Comparison of angiographic result and long-term outcome in patients with in-stent restenosis treated with cutting balloon or with scoring balloon angioplasty.

BACKGROUND: Lesion preparation with a cutting (CB) or scoring balloon (SB) is often used in patients with in-stent restenosis (ISR). However, there are no comparative studies. METHODS: We analyzed 81 patients (CB group: n = 38; SB group: n = 43) who had a calcified ISR from November 2019 to September 2021. The primary endpoint was strategy success (less than 20% residual stenosis); the secondary endpoints were major adverse cardiovascular events during the 1-year follow-up. Quantitative coronary angiography was performed to evaluate the strategy success. RESULTS: The patients in the CB group were more likely to have a severe calcified ISR (P = .001) and multiple stent layers (P = .001). A total of 64 patients (79.0%) reached the primary endpoint. Residual stenosis greater than 20% was more common in the CB group (39.5% vs 4.7%; P = .001). In the multivariate analysis, an effect of the intervention group on the achievement of the primary endpoint could be excluded (estimate 1.06; standard error 1.07; P = .322). The time interval of stent implantation prior to CB/SB (P = .007) and severe calcified ISR (P = .009) had a negative impact on reaching the primary endpoint. During the follow-up, there were no differences in rates of cardiac death (CB 2.5% vs. SB 1.2%; P = .598), acute myocardial infarction (CB 0% vs. SB 4.9%; P = .119), and target lesion failure (CB 3.7% vs SB 12.3%; P = .074). CONCLUSIONS: In our cohort, multivariate analysis showed that lesion preparation with CB or SB must be considered equivalent in terms of angiographic results. Factors like severe calcified ISR and the time interval of prior stent implantation negatively influenced the angiographic outcome.

Modeling brain network flexibility in networks of coupled oscillators: a feasibility study.

Modeling the functionality of the human brain is a major goal in neuroscience for which many powerful methodologies have been developed over the last decade. The impact of working memory and the associated brain regions on the brain dynamics is of particular interest due to their connection with many functions and malfunctions in the brain. In this context, the concept of brain flexibility has been developed for the characterization of brain functionality. We discuss emergence of brain flexibility that is commonly measured by the identification of changes in the cluster structure of co-active brain regions. We provide evidence that brain flexibility can be modeled by a system of coupled FitzHugh-Nagumo oscillators where the network structure is obtained from human brain Diffusion Tensor Imaging (DTI). Additionally, we propose a straightforward and computationally efficient alternative macroscopic measure, which is derived from the Pearson distance of functional brain matrices. This metric exhibits similarities to the established patterns of brain template flexibility that have been observed in prior investigations. Furthermore, we explore the significance of the brain's network structure and the strength of connections between network nodes or brain regions associated with working memory in the observation of patterns in networks flexibility. This work enriches our understanding of the interplay between the structure and function of dynamic brain networks and proposes a modeling strategy to study brain flexibility.

COPD basal cells are primed towards secretory to multiciliated cell imbalance driving increased resilience to environmental stressors.

INTRODUCTION: Environmental pollutants injure the mucociliary elevator, thereby provoking disease progression in chronic obstructive pulmonary disease (COPD). Epithelial resilience mechanisms to environmental nanoparticles in health and disease are poorly characterised. METHODS: We delineated the impact of prevalent pollutants such as carbon and zinc oxide nanoparticles, on cellular function and progeny in primary human bronchial epithelial cells (pHBECs) from end-stage COPD (COPD-IV, n=4), early disease (COPD-II, n=3) and pulmonary healthy individuals (n=4). After nanoparticle exposure of pHBECs at air-liquid interface, cell cultures were characterised by functional assays, transcriptome and protein analysis, complemented by single-cell analysis in serial samples of pHBEC cultures focusing on basal cell differentiation. RESULTS: COPD-IV was characterised by a prosecretory phenotype (twofold increase in MUC5AC+) at the expense of the multiciliated epithelium (threefold reduction in Ac-Tub+), resulting in an increased resilience towards particle-induced cell damage (fivefold reduction in transepithelial electrical resistance), as exemplified by environmentally abundant doses of zinc oxide nanoparticles. Exposure of COPD-II cultures to cigarette smoke extract provoked the COPD-IV characteristic, prosecretory phenotype. Time-resolved single-cell transcriptomics revealed an underlying COPD-IV unique basal cell state characterised by a twofold increase in KRT5+ (P=0.018) and LAMB3+ (P=0.050) expression, as well as a significant activation of Wnt-specific (P=0.014) and Notch-specific (P=0.021) genes, especially in precursors of suprabasal and secretory cells. CONCLUSION: We identified COPD stage-specific gene alterations in basal cells that affect the cellular composition of the bronchial elevator and may control disease-specific epithelial resilience mechanisms in response to environmental nanoparticles. The identified phenomena likely inform treatment and prevention strategies.

Information-theoretic analyses of neural data to minimize the effect of researchers' assumptions in predictive coding studies.

Studies investigating neural information processing often implicitly ask both, which processing strategy out of several alternatives is used and how this strategy is implemented in neural dynamics. A prime example are studies on predictive coding. These often ask whether confirmed predictions about inputs or prediction errors between internal predictions and inputs are passed on in a hierarchical neural system-while at the same time looking for the neural correlates of coding for errors and predictions. If we do not know exactly what a neural system predicts at any given moment, this results in a circular analysis-as has been criticized correctly. To circumvent such circular analysis, we propose to express information processing strategies (such as predictive coding) by local information-theoretic quantities, such that they can be estimated directly from neural data. We demonstrate our approach by investigating two opposing accounts of predictive coding-like processing strategies, where we quantify the building blocks of predictive coding, namely predictability of inputs and transfer of information, by local active information storage and local transfer entropy. We define testable hypotheses on the relationship of both quantities, allowing us to identify which of the assumed strategies was used. We demonstrate our approach on spiking data collected from the retinogeniculate synapse of the cat (N = 16). Applying our local information dynamics framework, we are able to show that the synapse codes for predictable rather than surprising input. To support our findings, we estimate quantities applied in the partial information decomposition framework, which allow to differentiate whether the transferred information is primarily bottom-up sensory input or information transferred conditionally on the current state of the synapse. Supporting our local information-theoretic results, we find that the synapse preferentially transfers bottom-up information.

Toward dynamic stability assessment of power grid topologies using graph neural networks.

To mitigate climate change, the share of renewable energies in power production needs to be increased. Renewables introduce new challenges to power grids regarding the dynamic stability due to decentralization, reduced inertia, and volatility in production. Since dynamic stability simulations are intractable and exceedingly expensive for large grids, graph neural networks (GNNs) are a promising method to reduce the computational effort of analyzing the dynamic stability of power grids. As a testbed for GNN models, we generate new, large datasets of dynamic stability of synthetic power grids and provide them as an open-source resource to the research community. We find that GNNs are surprisingly effective at predicting the highly non-linear targets from topological information only. For the first time, performance that is suitable for practical use cases is achieved. Furthermore, we demonstrate the ability of these models to accurately identify particular vulnerable nodes in power grids, so-called troublemakers. Last, we find that GNNs trained on small grids generate accurate predictions on a large synthetic model of the Texan power grid, which illustrates the potential for real-world applications.

The proteasome regulator PSME4 modulates proteasome activity and antigen diversity to abrogate antitumor immunity in NSCLC.

Immunotherapy revolutionized treatment options in cancer, yet the mechanisms underlying resistance in many patients remain poorly understood. Cellular proteasomes have been implicated in modulating antitumor immunity by regulating antigen processing, antigen presentation, inflammatory signaling and immune cell activation. However, whether and how proteasome complex heterogeneity may affect tumor progression and the response to immunotherapy has not been systematically examined. Here, we show that proteasome complex composition varies substantially across cancers and impacts tumor-immune interactions and the tumor microenvironment. Through profiling of the degradation landscape of patient-derived non-small-cell lung carcinoma samples, we find that the proteasome regulator PSME4 is upregulated in tumors, alters proteasome activity, attenuates presented antigenic diversity and associates with lack of response to immunotherapy. Collectively, our approach affords a paradigm by which proteasome composition heterogeneity and function should be examined across cancer types and targeted in the context of precision oncology.

Comparison of long-term outcome in patients with calcified stenosis treated with intravascular lithotripsy or with modified balloon angioplasty: a propensity score-adjusted study.

Background: The aim of this two-center, all-comers registry was to compare the effectiveness and safety of intravascular lithotripsy (IVL) to that of modified balloon angioplasty (MB). MB angioplasty using a cutting or scoring balloon is commonly used in patients with calcified coronary arteries. IVL is a new technology for lesion preparation. This is the first study to compare MB with IVL. Methods: The cohort included all patients treated by MB angioplasty or IVL between 2019 and 2021. The primary endpoint was strategy success (<20% residual stenosis). The secondary endpoint was long-term safety outcomes [cardiac death, acute myocardial infarction (AMI), target lesion failure/revascularization (TVR)]. Quantitative coronary angiography (QCA) was performed in all patients. Primary and secondary endpoints were compared using inverse probability of treatment weighting (IPTW) for treatment effect estimation. Results: A total of n = 86 patients were treated by IVL and n = 92 patients by MB angioplasty. The primary endpoint was reached in 152 patients (85.4%). Patients in the IVL group had less residual stenosis (5.8% vs. 22.8%; p = 0.001) in QCA. Weighted multivariable regression analysis revealed that IVL had a significant positive effect on reaching the primary endpoint of strategy success [odds ratio (OR) 24.58; 95% confidence interval (95% CI) 7.40-101.86; p = 0.001]. In addition, severe calcification was shown to result in a lower probability of achieving the primary endpoint (OR 0.08; 95% CI 0.02-0.24; p = 0.001). During the follow-up period (450 days) there was no difference in cardiovascular mortality rate [IVL (n = 5) 2.8% vs. MB (n = 3) 1.7%; p = 0.129]. Patients with unstable angina at the time of the index procedure had the highest probability of cardiovascular death [hazard ratio (HR) 7.136; 95% CI 1.248-40.802; p = 0.027]. No differences were found in long-term rates of AMI (IVL 1.7% vs. MB 2.8%; p = 0.399; IVL HR 2.73; 95% CI 0.4-17.0; p = 0.281) or TVR (IVL 5.6% vs. MB 9%; p = 0.186; IVL HR 0.78; 95% CI 0.277-2.166; p = 0.626). Conclusion: IVL leads to a significantly better angiographic intervention outcome compared to MB angioplasty in our cohort. During long-term follow-up, no differences in cardiovascular mortality, rate of acute myocardial infarction, or target lesion failure/revascularization were observed.

Non-Oncogene Addiction of KRAS-Mutant Cancers to IL-1ß via Versican and Mononuclear IKKß.

Kirsten rat sarcoma virus (KRAS)-mutant cancers are frequent, metastatic, lethal, and largely undruggable. While interleukin (IL)-1ß and nuclear factor (NF)-κB inhibition hold promise against cancer, untargeted treatments are not effective. Here, we show that human KRAS-mutant cancers are addicted to IL-1ß via inflammatory versican signaling to macrophage inhibitor of NF-κB kinase (IKK) ß. Human pan-cancer and experimental NF-κB reporter, transcriptome, and proteome screens reveal that KRAS-mutant tumors trigger macrophage IKKß activation and IL-1ß release via secretory versican. Tumor-specific versican silencing and macrophage-restricted IKKß deletion prevents myeloid NF-κB activation and metastasis. Versican and IKKß are mutually addicted and/or overexpressed in human cancers and possess diagnostic and prognostic power. Non-oncogene KRAS/IL-1ß addiction is abolished by IL-1ß and TLR1/2 inhibition, indicating cardinal and actionable roles for versican and IKKß in metastasis.

Bronchoscopic Probe-Based Confocal Laser Endomicroscopy to Diagnose Diffuse Parenchymal Lung Diseases.

Background: Diagnosis of diffuse parenchymal lung disease (DPLD) is based on clinical evaluation, radiological imaging and histology. However, additional techniques are warranted to improve diagnosis. Aims and objective: Probe based confocal laser endomicroscopy (pCLE) allows real time in vivo visualisation of the alveolar compartment during bronchoscopy based on autofluorescence of elastic fibres. We used pCLE (Cellvizio®, Mauna Kea Technology. Inc, Paris, France) to characterise alveolar patterns in patients with different types of DPLD. Methods: In this pilot study we included 42 therapy naive patients (13 female, age 72.6 +/- 2.3 years), who underwent bronchoscopy for workup of DPLD. pCLE images were obtained during rigid bronchoscopy in affected lung segments according to HR-CT scan, followed by cryobiopsies in the identical area. Diagnoses were made by a multidisciplinary panel. The description of pCLE patterns was based on the degree of distortion of the hexagonal alveolar pattern, the density of alveolar structures, the presence of consolidations or loaded alveolar macrophages (AM). The assessment was performed by 2 investigators blinded for the final diagnosis. Results: The normal lung showed a typical alveolar loop pattern. In amiodarone lung disease loaded AM were predominant. COP showed characteristic focal consolidations. IPF was characterized by significant distortion and destruction, NSIP showed significant increase in density, and chronic HP presented with consolidations, mild distortion and density. Conclusion: pCLE shows potential as an adjunctive bronchoscopic imaging technique in the differential diagnosis of DPLD. Structured and quantitative analysis of the images is required.

Intrathoracic migration of a breast implant seven years after thoracotomy. A case report.

A 52-year-old woman, who had previous bilateral subpectoral breast augmentation, underwent thoracotomy for a right upper lobe pulmonary adenocarcinoma. Seven years after her thoracic surgery, the patient noticed a reduction in her right breast volume, with shortness of breath and cough. A computed tomography study of the chest revealed intrathoracic migration of her right breast implant with no sing of capsule rupture. Subsequent video-assisted thoracoscopy confirmed this diagnosis.

Validation of in vitro models for smoke exposure of primary human bronchial epithelial cells.

The bronchial epithelium is constantly challenged by inhalative insults including cigarette smoke (CS), a key risk factor for lung disease. In vitro exposure of bronchial epithelial cells using CS extract (CSE) is a widespread alternative to whole CS (wCS) exposure. However, CSE exposure protocols vary considerably between studies, precluding direct comparison of applied doses. Moreover, they are rarely validated in terms of physiological response in vivo and the relevance of the findings is often unclear. We tested six different exposure settings in primary human bronchial epithelial cells (phBECs), including five CSE protocols compared with wCS exposure. We quantified cell-delivered dose and directly compared all exposures using expression analysis of 10 well-established smoke-induced genes in bronchial epithelial cells. CSE exposure of phBECs was varied in terms of differentiation state, exposure route, duration of exposure, and dose. Gene expression was assessed by quantitative real-time PCR (qPCR) and Western Blot analysis. Cell type-specific expression of smoke-induced genes was analyzed by immunofluorescent analysis. Three surprisingly dissimilar exposure types, namely, chronic CSE treatment of differentiating phBECs, acute CSE treatment of submerged basal phBECs, and wCS exposure of differentiated phBECs performed best, resulting in significant upregulation of seven (chronic CSE) and six (acute wCS, acute submerged CSE exposure) out of 10 genes. Acute apical or basolateral exposure of differentiated phBECs with CSE was much less effective despite similar doses used. Our findings provide guidance for the design of human in vitro CS exposure models in experimental and translational lung research.

Prognostic phenotypes of early-stage lung adenocarcinoma.

BACKGROUND: Survival after curative resection of early-stage lung adenocarcinoma (LUAD) varies and prognostic biomarkers are urgently needed. METHODS: Large-format tissue samples from a prospective cohort of 200 patients with resected LUAD were immunophenotyped for cancer hallmarks TP53, NF1, CD45, PD-1, PCNA, TUNEL and FVIII, and were followed for a median of 2.34 (95% CI 1.71-3.49) years. RESULTS: Unsupervised hierarchical clustering revealed two patient subgroups with similar clinicopathological features and genotype, but with markedly different survival: "proliferative" patients (60%) with elevated TP53, NF1, CD45 and PCNA expression had 50% 5-year overall survival, while "apoptotic" patients (40%) with high TUNEL had 70% 5-year survival (hazard ratio 2.23, 95% CI 1.33-3.80; p=0.0069). Cox regression and machine learning algorithms including random forests built clinically useful models: a score to predict overall survival and a formula and nomogram to predict tumour phenotype. The distinct LUAD phenotypes were validated in The Cancer Genome Atlas and KMplotter data, and showed prognostic power supplementary to International Association for the Study of Lung Cancer tumour-node-metastasis stage and World Health Organization histologic classification. CONCLUSIONS: Two molecular subtypes of LUAD exist and their identification provides important prognostic information.

KRAS signaling in malignant pleural mesothelioma.

Malignant pleural mesothelioma (MPM) arises from mesothelial cells lining the pleural cavity of asbestos-exposed individuals and rapidly leads to death. MPM harbors loss-of-function mutations in BAP1, NF2, CDKN2A, and TP53, but isolated deletion of these genes alone in mice does not cause MPM and mouse models of the disease are sparse. Here, we show that a proportion of human MPM harbor point mutations, copy number alterations, and overexpression of KRAS with or without TP53 changes. These are likely pathogenic, since ectopic expression of mutant KRASG12D in the pleural mesothelium of conditional mice causes epithelioid MPM and cooperates with TP53 deletion to drive a more aggressive disease form with biphasic features and pleural effusions. Murine MPM cell lines derived from these tumors carry the initiating KRASG12D lesions, secondary Bap1 alterations, and human MPM-like gene expression profiles. Moreover, they are transplantable and actionable by KRAS inhibition. Our results indicate that KRAS alterations alone or in accomplice with TP53 alterations likely play an important and underestimated role in a proportion of patients with MPM, which warrants further exploration.

Phenotypic drug screening in a human fibrosis model identified a novel class of antifibrotic therapeutics.

Fibrogenic processes instigate fatal chronic diseases leading to organ failure and death. Underlying biological processes involve induced massive deposition of extracellular matrix (ECM) by aberrant fibroblasts. We subjected diseased primary human lung fibroblasts to an advanced three-dimensional phenotypic high-content assay and screened a repurposing drug library of small molecules for inhibiting ECM deposition. Fibrotic Pattern Detection by Artificial Intelligence identified tranilast as an effective inhibitor. Structure-activity relationship studies confirmed N-(2-butoxyphenyl)-3-(phenyl)acrylamides (N23Ps) as a novel and highly potent compound class. N23Ps suppressed myofibroblast transdifferentiation, ECM deposition, cellular contractility, and altered cell shapes, thus advocating a unique mode of action. Mechanistically, transcriptomics identified SMURF2 as a potential therapeutic target network. Antifibrotic activity of N23Ps was verified by proteomics in a human ex vivo tissue fibrosis disease model, suppressing profibrotic markers SERPINE1 and CXCL8. Conclusively, N23Ps are a novel class of highly potent compounds inhibiting organ fibrosis in patients.

NetworkDynamics.jl-Composing and simulating complex networks in Julia.

NetworkDynamics.jl is an easy-to-use and computationally efficient package for simulating heterogeneous dynamical systems on complex networks, written in Julia, a high-level, high-performance, dynamic programming language. By combining state-of-the-art solver algorithms from DifferentialEquations.jl with efficient data structures, NetworkDynamics.jl achieves top performance while supporting advanced features such as events, algebraic constraints, time delays, noise terms, and automatic differentiation.

Sensing and seeing associated with overlapping occipitoparietal activation in simultaneous EEG-fMRI.

The presence of a change in a visual scene can influence brain activity and behavior, even in the absence of full conscious report. It may be possible for us to sense that such a change has occurred, even if we cannot specify exactly where or what it was. Despite existing evidence from electroencephalogram (EEG) and eye-tracking data, it is still unclear how this partial level of awareness relates to functional magnetic resonance imaging (fMRI) blood oxygen level dependent (BOLD) activation. Using EEG, fMRI, and a change blindness paradigm, we found multi-modal evidence to suggest that sensing a change is distinguishable from being blind to it. Specifically, trials during which participants could detect the presence of a colour change but not identify the location of the change (sense trials), were compared to those where participants could both detect and localise the change (localise or see trials), as well as change blind trials. In EEG, late parietal positivity and N2 amplitudes were larger for localised changes only, when compared to change blindness. However, ERP-informed fMRI analysis found no voxels with activation that significantly co-varied with fluctuations in single-trial late positivity amplitudes. In fMRI, a range of visual (BA17,18), parietal (BA7,40), and mid-brain (anterior cingulate, BA24) areas showed increased fMRI BOLD activation when a change was sensed, compared to change blindness. These visual and parietal areas are commonly implicated as the storage sites of visual working memory, and we therefore argue that sensing may not be explained by a lack of stored representation of the visual display. Both seeing and sensing a change were associated with an overlapping occipitoparietal network of activation when compared to blind trials, suggesting that the quality of the visual representation, rather than the lack of one, may result in partial awareness during the change blindness paradigm.

Concurrent neuroimaging and neurostimulation reveals a causal role for dlPFC in coding of task-relevant information.

Dorsolateral prefrontal cortex (dlPFC) is proposed to drive brain-wide focus by biasing processing in favour of task-relevant information. A longstanding debate concerns whether this is achieved through enhancing processing of relevant information and/or by inhibiting irrelevant information. To address this, we applied transcranial magnetic stimulation (TMS) during fMRI, and tested for causal changes in information coding. Participants attended to one feature, whilst ignoring another feature, of a visual object. If dlPFC is necessary for facilitation, disruptive TMS should decrease coding of attended features. Conversely, if dlPFC is crucial for inhibition, TMS should increase coding of ignored features. Here, we show that TMS decreases coding of relevant information across frontoparietal cortex, and the impact is significantly stronger than any effect on irrelevant information, which is not statistically detectable. This provides causal evidence for a specific role of dlPFC in enhancing task-relevant representations and demonstrates the cognitive-neural insights possible with concurrent TMS-fMRI-MVPA.

Integrative analysis of cell state changes in lung fibrosis with peripheral protein biomarkers.

The correspondence of cell state changes in diseased organs to peripheral protein signatures is currently unknown. Here, we generated and integrated single-cell transcriptomic and proteomic data from multiple large pulmonary fibrosis patient cohorts. Integration of 233,638 single-cell transcriptomes (n = 61) across three independent cohorts enabled us to derive shifts in cell type proportions and a robust core set of genes altered in lung fibrosis for 45 cell types. Mass spectrometry analysis of lung lavage fluid (n = 124) and plasma (n = 141) proteomes identified distinct protein signatures correlated with diagnosis, lung function, and injury status. A novel SSTR2+ pericyte state correlated with disease severity and was reflected in lavage fluid by increased levels of the complement regulatory factor CFHR1. We further discovered CRTAC1 as a biomarker of alveolar type-2 epithelial cell health status in lavage fluid and plasma. Using cross-modal analysis and machine learning, we identified the cellular source of biomarkers and demonstrated that information transfer between modalities correctly predicts disease status, suggesting feasibility of clinical cell state monitoring through longitudinal sampling of body fluid proteomes.

Inhibition of LTßR signalling activates WNT-induced regeneration in lung.

Lymphotoxin ß-receptor (LTßR) signalling promotes lymphoid neogenesis and the development of tertiary lymphoid structures1,2, which are associated with severe chronic inflammatory diseases that span several organ systems3-6. How LTßR signalling drives chronic tissue damage particularly in the lung, the mechanism(s) that regulate this process, and whether LTßR blockade might be of therapeutic value have remained unclear. Here we demonstrate increased expression of LTßR ligands in adaptive and innate immune cells, enhanced non-canonical NF-κB signalling, and enriched LTßR target gene expression in lung epithelial cells from patients with smoking-associated chronic obstructive pulmonary disease (COPD) and from mice chronically exposed to cigarette smoke. Therapeutic inhibition of LTßR signalling in young and aged mice disrupted smoking-related inducible bronchus-associated lymphoid tissue, induced regeneration of lung tissue, and reverted airway fibrosis and systemic muscle wasting. Mechanistically, blockade of LTßR signalling dampened epithelial non-canonical activation of NF-κB, reduced TGFß signalling in airways, and induced regeneration by preventing epithelial cell death and activating WNT/ß-catenin signalling in alveolar epithelial progenitor cells. These findings suggest that inhibition of LTßR signalling represents a viable therapeutic option that combines prevention of tertiary lymphoid structures1 and inhibition of apoptosis with tissue-regenerative strategies.