Processed Radio Frequency towards Pancreas Enhancing the Deadly Diabetes Worldwide

Authors

  • Md. Rahimullah Miah Department of Health Information Technology, Northeast Medical Pvt. Limited, Sylhet, Bangladesh
  • Mohammad Abdul Hannan Department of Endocrinology, North East Medical College & Hospital, Sylhet, Bangladesh
  • AAM Shazzadur Rahman Department of Medicine, North East Medical College, Sylhet, Bangladesh
  • Md. Shahariar Khan Department of Paediatrics, North East Medical College & Hospital, Sylhet, Bangladesh
  • Md. Mokbul Hossain Department of Pharmacology, North East Medical College and Hospital, Sylhet, Bangladesh
  • Ishrat Tasnim Rahman Ananda Niketan, Sylhet, Bangladesh
  • Md. Sabbir Hossain Department of Pathology, North East Medical College and Hospital, Sylhet, Bangladesh
  • Chowdhury Shadman Shahriar USA and Ex-student of North East Medical College, Sylhet, Bangladesh
  • Mohammad Basir Uddin Department of Paediatrics, North East Medical College and Hospital, Sylhet, Bangladesh
  • Mohammad Taimur Hossain Talukdar Department of Clinical Oncology, North East Medical College and Hospital, Sylhet, Bangladesh
  • Mohammad Shamsul Alam Department of Forensic Medicine, North East Medical College and Hospital, Sylhet, Bangladesh
  • S.A.M. Imran Hossain Department of Oral and Maxillofacial Surgery, North East Medical College, Sylhet, Bangladesh
  • Alamgir Adil Samdany Department of Orthopedics, North East Medical College, Sylhet, Bangladesh
  • Shahriar Hussain Chowdhury Department of Dermatology, North East Medical College, Sylhet, Bangladesh
  • Alexander Kiew Sayok IBEC, University Malaysia Sarawak, Kota Samarahan, Sarawak, Malaysia

DOI:

https://doi.org/10.30564/jer.v3i1.2826

Abstract

Diabetes is a chronic and debilitating disease, which is associated with a range of complications putting tremendous burden on medical, economic and socio-technological infrastructure globally. Yet the higher authorities of health services are facing the excruciating cumulative reasons of diabetes as a very imperative worldwide issue in the 21st century. The study aims to relook at the misapplication of the processed radio frequency that frailties in the pancreas within and around the personal body boundary area. The administered sensor data were obtained at laboratory experiments from the selected specimens on dogs and cats in light and dark environments. The study shows the frequent urine flow speed varies with sudden infection due to treated wireless sensor networks in active open eyes. The overweight and obese persons are increasingly affected in diabetes with comprehensive urinary pressure due to continuous staying at dark environment. The findings replicate the increasing tide of diabetes globally. The study also represents the difficulties of physicians to provide adequate diabetic management according to their expectancy due to insecure personal area network control unit.Dynamic sensor network is indispensable for healthcare but such network is at risk to health security due to digitalized poisoning within GPS positions. The study recommends the anti-radiation integrated system policy with user’s security alternative approach to inspire dealing with National Health Policy and Sustainable Development Goals 2030.

Keywords:

Diabetes; Radio frequency; Pancreas; Active open eyes; Body boundary; Network security

References

[1] Saeedi, P., Petersohn, I., Salpea, P., Malanda, B., Karuranga, S., Unwin, N., Colagiuri, S., Guariguata, L., Motala, A.A., Ogurtsova, K., Shaw, J.E., Brighth, D., Williams. R. and IDF Diabetes Atlas Committee. (2019). Global and regional diabetes prevalence estimates for 2019 and projections for 2030 and 2045: Results from the International Diabetes Federation Diabetes Atlas, 9thedition. Diabetes Research and Clinical Practice,157, 107843, 1-10. DOI: https://doi.org/10.1016/j.diabres.2019.107843.

[2] Narayan, K.M.V., Zhang, P., Kanaya, A.M., Williams, D.E., Engelgau, M.M., Imperatore, G. and Ramachandran, A. (2006). Disease Control Priorities in Developing Countries. 2nd edition. Jamison DT, Breman JG, Measham AR, et al. [eds]. Chapter 30Diabetes: The Pandemic and Potential Solutions. NCBI. 1-20. URL: https://www.ncbi.nlm.nih.gov/ books/NBK11777/.

[3] Lin, X., Xu, Y., Pan, X., Xu, J., Ding, Y., Sun, X., Song, X., Ren, Y. and Shan, P.F. (2020). Global, regional, and national burden and trend of diabetes in 195 countries and territories: an analysis from 1990 to 2025. Scientific Report, 10, 14790. DOI: https://doi.org/10.1038/s41598-020-71908-9.

[4] IDF. (2020). Diabetes facts & figures. International Diabetes Federation (IDF), Belgium. URL: https://www.idf.org/aboutdiabetes/what-is-diabetes/ facts-figures.html (Accessed time on January 19, 2021 at 12:00 pm).

[5] Miah M.R., Khan,M. S., Rahman, A.A.M.S., Samdany, A.A., Hannan, M.A., Chowdhury, S.H., Sayok, A.K. (2020). Impact of Sensor Networks towards Individuals Augmenting Causes of Diabetes. International Journal of Diabetes Research, 9(2),1- 10. DOI: 10.5923/j.diabetes.20200902.

[6] Padmapriya, S., Chowdary, V.A. and Dinesh, V.S. (2013). Wireless sensor networks to monitor Glucose level in blood. International Journal of Advancements in Research & Technology, 2(4): 322–326. URL: http://www.ijoart.org/docs/Wireless-sensor-networks-to-monitor-Glucose-level-inblood.pdf

[7] Miah, M.R., Rahman, A.A.M.S., Khan, M.S., Samdany, A.A., Hannan, M.A., Chowdhury, S.H., Sayok, A.K. (2020a). Impact of Sensor Technology Enhancing Corona Disease. American Journal of Biomedical Engineering, 10 (1), 1-11. DOI:10.5923/j.ajbe.20201002.

[8] Chaudhary, D. and Waghmare, L.M. (2014). Design Challenges of Wireless Sensor Networks and Impact on Healthcare Applications. International Journal of Latest Research in Science and Technology, 3(2):110–114.

[9] Abidi, B., Jilbab, A., and Haziti, M.E.L. (2016). Wireless Sensor Networks in biomedical: wireless body area networks. In: Procedings of the Europe, Middle East and North Africa Conference on Technology and Security to support Learning. EMENA-TSSL, SaidaOujda, Morocco, 3–5.

[10] Wu, F., Xu, L., and Kumari, S. (2017). An Improved and Anonymous two factor authentication protocol for healthcare applications with wireless medical sensor networks. MultimedSyst, 23 (2), 195–205. DOI: https://doi.org/10.1007/s00530-015-0476-3

[11] Miah, M.R., Rahman, A.A.M.S., Samdany, A.A. and Chowdhury, S.H. (2021). A Dynamic Scientific Model for Recovery of Corona Disease. Frontiers in Science, 11(1), 1-17. DOI: 10.5923/j.fs.20211101.01, URL: http://article. sapub.org/10.5923.j.fs.20211101.01.html.

[12] Khan, R.I. and Pathan, A.S. (2018). The stateof-the-art wireless body area sensor networks: A survey. International Journal of Distributed Sensor Networks, 14(4):1–16. DOI: 10.1177/1550147718768994.

[13] Ding, S. and Schumacher, M. (2016). Sensor Monitoring of Physical Activity to Improve Glucose Management in Diabetic Patients: A Review. Sensors, 16, 589: 1–13. DOI:10.3390/s16040589.

[14] Li, T., Li, Y. and Zhang, T. (2019). Materials, structures, and functions for flexible and stretchable biomimetic sensors. Accounts of Chemical Research, 52(2):288–296. DOI:10.1021/acs.accounts.

[15] Kim, D. H., Lu, N., Ma, R., Kim, Y. S., Kim, R. H., Wang, S., Wu, J., Won, S. M., Tao, H., Islam, A., Yu, K. J., Kim, T. I., Chowdhury, R., Ying, M., Xu, L., Li, M., Chung, H. J., Keum, H., McCormick, M., Liu, P., Zhang, Y. W., Omenetto, F. G., Huang, Y., Coleman, T. and Rogers, J. A. (2011). Epidermal electronics. Science, 333(6044): 838–843. DOI:10.1126/science.1206157.

[16] Gao, W., Emaminejad, S., Nyein, H. Y. Y., Challa, S., Chen, K., Peck, A., Fahad, H. M., Ota, H., Shiraki, H., Kiriya, D., Lien, D. H., Brooks, G. A., Davis, R. W. and Javey, A. (2016). Fully integrated wearable sensor arrays for multiplexed in situ perspiration analysis. Nature, 529(7587): 509–514. DOI:10.1038/nature16521.

[17] Wang, X. W., Gu, Y., Xiong, Z. P., Cui, Z. and Zhang, T. (2014). Electronic skin: silk-molded flexible, ultrasensitive, and highly stable electronic skin for monitoring human physiological signals. Advanced Materials, 26(9): 1309. DOI:10.1002/adma.201470054.

[18] Sheridan C. (2014). Apple moves on health, drug developers shift into smart gear. Nature Biotechnology, 32(10): 965–966. DOI:10.1038/nbt1014-965a.

[19] Zang, Y. P., Zhang, F. J., Di, C. A. and Zhu, D. B. (2015). Advances of flexible pressure sensors toward artificial intelligence and health care applications. Materials Horizons, 2(2):140–156. DOI:10.1039/c4mh00147h.

[20] Zhao, W. X., Bhushan, A., Santamaria, A., Simon, M. and Davis, C.(2008). Machine learning: A crucial tool for sensor design. Algorithms,1(2): 130– 152. DOI:10.3390/a1020130.

[21] Vu, C. and Kim, J. (2018). Human motion recognition by textile sensors based on machine learning algorithms. Sensors, 18(9): 3109. DOI:10.3390/s18093109.

[22] IDF (2019). What is Diabetes? About Diabetes.International Diabetes Federation, Brussels, Belgium. URL:https://www.idf.org/aboutdiabetes/what-is-diabetes.html?gcid=EAIaIQobChMInML08.001. 8b00497.

[23] WHO.(2018). Key Facts.Diabetes.url: https://www. who.int/news-room/fact-sheets/detail/diabetes (Accessed time on March 16, 2021 at 9:00 am)

[24] Mazid, M.A. (2019, Nov14.). Global Economic Impact of Diabetes. The Daily Asian Age, Dhaka, Bangladesh. url: https://dailyasianage.com/ news/204986/global-economic-impact-of-diabetes (Accessed time on March 13, 2021 at 9:00 am)

[25] Murray, C.J.L. and Lopez, A.D.(eds.). (1996). The Global Burden of Disease: A Comprehensive Assessment of Mortality and Disability from Diseases, Injuries, and Risk Factors in 1990 and Projected to 2020. The Harvard School of Public Health on behalf of the World Health Organization and World Bank and distributed by Harvard University Press. 1–43. URL:

[26] Centers for Disease Control and Prevention. (2011). National diabetes fact sheet: national estimates and general information on diabetes and pre-diabetes in the United States, Atlanta, GA: US Department of Health and Human Services, Centers for Disease Control and Prevention, 2011, Atlanta, GA, U.S.1-12. URL:http://www.diabetesincontrol. com/wp-content/uploads/PDF/ndep_diabetes_ facts_2011.pdf (Accessed time on March 16, 2021 at 11:00 am).

[27] Deedwania, P. C. and Fonseca, V. A. (2005). Diabetes, prediabetes, and cardiovascular risk: shifting the paradigm. The American journal of medicine, 118: 939–947. DOI: 10.1016/j.amjmed.2005.05.018

[28] Meo, S., Alsubaie, Y., Almubarak, Z., Almutawa, H., AlQasem, Y. and Hasanato, R. (2015). Association of Exposure to Radio-Frequency Electromagnetic Field Radiation (RF-EMFR) Generated by Mobile Phone Base Stations with Glycated Hemoglobin (HbA1c) and Risk of Type 2 Diabetes Mellitus. International Journal of Environmental Research and Public Health, 12(11),14519–14528. DOI:10.3390/ijerph121114519.

[29] Algoblan, A., Alalfi, M., & Khan, M. (2014). Mechanism linking diabetes mellitus and obesity. Diabetes, Metabolic Syndrome and Obesity: Targets and Therapy, 587. DOI:10.2147/dmso.s67400.

[30] Bonsembiante B., Dalfrà, M.G., Masin, M., Gallo, A. and Lapolla. A., (2013). Adult-Onset Type 1 Diabetes and Pregnancy: Three Case Reports. Case Reports in Medicine, 1-3. DOI: http://dx.doi.org/10.1155/2013/920861.

[31] Geerlings, S., Fonseca, V., Castro-Diaz, D., List, J. and Parikh, S. (2014). Genital and urinary tract infections in diabetes: Impact of pharmacologically-induced glucosuria. Diabetes Research and Clinical Practice, 103(3), 373–381. DOI: 10.1016/j.diabres.2013.12.052.

[32] Sjoberg, R. J. and Kidd, G. S. (1989). Pancreatic Diabetes Mellitus. Diabetes Care, 12(10), 715–724. DOI:10.2337/diacare.12.10.715.

[33] Meier, J. J. and Giese, A. (2015). Diabetes associated with pancreatic diseases. Current Opinion in Gastroenterology, 31(5), 400–406. DOI:10.1097/mog.0000000000000199.

[34] Tolman, K. G., Fonseca, V., Dalpiaz, A. and Tan, M. H. (2007). Spectrum of Liver Disease in Type 2 Diabetes and Management of Patients with Diabetes and Liver Disease. Diabetes Care, 30(3), 734–743. DOI:10.2337/dc06-1539.

[35] Blendea, M. C., Thompson, M. J. and Malkani, S. (2010). Diabetes and Chronic Liver Disease: Etiology and Pitfalls in Monitoring. Clinical Diabetes, 28(4), 139–144. DOI:10.2337/diaclin.28.4.139.

[36] Sami, W., Ansari, T., Butt, N. S. and Hamid, M. (2017). Effect of diet on type 2 diabetes mellitus: A review. International journal of health sciences, 11(2), 65–71. PMID: 28539866.

[37] ADA (American Diabetes Association). (2003a). Nutrition Principles and Recommendations in Diabetes. Diabetes Care, 27(Supplement 1), S36–S36. DOI:10.2337/diacare.27.2007.s36.

[38] Takei, K., Honda, W., Harada, S., Arie, T. and Akita S. (2015). Toward flexible and wearable human-interactive health-monitoring devices. Advanced Healthcare Materials, 4(4): 487–500. DOI:10.1002/adhm.201400546.

[39] Knop, F.K., Vilsboll, T., Hojberg, P.V., Larsen, S., Madsbad, S., Vølund, A., Holst, J.J. and Krarup, T. (2007). Reduced incretin effect in type 2 diabetes: cause or consequence of the diabetic state? Diabetes, 56:1951–1959. DOI: 10.2337/db07-0100.

[40] Lou, Z., Wang, L. L. and Shen, G. Z. (2018). Recent advances in smart wearable sensing systems. Advanced Materials Technologies, 3(12): 1800444. DOI:10.1002/admt.201800444.

[41] Khan, Y., OstfeldA, E., Lochner, C. M. and Pierre, A. A. C. (2016). Monitoring of Vital Signs with Flexible and Wearable Medical Devices. Advanced Materials, 28(22): 4373–4395. DOI:10.1002/adma.201504366.

[42] Zhang, T., Bai, Y.Y. and Sun, F. Q. (2018). Recent advances in flexible self-healing materials and sensors. ScientiaSinicaInformationis, 48(6): 650–669. DOI:10.1360/n112018-00117.

[43] Li, Y., Zheng, L. and Wang, X. (2019). Flexible and wearable healthcare sensors for visual reality healthmonitoring. Virtual Reality & Intelligent Hardware, 1(4):411—427. DOI: 10.1016/j.vrih.2019.

[44] Peiris, V. (2013). Highly integrated wireless sensing for body area network applications. The International Society for Optics and Photonics. SPIENewsroom. DOI:10.1117/2.1201312.005120.

[45] O’Donovan, T., O’Donoghue, J., Sreenan, C., Sammon, D., O’Reilly, P. and O’Connor, K.A. (2009). A Context Aware Wireless Body Area Network. Pervasive Computing Technologies for Healthcare. 1–2, DOI:10.4108/ICST.PERVASIVEHEALTH2009.5987.

[46] Bilal, M and Kang, S.G.(2017).An Authentication Protocol for Future Sensor Networks. Sensors, 17(5): 979. DOI:10.3390/s170509.79.

[47] Nall, R. (2018). An overview of diabetes types and treatments.Newsletter on Health. Medical News Today,1(1): 1–5. URL: https://www.medicalnewstoday.com/articles/323627.

[48] Goharimanesh, M., Lashkaripour, A. and Akbari, A. (2015). A Comparison of Fuzzy Types 1 and 2 in Diabetics Control, Based on Augmented Minimal Model. Journal of World’s Electrical Engineering and Technology, 4(2): 70–75. DOI/URL: https://profdoc.um.ac.ir/articles/ a/1053908.pdf.

[49] Apicella, M., Campopiano, M.C., Mantuano, M., Mazoni, L., Coppelli, A., Prato, S.D. (2020).COVID-19 in people with diabetes: understanding the reasons for worse outcomes. The LANCET Diabetes and Endocrinology, 8 (9), 782-792. DOI: https://doi.org/10.1016/S2213-8587(20)30238-2.

[50] Health Hub. (2021). Diabetes Mellitus, Health Hub, Singapore. URL: https://www.healthhub.sg/a-z/ diseases-and-conditions/102/topics_diabetes (Accessed time on January18, 2021 at 9:00 am).

[51] Cryer, P.E., Davis, S.N. and Shamoon, H. (2003). Hypoglycemia in diabetes. Diabetes Care, 26:1902– 1912. DOI: https://doi.org/10.2337/diacare.26.6.1902.

[52] Havas, M. (2008). Dirty electricity elevates blood sugar among electrically sensitive diabetics and may explain brittle diabetes. Electromagn. Biol. Med., 27, 135–146. DOI: 10.1080/15368370802072075.

[53] Sha, H., Zeng, H., Zhao, J. and Jin, H. (2019). Mangiferin ameliorates gestational diabetes mellitus-induced placental oxidative stress, inflammation and endoplasmic reticulum stress and improves fetal outcomes in mice. European Journal of Pharmacology, 859: 172522. DOI:10.1016/j.ejphar.2019.172522.

[54] Kays, R., Tilak, S., Crofoot, M., Fountain, T., Obando, D., Ortega, A., Kuemmeth, F., Mandel, J., Swenson, G., Lambert, T., Hirsch, B. and Wikelski, M. (2011). Tracking Animal Location and Activity with an Automated Radio Telemetry System in a Tropical Rainforest. Published by Oxford University Press on behalf of the British Computer Society. The Computer Journal, 1(1): 1–18, DOI: 10.1093/comjnl/bxr072.

[55] Waltham. (2017). Feline Body Mass Index (FBMI). Waltham FBMI Calculator. 1–2. URL: https://jscalc.z6_io/calc/hORP8x2bWjQU7qxq (Accessed time on March 16, 2017 at 9:00 am)

[56] IDF. (2020a). COVID-19 and diabetes. IDF, Belgium. URL: https://www.idf.org/aboutdiabetes/ what-is-diabetes/covid-19-and-diabetes/1-covid-19- and-diabetes.html (Accessed time on January 19, 2021 at 1:00 pm).

[57] Glasgow, R.E. (1995). A Practical Model of Diabetes Management and Education. DiabetesCare, 18(1): 117–126.

[58] Frier, B.M. (2014). Hypoglycaemia in diabetes mellitus: Epidemiology and clinical implications. Nat. Rev. Endocrinol.,10: 711–722. DOI: 10.1038/nrendo.2014.170.

[59] Burge, M.R., Mitchell, S., Sawyer, A.,Schade, D.S.(2008). Continuous glucose monitoring: the future of diabetes management. Diabetes Spectr.,21:112–119. DOI: https://doi.org/10.2337/diaspect.21.2.112.

[60] Miah, M.R., Rahman, A.A.M.S., Khan, M.S., Hannan, M.A., Hossain, M.S., Shahriar, C.S., Hossain, S.A.M.I., Talukdar, M.T.H., Samdany, A.A., Alam, M.S., Uddin, M.B., Sayok, A.K., Chowdhury, S.H. (2021a). Effect of Coronavirus Worldwide through Misusing of Wireless Sensor Networks. American Journal of Bioinformatics Research, 11(1), 1-31. DOI: 10.5923/j.bioinformatics.20211101.01 (URL: http://article.sapub.org/10.5923.j.bioinformatics.20211101.01.html).

[61] Marcus, A.O. (2002). Outpatient Technologies for the treatment and prevention of Diabetes. Diabetes Spectrum, 15(2), 78-80. DOI: 10.2337.

[62] Khan Y, Han D, Pierre A, Ting J, Wang X C, Lochner C M, Bovo G, Yaacobi-Gross N, Newsome C, Wilson R, Arias A C. (2018). A flexible organic reflectance oximeter array. Proceedings of the National Academy of Sciences, 115(47): E11015–E11024. DOI:10.1073/pnas.1813053115.

[63] Schiel, R., Bambauer, R. and Steveling, A. (2018). Technology in Diabetes Treatment: Update and Future. Artificial Organs, 42 (11), 1017–1027. DOI/URL: https://doi.org/10.1111/aor.13296.

[64] Delamater,A. M., Jacobson,A. M., Anderson, B., Cox,D., Fisher,L.,Lustman, P., Rubin, R.and Wysocki, T. (2001). Psychosocial Therapies in Diabetes: Report of the Psychosocial Therapies Working Group. Diabetes Care, 24(7): 1286-1292. DOI: https://doi.org/10.2337/diacare.24.7.1286.

[65] ADA (). (2003). Physical Activity/Exercise and Diabetes Mellitus. American Diabetes Association (ADA) Diabetes Care, suppl 1: s73-s77. DOI/URL: https://doi.org/10.2337/diacare.26.2007. S73.

[66] Moradi, B., Abbaszadeh, S., Shahsavari, S., Alizadeh,M. and Beyranvand, F. (2018). The most useful medicinal herbs to treat diabetes. Biomedical Research and Therapy, 5(8): 2538–2551.

[67] Azizi, F., Hatami, H. and Janghorbani, M. (2007). Epidemiology and Control of Common Disease in Iran.Tehran: Eshtiagh Press, 1–5.

[68] Gupta, V.K., Gupta, M., and Arora.S. (2017). Diabetes: Ethical Issues. Chapter 159, Medicine Update, India. 742-745. URL: http://www.apiindia.org/ pdf/medicine_update_2017/mu_159.pdf. (Accessed time on March 16, 2020 at 9:00 am)

[69] Dazzi, D., Taddei, F., Gavarini, E A., Negro, U.R. and Pezzarossa, A. (2001). The control of blood glucose in the critical diabetic patient: a neuro-fuzzy method. Journal of Diabetes and its Complications, 15: 80–87. DOI: 10.1016/s1056-8727(00)00137-9.

[70] Grant, P. (2007). A new approach to diabetic control: fuzzy logic and insulin pump technology. Medical engineering & physics, 29: 824–827. DOI: 10.1016/j.medengphy.2006.08.014.

[71] Forouhi, N.G., Misra, A., Mohan,V., Taylor, R. and Yancy., W. (2018). Dietary and nutritional approaches for prevention and management of type 2 diabetes. BMJ, 361:k2234,1–9. DOI: 10.1136/bmj.k2234.

[72] IDF (International Diabetes Federation). (2017). Diabetes atlas. 8th ed. IDF, 2017. URL: ww.diabetesatlas.org (Accessed time on March 15, 2020at 9:00 am). URL: https://www.diabetesatlas.org/ upload/resources/previous/files/8/IDF_DA_8e-ENfinal.pdf.

[73] Johnston, B.C., Kanters, S., Bandayrel, K. Wu, P., Naji, F., Siemieniuk, R.A., Ball, G.D.C., Busse, J.W., Thorlund, K., Guyatt, G., Jansen, J.P. and Mills, E.J. (2014). Comparison of weight loss among named diet programs in overweight and obese adults: a meta-analysis. JAMA, 312(9):923-33. DOI:10.1001/jama.2014.10397.

[74] Westman, E.C., Yancy, W.S. Jr. and Humphreys, M. (2006). Dietary treatment of diabetes mellitus in the pre-insulin era(1914-1922). PerspectBiol Med,49:77-83. DOI:10.1353/pbm.2006.0017.

[75] Cronkleton, E. (2018). Yoga for Diabetes. Healthline. URL: https://www.healthline.com/health/diabetes/yoga-for-diabetes (Accessed time on March 15, 2021 at 2:00 pm).

[76] Raveendran, A. V., Deshpandae, A. and Joshi, S. R. (2018). Therapeutic Role of Yoga in Type 2 Diabetes. Endocrinology and Metabolism, 33(3), 307. DOI:10.3803/enm.2018.33.3.307.

[77] Soroka, E. (2019). Yoga for Diabetes: 12 Poses and a Meditation to Mitigate Stress. Yoga Journal. 1-26. URL: https://www.yogajournal.com/practice/yoga-for-diabetes/ (Accessed time on March 15, 2021 at 3:00 pm).

[78] Sharma, M. and Knowlden, A.P. (2012). Role of Yoga in Preventing and Controlling Type 2 Diabetes Mellitus. Journal of Evidence-Based Complementary & Alternative Medicine,17(2) 88-95. DOI: 10.1177/2156587212438899.

[79] Johnson, J. (2019). A review of therapies and lifestyle changes for diabetes. Medical News Today, 1-2. URL: https://www.medicalnewstoday.com/articles/317074.php (Accessed time on March 10, 2021 at 9:00 am).

[80] Babamiri, B., Bahari, D. and Salimi, A. (2019). Highly sensitive bioaffinityelectrochemiluminescence sensors: Recent advances and future directions. Biosensors and Bioelectronics, 111530. DOI: https://doi.org/10.1016/j.bios.2019.111530.

[81] Hardt, P.D., Brendel, M.D., Kloer, H.U. and Bretzel, R.G. (2008). Is pancreatic diabetes (type 3c diabetes) underdiagnosed and misdiagnosed? Diabetes Care,31 (Suppl 2):S165–S169. DOI: 10.2337/dc08-s244.

[82] Boutry, C. M., Beker, L., Kaizawa, Y., Vassos, C., Tran, H., Hinckley, A. C., Pfattner, R., Niu, S. M., Li, J. H., Claverie, J., Wang, Z., Chang, J., Fox, P. M. and Bao, Z. N. (2019). Biodegradable and flexible arterial-pulse sensor for the wireless monitoring of blood flow. Nature Biomedical Engineering, 3(1): 47–57. DOI:10.1038/s41551-018-0336-5.

[83] Islam, D., Huque, A., Sheuly, Mohanta, L.C., Das, S.K. and Sultana, A. (2018). Hypoglycemic and hypolipidemic effects of Nelumbonucifera flower in Long-Evans rats. Journal of Herbmed Pharmacology, 7:148–54. DOI:10.15171/jhp.2018.25.

[84] Rahimi-Madiseh, M., Karimian, P., Kafeshani, M. and Rafieian-Kopaei, M. (2017). The effects of ethanol extract of Berberis vulgaris fruit on histopathological changes andbiochemical markers of the liver damage in diabetic rats. Iranian Journal of Basic Medical Sciences, 20:552–556. DOI: 10.22038/IJBMS.2017.8681.

[85] Maideen, N.M.P. and Balasubramaniam, R.(2018). Pharmacologically relevant drug interactions of sulfonylurea antidiabetics with commonherbs. Journal of Herbmed Pharmacology.7:200–10. DOI:10.15171/jhp.2018.32.

[86] Rosenstock, J., Seman, L.J., Jelaska, A., Hantel, S., Pinnetti ,S., Hach, T. and Woerle, H.J. (2013). Efficacy and safety of empagliflozin, a sodium glucose cotransporter 2 (SGLT2) inhibitor, as add-on to metformin in type 2 diabetes with mild hyperglycaemia. Diabetes Obes Metab, 15(12):1154–60. DOI: 10.1111/dom.12185.

[87] MIT. (2018). A GPS for inside your body: Wireless system suggests future where doctors could implant sensors to track tumors or even dispense drugs. Computer Science and Artificial Intelligence Laboratory (CSAIL), Massachusetts Institute of Technology (MIT), USA. ScienceDaily, August 20, 2018. URL: www.sciencedaily.com/releases/2018/08/180820085158.html (Acceessed on February 5, 2021 at 12:00 pm).

[88] Wilding, J. P. H., Norwood, P., T’joen, C., Bastien, A., List, J. F. and Fiedorek, F. T. (2009). A Study of Dapagliflozin in Patients With Type 2 Diabetes Receiving High Doses of Insulin Plus Insulin Sensitizers: Applicability of a novel insulin-independent treatment. Diabetes Care, 32(9), 1656–1662. DOI:10.2337/dc09-0517.

[89] Philippe, M.F., Benabadji, S., Barbot-Trystram, L., Vadrot, D., Boitard, C. (2011). Larger E. Pancreatic volume and endocrine and exocrine functions in patients with diabetes. Pancreas, 40(3):359–363. DOI: 10.1097/MPA.0b013e3182072032.

[90] Ershow, A.G. (2009). Environmental influences on development of type 2 diabetes and obesity: challenges in personalizing prevention and management. J Diabetes Sci Technol., 3(4):727–734. DOI: 10.1177/193229680900300418.

[91] Osler, W. and McCrae, T. (1921). The principles and practice of medicine: Designed for the use of Practitioners and students of Medicine. D. Appleton and Company, 1921, New York and London.. URL: https://archive.org/details/principlesandpr00mccrgoog/page/n6/mode/2up (Accessed time on March 16, 2021 at 10:00am).

[92] Wild, S., Roglic, G., Green, A., Sicree, R. and King, H. (2004). Global prevalence of diabetes: estimates for the year 2000 and projections for 2030. Diabetes Care, 27(5):1047–1053. DOI: 10.2337/diacare.27.5.1047

[93] Fowler, M.J. (2008). Microvascular and Macrovascular Complications of Diabetes. Clinical Diabetes, 26(2):77–82. DOI: https://doi.org/10.2337/diaclin.26.2.77.

[94] Naser, K.A., Gruber, A. and Thomson, G.A. (2006). The emerging pandemic of obesity and diabetes: are we doing enough to prevent a disaster? Int J Clin Pract., 60(9):1093–1097. DOI: 10.1111/j.1742-1241.2006.01003.x.

[95] Frei, P., Mohler, E., Neubauer, G., Theis, G., Bürgi, A., Fröhlich, J., Braun-Fahrländer, C., Bolte, J., Egger, M. and Röösli, M. (2009). Temporal and spatial variability of personal exposure to radio frequency electromagnetic Fields. Environ. Res., 109, 779–785. DOI: https://doi.org/10.1016/j.envres.2009.04.015.

[96] Forouzanfar M.H., Forouzanfar, M.H., Alexander, L., Anderson, H.R., Bachman, V.F., Biryukov, S., Brauer, M., Burnett, R., Casey, D., Coates, M.M., Aaron Cohen, A., Delwiche, K., Estep, K., Frostad, J.J., Astha, K.C., Kyu, H.H., Moradi-Lakeh, M., Ng, M., Slepak, E.L., Thomas, B.A., Wagner, J., Aasvang, G.M., Abbafati, C., Ozgoren, A.A., Abd-Allah, F., Abera,S.F., Aboyans, V., Abraham, B., Abraham, J.P., Abubakar, I., Abu-Rmeileh, N.M.E., Aburto, T.C., Achoki, T., Adelekan, A., Adofo, K., Adou, A.K., Adsuar, J.C., Afshin, A., Agardh, E.E., Al-Khabouri, M.J., Al Lami, F.H., Alam,S.S., Alasfoor, D., Albittar, M.I., Alegretti, M.A., Aleman, A.V., Zewdie A Alemu, Z.A., Alfonso-Cristancho, R., Alhabib, S., Ali, R., Ali, M.K., Alla, F., Allebeck, P., Allen, P.J., Ubai Alsharif, U., Alvarez, E., Alvis-Guzman, N., Amankwaa, A.A., Amare, A.T., Ameh, E.A., Ameli, O., Amini, H., Ammar, W., Anderson, B.O., Antonio, C.A.T., Anwari, P., Cunningham, S.A., Arnlöv, J., Arsenijevic, V.S.A., Artaman, A., Asghar, R.J., Assadi, R., Atkins, L.S., Atkinson, C., Avila, M.A., Awuah, B., Badawi, A., Bahit, M.C., Bakfalouni, T., Balakrishnan, K., Balalla, S., Balu, R.K., Banerjee, A.,Barber, R.M., Barker-Collo, S.L., Barquera, S., Barregard, L., Barrero, L.H., Barrientos-Gutierrez, T., Basto-Abreu, A.C., Basu, A., Basu, S., Basulaiman, M.O., Ruvalcaba, C.B., Beardsley, J., Bedi, N., Bekele, T., Bell, M. L., Benjet, C., Bennett, D.A., Benzian, H., Bernabé, E., Beyene, T.J., Bhala, N., Bhalla, A., Bhutta, Z.A., Bikbov, B., Abdulhak, A.A.B., Blore, J.D., Blyth, F.M., Bohensky, M.A., Başara, B.B., Borges, G., Bornstein, N.M., Bose, D., Boufous, S., Bourne, R.R., Brainin, M., Brazinova, A., Breitborde, N.J., Brenner, H., Briggs, A.D.M., Broday, D.M., Brooks, P.M., Bruce, N.G., Brugha, T.S., Brunekreef, B., Buchbinder, R., Bui, L.N., Bukhman, G., Bulloch, A.G., Burch, M., Burney, P.G.J., Campos-Nonato, I.R., Campuzano, J.C., Cantoral, A.J., Caravanos, J., Cárdenas, R., Cardis, E., Carpenter, D.O., Caso, V., Castañeda-Orjuela, C.A., Castro, R.E., CataláLópez, F., Cavalleri, F., Çavlin, A., Chadha, V.K., Chang, J.C., Charlson, F.J., Chen, H., Chen, W., Chen, Z., Chiang, P.P., Chimed-Ochir, O., Chowdhury, R., Christophi, C.A., Chuang, T.W., Chugh, S.S., Cirillo, M., Claßen, T.K.D., Colistro, V., Colomar, M., Colquhoun, S.M., Contreras, A.G., Cooper, C., Cooperrider,K., Cooper, L.T., Coresh,. J. Courville, K.J., Criqui, M.H., Cuevas-Nasu, L., Damsere-Derry, J., Danawi, H., Dandona, L., Dandona, R., Dargan, P.I., Davis, A., Davitoiu, D.V., Dayama, A., de Castro, E.F., De la Cruz-Góngora, V., De Leo, D., de Lima, G., Degenhardt, L., Pozo-Cruz, B.D., Dellavalle, R.P., Deribe, K., Derrett, S., Jarlais, D.C.D., Dessalegn, M., deVeber, G.A., Devries, K.M., Dharmaratne, S.D., Dherani, M.K., Dicker, D., Eric L Ding, D.E.L., Dokova, K., Dorsey, E.R., Driscoll, T.R., Duan, L., Durrani,A.M., Ebel, B.E., Ellenbogen, R.G., Elshrek, Y.M., Endres, M., Ermakov, S.P. Erskine, H.E., Eshrati, B., Esteghamati, A., Fahimi, S., Faraon, E.J.A., Farzadfar, F., Fay, D.F.J., Feigin, V.L., Feigl, A.B., Fereshtehnejad, S.M., Ferrari, A.J., Ferri, C.P., Flaxman, A.D., Fleming, T.D., Foigt, N., Foreman, K.J., Paleo, U.F., Franklin, R.C., Gabbe, B., Gaffikin, L., Gakidou, E., Gamkrelidze, A., Gankpé, F.G., Gansevoort, R.T., García-Guerra, F.A., Gasana, E., Geleijnse, J.M., Gessner, B.D., Gething, P., Gibney, K.B., Gillum, R.F., Ginawi, I.A.M., Giroud, M., Giussani, G., Goenka, S., Goginashvili, K., Dantes, H.G., Gona, P., de Cosio, T.G., González-Castell, D., Gotay, C.C., Goto, A., Gouda, H.N., Guerrant, R.L., Gugnani, H.C., Guillemin, F., Gunnell, D., Gupta, R., Rajeev Gupta, Rv., Gutiérrez, R.A., Hafezi-Nejad, N., Hagan, H., Hagstromer, M., Halasa, Y.A., Hamadeh, R.R., Hammami, M., Hankey, G.J., Hao, Y., Harb, H.L., Haregu, T.N., Haro, J.M., Havmoeller, R., Hay, S.I., Hedayati, M.T., Heredia-Pi, I.B., Hernandez, L., Heuton, K.R., Heydarpour, P., Hijar, M., Hoek, H.W., Hoffman, H.J., Hornberger, J.C., Hosgood, H.D., Hoy, D.G., Hsairi, M., Hu, G., Hu, H., Huang, C., Huang, J.J., Hubbell, B.J., Huiart, L., Husseini, A., Iannarone, M.L., Iburg, K.M., Idrisov, B.T., Ikeda, N., Innos, K., Inoue, M., Islami, F., Ismayilova, S., Jacobsen, K.H., Jansen, H.A., Jarvis, D.L., Jassal, S.K., Jauregui, A., Jayaraman, S., Jeemon, P., Jensen, P.N., Jha, V., Jiang, F., Jiang, G., Jiang, Y., Jonas, J., B., Juel, K., Kan, H., Roseline, S.S.K., Karam, N.E., Karch, A., Karema, C.K., Karthikeyan, G., Kaul, A., Kawakami, N., Kazi, D.S., Kemp, A.H., Kengne, A.P., Keren, A., Khader, Y.S., Khalifa, S.E.A.H., Khan, E.A., Khang, Y.H., Khatibzadeh, S., Khonelidze, I., Kieling, C., Kim, D., Kim, S., Kim, Y., Kimokoti, R.W., Kinfu, Y., Kinge, J.M., Kissela, B.M., Kivipelto, M., Knibbs, L.D., Knudsen, A.K., Kokubo, Y., Kose, M.R., Kosen, S., Kraemer, A., Kravchenko, M., Krishnaswami, S., Kromhout, H., Ku, T., Defo, B.K., Bicer, B.K., Kuipers, E.J., Kulkarni, C., Kulkarni, V.S., Kumar, G.A., Kwan, G.F., Lai, T., Balaji, A.L., Lalloo, R., Lallukka, T., Lam, H., Lan, Q., Lansingh, V.C., Larson, H.J., Larsson, A., Laryea, D.O., Lavados, P.M., Lawrynowicz, A.E. et al………Murray, C.J. and GBD 2013 Risk Factors Collaborators. (2015). Global, regional, and national comparative risk assessment of 79 behavioural, environmental and occupational, and metabolic risks or clusters of risks in 188 countries, 1990-2013: a systematic analysis for the Global Burden of Disease Study 2013. Lancet, 386(10010):2287-323.DOI: 10.1016/S0140-6736(15)00128-2.

[97] Clark, N. G., Fox, K. M. and Grandy, S. (2007). Symptoms of Diabetes and Their Association with the Risk and Presence of Diabetes: Findings from the Study to Help Improve Early evaluation and management of risk factors Leading to Diabetes (SHIELD). Diabetes Care, 30(11), 2868–2873. DOI:10.2337/dc07-0816.

[98] Wang J. (2008). Electrochemical glucose biosensors. Chemical Reviews, 108:814–825. DOI: 10.1021/cr068123a.

[99] Bowe, B., Xie, Y., Li, T., Yan, Y., Xian, H. and AlAly, Z. (2018). The 2016 global and national burden of diabetes mellitus attributable to PM 2·5 air pollution. The Lancet Planetary Health, 2(7), e301– e312. DOI:10.1016/s2542-5196(18)30140-2.

[100] Fairbrother, N., Newth, S. J. and Rachman, S. (2005). Mental pollution: feelings of dirtiness without physical contact. Behaviour Research and Therapy, 43(1), 121–130. DOI: 10.1016/j.brat.2003.12.005.

[101] Sancar, F. (2019). Childhood Lead Exposure May Affect Personality, Mental Health in Adulthood. JAMA, 321(15):1445–1446. DOI:10.1001/jama.2019.1116.

[102] Reuben A, Schaefer JD, Moffitt TE, et al. (2019). Association of Childhood Lead Exposure With Adult Personality Traits and Lifelong Mental Health. JAMA Psychiatry,76(4):418–425. DOI:10.1001/jamapsychiatry.2018.4192.

[103] Yao, J., Brauer, M., Wei, J., McGrail, K. M., Johnston, F. H., & Henderson, S. B. (2020). Sub-Daily Exposure to Fine Particulate Matter and Ambulance Dispatches during Wildfire Seasons: A Case-Crossover Study in British Columbia, Canada. Environmental Health Perspectives, 128(6), 067006. DOI:10.1289/ehp5792.

[104] Bennett, C. (2020). Pollution and Mental Health. News Medical Life Sciences. URL: https://www. news-medical.net/health/Pollution-and-Mental-Health.aspx (Accessed on March 13, 2021 at 12:00 pm).

[105] Cetin, Y. (2012). Impact of Mental Pollution on Learning and Memory. Procedia - Social and Behavioral Sciences, 46, 5320–5323. DOI: 10.1016/j.sbspro.2012.06.431.

[106] Dendup, T., Feng, X., Clingan, S. and Astell-Burt, T. (2018). Environmental Risk Factors for Developing Type 2 Diabetes Mellitus: A Systematic Review. International Journal of Environmental Research and Public Health, 15(1), 78.DOI:10.3390/ijerph15010078.

[107] Khan, A., Plana-Ripoll, O., Antonsen, S., Brandt, J., Geels, C., Landecker, H., Sullivan, P.F., Pedersen, C.B.,Rzhetsky, A. (2019). Environmental pollution is associated with increased risk of psychiatric disorders in the US and Denmark. PLOS Biology, 17(8), e3000353, 1-28. DOI: 10.1371/journal.pbio.3000353.

[108] Rajagopalan, S. and Brook, R. D. (2012). Air Pollution and Type 2 Diabetes: Mechanistic Insights. Diabetes, 61(12), 3037–3045. DOI:10.2337/db12-0190.

[109] WHO. (2004). Promoting mental health: Concepts, emerging evidence, practice: summary report. World Health Organization. URL : https://apps.who. int/iris/bitstream/handle/10665/42940/9241591595. pdf (Accessed time on March 11, 2021 at 11:00 am)

[110] Brokamp, C., Strawn, J. R., Beck, A. F., & Ryan, P. (2019). Pediatric Psychiatric Emergency Department Utilization and Fine Particulate Matter: A Case-Crossover Study. Environmental Health Perspectives, 127(9), 097006.1-7. DOI:10.1289/ehp4815.

[111] Lelieveld, J., Evans, J.S., Fnais, M., Giannadaki, D. and Pozzer, A. (2015). The contribution of outdoor air pollution sources to premature mortality on a global scale. Nature,525: 367–71. DOI: https://doi.org/10.1038/nature15371.

[112] Brunst, K. J. (2019). Myo-inositol mediates the effect of traffic-related air pollution on generalized anxiety symptoms at age 12 years. Environmental research, 175, 71–78. DOI: https://doi.org/10.1016/j.envres.2019.05.009.

[113] Dzhambov, A. M. (2018). Ambient air pollution and diabetes in China. The Lancet Planetary Health, 2(2), e52–e53. DOI:10.1016/s2542-5196(18)30002-0.

[114] Ruder, K. (2021, January 20). Is There a Link Between Type 2 Diabetes and Air Pollution? Everyday Health. Newsletter. URL: https://www.everydayhealth.com/type-2-diabetes/is-there-a-link-betweentype-2-diabetes-and-air-pollution/ (Accessed time on March 13, 2021 at 12:00 pm).

[115] Porter, E. (2018). Is Frequent Urination a Sign of Diabetes? Healthline. URL: https://www.healthline. com/health/frequent-urination-diabetes (Accessed time on February 15, 2021 at 11:00 am).

[116] Agarwal, N. and Hussain, S.Z. (2018). A Closer Look at Intrusion Detection System for Web Applications. Security and Communication Networks, 1–28. DOI: https://doi.org/10.1155/2018/96013.

[117] Butun I., Morgera S. and Sankar R. (2014). A survey of intrusion detection systems in wireless sensor networks.IEEE Commun. Surv. Tutor, 16:266– 282. DOI: 10.1109/SURV.2013.050113.00191.

[118] Butun I., Ra I.H. and Sankar R. (2015). PCAC: Power-and Connectivity-Aware Clustering for Wireless Sensor Networks. EURASIP J. Wirel. Commun. Netw., 1:1–15. DOI: 10.1186/s13638-015-0321-6.

[119] Bal, A. (2000). Diabetes: ethical, social and economic aspects.The Indian Journal of Medical Ethics, 8:3. PMID: 16323366.

[120] WHO. (2020c). WHO works with the Government of the United Kingdom to tackle misinformation. World Health Organization (WHO). URL: https://www.who.int/campaigns/connecting-the-world-to-combat-coronavirus/how-to-report-misinformation-online (Accessed time on January 11, 2021 at 12:00pm.).

[121] Roozenbeek, J., Schneider, C.R., Dryhurst, S., Kerr, J., Freeman, A.L.J., Recchia, G., vander Bles, A.M. and van der Linden, S. (2020). Susceptibility to misinformation about COVID-19 around the world. Royal Society Open Science, 7: 201199, 1-15. DOI: http://dx.doi.org/10.1098/rsos.201199.

[122] Giles Keir. (2020, April 9). Beware Russian and Chinese Positioning for after the pandemic. Chatham house.URL:https://www.chathamhouse. org/2020/04/beware-russian-and-chinese-positioning-after-pandemic?gclid=EAIaIQobChMInIPlhsqa7gIVNdWWCh1xeA3uEAMYASAAEgKkCvD_BwE (Accessed time on January 10, 2021 at 3:00 pm.).

[123] Cinelli, M., Quattrociocchi, W., Galeazzi, A., Valensise, C.M., Brugnoli, E., Schmidt, A.L., Zola, P., Zollo, F. and Scala, A. (2020). The COVID-19 social media infodemic. Scientific Report, 10, 16598. DOI: https://doi.org/10.1038/s41598-020-73510-5.

[124] CDC. (2020). National Diabetes Statistics Report 2020: Estimates of Diabetes and its Burden in the United States, U.S. Department of Health and Human Services, Centers for Disease Control and Prevention (CDC), 1-31. URL: https://www.cdc.gov/ diabetes/pdfs/data/statistics/national-diabetes-statistics-report.pdf (Accessed time on March 16, 2021 at 12:00 pm).

[125] Ding, K., Reynolds, C.M., Driscoll, K.A. and Janicke, D.M. (2021). The Relationship Between Executive Functioning, Type 1 Diabetes Self-Management Behaviors, and Glycemic Control in Adolescents and Young Adults. Current Diabetes Report, 21 (10). DOI: https://doi.org/10.1007/s11892-021-01379-3.

[126] Lyles, C.R., Sarkar, U. & Osborn, C.Y. (2014). Getting a Technology-Based Diabetes Intervention Ready for Prime Time: A Review of Usability Testing Studies. Current Diabetes Report, 14 (10), 534. DOI: https://doi.org/10.1007/s11892-014-0534-9.

[127] Martin, K., Hatab, A., Athwal, V.S., Jokl, E. and Hanley, K.P. (2021). Genetic Contribution to Non-alcoholic Fatty Liver Disease and Prognostic Implications. Current Diabetes Report, 21(8), 1-8. DOI: https://doi.org/10.1007/s11892-021-01377-5.

[128] Gu, Y., Rampin, A., Alvino, V.V., G. Spinetti and P. Madedduet. (2021). Therapy for Critical Limb Ischemia: Advantages, Limitations, and New Perspectives for Treatment of Patients with Critical Diabetic Vasculopathy. Currernt Diabetes Report, 21 (11), 1-13. DOI: https://doi.org/10.1007/s11892-021-01378-4.

[129] Greene, F. L., Compton, C. C., Fritz, A. G., Shah, J. P. and Winchester, D. P. (Eds.). (2006). AJCC Cancer Staging Atlas. DOI:10.1007/0-387-33126-3.

[130] Nix, G., Wilson, J., Schmitz, P., Dees, J. and Hofwijk, R. (1983). Carcinoma of the ampulla and papilla of Vater. RöFo - Fortschritte Auf Dem Gebiet Der Röntgenstrahlen Und Der Bildgebenden Verfahren, 138(05), 531–535. DOI:10.1055/s-2008-1055779.

[131] Atkinson, M.A., Campbell-Thompson, M., Kusmartseva, I. and Kaestner, K.H. (2020). Organisation of the human pancreas in health and in diabetes. Diabetologia, 63,1966–1973. DOI: https://doi.org/10.1007/s00125-020-05203-7.

[132] He, X.D., Wu, Q., Liu, W., Hong, T., Li, J.J., Miao, R.Y. and Zhao, H.T. (2014). As-sociation of metabolic syndromes and risk factors with ampullary tumors development: A case-control study in China. World J Gastroenterol, 20(28): 9541-9548 URL: http://www.wjgnet.com/1007-9327/full/v20/ i28/9541.htm DOI: http://dx.doi.org/10.3748/wjg.v20.i28.9541.

[133] Gruberg, L., Weissman, N.J., Waksman, R.F., Fuchs, S., Deible,R., Pinnow, E.E., Ahmed, L.M., Kent, K.M., Pichard, A.D., Suddath, W.O., Satler, L.F., Lindsay Jr. J. (2002). The impact of obesity on the short-term and long-term outcomes after percutaneous coronary intervention: The obesity paradox? J Am Coll Cardiol, 39:578-84.

[134] García-Cano, J. (2016). If you suffer from type2 diabetes mellitus, your ERCP is likely to have a better outcome. Editorial. RoFo-Revista Española de Enfermedades Digestivas, 108(7).

[135] Li, D. (2011). Diabetes and Pancreatic Cancer. Molecular Carcinogenesis, 51(1), 64–74. DOI: 10.1002/mc.20771. DOI: http://dx.doi.org/10.17235/reed.2016.4521/2016.

[136] DAB. (2018). Introduction to diabetes mellitus: Epidemiology of diabetes mellitus, Chap. 1. Diabetes Mellitus, 5th Edn, Ahmed, T. (E. Ed.). Certificate Course on Diabetology: Distance Learning Program. Diabetes Association of Bangladesh (DAB), 1–173. ISBN: 984-32-2552-X.

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Miah, M. R., Hannan, M. A., Rahman, A. S., Khan, M. S., Hossain, M. M., Rahman, I. T., Hossain, M. S., Shahriar, C. S., Uddin, M. B., Talukdar, M. T. H., Alam, M. S., Hossain, S. I., Samdany, A. A., Chowdhury, S. H., & Sayok, A. K. (2021). Processed Radio Frequency towards Pancreas Enhancing the Deadly Diabetes Worldwide. Journal of Endocrinology Research, 3(1), 1–20. https://doi.org/10.30564/jer.v3i1.2826

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