Search

Peritoneal dialysis (PD) is an increasingly needed, life-maintaining kidney replacement therapy; efficient solute transport is critical for patient outcome. While the role of peritoneal perfusion on solute transport in PD has been described, the role of cellular barriers is uncertain, the mesothelium has been considered irrelevant. We calculated peritoneal blood microvascular endothelial (BESA) to mesothelial surface area (MSA) ratio in human peritonea in health, chronic kidney disease, and on PD, and performed molecular transport related gene profiling and single molecule localization microscopy in two mesothelial (MC) and two endothelial cell lines (EC). Molecular-weight dependent transport was studied in-vitro, ex-vivo and in mice. Peritoneal BESA is 1-3-fold higher than MSA across age groups, and increases with PD, while the mesothelium is preserved during the first two years of PD. Tight junction, transmembrane and transcytotic transporter expression are cell-type specifically expressed. At nanoscale, tight junction anchoring protein Zonula occludens-1 is more abundant and more continuously expressed along the MC than the EC. Ionic conductance is 3-fold lower across the MC than human microvascular EC, as is the permeability for creatinine, 4- and 10-kDa, but not for 70-kDa dextran. MC removal from sheep peritoneum abolishes ionic barrier function. Short term intraperitoneal LPS exposure in mice selectively affects peritoneal mesothelial integrity and increases transperitoneal solute transport. We provide molecular correlates and consistent functional evidence for the mesothelium as a barrier for peritoneal solute transport, i.e., essential information on peritoneal transport modelling, and for interventions to improve PD efficiency and biocompatibility, and beyond., (© The Author(s) 2024. Published by Oxford University Press on behalf of American Physiological Society.)

Biological neural networks effortlessly tackle complex computational problems and excel at predicting outcomes from noisy, incomplete data. Artificial neural networks (ANNs), inspired by these biological counterparts, have emerged as powerful tools for deciphering intricate data patterns and making predictions. However, conventional ANNs can be viewed as "point estimates" that do not capture the uncertainty of prediction, which is an inherently probabilistic process. In contrast, treating an ANN as a probabilistic model derived via Bayesian inference poses significant challenges for conventional deterministic computing architectures. Here, we use chaotic light in combination with incoherent photonic data processing to enable high-speed probabilistic computation and uncertainty quantification. We exploit the photonic probabilistic architecture to simultaneously perform image classification and uncertainty prediction via a Bayesian neural network. Our prototype demonstrates the seamless cointegration of a physical entropy source and a computational architecture that enables ultrafast probabilistic computation by parallel sampling., Competing Interests: Competing interests: The authors declare no competing interests., (© 2024. The Author(s).)

The Stark effect provides a powerful method to shift the spectra of molecules, atoms, and electronic transitions in general, becoming one of the simplest and most straightforward ways to tune the frequency of quantum emitters by means of a static electric field. At the same time, in order to reduce the emitter sensitivity to charge noise, inversion symmetric systems are typically designed, providing a stable emission frequency with a quadratic-only dependence on the applied field. However, such nonlinear behavior might be reflected in correlations between the tuning ability and unwanted spectral fluctuations. Here, we provide experimental evidence of this trend using molecular quantum emitters in the solid state cooled down to liquid helium temperatures. We finally combine the electric field generated by electrodes, which is parallel to the molecule's induced dipole, with optically excite long-lived charge states acting in the perpendicular direction. Based on the anisotropy of the molecule's polarizability, our two-dimensional control of the local electric field allows us not only to tune the emitter's frequency but also to sensibly suppress the spectral instabilities associated with field fluctuations.

The structure of the cell nucleus of higher organisms has become a major topic of advanced light microscopy. So far, a variety of methods have been applied, including confocal laser scanning fluorescence microscopy, 4Pi, STED and localisation microscopy approaches, as well as different types of patterned illumination microscopy, modulated either laterally (in the object plane) or axially (along the optical axis). Based on our experience, we discuss here some application perspectives of Modulated Illumination Microscopy (MIM) and its combination with single-molecule localisation microscopy (SMLM). For example, spatially modulated illumination microscopy/SMI (illumination modulation along the optical axis) has been used to determine the axial extension (size) of small, optically isolated fluorescent objects between ≤ 200 nm and ≥ 40 nm diameter with a precision down to the few nm range; it also allows the axial positioning of such structures down to the 1 nm scale; combined with laterally structured illumination/SIM, a 3D localisation precision of ≤1 nm is expected using fluorescence yields typical for SMLM applications. Together with the nanosizing capability of SMI, this can be used to analyse macromolecular nuclear complexes with a resolution approaching that of cryoelectron microscopy., (© 2024 The Author(s). Journal of Microscopy published by John Wiley & Sons Ltd on behalf of Royal Microscopical Society.)

Novel microporous polymers were synthesized through Yamamoto polymerization of selectively brominated spirofluorene-bridged N -heterotriangulenes. Extensive characterization, including combustion analysis, ToF-SIMS, IR, and Raman spectroscopy, confirmed the elemental composition and integrity of the polymers. The amorphous polymers, observed by scanning electron microscopy as globular particles aggregating into larger structures, exhibited remarkable thermal stability (decomposition temperatures > 400 °C) and BET surface areas up to 690 m 2 g -1 . Dispersions of the tert -butyl-substituted polymer in different solvents displayed bathochromically shifted emission with remarkable solvatochromism. The polymer is reversibly oxidized at +3.81 V ( vs. Li/Li + ) in composite electrodes with carbon black and reaches specific capacities up to 26 mA h g -1 and excellent cycling stability when implemented as cathode material in lithium-ion batteries. Our results highlight the potential of spirofluorene-bridged N -heterotriangulenes as versatile building blocks for the development of functional redox-active porous polymers., Competing Interests: There are no conflicts to declare., (This journal is © The Royal Society of Chemistry.)

Background: It is widely accepted that the 3D chromatin organization in human cell nuclei is not random and recent investigations point towards an interactive relation of epigenetic functioning and chromatin (re-)organization. Although chromatin organization seems to be the result of self-organization of the entirety of all molecules available in the cell nucleus, a general question remains open as to what extent chromatin organization might additionally be predetermined by the DNA sequence and, if so, if there are characteristic differences that distinguish typical regions involved in dysfunction-related aberrations from normal ones, since typical DNA breakpoint regions involved in disease-related chromosome aberrations are not randomly distributed along the DNA sequence., Methods: Highly conserved k -mer patterns in intronic and intergenic regions have been reported in eukaryotic genomes. In this article, we search and analyze regions deviating from average spectra (ReDFAS) of k -mer word frequencies in the human genome. This includes all assembled regions, e.g., telomeric, centromeric, genic as well as intergenic regions., Results: A positive correlation between k -mer spectra and 3D contact frequencies, obtained exemplarily from given Hi-C datasets, has been found indicating a relation of ReDFAS to chromatin organization and interactions. We also searched and found correlations of known functional annotations, e.g., genes correlating with ReDFAS. Selected regions known to contain typical breakpoints on chromosomes 9 and 5 that are involved in cancer-related chromosomal aberrations appear to be enriched in ReDFAS. Since transposable elements like ALUs are often assigned as major players in 3D genome organization, we also studied their impact on our examples but could not find a correlation between ALU regions and breakpoints comparable to ReDFAS., Conclusions: Our findings might show that ReDFAS are associated with instable regions of the genome and regions with many chromatin contacts which is in line with current research indicating that chromatin loop anchor points lead to genomic instability.

An on-chip asymmetric directional coupler (DC) can convert fundamental modes to higher-order modes and is one of the core components of mode-division multiplexing (MDM) technology. In this study, we propose that waveguides of the asymmetric DC can be trimmed by silicon ion implantation to tune the effective refractive index and facilitate mode conversion into higher-order modes. Through this method of tuning, transmission changes of up to 18 dB have been realized with one ion implantation step. In addition, adjusting the position of the ion implantation on the waveguide can provide a further degree of control over the transmission into the resulting mode. The results of this work present a promising new route for the development of high-efficiency, low-loss mode converters for integrated photonic platforms, and aim to facilitate the application of MDM technology in emerging photonic neuromorphic computing.

A core challenge for the brain is to process information across various timescales. This could be achieved by a hierarchical organization of temporal processing through intrinsic mechanisms (e.g., recurrent coupling or adaptation), but recent evidence from spike recordings of the rodent visual system seems to conflict with this hypothesis. Here, we used an optimized information-theoretic and classical autocorrelation analysis to show that information- and correlation timescales of spiking activity increase along the anatomical hierarchy of the mouse visual system under visual stimulation, while information-theoretic predictability decreases. Moreover, intrinsic timescales for spontaneous activity displayed a similar hierarchy, whereas the hierarchy of predictability was stimulus-dependent. We could reproduce these observations in a basic recurrent network model with correlated sensory input. Our findings suggest that the rodent visual system employs intrinsic mechanisms to achieve longer integration for higher cortical areas, while simultaneously reducing predictability for an efficient neural code., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Rudelt et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Super-resolution microscopy has been used to show the formation of receptor clusters and adapted lipid organization of cell membranes for many members of the ErbB receptor family. The clustering behaviour depends on the receptor size and shape, possibly ligand binding or expression activity. Using single molecule localization microscopy (SMLM), we also showed this typical clustering for the epidermal growth factor receptor variant III (EGFRvIII) in glioblastoma multiforme (GBM) cells. EGFRvIII is co-expressed with the wild type (EGFRwt) and both receptors are assumed to preferentially form hetero-dimers leading to transactivation and elevated oncogenic EGFR-signalling in GBM cells. Here, we analysed EGFRvIII and EGFRwt co-localization using our already described model system of the glioblastoma cell line DKMG, displaying endogenous EGFRvIII expression. Using EGFRvIII and EGFRwt specific antibodies, EGFR localization and their potential for dimerization in a given membrane cluster were analysed by dual colour SMLM supported by novel approaches of mathematic evaluations including Ripley statistics, persistent homology and similarity algorithms. Surprisingly, cluster analysis, Ripley point-to-point distance statistics for cluster geometry and persistent homology comparing cluster topology, revealed that both EGFRvIII and EGFRwt do primarily not form hetero-dimers but the results support the hypothesis that they tend to form homo-dimers. The ratio of homo-dimers obtained by this calculation was significantly higher (>5σ, standard deviation) than expected from randomly arranged points. In comparison, hetero-dimer formation was only slightly increased. We confirmed these data by immunoprecipitation, which show no co-precipitation of EGFRvIII and EGFRwt. Furthermore, we showed that the topology of the clusters was more similar among the same type than among the different types of receptors. Taken together, these data indicate that EGFRvIII does induce oncogenic signalling by homo-dimerisation and not preferentially by hetero-dimer formation with EGFRwt. These data offer a new perspective on EGFRvIII signalling which will lead to a better understanding of this tumour associated receptor variant in GBM.

Lithium-rich antiperovskites promise to be a compelling class of high-capacity cathode materials due to the existence of both cationic and anionic redox activity. Little is however known about the effect of separating the electrochemical cationic process from the anionic process and the associated implications on the electrochemical performance. In this context, we report the electrochemical properties of the illustrative example of three different (Li 2 Fe)SO materials with a focus on separating cationic from anionic effects. With the high-voltage anionic process, an astonishing electrochemical capacity of around 400 mAh g -1 can initially be reached. Our results however identify the anionic process as the cause of poor cycling stability and demonstrate that the fading reported in previous literature is avoided by restricting to only the cationic processes. Following this path, our (Li 2 Fe)SO-BM500 shows strongly improved performance as indicated by constant electrochemical cycling over 100 cycles at a capacity of around 175 mAh g -1 at 1 C. Our approach also allows us to investigate the electrochemical performance of the bare antiperovskite phase excluding extrinsic activity from initial or cycling-induced impurity phases. Our results underscore that synthesis conditions are a critical determinant of electrochemical performance in lithium-rich antiperovskites, especially with regard to the amount of electrochemical secondary phases, while the particle size has not been found to be a crucial parameter. Overall, separating and understanding the effects of the cationic from the anionic redox activity in lithium-rich antiperovskites provides the route to further improve their performance in electrochemical energy storage.

Advancements in optical coherence control 1-5 have unlocked many cutting-edge applications, including long-haul communication, light detection and ranging (LiDAR) and optical coherence tomography 6-8 . Prevailing wisdom suggests that using more coherent light sources leads to enhanced system performance and device functionalities 9-11 . Our study introduces a photonic convolutional processing system that takes advantage of partially coherent light to boost computing parallelism without substantially sacrificing accuracy, potentially enabling larger-size photonic tensor cores. The reduction of the degree of coherence optimizes bandwidth use in the photonic convolutional processing system. This breakthrough challenges the traditional belief that coherence is essential or even advantageous in integrated photonic accelerators, thereby enabling the use of light sources with less rigorous feedback control and thermal-management requirements for high-throughput photonic computing. Here we demonstrate such a system in two photonic platforms for computing applications: a photonic tensor core using phase-change-material photonic memories that delivers parallel convolution operations to classify the gaits of ten patients with Parkinson's disease with 92.2% accuracy (92.7% theoretically) and a silicon photonic tensor core with embedded electro-absorption modulators (EAMs) to facilitate 0.108 tera operations per second (TOPS) convolutional processing for classifying the Modified National Institute of Standards and Technology (MNIST) handwritten digits dataset with 92.4% accuracy (95.0% theoretically)., (© 2024. The Author(s).)

This roadmap reviews the new, highly interdisciplinary research field studying the behavior of condensed matter systems exposed to radiation. The Review highlights several recent advances in the field and provides a roadmap for the development of the field over the next decade. Condensed matter systems exposed to radiation can be inorganic, organic, or biological, finite or infinite, composed of different molecular species or materials, exist in different phases, and operate under different thermodynamic conditions. Many of the key phenomena related to the behavior of irradiated systems are very similar and can be understood based on the same fundamental theoretical principles and computational approaches. The multiscale nature of such phenomena requires the quantitative description of the radiation-induced effects occurring at different spatial and temporal scales, ranging from the atomic to the macroscopic, and the interlinks between such descriptions. The multiscale nature of the effects and the similarity of their manifestation in systems of different origins necessarily bring together different disciplines, such as physics, chemistry, biology, materials science, nanoscience, and biomedical research, demonstrating the numerous interlinks and commonalities between them. This research field is highly relevant to many novel and emerging technologies and medical applications.

The BrainScaleS-2 system is an established analog neuromorphic platform with versatile applications in the diverse fields of computational neuroscience and spike-based machine learning. In this work, we extend the system with a configurable realtime event interface that enables a tight coupling of its distinct analog network core to external sensors and actuators. The 1,000-fold acceleration of the emulated nerve cells allows us to target high-speed robotic applications that require precise timing on a microsecond scale. As a showcase, we present a closed-loop setup for commuting brushless DC motors: we utilize PyTorch to train a spiking neural network emulated on the analog substrate to control an electric motor from a sensory event stream. The presented system enables research in the area of event-driven controllers for high-speed robotics, including self-supervised and biologically inspired online learning for such applications., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Stradmann and Schemmel.)

Photonic integrated circuits (PICs) are revolutionizing the realm of information technology, promising unprecedented speeds and efficiency in data processing and optical communication. However, the nanoscale precision required to fabricate these circuits at scale presents significant challenges, due to the need to maintain consistency across wavelength-selective components, which necessitates individualized adjustments after fabrication. Harnessing spectral alignment by automated silicon ion implantation, in this work scalable and non-volatile photonic computational memories are demonstrated in high-quality resonant devices. Precise spectral trimming of large-scale photonic ensembles from a few picometers to several nanometres is achieved with long-term stability and marginal loss penalty. Based on this approach, spectrally aligned photonic memory and computing systems for general matrix multiplication are demonstrated, enabling wavelength multiplexed integrated architectures at large scales., (© 2023 The Authors. Advanced Materials published by Wiley-VCH GmbH.)

Fast modulation of optical signals that carry multidimensional information in the form of wavelength, phase or polarization has fueled an explosion of interest in integrated photonics. This interest however masks a significant challenge which is that independent modulation of multi-wavelength carrier signals in a single waveguide is not trivial. Such challenge is attributed to the longitudinal direction of guided-mode propagation, limiting the spatial separation and modulation of electric-field. Here, we overcome this using a single photonic element that utilizes active coherent (near) perfect absorption. We make use of standing wave patterns to exploit the spatial-degrees-of-freedom of in-plane modes and individually address elements according to their mode number. By combining the concept of coherent absorption in spatio-spectral domain with active phase-change nanoantennas, we engineer and test an integrated, reconfigurable and multi-spectral modulator operating within a single element. Our approach demonstrates for the first time, a non-volatile, wavelength-addressable element, providing a pathway for exploring the tunable capabilities in both spatial and spectral domains of coherent nanophotonics., Competing Interests: Conflict of interest: Authors state no conflicts of interest., (© 2023 the author(s), published by De Gruyter, Berlin/Boston.)

The specific characteristics of k-mer words (2 ≤ k ≤ 11) regarding genomic distribution and evolutionary conservation were recently found. Among them are, in high abundance, words with a tandem repeat structure (repeat unit length of 1 bp to 3 bp). Furthermore, there seems to be a class of extremely short tandem repeats (≤12 bp), so far overlooked, that are non-random-distributed and, therefore, may play a crucial role in the functioning of the genome. In the following article, the positional distributions of these motifs we call super-short tandem repeats (SSTRs) were compared to other functional elements, like genes and retrotransposons. We found length- and sequence-dependent correlations between the local SSTR density and G+C content, and also between the density of SSTRs and genes, as well as correlations with retrotransposon density. In addition to many general interesting relations, we found that SINE Alu has a strong influence on the local SSTR density. Moreover, the observed connection of SSTR patterns to pseudogenes and -exons might imply a special role of SSTRs in gene expression. In summary, our findings support the idea of a special role and the functional relevance of SSTRs in the genome.

We present an adaptive optical neural network based on a large-scale event-driven architecture. In addition to changing the synaptic weights (synaptic plasticity), the optical neural network's structure can also be reconfigured enabling various functionalities (structural plasticity). Key building blocks are wavelength-addressable artificial neurons with embedded phase-change materials that implement nonlinear activation functions and nonvolatile memory. Using multimode focusing, the activation function features both excitatory and inhibitory responses and shows a reversible switching contrast of 3.2 decibels. We train the neural network to distinguish between English and German text samples via an evolutionary algorithm. We investigate both the synaptic and structural plasticity during the training process. On the basis of this concept, we realize a large-scale network consisting of 736 subnetworks with 16 phase-change material neurons each. Overall, 8398 neurons are functional, highlighting the scalability of the photonic architecture.

Exposure to high acute doses of ionizing radiation (IR) can induce cutaneous radiation syndrome. Weeks after such radiation insults, keratinocyte nuclei of the epidermis exhibit persisting genomic lesions that present as focal accumulations of DNA double-strand break (DSB) damage marker proteins. Knowledge about the nanostructure of these genomic lesions is scarce. Here, we compared the chromatin nano-architecture with respect to DNA damage response (DDR) factors in persistent genomic DNA damage regions and healthy chromatin in epidermis sections of two minipigs 28 days after lumbar irradiation with ~50 Gy γ-rays, using single-molecule localization microscopy (SMLM) combined with geometric and topological mathematical analyses. SMLM analysis of fluorochrome-stained paraffin sections revealed, within keratinocyte nuclei with perisitent DNA damage, the nano-arrangements of pATM, 53BP1 and Mre11 DDR proteins in γ-H2AX-positive focal chromatin areas (termed macro-foci). It was found that persistent macro-foci contained on average ~70% of 53BP1, ~23% of MRE11 and ~25% of pATM single molecule signals of a nucleus. MRE11 and pATM fluorescent tags were organized in focal nanoclusters peaking at about 40 nm diameter, while 53BP1 tags formed nanoclusters that made up super-foci of about 300 nm in size. Relative to undamaged nuclear chromatin, the enrichment of DDR protein signal tags in γ-H2AX macro-foci was on average 8.7-fold (±3) for 53BP1, 3.4-fold (±1.3) for MRE11 and 3.6-fold (±1.8) for pATM. The persistent macro-foci of minipig epidermis displayed a ~2-fold enrichment of DDR proteins, relative to DSB foci of lymphoblastoid control cells 30 min after 0.5 Gy X-ray exposure. A lasting accumulation of damage signaling and sensing molecules such as pATM and 53BP1, as well as the DSB end-processing protein MRE11 in the persistent macro-foci suggests the presence of diverse DNA damages which pose an insurmountable problem for DSB repair.

The spatial organization of euchromatin (EC) and heterochromatin (HC) appears as a cell-type specific network, which seems to have an impact on gene regulation and cell fate. The spatial organization of cohesin should thus also be characteristic for a cell type since it is involved in a TAD (topologically associating domain) formation, and thus in gene regulation or DNA repair processes. Based on the previous hypotheses and results on the general importance of heterochromatin organization on genome functions in particular, the configurations of these organizational units (EC represented by H3K4me3-positive regions, HC represented by H3K9me3-positive regions, cohesins) are investigated in the cell nuclei of different cancer and non-cancerous cell types and under different anti-cancer treatments. Confocal microscopic images of the model cell systems were used and analyzed using analytical processes of quantification created in Fiji, an imaging tool box well established in different fields of science. Human fibroblasts, breast cancer and glioblastoma cells as well as murine embryonal terato-carcinoma cells were used as these cell models and compared according to the different parameters of spatial arrangements. In addition, proliferating, quiescent and from the quiescent state reactivated fibroblasts were analyzed. In some selected cases, the cells were treated with X-rays or azacitidine. Heterogeneous results were obtained by the analyses of the configurations of the three different organizational units: granulation and a loss of H3K4me3-positive regions (EC) occurred after irradiation with 4 Gy or azacitidine treatment. While fibroblasts responded to irradiation with an increase in cohesin and granulation, in breast cancer cells, it resulted in decreases in cohesin and changes in granulation. H3K9me3-positive regions (HC) in fibroblasts experienced increased granulation, whereas in breast cancer cells, the amount of such regions increased. After azacitidine treatment, murine stem cells showed losses of cohesin and granulation and an increase in the granulation of H3K9me3-positive regions. Fibroblasts that were irradiated with 2 Gy only showed irregularities in structural amounts and granulation. Quiescent fibroblasts contained less euchromatin-related H3K4me3-positive signals and cohesin levels as well as higher heterochromatin-related H3K9me3-positive signals than non-quiescent ones. In general, fibroblasts responded more intensely to X-ray irradiation than breast cancer cells. The results indicate the usefulness of model cell systems and show that, in general, characteristic differences initially existing in chromatin and cohesin organizations result in specific responses to anti-cancer treatment.

This paper introduces assignment flows for density matrices as state spaces for representation and analysis of data associated with vertices of an underlying weighted graph. Determining an assignment flow by geometric integration of the defining dynamical system causes an interaction of the non-commuting states across the graph, and the assignment of a pure (rank-one) state to each vertex after convergence. Adopting the Riemannian-Bogoliubov-Kubo-Mori metric from information geometry leads to closed-form local expressions that can be computed efficiently and implemented in a fine-grained parallel manner. Restriction to the submanifold of commuting density matrices recovers the assignment flows for categorical probability distributions, which merely assign labels from a finite set to each data point. As shown for these flows in our prior work, the novel class of quantum state assignment flows can also be characterized as Riemannian gradient flows with respect to a non-local, non-convex potential after proper reparameterization and under mild conditions on the underlying weight function. This weight function generates the parameters of the layers of a neural network corresponding to and generated by each step of the geometric integration scheme. Numerical results indicate and illustrate the potential of the novel approach for data representation and analysis, including the representation of correlations of data across the graph by entanglement and tensorization.

Chromatin compaction differences may have a strong impact on accessibility of individual macromolecules and macromolecular assemblies to their DNA target sites. Estimates based on fluorescence microscopy with conventional resolution, however, suggest only modest compaction differences (∼2-10×) between the active nuclear compartment (ANC) and inactive nuclear compartment (INC). Here, we present maps of nuclear landscapes with true-to-scale DNA densities, ranging from <5 to >300 Mbp/μm 3 . Maps are generated from individual human and mouse cell nuclei with single-molecule localization microscopy at ∼20 nm lateral and ∼100 nm axial optical resolution and are supplemented by electron spectroscopic imaging. Microinjection of fluorescent nanobeads with sizes corresponding to macromolecular assemblies for transcription into nuclei of living cells demonstrates their localization and movements within the ANC and exclusion from the INC., Competing Interests: Declaration of interests C.C. is a co-founder and shareholder of FZM LuciaOptics gUG (Karlsruhe/Germany), a non-profit organization to promote research and applications in advanced microscopy; FZM holds a variety of patents in the field of super-resolution microscopy., (Copyright © 2023 The Authors. Published by Elsevier Inc. All rights reserved.)

Integrated photonic circuits (PICs) have seen an explosion in interest, through to commercialization in the past decade. Most PICs rely on sharp resonances to modulate, steer, and multiplex signals. However, the spectral characteristics of high-quality resonances are highly sensitive to small variations in fabrication and material constants, which limits their applicability. Active tuning mechanisms are commonly employed to account for such deviations, consuming energy and occupying valuable chip real estate. Readily employable, accurate, and highly scalable mechanisms to tailor the modal properties of photonic integrated circuits are urgently required. Here, we present an elegant and powerful solution to achieve this in a scalable manner during the semiconductor fabrication process using existing lithography tools: by exploiting the volume shrinkage exhibited by certain polymers to permanently modulate the waveguide's effective index. This technique enables broadband and lossless tuning with immediate applicability in wide-ranging applications in optical computing, telecommunications, and free-space optics.

Electronically reprogrammable photonic circuits based on phase-change chalcogenides present an avenue to resolve the von-Neumann bottleneck; however, implementation of such hybrid photonic-electronic processing has not achieved computational success. Here, we achieve this milestone by demonstrating an in-memory photonic-electronic dot-product engine, one that decouples electronic programming of phase-change materials (PCMs) and photonic computation. Specifically, we develop non-volatile electronically reprogrammable PCM memory cells with a record-high 4-bit weight encoding, the lowest energy consumption per unit modulation depth (1.7 nJ/dB) for Erase operation (crystallization), and a high switching contrast (158.5%) using non-resonant silicon-on-insulator waveguide microheater devices. This enables us to perform parallel multiplications for image processing with a superior contrast-to-noise ratio (≥87.36) that leads to an enhanced computing accuracy (standard deviation σ ≤ 0.007). An in-memory hybrid computing system is developed in hardware for convolutional processing for recognizing images from the MNIST database with inferencing accuracies of 86% and 87%., (© 2023. The Author(s).)

Dinucleotides are known as determinants for various structural and physiochemical properties of DNA and for binding affinities of proteins to DNA. These properties (e.g., stiffness) and bound proteins (e.g., transcription factors) are known to influence important biological functions, such as transcription regulation and 3D chromatin organization. Accordingly, the question arises of how the considerable variations in dinucleotide contents of eukaryotic chromosomes could still provide consistent DNA properties resulting in similar functions and 3D conformations. In this work, we investigate the hypothesis that coupled dinucleotide contents influence DNA properties in opposite directions to moderate each other's influences. Analyzing all 2478 chromosomes of 155 eukaryotic species, considering bias from coding sequences and enhancers, we found sets of correlated and anti-correlated dinucleotide contents. Using computational models, we estimated changes of DNA properties resulting from this coupling. We found that especially pure A/T dinucleotides (AA, TT, AT, TA), known to influence histone positioning and AC/GT contents, are relevant moderators and that, e.g., the Roll property, which is known to influence histone affinity of DNA, is preferably moderated. We conclude that dinucleotide contents might indirectly influence transcription and chromatin 3D conformation, via regulation of histone occupancy and/or other mechanisms., Competing Interests: The authors declare no conflict of interest.

The cell as a system of many components, governed by the laws of physics and chemistry drives molecular functions having an impact on the spatial organization of these systems and vice versa. Since the relationship between structure and function is an almost universal rule not only in biology, appropriate methods are required to parameterize the relationship between the structure and function of biomolecules and their networks, the mechanisms of the processes in which they are involved, and the mechanisms of regulation of these processes. Single molecule localization microscopy (SMLM), which we focus on here, offers a significant advantage for the quantitative parametrization of molecular organization: it provides matrices of coordinates of fluorescently labeled biomolecules that can be directly subjected to advanced mathematical analytical procedures without the need for laborious and sometimes misleading image processing. Here, we propose mathematical tools for comprehensive quantitative computer data analysis of SMLM point patterns that include Ripley distance frequency analysis, persistent homology analysis, persistent 'imaging', principal component analysis and co-localization analysis. The application of these methods is explained using artificial datasets simulating different, potentially possible and interpretatively important situations. Illustrative analyses of real complex biological SMLM data are presented to emphasize the applicability of the proposed algorithms. This manuscript demonstrated the extraction of features and parameters quantifying the influence of chromatin (re)organization on genome function, offering a novel approach to study chromatin architecture at the nanoscale. However, the ability to adapt the proposed algorithms to analyze essentially any molecular organizations, e.g., membrane receptors or protein trafficking in the cytosol, offers broad flexibility of use., (© 2023 The Authors.)

Exposure to environmental factors is generally expected to cause degradation in perovskite films and solar cells. Herein, we show that films with certain defect profiles can display the opposite effect, healing upon exposure to oxygen under illumination. We tune the iodine content of methylammonium lead triiodide perovskite from understoichiometric to overstoichiometric and expose them to oxygen and light prior to the addition of the top layers of the device, thereby examining the defect dependence of their photooxidative response in the absence of storage-related chemical processes. The contrast between the photovoltaic properties of the cells with different defects is stark. Understoichiometric samples indeed degrade, demonstrating performance at 33% of their untreated counterparts, while stoichiometric samples maintain their performance levels. Surprisingly, overstoichiometric samples, which show low current density and strong reverse hysteresis when untreated, heal to maximum performance levels (the same as untreated, stoichiometric samples) upon the photooxidative treatment. A similar, albeit smaller-scale, effect is observed for triple cation and methylammonium-free compositions, demonstrating the general application of this treatment to state-of-the-art compositions. We examine the reasons behind this response by a suite of characterization techniques, finding that the performance changes coincide with microstructural decay at the crystal surface, reorientation of the bulk crystal structure for the understoichiometric cells, and a decrease in the iodine-to-lead ratio of all films. These results indicate that defect engineering is a powerful tool to manipulate the stability of perovskite solar cells., Competing Interests: There are no conflicts to declare., (This journal is © The Royal Society of Chemistry.)

Efficiently collecting light from single-photon emitters is crucial for photonic quantum technologies. Here, we develop and use an ultralow fluorescence photopolymer to three-dimensionally print micrometer-sized elliptical lenses on individual precharacterized single-photon emitters in hexagonal boron nitride (hBN) nanocrystals, operating in the visible regime. The elliptical lens design beams the light highly efficiently into the far field, rendering bulky objective lenses obsolete. Using back focal plane imaging, we confirm that the emission is collimated to a narrow low-divergence beam with a half width at half-maximum of 2.2°. Using photon correlation measurements, we demonstrate that the single-photon character remains undisturbed by the polymer lens. The strongly directed emission and increased collection efficiency is highly beneficial for quantum optical experiments. Furthermore, our approach paves the way for a highly parallel fiber-based detection of single photons from hBN nanocrystals.

Super-resolution fluorescence microscopy has revolutionized multicolor imaging of nuclear structures due to the combination of high labeling specificity and high resolution. Here we expanded the recently developed fBALM (DNA structure fluctuation-assisted binding activated localization microscopy) method by developing a stable methodological sequence that enables dual-color imaging of high-resolution genomic DNA together with an immunofluorescently labeled intranuclear protein. Our measurements of the nuclear periphery, imaging DNA and LaminB1 in biologically relevant samples, show that this novel dual-color imaging method is feasible for further quantitative evaluations. We were able to study the relative spatial signal organization between DNA and LaminB1 by means of highly specific colocalization measurements at nanometer resolution. Measurements were performed with and without the antifade embedding medium ProLong Gold, which proved to be essential for imaging of LaminB1, but not for imaging of SytoxOrange labeled DNA. The localization precision was used to differentiate between localizations with higher and lower amounts of emitting photons. We interpret high intensity localizations to be renatured DNA sections in which a high amount of Sytox Orange molecules were bound. This could give insight into the denaturation kinetics of DNA during fBALM. These results were further complemented by measurements of γH2AX and H3K9me3 signal organization to demonstrate differences within the chromatin landscape, which were quantified with image processing methods such as Voronoi segmentation.

Quantum computation builds on the use of correlations. Correlations could also play a central role for artificial intelligence, neuromorphic computing or "biological computing." As a step toward a systematic exploration of "correlated computing" we demonstrate that neuromorphic computing can perform quantum operations. Spiking neurons in the active or silent states are connected to the two states of Ising spins. A quantum density matrix is constructed from the expectation values and correlations of the Ising spins. We show for a two qubit system that quantum gates can be learned as a change of parameters for neural network dynamics. These changes respect restrictions which ensure the quantum correlations. Our proposal for probabilistic computing goes beyond Markov chains and is not based on transition probabilities. Constraints on classical probability distributions relate changes made in one part of the system to other parts, similar to entangled quantum systems.

While major changes in cellular morphology during apoptosis have been well described, the subcellular changes in nuclear architecture involved in this process remain poorly understood. Imaging of nucleosomes in cortical neurons in vitro before and during apoptosis revealed that chromatin compaction precedes the activation of caspase-3 and nucleus shrinkage. While this early chromatin compaction remained unaffected by pharmacological blockade of the final execution of apoptosis through caspase-3 inhibition, interfering with the chromatin dynamics by modulation of actomyosin activity prevented apoptosis, but resulted in necrotic-like cell death instead. With super-resolution imaging at different phases of apoptosis in vitro and in vivo, we demonstrate that chromatin compaction occurs progressively and can be classified into five stages. In conclusion, we show that compaction of chromatin in the neuronal nucleus precedes apoptosis execution. These early changes in chromatin structure critically affect apoptotic cell death and are not part of the final execution of the apoptotic process in developing cortical neurons., (© 2022. The Author(s).)

Neuromorphic systems open up opportunities to enlarge the explorative space for computational research. However, it is often challenging to unite efficiency and usability. This work presents the software aspects of this endeavor for the BrainScaleS-2 system, a hybrid accelerated neuromorphic hardware architecture based on physical modeling. We introduce key aspects of the BrainScaleS-2 Operating System: experiment workflow, API layering, software design, and platform operation. We present use cases to discuss and derive requirements for the software and showcase the implementation. The focus lies on novel system and software features such as multi-compartmental neurons, fast re-configuration for hardware-in-the-loop training, applications for the embedded processors, the non-spiking operation mode, interactive platform access, and sustainable hardware/software co-development. Finally, we discuss further developments in terms of hardware scale-up, system usability, and efficiency., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Müller, Arnold, Breitwieser, Czierlinski, Emmel, Kaiser, Mauch, Schmitt, Spilger, Stock, Stradmann, Weis, Baumbach, Billaudelle, Cramer, Ebert, Göltz, Ilmberger, Karasenko, Kleider, Leibfried, Pehle and Schemmel.)

The use of nonlinear elements with memory as photonic computing components has seen a huge surge in interest in recent years with the rise of artificial intelligence and machine learning. A key component is the nonlinear element itself. A class of materials known as phase change materials has been extensively used to demonstrate the viability of such computing. However, such materials continue to have relatively slow switching speeds, and issues with cyclability related to phase segregation of phase change alloys. Here, using antimony (Sb) thin films with thicknesses less than 5 nm we demonstrate reversible, ultrafast switching on an integrated photonic platform with retention time of tens of seconds. We use subpicosecond pulses, the shortest used to switch such elements, to program seven distinct memory levels. This portends their use in ultrafast nanophotonic applications ranging from nanophotonic beam steerers to nanoscale integrated elements for photonic computing.

Antimony sulfide, Sb 2 S 3 , is interesting as the phase-change material for applications requiring high transmission from the visible to telecom wavelengths, with its band gap tunable from 2.2 to 1.6 eV, depending on the amorphous and crystalline phase. Here we present results from an interlaboratory study on the interplay between the structural change and resulting optical contrast during the amorphous-to-crystalline transformation triggered both thermally and optically. By statistical analysis of Raman and ellipsometric spectroscopic data, we have identified two regimes of crystallization, namely 250°C ≤ T  < 300°C, resulting in Type-I spherulitic crystallization yielding an optical contrast Δ n ∼ 0.4, and 300 ≤ T  < 350°C, yielding Type-II crystallization bended spherulitic structure with different dielectric function and optical contrast Δ n ∼ 0.2 below 1.5 eV. Based on our findings, applications of on-chip reconfigurable nanophotonic phase modulators and of a reconfigurable high-refractive-index core/phase-change shell nanoantenna are designed and proposed., Competing Interests: The authors declare no competing interests., (© 2022 The Author(s).)