Protocol for creating representations of molecular structures using a polymer-specific decoder

To supply chemical structures of polymers for machine learning applications, decoding is necessary. Here, we present a protocol for generating polymer fingerprints (PFPs), which are representations of molecular structures, using a polymer-specific decoder. We outline steps for downloading, installing, and basic application of the software. Moreover, we present procedures for processing and analyzing polymer structure data and the preparation for integration into machine learning methods. On this basis, we explain how artificial neural networks can be utilized to predict polymer properties. For complete details on the use and execution of this protocol, please refer to Köster et al.1.

An Iridium Complex as Bidentate Halogen Bond-Based Anion Receptor Featuring an IncreasedOptical Response

We present a luminescent Ir(III) complex featuring a bidentate halogen bond donor site capable of strong anion binding. The tailor-made Ir(III)(L)2 moiety offers a significantly higher emission quantum yield (8.4 %) compared to previous Ir(III)-based chemo-sensors (2.5 %). The successful binding of chloride, bromide and acetate is demonstrated using emission titrations. These experiments reveal association constants of up to 1.6×105 M-1. Furthermore, a new approach to evaluate the association constant by utilizing the shift of the emission was used for the first time. The experimentally observed characteristics are supported by quantum chemical simulations.

Optimization of Mixed Micelles Based on Oppositely Charged Block Copolymers by Machine Learning for Application in Gene Delivery

The COVID-19 mRNA vaccines represent a milestone in developing non-viral gene carriers, and their success highlights the crucial need for continued research in this field to address further challenges. Polymer-based delivery systems are particularly promising due to their versatile chemical structure and convenient adaptability, but struggle with the toxicity-efficiency dilemma. Introducing anionic, hydrophilic, or "stealth" functionalities represents a promising approach to overcome this dilemma in gene delivery. Here, two sets of diblock terpolymers are created comprising hydrophobic poly(n-butyl acrylate) (PnBA), a copolymer segment made of hydrophilic 4-acryloylmorpholine (NAM), and either the cationic 3-guanidinopropyl acrylamide (GPAm) or the 2-carboxyethyl acrylamide (CEAm), which is negatively charged at neutral conditions. These oppositely charged sets of diblocks are co-assembled in different ratios to form mixed micelles. Since this experimental design enables countless mixing possibilities, a machine learning approach is applied to identify an optimal GPAm/CEAm ratio for achieving high transfection efficiency and cell viability with little resource expenses. After two runs, an optimal ratio to overcome the toxicity-efficiency dilemma is identified. The results highlight the remarkable potential of integrating machine learning into polymer chemistry to effectively tackle the enormous number of conceivable combinations for identifying novel and powerful gene transporters.

Molecular in situ monitoring of the pH-triggered response in adaptive polymers by two-dimensional Raman micro-correlation-spectroscopy

Stimuli-responsive polymers can switch specific physical properties in response to a change of the environmental conditions. This behavior offers unique advantages in applications where adaptive materials are needed. To tune the properties of stimuli-responsive polymers, a detailed understanding of the relationship between the applied stimulus and changes in molecular structure as well as the relationship between the latter and macroscopic properties is required, which until now has required laborious methods. Here, we present a straightforward way to investigate the progressing trigger, the change of the chemical composition of the polymer and the macroscopic properties simultaneously. Thereby, the response behavior of the reversible polymer is studied in situ with molecular sensitivity and spatial as well as temporal resolution utilizing Raman micro-spectroscopy. Combined with two-dimensional correlation analysis (2DCOS), this method reveals the stimuli-response on a molecular level and determines the sequence of changes and the diffusion rate inside the polymer. Due to the label-free and non-invasive approach, it is furthermore possible to combine this method with the investigation of macroscopic properties revealing the response of the polymer to the external stimulus on both the molecular and the macroscopic level.

Oxymethylene Ether (OME) Fuel Catalyst Screening Using in-situ NMR spectroscopy

Online NMR measurements are introduced in the current study as a new analytical setup for investigation of the oxymethylene dimethyl ether (OME) synthesis. For the validation of the setup, the newly established method is compared with state-of-the-art gas chromatographic analysis. Afterwards, the influence of different parameters, such as temperature, catalyst concentration and catalyst type on the OME fuel formation based on trioxane and dimethoxymethane is investigated. As catalysts, AmberlystTM 15 (A15) and trifluoromethanesulfonic acid (TfOH) are utilized. A kinetic model is applied to describe the reaction in more detail. Based on these results, the activation energy (A15: 46.3 kJ mol -1 and TfOH: 79.8 kJ mol-1) and the order in catalyst (A15: 0.8 and TfOH: 2.2) are calculated and discussed.

Improvement of High-Throughput Experimentation Using Synthesis Robots by the Implementation of Tailor-Made Sensors

A small, low-cost, self-produced photometer is implemented into a synthesis robot and combined with a modified UV chamber to enable automated sampling and online characterization. In order to show the usability of the new approach, two different reversible addition–fragmentation chain transfer (RAFT) polymers were irradiated with UV light. Automated sampling and subsequent characterization revealed different reaction kinetics depending on polymer type. Thus, a long initiation time (20 min) is required for the end-group degradation of poly(ethylene glycol) ether methyl methacrylate (poly(PEGMEMA)), whereas poly(methyl methacrylate) (PMMA) is immediately converted. Lastly, all photometric samples are characterized via size-exclusion chromatography using UV and RI detectors to prove the results of the self-produced sensor and to investigate the molar mass shift during the reaction.

Fully Automated Multi-Step Synthesis of Block Copolymers

An automated synthesis protocol is developed for the synthesis of block copolymers in a multi-step approach in a fully automated manner. For this purpose, an automated dialysis setup is combined with robot-based synthesis protocols. Consequently, several block copolymerizations are executed completely automated and compared to the respective manual synthesis. As a result, this study opens up the field of autonomous multi-step reactions without any human interactions.

A user-guide for polymer purification using dialysis

Dialysis diffusion kinetics are performed via in-situ NMR spectroscopy for numerous different raw polymeric solutions to result in a general guideline for polymer purification using dialysis. In several approaches, a...

[Update on collaborative autopsy-based research in German pathology, neuropathology, and forensic medicine]

BACKGROUND

Autopsies are a valuable tool for understanding disease, including COVID-19.

MATERIALS AND METHODS

The German Registry of COVID-19 Autopsies (DeRegCOVID), established in April 2020, serves as the electronic backbone of the National Autopsy Network (NATON), launched in early 2022 following DEFEAT PANDEMIcs.

RESULTS

The NATON consortium's interconnected, collaborative autopsy research is enabled by an unprecedented collaboration of 138 individuals at more than 35 German university and non-university autopsy centers through which pathology, neuropathology, and forensic medicine autopsy data including data on biomaterials are collected in DeRegCOVID and tissue-based research and methods development are conducted. More than 145 publications have now emerged from participating autopsy centers, highlighting various basic science and clinical aspects of COVID-19, such as thromboembolic events, organ tropism, SARS-CoV‑2 detection methods, and infectivity of SARS-CoV-2 at autopsy.

CONCLUSIONS

Participating centers have demonstrated the high value of autopsy and autopsy-derived data and biomaterials to modern medicine. The planned long-term continuation and further development of the registry and network, as well as the open and participatory design, will allow the involvement of all interested partners.

Prediction of Nanoparticle Sizes for Arbitrary Methacrylates Using Artificial Neuronal Networks

Particle sizes represent one of the key factors influencing the usability and specific targeting of nanoparticles in medical applications such as vectors for drug or gene therapy. A multi-layered graph convolutional network combined with a fully connected neuronal network is presented for the prediction of the size of nanoparticles based only on the polymer structure, the degree of polymerization, and the formulation parameters. The model is capable of predicting particle sizes obtained by nanoprecipitation of different poly(methacrylates). This includes polymers the network has not been trained with, indicating the high potential for generalizability of the model. By utilizing this model, a significant amount of time and resources can be saved in formulation optimization without extensive primary testing of material properties.

Generation and functional characterization of recombinant Porphyromonas gingivalis W83 FimA

Porphyromonas gingivalis (P. gingivalis) is regarded as a keystone pathogen in destructive periodontal diseases. It expresses a variety of virulence factors, amongst them fimbriae that are involved in colonization, invasion, establishment and persistence of the bacteria inside the host cells. The fimbriae also were demonstrated to affect the host immune-response mechanisms. The major fimbriae are able to bind specifically to different host cells, amongst them peripheral blood monocytes. The interaction of these cells with fimbriae induces release of cytokines such as interleukin-1 (IL-1), IL-6, and tumor necrosis factor-α (TNF-α). The aim of this study was to generate recombinant major FimA protein from P. gingivalis W83 fimbriae and to prove its biological activity. FimA of P. gingivalis W83 was amplified from chromosomal DNA, cloned in a vector and transferred into Listeria innocua. (L. innocua).The expressed protein was harvested and purified using FPLC via a His trap HP column. The identity and purity was demonstrated by gel-electrophoresis and mass-spectrometry. The biological activity was assessed by stimulation of human oral epithelial cells and peripheral blood monocytes with the protein and afterwards cytokines in the supernatants were quantified by enzyme linked immunosorbent assay (ELISA) and cytometric bead array. Recombinant FimA could successfully be generated and purified. Gel-electrophoresis and mass-spectrometry confirmed that the detected sequences are identical with FimA. Stimulation of human monocytes induced the release of high concentrations of IL-1β, IL-6, IL-10 and TNF-α by these cells. In conclusion, a recombinant FimA protein was established and its biological activity was proven. This protein may serve as a promising agent for further investigation of its role in periodontitis and possible new therapeutic approaches.

In-depth characterization of self-healing polymers based on π-π interactions

The self-healing behavior of two supramolecular polymers based on π–π-interactions featuring different polymer backbones is presented. For this purpose, these polymers were synthesized utilizing a polycondensation of a perylene tetracarboxylic dianhydride with polyether-based diamines and the resulting materials were investigated using various analytical techniques. Thus, the molecular structure of the polymers could be correlated with the ability for self-healing. Moreover, the mechanical behavior was studied using rheology. The activation of the supramolecular interactions results in a breaking of these noncovalent bonds, which was investigated using IR spectroscopy, leading to a sufficient increase in mobility and, finally, a healing of the mechanical damage. This scratch-healing behavior was also quantified in detail using an indenter.

Halogen bonding in polymer science: towards new smart materials

The halogen bond is a special non-covalent interaction, which can represent a powerful tool in supramolecular chemistry. Although the halogen bond offers several advantages compared to the related hydrogen bond, it is currently still underrepresented in polymer science. The structural related hydrogen bonding assumes a leading position in polymer materials containing supramolecular interactions, clearly indicating the high potential of using halogen bonding for the design of polymeric materials. The current developments regarding halogen bonding containing polymers include self-assembly, photo-responsive materials, self-healing materials and others. These aspects are highlighted in the present perspective. Furthermore, a perspective on the future of this rising young research field is provided.

The incorporation of halogen bonding into polymer architectures is a new approach for the design of functional materials. This perspective emphasizes the current development in the field of halogen bonding featuring polymer materials.

DNA Origami Meets Polymers: A Powerful Tool for the Design of Defined Nanostructures

The combination of DNA origami nanostructures and polymers provides a new possibility to access defined structures in the 100 nm range. In general, DNA origami serves as a versatile template for the highly specific arrangement of polymer chains. Polymer-DNA hybrid nanostructures can either be created by growing the polymer from the DNA template or by attaching preformed polymers to the DNA scaffold. These conjugations can be of a covalent nature or be based on base-pair hybridization between respectively modified polymers and DNA origami. Furthermore, the negatively charged DNA backbone permits interaction with positively charged polyelectrolytes to form stable complexes. The combination of polymers with tuneable characteristics and DNA origami allows the creation of a new class of hybrid materials, which could offer exciting applications for controlled energy transfer, nanoscale organic circuits, or the templated synthesis of nanopatterned polymeric structures.

Shape-Memory Metallopolymers Based on Two Orthogonal Metal-Ligand Interactions

A new shape-memory polymer is presented, in which both the stable phase as well as the switching unit consist of two different metal complexes. Suitable metal ions, which simultaneously form labile complexes with histidine and stable ones with terpyridine ligands, are identified via isothermal titration calorimetry (ITC) measurements. Different copolymers are synthesized, which contain butyl methacrylate as the main monomer and the metal-binding ligands in the side chains. Zn(TFMS)₂ and NiCl₂ are utilized for the dual crosslinking, resulting in the formation of metallopolymer networks. The switching temperature can simply be tuned by changing the composition as well as by the choice of the metal ion. Strain fixity rates (about 99%) and very high strain recovery rates (up to 95%) are achieved and the mechanism is revealed using different techniques such as Raman spectroscopy.

Digital Transformation in Materials Science: A Paradigm Change in Material's Development

The ongoing digitalization is rapidly changing and will further revolutionize all parts of life. This statement is currently omnipresent in the media as well as in the scientific community; however, the exact consequences of the proceeding digitalization for the field of materials science in general and the way research will be performed in the future are still unclear. There are first promising examples featuring the potential to change discovery and development approaches toward new materials. Nevertheless, a wide range of open questions have to be solved in order to enable the so-called digital-supported material research. The current state-of-the-art, the present and future challenges, as well as the resulting perspectives for materials science are described.

Novel Biobased Self-Healing Ionomers Derived from Itaconic Acid Derivates

This article presents novel biobased ionomers featuring self-healing abilities. These smart materials are synthesized from itaconic acid derivates. Large quantities of itaconic acid can be produced from diverse biomass like corn, rice, and others. This study presents a comprehensive investigation of their thermal and mechanical properties via differential scanning calorimetry (DSC), thermo gravimetric analysis (TGA), and FT-Raman and FT-IR measurements as well as dynamic mechanic analysis. Within all these measurements, different kinds of structure-property relationships could be derived from these measurements. For example, the proportion of ionic groups enormously influences the self-healing efficiency. The investigation of the self-healing abilities reveals healing efficiencies up to 99% in 2 h at 90 °C for the itaconic acid based ionomer with the lowest ionic content.

Automated Polymer Purification Using Dialysis

The automated dialysis of polymers in synthetic robots is described as a first approach for the purification of polymers using an automated protocol. For this purpose, a dialysis apparatus was installed within a synthesis robot. Therein, the polymer solution could be transferred automatically into the dialysis tube. Afterwards, a permanent running dialysis could be started, enabling the removal of residual monomer. Purification efficiency was studied using chromatography and NMR spectroscopy, showing that the automated dialysis requires less solvent and is faster compared to the classical manual approach.

Fluorescence upconversion by triplet-triplet annihilation in all-organic poly(methacrylate)-terpolymers

Fluorescence upconversion by triplet-triplet annihilation is demonstrated for a fully polymer-integrated material, i.e. in the limit of restricted diffusion. Organic sensitizer and acceptor are covalently attached to a poly(methacrylate) backbone, yielding a metal-free macromolecular all-in-one system for fluorescence upconversion. Due to the spatial confinement of the optically active molecular components, i.e. annihilator and sensitizer, UC by TTA in the constrained polymer system in solution is achieved at exceptionally low averaged annihilator concentrations. However, the UC quantum yield in the investigated systems is found to be low, highlighting that only chromophores in specific local surroundings yield upconversion in the limit of restricted diffusion. A photophysical model is proposed taking the heterogeneous local environment within the polymers into account.

Shape-Memory Metallopolymer Networks Based on a Triazole-Pyridine Ligand

Shape memory polymers represent an interesting class of stimuli-responsive polymers. With their ability to memorize and recover their original shape, they could be useful in almost every area of our daily life. We herein present the synthesis of shape-memory metallopolymers in which the switching unit is designed by using bis(pyridine-triazole) metal complexes. The polymer networks were synthesized via free radical polymerization of methyl-, ethyl- or butyl-methacrylate, tri(ethylene glycol) dimethacrylate and a methacrylate moiety of the triazole-pyridine ligand. By the addition of zinc(II) or cobalt(II) acetate it was possible to achieve metallopolymer networks featuring shape-memory abilities. The successful formation of the metal-ligand complex was proven by Fourier transform infrared (FT-IR) spectroscopy and by 1H NMR spectroscopy. Furthermore, the shape-recovery behavior was studied in detailed fashion and even triple-shape memory behavior could be revealed.

Detailed Analysis of the Influencing Parameters on the Self-Healing Behavior of Dynamic Urea-Crosslinked Poly(methacrylate)s

For this paper, the self-healing ability of poly(methacrylate)s crosslinked via reversible urea bonds was studied in detail. In this context, the effects of healing time and temperature on the healing process were investigated. Furthermore, the impact of the size of the damage (i.e., area of the scratch) was monitored. Aging processes, counteracting the self-healing process, result in a decrease in the mechanical performance. This effect diminishes the healing ability. Consequently, the current study is a first approach towards a detailed analysis of self-healing polymers regarding the influencing parameters of the healing process, considering also possible aging processes for thermo-reversible polymer networks.

Healing through Histidine: Bioinspired Pathways to Self-Healing Polymers via Imidazole⁻Metal Coordination

Biology offers a valuable inspiration toward the development of self-healing engineering composites and polymers. In particular, chemical level design principles extracted from proteinaceous biopolymers, especially the mussel byssus, provide inspiration for design of autonomous and intrinsic healing in synthetic polymers. The mussel byssus is an acellular tissue comprised of extremely tough protein-based fibers, produced by mussels to secure attachment on rocky surfaces. Threads exhibit self-healing response following an apparent plastic yield event, recovering initial material properties in a time-dependent fashion. Recent biochemical analysis of the structure-function relationships defining this response reveal a key role of sacrificial cross-links based on metal coordination bonds between Zn2+ ions and histidine amino acid residues. Inspired by this example, many research groups have developed self-healing polymeric materials based on histidine (imidazole)-metal chemistry. In this review, we provide a detailed overview of the current understanding of the self-healing mechanism in byssal threads, and an overview of the current state of the art in histidine- and imidazole-based synthetic polymers.

Hydrogel-Embedded Model Photocatalytic System Investigated by Raman and IR Spectroscopy Assisted by Density Functional Theory Calculations and Two-Dimensional Correlation Analysis

The presented study reports the synthesis and the vibrational spectroscopic characterization of different matrix-embedded model photocatalysts. The goal of the study is to investigate the interaction of a polymer matrix with photosensitizing dyes and metal complexes for potential future photocatalytic applications. The synthesis focuses on a new rhodamine B derivate and a Pt(II) terpyridine complex, which both contain a polymerizable methacrylate moiety and an acid labile acylhydrazone group. The methacrylate moieties are afterward utilized to synthesize functional model hydrogels mainly consisting of poly(ethylene glycol) methacrylate units. The pH-dependent and temperature-dependent behavior of the hydrogels is investigated by means of Raman and IR spectroscopy assisted by density functional theory calculations and two-dimensional correlation spectroscopy. The spectroscopic results reveal that the Pt(II) terpyridine complex can be released from the polymer matrix by cleaving the C═N bond in an acid environment. The same behavior could not be observed in the case of the rhodamine B dye although it features a comparable C═N bond. The temperature-dependent study shows that the water evaporation has a significant influence neither on the molecular structure of the hydrogel nor on the model photocatalytic moieties.

Do You Get What You See? Understanding Molecular Self-Healing

The self-healing ability of self-healing materials is often analyzed using morphologic microscopy images. Here it was possible to show that morphologic information alone is not sufficient to judge the status of a self-healing process and molecular information is required as well. When comparing molecular coherent anti-Stokes Raman scattering (CARS) and morphological laser reflection images during a standard scratch healing test of an intrinsic self-healing polymer network, it was found that the morphologic closing of the scratch and the molecular crosslinking of the material do not take place simultaneously. This important observation can be explained by the fact that the self-healing process of the thiol-ene based polymer network is limited by the mobility of alkene-containing compounds, which can only be monitored by molecular CARS microscopy and not by standard morphological imaging. Additionally, the recorded CARS images indicate a mechanochemical activation of the self-healing material by the scratching/damaging process, which leads to an enhanced self-healing behavior in the vicinity of the scratch.

A translation of the structure of mussel byssal threads into synthetic materials by the utilization of histidine-rich block copolymers

The self-healing capacities of mussel-inspired metallopolymers based on block copolymers containing histidine are briefly presented.

A healing ionomer crosslinked by a bis-bidentate halogen bond linker: a route to hard and healable coatings

A bis-bidentate halogen bond linker was introduced into a fully organic, phosphate based ionomer, yielding a crosslinked network with healing abilities and improved mechanical properties.

Expression of trkB and trkC receptors and their ligands brain-derived neurotrophic factor and neurotrophin-3 in the murine amygdala

The neurotrophin brain-derived neurotrophic factor (BDNF) and neurotrophin-3 (NT-3) and their cognate receptors, trkB and trkC, have a variety of physiological brain functions, ranging from cell survival to mechanisms involved in learning and memory and long-term potentiation (LTP). LTP can be induced in the cortex and hippocampus, as well as within the amygdala. However, the role of neurotrophins in amygdalar LTP is largely unknown. Expression patterns of BDNF and NT-3 and their cognate receptors in the adult mouse amygdala have not been analyzed in detail. We have therefore examined the expression of trkB, trkC, BDNF, and NT-3 mRNA and protein in different amygdalar nuclei as well as in the hippocampal areas CA1-CA3 and the dentate gyrus. The distribution pattern of trkB, trkC, BDNF, and NT-3 mRNA in the murine hippocampus is comparable to that seen in rats. Within most amygdalar nuclei, a moderate BDNF mRNA expression was found; however, BDNF mRNA was virtually absent from the central nucleus. No expression of NT-3 mRNA was found within the amygdala, but trkC mRNA-expressing cells were widely distributed within this brain region. trkB mRNA was strongly expressed in the amygdala. Because trkB is expressed in a full-length and a truncated form (the latter form is also expressed by nonneuronal cells), we also investigated the distribution of full-length trkB mRNA-expressing cells and could demonstrate that this version of trkB receptors is also widely expressed in the amygdala. These results can serve as a basis for studies elucidating the physiological roles of these receptors in the amygdala.