Deformation Behavior of Cross-Linked Supercrystalline Nanocomposites: An in Situ SAXS/WAXS Study during Uniaxial Compression.

With the ever-expanding functional applications of supercrystalline nanocomposites (a relatively new category of materials consisting of organically functionalized nanoparticles arranged into periodic structures), it becomes necessary to ensure their structural stability and understand their deformation and failure mechanisms. Inducing the cross-linking of the functionalizing organic ligands, for instance, leads to a remarkable enhancement of the nanocomposites' mechanical properties. It is however still unknown how the cross-linked organic phase redistributes applied loads, how the supercrystalline lattice accommodates the imposed deformations, and thus in general what phenomena govern the overall material's mechanical response. This work elucidates these aspects for cross-linked supercrystalline nanocomposites through an in situ small- and wide-angle X-ray scattering study combined with uniaxial pressing. Because of this loading condition, it emerges that the cross-linked ligands effectively carry and distribute loads homogeneously throughout the nanocomposites, while the superlattice deforms via rotation, slip, and local defects generation.

With a little help from familiar interlocutors: real-world language use in young and older adults.

OBJECTIVES: Functional psychologists are concerned with the performance of cognitive activities in the real world in relation to cognitive changes in older age. Conversational contexts may mitigate the influence of cognitive aging on the cognitive activity of language production. This study examined effects of familiarity with interlocutors, as a context, on language production in the real world. METHOD: We collected speech samples using iPhones, where an audio recording app (i.e. Electronically Activated Recorder [EAR]) was installed. Over 31,300 brief audio files (30-second long) were randomly collected across four days from 61 young and 48 healthy older adults in Switzerland. We transcribed the audio files that included participants' speech and manually coded for familiar interlocutors (i.e. significant other, friends, family members) and strangers. We computed scores of vocabulary richness and grammatical complexity from the transcripts using computational linguistics techniques. RESULTS: Bayesian multilevel analyses showed that participants used richer vocabulary and more complex grammar when talking with familiar interlocutors than with strangers. Young adults used more diverse vocabulary than older adults and the age effects remained stable across contexts. Furthermore, older adults produced equally complex grammar as young adults did with the significant other, but simpler grammar than young adults with friends and family members. CONCLUSION: Familiarity with interlocutors is a promising contextual factor for research on aging and language complexity in the real world. Results were discussed in the context of cognitive aging.

Mapping the Mechanical Properties of Hierarchical Supercrystalline Ceramic-Organic Nanocomposites.

Multiscale ceramic-organic supercrystalline nanocomposites with two levels of hierarchy have been developed via self-assembly with tailored content of the organic phase. These nanocomposites consist of organically functionalized ceramic nanoparticles forming supercrystalline micron-sized grains, which are in turn embedded in an organic-rich matrix. By applying an additional heat treatment step at mild temperatures (250-350 °C), the mechanical properties of the hierarchical nanocomposites are here enhanced. The heat treatment leads to partial removal and crosslinking of the organic phase, minimizing the volume occupied by the nanocomposites' soft phase and triggering the formation of covalent bonds through the organic ligands interfacing the ceramic nanoparticles. Elastic modulus and hardness up to 45 and 2.5 GPa are attained, while the hierarchical microstructure is preserved. The presence of an organic phase between the supercrystalline grains provides a toughening effect, by curbing indentation-induced cracks. A mapping of the nanocomposites' mechanical properties reveals the presence of multiple microstructural features and how they evolve with heat treatment temperature. A comparison with non-hierarchical, homogeneous supercrystalline nanocomposites with lower organic content confirms how the hierarchy-inducing organic excess results in toughening, while maintaining the beneficial effects of crosslinking on the materials' stiffness and hardness.

Modulating the Mechanical Properties of Supercrystalline Nanocomposite Materials via Solvent-Ligand Interactions.

Supercrystalline nanocomposite materials with micromechanical properties approaching those of nacre or similar structural biomaterials can be produced by self-assembly of organically modified nanoparticles and further strengthened by cross-linking. The strengthening of these nanocomposites is controlled via thermal treatment, which promotes the formation of covalent bonds between interdigitated ligands on the nanoparticle surface. In this work, it is shown how the extent of the mechanical properties enhancement can be controlled by the solvent used during the self-assembly step. We find that the resulting mechanical properties correlate with the Hansen solubility parameters of the solvents and ligands used for the supercrystal assembly: the hardness and elastic modulus decrease as the Hansen solubility parameter of the solvent approaches the Hansen solubility parameter of the ligands that stabilize the nanoparticles. Moreover, it is shown that self-assembled supercrystals that are subsequently uniaxially pressed can deform up to 6 %. The extent of this deformation is also closely related to the solvent used during the self-assembly step. These results indicate that the conformation and arrangement of the organic ligands on the nanoparticle surface not only control the self-assembly itself but also influence the mechanical properties of the resulting supercrystalline material. The Hansen solubility parameters may therefore serve as a tool to predict what solvents and ligands should be used to obtain supercrystalline materials with good mechanical properties.

Organically linked iron oxide nanoparticle supercrystals with exceptional isotropic mechanical properties.

It is commonly accepted that the combination of the anisotropic shape and nanoscale dimensions of the mineral constituents of natural biological composites underlies their superior mechanical properties when compared to those of their rather weak mineral and organic constituents. Here, we show that the self-assembly of nearly spherical iron oxide nanoparticles in supercrystals linked together by a thermally induced crosslinking reaction of oleic acid molecules leads to a nanocomposite with exceptional bending modulus of 114 GPa, hardness of up to 4 GPa and strength of up to 630 MPa. By using a nanomechanical model, we determined that these exceptional mechanical properties are dominated by the covalent backbone of the linked organic molecules. Because oleic acid has been broadly used as nanoparticle ligand, our crosslinking approach should be applicable to a large variety of nanoparticle systems.

Metal Nanoparticle Growth within Clay-Polymer Nacre-Inspired Materials for Improved Catalysis and Plasmonic Detection in Complex Biofluids.

Recent studies have shown that layered silicate clays can be used to form a nacre-like bioinspired layered structure with various polymer fillers, leading to composite films with good material strength, gas-barrier properties, and high loading capacity. We go one step further by in situ growing metal nanoparticles in nacre-like layered films based on layered silicate clays, which can be used for applications in plasmonic sensing and catalysis. The degree of anisotropy of the nanoparticles grown in the film can be controlled by adjusting the ratio of clay to polymer or gold to clay and reducing agent concentration, as well as silver overgrowth, which greatly enhances the surface enhanced Raman scattering activity of the composite. We show the performance of the films for SERS detection of bacterial quorum sensing molecules in culture medium, and catalytic properties are demonstrated through the reduction of 4-nitroaniline. These films serve as the first example of seedless, in situ nanoparticle growth within nacre-mimetic materials, and open the path to basic research on the influence of different building blocks and polymeric mortars on nanoparticle morphology and distribution, as well as applications in catalysis, sensing, and antimicrobial surfaces using such materials.

Determination of the packing fraction in photonic glass using synchrotron radiation nanotomography.

Photonic glass is a material class that can be used as photonic broadband reflectors, for example in the infrared regime as thermal barrier coating films. Photonic properties such as the reflectivity depend on the ordering and material packing fraction over the complete film thickness of up to 100 µm. Nanotomography allows acquiring these key parameters throughout the sample volume at the required resolution in a non-destructive way. By performing a nanotomography measurement at the PETRA III beamline P05 on a photonic glass film, the packing fraction throughout the complete sample thickness was analyzed. The results showed a packing fraction significantly smaller than the expected random close packing giving important information for improving the fabrication and processing methods of photonic glass material in the future.

Influence of water and protein content on the creep behavior in dental enamel.

The creep behavior of untreated and deproteinized dental enamel in dry and wet state was analyzed by nanoindentation with a spherical tip. Additionally, the influence of the loading rate was investigated. Dry untreated and deproteinized dental enamel only showed minor creep over 100 s and deproteinization did not affect the dry enamel's behavior significantly. With slower loading rates some creep already occurs during the loading period, such that the creep displacement during load hold is less than with faster loading rates. Wet untreated and deproteinized enamel showed significantly more creep compared to the dry samples. The differences between the untreated and deproteinized enamel were only minor but significant, revealing that water affects the creep behavior of biological materials such as enamel significantly. The proposed deformation mechanism of naturally porous enamel under compression is compaction of the HAP crystallites and fluid displacement within material underneath the indented area. STATEMENT OF SIGNIFICANCE: This study investigates the creep behavior of untreated and deproteinized dental enamel in dry and wet conditions. It is shown that while the protein content does not affect enamel's behavior significantly, the wet conditions lead to an increased creep in enamel. The proposed deformation mechanism of naturally porous enamel under compression is compaction of the HAP crystallites and fluid displacement within material underneath the indented area. Based on this observation a simple analytical model has been developed, aiming to deepen our understanding of the deformation behavior of biological materials.

Exploring the role of AI in classifying, analyzing, and generating case reports on assisted suicide cases: feasibility and ethical implications.

This paper presents a study on the use of AI models for the classification of case reports on assisted suicide procedures. The database of the five Dutch regional bioethics committees was scraped to collect the 72 case reports available in English. We trained several AI models for classification according to the categories defined by the Dutch Termination of Life on Request and Assisted Suicide (Review Procedures) Act. We also conducted a related project to fine-tune an OpenAI GPT-3.5-turbo large language model for generating new fictional but plausible cases. As AI is increasingly being used for judgement, it is possible to imagine an application in decision-making regarding assisted suicide. Here we explore two arising questions: feasibility and ethics, with the aim of contributing to a critical assessment of the potential role of AI in decision-making in highly sensitive areas.

Solvent controlled 2D structures of bottom-up fabricated nanoparticle superlattices.

We demonstrate that oleyl phosphate ligand-stabilized iron oxide nanocubes as building blocks can be assembled into 2D supercrystalline mono- and multilayers on flat YSZ substrates within a few minutes using a simple spin-coating process. As a bottom-up process, the growth takes place in a layer-by-layer mode and therefore by tuning the spin-coating parameters, the exact number of deposited monolayers can be controlled. Furthermore, ex situ scanning electron and atomic force microscopy as well as X-ray reflectivity measurements give evidence that the choice of solvent allows the control of the lattice type of the final supercrystalline monolayers. This observation can be assigned to the different Hansen solubilities of the solvents used for the nanoparticle dispersion because it determines the size and morphology of the ligand shell surrounding the nanoparticle core. Here, by using toluene and chloroform as solvents, it can be controlled whether the resulting monolayers are ordered in a square or hexagonal supercrystalline lattice.

Challenges and best practices for digital unstructured data enrichment in health research: A systematic narrative review.

Digital data play an increasingly important role in advancing health research and care. However, most digital data in healthcare are in an unstructured and often not readily accessible format for research. Unstructured data are often found in a format that lacks standardization and needs significant preprocessing and feature extraction efforts. This poses challenges when combining such data with other data sources to enhance the existing knowledge base, which we refer to as digital unstructured data enrichment. Overcoming these methodological challenges requires significant resources and may limit the ability to fully leverage their potential for advancing health research and, ultimately, prevention, and patient care delivery. While prevalent challenges associated with unstructured data use in health research are widely reported across literature, a comprehensive interdisciplinary summary of such challenges and possible solutions to facilitate their use in combination with structured data sources is missing. In this study, we report findings from a systematic narrative review on the seven most prevalent challenge areas connected with the digital unstructured data enrichment in the fields of cardiology, neurology and mental health, along with possible solutions to address these challenges. Based on these findings, we developed a checklist that follows the standard data flow in health research studies. This checklist aims to provide initial systematic guidance to inform early planning and feasibility assessments for health research studies aiming combining unstructured data with existing data sources. Overall, the generality of reported unstructured data enrichment methods in the studies included in this review call for more systematic reporting of such methods to achieve greater reproducibility in future studies.

When Cortical Bone Matrix Properties Are Indiscernible between Elderly Men with and without Type 2 Diabetes, Fracture Resistance Follows Suit.

Type 2 diabetes mellitus (T2DM) is a metabolic disease affecting bone tissue and leading to increased fracture risk in men and women, independent of bone mineral density (BMD). Thus, bone material quality (i.e., properties that contribute to bone toughness but are not attributed to bone mass or quantity) is suggested to contribute to higher fracture risk in diabetic patients and has been shown to be altered. Fracture toughness properties are assumed to decline with aging and age-related disease, while toughness of human T2DM bone is mostly determined from compression testing of trabecular bone. In this case-control study, we determined fracture resistance in T2DM cortical bone tissue from male individuals in combination with a multiscale approach to assess bone material quality indices. All cortical bone samples stem from male nonosteoporotic individuals and show no significant differences in microstructure in both groups, control and T2DM. Bone material quality analyses reveal that both control and T2DM groups exhibit no significant differences in bone matrix composition assessed with Raman spectroscopy, in BMD distribution determined with quantitative back-scattered electron imaging, and in nanoscale local biomechanical properties assessed via nanoindentation. Finally, notched three-point bending tests revealed that the fracture resistance (measured from the total, elastic, and plastic J-integral) does not significantly differ in T2DM and control group, when both groups exhibit no significant differences in bone microstructure and material quality. This supports recent studies suggesting that not all T2DM patients are affected by a higher fracture risk but that individual risk profiles contribute to fracture susceptibility, which should spur further research on improving bone material quality assessment in vivo and identifying risk factors that increase bone fragility in T2DM. © 2023 The Authors. JBMR Plus published by Wiley Periodicals LLC on behalf of American Society for Bone and Mineral Research.

Relation mining experiments in the pharmacogenomics domain.

The mutual interactions among genes, diseases, and drugs are at the heart of biomedical research, and are especially important for the pharmacological industry. The recent trend towards personalized medicine makes it increasingly relevant to be able to tailor drugs to specific genetic makeups. The pharmacogenetics and pharmacogenomics knowledge base (PharmGKB) aims at capturing relevant information about such interactions from several sources, including curation of the biomedical literature. Advanced text mining tools which can support the process of manual curation are increasingly necessary in order to cope with the deluge of new published results. However, effective evaluation of those tools requires the availability of manually curated data as gold standard. In this paper we discuss how the existing PharmGKB database can be used for such an evaluation task in a way similar to the usage of gold standard data derived from protein-protein interaction databases in one of the recent BioCreative shared tasks. Additionally, we present our own considerations and results on the feasibility and difficulty of such a task.

Strengthening Engineered Nanocrystal Three-Dimensional Superlattices via Ligand Conformation and Reactivity.

Nanocrystal assembly into ordered structures provides mesostructural functional materials with a precise control that starts at the atomic scale. However, the lack of understanding on the self-assembly itself plus the poor structural integrity of the resulting supercrystalline materials still limits their application into engineered materials and devices. Surface functionalization of the nanobuilding blocks with organic ligands can be used not only as a means to control the interparticle interactions during self-assembly but also as a reactive platform to further strengthen the final material via ligand cross-linking. Here, we explore the influence of the ligands on superlattice formation and during cross-linking via thermal annealing. We elucidate the effect of the surface functionalization on the nanostructure during self-assembly and show how the ligand-promoted superlattice changes subsequently alter the cross-linking behavior. By gaining further insights on the chemical species derived from the thermally activated cross-linking and its effect in the overall mechanical response, we identify an oxidative radical polymerization as the main mechanism responsible for the ligand cross-linking. In the cascade of reactions occurring during the surface-ligands polymerization, the nanocrystal core material plays a catalytic role, being strongly affected by the anchoring group of the surface ligands. Ultimately, we demonstrate how the found mechanistic insights can be used to adjust the mechanical and nanostructural properties of the obtained nanocomposites. These results enable engineering supercrystalline nanocomposites with improved cohesion while preserving their characteristic nanostructure, which is required to achieve the collective properties for broad functional applications.

Detection of interaction articles and experimental methods in biomedical literature.

BACKGROUND: This article describes the approaches taken by the OntoGene group at the University of Zurich in dealing with two tasks of the BioCreative III competition: classification of articles which contain curatable protein-protein interactions (PPI-ACT) and extraction of experimental methods (PPI-IMT). RESULTS: Two main achievements are described in this paper: (a) a system for document classification which crucially relies on the results of an advanced pipeline of natural language processing tools; (b) a system which is capable of detecting all experimental methods mentioned in scientific literature, and listing them with a competitive ranking (AUC iP/R > 0.5). CONCLUSIONS: The results of the BioCreative III shared evaluation clearly demonstrate that significant progress has been achieved in the domain of biomedical text mining in the past few years. Our own contribution, together with the results of other participants, provides evidence that natural language processing techniques have become by now an integral part of advanced text mining approaches.

The Protein-Protein Interaction tasks of BioCreative III: classification/ranking of articles and linking bio-ontology concepts to full text.

BACKGROUND: Determining usefulness of biomedical text mining systems requires realistic task definition and data selection criteria without artificial constraints, measuring performance aspects that go beyond traditional metrics. The BioCreative III Protein-Protein Interaction (PPI) tasks were motivated by such considerations, trying to address aspects including how the end user would oversee the generated output, for instance by providing ranked results, textual evidence for human interpretation or measuring time savings by using automated systems. Detecting articles describing complex biological events like PPIs was addressed in the Article Classification Task (ACT), where participants were asked to implement tools for detecting PPI-describing abstracts. Therefore the BCIII-ACT corpus was provided, which includes a training, development and test set of over 12,000 PPI relevant and non-relevant PubMed abstracts labeled manually by domain experts and recording also the human classification times. The Interaction Method Task (IMT) went beyond abstracts and required mining for associations between more than 3,500 full text articles and interaction detection method ontology concepts that had been applied to detect the PPIs reported in them. RESULTS: A total of 11 teams participated in at least one of the two PPI tasks (10 in ACT and 8 in the IMT) and a total of 62 persons were involved either as participants or in preparing data sets/evaluating these tasks. Per task, each team was allowed to submit five runs offline and another five online via the BioCreative Meta-Server. From the 52 runs submitted for the ACT, the highest Matthew's Correlation Coefficient (MCC) score measured was 0.55 at an accuracy of 89% and the best AUC iP/R was 68%. Most ACT teams explored machine learning methods, some of them also used lexical resources like MeSH terms, PSI-MI concepts or particular lists of verbs and nouns, some integrated NER approaches. For the IMT, a total of 42 runs were evaluated by comparing systems against manually generated annotations done by curators from the BioGRID and MINT databases. The highest AUC iP/R achieved by any run was 53%, the best MCC score 0.55. In case of competitive systems with an acceptable recall (above 35%) the macro-averaged precision ranged between 50% and 80%, with a maximum F-Score of 55%. CONCLUSIONS: The results of the ACT task of BioCreative III indicate that classification of large unbalanced article collections reflecting the real class imbalance is still challenging. Nevertheless, text-mining tools that report ranked lists of relevant articles for manual selection can potentially reduce the time needed to identify half of the relevant articles to less than 1/4 of the time when compared to unranked results. Detecting associations between full text articles and interaction detection method PSI-MI terms (IMT) is more difficult than might be anticipated. This is due to the variability of method term mentions, errors resulting from pre-processing of articles provided as PDF files, and the heterogeneity and different granularity of method term concepts encountered in the ontology. However, combining the sophisticated techniques developed by the participants with supporting evidence strings derived from the articles for human interpretation could result in practical modules for biological annotation workflows.

Direct writing of colloidal suspensions onto inclined surfaces: Optimizing dispense volume for homogeneous structures.

HYPOTHESIS: A process to fabricate structures on inclined substrates has the potential to yield novel applications for colloidal-based structures. However, for conventional techniques, besides the coffee ring effect (CRE), anisotropic particle deposition along the inclination direction (IE) is expected to occur. We hypothesize that both effects can be inhibited by reducing the dispense volume during printing by direct writing. EXPERIMENTS: We combined an additive manufacturing technique, namely direct writing, with colloidal assembly (AMCA) for an automated and localized drop-cast of polystyrene and silica suspensions onto inclined surfaces. Herein, we investigated the influence of the substrate tilting angle and the dispense volume on the printing of colloids and the resulting structures' morphology. FINDINGS: The results demonstrate that a reduction in the dispense volume hinders the CRE and IE for both particles' systems, even though the evaporation mode is different. For polystyrene, the droplets evaporated solely in stick-mode, enabling a "surface capturing effect", while for silica, droplets evaporated in mixed stick-slip mode and a "confinement effect" was observed, which improved uniformity of the deposition. These findings were used to generate a model of the critical droplet radius needed to print homogeneous colloidal-based structures onto inclined substrates.

Tailoring Disorder and Quality of Photonic Glass Templates for Structural Coloration by Particle Charge Interactions.

To obtain high-quality homogeneous photonic glass-based structural color films over large areas, it is essential to precisely control the degree of disorder of the spherical particles used and reduce the crack density within the films as much as possible. To tailor the disorder and quality of photonic glasses, a heteroaggregation-based process was developed by employing two oppositely charged equal-sized polystyrene (PS) particle types. The influence of the particle size ratio on the extent of heteroaggregation in the suspension mixes is investigated and correlated with both the morphology and the resultant optical properties of the films. The results show that the oppositely charged particle size ratio within the mix greatly influences the assembled structure in the films, affecting their roughness, crack density, and the coffee-ring formation. To better differentiate the morphology of the films, scanning electron microscopy images of the microstructures were classified by a supervised training of a deep convolutional neural network model to find distinctions that are inaccessible by conventional image analysis methods. Selected compositions were then infiltrated with TiO2 via atomic layer deposition, and after removal of the PS spheres, surface-templated inverse photonic glasses were obtained. Different color impressions and optical properties were obtained depending on the heteroaggregation level and thus the quality of the resultant films. The best results regarding the stability of the films and suppression of coffee-ring formation are obtained with a 35 wt % positively charged over negatively charged particle mix, which yielded enhanced structural coloration associated with improved film quality, tailored by the heteroaggregation fabrication process.

The geometrical structure of interfaces in dental enamel: A FIB-STEM investigation.

In this study a high resolution structural analysis revealed that enamel prisms are surrounded by an interface that is discontinuous with frequent mineral to mineral contact separated by gaps. This contact manifests either by crystallites bridging the boundary between prismatic and interprismatic enamel or continuous crystallites curving and bridging the interprismatic enamel to the prisms. The geometrical resolution of this TEM investigation of the interfaces is ≤2 nm as a basis for micromechanical models. Within this resolution, contrary to existing structural descriptions of dental enamel structure in materials science literature, here the crystallites themselves are shown to be either in direct contact with each other, sometimes even fusing together, or are separated by gaps. Image analysis revealed that on average only 57 ± 15% of the interface consists of points of no contact between crystallites. This work reveals structural features of dental enamel that contribute important understanding to both the architecture and mechanical properties of this biological material. A new structural model is proposed and the implications for the mechanical properties of dental enamel are discussed. STATEMENT OF SIGNIFICANCE: In this study a high resolution structural analysis, employing focused ion beam and transmission electron microscopy revealed that enamel prisms are surrounded by interfaces that are discontinuous with frequent mineral to mineral contact separated by gaps. Although the interfaces in enamel have been investigated previously, existing studies are lacking in detail considering the geometry and morphology of the interfaces. We think that this result is of great importance when it comes to the understanding of the mechanical properties. In our opinion the concept of soft sheaths is no longer feasible. The resulting observations are included in a new structural model which provides new qualitative insights into the mechanical behavior. Existing analytical models were applied to simulate the new geometrical structure.