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1. FA4SANS-GAN: A Novel Machine Learning Generative Adversarial Network to Further Understand Ophthalmic Changes in Spaceflight Associated Neuro-Ocular Syndrome (SANS)

Author: Sharif Amit Kamran, PhD, Khondker Fariha Hossain, MS, Joshua Ong, MD, Ethan Waisberg, Mb BCh, BAO, Nasif Zaman, MS, Salah A. Baker, PhD, Andrew G. Lee, MD, and Alireza Tavakkoli, PhD
Subjects: Spaceflight-associated neuro-ocular syndrome, Generative adversarial networks, Ophthalmic imaging, Space medicine, Astronaut, Ophthalmology, RE1-994
Abstract: Purpose: To provide an automated system for synthesizing fluorescein angiography (FA) images from color fundus photographs for averting risks associated with fluorescein dye and extend its future application to spaceflight associated neuro-ocular syndrome (SANS) detection in spaceflight where resources are limited. Design: Development and validation of a novel conditional generative adversarial network (GAN) trained on limited amount of FA and color fundus images with diabetic retinopathy and control cases. Participants: Color fundus and FA paired images for unique patients were collected from a publicly available study. Methods: FA4SANS-GAN was trained to generate FA images from color fundus photographs using 2 multiscale generators coupled with 2 patch-GAN discriminators. Eight hundred fifty color fundus and FA images were utilized for training by augmenting images from 17 unique patients. The model was evaluated on 56 fluorescein images collected from 14 unique patients. In addition, it was compared with 3 other GAN architectures trained on the same data set. Furthermore, we test the robustness of the models against acquisition noise and retaining structural information when introduced to artificially created biological markers. Main Outcome Measures: For GAN synthesis, metric Fréchet Inception Distance (FID) and Kernel Inception Distance (KID). Also, two 1-sided tests (TOST) based on Welch’s t test for measuring statistical significance. Results: On test FA images, mean FID for FA4SANS-GAN was 39.8 (standard deviation, 9.9), which is better than GANgio model’s mean of 43.2 (standard deviation, 13.7), Pix2PixHD’s mean of 57.3 (standard deviation, 11.5) and Pix2Pix’s mean of 67.5 (standard deviation, 11.7). Similarly for KID, FA4SANS-GAN achieved mean of 0.00278 (standard deviation, 0.00167) which is better than other 3 model’s mean KID of 0.00303 (standard deviation, 0.00216), 0.00609 (standard deviation, 0.00238), 0.00784 (standard deviation, 0.00218). For TOST measurement, FA4SANS-GAN was proven to be statistically significant versus GANgio (P = 0.006); versus Pix2PixHD (P < 0.00001); and versus Pix2Pix (P < 0.00001). Conclusions: Our study has shown FA4SANS-GAN to be statistically significant for 2 GAN synthesis metrics. Moreover, it is robust against acquisition noise, and can retain clear biological markers compared with the other 3 GAN architectures. This deployment of this model can be crucial in the International Space Station for detecting SANS. Financial Disclosure(s): The authors have no proprietary or commercial interest in any materials discussed in this article.
Published: 2024
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2. Inhibition of PTEN Gene Expression by Oncogenic miR-23b-3p in Renal Cancer

Author: Dahiya, Rajvir, Zaman, MS, Thamminana, S, Shahryari, V, Chiyomaru, T, Deng, G, Saini, S, Majid, S, Fukuhara, S, Chang, I, and Arora, S
Abstract: Background: miR-23b is located on chromosome number 9 and plays different roles in different organs especially with regards to cancer development. However, the functional significance of miR-23b-3p in renal cell carcinoma (RCC) has not been reported. Metho
Published: 2012

3. MicroRNA-1280 Inhibits Invasion and Metastasis by Targeting ROCK1 in Bladder Cancer

Author: Tabatabai, Zohreh, Dahiya, Rajvir, Majid, S, Dar, AA, Saini, S, Shahryari, V, Arora, S, Zaman, MS, Chang, I, Yamamura, S, Chiyomaru, T, and Fukuhara, S
Abstract: MicroRNAs (miRNAs) are non-protein-coding sequences that can function as oncogenes or tumor suppressor genes. This study documents the tumor suppressor role of miR-1280 in bladder cancer. Quantitative real-time PCR and in situ hybridization analyses showed
Published: 2012

4. Genistein suppresses prostate cancer growth through inhibition of oncogenic MicroRNA-151

Author: Tabatabai, Zohreh, Dahiya, Rajvir, Chiyomaru, T, Yamamura, S, Zaman, MS, Majid, S, Deng, G, Shahryari, V, Saini, S, Hirata, H, Ueno, K, and Chang, I
Abstract: Genistein has been shown to suppress the growth of several cancers through modulation of various pathways. However, the effects of genistein on the regulation of oncogenic microRNA-151 (miR-151) have not been reported. In this study, we investigated whethe
Published: 2012

5. Tumour suppressor microRNA-584 directly targets oncogene Rock-1 and decreases invasion ability in human clear cell renal cell carcinoma

Author: Ueno, K, Hirata, H, Shahryari, V, Chen, Y, Zaman, MS, Singh, K, Tabatabai, ZL, Hinoda, Y, and Dahiya, R
Subjects: Biomedical and Clinical Sciences, Oncology and Carcinogenesis, Biotechnology, Kidney Disease, Genetics, 2.1 Biological and endogenous factors, Aetiology, Cancer, 3' Untranslated Regions, Base Sequence, Carcinoma, Renal Cell, Cell Line, Tumor, DNA Primers, Gene Knockdown Techniques, Humans, Kidney Neoplasms, MicroRNAs, Neoplasm Invasiveness, rho-Associated Kinases, miRNA-584, motility, RCC, ROCK-1, Public Health and Health Services, Oncology & Carcinogenesis, Oncology and carcinogenesis
Abstract: BackgroundThe purpose of this study was to identify new tumour suppressor microRNAs (miRs) in clear cell renal cell carcinoma (ccRCC), carry out functional analysis of their suppressive role and identify their specific target genes.MethodsTo explore suppressor miRs in RCC, miR microarray and real-time PCR were performed using HK-2 and A-498 cells. Cell viability, invasion and wound healing assays were carried out for functional analysis after miR transfection. To determine target genes of miR, we used messenger RNA (mRNA) microarray and target scan algorithms to identify target oncogenes. A 3'UTR luciferase assay was also performed. Protein expression of target genes in ccRCC tissues was confirmed by immunohistochemistry and was compared with miR-584 expression in ccRCC tissues.ResultsExpression of miR-584 in RCC (A-498 and 769-P) cells was downregulated compared with HK-2 cells. Transfection of miR-584 dramatically decreased cell motility. The ROCK-1 mRNA was inhibited by miR-584 and predicted to be target gene. The miR-584 decreased 3'UTR luciferase activity of ROCK-1 and ROCK-1 protein expression. Low expression of miR-584 in ccRCC tissues was correlated with high expression of ROCK-1 protein. The knockdown of ROCK-1 by siRNA inhibited cell motility.ConclusionmiR-584 is a new tumour suppressor miR in ccRCC and inhibits cell motility through downregulation of ROCK-1.
Published: 2011

6. The functional significance of microRNA-145 in prostate cancer

Author: Zaman, MS, Chen, Y, Deng, G, Shahryari, V, Suh, SO, Saini, S, Majid, S, Liu, J, Khatri, G, Tanaka, Y, and Dahiya, R
Subjects: Biomedical and Clinical Sciences, Oncology and Carcinogenesis, Genetics, Prostate Cancer, Cancer, Urologic Diseases, Biotechnology, Aging, 2.1 Biological and endogenous factors, Aetiology, Apoptosis, Azacitidine, Cell Cycle, Cell Line, Tumor, DNA Methylation, Decitabine, Down-Regulation, Gene Silencing, Genistein, Humans, Hydroxamic Acids, Male, MicroRNAs, Microarray Analysis, Prostatic Neoplasms, TNF-Related Apoptosis-Inducing Ligand, Up-Regulation, miR145, prostate, cell growth, apoptosis, TNFSF10, Public Health and Health Services, Oncology & Carcinogenesis, Oncology and carcinogenesis
Abstract: BackgroundMicroRNAs (miRNAs) are small noncoding RNAs that have important roles in numerous cellular processes. Recent studies have shown aberrant expression of miRNAs in prostate cancer tissues and cell lines. On the basis of miRNA microarray data, we found that miR-145 is significantly downregulated in prostate cancer.Methods and resultsWe investigated the expression and functional significance of miR-145 in prostate cancer. The expression of miR-145 was low in all the prostate cell lines tested (PC3, LNCaP and DU145) compared with the normal cell line, PWR-1E, and in cancerous regions of human prostate tissue when compared with the matched adjacent normal. Overexpression of miR-145 in PC3-transfected cells resulted in increased apoptosis and an increase in cells in the G2/M phase, as detected by flow cytometry. Investigation of the mechanisms of inactivation of miR-145 through epigenetic pathways revealed significant DNA methylation of the miR-145 promoter region in prostate cancer cell lines. Microarray analyses of miR-145-overexpressing PC3 cells showed upregulation of the pro-apoptotic gene TNFSF10, which was confirmed by real-time PCR and western analysis.ConclusionOne of the genes significantly upregulated by miR-145 overexpression is the proapoptotic gene TNFSF10. Therefore, modulation of miR-145 may be an important therapeutic approach for the management of prostate cancer.
Published: 2010

7. Spatial, temporal, and demographic patterns in prevalence of smoking tobacco use and attributable disease burden in 204 countries and territories, 1990-2019: a systematic analysis from the Global Burden of Disease Study 2019

Author: Reitsma, MB, Kendrick, PJ, Ababneh, E, Abbafati, C, Abbasi-Kangevari, M, Abdoli, A, Abedi, A, Abhilash, ES, Abila, DB, Aboyans, V, Abu-Rmeileh, NME, Adebayo, OM, Advani, SM, Aghaali, M, Ahinkorah, BO, Ahmad, S, Ahmadi, K, Ahmed, H, Aji, B, Akunna, CJ, Al-Aly, Z, Alanzi, TM, Alhabib, KF, Ali, L, Alif, SM, Alipour, V, Aljunid, SM, Alla, F, Allebeck, P, Alvis-Guzman, N, Amin, TT, Amini, S, Amu, H, Amul, GGH, Ancuceanu, R, Anderson, JA, Ansari-Moghaddam, A, Antonio, CAT, Antony, B, Anvari, D, Arabloo, J, Arian, ND, Arora, M, Asaad, M, Ausloos, M, Awan, AT, Ayano, G, Aynalem, GL, Azari, S, Darshan, BB, Badiye, AD, Baig, AA, Bakhshaei, MH, Banach, M, Banik, PC, Barker-Collo, SL, Barnighausen, TW, Barqawi, HJ, Basu, S, Bayati, M, Bazargan-Hejazi, S, Behzadifar, M, Bekuma, TT, Bennett, DA, Bensenor, IM, Berfield, KSS, Bhagavathula, AS, Bhardwaj, N, Bhardwaj, P, Bhattacharyya, K, Bibi, S, Bijani, A, Bintoro, BS, Biondi, A, Birara, S, Braithwaite, D, Brenner, H, Brunoni, AR, Burkart, K, Butt, ZA, Caetano dos Santos, FL, Alberto Camera, L, Car, J, Cardenas, R, Carreras, G, Carrero, JJ, Castaldelli-Maia, JM, Cattaruzza, MSS, Chang, J-C, Chen, S, Chu, D-T, Chung, S-C, Cirillo, M, Costa, VM, Couto, RAS, Dadras, O, Dai, X, Damasceno, AAM, Damiani, G, Dandona, L, Dandona, R, Daneshpajouhnejad, P, Gela, JD, Davletov, K, Molla, MD, Dessie, GA, Desta, AA, Dharmaratne, SD, Dianatinasab, M, Diaz, D, Hoa, TD, Douiri, A, Duncan, BB, Duraes, AR, Eagan, AW, Kalan, ME, Edvardsson, K, Elbarazi, I, El Tantawi, M, Esmaeilnejad, S, Fadhil, I, Faraon, EJA, Farinha, CSES, Farwati, M, Farzadfar, F, Fazlzadeh, M, Feigin, VL, Feldman, R, Prendes, CF, Ferrara, P, Filip, I, Filippidis, F, Fischer, F, Flor, LS, Foigt, NA, Folayan, MO, Foroutan, M, Gad, MM, Gaidhane, AM, Gallus, S, Geberemariyam, BS, Ghafourifard, M, Ghajar, A, Ghashghaee, A, Giampaoli, S, Gill, PS, Glozah, FN, Gnedovskaya, EV, Golechha, M, Gopalani, SV, Gorini, G, Goudarzi, H, Goulart, AC, Greaves, F, Guha, A, Guo, Y, Gupta, B, Das Gupta, R, Gupta, R, Gupta, T, Gupta, V, Hafezi-Nejad, N, Haider, MR, Hamadeh, RR, Hankey, GJ, Hargono, A, Hartono, RK, Hassankhani, H, Hay, SI, Heidari, G, Herteliu, C, Hezam, K, Hird, TR, Hole, MK, Holla, R, Hosseinzadeh, M, Hostiuc, S, Househ, M, Hsiao, T, Huang, J, Iannucci, VC, Ibitoye, SE, Idrisov, B, Ilesanmi, OS, Ilic, IM, Ilic, MD, Inbaraj, LR, Irvani, SSN, Islam, JY, Islam, RM, Shariful Islam, Sheikh, Islami, F, Iso, H, Itumalla, R, Iwagami, M, Jaafari, J, Jain, V, Jakovljevic, M, Jang, S-I, Janjani, H, Jayaram, S, Jeemon, P, Jha, RP, Jonas, JB, Joo, T, Jurisson, M, Kabir, A, Kabir, Z, Kalankesh, LR, Kanchan, T, Kandel, H, Kapoor, N, Karimi, SE, Katikireddi, SV, Kebede, HK, Kelkay, B, Kennedy, RD, Khoja, AT, Khubchandani, J, Kim, GR, Kim, Y-E, Kimokoti, RW, Kivimaki, M, Kosen, S, Laxminarayana, SLK, Koyanagi, A, Krishan, K, Kugbey, N, Kumar, GA, Kumar, N, Kurmi, OP, Kusuma, D, Lacey, B, Lam, JO, Landires, I, Lasrado, S, Lauriola, P, Lee, DW, Lee, YH, Leung, J, Li, S, Lin, H, Linn, S, Liu, W, Lopez, AD, Lopukhov, PD, Lorkowski, S, Lugo, A, Majeed, A, Maleki, A, Malekzadeh, R, Malta, DC, Mamun, AA, Manjunatha, N, Mansouri, B, Mansournia, MA, Martinez-Raga, J, Martini, S, Mathur, MR, Medina-Solis, CE, Mehata, S, Mendoza, W, Menezes, RG, Meretoja, A, Meretoja, TJ, Miazgowski, B, Michalek, IM, Miller, TR, Mirrakhimov, EM, Mirzaei, H, Mirzaei-Alavijeh, M, Misra, S, Moghadaszadeh, M, Mohammad, Y, Mohammadian-Hafshejani, A, Mohammed, S, Mokdad, AH, Monasta, L, Moni, MA, Moradi, G, Moradi-Lakeh, M, Moradzadeh, R, Morrison, SD, Mossie, TB, Mubarik, S, Mullany, EC, Murray, CJL, Naghavi, M, Naghshtabrizi, B, Nair, S, Nalini, M, Nangia, V, Naqvi, AA, Swamy, SN, Naveed, M, Nayak, S, Nayak, VC, Nazari, J, Nduaguba, SO, Kandel, SN, Cuong, TN, Huong, LTN, Son, HN, Trang, HN, Nixon, MR, Nnaji, CA, Norrving, B, Noubiap, JJ, Nowak, C, Ogbo, FA, Oguntade, AS, Oh, I-H, Olagunju, AT, Oren, E, Otstavnov, N, Otstavnov, SS, Owolabi, MO, Pakhale, MPAS, Pakshir, K, Palladino, R, Pana, A, Panda-Jonas, S, Pandey, A, Parekh, U, Park, E-C, Park, E-K, Kan, FP, Patton, GC, Pawar, S, Pestell, RG, Pinheiro, M, Piradov, MA, Pirouzpanah, S, Pokhrel, KN, Polibin, RV, Prashant, A, Pribadi, DRA, Radfar, A, Rahimi-Movaghar, V, Rahman, A, Rahman, MHU, Rahman, Muhammad, Rahmani, AM, Rajai, N, Ram, P, Ranabhat, CL, Rathi, P, Rawal, L, Renzaho, AMN, Myriam Reynales-Shigematsu, L, Rezapour, A, Riahi, SM, Riaz, MA, Roever, L, Ronfani, L, Roshandel, G, Roy, A, Roy, B, Sacco, S, Saddik, B, Sahebkar, A, Salehi, S, Salimzadeh, H, Samaei, M, Samy, AM, Santos, IS, Santric-Milicevic, MM, Sarrafzadegan, N, Sathian, B, Sawhney, M, Saylan, M, Schaub, MP, Schmidt, MI, Ceola Schneider, IJ, Schutte, AE, Schwendicke, F, Seidu, A-A, Kumar, NS, Sepanlou, SG, Seylani, A, Shafaat, O, Shah, SM, Shaikh, MA, Shalash, AS, Shannawaz, M, Sharafi, K, Sheikh, A, Sheikhbahaei, S, Shigematsu, M, Shiri, R, Shishani, K, Shivakumar, KM, Shivalli, S, Shrestha, R, Siabani, S, Sidemo, NB, Sigfusdottir, ID, Sigurvinsdottir, R, Santos Silva, DA, Silva, JP, Singh, A, Singh, JA, Singh, V, Sinha, DN, Sitas, F, Skryabin, VY, Skryabina, AA, Soboka, M, Soriano, JB, Soroush, A, Soshnikov, S, Soyiri, IN, Spurlock, EE, Sreeramareddy, CT, Stein, DJ, Steiropoulos, P, Stortecky, S, Straif, K, Abdulkader, RS, Sulo, G, Sundstrom, J, Tabuchi, T, Tadakamadla, SK, Taddele, BW, Tadesse, EG, Tamiru, AT, Tareke, M, Tareque, MI, Tarigan, IU, Temsah, M-H, Thankappan, KR, Thapar, R, Tichopad, A, Tolani, MA, Topouzis, F, Tovani-Palone, MR, Bach, XT, Tripathy, JP, Tsegaye, GW, Tsilimparis, N, Tymeson, HD, Ullah, A, Ullah, S, Unim, B, Updike, RL, Vacante, M, Valdez, PR, Vardavas, C, Varona Perez, P, Vasankari, TJ, Venketasubramanian, N, Verma, M, Vetrova, MV, Bay, V, Giang, TV, Waheed, Y, Wang, Y, Welding, K, Werdecker, A, Whisnant, JL, Wickramasinghe, ND, Yamagishi, K, Yandrapalli, S, Yatsuya, H, Yazdi-Feyzabadi, V, Yeshaw, Y, Yimmer, MZ, Yonemoto, N, Yu, C, Yunusa, I, Yusefzadeh, H, Moghadam, TZ, Zaman, MS, Zamanian, M, Zandian, H, Zar, HJ, Zastrozhin, MS, Zastrozhina, A, Zavala-Arciniega, L, Zhang, J, Zhang, Z-J, Zhong, C, Zuniga, YMH, Gakidou, E, Reitsma, MB, Kendrick, PJ, Ababneh, E, Abbafati, C, Abbasi-Kangevari, M, Abdoli, A, Abedi, A, Abhilash, ES, Abila, DB, Aboyans, V, Abu-Rmeileh, NME, Adebayo, OM, Advani, SM, Aghaali, M, Ahinkorah, BO, Ahmad, S, Ahmadi, K, Ahmed, H, Aji, B, Akunna, CJ, Al-Aly, Z, Alanzi, TM, Alhabib, KF, Ali, L, Alif, SM, Alipour, V, Aljunid, SM, Alla, F, Allebeck, P, Alvis-Guzman, N, Amin, TT, Amini, S, Amu, H, Amul, GGH, Ancuceanu, R, Anderson, JA, Ansari-Moghaddam, A, Antonio, CAT, Antony, B, Anvari, D, Arabloo, J, Arian, ND, Arora, M, Asaad, M, Ausloos, M, Awan, AT, Ayano, G, Aynalem, GL, Azari, S, Darshan, BB, Badiye, AD, Baig, AA, Bakhshaei, MH, Banach, M, Banik, PC, Barker-Collo, SL, Barnighausen, TW, Barqawi, HJ, Basu, S, Bayati, M, Bazargan-Hejazi, S, Behzadifar, M, Bekuma, TT, Bennett, DA, Bensenor, IM, Berfield, KSS, Bhagavathula, AS, Bhardwaj, N, Bhardwaj, P, Bhattacharyya, K, Bibi, S, Bijani, A, Bintoro, BS, Biondi, A, Birara, S, Braithwaite, D, Brenner, H, Brunoni, AR, Burkart, K, Butt, ZA, Caetano dos Santos, FL, Alberto Camera, L, Car, J, Cardenas, R, Carreras, G, Carrero, JJ, Castaldelli-Maia, JM, Cattaruzza, MSS, Chang, J-C, Chen, S, Chu, D-T, Chung, S-C, Cirillo, M, Costa, VM, Couto, RAS, Dadras, O, Dai, X, Damasceno, AAM, Damiani, G, Dandona, L, Dandona, R, Daneshpajouhnejad, P, Gela, JD, Davletov, K, Molla, MD, Dessie, GA, Desta, AA, Dharmaratne, SD, Dianatinasab, M, Diaz, D, Hoa, TD, Douiri, A, Duncan, BB, Duraes, AR, Eagan, AW, Kalan, ME, Edvardsson, K, Elbarazi, I, El Tantawi, M, Esmaeilnejad, S, Fadhil, I, Faraon, EJA, Farinha, CSES, Farwati, M, Farzadfar, F, Fazlzadeh, M, Feigin, VL, Feldman, R, Prendes, CF, Ferrara, P, Filip, I, Filippidis, F, Fischer, F, Flor, LS, Foigt, NA, Folayan, MO, Foroutan, M, Gad, MM, Gaidhane, AM, Gallus, S, Geberemariyam, BS, Ghafourifard, M, Ghajar, A, Ghashghaee, A, Giampaoli, S, Gill, PS, Glozah, FN, Gnedovskaya, EV, Golechha, M, Gopalani, SV, Gorini, G, Goudarzi, H, Goulart, AC, Greaves, F, Guha, A, Guo, Y, Gupta, B, Das Gupta, R, Gupta, R, Gupta, T, Gupta, V, Hafezi-Nejad, N, Haider, MR, Hamadeh, RR, Hankey, GJ, Hargono, A, Hartono, RK, Hassankhani, H, Hay, SI, Heidari, G, Herteliu, C, Hezam, K, Hird, TR, Hole, MK, Holla, R, Hosseinzadeh, M, Hostiuc, S, Househ, M, Hsiao, T, Huang, J, Iannucci, VC, Ibitoye, SE, Idrisov, B, Ilesanmi, OS, Ilic, IM, Ilic, MD, Inbaraj, LR, Irvani, SSN, Islam, JY, Islam, RM, Shariful Islam, Sheikh, Islami, F, Iso, H, Itumalla, R, Iwagami, M, Jaafari, J, Jain, V, Jakovljevic, M, Jang, S-I, Janjani, H, Jayaram, S, Jeemon, P, Jha, RP, Jonas, JB, Joo, T, Jurisson, M, Kabir, A, Kabir, Z, Kalankesh, LR, Kanchan, T, Kandel, H, Kapoor, N, Karimi, SE, Katikireddi, SV, Kebede, HK, Kelkay, B, Kennedy, RD, Khoja, AT, Khubchandani, J, Kim, GR, Kim, Y-E, Kimokoti, RW, Kivimaki, M, Kosen, S, Laxminarayana, SLK, Koyanagi, A, Krishan, K, Kugbey, N, Kumar, GA, Kumar, N, Kurmi, OP, Kusuma, D, Lacey, B, Lam, JO, Landires, I, Lasrado, S, Lauriola, P, Lee, DW, Lee, YH, Leung, J, Li, S, Lin, H, Linn, S, Liu, W, Lopez, AD, Lopukhov, PD, Lorkowski, S, Lugo, A, Majeed, A, Maleki, A, Malekzadeh, R, Malta, DC, Mamun, AA, Manjunatha, N, Mansouri, B, Mansournia, MA, Martinez-Raga, J, Martini, S, Mathur, MR, Medina-Solis, CE, Mehata, S, Mendoza, W, Menezes, RG, Meretoja, A, Meretoja, TJ, Miazgowski, B, Michalek, IM, Miller, TR, Mirrakhimov, EM, Mirzaei, H, Mirzaei-Alavijeh, M, Misra, S, Moghadaszadeh, M, Mohammad, Y, Mohammadian-Hafshejani, A, Mohammed, S, Mokdad, AH, Monasta, L, Moni, MA, Moradi, G, Moradi-Lakeh, M, Moradzadeh, R, Morrison, SD, Mossie, TB, Mubarik, S, Mullany, EC, Murray, CJL, Naghavi, M, Naghshtabrizi, B, Nair, S, Nalini, M, Nangia, V, Naqvi, AA, Swamy, SN, Naveed, M, Nayak, S, Nayak, VC, Nazari, J, Nduaguba, SO, Kandel, SN, Cuong, TN, Huong, LTN, Son, HN, Trang, HN, Nixon, MR, Nnaji, CA, Norrving, B, Noubiap, JJ, Nowak, C, Ogbo, FA, Oguntade, AS, Oh, I-H, Olagunju, AT, Oren, E, Otstavnov, N, Otstavnov, SS, Owolabi, MO, Pakhale, MPAS, Pakshir, K, Palladino, R, Pana, A, Panda-Jonas, S, Pandey, A, Parekh, U, Park, E-C, Park, E-K, Kan, FP, Patton, GC, Pawar, S, Pestell, RG, Pinheiro, M, Piradov, MA, Pirouzpanah, S, Pokhrel, KN, Polibin, RV, Prashant, A, Pribadi, DRA, Radfar, A, Rahimi-Movaghar, V, Rahman, A, Rahman, MHU, Rahman, Muhammad, Rahmani, AM, Rajai, N, Ram, P, Ranabhat, CL, Rathi, P, Rawal, L, Renzaho, AMN, Myriam Reynales-Shigematsu, L, Rezapour, A, Riahi, SM, Riaz, MA, Roever, L, Ronfani, L, Roshandel, G, Roy, A, Roy, B, Sacco, S, Saddik, B, Sahebkar, A, Salehi, S, Salimzadeh, H, Samaei, M, Samy, AM, Santos, IS, Santric-Milicevic, MM, Sarrafzadegan, N, Sathian, B, Sawhney, M, Saylan, M, Schaub, MP, Schmidt, MI, Ceola Schneider, IJ, Schutte, AE, Schwendicke, F, Seidu, A-A, Kumar, NS, Sepanlou, SG, Seylani, A, Shafaat, O, Shah, SM, Shaikh, MA, Shalash, AS, Shannawaz, M, Sharafi, K, Sheikh, A, Sheikhbahaei, S, Shigematsu, M, Shiri, R, Shishani, K, Shivakumar, KM, Shivalli, S, Shrestha, R, Siabani, S, Sidemo, NB, Sigfusdottir, ID, Sigurvinsdottir, R, Santos Silva, DA, Silva, JP, Singh, A, Singh, JA, Singh, V, Sinha, DN, Sitas, F, Skryabin, VY, Skryabina, AA, Soboka, M, Soriano, JB, Soroush, A, Soshnikov, S, Soyiri, IN, Spurlock, EE, Sreeramareddy, CT, Stein, DJ, Steiropoulos, P, Stortecky, S, Straif, K, Abdulkader, RS, Sulo, G, Sundstrom, J, Tabuchi, T, Tadakamadla, SK, Taddele, BW, Tadesse, EG, Tamiru, AT, Tareke, M, Tareque, MI, Tarigan, IU, Temsah, M-H, Thankappan, KR, Thapar, R, Tichopad, A, Tolani, MA, Topouzis, F, Tovani-Palone, MR, Bach, XT, Tripathy, JP, Tsegaye, GW, Tsilimparis, N, Tymeson, HD, Ullah, A, Ullah, S, Unim, B, Updike, RL, Vacante, M, Valdez, PR, Vardavas, C, Varona Perez, P, Vasankari, TJ, Venketasubramanian, N, Verma, M, Vetrova, MV, Bay, V, Giang, TV, Waheed, Y, Wang, Y, Welding, K, Werdecker, A, Whisnant, JL, Wickramasinghe, ND, Yamagishi, K, Yandrapalli, S, Yatsuya, H, Yazdi-Feyzabadi, V, Yeshaw, Y, Yimmer, MZ, Yonemoto, N, Yu, C, Yunusa, I, Yusefzadeh, H, Moghadam, TZ, Zaman, MS, Zamanian, M, Zandian, H, Zar, HJ, Zastrozhin, MS, Zastrozhina, A, Zavala-Arciniega, L, Zhang, J, Zhang, Z-J, Zhong, C, Zuniga, YMH, and Gakidou, E
Published: 2021

8. Spatial, temporal, and demographic patterns in prevalence of chewing tobacco use in 204 countries and territories, 1990-2019: a systematic analysis from the Global Burden of Disease Study 2019

Author: Kendrick, PJ, Reitsma, MB, Abbasi-Kangevari, M, Abdoli, A, Abdollahi, M, Abedi, A, Abhilash, ES, Aboyans, V, Adebayo, OM, Advani, SM, Ahinkorah, BO, Ahmad, S, Ahmadi, K, Ahmed, H, Aji, B, Akalu, Y, Akunna, CJ, Alahdab, F, Al-Aly, Z, Alanezi, FM, Alanzi, TM, Alhabib, KF, Ali, T, Alif, SM, Alipour, V, Aljunid, SM, Alomari, MA, Amin, TT, Amini, S, Amu, H, Ancuceanu, R, Anderson, JA, Andrei, CL, Andrei, T, Ansari-Moghaddam, A, Antony, B, Anvari, D, Arabloo, J, Arian, ND, Arora, M, Artanti, KD, Asmare, WN, Atnafu, DD, Ausloos, M, Awan, AT, Ayano, G, Aynalem, GL, Azari, S, Darshan, BB, Badiye, AD, Baig, AA, Banach, M, Banerjee, SK, Barker-Collo, SL, Barnighausen, TW, Barqawi, HJ, Basu, S, Bayati, M, Bazargan-Hejazi, S, Bekuma, TT, Bennett, DA, Bensenor, IM, Benzian, H, Benziger, CP, Berman, AE, Bhagavathula, AS, Bhala, N, Bhardwaj, N, Bhardwaj, P, Bhattacharyya, K, Bibi, S, Bijani, A, Biondi, A, Braithwaite, D, Brenner, H, Brunoni, AR, Burkart, K, Nagaraja, SB, Butt, ZA, dos Santos, FLC, Car, J, Carreras, G, Castaldelli-Maia, JM, Cattaruzza, MSS, Chang, J-C, Chaturvedi, P, Chen, S, Chido-Amajuoyi, OG, Chu, D-T, Chung, S-C, Ciobanu, LG, Costa, VM, Couto, RAS, Dagnew, B, Dai, X, Damasceno, AAM, Damiani, G, Dandona, L, Dandona, R, Daneshpajouhnejad, P, Gela, JD, Molla, MD, Desta, AA, Dharmaratne, SD, Dhimal, M, Eagan, AW, Kalan, ME, Edvardsson, K, Effiong, A, El Tantawi, M, Elbarazi, I, Esmaeilnejad, S, Fadhil, I, Faraon, EJA, Farwati, M, Farzadfar, F, Fazlzadeh, M, Feigin, VL, Feldman, R, Filip, I, Filippidis, F, Fischer, F, Flor, LS, Foigt, NA, Folayan, MO, Foroutan, M, Gad, MM, Gallus, S, Geberemariyam, BS, Gebregiorgis, BG, Getacher, L, Obsa, AG, Ghafourifard, M, Gheshlagh, RG, Ghashghaee, A, Ghith, N, Gil, GF, Gill, PS, Ginawi, IA, Goharinezhad, S, Golechha, M, Gopalani, SV, Gorini, G, Grivna, M, Guha, A, Guimaraes, RA, Guo, Y, Das Gupta, R, Gupta, R, Gupta, T, Gupta, V, Hafezi-Nejad, N, Haider, MR, Hamadeh, RR, Hankey, GJ, Hargono, A, Hay, S, Heidari, G, Herteliu, C, Hezam, K, Hird, TR, Holla, R, Hosseinzadeh, M, Hostiuc, M, Hostiuc, S, Househ, M, Hsiao, T, Huang, J, Ibeneme, CU, Ibitoye, SE, Ilic, IM, Ilic, MD, Inbaraj, LR, Irvani, SSN, Islam, JY, Islam, RM, Shariful Islam, Sheikh, Islami, F, Iso, H, Itumalla, R, Jaafari, J, Jain, V, Jakovljevic, M, Jang, S-I, Jayaram, S, Jeemon, P, Jha, RP, Jonas, JB, Jurisson, M, Kabir, A, Kabir, Z, Kalankesh, LR, Kanchan, T, Kandel, H, Kapoor, N, Karch, A, Karimi, SE, Kebede, KM, Kelkay, B, Kennedy, RD, Khader, YS, Khan, EA, Khayamzadeh, M, Kim, GR, Kimokoti, RW, Kivimaki, M, Kosen, S, Laxminarayana, SLK, Koyanagi, A, Krishan, K, Kugbey, N, Kumar, GA, Kumar, N, Kurmi, OP, Kusuma, D, Lacey, B, Landires, I, Lasrado, S, Lauriola, P, Lee, DW, Lee, YH, Leung, J, Li, S, Lin, H, Liu, W, Lugo, A, Kunjathur, SM, Majeed, A, Maleki, A, Malekzadeh, R, Malta, DC, Mamun, AA, Manjunatha, N, Mansouri, B, Mansournia, MA, Martini, S, Mathur, MR, Mathur, P, Mazidi, M, McKee, M, Medina-Solis, CE, Mehata, S, Mendoza, W, Menezes, RG, Miazgowski, B, Michalek, IM, Miller, TR, Mini, G, Mirica, A, Mirrakhimov, EM, Mirzaei, H, Misra, S, Mohammad, Y, Mohammadian-Hafshejani, A, Mohammed, S, Mokdad, AH, Molokhia, M, Monasta, L, Moni, MA, Moradzadeh, R, Morrison, SD, Mossie, TB, Mubarik, S, Mullany, EC, Murray, CJL, Nagaraju, SP, Naghavi, M, Naik, N, Nalini, M, Nangia, V, Naqvi, AA, Swamy, SN, Naveed, M, Nazari, J, Nduaguba, SO, Negoi, RI, Kandel, SN, Nguyen, HLT, Nigatu, YT, Nixon, MR, Nnaji, CA, Noubiap, JJ, Nowak, C, Nunez-Samudio, V, Ogbo, FA, Oguntade, AS, Oh, I-H, Olagunju, AT, Owolabi, MO, Mahesh, PA, Pakshir, K, Pana, A, Panagiotakos, D, Panda-Jonas, S, Pandey, A, Parekh, U, Park, E-C, Park, E-K, Kan, FP, Pathak, M, Pawar, S, Pestell, RG, Pham, HQ, Pinheiro, M, Pokhrel, KN, Pourshams, A, Prashant, A, Radfar, A, Rahimi-Movaghar, V, Rahman, MHU, Rahman, Muhammad, Rahmani, AM, Ram, P, Rana, J, Ranabhat, CL, Rathi, P, Rawaf, DL, Rawaf, S, Rawassizadeh, R, Renzaho, AMN, Rezapour, A, Riaz, MA, Roever, L, Ronfani, L, Roshandel, G, Roy, A, Roy, B, Saddik, B, Sahebkar, A, Salehi, S, Salimzadeh, H, Samy, AM, Sanabria, J, Santric-Milicevic, MM, Sao Jose, BP, Sathian, B, Sawhney, M, Saya, GK, Schwendicke, F, Seidu, A-A, Kumar, NS, Sepanlou, SG, Shafaat, O, Shah, SM, Shaikh, MA, Shannawaz, M, Sharafi, K, Sheikh, A, Sheikhbahaei, S, Shigematsu, M, Shiri, R, Shishani, K, Shivakumar, KM, Shivalli, S, Shrestha, R, Siabani, S, Sidemo, NB, Sigfusdottir, ID, Sigurvinsdottir, R, Silva, JP, Singh, A, Singh, JA, Singh, V, Sinha, DN, Skryabin, VY, Skryabina, AA, Soroush, A, Soyiri, IN, Sreeramareddy, CT, Stein, DJ, Steiropoulos, P, Stortecky, S, Straif, K, Abdulkader, RS, Sulo, G, Sundstrom, J, Tabuchi, T, Tadesse, EG, Tamiru, AT, Tareke, M, Tareque, MI, Tarigan, IU, Thakur, B, Thankappan, KR, Thapar, R, Tolani, MA, Tovani-Palone, MR, Tran, BX, Tripathy, JP, Tsegaye, GW, Tymeson, HD, Ullah, S, Unim, B, Updike, RL, Uthman, OA, Vacante, M, Vardavas, C, Venketasubramanian, N, Verma, M, Vidale, S, Vo, B, Vu, GT, Waheed, Y, Wang, Y, Welding, K, Werdecker, A, Whisnant, JL, Wickramasinghe, ND, Wubishet, BL, Yamagishi, K, Yano, Y, Yazdi-Feyzabadi, V, Yeshaw, Y, Yimmer, MZ, Yonemoto, N, Yousefi, Z, Yu, C, Yunusa, I, Yusefzadeh, H, Zaman, MS, Zamani, M, Zamanian, M, Zastrozhin, MS, Zastrozhina, A, Zhang, J, Zhang, Z-J, Zhong, C, Zuniga, YMH, Gakidou, E, Kendrick, PJ, Reitsma, MB, Abbasi-Kangevari, M, Abdoli, A, Abdollahi, M, Abedi, A, Abhilash, ES, Aboyans, V, Adebayo, OM, Advani, SM, Ahinkorah, BO, Ahmad, S, Ahmadi, K, Ahmed, H, Aji, B, Akalu, Y, Akunna, CJ, Alahdab, F, Al-Aly, Z, Alanezi, FM, Alanzi, TM, Alhabib, KF, Ali, T, Alif, SM, Alipour, V, Aljunid, SM, Alomari, MA, Amin, TT, Amini, S, Amu, H, Ancuceanu, R, Anderson, JA, Andrei, CL, Andrei, T, Ansari-Moghaddam, A, Antony, B, Anvari, D, Arabloo, J, Arian, ND, Arora, M, Artanti, KD, Asmare, WN, Atnafu, DD, Ausloos, M, Awan, AT, Ayano, G, Aynalem, GL, Azari, S, Darshan, BB, Badiye, AD, Baig, AA, Banach, M, Banerjee, SK, Barker-Collo, SL, Barnighausen, TW, Barqawi, HJ, Basu, S, Bayati, M, Bazargan-Hejazi, S, Bekuma, TT, Bennett, DA, Bensenor, IM, Benzian, H, Benziger, CP, Berman, AE, Bhagavathula, AS, Bhala, N, Bhardwaj, N, Bhardwaj, P, Bhattacharyya, K, Bibi, S, Bijani, A, Biondi, A, Braithwaite, D, Brenner, H, Brunoni, AR, Burkart, K, Nagaraja, SB, Butt, ZA, dos Santos, FLC, Car, J, Carreras, G, Castaldelli-Maia, JM, Cattaruzza, MSS, Chang, J-C, Chaturvedi, P, Chen, S, Chido-Amajuoyi, OG, Chu, D-T, Chung, S-C, Ciobanu, LG, Costa, VM, Couto, RAS, Dagnew, B, Dai, X, Damasceno, AAM, Damiani, G, Dandona, L, Dandona, R, Daneshpajouhnejad, P, Gela, JD, Molla, MD, Desta, AA, Dharmaratne, SD, Dhimal, M, Eagan, AW, Kalan, ME, Edvardsson, K, Effiong, A, El Tantawi, M, Elbarazi, I, Esmaeilnejad, S, Fadhil, I, Faraon, EJA, Farwati, M, Farzadfar, F, Fazlzadeh, M, Feigin, VL, Feldman, R, Filip, I, Filippidis, F, Fischer, F, Flor, LS, Foigt, NA, Folayan, MO, Foroutan, M, Gad, MM, Gallus, S, Geberemariyam, BS, Gebregiorgis, BG, Getacher, L, Obsa, AG, Ghafourifard, M, Gheshlagh, RG, Ghashghaee, A, Ghith, N, Gil, GF, Gill, PS, Ginawi, IA, Goharinezhad, S, Golechha, M, Gopalani, SV, Gorini, G, Grivna, M, Guha, A, Guimaraes, RA, Guo, Y, Das Gupta, R, Gupta, R, Gupta, T, Gupta, V, Hafezi-Nejad, N, Haider, MR, Hamadeh, RR, Hankey, GJ, Hargono, A, Hay, S, Heidari, G, Herteliu, C, Hezam, K, Hird, TR, Holla, R, Hosseinzadeh, M, Hostiuc, M, Hostiuc, S, Househ, M, Hsiao, T, Huang, J, Ibeneme, CU, Ibitoye, SE, Ilic, IM, Ilic, MD, Inbaraj, LR, Irvani, SSN, Islam, JY, Islam, RM, Shariful Islam, Sheikh, Islami, F, Iso, H, Itumalla, R, Jaafari, J, Jain, V, Jakovljevic, M, Jang, S-I, Jayaram, S, Jeemon, P, Jha, RP, Jonas, JB, Jurisson, M, Kabir, A, Kabir, Z, Kalankesh, LR, Kanchan, T, Kandel, H, Kapoor, N, Karch, A, Karimi, SE, Kebede, KM, Kelkay, B, Kennedy, RD, Khader, YS, Khan, EA, Khayamzadeh, M, Kim, GR, Kimokoti, RW, Kivimaki, M, Kosen, S, Laxminarayana, SLK, Koyanagi, A, Krishan, K, Kugbey, N, Kumar, GA, Kumar, N, Kurmi, OP, Kusuma, D, Lacey, B, Landires, I, Lasrado, S, Lauriola, P, Lee, DW, Lee, YH, Leung, J, Li, S, Lin, H, Liu, W, Lugo, A, Kunjathur, SM, Majeed, A, Maleki, A, Malekzadeh, R, Malta, DC, Mamun, AA, Manjunatha, N, Mansouri, B, Mansournia, MA, Martini, S, Mathur, MR, Mathur, P, Mazidi, M, McKee, M, Medina-Solis, CE, Mehata, S, Mendoza, W, Menezes, RG, Miazgowski, B, Michalek, IM, Miller, TR, Mini, G, Mirica, A, Mirrakhimov, EM, Mirzaei, H, Misra, S, Mohammad, Y, Mohammadian-Hafshejani, A, Mohammed, S, Mokdad, AH, Molokhia, M, Monasta, L, Moni, MA, Moradzadeh, R, Morrison, SD, Mossie, TB, Mubarik, S, Mullany, EC, Murray, CJL, Nagaraju, SP, Naghavi, M, Naik, N, Nalini, M, Nangia, V, Naqvi, AA, Swamy, SN, Naveed, M, Nazari, J, Nduaguba, SO, Negoi, RI, Kandel, SN, Nguyen, HLT, Nigatu, YT, Nixon, MR, Nnaji, CA, Noubiap, JJ, Nowak, C, Nunez-Samudio, V, Ogbo, FA, Oguntade, AS, Oh, I-H, Olagunju, AT, Owolabi, MO, Mahesh, PA, Pakshir, K, Pana, A, Panagiotakos, D, Panda-Jonas, S, Pandey, A, Parekh, U, Park, E-C, Park, E-K, Kan, FP, Pathak, M, Pawar, S, Pestell, RG, Pham, HQ, Pinheiro, M, Pokhrel, KN, Pourshams, A, Prashant, A, Radfar, A, Rahimi-Movaghar, V, Rahman, MHU, Rahman, Muhammad, Rahmani, AM, Ram, P, Rana, J, Ranabhat, CL, Rathi, P, Rawaf, DL, Rawaf, S, Rawassizadeh, R, Renzaho, AMN, Rezapour, A, Riaz, MA, Roever, L, Ronfani, L, Roshandel, G, Roy, A, Roy, B, Saddik, B, Sahebkar, A, Salehi, S, Salimzadeh, H, Samy, AM, Sanabria, J, Santric-Milicevic, MM, Sao Jose, BP, Sathian, B, Sawhney, M, Saya, GK, Schwendicke, F, Seidu, A-A, Kumar, NS, Sepanlou, SG, Shafaat, O, Shah, SM, Shaikh, MA, Shannawaz, M, Sharafi, K, Sheikh, A, Sheikhbahaei, S, Shigematsu, M, Shiri, R, Shishani, K, Shivakumar, KM, Shivalli, S, Shrestha, R, Siabani, S, Sidemo, NB, Sigfusdottir, ID, Sigurvinsdottir, R, Silva, JP, Singh, A, Singh, JA, Singh, V, Sinha, DN, Skryabin, VY, Skryabina, AA, Soroush, A, Soyiri, IN, Sreeramareddy, CT, Stein, DJ, Steiropoulos, P, Stortecky, S, Straif, K, Abdulkader, RS, Sulo, G, Sundstrom, J, Tabuchi, T, Tadesse, EG, Tamiru, AT, Tareke, M, Tareque, MI, Tarigan, IU, Thakur, B, Thankappan, KR, Thapar, R, Tolani, MA, Tovani-Palone, MR, Tran, BX, Tripathy, JP, Tsegaye, GW, Tymeson, HD, Ullah, S, Unim, B, Updike, RL, Uthman, OA, Vacante, M, Vardavas, C, Venketasubramanian, N, Verma, M, Vidale, S, Vo, B, Vu, GT, Waheed, Y, Wang, Y, Welding, K, Werdecker, A, Whisnant, JL, Wickramasinghe, ND, Wubishet, BL, Yamagishi, K, Yano, Y, Yazdi-Feyzabadi, V, Yeshaw, Y, Yimmer, MZ, Yonemoto, N, Yousefi, Z, Yu, C, Yunusa, I, Yusefzadeh, H, Zaman, MS, Zamani, M, Zamanian, M, Zastrozhin, MS, Zastrozhina, A, Zhang, J, Zhang, Z-J, Zhong, C, Zuniga, YMH, and Gakidou, E
Published: 2021

9. Global, regional, and national burden of stroke and its risk factors, 1990-2019: a systematic analysis for the Global Burden of Disease Study 2019

Author: Feigin, VL, Stark, BA, Johnson, CO, Roth, GA, Bisignano, C, Abady, GG, Abbasifard, M, Abbasi-Kangevari, M, Abd-Allah, F, Abedi, V, Abualhasan, A, Abu-Rmeileh, NM, Abushouk, A, Adebayo, OM, Agarwal, G, Agasthi, P, Ahinkorah, BO, Ahmad, S, Ahmadi, S, Salih, YA, Aji, B, Akbarpour, S, Akinyemi, RO, Al Hamad, H, Alahdab, F, Alif, SM, Alipour, V, Aljunid, SM, Almustanyir, S, Al-Raddadi, RM, Salman, RA-S, Alvis-Guzman, N, Ancuceanu, R, Anderlini, D, Anderson, JA, Ansar, A, Antonazzo, IC, Arabloo, J, Arnlov, J, Artanti, KD, Aryan, Z, Asgari, S, Ashraf, T, Athar, M, Atreya, A, Ausloos, M, Baig, AA, Baltatu, OC, Banach, M, Barboza, MA, Barker-Collo, SL, Barnighausen, TW, Barone, MTU, Basu, S, Bazmandegan, G, Beghi, E, Beheshti, M, Bejot, Y, Bell, AW, Bennett, DA, Bensenor, IM, Bezabhe, WM, Bezabih, YM, Bhagavathula, AS, Bhardwaj, P, Bhattacharyya, K, Bijani, A, Bikbov, B, Birhanu, MM, Boloor, A, Bonny, A, Brauer, M, Brenner, H, Bryazka, D, Butt, ZA, dos Santos, FLC, Campos-Nonato, IR, Cantu-Brito, C, Carrero, JJ, Castaneda-Orjuela, CA, Catapano, AL, Chakraborty, PA, Charan, J, Choudhari, SG, Chowdhury, EK, Chu, D-T, Chung, S-C, Colozza, D, Costa, VM, Costanzo, S, Criqui, MH, Dadras, O, Dagnew, B, Dai, X, Dalal, K, Damasceno, AAM, D'Amico, E, Dandona, L, Dandona, R, Gela, JD, Davletov, K, De La Cruz-Gongora, V, Desai, R, Dhamnetiya, D, Dharmaratne, SD, Dhimal, ML, Dhimal, M, Diaz, D, Dichgans, M, Dokova, K, Doshi, R, Douiri, A, Duncan, BB, Eftekharzadeh, S, Ekholuenetale, M, El Nahas, N, Elgendy, IY, Elhadi, M, El-Jaafary, S, Endres, M, Endries, AY, Erku, DA, Faraon, EJA, Farooque, U, Farzadfar, F, Feroze, AH, Filip, I, Fischer, F, Flood, D, Gad, MM, Gaidhane, S, Gheshlagh, RG, Ghashghaee, A, Ghith, N, Ghozali, G, Ghozy, S, Gialluisi, A, Giampaoli, S, Gilani, SA, Gill, PS, Gnedovskaya, E, Golechha, M, Goulart, AC, Guo, Y, Gupta, R, Gupta, VB, Gupta, VK, Gyanwali, P, Hafezi-Nejad, N, Hamidi, S, Hanif, A, Hankey, GJ, Hargono, A, Hashi, A, Hassan, TS, Hassen, HY, Havmoeller, RJ, Hay, S, Hayat, K, Hegazy, M, Herteliu, C, Holla, R, Hostiuc, S, Househ, M, Huang, J, Humayun, A, Hwang, B-F, Iacoviello, L, Iavicoli, I, Ibitoye, SE, Ilesanmi, OS, Ilic, IM, Ilic, MD, Iqbal, U, Irvani, SSN, Islam, SMS, Ismail, NE, Iso, H, Isola, G, Iwagami, M, Jacob, L, Jain, V, Jang, S-I, Jayapal, SK, Jayaram, S, Jayawardena, R, Jeemon, P, Jha, RP, Johnson, WD, Jonas, JB, Joseph, N, Jozwiak, JJ, Jurisson, M, Kalani, R, Kalhor, R, Kalkonde, Y, Kamath, A, Kamiab, Z, Kanchan, T, Kandel, H, Karch, A, Katoto, PDMC, Kayode, GA, Keshavarz, P, Khader, YS, Khan, EA, Khan, IA, Khan, M, Khan, MAB, Khatib, MN, Khubchandani, J, Kim, GR, Kim, MS, Kim, YJ, Kisa, A, Kisa, S, Kivimaki, M, Kolte, D, Koolivand, A, Laxminarayana, SLK, Koyanagi, A, Krishan, K, Krishnamoorthy, V, Krishnamurthi, R, Kumar, GA, Kusuma, D, La Vecchia, C, Lacey, B, Lak, HM, Lallukka, T, Lasrado, S, Lavados, PM, Leonardi, M, Li, B, Li, S, Lin, H, Lin, R-T, Liu, X, Lo, WD, Lorkowski, S, Lucchetti, G, Saute, RL, Razek, HMAE, Magnani, FG, Mahajan, PB, Majeed, A, Makki, A, Malekzadeh, R, Malik, AA, Manafi, N, Mansournia, MA, Mantovani, LG, Martini, S, Mazzaglia, G, Mehndiratta, MM, Menezes, RG, Meretoja, A, Mersha, AG, Jonasson, JM, Miazgowski, B, Miazgowski, T, Michalek, IM, Mirrakhimov, EM, Mohammad, Y, Mohammadian-Hafshejani, A, Mohammed, S, Mokdad, AH, Mokhayeri, Y, Molokhia, M, Moni, MA, Al Montasir, A, Moradzadeh, R, Morawska, L, Morze, J, Muruet, W, Musa, KI, Nagarajan, AJ, Naghavi, M, Swamy, SN, Nascimento, BR, Negoi, RI, Kandel, SN, Trang, HN, Norrving, B, Noubiap, JJ, Nwatah, VE, Oancea, B, Odukoya, OO, Olagunju, AT, Orru, H, Owolabi, MO, Padubidri, JR, Pana, A, Parekh, T, Park, E-C, Kan, FP, Pathak, M, Peres, MFP, Perianayagam, A, Truong-Minh, P, Piradov, MA, Podder, V, Polinder, S, Postma, MJ, Pourshams, A, Radfar, A, Rafiei, A, Raggi, A, Rahim, F, Rahimi-Movaghar, V, Rahman, M, Rahman, MA, Rahmani, AM, Rajai, N, Ranasinghe, P, Rao, CR, Rao, SJ, Rathi, P, Rawaf, DL, Rawaf, S, Reitsma, MB, Renjith, V, Renzaho, AMN, Rezapour, A, Rodriguez, JAB, Roever, L, Romoli, M, Rynkiewicz, A, Sacco, S, Sadeghi, M, Moghaddam, SS, Sahebkar, A, Saif-Ur-Rahman, K, Salah, R, Samaei, M, Samy, AM, Santos, IS, Santric-Milicevic, MM, Sarrafzadegan, N, Sathian, B, Sattin, D, Schiavolin, S, Schlaich, MP, Schmidt, MI, Schutte, AE, Sepanlou, SG, Seylani, A, Sha, F, Shahabi, S, Shaikh, MA, Shannawaz, M, Shawon, MSR, Sheikh, A, Sheikhbahaei, S, Shibuya, K, Siabani, S, Silva, DAS, Singh, JA, Singh, JK, Skryabin, VY, Skryabina, AA, Sobaih, BH, Stortecky, S, Stranges, S, Tadesse, EG, Tarigan, IU, Temsah, M-H, Teuschl, Y, Thrift, AG, Tonelli, M, Tovani-Palone, MR, Bach, XT, Tripathi, M, Tsegaye, GW, Ullah, A, Unim, B, Unnikrishnan, B, Vakilian, A, Tahbaz, SV, Vasankari, TJ, Venketasubramanian, N, Vervoort, D, Vo, B, Volovici, V, Vosoughi, K, Giang, TV, Linh, GV, Wafa, HA, Waheed, Y, Wang, Y, Wijeratne, T, Winkler, AS, Wolfe, CDA, Woodward, M, Wu, JH, Hanson, SW, Xu, X, Yadav, L, Yadollahpour, A, Jabbari, SHY, Yamagishi, K, Yatsuya, H, Yonemoto, N, Yu, C, Yunusa, I, Zaman, MS, Bin Zaman, S, Zamanian, M, Zand, R, Zandifar, A, Zastrozhin, MS, Zastrozhina, A, Zhang, Y, Zhang, Z-J, Zhong, C, Zuniga, YMH, Murray, CJL, Feigin, VL, Stark, BA, Johnson, CO, Roth, GA, Bisignano, C, Abady, GG, Abbasifard, M, Abbasi-Kangevari, M, Abd-Allah, F, Abedi, V, Abualhasan, A, Abu-Rmeileh, NM, Abushouk, A, Adebayo, OM, Agarwal, G, Agasthi, P, Ahinkorah, BO, Ahmad, S, Ahmadi, S, Salih, YA, Aji, B, Akbarpour, S, Akinyemi, RO, Al Hamad, H, Alahdab, F, Alif, SM, Alipour, V, Aljunid, SM, Almustanyir, S, Al-Raddadi, RM, Salman, RA-S, Alvis-Guzman, N, Ancuceanu, R, Anderlini, D, Anderson, JA, Ansar, A, Antonazzo, IC, Arabloo, J, Arnlov, J, Artanti, KD, Aryan, Z, Asgari, S, Ashraf, T, Athar, M, Atreya, A, Ausloos, M, Baig, AA, Baltatu, OC, Banach, M, Barboza, MA, Barker-Collo, SL, Barnighausen, TW, Barone, MTU, Basu, S, Bazmandegan, G, Beghi, E, Beheshti, M, Bejot, Y, Bell, AW, Bennett, 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Vasankari, TJ, Venketasubramanian, N, Vervoort, D, Vo, B, Volovici, V, Vosoughi, K, Giang, TV, Linh, GV, Wafa, HA, Waheed, Y, Wang, Y, Wijeratne, T, Winkler, AS, Wolfe, CDA, Woodward, M, Wu, JH, Hanson, SW, Xu, X, Yadav, L, Yadollahpour, A, Jabbari, SHY, Yamagishi, K, Yatsuya, H, Yonemoto, N, Yu, C, Yunusa, I, Zaman, MS, Bin Zaman, S, Zamanian, M, Zand, R, Zandifar, A, Zastrozhin, MS, Zastrozhina, A, Zhang, Y, Zhang, Z-J, Zhong, C, Zuniga, YMH, and Murray, CJL
Abstract: BACKGROUND: Regularly updated data on stroke and its pathological types, including data on their incidence, prevalence, mortality, disability, risk factors, and epidemiological trends, are important for evidence-based stroke care planning and resource allocation. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) aims to provide a standardised and comprehensive measurement of these metrics at global, regional, and national levels. METHODS: We applied GBD 2019 analytical tools to calculate stroke incidence, prevalence, mortality, disability-adjusted life-years (DALYs), and the population attributable fraction (PAF) of DALYs (with corresponding 95% uncertainty intervals [UIs]) associated with 19 risk factors, for 204 countries and territories from 1990 to 2019. These estimates were provided for ischaemic stroke, intracerebral haemorrhage, subarachnoid haemorrhage, and all strokes combined, and stratified by sex, age group, and World Bank country income level. FINDINGS: In 2019, there were 12·2 million (95% UI 11·0-13·6) incident cases of stroke, 101 million (93·2-111) prevalent cases of stroke, 143 million (133-153) DALYs due to stroke, and 6·55 million (6·00-7·02) deaths from stroke. Globally, stroke remained the second-leading cause of death (11·6% [10·8-12·2] of total deaths) and the third-leading cause of death and disability combined (5·7% [5·1-6·2] of total DALYs) in 2019. From 1990 to 2019, the absolute number of incident strokes increased by 70·0% (67·0-73·0), prevalent strokes increased by 85·0% (83·0-88·0), deaths from stroke increased by 43·0% (31·0-55·0), and DALYs due to stroke increased by 32·0% (22·0-42·0). During the same period, age-standardised rates of stroke incidence decreased by 17·0% (15·0-18·0), mortality decreased by 36·0% (31·0-42·0), prevalence decreased by 6·0% (5·0-7·0), and DALYs decreased by 36·0% (31·0-42·0). However, among people younger than 70 years, prevalence rates increased by 22·0% (21·0-24·0) and incidence rat
Published: 2021

10. Global Burden of Cardiovascular Diseases and Risk Factors, 1990–2019

Author: Roth, GA, Mensah, GA, Johnson, CO, Addolorato, G, Ammirati, E, Baddour, LM, Barengo, NC, Beaton, AZ, Benjamin, EJ, Benziger, CP, Bonny, A, Brauer, M, Brodmann, M, Cahill, TJ, Carapetis, J, Catapano, AL, Chugh, SS, Cooper, LT, Coresh, J, Criqui, M, DeCleene, N, Eagle, KA, Emmons-Bell, S, Feigin, VL, Fernández-Solà, J, Fowkes, G, Gakidou, E, Grundy, SM, He, FJ, Howard, G, Hu, F, Inker, L, Karthikeyan, G, Kassebaum, N, Koroshetz, W, Lavie, C, Lloyd-Jones, D, Lu, HS, Mirijello, A, Temesgen, AM, Mokdad, A, Moran, AE, Muntner, P, Narula, J, Neal, B, Ntsekhe, M, Moraes de Oliveira, G, Otto, C, Owolabi, M, Pratt, M, Rajagopalan, S, Reitsma, M, Ribeiro, ALP, Rigotti, N, Rodgers, A, Sable, C, Shakil, S, Sliwa-Hahnle, K, Stark, B, Sundström, J, Timpel, P, Tleyjeh, IM, Valgimigli, M, Vos, T, Whelton, PK, Yacoub, M, Zuhlke, L, Murray, C, Fuster, V, Beaton, A, Carapetis, JR, Chugh, S, Criqui, MH, DeCleene, NK, Fernández-Sola, J, Fowkes, FGR, Kassebaum, NJ, Koroshetz, WJ, Misganaw, AT, Mokdad, AH, Oliveira, GMM, Otto, CM, Owolabi, MO, Reitsma, MB, Rigotti, NA, Sable, CA, Shakil, SS, Sliwa, K, Stark, BA, Tleyjeh, II, Zuhlke, LJ, Abbasi-Kangevari, M, Abdi, A, Abedi, A, Aboyans, V, Abrha, WA, Abu-Gharbieh, E, Abushouk, AI, Acharya, D, Adair, T, Adebayo, OM, Ademi, Z, Advani, SM, Afshari, K, Afshin, A, Agarwal, G, Agasthi, P, Ahmad, S, Ahmadi, S, Ahmed, MB, Aji, B, Akalu, Y, Akande-Sholabi, W, Aklilu, A, Akunna, CJ, Alahdab, F, Al-Eyadhy, A, Alhabib, KF, Alif, SM, Alipour, V, Aljunid, SM, Alla, F, Almasi-Hashiani, A, Almustanyir, S, Al-Raddadi, RM, Amegah, AK, Amini, S, Aminorroaya, A, Amu, H, Amugsi, DA, Ancuceanu, R, Anderlini, D, Andrei, T, Andrei, CL, Ansari-Moghaddam, A, Anteneh, ZA, Antonazzo, IC, Antony, B, Anwer, R, Appiah, LT, Arabloo, J, Ärnlöv, J, Artanti, KD, Ataro, Z, Ausloos, M, Avila-Burgos, L, Awan, AT, Awoke, MA, Ayele, HT, Ayza, MA, Azari, S, B, DB, Baheiraei, N, Baig, AA, Bakhtiari, A, Banach, M, Banik, PC, Baptista, EA, Barboza, MA, Barua, L, Basu, S, Bedi, N, Béjot, Y, Bennett, DA, Bensenor, IM, Berman, AE, Bezabih, YM, Bhagavathula, AS, Bhaskar, S, Bhattacharyya, K, Bijani, A, Bikbov, B, Birhanu, MM, Boloor, A, Brant, LC, Brenner, H, Briko, NI, Butt, ZA, Caetano dos Santos, FL, Cahill, LE, Cahuana-Hurtado, L, Cámera, LA, Campos-Nonato, IR, Cantu-Brito, C, Car, J, Carrero, JJ, Carvalho, F, Castañeda-Orjuela, CA, Catalá-López, F, Cerin, E, Charan, J, Chattu, VK, Chen, S, Chin, KL, Choi, J-YJ, Chu, D-T, Chung, S-C, Cirillo, M, Coffey, S, Conti, S, Costa, VM, Cundiff, DK, Dadras, O, Dagnew, B, Dai, X, Damasceno, AAM, Dandona, L, Dandona, R, Davletov, K, De la Cruz-Góngora, V, De la Hoz, FP, De Neve, J-W, Denova-Gutiérrez, E, Derbew Molla, M, Derseh, BT, Desai, R, Deuschl, G, Dharmaratne, SD, Dhimal, M, Dhungana, RR, Dianatinasab, M, Diaz, D, Djalalinia, S, Dokova, K, Douiri, A, Duncan, BB, Duraes, AR, Eagan, AW, Ebtehaj, S, Eftekhari, A, Eftekharzadeh, S, Ekholuenetale, M, El Nahas, N, Elgendy, IY, Elhadi, M, El-Jaafary, SI, Esteghamati, S, Etisso, AE, Eyawo, O, Fadhil, I, Faraon, EJA, Faris, PS, Farwati, M, Farzadfar, F, Fernandes, E, Fernandez Prendes, C, Ferrara, P, Filip, I, Fischer, F, Flood, D, Fukumoto, T, Gad, MM, Gaidhane, S, Ganji, M, Garg, J, Gebre, AK, Gebregiorgis, BG, Gebregzabiher, KZ, Gebremeskel, GG, Getacher, L, Obsa, AG, Ghajar, A, Ghashghaee, A, Ghith, N, Giampaoli, S, Gilani, SA, Gill, PS, Gillum, RF, Glushkova, EV, Gnedovskaya, EV, Golechha, M, Gonfa, KB, Goudarzian, AH, Goulart, AC, Guadamuz, JS, Guha, A, Guo, Y, Gupta, R, Hachinski, V, Hafezi-Nejad, N, Haile, TG, Hamadeh, RR, Hamidi, S, Hankey, GJ, Hargono, A, Hartono, RK, Hashemian, M, Hashi, A, Hassan, S, Hassen, HY, Havmoeller, RJ, Hay, SI, Hayat, K, Heidari, G, Herteliu, C, Holla, R, Hosseini, M, Hosseinzadeh, M, Hostiuc, M, Hostiuc, S, Househ, M, Huang, J, Humayun, A, Iavicoli, I, Ibeneme, CU, Ibitoye, SE, Ilesanmi, OS, Ilic, IM, Ilic, MD, Iqbal, U, Irvani, SSN, Shariful Islam, Sheikh, Islam, RM, Iso, H, Iwagami, M, Jain, V, 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Stortecky, S, Stranges, S, Suliankatchi Abdulkader, R, Tadbiri, H, Tadesse, EG, Tadesse, DB, Tajdini, M, Tariqujjaman, M, Teklehaimanot, BF, Temsah, M-H, Tesema, AK, Thakur, B, Thankappan, KR, Thapar, R, Thrift, AG, Timalsina, B, Tonelli, M, Touvier, M, Tovani-Palone, MR, Tripathi, A, Tripathy, JP, Truelsen, TC, Tsegay, GM, Tsegaye, GW, Tsilimparis, N, Tusa, BS, Tyrovolas, S, Umapathi, KK, Unim, B, Unnikrishnan, B, Usman, MS, Vaduganathan, M, Valdez, PR, Vasankari, TJ, Velazquez, DZ, Venketasubramanian, N, Vu, GT, Vujcic, IS, Waheed, Y, Wang, Y, Wang, F, Wei, J, Weintraub, RG, Weldemariam, AH, Westerman, R, Winkler, AS, Wiysonge, CS, Wolfe, CDA, Wubishet, BL, Xu, G, Yadollahpour, A, Yamagishi, K, Yan, LL, Yandrapalli, S, Yano, Y, Yatsuya, H, Yeheyis, TY, Yeshaw, Y, Yilgwan, CS, Yonemoto, N, Yu, C, Yusefzadeh, H, Zachariah, G, Zaman, SB, Zaman, MS, Zamanian, M, Zand, R, Zandifar, A, Zarghi, A, Zastrozhin, MS, Zastrozhina, A, Zhang, Z-J, Zhang, Y, Zhang, W, Zhong, C, Zou, Z, Zuniga, YMH, Murray, CJL, Roth, GA, Mensah, GA, Johnson, CO, Addolorato, G, Ammirati, E, Baddour, LM, Barengo, NC, Beaton, AZ, Benjamin, EJ, Benziger, CP, Bonny, A, Brauer, M, Brodmann, M, Cahill, TJ, Carapetis, J, Catapano, AL, Chugh, SS, Cooper, LT, Coresh, J, Criqui, M, DeCleene, N, Eagle, KA, Emmons-Bell, S, Feigin, VL, Fernández-Solà, J, Fowkes, G, Gakidou, E, Grundy, SM, He, FJ, Howard, G, Hu, F, Inker, L, Karthikeyan, G, Kassebaum, N, Koroshetz, W, Lavie, C, Lloyd-Jones, D, Lu, HS, Mirijello, A, Temesgen, AM, Mokdad, A, Moran, AE, Muntner, P, Narula, J, Neal, B, Ntsekhe, M, Moraes de Oliveira, G, Otto, C, Owolabi, M, Pratt, M, Rajagopalan, S, Reitsma, M, Ribeiro, ALP, Rigotti, N, Rodgers, A, Sable, C, Shakil, S, Sliwa-Hahnle, K, Stark, B, Sundström, J, Timpel, P, Tleyjeh, IM, Valgimigli, M, Vos, T, Whelton, PK, Yacoub, M, Zuhlke, L, Murray, C, Fuster, V, Beaton, A, Carapetis, JR, Chugh, S, Criqui, MH, DeCleene, NK, Fernández-Sola, J, Fowkes, FGR, Kassebaum, NJ, Koroshetz, WJ, Misganaw, AT, Mokdad, AH, Oliveira, GMM, Otto, CM, Owolabi, MO, Reitsma, MB, Rigotti, NA, Sable, CA, Shakil, SS, Sliwa, K, Stark, BA, Tleyjeh, II, Zuhlke, LJ, Abbasi-Kangevari, M, Abdi, A, Abedi, A, Aboyans, V, Abrha, WA, Abu-Gharbieh, E, Abushouk, AI, Acharya, D, Adair, T, Adebayo, OM, Ademi, Z, Advani, SM, Afshari, K, Afshin, A, Agarwal, G, Agasthi, P, Ahmad, S, Ahmadi, S, Ahmed, MB, Aji, B, Akalu, Y, Akande-Sholabi, W, Aklilu, A, Akunna, CJ, Alahdab, F, Al-Eyadhy, A, Alhabib, KF, Alif, SM, Alipour, V, Aljunid, SM, Alla, F, Almasi-Hashiani, A, Almustanyir, S, Al-Raddadi, RM, Amegah, AK, Amini, S, Aminorroaya, A, Amu, H, Amugsi, DA, Ancuceanu, R, Anderlini, D, Andrei, T, Andrei, CL, Ansari-Moghaddam, A, Anteneh, ZA, Antonazzo, IC, Antony, B, Anwer, R, Appiah, LT, Arabloo, J, Ärnlöv, J, Artanti, KD, Ataro, Z, Ausloos, M, Avila-Burgos, L, Awan, AT, Awoke, MA, Ayele, HT, Ayza, MA, Azari, S, B, DB, Baheiraei, N, Baig, AA, Bakhtiari, A, Banach, M, Banik, PC, Baptista, EA, Barboza, MA, Barua, L, Basu, S, Bedi, N, Béjot, Y, Bennett, DA, Bensenor, IM, Berman, AE, Bezabih, YM, Bhagavathula, AS, Bhaskar, S, Bhattacharyya, K, Bijani, A, Bikbov, B, Birhanu, MM, Boloor, A, Brant, LC, Brenner, H, Briko, NI, Butt, ZA, Caetano dos Santos, FL, Cahill, LE, Cahuana-Hurtado, L, Cámera, LA, Campos-Nonato, IR, Cantu-Brito, C, Car, J, Carrero, JJ, Carvalho, F, Castañeda-Orjuela, CA, Catalá-López, F, Cerin, E, Charan, J, Chattu, VK, Chen, S, Chin, KL, Choi, J-YJ, Chu, D-T, Chung, S-C, Cirillo, M, Coffey, S, Conti, S, Costa, VM, Cundiff, DK, Dadras, O, Dagnew, B, Dai, X, Damasceno, AAM, Dandona, L, Dandona, R, Davletov, K, De la Cruz-Góngora, V, De la Hoz, FP, De Neve, J-W, Denova-Gutiérrez, E, Derbew Molla, M, Derseh, BT, Desai, R, Deuschl, G, Dharmaratne, SD, Dhimal, M, Dhungana, RR, Dianatinasab, M, Diaz, D, Djalalinia, S, Dokova, K, Douiri, A, Duncan, BB, Duraes, AR, Eagan, AW, Ebtehaj, S, Eftekhari, A, Eftekharzadeh, S, Ekholuenetale, M, El Nahas, N, Elgendy, IY, Elhadi, M, El-Jaafary, SI, Esteghamati, S, Etisso, AE, Eyawo, O, Fadhil, I, Faraon, EJA, Faris, PS, Farwati, M, Farzadfar, F, Fernandes, E, Fernandez Prendes, C, Ferrara, P, Filip, I, Fischer, F, Flood, D, Fukumoto, T, Gad, MM, Gaidhane, S, Ganji, M, Garg, J, Gebre, AK, Gebregiorgis, BG, Gebregzabiher, KZ, Gebremeskel, GG, Getacher, L, Obsa, AG, Ghajar, A, Ghashghaee, A, Ghith, N, Giampaoli, S, Gilani, SA, Gill, PS, Gillum, RF, Glushkova, EV, Gnedovskaya, EV, Golechha, M, Gonfa, KB, Goudarzian, AH, Goulart, AC, Guadamuz, JS, Guha, A, Guo, Y, Gupta, R, Hachinski, V, Hafezi-Nejad, N, Haile, TG, Hamadeh, RR, Hamidi, S, Hankey, GJ, Hargono, A, Hartono, RK, Hashemian, M, Hashi, A, Hassan, S, Hassen, HY, Havmoeller, RJ, Hay, SI, Hayat, K, Heidari, G, Herteliu, C, Holla, R, Hosseini, M, Hosseinzadeh, M, Hostiuc, M, Hostiuc, S, Househ, M, Huang, J, Humayun, A, Iavicoli, I, Ibeneme, CU, Ibitoye, SE, Ilesanmi, OS, Ilic, IM, Ilic, MD, Iqbal, U, Irvani, SSN, Shariful Islam, Sheikh, Islam, RM, Iso, H, Iwagami, M, Jain, V, Javaheri, T, Jayapal, SK, Jayaram, S, Jayawardena, R, Jeemon, P, Jha, RP, Jonas, JB, Jonnagaddala, J, Joukar, F, Jozwiak, JJ, Jürisson, M, Kabir, A, Kahlon, T, Kalani, R, Kalhor, R, Kamath, A, Kamel, I, Kandel, H, Kandel, A, Karch, A, Kasa, AS, Katoto, PDMC, Kayode, GA, Khader, YS, Khammarnia, M, Khan, MS, Khan, MN, Khan, M, Khan, EA, Khatab, K, Kibria, GMA, Kim, YJ, Kim, GR, Kimokoti, RW, Kisa, S, Kisa, A, Kivimäki, M, Kolte, D, Koolivand, A, Korshunov, VA, Koulmane Laxminarayana, SL, Koyanagi, A, Krishan, K, Krishnamoorthy, V, Kuate Defo, B, Kucuk Bicer, B, Kulkarni, V, Kumar, GA, Kumar, N, Kurmi, OP, Kusuma, D, Kwan, GF, La Vecchia, C, Lacey, B, Lallukka, T, Lan, Q, Lasrado, S, Lassi, ZS, Lauriola, P, Lawrence, WR, Laxmaiah, A, LeGrand, KE, Li, M-C, Li, B, Li, S, Lim, SS, Lim, L-L, Lin, H, Lin, Z, Lin, R-T, Liu, X, Lopez, AD, Lorkowski, S, Lotufo, PA, Lugo, A, M, NK, Madotto, F, Mahmoudi, M, Majeed, A, Malekzadeh, R, Malik, AA, Mamun, AA, Manafi, N, Mansournia, MA, Mantovani, LG, Martini, S, Mathur, MR, Mazzaglia, G, Mehata, S, Mehndiratta, MM, Meier, T, Menezes, RG, Meretoja, A, Mestrovic, T, Miazgowski, B, Miazgowski, T, Michalek, IM, Miller, TR, Mirrakhimov, EM, Mirzaei, H, Moazen, B, Moghadaszadeh, M, Mohammad, Y, Mohammad, DK, Mohammed, S, Mohammed, MA, Mokhayeri, Y, Molokhia, M, Montasir, AA, Moradi, G, Moradzadeh, R, Moraga, P, Morawska, L, Moreno Velásquez, I, Morze, J, Mubarik, S, Muruet, W, Musa, KI, Nagarajan, AJ, Nalini, M, Nangia, V, Naqvi, AA, Narasimha Swamy, S, Nascimento, BR, Nayak, VC, Nazari, J, Nazarzadeh, M, Negoi, RI, Neupane Kandel, S, Nguyen, HLT, Nixon, MR, Norrving, B, Noubiap, JJ, Nouthe, BE, Nowak, C, Odukoya, OO, Ogbo, FA, Olagunju, AT, Orru, H, Ortiz, A, Ostroff, SM, Padubidri, JR, Palladino, R, Pana, A, Panda-Jonas, S, Parekh, U, Park, E-C, Parvizi, M, Pashazadeh Kan, F, Patel, UK, Pathak, M, Paudel, R, Pepito, VCF, Perianayagam, A, Perico, N, Pham, HQ, Pilgrim, T, Piradov, MA, Pishgar, F, Podder, V, Polibin, RV, Pourshams, A, Pribadi, DRA, Rabiee, N, Rabiee, M, Radfar, A, Rafiei, A, Rahim, F, Rahimi-Movaghar, V, Ur Rahman, MH, Rahman, Muhammad, Rahmani, AM, Rakovac, I, Ram, P, Ramalingam, S, Rana, J, Ranasinghe, P, Rao, SJ, Rathi, P, Rawal, L, Rawasia, WF, Rawassizadeh, R, Remuzzi, G, Renzaho, AMN, Rezapour, A, Riahi, SM, Roberts-Thomson, RL, Roever, L, Rohloff, P, Romoli, M, Roshandel, G, Rwegerera, GM, Saadatagah, S, Saber-Ayad, MM, Sabour, S, Sacco, S, Sadeghi, M, Saeedi Moghaddam, S, Safari, S, Sahebkar, A, Salehi, S, Salimzadeh, H, Samaei, M, Samy, AM, Santos, IS, Santric-Milicevic, MM, Sarrafzadegan, N, Sarveazad, A, Sathish, T, Sawhney, M, Saylan, M, Schmidt, MI, Schutte, AE, Senthilkumaran, S, Sepanlou, SG, Sha, F, Shahabi, S, Shahid, I, Shaikh, MA, Shamali, M, Shamsizadeh, M, Shawon, MSR, Sheikh, A, Shigematsu, M, Shin, M-J, Shin, JI, Shiri, R, Shiue, I, Shuval, K, Siabani, S, Siddiqi, TJ, Silva, DAS, Singh, JA, Mtech, AS, Skryabin, VY, Skryabina, AA, Soheili, A, Spurlock, EE, Stockfelt, L, Stortecky, S, Stranges, S, Suliankatchi Abdulkader, R, Tadbiri, H, Tadesse, EG, Tadesse, DB, Tajdini, M, Tariqujjaman, M, Teklehaimanot, BF, Temsah, M-H, Tesema, AK, Thakur, B, Thankappan, KR, Thapar, R, Thrift, AG, Timalsina, B, Tonelli, M, Touvier, M, Tovani-Palone, MR, Tripathi, A, Tripathy, JP, Truelsen, TC, Tsegay, GM, Tsegaye, GW, Tsilimparis, N, Tusa, BS, Tyrovolas, S, Umapathi, KK, Unim, B, Unnikrishnan, B, Usman, MS, Vaduganathan, M, Valdez, PR, Vasankari, TJ, Velazquez, DZ, Venketasubramanian, N, Vu, GT, Vujcic, IS, Waheed, Y, Wang, Y, Wang, F, Wei, J, Weintraub, RG, Weldemariam, AH, Westerman, R, Winkler, AS, Wiysonge, CS, Wolfe, CDA, Wubishet, BL, Xu, G, Yadollahpour, A, Yamagishi, K, Yan, LL, Yandrapalli, S, Yano, Y, Yatsuya, H, Yeheyis, TY, Yeshaw, Y, Yilgwan, CS, Yonemoto, N, Yu, C, Yusefzadeh, H, Zachariah, G, Zaman, SB, Zaman, MS, Zamanian, M, Zand, R, Zandifar, A, Zarghi, A, Zastrozhin, MS, Zastrozhina, A, Zhang, Z-J, Zhang, Y, Zhang, W, Zhong, C, Zou, Z, Zuniga, YMH, and Murray, CJL
Abstract: Cardiovascular diseases (CVDs), principally ischemic heart disease (IHD) and stroke, are the leading cause of global mortality and a major contributor to disability. This paper reviews the magnitude of total CVD burden, including 13 underlying causes of cardiovascular death and 9 related risk factors, using estimates from the Global Burden of Disease (GBD) Study 2019. GBD, an ongoing multinational collaboration to provide comparable and consistent estimates of population health over time, used all available population-level data sources on incidence, prevalence, case fatality, mortality, and health risks to produce estimates for 204 countries and territories from 1990 to 2019.Prevalent cases of total CVD nearly doubled from 271 million (95% uncertainty interval [UI]: 257 to 285 million) in 1990 to 523 million (95% UI: 497 to 550 million) in 2019, and the number of CVD deaths steadily increased from 12.1 million (95% UI:11.4 to 12.6 million) in 1990, reaching 18.6 million (95% UI: 17.1 to 19.7 million) in 2019. The global trends for disability-adjusted life years (DALYs) and years of life lost also increased significantly, and years lived with disability doubled from 17.7 million (95% UI: 12.9 to 22.5 million) to 34.4 million (95% UI:24.9 to 43.6 million) over that period. The total number of DALYs due to IHD has risen steadily since 1990, reaching 182 million (95% UI: 170 to 194 million) DALYs, 9.14 million (95% UI: 8.40 to 9.74 million) deaths in the year 2019, and 197 million (95% UI: 178 to 220 million) prevalent cases of IHD in 2019. The total number of DALYs due to stroke has risen steadily since 1990, reaching 143 million (95% UI: 133 to 153 million) DALYs, 6.55 million (95% UI: 6.00 to 7.02 million) deaths in the year 2019, and 101 million (95% UI: 93.2 to 111 million) prevalent cases of stroke in 2019.Cardiovascular diseases remain the leading cause of disease burden in the world. CVD burden continues its decades-long rise for almost all countries outside hi
Published: 2020

11. Metabolic Phenotyping Using Metabolic Syndrome Criteria and Cardiometabolic Disabilities Criteria in Bangladeshi Adult Population

Author: Naher, S, primary, Sejooti, SS, primary, Hoque, MM, primary, Zaman, MS, primary, Imam, H, primary, Ahmed, T, primary, Tabassum, R, primary, and Ferdous, M, primary
Published: 2019
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12. Intercropping gardenpea (Pisium sativum) with Maize (Zea mays) at farmers’ field

Author: Khan, MAH, primary, Sultana, N, primary, Akter, N, primary, Zaman, MS, primary, and Islam, MR, primary
Published: 2018
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13. Increasing cropping intensity and productivity through mungbean inclusion in wheat-fallow-T. Aman rice cropping pattern

Author: Khan, MAH, primary, Sultana, N, primary, Akter, N, primary, Zaman, MS, primary, and Choudhury, AK, primary
Published: 2018
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14. Increasing cropping intensityand productivity through boro t.aus-t.aman-mustard cropping pattern in Bangladesh

Author: Khan, MAH, primary, Zaman, MS, primary, Hasan, MK, primary, and Khan, ASMMR, primary
Published: 2018
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15. Performance of Intercropping Groundnut with Sesame

Author: Khan, MAH, primary, Sultana, N, primary, Akhtar, S, primary, Akter, N, primary, and Zaman, MS, primary
Published: 2017
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16. Performance of ash gourd (benincasa hispida) in intercrop with different leafy vegetables

Author: Sultana, N, primary, Khan, MAH, primary, Akhtar, S, primary, Zaman, MS, primary, and Khan, ASMMR, primary
Published: 2017
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17. Intercropping of root crops with chilli in charlands of Mymensingh

Author: Begum, SA, primary, Zaman, MS, primary, and Khan, ASMMR, primary
Published: 2015
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18. Water quality of shallow tube wells as affected by sanitary latrines and groundwater flow

Author: Rahman, SH, Fakhruddin, ANM, Uddin, MJ, Zaman, MS, Talukder, A, Adyel, Tanveer, Sarker, MMR, Rahman, SH, Fakhruddin, ANM, Uddin, MJ, Zaman, MS, Talukder, A, Adyel, Tanveer, and Sarker, MMR
Abstract: The present study investigated the probable influence of latrines and groundwater flow on the water quality of shallow tube wells in Shinduria village (23?52' N and 90?14' E) of Dhaka district, Bangladesh. A questionnaire survey was made to collect basic information on tube wells and latrines. Four boreholes were drilled to investigate lithostratigraphy. Twenty one water samples were collected and their physico-chemical parameters (Dissolved Oxygen, pH, phosphate, sulphate, nitrate, nitrite and iron) were analyzed using standard method. Total viable bacterial count (TVBC), total coliform count (TCC), total faecal coliform count (TFCC), total salmonella shigella (TSS) and total vibrio count (TVC) were also made using membrane filtration method. Average depth of the tube wells was 120 ft and most of them were less then ten years old. About 85% latrines were ring slab type and about 50% of these were built during the last five years. From borehole data, a shallow aquifer was identified at a depth of hundred feet from where local people extract drinking water. Although most of the physico-chemical parameters of the tested samples were within the Department of Environment (DoE). But almost all of the tested samples failed to ensure the quality of acceptable level for drinking water recommended by World Health Organization (WHO) due to the presence of higher load of TVBC (5.07 × 10³ cfu/100 ml), TCC (8.44 × 103cfu/10 0ml), TFCC (5.16 × 10² cfu/100 ml) and TSS (1.10 × 103cfu/100 ml). Local geological conditions and proximity between tube well and latrine promoted bacterial transport towards tube well while groundwater flow direction from the adjacent Bangshi River influenced the phenomenon. DOI: http://dx.doi.org/10.3329/jbas.v37i2.17565 Journal of Bangladesh Academy of Scinces, Vol. 37, No. 2, 231-243, 2013
Published: 2013

19. HIV-related risk behaviours among drug users in Bangladesh

Author: Sekimoto M, Zaman Ms, Fukui T, and Rahman M
Subjects: Drug, Adult, Male, media_common.quotation_subject, Sexual Behavior, Human immunodeficiency virus (HIV), HIV Infections, Dermatology, medicine.disease_cause, Acquired immunodeficiency syndrome (AIDS), Risk Factors, Environmental health, medicine, Humans, Pharmacology (medical), Needle Sharing, Substance Abuse, Intravenous, media_common, Needle sharing, Bangladesh, Risk behaviour, biology, business.industry, Public Health, Environmental and Occupational Health, Risk factor (computing), biology.organism_classification, medicine.disease, Sexual intercourse, Infectious Diseases, Lentivirus, Immunology, Female, business
Published: 2001

20. Knowledge on the Effects of Drug Abuse among the Students In A Selected High School In Dhaka City

Author: Zaman, MS, primary, Almajidi, WA, primary, and Hurunnaher, Dr, primary
Published: 2013
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21. Compositional Nutrient Diagnosis (Cnd) Of Onion (Allium cepa L.)

Author: Yousuf, MN, primary, Akter, S, primary, Haque, MI, primary, Mohammad, N, primary, and Zaman, MS, primary
Published: 2013
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22. Effect of Sulphur Fertilization on The Growth and Yield of Garlic (Allium Sativum L.)

Author: Zaman, MS, primary, Hashem, MA, primary, Jahiruddin, M, primary, and Rahim, MA, primary
Published: 2012
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23. Nutrient composition, in vitro gas production and digestibility of fenugreek (Trigonella foenum-graecum) and alfalfa forages

Author: Mir, Z., primary, Acharya, SN, additional, Mir, PS, additional, Taylor, WG, additional, Zaman, MS, additional, Mears, GJ, additional, and Goonewardene, LA, additional
Published: 1995
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24. Effect Of Nitrogen For Yield Maximization Of Garlic In Old Brahmaputra Flood Plain Soil

Author: Zaman, MS, primary, Hashem, MA, primary, Jahiruddin, M, primary, and Rahim, MA, primary
Published: 1970
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25. Research involvement among undergraduate medical students in Bangladesh: a multicenter cross-sectional study.

Author: Hasan MJ, Islam S, Sujon H, Chowdhury FI, Islam M, Ahmed M, Shabnam M, Rishad MM, Nurunnabi M, Rahman MM, Fardous J, Zaman MS, Zaman MP, Ali MA, Awal MR, Choudhury T, Shuvo AU, Sultana S, Tabassum T, Rahman M, Barshan AD, Tabassum T, Rafi MA, and Yasmeen S
Subjects: Humans, Cross-Sectional Studies, Bangladesh, Female, Male, Young Adult, Adult, Students, Medical psychology, Students, Medical statistics & numerical data, Education, Medical, Undergraduate, Biomedical Research, Career Choice
Abstract: Background: The involvement of undergraduate medical students in research is pivotal for the advancement of evidence-based clinical practice. This study aimed to assess the extent of research involvement and the factors influencing it among undergraduate medical students in Bangladesh., Methods: A multi-center cross-sectional study involving 2864 medical students from both public and private medical colleges was conducted between June and December 2023. Data on demographics, research involvement, participation in research training, future career aspirations in research, and obstacles encountered by students were collected. Statistical analyses were performed using SPSS 25., Results: The mean age of the students was 21.8 ± 1.8 (SD) years, with the majority being female (61.8%). Overall, 21.5% (n = 617) were actively participating in research beyond academic activities. Approximately 7% (n = 205) had undergone formal research training, and 6.5% (n = 187) had experience in publications in peer-reviewed journals as first authors or coauthors. A total of 45.5% of the students faced multiple challenges during participating in research, with the two most difficult tasks being designing a study (26.7%) and data collection and recruitment of study participants (19.6%). Almost half of the students (47.2%, n = 1352) showed an interest in pursuing a research career in the near future. The primary barriers preventing students from choosing a future research career were insufficient mentorship (16.3%), the perception of a lengthy career path (17.2%), and limited funding opportunities (15.9%). Factors that significantly encouraged research involvement included being male (adjusted odds ratio [aOR] 1.5, 95% CI: 1.2-1.8), studying in the senior academic phase (aOR 3.9, 95% CI: 2.7-5.6), previous education from an English-medium educational institute (aOR 1.8, 95% CI: 1.2-2.2), and encouragement from faculty (aOR 1.4, 95% CI: 1.1-1.7)., Conclusion: The proportion of research participation among the students was relatively low. To promote research engagement among undergraduate medical students in Bangladesh, comprehensive policy formulation and strong commitment at the highest levels are essential. Integrating national research policy into the curriculum could serve as a strategic measure for achieving this objective., Competing Interests: Declarations. Ethics approval and consent to participate: The study was approved by the Ethical Review Committee of Public Health Foundation Bangladesh. Informed written consent was obtained from all eligible participants who agreed to participate. The authors declare that no human subjects were harmed, and the procedures followed were in accordance with the ethical standards and regulations established by the Helsinki Declaration of the World Medical Association. Use of AI: Chat-GPT 3 was used to improve the clarity of the manuscript and for language editing. Consent for publication: Not applicable. Competing interests: The authors declare no competing interests., (© 2024. The Author(s).)
Published: 2025
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26. Janus Films Wound Dressing Comprising Electrospun Gelatin/PCL Nanofibers and Gelatin/Honey/Curcumin Thawed Layer.

Author: Kheradvar Kolour A, Ghoraishizadeh S, Zaman MS, Alemzade A, Banavand M, Esmaeili J, and Shahrousvand M
Subjects: Animals, Particle Size, Gelatin chemistry, Curcumin chemistry, Curcumin pharmacology, Nanofibers chemistry, Bandages, Honey, Wound Healing drug effects, Materials Testing, Biocompatible Materials chemistry, Biocompatible Materials pharmacology, Polyesters chemistry
Abstract: A promising approach for wound treatment is using multilayer wound dressings that offer multifunctional properties. In this study, a bilayered electrospun/hydrogel gelatin-based scaffold integrated with honey and curcumin was developed to treat wounds under an in vivo study. The first layer consisted of an enzymatic cross-linked gelatin hydrogel containing honey and curcumin, which gelatin/PCL nanofibers reinforced. The physicochemical, mechanical, and biological properties of both layers were evaluated. Then, the bilayered wound dressing was compared to a commercial wound dressing in an in vivo study. The results showed that this strategy provided the wound dressing with a strength of 40 MPa, 70% elongation, 800% swelling rate, and 8 g/h/m 2 water vapor permeability. Furthermore, MTT and histopathological staining demonstrated that the bilayered wound dressing promoted wound closure accelerated collagen production and tissue granulation, and promoted immune system response and re-epithelialization compared to other groups. The presence of a nanofibrous layer on the surface of the wound dressing facilitated its use, and the inclusion of honey and gelatin in the hydrogel layer prevented adhesion to the wound tissue and allowed for easy replacement without damaging the wound bed. Overall, the bilayered dressing with multifunctional properties holds great potential for developing wound dressings.
Published: 2024
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27. Distinctive expression and cellular localisation of zinc homeostasis-related proteins in breast and prostate cancer cells.

Author: Barman SK, Nesarajah AN, Zaman MS, Malladi CS, Mahns DA, and Wu MJ
Subjects: Humans, Male, Female, Cell Line, Tumor, Metallothionein metabolism, Metallothionein genetics, Cation Transport Proteins metabolism, Cation Transport Proteins genetics, Gene Expression Regulation, Neoplastic, Prostatic Neoplasms metabolism, Prostatic Neoplasms pathology, Prostatic Neoplasms genetics, Zinc metabolism, Breast Neoplasms metabolism, Breast Neoplasms pathology, Breast Neoplasms genetics, Homeostasis
Abstract: Background: Zinc transport proteins (ZIP and ZnT), metallothioneins (MT) and protein kinase CK2 are involved in dysregulation of zinc homeostasis in breast and prostate cancer cells. Following up our previous research, we targeted ZIP12, ZnT1, MT2A and CK2 in this study by investigating their expression levels and protein localisation., Methods: Quantitative reverse transcription polymerase chain reaction (qRT-PCR) and immunofluorescence confocal microscopy were employed to quantify the expression of ZIP12, ZnT1, MT2A and CK2 subunits in a panel of breast and prostate cell lines without or with extracellular zinc exposure. The cellular localisations of these target proteins were also examined by immunofluorescence confocal microscopy., Results: In response to the extracellular zinc exposure, the gene expression was elevated for SLC39A12 (ZIP12), SLC30A1 (ZnT1) and MT2A (MT2A) in normal prostate epithelial cells (RWPE-1) in contrast to their cancerous counterparts (PC3 and DU145), whilst the gene expression was higher for SLC39A12 (ZIP12) and SLC30A1 (ZnT1) in both normal (MCF10A) and basal breast cancer cells (MDA-MB-231) compared to luminal breast cancer cells (MCF-7). At the protein level, the expression for both ZIP12 and ZnT1 was trending lower in the time course for the breast cancer cells whilst their expression was remained constant in the normal breast epithelial cells. The expression of ZIP12 in prostate cancer cells was higher than the normal prostate cells. The protein expression for CK2 α/αꞌ and CK2β was markedly higher in prostate cancer cells than the normal prostate cells. Upon extracellular zinc exposure, ZIP12 was, for the first time, conspicuously localised in the plasma membrane of breast cancer cells but not in normal breast epithelial cells and prostate cells. ZnT1 is only localised in the plasma membrane of breast cancer cells. MT2A is distinctively seen close to the plasma membrane in breast cancer cells. CK2 is also for the first time shown to be localised in proximity to the plasma membrane of breast cancer cells., Conclusion: The findings, particularly the localisation of ZIP12 and CK2, are novel and significant for our understanding of zinc homeostasis in breast and prostate cancer cells., Competing Interests: Declaration of Competing Interest The authors declare no conflict of interest., (Copyright © 2024 The Authors. Published by Elsevier GmbH.. All rights reserved.)
Published: 2024
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28. Medical aesthetic awareness among public in Malaysia and the factors that may influence it: A cross-sectional study.

Author: Allan YTH, Richard KFN, Nur Dianah F, Prathishaa J, Syafiqa Nur 'Ukail S, Ernieda Md H, Muhammad Farhan AR, Ungku Mohd Zaman MS, and Adibah HI
Abstract: Introduction: Medical aesthetic practice is growing rapidly in Malaysia due to rising market demand, yet public understanding of these practices remains limited. This study evaluated the awareness and attitudes towards medical aesthetics among Malaysians., Methods: A cross-sectional survey was conducted among individuals aged > 18 years old in Malaysia from December 2021 to May 2022. The survey was distributed both online and in public settings. The survey comprised of respondents' sociodemographic, perception of physical attractiveness, knowledge and attitude towards medical aesthetic practices. The factors influencing respondents' attitudes towards medical aesthetic practices in the country were analysed using binary logistic regression, with the significance level set at P<0.05., Results: A total of 382 respondents participated in this study with average age of 30.81 (±9.38) years, ranging from 18 to 68 years. The majority were women (77.5%), Malay (53.7%) and Muslim (57.1%). Although most respondents had no prior experience in medical aesthetic treatment (68.1%), 76.2% respondents demonstrated good knowledge and 70.2% had positive attitude towards these services. Additionally, 53.9% of the respondents highly valued the importance of physical attractiveness. The Buddhists and Hindus exhibited more positive attitude than the Muslims. Conversely, those who placed higher importance on physical attractiveness were 0.5 times less likely to develop a positive attitude towards medical aesthetic services., Conclusion: In conclusion, despite limited experience in medical aesthetic treatments and practice, most Malaysians possess good knowledge and positive attitudes towards medical aesthetics, indicating a growing interest and potential willingness to consider these services for enhancing their appearance., Competing Interests: The authors have no conflicts of interest to declare., (© Academy of Family Physicians of Malaysia.)
Published: 2024
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29. Violence against physicians working in public tertiary care hospital of Bangladesh: a facility-based cross-sectional study.

Author: Hasan MJ, Sarkar TY, Ahmed M, Banik A, Islam S, Zaman MS, Mahmud F, Paul A, Sakib MN, Dev A, Hossain MJ, Fardous J, Nishat NH, and Rahman M
Subjects: Humans, Male, Adult, Cross-Sectional Studies, Tertiary Care Centers, Bangladesh, Surveys and Questionnaires, Workplace psychology, Prevalence, Physicians psychology, Workplace Violence
Abstract: Background: Violence against physicians in the workplace is a prevalent global issue, and Bangladesh is no exception. Such violence significantly disrupts healthcare delivery and the attainment of universal health coverage. This study aimed to comprehensively evaluate the prevalence, nature and associated risk factors of workplace violence (WPV) against physicians in Bangladesh., Methods: This descriptive cross-sectional study was conducted at a public tertiary care hospital involving 441 physicians with a minimum tenure of 6 months. Data were gathered through a structured self-reported questionnaire, and statistical analyses were performed by using SPSS V.25., Results: Out of the surveyed physicians, 67.3% (n=297) reported experiencing violence, categorised as 84.5% psychological, 13.5% physical and 2% sexual in nature. Predominant forms of psychological violence included bullying (48.8%) and threats (40.1%). The mean age of exposed physicians was 32.5±4.3 (SD) years. Those working in the emergency unit (45.8%), surgery and allied departments (54.2%), engaging in rotating shift work (70%), morning shifts (59.6%) and postgraduate trainees (68%) were frequently subjected to violence. Factors significantly associated with WPV included placement in surgery and allied departments (p<0.001), working rotating shifts (p<0.001), marital status (p=0.011) and being a male physician (p=0.010). Perpetrators were primarily identified as relatives of patients (66%). Working in rotating shifts (adjusted OR(AOR):2.6, 95% CI:1.2 to 5.4) and surgery and allied departments (AOR:5.7, 95% CI:3.4 to 9.8) emerged as significant risk factors of violence against physicians., Conclusion: A higher proportion of physicians at the early to mid-level stages of their careers, especially those in rotating shifts and surgery-related departments, reported incidence of WPV. Urgent intervention from policy-makers and healthcare entities is imperative to implement preventive measures. Strengthening security measures, establishing antiviolence policies and providing comprehensive training programmes are crucial steps towards ensuring a safer work environment for healthcare professionals., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2024. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)
Published: 2024
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30. Exploring the anodic performance of ScSeS and TiSeS monolayers of modified transition metal dichalcogenides for Mg ion batteries via DFT calculations.

Author: Rifah SS, Zaman MS, Piya AA, and Shamim SUD
Abstract: Due to the significant ambient abundance of magnesium metal and the divalent nature of the magnesium ion, rechargeable magnesium-ion batteries are a strong candidate to fulfill the forthcoming demands for electrical energy storage in both extensive mobile and stationary applications. Transition metal dichalcogenides (TMDs) are still regarded as newcomers within the realm of 2D nanomaterials, particularly in the context of their applications in energy storage. Here, we report a DFT-based analysis on TMDs as anode materials in Mg ion batteries using the GGA-PBE exchange-correlation functional. This study investigates the structural, electronic and adsorption behavior of ScSeS and TiSeS nanosheets. All predicted TMDs adsorbed Mg-atoms with favorable adsorption energy ( E ads ) without any noticeable structural distortion, exhibiting good structural stability. For three distinct adsorption sites, top of the transition metal (Sc, Ti), Se and S, the E ads are calculated as -3.74 eV, -3.62 eV, -3.40 eV and -1.23 eV, -1.38 eV, -0.91 eV, which indicates that E ads is higher when the Mg ion is adsorbed at the Sc and Se atomic sites, respectively. The E ads for ScSeS are almost two times the E ads for TiSeS. In the band structure, it is seen that for both ScSeS and TiSeS, the conduction band crosses the Fermi level, which implies the metallic behavior of the nanosheets. Furthermore, they show a maximum theoretical specific capacity of about 686.18 mA h g -1 and 546.63 mA h g -1 , which is almost two times higher than that of the bulk graphite anode material. The average open circuit voltages are calculated as 0.43 V and 0.11 V for ScSeS and TiSeS, respectively.
Published: 2024
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31. A dataset on social media users' engagement with religious misinformation.

Author: Al-Zaman MS and Noman MMS
Abstract: This dataset comprises Facebook data on five cases of religious misinformation in Bangladesh. To the best of our knowledge, it is the first publicly accessible dataset on Facebook-based religious misinformation in the country, featuring 7350 comments contributed by unique users. As online religious misinformation has been implicated in causing interreligious violence and tension in Bangladesh, this dataset can offer crucial insights into how social media is being exploited to foment such events. It may also help advance policy reform and activism to protect human rights and prevent the spread of religious misinformation., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2023 The Author(s).)
Published: 2023
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32. Fc-competent multispecific PDL-1/TIGIT/LAG-3 antibodies potentiate superior anti-tumor T cell response.

Author: Yang R, Huang S, Huang C, Fay NS, Wang Y, Putrevu S, Wright K, Zaman MS, Cai W, Huang B, Wang B, Wright M, Hoag MR, Titong A, and Liu Y
Subjects: Animals, Humans, Nivolumab, Receptors, Immunologic, Immunotherapy, T-Lymphocytes, Neoplasms therapy, Melanoma
Abstract: The landscape of current cancer immunotherapy is dominated by antibodies targeting PD-1/PD-L1 and CTLA-4 that have transformed cancer therapy, yet their efficacy is limited by primary and acquired resistance. The blockade of additional immune checkpoints, especially TIGIT and LAG-3, has been extensively explored, but so far only a LAG-3 antibody has been approved for combination with nivolumab to treat unresectable or metastatic melanoma. Here we report the development of a PDL1 × TIGIT bi-specific antibody (bsAb) GB265, a PDL1 × LAG3 bsAb GB266, and a PDL1 × TIGIT × LAG3 tri-specific antibody (tsAb) GB266T, all with intact Fc function. In in vitro cell-based assays, these antibodies promote greater T cell expansion and tumor cell killing than benchmark antibodies and antibody combinations in an Fc-dependent manner, likely by facilitating T cell interactions (bridging) with cancer cells and monocytes, in addition to blocking immune checkpoints. In animal models, GB265 and GB266T antibodies outperformed benchmarks in tumor suppression. This study demonstrates the potential of a new generation of multispecific checkpoint inhibitors to overcome resistance to current monospecific checkpoint antibodies or their combinations for the treatment of human cancers., (© 2023. The Author(s).)
Published: 2023
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33. Pyrazoline scaffold: hit identification to lead synthesis and biological evaluation as antidiabetic agents.

Author: Sharma S, Rehman Ansari MH, Sharma K, Singh RK, Ali S, Alam MM, Zaman MS, Alam P, and Akhter M
Subjects: Rats, Animals, Rats, Wistar, Glucose Tolerance Test, Molecular Docking Simulation, Structure-Activity Relationship, Hypoglycemic Agents pharmacology, Aminosalicylic Acids
Abstract: Background: Mining of novel scaffolds as potential DPP-IV inhibitors for future development of potential candidates as antidiabetic agents to address global issues. Methodology: The identified hit KB-10 from a previously reported study was taken as a lead for designing a library of analogues and screened initially based on in silico parameters and docking score. A series of selected (2[4-(1-acetyl-5-phenyl-4,5-dihydro-1 H -pyrazol-3-yl)phenoxy]-1-phenylethanone derivatives were synthesized and evaluated through in vitro studies. Compounds KB-23 , KB-22 and KB-06 were found to be as potent, with IC 50 values of 0.10 μM, 0.12 μM and 0.35 μM, respectively. They also showed promising antihyperglycemic potential in in vivo studies (oral glucose tolerance tests) in Wistar rats. Conclusion: This work establishes pyrazoline analogues KB-23 , KB-22 and KB-06 as promising starting points for the development of potential antidiabetic agents.
Published: 2023
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34. Thwarted belongingness, perceived burdensomeness, and acquired capability for suicide among university students of Bangladesh: Scales validation and status assessment.

Author: Arafat SMY, Hussain F, Zaman MS, Tabassum T, Islam MK, Shormi FR, Khan AR, Islam MR, Redwan ASM, Giasuddin NA, Mubashir A, and Khan MAS
Abstract: Background: Identification of prior mental events of suicide attempts has immense importance in suicide prevention. However, it has not been studied in Bangladesh as there was no available psychometrically valid instrument measuring it., Objectives: We aimed to test the psychometric properties of the interpersonal needs questionnaire (INQ-15) and acquired capability for suicide scale-fearlessness about death (ACSS-FAD) in Bangla along with the determination of the level of thwarted belongingness, perceived burdensomeness, and acquired capability for suicide., Materials and Methods: We collected data between 29 March and 14 April 2022 from 1,207 students of medical colleges and universities in Bangladesh by Google form . We assessed the psychometric properties of Bangla INQ and ACSS-FAD scales and examined factors associated with thwarted belongingness, perceived burdensomeness, and acquired capability for suicide., Results: The mean age of the participants was 22.82 ± 1.68 (range 18-29) years, 51% were females, 84% were graduate students, and 92% were unmarried. Both of the scales revealed acceptable levels of reliability. Confirmatory factor analysis revealed a two-factor structure of Bangla INQ after dropping three items from thwarted belongingness domain (item 9, 11, and 12) and a single factor structure for Bangla ACSS-FAD after dropping three items (item 1, 4, and 6). Perceived burdensomeness was significantly higher in females, students with a history of mental illness, family history of suicide, and the history of suicidal attempts. Fearlessness about death was significantly higher among females, non-Muslim participants, and history of suicidal attempts., Conclusion: The current study revealed psychometric properties of two suicide scales (INQ and ACSS-FAD) in Bangla that can be used in subsequent studies. Prevention strategies targeting to females, persons with psychiatric disorder, history of previous attempt(s) should be prioritized specially among the young age group., Competing Interests: Authors MZ, TT, and MK were employed by Pi Research Consultancy Center. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Arafat, Hussain, Zaman, Tabassum, Islam, Shormi, Khan, Islam, Redwan, Giasuddin, Mubashir and Khan.)
Published: 2022
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35. Expression profiles of the genes associated with zinc homeostasis in normal and cancerous breast and prostate cells.

Author: Barman SK, Zaman MS, Veljanoski F, Malladi CS, Mahns DA, and Wu MJ
Subjects: Homeostasis, Humans, Male, Metallothionein metabolism, Prostate metabolism, Prostate pathology, Zinc metabolism, Breast Neoplasms metabolism, Prostatic Neoplasms genetics, Prostatic Neoplasms metabolism
Abstract: Zn2+ dyshomeostasis is an intriguing phenomenon in breast and prostate cancers, with breast cancer cells exhibiting higher intracellular Zn2+ level compared to their corresponding normal epithelial cells, in contrast to the low Zn2+ level in prostate cancer cells. In order to gain molecular insights into the zinc homeostasis of breast and prostate cancer cells, this study profiled the expression of 28 genes, including 14 zinc importer genes (SLC39A1-14) that encode Zrt/Irt-like proteins 1-14 to transport Zn2+ into the cytoplasm, 10 zinc exporter genes (SLC30A1-10) which encode Zn2+ transporters 1-10 to transport Zn2+ out of the cytoplasm, and 4 metallothionein genes (MT1B, MT1F, MT1X, MT2A) in breast (MCF10A, MCF-7, MDA-MB-231) and prostate (RWPE-1, PC3, DU145) cell lines in response to extracellular zinc exposures at a mild cytotoxic dosage and a benign dosage. The RNA samples were prepared at 0 min (T0), 30 min (T30), and 120 min (T120) in a time course with or without zinc exposure, which were used for profiling the baseline and dynamic gene expression. The up-regulation of MT genes was observed across the breast and prostate cancer cell lines. The expression landscape of SLC39A and SLC30A was revealed by the quantitative reverse transcription polymerase chain reaction data of this study, which sheds light on the divergence of intracellular Zn2+ levels for breast and prostate cancer cells. Taken together, the findings are valuable in unraveling the molecular intricacy of zinc homeostasis in breast and prostate cancer cells., (© The Author(s) 2022. Published by Oxford University Press.)
Published: 2022
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36. Molecular details of aluminium-amyloid β peptide interaction by nuclear magnetic resonance.

Author: Petersingham G, Zaman MS, Johnson AJ, Reddy N, Torres AM, and Wu MJ
Subjects: Amino Acid Sequence, Copper chemistry, Humans, Magnetic Resonance Spectroscopy, Peptide Fragments chemistry, Aluminum chemistry, Alzheimer Disease metabolism, Amyloid beta-Peptides chemistry
Abstract: Alzheimer's disease (AD) is a devastating neurodegenerative condition that poses major challenges to human health. Both amyloid β (Aβ) and metal ions such as aluminium are implicated in the development of AD. By the means of NMR, the interactions of Al 3+ with Aβ 1-28 peptide as well as the Aβ 1-28 analogues were studied, and the key binding sites of Al 3+ in Aβ determined. NMR data showed Al 3+ interacts with Aβ 1-28 at the NH and αH of numerous residues by exhibiting upfield shifts. Using Aβ analogues where His6, His13 and His14 were individually replaced by alanine residue(s), including Aβ H6A, Aβ H13A, Aβ H14A, and Aβ H6,13,14A, the results demonstrated that the histidine residues (His6, His13 and His14) and N-terminal Asp1 were involved in the Al 3+ coordination. These findings provide, for the first time, the details of the molecular interaction between Al 3+ and Aβ, which points to the potential role of Al 3+ in Aβ aggregation, hence in AD development., (© 2022. The Author(s), under exclusive licence to Springer Nature B.V.)
Published: 2022
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37. Empowered patient: A program to improve people with Parkinson's communication with health care professionals.

Author: Zaman MS, Ghahari S, and McColl MA
Abstract: Background: Communication breakdown between patients and health care professionals poses an accessibility gap preventing adequate health care. The Empowered Patient Program was developed to support people with Parkinson's in improving their health communication skills/strategies and thus facilitate the accessibility gap in their care., Objective: Our pilot study aimed to test the feasibility and preliminary effect of the Empowered Patient Program within a small cohort of individuals with Parkinson's disease., Methods: We completed a pre-test-post-test pilot study. Eight participants completed the Empowered Patient Program for this pilot study. Data collection was completed by administering a questionnaire prior to the program, immediately after program completion, and three months post-completion. We additionally conducted two telephone interviews with the participants to qualitatively gather feedback on the program., Results: The program elucidated statistically significant improvement across domains/areas of knowledge (p = 0.01) and self-perceived communication skills (p = 0.04) among the participants. Through feedback from the patient interviews, it was confirmed that these significant improvements were owed largely to the high level of organization, intuitive user interface, and suitable content of the program for this cohort., Conclusions: The Empowered Patient Program pilot resulted in a desired outcome indicating its satisfactory development. The next steps are to test the Empowered Patient program in a larger sample., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2022 The Authors.)
Published: 2022
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38. Prevalence of type 2 diabetes and pre-diabetes among pulmonary and extrapulmonary tuberculosis patients of Bangladesh: A cross-sectional study.

Author: Sheuly AH, Arefin SMZH, Barua L, Zaman MS, and Chowdhury HA
Subjects: Bangladesh epidemiology, Cross-Sectional Studies, Humans, Prevalence, Diabetes Mellitus, Type 2 complications, Diabetes Mellitus, Type 2 epidemiology, Hyperglycemia, Prediabetic State epidemiology, Tuberculosis diagnosis, Tuberculosis epidemiology, Tuberculosis, Pulmonary epidemiology
Abstract: Background: We aimed to determine the prevalence of type 2 diabetes (T2D) and pre-diabetes (pre-DM) among patients with pulmonary tuberculosis (PTB) and extrapulmonary tuberculosis (EPTB) in Bangladesh. We also examined the association between type of TB and hyperglycaemia as an adjunct to the primary objective., Materials and Methods: This cross-sectional analytical study recruited 350 TB patients (175 PTB and 175 EPTB) from two tertiary care hospitals specialized for TB treatment. Oral glucose tolerance tests and fasting plasma glucose measurements were carried out for unknown glycaemic status and those with previously known diabetes, respectively., Results: Overall, the prevalence of T2D and pre-DM was 19.1% (new 85.1%, old 14.9%) and 34.3%, respectively. Although the risk factors were highly prevalent among the patients with EPTB, a higher proportion of T2D (26.3%) and pre-DM (34.3%) was detected among the patients with PTB. The proportion of impaired fasting glucose was low in both groups, but a high trend of impaired glucose tolerance was observed across the groups, with a higher proportion (35.4%) in the PTB group. Both pre-DM and T2D showed significantly higher odds (pre-DM, AOR: 4.488; CI: 2.531-7.958; p < .001 and T2D, AOR: 4.280; CI: 2.305-7.946; p < .001) for having PTB., Conclusion: The prevalence of T2D and pre-DM was higher among the patients with PTB, and it (PTB) appeared as a predictor of hyperglycaemia. It indicates the primary intervention should target the patients with PTB to get the maximum benefit of screening to reduce the number of risk factors, disease burden and subsequent complications., (© 2022 The Authors. Endocrinology, Diabetes & Metabolism published by John Wiley & Sons Ltd.)
Published: 2022
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39. Social mediatization of religion: islamic videos on YouTube.

Author: Al-Zaman MS
Abstract: Based on the conceptual framework of social mediatization of religion, this paper seeks to understand three pertinent phenomena: trends of online religious content, users' engagement with them, and correlations between interaction indicators. To answer the research inquiries, we quantitatively analyzed 73,120 Islamic videos uploaded on YouTube in 2011-2020. The result shows that Islamic videos on YouTube are growing continuously without any decline, from 6.04% in 2011 to 13.11% in 2019, more than two-fold in eight years. Also, with a strong positive correlation, comments and likes ( r = .862; p < .01) are increasing at a remarkable rate than the other interaction variables. We observed that users who watch Islamic videos are more likely to like the videos than to dislike them. Users' engagement is not related to the length of Islamic videos in any significant way. These two results partly suggest users' positive and supportive attitudes toward online Islamic videos. Finally, this study recommends investigating the thematic temporal distribution of Islamic videos for an in-depth understanding of the users' topical interest patterns., Competing Interests: The authors declare no conflict of interest., (© 2022 The Author(s).)
Published: 2022
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40. Intravenous iron sucrose vs. blood transfusion in the management of moderate postpartum iron deficiency anemia: A non-randomized quasi-experimental study.

Author: Hye RA, Sayeeda N, Islam GMR, Mitu JF, and Zaman MS
Abstract: Introduction: Postpartum anemia is often over-treated with blood transfusion without clear indication despite having a potential alternative of parenteral iron therapy. The present study aimed to compare the efficacy of intravenous (IV) iron sucrose with blood transfusion in increasing the hematological parameters in postpartum women with moderate anemia., Methods: This prospective non-randomized quasi-experimental study was conducted among 44 hemodynamically stable postpartum women with moderate anemia (Hb 7-8 g/dl) in the Obstetrics department of Dhaka Medical College Hospital (DMCH) from January to June 2021. Among them, 22 patients received 600 mg of IV iron sucrose after 48 h of delivery for three subsequent days and the other 22 patients received two units of blood transfusion after 48 h of delivery in two subsequent days. The primary endpoint was increase in Hemoglobin (Hb) and serum ferritin level after 6 weeks of the intervention. Two-way repeated measures ANOVA (mixed factor ANOVA) was applied to compare between before and after effect in the two intervention groups., Results: Baseline Hb and ferritin were 7.4 g/dl and 73.5 μg/l in IV iron group and 7.3 g/dl and 73.2 μg/l in blood transfusion group. Mean Hb level was increased 4.2 g/dl in IV iron sucrose group and 4.5 g/dl in blood transfusion group at sixth week. Besides, serum ferritin level was increased 40.5 μg/l and 44.8 μg/l after six weeks in IV iron sucrose group and blood transfusion group respectively. Other hematological parameters like reticulocyte count, MCV, MCH, and MCHC also increased significantly after intervention in both groups. However, no significant difference was noticed in the change of hematological parameters in between the groups., Conclusions: The IV iron sucrose is as effective as blood transfusion in replenishing the hemoglobin and iron storage status in hemodynamically stable women with moderate post-partum anemia. This could be an effective alternative of blood transfusion in treating these patients, especially in resource-poor settings., Competing Interests: The authors declare no conflict of interest., (© 2022 The Author(s).)
Published: 2022
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41. Evidence-Based Mechanical Ventilatory Strategies in ARDS.

Author: Liaqat A, Mason M, Foster BJ, Kulkarni S, Barlas A, Farooq AM, Patak P, Liaqat H, Basso RG, Zaman MS, and Pau D
Abstract: Acute respiratory distress syndrome (ARDS) remains one of the leading causes of morbidity and mortality in critically ill patients despite advancements in the field. Mechanical ventilatory strategies are a vital component of ARDS management to prevent secondary lung injury and improve patient outcomes. Multiple strategies including utilization of low tidal volumes, targeting low plateau pressures to minimize barotrauma, using low FiO 2 (fraction of inspired oxygen) to prevent injury related to oxygen free radicals, optimization of positive end expiratory pressure (PEEP) to maintain or improve lung recruitment, and utilization of prone ventilation have been shown to decrease morbidity and mortality. The role of other mechanical ventilatory strategies like non-invasive ventilation, recruitment maneuvers, esophageal pressure monitoring, determination of optimal PEEP, and appropriate patient selection for extracorporeal support is not clear. In this article, we review evidence-based mechanical ventilatory strategies and ventilatory adjuncts for ARDS.
Published: 2022
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42. Fast Posterior Estimation of Cardiac Electrophysiological Model Parameters via Bayesian Active Learning.

Author: Zaman MS, Dhamala J, Bajracharya P, Sapp JL, Horácek BM, Wu KC, Trayanova NA, and Wang L
Abstract: Probabilistic estimation of cardiac electrophysiological model parameters serves an important step toward model personalization and uncertain quantification. The expensive computation associated with these model simulations, however, makes direct Markov Chain Monte Carlo (MCMC) sampling of the posterior probability density function (pdf) of model parameters computationally intensive. Approximated posterior pdfs resulting from replacing the simulation model with a computationally efficient surrogate, on the other hand, have seen limited accuracy. In this study, we present a Bayesian active learning method to directly approximate the posterior pdf function of cardiac model parameters, in which we intelligently select training points to query the simulation model in order to learn the posterior pdf using a small number of samples. We integrate a generative model into Bayesian active learning to allow approximating posterior pdf of high-dimensional model parameters at the resolution of the cardiac mesh. We further introduce new acquisition functions to focus the selection of training points on better approximating the shape rather than the modes of the posterior pdf of interest. We evaluated the presented method in estimating tissue excitability in a 3D cardiac electrophysiological model in a range of synthetic and real-data experiments. We demonstrated its improved accuracy in approximating the posterior pdf compared to Bayesian active learning using regular acquisition functions, and substantially reduced computational cost in comparison to existing standard or accelerated MCMC sampling., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2021 Zaman, Dhamala, Bajracharya, Sapp, Horácek, Wu, Trayanova and Wang.)
Published: 2021
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43. Diverse Manifestations of COVID-19: Some Suggested Mechanisms.

Author: Zaman MS and Sizemore RC
Subjects: Humans, Lung, Pandemics, SARS-CoV-2, COVID-19
Abstract: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the cause of the novel respiratory disease COVID-19, has reached pandemic status and presents a wide range of manifestations of diverse magnitude, including fever, cough, shortness of breath, and damage to vital organs, such as the heart, lung, kidney, and brain. Normally, older individuals and those with underlying health issues are more at risk. However, about 40% of COVID-19 positive individuals are asymptomatic. This review aims to identify suggested mechanisms of diverse manifestations of COVID-19. Studies suggest that T cell-mediated immunity and specific and/or nonspecific immunity from other vaccines could protect against SARS-CoV-2. The potential role of cross-reacting antibodies to coronaviruses that cause the common cold, mumps virus, polio virus, and pneumococcal bacteria are also suggested to help protect against COVID-19. Decreased production of Type I interferons (IFN-α and IFN-β) could also be linked to COVID-19 manifestations. Several studies suggest that ACE2 cell membrane receptors are involved in SARS-CoV-2 infection. However, the relationship between an abundance of ACE2 receptors and the infectivity of the virus is unknown. Unlocking these manifestation mysteries could be crucial as this could help researchers better understand the virulence, pathology, and immune responses associated with SARS-CoV-2, leading to the development of effective therapies and treatment plans.
Published: 2021
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44. Transcriptomic insights into the zinc homeostasis of MCF-7 breast cancer cells via next-generation RNA sequencing.

Author: Zaman MS, Barman SK, Corley SM, Wilkins MR, Malladi CS, and Wu MJ
Subjects: Apoptosis, Biomarkers, Tumor genetics, Breast Neoplasms drug therapy, Breast Neoplasms genetics, Breast Neoplasms pathology, Cell Proliferation, Female, Humans, MCF-7 Cells, Biomarkers, Tumor metabolism, Breast Neoplasms metabolism, Gene Expression Regulation, Neoplastic drug effects, High-Throughput Nucleotide Sequencing methods, Homeostasis, Transcriptome drug effects, Zinc pharmacology
Abstract: A significant gap in the knowledge of zinc homeostasis exists for breast cancer cells. In this study, we investigated the transcriptomic response of the luminal breast cancer cells (MCF-7) to the exposure of extracellular zinc using next-generation RNA sequencing. The dataset was collected for three time points (T0, T30, and T120) in the time course of zinc treatment, which revealed the dramatic increase, up to 869-fold, of the gene expression for metallothioneins (MT1B, MT1F, MT1X, and MT2A) and the zinc exporter ZnT1 (SLC30A1) at T30, continuingly through to T120. The similar dynamic expression pattern was found for the autophagy-related gene (VMP1) and numerous genes for zinc finger proteins (e.g. RNF165, ZNF365, ZBTB2, SNAI1, ZNF442, ZNF547, ZNF563, and ZNF296). These findings point to the all-hands-on-deck strategy adopted by the cancer cells for maintaining zinc homeostasis. The stress responsive genes encoding heat shock proteins (HSPA1A, HSPA1B, HSPA1L, HSPA4L, HSPA6, HSPA8, HSPH1, HSP90AA1, and HSP90AB1) and the MTF-1 biomarker genes (AKR1C2, CLU, ATF3, GDF15, HMOX1, MAP1A, MAFG, SESN2, and UBC) were also differentially up-regulated at T120, suggesting a role of heat shock proteins and the MTF-1 related stress proteins in dealing with zinc exposure. It is for the first time that the gene encoding Polo-like kinase 2 (PLK2) was found to be involved in zinc-related response. The top differentially expressed genes were validated by qRT-PCR and further extended to the basal type breast cancer cells (MDA-MB-231). It was found that the expression level of SLC30A1 in MDA-MB-231 was higher than MCF-7 in response to zinc exposure. Taken together, the findings contribute to our knowledge and understanding of zinc homeostasis in breast cancer cells., (© The Author(s) 2021. Published by Oxford University Press.)
Published: 2021
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45. Letter to the Editor: COVID-19 'Solutions' in Bangladesh.

Author: Al-Zaman MS
Subjects: Bangladesh epidemiology, COVID-19 pathology, COVID-19 virology, Humans, SARS-CoV-2 isolation & purification, Social Media, COVID-19 epidemiology, Public Health
Abstract: Competing Interests: The author has no potential conflicts of interest to disclose.
Published: 2021
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46. Social media and COVID-19 misinformation: how ignorant Facebook users are?

Author: Al-Zaman MS
Abstract: The COVID-19 pandemic has claimed a lot of lives around the world, not only with the virus but also with misinformation. Many researchers have investigated COVID-19 misinformation, but none of them was related to social media users' diverse responses to different types of COVID-19 misinformation, which could be a timely exploration. To bridge this gap in scholarly literature, the present study based on 11,716 comments from 876 Facebook posts on five COVID-19 misinformation seeks to answer two relevant research questions: (a) How ignorant social media users are about misinformation? (b) How do they react to different types of misinformation? Following a quantitative content analysis method, this study produces a few novel findings. The results show that most of the users trust misinformation (60.88%), and fewer can deny (16.15%) or doubt (13.30%) the claims based on proper reasons. The acceptance of religious misinformation (94.72%) surpassed other types of misinformation. Most of the users react happily (34.50%) to misinformation: the users who accept misinformation are mostly happy (55.02%) because it may satisfy their expectations, and the users who distrust misinformation are mostly angry (44.05%) presuming it may cause harm to people. The chi-square and phi coefficient values show strong positive and significant associations between the themes, levels of ignorance, and reactions to misinformation. Some strengths, limitations, and ethical concerns of this study have also been discussed., Competing Interests: The authors declare no conflict of interest., (© 2021 The Author(s).)
Published: 2021
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47. Association of Low Serum Free Testosterone with Carotid Atherosclerosis in Male.

Author: Nahid KA, Akter K, Saqueeb SN, Zaman MS, Khalilullah MI, Jesmin S, Iqbal MG, Islam MA, Wadud MA, Aziz AS, and Hoque MM
Subjects: Bangladesh, Carotid Arteries, Cross-Sectional Studies, Humans, Male, Testosterone, Carotid Artery Diseases diagnostic imaging
Abstract: The cross sectional descriptive type of observational study was aimed to evaluate the association of serum free testosterone in 59 patients of carotid atherosclerotic male {<50% stenosis (n=26); >50% stenosis (n=33) } from March 2015 to February 2016 in the Department of Radiology & Imaging of Bangabandhu Sheikh Mujib Medical University (BSMMU) & National Institute of Neurosciences (NINS), Dhaka, Bangladesh. Twenty seven patients who had normal carotid doppler findings were taken as control. Serum total testosterone and sex hormone binding globulin was measured by chemiluminescence micro particle immunoassay and free testosterone was done by using Vermeulen formula. Concentration of free testosterone differed significantly among groups (p=0.004) and it was significantly lower in <50% stenosed group. Logistic regression analysis revealed that low free testosterone (free testosterone ≤0.24 nmol/L) was independently associated with development of carotid atherosclerosis (p=0.04, OR 3.07, 95% CI 1.14-9.30). In conclusion low serum free testosterone was associated with carotid atherosclerosis in male.
Published: 2021

48. Comparative lipid and uric acid suppressing properties of four common herbs in high fat-induced obese mice with their total phenolic and flavonoid index.

Author: Mazumder T, Mamun IP, Zaman MS, Islam AKMK, Chowdhury S, Reza MS, and Hussain MS
Abstract: Our present study was designed to investigate the comparative anti-obesity efficacy of ethanolic extract of Azadirachta indica A. Juss. , Trigonella foenum-graecum L. , Allium sativum L. and Zingiber officinale Roscoe in high fat-induced mice with their total phenolic and flavonoid profile. Total phenolic and flavonoid content were determined by Folin-Ciocalteu's and Aluminium chloride UV method respectively. In our study, 55 healthy mice were separated into 11 groups to take their respective treatments. Lipid and uric acid profile were estimated by using the enzymatic colourimetric method. Ethanolic extract of A. indica contained the highest phenolic and flavonoid content. A. indica normal and high fat diet group showed reduced weight gaining tendency than other extract groups. A. indica at a dose of 400 mg/kg body weight significantly (p < 0.001) reduced serum cholesterol (SC), triglyceride (TG), and uric acid (UA) level than other three extracts when compared with the control group. Thus, a considerable correlation was found between serum uric acid reducing potentials of the present experimental extracts with a lipid-lowering profile. Pathological examination revealed that the average weight of liver and kidney were significantly decreased in A. indica normal. Results obtained from the present study it can be concluded that ethanolic extract of A. indica possesses better lipid-lowering efficacy than the other three herbs., Competing Interests: The authors declare that they have no competing interests., (© 2021 The Author(s).)
Published: 2021
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49. An exploratory study of social media users' engagement with COVID-19 vaccine-related content.

Author: Al-Zaman MS
Subjects: COVID-19 Vaccines, Humans, Pandemics, SARS-CoV-2, COVID-19, Social Media
Abstract: Background: Facebook, as the world's most popular social media platform, has been playing various important roles throughout the COVID-19 pandemic, allowing users to produce and share health-related information that both eases and complicates public health communication. However, the characteristics of vaccine-related Facebook content and users' reaction to the vaccine issue has been an unexplored area to date. Methods: To fill the previous knowledge-gap, this exploratory study wants to understand the communication climate of Facebook on the COVID-19 vaccine issue, including the nature of dominant content and users' engagement patterns with them. Therefore, the study analyzes the 10,000 most popular Facebook posts with the highest interactions on the vaccine issue. Results: The results show that Facebook users prioritize more vaccine-related news links (71.22%) over other content. The declining interactions on the issue suggests that interaction growth mainly depends on positive news on the vaccine. Finally, users' reaction to the vaccine issue is dominantly positive, though they may show a highly negative attitude toward vaccine misinformation. Conclusions: A few limitations and strengths of this study are discussed along with values and implications. This study for the first time analyzes Bangla language-based Facebook content related to the COVID-19 vaccine issue, which is largely overlooked in global academic research., Competing Interests: No competing interests were disclosed., (Copyright: © 2021 Al-Zaman MS.)
Published: 2021
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50. Mental Health of the COVID-19 Patients in Bangladesh.

Author: Hasan MJ, Tabssum T, Ambia NE, Zaman MS, Rahman M, and Khan AS
Subjects: Adult, Bangladesh epidemiology, Communicable Disease Control, Cross-Sectional Studies, Depression epidemiology, Humans, Male, Middle Aged, SARS-CoV-2, Surveys and Questionnaires, COVID-19, Mental Health
Abstract: The mental health aspect of coronavirus disease-19 (COVID-19) patients in Bangladesh has remained less focused and has not been addressed properly. The objective of the study was to assess the levels of anxiety and depression in COVID-19 patients. We adopted a mixed online and telephone-based survey using Google Forms. Recruitment was performed through a snowball sampling approach. The Google Form was initially circulated in Facebook to identify interested participants. Then, three trained physicians interviewed the online responders over telephone for a period spanning from April 2020 to June 2020. Two well-known questionnaires, the Generalized Anxiety Disorder 7-item (GAD-7) scale and the Patient Health Questionnaire (PHQ-9), were used for the assessment of anxiety and depression, respectively. Here, the severity of anxiety was classified with the standard thresholds: minimal or none (0-4), mild (5-9), moderate (10-14) and severe (>15) for the GAD-7. Depression severity score: 0-4 was considered as none or no depression, 5-9: mild, 10-14: moderate, 15-19: moderately severe, 20-27 was for severe depression. A total of 237 patients were finally analyzed. The mean age ±SD of the patients was 41.59±13.73 years. Most of them were male (73%) and lived in urban areas (90.29%). Half of the patients were unemployed, and 17.7% admitted loss of job due to lockdown. The overall prevalence of anxiety and depression was 55.7% and 87.3%, respectively. The mean GAD-7 score was 5.79±4.95, and the mean PHQ-9 score was 5.64±5.15. Among the depressive patients, 3% had minimal depression, 38.4% had mild depression, 32.1% had moderate depression, 11.8% had moderate depression, and 2.1% had a severe depression. Similarly, 37.1%, 10.5% and 8% had mild, moderate and severe levels of anxiety, respectively. Nearly half of the study population (47.7%) was suffering from both depression and anxiety. Living in urban area was an independent predictor for depression (OR 3.882; CI: 1.249-12.069). Considering the high comorbid burden, the mental health issues of these patients need to be addressed and reinforced to the existing health system on a priority basis.
Published: 2021

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