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Abstract Lipid nanoparticles (LNPs) exhibit remarkable mRNA delivery efficiency, yet their majority accumulate in the liver or spleen after injection. Tissue‐specific mRNA delivery can be achieved through modulating LNP properties, such as tuning PEGylation or varying lipid components systematically. In this paper, a streamlined method is used for incorporating tumor‐targeting peptides into the LNPs; the programmed death ligand 1 (PD‐L1) binding peptides are conjugated to PEGylated lipids via a copper‐free click reaction, and directly incorporated into the LNP composition (Pep LNPs). Notably, Pep LNPs display robust interaction with PD‐L1 proteins, which leads to the uptake of LNPs into PD‐L1 overexpressing cancer cells both in vitro and in vivo. To evaluate anticancer immunotherapy mediated by restoring tumor suppressor, mRNA encoding phosphatase and tensin homolog (PTEN) is delivered via Pep LNPs to PTEN‐deficient triple‐negative breast cancers (TNBCs). Pep LNPs loaded with PTEN mRNA specifically promotes autophagy‐mediated immunogenic cell death in 4T1 tumors, resulting in effective anticancer immune responses. This study highlights the potential of tumor‐targeted LNPs for mRNA‐based cancer therapy.

In this paper, we present a practical approach for the integrated problem of train timetabling and rolling stock scheduling, namely the Resource-oriented Augmentation of a Train Timetable (RATT). As the integrated problem is known to be challenging for real-world instances, the RATT approach is a possible alternative to handle the problem, especially considering the Korean high-speed railway circumstances. In our RATT approach, we extend an existing timetable via train augmentation under the given number of rolling stocks and the managerial constraints of a railway company. To this end, we develop three approaches to solve a real-world problem from a Korean high-speed railway company. First, a generic mixed integer programming model based on the network flow structure is formulated. Second, a train generation technique is adopted to the generic model to enhance the model solvability. Finally, an iterative decomposition scheme is tested to handle large scale problems. Through computational experiments, we show that the train generation technique is essential for the RATT approach, and the decomposition scheme should be considered for large scale problems.

The success of research using convolutional neural network (CNN)-based camera sensor processing for autonomous driving has accelerated the development of autonomous driving vehicles. Since autonomous driving algorithms require high-performance computing for fast and accurate perception, a heterogeneous embedded platform consisting of a graphics processing unit (GPU) and a power-efficient dedicated deep learning accelerator (DLA) has been developed to efficiently implement deep learning algorithms in limited hardware environments. However, because the hardware utilization of these platforms remains low, performance differences such as processing speed and power efficiency between the heterogeneous platform and an embedded platform with only GPUs remain insignificant. To address this problem, this paper proposes an optimization technique that fully utilizes the available hardware resources in heterogeneous embedded platforms using parallel processing on DLA and GPU. Our proposed power-efficient network inference method improves processing speed without losing accuracy based on analyzing the problems encountered when dividing the networks between DLA and GPU for parallel processing. Moreover, the high compatibility of the proposed method is demonstrated by applying the proposed method to various CNN-based object detectors. The experimental results show that the proposed method increases the processing speed by 77.8%, 75.6%, and 55.2% and improves the power efficiency by 84%, 75.9%, and 62.3% on YOLOv3, SSD, and YOLOv5 networks, respectively, without an accuracy penalty.

Long acting injectables (LAIs) using polymeric microspheres has been developed to increase patient compliance and reduce side effects. Among many methods for manufacturing polymeric microspheres, microfluidics technology is known to have excellent characteristics in that the produced polymeric microspheres have perfect spherical shape without surface defect and uniform size, and thus have outstanding efficacy without initial burst. However, the mass production of polymeric microspheres was not realized by the inherent limitation that microfluidics is suitable for small quantity manufacturing. Overcoming such limitations, we could show mass production of finasteride-loaded polymeric microspheres (PLGA 7525) for LAIs using our microfluidic manufacturing platform technology, IVL-DrugFluidic®. The microfluidic channels used in manufacturing were optimized through computational fluid dynamics (CFD) simulation to minimize the flow variation between microchannels and eliminated disturbance outside of microchannels by resistance channels. In addition, the solvent removal was improved by applying the baffle and foam breaker system. Therefore, microspheres were mass-produced in the GMP manufacturing environment in perfect spherical shape, smooth surface, and even size distribution. The encapsulation efficiency was almost 100% and the residual solvent was under the Standard of regulation. In the clinical trial using microspheres mass-produced by IVL-DrugFluidic®, we confirmed that the drug release was stably maintained for a month, the target period without initial burst. It was also confirmed that the drug release by dose of microspheres was uniformly proportional. In conclusion, the microsphere manufacturing platform technology, IVL-DrugFluidic® has been proven to be an appropriate system for mass production of polymeric microspheres optimized for LAIs through physicochemical characteristics and clinical trial.

Abstract Background Photodynamic therapy (PDT) is a promising strategy to promote antitumor immunity by inducing immunogenic cell death (ICD) in tumor cells. However, practical PDT uses an intense visible light owing to the shallow penetration depth of the light, resulting in immunosuppression at the tumor tissues. Methods Herein, we propose an implantable micro-scale light-emitting diode device (micro-LED) guided PDT that enables the on-demand light activation of photosensitizers deep in the body to potentiate antitumor immunity with mild visible light. Results The micro-LED is prepared by stacking one to four micro-scale LEDs (100 μm) on a needle-shape photonic device, which can be directly implanted into the core part of the tumor tissue. The photonic device with four LEDs efficiently elicits sufficient light output powers without thermal degradation and promotes reactive oxygen species (ROS) from a photosensitizer (verteporfin; VPF). After the intravenous injection of VPF in colon tumor-bearing mice, the tumor tissues are irradiated with optimal light intensity using an implanted micro-LED. While tumor tissues under intense visible light causes immunosuppression by severe inflammatory responses and regulatory T cell activation, mild visible light elicits potent ICD in tumor cells, which promotes dendritic cell (DC) maturation and T cell activation. The enhanced therapeutic efficacy and antitumor immunity by micro-LED guided PDT with mild visible light are assessed in colon tumor models. Finally, micro-LED guided PDT in combination with immune checkpoint blockade leads to 100% complete tumor regression and also establishes systemic immunological memory to prevent the recurrence of tumors. Conclusion Collectively, this study demonstrates that micro-LED guided PDT with mild visible light is a promising strategy for cancer immunotherapy.

We applied quantitative CT image matching to assess the degree of motion in the idiopathic ILD such as usual interstitial pneumonia (UIP) and nonspecific interstitial pneumonia (NSIP). Twenty-one normal subjects and 42 idiopathic ILD (31 UIP and 11 NSIP) patients were retrospectively included. Inspiratory and expiratory CT images, reviewed by two experienced radiologists, were used to compute displacement vectors at local lung regions matched by image registration. Normalized three-dimensional and two-dimensional (dorsal-basal) displacements were computed at a sub-acinar scale. Displacements, volume changes, and tissue fractions in the whole lung and the lobes were compared between normal, UIP, and NSIP subjects. The dorsal-basal displacement in lower lobes was smaller in UIP patients than in NSIP or normal subjects (p = 0.03, p = 0.04). UIP and NSIP were not differentiated by volume changes in the whole lung or upper and lower lobes (p = 0.53, p = 0.12, p = 0.97), whereas the lower lobe air volume change was smaller in both UIP and NSIP than normal subjects (p = 0.02, p = 0.001). Regional expiratory tissue fractions and displacements showed positive correlations in normal and UIP subjects but not in NSIP subjects. In summary, lung motionography quantified by image registration-based lower lobe dorsal-basal displacement may be used to assess the degree of motion, reflecting limited motion due to fibrosis in the ILD such as UIP and NSIP.

Abstract In vivo presentation of airway hyper-responsiveness (AHR) at the different time points of the allergic reaction is not clearly understood. The purpose of this study was to investigate how AHR manifests in the airway and the lung parenchyma in vivo following exposure to different stimuli and in the early and late phases of asthma after allergen exposure. Ovalbumin (OVA)-induced allergic asthma model was established using 6-week female BALB/c mice. Enhanced pause was measured with a non-invasive method to assess AHR. The dynamic changes of the airway and lung parenchyma were evaluated with ultra-high-resolution computed tomography (128 multi-detector, 1024 × 1024 matrix) for 10 h. While the methacholine challenge showed no grossly visible changes in the proximal airway and lung parenchyma despite provoking AHR, the OVA challenge induced significant immediate changes manifesting as peribronchial ground glass opacities, consolidations, air-trapping, and paradoxical proximal airway dilatations. After resolution of immediate response, multiple episodes of AHRs occurred with paradoxical proximal airway dilatation and peripheral air-trapping in late phase over a prolonged time period in vivo. Understanding of airflow limitation based on the structural changes of asthmatic airway would be helpful to make an appropriate drug delivery strategy for the treatment of asthma.

Abstract Image registration-based local displacement analysis enables evaluation of respiratory motion between two computed tomography-captured lung volumes. The objective of this study was to compare diaphragm movement among emphysema, idiopathic pulmonary fibrosis (IPF) and normal subjects. 29 normal, 50 emphysema, and 51 IPF subjects were included. A mass preserving image registration technique was used to compute displacement vectors of local lung regions at an acinar scale. Movement of the diaphragm was assumed to be equivalent to movement of the basal lung within 5 mm from the diaphragm. Magnitudes and directions of displacement vectors were compared between the groups. Three-dimensional (3D) and apico-basal displacements were smaller in emphysema than normal subjects (P = 0.003, P = 0.002). Low lung attenuation area on expiration scan showed significant correlations with decreased 3D and apico-basal displacements (r = − 0.546, P

Abstract Chronic obstructive pulmonary disease (COPD) is a heterogeneous disease and the traditional variables extracted from computed tomography (CT) images may not be sufficient to describe all the topological features of lung tissues in COPD patients. We employed an unsupervised three-dimensional (3D) convolutional autoencoder (CAE)-feature constructor (FC) deep learning network to learn from CT data and derive tissue pattern-clusters jointly. We then applied exploratory factor analysis (EFA) to discover the unobserved latent traits (factors) among pattern-clusters. CT images at total lung capacity (TLC) and residual volume (RV) of 541 former smokers and 59 healthy non-smokers from the cohort of the SubPopulations and Intermediate Outcome Measures in the COPD Study (SPIROMICS) were analyzed. TLC and RV images were registered to calculate the Jacobian (determinant) values for all the voxels in TLC images. 3D Regions of interest (ROIs) with two data channels of CT intensity and Jacobian value were randomly extracted from training images and were fed to the 3D CAE-FC model. 80 pattern-clusters and 7 factors were identified. Factor scores computed for individual subjects were able to predict spirometry-measured pulmonary functions. Two factors which correlated with various emphysema subtypes, parametric response mapping (PRM) metrics, airway variants, and airway tree to lung volume ratio were discriminants of patients across all severity stages. Our findings suggest the potential of developing factor-based surrogate markers for new COPD phenotypes.

Abstract Background Previous studies suggested that the prone position (PP) improves oxygenation and reduces mortality among patients with acute respiratory distress syndrome (ARDS). However, the mechanism of this clinical benefit of PP is not completely understood. The aim of the present study was to quantitatively compare regional characteristics of lung functions in the PP with those in the supine position (SP) using inspiratory and expiratory computed tomography (CT) scans. Methods Ninety subjects with normal pulmonary function and inspiration and expiration CT images were included in the study. Thirty-four subjects were scanned in PP, and 56 subjects were scanned in SP. Non-rigid image registration-based inspiratory-expiratory image matching assessment was used for regional lung function analysis. Tissue fractions (TF) were computed based on the CT density and compared on a lobar basis. Three registration-derived functional variables, relative regional air volume change (RRAVC), volumetric expansion ratio (J), and three-dimensional relative regional displacement (s*) were used to evaluate regional ventilation and deformation characteristics. Results J was greater in PP than in SP in the right middle lobe (P = 0 .025), and RRAVC was increased in the upper and right middle lobes (P

Abstract Background Dust exposure has been reported as a risk factor of pulmonary disease, leading to alterations of segmental airways and parenchymal lungs. This study aims to investigate alterations of quantitative computed tomography (QCT)-based airway structural and functional metrics due to cement-dust exposure. Methods To reduce confounding factors, subjects with normal spirometry without fibrosis, asthma and pneumonia histories were only selected, and a propensity score matching was applied to match age, sex, height, smoking status, and pack-years. Thus, from a larger data set (N = 609), only 41 cement dust-exposed subjects were compared with 164 non-cement dust-exposed subjects. QCT imaging metrics of airway hydraulic diameter (D h), wall thickness (WT), and bifurcation angle (θ) were extracted at total lung capacity (TLC) and functional residual capacity (FRC), along with their deformation ratios between TLC and FRC. Results In TLC scan, dust-exposed subjects showed a decrease of D h (airway narrowing) especially at lower-lobes (p

A prodrug is bioreversible medication that is specifically converted to the active drugs by enzymes overexpressed in the tumor microenvironment, which can considerably reduce the chemotherapy-induced side effects. However, prodrug strategies usually have low antitumor efficacy compared to free drugs by delayed drug release. This is because they need time to be activated by enzymatic cleavage and they also cannot be fully recovered to the active drugs. Therefore, highly potent anticancer drug should be considered to expect a sufficient antitumor efficacy. Herein, we propose tumor-specific monomethyl auristatin E (MMAE) prodrug nanoparticles for safe and effective chemotherapy. The cathepsin B-specific cleavable FRRG peptide and MMAE are chemically conjugated via one-step simple synthetic chemistry. The resulting FRRG-MMAE molecules form stable nanoparticles without any additional carrier materials by hydrophobic interaction-derived aggregations. The FRRG-MMAE nanoparticles efficiently accumulate within the tumor tissues owing to the enhanced permeability and retention (EPR) effect and inhibit the tubulin polymerization by releasing free MMAE in the cathepsin B-overexpressed tumor cells. In contrast, FRRG-MMAE nanoparticles maintain a non-toxic inactive state in the normal tissues owing to innately low cathepsin B expression, thereby reducing MMAE-related severe toxicity. Collectively, this study provides a promising approach for safe and effective chemotherapy via MMAE-based prodrug nanoparticles, which may open new avenues for advanced drug design for translational nanomedicine.

Abstract Background Quantitative computed tomographic (QCT) imaging-based metrics enable to quantify smoking induced disease alterations and to identify imaging-based clusters for current smokers. We aimed to derive clinically meaningful sub-groups of former smokers using dimensional reduction and clustering methods to develop a new way of COPD phenotyping. Methods An imaging-based cluster analysis was performed for 406 former smokers with a comprehensive set of imaging metrics including 75 imaging-based metrics. They consisted of structural and functional variables at 10 segmental and 5 lobar locations. The structural variables included lung shape, branching angle, airway-circularity, airway-wall-thickness, airway diameter; the functional variables included regional ventilation, emphysema percentage, functional small airway disease percentage, Jacobian (volume change), anisotropic deformation index (directional preference in volume change), and tissue fractions at inspiration and expiration. Results We derived four distinct imaging-based clusters as possible phenotypes with the sizes of 100, 80, 141, and 85, respectively. Cluster 1 subjects were asymptomatic and showed relatively normal airway structure and lung function except airway wall thickening and moderate emphysema. Cluster 2 subjects populated with obese females showed an increase of tissue fraction at inspiration, minimal emphysema, and the lowest progression rate of emphysema. Cluster 3 subjects populated with older males showed small airway narrowing and a decreased tissue fraction at expiration, both indicating air-trapping. Cluster 4 subjects populated with lean males were likely to be severe COPD subjects showing the highest progression rate of emphysema. Conclusions QCT imaging-based metrics for former smokers allow for the derivation of statistically stable clusters associated with unique clinical characteristics. This approach helps better categorization of COPD sub-populations; suggesting possible quantitative structural and functional phenotypes.

Immunogenic cell death (ICD) is a powerful trigger eliciting strong immune responses against tumors. However, traditional chemoimmunotherapy (CIT) does not last long enough to induce sufficient ICD, and also does not guarantee the safety of chemotherapeutics. To overcome the disadvantages of the conventional approach, we used doxorubicin (DOX) as an ICD inducer, and poly(lactic-co-glycolic acid) (PLGA)-based nanomedicine platform for controlled release of DOX. The diameter of 138.7 nm of DOX-loaded PLGA nanoparticles (DP-NPs) were stable for 14 days in phosphate-buffered saline (PBS, pH 7.4) at 37 °C. Furthermore, DOX was continuously released for 14 days, successfully inducing ICD and reducing cell viability in vitro. Directly injected DP-NPs enabled the remaining of DOX in the tumor site for 14 days. In addition, repeated local treatment of DP-NPs actually lasted long enough to maintain the enhanced antitumor immunity, leading to increased tumor growth inhibition with minimal toxicities. Notably, DP-NPs treated tumor tissues showed significantly increased maturated dendritic cells (DCs) and cytotoxic T lymphocytes (CTLs) population, showing enhanced antitumor immune responses. Finally, the therapeutic efficacy of DP-NPs was maximized in combination with an anti-programmed death-ligand 1 (PD-L1) antibody (Ab). Therefore, we expect therapeutic efficacies of cancer CIT can be maximized by the combination of DP-NPs with immune checkpoint blockade (ICB) by achieving proper therapeutic window and continuously inducing ICD, with minimal toxicities.

Abstract Background Classification of COPD is usually based on the severity of airflow, which may not sensitively differentiate subpopulations. Using a multiscale imaging-based cluster analysis (MICA), we aim to identify subpopulations for current smokers with COPD. Methods Among the SPIROMICS subjects, we analyzed computed tomography images at total lung capacity (TLC) and residual volume (RV) of 284 current smokers. Functional variables were derived from registration of TLC and RV images, e.g. functional small airways disease (fSAD%). Structural variables were assessed at TLC images, e.g. emphysema and airway wall thickness and diameter. We employed an unsupervised method for clustering. Results Four clusters were identified. Cluster 1 had relatively normal airway structures; Cluster 2 had an increase of fSAD% and wall thickness; Cluster 3 exhibited a further increase of fSAD% but a decrease of wall thickness and airway diameter; Cluster 4 had a significant increase of fSAD% and emphysema. Clinically, Cluster 1 showed normal FEV1/FVC and low exacerbations. Cluster 4 showed relatively low FEV1/FVC and high exacerbations. While Cluster 2 and Cluster 3 showed similar exacerbations, Cluster 2 had the highest BMI among all clusters. Conclusions Association of imaging-based clusters with existing clinical metrics suggests the sensitivity of MICA in differentiating subpopulations.

Block-based hierarchical motion estimations are widely used for frame interpolation in frame-rate up-conversion and are successful in generating high-quality interpolations. However, it still fails in the motion estimation of small objects when a background region moves in a different direction. This is because the motion of small objects is neglected by the down-sampling and over-smoothing operations at the top level of image pyramids in the maximum a posterior (MAP) method. Consequently, the motion vector of small objects cannot be detected at the bottom level, and therefore, the small objects often appear deformed in an interpolated frame. This paper proposes a novel algorithm that preserves the motion vector of the small objects by adding a secondary motion vector candidate that represents the movement of the small objects. This additional candidate always propagates from the top to the bottom layers of the image pyramid. Experimental results demonstrate that the intermediate frame interpolated by the proposed algorithm significantly improves the visual quality when compared with conventional MAP-based frame interpolation.

ObjectivesExtra-thoracic tumors send out pilot cells that attach to the pulmonary endothelium. We hypothesized that this could alter regional lung mechanics (tissue stiffening or accumulation of fluid and inflammatory cells) through interactions with host cells. We explored this with serial inspiratory computed tomography (CT) and image matching to assess regional changes in lung expansion.Materials and methodsWe retrospectively assessed 44 pairs of two serial CT scans on 21 sarcoma patients: 12 without lung metastases and 9 with lung metastases. For each subject, two or more serial inspiratory clinically-derived CT scans were retrospectively collected. Two research-derived control groups were included: 7 normal nonsmokers and 12 asymptomatic smokers with two inspiratory scans taken the same day or one year apart respectively. We performed image registration for local-to-local matching scans to baseline, and derived local expansion and density changes at an acinar scale. Welch two sample t test was used for comparison between groups. Statistical significance was determined with a p value < 0.05.ResultsLung regions of metastatic sarcoma patients (but not the normal control group) demonstrated an increased proportion of normalized lung expansion between the first and second CT. These hyper-expanded regions were associated with, but not limited to, visible metastatic lung lesions. Compared with the normal control group, the percent of increased normalized hyper-expanded lung in sarcoma subjects was significantly increased (p < 0.05). There was also evidence of increased lung "tissue" volume (non-air components) in the hyper-expanded regions of the cancer subjects relative to non-hyper-expanded regions. "Tissue" volume increase was present in the hyper-expanded regions of metastatic and non-metastatic sarcoma subjects. This putatively could represent regional inflammation related to the presence of tumor pilot cell-host related interactions.ConclusionsThis new quantitative CT (QCT) method for linking serial acquired inspiratory CT images may provide a diagnostic and prognostic means to objectively characterize regional responses in the lung following oncological treatment and monitoring for lung metastases.