Abstract: Today, the incidence of type 2 diabetes mellitus is increasing rapidly on global. This disease is shown with many complications that significantly affect public health. One of them is kidney complications, which have a high incidence among diabetic patients in Vietnam (25.6-33.1%). Age, history of hypertension, and dyslipidemia are considered to be the main risk factors for diabetic nephropathy. Thus, early detection of these factors for kidney damage is significant for diagnosing, monitoring, treatment, and prognosis of diabetic patients. Our descriptive, cross-sectional study conducting on 120 diabetic patients at E Hospital has observed that blood cholesterol levels, HbA1c levels were independently related to eGFR decline below 60 mL/min/1.73m2. From those data, an equation to predict the risk of diabetic kidney disease was estimated as p =  with k = Keyword: Type 2 diabetes, Diabetic nephropathy, Risk factor Today, the incidence of type 2 diabetes mellitus is increasing rapidly on global. This disease is shown with many complications that significantly affect public health. One of them is kidney complications, which have a high incidence among diabetic patients in Vietnam (25.6-33.1%). Age, history of hypertension, and dyslipidemia are considered to be the main risk factors for diabetic nephropathy. Thus, early detection of these factors for kidney damage is significant for diagnosing, monitoring, treatment, and prognosis of diabetic patients. Our descriptive, cross-sectional study conducting on 120 diabetic patients at E Hospital has observed that blood cholesterol levels, HbA1c levels were independently related to eGFR decline below 60 mL/min/1.73m2. From those data, an equation to predict the risk of diabetic kidney disease was estimated as p =  with k = Keyword Type 2 diabetes, Diabetic nephropathy, Risk factor. References [1] N. H. Cho, J. Kirigia, J. C. Mnanya, K. Ogurstova, L. Guraiguata, W. Rathmann, G. Roglic, N. Forouhi, R. Dajani, A. Esteghmati, E. Boyko, L. Hambleton, O. L. M. Neto, P. A. Montoya, S. Joshi, J. Chan, J. Shaw, T.A. Samuels, M. Pavkov, A. Reja, IDF Diabetes Atlas Eight Edition, International Diabete Federation, England, 2017.[2] N. T. Khue, Diabetes – General Endocrinology, Ho Chi Minh Publisher, Ho Chi Minh city, 2003 (in Vietnamese). [3] H. H. Kiem, Clinical Nephrology, Medical Publishing House, Hanoi, 2010 (in Vietnamese). [4] T. H. Quang, Practice Diabetes - Endocrine Disease, Medical Publishing House Hanoi, Hanoi, 2010 (in Vietnamese). [5] D. T. M. Hao, T. T. A. Thu, Diabetic Kidney Disease: Attention Problems, Vietnam Journal of Diabetes and Endocrinology, Vol. 38, 2020, pp. 12-17 (in Vietnamese), https://doi.org/10.47122/vjde.2020.38.2. [6] K. Tziomalos, A. Vasilios G, Diabetic Nephropathy: New Risk Factors and Improvements in Diagnosis, The Review of Diabetic Studies: RDS, Vol. 12, No. 1-2, 2015, pp. 110-118, https://doi.org/10.1900/RDS.2015.12.110.[7] American Diabetes Association, 2. Classification and Diagnosis of Diabetes: Standards of Medical Care in Diabetes-2020, Journal Diabetes Care, Vol. 43, No. 1, 2020, pp. S14, https://doi.org/10.2337/dc20-S002.[8] A. S. Levey, J. Coresh, E. Balk, A. T. Kausz, A. Levin, M. W. Steffes, R. J. Hogg, R. D. Perrone, J. Lau, G. Eknoyan, National Kidney Foundation Practice Guidelines for Chronic Kidney Disease: Evaluation, Classification, and Stratification, Ann Intern Med, Vol. 139, 2003, pp. 137-147, https://doi.org/10.7326/0003-4819-139-2-200307150-00013.[9] D. S. Freedman, M. Horlick, G. S. Berenson, A Comparison of The Slaughter Skinfold-thickness Equations and BMI in Predicting Body Fatness and Cardiovascular Disease Risk Factor Levels in Children, The American Journal of Clinical Nutrition, Vol. 98, No. 6, 2013, pp. 1417-1424, https://doi.org/10.3945/ajcn.113.065961.[10] National Heart, Lung and Blood Institutes, National Cholesterol Education Program: ATP III Guidelines at-a-glance Quick Desk Reference, https://www.nhlbi.nih.gov/files/docs/guidelines/atglance.pdf, (accessed on: 5th April 2021).[11] K. Eckardt, B. Kasiske, D. Wheeler, K. Uhlig, D. Miskulin, A. Earley, S. Haynes, J. Lamont, KDIGO 2012 Clinical Practice Guideline for the Evaluation and Management of Chronic Kidney Disease: Definition and Classification of CKD, Kidney International Supplements, Vol. 3, 2013, pp. 5-14, https://doi.org/10.1038/kisup.2012.77.[12] I. H. Boer, M. L. Caramori, J. C. N. Chan, H. J. L. Heerspink, C. Hurst, K. Khunti, A. Liew, E. D. Michos, S. D. navaneethan, P. Rossing, W. A. Olowu, T. Sadusky, N. Tandon, K. R. Tuttle, C. Wanner, K. G. Wilkens, S. Zoungas, KDIGO 2020 Clinical Practice Guideline for Diabetes Management in Chronic Kidney Disease, Kidney international, Vol. 98, No. 4S, 2020, pp. S1-S115, http://dx.doi.org/10.1016/j.kint.2020.06.019.[13] B. T. T. Huong, N. T. Giang, Values of Cystatin C in Early Diagnosis of Renal Disease in Patients with Typ 2 Diabetes in Thai Nguyen National Hospital, Vietnam Medical Journal, Vol. 498, No. 2, 2021, pp. 13-17 (in Vietnamese).[14] L. X. Truong, N. D. Tai, T. Q. P. Linh, T. T. Nhung, The Prevalence of The Positive Microalbumin Urine in The Type 2 Diabetic Patients at District 2 Hospital, Y Hoc TP. Ho Chi Minh, Vol. 22, No. 2, 2018, pp. 139-143 (in Vietnamese).[15] S. Yi, S. Park, Y. Lee, H Park, B. Balkau, J. Yi, Association Between Fasting Glucose and All-cause Mortality According to Sex and Age: A Prospective Cohort Study, Scientific Reports, Vol. 7, No. 1, 2017, pp. 1-9, https://doi.org/10.1038/s41598-017-08498-6.[16] R. Gupta, M. Sharma, N. K. Goyal, P. S. Lodha, K. K. Sharma, Gender Differences in 7 Years Trends in Cholesterol Lipoproteins and Lipids in India: Insights From A Hospital Database, Indian Journal of Endocrinology Metabolism, Vol. 20, No. 2, 2016, pp. 211-8, https://doi.org/10.4103/2230-8210.176362.[17] X. Zhang, Z. Meng, X. Li, M. Liu, X. Ren, M. Zhu, Q. He, Q Zhang, K. Song, Q. Jia, C. Zhang, X Wang, X. Liu, The Association Between Total Bilirubin and Serum Triglyceride in Both Sexes in Chinese, Lipids In Health and Disease, Vol. 17, No. 1, 2017, pp. 1-8, https://doi.org/10.1186/s12944-018-0857-7.[18] S. Palazhy, V. Viswanathan, Lipid Abnormalities in Type 2 Diabetes Mellitus Patients with Overt Nephropathy, Diabetes Metabolism Journal, Vol. 41, No. 2, 2017, pp. 128-134, https://doi.org/ 10.4093/dmj.2017.41.2.128.[19] R. I. Papacocea, D. Timofte, M. Tanasescu, A. Balcangiu stroescu, D. G. Balan, A. Tulin, O. Stiru, I. A. Vacaroiu, A. Mihai, C. C. Popa, C. Cosconel, M. Enyedi, D. Miricescu, L. Raducu, D. Ionescu, Kidney Aging Process and The Management of The Elderly Patient with Renal Impairment, Experimental and Therapeutic Medicine, Vol. 21, 2021, pp. 266, https://doi.org/10.3892/etm.2021.9697.[20] R. D. Lindeman, Overview: Renal Physiology and Pathophysiology of Aging, Am J Kidney Dis, Vol. 16, 1990, pp. 275–282, https://doi.org/10.1016/s0272-6386(12)80002-3.[21] G. Zoppini, G. Targher, M. Chonchol, V. Ortalda, C. Negri, V. Stoicio, E. Bonora, Predictors of Estimated GFR Decline in Patients With Type 2 Diabetes and Preserved Kidney Function, Clinical Journal of the American Society of Nephrology, Vol. 7, No. 3, 2012, pp. 401-408, https://doi.org/10.2215/CJN.07650711.[22] R. Trevisan, A. R. Dodesini, G. Lepore, Lipids and Renal Disease, Journal of the American Society of Nephrology, Vol. 17, No. 2-4, 2006, pp. S145-S147. https://doi.org/10.1681/ASN.2005121320.[23] V. T. Samuel, G. I. Shulman, Mechanisms for Insulin Resistance: Common Threads and Missing Links, Cell, Vol. 148, No. 5, 2012, pp. 852-871, https://doi.org/10.1016/j.cell.2012.02.017.[24] W. Patricia, D. Gloria Michelle, F. Alessia, Systemic and Renal Lipids in Kidney Disease Development and Progression, American Journal of Physiology-Renal Physiology, Vol. 310, No. 6, 2016, pp. F433-F445, https://doi.org/ 10.1152/ajprenal.00375.2015.[25] F. M. Sacks, M. P. Hermans, P. Fioretto, P. Valensi, T. Davis, E. Horton, C. Wanner, K. A. Rubeaan, I. Barzon, L. Bishop, E. Bonora, P. Bunnag, L. Chuang, C. Deerochanawong, R. Goldenberg, B. Harshfiled, C. Hernandez, S. H. Botein, H. Itoh, W. Jia, Y. Jiang, T. Kadowaki, N. Laranjo, L. Leiter, T. Miwwa, M. Odawara, K. Ohashi, A. Ohno, C. Pan, J. Pan, J. P. Botet, Z. Reiner, C. M. Rotella, R. Simo, M. Tanaka, E. T. Reiner, D. T. Barima, G. Zoppini, V. J. Carey, Association between Plasma Triglycerides and High-density Lipoprotein Cholesterol and Microvascular Kidney Disease and Retinopathy in Type 2 Diabetes Mellitus: A Global Case–control Study In 13 Countries, Circulation. Vol. 129, No. 9, 2014, pp. 999-1008, https://doi.org/10.1161/CIRCULATIONAHA.113.002529.[26] Y. Wang, X. Qiu, L. Lv, C. Wang, Z. Ye, S. Li, Q. Liu, T. Lou, X. Liu, Correlation Between Serum Lipid Levels and Measured Glomerular Filtration Rate In Chinese Patients With Chronic Kidney Disease, PLoS One, Vol. 11, No. 10, 2016, pp. e0163767, https://doi.org/10.1371/journal.pone.0163767.[27] N. J. Radcliffe, J. Seah, M. Clarke, R. J. Maclsaac, G. Jerrums, E. I. Ekinci, Clinical Predictive Factors in Diabetic Kidney Disease Progression, Journal of Diabetes Investigation, Vol. 8, No. 1, 2017, pp. 6-18, https://doi.org/10.1111/jdi.12533.[28] D. D. Miao, E. C. Pan, Q. Zhang, Z. M. Sun, Y. Qin, M. Wu, Development and Validation of A Model for Predicting Diabetic Nephropathy in Chinese People, Biomedical and Environmental Sciences, Vol. 30, No. 2, 2017, pp. 106-112, https://doi.org/10.3967/bes2017.014.[29] R. G. Nelson, M. E. Grams, S. H. Ballew, Y. Sang, F. Azizi, S. J. Chadban, L. Chaker, S. C. Dunning, C. Fox, Y. Hirakawa, K. Iseki, J. Ix, T. H. Jafar, A. Kottgen, D. M. J. Naimark, T. Ohjubo, G. J. Prescott, C. M. Bebholz, C. Sabanayagam, T. Sairenchi, B. Schottker, Y. Shibagaki, M. Tonelli, L. Zhang, R. T. Gansevoort, K. Matsushita, M. Woodward, J. Coresh, V. Shalev, Development of Risk Prediction Equations For Incident Chronic Kidney Disease, Jama, Vol. 322, No. 21, 2019, pp. 2104-2114, https://doi.org/10.1001/jama.2019.17379.    

Abstract: This study presents a novel process to synthesize curcumin nanoparticles from fresh turmeric. An ultrasonic-assisted cajeput oil in water emulsion technique was used to synthesize nanocurcumin. The prepared nanocurcumin was spherical with an average size of 47 nm and size distribution of 5–80 nm. The synthesized nanocurcumin showed improved aqueous-phase solubility, and it was used as a reducing agent and stabilizer for biosynthesizing silver nanoparticles. Furthermore, the X-ray diffraction pattern of the silver nanoparticles showed four distinct diffraction peaks at 38.3°, 44.6°, 65.1°, and 78.1° corresponding to the lattice planes of face-centered cubic silver ((111), (200), (220), and (311)). Transmission electron microscopy analysis indicated the average size and maximum size distribution (80 %) of the silver nanoparticles were 10.9 nm and 5–15 nm, respectively. UV–visible spectroscopy measurement of samples indicated the localized surface plasmon resonance absorbance of an aqueous dispersion of silver nanoparticles at 406 nm. Zeta potential analysis revealed a negative charge with a magnitude of −27.2 mV, which indicated higher aqueous dispersion stability of the silver nanoparticles prepared from nanocurcumin. The nanoparticles showed antibacterial activity against Vibrio parahaemolyticus .

Abstract: This study is aimed at exploring undergraduate students’ abilities to recognize anxiety disorder and depression symptoms, and their literacy of mental first-aid supports for these problems. Using a mixed-method, cross-sectional design, data were collected from 724 undergraduate students in Hanoi. This used a questionnaire on literacy of anxiety disorder and depression, adapted from the Australian National Survey of Mental Health Literacy and Stigma. The prevalence of the respondents who could identify anxiety disorder and depression symptoms were 25.9% and 42.3%, respectively. Literacy of mental first-aid supports focused on: listening to the person in an understanding way, encouraging the person to be more active, seeking professional help, make appointment with the general doctor.

Abstract: 〈 span 〉 Content addressable memory (CAM) and ternary content addressable memory (TCAM) are specialized high-speed memories for data searching. CAM and TCAM have many applications in network routing, packet forwarding and Internet data centers. These types of memories have drawbacks on power dissipation and area. As field-programmable gate array (FPGA) is recently being used for network acceleration applications, the demand to integrate TCAM and CAM on FPGA is increasing. Because most FPGAs do not support native TCAM and CAM hardware, methods of implementing algorithmic TCAM using FPGA resources have been proposed through recent years. Algorithmic TCAM on FPGA have the advantages of FPGAs low power consumption and high intergration scalability. This paper proposes a scaleable algorithmic TCAM design on FPGA. The design uses memory blocks to negate power dissipation issue and data collision to save area. The paper also presents a design of a 256 x 104-bit algorithmic TCAM on Intel FPGA Cyclone V, evaluates the performance and application ability of the design on large scale and in future developments. 〈 /span 〉

Abstract: The AFFINITY trial (Assessment of Fluoxetine in Stroke Recovery) reported that oral fluoxetine 20 mg daily for 6 months after acute stroke did not improve functional outcome and increased the risk of falls, bone fractures, and seizures. After trial medication was ceased at 6 months, survivors were followed to 12 months post-randomization. This preplanned secondary analysis aimed to determine any sustained or delayed effects of fluoxetine at 12 months post-randomization. Methods: AFFINITY was a randomized, parallel-group, double-blind, placebo-controlled trial in adults (n=1280) with a clinical diagnosis of stroke in the previous 2 to 15 days and persisting neurological deficit who were recruited at 43 hospital stroke units in Australia (n=29), New Zealand (4), and Vietnam (10) between 2013 and 2019. Participants were randomized to oral fluoxetine 20 mg once daily (n=642) or matching placebo (n=638) for 6 months and followed until 12 months after randomization. The primary outcome was function, measured by the modified Rankin Scale, at 6 months. Secondary outcomes for these analyses included measures of the modified Rankin Scale, mood, cognition, overall health status, fatigue, health-related quality of life, and safety at 12 months. Results: Adherence to trial medication was for a mean 167 (SD 48) days and similar between randomized groups. At 12 months, the distribution of modified Rankin Scale categories was similar in the fluoxetine and placebo groups (adjusted common odds ratio, 0.93 [95% CI, 0.76–1.14]; P =0.46). Compared with placebo, patients allocated fluoxetine had fewer recurrent ischemic strokes (14 [2.18%] versus 29 [4.55%] ; P =0.02), and no longer had significantly more falls (27 [4.21%] versus 15 [2.35%] ; P =0.08), bone fractures (23 [3.58%] versus 11 [1.72%] ; P =0.05), or seizures (11 [1.71%] versus 8 [1.25%] ; P =0.64) at 12 months. Conclusions: Fluoxetine 20 mg daily for 6 months after acute stroke had no delayed or sustained effect on functional outcome, falls, bone fractures, or seizures at 12 months poststroke. The lower rate of recurrent ischemic stroke in the fluoxetine group is most likely a chance finding. Registration: URL: http://www.anzctr.org.au/ ; Unique identifier: ACTRN12611000774921.

Abstract: One hundred days after severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was first reported in Vietnam on 23 January, 270 cases were confirmed, with no deaths. We describe the control measures used by the government and their relationship with imported and domestically acquired case numbers, with the aim of identifying the measures associated with successful SARS-CoV-2 control. Methods Clinical and demographic data on the first 270 SARS-CoV-2 infected cases and the timing and nature of government control measures, including numbers of tests and quarantined individuals, were analyzed. Apple and Google mobility data provided proxies for population movement. Serial intervals were calculated from 33 infector-infectee pairs and used to estimate the proportion of presymptomatic transmission events and time-varying reproduction numbers. Results A national lockdown was implemented between 1 and 22 April. Around 200 000 people were quarantined and 266 122 reverse transcription polymerase chain reaction (RT-PCR) tests conducted. Population mobility decreased progressively before lockdown. In total, 60% (163/270) of cases were imported; 43% (89/208) of resolved infections remained asymptomatic for the duration of infection. The serial interval was 3.24 days, and 27.5% (95% confidence interval [CI], 15.7%-40.0%) of transmissions occurred presymptomatically. Limited transmission amounted to a maximum reproduction number of 1.15 (95% CI, .·37–2.·36). No community transmission has been detected since 15 April. Conclusions Vietnam has controlled SARS-CoV-2 spread through the early introduction of mass communication, meticulous contact tracing with strict quarantine, and international travel restrictions. The value of these interventions is supported by the high proportion of asymptomatic and imported cases, and evidence for substantial presymptomatic transmission.

Abstract: Little is known about the natural history of asymptomatic severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. Methods We conducted a prospective study at a quarantine center for coronavirus disease 2019 in Ho Chi Minh City, Vietnam. We enrolled quarantined people with reverse-transcription polymerase chain reaction (RT-PCR)–confirmed SARS-CoV-2 infection, collecting clinical data, travel and contact history, and saliva at enrollment and daily nasopharyngeal/throat swabs (NTSs) for RT-PCR testing. We compared the natural history and transmission potential of asymptomatic and symptomatic individuals. Results Between 10 March and 4 April 2020, 14 000 quarantined people were tested for SARS-CoV-2; 49 were positive. Of these, 30 participated in the study: 13 (43%) never had symptoms and 17 (57%) were symptomatic. Seventeen (57%) participants imported cases. Compared with symptomatic individuals, asymptomatic people were less likely to have detectable SARS-CoV-2 in NTS collected at enrollment (8/13 [62%] vs 17/17 [100%] ; P = .02). SARS-CoV-2 RNA was detected in 20 of 27 (74%) available saliva samples (7 of 11 [64%] in the asymptomatic group and 13 of 16 [81%] in the symptomatic group; P = .56). Analysis of RT-PCR positivity probability showed that asymptomatic participants had faster viral clearance than symptomatic participants (P  & lt; .001 for difference over the first 19 days). This difference was most pronounced during the first week of follow-up. Two of the asymptomatic individuals appeared to transmit SARS-CoV-2 to 4 contacts. Conclusions Asymptomatic SARS-CoV-2 infection is common and can be detected by analysis of saliva or NTSs. The NTS viral loads fall faster in asymptomatic individuals, but these individuals appear able to transmit the virus to others.