Diaphragmatic Injuries among Severely Injured Patients (ISS ≥ 16)-An Indicator of Injury Pattern and Severity of Abdominal Trauma.

Background and Objectives: Abdominal trauma among severely injured patients with an injury severity score (ISS) of 16 and above can lead to potentially life-threatening injuries that might need immediate surgical intervention. Traumatic injuries to the diaphragm (TID) are a challenging condition often accompanied by other injuries in the thoracoabdominal region. Materials and Methods: We retrospectively analyzed the occurrence and clinical course of TID among severely injured patients treated at our center between 2008 and 2019 and compared them to other groups of severely injured patients without TID. Results: Thirty-five patients with TID and a median ISS of 41 were treated in the period mentioned above. They were predominantly middle-aged men and mostly victims of blunt trauma as a consequence of motor vehicle accidents. A total of 70.6% had left-sided TID, and in 69.6%, the size of defect was larger than 10 cm. The diagnosis was made with computed tomography (CT) in 68.6% of the cases, while in 25.8%, it was made intraoperatively or delayed by a false-negative initial CT scan, and in 5.7%, an intraoperative diagnosis was made without preoperative CT imaging. Surgical repair was mostly conducted via laparotomy, performing a direct closure with continuous suture. A comparison to 191 patients that required laparotomy for abdominal injuries other than TID revealed significantly higher rates of concomitant injuries to several abdominal organs among patients suffering from TID. Compared to all other severely injured patients treated in the same period (n = 1377), patients suffering from TID had a significantly higher median ISS and a longer mean duration of hospital stay. Conclusions: Our findings show that TID can be seen as an indicator of particularly severe thoracoabdominal trauma that requires increased attention from the treatment team so as not to miss relevant concomitant injuries that require immediate intervention.

Publisher Correction: Precision and accuracy of single-molecule FRET measurements-a multi-laboratory benchmark study.

This paper was originally published under standard Springer Nature copyright. As of the date of this correction, the Analysis is available online as an open-access paper with a CC-BY license. No other part of the paper has been changed.

Precision and accuracy of single-molecule FRET measurements-a multi-laboratory benchmark study.

Single-molecule Förster resonance energy transfer (smFRET) is increasingly being used to determine distances, structures, and dynamics of biomolecules in vitro and in vivo. However, generalized protocols and FRET standards to ensure the reproducibility and accuracy of measurements of FRET efficiencies are currently lacking. Here we report the results of a comparative blind study in which 20 labs determined the FRET efficiencies (E) of several dye-labeled DNA duplexes. Using a unified, straightforward method, we obtained FRET efficiencies with s.d. between ±0.02 and ±0.05. We suggest experimental and computational procedures for converting FRET efficiencies into accurate distances, and discuss potential uncertainties in the experiment and the modeling. Our quantitative assessment of the reproducibility of intensity-based smFRET measurements and a unified correction procedure represents an important step toward the validation of distance networks, with the ultimate aim of achieving reliable structural models of biomolecular systems by smFRET-based hybrid methods.

HCC recurrence in HCV-infected patients after liver transplantation: SiLVER Study reveals benefits of sirolimus in combination with CNIs - a post-hoc analysis.

Factors affecting outcomes in liver transplant (LTx) recipients with hepatocellular carcinoma (HCC) and hepatitis C viral (HCV) infection include the choice of immunosuppression. Here, we analyzed the HCV+ subgroup of patients from the randomized controlled, international SiLVER Study. We performed a post hoc analysis of 166 HCV+ SiLVER Study patients regarding HCC outcome after LTx. Control patients (group A: n = 88) received mTOR inhibitor (mTORi)-free, calcineurin inhibitor (CNI)-based versus sirolimus-based immunosuppression (group B: n = 78). We found no significant difference regarding HCV-RNA titers between group A and B. Since no effect in group B could be due to variable sirolimus dosing, we split group B into patients receiving sirolimus-based immunosuppression + CNIs for >50% (B1; n = 44) or <50% (B2; n = 34) of the time. While there remained no difference in HCV-RNA titer between groups, HCC recurrence-free survival in group B1 (81.8%) was markedly better versus both group A (62.7%; P = 0.0136) and group B2 (64.7%; P = 0.0326); Interestingly, further subgroup analysis revealed an increase (P = 0.0012) in liver enzyme values in group B2. Taken together, in HCV-infected patients with HCC and LTx, mTORi immunosuppression + CNIs yields excellent outcomes. Unexpectedly, higher levels of liver inflammation and poorer outcomes occur with mTORi monotherapy in the HCV+ subgroup.

Conformational Dynamics of a Single Protein Monitored for 24 h at Video Rate.

We use plasmon rulers to follow the conformational dynamics of a single protein for up to 24 h at a video rate. The plasmon ruler consists of two gold nanospheres connected by a single protein linker. In our experiment, we follow the dynamics of the molecular chaperone heat shock protein 90 (Hsp90), which is known to show "open" and "closed" conformations. Our measurements confirm the previously known conformational dynamics with transition times in the second to minute time scale and reveals new dynamics on the time scale of minutes to hours. Plasmon rulers thus extend the observation bandwidth 3-4 orders of magnitude with respect to single-molecule fluorescence resonance energy transfer and enable the study of molecular dynamics with unprecedented precision.

Biomarker-guided Intervention to Prevent Acute Kidney Injury After Major Surgery: The Prospective Randomized BigpAK Study.

OBJECTIVE: To determine the impact of renal biomarker-guided implementation of the Kidney Disease Improving Global Outcomes (KDIGO) care bundle on the incidence of acute kidney injury (AKI) after major noncardiac surgery in a single-center unblinded randomized clinical trial. BACKGROUND: Early optimization of volume status and discontinuation of nephrotoxic medication before the occurrence of AKI may be the crucial step to reduce preventable AKI. METHODS: The urinary biomarker-triggered KDIGO care bundle (early optimization of fluid status, maintenance of perfusion pressure, discontinuation of nephrotoxic agents) was compared to standard intensive care unit (ICU) care in 121 patients with an increased AKI risk after major abdominal surgery that was determined by urinary biomarker (inhibitor of metalloproteinase-2 × insulin-like growth factor-binding protein 7) >0.3. Incidence of overall AKI, severity of AKI, length of stay, major kidney events at discharge, and cost effectiveness were evaluated. RESULTS: The overall stages of AKI were not statistically different between the 2 groups, but in patients with inhibitor of metalloproteinase-2 × insulin-like growth factor-binding protein 7 values of 0.3 to 2.0 a subgroup analysis demonstrated a significantly reduced incidence of AKI 13/48 (27.1%) in the intervention group compared to control 24/50 (48.0%, P = 0.03). Incidence of moderate and severe AKI (P = 0.04), incidence of creatinine increase >25% of baseline value (P = 0.01), length of ICU, and hospital stay (P = 0.04) were significantly lower in the intervention group. Intervention was associated with cost reduction. There were no significant differences regarding renal replacement therapy, in-hospital mortality, or major kidney events at hospital discharge. CONCLUSIONS: Early biomarker-based prediction of imminent AKI followed by implementation of KDIGO care bundle reduced AKI severity, postoperative creatinine increase, length of ICU, and hospital stay in patients after major noncardiac surgery.

Effects of Inhibitors on Hsp90's Conformational Dynamics, Cochaperone and Client Interactions.

The molecular chaperone and heat-shock protein Hsp90 has become a central target in anti-cancer therapy. Nevertheless, the effect of Hsp90 inhibition is still not understood at the molecular level, preventing a truly rational drug design. Here we report on the effect of the most prominent drug candidates, namely, radicicol, geldanamycin, derivatives of purine, and novobiocin, on Hsp90's characteristic conformational dynamics and the binding of three interaction partners. Unexpectedly, the global opening and closing transitions are hardly affected by Hsp90 inhibitors. Moreover, we find no significant changes in the binding of the cochaperones Aha1 and p23 nor of the model substrate Δ131Δ. This holds true for competitive and allosteric inhibitors. Therefore, direct inhibition mechanisms affecting only one molecular interaction are unlikely. We suggest that the inhibitory action observed in vivo is caused by a combination of subtle effects, which can be used in the search for novel Hsp90 inhibition mechanisms.

Cooperative Nucleotide Binding in Hsp90 and Its Regulation by Aha1.

The function of the molecular chaperone Hsp90 depends on large conformational changes, the rearrangement of local motifs, and the binding and hydrolysis of ATP. The size and complexity of the Hsp90 system impedes the detailed investigation of their interplay using standard methods. To overcome this limitation, we developed a three-color single-molecule FRET assay to study the interaction of Hsp90 with a fluorescently labeled reporter nucleotide in detail. It allows us to directly observe the cooperativity between the two nucleotide binding pockets in the protein dimer. Furthermore, our approach disentangles the protein conformation and the nucleotide binding state of Hsp90 and extracts the kinetics of the state transitions. Thereby, we can identify the kinetic causes mediating the cooperativity. We find that the presence of the first nucleotide prolongs the binding of the second nucleotide to Hsp90. In addition, we observe changes in the kinetics for both the open and the closed conformation of Hsp90 in dependence on the number of occupied nucleotide binding sites. Our analysis also reveals how the co-chaperone Aha1, known to accelerate Hsp90's ATPase activity, affects those transitions in a nucleotide-dependent and independent manner, thereby adding another layer of regulation to Hsp90.

Single-Molecule Analysis beyond Dwell Times: Demonstration and Assessment in and out of Equilibrium.

We present a simple and robust technique for extracting kinetic rate models and thermodynamic quantities from single-molecule time traces. Single-molecule analysis of complex kinetic sequences (SMACKS) is a maximum-likelihood approach that resolves all statistically relevant rates and also their uncertainties. This is achieved by optimizing one global kinetic model based on the complete data set while allowing for experimental variations between individual trajectories. In contrast to dwell-time analysis, which is the current standard method, SMACKS includes every experimental data point, not only dwell times. As a result, it works as well for long trajectories as for an equivalent set of short ones. In addition, the previous systematic overestimation of fast over slow rates is solved. We demonstrate the power of SMACKS on the kinetics of the multidomain protein Hsp90 measured by single-molecule Förster resonance energy transfer. Experiments in and out of equilibrium are analyzed and compared to simulations, shedding new light on the role of Hsp90's ATPase function. SMACKS resolves accurate rate models even if states cause indistinguishable signals. Thereby, it pushes the boundaries of single-molecule kinetics beyond those of current methods.

Discovering Process Dynamics for Scalable Perovskite Solar Cell Manufacturing with Explainable AI.

Large-area processing of perovskite semiconductor thin-films is complex and evokes unexplained variance in quality, posing a major hurdle for the commercialization of perovskite photovoltaics. Advances in scalable fabrication processes are currently limited to gradual and arbitrary trial-and-error procedures. While the in situ acquisition of photoluminescence (PL) videos has the potential to reveal important variations in the thin-film formation process, the high dimensionality of the data quickly surpasses the limits of human analysis. In response, this study leverages deep learning (DL) and explainable artificial intelligence (XAI) to discover relationships between sensor information acquired during the perovskite thin-film formation process and the resulting solar cell performance indicators, while rendering these relationships humanly understandable. The study further shows how gained insights can be distilled into actionable recommendations for perovskite thin-film processing, advancing toward industrial-scale solar cell manufacturing. This study demonstrates that XAI methods will play a critical role in accelerating energy materials science.

pyHiM: a new open-source, multi-platform software package for spatial genomics based on multiplexed DNA-FISH imaging.

Genome-wide ensemble sequencing methods improved our understanding of chromatin organization in eukaryotes but lack the ability to capture single-cell heterogeneity and spatial organization. To overcome these limitations, new imaging-based methods have emerged, giving rise to the field of spatial genomics. Here, we present pyHiM, a user-friendly python toolbox specifically designed for the analysis of multiplexed DNA-FISH data and the reconstruction of chromatin traces in individual cells. pyHiM employs a modular architecture, allowing independent execution of analysis steps and customization according to sample specificity and computing resources. pyHiM aims to facilitate the democratization and standardization of spatial genomics analysis.

Providing AI expertise as an infrastructure in academia.

Artificial intelligence (AI) is proliferating and developing faster than any domain scientist can adapt. To support the scientific enterprise in the Helmholtz association, a network of AI specialists has been set up to disseminate AI expertise as an infrastructure among domain scientists. As this effort exposes an evolutionary step in science organization in Germany, this article aspires to describe our setup, goals, and motivations. We comment on past experiences, current developments, and future ideas as we bring our expertise as an infrastructure closer to scientists across our organization. We hope that this offers a brief yet insightful view of our activities as well as inspiration for other science organizations.

Thermal Bridges on Building Rooftops.

Thermal Bridges on Building Rooftops (TBBR) is a multi-channel remote sensing dataset. It was recorded during six separate UAV fly-overs of the city center of Karlsruhe, Germany, and comprises a total of 926 high-resolution images with 6927 manually-provided thermal bridge annotations. Each image provides five channels: three color, one thermographic, and one computationally derived height map channel. The data is pre-split into training and test data subsets suitable for object detection and instance segmentation tasks. All data is organized and structured to comply with FAIR principles, i.e. being findable, accessible, interoperable, and reusable. It is publicly available and can be downloaded from the Zenodo data repository. This work provides a comprehensive data descriptor for the TBBR dataset to facilitate broad community uptake.

RNA contact prediction by data efficient deep learning.

On the path to full understanding of the structure-function relationship or even design of RNA, structure prediction would offer an intriguing complement to experimental efforts. Any deep learning on RNA structure, however, is hampered by the sparsity of labeled training data. Utilizing the limited data available, we here focus on predicting spatial adjacencies ("contact maps") as a proxy for 3D structure. Our model, BARNACLE, combines the utilization of unlabeled data through self-supervised pre-training and efficient use of the sparse labeled data through an XGBoost classifier. BARNACLE shows a considerable improvement over both the established classical baseline and a deep neural network. In order to demonstrate that our approach can be applied to tasks with similar data constraints, we show that our findings generalize to the related setting of accessible surface area prediction.

Alkyne derivatives of isocoumarins as clickable activity-based probes for serine proteases.

Activity-based probes (ABPs) have found increasing use in functional proteomics studies. Recently, ABPs that can be employed in combination with click chemistry gained particular attention due to their flexible application in vitro and in vivo. Moreover, there is a continuous need for new ABPs that target small subsets of enzymes. We here report novel clickable ABPs based on the 4-chloro-isocoumarin (IC) electrophile, a mechanism-based inhibitor scaffold that covalently binds serine proteases. We describe the synthesis of a small library of IC ABPs containing an alkyne function and a set of diverse selectivity elements. The different substituents on the IC structure determine which proteases are bound, showing good correlation with the preferred substrate preferences. The IC ABPs can detect their target proteases in a proteome background in a sensitive manner (down to 0.007% of total protein). Furthermore, we show activity-dependent and selective labeling of endogenous proteases in a tissue proteome. These ICs therefore represent a valuable extension to already existing ABPs for serine proteases and may be instrumental in future elucidation of serine protease functions.

The Impact of Space and Time on the Functional Output of the Genome.

Over the past two decades, it has become clear that the multiscale spatial and temporal organization of the genome has important implications for nuclear function. This review centers on insights gained from recent advances in light microscopy on our understanding of transcription. We discuss spatial and temporal aspects that shape nuclear order and their consequences on regulatory components, focusing on genomic scales most relevant to function. The emerging picture is that spatiotemporal constraints increase the complexity in transcriptional regulation, highlighting new challenges, such as uncertainty about how information travels from molecular factors through the genome and space to generate a functional output.

Multiple parameters shape the 3D chromatin structure of single nuclei at the doc locus in Drosophila.

The spatial organization of chromatin at the scale of topologically associating domains (TADs) and below displays large cell-to-cell variations. Up until now, how this heterogeneity in chromatin conformation is shaped by chromatin condensation, TAD insulation, and transcription has remained mostly elusive. Here, we used Hi-M, a multiplexed DNA-FISH imaging technique providing developmental timing and transcriptional status, to show that the emergence of TADs at the ensemble level partially segregates the conformational space explored by single nuclei during the early development of Drosophila embryos. Surprisingly, a substantial fraction of nuclei display strong insulation even before TADs emerge. Moreover, active transcription within a TAD leads to minor changes to the local inter- and intra-TAD chromatin conformation in single nuclei and only weakly affects insulation to the neighboring TAD. Overall, our results indicate that multiple parameters contribute to shaping the chromatin architecture of single nuclei at the TAD scale.

A blind benchmark of analysis tools to infer kinetic rate constants from single-molecule FRET trajectories.

Single-molecule FRET (smFRET) is a versatile technique to study the dynamics and function of biomolecules since it makes nanoscale movements detectable as fluorescence signals. The powerful ability to infer quantitative kinetic information from smFRET data is, however, complicated by experimental limitations. Diverse analysis tools have been developed to overcome these hurdles but a systematic comparison is lacking. Here, we report the results of a blind benchmark study assessing eleven analysis tools used to infer kinetic rate constants from smFRET trajectories. We test them against simulated and experimental data containing the most prominent difficulties encountered in analyzing smFRET experiments: different noise levels, varied model complexity, non-equilibrium dynamics, and kinetic heterogeneity. Our results highlight the current strengths and limitations in inferring kinetic information from smFRET trajectories. In addition, we formulate concrete recommendations and identify key targets for future developments, aimed to advance our understanding of biomolecular dynamics through quantitative experiment-derived models.

Cis-regulatory chromatin loops arise before TADs and gene activation, and are independent of cell fate during early Drosophila development.

Acquisition of cell fate is thought to rely on the specific interaction of remote cis-regulatory modules (CRMs), for example, enhancers and target promoters. However, the precise interplay between chromatin structure and gene expression is still unclear, particularly within multicellular developing organisms. In the present study, we employ Hi-M, a single-cell spatial genomics approach, to detect CRM-promoter looping interactions within topologically associating domains (TADs) during early Drosophila development. By comparing cis-regulatory loops in alternate cell types, we show that physical proximity does not necessarily instruct transcriptional states. Moreover, multi-way analyses reveal that multiple CRMs spatially coalesce to form hubs. Loops and CRM hubs are established early during development, before the emergence of TADs. Moreover, CRM hubs are formed, in part, via the action of the pioneer transcription factor Zelda and precede transcriptional activation. Our approach provides insight into the role of CRM-promoter interactions in defining transcriptional states, as well as distinct cell types.