All Data

本稿は、低学年「生活」教科書をもとに、台湾における環境教育カリキュラムの構造を明らかにしようとしたものである。環境問題は、一国にとざされたものではなく、地球的課題としてどのように向き合うのかという「グローバル教育」の地平線にたって実践的可能性を模索しなければならない。しかしながら、小学校低学年の場合、冒頭からグローバルな空間認識のもとで実践を展開させていくことは難しい。ここで有効となり得るのが国際的な比較研究であり、台湾は日本と同じく低学年に「生活」があることから、「生活」教科書にあるプラスチックごみの削減を題材とした単元を取りあげ分析することで、比較カリキュラム論として国際的な参照軸から実践的可能性の展望を見出すことができる。

This study investigated the potential of adalimumab (ADA), a monoclonal antibody targeting TNF-alfa, to protect the inner ear from intense sound exposure, given that inflammatory cytokines, including TNF-alfa, are linked to hearing loss in acoustic disorders. In this study, adalimumab was administered to mice, and its effect on the inner ear was assessed. We examined the translocation of ADA to the inner ear and its ototoxicity and impact on acoustic exposure. The results showed that adalimumab partially reached the cochlea after administration but increased the susceptibility to acoustic exposure, resulting in higher hair cell loss in the inner ear. While TNF-alfa had been considered a potential therapeutic target, the results suggested that excessive TNF-alfa suppression could harm the inner ear. We acknowledged some limitations, such as the use of adalimumab instead of an anti-mouse TNF-alfa antibody and the need to explore the suppression of other cytokines for better inner ear protection. In conclusion, adalimumab administration was found to increase the inner earʼs susceptibility to acoustic exposure, potentially leading to more significant hair cell damage, possibly due to excessive TNF-alfa suppression

Vestibular hair cells are susceptible to damage from various stimuli such as infections, ischemia, and certain therapeutic drugs, including aminoglycoside antibiotics and the antineoplastic agent cisplatin. In mammals, damage to the vestibular hair cells is permanent. This study aimed to evaluate the protective effects of nobiletin (NOB) against aminoglycoside-induced hair cell death using utricles collected from adult mice. The utricles removed from CBA/N mice were assigned to eight groups according to the dose of NOB and the administration or not of neomycin. Hair cells in the utricles were counted by double labeling with calmodulin and calbindin. NOB inhibited hair cell death in utricles exposed to neomycin. The protective effect of NOB on hair cells in the utricles was also suggested to have resulted from the inhibition of the production and accumulation of 4-hydroxy-2-nonenal, the final product of lipid peroxide aldehyde. NOB suppressed neomycin-induced hair cell death. The principle of hair cell protection from aminoglycoside-induced hair cell death suggests that NOB inhibits reactive oxygen species formation in the utricles exposed to neomycin.

Objective: The objective was to explore the potential existence and nature of the relationship between serum of uric acid (SUA) and serum uric acid to serum creatinine ratio (SUA/SCr) with reduced estimated glomerular filtration rate (eGFR) in patients with non-alcoholic fatty liver disease (NAFLD). Methods: A cross-sectional study was conducted among apparently healthy subjects with NAFLD (n=485). The association between tertiles of SUA and SUA/SCr with reduced eGFR (n=56) were investigated after adjustments for potentially relevant confounders. Also, the diagnostic performances of SUA and SUA/SCr were evaluated with the receiver operating characteristic (ROC) curve analysis. Results: In the adjusted models, SUA showed a significant positive association with reduced eGFR in the highest tertile (OR 5.65, 95% CI 2.48-12.86, p<0.001), and SUA/SCr, in the lowest tertile (4.21, 95% CI 1.76-10.07, p=0.001). The ROC curve analysis did not reveal any significant difference between the corresponding values of area under the curve for SUA and SUA/SCr (0.70 and 0.67, respectively; p=0.521). Conclusions: We revealed significant and independent associations of elevated SUA and reduced SUA/SCr with kidney function decline in NAFLD. However, the clinical utility of these two biomarkers seemed to be limited for the mentioned purpose and needs further investigations.

Benign paroxysmal positional vertigo (BPPV) is the most common vertigo disease and is more likely to occur in perimenopausal women, suggesting an association with osteoporosis. Since otoconia are primarily composed of calcium carbonate, abnormal calcium metabolism may lead to otoconia dislocation. However, the detailed mechanism is currently unknown. In this study, we investigated the effects of drugs (cadmium and dexamethasone) that cause abnormal calcium metabolism on otolith formation in zebrafish larvae. Here, otolith size was clearly reduced in the cadmium group, and the calcium content of the larvae was also markedly reduced. In contrast, in the dexamethasone group, which also had a lower calcium content than the control group, otolith size increased. Our results suggest that, as in bone, calcium metabolism influences the repeated dissolution and recrystallization of otoliths and maintains homeostasis in response to calcium concentrations in the endolymphatic fluid.

In Japan, China, and Singapore, several studies have reported increased incidences of peripheral venous catheter-related bloodstream infection by Bacillus cereus during the summer. Therefore, we hypothesized that bed bathing with a B. cereus-contaminated “clean” towels increases B. cereus contact with the catheter and increases the odds of contaminating the peripheral parenteral nutrition (PPN). We found that 1) professionally laundered “clean” towels used in hospitals have B. cereus (3.3×10^4 colony forming units (CFUs) / 25cm^2), 2) B. cereus is transferable onto the forearms of volunteers by wiping with the towels (n=9), and 3) B. cereus remain detectable (80∼660 CFUs /50cm^2) on the forearms of volunteers even with subsequent efforts of disinfection using alcohol wipes. We further confirmed that B. cereus grow robustly (10^2 CFUs /mL to more than 10^6 CFUs /mL) within 24hours at 30°C in PPN. Altogether we find that bed bathing with a towel contaminated with B. cereus leads to spore attachments to the skin, and that B. cereus can proliferate at an accelerated rate at 30°C compared to 20°C in PPN. We therefore highly recommend ensuring the use of sterile bed bath towels prior to PPN administration with catheter in patients requiring bed bathing.

The COVID-19 pandemic has significantly transformed higher education, shifting it from traditional classrooms to online platforms. This change requires reassessment and adaptation of educational methods, particularly student assessment. Online formative assessments have become essential for improving teaching and learning outcomes because they provide immediate feedback, enable interactive support, and encourage selfassessment, thereby playing a key role in the learning process. The multiple-choice test is widely used to assess students. However, the inherent nature of multiple-choice questions poses the risk of obtaining correct answers, even without a genuine understanding of the content. To mitigate this issue, typical measures involve increasing the number of questions. To address this concern, this study implemented a new constraint aimed at enhancing the inherent characteristics of the multiple-choice format. This research objective focuses on investigating innovative scoring methods for formative assessments in online courses that can improve learning in higher education within the context of Yamaguchi University. This study evaluated the effectiveness of this learning assessment method by employing multiple-choice questions, presenting a practical and efficient approach for online formative learning assessment designed to assess a large student cohort. The new scoring method in this study extends Ikebururo's concepts that introduce partial scoring systems in MCQ design, driving the creation of a new scoring system centered on the "degree of matching.” This approach involved comparing the alignment between student responses and the instructor's design, resulting in a detailed five-level scoring system for four-choice questions. This scoring method hinges on evaluating how closely students’ answers align with the instructor's intended choices. Each question, with its four choices, is akin to a binary process, represented by a 4-digit binary number. Each digit in this comparison corresponds to a specific choice, allowing for a granular assessment of the match between student selection and the ideal answer. This innovative approach steps away from the conventional pass-fail binary system, offering a spectrum of evaluation outcomes. It provides a better understanding of students’ comprehension by gauging the extent of the alignment between their choices and the instructor's design. This method can enhance assessment accuracy by capturing the subtleties of student responses beyond mere correctness, earning partial points for partial knowledge or progress via multistep reasoning, promoting critical thinking, recognizing the importance of incremental progress, and capturing the depth of a respondent's knowledge. Initially, an extensive literature review established a theoretical framework, identifying gaps in the current understanding of online formative assessments. Subsequently, the study examined data collected from graduate students in the 'Advanced Research and Development Strategies' course at Yamaguchi University. The data span two academic years, 2019 and 2020, and provide a comparative view of face-to-face and online Lecturer Formats. Furthermore, the k-means clustering algorithm was used to analyze student performance using formative assessment scores. This method categorizes student performance into distinct clusters, revealing insights into individual learning behaviors. The k-means method, a popular technique in data mining and pattern recognition, efficiently groups data into 'k' clusters. It is effective for large datasets and versatile across various data types. The technique involves steps such as initialization, assignment, centroid updating, and convergence checking, and is instrumental in identifying performance patterns, enabling the development of more focused educational strategies. The results demonstrate the potential of the four-choice multiple-choice scoring method to revitalize online formative assessments. The key contributions of this study are as follows: ・Innovative Scoring Method: This study shows how the four-choice method can lead to more dynamic and engaging online assessments. This approach captures student performance more accurately and encourages deeper engagement with the material. ・Enhanced Student Engagement and Understanding: The new four-multiple-choice scoring method significantly affected student engagement and understanding. This fosters an environment in which students are more actively involved in their learning processes, contributing to better comprehension and retention of material. ・Practical Implications for Educators and Institutions: The need to adapt assessment strategies for digital learning, focusing on continuous feedback and personalized learning. ・Educational Technology Contribution: Key insights into adapting assessment strategies for digital learning, emphasizing continuous feedback, and personalized learning. This dissertation presents a comprehensive examination of new assessment techniques in the context of online learning. This provides a critical roadmap for educators and institutions to adapt to the digital educational environment for more effective and engaging assessment practices in online higher education.

As the population ages, the demand for elderly care services will continue to increase, which includes providing specialized care, daily life support, and medical health services. As a result, informal caregiving provided by non-professionals such as family, friends, neighbors, and volunteers is becoming more prevalent. Injuries that occur during caregiving can affect the caregiving’s life, especially their mental and physical health. Therefore, the correct positioning and posture during caregiving are crucial to prevent musculoskeletal disorders among caregivers. Although training programs are useful to reduce the risk of musculoskeletal disorders for informal caregivers, many of them express that it is still difficult for them to grasp the correct caregiving postures. Moreover, they struggle to obtain professional advice to correct their posture through long-term practice. Therefore, finding a targeted ergonomic posture risk assessment and guidance method is crucial to improve caregivers' posture-related risks, enhance work efficiency, and safeguard their physical health. Rapid Entire Body Assessment (REBA) is a postural risk assessment method based on ergonomics that has been attracting attention recently, and it basically evaluates the risk from the angle of each joint of the body. However, in caregiving movements, the way of load placed on the caregiver and the time to maintain the movements vary greatly depending on the weight and posture of the cared person, so the current risk assessment using REBA is insufficient for caregiving movements. Additionally, posture recognition algorithms such as OpenPose are often used to extract skeletons. With these techniques, problems such as missing skeletons or misrecognition often occur due to image conditions or the overlapping of multiple people, and skeleton extraction may sometimes fail. In this research, the Spatial Temporal Graph Convolution Network (ST-GCN) is applied to develop a technique for complementing missing skeletons based on behavioral features and a technique for correcting skeletons that are misrecognized due to overlapping people, and to improve the accuracy of calculating skeletal joint angles. In order to evaluate caregiving posture risk more appropriately, some parameters such as center of gravity trajectory, load duration, asymmetric load during caregiving movements are investigated and a new REBA method is proposed. This paper consists of six chapters. In Chapter 2, to solve the problems of skeleton misidentification and missing information by OpenPose an improved skeleton reconstruction method based on ST-GCN is propose. The method compensates for missing skeletons in terms of behavioral features and corrects incorrectly identified skeletons based on skeleton weight features. This approach improves the accuracy and robustness of pose recognition and allows more accurate estimation of skeletal joint angles and its REBA score. In Chapter 3, to address the issue of REBA evaluation scores being too high for caregiving scenarios, a postural risk assessment method (C-REBA) is proposed by considering the characteristics of caregiving task. Customize the traditional REBA method and add parameters such as center of gravity trajectory, load duration, and asymmetric loading to the evaluation score. the caregiving movements to assist in transferring from a bed to a wheelchair on a group of experienced nurses and a group of inexperienced caregivers are analyzed and the effectiveness of the C-REBA method is verified. In Chapter 4, a method that combines the ST-GCN framework and C-REBA for postural risk assessment is proposed. The deep neural network algorism is applied to learn motion features and additional features such as load duration, motion frequency, center of gravity variation, and asymmetric load. So that all evaluation parameters for C-REBA rules can be obtained automatically. With this method, postural risk assessment processes in caregiving operations can be performed automatically. In Chapter 5, "Behavior Analysis and Posture Assessment System" (BAPAS) is developed. BAPAS is a system aimed at assessing the risk of musculoskeletal disorders related to working postures in medical support work. This chapter introduces the functions and usefulness of this system and demonstrates how this system can be extended to other medical fields easily by setting parameter is settings. Chapter 6 provides a summary of the paper as a whole and future prospect.

In recent years, not only mRNA (messenger RNA) but also other small non-coding RNA have focused on molecular diagnosis and therapy in oncology fields. Especially in human medicine, many studies elucidate the ability and function of many microRNAs, which are small non-coding RNAs. However, there are still not many studies in the veterinary field. In my PhD study, I focused on the non-coding small RNA in canine oncology fields. In the first chapter, I studied the dysregulated micro RNA in canine oral melanoma. At first, I performed the microarray-based miRNA profiling of canine malignant melanoma (CMM) tissue obtained from the oral cavity. Then, I also confirmed the differentially expressed microRNA by quantitative reverse transcription-PCR (qRT-PCR). An analysis of the microarray data revealed 17 dysregulated miRNAs; 5 were up-regulated, and 12 were downregulated. qRT-PCR analysis was performed for 2 up-regulated (miR-204 and miR-383), 3 down-regulated (miR-122, miR-143, and miR-205) and 6 additional oncogenic miRNAs (oncomiRs; miR-16, miR-21, miR-29b, miR-92a, miR-125b and miR-222). The expression levels of seven of the miRNAs, miR16, miR-21, miR-29b, miR-122, miR-125b, miR-204, and miR-383 were significantly up-regulated, while the expression of miR-205 was down- 2 regulated in CMM tissues compared with normal oral tissues. The microarray and qRT-PCR analyses validated the up-regulation of two potential oncomiRs, miR-204 and miR-383. I also constructed a protein interaction network and a miRNA–target regulatory interaction network using STRING and Cytoscape. In the proposed network, was a target for miR-383, and were targets for miR-204, and was a target for both. The miR-383 and miR-204 were potential oncomiRs that may be involved in regulating melanoma development by evading DNA repair and apoptosis. In my second chapter, I focused on non-coding RNA other than microRNA, and I compared canine hepatocellular carcinomas (HCC) and hepatocellular adenomas (HCA). I elucidated the differential expression of Y RNA-derived fragments because Y RNA-derived fragments have yet to be investigated in canine HCC and HCA. I used qRT-PCR to determine Y RNA expression in clinical tissues, plasma, and plasma extracellular vesicles, and two HCC cell lines (95-1044 and AZACH). Y RNA was significantly decreased in tissue, plasma, and plasma extracellular vesicles for canine HCC versus canine HCA and healthy controls. Y RNA was decreased in 95-1044 and AZACH cells versus normal liver tissue and 3 in AZACH versus 95-1044 cells. In plasma samples, Y RNA levels were decreased in HCC versus HCA and Healthy controls and increased in HCA versus Healthy controls. Receiver operating characteristic analysis showed that Y RNA could be a promising biomarker for distinguishing HCC from HCA and healthy controls. Overall, the dysregulated expression of Y RNA can distinguish canine HCC from HCA. However, further research is necessary to elucidate the underlying Y RNA-related molecular mechanisms in hepatocellular neoplastic diseases. To the best of my knowledge, this is the first report on the relative expression of Y RNA in canine HCC and HCA. In conclusion, I have demonstrated the up-regulation of potential oncomiRs, miR-16, miR-21, miR-29b, miR-122, miR-125b, miR-204 and miR383 in CMM tissues. In particular, the strong up-regulation of miR-383 in CMM tissues compared with normal oral tissues identified by microarray screening was confirmed by qRT-PCR. I conclude that miR-383 and miR-204 may promote melanoma development by regulating the DNA repair/checkpoint and apoptosis. Then, I also demonstrated the Y RNA dysregulation in the cHCC. Especially to my knowledge, this is the first report on Y RNA in canine tumors. Interestingly, this ncRNA has distinctive characteristics and differentiates malignant tumors (HCC) from benign 4 tumors (HCA). The expression pattern of Y RNA is consistent across clinical samples and cell lines. Thus, Y RNA has promising potential for differentiating HCC from HCA. Further research is required to fully elucidate the role of Y RNA in the development and progression of canine HCC and HCA.

In China, there are about 800,000 congenital diseases among 20 million newborns, of which nearly 200,000 fetuses have serious defects or diseases. The birth of these sick fetuses brings serious economic burden and social problems to the family and even the society. It is therefore important to carry out early fetal monitoring in order to detect fetal defects and diseases as early as possible. Umbilical artery blood signals contain important information about fetal growth and development, reflecting various problems during pregnancy, such as intrauterine g rowth r etardationetardation（IUGR）, hypoxia and maternal hypertension, which can be determined by umbilical artery blood signals. Therefore, the analysis of umbilical artery blood signals is important for prenatal monitoring and fetal health status diagnosis. The acoustics pectral parameter method is a conventional technique for analyzing the umbilical artery blood signals and consists of three parameters that serve as clinical diagnostic criteria: resistance index (RI), pulsesatility index (PI) and maximum systolic/end diastolic umbilical flow velocity (S/D). However, these parameters ignore phase properties of the signal, such as phase delay, phase frequency and phase mode, and focus only on the fundamental statistical parameters of blood velocity, s uch as maximum, minimum and mean values. This may lead to clinical misdiagnosis. Umbilical artery blood signals have complicated structures and nonlinear characteristics in addition to changes in signal amplitude. This paper presents a comprehensive new approach for characteristics parameter extraction and classification of umbilical artery blood signals using fractal theory and Chaos theory in order to handle these complex structures and nonlinear properties of the signal. First, by focusing on the fract al characteristics of umbilical artery blood signals, the fractal dimension (BD) and the correlation dimension (CD) are obtained to verified that BD is positively correlated with the gestational week and CD is effective in discriminating normal from abnormal. Next, we obtain the maximum Lyapunov exponent (MLE) of the chaotic characteristics of umbilical artery blood time series, and verified its effectiveness in distinguishing normal signals from abnormal signals. Finally, a diagnostic model is proposed b y applying particle swarm optimization support vector machine (PSO SVM) to the conventional feature parameters (RI, PI, S/D) and newly obtained parameters (BD, CD, MLE) to classify and diagnose the umbilical blood signals in the four statuses (normal, oligohydramnios, umbilical cord around neck, fetal malposition). This doctoral dissertation consists of 6 chapters. Chapter 1 introduces the background and means of umbilical artery blood study as well as reviewing the current re search situation. The outline o f this dissertation is also given. In chapter 2, the fundamentals of fetal hemodynamics are described. The clinical significance and normal reference values of umbilical artery blood signal parameters are outlined. Details of the umbilical artery signal acquisition equipment, data classification and acquisition process are explained. In chapter 3，the fractal dimension box counting method (BD) and the correlation dimension (CD) are used to investigate the nonlinear characteristics of the umbilical artery blood signals based on fractal theory. First, the BD of the umbilical artery blood signals is calculated and the fractal characteristics of the signals are analyzed. Results show a positive relationship between the fractal dimension of umbilical artery blood signals and gestational weeks. A bnormal and normal umbilical artery signals are then classified into abnormal group and n ormal group. T h e Grassberg P rocaccia algorithm (GP algorithm) is used to calculate and analyze the CD of the two groups. T he overall CD of normal umbilical artery blood signals is greater than that of abnormal signal s. CD is significantly better at discriminating the normality of the umbilical artery blood signal compared to conventional parameters. Furthermore, t he Hurst exponent of umbilical artery blood signal is calculated and analyzed by Lo method. The results show that umbilical artery blood signal belong s to non sta tionary signal and show obvious “1/f fluctuation” characteristics. In chapter 4，c haotic phase space diagram method and m aximum L yapunov e xponent (MLE) are used to determine the chaotic characteristics of umbilical artery blood signals from qualitative and quantitative perspectives. The attractor reconstruction of umbilica l artery blood signals is performed in t hree d imension (3D) and t wo d imension (2D) phase space. The results show that the chaotic phase diagram of the time series for abnormal umbilical artery signals show a jumbled “ball of wool” state and the chaotic “shape” appears to converge. Application of the r eceiver o perating c haracteristic (ROC) curve to the obtained maximum Lyapunov exponent (MLE) shows that the rate of discrimination of normality of the umbilical artery blood signal is significantly better than the conventional feature parameters. In chapter 5，an artificial intelligent classifier is proposed to classify the four states of umbilical artery blood signals (normal, oligohydramnios, umbilical cord around neck and fetal malposition). The support vector machine (SVM) classifying method is constructed based on the conventional parameters, S/D, PI and RI. The particle swarm optimisation support vector machine (PSO SVM) classifier is also constructed using the fractal dimension (BD), correlation dimension ( CD) and maximum L yapunov exponent (MLE) derived in Chapters 3 and 4 as feature parameters. The results of the classification tests show that the PSO SVM classifier is more accurate , confirming the usefulness and effectiveness of the proposed classification method. In Chapter 6, summary of this dissertation and future work are described.