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Undesired coupling to the surrounding environment destroys long-range correlations in quantum processors and hinders coherent evolution in the nominally available computational space. This noise is an outstanding challenge when leveraging the computation power of near-term quantum processors 1 . It has been shown that benchmarking random circuit sampling with cross-entropy benchmarking can provide an estimate of the effective size of the Hilbert space coherently available 2-8 . Nevertheless, quantum algorithms' outputs can be trivialized by noise, making them susceptible to classical computation spoofing. Here, by implementing an algorithm for random circuit sampling, we demonstrate experimentally that two phase transitions are observable with cross-entropy benchmarking, which we explain theoretically with a statistical model. The first is a dynamical transition as a function of the number of cycles and is the continuation of the anti-concentration point in the noiseless case. The second is a quantum phase transition controlled by the error per cycle; to identify it analytically and experimentally, we create a weak-link model, which allows us to vary the strength of the noise versus coherent evolution. Furthermore, by presenting a random circuit sampling experiment in the weak-noise phase with 67 qubits at 32 cycles, we demonstrate that the computational cost of our experiment is beyond the capabilities of existing classical supercomputers. Our experimental and theoretical work establishes the existence of transitions to a stable, computationally complex phase that is reachable with current quantum processors., (© 2024. The Author(s).)

Introduction: The PROSTest is a novel machine learning-based liquid biopsy assay that functions as a diagnostic and prognostic tool in prostate cancer (PCa). The algorithm outcome (scored 0-100) has a cutoff of >50 to indicate PCa. In this study, we evaluated the screening utility of the test in comparison with the commonly used PSA test., Materials and Methods: 509 men (median age: 62 [40-88]), predominantly Afro-Caribbean (n=449, 88.2 %) were enrolled in this study at a referral centre for prostatic cancer screening and management. These included 417 symptomatic patients with urinary tract (UT) problems, of which 12 were diagnosed with PCa, 53 with benign prostatic hyperplasia (BPH) and 352 were free from prostatic diseases, prior to PROSTest (Cohort 1). The remaining 92 of the 509, with relatively young age (median 49 and range 40-75 years) were screened with the PROSTest first and included 28 with UT symptoms and 64 asymptomatic but with a family history of cancer (Cohort 2). PROSTest and PSA was performed on all subjects., Results: In Cohort 1, the PROSTest was positive in 11 (91.7 %) PCa, 9 (17.0 %) of BPH, and 29 (8.2 %) of subject with UT symptoms but no disease. In Cohort 2, PROSTest was positive in 4 of 28 (14.3 %) symptomatic patients and in 5 of 64 (7.8 %) asymptomatic subjects. A total of 111 individuals (from both cohorts) were identified as "at risk" (PSA >4 ng/mL). Sixteen of 111 (14.4 %) were PROSTest-positive. Thirty-nine percent (43/111) have completed a 1-year follow-up. Of the 43 with elevated PSA, 2 out of 2 (100 %) who were also PROSTest-positive, were diagnosed with PCa., Conclusion: PROSTest is a more sensitive and specific biomarker than PSA in the diagnosis and, potentially, screening for PCa. The seemingly false positive PROSTest results in BPH or symptomatic UT require a longer follow-up of these patients., Competing Interests: Declaration of Competing Interest DR: no Conflict of interest. AH: no conflict. MK: employee of Wren Laboratories. Patent# 16/281315 (filed 2/21/2019). IAD: employee of Bering Research. Consultant for Wren Laboratories. Patent# 16/281315 (filed 2/21/2019). IMM: consultant for Novartis, Ipsen, Mallinckrodt, Nycomed, Wren Laboratories, and Wyeth. Patent# 16/281315 (filed 2/21/2019). AH: employee of Wren Laboratories., (Copyright © 2024. Published by Elsevier Ltd.)

Introduction and Objectives: Despite the huge clinical burden of MASLD, validated tools for early risk stratification are lacking, and heterogeneous disease expression and a highly variable rate of progression to clinical outcomes result in prognostic uncertainty. We aimed to investigate longitudinal electronic health record-based outcome prediction in MASLD using a state-of-the-art machine learning model., Patients and Methods: n = 940 patients with histologically-defined MASLD were used to develop a deep-learning model for all-cause mortality prediction. Patient timelines, spanning 12 years, were fully-annotated with demographic/clinical characteristics, ICD-9 and -10 codes, blood test results, prescribing data, and secondary care activity. A Transformer neural network (TNN) was trained to output concomitant probabilities of 12-, 24-, and 36-month all-cause mortality. In-sample performance was assessed using 5-fold cross-validation. Out-of-sample performance was assessed in an independent set of n = 528 MASLD patients., Results: In-sample model performance achieved AUROC curve 0.74-0.90 (95 % CI: 0.72-0.94), sensitivity 64 %-82 %, specificity 75 %-92 % and Positive Predictive Value (PPV) 94 %-98 %. Out-of-sample model validation had AUROC 0.70-0.86 (95 % CI: 0.67-0.90), sensitivity 69 %-70 %, specificity 96 %-97 % and PPV 75 %-77 %. Key predictive factors, identified using coefficients of determination, were age, presence of type 2 diabetes, and history of hospital admissions with length of stay >14 days., Conclusions: A TNN, applied to routinely-collected longitudinal electronic health records, achieved good performance in prediction of 12-, 24-, and 36-month all-cause mortality in patients with MASLD. Extrapolation of our technique to population-level data will enable scalable and accurate risk stratification to identify people most likely to benefit from anticipatory health care and personalized interventions., Competing Interests: Conflicts of interest ID and BS are employees of Bering Limited. ID is a shareholder at Bering Limited. The funder (Innovate UK) provided support in the form of salaries for authors ID and BS but did not have any additional role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript. Views expressed are those of the authors and not necessarily those of Innovate UK or Bering. IAR serves as a consultant or has received speakers’ fees from Novo Nordisk, Boehringer Ingelheim, Bayer, Roche, and Norgine. TJK serves as a consultant for or has received speakers’ fees from Resolution Therapeutics, Clinnovate Health, Perspectum, Servier Laboratories, Kynos Therapeutics, Concept Life Sciences, HistoIndex, Fibrofind, and Incyte Corporation. JAF serves as a consultant or advisory board member for Resolution Therapeutics, Kynos Therapeutics, Ipsen, River 2 Renal Corp., Stimuliver, Global Clinical Trial Partners and Guidepoint and has received research grant funding from GlaxoSmithKline, Intercept Pharmaceuticals and Genentech., (Copyright © 2024 Fundación Clínica Médica Sur, A.C. Published by Elsevier España, S.L.U. All rights reserved.)

Understanding universal aspects of quantum dynamics is an unresolved problem in statistical mechanics. In particular, the spin dynamics of the one-dimensional Heisenberg model were conjectured as to belong to the Kardar-Parisi-Zhang (KPZ) universality class based on the scaling of the infinite-temperature spin-spin correlation function. In a chain of 46 superconducting qubits, we studied the probability distribution of the magnetization transferred across the chain's center, [Formula: see text]. The first two moments of [Formula: see text] show superdiffusive behavior, a hallmark of KPZ universality. However, the third and fourth moments ruled out the KPZ conjecture and allow for evaluating other theories. Our results highlight the importance of studying higher moments in determining dynamic universality classes and provide insights into universal behavior in quantum systems.

Engineered dissipative reservoirs have the potential to steer many-body quantum systems toward correlated steady states useful for quantum simulation of high-temperature superconductivity or quantum magnetism. Using up to 49 superconducting qubits, we prepared low-energy states of the transverse-field Ising model through coupling to dissipative auxiliary qubits. In one dimension, we observed long-range quantum correlations and a ground-state fidelity of 0.86 for 18 qubits at the critical point. In two dimensions, we found mutual information that extends beyond nearest neighbors. Lastly, by coupling the system to auxiliaries emulating reservoirs with different chemical potentials, we explored transport in the quantum Heisenberg model. Our results establish engineered dissipation as a scalable alternative to unitary evolution for preparing entangled many-body states on noisy quantum processors.

Metabolic dysfunction-associated steatotic liver disease (MASLD), defined by the presence of liver steatosis together with at least one out of five cardiometabolic factors, is the most common cause of chronic liver disease worldwide, affecting around one in three people. Yet the clinical presentation of MASLD and the risk of progression to cirrhosis and adverse clinical outcomes is highly variable. It, therefore, represents both a global public health threat and a precision medicine challenge. Artificial intelligence (AI) is being investigated in MASLD to develop reproducible, quantitative, and automated methods to enhance patient stratification and to discover new biomarkers and therapeutic targets in MASLD. This review details the different applications of AI and machine learning algorithms in MASLD, particularly in analyzing electronic health record, digital pathology, and imaging data. Additionally, it also describes how specific MASLD consortia are leveraging multimodal data sources to spark research breakthroughs in the field. Using a new national-level 'data commons' (SteatoSITE) as an exemplar, the opportunities, as well as the technical challenges of large-scale databases in MASLD research, are highlighted., Competing Interests: Declaration of interests T.J.K. serves as a consultant for or has received speakers’ fees from Resolution Therapeutics, Clinnovate Health, Perspectum, Servier Laboratories, Kynos Therapeutics, and Incyte Corporation. J.A.F. serves as a consultant or advisory board member for Resolution Therapeutics, Kynos Therapeutics, Sosei Heptares, Ipsen, Redx Pharma, River 2 Renal Corp., Stimuliver, Galecto Biotech, Global Clinical Trial Partners and Guidepoint and has received research grant funding from Intercept Pharmaceuticals and Genentech. I.D. is a shareholder in Bering Limited., (Copyright © 2023 Fundación Clínica Médica Sur, A.C. Published by Elsevier España, S.L.U. All rights reserved.)

The detection of individual quanta of light is important for quantum communication, fluorescence lifetime imaging, remote sensing and more. Due to their high detection efficiency, exceptional signal-to-noise ratio and fast recovery times, superconducting-nanowire single-photon detectors (SNSPDs) have become a critical component in these applications. However, the operation of conventional SNSPDs requires costly cryocoolers. Here we report the fabrication of two types of high-temperature superconducting nanowires. We observe linear scaling of the photon count rate on the radiation power at the telecommunications wavelength of 1.5 μm and thereby reveal single-photon operation. SNSPDs made from thin flakes of Bi 2 Sr 2 CaCu 2 O 8+δ exhibit a single-photon response up to 25 K, and for SNSPDs from La 1.55 Sr 0.45 CuO 4 /La 2 CuO 4 bilayer films, this response is observed up to 8 K. While the underlying detection mechanism is not fully understood yet, our work expands the family of materials for SNSPD technology beyond the liquid helium temperature limit and suggests that even higher operation temperatures may be reached using other high-temperature superconductors., (© 2023. The Author(s), under exclusive licence to Springer Nature Limited.)

Purpose: To develop and validate a deep learning model for detection of nasogastric tube (NGT) malposition on chest radiographs and assess model impact as a clinical decision support tool for junior physicians to help determine whether feeding can be safely performed in patients (feed/do not feed)., Materials and Methods: A neural network ensemble was pretrained on 1 132 142 retrospectively collected (June 2007-August 2019) frontal chest radiographs and further fine-tuned on 7081 chest radiographs labeled by three radiologists. Clinical relevance was assessed on an independent set of 335 images. Five junior emergency medicine physicians assessed chest radiographs and made feed/do not feed decisions without and with artificial intelligence (AI)-generated NGT malposition probabilities placed above chest radiographs. Decisions from the radiologists served as ground truths. Model performance was evaluated using receiver operating characteristic analysis. Agreement between junior physician and radiologist decision was determined using the Cohen κ coefficient., Results: In the testing set, the ensemble achieved area under the receiver operating characteristic curve values of 0.82 (95% CI: 0.78, 0.86), 0.77 (95% CI: 0.71, 0.83), and 0.98 (95% CI: 0.96, 1.00) for satisfactory, malpositioned, and bronchial positions, respectively. In the clinical evaluation set, mean interreader agreement for feed/do not feed decisions among junior physicians was 0.65 ± 0.03 (SD) and 0.77 ± 0.13 without and with AI support, respectively. Mean agreement between junior physicians and radiologists was 0.53 ± 0.05 (unaided) and 0.65 ± 0.09 (AI-aided)., Conclusion: A simple classifier for NGT malposition may help junior physicians determine the safety of feeding in patients with NGTs. Keywords: Neural Networks, Feature Detection, Supervised Learning, Machine Learning Supplemental material is available for this article. Published under a CC BY 4.0 license., Competing Interests: Disclosures of conflicts of interest: I.D. Salary from Bering Limited; grant funding from Innovate UK to support salaries; support for attending meetings/travel from Innovate UK; stock/stock options from Bering Limited. R.D. No relevant relationships. B.S. No relevant relationships. J.D. Employed by NHS Greater Glasgow and Clyde as a Clinical Development Fellow (a clinical junior Doctor) while working data for this manuscript; currently employed by another NHS trust. D.G. No relevant relationships. N.H. No relevant relationships. A.S. No relevant relationships. S.R. No relevant relationships. R.G. No relevant relationships. S.P. No relevant relationships. M.H. Royal College of Radiologists, Artificial Intelligence Steering Group (no payments, three monthly meetings). D.J.L. Innovate UK funded iCAIRD., (© 2023 by the Radiological Society of North America, Inc.)

Macrophages are integral to the pathogenesis of atherosclerosis, but the contribution of distinct macrophage subsets to disease remains poorly defined. Using single cell technologies and conditional ablation via a LysM Cre+ Clec4a2 flox/DTR mouse strain, we demonstrate that the expression of the C-type lectin receptor CLEC4A2 is a distinguishing feature of vascular resident macrophages endowed with athero-protective properties. Through genetic deletion and competitive bone marrow chimera experiments, we identify CLEC4A2 as an intrinsic regulator of macrophage tissue adaptation by promoting a bias in monocyte-to-macrophage in situ differentiation towards colony stimulating factor 1 (CSF1) in vascular health and disease. During atherogenesis, CLEC4A2 deficiency results in loss of resident vascular macrophages and their homeostatic properties causing dysfunctional cholesterol metabolism and enhanced toll-like receptor triggering, exacerbating disease. Our study demonstrates that CLEC4A2 licenses monocytes to join the vascular resident macrophage pool, and that CLEC4A2-mediated macrophage homeostasis is critical to combat cardiovascular disease., (© 2022. The Author(s).)

Chest X-rays (CXRs) are the first-line investigation in patients presenting to emergency departments (EDs) with dyspnoea and are a valuable adjunct to clinical management of COVID-19 associated lung disease. Artificial intelligence (AI) has the potential to facilitate rapid triage of CXRs for further patient testing and/or isolation. In this work we develop an AI algorithm, CovIx, to differentiate normal, abnormal, non-COVID-19 pneumonia, and COVID-19 CXRs using a multicentre cohort of 293,143 CXRs. The algorithm is prospectively validated in 3289 CXRs acquired from patients presenting to ED with symptoms of COVID-19 across four sites in NHS Greater Glasgow and Clyde. CovIx achieves area under receiver operating characteristic curve for COVID-19 of 0.86, with sensitivity and F1-score up to 0.83 and 0.71 respectively, and performs on-par with four board-certified radiologists. AI-based algorithms can identify CXRs with COVID-19 associated pneumonia, as well as distinguish non-COVID pneumonias in symptomatic patients presenting to ED. Pre-trained models and inference scripts are freely available at https://github.com/beringresearch/bravecx-covid ., (© 2021. The Author(s).)

Background: The NETest is a multigene assay comprising 51 circulating neuroendocrine tumor (NET)-specific transcripts. The quotient of the 51-gene assay is based upon an ensemble of machine learning algorithms. Eight cancer hallmarks or "omes" (apoptome, epigenome, growth factor signalome, metabolome, proliferome, plurome, secretome, SSTRome) represent 29 genes. The NETest is an accurate diagnostic (>90%) test, but its prognostic utility has not been assessed. In this study, we describe the expansion of the NETest omic cluster components and demonstrate that integration amplifies NETest prognostic accuracy., Methods: Group 1: n = 222; including stable disease (SD, n = 146), progressive disease (PD, n = 76), and controls (n = 139). Group 2: NET Registry NCT02270567; n = 88; prospective samples (SD, n = 54; PD, n = 34) with up to 24 months follow-up. We used PubMed literature review, interactomic analysis, nonparametric testing, Kaplan-Meier survival curves, and χ2 analyses to inform and define the prognostic significance of NET genomic "hallmarks.", Results: 2020 analyses: In-depth analyses of 47 -NETest genes identified a further six omes: fibrosome, inflammasome, metastasome, NEDome, neurome, and TFome. Group 1 analysis: Twelve omes, excluding the inflammasome and apoptome, were significantly (p < 0.05, 2.1- to 8.2-fold) elevated compared to controls. In the PD group, seven omes (proliferome, NEDome, epigenome, SSTRome, neurome, metastasome, and fibrosome) were elevated (both expression levels and fold change >2) versus SD. Group 2 analysis: All these seven omes were upregulated. In PD, they were significantly more elevated (p < 0.02) than in SD. The septet omic expression exhibited a 69% prognostic accuracy. The NETest alone was 70.5% accurate. A low NETest (≤40) integrated with epigenome/metastasome levels was an accurate prognostic for PD (90%). A high NETest (>40) including the fibrosome/NEDome predicted PD development within 3 months (100%). Using decision tree analysis to integrate the four omes (epigenome, metastasome, fibrosome, and NEDome) with the NETest score generated an overall prognostic accuracy of 93%., Conclusions: Examination of NETest omic gene cluster analysis identified five additional clinically relevant cancer hallmarks. Identification of seven omic clusters (septet) provides a molecular pathological signature of disease progression. The integration of the quartet (epigenome, fibrosome, metastasome, NEDome) and the NETest score yielded a 93% accuracy in the prediction of future disease status., (© 2020 S. Karger AG, Basel.)

The differentiation of IL-10-producing regulatory B cells (Bregs) in response to gut-microbiota-derived signals supports the maintenance of tolerance. However, whether microbiota-derived metabolites can modulate Breg suppressive function remains unknown. Here, we demonstrate that rheumatoid arthritis (RA) patients and arthritic mice have a reduction in microbial-derived short-chain fatty acids (SCFAs) compared to healthy controls and that in mice, supplementation with the SCFA butyrate reduces arthritis severity. Butyrate supplementation suppresses arthritis in a Breg-dependent manner by increasing the level of the serotonin-derived metabolite 5-Hydroxyindole-3-acetic acid (5-HIAA), which activates the aryl-hydrocarbon receptor (AhR), a newly discovered transcriptional marker for Breg function. Thus, butyrate supplementation via AhR activation controls a molecular program that supports Breg function while inhibiting germinal center (GC) B cell and plasmablast differentiation. Our study demonstrates that butyrate supplementation may serve as a viable therapy for the amelioration of systemic autoimmune disorders., Competing Interests: Declaration of Interests The authors declare no competing interests., (Copyright © 2020 The Authors. Published by Elsevier Inc. All rights reserved.)

Chest radiography (CXR) is the most commonly used imaging modality and deep neural network (DNN) algorithms have shown promise in effective triage of normal and abnormal radiograms. Typically, DNNs require large quantities of expertly labelled training exemplars, which in clinical contexts is a major bottleneck to effective modelling, as both considerable clinical skill and time is required to produce high-quality ground truths. In this work we evaluate thirteen supervised classifiers using two large free-text corpora and demonstrate that bi-directional long short-term memory (BiLSTM) networks with attention mechanism effectively identify Normal, Abnormal, and Unclear CXR reports in internal (n = 965 manually-labelled reports, f1-score = 0.94) and external (n = 465 manually-labelled reports, f1-score = 0.90) testing sets using a relatively small number of expert-labelled training observations (n = 3,856 annotated reports). Furthermore, we introduce a general unsupervised approach that accurately distinguishes Normal and Abnormal CXR reports in a large unlabelled corpus. We anticipate that the results presented in this work can be used to automatically extract standardized clinical information from free-text CXR radiological reports, facilitating the training of clinical decision support systems for CXR triage., Competing Interests: ID and BS are employees of Bering Limited. This does not alter our adherence to PLOS ONE policies on sharing data and materials.

Purpose: There are few effective biomarkers for neuroendocrine tumors. Precision oncology strategies have provided liquid biopsies for real-time and tailored decision-making. This has led to the development of the first neuroendocrine tumor liquid biopsy (the NETest). The NETest represents a transcriptomic signature of neuroendocrine tumor (NETs) that captures tumor biology and disease activity. The data have direct clinical application in terms of identifying residual disease, disease progress and the efficacy of treatment. In this overview we assess the available published information on the metrics and clinical efficacy of the NETest., Material and Methods: Published data on the NETest have been collated and analyzed to understand the clinical application of this multianalyte biomarker in NETs., Results: NETest assay has been validated as a standardized and reproducible clinical laboratory measurement. It is not affected by demographic characteristics, or acid suppressive medication. Clinical utility of the NETest has been documented in gastroenteropancreatic, bronchopulmonary NETs, in paragangliomas and pheochromocytomas. The test facilitates accurate diagnosis of a NET disease, and real-time monitoring of the disease status (stable/progressive disease). It predicts aggressive tumor behavior, identifies operative tumor resection, and efficacy of the medical treatment (e.g. somatostatin analogues), or peptide receptor radionuclide therapy (PRRT). NETest metrics and clinical applications out-perform standard biomarkers like chromogranin A., Conclusions: The NETest exhibits clinically competent metrics as an effective biomarker for neuroendocrine tumors. Measurement of NET transcripts in blood is a significant advance in neuroendocrine tumor management and demonstrates that blood provides a viable source to identify and monitor tumor status., Competing Interests: Declaration of competing interest Mark Kidd is an employee of Wren Laboratories. Somer Matar formerly worked at Wren Laboratories. Irvin M. Modlin and Ignat Drozdov are consultants to Wren Laboratories., (Copyright © 2020 The Authors. Published by Elsevier B.V. All rights reserved.)

In cuprate superconductors, superconductivity is accompanied by a plethora of orders and phenomena that complicate our understanding of superconductivity in these materials. Prominent in the underdoped regime, these orders weaken or vanish with overdoping. Here, we approach the superconducting phase from the more conventional overdoped side. We present angle-resolved photoemission spectroscopy studies of Bi[Formula: see text]Sr[Formula: see text]CaCu[Formula: see text]O[Formula: see text], cleaved and annealed in ozone to increase the doping all the way to the non-superconducting phase. We show that the mass renormalization in the antinodal region of the Fermi surface that possibly reflects the pairing, weakens with doping and completely disappears precisely where superconductivity disappears. This is the evidence that in the overdoped regime, superconductivity is determined primarily by the coupling strength. A doping dependence and an abrupt disappearance above the transition temperature eliminate phononic mechanism of the observed renormalization and identify the onset of spin-fluctuations as its likely origin.

Regulatory B cells (Bregs) play a critical role in the control of autoimmunity and inflammation. IL-10 production is the hallmark for the identification of Bregs. However, the molecular determinants that regulate the transcription of IL-10 and control the Breg developmental program remain unknown. Here, we demonstrate that aryl hydrocarbon receptor (AhR) regulates the differentiation and function of IL-10-producing CD19 + CD21 hi CD24 hi Bregs and limits their differentiation into B cells that contribute to inflammation. Chromatin profiling and transcriptome analyses show that loss of AhR in B cells reduces expression of IL-10 by skewing the differentiation of CD19 + CD21 hi CD24 hi B cells into a pro-inflammatory program, under Breg-inducing conditions. B cell AhR-deficient mice develop exacerbated arthritis, show significant reductions in IL-10-producing Bregs and regulatory T cells, and show an increase in T helper (Th) 1 and Th17 cells compared with B cell AhR-sufficient mice. Thus, we identify AhR as a relevant contributor to the transcriptional regulation of Breg differentiation., (Copyright © 2019 The Author(s). Published by Elsevier Inc. All rights reserved.)

Single-cell technologies offer an unprecedented opportunity to effectively characterize cellular heterogeneity in health and disease. Nevertheless, visualisation and interpretation of these multi-dimensional datasets remains a challenge. We present a novel framework, ivis, for dimensionality reduction of single-cell expression data. ivis utilizes a siamese neural network architecture that is trained using a novel triplet loss function. Results on simulated and real datasets demonstrate that ivis preserves global data structures in a low-dimensional space, adds new data points to existing embeddings using a parametric mapping function, and scales linearly to hundreds of thousands of cells. ivis is made publicly available through Python and R interfaces on https://github.com/beringresearch/ivis .

In cuprate superconductors, the doping of carriers into the parent Mott insulator induces superconductivity and various other phases whose characteristic temperatures are typically plotted versus the doping level p. In most materials, p cannot be determined from the chemical composition, but it is derived from the superconducting transition temperature, T c , using the assumption that the T c dependence on doping is universal. Here, we present angle-resolved photoemission studies of Bi 2 Sr 2 CaCu 2 O 8+δ , cleaved and annealed in vacuum or in ozone to reduce or increase the doping from the initial value corresponding to T c  = 91 K. We show that p can be determined from the underlying Fermi surfaces and that in-situ annealing allows mapping of a wide doping regime, covering the superconducting dome and the non-superconducting phase on the overdoped side. Our results show a surprisingly smooth dependence of the inferred Fermi surface with doping. In the highly overdoped regime, the superconducting gap approaches the value of 2Δ 0  = (4 ± 1)k B T c .

The neuroendocrine neoplasms test (NETest) is a multianalyte liquid biopsy that measures neuroendocrine tumor gene expression in blood. This unique signature precisely defines the biological activity of an individual tumor in real time. The assay meets the 3 critical requirements of an optimal biomarker: diagnostic accuracy, prognostic value, and predictive therapeutic assessment. NETest performance metrics are sensitivity and specificity and in head-to-head comparison are 4-fold to 10-fold more accurate than chromogranin A. NETest accurately identifies completeness of surgery and response to somatostatin analogs. Clinical registry data demonstrate significant clinical utility in watch/wait programs., (Copyright © 2018 Elsevier Inc. All rights reserved.)

The mathematical field of topology has become a framework to describe the low-energy electronic structure of crystalline solids. A typical feature of a bulk insulating three-dimensional topological crystal are conducting two-dimensional surface states. This constitutes the topological bulk-boundary correspondence. Here, we establish that the electronic structure of bismuth, an element consistently described as bulk topologically trivial, is in fact topological and follows a generalized bulk-boundary correspondence of higher-order: not the surfaces of the crystal, but its hinges host topologically protected conducting modes. These hinge modes are protected against localization by time-reversal symmetry locally, and globally by the three-fold rotational symmetry and inversion symmetry of the bismuth crystal. We support our claim theoretically and experimentally. Our theoretical analysis is based on symmetry arguments, topological indices, first-principle calculations, and the recently introduced framework of topological quantum chemistry. We provide supporting evidence from two complementary experimental techniques. With scanning-tunneling spectroscopy, we probe the unique signatures of the rotational symmetry of the one-dimensional states located at step edges of the crystal surface. With Josephson interferometry, we demonstrate their universal topological contribution to the electronic transport. Our work establishes bismuth as a higher-order topological insulator.

Background: Recurrence of pancreatic neuroendocrine tumors (pNET) after surgery is common. Strategies to detect recurrence have limitations. We investigated the role of clinical criteria and the multigene polymerase chain reaction-based NETest during post-operative follow-up of pNET., Methods: We studied 3 groups of resections: R0 with no recurrence (n = 11), R0 with recurrence (n = 12), and R1 with no recurrence (n = 12). NETest levels (>40%) were compared with chromogranin A (CgA) and clinicopathological criteria (CC; grade, lymph node metastases, size). Nonparametric, receiver operating characteristics, logistic regression, and predictive feature importance analyses were performed., Results: NETest was higher in R0 with recurrence (56 ± 8%) compared with R1 with no recurrence (39 ± 6%) and R0 with no recurrence (28 ± 6%, P < .005). NETest positively correlated with recurrence (area under the curve: 0.82), CgA was not (area under the curve: 0.51 ± 0.09). Multiple regression analysis defined factor impact as highest for NETest (P < .005) versus CC (P < .03) and CgA (P = .23). NETest gave false positive or negative recurrence in 18% using a 40% cutoff. Logistic regression modeling of CC was 83% accurate; it was 91% when the NETest was included. Combining CC and NETest was approximately 2× more effective than individual CC alone (increase in R 2 value from 43% to 80%)., Conclusions: A multigene blood test facilitates effective identification of pNET recurrence, prediction of disease relapse, and outperforms CgA., (© 2018 Wiley Periodicals, Inc.)

Objectives: The management of bronchopulmonary neuroendocrine tumours (BPNETs) is difficult, since imaging, histology and biomarkers have a limited value in diagnosis, predicting outcome and defining therapeutic efficacy. We evaluated a NET multigene blood test (NETest) to diagnose BPNETs, assess disease status and evaluate surgical resection., Methods: (i) Diagnostic cohort: BP carcinoids (n = 118)-typical carcinoid, n = 67 and atypical carcinoid, n = 51; other lung NEN (large-cell neuroendocrine carcinoma and small-cell lung carcinoma, n = 13); adenocarcinoma, (n = 26); squamous cell carcinoma (n = 23); controls (n = 90) and chronic obstructive pulmonary disease (n = 18). (ii) Surgical cohort, n = 28: BP carcinoids (n = 16: typical carcinoid 12; atypical carcinoid 4); large-cell neuroendocrine carcinoma, n = 3; lung adenocarcinoma, n = 8 and squamous cell carcinoma, n = 1. Blood sampling was performed presurgery and 30 days post-surgery. Transcript levels measured by quantitative polymerase chain reaction were calculated as activity scores (0-100% scale: normal < 14%) and compared with chromogranin A (enzyme-linked immunosorbent assay; normal <109 ng/ml)., Results: NETest was significantly elevated in carcinoids (48.7 ± 27%) versus controls (6 ± 6%, P < 0.001) with metrics: sensitivity 93%, specificity 89%, positive predictive value 92% and negative predictive value 91%. NETest differentiated progressive disease (73 ± 22%) from stable disease (36 ± 19%, P < 0.001) and R0 resections (10 ± 5%, P < 0.001, area under the curve: 0.98). Levels in chronic obstructive pulmonary disease and lung cancers were 18-24% while elevated in small-cell lung carcinoma/large-cell neuroendocrine carcinoma (59 ± 10%). In BPNETs on postoperative Day 30, NETest decreased by 60% (P < 0.001). Chromogranin A was elevated in only 40% of carcinoids and not altered by surgery., Conclusions: Blood NET gene levels accurately identified BPNETs (100%) and differentiated these from controls, benign and malignant lung disease. Progressive disease could be identified and surgical resection verified. Chromogranin A had no clinical utility. Monitoring NET transcript levels in blood will facilitate management by detecting residual tumour and identifying progressive disease., (© The Author 2017. Published by Oxford University Press on behalf of the European Association for Cardio-Thoracic Surgery. All rights reserved.)

Regulatory B cells (Breg) express high levels of CD1d that presents lipid antigens to invariant natural killer T (iNKT) cells. The function of CD1d in Breg biology and iNKT cell activity during inflammation remains unclear. Here we show, using chimeric mice, cell depletion and adoptive cell transfer, that CD1d-lipid presentation by Bregs induces iNKT cells to secrete interferon (IFN)-γ to contribute, partially, to the downregulation of T helper (Th)1 and Th17-adaptive immune responses and ameliorate experimental arthritis. Mice lacking CD1d-expressing B cells develop exacerbated disease compared to wild-type mice, and fail to respond to treatment with the prototypical iNKT cell agonist α-galactosylceramide. The absence of lipid presentation by B cells alters iNKT cell activation with disruption of metabolism regulation and cytokine responses. Thus, we identify a mechanism by which Bregs restrain excessive inflammation via lipid presentation.

No effective blood biomarker exists to detect and clinically manage bronchopulmonary (BP) neuroendocrine tumors (NET). We developed a blood-based 51 NET-specific transcript set for diagnosis and monitoring and evaluated clinical performance metrics. It accurately diagnosed the tumor and differentiated stable from progressive disease as determined by RECIST criteria. Gene expression was evaluated in: a) publicly available BPNET transcriptomes (GSE35679); b) two BPNET cell-lines; and c) BPNET tissue with paired blood ( n = 7). Blood gene expression was assessed in 194 samples including controls, benign lung diseases, malignant lung diseases and small bowel NETs. A separate validation study in 25 age- and gender-matched BPNETs/controls was performed. Gene expression measured by real-time PCR was scored (0-100%; normal: < 14%). Regression analyses, Principal Component Analysis (PCA), hierarchical clustering, Fisher's and non-parametric evaluations were undertaken. All 51 genes were identified in BPNET transcriptomes, tumor samples and cell-lines. Significant correlations were evident between paired tumor and blood (R2:0.63-0.91, p < 0.001). PCA and hierarchical clustering identified blood gene expression was significantly different between lung cancers and benign diseases, including BPNETs. Gene expression was highly correlated (R 2 : 0.91, p = 1.7 × 10- 15 ) between small bowel and BPNET. For validation, all 25 BPNETs were positive compared to 20% controls ( p < 0.0001). Scores were significantly elevated ( p < 0.0001) in BPNETs (57 ± 28%) compared to controls (4 ± 5%). BPNETs with progressive disease (85 ± 11%) exhibited higher scores than stable disease (32 ± 7%, p < 0.0001). Blood measurements accurately diagnosed bronchopulmonary carcinoids, distinguishing stable from progressive disease. This marker panel will have clinical utility as a diagnostic liquid biopsy able to define disease activity and progression in real-time., Competing Interests: CONFLICTS OF INTEREST None.

Background/aims: A key issue in gastroenteropancreatic neuroendocrine tumors (GEP-NETs) is early identification and prediction of disease progression. Clinical evaluation and imaging are limited due to the lack of sensitivity and disease indolence. We assessed the NETest as a predictive and prognostic marker of progression in a long-term follow-up study., Methods: GEP-NETs (n = 34) followed for a median 4 years (2.2-5.4) were evaluated. WHO tumor grade/stage grade 1: n = 17, grade 2: n = 14, grade 3: n = 1 (for 2, no grade was available); 31 (91%) were stage IV. Baseline and longitudinal imaging and blood biomarkers were available in all, and progression was defined per standard clinical protocols (RECIST 1.0). The NETest was measured by quantitative PCR of blood and multianalyte algorithmic analysis (disease activity scaled 0-100% with low <40% and high activity risk cutoffs >80%); chromogranin A (CgA) was measured by radioimmunoassay (normal <150 µg/l); progression-free survival (PFS) was analyzed by Cox proportional-hazard regression and Kaplan-Meier analysis., Results: At baseline, 100% were NETest positive, and CgA was elevated in 50%. The only baseline variable (Cox modeling) associated with PFS was NETest (hazard ratio = 1.022, 95% confidence interval = 1.005-1.04; p < 0.012). Using Kaplan-Meier analyses, the baseline NETest (>80%) was significantly associated (p = 0.01) with disease progression (median PFS 0.68 vs. 2.78 years with <40% levels). The NETest was more informative (96%) than CgA changes (>25%) in consistently predicting disease alterations (40%, p < 2 × 10-5, χ2 = 18). The NETest had an earlier time point change than imaging (1.02 ± 0.15 years). Baseline NETest levels >40% in stable disease were 100% prognostic of disease progression versus CgA (χ2 = 5, p < 0.03). Baseline NETest values <40% accurately (100%) predicted stability over 5 years (p = 0.05, χ2 = 3.8 vs. CgA)., Conclusion: The NETest correlated with a well-differentiated GEP-NET clinical status. The NETest has predictive and prognostic utility for GEP-NETs identifying clinically actionable alterations ∼1 year before image-based evidence of progression., (© 2016 S. Karger AG, Basel.)

The complexity of the clinical management of neuroendocrine neoplasia (NEN) is exacerbated by limitations in imaging modalities and a paucity of clinically useful biomarkers. Limitations in currently available imaging modalities reflect difficulties in measuring an intrinsically indolent disease, resolution inadequacies and inter-/intra-facility device variability and that RECIST (Response Evaluation Criteria in Solid Tumors) criteria are not optimal for NEN. Limitations of currently used biomarkers are that they are secretory biomarkers (chromogranin A, serotonin, neuron-specific enolase and pancreastatin); monoanalyte measurements; and lack sensitivity, specificity and predictive capacity. None of them meet the NIH metrics for clinical usage. A multinational, multidisciplinary Delphi consensus meeting of NEN experts (n = 33) assessed current imaging strategies and biomarkers in NEN management. Consensus (>75%) was achieved for 78% of the 142 questions. The panel concluded that morphological imaging has a diagnostic value. However, both imaging and current single-analyte biomarkers exhibit substantial limitations in measuring the disease status and predicting the therapeutic efficacy. RECIST remains suboptimal as a metric. A critical unmet need is the development of a clinico-biological tool to provide enhanced information regarding precise disease status and treatment response. The group considered that circulating RNA was better than current general NEN biomarkers and preliminary clinical data were considered promising. It was resolved that circulating multianalyte mRNA (NETest) had clinical utility in both diagnosis and monitoring disease status and therapeutic efficacy. Overall, it was concluded that a combination of tumor spatial and functional imaging with circulating transcripts (mRNA) would represent the future strategy for real-time monitoring of disease progress and therapeutic efficacy., (© 2016 The authors.)

Background: Peptide receptor radionuclide therapy (PRRT) is an effective method for treating neuroendocrine tumors (NETs). It is limited, however, in the prediction of individual tumor response and the precise and early identification of changes in tumor size. Currently, response prediction is based on somatostatin receptor expression and efficacy by morphological imaging and/or chromogranin A (CgA) measurement. The aim of this study was to assess the accuracy of circulating NET transcripts as a measure of PRRT efficacy, and moreover to identify prognostic gene clusters in pretreatment blood that could be interpolated with relevant clinical features in order to define a biological index for the tumor and a predictive quotient for PRRT efficacy., Methods: NET patients (n = 54), M: F 37:17, median age 66, bronchial: n = 13, GEP-NET: n = 35, CUP: n = 6 were treated with (177)Lu-based-PRRT (cumulative activity: 6.5-27.8 GBq, median 18.5). At baseline: 47/54 low-grade (G1/G2; bronchial typical/atypical), 31/49 (18)FDG positive and 39/54 progressive. Disease status was assessed by RECIST1.1. Transcripts were measured by real-time quantitative reverse transcription PCR (qRT-PCR) and multianalyte algorithmic analysis (NETest); CgA by enzyme-linked immunosorbent assay (ELISA). Gene cluster (GC) derivations: regulatory network, protein:protein interactome analyses., Statistical Analyses: chi-square, non-parametric measurements, multiple regression, receiver operating characteristic and Kaplan-Meier survival., Results: The disease control rate was 72 %. Median PFS was not achieved (follow-up: 1-33 months, median: 16). Only grading was associated with response (p < 0.01). At baseline, 94 % of patients were NETest-positive, while CgA was elevated in 59 %. NETest accurately (89 %, χ(2) = 27.4; p = 1.2 × 10(-7)) correlated with treatment response, while CgA was 24 % accurate. Gene cluster expression (growth-factor signalome and metabolome) had an AUC of 0.74 ± 0.08 (z-statistic = 2.92, p < 0.004) for predicting response (76 % accuracy). Combination with grading reached an AUC: 0.90 ± 0.07, irrespective of tumor origin. Circulating transcripts correlated accurately (94 %) with PRRT responders (SD+PR+CR; 97 %) vs. non-responders (91 %)., Conclusions: Blood NET transcript levels and the predictive quotient (circulating gene clusters+grading) accurately predicted PRRT efficacy. CgA was non-informative.

Canonical Wnt signaling is involved in gastric carcinogenesis. The aim of this study was to identify the link between Wnt signaling and aurora kinase A (AURKA), a target for the treatment of gastrointestinal cancers. Publicly available microarray data were used to identify phenotype-specific protein-protein interaction (PPI) subnetworks. The in silico analysis revealed a gastric cancer-specific PPI subnetwork consisting of 2745 proteins and 50,935 interactions. We focused on the link of AURKA to a Wnt-specific interaction module consisting of 92 proteins. There was a direct association of AURKA with Rac GTPase-activating protein 1 (RACGAP1), as well as with CTNBB1 (β-catenin) and CDKN1A as second-order interactors. Differential expression analysis revealed a significant downregulation of both AURKA and RACGAP1 in gastric cancer compared to noncancer controls. Biopsies from a prospective cohort of 56 patients with gastric cancer (32 intestinal type, 24 diffuse type) and 20 noncancer controls were used for validation of the identified targets. The RT-PCR data confirmed a strong correlation of AURKA and RACGAP1 gene expression both in the tumor, the tumor-adjacent and the tumor-distant mucosa. RACGAP1 in the tumor was also associated with CTNBB1 expression, and inversely associated with CDKN1A gene expression. Immunohistochemistry confirmed expression of the RACGAP1 protein in gastric cancer and the tumor-adjacent mucosa. RACGAP1 expression was not associated with tumor stage, grading, Lauren type, Helicobacter pylori infection, or age. In conclusion, AURKA is directly associated with the expression of RACGAP1, a modulator of the canonical Wnt signaling pathway., (© 2016 The Authors. Cancer Medicine published by John Wiley & Sons Ltd.)

Background: Surgery is the only curative treatment for gastroenteropancreatic neuroendocrine tumors (GEP-NETs), but the prediction of residual disease/recurrence is limited in the absence of optimal biomarkers. We examined whether a blood-based multianalyte neuroendocrine gene transcript assay (NETest) would define tumor cytoreduction and therapeutic efficacy., Methods: The NETest is a polymerase chain reaction-based analysis of 51 genes. Disease activity is scaled 0-100%; minimal <14%, low 14-47%, and high >47%. A total of 35 GEP-NETs in 2 groups were evaluated. I: after surgery (R0, n = 15; residual, n = 12); II: nonsurgery (n = 8: embolization with gel-foam alone [bland: n = 3]), transarterial chemoembolization (n = 2), and radiofrequency embolization (n = 3). Measurement (quantitative real-time-polymerase chain reaction) and chromogranin A (CgA; enzyme-linked immunosorbent assay) were undertaken preoperatively and 1 month after treatment., Results: NETest score was increased in 35 (100%) preoperatively; 14 (40%) had increased CgA (χ(2) = 30, P < 2 × 10(-8)). Resection reduced NETest from 80 ± 5% to 29% ± 5, (P < .0001). CgA decrease was insignificant (14.3 ± 1.6 U/L to 12.2 ± 1.7 U/L). NETest decreases correlated with diminished tumor volume (R(2) = 0.29, P = .03). Cytoreduction significantly reduced NETest from 82 ± 3% to 41% ± 6, P < .0001). CgA was not decreased (21.4 ± 5.5 U/L to 18.4 ± 10.1 U/L). Four (36%) of 11 R0s with increased NETest at 1 month developed positive imaging (sensitivity 100%, specificity 20%). One hundred percent (ablated group) were transcript- and image-positive., Conclusion: Blood NET transcripts delineate surgical resection/cytoreduction and facilitate identification of residual disease., (Copyright © 2016 Elsevier Inc. All rights reserved.)

Objectives: Current monoanalyte blood-based biomarkers for the diagnosis and follow-up of neuroendocrine tumors (NETs) do not achieve satisfactory metrics of sensitivity and specificity. We report the sensitivity and selectivity of the PCR-based test, the NETest, to detect tumors with reference to other benign and malignant gastrointestinal diseases., Methods: A total of 179 cases (gastrointestinal tumors: n=81; pancreatic disease: n=98) were prospectively collected and assessed using the NETest or chromogranin A (CgA) to determine metrics for detecting small intestinal and pancreatic NETs., Results: For intestinal carcinoids, the accuracy of the NETest was 93% (all NETs positive and 3 (12%) colorectal tumors were positive). CgA was positive in 80%, but 29% (n=7) of colorectal cancers were CgA positive. For pancreatic disease, the NETest accuracy was 94% (96% NETs positive, 2 (6%) of intraductal papillary mucinous neoplasms (IPMNs) were positive). The accuracy of CgA was 56% (29% of pancreatic NETs were CgA positive). Overall, the NETest was significantly more sensitive than CgA for the detection of small intestinal (area under the curve 0.98 vs. 0.75 P<0.0001) and pancreatic NETs (0.94 vs. 0.52, P<0.0001). NETest scores were elevated (P<0.05) in extensive disease and were more accurate (76-80%) than CgA levels (20-32%). The metrics of the multianalyte NETest met the performance criteria proposed by the National Institutes of Health for biomarkers, whereas CgA measurement did not., Conclusions: This study demonstrates that a blood-based multianalyte NET gene transcript measurement of well-differentiated small intestinal and pancreatic neuroendocrine tumor disease is sensitive and specific and outperforms the current monoanalyte diagnostic strategy of plasma CgA measurement.

A multianalyte algorithmic assay (MAAA) identifies circulating neuroendocrine tumor (NET) transcripts (n=51) with a sensitivity/specificity of 98%/97%. We evaluated whether blood measurements correlated with tumor tissue transcript analysis. The latter were segregated into gene clusters (GC) that defined clinical 'hallmarks' of neoplasia. A MAAA/cluster integrated algorithm (CIA) was developed as a predictive activity index to define tumor behavior and outcome. We evaluated three groups. Group 1: publically available NET transcriptome databases (n=15; GeneProfiler). Group 2: prospectively collected tumors and matched blood samples (n=22; qRT-PCR). Group 3: prospective clinical blood samples, n=159: stable disease (SD): n=111 and progressive disease (PD): n=48. Regulatory network analysis, linear modeling, principal component analysis (PCA), and receiver operating characteristic analyses were used to delineate neoplasia 'hallmarks' and assess GC predictive utility. Our results demonstrated: group 1: NET transcriptomes identified (92%) genes elevated. Group 2: 98% genes elevated by qPCR (fold change >2, P<0.05). Correlation analysis of matched blood/tumor was highly significant (R(2)=0.7, P<0.0001), and 58% of genes defined nine omic clusters (SSTRome, proliferome, signalome, metabolome, secretome, epigenome, plurome, and apoptome). Group 3: six clusters (SSTRome, proliferome, metabolome, secretome, epigenome, and plurome) differentiated SD from PD (area under the curve (AUC)=0.81). Integration with blood-algorithm amplified the AUC to 0.92±0.02 for differentiating PD and SD. The CIA defined a significantly lower SD score (34.1±2.6%) than in PD (84±2.8%, P<0.0001). In conclusion, circulating transcripts measurements reflect NET tissue values. Integration of biologically relevant GC differentiate SD from PD. Combination of GC data with the blood-algorithm predicted disease status in >92%. Blood transcript measurement predicts NET activity., (© 2015 Society for Endocrinology.)

Purpose: Precise determination of neuroendocrine tumor (NET) disease status and response to therapy remains a rate-limiting concern for disease management. This reflects limitations in biomarker specificity and resolution capacity of imaging. In order to evaluate biomarker precision and identify if combinatorial blood molecular markers and imaging could provide added diagnostic value, we assessed the concordance between (68)Ga-somatostatin analog (SSA) positron emission tomography (PET), circulating NET gene transcripts (NETest), chromogranin A (CgA), and Ki-67 in NETs., Methods: We utilized two independent patient groups with positive (68)Ga-SSA PET: data set 1 ((68)Ga-SSA PETs undertaken for peptide receptor radionuclide therapy (PRRT), as primary or salvage treatment, n = 27) and data set 2 ((68)Ga-SSA PETs performed in patients referred for initial disease staging or restaging after various therapies, n = 22). We examined the maximum standardized uptake value (SUVmax), circulating gene transcripts, CgA levels, and baseline Ki-67. Regression analyses, generalized linear modeling, and receiver-operating characteristic (ROC) analyses were undertaken to determine the strength of the relationships., Results: SUVmax measured in two centers were mathematically evaluated (regression modeling) and determined to be comparable. Of 49 patients, 47 (96 %) exhibited a positive NETest. Twenty-six (54 %) had elevated CgA (χ(2) = 20.1, p < 2.5×10(-6)). The majority (78 %) had Ki-67 < 20 %. Gene transcript scores were predictive of imaging with >95 % concordance and significantly correlated with SUVmax (R (2) = 0.31, root-mean-square error = 9.4). The genes MORF4L2 and somatostatin receptors SSTR1, 3, and 5 exhibited the highest correlation with SUVmax. Progressive disease was identified by elevated levels of a quotient of MORF4L2 expression and SUVmax [ROC-derived AUC (R (2) = 0.7, p < 0.05)]. No statistical relationship was identified between CgA and Ki-67 and no relationship with imaging parameters was evident., Conclusion: (68)Ga-SSA PET imaging parameters (SUVmax) correlated with a circulating NET transcript signature. Disease status could be predicted by an elevated quotient of gene expression (MORF4L2) and SUVmax. These observations provide the basis for further exploration of strategies that combine imaging parameters and disease-specific molecular data for the improvement of NET management.

Rationale: Matrix vesicles (MVs), secreted by vascular smooth muscle cells (VSMCs), form the first nidus for mineralization and fetuin-A, a potent circulating inhibitor of calcification, is specifically loaded into MVs. However, the processes of fetuin-A intracellular trafficking and MV biogenesis are poorly understood., Objective: The objective of this study is to investigate the regulation, and role, of MV biogenesis in VSMC calcification., Methods and Results: Alexa488-labeled fetuin-A was internalized by human VSMCs, trafficked via the endosomal system, and exocytosed from multivesicular bodies via exosome release. VSMC-derived exosomes were enriched with the tetraspanins CD9, CD63, and CD81, and their release was regulated by sphingomyelin phosphodiesterase 3. Comparative proteomics showed that VSMC-derived exosomes were compositionally similar to exosomes from other cell sources but also shared components with osteoblast-derived MVs including calcium-binding and extracellular matrix proteins. Elevated extracellular calcium was found to induce sphingomyelin phosphodiesterase 3 expression and the secretion of calcifying exosomes from VSMCs in vitro, and chemical inhibition of sphingomyelin phosphodiesterase 3 prevented VSMC calcification. In vivo, multivesicular bodies containing exosomes were observed in vessels from chronic kidney disease patients on dialysis, and CD63 was found to colocalize with calcification. Importantly, factors such as tumor necrosis factor-α and platelet derived growth factor-BB were also found to increase exosome production, leading to increased calcification of VSMCs in response to calcifying conditions., Conclusions: This study identifies MVs as exosomes and shows that factors that can increase exosome release can promote vascular calcification in response to environmental calcium stress. Modulation of the exosome release pathway may be as a novel therapeutic target for prevention., (© 2015 American Heart Association, Inc.)

Gastroenteropancreatic neuroendocrine neoplasms (GEP-NEN), considered a heterogeneous neoplasia, exhibit ill-defined pathobiology and protean symptomatology and are ubiquitous in location. They are difficult to diagnose, challenging to manage, and outcome depends on cell type, secretory product, histopathologic grading, and organ of origin. A morphologic and molecular genomic review of these lesions highlights tumor characteristics that can be used clinically, such as somatostatin-receptor expression, and confirms features that set them outside the standard neoplasia paradigm. Their unique pathobiology is useful for developing diagnostics using somatostatin-receptor targeted imaging or uptake of radiolabeled amino acids specific to secretory products or metabolism. Therapy has evolved via targeting of protein kinase B signaling or somatostatin receptors with drugs or isotopes (peptide-receptor radiotherapy). With DNA sequencing, rarely identified activating mutations confirm that tumor suppressor genes are relevant. Genomic approaches focusing on cancer-associated genes and signaling pathways likely will remain uninformative. Their uniquely dissimilar molecular profiles mean individual tumors are unlikely to be easily or uniformly targeted by therapeutics currently linked to standard cancer genetic paradigms. The prevalence of menin mutations in pancreatic NEN and P27 KIP1 mutations in small intestinal NEN represents initial steps to identifying a regulatory commonality in GEP-NEN. Transcriptional profiling and network-based analyses may define the cellular toolkit. Multianalyte diagnostic tools facilitate more accurate molecular pathologic delineations of NEN for assessing prognosis and identifying strategies for individualized patient treatment. GEP-NEN remain unique, poorly understood entities, and insight into their pathobiology and molecular mechanisms of growth and metastasis will help identify the diagnostic and therapeutic weaknesses of this neoplasia.

Purpose: Peptide receptor radionuclide therapy (PRRT) with (90)Y and (177)Lu provides objective responses in neuroendocrine tumours, and is well tolerated with moderate toxicity. We aimed to identify clinical parameters predictive of long-term renal and haematological toxicity (myelodysplastic syndrome and acute leukaemia)., Methods: Of 807 patients studied at IEO-Milan (1997-2013), 793 (98 %) received (177)Lu (278, 34.4 %), (90)Y (358, 44.4 %) or (177)Lu and (90)Y combined (157. 19.5 %), and 14 (2 %) received combinations of PRRT and other agents. Follow-up was 30 months (1-180 months). The parameters evaluated included renal risk factors, bone marrow toxicity and PRRT features. Data analysis included multiple regression, random forest feature selection, and recursive partitioning and regression trees., Results: Treatment with (90)Y and (90)Y + (177)Lu was more likely to result in nephrotoxicity than treatment with (177)Lu alone (33.6 %, 25.5 % and 13.4 % of patients, respectively; p < 0.0001). Nephrotoxicity (any grade), transient and persistent, occurred in 279 patients (34.6 %) and was severe (grade 3 + 4) in 12 (1.5 %). In only 20-27 % of any nephrotoxicity was the disease modelled by risk factors and codependent associations (p < 0.0001). Hypertension and haemoglobin toxicity were the most relevant factors. Persistent toxicity occurred in 197 patients (24.3 %). In only 22-34 % of affected patients was the disease modelled by the clinical data (p < 0.0001). Hypertension (regression coefficient 0.14, p < 0.0001) and haemoglobin toxicity (regression coefficient 0.21, p < 0.0001) were pertinent factors. Persistent toxicity was associated with shorter PRRT duration from the first to the last cycle (mean 387 vs. 658 days, p < 0.004). Myelodysplastic syndrome occurred in 2.35 % of patients (modelled by the clinical data in 30 %, p < 0.0001). Platelet toxicity grade (2.05 ± 1.2 vs. 0.58 ± 0.8, p < 0.0001) and longer PRRT duration (22.6 ± 24 vs. 15.5 ± 9 months, p = 0.01) were relevant. Acute leukaemia occurred in 1.1 % of patients (modelled by the clinical data in 18 %, p < 0.0001)., Conclusion: Identified risk factors provide a limited (<30 %) risk estimate even with target tissue dosimetry. These data strongly suggest the existence of unidentified individual susceptibilities to radiation-associated disease.

Objective: Activation of membrane receptor guanylate cyclase-C (GC-C) is implicated in gastrointestinal fluid and electrolyte balance, preservation of intestinal barrier integrity, anti-trophic effects and inhibition of pain sensation. To evaluate GC-C signaling, we examined the regulation of GC-C (GUCY2C/Gucy2c) and its endogenous ligands guanylin (GN/GUCA2A/Guca2a) and uroguanylin (UGN/GUCA2B/Guca2b) in colonic Crohn's disease (CD), ulcerative colitis (UC) and in rats with 2,4,6-Trinitrobenzene sulphonic acid (TNBS) colitis. Correlation analyses between expression of GUCA2A and GUCY2C and expression of inflammatory cytokines (IL1A, IL1B, TNFA and IFNG) were conducted. Additionally, expression of transcription factors for GUCA2A and GUCY2C, and the GC-C signaling pathway, were examined., Material and Methods: Biopsies from active UC/CD, un-inflamed UC/CD and healthy controls, and inflamed and healthy rat colon were investigated with gene expression microarray, immunohistochemistry (IHC) and in situ hybridization (ISH)., Results: GUCA2A/Guca2a, GUCA2B, GUCY2C/Gucy2c, transcription factors, as well as several cyclic guanosine-3',5'-monophosphate downstream mediators were all significantly down-regulated in both inflamed colonic inflammatory bowel disease (IBD) mucosa and TNBS colitis. Expression of GUCA2A and GUCY2C negatively correlated to expression of inflammatory cytokines. IHC and ISH confirmed microarray results for GUCA2A/Guca2a and GUCY2C/Gucy2c in inflamed samples. We identified a highly significant positive correlation between the expression of the transcription factor caudal type homeobox 2 (CDX2) and the expression of the downstream target gene GUCY2C., Conclusions: GUCA2A, GUCA2B and GUCY2C as well as several steps of the GC-C signaling pathway are down-regulated in IBD. This may have implications in IBD pathogenesis.

A critical requirement in neuroendocrine tumor (NET) management is a blood biomarker test that is sensitive, specific and reproducible. We evaluated a PCR-based 51-transcript signature to detect tumors, compared it with chromogranin A (CgA) and examined the confounding effect of proton pump inhibitors (PPIs), which cause falsely elevated CgA levels. The multigene signature was evaluated in two groups. Group 1: 125 prospectively collected NETs: gastroenteropancreatic NETs (n=91, including 42 pancreatic and 40 small intestinal), carcinoids of unknown primary (n=18) and other sites (n=16). Group 2: prospectively collected non-NET patients receiving PPIs (>1 month; dyspepsia, n=19; GERD, n=6; and pancreatitis, n=4) and 50 controls. All samples were analyzed by PCR (marker genes) and ELISA (DAKO-CgA). Sensitivity comparisons included χ(2), non-parametric measurements, and receiver operating characteristic (ROC) curves. Group 1: 123 NETs were PCR-positive (98.4%) compared with 50 (40%) CgA-positive (χ(2)=97.3, P<10(-26)). Significant differences (P<0.001) were noted between pancreas: PCR 95% vs CgA 29.2% (P<10(-9)) and small intestine: 100 vs 58% (P<10(-4)). The multigene test was elevated in all grades (G1-G3), in both local and disseminated disease, and was not normalized by somatostatin analog therapy. It was also elevated in 97% of CgA normal NETs. Group 2: PPI administration increased CgA in 83% and CgA was elevated in 26% of controls. PCR values were not elevated in either group. PCR performance metrics were as follows: sensitivity 98.4%, specificity 100%, positive predictive value 100%, negative predictive value 97.8%, and the ROC-derived area under the curve (AUC) was 0.997. These were significantly better than CgA (all metrics <60%; AUC, 0.54; Z-statistic, 10.44, P<0.0001). A 51-panel multigene blood transcript analysis is significantly more sensitive than plasma CgA for NET detection and is unaffected by acid suppression therapy., (© 2014 The authors.)

Background: Detection of neuroendocrine tumor (NET) disease progression is a key issue in determining management. Currently, assessment is by imaging (MRI/CT and Octreoscan®) and plasma Chromogranin A (CgA) measurement., Case Presentation: We report use of a NET-specific multigene PCR-derived blood transcript signature (NET Index) to assess disease and correlated CgA and gene transcripts with MRI, CT, Octreoscan®, 11C-5HTP-PET/CT and (68)Ga-DOTA-PET/CT in a patient with NET., Conclusions: Our results identify limitations in evaluating disease status by CgA and identify that a PCR-based test is more sensitive. Alteration in NET blood gene transcript levels prior to image-based tumor confirmation suggests this parameter may also have utility as an index of therapeutic efficacy.

A critical requirement in neuroendocrine tumor (NET) management is a sensitive, specific and reproducible blood biomarker test. We evaluated a PCR-based 51 transcript signature (NETest) and compared it to chromogranin A (CgA), pancreastatin (PST) and neurokinin A (NKA). The multigene signature was evaluated in two groups: i) a validation set of 40 NETs and controls and ii) a prospectively collected group of NETs (n=41, 61% small intestinal, 50% metastatic, 44% currently treated and 41 age-sex matched controls). Samples were analyzed by a two-step PCR (51 marker genes) protocol and ELISAs for CgA, PST and NKA. Sensitivity comparisons included χ(2), non-parametric measurements, ROC curves and predictive feature importance (PFAI) analyses. NETest identified 38 of 41 NETs. Performance metrics were: sensitivity 92.8%, specificity 92.8%, positive predictive value 92.8% and negative predictive value 92.8%. Single analyte ELISA metrics were: CgA 76, 59, 65, and 71%; PST 63, 56, 59, and 61% and NKA 39, 93, 84, and 60%. The AUCs (ROC analysis) were: NETest: 0.96±0.025, CgA: 0.67±0.06, PST 0.56±0.06, NKA: 0.66±0.06. NETest significantly outperformed single analyte tests (area differences: 0.284-0.403, Z-statistic 4.85-5.9, P<0.0001). PFAI analysis determined NETest had most value (69%) in diagnosis (CgA (13%), PST (9%), and NKA (9%)). Test data were consistent with the validation set (NETest >95% sensitivity and specificity, AUC =0.98 vs single analytes: 59-67% sensitivity, AUCs: 0.58-0.63). The NETest is significantly more sensitive and efficient (>93%) than single analyte assays (CgA, PST or NKA) in NET diagnosis. Blood-based multigene analytic measurement will facilitate early detection of disease recurrence and can predict therapeutic efficacy., (©  2014 Society for Endocrinology.)

Background: Tumor transcriptomes contain information of critical value to understanding the different capacities of a cell at both a physiological and pathological level. In terms of clinical relevance, they provide information regarding the cellular "toolbox" e.g., pathways associated with malignancy and metastasis or drug dependency. Exploration of this resource can therefore be leveraged as a translational tool to better manage and assess neoplastic behavior. The availability of public genome-wide expression datasets, provide an opportunity to reassess neuroendocrine tumors at a more fundamental level. We hypothesized that stringent analysis of expression profiles as well as regulatory networks of the neoplastic cell would provide novel information that facilitates further delineation of the genomic basis of small intestinal neuroendocrine tumors., Results: We re-analyzed two publically available small intestinal tumor transcriptomes using stringent quality control parameters and network-based approaches and validated expression of core secretory regulatory elements e.g., CPE, PCSK1, secretogranins, including genes involved in depolarization e.g., SCN3A, as well as transcription factors associated with neurodevelopment (NKX2-2, NeuroD1, INSM1) and glucose homeostasis (APLP1). The candidate metastasis-associated transcription factor, ST18, was highly expressed (>14-fold, p < 0.004). Genes previously associated with neoplasia, CEBPA and SDHD, were decreased in expression (-1.5 - -2, p < 0.02). Genomic interrogation indicated that intestinal tumors may consist of two different subtypes, serotonin-producing neoplasms and serotonin/substance P/tachykinin lesions. QPCR validation in an independent dataset (n = 13 neuroendocrine tumors), confirmed up-regulated expression of 87% of genes (13/15)., Conclusions: An integrated cellular transcriptomic analysis of small intestinal neuroendocrine tumors identified that they are regulated at a developmental level, have key activation of hypoxic pathways (a known regulator of malignant stem cell phenotypes) as well as activation of genes involved in apoptosis and proliferation. Further refinement of these analyses by RNAseq studies of large-scale databases will enable definition of individual master regulators and facilitate the development of novel tissue and blood-based tools to better understand diagnose and treat tumors.

Background: We have developed a PCR-based tool that measures a 51-gene panel for identification of gastroenteropancreatic (GEP) neuroendocrine neoplasms (NENs) in peripheral blood. This manuscript assesses the robustness (performance metrics) of this tool with a specific focus on the effects of individual parameters including collection, storage, acid suppressive medication [proton pump inhibitor (PPI)], age, sex, race and food on accuracy., Methods: Performance metrics were evaluated using a gold standard (mRNA derived from three individual human neuroendocrine tumor cell lines) and clinical samples using qPCR., Results: One hundred percent of the 51 transcripts were amplified in the gold standard (NEN cell line-derived mRNA) (CQ<35, average efficiency 1.94). The inter- and intra-assay variations were 1%-2%. In clinical samples, 50 of 51 targets (98%) were amplified. The inter- and intra-assay reproducibility ranged between 0.4% and 1.2%. The coefficient of variation (CV) was 5.3%. Expression of the reference gene, ALG9, was robust [low variation, low M-value, high (99.5%) PCR efficiency] and unaffected by sample processing. Test meals, long-term PPI use (>1 year), age, sex and ethnicity had no effect on the signature. Expression of two genes, ALP2 and CD59 correlated strongly with RNA integrity (R=0.72, p<0.001) and could be used to assess storage and processing., Conclusions: The 51 marker gene signature was robust and reproducible, exhibiting acceptable inter- and intra-assay metrics (<5%). Feeding, PPI intake, age, sex and ethnicity do not affect the signature. Expression levels of APLP2 and CD59 are effective surrogate markers of proper sample collection and processing.

The identification of accurate harbingers of disease status and therapeutic efficacy are critical requirements in precise diagnosis and effective management. Initially, tissue analysis was regarded as ideal but invasive strategies represent risk compared with peripheral blood sampling. Thus far, most biomarkers, whether in tissue or blood/urine, have been single analytes with varying degrees of sensitivity and specificity. Some analytes have not exhibited robust metrics or have lacked methodological rigor. Neuroendocrine disease represents an area of dire biomarker paucity since the individual biomarkers (gastrin, insulin, etc.) are not widely applicable to the diverse types of neuroendocrine neoplasia. Broad-spectrum markers such as chromogranin A have limitations in sensitivity, specificity and reproducibility. Monoanalytes cannot define the multiple variables (proliferation, metabolic activity, invasive potential, metastatic propensity) that constitute tumor growth. The restricted status of the neuroendocrine neoplasia field has resulted in a lack of comprehensive knowledge of the molecular and cellular biology of the disease, with tardy application of innovative technology. This overview examines limitations in current practice and describes contemporary viable strategies under evaluation, including the identification of novel analytes (gene transcripts, microRNA), circulating tumor cells and metabolic imaging agents that identify disease. Novel requirements are necessary to develop biomathematical algorithms for synchronous calibration of multiple molecular markers and predictive nomograms that interface biological variables to delineate disease progress or treatment efficacy. Optimally, the application of novel techniques and amalgamations of multianalyte assessment will provide a personalized molecular disease signature extrapolative of neuroendocrine neoplasia status and likelihood of progression and predictive of therapeutic opportunity.

Background: The molecular mechanisms underlying similarities and differences between physiological and pathological left ventricular hypertrophy (LVH) are of intense interest. Most previous work involved targeted analysis of individual signaling pathways or screening of transcriptomic profiles. We developed a network biology approach using genomic and proteomic data to study the molecular patterns that distinguish pathological and physiological LVH., Methods and Results: A network-based analysis using graph theory methods was undertaken on 127 genome-wide expression arrays of in vivo murine LVH. This revealed phenotype-specific pathological and physiological gene coexpression networks. Despite >1650 common genes in the 2 networks, network structure is significantly different. This is largely because of rewiring of genes that are differentially coexpressed in the 2 networks; this novel concept of differential wiring was further validated experimentally. Functional analysis of the rewired network revealed several distinct cellular pathways and gene sets. Deeper exploration was undertaken by targeted proteomic analysis of mitochondrial, myofilament, and extracellular subproteomes in pathological LVH. A notable finding was that mRNA-protein correlation was greater at the cellular pathway level than for individual loci., Conclusions: This first combined gene network and proteomic analysis of LVH reveals novel insights into the integrated pathomechanisms that distinguish pathological versus physiological phenotypes. In particular, we identify differential gene wiring as a major distinguishing feature of these phenotypes. This approach provides a platform for the investigation of potentially novel pathways in LVH and offers a freely accessible protocol (http://sites.google.com/site/cardionetworks) for similar analyses in other cardiovascular diseases.

Rationale: MicroRNAs (miRNAs), in particular miR-29b and miR-30c, have been implicated as important regulators of cardiac fibrosis., Objective: To perform a proteomics comparison of miRNA effects on extracellular matrix secretion by cardiac fibroblasts., Methods and Results: Mouse cardiac fibroblasts were transfected with pre-/anti-miR of miR-29b and miR-30c, and their conditioned medium was analyzed by mass spectrometry. miR-29b targeted a cadre of proteins involved in fibrosis, including multiple collagens, matrix metalloproteinases, and leukemia inhibitory factor, insulin-like growth factor 1, and pentraxin 3, 3 predicted targets of miR-29b. miR-29b also attenuated the cardiac fibroblast response to transforming growth factor-β. In contrast, miR-30c had little effect on extracellular matrix production but opposite effects regarding leukemia inhibitory factor and insulin-like growth factor 1. Both miRNAs indirectly affected cardiac myocytes. On transfection with pre-miR-29b, the conditioned medium of cardiac fibroblasts lost its ability to support adhesion of rat ventricular myocytes and led to a significant reduction of cardiac myocyte proteins (α-actinin, cardiac myosin-binding protein C, and cardiac troponin I). Similarly, cardiomyocytes derived from mouse embryonic stem cells atrophied under pre-miR-29 conditioned medium, whereas pre-miR-30c conditioned medium had a prohypertrophic effect. Levels of miR-29a, miR-29c, and miR-30c, but not miR-29b, were significantly reduced in a mouse model of pathological but not physiological hypertrophy. Treatment with antagomiRs to miR-29b induced excess fibrosis after aortic constriction without overt deterioration in cardiac function., Conclusions: Our proteomic analysis revealed novel molecular targets of miRNAs that are linked to a fibrogenic cardiac phenotype. Such comprehensive screening methods are essential to define the concerted actions of miRNAs in cardiovascular disease.

We describe the construction and performance of a scanning tunneling microscope capable of taking maps of the tunneling density of states with sub-atomic spatial resolution at dilution refrigerator temperatures and high (14 T) magnetic fields. The fully ultra-high vacuum system features visual access to a two-sample microscope stage at the end of a bottom-loading dilution refrigerator, which facilitates the transfer of in situ prepared tips and samples. The two-sample stage enables location of the best area of the sample under study and extends the experiment lifetime. The successful thermal anchoring of the microscope, described in detail, is confirmed through a base temperature reading of 20 mK, along with a measured electron temperature of 250 mK. Atomically resolved images, along with complementary vibration measurements, are presented to confirm the effectiveness of the vibration isolation scheme in this instrument. Finally, we demonstrate that the microscope is capable of the same level of performance as typical machines with more modest refrigeration by measuring spectroscopic maps at base temperature both at zero field and in an applied magnetic field.

We studied the cardioprotective properties of mexidol and 3-hydroxypyridine fumarate in rat model of chronic myocardial injury. We found that 3-hydroxypyridine fumarate (25 mg/kg) produced more pronounced antioxidant and cardioprotective effects than mexidol (25 mg/kg).

Gastroenteropancreatic (GEP) neuroendocrine neoplasms (NENs) are increasing in both incidence and prevalence. A delay in correct diagnosis is common for these lesions. This reflects the absence of specific blood biomarkers to detect NENs. Measurement of the neuroendocrine secretory peptide Chromogranin A (CgA) is used, but is a single value, is non-specific and assay data are highly variable. To facilitate tumor detection, we developed a multi-transcript molecular signature for PCR-based blood analysis. NEN transcripts were identified by computational analysis of 3 microarray datasets: NEN tissue (n = 15), NEN peripheral blood (n = 7), and adenocarcinoma (n = 363 tumors). The candidate gene signature was examined in 130 blood samples (NENs: n = 63) and validated in two independent sets (Set 1 [n = 115, NENs: n = 72]; Set 2 [n = 120, NENs: n = 58]). Comparison with CgA (ELISA) was undertaken in 176 samples (NENs: n = 81). 51 significantly elevated transcript markers were identified. Gene-based classifiers detected NENs in independent sets with high sensitivity (85-98%), specificity (93-97%), PPV (95-96%) and NPV (87-98%). The AUC for the NEN gene-based classifiers was 0.95-0.98 compared to 0.64 for CgA (Z-statistic 6.97-11.42, p<0.0001). Overall, the gene-based classifier was significantly (χ(2) = 12.3, p<0.0005) more accurate than CgA. In a sub-analysis, pancreatic NENs and gastrointestinal NENs could be identified with similar efficacy (79-88% sensitivity, 94% specificity), as could metastases (85%). In patients with low CgA, 91% exhibited elevated transcript markers. A panel of 51 marker genes differentiates NENs from controls with a high PPV and NPV (>90%), identifies pancreatic and gastrointestinal NENs with similar efficacy, and confirms GEP-NENs when CgA levels are low. The panel is significantly more accurate than the CgA assay. This reflects its utility to identify multiple diverse biological components of NENs. Application of this sensitive and specific PCR-based blood test to NENs will allow accurate detection of disease, and potentially define disease progress enabling monitoring of treatment efficacy.

Rationale: Vascular calcification is prevalent in the aging population, yet little is known of the mechanisms driving age-associated vascular smooth muscle cell (VSMC) phenotypic change., Objective: To investigate the role of nuclear lamina disruption, a specific hallmark of VSMC aging, in driving VSMC osteogenic differentiation., Methods and Results: Prelamin A, the unprocessed form of the nuclear lamina protein lamin A, accumulated in calcifying human VSMCs in vitro and in vivo, and its overexpression promoted VSMC osteogenic differentiation and mineralization. During VSMC aging in vitro, prelamin A accumulation occurred concomitantly with increased p16 expression and osteogenic differentiation and was associated with increased levels of DNA damage. Microarray analysis showed that DNA damage repair pathways were significantly impaired in VSMCs expressing prelamin A and that chemical inhibition and siRNA depletion of the DNA damage response kinases ataxia-telangiectasia mutated/ataxia-telangiectasia- and Rad3-related effectively blocked VSMC osteogenic differentiation and mineralization. In coculture experiments, prelamin A-expressing VSMCs induced alkaline phosphatase activity in mesenchymal progenitor cells, and this was abrogated by inhibition of ataxia-telangiectasia-mutated signaling, suggesting that DNA damage induces the secretion of pro-osteogenic factors by VSMCs. Cytokine array analysis identified several ataxia-telangiectasia mutated-dependent senescence-associated secretory phenotype factors/cytokines released by prelamin A-positive VSMCs, including the calcification regulators bone morphogenetic protein 2, osteoprotegerin, and interleukin 6., Conclusions: Prelamin A promotes VSMC calcification and aging by inducing persistent DNA damage signaling, which acts upstream of VSMC osteogenic differentiation and the senescence-associated secretory phenotype. Agents that target the DNA damage response and prelamin A toxicity may be potential therapies for the treatment of vascular calcification.

The conventional reductionist approach to cardiovascular research investigates individual candidate factors or linear signalling pathways but ignores more complex interactions in biological systems. The advent of molecular profiling technologies that focus on a global characterization of whole complements allows an exploration of the interconnectivity of pathways during pathophysiologically relevant processes, but has brought about the issue of statistical analysis and data integration. Proteins identified by differential expression as well as those in protein-protein interaction networks identified through experiments and through computational modelling techniques can be used as an initial starting point for functional analyses. In combination with other '-omics' technologies, such as transcriptomics and metabolomics, proteomics explores different aspects of disease, and the different pillars of observations facilitate the data integration in disease-specific networks. Ultimately, a systems biology approach may advance our understanding of cardiovascular disease processes at a 'biological pathway' instead of a 'single molecule' level and accelerate progress towards disease-modifying interventions.