Charge Transfer Dynamics in Organic-Inorganic Hybrid Heterostructures-Insights by Vibrational-Sum Frequency Generation Spectroscopy

Organic-inorganic heterostructures play a pivotal role in modern electronic and optoelectronic applications including photodetectors and field effect transistors, as well as in solar energy conversion such as photoelectrodes of dye-sensitized solar cells, photoelectrochemical cells, and in organic photovoltaics. To a large extent, performance of such devices is controlled by charge transfer dynamics at and across (inner) interfaces, e.g., between a wide band gap semiconductor and molecular sensitizers and/or catalysts. Hence, a detailed understanding of the structure-dynamics-function relationship of such functional interfaces is necessary to rationalize possible performance limitations of these materials and devices on a molecular level. Vibrational sum-frequency generation (VSFG) spectroscopy, as an interface-sensitive spectroscopic technique, allows to obtain chemically specific information from interfaces and combines such chemical insights with ultrafast time resolution, when integrated as a spectroscopic probe into a pump-probe scheme. Thus, this minireview discusses the advantages and potential of VSFG spectroscopy for investigating interfacial charge transfer dynamics and structural changes at inner interfaces. A critical perspective of the unique spectroscopic view of otherwise inaccessible interfaces is presented, which we hope opens new opportunities for an improved understanding of function-determining processes in complex materials, and brings together communities who are devoted to designing materials and devices with spectroscopists.

"TiC-TUG": technology in clinical practice using the instrumented timed up and go test-a scoping review

Digitized assessments have a considerable potential to guide clinicial decision making and monitor progress and disease trajectories. The Timed Up and Go test (TUG) has been long established for assessment in geriatric medicine and instrumented versions (iTUG) have been developed and validated. This scoping review includes studies that applied the iTUG and aims to identify use cases to show where and how iTUG assessment could guide interventions and clinical management. The literature search was limited to peer-reviewed studies that performed pre- and post-intervention measurements with a 3-meter TUG instrumented with body-worn technology in samples of at least 20 subjects aged 60+ years. Of 3018 identified articles 20 were included. Four clinical use cases were identified: stratification for subsequent therapy, monitoring of disease or treatment-associated changes and evaluation of interventions in patients with idiopathic normal pressure hydrocephalus (1), and patients with Parkinson's disease (2); monitoring after joint replacement surgery (3), and evaluation after different exercise and rehabilitation interventions (4). The included studies show diversity in terms of iTUG technology and procedures. The identified use cases highlight clinical relevance and high potential for the clinical application of the iTUG. A consensual approach as well as comprehensive reporting would help to further exploit the potential of the iTUG to support clinical management. Future studies should investigate the benefits of segmental iTUG analysis, responsiveness and participants' perspectives on clinically meaningful changes in iTUG.

Efficacy and safety of the implantation of a single-piece angulated foldable IOL in the sulcus

PURPOSE

To study the visual results and tolerance of a Zeiss CT Lucia 601P intraocular lens (IOL) implanted in the sulcus after complicated cataract surgery or during IOL exchange for clouded IOL.

METHODS

In total, 64 patients who underwent sulcus implantation were recalled to the hospital to undergo subjective and objective refraction, best corrected visual acuity measurement, tonometry, optical coherence tomography, laser flare photometry, biometry, and wavefront aberrometry.

RESULTS

In spite of a large variation in preoperative refraction, the target refraction was obtained within 1.5 diopters in approximately 97% of patients and within 0.5 diopter in 53% of patients. Average BCVA was high (Snellen 0.86) and related to concomitant (mostly retinal) pathologies in eyes with poorer visual performance. Wavefront aberrometry showed no evidence of IOL tilting or decentration after long-term implantation in the sulcus. Tonometry was not different from the fellow eye of the patient (p > 0.5). In 53 patients with bilateral pseudophakia, the laser flare photometry was not significantly different from the fellow eye (p < 0.05).

CONCLUSION

This study demonstrates that this single-piece angulated foldable acrylic IOL can be considered for implantation in the sulcus. The visual results are favorable, and the IOL can be well-positioned and tolerated in the sulcus. Moreover, there were no safety issues found since there was no evidence of elevated IOP or chronic uveitis.

Blooming and pruning: learning from mistakes with memristive synapses

Blooming and pruning is one of the most important developmental mechanisms of the biological brain in the first years of life, enabling it to adapt its network structure to the demands of the environment. The mechanism is thought to be fundamental for the development of cognitive skills. Inspired by this, Chialvo and Bak proposed in 1999 a learning scheme that learns from mistakes by eliminating from the initial surplus of synaptic connections those that lead to an undesirable outcome. Here, this idea is implemented in a neuromorphic circuit scheme using CMOS integrated HfO2-based memristive devices. The implemented two-layer neural network learns in a self-organized manner without positive reinforcement and exploits the inherent variability of the memristive devices. This approach provides hardware, local, and energy-efficient learning. A combined experimental and simulation-based parameter study is presented to find the relevant system and device parameters leading to a compact and robust memristive neuromorphic circuit that can handle association tasks.

Age- and sex-related differences in trunk kinematics during walking in able-bodied adults

INTRODUCTION

Trunk motion during walking acts as a biomarker for decreased mobility and can differ between sexes. Knowing how age and sex affect trunk motion and energy conservation can help clinicians decide when and in whom to intervene with physiotherapy to prolong functional mobility.

METHODS

A large sample of 138 able-bodied males and females in the age-categories 20-39 years, 40-59 years, 60-69 years, 70-79 years, and 80-89 years received a full-body 3D gait analysis. A two-factor ANOVA was performed to examine the effect of age and sex and their interaction on 3D trunk kinematics and positive mechanical work of the lower limbs, head-arms-trunk (HAT) segment and whole body.

RESULTS

A significant decrease in walking speed was only found in those above 80 years (~ .05 nm/s, p < .006), while changes in 3D trunk kinematics were observed earlier. From 60 years on, trunk rotations decreased (~ 2-3°, p < .05), from 70-year frontal pelvic motion (~ 4°, p < .001), and from the age of 80 years sagittal thorax motion (~ 1-6°, p < .05). There were only small aging effects for mechanical energy demands that were more pronounced in females, showing decreased of HAT contributions (p = .020). Furthermore, age-related differences in trunk kinematics are highly dependent on sex whereby age-related changes were observed sooner in females than males in all three planes of motion.

CONCLUSIONS

Age-related differences in 3D trunk kinematics are observed from 60 years onward and increase with age. Age-related stiffening of the trunk did not seem to affect the body's total mechanical work. Importantly, our data did show a stark contrast between males and females, indicating that training to prolong mobility should be tailored to sex. Future research should include sex-matched data when examining normal age and pathologic gait decline.

Automated nuclear magnetic resonance fingerprinting of mixtures

Nuclear magnetic resonance (NMR) spectroscopy is a powerful tool for qualitative and quantitative analysis. However, for complex mixtures, determining the speciation from NMR spectra can be tedious and sometimes even unfeasible. On the other hand, identifying and quantifying structural groups in a mixture from NMR spectra is much easier than doing the same for components. We call this group-based approach "NMR fingerprinting." In this work, we show that NMR fingerprinting can even be performed in an automated way, without expert knowledge, based only on standard NMR spectra, namely, 13C, 1H, and 13C DEPT NMR spectra. Our approach is based on the machine-learning method of support vector classification (SVC), which was trained here on thousands of labeled pure-component NMR spectra from open-source data banks. We demonstrate the applicability of the automated NMR fingerprinting using test mixtures, of which spectra were taken using a simple benchtop NMR spectrometer. The results from the NMR fingerprinting agree remarkably well with the ground truth, which was known from the gravimetric preparation of the samples. To facilitate the application of the method, we provide an interactive website (https://nmr-fingerprinting.de), where spectral information can be uploaded and which returns the NMR fingerprint. The NMR fingerprinting can be used in many ways, for example, for process monitoring or thermodynamic modeling using group-contribution methods-or simply as a first step in species analysis.

A paradigm shift?-On the ethics of medical large language models

After a wave of breakthroughs in image-based medical diagnostics and risk prediction models, machine learning (ML) has turned into a normal science. However, prominent researchers are claiming that another paradigm shift in medical ML is imminent-due to most recent staggering successes of large language models-from single-purpose applications toward generalist models, driven by natural language. This article investigates the implications of this paradigm shift for the ethical debate. Focusing on issues like trust, transparency, threats of patient autonomy, responsibility issues in the collaboration of clinicians and ML models, fairness, and privacy, it will be argued that the main problems will be continuous with the current debate. However, due to functioning of large language models, the complexity of all these problems increases. In addition, the article discusses some profound challenges for the clinical evaluation of large language models and threats to the reproducibility and replicability of studies about large language models in medicine due to corporate interests.

Unraveling Eumelanin Radical Formation by Nanodiamond Optical Relaxometry in a Living Cell

Defect centers in a nanodiamond (ND) allow the detection of tiny magnetic fields in their direct surroundings, rendering them as an emerging tool for nanoscale sensing applications. Eumelanin, an abundant pigment, plays an important role in biology and material science. Here, for the first time, we evaluate the comproportionation reaction in eumelanin by detecting and quantifying semiquinone radicals through the nitrogen-vacancy color center. A thin layer of eumelanin is polymerized on the surface of nanodiamonds (NDs), and depending on the environmental conditions, such as the local pH value, near-infrared, and ultraviolet light irradiation, the radicals form and react in situ. By combining experiments and theoretical simulations, we quantify the local number and kinetics of free radicals in the eumelanin layer. Next, the ND sensor enters the cells via endosomal vesicles. We quantify the number of radicals formed within the eumelanin layer in these acidic compartments by applying optical relaxometry measurements. In the future, we believe that the ND quantum sensor could provide valuable insights into the chemistry of eumelanin, which could contribute to the understanding and treatment of eumelanin- and melanin-related diseases.

Closed-Loop Recyclable and Nonpersistent Polyethylene-like Polyesters

ConspectusAliphatic polyesters based on long-chain monomers were synthesized for the first time almost a century ago. In fact, Carothers' seminal observations that founded the entire field of synthetic polymer fibers were made on such a polyester sample. However, as materials, they have evolved only over the past decade. This is driven by the corresponding monomers becoming practically available from advanced catalytic conversions of plant oils, and future prospects comprise a possible generation from third-generation feedstocks, such as microalgae or waste. Long-chain polyesters such as polyester-18.18 can be considered to be polyethylene chains with a low density of potential breakpoints in the chain. These do not compromise the crystalline structure or the material properties, which resemble linear high-density polyethylene (HDPE), and the materials can also be melt processed by injection molding, film or fiber extrusion, and filament deposition in additive manufacturing. At the same time, they enable closed-loop chemical recycling via solvolysis, which is also possible in mixed waste streams containing polyolefins and even poly(ethylene terephthalate). Recovered monomers possess a quality that enables the generation of recycled polyesters with properties on par with those of the virgin material. The (bio)degradability varies enormously with the constituent monomers. Polyesters based on short-chain diols and long-chain dicarboxylates fully mineralize under industrial composting conditions, despite their HDPE-like crystallinity and hydrophobicity. Fundamental studies of the morphology and thermal behavior of these polymers revealed the location of the in-chain groups and their peculiar role in structure formation during crystallization as well as during melting. All of the concepts outlined were extended to, and elaborated on further, by analogous long-chain aliphatic polymers with other in-chain groups such as carbonates and acetals. The title materials are a potential solution for much needed circular closed-loop recyclable plastics that also as a backstop if lost to the environment will not be persistent for many decades.

Wetting Behavior of Inkjet-Printed Electronic Inks on Patterned Substrates

In inkjet printing technology, one important factor influencing the printing quality and reliability of printed films is the interaction of the jetted ink with the substrate surface. This short-range interaction determines the wettability and the adhesion of the ink to the solid surface and is hence responsible for the final shape of the deposited ink. Here, we investigate wetting morphologies of inkjet-printed inks on patterned substrates by carefully designed experimental test structures and simulations. The contact angles, the surface properties, and drop shapes, as well as their influence on the device variability, are experimentally and theoretically analyzed. For the simulations, we employ the phase-field method, which is based on the free energy minimization of the two-phase system with the given wetting boundary conditions. Through a systematic investigation of printed drops on patterned substrates consisting of hydrophilic and hydrophobic areas, we report that the printed morphology is related not only to the designed layout and the drop volume but also to the printing strategy and the wettability. Furthermore, we show how one can modify the intrinsic wettability of the patterned substrates to enhance the printing quality and reliability. Based on the present findings, we cast light on the improvement of the fabrication quality of thin film transistors.

BrainAGE: Revisited and reframed machine learning workflow

Since the introduction of the BrainAGE method, novel machine learning methods for brain age prediction have continued to emerge. The idea of estimating the chronological age from magnetic resonance images proved to be an interesting field of research due to the relative simplicity of its interpretation and its potential use as a biomarker of brain health. We revised our previous BrainAGE approach, originally utilising relevance vector regression (RVR), and substituted it with Gaussian process regression (GPR), which enables more stable processing of larger datasets, such as the UK Biobank (UKB). In addition, we extended the global BrainAGE approach to regional BrainAGE, providing spatially specific scores for five brain lobes per hemisphere. We tested the performance of the new algorithms under several different conditions and investigated their validity on the ADNI and schizophrenia samples, as well as on a synthetic dataset of neocortical thinning. The results show an improved performance of the reframed global model on the UKB sample with a mean absolute error (MAE) of less than 2 years and a significant difference in BrainAGE between healthy participants and patients with Alzheimer's disease and schizophrenia. Moreover, the workings of the algorithm show meaningful effects for a simulated neocortical atrophy dataset. The regional BrainAGE model performed well on two clinical samples, showing disease-specific patterns for different levels of impairment. The results demonstrate that the new improved algorithms provide reliable and valid brain age estimations.

Two-Color Spatially Resolved Tuning of Polymer-Coated Metasurfaces

For the realization of truly reconfigurable metasurface technologies, dynamic spatial tuning of the metasurface resonance is required. Here we report the use of organic photoswitches as a means for the light-induced spatial tuning of metasurface resonances. Coating of a dielectric metasurface, hosting high-quality-factor resonances, with a spiropyran (SPA)-containing polymer enabled dynamic resonance tuning up to 4 times the resonance full-width at half-maximum with arbitrary spatial precision. A major benefit of employing photoswitches is the broad toolbox of chromophores available and the unique optical properties of each. In particular, SPA and azobenzene (AZO) photoswitches can both be switched with UV light but exhibit opposite refractive index changes. When applied to the metasurface, SPA induced a red shift in the metasurface resonance with a figure of merit of 97 RIU-1, while AZO caused a blue shift in the resonance with an even greater sensitivity of 100 RIU-1. Critically, SPA and AZO can be individually recovered with red and blue light, respectively. To exploit this advantage, we coated a dielectric metasurface with spatially offset SPA- and AZO-containing polymers to demonstrate wavelength-dependent, spatially resolved control over the metasurface resonance tuning.

A Multi-Scale Approach to Simulate the Nonlinear Optical Response of Molecular Nanomaterials

Nonlinear optics is essential for many recent photonic technologies. Here, a novel multi-scale approach is introduced to simulate the nonlinear optical response of molecular nanomaterials combining ab initio quantum-chemical and classical Maxwell-scattering computations. In this approach, the first hyperpolarizability tensor is computed with time-dependent density-functional theory and incorporated into a multi-scattering formalism that considers the optical interaction between neighboring molecules. Such incorporation is achieved by a novel object: the Hyper-Transition(T)-matrix. With this object at hand, the nonlinear optical response from single molecules and also from entire photonic devices can be computed, including the full tensorial and dispersive nature of the optical response of the molecules, as well as the optical interaction between different molecules as, for example, in the lattice of a molecular crystal. To demonstrate the applicability of the novel approach, the generation of a second-harmonic signal from a thin film of an Urea molecular crystal is computed and compared to more traditional simulations. Furthermore, an optical cavity is designed, which enhances the second-harmonic response of the molecular film up to more than two orders of magnitude. This approach is highly versatile and accurate and can be the working horse for the future exploration of nonlinear photonic molecular materials in structured photonic environments.

Spontaneous Modulation Doping in Semi-Crystalline Conjugated Polymers Leads to High Conductivity at Low Doping Concentration

The possibility to control the charge carrier density through doping is one of the defining properties of semiconductors. For organic semiconductors, the doping process is known to come with several problems associated with the dopant compromising the charge carrier mobility by deteriorating the host morphology and/or introducing Coulomb traps. While for inorganic semiconductors these factors can be mitigated through (top-down) modulation doping, this concept has not been employed in organics. Here, this work shows that properly chosen host/dopant combinations can give rise to spontaneous, bottom-up modulation doping, in which the dopants preferentially sit in an amorphous phase, while the actual charge transport occurs predominantly in a crystalline phase with an unaltered microstructure, spatially separating dopants and mobile charges. Combining experiments and numerical simulations, this work shows that this leads to exceptionally high conductivities at relatively low dopant concentrations.

Intrinsic Dynamics of Amorphous Ice Revealed by a Heterodyne Signal in X-ray Photon Correlation Spectroscopy Experiments

Unraveling the mechanism of water's glass transition and the interconnection between amorphous ices and liquid water plays an important role in our overall understanding of water. X-ray photon correlation spectroscopy (XPCS) experiments were conducted to study the dynamics and the complex interplay between the hypothesized glass transition in high-density amorphous ice (HDA) and the subsequent transition to low-density amorphous ice (LDA). Our XPCS experiments demonstrate that a heterodyne signal appears in the correlation function. Such a signal is known to originate from the interplay of a static component and a dynamic component. Quantitative analysis was performed on this heterodyne signal to extract the intrinsic dynamics of amorphous ice during the HDA-LDA transition. An angular dependence indicates non-isotropic, heterogeneous dynamics in the sample. Using the Stokes-Einstein relation to extract diffusion coefficients, the data are consistent with the scenario of static LDA islands floating within a diffusive matrix of high-density liquid water.

"If this is what it means to be old…": a mixed methods study on the effects of age simulation on views on aging and perceptions of age-related impairments

Age simulation suits are a promising tool to increase empathy and to promote positive attitudes toward older adults. However, studies have largely focused on (young) healthcare professionals, are probably biased by social desirability, and have not addressed participants' views of the aging process triggered by the simulation. The current work combines two studies addressing effects of aging suits on both general and personal views on aging among heterogeneous samples, and exploring spontaneous associations during the simulation. In study 1, N = 165 adults (M = 37.1 years, SD = 15.4, range 18-74 years) answered questionnaires containing general views regarding older adults ("old people are…") as well as personal perceptions ("aging means to me…") before and after wearing an aging suit. In study 2, young adults (N = 22; M = 24.8 years, SD = 4.3, range 20-38 years) and middle-aged adults (N = 41; M = 60.8 years, SD = 6.9, range 40-75 years) carried out established geriatric assessments with and without aging suit, and spontaneous impressions on the instant aging experience were recorded. Findings indicated negative shifts in both general and personal views on aging measures in both age groups (d = .30 to d = .44). Analyses of qualitative data resulted in seven main themes, e.g., "strain/coordination", "future me", "empathy/insight". Group comparisons revealed higher frequencies of future-self related thoughts among middle-aged adults, whereas younger adults mentioned predominantly physical effects of the suit. In conclusion, applying age simulation suits might evoke unintended negative views on aging. In comparison with young adults, middle-aged adults showed broader reflections including thoughts related to emotions, future-self, and potential struggles of older people.

Neuromorphic Computing via Fission-based Broadband Frequency Generation

The performance limitations of traditional computer architectures have led to the rise of brain-inspired hardware, with optical solutions gaining popularity due to the energy efficiency, high speed, and scalability of linear operations. However, the use of optics to emulate the synaptic activity of neurons has remained a challenge since the integration of nonlinear nodes is power-hungry and, thus, hard to scale. Neuromorphic wave computing offers a new paradigm for energy-efficient information processing, building upon transient and passively nonlinear interactions between optical modes in a waveguide. Here, an implementation of this concept is presented using broadband frequency conversion by coherent higher-order soliton fission in a single-mode fiber. It is shown that phase encoding on femtosecond pulses at the input, alongside frequency selection and weighting at the system output, makes transient spectro-temporal system states interpretable and allows for the energy-efficient emulation of various digital neural networks. The experiments in a compact, fully fiber-integrated setup substantiate an anticipated enhancement in computational performance with increasing system nonlinearity. The findings suggest that broadband frequency generation, accessible on-chip and in-fiber with off-the-shelf components, may challenge the traditional approach to node-based brain-inspired hardware design, ultimately leading to energy-efficient, scalable, and dependable computing with minimal optical hardware requirements.

T helper cell subsets: diversification of the field

Polarized T helper cell (Th cell) responses are important determinants of host protection. Th cell subsets tailor their functional repertoire of cytokines to their cognate antigens to efficiently contribute to their clearance. In contrast, in settings of immune abrogation, these polarized cytokine patterns of Th cells can mediate tissue damage and pathology resulting in allergy or autoimmunity. Recent technological developments in single-cell genomics and proteomics as well as advances in the high-dimensional bioinformatic analysis of complex datasets have challenged the prevailing Th cell subset classification into Th1, Th2, Th17, and other subsets. Additionally, systems immunology approaches have revealed that instructive input from the peripheral tissue microenvironment can have differential effects on the overall phenotype and molecular wiring of Th cells depending on their spatial distribution. Th cells from the blood or secondary lymphoid organs are therefore expected to follow distinct rules of regulation. In this review, the functional heterogeneity of Th cell subsets will be reviewed in the context of new technological developments and T-cell compartmentalization in tissue niches. This work will especially focus on challenges to the traditional boundaries of Th cell subsets and will discuss the underlying regulatory checkpoints, which could reveal new therapeutic strategies for various immune-mediated diseases.

The rediscovery of the putative ant social parasite Manica parasitica syn. nov. (Hymenoptera: Formicidae) reveals an unexpected endoparasite syndrome

Parasitism is ubiquitous across the tree of life, and parasites comprise approximately half of all animal species. Social insect colonies attract many pathogens, endo- and ectoparasites, and are exploited by social parasites, which usurp the social environment of their hosts for survival and reproduction. Exploitation by parasites and pathogens versus social parasites may cause similar behavioural and morphological modifications of the host. Ants possess two overlapping syndromes: the endo- and social parasite syndromes. We rediscovered two populations of the putative social parasite Manica parasitica in the Sierra Nevada, and tested the hypothesis that M. parasitica is an independently evolving social parasite. We evaluated traits used to discriminate M. parasitica from its host Manica bradleyi, and examined the morphology of M. parasitica in the context of ant parasitic syndromes. We find that M. parasitica is not a social parasite. Instead, M. parasitica represents cestode-infected M. bradleyi. We propose that M. parasitica should be regarded as a junior synonym of M. bradleyi. Our results emphasize that an integrative approach is essential for unravelling the complex life histories of social insects and their symbionts.

Structural insights into hybrid immiscible blends of metal-organic framework and sodium ultraphosphate glasses

Recently, increased attention has been focused on amorphous metal-organic frameworks (MOFs) and, more specifically, MOF glasses, the first new glass category discovered since the 1970s. In this work, we explore the fabrication of a compositional series of hybrid blends, the first example of blending a MOF and inorganic glass. We combine ZIF-62(Zn) glass and an inorganic glass, 30Na2O-70P2O5, to combine the chemical versatility of the MOF glass with the mechanical properties of the inorganic glass. We investigate the interfacial interactions between the two components using pair distribution function analysis and solid state NMR spectroscopy, and suggest potential interactions between the two phases. Thermal analysis of the blend samples indicated that they were less thermally stable than the starting materials and had a Tg shifted relative to the pristine materials. Annular dark field scanning transmission electron microscopy tomography, X-ray energy dispersive spectroscopy (EDS), nanoindentation and 31P NMR all indicated close mixing of the two phases, suggesting the formation of immiscible blends.

Interfacial Bonding between a Crystalline Metal-Organic Framework and an Inorganic Glass

The interface within a composite is critically important for the chemical and physical properties of these materials. However, experimental structural studies of the interfacial regions within metal-organic framework (MOF) composites are extremely challenging. Here, we provide the first example of a new MOF composite family, i.e., using an inorganic glass matrix host in place of the commonly used organic polymers. Crucially, we also decipher atom-atom interactions at the interface. In particular, we dispersed a zeolitic imidazolate framework (ZIF-8) within a phosphate glass matrix and identified interactions at the interface using several different analysis methods of pair distribution function and multinuclear multidimensional magic angle spinning nuclear magnetic resonance spectroscopy. These demonstrated glass-ZIF atom-atom correlations. Additionally, carbon dioxide uptake and stability tests were also performed to check the increment of the surface area and the stability and durability of the material in different media. This opens up possibilities for creating new composites that include the intrinsic chemical properties of the constituent MOFs and inorganic glasses.

TURBOMOLE: Today and Tomorrow

TURBOMOLE is a highly optimized software suite for large-scale quantum-chemical and materials science simulations of molecules, clusters, extended systems, and periodic solids. TURBOMOLE uses Gaussian basis sets and has been designed with robust and fast quantum-chemical applications in mind, ranging from homogeneous and heterogeneous catalysis to inorganic and organic chemistry and various types of spectroscopy, light-matter interactions, and biochemistry. This Perspective briefly surveys TURBOMOLE's functionality and highlights recent developments that have taken place between 2020 and 2023, comprising new electronic structure methods for molecules and solids, previously unavailable molecular properties, embedding, and molecular dynamics approaches. Select features under development are reviewed to illustrate the continuous growth of the program suite, including nuclear electronic orbital methods, Hartree-Fock-based adiabatic connection models, simplified time-dependent density functional theory, relativistic effects and magnetic properties, and multiscale modeling of optical properties.

Understanding the Optical Properties of Doped and Undoped 9-Armchair Graphene Nanoribbons in Dispersion

Graphene nanoribbons are one-dimensional stripes of graphene with width- and edge-structure-dependent electronic properties. They can be synthesized bottom-up in solution to obtain precise ribbon geometries. Here we investigate the optical properties of solution-synthesized 9-armchair graphene nanoribbons (9-aGNRs) that are stabilized as dispersions in organic solvents and further fractionated by liquid cascade centrifugation (LCC). Absorption and photoluminescence spectroscopy reveal two near-infrared absorption and emission peaks whose ratios depend on the LCC fraction. Low-temperature single-nanoribbon photoluminescence spectra suggest the presence of two different nanoribbon species. Based on density functional theory (DFT) and time-dependent DFT calculations, the lowest energy transition can be assigned to pristine 9-aGNRs, while 9-aGNRs with edge-defects, caused by incomplete graphitization, result in more blue-shifted transitions and higher Raman D/G-mode ratios. Hole doping of 9-aGNR dispersions with the electron acceptor F4TCNQ leads to concentration dependent bleaching and quenching of the main absorption and emission bands and the appearance of red-shifted, charge-induced absorption features but no additional emission peaks, thus indicating the formation of polarons instead of the predicted trions (charged excitons) in doped 9-aGNRs.

De novo genome assembly resolving repetitive structures enables genomic analysis of 35 European Mycoplasmopsis bovis strains

Mycoplasmopsis (M.) bovis, the agent of mastitis, pneumonia, and arthritis in cattle, harbors a small genome of approximately 1 Mbp. Combining data from Illumina and Nanopore technologies, we sequenced and assembled the genomes of 35 European strains and isolate DL422_88 from Cuba. While the high proportion of repetitive structures in M. bovis genomes represent a particular challenge, implementation of our own pipeline Mycovista (available on GitHub www.github.com/sandraTriebel/mycovista ) in a hybrid approach enabled contiguous assembly of the genomes and, consequently, improved annotation rates considerably. To put our European strain panel in a global context, we analyzed the new genome sequences together with 175 genome assemblies from public databases. Construction of a phylogenetic tree based on core genes of these 219 strains revealed a clustering pattern according to geographical origin, with European isolates positioned on clades 4 and 5. Genomic data allowing assignment of strains to tissue specificity or certain disease manifestations could not be identified. Seven strains isolated from cattle with systemic circular condition (SCC), still a largely unknown manifestation of M. bovis disease, were located on both clades 4 and 5. Pairwise association analysis revealed 108 genomic elements associated with a particular clade of the phylogenetic tree. Further analyzing these hits, 25 genes are functionally annotated and could be linked to a M. bovis protein, e.g. various proteases and nucleases, as well as ten variable surface lipoproteins (Vsps) and other surface proteins. These clade-specific genes could serve as useful markers in epidemiological and clinical surveys.

Cooperative Network Formation via Two-Colour Light-Activated λ-Orthogonal Chromophores

Independently addressing photoreactive sites within one molecule with two colours of light is a formidable challenge. Here, we combine two sequence independent λ-orthogonal chromophores in one heterotelechelic dilinker molecule, to exploit their disparate reactivity utilizing the same reaction partner, a maleimide-containing polymer. We demonstrate that polymer network formation only proceeds if two colours of light are employed. Upon single colour irradiation, linker-decorated post-functionalized polymers are generated at either wavelength and in either sequence. Network formation, however, is only achieved by sequential or simultaneous two colour irradiation. The herein introduced photoreactive system demonstrates the power of wavelength orthogonal chemistry in macromolecular synthesis.

MetaTransformer: deep metagenomic sequencing read classification using self-attention models

Deep learning has emerged as a paradigm that revolutionizes numerous domains of scientific research. Transformers have been utilized in language modeling outperforming previous approaches. Therefore, the utilization of deep learning as a tool for analyzing the genomic sequences is promising, yielding convincing results in fields such as motif identification and variant calling. DeepMicrobes, a machine learning-based classifier, has recently been introduced for taxonomic prediction at species and genus level. However, it relies on complex models based on bidirectional long short-term memory cells resulting in slow runtimes and excessive memory requirements, hampering its effective usability. We present MetaTransformer, a self-attention-based deep learning metagenomic analysis tool. Our transformer-encoder-based models enable efficient parallelization while outperforming DeepMicrobes in terms of species and genus classification abilities. Furthermore, we investigate approaches to reduce memory consumption and boost performance using different embedding schemes. As a result, we are able to achieve 2× to 5× speedup for inference compared to DeepMicrobes while keeping a significantly smaller memory footprint. MetaTransformer can be trained in 9 hours for genus and 16 hours for species prediction. Our results demonstrate performance improvements due to self-attention models and the impact of embedding schemes in deep learning on metagenomic sequencing data.

4D Printed Shape-Memory Elastomer for Thermally Programmable Soft Actuators

Polymeric shape-memory elastomers can recover to a permeant shape from any programmed deformation under external stimuli. They are mostly cross-linked polymeric materials and can be shaped by three-dimensional (3D) printing. However, 3D printed shape-memory polymers so far only exhibit elasticity above their transition temperature, which results in their programmed shape being inelastic or brittle at lower temperatures. To date, 3D printed shape-memory elastomers with elasticity both below and above their transition temperature remain an elusive goal, which limits the application of shape-memory materials as elastic materials at low temperatures. In this paper, we printed, for the first time, a custom-developed shape-memory elastomer based on polyethylene glycol using digital light processing, which possesses elasticity and stretchability in a wide temperature range, below and above the transition temperature. Young's modulus in these two states can vary significantly, with a difference of up to 2 orders of magnitude. This marked difference in Young's modulus imparts excellent shape-memory properties to the material. The difference in Young's modulus at different temperatures allows for the programming of the pneumatic actuators by heating and softening specific areas. Consequently, a single actuator can exhibit distinct movement modes based on the programming process it undergoes.

Combining molecular dynamics simulations and scoring method to computationally model ubiquitylated linker histones in chromatosomes

The chromatin in eukaryotic cells plays a fundamental role in all processes during a cell's life cycle. This nucleoprotein is normally tightly packed but needs to be unpacked for expression and division. The linker histones are critical for such packaging processes and while most experimental and simulation works recognize their crucial importance, the focus is nearly always set on the nucleosome as the basic chromatin building block. Linker histones can undergo several modifications, but only few studies on their ubiquitylation have been conducted. Mono-ubiquitylated linker histones (HUb), while poorly understood, are expected to influence DNA compaction. The size of ubiquitin and the globular domain of the linker histone are comparable and one would expect an increased disorder upon ubiquitylation of the linker histone. However, the formation of higher order chromatin is not hindered and ubiquitylation of the linker histone may even promote gene expression. Structural data on chromatosomes is rare and HUb has never been modeled in a chromatosome so far. Descriptions of the chromatin complex with HUb would greatly benefit from computational structural data. In this study we generate molecular dynamics simulation data for six differently linked HUb variants with the help of a sampling scheme tailored to drive the exploration of phase space. We identify conformational sub-states of the six HUb variants using the sketch-map algorithm for dimensionality reduction and iterative HDBSCAN for clustering on the excessively sampled, shallow free energy landscapes. We present a highly efficient geometric scoring method to identify sub-states of HUb that fit into the nucleosome. We predict HUb conformations inside a nucleosome using on-dyad and off-dyad chromatosome structures as reference and show that unbiased simulations of HUb produce significantly more fitting than non-fitting HUb conformations. A tetranucleosome array is used to show that ubiquitylation can even occur in chromatin without too much steric clashes.

G × E interactions as a basis for toxicological uncertainty

To transfer toxicological findings from model systems, e.g. animals, to humans, standardized safety factors are applied to account for intra-species and inter-species variabilities. An alternative approach would be to measure and model the actual compound-specific uncertainties. This biological concept assumes that all observed toxicities depend not only on the exposure situation (environment = E), but also on the genetic (G) background of the model (G × E). As a quantitative discipline, toxicology needs to move beyond merely qualitative G × E concepts. Research programs are required that determine the major biological variabilities affecting toxicity and categorize their relative weights and contributions. In a complementary approach, detailed case studies need to explore the role of genetic backgrounds in the adverse effects of defined chemicals. In addition, current understanding of the selection and propagation of adverse outcome pathways (AOP) in different biological environments is very limited. To improve understanding, a particular focus is required on modulatory and counter-regulatory steps. For quantitative approaches to address uncertainties, the concept of "genetic" influence needs a more precise definition. What is usually meant by this term in the context of G × E are the protein functions encoded by the genes. Besides the gene sequence, the regulation of the gene expression and function should also be accounted for. The widened concept of past and present "gene expression" influences is summarized here as Ge. Also, the concept of "environment" needs some re-consideration in situations where exposure timing (Et) is pivotal: prolonged or repeated exposure to the insult (chemical, physical, life style) affects Ge. This implies that it changes the model system. The interaction of Ge with Et might be denoted as Ge × Et. We provide here general explanations and specific examples for this concept and show how it could be applied in the context of New Approach Methodologies (NAM).

Are nursing home employees ready for the technical evolution? German-wide survey on the status quo of affinity for technology and technology interaction

Background

Technological devices can support nursing home employees; however, their perspective is not sufficiently studied. Our aims were thus to (a) examine affinity for technology and technology interaction and related sociodemographic confounders, as well as (b) detect possible requirements and boundary conditions relevant for the development and implementation of assistive technologies among nursing home employees.

Methods

We conducted an online survey between May and July of 2022 among 200 nursing home employees in Germany. The survey included two questionnaires, that is, Affinity for Technology Interaction (ATI) and Affinity for Technology-Electronic Devices (TA-EG; subscales TA-EG-Enthusiasm, TA-EG-Competence, TA-EG-Positive Consequences, and TA-EG-Negative Consequences), as well as sociodemographic variables, that is, age, gender, professional groups, education/graduation level. We carried out factorial variance and multiple regression analyses.

Results

There were differences between age groups in ATI (lower score with increasing age) and between gender, age, and professional group in TA-EG (lower score for females, participants with higher ages, and nursing home managers). Predictors of ATI were age and professional group, predictors of TA-EG, TA-EG-Enthusiasm, and TA-EG-Competence were gender, age, and professional group. Predictors of TA-EG-Positive Consequences were education and professional group.

Conclusions

We observed rather high affinity for technology and technology interaction values overall, and particularly for nursing home employees compared to managers. Significant predictors for technology affinity and interaction may have important implications, for example the perspectives of nursing home employees and managers should be considered separately in the technological design, development, and implementation process. Furthermore, an open dialogue between all stakeholders should be encouraged to increase the probability of actual technology use.

Digital media in intergenerational communication: Status quo and future scenarios for the grandparent-grandchild relationship

Communication technologies play an important role in maintaining the grandparent-grandchild (GP-GC) relationship. Based on Media Richness Theory, this study investigates the frequency of use (RQ1) and perceived quality (RQ2) of established media as well as the potential use of selected innovative media (RQ3) in GP-GC relationships with a particular focus on digital media. A cross-sectional online survey and vignette experiment were conducted in February 2021 among N = 286 university students in Germany (mean age 23 years, 57% female) who reported on the direct and mediated communication with their grandparents. In addition to face-to-face interactions, non-digital and digital established media (such as telephone, texting, video conferencing) and innovative digital media, namely augmented reality (AR)-based and social robot-based communication technologies, were covered. Face-to-face and phone communication occurred most frequently in GP-GC relationships: 85% of participants reported them taking place at least a few times per year (RQ1). Non-digital established media were associated with higher perceived communication quality than digital established media (RQ2). Innovative digital media received less favorable quality evaluations than established media. Participants expressed doubts regarding the technology competence of their grandparents, but still met innovative media with high expectations regarding improved communication quality (RQ3). Richer media, such as video conferencing or AR, do not automatically lead to better perceived communication quality, while leaner media, such as letters or text messages, can provide rich communication experiences. More research is needed to fully understand and systematically improve the utility, usability, and joy of use of different digital communication technologies employed in GP-GC relationships.

Substrate-Independent Maskless Writing of Functionalized Microstructures Using CHic Chemistry and Digital Light Processing

Maskless photolithography based on digital light processing (DLP) is an attractive technique for the rapid, flexible, and cost-effective fabrication of complex structures with arbitrary surface profiles on the microscale. In this work, we introduce a new material system for structure formation by DLP that is based on photoreactive polymers for the local and light-induced C,H-insertion cross-linking (CHic). This approach allows a simple and versatile generation of microstructures with a broad spectrum of geometries and chemistries irrespective of the nature of the chosen substrates and thus allows direct writing of surface functionalization patterns with high spatial control. The CHicable prepolymer is first coated on a substrate to form a solvent-free (glassy) film, and then the DLP system patterns the light with arbitrary shape to induce local cross-linking of the prepolymer. Using this method, the desired structures with complex features with a lateral resolution of several microns and a topography of tens of nanometers could be fabricated within 30 s. Furthermore, the universal applicability of the CHic reaction enables the printing on a wide variety of substrates, which greatly broadens the using scenarios of this printing approach.

Infrared Spectroscopy on Equilibrated High-Density Amorphous Ice

High-density (HDA) and low-density amorphous ices (LDA) are believed to be counterparts of the high- and low-density liquid phases of water, respectively. In order to better understand how the vibrational modes change during the transition between the two solid states, we present infrared spectroscopy measurements, following the change of the decoupled OD-stretch (v_OD) (∼2460 cm^-1) and OH-combinational mode (v_OH + v₂, v_OH + 2v_R) (∼5000 cm^-1). We observe a redshift from HDA to LDA, accompanied with a drastic decrease of the bandwidth. The hydrogen bonds are stronger in LDA, which is caused by a change in the coordination number and number of water molecules interstitial between the first and second hydration shell. The unusually broad uncoupled OD band also clearly distinguishes HDA from other crystalline high-pressure phases, while the shape and position of the in situ prepared LDA are comparable to those of vapor-deposited amorphous ice.

The Impact of the COVID-19 Pandemic on Trajectories of Well-Being of Middle-Aged and older Adults: A Multidimensional and Multidirectional Perspective

The COVID-19 pandemic has resulted in profound changes of individuals' everyday lives. Restrictions in social contacts and in leisure activities and the threatening situation of a spreading virus might have resulted in compromised well-being. At the same time, the pandemic could have promoted specific aspects of psychosocial well-being, e.g., due to intensified relationships with close persons during lockdown periods. We investigated this potentially multidimensional and multi-directional pattern of pandemic-specific change in well-being by analyzing changes over up to 8 years (2012-2020) in two broad well-being domains, hedonic well-being (life satisfaction) and eudaimonic well-being (one overarching eudaimonic well-being indicator as well as environmental mastery, personal growth, positive relations with others, and self-acceptance), among 423 adults who were aged 40-98 years in 2012. By modelling longitudinal multilevel regression models and allowing for a measurement-specific intra-individual deviation component from the general slope in 2020, i.e. after the pandemic outbreak, we analyzed potential normative history-graded changes due to the pandemic. All mean-level history-graded changes were nonsignificant, but most revealed substantial interindividual variability, indicating that individuals' pandemic-related well-being changes were remarkably heterogeneous. Only for personal growth and self-acceptance, adding a pandemic-related change component (and interindividual variability thereof) did not result in a better model fit. Individuals with poorer self-rated health at baseline in 2012 revealed a pandemic-related change toward lower life satisfaction. Our findings suggest that not all well-being domains - and not all individuals - are equally prone to "COVID-19 effects", and even pandemic-associated gains were observed for some individuals in certain well-being domains.

Can Organic Solar Cells Beat the Near-Equilibrium Thermodynamic Limit?

Despite an impressive increase over the past decade, experimentally determined power conversion efficiencies of organic photovoltaic cells still fall considerably below the theoretical upper bound for near-equilibrium solar cells. Even in otherwise optimized devices, a prominent yet incompletely understood loss channel is the thermalization of photogenerated charge carriers in the density of states that is broadened by energetic disorder. Here, we demonstrate by extensive numerical modeling how this loss channel can be mitigated in carefully designed morphologies. Specifically, we show how funnel-shaped donor- and acceptor-rich domains in the phase-separated morphology that are characteristic of organic bulk heterojunction solar cells can promote directed transport of positive and negative charge carriers toward the anode and cathode, respectively. We demonstrate that in optimized funnel morphologies this kinetic, nonequilibrium effect, which is boosted by the slow thermalization of photogenerated charges, allows one to surpass the near-equilibrium limit for the same material in the absence of gradients.

Prediction of Antibiotic Susceptibility Profiles of Vibrio cholerae Isolates From Whole Genome Illumina and Nanopore Sequencing Data: CholerAegon

During the last decades, antimicrobial resistance (AMR) has become a global public health concern. Nowadays multi-drug resistance is commonly observed in strains of Vibrio cholerae, the etiological agent of cholera. In order to limit the spread of pathogenic drug-resistant bacteria and to maintain treatment options the analysis of clinical samples and their AMR profiles are essential. Particularly, in low-resource settings a timely analysis of AMR profiles is often impaired due to lengthy culturing procedures for antibiotic susceptibility testing or lack of laboratory capacity. In this study, we explore the applicability of whole genome sequencing for the prediction of AMR profiles of V. cholerae. We developed the pipeline CholerAegon for the in silico prediction of AMR profiles of 82 V. cholerae genomes assembled from long and short sequencing reads. By correlating the predicted profiles with results from phenotypic antibiotic susceptibility testing we show that the prediction can replace in vitro susceptibility testing for five of seven antibiotics. Because of the relatively low costs, possibility for real-time data analyses, and portability, the Oxford Nanopore Technologies MinION sequencing platform-especially in light of an upcoming less error-prone technology for the platform-appears to be well suited for pathogen genomic analyses such as the one described here. Together with CholerAegon, it can leverage pathogen genomics to improve disease surveillance and to control further spread of antimicrobial resistance.

Novel Three-Dimensional and Biocompatible Lift-Off Method for Selective Metallization of a Scleral Contact Lens Electrode for Biopotential Detection

Presbyopia describes the eye's physiological loss of the ability to see close objects clearly. The adaptation to different viewing distances, termed accommodation, is achieved by a change in the curvature of the eye lens induced by the ciliary muscle. A possible approach to correct presbyopia could be to detect the ciliary muscle's neuromuscular signals during accommodation and transfer these signals electronically to a biomimetic, micro-optical system to provide the necessary refractive power. As a preliminary step toward such a described system, a novel three-dimensional and biocompatible lift-off method was developed. In addition, the influence of the distance between the electrically conducting surfaces of the lens on the accommodated signal amplitudes was investigated. Compared to the conventional masking methods, this process has the advantage that three-dimensional surfaces can be masked with biocompatible gelling sugar by utilizing a direct writing process with a dispensing robot. Since gelling sugar can be used at room temperature and is water-soluble, the process presented is suitable for materials that should not be exposed to organic solvents or excessively high temperatures. Apart from investigating the shrinkage behavior of the gelling sugar during the physical vapor deposition (PVD) coating process, this paper also describes the approaches used to partially coat a commercial scleral contact lens with an electrically conductive material. It was shown that gelling sugar withstands the conditions during the PVD processes and a successful lift-off was performed. To investigate the influence of the spacing between the electrically conductive regions of the contact lens on the measured signals, three simplified electrode configurations with different distances were fabricated using a 3D printer. By testing these in an experimental setup, it could be demonstrated that the distance between the conductive surfaces has a significant influence on the amplitude. Regarding the described lift-off process using gelling sugar, it was found that the dispensing flow rate has a direct influence on the line uniformity. Future work should address the influence of the viscosity of the gelling sugar as well as the diameter of the cannula. It is assumed that they are the prevailing limitations for the lateral resolution.

Bottom-Up Assembly of Synthetic Cells with a DNA Cytoskeleton

Cytoskeletal elements, like actin and myosin, have been reconstituted inside lipid vesicles toward the vision to reconstruct cells from the bottom up. Here, we realize the de novo assembly of entirely artificial DNA-based cytoskeletons with programmed multifunctionality inside synthetic cells. Giant unilamellar lipid vesicles (GUVs) serve as cell-like compartments, in which the DNA cytoskeletons are repeatedly and reversibly assembled and disassembled with light using the cis-trans isomerization of an azobenzene moiety positioned in the DNA tiles. Importantly, we induced ordered bundling of hundreds of DNA filaments into more rigid structures with molecular crowders. We quantify and tune the persistence length of the bundled filaments to achieve the formation of ring-like cortical structures inside GUVs, resembling actin rings that form during cell division. Additionally, we show that DNA filaments can be programmably linked to the compartment periphery using cholesterol-tagged DNA as a linker. The linker concentration determines the degree of the cortex-like network formation, and we demonstrate that the DNA cortex-like network can deform GUVs from within. All in all, this showcases the potential of DNA nanotechnology to mimic the diverse functions of a cytoskeleton in synthetic cells.

Designing Prosthetic Hands With Embodied Intelligence: The KIT Prosthetic Hands

Hand prostheses should provide functional replacements of lost hands. Yet current prosthetic hands often are not intuitive to control and easy to use by amputees. Commercially available prostheses are usually controlled based on EMG signals triggered by the user to perform grasping tasks. Such EMG-based control requires long training and depends heavily on the robustness of the EMG signals. Our goal is to develop prosthetic hands with semi-autonomous grasping abilities that lead to more intuitive control by the user. In this paper, we present the development of prosthetic hands that enable such abilities as first results toward this goal. The developed prostheses provide intelligent mechatronics including adaptive actuation, multi-modal sensing and on-board computing resources to enable autonomous and intuitive control. The hands are scalable in size and based on an underactuated mechanism which allows the adaptation of grasps to the shape of arbitrary objects. They integrate a multi-modal sensor system including a camera and in the newest version a distance sensor and IMU. A resource-aware embedded system for in-hand processing of sensory data and control is included in the palm of each hand. We describe the design of the new version of the hands, the female hand prosthesis with a weight of 377 g, a grasping force of 40.5 N and closing time of 0.73 s. We evaluate the mechatronics of the hand, its grasping abilities based on the YCB Gripper Assessment Protocol as well as a task-oriented protocol for assessing the hand performance in activities of daily living. Further, we exemplarily show the suitability of the multi-modal sensor system for sensory-based, semi-autonomous grasping in daily life activities. The evaluation demonstrates the merit of the hand concept, its sensor and in-hand computing systems.

A Quantitative Comparison of Slackline Balancing Capabilities of Experts and Beginners

Mechanical stability criteria are able to explain balance and robustness during simple motions, however, humans have learned many complex balancing tasks for which science lacks a thorough understanding. In this work, we analyzed slackline balancing to define general balance performance indicators. The goal is to not only measure slackline expertise, but to be able to quantify stability during any balance task. For this, we compared beginners that had never balanced on a slackline before to professional slackline athletes. Further, all participants performed a static balance test, based on which we divided beginners into a balance-experienced and a balance-inexperienced group. On average, the balance experienced group was able to balance twice as long on the slackline and therefore, we showed that this static balance experience is a predictor of slackline balance performance. Based on over 300 balancing trials on the slackline of 20 participants, we then defined and evaluated over 30 balance metrics. The parameters can be grouped into quantification of stability and recovery movements, balance specific skills and balance strategies. We found that normalized angular momentum and center of mass acceleration are measures for overall stability, with lower values representing better stability and fewer recovery movements. We showed that improved hand coordination and adjusted stance leg compliance are valuable skills for balance tasks. especially when controlling external forces. Looking at posture and movement strategies, we found that professional slackliners have adapted a different mean pose with larger inertia and an upright head position, when compared to beginners.

Actomyosin-Assisted Pulling of Lipid Nanotubes from Lipid Vesicles and Cells

Molecular motors are pivotal for intracellular transport as well as cell motility and have great potential to be put to use outside cells. Here, we exploit engineered motor proteins in combination with self-assembly of actin filaments to actively pull lipid nanotubes from giant unilamellar vesicles (GUVs). In particular, actin filaments are bound to the outer GUV membrane and the GUVs are seeded on a heavy meromyosin-coated substrate. Upon addition of ATP, hollow lipid nanotubes with a length of tens of micrometer are pulled from single GUVs due to the motor activity. We employ the same mechanism to pull lipid nanotubes from different types of cells. We find that the length and number of nanotubes critically depends on the cell type, whereby suspension cells form bigger networks than adherent cells. This suggests that molecular machines can be used to exert forces on living cells to probe membrane-to-cortex attachment.

Homeostatic control of synaptic rewiring in recurrent networks induces the formation of stable memory engrams

Brain networks store new memories using functional and structural synaptic plasticity. Memory formation is generally attributed to Hebbian plasticity, while homeostatic plasticity is thought to have an ancillary role in stabilizing network dynamics. Here we report that homeostatic plasticity alone can also lead to the formation of stable memories. We analyze this phenomenon using a new theory of network remodeling, combined with numerical simulations of recurrent spiking neural networks that exhibit structural plasticity based on firing rate homeostasis. These networks are able to store repeatedly presented patterns and recall them upon the presentation of incomplete cues. Storage is fast, governed by the homeostatic drift. In contrast, forgetting is slow, driven by a diffusion process. Joint stimulation of neurons induces the growth of associative connections between them, leading to the formation of memory engrams. These memories are stored in a distributed fashion throughout connectivity matrix, and individual synaptic connections have only a small influence. Although memory-specific connections are increased in number, the total number of inputs and outputs of neurons undergo only small changes during stimulation. We find that homeostatic structural plasticity induces a specific type of "silent memories", different from conventional attractor states.

pH-Triggered Assembly of Endomembrane Multicompartments in Synthetic Cells

By using electrostatic interactions as driving force to assemble vesicles, the droplet-stabilized method was recently applied to reconstitute and encapsulate proteins, or compartments, inside giant unilamellar vesicles (GUVs) to act as minimal synthetic cells. However, the droplet-stabilized approach exhibits low production efficiency associated with the troublesome release of the GUVs from the stabilized droplets, corresponding to a major hurdle for the droplet-stabilized approach. Herein, we report the use of pH as a potential trigger to self-assemble droplet-stabilized GUVs (dsGUVs) by either bulk or droplet-based microfluidics. Moreover, pH enables the generation of compartmentalized GUVs with flexibility and robustness. By co-encapsulating pH-sensitive small unilamellar vesicles (SUVs), negatively charged SUVs, and/or proteins, we show that acidification of the droplets efficiently produces dsGUVs while sequestrating the co-encapsulated material. Most importantly, the pH-mediated assembly of dsGUVs significantly improves the production efficiency of free-standing GUVs (i.e., released from the stabilizing-droplets) compared to its previous implementation.

Comparison of direct and inverse methods for 2.5D traction force microscopy

Essential cellular processes such as cell adhesion, migration and division strongly depend on mechanical forces. The standard method to measure cell forces is traction force microscopy (TFM) on soft elastic substrates with embedded marker beads. While in 2D TFM one only reconstructs tangential forces, in 2.5D TFM one also considers normal forces. Here we present a systematic comparison between two fundamentally different approaches to 2.5D TFM, which in particular require different methods to deal with noise in the displacement data. In the direct method, one calculates strain and stress tensors directly from the displacement data, which in principle requires a divergence correction. In the inverse method, one minimizes the difference between estimated and measured displacements, which requires some kind of regularization. By calculating the required Green's functions in Fourier space from Boussinesq-Cerruti potential functions, we first derive a new variant of 2.5D Fourier Transform Traction Cytometry (FTTC). To simulate realistic traction patterns, we make use of an analytical solution for Hertz-like adhesion patches. We find that FTTC works best if only tangential forces are reconstructed, that 2.5D FTTC is more precise for small noise, but that the performance of the direct method approaches the one of 2.5D FTTC for larger noise, before both fail for very large noise. Moreover we find that a divergence correction is not really needed for the direct method and that it profits more from increased resolution than the inverse method.

Tuning Epithelial Cell-Cell Adhesion and Collective Dynamics with Functional DNA-E-Cadherin Hybrid Linkers

The binding strength between epithelial cells is crucial for tissue integrity, signal transduction and collective cell dynamics. However, there is no experimental approach to precisely modulate cell-cell adhesion strength at the cellular and molecular level. Here, we establish DNA nanotechnology as a tool to control cell-cell adhesion of epithelial cells. We designed a DNA-E-cadherin hybrid system consisting of complementary DNA strands covalently bound to a truncated E-cadherin with a modified extracellular domain. DNA sequence design allows to tune the DNA-E-cadherin hybrid molecular binding strength, while retaining its cytosolic interactions and downstream signaling capabilities. The DNA-E-cadherin hybrid facilitates strong and reversible cell-cell adhesion in E-cadherin deficient cells by forming mechanotransducive adherens junctions. We assess the direct influence of cell-cell adhesion strength on intracellular signaling and collective cell dynamics. This highlights the scope of DNA nanotechnology as a precision technology to study and engineer cell collectives.

Measuring Achievement, Affiliation, and Power Motives in Mobility Situations: Development of the Multi-Motive Grid Mobility

The current study introduces the Multi-Motive Grid Mobility (MMG-M) in an age-stratified sample (N = 206) that aims to disentangle six motive components - hope of success, hope of affiliation, hope of power, fear of failure, fear of rejection, and fear of power - in mobility-related and mobility-unrelated scenarios. Similar to the classical Multi-Motive Grid (MMG), we selected 14 picture scenarios representing seven mobility and seven non-mobility situations. The scenarios were combined with 12 statements from the MMG. Both the MMG-M and MMG were assessed to allow comparability between psychometric criteria. The results of confirmatory factor analyses yielded a good model fit for a six-factor solution with an additional mobility factor for the MMG-M. Internal consistency of the items was similar to the MMG. Lastly, we investigated associations between the motive components and mobility-related variables. We found that risk awareness was positively related to all fear components in both mobility and non-mobility scenarios. Most importantly, physical constraint was positively associated with fear of rejection and fear of power in mobility situations underlining the importance to create support systems to reduce these concerns in people's everyday lives.

Melt-Extrusion-Based Additive Manufacturing of Transparent Fused Silica Glass

In recent years, additive manufacturing (AM) of glass has attracted great interest in academia and industry, yet it is still mostly limited to liquid nanocomposite-based approaches for stereolithography, two-photon polymerization, or direct ink writing. Melt-extrusion-based processes, such as fused deposition modeling (FDM), which will allow facile manufacturing of large thin-walled components or simple multimaterial printing processes, are so far inaccessible for AM of transparent fused silica glass. Here, melt-extrusion-based AM of transparent fused silica is introduced by FDM and fused feedstock deposition (FFD) using thermoplastic silica nanocomposites that are converted to transparent glass using debinding and sintering. This will enable printing of previously inaccessible glass structures like high-aspect-ratio (>480) vessels with wall thicknesses down to 250 µm, delicate parts including overhanging features using polymer support structures, as well as dual extrusion for multicolored glasses.

Time-Resolved Scanning Ion Conductance Microscopy for Three-Dimensional Tracking of Nanoscale Cell Surface Dynamics

Nanocharacterization plays a vital role in understanding the complex nanoscale organization of cells and organelles. Understanding cellular function requires high-resolution information about how the cellular structures evolve over time. A number of techniques exist to resolve static nanoscale structure of cells in great detail (super-resolution optical microscopy, EM, AFM). However, time-resolved imaging techniques tend to either have a lower resolution, are limited to small areas, or cause damage to the cells, thereby preventing long-term time-lapse studies. Scanning probe microscopy methods such as atomic force microscopy (AFM) combine high-resolution imaging with the ability to image living cells in physiological conditions. The mechanical contact between the tip and the sample, however, deforms the cell surface, disturbs the native state, and prohibits long-term time-lapse imaging. Here, we develop a scanning ion conductance microscope (SICM) for high-speed and long-term nanoscale imaging of eukaryotic cells. By utilizing advances in nanopositioning, nanopore fabrication, microelectronics, and controls engineering, we developed a microscopy method that can resolve spatiotemporally diverse three-dimensional (3D) processes on the cell membrane at sub-5-nm axial resolution. We tracked dynamic changes in live cell morphology with nanometer details and temporal ranges of subsecond to days, imaging diverse processes ranging from endocytosis, micropinocytosis, and mitosis to bacterial infection and cell differentiation in cancer cells. This technique enables a detailed look at membrane events and may offer insights into cell-cell interactions for infection, immunology, and cancer research.

Probing the explanation of the muon (g-2) anomaly and thermal light dark matter with the semi-visible dark photon channel

We report the results of a search for a new vector boson ( A ' ) decaying into two dark matter particles χ 1 χ 2 of different mass. The heavier χ 2 particle subsequently decays to χ 1 and an off-shell Dark Photon A ' ∗ → e + e - . For a sufficiently large mass splitting, this model can explain in terms of new physics the recently confirmed discrepancy observed in the muon anomalous magnetic moment at Fermilab. Remarkably, it also predicts the observed yield of thermal dark matter relic abundance. A detailed Monte-Carlo simulation was used to determine the signal yield and detection efficiency for this channel in the NA64 setup. The results were obtained re-analyzing the previous NA64 searches for an invisible decay A ' → χ χ ¯ and axion-like or pseudo-scalar particles a → γ γ . With this method, we exclude a significant portion of the parameter space justifying the muon g-2 anomaly and being compatible with the observed dark matter relic density for A ' masses from 2 m e up to 390 MeV and mixing parameter ε between 3 × 10 - 5 and 2 × 10 - 2 .

Slow Relaxation of Photogenerated Charge Carriers Boosts Open-Circuit Voltage of Organic Solar Cells

Among the parameters determining the efficiency of an organic solar cell, the open-circuit voltage (V_OC) is the one with most room for improvement. Existing models for the description of V_OC assume that photogenerated charge carriers are thermalized. Here, we demonstrate that quasi-equilibrium concepts cannot fully describe V_OC of disordered organic devices. For two representative donor:acceptor blends, it is shown that V_OC is actually 0.1-0.2 V higher than it would be if the system was in thermodynamic equilibrium. Extensive numerical modeling reveals that the excess energy is mainly due to incomplete relaxation in the disorder-broadened density of states. These findings indicate that organic solar cells work as nonequilibrium devices, in which part of the photon excess energy is harvested in the form of an enhanced V_OC.