Multifunctional bispecific nanovesicles targeting SLAMF7 trigger potent antitumor immunity.

The effectiveness of immune checkpoint inhibitor (ICI) therapy is hindered by the ineffective infiltration and functioning of cytotoxic T cells and the immunosuppressive tumor microenvironment (TME). Signaling lymphocytic activation molecule family member 7 (SLAMF7) is a pivotal co-stimulatory receptor thought to simultaneously trigger natural killer (NK)-cell, T-cell, and macrophage antitumor cytotoxicity. However, the potential of this collaborative immune stimulation in antitumor immunity for solid tumors is under-explored due to the exclusive expression of SLAMF7 by hematopoietic cells. Here, we report the development and characterization of multifunctional bispecific nanovesicles targeting SLAMF7 and Glypican-3-a hepatocellular carcinoma (HCC)-specific tumor antigen. We found that by effectively "decorating" the surface of solid tumors with SLAMF7, these nanovesicles directly induced potent and specific antitumor immunity and remodeled the immunosuppressive TME, sensitizing the tumors to programmed cell death protein 1 (PD-1) blockade. Our findings highlight the potential of SLAMF7-targeted multifunctional bispecific nanovesicles as an anticancer strategy with implications for designing next-generation targeted cancer therapies.

STING-Targeted PET Imaging for Specific Detection and Therapeutic Monitoring of Myocarditis.

Imaging strategies for the specific detection and therapeutic monitoring of myocarditis are still lacking. Stimulator of interferon genes (STING) is a signal transduction molecule involved in an innate immune response. Here, we evaluated the feasibility of the recently developed STING-targeted radiotracer [18F]FBTA for positron emission tomography (PET) imaging to detect myocardial inflammation and monitor treatment in myocarditis mice. [18F]FBTA-PET imaging was performed in myocarditis mice and normal mice to verify the specificity of [18F]FBTA for the diagnosis of myocarditis. We also performed PET imaging in mice with myocarditis treated to verify the ability of [18F]FBTA in therapeutic monitoring. The expression of STING and inflammatory cell types was confirmed by flow cytometry and immunohistochemistry. [18F]FDG-PET imaging of myocarditis was used as a contrast. [18F]FBTA-PET imaging showed that the average radioactive uptake was significantly higher in the hearts of the myocarditis group than in the control group. STING was highly overexpressed in cardiac inflammatory cells, including macrophages, dendritic cells (DCs), and T cells. However, there was no significant difference in cardiac radiotracer uptake of [18F]FDG between the myocarditis group and the control group. Moreover, cardiac uptake of [18F]FBTA was significantly reduced in cyclosporin A-treated myocarditis mice and myocardial STING expression was also significantly reduced after the treatment. Overall, we showed that a STING-targeted PET tracer [18F]FBTA can be used to monitor changes in the inflammatory microenvironment in myocarditis. Besides, [18F]FBTA-PET is also suitable for real-time monitoring of myocarditis treatment, representing a promising diagnostic and therapeutic monitoring approach for myocarditis.

b-MAR: bidirectional artifact representations learning framework for metal artifact reduction in dental CBCT.

OBJECTIVE: Metal artifacts in computed tomography (CT) images hinder diagnosis and treatment significantly. Specifically, dental cone-beam computed tomography (Dental CBCT) images are seriously contaminated by metal artifacts due to the widespread use of low tube voltages and the presence of various high-attenuation materials in dental structures. Existing supervised metal artifact reduction (MAR) methods mainly learn the mapping of artifact-affected images to clean images, while ignoring the modeling of the metal artifact generation process. Therefore, we propose the bidirectional artifact representations learning framework to adaptively encode metal artifacts caused by various dental implants and model the generation and elimination of metal artifacts, thereby improving MAR performance. Approach. we introduce an efficient artifact encoder to extract multi-scale representations of metal artifacts from artifact-affected images. These extracted metal artifact representations are then bidirectionally embedded into both the metal artifact generator and the metal artifact eliminator, which can simultaneously improve the performance of artifact removal and artifact generation. The artifact eliminator learns artifact removal in a supervised manner, while the artifact generator learns artifact generation in an adversarial manner. To further improve the performance of the bidirectional task networks, we propose artifact consistency loss to align the consistency of images generated by the eliminator and the generator with or without embedding artifact representations. Main results. To validate the effectiveness of our algorithm, experiments are conducted on simulated and clinical datasets containing various dental metal morphologies. Quantitative metrics are calculated to evaluate the results of the simulation tests,which demonstrate b-MAR improvements of > 1.4131 dB in PSNR, > 0.3473 HU decrements in RMSE, and > 0.0025 promotion in SSIM over the current state-of-the-art MAR methods. All results indicate that the proposed b-MAR method can remove artifacts caused by various metal morphologies and restore the structural integrity of dental tissues effectively. Significance. The proposed b-MAR method strengthens the joint learning of the artifact removal process and the artifact generation process by bidirectionally embedding artifact representations, thereby improving the model's artifact removal performance. Compared with other comparison methods, b-MAR can robustly and effectively correct metal artifacts in dental CBCT images caused by different dental metals.

DDT-Net: Dose-Agnostic Dual-Task Transfer Network for Simultaneous Low-Dose CT Denoising and Simulation.

Deep learning (DL) algorithms have achieved unprecedented success in low-dose CT (LDCT) imaging and are expected to be a new generation of CT reconstruction technology. However, most DL-based denoising models often lack the ability to generalize to unseen dose data. Moreover, most simulation tools for LDCT typically operate on proprietary projection data, which is generally not accessible without an established collaboration with CT manufacturers. To alleviate these issues, in this work, we propose a dose-agnostic dual-task transfer network, termed DDT-Net, for simultaneous LDCT denoising and simulation. Concretely, the dual-task learning module is constructed to integrate the LDCT denoising and simulation tasks into a unified optimization framework by learning the joint distribution of LDCT and NDCT data. We approximate the joint distribution of continuous dose level data by training DDT-Net with discrete dose data, which can be generalized to denoising and simulation of unseen dose data. In particular, the mixed-dose training strategy adopted by DDT-Net can promote the denoising performance of lower-dose data. The paired dataset simulated by DDT-Net can be used for data augmentation to further restore the tissue texture of LDCT images. Experimental results on synthetic data and clinical data show that the proposed DDT-Net outperforms competing methods in terms of denoising and generalization performance at unseen dose data, and it also provides a simulation tool that can quickly simulate realistic LDCT images at arbitrary dose levels.

Development of cancer biomarker heat shock protein 90α certified reference material using two different isotope dilution mass spectrometry techniques.

Heat shock protein 90α (HSP90α) has been regarded as an important indicator for judging tumor metastasis and prognosis due to its significant upregulation in various tumors. Therefore, the accurate quantification of HSP90α is of great significance for clinical diagnosis and therapy of cancers. However, the lack of HSP90α certified reference material (CRM) leads to the accuracy and consistency of quantification methods not being effectively evaluated. Besides, quantitative results without traceability make comparisons between different studies difficult. In this study, an HSP90α solution CRM was developed from the recombinant protein raw material. The recombinant protein is a dimer, and the purity of the CRM candidate reached 96.71%. Both amino acid analysis-isotope dilution mass spectrometry (AAA-IDMS) and unique peptide analysis-isotope dilution mass spectrometry (UPA-IDMS) were performed to measure the content of HSP90α in the solution CRM candidate, and the certified value was assessed to be 66.2 ± 8.8 µg/g. Good homogeneity of the CRM was identified, and the stability examination suggested that the CRM was stable for at least 4 months at - 80 °C and for 7 days at 4 °C. With traceability to SI unit (kg), this CRM has potential to help establish a metrological traceability chain for quantification of HSP90α, which will make the quantification results standardized and comparable regardless of the quantitative methods.

Precise Control of Trypsin Immobilization by a Programmable DNA Tetrahedron Designed for Ultrafast Proteome Digestion and Accurate Protein Quantification.

In proteomics research, with advantages including short digestion times and reusable applications, immobilized enzyme reactors (IMERs) have been paid increasing attention. However, traditional IMERs ignore the reasonable spatial arrangement of trypsin on the supporting matrixes, resulting in the partial overlapping of the active domain on trypsin and reducing digesting efficiency. In this work, a DNA tetrahedron (DNA TET)-based IMER Fe3O4-GO-AuNPs-DNA TET-Trypsin was designed and prepared. The distance between vertices of DNA TETs effectively controls the distribution of trypsin on the nanomaterials; thus, highly efficient protein digestion and accurate quantitative results can be achieved. Compared to the in-solution digestion (12-16 h), the sequence coverage of bovine serum albumin was up to 91% after a 2-min digestion by the new IMER. In addition, 3328 proteins and 18,488 peptides can be identified from HeLa cell protein extract after a 20-min digestion. For the first time, human growth hormone reference material was rapidly and accurately quantified after a 4-h digestion by IMER. Therefore, this new IMER has great application potential in proteomics research and SI traceable quantification.

Traceable value of immunoglobulin G against receptor-binding domain of SARS-CoV-2 confirmation and application to point-of-care testing system development.

A highly purified and bioactive immunoglobulin G monoclonal antibody against receptor-binding domain of SARS-CoV-2 (RBD-IgG-MAb) has been accurately quantified by amino acid determination using isotope dilution liquid chromatography-mass spectrometry. Absolute quantification of RBD-IgG-MAb was achieved by averaging 4 amino acid certified reference materials, which allows the quantitative value (66.1 ± 5.8 µg/L) to be traced to SI unit (mol). Afterwards, the RBD-IgG-MAb was employed as control and calibration compound for the development of a point-of-care testing (POCT) system based on colloidal gold lateral flow immunoassay, which aimed to rapidly and accurately detect the level of protective RBD-IgG after vaccination. Under the detection parameters, a sigmoidal curve has been plotted between signal intensity and the logarithmic concentration for quantitative detection with the limit of detection of about 0.39 µg/mL. The relative standard deviations of intra-assay and inter-assay were lower than 2.3% and 14%, and the recoveries ranged from 87 to 100%, respectively. Fingertip blood samples from 37 volunteers after vaccination were analyzed by the POCT system; results showed that levels of RBD-IgG in 33 out of 37 samples ranged from 0.45 to 2.46 µg/mL with the average level of 0.91 µg/mL. The developed POCT system has been successfully established with the quantity-traceability RBD-IgG-MAb as control and calibration compound, and the scientific contribution of this work can be promoted to other areas.

The concentration-dependent physiological damage, oxidative stress, and DNA lesions in Caenorhabditis elegans by subacute exposure to landfill leachate.

The leakage of landfill leachate (LL) into environmental media would be happened even in the sanitary/controlled landfill, due to the deterioration of geomembrane and the blockage of drainage system after long-term operation. Considering the complex composition and high concentration of pollutants in LL, its toxicity assessment should be conducted as a whole liquid contaminant. Therefore, the impacts of LL on Caenorhabditis elegans (C. elegans) were investigated under the condition of different exposure time and exposure volume fraction (EVF). The stimulating effects on locomotion behavior and growth of C. elegans were observed after acute (24 h) exposure to LL, which were increased firstly and then decreased with the increase of EVF. Meanwhile, the intestinal barrier was not affected by LL, and levels of reactive oxygen species (ROS) and cell apoptosis significantly decreased. However, stimulation and inhibition effects on locomotion behavior and growth of C. elegans were observed when subacute (72 h) exposure to 0.25%-0.5% and 1%-4% of LL, respectively. The intestinal injury index and levels of ROS and cell apoptosis significantly increased when EVF were 2% and 4%. Although the acute exposure of LL had resulted in obviously biological adaptability and antioxidant defense in C. elegans, the protective mechanisms failed to be induced as the exposure time increased (subacute exposure). The toxic effects were confirmed by the down-regulation of genes associated with antioxidant defense and neurobehavior, accompanied by the up-regulation of intestinal injury and cell apoptosis related genes. Moreover, the disturbance of metabolic pathways that associated with locomotion behaviors, growth, and antioxidant defense provided good supplementary evidence for the confirmation of oxidative stress in C. elegans. The research results verified the potential of C. elegans as model organism to determine the complex toxic effects of LL.

Natural deep eutectic solvent-A novel green solvent for protein stabilization.

Natural deep eutectic solvents (NADESs) have been explored to provide a favorable environment for protein stabilization. In this context, NADESs were prepared with the molar ratio of trehalose to betaine ranging from 1:3 to 1:9 (NADES 1-3 to NADES 1-9). There was a strong hydrogen bond interaction between trehalose and betaine, and the interaction weakened with the reduction of trehalose. The NADES 1-7 had good thermal stability (-60-100 °C), low viscosity, and suitable pH (around 7). Trypsin had the highest relative enzyme activity in 50 % (v/v) NADES 1-7 under different temperatures, pH, and storage time. Furthermore, the changes in kinetic parameters indicated that the hydrogen bond environment of 50 % NADES 1-7 increased the contact between the substrate and the trypsin, speeding up the enzymatic reaction rate. This stabilizing effect mainly derived from the virtue of NADES 1-7 itself rather than the superposition of individual components. Additionally, spectral analysis revealed that the NADES 1-7 promoted trypsin conformational folding, effectively protecting the natural structure of trypsin. Importantly, the NADES 1-7 had good biocompatibility, further expanding its application.

Do footbridge and underpass improve pedestrian safety? A Hong Kong case study using three-dimensional digital map of pedestrian network.

Hong Kong is a compact city with high activity and travel intensity. In the past decades, many footbridges and underpasses were installed to reduce the pedestrian-vehicle conflicts on urban roads. However, it is rare that the effects of configuration of pedestrian network on pedestrian crashes are investigated. In Hong Kong, many footbridges and underpasses are connected to major transport hubs and commercial building development and become parts of giant elevated and underground walkway systems. It is challenging to characterize such a complicated pedestrian network. In this study, a three-dimensional digital map is applied to estimate the connectivity and accessibility of pedestrian network, and measure the relationship between pedestrian network characteristics and pedestrian safety at the macroscopic level. Hence, the effects of footbridge and underpass on pedestrian safety are examined. For example, comprehensive built environment, pedestrian network, traffic, and crash data are aggregated to 379 grids (0.5 km × 0.5 km). Then, multivariate Poisson lognormal regression approach is applied to model fatal and severe injury (FSI) and slight injury pedestrian crashes, with which the effects of unobserved heterogeneity, spatial correlation, and correlation between crash counts are accounted. Results indicate that population density, traffic volume, walking trip, footpath density, node density, number of vertices per footpath segment, bus stop, metro exit, residential area, commercial area, and government and utility area are positively associated with pedestrian crashes. In contrast, average gradient, accessibility of footbridge, accessibility of underpass, and number of crossings per road segment are negatively associated with pedestrian crashes. In other word, pedestrian safety would be improved when footbridge and underpass are more accessible. Findings have implications for the design and planning of pedestrian network to promote walkability and improve pedestrian safety.

Environmental impacts and optimization simulation of aerobic anaerobic combination treatment technology for food waste with life cycle assessment.

After the implementation of waste sorting policy in Shanghai, the amount of food waste (FW) separation and treatment demand has increased significantly. It is necessary to establish the life cycle assessment (LCA) to assess the environmental impacts of various treatment technologies comprehensively, thus provide support for sorting, recycling, treatment and disposal strategies of FW. In this study, a local FW treatment plant in Shanghai, using typically aerobic anaerobic combination treatment technology was selected to analyze the environmental impacts with LCA. The process mainly included pretreatment, power, aerobic composting, anaerobic digestion, and further process systems. LCA results showed that the environmental impacts mainly came from the power and aerobic composting systems on the fine particulate matter formation and eutrophication, and freshwater ecotoxicity and terrestrial acidification, respectively. Considering the carbon footprint, the aerobic composting system contributed 3.61E + 02 kg CO2 eq and represented the largest source of carbon emission. The soil conditioner yielded both environmental benefits on eutrophication and terrestrial ecotoxicity, and ecological benefits of 75.33 million CNY per year being the major revenue for the treatment plant. It also suggested that the biogas generation capacity of anaerobic digestion could be increased to achieve electricity self-sufficiency, thus save about 7.12 million CNY per year in electricity costs, and avoid corresponding environmental impacts caused by coal-fired. In summary, the aerobic anaerobic combination treatment could be further optimized and applied in FW treatment to reduce the environmental impacts, and enhance resource recovery and secondary pollution control.

Corneal Epithelial Remodeling in a 6-Month Follow-up Period in Myopic Corneal Refractive Surgeries.

PURPOSE: To investigate corneal epithelial thickness changes during a 6-month follow-up period after transepithelial photorefractive keratectomy (tPRK), femtosecond laser-assisted laser in situ keratomileusis (FS-LASIK), and small incision lenticule extraction (SMILE). METHODS: This prospective study included 76 eyes of 76 participants who underwent myopic refractive surgery (23 FS-LASIK, 22 SMILE, and 31 tPRK). Epithelial thickness and anterior curvature were averaged over 4 regions (subdivided into 25 areas) and measured by spectral-domain optical coherence tomography and Scheimpflug tomography before the operation (pre) and at 1 or 3 days (pos1-3d), 1 week (pos1w), and 1 month (pos1m), 3 months (pos3m), and 6 months (pos6m) postoperatively. RESULTS: The epithelial thickness of the three groups was similar in both the pre and pos6m (all P > .05), but the tPRK group fluctuated the most during the follow-up period. The largest increase was in the inferior-temporal paracentral area (7.25 ± 2.58 µm for FS-LASIK; 5.79 ± 2.41 µm for SMILE; 4.88 ± 5.84 µm for tPRK; all P < .001). Only the epithelial thickness of tPRK increased from pos3m to pos6m (P < .05), whereas all changes for FS-LASIK and SMILE were not significant (P > .05). A positive correlation of thickness changes with curvature gradient in the paracentral region of tPRK was found (r = 0.549, P = .018), but not in other regions in all groups. CONCLUSIONS: Epithelial remodeling followed different trends after different surgeries from the early postoperative stage onward, but exhibited similar values at pos6m. Although remodeling after FS-LASIK and SMILE stabilized by pos3m, it remained unstable at pos6m after tPRK. These changes may affect corneal profile and lead to deviation from the intended surgical outcome. [J Refract Surg. 2023;39(3):187-196.].

Dynamic topography analysis of the cornea and its application to the diagnosis of keratoconus.

PROPOSE: To establish a dynamic topography analysis method which simulates the dynamic biomechanical response of the cornea and reveals the variations of such response within the corneal surface, and thereafter to propose and clinically evaluate new parameters for the definite diagnosis of keratoconus. METHODS: 58 normal (Normal) and 56 keratoconus (KC) subjects were retrospectively included. Personalized corneal air-puff model was established using corneal topography data by Pentacam for each subject, and the dynamic deformation under air-puff loading was simulated using finite element method, which then enabled calculations of corneal biomechanical parameters of the entire corneal surface along any meridian. Variations in these parameters across different meridians and between different groups were explored by two-way repeated measurement analysis of variance. New dynamic topography parameters were proposed as the range of the calculated biomechanical parameters within the entire corneal surface, and the AUC of ROC curve was used to compare the diagnostic efficiency of newly proposed and existing parameters. RESULTS: Corneal biomechanical parameters measured in different meridians varied significantly which were more pronounced in KC group due to its irregularity in corneal morphology. Considering such between-meridian variations thus led to improved diagnostic efficiency of KC as presented by the proposed dynamic topography parameter rIR with an AUC of 0.992 (sensitivity: 91.1%, specificity: 100%), significantly better than the current topography and biomechanical parameters. CONCLUSIONS: The diagnosis of keratoconus may be affected by the significant variations of corneal biomechanical parameters due to corneal morphology irregularity. By considering such variations, the current study established the dynamic topography analysis process which benefits from the high accuracy of (static) corneal topography measurement while improving its diagnosis capacity. The proposed dynamic topography parameters, especially the rIR parameter, showed comparable or better diagnostic efficiency for KC than existing topography and biomechanical parameters, which can be of great clinical significance for clinics without access to instrument for biomechanical evaluations.

Physics-informed sinogram completion for metal artifact reduction in CT imaging.

Objective.Metal artifacts in the computed tomography (CT) imaging are unavoidably adverse to the clinical diagnosis and treatment outcomes. Most metal artifact reduction (MAR) methods easily result in the over-smoothing problem and loss of structure details near the metal implants, especially for these metal implants with irregular elongated shapes. To address this problem, we present the physics-informed sinogram completion (PISC) method for MAR in CT imaging, to reduce metal artifacts and recover more structural textures.Approach.Specifically, the original uncorrected sinogram is firstly completed by the normalized linear interpolation algorithm to reduce metal artifacts. Simultaneously, the uncorrected sinogram is also corrected based on the beam-hardening correction physical model, to recover the latent structure information in metal trajectory region by leveraging the attenuation characteristics of different materials. Both corrected sinograms are fused with the pixel-wise adaptive weights, which are manually designed according to the shape and material information of metal implants. To furtherly reduce artifacts and improve the CT image quality, a post-processing frequency split algorithm is adopted to yield the final corrected CT image after reconstructing the fused sinogram.Main results.We qualitatively and quantitatively evaluated the presented PISC method on two simulated datasets and three real datasets. All results demonstrate that the presented PISC method can effectively correct the metal implants with various shapes and materials, in terms of artifact suppression and structure preservation.Significance.We proposed a sinogram-domain MAR method to compensate for the over-smoothing problem existing in most MAR methods by taking advantage of the physical prior knowledge, which has the potential to improve the performance of the deep learning based MAR approaches.

Nanoparticles alleviate non-alcoholic steatohepatitis via ER stress sensor-mediated intestinal barrier damage and gut dysbiosis.

Introduction: The gut microbiota plays an important role in the development of non-alcoholic steatohepatitis (NASH), but the underlying mechanism is unclear. It has been found that the transcription factor XBP1s plays an important role in regulating inflammation and lipid metabolism and maintaining the integrity of intestinal barrier. However, whether XBP1s modulates the development of NASH by regulating the integrity of the intestinal barrier and altering the composition of the gut microbiota remains unknown. Methods: Mice fed with a fat-, fructose-, cholesterol-rich (FFC) diet for 24 weeks successfully established the NASH model, as demonstrated by significant hepatic steatosis, inflammation, hepatocyte injury and fibrosis. The profile of gut microbiota dynamically changed with the different stages of NAFLD via 16S rDNA sequencing the feces from mice fed with FFC diet for 0, 12, or 24 weeks or NASH mice treated with siRNA-loaded folic acid-modified TPGS (hereafter named FT@XBP1). Results: NASH mice had significantly higher abundance of Firmicutes, Blautia and Bacteroides, and lower abundance of Bifidobacterium and GCA-900066575. FT@XBP1 supplementation had a significantly attenuated effect on FFC diet-induced weight gain, hepatic fat accumulation, dyslipidemia, inflammatory cytokines, ER stress and fibrosis. In particularly, FT@XBP1 modulates the composition of the intestinal flora; for example, NASH mice demonstrated higher abundance of Blautia and Bacteroides, and lower abundance of Actinobacteriota, Muribaculaceae and Bifidobacterium, which were partially restored by FT@XBP1 treatment. Mechanistically, FT@XBP1 increased the expression of ZO-1 in the intestine and had the potential to restore intestinal barrier integrity and improve antimicrobial defense to alleviate enterogenic endotoxemia and activation of inflammatory signaling pathways. Discussion: Regulation of the key transcription factor XBP1s can partially restore the intestinal microbiota structure, maintain the integrity of intestinal mucosal barrier, and prevent the progression of NASH, providing new evidence for treating NASH.

Structure-preserved meta-learning uniting network for improving low-dose CT quality.

Objective.Deep neural network (DNN) based methods have shown promising performances for low-dose computed tomography (LDCT) imaging. However, most of the DNN-based methods are trained on simulated labeled datasets, and the low-dose simulation algorithms are usually designed based on simple statistical models which deviate from the real clinical scenarios, which could lead to issues of overfitting, instability and poor robustness. To address these issues, in this work, we present a structure-preserved meta-learning uniting network (shorten as 'SMU-Net') to suppress noise-induced artifacts and preserve structure details in the unlabeled LDCT imaging task in real scenarios.Approach.Specifically, the presented SMU-Net contains two networks, i.e., teacher network and student network. The teacher network is trained on simulated labeled dataset and then helps the student network train with the unlabeled LDCT images via the meta-learning strategy. The student network is trained on real LDCT dataset with the pseudo-labels generated by the teacher network. Moreover, the student network adopts the Co-teaching strategy to improve the robustness of the presented SMU-Net.Main results.We validate the proposed SMU-Net method on three public datasets and one real low-dose dataset. The visual image results indicate that the proposed SMU-Net has superior performance on reducing noise-induced artifacts and preserving structure details. And the quantitative results exhibit that the presented SMU-Net method generally obtains the highest signal-to-noise ratio (PSNR), the highest structural similarity index measurement (SSIM), and the lowest root-mean-square error (RMSE) values or the lowest natural image quality evaluator (NIQE) scores.Significance.We propose a meta learning strategy to obtain high-quality CT images in the LDCT imaging task, which is designed to take advantage of unlabeled CT images to promote the reconstruction performance in the LDCT environments.

Effect of urban street trees on pedestrian safety: A micro-level pedestrian casualty model using multivariate Bayesian spatial approach.

In the past decades, trees were considered roadside hazard. Street trees were removed to provide clear zone and improve roadside safety. Nowadays, street trees are considered to play an important role in urban design. Also, street tree is considered a traffic calming measure. Studies have examined the effects of urban street trees on driver perception, driving behaviour, and general road safety. However, it is rare that the relationship between urban street trees and pedestrian safety is investigated. In this study, a micro-level frequency model is established to evaluate the effects of tree density and tree canopy cover on pedestrian injuries, accounting for pedestrian crash exposure based on comprehensive pedestrian count data from a state in Australia, Melbourne. In addition, effects of road geometry, traffic characteristics, and temporal distribution are also considered. Furthermore, effects of spatial dependency and correlation between pedestrian casualty counts of different injury severity levels are accounted using a multivariate Bayesian spatial approach. Results indicate that road width, bus stop, tram station, on-street parking, and 85th percentile speed are positively associated with pedestrian casualty. In contrast, pedestrian casualty decreases when there is a pedestrian crosswalk and increases in tree density and canopy. Also, time variation in pedestrian injury risk is significant. To sum up, urban street trees should have favorable effect on pedestrian safety. Findings are indicative to optimal policy strategies that can enhance the walking environment and overall pedestrian safety. Therefore, sustainable urban and transport development can be promoted.

Exploring the impacts of street layout on the frequency of pedestrian crashes: A micro-level study.

INTRODUCTION: Pedestrian safety has become a critical issue since walking is increasingly promoted as a sustainable transport mode. However, pedestrians are vulnerable to severe injury and mortality in road crashes. Therefore, it is important to understand the factors that affect the safety of pedestrians. This paper investigates the impacts of street layout on the frequency of pedestrian crashes by examining the interactive pattern of built environment, crossing facilities, and road characteristics. METHOD: A surrogate exposure variable of pedestrian crashes at the road-segment level is proposed by considering the locations of crossing facilities, distribution of points of interest (POIs), road characteristics, and pedestrian activities. A network-based kernel density technique is used to identify the pedestrian crash risk at the road segment level. Bayesian spatial models based on different exposure variables are employed and compared. RESULTS: The results suggest that models using the surrogate exposure of pedestrian crashes provide better model fit than the ones simply using the density of pedestrians. It is also found that the presence of POIs is related to a higher risk of pedestrian-vehicle crash. In addition, a significantly higher number of pedestrian crashes are found to occur on segments with more bus stops and metro stations. Results also show that the longer the distance between the crossing facilities and road segments, the more pedestrian crashes are observed. CONCLUSIONS: The proposed aggregated indicator can provide more efficient exposure and higher prediction accuracy than the density of pedestrians. Besides, the POIs, crossing facilities, and road types were all significantly related to pedestrian crashes. PRACTICAL APPLICATIONS: Our results suggest that the locations of POIs and transport facilities should be planned in a way that can decrease the number of road crossed or guide pedestrians to take safe crossing path.

Biomechanical Effects of tPRK, FS-LASIK, and SMILE on the Cornea.

Purpose: The objective of this study is to evaluate the in vivo corneal biomechanical response to three laser refractive surgeries. Methods: Two hundred and twenty-seven patients who submitted to transepithelial photorefractive keratectomy (tPRK), femtosecond laser-assisted in-situ keratomileusis (FS-LASIK), or small-incision lenticule extraction (SMILE) were included in this study. All cases were examined with the Corvis ST preoperatively (up to 3 months) and postoperatively at 1, 3, and 6 months, and the differences in the main device parameters were assessed. The three groups were matched in age, gender ratio, corneal thickness, refractive error corrections, optical zone diameter, and intraocular pressure. They were also matched in the preoperative biomechanical metrics provided by the Corvis ST including stiffness parameter at first applanation (SP-A1), integrated inverse radius (IIR), deformation amplitude (DA), and deformation amplitude 2 mm away from apex and the apical deformation (DARatio2mm). Results: The results demonstrated a significant decrease post-operation in SP-A1 and significant increases in IIR, DA, and DARatio2mm (p < 0.05), all of which indicated reductions in overall corneal stiffness. Inter-procedure comparisons provided evidence that the smallest overall stiffness reduction was in the tPRK group, followed by the SMILE, and then the FS-LASIK group (p < 0.05). These results remained valid after correction for the change in CCT between pre and 6 months post-operation and for the percentage tissue altered. In all three surgery groups, higher degrees of refractive correction resulted in larger overall stiffness losses based on most of the biomechanical metrics. Conclusion: The corneal biomechanical response to the three surgery procedures varied significantly. With similar corneal thickness loss, the reductions in overall corneal stiffness were the highest in FS-LASIK and the lowest in tPRK.

Preparation and evaluation of ultra-long open-tubular capillary columns modified with zeolitic imidazolate framework-8 incorporated polymeric porous layer for liquid chromatography.

An ultra-long (5 m) open tubular capillary liquid chromatographic column was prepared by incorporating Metal Organic Framework (MOF), zeolitic imidazolate framework-8 (ZIF-8), directly into polymer coating, which was synthesized by the copolymerization of 4-vinylbenzyl chloride and divinylbenzene, on the capillary inner surface. The prepared ZIF-8 incorporate polymeric open tubular capillary column (denoted as ZIF-8-p(VBC/DVB) OTCC) was evaluated with thiourea, alkylbenzenes and polycyclic aromatic hydrocarbons as probe molecules. The results showed that the ultra-long column achieved absolute column efficiency of 130,000 plates for thiourea, and the incorporation of ZIF-8 effectively improved the chromatography performance of the OTCC. Baseline separation of aromatic compounds and position isomers was achieved based on multiple interactions provided by the zeolitic imidazolate framework and polymer, including hydrophobic interaction, π-π stacking interaction and the coordination effect. The RSD values (run-to-run, day-to-day, column-to-column, n = 3) of retention time of phenylenediamine isomers and propylbenzene isomers were less than 0.7%, 1.2% and 4.0% respectively, suggesting excellent repeatability. Finally, the prepared ZIF-8-p(VBC/DVB) OTCC was applied to the separation of hydroxyacetophenone isomers with satisfied results.