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  • Article
    Widiastuti W.
    Biodivers Data J. 2021;9:e76001.
    This report documents the first record of the genera Eucheilota and Mitrocomella and species Porpitaporpita and Physaliaphysalis in Bali, Indonesia, based on observed occurrences in different times and sites. The coincidence of the annual stranding of Physaliaphysalis in the east Bali and south Java coasts during the monsoon periods in Indonesia suggests a link with the upwelling events in the areas. However, more work is needed to analyse this phenomenon and study the occurrences of other Hydromedusae due to the limited data on hydrozoans in Indonesian waters. Overall, this report provides primary data to contribute to the general understanding of the biodiversity of marine organisms in Indonesia.
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  • Article
    Orieux A, Versteegh MAM, Jöns KD, Ducci S.
    Rep Prog Phys. 2017 07;80(7):076001.
    Entanglement is one of the most fascinating properties of quantum mechanical systems; when two particles are entangled the measurement of the properties of one of the two allows the properties of the other to be instantaneously known, whatever the distance separating them. In parallel with fundamental research on the foundations of quantum mechanics performed on complex experimental set-ups, we assist today with bourgeoning of quantum information technologies bound to exploit entanglement for a large variety of applications such as secure communications, metrology and computation. Among the different physical systems under investigation, those involving photonic components are likely to play a central role and in this context semiconductor materials exhibit a huge potential in terms of integration of several quantum components in miniature chips. In this article we review the recent progress in the development of semiconductor devices emitting entangled photons. We will present the physical processes allowing the generation of entanglement and the tools to characterize it; we will give an overview of major recent results of the last few years and highlight perspectives for future developments.
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  • Article
    Reed MS, Ochoa M, Tichauer KM, Weichmann A, Doyley MM, Pogue BW.
    J Biomed Opt. 2023 07;28(7):076001.
    Significance: Pancreatic cancer tumors are known to be avascular, but their neovascular capillaries are still chaotic leaky vessels. Capillary permeability could have significant value for therapy assessment, and its quantification might be possible with macroscopic imaging of indocyanine green (ICG) kinetics in tissue.
    Aim: The capacity of using standard fluorescence surgical systems for ICG kinetic imaging as a probe for capillary leakage was evaluated using a clinical surgical fluorescence imaging system, as interpreted through vascular permeability modeling.
    Approach: Xenograft pancreatic adenocarcinoma models were imaged in mice during bolus injection of ICG to capture the kinetics of uptake. Image analysis included ratiometric data, normalization, and match to theoretical modeling. Kinetic data were converted into the extraction fraction of the capillary leakage.
    Results: Pancreatic tumors were usually less fluorescent than the surrounding healthy tissues, but still the rate of tumor perfusion could be assessed to quantify capillary extraction. Model simulations showed that flow kinetics stabilized after about 1 min beyond the initial bolus injection and that the relative extraction fraction model estimates matched the experimental data of normalized uptake within the tissue. The kinetics in the time period of 1 to 2 min post-injection provided optimal differential data between AsPC1 and BxPC3 tumors, although high individual variation exists between tumors.
    Conclusions: ICG kinetic imaging during the initial leakage phase was diagnostic for quantitative vascular permeability within pancreatic tumors. Methods for autogain correction and normalized model-based interpretation allowed for quantification of extraction fraction and difference identification between tumor types in early timepoints.
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  • Article
    McLeod E, Ozcan A.
    Rep Prog Phys. 2016 07;79(7):076001.
    In the past two decades or so, there has been a renaissance of optical microscopy research and development. Much work has been done in an effort to improve the resolution and sensitivity of microscopes, while at the same time to introduce new imaging modalities, and make existing imaging systems more efficient and more accessible. In this review, we look at two particular aspects of this renaissance: computational imaging techniques and compact imaging platforms. In many cases, these aspects go hand-in-hand because the use of computational techniques can simplify the demands placed on optical hardware in obtaining a desired imaging performance. In the first main section, we cover lens-based computational imaging, in particular, light-field microscopy, structured illumination, synthetic aperture, Fourier ptychography, and compressive imaging. In the second main section, we review lensfree holographic on-chip imaging, including how images are reconstructed, phase recovery techniques, and integration with smart substrates for more advanced imaging tasks. In the third main section we describe how these and other microscopy modalities have been implemented in compact and field-portable devices, often based around smartphones. Finally, we conclude with some comments about opportunities and demand for better results, and where we believe the field is heading.
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  • Article
    Lau AK, Wong TT, Ho KK, Tang MT, Chan AC, Wei X, Lam EY, Shum HC, Wong KK, Tsia KK.
    J Biomed Opt. 2014;19(7):76001.
    Quantitative phase imaging (QPI) has been proven to be a powerful tool for label-free characterization of biological specimens. However, the imaging speed, largely limited by the image sensor technology, impedes its utility in applications where high-throughput screening and efficient big-data analysis are mandated. We here demonstrate interferometric time-stretch (iTS) microscopy for delivering ultrafast quantitative phase cellular and tissue imaging at an imaging line-scan rate >20 MHz—orders-of-magnitude faster than conventional QPI. Enabling an efficient time-stretch operation in the 1-μm wavelength window, we present an iTS microscope system for practical ultrafast QPI of fixed cells and tissue sections, as well as ultrafast flowing cells (at a flow speed of up to 8 m∕s). To the best of our knowledge, this is the first time that time-stretch imaging could reveal quantitative morphological information of cells and tissues with nanometer precision. As many parameters can be further extracted from the phase and can serve as the intrinsic biomarkers for disease diagnosis, iTS microscopy could find its niche in high-throughput and high-content cellular assays (e.g., imaging flow cytometry) as well as tissue refractometric imaging (e.g., whole-slide imaging for digital pathology).
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  • Article
    Niu J, Bastiaans KM, Ge JF, Tomar R, Jesudasan J, Raychaudhuri P, Karrer M, Kleiner R, Koelle D, Barbier A, Driessen EFC, Blanter YM, Allan MP.
    Phys Rev Lett. 2024 Feb 16;132(7):076001.
    The shot noise in tunneling experiments reflects the Poissonian nature of the tunneling process. The shot-noise power is proportional to both the magnitude of the current and the effective charge of the carrier. Shot-noise spectroscopy thus enables us, in principle, to determine the effective charge q of the charge carriers of that tunnel. This can be used to detect electron pairing in superconductors: In the normal state, the noise corresponds to single electron tunneling (q=1e), while in the paired state, the noise corresponds to q=2e. Here, we use a newly developed amplifier to reveal that in typical mesoscopic superconducting junctions, the shot noise does not reflect the signatures of pairing and instead stays at a level corresponding to q=1e. We show that transparency can control the shot noise, and this q=1e is due to the large number of tunneling channels with each having very low transparency. Our results indicate that in typical mesoscopic superconducting junctions, one should expect q=1e noise and lead to design guidelines for junctions that allow the detection of electron pairing.
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  • Article
    Liang YC, Yeh YH, Mendonça PEMF, Teh RY, Reid MD, Drummond PD.
    Rep Prog Phys. 2019 Jul;82(7):076001.
    Applications of quantum technology often require fidelities to quantify performance. These provide a fundamental yardstick for the comparison of two quantum states. While this is straightforward in the case of pure states, it is much more subtle for the more general case of mixed quantum states often found in practice. A large number of different proposals exist. In this review, we summarize the required properties of a quantum fidelity measure, and compare them, to determine which properties each of the different measures has. We show that there are large classes of measures that satisfy all the required properties of a fidelity measure, just as there are many norms of Hilbert space operators, and many measures of entropy. We compare these fidelities, with detailed proofs of their properties. We also summarize briefly the applications of these measures in teleportation, quantum memories and quantum computers, quantum communications, and quantum phase-space simulations.
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  • Article
    Fyhn EH, Brataas A, Qaiumzadeh A, Linder J.
    Phys Rev Lett. 2023 Aug 18;131(7):076001.
    Antiferromagnets have no net spin splitting on the scale of the superconducting coherence length. Despite this, antiferromagnets have been observed to suppress superconductivity in a similar way as ferromagnets, a phenomenon that still lacks a clear understanding. We find that this effect can be explained by the role of impurities in antiferromagnets. Using quasiclassical Green's functions, we study the proximity effect and critical temperature in diffusive superconductor-metallic antiferromagnet bilayers. The nonmagnetic impurities acquire an effective magnetic component in the antiferromagnet. This not only reduces the critical temperature but also separates the superconducting correlations into short-ranged and long-ranged components, similar to ferromagnetic proximity systems.
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  • Article
    Yang L, Mukamel S.
    Proc SPIE Int Soc Opt Eng. 2010;7600:76001G1-76001G9.
    Multidimensional analysis of coherent signals is commonly used in nuclear magnetic resonance to study correlations among spins. These techniques were recently extended to the femtosecond regime and applied to chemical, biological and semiconductor systems. In this work, we apply a two-dimensional correlation spectroscopy technique which employs double-quantum-coherence to investigate many-body effects in a semiconductor quantum well. The signal is detected along the direction k(1)+ k(2)- k(3), where k(1), k(2) and k(3) are the pulse wave vectors in chronological order. We show that this signal is particularly sensitive to many-body correlations which are missed by time-dependent Hartree-Fock approximation. The correlation energy of two-exciton can be probed with a very high resolution arising from a two-dimensional correlation spectrum, where two-exciton couplings spread the cross peaks along both axes of the 2D spectrum to create a characteristic highly resolved pattern. This level of detail is not available from conventional one-dimensional four-wave mixing or other two-dimensional correlation spectroscopy signals such as the photo echo (-k(1)+ k(2)+ k(3)).
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  • Article
    Ebrahimi B, Le D, Abtahi M, Dadzie AK, Rossi A, Rahimi M, Son T, Ostmo S, Campbell JP, Paul Chan RV, Yao X.
    J Biomed Opt. 2024 Jul;29(7):076001.
    Significance: Retinopathy of prematurity (ROP) poses a significant global threat to childhood vision, necessitating effective screening strategies. This study addresses the impact of color channels in fundus imaging on ROP diagnosis, emphasizing the efficacy and safety of utilizing longer wavelengths, such as red or green for enhanced depth information and improved diagnostic capabilities.
    Aim: This study aims to assess the spectral effectiveness in color fundus photography for the deep learning classification of ROP.
    Approach: A convolutional neural network end-to-end classifier was utilized for deep learning classification of normal, stage 1, stage 2, and stage 3 ROP fundus images. The classification performances with individual-color-channel inputs, i.e., red, green, and blue, and multi-color-channel fusion architectures, including early-fusion, intermediate-fusion, and late-fusion, were quantitatively compared.
    Results: For individual-color-channel inputs, similar performance was observed for green channel (88.00% accuracy, 76.00% sensitivity, and 92.00% specificity) and red channel (87.25% accuracy, 74.50% sensitivity, and 91.50% specificity), which is substantially outperforming the blue channel (78.25% accuracy, 56.50% sensitivity, and 85.50% specificity). For multi-color-channel fusion options, the early-fusion and intermediate-fusion architecture showed almost the same performance when compared to the green/red channel input, and they outperformed the late-fusion architecture.
    Conclusions: This study reveals that the classification of ROP stages can be effectively achieved using either the green or red image alone. This finding enables the exclusion of blue images, acknowledged for their increased susceptibility to light toxicity.
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  • Article
    Li Z, Szlufarska I.
    Phys Rev Lett. 2021 Feb 19;126(7):076001.
    We used density functional theory calculations to investigate the physical origin of the mechanochemical response of material interfaces. Our results show that the mechanochemical response can be decomposed into the contribution from the interface itself (deformation of interfacial bonds) and a contribution from the underlying solid. The relative contributions depend on the stiffness of these regions and the contact geometry, which affects the stress distribution within the bulk region. We demonstrate that, contrary to what is commonly assumed, the contribution to the activation volume from the elastic deformation of the surrounding bulk is significant and, in some case, may be dominant. We also show that the activation volume and the mechanochemical response of interfaces should be finite due to the effects on the stiffness and stress distribution within the near-surface bulk region. Our results indicate that the large range of activation volumes measured in the previous experiments even for the same material system might originate from the different degrees of contributions probed from the bulk vs interface.
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  • Article
    Gupta A, Zuk PJ, Stone HA.
    Phys Rev Lett. 2020 Aug 14;125(7):076001.
    The charging of electrical double layers inside a cylindrical pore has applications to supercapacitors, batteries, desalination and biosensors. The charging dynamics in the limit of thin double layers, i.e., when the double layer thickness is much smaller than the pore radius, is commonly described using an effective RC transmission line circuit. Here, we perform direct numerical simulations (DNS) of the Poisson-Nernst-Planck equations to study the double layer charging for the scenario of overlapping double layers, i.e., when the double layer thickness is comparable to the pore radius. We develop an analytical model that accurately predicts the results of DNS. Also, we construct a modified effective circuit for the overlapping double layer limit, and find that the modified circuit is identical to the RC transmission line but with different values and physical interpretation of the capacitive and resistive elements. In particular, the effective surface potential is reduced, the capacitor represents a volumetric current source, and the charging timescale is weakly dependent on the ratio of the pore radius and the double layer thickness.
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  • Article
    Lian C, Janssen M, Liu H, van Roij R.
    Phys Rev Lett. 2020 Feb 21;124(7):076001.
    The development of novel electrolytes and electrodes for supercapacitors is hindered by a gap of several orders of magnitude between experimentally measured and theoretically predicted charging time scales. Here, we propose an electrode model, containing many parallel stacked electrodes, that explains the slow charging dynamics of supercapacitors. At low applied potentials, the charging behavior of this model is described well by an equivalent circuit model. Conversely, at high potentials, charging dynamics slow down and evolve on two relaxation time scales: a generalized RC time and a diffusion time, which, interestingly, become similar for porous electrodes. The charging behavior of the stack-electrode model presented here helps to understand the charging dynamics of porous electrodes and qualitatively agrees with experimental time scales measured with porous electrodes.
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  • Article
    Honea RA, Cruchaga C, Perea RD, Saykin AJ, Burns JM, Weinberger DR, Goate AM, Alzheimer’s Disease Neuroimaging Initiative (ADNI).
    PLoS One. 2013;8(9):e76001.
    There is accumulating evidence that neurotrophins, like brain-derived neurotrophic factor (BDNF), may impact aging and Alzheimer's Disease. However, traditional genetic association studies have not found a clear relationship between BDNF and AD. Our goal was to test whether BDNF single nucleotide polymorphisms (SNPs) impact Alzheimer's Disease-related brain imaging and cognitive markers of disease. We completed an imaging genetics study on 645 Alzheimer's Disease Neuroimaging Initiative participants (ND=175, MCI=316, AD=154) who had cognitive, brain imaging, and genetics data at baseline and a subset of those with brain imaging data at two years. Samples were genotyped using the Illumina Human610-Quad BeadChip. 13 SNPs in BDNF were identified in the dataset following quality control measures (rs6265(Val66Met), rs12273363, rs11030094, rs925946, rs1050187, rs2203877, rs11030104, rs11030108, rs10835211, rs7934165, rs908867, rs1491850, rs1157459). We analyzed a subgroup of 8 SNPs that were in low linkage disequilibrium with each other. Automated brain morphometric measures were available through ADNI investigators, and we analyzed baseline cognitive scores, hippocampal and whole brain volumes, and rates of hippocampal and whole brain atrophy and rates of change in the ADAS-Cog over one and two years. Three out of eight BDNF SNPs analyzed were significantly associated with measures of cognitive decline (rs1157659, rs11030094, rs11030108). No SNPs were significantly associated with baseline brain volume measures, however six SNPs were significantly associated with hippocampal and/or whole brain atrophy over two years (rs908867, rs11030094, rs6265, rs10501087, rs1157659, rs1491850). We also found an interaction between the BDNF Val66Met SNP and age with whole brain volume. Our imaging-genetics analysis in a large dataset suggests that while BDNF genetic variation is not specifically associated with a diagnosis of AD, it appears to play a role in AD-related brain neurodegeneration.
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  • Article
    Lee HC, Ahsen OO, Liu JJ, Tsai TH, Huang Q, Mashimo H, Fujimoto JG.
    J Biomed Opt. 2017 07 01;22(7):76001.
    Radiofrequency ablation (RFA) is widely used for the eradication of dysplasia and the treatment of early stage esophageal carcinoma in patients with Barrett’s esophagus (BE). However, there are several factors, such as variation of BE epithelium (EP) thickness among individual patients and varying RFA catheter-tissue contact, which may compromise RFA efficacy. We used a high-speed optical coherence tomography (OCT) system to identify and monitor changes in the esophageal tissue architecture from RFA. Two different OCT imaging/RFA application protocols were performed using an <italic<ex vivo</italic< swine esophagus model: (1) post-RFA volumetric OCT imaging for quantitative analysis of the coagulum formation using RFA applications with different energy settings, and (2) M-mode OCT imaging for monitoring the dynamics of tissue architectural changes in real time during RFA application. Post-RFA volumetric OCT measurements showed an increase in the coagulum thickness with respect to the increasing RFA energies. Using a subset of the specimens, OCT measurements of coagulum and coagulum + residual EP thickness were shown to agree with histology, which accounted for specimen shrinkage during histological processing. In addition, we demonstrated the feasibility of OCT for real-time visualization of the architectural changes during RFA application with different energy settings. Results suggest feasibility of using OCT for RFA treatment planning and guidance.
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  • Article
    Khaksari K, Kirkpatrick SJ.
    J Biomed Opt. 2016 07 01;21(7):76001.
    Unlike laser Doppler flowmetry, there has yet to be presented a clear description of the physical variables that laser speckle contrast imaging (LSCI) is sensitive to. Herein, we present a theoretical basis for demonstrating that LSCI is sensitive to total flux and, in particular, the summation of diffusive flux and advective flux. We view LSCI from the perspective of mass transport and briefly derive the diffusion with drift equation in terms of an LSCI experiment. This equation reveals the relative sensitivity of LSCI to both diffusive flux and advective flux and, thereby, to both concentration and the ordered velocity of the scattering particles. We demonstrate this dependence through a short series of flow experiments that yield relationships between the calculated speckle contrast and the concentration of the scatterers (manifesting as changes in scattering coefficient), between speckle contrast and the velocity of the scattering fluid, and ultimately between speckle contrast and advective flux. Finally, we argue that the diffusion with drift equation can be used to support both Lorentzian and Gaussian correlation models that relate observed contrast to the movement of the scattering particles and that a weighted linear combination of these two models is likely the most appropriate model for relating speckle contrast to particle motion.
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  • Article
    Silletta EV, Tuckerman ME, Jerschow A.
    Phys Rev Lett. 2018 Aug 17;121(7):076001.
    Water exhibits numerous anomalous properties, many of which remain poorly understood. One of its intriguing behaviors is that it exhibits a temperature of maximum density (TMD) at 4 °C. We provide here new experimental evidence for hitherto unknown abrupt changes in proton transfer kinetics at the TMD. In particular, we show that the lifetime of OH^{-} ions has a maximum at this temperature, in contrast to hydronium ions. Furthermore, base-catalyzed proton transfer shows a sharp local minimum at this temperature, and activation energies change abruptly as well. The measured lifetimes agree with earlier theoretical predictions as the temperature approaches the TMD. Similar results are also found for heavy water at its own TMD. These findings point to a high propensity of forming fourfold coordinated OH^{-} solvation complexes at the TMD, underlining the asymmetry between hydroxide and hydronium transport. These results could help to further elucidate the unusual properties of water and related liquids.
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  • Article
    Devitt SJ, Munro WJ, Nemoto K.
    Rep Prog Phys. 2013 Jul;76(7):076001.
    Quantum error correction (QEC) and fault-tolerant quantum computation represent one of the most vital theoretical aspects of quantum information processing. It was well known from the early developments of this exciting field that the fragility of coherent quantum systems would be a catastrophic obstacle to the development of large-scale quantum computers. The introduction of quantum error correction in 1995 showed that active techniques could be employed to mitigate this fatal problem. However, quantum error correction and fault-tolerant computation is now a much larger field and many new codes, techniques, and methodologies have been developed to implement error correction for large-scale quantum algorithms. In response, we have attempted to summarize the basic aspects of quantum error correction and fault-tolerance, not as a detailed guide, but rather as a basic introduction. The development in this area has been so pronounced that many in the field of quantum information, specifically researchers who are new to quantum information or people focused on the many other important issues in quantum computation, have found it difficult to keep up with the general formalisms and methodologies employed in this area. Rather than introducing these concepts from a rigorous mathematical and computer science framework, we instead examine error correction and fault-tolerance largely through detailed examples, which are more relevant to experimentalists today and in the near future.
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  • Article
    Jiang L, Zhang Z, Roux P.
    JASA Express Lett. 2022 07;2(7):076001.
    Separating raypaths in a multipath shallow-water environment is a challenge due to the interferences between them and the colored noise that exists in an ocean environment, especially for two raypaths that arrive close to each other. Thus, in this paper, a three-dimensional (3D) higher-order raypath separation in an array to array configuration is proposed. Performance tests using simulation data in a multipath environment, real data obtained in an ultrasonic waveguide, and ocean shallow-water data, respectively, illustrate that the proposed algorithm achieves a higher resolution and a stronger robustness compared to the existing algorithms.
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  • Article
    Jia Y, Lin Z, He Z, Li C, Zhang Y, Wang J, Liu F, Li J, Huang K, Cao J, Gong X, Lu X, Chen S.
    Environ Health Perspect. 2023 07;131(7):76001.
    BACKGROUND: Heart failure (HF) poses a significant global disease burden. The current evidence on the impact of air pollution on HF remains inconsistent.
    OBJECTIVES: We aimed to conduct a systematic review of the literature and meta-analysis to provide a more comprehensive and multiperspective assessment of the associations between short- and long-term air pollution exposure and HF from epidemiological evidences.
    METHODS: Three databases were searched up to 31 August 2022 for studies investigating the association between air pollutants (PM2.5, PM10, NO2, SO2, CO, O3) and HF hospitalization, incidence, or mortality. A random effects model was used to derive the risk estimations. Subgroup analysis was conducted by geographical location, age of participants, outcome, study design, covered area, the methods of exposure assessment, and the length of exposure window. Sensitivity analysis and adjustment for publication bias were performed to test the robustness of the results.
    RESULTS: Of 100 studies covering 20 countries worldwide, 81 were for short-term and 19 were for long-term exposure. Almost all air pollutants were adversely associated with the risk of HF in both short- and long-term exposure studies. For short-term exposures, we found the risk of HF increased by 1.8% [relative risk (RR)=1.018, 95% confidence interval (CI): 1.011, 1.025] and 1.6% (RR=1.016, 95% CI: 1.011, 1.020) per 10-μg/m3 increment of PM2.5 and PM10, respectively. HF was also significantly associated with NO2, SO2, and CO, but not O3. Positive associations were stronger when exposure was considered over the previous 2 d (lag 0-1) rather than on the day of exposure only (lag 0). For long-term exposures, there were significant associations between several air pollutants and HF with RR (95% CI) of 1.748 (1.112, 2.747) per 10-μg/m3 increment in PM2.5, 1.212 (1.010, 1.454) per 10-μg/m3 increment in PM10, and 1.204 (1.069, 1.356) per 10-ppb increment in NO2, respectively. The adverse associations of most pollutants with HF were greater in low- and middle-income countries than in high-income countries. Sensitivity analysis demonstrated the robustness of our results.
    DISCUSSION: Available evidence highlighted adverse associations between air pollution and HF regardless of short- and long-term exposure. Air pollution is still a prevalent public health issue globally and sustained policies and actions are called for to reduce the burden of HF. https://doi.org/10.1289/EHP11506.
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