700 nm) regions had a minor impact. Strong correlations were found between absorbance (R2 = 0.87 and 0.91) and reflectance (R2 = 0.80 and 0.78) for chlorophyll and carotenoids, respectively. Carotenoids showed particularly high and significant correlation coefficients using the partial least squares regression (PLSR) method (R2C = 0.91, R2cv = 0.85, and R2P = 0.90) when associated with hyperspectral absorbance data. Our hypothesis was supported, and these results demonstrate the effectiveness of using two hyperspectral sensors for optical leaf profile analysis and predicting the concentration of photosynthetic pigments using multivariate statistical methods. This method for two sensors is more efficient and shows better results compared to traditional single sensor techniques for measuring chloroplast changes and pigment phenotyping in plants.

Universality of Form: The Case of Retinal Cone Photoreceptor Mosaics.

Cone photoreceptor cells are wavelength-sensitive neurons in the retinas of vertebrate eyes and are responsible for color vision. The spatial distribution of these nerve cells is commonly referred to as the cone photoreceptor mosaic. By applying the principle of maximum entropy, we demonstrate the universality of retinal cone mosaics in vertebrate eyes by examining various species, namely, rodent, dog, monkey, human, fish, and bird. We introduce a parameter called retinal temperature, which is conserved across the retinas of vertebrates. The virial equation of state for two-dimensional cellular networks, known as Lemaître's law, is also obtained as a special case of our formalism. We investigate the behavior of several artificially generated networks and the natural one of the retina concerning this universal, topological law.

Coaxial Alginate Hydrogels: From Self-Assembled 3D Cellular Constructs to Long-Term Storage.

Alginate as a versatile naturally occurring biomaterial has found widespread use in the biomedical field due to its unique features such as biocompatibility and biodegradability. The ability of its semipermeable hydrogels to provide a favourable microenvironment for clinically relevant cells made alginate encapsulation a leading technology for immunoisolation, 3D culture, cryopreservation as well as cell and drug delivery. The aim of this work is the evaluation of structural properties and swelling behaviour of the core-shell capsules for the encapsulation of multipotent stromal cells (MSCs), their 3D culture and cryopreservation using slow freezing. The cells were encapsulated in core-shell capsules using coaxial electrospraying, cultured for 35 days and cryopreserved. Cell viability, metabolic activity and cell-cell interactions were analysed. Cryopreservation of MSCs-laden core-shell capsules was performed according to parameters pre-selected on cell-free capsules. The results suggest that core-shell capsules produced from the low viscosity high-G alginate are superior to high-M ones in terms of stability during in vitro culture, as well as to solid beads in terms of promoting formation of viable self-assembled cellular structures and maintenance of MSCs functionality on a long-term basis. The application of 0.3 M sucrose demonstrated a beneficial effect on the integrity of capsules and viability of formed 3D cell assemblies, as compared to 10% dimethyl sulfoxide (DMSO) alone. The proposed workflow from the preparation of core-shell capsules with self-assembled cellular structures to the cryopreservation appears to be a promising strategy for their off-the-shelf availability.

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.

Automatic Counting of Intra-Cellular Ribonucleo-Protein Aggregates in Saccharomyces cerevisiae Using a Textural Approach.

In the context of microbiology, recent studies show the importance of ribonucleo-protein aggregates (RNPs) for the understanding of mechanisms involved in cell responses to specific environmental conditions. The assembly and disassembly of aggregates is a dynamic process, the characterization of the stage of their evolution can be performed by the evaluation of their number. The aim of this study is to propose a method to automatically determine the count of RNPs. We show that the determination of a precise count is an issue by itself and hence, we propose three textural approaches: a classical point of view using Haralick features, a frequency point of view with generalized Fourier descriptors, and a structural point of view with Zernike moment descriptors (ZMD). These parameters are then used as inputs for a supervised classification in order to determine the most relevant. An experiment using a specific Saccharomyces cerevisiae strain presenting a fusion between a protein found in RNPs (PAB1) and the green fluorescent protein was performed to benchmark this approach. The fluorescence was observed with two-photon fluorescence microscopy. Results show that the textural approach, by mixing ZMD with Haralick features, allows for the characterization of the number of RNPs.

Assessing tumor cytoarchitecture using multiecho DSC-MRI derived measures of the transverse relaxivity at tracer equilibrium (TRATE).

PURPOSE: In brain tumor dynamic susceptibility contrast (DSC)-MRI studies, multiecho acquisition methods are used to quantify the dynamic changes in T1 and T2 * that occur when contrast agent (CA) extravasates. Such methods also enable the estimation of the effective tissue CA transverse relaxivity. The goal of this study was to evaluate the sensitivity of the transverse relaxivity at tracer equilibrium (TRATE) to tumor cytoarchitecture. METHODS: Computational and in vitro studies were used to evaluate the biophysical basis of TRATE. In 9L, C6, and human brain tumors, TRATE, the apparent diffusion coefficient (ADC), the CA transfer constant (K(trans) ), the extravascular extracellular volume fraction (ve ), and histological data were compared. RESULTS: Simulations and in vitro results indicate that TRATE is highly sensitive to variations in cellular properties such as cell size and density. The histologic cell density and TRATE values were significantly higher in 9L tumors as compared to C6 tumors. In animal and human tumors, a voxel-wise comparison of TRATE with ADC, ve , and K(trans) maps showed low spatial correlation. CONCLUSION: The assessment of TRATE is clinically feasible and its sensitivity to tissue cytoarchitectural features not present in other imaging methods indicate that it could potentially serve as a unique structural signature or "trait" of cancer.

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.

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.

Foams with 3D Spatially Programmed Mechanics Enabled by Autonomous Active Learning on Viscous Thread Printing.

Foams are versatile by nature and ubiquitous in a wide range of applications, including padding, insulation, and acoustic dampening. Previous work established that foams 3D printed via Viscous Thread Printing (VTP) can in principle combine the flexibility of 3D printing with the mechanical properties of conventional foams. However, the generality of prior work is limited due to the lack of predictable process-property relationships. In this work, a self-driving lab is utilized that combines automated experimentation with machine learning to identify a processing subspace in which dimensionally consistent materials are produced using VTP with spatially programmable mechanical properties. In carrying out this process, an underlying self-stabilizing characteristic of VTP layer thickness is discovered as an important feature for its extension to new materials and systems. Several complex exemplars are constructed to illustrate the newly enabled capabilities of foams produced via VTP, including 1D gradient rectangular slabs, 2D localized stiffness zones on an insole orthotic and living hinges, and programmed 3D deformation via a cable-driven humanoid hand. Predictive mapping models are developed and validated for both thermoplastic polyurethane (TPU) and polylactic acid (PLA) filaments, suggesting the ability to train a model for any material suitable for material extrusion (ME) 3D printing.

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 vf and the structural anisotropy orientation ß. 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 vf and ß 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.

Researching on the Effect of Input Parameters on the Quality and Manufacturability of 3D-Printed Cellular Samples from Nylon 12 CF in Synergy with Testing Their Behavior in Bending.

The study of cellular structures and their properties represents big potential for their future applications in real practice. The article aims to study the effect of input parameters on the quality and manufacturability of cellular samples 3D-printed from Nylon 12 CF in synergy with testing their bending behavior. Three types of structures (Schwarz Diamond, Shoen Gyroid, and Schwarz Primitive) were selected for investigation that were made via the fused deposition modeling technique. As part of the research focused on the settings of input parameters in terms of the quality and manufacturability of the samples, input parameters such as volume fraction, temperature of the working space, filament feeding method and positioning of the sample on the printing pad were specified for the combination of the used material and 3D printer. During the experimental investigation of the bending properties of the samples, a three-point bending test was performed. The dependences of force on deflection were mathematically described and the amount of absorbed energy and ductility were evaluated. The results show that among the investigated structures, the Schwarz Diamond structure appears to be the most suitable for bending stress applications.

Nature's Load-Bearing Design Principles and Their Application in Engineering: A Review.

Biological structures optimized through natural selection provide valuable insights for engineering load-bearing components. This paper reviews six key strategies evolved in nature for efficient mechanical load handling: hierarchically structured composites, cellular structures, functional gradients, hard shell-soft core architectures, form follows function, and robust geometric shapes. The paper also discusses recent research that applies these strategies to engineering design, demonstrating their effectiveness in advancing technical solutions. The challenges of translating nature's designs into engineering applications are addressed, with a focus on how advancements in computational methods, particularly artificial intelligence, are accelerating this process. The need for further development in innovative material characterization techniques, efficient modeling approaches for heterogeneous media, multi-criteria structural optimization methods, and advanced manufacturing techniques capable of achieving enhanced control across multiple scales is underscored. By highlighting nature's holistic approach to designing functional components, this paper advocates for adopting a similarly comprehensive methodology in engineering practices to shape the next generation of load-bearing technical components.

Recent Advances in Single Cell Analysis by Electrochemiluminescence.

Understanding biological mechanisms operating in cells is one of the major goals of biology. Since heterogeneity is the fundamental property of cellular systems, single cell measurements can provide more accurate information about the composition, dynamics, and regulatory circuits of cells than population-averaged assays. Electrochemiluminescence (ECL), the light emission triggered by electrochemical reactions, is an emerging approach for single cell analysis. Numerous analytes, ranging from small biomolecules such as glucose and cholesterol, proteins and nucleic acids to subcellular structures, have been determined in single cells by ECL, which yields new insights into cellular functions. This review aims to provide an overview of research progress on ECL principles and systems for single cell analysis in recent years. The ECL reaction mechanisms are briefly introduced, and then the advances and representative works in ECL single cell analysis are summarized. Finally, outlooks and challenges in this field are addressed.

Process Parameter Investigation and Torsional Strength Analysis of the Additively Manufactured 3D Structures Made of 20MnCr5 Steel.

An ongoing growth of the available materials dedicated to additive manufacturing (AM) significantly extends the possibilities of their usage in many applications. A very good example is 20MnCr5 steel which is very popular in conventional manufacturing technologies and shows good processability in AM processes. This research takes into account the process parameter selection and torsional strength analysis of AM cellular structures. The conducted research revealed a significant tendency for between-layer cracking which is strictly dependent on the layered structure of the material. Additionally, the highest torsional strength was registered for specimens with a honeycomb structure. To determine the best-obtained properties, in the case of the samples with cellular structures, a torque-to-mass coefficient was introduced. It indicated the best properties of honeycomb structures, which have about 10% smaller torque-to-mass coefficient values than monolithic structures (PM samples).

Applications of Fourier Transform-Infrared spectroscopy in microbial cell biology and environmental microbiology: advances, challenges, and future perspectives.

Microorganisms play pivotal roles in shaping ecosystems and biogeochemical cycles. Their intricate interactions involve complex biochemical processes. Fourier Transform-Infrared (FT-IR) spectroscopy is a powerful tool for monitoring these interactions, revealing microorganism composition and responses to the environment. This review explores the diversity of applications of FT-IR spectroscopy within the field of microbiology, highlighting its specific utility in microbial cell biology and environmental microbiology. It emphasizes key applications such as microbial identification, process monitoring, cell wall analysis, biofilm examination, stress response assessment, and environmental interaction investigation, showcasing the crucial role of FT-IR in advancing our understanding of microbial systems. Furthermore, we address challenges including sample complexity, data interpretation nuances, and the need for integration with complementary techniques. Future prospects for FT-IR in environmental microbiology include a wide range of transformative applications and advancements. These include the development of comprehensive and standardized FT-IR libraries for precise microbial identification, the integration of advanced analytical techniques, the adoption of high-throughput and single-cell analysis, real-time environmental monitoring using portable FT-IR systems and the incorporation of FT-IR data into ecological modeling for predictive insights into microbial responses to environmental changes. These innovative avenues promise to significantly advance our understanding of microorganisms and their complex interactions within various ecosystems.