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Introduction Postoperative dysphonia is mostly caused by vocal fold scarring, and careful management of vocal fold surgery has been reported to reduce the risk of scar formation. However, depending on the vocal fold injury, treatment of postoperative dysphonia can be challenging. Objective The goal of the current study was to develop a novel prophylactic regenerative approach for the treatment of injured vocal folds after surgery, using biodegradable gelatin hydrogel microspheres as a drug delivery system for basic fibroblast growth factor. Methods Videoendoscopic laryngeal surgery was performed to create vocal fold injury in 14 rabbits. Immediately following this procedure, biodegradable gelatin hydrogel microspheres with basic fibroblast growth factor were injected in the vocal fold. Two weeks after injection, larynges were excised for evaluation of vocal fold histology and mucosal movement. Results The presence of poor vibratory function was confirmed in the injured vocal folds. Histology and digital image analysis demonstrated that the injured vocal folds injected with gelatin hydrogel microspheres with basic fibroblast growth factor showed less scar formation, compared to the injured vocal folds injected with gelatin hydrogel microspheres only, or those without any injection. Conclusion A prophylactic injection of basic fibroblast growth factor -containing biodegradable gelatin hydrogel microspheres demonstrates a regenerative potential for injured vocal folds in a rabbit model. Resumo Introdução A disfonia pós-operatória é causada principalmente por cicatrizes nas pregas vocais. Tem sido relatado que o manejo cuidadoso da cirurgia das pregas vocais reduz o risco de formação de cicatriz. No entanto, a depender da lesão da prega vocal, o tratamento da disfonia pós-operatória pode ser desafiador. Objetivo Desenvolver uma nova abordagem regenerativa profilática para o tratamento de pregas vocais lesionadas após a cirurgia, com microesferas biodegradáveis de hidrogel de gelatina como sistema de administração de medicamentos para o Fator Básico de Crescimento de Fibroblastos (bFGF). Método A cirurgia laríngea videoendoscópica foi feita para criar lesão nas pregas vocais em 14 coelhos. Imediatamente após esse procedimento, microesferas biodegradáveis de hidrogel de gelatina com bFGF foram injetadas na prega vocal. Duas semanas após a injeção, as laringes foram excisadas para avaliação da histologia das pregas vocais e do movimento da mucosa. Resultados A presença de função vibratória deficiente foi confirmada nas pregas vocais lesionadas. A histologia e a análise de imagem digital demonstraram que as pregas vocais lesionadas injetadas com microesferas de hidrogel de gelatina com bFGF apresentaram menor formação de cicatriz, em comparação com as pregas vocais lesionadas injetadas apenas com microesferas de hidrogel de gelatina ou aquelas sem injeção. Conclusão Uma injeção profilática de microesferas biodegradáveis de hidrogel de gelatina com bFGF demonstra um potencial regenerativo para pregas vocais lesionadas em um modelo de coelho.

Background The present study aimed to evaluate the toxicity and efficacy of stereotactic body radiotherapy (SBRT) for localized prostate cancer. Patients and methods We investigated 25 patients treated with SBRT of 35 Gy per five fractions from May 2014 to March 2015. Results The median age of patients was 70 years, four (16%) patients were low risk and 21 (84%) were intermediate risk. Seven (28%) patients received neoadjuvant androgen-deprivation therapy. The median follow-up time was 53 months. Grade 2 acute and late genitourinary toxicities were observed in five (20%) and two (8%) patients and there were no Grade 2 gastrointestinal toxicities. There were no Grade 3 or higher acute or late toxicities at 2 years follow-up. The biochemical relapse-free survival rate at 2 years was 100%. Conclusion SBRT of 35 Gy per five fractions is a promising treatment method in the short term for prostate cancer.

Chlorophyll content is one of the essential parameters to assess the growth process of the fruit trees. This present study developed a model for estimation of canopy averaged chlorophyll content (CACC) of pear trees using the convolutional autoencoder (CAE) features of hyperspectral (HS) data. This study also demonstrated the inspection of anomaly among the trees by employing multidimensional scaling on the CAE features and detected outlier trees prior to fit nonlinear regression models. These outlier trees were excluded from the further experiments that helped in improving the prediction performance of CACC. Gaussian process regression (GPR) and support vector regression (SVR) techniques were investigated as nonlinear regression models and used for prediction of CACC. The CAE features were proven to be providing better prediction of CACC when compared with the direct use of HS bands or vegetation indices as predictors. The CACC prediction performance was improved with the exclusion of the outlier trees during training of the regression models. It was evident from the experiments that GPR could predict the CACC with better accuracy compared to SVR. In addition, the reliability of the tree canopy masks, which were utilized for averaging the features' values for a particular tree, was also evaluated.

Water/ice/land region segmentation is an important task for remote sensing, as it analyses the occurrence of water or ice on the earth's surface. Many previous deep learning researches effectively utilized multispectral satellite images for highly accurate water/ice/land region segmentation. However, the deep-learning-based segmentation of synthetic aperture radar images still remains a challenging task due to the unavailability of enough labeled data. In order to overcome this issue, we designed a two-step deep-learning-based transfer learning model that needs a very limited number of labeled samples. The proposed approach consists of two models. The first model is a deep encoder–decoder 6SD to Landsat-8 multispectral translation model (DTF) that translates fully polarimetric PALSAR-2 6SD data to six new features. As for the second model (transfer learning), it utilizes the DTF features to fine-tune the model using the Landsat-8 multispectral pretrained model for water/ice/land segmentation. Hereinafter, the proposed two-step model is referred to as DTF-TL. Also, a qualitative and quantitative analysis was carried out to evaluate the performance of the proposed model (DTF-TL) and compare it with various transfer learning methods. Overall, the DTF-TL model outperformed the other models with consistent and reliable water/ice/land segmentation results in terms of the recall (0.980), precision (0.981), F1-score (0.981), mean intersection over union (0.962), and accuracy (0.989).

Severe cutaneous adverse reactions (SCARs) are important in postmarketing drug safety because SCAR patients were highest in the adverse drug reaction relief system of Japan. The SCAR symptoms of Stevens-Johnson syndrome (SJS) and toxic epidermal necrolysis (TEN) include high fever, severe mucosal impairment, and epidermal necrosis-induced erosions and blisters. Approximately 600 cases of SJS and 300 cases of TEN are reported annually in Japan. Many suspected drugs such as acetaminophen, lamotrigine, allopurinol, and carbamazepine have been reported. Over the last 15 years, an association between human leukocyte antigen and SJS/TEN onset has been reported with several drugs. Pathophysiological examinations in those reports revealed marked CD8-positive T cell infiltration into epidermal lesions, and the presence of cytotoxic granulysin, soluble Fas ligand, and tumor necrosis factor (TNF)-α in blister fluid. Therefore, SJS and TEN are immunological disorders that lead to epidermal necrosis and are consequently treated with the systemic administration of corticosteroids and with high-dose intravenous immunoglobulin therapy and plasma exchange in severe cases. Additionally, because the epidermal necrosis has characteristics similar to those of organ rejection after transplantation, the administration of cyclosporine, an immunosuppressant that inhibits helper T cell activation, has been attempted. Further, the administration of the TNF-α inhibitor etanercept has also been reported. This review summarizes current knowledge on the mechanisms of onset of SJS/TEN and their treatments.

Different from the saliency detection on static images, the context and dynamic information from video sequences play an important role in saliency prediction on dynamic scenes. In this work, we propose a novel feedback recurrent network (FBR-CNN) to simultaneously learn the abundant contextual and dynamic features for video saliency detection. In order to learn the dynamic relationship from video frames, we incorporate the recurrent convolutional layers into the standard feed-forward CNN model. With multiple video frames as inputs, the long-term dependence and contextual relevance over time could be strengthen due to the powerful recurrent units. Unlike the feed-forward only CNN models, we propose to feed back the learned CNN features from high-level feedback recurrent blocks (FBR-block) to low-level layers to further enhance the the contextual representations. Experiments on the public video saliency benchmarks demonstrate that the model with feedback connections and recurrent units can dramatically improve the performance of the baseline feedforward structure. Moreover, although the proposed model has few parameters (~6.5 MB), it achieves comparable performance against the existing video saliency approaches.

For the semiconductor and liquid crystal display manufacturing process, resist removal by using laser irradiation has been investigated instead of conventional processes such as oxygen plasma and chemical method. An advanced laser resist stripping method for the positive-tone diazonaphthoquinone (DNQ) / novolak resist was successfully developed without causing the laser damage to the Si wafer. The pulsed laser irradiation in water can improve the resist stripping effect when compared with that of conventional atmosphere irradiation, however, the mechanism has yet to be clarified. In this study, we investigated the analysis of resist stripping phenomenon by using a high-speed laser imaging system. A pulsed laser at 640 nm (pulse duration: 40 ns) was used as an illumination laser and a CCD camera detected the reflectance image on the sample. Time resolution of this system depended on the pulse duration of illumination laser. Time-resolved images were acquired based on the “1-on-1” method. Time-resolved images were acquired from 40 ns to 10 us after the laser irradiation. At the laser irradiated spot, changes of the resist were observed after 40 ns from the laser irradiation. The resist was completely stripped from the Si wafer surface after 10 us. The duration of resist removal phenomenon in the water condition was longer than that in the normal atmosphere condition. A resist stripping mechanism could be elucidated by combining experimental high-speed laser imaging and a finite element (FE) analysis. The mechanism of the resist stripping in the water condition will be presented.

Biomarkers are an important drug developmental tool. Assessment of quantitative analytical methods of biomarkers is not included in any regulatory documents in Japan. Use of biomarkers in clinical evaluations and supporting the post-marketing evaluation of drug efficacy and/or adverse reactions requires assessment and full validation of analytical methods for these biomarkers. The Biomarker Analytical Method Validation Study Group is a research group in Japan comprising industry and regulatory experts. Group members discussed and prepared this ‘points to consider document’ covering measurements of endogenous metabolites/peptides/proteins by ligand binding assays and chromatographic methods with or without mass spectrometry. We hope this document contributes to the global harmonization of biomarker assay validation.

Saliency detection research has achieved great progress with the emergence of convolutional neural network (CNN) in recent years. Most deep learning based saliency models mainly adopt the feed-forward CNN architecture with heavy burden of parameters to learn features via bottom-up manner. However, this forward only process may ignore the intrinsic relationship and potential benefits of top-down connections or information flow. To the best of our knowledge, there is not any work to explore the feedback connection especially in a recursive manner for saliency detection. Therefore, we propose and explore a simple, intuitive yet powerful feedback recursive convolutional model (FBNet) for image saliency detection. Specifically, we first select and define a lightweight baseline feed-forward CNN structure (~4.7MB), then the high-level multi-scale saliency features are fed back to the low-level convolutional blocks in a recursive process. Experimental results show that the feedback recursive process is a promising way to improve the performance of the baseline forward CNN model. Besides, despite having relatively few CNN parameters, the proposed FBNet model achieves competitive results on the public saliency detection benchmarks.

Among the various histopathological patterns of drug-induced interstitial lung disease (DILD), diffuse alveolar damage (DAD) is associated with poor prognosis. However, there is no reliable biomarker for its accurate diagnosis. Here, we show stratifin/14-3-3σ (SFN) as a biomarker candidate found in a proteomic analysis. The study included two independent cohorts and controls (n = 432 samples). SFN was specifically elevated in DILD patients with DAD, and was superior to the known biomarkers, KL-6 and SP-D, in discrimination of DILD patients with DAD from patients with other DILD patterns or other lung diseases, including bacterial pneumonia. SFN was also increased in serum from patients with idiopathic DAD, and in lung tissues and bronchoalveolar lavage fluid of patients with DAD. In vitro analysis using the A549 cell line suggested that extracellular release of SFN occurred via p53 activation. We conclude that serum SFN is a promising biomarker for DAD diagnosis.

This study investigates determinants of debt covenants in Japanese loan markets. We focus on a unique monitoring mechanism by Japanese banks and hypothesise that debt covenants substitute for the traditional main bank governance. Consistently, we find that debt covenants are less likely to be used for firms with stronger ties with their main banks. We also document that such use of debt covenants results in borrower’s upward earnings management. Overall, our evidence suggests that, in the Japanese context, debt covenants are used as a substitute for the main bank system yet they alone are an incomplete monitoring mechanism.

Stevens–Johnson syndrome (SJS) and toxic epidermal necrolysis (TEN) are acute-onset mucocutaneous diseases induced by infectious agents and/or inciting drugs. We have reported that the main causative drugs for SJS/TEN with severe ocular complications (SOC) were cold medicines, including multi-ingredient cold medications and nonsteroidal anti-inflammatory drugs (NSAIDs). Moreover, we also reported that acetaminophen is the most frequent causative drug in various cold medicines. In this study, we focused on acetaminophen-related SJS/TEN with SOC and analyzed HLA-class II (HLA-DRB1, DQB1) in addition to HLA-class I (HLA-A, B, C). We studied the histocompatibility antigen genes HLA-DRB1 and DQB1 in addition to HLA-A, B, and C in 80 Japanese patients with acetaminophen-related SJS/TEN with SOC. We performed polymerase chain reaction amplification followed by hybridization with sequence-specific oligonucleotide probes (PCR-SSO) using commercial bead-based typing kits. We also used genotyped data from 113 healthy volunteers for HLA-DRB1 and DQB1, and 639 healthy volunteers for HLA-A, B, and C. HLA-DRB1*08:03 and DRB1*12:02 were associated with acetaminophen-related SJS/TEN with SOC, although the results ceased to be significant when we corrected the p-value for the number of alleles detected. HLA-A*02:06 was strongly associated with acetaminophen-related SJS/TEN with SOC (carrier frequency: p = 4.7 × 10−12, Pc = 6.6 × 10−11, OR = 6.0; gene frequency: p = 8.0 × 10−13, Pc = 1.1 × 10−11, OR = 4.9). HLA-B*13:01 (carrier frequency: p = 2.0 × 10−3, Pc = 0.042, OR = 4.1; gene frequency: p = 2.2 × 10−3, Pc = 0.047, OR = 3.9), HLA-B*44:03 (carrier frequency: p = 2.1 × 10−3, Pc = 0.045, OR = 2.4) and HLA-C*14:03 (carrier frequency: p = 3.4 × 10−3, Pc = 0.045, OR = 2.3) were also significantly associated, while HLA-A*24:02 was inversely associated (gene frequency: p = 6.3 × 10−4, Pc = 8.8 × 10−3, OR = 0.5). Acetaminophen-related SJS/TEN with SOC was not associated with HLA-class II (HLA-DRB1, DQB1). However, for acetaminophen-related SJS/TEN with SOC, we found an association with HLA-B*13:01 and HLA- C*14:03 in addition to HLA-A*02:06 and HLA-B*44:03, which have been described previously., Stevens–Johnson syndrome: Gene variants predispose to reaction to cold drug Researchers have identified two new gene variants that could predispose to a rare drug reaction to a common cold drug. Stevens–Johnson syndrome can be triggered by drugs and infections and is characterized by blistering of the skin and mucous membranes. Mayumi Ueta of Kyoto Prefectural University of Medicine in Japan and colleagues found an association between variants in two genes coding for human leukocyte antigen (HLA) class I molecules and Stevens–Johnson syndrome induced by acetominophen and complicated by severe eye ulcerations in Japanese patients. HLA genes code for cell surface proteins that help the immune system distinguish normal from foreign cells. Other studies have identified population-specific HLA variants associated with the syndrome. This study provides further evidence of HLA-specific ethnic differences in people diagnosed with the condition.

An automatic object-detection method is necessary to facilitate the efficient analysis of satellite images consisting of multispectral images. Considering that the relationship between spectrums is...

Objectives Macrophages are prominent inflammatory cells in wounds, and their phenotypes are altered during wound healing. They are reported to contribute to not only inflammatory responses but also tissue remodeling. However, few studies in vocal fold biology have focused on the function of macrophages. The purpose of this study was to investigate macrophage polarization and distribution in injured murine vocal folds. Study design Animal experiments with controls. Method Unilateral vocal fold stripping was performed on C57BL/6 mice, and larynges were harvested 1, 3, 5, 7, and 14 days postinjury. Immunohistochemical analysis of the vocal fold lamina propria was performed to detect the expression of classically activated (M1) and alternatively activated (M2) macrophage markers (inducible nitric oxide synthase [iNOS] and CD206, respectively) in F4/80+ macrophages. Results The proportion of F4/80+ iNOS+ cells out of all F4/80+ cells tended to increase from day 1. F4/80+ iNOS+ cell percentage tended to be high at days 1 through 7 and declined to close to a normal level by day 14. F4/80+ CD206+ cell percentage tended to decrease at day 1 and then to increase the rest of the time. In the normal vocal fold, the majority of F4/80+ macrophages were only positive for CD206. F4/80+ iNOS+ CD206+ cells were observed at days 1 through 7. Conclusion The main population of injured sites gradually shifted from M1 to M2 marker-positive macrophages in murine vocal folds. However, coexistence of M1 and M2 markers in the same macrophages was observed. Our results suggest that macrophage phenotypes are regulated by complex tissue-derived signals and exhibit dynamic changes during wound healing. Level of evidence NA Laryngoscope, 129:E135-E142, 2019.

We present a lightweight post-processing method to refine the semantic segmentation results of point cloud sequences. Most existing methods usually segment frame by frame and encounter the inherent ambiguity of the problem: based on a measurement in a single frame, labels are sometimes difficult to predict even for humans. To remedy this problem, we propose to explicitly train a network to refine these results predicted by an existing segmentation method. The network, which we call the P2Net, learns the consistency constraints between "coincident" points from consecutive frames after registration. We evaluate the proposed post-processing method both qualitatively and quantitatively on the SemanticKITTI dataset that consists of real outdoor scenes. The effectiveness of the proposed method is validated by comparing the results predicted by two representative networks with and without the refinement by the post-processing network. Specifically, qualitative visualization validates the key idea that labels of the points that are difficult to predict can be corrected with P2Net. Quantitatively, overall mIoU is improved from 10.5% to 11.7% for PointNet [1] and from 10.8% to 15.9% for PointNet++ [2].

Since the huge earth quake in 2011 in Japan, the Japanese government has strongly encouraged growth of renewable energy use. As a result, even we focus on only mega-solar photovoltaic (PV) power plants (> 1,000 kW), the amount of the power generation significantly increased. Because such rapid increasing of the PV power plants changes land use widely, verification of the spreading of the PV power plants should be essential for assessing economic/environmental issues. In this study, to verify the increasing of the PV power plants based on observations, we applied a method that can detect the PV power plants efficiently with a convolutional neural network to Landsat-8 images. From the detection, we successfully identified the increasing of the area of the PV power plants quantitatively at the same time identifying the location of each PV power plant in many prefectures in the capital region of Japan.

OBJECTIVES It is unclear whether the movement and function of the regenerated cilia on collagen-conjugated artificial trachea are the same as those of normal cilia. This study assessed the ciliary beat frequency (CBF) and ciliary transport functions (CTFs) of regenerated cilia in a canine model. METHODS A tracheal defect introduced into the anterior portion of the cervical trachea of an adult beagle dog was covered with a collagen-conjugated prosthesis. Two months later, the trachea was harvested along the long axis, both from normal and regenerated regions. The cilia were stained with isothiocyanate-conjugated wheat germ agglutinin, and their movement was monitored with a high-speed camera to analyse CBF and CTF. Four samples each were obtained from the regenerated and normal regions for CBF analysis and 7 samples each were obtained for CTF analysis. RESULTS The wheat germ agglutinin-stained cells showed well-regulated beats in both the regenerated and normal regions of the trachea. Mean CBF in the regenerated and normal regions did not differ significantly (7.11 ± 0.41 vs 7.14 ± 1.09 Hz; P = 981). By contrast, CTF was significantly lower in the regenerated region than in the normal region (30.0 ± 6.62 vs 7.43 ± 0.58 μm/s; P = 0.005). CONCLUSIONS Mean CBF in the regenerated and normal regions did not differ significantly at 2 months. The CTF in the regenerated region recovered partially but remained lower than those in the normal region. Methods are needed to improve the CTF of regenerated cilia.

To develop a pre-emptive genetic test that comprises multiple predisposing alleles for the prevention of phenytoin-related severe cutaneous adverse reactions (SCARs), three sets of patients with phenytoin-SCAR and drug-tolerant controls from Taiwan, Thailand, and Japan, were enrolled for this study. In addition to cytochrome P450 (CYP)2C9*3, we found that HLA-B*13:01, HLA-B*15:02, and HLA-B*51:01 were significantly associated with phenytoin hypersensitivity with distinct phenotypic specificities. Strikingly, we showed an increase in predictive sensitivity of concurrently testing CYP2C9*3/HLA-B*13:01/HLA-B*15:02/HLA-B*51:01 from 30.5-71.9% for selecting the individuals with the risk of developing phenytoin-SCAR in Taiwanese cohorts, accompanied by a specificity of 77.7% (combined sensitivity, 64.7%; specificity, 71.9% for three Asian populations). Meta-analysis of the four combined risk alleles showed significant associations with phenytoin-SCAR in three Asian populations. In conclusion, combining the assessment of risk alleles of HLA and CYP2C9 potentiated the usefulness of predictive genetic tests to prevent phenytoin hypersensitivity in Asians.

3D semantic segmentation of point cloud aims at assigning semantic labels to each point by utilizing and respecting the 3D representation of the data. Detailed 3D semantic segmentation of urban areas can assist policymakers, insurance companies, governmental agencies for applications such as urban growth assessment, disaster management, and traffic supervision. The recent proliferation of remote sensing techniques has led to producing high resolution multimodal geospatial data. Nonetheless, currently, only limited technologies are available to fuse the multimodal dataset effectively. Therefore, this paper proposes a novel deep learning-based end-to-end Point-wise LiDAR and Image Multimodal Fusion Network (PMNet) for 3D segmentation of aerial point cloud by fusing aerial image features. PMNet respects basic characteristics of point cloud such as unordered, irregular format and permutation invariance. Notably, multi-view 3D scanned data can also be trained using PMNet since it considers aerial point cloud as a fully 3D representation. The proposed method was applied on two datasets (1) collected from the urban area of Osaka, Japan and (2) from the University of Houston campus, USA and its neighborhood. The quantitative and qualitative evaluation shows that PMNet outperforms other models which use non-fusion and multimodal fusion (observational-level fusion and feature-level fusion) strategies. In addition, the paper demonstrates the improved performance of the proposed model (PMNet) by over-sampling/augmenting the medium and minor classes in order to address the class-imbalance issues.

The orbital angular momentum of an optical vortex field is found to twist high viscosity donor material to form a micron-scale 'spin jet'. This unique phenomenon manifests the helical trajectory of the optical vortex. Going beyond both the conventional ink jet and laser induced forward mass transfer (LIFT) patterning technologies, it also offers the formation and ejection of a micron-scale 'spin jet' of the donor material even with an ultrahigh viscosity of 4 Pa·s. This optical vortex laser induced forward mass transfer (OV-LIFT) patterning technique will enable the development of next generation printed photonic/electric/spintronic circuits formed of ultrahigh viscosity donor dots containing functional nanoparticles, such as quantum dots, metallic particles and magnetic ferrite particles, with ultrahigh spatial resolution. It can also potentially explore a completely new needleless drug injection.

In this work, we propose a Cloud Discrimination Algorithm for Landsat 8 (CDAL8) to improve a high-frequency automatic land change detection system developed at the National Institute of Advanced In...

Pharmacotherapy shows striking individual differences in pharmacokinetics and pharmacodynamics, involving drug efficacy and adverse reactions. Recent genetic research has revealed that genetic polymorphisms are important intrinsic factors for these inter-individual differences. This pharmacogenomic information could help develop safer and more effective precision pharmacotherapies and thus, regulatory guidance/guidelines were developed in this area, especially in the EU and US. The Project for the Promotion of Progressive Medicine, Medical Devices, and Regenerative Medicine by the Ministry of Health, Labour and Welfare, performed by Tohoku University, reported scientific information on the evaluation of genetic polymorphisms, mainly on drug metabolizing enzymes and transporters, during non-clinical studies and phase I clinical trials in Japanese subjects/patients. We anticipate that this paper will be helpful in drug development for the regulatory usage of pharmacogenomic information, most notably pharmacokinetics.

A recent study using the microarray for single-nucleotide polymorphisms (SNPs) genotyping specifically designed for the Japanese population in combination with genome-wide imputation showed the association of several SNPs with cold medicine-related Stevens-Johnson syndrome (SJS) and toxic epidermal necrolysis (TEN) with severe ocular complications. However, it remains to be determined whether these polymorphisms are associated with the onset of antipyretic analgesic (AA)-related SJS/TEN, the progression of severe ocular involvements (SOIs), or both AA-related SJS/TEN and SOI phenotypes. To gain a better understanding of the features of these genetic markers, we compared the allele and carrier frequencies of these SNPs among our original SJS/TEN patient groups: (a) AA-related SJS/TEN with SOIs, (b) AA-related SJS/TEN without SOIs, and (c) AA-unrelated SJS/TEN with SOIs. AA-related SJS/TEN with SOIs were found to be associated significantly with both rs6500265 [allele frequency: odds ratio (OR): 2.18; 95% confidence interval (CI): 1.30-3.65; P=0.0052; carrier frequency: OR: 2.52; 95% CI: 1.33-4.78; P=0.058] and rs9933632 (allele frequency: OR: 2.28: 95% CI: 1.37-3.79; P=0.0032; carrier frequency: OR: 2.76; 95% CI: 1.46-5.22; P=0.0031). In contrast, allele and carrier frequencies of these SNPs in patients with AA-related SJS/TEN without SOIs or with SOIs not treated with any AAs were comparable with those in healthy Japanese controls. Collectively, our findings indicate that the rs6500265 and rs9933632 SNPs could be specific markers for AA-related SJS/TEN with SOIs, suggesting that certain genetic backgrounds contribute toward the etiology of this complex syndrome.

The emergence of deep learning applications such as convolutional neural networks (CNNs) have resulted in huge improvements on computer vision applications in a wide variety of fields. However, several works demonstrated that low-quality or noisy data (even including perceptually not visible noises) may have a huge impact on the accuracy of CNN models. Therefore, as inspired by biological perception systems, some recent works proposed the use of recurrent and feedback features in CNNs as an improvement to the existing feed-forward CNNs. These recent works on the integration of recurrence and/or feedback to CNNs mostly tested deep networks on natural scenes with relatively perceptually good resolution color images. In this work, we explored the effectiveness of CNNs with recurrent and feedback features for the solar-power plant classification task on mid-resolution (1 pixel - 30×30 square meters per pixel) multi-spectral satellite images. Experiments show promising results when using top-down signals (especially recurrent and feedback features together) on CNNs for multi-spectral image classification tasks, outperforming the baseline CNN model without any recurrent and feedback structure and other approaches in the literature including deep models.

It has been reported recently that immune reactions are involved in the pathogenesis of certain types of adverse drug reactions (ADRs). We aimed to determine the associations between infections and drug-induced interstitial lung disease (DILD), rhabdomyolysis, Stevens-Johnson syndrome (SJS) and toxic epidermal necrolysis (TEN), or drug-induced liver injury (DILI) using a spontaneous adverse drug event reporting database in Japan. The reported cases were classified into three categories (anti-infectious drug group, concomitant infection group, and non-infection group) based on the presence of anti-infectious drugs (either as primary suspected drug or concomitant drug) and infectious disease. We assessed the association between four severe ADRs and the presence and seriousness of infection using logistic regression analysis. We identified 177,649 cases reported in the study period (2009–2013). Logistic regression analysis showed significant positive associations between infection status and onset of SJS/TEN or DILI (SJS/TEN: anti-infectious drug group: odds ratio (OR) 2.04, 95% CI [1.85–2.24], concomitant infection group: OR 2.44, 95% CI [2.21–2.69], DILI: anti-infectious drug group: OR 1.27, 95% CI [1.09–1.49], concomitant infection group: OR 1.25, 95% CI [1.04–1.49]), compared to the non-infection group. By contrast, there were negative or no associations between infection and DILD or rhabdomyolysis. A significantly positive association between infection and SJS/TEN seriousness (OR 1.48, 95% CI [1.10–1.98]) was observed. This study suggested that infection plays an important role in the development of SJS/TEN and DILI. For the patients with infection and/ or anti-infectious drugs, careful monitoring for severe ADRs, especially SJS/TEN, might be needed.

We develop a fully automated algorithm for determining the geological ages by crater counting from the digital terrain model (DTM) and the digital elevation model (DEM) taken by remote-sensing observations. The algorithm is based on the rotational pixel swapping method, which uses a multiplication operation between the original DTM/DEM data and the rotated data to detect impact craters. Our method does not need binarization and/or noise reduction, because noise components are automatically erased. We show that our method can detect not only simple craters but also complex circular structures such as imperfect, degraded, or overlapping craters. We demonstrate that this method succeeds in the automatic detection of hundreds to thousands of impact craters, and the estimated ages are consistent with those by manual counting in previous works. In addition, it is shown that the calculation time by this method is more than several hundred times faster than by previous methods.

In this paper, we propose a method for cloud removal from visible light RGB satellite images by extending the conditional Generative Adversarial Networks (cGANs) from RGB images to multispectral images. Satellite images have been widely utilized for various purposes, such as natural environment monitoring (pollution, forest or rivers), transportation improvement and prompt emergency response to disasters. However, the obscurity caused by clouds makes it unstable to monitor the situation on the ground with the visible light camera. Images captured by a longer wavelength are introduced to reduce the effects of clouds. Synthetic Aperture Radar (SAR) is such an example that improves visibility even the clouds exist. On the other hand, the spatial resolution decreases as the wavelength increases. Furthermore, the images captured by long wavelengths differs considerably from those captured by visible light in terms of their appearance. Therefore, we propose a network that can remove clouds and generate visible light images from the multispectral images taken as inputs. This is achieved by extending the input channels of cGANs to be compatible with multispectral images. The networks are trained to output images that are close to the ground truth using the images synthesized with clouds over the ground truth as inputs. In the available dataset, the proportion of images of the forest or the sea is very high, which will introduce bias in the training dataset if uniformly sampled from the original dataset. Thus, we utilize the t- Distributed Stochastic Neighbor Embedding (t-SNE) to improve the problem of bias in the training dataset. Finally, we confirm the feasibility of the proposed network on the dataset of four bands images, which include three visible light bands and one near-infrared (NIR) band.

Objectives: Compared with using autologous tissue, the use of artificial materials in the regeneration of tracheal defects is minimally invasive. However, this technique requires early epithelialization on the inner side of the artificial trachea. After differentiation from induced pluripotent stem cells (iPSCs), tracheal epithelial tissues may be used to produce artificial tracheas. Herein, we aimed to demonstrate that after differentiation from fluorescent protein-labeled iPSCs, tracheal epithelial tissues survived in nude rats with tracheal defects. Methods: Red fluorescent tdTomato protein was electroporated into mouse iPSCs to produce tdTomato-labeled iPSCs. Embryoid bodies derived from these iPSCs were then cultured in differentiation medium supplemented with growth factors, followed by culture on air-liquid interfaces for further differentiation into tracheal epithelium. The cells were implanted with artificial tracheas into nude rats with tracheal defects on day 26 of cultivation. On day 7 after implantation, the tracheas were exposed and examined histologically. Results: Tracheal epithelial tissue derived from tdTomato-labeled iPSCs survived in the tracheal defects. Moreover, immunochemical analyses showed that differentiated tissues had epithelial structures similar to those of proximal tracheal tissues. Conclusions: After differentiation from iPSCs, tracheal epithelial tissues survived in rat bodies, warranting the use of iPSCs for epithelial regeneration in tracheal defects.

Stevens-Johnson syndrome (SJS) and toxic epidermal necrolysis (TEN) are severe cutaneous adverse drug reactions. Recent studies have revealed that the prevalence of SJS/TEN is associated with genetic backgrounds, such as polymorphisms in human leukocyte antigens (HLAs). However, non-genetic factors contributing to the etiology of SJS/TEN are largely unknown. This study aimed to assess the involvement of concurrent infection on the pathological states of SJS/TEN, examining the severity of cutaneous symptoms and ocular involvement as well as the time to onset in drug-induced SJS/TEN patients. We recruited 257 Japanese SJS/TEN patients from June 2006 to September 2013 through a nationwide case collection network and participating hospitals and reviewed the clinical information including patient backgrounds, primary disease and medication status. Association between infection and pathological states of SJS/TEN was assessed using univariate and multivariate analyses. The concurrent infectious group of SJS/TEN patients showed a significantly higher rate of exhibiting severer dermatological and ophthalmological phenotypes and an earlier onset of SJS/TEN than the non-infectious group. Our results suggest that the infection could be a risk factor to cause severer symptoms and earlier onset of SJS/TEN.

Numerical simulations demonstrate that mid-infrared pulses are arbitrarily shaped during the differential frequency mixing of two femtosecond near-infrared pulses propagating in an engineered quasi-periodic poled medium with optical nonlinearity and group velocity dispersion. Shaped pulses, including linearly chirped pulses and pulse trains, are generated with high conversion efficiencies.

Drug-induced interstitial lung disease (DILD) is a life-threatening adverse reaction. The Japanese population is more susceptible to DILD as compared with other populations, suggesting its pathogenesis could vary depending on ethnic genetic background. We conducted case-control studies to elucidate the association between DILD and HLA alleles in the Japanese. The 177 clinically diagnosed DILD patients and 3002 healthy controls for exploration and 55 DILD patients and 201 healthy controls for validation were genotyped for four HLA genes. HLA-DRB1*04:05 was significantly associated with DILD (corrected p = 0.014); this was also validated in the other set of patients/controls. Chemical drugs other than protein therapeutics showed this association (p = 1.7 × 10−4) . The Japanese population showed a higher HLA-DRB1*04:05 frequency than most other populations. In conclusion, HLA-DRB1*04:05 could be associated with DILD susceptibility in Japanese individuals, and its high general frequency may explain the high reported incidence of DILD in Japanese.

Hyperspectral Imager Suite (HISUI) is a future spaceborne hyperspectral Earth imaging system being developed by Japanese Ministry of Economy, Trade, and Industry (METI). HISUI will be launched and deployed on International Space Station (ISS) for two - three year operation from 2020.Manufacturing and testing of Hyperspectral sensor were completed. Integration and test of HISUI Exposed Payload System is being conducted. HISUI data policy and research announcement as well as synergy with other earth observing instruments onboard ISS are also being discussed.

The building change detection, which is important for monitoring human activity in urban and sub-urban area, can be done by the using of remote sensing data. To overcome the cloud cover problem that cause the limited utilizing in optical images which is repeatedly occurred in tropical areas, we decided to use synthetic aperture radar (SAR) data, a kind of remote sensing data that does not get affected by weather condition, to fulfill this change detection purpose. In this study, Bangkok, Thailand were selected as our study area in order to demonstrate that the SAR data can be used in the area that optical data cannot be used such as tropical areas like in Thailand. As our target is to detect changes of buildings, so we have to consider separating the change that cause by seasonal and other non-target objects. To complete this purpose, we decided to use one of the deep learning techniques called U-net which is created for the image segmentation task. We have created the ground truth and used one portion for training the network and another portion for validate the result. Finally, the model that trained by our training data was able to provide promising results.

This paper presents a novel method for rare event detection from an image pair with class-imbalanced datasets. A straightforward approach for event detection tasks is to train a detection network from a large-scale dataset in an end-to-end manner. However, in many applications such as building change detection on satellite images, few positive samples are available for the training. Moreover, an image pair of scenes contains many trivial events, such as in illumination changes or background motions. These many trivial events and the class imbalance problem lead to false alarms for rare event detection. In order to overcome these difficulties, we propose a novel method to learn disentangled representations from only low-cost negative samples. The proposed method disentangles the different aspects in a pair of observations: variant and invariant factors that represent trivial events and image contents, respectively. The effectiveness of the proposed approach is verified by the quantitative evaluations on four change detection datasets, and the qualitative analysis shows that the proposed method can acquire the representations that disentangle rare events from trivial ones.

OBJECTIVES/HYPOTHESIS To regenerate defected recurrent laryngeal nerves (RLNs), various methods have been developed. However, no consistently effective treatments are currently available because of their insufficient functional recovery. RADA16-I, a self-assembling peptide used clinically as a hemostat, reportedly supports neurite outgrowth and functional synapse formation in vitro. The purpose of this study was to investigate the effect of RADA16-I hydrogels on transected RLNs in rats. STUDY DESIGN Animal experiments with controls. METHODS Fifteen adult rats were divided into the following three groups: RADA16-I (+), RADA16-I (-), and neurectomy. A 6-mm gap of the left RLN was bridged using an 8-mm silicone tube in the RADA16-I (-) and RADA16-I (+) groups. Subsequently, RADA16-I hydrogel was injected into the tube in the RADA16-I (+) group. The surgical incisions were closed without any further treatment in the neurectomy group. After 8 weeks, laryngoscopy and electrophysiological and histological examinations were performed to evaluate the effect of RADA16-I on nerve regeneration and thyroarytenoid muscle atrophy. RESULTS Although most rats in the three groups exhibited no improvements of their vocal fold movement, partial recovery was observed in one rat in the RADA16-I (+) group. The neurofilament-positive areas and the number of myelinated nerves in the RADA16-I (+) group were significantly higher than in the RADA16-I (-) group. The area of the left thyroarytenoid muscle in the RADA16-I (+) group was significantly larger than that of the neurectomy group. CONCLUSIONS Our results suggested that RADA16-I hydrogel was effective for RLN regeneration. LEVEL OF EVIDENCE NA Laryngoscope, 130:2420-2427, 2020.

Femtosecond time-resolved mid-infrared (MIR) spectroscopy based on chirped-pulse upconversion is a promising method for observing molecular structure and vibrational dynamics. By using a polarized narrowband pump pulse in which center frequency is rapidly scanned with an electrically tunable Fabry-Perot filter, we have developed a femtosecond MIR spectrometer that is more sensitive to molecular structure. The pump energy and polarization dependences of transient MIR absorption spectra measured with the spectroscopic system revealed the appearance of a dark (infrared-inactive) mode due to a slight decrease in the molecular symmetry of a metal carbonyl complex, Mn2(CO)10, in solution. In addition, the rotational relaxation time of Mn2(CO)10 in solution was determined as approximately 20 ps.

This paper proposes a novel method of estimating the absolute scale of monocular SfM for a multi-modal stereo camera. In the fields of computer vision and robotics, scale estimation for monocular SfM has been widely investigated in order to simplify systems. This paper addresses the scale estimation problem for a stereo camera system in which two cameras capture different spectral images (e.g., RGB and FIR), whose feature points are difficult to directly match using descriptors. Furthermore, the number of matching points between FIR images can be comparatively small, owing to the low resolution and lack of thermal scene texture. To cope with these difficulties, the proposed method estimates the scale parameter using batch optimization, based on the epipolar constraint of a small number of feature correspondences between the invisible light images. The accuracy and numerical stability of the proposed method are verified by synthetic and real image experiments.

Tight fixation of the artificial trachea is important for epithelialization and tracheal stenosis.The authors have developed an artificial trachea and have used it for tracheal reconstruction. Although various studies on tracheal reconstruction have been conducted, no studies have examined the effect of artificial tracheal fixation on tracheal stenosis and regeneration. Therefore, the purpose of the present study was to evaluate the effect of artificial tracheal fixation.Preliminary animal experiment.Artificial tracheae were implanted into rabbits with partial tracheal defects. Tracheal stenosis and regeneration of the tracheal epithelium on the artificial tracheae were evaluated by endoscopic examination, scanning electron microscopic analysis, and histological examination. The artificial tracheae fixed to the tracheal defects were classified into three groups (0-point, 4-point, and 8-point) by the number of fixation points.At 14 and 28 days post-implantation, the luminal surface of the implantation area was mostly covered with epithelium in all fixation groups. However, a small amount of granulation tissue was observed in the 0-point fixation group at 14 days post-implantation. Moreover, tracheal stenosis did not occur in the 8-point fixation group, but stenosis was detected in the other groups.

Accepted: 2016-02-11, 資料番号: SA1160029000