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2. Clinical profile and prognosis of patients with acute kidney injury from a tertiary care hospital in south India

Author

Priyashree R, Shyamsundar CM, and Kumar NS

Subjects
acute kidney injury, infections, hemodialysis, mortality, Medicine (General), R5-920
Abstract

Introduction: Acute kidney injury (AKI) is associated with significant mortality and prognosis depends on spectrum of etiologies and management. There are regional differences in etiology and outcomes of AKI. This study was undertaken to determine clinical characteristics, etiologies of AKI, modality of treatment and prognosis of AKI in our cohort of population. Methodology: This is a retrospective observational study conducted over a period of 6 months from a tertiary care hospital. All patients above 15 years admitted with AKI are included in the study. Clinical parameters, risk factors, cause of AKI (as per KDIGO criteria) and treatment received were studied. Patients with underlying chronic kidney disease (CKD), obstructive causes, drugs and toxin mediated AKI were excluded from the study. Results: A total of 50 patients with AKI were studied in this period. The mean age of patient was 41 years with slightly predominant male patients. The common etiologies of AKI included: infections (48%), snake bite (18%), hepatorenal syndrome (18%), cardiorenal causes (10%), and rhabdomyolysis in 6%. Oliguria was most common symptom at presentation (46%) followed by fever and breathlessness. Dialysis was required in 22 patients. Dialysis was equally effective in infective and non-infective causes of AKI. Mean duration of hospital stay was 7.8±2.5 days. Two patients died during study period due to multiorgan failure. Conclusion: Infections are common cause for AKI in this study. Renal replacement therapy is equally effective in both infective and non-infective causes of AKI with favourable prognosis.

Published
2022
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3. Arterial blood gas analysis and dyselectrolytemia in acute exacerbation of COPD as a prognostic marker

Author

Priyashree R, Kumar NS, and Handargal HN

Subjects
pulmonary disease, copd, dyselectrolytemia, acute exacerbation, Medicine (General), R5-920
Abstract

Background: Chronic obstructive pulmonary disease (COPD) is a disease state characterized by airflow limitation that is not fully reversible. COPD is the umbrella term used to include three different respiratory conditions defined clinically as chronic bronchitis and pathologically as Emphysema and it also includes small airway disease. COPD patients mostly present with the features of acute respiratory infectionsbut there may be a number of metabolic derangements arising out of the disease process or as a consequence of the therapy instituted like hyponatremia, hypokalemia, elevated liver enzymes and blood urea. These abnormalities are very often missed and may contribute to morbidity and mortality, if overlooked. Objectives: To study the levels of hypoxemia and serum electrolytes like sodium and potassium in cases of acute exacerbation of COPD and to assess the significance of dyselectrolytemia, as a prognostic marker in these patients. Materials and methods: The study was undertaken from November 2014 to October 2016 among the patients attending, Victoria hospital and Bowring and Lady Curzon hospital attached to Bangalore Medical College and Research Institute, with acute exacerbation of COPD diagnosed clinically and by the pulmonary function tests. 50 patients with acute exacerbation of COPD and 50 disease free healthy controls were included in the study. The Statistical software SAS 9.2, SPSS 15.0, were used for the analysis of the data and Microsoft word and excel have been used to generate graphs, tables etc. Conclusion: Electrolyte abnormalities are most commonly seen in patients with COPD with acute exacerbation and carry very poor prognosis in this group of patients. Thus, overlooking of coexistant metabolic abnormalities may contribute to a great deal of mortality and morbidity in COPD patients during their acute exacerbation episodes.

Published
2021
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4. Valsartan in combination with metformin and gliclazide in diabetic rat model using developed RP-HPLC method

Author

Rasmita Patra, Yedukondalu Kollati, Sampath Kumar NS, and Vijaya R. Dirisala

Subjects
RP-HPLC, Metformin, Valsartan, Gliclazide, Hypertension, Diabetes mellitus, Therapeutics. Pharmacology, RM1-950, Pharmacy and materia medica, RS1-441
Abstract

Abstract Background Oral administration of biguanides (metformin) and sulfonylureas (gliclazide) are the most common approach of management of type 2 diabetes in humans. Among these diabetic patients, approximately 40–60% suffers from hypertension. Hence, the need of the day is application of polytherapy. A major challenge in polytherapy is the drug-drug interactions that may arise. Hence, this study is focused to develop a reverse phase high-performance liquid chromatography (RP-HPLC) method for concurrent estimation of diabetic drug metformin and hypertension drug valsartan using C18 column and find any possible pharmacokinetic interactions between the two drug combinations strategies, i.e., metformin-valsartan and gliclazide-valsartan in streptozotocin-induced diabetic rats. Result The bioanalysis of drug-drug interaction pharmacokinetic result showed no significant difference in the tmax of single treatment of gliclazide and single treatment of metformin or upon co-administration with valsartan. Conclusion Our study has shown that polytherapy of valsartan, a drug administered for hypertension along with hypoglycemic drugs metformin and gliclazide, can be advantageous and safe in patients suffering from both diabetes and hypertension.

Published
2021
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5. Clinical profile and risk stratification in multidrug-resistant tuberculosis (MDR-TB) and non-MDR-TB patients: A prospective study in a tertiary care hospital

Author

Kumar NS, Priyashree R, Gopal KV, and Gadwalkar RS

Subjects
multidrug resistant tb, breathlessness, human immunodeficiency virus, cavity lesion, reticulonodular patterns, Medicine (General), R5-920
Abstract

Background: Multidrug resistant tuberculosis (MDR-TB) is a major threat for successful control of TB. Early diagnosis and drug sensitivity testing helps in improving disease prevalence. This study was undertaken to determine clinical profile and risk factors for MDR-TB and factors differentiating it from non MDR-TB. Materials and methods: This is a prospective study conducted at a TB hospital attached to Vijayanagara institute of medical sciences, Bellary, Karnataka in South India over a period of 2 years. All patients diagnosed with MDR-TB were studied for clinical parameters and another cohort of non MDR-TB in same study period were included for comparison. Clinical and radiological characteristics, and risk factors were compared between two groups. Results: A total of 59 MDR-TB and 72 non MDR-TB patients were studied in this period. Males were predominant in both groups. Body mass index (BMI) was significantly low in MDR-TB group (18.5 vs 20.3 kg/m2). Among clinical symptoms, breathlessness was significantly seen in MDR-TB group. Defaulter, failure and relapse were seen in 6.8%, 54.3% and 37.3% respectively. Cavitary lesions and reticulonodular patterns in imaging were significantly seen in MDR group. Eight patients in non MDR group had human immunodeficiency virus (HIV) infection compared to one patient in MDR. Conclusion: Presence of cavity and reticulonodular patterns in imaging, significant breathlessness and lower BMI are significantly common in MDR TB patients. These parameters maybe considered for early suspicion and monitoring for drug resistance in index presentation.

Published
2021
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7. A Molecular Epidemiological Analysis Of Programmed Cell Death Ligand-1 (PD-L1) Protein Expression, Mutations And Survival In Non-Small Cell Lung Cancer

Author

Schabath MB, Dalvi TB, Dai HA, Crim AL, Midha A, Shire N, Gimbrone NT, Walker J, Greenawalt DM, Lawrence D, Rigas JR, Brody R, Potter D, Kumar NS, Huntsman SA, and Gray JE

Subjects
non-small cell lung cancer, patient outcomes, tumor mutational burden, prognostic biomarker, Neoplasms. Tumors. Oncology. Including cancer and carcinogens, RC254-282
Abstract

Matthew B Schabath,1,2 Tapashi B Dalvi,3 Hongyue A Dai,4 Alan L Crim,4 Anita Midha,5 Norah Shire,3 Nicholas T Gimbrone,1 Jill Walker,6 Danielle M Greenawalt,7 David Lawrence,8 James R Rigas,9 Robert Brody,9 Danielle Potter,9 Naveen S Kumar,4 Shane A Huntsman,4 Jhanelle E Gray2 1Department of Cancer Epidemiology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, USA; 2Department of Thoracic Oncology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, USA; 3Oncology R&D, AstraZeneca, Gaithersburg, MD, USA; 4M2Gen, Tampa, FL, USA; 5Department of Personalised Healthcare and Biomarkers, AstraZeneca, Cambridge, UK; 6Department of Precision Medicine Oncology, AstraZeneca, Cambridge, UK; 7Department of iMED Oncology Informatics, AstraZeneca, Waltham, MA, USA; 8Department of Global Medicines Development, AstraZeneca, Cambridge, UK; 9Department of Global Medical Affairs Oncology, AstraZeneca, Gaithersburg, MD, USACorrespondence: Matthew B SchabathH. Lee Moffitt Cancer Center and Research Institute, Tampa, FL 33612, USATel +1 813 745 4150Fax +1 813 745 6525Email matthew.schabath@moffitt.orgPurpose: To characterize programmed cell death ligand-1 (PD-L1) expression in relation to survival and gene mutation status in patients with advanced NSCLC. The study also explored the influence of tumor mutational burden (TMB) on PD-L1 expression and patient characteristics.Patients and methods: Adult patients with histologically or cytologically documented Stage IIIB/Stage IV/recurrent/progressive NSCLC, Eastern Cooperative Oncology Group performance status 0 to 3, and >2 lines of prior systemic treatment regimens were included in this retrospective analysis. Patients were treated from 1997 to 2015 at H. Lee Moffitt Cancer Center and Research Institute, Tampa, or at 7 community centers across the United States. PD-L1 expression level was determined using the VENTANA PD-L1 (SP263) Assay. EGFR and KRAS mutation status and ALK rearrangements were determined by targeted DNA sequencing; these were obtained from clinical records where targeted DNA sequencing was not performed. TMB was calculated as the total number of somatic mutations per sample.Results: From a total of 136 patients included in the study, 23.5% had tumors with high PD-L1 expression (≥25%). There were no significant differences in patient characteristics, overall survival (OS), and progression-free survival (PFS) between patients with high PD-L1 expression (median OS: 39.5 months; median PFS: 15.8 months) vs low PD-L1 expression (

Published
2019

8. Knowledge, Attitude and Practice in Managing Chronic Kidney Disease with SGLT2 Inhibitors

Author

Bipin Kumar Sethi, Chethan Dev K, Praveen Kumar Ns, A Thamburaj, Ashish Birla, Ashish Prasad, Bipin Kumar Sethi, Chethan Dev K, Praveen Kumar Ns, A Thamburaj, Ashish Birla, and Ashish Prasad

Abstract

Background and objective: Chronic kidney disease (CKD), and its increasing global burden, is associated with significant morbidity and mortality. This survey-based study aims to capture the knowledge, attitude and practices (KAP) amongst practicing physicians in considering sodium-glucose co-transporter 2 inhibitors (SGLT2i) for the prevention and progression of CKD in diabetic or nondiabeticindividuals. Methodology: An online questionnaire-based survey was conducted among 262 health care practitioners (HCPs) who manage people with CKD with or without diabetes. The survey was prepared as a Google form and circulated through email to different HCPs. The survey consisted of 6 knowledge-based questions, 4 attitude-based questions and 4 practice-based questions. The forms were filled up voluntarily by the participants and the authors had no control over the response provided. All the responses wereconsolidated using Microsoft Excel and analyzed. Results: A total of 262 HCPs from different regions of the country participated in the survey. About 87% to 94% of the participants were aware that SGLT2i, specifically dapagliflozin, is approved for use in CKD patients with or without diabetes. About threefourths of the HCPs accepted that an initial drop in estimated glomerular filtration rate (eGFR) occursupon initiation of dapagliflozin treatment. Almost 90% of them acknowledged the importance of screening for CKD in diabetic patients, and the majority were aware of the renal benefits of SGLT2i. Almost 96% of HCPs consider that dapagliflozin could be used in all patients with CKD irrespective of their diabetes status. Major determining factors with respect to a setback in practice are fear of side effects (54%) and hesitation in switching to newer medications when older medications work fine (34%). Conclusion:SGLT2i have demonstrated significant clinical benefits in patients with CKD with or without diabetes. This survey has shown good awareness among clinicians of the benefi

Published
2023

13. Evolution of Synonymous Codon Usage Bias in West African and Central African Strains of Monkeypox Virus

Author

Sudeesh Karumathil, Nimal T Raveendran, Doss Ganesh, Sampath Kumar NS, Rahul R Nair, and Vijaya R Dirisala

Subjects
Evolution, QH359-425
Abstract

The evolution of bias in synonymous codon usage in chosen monkeypox viral genomes and the factors influencing its diversification have not been reported so far. In this study, various trends associated with synonymous codon usage in chosen monkeypox viral genomes were investigated, and the results are reported. Identification of factors that influence codon usage in chosen monkeypox viral genomes was done using various codon usage indices, such as the relative synonymous codon usage, the effective number of codons, and the codon adaptation index. The Spearman rank correlation analysis and a correspondence analysis were used for correlating various factors with codon usage. The results revealed that mutational pressure due to compositional constraints, gene expression level, and selection at the codon level for utilization of putative optimal codons are major factors influencing synonymous codon usage bias in monkeypox viral genomes. A cluster analysis of relative synonymous codon usage values revealed a grouping of more virulent strains as one major cluster (Central African strains) and a grouping of less virulent strains (West African strains) as another major cluster, indicating a relationship between virulence and synonymous codon usage bias. This study concluded that a balance between the mutational pressure acting at the base composition level and the selection pressure acting at the amino acid level frames synonymous codon usage bias in the chosen monkeypox viruses. The natural selection from the host does not seem to have influenced the synonymous codon usage bias in the analyzed monkeypox viral genomes.

Published
2018
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14. Valsartan in combination with metformin and gliclazide in diabetic rat model using developed RP-HPLC method

Author

Vijaya R. Dirisala, R. C. Patra, Yedukondalu Kollati, and Sampath Kumar Ns

Subjects
Drug, media_common.quotation_subject, 030209 endocrinology & metabolism, Type 2 diabetes, RM1-950, Pharmacology, 01 natural sciences, 03 medical and health sciences, 0302 clinical medicine, Diabetes mellitus, Pharmacy and materia medica, Pharmacokinetics, Oral administration, medicine, Gliclazide, media_common, business.industry, 010401 analytical chemistry, medicine.disease, Metformin, 0104 chemical sciences, RS1-441, Valsartan, RP-HPLC, Hypertension, Therapeutics. Pharmacology, business, medicine.drug
Abstract

Background Oral administration of biguanides (metformin) and sulfonylureas (gliclazide) are the most common approach of management of type 2 diabetes in humans. Among these diabetic patients, approximately 40–60% suffers from hypertension. Hence, the need of the day is application of polytherapy. A major challenge in polytherapy is the drug-drug interactions that may arise. Hence, this study is focused to develop a reverse phase high-performance liquid chromatography (RP-HPLC) method for concurrent estimation of diabetic drug metformin and hypertension drug valsartan using C18 column and find any possible pharmacokinetic interactions between the two drug combinations strategies, i.e., metformin-valsartan and gliclazide-valsartan in streptozotocin-induced diabetic rats. Result The bioanalysis of drug-drug interaction pharmacokinetic result showed no significant difference in the tmax of single treatment of gliclazide and single treatment of metformin or upon co-administration with valsartan. Conclusion Our study has shown that polytherapy of valsartan, a drug administered for hypertension along with hypoglycemic drugs metformin and gliclazide, can be advantageous and safe in patients suffering from both diabetes and hypertension.

Published
2021

15. Diabetes mortality and trends before 25 years of age: an analysis of the Global Burden of Disease Study 2019

Author

Cousin, E, Duncan, BB, Stein, C, Ong, KL, Vos, T, Abbafati, C, Abbasi-Kangevari, M, Abdelmasseh, M, Abdoli, A, Abd-Rabu, R, Abolhassani, H, Abu-Gharbieh, E, Accrombessi, MMK, Adnani, QES, Afzal, MS, Agarwal, G, Agrawaal, KK, Agudelo-Botero, M, Ahinkorah, BO, Ahmad, S, Ahmad, T, Ahmadi, K, Ahmadi, S, Ahmadi, A, Ahmed, A, Salih, YA, Akande-Sholabi, W, Akram, T, Al Hamad, H, Al-Aly, Z, Alcalde-Rabanal, JE, Alipour, V, Aljunid, SM, Al-Raddadi, RM, Alvis-Guzman, N, Amini, S, Ancuceanu, R, Andrei, T, Andrei, CL, Anjana, RM, Ansar, A, Antonazzo, IC, Antony, B, Anyasodor, AE, Arabloo, J, Arizmendi, D, Armocida, B, Artamonov, AA, Arulappan, J, Aryan, Z, Asgari, S, Ashraf, T, Astell-Burt, T, Atorkey, P, Atout, MMW, Ayanore, MA, Badiye, AD, Baig, AA, Bairwa, M, Baker, JL, Baltatu, OC, Banik, PC, Barnett, A, Barone, MTU, Barone-Adesi, F, Barrow, A, Bedi, N, Belete, R, Belgaumi, UI, Bell, AW, Bennett, DA, Bensenor, IM, Beran, D, Bhagavathula, AS, Bhaskar, S, Bhattacharyya, K, Bhojaraja, VS, Bijani, A, Bikbov, B, Birara, S, Bodolica, V, Bonny, A, Brenner, H, Briko, NI, Butt, ZA, dos Santos, FLC, Camera, LA, Campos-Nonato, IR, Cao, Y, Cao, C, Cerin, E, Chakraborty, PA, Chandan, JS, Chattu, VK, Chen, S, Choi, J-YJ, Choudhari, SG, Chowdhury, EK, Chu, D-T, Corso, B, Dadras, O, Dai, X, Damasceno, AAM, Dandona, L, Dandona, R, Davila-Cervantes, CA, De Neve, J-W, Denova-Gutierrez, E, Dhamnetiya, D, Diaz, D, Ebtehaj, S, Edinur, HA, Eftekharzadeh, S, El Sayed, I, Elgendy, IY, Elhadi, M, Elmonem, MA, Faisaluddin, M, Farooque, U, Feng, X, Fernandes, E, Fischer, F, Flood, D, Freitas, M, Gaal, PA, Gad, MM, Gaewkhiew, P, Getacher, L, Ghafourifard, M, Gheshlagh, RG, Ghashghaee, A, Ghith, N, Ghozali, G, Gill, PS, Ginawi, IA, Glushkova, EV, Golechha, M, Gopalani, SV, Guimaraes, RA, Das Gupta, R, Gupta, R, Gupta, VK, Gupta, VB, Gupta, S, Habtewold, TD, Hafezi-Nejad, N, Halwani, R, Hanif, A, Hankey, GJ, Haque, S, Hasaballah, AI, Hasan, SS, Hashi, A, Hassanipour, S, Hay, SI, Hayat, K, Heidari, M, Hossain, MBH, Hossain, S, Hosseini, M, Hoveidamanesh, S, Huang, J, Humayun, A, Hussain, R, Hwang, B-F, Ibitoye, SE, Ikuta, KS, Inbaraj, LR, Iqbal, U, Islam, MS, Islam, SMS, Islam, RM, Ismail, NE, Isola, G, Itumalla, R, Iwagami, M, Iyamu, IO, Jahani, MA, Jakovljevic, M, Jayawardena, R, Jha, RP, John, O, Jonas, JB, Joo, T, Kabir, A, Kalhor, R, Kamath, A, Kanchan, T, Kandel, H, Kapoor, N, Kayode, GA, Kebede, SA, Keshavarz, P, Keykhaei, M, Khader, YS, Khajuria, H, Khan, MAB, Khan, MN, Khan, M, Khater, AM, Khoja, TAM, Khubchandani, J, Kim, MS, Kim, YJ, Kimokoti, RW, Kisa, S, Kisa, A, Kivimaki, M, Korshunov, VA, Korzh, O, Koyanagi, A, Krishan, K, Defo, BK, Kumar, GA, Kumar, N, Kusuma, D, La Vecchia, C, Lacey, B, Larsson, AO, Lasrado, S, Lee, W-C, Lee, CB, Lee, PH, Lee, SWH, Li, M-C, Lim, SS, Lim, L-L, Lucchetti, G, Majeed, A, Malik, AA, Mansouri, B, Mantovani, LG, Martini, S, Mathur, P, McAlinden, C, Mehedi, N, Mekonnen, T, Menezes, RG, Mersha, AG, Jonasson, JM, Miazgowski, T, Michalek, IM, Mirica, A, Mirrakhimov, EM, Mirza, AZ, Mithra, P, Mohammadian-Hafshejani, A, Mohammadpourhodki, R, Mohammed, A, Mokdad, AH, Molokhia, M, Monasta, L, Moni, MA, Moradpour, F, Moradzadeh, R, Mostafavi, E, Mueller, UO, Murray, CJL, Mustafa, A, Nagel, G, Nangia, V, Naqvi, AA, Nayak, BP, Nazari, J, Ndejjo, R, Negoi, RI, Kandel, N, Nguyen, CT, Nguyen, HLT, Noubiap, JJ, Nowak, C, Oancea, B, Odukoya, OO, Oguntade, AS, Ojo, TT, Olagunju, AT, Onwujekwe, OE, Ortiz, A, Owolabi, MO, Palladino, R, Panda-Jonas, S, Pandi-Perumal, SR, Pardhan, S, Parekh, T, Parvizi, M, Pepito, VCF, Perianayagam, A, Petcu, I-R, Pilania, M, Podder, V, Polibin, RV, Postma, MJ, Prashant, A, Rabiee, N, Rabiee, M, Rahimi-Movaghar, V, Rahman, MA, Rahman, MM, Rahman, M, Rahmawaty, S, Rajai, N, Ram, P, Rana, J, Ranabhat, K, Ranasinghe, P, Rao, CR, Rao, S, Rawaf, S, Rawaf, DL, Rawal, L, Renzaho, AMN, Rezaei, N, Rezapour, A, Riahi, SM, Ribeiro, D, Rodriguez, JAB, Roever, L, Rohloff, P, Rwegerera, GM, Ryan, PM, Saber-Ayad, MM, Sabour, S, Saddik, B, Moghaddam, SS, Sahebkar, A, Sahoo, H, Saif-Ur-Rahman, K, Salimzadeh, H, Samaei, M, Sanabria, J, Santric-Milicevic, MM, Sathian, B, Sathish, T, Schlaich, MP, Seidu, A-A, Sekerija, M, Kumar, NS, Seylani, A, Shaikh, MA, Shamshad, H, Shawon, MSR, Sheikhbahaei, S, Shetty, JK, Shiri, R, Shivakumar, KM, Shuval, K, Singh, JA, Singh, A, Skryabin, VY, Skryabina, AA, Sofi-Mahmudi, A, Soheili, A, Sun, J, Szerencses, V, Szocska, M, Tabares-Seisdedos, R, Tadbiri, H, Tadesse, EG, Tariqujjaman, M, Thankappan, KR, Thapar, R, Thomas, N, Timalsina, B, Tobe-Gai, R, Tonelli, M, Tovani-Palone, MR, Tran, BX, Tripathy, JP, Car, LT, Tusa, BS, Uddin, R, Upadhyay, E, Tahbaz, SV, Valdez, PR, Vasankari, TJ, Verma, M, Villalobos-Daniel, VE, Vladimirov, SK, Vo, B, Vu, GT, Vukovic, R, Waheed, Y, Wamai, RG, Werdecker, A, Wickramasinghe, ND, Winkler, AS, Wubishet, BL, Xu, X, Xu, S, Jabbari, SHY, Yatsuya, H, Yaya, S, Yazie, TSY, Yi, S, Yonemoto, N, Yunusa, I, Zadey, S, Bin Zaman, S, Zamanian, M, Zamora, N, Zastrozhin, MS, Zastrozhina, A, Zhang, Z-J, Zhong, C, Zmaili, M, Zumla, A, Naghavi, M, Schmidt, MI, Cousin, E, Duncan, BB, Stein, C, Ong, KL, Vos, T, Abbafati, C, Abbasi-Kangevari, M, Abdelmasseh, M, Abdoli, A, Abd-Rabu, R, Abolhassani, H, Abu-Gharbieh, E, Accrombessi, MMK, Adnani, QES, Afzal, MS, Agarwal, G, Agrawaal, KK, Agudelo-Botero, M, Ahinkorah, BO, Ahmad, S, Ahmad, T, Ahmadi, K, Ahmadi, S, Ahmadi, A, Ahmed, A, Salih, YA, Akande-Sholabi, W, Akram, T, Al Hamad, H, Al-Aly, Z, Alcalde-Rabanal, JE, Alipour, V, Aljunid, SM, Al-Raddadi, RM, Alvis-Guzman, N, Amini, S, Ancuceanu, R, Andrei, T, Andrei, CL, Anjana, RM, Ansar, A, Antonazzo, IC, Antony, B, Anyasodor, AE, Arabloo, J, Arizmendi, D, Armocida, B, Artamonov, AA, Arulappan, J, Aryan, Z, Asgari, S, Ashraf, T, Astell-Burt, T, Atorkey, P, Atout, MMW, Ayanore, MA, Badiye, AD, Baig, AA, Bairwa, M, Baker, JL, Baltatu, OC, Banik, PC, Barnett, A, Barone, MTU, Barone-Adesi, F, Barrow, A, Bedi, N, Belete, R, Belgaumi, UI, Bell, AW, Bennett, DA, Bensenor, IM, Beran, D, Bhagavathula, AS, Bhaskar, S, Bhattacharyya, K, Bhojaraja, VS, Bijani, A, Bikbov, B, Birara, S, Bodolica, V, Bonny, A, Brenner, H, Briko, NI, Butt, ZA, dos Santos, FLC, Camera, LA, Campos-Nonato, IR, Cao, Y, Cao, C, Cerin, E, Chakraborty, PA, Chandan, JS, Chattu, VK, Chen, S, Choi, J-YJ, Choudhari, SG, Chowdhury, EK, Chu, D-T, Corso, B, Dadras, O, Dai, X, Damasceno, AAM, Dandona, L, Dandona, R, Davila-Cervantes, CA, De Neve, J-W, Denova-Gutierrez, E, Dhamnetiya, D, Diaz, D, Ebtehaj, S, Edinur, HA, Eftekharzadeh, S, El Sayed, I, Elgendy, IY, Elhadi, M, Elmonem, MA, Faisaluddin, M, Farooque, U, Feng, X, Fernandes, E, Fischer, F, Flood, D, Freitas, M, Gaal, PA, Gad, MM, Gaewkhiew, P, Getacher, L, Ghafourifard, M, Gheshlagh, RG, Ghashghaee, A, Ghith, N, Ghozali, G, Gill, PS, Ginawi, IA, Glushkova, EV, Golechha, M, Gopalani, SV, Guimaraes, RA, Das Gupta, R, Gupta, R, Gupta, VK, Gupta, VB, Gupta, S, Habtewold, TD, Hafezi-Nejad, N, Halwani, R, Hanif, A, Hankey, GJ, Haque, S, Hasaballah, AI, Hasan, SS, Hashi, A, Hassanipour, S, Hay, SI, Hayat, K, Heidari, M, Hossain, MBH, Hossain, S, Hosseini, M, Hoveidamanesh, S, Huang, J, Humayun, A, Hussain, R, Hwang, B-F, Ibitoye, SE, Ikuta, KS, Inbaraj, LR, Iqbal, U, Islam, MS, Islam, SMS, Islam, RM, Ismail, NE, Isola, G, Itumalla, R, Iwagami, M, Iyamu, IO, Jahani, MA, Jakovljevic, M, Jayawardena, R, Jha, RP, John, O, Jonas, JB, Joo, T, Kabir, A, Kalhor, R, Kamath, A, Kanchan, T, Kandel, H, Kapoor, N, Kayode, GA, Kebede, SA, Keshavarz, P, Keykhaei, M, Khader, YS, Khajuria, H, Khan, MAB, Khan, MN, Khan, M, Khater, AM, Khoja, TAM, Khubchandani, J, Kim, MS, Kim, YJ, Kimokoti, RW, Kisa, S, Kisa, A, Kivimaki, M, Korshunov, VA, Korzh, O, Koyanagi, A, Krishan, K, Defo, BK, Kumar, GA, Kumar, N, Kusuma, D, La Vecchia, C, Lacey, B, Larsson, AO, Lasrado, S, Lee, W-C, Lee, CB, Lee, PH, Lee, SWH, Li, M-C, Lim, SS, Lim, L-L, Lucchetti, G, Majeed, A, Malik, AA, Mansouri, B, Mantovani, LG, Martini, S, Mathur, P, McAlinden, C, Mehedi, N, Mekonnen, T, Menezes, RG, Mersha, AG, Jonasson, JM, Miazgowski, T, Michalek, IM, Mirica, A, Mirrakhimov, EM, Mirza, AZ, Mithra, P, Mohammadian-Hafshejani, A, Mohammadpourhodki, R, Mohammed, A, Mokdad, AH, Molokhia, M, Monasta, L, Moni, MA, Moradpour, F, Moradzadeh, R, Mostafavi, E, Mueller, UO, Murray, CJL, Mustafa, A, Nagel, G, Nangia, V, Naqvi, AA, Nayak, BP, Nazari, J, Ndejjo, R, Negoi, RI, Kandel, N, Nguyen, CT, Nguyen, HLT, Noubiap, JJ, Nowak, C, Oancea, B, Odukoya, OO, Oguntade, AS, Ojo, TT, Olagunju, AT, Onwujekwe, OE, Ortiz, A, Owolabi, MO, Palladino, R, Panda-Jonas, S, Pandi-Perumal, SR, Pardhan, S, Parekh, T, Parvizi, M, Pepito, VCF, Perianayagam, A, Petcu, I-R, Pilania, M, Podder, V, Polibin, RV, Postma, MJ, Prashant, A, Rabiee, N, Rabiee, M, Rahimi-Movaghar, V, Rahman, MA, Rahman, MM, Rahman, M, Rahmawaty, S, Rajai, N, Ram, P, Rana, J, Ranabhat, K, Ranasinghe, P, Rao, CR, Rao, S, Rawaf, S, Rawaf, DL, Rawal, L, Renzaho, AMN, Rezaei, N, Rezapour, A, Riahi, SM, Ribeiro, D, Rodriguez, JAB, Roever, L, Rohloff, P, Rwegerera, GM, Ryan, PM, Saber-Ayad, MM, Sabour, S, Saddik, B, Moghaddam, SS, Sahebkar, A, Sahoo, H, Saif-Ur-Rahman, K, Salimzadeh, H, Samaei, M, Sanabria, J, Santric-Milicevic, MM, Sathian, B, Sathish, T, Schlaich, MP, Seidu, A-A, Sekerija, M, Kumar, NS, Seylani, A, Shaikh, MA, Shamshad, H, Shawon, MSR, Sheikhbahaei, S, Shetty, JK, Shiri, R, Shivakumar, KM, Shuval, K, Singh, JA, Singh, A, Skryabin, VY, Skryabina, AA, Sofi-Mahmudi, A, Soheili, A, Sun, J, Szerencses, V, Szocska, M, Tabares-Seisdedos, R, Tadbiri, H, Tadesse, EG, Tariqujjaman, M, Thankappan, KR, Thapar, R, Thomas, N, Timalsina, B, Tobe-Gai, R, Tonelli, M, Tovani-Palone, MR, Tran, BX, Tripathy, JP, Car, LT, Tusa, BS, Uddin, R, Upadhyay, E, Tahbaz, SV, Valdez, PR, Vasankari, TJ, Verma, M, Villalobos-Daniel, VE, Vladimirov, SK, Vo, B, Vu, GT, Vukovic, R, Waheed, Y, Wamai, RG, Werdecker, A, Wickramasinghe, ND, Winkler, AS, Wubishet, BL, Xu, X, Xu, S, Jabbari, SHY, Yatsuya, H, Yaya, S, Yazie, TSY, Yi, S, Yonemoto, N, Yunusa, I, Zadey, S, Bin Zaman, S, Zamanian, M, Zamora, N, Zastrozhin, MS, Zastrozhina, A, Zhang, Z-J, Zhong, C, Zmaili, M, Zumla, A, Naghavi, M, and Schmidt, MI

Abstract

BACKGROUND: Diabetes, particularly type 1 diabetes, at younger ages can be a largely preventable cause of death with the correct health care and services. We aimed to evaluate diabetes mortality and trends at ages younger than 25 years globally using data from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019. METHODS: We used estimates of GBD 2019 to calculate international diabetes mortality at ages younger than 25 years in 1990 and 2019. Data sources for causes of death were obtained from vital registration systems, verbal autopsies, and other surveillance systems for 1990-2019. We estimated death rates for each location using the GBD Cause of Death Ensemble model. We analysed the association of age-standardised death rates per 100 000 population with the Socio-demographic Index (SDI) and a measure of universal health coverage (UHC) and described the variability within SDI quintiles. We present estimates with their 95% uncertainty intervals. FINDINGS: In 2019, 16 300 (95% uncertainty interval 14 200 to 18 900) global deaths due to diabetes (type 1 and 2 combined) occurred in people younger than 25 years and 73·7% (68·3 to 77·4) were classified as due to type 1 diabetes. The age-standardised death rate was 0·50 (0·44 to 0·58) per 100 000 population, and 15 900 (97·5%) of these deaths occurred in low to high-middle SDI countries. The rate was 0·13 (0·12 to 0·14) per 100 000 population in the high SDI quintile, 0·60 (0·51 to 0·70) per 100 000 population in the low-middle SDI quintile, and 0·71 (0·60 to 0·86) per 100 000 population in the low SDI quintile. Within SDI quintiles, we observed large variability in rates across countries, in part explained by the extent of UHC (r2=0·62). From 1990 to 2019, age-standardised death rates decreased globally by 17·0% (-28·4 to -2·9) for all diabetes, and by 21·0% (-33·0 to -5·9) when considering only type 1 diabetes. However, the low SDI quintile had the lowest decline for both all diabetes (-13·6% [-2

Published
2022

16. Population-level risks of alcohol consumption by amount, geography, age, sex, and year: a systematic analysis for the Global Burden of Disease Study 2020

Author

Bryazka, D, Reitsma, MB, Griswold, MG, Abate, KH, Abbafati, C, Kangevari, MA, Kangevari, ZA, Abdoli, A, Abdollahi, M, Abdullah, AYM, Abhilash, ES, Abu Gharbieh, E, Acuna, JM, Addolorato, G, Adebayo, OM, Adekanmbi, V, Adhikari, K, Adhikari, S, Adnani, QES, Afzal, S, Agegnehu, WY, Aggarwal, M, Ahinkorah, BO, Ahmad, AR, Ahmad, S, Ahmad, T, Ahmadi, A, Ahmadi, S, Ahmed, H, Rashid, TA, Akunna, CJ, Al Hamad, H, Alam, MZ, Alem, DT, Alene, KA, Alimohamadi, Y, Alizadeh, A, Allel, K, Alonso, J, Alvand, S, Guzman, NA, Amare, F, Ameyaw, EK, Amiri, S, Ancuceanu, R, Anderson, JA, Andrei, CL, Andrei, T, Arabloo, J, Arshad, M, Artamonov, AA, Aryan, Z, Asaad, M, Asemahagn, MA, Burt, TA, Athari, SS, Atnafu, DD, Atorkey, P, Atreya, A, Ausloos, F, Ausloos, M, Ayano, G, Ayanore, MA, Ayinde, OO, Mateos, JLA, Azadnajafabad, S, Azanaw, MM, Khyavy, MA, Jafari, AA, Azzam, AY, Badiye, AD, Bagheri, N, Bagherieh, S, Bairwa, M, Bakkannavar, SM, Bakshi, RK, Balchut, AH, Null, T, Barra, F, Barrow, A, Baskaran, P, Belo, L, Bennett, DA, Bensenor, IM, Bhagavathula, AS, Bhala, N, Bhalla, A, Bhardwaj, N, Bhardwaj, P, Bhaskar, S, Bhattacharyya, K, Bhojaraja, VS, Bintoro, BS, Blokhina, EAE, Bodicha, BBA, Boloor, A, Bosetti, C, Braithwaite, D, Brenner, H, Briko, NI, Brunoni, AR, Butt, ZA, Cao, C, Cao, Y, Cardenas, R, Carvalho, AF, Carvalho, M, Maia, JMC, Castelpietra, G, de Araujo, LFSC, Cattaruzza, MS, Chakraborty, PA, Charan, J, Chattu, VK, Chaurasia, A, Cherbuin, N, Dinh, TC, Chudal, N, Chung, SC, Churko, C, Ciobanu, LG, Cirillo, M, Claro, RM, Costanzo, S, Cowden, RG, Criqui, MH, Martins, NC, Culbreth, GT, Dachew, BA, Dadras, O, Dai, X, Damiani, G, Dandona, L, Dandona, R, Daniel, BD, Danielewicz, A, Gela, JD, Davletov, K, de Araujo, JAP, de Sa Junior, AR, Debela, SA, Dehghan, A, Demetriades, AK, Molla, MD, Desai, R, Desta, AA, da Silva, DD, Diaz, D, Digesa, LE, Diress, M, Dodangeh, M, Dongarwar, D, Dorostkar, F, Dsouza, HL, Duko, B, Duncan, BB, Edvardsson, K, Ekholuenetale, M, Elgar, FJ, Elhadi, M, Elmonem, MA, Endries, AY, Eskandarieh, S, Etemadimanesh, A, Fagbamigbe, AF, Fakhradiyev, IR, Farahmand, F, Sa Farinha, CSE, Faro, A, Farzadfar, F, Fatehizadeh, A, Fauk, NK, Feigin, VL, Feldman, R, Feng, X, Fentaw, Z, Ferrero, S, Desideri, LF, Filip, I, Fischer, F, Francis, JM, Franklin, RC, Gaal, PA, Gad, MM, Gallus, S, Galvano, F, Ganesan, B, Garg, T, Gebrehiwot, MGD, Gebremeskel, TG, Gebremichael, MA, Gemechu, TR, Getacher, L, Getachew, ME, Obsa, AG, Getie, A, Ghaderi, A, Ghafourifard, M, Ghajar, A, Ghamari, SH, Ghandour, LA, Nour, MG, Ghashghaee, A, Ghozy, S, Glozah, FN, Glushkova, EV, Godos, J, Goel, A, Goharinezhad, S, Golechha, M, Goleij, P, Golitaleb, M, Greaves, F, Grivna, M, Grosso, G, Gudayu, TW, Gupta, B, Gupta, R, Gupta, S, Gupta, VB, Gupta, VK, Nejad, NH, Mirzaian, AH, Hall, BJ, Halwani, R, Handiso, TB, Hankey, GJ, Hariri, S, Haro, JM, Hasaballah, A, Moghaddam, HH, Hay, S, Hayat, K, Heidari, G, Heidari, M, Hendrie, D, Herteliu, C, Heyi, DZ, Hezam, K, Hlongwa, MM, Holla, R, 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MS, Sheikhbahaei, S, Sheikhi, RA, Shetty, A, Shetty, JK, Shiferaw, DS, Shigematsu, M, Shiri, R, Shirkoohi, R, Shivakumar, KM, Shivarov, V, Shobeiri, P, Shrestha, R, Sidemo, NB, Sigfusdottir, ID, Silva, DAS, da Silva, NT, Singh, JA, Singh, S, Skryabin, VY, Skryabina, AA, Sleet, DA, Solmi, M, Solomon, Y, Song, S, Song, Y, Sorensen, RJD, Soshnikov, S, Soyiri, IN, Stein, DJ, Subba, SH, Szocska, M, Seisdedos, RT, Tabuchi, T, Taheri, M, Tan, KK, Tareke, M, Tarkang, EE, Temesgen, G, Temesgen, WA, Temsah, MH, Thankappan, KR, Thapar, R, Thomas, NK, Tiruneh, C, Todorovic, J, Torrado, M, Touvier, M, Palone, MRT, Mai, TNT, Llimos, ST, Tripathy, JP, Vakilian, A, Valizadeh, R, Varmaghani, M, Varthya, SB, Vasankari, TJ, Vos, T, Wagaye, B, Waheed, Y, Walde, MT, Wang, C, Wang, Y, Wang, YP, Westerman, R, Wickramasinghe, ND, Wubetu, AD, Xu, S, Yamagishi, K, Yang, L, Yesera, GEE, Yigit, A, Yigit, V, Yimaw, AE, Yon, DK, Yonemoto, N, Yu, C, Zadey, S, Zahir, M, Zare, I, Zastrozhin, MS, Zastrozhina, A, Zhang, ZJ, Zhong, C, Zmaili, M, Zuniga, YMH, Gakidou, E, Madureira-Carvalho, AM, Bryazka, D, Reitsma, MB, Griswold, MG, Abate, KH, Abbafati, C, Kangevari, MA, Kangevari, ZA, Abdoli, A, Abdollahi, M, Abdullah, AYM, Abhilash, ES, Abu Gharbieh, E, Acuna, JM, Addolorato, G, Adebayo, OM, Adekanmbi, V, Adhikari, K, Adhikari, S, Adnani, QES, Afzal, S, Agegnehu, WY, Aggarwal, M, Ahinkorah, BO, Ahmad, AR, Ahmad, S, Ahmad, T, Ahmadi, A, Ahmadi, S, Ahmed, H, Rashid, TA, Akunna, CJ, Al Hamad, H, Alam, MZ, Alem, DT, Alene, KA, Alimohamadi, Y, Alizadeh, A, Allel, K, Alonso, J, Alvand, S, Guzman, NA, Amare, F, Ameyaw, EK, Amiri, S, Ancuceanu, R, Anderson, JA, Andrei, CL, Andrei, T, Arabloo, J, Arshad, M, Artamonov, AA, Aryan, Z, Asaad, M, Asemahagn, MA, Burt, TA, Athari, SS, Atnafu, DD, Atorkey, P, Atreya, A, Ausloos, F, Ausloos, M, Ayano, G, Ayanore, MA, Ayinde, OO, Mateos, JLA, Azadnajafabad, S, Azanaw, MM, Khyavy, MA, Jafari, AA, Azzam, AY, Badiye, AD, Bagheri, N, Bagherieh, S, Bairwa, M, Bakkannavar, SM, Bakshi, RK, Balchut, AH, Null, T, Barra, F, Barrow, A, Baskaran, P, Belo, L, Bennett, DA, Bensenor, IM, Bhagavathula, AS, Bhala, N, Bhalla, A, Bhardwaj, N, Bhardwaj, P, Bhaskar, S, Bhattacharyya, K, Bhojaraja, VS, Bintoro, BS, Blokhina, EAE, Bodicha, BBA, Boloor, A, Bosetti, C, Braithwaite, D, Brenner, H, Briko, NI, Brunoni, AR, Butt, ZA, Cao, C, Cao, Y, Cardenas, R, Carvalho, AF, Carvalho, M, Maia, JMC, Castelpietra, G, de Araujo, LFSC, Cattaruzza, MS, Chakraborty, PA, Charan, J, Chattu, VK, Chaurasia, A, Cherbuin, N, Dinh, TC, Chudal, N, Chung, SC, Churko, C, Ciobanu, LG, Cirillo, M, Claro, RM, Costanzo, S, Cowden, RG, Criqui, MH, Martins, NC, Culbreth, GT, Dachew, BA, Dadras, O, Dai, X, Damiani, G, Dandona, L, Dandona, R, Daniel, BD, Danielewicz, A, Gela, JD, Davletov, K, de Araujo, JAP, de Sa Junior, AR, Debela, SA, Dehghan, A, Demetriades, AK, Molla, MD, Desai, R, Desta, AA, da Silva, DD, Diaz, D, Digesa, LE, Diress, M, Dodangeh, M, Dongarwar, D, Dorostkar, F, Dsouza, HL, Duko, B, Duncan, BB, Edvardsson, K, Ekholuenetale, M, Elgar, FJ, Elhadi, M, Elmonem, MA, Endries, AY, Eskandarieh, S, Etemadimanesh, A, Fagbamigbe, AF, Fakhradiyev, IR, Farahmand, F, Sa Farinha, CSE, Faro, A, Farzadfar, F, Fatehizadeh, A, Fauk, NK, Feigin, VL, Feldman, R, Feng, X, Fentaw, Z, Ferrero, S, Desideri, LF, Filip, I, Fischer, F, Francis, JM, Franklin, RC, Gaal, PA, Gad, MM, Gallus, S, Galvano, F, Ganesan, B, Garg, T, Gebrehiwot, MGD, Gebremeskel, TG, Gebremichael, MA, Gemechu, TR, Getacher, L, Getachew, ME, Obsa, AG, Getie, A, Ghaderi, A, Ghafourifard, M, Ghajar, A, Ghamari, SH, Ghandour, LA, Nour, MG, Ghashghaee, A, Ghozy, S, Glozah, FN, Glushkova, EV, Godos, J, Goel, A, Goharinezhad, S, Golechha, M, Goleij, P, Golitaleb, M, Greaves, F, Grivna, M, Grosso, G, Gudayu, TW, Gupta, B, Gupta, R, Gupta, S, Gupta, VB, Gupta, VK, Nejad, NH, Mirzaian, AH, Hall, BJ, Halwani, R, Handiso, TB, Hankey, GJ, Hariri, S, Haro, JM, Hasaballah, A, Moghaddam, HH, Hay, S, Hayat, K, Heidari, G, Heidari, M, Hendrie, D, Herteliu, C, Heyi, DZ, Hezam, K, Hlongwa, MM, Holla, R, Hossain, MM, Hossain, S, Hosseini, SK, Hosseinzadeh, M, Hostiuc, M, Hostiuc, S, Hu, G, Huang, J, Hussain, S, Ibitoye, SE, Ilic, IM, Ilic, MD, Immurana, M, Irham, LM, Islam, MM, Islam, RM, Islam, SMS, Iso, H, Itumalla, R, Iwagami, M, Jabbarinejad, R, Jacob, L, Jakovljevic, M, Jamalpoor, Z, Jamshidi, E, Jayapal, SK, Jayarajah, UU, Jayawardena, R, Jebai, R, Jeddi, SA, Jema, AT, Jha, RP, Jindal, HA, Jonas, JB, Joo, T, Joseph, N, Joukar, F, Jozwiak, JJ, Jurisson, M, Kabir, A, Kabthymer, RH, Kamble, BD, Kandel, H, Kanno, GG, Kapoor, N, Karaye, IM, Karimi, SE, Kassa, BG, Kaur, RJ, Kayode, GA, Keykhaei, M, Khajuria, H, Khalilov, R, Khan, IA, Ab Khan, M, Kim, H, Kim, J, Kim, MS, Kimokoti, RW, Kivimaki, M, Klymchuk, V, Knudsen, AKS, Kolahi, AA, Korshunov, VA, Koyanagi, A, Krishan, K, Krishnamoorthy, Y, Kumar, GA, Kumar, N, Ben, L, Lallukka, T, Lasrado, S, Lau, J, Lee, SW, Lee, WC, Lee, YH, Lim, LL, Lim, SS, Lobo, SW, Lopukhov, PD, Lorkowski, S, Lozano, R, Lucchetti, G, Madadizadeh, F, Mahjoub, S, Mahmoodpoor, A, Mahumud, RA, Makki, A, Malekpour, MR, Manjunatha, N, Mansouri, B, Mansournia, MA, Raga, JM, Villa, FAM, Matzopoulos, R, Maulik, PK, Mayeli, M, McGrath, JJ, Meena, JK, Nasab, EM, Menezes, RG, Mensink, GBM, Mentis, AFA, Meretoja, A, Merga, BT, Mestrovic, T, Jonasson, JM, Miazgowski, B, de Sa, ACMGN, Miller, TR, Mini, G, Mirica, A, Mirijello, A, Mirmoeeni, S, Mirrakhimov, EM, Misra, S, Moazen, B, Mobarakabadi, M, Moccia, M, Mohammad, Y, Mohammadi, E, Hafshejani, AM, Mohammed, TA, Moka, N, Mokdad, AH, Momtazmanesh, S, Moradi, Y, Mostafavi, E, Mubarik, S, Mullany, EC, Mulugeta, BT, Zamora, EM, Murray, CJL, Mwita, JC, Naghavi, M, Naimzada, MD, Nangia, V, Nayak, BP, Negoi, I, Negoi, RI, Nejadghaderi, SA, Nepal, S, Neupane, SPP, Kandel, SN, Nigatu, YT, Nowroozi, A, Nuruzzaman, KM, Nzoputam, CI, Obamiro, KO, Ogbo, FA, Oguntade, AS, Aliabad, HO, Olakunde, BO, Oliveira, GMM, Bali, AO, Omer, E, Altamirano, DVO, Otoiu, A, Otstavnov, SS, Oumer, B, Mahesh, PA, Monedero, AP, Palladino, R, Pana, A, Jonas, SP, Pandey, A, Pardhan, S, Parekh, T, Park, EK, Parry, CDH, Kan, FP, Patel, J, Pati, S, Patton, GC, Paudel, U, Pawar, S, Peden, AE, Petcu, IR, Phillips, MR, Pinheiro, M, Plotnikov, E, Pradhan, PMS, Prashant, A, Quan, J, Radfar, A, Rafiei, A, Raghav, PR, Movaghar, VR, Rahman, A, Rahman, MM, Rahman, M, Rahmani, AM, Rahmani, S, Ranabhat, CL, Ranasinghe, P, Rao, CR, Rasali, DP, Rashidi, MM, Ratan, ZA, Rawaf, DL, Rawaf, S, Rawal, L, Renzaho, AMN, Rezaei, N, Rezaei, S, Rezaeian, M, Riahi, SM, Rodriguez, ER, Roth, GA, Rwegerera, GM, Saddik, B, Sadeghi, E, Sadeghian, R, Saeed, U, Saeedi, F, Sagar, R, Sahebkar, A, Sahoo, H, Sahraian, MA, Rahman, KSU, Salahi, S, Salimzadeh, H, Samy, AM, Sanmarchi, F, Milicevic, MMS, Sarikhani, Y, Sathian, B, Saya, GK, Sayyah, M, Schmidt, MI, Schutte, AE, Schwarzinger, M, Schwebel, DC, Seidu, AA, Kumar, NS, SeyedAlinaghi, S, Seylani, A, Sha, F, Shahin, S, Sanavi, FS, Shahrokhi, S, Shaikh, MA, Shaker, E, Shakhmardanov, MZ, Beyranvand, MS, Sheikhbahaei, S, Sheikhi, RA, Shetty, A, Shetty, JK, Shiferaw, DS, Shigematsu, M, Shiri, R, Shirkoohi, R, Shivakumar, KM, Shivarov, V, Shobeiri, P, Shrestha, R, Sidemo, NB, Sigfusdottir, ID, Silva, DAS, da Silva, NT, Singh, JA, Singh, S, Skryabin, VY, Skryabina, AA, Sleet, DA, Solmi, M, Solomon, Y, Song, S, Song, Y, Sorensen, RJD, Soshnikov, S, Soyiri, IN, Stein, DJ, Subba, SH, Szocska, M, Seisdedos, RT, Tabuchi, T, Taheri, M, Tan, KK, Tareke, M, Tarkang, EE, Temesgen, G, Temesgen, WA, Temsah, MH, Thankappan, KR, Thapar, R, Thomas, NK, Tiruneh, C, Todorovic, J, Torrado, M, Touvier, M, Palone, MRT, Mai, TNT, Llimos, ST, Tripathy, JP, Vakilian, A, Valizadeh, R, Varmaghani, M, Varthya, SB, Vasankari, TJ, Vos, T, Wagaye, B, Waheed, Y, Walde, MT, Wang, C, Wang, Y, Wang, YP, Westerman, R, Wickramasinghe, ND, Wubetu, AD, Xu, S, Yamagishi, K, Yang, L, Yesera, GEE, Yigit, A, Yigit, V, Yimaw, AE, Yon, DK, Yonemoto, N, Yu, C, Zadey, S, Zahir, M, Zare, I, Zastrozhin, MS, Zastrozhina, A, Zhang, ZJ, Zhong, C, Zmaili, M, Zuniga, YMH, Gakidou, E, and Madureira-Carvalho, AM

Abstract

BACKGROUND: The health risks associated with moderate alcohol consumption continue to be debated. Small amounts of alcohol might lower the risk of some health outcomes but increase the risk of others, suggesting that the overall risk depends, in part, on background disease rates, which vary by region, age, sex, and year. METHODS: For this analysis, we constructed burden-weighted dose-response relative risk curves across 22 health outcomes to estimate the theoretical minimum risk exposure level (TMREL) and non-drinker equivalence (NDE), the consumption level at which the health risk is equivalent to that of a non-drinker, using disease rates from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2020 for 21 regions, including 204 countries and territories, by 5-year age group, sex, and year for individuals aged 15-95 years and older from 1990 to 2020. Based on the NDE, we quantified the population consuming harmful amounts of alcohol. FINDINGS: The burden-weighted relative risk curves for alcohol use varied by region and age. Among individuals aged 15-39 years in 2020, the TMREL varied between 0 (95% uncertainty interval 0-0) and 0·603 (0·400-1·00) standard drinks per day, and the NDE varied between 0·002 (0-0) and 1·75 (0·698-4·30) standard drinks per day. Among individuals aged 40 years and older, the burden-weighted relative risk curve was J-shaped for all regions, with a 2020 TMREL that ranged from 0·114 (0-0·403) to 1·87 (0·500-3·30) standard drinks per day and an NDE that ranged between 0·193 (0-0·900) and 6·94 (3·40-8·30) standard drinks per day. Among individuals consuming harmful amounts of alcohol in 2020, 59·1% (54·3-65·4) were aged 15-39 years and 76·9% (73·0-81·3) were male. INTERPRETATION: There is strong evidence to support recommendations on alcohol consumption varying by age and location. Stronger interventions, particularly those tailored towards younger individuals, are needed to reduce the substantial global health loss attribu

Published
2022

22. Code Semantic Detection

Author

Arora, Bhavna, primary, VC, Skanda, additional, Dheemanth, G R, additional, Thakral, Mehul, additional, and Kumar, NS, additional

Published
2021
Full Text
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23. A Survey on Workplace Violence Experienced by Critical Care Physicians

Author

Munta K, Harde Y, Dnyaneshwar M, Kumar Ns, Kumar, and Rao Sm

Subjects
medicine.medical_specialty, Workplace violence, business.industry, media_common.quotation_subject, Incidence (epidemiology), Communication, 030208 emergency & critical care medicine, Critical Care and Intensive Care Medicine, Work hours, Scarcity, 03 medical and health sciences, 0302 clinical medicine, 030228 respiratory system, Family medicine, Health care, medicine, Conflict management, Original Article, business, Curriculum, Duty, Verbal violence, media_common, Critical care physicians
Abstract

Introduction Workplace violence (WPV) has been defined as, “violent acts including physical assault and threats of assault directed toward personnel at work or on duty”. Healthcare staff are at highest risk of WPV among the professionals and it is more common among the critical care services. Prevalence of WPV among doctors all over the world is around 56–80% and in Indian scenario, it is around 40.8–75%. There is scarcity of studies on WPV among doctors from India. To our knowledge, this is the first of its kind survey conducted to know about the incidence of WPV amongst critical care physicians in India. Materials and Methods This survey was conducted after taking due ethical committee clearance amongst critical care physicians attending a critical care conference. The purpose of the study was informed to the participants and a pretested, self-administered, semi-structured questionnaire was distributed among them for their voluntary and anonymous response. Results Out of 160 delegates who were given the questionnaire, 118 responses were collected and their forms were analyzed. Maximum responses (84%) received were of age group 20–40 years. Seventy-two percent respondents experienced WPV during their work hours. Most common type of violence reported was verbal violence (67%). Sixty-five percent respondents reported that poor communication was the leading cause of WPV. Due to WPV, most of the respondents (60%) had to change their place and pattern of work. Proper communication (76%) was the most common measure among multiple measures suggested by respondents for avoiding WPV. Eighty-three (98%) respondents opined that conflict management should be part of regular curriculum in medical education. Conclusion Improving the communication skills amongst critical care physicians, teaching doctors about conflict management in their regular curriculum of medical education, spreading awareness in public about patient rights and taking initiatives in propagating an idea to “Fight against the diseases and not against the doctors” are the key measures to combat WPV. How to cite this article Kumar NS, Munta K, Kumar JR, Rao SM, Dnyaneshwar M, Harde Y. A Survey on Workplace Violence Experienced by Critical Care Physicians. Indian J Crit Care Med 2019;23(7):295–301.

Published
2019

24. Nano zinc ferrite modified electrode as a novel electrochemical sensing platform in simultaneous measurement of trace level lead and cadmium

Author

Ashoka S, Pandurangappa Malingappa, and Arun Kumar Ns

Subjects
Cadmium, Materials science, Process Chemistry and Technology, Nanoparticle, chemistry.chemical_element, 02 engineering and technology, 010402 general chemistry, 021001 nanoscience & nanotechnology, Electrochemistry, 01 natural sciences, Pollution, 0104 chemical sciences, Anodic stripping voltammetry, Zinc ferrite, Chemical engineering, chemistry, Electrode, Nano, Chemical Engineering (miscellaneous), Particle size, 0210 nano-technology, Waste Management and Disposal
Abstract

Nano sized zinc ferrite (ZnFe2O4) particles have been synthesized by a simple solution combustion method and its electrochemical sensing application has been reported after modifying the glassy carbon electrode with thin film of zinc ferrite. The nanoparticles have been characterized by FTIR, XRD, BET, FESEM and TEM techniques to ascertain the particle size and its surface morphology. It has been used as an electrochemical sensing tool in the simultaneous measurement of lead and cadmium ions at trace level by differential pulse anodic stripping voltammetry (DPASV). All the experimental variables have been optimized and it has been utilized in real sample analysis. The sensor exhibited wide linearity in the concentration range 10–130 ppb with detection limits of 1.12 and 2.52 ppb for lead and cadmium metal ions, respectively.

Published
2018

25. 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, 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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, 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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

26. 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

31. EVB761368_Supplementary_Material_REV1 – Supplemental material for Evolution of Synonymous Codon Usage Bias in West African and Central African Strains of Monkeypox Virus

Author

Sudeesh Karumathil, Nimal T Raveendran, Doss Ganesh, Sampath Kumar NS, Nair, Rahul R, and Dirisala, Vijaya R

Subjects
Cell Biology
Abstract

Supplemental material, EVB761368_Supplementary_Material_REV1 for Evolution of Synonymous Codon Usage Bias in West African and Central African Strains of Monkeypox Virus by Sudeesh Karumathil, Nimal T Raveendran, Doss Ganesh, Sampath Kumar NS, Rahul R Nair and Vijaya R Dirisala in Evolutionary Bioinformatics

Published
2018
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35. Naphthoquinone Metabolites Produced by Monacrosporium ambrosium, the Ectosymbiotic Fungus of Tea Shot-Hole Borer, Euwallacea fornicatus, in Stems of Tea, Camellia sinensis

Author

Kehelpannala, C, Kumar, NS, Jayasinghe, L, Araya, H, Fujimoto, Y, Kehelpannala, C, Kumar, NS, Jayasinghe, L, Araya, H, and Fujimoto, Y

Abstract

The tea shot-hole borer beetle (TSHB, Euwallacea fornicatus) causes serious damage in plantations of tea, Camellia sinensis var. assamica, in Sri Lanka and South India. TSHB is found in symbiotic association with the ambrosia fungus, Monacrosporium ambrosium (syn. Fusarium ambrosium), in galleries located within stems of tea bushes. M. ambrosium is known to be the sole food source of TSHB. Six naphthoquinones produced during spore germination in a laboratory culture broth of M. ambrosium were isolated and identified as dihydroanhydrojavanicin, anhydrojavanicin, javanicin, 5,8-dihydroxy-2-methyl-3-(2-oxopropyl)naphthalene-1,4-dione, anhydrofusarubin and solaniol. Chloroform extracts of tea stems with red-colored galleries occupied by TSHB contained UV active compounds similar to the above naphthoquinones. Laboratory assays demonstrated that the combined ethyl acetate extracts of the fungal culture broth and mycelium inhibited the growth of endophytic fungi Pestalotiopsis camelliae and Phoma multirostrata, which were also isolated from tea stems. Thus, pigmented naphthoquinones secreted by M. ambrosium during spore germination may prevent other fungi from invading TSHB galleries in tea stems. The antifungal nature of the naphthoquinone extract suggests that it protects the habitat of TSHB. We propose that the TSHB fungal ectosymbiont M. ambrosium provides not only the food and sterol skeleton necessary for the development of the beetle during its larval stages, but also serves as a producer of fungal inhibitors that help to preserve the purity of the fungal garden of TSHB.

Published
2018

36. Effectiveness of Community-Based Rehabilitation on the lives of Parents of Children with Cerebral Palsy: A Mixed Method Study in Karnataka, India.

Author

Bokalial, Doly, Hossain, Md Forhad, Kumar, NS Senthil, and Bajracharya, Shristi

Subjects
COMMUNITY health services, CONFIDENCE intervals, HOME remodeling, HEALTH status indicators, INTERVIEWING, RESEARCH methodology, PARENTS of children with disabilities, QUALITY of life, QUESTIONNAIRES, REHABILITATION, STATISTICAL sampling, SELF-efficacy, SOCIAL participation, LOGISTIC regression analysis, ACCESSIBLE design, ASSISTIVE technology, PSYCHOSOCIAL factors, BURDEN of care, PARENT attitudes, CROSS-sectional method, HEALTH literacy, REHABILITATION of children with cerebral palsy, EVALUATION of human services programs, DATA analysis software, DESCRIPTIVE statistics, INFERENTIAL statistics, ODDS ratio
Abstract

Purpose: The study aimed to identify the effects of the CBR programme on parents of children with Cerebral Palsy, living in Karnataka State, India. It also tried to find the challenges and improvements needed to make the CBR programme more effective. Method: A cross-sectional, descriptive study design was used to collect a sample of 100 parents of children with Cerebral Palsy, with GMFCS levels IV and V. The sample was drawn from various communities in Bangalore, Davanagere and Bijapur, where the services of The Association of People with Disability are available. Face-to-face interviews were conducted with the study subjects. Data was analysed by SPSS using descriptive and inferential statistics. Results: It was observed that the CBR programme had a positive effect on parents' health, knowledge, social lives and empowerment. A binary logistic regression was done to find the relationship between health, knowledge, social lives and assistive devices use. A strong association was found between all the areas (p=.001) except GMFCS and assistive devices use (p=.004) at 95% CI. The odds ratios between them were greater than 1 and showed the strong positive effect of the CBR programme on parents. Conclusion: The CBR programme not only has a positive effect on children with Cerebral Palsy, but also plays an important role in parents' lives. It contributes in a positive way to parents' overall activity. [ABSTRACT FROM AUTHOR]

Published
2020
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39. Evolution of Synonymous Codon Usage Bias in West African and Central African Strains of Monkeypox Virus

Author

Nimal Thattaruparambil Raveendran, Vijaya R. Dirisala, D. Ganesh, Sampath Kumar Ns, Sudeesh Karumathil, and Rahul Raveendran Nair

Subjects
0301 basic medicine, Codon Adaptation Index, viruses, lcsh:Evolution, Monkeypox viruses (MPXV), 03 medical and health sciences, Monkeypox, mutational pressure, Gene expression level, lcsh:QH359-425, Genetics, medicine, Mutational pressure, synonymous codon usage bias (SCUB), Ecology, Evolution, Behavior and Systematics, Selection (genetic algorithm), Original Research, biology, biology.organism_classification, medicine.disease, Computer Science Applications, West african, 030104 developmental biology, selection pressure, Codon usage bias, Monkeypox virus
Abstract

The evolution of bias in synonymous codon usage in chosen monkeypox viral genomes and the factors influencing its diversification have not been reported so far. In this study, various trends associated with synonymous codon usage in chosen monkeypox viral genomes were investigated, and the results are reported. Identification of factors that influence codon usage in chosen monkeypox viral genomes was done using various codon usage indices, such as the relative synonymous codon usage, the effective number of codons, and the codon adaptation index. The Spearman rank correlation analysis and a correspondence analysis were used for correlating various factors with codon usage. The results revealed that mutational pressure due to compositional constraints, gene expression level, and selection at the codon level for utilization of putative optimal codons are major factors influencing synonymous codon usage bias in monkeypox viral genomes. A cluster analysis of relative synonymous codon usage values revealed a grouping of more virulent strains as one major cluster (Central African strains) and a grouping of less virulent strains (West African strains) as another major cluster, indicating a relationship between virulence and synonymous codon usage bias. This study concluded that a balance between the mutational pressure acting at the base composition level and the selection pressure acting at the amino acid level frames synonymous codon usage bias in the chosen monkeypox viruses. The natural selection from the host does not seem to have influenced the synonymous codon usage bias in the analyzed monkeypox viral genomes.

Published
2018

41. Lipodystrophy in Human Immunodeficiency Virus (HIV) Patients on Highly Active Antiretroviral Therapy (HAART)

Author

Vishwanatha H, Menon M, Shashibhushan J, Malappa, Venugopal K, and Kumar Ns

Subjects
medicine.medical_specialty, Clinical Biochemistry, Human immunodeficiency virus (HIV), lcsh:Medicine, medicine.disease_cause, Internal medicine, medicine, Lipid deposition, fat redistribution, lipohypertrophy, Lipoatrophy, lipoatrophy, Internal Medicine Section, business.industry, lcsh:R, virus diseases, Lipohypertrophy, General Medicine, medicine.disease, Antiretroviral therapy, treatment adherance, Fat redistribution, Immunology, Hiv patients, Lipodystrophy, business
Abstract

Background: In recent years, abnormal lipid deposition (both lipoatrophy and fat redistribution) and its related complications have changed from an anecdotal issue into a major problem for HIV (Human Immunodeficiency Virus) infected patients on HAART (Highly Active Anti-Retroviral Therapy). Lipoatrophy and fat redistribution are potentially stigmatizing complications of HAART and leads to poor adherence among patients. Hence we conducted this study to determine the pattern and to assess various risk factors for maldeposition of lipids in HIV patients. Materials and Methods: A cross-sectional case series study was conducted in ART PLUS centre, Bellary over a period of 8 months from January to August 2014 in HIV patients on ART to determine risk factors associated with and epidemiological pattern of fat redistribution or atrophy. Results: A total of 50 patients with LD {lipodystrophy} (26 with fat redestribution and 24 with lipoatrophy {LA} were diagnosed in this period. Most of them belonged to younger age and was commonly seen in females (76%). Patients with LA had a significantly lower BMI (18.73 ± 7.4), {the p-value being 0.19} compared to LH group (21.54 ± 7.62). The duration of disease was comparable among both groups (6.96 years in LH and 5.79 years in LA group) {p-value is 0.29}. There was a relatively good immunity among these patients with mean CD4 count was 509.23 in LH and 545.91 in LA group {single CD4 count was taken and the p-value was 0.001}. Most of the patients were in TLN (Tenofovir, Lamivudine, Nevirapine) regimen (58%). The duration that patient was on ART before commencement of study varied from patient to patient, but the mean duration was approximately five years in fat redistribution group and 4.5 years in LA group. There were no derangements in lipid and sugar levels among them. Conclusion: This study shows the need to identify and impact of LD with respect to treatment adherence in young patients especially female patients. Early community based screening for LD by social workers and targeted annual screening might help early detection and awareness about LD. Also adopting the least toxic regimen is one of the main aspects of LD management.

Published
2015

42. Production of Antitumor Antibiotic GKK1032B by Penicillium citrinum, an Endophytic Fungus Isolated from Garcinia mangostana Fruits

Author

Qader Mm, Kumar Ns, Yoshinori Fujimoto, and Jayasinghe L

Subjects
food.ingredient, biology, food and beverages, Fungus, biology.organism_classification, Plant use of endophytic fungi in defense, Citrinin, chemistry.chemical_compound, food, chemistry, Penicillium, Botany, Garcinia mangostana, Fermentation, Food science, Penicillium citrinum, Mycelium
Abstract

Endophytic fungi are considered as a good source to produce important secondary metabolites with interesting bioactivities. In a continuation of our studies towards the search for environmentally friendly bioactive compounds from Sri Lankan flora we investigated the secondary metabolites produced by the endophytic fungi Penicillium citrinum isolated from the fruits of Garcinia mangostana. The pure culture of the P. citrinum was grown on potato dextrose broth (PDB) media. After four weeks fermentation, fungal medium and mycelium were extracted with ethyl acetate. Chromatographic separation of the EtOAc extracts over silica gel, Sephadex LH-20 and PTLC furnished a peptide-polyketide hybrid compound, GKK1032B and citrinin. GKK1032B has been reported previously from an unidentified species of Penicillium as an antitumor antibiotic. The present work suggested that the unidentified species could be Penicillium citrinum.

Published
2015

43. Studies of genetics of yield and yield component characters in F2 and F3 generations of rice (Oryza sativa L.)

Author

Thirugnanakumar, S, Narasimman, R, Anandan, A, and Kumar, NS

Subjects
Rice, segregating generations, F2, F3
Abstract

Three parents with three different durations were crossed in full diallel fashion. The resultant six hybrids were selfed along with their three parents to get six F2’s. The F2’s were selfed to obtain six F3’s. The aforementioned five generations of the six crosses were studied for days to flowering, number of productive tillers per plant, number of filled grains per panicle, 100 seed weight, grain L/B ratio, grain yield per plant and harvest index. The distribution pattern of the segregating generations revealed that, the F3’s of the cross ADT 38 x ADT 37 for hundred seed weight and the F3’s the cross ADT 38 x ADT 44 for grain yield per plant showed normal symmetrical distribution. The kurtosis value was almost negligible indicating mesocurtic nature of the distribution. The F3’s of ADT 38 x ADT 44 recorded high mean coupled with higher coefficient of variation, indicating the presence of additive genetic control. The higher mean performance in F3 may be due to accumulation of favourable genes. All the other crosses and generations showed asymmetric distribution in positive as well as negative direction, for almost all the characters of interest. The mean was comparatively higher but the coefficients of variation were comparatively lower, indicating the preponderance of non-additive genetic control in the expression of the traits of interest. It is better to resort to intermating of segregants followed by recurrent selection for further improvement. The F3’s unique cross ADT 38 x ADT 44 had taken less number of days to first flowering, higher grain L/B ratio coupled with higher grain yield. A simple selection among the F3 progenies of the cross ADT 38 x ADT 44 may yield some useful segregants with earliness, desirable grain quality and higher grain yield.Key words: Rice, segregating generations, F2, F3.

Published
2013

45. CeO2 nanoparticle-modified electrode as a novel electrochemical interface in the quantification of Zn2+ ions at trace level: application to real sample analysis.

Author

Arun Kumar NS, Adarakatti, Prashanth Shivappa, Ashoka S, and Malingappa, Pandurangappa

Subjects
*ZINC ions, *CERIUM oxides, *NANOPARTICLES, *CARBON electrodes, *ELECTROCHEMICAL analysis, *CYCLIC voltammetry
Abstract

A simple strategy has been proposed to quantify Zn2+ ions using CeO2 nanoparticle-modified glassy carbon electrode. The CeO2 nanoparticles were prepared by sucrose-nitrate decomposition method, and it was characterized by X-ray diffraction (XRD), FT-IR, TEM, and surface area analyzer. The synthesized CeO2 nanoparticles were used as modifier molecules as a thin film on glassy carbon electrode (GCE) in the trace level quantification of Zn2+ by using cyclic voltammetry (CV) and differential pulse anodic stripping voltammetry (DPASV) techniques. The fabricated sensor exhibited a good analytical response towards Zn2+ ions. The modified electrode showed a wide linearity in the concentration range 20-380 μg L−1 with a limit of detection 0.36 μg L−1. The proposed electrochemical sensor was successfully applied to trace level Zn2+ quantification from real sample matrices. [ABSTRACT FROM AUTHOR]

Published
2018
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46. Prevalence and pattern of self-medication practices among population of three districts of South Karnataka

Author

Nagarajaiah Bh, Shashi Kumar Ns, Praveen Panchakshari, and Kishore Ms

Subjects
Drug, medicine.medical_specialty, Physiology, media_common.quotation_subject, Population, 0507 social and economic geography, Pharmacist, 050701 cultural studies, 030207 dermatology & venereal diseases, 03 medical and health sciences, 0302 clinical medicine, medicine, Statistical analysis, General Pharmacology, Toxicology and Pharmaceutics, education, media_common, education.field_of_study, High prevalence, business.industry, 05 social sciences, Common cold, medicine.disease, Family medicine, business, Opioid analgesics, Self-medication
Abstract

Background: Self-medication is a general practice globally. People self-medicate by buying medicines at a medical shop either by asking its properties/symptoms such as pain killers/gastric drugs or by the advice of a qualified pharmacist/unqualified person in the medical store. This may lead to masking of severe/dangerous illness, which in turn can produce severe complications and heavy financial burden or loss of a life. Substandard drugs, improper dosage, dose intervals, lack of awareness of precautions or contraindications, and associated diseases can lead to drug interactions, drug poisoning/toxicity, and abuse of drugs. Aims and Objective: To assess the prevalence, pattern, and reasons for self-medication practices among population of three districts of South Karnataka. Materials and Methods: A preformed, pretested, and semistructured questionnaire was used to obtain the data. The questionnaire comprised questions regarding sociodemographic profile, use of self-medication, pattern of use of drugs, factors affecting their use, knowledge of the people regarding dose, duration, side effects, and interactions of the drugs in use, source of information about the drugs, and attitude toward allopathic, ayurvedic, and homeopathic medicines. The subjects were interviewed regarding the use of self-medication drugs for a recall period of 6 months duration. Statistical analysis was done using appropriate statistical method and software. Result: Of the 5,489 respondents, 4,316 (78.63%) reported self-medication within a 6-month recall period. Of these respondents, Mandya reported high self-medication practices (81.86%) when compared with Bangaloreans (72.39%). The difference was significant. Among the different age groups, high self-medication was seen in 41–60 years age group (40.48%) and low among those aged > 60 years (29.37%). The difference was significant. Self-medication was high in male (82.76%).than female subjects (72.87%). Self-medication was slightly more in rural population (79.05%) than urban respondents (78.20%). The most common conditions/symptoms for which self-medication was done was for gastric symptoms (72.10%), followed by joint pains (65.89%), headache (63.02%), fever (47.87%), and common cold (37.95%). The difference was statistically significant, with P < 0.001. Self-medication was significantly more in rural owing to nonavailability of doctors (62.01%) when compared with urban residents (38.14%). Self-medication was time-saving and, for minor illnesses, was also more in rural (64.99% and 73.78%, respectively) when compared with urban (58.82% and 68.76%, respectively) residents. The most important source of drug information for self-medication was family members and relatives (32.30%). Conclusion: The study showed the high prevalence of self-medication, and it was nearly same in both rural and urban population. Although most of the drugs self-medicated were in the list of over-the-counter drugs, but many used antimicrobial drugs, and some even got opioid analgesics as pain killers. In our study, we came to know that, on comparison, many rural female subjects were using steroids creams/ointments as fairness cream than urban female subjects. This is very dangerous, and government should have very strict guidelines for the sale of drugs for self-medication.

Published
2016

47. Strengthening transversus abdominis in pregnancy related pelvic pain: the pressure biofeedback stabilization training

Author

Senthil Kumar Ns and Rajalakshmi D

Subjects
Adult, medicine.medical_specialty, Activities of daily living, medicine.medical_treatment, efficacy, Single-subject design, Biofeedback, Sitting, Pelvic Pain, Physical medicine and rehabilitation, Pregnancy, Outcome Assessment, Health Care, Medicine, Humans, pain, Transversus abdominis, pregnancy related pelvic pain, Abdominal Muscles, Core (anatomy), business.industry, Pelvic pain, Biofeedback, Psychology, General Medicine, Articles, pressure biofeedback unit, medicine.disease, Exercise Therapy, Pregnancy Complications, disability, Physical therapy, Female, medicine.symptom, business, Muscle Contraction, transverse abdominis
Abstract

Pregnancy related pelvic pain (PRPP) refers to musculoskeletal type of persistent posterior pelvic pain during and after pregnancy with feature of reduced endurance capacity for standing, walking and sitting which leads to severe discomfort and considerable impairment of daily activities. Objective: To test the effect of pressure biofeedback stabilizer training, on the pain and dysfunction of a thirty year old subject who presented with PRPP. Study design: Single case design. Outcome variables: Oswestry pain and disability index, TrA efficacy. Methodology: An initial assessment was followed by treatment sessions which consist of 2 phases (Phase A & Phase B). The baseline phase (A) consists of conventional therapeutic exercises while the intervention phase (B) consists of pressure biofeedback training in conjunction with the conventional therapeutic exercises. Result: The study data demonstrated that the subject showed minimal improvement in pain, disability and TrA efficacy during the baseline phase and shown a steady improvement in all these variables during the intervention phase. Conclusion: Core muscle performance (TrA) can be retrained with pressure biofeedback stabilization training program in subject with PRPP thereby reducing pain and disability.

Published
2012

48. A 3-Vinyl Cephem Derivative, a Useful Intermediate in the Synthesis of Cepham Antibiotics, from Aspergillus awamori Associated with Banana Fruit

Author

Kumar Ns, H.M.S.K.H. Bandara, Lalith Jayasinghe, Hironori Masubuti, and Yoshinori Fujimoto

Subjects
Pharmacology, Cephem, Aspergillus, Molecular Structure, biology, Musa, Plant Science, General Medicine, biology.organism_classification, Chemical synthesis, Anti-Bacterial Agents, Microbiology, chemistry.chemical_compound, Complementary and alternative medicine, chemistry, Fruit, Musa acuminata, Fermentation, Drug Discovery, Potato dextrose agar, Food science, Derivative (chemistry), Aspergillus awamori
Abstract

Aspergillus awamori was isolated from a diseased banana fruit, Musa acuminata cv. Ambul. The fungus was fermented in potato dextrose broth and on potato dextrose agar media and the fungal media were extracted with EtOAc. Chromatographic separation of the EtOAc extracts furnished 4-methoxybenzyl 7-phenylacetamido-3-vinyl-3-cephem-4-carboxylate (1), along with three naphtho-γ-pyrones, flavasperone (2), foncesinone A (3) and aurasperone A (4), and three alkaloids, aspernigrin A (5), pestalamide C (6) and nigragillin (7). Compound 1, a known key intermediate in the chemical synthesis of cepham antibiotics, was isolated from a natural source for the first time. Compound 1 is the first 3-vinyl cephem derivative of microbial origin.

Published
2015

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