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Defect engineering is foundational to classical electronic device development and for emerging quantum devices. Here, we report on defect engineering of silicon with ion pulses from a laser accelerator in the laser intensity range of 1019 W cm−2 and ion flux levels of up to 1022 ions cm−2 s−1, about five orders of magnitude higher than conventional ion implanters. Low energy ions from plasma expansion of the laser-foil target are implanted near the surface and then diffuse into silicon samples locally pre-heated by high energy ions from the same laser-ion pulse. Silicon crystals exfoliate in the areas of highest energy deposition. Color centers, predominantly W and G-centers, form directly in response to ion pulses without a subsequent annealing step. We find that the linewidth of G-centers increases with high ion flux faster than the linewidth of W-centers, consistent with density functional theory calculations of their electronic structure. Intense ion pulses from a laser-accelerator drive materials far from equilibrium and enable direct local defect engineering and high flux doping of semiconductors.

To ensure the safe repurposing of post-mining landscapes, understanding and managing geotechnical risks, particularly ground movements such as settlements on opencast mining dump surfaces, is critical. Satellite-based radar interferometry (InSAR) technology offers highly detailed data on vertical ground movements with a high spatial and temporal resolution. By combining a data-driven approach, using InSAR-generated high-resolution datasets, with model-driven methods such as inverse modeling and classic time–settlement models, the efficient monitoring and prediction of opencast mine dump settlements can be achieved. This dual approach—leveraging advanced data analysis tools and precise modeling—yields valuable insights into spatial settlement behavior. In particular, classic time–settlement models are applied to the InSAR data through least square regression and Taylor approximation. The integration of both approaches enables the more robust, data-validated forecasts of key geotechnical indicators, such as the time to settlement stabilization and the expected maximum settlement over large areas. An application at a mine in central Germany illustrates the method by generating spatial predictions of the settlement behavior over more than 200 ha. In general, the results provide a comprehensive dataset for investigating other factors influencing the settlement behavior of opencast mine dumps.

Extracranial vascular pathology uncommonly causes intracranial subarachnoid hemorrhage (SAH). Among possible lesions are aneurysms at the craniocervical junction arising from a posterior inferior cerebellar artery (PICA) with an extradural origin. We describe a case of a 55-year-old female presenting with a sudden and severe headache. A computed tomography scan revealed a SAH within the fourth ventricle and cervical spinal canal, and a ruptured saccular aneurysm on a PICA with extradural C2-origin. Despite difficult access anatomy, endovascular treatment was feasible and resulted in subtotal initial occlusion and preservation of distal PICA flow. Upon 3-month follow-up, the aneurysm was completely occluded with a patent PICA. The patient’s clinical status remained stable at the 1.5-year follow-up. In conclusion, we present a rare case of an aneurysm originating from a PICA with extradural C2-origin that was treated endovascularly with preservation of the PICA.

IntroductionPhages are viruses that infect prokaryotes and can shape microbial communities by lysis, thus offering applications in various fields. However, challenges exist in sampling, isolation and accurate prediction of the host specificity of phages as well as in the identification of newly replicated virions in response to environmental challenges.MethodsA new workflow using biorthogonal non-canonical amino acid tagging (BONCAT) and click chemistry (CC) allowed the combined analysis of phages and their hosts, the identification of newly replicated virions, and the specific tagging of phages with biotin for affinity chromatography.ResultsReplication of phage λ in Escherichia coli was selected as a model for workflow development. Specific labeling of phage λ proteins with the non-canonical amino acid 4-azido-L-homoalanine (AHA) during phage development in E. coli was confirmed by LC–MS/MS. Subsequent tagging of AHA with fluorescent dyes via CC allowed the visualization of phages adsorbed to the cell surface by fluorescence microscopy. Flow cytometry enabled the automated detection of these fluorescent phage-host complexes. Alternatively, AHA-labeled phages were tagged with biotin for purification by affinity chromatography. Despite biotinylation the tagged phages could be purified and were infectious after purification.DiscussionApplying this approach to environmental samples would enable host screening without cultivation. A flexible and powerful workflow for the detection and enrichment of phages and their hosts in pure cultures has been established. The developed method lays the groundwork for future workflows that could enable the isolation of phage-host complexes from diverse complex microbial communities using fluorescence-activated cell sorting or biotin purification. The ability to expand and customize the workflow through the growing range of compounds for CC offers the potential to develop a versatile toolbox in phage research. This work provides a starting point for these further studies by providing a comprehensive standard operating procedure.

Microbiomes, comprised of diverse microbial species and viruses, play pivotal roles in human health, environmental processes, and biotechnological applications and interact with each other, their environment, and hosts via ecological interactions. Our understanding of microbiomes is still limited and hampered by their complexity. A concept improving this understanding is systems biology, which focuses on the holistic description of biological systems utilizing experimental and computational methods. An important set of such experimental methods are metaomics methods which analyze microbiomes and output lists of molecular features. These lists of data are integrated, interpreted, and compiled into computational microbiome models, to predict, optimize, and control microbiome behavior. There exists a gap in understanding between microbiologists and modelers/bioinformaticians, stemming from a lack of interdisciplinary knowledge. This knowledge gap hinders the establishment of computational models in microbiome analysis. This review aims to bridge this gap and is tailored for microbiologists, researchers new to microbiome modeling, and bioinformaticians. To achieve this goal, it provides an interdisciplinary overview of microbiome modeling, starting with fundamental knowledge of microbiomes, metaomics methods, common modeling formalisms, and how models facilitate microbiome control. It concludes with guidelines and repositories for modeling. Each section provides entry-level information, example applications, and important references, serving as a valuable resource for comprehending and navigating the complex landscape of microbiome research and modeling.

Small heat shock proteins (sHSPs) emerged early in evolution and occur in all domains of life and nearly in all species, including humans. Mutations in four sHSPs (HspB1, HspB3, HspB5, HspB8) are associated with neuromuscular disorders. The aim of this study is to investigate the evolutionary forces shaping these sHSPs during vertebrate evolution. We performed comparative evolutionary analyses on a set of orthologous sHSP sequences, based on the ratio of non-synonymous: synonymous substitution rates for each codon. We found that these sHSPs had been historically exposed to different degrees of purifying selection, decreasing in this order: HspB8 > HspB1, HspB5 > HspB3. Within each sHSP, regions with different degrees of purifying selection can be discerned, resulting in characteristic selective pressure profiles. The conserved α-crystallin domains were exposed to the most stringent purifying selection compared to the flanking regions, supporting a 'dimorphic pattern' of evolution. Thus, during vertebrate evolution the different sequence partitions were exposed to different and measurable degrees of selective pressures. Among the disease-associated mutations, most are missense mutations primarily in HspB1 and to a lesser extent in the other sHSPs. Our data provide an explanation for this disparate incidence. Contrary to the expectation, most missense mutations cause dominant disease phenotypes. Theoretical considerations support a connection between the historic exposure of these sHSP genes to a high degree of purifying selection and the unusual prevalence of genetic dominance of the associated disease phenotypes. Our study puts the genetics of inheritable sHSP-borne diseases into the context of vertebrate evolution.

The geotechnical characterization of the subsurface is a key requirement for most soil investigations, incl. those for reclaiming landfills and waste dumps associated with mining operations. New sensor technology, combined with intelligent analysis algorithms, allow for a faster and less expensive acquisition of the necessary information without loss of data quality. The use of advanced technologies to support and back up common site investigation techniques, such as cone penetration testing (CPT), can enhance the underground characterization process. This study aims to investigate the possibilities of image analysis for material recognition to advance the geotechnical characterization process. The grey level co-occurrence matrix (GLCM) image processing technique is used in a wide range of study fields to estimate textures, patterns and structure anomalies. This method was adjusted and applied to process the video recorded during a CPT sounding, in order to distinguish soil types by its changing surface characteristics. From the results of the video processing, it is evident that the GLCM technique can identify transitions in soil types that were captured in the video recording. This enables the prospect of image analysis not just for soil investigations, but also for monitoring of the conveyor belt in the mining field, to allow for efficient preliminary decision making, material documentation and quality control by providing information in a cost effective and efficient manner.

Abstract Endothelial cells (EC) are key players in vascular function, homeostasis and inflammation. EC show substantial heterogeneity due to inter-individual variability (e.g. sex-differences) and intra-individual differences as they originate from different organs or vessels. This variability may lead to different responsiveness to external stimuli. Here we compared the responsiveness of female human primary EC from the aorta (HAoEC) and coronary arteries (HCAEC) to Epidermal Growth Factor Receptor (EGFR) activation. EGFR is an important signal integration hub for vascular active substances with physiological and pathophysiological relevance. Our transcriptomic analysis suggested that EGFR activation differentially affects the inflammatory profiles of HAoEC and HCAEC, particularly by inducing a HCAEC-driven leukocyte attraction but a downregulation of adhesion molecule and chemoattractant expression in HAoEC. Experimental assessments of selected inflammation markers were performed to validate these predictions and the results confirmed a dual role of EGFR in these cells: its activation initiated an anti-inflammatory response in HAoEC but a pro-inflammatory one in HCAEC. Our study highlights that, although they are both arterial EC, female HAoEC and HCAEC are distinguishable with regard to the role of EGFR and its involvement in inflammation regulation, what may be relevant for vascular maintenance but also the pathogenesis of endothelial dysfunction.

Background: Paracetamol and non-steroidal anti-inflammatory drugs (NSAIDs) are frequently used during pregnancy. Due to their fetotoxicity, NSAIDs are contraindicated during the third trimester. There is ongoing controversy about the extent to which NSAIDs may cause cardiovascular and renal impairment in the fetus earlier in the second trimester. Paracetamol, used as an effective treatment for closure of patent ductus arteriosus (PDA) after birth, is suspected to cause similar but unwanted effects during the third trimester of pregnancy. Methods: Three major pharmacovigilance databases (VigilanceCentral, EudraVigilance, and VigiBase) were searched for Individual Case Safety Reports (ICSRs; n = 1288) on fetotoxic effects that have been shown to result from NSAID exposure in late pregnancy. Results: In 219/1288 cases, an NSAID and/or paracetamol was taken after the first trimester, and the ICSR was not related to other reported risk factors. Out of these 219 ICSRs, 48 were exposed to NSAIDs in the second but not the third trimester or to paracetamol in the third trimester. Causality assessment was “probable or likely” in four NSAID reports and none of the paracetamol reports. Conclusions: The scarcity of adverse drug reactions (ADRs) in our study and in the literature, despite decades of pharmaceutical marketing and worldwide use of paracetamol as an analgesic of choice in the third trimester and the absence of formal contraindications against NSAIDs in the second trimester, speaks against a substantial cardiovascular and nephrotoxic risk of temporary use of NSAIDs in the second trimester or paracetamol in the third trimester. NSAIDs continue to be contraindicated in the third trimester.

Electrical and thermal transport measurements on quenched NaCl-type Ag1/3Pb1/3Sb1/3Se reveal an n-type semiconductor with a Seebeck coefficient up to −140 μVK−1 and a thermal conductivity as low as 0.52 WmK−1. Short-range order is indicated by disorder diffuse scattering in electron diffraction patterns. In contrast, 4L-Ag0.61Pb1.79Sb2.61Se6 (space group Cmcm with a = 4.2129(1) Å, b = 13.852(1) Å, and c = 20.866(1) Å, Z = 4) features the first lillianite-type structure in the system Ag/Pb/Sb/Se. It consists of slab-like NaCl-type building blocks that are interconnected via trigonal [PbSe6] prisms. As such structures typically do not form with Te as an anion, the first “sulfosalt-like” compound, Ag0.38Pb0.25Sb2.38Te4, in the system Ag/Pb/Sb/Te forms a layered tetradymite-like structure (space group R3-m with a = 4.2887(1) Å, c = 41.544(1) Å, Z = 3). Its slabs, which are separated by van der Waals gaps, are built up from three layers of distorted [MTe6] octahedra. Crystals of Ag0.38Pb0.25Sb2.38Te4 were grown by chemical transport.

Abstract Influenza A virus (IAV) defective interfering particles (DIPs) are considered as new promising antiviral agents. Conventional DIPs (cDIPs) contain a deletion in the genome and can only replicate upon co-infection with infectious standard virus (STV), during which they suppress STV replication. We previously discovered a new type of IAV DIP “OP7” that entails genomic point mutations and displays higher antiviral efficacy than cDIPs. To avoid safety concerns for the medical use of OP7 preparations, we developed a production system that does not depend on infectious IAV. We reconstituted a mixture of DIPs consisting of cDIPs and OP7 chimera DIPs, in which both harbor a deletion in their genome. To complement the defect, the deleted viral protein is expressed by the suspension cell line used for production in shake flasks. Here, DIP preparations harvested are not contaminated with infectious virions, and the fraction of OP7 chimera DIPs depended on the multiplicity of infection. Intranasal administration of OP7 chimera DIP material was well tolerated in mice. A rescue from an otherwise lethal IAV infection and no signs of disease upon OP7 chimera DIP co-infection demonstrated the remarkable antiviral efficacy. The clinical development of this new class of broad-spectrum antiviral may contribute to pandemic preparedness.

Vertebro-vertebral fistulas (VVFs) are vascular lesions that may develop after trauma or spontaneously in association with connective tissue disorders. We present a rare case of a post-traumatic VVF in a young patient presenting with a painless swelling and a bruit in her left upper neck. Digital subtraction angiography showed an arteriovenous fistula between the left vertebral artery (VA) and the vertebral venous plexus with significant steal phenomenon. Endovascular therapy was performed using a Woven EndoBridgeTM (WEB)-device combined with coils that allowed preservation of the VA. The patient fully recovered from her symptoms and follow-up imaging showed stable occlusion. In conclusion, VVFs can be effectively treated using intrasaccular flow diverters such as the WEB-device, allowing for complete and stable occlusion while preserving the parent artery.

Prostate magnetic resonance imaging has become the imaging standard for prostate cancer in various clinical settings, with interpretation standardized according to the Prostate Imaging Reporting and Data System (PI-RADS). Each year, hundreds of scientific studies that report on the diagnostic performance of PI-RADS are published. To keep up with this ever-increasing evidence base, systematic reviews and meta-analyses are essential. As systematic reviews are highly resource-intensive, we investigated whether a machine learning framework can reduce the manual workload and speed up the screening process (title and abstract). We used search results from a living systematic review of the diagnostic performance of PI-RADS (1585 studies, of which 482 were potentially eligible after screening). A naïve Bayesian classifier was implemented in an active learning environment for classification of the titles and abstracts. Our outcome variable was the percentage of studies that can be excluded after 95% of relevant studies have been identified by the classifier (work saved over sampling: WSS@95%). In simulation runs of the entire screening process (controlling for classifier initiation and the frequency of classifier updating), we obtained a WSS@95% value of 28% (standard error of the mean ±0.1%). Applied prospectively, our classification framework would translate into a significant reduction in manual screening effort. Patient summary: Systematic reviews of scientific evidence are labor-intensive and take a lot of time. For example, many studies on prostate cancer diagnosis via MRI (magnetic resonance imaging) are published every year. We describe the use of machine learning to reduce the manual workload in screening search results. For a review of MRI for prostate cancer diagnosis, this approach reduced the screening workload by about 28%.

Abstract Ligand-gated ion channels are formed by three to five subunits that control the opening of the pore in a cooperative fashion. We developed a microfluidic chip-based technique for studying ion currents and fluorescence signals in either excised membrane patches or whole cells to measure activation and deactivation kinetics of the channels as well as ligand binding and unbinding when using confocal patch-clamp fluorometry. We show how this approach produces in a few seconds either unidirectional concentration-activation relationships at or near equilibrium and, moreover, respective time courses of activation and deactivation for a large number of freely designed steps of the ligand concentration. The short measuring period strongly minimizes the contribution of disturbing superimposing effects such as run-down phenomena and desensitization effects. To validate gating mechanisms, complex kinetic schemes are quantified without the requirement to have data at equilibrium. The new method has potential for functionally analyzing any ligand-gated ion channel and, beyond, also for other receptors.