20 research outputs found
Post-Mortem Identity and Burial Obligation : On Blood Relations, Place Relations, and Associational Relations in the Japanese Community of Singapore
For Science, Co-Prosperity, and Love : The Re-imagination of Taiwanese Folklore and Japan's Greater East Asian War
Nature, Development and Disaster in Postwar Kobe: An Exploration of the Environmental Thinking of Japanese Local Politicians
見い出す(Seeing)、関連させる(Relating)、織り込む(Integrating) : 日本の中国人移民と諸外国人コミュニティの史的研究 (<特集>国際ワークショップ「日本在住外国人コミュニティーの歴史の発見 : 研究・アーカイブス・特別コレクション」)
Biosensing Amplification by Hybridization Chain Reaction on Phase-Sensitive Surface Plasmon Resonance
Surface Plasmon Resonance (SPR) is widely used in biological and chemical sensing with fascinating properties. However, the application of SPR to detect trace targets is hampered by non-specific binding and poor signal. A variety of approaches for amplification have been explored to overcome this deficiency including DNA aptamers as versatile target detection tools. Hybridization chain reaction (HCR) is a high-efficiency enzyme-free DNA amplification method operated at room temperature, in which two stable species of DNA hairpins coexist in solution until the introduction of the initiator strand triggers a cascade of hybridization events. At an optimal salt condition, as the concentrations of H1 and H2 increased, the HCR signals were enhanced, leading to signal amplification reaching up to 6.5-fold of the detection measure at 30 min. This feature enables DNA to act as an amplifying transducer for biosensing applications to provide an enzyme-free alternative that can easily detect complex DNA sequences. Improvement of more diverse recognition events can be achieved by integrating HCR with a phase-sensitive SPR (pSPR)-tested aptamer stimulus. This work seeks to establish pSPR aptamer system for highly informative sensing by means of an amplification HCR. Thus, combining pSPR and HCR technologies provide an expandable platform for sensitive biosensing
Biosensing Amplification by Hybridization Chain Reaction on Phase-Sensitive Surface Plasmon Resonance
Surface Plasmon Resonance (SPR) is widely used in biological and chemical sensing with fascinating properties. However, the application of SPR to detect trace targets is hampered by non-specific binding and poor signal. A variety of approaches for amplification have been explored to overcome this deficiency including DNA aptamers as versatile target detection tools. Hybridization chain reaction (HCR) is a high-efficiency enzyme-free DNA amplification method operated at room temperature, in which two stable species of DNA hairpins coexist in solution until the introduction of the initiator strand triggers a cascade of hybridization events. At an optimal salt condition, as the concentrations of H1 and H2 increased, the HCR signals were enhanced, leading to signal amplification reaching up to 6.5-fold of the detection measure at 30 min. This feature enables DNA to act as an amplifying transducer for biosensing applications to provide an enzyme-free alternative that can easily detect complex DNA sequences. Improvement of more diverse recognition events can be achieved by integrating HCR with a phase-sensitive SPR (pSPR)-tested aptamer stimulus. This work seeks to establish pSPR aptamer system for highly informative sensing by means of an amplification HCR. Thus, combining pSPR and HCR technologies provide an expandable platform for sensitive biosensing
Comparison of the Results of Cardiopulmonary Exercise Testing between Healthy Peers and Pediatric Patients with Different Echocardiographic Severity of Mitral Valve Prolapse
Patients with mitral valve prolapse (MVP) have been reported to have exercise intolerance. However, the underlying pathophysiological mechanisms and their physical fitness remain unclear. We aimed to determine the exercise capacity of patients with MVP through the cardiopulmonary exercise test (CPET). We retrospectively collected the data of 45 patients with a diagnosis of MVP. Their CPET and echocardiogram results were compared with 76 healthy individuals as primary outcomes. No significant differences regarding the patient’s baseline characteristics and echocardiographic data were found between the two groups, except for the lower body mass index (BMI) of the MVP group. Patients in the MVP group demonstrated a similar peak metabolic equivalent (MET), but a significantly lower peak rate pressure product (PRPP) (p = 0.048). Patients with MVP possessed similar exercise capacity to healthy individuals. The reduced PRPP may indicate compromised coronary perfusion and subtle left ventricular function impairment
Comparison of the Results of Cardiopulmonary Exercise Testing between Healthy Peers and Pediatric Patients with Different Echocardiographic Severity of Mitral Valve Prolapse
Patients with mitral valve prolapse (MVP) have been reported to have exercise intolerance. However, the underlying pathophysiological mechanisms and their physical fitness remain unclear. We aimed to determine the exercise capacity of patients with MVP through the cardiopulmonary exercise test (CPET). We retrospectively collected the data of 45 patients with a diagnosis of MVP. Their CPET and echocardiogram results were compared with 76 healthy individuals as primary outcomes. No significant differences regarding the patient’s baseline characteristics and echocardiographic data were found between the two groups, except for the lower body mass index (BMI) of the MVP group. Patients in the MVP group demonstrated a similar peak metabolic equivalent (MET), but a significantly lower peak rate pressure product (PRPP) (p = 0.048). Patients with MVP possessed similar exercise capacity to healthy individuals. The reduced PRPP may indicate compromised coronary perfusion and subtle left ventricular function impairment
Artificial Intelligence Assisted Computational Tomographic Detection of Lung Nodules for Prognostic Cancer Examination: A Large-Scale Clinical Trial
Low-dose computed tomography (LDCT) has emerged as a standard method for detecting early-stage lung cancer. However, the tedious computer tomography (CT) slide reading, patient-by-patient check, and lack of standard criteria to determine the vague but possible nodule leads to variable outcomes of CT slide interpretation. To determine the artificial intelligence (AI)-assisted CT examination, AI algorithm-assisted CT screening was embedded in the hospital picture archiving and communication system, and a 200 person-scaled clinical trial was conducted at two medical centers. With AI algorithm-assisted CT screening, the sensitivity of detecting nodules sized 4–5 mm, 6~10 mm, 11~20 mm, and >20 mm increased by 41%, 11.2%, 10.3%, and 18.7%, respectively. Remarkably, the overall sensitivity of detecting varied nodules increased by 20.7% from 67.7% to 88.4%. Furthermore, the sensitivity increased by 18.5% from 72.5% to 91% for detecting ground glass nodules (GGN), which is challenging for radiologists and physicians. The free-response operating characteristic (FROC) AI score was ≥0.4, and the AI algorithm standalone CT screening sensitivity reached >95% with an area under the localization receiver operating characteristic curve (LROC-AUC) of >0.88. Our study demonstrates that AI algorithm-embedded CT screening significantly ameliorates tedious LDCT practices for doctors