Author: "Si, Y" - Searchworks@Jio Institute Digital Library Search Results

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2,505 results on '"Si, Y"'

1. The Complete Mitochondrial Genome of the Goitered Gazelle (Gazella subgutturosa hillieriana) from Ningxia Hui Autonomous Region, China

Author: Si, Y. H., Meng, D. H., Li, Z. Z., Hu, T. H., Teng, L. W., and Liu, Z. S.
Published: 2023
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2. A Prospective Randomized Controlled Trial Assessing the Impact of Preoperative Combined with Postoperative Progressive Resistance Training on Muscle Strength, Gait, Balance and Function in Patients Undergoing Total Hip Arthroplasty

Author: Chen G, Yu D, Wang Y, Ma Z, Bi M, Lu L, Zhang S, Liu J, Chen H, Shen H, Zhang H, Luo X, Si Y, and Zhang P
Subjects: exercise therapy, muscle strength, progressive resistance training, total hip arthroplasty, gait variability, Geriatrics, RC952-954.6
Abstract: Guo Chen,1 Duoduo Yu,2 Yichen Wang,1 Zou Ma,1 Mengna Bi,1 Lisha Lu,1 Shangshang Zhang,1 Jiaxin Liu,1 Hu Chen,1 Hai Shen,2 Huiwu Zhang,2 Xiaobing Luo,2 Yan Si,1 Peng Zhang1 1Department of Geriatric Orthopedics(1), Sichuan Provincial Orthopedic Hospital, Chengdu, Sichuan, 610041, People’s Republic of China; 2Sichuan Provincial Orthopedic Hospital, Chengdu, Sichuan, 610041, People’s Republic of ChinaCorrespondence: Peng Zhang, Tel +86-19980487275, Email yicoal@yeah.netPurpose: The aim of this study is to investigate the effects of a preoperative combined with postoperative moderate-intensity progressive resistance training (PRT) of the operative side in patients with hip osteoarthritis (HOA) who are undergoing total hip arthroplasty (THA). The study seeks to evaluate the impact of this combined intervention on muscle strength, gait, balance, and hip joint function in a controlled, measurable, and objective manner. Additionally, the study aims to compare the outcomes of this combined intervention with those of preoperative or postoperative muscle strength training conducted in isolation.Methods: A total of 90 patients with HOA scheduled for unilateral primary THA were randomly assigned to three groups: Pre group (preoperative PRT), Post group (postoperative PRT), and Pre& Post group (preoperative combined with postoperative PRT) focusing on hip flexion, extension, adduction, and abduction of operated side. Muscle strength, gait parameters, balance, and hip function were assessed at specific time points during a 12-month follow-up period.Results: All three groups showed significant improvements in muscle strength, with the Pre& Post group demonstrating the most pronounced and sustained gains. Gait velocity and cadence were significantly improved in the Pre& Post group at 1-month and 3-month postoperative follow-ups compared to the other groups. Similarly, the Pre& Post group exhibited superior balance performance at 3-month and 12-month postoperative follow-ups. The Harris Hip Score also showed better outcomes in the Pre& Post group at all follow-up intervals.Conclusion: Preoperative combined with postoperative moderate-intensity PRT in HOA patients undergoing THA led to superior improvements in muscle strength, gait, balance, and hip joint function compared to preoperative or postoperative PRT alone. This intervention shows significant promise in optimizing postoperative rehabilitation and enhancing patient outcomes following THA.Keywords: exercise therapy, muscle strength, progressive resistance training, total hip arthroplasty, gait variability
Published: 2024

3. Allisartan Isoproxil Promotes Uric Acid Excretion by Interacting with Intestinal Urate Transporters in Hyperuricemic Zebrafish (Danio rerio)

Author: Xiao, Y., Miao, Z., Sun, J., Xing, W., Wei, Y., Bai, J., Ye, H., Si, Y., and Cai, L.
Published: 2023
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4. Designing heat transfer pathways for advanced thermoregulatory textiles

Author: Lan, X., Wang, Y., Peng, J., Si, Y., Ren, J., Ding, B., and Li, B.
Subjects: Physics - Applied Physics, Condensed Matter - Materials Science
Abstract: Thermal comfort of textiles plays an indispensable role in the process of human civilization. Advanced textile for personal thermal management shapes body microclimates by merely regulating heat transfer between the skin and local ambient without wasting excess energy. Therefore, numerous efforts have recently been devoted to the development of advanced thermoregulatory textiles. In this review, we provide a unified perspective on those state-of-the-art efforts by emphasizing the design of diverse heat transfer pathways. We focus on engineering certain physical quantities to tailor the heat transfer pathways, such as thermal emittance/absorptance, reflectance and transmittance in near-infrared and mid-infrared radiation, as well as thermal conductance in conduction. Tuning those heat transfer pathways can achieve different functionalities for personal thermal management, such as passive cooling, warming, or even dual-mode (cooling-warming), either static switching or dynamic adapting. Finally, we point out the challenges and opportunities in this emerging field, including but not limited to the impact of evaporation and convection with missing blocks of heat pathways, the bio-inspired and artificial-intelligence-guided design of advanced functional textiles., Comment: 31 pages, 22 figures, the final published version can be found in https://doi.org/10.1016/j.mtphys.2021.100342
Published: 2021
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5. Novel Bedside Dynamic Nomograms to Predict the Probability of Postoperative Cognitive Dysfunction in Elderly Patients Undergoing Noncardiac Surgery: A Retrospective Study

Author: Li J, Xie X, Zhang J, Shen P, Zhang Y, Chen C, Si Y, and Zou J
Subjects: postoperative cognitive dysfunction, elderly patients, noncardiac surgery, dynamic nomograms, predict, pre-and postoperative models, Geriatrics, RC952-954.6
Abstract: Junlin Li,1,2,&ast; Xianhai Xie,1,2,&ast; Jiayong Zhang,3,4,&ast; Po Shen,3,4 Yuan Zhang,3 Chen Chen,2,5 Yanna Si,3 Jianjun Zou2,5 1School of Basic Medicine and Clinical Pharmacy, China Pharmaceutical University, Nanjing, People’s Republic of China; 2Department of Clinical Pharmacology, Nanjing First Hospital, Nanjing Medical University, Nanjing, People’s Republic of China; 3Department of Anesthesiology, Nanjing First Hospital, Nanjing Medical University, Nanjing, People’s Republic of China; 4Department of Anesthesiology, The Fourth Affiliated Hospital of Nanjing Medical University, Nanjing Medical University, Nanjing, People’s Republic of China; 5Department of Pharmacy, Nanjing First Hospital, China Pharmaceutical University, Nanjing, People’s Republic of China&ast;These authors contributed equally to this workCorrespondence: Yanna Si; Jianjun Zou, Department of Anesthesiology, Nanjing First Hospital, Nanjing Medical University, Nanjing, China; Department of Clinical Pharmacology, Nanjing First Hospital, Nanjing Medical University, Nanjing, People’s Republic of China, Tel +86 13851639332 ; +86 15380998951, Email siyanna@163.com; zoujianjun100@126.comPurpose: Early and accurate prediction of elderly patients at high risk of postoperative cognitive dysfunction (POCD) after non-cardiac surgery will provide favorable evidence for rational perioperative management and long-term postoperative recovery. This study aimed to develop bedside dynamic nomograms to provide accurately an individualized prediction of the risk of POCD at 6-month postoperatively with patients undergoing non-cardiac surgery and to guide clinical decision-making and postoperative management.Patients and Methods: We retrospectively collected patients undergoing surgical treatment at the Nanjing First Hospital between May 2020 and May 2021. We collected the data on preoperative, intraoperative, and postoperative variables. Clinical and laboratory data on admission and intraoperative variables and postoperative variables were used. We measured the performances of the nomograms using sensitivity, specificity of the receiver operating characteristic (ROC), the area under the ROC curves (AUC), the 10-fold cross-validation, and decision curve analysis (DCA).Results: POCD was observed in 23 of 415 patients (5.6%) at 6-month postoperatively. The preoperative and postoperative models obtained 91.6% and 94.0% accuracy rates on the data. Compared to the preoperative model, the postoperative model had an area under the receiver characteristic curve (AUC) of 0.973 vs 0.947, corresponding to a specificity of 0.941 vs 0.918 and a sensitivity of 0.913 vs 0.870. The overall performance of the postoperative model was better than the preoperative model.Conclusion: In this study, we developed novel bedside dynamic nomograms with reasonable clinical utility that can provide individualized prediction of POCD risk at 6-month postoperatively in elderly patients undergoing non-cardiac surgery at different time points based on patient admission and postoperative data. External validations are needed to ensure their value in predicting POCD in elderly patients.Keywords: postoperative cognitive dysfunction, elderly patients, noncardiac surgery, dynamic nomograms, predict, pre- and postoperative models
Published: 2022

6. Automated Digitization of the Cardiotocography Signals from Real Scene Image of Binary Clinic Report

Author: Zhang, Y., Si, Y., Liu, Z., Zhao, Z., and Ye, H.
Published: 2022
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7. Assessment of Completeness of Reporting in Randomized Controlled Trials of Acupuncture Therapy for Chronic Obstructive Pulmonary Disease

Author: Ruan H, Zhang H, Feng Z, Li X, Han W, Si Y, and Li J
Subjects: chronic obstructive pulmonary disease, acupuncture therapy, randomized controlled trials, completeness of reporting, Medicine (General), R5-920
Abstract: Huanrong Ruan,1,2 Hailong Zhang,1– 3 Zhenzhen Feng,1– 3 Xuanlin Li,1,2 Weihong Han,1,2 Yimei Si,1,2 Jiansheng Li1– 3 1Co-construction Collaborative Innovation Center for Chinese Medicine and Respiratory Diseases by Henan & Education Ministry of P.R. China, Henan University of Chinese Medicine, Zhengzhou, Henan, 450046, People’s Republic of China; 2Henan Key Laboratory of Chinese Medicine for Respiratory Disease, Henan University of Chinese Medicine, Zhengzhou, Henan, 450046, People’s Republic of China; 3Department of Respiratory Diseases, The First Affiliated Hospital of Henan University of Chinese Medicine, Zhengzhou, Henan, 450003, People’s Republic of ChinaCorrespondence: Jiansheng Li, Henan University of Chinese Medicine, No. 156 Jinshui East Road, Zhengzhou, 450046, People’s Republic of China, Tel +86 371 65676568, Fax +86 371 65944307, Email li_js8@163.comObjective: To assess the completeness of reporting in randomized controlled trials (RCTs) of acupuncture therapy (AT) for chronic obstructive pulmonary disease (COPD).Methods: We systematically searched PubMed, Embase, Cochrane Library, Web of Science, China National Knowledge Infrastructure (CNKI), Chongqing VIP (CQVIP), WANFANG Data, and China Biology Medicine (CBM) for studies published from their inception to May 8, 2021. The completeness of reporting was evaluated by CONSORT statement and STRICTA guidelines. Univariate and multivariate regression analyses were performed to preliminarily explore the factors related to completeness of reporting.Results: A total of 44 RCTs were included. The overall quality score (OQS) based on the CONSORT statement and STRICTA guidelines ranged from 3 to 26 and 7 to 14, with a median of 10 and 11, respectively. Among the 35 items of the CONSORT statement, 10 items were fully reported with reporting rate > 70%, and 11 items were poorly reported at a rate < 5%. Among the 17 items of the STRICTA guidelines, 10 items were adequately reported with > 70%, and only 3 items were incompletely reported at a rate < 20%. The agreement of most items was determined as “good”, “substantial”, or “moderate”. By regression analysis, publication language (β coefficient: 6.432, 95% CI: 3.202 to 9.663, P < 0.001) and funding source (β coefficient: 3.159, 95% CI: 1.045 to 5.273, P =0.004) acted as independent predictors of completeness of reporting according to the CONSORT statement. However, no variables associated with the STRICTA guidelines were identified.Conclusion: The completeness of reporting of AT for COPD was inadequate. The condition relatively improved for trials with publication in the English language and funding source. By recommendation, reports should be strictly standardized in accordance with the CONSORT statement and STRICTA guidelines to improve the clinical research evidence of AT for COPD.Keywords: chronic obstructive pulmonary disease, acupuncture therapy, randomized controlled trials, completeness of reporting
Published: 2022

8. Non-Tuberculous Mycobacterial Pulmonary Disease with Detection of Mycobacterium Tuberculosis in Pleural Fluid.

Author: Ling Zhang, Sun, Si Y., Yao, Xue X., Fu, Ai S., and Ge, Yan L.
Subjects: EXTRAPULMONARY tuberculosis, MYCOBACTERIAL diseases, MYCOBACTERIUM tuberculosis, TUBERCULOSIS, LUNG diseases
Abstract: Background: Tuberculous pleurisy (TP) is one of the most common types of extrapulmonary tuberculosis, often secondary to tuberculosis (TB). Clinical and imaging manifestations of non-tuberculous mycobacterial pulmonary diseases (NTM-PD) are usually similar to those of tuberculosis. Because of their similarity and the high incidence of tuberculosis, non-tuberculous mycobacterial infections are often overlooked for a long time. Especially in people without immunodeficiency. Methods: Mycobacterium tuberculosis (MTB) in pleural effusion was found by metagenomic next-generation sequencing (mNGS). During anti-tuberculosis treatment, mNGS of lung tissue by ultrasound-guided percutaneous lung puncture revealed that this patient had combined NTM-PD. Results: Mycobacterium chelonae (M. chelonae) was detected by mNGS, and after anti-NTM treatment, the patient's chest CT showed that the inflammation was absorbed more than before, and the patient's symptoms improved. Conclusions: When TB is poorly treated with standardized anti-tuberculosis therapy, comorbid non-tuberculous mycobacterial infections may be considered, and mNGS may complement traditional pathogenetic testing. [ABSTRACT FROM AUTHOR]
Published: 2024
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9. The short-term efficacy of electrical pudendal nerve stimulation versus intravesical instillation for the urethral pain syndrome: a randomized clinical trial

Author: Li, Tian, Feng, Xin Y., Feng, Xiao M., Lv, Jian W., Lv, Ting T., and Wang, Si Y.
Published: 2021
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10. Global age-sex-specific mortality, life expectancy, and population estimates in 204 countries and territories and 811 subnational locations, 1950–2021, and the impact of the COVID-19 pandemic : a comprehensive demographic analysis for the Global Burden of Disease Study 2021

Author: Schumacher, A. E., Kyu, H. H., Antony, C. M., Aravkin, A. Y., Azhar, G. S., Bisignano, C., Burkart, K., Cercy, K. M., Chung, E., Coberly, K., Comfort, H., Cousin, E., Culbreth, G. T., Cunningham, M., Weaver, N. D., Degenhardt, L., Deitesfeld, L., Dirac, M. A., Estep, K., Feigin, V. L., Flaxman, A. D., Flor, L. S., Force, L. M., Fuller, J. E., Gakidou, E., Hay, S. I., Ikuta, K. S., Jones, D. P., Kassebaum, N. J., Kassel, M. B., Keller, C., Kinzel, K. E., Krohn, K. J., Lozano, R., May, E. A., McKowen, A. W., McLaughlin, S. A., Mehlman, M. L., Mestrovic, T., Mokdad, A. H., Mosser, J. F., Mougin, V., Naghavi, M., Nesbit, O. D., Novotney, A., Ozten, Y., Pease, S. A., Pigott, D. M., Reiner, R. C., Robinson-Oden, H. E., Shaw, D. H., Slepak, E. L. N., Sorensen, R. J. D., Verghese, N. A., Vollset, S., Vongpradith, A., Vos, T., Wang, D., Watson, S., Weaver, M. R., Wells, K. M., Wilson, S., Wool, E. E., Zheng, P., Lim, S. S., Murray, C. J. L., Boyko, E. J., Chahine, Y., Kalani, R., Krishnamoorthy, V., Khalil, I. A., Minja, N. W., Morrison, S. D., Nafukho, F. M., Olivas-Martinez, A., Orellana, E., Tram, K., Aali, A., Rahnavard, N., Ahmadzade, A., Mohammad-Pour, S., Morovatdar, N., Pourali, G., Zafari, N., Abbafati, C., Cattaruzza, M. S., Abbas, J., Phillips, M. R., Abbasgholizadeh, R., Emamverdi, M., Friedman, J., Abbasi, M. A., Daneshvar, S., Dashti, M., Ghasemzadeh, A., Mirza-Aghazadeh-Attari, M., Doshmangir, L., Ghafourifard, M., Lotfi, M., Hosseini, M., Jadidi-Niaragh, F., Kalankesh, L. R., Karimi, S., Mohammad-Alizadeh-Charandabi, S., Khalafi, M., Mirghafourvand, M., Mirinezhad, S., Heris, R. M., Mousavi, S., Kafil, H. S., Abbasian, M., Momenzadeh, K., Santos, F. C. D., Carr, S., Chi, G., Elgendy, I. Y., Feroze, A. H., Kempen, J. H., Kubeisy, C. M., Li, Z., Rohloff, P., Liu, X., Natto, Z. S., Olanipekun, T. O., Pigeolet, M., Pradhan, P. M. S., Zweck, E., Sharfaei, S., Sheikh, A., Abtahi, D., Salimi, S., Shakeri, A., Tajbakhsh, A., Aghamiri, S., Ahmadzade, M., Hashemi, M. B., Ajami, M., Asgary, S., Ghasemi, M., Hassanian-Moghaddam, H., Kolahi, A., Nikoobar, A., Heidari-Foroozan, M., Montazeri, F., Nejadghaderi, S., Rahmani, S., Ziaeefar, P., Hesami, H., Zahir, M., Jahankhani, K., Rasouli-Saravani, A., Jahanmehr, N., Kashani, H. K., Nasiri, M., Raee, P., Rezaee, M., Safi, S., Shool, S., Tabatabai, S., ElHafeez, S. A., Tantawi, M. E., Elmeligy, O. A. A., Ghazy, R. M., Talaat, I. M., Abdelmasseh, M., Sanabria, J., Abd-Elsalam, S., Abdelwahab, A., Abdollahi, M., Abolhassani, H., Rezaei, N., Saghazadeh, A., Ala, M., Noroozi, N., Bahri, R. A., Khatami, F., Ayyoubzadeh, S., Azadnajafabad, S., Keykhaei, M., Momtazmanesh, S., Mousavi, P., Behnoush, A., Farrokhpour, H., Karimi, H., Khalaji, A., Khanmohammadi, S., Mayeli, M., Mohammadi, S., Eskandarieh, S., Sahraian, M., Fahimi, S., Malekzadeh, R., Mansouri, V., Sepanlou, S. G., Ghassemi, F., Haddadi, M., Kazemian, S., Khadembashiri, M., Khamesipour, F., Khavandegar, A., Khormali, M., Salamati, P., Kompani, F., Larijani, B., Mirdamadi, N., Seyedi, S., Malazy, O. T., Mahmoudi, E., Rashedi, S., Rad, E. M., Mansournia, M., Nasab, E. M., Mohammadshahi, M., Mostafavi, H., SeyedAlinaghi, S., Shafie, M., Shahbandi, A., Vahdani, A. M., Sharifan, A., Shirkoohi, R., Sohrabi, H., Tavangar, S., Heidari-Soureshjani, R., Abdoun, M., Abdullahi, A., Awotidebe, A. W., Borodo, S. B., Gadanya, M. A., Ladan, M., Ali, M. U., Tyrovolas, S., Abdurehman, A. M., Debele, A. T., Getachew, T., Gudeta, M. D., Misgana, T., Sertsu, A., Abebe, M., Ayele, G. M., Afework, A., Lerango, T. L., Tebeje, T. M., Sibhat, M. M., Tesfaye, S. H., Abedi, A., Gholamrezanezhad, A., Salehi, S., Athari, S., Hanifi, N., Abegaz, T. M., Kifle, Z. D., Zuñiga, R. A. A., Abhilash, E. S., Abiodun, O. O., Aboagye, R. G., Amu, H., Ayanore, M. A., Dowou, R. K., Immurana, M., Klu, D., Orish, V. N., Carrero, J. J., Cederroth, C. R., Deuba, K., Laflamme, L., Fereshtehnejad, S., Kauppila, J. H., Abouzid, M., Abreu, L. G., Malta, D. C., Prates, E. J. S., Nascimento, B. R., Abrha, W. A., Weldemariam, A. H., Girmay, A., Abrigo, M. R. M., Rumeileh, S. A., Abu-Rmeileh, N. M., Aburuz, S., Ahmed, L. A., Alam, Z., Elbarazi, I., Grivna, M., Nauman, J., Khan, G., Khan, M. A., Zaki, N., Ahmad, M. M., Abu-Zaid, A., Temsah, R. M. H., Zand, R., Acuna, J. M., Gautam, P., Chowdhury, R., Adair, T., Jiang, H., Babu, A. S., Borschmann, R., Meretoja, A., Wijeratne, T., Addo, I. Y., Okeke, S. R., Dai, Z., Xu, X., Huda, M., Mitchell, P. B., Peden, A. E., Resnikoff, S., Sharma, S., Si, Y., Sitas, F., Ye, P., Adebayo, O. M., Aladelusi, T. O., Salami, A. A., Ilesanmi, O. S., Owolabi, M. O., Adegboye, O. A., Adekanmbi, V., AlBataineh, M. T., Almahmeed, W., Aden, B., Adepoju, A. V., Adetunji, C. O., Adeyeoluwa, T. E., Oyeyemi, I. T., Oyeyemi, O. T., Udoakang, A. J., Adeyomoye, O. I., Anuoluwa, I. A., Bello, O. O., Oluwafemi, Y. D., Ekundayo, T. C., Idowu, O. O., Oluwatunase, G. O., Afolabi, A. A., Ekholuenetale, M., Fagbamigbe, A. F., Olufadewa, I. I., Ibitoye, S. E., Okekunle, A. P., Adha, R., Adikusuma, W., Adibi, A., Chen, M., Hossain, M., Rasali, D. P., Pashaei, A., Adnani, Q. E. S., Postma, M. J., Adra, S., Barqawi, H. J., Dash, N. R., Halwani, R., Maghazachi, A. A., Saber-Ayad, M. M., Sharif-Askari, N. S., Ahmad, F., Saddik, B., Saleh, M. A., Alzoubi, K. H., Omar, H. A., Arumugam, A., Bustanji, Y., Elemam, N. M., Faris, M. E. M., Karim, A., Qaisar, R., Semreen, M. H., Soliman, S. S. M., Altirkawi, K. A., Afraz, A., Ilaghi, M., Nematollahi, M., Afyouni, S., Amindarolzarbi, A., Zandieh, G. G. Z., Columbus, A., Kamireddy, A., Shafaat, O., Kazemi, F., Vervoort, D., Zhang, H., Jamshidi, E., Afzal, S., Agasthi, P., Agodi, A., Barchitta, M., D'Amico, E., Maugeri, A., Veroux, M., Biondi, A., Isola, G., Vacante, M., Falzone, L., Libra, M., Agyemang-Duah, W., Nikpoor, A., Ahinkorah, B. O., Demant, D., Ahmad, A., Mustafa, G., Pathan, A. R., Tabish, M., Ahmad, D., Bagheri, N., Burns, R. A., Cherbuin, N., Ahmad, T., Ahmadi, K., Saxena, S., Beaney, T., Palladino, R., Rawaf, S., Mossialos, E., Rawaf, D. L., Ahmed, A., Siddig, E. E., Ahmed, H., Ahmed, M. B., Shiferaw, D., Ashemo, M. Y., Gerema, U., Getachew, M. E., Bayileyegn, N. S., Mohamed, A. I., Eshetie, T. C., Tiruye, T. Y., Ahmed, S., Ali, H., Bodunrin, A. O., Tumurkhuu, M., Tung, K., Ubah, C. S., Aruleba, R. T., Aji, B., Ajumobi, O., Akalu, G. T., Beyene, H. B., Deribe, K., Ijo, D., Kassaw, N. A., Akara, E., Akinosoglou, K., Akkala, S., Asaad, M., Hassan, A. M., Bleyer, A., Akyirem, S., Bell, M. L., Song, Y., Etaee, F., Goldust, M., Li, W., Pawar, S., Hamad, H. A., Sathian, B., Hasan, S. A., Homsi, A. A., Almidani, O., Göbölös, L., Qadire, M. A., AL-Ahdal, T. M. A., Chen, S., Moazen, B., Alalalmeh, S. O., Hegazi, O. E., Shahwan, M. J., Shamsi, M. A., Zyoud, S. H., Al-Aly, Z., Wang, C., Alam, K., Alam, M., Al-Amer, R. M., Naik, G. R., Alanzi, T. M., Bah, S., Menezes, R. G., Alanezi, F. M., Albashtawy, M., Aldridge, R. W., Chung, S., Hossain, S., Kim, J., Kivimäki, M., Sunkersing, D., Umar, T., Zumla, A., Alemi, S., Al-Eyadhy, A., Temsah, M., Alhabib, K. F., ElGohary, G. M. T., Meo, S. A., Al-Gheethi, A. A. S., Kiross, G. T., Alhalaiqa, F. A. N., Al-Maweri, S. A. A., Alomari, M. A., Mohammed, M., Al-Hanawi, M. K., Binmadi, N., Malik, A. A., Samargandy, S., Ali, A., Khan, I., Sawyer, S. M., Ali, B. A., Ali, R., Ali, S. S., Ali, Z., Samakkhah, S. A., Alicandro, G., Alif, S. M., Maharjan, P., Rai, P., Hasan, M., Thapa, R., Thrift, A. G., Aligol, M., Alimi, R., Aliyi, A. A., Jema, A., Al-Jumaily, A., Hankey, G. J., Kujan, O., Mansour, A., Aljunid, S. M., Al-Sabah, S. K., Al-Marwani, S., Almazan, J. U., Poddighe, D., Al-Mekhlafi, H. M., Ariffin, H., Lim, L., Bandyopadhyay, S., Basnyat, B., Maude, R. J., Bennett, D. A., Browne, A. J., Dolecek, C., Dunachie, S. J., Newton, C. R. J., Rodriguez, J. A. B., Kheirallah, K. A., Alonso, N., Bensenor, I. M., Brunoni, A. R., Castaldelli-Maia, J., Peres, M. F. P., Wang, Y., Alqahtani, J. S., Alqutaibi, A., Altaf, A., Alvi, F. J., Nargus, S., Arooj, M., Latif, M., Shahid, S., Shahid, W., Ashraf, M., Riaz, M. A., Al-Tawfiq, J. A., Alwafi, H., Rehman, F., Al-Worafi, Y. M., Aly, H., Ali, A. H., Amare, A., Gill, T. K., Yadav, L., Noubiap, J., Opio, J., Mengesha, E. W., Ameyaw, E. K., Amhare, A., Lin, S., Amin, T. T., Elhabashy, H. R., Hassan, A., Dehkordi, J. A., Kabir, H., Amiri, S., Amugsi, D. A., Wado, Y. D., Amzat, J., Bello, M. B., Shittu, A., Aruleba, I. T., Ancuceanu, R., Andrei, C., Florin, B. T., Negoi, I., Serban, D., Hostiuc, M., Hostiuc, S., Matei, C. N., Negoi, R. I., Anderlini, D., Begum, T., Kanmiki, E., Maravilla, J. C., Khan, A., Moni, M., Lalloo, R., McGrath, J. J., Veerman, L. J., Andrade, P. P., Busse, R., Mohammed, S., Andrei, T., Herteliu, C., Mirica, A., Otoiu, A., Petcu, I., Dima, A., Stefan, S., Angappan, D., Anil, A., Charan, J., Shamim, M., Singh, S., Varthya, S. B., Baskaran, P., Bhardwaj, P., Bhardwaj, N., Dixit, S. G., Krishna, H., Nayyar, A. K., Choudhary, R., Dixit, A., Misra, S., Mittal, M., Saravanan, A., Singh, M., Ram, P., Anjum, A., Antriyandarti, E., Anwar, S., Anyasodor, A. E., Appiah, S., Boampong, M. S., Aqeel, M., Arabloo, J., Eghdami, S., Panahi, P., Kabir, A., Salahi, S., Behnagh, A. K., Kasraei, H., Khodadoust, E., Latifinaibin, K., Moradi-Lakeh, M., Toroudi, H. P., Sarveazad, A., Zahedi, M., Moradi, M., Arab-Zozani, M., Ghalibaf, A. M., Rajabpour-Sanati, A., Arafat, M., Araújo, A. M., Belo, L., Carvalho, F., Costa, V. M., da Silva, D. D., Silva, J. P., Carvalho, M., Cruz-Martins, N., Freitas, A., Vieira, R. J., Pinheiro, M., Ribeiro, A., Aremu, A., Odetokun, I. A., Aripov, T., Armocida, B., Unim, B., Sabbatucci, M., Artamonov, A. A., Artanti, K. 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Abstract: Background: Estimates of demographic metrics are crucial to assess levels and trends of population health outcomes. The profound impact of the COVID-19 pandemic on populations worldwide has underscored the need for timely estimates to understand this unprecedented event within the context of long-term population health trends. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 provides new demographic estimates for 204 countries and territories and 811 additional subnational locations from 1950 to 2021, with a particular emphasis on changes in mortality and life expectancy that occurred during the 2020–21 COVID-19 pandemic period. Methods: 22 223 data sources from vital registration, sample registration, surveys, censuses, and other sources were used to estimate mortality, with a subset of these sources used exclusively to estimate excess mortality due to the COVID-19 pandemic. 2026 data sources were used for population estimation. Additional sources were used to estimate migration; the effects of the HIV epidemic; and demographic discontinuities due to conflicts, famines, natural disasters, and pandemics, which are used as inputs for estimating mortality and population. Spatiotemporal Gaussian process regression (ST-GPR) was used to generate under-5 mortality rates, which synthesised 30 763 location-years of vital registration and sample registration data, 1365 surveys and censuses, and 80 other sources. ST-GPR was also used to estimate adult mortality (between ages 15 and 59 years) based on information from 31 642 location-years of vital registration and sample registration data, 355 surveys and censuses, and 24 other sources. Estimates of child and adult mortality rates were then used to generate life tables with a relational model life table system. For countries with large HIV epidemics, life tables were adjusted using independent estimates of HIV-specific mortality generated via an epidemiological analysis of HIV prevalence surveys, ant
Published: 2024
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11. Burden of disease scenarios for 204 countries and territories, 2022-2050: a forecasting analysis for the Global Burden of Disease Study 2021

Author: Vollset, SE, Ababneh, HS, Abate, YH, Abbafati, C, Abbasgholizadeh, R, Abbasian, M, Abbastabar, H, Abd Al Magied, AHA, Abd ElHafeez, S, Abdelkader, A, Abdelmasseh, M, Abd-Elsalam, S, Abdi, P, Abdollahi, M, Abdoun, M, Abdullahi, A, Abebe, M, Abiodun, O, Aboagye, RG, Abolhassani, H, Abouzid, M, Aboye, GB, Abreu, LG, Absalan, A, Abualruz, H, Abubakar, B, Abukhadijah, HJJ, Addolorato, G, Adekanmbi, V, Adetunji, CO, Adetunji, JB, Adeyeoluwa, TE, Adha, R, Adhikary, RK, Adnani, QES, Adzigbli, LA, Afrashteh, F, Afzal, MS, Afzal, S, Agbozo, F, Agodi, A, Agrawal, A, Agyemang-Duah, W, Ahinkorah, BO, Ahlstrom, AJ, Ahmad, A, Ahmad, F, Ahmad, MM, Ahmad, S, Ahmed, A, Ahmed, H, Ahmed, S, Ahmed, SA, Akinosoglou, K, Akkaif, MA, Akrami, AE, Akter, E, Al Awaidy, S, Al Hasan, SM, Al Mosa, AS, Al Ta'ani, O, Al Zaabi, OAM, Alahdab, F, Alajlani, MM, Al-Ajlouni, Y, Alalalmeh, SO, Al-Aly, Z, Alam, K, Alam, N, Alam, T, Alam, Z, Al-Amer, RM, Alanezi, FM, Alanzi, TM, Albakri, A, Aldhaleei, WA, Aldridge, RW, Alemohammad, SY, Alemu, YM, Al-Gheethi, AAS, Al-Hanawi, MK, Ali, A, Ali, I, Ali, MU, Ali, R, Ali, SSS, Ali, VE, Ali, W, Al-Ibraheem, A, Alicandro, G, Alif, SM, Aljunid, SM, Alla, F, Almazan, JU, Al-Mekhlafi, HM, Alqutaibi, AY, Alrawashdeh, A, Alrousan, SM, Al-Sabah, SK, Alsabri, MA, Altaany, Z, Al-Tammemi, AB, Al-Tawfiq, JA, Altirkawi, KA, Aluh, DO, Alvis-Guzman, N, Al-Wardat, MS, Al-Worafi, YM, Aly, H, Alyahya, MS, Alzoubi, KH, Al-Zyoud, W, Amani, R, Ameyaw, EK, Amin, TT, Amindarolzarbi, A, Amiri, S, Amirzade-Iranaq, MH, Amu, H, Amugsi, DA, Ancuceanu, R, Anderlini, D, Anderson, DB, Andrade, PP, Andrei, CL, Andrei, T, Andrews, EA, Anil, A, Anil, S, Anoushiravani, A, Antony, CM, Antriyandarti, E, Anuoluwa, BS, Anvari, S, Anyasodor, AE, Appiah, F, Aquilano, M, Arab, JP, Arabloo, J, Arafa, EA, Arafat, M, Aravkin, AY, Ardekani, A, Areda, D, Aregawi, BB, Aremu, A, Ariffin, H, Arkew, M, Armani, K, Artamonov, AA, Arumugam, A, Asghari-Jafarabadi, M, Ashbaugh, C, Astell-Burt, T, Athari, SS, Atorkey, P, Atout, MMW, Aujayeb, A, Ausloos, M, Awad, H, Awotidebe, AW, Ayatollahi, H, Ayuso-Mateos, JL, Azadnajafabad, S, Azeez, FK, Azevedo, RMS, Badar, M, Baghdadi, S, Bagheri, M, Bagheri, N, Bai, R, Baker, JL, Bako, AT, Balakrishnan, S, Balcha, WF, Baltatu, OC, Barchitta, M, Bardideh, E, Barker-Collo, SL, Barnighausen, TW, Barqawi, HJ, Barteit, S, Basiru, A, Basso, JD, Bastan, M-M, Basu, S, Bauckneht, M, Baune, BT, Bayati, M, Bayileyegn, NS, Behnoush, AH, Behzadi, P, Beiranvand, M, Bello, OO, Belo, L, Beloukas, A, Bemanalizadeh, M, Bensenor, IM, Benzian, H, Beran, A, Berezvai, Z, Bernstein, RS, Bettencourt, PJG, Beyene, KA, Beyene, MG, Bhagat, DS, Bhagavathula, AS, Bhala, N, Bhandari, D, Bharadwaj, R, Bhardwaj, N, Bhardwaj, P, Bhargava, A, Bhaskar, S, Bhat, V, Bhattacharjee, NV, Bhatti, GK, Bhatti, JS, Bhatti, MS, Bhuiyan, MA, Bisignano, C, Biswas, B, Bjorge, T, Bodolica, V, Bodunrin, AO, Hashemi, MB, Basara, BB, Borhany, H, Bosoka, SA, Carvajal, AB, Bouaoud, S, Boufous, S, Boxe, C, Boyko, EJ, Brady, OJ, Braithwaite, D, Brauer, M, Brazo-Sayavera, J, Brenner, H, Brown, CS, Browne, AJ, Brugha, T, Bryazka, D, Bulamu, NB, Buonsenso, D, Burkart, K, Burns, RA, Busse, R, Bustanji, Y, Butt, ZA, dos Santos, FLC, Barsbay, MC, Calina, D, Campos, LA, Cao, S, Capodici, A, Cardenas, R, Carreras, G, Carugno, A, Carvalho, M, Castaldelli-Maia, JM, Castelpietra, G, Cattaruzza, MS, Caye, A, Cegolon, L, Cembranel, F, Cenko, E, Cerin, E, Chadban, SJ, Chadwick, J, Chakraborty, C, Chakraborty, S, Chalek, J, Chan, JSK, Chandika, RM, Chandy, S, Charan, J, Chaudhary, AA, Chaurasia, A, Chen, A-T, Chen, H, Chen, MX, Chen, S, Cherbuin, N, Chi, G, Chichagi, F, Chimed-Ochir, O, Chimoriya, R, Ching, PR, Chirinos-Caceres, JL, Chitheer, A, Cho, DY, Cho, WCS, Choi, D-W, Chong, B, Chong, CL, Chopra, H, Chu, D-T, Chung, E, Chutiyami, M, Clayton, JT, Cogen, RM, Cohen, AJ, Columbus, A, Comfort, H, Conde, J, Connolly, JT, Cooper, EEK, Cortese, S, Cruz-Martins, N, da Silva, AG, Dadras, O, Dai, X, Dai, Z, Dalton, BE, Damiani, G, Dandona, L, Dandona, R, Das, JK, Das, S, Dash, NR, Davletov, K, De la Hoz, FP, De Leo, D, Debopadhaya, S, Delgado-Enciso, I, Denova-Gutierrez, E, Dervenis, N, Desai, HD, Devanbu, VGC, Dewan, SMR, Dhama, K, Dhane, AS, Dhingra, S, da Silva, DD, Diaz, D, Diaz, LA, Diaz, MJ, Dima, A, Ding, DD, Do, THP, Do Prado, CB, Dodangeh, M, Doegah, PT, Dohare, S, Dong, W, D'Oria, M, Doshi, R, Dowou, RK, Dsouza, HL, Dsouza, V, Dube, J, Dumith, SC, Duncan, BB, Duraes, AR, Duraisamy, S, Durojaiye, OC, Dushpanova, A, Dutta, S, Dzianach, PA, Dziedzic, AM, Eboreime, E, Ebrahimi, A, Kalan, ME, Edinur, HA, Efendi, F, Eikemo, TA, Eini, E, Ekundayo, TC, El Arab, RA, El Sayed, I, Elamin, O, Elemam, NM, ElGohary, GMT, Elhadi, M, Elmeligy, OAA, Elmoselhi, AB, Elshaer, M, Elsohaby, I, Eltahir, ME, Emeto, TI, Eshrati, B, Eslami, M, Esmaeili, Z, Fabin, N, Fagbamigbe, AF, Fagbule, OF, Falzone, L, Fareed, M, Farinha, CSES, Faris, MEM, Faro, A, Fasihi, K, Fatehizadeh, A, Fauk, NK, Fazylov, T, Feigin, VL, Fekadu, G, Feng, X, Fereshtehnejad, S-M, Ferrara, P, Ferreira, N, Firew, BS, Fischer, F, Fitriana, I, Flavel, J, Flor, LS, Folayan, MO, Foley, KM, Fonzo, M, Force, LM, Foschi, M, Freitas, A, Fridayani, NKY, Fukutaki, KG, Furtado, JM, Fux, B, Gaal, PA, Gadanya, MA, Gallus, S, Ganesan, B, Ganiyani, MA, Gautam, RK, Gebi, TG, Gebregergis, MW, Gebrehiwot, M, Getacher, L, Getahun, GKA, Gething, PW, Ghadimi, DJ, Ghadirian, F, Ghafarian, S, Ghailan, KY, Ghasemi, M, Dabaghi, GG, Ghazy, RM, Ghoba, S, Gholami, E, Gholamrezanezhad, A, Gholizadeh, N, Ghorbani, M, Vajargah, PG, Ghotbi, E, Gil, AU, Gill, TK, Girmay, A, Glasbey, JC, Glushkova, EV, Gnedovskaya, EV, Gobolos, L, Goldust, M, Goleij, P, Golinelli, D, Gopalani, SV, Goulart, AC, Gouravani, M, Goyal, A, Grivna, M, Grosso, G, Guarducci, G, Gubari, MIM, Guicciardi, S, Guimaraes, RA, Gulati, S, Gulisashvili, D, Gunawardane, DA, Guo, C, Gupta, AK, Gupta, R, Gupta, S, Gupta, VK, Haakenstad, A, Hadi, NR, Haep, N, Hafiz, A, Haghmorad, D, Haile, D, Ali, AH, Ali, HA, Haj-Mirzaian, A, Halboub, ES, Haller, S, Halwani, R, Abdullah, KH, Hamdy, NM, Hamoudi, R, Hanifi, N, Hankey, GJ, Haq, ZA, Haque, MR, Harapan, H, Hargono, A, Haro, JM, Hasaballah, AI, Hasan, SMM, Hasanian, M, Hasnain, MS, Hassan, A, Haubold, J, Hay, SI, Hebert, JJ, Hegazi, OE, Heidari, M, Hemmati, M, Henson, CA, Herrera-Serna, BY, Herteliu, C, Heydari, M, Hezam, K, Hidayana, I, Hiraike, Y, Hoan, NQ, Holla, R, Hoogar, P, Horita, N, Hossain, MM, Hosseinzadeh, H, Hosseinzadeh, M, Hostiuc, M, Hostiuc, S, Hu, C, Huang, J, Hultstrom, M, Hundie, TG, Hunt, AJ, Hushmandi, K, Hussain, J, Hussain, MA, Hussein, NR, Huynh, H-H, Hwang, B-F, Ibitoye, SE, Iftikhar, PM, Ikiroma, AI, Ikwegbue, PC, Ilic, IM, Ilic, MD, Immurana, M, Isa, MA, Islam, MR, Islam, SMS, Ismail, F, Ismail, NE, Isola, G, Iwagami, M, Iyamu, IO, Jacob, L, Jacobsen, KH, Jafarinia, M, Jahankhani, K, Jahanmehr, N, Jain, N, Jairoun, AA, Mani, DRJ, Jamil, S, Jamora, RDG, Jatau, AI, Javadov, S, Javaheri, T, Jayaram, S, Jee, SH, Jeganathan, J, Jiang, H, Jokar, M, Jonas, JB, Joseph, N, Joshua, CE, Jurisson, M, Vaishali, K, Kabir, A, Kabir, Z, Kadashetti, V, Kalankesh, LR, Kalra, S, Kamath, A, Kamath, R, Kamireddy, A, Kanaan, M, Kanchan, T, Kanmiki, EW, Kanmodi, KK, Kansal, SK, Karim, A, Karkhah, S, Kashoo, FZ, Kasraei, H, Kassel, MB, Katikireddi, SV, Kauppila, JH, Kaur, H, Kayode, GA, Kazemi, F, Kazemian, S, Kebede, F, Kendal, ES, Kesse-Guyot, E, Khademvatan, S, Khajuria, H, Khalaji, A, Khalid, A, Khalid, N, Khalilian, A, Khamesipour, F, Khan, F, Khan, MJ, Khan, MAB, Khanmohammadi, S, Khatab, K, Khatatbeh, H, Khatatbeh, MM, Khatib, MN, Kashani, HRK, Kheirallah, KA, Khokhar, M, Khormali, M, Khorrami, Z, Khosla, AA, Khosravi, M, Khosrowjerdi, M, Khubchandani, J, Kifle, ZD, Kim, G, Kim, JS, Kim, MS, Kim, YJ, Kimokoti, RW, Kisa, A, Kisa, S, Knibbs, LD, Knudsen, AKS, Kochhar, S, Kolahi, A-A, Kompani, F, Koren, G, Korzh, O, Krishan, K, Krishna, V, Krishnamoorthy, V, Bicer, BK, Kuddus, MA, Kuddus, M, Kuitunen, I, Kujan, O, Kulimbet, M, Kulkarni, V, Kumar, GA, Kumar, H, Kumar, N, Kumar, R, Kumar, V, Kundu, A, Kusuma, D, Kyei-Arthur, F, Kyto, V, Kyu, HH, La Vecchia, C, Lacey, B, Ladan, MA, Laflamme, L, Lahariya, C, Lai, DTC, Lalloo, R, Lallukka, T, Lam, J, Lan, Q, Lan, T, Landires, I, Lanfranchi, F, Langguth, B, Lansingh, VC, Laplante-Levesque, A, Larijani, B, Larsson, AO, Lasrado, S, Lauriola, P, Lawlor, HR, Le, H-H, Le, LKD, Le, NHH, Le, TTT, Le, TDT, Leasher, JL, Lee, DW, Lee, M, Lee, PH, Lee, S-W, Lee, SW, Lee, SWH, Lee, YH, Leigh, J, Leong, E, Li, M-C, Libra, M, Ligade, VS, Lim, L-L, Lim, SS, Limenh, LW, Lindholm, D, Lindstedt, PA, Listl, S, Liu, G, Liu, S, Liu, X, Llanaj, E, Lopez-Bueno, R, Lopez-Gil, JF, Loreche, AM, Lotufo, PA, Lozano, R, Lubinda, J, Lucchetti, G, Luo, L, Lusk, JB, Lv, L, Amin, HIM, Ma, ZF, Maass, KL, Machairas, N, Machoy, M, Madureira-Carvalho, AM, Abd El Razek, HM, Maghazachi, AA, Prasad, DRM, Mahalleh, M, Mahasha, PW, Mahmoud, MA, Mahmoudi, E, Mahmoudvand, G, Makama, M, Rad, EM, Malhotra, K, Malik, AA, Malta, DC, Manla, Y, Mansour, A, Mansouri, MH, Mansouri, P, Mansouri, V, Mansourian, M, Mansournia, MA, Marasini, BP, Marateb, HR, Maravilla, JC, Mardi, P, Marjani, A, Moghadam, HM, Arnedo, CAM, Martinez, G, Martinez-Piedra, R, Martins-Melo, FR, Martorell, M, Marx, W, Marzo, RR, Masoudi, S, Mathangasinghe, Y, Mathioudakis, AG, Mathur, M, Mathur, N, Matozinhos, FP, Mattumpuram, J, Maude, RJ, Maugeri, A, Mayeli, M, Mazidi, M, Mazzotti, A, McGrath, JJ, Mckee, M, McKowen, ALW, McPhail, MA, McPhail, SM, Mehmood, A, Mehrabani-Zeinabad, K, Mehravar, S, Meto, TM, Melese, EB, Mendez-Lopez, MAM, Mendoza, W, Menezes, RG, Mensah, GA, Mensah, LG, Mentis, A-FA, Meo, SA, Meretoja, A, Meretoja, TJ, Mersha, AM, Mestrovic, T, Mettananda, KCD, Mettananda, S, Mhlanga, A, Mhlanga, L, Miazgowski, T, Michalek, IM, de Sa, ACMGN, Miller, TR, Minh, LHN, Mirahmadi, A, Mirijello, A, Mirrakhimov, EM, Mirzaei, R, Mitchell, PB, Mittal, C, Moberg, ME, Fard, AM, Mohajelin, S, Mohamadkhani, A, Mohamed, AI, Mohamed, J, Mohamed, MFH, Mohamed, NS, Mohammad, AM, Mohammadi, S, Mohammed, H, Mohammed, M, Mohammed, S, Mokdad, AH, Molokhia, M, Momani, SM, Momtazmanesh, S, Monasta, L, Mondello, S, Moni, MA, Montazeri, F, Ghalibaf, AM, Moradi, M, Moradi, Y, Moraga, P, Morawska, L, Moreira, RS, Morovatdar, N, Morrison, SD, Mosapour, A, Mosser, JF, Mossialos, E, Motappa, R, Mougin, V, Mousavi, P, Mrejen, M, Mubarik, S, Mueller, UO, Mulita, F, Munjal, K, Murillo-Zamora, E, Musallam, KM, Musina, A-M, Mustafa, G, Myung, W, Nafei, A, Nagarajan, AJ, Naghavi, P, Naik, GR, Naik, G, Nainu, F, Najdaghi, S, Ansari, NN, Nangia, V, Swamy, SN, Nargus, S, Davani, DN, Nascimento, BR, Nascimento, GG, Naser, AY, Nashwan, AJ, Natto, ZS, Nauman, J, Navaratna, SNK, Naveed, M, Nawsherwan, Nayak, BP, Nayak, VC, Negash, H, Negoi, I, Negoi, RI, Nejadghaderi, SA, Nejjari, C, Nematollahi, S, Netsere, HB, Ng, M, Nguefack-Tsague, G, Ngunjiri, JW, Nguyen, AH, Nguyen, DH, Nguyen, HTH, Nguyen, N, Nguyen, NNY, Nguyen, PT, Nguyen, QP, Nguyen, VT, Minh, DNT, Niazi, RK, Nigatu, YT, Niknam, M, Nikoobar, A, Nikpoor, AR, Nikravangolsefid, N, Noman, EA, Nomura, S, Noor, STA, Noroozi, N, Nouri, M, Nozari, M, Nri-Ezedi, CA, Ntaios, G, Nunemo, MH, Nurrika, D, Nutor, JJ, Nzoputam, CI, Nzoputam, OJ, Oancea, B, Obamiro, KO, Odetokun, IA, Oduro, MS, Ogundijo, OA, Ogunfowokan, AA, Ogunkoya, A, Oguntade, AS, Oh, I-H, Ojo-Akosile, TR, Okati-Aliabad, H, Okekunle, AP, Okonji, OC, Olagunju, AT, Olatubi, MI, Oliveira, GMM, Olusanya, BO, Olusanya, JO, Oluwafemi, YD, Omar, HA, Omer, GL, Ong, S, Onie, S, Onwujekwe, OE, Opejin, AO, Ordak, M, Orish, VN, Ortiz, A, Ortiz-Prado, E, Osman, WMS, Ostojic, SM, Ostroff, SM, Osuagwu, UL, Otoiu, A, Otstavnov, SS, Ouyahia, A, Owolabi, MO, Oyeyemi, OT, Ozair, A, Padukudru, MPA, Padron-Monedero, A, Padubidri, JR, Pal, PK, Palicz, T, Pan, F, Pan, H-F, Panda-Jonas, S, Pandey, A, Pando-Robles, V, Pangaribuan, HU, Panos, GD, Panos, LD, Pantazopoulos, I, Stoian, AMP, Parikh, RR, Park, E-K, Park, S, Parsons, N, Parthasarathi, A, Pasovic, M, Passera, R, Patel, J, Pathan, AR, Patil, S, Patoulias, D, Pawar, S, Toroudi, HP, Pease, SA, Peden, AE, Pedersini, P, Pensato, U, Pepito, VCF, Peprah, P, Pereira, M, Pereira, MO, Perianayagam, A, Perico, N, Perna, S, Pesudovs, K, Petermann-Rocha, FE, Pham, HT, Philip, AK, Phillips, MR, Pigeolet, M, Piradov, MA, Pisoni, E, Plotnikov, E, Poddighe, D, Polibin, RV, Poluru, R, Ponkilainen, VT, Popovic, DS, Postma, MJ, Pour-Rashidi, A, Prabhu, D, Prada, SI, Pradhan, J, Pradhan, PMS, Prashant, A, Prates, EJS, Priscilla, T, Purnobasuki, H, Purohit, BM, Puvvula, J, Qasim, NH, Qattea, I, Qazi, AS, Qian, G, Rad, MR, Radhakrishnan, V, Shahraki, HR, Rafferty, Q, Raggi, A, Raggi, C, Raheem, N, Rahim, F, Rahim, MJ, Rahimibarghani, S, Rahman, MMMR, Rahman, M, Rahman, MA, Rahman, T, Rahmani, AM, Rahmanian, M, Rahmanian, N, Rahmati, R, Rahmawaty, S, Raimondo, D, Raja, A, Rajput, P, Ramadan, M, Ramasamy, SK, Ramazanu, S, Ramteke, PW, Rana, K, Rana, RK, Ranabhat, CL, Rane, A, Rao, CR, Rao, M, Rasella, D, Rashedi, V, Rashid, AM, Rasouli-Saravani, A, Rastogi, P, Rasul, A, Rathish, D, Babu, GR, Rauniyar, SK, Ravangard, R, Rawaf, DL, Rawaf, S, Raza, RZ, Redwan, EMM, Reifels, L, Reitsma, MB, Remuzzi, G, Rengasamy, KRR, Reshmi, B, Resnikoff, S, Restaino, S, Reyes, LF, Rezaei, N, Rezaei, ZS, Rezaeian, M, Rhee, TG, Rickard, J, Robalik, T, Robinson-Oden, HE, Rocha, HAL, Rodrigues, M, Rodriguez, JAB, Roever, L, Romadlon, DS, Ronfani, L, Rony, MKK, Roshandel, G, Rotimi, K, Rout, HS, Roy, B, Rubagotti, E, Ruela, GDA, Rumisha, SF, Runghien, T, Russo, M, Saad, AMA, Saber, K, Saber-Ayad, MM, Sabet, CJ, Sabour, S, Sachdev, PS, Saddler, A, Sadee, BA, Sadeghi, M, Saeb, MR, Saeed, U, Safi, SZ, Sagar, R, Saghafi, A, Sagoe, D, Sahebkar, A, Sahoo, PM, Sajid, MR, Salam, N, Salamati, P, Salami, AA, Saleh, MA, Salehi, L, Salem, MR, Salemcity, AJ, Salimi, S, Kafil, HS, Samargandy, S, Samodra, YL, Samy, AM, Sanabria, J, Sanna, 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Abstract: BACKGROUND: Future trends in disease burden and drivers of health are of great interest to policy makers and the public at large. This information can be used for policy and long-term health investment, planning, and prioritisation. We have expanded and improved upon previous forecasts produced as part of the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) and provide a reference forecast (the most likely future), and alternative scenarios assessing disease burden trajectories if selected sets of risk factors were eliminated from current levels by 2050. METHODS: Using forecasts of major drivers of health such as the Socio-demographic Index (SDI; a composite measure of lag-distributed income per capita, mean years of education, and total fertility under 25 years of age) and the full set of risk factor exposures captured by GBD, we provide cause-specific forecasts of mortality, years of life lost (YLLs), years lived with disability (YLDs), and disability-adjusted life-years (DALYs) by age and sex from 2022 to 2050 for 204 countries and territories, 21 GBD regions, seven super-regions, and the world. All analyses were done at the cause-specific level so that only risk factors deemed causal by the GBD comparative risk assessment influenced future trajectories of mortality for each disease. Cause-specific mortality was modelled using mixed-effects models with SDI and time as the main covariates, and the combined impact of causal risk factors as an offset in the model. At the all-cause mortality level, we captured unexplained variation by modelling residuals with an autoregressive integrated moving average model with drift attenuation. These all-cause forecasts constrained the cause-specific forecasts at successively deeper levels of the GBD cause hierarchy using cascading mortality models, thus ensuring a robust estimate of cause-specific mortality. For non-fatal measures (eg, low back pain), incidence and prevalence were forecasted from mixed-effects m
Published: 2024

12. Global age-sex-specific mortality, life expectancy, and population estimates in 204 countries and territories and 811 subnational locations, 1950–2021, and the impact of the COVID-19 pandemic: a comprehensive demographic analysis for the Global Burden of Disease Study 2021

Author: Schumacher, A, Kyu, H, Aali, A, Abbafati, C, Abbas, J, Abbasgholizadeh, R, Abbasi, M, Abbasian, M, Abd ElHafeez, S, Abdelmasseh, M, Abd-Elsalam, S, Abdelwahab, A, Abdollahi, M, Abdoun, M, Abdullahi, A, Abdurehman, A, Abebe, M, Abedi, A, Abegaz, T, Abeldaño Zuñiga, R, Abhilash, E, Abiodun, O, Aboagye, R, Abolhassani, H, Abouzid, M, Abreu, L, Abrha, W, Abrigo, M, Abtahi, D, Abu Rumeileh, S, Abu-Rmeileh, N, Aburuz, S, Abu-Zaid, A, Acuna, J, Adair, T, Addo, I, Adebayo, O, Adegboye, O, Adekanmbi, V, Aden, B, Adepoju, A, Adetunji, C, Adeyeoluwa, T, Adeyomoye, O, Adha, R, Adibi, A, Adikusuma, W, Adnani, Q, Adra, S, Afework, A, Afolabi, A, Afraz, A, Afyouni, S, Afzal, S, Agasthi, P, Aghamiri, S, Agodi, A, Agyemang-Duah, W, Ahinkorah, B, Ahmad, A, Ahmad, D, Ahmad, F, Ahmad, M, Ahmad, T, Ahmadi, K, Ahmadzade, A, Ahmadzade, M, Ahmed, A, Ahmed, H, Ahmed, L, Ahmed, M, Ahmed, S, Ajami, M, Aji, B, Ajumobi, O, Akalu, G, Akara, E, Akinosoglou, K, Akkala, S, Akyirem, S, Al Hamad, H, Al Hasan, 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Published: 2024

13. Burden of disease scenarios for 204 countries and territories, 2022–2050: a forecasting analysis for the Global Burden of Disease Study 2021

Author: Vollset, S, Ababneh, H, Abate, Y, Abbafati, C, Abbasgholizadeh, R, Abbasian, M, Abbastabar, H, Abd Al Magied, A, Abd ElHafeez, S, Abdelkader, A, Abdelmasseh, M, Abd-Elsalam, S, Abdi, P, Abdollahi, M, Abdoun, M, Abdullahi, A, Abebe, M, Abiodun, O, Aboagye, R, Abolhassani, H, Abouzid, M, Aboye, G, Abreu, L, Absalan, A, Abualruz, H, Abubakar, B, Abukhadijah, H, Addolorato, G, Adekanmbi, V, Adetunji, C, Adetunji, J, Adeyeoluwa, T, Adha, R, Adhikary, R, Adnani, Q, Adzigbli, L, Afrashteh, F, Afzal, M, Afzal, S, Agbozo, F, Agodi, A, Agrawal, A, Agyemang-Duah, W, Ahinkorah, B, Ahlstrom, A, Ahmad, A, Ahmad, F, Ahmad, M, Ahmad, S, Ahmed, A, Ahmed, H, Ahmed, S, Akinosoglou, K, Akkaif, M, Akrami, A, Akter, E, Al Awaidy, S, Al Hasan, S, Al Mosa, A, Al Ta'ani, O, Al Zaabi, O, Alahdab, F, Alajlani, M, Al-Ajlouni, Y, Alalalmeh, S, Al-Aly, Z, Alam, K, Alam, N, Alam, T, Alam, Z, Al-amer, R, Alanezi, F, Alanzi, T, Albakri, A, Aldhaleei, W, Aldridge, R, Alemohammad, S, Alemu, Y, Al-Gheethi, A, Al-Hanawi, M, Ali, A, Ali, I, Ali, M, Ali, R, Ali, S, Ali, V, Ali, W, Al-Ibraheem, A, Alicandro, G, Alif, S, Aljunid, S, Alla, F, Almazan, J, Al-Mekhlafi, H, Alqutaibi, A, Alrawashdeh, A, Alrousan, S, Al-Sabah, S, Alsabri, M, Altaany, Z, Al-Tammemi, A, Al-Tawfiq, J, Altirkawi, K, Aluh, D, Alvis-Guzman, N, Al-Wardat, M, Al-Worafi, Y, Aly, H, Alyahya, M, Alzoubi, K, Al-Zyoud, W, Amani, R, Ameyaw, E, Amin, T, Amindarolzarbi, A, Amiri, S, Amirzade-Iranaq, M, Amu, H, Amugsi, D, Ancuceanu, R, Anderlini, D, Anderson, D, Andrade, P, Andrei, C, Andrei, T, Andrews, E, Anil, A, Anil, S, Anoushiravani, A, Antony, C, Antriyandarti, E, Anuoluwa, B, Anvari, S, Anyasodor, A, Appiah, F, Aquilano, M, Arab, J, Arabloo, J, Arafa, E, Arafat, M, Aravkin, A, Ardekani, A, Areda, D, Aregawi, B, Aremu, A, Ariffin, H, Arkew, M, Armani, K, Artamonov, A, Arumugam, A, Asghari-Jafarabadi, M, Ashbaugh, C, Astell-Burt, T, Athari, S, Atorkey, P, Atout, M, Aujayeb, A, Ausloos, M, Awad, H, Awotidebe, A, Ayatollahi, H, 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Yonemoto, Naohiro, You, Yuyi, Younis, Mustafa Z, Yu, Chuanhua, Yu, Elaine A, Yu, Yong, Yuan, Chun-Wei, Yusuf, Hadiza, Zafar, Uzma, Zafari, Nima, Zahid, Mondal Hasan, Zakham, Fathiah, Zaki, Nazar, Zerfu, Taddese Alemu, Zhang, Haijun, Zhang, Jingya, Zhang, Liqun, Zhang, Yunquan, Zhang, Zhiqiang, Zhao, Xiu-Ju George, Zhao, Yang, Zhao, Zhongyi, Zhong, Chenwen, Zhou, Bolun, Zhou, Juexiao, Zhou, Shangcheng, Zhu, Bin, Zhumagaliuly, Abzal, Zielińska, Magdalena, Zoghi, Ghazal, Zumla, Alimuddin, Zyoud, Sa'ed H, Zyoud, Samer H, Smith, Amanda E, and Murray, Christopher J L
Published: 2024

14. Global burden and strength of evidence for 88 risk factors in 204 countries and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

Author: Brauer, M, Roth, G, Aravkin, A, Zheng, P, Abate, K, Abate, Y, Abbafati, C, Abbasgholizadeh, R, Abbasi, M, Abbasian, M, Abbasifard, M, Abbasi-Kangevari, M, Abd ElHafeez, S, Abd-Elsalam, S, Abdi, P, Abdollahi, M, Abdoun, M, Abdulah, D, Abdullahi, A, Abebe, M, Abedi, A, Abegaz, T, Abeldaño Zuñiga, R, Abiodun, O, Abiso, T, Aboagye, R, Abolhassani, H, Abouzid, M, Aboye, G, Abreu, L, Abualruz, H, Abubakar, B, Abu-Gharbieh, E, Abukhadijah, H, Aburuz, S, Abu-Zaid, A, Adane, M, Addo, I, Addolorato, G, Adedoyin, R, Adekanmbi, V, Aden, B, Adetunji, J, Adeyeoluwa, T, Adha, R, Adibi, A, Adnani, Q, Adzigbli, L, Afolabi, A, Afolabi, R, Afshin, A, Afyouni, S, Afzal, M, Afzal, S, Agampodi, S, Agbozo, F, Aghamiri, S, Agodi, A, Agrawal, A, Agyemang-Duah, W, Ahinkorah, B, Ahmad, A, Ahmad, D, Ahmad, F, Ahmad, N, Ahmad, S, Ahmad, T, Ahmed, A, Ahmed, L, Ahmed, M, Ahmed, S, Ajami, M, Akalu, G, Akara, E, Akbarialiabad, H, Akhlaghi, S, Akinosoglou, K, Akinyemiju, T, Akkaif, M, Akkala, S, 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Subah Abderehim, Yezli, Saber, Yi, Siyan, Yiğit, Arzu, Yigzaw, Zeamanuel Anteneh, Yin, Dehui, Yip, Paul, Yismaw, Malede Berihun, Yon, Dong Keon, Yonemoto, Naohiro, You, Yuyi, Younis, Mustafa Z, Yousefi, Zabihollah, Yu, Chuanhua, Yu, Yong, Zadey, Siddhesh, Zadnik, Vesna, Zakham, Fathiah, Zaki, Nazar, Zakzuk, Josefina, Zamagni, Giulia, Zaman, Sojib Bin, Zandieh, Ghazal G Z, Zanghì, Aurora, Zar, Heather J, Zare, Iman, Zarimeidani, Fatemeh, Zastrozhin, Mikhail Sergeevich, Zeng, Youjie, Zhai, Chunxia, Zhang, Anthony Lin, Zhang, Haijun, Zhang, Liqun, Zhang, Meixin, Zhang, Yunquan, Zhang, Zhenyu, Zhang, Zhi-Jiang, Zhao, Hanqing, Zhao, Jeff T, Zhao, Xiu-Ju George, Zhao, Yang, Zhao, Yong, Zhong, Chenwen, Zhou, Jingjing, Zhou, Juexiao, Zhou, Shangcheng, Zhu, Bin, Zhu, Lei, Zhu, Zhaohua, Ziaeian, Boback, Ziafati, Makan, Zielińska, Magdalena, Zimsen, Stephanie R M, Zoghi, Ghazal, Zoller, Thomas, Zumla, Alimuddin, Zyoud, Sa'ed H, Zyoud, Samer H, Murray, Christopher J L, and Gakidou, Emmanuela
Abstract: Background: Understanding the health consequences associated with exposure to risk factors is necessary to inform public health policy and practice. To systematically quantify the contributions of risk factor exposures to specific health outcomes, the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 aims to provide comprehensive estimates of exposure levels, relative health risks, and attributable burden of disease for 88 risk factors in 204 countries and territories and 811 subnational locations, from 1990 to 2021. Methods: The GBD 2021 risk factor analysis used data from 54 561 total distinct sources to produce epidemiological estimates for 88 risk factors and their associated health outcomes for a total of 631 risk–outcome pairs. Pairs were included on the basis of data-driven determination of a risk–outcome association. Age-sex-location-year-specific estimates were generated at global, regional, and national levels. Our approach followed the comparative risk assessment framework predicated on a causal web of hierarchically organised, potentially combinative, modifiable risks. Relative risks (RRs) of a given outcome occurring as a function of risk factor exposure were estimated separately for each risk–outcome pair, and summary exposure values (SEVs), representing risk-weighted exposure prevalence, and theoretical minimum risk exposure levels (TMRELs) were estimated for each risk factor. These estimates were used to calculate the population attributable fraction (PAF; ie, the proportional change in health risk that would occur if exposure to a risk factor were reduced to the TMREL). The product of PAFs and disease burden associated with a given outcome, measured in disability-adjusted life-years (DALYs), yielded measures of attributable burden (ie, the proportion of total disease burden attributable to a particular risk factor or combination of risk factors). Adjustments for mediation were applied to account for relationships involving risk
Published: 2024

15. Phase-Transformation Nanoparticle-Mediated Sonodynamic Therapy: An Effective Modality to Enhance Anti-Tumor Immune Response by Inducing Immunogenic Cell Death in Breast Cancer

Author: Si Y, Yue J, Liu Z, Li M, Du F, Wang X, Dai Z, Hu N, Ju J, Gao S, and Yuan P
Subjects: breast cancer, immune response, phase-transformation nanoparticles, immunogenic cell death, dc maturation, Medicine (General), R5-920
Abstract: Yiran Si,1 Jian Yue,2 Zhaoyang Liu,3 Mo Li,3 Feng Du,4 Xue Wang,2 Zhong Dai,5 Nanlin Hu,1 Jie Ju,1 Songlin Gao,1 Xiaobing Wang,3 Peng Yuan2 1Department of Medical Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, People’s Republic of China; 2Department of VIP Medical Services, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, People’s Republic of China; 3State Key Laboratory of Molecular Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, People’s Republic of China; 4China Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), The VIPII Gastrointestinal Cancer Division of Medical Department, Peking University Cancer Hospital and Institute, Beijing, 100142, People’s Republic of China; 5Department of Medical Oncology, Cancer Hospital of Huanxing Chaoyang District, Beijing, 100005, People’s Republic of ChinaCorrespondence: Peng YuanDepartment of VIP Medical Services, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, #17 Pan Jia Yuan Nan Li, Chao Yang District, Beijing, 100021, People’s Republic of ChinaTel +86 10-87787245Email yuanpeng01@hotmail.comXiaobing WangState Key Laboratory of Molecular Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, #17 Pan Jia Yuan Nan Li, Chao Yang District, Beijing, 100021, People’s Republic of ChinaTel +86 10-87788430Email wangxb@cicams.ac.cnPurpose: Immunologically quiescent of breast cancer cells has been recognized as the key impediment for the breast cancer immunotherapy. In this study, we aimed to investigate the role of nanoparticle-mediated sonodynamic therapy (SDT) in promoting anti-tumor immune of breast cancer cells and its potential immune mechanisms.Materials and Methods: The phase-transformation nanoparticles (LIP-PFH nanoparticles) were in-house prepared and its physiochemical characters were detected. The CCK-8 assay, apoptosis analysis and Balb/c tumor model establishment were used to explore the anti-tumor effect of LIP-PFH nanoparticles triggered by low-intensity focused ultrasound (LIFU) both in vitro and in vivo. Flow cytometry and immunohistochemistry of CD4+T, CD8+T, CD8+PD-1+T in blood, spleen and tumor tissue were performed to represent the change of immune response. Detection of immunogenic cell death (ICD) markers was examined to study the potential mechanisms.Results: LIP-PFH nanoparticles triggered by LIFU could inhibit the proliferation and promote the apoptosis of 4T1 cells both in vitro and in vivo. CD4+T and CD8+T cell subsets were significantly increased in blood, spleen and tumor tissue, meanwhile CD8+PD-1+T cells were reduced, indicating enhancement of anti-tumor immune response of breast cancer cells in the nanoparticle-mediated SDT group. Detection of ICD markers (ATP, high-mobility group box B1, and calreticulin) and flow cytometric analysis of dendritic cell (DC) maturity further showed that the nanoparticle-mediated SDT can promote DC maturation to increase the proportion of cytotoxic T cells by inducing ICD of breast cancer cells.Conclusion: The therapy of nanoparticles-mediated SDT can effectively enhance anti-tumor immune response of breast cancer.Keywords: breast cancer, immune response, phase-transformation nanoparticles, immunogenic cell death, DC maturation
Published: 2021

16. A Case of Invasive Pulmonary Mycosis (Rhizopus microspores) secondary to Hematological Disease.

Author: Yao, Xue X., Ling Zhang, Sun, Si Y., Fu, Ai S., Liu, Tie J., Tong Chen, and Ge, Yan L.
Subjects: BLOOD diseases, RHIZOPUS, MYCOSES, MUCORMYCOSIS, HEMATOLOGIC malignancies, PULMONARY aspergillosis, BRONCHOALVEOLAR lavage
Abstract: Background: Pulmonary mucormycosis is most common in patients with hematologic malignancies and transplant recipients. This article describes a case of mucormycosis in the lungs secondary to a hematologic disorder with suspected lung cancer. Methods: Rhizopus (Rhizopus microspores) was detected by blood NGS and bronchoalveolar lavage fluid NGS, and pulmonary mucormycosis was confirmed. Results: Secondary to hematologic disease, pulmonary pneumonia, mycosis, and symptoms improved after comprehensive treatment. Conclusions: Clinical data and radiologic knowledge are combined to diagnose invasive pulmonary mycoses; early empirical medicine is very important. [ABSTRACT FROM AUTHOR]
Published: 2024
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17. Respiratory Syncytial Virus Infection in an Adult with Immunodeficiency.

Author: Sun, Si Y., Yao, Xue X., Ling Zhang, Fu, Ai S., and Ge, Yan L.
Subjects: RESPIRATORY infections, RESPIRATORY syncytial virus infections, PARAINFLUENZA viruses, ADULTS, RESPIRATORY syncytial virus, LUNG diseases, OLDER patients
Abstract: Background: Respiratory syncytial virus (RSV) is a single-stranded RNA virus that commonly causes symptoms of upper respiratory tract infections in humans, with a clear seasonal trend. However, in immunocompromised and elderly patients, RSV infections still result in high rates of hospitalization and even risk of death. Methods: We report a case of RSV infection in an adult with immunodeficiency, which initially showed only mild symptoms of upper respiratory tract infection, which did not improve after receiving empirical anti-infective treatment, and the foci of infection in the lungs continued to expand, which led to the aggravation of the disease. The diagnosis of RSV infection was finally confirmed by electron bronchoscopy and pathogenetic examination of the bronchoalveolar lavage fluid. The patient was given intravenous ribavirin treatment for one week. After one week of intravenous ribavirin treatment, the patient's symptoms improved significantly. A repeat chest CT suggested that the lung lesions were smaller than before. In order to improve clinicians' awareness of this disease, we jointly conducted a literature analysis. Results: The final diagnosis of RSV was made by analyzing the patient's history, symptoms, and signs and performing relevant examinations. Conclusions: For patients with poor results of empirical application of antibiotics, electronic bronchoscopy and pathogenetic examination should be carried out at an early stage to clarify the nature of the lesions and to avoid rapid deterioration of the condition leading to life-threatening conditions in the patients. More consideration should be given to the possibility of disease diagnosis to avoid misdiagnosis and underdiagnosis, and appropriate treatment should be given at an early stage. [ABSTRACT FROM AUTHOR]
Published: 2024
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18. A Case of IgG4 Related Lung Disease.

Author: Sun, Si Y., Yao, Xue X., Ling Zhang, Fu, Ai S., and Ge, Yan L.
Subjects: LUNG diseases, LUNGS, SYMPTOMS, DIAGNOSIS, LUNG infections, BRONCHOALVEOLAR lavage
Abstract: Background: IgG4-related disease (IgG4-RD) is an immune-mediated systemic inflammatory fibrotic disease, which is a relatively rare and novel disease that can involve multiple organs or tissues, with variable clinical manifestations, and for which pulmonary involvement has been reported relatively infrequently. Methods: Here we report a case of pulmonary infection that was initially suspected and received anti-inflammatory treatment, but the symptoms did not improve. CT examination indicated progression of the pulmonary lesion, and the nature of the lesion could not be determined by tracheoscopy and bronchoalveolar lavage. The diagnosis of IgG4 related lung disease (IgG4-RLD) was confirmed by percutaneous lung biopsy. A joint literature analysis was conducted to improve clinicians' understanding of this disease. Results: The patient's history, symptoms, signs and relevant examination results were analyzed. The final diagnosis was IgG4-RLD. Conclusions: When the clinical symptoms and imaging manifestations of the patients are consistent with IgG4-RLD, pathological examination can be appropriately performed to clarify the nature of the lesions. More consideration should be given to the possibility of disease diagnosis to avoid misdiagnosis and underdiagnosis, and proper treatment should be given at an early stage. [ABSTRACT FROM AUTHOR]
Published: 2024
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19. A Case of Invasive Pulmonary Aspergillosis.

Author: Sun, Si Y., Ling Zhang, Yao, Xue X., Fu, Ai S., and Ge, Yan L.
Subjects: PULMONARY aspergillosis, ASPERGILLOSIS, COMPUTED tomography, LUNG diseases, DIAGNOSIS, MYCOSES, COMMUNITY-acquired pneumonia
Abstract: Background: Invasive pulmonary aspergillosis (IPA) is a deep fungal infection caused by invasion of Aspergillus mycelium into the lung parenchyma resulting in tissue destruction and necrosis, which occurs more often in immunosuppressed populations. The severity of the disease and the rapid progression of the lung lesions puts patients at high risk of death and poor prognosis if the correct therapeutic intervention is not given as early as possible. Methods: Here we report a case of IPA, which was initially diagnosed as community-acquired pneumonia in a local hospital. The symptoms did not improve after receiving anti-infective treatment. The patient was diagnosed with IPA after completing a chest CT examination and an electronic bronchoscopy, as well as pathogenetic examination of the bronchoalveolar lavage fluid and pathological examination of the left bronchial mass in the respiratory department of our hospital, which was finally diagnosed as IPA. After one week of administration of voriconazole for anti-fungal infection treatment, the patient's symptoms improved significantly, and a repeat chest CT suggested that the lung lesions were better than before. In order to raise clinicians' awareness of this disease, we also conducted a literature analysis. Results: The final diagnosis of IPA was made by analyzing the patient's history, symptoms, signs, and relevant findings. Conclusions: When the patient's clinical symptoms and imaging manifestations are consistent with IPA, electronic bronchoscopy and pathogenetic and pathological examinations may be appropriately performed to clarify the nature of the lesion. More consideration should be given to the possibility of disease diagnosis to avoid misdiagnosis and underdiagnosis. Appropriate treatment should be given at an early stage. [ABSTRACT FROM AUTHOR]
Published: 2024
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20. Potential difference methods for measuring crack growth: A review

Author: Si, Y., Rouse, J.P., and Hyde, C.J.
Published: 2020
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21. Effects of Chinese Herbal Medicine on Acute Exacerbations of COPD: A Randomized, Placebo-Controlled Study

Author: Li J, Zhang H, Ruan H, Si Y, Sun Z, Liu H, Feng J, Wang Y, Li L, Bai L, and Sun H
Subjects: acute exacerbations, chronic obstructive pulmonary disease, randomized controlled trial, chinese herbal medicine, Diseases of the respiratory system, RC705-779
Abstract: Jiansheng Li,1,2,* Hailong Zhang,1,3,* Huanrong Ruan,3 Yimei Si,3 Zikai Sun,4 Hong Liu,5 Jihong Feng,6 Yanqing Wang,7 Lihua Li,8 Li Bai,9 Hui Sun10 1Co-Construction Collaborative Innovation Center for Chinese Medicine and Respiratory Diseases by Henan & Education Ministry of P.R. China, Henan University of Chinese Medicine, Zhengzhou, People’s Republic of China; 2Henan Key Laboratory of Chinese Medicine for Respiratory Disease, Henan University of Chinese Medicine, Zhengzhou, People’s Republic of China; 3The First Affiliated Hospital of Henan University of Chinese Medicine, Zhengzhou, People’s Republic of China; 4Jiangsu Province Hospital of Traditional Chinese Medicine, Nanjing, People’s Republic of China; 5The First Affiliated Hospital of Zhengzhou University, Zhengzhou, People’s Republic of China; 6The Second Affiliated Hospital of Tianjin University of Traditional Chinese Medicine, Tianjin, People’s Republic of China; 7Haici Hospital of Qingdao, Qingdao, People’s Republic of China; 8Zhengzhou People’s Hospital, Zhengzhou, People’s Republic of China; 9Shanxi Hospital of Integrated Traditional and Western Medicine, Taiyuan, People’s Republic of China; 10Nanyang City Center Hospital, Nanyang, People’s Republic of China*These authors contributed equally to this workCorrespondence: Jiansheng Li No. 156 Jinshui East Road, Zhengdong New District, Zhengzhou, Henan 450046, People’s Republic of ChinaTel +86 371 65676568Fax +86 371 65944307Email li_js8@163.comPurpose: Acute exacerbation of chronic obstructive pulmonary disease (AECOPD) is an essential occurrence in COPD management and is the leading cause of morbidity and mortality. Chinese herbal medicine is widely used in the treatment of AECOPD, but high quality randomized controlled trials are limited. This study aimed to evaluate the efficacy and safety of Chinese herbal medicine as adjuvant therapy for patients with AECOPD.Methods: This was a randomized, double-blind, placebo-controlled study of 378 participants from eight centers in China. Participants were randomly assigned to receive 10 g of Chinese herbal medicine (according to the type of Traditional Chinese medicine syndrome: Sanhanhuayin, Qingrehuatan, or Zaoshihuatan granules) or placebo, two times per day, for 14 days, in addition to conventional medicine. Participants were followed up for 84 days after the treatment. The primary end point was the COPD assessment test (CAT) score. Secondary end points included the Modified British Medical Research Council (mMRC) questionnaire and the COPD patient-reported outcome scale (COPD-PRO). We also assessed treatment failure and treatment success rate, length of hospitalization, number of patients with acute exacerbations, number of patients readmitted due to AECOPD, and number of deaths and intubation.Results: The between-group difference in the change from baseline for CAT on day 14 (end of treatment) was − 2.11 (95% confidence interval [CI], − 3.198 to − 1.050; P< 0.001), exceeding the minimal clinically important difference. The mMRC and COPD-PRO scores were lower in the intervention group compared to the control group (between-group difference in the change from baseline, − 0.28; 95% CI, − 0.48 to − 0.08; P=0.007 and − 2.51; 95% CI, − 4.087 to − 0.929; P=0.002, respectively) on day 14. The intervention group had a significantly shorter duration of hospital stay than the control group (mean difference, − 1.21days; 95% CI, − 2.041 to − 0.419; P=0.003), significantly lower of number of exacerbations (risk ratio [RR], 0.60; 95% CI, 0.409 to 0.892; P=0.010), and significantly lower number of readmissions due to AECOPD (RR, 0.41; 95% CI, 0.193 to 0.865; P=0.015). Significant differences in the number of treatment failures or successes, deaths, and intubation were not observed. The difference in safety variables and adverse events between the two groups was not observed.Conclusion: Chinese herbal medicine appears to be safe and beneficial for AECOPD and can be considered a complementary treatment for patients with AECOPD.Keywords: acute exacerbations, chronic obstructive pulmonary disease, randomized controlled trial, Chinese herbal medicine
Published: 2020

22. Dexmedetomidine attenuation of renal ischaemia-reperfusion injury requires sirtuin 3 activation

Author: Si, Y., Bao, H., Han, L., Chen, L., Zeng, L., Jing, L., Xing, Y., and Geng, Y.
Published: 2018
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23. A Case of Organizing Pneumonia Resembling Lung Cancer.

Author: Yao, Xue X., Sun, Si Y., Ling Zhang, Ren, Hong Q., Fu, Ai S., and Ge, Yan L.
Subjects: ORGANIZING pneumonia, LUNG cancer, DELAYED diagnosis, SYMPTOMS, JOINT infections, MEDICATION reconciliation
Abstract: Background: Organizing pneumonia (OP) is a pathologic diagnosis with clinical and imaging manifestations that often resemble other diseases, such as infections and cancers, which can lead to delays in diagnosis and inappropriate management of the underlying disease. In this article, we present a case of organized pneumonia that resembles lung cancer. Methods: We report a case of initial suspicion of pulmonary malignancy, treated with anti-inflammatory medication and then reviewed with CT suggesting no improvement, and finally confirmed to be OP by pathological biopsy taken via transbronchoscopy. A joint literature analysis was performed to raise clinicians' awareness of the diagnosis and treatment of OP. Results: Initially, because of the atypical auxiliary findings, we thought that the disease turned out to be a lung tumor, which was eventually confirmed as OP by pathological diagnosis. Conclusions: The diagnosis and treatment of OP requires a combination of clinical information and radiological expertise, as well as biopsy to obtain histopathological evidence. That is, clinical-imaging-pathological tripartite cooperation and comprehensive analysis. [ABSTRACT FROM AUTHOR]
Published: 2024
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24. A Prediction Model for Prolonged Hospital Length of Stay (ProLOS) in Coronavirus Disease 2019 (COVID-19) Patients.

Author: Ling Zhang, Mi, Guo C., Yao, Xue X., Sun, Si Y., Fu, Ai S., and Ge, Yan L.
Subjects: SARS-CoV-2, COVID-19, LENGTH of stay in hospitals, RESPIRATORY diseases, LEUKOCYTE count
Abstract: Background: Coronavirus disease 2019 (COVID-19) is an acute respiratory infectious disease caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). With the normalization of COVID-19 globally, it is crucial to construct a prediction model that enables clinicians to identify patients at risk for ProLOS based on demographics and serum inflammatory biomarkers. Methods: The study included hospitalized patients with a confirmed diagnosis of COVID-19. These patients were randomly grouped into a training (80%) and a test (20%) cohort. The LASSO regression and ten-fold crossvalidation method were applied to filter variables. The training cohort utilized multifactorial logistic regression analyses to identify the independent factors of ProLOS in COVID-19 patients. A 4-variable nomogram was created for clinical use. ROC curves were plotted, and the area under the curve (AUC) was calculated to evaluate the model's discrimination; calibration analysis was planned to assess the validity of the nomogram, and decision curve analysis (DCA) was used to evaluate the clinical usefulness of the model. Results: The results showed that among 310 patients with COVID-19, 80 had extended hospitalization (80/310). Four independent risk factors for COVID-19 patients were identified: age, coexisting chronic respiratory diseases, white blood cell count (WBC), and serum albumin (ALB). A nomogram based on these variables was created. The AUC in the training cohort was 0.808 (95% CI: 0.75 - 0.8671), and the AUC in the test cohort was 0.815 (95% CI: 0.7031 - 0.9282). The model demonstrates good calibration and can be used with threshold probabilities ranging from 0% to 100% to obtain clinical net benefits. Conclusions: A predictive model has been created to accurately predict whether the hospitalization duration of COVID-19 patients will be prolonged. This model incorporates serum WBC, ALB levels, age, and the presence of chronic respiratory system diseases. [ABSTRACT FROM AUTHOR]
Published: 2024
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25. A Case of Tuberculosis Misdiagnosed as Sarcoidosis and then Confirmed by NGS Testing.

Author: Wen Yang, Jiao Jiang, Qian Zhao, Hong Q. Ren, Xue X. Yao, Si Y. Sun, Ling Zhang, Fu, Ai S., and Ge, Yan L.
Subjects: MEDICAL personnel, TUBERCULOSIS, SYMPTOMS, MYCOBACTERIUM tuberculosis, SARCOIDOSIS, WAKEFULNESS
Abstract: Background: Pulmonary tuberculosis (PTB) is an important infectious disease that threatens the health and life of human beings. In the diagnosis of PTB, imaging plays a dominant role, but due to the increasing drug resistance of Mycobacterium tuberculosis, atypical clinical manifestations, "different images with the same disease" or "different diseases with the same image" in chest imaging, and the low positivity rate of routine sputum bacteriology, which leads to a high rate of misdiagnosis of PTB. We report a case of pulmonary tuberculosis that was misdiagnosed on imaging. We report a case of pulmonary tuberculosis that resembled sarcoidosis on imaging and was negative for antacid staining on sputum smear and alveolar lavage fluid, and was later diagnosed by microbial next-generation sequencing (NGS). The case was initially misdiagnosed as sarcoidosis. Methods: Alveolar lavage fluid NGS, chest CT, bronchoscopy. Results: Chest CT showed multiple inflammatory lesions in both lungs, multiple nodular foci in both lungs, and multiple enlarged lymph nodes in the mediastinum and hilar region on both sides. Fiberoptic bronchoscopy was performed in the basal segment of the left lower lobe of the lungs to carry out bronchoalveolar lavage, and the lavage fluid was sent to the NGS test and returned the following results: Mycobacterium tuberculosis complex group detected in the number of sequences of 293. Based on the results of the NGS test, the diagnosis of pulmonary tuberculosis could be confirmed. Conclusions: The diagnosis of pulmonary tuberculosis cannot be easily excluded in patients with "different images with the same disease" or "different diseases with the same image" on chest imaging without the support of sputum positivity. The goal was to improve the alertness of medical personnel to the misdiagnosis of tuberculosis and the application of NGS technology. [ABSTRACT FROM AUTHOR]
Published: 2024
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26. Deficient <scp>chaperone‐mediated</scp> autophagy in macrophage aggravates inflammation of nonalcoholic steatohepatitis by targeting Nup85

Author: Miao Zhang, Si Y Tian, Shuo Y Ma, Xia Zhou, Xiao H Zheng, Bo Li, Guan Y Guo, Jia H Yu, Rui Su, Fang F Yang, Yi N Hu, Gang Ma, Hui Yang, Lin H Zheng, Chang C Guo, Yu L Shang, Jing B Wang, and Ying Han
Subjects: Hepatology
Published: 2023

27. A mixed characteristic boundary condition for simulating viscous incompressible fluid flows around a hydrofoil

Author: Zhang, D. H., Shi, Y. X., Huang, C., Si, Y. L., and Li, W.
Published: 2019
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28. On Optimal Progressive Censoring Schemes for Normal Distribution

Author: Salemi, U. H., Rezaei, S., Si, Y., and Nadarajah, S.
Published: 2018
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29. Inferior vena cava filter migration due to guidewire ensnarement during peripherally inserted central catheterisation

Author: Chew, Si Y, Lim, Huey Y, Ong, Heng A, Sannasi, Vikram Vijayan, Wee, Bernard, Tan, Chee K, and Kansal, Amit
Published: 2021

30. The variability of co-activation pattern of antagonist muscles in human infant crawling.

Author: Qi L. Xiong, Xiao Y. Wu, Nong Xiao, Si Y. Zeng, Xiao L. Zheng, Di Wu, and Wen S. Hou
Published: 2016
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31. CEA Negative Initial Diagnosis of HP Infection Finally Confirmed by Bronchoscopic Biopsy as Lung Adenocarcinoma.

Author: Qian Zhao, Ren, Hong Q., Jiao Jiang, Wen Yang, Yao, Xue X., Ling Zhang, Sun, Si Y., and Ge, Yan L.
Subjects: LUNGS, RESPIRATORY organs, HYPERSENSITIVITY pneumonitis, INTERSTITIAL lung diseases, CARCINOEMBRYONIC antigen, COMPUTED tomography
Abstract: Background: Carcinoembryonic antigen (CEA) is a polysaccharide complex that is found in the human respiratory system. It is of significant use in disease surveillance of lung cancer; however, serum CEA can occasionally only offer little assistance. We present a case of recurring infection initially diagnosed as carcinoembryonic antigennegative in a patient with a history of hypersensitivity pneumonitis infection, which finally led to the diagnosis of lung adenocarcinoma following percutaneous lung puncture. Methods: Appropriate laboratory tests, chest CT, bronchoscopy, percutaneous lung puncture, and pathologic examination were performed to explore the cause of the disease. Results: Because CEA was negative and a chest CT showed interstitial changes in both lungs with numerous hyperdense shadows, coupled with the patient's history of hypersensitivity pneumonitis, we initially believed that the infection was relapsing. However, a percutaneous lung puncture eventually revealed that the patient had lung adenocarcinoma. Conclusions: Vigilance needs to be increased in clinical work for patients with interstitial lung disease, low tumor markers such as CEA, and imaging suggestive of inflammatory progression, which in fact turns into lung cancer. When the treatment is ineffective after standardized application of hormone and anti-infection, lung tissue should be obtained for pathological examination in time to obtain pathological evidence. [ABSTRACT FROM AUTHOR]
Published: 2024
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32. Accidental Detection of Tuberculous Empyema at Health Check-Up.

Author: Hong Q. Ren, Qian Zhao, Jiao Jiang, Wen Yang, Sun, Si Y., Ling Zhang, Yao, Xue X., and Ge, Yan L.
Subjects: TUBERCULOSIS, EMPYEMA, ADENOSINE deaminase, MYCOBACTERIAL diseases, MYCOBACTERIUM tuberculosis
Abstract: Background: Patients with tuberculous empyema (TE) can have a serious impact on lung function as their disease progresses, and, if left untreated, can cause damage to other parts of the body such as the thorax and spine, causing pain and inconvenience to the patient. Early diagnosis and the search for appropriate treatment are key to improving the survival rate of the disease. Methods: We report a case of a young patient with an unexpected finding of right pleural effusion on physical examination, who was eventually diagnosed with TE using next-generation sequencing of pleural tissue. We analyzed the literature to improve clinicians' understanding of TE and how to properly diagnose and treat the disease. Results: Laboratory results of the pleural effusion suggested a possible Mycobacterium tuberculosis infection, but pathogen-related tests were negative, and the diagnosis was eventually successfully confirmed by thoracoscopic pleural biopsy. Conclusions: The diagnosis of TE should be considered in young patients with pleural thickening of the empyema. Adenosine deaminase may provide diagnostic direction in patients with unexplained thorax abscess. Pleural biopsy, although an invasive procedure, is an essential diagnostic tool in some cases. [ABSTRACT FROM AUTHOR]
Published: 2024
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33. Antagonist muscle co-activation of limbs in human infant crawling: A pilot study.

Author: Qi L. Xiong, Xiao Y. Wu, Nong Xiao, Si Y. Zeng, Xiao P. Wan, Xiao L. Zheng, and Wen S. Hou
Published: 2015
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34. Back Cover

Author: Zhang, Miao, primary, Tian, Si Y, additional, Ma, Shuo Y, additional, Zhou, Xia, additional, Zheng, Xiao H, additional, Li, Bo, additional, Guo, Guan Y, additional, Yu, Jia H, additional, Su, Rui, additional, Yang, Fang F, additional, Hu, Yi N, additional, Ma, Gang, additional, Yang, Hui, additional, Zheng, Lin H, additional, Guo, Chang C, additional, Shang, Yu L, additional, Wang, Jing B, additional, and Han, Ying, additional
Published: 2023
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35. Granger Causal Inference Based on Dual Laplacian Distribution and Its Application to MI-BCI Classification.

Author: Li, P, Gao, X, Li, C, Yi, C, Huang, W, Si, Y, Li, F, Cao, Z, Tian, Y, Xu, P, Li, P, Gao, X, Li, C, Yi, C, Huang, W, Si, Y, Li, F, Cao, Z, Tian, Y, and Xu, P
Abstract: Granger causality-based effective brain connectivity provides a powerful tool to probe the neural mechanism for information processing and the potential features for brain computer interfaces. However, in real applications, traditional Granger causality is prone to the influence of outliers, such as inevitable ocular artifacts, resulting in unreasonable brain linkages and the failure to decipher inherent cognition states. In this work, motivated by constructing the sparse causality brain networks under the strong physiological outlier noise conditions, we proposed a dual Laplacian Granger causality analysis (DLap-GCA) by imposing Laplacian distributions on both model parameters and residuals. In essence, the first Laplacian assumption on residuals will resist the influence of outliers in electroencephalogram (EEG) on causality inference, and the second Laplacian assumption on model parameters will sparsely characterize the intrinsic interactions among multiple brain regions. Through simulation study, we quantitatively verified its effectiveness in suppressing the influence of complex outliers, the stable capacity for model estimation, and sparse network inference. The application to motor-imagery (MI) EEG further reveals that our method can effectively capture the inherent hemispheric lateralization of MI tasks with sparse patterns even under strong noise conditions. The MI classification based on the network features derived from the proposed approach shows higher accuracy than other existing traditional approaches, which is attributed to the discriminative network structures being captured in a timely manner by DLap-GCA even under the single-trial online condition. Basically, these results consistently show its robustness to the influence of complex outliers and the capability of characterizing representative brain networks for cognition information processing, which has the potential to offer reliable network structures for both cognitive studies and future brain
Published: 2023

36. Information transmission velocity-based dynamic hierarchical brain networks.

Author: Jiang, L, Li, F, Chen, Z, Zhu, B, Yi, C, Li, Y, Zhang, T, Peng, Y, Si, Y, Cao, Z, Chen, A, Yao, D, Chen, X, Xu, P, Jiang, L, Li, F, Chen, Z, Zhu, B, Yi, C, Li, Y, Zhang, T, Peng, Y, Si, Y, Cao, Z, Chen, A, Yao, D, Chen, X, and Xu, P
Abstract: The brain functions as an accurate circuit that regulates information to be sequentially propagated and processed in a hierarchical manner. However, it is still unknown how the brain is hierarchically organized and how information is dynamically propagated during high-level cognition. In this study, we developed a new scheme for quantifying the information transmission velocity (ITV) by combining electroencephalogram (EEG) and diffusion tensor imaging (DTI), and then mapped the cortical ITV network (ITVN) to explore the information transmission mechanism of the human brain. The application in MRI-EEG data of P300 revealed bottom-up and top-down ITVN interactions subserving P300 generation, which was comprised of four hierarchical modules. Among these four modules, information exchange between visual- and attention-activated regions occurred at a high velocity, related cognitive processes could thus be efficiently accomplished due to the heavy myelination of these regions. Moreover, inter-individual variability in P300 was probed to be attributed to the difference in information transmission efficiency of the brain, which may provide new insight into the cognitive degenerations in clinical neurodegenerative disorders, such as Alzheimer's disease, from the transmission velocity perspective. Together, these findings confirm the capacity of ITV to effectively determine the efficiency of information propagation in the brain.
Published: 2023

37. Effective Emotion Recognition by Learning Discriminative Graph Topologies in EEG Brain Networks.

Author: Li, C, Li, P, Zhang, Y, Li, N, Si, Y, Li, F, Cao, Z, Chen, H, Chen, B, Yao, D, Xu, P, Li, C, Li, P, Zhang, Y, Li, N, Si, Y, Li, F, Cao, Z, Chen, H, Chen, B, Yao, D, and Xu, P
Abstract: Multichannel electroencephalogram (EEG) is an array signal that represents brain neural networks and can be applied to characterize information propagation patterns for different emotional states. To reveal these inherent spatial graph features and increase the stability of emotion recognition, we propose an effective emotion recognition model that performs multicategory emotion recognition with multiple emotion-related spatial network topology patterns (MESNPs) by learning discriminative graph topologies in EEG brain networks. To evaluate the performance of our proposed MESNP model, we conducted single-subject and multisubject four-class classification experiments on two public datasets, MAHNOB-HCI and DEAP. Compared with existing feature extraction methods, the MESNP model significantly enhances the multiclass emotional classification performance in the single-subject and multisubject conditions. To evaluate the online version of the proposed MESNP model, we designed an online emotion monitoring system. We recruited 14 participants to conduct the online emotion decoding experiments. The average online experimental accuracy of the 14 participants was 84.56%, indicating that our model can be applied in affective brain-computer interface (aBCI) systems. The offline and online experimental results demonstrate that the proposed MESNP model effectively captures discriminative graph topology patterns and significantly improves emotion classification performance. Moreover, the proposed MESNP model provides a new scheme for extracting features from strongly coupled array signals.
Published: 2023

38. Back Cover

Author: Miao Zhang, Si Y Tian, Shuo Y Ma, Xia Zhou, Xiao H Zheng, Bo Li, Guan Y Guo, Jia H Yu, Rui Su, Fang F Yang, Yi N Hu, Gang Ma, Hui Yang, Lin H Zheng, Chang C Guo, Yu L Shang, Jing B Wang, and Ying Han
Subjects: Hepatology
Published: 2023

39. Peritectic solidification mechanism and accompanying microhardness enhancement of rapidly quenched Ni–Zr alloys

Author: Si, Y. F., Wang, H. P., Lü, P., and Wei, B.
Published: 2019
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40. Acute Eosinophilic Pneumonia Masquerading as a Lung Abscess.

Author: Ren, Hong Q., Qian Zhao, Jiao Jiang, Wen Yang, Ling Zhang, Sun, Si Y., Yao, Xue X., and Ge, Yan L.
Subjects: PULMONARY eosinophilia, LUNGS, ABSCESSES, BRONCHOALVEOLAR lavage, MEDICAL personnel, DIAGNOSTIC imaging
Abstract: Background: Acute Eosinophilic Pneumonia (AEP) is a rare form of non-infectious pneumonia that is easily missed and misdiagnosed because of its atypical clinical symptoms and misleading laboratory and imaging studies. Methods: By reporting a case of an initial diagnosis of lung abscess, which was treated with antibiotics and then CT suggesting that the lesion continued to worsen, it was eventually confirmed to be AEP by lung biopsy, A joint literature analysis was conducted to improve clinicians' understanding of the diagnosis and treatment of AEP. Results: Initially, because of the atypical ancillary findings, we thought the disease was a lung abscess, which was eventually confirmed by pathology as AEP. Conclusions: The presence of AEP needs to be considered when various laboratory findings point to infectious disease, but anti-infection is not effective. Diagnosis can be confirmed by bronchoalveolar lavage and lung tissue biopsy. Prompt treatment can provide rapid relief and reduce the risk of patient death. [ABSTRACT FROM AUTHOR]
Published: 2023
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41. Optimization design for throttle valve of managed pressure drilling based on CFD erosion simulation and response surface methodology

Author: Wang, Guo R, Chu, Fei, Tao, Si y, Jiang, Long, and Zhu, Hao
Published: 2015
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42. Buoyancy-driven flow of the Antarctic slope undercurrent and heat transport toward Amundsen Sea ice shelves

Author: Si, Y., Stewart, A., Silvano, A., and Naveira Garabato, A.
Abstract: Elevated ice shelf melt rates in the Amundsen Sea have been attributed to transport of warm Circumpolar Deep Water onto the continental shelf via bathymetric troughs. These inflows are supplied by an eastward, subsurface slope current that opposes the westward momentum input from local winds and tides, referred to as the Antarctic slope undercurrent. Previous studies have linked variations in the melt rates of the Amundsen Sea ice shelves to wind fluctuations. Yet the mechanism via which the undercurrent forms, and thus what controls the mean shoreward heat transport, remains unclear. In this study we investigate the dynamics of the undercurrent using a high-resolution ocean-sea ice process model coupled to a static ice shelf. We explore the sensitivities of the undercurrent strength, shoreward heat transport, and ice shelf melt rates to winds, tides, diapycnal mixing, and geometry. We find that the undercurrent forms with realistic strength provided that there is a trough allowing access to the continental shelf and ice shelf cavity, and that there is a cross-slope buoyancy gradient. The vorticity balance within the CDW layer reveals that the bathymetric steering of the undercurrent towardthe ice shelfis related to diapycnal upwelling that occurs as CDW melts the ice. These findings imply that the mean flow of the Antarctic slope undercurrent is primarily established by buoyancy forcing on the continental shelf, and motivate a focus on processes that influence cross-shelf/slope buoyancy gradients to better understand future changes in shoreward heat transport., The 28th IUGG General Assembly (IUGG2023) (Berlin 2023)
Published: 2023
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43. Sex difference in the expression of PD-1 of non-small cell lung cancer

Author: Yong, Gu, Ying Y, Tang, Jian X, Wan, Jian Y, Zou, Chuan G, Lu, Hao S, Zhu, Si Y, Sheng, Yan F, Wang, Hai Ch, Liu, Jia, Yang, and Hai, Hong
Subjects: Male, Sex Characteristics, Lung Neoplasms, Carcinoma, Non-Small-Cell Lung, Programmed Cell Death 1 Receptor, Immunology, Humans, Immunology and Allergy, Female, Testosterone
Abstract: Evidence increasingly indicated that lung cancer incidence in female individuals continue to rise, and women have a higher risk to develop adenocarcinoma than men. Male and female individuals differ in their innate and adaptive immune responses, and there are sex differences in response to the PD-1/PD-L1-dependent blocking immunotherapy. Whether the differential expression of PD-1 between genders affect the response to blocking treatment is currently unknown. In this study, we examined sex differences in serum sPD-1, mPD-1 expression on T cells, and sex hormone levels in non-small cell lung cancer (NSCLC) patients. Our results revealed a higher level of sPD-1 and expression of PD-1 on CD4+T cell in female patients than in male patients; we identified that serum sPD-1 level and the expression of mPD-1 on T cells were significantly reduced in NSCLC; we also found that serum testosterone level increased in female patients compared with control subjects and that increased testosterone downregulated the expression of mPD-1 on T cell. These findings provide a better understanding of the differences in PD-1 expression between genders in NSCLC patients and the effect of sex hormones on PD-1 expression and supply evidence for early lung cancer diagnosis and responsiveness to immune checkpoint inhibitors.
Published: 2022

44. Sex difference in the expression of PD-1 of non-small cell lung cancer

Author: Gu, Yong, primary, Tang, Ying Y., additional, Wan, Jian X., additional, Zou, Jian Y., additional, Lu, Chuan G., additional, Zhu, Hao S., additional, Sheng, Si Y., additional, Wang, Yan F., additional, Liu, Hai Ch., additional, Yang, Jia, additional, and Hong, Hai, additional
Published: 2022
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45. Transient thermal analysis for radioactive liquid mixing operations in a large-scaled tank

Author: Lee, Si Y. and Smith, Frank G.
Published: 2014
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46. Prediction of Health Risk Preventative Behavior of Amateur Marathon Runners: A Cross-Sectional Study

Author: Zuo Y, Zhang M, Si Y, Wu X, and Ren Z
Subjects: health values, health belief model, Public aspects of medicine, RA1-1270, human activities, perceived health threat, self-efficacy, health behavior expectation, behavioral attitude
Abstract: Yifan Zuo,1,2 Mu Zhang,2 Yuqi Si,2 Xiaoyuan Wu,3 Zhanbing Ren3 1School of Management, Jinan University, Guangzhou, 510632, People’s Republic of China; 2Shenzhen Tourism College, Jinan University, Shenzhen, 518053, People’s Republic of China; 3Department of Physical Education, Shenzhen University, Shenzhen, 518061, People’s Republic of ChinaCorrespondence: Zhanbing RenDepartment of Physical Education, Shenzhen University, 3688 Nanhai Avenue, Nanshan District, Shenzhen, Guangdong Province, People’s Republic of ChinaTel +86755-26534772Fax +860755-26534772Email rzb@szu.edu.cnIntroduction: Prevention of the health risk of amateur marathon runners is of great significance for the sustainable development of marathon. To reduce the psychological burden of amateur marathon runners and improve the participation experience, the current study used the health belief model to study the relationship among health beliefs, attitude to preventative behavior, self-efficacy, and health values of amateur marathon runners.Methods: A total of 342 data were collected, and using the PROCESS (analytical procedures developed for mediating and moderating effects tests based on SPSS and SAS). A series of multiple linear regression models were established to study the relationship between variables, and the bootstrap confidence interval was selected to test the mediating and moderating effect.Results: The results showed that perceived health threat (b = 0.463, p < 0.05), health behavior expectations (b = 0.373, p < 0.001), self-efficacy (b = 0.322, p < 0.001), and behavioral attitudes (b = 0.230, p < 0.001) can be regarded as antecedent variables for predicting preventative behaviors. In addition, the results also show that health behavior expectations, self-efficacy, and behavioral attitudes play chain-mediating role between perceived health threat and preventative behaviors. Health values appear to play a moderating role in the direct/indirect effects of perceived health threat on preventive behavior through a number of mediating variables.Discussion: This study emphasizes that the amateur marathon runners must improve their health concept and take effective preventive measures before participating in the competition. According to this research, it is the responsibility of the event parties, public health officials and relevant departments of the host city to provide rich health information and risk education to amateur marathon runners. More public service advertisements or educational materials are needed to be placed on runners to enhance their awareness of the necessity and importance of taking preventive measures.Keywords: health belief model, perceived health threat, health behavior expectation, self-efficacy, behavioral attitude, health values
Published: 2021

47. Design and implementation of a PM2.5 remote sensing monitoring system based on Hadoop

Author: Wang, L, primary, Xu, S, additional, Zheng, F, additional, Si, Y, additional, and Ge, Q, additional
Published: 2017
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48. Molecular Diagnosis of Cystic Fibrosis

Author: Si, Y., primary and Best, D.H., additional
Published: 2017
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49. The short-term efficacy of electrical pudendal nerve stimulation versus intravesical instillation for the urethral pain syndrome: a randomized clinical trial

Author: Jian Wei Lv, Tian Li, Ting Lv, Xin Y Feng, Xiao M Feng, and Si Y Wang
Subjects: Lidocaine, business.industry, Visual analogue scale, Urology, Pelvic pain, 030232 urology & nephrology, medicine.disease, law.invention, 03 medical and health sciences, 0302 clinical medicine, Urethra, medicine.anatomical_structure, Randomized controlled trial, law, Lower urinary tract symptoms, 030220 oncology & carcinogenesis, Anesthesia, Neuropathic pain, Clinical endpoint, Medicine, medicine.symptom, business, medicine.drug
Abstract: Urethral pain syndrome is a chronic condition characterized by disturbing feeling or server pain sensed at the urethra without specific treatment. This double-center, two-arm controlled trial aimed to explore the efficacy of electrical pudendal nerve stimulation (EPNS) versus intravesical instillation (II) of heparin and alkalinized lidocaine for urethral pain syndrome (UPS). Eighty eligible patients took three sessions of EPNS, or 1 session of II per week, for 6 consecutive weeks. The primary end point was the change of pelvic pain and urgency/frequency symptom (PUF) score from baseline to week 6. Secondary outcome measures included changes of visual analogue scale (VAS) score and three sub-score extracted from PUF score. The enrolled participants were all included in the intention-to-treat analyses, and baseline characteristics between the two groups were well balanced. The post-treatment PUF score decreased by 10.0 (7.00, 16.50) in the EPNS group, and by 7.0 (3.00, 10.00) in the II group. At the closure of treatment, the medians of changes in symptom score, bother score, pain-related score and VAS score were 6.50 (4.25, 10.00), 4.00 (2.00, 6.00), 6.00 (5.00, 8.00),4.50 (2.25, 6.00), respectively, in the EPNS group, and 4.00 (2.00, 7.00), 3.00 (1.00, 3.00), 3.00 (2.00, 6.00), 2.00 (1.00, 4.00), respectively, in the II group. All the between-group differences were statistically significant. Compared with the II, the EPNS results in superior pain control and better relief of lower urinary tract symptoms, and deserves further attention. ClinicalTrials.gov (NCT03671993)
Published: 2021

50. Velocity Estimation and Cost Map Generation for Dynamic Obstacle Avoidance of ROS Based AMR

Author: Chen, Chin S., primary, Lin, Chia J., additional, Lai, Chun C., additional, and Lin, Si Y., additional
Published: 2022
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