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Ma J, Li H, Anwer S, Umer W, Antwi-Afari MF, Xiao EB. Evaluation of sweat-based biomarkers using wearable biosensors for monitoring stress and fatigue: a systematic review. INTERNATIONAL JOURNAL OF OCCUPATIONAL SAFETY AND ERGONOMICS 2024:1-27. [PMID: 38581242 DOI: 10.1080/10803548.2024.2330242] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/08/2024]
Abstract
Objectives. This systematic review aims to report the evaluation of wearable biosensors for the real-time measurement of stress and fatigue using sweat biomarkers. Methods. A thorough search of the literature was carried out in databases such as PubMed, Web of Science and IEEE. A three-step approach for selecting research articles was developed and implemented. Results. Based on a systematic search, a total of 17 articles were included in this review. Lactate, cortisol, glucose and electrolytes were identified as sweat biomarkers. Sweat-based biomarkers are frequently monitored in real time using potentiometric and amperometric biosensors. Wearable biosensors such as an epidermal patch or a sweatband have been widely validated in scientific literature. Conclusions. Sweat is an important biofluid for monitoring general health, including stress and fatigue. It is becoming increasingly common to use biosensors that can measure a wide range of sweat biomarkers to detect fatigue during high-intensity work. Even though wearable biosensors have been validated for monitoring various sweat biomarkers, such biomarkers can only be used to assess stress and fatigue indirectly. In general, this study may serve as a driving force for academics and practitioners to broaden the use of wearable biosensors for the real-time assessment of stress and fatigue.
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Affiliation(s)
- Jie Ma
- Department of Building and Real Estate, Hong Kong Polytechnic University, People's Republic of China
| | - Heng Li
- Department of Building and Real Estate, Hong Kong Polytechnic University, People's Republic of China
| | - Shahnawaz Anwer
- Department of Building and Real Estate, Hong Kong Polytechnic University, People's Republic of China
| | - Waleed Umer
- Department of Mechanical and Construction Engineering, Northumbria University, UK
| | | | - Eric Bo Xiao
- Department of Building and Real Estate, Hong Kong Polytechnic University, People's Republic of China
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Ali N, Rahat ST, Mäkelä M, Nasserinejad M, Jaako T, Kinnunen M, Schroderus J, Tulppo M, Nieminen AI, Vainio S. Metabolic patterns of sweat-extracellular vesicles during exercise and recovery states using clinical grade patches. Front Physiol 2023; 14:1295852. [PMID: 38143912 PMCID: PMC10748597 DOI: 10.3389/fphys.2023.1295852] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2023] [Accepted: 11/28/2023] [Indexed: 12/26/2023] Open
Abstract
Background: Metabolite-based sensors are attractive and highly valued for monitoring physiological parameters during rest and/or during physical activities. Owing to their molecular composition consisting of nucleic acids, proteins, and metabolites, extracellular vesicles (EVs) have become acknowledged as a novel tool for disease diagnosis. However, the evidence for sweat related EVs delivering information of physical and recovery states remains to be addressed. Methods: Taking advantage of our recently published methodology allowing the enrichment and isolation of sweat EVs from clinical patches, we investigated the metabolic load of sweat EVs in healthy participants exposed to exercise test or recovery condition. -Ten healthy volunteers (-three females and -seven males) were recruited to participate in this study. During exercise test and recovery condition, clinical patches were attached to participants' skin, on their back. Following exercise test or recovery condition, the patches were carefully removed and proceed for sweat EVs isolation. To explore the metabolic composition of sweat EVs, a targeted global metabolomics profiling of 41 metabolites was performed. Results: Our results identified seventeen metabolites in sweat EVs. These are associated with amino acids, glutamate, glutathione, fatty acids, creatine, and glycolysis pathways. Furthermore, when comparing the metabolites' levels in sweat EVs isolated during exercise to the metabolite levels in sweat EVs collected after recovery, our findings revealed a distinct metabolic profiling of sweat EVs. Furthermore, the level of these metabolites, mainly myristate, may reflect an inverse correlation with blood glucose, heart rate, and respiratory rate levels. Conclusion: Our data demonstrated that sweat EVs can be purified using routinely used clinical patches during physical activity, setting the foundations for larger-scale clinical cohort work. Furthermore, the metabolites identified in sweat EVs also offer a realistic means to identify relevant sport performance biomarkers. This study thus provides proof-of-concept towards a novel methodology that will focus on the use of sweat EVs and their metabolic composition as a non-invasive approach for developing the next-generation of sport wearable sensors.
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Affiliation(s)
- Nsrein Ali
- Laboratory of Developmental Biology, Faculty of Biochemistry and Molecular Medicine, Oulu, Finland
- Infotech Oulu, Oulu, Finland
- Flagship GeneCellNano, University of Oulu, Oulu, Finland
- Netskinmodels Cost Action CA21108, Oulu, Finland
| | - Syeda Tayyiba Rahat
- Laboratory of Developmental Biology, Faculty of Biochemistry and Molecular Medicine, Oulu, Finland
| | - Mira Mäkelä
- Laboratory of Developmental Biology, Faculty of Biochemistry and Molecular Medicine, Oulu, Finland
| | - Maryam Nasserinejad
- Infotech Oulu, Oulu, Finland
- Research Unit of Population Health Research, Research Center, Faculty of Medicine, University of Oulu, Oulu, Finland
| | | | | | | | - Mikko Tulppo
- Edical Research Center Oulu, Faculty of Medicine, University of Oulu, Oulu, Finland
- Resaerch Unit of Biomedicine and Internal Medicine, Faculty of Medicine, University of Oulu, Oulu, Finland
| | - Anni I. Nieminen
- FIMM Metabolomics Unit, Institute for Molecular Medicine Finland, University of Helsinki, Oulu, Finland
| | - Seppo Vainio
- Laboratory of Developmental Biology, Faculty of Biochemistry and Molecular Medicine, Oulu, Finland
- Infotech Oulu, Oulu, Finland
- Flagship GeneCellNano, University of Oulu, Oulu, Finland
- Netskinmodels Cost Action CA21108, Oulu, Finland
- Kvantum Institute, University of Oulu, Oulu, Finland
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Muramoto Y, Nakashima D, Amano T, Harita T, Sugai K, Daigo K, Iwasawa Y, Ichihara G, Okawara H, Sawada T, Kinoda A, Yamada Y, Kimura T, Sato K, Katsumata Y. Estimation of maximal lactate steady state using the sweat lactate sensor. Sci Rep 2023; 13:10366. [PMID: 37365235 DOI: 10.1038/s41598-023-36983-8] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2023] [Accepted: 06/13/2023] [Indexed: 06/28/2023] Open
Abstract
A simple, non-invasive algorithm for maximal lactate steady state (MLSS) assessment has not been developed. We examined whether MLSS can be estimated from the sweat lactate threshold (sLT) using a novel sweat lactate sensor for healthy adults, with consideration of their exercise habits. Fifteen adults representing diverse fitness levels were recruited. Participants with/without exercise habits were defined as trained/untrained, respectively. Constant-load testing for 30 min at 110%, 115%, 120%, and 125% of sLT intensity was performed to determine MLSS. The tissue oxygenation index (TOI) of the thigh was also monitored. MLSS was not fully estimated from sLT, with 110%, 115%, 120%, and 125% of sLT in one, four, three, and seven participants, respectively. The MLSS based on sLT was higher in the trained group as compared to the untrained group. A total of 80% of trained participants had an MLSS of 120% or higher, while 75% of untrained participants had an MLSS of 115% or lower based on sLT. Furthermore, compared to untrained participants, trained participants continued constant-load exercise even if their TOI decreased below the resting baseline (P < 0.01). MLSS was successfully estimated using sLT, with 120% or more in trained participants and 115% or less in untrained participants. This suggests that trained individuals can continue exercising despite decreases in oxygen saturation in lower extremity skeletal muscles.
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Affiliation(s)
- Yuki Muramoto
- Institute for Integrated Sports Medicine, Keio University School of Medicine, Tokyo, Japan
| | - Daisuke Nakashima
- Department of Orthopaedic Surgery, Keio University School of Medicine, Tokyo, Japan
| | | | | | - Kazuhisa Sugai
- School of Veterinary Nursing and Technology, Faculty of Veterinary Science, Nippon Veterinary and Life Science University, Tokyo, Japan
| | - Kyohei Daigo
- Department of Cardiology, Keio University School of Medicine, Tokyo, Japan
| | - Yuji Iwasawa
- Department of Cardiology, Keio University School of Medicine, Tokyo, Japan
| | - Genki Ichihara
- Department of Cardiology, Keio University School of Medicine, Tokyo, Japan
| | - Hiroki Okawara
- Department of Orthopaedic Surgery, Keio University School of Medicine, Tokyo, Japan
| | - Tomonori Sawada
- Department of Orthopaedic Surgery, Keio University School of Medicine, Tokyo, Japan
| | - Akira Kinoda
- Institute for Integrated Sports Medicine, Keio University School of Medicine, Tokyo, Japan
| | - Yuichi Yamada
- Institute for Integrated Sports Medicine, Keio University School of Medicine, Tokyo, Japan
| | - Takeshi Kimura
- Institute for Integrated Sports Medicine, Keio University School of Medicine, Tokyo, Japan
| | - Kazuki Sato
- Institute for Integrated Sports Medicine, Keio University School of Medicine, Tokyo, Japan
| | - Yoshinori Katsumata
- Institute for Integrated Sports Medicine, Keio University School of Medicine, Tokyo, Japan.
- Department of Cardiology, Keio University School of Medicine, Tokyo, Japan.
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Rahat ST, Mäkelä M, Nasserinejad M, Ikäheimo TM, Hyrkäs-Palmu H, Valtonen RIP, Röning J, Sebert S, Nieminen AI, Ali N, Vainio S. Clinical-Grade Patches as a Medium for Enrichment of Sweat-Extracellular Vesicles and Facilitating Their Metabolic Analysis. Int J Mol Sci 2023; 24:ijms24087507. [PMID: 37108669 PMCID: PMC10139190 DOI: 10.3390/ijms24087507] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2023] [Revised: 04/03/2023] [Accepted: 04/11/2023] [Indexed: 04/29/2023] Open
Abstract
Cell-secreted extracellular vesicles (EVs), carrying components such as RNA, DNA, proteins, and metabolites, serve as candidates for developing non-invasive solutions for monitoring health and disease, owing to their capacity to cross various biological barriers and to become integrated into human sweat. However, the evidence for sweat-associated EVs providing clinically relevant information to use in disease diagnostics has not been reported. Developing cost-effective, easy, and reliable methodologies to investigate EVs' molecular load and composition in the sweat may help to validate their relevance in clinical diagnosis. We used clinical-grade dressing patches, with the aim being to accumulate, purify and characterize sweat EVs from healthy participants exposed to transient heat. The skin patch-based protocol described in this paper enables the enrichment of sweat EVs that express EV markers, such as CD63. A targeted metabolomics study of the sweat EVs identified 24 components. These are associated with amino acids, glutamate, glutathione, fatty acids, TCA, and glycolysis pathways. Furthermore, as a proof-of-concept, when comparing the metabolites' levels in sweat EVs isolated from healthy individuals with those of participants with Type 2 diabetes following heat exposure, our findings revealed that the metabolic patterns of sweat EVs may be linked with metabolic changes. Moreover, the concentration of these metabolites may reflect correlations with blood glucose and BMI. Together our data revealed that sweat EVs can be purified using routinely used clinical patches, setting the foundations for larger-scale clinical cohort work. Furthermore, the metabolites identified in sweat EVs also offer a realistic means to identify relevant disease biomarkers. This study thus provides a proof-of-concept towards a novel methodology that will focus on the use of the sweat EVs and their metabolites as a non-invasive approach, in order to monitor wellbeing and changes in diseases.
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Affiliation(s)
- Syeda Tayyiba Rahat
- Laboratory of Developmental Biology, Faculty of Biochemistry and Molecular Medicine, University of Oulu, 90220 Oulu, Finland
| | - Mira Mäkelä
- Laboratory of Developmental Biology, Faculty of Biochemistry and Molecular Medicine, University of Oulu, 90220 Oulu, Finland
| | - Maryam Nasserinejad
- Research Unit of Population Health Research, Faculty of Medicine, University of Oulu, 90570 Oulu, Finland
- Infotech Oulu, University of Oulu, 90014 Oulu, Finland
| | - Tiina M Ikäheimo
- Department of Community Medicine, University of Tromsø, N-9037 Tromsø, Norway
- Research Unit of Population Health, University of Oulu, 90220 Oulu, Finland
| | - Henna Hyrkäs-Palmu
- Research Unit of Population Health, University of Oulu, 90220 Oulu, Finland
| | - Rasmus I P Valtonen
- Research Unit of Biomedicine, Medical Research Center, Faculty of Medicine, University of Oulu, Oulu University Hospital, 90220 Oulu, Finland
| | - Juha Röning
- Infotech Oulu, University of Oulu, 90014 Oulu, Finland
- Biomimetics and Intelligent Systems Group, Faculty of Information Technology and Electrical Engineering, University of Oulu, 90570 Oulu, Finland
| | - Sylvain Sebert
- Research Unit of Population Health Research, Faculty of Medicine, University of Oulu, 90570 Oulu, Finland
- Infotech Oulu, University of Oulu, 90014 Oulu, Finland
| | - Anni I Nieminen
- FIMM Metabolomics Unit, Institute for Molecular Medicine Finland, University of Helsinki, 00014 Helsinki, Finland
| | - Nsrein Ali
- Laboratory of Developmental Biology, Faculty of Biochemistry and Molecular Medicine, University of Oulu, 90220 Oulu, Finland
- Infotech Oulu, University of Oulu, 90014 Oulu, Finland
- Flagship GeneCellNano, University of Oulu, 90220 Oulu, Finland
| | - Seppo Vainio
- Laboratory of Developmental Biology, Faculty of Biochemistry and Molecular Medicine, University of Oulu, 90220 Oulu, Finland
- Infotech Oulu, University of Oulu, 90014 Oulu, Finland
- Flagship GeneCellNano, University of Oulu, 90220 Oulu, Finland
- Kvantum Institute, University of Oulu, 90014 Oulu, Finland
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Maeda Y, Okawara H, Sawada T, Nakashima D, Nagahara J, Fujitsuka H, Ikeda K, Hoshino S, Kobari Y, Katsumata Y, Nakamura M, Nagura T. Implications of the Onset of Sweating on the Sweat Lactate Threshold. SENSORS (BASEL, SWITZERLAND) 2023; 23:3378. [PMID: 37050438 PMCID: PMC10098635 DOI: 10.3390/s23073378] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 02/08/2023] [Revised: 03/05/2023] [Accepted: 03/20/2023] [Indexed: 06/19/2023]
Abstract
The relationship between the onset of sweating (OS) and sweat lactate threshold (sLT) assessed using a novel sweat lactate sensor remains unclear. We aimed to investigate the implications of the OS on the sLT. Forty healthy men performed an incremental cycling test. We monitored the sweat lactate, blood lactate, and local sweating rates to determine the sLT, blood LT (bLT), and OS. We defined participants with the OS during the warm-up just before the incremental test as the early perspiration (EP) group and the others as the regular perspiration (RP) group. Pearson's correlation coefficient analysis revealed that the OS was poorly correlated with the sLT, particularly in the EP group (EP group, r = 0.12; RP group, r = 0.56). Conversely, even in the EP group, the sLT was strongly correlated with the bLT (r = 0.74); this was also the case in the RP group (r = 0.61). Bland-Altman plots showed no bias between the mean sLT and bLT (mean difference: 19.3 s). Finally, in five cases with a later OS than bLT, the sLT tended to deviate from the bLT (mean difference, 106.8 s). The sLT is a noninvasive and continuous alternative to the bLT, independent of an early OS, although a late OS may negatively affect the sLT.
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Affiliation(s)
- Yuta Maeda
- Department of Orthopaedic Surgery, Keio University School of Medicine, Shinjuku, Tokyo 160-8582, Japan
| | - Hiroki Okawara
- Department of Orthopaedic Surgery, Keio University School of Medicine, Shinjuku, Tokyo 160-8582, Japan
| | - Tomonori Sawada
- Department of Orthopaedic Surgery, Keio University School of Medicine, Shinjuku, Tokyo 160-8582, Japan
| | - Daisuke Nakashima
- Department of Orthopaedic Surgery, Keio University School of Medicine, Shinjuku, Tokyo 160-8582, Japan
| | - Joji Nagahara
- Department of Orthopaedic Surgery, Keio University School of Medicine, Shinjuku, Tokyo 160-8582, Japan
| | - Haruki Fujitsuka
- Department of Orthopaedic Surgery, Keio University School of Medicine, Shinjuku, Tokyo 160-8582, Japan
| | - Kaito Ikeda
- Department of Orthopaedic Surgery, Keio University School of Medicine, Shinjuku, Tokyo 160-8582, Japan
| | - Sosuke Hoshino
- Department of Orthopaedic Surgery, Keio University School of Medicine, Shinjuku, Tokyo 160-8582, Japan
| | - Yusuke Kobari
- Department of Cardiology, Keio University School of Medicine, Shinjuku, Tokyo 160-8582, Japan
| | - Yoshinori Katsumata
- Department of Cardiology, Keio University School of Medicine, Shinjuku, Tokyo 160-8582, Japan
- Institute for Integrated Sports Medicine, Keio University School of Medicine, Shinjuku, Tokyo 160-8582, Japan
| | - Masaya Nakamura
- Department of Orthopaedic Surgery, Keio University School of Medicine, Shinjuku, Tokyo 160-8582, Japan
| | - Takeo Nagura
- Department of Orthopaedic Surgery, Keio University School of Medicine, Shinjuku, Tokyo 160-8582, Japan
- Department of Clinical Biomechanics, Keio University School of Medicine, Shinjuku, Tokyo 160-8582, Japan
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Okawara H, Sawada T, Nakashima D, Maeda Y, Minoji S, Morisue T, Katsumata Y, Matsumoto M, Nakamura M, Nagura T. Realtime Monitoring of Local Sweat Rate Kinetics during Constant-Load Exercise Using Perspiration-Meter with Airflow Compensation System. SENSORS (BASEL, SWITZERLAND) 2022; 22:5473. [PMID: 35897977 PMCID: PMC9331097 DOI: 10.3390/s22155473] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 06/17/2022] [Revised: 07/06/2022] [Accepted: 07/20/2022] [Indexed: 06/15/2023]
Abstract
Epidermal wearable sweat biomarker sensing technologies are likely affected by sweat rate because of the dilution effect and limited measurement methods. However, there is a dearth of reports on the local sweat rate (LSR) monitored in real-time during exercise. This explorative study investigated the feasibility of real-time LSR monitoring and clarified LSR kinetics on the forehead and upper arm during constant-load exercise using a perspiration meter with an airflow compensation system. This observational cross-sectional study included 18 recreationally trained males (mean age, 20.6 ± 0.8 years). LSR on the forehead and upper arm (mg/cm2/min) were measured during a constant-load exercise test at 25% of their pre-evaluated peak power until exhaustion. The LSR kinetics had two inflection points, with a gradual decrease in the incremental slope for each section. After the second flexion point, the LSR slope slightly decreased and was maintained until exhaustion. However, the degree of change varied among the participants. Although the ratio of forehead LSR to upper arm LSR tended to decrease gradually over time, there was little change in this ratio after a second flexion point of LSR in both. These findings suggest possible differences in LSR control between the forehead and upper arm during constant-load exercise to prolonged exhaustion.
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Affiliation(s)
- Hiroki Okawara
- Department of Orthopaedic Surgery, Keio University School of Medicine, 35 Shinanomachi, Shinjuku-ku, Tokyo 160-8582, Japan; (H.O.); (Y.M.); (S.M.); (T.M.); (M.M.); (M.N.); (T.N.)
| | - Tomonori Sawada
- Institute for Integrated Sports Medicine, Keio University School of Medicine, 35 Shinanomachi, Shinjuku-ku, Tokyo 160-8582, Japan;
| | - Daisuke Nakashima
- Department of Orthopaedic Surgery, Keio University School of Medicine, 35 Shinanomachi, Shinjuku-ku, Tokyo 160-8582, Japan; (H.O.); (Y.M.); (S.M.); (T.M.); (M.M.); (M.N.); (T.N.)
| | - Yuta Maeda
- Department of Orthopaedic Surgery, Keio University School of Medicine, 35 Shinanomachi, Shinjuku-ku, Tokyo 160-8582, Japan; (H.O.); (Y.M.); (S.M.); (T.M.); (M.M.); (M.N.); (T.N.)
| | - Shunsuke Minoji
- Department of Orthopaedic Surgery, Keio University School of Medicine, 35 Shinanomachi, Shinjuku-ku, Tokyo 160-8582, Japan; (H.O.); (Y.M.); (S.M.); (T.M.); (M.M.); (M.N.); (T.N.)
| | - Takashi Morisue
- Department of Orthopaedic Surgery, Keio University School of Medicine, 35 Shinanomachi, Shinjuku-ku, Tokyo 160-8582, Japan; (H.O.); (Y.M.); (S.M.); (T.M.); (M.M.); (M.N.); (T.N.)
| | - Yoshinori Katsumata
- Institute for Integrated Sports Medicine, Keio University School of Medicine, 35 Shinanomachi, Shinjuku-ku, Tokyo 160-8582, Japan;
- Department of Cardiology, Keio University School of Medicine, 35 Shinanomachi, Shinjuku-ku, Tokyo 160-8582, Japan
| | - Morio Matsumoto
- Department of Orthopaedic Surgery, Keio University School of Medicine, 35 Shinanomachi, Shinjuku-ku, Tokyo 160-8582, Japan; (H.O.); (Y.M.); (S.M.); (T.M.); (M.M.); (M.N.); (T.N.)
| | - Masaya Nakamura
- Department of Orthopaedic Surgery, Keio University School of Medicine, 35 Shinanomachi, Shinjuku-ku, Tokyo 160-8582, Japan; (H.O.); (Y.M.); (S.M.); (T.M.); (M.M.); (M.N.); (T.N.)
| | - Takeo Nagura
- Department of Orthopaedic Surgery, Keio University School of Medicine, 35 Shinanomachi, Shinjuku-ku, Tokyo 160-8582, Japan; (H.O.); (Y.M.); (S.M.); (T.M.); (M.M.); (M.N.); (T.N.)
- Department of Clinical Biomechanics, Keio University School of Medicine, 35 Shinanomachi, Shinjuku-ku, Tokyo 160-8582, Japan
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