Search

Radiative transfer simulations and remote sensing studies fundamentally require accurate and efficient computation of the optical properties of non-spherical particles. This paper proposes a deep learning (DL) scheme in conjunction with an optical property database to achieve this goal. Deep neural network (DNN) architectures were obtained from a dataset of the optical properties of super-spheroids with extensive shape parameters, size parameters, and refractive indices. The dataset was computed through the invariant imbedding T-matrix method. Four separate DNN architectures were created to compute the extinction efficiency factor, single-scattering albedo, asymmetry factor, and phase matrix. The criterion for designing these neural networks was the achievement of the highest prediction accuracy with minimal DNN parameters. The numerical results demonstrate that the determination coefficients are greater than 0.999 between the prediction values from the neural networks and the truth values from the database, which indicates that the DNN can reproduce the optical properties in the dataset with high accuracy. In addition, the DNN model can robustly predict the optical properties of particles with high accuracy for shape parameters or refractive indices that are unavailable in the database. Importantly, the ratio of the database size (∼127 GB) to that of the DNN parameters (∼20 MB) is approximately 6810, implying that the DNN model can be treated as a highly compressed database that can be used as an alternative to the original database for real-time computing of the optical properties of non-spherical particles in radiative transfer and atmospheric models. [ABSTRACT FROM AUTHOR]

Circular RNAs (circRNAs) have been reported to play important roles in human cancers. Circular RNA homeodomain interacting protein kinase 3 (Circ-HIPK3) was investigated to be involved in tumorigenesis. However, the functions of circ-HIPK3 in oral squamous cell carcinoma (OSCC) remain vague. The expression of circ-HIPK3, microRNA (miR)-381-3p and Yes-associated protein1 (YAP1) was detected by qRT-PCR or western blot. Cell proliferation, apoptosis, invasion and migration were measured by MTT assay, flow cytometry, or transwell assay. The dual-luciferase reporter assay was employed to test the target correlations miR-381-3p and circ-HIPK3 or YAP1. Murine xenograft model was established to conduct in vivo assay. Circ-HIPK3 was elevated in OSCC tissues and cell lines, and decrease of circ-HIPK3 suppressed OSCC cell proliferation, invasion, migration and induced apoptosis in vitro as well as inhibited tumor growth in vivo. Rescue assay indicated circ-HIPK3 silence mediated OSCC progression inhibition by sponging miR-381-3p, which was a target of circ-HIPK3. Furthermore, miR-381-3p directly interacted with YAP1 and miR-381-3p inhibition could attenuate YAP1 deletion-induced suppression on cell malignant biological behavior in OSCC. Meanwhile, co-expression analysis showed circ-HIPK3 could regulate YAP1 expression by competing for miR-381-3p. Circ-HIPK3 contributed to OSCC growth and development through regulating YAP1 expression by sponging miR-381-3p, indicating a promising therapeutic strategy for OSCC. [ABSTRACT FROM AUTHOR]

In this study, four functional β-cyclodextrin derivatives including amidoxime linear-linked and cross-linked β-cyclodextrin/acrylonitrile/acrylic terpolymer (l-CD-AO-AA and c-CD-AO-AA), citric acid cross-linked poly-β-cyclodextrin (PCD), amidoxime cross-linked β-cyclodextrin and acrylonitrile–acrylic block copolymer (CD-b-AO-AA) were synthesized and properties of β-CD derivatives were characterized by FT-IR, SEM, TGA and element analysis. The effect of solid liquid ratio of the adsorbents, ionic strength, pH, contact time, initial concentration of U(VI), adsorption temperature, selective adsorption for different metal ions and the reasonable desorption conditions were studied. It was found when content of U(VI) was 22 mg/L, the four functional materials l-CD-AO-AA, c-CD-AO-AA, PCD and CD-AO-b-AA completely adsorbed U(VI) at 0.06 g/L (R ≈ 97%), 0.10 g/L (R ≈ 96%), 0.08 g/L (R ≈ 94%) and 0.52 g/L (R ≈ 94%), respectively. [ABSTRACT FROM AUTHOR]

Purpose: The aim of this study is to evaluate the efficacy of intracameral preservative-free triamcinolone acetonide (TA) on reducing inflammatory reactions after pediatric cataract surgery. Methods: Researches were comprehensively searched in PubMed, Embase, and the Cochrane Central Register of Controlled Trials up to 30 November, 2019. Data of interest were extracted and analyzed by Review Manager 5.2. The primary outcome was cell deposits. The secondary outcomes included posterior synechias, fibrinous anterior chamber reaction, visual axis obscuration, and posterior capsule opacification. The odds ratio (OR), weight mean difference (WMD), and their 95% confidence intervals (95% CI) were used to assess the strength of the association. Results: In total, 45 articles were obtained. Finally, 5 studies with a total of 308 eyes were enrolled in this meta-analysis. Among these, 134 eyes underwent intracameral TA treatment and 174 eyes did not. In intracameral TA treatment group, the incidence of cell deposits (OR = 0.35, 95% CI 0.16–0.76, P = 0.008), posterior synechias (OR = 0.44, 95% CI 0.23–0.86, P = 0.02), and fibrinous anterior chamber reaction (OR = 0.12, 95% CI 0.01–1.05, P = 0.05) were lower compared to those in patients without intracameral TA treatment. Meanwhile, the incidence of visual axis obscuration (OR = 0.10, 95% CI 0.01–0.85, P = 0.04) and posterior capsule opacification (OR = 0.09, 95% CI 0.02–0.55, P = 0.009) were also reduced significantly. The intraocular pressure (IOP) was evaluated at the first month postoperatively (WMD = 0.84 mmHg, 95% CI 0.14–1.53, P = 0.02), but within the normal range. There was no difference of IOP between two groups at 6 months or above after operation (P = 0.93). Conclusions: The intracameral preservative-free TA in pediatric cataract surgery contributed to much less inflammatory reaction with the normal IOP range. [ABSTRACT FROM AUTHOR]

We study the Imbert-Fedorov (IF) effect in Kretschmann configuration with anisotropic metamaterial to explore a flexible method to enhance and modulate IF shift. The physical mechanism for large IF shifts in an anisotropic waveguide based on spin-orbit angular momentum coupling is explained. The influences of metamaterial thickness, anisotropy, and loss on IF shift are systematically discussed. This provides a theoretical prediction of IF shift in a Kretschmann configuration which is verified by simulation results in semiconductor metamaterial waveguide. The simulation results show that both metamaterial anisotropy and loss contributes significantly to the IF shift. Thus, reducing the loss and enhancing the metamaterial anisotropy are necessary and important measures to realize enhanced IF effect in the proposed Kretschmann configuration. [ABSTRACT FROM AUTHOR]

Segmentation of regions of interest (ROIs) in medical images is an important step for image analysis in computer-aided diagnosis systems. In recent years, segmentation methods based on fully convolutional networks (FCNs) have achieved great success in general images. FCN performance is primarily due to it leveraging large labeled datasets to hierarchically learn the features that correspond to the shallow appearance as well as the deep semantics of the images. However, such dependence on large dataset does not translate well into medical images where there is a scarcity of annotated medical training data, and FCN results in coarse ROI detections and poor boundary definitions. To overcome this limitation, medical image-specific FCN methods have been introduced with post-processing techniques to refine the segmentation results; however, the performance of these methods is reliant on the appropriate tuning of a large number of parameters and dependence on data-specific post-processing techniques. In this study, we leverage the state-of-the-art image feature learning method of generative adversarial network (GAN) for its inherent ability to produce consistent and realistic images features by using deep neural networks and adversarial learning concept. We improve upon GAN such that ROI features can be learned at different levels of complexities (simple and complex), in a controlled manner, via our proposed dual-path adversarial learning (DAL). The outputs from our DAL are then augmented to the learned ROI features into the existing FCN training data, which increases the overall feature diversity. We conducted experiments on three public datasets with a variety of visual characteristics. Our results demonstrate that our DAL can improve FCN-based segmentation methods and outperform or be competitive in performances to the state-of-the-art methods without using medical image-specific optimizations. [ABSTRACT FROM AUTHOR]

The automated segmentation of regions of interest (ROIs) in medical imaging is the fundamental requirement for the derivation of high-level semantics for image analysis in clinical decision support systems. Traditional segmentation approaches such as region-based depend heavily upon hand-crafted features and a priori knowledge of the user. As such, these methods are difficult to adopt within a clinical environment. Recently, methods based on fully convolutional networks (FCN) have achieved great success in the segmentation of general images. FCNs leverage a large labeled dataset to hierarchically learn the features that best correspond to the shallow appearance as well as the deep semantics of the images. However, when applied to medical images, FCNs usually produce coarse ROI detection and poor boundary definitions primarily due to the limited number of labeled training data and limited constraints of label agreement among neighboring similar pixels. In this paper, we propose a new stacked FCN architecture with multi-channel learning (SFCN-ML). We embed the FCN in a stacked architecture to learn the foreground ROI features and background non-ROI features separately and then integrate these different channels to produce the final segmentation result. In contrast to traditional FCN methods, our SFCN-ML architecture enables the visual attributes and semantics derived from both the fore- and background channels to be iteratively learned and inferred. We conducted extensive experiments on three public datasets with a variety of visual challenges. Our results show that our SFCN-ML is more effective and robust than a routine FCN and its variants, and other state-of-the-art methods. [ABSTRACT FROM AUTHOR]

Two kinds of poly(vinyl alcohol) (PVA)-silica composites were prepared with different methods. One composite was prepared by directly mixing PVA with 80 nm silica nano-particles which were made from tetraethoxysilane (TEOS). The another was obtained by the mixing PVA and hydrolyzed TEOS in the presence of acid-catalyst. The properties of the two PVA/silica hybrids were characterized by means of scanning electron microscopy (SEM), UV-Visible spectroscopy, solubility tests, limiting oxygen index (LOI) test, tensile test and dynamical mechanical analysis (DMA), respectively. The results indicate that PVA-TEOS composites (PT for short) display more transparency than PVA-silica nano-particles hybrids (PS for short). At the same time, The PT composites presented more excellent performance than PS in water resistance, fire resistance and mechanical properties. Moreover, the T of PT increased with increasing TEOS content, while that of PS decreased. [ABSTRACT FROM AUTHOR]

Non-reciprocal photonic devices, including optical isolators and circulators, are indispensible components in optical communication systems. However, the integration of such devices on semiconductor platforms has been challenging because of material incompatibilities between semiconductors and magneto-optical materials that necessitate wafer bonding, and because of the large footprint of isolator designs. Here, we report the first monolithically integrated magneto-optical isolator on silicon. Using a non-reciprocal optical resonator on an silicon-on-insulator substrate, we demonstrate unidirectional optical transmission with an isolation ratio up to 19.5 dB near the 1,550 nm telecommunication wavelength in a homogeneous external magnetic field. Our device has a small footprint that is 290 µm in length, significantly smaller than a conventional integrated optical isolator on a single crystal garnet substrate. This monolithically integrated non-reciprocal optical resonator may serve as a fundamental building block in a variety of ultracompact silicon photonic devices including optical isolators and circulators, enabling future low-cost, large-scale integration. [ABSTRACT FROM AUTHOR]

Purpose: To optimize chemotherapy regimens and improve the effectiveness of chemotherapy combined with immunotherapy, a PET tracer specifically targeting the stimulator of interferon genes (STING), denoted as [18F]FBTA was used to monitor the early changes in tumor immunogenicity after chemotherapy in colorectal cancer (CRC) mice. Methods: The toluene sulfonate precursor was labeled with 18F to produce the STING targeted probe—[18F]FBTA. [18F]FBTA-PET imaging and biodistribution were performed using CRC mice treated with oxaliplatin (OXA) or cisplatin (CDDP). CRC mice were also treated with low (CDDP-LD: 1 mg/kg) or medium (CDDP-MD: 2.5 mg/kg) doses of CDDP, and subjected to PET imaging and biodistribution. The effects of different chemotherapeutic agents and different doses of CDDP on tumor innate immunity were verified by flow cytometry and immunohistochemistry. Results: PET imaging of CRC mice exhibited notably enhanced tumor uptake in the early phase of chemotherapy with treatment with OXA (3.09 ± 0.25%ID/g) and CDDP (4.01 ± 0.18%ID/g), especially in the CDDP group. The PET-derived tumor uptake values have strong correlations with STING immunohistochemical score. Flow cytometry showed both agents led to DCs and macrophages infiltration in tumors. Compared with OXA, CDDP treatment recruits more DCs and macrophages in CRC tumors. Both CDDP-LD and CDDP-MD treatment elevated uptake in CRC tumors, especially in CDDP-MD group. Immunohistochemistry and flow cytometry confirmed CDDP-MD treatment recruits more DCs and macrophages than CDDP-LD treatment. Conclusion: Overall, the STING-targeted tracer—[18F]FBTA was demonstrated to monitor early changes in tumor immunogenicity in CRC mice after chemotherapy. Besides, the STING-targeted strategy may help to select the appropriate chemotherapy regimen, including chemotherapeutic agents and doses, which further improve clinical decision making for combination immunotherapy after chemotherapy for CRC. [ABSTRACT FROM AUTHOR]

Purpose: Prognostic prediction is crucial to guide individual treatment for locoregionally advanced nasopharyngeal carcinoma (LA-NPC) patients. Recently, multi-task deep learning was explored for joint prognostic prediction and tumor segmentation in various cancers, resulting in promising performance. This study aims to evaluate the clinical value of multi-task deep learning for prognostic prediction in LA-NPC patients. Methods: A total of 886 LA-NPC patients acquired from two medical centers were enrolled including clinical data, [18F]FDG PET/CT images, and follow-up of progression-free survival (PFS). We adopted a deep multi-task survival model (DeepMTS) to jointly perform prognostic prediction (DeepMTS-Score) and tumor segmentation from FDG-PET/CT images. The DeepMTS-derived segmentation masks were leveraged to extract handcrafted radiomics features, which were also used for prognostic prediction (AutoRadio-Score). Finally, we developed a multi-task deep learning-based radiomic (MTDLR) nomogram by integrating DeepMTS-Score, AutoRadio-Score, and clinical data. Harrell's concordance indices (C-index) and time-independent receiver operating characteristic (ROC) analysis were used to evaluate the discriminative ability of the proposed MTDLR nomogram. For patient stratification, the PFS rates of high- and low-risk patients were calculated using Kaplan–Meier method and compared with the observed PFS probability. Results: Our MTDLR nomogram achieved C-index of 0.818 (95% confidence interval (CI): 0.785–0.851), 0.752 (95% CI: 0.638–0.865), and 0.717 (95% CI: 0.641–0.793) and area under curve (AUC) of 0.859 (95% CI: 0.822–0.895), 0.769 (95% CI: 0.642–0.896), and 0.730 (95% CI: 0.634–0.826) in the training, internal validation, and external validation cohorts, which showed a statistically significant improvement over conventional radiomic nomograms. Our nomogram also divided patients into significantly different high- and low-risk groups. Conclusion: Our study demonstrated that MTDLR nomogram can perform reliable and accurate prognostic prediction in LA-NPC patients, and also enabled better patient stratification, which could facilitate personalized treatment planning. [ABSTRACT FROM AUTHOR]

Purpose: Ankylosing spondylitis (AS) is a chronic inflammatory disease of the axial spine; however, the quantitative detection of inflammation in AS remains a challenge in clinical settings. We aimed to investigate the feasibility of using a specific P2X7R-targeting 18F-labeled tracer [18F]GSK1482160 for positron emission tomography (PET) imaging and the quantification of AS. Methods: The radioligand [18F]GSK1482160 was obtained based on nucleophilic aliphatic substitution. Dynamic [18F]GSK1482160 and [18F]FDG micro-PET/CT imaging were performed on AS mice (n = 8) and age-matched controls (n = 8). Tracer kinetics modeling was performed using Logan's graphical arterial input function analysis to quantify the in vivo expression of P2X7R. The post-PET tissues were collected for hematoxylin–eosin (H&E), immunohistochemical (IHC), and immunofluorescence (IF) staining. Results: [18F]GSK1482160 PET/CT imaging revealed that the specific binding in the ankle joint and sacroiliac joint (SIJ) of the AS at 8 weeks group (BPNDankle−AS−8W (non-displaceable binding potential of the ankle) 3.931 ± 0.74; BPNDSIJ−AS−8W (BPBD of the SIJ) 4.225 ± 0.84) were significantly higher than the controls at 8 weeks group (BPNDankle−Ctr−8W 0.325 ± 0.15, BPNDSJJ−Ctr−8W 0.319 ± 0.17) respectively, and the AS at 14 weeks group (BPNDankle−AS−14W 12.212 ± 2.25; BPNDSJJ−AS−14W 13.389 ± 3.60) were significantly higher than the controls at 14 weeks group (BPNDankle−Ctr−14W 0.204 ± 0.16, BPNDSJJ−Ctr−14W 0.655 ± 0.35) respectively. The four groups had no significant difference in the [18F]FDG uptake of ankle and SIJ. IHC and IF staining revealed that the overexpression of P2X7R was colocalized with activated macrophages from the ankle synovium and spinal endplate in mice with AS, indicating that quantification of P2X7R may contribute to the understanding of the pathogenesis of inflammation in human AS. Conclusion: This study developed a novel P2X7R-targeting PET tracer [18F]GSK1482160 to detect the expression of P2X7R in AS mouse models and provided powerful non-invasive PET imaging and quantification for AS. [ABSTRACT FROM AUTHOR]

Purpose: Here, we aim to identify a CEACAM5-targeted nanobody and demonstrate its application in positron emission tomography (PET) imaging and near-infrared (NIR) fluorescence imaging in colorectal cancer (CRC). Methods: Immunohistochemistry was applied to verify CEACAM5 expression in CRC and metastatic lymph nodes (mLNs). CEACAM5-targeted nanobodies were obtained by immunization of human CEACAM5 protein in a dromedary, followed by several rounds of phage screenings. Immunofluorescence staining and flow cytometry was carried out to determine the binding affinity of the nanobodies. The nanobodies were radiolabeled by coupling 18F-SFB for PET imaging of CRC subcutaneous xenografts and lymph node metastasis (LNM). IRDye800CW (IR800) were conjugated to form NIR probes for NIR imaging in CRC subcutaneous models. Results: CEACAM5 was overexpressed in either human CRC tissues or mLNs. A CEACAM5 targeted nanobody, Nb41 was successfully generated, with excellent in vitro binding properties. Incorporation of albumin binding domain (ABD) did not affect the affinity of Nb41. In vivo imaging showed that both 18F-FB-Nb41 and 18F-FB-Nb41-ABD showed obvious accumulation in the tumor. Due to the longer retention in the blood, 18F-FB-Nb41-ABD enrichment in tumors was significantly delayed but higher compared to 18F-FB-Nb41. Both 18F-FB-Nb41 and 18F-FB-Nb41-ABD showed prominent LNM enrichment. Similarly, the IR800-conjugated nanobodies Nb41-IR800 and Nb41-ABD-IR800 exhibited superior imaging effects in subcutaneous models, while Nb41-ABD-IR800 exhibited higher fluorescence intensity in the tumor accompanied with a remarkedly delay compared to Nb41-IR800. Conclusion: Collectively, we presented the identification and in vivo validation of a CEACAM5-targeted nanobody and a fused nanobody with an ABD, which enabled to the non-invasive visualization of malignancy of CRC using PET imaging and NIR imaging in subcutaneous models as well as LNM models. [ABSTRACT FROM AUTHOR]

Purpose: Early diagnosis of sepsis-associated encephalopathy (SAE) is essential for the treatment and prognosis of septic patients. Static PET and MRI have shown promise for early diagnosis, while pharmacokinetic parameters from dynamic PET may provide better quantification for SAE. This study aims to compare the performance of dynamic 2-deoxy-2-[18F]fluoro-D-glucose ([18F]F-FDG) PET and multiparametric MRI in early imaging SAE with a view to providing guidance for the early diagnosis of SAE. Procedures: Dynamic [18F]F-FDG-PET/CT scans and multiparametric MRI were performed in SAE mice induced by LPS. Standardized uptake value (SUV) was measured in static scan images and [18F]F-FDG pharmacokinetic parameters were analyzed with two-tissue compartment model and Patlak plot. MRI relative signal intensity (rT1) derived from T1-weighted images (pre and post contrast) and 4 parameters originating from diffusion-weighted data were measured. Results: Both SUV and dephosphorylation rate constant (k4) increased in SAE model as early as 6 h post sepsis induction, while k4 increased with the relative value (SAE/normal) significantly stronger than that of SUV. Moreover, the net influx constant (Ki) showed significant decrease in SAE as early as 6 h compared with normal mice. Increased signal intensity was identified in T1-weighted contrast enhanced images and rT1 value increased at 12 h post induction. Diffusion tensor imaging (DTI) revealed fractional anisotropy (FA) decreased at 12 h and 24 h in external capsule (ec) and declined axial diffusivity (AD) was shown in white matter at 24 h. Conclusions: The dynamic PET (k4) was more sensitive than static PET (SUV) for early diagnosis of SAE and declined Ki was firstly found in murine SAE, which indicated the advantage of dynamic PET/CT in early detection and differential diagnosis of SAE. While MRI has a higher soft tissue resolution than PET/CT and can classify more subtle brain areas, the comprehensive utilization of the two modalities is helpful for managing SAE. [ABSTRACT FROM AUTHOR]

Purpose: Sigma-1 receptor (Sig-1R), a chaperone that resides at the mitochondrion-associated endoplasmic reticulum (ER) membrane, is an ER stress biomarker. It is thought that ER stress plays a critical role in the progression of metabolic-associated fatty liver disease (MAFLD). The aim of this study was to evaluate a positron emission tomography (PET) tracer [18F]F-TZ3108 targeting Sig-1R for MAFLD. Procedures: The mouse model of MAFLD was established by feeding high-fat diet (HFD) for 12 weeks. Dynamic (0–60 min) PET/CT scans were performed after intravenous injection of 2-deoxy-2[18F]fluoro-D-glucose ([18F]-FDG) and [18F]F-TZ3108. Tracer kinetic modeling was performed for quantification of the PET/CT imaging of the liver. Post-PET biodistribution, the liver tissue western blotting (WB), and immunofluorescence (IF) were performed to compare the expression of Sig-1R levels in the organs harvested from both MAFLD and age-matched control mice. Results: The micro PET/CT imaging revealed a significantly decreased uptake of [18F]F-TZ3108 in the livers of the MAFLD group compared to the healthy controls, while the uptake of [18F]-FDG in the livers was not significantly different between the two groups. Based on the tracer kinetic modeling, the binding disassociate rate (k4) for [18F]F-TZ3108 was significantly increased in MAFLD group compared to healthy controls. The volume distribution (VT), and the non-displacement binding potential (BPND) revealed significantly decrease in MAFLD compared to healthy controls respectively. The post-PET biodistribution (%ID/g) of [18F]F-TZ3108 in the livers of MAFLD mice was significantly reduced nearly twofold than that in the livers of control mice. WB and IF experiments further confirmed the reduction of Sig-1R expression in the MAFLD group. Conclusions: The expression of Sig-1R in the liver, measured by the PET tracer, [18F]F-TZ3108, was significantly decreased in mouse model of MAFLD. The [18F]F-TZ3108 PET/CT imaging may provide a novel means of visualization for ER stress in MAFLD or other diseases in vivo. [ABSTRACT FROM AUTHOR]

Recent theoretically predicted strong anisotropic spin Hall effect (SHE) or inverse SHE (ISHE) in chiral antiferromagnetic compounds Mn3X (X = Ge, Sn, Ga, Ir, Rh, and Pt) could potentially expand the horizons of the antiferromagnet spintronics; however, it has not been experimentally observed yet. For achieving this goal, we have first successfully fabricated high-quality Kagome phase Mn3Sn films with smooth surface by a combination of room-temperature magnetron sputtering and high-temperate annealing. These Mn3Sn films were proved to be epitaxially grown on MgO (110) single crystal substrate with a seldom reported (101-0\documentclass[12pt]{minimal}\usepackage{amsmath}\usepackage{wasysym}\usepackage{amsfonts}\usepackage{amssymb}\usepackage{amsbsy}\usepackage{mathrsfs}\usepackage{upgreek}\setlength{\oddsidemargin}{-69pt}\begin{document}$${1}{\text{0}}\stackrel{\text{-}}{1}{\text{0}}$$\end{document}) orientation that could serve as a good platform for the studies of the crystalline orientation-related anisotropic phenomenon. Then, by employing spin pumping-induced inverse spin Hall effect (SP-ISHE) voltage measurements, we have experimentally proved the existence of crystalline orientation-related anisotropic ISHE with an amplitude of more than 35% in our Mn3Sn films. [ABSTRACT FROM AUTHOR]

Hypertensive retinopathy (HR) can potentially lead to vision loss if left untreated. Early screening and treatment are critical in reducing the risk of vision loss. The computer-aided diagnostic system presents an opportunity to improve the efficiency and reliability of HR screening and diagnosis, particularly given the shortage of specialized medical professionals and the challenges faced by primary care physicians in making precise diagnoses. A notable barrier to the development of such diagnostic algorithms is the lack of publicly available benchmarks and datasets. To address these issues, we organized a challenge named “HRDC—Hypertensive Retinopathy Diagnosis Challenge” in conjunction with the Computer Graphics International (CGI) 2023 conference. The challenge provided a fundus image dataset for two clinical tasks: hypertension classification and HR classification, with each task containing 1000 images. This paper presents a concise summary and analysis of the submitted methods and results for the two challenge tasks. For hypertension classification, the best performing algorithm achieved a Kappa score of 0.3819, an F1 score of 0.6337, and a specificity of 0.8472. For HR classification, the best performing algorithm achieved a Kappa score of 0.4154, an F1 score of 0.6122, and a specificity of 0.8444. We also explored an ensemble approach to the top-ranking methods, which further improved performance beyond the individual best performing algorithm for each task. The challenge results show that there is room for further optimization of these methods, but the insights and methodologies derived from this challenge provide valuable directions for developing more precise and reliable classification models for hypertension and HR. [ABSTRACT FROM AUTHOR]

Swept-source optical coherence tomography (SS-OCT) is widely used to diagnose high myopia due to its advantage in imaging the ocular anatomic structures. Although the scleral deformation provides information on the risk of the high myopia, further validation of these highly promising findings in clinical studies has been limited by the current semi-automated software, which requires human input, and the automatic analysis of the scleral structure is quite challenging due to the ambiguous boundaries. To address these challenges, we propose a deep contour attention network (DCANet) for automatic segmentation of scleral deformation structure. Specifically, we design a scale-aware attention feature fusion module to achieve cross-scale feature fusion, which can facilitate the network to learn complementary information from multi-scale features. In addition, we develop a pyramid feature enhancement module to allow the network to learn global contextual features through the combination of receptive field and attention mechanism, and we also propose a boundary heatmap label to enrich boundary information. We evaluate the performance of the proposed method on two in-house SS-OCT datasets. In addition to the multiple metrics that are used for evaluating the segmentation performance, including Jaccard similarity coefficient, dice similarity coefficient and boundary distance error, we also propose length similarity coefficient and angle similarity coefficient to evaluate the length estimation and angle estimation, respectively. The experimental results show that our method can effectively improve the segmentation performance, and our DCANet achieves the overall best performance on two datasets compared with other state-of-the-art networks. Our findings motivate the development of clinically applicable deep learning systems for the prediction of high myopia progression on the basis of the scleral phenotypes from SS-OCT images. [ABSTRACT FROM AUTHOR]

Presented is a review of the radiative properties of ice clouds from three perspectives: light scattering simulations, remote sensing applications, and broadband radiation parameterizations appropriate for numerical models. On the subject of light scattering simulations, several classical computational approaches are reviewed, including the conventional geometric-optics method and its improved forms, the finite-difference time domain technique, the pseudo-spectral time domain technique, the discrete dipole approximation method, and the T-matrix method, with specific applications to the computation of the single-scattering properties of individual ice crystals. The strengths and weaknesses associated with each approach are discussed. With reference to remote sensing, operational retrieval algorithms are reviewed for retrieving cloud optical depth and effective particle size based on solar or thermal infrared (IR) bands. To illustrate the performance of the current solar- and IR-based retrievals, two case studies are presented based on spaceborne observations. The need for a more realistic ice cloud optical model to obtain spectrally consistent retrievals is demonstrated. Furthermore, to complement ice cloud property studies based on passive radiometric measurements, the advantage of incorporating lidar and/or polarimetric measurements is discussed. The performance of ice cloud models based on the use of different ice habits to represent ice particles is illustrated by comparing model results with satellite observations. A summary is provided of a number of parameterization schemes for ice cloud radiative properties that were developed for application to broadband radiative transfer submodels within general circulation models (GCMs). The availability of the single-scattering properties of complex ice habits has led to more accurate radiation parameterizations. In conclusion, the importance of using nonspherical ice particle models in GCM simulations for climate studies is proven. [ABSTRACT FROM AUTHOR]

As the key link connecting the earth's spheres, continental weathering plays an important role in regulating the global biogeochemical cycle and long-term climate change. Siliciclastic sediments derived from large river basins can record continental weathering and erosion signals, and are thus widely used to investigate weathering processes. However, sediment grain size, hydrodynamic sorting and sedimentary recycling complicate the interpretation of sediment weathering proxies. This study presents elemental and lithium isotope compositions of estuarine surface sediments (SS) and suspended particulate matters (SPM) collected from the Changjiang (Yangtze River) Estuary. Based on a simple mass balance model, the proportions of different end-members (i.e., igneous rocks, modern weathering products and inherited weathering products) in sediments were quantitatively calculated and thus the silicate weathering process can be estimated. Overall, the sediments in the Changjiang Estuary are mainly eroded from un-weathered rock fragments (>60%), while modern weathering products account for less than 40%. The fine-grained SPM contain more shale components (52–66%), and the modern weathering products account for 21–40%. Comparatively, the coarse-grained surface sediments contain more un-weathered igneous rock fragments (63–84%) and less modern weathering products (only 4–18%). The comparison of δ7Li values with the weathering proxy (Chemical Index of Alteration, CIA) suggests that sediment weathering intensity declines with increasing proportion of un-weathered igneous rock fragments. Additionally, the occurrence of inherited weathering products (i.e., shale) in modern sediments makes it a challenge to simply use CIA and δ7Li as indicators of weathering intensity. This study confirms that fine-grained particles are more suitable for tracing contemporary weathering process, albeit with the influence of sedimentary recycling. Lithium isotopes combining with the mass balance model can quantitatively constrain the continental weathering processes in large river basins. [ABSTRACT FROM AUTHOR]

Ankle–foot orthoses (AFOs) are devices prescribed to improve mobility in people with neuromuscular disorders. Traditionally, AFOs are manually fabricated by an orthotist based on a plaster impression of the lower leg which is modified to correct for impairments. This study aimed to digitally analyse this manual modification process, an important first step in understanding the craftsmanship of AFO fabrication to inform the digital workflows (i.e. 3D scanning and 3D printing), as viable alternatives for AFO fabrication. Pre- and post-modified lower limb plaster casts of 50 children aged 1–18 years from a single orthotist were 3D scanned and registered. The Euclidean distance between the pre- and post-modified plaster casts was calculated, and relationships with participant characteristics (age, height, AFO type, and diagnosis) were analysed. Modification maps demonstrated that participant-specific modifications were combined with universally applied modifications on the cast's anterior and plantar surfaces. Positive differences (additions) ranged 2.12–3.81 mm, negative differences (subtractions) ranged 0.76–3.60 mm, with mean differences ranging from 1.37 to 3.12 mm. Height had a medium effect on plaster additions (rs = 0.35). We quantified the manual plaster modification process and demonstrated a reliable method to map and compare pre- and post-modified casts used to fabricate children's AFOs. [ABSTRACT FROM AUTHOR]

Myopia is a serious threat to eye health and can even cause blindness. It is important to grade myopia and carry out targeted intervention. Nowadays, various studies using deep learning models based on optical coherence tomography (OCT) images to screen for high myopia. However, since regions of interest (ROIs) of pre-myopia and low myopia on OCT images are relatively small, it is rather difficult to use OCT images to conduct detailed myopia grading. There are few studies using OCT images for more detailed myopia grading. To address these problems, we propose a novel attention-based multi-scale feature fusion network named AMFF for myopia grading using OCT images. The proposed AMFF mainly consists of five modules: a pre-trained vision transformer (ViT) module, a multi-scale convolutional module, an attention feature fusion module, an Avg-TopK pooling module and a fully connected (FC) classifier. Firstly, unsupervised pre-training of ViT on the training set can better extract feature maps. Secondly, multi-scale convolutional layers further extract multi-scale feature maps to obtain more receptive fields and extract scale-invariant features. Thirdly, feature maps of different scales are fused through channel attention and spatial attention to further obtain more meaningful features. Lastly, the most prominent features are obtained by the weighted average of the highest activation values of each channel, and then they are used to classify myopia through a fully connected layer. Extensive experiments show that our proposed model has the superior performance compared with other state-of-the-art myopia grading models. [ABSTRACT FROM AUTHOR]

Forward radiative transfer models (RTM) are an indispensable tool for quantitative applications of satellite radiometers, e.g., for data calibration, instrument development, retrieval, and so on. In this study, we develop an accurate and efficient RTM for radiometers onboard Fengyun satellites, namely FYRTM (RTM for Fengyun Radiometers). Correlated k-distribution models are developed to improve the computational efficiency for gas absorption, and the effects of cloud and aerosol multiple scattering and emission are accelerated with pre-computed look-up tables. FYRTM is evaluated with a rigorous simulation based on discrete ordinate radiative transfer model (DISORT) as well as a popular fast forward model, i.e., the Community Radiative Transfer Model (CRTM). Results indicate that FYRTM-based simulations are two to three orders of magnitudes faster than the DISORT-based simulations. Compared to the rigorous model, FYRTM relative errors are within 2% at solar channels, and brightness temperatures (BT) differences are within 1 K at infrared channels. Compared with CRTM, FYRTM is computationally similar at solar channels, but three times faster at infrared channels. Furthermore, simulated reflectances/BTs using FYRTM are in a good agreement with the satellite observations. Overall, FYRTM is capable to simulate satellite observations under different atmospheric conditions, and can be extended to other radiometers onboard the Fengyun satellites (both geostationary and polar-orbiting satellites). It is expected to play important roles in future applications with Fengyun observations. [ABSTRACT FROM AUTHOR]

As a result of recycling, the mineralogical and chemical compositions of riverine sediments may reflect the combined effects of the present-day weathering regime as well as previous weathering and diagenetic alteration history. River sediments can be interpreted as a mixture of non-weathered bedrock-of igneous, metamorphic, or sedimentary origin-and solids formed by the modern weathering system. The correlation between the weathering proxies chemical index of alteration and weathering index of Parker offers an approach to distinguish fine suspended particles, coarse bedload sediments, and recycled sediments under the influence of quartz dilution. Recycling of cation-depleted source rocks formed during past geological weathering episodes may have great impacts on the weathering indices of sediments from the Changjiang (Yangzte) and Zhuoshui Rivers. Special caution is required when using chemical weathering indices to investigate the intensity of chemical weathering registered in fluvial sediments. To minimize the effect of hydrodynamic sorting or sediment recycling, we suggest that the fine sediments (e.g. suspended particles and <2 μm fractions of bedload sediments) in rivers better reflect the average of weathered crust in catchments and the terrigenous end-member in marginal seas. [ABSTRACT FROM AUTHOR]