Heterogeneous network embedding enabling accurate disease association predictions.

BackgroundIt is significant to identificate complex biological mechanisms of various diseases in biomedical research. Recently, the growing generation of tremendous amount of data in genomics, epigenomics, metagenomics, proteomics, metabolomics, nutriomics, etc., has resulted in the rise of systematic biological means of exploring complex diseases. However, the disparity between the production of the multiple data and our capability of analyzing data has been broaden gradually. Furthermore, we observe that networks can represent many of the above-mentioned data, and founded on the vector representations learned by network embedding methods, entities which are in close proximity but at present do not actually possess direct links are very likely to be related, therefore they are promising candidate subjects for biological investigation.ResultsWe incorporate six public biological databases to construct a heterogeneous biological network containing three categories of entities (i.e., genes, diseases, miRNAs) and multiple types of edges (i.e., the known relationships). To tackle the inherent heterogeneity, we develop a heterogeneous network embedding model for mapping the network into a low dimensional vector space in which the relationships between entities are preserved well. And in order to assess the effectiveness of our method, we conduct gene-disease as well as miRNA-disease associations predictions, results of which show the superiority of our novel method over several state-of-the-arts. Furthermore, many associations predicted by our method are verified in the latest real-world dataset.ConclusionsWe propose a novel heterogeneous network embedding method which can adequately take advantage of the abundant contextual information and structures of heterogeneous network. Moreover, we illustrate the performance of the proposed method on directing studies in biology, which can assist in identifying new hypotheses in biological investigation

Aggressive maneuver oriented robust actuator fault estimation of a 3-DOF helicopter prototype considering measurement noises

This paper presents a robust actuator fault estimation strategy design for a 3-DOF helicopter prototype which can be adapted to aggressive maneuvers. First, considering large pitch angle condition during flight, nonlinear coupling characteristic of the helicopter system is exploited. As the pitch angle can be measured in real time, a polytopic linear parameter-varying (LPV) model is developed for the helicopter system. Furthermore, considering measurement noises in the actual helicopter system, the dynamical model of helicopter system is modified accordingly. Then, based on the modified polytopic LPV model, a robust unknown input observer (UIO) is developed for the helicopter system to realize actuator fault estimation, in which both measurement noises and large pitch angle are considered. Robust performance of proposed fault estimation approach is guaranteed by using energy-to-energy strategy. And the observer gains are calculated by using linear matrix inequalities. Finally, based on a 3-DOF helicopter prototype, both simulations and experiments are conducted. The effects of measurement noises and large pitch angle on the fault estimation performance are sufficiently demonstrated. And effectiveness as well as advantages of the proposed observer is verified by using comparative analysis

Microwave-to-optical conversion using lithium niobate thin-film acoustic resonators

Acoustic or mechanical resonators have emerged as a promising means to mediate efficient microwave-to-optical conversion. Here, we demonstrate conversion of microwaves up to 4.5 GHz in frequency to 1500 nm wavelength light using optomechanical interactions on suspended thin-film lithium niobate. Our method uses an interdigital transducer that drives a freestanding 100 μm-long thin-film acoustic resonator to modulate light traveling in a Mach–Zehnder interferometer or racetrack cavity. The strong microwave-to-acoustic coupling offered by the transducer in conjunction with the strong photoelastic, piezoelectric, and electro-optic effects of lithium niobate allows us to achieve a half-wave voltage of Vπ = 4.6 V and Vπ = 0.77 V for the Mach–Zehnder interferometer and racetrack resonator, respectively. The acousto-optic racetrack cavity exhibits an optomechanical single-photon coupling strength of 1.1 kHz. To highlight the versatility of our system, we also demonstrate a microwave photonic link with unitary gain, which refers to a 0 dB microwave power transmission over an optical channel. Our integrated nanophotonic platform, which leverages the compelling properties of lithium niobate, could help enable efficient conversion between microwave and optical fields

Health care costs of cardiovascular disease in China: a machine learning-based cross-sectional study

BackgroundCardiovascular disease (CVD) causes substantial financial burden to patients with the condition, their households, and the healthcare system in China. Health care costs for treating patients with CVD vary significantly, but little is known about the factors associated with the cost variation. This study aims to identify and rank key determinants of health care costs in patients with CVD in China and to assess their effects on health care costs.MethodsData were from a survey of patients with CVD from 14 large tertiary grade-A general hospitals in S City, China, between 2018 and 2020. The survey included information on demographic characteristics, health conditions and comorbidities, medical service utilization, and health care costs. We used re-centered influence function regression to examine health care cost concentration, decomposing and estimating the effects of relevant factors on the distribution of costs. We also applied quantile regression forests—a machine learning approach—to identify the key factors for predicting the 10th (low), 50th (median), and 90th (high) quantiles of health care costs associated with CVD treatment.ResultsOur sample included 28,213 patients with CVD. The 10th, 50th and 90th quantiles of health care cost for patients with CVD were 6,103 CNY, 18,105 CNY, and 98,637 CNY, respectively. Patients with high health care costs were more likely to be older, male, and have a longer length of hospital stay, more comorbidities, more complex medical procedures, and emergency admissions. Higher health care costs were also associated with specific CVD types such as cardiomyopathy, heart failure, and stroke.ConclusionMachine learning methods are useful tools to identify determinants of health care costs for patients with CVD in China. Findings may help improve policymaking to alleviate the financial burden of CVD, particularly among patients with high health care costs

Microwave-to-optical conversion using lithium niobate thin-film acoustic resonators

Acoustic or mechanical resonators have emerged as a promising means to mediate efficient microwave-to-optical conversion. Here, we demonstrate conversion of microwaves up to 4.5 GHz in frequency to 1500 nm wavelength light using optomechanical interactions on suspended thin-film lithium niobate. Our method uses an interdigital transducer that drives a freestanding 100 μm-long thin-film acoustic resonator to modulate light traveling in a Mach–Zehnder interferometer or racetrack cavity. The strong microwave-to-acoustic coupling offered by the transducer in conjunction with the strong photoelastic, piezoelectric, and electro-optic effects of lithium niobate allows us to achieve a half-wave voltage of Vπ = 4.6 V and Vπ = 0.77 V for the Mach–Zehnder interferometer and racetrack resonator, respectively. The acousto-optic racetrack cavity exhibits an optomechanical single-photon coupling strength of 1.1 kHz. To highlight the versatility of our system, we also demonstrate a microwave photonic link with unitary gain, which refers to a 0 dB microwave power transmission over an optical channel. Our integrated nanophotonic platform, which leverages the compelling properties of lithium niobate, could help enable efficient conversion between microwave and optical fields

Integrated Lithium Niobate Acousto-optic Cavities for Microwave-to-optical Conversion

Using integrated acousto-optic cavities on thin-film lithium niobate, we demonstrate efficient conversion of GHz microwaves to 1.5 pm wavelength light via the piezoelectric effects and the optomechanical interactions

Integrated Lithium Niobate Acousto-optic Cavities for Microwave-to-optical Conversion

Using integrated acousto-optic cavities on thin-film lithium niobate, we demonstrate efficient conversion of GHz microwaves to 1.5 pm wavelength light via the piezoelectric effects and the optomechanical interactions

[18F]AlF-NOTA-ADH-1: A new PET molecular radiotracer for imaging of N-cadherin-positive tumors

BackgroundThe cell adhesion molecule (CAM) N-cadherin has become an important target for tumor therapy. The N-cadherin antagonist, ADH-1, exerts significant antitumor activity against N-cadherin-expressing cancers.MethodsIn this study, [18F]AlF-NOTA-ADH-1 was radiosynthesized. An in vitro cell binding test was performed, and the biodistribution and micro-PET imaging of the probe targeting N-cadherin were also studied in vivo.ResultsRadiolabeling of ADH-1 with [18F]AlF achieved a yield of up to 30% (not decay-corrected) with a radiochemical purity of >97%. The cell uptake study showed that Cy3-ADH-1 binds to SW480 cells but weakly binds to BXPC3 cells in the same concentration range. The biodistribution results demonstrated that [18F]AlF-NOTA-ADH-1 had a good tumor/muscle ratio (8.70±2.68) in patient-derived xenograft (PDX) tumor xenografts but a lower tumor/muscle ratio (1.91±0.69) in SW480 tumor xenografts and lowest tumor/muscle ratio (0.96±0.32) in BXPC3 tumor xenografts at 1 h post-injection (p.i.) These findings were in accordance with the immunohistochemistry results. The micro PET imaging results revealed good [18F]AlF-NOTA-ADH-1 tumor uptake in pancreatic cancer PDX xenografts with strong positive N-calcium expression, while lower tumor uptake in SW480 xenografts with positive expression of N-cadherin, and significantly lower tumor uptake in BXPC3 xenografts with low expression of N-cadherin, which was consistent with the biodistribution and immunohistochemistry results. The N-cadherin-specific binding of [18F]AlF-NOTA-ADH-1 was further verified by a blocking experiment involving coinjection of a non radiolabeled ADH-1 peptide, resulting in a significant reduction in tumor uptake in PDX xenografts and SW480 tumor.Conclusion[18F]AlF-NOTA-ADH-1 was successfully radiosynthesized, and Cy3-ADH-1 showed favorable N-cadherin-specific targeting ability by in vitro data. The biodistribution and microPET imaging of the probe further showed that [18F]AlF-NOTA-ADH-1 could discern different expressions of N-cadherin in tumors. Collectively, the findings demonstrated the potential of [18F]AlF-NOTA-ADH-1 as a PET imaging probe for non-invasive evaluation of the N-cadherin expression in tumors

Chronic Myeloid Leukemia Patients Sensitive and Resistant to Imatinib Treatment Show Different Metabolic Responses

The BCR-ABL tyrosine kinase inhibitor imatinib is highly effective for chronic myeloid leukemia (CML). However, some patients gradually develop resistance to imatinib, resulting in therapeutic failure. Metabonomic and genomic profiling of patients' responses to drug interventions can provide novel information about the in vivo metabolism of low-molecular-weight compounds and extend our insight into the mechanism of drug resistance. Based on a multi-platform of high-throughput metabonomics, SNP array analysis, karyotype and mutation, the metabolic phenotypes and genomic polymorphisms of CML patients and their diverse responses to imatinib were characterized. The untreated CML patients (UCML) showed different metabolic patterns from those of healthy controls, and the discriminatory metabolites suggested the perturbed metabolism of the urea cycle, tricarboxylic acid cycle, lipid metabolism, and amino acid turnover in UCML. After imatinib treatment, patients sensitive to imatinib (SCML) and patients resistant to imatinib (RCML) had similar metabolic phenotypes to those of healthy controls and UCML, respectively. SCML showed a significant metabolic response to imatinib, with marked restoration of the perturbed metabolism. Most of the metabolites characterizing CML were adjusted to normal levels, including the intermediates of the urea cycle and tricarboxylic acid cycle (TCA). In contrast, neither cytogenetic nor metabonomic analysis indicated any positive response to imatinib in RCML. We report for the first time the associated genetic and metabonomic responses of CML patients to imatinib and show that the perturbed in vivo metabolism of UCML is independent of imatinib treatment in resistant patients. Thus, metabonomics can potentially characterize patients' sensitivity or resistance to drug intervention